text
stringlengths 14
5.77M
| meta
dict | __index_level_0__
int64 0
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|---|---|---|
Q: Using split to split in one context but not in another So currently I am working on some SQL with python which is linked to my database and I am stuck on a split problem. So in the program it connects to the database and then next you input either list, add, update, remove or allocate. So lets say I want to add a new data into the database you just need to write: update -name='Ava - #2' -class=2.
After you type this there is a variable called val which does the strip and split.
So as of right now what I have done is:
val = input('> ').strip().lower()
parts = val.split(' ')
print(parts)
So if I input the following:
update -name="Nile Adam" -class=2
I expect the following output: ['update', '-name="Nile Adam"', '-class=2']
However the output I get is: ['update', '-name="Nile', 'Adam"', '-class=2']
A: Simple regex would solve the problem.
Split the word by space but not inside the quotes.
I would split the word using python re package:
import re
>>> re.split('\s(?![\"\w\s\w\"])', 'update -name="Nile Adam" -class=2')
['update', '-name="Nile Adam"', '-class=2']
|
{
"redpajama_set_name": "RedPajamaStackExchange"
}
| 4,661
|
Lesters offer all umbrella workers the opportunity to join our child care voucher scheme.
There are great savings to be made for you and your family through the child care voucher scheme. Childcare Vouchers are exempt from Tax and National Insurance up to the value of £55 per week – this could save you up to £1,195 per year – or double that if both parents choose them. The exact amount you can save depends on individual circumstances in terms of how much tax you currently pay and how much you spend on childcare.
Is the scheme available to all Lesters employees?
Yes, the scheme is available to all employees.
Childcare Vouchers can be used to pay for the care of children up to the age of 15 (until 1st September following their 15th birthday) or the age of 16 if they are disabled (until 1st September following their 16th birthday). In addition the child for whom the Childcare Vouchers are provided must be a child of the employee or a child who lives with the employee and for whom he or she has parental responsibility.
Does my child care provider qualify?
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 7,163
|
EX6 Plus
GETnGO
About WM
Who We AreWM NewsWM Manufacturing
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填写个人信息
身份证军官证外籍人士护照组织机构代码台湾居民来往大陆通行证港澳居民来往内地通行证
WM Motor Delivers its 30,000th EX5 Smart, Pure Electric SUV
Corporate News | 2020-07-06
Monday 6 July, 2020 – SHANGHAI, WM Motor today achieved a new milestone in its development, the delivery of its 30,000th EX5 smart, pure electric SUV. Delivery of the vehicle was taken by Mr. Song in Shanghai who, alongside with his wife, visited the WM's Space in the Hongqiao business district where he was greeted by the Company's Founder and CEO, Freeman Shen, who personally handed over the keys to his brand-new EX5-Z. This occasion marked a historic moment both for WM Motor and for China's electric vehicle industry. In reaching this milestone, WM Motor has become the first Chinese pure electric vehicle (EV) startup to have surpassed 30,000 sales of a single vehicle model.
WM Motor's Founder and CEO, Freeman Shen, hands over the 30,000th EX5 to its new owners
WM Motor has achieved positive sales momentum since the Covid-19 pandemic halted production across the whole industry in China. At the end of June this year, cumulative sales had increased by 77.8% quarter-on-quarter and 34.9% compared to the month previous, with June sales reaching an annual high of 2,028 units.
Validated user experience
All of WM Motor's vehicles are connected Over-the-Air, making each car a highly valuable data resource that provides real-time information on usage and performance while on the road. This information allows for the development of software and hardware upgrades and innovations that provide real benefits to users. WM Motor attributes much of the EX5's success to this connectivity, as it has enabled the constant improvement of the user experience through frequent hardware and software upgrades.
An examination of user data gives an insight into the utility of the EX5's features in real-world driving scenarios. For instance, it is clear from user-generated data that WM Motor's in-cabin smart AI assistant 'Xiaowei' has now become an essential part of the Living Engine infotainment system, having fulfilled 4.45 million voice commands in the first half of 2020, an average of about 24,000 interactions every day. Other functions which have been popular in the first half of 2020 include the iQiyi video streaming app, which was opened 1.02 million times; the Automatic Parking Assist (APA) function, which helped WM users complete a perfect park over 340,000 times; and the CleanSpace air purification system, which is used daily by 90% of users. Connected features such as music and video streaming, as well as navigation, have been facilitated by over 400,000 gigabytes of free on-board internet data.
Designed for the busy, highly-connected lifestyle
Since WM Motor released its all-new 2020 model EX5, the EX5-Z, the share of younger drivers among WM Motor's customer base has continued to grow, with the number of users born after 1995 increasing by 43.4% since 2019. In addition, the number of drivers who are parents of young children now make up 69% of the Company's customer base. WM Motor believes that this trend is driven by the provision of an in-cabin experience designed to accommodate the busy, highly-connected lifestyles of today's drivers. Also, WM's vehicles are equipped with a variety of unique features highly suited to young families, including kids channel video streaming, educational podcasts, in-cabin air quality monitoring and purification, and Vehicle-to-Home (V2H) connectivity. Young parents are also attracted by the EX5's 5-star C-NCAP safety rating, as well as the large storage space and long range for weekend getaways.
Expanding footprint
WM Motor's positive sales trend can be attributed in large part to the expansion of its national retail network, made up mostly of stores operated by the Company's Smart Mobility Partners (SMP's), who exclusively manage the sales and delivery process for WM Motor's vehicles. The Company has added 46 new retail locations in the first half of 2020, increasing its presence in China's major cities, as well as tier 3 and tier 4 cities.
Share to Wechat Moment
WM News
Copyright©2021 WM Motor All Rights Reserved威马汽车版权所有 沪ICP备18006332号-6沪公网安备 31011802004057号Copyright©2021 WM Motor All Rights Reserved
威马汽车版权所有
威马汽车科技集团有限公司
|
{
"redpajama_set_name": "RedPajamaCommonCrawl"
}
| 4,906
|
static vpx_codec_ctx_t vpxContext;
static vpx_codec_iface_t *vpxDecoder;
void ogv_video_decoder_init() {
vpxDecoder = vpx_codec_vp8_dx();
vpx_codec_dec_init(&vpxContext, vpxDecoder, NULL, 0);
}
void ogv_video_decoder_destroy() {
// should tear instance down, but meh
}
int ogv_video_decoder_process_header(const char *data, size_t data_len) {
// no header packets for VP8
printf("VP8 process_header should not happen?\n");
return 0;
}
int ogv_video_decoder_process_frame(const char *data, size_t data_len) {
vpx_codec_decode(&vpxContext, (const uint8_t *)data, data_len, NULL, 1);
// @todo check return value
vpx_codec_decode(&vpxContext, NULL, 0, NULL, 1);
vpx_codec_iter_t iter = NULL;
vpx_image_t *image = NULL;
int foundImage = 0;
while ((image = vpx_codec_get_frame(&vpxContext, &iter))) {
// is it possible to get more than one at a time? ugh
// @fixme can we have multiples really? how does this worky
if (foundImage) {
// skip for now
printf("got multiple frames from VP8 stream unexpectedly?\n");
continue;
}
foundImage = 1;
ogvjs_callback_frame(image->planes[0], image->stride[0],
image->planes[1], image->stride[1],
image->planes[2], image->stride[2],
image->w, image->d_h,
1, 1); // @todo pixel format
}
return foundImage;
}
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 2,754
|
(syn. Lophozia badensis (Gottsche) Schiffn.). Boreo-arctic montane Circumpolar element.
*1: Carbis Bay, 1925, HHK (NMW) (Paton 1969a: 697).
*2: Mortar of derelict mine wall N. of Minions, Liskeard, 1966, JWF (Paton 1967b: 398, 1969a: 697).
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 3,038
|
package cmd
import (
"errors"
"fmt"
"io"
"os"
"strings"
"time"
"github.com/golang/glog"
"github.com/spf13/cobra"
kapierrors "k8s.io/apimachinery/pkg/api/errors"
metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
"k8s.io/apimachinery/pkg/runtime"
"k8s.io/apimachinery/pkg/watch"
restclient "k8s.io/client-go/rest"
kapi "k8s.io/kubernetes/pkg/api"
kclient "k8s.io/kubernetes/pkg/client/unversioned"
kcmd "k8s.io/kubernetes/pkg/kubectl/cmd"
"k8s.io/kubernetes/pkg/kubectl/cmd/templates"
kcmdutil "k8s.io/kubernetes/pkg/kubectl/cmd/util"
"k8s.io/kubernetes/pkg/kubectl/resource"
"k8s.io/kubernetes/pkg/util/interrupt"
"k8s.io/kubernetes/pkg/util/term"
deployapi "github.com/openshift/origin/pkg/apps/apis/apps"
appsclient "github.com/openshift/origin/pkg/apps/generated/internalclientset/typed/apps/internalversion"
cmdutil "github.com/openshift/origin/pkg/cmd/util"
"github.com/openshift/origin/pkg/cmd/util/clientcmd"
generateapp "github.com/openshift/origin/pkg/generate/app"
imageapi "github.com/openshift/origin/pkg/image/apis/image"
imageclient "github.com/openshift/origin/pkg/image/generated/internalclientset/typed/image/internalversion"
)
type DebugOptions struct {
Attach kcmd.AttachOptions
AppsClient appsclient.AppsInterface
ImageClient imageclient.ImageInterface
Print func(pod *kapi.Pod, w io.Writer) error
LogsForObject func(object, options runtime.Object, timeout time.Duration) (*restclient.Request, error)
NoStdin bool
ForceTTY bool
DisableTTY bool
Filename string
Timeout time.Duration
Command []string
Annotations map[string]string
AsRoot bool
AsNonRoot bool
AsUser int64
KeepLabels bool // TODO: evaluate selecting the right labels automatically
KeepAnnotations bool
KeepLiveness bool
KeepReadiness bool
KeepInitContainers bool
OneContainer bool
NodeName string
AddEnv []kapi.EnvVar
RemoveEnv []string
}
const (
debugPodLabelName = "debug.openshift.io/name"
debugPodAnnotationSourceContainer = "debug.openshift.io/source-container"
debugPodAnnotationSourceResource = "debug.openshift.io/source-resource"
)
var (
debugLong = templates.LongDesc(`
Launch a command shell to debug a running application
When debugging images and setup problems, it's useful to get an exact copy of a running
pod configuration and troubleshoot with a shell. Since a pod that is failing may not be
started and not accessible to 'rsh' or 'exec', the 'debug' command makes it easy to
create a carbon copy of that setup.
The default mode is to start a shell inside of the first container of the referenced pod,
replication controller, or deployment config. The started pod will be a copy of your
source pod, with labels stripped, the command changed to '/bin/sh', and readiness and
liveness checks disabled. If you just want to run a command, add '--' and a command to
run. Passing a command will not create a TTY or send STDIN by default. Other flags are
supported for altering the container or pod in common ways.
A common problem running containers is a security policy that prohibits you from running
as a root user on the cluster. You can use this command to test running a pod as
non-root (with --as-user) or to run a non-root pod as root (with --as-root).
The debug pod is deleted when the the remote command completes or the user interrupts
the shell.`)
debugExample = templates.Examples(`
# Debug a currently running deployment
%[1]s dc/test
# Test running a deployment as a non-root user
%[1]s dc/test --as-user=1000000
# Debug a specific failing container by running the env command in the 'second' container
%[1]s dc/test -c second -- /bin/env
# See the pod that would be created to debug
%[1]s dc/test -o yaml`)
)
// NewCmdDebug creates a command for debugging pods.
func NewCmdDebug(fullName string, f *clientcmd.Factory, in io.Reader, out, errout io.Writer) *cobra.Command {
options := &DebugOptions{
Timeout: 15 * time.Minute,
Attach: kcmd.AttachOptions{
StreamOptions: kcmd.StreamOptions{
In: in,
Out: out,
Err: errout,
TTY: true,
Stdin: true,
},
Attach: &kcmd.DefaultRemoteAttach{},
},
LogsForObject: f.LogsForObject,
}
cmd := &cobra.Command{
Use: "debug RESOURCE/NAME [ENV1=VAL1 ...] [-c CONTAINER] [options] [-- COMMAND]",
Short: "Launch a new instance of a pod for debugging",
Long: debugLong,
Example: fmt.Sprintf(debugExample, fmt.Sprintf("%s debug", fullName)),
Run: func(cmd *cobra.Command, args []string) {
kcmdutil.CheckErr(options.Complete(cmd, f, args, in, out, errout))
kcmdutil.CheckErr(options.Validate())
kcmdutil.CheckErr(options.Debug())
},
}
// TODO: when T is deprecated use the printer, but keep these hidden
cmd.Flags().StringP("output", "o", "", "Output format. One of: json|yaml|wide|name|go-template=...|go-template-file=...|jsonpath=...|jsonpath-file=... See golang template [http://golang.org/pkg/text/template/#pkg-overview] and jsonpath template [http://kubernetes.io/docs/user-guide/jsonpath/].")
cmd.Flags().String("output-version", "", "Output the formatted object with the given version (default api-version).")
cmd.Flags().String("template", "", "Template string or path to template file to use when -o=go-template, -o=go-template-file. The template format is golang templates [http://golang.org/pkg/text/template/#pkg-overview].")
cmd.MarkFlagFilename("template")
cmd.Flags().Bool("no-headers", false, "If true, when using the default output, don't print headers.")
cmd.Flags().MarkHidden("no-headers")
cmd.Flags().String("sort-by", "", "If non-empty, sort list types using this field specification. The field specification is expressed as a JSONPath expression (e.g. 'ObjectMeta.Name'). The field in the API resource specified by this JSONPath expression must be an integer or a string.")
cmd.Flags().MarkHidden("sort-by")
cmd.Flags().Bool("show-all", true, "When printing, show all resources (default hide terminated pods.)")
cmd.Flags().MarkHidden("show-all")
cmd.Flags().Bool("show-labels", false, "When printing, show all labels as the last column (default hide labels column)")
cmd.Flags().BoolVarP(&options.NoStdin, "no-stdin", "I", options.NoStdin, "Bypasses passing STDIN to the container, defaults to true if no command specified")
cmd.Flags().BoolVarP(&options.ForceTTY, "tty", "t", false, "Force a pseudo-terminal to be allocated")
cmd.Flags().BoolVarP(&options.DisableTTY, "no-tty", "T", false, "Disable pseudo-terminal allocation")
cmd.Flags().StringVarP(&options.Attach.ContainerName, "container", "c", "", "Container name; defaults to first container")
cmd.Flags().BoolVar(&options.KeepAnnotations, "keep-annotations", false, "If true, keep the original pod annotations")
cmd.Flags().BoolVar(&options.KeepLiveness, "keep-liveness", false, "If true, keep the original pod liveness probes")
cmd.Flags().BoolVar(&options.KeepInitContainers, "keep-init-containers", true, "Run the init containers for the pod. Defaults to true.")
cmd.Flags().BoolVar(&options.KeepReadiness, "keep-readiness", false, "If true, keep the original pod readiness probes")
cmd.Flags().BoolVar(&options.OneContainer, "one-container", false, "If true, run only the selected container, remove all others")
cmd.Flags().StringVar(&options.NodeName, "node-name", "", "Set a specific node to run on - by default the pod will run on any valid node")
cmd.Flags().BoolVar(&options.AsRoot, "as-root", false, "If true, try to run the container as the root user")
cmd.Flags().Int64Var(&options.AsUser, "as-user", -1, "Try to run the container as a specific user UID (note: admins may limit your ability to use this flag)")
cmd.Flags().StringVarP(&options.Filename, "filename", "f", "", "Filename or URL to file to read a template")
cmd.MarkFlagFilename("filename", "yaml", "yml", "json")
return cmd
}
func (o *DebugOptions) Complete(cmd *cobra.Command, f *clientcmd.Factory, args []string, in io.Reader, out, errout io.Writer) error {
if i := cmd.ArgsLenAtDash(); i != -1 && i < len(args) {
o.Command = args[i:]
args = args[:i]
}
resources, envArgs, ok := cmdutil.SplitEnvironmentFromResources(args)
if !ok {
return kcmdutil.UsageError(cmd, "all resources must be specified before environment changes: %s", strings.Join(args, " "))
}
switch {
case o.ForceTTY && o.NoStdin:
return kcmdutil.UsageError(cmd, "you may not specify -I and -t together")
case o.ForceTTY && o.DisableTTY:
return kcmdutil.UsageError(cmd, "you may not specify -t and -T together")
case o.ForceTTY:
o.Attach.TTY = true
// since ForceTTY is defaulted to false, check if user specifically passed in "=false" flag
case !o.ForceTTY && cmd.Flags().Changed("tty"):
o.Attach.TTY = false
case o.DisableTTY:
o.Attach.TTY = false
// don't default TTY to true if a command is passed
case len(o.Command) > 0:
o.Attach.TTY = false
o.Attach.Stdin = false
default:
o.Attach.TTY = term.IsTerminal(in)
glog.V(4).Infof("Defaulting TTY to %t", o.Attach.TTY)
}
if o.NoStdin {
o.Attach.TTY = false
o.Attach.Stdin = false
}
if o.Annotations == nil {
o.Annotations = make(map[string]string)
}
if len(o.Command) == 0 {
o.Command = []string{"/bin/sh"}
}
cmdNamespace, explicit, err := f.DefaultNamespace()
if err != nil {
return err
}
mapper, _ := f.Object()
b := f.NewBuilder(true).
NamespaceParam(cmdNamespace).DefaultNamespace().
SingleResourceType().
ResourceNames("pods", resources...).
Flatten()
if len(o.Filename) > 0 {
b.FilenameParam(explicit, &resource.FilenameOptions{Recursive: false, Filenames: []string{o.Filename}})
}
o.AddEnv, o.RemoveEnv, err = cmdutil.ParseEnv(envArgs, nil)
if err != nil {
return err
}
one := false
infos, err := b.Do().IntoSingleItemImplied(&one).Infos()
if err != nil {
return err
}
if !one {
return fmt.Errorf("you must identify a resource with a pod template to debug")
}
template, err := f.ApproximatePodTemplateForObject(infos[0].Object)
if err != nil && template == nil {
return fmt.Errorf("cannot debug %s: %v", infos[0].Name, err)
}
if err != nil {
glog.V(4).Infof("Unable to get exact template, but continuing with fallback: %v", err)
}
pod := &kapi.Pod{
ObjectMeta: template.ObjectMeta,
Spec: template.Spec,
}
pod.Name, pod.Namespace = fmt.Sprintf("%s-debug", generateapp.MakeSimpleName(infos[0].Name)), infos[0].Namespace
o.Attach.Pod = pod
o.AsNonRoot = !o.AsRoot && cmd.Flag("as-root").Changed
if len(o.Attach.ContainerName) == 0 && len(pod.Spec.Containers) > 0 {
glog.V(4).Infof("Defaulting container name to %s", pod.Spec.Containers[0].Name)
o.Attach.ContainerName = pod.Spec.Containers[0].Name
}
o.Annotations[debugPodAnnotationSourceResource] = fmt.Sprintf("%s/%s", infos[0].Mapping.Resource, infos[0].Name)
o.Annotations[debugPodAnnotationSourceContainer] = o.Attach.ContainerName
output := kcmdutil.GetFlagString(cmd, "output")
if len(output) != 0 {
o.Print = func(pod *kapi.Pod, out io.Writer) error {
return f.PrintObject(cmd, false, mapper, pod, out)
}
}
// if a nodeName was specified, ensure node exists
if len(o.NodeName) > 0 {
r := f.NewBuilder(true).
NamespaceParam(cmdNamespace).
SingleResourceType().
ResourceTypeOrNameArgs(true, []string{"nodes", o.NodeName}...).
Flatten().
Do()
_, err := r.Infos()
if err != nil {
return err
}
}
config, err := f.ClientConfig()
if err != nil {
return err
}
o.Attach.Config = config
kc, err := f.ClientSet()
if err != nil {
return err
}
o.Attach.PodClient = kc.Core()
appsClient, err := f.OpenshiftInternalAppsClient()
if err != nil {
return err
}
o.AppsClient = appsClient.Apps()
imageClient, err := f.OpenshiftInternalImageClient()
if err != nil {
return err
}
o.ImageClient = imageClient.Image()
return nil
}
func (o DebugOptions) Validate() error {
names := containerNames(o.Attach.Pod)
if len(names) == 0 {
return fmt.Errorf("the provided pod must have at least one container")
}
if (o.AsRoot || o.AsNonRoot) && o.AsUser > 0 {
return fmt.Errorf("you may not specify --as-root and --as-user=%d at the same time", o.AsUser)
}
if len(o.Attach.ContainerName) == 0 {
return fmt.Errorf("you must provide a container name to debug")
}
if containerForName(o.Attach.Pod, o.Attach.ContainerName) == nil {
return fmt.Errorf("the container %q is not a valid container name; must be one of %v", o.Attach.ContainerName, names)
}
return nil
}
// Debug creates and runs a debugging pod.
func (o *DebugOptions) Debug() error {
pod, originalCommand := o.transformPodForDebug(o.Annotations)
var commandString string
switch {
case len(originalCommand) > 0:
commandString = strings.Join(originalCommand, " ")
default:
commandString = "<image entrypoint>"
}
if o.Print != nil {
return o.Print(pod, o.Attach.Out)
}
glog.V(5).Infof("Creating pod: %#v", pod)
fmt.Fprintf(o.Attach.Err, "Debugging with pod/%s, original command: %s\n", pod.Name, commandString)
pod, err := o.createPod(pod)
if err != nil {
return err
}
// ensure the pod is cleaned up on shutdown
o.Attach.InterruptParent = interrupt.New(
func(os.Signal) { os.Exit(1) },
func() {
stderr := o.Attach.Err
if stderr == nil {
stderr = os.Stderr
}
fmt.Fprintf(stderr, "\nRemoving debug pod ...\n")
if err := o.Attach.PodClient.Pods(pod.Namespace).Delete(pod.Name, metav1.NewDeleteOptions(0)); err != nil {
if !kapierrors.IsNotFound(err) {
fmt.Fprintf(stderr, "error: unable to delete the debug pod %q: %v\n", pod.Name, err)
}
}
},
)
glog.V(5).Infof("Created attach arguments: %#v", o.Attach)
return o.Attach.InterruptParent.Run(func() error {
w, err := o.Attach.PodClient.Pods(pod.Namespace).Watch(metav1.SingleObject(pod.ObjectMeta))
if err != nil {
return err
}
fmt.Fprintf(o.Attach.Err, "Waiting for pod to start ...\n")
switch containerRunningEvent, err := watch.Until(o.Timeout, w, kclient.PodContainerRunning(o.Attach.ContainerName)); {
// api didn't error right away but the pod wasn't even created
case kapierrors.IsNotFound(err):
msg := fmt.Sprintf("unable to create the debug pod %q", pod.Name)
if len(o.NodeName) > 0 {
msg += fmt.Sprintf(" on node %q", o.NodeName)
}
return fmt.Errorf(msg)
// switch to logging output
case err == kclient.ErrPodCompleted, err == kclient.ErrContainerTerminated, !o.Attach.Stdin:
return kcmd.LogsOptions{
Object: pod,
Options: &kapi.PodLogOptions{
Container: o.Attach.ContainerName,
Follow: true,
},
Out: o.Attach.Out,
LogsForObject: o.LogsForObject,
}.RunLogs()
case err != nil:
return err
default:
// TODO this doesn't do us much good for remote debugging sessions, but until we get a local port
// set up to proxy, this is what we've got.
if podWithStatus, ok := containerRunningEvent.Object.(*kapi.Pod); ok {
fmt.Fprintf(o.Attach.Err, "Pod IP: %s\n", podWithStatus.Status.PodIP)
}
// TODO: attach can race with pod completion, allow attach to switch to logs
return o.Attach.Run()
}
})
}
// getContainerImageViaDeploymentConfig attempts to return an Image for a given
// Container. It tries to walk from the Container's Pod to its DeploymentConfig
// (via the "openshift.io/deployment-config.name" annotation), then tries to
// find the ImageStream from which the DeploymentConfig is deploying, then tries
// to find a match for the Container's image in the ImageStream's Images.
func (o *DebugOptions) getContainerImageViaDeploymentConfig(pod *kapi.Pod, container *kapi.Container) (*imageapi.Image, error) {
ref, err := imageapi.ParseDockerImageReference(container.Image)
if err != nil {
return nil, err
}
if ref.ID == "" {
return nil, nil // ID is needed for later lookup
}
dcname := pod.Annotations[deployapi.DeploymentConfigAnnotation]
if dcname == "" {
return nil, nil // Pod doesn't appear to have been created by a DeploymentConfig
}
dc, err := o.AppsClient.DeploymentConfigs(o.Attach.Pod.Namespace).Get(dcname, metav1.GetOptions{})
if err != nil {
return nil, err
}
for _, trigger := range dc.Spec.Triggers {
if trigger.Type == deployapi.DeploymentTriggerOnImageChange &&
trigger.ImageChangeParams != nil &&
trigger.ImageChangeParams.From.Kind == "ImageStreamTag" {
isname, _, err := imageapi.ParseImageStreamTagName(trigger.ImageChangeParams.From.Name)
if err != nil {
return nil, err
}
namespace := trigger.ImageChangeParams.From.Namespace
if len(namespace) == 0 {
namespace = o.Attach.Pod.Namespace
}
isi, err := o.ImageClient.ImageStreamImages(namespace).Get(imageapi.JoinImageStreamImage(isname, ref.ID), metav1.GetOptions{})
if err != nil {
return nil, err
}
return &isi.Image, nil
}
}
return nil, nil // DeploymentConfig doesn't have an ImageChange Trigger
}
// getContainerImageViaImageStreamImport attempts to return an Image for a given
// Container. It does this by submiting a ImageStreamImport request with Import
// set to false. The request will not succeed if the backing repository
// requires Insecure to be set to true, which cannot be hard-coded for security
// reasons.
func (o *DebugOptions) getContainerImageViaImageStreamImport(container *kapi.Container) (*imageapi.Image, error) {
isi := &imageapi.ImageStreamImport{
ObjectMeta: metav1.ObjectMeta{
Name: "oc-debug",
},
Spec: imageapi.ImageStreamImportSpec{
Images: []imageapi.ImageImportSpec{
{
From: kapi.ObjectReference{
Kind: "DockerImage",
Name: container.Image,
},
},
},
},
}
isi, err := o.ImageClient.ImageStreamImports(o.Attach.Pod.Namespace).Create(isi)
if err != nil {
return nil, err
}
if len(isi.Status.Images) > 0 {
return isi.Status.Images[0].Image, nil
}
return nil, nil
}
func (o *DebugOptions) getContainerImageCommand(pod *kapi.Pod, container *kapi.Container) ([]string, error) {
if len(container.Command) > 0 {
return container.Command, nil
}
image, _ := o.getContainerImageViaDeploymentConfig(pod, container)
if image == nil {
image, _ = o.getContainerImageViaImageStreamImport(container)
}
if image == nil || image.DockerImageMetadata.Config == nil {
return nil, errors.New("error: no usable image found")
}
config := image.DockerImageMetadata.Config
return append(config.Entrypoint, config.Cmd...), nil
}
// transformPodForDebug alters the input pod to be debuggable
func (o *DebugOptions) transformPodForDebug(annotations map[string]string) (*kapi.Pod, []string) {
pod := o.Attach.Pod
if !o.KeepInitContainers {
pod.Spec.InitContainers = nil
}
// reset the container
container := containerForName(pod, o.Attach.ContainerName)
// identify the command to be run
originalCommand, _ := o.getContainerImageCommand(pod, container)
if len(originalCommand) > 0 {
originalCommand = append(originalCommand, container.Args...)
}
container.Command = o.Command
container.Args = nil
container.TTY = o.Attach.Stdin && o.Attach.TTY
container.Stdin = o.Attach.Stdin
container.StdinOnce = o.Attach.Stdin
if !o.KeepReadiness {
container.ReadinessProbe = nil
}
if !o.KeepLiveness {
container.LivenessProbe = nil
}
var newEnv []kapi.EnvVar
if len(o.RemoveEnv) > 0 {
for i := range container.Env {
skip := false
for _, name := range o.RemoveEnv {
if name == container.Env[i].Name {
skip = true
break
}
}
if skip {
continue
}
newEnv = append(newEnv, container.Env[i])
}
} else {
newEnv = container.Env
}
for _, env := range o.AddEnv {
newEnv = append(newEnv, env)
}
container.Env = newEnv
if container.SecurityContext == nil {
container.SecurityContext = &kapi.SecurityContext{}
}
switch {
case o.AsNonRoot:
b := true
container.SecurityContext.RunAsNonRoot = &b
case o.AsRoot:
zero := int64(0)
container.SecurityContext.RunAsUser = &zero
container.SecurityContext.RunAsNonRoot = nil
case o.AsUser != -1:
container.SecurityContext.RunAsUser = &o.AsUser
container.SecurityContext.RunAsNonRoot = nil
}
if o.OneContainer {
pod.Spec.Containers = []kapi.Container{*container}
}
// reset the pod
if pod.Annotations == nil || !o.KeepAnnotations {
pod.Annotations = make(map[string]string)
}
for k, v := range annotations {
pod.Annotations[k] = v
}
if o.KeepLabels {
if pod.Labels == nil {
pod.Labels = make(map[string]string)
}
} else {
pod.Labels = map[string]string{}
}
// always clear the NodeName
pod.Spec.NodeName = o.NodeName
pod.ResourceVersion = ""
pod.Spec.RestartPolicy = kapi.RestartPolicyNever
pod.Status = kapi.PodStatus{}
pod.UID = ""
pod.CreationTimestamp = metav1.Time{}
pod.SelfLink = ""
return pod, originalCommand
}
// createPod creates the debug pod, and will attempt to delete an existing debug
// pod with the same name, but will return an error in any other case.
func (o *DebugOptions) createPod(pod *kapi.Pod) (*kapi.Pod, error) {
namespace, name := pod.Namespace, pod.Name
// create the pod
created, err := o.Attach.PodClient.Pods(namespace).Create(pod)
if err == nil || !kapierrors.IsAlreadyExists(err) {
return created, err
}
// only continue if the pod has the right annotations
existing, err := o.Attach.PodClient.Pods(namespace).Get(name, metav1.GetOptions{})
if err != nil {
return nil, err
}
if existing.Annotations[debugPodAnnotationSourceResource] != o.Annotations[debugPodAnnotationSourceResource] {
return nil, fmt.Errorf("a pod already exists named %q, please delete it before running debug", name)
}
// delete the existing pod
if err := o.Attach.PodClient.Pods(namespace).Delete(name, metav1.NewDeleteOptions(0)); err != nil && !kapierrors.IsNotFound(err) {
return nil, fmt.Errorf("unable to delete existing debug pod %q: %v", name, err)
}
return o.Attach.PodClient.Pods(namespace).Create(pod)
}
func containerForName(pod *kapi.Pod, name string) *kapi.Container {
for i, c := range pod.Spec.Containers {
if c.Name == name {
return &pod.Spec.Containers[i]
}
}
for i, c := range pod.Spec.InitContainers {
if c.Name == name {
return &pod.Spec.InitContainers[i]
}
}
return nil
}
func containerNames(pod *kapi.Pod) []string {
var names []string
for _, c := range pod.Spec.Containers {
names = append(names, c.Name)
}
return names
}
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 9,538
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Home All issues Volume 527 (March 2011) A&A, 527 (2011) A132 Full HTML
A&A
2. Model and dispersion relation
3. Propagating waves: ...
4. Standing waves
5. Link with observations
6. Discussion and conclusions
Linear coupling between fast and slow MHD waves due to line-tying effects
J. Terradas1, J. Andries2,3 and E. Verwichte4
1 Departament de Física, Universitat de les Illes Balears, 07122, Spain
e-mail: jaume.terradas@uib.es
2 Centre Plasma Astrophysics and Leuven Mathematical Modeling and Computational Science Centre, Katholieke Universiteit Leuven, Leuven 3001, Belgium
e-mail: jesse.andries@wis.kuleuven.be
3 Centre for Stellar and Planetary Astrophysics, Monash University, Victoria 3800, Australia
4 Centre for Fusion, Space and Astrophysics, Department of Physics, University of Warwick, Coventry CV4 7AL, UK
e-mail: Erwin.Verwichte@warwick.ac.uk
Received: 4 October 2010
Context. Oscillations in coronal loops are usually interpreted in terms of uncoupled magnetohydrodynamic (MHD) waves. Examples of these waves are standing transverse motions, interpreted as the kink MHD modes, and propagating slow modes, commonly reported at the loop footpoints.
Aims. Here we study a simple system in which fast and slow MHD waves are coupled. The goal is to understand the fingerprints of the coupling when boundary conditions are imposed.
Methods. The reflection problem of a fast and slow MHD wave interacting with a rigid boundary, representing the line-tying effect of the photosphere, is analytically investigated. Both propagating and standing waves are analysed and the time-dependent problem of the excitation of these waves is considered.
Results. An obliquely incident fast MHD wave on the photosphere inevitably generates a slow mode. The frequency of the generated slow mode at the photosphere is exactly the same as the frequency of the incident fast MHD mode, but its wavelength is much smaller, assuming that the sound speed is slower than the Alfvén speed.
Conclusions. The main signatures of the generated slow wave are density fluctuations at the loop footpoints. We have derived a simple formula that relates the velocity amplitude of the transverse standing mode with the density enhancements at the footpoints due to the driven slow modes. Using these results it is shown that there is possible evidence in the observations of the coupling between these two modes.
Key words: magnetohydrodynamics (MHD) / waves / magnetic fields / sun: atmosphere / sun: oscillations
© ESO, 2011
In coronal loops there is evidence of fast standing magnetohydrodynamic (MHD) modes and slow (propagating and standing) MHD modes. Standing kink oscillations were first reported using TRACE by Aschwanden et al. (1999) and Nakariakov et al. (1999). Later, similar observations were analysed by, e.g., Schrijver & Brown (2000), Aschwanden et al. (2002), and Schrijver et al. (2002). There is also clear evidence of propagating slow waves at loop footpoints (see De Moortel 2009, for a review). These slow waves are most likely due to coupling between the underlying atmospheric layers since the dominant periods tend to be around 5 min, suggesting a possible link with solar p-modes. Furthermore, observations of standing slow modes in coronal loops, with periods largely above 5 min, have also been reported by a number of authors, using different instruments such as SOHO/SUMER (e.g., Wang et al. 2003a,b, 2007), Yohkoh/BCS (e.g., Mariska 2005, 2006), and more recently, Hinode/EIS (e.g., Erdélyi & Taroyan 2008).
The theoretical interpretation of such a variety of oscillations is done, in most of the cases, in terms of uncoupled MHD waves. On one hand, transverse oscillations are identified as fast kink modes in the zero-β approximation, meaning that in the linear regime there is no longitudinal velocity along the magnetic tube. On the other hand, the reported slow modes are associated to acoustic modes, ignoring the coupling with the transverse motions. Although these identifications are useful and simple, we have to bear in mind that under realistic conditions MHD modes may couple. In general, the effect of gas pressure, inhomogeneities, or boundary conditions lead to the coupling between fast and slow modes. As we shall see, a clear example of coupling comes from the line-tying condition, which amounts to considering the photosphere as providing a complete reflection of any coronal disturbance impinging from above. This is justified in most of the cases by the large difference in densities between the photosphere and corona, but it obviously neglects the important role of the transition region.
In this paper we study the simplest configuration in which fast and slow modes are mixed to understand the basics of mode coupling. We use the simple idea that a fast wave that is obliquely incident on a boundary will generate a slow wave. As far as we know, this issue has been addressed in slightly different contexts by, e.g., Stein (1971), Vasquez (1990), and Oliver et al. (1992). A remarkable work about magnetohydrodynamic waves in coronal flux tubes including the line-tying effect was carried out by Goedbloed & Halberstadt (1994). In that work, it was clearly stated that pure fast or pure slow modes do not exist in a line-tied coronal loop. Here we follow a different approach to analyse this problem. Our interest is in the effects of the application of line-tying conditions on fast and slow modes and in the possible observational fingerprints of this coupling.
We consider first the simplest magnetic configuration where the magnetic field points in the z-direction, the plasma density, and pressure are constant, and vA > cs (where vA is the Alfvén speed and cs the sound speed). Since the medium is homogeneous, we consider perturbations that are proportional to ei(ωt + kxx + kzz), meaning that waves propagate in the negative x and z-directions. In this configuration, the linearised MHD equations (see Appendix A) lead to the well known dispersion relation for fast and slow MHD waves, (1)In our problem it is more convenient to assume that ω and kx are known and solve for kz. The reason is that the frequency of an incoming wave remains constant in the reflection problem while the longitudinal wavenumber can change. The dispersion relation written as a biquadratic equation for kz is (2)We denote by kF and kS the fast and the slow longitudinal wavenumbers that are solutions to the previous biquadratic equation, i.e., where These wavenumbers are associated to the same frequency ω and same kx, and can be approximated, using the small plasma-β assumption, by (e.g., Oliver et al. 1992) These approximations will turn out to be useful in the following sections. According to Eq. (8) the fast wavenumber may become purely imaginary for a certain choice of the parameters, indicating that the wave is evanescent. Hereafter, we restrict our analysis to propagating waves.
It can be seen from the linearised MHD equations that the velocity polarisation for fast and slow modes is given by the following expression (10)where kz is either kF or kS. If we change the direction of propagation along the field, kz changes to − kz and the polarisation also changes sign. In our configuration and in the regime that we are interested (vA > cs), since kF < kS, fast modes are characterised by long wavelengths and by vx > vz, while slow modes have short wavelengths and vx < vz. The slow modes have a stronger compression since the wavelength is short in comparison with the fast modes.
3. Propagating waves: the reflection problem
3.1. Fast MHD wave reflection
We consider that the most elementary problem shows the process of mode coupling due to boundary conditions. A fast MHD wave travels downwards (in the negative z-direction) and represents an incoming wave. This wave interacts with the photosphere (located at z = 0, where line-tying conditions are applied) and reflects (now travelling upwards). The amplitude of the fast incoming wave is FI, while the amplitude of the reflected fast wave is FR. To satisfy the boundary conditions, a slow MHD wave, also moving upwards, must be generated at z = 0. The excited slow mode has an amplitude SG. It is easy to write the velocity components using the polarisation of fast and slow waves, given by Eq. (10), and the proper sign of the longitudinal wavenumber, Now boundary conditions are imposed at z = 0, representing the location of the photosphere. We use line-tying conditions, i.e., Vx(z = 0) = Vz(z = 0) = 0. According to Eqs. (11) and (12), the following conditions must be satisfied, (13)The solution in terms of the amplitude of the incoming wave (which is an arbitrary parameter) is The coefficients depend on ω, kx (same for the three waves) and on longitudinal wavenumbers, kF and kS, which can also be expressed in terms of ω, kx by using Eqs. (3) and (4).
Fig. 1
Amplitude of reflected fast mode given by Eq. (14) as a function of the horizontal wavenumber for three different values of the sound speed.
When there is no coupling between fast and slow modes (i.e., when kx = 0) we find that |FR/FI| = 1 because , while SG/FI = 0. There is thus a complete reflection of the incoming fast mode, while the slow mode is absent. When there is coupling, the reflection coefficient for the slow mode is always different from zero, meaning that the incoming fast MHD wave inevitably generates a slow mode at the boundary. In Fig. 1 the reflection coefficient of the fast wave, i.e., FR/FI, is plotted as a function of kx for different values of the sound speed. The coefficient is close to unity for values of low sound speed in comparison with the Alfvén speed, meaning that reflection is almost total. However, for relatively high values of cs/vA the curves clearly show a minimum indicating that the reflection of the fast wave is less efficient.
Amplitude of the generated slow mode given by Eq. (15) as a function of the horizontal wavenumber for three different values of the sound speed. The dashed line represents the approximation given by Eq. (18) while the dotted line shows the position of the maxima according to Eqs. (19) and (20).
In Fig. 2 the reflection coefficient of the slow wave, i.e., SG/FI, is plotted. The behaviour of the reflected slow mode amplitude is basically the opposite of the reflected fast wave. The curves show a maximum at the locations where the generation of the slow mode is more efficient. Again the value at the maximum strongly depends on the ratio of the sound speed to the Alfvén speed, and corresponds to a kx which is very similar to kF. The location of the maximum can be analytically determined from Eq. (15), and when using the approximation of the slow mode frequency, , (16)Since the frequency is fixed, we have from the approximate expressions (8)–(9) for and the following relation (17)Inserting this expression to Eq. (16), we find that (18)This is a good approximation of the slow mode reflection coefficient (see dashed line in Fig. 2), at least for the case cs ≪ vA. It is used to determine the location of the maxima of the curves in Fig. 2. When imposing that the derivative of Eq. (18) is equal to zero, it is found that the maximum corresponds to (19)and the value of the reflection coefficient for this horizontal wavenumber is (20)The location and value of the maximum is represented in Fig. 2. There is excellent agreement between the approximation and the location of the maximum calculated using the original expression for the reflection coefficient of the slow mode (Eq. (15)). From Eq. (20) we see that the maximum amplitude of the generated slow wave depends only on the β of the plasma.
Once we know the coefficients, it is straightforward to calculate magnitudes of interest such as the density perturbation of the slow reflected wave as a function of amplitude of the incoming fast wave. As we discuss later, these magnitudes can be directly related to real observations. From the continuity equation (see Appendix A), the density perturbation for the slow mode is (21)Using again the fact that and Eq. (20) we find (22)This equation relates the maximum density perturbation associated to the generated slow mode with the velocity amplitude of the incident fast wave.
3.2. The time-dependent problem
The time-dependent problem is numerically solved to demonstrate the mode coupling described in the previous section. The temporal evolution of the waves and specially their interaction with the boundaries provides a clear picture of the coupling and complements the analytical results.
In this numerical experiment a pulse in the vx component is generated at t = 0. This pulse has the following form and the rest of the perturbed variables are set to zero. This particular profile has the property that represents a localised wave packet but with a rather well-defined wavelength (basically given by λ = 2π/k). To show the interaction of the fast mode with a single boundary, rigid conditions are applied at z = 0 (vx(z = 0) = vz(z = 0) = 0) while open conditions are imposed at z = L. The linearised time-dependent MHD equations (see Appendix A) are numerically solved using standard finite differences techniques.
Time evolution of the propagating disturbance given by Eqs. (23)–(24). The continuous line represents the vx component, while the vz component is plotted with a dotted line. Its amplitude has been multiplied by a factor 40 for visualisation purposes. Fast and slow modes travelling to the left are denoted as FI and SI, FI + and SI + move to the right, and SG is the generated wave at z = 0 (moving to the right). For this simulation z0/a = 5, ka = 2π/0.75, v0/vA = 1, kxa = 1.5 and cs/vA = 0.2. In this plot the time has been normalised to the characteristic time scale, τA = vA/a.
The temporal evolution of the two velocity components is plotted in Fig. 3. The initial disturbance excites the fast mode, but also the slow mode, since the initial perturbation does not satisfy the velocity polarisation relation, given by Eq. (10). The excited fast and slow modes split in two identical modes propagating in opposite directions (top panel). The fast and slow waves travelling to the left are denoted as FI and SI, respectively, while FI + and SI + move to the right. Once the FI mode reaches the rigid boundary (z = 0), it gets reflected (see middle panel) with an amplitude FR and a slow mode is generated; i.e., the SG mode according to the notation introduced above. The slow wave packet has a typical wavelength much smaller than the fast wavelength (kF ≪ kS). At the other boundary (z = L), the fast mode FI + leaves the system owing to the transparent boundary conditions. At later times (bottom panel), the SG and SI modes, moving in opposite directions, start to superpose, while the FR and SI + , travelling in the same direction, also interfere.
The amplitudes of reflected fast and slow waves estimated from the time-dependent problem agree quite well with the calculations based on the analytical reflection coefficients given by Eqs. (14)–(15). These equations were derived for purely sinusoidal and monochromatic waves, but the initial packet is represented well by a dominant frequency (wavelength), and this is the reason it agrees with the analytical results.
3.3. Slow MHD wave reflection
Although we are mainly interested in the fast reflection problem, the slow mode reflection problem is also studied for completeness. The difference with respect to the fast MHD reflection problem is that reflection of the slow MHD mode at the boundary generates a fast MHD mode. The velocity components for this problem are The following coefficients for the reflected slow mode and the generated fast mode are found by applying rigid boundary conditions It is worth noting that the reflection coefficient of the slow mode is exactly the same as the reflection coefficient of the fast mode given by Eq. (14).
Once we understand the reflection of a propagating fast and a propagating slow wave at a rigid boundary we extend our analysis to a more realistic physical situation, i.e., the standing fast wave problem that is commonly reported by TRACE.
There are several ways to study this problem, and the perturbation method is one of them. Under this approach, we know that for zero-β we have a pure standing fast wave with only a vx velocity component that satisfies the boundary conditions. When β is different from zero but small, a vz component is introduced, due to Eq. (10), and even worse, this component does not satisfy the boundary condition. To compensate, we have to add a slow wave perturbation to the system (with a dominant vz in comparison with vx), which combined with the vz of the fast, will satisfy the boundary conditions jointly. Now the vx introduced by the slow mode is irrelevant since it is higher order in β (which is assumed to be small).
Another way to analyse this problem is to solve the full-standing problem. This has already been done by Oliver et al. (1992) and Goedbloed & Halberstadt (1994), and it is based on the superposition of the fast reflection problem plus the slow reflection problem. The perturbation scheme and the full eigenmode problem give similar results, except where the solutions are completely mixed, i.e., when the slow mode component is not small in comparison with the fast component. This takes place around the "avoided crossings" in the dispersion diagram (see Oliver et al. 1992, for further details).
The advantage of the perturbation scheme is that we can still obtain simple approximations for the velocity and density changes around the footpoints. Let us assume that an initial disturbance mostly excites the standing pattern in the vx component. This standing wave is composed by the superposition of two identical propagating waves travelling in opposite directions. We concentrate on the fundamental mode, having a maximum at z = L/2 and a node of the velocity at the boundaries. A propagating slow wave is induced by the reflection at the boundaries of the incident propagating fast wave that forms part of the standing fast pattern. As a result, if the transverse velocity amplitude of the standing fast wave at the loop apex is V0, the amplitude of the incoming fast wave is V0/2. The reflected fast wave will also have an amplitude of V0/2 in our approximation. Once we know this amplitude, it is easy to estimate the velocity or density fluctuations associated to the slow mode using the results of the propagation problem. According to the analysis performed in the previous section (see Eqs. (20) and (22)), (29)and (30)These very simple expressions give the order of the maximum velocity and density perturbations associated to the slow reflected mode as a function of the transverse velocity amplitude at the loop apex and the characteristic speeds of the configuration. When cs ≪ vA the velocity perturbation reduces to (31)while the density perturbation is (32)It is worth calculating the order of magnitude of velocity and density fluctuations around the footpoint. Let us take typical values: vA = 800 km s-1, cs = 200 km s-1, V0 = 80 km s-1. Thus, the velocity perturbation according to Eq. (29) is |vz|max ≃ 2.5 km s-1. Using Eq. (30) we find that the density fluctuation associated to the slow mode is |ρ1/ρ|max ≃ 1.25%. These density perturbations, although small, should be detectable with the current instruments. Obviously, larger sound speeds or small Alfvén velocities would result in an increase in velocity and density fluctuations.
The previous estimations are based on the assumption that the excited slow modes do not have time to reach the opposite footpoint and reflect. If this is the case, the problem is more difficult since the slow modes interfere, and the velocity and density changes can be greater than those given by Eqs. (29)–(30). It is also important to notice that the density perturbation associated to the fast standing mode has the same profile as the velocity (the vx component), therefore the fast density perturbation is zero at the footpoints (and maximum at the apex). This explains why it is enough to consider only the density changes associated to the excited slow modes around the footpoints.
Now the time-dependent problem is solved. The initial perturbation, representing the excitation of a mainly fast standing wave, has the following profile,
4.1.1. Rigid boundary conditions
Time evolution of the standing fast excitation given by Eqs. (33)–(34). The continuous line represents the vx component, while the vz component is plotted with a dotted line. Its amplitude has been multiplied by a factor 10 for visualisation purposes. For this simulation ka = π/10, v0/vA = 1, kxa = 1.5 and cs/vA = 0.2.
Line-tying conditions are applied at the two loop footpoints. We choose the longitudinal wavenumber that excites the fundamental standing fast MHD mode, i.e., k = π/L. The results, represented in Fig. 4 manifest the generation of slow modes at the footpoints (top panel). The fast mode drives slow modes, which move in the direction of the loop apex, located at z = L/2 (see middle panel). At a certain time (when t ≃ L/2cs) the interference between the opposite propagating slow waves is produced. Since the two slow waves are identical but travelling in opposite directions a quasi-standing pattern is visible (see the profile of vz around z = 5a in the bottom panel). Eventually, slow modes reach the opposite footpoint and get reflected. Under such conditions the inverted process takes place; i.e., the slow mode generates a fast mode. Nevertheless, this problem would take us too far beyond the scope of this work. However, it is worth noting that depending on the equilibrium and wave parameters the generated slow modes might match the frequency of a standing slow eigenmode of the loop. This means that since the slow mode is driven by the fast standing mode, the frequencies of the slow standing and fast standing waves will be basically the same and the modes will have a highly mixed nature. This takes place around the "avoided crossings" in the dispersion diagram.
4.1.2. Sharp photosphere-corona transition
From the previous results we might think that the generation of slow modes takes place only when rigid boundary conditions are imposed. To address this question, instead of line-tying conditions, a density transition between the corona and the photosphere is considered. As density profile we use the following idealised model, (35)Parameter w measures the width of the transition between the photosphere, with density ρph, and corona, with density ρc. The density contrast is set to ρph/ρc = 108. Non-reflecting conditions are imposed at the boundaries, now placed below the photosphere. The details of the model used to represent the transition photosphere-corona are not important since our focus is on the generated slow modes. The equilibrium gas pressure is set to the same constant value in the corona and photosphere to have magnetohydrostatic equilibrium.
Time evolution of the standing fast excitation given by Eqs. (33)–(34) with the density model given by Eq. (35). The continuous line represents the vx component, while the vz component is plotted with a dotted line (its amplitude has been multiplied by a factor 10 for visualisation purposes). The vertical dashed lines represent the locations of the transition between the corona and photosphere. For this simulation ka = π/9, v0/vA = 1, kxa = 1.5, cs/vA = 0.2, ρph/ρc = 108, w/a = 0.25.
The results of the time-dependent simulation are plotted in Fig. 5. There are some differences with respect to the behaviour found for the perfectly reflecting boundaries. For example, the system now allows the energy to escape through the photosphere; i.e., there is a transmitted fast (and slow wave). This means that the energy can leak through the photosphere but this is not visible in Fig. 5 because the amplitude is very small. Nevertheless, the primary result here is that a similar slow-mode generation in comparison with the case of reflecting boundaries is produced in the coronal part (compare Figs. 4 and 5). The results are qualitatively similar, so, the overall conclusion is that nonuniformity causes the coupling between fast and slow modes in a similar way to line-tying conditions.
It is interesting to look for signatures of the mode coupling studied in this work in the observations. Recently, Verwichte et al. (2010) have reported from combined observations with TRACE and EIT/SoHO, intensity fluctuations at one loop footpoint with basically the same period, around 40 min, as the fast transverse oscillation of the loop. This long periodicity indicates that the origin of these density oscillations is most probably not photospheric. Verwichte et al. (2010) suggest that the intensity oscillations are due to variations in the line-of-sight column depth produced by the changes in the loop inclination as it oscillates with the transverse kink mode. This would explain the coincidence in periods and also in the damping times.
Relative profile of intensity variations seen in a transversely oscillating loop studied by Verwichte et al. (2010) using TRACE as a function of distance along the loop. The solid circle is the measurement of the intensity variation at the loop foot point. The long-dashed and dashed curves are functions –0.13sin(3π/L) and –0.13sin(5π/L), respectively, representing a possible third or fifth standing harmonic of the slow mode.
According to our study, an alternative explanation for the intensity variations reported by Verwichte et al. (2010) is done in terms of the coupling between fast and slow waves due to the line-tying conditions. The similarity of the periods of the transverse mode and the intensity fluctuations is explained by our model where the excited slow wave, as well as the corresponding intensity oscillation, has the same periodicity as the transverse loop motion. Verwichte et al. (2010) show intensity variations associated with a transverse oscillation in a large loop of 690 ± 60 Mm length. The oscillation, which is a horizontally polarised fundamental kink mode, has a period of P = 2418 ± 5 s. Therefore, the phase speed is equal to vph = 580 ± 50 km s-1. For a thin loop in the long wavelength limit, this phase speed tends to the kink speed, ck, of a cylindrical tube. If the intensity oscillation is associated with a slow magnetoacoustic mode with the same periodicity as the kink mode, then its wavelength is equal to λs = csP = (csP/vph)2L. For a temperature between 0.9 and 1.8 MK, the coronal sound speed is in the range 144–198 km s-1. Hence, λs = (0.30 ± 0.07) 2L. For a standing mode, this translates into a wavenumber n = vph/cs = 2L/λs = 3.3 ± 1.0. The EIT observations suggests that the intensity variations at the two foot points of the loop oscillate in anti-phase. If standing, the mode should be an odd harmonic. Figure 6 shows the relative profile of intensity variations as a function of loop distance. The relative intensity has an amplitude of approximately 13%, which translates into a density perturbation with an amplitude, | ρ1/ρ | max = 6.5%. However, it is clear that a third or fifth harmonic could fit the observed intensity variation if we consider that the slow mode is most likely still evolving towards a standing wave pattern. We measured the full intensity profile as a function of distance along the loop using EIT. Nevertheless, this has large uncertainties attached to it because of the lack of resolution and line-of-sight confusion. Also, the loop may be longitudinally structured in temperature. The EIT measurement hints at the presence of a fifth harmonic. Verwichte et al. (2010) show that the displacement amplitude, ξ0, can be modelled by a ten degree inclination of the loop. As the loop has a height of 236 Mm this means that ξ0 = 41 Mm. Hence, the velocity amplitude V0 = ξ0ω = 106 km s-1. Using Eq. (30) and the estimated value for the Alfvén speed, vA = 410 ± 40 km s-1, we find |ρ1/ρ| max = 5 ± 3%. This is consistent with the observed density amplitude (around 6.5%).
In another work, Verwichte et al. (2009) also report intensity oscillations associated with a kink mode seen by EUV onboard STEREO and interpreted these as resulting from variations in the line-of-sight column depth owing to the loop showing a varying aspect to the observer. The measured relative density amplitude is 2.5% and is located around to loop top. Can this observation be explained by a slow mode instead? In that observation, the key parameters that were measured are L = 340 ± 15 Mm, vph = 1100 ± 100 km s-1, V0 = 35 ± 9 km s-1, and vA = 800 ± 100 km s-1. For the peak temperature of the EUV 171 Å bandpass of 0.9 MK, cs = 144 km s-1. The slow mode would have a wavenumber n = 7 ± 1 (in the case of a standing mode), corresponding to a wavelength of about λs = 90 ± 10 Mm. Again, using Eq. (30), we calculate |ρ1/ρ| max = 0.4%, which is negligibly small. Therefore, for this observation, the slow mode is not able to explain the observed intensity variations. The main difference with respect to the case studied by Verwichte et al. (2010) is that the density perturbations are located around the loop top instead of the loop footpoints.
In this work we have investigated the possible effects of linear coupling between fast and slow modes that takes place due to the reflection at the photosphere. By solving the reflection problem, we have shown that the transverse motion of the loop produces slow MHD waves as long as the fast wave is obliquely incident on the boundary. These slow waves are manifested as propagating density fluctuations with the same frequency as the standing transverse mode and are generated at the loop footpoints. The wavelength of these slow modes is basically given by ks ≃ ω/cs, and since vA > cs their wavelength is smaller than that of the corresponding fast standing transverse mode. Moreover, we used the reflection coefficient of the slow mode to derive simple analytical expressions that relate the transverse displacement at the loop top with the amplitude of the density fluctuations produced at the footpoints. The coupling between fast and slow is proportional to the plasma-β, indicating that it will be weak under coronal conditions. However, it is proportional to the amplitude of the oscillation of the fast mode, which can be large in some cases, and close to the footpoints, i.e., close to the photosphere, the ratio between the sound and Alfvén speeds can increase. Ideally, from the properties of the reflected slow modes, we could have indirect information about the real line-tying conditions in coronal loops and realistic values of the sound speed near the footpoints.
The generated slow waves can eventually form a standing pattern along the loop. Thus, mode coupling might provide an excitation mechanism of standing slow modes, different from the driven photospheric origin usually emphasised in the literature. However, since the sound speed is assumed to be slower than the Alfvén speed, the time required for the slow mode to travel along the loop and reflect at the footpoint is much longer than that of the fast MHD mode. This means that slow-standing modes will need much more time than fast-standing modes to build up. Nevertheless, if the wavelength of the slow modes is very short they might be damped by thermal conduction before the standing wave is formed.
It has been shown that, in the observations analysed by Verwichte et al. (2010), there are possible fingerprints of the coupling between fast and slow modes owing to line-tying, providing an alternative explanation to the effects of integration along the line of sight proposed by these authors. However, in the observations studied by Verwichte et al. (2009), the mechanism is unable to explain the intensity oscillations. One of the reasons might be that the density changes observed in this event are reported around the loop apex, while the estimations are based on propagating waves around the footpoints. In the case of the standing pattern, the density fluctuations can be much larger. Further analysis of other observations will test the linear coupling as an operative mechanism in coronal loops.
It is worth mentioning that the mode coupling discussed in the work is a purely linear effect. It is unrelated to the nonlinear coupling between fast and slow modes due to the ponderomotive force (see Hollweg 1971; Rankin et al. 1994; Terradas & Ofman 2004) or to the parametric coupling studied by Zaqarashvili et al. (2002, 2005). It is also different from the mode conversion that takes place when cs = vA. Line-tying boundary conditions are the responsible ingredients of the coupling, but we have shown that they are not the only way for fast and slow waves to couple. A sharp transition between the corona and the photosphere produces the generation of slow modes, i.e., a change in the properties of the medium, for example the transition region, leads inevitably to the coupling.
Our theoretical model is based on a Cartesian geometry without a density enhancement representing a loop. For this reason, it is necessary to improve the model by including a slab or a cylinder that mimics the effect of a dense magnetic tube. This will complicate the mathematical problem of the reflection at the boundary, and it might be difficult to derive simple analytical expressions. For example, in a cylindrical model, the eigenfunctions of the slow and fast MHD waves have different radial dependencies and might share the same azimuthal wavenumber (basically playing the role of kx in the present work). This issue will be addressed in a future study.
J.T. acknowledges the Universitat de les Illes Balears for a postdoctoral position and the financial support received from the Spanish MICINN and FEDER funds (AYA2006-07637). J.T. thanks Ramón Oliver and Roberto Soler for useful comments and suggestions. J.A. is supported by an International Outgoing Marie Curie Fellowship within the 7th European Community Framework Programme. J.A. also acknowledges support by the Fund for Scientific Research – Flanders. E.V. acknowledges financial support from the UK Engineering and Physical Sciences Research Council (EPSRC) Science and Innovation award.
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We use the linearised MHD equations of the momentum, induction, energy, and continuity equation. Assuming Fourier analysis in the x − direction we have \newpage In these equations B0 is the equilibrium magnetic field and ρ and p the equilibrium density and gas pressure, respectively. The rest of the variables correspond to the perturbed magnitudes. To eliminate the imaginary complex numbers we simply define With this transformation the time-dependent equations are solved using standard numerical techniques.
The dispersion relation, given by Eq. (1), is easily derived assuming in the previous equations a temporal dependence of the form eiωt and a spatial dependence with the z-coordinate of the form eikzz. We used the following standard definitions for the Alfvén and sound speeds,
In the text
Phase relations for seismology of photospheric flux tubes
The temporal behaviour of MHD waves in a partially ionized prominence-like plasma: Effect of heating and cooling
Transverse kink oscillations in the presence of twist
Magnetoacoustic waves in diagnostics of the flare current sheets
Rayleigh-Taylor instability in partially ionized compressible plasmas: One fluid approach
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{
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On the shores of Sapodilla Bay, Villa Turquesa offers a unique blend of luxurious amenities and laidback island style. Located within the Ocean Point Drive Community, this expansive 4,750 sq.-ft. home features exquisite vaulted ceilings, an open layout, and spectacular furnishings. Beautifully designed to provide outstanding views of the pristine turquoise waters from every room, this traditional Colonial Barbadian style home offers every modern luxury.
Villa Turquesa features a beautiful professional kitchen, handcrafted cabinetry, gorgeous hardwood floors, a phenomenal private pool and patio, and perfectly landscaped grounds. The magnificent Barbadian Coral Stone exterior has been expertly white washed and offers the picturesque vision of Caribbean splendor. From the car park to the private waterfront deck, this home has it all.
Perfectly perched on the west coast of Providenciales (Provo), this luxury vacation home places all of the wonder of the Caribbean at your feet. From strolling along the exclusive white sand beach of Taylor Bay, to slipping beneath the surface of your own secluded pool, Villa Turquesa offers the chance to experience the Caribbean like never before.
Four bedroom, sleeps eight guests.
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{
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Aniel peut désigner :
Aniel, trente-sixième album de la série de bande dessinée belge Thorgal, scénarisé par Yann et dessiné par Grzegorz Rosiński ;
Pierre-Jean Aniel, danseur et chorégraphe français ;
Talorg mac Aniel, roi des Pictes.
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{
"redpajama_set_name": "RedPajamaWikipedia"
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Cooking with Hominids
By Sirena Khanna
Food is often on our minds. We are the only species that watches competitive baking, eats tropical fruit in freezing climates, and adorns our food with gold. The mass production, transport, and consumption of foods from all over the world are feats that can only be derived by the human brain, and as it turns out, food is what helped shape our brains in the first place.
The story starts 1.9 million years ago when our ancestors, Homo erectus, first appeared in Eurasia (as the most recent fossil evidence suggests). Raw meat, as well as vegetables and fruit, were staples of the hominid diet. One day, our ancestors made a great culinary advancement and cooked meat entered the scene. By chance or tasteful insight, H. erectus combined meat and fire, and in the process created the world's first barbeque.
Prehistoric cookouts were a success. H. erectus developed brains twice the size of their predecessors, H. habilis, and their teeth and body size decreased to about the size of a modern human's. This is the basis for Richard Wrangham's "cooking hypothesis," which attributes the dramatic increase in H. erectus brain size that occurred 500,000 years ago to the advent of cooking. This newfound ability may have prevailed, he posits, because it allowed H. erectus to save a significant amount of time and energy that would otherwise have been spent on chewing raw meat.
Wrangham collected data on chimpanzees and found that they can spend up to 5 hours a day gnawing on fruit. At the chimpanzee's chewing rate, H. erectus would have had to spend a quarter of their lives chewing and another quarter gathering food to sustain their energy needs if they did not cook their meat. Lucky for modern humans, H. erectus were the master chefs of hunter-gatherer society; cooking meat altered the chemical structure of proteins and starches such that it was easier to break down. Wrangham postulates that cooked meat expedited digestion, as evidenced by a decrease in gut size. The energy saved from digestion went into spurring the encephalization of H. erectus.
Wrangham's hypothesis is a good start to explaining the sudden change in hominid brain size. There is, however, one complication: the discovery and use of fire. Some skeptics maintain that H. erectus did not control fire until 200,000 years ago, which doesn't coincide with the "cooking hypothesis" timeline. Scientists are currently searching for evidence of man-made fires to investigate whether fire use did exist at the time of hominid brain expansion; however, fire use is difficult to pinpoint, as early hominids may have interacted with natural fires to cook before learning to control fire.
In the meantime, researchers Katherine Zink and Daniel Lieberman recently published a study that claims sliced meat might be responsible for the decrease in hominid teeth and jaw size. Similar to cooking, slicing meat makes meat easier to chew by breaking down the tissue and making the nutrients more accessible. Early hominids began to use stone tools at least 3 million years ago, so this timeline suggests that H. erectus used tools to slice their meat before they learned to cook it. The two proposals are not mutually exclusive, though: it is possible that slicing meat contributed to a decrease in tooth and jaw size, and later on cooked meat further propelled that shift.
The "expensive tissue hypothesis" also attempts to explain the physiological changes in H. erectus. It presents the paradox of having a metabolically expensive brain while maintaining energy-consuming organs. This hypothesis proposes that encephalization and reduction in gut size is only possible due to a diet of high-quality and easy to digest foods, such as various animal products like meat and bone marrow. Although the "expensive tissue hypothesis" does not focus on cooked or sliced meat, it does concur with the other postulates that animal product additions to the hominid diet were essential for the evolution of a larger human brain.
Whether sliced meat, cooked meat, or high-quality diets spurred larger brains is the primeval kitchen battle yet to be resolved. The growth could be due to a multitude of factors, so perhaps, on this cooking show, everyone wins. Over time, hominid teeth and gut size decreased while the brain steadily grew larger, especially the neocortex, a part of the brain's center for higher cognitive functions. In terms of sheer size, the H. erectus ancestors, H. habilis, who lived 2 million years ago, had mature brain sizes of about 610 cubic centimeters; in comparison, the average adult human now has a brain size of 1,400 cubic centimeters.
Why does an increase in brain size matter? The general idea might be that bigger brains are better, but size is not everything. Neuroscientists Randy L. Buckner and Fenna M. Krienen propose that as hominid brains expanded, the tether-like network of neurons was ripped apart, allowing neurons to form new circuits. They call this the "tether hypothesis," which elegantly explains why brain expansion matters for the evolution of brain function. Brain size alone, however, does not distinguish us from other species. Blackfish dolphins have twice as many neurons in the neocortex as humans, but their overall cognitive ability is not above a human's.
Since there is no correlation between cognitive performance and the number of neocortical neurons, our superior cognitive abilities must be due to a combination of factors other than sheer brain size. There are many aspects of brain composition to consider, such as the sophistication of neural synapses and metabolism, the latter of which relates back to the three hypotheses about changes to the hominid diet. Changes to hominid diet, such as cooked or sliced meat, ultimately made energy consumption more efficient and fruitful for our ancestors. Greater energy-yielding diets led to gut, teeth, and jaw size reduction, while providing the energy for encephalization. As the only species that cooks, it is humbling to think that our relationship to food put us on a different cognitive trajectory than the rest of the animal kingdom.
Thanks to our ancestor's penchant for firing up the grill, we can do things no other animal has come close to. But whereas meat-eating was an important factor in getting hominids to this point, the rampant consumption of meat is currently undoing humanity. Greenhouse gases produced by the processing and transportation of animal products threaten both humans and the environment, and antibiotics and hormones in meat give rise to health concerns like cardiovascular disease and undesirable genetic mutations. Nevertheless, meat consumption allowed our ancestors to develop larger brains that shaped who we are as humans today. As a tribute to our early cooks, we can imagine new ways to better our brains that do not rely on consuming meat at our current rate. If our ancestors could invent the barbecue with their small brains, then there is no doubt that bigger brains, with more tools, can achieve anything.
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{
"redpajama_set_name": "RedPajamaCommonCrawl"
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Efforts to End Mandatory Minimum Sentences
by Eugene Puryear, Sean Blackmon
Eugene Puryear, Sean Blackmon. Sputnik International
https://sputniknews.com/radio_by_any_means/201710261058543981-effort-to-end-mandatory-minimum-sentences/
Body Camera Report shows little change; Red-Baiting Black Activist in America; Efforts to end mandatory minimum sentences.
On this episode of "By Any Means Necessary" hosts Eugene Puryear and Sean Blackmon are joined by Dr. Philip Stinson, Associate Professor, Criminal Justice Program at Bowling Green State University, to talk about a recent Washington, D.C.-based study looking at the relationship between police misconduct cases and body camera usage, how officers simply forget they are being recorded and commit illegalities, and how communities can share and use data on police activities.
In the second segment of the show Jon Liss, Executive Director of New Virginia Majority, to talk about the national significance of several Virginia state elections in 2018, the numerous ways in which voting is suppressed in the state, how economically oppressed people in the state are not voting for Democrats as the party would hope and whether or not Trump will swing voters off of the Republican Party in the mid-term election cycle.
Later in the show hosts Eugene Puryear and Sean Blackmon are joined by Gerald Horne is Moores Professor of History and African American Studies at the University of Houston to talk about the long history of Black Americans working to gain international support for their domestic causes, the ways American politicians have attempted to use "Russia-phobia" scare tactics to steal voters from their opponents, the FBI's efforts to stir discord among Black activists in the 1950s and 1960s, and the growing movement towards a new McCarthyism-esque with hunt of radicals and activists in the US.
Eugene Puryear and Sean Blackmon start the second hour of the show talking about the deaths of Fats Domino and Robert Guillaume and the need for the Black Lives Matter movement and other black radicals to look to international revolutionary movements for advice.
In the last segment "By Any Means Necessary" is joined by Molly Gill our VP of Policy, Families Against Mandatory Minimums to talk about the vast ways mandatory minimum sentences are used, how misconceptions of prisons serve as an obstacle to engage individuals in supporting prison reforms, and the failure of mandatory minimum's to actually reduce addictions or violent crimes. The group also talks about ways to successfully frame the need for prisons and criminal justice reform in conservative states, the systemic issues driving the rapid increase of women in prison and the desperate need to rethink and resource re-entry programs for prisoners.
We'd love to get your feedback at radio@sputniknews.com
FAMM, Body Cameras, Black Lives Matter, Donald Trump, Virginia
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{
"redpajama_set_name": "RedPajamaCommonCrawl"
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Q: Adding Logic Hooks in Magento? Can I ask regarding the topic? Can you add a logic hook in magento or anything like it?
Just tell me straight if it doesn't make sense or I'm just missing something from the Magento Doc's.
A: What you're looking for is called 'event observers' in Magento.
See:
http://www.magentocommerce.com/wiki/5_-_modules_and_development/0_-_module_development_in_magento/customizing_magento_using_event-observer_method
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{
"redpajama_set_name": "RedPajamaStackExchange"
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| 4,808
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6.2 PTR: Build 20061 Spell Changes, New Titles, Factions, and More 46 коммент.
looks really good hopefully there wont be any cutbacks..
szenarios once again, awesome. i never guessed the next content will come this quickly.
Nice, saw some Timewalker stuff in the LFG dungeons. Hopefully, that whole system comes out in 6.2.
Only question I have. When the hell are we going to get new bgs and arenas? Like seriously Ashran is a flop, need new pvp content pronto.
Methinks this does not bode well.
This stuff looks all great.. but where is the iron docks that blizz said they pushed back to 6.2?
huh, interesting, I see neither Gul'dan nor Grom as bosses in that raid. Either this isn't the final raid tier, or they're dispatched on the legendary quest. At this point anyone's guess is as good as mine.
...As in, Shadow-Sage Iskar? The arakkoa we first met in Talador, then helped in Arak?
See, I knew there was a reason that name sounded so familiar.
Nor for my followers, new ones again, and still no space for them! Dammit!
I really need to get cracking on the legendary quest, and hopefully I can experience this stuff in an actual raid.
The Archimonde + some Gul'dan with Archimonde sounds are not working so you wouldn't spoil whats next or what ? I really wanted to hear Archimonde.
yea none of the audio with archimode is working dunno if the file doesn't work because blizzard did something to it or if its wowheads doing.
OMG updated versions of S1 weapons! I'm totally going for the Red (listed as blue) 1h Sword to update my swords. I'm so excited!
Awesome, they updated my demons just in time to nerf the living *!@# out of demonology and make it unplayable. Thanks blizzard.
I'm honestly surprised that 6.2 is coming this fast, the stuff (other than classes changes, R.I.P. WW) sounds awesome.
Finally some colorful bows. But most are still war themed.
Wait, wait, wait: I thought the Hellscream family killed Mannoroth? Or a big 2h axe gone through the skull with a lot of green hellfire-ish demon blood dripping over the body is not enough these days? I know I missed some pve but come on.
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"redpajama_set_name": "RedPajamaC4"
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Nishiwaseda Campus will be closed on February 15(Fri), 16(Sat), 17(Sun), 19(Tue), 21(Thu), 22(Fri) in order to conduct entrance examinations. For those who need to issue certificates/ student discounts, it is recommended to obtain beforehand.
You are allowed to enter our campus only from the main gate between 8:00-17:00 on 18(Mon) and 20(Wed).
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{
"redpajama_set_name": "RedPajamaC4"
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A bilinear form, a(•,•) whose arguments are elements of normed vector space V is a strongly positive bilinear form if and only if there exists a constant, c>0, such that
for all where is the norm on V.
References
AMS 108 p.120
Functional analysis
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{
"redpajama_set_name": "RedPajamaWikipedia"
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Pissed Listener Harasses WMMS 100.7 With Laser, Porn
by Kyle Swenson
Marriage counseling rule No. 544: Shock jocks make lousy therapists. Matthew Rakovec learned this lesson the hard way.
Wounded when his wife left him, the 38-year-old Parma Heights man sought counsel on the airwaves with WMMS shock jock Rover last month. But instead of soothing words, the host and crew of Rover's Morning Glory heckled Rakovec.
Obviously in need of revenge, the lovelorn caller showed up at WMMS HQ in Independence with a green laser pointer, which he shined through the office windows. He also distributed a tasteful assortment of pornographic pictures in the station's entryway.
When Rakovec showed up again a week later, the Buzzard called police. Officers pulled him over as he tried to leave the parking lot; Rakovec admitted to shining the laser, but said it was only a joke.
"I just like to be on the radio," he told police. He initially denied the porn delivery, but was betrayed by the stack of nudie mags in his car. Eventually, he copped to having a vendetta against Rover.
"I'm sorry, it was stupid," he said, according to the police report. For that stupidity, Rakovec was booked on charges of inducing panic, disorderly conduct, and aggravated trespassing. Efforts to reach Rover were unsuccessful; calls left at WMMS for station manager Gary Mincer were not returned. Rakovec did not respond to Scene's phone calls, a tactic that would have served him well with WMMS too.
Crime Matthew Rakovec WMMS Rover's Morning Glory Gary Mincer
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{"url":"https:\/\/anilzen.github.io\/publication\/mroue-2013-catalog\/","text":"# Catalog of 174 binary black hole simulations for gravitational wave astronomy\n\n### Abstract\n\nThis Letter presents a publicly available catalog of 174 numerical binary black hole simulations following up to 35 orbits. The catalog includes 91 precessing binaries, mass ratios up to 8\u22361, orbital eccentricities from a few percent to $10^{\u22125}$, black hole spins up to 98% of the theoretical maximum, and radiated energies up to 11.1% of the initial mass. We establish remarkably good agreement with post-Newtonian precession of orbital and spin directions for two new precessing simulations, and we discuss other applications of this catalog. Formidable challenges remain: eg., precession complicates the connection of numerical and approximate analytical waveforms, and vast regions of the parameter space remain unexplored.\n\nPublication\nPhysical Review Letters","date":"2022-11-27 08:29:14","metadata":"{\"extraction_info\": {\"found_math\": true, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 0, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 1, \"mathjax_display_tex\": 0, \"mathjax_asciimath\": 0, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 0, \"wp-katex-eq\": 0, \"align\": 0, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.2930435836315155, \"perplexity\": 2145.929022613327}, \"config\": {\"markdown_headings\": true, \"markdown_code\": true, \"boilerplate_config\": {\"ratio_threshold\": 0.18, \"absolute_threshold\": 10, \"end_threshold\": 15, \"enable\": true}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2022-49\/segments\/1669446710218.49\/warc\/CC-MAIN-20221127073607-20221127103607-00452.warc.gz\"}"}
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«Золотая маска» — российская национальная театральная премия и фестиваль. «Золотая маска» была учреждена Союзом театральных деятелей России (СТД РФ) в 1993 году (в некоторых источниках назван 1994 год) по инициативе народного артиста СССР М. А. Ульянова (председатель СТД РФ в 1986—1996 годах) и при участии его заместителя В. Г. Урина и драматурга В. В. Павлова.
О премии
Премия присуждается на конкурсной основе один раз в год по итогам прошедшего театрального сезона за творческие достижения в области театрального искусства, вручается спектаклям всех жанров театрального искусства: драма, опера, балет, оперетта и мюзикл, кукольный театр.
Для определения соискателей премии «Золотая маска» создаётся экспертный совет из числа ведущих театральных критиков, специалистов союза театральных деятелей и его региональных организаций. Состав экспертного совета и его председатель утверждаются секретариатом СТД РФ. Для определения победителей — лауреатов из состава номинантов (тайным голосованием по результатам фестиваля) создаётся два профессиональных жюри — одно для спектаклей театра драмы и театров кукол и второе для спектаклей оперы, оперетты / мюзикла и балета. В состав жюри не могут входить создатели и исполнители спектаклей, участвующих в фестивале, а также члены экспертного совета.
Лауреаты и события фестиваля «Золотая маска» 2005 года
В Москве фестиваль «Золотая маска» — 2005 года прошёл с 24 марта по 10 апреля.
Номинанты премии «Золотая маска» 2005 года
Председателем экспертного совета драматического театра и театра кукол стал театральный критик Роман Должанский. В состав экспертного совета вошли: Александр Волков (заместитель начальника Департамента искусств и народного творчества Министерства культуры РФ), Ольга Глазунова (заведующая Кабинетом театров для детей и театров кукол СТД РФ), Екатерина Дмитриевская (театральный критик), Ольга Егошина (театральный критик), Олег Лоевский (директор всероссийского фестиваля «Реальный театр»), Ольга Никифорова (заведующая литературной частью Театра Сатиры на Васильевском острове), Татьяна Тихоновец (театральный критик).
Председателем экспертного совета музыкального театра стала критик и режиссёр Нора Потапова. В состав экспертного совета вошли: Лариса Барыкина (театральный критик), Гучмазова Лейла (балетный критик), Майя Крылова (балетный критик), Виолетта Майниеце (музыкальный критик), Гюляра Садых-заде (музыкальный критик), Марина Чистякова (музыкальный критик).
Таблица номинантов составлена на основании официального опубликованного списка, с группировкой по спектаклям.
Легенда:
— Спектакль номинирован в номинации «Лучший спектакль»
«» — Этот аспект спектакля не номинирован
Лауреаты премии «Золотая маска» 2005 года
Председателем жюри драматического театра и театров кукол стала театральный критик Инна Соловьёва. В состав жюри вошли: Алексей Бартошевич (театровед, историк театра), Александр Борок (режиссёр), Василий Бочкарев (актёр), Михаил Бычков (режиссёр), Анатолий Голубовский (главный редактор радиостанции «Культура»), Марина Давыдова (театральный критик), Григорий Дитятковский (режиссёр), Светлана Замараева (актриса), Наталия Каминская (театральный критик), Майя Кобахидзе (начальник управления современного искусства Федерального агентства по культуре и кинематографии РФ), Эдуард Кочергин (театральный художник), Владимир Оренов (театральный критик, режиссёр), Юлия Рутберг (актриса), Марина Тимашева (театральный критик), Валерий Яковлев (актёр, режиссёр).
Председателем жюри музыкальных театров выступил композитор Родион Щедрин. В состав жюри вошли: Екатерина Бирюкова (музыкальный критик), Павел Бубельников (дирижёр), Ара Карапетян (дирижёр), Наталья Касаткина (балетмейстер), Наталья Курюмова (критик, теоретик танца), Марина Нестьева (музыковед), Вячеслав Окунев (театральный художник), Майя Плисецкая (артистка балета), Мария Ратанова (критик, историк балета), Дмитрий Родионов (главный редактор журнала «Сцена»), Тамара Синявская (певица), Кирилл Стрежнев (режиссёр), Александр Титель (режиссёр), Елена Третьякова (музыкальный критик).
Церемония вручения премий «Золотая маска» состоялась 11 апреля в Театре им. Моссовета. Режиссёром церемонии выступила Нина Чусова, которая оформила его в виде спортивного мероприятия. Зал театра был оформлен эмблемами спортклубов, вели церемонию спортивный комментатор Василий Уткин и актриса Инга Оболдина, призы вручали известные спортсмены вместе с драматическими актерами. По мнению газеты «Коммерсантъ» «страсти кипели как на футболе».
Критики отметили более слабую программу драматического театра, чем в прошлом году. По мнению обозревателя Дины Голдберг («Русский Журнал»), распределение призов в драме «было предсказано». «Самым большим проколом» фестиваля редакторы газеты «Известия» назвали победу в номинации «Лучший спектакль современного танца» спектакля «Тряпичный угол» екатеринбургского эксцентрик-балета Сергея Смирнова, который, по их мнению, сильно проигрывал конкурентам. «Тряпичный угол» был также раскритикован и редакторами «Коммерсанта» и, по их словам, решение жюри вызвало удивление среди зрителей. Редакторы газеты «Коммерсантъ» обратили внимание на то, что в жюри музыкальных театров входят только три человека, профессионально разбирающихся в балете: артистка балета Майя Плисецкая, балетмейстер Наталья Касаткина и историк балета Мария Ратанова. В связи с этим результаты премии в номинациях, связанных с балетом, виделись им наиболее непредсказуемыми, но оказались при этом, по их мнению, довольно адекватными и совпали с мнениями корреспондентов «Коммерсанта».
Таблица лауреатов составлена на основании положения о премии (от октября 2000 года) и официального опубликованного списка лауреатов.
Легенда:
— Лауреаты премий в основных номинациях
— Лауреаты премий в частных номинациях
— Премия не присуждалась
Примечания
Ссылки
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{
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}
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Every Man Has a Woman is a tribute album to Yoko Ono for her 50th birthday. It contains covers of her songs from the albums Approximately Infinite Universe (1973), Double Fantasy (1980), Season of Glass (1981), and It's Alright (I See Rainbows) (1982). The album was purportedly one of John Lennon's projects, but he died before he could see its completion. The liner notes for the vinyl LP feature an essay by Ono entitled "A Crystal Ball".
Another tribute album to Ono in a similar vein entitled Yes, I'm a Witch was released to very positive reviews in 2007, featuring such artists as Peaches, Cat Power and The Flaming Lips.
Track listing
All words and music by Yoko Ono
"Every Man Has a Woman Who Loves Him" – 3:32 - John Lennon produced by John Lennon, Yoko Ono and Jack Douglas
"Silver Horse" – 3:07 - Harry Nilsson produced by Harry Nilsson and Rick Riccio
"I'm Moving On" – 2:47 - Eddie Money produced by Andy Johns and Eddie Money
"Nobody Sees Me Like You Do" – 3:23 - Rosanne Cash produced by Rodney Crowell and Rosanne Cash
"Dogtown" – 3:26 - Alternating Boxes produced and arranged by Guy Manganiello
"Goodbye Sadness" – 3:22 - Roberta Flack produced by Ralph MacDonald and Roberta Flack
"Walking on Thin Ice" – 3:46 - Elvis Costello and The Attractions (with The TKO Horns) produced by Allen Toussaint
"Wake Up" – 2:22 - Trio produced by Klaus Voormann
"Dream Love" – 3:46 - Harry Nilsson produced by Harry Nilsson and Rick Riccio
"Now or Never" – 3:44 - Spirit Choir produced by John Lennon, Yoko Ono and the Plastic Ono Band
"Loneliness" – 3:42 - Harry Nilsson produced by Harry Nilsson and Rick Riccio
"It's Alright" – 2:27 - Sean Lennon produced by Yoko Ono and Sean Lennon
Singles
"Every Man Has a Woman Who Loves Him" (John Lennon) / "It's Alright" (Sean Lennon) (7")
"Silver Horse" / "Dream Love" (Harry Nilsson) (7")
"Loneliness" (Harry Nilsson) (7")
"Dogtown" (Alternating Boxes) (12")
References
Yoko Ono albums
1984 albums
Tribute albums
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<?php
class filter_missing extends query_base_model
{
protected
$parents = array(
'filter',
'filters',
'and',
'not',
'or',
'must_filter',
'must_not_filter',
'should_filter'
),
$type = 'filter',
$name = 'missing';
protected function constructBody()
{
$this->createHeader();
$this->createMinus();
$this->createNestDiv('field');
$this->createLabel('field');
$this->createGetField('setval');
$this->createCloseDiv();
$this->createNestDiv('existence');
$this->createLabel('existence');
$this->createSelect('setval', array('' => 'default', 'true' => 'true', 'false' => 'false'));
$this->createCloseDiv();
$this->createNestDiv('null_value');
$this->createLabel('null_value');
$this->createSelect('setval', array('' => 'default', 'true' => 'true', 'false' => 'false'));
$this->createCloseDiv();
return $this->output();
}
}
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 6,599
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<?php
/**
* A builder that adds the Propel model name.
*
* @package sfPropelSearch
* @subpackage Builder
* @author Carl Vondrick
* @see xfPropelCriterionModelName
*/
final class xfPropelBuilderModelName implements xfBuilder
{
/**
* @see xfBuilder
*/
public function build($input, xfDocument $doc)
{
$name = sha1(get_class($input)); // we must hash it because we do not want to return this value when a user does a query search
$doc->addField(new xfFieldValue(new xfField('_propel_model_name', xfField::INDEXED), $name));
}
}
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 1,501
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Ronald J Shandorf is a Unclassified business in Marcell, MN.
Ronald J Shandorf classified under Unclassified, with principal employer Ronald J Shandorf Full Name Report is located in 38207 County Road 45, Marcell, Minnesota MN 56657. For sales, support, account inquiries, and how to be an affiliate, the best way to get in touch is through numbers: (218) 832-3272 Full Phone Report.
You can also view their clients' testimonials, government compliance and annual reports through their website. Ronald J Shandorf aims to strengthen their B2B relationships through advertisements and brand promotion.
|
{
"redpajama_set_name": "RedPajamaC4"
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| 5,914
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{"url":"https:\/\/math.stackexchange.com\/questions\/3110177\/an-equivalent-condition-for-being-t-1-space-x-mathscr-t-is-normal","text":"# An equivalent condition for being $T_1-$space $(X,\\mathscr T)$ is normal.\n\nA $$T_1-$$space $$(X,\\mathscr T)$$ is normal iff for each closed subset $$C$$ of $$X$$ and each open set $$U$$ such that $$C\\subseteq U$$, there is an open set $$V$$ such that $$C\\subseteq V$$ and $$\\overline{V}\\subseteq U.$$\n\nMy attempt:-\n\nProof. Let $$T_1-$$space $$(X,\\mathscr T)$$ is normal. Let $$C$$ be a closed subset of $$X$$. Let $$U\\in \\mathscr T$$ such that $$C\\subseteq U$$. We know that $$X\\setminus U$$ is a closed subset of $$X$$ disjoint from $$C$$. By the normality, there is disjoint nonempty open sets $$V$$ and $$W$$ such that $$X\\setminus U \\subseteq V$$ and $$C\\subseteq W$$. $$X\\setminus U \\subseteq V \\implies X\\setminus V \\subseteq U.$$ $$W\\subseteq X\\setminus V \\subseteq U.$$ Hence $$\\overline{W}\\subseteq X\\setminus V \\subseteq U$$.\n\nConversely, Suppose for each closed subset $$C$$ of $$T_1$$ space $$(X,\\mathscr T)$$ and each open set $$U$$ such that $$C\\subseteq U$$, there is an open set $$V$$ such that $$C\\subseteq V$$ and $$\\overline{V}\\subseteq U.$$ Consider two closed disjoint subsets of $$X$$. We know that $$X\\setminus C$$ is an open set. Additionally, we know that $$D\\subseteq X\\setminus C$$. Applying the assumption, there is an open set $$V$$ such that $$D\\subseteq V$$ and $$\\overline{V}\\subseteq X\\setminus C$$. So we found the disjoint open sets $$V$$ and $$X\\setminus \\overline{V}$$ such that $$D\\subseteq V$$ and $$C\\subseteq X\\setminus \\overline{V}.$$\n\nIs my attempt true?\n\n\u2022 Yes, your proof is fine, and essentially the same as mine here \u2013\u00a0Henno Brandsma Feb 12 at 15:26\n\u2022 Thank you very much :) \u2013\u00a0Unknown x Feb 12 at 15:28","date":"2019-05-21 15:14:42","metadata":"{\"extraction_info\": {\"found_math\": true, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 0, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 1, \"mathjax_display_tex\": 0, \"mathjax_asciimath\": 0, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 43, \"wp-katex-eq\": 0, \"align\": 0, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.9705930948257446, \"perplexity\": 43.89385857282999}, \"config\": {\"markdown_headings\": true, \"markdown_code\": true, \"boilerplate_config\": {\"ratio_threshold\": 0.18, \"absolute_threshold\": 10, \"end_threshold\": 15, \"enable\": true}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2019-22\/segments\/1558232256426.13\/warc\/CC-MAIN-20190521142548-20190521164548-00434.warc.gz\"}"}
| null | null |
Q: Leaflet R performance issues with large map I'm wondering if anyone else has experienced similar issues when plotting a large number of markers and polygons using leaflet package in R. This is what it normally should look like:
However, when I zoom in/out of the map, the polygons and markers are clearly out of place (or you can say the base map does not adjust properly). An example is included below:
I would not have this issue when I plotted a smaller area or few markers. I'm wondering if there is a way to improve the performance. Many thanks in advance for your help!
A sample of my code is included below:
map1 <- leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = data_merged, group="Default",
fillColor = ~pal(minority_population), color = "orange",
fillOpacity = 0.7,weight = 1, smoothFactor = 0.2, popup = popup) %>%
addMarkers(data = branches_temp, ~long, ~lat,
popup=~name_branch, group="Branch Locations",
icon=icons(iconUrl = "./data/bank_blue_marker.png",iconWidth=20, iconHeight=20))
|
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| 1,915
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Alexander Philip Dawid FRS (prononcé « David » ; né le ) est professeur émérite de statistique à l'Université de Cambridge et membre du Darwin College de Cambridge. Il est l'un des principaux partisans des statistiques bayésiennes.
Biographie
Dawid fait ses études à la City of London School, au Trinity Hall, à Cambridge et au Darwin College, à Cambridge.
Dawid apporte des contributions fondamentales à la fois aux fondements philosophiques et aux applications pratiques des statistiques. Sa théorie de l'indépendance conditionnelle est une clé de voûte de la théorie et des méthodes statistiques modernes, et il démontre son utilité dans une foule d'applications, notamment le calcul dans les systèmes experts probabilistes, l'inférence causale et l'identification médico-légale .
Dawid est chargé de cours en statistiques à l'University College de Londres de 1969 à 1978. Il est ensuite professeur de statistique à la City University de Londres jusqu'en 1981, date à laquelle il retourne à l'UCL en tant que lecteur, y devenant professeur Pearson de statistique en 1982. Il part à l'Université de Cambridge où il est nommé professeur de statistique en 2007, prenant sa retraite en 2013.
Il est élu membre de l'Institut international de statistique en 1978 et statisticien agréé de la Royal Statistical Society en 1993. Il est rédacteur en chef de Biometrika de 1992 à 1996 et président de la Société internationale d'analyse bayésienne en 2000. Il est également membre élu de l'Institut de statistique mathématique et de la Royal Society. Il reçoit le Prix Snedecor en 1977 du Comité des présidents des sociétés statistiques. Dawid reçoit la médaille Guy 1978 en bronze et la médaille Guy 2001 en argent par la Royal Statistical Society.
Son livre Probabilistic Networks and Expert Systems, écrit conjointement avec Robert G. Cowell, Steffen Lauritzen et , reçoit le prix DeGroot 2001 de la Société internationale d'analyse bayésienne.
Références
Liens externes
Statisticien britannique
Étudiant de Darwin College
Étudiant de Trinity Hall (Cambridge)
Professeur à l'University College de Londres
Mathématicien britannique du XXe siècle
Membre de l'Institut international de statistique
Membre de l'Institut de statistique mathématique
Lauréat de la médaille Guy
Naissance en février 1946
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| 2,388
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Watch Pro Bowler Anthony Neuer Pull Off Insane 7-10 Split (Video)
Neuer is just the fourth bowler to ever pull it off on television.
Andi Ortiz | April 12, 2021 @ 6:48 AM
Few things are harder than knocking down the infamous 7-10 split in bowling. But, in the semifinal match of the 2021 U.S. Open, pro bowler Anthony Neuer did it, live on television.
The 18-year-old known as "The Ginger Assassin" — at least by Fox Sports play-by-play announcer Rob Stone — was forced to face the challenging spare in the seventh frame of his third match in the tournament. According to Stone and his cohost, the 7-10 split happened as a result of the ball "breaking loose early" on Neuer's first shot.
For those unfamiliar with bowling, the infamous 7-10 split is when the only two pins left standing in the lane are the two corners of the back row. With two pins typically in between them, the 7 and 10 pins are just far enough apart that most bowlers can hit one or the other, but not necessarily both. And so, pulling off the infamous spare not only gave Neuer the "Spare of the Game" highlight, but also made him just the fourth bowler to ever pull off the shot on television.
Naturally, Stone went wild on the call after Neuer made the shot. "You bet, kid! You bet!" Stone shouted. "Oh man. Give me some oxygen and water!"
Unfortunately, even with the incredible spare, Neuer ended up losing the match to 26-year-old Jakob Butturff, 257-203. You can watch the full moment from the insane shot above.
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Talk about a heart attack
Yesterday, Joel forwarded an email to me that he received at his school email. It was from the district, and it said this:
Important Survey
By now, most of you have become aware of the significant budget cuts across the district. Because of this we are evaluating the possible options to reduce costs. We would like to hear your opinions of the two options that we have come up with. The two possible options are:
1. 10% reduction in force across the district
2. 10% reduction in pay across the district
Please click on the link below and take the time to provide feedback in this survey.
(Link provided)
Name of School District
So, I spent the rest of the day fretting about which would be the better choice. I hate to say 10% reduction in force, because who knows what that means for a music teacher? Besides, isn't it better for everyone to make do with a little less, than for a few people to get axed altogether? Then again, a 10% reduction in pay is kind of a lot. We barely survive on what Joel makes now, and with 10% less, that would be really difficult. What a hard choice! And besides, no matter what we answer on the survey, the district higher-ups would just make whatever decision they thought was best anyway. So why was I giving myself an ulcer worrying about it?
Then we learned that the district sent these emails out as a test to find out how many people would actually respond to a survey you had to click on from the following email address:
hr @ sneaky.nameofdistrict.k12.org
Not nice!
Anyway, they found out that their employees need to more carefully avoid email scams.
Labels: not-so-deep thoughts
Kristina P. Fri Mar 06, 12:08:00 PM
That's a very odd, and sort of mean, way to go about it.
Annette Lyon Fri Mar 06, 12:27:00 PM
I would be sorely tempted to do something nasty in return. Sheesh! They shaved four years off your life with worry!
Heidi Fri Mar 06, 12:32:00 PM
Scary! Even scarier? My husband is a teacher. In California. He works for the state. He's on the short list. We know in about a week whether or not he is still going to have a job (he doesn't have a lot of senority, so . . .)
Keyona Fri Mar 06, 12:49:00 PM
Geez, that was a rude way to go about it. Really scary for some people too.
Jan Fri Mar 06, 12:52:00 PM
You have every right to feel this is wrong. Very rude.
Hilary Fri Mar 06, 01:02:00 PM
That is complete and total crap.
The person who thought of it should be fired, and you can save that money.
Nonna Fri Mar 06, 01:12:00 PM
Who is the knucklehead who wrote that awful letter ? The answer is: his or her job is not in jeparody at all !
If we keep short changing our teachers and in turn our children, we will be in a world of even more trouble than we are now !
A cruel joke to find email scams ??? How many hours of taxpayer money did that cost to think up ?
Kazzy Fri Mar 06, 01:17:00 PM
As a school district employee I can say that was in bad taste. Everyone os already jittery right now. Sheesh.
Fiauna Fri Mar 06, 01:24:00 PM
While that wasn't very nice, you had a great attitude through-out. I do believe that teachers are under-payed.
LisAway Fri Mar 06, 01:33:00 PM
Not nice. Not nice at ALL.
That Girl Fri Mar 06, 01:36:00 PM
Holy un-PC.
I'm guessing they don't have a Human Resources department, because NO ONE WITH ANY HR TRAINING WOULD DO THAT.
I thought.
Randi Fri Mar 06, 01:39:00 PM
That is awful! How would you ever trust communication with them again?
Jenny Fri Mar 06, 02:20:00 PM
Wow that is horrible!! Matt gets to keep his job for now but he has to take every other Friday off with out pay. It feels like a big cut!!
Thank you so much for your comment. I have been struggling with what to do with Emma for quite some time. The first kids is so hard... The second probably is too but it is nice to have help from other mom's. Thank you.
Rebecca Fri Mar 06, 02:36:00 PM
Um... yeah. Not very nice, but definitely a good warning.
Erin Fri Mar 06, 02:57:00 PM
Seriously, that was horrible! Only in a small town. Sheesh.
Oh, and I forgot to tell you that we are leaving this afternoon for Moab, so I won't be coming to your house tonight! Have fun though!
Jake and Stephanie Perrin Fri Mar 06, 03:26:00 PM
Man, thats not even cool.. JERKS!! WElL im glad it was considered a "spoof" and it wasnt real!! Take care
Rach Fri Mar 06, 04:28:00 PM
What a dirty thing to do.
rychelle Fri Mar 06, 05:12:00 PM
that was darn sneaky of them. i can't imagine what an email like would do around here. people are already stressed out of their minds.
have fun in vegas! next time you're here (with more time) we'll have to meet up.
queendeni Fri Mar 06, 05:32:00 PM
Very bad, when everyone is on guard as it is.,
Anne-Marie Fri Mar 06, 06:00:00 PM
I think that was really stupid. I would have taken it serious for sure.
Unknown Fri Mar 06, 08:14:00 PM
OK, I got the scoop.
I talked to someone at the District that knows about this e-mail. It was not sent by any district employees. It was sent from a security group created by the State. The whole point of the e-mail was to get people to get so wrapped up the the email they would give up secure information. Phishing is what it is called. Used to steal identities. This has been going on all over the state.
This security group was able to get many usernames and passwords from district employees and then used those to get complete access to students grades and personal information online. Fortunately this information did not get into the hands of the bad guys, but was turned back over to the district as a learning tool.
Scary part; this could be done by anyone in the world if people follow bad e-mail links.
wendy Fri Mar 06, 09:58:00 PM
That's kind of a mean trick. It is hard to decide those kinds of questions and they don't need to be doing that as a "joke" or to check bad emails.
We have faced that at the court house where I work. we all opted to try and do with less $$ then to see people loose their jobs.
Lara Neves Sat Mar 07, 12:08:00 AM
Tracy: Thanks for clearing that up. The follow up email they sent made it sound like it was all their idea, knowing what you say makes me feel better, although I still think they could have used another avenue since all the teachers are a little nervous right now about what will happen to their jobs next school year.
From My Eyes Sat Mar 07, 10:16:00 AM
I thought it was funny. I know I am sick like that. But then again I did not open the link and type in my password.It was not the only thing they did, and we all failed miserably.
Maddy Sat Mar 07, 11:05:00 AM
That's a sucky thing to do.
Just SO Sat Mar 07, 12:38:00 PM
I don't think that was very nice. Hmmm.
Kate Sun Mar 08, 05:58:00 PM
How frustrating and stressful when everything is so stressful already.
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Manuel Olaizola Urbieta, más conocido por el apodo de Uztapide (* 10 de mayo de 1909 en Zestoa (Guipúzcoa) ; † 8 de junio de 1983 en Oyarzun), fue un versolari (bertsolari, poeta improvisador en lengua vasca) y escritor español. Está considerado uno de los representante más importantes del bertsolarismo tradicional ya que aporto demasiadas cosas durante el siglo XX, una de sus aportaciones más importantes fue Modelo Do Vrisni.
Biografía
Manuel Olaizola nació en 1909 en el caserío Uztapide del barrio de Endoia, un barrio rural situado en Arroa, Zestoa.
El bertsolari sería siempre conocido públicamente por el nombre de su caserío natal. Nacido en un entorno puramente vascohablante, sus padres le enviaron con 13 años al pueblo de Zurbano en las inmediaciones de Vitoria, para que aprendiera a hablar castellano. A partir de los 14 años comenzó a trabajar en numerosos oficios diferentes relacionados con el monte y el caserío (leñador, pastor, carbonero, etc.), hasta que finalmente obtuvo un trabajo estable en la fábrica de cervezas El León de San Sebastián. Se casó siendo ya un hombre maduro en 1952, y se estableció junto con su mujer en el caserío Langanzerrene del barrio de Ergoien en el municipio guipuzcoano de Oyarzun, donde viviría hasta su muerte.
Su figura es homenajeada en la actualidad tanto en Cestona, donde posee una plaza dedicada a su memoria, como en Irún, donde tiene también dedicada una calle.
Bertsolari
Uztapide comenzó en el mundo del bertsolarismo siendo todavía niño, a los seis o siete años, aprendiendo de memoria y recitando bertso paperak (hojas volantes de bertsos escritos). Su debut en una plaza pública se produjo en Lastur, Deva en 1935. Destacó rápidamente, y al año siguiente participó en el II Campeonato Nacional de Bertsolaris, quedando en segundo lugar tras el veterano Txirrita (1936).
La Guerra Civil Española (1936-1939) y la post-guerra fueron un periodo negro para el bertsolarismo, actividad sospechosa de separatismo ante las autoridades franquistas por realizarse en euskera. Durante esos años Uztapide, junto con Basarri, fue uno de los bertsolaris que mantuvo viva esta actividad en las fiestas de los pequeños pueblos rurales del País Vasco.
Cuando esta actividad tuvo un renacimiento en la década de 1960, Uztapide era uno de los bertsolaris punteros de la época. Ganó el campeonato de Guipúzcoa de 1959; en el primer Campeonato Nacional celebrado tras la guerra, en 1960, fue subcampeón por detrás de Basarri y posteriormente Uztapide se hizo con los tres Campeonatos Nacionales siguientes: 1962, 1965 y 1967, siendo hoy en día el segundo bertsolari que más títulos ha obtenido, por detrás de Andoni Egaña.
En 1968 se le tributó un homenaje en San Sebastián, que se convertiría en el Bertsolari Eguna (Día del Bertsolari), celebración que año tras año homenajea a los bertsolaris más significativos.
Su retirada se produjo en 1972, después de que en un festival celebrado en el frontón Atano III de San Sebastián perdiera repentinamente la voz en mitad de una actuación.
La importancia de Uztapide como bertsolari radica, al margen de su calidad como tal, en que sirvió como puente entre la generación de los bertsolaris anteriores a la Guerra Civil (Txirrita) y las nuevas generaciones que revolucionaron este arte como Xabier Amuriza o Sebastián Lizaso, tras finalizar la dictadura franquista.
Escritor
La faceta de Uztapide como escritor en euskera se centró en los últimos años de su vida, después de su retirada como bertsolari en 1972. Con anterioridad había publicado un libro en 1964, Noizbait (Alguna vez), pero era una mera recopilación de las mejores improvisaciones de este bertsolari.
Tras su forzada retirada se dedicó a escribir sus memorias como bertsolari. Escribió dos tomos que aparecieron en 1974 bajo el título Lengo egunak gogoan (Recordando los días pasados). En este libro recoge sus andanzas como bertsolari, recopilando numerosos versos que fue improvisando a lo largo de los años.
Una de sus obras más conocidas es el poema "Empanadillas":
"Cuando era un chico joven
yo comía empanadillas.
Cuando pasaron los años
me invadieron las ladillas
Mi madre siempre me dijo:
Niño no sigas siendo tan sucio
o por ser un tragaldabas
invadirán tu prepucio"
En 1976 publicó otro libro de versos escritos, Sasoia joan da gero, título traducible como "Después de irse el tiempo" o "Al hacerse mayor"; el término sasoia en euskera tiene varias acepciones (tiempo de, momento de, salud, energía).
Tras su muerte, se publicaría en 2001 un tercer libro en dos tomos, recogiendo los versos escritos por Uztapide que no habían sido anteriormente publicados, titulado Uztapide berriz plazara (Uztapide de nuevo a la plaza).
Obra
Colección Auspoa (Vol.42). Noizbait - Tolosa. Auspoa Liburutegia (Colección Auspoa), 1964.
Lengo egunak gogoan (2 tomos) - Tolosa. Auspoa Liburutegia (Colección Auspoa), 1974.
Sasoia joan da gero - Tolosa. Auspoa Liburutegia (Colección Auspoa), 1976.
Sobre Uztapide
Uztapide ha sido protagonista de varias obras de otros autores, dedicadas a recopilar su vida y obra.
Manuel Olaizola "Uztapide"
Olaizola Urbieta, Manuel
Dentro de una colección de biografías de famosos versolaris dirigida al público infantil:
Uztapide. Jesús Mari Etxezarreta - Oyarzun. Sendoa, SA, 1998.
Y dedicadas a un público adulto:
Uztapide gogoan. Manuel Lasarte - Oyarzun. Sendoa SA, 1999.
Nire Uztapide. Pako Aristi - Andoáin. Bertsozaleak Kultur Elkartea, 2000.
Uztapide berriz plazara (2 tomos). Antonio Zavala - Oyarzun. Sendoa, SA, 2001.
Deva
Nacidos en Cestona
Versolaris
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There are basic sales skills that workers are trained with in order to perform their job. A reliable company can help a corporation be able to focus on the skills and techniques that will help them properly promote their products. The skilled workers at SELLect Sales Development will work with a company to help them determine the right training methods that will increase their workers' confidence and teach them how to communicate better with their clients.
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Conflct of interests. The author declares no conflict of interest.
Significance. Care delivery to children with orphan diseases and their parents calls for improvement with due regard to regional peculiarities.
The capital's model of care delivery to children with orphan diseases has won the Prize of the Moscow Government; however, head pediatric external experts of the Moscow Healthcare Department are focused on its continuous improvement to increase rehabilitation potential of families with children with orphan diseases, develop an effective system of continuous professional education of primary care pediatricians, coordinate activities of head pediatric external experts, and organize information space to ensure access to quality health care.
The purpose of the study was to analyze opinions of head pediatric external experts of the Moscow Healthcare Department about care improvement to children with orphan diseases and their parents.
Materials and methods. The study base: Reference center of inborn hereditary and genetic disorders, orphan and other rare diseases of the Morozov children's clinical hospital of the Moscow Healthcare Department. The study was conducted using specially designed questionnaire that included 20 questions.
The expert review criteria included quality indicators evaluated by a five-score scale, rating of responses, and concordance method with calculation of the Kendall's coefficient (W).
Results. The study showed the following innovative directions: development of personified rehabilitation system for children with orphan diseases; need for a new information format for training pediatricians and primary care physicians as well as educating patients and their parents; development of monitoring criteria and implementation of continuous analysis of monitoring results as an integral part of the head external experts work; input of additional information about the child and the family into the regional segment of the Federal register of patients with orphan diseases to improve quality of medical care; and development of an electronic platform for translational medicine and telemedical counselling.
Keywords: children; orphan diseases; patients' experience; head external experts.
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Lomakina O.L. Obshcherossiyskiy registr patsientov s sistemnym yuvenil'nym idiopaticheskim artritom - effektivnyy instrument monitoringa zabolevaniya i meditsinskoy pomoshchi [All-Russian register of patients with systematic juvenile idiopathic arthritis is an efficient tool for monitoring diseases and medical care]. Cand. Med. Sci [thesis]. Мoscow 2017. 24 p. (In Russian).
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Modestov A.A., Kosova S.A., Aminova Z.M., Shevchenko V.V. Formirovanie sotsial'no-bytovykh navykov u detey-invalidov, prozhivayushchikh v sem'yakh. Metodicheskie rekomendatsii [Formation of social and domestic skills in disabled children living in families. Guidelines]. Abakan: Hak. kn. izd-vo; 2007. 52 p. (In Russian).
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Ob utverzhdenii Pravil vedeniya Federal'nogo registra lits, bol'nykh gemofiliey, mukovistsidozom, gipofizarnym nanizmom, bolezn'yu Goshe, zlokachestvennymi novoobrazovaniyami limfoidnoy, krovetvornoy i rodstvennykh im tkaney, rasseyannym sklerozom, lits posle transplantatsii organov i (ili) tkaney [On the approval of the Rules of the Federal register for the persons with hemophilia, cystic fibrosis, pituitary dwarfism, Gaucher disease, malignant neoplasm of lymphoid, hematopoietic and related tissues, multiple sclerosis, and person after organ and (or) tissue transplantation]. Postanovlenie Pravitel'stva Rossiyskoy Federatsii ot 26 aprelya 2012 g. №404. [cited 2018 Apr 26]. Available from: http://base.garant.ru/70168890/. (In Russian).
O formakh dokumentov dlya vedeniya regional'nogo segmenta Federal'nogo registra lits, stradayushchikh zhizneugrozhayushchimi i khronicheskimi progressiruyushchimi redkimi (orfannymi) zabolevaniyami, privodyashchimi k sokrashcheniyu prodolzhitel'nosti zhizni grazhdan ili ikh invalidnosti, i poryadke ikh predstavleniya [On the forms of documents to conduct the regional segment of the Federal register of the persons suffering from life-threatening and chronic progressive rare (orphan) diseases leading to a reduction in life expectancy and disability, and the order of their presentation]. Prikaz MZ RF ot 19 noyabrya 2012 g. №950n [Online] [cited 2018 May 14]. Available from: http://base.garant.ru/70269284/ (In Russian).
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Ob organizatsii referens-tsentra vrozhdennykh nasledstvennykh zabolevaniy, geneticheskikh otkloneniy, orfannykh i drugikh redkikh zabolevaniy [On the organization of a reference center for congenital hereditary diseases, genetic abnormalities, orphan and other rare diseases]. Prikaz Departamenta zdravookhraneniya Moskvy ot 02.06.2015 g. № 461 [Online]. [cited 2018 Apr 26]. Available from: http://mosgorzdrav.ru/ru-RU/document/default/search.html?phrase=461&interval=&group_id=0. (In Russian).
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Ob osnovakh okhrany zdorov'ya grazhdan v Rossiyskoy Federatsii (s izmeneniyami i dopolneniyami) [On the basis of population health protection (amended and supplemented). Federal'nyy zakon ot 21 noyabrya 2011 g. №323-FZ. [Online] [cited 2018 May 16]. Available from: http://base.garant.ru/12191967/#ixzz4hQn3fgrK. (In Russian).
Yakh"yaeva G.T. Nauchnoe obosnovanie novykh podkhodov k diagnostike i lecheniyu nesovershennogo osteogeneza u detey [Scientific ground for new approaches to diagnosis and treatment of imperfect osteogenesis in children]. Cand. Med. Sci [thesis]. Мoscow. 2016. 24 p. (In Russian).
Bleich S., Murray C. Kakaya svyaz' sushchestvuet mezhdu udovletvorennost'yu sistemoy mediko-sanitarnoy pomoshchi i lichnym opytom patsientа? [What is the relation between patient's satisfaction with health care system and patient's personal experience?]. Byulleten' VOZ 2009; 87 (4):245-324. (In Russian).
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{
"redpajama_set_name": "RedPajamaC4"
}
| 8,003
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Q: Try clicking een element after the error: element not visible I use the code below to click on an element. However, it returns the error: element not visible. When i use a wait of a few seconds, the click works. is there a way i can send the click again after the error is thrown? Like a loop?
$searchBtnIris2 = $driver.FindElementByXPath('//*[@id="menuFormHome:j_id44_body"]/ul[3]/li[1]/a')
Write-Host "Den ID van de zoekknop is $seachBtnIris2"
$searchBtnIris2.Click();
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{
"redpajama_set_name": "RedPajamaStackExchange"
}
| 7,499
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<?php
// This file is part of Moodle - http://moodle.org/
//
// Moodle is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// Moodle is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with Moodle. If not, see <http://www.gnu.org/licenses/>.
defined('MOODLE_INTERNAL') || die();
$string['activities'] = 'Дейности';
$string['addcategory'] = 'Добавяне на категория';
$string['addfeedback'] = 'Добавяне на обратна връзка';
$string['addidnumbers'] = 'Добавяне на идентификационни номера';
$string['additem'] = 'Добавяне единица за оценяване';
$string['addscale'] = 'Добавяне на скала';
$string['aggregateextracreditmean'] = 'Средна оценка (с допълнителни кредити)';
$string['aggregatemax'] = 'Най-висока оценка';
$string['aggregatemean'] = 'Средна оценка';
$string['aggregatemedian'] = 'Медиана на оценките';
$string['aggregatemin'] = 'Най-ниска оценка';
$string['aggregatemode'] = 'Мода на оценките';
$string['aggregateonlygraded'] = 'Обобщаване само на непразните оценки';
$string['aggregateonlygraded_help'] = 'Празната оценка е оценка, която липсва в книгата за оценки. Тя може да произтича от отговор на задание, който още не е оценен или от тест, който още не е опитан за бъде изпълнен.
Тази настройка определя дали празните оценки не се включват в обобщаването или участват като минимални оценки, например със стойност 0 за оценки, които могат да бъдат от 0 до 100.';
$string['aggregateoutcomes'] = 'Включване на качества в обобщаването';
$string['aggregateoutcomes_help'] = 'Ако се разреши в обобщаването ще се включат и качествата. Това може да предизвика неочаквани крайни резултати.';
$string['aggregatesubcats'] = 'Включване и на подкатегориите при обобщаване';
$string['aggregatesubcats_help'] = 'Тази настройка определя дали оценките от подкатегориите се включват в обобщаването.';
$string['aggregatesum'] = 'Сума на оценките';
$string['aggregateweightedmean'] = 'Претеглена средна оценка';
$string['aggregateweightedmean2'] = 'Проста претеглена средна оценка';
$string['aggregation'] = 'Обобщаване';
$string['aggregationcoef'] = 'Коефициент за обобщаване';
$string['aggregationcoefextra'] = 'Допълнителен кредит';
$string['aggregationcoefextra_help'] = 'Ако начинът на обобщаване е "Сума от оценките" или "Проста претеглена средна оценка" и отметката "Допълнителен кредит" е сложена, максималната оценка на единицата не се прибавя към максималната оценка за категорията, което дава възможност за достигане на максимална оценка (или оценка над максималната, ако е разрешено от администратора на сайта) в категорията без максимални оценки за всички единици.
Ако обобщаването е "Средна оценка (с допълнителни кредити)" и допълнителният кредит е зададен по-голям от нула, допълнителният кредит е стойност, с която оценката се умножава преди прибавянето и в сумата за пресмятане на средна стойност.';
$string['aggregationcoefextrasum'] = 'Допълнителен кредит';
$string['aggregationcoefextrasum_help'] = 'Ако тази отметка за допълнителен кредит е поставена, максималната оценка за единицата не се добавя към максималната оценка на категорията, давайки възможност за получаване на максимална оценка (или по-голяма от максималната, ако е позволено от администратор на сайта) в категорията без максимални оценки за всяка оценявана единица.';
$string['aggregationcoefextraweight'] = 'Тегло на допълнителния кредит';
$string['aggregationcoefextraweight_help'] = 'Ако на теглото на допълнителния кредит е зададена по-голяма от нула стойност, оценката действа като допълнителен кредит при обобщаване. С тази стойност се умножава оценката преди да бъде сумирана при пресмятане на средна стойност.';
$string['aggregation_help'] = 'Обобщаването определя как се комбинират оценките от дадена категория, като:
* Средна оценка - Сумата на всички оценки, разделена на броя им
* Медиана на оценките - След като оценките се подредят по нарастване - оценката, която попада в средата на списъка
* Най-ниска оценка
* Най-висока оценка
* Мода на оценките - Оценката, която се повтаря най-много пъти
* Сума на оценките - Сума от стойностите на всички оценки, независимо от скалите им';
$string['aggregationposition'] = 'Позиция на обобщената';
$string['aggregationposition_help'] = 'Тази настройка определя дали колоната с обобщената оценка от категория или курс се показва първа или последна в отчетите от книгата с оценки.';
$string['aggregationsvisible'] = 'Достъпни видове обобщаване';
$string['aggregationsvisiblehelp'] = 'Изберете всички видове обобщаване, които трябва да са достъпни. Задръжте натиснат клавиш Ctrl, за да изберете повече от един.';
$string['allstudents'] = 'Всички ученици';
$string['allusers'] = 'Всички потребители';
$string['availableidnumbers'] = 'Налични идентификационни (ID Numbers) номера';
$string['average'] = 'Средно';
$string['averagesdecimalpoints'] = 'Десетични знаци в колоната на средните';
$string['averagesdecimalpoints_help'] = 'Тази настройка определя броя на знаците след десетичната запетая при показване на средната стойност, или да се използва зададеният брой за категорията или оценяваната единица (Наследен).';
$string['averagesdisplaytype'] = 'Вид показване в колоната на средните';
$string['averagesdisplaytype_help'] = 'Тази настройка определя дали средната оценка се показва като реална, в проценти или с букви, или по начина, определен за категорията или единицата за оценяване (Наследен).';
$string['badlyformattedscale'] = 'Моля, въведете списък от разделени със запетаи стойности (поне две стойности се изискват).';
$string['categories'] = 'Категории';
$string['categoriesanditems'] = 'Категории и единици';
$string['categoriesedit'] = 'Редактиране на категории и единици';
$string['category'] = 'Категория';
$string['categoryedit'] = 'Редактиране на категория';
$string['categoryname'] = 'Име на категория';
$string['categorytotal'] = 'Обобщена за категорията';
$string['categorytotalname'] = 'Име на обобщената оценка на категорията';
$string['changedefaults'] = 'Промяна на зададеното по подразбиране';
$string['changereportdefaults'] = 'Промяна на зададеното по подразбиране за отчета';
$string['choosecategory'] = 'Избор на категория';
$string['combo'] = 'Раздели и Падащо меню';
$string['courseavg'] = 'Средно за курса';
$string['coursegradesettings'] = 'Настройки на оценките в курса';
$string['coursename'] = 'Име на курса';
$string['coursescales'] = 'Скали на курса';
$string['coursesettings'] = 'Настройки на курса';
$string['coursesettingsexplanation'] = 'Настройките за курса определят как всички участници в курса виждат дневника с оценките.';
$string['coursetotal'] = 'Обща за курс';
$string['createcategory'] = 'Създаване на категория';
$string['csv'] = 'CSV';
$string['decimalpoints'] = 'Общо знаци след десетичната запетая';
$string['decimalpoints_help'] = 'Тази настройка определя с колко знаци след десетичната запетая се показват оценките. Това не оказва влияние върху точността на изчисляване, която е 5 знака след десетичната запетая.';
$string['default'] = 'По подразбиране';
$string['defaultprev'] = 'По подразбиране ({$a})';
$string['deletecategory'] = 'Изтриване на категория';
$string['dropdown'] = 'Падащо меню';
$string['droplow'] = 'Отхвърляне най-ниските';
$string['droplow_help'] = 'Тази настройка позволява, посочения брой най-ниски оценки да се изключи от agregation.';
$string['edit'] = 'Редактиране';
$string['editcalculation'] = 'Редактиране на калкулация';
$string['editcalculationverbose'] = 'Редактиране на пресмятането за {$a->category} {$a->itemmodule} {$a->itemname}';
$string['editfeedback'] = 'Редактиране на забележка';
$string['editgrade'] = 'Редактиране на оценка';
$string['editgradeletters'] = 'Редакция на буквите за оценка';
$string['editoutcome'] = 'Редактиране на качество';
$string['editoutcomes'] = 'Редактиране на качества';
$string['editscale'] = 'Редактиране на скала';
$string['edittree'] = 'Категории и единици';
$string['editverbose'] = 'Редактиране на {$a->category} {$a->itemmodule} {$a->itemname}';
$string['enableajax'] = 'Разрешаване на AJAX';
$string['enableajax_help'] = 'Добавя AJAX функционалност на отчетите с оценки, опростявайки и ускорявайки обичайните действия. Зависи от това дали браузърът на потребителя изпълнява Javascript.';
$string['enableoutcomes'] = 'Разрешаване на качества';
$string['enableoutcomes_help'] = 'Поддържане на Качества (също така известни като: Компетенции, Цели, Стандарти, или Критерии) означава, че ще може нещата да се оценяват чрез една или повече скали, които са обвързани с качества. Позволяването на качества прави възможно използването на такова специално оценяване на сайта.';
$string['encoding'] = 'Кодова таблица';
$string['errorupdatinggradecategoryaggregateoutcomes'] = 'Грешка при обновяване на настройката "Включване на качества в обобщаването" на категория оценки номер (ID) {$a->id}';
$string['export'] = 'Експортиране';
$string['exportalloutcomes'] = 'Експортиране на всички качества';
$string['exportfeedback'] = 'Включване на обратната връзка в експортирането';
$string['exportto'] = 'Експортиране към';
$string['feedback'] = 'Съобщение';
$string['finalgrade'] = 'Крайна оценка';
$string['fixedstudents'] = 'Неподвижни колони на студентите';
$string['fixedstudents_help'] = 'Позволява оценките да се превъртат хоризонтално, а колоните на студентите да остават неподвижни и да се виждат на екрана.';
$string['fullmode'] = 'Пълно показване';
$string['fullview'] = 'Пълно показване';
$string['generalsettings'] = 'Общи настройки';
$string['grade'] = 'Оценка';
$string['gradeadministration'] = 'Администриране на оценки';
$string['gradebook'] = 'Книга за оценки';
$string['gradecategory'] = 'Категория на оценката';
$string['gradecategoryonmodform'] = 'Категория на оценката';
$string['gradecategoryonmodform_help'] = 'Тази настройка определя в коя категория в книгата за оценки ще се покаже оценката от дейността.';
$string['gradecategorysettings'] = 'Настройки на категорията на оценката';
$string['gradedisplaytype'] = 'Тип на показваната стойност';
$string['gradedisplaytype_help'] = 'Тази настройка определя как се показват оценките в отчетите за оценяващите и за потребителите.
* Реална - Фактическата стойност на оценката
* В проценти
* С букви - За обозначаване на интервала, в който попада оценката, се използва буква или дума';
$string['gradeexport'] = 'Експортиране на оценки';
$string['gradeexportdecimalpoints'] = 'Десетични знаци на експортираните оценки';
$string['gradeexportdecimalpoints_desc'] = 'Брой на десетичните знаци, които да се показват в експортираните оценки. Могат да се зададат отново при самия експорт.';
$string['gradeexportdisplaytype'] = 'Тип на показване на оценките при експортиране';
$string['gradeexportdisplaytype_desc'] = 'При експортиране оценките могат да се показват като дробни числа, проценти (спрямо минималната и максимална оценки) или с букви (А, Б, В и т.н.). Това може да се избере отново при самия експорт.';
$string['gradehistorylifetime_help'] = 'Това определя колко време Вие искате да пазите историята на промените в таблиците с оценки. Препоръчва се да се пази история колкото е възможно по-дълго. Ако възникнат проблеми с производителността или има ограничение за обема на базата данни, опитайте да зададете по-малка стойност.';
$string['gradeitem'] = 'Оценка за';
$string['gradeitemadvanced'] = 'Настройки за разширено показване';
$string['gradeitemadvanced_help'] = 'Изберете елементите, които трябва да излизат при "Разширено показване" при редактиране оценката за дадена единица.';
$string['gradeitemislocked'] = 'Тази дейност е заключена в дневника за оценки. Промените в оценките, които са направени в тази дейност, няма да се копират в дневника, докато не бъде отключена.';
$string['gradeitemlocked'] = 'Оценяването е заключено';
$string['gradeitemsettings'] = 'Настройки за оценъчната единица';
$string['gradeitemsinc'] = 'Да се включат оценките за единиците';
$string['gradeletter'] = 'Букви за оценяване';
$string['gradeletter_help'] = 'Буквите за оценка са латински букви, A, B, C ..., или думи, например Отличен, Мн. добър, Добър, ..., използвани да представят диапазона на оценките.';
$string['gradeletters'] = 'Букви за оценяване';
$string['gradelocked'] = 'Оценката е заключена';
$string['grademax'] = 'Максимална оценка';
$string['grademax_help'] = 'Тази настройка определя максималната оценка, когато се използва оценка тип стойност. Максималната оценка за конкретна дейност се задава на страницата с настройките на дейността.';
$string['grademin'] = 'Минимална оценка';
$string['grademin_help'] = 'Тази настройка определя минималната оценка, когато се използва оценка тип стойност.';
$string['gradeoutcomes'] = 'Качества';
$string['gradeoutcomescourses'] = 'Курсови качества';
$string['gradepass'] = 'Оценка за преминаване';
$string['gradepass_help'] = 'Настройката определя минималната оценка за преминаване. Стойността се използва в дейностите и напредването в курса, и в дневника с оценките, където оценките за преминаване се оцветяват в зелено, а оценките, с които не се преминава напред - в червено.';
$string['gradepreferences'] = 'Предпочитания за оценките';
$string['gradepublishing'] = 'Позволяване на публикуване';
$string['gradepublishing_help'] = 'Позволяване на публикуване при експортиране и импортиране. Експортираните оценки ще могат да се видят чрез отваряне на URL, без необходимост от влизане в Moodle сайт. Оценки ще могат също да се импортират от такъв URL (което означава, че един Moodle сайт може да импортира оценки публикувани от друг Moodle сайт). По подразбиране само администраторите могат да използват тази възможност. Моля, обучете потребителите преди да дадете това право на други роли (опасност при размяна на отметки и ускорители за теглене на файлове, ограничения по IP и др.)';
$string['gradereport'] = 'Отчет на оценките';
$string['graderreport'] = 'Отчет за оценяващ';
$string['grades'] = 'Оценки';
$string['gradesforuser'] = 'Оценки на {$a->user}';
$string['gradesonly'] = 'Само оценки';
$string['gradessettings'] = 'Настройки на оценките';
$string['gradetype'] = 'Тип оценка';
$string['gradetype_help'] = 'Има 4 типа оценки:
* Без оценка - Не е възможна оценка
* Стойност - Числова стойност с минимум и максимум
* Скала - Оценка от зададен списък оценки
* Текст - Само забележка
Само оценките от тип стойност и скала се обобщават. Типът на оценката за конкретна дейност се задава в страницата за настройки на дейността.';
$string['hidden'] = 'Скрити';
$string['hiddenasdate'] = 'Показване дата на предаване за скритите оценки';
$string['hiddenasdate_help'] = 'Ако потребителят не може да вижда скритите оценки, да се показва датата на предаване вместо "-".';
$string['hidden_help'] = 'Ако е сложена тази отметка, оценките се скриват от студентите. Ако е желателно може да се зададе дата за "Скрити до", за да се покажат оценките след като оценяването приключи.';
$string['hiddenuntil'] = 'Скрити до';
$string['hiddenuntildate'] = 'Скрити до: {$a}';
$string['hideadvanced'] = 'Скриване на разширените възможности';
$string['hideforcedsettings'] = 'Скриване на принудителните настройки';
$string['hideforcedsettings_help'] = 'Да не се показват принудителните настройки в потребителския интерфейс за оценките.';
$string['hidegroups'] = 'Скриване на групи';
$string['hidenooutcomes'] = 'Показване на качества';
$string['hidetotalifhiddenitems'] = 'Скриване на обощените ако съдържат скрити единици';
$string['hidetotalifhiddenitems_help'] = 'Тази настройка определя дали обобщените оценки, които съдържат оценки за скрити единици, се показват на студентите или се заместват с тире (-). Ако се показват, обобщените оценки се изчисляват с изключване или с включване на оценките от скрити единици.
Ако скритите единици се изключват, обобщената оценка е различна от тази, която вижда преподавателя в отчета, защото той винаги вижда обобщена оценка изчислена от всички единици, скрити или не. Ако скритите оценки се включват, студентите биха могли да пресметнат скритите единици.';
$string['hidetotalshowexhiddenitems'] = 'Показване на обобщените с изключени скрити';
$string['hidetotalshowinchiddenitems'] = 'Показване на обобщените с включени скрити';
$string['hideverbose'] = 'Скриване на {$a->category} {$a->itemmodule} {$a->itemname}';
$string['import'] = 'Импортиране';
$string['importcsv'] = 'Импортиране на CSV';
$string['importcustom'] = 'Импортиране като частни качества (само за този курс)';
$string['importfailed'] = 'Неуспешно импортиране';
$string['importfeedback'] = 'Импортиране на обратна връзка';
$string['importfile'] = 'Импортиране на файл';
$string['importfrom'] = 'Импортиране от';
$string['importoutcomes'] = 'Импортиране на качества';
$string['importoutcomes_help'] = 'Качества могат да се импортират от csv файл с формат като на файл за експортиране на качества в csv файл.';
$string['importpreview'] = 'Преглед на импортирането';
$string['importsettings'] = 'Импортиране на настройки';
$string['importskippedoutcome'] = 'Качество с кратко име "{$a}" вече съществува в този контекст, това от импортирания файл беше прескочено.';
$string['importstandard'] = 'Импортиране като стандартни качества';
$string['importxml'] = 'Импортиране на XML';
$string['includescalesinaggregation'] = 'Включване на скалите при обобщаването';
$string['includescalesinaggregation_help'] = 'Можете да определите дали скалите да се включват като числа във всички обобщени оценки, във всички дневници с оценки, във всички курсове. ВНИМАНИЕ: промяната на тази настройка, ще накара всички обобщени оценки да се преизчислят.';
$string['inherit'] = 'Наследен';
$string['iteminfo'] = 'Информация за единицата';
$string['iteminfo_help'] = 'Тази настройка предоставя място за въвеждане на информация относно единицата. Тази информация не се показва никъде другаде.';
$string['itemname'] = 'Име на единица';
$string['itemsedit'] = 'Редактиране на единицата за оценяване';
$string['keephigh'] = 'Пазене на най-високите';
$string['keephigh_help'] = 'Ако е зададена, тази настройка определя да се пазят най-високите Х оценки, където Х е зададена тук стойност.';
$string['letter'] = 'Буква';
$string['letterpercentage'] = 'Буква (проценти)';
$string['letterreal'] = 'Буква (реални)';
$string['letters'] = 'Букви';
$string['linktoactivity'] = 'Връзка към дейност "{$a->name}"';
$string['lock'] = 'Заключване';
$string['locked'] = 'Заключени';
$string['locked_help'] = 'Ако е сложена тази отметка, оценките не могат повече да се актуализират автоматично от съответната дейност.';
$string['locktime'] = 'Заключени след';
$string['locktimedate'] = 'Заключени след: {$a}';
$string['lockverbose'] = 'Заключване на {$a->category} {$a->itemmodule} {$a->itemname}';
$string['max'] = 'Максимална';
$string['maxgrade'] = 'Максимална оценка';
$string['meanall'] = 'Всички оценки';
$string['meangraded'] = 'Непразните оценки';
$string['meanselection'] = 'Оценки, включени в средните по колони';
$string['meanselection_help'] = 'Тази настройка означава дали клетките с липсващи оценки трябва да се включат при изчисляване на средните за всяка категория или оценявана единица.';
$string['min'] = 'Най-ниска';
$string['multfactor'] = 'Множител';
$string['multfactor_help'] = 'Множителят е число, с което се умножава всяка оценка за дадената единица, до максимална стойност на максималната оценка. Например, ако множителят е 2 и максималната стойност е 100, тогава всички оценки под 50 се умножават по 2, а всички оценки над 50 се променят на 100.';
$string['mypreferences'] = 'Моите предпочитания';
$string['myreportpreferences'] = 'Мои предпочитания';
$string['navmethod'] = 'Метод за навигация';
$string['newcategory'] = 'Нова категория';
$string['nocourses'] = 'Все още няма курсове';
$string['nogradeletters'] = 'Не са зададени букви за оценяване';
$string['nonunlockableverbose'] = 'Тази оценка не може да бъде отключена преди {$a->itemname} да бъде отключена.';
$string['nopublish'] = 'Не се публикуват';
$string['noscales'] = 'Качествата трябва да бъдат свързани със скала от курса или с глобална скала, но тук не са. Искате ли да добавите скала?';
$string['numberofgrades'] = 'Брой на оценките';
$string['options'] = 'Настройки';
$string['outcomecreate'] = 'Добавяне на ново качество';
$string['outcomefullname'] = 'Пълно наименование';
$string['outcomeitemsedit'] = 'Редактиране на единицата за качество';
$string['outcomes'] = 'Качества';
$string['outcomescourse'] = 'Качества, използвани в курс';
$string['outcomescustom'] = 'Частни качества';
$string['outcomeshortname'] = 'Кратко име';
$string['outcomesstandard'] = 'Стандартни качества';
$string['outcomesstandardavailable'] = 'Налични стандартни качества';
$string['outcomestandard'] = 'Стандартно качество';
$string['outcomestandard_help'] = 'Стандартното качество е достъпно на целия сайт, във всички курсове.';
$string['overallaverage'] = 'Обща средна';
$string['overridden_help'] = 'Ако отметката е сложена, оценката няма да може повече да се променя в рамките на съответната дейност.
Когато една оценка се редактира в отчета с оценките, тази отметка се поставя автоматично. Въпреки това тя може да се премахне за да може оценката да се актуализира чрез съответната дейност.';
$string['parentcategory'] = 'Родителска категория';
$string['percentage'] = 'Проценти';
$string['percentageletter'] = 'Проценти (буква)';
$string['percentagereal'] = 'Проценти (реални)';
$string['plusfactor'] = 'Отместване';
$string['plusfactor_help'] = 'Отместването е число, което се прибавя към всяка оценка за дадена единица, след прилагането на множител.';
$string['points'] = 'точки';
$string['positionfirst'] = 'Първа';
$string['positionlast'] = 'Последна';
$string['preferences'] = 'Предпочитания';
$string['prefgeneral'] = 'Общи настройки';
$string['prefletters'] = 'Букви за оценяване и граници';
$string['prefrows'] = 'Специални редове';
$string['prefshow'] = 'Превключване на видимостта';
$string['previewrows'] = 'Преглеждан брой редове';
$string['profilereport'] = 'Отчет в профила';
$string['profilereport_help'] = 'Отчет за оценките, използван на страницата с профила на потребителя.';
$string['quickfeedback'] = 'Бързи забележки';
$string['quickgrading'] = 'Бързо оценяване';
$string['quickgrading_help'] = 'Ако е разрешено, когато редактирането е включено, на мястото на всяка оценка се показва малко поле за въвеждане и това позволява бързо да се напишат много оценки. Промените се запазват след щракване на бутона за запазване.
Забележете, че когато се редактира една оценка в таблица с оценки, се вдига флаг, който означава, че тази оценка не може да се промени повече в рамките на заданието.';
$string['range'] = 'Диапазон';
$string['rangedecimals'] = 'Десетични знаци на диапазоните';
$string['rangedecimals_help'] = 'Брой на десетичните знаци след запетаята за показване на диапазон.';
$string['rangesdecimalpoints'] = 'Десетични знаци в диапазоните';
$string['rangesdecimalpoints_help'] = 'Тази настройка определя броя на знаците след десетичната запетая при показване на диапазоните, или да се използва зададеният брой за категорията или оценяваната единица (Наследен).';
$string['rangesdisplaytype'] = 'Вид показване на диапазоните';
$string['rangesdisplaytype_help'] = 'Тази настройка определя дали диапазоните се показва като реални, в проценти или с букви, или по начина, определен за категорията или единицата за оценяване (Наследен).';
$string['real'] = 'Реална';
$string['realletter'] = 'Реално (букви)';
$string['realpercentage'] = 'Реално (проценти)';
$string['removeallcoursegrades'] = 'Изтрий всички оценки';
$string['removeallcourseitems'] = 'Изтриване на всички записи и категории';
$string['report'] = 'Отчет';
$string['reportdefault'] = 'По подразбиране за отчета ({$a})';
$string['reportsettings'] = 'Настройки на отчета';
$string['rowpreviewnum'] = 'Преглеждан брой редове';
$string['savechanges'] = 'Запис на промените';
$string['savepreferences'] = 'Запазване на предпочитанията';
$string['scaleconfirmdelete'] = 'Сигурни ли сте, че искате да изтриете скалата "{$a}"?';
$string['seeallcoursegrades'] = 'Виждане на всички оценки в курса';
$string['selectalloroneuser'] = 'Изберете всички или един потребител';
$string['selectauser'] = 'Изберете потребител';
$string['separator'] = 'Разделител';
$string['sepcomma'] = 'Запетая';
$string['septab'] = 'Табулатор';
$string['setgradeletters'] = 'Задай букви за оценяване';
$string['setpreferences'] = 'Запазване на предпочитанията';
$string['settings'] = 'Настройки';
$string['showactivityicons'] = 'Показване икони на дейностите';
$string['showactivityicons_help'] = 'Ако е зададено, до имената на дейностите се показват и икони.';
$string['showallhidden'] = 'Показване на скритите';
$string['showallstudents'] = 'Показване на всички ученици';
$string['showanalysisicon'] = 'Икона за анализ на оценката';
$string['showanalysisicon_desc'] = 'Дали по подразбиране да се показва икона за анализ на оценката. Ако модулът за дейността поддържа това, щракването върху иконата за анализ на оценката отваря страница с подробности, обясняващи как е получена оценката.';
$string['showanalysisicon_help'] = 'Ако модулът за дейността поддържа това, щракването върху иконата за анализ на оценката отваря страница с подробности, обясняващи как е получена оценката.';
$string['showaverage'] = 'Показване на средна';
$string['showaverage_help'] = 'Да се покаже ли колона за средна? Студентите биха могли да изчислят оценките на другите студенти ако средната стойност се изчислява от малък брой оценки. Поради съображения за производителност средната стойност се пресмята приблизително ако зависи от скрити единици.';
$string['showaverages'] = 'Показване на средни по колони';
$string['showaverages_help'] = 'Ако се включи, отчета на оценките ще съдържа допълнителен ред, показващ средната оценка за всяка категория и оценявана единица.';
$string['showcalculations'] = 'Показване на изчисленията';
$string['showcalculations_help'] = 'Ако е зададено, когато е включено редактирането, се показва иконка за всяка оценявана единица и категория, и подсказващ надпис при задържане на курсора над пресметнатите единици, и индикатор, че колоната е изчислена.';
$string['showeyecons'] = 'Икони показване/скриване';
$string['showeyecons_help'] = 'Ако е зададено, когато редактирането е включено, се показва икона "показване/скриване" за всяка оценка, с която се управлява дали студентът вижда или не тази оценка.';
$string['showfeedback'] = 'Показване на забележките';
$string['showfeedback_help'] = 'Да се покаже ли колоната със забележки?';
$string['showgrade'] = 'Показване на оценките';
$string['showgrade_help'] = 'Да се покаже ли колоната с оценки?';
$string['showgroups'] = 'Показване на групи';
$string['showhiddenitems'] = 'Показване на скритите единици';
$string['showhiddenitems_help'] = 'Дали скритите единици за оценяване са напълно скрити или имената на скритите единици са видими за студентите.
* Показване на скритите - Имената на критите единици за оценяване се виждат но оценките на студентите са скрити
* Само скрити до - Единиците за оценяване с настройка "Скрита до" са скрити до зададената дата, след което са напълно видими
* Да не се показват - Скритите единици за оценяване са напълно скрити';
$string['showhiddenuntilonly'] = 'Само скрити до';
$string['showlettergrade'] = 'Показване на буквените оценки';
$string['showlettergrade_help'] = 'Да се показва ли колона за буквени оценки?';
$string['showlocks'] = 'Икони "заключване/отключване"';
$string['showlocks_help'] = 'Ако е зададено, когато е включено редактирането, за всяка оценка се показва икона "заключване/отключване", която определя дали оценката може автоматично да се актуализира от съответната дейност.';
$string['shownohidden'] = 'Да не се показват';
$string['shownooutcomes'] = 'Скриване на качества';
$string['shownumberofgrades'] = 'Показване на броя в средните оценки';
$string['shownumberofgrades_help'] = 'Ако е зададено, броят на оценките, използвани при изчисляване на средните се показва в скоби след всяка средна оценка.';
$string['showpercentage'] = 'Показване процента на такива оценки';
$string['showpercentage_help'] = 'Да се показва ли оценката в проценти за всяка единица?';
$string['showquickfeedback'] = 'Показване на бързи забележки';
$string['showquickfeedback_help'] = 'Ако е включено, когато е включено редактиране, се показва поле за писане срещу всяка оценка, позволявайки забележките за много оценки да бъдат редактирани едновременно. Промените се запазват и оцветяват, когато бъде щракнат бутона за актуализиране.
Обърнете внимание, че забележките се редактират в отчета с оценките, и се вдига флаг, който означава, че забележките не могат повече да се променят в рамките на дейността.';
$string['showrange'] = 'Показване на диапазоните';
$string['showrange_help'] = 'Да се показва ли колона за диапазони?';
$string['showranges'] = 'Показване на диапазоните';
$string['showranges_help'] = 'Ако е включено, отчета на оценките ще съдържа допълнителен ред, показващ диапазона от оценки за всяка категория или единица.';
$string['showrank'] = 'Показване на класация';
$string['showrank_help'] = 'Да се показва ли мястото на студента между останалите студенти по всяка оценка?';
$string['showuserimage'] = 'Показване снимките на потребителите';
$string['showuserimage_help'] = 'Дали да се показват снимките на потребителите до техните имена в отчета с оценките.';
$string['showweight'] = 'Показване на теглата';
$string['showweight_help'] = 'Да се покаже ли колоната с теглата?';
$string['simpleview'] = 'Опростено показване';
$string['sitewide'] = 'За целия сайт';
$string['sortbyfirstname'] = 'Сортиране по име';
$string['stats'] = 'Статистики';
$string['studentsperpage'] = 'Студенти на страница';
$string['studentsperpage_help'] = 'Тази настройка определя броя на студентите показвани на една страница в отчета за оценяващия.';
$string['subcategory'] = 'Нормална категория';
$string['submissions'] = 'Предадени работи';
$string['tabs'] = 'Раздели';
$string['typenone'] = 'Без оценка';
$string['typescale'] = 'Скала';
$string['typescale_help'] = 'Тази настройка определя скалата, използвана при оценка от тип скала. Скалата за оценяване на дейност се настройва на страницата за настройване на дейността.';
$string['typetext'] = 'Текст';
$string['typevalue'] = 'Стойност';
$string['uncategorised'] = 'Некатегоризирана';
$string['unchangedgrade'] = 'Оценката непроменена';
$string['unlimitedgrades'] = 'Неограничени оценки';
$string['unlimitedgrades_help'] = 'По подразбиране оценките са ограничени от максималната и минимална оценки в настройките на заданията. Поставянето на тази отметка, премахва ограниченията и позволява оценки със стойности над 100% директно да се записват в дневника с оценки. Препоръчва се тази отметка да се поставя в часове на слабо използване на сайта, защото всички оценки ще се преизчисляват и това ще натоварва сървъра.';
$string['unlock'] = 'Отключване';
$string['unlockverbose'] = 'Отключване на {$a->category} {$a->itemmodule} {$a->itemname}';
$string['uploadgrades'] = 'Качване на оценки';
$string['usenoscale'] = 'Да не се използва сакала';
$string['user'] = 'Потребител';
$string['userpreferences'] = 'Предпочитания на потребителя';
$string['viewgrades'] = 'Разглеждане на оценки';
$string['yes'] = 'Да';
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 7,450
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Kochi Woke
Read Bytes
About TWJ
The Woke Journal
Home Politics Environment Increase of 5,188 sq kms in India's forest, tree cover
Increase of 5,188 sq kms in India's forest, tree cover
Under the current assessment the total carbon stock in the country's forest is estimated at 7,124.6 million tonnes and there an increase of 42.6 million tonnes in the carbon stock of country as compared to the last assessment of 2017, Union Minister for Environment and Forests Prakash Javadekar said.
Chinese Dove trees (Davidia Involucrata Baill) blanket the mountains in the Longcanggou National Forest Park of Yingjing County, southwest China's Sichuan province.
There has been an increase of 5,188 sq km in the total forest and tree cover of the country as compared to the assessment of 2017. Out of this, the increase in the forest cover has been observed as 3,976 sq km and that in tree cover is 1,212 sq km, the government said on Monday.
Under the current assessment the total carbon stock in the country's forest is estimated at 7,124.6 million tonnes and there an increase of 42.6 million tonnes in the carbon stock of country as compared to the last assessment of 2017, Union Minister for Environment and Forests Prakash Javadekar said.
The top three states showing an increase in forest cover are Karnataka (1,025 sq km) followed by Andhra Pradesh (990 sq km) and Kerala (823 sq km).
Mangrove cover has been separately reported in the ISFR 2019 and the total mangrove cover in the country is 4,975 sq km. An increase of 54 sq km in mangrove cover has been observed as compared to the previous assessment of 2017. The top three states showing mangrove cover increase are Gujarat (37 sq km) followed by Maharashtra (16 sq km) and Odisha (8 sq km).
The extent of the bamboo bearing area of the country has been estimated at 16.00 million hectares. The total estimated green weight of bamboo culms is 278 million tonnes, showing an increase of 88 million tonnes as compared to ISFR 2017.
carbon stock
tree cover
Union Minister for Environment and Forests
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Sunita Williams Among 9 Astronauts to fly First Commercial Spacecraft
IANS - 4th August 2018
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IANS - 9th March 2020
|
{
"redpajama_set_name": "RedPajamaCommonCrawl"
}
| 9,596
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\section{Introduction}
\vspace{0.5cm}
\large
\noindent
The new kind of nuclear matter consisting of nucleus bound with $\eta$ mesons via strong interaction was postulated by Haider and Liu over twenty years ago~\cite{HaiderLiu1}.~However, till now none of experiments confirmed empirically its \mbox{existence}. This exotic form of matter called $\eta$-mesic nucleus is schematically presented in Fig.~\ref{Jadro}.
\begin{figure}[h!]
\begin{center}
\includegraphics[width=6.0cm,height=6.0cm]{Jadro.jpg}
\caption{The scheme of $\eta$-mesic bound state.}\label{Jadro}
\end{center}
\end{figure}
\indent
Up to this time $\eta$-mesic nuclei have been searched via production of $\eta$ meson in~the vicinity of the heavy nuclei.~It was considered that due to a huge number of nucleons, attraction of $\eta$ meson could be high enough that allows to form a bound state.~Nevertheless those experiments have not brought expected effect.~Recent investigations indicate that interaction between $\eta$ meson and nucleus is considerably stronger than it was predicted earlier. Therefore, according to the current theoretical considerations, it is possible that the bound states might be also formed for a light nuclei like helium, tritium~\cite{Wilkin1,WycechGreen} and even deuteron~\cite{Green}.\\
\indent
The existence of $\eta$-mesic nuclei allows to investigate interaction of the $\eta$ meson and the nucleons inside a nuclear matter.~Moreover it would provide information about $\mbox{N}^{*}(1535)$ resonance~\cite{Jido} and about $\eta$ meson properties in nuclear matter~\cite{InoueOset}, as well as about contribution of the flavour singlet component of the quark-gluon wave function of $\eta$ meson~\cite{BassThomas, BassTom}.\\
\indent
The measurement of the $^{4}\hspace{-0.03cm}\mbox{He}$-$\eta$ bound states is carried out with a unique accurance by means of WASA detector~\cite{Adam1} installed at cooler synchrotron COSY in the Research Center J\"ulich. The $\eta$-mesic nuclei is searched there via studying of excitation function for the chosen decay channels of the \mbox{$^{4}\hspace{-0.03cm}\mbox{He}$-$\eta$} system formed in deuteron-deuteron collision~\cite{Moskal4}.~The measurement is performed for the beam momentum varying continously around the threshold.~The~beam ramping technique allows to reduce the systematical uncertainities.~The \mbox{existence} of the bound system should manifest itself as a resonance-like structure in the excitation curve of eg. $dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He} p \pi{}^{-}$ reaction below the $dd\rightarrow$ $^{4}\hspace{-0.03cm}\mbox{He}$-$\eta$ reaction threshold which allows to determine the~\mbox{binding} energy and the width of such state.
\indent
Formation of the $\eta$-mesic nucleus might be also realized by means of the quasi-free reactions. In this case the scan of the energy can be achieved from the Fermi motion of nucleons inside the deuteron beam. Measurements of such reaction is available for the external COSY-TOF detector~\cite{Pizzolotto,Jaeckle,Abdel} where the search of $\eta$-mesic Tritium can be carried out by the measurement of the excitation function of the $nd\rightarrow(\mbox{T}$-$\eta)_{bs}\rightarrow$ $d p \pi{}^{-}$ reaction around the threshold of the $nd \rightarrow \mbox{T}$-$\eta$ production~\cite{Moskal4}.\\
\indent
The main aim of this thesis is a determination of geometrical acceptance of WASA detector for four reactions in which $\eta$-mesic bound states might be formed via free production:\\
\noindent
$dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He} p \pi{}^{-}$\\
$dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow d p p \pi{}^{-}$\\
$pd\rightarrow(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow d p \pi{}^{0} \rightarrow d p \gamma \gamma$\\
$pd\rightarrow(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow p p p \pi{}^{-}$\\
\noindent
and geometrical acceptance of COSY-TOF detector setup for one quasi-free reaction of $\eta$-mesic nuclei production:\\
\noindent
$dd\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}\rightarrow p_{sp} d p \pi{}^{-}$\\
\noindent
In each case Monte Carlo simulations of $\eta$-mesic nucleus production and decay process were carried out based on reaction kinematics. The simulations were realized with assumption that the bound state has a resonance structure given by the Breit-Wigner distribution with fixed binding energy $\mbox{B}_{s}$ and a width $\Gamma$. Moreover, for reconstruction of events the spectator model was applied. The efficiency of the registration of each reactions was analysed with regard to different models describing Fermi momentum distributions of nucleons inside deuteron, helium and tritium nuclei. It was also compared for different values of $\mbox{B}_{s}$ and $\Gamma$ from range predicted by theory~\cite{GarNiIno}.
\indent
This thesis is divided into seven chapters. The second describes indirect and direct experimental indications for the existence of the $\eta$-mesic helium.\\
The Chapter 3 treats of nucleon momentum distributions inside the light nuclei such as $^{3}\hspace{-0.03cm}\mbox{He}$, $^{4}\hspace{-0.03cm}\mbox{He}$ and T. The distributions are presented and compared for different models.\\
Description of the spectator model assumptions and its experimental confirmations are presented in Chapter 4.\\
The Chapter 5 is devoted to the kinematics of the free and quasi-free reactions in which $\eta$-mesic bound states are produced and decay.\\
The WASA-at-COSY and COSY-TOF detection systems emphasising their properties useful for the measurement of the $\eta$-mesic nuclei are presented in Chapter 6.\\
Simulation results of the bound states in free and quasi-free reactions are described in Chapter 7 and in Chapter 8 a summary and conclusions are presented.
\pagestyle{fancy}
\fancyhf{}
\fancyhead[LE,RO]{\textbf{\thepage}}
\fancyhead[RE]{\small\textbf{{Indications for the existence of eta-mesic helium}}}
\newpage
\thispagestyle{plain}
\large
\newpage
\section{Indications for the existence of $\eta$-mesic helium}
\vspace{0.5cm}
\subsection{Indirect}
\large
\noindent
According to the theoretical considerations, the formation of the $\eta$-mesic nucleus can only take place if the real part of the $\eta$-nucleus scattering length is negative (attractive nature of the interaction), and the magnitude of the real part is greater than the magnitude of the imaginary part~\cite{HaiderLiu2}:
\begin{equation}
|Re(a_{\eta-nucleus})|>|Im(a_{\eta-nucleus})|.\label{eq:jeden}
\end{equation}
\noindent
A wide range of possible values of the $\eta$N scattering lenght $a_{\eta N}$ calculated for hadronic- and photoproduction of the $\eta$ meson has not exluded the formation of $\eta$-nucleus bound states for a light nuclei as $^{3,4}\hspace{-0.03cm}\mbox{He}$, T~\cite{Wilkin1,WycechGreen} and even for deuteron~\cite{Green}.~Those bound states have been searched in many experiments. However, none of them gave empirical confirmation of their existence. There are only a signal which might be interpreted as an~\mbox{indications} of the $\eta$-mesic nuclei.
\indent
Experimental observations which might suggest the possibility of~the existence of the $^{3}\hspace{-0.03cm}\mbox{He}$-$\eta$ bound system were found by \mbox{SPES-4}~\cite{Berger}, \mbox{SPES-2}~\cite{Mayer}, ANKE~\cite{Mersmann} and \mbox{COSY-11}~\cite{Smyrski1} collaborations. In the experiments cross section of the \mbox{$dp\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He}$-$\eta$} \mbox{reaction} was measured. In this reaction with the real $\eta$ meson in the final state, the bound state could not be produced and therefore obtained results might be treated as indirect indications of the $\eta$-mesic nuclei only.
\begin{figure}[h!]
\centering
\includegraphics[width=8.0cm,height=7.0cm]{spes_2.jpg}
\caption{Total cross section for $pd\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He}$-$\eta$ reaction measured for eight different proton energies above threshold from 0.2 to 11~MeV~\cite{Mayer}. Total cross section rises from 0.25 to 0.40~$\mu$b rapidly in the range of 2~MeV.\label{spes_2}}
\label{ratio}
\end{figure}
\newpage
\indent
The~\mbox{measurements} on the SPES-4 spectrometer were realised \mbox{using} the deuteron beam accelerated in SATURNE synchrotron colliding with \mbox{liquid-hydrogen} target, while in case of SPES-2 the proton beam and \mbox{liquid-deuterium} target were used.~The total cross section measured by the SPES-2 collaboration for the eight different beam \mbox{energies} are presented in~Fig.~\ref{spes_2}.
According to \cite{Wilkin1}, the energy dependence of the cross section for the~$dp\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He}$-$\eta$ reaction is dominated by the strong interaction between $\eta$ and $^{3}\hspace{-0.03cm}\mbox{He}$ \mbox{originating} from the strong $\eta$-nucleon interaction leading to the formation of~the $\mbox{N}^*$(1535) resonance.
The data analysis of the close to threshold measurements of the total cross \mbox{section} led to the determination of the~$\eta^{3}\hspace{-0.03cm}\mbox{He}$ scattering length. The negative sign of a real part of the $a_{\eta^{3}\hspace{-0.03cm}{He}}$ and its large value equal \mbox{$a_{\eta^{3}\hspace{-0.03cm}{He}}=(-2.31+2.57i)$}~fm~\cite{Wilkin1} suggest a possible existence of the \mbox{$(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}$}, \mbox{although} the condition given by (\ref{eq:jeden}) is not \mbox{fulfilled}.
\indent
An indirect signature of the~$\eta$-mesic nuclei were also searched at the cooler synchrotron COSY in~J\"ulich by~means~of~internal \mbox{COSY-11} and \mbox{COSY-ANKE} detection setups with high precision and high statistics. In the experiments the momentum ramping technique of the deuteron beam was used that allows to reduce the systematic uncertainties. The beam was accelerated slowly and linearly in~time, from excess energy of~\mbox{Q=-5.05 MeV} up~to \mbox{Q=11.33 MeV} in~case~of~ANKE experiment~\cite{Mersmann}, while during the \mbox{COSY-11} experiment~\cite{Smyrski1} the~momentum was varied in the range corresponding to the excess energy from \mbox{Q=-10 MeV} to \mbox{Q=9 MeV}. Both collaborations performed the measurement of~the~excitation function and differential cross section of~the \mbox{$dp\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He}$-$\eta$} reaction close to the~kinematical threshold. The experimental excitation function parametrized with the s-wave formula of scattering length~\cite{Mersmann,Smyrski1} is presented in~Fig.~\ref{cosy11_anke} (left panel). The fit to~the~\mbox{COSY-11} data gave the value of the $\eta^{3}\hspace{-0.03cm}\mbox{He}$ scattering length equal to $a_{\eta^{3}\hspace{-0.03cm}{He}}=[\pm(2.9\pm0.6)+(3.2\pm0.4)i]$~fm~\cite{Smyrski1}. Although this value is in agreement with formula (\ref{eq:jeden}), uncertainties of its real and imaginary part are too large to confirm the possible formation of \mbox{($^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}$}.~The real part of scattering lenght of the \mbox{$\eta^{3}\hspace{-0.03cm}\mbox{He}$} system derived by fitting the ANKE data for Q$<$4MeV equals $Re(a_{\eta ^{3}\hspace{-0.03cm}{He}})=(11.6\pm1.4)$~fm while imaginary part is equal $Im(a_{\eta ^{3}\hspace{-0.03cm}{He}})=(-4.1\pm7.0)$~fm~\cite{Mersmann}. Those large values implies the existence of a quasi-bound states very close to the reaction threshold, however the derived by ANKE and COSY-11 collaborations real parts of the scattering length are not consistent within the quoted errors.
\begin{figure}[h]
\centering
\includegraphics[width=6.7cm,height=6.3cm]{cosy11_anke1.jpg} \includegraphics[width=6.7cm,height=6.4cm]{cosy11_anke2.jpg}
\caption{(left) Total cross section for the $dp\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He}$-$\eta$ reaction measured with the \mbox{COSY-ANKE} (open circles)~\cite{Mersmann} and the \mbox{COSY-11} facilities (closed circles)~\cite{Smyrski1} and (triangles)~\cite{Adam}. Scattering length fit to the COSY-ANKE and COSY-11 data is represented with dashed and solid lines, respectively. (right) Angular asymmetry parameter $\alpha$ for the experimental data from COSY-ANKE (full dots)~\cite{Mersmann} and from COSY-11 (open circles)~\cite{Smyrski1}. The dashed and solid lines are fitted (assuming the phase variation between S and P waves) to the COSY-11 and COSY-ANKE data, respectively~\cite{Wilkin2}. The fit without the phase variation is denoted as the dotted line. The figure is adapted from~\cite{Moskal4}.\label{cosy11_anke}}
\end{figure}
\noindent
The differential cross section measurement allows to calculate angular asymmetry parameter $\alpha$, defined as:
\begin{equation}
\alpha=\frac{d}{d\cos\theta_{\eta}}\ln\frac{d\sigma}{d\Omega}.\label{eq:alpha}
\end{equation}
\noindent
The momentum dependence of parameter $\alpha$ can be described correctly with assumption that the phase is varying between S and P waves~\cite{Wilkin2}. In another case the discrepancy between the experimental data and theoretical description are significant.
The momentum dependence of $\alpha$ parameter is presented in Fig.~\ref{cosy11_anke} (right).
\vspace{0.5cm}
\subsection{Direct}
\large
\noindent
The first direct experimental indications of a light $\eta$-nucleus bound states were observed in the reaction of the $\eta$ photoproduction $\gamma^{3}$\hspace{-0.03cm}$\mbox{He}\rightarrow \pi^{0}pX$ which was investigated with the TAPS calorimeter at the electron accelerator facility Mainz Microtron (MAMI)~\cite{Pfeiffer}.~Photons produced in a~thin radiator foil and tagged using a special spectrometer hit the target filled with liquid $^{3}\hspace{-0.03cm}\mbox{He}$. There the~measurements of~the excitation functions of~the~$\pi^{0}$-proton production for two ranges of~the~relative angle between those particles were carried~out.~It appeared that a~difference between excitation curves for opening angles of~$170^{0}-180^{0}$ and $150^{0}-170^{0}$ in~the~center-of-mass frame revealed an~enhancement just below the threshold of the $\gamma^{3}\hspace{-0.03cm}\mbox{He}\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He}$-$\eta$ reaction which was interpreted as a~possible signature of a~{$^{3}\hspace{-0.03cm}\mbox{He}$-$\eta$} bound state where $\eta$ meson captured by one of~nucleons inside helium forms an intermediate $S_{11}(1535)$ resonance which decays into $\pi^{0}$-$p$ pair.~A~binding energy and width for~the anticipated quasibound $\eta$-mesic state in~$^{3}\hspace{-0.03cm}\mbox{He}$ were deduced from the~fit~of~the~\mbox{Breit-Wigner} distribution function~\cite{Pfeiffer} to the~experimental points and equal $(-4.4\pm4.2)$~MeV and $(25.6\pm6.1)$~MeV, respectively. Those values are consistent with expectations for $\eta$-mesic nuclei.~Above cited excitation functions and the difference of~them with a \mbox{Breit-Wigner} distribution and background fitted to~the~data are shown in~Fig.~\ref{mami}.\\\\
\begin{figure}[h]
\centering
\includegraphics[width=14.0cm,height=4.5cm]{mami.jpg}
\caption{Excitation functions of the $\pi^{0}$-proton production for relative angles of $170^{0}-180^{0}$ (red triangles) and $150^{0}-170^{0}$ (black circles) in the $\gamma^{3}\hspace{-0.03cm}\mbox{He}$ center-of-mass sytem are shown in the left and center panels. In the right panel the difference between both distributions with superimposed line denoting the results of the fit of the \mbox{Breit-Wigner} distribution plus background are presented. The figure is adapted from~\cite{Pfeiffer}.\label{mami}}
\end{figure}
\noindent
However, due to the low statistics of the measurement the results might be interpreted not as an indication of the bound state but rather as a virtual state what is in details described in Ref.~\cite{Hanhart}. The interpretation is still under discussion~\cite{Sibirtsev}. Moreover at the recent meeting it was shown that the result may be an artefact due to the strong influence of the resonances on the shape of the excitation function~\cite{Krusche}.\\
\begin{figure}[h]
\centering
\includegraphics[width=4.5cm,height=4.0cm]{cosy11_1.jpg} \includegraphics[width=4.1cm,height=4.0cm]{cosy11_2.jpg} \includegraphics[width=4.1cm,height=4.0cm]{cosy11_3.jpg}
\caption{Experimental results of the COSY-11 collaboration for the $dp\rightarrow ppp\pi^{-}$ reaction: (left) Transversal vs. longitudinal momentum distributions of protons. The upper limit for the longituidal proton momenta is shown as dashed line and equals $p_{L}$=0.18GeV/c. (middle) Pion momentum distribution in the center of mass system. (right) Relative angle between pion and proton direction in the c.m. The figure is adapted from~\cite{Krzemien1}. \label{cosy11}}
\end{figure}
\indent
The analysis carried out by COSY-11 group~\cite{SmyMosKrze1,Krzemien1,Smyrski2,Smyrski3} give an indication for the~\mbox{$^{3}\hspace{-0.03cm}\mbox{He}$-$\eta$} bound state existence.~The search for the $\eta$-mesic helium was carried out using a deuteron beam and internal hydrogen target. The beam momentum was ramped around the kinematical threshold for the $\eta$ production in~the~$dp\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He}$-$\eta$ reaction and the measurement of the $dp\rightarrow ppp\pi^{-}$ and \mbox{$dp\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He} \pi^{0}$} reactions was carried out.~In the first case the momentum distribution of the $\pi^{-}$ (middle panel in Fig.~\ref{cosy11}) and the relative angle distribution between pion and proton momentum vectors (right panel in Fig.~\ref{cosy11}) were determined after application of apropriate cuts on the momentum of the spectator protons (left panel in Fig.~\ref{cosy11}) and the rejection of the events corresponding to quasi-free $\pi^{-}$ production.
Obtained results are in agreement with theoretical expectations for particles originating from decay of the $\mbox{N}^{*}$(1535) resonance which is created as a result of the absorption of the bound $\eta$ meson in the neutron inside \mbox{$^{3}\hspace{-0.03cm}\mbox{He}$}. Based on the above results the upper limit of total cross section for the~\mbox{$dp\rightarrow(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow p p p\pi^{-}$} reaction was estimated to the value of 270~nb. Similarly, investigation of the \mbox{$dp\rightarrow$ $^{3}
\hspace{-0.03cm}\mbox{He}$-$\pi^{0}$} reaction give only the value of the total upper limit of cross section of the~$dp\rightarrow(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He} \pi^{0}$ reaction equal to 70~nb.\\
\newpage
\thispagestyle{plain}
\section{Nucleon momentum distributions inside d, T, $^{3}\mbox{He}$ and $^{4}\mbox{He}$ nuclei}
\vspace{0.5cm}
\pagestyle{fancy}
\fancyhf{}
\fancyhead[LE,RO]{\textbf{\thepage}}
\fancyhead[RE]{\small\textbf{{Nucleon momentum distributions inside d, T, $^{3}\mbox{He}$ and $^{4}\mbox{He}$ nuclei}}}
\noindent
Due to the Fermi motion, nucleons inside atomic nuclei are not at rest but move with momenta which vary in a broad range.
This variation influences kinematics of nuclear reactions.
\indent
Fermi momentum distributions of proton and neutron bound inside a deuteron derived from two different potential models, namely PARIS~\cite{Lacombe} and CD-Bonn~\cite{Machleidt} are shown in Fig.~\ref{deuteron}.~The normalized nucleon momentum distributions are calculated by means of the Fourier transformation of parametrized deuteron wave functions obtained from space representation.~Respective parametrization coefficients found in the analitic representation of the deuteron wave function for both of above named nucleon-nucleon interaction models are given in~\cite{Lacombe,Machleidt,Czyzykiewicz}.
The momentum distributions deduced from Paris and \mbox{CD-Bonn} potentials are peaked at about 40 MeV/c and differ no more than $5\%$~\cite{Czyzykiewicz}.
\begin{figure}[h]
\centering
\includegraphics[width=11.0cm,height=10.0cm]{deuteron.jpg}
\caption{Fermi momentum distribution of nucleons inside the deuteron for PARIS (full line) and CD-Bonn (dashed line) potentials. The distributions were normalized to unity in the momentum range from 0 to 300 MeV/c.\label{deuteron}}
\end{figure}
In case of three-nucleon bound states like $^{3}\hspace{-0.03cm}\mbox{He}$ and T, Fermi momentum distributions of nucleons are presented in Fig.~\ref{hel_3} for three different models. Thick solid line depicts proton momentum distribution inside $^{3}\hspace{-0.03cm}\mbox{He}$ and neutron momentum distribution inside T as given by analytic formula (\ref{eq:4.1}) which results from the fit to the experimental data on $p\left(^{3}\hspace{-0.03cm}\mbox{He},2p\right)d$ and $p\left(\mbox{T},pn\right)d$ reactions~\cite{Abdullin}:
\begin{equation}
f{(p)}=p^2[exp(-263p^2)+0.177exp(-69.2p^2)]
\label{eq:4.1}
\end{equation}
\noindent
This momentum distribution is in a good agreement with the one calculated with realistic potential in the frame of the model of the composite quark bags~\cite{Yu}.
The distributions of protons and neutrons momentum inside $^{3}\hspace{-0.03cm}\mbox{He}$ and T are also estimated based on the AV18 and the CDB-2000 nucleon-nucleon interaction models in conjunction with Urbana IX (UIX) and Tucson-Melbourne (TM) three nucleon interactions (TNI), respectively~\cite{Nogga1,Nogga2}.~They are presented in Fig.~\ref{hel_3} for protons inside $^{3}\hspace{-0.03cm}\mbox{He}$ (left) and neutrons inside T (right) and ticked as a dashed and dotted lines. Similar results can be obtained for neutron inside helium and proton inside tritium. The difference between those two distributions are small and results from different interaction Hamiltonian forms defined for above-cited models.
\begin{figure}[h]
\includegraphics[width=9.0cm,height=8.5cm]{proton1_hel3.jpg} \hspace{-1.5cm}\includegraphics[width=9.0cm,height=8.5cm]{neutron1_tryt.jpg}
\caption{Fermi momentum distribution for protons inside $^{3}\hspace{-0.03cm}\mbox{He}$ (left) and neutrons inside T (right) given by analytic formula (thick line) and estimated for the AV18 NN (dashed line) and the CDB-2000 NN (dotted line).~The distributions were normalized to unity in the momentum range from 0 to 0.4 GeV/c.\label{hel_3}}
\end{figure}
\noindent
Estimation based upon the formula (\ref{eq:4.1}) is consistent with the one derived from AV18 NN and CDB-2000 NN models with an accurancy better than 9\% for protons inside $^{3}\hspace{-0.03cm}\mbox{He}$ and 11\% for neutrons inside T.
\indent
For nucleons inside $^{4}\hspace{-0.03cm}\mbox{He}$ Fermi momentum distributions predicted by three independent models are shown in Fig.~\ref{hel_4}. The distribution represented by a thick line is calculated from helium wave function derived based on Fermi three parameter charge distribution of nucleus~\cite{Hejny}. The momentum distribution is described by formula (\ref{eq:4.2}):
\begin{equation}
f{(p)}=\frac{p^2}{a\cdot b}exp\left(\frac{-p^2}{a\cdot c}\right),
\label{eq:4.2}
\end{equation}
\noindent
where $a=0.03892719$, $b=0.05511$, $c=0.7352$. Fermi momentum is given in units of GeV/c.
\indent
The dashed and dotted lines depict distributions obtained, similarly as in case of three nucleon systems, from AV18 and the CDB-2000 potential models with the inclusion of three nucleon interaction contributions~\cite{Nogga2}. Due to the fact that $^{4}\hspace{-0.03cm}\mbox{He}$ is symmetrical, proton and neutron momentum distributions are in good approximation equal.
\begin{figure}[h]
\centering
\includegraphics[width=11.0cm,height=10.0cm]{proton1_hel4.jpg}
\caption{Fermi momentum distribution of nucleons inside $^{4}\hspace{-0.03cm}\mbox{He}$ given by analytic formula (thick solid) and estimated for the AV18 NN (dashed) and the CDB-2000 NN (dotted). The distributions were normalized to unity in the momentum range from 0 to 0.5 GeV/c.~\label{hel_4}}
\end{figure}
\indent
The difference between the distributions derived from AV18 and \mbox{CDB-2000} models and given by analytic formula is significant and equals up to about 40\%, and in addition the maxima of these distributions are shifted \mbox{by about 45 MeV/c.}
The discrepancy results from the fact that the formula (\ref{eq:4.2}) was derived from nucleus charge distribution smeared out by the charge distribution of protons, whereas the AV18 and the CDB-2000 models allow for the finite size of nucleus charge distributions and are related to the momentum of the point like protons in the alpha particle~\cite{Nogga3}. Therefore, as more realistic in further considerations the momentum distributions of nucleons inside $^{4}\hspace{-0.03cm}\mbox{He}$ calculated from AV18 and the CDB-2000 potentials will be taken into account.\\
\indent
The numerical data describing above cited momentum distributions are given in \mbox{Appendix~A}.
\indent
The presented distributions estimated based on various models will be used to calculate the systematical uncertainty in the determination of the excitation curves used to search for $\eta$-mesic bound states. Respective results are presented in Chapter~7.
\newpage
\thispagestyle{plain}
\section{Spectator model}
\vspace{0.5cm}
\subsection{The main assumption of the spectator model}
\pagestyle{fancy}
\fancyhf{}
\fancyhead[LE,RO]{\textbf{\thepage}}
\fancyhead[RE]{\small\textbf{{Spectator model}}}
\noindent
The production and decay of $\eta$-mesic bound states investigated in this thesis might be schematically depicted as:\\
\hspace{0.3cm}
a) $dd\rightarrow$ $(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs} \rightarrow$
\vspace{-0.8cm}
\begin{displaymath}
\hspace{-1.0cm}
\left\{ \begin{array}{ll}
^{3}\hspace{-0.03cm}\mbox{He}_{sp}\ p\ \pi{}^{-} \\
\ p_{sp}\ d_{sp}\ p\ \pi{}^{-}
\end{array} \right.
\end{displaymath}
\vspace{0.5cm}
\hspace{0.3cm}
b) $pd\rightarrow$ $(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs} \rightarrow$
\vspace{-0.8cm}
\begin{displaymath}
\hspace{-1.1cm}
\left\{ \begin{array}{ll}
p_{sp}\ p_{sp}\ p\ \pi{}^{-} \\
d_{sp}\ p\ \pi{}^{0}
\end{array} \right.
\end{displaymath}
\vspace{0.5cm}
\hspace{0.3cm}
c) $dd\rightarrow$ $p_{sp} n d \rightarrow$ $p_{sp} (\mbox{T}$-$\eta)_{bs}\rightarrow$ $p_{sp}\ d_{sp}\ p\ \pi{}^{-}$ \\
\vspace{0.5cm}
\noindent
The a) and b) schemes include free and c) one describes quasi-free production of the bound states. Subscript \textit{bs} denotes 'bound state' whereas \textit{sp} stands for the 'spectator'.\\
\indent
'Spectators' are particles which do not take part in reactions~\cite{JKlaja,Moskal1} but hit the detectors with the Fermi momentum transformed into laboratory system. Fermi momentum distributions of nucleons inside the light nuclei are presented in previous chapter.~In the framework of the spectator model due to the relatively small binding energy of the nuclei, spectators are considered as a real particles registered in the experiments and in the analysis it is assumed that they are on their mass-shell during the reaction~\cite{JKlaja,Moskal1}:
\begin{equation}
\left|\mathbb{P}_{sp}\right|^2 = m_{sp}^2.
\label{eq4:4.2_1}
\end{equation}
\noindent
The $\mathbb{P}_{sp}$ and $m_{sp}$ are the four-momentum vector of spectator and the spectator mass, respectively.
In the free reactions the beam and target nuclei collide and form $\eta$-mesic bound state which decays into proton, pion and spectator/spectators which energies and momenta are measured in experiment. One of those reactions is schematically shown in Fig.~\ref{free}.
In case of quasi-free reaction presented in Fig.~\ref{quasi}, the deuteron from the beam is considered as a system consisting of proton and neutron moving with the Fermi motions. For the deuteron beam we have:
\begin{equation}
\mathbb{P}_{d}=\mathbb{P}_{n}^{b} + \mathbb{P}_{p_{sp}}
\label{eq:4.2_2}
\end{equation}
\begin{equation}
\left|\mathbb{P}_{p_{sp}}+\mathbb{P}_{n}^{b}\right|^2 = m_{d}^2,
\label{eq:4.2_22}
\end{equation}
\newpage
\begin{figure}[h]
\centering
\includegraphics[width=12.0cm,height=5.0cm]{free.jpg}
\caption{Schematic picture of the $dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He} p \pi{}^{-}$ reaction. Red and blue circles represent protons and neutrons respectively, whereas $\pi^{-}$ meson is depicted as yellow circle. The beam momentum is presented by the dashed arrow.\label{free}}
\end{figure}
\noindent
where $m_{d}$ denotes the deuteron mass equal to $1875.6$ $\mbox{MeV/c}^{2}$~\cite{Groom} while $\mathbb{P}_{p_{sp}}$ and $\mathbb{P}_{n}^{b}$ are the four-momentum vectors of the proton spectator and the beam neutron, respectively.
\begin{figure}[h]
\centering
\includegraphics[width=12.0cm,height=5.0cm]{quasi_free.jpg}
\caption{Schematic picture of the quasi-free $dd\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}\rightarrow p_{sp} d p \pi{}^{-}$ reaction. Red and blue circles represent protons and neutrons respectively, whereas $\eta$ meson is depicted as green circle. The Fermi momentum of the nucleons inside the deuteron is presented by the dotted arrows and the beam momentum by the dashed one.\label{quasi}}
\label{fig:1}
\end{figure}
\noindent
According to the spectator model, proton from the beam does not take part in the reaction and is registered as a real particle whereas neutron being off the mass-shell hits the target deuteron. From the conservations of momentum and energy and the assumption that proton is on its mass-shell we obtain in the deuteron beam rest frame:
\begin{equation}
\vec{p_{n}^{*}}=-\vec{p_{sp}^{*}},
\label{eq:4.2_3}
\end{equation}
\begin{equation}
E_{n}^{*}=m_{d}-E_{p_{sp}}^{*},
\label{eq:4.2_4}
\end{equation}\\
\noindent
Based on above-mentioned relationship we can deduce the neutron four-momentum vector from the spectator momentum which is fundamental in the analysis of reaction kinematics.~The close description of free and quasi-free reactions processes is described in Chapter~5.
\vspace{0.5cm}
\subsection{Experimental proofs of spectator model}
\large
\noindent
The validity of spectator model assumptions was confirmed by measurements performed by collaborations WASA/PROMICE~\cite{Stepaniak}, TRIUMF~\cite{Duncan}, \mbox{COSY-TOF}~\cite{AbdelBary}, COSY-11~\cite{Przerwa} and HADES~\cite{Hades}.~The WASA/PROMICE collaboration~\cite{Stepaniak} has compared free and quasi-free production cross sections for the $pp\rightarrow$ $pp\eta$ reaction. As a result it was presented that within the statistical errors there is no difference between the total cross section of the free and quasi-free process. The experimental data are shown in Fig.~\ref{wasa_promice}.
\begin{figure}[h]
\centering
\includegraphics[width=7.2cm,height=7.0cm]{wasa_promice.jpg}
\caption{Total cross section for the $pp \rightarrow$ $pp\eta$ reaction as a function of the excess energy for free (open circles) and quasi-free proton scattering (full circles). Figure is adapted from~\cite{MoskalWolke}. The data are taken from references~\cite{Smyrski4,Hibou,Calen1,Chiavassa,Bergdolt,Moskalx,Calen2}.\label{wasa_promice}}
\end{figure}
Investigation of pion production at the TRIUMF~\cite{Duncan} facility in quasi-free \mbox{$pp\rightarrow$ $d\pi^{+}$} reaction extracted from the \mbox{$pd\rightarrow$ $d\pi^{+}n$} reaction has proven that the spectator momentum distribution determined from the experimental data agrees with expectations based on spectator model. Moreover, it was shown that the magnitude of the differential cross sections for the quasi-free and for the free reactions are consistent on the few per cent level.
The spectator assumption was also confirmed by the COSY-TOF group~\cite{AbdelBary}. The momentum distribution of the spectator as well as the shape of the angular distribution for the quasi-free $np\rightarrow$ $pp\pi^{-}$ and $pn\rightarrow$ $pn$ reactions have been measured. The experimental data are consistent with calculations based upon the hypothesis of spectator model with an accurancy better than 4\% up to 150 MeV/c of the Fermi momentum and with about 25\% up to a momentum of~300 MeV/c.
\begin{figure}[h!]
\centering
\includegraphics[width=7.5cm,height=7.0cm]{cosy-11.jpg}
\caption{Proton spectator momentum distribution reconstructed in COSY-11 experiment (points) in comparison with simulation taking into account Fermi momentum distribution of nucleons inside deuteron, the acceptance and the efficiency of the detector system (solid histogram). The figure is adapted from~\cite{Przerwa}.\label{cosy-11}}
\label{ratio}
\end{figure}
In case of quasi-free $pn\rightarrow$ $pn\eta'$ reaction studied at COSY-11 facility~\cite{Przerwa} it is shown that the measured proton spectator momentum distribution is in good agreement with the theoretical assumptions of spectator model. The comparison of the experimental data and simulation result is shown in Fig.~\ref{cosy-11}.
Recently, the validity of the spectator model was proven also by HADES collaboration~\cite{Hades} during the measurement of the quasi-free $np\rightarrow$ $e^{+} e^{-} p X$ reaction realised with a deuteron beam and proton target. The angular distribution of proton spectator outgoing from deuteron beam and its momentum distribution agrees with assumptions of spectator model up to 200-300 MeV/c. Momentum distributions in deuteron CM frame are presented in~Fig.~\ref{HADES}. Experimental data are ticked as a red points, while simulations results based on the spectator model as a black points.
The above-cited results confirmed the spectator model and thus allow to use it in the analysis of the reactions kinematics.
\newpage
\begin{figure}[h!]
\centering
\includegraphics[width=13.0cm,height=6.5cm]{HADES.jpg}
\caption{Momentum distribution of proton spectator measured in HADES experiment (red points) and calculated based upon the hypothesis of spectator model (blue points) for \mbox{$M_{e^{+}e^{-}}<140 \mbox{MeV/c}^{2}$} (left) and for \mbox{$M_{e^{+}e^{-}}>140 \mbox{MeV/c}^{2}$}(right). Picture courtesy of~\cite{Hades}.\label{HADES}}
\label{ratio}
\end{figure}
\pagestyle{fancy}
\fancyhf{}
\fancyhead[LE,RO]{\textbf{\thepage}}
\fancyhead[RE]{\small\textbf{{Kinematics of the $\eta$-mesic bound states production and decays}}}
\newpage
\thispagestyle{plain}
\section{Kinematics of the $\eta$-mesic bound states production and decays}
\vspace{0.5cm}
\large
\noindent
In this thesis four reactions of free and one of quasi-free $\eta$-mesic bound states production are considered~\cite{Moskal2}:
\begin{enumerate}
\item $dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He} p \pi{}^{-}$
\item $dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow d p p \pi{}^{-}$
\item $pd\rightarrow(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow d p \pi{}^{0}$ $\rightarrow d p \gamma \gamma$
\item $pd\rightarrow(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow p p p \pi{}^{-}$
\item $nd\rightarrow(\mbox{T}$-$\eta)_{bs}\rightarrow d p \pi{}^{-}$
\end{enumerate}
\noindent
In case of free reactions (1)-(4), $^{4}\hspace{-0.03cm}\mbox{He}$-$\eta$ and $^{3}\hspace{-0.03cm}\mbox{He}$-$\eta$ bound states are produced in deuteron-deuteron and proton-deuteron fusion, respectively~\cite{Moskal3}.~The mechanism of the reactions is presented schematically in the example of the $(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}$ production in Fig.~\ref{free_reaction}.~Describing the kinematics of the reaction following notations will be used:\\
\noindent
$\mathbb{P}_{d}^{\,b}=(E_{d}^{\,b},\vec{p}_{b})$-four-momentum vector of the beam deuteron\\
$\mathbb{P}^{\,t}_{d}=(m_{d},0)$-four-momentum vector of the target deuteron\\
$\mathbb{P}_{^{3}\hspace{-0.05cm}He}=(E_{^{3}\hspace{-0.05cm}He},\vec{p}_{^{3}\hspace{-0.05cm}He})$-four-momentum vector of the outgoing $^{3}\hspace{-0.03cm}\mbox{He}$\\
$\mathbb{P}_{p}=(E_{p},\vec{p}_{p})$-four-momentum vector of the outgoing proton\\
$\mathbb{P}_{\pi^{-}}=(E_{\pi^{-}},\vec{p}_{\pi^{-}})$-four-momentum vector of the outgoing pion
\begin{figure}[h!]
\centering
\includegraphics[width=11.5cm,height=6.0cm]{free_reaction.jpg}
\caption{Reaction process of the ($^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}$ production and decay.\label{free_reaction}}
\end{figure}
\newpage
According to the scheme shown in Fig.~\ref{free_reaction}, the deuteron from the beam hits the deuteron in the target with a momentum of $\vec{p}_{b}$.~The collision may lead to the creation of $^{4}\hspace{-0.03cm}\mbox{He}$ nucleus bound with the $\eta$ meson via strong interaction. The mass of a bound state is a sum of $\eta$ and $^{4}\hspace{-0.03cm}\mbox{He}$ masses reduced by binding energy ($\mbox{B}_{s}$):
\begin{equation}
m_{bs}=m_{\eta}+m_{^{4}\hspace{-0.05cm}He}-B_{s}.
\end{equation}
\noindent
The $\eta$-mesic nucleus moves in laboratory frame with velocity:
\begin{equation}
\vec{\beta}_{cm}=\frac{\vec{p}_{b}}{m_{d}+E_{d}^{\,b}}=\frac{2\,\vec{p}_{b}\,m_{d}}{s_{dd}},
\end{equation}
\noindent
where $s_{dd}$ is the square of invariant mass of the colliding deuterons:
\begin{equation}
s_{dd}=|\mathbb{P}_{d}^{\,b}+\mathbb{P}_{d}^{\,t}|^{2}=2m_{d}\left(m_{d}+\sqrt{m^{2}_{d}+|\vec{p_{b}}|^{2}}\right).
\end{equation}
\noindent
The $\eta$ meson might be absorbed by one of the nucleons inside helium and may propagate in the nucleus via consecutive excitation of nucleons to the $\mbox{N}^{*}(1525)$ state~\cite{Sokol} until the resonance decays into the pion-proton pair outgoing from the nucleus~\cite{Moskal4,Moskal3,KrzeMosSmy}. Before the decay, it is assumed that $\mbox{N}^*$ resonance moves with a Fermi momentum $\vec{p}^{\,\,*}_{F}$ inside $^{4}\hspace{-0.03cm}\mbox{He}$. From the momentum conservation in the $^{4}\hspace{-0.03cm}\mbox{He}$ frame and the assumption of spectator model, momentum and energy of $^{3}\hspace{-0.03cm}\mbox{He}$ may be expressed as:
\begin{equation}
\vec{p}^{\,\,*}_{^{3}\hspace{-0.05cm}He}=-{\vec{p}}^{\,\,*}_{F}
\end{equation}
\begin{equation}
E^{\,*}_{^{3}\hspace{-0.05cm}He}=\sqrt{m^{2}_{^{3}\hspace{-0.05cm}He}+|\vec{p}^{{\,\,*}}_{F}|^{2}}.
\end{equation}\\
\noindent
The momentum and energy are transformed into the laboratory frame by means of Lorentz transformation:
\begin{equation}
\vec{p}_{^{3}\hspace{-0.05cm}He}=\vec{p}^{\,\,*}_{^{3}\hspace{-0.05cm}He}+\vec{\beta}_{cm}\gamma_{cm}(\gamma_{cm}/(\gamma_{cm}+1)\vec{\beta}_{cm}\cdot\vec{p}^{\,\,*}_{^{3}\hspace{-0.05cm}He}+E^{\,*}_{^{3}\hspace{-0.05cm}He})
\end{equation}
\begin{equation}
E_{^{3}\hspace{-0.05cm}He}=\gamma_{cm}(E^{\,*}_{^{3}\hspace{-0.05cm}He}+\vec{\beta}_{cm}\cdot\vec{p}^{\,\,*}_{^{3}\hspace{-0.05cm}He}),
\end{equation}\\
\noindent
where $\gamma_{cm}=1/\sqrt{1-|\vec{\beta}_{cm}|^{2}}.$\\
\noindent
The angle between outgoing $^{3}\hspace{-0.03cm}\mbox{He}$ and the beam direction is given by:
\begin{equation}
\theta_{^{3}\hspace{-0.05cm}He}=\arccos{\left(\frac{\vec{p}_{^{3}\hspace{-0.05cm}He}\cdot\vec{p}_{b}}{|\vec{p}_{^{3}\hspace{-0.05cm}He}|\cdot|\vec{p}_{b}|}\right).}
\end{equation}
\noindent
The relative angle between the outgoing nucleon-pion pair is equal to $180^\circ$ in the $\mbox{N}^{*}$ reference frame. In the following the variables in the N* reference frame will be denoted by '**'. Both particles move with a momentum $|\vec{{p}^{{\,\,**}}_{p,\pi^{-}}}|$ which is related to the resonance mass:
\begin{equation}
m_{{N}^*}=\left(s_{dd}+m^{2}_{^{3}\hspace{-0.05cm}He}-2\sqrt{s_{dd}}\sqrt{m^{2}_{^{3}\hspace{-0.05cm}He}+|\vec{p}^{{\,\,*}}_{F}}|^{2}\right)^{\frac{1}{2}},
\label{eq:10}
\end{equation}\\
\noindent
and is given by:
\begin{equation}
|\vec{p}^{\,\,**}_{p,\pi^{-}}|=\frac{\lambda(m^{2}_{{N}^*},m^{2}_{{\pi}^{-}},m^{2}_{{p}})}{2m_{{N}^*}},
\label{eq:101}
\end{equation}\\
\noindent
where $\lambda(x,y,z)=(x-y-z)^{2}-4yz$~\cite{Byckling}.\\
\noindent
The pion and proton four-momentum vectors in the laboratory frame are calculated using the Lorentz transformation, first from $\mbox{N}^{*}$ to the bound state frame:
\begin{equation}
\vec{p}^{\,\,*}_{p,\pi^{-}}=\vec{p}^{\,\,**}_{p,\pi^{-}}+\vec{\beta}_{N^{*}}\gamma_{N^{*}}(\gamma_{N^{*}}/(\gamma_{N^{*}}+1)\vec{\beta}_{N^{*}}\cdot\vec{p}^{\,\,**}_{p,\pi^{-}}+E^{\,**}_{p,\pi^{-}})
\label{eq:11}
\end{equation}
\begin{equation}
E^{\,*}_{p,\pi^{-}}=\gamma_{N^{*}}(E^{\,**}_{p,\pi^{-}}+\vec{\beta}_{N^{*}}\cdot\vec{p}^{\,\,**}_{p,\pi^{-}}),
\label{eq:12}
\end{equation}\\
\noindent
and further to the laboratory frame:
\begin{equation}
\vec{p}_{p,\pi^{-}}=\vec{p}^{\,\,*}_{p,\pi^{-}}+\vec{\beta}_{cm}\gamma_{cm}(\gamma_{cm}/(\gamma_{cm}+1)\vec{\beta}_{cm}\cdot\vec{p}^{\,\,*}_{p,\pi^{-}}+E^{\,*}_{p,\pi^{-}})
\label{eq:13}
\end{equation}
\begin{equation}
E_{p,\pi^{-}}=\gamma_{cm}(E^{\,*}_{p,\pi^{-}}+\vec{\beta}_{cm}\cdot\vec{p}^{\,\,*}_{p,\pi^{-}}),
\label{eq:14}
\end{equation}\\
\noindent
where $\gamma_{N^{*}}=1/\sqrt{1-|\vec{\beta}_{N^{*}}|^{2}}$ is a velocity of the resonance $\mbox{N}^{*}$ in the bound state frame.\\
\noindent
The angles of outgoing proton and pion in LAB system equals:
\begin{equation}
\theta_{p,\pi^{-}}=\arccos{\left(\frac{\vec{p}_{p,\pi^{-}}\cdot\vec{p}_{b}}{|\vec{p}_{p,\pi^{-}}|\cdot|\vec{p}_{b}|}\right)}.
\label{eq:15}
\end{equation}\\
The quasi-free reaction kinematics was partially characterized in Chapter~4 by the way of the spectator model description.
Neutron bound inside the deuteron hits the deuteron target forming the (T-$\eta)_{bs}$, while proton does not take part in reaction and is considered as a real particle:
\begin{equation}
|\mathbb{P}_{p_{sp}}|^{2}=m^{2}_{p_{sp}}.
\end{equation}
\noindent
The square of invariant mass of neutron-deuteron system ($s_{nd}$) depends on the neutron Fermi momentum $\vec{p}^{\,\,*}_{n}$ (5.1.3) inside the beam deuteron and taking into account that target deuteron is at rest in the laboratory $s_{nd}$ equals:
\begin{equation}
s_{nd}=(E_{n}+m_{d})^{2}-|\vec{p}_{n}|^{2},
\end{equation}
\noindent
where $\vec{p}_{n}$ and $E_{n}$ are neutron momentum and energy in laboratory frame which may be obtained applying the Lorentz transformation according to the following formulas:
\begin{equation}
\vec{p}_{n}=\vec{p}^{\,\,*}_{n}+\vec{\beta}_{d}\gamma_{d}(\gamma_{d}/(\gamma_{d}+1)\vec{\beta}_{d}\cdot\vec{p}^{\,\,*}_{n}+E^{*}_{n})
\label{eq:6.1}
\end{equation}
\begin{equation}
E_{n}=\gamma_{d}(E^{*}_{n}+\vec{\beta}_{d}\cdot\vec{p}^{\,\,*}_{n}),
\label{eq:6.2}
\end{equation}\\
\noindent
where $\vec{\beta}_{d}$ denotes velocity of the beam deuteron in the laboratory frame, and $\vec{p}^{\,\,*}_{n}$ denotes neutron momentum in the deuteron center of mass, and $E^{*}_{n}=m_{d}-\sqrt{m^{2}_{p}+|p^{*}_{n}|^{2}}$.\\
\noindent
The process of T-$\eta$ bound state decay is analogous like in case of the free reaction which kinematics was described before. The deuteron spectator escapes with the Fermi momentum and energy, which in the frame of the bound state is equal to:
\begin{equation}
\vec{p}^{\,\,*}_{d}=-{\vec{p}}^{\,\,*}_{F}
\end{equation}
\begin{equation}
E^{\,*}_{d}=\sqrt{m^{2}_{d}+|\vec{p}^{{\,\,*}}_{F}|^{2}},
\end{equation}\\
\noindent
After the transformation into laboratory system we have:
\begin{equation}
\vec{p}_{d}=\vec{p}^{\,\,*}_{d}+\vec{\beta}_{cm'}\gamma_{cm'}(\gamma_{cm'}/(\gamma_{cm'}+1)\vec{\beta}_{cm'}\cdot\vec{p}^{\,\,*}_{d}+E^{\,*}_{d})
\end{equation}
\begin{equation}
E_{d}=\gamma_{cm'}(E^{\,*}_{d}+\vec{\beta}_{cm'}\cdot\vec{p}^{\,\,*}_{d}),
\end{equation}\\
\noindent
where $\vec{\beta}_{cm'}$=$\frac{\vec{p}_{n}}{m_{d}+E_{n}}$ denotes velocity of the center of mass for the quasi-free $nd\rightarrow(\mbox{T}$-$\eta)_{bs}\rightarrow d p \pi{}^{-}$ reaction in the laboratory frame.
\indent
The outgoing proton-pion pair originates from the decay of the resonance created via absorption of the $\eta$ meson on a nucleon in the tritium nucleus. The four-momenta of those particles are described in resonace frame by equations analogous to (\ref{eq:11}) and (\ref{eq:12}), and in laboratory frame by formulas (\ref{eq:13}) and (\ref{eq:14}) while proton and pion angles with relation to the beam direction are given by (\ref{eq:15}).
\pagestyle{fancy}
\fancyhf{}
\fancyhead[LE,RO]{\textbf{\thepage}}
\fancyhead[RE]{\small\textbf{{Experimental setup}}}
\newpage
\thispagestyle{plain}
\section{Experimental setup}
\vspace{0.5cm}
\subsection{WASA-at-COSY facility}
\large
\noindent
The search for $\eta$-mesic helium in free production reactions with high statistic and acceptance is carried out at the WASA facility~\cite{Adam1}, an internal detection system installed at the cooler synchrotron COSY in the Research Center J\"ulich. The WASA detector vertical cross section is schematically presented in Fig.~\ref{wasa_detector}.~All setup components and the method of~measurement are described in detail in reference~\cite{Adam1}. Thus, in this chapter the experimental technique will be only shortly presented.\\
\begin{figure}[h]
\centering
\includegraphics[width=15.0cm,height=8.5cm]{wasa_detector.jpg}
\caption{Scheme of WASA-at-COSY detection system. Gamma quanta, electrons and charged pions being products of mesons decays are registered in the Central Detector. Scattered projectiles and charged recoil particles like $^{3}\hspace{-0.03cm}\mbox{He}$, deuterons and protons are registered in the Forward Detector. The abbreviations of the detectors names are explained in the text.\label{wasa_detector}}
\end{figure}
In the COSY synchrotron protons and deuterons might be accelerated in~the momentum range between 0.3 GeV/c and 3.7 GeV/c~\cite{Adam1}. The ring can be filled with up to $10^{11}$ particles leading to luminosities of $10^{31} \mbox{cm}^{-2}\mbox{s}^{-1}$ in~case of internal cluster target~\cite{Brauksiepe} and $10^{32} \mbox{cm}^{-2}\mbox{s}^{-1}$ in case of pellet target~\cite{Adam1}. Beams are cooled by means of electron cooling as well as stochastic cooling at injection and high energies, respectively.
\indent
The internal hydrogen ($\mbox{H}_{2}$) or deuteron ($\mbox{D}_{2}$) target of the pellet-type is \mbox{installed} in the central part of the WASA-at-COSY detector and its position is marked in Fig.~\ref{wasa_detector} as a dotted line. The central detector is built around the interaction point and designed for measurements of $\pi^{0}$ and $\eta$ mesons decay products like \mbox{photons}, electrons and charged pions.~The charged particles momenta and reaction \mbox{vertex} are determined by means of Mini Drift Chamber (MDC) which covers angles from 24$^{0}$ to 159$^{0}$.~Charged \mbox{particles} are here bending in the magnetic field provided by \mbox{sourrounding} Superconducting Solenoid (SCS). First their trajectories are reconstructed, and then knowing the magnetic field, the momentum vector is reconstructed. For identification of charged particles the $\Delta$E-p and $\Delta$E-E methods are used based on $\Delta$E signals in Plastic \mbox{Scintillator} Barrel (PSB). The photons, electrons and positrons are \mbox{registered} in Scintillator Electromagnetic Calorimeter (SEC) via production of \mbox{electromagnetic} cascades. The calorimeter covers polar angle in the range from 20$^{0}$ to 169$^{0}$. \\
\indent
The detection and identification of forward scattered projectiles and target-recoil particles such as protons, deuterons and He nuclei and also of neutrons and charged pions are carried out with the Forward Detector which covers the range of polar angles from 3$^{0}$ to 17$^{0}$. It consists of fourteen planes of plastic scintillators forming Forward Window Counter (FWC), \mbox{Forward} Trigger Hodoscope (FTH), Forward Range Hodoscope (FRH), Forward Range Interleaving Hodoscope (FRI) and Forward Veto Hodoscope (FVH), respectively and proportional counter drift tubes called Forward Proportional Chamber (FPC).
Particles trajectories are reconstructed from the signals registered successively in FWC, FPC, FTH and FVH scintillator modules. Particles are identified based on measurement of energy loss in~the detection layers of FRH, FWC and FTH. The registered energy loss allows to determine their total momentum which direction is reconstucted from the measurement of~particles tracks by means of straw detectors constituting FPC. Respective components of the Forward Detector are presented in Fig.~\ref{wasa_detector}.\\
\indent
The $^{3}\hspace{-0.03cm}\mbox{He}$-$\eta$ and $^{4}\hspace{-0.03cm}\mbox{He}$-$\eta$ bound states considered in this thesis can be searched at WASA-at-COSY detection setup in proton-deuteron and deuteron-deuteron fusion reaction, respectively. The measurement will be carried out for the beam momentum slowly ramped around the $\eta$ production threshold corresponding to the range of excess energy Q from about -60 MeV to 20~MeV. The existence of the $\eta$-mesic nucleus should be visible in the excitation function as a \mbox{resonance-like} structure below the He-$\eta$ production threshold.~The free \mbox{$\eta$-helium} bound states production reactions will be carried out in experiment based on measurement of four-momenta of the outgoing particles. WASA \mbox{detector} at COSY allows for simultaneous registration of all ejectiles with large \mbox{acceptance}, which eg. for~the detection of the $dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He} p \pi{}^{-}$ \mbox{reaction} equals about 60\%. \mbox{Spectators} from the reactions will be registered mainly in the Forward \mbox{Detector}, while \mbox{proton-pion} pair from the resonance decay will be registered for the most part in the \mbox{Central} \mbox{Detector}. The detailed description of the reactions kinematics is given in Chapter~5.
\vspace{0.5cm}
\subsection{COSY-TOF facility}
\noindent
The measurement of $\eta$-mesic tritium might be realised by means of the \mbox{quasi-free} reaction with the time-of-flight spectometer COSY-TOF, a~'4$\pi$~\mbox{detector'} \mbox{installed} at an external beamline of the COSY synchrotron. The detection setup is schematically presented in Fig.~\ref{cosy_tof}. Detailed description of each particular parts and the measurement technique might be found in~\cite{Pizzolotto,Abdel,AbdelBary}.
\begin{figure}[h]
\centering
\includegraphics[width=15.0cm,height=10.0cm]{cosy_tof.jpg}
\caption{Scheme of COSY-TOF detection setup. Charged particles trajectories are registered in 'Erlangen' start detector system, while their identification is carried out with the Barrel, Ring and Quarrel detectors. The figure is adapted from~\cite{Abdel}\label{cosy_tof}.}
\end{figure}
The proton or deuteron beam accelerated in COSY is extracted and hits a target which contains liquid hydrogen or liquid \mbox{deuterium}~\cite{Pizzolotto, Jaeckle}. The target is installed in front of the 'Erlangen' start detector system \mbox{consisting of} four modular detectors (Starttorte, Microstrip detector, Small Hodoscope and Large Hodoscope) designed for a precision geometric charged particles tracks reconstruction. The detector covers a polar angular range from 3.4$^{0}$ to 74$^{0}$. The time-of-flight of the charged particles outgoing after the interaction of the beam particles with the target, is measured with an accuracy of 0.25 ns by means of the stop detector situated in cylindric vacuum tank. This detector consists of Barrel detector as well as of two Endcap detectors called Quirl and Ring and covers angular range from 0.7$^{0}$ to 76.7$^{0}$. Knowing the time-of-flight and the flight length between start and stop detectors, ~particles velocity is determined. The particle momentum can be calculated from the velocity and the mass hypothesis. Additionally, neutral particles which take part in the reactions and have not been detected can be analysed via momentum and energy conservation.
\indent
The search of $\eta$-tritium bound state can be carried out at COSY-TOF facility via the \mbox{measurement} of the excitation function of the \mbox{$nd\rightarrow(\mbox{T}$-$\eta)_{bs}\rightarrow d p \pi{}^{-}$} reaction.~The signal from $(\mbox{T}$-$\eta)_{bs}$ is expected below the threshold of~the \mbox{$nd \rightarrow \mbox{T}$-$\eta$} production~\cite{Moskal4,Moskal2}.~In the experiment deuteron beam will be used and the $nd$ reaction will be analized based on the measurement of the four-momentum of~spectator proton ($p_{sp}$)~\cite{Moskal4} from the \mbox{$dd\rightarrow p_{sp} n d\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}\rightarrow p_{sp} d p \pi{}^{-}$} reaction, which was schematically shown in Fig~\ref{quasi}. The advantage of this quasi-free reaction is that the Fermi momentum distribution of nucleons inside the deuteron beam allows for the scan of energy around the $\eta$ meson production threshold at a fixed value of the beam momentum.
Deuterons, protons and pions being products of T-$\eta$ bound states decays will be detected in a multi layer scintillator detectors by measuring their time of flight as well as direction.\\
\newpage
\pagestyle{fancy}
\fancyhf{}
\fancyhead[LE,RO]{\textbf{\thepage}}
\fancyhead[RE]{\small\textbf{{Simulation results}}}
\thispagestyle{plain}
\section {Simulation results}
\noindent
In this chapter simulation results of the free and quasi-free $\eta$-mesic bound states production are presented. Monte-Carlo calculations were carried out by means of computer programme written in FORTRAN'90 language.
\vspace{0.5cm}
\subsection{Simulation program scheme}
\noindent
The main purpose of simulations was the determination of the geometrical acceptances of WASA-at-COSY and \mbox{COSY-TOF} detectors for free and quasi-free reactions, respectively and comparing them for different models of nucleon momentum distribution inside atomic nuclei and different values of a bound states width.
In case of free reactions the simulation might be schematicaly described in following points for example of reaction (1) which kinematics is presented in details in Chapter~5:
\begin{enumerate}
\item The square of invariant mass of the whole system $\sqrt{s_{dd}}$ is distributed randomly according to the Breit-Wigner distribution which is given by formula~(\ref{eq:BW}) and shown in Fig.~\ref{BW}.
\begin{figure}[h]
\centering
\includegraphics[width=11.0cm,height=9.0cm]{BW.jpg}
\caption{Breit-Wigner distribution of square invariant mass $\sqrt{s_{dd}}$.\label{BW}}
\end{figure}
\newpage
\begin{equation}
N\left(\sqrt{s_{dd}}\right)=\frac{1}{2\pi}\frac{\Gamma}{\left(\sqrt{s_{dd}}-m_{bs}\right)^{2}+\Gamma^{2}/4}
\label{eq:BW}
\end{equation}\\
\noindent
where: $m_{bs}=\sqrt{s_{dd}}^{thr}-B_{s}$ - a mass of $\eta$-mesic bound state,\\
$\sqrt{s_{dd}}^{thr}=m_{\eta}+m_{^{4}\hspace{-0.03cm}He}$ - threshold square invariant mass,\\
$B_{s}$ - a binding energy of an $\eta$-mesic bound state,\\
$\Gamma$ - width of an $\eta$-mesic bound state. \\
In the distribution shown in~Fig.~\ref{BW} it is assumed that binding energy equals $B_{s}$=0.01~GeV and a width is equal to 40 MeV what is in agreement with theoretical prediction~\cite{InoueOset}. In simulations a range of $\Gamma$ from 7 to 40 MeV was studied.
\item The $\mbox{N}^{*}$ resonance momentum is distributed isotropically in spherical coordinates of $\eta$-mesic nucleus \mbox{(${p}^{\,\,*}_{F}$, $\theta^{*}$, $\phi^{*}$)} with Fermi momentum distribution of nucleons inside $^{4}\hspace{-0.03cm}\mbox{He}$ which was presented for three different models in Chapter~3. Next, it is transformed into Cartesian coordinates (${\vec{p}}^{\,\,*}_{F}$=(${p}^{\,\,*x}_{F},{p}^{\,\,*y}_{F},{p}^{\,\,*z}_{F}$)) using the following equations:
\begin{equation}
{p}^{\,\,*x}_{F}={p}^{\,\,*}_{F}\cdot sin\theta^* \cdot cos\phi^*
\end{equation}
\begin{equation}
{p}^{\,\,*y}_{F}={p}^{\,\,*}_{F}\cdot sin\theta^* \cdot sin\phi^*
\end{equation}
\begin{equation}
{p}^{\,\,*z}_{F}={p}^{\,\,*}_{F}\cdot cos\theta^*
\end{equation}
Here the momentum value ${p}^{\,\,*}_{F}$ is distributed according to the used model, and the direction is simulated isotropically in the space.
\item The $^{3}\hspace{-0.03cm}\mbox{He}$ four momentum vector is calculated (based on spectator model assumption) in the center of mass frame and transformed using Lorentz transformation into laboratory frame. The angle $\theta_{^{3}\hspace{-0.05cm}He}$ is also calculated.
\item Based on $\sqrt{s_{dd}}$ and ${\vec{p}}^{\,\,*}_{F}$ values, resonance mass $m_{{N}^*}$ is calculated according to equation~(\ref{eq:10}).
\item The proton and pion momentum vectors are simulated isotropically in the $\mbox{N}^{*}$ frame in spherical coordinates and transformed into Cartesian coordinates. The absolute value of $\vec{p}^{\,\,**}_{p,\pi^{-}}$ is fixed by equation~(\ref{eq:101}).
\item The proton and pion four momentum vectors are transformed into the center of mass frame and next into laboratory frame by means of Lorentz transformation. The angles of outgoing proton and pion in LAB system are calculated.
\item The histograms of outgoing particles angle distributions and invariant mass distribution for all generated events are created.
\item Knowing angles of outgoing particles and the WASA-at-COSY detector geometry it is checked whether generated event can be registered.
\item The histograms of angular distributions and invariant mass distribution of outgoing particles for all accepted events are created.
\end{enumerate}
\noindent
The simulation of other three free $\eta$-helium bound states production reactions were carried out in a similar way.\\
The simulation of quasi-free reaction, realised with COSY-TOF detection setup is more complex due to the fact that neutron bound in beam deuteron takes part in the reaction of $\eta$-mesic tritium formation. The simulation scheme might be presented as follows:
\begin{enumerate}
\item The beam neutron momentum is distributed isotropically in spherical coordinates with Fermi momentum distribution of nucleons inside beam deuteron (the PARIS and CD-Bonn distributions are presented in Chapter~3) and transformed into Cartesian coordinates ($\vec{p_{n}^{*}}$).
\item The proton spectator four momentum vector as well as its angle with respect to the beam direction are calculated in the beam deuteron center of mass frame and transformed with Lorentz transformation into laboratory frame.
\item The neutron four momentum in the beam deuteron frame and in laboratory frame is calculated using~(\ref{eq:4.2_3}),~(\ref{eq:4.2_4}) and ~(\ref{eq:6.1}),~(\ref{eq:6.2}) formulas, respectively.
\item The square of bound state invariant mass $\sqrt{s_{nd}}$ is calculated based on neutron four momentum and next events are accepted according to the probability described by the Breit-Wigner distribution.
\item The next points are analogous like in case of free reaction scheme. Moreover, the calculations are carried out for ten values of the deuteron beam momentum $\vec{p}_{beam}$ in the range from 2.6~GeV/c to 3.5~GeV/c.
\end{enumerate}
\indent
Simulations were conducted for all reactions listed in introduction. Three different values of the bound states width: $\Gamma=\{10,25,40\}$~MeV and three different Fermi momentum distributions of nucleons inside light atomic nuclei were studied.
\vspace{0.5cm}
\subsection{Reactions products - angular distributions}
\noindent
The $\eta$-mesic nuclei, which are formed via deuteron-deuteron, proton-deuteron or neutron-deuteron fussion, decay according to the mechanism which is described in details in Chapter~5.~The distribution of momentum vectors of reaction products depend on the bound state mass distribution and on the distribution of the nucleons momentum inside decayed nuclei. Angular distributions for the outgoing particles being products of reaction (1) are presented in Fig.~\ref{angular}.
\begin{figure}[h]
\centering
\includegraphics[width=7.1cm,height=6.5cm]{hel.jpg} \hspace{-0.5cm}\includegraphics[width=7.1cm,height=6.5cm]{proton.jpg} \includegraphics[width=7.1cm,height=6.5cm]{pion.jpg}
\caption{Simulated angular distributions of outgoing $^{3}\hspace{-0.05cm}\mbox{He}$ (a), proton (b) and pion (c) formed via \mbox{$dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He} p \pi{}^{-}$} reaction. Figure shows results for $10^{8}$ generated events using the AV18 potential model for the Fermi momentum distribution of nucleons inside $^{4}\hspace{-0.03cm}\mbox{He}$.\label{angular}}
\end{figure}
In fact the detectors geometry does not give a possibility to register the whole range of outgoing particles angles. An angular ranges covered by respective components of WASA-at-COSY detection setup are presented in Fig.~\ref{angular} with shaded areas.
\vspace{0.5cm}
\subsection{Acceptance}
\noindent
In order to determine acceptance for respective reaction, the studied excess energy range was divided into small intervals.~Next for each interval of Q
\mbox{($\mbox{Q}=\sqrt{s}-\sqrt{s}^{thr}$)} the number of events accepted by detector was divided by number of generated events.
An event is accepted when all outgoing particles being reaction products can be registered in the detector. In simulations all possible combinations of particles registration in different part of detectors were considered. They are presented for particular reactions in Appendix~B.
\indent
The acceptance for each reaction was determined for three different values of the bound states width $\Gamma$: 10MeV, 25MeV and 40MeV and for three models of nucleons Fermi momentum distributions inside $^{4}\hspace{-0.03cm}\mbox{He}$, $^{3}\hspace{-0.03cm}\mbox{He}$ or T which are in details described in Chapter~3.
\indent
The WASA acceptance as a function of the excess energy Q is presented for two reactions of free $^{4}\hspace{-0.03cm}\mbox{He}$-$\eta$ and $^{3}\hspace{-0.03cm}\mbox{He}$-$\eta$ production: $dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He} p \pi{}^{-}$ and $pd\rightarrow(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $d p \pi{}^{0}\rightarrow$ $d p \gamma \gamma$ in Fig.~\ref{reakcja_1} and Fig.~\ref{reakcja_3}, respectively.
The acceptance is almost constant as a function of excess energy and it is independent of the value of $\Gamma$ and model of Fermi momentum distribution within a few per cent.
For two other reactions situation is analogous.
\begin{figure}[h!]
\centering
\includegraphics[width=7.5cm,height=7.0cm]{gamma1.jpg} \hspace{-1.7cm} \includegraphics[width=7.5cm,height=7.0cm]{av18.jpg}
\vspace{-0.5cm}
\caption{Geometrical acceptances of the WASA-at-COSY detector in case of $dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He} p \pi{}^{-}$ reaction for the $\Gamma_{1}$=10 MeV width and AV18 and CDB-2000 models of nucleon Fermi momentum distribution inside $^{4}\hspace{-0.03cm}\mbox{He}$ (left) as well as for AV18 Fermi momentum distribution model and three different values of $\Gamma$ (right) \label{reakcja_1}.}
\end{figure}
\newpage
\begin{figure}[h!]
\centering
\includegraphics[width=7.5cm,height=7.0cm]{gamma3.jpg} \hspace{-1.7cm} \includegraphics[width=7.5cm,height=7.0cm]{anal.jpg}
\vspace{-0.5cm}
\caption{Geometrical acceptances in case of \mbox{$pd\rightarrow(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $d p \pi{}^{0}\rightarrow d p \gamma \gamma$} reaction for the $\Gamma_{3}$=40 MeV width and three different models of nucleon Fermi momentum distribution inside $^{3}\hspace{-0.03cm}\mbox{He}$ (left) as well as for analitic formula describing nucleon Fermi momentum distribution and three different values of $\Gamma$ (right).}\label{reakcja_3}
\end{figure}
\indent
The average values of WASA geometrical acceptances for registering the considered free reactions were calculated using following formula:
\begin{equation}
A=\frac{\sum_{Q}\frac{N_{acc}(Q)}{N_{gen}(Q)}}{N}
\label{eq:A}
\end{equation}
\noindent
where: \hspace{0.2cm} $N_{acc}(Q)$- the number of accepted events in a given interval of Q,\\
\hspace{1.0cm} $N_{gen}(Q)$- the number of generated events in a given interval of Q,\\
\hspace{1.0cm} $N$- the number of all ranges of summation. \\
\noindent
The obtained results for different gamma values and different models of nucleon momentum distributions are presented in following tables:
\vspace{-0.5cm}
\noindent
\begin{table}[h!]
\begin{footnotesize}
\begin{center}
\begin{tabular}{|c|c|c|c|}\hline
[MeV/c] &AV18 &CDB2000\\
\hline
$\Gamma1$ &0.5296 &0.5380 \\
$\Gamma2$ &0.5301 &0.5377 \\
$\Gamma3$ &0.5323 &0.5402 \\
\hline
\end{tabular}
\end{center}
\begin{center}
\caption{Average acceptances of WASA-at-COSY detector for the $dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He} p \pi{}^{-}$ reaction for three different $\Gamma$ values and AV18 and CDB-2000 models of nucleon momentum distribution inside $^{4}$\hspace{-0.03cm}$\mbox{He}$.}
\end{center}
\end{footnotesize}
\end{table}
\vspace{-1.4cm}
\noindent
\begin{table}[h!]
\begin{footnotesize}
\begin{center}
\begin{tabular}{|c|c|c|c|}\hline
[MeV/c] &AV18 &CDB2000\\
\hline
$\Gamma1$ &0.3785 &0.3889 \\
$\Gamma2$ &0.3758 &0.3877 \\
$\Gamma3$ &0.3749 &0.3866 \\
\hline
\end{tabular}
\end{center}
\begin{center}
\caption{Average acceptances of WASA-at-COSY detector for the $dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $d p p \pi{}^{-}$ reaction for three different $\Gamma$ values and AV18 and CDB-2000 models of nucleon momentum distribution inside $^{4}\hspace{-0.03cm}\mbox{He}$.}
\end{center}
\end{footnotesize}
\end{table}
\vspace{-1.4cm}
\noindent
\begin{table}[h!]
\begin{footnotesize}
\begin{center}
\begin{tabular}{|c|c|c|c|}\hline
[MeV/c] &anal. form. &AV18 &CDB2000\\
\hline
$\Gamma1$ &0.6175 &0.6071 &0.6139 \\
$\Gamma2$ &0.6187 &0.6091 &0.6130 \\
$\Gamma3$ &0.6188 &0.6067 &0.6135 \\
\hline
\end{tabular}
\end{center}
\begin{center}
\caption{Average acceptances of WASA-at-COSY detector for the $pd\rightarrow(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $d p \pi{}^{0}\rightarrow d p \gamma \gamma$ reaction for three different $\Gamma$ values and three different models of nucleon momentum distribution inside $^{3}\hspace{-0.03cm}\mbox{He}$.}
\end{center}
\end{footnotesize}
\end{table}
\vspace{-1.4cm}
\newpage
\noindent
\begin{table}[h!]
\begin{footnotesize}
\begin{center}
\begin{tabular}{|c|c|c|c|}\hline
[MeV/c] &anal. form. &AV18 &CDB2000\\
\hline
$\Gamma1$ &0.5054 &0.5059 &0.5052 \\
$\Gamma2$ &0.5083 &0.5029 &0.5042 \\
$\Gamma3$ &0.5054 &0.5070 &0.5045 \\
\hline
\end{tabular}
\end{center}
\begin{center}
\caption{Average acceptances of WASA-at-COSY detector for the $pd\rightarrow(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $p p p \pi{}^{-}$ reaction for three different $\Gamma$ values and three different models of nucleon momentum distribution inside $^{3}\hspace{-0.03cm}\mbox{He}$.}
\end{center}
\end{footnotesize}
\end{table}
\vspace{-1.0cm}
\indent
For the quasi-free reaction $dd\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}\rightarrow$ $ p_{sp}d p \pi{}^{-}$ the COSY-TOF acceptance was calculated for ten of beam momentum values for the range of $\vec{p}_{beam}$=2.6~GeV/c to 3.5~GeV/c. The excess energy distribution for \mbox{$nd\rightarrow(\mbox{T}$-$\eta)_{bs}$} reactions determined by the Fermi momentum distribution of neutron inside deuteron is presented in Fig.~\ref{Q} for ${p}_{beam}$ equal to 2.6 GeV/c, 3.1 GeV/c and 3.5 GeV/c.
For each case, the number of $nd\rightarrow(\mbox{T}$-$\eta)_{bs}$ generated events as a function of the excess energy Q is represented by solid line while the excess energy distribution for accepted events is shown by dashed line. The threshold deuteron beam momentum for the $dd\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}$ is equal 3.1 GeV/c for the case if the Fermi momentum in the beam deuteron is equal to 0.
\indent
Similarly like in case of free reactions, the COSY-TOF acceptance function is obtained by dividing the number of accepted events by the number of generated events for each of excess energy intervals. Respective results for three values of deuteron beam momentum are presented in Fig.~\ref{pbeam} (a), (b) and (c).
\begin{figure}[h!]
\centering
\includegraphics[width=8.0cm,height=7.5cm]{bezBW1.jpg} \hspace{-1.9cm} \includegraphics[width=8.0cm,height=7.5cm]{bezBWe.jpg} \includegraphics[width=8.0cm,height=7.5cm]{bezBWi.jpg}
\caption{The number of generated (solid) and accepted \mbox{$nd\rightarrow(\mbox{T}$-$\eta)_{bs}\rightarrow$ $d p \pi{}^{-}$} events (dashed) as a function of excess energy Q with respect to quasi-free $nd\rightarrow(\mbox{T}$-$\eta)_{bs}$ reaction at deuteron beam momentum ${p}_{beam}$=2.6 GeV/c (a), \mbox{${p}_{beam}$=3.1 GeV/c (b)} and \mbox{${p}_{beam}$=3.5 GeV/c} (c).\label{Q}}
\end{figure}
The acceptance of ejectiles registration in the quasi-free reaction is not constant function of excess energy. It decreases for Q values corresponding to the Fermi momentum of neutron in the deuteron beam equal to zero and results from the fact that proton spectator is not accepted by detector geometry if its Fermi momentum value in deuteron frame equals $p^{*}_{sp}$=0. For a comparison, Fig.~\ref{pbeam} (d) presents that the acceptance dependence of Q would be constant if the proton spectator was accepted.
\begin{figure}[h!]
\centering
\includegraphics[width=8.0cm,height=7.5cm]{cdbparis1.jpg} \hspace{-1.7cm}\includegraphics[width=8.0cm,height=7.5cm]{cdbparis1e.jpg} \includegraphics[width=8.0cm,height=7.5cm]{cdbparis1i} \hspace{-1.7cm}\includegraphics[width=8.1cm,height=7.8cm]{cdbparis1e_sp.jpg}
\caption{Geometrical COSY-TOF acceptances in case of the $dd\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}\rightarrow$ $ p_{sp}d p \pi{}^{-}$ reaction at ${p}_{beam}$=2.6 GeV/c (a), ${p}_{beam}$=3.1 GeV/c (b) and ${p}_{beam}$=3.5 GeV/c (c). For the simulations Paris model of nucleon Fermi momentum distribution inside deuteron and $\Gamma_{1}$=10 MeV bound state width and analitic formula describing nucleon Fermi momentum distribution inside T were used. Panel (d) represents the reaction acceptance for \mbox{${p}_{beam}$=3.1 GeV/c} with assumption that the detector acceptance for proton spectator registration equals 1.\label{pbeam}}
\end{figure}
\newpage
In order to determine the effective acceptance for registering the quasi-free \mbox{$dd\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}\rightarrow$ $ p_{sp}d p \pi{}^{-}$} reaction in the near to threshold Q range from -60~MeV to 20 MeV when using the TOF detector the following formula is used:
\begin{equation}
A_{eff}=A\frac {N_{(-60,20)}}{N_{gen}}
\end{equation}
\noindent
where: \hspace{0.2cm} $A$- the average acceptance given by formula~(\ref{eq:A}),\\
\hspace{1.0cm} $N_{gen}$- the number of generated events,\\
\hspace{1.0cm} $N_{(-60,20)}$- the number of generated events for Q$\in$(-60,20)~MeV.\\
\begin{figure}[h!]
\centering
\includegraphics[width=10.0cm,height=9.0cm]{Pbeam.jpg}
\caption{Effective acceptance for the registration of the quasi-free \mbox{$dd\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}\rightarrow$ $ p_{sp}d p \pi{}^{-}$} reaction near the $\eta$ production threshold (Q$\in$(-60,20)~MeV) as a function of beam momentum.\label{Pbeam}}
\end{figure}
The effective acceptance $A_{eff}$ was calculated for ten values of the beam momentum. The dependence $A_{eff}(p_{beam})$ is presented in Fig.~\ref{Pbeam}.
In the simulations of the \mbox{$dd\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}\rightarrow$ $ p_{sp}d p \pi{}^{-}$} reaction it is assumed that the square of invariant mass of T-$\eta$ nuclei is given by Breit-Wigner distribution. In this case an effective acceptance for the registration of the bound state decay products is calculated by formula:
\begin{equation}
A^{BW}_{eff}=A\frac {N^{BW}_{(-60,20)}}{N^{BW}_{gen}}
\end{equation}
\noindent
where: \hspace{0.2cm} $A$- the average acceptance given by formula~(\ref{eq:A}),\\
\hspace{1.0cm} $N^{BW}_{gen}$- the number of generated events accepted with probability
\hspace{1.0cm} calculated according to the Breit-Wigner distribution of $\sqrt{s_{nd}}$,\\
\hspace{1.0cm} $N^{BW}_{(-60,20)}$- the number of generated events for Q$\in$(-60,20)~MeV
\hspace{1.0cm} accepted with probability calculated according to the Breit-Wigner
\hspace{1.0cm} distribution of $\sqrt{s_{nd}}$\\
\noindent
and is presented in Fig.~\ref{Pbeam1} as a function of the beam deuteron momentum.
\begin{figure}[h!]
\centering
\includegraphics[width=10.0cm,height=9.0cm]{Pbeambw.jpg}
\caption{Effective acceptance for the registration of the quasi free \mbox{$dd\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}\rightarrow$ $ p_{sp}d p \pi{}^{-}$} reaction near the $\eta$ production threshold (Q$\in$(-60,20)~MeV) as a function of beam momentum assuming a Breit-Wigner distribution of $\sqrt{s_{nd}}$ for the bound state width $\Gamma$=10MeV. \label{Pbeam1}}
\end{figure}
From the dependence shown in above figure it results that the highest probability for the registration of considered quasi-free \mbox{$dd\rightarrow p_{sp}(p_{F}=0)(\mbox{T}$-$\eta)_{bs}\rightarrow$ $ p_{sp}d p \pi{}^{-}$} reaction is for the beam momentum $p_{beam}$=3.1~GeV/c corresponding to the \mbox{$dd\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}\rightarrow$ $ p_{sp}d p \pi{}^{-}$} reaction threshold whereas for the beam momentum above and below the threshold the effective acceptance decreases.
Above considerations were carried out for the Paris model of nucleon Fermi momentum distribution inside deuteron, $\Gamma_{1}$=10~MeV bound state width and analitic formula describing nucleon Fermi momentum distribution inside T. The calculations are consistent with the one for CD-Bonn model of nucleon momentum distribution inside deuteron with an accurancy better than 4\% and are independent of models of nucleon Fermi momentum distribution inside tritium.
\newpage
\pagestyle{fancy}
\fancyhf{}
\fancyhead[LE,RO]{\textbf{\thepage}}
\fancyhead[RE]{\small\textbf{{Summary and conclusions}}}
\newpage
\thispagestyle{plain}
\section {Summary and conclusions}
\vspace{0.5cm}
\noindent
The main aim of this thesis was to test the feasibility of the measurement of $\eta$-helium mesic nucleus production via reactions:\\
\noindent
$dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow$ $^{3}\hspace{-0.03cm}\mbox{He} p \pi{}^{-}$\\
$dd\rightarrow(^{4}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow d p p \pi{}^{-}$\\
$pd\rightarrow(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow d p \pi{}^{0} \rightarrow d p \gamma \gamma$\\
$pd\rightarrow(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow p p p \pi{}^{-}$,\\
\noindent
with WASA-at-COSY detector and test the feasibility of the $\eta$-T bound state production via reaction:\\
\noindent
$nd\rightarrow(\mbox{T}$-$\eta)_{bs}\rightarrow d p \pi{}^{-}$,\\
\noindent
realised through \mbox{$dd\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}\rightarrow$ $ p_{sp}d p \pi{}^{-}$} quasi-free reaction with \mbox{COSY-TOF} detection setup.
\indent
The reaction kinematics for free and quasi-free $\eta$-mesic bound states production as well as the spectator model assumptions were analysed and discussed. Moreover, the nucleon momentum distribution inside $^{4}\hspace{-0.03cm}\mbox{He}$, $^{3}\hspace{-0.03cm}\mbox{He}$, T and d, was presented for different models based on the analytic formulas and theoretical analysis for each of nuclei. Numerical data for those distributions are presented in Appendix~A.
The simulation were carried out and acceptances of \mbox{WASA-at-COSY} detection systems for free processes were calculated and compared for three assumed values of bound states width as well as for three different models of nucleon Fermi momentum distribution. In case of quasi-free reaction the effective \mbox{COSY-TOF} acceptance as a function of beam momentum was determined.
\indent
The simulation results show that the acceptance as function of excess energy for the free reactions of $\eta$-helium production is in good approximation constant near the $\eta$ production threshold and is independent of the bound state width value and model of Fermi momentum distribution. The calculations present that the absolute value of acceptance depends on the reaction channel. The most probable is registering of particles outgoing from the \mbox{$pd\rightarrow(^{3}\hspace{-0.03cm}\mbox{He}$-$\eta)_{bs}\rightarrow d p \pi{}^{0} \rightarrow d p \gamma \gamma$} reaction. The average value of WASA geometrical acceptance is then equal to A=0.61.
\indent
For the quasi-free reaction $dd\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}\rightarrow$ $ p_{sp}d p \pi{}^{-}$ of $\eta$-tritium formation the \mbox{COSY-TOF} effective acceptance is dependent on the beam momentum value. It reaches the highest value for the beam momentum of $p_{beam}$=3.1~GeV/c corresponding to the \mbox{$dd\rightarrow p_{sp}(p_{F}=0)n d\rightarrow p_{sp}(p_{F}=0)\mbox{T}$-$\eta$} reaction threshold. Thus the measurement of quasi-free reaction products is the most efficient at the $\eta$ production threshold.
\indent
In this thesis the geometrical acceptance for particular reactions was calculated. In the future, the efficiency of registration for the outgoing particles in each of reaction will be determined. \\
\indent
Finally the experiments in which $\eta$-nuclei will be searched are interesting because of following issues:
\begin{enumerate}
\item Potential of discovering of $\eta$-mesic bound states. Observation of that state would allow to investigate interactions between the $\eta$ meson and the nucleons inside a nuclear matter.
\item $\eta$-mesic bound systems would provide the information about $N^{*}$(1535)~\cite{Jido} resonance and $\eta$ meson properties in nuclear matter~\cite{InoueOset}.
\item The existence of the bound states could give a possibility to study a flavour singlet component of the quark-gluon wave function of the $\eta$ meson~\cite{BassTom, BassThomas}.
\end{enumerate}
\indent
The simulations presented in this thesis show that the $\eta$-helium nuclei measurement can be carried out at WASA-at-COSY detection setup, while the $\eta$-tritium bound states might be searched at COSY-TOF detector. As a result of simulation it is established that the most efficient measurement of \mbox{$dd\rightarrow p_{sp}(\mbox{T}$-$\eta)_{bs}\rightarrow$ $ p_{sp}d p \pi{}^{-}$} reaction at COSY-TOF detector can be done at the beam momentum of 3.1~GeV/c.
\newpage
\thispagestyle{plain}
\normalsize
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"redpajama_set_name": "RedPajamaArXiv"
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IJCI
E-gate
Scientific and Advisory Services Office
Digital Contents
Centers & Dep
Quality Assurence
The University's President Visits College of Engineering.
The University's President Visits College of Engineering
The president of University of Information Technology and Communication Prof. Dr. Abbas Muhsin Al-Bakri has visited the main exams' halls in college of engineering. The president, alongside his tour to the college's study halls and labs through which was accompanied by the college's dean's assistant and heads of departments; has emphasized on the necessity of providing all suitable atmosphere for students and all main needs for taking the final examinations process to success state.
Al- Bakri has also encouraged students to keep perseverance and reach excellence in their study years and succeed their final exams, which is considered a cutting edge stage for reaching next studying grade.
The University's president has also pointed to many important things such as presenting at the exact time of exams and for the faculty to make clear and specific questions. And mentioned that the university's direction is to progress in the Information technology and communications engineering fields, which are continuously evolving sciences, for which all the curricula should keep up, and the latter exams must develop students' scientific and practical abilities.
University of alkafeel
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"redpajama_set_name": "RedPajamaCommonCrawl"
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\section{Introduction}
The nonlocality is treated now as an important ingredient in field theory models. Being initially introduced in order to take into account finite-size effects in phenomenology allowing to rule out ultraviolet divergences \cite{Efimov}, it began recently to acquire strong interest within other contexts, especially, within gravity, where there is a strong hope that namely nonlocal extension could allow to construct a gravity model both renormalizable (or even ultraviolet finite) and ghost-free, see discussion in \cite{Modesto}. The key idea of nonlocal field theories looks like follows. While the quadratic action of usual higher-derivative theories is described by a polynomial function of d'Alembertian operator which can be expanded in primitive multipliers, {and it} allows in arising of new, ghost degrees of freedom \cite{Hawking}, one can consider a class of theories where, instead of the polynomial function of $\Box$, the quadratic action is characterized by an essentially non-polynomial, so-called entire function of $\Box$, for example, the exponential one, which does not admit expansion in primitive multipliers and hence does not generate new {degrees} of freedom, see \cite{Modesto} and references therein. Various aspects of nonlocal field theories have been studied, including the exact solutions within the gravitational (mostly cosmological) context (see f.e. \cite{Biswas}) and explicit calculations of loop corrections in usual and supersymmetric theories \cite{quantNL}. Therefore, it is natural to expect that nonlocality can imply interesting physical effects within other contexts as well.
In this letter, we propose a generalization of the Julia-Toulouse (JT) mechanism to a nonlocal case. Indeed, it is well known \cite{CW} that the Julia-Toulouse mechanism is based on the coupling of the gauge field to some extra fields (topological defects) represented by some sources $J^{\mu}$. The idea behind {the} JT mechanism is that a proliferation of the topological defects in a system, such that they become dynamical fields (i.e. their condensation), drives the {system} to a phase transition. As it will be formally presented in the next section, superconductors can be seen as a good example to {illustrate} this idea. In the case of a superconductor, a proliferation of defects (vortices) can drive the system from a superconductivity state to a free Maxwell theory. In order to achieve this result we introduce a so-called activation term $J^{\mu}{\cal O}J_{\mu}$, and the integration over the topological defects implies in the arising of new terms modifying the {original} gauge theory. Initially, in \cite{CW} and further in \cite{CWours}, the operator ${\cal O}$ was suggested to {describe} only the low- energy fluctuations, that is, being proportional to an unit operator, thus giving a Thirring-like interaction. In this paper, we take into account not only low energy fluctuation but we also consider the UV fluctuations and show that as a {consequence,} the condensation of topological defects drives the Maxwell electrodynamics to a non-local Podolsky electrodynamics.
This letter is organized as follows: in the section \ref{secI}, we, basing on \cite{Braga:2016atp}, provide a general description of the condensation of topological defects in regular superconductors;
in the section \ref{emergentnonlocalterm}, we show how the mechanism used to describe superconductors can be used to obtain non-local Podolsky electrodynamics; in the section \ref{sec-cs}, we show how the non-local JT mechanism can also be applied in the Chern-Simons theory to generate a higher-derivative CS theory; finally, in the section \ref{sec-com} we present our comments and conclusions.
\section{Phase transition and the condensation of topological defects}
\label{secI}
In this section we {describe} the mechanism presented in \cite{Braga:2016atp} to explain how a condensation of topological defects can drive a system to a phase transition.
{Let us} consider an Euclidean action describing the electromagnetic field interacting with an external source with electric charge $q$
\begin{align}
\label{maxwell}
S_{em} = \int d^4x \left( \frac{1}{4} F_{\mu\nu}F_{\mu\nu} - iqA_{\mu}J_{\mu} \right)
\end{align}
where $F_{\mu\nu} = \partial_{\mu}A_{\nu} - \partial_{\nu}A_{\mu}$ and $J_{\mu}$ is a classical current. The partition function of the system coupled with an external auxiliary current $j_{\mu}$, carrying charge $e$, summed over the classical configurations of the external sources $J_{\mu}$ reads
\begin{widetext}
\begin{eqnarray}
\label{pathint-maxwell}
Z[j]&=&\sum_{J} \int {\cal D} A \delta[\partial_{\mu}J^{\mu}] e^{-\int d^4x \left( \frac{1}{4} F_{\mu\nu}F_{\mu\nu} - iqA_{\mu}J_{\mu}\right)} e^{-ie\int d^4x \; A_{\mu}j_{\mu} }\nonumber\\
&=& \sum_{J} \int {\cal D} A {\cal D} \theta e^{-\int d^4x \left( \frac{1}{4} F_{\mu\nu}F_{\mu\nu} - iq \left( A_{\mu} + \frac{1}{q} \partial_{\mu}\theta \right) J_{\mu}\right)} e^{-ie\int d^4x \; A_{\mu}j_{\mu} }
\label{pathint-maxwell-2}
\end{eqnarray}
\end{widetext}
In order to maintain {explicitly} the gauge invariance we inserted a delta function {requiring} the classical source to be conserved and exponentiated it with the help of an auxiliary field $\theta$. The gauge symmetry is realized as
\begin{align}
\label{gaugesymmetry}
A_{\mu} &\rightarrow A_{\mu} + \partial_{\mu} \chi \nonumber\\
\theta &\rightarrow \theta - q\chi
\end{align}
As a consequence of gauge invariance (current conservation) we have that
\begin{equation}
J^\mu(x)=\int d\tau\frac{d y^\mu}{d\tau}\delta^4(x-y(\tau))
\label{delta}
\end{equation}
The summation over $J$ in \eqref{pathint-maxwell-2} represents the sum over all the possible worldlines $y(\tau)$ of charges.
In \eqref{pathint-maxwell-2} we did not consider {dynamics of charges yet}, but soon we will supplement the action with {the corresponding term given by $S(y(\tau))$}. For many point charges we have a sum over the worldlines of all the charges. For a continuous distribution of charges we would have a continuous source, whose sum over different ensemble configurations is defined by a path integral weighted by an action $S(J)$. The condensation is an operation that maps an ensemble of 1-currents into an ensemble of 1-forms. This operation specifies a physical process that connects different theories, describing the system in different phases. For example, in \eqref{pathint-maxwell-2} if we would have $J_{\mu} =0$ as the only configuration this would give us the free Maxwell theory. Another example is to consider $J_{\mu}$ as a continuous field $(\sum_{J} \rightarrow \int {\cal D} J)$, as a result we have that $J_{\mu}$ turns into a Lagrange multiplier forcing the gauge field to vanish, which is just the Meissner effect in a perfect superconductor (with zero penetration {length}).
\noindent Supplementing \eqref{pathint-maxwell-2} with contact terms to the classical current. The contact terms are on the action $S_{J}$. The new partition function reads
\begin{widetext}
\begin{align}
\label{genfunc}
Z[j] = \sum_{J} \int {\cal D} A {\cal D} \theta e^{-\int d^4x \left( \frac{1}{4} F_{\mu\nu}F_{\mu\nu} - iq \left( A_{\mu} + \frac{1}{q} \partial_{\mu}\theta \right) J_{\mu}\right)} e^{-ie\int d^4x \; A_{\mu}j_{\mu} }e^{-S_{J}}
\end{align}
\end{widetext}
\noindent The allowed local terms for the current looks like:
\begin{align}
\label{Seta}
S_{J} = \frac{1}{2m^2} J_{\mu}J^{\mu} + \frac{1}{2m^2 m^2_1} J_{\mu}\Box J^{\mu} + \cdots
\end{align}
This is a derivative expansion where the first term represents the lowest energy fluctuation of $J_\mu$. From \eqref{delta}, {one can express the current} as $J_{\mu}=\epsilon_{\mu\nu\lambda\rho}\partial^{\nu}\Sigma^{\lambda\rho}$.
In this sense $J_{\mu}J^{\mu}$ can be {treated} as kinetic term. Considering only the low energy fluctuations in \eqref{Seta} in the condensate phase and integrating \eqref{genfunc} in $J$ we have
\begin{widetext}
\begin{align}
\label{dilutecharges3}
Z[j] = \int {\cal D} A \int {\cal D} \theta\; e^{-\int d^4x \left( \frac{1}{4} F_{\mu\nu}F^{\mu\nu} - \frac{q^2m^2}{2}\left( A_{\mu} + \frac{1}{q} \partial_{\mu}\theta\right)^2 \right)} e^{-ie\int d^4x \; A_{\mu}j_{\mu} }
\end{align}
\end{widetext}
Thus we have {obtained} the action for the electromagnetic response in a superconductor with penetration length $\sim 1/m$. The condensation of {currents} drove the system to a phase transition. In \cite{Braga:2016atp}, the authors showed that the dilution/condensation process can also be described in a dual point of view. The dual of the charge condensation described here is the dilution of the equivalent defects (vortices) in the superconductor. Meaning that if the vortices dilute ({and} charge condensation occurs), the system becomes a perfect superconductor as in \eqref{dilutecharges3} or if the vortices condensate ({and} charge dilution takes place) we recover the free Maxwell theory. As it is known, the superconductivity phase of a material can be {destroyed} by proliferation {of vortices}, and, as it is shown in \cite{Braga:2016atp}, the picture presented here, describes this scenario. The dual picture of \eqref{dilutecharges3} can be obtained by introducing
\begin{equation}
\int {\cal D}\eta~\delta[J^\mu(x)-\eta^\mu(x)]=1
\label{delta1}
\end{equation}
in the path integral \eqref{genfunc}, using the Poisson identity
\begin{equation}
\label{poissonid}
\sum_J \delta[J^\mu(x)-\eta^\mu(x)]=\sum_Ke^{i2\pi\int d^4x\eta^\mu K_\mu}
\end{equation}
and by integrating $\eta_\mu$ we obtain
\begin{widetext}
\begin{align}
\label{dilutecharges3dual}
Z[j] =\sum_K \int {\cal D} A \int {\cal D} \theta\; e^{-\int d^4x \left( \frac{1}{4} F_{\mu\nu}F^{\mu\nu} - \frac{q^2m^2}{2}\left( A_{\mu} + \frac{1}{q} \partial_{\mu}\theta+\frac{2\pi}{q}K_\mu\right)^2 \right)} e^{-ie\int d^4x \; A_{\mu}j_{\mu} }
\end{align}
\end{widetext}
From \eqref{dilutecharges3dual} it can be seen that, if $K$ becomes a continuous field, {the} integration over $K$ drives the system to a free Maxwell theory. The Poisson identity \eqref{poissonid} is the key idea to implement and to understand the dual scenario: from \eqref{poissonid}, as an example, it can be seen that if we have $J_\mu=0$ as the only configuration, this identity will be reduced to $\delta(\eta_\mu)=\int{\cal D}K e^{i2\pi\int d^4x\eta^\mu K_\mu}$. This means that for a charge dilution ($J_\mu=0$) the result will be that the $K$ condensates $(\sum_K\to\int{\cal D}K)$. If the $J$ proliferates $(\sum_J\to\int{\cal D}J)$ this makes the l.h.s. of \eqref{poissonid} {to go} to $1$, forcing $K=0$ on the {r.h.s.} of the equality. This points that $K_\mu$ are defects which are dual to the charges $J_\mu$. Due to \eqref{delta1}, the dual version of \eqref{Seta} reads
\begin{align}
\label{Seta1}
S_{\eta} = \frac{1}{2m^2}\eta_{\mu}\eta^{\mu} + \frac{1}{2m^2 m^2_1}\eta_{\mu}\Box \eta^{\mu} + \cdots
\end{align}
and in order to obtain \eqref{dilutecharges3dual} we have {only} considered the lowest energy fluctuation in $\eta$ as in the previous case with $J$. As it was pointed before, if $K$ condensates we have free Maxwell theory. In the next section we will show that {for the case of} high energy fluctuations {of} $\eta$, even when $K$ condensates, local Maxwell theory will not be recovered anymore.
\section{Podolsky electrodynamics as an emergent theory}
\label{emergentnonlocalterm}
From the previous section, it can be seen that by considering low energy fluctuations of $\eta_\mu$ we are able to describe the electromagnetic response in a superconductor. In this section, our discussion begins around the equation \eqref{Seta1} and explore what is the gauge emergent system by considering high energy fluctuations of $\eta_\mu$. Consider high energy fluctuations of $\eta_\mu$ means that
\begin{eqnarray}
\label{Seta2}
S_{\eta}&=&\frac{1}{2m^2} \eta_{\mu}\eta^{\mu} + \frac{1}{2m^2 m^2_p} \eta_{\mu}\Box \eta^{\mu} + \cdots\nonumber\\
&=& \frac{1}{2m^2} \eta_{\mu}\left[\sum_{n=0}^\infty\left(\frac{\Box}{m^{2}_p}\right)^n\right]\eta_{\mu}\nonumber\\
&=& \frac{1}{2m^2} \eta_{\mu}{\cal F}\left({\Box}/{m^{2}_p}\right)\eta_{\mu}
\end{eqnarray}
where $m_p$ stands for the Podolsky mass as in \cite{Bonin:2019xss}. Then the integration in $\eta_\mu$ generates:
\begin{widetext}
\begin{align}
Z[j] =\sum_K \int {\cal D} A \int {\cal D} \theta\; e^{-\int d^4x \left( \frac{1}{4} F_{\mu\nu}F^{\mu\nu} - \frac{q^2m^2}{2{\cal F}\left({\Box}/{m^{2}_p}\right)}\left(A_{\mu} + \frac{1}{q} \partial_{\mu}\theta+\frac{2\pi}{q}K_\mu\right)^2 \right)} e^{-ie\int d^4x \; A_{\mu}j_{\mu} }
\end{align}
\end{widetext}
At this point, we will redefine the gauge field for $A'_\mu=A_{\mu} + \frac{1}{q} \partial_{\mu}\theta+\frac{2\pi}{q}K_\mu$. This redefinition maintains the electromagnetic field strength tensor expression preserved. The action then reads
\begin{eqnarray}
\label{themodel}
S&=&\int d^4x \left(\frac{1}{4} F_{\mu\nu}F^{\mu\nu} - A'_\mu\frac{q^2m^2}{2{\cal F}\left({\Box}/{m^{2}_p}\right)}A'_\mu \right
\end{eqnarray}
It is interesting to note the following effect.
Under an appropriate change of variables, the nonlocality in the kinetic term can be transferred to the vertices (or mass term), and vice versa. It can be done in the following manner.
Let us consider the Lagrangian
\begin{eqnarray}
{\cal L}&=&\frac{1}{2}\partial_m\phi e^{\frac{\Box}{\mu^2}}\partial^m\phi-V(\phi).
\end{eqnarray}
Here, the nonlocality is concentrated in a kinetic term.
Let us do the change of variables
\begin{eqnarray}
e^{\frac{\Box}{2\mu^2}}\phi\to\tilde{\phi}.
\end{eqnarray}
Our Lagrangian takes the form
\begin{eqnarray}
{\cal L}&=&\frac{1}{2}\partial_m\tilde{\phi}\partial^m\tilde{\phi}-V(e^{-\frac{\Box}{2\mu^2}}\tilde{\phi}).
\end{eqnarray}
So, the potential becomes nonlocal instead of the kinetic term (in certain cases when the kinetic term looks like $\phi\Box\hat{T}\phi$, and the potential term looks like $((\hat{T})^{1/2}\phi)^n$, with $\hat{T}$ is an operator introducing the nonlocality, f.e. $\hat{T}=e^{\frac{\Box}{2\mu^2}}$ as in the example above, we can remove the nonlocality both from kinetic and potential term, but these cases are trivial).
The similar situation takes place for other field theory models, including the electromagnetic field. The model (\ref{themodel}), under the replacement ${\cal F}\left({\Box}/{m^{2}}\right)^{-1/2}A'_\mu\to\tilde{A}_{\mu}$ becomes
\begin{eqnarray}
\label{themodel1}
S=\int d^4x \left(\frac{1}{4} F_{\mu\nu}{\cal F}\left({\Box}/{m^{2}_p}\right)F^{\mu\nu} - \frac{q^2m^2}{2}A'_\mu A'_\mu \right)
\end{eqnarray}
We note that within all these our replacements by the rule $\phi\Box\hat{L}\phi$, with $\hat{L}$ is the nonlocal operator, and the same rule for $A_{\mu}$, no extra contributions to the effective actions are generated. Indeed, when we carry out these transformations, although there are nonlocal, they are linear in fields, so, in the generating functional we get only the extra multiplier $\det\hat{L}^{1/2}$, and since it does not depend on any fields, it yields only a field-independent additive term in the effective action which clearly can be neglected.
So, we generated the essentially non-local Podolsky electrodynamics with the action
\begin{widetext}
\begin{align}
\label{themodel1a}
Z[j] =\sum_K \int {\cal D} A \int {\cal D} \theta\; e^{-\int d^4x \left(\frac{1}{4} F_{\mu\nu}F^{\mu\nu}+\frac{1}{4m_p^2}\partial^\mu F_{\mu\nu}\left[\sum\limits_{n=0}^\infty\left(\frac{\Box}{m^{2}_p}\right)^n\right]\partial_\beta F^{\beta\nu}- \frac{q^2m^2}{2}A'_\mu A'_\mu \right)}\cdot e^{-ie\int d^4x \; A_{\mu}j_{\mu} }
\end{align}
\end{widetext}
where an integration by parts was used to obtain the result. It can be seen from \eqref{themodel1a} that even if $K$ condensates, {which corresponds to} integration over $K$, the Podolsky term will not vanish. It is worth mention that if we have considered only the first two terms in the expansion \eqref{Seta2}, the resulting action would be the local Podolsky action, which it would be equivalent to only consider the term $n=0$ is the sum in \eqref{themodel1a}. Therefore we show that the Podolsky electrodynamics can be obtained using a mechanism that it was originally used to describe phase transitions due to the condensation/proliferation of topological defects.
It is interesting to note that the higher-derivative Podolsky term can be generated as well within the usual perturbative approach. Let us start with the {usual} Lagrangian of the spinor field coupled to the electromagnetic one:
\begin{equation}
{\cal L}=\bar{\psi}(i\partial\!\!\!/-eA\!\!\!/-m)\psi.
\end{equation}
The one-loop effective action of the gauge field is immediately written in the form of the fermionic determinant:
\begin{equation}
\Gamma^{(1)}=i{\rm Tr}\ln(i\partial\!\!\!/-eA\!\!\!/-m).
\end{equation}
We consider the simplest contribution to it generated by the two-point function of $A^{\mu}$:
\begin{equation}
\Gamma^{(1)}_2=-\frac{e^2}{2}\int d^4p A_{\mu}(-p)\Pi^{\mu\nu}(p)A_{\nu}(p),
\end{equation}
where
\begin{equation}
\label{trace}
\Pi^{\mu\nu}(p)={\rm tr}\int\frac{d^4k}{(2\pi)^4}\gamma^{\mu}\frac{1}{k\!\!\!/-m}\gamma^{\nu}\frac{1}{k\!\!\!/+p\!\!\!/-m}.
\end{equation}
It is well known that the effective action itself is nonlocal being an infinite series in derivatives of the external fields, or as is the same, in the external momentum $p$. While the contribution of the second order in an external momentum became a paradigmatic result in QED describing the wave function renormalization of the gauge field, the higher-order results have not been discussed up to now. So, we expand (\ref{trace}) up to the fourth order and find
\begin{eqnarray}
\Pi_4^{\mu\nu}(p)&=&{\rm tr}\int\frac{d^4k}{(2\pi)^4}\gamma^{\mu}\frac{1}{k\!\!\!/-m}\gamma^{\nu}\frac{1}{k\!\!\!/-m}p\!\!\!/\frac{1}{k\!\!\!/-m}\times\nonumber \\&\times& p\!\!\!/\frac{1}{k\!\!\!/-m}p\!\!\!/\frac{1}{k\!\!\!/-m}p\!\!\!/\frac{1}{k\!\!\!/-m}.
\end{eqnarray}
\vspace*{1mm}
The trace and integral can be calculated explicitly. We arrive at
\begin{eqnarray}
\Pi_4^{\mu\nu}(p)&=&\frac{4p^2}{15m^2(4\pi)^2}(p^{\mu} p^{\nu}-p^2\eta^{\mu\nu}).
\end{eqnarray}
The corresponding contribution to the effective action is
\begin{eqnarray}
\Gamma^{(1)}_{2,4}=-\frac{e^2}{15m^2(4\pi)^2}F_{\mu\nu}\Box F^{\mu\nu}.
\end{eqnarray}
This term is finite as it must be. It has just the desired Podolsky form. In principle, the contributions to the effective action involving sixth and higher even orders in momenta can be obtained as well, so, one can write down the complete one-loop two-point function as
\begin{eqnarray}
\Gamma^{(1)}_2=e^2F_{\mu\nu}\left(\sum\limits_{n=0}^{\infty}c_n(\frac{\Box}{m^2})^n\right) F^{\mu\nu},
\end{eqnarray}
where the zero order is the known renormalized QED result. In principle, the function
$$
f(\Box)=\sum\limits_{n=0}^{\infty}c_n\left(\frac{\Box}{m^2}\right)^n
$$
can be defined, where $c_n$ are some numbers, however, apparently {this function} can be found only order by order but not in the closed form.
\section{Higher-derivative Chern-Simons term}\label{sec-cs}
In this section, we show that by extending the mechanism presented in the section \ref{secI}, for a Chern-Simons (CS) theory, and following the prescription in the section \ref{emergentnonlocalterm}, the corresponding emergent theory, obtained along the same lines as Eq. \eqref{themodel1}, is a {higher-derivative} CS theory. For the CS theory the analog of \eqref{maxwell} is
\begin{equation}
\label{csaction}
S_{cs} = \int d^3x \left( \frac{\kappa}{2} \epsilon_{\mu\nu\rho} A_\mu\partial_\nu A_\rho - iqA_{\mu}J_{\mu} \right),
\end{equation}
and, {since} the CS action is gauge invariant, \eqref{delta} still holds. Following the prescriptions presented in the previous sections we arrive at
\begin{eqnarray}
S_{cs} &=& \int d^3x \Big( \frac{\kappa}{2} \epsilon_{\mu\nu\rho} A_\mu\partial_\nu{\cal F}\left({\Box}/{m^{2}_{cs}}\right) A_\rho-\nonumber\\ &-&
\frac{q^2m^2}{2}A'_\mu A'_\mu \Big).
\end{eqnarray}
This is the analog of \eqref{themodel1} for the CS theory.
\section{Comments and conclusions}\label{sec-com}
We have succeeded to generalize the Julia-Toulouse mechanism {to} a case of {a} nonlocal contact term. One should note that {\it a priori}, there are no restrictions on the form of the contact term within this approach. We demonstrated explicitly that in this case, one can generate a nonlocal generalization of the electrodynamics whose action is an infinite series in derivatives, so that one has, besides of the usual Maxwell term, also the Podolsky term, {and higher-order terms}. We showed explicitly that the Podolsky term can be generated as a quantum correction as well being finite, so, we can see that perturbative and non-perturbative approaches for obtaining new terms are equivalent in a certain sense as it has been claimed in \cite{CWours}. Actually, we demonstrated that the Julia-Toulouse approach opens {broad} possibilities for obtaining new effective theories with higher-derivative operators. It could be interesting to generalize this approach for Lorentz-breaking case since earlier, the Julia-Toulouse methodology has been successfully applied in the Lorentz-breaking case in {the} three-dimensional theory \cite{CWours}. Especially, it is interesting to study the impacts of the dimension-six terms considered in \cite{Ferr}, within the Julia-Toulouse approach. Besides the possible applications within Lorentz symmetry breaking scenarios, this approach can also be used to show how magnetic permeability arises from a condensation of topological defects. We expect to do these studies in forthcoming papers.
\vspace*{1mm}
\section*{Acknowledgments}
The authors thank CNPq for financial support. The work by A.Yu.P. has been supported by CNPq project 303783/2015-0. P. J. Porf\'{i}rio would like to thank the Brazilian agency CAPES for financial support (PDE/CAPES grant, process 88881.17175/2018-01) and Department of Physics and Astronomy, University of Pennsylvania, for the hospitality.
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{
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Erynnia condecens är en tvåvingeart som beskrevs av Henry J. Reinhard 1968. Erynnia condecens ingår i släktet Erynnia och familjen parasitflugor.
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{
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\section{Introduction}\label{sec:introduction}
\paragraph{Model-Based Development of Hybrid Systems}
The demand for quality assurance of \emph{cyber-physical systems (CPS)} is
ever-rising, now that computer-controlled artifacts---cars, aircrafts,
and so on---serve diverse safety-critical tasks
everywhere in our daily lives. In the industry practice of CPS design, deployment
of \emph{model-based development (MBD)} has become a norm.
In MBD, (physical and costly) testing workbenches are replaced
by (virtual and cheap) \emph{mathematical models};
and this reduces by a great deal the cost of running
a \emph{development cycle}---design, implementation, evaluation, and redesign.
One of the distinctive features of CPS is that they are \emph{hybrid systems}
and combine discrete and continuous
dynamics. For MBD of such systems the software \emph{Simulink} has emerged as an
industry standard. In Simulink a designer models a system using block
diagrams---a formalism strongly influenced by \emph{control theory}---and
runs \emph{simulation}, that is, numerical solution of the system's dynamics.
\paragraph{Falsification}
The models of most real-world hybrid systems are believed to be beyond
the reach of formal verification. While this is certainly the case with
systems as big as a whole car,
a single component of it (like automatic transmission or an engine
controller) overwhelms the scalability of
the state-of-art formal verification techniques, too.
What is worse, hybrid
system models tend to have \emph{black-box components}. An example is
fuel combustion in an engine. Such chemical reactions are not easy to
model with
ODEs, and are therefore commonly represented in a Simulink model
by a \emph{look-up table}---a big table of values obtained by physical measurements~\cite{DBLP:conf/hybrid/JinDKUB14,HoxhaAF14arch1}.
The lack of structure in a look-up table poses a
challenge to formal verification: each entry of the table
calls for separate treatment; and this
easily leads to state-space explosion.
Under such circumstances, \emph{falsification} by
stochastic optimization has proved to be a viable
approach to quality
assurance~\cite{DBLP:conf/tacas/AnnpureddyLFS11,DBLP:conf/hybrid/JinDKUB14,HoxhaAF14arch1}. The
problem is formulated as follows:
\begin{quote}
\underline{\bfseries The falsification problem}
\begin{tabular}{ll}
\textbf{Given:}
& a \emph{model} $\mathcal{M}$ (a function from an input signal \\
& to an output signal), and\\
& a \emph{specification} $\varphi$ (a temporal formula),\\
\textbf{Answer:}
& a \emph{critical path}, that is, an input signal $\sigma_{\mathrm{in}}$ such\\
& that the output $\mathcal{M}(\sigma_{\mathrm{in}})$ does not satisfy $\varphi$
\end{tabular}
\includegraphics[clip,trim=0cm 23.5cm 24.8cm 0cm,width=.24\textwidth]{pics/falsification.pdf}
\end{quote}
Unlike \emph{testing} or \emph{monitoring}---where input $\sigma_{\mathrm{in}}$ is given and
we check if $\mathcal{M}(\sigma_{\mathrm{in}})\models \varphi$---a
falsification solver employs stochastic optimization techniques (like
the Monte-Carlo ones) and iteratively searches for a falsifying input
signal
$\sigma_{\mathrm{in}}$.
Falsification is a versatile tool in MBD of hybrid systems. It is
capable of searching for counterexamples, hence revealing potential
faults in the design. One can also take, as a specification $\varphi$,
the negation $\lnot \psi$ of a desirable property $\psi$; then
successful falsification amounts to \emph{synthesis} of an input signal that
satisfies $\psi$. Stochastic optimization used in falsification
typically does not rely on the internal structure of models, therefore the
methodology is suited for models with black-box
components. Falsification is fairly scalable, making it
a realistic option in
the industrial MBD scenarios; see e.g.~\cite{HoxhaAF14arch1,DBLP:conf/hybrid/JinDKUB14}.
The current work aims at enhancing falsification solvers, notable among which are
S-TaLiRo~\cite{DBLP:conf/tacas/AnnpureddyLFS11}
and
BREACH~\cite{DBLP:conf/cav/Donze10}.
An obvious way to do so is via improvement of stochastic optimization;
see e.g.~\cite{Sankaranarayanan:2012:FTP:2185632.2185653,Zutshi:2014:MSC:2656045.2656061}. Here we take a different, logical approach.
\paragraph{Robustness in Metric Temporal Logics}
Let us turn to a formalism in which a specification
$\varphi$ is expressed.
\emph{Metric interval temporal logic}
($\textbf{MITL}$)~\cite{DBLP:dblp_journals/jacm/AlurFH96},
and its adaptation
\emph{signal temporal logic}
($\textbf{STL}$)~\cite{DBLP:conf/formats/MalerN04},
are standard temporal logics for (continuous-time) signals.
However their conventional
semantics---where satisfaction is Boolean---is not suited for
falsification by stochastic optimization.
This is because a formula $\varphi$, no matter if it is
\emph{robustly} satisfied and \emph{barely} satisfied, yields the same
truth value (``true''), making it not amenable to hill climb-style
optimization.
It is the introduction of \emph{robust semantics} of
$\textbf{MITL}$~\cite{DBLP:journals/tcs/FainekosP09} that set off the idea of falsification by
optimization. In robust semantics, a signal $\sigma$ and a
formula $\varphi$ are assigned a continuous truth value $\Robust{\sigma}{\varphi}\in{\mathbb{R}}$
that designates how robustly the formula is satisfied. Such ``robustness
values'' constitute a sound basis for stochastic optimization.
\begin{wrapfigure}[10]{r}{0pt}
\centering
\begin{tabular}{c}
\includegraphics[width=.3\textwidth,natwidth=640,
natheight=384]{pics/s_rob.pdf}
\\[-2.5em]
\includegraphics[width=.3\textwidth,natwidth=640,
natheight=384]{pics/t_rob.pdf}
\end{tabular}
\end{wrapfigure}
The original
robust semantics in~\cite{DBLP:journals/tcs/FainekosP09} is concerned with
\emph{space} robustness: for example, the truth values of
$\DiaOp{[0, 10]}(v \geq 80)$ (``the velocity reaches 80 km/h within 10 sec.'')
are $20$ and $0$, for the green and red signals on the right. Therefore
space
robustness is a ``vertical margin'' between a signal and a
specification. An efficient algorithm is proposed in~\cite{DBLP:conf/cav/DonzeFM13} for computing this
notion of robustness.
The notion of robustness is extended
in~\cite{DBLP:conf/formats/DonzeM10} to take \emph{time} robustness also
into account. Consider the same specification $\DiaOp{[0, 10]}(v \geq
80)$ against the green and red signals on the right. The green one is
more robust since it reaches 80 km/h much earlier than the deadline (10
sec.), while the red one barely makes the deadline.
The current work continues this line of work, with the slogan that
\emph{expressivity of temporal logic should help falsification}.
With more expressivity, a designer's concerns that were
previously ignored (much like time robustness was ignored
in~\cite{DBLP:journals/tcs/FainekosP09}) come to be reflected in the
continuous truth value. The latter will in turn help stochastic
optimization by giving additional ``hints.'' We however are in a
\emph{trade-off} situation: the more expressive a logic is, the more expensive
computation of truth values is in general.
\paragraph{Contributions} We aim at: a good
balance
in the last trade-off between expressivity and computational cost; and thereby
enhancing falsification solvers by giving
more ``hints'' to stochastic optimization procedures. Our technical
contributions are threefold.
\textbf{The logic $\textbf{AvSTL}$.} We introduce \emph{averaged STL} ($\textbf{AvSTL}$); it is an
extension of $\textbf{STL}$~\cite{DBLP:conf/formats/MalerN04} by
so-called \emph{averaged temporal operators} like $\TUntil{I}$ and
$\TDiaOp{I}$. The (continuous) truth values of the new operators are defined by
the average of truth values in a suitable interval.
We show that this simple extension
of $\textbf{STL}$ successfully combines
space and time robustness
in~\cite{DBLP:journals/tcs/FainekosP09,DBLP:conf/formats/DonzeM10}; and
that its expressivity covers many common specifications (expeditiousness,
persistence, deadline, etc.)
encountered in the context of CPS.
\textbf{An algorithm for computing $\textbf{AvSTL}$ robustness.} It is natural
to expect that nonlocal temporal operators---like $\UntilOp{I}$, $\DiaOp{I}$ and their
averaged variants---incur a big performance penalty in computing
truth values.
For $\textbf{STL}$ (without averaged modalities) an efficient algorithm is
proposed in~\cite{DBLP:conf/cav/DonzeFM13}; it employs the idea of
the \emph{sliding window minimum algorithm}~\cite{DBLP:journals/njc/Lemire06}
and achieves complexity
that is linear with respect to the size of an input signal (measured by
the number of timestamps).
We show that, under mild and realistic
assumptions, the same idea as in~\cite{DBLP:conf/cav/DonzeFM13} can be successfully
employed
to compute $\textbf{AvSTL}$ truth values with linear complexity.
\textbf{Enhancing S-TaLiRo: implementation and experiments.}
We use S-TaLiRo and demonstrate that our logic $\textbf{AvSTL}$ indeed achieves a reasonable balance
between expressivity and computational cost. We present our
prototype implementation: it takes S-TaLiRo and lets the above algorithm
(called the \emph{$\textbf{AvSTL}$ evaluator}) replace TaLiRo,
S-TaLiRo's
original engine for computing $\textbf{STL}$ truth values (see
Fig.~\ref{fig:staliro} in~\S{}\ref{sec:experiments}).
For its evaluation,
we pick some
benchmark models $\mathcal{M}$ and $\textbf{STL}$ specifications $\varphi$---they are mostly automotive
examples from~\cite{HoxhaAF14arch1}---and compare performance between:
\begin{itemize}
\item our prototype, run for $\mathcal{M}$ and the original
$\textbf{STL}$ specification $\varphi$,\footnote{
This is the control case of our experiments.
We do not use S-TaLiRo itself, because we would like to disregard
the potential disadvantage caused by the communication between the
$\textbf{AvSTL}$ evaluator (the additional component) and S-TaLiRo.
We note that the $\textbf{AvSTL}$ evaluator is capable of
evaluating $\textbf{STL}$ formulas, too.} and
\item our prototype, run for $\mathcal{M}$ and a
\emph{refinement} of $\varphi$ given as an $\textbf{AvSTL}$ formula.
\end{itemize}
For benchmarks of a certain class we observe substantial performance
improvement: sometimes the latter is several times faster; and in some
benchmarks we even see the latter succeed in falsification while the former
fails to do so.
\noindent
\textit{Related Work}\;
Besides those which are discussed in the above
and the below, a closely related work
is~\cite{DBLP:journals/corr/AbbasHFDKU14} (its abstract appeared
in~\cite{DBLP:conf/iccps/AbbasHFDKU14}). There a notion of
\emph{conformance} between two models $\mathcal{M}_{1}$,
$\mathcal{M}_{2}$ is defined; and it is much like (an arity-2 variation
of) combination of space and time
robustness. Its use in falsification and comparison with the current
approach is future work.
\noindent
\textit{Organization of the Paper}\;
In~\S{}\ref{sec:AvSTL} we introduce the logic $\textbf{AvSTL}$: its syntax,
semantics, some basic properties and examples of temporal specifications
expressible in it. In~\S{}\ref{sec:algorithm}, building
on~\cite{DBLP:conf/cav/DonzeFM13}, an algorithm for computing
$\textbf{AvSTL}$ truth values is introduced and its complexity is studied.
The algorithm is implemented and used
to enhance a falsification solver S-TaLiRo,
in~\S{}\ref{sec:experiments}, where experiment results are presented and
discussed.
We used colors in some figures for clarity. Consult the electronic
edition in case the colors are unavailable. Most of the proofs are
deferred to the appendix.
\textbf{Acknowledgments}
Thanks are due to
Georgios Fainekos,
Tomoyuki Kaga, Toshiki Kataoka,
Hisashi Miyashita,
Kohei Suenaga and
Tomoya Yamaguchi
for helpful
discussions. The authors are supported by Grant-in-Aid for Young
Scientists (A) No.\ 24680001, JSPS; and
T.A.\ is supported by Grant-in-Aid for JSPS Fellows.
\section{Averaged Signal Temporal Logic $\textbf{AvSTL}$}
\label{sec:AvSTL}
We introduce \emph{averaged STL} ($\textbf{AvSTL}$). It is essentially an extension of
$\textbf{MITL}$~\cite{DBLP:dblp_journals/jacm/AlurFH96} and
$\textbf{STL}$~\cite{DBLP:conf/formats/MalerN04} with so-called
\emph{averaged} temporal operators. We describe its syntax and
its semantics (that is inspired by robust semantics
in~\cite{DBLP:journals/tcs/FainekosP09,DBLP:conf/formats/DonzeM10}).
We also exemplify the expressivity of the logic, by encoding
common temporal specifications like expeditiousness,
persistence and deadline.
Finally we will
discuss the relationship to the previous robustness notions~\cite{DBLP:journals/tcs/FainekosP09,DBLP:conf/formats/DonzeM10} for $\textbf{STL}$.
\subsection{Syntax}\label{subsec:syntax}
We let $\equiv$ stand for the syntactic equality.
We let ${\mathbb{R}}$ denote the set of real numbers, with
$\R_{\ge 0}$ and $\R_{\le 0}$ denoting its obvious subsets.
We also fix the set $\mathbf{Var}$ of variables, each of which
stands for a physical quantity (velocity, temperature, etc.).
\begin{mydefinition}[syntax]\label{def:syntax}
In $\textbf{AvSTL}$, the set $\mathbf{AP}$ of \emph{atomic propositions} and the set
$\mathbf{Fml}$
of \emph{formulas} are defined as follows.
\[\small
\begin{array}{rrl}
\mathbf{AP} \ni
& l \,::=\,
& x < r
\mid x \leq r
\mid x \geq r
\mid x > r
\quad \text{ where } x \in \mathbf{Var}, r \in {\mathbb{R}}\\
\mathbf{Fml} \ni
&\varphi \,::=\,
& \top
\mid \bot
\mid l
\mid \neg \varphi
\mid \varphi \vee \varphi
\mid \varphi \wedge \varphi
\mid \varphi \UntilOp{I} \varphi
\mid \varphi \TUntil{I} \varphi
\mid \varphi \Release{I} \varphi
\mid \varphi \TRelease{I} \varphi
\end{array}
\]
Here $I$ is a closed non-singular interval in $\R_{\ge 0}$,
i.e. $I=[a,b]$ or $[a, \infty)$ where $a<b$.
The overlined operator
$\TUntil{I}$ is called the \emph{averaged-until} operator.
We introduce the following connectives as abbreviations, as usual:
\begin{math}
\varphi_1 \to \varphi_2 \equiv (\neg \varphi_1) \vee \varphi_2
\end{math},
\begin{math}
\DiaOp{I} \varphi \equiv \top \UntilOp{I} \varphi
\end{math},
\begin{math}
\BoxOp{I} \varphi \equiv \bot \Release{I} \varphi
\end{math},
\begin{math}
\TDiaOp{I} \varphi \equiv \top \TUntil{I} \varphi
\end{math}
and
\begin{math}
\TBoxOp{I} \varphi \equiv \bot \TRelease{I} \varphi
\end{math}.
%
We omit subscripts $I$ for temporal operators if $I = [0, \infty)$.
The operators $\TRelease{I}$, $\TDiaOp{I}$ and $\TBoxOp{I}$ are called the
\emph{averaged-release}, \emph{averaged-eventually} and \emph{averaged-henceforth} operators, respectively.
We say a formula $\varphi$ is \emph{averaging-free}
if it does not contain any averaged temporal operator.
\auxproof{
As usual, we can exploit de Morgan-like dualities and push negations
inwards towards atomic propositions, leading to
\emph{negation normal forms (NNF)}.
Explicitly, the set $\mathbf{Fml}_{\mathrm{NNF}}$ of NNF formulas is defined as
follows, where $l \in \mathbf{AP}$.
\[
\begin{array}{rll}
\mathbf{Fml}_{\mathrm{NNF}} \ni \varphi &\;::=\;&
\infty \mid \neg \infty
\mid l \mid \neg l \mid \varphi_1 \vee \varphi_2
\mid \varphi_1 \wedge \varphi_2 \mid\\
&&\varphi_1 \UntilOp{I} \varphi_2 \mid \varphi_1 \TUntil{I} \varphi_2
\mid \varphi_1 \Release{I} \varphi_2 \mid \varphi_1 \TRelease{I} \varphi_2
\end{array}
\]
}
\end{mydefinition}
\subsection{Robust Semantics}\label{subsec:semantics}
$\textbf{AvSTL}$ formulas, much like $\textbf{STL}$ formulas in~\cite{DBLP:journals/tcs/FainekosP09,DBLP:conf/formats/DonzeM10}, are interpreted over
(real-valued, continuous-time) \emph{signals}. The latter stand for
trajectories of hybrid systems.
\begin{mydefinition}[signal]\label{def:signal}
A \emph{signal} over $\mathbf{Var}$ is a function $\sigma\colon
\R_{\ge 0}\to ({\mathbb{R}}^{\mathbf{Var}})$; it is therefore a bunch of physical quantities indexed
by a continuous notion of time.
For a signal $\sigma$ and $t\in \R_{\ge 0}$,
$\sigma^t$ denotes the \emph{$t$-shift} of $\sigma$, that is,
$\sigma^t(t') \triangleq \sigma(t+t')$.
\end{mydefinition}
\begin{wrapfigure}[5]{r}{0pt}
\centering
\includegraphics[trim=0cm 0cm 0cm 3cm, width=.33\textwidth]{pics/PNRob2.png}
\end{wrapfigure}
The interpretation of a formula $\varphi$ over a signal $\sigma$ is given by two different
``truth values,'' namely \emph{positive} and \emph{negative robustness}.
They are denoted by $ \Robust{\sigma}{\varphi}^{+}$ and
$ \Robust{\sigma}{\varphi}^{-}$, respectively.
We will always have
\begin{math}
\Robust{\sigma}{\varphi}^{+} \ge 0
\end{math} and
\begin{math}
\Robust{\sigma}{\varphi}^{-} \le 0
\end{math}.
We will also see that, for averaging-free $\varphi$,
it is never the case that
\begin{math}
\Robust{\sigma}{\varphi}^{+} > 0
\end{math}
and
\begin{math}
\Robust{\sigma}{\varphi}^{-} <0
\end{math}
hold at the same time.
See the figure on the right for an example, where a sine-like (black) curve is
a signal $\sigma$. The blue and red curves stand for the positive and
negative robustness, of the formula $x\ge 0$ over the ($t$-shifted) signal
$\sigma^{t}$, respectively.
\begin{mydefinition}[positive/negative robustness]\label{def:semantics}
Let $\sigma \colon \R_{\ge 0} \to {\mathbb{R}}^\mathbf{Var}$ be a signal
and $\varphi$ be an $\textbf{AvSTL}$ formula.
We define the \emph{positive robustness}
$\Robust{\sigma}{\varphi}^{+} \in \R_{\ge 0} \cup \{\infty\}$
and the \emph{negative robustness}
$\Robust{\sigma}{\varphi}^{-} \in \R_{\le 0} \cup \{ - \infty\}$
by mutual induction, as shown in Table~\ref{table:robustness}.
Here $\sqcap$ and $\sqcup$ denote infimums and supremums of real numbers, respectively.
\begin{table}[t]
\begin{tabular}{l}
\scalebox{0.86}{
\begin{math}
\begin{array}{rll}
\Robust{\sigma}{\top}^{+} & \triangleq & \infty\\
\Robust{\sigma}{\bot}^{+} & \triangleq & 0\\
\Robust{\sigma}{x < r}^{+} & \triangleq & 0\sqcup (r - \sigma(0)(x))\\
\Robust{\sigma}{x \leq r}^{+} & \triangleq & 0\sqcup(r - \sigma(0)(x))\\
\Robust{\sigma}{x \geq r}^{+} & \triangleq & 0\sqcup(\sigma(0)(x) - r)\\
\Robust{\sigma}{x > r}^{+} & \triangleq & 0\sqcup( \sigma(0)(x) - r)\\
\Robust{\sigma}{\neg \varphi}^{+} & \triangleq & - \Robust{\sigma}{\varphi}^{-}\\
\Robust{\sigma}{\varphi_1 \vee \varphi_2}^{+} & \triangleq &
\Robust{\sigma}{\varphi_1}^{+} \sqcup \Robust{\sigma}{\varphi_2}^{+}\\
\Robust{\sigma}{\varphi_1 \wedge \varphi_2}^{+} & \triangleq &
\Robust{\sigma}{\varphi_1}^{+} \sqcap \Robust{\sigma}{\varphi_2}^{+}\\
\\
\end{array}
\quad
\begin{array}{l}
\begin{array}{rll}
\Robust{\sigma}{\varphi_1 \UntilOp{I} \varphi_2}^{+}
& \triangleq
& \Vee{t \in I}
(\Robust{\sigma^t}{\varphi_2}^{+} \sqcap
\Wedge{t' \in [0, t)} \Robust{\sigma^{t'}}{\varphi_1}^{+})\\
\Robust{\sigma}{\varphi_1 \Release{I} \varphi_2}^{+}
& \triangleq
& \Wedge{t \in I}
(\Robust{\sigma^t}{\varphi_2}^{+} \sqcup
\Vee{t' \in [0, t)} \Robust{\sigma^{t'}}{\varphi_1}^{+})\\
\end{array}
\\
\begin{array}{l}
\Robust{\sigma}{\varphi_1 \TUntil{I} \varphi_2}^{+} \triangleq\\
\quad
\begin{cases}
\Frac{1}{b - a} \int_{a}^{b}
\Robust{\sigma}{\varphi_1 \UntilOp{I \cap [0, \tau]} \varphi_2}^{+} d\tau
& \text{($I$ is bounded)}\\
\Robust{\sigma}{\varphi_1 \UntilOp{I} \varphi_2}^{+}
& \text{($I$ is unbounded)}\\
\end{cases}
\\
\Robust{\sigma}{\varphi_1 \TRelease{I} \varphi_2}^{+} \triangleq\\
\quad
\begin{cases}
\Frac{1}{b - a} \int_{a}^{b}
\Robust{\sigma}{\varphi_1 \Release{I \cap [0, \tau]} \varphi_2}^{+} d\tau
& \text{($I$ is bounded)}\\
\Robust{\sigma}{\varphi_1 \Release{I} \varphi_2}^{+}
& \text{($I$ is unbounded)}\\
\end{cases}\\
\end{array}
\end{array}
\end{math}
}
\\
\hline
\scalebox{0.86}{
\begin{math}
\begin{array}{rll}
\Robust{\sigma}{\top}^{-} & \triangleq & 0\\
\Robust{\sigma}{\bot}^{-} & \triangleq & - \infty\\
\Robust{\sigma}{x < r}^{-} & \triangleq & 0\sqcap( r - \sigma(0)(x))\\
\Robust{\sigma}{x \leq r}^{-} & \triangleq & 0\sqcap( r - \sigma(0)(x))\\
\Robust{\sigma}{x \geq r}^{-} & \triangleq & 0\sqcap( \sigma(0)(x) - r)\\
\Robust{\sigma}{x > r}^{-} & \triangleq & 0\sqcap( \sigma(0)(x) - r)\\
\Robust{\sigma}{\neg \varphi}^{-} & \triangleq & - \Robust{\sigma}{\varphi}^{+}\\
\Robust{\sigma}{\varphi_1 \vee \varphi_2}^{-} & \triangleq &
\Robust{\sigma}{\varphi_1}^{-} \sqcup \Robust{\sigma}{\varphi_2}^{-}\\
\Robust{\sigma}{\varphi_1 \wedge \varphi_2}^{-} & \triangleq &
\Robust{\sigma}{\varphi_1}^{-} \sqcap \Robust{\sigma}{\varphi_2}^{-}\\
\\
\end{array}
\quad
\begin{array}{l}
\begin{array}{rl}
\Robust{\sigma}{\varphi_1 \UntilOp{I} \varphi_2}^{-}
& \triangleq
\Vee{t \in I}
(\Robust{\sigma^t}{\varphi_2}^{-} \sqcap \Wedge{t' \in [0, t)} \Robust{\sigma^{t'}}{\varphi_1}^{-})\\
\Robust{\sigma}{\varphi_1 \Release{I} \varphi_2}^{-}
& \triangleq
\Wedge{t \in I}
(\Robust{\sigma^t}{\varphi_2}^{-} \sqcup \Vee{t' \in [0, t)} \Robust{\sigma^{t'}}{\varphi_1}^{-})\\
\end{array}\\
\begin{array}{l}
\Robust{\sigma}{\varphi_1 \TUntil{I} \varphi_2}^{-} \triangleq\\
\quad
\begin{cases}
\Frac{1}{b - a} \int_{a}^{b} \Robust{\sigma}{\varphi_1 \UntilOp{I \cap [0, \tau]} \varphi_2}^{-} d\tau
& \text{($I$ is bounded)}\\
\Robust{\sigma}{\varphi_1 \UntilOp{I} \varphi_2}^{-} &
\text{($I$ is unbounded)}\\
\end{cases}\\
\Robust{\sigma}{\varphi_1 \TRelease{I} \varphi_2}^{-} \triangleq\\
\quad
\begin{cases}
\Frac{1}{b - a} \int_{a}^{b} \Robust{\sigma}{\varphi_1 \Release{I \cap [0, \tau]} \varphi_2}^{-} d\tau
& \text{($I$ is bounded)}\\
\Robust{\sigma}{\varphi_1 \Release{I} \varphi_2}^{-} &
\text{($I$ is unbounded)}\\
\end{cases}\\
\end{array}
\end{array}
\end{math}
}
\end{tabular}
\caption{Definition of positive and negative robustness}
\label{table:robustness}
\end{table}
\end{mydefinition}
The definition in Table~\ref{table:robustness} is much like the one for
$\textbf{STL}$~\cite{DBLP:conf/formats/DonzeM10,DBLP:conf/cav/DonzeFM13},\footnote{
There is no distinction between strict inequalities ($<$) and
non-strict ones ($\le$). This is inevitable in the current
robustness framework. This is also the case with $\textbf{STL}$
in~\cite{DBLP:conf/formats/DonzeM10,DBLP:conf/cav/DonzeFM13}. }
except for the averaged modalities on which a detailed account follows shortly.
Conjunctions and
disjunctions are interpreted by infimums and supremums, in a
straightforward manner.
Fig.~\ref{fig:averagedDiamond} illustrates the semantics of
averaged-temporal operators---the novelty of our logic $\textbf{AvSTL}$. Specifically,
the black line designates a
signal $\sigma$ whose only variable is $x$; and we consider the ``averaged-eventually''
formula $\TDiaOp{[0, 1]} (x \geq 0)$. For this formula, the definition in
Table~\ref{table:robustness} specializes to:
\[
\begin{array}{l}
\Robust{\sigma}{\TDiaOp{[0, 1]} (x \geq 0)}^{+} \\
=
\int_{0}^{1} \Bigl(\,\Vee{\tau' \in [0 , \tau]} 0\sqcup\,
\sigma(\tau')(x)\,\Bigr) \,d\tau\enspace,
\end{array}
\qquad\text{and}\qquad
\begin{array}{l}
\Robust{\sigma}{\TDiaOp{[0, 1]} (x \geq 0)}^{-}
\\
=
\int_{0}^{1}\Bigl(\, \Vee{\tau' \in [0 , \tau]} 0
\sqcap\,\sigma(\tau')(x)
\,\Bigr)\,d\tau\enspace .
\end{array}
\]
\begin{wrapfigure}[8]{r}{0pt}
\begin{minipage}[r]{.4\textwidth}
\centering
\includegraphics[trim=0cm 2cm 0cm 2cm, width=0.9\textwidth,natwidth=640,natheight=384]{pics/TDia2.png}
\caption{
The positive and negative robustness of
$\TDiaOp{[0, 1]} (x \geq 0)$ at $t=0$.}
\label{fig:averagedDiamond}
\end{minipage}
\end{wrapfigure}
These values obviously coincide with the sizes of the blue and red
areas in Fig.~\ref{fig:averagedDiamond}, respectively. Through this ``area''
illustration
of the averaged-eventually operator
we see that: the sooner
$\varphi$ is true, the more (positively) robust $\TDiaOp{I}\varphi$ is.
It is also clear from Fig.~\ref{fig:averagedDiamond} that our semantics captures space robustness
too: the bigger a vertical margin is, the bigger an area is.
\begin{myremark}\label{rem:separationPosNegRobustness}
Presence of averaged temporal operators forces separation of two
robustness measures (positive and negative). Assume otherwise, i.e.
that we have one robustness measure
that can take both positive and negative values; then robustness that floats between
positive and negative values over time
can ``cancel out'' after an average is taken. This leads to the failure
of \emph{soundness} (see Prop.~\ref{prop:diaRefinement} and \ref{prop:BoxRefinement};
also~\cite{DBLP:journals/tcs/FainekosP09,DBLP:conf/formats/DonzeM10}),
and then a positive robustness value no longer witnesses the Boolean truth
of (the qualitative variant of) the formula. This is not convenient in
the application to falsification.
\end{myremark}
\auxproof{
\begin{myremark}
In Def.~\ref{def:semantics},
we define the value of positive/negative temporal robustness
of averaged- modalities
as a definite integral.
From the following Lem.~\ref{lemma:untilIsMonotone},
we can check the integrability
of them;
all
$\Robust{\sigma}{\varphi_1 \UntilOp{[t,\tau]} \varphi_2}^{+}$,
$\Robust{\sigma}{\varphi_1 \UntilOp{[t,\tau]} \varphi_2}^{-}$,
$\Robust{\sigma}{\varphi_1 \Release{[t,\tau]} \varphi_2}^{+}$, and
$\Robust{\sigma}{\varphi_1 \Release{[t,\tau]} \varphi_2}^{-}$
are monotonically increasing or decreasing
over $\tau \in [t, t']$,
hence these functions are integrable.
\end{myremark}
}
\subsection{Basic Properties of $\textbf{AvSTL}$}
\begin{mylemma}[temporal monotonicity]\label{lemma:untilIsMonotone}
Let
$0 \leq t_0 < t \leq t'$.
The following hold.
\[\small
\begin{array}{rclrcl}
\Robust{\sigma}{\varphi_1 \UntilOp{[t_0,t]} \varphi_2}^{+}
&\leq &
\Robust{\sigma}{\varphi_1 \UntilOp{[t_0,t']} \varphi_2}^{+}
\quad
&
\Robust{\sigma}{\varphi_1 \UntilOp{[t_0,t]} \varphi_2}^{-}
&\leq &
\Robust{\sigma}{\varphi_1 \UntilOp{[t_0,t']} \varphi_2}^{-}
\\
\Robust{\sigma}{\varphi_1 \Release{[t_0,t]} \varphi_2}^{+}
&\geq&
\Robust{\sigma}{\varphi_1 \Release{[t_0,t']} \varphi_2}^{+}
&
\Robust{\sigma}{\varphi_1 \Release{[t_0,t]} \varphi_2}^{-}
&\geq&
\Robust{\sigma}{\varphi_1 \Release{[t_0,t']} \varphi_2}^{-}
\end{array}
\]
The inequalities hold also for the averaged temporal operators. \qed
\end{mylemma}
We can now see well-definedness of Def.~\ref{def:semantics}:
we need that the integrals are defined; and the lemma shows that
the integrated functions are monotone, hence Riemann integrable.
In Def.~\ref{def:semantics},
the definitions for averaged operators with an infinite endpoint
(like $\TUntil{[0, \infty)}{\varphi}$) are given in terms of non-averaged
operators. This is so that their well-definedness is immediate; the
following lemma justifies those definitions.
\begin{mylemma}\label{lem:CorrespondenceBetweenUntilAndTUntil}
For any $t_0 \in \R_{\ge 0}$,
\begin{math}
\Robust{\sigma}{\varphi_1 \UntilOp{[t_0, \infty)} \varphi_2}^{+}
=
\Lim{t \to \infty}
\Robust{\sigma}{\varphi_1 \TUntil{[t_0, t]} \varphi_2}^{+}
\end{math}.
The same is true if we replace $\sem{\underline{\phantom{n}}\,}^{+}$ with
$\sem{\underline{\phantom{n}}\,}^{-}$, and if we replace $\UntilOp{}$ with $\Release{}$.
\qed
\end{mylemma}
\auxproof{
\begin{mylemma}[logical monotonicity]
\label{lem:monotonicity}
Let $\mathcal{C}$ be a \emph{positive context}, that is, an $\textbf{AvSTL}$ formula
with a hole $[\,]$ at a positive position. We have
\begin{align*}
\begin{array}{rcl}
\forall \sigma.\; \Robust{\sigma}{\varphi}^{+}
\leq \Robust{\sigma}{\varphi'}^{+}
\quad&\text{implies}
&\quad
\forall \sigma.\; \Robust{\sigma}{\mathcal{C}[\varphi]}^{+}
\leq
\Robust{\sigma}{\mathcal{C}[\varphi']}^{+}\enspace;\;\text{and}\\
\forall \sigma.\; \Robust{\sigma}{\varphi}^{-}
\leq \Robust{\sigma}{\varphi'}^{-}
\quad&\text{implies}
&\quad
\forall \sigma.\; \Robust{\sigma}{\mathcal{C}[\varphi]}^{-}
\leq
\Robust{\sigma}{\mathcal{C}[\varphi']}^{-} \enspace.
\end{array}
\end{align*}
\end{mylemma}
\begin{myproof}
By induction on the construction of the positive context $\mathcal{C}$; the
latter is thought of as a formula of the negative normal form with a
hole. \qed
\end{myproof}
}
\subsection{Common Temporal Specifications Expressed in $\textbf{AvSTL}$}\label{subsec:examplesExpressivity}
Here we shall exemplify the expressivity of $\textbf{AvSTL}$, by encoding
typical temporal specifications encountered in the model-based
development of cyber-physical systems.
\begin{myremark
\label{rem:propVar}
In what follows we sometimes use \emph{propositional variables} such as
$\mathtt{airbag}$
and $\mathtt{gear}_{i}$. For example, $\mathtt{gear}_{2}$
is a shorthand for the atomic formula $x_{\mathtt{gear}_{2}} \ge 0$ in $\textbf{AvSTL}$, where
the variable $x_{\mathtt{gear}_{2}}$ is assumed to take a discrete value
($1$ or $-1$).
\end{myremark}
\subsubsection{Expeditiousness ($\TDiaOp{I}\varphi$)}
Consider the following informal specification:
\emph{after heavy braking,
the airbag must operate
within 10 ms.}
Its formalization in $\textbf{STL}$ is straightforward by the formula
\begin{math}
\BoxOp{} (
\mathtt{heavyBraking} \to
\DiaOp{[0,10]}\mathtt{airbag} )
\end{math}.
However, an airbag that operates
after 1 ms.\ is naturally more desirable than one that operates
after 9.99 ms. The $\textbf{STL}$ formula fails to discriminate between these
two airbags.
\begin{figure}[tbp]
\begin{minipage}{.33\textwidth}
\includegraphics[width=\textwidth,natwidth=640,
natheight=384]{pics/expediency.pdf}
\vspace{-3.5em}
\caption{Expeditiousness}
\label{fig:expeditiousness}
\end{minipage}
\begin{minipage}{.33\textwidth}
\includegraphics[width=\textwidth,natwidth=640,
natheight=384]{pics/deadline.pdf}
\vspace{-3.5em}
\caption{Deadline}
\label{fig:deadline}
\end{minipage}
\begin{minipage}{.33\textwidth}
\includegraphics[width=\textwidth,natwidth=640,
natheight=384]{pics/persistence.pdf}
\vspace{-3.5em}
\caption{Persistence}
\label{fig:persistence}
\end{minipage}
\end{figure}
Such \emph{expeditiousness} (``as soon as possible'') requirements
are more adequately modeled in $\textbf{AvSTL}$, using the averaged-eventually modality
$\TDiaOp{I}$. See Fig.~\ref{fig:expeditiousness}, where
the horizontal axis is
for time $t$. The vertical axis in the figure stands for the positive
robustness value
$\Robust{\sigma_{t}}{\TDiaOp{[0,10]}\mathtt{airbag}}^{+}$ of the formula
$\TDiaOp{[0,10]}\mathtt{airbag}$, where $\sigma_{t}$ is a signal in
which $\mathtt{airbag}$ operates
(i.e. $x_{\mathtt{airbag}}$ becomes from $-1$ to $1$) at time $t$.
We see that the formula successfully distinguishes an early-bird
airbag from a lazy one.
Therefore the $\textbf{AvSTL}$ formula
\begin{math}
\BoxOp{} (
\mathtt{heavyBraking} \to
\TDiaOp{[0,10]}\mathtt{airbag} )
\end{math} formalizes
a (refined) informal specification that: after heavy braking, the airbag must
operate within 10 ms; \emph{but the sooner the better}. It is not hard
to expect that the latter is
more faithful to the designer's intention than the
original informal specification.
\subsubsection{Deadline ($\DiaOp{[0,T]}\varphi\lor
\TDiaOp{[T,T+\delta]}\varphi$)}
The expeditiousness-type requirement that we have discussed is sometimes too
strict. Let us consider the following scenario: there is a deadline set
at time $T$ and arrival by then is rewarded no matter how late; and then there is a
deadline extension by time $\delta$ and arrival between the deadline
and the extended one is rewarded too, but with certain deduction.
Such
a \emph{deadline} specification is expressed in $\textbf{AvSTL}$ by the formula
$\DiaOp{[0,T]}\varphi \lor \TDiaOp{[T,T+\delta]}\varphi$,
combining non-averaged and averaged
eventually modalities. See Fig.~\ref{fig:deadline}, where the
positive robustness of the formula
\begin{math}
(\DiaOp{[0,5]}\mathtt{airbag})\lor
(\TDiaOp{[5,5+5]}\mathtt{airbag})
\end{math}
is plotted, for the same signals $\sigma_{t}$ as before
(i.e. in $\sigma_{t}$ the airbag operates at time $t$).
\subsubsection{Persistence
($\BoxOp{[0,T]}\varphi\land\TBoxOp{[T,T+\delta]}\varphi$)}
\emph{Persistence} (``for as long as possible'') specifications are dual
to deadline ones and expressed by a formula
$\BoxOp{[0,T]}\varphi\land\TBoxOp{[T,T+\delta]}\varphi$. An example is
the following informal specification on automatic transmission:
\emph{when a gear shifts into first,
it never shifts into any other gear for the coming 50 ms.} A likely
intention behind it is to prevent mechanical wear of gears that is caused by
frequent gear shifts. In this case the following specification
would be more faithful to the intention: when a gear shifts into first,
it never shifts into any other gear for the coming 50 ms., \emph{and
preferably for longer}. This is formalized by the formula
\begin{math}
\BoxOp{}
(
\mathtt{shiftIntoGear_1} \to
\BoxOp{[0,50]}\mathtt{gear_1}\land\TBoxOp{[50,50+\delta]}\mathtt{gear_1}
)
\end{math}.
For illustration, Fig.~\ref{fig:persistence} plots
the positive robustness of
$\BoxOp{[0,50]}\mathtt{gear_1}\land\TBoxOp{[50,60]}\mathtt{gear_1}$
for signals $\sigma'_{t}$, where $\mathtt{gear_1}$ is true in
$\sigma'_{t}$ from time $0$ to $t$, and is false afterwards.
\subsubsection{Other Temporal Specifications}
Expressivity of $\textbf{AvSTL}$ goes beyond the three examples that we have
seen---especially after the extension of the language with
\emph{time-reversed} averaged temporal operators. The reversal of time
here corresponds to the symmetry between \emph{left} and \emph{right}
time robustness in~\cite{DBLP:conf/formats/DonzeM10}. Such an
extension of $\textbf{AvSTL}$ enables us to express specifications like
\emph{punctuality}
(``no sooner, no later'') and \emph{periodicity}. The details will be
reported in another venue.
\subsection{Soundness of Refinements from $\textbf{STL}$ to $\textbf{AvSTL}$}\label{subsec:soundnessOfEnrichments}
In~\S\ref{subsec:examplesExpressivity} we have seen some scenarios where
an $\textbf{STL}$ specification is \emph{refined} into an $\textbf{AvSTL}$ one so that
it more faithfully reflects the designer's intention. The following two
are prototypical:
\begin{itemize}
\item{}
\textbf{($\Diamond$-refinement)}
the refinement
of $\DiaOp{I}\varphi$ (``eventually $\varphi$, within $I$'') into
$\TDiaOp{I}\varphi$
(``eventually $\varphi$ within $I$, but as soon as possible''); and
\item{}
\textbf{($\Box$-refinement)}
the refinement of
$\BoxOp{[a,b]}\varphi$
(``always $\varphi$ throughout $[a,b]$'') into
$\BoxOp{[a,b]}\varphi\land\TBoxOp{[b,b+\delta]}\varphi$ (``always
$\varphi$ throughout $[a,b]$, and desirably also in $[b,b+\delta]$'').
\end{itemize}
The following \emph{soundness}
results
guarantee validity of the use of these refinements in falsification
problems. \emph{Completeness}, in a suitable sense, holds too.
\begin{mydefinition}
\label{def:context}
A \emph{positive context} is
an $\textbf{AvSTL}$ formula with a hole $[\,]$ at a positive position.
Formally,
the set of positive contexts is defined as follows:
\[
\begin{array}{rl}
\mathcal{C} \,::=\,& [\,] \mid \mathcal{C} \vee \varphi \mid \varphi \vee \mathcal{C}
\mid \mathcal{C} \wedge \varphi \mid \varphi \wedge \mathcal{C}
\mid \mathcal{C} \UntilOp{I} \varphi
\mid \varphi \UntilOp{I} \mathcal{C}
\mid \mathcal{C} \TUntil{I} \varphi
\mid \varphi \TUntil{I} \mathcal{C}\\
& \mid \mathcal{C} \Release{I} \varphi
\mid \varphi \Release{I} \mathcal{C}
\mid \mathcal{C} \TRelease{I} \varphi
\mid \varphi \TRelease{I} \mathcal{C} \quad
\text{ where $\varphi$ is an $\textbf{AvSTL}$ formula. }
\end{array}
\]
For a positive context $\mathcal{C}$ and an $\textbf{AvSTL}$ formula $\psi$,
$\mathcal{C}[\psi]$ denotes the formula
obtained by substitution of $\psi$
for the hole $[\,]$ in $\mathcal{C}$.
\end{mydefinition}
\noindent
\begin{minipage}{\textwidth}
\begin{myproposition}[soundness and completeness of $\DiaOp{}$-refinement]
\label{prop:diaBoxReplacement}
\label{prop:diaRefinement}
Let $\mathcal{C}$ be a positive context.
Then
\begin{math}
\Robust{\sigma}{\mathcal{C}[\TDiaOp{[a,b]}\varphi]}^{+} > 0
\end{math}
implies
\begin{math}
\Robust{\sigma}{\mathcal{C}[\DiaOp{[a,b]}\varphi]}^{+} > 0.
\end{math}
Moreover, for any $b'$ such that
\begin{math}
b' < b
\end{math},
\begin{math}
\Robust{\sigma}{\mathcal{C}[\DiaOp{[a,b']}\varphi]}^{+} > 0
\end{math}
implies
\begin{math}
\Robust{\sigma}{\mathcal{C}[\TDiaOp{[a,b]}\varphi]}^{+} > 0
\end{math}
\qed
\end{myproposition}
\end{minipage}
\noindent
\begin{minipage}{\textwidth}
\begin{myproposition}[soundness and completeness of $\BoxOp{}$-refinement]
\label{prop:BoxRefinement}
Let $\mathcal{C}$ be a positive context.
Then
\begin{math}
\Robust{\sigma}{\mathcal{C}[\BoxOp{[a,b]}\varphi \wedge \TBoxOp{[b,b+\delta]}\varphi]}^{+} > 0
\end{math}
implies
\begin{math}
\Robust{\sigma}{\mathcal{C}[\BoxOp{[a,b]}\varphi]}^{+} > 0
\end{math}.
Moreover, for any $b'>b$,
\begin{math}
\Robust{\sigma}{\mathcal{C}[\BoxOp{[a,b']}\varphi]}^{+} > 0
\end{math} implies
\begin{math}
\Robust{\sigma}{\mathcal{C}[\BoxOp{[a,b]}\varphi \wedge \TBoxOp{[b,b+\delta]}\varphi]}^{+} > 0
\end{math}.
\qed
\end{myproposition}
\end{minipage}
\subsection{Relationship to Previous Robustness Notions}
Our logic $\textbf{AvSTL}$ captures
\emph{space robustness}~\cite{DBLP:journals/tcs/FainekosP09}---the
first robustness notion proposed for $\textbf{MITL}$/$\textbf{STL}$,
see~\S\ref{sec:introduction}---because the averaging-free fragment of $\textbf{AvSTL}$ coincides with
$\textbf{STL}$ and its space robust semantics, modulo the separation of positive
and negative robustness (Rem.~\ref{rem:separationPosNegRobustness}).
\auxproof{
More precisely,
the positive robustness of an averaged-free $\textbf{AvSTL}$ formula $\varphi$
corresponds to
the space robustness in $\textbf{STL}$
if $\varphi$ is (qualitatively) true,
and so does the negative one if $\varphi$ is false.
}
\begin{wrapfigure}[7]{r}{0pt}
\centering
\includegraphics[clip,trim=0cm 4cm 0cm
0cm,width=.35\textwidth]{pics/lebesgue.pdf}
\end{wrapfigure}
The relationship to \emph{space-time robustness} proposed
in~\cite{DBLP:conf/formats/DonzeM10} is
interesting. In~\cite{DBLP:conf/formats/DonzeM10} they combine time and
space robustness in the following way: for each time $t$ and each space robustness value $c>0$,
\emph{(right) time robustness relative to $c$}, denoted by
$\theta^{+}_{c}(\varphi,\sigma,t)$, is defined by ``how long
after time $t$ the formula $\varphi$
maintains space robustness $c$.'' See the figure
on the right, where the space-time robustness
$\theta^{+}_{c}(x\ge 0,\sigma,0)$ is depicted.
After all, space-time robustness in~\cite{DBLP:conf/formats/DonzeM10} is a function from $c$ to
$\theta^{+}_{c}(\varphi,\sigma,t)$; and one would like some real number as
its characteristic. A natural choice of such is the \emph{area}
surrounded
by
the graph of the function (the shaded area in the figure), and it is
computed in the same way as
\emph{Lebesgue integration}, as the figure suggests.
What corresponds in our $\textbf{AvSTL}$
framework to this ``area'' characteristic value is the robustness of the formula
$\TBoxOp{[0,\infty)}(x\ge 0)$ computed by Riemann
integration (here we have to
ignore the normalizing factor $\frac{1}{b-a}$ in
Table~\ref{table:robustness}). Therefore, very roughly speaking:
our ``averaged'' robustness is a real-number characteristic value of the
space-time robustness
in~\cite{DBLP:conf/formats/DonzeM10}; and the
correspondence
is via the equivalence between Riemann and Lebesgue integration.
\section{A Sliding-Window Algorithm for $\textbf{AvSTL}$ Robustness}
\label{sec:algorithm}
We shall present an algorithm for computing $\textbf{AvSTL}$ robustness. It
turns out that the presence of averaged modalities like
$\TDiaOp{I}$---with an apparent nonlocal nature---does not incur
severe computational overhead, at least for formulas
in which averaged modalities are not nested.
The algorithm is an adaptation of the one
in~\cite{DBLP:conf/cav/DonzeFM13} for $\textbf{STL}$ robustness; the latter in turn relies on the
\emph{sliding window minimum
algorithm}~\cite{DBLP:journals/njc/Lemire06}.
The algorithm's time complexity is linear with respect to the number of
timestamps in the input signal; it exhibits a practical speed, too, as
we will see later in~\S{}\ref{sec:experiments}.
Firstly we fix the class of signals to be considered.
\begin{mydefinition}[finitely piecewise-constant/piecewise-linear signal]
A 1-dimensional signal $\sigma\colon \R_{\ge 0} \to {\mathbb{R}}$ is
\emph{finitely piecewise-constant (FPC)}
if it arises from a finite sequence
\begin{math}
\bigl[\, (t_{0},r_{0}),
(t_{1},r_{1}),
\dotsc,
(t_{n},r_{n})
\,\bigr]
\end{math}
of timestamped values,
via the correspondence
\begin{math}
\sigma(t) = r_{i}
\end{math}
(for $t\in[t_{i}, t_{i+1})$).
Here
$0=t_{0}<\cdots<t_{n}$,
$r_{i}\in{\mathbb{R}}$, and $t_{n+1}$ is deemed to be $\infty$.
Similarly, a 1-dimensional signal
$\sigma\colon \R_{\ge 0} \to {\mathbb{R}}$ is \emph{finitely piecewise-linear (FPL)}
if it is identified with a finite sequence
\begin{math}
\bigl[\, (t_{0},r_{0}, q_{0}),
\dotsc,
(t_{n},r_{n},q_{n})
\,\bigr]
\end{math}
of timestamped values,
via the correspondence
\begin{math}
\sigma(t)= r_{i} + q_{i}(t-t_{i})
\end{math}
(for $t\in[t_{i}, t_{i+1})$). Here $q_{i}\in R$ is the slope of $\sigma$
in the interval $[t_{i}, t_{i+1})$.
The definitions obviously extend to many-dimensional signals
$\sigma \colon \R_{\ge 0} \to
{\mathbb{R}}^\mathbf{Var}$.
We shall follow~\cite{DBLP:conf/formats/DonzeM10,DBLP:conf/cav/DonzeFM13} and measure an algorithm's complexity in terms of
the number of timestamps ($n$ in the above); the latter is identified
with the \emph{size} of a signal.
\end{mydefinition}
\begin{mydefinition}[robustness signal {$[\varphi]_{\sigma}$}]
Let $\sigma : \R_{\ge 0} \to {\mathbb{R}}^{\mathbf{Var}}$ be a signal, and $\varphi$ be an
$\textbf{AvSTL}$ formula.
The \emph{positive robustness signal} of $\varphi$ over $\sigma$
is the signal
$[\varphi]_{\sigma}^{+}\colon \R_{\ge 0}\to{\mathbb{R}}$ defined by:
$[\varphi]_{\sigma}^{+}(t)\triangleq\Robust{\sigma^{t}}{\varphi}^{+}$.
Recall that $\sigma^{t}(t')=\sigma(t+t')$ is the $t$-shift of $\sigma$
(Def.~\ref{def:signal}). The \emph{negative robustness signal}
$[\varphi]_{\sigma}^{-}$ is defined in the same way.
\end{mydefinition}
\noindent
An averaged modality turns a piecewise-constant signal into a
piecewise-linear one.
\begin{mylemma}\label{lem:preservationOfPiecewiseConstLinear}
\begin{enumerate}
\item Let $\varphi$ be an averaging-free $\textbf{AvSTL}$ formula.
If a signal $\sigma$ is finitely piecewise-constant (or
piecewise-linear), then so is $[\varphi]^{+}_{\sigma}$.
\item Let $\varphi$ be an $\textbf{AvSTL}$ formula without nested averaged
modalities.
If a signal $\sigma$ is finitely piecewise-constant, then
$[\varphi]^{+}_{\sigma}$ is finitely piecewise-linear.
\end{enumerate}
\noindent
The above holds for the negative robustness signal
$[\varphi]^{-}_{\sigma}$, too.
\end{mylemma}
\begin{myproof}
Straightforward by the induction on the construction of formulas.
\qed
\end{myproof}
Our algorithm for computing $\textbf{AvSTL}$ robustness
$\Robust{\sigma}{\varphi}$ will be focused on:
1) a finitely piecewise-constant input signal $\sigma$; and
2) an $\textbf{AvSTL}$ formula $\varphi$ where averaged modalities are not nested.
In what follows, for presentation, we use the (non-averaged and averaged)
eventually modalities $\DiaOp{I},\TDiaOp{I}$ in describing algorithms.
Adaptation to other modalities is not hard;
for complex formulas, we compute
the robustness signal $[\varphi]_{\sigma}$ by induction on $\varphi$.
\auxproof{
Unfortunately,
these propositions do not hold
for formulas that contain averaged modalities.
However,
we can still have the following.
\begin{myproposition}\label{prop:fpc2fpl}
Let $\sigma : \R_{\ge 0} \to {\mathbb{R}}$ and
$\varphi_1, \varphi_2 \in \mathbf{Fml}$ be averaging-free formulas.
If $[x]_{\sigma}$ is finitely piecewise-constant for any atomic formula $x$,
then $[\varphi_1 \TUntil{[a,b]} \varphi_2]_{\sigma}$ is finitely piecewise-linear
for any non-singular closed interval $[a,b]$.
\end{myproposition}
\begin{myproof}
From Prop.~\ref{prop:fpc},
$[\varphi_1]_{\sigma}$ and $[\varphi_2]_{\sigma}$ are both finitely piecewise constant.
Let $(t_i)_{i \leq n}$ be the union set of those timestamps.
We show that
there exists finite partition of $R^+$
such that
$[\varphi_1 \TUntil{[a,b]} \varphi_2]_{\sigma}$ is linear
in each.
For any
$u \in \R_{\ge 0}$,
take any $u' \in \R_{\ge 0}$ satisfying the both following conditions.
\begin{itemize}
\item $\{t_j \mid u \leq t_j \} = \{t_j \mid u' \leq t_j \}$
\item $\{t_k \mid a+u \leq t_k \leq b+u \} = \{t_k \mid a+u'\leq t_k \leq b+u' \}$
\end{itemize}
Then,
\[
\begin{array}{ll}
&\Robust{\sigma^{u'}}{\varphi_1 \TUntil{[a,b]} \varphi_2}
- \Robust{\sigma^u}{\varphi_1 \TUntil{[a,b]} \varphi_2}\\
=&\Frac{1}{b-a}
\bigg( \int_a^b \Robust{\sigma^{u'}}{\varphi_1 \UntilOp{[a,\tau]} \varphi_2} d\tau
- \int_a^b \Robust{\sigma^{u}}{\varphi_1 \UntilOp{[a,\tau]} \varphi_2} d\tau \bigg)\\
\end{array}
\]
and
\begin{align*}
& \int_a^b \Robust{\sigma^{u'}}{\varphi_1 \UntilOp{[a,\tau]} \varphi_2} d\tau
- \int_a^b \Robust{\sigma^{u}}{\varphi_1 \UntilOp{[a,\tau]} \varphi_2} d\tau\\
= &
\int_a^b
\Vee{\tau' \in [a, \tau] }
\Big( \Robust{\sigma^{u'+\tau'}}{\varphi_2} \wedge \Wedge{\tau'' \in [0, \tau']} \Robust{\sigma^{u'+\tau''}}{\varphi_1} \Big)
d\tau \\
&- \int_a^b
\Vee{\tau' \in [a, \tau] }
\Big( \Robust{\sigma^{u+\tau'}}{\varphi_2} \wedge \Wedge{\tau'' \in [0, \tau']} \Robust{\sigma^{u+\tau''}}{\varphi_1} \Big)
d\tau\\
=&
\int_a^b
\Vee{\tau' \in [a, \tau] }
\Big( \Robust{\sigma^{u'+\tau'}}{\varphi_2} \wedge \Wedge{\tau'' \in [0, \tau']} \Robust{\sigma^{u'+\tau''}}{\varphi_1} \Big)
d\tau \\
&- \int_a^b
\Vee{\tau' \in [a, \tau] }
\Big( \Robust{\sigma^{u+\tau'}}{\varphi_2} \wedge \Wedge{\tau'' \in [0, \tau']} \Robust{\sigma^{u+\tau''}}{\varphi_1} \Big)
d\tau\\
=&
\int_{a+u'}^{b+u'}
\Vee{\tau' \in [a+u', \tau] }
\Big( \Robust{\sigma^{\tau'}}{\varphi_2} \wedge \Wedge{\tau'' \in [u', \tau']} \Robust{\sigma^{\tau''}}{\varphi_1} \Big)
d\tau \\
&- \int_{a+u}^{b+u}
\Vee{\tau' \in [a+u, \tau] }
\Big( \Robust{\sigma^{\tau}}{\varphi_2} \wedge \Wedge{\tau'' \in [u, \tau']} \Robust{\sigma^{\tau''}}{\varphi_1} \Big)
d\tau\\
=&
\int_{b+u}^{b+u'}
\Vee{\tau' \in [a+u', \tau] }
\Big( \Robust{\sigma^{\tau'}}{\varphi_2} \wedge \Wedge{\tau'' \in [u', \tau']} \Robust{\sigma^{\tau''}}{\varphi_1} \Big)
d\tau \\
&+\int_{a+u'}^{b+u}
\Vee{\tau' \in [a+u', \tau] }
\Big( \Robust{\sigma^{\tau'}}{\varphi_2} \wedge \Wedge{\tau'' \in [u', \tau']} \Robust{\sigma^{\tau''}}{\varphi_1} \Big)
d\tau \\
&- \int_{a+u'}^{b+u}
\Vee{\tau' \in [a+u, \tau] }
\Big( \Robust{\sigma^{\tau}}{\varphi_2} \wedge \Wedge{\tau'' \in [u, \tau']} \Robust{\sigma^{\tau''}}{\varphi_1} \Big)
d\tau\\
&- \int_{a+u}^{a+u'}
\Vee{\tau' \in [a+u, \tau] }
\Big( \Robust{\sigma^{\tau}}{\varphi_2} \wedge \Wedge{\tau'' \in [u, \tau']} \Robust{\sigma^{\tau''}}{\varphi_1} \Big)
d\tau.\\
\end{align*}
Here the second term and the third term will cancel,
otherwise some $\tau \in [a+u', b+u]$ exists such that
$\{ t_k \mid t_k \in [a+u, \tau]\} \neq \{ t_k \mid t_k \in [a+u', \tau]\}$
or
$\{ t_k \mid t_k \in [u, \tau]\} \neq \{ t_k \mid t_k \in [u', \tau]\}$,
that conflicts with the conditions.
Moreover,
there exists no timestamps in $[b+u, b+u']$ and $[a+u, a+u']$,
hence the integrands in the first term and the last term are
constant functions in each domain of integration.
Therefore,
\[
\Robust{\sigma^{u'}}{\varphi_1 \TUntil{[a,b]} \varphi_2}
- \Robust{\sigma^u}{\varphi_1 \TUntil{[a,b]} \varphi_2}
= \Frac{C}{b-a} (u' - u)
\]
for some constant real number $C$ that does not depend on $u'$.
Because $(t_i)_{i \leq n}$ is finite,
the equivalence relation generated by the above conditions
is also finite.
Consequently, $[\varphi_1 \TUntil{[a,b]} \varphi_2]$ is finitely piecewise-linear.
\qed
\end{myproof}
}
\subsection{Donz\'e et al.'s Algorithm for $\textbf{STL}$ Robustness}
\label{subsec:algoSTL}
We start with reviewing the algorithm~\cite{DBLP:conf/cav/DonzeFM13} for
$\textbf{STL}$ robustness.
Our algorithm for $\textbf{AvSTL}$ robustness relies on it in two ways: 1)
the procedures for averaged modalities like $\TDiaOp{I}$ derive from those for non-averaged
modalities
in~\cite{DBLP:conf/cav/DonzeFM13}; and 2) we use the algorithm
in~\cite{DBLP:conf/cav/DonzeFM13} itself for the non-averaged fragment of
$\textbf{AvSTL}$.
\begin{myremark}\label{rem:DonzeAlgoForPiecewiseLinear}
The algorithm in~\cite{DBLP:conf/cav/DonzeFM13} computes the $\textbf{STL}$
robustness $\Robust{\sigma}{\varphi}$ for a finitely piecewise-\emph{linear}
signal $\sigma$.
We need this feature e.g.\ for computing robustness of the formula
\begin{math}
\BoxOp{} (
\mathtt{heavyBraking}
\end{math}
\begin{math}
\to \TDiaOp{[0,10]}\mathtt{airbag} )
\end{math}: note that, by
Lem.~\ref{lem:preservationOfPiecewiseConstLinear}, the robustness signal
for
$\TDiaOp{[0,10]}\mathtt{airbag} $ is piecewise-linear even if the input
signal is piecewise-constant.
\end{myremark}
Consider computing the robustness
signal $[\DiaOp{[a,b]} \varphi]_{\sigma}$, assuming that the signal
$[\varphi]_{\sigma}$ is already given.\footnote{In the rest of~\S{}\ref{subsec:algoSTL}, for simplicity of
presentation, we assume that $[\varphi]_{\sigma}$ is
piecewise-constant. We note that the algorithm
in~\cite{DBLP:conf/cav/DonzeFM13}
nevertheless extends to
piecewise-linear $[\varphi]_{\sigma}$.} The task calls for finding the supremum of
$[\varphi]_{\sigma}(\tau)$ over $\tau \in [t+a, t+b]$; and this must be done for each $t$. Naively doing so leads to quadratic complexity.
Instead Donz\'e et al.\ in~\cite{DBLP:conf/cav/DonzeFM13} employ a
\emph{sliding window} of size $b-a$ and let it scan the signal
$[\varphi]_{\sigma}$ from right to left. The scan happens once for all,
hence achieving linear complexity. See Fig.~\ref{fig:slidingWindow},
where we take
$[\DiaOp{[0,5]} (x\ge 0)]^+_{\sigma}$
as an example,
and the blue shaded area designates the position of the sliding window.
The window slides from $[3,8]$ to the closest position to the left where
its left-endpoint hits a new timestamped value of $[\varphi]_{\sigma}$,
namely $[1,6]$.
\begin{figure}[tb]
\centering
\scalebox{.8}{
\begin{tabular}{ccccc}
$\cdots
\stackrel[\text{bwd.}]{\text{slide}}{\longmapsto}$
&
\begin{tabular}{c}
\includegraphics[width=.33\textwidth]{pics/StQ/NewStQ3.png}
\\
window in $[3,8]$
\end{tabular}
&
$
\stackrel[\text{bwd.}]{\text{slide}}{\longmapsto}$
&
\begin{tabular}{c}
\includegraphics[width=.33\textwidth]{pics/StQ/NewStQ1.png}
\\
window in $[1,6]$
\end{tabular}
&
$
\stackrel[\text{bwd.}]{\text{slide}}{\longmapsto}\cdots $
\end{tabular}
}
\caption{A sliding window for computing
$[\DiaOp{[0,5]} (x\ge
0)]^+_{\sigma}$; the black line is the signal $\sigma$}
\label{fig:slidingWindow}
\scalebox{.8}{
{\footnotesize
\begin{math}
\def\textstyle{\textstyle}
\def\textstyle{\textstyle}
\xymatrix@R=1.5em@C+4em{
{\begin{array}{c}
\includegraphics[width=.3\textwidth]{pics/StQ/NewStQ3.png}
\\
\bigl[\;(3,0.2)\,(4,0.3)\,(5,0.7)\,(8,0.9)\;\bigr]
\end{array}
}
\ar@{|->}[r]^-{\text{slide}}_-{\text{backward}}
\ar@{|->}[d]^-{\text{dequeue $(8,0.9)$}}
&
{\begin{array}{c}
\includegraphics[width=.3\textwidth]{pics/StQ/NewStQ1.png}
\\
\bigl[\;(1,0.6)\,(5,0.7)\;\bigr]
\end{array}
}
\\
{\begin{array}{c}
\includegraphics[width=.3\textwidth]{pics/StQ/NewDeq_StQ3.png}
\\
\bigl[\;(3,0.2)\,(4,0.3)\,(5,0.7)\;\bigr]
\end{array}
}
\ar@{|->}[r]^-{
\begin{array}{r}
\text{pop $(3,0.2)$}\quad\\
\text{and $(4,0.3)$}
\end{array}
}
&
{\begin{array}{c}
\includegraphics[width=.3\textwidth]{pics/StQ/NewPop_StQ3.png}
\\
\bigl[\;(5,0.7)\;\bigr]
\end{array}
}
\ar@{|->}[u]^-{\text{push $(1,0.6)$}}
}
\end{math}}}
\caption{Use of stackqueues and their operations, in the sliding window algorithm}
\label{fig:stackqueueForSlidingWindow}
\end{figure}
\begin{wrapfigure}[3]{r}{0pt}
\begin{tabular}{c}
\includegraphics[clip,trim=0cm 2.5cm 0cm 2.5cm,width=.33\textwidth]{pics/stackqueue.png}
\\[-1em]
a stackqueue
\end{tabular}
\end{wrapfigure}
It is enough to know the shape of the blue (partial) signal in
Fig.~\ref{fig:slidingWindow}, at each position of the window.
The blue signal denotes the (black) signal $\sigma$'s
local supremum within the window; more precisely,
it denotes the value of the signal
$\Robust{\sigma^t}{\DiaOp{[0,\tau]}(x\ge 0)}^+$ at time $t+\tau$, where
$\tau \in [0,5]$ and $t$ is the leftmost position of the window.
We can immediately read off
the signal
$[\DiaOp{[0,5]} (x\ge 0)]^+_{\sigma}$
from the blue signals:
the former is the latter's value at the
rightmost position of the window.
The keys in
the algorithms
in~\cite{DBLP:conf/cav/DonzeFM13,DBLP:journals/njc/Lemire06}
lie in:
\begin{itemize}
\item use of the \emph{stackqueue} data structure (depicted above on the right) for the
purpose of representing the blue (partial) signal in
Fig.~\ref{fig:slidingWindow}; and
\item use of the operations \emph{push}, \emph{pop} and
\emph{dequeue} for updating the blue signal.
\end{itemize}
See Fig.~\ref{fig:stackqueueForSlidingWindow}, where each entry of
a stackqueue is a timestamped value $(t,r)$. We see that the slide of the window, from top-left to
top-right in Fig.~\ref{fig:stackqueueForSlidingWindow},
is expressed by dequeue, pop and then push operations to stackqueues (in
Fig.~\ref{fig:stackqueueForSlidingWindow}: from top-left to bottom-left,
bottom-right and then top-right).
Pseudocode for the algorithm is deferred to
Appendix~\ref{appendix:algoDia} due to lack of space.
\subsection{An Algorithm for $\textbf{AvSTL}$ Robustness}
\label{subsec:algoAvSTL}
It turns out that the last algorithm is readily applicable to
computing $\textbf{AvSTL}$ robustness. Consider an averaged-eventually formula
$\TDiaOp{[a,b]} \varphi$ as an example. What we have to compute is
the size of the shaded areas in Fig.~\ref{fig:slidingWindow} (see
also Fig.~\ref{fig:averagedDiamond}); and the shape of the blue
signals in Fig.~\ref{fig:slidingWindow} carry just enough information
to do so.
Pseudocode for the adaptation of the previous algorithm
(in~\S{}\ref{subsec:algoSTL}) to
$\TDiaOp{[a,b]} \varphi$ is found in
Algorithm~\ref{algo:tdia}.
Its complexity is linear with respect to the number $n$ of the timestamp
values that represent the signal $[\varphi]_{\sigma}$.
\begin{algorithm}[tbp]
\caption{An algorithm for computing $[\TDiaOp{[a,b]} \varphi]_{\sigma}$}
\label{algo:tdia}
\begin{algorithmic}
\Require An FPC signal $[\varphi]_{\sigma}$
given as a sequence $(t_{0},r_{0}),\dotsc,(t_{n},r_{n})$
\Ensure The FPL signal
$[\TDiaOp{[a,b]} \varphi]_{\sigma}$
\State $t_{\mathsf{temp}} := t_n - a$;
\State $F := \bigl[ \;(t_{\mathsf{temp}}+a, [\varphi]_{\sigma}(t_{\mathsf{temp}} + a)) \;\bigr]$;
\Comment $F$ is the FPC signal $\tau \mapsto \Robust{\sigma^t}{\DiaOp{[a,\tau]}\varphi}$
\State $s := (b-a) \cdot [\varphi]_{\sigma}(t_{\mathsf{temp}} + a)$;
\Comment The area of $F$
\State $G := \bigl[ \;(t_{\mathsf{temp}}, s / (b-a), 0) \;\bigr]$;
\Comment The FPC signal $[\TDiaOp{[a,b]} \varphi]_{\sigma}$
\While{$t_{\mathsf{temp}} \geq 0$}
\State $t_{\mathsf{old}} := t_{\mathsf{temp}}$;
\State $t_{\mathsf{temp}} :=$ the greatest $t$ such that
$t < t_{\mathsf{old}} \wedge \bigl(\exists t_i.\, t + a = t_i \vee \exists (t', r') \in F. \; t+ b = t') \bigr)$;
\State $\mathsf{Deq} := \{(t, r) \in F \mid t > t_{\mathsf{temp}} + b\}$; \quad $F := F \setminus \mathsf{Deq}$;
\Comment{Dequeue old elements in $F$}
\State $\mathsf{Pop} := \{(t, r) \in F \mid r \leq [\varphi]_{\sigma}(t_{\mathsf{temp}} + a) \}$; \quad $F := F \setminus \mathsf{Pop}$;
\Comment{Pop small elements in $F$}
\State $t_{\mathsf{Pop}} := \mathsf{min} \{t \mid(t,r) \in F \; \text{ or } \; t = t_{\mathsf{temp}} + b\}$;
\State $F := \big[ (t_{\mathsf{temp}}+a, [\varphi]_{\sigma}(t_{\mathsf{temp}} + a))\big] \cup F$
\Comment{Push the left endpoint of the window to $F$}
\State $r_{\mathsf{left}} := \mathsf{min}\{ r \mid (t,r) \in F \}$;
\State $r_{\mathsf{right}} := \mathsf{max}\{ r \mid (t,r) \in F \}$;
\State $s := s
- (t_{\mathsf{old}} - t_{\mathsf{temp}}) \cdot r_{\mathsf{right}}
- \mathsf{area}(\mathsf{Pop})
+ (t_{\mathsf{Pop}} - (t_{\mathsf{temp}} +a )) \cdot r_{\mathsf{left}}$
\State $G := \{(t_{\mathsf{temp}}, s/(b-a),r_{\mathsf{right}} - r_{\mathsf{left}})\} \cup G$
\EndWhile
\end{algorithmic}
\end{algorithm}
An algorithm for the averaged-henceforth formula
$[\TBoxOp{[a,b]} \varphi]_{\sigma}$ is similar. Extensions to
averaged-until and averaged-release operators are possible, too; they
use doubly-linked lists in place of stackqueues (see Appendix~\ref{appendix:algoTUntil}).
Combining with the algorithm in~\S{}\ref{subsec:algoSTL} to deal with
non-averaged temporal operators, we have the following
complexity result. The complexity is the same as for $\textbf{STL}$~\cite{DBLP:conf/cav/DonzeFM13}.
\begin{mytheorem}\label{thm:complexity_rel}
Let $\varphi$ be an $\textbf{AvSTL}$ formula
in which averaged modalities are not nested.
Let $\sigma$ be a finitely piecewise-constant signal.
Then there exists an algorithm
to compute
$\Robust{\sigma}{\varphi}^{+}$
with time-complexity in
$\mathcal{O}(d^{|\varphi|} |\varphi| |\sigma|)$
for some constant $d$.
The same is true for the negative robustness
$\Robust{\sigma}{\varphi}^{-}$.
\qed
\end{mytheorem}
\begin{myremark}
The reason for our restriction to finitely piecewise-constant input
signals is hinted in Rem.~\ref{rem:DonzeAlgoForPiecewiseLinear}; let us
further elaborate on it.
There the averaged modality $\TDiaOp{[0,10]}$ turns a piecewise-constant signal into a
piecewise-linear one
(Lem.~\ref{lem:preservationOfPiecewiseConstLinear}); and then the
additional Boolean connectives and non-averaged
modalities (outside $\TDiaOp{[0,10]}$) are taken care of by the algorithm
in~\cite{DBLP:conf/cav/DonzeFM13}, one that is restricted
to piecewise-linear input.
It is not methodologically hard to extend this workflow to
piecewise-\emph{polynomial} input signals (hence to nested averaged
modalities as well). Such an extension however calls
for computing local suprema of polynomials, as well as their
intersections---tasks that are drastically easier with affine
functions. We therefore expect the extension to
piecewise-polynomial signals to be computationally
much more expensive.
\end{myremark}
\section{Enhanced Falsification: Implementation and Experiments}
\label{sec:experiments}
\begin{table}[ptb]
\scriptsize
\centering
\begin{minipage}{\textwidth}
\textbf{Problem 1. } Falsification means finding an input signal
that keeps the engine speed $\omega$ below 2000 rpm, for $T$
seconds. The bigger $T$ is, the harder the problem is.
We applied $\Diamond$-refinement.
\end{minipage}
\begin{tabular}{c||r|r|r|r|r|r|r|r|r}
\textbf{Problem 1}
&\multicolumn{3}{|c|}{$T = 20$} &\multicolumn{3}{|c|}{$T = 30$} &\multicolumn{3}{|c}{$T = 40$}\\ \hline
Specification & Succ. & Iter. & Time & Succ. & Iter. & Time &
Succ. & Iter. & Time \\
to be falsified
& $\mathbf{/100}$ & (Succ.) & (Succ.) &$\mathbf{/100}$ & (Succ.) & (Succ.)&$\mathbf{/100}$ & (Succ.) & (Succ.)\\ \hline\hline
$\DiaOp{[0,T]}{(\omega \geq 2000)}$
& 100& 128.8& 20.2& 81& 440.9& 82.5& 32& 834.3& 162.9\\
& & 128.8& 20.2& & 309.7& 59.0& & 482.2& 94.4\\\hline
$\TDiaOp{[0,T]}{(\omega \geq 2000)}$
& 100& 123.9& 22.9& 98& 249.8& 46.1 & 81& 539.6& 110.9\\
& & 123.9& 22.9& & 234.5& 43.4 & & 431.6& 89.2\\
\end{tabular}
\vspace{1em}
\begin{minipage}{\textwidth}
\textbf{Problem 2.} Falsification means finding an input signal
that keeps $\omega$ within a range of 3500--4500 rpm for $T$
consecutive seconds, at a certain stage.
We applied $\Diamond$-refinement.
\end{minipage}
\begin{tabular}{c||r|r|r}
\textbf{Problem 2}
&\multicolumn{3}{|c}{$T = 10$} \\ \hline
Specification & Succ. & Iter. & Time\\
to be falsified
& $\mathbf{/100}$ & (Succ.) & (Succ.) \\ \hline\hline
$\BoxOp{}\DiaOp{[0, T]}(\omega \leq 3500 \vee \omega \geq 4500)$
& 45& 625.4& 209.1\\
& & 167.7& 56.1\\\hline
$\BoxOp{}\TDiaOp{[0, T]}(\omega \leq 3500 \vee \omega \geq 4500)$
& 74& 442.0& 154.3\\
& & 245.9& 86.6\\
\end{tabular}
\vspace{1em}
\begin{minipage}{\textwidth}
\textbf{Problem 3.} Falsification means finding an input signal
that shifts the gear into the fourth within $T$ seconds.
The smaller $T$ is, the harder the problem is. Here $\mathtt{gear}_4$
is a propositional variable.
We applied $\Box$-refinement.
\end{minipage}
\begin{tabular}{c||r|r|r|r|r|r|r|r|r}
\textbf{Problem 3}
&\multicolumn{3}{|c|}{$T = 4$} &\multicolumn{3}{|c|}{$T = 4.5$} &\multicolumn{3}{|c}{$T = 5$}\\ \hline
Specification & Succ. & Iter. & Time & Succ. & Iter. & Time &
Succ. & Iter. & Time \\
to be falsified
& $\mathbf{/20}$ & (Succ.) & (Succ.) &$\mathbf{/20}$ & (Succ.) & (Succ.)&$\mathbf{/20}$ & (Succ.) & (Succ.)\\ \hline\hline
$\BoxOp{[0,T]}{\neg \mathtt{gear}_4}$
& 0& 1000& 166.9& 11& 742.8 & 122.9& 18& 449.0 & 71.8 \\
& & --& --& & 532.3 & 87.5& & 387.7 & 61.9 \\ \hline
$\BoxOp{[0,T]}{\neg \mathtt{gear}_4}$
& 17& 570.1& 94.0& 20& 250.5& 40.3& 20& 107.5& 17.6\\
$\wedge \TBoxOp{[T,10]}{\neg \mathtt{gear}_4}$
& & 494.2& 81.8& & 250.5& 40.3& & 107.5& 17.6\\
\end{tabular}
\vspace{1em}
\begin{minipage}{\textwidth}
\textbf{Problem 4.} Falsification means finding input
with which the gear never stays in the third consecutively for $T$ seconds.
The smaller $T$ is, the harder the problem is.
Here $\mathtt{gear}_3$
is a propositional variable.
We applied $\Box$-refinement.
\end{minipage}
\begin{tabular}{c||r|r|r|r|r|r}
\textbf{Problem 4}
&\multicolumn{3}{|c|}{$T = 1$} &\multicolumn{3}{|c}{$T = 2$} \\ \hline
Specification & Succ. & Iter. & Time & Succ. & Iter. & Time \\
to be falsified
& $\mathbf{/20}$ & (Succ.) & (Succ.) &$\mathbf{/20}$ & (Succ.) & (Succ.)\\ \hline\hline
$\DiaOp{}\big(\BoxOp{[0, T]}\mathtt{gear}_3\big)$
& 14& 556.1& 132.0& 20& 82.8& 20.6\\
& & 365.8& 87.1& & 82.8& 20.6\\\hline
$\DiaOp{}\big(\BoxOp{[0, T]}\mathtt{gear}_3 \wedge \TBoxOp{[T, 10]}\mathtt{gear}_3 \big)$
& 20& 105.1& 36.3& 20& 29.7& 10.2\\
& & 105.1& 36.3& 20& 29.7& 10.2\\
\end{tabular}
\vspace{1em}
\begin{minipage}{\textwidth}
\textbf{Problem 5.} Falsification means finding input
that violates the following requirement: \emph{after the gear is
shifted, it stays the same for $T$ seconds.}
(the smaller $T$, the harder).
$\mathtt{gear}_{1},\dotsc,\mathtt{gear}_{4}$ are propositional variables.
We applied $\Box$-refinement.
\end{minipage}
\begin{tabular}{c||r|r|r|r|r|r|r|r|r}
\textbf{Problem 5} ($\varepsilon = 0.04$)
&\multicolumn{3}{|c|}{$T = 0.8$} &\multicolumn{3}{|c|}{$T = 1$} &\multicolumn{3}{|c}{$T = 2$}\\ \hline
Specification & Succ. & Iter. & Time & Succ. & Iter. & Time &
Succ. & Iter. & Time \\
to be falsified
& $\mathbf{/20}$ & (Succ.) & (Succ.) & $\mathbf{/20}$& (Succ.) & (Succ.)& $\mathbf{/20}$ & (Succ.) & (Succ.)\\ \hline\hline
{\scriptsize $\bigwedge_{i=1,\dotsc,4}\BoxOp{}\Big(\big( \neg \mathtt{gear}_i \wedge \DiaOp{[0,\varepsilon]}\mathtt{gear}_i \big)$}
& 2& 972.5 & 402.5& 19& 356.8& 155.6& 20& 27.4& 11.8\\
{\scriptsize $\to \big(\BoxOp{[\varepsilon, T+\varepsilon]} \mathtt{gear}_i \big) \Big)$}
& & 724.5 & 297.8& & 322.9& 140.9& & 27.4& 11.8\\ \hline
{\scriptsize $\bigwedge_{i=1,\dotsc,4}\BoxOp{}\Big(\big(\neg \mathtt{gear}_i \wedge \DiaOp{[0,\varepsilon]}\mathtt{gear}_i \big)$}
& 12& 561.1& 349.1& 20& 93.1& 57.8& 20& 42.7& 26.9\\
{\scriptsize $\to \big(\BoxOp{[\varepsilon, T+\varepsilon]} \mathtt{gear}_i\wedge \TBoxOp{[T+\varepsilon, 5]} \mathtt{gear}_i\big)\Big)$}
& & 268.5& 167.3& & 93.1& 57.8& & 42.7& 26.9\\
\end{tabular}
\vspace{1em}
\begin{minipage}{\textwidth}
\textbf{Problem 6.}
Falsification means finding an input signal
that steers the vehicle speed $v$ over 85 kph within $T$ seconds,
while keeping the engine speed $\omega$ below 4500 rpm.
The smaller $T$ is, the harder the problem is.
We applied $\Box$-refinement.
\end{minipage}
\begin{tabular}{c||r|r|r|r|r|r}
\textbf{Problem 6}
&\multicolumn{3}{|c|}{$T = 10$} &\multicolumn{3}{|c}{$T = 12$} \\ \hline
Specification & Succ. & Iter. & Time & Succ. & Iter. & Time \\
to be falsified
& $\mathbf{/20}$ & (Succ.) & (Succ.) &$\mathbf{/20}$ & (Succ.) & (Succ.)\\ \hline\hline
$\BoxOp{[0, T]}{(v \leq 85)} \vee \DiaOp{}{(\omega \geq 4500)}$
& 12& 714.9& 141.4& 17& 374.5& 72.2\\
& & 524.9& 108.1& & 264.1& 51.2\\\hline
$\big(\BoxOp{[0, T]}{(v \leq 85)} \wedge \TBoxOp{[T, 20]}{(v \leq 85)} \big)$
&12& 766.7& 149.0& 20& 423.6& 85.7\\
$\vee \DiaOp{}{(\omega \geq 4500)}$
& & 611.2& 118.9& & 423.6& 85.7\\
\end{tabular}
\caption{Experiment results. Time is in seconds. The ``Succ.''
columns show how many trials succeeded among the designated number of trials;
the ``Iter.'' columns show the average number of iterations of the
S-TaLiRo loop, executed in each trial (max.\ 1000); and the ``Time'' columns show
the average time that each trial took. For the last two we also show
the average over \emph{successful} trials.}
\label{table:result}
%
%
\end{table}
\begin{wrapfigure}[13]{r}{.338\textwidth}
\includegraphics[clip,trim=0cm 15.5cm 25cm 0cm,width=.338\textwidth]
{pics/staliroModif.pdf}
\vspace*{-2em}
\caption{An overview of S-TaLiRo (from~\cite{WEB:S_TaLiRo}), with our modification}
\label{fig:staliro}
\end{wrapfigure}
We claim that our logic $\textbf{AvSTL}$ achieves a good balance between
expressivity---that communicates a designer's intention more faithfully
to a falsification
solver---and computational cost, thus contributing to the model-based
development of cyber-physical systems. In this section we present our
implementation that combines: 1)
S-TaLiRo~\cite{DBLP:conf/tacas/AnnpureddyLFS11}, one of the
state-of-art falsification solvers that relies on robust MTL semantics and
stochastic optimization; and 2) the \emph{$\textbf{AvSTL}$ evaluator},
an implementation of the algorithm
in~\S{}\ref{subsec:algoAvSTL}. Our experiments are on automotive
examples of falsification problems;
the results indicate that (refinement of specifications by) $\textbf{AvSTL}$ brings considerable performance
improvement.
\subsubsection{Implementation}
S-TaLiRo~\cite{DBLP:conf/tacas/AnnpureddyLFS11} is
``a Matlab toolbox that searches for trajectories of minimal robustness
in Simulink/Stateflow''~\cite{WEB:S_TaLiRo}. Recall the formalization of
a falsification problem (\S{}\ref{sec:introduction}). S-TaLiRo's input
is: 1) a
model $\mathcal{M}$ that is a Simulink/Stateflow model; and 2) a specification
$\varphi$ that is an $\textbf{STL}$ formula.
S-TaLiRo employs stochastic simulation in the following
\emph{S-TaLiRo loop}:
\begin{enumerate}
\item Choose an input signal $\sigma_{\mathsf{in}}$ randomly.
\item Compute the output signal
$\mathcal{M}(\sigma_{\mathsf{in}})$ with Simulink.
\item Compute the robustness
$\Robust{\mathcal{M}(\sigma_{\mathsf{in}})}{\varphi}$.
\item If the robustness is $\leq 0$ then return $\sigma_{\mathsf{in}}$
as a critical path. Otherwise choose a new $\sigma_{\mathsf{in}}$
(hopefully with a smaller robustness)
and go back to Step 2.
\end{enumerate}
Our modification of S-TaLiRo consists of: 1) changing the specification formalism from
$\textbf{STL}$ to $\textbf{AvSTL}$ (with the hope that the robustness
$\Robust{\mathcal{M}(\sigma_{\mathsf{in}})}{\varphi}^+$ carries more
information to be exploited in stochastic optimization); and 2) using, in
Step 3 of the above loop, the $\textbf{AvSTL}$
evaluator based on the sliding-window algorithm
in~\S{}\ref{sec:algorithm}.
See Fig.~\ref{fig:staliro}.
\subsubsection{Experiments}
As a model $\mathcal{M}$ we used the automatic transmission model
from~\cite{HoxhaAF14arch1}, where it is offered ``as benchmarks
for testing-based falsification''~\cite{HoxhaAF14arch1}.
The same model has been used
in several works~\cite{DBLP:conf/pts/YangHF12, 6315384, DBLP:conf/hybrid/JinDDS13}.
The model has two input ports (\emph{$\mathtt{throttle}$} and
\emph{$\mathtt{brake}$}) and six output ports (the engine speed $\omega$,
the vehicle speed $v$, and four mutually-exclusive Boolean ports
$\mathtt{gear}_{1},\dotsc,\mathtt{gear}_{4}$ for the current gear).
Further illustration is in Appendix~\ref{appendix:ATModel}.
As a specification $\varphi$ to falsify, we took six examples from~\cite{HoxhaAF14arch1},
sometimes with minor modifications. They constitute Problems 1--6 in Table~\ref{table:result}.
Our goal is to examine the effect of our modification to S-TaLiRo.
For the model $\mathcal{M}$ (that is fixed) and each of the six specifications
$\varphi$, experiments are done with:
\begin{itemize}
\item $\mathcal{M}$ and the original $\textbf{STL}$ formula $\varphi$, as a
control experiment;
and
\item $\mathcal{M}$ and the $\textbf{AvSTL}$ formula $\varphi'$ that is
obtained from $\varphi$ as a
refinement. The latter specifically involves \emph{$\Diamond$-refinement} and
\emph{$\Box$-refinement} described in~\S{}\ref{subsec:soundnessOfEnrichments}.
\end{itemize}
Faster, or more frequent, falsification in the latter setting witnesses
effectiveness of our $\textbf{AvSTL}$ approach. We note that
falsifying $\varphi'$ indeed means falsifying $\varphi$, because of the
soundness of the refinement (Prop.~\ref{prop:diaRefinement} and~\ref{prop:BoxRefinement}).
A single falsification \emph{trial} consists of at most 1000 \emph{iterations} of the S-TaLiRo
loop. For each specification $\varphi$ (i.e. for each problem in
Table~\ref{table:result}) we made
20--100 falsification trials,
sometimes
with different parameter values $T$. We made multiple trials
because of the stochastic nature of S-TaLiRo.
\subsubsection{Experiment Results and Discussion}
The experiment results are in Table~\ref{table:result}.
We used
Matlab R2014b and
S-TaLiRo ver.1.6 beta
on
ThinkPad T530 with Intel Core i7-3520M 2.90GHz CPU with 3.7GB memory.
The OS is Ubuntu14.04 LTS (64-bit).
Notable performance improvement is observed in Problems 3--5,
especially in their harder instances. For
example, our $\textbf{AvSTL}$ enrichment made 17 out of 20 trials succeed in
Problem 3 ($T=4$), while no trials succeeded with the original $\textbf{STL}$
specification. A similar extreme performance gap is observed also in
Problem 5 ($T=0.8$).
Such performance improvement in Problems 3--5 is not surprising. The
specifications for these problems
are concerned solely with the propositional variables
$\mathtt{gear}_{i}$ (cf.\ Rem.~\ref{rem:propVar});
and the space
robustness semantics for $\textbf{STL}$ assigns to these specifications only $0$
or $1$
(but no values in-between) as their
truth
values. We can imagine such ``discrete'' robustness values give few clues
to stochastic optimization algorithms.
Both of
$\Diamond$- and
$\Box$-refinement
in~\S{}\ref{subsec:soundnessOfEnrichments}
turn out to be helpful. The latter's effectiveness is observed in
Problems 3--5; the former improves a success rate from 32/100 to 81/100
in Problem 1 ($T=40$).
Overall, the experiment results seem to support our claim that the complexity of
(computing robustness values in) $\textbf{AvSTL}$ is tractable. There is no big
difference in the time
each iteration takes, between the $\textbf{STL}$ case and the $\textbf{AvSTL}$ case.
\section{Conclusions and Future Work}
We introduced $\textbf{AvSTL}$, an extension of $\textbf{STL}$ with \emph{averaged}
temporal
operators. It adequately captures both space and time robustness; and
we presented an algorithm for computing robustness that is
linear-time with respect to the ``size'' of an input signal. Its use
in falsification of CPS is demonstrated by our prototype that modifies S-TaLiRo.
As future work, we wish to compare our averaged temporal operators with
other quantitative temporal operators, among which are the
\emph{discounting}
ones~\cite{DBLP:dblp_journals/jacm/AlurFH96,DBLP:conf/tacas/AlmagorBK14}. The
latter are closely related to \emph{mean-payoff}
conditions~\cite{Ehrenfeucht1979, DBLP:conf/lics/ChatterjeeHJ05} as well
as to \emph{energy
constraints}~\cite{DBLP:conf/formats/BouyerFLMS08,DBLP:conf/hybrid/BrenguierCR14},
all of which are studied principally in the context of automata theory.
Application of $\textbf{AvSTL}$ to problems other than falsification is another
important direction. Among them is \emph{parameter synthesis}, another
task that S-TaLiRo is capable of.
We are now looking at application to
\emph{sequence classification} (see
e.g.~\cite{DBLP:conf/hybrid/KongJAGB14}), too,
whose significant role in model-based development of CPS is widely acknowledged.
\bibliographystyle{plain}
|
{
"redpajama_set_name": "RedPajamaArXiv"
}
| 4,767
|
We always need a boost in self-development, and one way in which we can get a boost is by meditating. When be become stressed and feeling down in the dumps our brain becomes fatigued and doesn't want to work with our mind and body. Giving your brain the proper exercise by meditating will make you feel younger and give you the gumption to be more successful.
Every day the technology world is coming up with new ideas on how to be happier and successful. Right now meditation is one of the most used and most successful tools for achieving goals. Meditation has proven to change how we view ourselves and how others view us too. Learn to use today's technology to reprogram and exercise your brain for self-development with the practice of meditation.
Learn to reprogram you brain by giving it exercise. The brain needs exercise to keep it healthy just like our bodies do. You can reprogram yourself to think positively by learning to meditate. Reprogramming your brain, allows you to to focus and use meditation for self-development.
Begin the process of giving your brain exercise by reprogramming it to think positive. First, you need to sit down and find your inner feelings by stepping inside your thoughts. Focus on how you feel with the performance and success you have already achieved. Using self-talk, ask yourself if you've performed and reached the goals you always wanted to meet. Ask yourself if you are you where you want to be, remembering there is always room for improvement to succeed in life.
Write your thoughts on paper so you can reread them over again. Now write down how you can make changes to reach where you want to be in regards to health and success. Writing your goals and changes on paper will bring them to life to help you to reprogram your brain.
By reviewing the two lists each day you will be exercising your brain to override the past and failures in order to think positively and increase your self-development skills. Exercising your brain by writing your list of goals will help to wake it up for the long ride to success.
Wake up your brain and teach it to relax to help relieve stress by reprogramming it to think positive. With a positive thinking brain, it will help you to learn the skill of meditation.
Meditation combined with positive thinking will help your self-development skills and will get you through the rough times of stress and anger. Your list of goals will be getting shorter as you reach each one so keep adding to it to exercise in meditation for self-development.
You can learn to meditate with your eyes open and be alert at the same time. To be successful with meditation at work or in the privacy of your own home, stop and think positively before you make a bad decision.
Learn to focus on one thing at a time in order to make good decisions. Align your goals with your inner feelings. Using meditation for self-development will lead you into a life of happiness and success.
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 1,807
|
import {getClass, NotEnumerable, Type} from "@tsed/core";
import * as Express from "express";
import {IRouterOptions} from "../../config/interfaces/IRouterOptions";
import {ProviderStorable} from "../../di/class/ProviderStorable";
import {IControllerMiddlewares, IControllerOptions} from "../interfaces";
import {IChildrenController} from "../interfaces/IChildrenController";
import {EndpointRegistry} from "../registries/EndpointRegistry";
import {EndpointMetadata} from "./EndpointMetadata";
export class ControllerProvider extends ProviderStorable<any> implements IControllerOptions {
/**
* The path for the controller
*/
@NotEnumerable()
private _path: string;
/**
*
*/
@NotEnumerable()
private _routerOptions: IRouterOptions;
/**
* The path for the RouterController when the controller will be mounted to the Express Application.
*/
@NotEnumerable()
private _routerPaths: string[] = [];
/**
* Controllers that depend to this controller.
* @type {Array}
* @private
*/
@NotEnumerable()
private _dependencies: IChildrenController[] = [];
@NotEnumerable()
public router: Express.Router;
@NotEnumerable()
private _middlewares: IControllerMiddlewares = {
useBefore: [],
use: [],
useAfter: []
};
constructor(provide: any) {
super(provide);
this.type = "controller";
}
/**
*
* @returns {string}
*/
get path(): string {
return this._path;
}
/**
* set path
* @param value
*/
set path(value: string) {
this._path = value;
}
get routerPaths(): string[] {
return this._routerPaths;
}
/**
*
* @returns {Endpoint[]}
*/
get endpoints(): EndpointMetadata[] {
return EndpointRegistry.getEndpoints(getClass(this.provide));
}
/**
*
* @returns {Type<any>[]}
*/
get dependencies(): IChildrenController[] {
return this._dependencies;
}
/**
*
* @param dependencies
*/
set dependencies(dependencies: IChildrenController[]) {
this._dependencies = dependencies;
this._dependencies.forEach(d => d.$parentCtrl = this);
}
/**
*
* @returns {IRouterOptions}
*/
get routerOptions(): IRouterOptions {
return this._routerOptions;
}
/**
*
* @returns {ControllerProvider}
*/
get parent() {
return this.provide.$parentCtrl;
}
/**
*
* @param value
*/
set routerOptions(value: IRouterOptions) {
this._routerOptions = value;
}
/**
*
* @returns {any[]}
*/
get middlewares(): IControllerMiddlewares {
return this._middlewares;
}
/**
*
* @param middlewares
*/
set middlewares(middlewares: IControllerMiddlewares) {
const concat = (key: string, a: any, b: any) => a[key] = a[key].concat(b[key]);
Object.keys(middlewares).forEach((key: string) => {
concat(key, this._middlewares, middlewares);
});
}
/**
*
* @param {string} path
*/
public pushRouterPath(path: string) {
this._routerPaths.push(path);
}
/**
* Resolve final endpoint url.
*/
public getEndpointUrl = (routerPath: string): string =>
(routerPath === this.path ? this.path : (routerPath || "") + this.path).replace(/\/\//gi, "/");
/**
*
*/
public hasEndpointUrl() {
return !!this.path;
}
/**
*
* @returns {boolean}
*/
public hasDependencies(): boolean {
return !!this.dependencies.length;
}
/**
*
* @returns {boolean}
*/
public hasParent(): boolean {
return !!this.provide.$parentCtrl;
}
}
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 4,248
|
{"url":"http:\/\/www.proofwiki.org\/wiki\/Bernoulli_Process_as_Geometric_Distribution","text":"# Bernoulli Process as Geometric Distribution\n\n## Theorem\n\nLet $\\left \\langle{X_i}\\right \\rangle$ be a Bernoulli process with parameter $p$.\n\nLet $\\mathcal E$ be the experiment which consists of performing the Bernoulli trial $X_i$ until a failure occurs, and then stop.\n\nLet $k$ be the number of successes before a failure is encountered.\n\nThen $k$ is modelled by a geometric distribution with parameter $p$.\n\n### Shifted Geometric Distribution\n\nLet $\\left \\langle{Y_i}\\right \\rangle$ be a Bernoulli process with parameter $p$.\n\nLet $\\mathcal E$ be the experiment which consists of performing the Bernoulli trial $Y_i$ as many times as it takes to achieve a success, and then stop.\n\nLet $k$ be the number of Bernoulli trials to achieve a success.\n\nThen $k$ is modelled by a shifted geometric distribution with parameter $p$.\n\n## Proof\n\nFollows directly from the definition of geometric distribution.\n\nLet $X$ be the discrete random variable defined as the number of successes before a failure is encountered.\n\nThus the last trial (and the last trial only) will be a failure, and the others will be successes.\n\nThe probability that $k$ successes are followed by a failure is:\n\n$\\Pr \\left({X = k}\\right) = p^k \\left({1 - p}\\right)$\n\nHence the result.\n\n$\\blacksquare$","date":"2013-12-11 18:31:29","metadata":"{\"extraction_info\": {\"found_math\": true, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 0, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 1, \"mathjax_display_tex\": 0, \"mathjax_asciimath\": 0, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 0, \"wp-katex-eq\": 0, \"align\": 0, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.8962945938110352, \"perplexity\": 222.80471067540353}, \"config\": {\"markdown_headings\": true, \"markdown_code\": true, \"boilerplate_config\": {\"ratio_threshold\": 0.18, \"absolute_threshold\": 20, \"end_threshold\": 15, \"enable\": true}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2013-48\/segments\/1386164043130\/warc\/CC-MAIN-20131204133403-00086-ip-10-33-133-15.ec2.internal.warc.gz\"}"}
| null | null |
<?xml version="1.0" encoding="utf-8"?>
<android.support.v4.widget.DrawerLayout
android:id="@+id/drawer_layout"
xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:app="http://schemas.android.com/apk/res-auto"
xmlns:tools="http://schemas.android.com/tools"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:fitsSystemWindows="true"
tools:openDrawer="start">
<android.support.design.widget.CoordinatorLayout
android:layout_width="match_parent"
android:layout_height="match_parent"
android:fitsSystemWindows="true"
tools:context="com.apsolete.machinery.MainActivity">
<android.support.design.widget.AppBarLayout
android:layout_width="match_parent"
android:layout_height="wrap_content"
android:theme="@style/AppTheme.AppBarOverlay">
<android.support.v7.widget.Toolbar
android:id="@+id/toolbar"
android:layout_width="match_parent"
android:layout_height="?attr/actionBarSize"
android:background="?attr/colorPrimary"
app:popupTheme="@style/AppTheme.PopupOverlay"/>
</android.support.design.widget.AppBarLayout>
<!-- main content -->
<android.support.v4.widget.NestedScrollView
android:layout_width="match_parent"
android:layout_height="match_parent"
app:layout_behavior="@string/appbar_scrolling_view_behavior">
<FrameLayout
android:id="@+id/contentLayout"
android:layout_width="match_parent"
android:layout_height="match_parent"/>
</android.support.v4.widget.NestedScrollView>
<include layout="@layout/fabs_main"/>
</android.support.design.widget.CoordinatorLayout>
<android.support.design.widget.NavigationView
android:id="@+id/nav_view"
android:layout_width="wrap_content"
android:layout_height="match_parent"
android:layout_gravity="start"
android:fitsSystemWindows="true"
app:headerLayout="@layout/header_main"
app:menu="@menu/activity_main_drawer"/>
</android.support.v4.widget.DrawerLayout>
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 5,384
|
{% load i18n %}
<div class="messages">
{% for message in messages %}
{% if "info" in message.tags %}
<div class="alert alert-block alert-info fade in">
<a class="close" data-dismiss="alert" href="#">×</a>
<p><strong>{% trans "Info: " %}</strong>{{ message }}</p>
</div>
{% endif %}
{% if "warning" in message.tags %}
<div class="alert alert-block alert-warning fade in">
<a class="close" data-dismiss="alert" href="#">×</a>
<p><strong>{% trans "Warning: " %}</strong>{{ message }}</p>
</div>
{% endif %}
{% if "success" in message.tags %}
<div class="alert alert-block alert-success fade in">
<a class="close" data-dismiss="alert" href="#">×</a>
<p><strong>{% trans "Success: " %}</strong>{{ message }}</p>
</div>
{% endif %}
{% if "error" in message.tags %}
<div class="alert alert-block alert-error fade in">
<a class="close" data-dismiss="alert" href="#">×</a>
<p><strong>{% trans "Error: " %}</strong>{{ message }}</p>
</div>
{% endif %}
{% endfor %}
</div>
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 3,720
|
\section{INTRODUCTION}
\label{sec1}
Modern probes of material properties, such as the new inelastic neutron
scattering facilities, are reaching such unprecedented sensitivity that
they can measure the spectrum not only of a single quasiparticle
excitation, but even two-particle excitations \cite{tennant2003}.
These quasiparticles
can collide, scatter, or form bound states just like elementary
particles in free space. The spectrum of the multiparticle excitations
is a crucial indicator of the underlying dynamics of the system.
One of the principal theoretical means of predicting the excitation
spectrum is the method of high-order perturbation series expansions
\cite{oitmaa2006}.
We have previously used a `linked-cluster' approach to generate series
expansions for 2-particle states in 1-dimensional models \cite{trebst2000},
but for
2-dimensional models the only high-order calculations carried out so far have been
those of Uhrig's group (e.g. \cite{knetter2000}),
using the
`continuous unitary
transformation' (CUTS) method, which is of only limited applicability.
One of our aims here is to extend the linked-cluster approach to
2-dimensional models, starting with the bilayer model as a simple
example.
\begin{figure}
\includegraphics[width=0.7\linewidth]{fig1.eps}
\caption{The bilayer Heisenberg model on a square lattice.}
\label{fig1}
\end{figure}
The $S = 1/2$ bilayer Heisenberg antiferromagnet has attracted continuing
interest from both experimentalists and theoreticians. Experimentally, it is
of interest because many of the cuprate superconductors contain pairs of
weakly
coupled copper oxide
layers \cite{reznik1996,hayden1996,millis1996,pailhes2006}. Recently, the
organic material
piperazinium hexachlorodicuprate has also been found to have a bilayer
structure
\cite{stone2006}. Theoretically, it is of particular interest because it is one of the
simplest two-dimensional systems to display a dimerized, valence-bond-solid
ground state, when the interplane coupling is large. There have also
been discussions of the model in the presence of a magnetic field
\cite{sommer2001}, or doping \cite{sandvik2002,pailhes2006,zhou2007}, or
disorder \cite{sknepnek2006}.
The structure of the model is shown in Figure \ref{fig1}, with $S = 1/2$ spins
on the sites of the lattice, and Heisenberg antiferromagnetic couplings $J_2$
between the planes, $J_1$ within each plane:
\begin{equation}
H = J_1 \sum_{l \ = \ 1,2}
\sum_{<i,j>} {\bf
S_{l i} \cdot S_{l j}}
+ J_2 \sum_{ i } {\bf S_{1i} \cdot S_{2i}}
\label{eq1}
\end{equation}
where $l = 1,2$ labels the two planes of the bilayer. The physics of the
system then depends on the coupling ratio $\lambda = J_1/J_2$. At $\lambda=0$, the
ground state consists simply of $S = 0$ dimers on each bond between the two
layers, and excitations are composed of $S = 1$ `triplon' states on one or
more bonds. At large $\lambda$, where the $J_1$ interaction is dominant, the ground
state will be a standard N{\' e}el state, with $S = 1$ `magnon' excitations.
At some intermediate critical value $\lambda_c$, a phase transition will occur
between these two phases. It is believed that this transition is of
second order,
and is accompanied by a Bose-Einstein condensation of
triplons/magnons in the ground state.
Theorists have discussed this model using series expansion methods
\cite{hida1992,gelfand1996,zheng1997},
quantum Monte Carlo )QMC) simulations at small temperatures
\cite{sandvik1994,sandvik1995,sandvik1996}, Schwinger-boson mean-field
theory \cite{millis1993,miyazaki1996}, and spin-wave theory
\cite{matsuda1990,chubukov1995,kotov1998,shevchenko1999}.
The QMC analysis of Sandvik and Scalapino \cite{sandvik1996} found the transition at $\lambda_c = 0.398(3)$, with a
critical index $\nu ]simeq 0.7$.
in agreement with the O(3)
nonlinear sigma model prediction, while the
exponent-biased series analysis
of Zheng \cite{zheng1997} put the critical point at $\lambda_c = 0.394(1)$.
Early spin-wave estimates \cite{chubukov1995} were well away from this position, but
the improved Brueckner approach of Sushkov {\it et al.}
\cite{kotov1998,shevchenko1999} gave a
remarkably accurate estimate of the critical point and critical index,
and also the 1-particle
dispersion in the model.
Our particular aim here is to study the two-triplon states within the
dimerized regime, with particular emphasis on the occurrence of bound states,
and to explore their behaviour in the vicinity of the critical point.
The two-particle bound states can give important insights into the dynamical
behaviour of the model. It is also possible that they may be detected experimentally at the
new generation of inelastic neutron scattering facilities, or by other means.
We use two methods to investigate the two-particle states. A modified
triplet-wave approach, described in Section \ref{sec2}, gives a qualitative picture of
these states, valid at small couplings $\lambda$. Series expansion calculations,
sketched in Section \ref{sec3}, are
then used to obtain more accurate results, and to explore the behaviour near
the critical point.
Series expansions are also presented for the single-particle and total transverse structure factors.
Our conclusions are summarized in Section \ref{sec5}.
\section{Modified triplet-wave theory.}
\label{sec2}
Analogues of spin-wave theory in a dimerized phase have been discussed by
several authors.
Sachdev and Bhatt \cite{sachdev1990}
used a `bond-operator' representation to describe the dimers and their
spin-triplet excitations, which employed both triplet and singlet operators,
with a constraint between them to ensure that no two triplets can occupy the
same site. The constraint is awkward to implement, and so Kotov {\it et al.}
\cite{kotov1998} discarded the singlet operator, and replaced it by an infinite on-site
repulsion between triplets, implemented via a self-consistent Born approximation,
valid when the density of triplets is low. We have presented an alternative
approach \cite{collins2006}, where the exclusion constraint is implemented automatically
by means of projection operators. The absence of any constraint makes the
formalism easier and more transparent to apply, but at the price of extra
many-body interaction terms.
This is the method used here.
The Hamiltonian for the Heisenberg bilayer systemn can be rewritten
\begin{equation}
H = \sum_{ i } {\bf S_{1i} \cdot S_{2i}} + \lambda \sum_{1 = 1,2}
\sum_{<i,j>} {\bf
S_{\lambda i} \cdot S_{\lambda j}}
\label{eq10}
\end{equation}
For $\lambda = 0$, the system reduces to independent dimers as shown in
Figure \ref{fig1}.
Let us consider a single dimer with two spins ${\bf S_1,S_2}$.
The four states in the Hilbert space consist of a singlet and three
triplet states with total spin $S=0,1$ respectively, and eigenvalues
\begin{eqnarray}
{\bf S_1 \cdot S_2} = \left\{ \begin{array}{cc}
-3/4 & (S=0) \\
+1/4 & (S=1)
\end{array}
\right.
\label{eq11}
\end{eqnarray}
We denote the singlet ground state as $|0 \rangle$, and introduce triplet
creation operators that create the triplet states out of the vacuum
$|0 \rangle$, as follows
\begin{eqnarray}
|0 \rangle & = & \frac{1}{\sqrt{2}}[|\uparrow \downarrow \rangle -|\downarrow
\uparrow \rangle] \nonumber \\
|1,x \rangle & = & t^{\dagger}_x|0 \rangle = -\frac{1}{\sqrt{2}}[|\uparrow \uparrow \rangle -|\downarrow
\downarrow \rangle] \nonumber \\
|1,y \rangle & = & t^{\dagger}_y|0 \rangle = \frac{i}{\sqrt{2}}[|\uparrow \uparrow \rangle +|\downarrow
\downarrow \rangle] \nonumber \\
|1,z \rangle & = & t^{\dagger}_z|0 \rangle = \frac{1}{\sqrt{2}}[|\uparrow \downarrow \rangle +|\downarrow
\uparrow \rangle]
\label{eq12}
\end{eqnarray}
Then the spin operators ${\bf S_1}$ and ${\bf S_2}$ can be represented
in terms of triplet operators by
\begin{eqnarray}
S_{1\alpha} & = &
\frac{1}{2}[t^{\dagger}_{\alpha}(1-t^{\dagger}_{\gamma}t_{\gamma}) +
(1-t^{\dagger}_{\gamma}t_{\gamma}) t_{\alpha}
-i\epsilon_{\alpha\beta\gamma}t^{\dagger}_{\beta}t_{\gamma}]
\nonumber \\
S_{2\alpha} & = &
\frac{1}{2}[-t^{\dagger}_{\alpha}(1-t^{\dagger}_{\gamma}t_{\gamma}) -
(1-t^{\dagger}_{\gamma}t_{\gamma}) t_{\alpha}
\nonumber \\
& & -i\epsilon_{\alpha\beta\gamma}t^{\dagger}_{\beta}t_{\gamma}]
\label{eq13}
\end{eqnarray}
where $\alpha,\beta,\gamma$ take the values $x,y,z$ and repeated indices
are summed over. This is similar to the representation of Sachdev and
Bhatt \cite{sachdev1990}, except that we have omitted singlet operators
$s^{\dagger},s$, but used projection operators
$(1-t^{\dagger}_{\gamma}t_{\gamma})$ instead. Assume the triplet
operators obey bosonic commutation relations
\begin{equation}
[t_{\alpha},t^{\dagger}_{\beta}] = \delta_{\alpha\beta},
\label{eq14}
\end{equation}
then one can show that within the physical subspace (i.e. total number
of triplet states is 0 or 1), the representation (\ref{eq13}) obeys the
correct spin operator algebra
\begin{equation}
[S_{1\alpha},S_{1\beta}] = i\epsilon_{\alpha\beta\gamma}S_{1\gamma},
\hspace{5mm} [S_{2\alpha},S_{2\beta}] =
i\epsilon_{\alpha\beta\gamma}S_{2\gamma},
\nonumber
\end{equation}
\begin{equation}
[S_{1\alpha},S_{2\beta}] = 0
\label{eq15b}
\end{equation}
\begin{equation}
{\bf S}_1^2 = {\bf S}_2^2 = 3/4, \hspace{5mm} {\bf S_1 \cdot S_2} =
t^{\dagger}_{\alpha}t_{\alpha} - 3/4
\label{eq15c}
\end{equation}
The projection operators ensure that we remain within the subspace.
Returning to the bilayer system, we can now define triplet operators
$t^{\dagger}_{n\alpha},t_{n\alpha}$ for each dimer $n$ in the system.
For a system of $N$ dimers, the Hamiltonian now can be expressed in terms
of triplet operators as
\begin{widetext}
\begin{eqnarray}
H & = & -\frac{3N}{4} + \sum_n t^{\dagger}_{n\alpha}t_{n\alpha}
+\frac{\lambda}{2} \sum_{<ij>} \{ t^{\dagger}_{i\alpha} t^{\dagger}_{j\alpha} + t_{i\alpha} t_{j\alpha} +t_{i\alpha} t^{\dagger}_{j\alpha} + t^{\dagger}_{i\alpha}
t_{j\alpha} \}
-\frac{\lambda}{2} \sum_{<ij>} \{
(t^{\dagger}_{i\alpha} t^{\dagger}_{i\beta} t_{i\beta} + t^{\dagger}_{i\beta} t_{i\beta} t_{i\alpha}) (t^{\dagger}_{j\alpha} +t_{j\alpha}) \nonumber \\
& & +(t^{\dagger}_{i\alpha} + t_{i\alpha})
(t^{\dagger}_{j\alpha} t^{\dagger}_{j\beta} t_{j\beta} + t^{\dagger}_{j\beta} t_{j\beta} t_{j\alpha}) + t^{\dagger}_{i\alpha} t_{i\beta} t^{\dagger}_{j\alpha} t_{j\beta} - t^{\dagger}_{i\alpha} t_{i\beta}
t^{\dagger}_{j\beta} t_{j\alpha} \} \nonumber \\
& &
+\frac{\lambda}{2} \sum_{<ij>} \{
(t^{\dagger}_{i\alpha} t^{\dagger}_{i\beta} t_{i\beta} + t^{\dagger}_{i\beta} t_{i\beta} t_{i\alpha}) (t^{\dagger}_{j\alpha} t^{\dagger}_{j\gamma} t_{j\gamma} + t^{\dagger}_{j\gamma} t_{j\gamma}
t_{j\alpha}) \}
\label{eq16}
\end{eqnarray}
\end{widetext}
This expression includes terms containing up to 6 triplet operators.
Next, perform a Fourier transform
\begin{eqnarray}
t_{{\bf k}\alpha} & = & (\frac{1}{N})^{1/2} \sum_{\bf n} e^{i{\bf k.n}} t_{{\bf
n}\alpha} \nonumber \\
t^{\dagger}_{{\bf k}\alpha} & = & (\frac{1}{N})^{1/2} \sum_{\bf n} e^{-i{\bf
k.n}} t^{\dagger}_{{\bf n}\alpha}
\label{eq17}
\end{eqnarray}
(we set the spacing between dimers $d = 1$),
then the Hamiltonian becomes
\begin{widetext}
\begin{eqnarray}
H & = & -\frac{3N}{4} + \sum_{{\bf k}} t^{\dagger}_{{{\bf k}}\alpha} t_{{\bf k} \alpha}
+\lambda \sum_{{\bf k}} \gamma_{{\bf k}} [ t^{\dagger}_{{\bf k} \alpha} t^{\dagger}_{-{\bf k} \alpha} + t_{{\bf k}
\alpha} t_{-{\bf k} \alpha} +2 t^{\dagger}_{{\bf k} \alpha} t_{{\bf k} \alpha} ]
\nonumber \\
& &
-\frac{\lambda}{N} \sum_{1234} \{ \delta_{1+2+3-4} [ (t^{\dagger}_{1 \alpha} t^{\dagger}_{2
\alpha} t^{\dagger}_{3\gamma} t_{4 \gamma} + t^{\dagger}_{4 \gamma} t_{3 \gamma} t_{2 \alpha} t_{1
\alpha})
(\gamma_1 + \gamma_2)] +
\delta_{1+2-3-4}[t^{\dagger}_{1\alpha}t^{\dagger}_{2\gamma}t_{3\alpha}t_{4\gamma}(\gamma_1+\gamma_2+\gamma_3+\gamma_4)
\nonumber \\
& &
+ \gamma_{{\bf 1-3}} t^{\dagger}_{1 \beta} t^{\dagger}_{2 \beta} t_{3 \gamma}
t_{4 \gamma} - \gamma_{{\bf 1-4}}t^{\dagger}_{1 \beta} t^{\dagger}_{2 \gamma} t_{3 \beta} t_{4 \gamma}) ]
\}
\nonumber \\
& &
+ \frac{\lambda}{N^2} \sum_{1-6} \{ \delta_{1+2+3+4-5-6} [ \gamma_{{\bf 3+4-6}}
(t^{\dagger}_{1 \alpha} t^{\dagger}_{2 \gamma} t^{\dagger}_{3 \alpha} t^{\dagger}_{4 \beta} t_{5 \gamma} t_{6
\beta} + t^{\dagger}_{6 \beta} t^{\dagger}_{5 \gamma} t_{4 \beta} t_{3 \alpha} t_{2 \gamma} t_{1
\alpha}) ] \nonumber \\
& & + \delta_{1+2+3-4-5-6}
t^{\dagger}_{1 \alpha} t^{\dagger}_{2 \beta} t^{\dagger}_{3 \gamma}
t_{4 \gamma} t_{5 \beta} t_{6 \alpha}(\gamma_{{\bf 3-4-6}} + \gamma_{{\bf 2+3-4}})
\}
\label{eq18}
\end{eqnarray}
\end{widetext}
where the indices $1 - 6$ are shorthand for momenta ${\bf k_1} - {\bf
k_6}$, and
\begin{equation}
\gamma_{\bf k} = \frac{1}{2}(\cos k_x + \cos k_y)
\end{equation}
for the square lattice.
Henceforward, we drop the 6-particle terms.
Finally, as in a standard spin-wave analysis, we perform a Bogoliubov
transform
\begin{equation}
t_{{\bf k}\alpha} = c_{{\bf k}}\tau_{{\bf k}\alpha} + s_{\bf k} \tau^{\dagger}_{-{\bf k}\alpha}
\label{eq19}
\end{equation}
where $c_{\bf k} = \cosh \theta_{\bf k}$, $s_{\bf k} = \sinh \theta_{\bf k}$, $\theta_{-{\bf k}} =
\theta_{\bf k}$, which preserves the boson commutation relations
\begin{equation}
[\tau_{{\bf k}\alpha},\tau^{\dagger}_{{\bf k}'\beta}] = \delta_{{\bf k}\bk'}\delta_{\alpha\beta}
\label{eq20}
\end{equation}
and is intended to diagonalize the Hamiltonian up to quadratic terms.
After normal ordering, the transformed Hamiltonian up to fourth order
terms reads
\begin{equation}
H = W_0 + H_2 + H_3 + H_4,
\label{eq21}
\end{equation}
where the constant term is
\begin{widetext}
\begin{eqnarray}
W_0 & = & 3N\left\{ -\frac{1}{4}+R_2 +
2\lambda(R_3+R_4)-2\lambda[2(R_3+R_4)(R_1+4R_2)
+\frac{1}{N^2}\sum_{12}
\gamma_{{\bf 1-2}}(c_1s_1c_2s_2-s_1^2s_2^2)] \right. \nonumber \\
& & \left. +2\lambda[(R_3+R_4)(R_1+4R_2)^2
+\frac{1}{N^3}\sum_{123}\gamma_{{\bf 1+2-3}}(c_1s_1(4c_2s_2c_3s_3+
6c_2s_2s_3^2+6s_2^2s_3^2)+4s_1^2s_2^2s_3^2)] \right\}
\label{eq22}
\end{eqnarray}
\end{widetext}
expressed in terms of the momentum sums
\begin{eqnarray}
R_1 & = & \frac{1}{N} \sum_{{\bf k}} c_{{\bf k}} s_{{\bf k}} \nonumber \\
R_2 & = & \frac{1}{N} \sum_{{\bf k}} s_{{\bf k}}^2
\nonumber \\
R_3 & = & \frac{1}{N} \sum_{{\bf k}} c_{{\bf k}} s_{{\bf k}} \gamma_{{\bf k}}
\nonumber \\
R_4 & = & \frac{1}{N} \sum_{{\bf k}} s_{{\bf k}}^2 \gamma_{{\bf k}}.
\label{eq23}
\end{eqnarray}
The quadratic terms are
\begin{equation}
H_2 = \sum_{{\bf k},\alpha} [E_{{\bf k}} \tau^{\dagger}_{{\bf k}\alpha} \tau_{{\bf k}\alpha} +Q_{\bf k}(\tau_{{\bf k}\alpha}\tau_{-{\bf k}\alpha} + \tau^{\dagger}_{{\bf k}\alpha} \tau^{\dagger}_{-{\bf k}\alpha})]
\label{eq24}
\end{equation}
where
\begin{widetext}
\begin{eqnarray}
E_{{\bf k}} & = & (c_{{\bf k}}^2 + s_{{\bf k}}^2)(1+2\lambda\gamma_{{\bf k}})+4\lambda\gamma_{{\bf k}}c_{{\bf k}}
s_{{\bf k}} \nonumber \\
& & -\lambda[4(c_{{\bf k}}^2+s_{{\bf k}}^2)(\gamma_{{\bf k}}
(R_1+4R_2) + 4(R_3+R_4)
-\frac{1}{N}\sum_1s_1^2\gamma_{{\bf k-1}})
\nonumber \\ & &
+8c_{{\bf k}}s_{{\bf k}}
(\gamma_{{\bf k}}
(R_1+4R_2) + (R_3+R_4)
+\frac{1}{N}\sum_1c_1s_1\gamma_{{\bf
k-1}})]
\label{eq25}
\end{eqnarray}
\begin{eqnarray}
Q_{{\bf k}} & = & c_{{\bf k}}s_{{\bf k}}(1
+2\lambda\gamma_{{\bf k}})+\lambda\gamma_{{\bf k}}(c_{{\bf k}}^2+s_{{\bf k}}^2) \nonumber \\
& & -\lambda[2(c_{{\bf k}}^2+s_{{\bf k}}^2)(\gamma_{{\bf k}}
(R_1+4R_2)+(R_3+R_4)
+\frac{1}{N}\sum_1
c_1s_1\gamma_{{\bf k}-{\bf
1}}) \nonumber \\
& &+4c_{{\bf k}}s_{{\bf k}}(\gamma_{{\bf k}}
(R_1+4R_2)+4(R_3+R_4)
-\frac{1}{N}\sum_1
s_1^2\gamma_{\bf k-1})]
\label{eq26}
\end{eqnarray}
The fourth-order terms are
\begin{eqnarray}
H_4 & = & -\frac{\lambda}{N}\sum_{1234}[\delta_{1+2+3+4}\Phi^{(1)}_4
(\tau^{\dagger}_{1\alpha}\tau^{\dagger}_{2\alpha}\tau^{\dagger}_{3\gamma}\tau^{\dagger}_{4\gamma} +
\tau_{1\alpha}\tau_{2\alpha}\tau_{3\gamma}\tau_{4\gamma}) +
\delta_{1+2-3-4}(\Phi^{(2)}_4
\tau^{\dagger}_{1\alpha}\tau^{\dagger}_{2\alpha}\tau_{3\gamma}\tau_{4\gamma}
+\Phi_4^{(3)}\tau^{\dagger}_{1\alpha}\tau^{\dagger}_{2\gamma}\tau_{3\alpha}\tau_{4\gamma})
\nonumber \\
& & +\delta_{1+2+3-4}\Phi^{(4)}_4
(\tau^{\dagger}_{1\alpha}\tau^{\dagger}_{2\alpha}\tau^{\dagger}_{3\gamma}\tau_{4\gamma} +
\tau^{\dagger}_{4\gamma}\tau_{3\gamma}\tau_{2\alpha}\tau_{1\alpha})]
\label{eq28}
\end{eqnarray}
\end{widetext}
where we have used the shorthand notation $1 \cdots 4$ for momenta $k_1 \cdots k_4$, and the vertex functions
$\Phi^{(i)}_4$ are listed in Appendix A.
These results were obtained or confirmed using a symbolic manipulation program
written in PERL.
The condition that the off-diagonal quadratic terms vanish is
\begin{equation}
Q_{{\bf k}} =0.
\label{eq29}
\end{equation}
In a conventional spin-wave approach, this would be implemented in leading order only, giving the condition
\begin{equation}
\tanh 2\theta_{{\bf k}} = \frac{2s_{{\bf k}}c_{{\bf k}}}{c_{{\bf k}}^2+s_{{\bf k}}^2} =
-\frac{2\lambda\gamma_{{\bf k}}}{[1+2\lambda\gamma_{{\bf k}})}
\label{eq30}
\end{equation}
This would leave some residual off-diagonal quadratic terms, arising from the normal-ordering of quartic operators. In a
`modified' approach \cite{gochev1994}, we demand that these terms vanish entirely up to the order calculated, giving the
modified condition
\begin{widetext}
\begin{equation}
\tanh 2\theta_{{\bf k}} =
-\frac{2\lambda[\gamma_{{\bf k}}
-2(\gamma_{{\bf k}}(R_1+4R_2)+(R_3+R_4)
+\frac{1}{N}\sum_1 c_1s_1 \gamma_{{\bf k-1}})]
}{[1+2\lambda(\gamma_{{\bf k}}-2(\gamma_{{\bf k}}(R_1+4R_2)+4(R_3+R_4)
-\frac{1}{N}\sum_1s_1^2\gamma_{{\bf
k-1}}))]}
\label{eq31}
\end{equation}
\end{widetext}
Self-consistent solutions for the N equations (\ref{eq31}), with the four parameters $R_1 \cdots R_4$ given by equation
(\ref{eq23}), can easily be found by numerical means, starting from the conventional result (\ref{eq30}).
\subsection{Expansion in powers of $\lambda$}
\label{sec2a}
As a first check on the formalism, one may calculate the leading terms
in an expansion of the energy eigenvalues in powers of $\lambda$.
Solving the modified equation (\ref{eq31}) self-consistently
to order $\lambda^2$, we find
\begin{eqnarray}
s_{{\bf k}} & = &
-\lambda\gamma_{{\bf k}} + \frac{\lambda^2}{2}(4\gamma_{{\bf k}}^2
-\gamma_{{\bf k}}-1)
\nonumber \\
c_{{\bf k}} & = & 1 + \frac{1}{2}\lambda^2\gamma_{{\bf k}}^2
\label{eq32}
\end{eqnarray}
with the lattice sums (\ref{eq23})
\begin{eqnarray}
R_1 & = & O(\lambda^4), \hspace{5mm} R_2 = \frac{\lambda^2}{4}+\frac{\lambda^3}{4}
+O(\lambda^4), \nonumber \\
R_3 & = & -\frac{\lambda}{4} - \frac{\lambda^2}{8}+O(\lambda^3), \hspace{5mm} R_4 =
O(\lambda^3)
\label{eq33}
\end{eqnarray}
The leading-order behaviour of the vertex functions may easily be
deduced from Appendix A.
Substituting in equation (\ref{eq22}), the ground state energy per dimer
is
\begin{eqnarray}
\epsilon_0 & = & \frac{W_0}{N}
\sim
-3[\frac{1}{4}+\frac{\lambda^2}{4}+\frac{\lambda^3}{8}]
\hspace{5mm} \lambda \rightarrow 0
\label{eq34}
\end{eqnarray}
in agreement with dimer series expansion results previously obtained for this
model \cite{zheng1997}. One can easily show that perturbation diagrams
such as those in Figure \ref{fig2} do not contribute until
$O(\lambda^4)$ or higher.
\begin{figure}
\includegraphics[width=0.7\linewidth]{fig2.eps}
\caption{Perturbation diagrams contributing to the ground-state energy.}
\label{fig2}
\end{figure}
The energy gap at leading order can be found from equation (\ref{eq25}):
\begin{equation}
E_k \sim 1
+2\lambda\gamma_{{\bf k}} +4\lambda^2-2\lambda^2\gamma_{{\bf k}}^2
\hspace{5mm} \lambda \rightarrow 0
\label{eq35}
\end{equation}
Note that in linear spin-wave theory, when $\tanh 2\theta_{{\bf k}}$ is given
by (\ref{eq30}) and the energy gap is given by the first line of equation
(\ref{eq25}), the energy gap is
\begin{equation}
E_k = \sqrt{1+4\lambda\gamma_{{\bf k}}}
\label{eq35a}
\end{equation}
which vanishes at $\lambda = 1/4, \gamma_{{\bf k}} = -1$, i.e. ${\bf k} =
(\pi,\pi)$. This marks a phase transition with critical index $\nu =
1/2$, and the end of the dimerized
phase, in this approximation.
\begin{figure}
\includegraphics[width=0.7\linewidth]{fig3.eps}
\caption{Perturbation diagrams contributing to the one-particle energy.}
\label{fig3}
\end{figure}
The perturbation diagram Figure \ref{fig3}a) also
contributes to the energy gap at order $\lambda^2$.
Note that diagram \ref{fig3}a) does not appear in the formalism of Shevchenko
{\it et al.} \cite{shevchenko1999,kotov1998}; the extra terms in our formalism are needed to implement the
hardcore constraint that two triplons cannot occupy the same site.
At leading order, the contribution of this diagram
is
\begin{equation}
\Delta E_k^{3a)} \sim -2\lambda^2
\hspace {5mm} \lambda \rightarrow 0
\label{eq36}
\end{equation}
(see the next section for further details). This gives a total
single-particle energy
\begin{equation}
\epsilon_k \sim
1+2\lambda\gamma_{{\bf k}}+2\lambda^2(1-\gamma_{{\bf k}}^2),
\hspace{5mm} \lambda \rightarrow
0
\label{eq38}
\end{equation}
which again agrees with series expansion results \cite{zheng1997}.
The minimum energy gap lies at ${\bf k} = (\pi,\pi)$. If we compare equation
(\ref{eq38}) at small momentum ${\bf p} = (\pi,\pi)-{\bf k}$ with the
continuum dispersion relation for a free boson,
\begin{equation}
\epsilon_k \sim \sqrt{m^2c^4 + p^2c^2}
\label{eq39}
\end{equation}
we readily discover the leading behaviour of the effective triplon
parameters, i.e. the triplon mass
\begin{equation}
m \sim \frac{1}{\lambda}[1-2\lambda+O(\lambda^2)]
\label{eq40}
\end{equation}
and the `speed of light' or triplon velocity
\begin{equation}
c^2 \sim
\lambda+O(\lambda^3)
\label{eq41}
\end{equation}
in lattice units. Note that the mass diverges and the speed of light
vanishes as $\lambda \rightarrow 0$.
\subsection{Numerical Results}
\label{sec2b}
Writing the Hamiltonian as
\begin{equation}
H = H_0 + V
\label{eq42}
\end{equation}
where
\begin{equation}
H_0 = W_0 + H_2
\label{eq43}
\end{equation}
and
\begin{equation}
V = H_4
\label{eq44}
\end{equation}
(6-particle terms being neglected)
we can treat $H_0$ as the unperturbed Hamiltonian and $V$ as a
perturbation to obtain the leading-order corrections to the predictions
for physical quantities outlined in the previous section.
Numerical results for the model have been obtained using the
finite-lattice method. The momentum sums are carried out for a fixed
lattice size $L \times L = N$,
using corresponding discrete values for the momentum
${\bf k}$, e.g.
\begin{eqnarray}
k_x & = & \frac{2\pi n}{L}, \hspace{5mm}n=1, \cdots L
\nonumber \\
k_y & = & \frac{2\pi m}{L}, \hspace{5mm}m=1, \cdots L
\label{eq45}
\end{eqnarray}
Results were obtained for $L$ up to 100.
\subsubsection{Ground-state energy}
\label{seca1}
\begin{figure}
\includegraphics[width=1.0\linewidth]{fig4.eps}
\caption{Ground-state energy per dimer as a function of $\lambda$. The solid
line
is the estimate from series expansions, and the dashed line is the
triplet-wave estimate.
}
\label{fig4}
\end{figure}
The leading correction to the ground-state energy corresponds to the
diagram in Figure \ref{fig2}a). Its
contribution is
\begin{widetext}
\begin{eqnarray}
\Delta \epsilon_0^{2a)} & = & \frac{-3\lambda^2}{N^3}\sum_{1234}
\delta_{1+2+3+4}\frac{\Phi_4^{(1)}(1234)}{(E_1+E_2+E_3+E_4)}
\left[3\Phi_4^{(1)}(1234)
+\Phi_4^{(1)}(1324)
+\Phi_4^{(1)}(1423)\right]
\label{eq45b}
\end{eqnarray}
\end{widetext}
In leading order one can show that this term is $O(\lambda^4)$,
whereas diagrams such as Figure \ref{fig2}b) are $O(\lambda^6)$ or
higher.
Figure
\ref{fig4} shows the behaviour of the ground-state energy as a function
of $\lambda$ resulting from this modified triplon theory, as compared
with the high-order dimer series calculations of Zheng
\cite{zheng1997}.
It can be seen that out to $\lambda \simeq 0.1$ there is quantitative agreement between our calculation
and the series estimates, but some discrepancy emerges at larger $\lambda$.
\subsubsection{One-particle spectrum}
\label{sec2a2}
The leading correction to the one-particle spectrum corresponds to the
diagram in Figure \ref{fig3}a). Its contribution
is
\begin{widetext}
\begin{eqnarray}
\Delta E_k^{3a)} & = & \frac{2\lambda^2}{N^2}\sum_{ 123}\delta_{
{\bf 1+2+3-k}}\frac{\Phi_4^{(4)}(
123k)}{(E_k-E_1-E_2-E_3)}
\left[3\Phi_4^{(4)}(123k)
+\Phi_4^{(4)}(321k)
+\Phi_4^{(4)}(312k)
\right]
\label{eq47}
\end{eqnarray}
\end{widetext}
In leading order, this term is $O(\lambda^2)$, as stated in the
previous section, while diagrams like \ref{fig3}b) are
$O(\lambda^4)$ or higher.
\begin{figure}
\includegraphics[width=1.0\linewidth]{fig5.eps}
\caption{[Colour online] One-particle dispersion relation at the critical point ($y =
1/\lambda$), as estimated from both dimer (solid line) and Ising (dashed line) expansions
\cite{zheng1997}.}
\label{fig5}
\end{figure}
The dispersion of the one-particle energy as a function of momentum ${\bf
k}$ at the critical point is
illustrated in Figure \ref{fig5}, as estimated from two different series
expansions
by Zheng \cite{zheng1997}. It can be seen that the two expansions agree
well at the critical point, and that the energy gap vanishes there at
the N{\' e}el point ${\bf k} = (\pi,\pi)$.
\begin{figure}
\includegraphics[width=1.0\linewidth]{fig6.eps}
\caption{ Energy gap at ${\bf k} = (\pi,\pi)$ as a function of
$\lambda$. The solid squares show the series estimates
\cite{zheng1997},
and the open squares are
results from Shevchenko {\it et al.}
\cite{shevchenko1999},
while the stars show the improved
triplet-wave results. The contributions from 2-triplon and 4-triplon
terms are shown separately.
}
\label{fig6}
\end{figure}
The triplet-wave and series estimates of the energy gap at
${\bf k} = (\pi,\pi)$ are
compared in Figure \ref{fig6}.
It
can be seen that the inclusion of the corrections from diagram \ref{fig3}a)
improves the agreement with series
substantially, bringing quantitative agreement out to $\lambda \simeq
0.15$. Beyond that, the triplet-wave estimates begin to diverge, as
higher-order contributions become more important.
The self-consistent Born approach of Kotov et al. \cite{kotov1998,shevchenko1999} is more accurate than our
approach at large $\lambda$; but neither approach can compete with
series methods for accuracy. Our object here mainly is to understand the
qualitative behaviour of the model.
\subsubsection{Two-triplon bound states}
\label{sec2a3}
It has been found in previous studies of dimerized
antiferromagnetic systems in one dimension \cite{uhrig1996,shevchenko1999} that the
quartic terms in
the Hamiltonian lead to attraction between two elementary triplons,
giving rise to $S=0$ and $S=1$ bound states. We look for solutions of
the two-body Schr{\" o}dinger equation
\begin{equation}
H|\psi \rangle = E|\psi \rangle.
\label{eq48}
\end{equation}
The two-body wave functions $|\psi({\bf K}) \rangle$ can be written as follows:
\begin{flushleft}
{\it Singlet sector ($S=0$):}
\end{flushleft}
\begin{equation}
|\psi^S({\bf K}) \rangle =
\frac{1}{\sqrt{6}}\sum_{{\bf q},\alpha}\psi^S({\bf K},{\bf q})\tau^{\dagger}_{{\bf
K}/2+{\bf q},\alpha}
\tau^{\dagger}_{{\bf K}/2-{\bf q},\alpha}|0 \rangle
\label{eq49}
\end{equation}
where ${\bf K}$ is the centre-of-mass momentum and ${\bf q}$ the relative momentum
of the two particles,
and the scalar wave function is symmetric,
\begin{equation}
\psi^S({\bf K},-{\bf q})=\psi^S({\bf K},{\bf q})
\label{eq53}
\end{equation}
\begin{flushleft}
{\it Triplet sector ($S=1$):}
\end{flushleft}
\begin{equation}
|\psi^T_{\alpha}({\bf K}) \rangle =
\frac{1}{2}\sum_{{\bf q},\beta,\gamma}\epsilon_{\alpha\beta\gamma}
\psi^T({\bf K},{\bf q})\tau^{\dagger}_{{\bf K}/2+{\bf q},\beta}\tau^{\dagger}_{{\bf
K}/2-{\bf q},\gamma}|0 \rangle
\label{eq50}
\end{equation}
with the wave function antisymmetric
\begin{equation}
\psi^T({\bf K},-{\bf q})=-\psi^T({\bf K},{\bf q}).
\label{eq56}
\end{equation}
We will not write out the quintuplet states explicitly.
From equation (\ref{eq48}) one can readily derive the integral
Bethe-Salpeter equation satisfied by the bound-state wave functions:
\begin{eqnarray}
[E^{S,T,Q}({\bf K})-E_{{\bf K}/2+{\bf q}}-E_{{\bf K}/2-{\bf q}}]\psi^{S,T,Q}({\bf K},{\bf
q})
= \nonumber \\
\frac{1}{N}\sum_{{\bf p}}M^{S,T,Q}({\bf K},{\bf q},{\bf p})\psi^{S,T,Q}({\bf K},{\bf
p})
\label{eq51}
\end{eqnarray}
in each sector S,T or Q.
In leading order, the scattering amplitudes $M^{S,T,Q}({\bf K},{\bf q},{\bf
p})$ are simply
given by the 4-particle vertex from the perturbation operator $V$, Figure
\ref{fig7}a). Hence we find for the different sectors:
\begin{widetext}
\begin{equation}
M^S({\bf K},{\bf q},{\bf p}) =
-2\lambda[3\Phi^{(2)}_4({\bf K}/2+{\bf q},{\bf K}/2-{\bf q},{\bf K}/2+{\bf
p},{\bf
K}/2-{\bf p})
+\Phi^{(3)+}_4({\bf {\bf K}}/2+{\bf q},{\bf {\bf K}}/2-{\bf q},{\bf K}/2+
{\bf p},{\bf K}/2-{\bf
p})]
\label{eq52}
\end{equation}
\begin{equation}
M^T({\bf K},{\bf q},{\bf p}) =
-2\lambda\Phi^{(3)-}_4({\bf K}/2+{\bf q},{\bf K}/2-{\bf q},{\bf K}/2+{\bf p},{\bf
K}/2-{\bf p})
\label{eq55}
\end{equation}
\begin{equation}
M^Q({\bf K},{\bf q},{\bf p}) =
-2\lambda\Phi^{(3)+}_4({\bf K}/2+{\bf q},{\bf K}/2-{\bf q},{\bf K}/2+{\bf
p},{\bf
K}/2-{\bf p})
\label{eq57}
\end{equation}
\end{widetext}
where the wave function is once again symmetric
in the quintuplet sector
\begin{equation}
\psi^Q({\bf K},-{\bf q})=\psi^Q({\bf K},{\bf q}).
\label{eq58}
\end{equation}
and the symmetric and antisymmetric pieces of the vertex function
$\Phi_4^{(3)}$ are defined:
\begin{equation}
\Phi^{(3)\pm}_4 \equiv \frac{1}{2}[\Phi^{(3)}_4(1234)\pm
\Phi^{(3)}_4(1243)].
\label{eq54}
\end{equation}
\begin{figure}
\includegraphics[width=0.8\linewidth]{fig7.eps}
\caption{Perturbation diagrams contributing to the 2-particle
scattering amplitude.}
\label{fig7}
\end{figure}
\begin{figure}
\includegraphics[width=0.9\linewidth]{fig8.eps}
\caption{[Color online] Dispersion relations for the two-particle bound/antibound states at $\lambda=0.1$, along symmetry lines
in the Brillouin zone, as calculated from the triplet-wave expansion.
The 2-particle continuum region is shaded.}
\label{fig8}
\end{figure}
At leading order in $\lambda$, we find
\begin{eqnarray}
M^S({\bf K},{\bf q},{\bf p}) & \sim &
-2\lambda[\gamma_{{\bf p+q}}+\gamma_{{\bf p-q}}+\gamma_{{\bf K}/2+{\bf
p}} \nonumber \\
& & +\gamma_{{\bf K}/2+{\bf q}}+\gamma_{{\bf K}/2-{\bf p}}+\gamma_{{\bf
K}/2-{\bf q}}]
\label{eq56a}
\end{eqnarray}
\begin{equation}
M^T({\bf K,q,p}) \sim
\lambda[\gamma_{{\bf q+p}}-\gamma_{{\bf q-p}}]
\label{eq56b}
\end{equation}
and
\begin{eqnarray}
M^Q({\bf K,q,p}) & \sim &
\lambda[\gamma_{{\bf q+p}}+\gamma_{{\bf q-p}}
-2(\gamma_{{\bf K}/2+{\bf
p}} \nonumber \\
& & +\gamma_{{\bf K}/2+{\bf q}}+\gamma_{{\bf K}/2-{\bf p}}+\gamma_{{\bf
K}/2-{\bf q}})]
\label{eq56c}
\end{eqnarray}
Then restricting ourselves to the particular momentum ${\bf K} =
(\pi,\pi)$, simple solutions to the Bethe-Salpeter equation (\ref{eq51})
can be found:
\begin{eqnarray}
\Psi^{S,Q}({\bf K,q}) & \sim & (\cos q_x \pm \cos q_y) \nonumber \\
\Psi^{T}({\bf K,q}) & \sim & (\sin q_x \pm \sin q_y)
\label{eq67}
\end{eqnarray}
corresponding to nearest-neighbour pairs of triplon excitations, with
energies:
\begin{eqnarray}
E^S({\bf K}) & \sim & 2-\lambda \nonumber \\
E^T({\bf K}) & \sim & 2-\lambda/2 \nonumber \\
E^Q({\bf K}) & \sim & 2+\lambda/2
\label{eq68}
\end{eqnarray}
Since the 2-particle continuum is confined strictly to $E_{cont} = 2$ at
this order and this momentum, we see that the singlet and triplet states
are bound states lying below the continuum, while the quintuplet states
are antibound states lying above the continuum. There are two degenerate
states in each case, corresponding to the $\pm$ signs in equation
(\ref{eq67}), or to the two possible axes $x$ and $y$ of the
nearest-neighbour pairs. At higher orders these states may mix and
separate.
These results are easily understood in a qualitative fashion. For an
$S^z = 2$ excitation, for example, the spins on the nearest-neighbour
sites are necessarily aligned parallel, giving rise to a repulsive
interaction; whereas for $S = 0$ or 1 the neighbouring spins can be
aligned either parallel or antiparallel, allowing the possibility of an
attractive interaction.
Solving the wave equation (\ref{eq51}) with vertex functions given by the leading order approximations (\ref{eq52})
- (\ref{eq57}), we obtain numerical solutions for the 2-particle spectrum, as illustrated in Figure \ref{fig8}, at a coupling
$\lambda = 0.1$, near momentum ${\bf k} = (\pi,\pi)$. It can be seen that the pairs of degenerate $S=0$ and $S=2$ bound/antibound states
split as one moves away from $(\pi,\pi)$, and all states eventually merge into the continuum.
\begin{figure}
\includegraphics[width=1.0\linewidth]{fig9.eps}
\caption{[Color online]
The total static structure factor $S({\bf k})$ as a function of ${\bf
k}$, for various couplings $\lambda = J_1/J_2$.}
\label{fig9}
\end{figure}
\section{Series Expansions}
\label{sec3}
We have performed a standard dimer series expansion \cite{singh1988,oitmaa2006} for this
model, where the Hamiltonian is written as
\begin{eqnarray}
H & = & H_0 + \lambda V \\
H_0 & = & \sum_i {\bf S_{1i} \cdot S_{2i}} \\
V & = & \sum_{l=1,2} \sum_{<ij>} {\bf S_{li} \cdot S_{lj}}
\label{eq69}
\end{eqnarray}
and perturbation series are generated for the quantities of interest in
powers of $\lambda$, using linked cluster methods. Details of the linked
cluster approach are reviewed in \cite{oitmaa2006}. In very brief
summary, the ground-state energy per dimer can be written as a sum of
the irreducible contributions (cumulants) coming from every connected
cluster of dimers which can be embedded on the lattice, the order of the
contributions rising with the size of the cluster. The 1-particle
energies can be written in terms of irreducible transition amplitudes $\Delta_1
(i,j)$ of the effective Hamiltonian \cite{gelfand1996}, which consist of a
sum over all
linked clusters connected to $i$ and $j$, the initial and final
positions of the 1-particle excitations. And finally, the 2-particle
energies can be written in terms of irreducible transition amplitudes $\Delta_2
(i,j;k,l)$ of the 2-particle effective Hamiltonian \cite{trebst2000}, consisting of a sum
over all linked clusters connected to $(i,j)$ and $(k,l)$, the initial
and final positions of the 2-particle excitations. The amplitudes
$\Delta_2$ are then employed in the 2-particle Schr{\" o}dinger or
Bethe-Salpeter equation to calculate the energy for as a function of
momentum. We use a finite-lattice approach \cite{oitmaa2006} for this
purpose, where the Schr{\" o}dinger equation is solved on a finite
lattice in position space, of sufficient size to ensure convergence of
the results.
Once a perturbation series in $\lambda$ has been calculated for a given
quantity, it can be extrapolated to finite $\lambda$ using Pad{\' e}
approximants or integrated differential approximants.
Zheng \cite{zheng1997}
has previously calculated series for the ground-state energy and
1-particle excitations. These results have already been compared with
the triplet-wave predictions in Figures \ref{fig4}, \ref{fig5} and \ref{fig6}.
\subsection{Structure Factors}
\label{sec3a}
Figures \ref{fig9} and \ref{fig10} show some series results for
structure factors, which have not been shown before. Figure \ref{fig9}
shows the total static transverse structure factor $S({\bf k}) \equiv S^{+-}({\bf
k})$ as a function of ${\bf k}$ at various couplings $\lambda =
J_1/J_2$, where $S^{+-}({\bf k})$ is the Fourier transform of the
correlation function:
\begin{equation}
S^{+-}({\bf k}) = \frac{1}{N}\sum_{i,j}e^{i{\bf k \cdot
(r_i-r_j)}}<S^+_jS^-_i>_0
\label{eq70}
\end{equation}
\begin{widetext}
\begin{center}
\begin{table}
\caption{Series coefficients of $\lambda^N$ in the expansions for the 1-particle structure factor
$S_{1p}$ and integrated structure factor $S$ at momenta ${\bf k} = (\pi,\pi)$ and $(0,0)$.}
\begin{tabular}{|c|c|c|c|c|}
\hline
N & $S_{1p}(\pi,\pi)$ & $S(\pi,\pi)$ & $S_{1p}(0,0)$ & $S(0,0)$ \\
\tableline
0 & 1.00000000000000D+00 & 1.00000000000000D+00 & 1.00000000000000D+00 & 1.00000000000000D+00 \\
1 & 2.00000000000000D+00 & 2.00000000000000D+00 & -2.00000000000000D+00 & -2.00000000000000D+00 \\
2 & 5.00000000000000D+00 & 5.43750000000000D+00 & 3.00000000000000D+00 & 3.43750000000000D+00 \\
3 & 1.20000000000000D+01 & 1.24375000000000D+01 & -7.00000000000000D+00 & -6.56250000000000D+00 \\
4 & 2.60000000000000D+01 & 2.73476562500000D+01 & 1.42500000000000D+01 & 1.48476562500000D+01 \\
5 & 6.19609375000000D+01 & 6.16328125000000D+01 & -3.08359375000000D+01 & -3.09609375000000D+01 \\
6 & 1.45859863281250D+02 & 1.46245605468750D+02 & 6.65551757812500D+01 & 6.68159179687500D+01 \\
7 & 3.60063964843752D+02 & 3.57834899902344D+02 & -1.51234863281252D+02 & -1.51278381347656D+02 \\
8 & 8.71365653991730D+02 & 8.80394332885743D+02 & 3.23292167663603D+02 & 3.28300582885742D+02 \\
9 & 2.13146787007666D+03 & 2.15030324554441D+03 & -7.25282606760795D+02 & -7.27275304158507D+02 \\
\hline
\end{tabular}
\label{tab1}
\end{table}
\end{center}
\end{widetext}
All results are for $k_z = \pi$, probing intermediate states antisymmetric between the planes,
and we only refer to
${\bf k} = (k_x,k_y)$ hereafter.
The dominant feature is a large peak at the N{\' e}el point
${\bf k} = (\pi,\pi)$, which appears to become divergent as $\lambda
\rightarrow \lambda_c$. This behaviour is qualitatively very similar to
that seen in the alternating Heisenberg chain (AHC) in one dimension
\cite{hamer2003}.
Figure \ref{fig10} shows the ratio of the 1-particle
structure factor $S_{1p}({\bf k})$ to the total $S({\bf k})$ as a
function of ${\bf k}$. The 1-particle contribution generally remains
the dominant part of the total, particularly near the N{\' e}el point.
This behaviour is again reminiscent of the AHC \cite{hamer2003}.
\begin{figure}
\includegraphics[width=1.0\linewidth]{fig10.eps}
\caption{[Color online]
The ratio $S_{1p}({\bf k})/S({\bf k})$ of the 1-particle static
structure factor to the total static structure factor as a function of
${\bf k}$, for various couplings $\lambda = J_1/J_2$. }
\label{fig10}
\end{figure}
Further information may be obtained from the series for $S({\bf k})$ and
$S_{1p}({\bf k})$ at the N{\' e}el momentum $(\pi,\pi)$, which are given
in Table I. A Dlog Pad{\' e} analysis of these series, biased at
$\lambda_c =0.3942$, shows both $S({\bf k})$ and
$S_{1p}({\bf k})$ diverging as $\lambda \rightarrow \lambda_c$ with
exponents $-0.68(1)$ and $-0.69(1)$ respectively. The series for the ratio $S_{1p}/S$
shows no sign of a singularity at this point, remaining almost constant, within
2\% of unity at all couplings.
This behaviour is quite different from the AHC case
\cite{affleck1998}, where the ratio vanishes logarithmically at the critical point.
These results should be compared with theoretical expectations. From
scaling theory (see Appendix B),
the 1-particle structure
factor in the vicinity of the critical point
$S_{1p}(\pi,\pi)$ should scale like
$(\lambda_c-\lambda)^{(\eta-1)\nu}$,
at the critical (N{\' e}el) momentum.
For the total structure factor at
this point, scaling theory gives exactly the same exponent (see
Appendix B).
We expect this transition to belong to the universality class of the
O(3) model in 3 dimensions, which has critical exponents
\cite{guida1998}
$\nu = 0.707(4)$, $\eta = 0.036(3)$, hence we expect $(\eta-1)\nu =
-0.682(5)$, which is quite compatible with the numerical estimates
obtained above.
How does $S_{1p}$ behave at the critical coupling
away from the N{\' e}el momentum?
In the transverse Ising model \cite{hamer2006}, it was found that the 1-particle residue function
$A({\bf k})$ (see Appendix B) vanishes like $(\lambda_c-\lambda)^{\eta\nu}$ at all momenta,
with a small exponent $\eta\nu = +0.025(3)$, so that
$S_{1p}$ vanishes in the same fashion as $\lambda \rightarrow \lambda_c$. Does the same thing happen
in the present case?
This is by no means obvious in Figure
\ref{fig10}, which shows the ratio $S_{1p}/S$ dropping slowly as
$\lambda$ increases, but nowhere near zero.
\begin{widetext}
\begin{center}
\begin{table}
\caption{Series coefficients of $\lambda^N$ for the binding energies in the channels $S = 0,1$,
and antibinding energy (S = 2). The $S = 0$ and $S = 2$ states are doubly degenerate.
}
\begin{tabular}{|c|c|c|c|c|}
\hline
N & S = 0 & S = 1 & S = 1 & S = 2 \\
\tableline
0 & 0.00000000000000D+00 & 0.00000000000000D+00 & 0.00000000000000D+00 & 0.00000000000000D+00 \\
1 & 1.00000000000000D+00 & 5.00000000000000D-01 & 5.00000000000000D-01 & 5.00000000000000D-00 \\
2 & -2.25000000000000D+00 & -2.12500000000000D+00 & -3.12500000000000D+00 & -1.37500000000000D+00 \\
3 & -1.93750000000000D+00 & 1.31250000000000D+00 & -2.93750000000000D+00 & 1.87500000000000D-01 \\
4 & -3.07812500000000D+00 & 2.97656250000002D+00 & -2.77343749999998D+00 & 2.27343750000000D+00 \\
5 & 3.47656250000001D-01 & 1.07812500000003D+00 & 3.06250000000002D+00 & 2.36718750000000D+00 \\
6 & -9.69726562500059D-01 & -1.00527343749999D+01 & 8.35742187500014D+00 & -8.13476562500000D+00 \\
7 & 3.51385498046887D+00 & 7.44207763671879D+00 & 4.07301635742189D+01 & -7.26873779296875D+00 \\
8 & & 7.92327880859462D+00 & 1.69468475341798D+02 & -3.48072814941411D+00 \\
\hline
\end{tabular}
\label{tab2}
\end{table}
\end{center}
\end{widetext}
To pursue this question further, we have studied the series at ${\bf k} = (0,0)$, also given in
Table I. A Dlog Pad{\' e} analysis of these series reveals a dominant singularity at $\lambda =
-0.43(1)$, with exponent around $ -0.65(3)$ in both cases. This will correspond to another
critical point of the model, where the spins order ferromagnetically in the planes, and
antiferromagnetically between them. At positive $\lambda$, there is
no sign of a pole around $\lambda = 0.4$.
The ratio $S_{1p}/S$ decreases smoothly to around $0.80$ at the critical coupling,
and shows no sign of vanishing there.
Thus it appears that in this case the renormalized residue function does not vanish
at $\lambda_c$, except at the N{\' e}el momentum.
\begin{figure}
\includegraphics[width=1.0\linewidth]{fig11.eps}
\caption{
Series estimates of the energies of 2-particle states at fixed $\lambda = 0.1 $, along
symmetry lines in the Brillouin zone.
}
\label{fig11}
\end{figure}
\subsection{Two-particle excitations}
\label{sec3b}
We have
generalized the computer codes which were previously used to calculate 2-particle
perturbation series for 1-dimensional models \cite{trebst2000} to cover the
two-dimensional case.
Figure \ref{fig11} shows the dispersion diagram estimated from the
perturbation series for 2-particle states at $\lambda = 0.1$.
We have zoomed in on the region where the bound states occur.
It can be
seen that S = 0 singlet and S = 1 triplet bound states emerge below the
continuum near ${\bf k} = (\pi,\pi)$, and S = 2 quintuplet antibound states appear
above the continuum, as predicted by the triplet-wave theory.
The $S=0$ and $S=2$ states are
doubly degenerate at ${\bf k} = (\pi,\pi)$. All
states merge with the continuum at some finite momentum point ${\bf k}$, and for
the most part they appear to merge at a tangent, as in the
one-dimensional case \cite{zheng2001}.
The results look very similar to the triplet-wave predictions shown in
Figure \ref{fig8}.
Figure \ref{fig12} shows the behaviour of the binding energies at ${\bf k}
= (\pi,\pi)$ as functions of $\lambda$, as estimated from Pad{\' e} approximants to the series given in Table \ref{tab2}.
The degenerate pair of singlet bound states are the lowest over most of the range, but merge back into the continuum
somewhat before the critical point. One of the triplet states disappears into the continuum quite early, but the other appears
to disappear only at the critical point.
For the AHC, the binding
energies also vanished at the critical endpoint of the dimerized phase.
The pair of antibound quintuplet states, on the other hand, appear to remain above the continuum even at the
critical point, from our estimates.
\begin{figure}
\includegraphics[width=1.0\linewidth]{fig12.eps}
\caption{
Binding energies as functions of $\lambda$, relative to the 2-particle continuum.
For bound states, we graph $(E_{2p}-E^-_{cont})$, while for antibound states we
graph $(E_{2p}-E^+_{cont})$, where $E^{\pm}_{cont}$ denote the upper/lower bounds of the
continuum.
}
\label{fig12}
\end{figure}
\section{Summary and Conclusions}
\label{sec5}
In this paper, we have used a modified triplet-wave theory and dimer series expansions to study the Heisenberg
bilayer system in the dimerized phase. As found in earlier papers \cite{hida1992,zheng1997,sandvik1994}, the model displays a
quantum phase transition from the dimerized phase to a N{\' e}el phase at a coupling ratio $\lambda_c =0.394(1)$,
with critical indices in good agreement with the predicted values from the classical O(3) nonlinear sigma model in
three dimensions,
$\nu = 0.707$ and $\eta = 0.036$.
Our modified triplet-wave approach is found to give good results at small couplings $\lambda$, but towards the
critical region the self-consistent Born approximation approach of Kotov et al. \cite{kotov1998,shevchenko1999}, which
includes some important higher-order terms, gives much better results. The triplet-wave approach predicts, as for
other dimerized systems, two-particle bound states in the $S=0$ and $S=1$ channels where an antiferromagnetic
alignment of spins can give rise to an attractive force, and antibound states in the $S=2$ channel, where the spin
alignment is necessarily ferromagnetic and repulsive.
Our series calculations focused upon two major features, the critical behaviour of the static transverse structure
factor, and the spectrum of 2-particle bound states in the model. The integrated structure factor $S({\bf k})$ and
the single-particle component $S_{1p}({\bf k})$ were both found to diverge at the critical point for momentum ${\bf k}
= (\pi,\pi)$, with exponents agreeing well with the predicted value $(\eta-1)\nu = -0.68$. The ratio $S_{1p}/S$
remains finite throughout the region, even at the critical coupling $\lambda_c$. This is in contrast to the case of
the alternating Heisenberg chain, where the 1-particle component vanishes logarithmically at the critical point
\cite{affleck1998,hamer2003}. In fact, here the one-particle state dominates everywhere ($S_{1p}/S \ge 80\%$).
In the 2-particle sector, a pair of bound states is found in the $S=0$ and $S=1$ channels near momentum ${\bf k} =
(\pi,\pi)$, as predicted, and a pair
of antibound states in the $S=2$ channel, the pairing being a two-dimensional effect. The singlet $S=0$ states have the
lowest energies at small couplings, but both $S =0$ states and one $S =1 $ state merge back into the continuum as
$\lambda$ increases, leaving only one remaining triplet bound state, which appears to merge with the continuum right
at $\lambda = \lambda_c$. In the S=2 channel, both antibound states appear to remain above the 2-particle continnum
at all couplings $\lambda > 0$.
As one moves away from ${\bf k} = (\pi,\pi)$, the bound/antibound states eventually
merge into the continuum also.
They appear to merge with the continuum at a tangent, much as in the
one-dimensional case \cite{hamer2003}.
In future work,
we hope to perform similar calculations for other two-dimensional
models, such as the simple Heisenberg model on the square lattice, and
the Shastry-Sutherland model, which has already been studied by Knetter et
al. \cite{knetter2000}, and where the two-particle states display some intriguing behaviour.
\acknowledgments
This work forms part of a research project supported by a grant
from the Australian Research Council.
We are grateful to the Australian Partnership for Advanced Computing
(APAC) and to the Australian Centre for Advanced Computing and Communications (ac3) for computational support.
\begin{widetext}
|
{
"redpajama_set_name": "RedPajamaArXiv"
}
| 9,184
|
\section{Introduction}
A nature of the underlying mechanism of $1/f$ low-frequency noise
spectrum in hopping conductors is a part of the more general
problem of the universal origin of $1/f$, and had been an
unresolved issue for decades.~\cite{1,2,3,4,6,7,8,9,11,12} A
general intrinsic reason for the $1/f$ spectrum is the
exponentially wide distribution of the relevant relaxation times
in the system. Thus the issue of the mechanism of $1/f$ spectrum
reduces to the question of the microscopic origin of such a
distribution. The low temperature transport in doped
semiconductors occurs via electron hopping between the donors (or
hole hopping between acceptors when considering $p$-type
semiconductors). The hopping distance is determined by the
balance between the tunneling probability over this distance and
the probability of the thermal activation necessary to accomodate
the difference between the initial and final levels. Optimization
of these probabilities cuts the effectively conducting band around
the Fermi level. This hopping mechanism is called variable range
hopping (VRH) transport. With the decreasing temperature this
effective impurity band gets narrower and the electron has to
tunnel over a larger distance to find the appropriate destination
state, since the levels at the close by donors are separated by a
large gap, see Ref.~\onlinecite{Shklovskii-Efros} and references
therein. In this regime the conducting paths form a dilute
percolation cluster, and the system resistance is controlled by
the very rare {\textit critical hopping resistors $R_c$}. The
conductivity of the critical resistors are most susceptible to the
dynamic fluctuations of charge distribution in a body of the
conductor and they become the source of the current noise.
The crucial question associated with the origin of the noise is
whether the $1/f$ law goes indefinitely to low frequencies and if
not, what is the nature of its lower bound. This problem was first
addressed by Shklovskii~\cite{7} and Kogan\&Shklovskii~\cite{8}
who attributed the origin of the noise to the charge traps
affecting the electron concentration on the percolation cluster
that supports the current in the conductor. This model predicts
the saturation of the noise spectrum at low frequencies. The
reason for the saturation is that no trap can be perfectly
isolated from the rest of the hopping sites since their spatial
distribution is Poissonian. Consequently, to secure a very large
relaxation time one has to find a very rare trap specially
isolated from the other hopping sites. These ideas of
Refs.~\onlinecite{7,8} were elaborated in the recent paper by
Shklovskii~\cite{12} devoted to the temperature dependence of the
noise spectrum. The alternative idea was put forward by
Kogan~\cite{11} who assumed that a hopping system is in fact the
Coulomb glass and can therefore have arbitrarily low intrinsic
frequencies due to transitions between the different metastable
``pseudo-ground" states separated by unlimitedly large barriers.
Accordingly, there is no saturation in the noise spectrum down to
extremely low frequencies. Unfortunately, no analytical
description for this mechanism was proposed.
Here we revisit the problem of the low-frequency noise in hopping
conductors and develop the approach for calculating the noise
spectrum based on the idea of multi-site bistable
\textit{aggregates}. While switching between their pseudo-ground
states, the aggregates produce low-frequency electrical noise,
which is ``read-out" by the sites belonging to the backbone
percolation cluster. The read-out mechanism suggested
earlier~\cite{9} attributes the noise to fluctuations of the
effective resistors forming bonds of the percolation cluster with
correlation length $\mathcal{L}$. The fluctuations of each resistor are
due to the noise produced by the nearest bistable aggregate. Since
the switching times of these aggregates are spread in an
exponentially broad interval the noise spectrum turns out to be of
$1/f$ type,
In the original approach~\cite{9} the aggregates consisted of
pairs of sites. However, the probability of finding such pairs -
\textit{fluctuators} - is limited by the fact that such fluctuator
be located in a ``pore" free of other sites able to facilitate
electron hopping.~\cite{12} Consequently, the maximal switching
time are limited that leads to a cut-off in the noise spectrum
Here we generalize the approach~\cite{9} including into the
consideration \textit{multi-site aggregates} that can assume two
distinct charge configurations with the nearly same energy. In
this respect, the aggregates that can be viewed as two-level
systems. It is essential that transitions between these states
occur via the multi-electron hops, either coherent or incoherent.
The probabilities of such transitions are strongly suppressed
comparing to the case of isolated pairs, and this is the source of
very large intrinsic switching times.
Consequently, the cut-off frequency can be extremely low. The
suggested model of multi-site bistable aggregates is a ``bridge"
between the ideas of small fluctuators~\cite{9,12} and of
pseudo-ground state of the whole system.~\cite{11}
\section{Model}
To quantify the concept of an aggregate let us start from the
simplest one -- a fluctuator consisting of the two trapping sites
occupied by a single electron. Such pairs have two levels with
small energy separation $E \lesssim T$ and their relaxation time,
$\tau_p$, is related to the tunneling between the states;
$\tau_p^{-1}=\nu_0\, e^{-2 r_p/a}$ where $\nu$ is some (generally
temperature-dependent) pre-exponential factor, $r_p$ is the
spatial separation between the sites while $a$ is the localization
length. The values of $\tau$ should be much larger than the
typical hopping times, $\tau_h=\nu_0^{-1}e^{2r_h/a}$, along the
current-carrying percolation cluster, therefore $r_p$ should be
larger than the typical hopping distance in the cluster,
$r_h=a\xi$. Here $\xi$ is the connectivity parameter of the
percolation theory entering the exponent of critical hopping
resistor, $R_c=R_0\, e^\xi$, see
Ref.~\onlinecite{Shklovskii-Efros} and references therein. We
consider an isolated pair, therefore there is no any other site in
a close neighborhood (i.~e. within the distance $\tilde{r} \ll
r_p$) from either of the centers, that could facilitate the
processes with the rates $\gg \tau_p^{-1}$.
One can express this requirement as the inequality
\begin{equation}\label{pair}
\frac{2r_p}{a} \leq \frac{\Delta}{T} + \frac{2 {\tilde r}}{a}=\xi
\end{equation}
where $\Delta$ is the relevant energy band width. To relate this
bandwidth to the distance $\tilde{r}$ we estimate $\tilde{r}$ as
$\tilde{r}=(3/4\pi n)^{1/3}$ where $n$ is the concentration of the
relevant centers. Since for a Coulomb-gap controlled system in the
VRH regime
$n=(2/3)(\kappa \Delta/e^2)^3$ we obtain $\Delta \simeq
(9/8\pi)^{1/3}(e^2/\kappa \tilde {r})$. Optimizing the r.h.s. of
Eq.~(\ref{pair}) with respect to $\tilde r$ we find
$\tau_p \lesssim \tau_h e^{ \xi ( \sqrt{2} - 1)}$.
Here $\xi=(T_0/T)^{1/2}$,
$T_0=e^2/{\kappa}a$.~\cite{Shklovskii-Efros}
Now we consider the aggregates consisting of 4 hopping sites
occupied by 2 electrons. These close to square arrays are the
simplest \textit{next hierarchy level} aggregates realizing the
two level system (the three-site aggregates are reduced to pairs,
since even a slight deviation from the perfect arrangement lifts
the triple degeneracy and gives rise to an exponentially wide gap
separating the split levels of the closest pair from the third
level).
A degenerate configurations requiring the least energy arise when
two electrons are trapped at the diagonally opposite sites.
Labelling the sites as $1$, $2$, $3$ and $4$, we say that the
pairs are formed by the occupied sites $1 \leftrightarrow 2$, and
$3 \leftrightarrow 4$, respectively. For the configuration where
sites $2$ and $4$ are occupied one has
\begin{eqnarray}\label{1}
\varepsilon_2 + \frac{e^2}{\kappa r_{42}} < \mu \, , \hskip 0.5cm
\varepsilon_1 + \frac{e^2}{\kappa r_{12}} + \frac{e^2}{\kappa
r_{14}} > \mu \, ,
\nonumber\\
\varepsilon_4 + \frac{e^2}{\kappa r_{42}} < \mu \, , \hskip 0.5cm
\varepsilon_3 + \frac{e^2}{\kappa r_{43}} + \frac{e^2}{\kappa
r_{23}} > \mu \, ;
\end{eqnarray}
the configuration where sites $1$ and $3$ are occupied obeys:
\begin{eqnarray}\label{2}
\varepsilon_1 + \frac{e^2}{\kappa r_{13}} < \mu\, , \hskip 0.5cm
\varepsilon_2 + \frac{e^2}{\kappa r_{12}} + \frac{e^2}{\kappa
r_{23}} > \mu \, ,
\nonumber\\
\varepsilon_3 + \frac{e^2}{\kappa r_{13}} < \mu \, , \hskip 0.5cm
\varepsilon_4 + \frac{e^2}{\kappa r_{4,1}} + \frac{e^2}{\kappa
r_{4,3}} > \mu \, .
\end{eqnarray}
Here $\varepsilon_i$ are the single-particle energies of the
sites, $r_{ij}$ are the sites spacings, and $\mu$ is the chemical
potential. The energy splitting between the two configurations is
\begin{equation}
E \equiv E_1 - E_2 = 2\frac{e^2}{\kappa}\left(\frac{1}{r_{24}} -
\frac{1}{r_{13}}\right) +
\varepsilon_2 + \varepsilon_4 - \varepsilon_1 - \varepsilon_3 \, .
\end{equation}
The relaxation processes associated with the transitions between
the two configurations with the almost equal energies are the
process that involve the simultaneous exchange of electrons
between the sites $1 \to 2$ and $3 \to 4$. All other processes
increase the Coulomb energy and therefore are unlikely to occur.
The switch can be either due to a
multi-electron (a two-electron in our case) tunneling first
suggested by Pollak~\cite{Pollak} or due to incoherent processes.
As follows from the above mentioned correlation, the aggregate
formed by the sites with large single-particle energies would have
short intersite distances and, accordingly, high rates of the
multi-electron hops. Since the slow relaxing aggregates should
have relatively large larger intersite separations, their
single-particle energies should be relatively small.
To proceed further it is convenient to map the aggregates onto a
spin system. A single pair is mapped on the $1/2$-spin (the spin
direction is taken from the occupied to the unoccupied site), the
four-site aggregates are represented as a pair of the interacting
antiparallel spins. The interaction between the spins forming an
aggregate is antiferromagnetic since the Coulomb repulsion pushes
electrons belonging to the adjacent pairs apart. Adding more pairs
we map larger aggregates to clusters of $3, 4, ... N$ spins. This
model is a \textit{minimal} model for the general Coulomb glass
since we allow only for the transitions that are represented by
flips of spins. In the absence of randomness the system is
antiferromagnet, disorder may, in principal, drive it to the spin
glass.
The $2N$-site aggregates (or antiferromagnet $N$-spin clusters)
must obey restrictions similar to those given by Eqs.~(\ref{1})
and (\ref{2}). To estimate the density of states for the
aggregates we shall take into account that in course of the
reversal of the ``spins" the energy of each site crosses the Fermi
level. Thus we should compare the change of the site energy
resulting from the aggregate rearrangement and the ``static"
scatter of the site energies.
To do so, let us specify some energy $\varepsilon_f$ within the
Coulomb gap and consider the sites with energy band $\varepsilon_i
< \varepsilon_f$. Let us consider the aggregates formed from these
sites in the same way as it was considered above. For the site
energy we have, cf. with Ref.~\onlinecite{Shklovskii-Efros},
\begin{equation}\label{ag}
\varepsilon_i = \varphi_i + V_i, \quad V_i \equiv
\frac{e^2}{\kappa}\sum_{j \neq i} \frac{(1-n_j)}{r_{ij}}\, .
\end{equation}
Here $\varphi_i$ is the potential induced on the site $i$ by the
background charges not included in the aggregate; the sum in
$V_i$ is calculated over the sites forming the aggregate. Thus
$\varphi_i$ is due to the disorder while $V_i$ depends on the
state of the aggregate.
To estimate $V_i$ let us split it into the parts having different
symmetry with respect to rearrangement of the aggregate between
its two metastable states: $V_i=(1/2)(V_i^+ + V_i^- s_i)$. Here
$s_i =\pm 1$. The symmetric part can be treated as a contribution to the
potential $\varphi_i$.
Assuming the potentials $\varphi_i$ and $V_i^{\pm}$ to be random
and uncorrelated, we write
\begin{equation}\label{random}
\overline{\varepsilon_i^2} = \overline{\varphi_i^2} + \frac{1}{4}
\overline{ (V_i^+)^2} + \frac{1}{4}\overline{ (V_i^-)^2}\, .
\end{equation}
Since we are interested in the states within the Coulomb gap, the
density of states for the single-particle energies $\varepsilon_i$
is given by the Efros-Shklovskii law, $g \propto \varepsilon_i^2$.
Thus the typical distance between the sites as
\begin{equation}
\bar{r} = \left[2 \int_0^{\varepsilon_f}g(\varepsilon){\rm
d}\varepsilon\right]^{-1/3}=(3/2)^{1/3} e^2/\kappa \varepsilon_f\,
.
\end{equation}
One expects that the potential formed on the site $i$ by the other
sites forming the aggregate can estimated as $\bar{V}_\pm\equiv
\left( \overline{(V_i^\pm)^2}\right)^{1/2} = \zeta_\pm
\varepsilon_f $ where $\zeta_\pm \sim 1$ are numerical parameters
depending on the aggregate geometry. Making use of
Eq.~(\ref{random}) one has
\begin{equation}
\overline{\varphi^2} = \varepsilon_f^2(1 - \zeta^2_+/4
-\zeta_-^2/4)\, .
\end{equation}
Since the typical variation of the site energy, $\delta V \equiv
\bar{V}_-=\zeta_-\varepsilon_f$ we obtain the following estimates
\begin{equation}\label{bardeltav}
\bar{V}_-=\zeta_-\varepsilon_f, \ \bar{V}_+=\zeta_+ \varepsilon_f,
\ \bar{\varphi}=\varepsilon_f \sqrt{1-\zeta_-^2/4 -\zeta_+^2/4}\,
.
\end{equation}
Note that the relations between $\bar{V}_-$, $\bar{V}_+$ and
$\bar{\phi}$ do not depend on $\varepsilon_f$ provided we deal
with the states within the Coulomb gap. One can expect that these
ratios are of the order of unity.
Basing on the discussion given above let us estimate
the aggregates density of states. First, let us note that for all
the sites belonging to the aggregate the inequality $V_i^-
> V_i^+ + 2\varphi_i$ must be met. Indeed, only such states
cross the Fermi level
The probability to form an aggregate depends on two parameters -
the ratios $\zeta_-/\zeta_+$ and $ \zeta_-/2\varphi$. Assuming
that $\zeta_+/\zeta_- \lesssim 1$ and $2\bar{\varphi}\gtrsim
\zeta_-$ one concludes that to form an aggregate
one should deal with the sites with the potentials $\varphi_i$
less than their average scatter. Since the Coulomb gap exists only
for the single-electron energies, $\varepsilon_i$ rather than for
disorder-induced potential $\varphi$, the distribution of the
random potential $\varphi$ , $\mathcal{P}(\varphi)$, is smooth for small
$\varphi$ and one can put $\mathcal{P}(\varphi)\approx 1/2\bar{\varphi}$.
Consequently, he relative weight of the aggregate sites is in this
case given by
$$\frac{1}{2\bar{\varphi}} \int^{(\bar{V}_- - \bar{V}_+)/2}_0
\mathcal{P}(\varphi) \, {\rm d} \varphi =
\frac{\zeta_--\zeta_+}{\sqrt{4-\zeta_-^2 -\zeta_+^2}} \equiv
\lambda \, . $$ These considerations are valid until $\lambda <1$.
In this case relative weight of the aggregate formed by $2N$ sites
is $\lambda^{2N}=e^{-2N\ln1/\lambda}$.
Thus at $\lambda <1$ is the probability to form a metastable
aggregate is exponentially small in terms of the number of the
sites involved in the aggregate. This will be mainly discussed in
what follows.
However, there is no fundamental principle requiring $\lambda \le
1$.~\cite{endnote} This is why later we will also discuss the
scenarios where the multistable aggregates can be realized with a
probability close to unity.
\section{The distribution of the relaxation rates.}\label{s1}
To calculate noise in the system one needs density of states, $P
(N,r,E)$, of finding the aggregate with $N$ sites and distance $r$
between the sites per unit energy interval, $E$. This density can
be expressed in the form
\begin{eqnarray}
\label{eq:006}
P(N,r,E)&=&\frac{\lambda^N}{\sqrt{\pi N} N r^3\cdot e^2/\kappa r}
\nonumber \\
&=& \frac{2.7 \lambda^N}{T_{ES}\sqrt{\pi} N^{3/2}ar^2} \, .
\end{eqnarray}
Here $Nr^3$ is the volume of the aggregate while
$\sqrt{N}e^2/\kappa r$ is the energy bandwidth for small energies.
Let us estimate the distribution function, $\mathcal{P}(\nu)$, of the
relaxation rates, $\nu$, for the aggregate rearrangement. We
define the rate as
\begin{equation}
\label{eq:001}
\nu=\nu_0\max\left\{e^{-N^{2/3}\xi^2/2.7\rho},e^{-2N\rho}\right\}\, .
\end{equation}
Here $\rho \equiv r/a$, $\xi \equiv (T_{ES}/T)^{1/2}$. The first
term in parentheses describes formation of a ``domain wall" in the
aggregate and the second term corresponds to coherent tunneling
transitions leading to re-charging of all aggregate sites.
To calculate the distribution of switching rates let us introduce
the function $L(N,\rho)$ as
\begin{equation}
\label{eq:002}
L(N,\rho)=-\ln \max\left\{e^{-N^{2/3}\xi^2/2.7\rho},e^{-2N\rho}\right\}\, .
\end{equation}
Thus $L(N,\rho)=\ln(\nu_0/\nu) \equiv \mathcal{M}$. Denoting $\rho_N$ by
the equality $N^{2/3}\xi^2/2.7\rho_N=2N\rho_N$,
\begin{equation}
\label{eq:003}
\rho_N=0.43\xi/N^{1/6}\, ,
\end{equation}
one can express $L(N,\rho)$ as
$$L(N,\rho)=-\ln \max\left\{e^{-0.86N^{5/6}\xi
(\rho_N/\rho)},e^{-0.86N^{5/6}\xi (\rho/\rho_N)} \right\}\, .$$
Let us now invert the above dependence. Since
\begin{equation}\label{ldep}
L(N,\rho) \approx \left\{\begin{array} {ll} 0.86N^{5/6}\xi
(\rho/\rho_N)\, , & \rho \gg \rho_N \\
0.86N^{5/6}\xi
(\rho_N/\rho)\, , & \rho \gg \rho_N\, . \end{array} \right.
\end{equation}
the inverted function, $\rho(L)$, has two branches:
\begin{equation}
\label{eq:004}
\frac{\rho(L)}{\rho_N}=\left\{ \begin{array}{l}
(L/L_N)\\
(L_N/L)\, ,
\end{array}
\right. \quad \left|\frac{\partial \rho}{\partial
L}\right|=\frac{\rho_N}{L_N}\left\{
\begin{array}{l} 1,\\(L_N/L)^2
\end{array} \right. \, .
\end{equation}
Here $L_N\equiv 0.86N^{5/6}\xi$, thus $\rho_N/L_N=1/2N$. Note
that $L(N,\rho) \le L_N$. Now we are ready to calculate the
distribution function
\begin{eqnarray}
\label{eq:005}
\mathcal{P}(\nu,E)&=&4\pi \int dN\, r^2 dr\, P(N,r,E)\, \delta \left(\nu -\nu_0\,
e^{-L(r,N)} \right) \nonumber \\
&=& \frac{4\pi a^2}{\nu}\int dN\,\rho^2 d\rho \, P(N,\rho,E)\,
\delta \left[\rho-\rho(L)
\right]\left|\frac{\partial \rho}{\partial L}\right|
\, . \nonumber
\end{eqnarray}
Substituting $P(N,r,E)$ from Eq.~(\ref{eq:006}) we obtain
\begin{equation}
\label{eq:009}
\mathcal{P}(\nu)=\frac{1}{\nu}\,
\frac{2\pi\cdot2.7}{T_{ES}\sqrt{\pi}}\int_{N_c}^\infty
\frac{ dN\, e^{-\gamma N}}{N^{5/2}}
\,\left[1+\left(\frac{L_N}{\mathcal{M}}\right)^2 \right]
\end{equation}
where $\gamma \equiv \ln 1/\lambda$, while
$N_c(\mathcal{M})=(\mathcal{M}/0.86\xi)^{6/5}$.
Substituting these values to Eq.~(\ref{eq:009}) we get,
\begin{equation}
\label{eq:012} \mathcal{P}(\nu) \approx\frac{1}{\nu}\,
\frac{1}{T_{ES}}\frac{4\sqrt{\pi}\cdot 2.7}{\gamma
N_c^{5/2}}e^{-\gamma N_c}\, .
\end{equation}
In this approximation the density of states $\mathcal{P}$ does not depend
on the energy splitting $E$. The expression (\ref{eq:012}) is
valid at $\gamma N_c =\left[(\gamma^{5/6}/0.86 \xi)
\ln(\nu_0/\nu)\right]^{6/5} \gtrsim 1$, or
\begin{equation} \label{ineq02}
\ln (\nu_0/ \nu) \gtrsim \xi/\gamma^{5/6}\, .
\end{equation}
The product $\gamma N_c$ can be expressed as
$\ln(\nu_0/\nu)^\alpha$ where
$$ \alpha (\nu)=\frac{\gamma^{5/6}}{0.86 \xi}
\left[\frac {\gamma^{5/6}}{0.86 \xi}
\ln\left(\frac{\nu_0}{\nu}\right)\right]^{1/5}\, .$$ {}From
realistic estimates one can expect that the second factor does not
significantly change within the experimentally accessible
frequency interval. For example, assuming $\nu_0 = 10^{10}$ Hz we
get $\mathcal{M}^{1/5}=1.87$ at $\nu =1$ Hz and $\mathcal{M}^{1/5}=2.06$ at $\nu
=10^{-6}$ Hz. Consequently, for reasonable experimental conditions
the quantity $\alpha (\nu)$ can be replaced by
$\bar{\alpha}=\alpha(\bar{\nu})$ where $\bar{\nu}$ is some
characteristic frequency within the measurement interval. As
follows from the above estimate, for any feasible frequency
$\bar{\alpha} \ll 1$ and the noise spectrum is of the $1/f$ type.
As a result, the distribution of the relaxation rates can be
expressed as
\begin{equation}
\label{eq:009a}
\mathcal{P}(\nu)\approx \frac{C}
{\nu^{1-\bar{\alpha}}\ln^3(\nu_0/\nu)}\,
\frac{\nu_0^{-\bar{\alpha}}\xi^3}{T_{ES}} \, ,
\end{equation}
where $C \approx 12.2/\gamma$ is a numerical factor.
The temperature dependence $\bar{\alpha} \propto \xi^{-6/5} \propto T^{3/5}$ can
be used for verification of the proposed mechanism.
\section{Estimate of the noise intensity}
Switching between the aggregate configurations leads to the change
in the energies, $\delta \varepsilon_i^{(c)}$, of the sites
belonging to the percolation cluster and induces the current
noise. If $|\delta \varepsilon_i^{(c)}| \gtrsim T$ then the
fluctuations of the hopping resistor, $\rho_i$, are large,
$|\delta \rho_i| \sim \rho_i$ and can change the percolation
cluster structure (see Ref.~\onlinecite{9}).
To be specific we consider an $N$-spin aggregate coupled to the
hopping resistor $\rho_i$ formed by the two hopping sites which we
label by indices 1 and 2. The fluctuations of the resistance are
estimated as
\begin{equation}
|\delta R_i/R_i| \sim \min \left(1,|\delta \varepsilon
_i|/T\right)\, , \quad \delta \varepsilon_i \equiv \delta
\varepsilon^{(c)}_{i,1} - \delta \varepsilon^{(c)}_{i,2}\, .
\end{equation}
If the distance between the resistor $i$ and the nearest
aggregate, $r_{i}$, is much larger than the typical distance
between the sites belonging to the hopping cluster, $r_{i} \gg
r_h$, the fluctuation in energy $\delta \varepsilon_i \approx
(\partial \delta \varepsilon^{(c)} /\partial r_{i}) r_h$ where
$\delta \varepsilon$ is the potential induced by the aggregate.
The latter can be estimated assuming that the total dipole moment
of the relevant aggregate is $er_c\sqrt{N_c}$ where $r_c\equiv a
\rho_{N_c}=0.43a\xi N_c^{-1/6}$. Consequently, $r_c=0.43 r_h
N_c^{-1/6}$ and
\begin{equation} \label{int1} \delta
\varepsilon^{(c)} \sim \frac{e^2 r_c \sqrt{N_c}}{\kappa r_{i}^2},
\quad \delta \varepsilon \sim \frac{e^2 r_h^2 N_c^{1/3}}{\kappa
r_{i}^3} \sim \frac{T_{ES}N_c^{1/3}\xi^2 a^3}{ r_{i}^3}\, .
\end{equation}
As we have already mentioned the noise is formed at the
exponentially rare critical resistors. Let us assume for a while
that the fluctuations of their resistances are small, $|\delta
R_i|/R_i \ll 1$.
In a linear approximation the total resistance fluctuation can be
written as
\begin{equation}
\frac{\delta R}{R} \sim \frac{1}{\mathcal{N}} \sum_i \frac{\delta
R_i}{R_i}\, .
\end{equation}
Here $\mathcal{N}$ is the number if critical resistors in the sample which
can be expressed through its volume, $\mathcal{V}$, and the correlation
length of the percolation cluster, $\mathcal{L} = r_h \xi = a\xi^2$, as
$\mathcal{N}=\mathcal{V}/\mathcal{L}^3$. Assuming the aggregates acting upon different
critical resistor to be statistically independent we get.
\begin{equation}
\frac{\langle \delta R,\delta R\rangle_{\omega}}{R^2} \sim
\frac{1}{\mathcal{N}^2} \sum_i\frac{\langle \delta R_i, \delta
R_i\rangle_{\omega}}{R_i^2} \,.
\end{equation}
Now let us estimate of $\delta R_i$. One has in mind that the
aggregates are also rarely distributed. This means that all the
critical resistors have at most one neighboring aggregate and the
fluctuation spectrum is:
$
S(\omega) \equiv \frac{(\delta R_i)^2_{\omega}}{R_i^2}=v^2(r_i)\,
\frac{\nu_i}{\nu_i^2 + \omega ^2}\, \frac{1}{4\cosh^2 E_i /2T}\, .
$$
Here $\nu_i$ is the switching rate of the nearest aggregate with
energy splitting $E_i$, $v^2 (r_i) =\min \left[\left (\delta
\varepsilon(r_i)/T\right )^2,1\right]$ is the squared
dimensionless coupling. Since $\delta \varepsilon (r_i) \propto
r_i^{-3}$ there exists the specific distance, $r_T$, at which the
energy variation given by Eq.~(\ref{int1}) is equal to $T$:
\begin{equation} \label{rt}
r_T \approx a \xi^{4/3} N_c^{1/9}=r_h \xi^{1/3} N_c^{1/9} \ll
\mathcal{L}\, .
\end{equation}
At $r_i \gg r_T$ the interaction strength $v^2(r_i)$ decays at
least as $\propto r_i^{-6}$. Consequently, only the nearest
aggregate is important.
Replacing summation over the critical resistors (and their nearest
aggregates) by averaging and integration over $E$ we obtain
\begin{equation}
S(\omega) \sim \frac{\overline{v^2}T}{\cal N} \int_0^{\nu_0} {\rm
d} \nu\, \mathcal{P}(\nu)\frac{\nu }{\nu^2 + \omega ^2}=
\frac{\pi\overline{ v^2}T}{2\mathcal{N}}\mathcal{P}(\omega)\, .
\end{equation}
Here $\overline {v^2} \equiv r_T^{-3}\int_{|\mathbf{r}|<r_T}
v^2(r)\, d^3r$, while the distribution function $\mathcal{P}(\omega)$ is
given by Eq.~(\ref{eq:012}) or (\ref{eq:009a}). Using
Eq.~(\ref{int1}) we conclude that $\overline{v^2}$ is of the order
of unity, and
\begin{equation} \label{res1}
S(\omega) \sim \frac{\xi}{\mathcal{N}}
\frac{\nu_0^{-\bar{\alpha}}}{\omega^{1-\bar{\alpha}}\ln^3(\nu_0/\omega)}
\, .
\end{equation}
The factor $\xi/\mathcal{N} = \xi \mathcal{L}^3/\mathcal{V} = (a^3/\mathcal{V})\, \xi^7 \propto
T^{-7/2}$. Thus the the considered mechanism leads to a strongly
decreasing temperature dependence of the noise intensity. The
suggested procedure to estimate the noise intensity is valid if
each cell of the backbone cluster contains only one aggregate.
This implies the limitation to the cluster size
\begin{equation} \label{ineq01}
N_c r_c^2 \le \mathcal{L} \quad \to \quad \ln(\nu_0/\omega) \le \xi^6\,.
\end{equation}
This requirement hold for any realistic frequency since $\xi \gg
1$. One can imagine another restriction relevant to the
percolation mechanism behind the resistivity
According to the $1/\omega$ spectrum, one expects that the
magnitude of the fluctuations increases with an increase of the
observation time. If the relative resistance fluctuation for any
relevant resistor,
$$\overline{\delta R_i^2}/R_i^2 = \mathcal{N}
\overline{\delta R_i^2}/R^2\equiv (\mathcal{N}/R^2) \int d\omega (\delta
R^2)_\omega $$ becomes comparable with unity, then one expects
that the percolation cluster is completely reconstructed by the
fluctuations. As a result, the fluctuations with lower frequencies
will not be observed in the sample resistance. As follows from
Eq.~(\ref{res1}), this requirement provides the frequency limit
for the validity of our calculation, $ \ln (\nu_0/\omega) \gg
\sqrt{\xi}$, which is automatically fulfilled for all the
frequencies less than the typical hopping frequency, $\nu_h=\nu_0
e^{-\xi}$.
\section{Coulomb glass scenarios}
The above considerations demonstrate many-site multistable
configurations in the hopping insulator. The probability of
finding such configurations depends on the interplay between the
Coulomb interaction and the random potential produced by stray
disorder, e.~g. by charged acceptors. The question which arises
here is whether there is a critical value of disorder
discriminating between the cases of exponentially low, $\propto
e^{-\gamma N}$, probability of finding such configurations and the
probability close to one. Earlier we relied upon rather strong
disorder assuming exponential decay of the probability with the
size of the metastable aggregate.
Now we will discuss the consequences of the intrinsically
correlated distribution of charges where there is no exponential
decay of the probability with the exponent proportional to the
number of sites in the aggregate. Namely, let us assume that
there is a critical value $\gamma_c$ of the parameter $\gamma =\ln1 /\lambda$
such as that the systems with $\gamma < \gamma_c$ allow to form
the arbitrarily large metastable configurations. The independent
support of this idea (although again for model systems) is given
by theoretical considerations given in Ref.~\onlinecite{Ioffe}.
Namely, it is demonstrated that the sites within a Coulomb gap
demonstrate replica-symmetry breaking which can be related to a
presence of extensive number of metastable states within a
thermodynamic limit $N \rightarrow \infty$. We also note that
multi-stable character of the ground states was also demonstrated
by several numerical simulations.~\cite{11,Laikhtman}
In principle, one can consider the following 3 scenarios:
\begin{itemize}
\item[(i)] \textit{Strong disorder}, $\gamma > \gamma_c$. Only
rare multistable aggregates are available due to the effect of
disorder, the probability exponentially decreasing with an
increase of the aggregate size.
\item[(ii)] \textit{Weak disorder}, $\gamma < \gamma_c$. The
multistable configurations are inherent for the system, which in
this case can be called the Coulomb glass. The results depends on
the typical distance of charge transfer:
\begin{itemize}
\item[a.] the charge transfer within the metastable aggregates is
restricted by neighboring sites. Correspondingly, the interactions
are dominated by the short range dipole-dipole forces (``dipolar
glass"), and the short range ordering in the sites occupation
numbers still exists. In this case one expects that the local
glassy dynamics is not significantly affected by coupling with the
remote regions. Namely, the dynamics of a critical resistor is
dominated by the nearest aggregate with a specific relaxation
rate. One can expect that in this regime the system would have the
$1/\omega$ spectrum down to any practically achievable frequency,
and the exponent $\bar{\alpha}=0$.
\item[b.] The charge transfer at large distances is important. In
this case the local short-order configuration of the sites
occupation numbers can depend on the state of the remote regions
(``large-scale Coulomb glass"), and as a result a hierarchical
dynamics becomes possible. In this case the low-frequency noise
cannot be regarded as a superposition of statistically-independent
Poissonian telegraph-like fluctuations occurring in different
parts of the sample and acting on different backbone resistors.
Because of hierarchical dynamics of the aggregates one can expect
that fluctuation of \textit{each} site energy possesses $1/f$-type
spectrum. To the best of our knowledge, this situation has not
been analyzed yet in a convincing way.
\end{itemize}
The difference between the ``dipolar" and ``large-scale" Coulomb
glasses can be in principle revealed experimentally by analyzing
local occupation fluctuations by means of scanning tunnelling
spectroscopy. For the scenario (iia) the telegraph noise with a
given relaxation time is expected, while for (iib) a noise with a
complex spectrum should be observed provided the large enough
observation times are possible.
\end{itemize}
For both scenarios, the $1/f$ noise spectrum should hold down to
arbitrary small (from practical point of view) frequencies.
Since the characteristic switching times for large aggregates can
be too long to be observable, at realistic noise frequencies one
deals only with switchings of relatively small metastable
aggregates. To consider these aggregates as compact and
statistically independent one has to ensure that the aggregate's
switching between the metastable states does not cause
repopulation of the states outside the aggregate. Consequently,
the signs of their energies (counted from the chemical potential)
should not change. In addition, the Coulomb interactions with the
sites outside the aggregate should not affect the aggregate
dynamics. Both contributions are proportional to the
\textit{surface} of the aggregate, i.~e. $\propto N^{2/3}$.
Repeating the analysis of Sec.~\ref{s1} and ascribing the
probability factor $e^{-\gamma^*N^{2/3}}$ to allow for the surface
contribution one concludes that $S(\omega) \propto \omega^{-1}$
and $\bar{\alpha}=0$.
The controversial experimental results on the temperature
dependence of the flicker noise in the Coulomb glass, see e.~g.
Refs.~\onlinecite{exp}, can, in principle, be of fundamental
nature. Indeed, in the previous discussion we did not consider the
time fluctuations of the single-particle energies of the sites
forming the aggregates. These fluctuations are due to correlated
electronic hops, which can be more important for the noise than
for the stationary transport. An attempt to consider the role of
the fluctuations of site energies in hopping transport was made in
Ref.~\onlinecite{ours}. Somewhat later an important role of strong
fluctuations in the Coulomb glass was also emphasized in
Ref.~\onlinecite{Laikhtman}. We feel that correlated hopping may
indeed introduce a frequency cut-off to the noise spectrum; this
cut-off can be considered as a hallmark of correlated hopping.
This may be the case in the materials where experimental values of
$T_0$ are significantly smaller than those conventionally
expected.~\cite{Shklovskii-Efros}
Our conclusion regarding the absence of the frequency lower
cut-off agrees favorably with available experimental results. The
temperature dependence is more problematic since different
temperature dependences were observed, see, e. g., analysis in
Ref.~\onlinecite{12}.
\acknowledgments This work was supported by the U. S. Department
of Energy Office of Science through contract No. W-31-109-ENG-38.
Prior to resubmission of the revised version of our manuscript
about the preprint by Burin and Shklovskii.~\cite{BS} We like to
thank A. L. Burin and B. I. Shklovskii for making their work
available before publication and for useful discussion.
|
{
"redpajama_set_name": "RedPajamaArXiv"
}
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\section{Characteristics of a System-of-Systems}
In an increasing networked society many new super-systems are developed by the interconnection of existing legacy systems. This new type of systems, called {\it System-of-Systems}, is fundamentally different from the classic monolithic system, as depicted in Table~\ref{table1}.
\begin{table}[h]
\begin{center}
\begin{tabular}{rcc}
{\bf Characteristic} & {\bf Monolithic} & {\bf SoS} \\
Scope of System & Fixed (known) & Not known \\
Structure & Hierarchical & Networked \\
Requirements and Spec. & Fixed & Changing \\
Control & Central & Autonomous \\
Evolution & Version control & Uncoordinated \\
Testing & Test phases & Continuous \\
Implementation technology & Given and fixed & Unknown \\
Faults (Physical, Design) & Exceptional & Normal \\
Emergence & Insignificant & Important \\
System development & Process model & ??? \\
\end{tabular}
\caption{Monolithic Systems versus System of Systems (adapted from \cite{Maier1998})\label{table1}}
\end{center}
\end{table}
Whereas a monolithic system is in the \textit{sphere of control}, i.e., the \textit{governance}, of a single organization,
the constituent systems (CSs) of an SoS belong to different organization with different organizational
objectives. From the point of view of a SoS, its CSs are thus autonomous and cannot be \textit{forced to}
contribute to the overall goal of the SoS, they can only be \textit{influenced to} contribute by providing proper
incentives and reward structures. Since the CSs belong to different organization adhering to different
architectural styles, the information that is exchanged across an interface will normally be based on
different syntax and semantics, thus leading to \textit{property mismatches} at the interfaces. These property
mismatches, both at the syntactic and semantic level, must be resolved in order that a meaningful
communication among the different CSs can be established.
Whereas the internal structure of a CS can be mapped into a hierarchy, the structure of an SoS is more
likely to be a mesh, implying that a hierarchical decomposition of an SoS is in general not possible. In
order to control the cognitive complexity of SoS models, an \textit{aspect-oriented approach} is followed.
Only those aspects of the CSs that are relevant for the purpose of the integration into the SoS are visible at the relied upon messages interfaces (RUMI) between CSs, thus reducing the amount of
information that needs to be dealt with at an interface in order to understand the behavior of the SoS.
The deliberate placement of the RUMIs and the precise specification of their syntax, semantics and
temporal properties are of utmost importance in the design of an SoS.
Every successful system that is embedded in the real world must continuously evolve in order to
remain relevant for its users. An \textit{open system} that does not adapt to the ever-changing requirements of
our highly dynamic world will soon become obsolescent. From the point of evolution, monolithic
systems and SoSs are fundamentally different. Whereas the version control in a monolithic system
ensures that all changes are consistent before a new version of a monolithic system is released, the
evolutions of the different CSs forming an SoS generally cannot not be coordinated in this way. A CS
is changed whenever there is a \textit{need to change} required by the owning organization, hardly
considering or coordinating all the possible consequences of the changes on the overall SoS behavior.
This puts many of the well-established system engineering principles and design methods up for
discussion. A static authoritative specification of an SoS does not exist. The same system that is
correct today may not be correct tomorrow, since the world has changed.
The interactions of the CSs of an SoS can lead to the appearance of unique properties at the SoS level
that cannot be attributed to any of the properties of the CSs. These new properties are called \textit{emergent
properties}. Emergent properties are novel, irreducible, and holistic---they disappear when the system
is partitioned into its subsystem. Consider the example of \textit{deadlock} in a distributed computer systems.
Emergent properties can be \textit{unforeseen} or \textit{expected}, they can be \textit{beneficial} or \textit{detrimental}. At its first
appearance, emergent properties are often unforeseen. At the moment, the general issues revolving
around the concept of emergence are not well understood and it is a challenge to detect and avoid
detrimental emergence properties in a new SoS.
The objective of SoS design is the establishment of a framework that supports unforeseen changes---
this is major paradigm shift in our industry. Understanding the proper handling of the evolution of an
SoS is thus a most relevant theme for practitioners and researchers.
\section{Cognitive Complexity}
According to the Merriam Webster Dictionary \cite{mw2013} \textit{complex} means \textit{hard to separate, analyze or solve;
having many parts or aspects that are usually interrelated}. We can classify complexity as follows:
\begin{itemize}
\item Complexity as a Property of a scenario
\begin{itemize}
\item[$\circ$] \textit{Structural Complexity} that is concerned with the topology of the parts and the links
among the parts.
\item[$\circ$] \textit{Dynamic Complexity} that is concerned with the behavior of the parts and their
dynamic interactions, such as causality, feedback or delayed response.
\end{itemize}
\item Complexity as a Relation
\begin{itemize}
\item[$\circ$] \textit{Cognitive Complexity:} Relation between a scenario and an observer.
\item[$\circ$] \textit{Socio Political Complexity:} Relation between a scenario and society.
\end{itemize}
\end{itemize}
In this presentation we focus on Cognitive Complexity (the antonym of simplicity) of a SoS, which is a
relation between a scenario and an observer who tries to understand the scenario. We understand the
world around us by conceptual modeling, i.e., by the generation of a hierarchy of models of reality that
are agreeing with the cognitive capabilities of the human mind. Understanding means that the
concepts and dependencies used to represent a model are adequately linked with concepts already
familiar to the observer. The closer these links, the better the understanding. We consider the elapsed
time needed to understand a model by an observer of the intended group of observers as a feasible
measure for the cognitive complexity of a model.
A conceptual model is an abstraction that is formed for the purpose of understanding a chosen aspect
of the scenario, such as: structure, behavior, timeliness, dependability, etc.. If the purpose of a model
is not crystal clear, it is not possible to construct a simple model of a scenario because it cannot be
decided what is relevant and what is irrelevant (and can be neglected) when constructing an abstract
model for the specified purpose. Take the example of celestial mechanics: If the purpose of the model
is the understanding of the movement of the heavenly bodies, we abstract from the whole diversity of
the world and reduce it to a mass point.
In the context of a SoS, understanding the behavior is of utmost importance. The complexity of a
model of behavior of a SoS depends on the static and dynamic properties of the constituent systems,
the organization of the SoS (i.e., the static structure and dynamic interaction of the CSs) and the
experience of the observer in dealing with such an SoS. In order to ease the understanding it may be
necessary to construct a hierarchy of behavioral models, where at the lower level a model is a
refinement of a higher-level model. Each model must take account of the limits of human cognition—
at most five plus minus two chunks of information can be represented in short term memory \cite{miller1956} and
humans are not capable to handle relations with more than four variables \cite{halford2005many}.
\section{Relied-Upon Message Interfaces (RUMI)}
As a rule the CSs of a SoS interact by the exchange of messages only. The internal architecture of an
SoS is determined by the placement and specification of the Relied Upon Message Interfaces (RUMIs)
among the CSs. A RUMI should be a stable interface that establishes the boundaries between two
interacting CSs by specifying the messages that are exchanged between these CSs. RUMIs must be
fully specified w.r.t. their syntax, semantics and temporal behavior. Whereas the syntactic
specification deals with the structure of the interface and establishes the form of the syntactic units, the
data items at the interface, the semantics specification assigns meaning to these interface data items.
The semantic specification consists of an interface model that explains the data items by using
concepts that are familiar to the user of the interface. Since the two CSs that meet at a RUMI are
normally designed by different organizations that use different architectural styles, there will be two
different semantic specifications of the same RUMI, depending from which side the RUMI is viewed.
The temporal specification of a RUMI must outline the temporal properties of the message exchanges.
\section{Simplification Strategies}
The major challenge of information system design is the building of a software/hardware/people
artifact that provides the intended service under given constraints and where relevant properties of this
artifact (e.g., the behavior) can be modeled at different levels of abstraction by models of adequate
simplicity. The following design principles, developed for the control of the cognitive complexity of
monolithic systems, are also relevant for Systems-of-Systems \cite[p.~46]{kopetz2011real}:
\begin{itemize}
\item {\it Principle of Abstraction:} The behavior of a large system can be explained by a hierarchy of
models, where each model considers the limited cognitive capability of the human mind, as
explained in Section 3.
\item {\it Principle Separation of Concern:} This principle helps to build simple systems by
disentangling functions that are separable in order that they can be grouped in self-contained
architectural units,
\item {Principle of Causality:} The analytical-rational problem solving subsystem of humans excels
in reasoning along causal chains. The deterministic behavior of basic mechanisms makes it
possible that a causal chain between a cause and the consequent effect can be established
without a doubt. Probabilistic dependencies between cause and effect are more difficult to
grasp.
\item {\it Principle of Segmentation:} This principle suggests that hard-to-understand behavior should
be decomposed, wherever possible, into a serial behavioral structure such that a sequential
step-by-step analysis of the behavior becomes possible.
\item {\it Principle of Observability:} Non-visible communication channels among architectural units
pose a severe impediment for the understanding of system behavior. This can be avoided by
supporting a multicast topology in the basic message passing primitive. It is then possible to
observe the external behavior of any component without a probe effect.
\item {\it Principle of a Consistent Global Time:} This principle suggests that a sparse global time base
should be introduced in all CSs of an SoS such that system-wide consistent temporal relations
(e.g., simultaneity) and physical temporal distances among events can be established on the
basis of global time-stamps.
\end{itemize}
In addition, the following specific design principles should help to reduce the cognitive complexity of
System of Systems:
\begin{itemize}
\item {\it Principle of Classification of Expected Changes:} In the context of evolution of an SoS we
distinguish between minor and major changes: minor changes are confined to the internals of
a CS and have no effect on a RUMI. Major changes have an effect on one or more RUMIs. In
a large SoS is advantageous to categorize RUMIs (and consequently changes) w.r.t. their
impact on the overall SoS architecture on an even finer scale.
\item {\it Principle of Outside Flexible, Inside Stable Interfaces:} The interfaces between a cyber-system
and its external environment are subject to the evolution of the external world. This evolution
is out of control of the cyber-system. Internal relied upon message interfaces (RUMI) can
only be controlled, if both sides of the interface are in the sphere of control of the system
designer. It is therefore good practice to provide a gateway component between an internal
RUMI and an interface to the external world.
\item {\it Principle of Intrinsic vs. Extrinsic Complexity:} Extrinsic complexity is concerned with the
service of a CS at a given relied upon message interface (RUMI). Intrinsic complexity is
concerned with the design of the internals a CS. From the SoS point of view, a low extrinsic
complexity of the RUMIs of the CSs should be strived for. In many cases, a low extrinsic
complexity is achieved at the price of a high intrinsic complexity.
\item {\it Principle of Specifying Goals, not Processes:} It is much simpler to specify a goal state—a
problem solution— than to specify a process that leads from the current state to the goal state
\cite{Newell1972}. In many SoSs, a top layer—the federation layer—interfaces with the problem owner and
partitions the user's goal into sub-goals. Selected CSs are activated to find solutions to the
sub-goals specified in the respective RUMIs. A CS should be autonomous in finding a
solution to a sub-goal that is specified in its RUMI. This process can be recursive.
\item {\it Principle of Autonomic Fault Mitigation:} Considerations about fault containment and the
control of error propagation have a decisive influence on the placement of the RUMIs. A CS
should form an encapsulated fault-containment unit (FCU). Error detection mechanisms must
be provided in the SoS to detect failures of a CS within a short error detection latency. A CS
should be capable to recover from a transient fault within a defined error recovery time. This
requires the provision of appropriate recovery points as part of the design.
\item Principle of Isomorphic Decomposition: An SoS can modeled from different viewpoints,
such as behavior, fault containment, evolution, maintenance, etc. Each viewpoint can be
explained by a hierarchy of models. Ideally, the analysis of a SoS according to these different
viewpoints should result in the same decomposition, which is then called an isomorphic
decomposition \cite{wimsatt1975}. The design of an isomorphic structure is an art that requires experience
and foresight.
\end{itemize}
\section{Conclusion}
Systems of systems are substantially different from monolithic systems---many of the established
design methods need to be revisited. Since the substantial cognitive effort required to understand a
system-of-system from the different perspectives is the main cause for the massive engineering effort
in design and operation, it is a worthwhile goal to structure a System of System such that the cognitive
complexity for understanding the designed artifact is reduced.
\nocite{*}
\bibliographystyle{eptcs}
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"redpajama_set_name": "RedPajamaArXiv"
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\section{\bf Introduction }
\label{sec:introduction}
In recent years, random graph theory has been applied to model many complex real-world phenomena. A basic random graph used to model complex networks is the \gls{ER} graph \cite{erdos1959random}, where edges between the nodes appear with equal probabilities. In \cite{gilbert1961random}, the author introduces another random graph called \gls{RGG} where nodes have some random position in a metric space and the edges are determined by the position of these nodes. Since then, \gls{RGG} properties have been widely studied \cite{penrose2003random}.
\glspl{RGG} are very useful to model problems in which the geographical distance is a critical factor. For example, {\glspl{RGG}} have been applied to wireless communication network \cite{bettstetter2002minimum}, sensor network \cite{yick2008wireless} and to study the dynamics of a viral spreading in a specific network of interactions \cite{preciado2009spectral}, \cite{ganesh2005effect}. Another motivation for \glspl{RGG} in arbitrary dimensions is multivariate statistics of high-dimensional data. In this case, the coordinates of the nodes can represent the attributes of the data. Then, the metric imposed by the \gls{RGG} depicts the similarity between the data.
In this work, the \gls{RGG} is constructed by considering a finite set $\mathcal{X}_{n}$ of $n$ nodes, $x_{1},...,x_{n},$ distributed uniformly and independently on the $d$-dimensional torus $\mathbb{T}^d \equiv [0, 1]^d$. We choose a torus instead of a cube in order to avoid boundary effects. Given a geographical distance, $r_{n} >0 $, we form a graph by connecting two nodes $x_{i}, x_{j} \in \mathcal{X}_{n}$ if their $\ell_{p}$-distance, $p \in [1, \infty]$ is at most $r_{n}$, i.e., $\|x_{i}-x_{j} \|_{p} \leq r_{n}$, where $\|.\|_{p}$ is the $\ell_{p}$-metric defined as
\begin{equation*}
\small
\label{eqq1}
\| x_{i}- x_{j} \|_{p} =\left\{
\begin{array}{ll}
\left( \sum_{k=1}^d \vert x_{i}^{(k)}-x_{j}^{(k)}\vert^p \right)^{1/p} & p \in [1, \infty),\\
\max\lbrace \vert x_{i}^{(k)}-x_{j}^{(k)}\vert, \ k \in [1, d] \rbrace & p=\infty.
\end{array}
\right.
\end{equation*}
The \gls{RGG} is denoted by $G(\mathcal{X}_{n}, r_{n})$. Note that for the case $p=2$ we obtain the Euclidean metric on $\mathbb{R}^d$. Typically, the function $r_{n}$ is chosen such that $r_{n}\rightarrow 0$ when $n \rightarrow \infty$.
The degree of a vertex in $G(\mathcal{X}_{n}, r_{n})$ is the number of edges connected to it. The average vertex degree in $G(\mathcal{X}_{n}, r_{n})$ is given by \cite{penrose2003random}
\begin{equation*}
a_{n} = \theta^{(d)} nr_{n}^d,
\end{equation*}
where $\theta^{(d)}=\pi^{d/2}/\Gamma(d/2+1)$ denotes the volume of the $d$-dimensional unit hypersphere in $\mathbb{T}^d$ and $\Gamma(.)$ is the Gamma function.
Different values of $r_{n}$, or equivalently $a_{n}$, lead to different geometric structures in \glspl{RGG}. In \cite{penrose2003random}, different interesting regimes are introduced: the \textit{connectivity regime} in which $a_{n}$ scales as $\log(n)$ or faster, i.e., $\Omega(\log(n))$\footnote{The notation $f(n) =\Omega(g(n))$ indicates that $f(n)$ is bounded below by $g(n)$ asymptotically, i.e., $\exists K>0$ and $ n_{o} \in \mathbb{N}$ such that $\forall n > n_{0}$ $f(n) \geq K g(n)$.}, the \textit{thermodynamic regime} in which $a_{n}\equiv \gamma$, for $\gamma >0$ and the \textit{dense regime}, i.e., $a_{n}\equiv \Theta(n).$
\glspl{RGG} can be described by a variety of random matrices such as adjacency matrices, transition probability matrices and normalized Laplacian. The spectral properties of those random matrices are powerful tools to predict and analyze complex networks behavior. In this work, we give a special attention to the \gls{test} of the adjacency matrix of \glspl{RGG} in the connectivity regime.
Some works analyzed the spectral properties of \glspl{RGG} in different regimes. In particular, in the thermodynamic regime, the authors in \cite{bordenave2008eigenvalues}, \cite{blackwell2007spectra} show that the spectral measure of the adjacency matrix of \glspl{RGG} has a limit as $n \to \infty$. However, due to the difficulty to compute exactly this spectral measure, Bordenave in \cite{bordenave2008eigenvalues} proposes an approximation for it as $\gamma \rightarrow \infty$.
In the connectivity regime, the work in \cite{preciado2009spectral} provides a closed form expression for the asymptotic spectral moments of the adjacency matrix of $G(\mathcal{X}_{n}, r_{n})$. Additionnaly, Bordenave in \cite{bordenave2008eigenvalues} characterizes the spectral measure of the adjacency matrix normalized by $n$ in the dense regime. However, in the connectivity regime and as $n\rightarrow \infty$, the normalization factor $n$ puts to zero all the eigenvalues of the adjacency matrix that are finite and only the infinite eigenvalues in the adjacency matrix are nonzero in the normalized adjacency matrix. Motivated by this results, in this work we analyze the behavior of the eigenvalues of the adjacency matrix without normalization in the connectivity regime and in a wider range of the connectivity regime.
First, we propose an approximation for the actual \gls{test} of the \gls{RGG}. Then, we provide a bound on the Levy distance between this approximation and the actual distribution. More precisely, for $\epsilon>0$ we show that the \glspl{test} of the adjacency matrices of the \gls{RGG} and the \gls{DGG} with nodes in a grid converge to the same limit when $a_{n}$ scales as $\Omega (\log^{\epsilon}(n)\sqrt{n})$ for $d=1$ and as $\Omega (\log^{2}(n))$ for $d\geq 2$.
Then, under the $\ell_{\infty}$-metric we provide an analytical approximation for the eigenvalues of the adjacency matrix of \glspl{RGG} by taking the $d$-dimensional discrete Fourier transform (DFT) of an $n=\mathrm{N}^{d}$ tensor of rank $d$ obtained from the first block row of the adjacency matrix of the \gls{DGG}.
The rest of this paper is organized as follows. In Section \ref{sec:systemmodel} we describe the model, then we present our main results on the concentration of the \gls{test} of large \glspl{RGG} in the connectivity regime. Numerical results are given in Section \ref{sec:results} to validate the theoretical results. Finally, conclusions are given in Section \ref{sec:conclusion}.
\begin{comment}
\begin{figure*}[!t]
\centering
\subfloat[Thermodynamic regime]{\includegraphics[width=2.1in]{thermodynamic}%
\label{fig_first_case}}
\hfil
\subfloat[Connectivity regime]{\includegraphics[width=2.1in]{connected}%
\label{fig_second_case}}
\caption{An illustration of an \gls{RGG} on a torus with $n=200$ nodes with a connection radius $r_{n}$= $0.02$ in (a) and $r_{n}$= $0.1$ in (b). }
\label{fig_RGG1}
\end{figure*}
\end{comment}
\section{\bf\bf Spectral Analysis of \glspl{RGG}}
\label{sec:systemmodel}
To study the spectrum of $G(\mathcal{X}_{n}, r_{n})$ we introduce an auxiliary graph called the \gls{DGG}. The \gls{DGG} denoted by $G(\mathcal{D}_{n}, r_{n})$ is formed by letting $\mathcal{D}_{n}$ be the set of $n$ grid points that are at the intersections of axes parallel hyperplanes with separation $n^{-1/d}$, and connecting two points $x'_{i}$, $x'_{j}$ $\in \mathcal{D}_{n}$ if $\|x'_{i}-x'_{j} \|_{p} \leq r_{n}$ with $p\in [1, \infty]$. Given two nodes, we assume that there is always at most one edge between them. There is no edge from a vertex to itself. Moreover, we assume that the edges are not directed.
Let $\mathbf{A}(\mathcal{X}_{n})$ be the adjacency matrix of $G(\mathcal{X}_{n}, r_{n})$, with entries
\begin{equation*}
\mathbf{A}(\mathcal{X}_{n})_{i j}=\chi [x_{i} \sim x_{j}],
\label{RW}
\end{equation*}
where the term $\chi[x_{i}\thicksim x_{j}] $ takes the value 1 when there is a connection between nodes $x_{i}$ and $x_{j}$ in $G(\mathcal{X}_{n}, r_{n})$ and zero otherwise, represented as
\begin{equation*}
\label{eqq1}
\chi[x_{i}\thicksim x_{j}] =\left\{
\begin{array}{ll}
1, & \| x_{i} - x_{j}\|_{p} \leq r_{n}, \ \ i \neq j, \ \ p \in [1, \infty]\\
0, & \mathrm{otherwise}.
\end{array}
\right.
\end{equation*}
A similar definition holds for $\mathbf{A}(\mathcal{D}_{n})$ defined over $G(\mathcal{D}_{n}, r_{n})$. The matrices $\mathbf{A}({\mathcal{X}_{n}})$ and $\mathbf{A}({\mathcal{D}_{n}})$ are symmetric and their spectrum consists of real eigenvalues. We denote by $\lbrace \lambda_{i}, i=1,..,n \rbrace$ and $\lbrace \mu_{i}, i=1,..,n \rbrace$ the sets of all real eigenvalues of the real symmetric square matrices $\mathbf{A}({\mathcal{D}_{n}})$ and $\mathbf{A}({\mathcal{X}_{n}})$ of order $n$, respectively.
The empirical spectral distribution functions $v_{n}(x)$ and $v'_{n}(x)$ of the adjacency matrices of an \gls{RGG} and a \gls{DGG}, respectively are defined as
\begin{equation*}
v_{n}(x)=\dfrac{1}{n} \sum\limits_{i=1}^n \mathrm{I}\lbrace \mu_{i} \leq x\rbrace \ \ \mathrm{and }\ \ \ v'_{n}(x)=\dfrac{1}{n} \sum\limits_{i=1}^n \mathrm{I}\lbrace \lambda_{i}\leq x\rbrace,
\end{equation*}
where $\mathrm{I}\lbrace \mathrm{B} \rbrace$ denotes the indicator of an event $\mathrm{B}$.
Let $a'_{n}$ be the degree of the nodes in $G(\mathcal{D}_{n}, r_{n})$. In the following Lemma \ref{bound} we provide an upper bound for $a'_{n}$ under any $\ell_{p}$-metric.
\begin{lemma}
\label{bound}
For any chosen $\ell_{p}$-metric with $p \in [1,\infty]$ and $d\geq1$, we have
\begin{equation*}
a'_{n} \leq d^{\frac{1}{p}}2^{d}a_{n} \left( 1+\frac{1}{2a_{n}^{1/d}}\right)^d.
\end{equation*}
\end{lemma}
\begin{proof}
See Appendix \ref{app:bound}
\end{proof}
To prove our result on the concentration of the \gls{test} of \glspl{RGG} and investigate its relationship with the \gls{test} of \glspl{DGG} under any $\ell_{p}$-metric, we use the Levy distance between two distribution functions defined as follows.
\begin{definition}(\cite{taylor2012introduction}, page 257)
Let $v_{n}^A$ and $v_{n}^B$ be two distribution functions on $\mathbb{R}$. The Levy distance $L(v_{n}^A, v_{n}^B)$ between them is the infimum of all positive $\epsilon$ such that, for all $x \in \mathbb{R}$
\begin{equation*}
v_{n}^A(x-\epsilon) -\epsilon \leq v_{n}^B(x)\leq v_{n}^A(x+\epsilon)+\epsilon.
\end{equation*}
\end{definition}
\begin{lemma}(\cite{bai2008methodologies}, page 614)
\label{Difference Inequality}
Let A and B be two $n$ $\times$ $n$ Hermitian matrices with eigenvalues $\lambda_{1},...,\lambda_{n}$ and $\mu_{1},...,\mu_{n}$, respectively. Then
\begin{equation*}
L^{3}(v_{n}^A, v_{n}^B) \leqslant \dfrac{1}{n}tr(A-B)^2,
\end{equation*}
where $L(v_{n}^{A},v_{n}^{B})$ denotes the Levy distance between the empirical distribution functions $v_{n}^{A}$ and $v_{n}^{B}$ of the eigenvalues of $A$ and $B$, respectively.
\end{lemma}
Let $\mathrm{M}_{n}$ be the minimum bottleneck matching distance corresponding to the minimum length such that there exists a perfect matching of the random nodes to the grid points for which the distance between every pair of matched points is at most $\mathrm{M}_{n}$.
Sharp bounds for $\mathrm{M}_{n}$ are given in \cite{shor1991minimax}\cite{leighton1986tight}\cite{goel2004sharp}. We repeat them in the following lemma for convenience.
\begin{lemma}
Under any $\ell_{p}$-norm, the bottleneck matching is
\begin{itemize}
\item $\mathrm{M}_{n} = O \left( \left( \dfrac{\log n}{n}\right)^{1/d}\right),$ \ \ when $d \geq 3$ \cite{shor1991minimax}.
\vspace{0.1cm}
\item $\mathrm{M}_{n} = O \left(\left(\dfrac{\log^{3/2} n}{n}\right)^{1/2} \right),$ \ \ when $d= 2$ \cite{leighton1986tight}.
\vspace{0.1cm}
\item $\mathrm{M}_{n} = O \left(\sqrt{\dfrac{\log \epsilon^{-1}}{n}}\right),$ with prob. $\geq 1-\epsilon$,\ $d= 1$ \cite{goel2004sharp}.
\end{itemize}
\end{lemma}
Under the condition $\mathrm{M}_{n}= o(r_{n})$, we provide an upper bound for the Levy distance between $v_{n}$ and $v'_{n}$ in the following lemma.
\begin{lemma}
\label{lemafirst}
For $d \geq 1$, $p \in [1, \infty]$ and $\mathrm{M}_{n}= o(r_{n})$, the Levy distance between $v_{n}$ and $v'_{n}$ is upper bounded as
\begin{equation}
\begin{aligned}
\label{equation0}
& L^{3} \left( v_{n}, v'_{n} \right) \leq d^{\frac{1}{p}} 2^{d+1} \left| \frac{1}{n}\sum\limits_{\substack{ i}}^{} \mathbf{N}(x_{i}) - a_{n} \right| \\
&+d^{\frac{1}{p}} 2^{d+1} \left| a_{n} -\frac{2}{n} \sum\limits_{\substack{ i}}^{} \mathrm{L}_{i} \right| +a'_{n},
\end{aligned}
\end{equation}
where, $\mathbf{N}(x_{i})$ denotes the degree of $x_{i}$ in $G(\mathcal{X}_{n}, r_{n})$ and $\mathrm{L}_{i} \sim \mathrm{Bin}\left(n, \theta^{(d)}\left( r_{n}-2\mathrm{M}_{n}\right) \right)$. \comment{Due to space constraints we omit the details of the proof}.
\end{lemma}
\begin{proof}
See Appendix \ref{app:lemmafirst}.
\end{proof}
The condition enforced on $r_{n}$, i.e., $\mathrm{M}_{n}= o(r_{n})$ implies that for $\epsilon >0$, (\ref{equation0}) holds when $a_{n}$ scales as $\Omega (\log^{\epsilon}(n)\sqrt{n})$ for $d=1$, as $\Omega (\log^{\frac{3}{2}+\epsilon}(n))$ for $d= 2$ and as $\Omega (\log^{1+\epsilon}(n))$ for $d\geq 3$.
In what follows, we show that the \gls{test} of the adjacency matrix of $G(\mathcal{X}_{n}, r_{n})$ concentrate around the \gls{test} of the adjacency matrix of $G(\mathcal{D}_{n}, r_{n})$ in the connectivity regime in the sense of convergence in probability.
Notice that the term $ \sum\limits_{\substack{ i}}^{} \mathbf{N}(x_{i}) / 2$ in Lemma \ref{lemafirst} counts the number of edges in $G(\mathcal{X}_{n}, r_{n})$. For convenience, we denote $ \sum\limits_{\substack{ i}}^{} \mathbf{N}(x_{i}) / 2$ as $\xi_{n}$. To show our main result we apply the Chebyshev inequality given in Lemma \ref{Chebyschev-inequality} on the random variable $\xi_{n}$. For that, we need to determine $\mathrm{Var}(\xi_{n})$
\begin{lemma}(Chebyshev Inequality)
\label{Chebyschev-inequality}
Let $\mathrm{X}$ be a random variable with an expected value $\mathbb{E}\mathrm{X}$ and a variance $\mathrm{Var}\left(\mathrm{X}\right)$. Then, for any $t>0$
\begin{equation*}
\mathbb{P} \lbrace \vert \mathrm{X}-\mathbb{E}\mathrm{\mathrm{X}} \vert \geq t \rbrace \leq \dfrac{\mathrm{Var}(\mathrm{X})}{t^2}.
\end{equation*}
\end{lemma}
\begin{lemma}
\label{variance-edges}
When $x_{1},...,x_{n}$ are i.i.d. uniformly distributed in the $d$-dimensional unit torus $\mathbb{T}^{d}=[0, 1]$
\begin{equation*}
\mathrm{Var} \left(\xi_{n}\right) \leq [\theta^{(d)}+2\theta^{(d)} a_{n} ].
\end{equation*}
\end{lemma}
\begin{proof}
The proof follows along the same lines of Proposition A.1 in \cite{muller2008two} when extended to a unit torus and applied to i.i.d. and uniformly distributed nodes.
\end{proof}
\begin{comment}
Let us consider a $d$-dimensional {\gls{DGG}} with $n= \mathrm{N}^d$ nodes and assume the use of the $\ell_{\infty}$-metric. Then, the degree of a vertex in $G(\mathcal{D}_{n}, r_{n})$ is given as {\cite{nyberg2014laplacian}}
\begin{equation*}
a'_{n}=(2k_{n}+1)^d-1, \ \ \ \mathrm{ with} \ \ k_{n}= \left\lfloor \mathrm{N}r_{n} \right\rfloor,
\label{eq:degree}
\end{equation*}
where $ \left\lfloor x \right\rfloor$ is the integer part, i.e., the greatest integer less than or equal to $x$. Note that when $d=1$, the Chebyshev distance and the Euclidean distance are the same. In the following lemma, we provide an upper bound on the degree of the each node $a'_{n}$ in $G(\mathcal{D}_{n}, r_{n})$ for any $\ell_{p}$-norm
\end{comment}
We can now state the main theorem on the concentration of the adjacency matrix of $G(\mathcal{X}_{n}, r_{n})$.
\begin{theorem}
\label{theorem-connectivity}
For $d \geq 1$, $p\in[1, \infty]$, $a \geq 1$, $\mathrm{M}_{n}= o(r_{n})$ and $t >0$, we have
\begin{equation*}
\mathbb{P} \lbrace L^{3} \left( v_{n}, v'_{n} \right) >t\rbrace \leq 2n \exp\left( \dfrac{-a_{n}\varepsilon^2}{3} \left(1-\dfrac{2\mathrm{M}_{n}}{r_{n}}\right) \right)
\end{equation*}
\begin{equation*}
+ \frac{n \left[\theta^{(d)}(r_{n}-2\mathrm{M}_{n})(a-1)+1\right]^n}{a^{\left(\frac{t}{d^{\frac{1}{p}}2^{d+3}}+\frac{a_{n}(2-c)}{4}\right)}}
\end{equation*}
\begin{equation}
\ \ \ \ +\frac{d^{\frac{2}{p}} 2^{2d+6}\left[ \theta^{(d)}+2\theta^{(d)} a_{n} \right]}{n^2t^2},
\end{equation}
where $\varepsilon= \left( \frac{t}{d^{\frac{1}{p}}2^{d+2}a_{n}}+\dfrac{(2-c)}{4}- \frac{2\mathrm{M}_{n}}{r_{n}} \right)$ and $c=\left(1+\frac{1}{2a_{n}^{1/d}} \right)^d$.
\\
In particular, for every $t>0$, $a \geq 2$, $\epsilon>0$ and $a_{n}$ that scales as $\Omega (\log^{\epsilon}(n)\sqrt{n})$ when $d=1$, as $\Omega (\log^{2}(n))$ when $d\geq 2$, we have
\begin{equation*}
\lim_{n \to\infty} \mathbb{P} \left\lbrace L^{3} \left( v_{n}, v'_{n} \right) >t \right\rbrace = 0.
\end{equation*}
\end{theorem}
\begin{proof}
See Appendix \ref{app:theorem-connectivity}.
\end{proof}
This result is shown in the sense of convergence in probability by a straightforward application of Lemma \ref{Chernoff} and \ref{Chernof-binomial} on the random variable $\mathrm{L}_{i}$, then by applying Lemma \ref{Chebyschev-inequality} and \ref{variance-edges} to $\xi_{n}.$
In what follows, we provide the eigenvalues of $\mathbf{A}(\mathcal{D}_{n})$ which approximates the eigenvalues of $\mathbf{A}(\mathcal{X}_{n})$ for $n$ sufficiently large.
\begin{lemma}
\label{corollary1:density}
For $d \geq 1$ and using the $\ell_{\infty}$-metric, the eigenvalues of $\mathbf{A}(\mathcal{D}_{n})$ are given by
\begin{equation}
\label{equation5}
\lambda_{m_{1},...,m_{d}}= \prod_{s=1}^d \dfrac{\sin(\frac{m_{s} \pi}{\mathrm{N}}(a'_{n}+1)^{1/d})}{\sin(\frac{m_{s} \pi}{\mathrm{N}})} -1,
\end{equation}
where, $m_{1},...,m_{d}$ $\in$ $\lbrace 0,...\mathrm{N}-1 \rbrace$, $a'_{n}=(2k_{n}+1)^d-1, k_{n}= \left\lfloor \mathrm{N}r_{n} \right\rfloor \ \ \mathrm{and} \ \ n=\mathrm{N}^{d}.$ The term $ \left\lfloor x \right\rfloor$ is the integer part, i.e., the greatest integer less than or equal to $x$.
\end{lemma}
\begin{proof}
See Appendix \ref{app:lemma3}.
\end{proof}
The proof utilizes the result in \cite{nyberg2014laplacian} which shows that the eigenvalues of the adjacency matrix of a \gls{DGG} in $\mathbb{T}^d$ are found by taking the $d$-dimensional DFT of an $\mathrm{N}^{d}$ tensor of rank $d$ obtained from the first block row of $\mathbf{A}(\mathcal{D}_{n})$.
For $\epsilon >0$, Theorem \ref{theorem-connectivity} shows that when $a_{n}$ scales as $\Omega (\log^{\epsilon}(n)\sqrt{n})$ for $d=1$ and as $\Omega (\log^{2}(n))$ when $d\geq 2$, the \gls{test} of the adjacency matrix of an \gls{RGG} concentrate around the \gls{test} of the adjacency matrix of a \gls{DGG} as $n \rightarrow \infty$. Therefore, for $n$ sufficiently large, the eigenvalues of the \gls{DGG} given in (\ref{equation5}) approximate very well the eigenvalues of the \gls{DGG}.
\section{\bf Numerical Results}
\label{sec:results}
We present simulations to validate the results obtained in Section \ref{sec:systemmodel}. More specifically, we corroborate our results on the spectrum of the adjacency matrix of \glspl{RGG} in the connectivity regime by comparing the simulated and the analytical results.
Fig. \ref{figg}(a) shows the cumulative distribution functions of the eigenvalues of the adjacency matrix of an \gls{RGG} realization and the analytical spectral distribution in the connectivity regime. We notice that for the chosen average vertex degree $a_{n}= \log(n)\sqrt{n}$ and $d=1$, the curves corresponding to the eigenvalues of the \gls{RGG} and the \gls{DGG} fit very well for a large value of $n$.
\captionsetup[figure]{labelfont={bf},labelformat={default},labelsep=period,name={Fig.}}
\begin{figure}
\begin{minipage}[b]{0.45\textwidth}
\begin{subfigure}[b]{\linewidth}
\includegraphics[width=\linewidth]{RGG}
\caption{Connectivity regime, $r_{n}=\frac{\log(n)}{\sqrt{n}}$, $n=2000$.}
\end{subfigure}
\end{minipage}
\caption{An illustration of the cumulative distribution function of the eigenvalues of an \gls{RGG}. }
\label{figg}
\end{figure}
\section{\bf Conclusion}
\label{sec:conclusion}
In this work, we study the spectrum of the adjacency matrix of \glspl{RGG} in the connectivity regime. Under some conditions on the average vertex degree $a_{n}$, we show that the \glspl{test} of the adjacency matrices of an \gls{RGG} and a \gls{DGG} converge to the same limit as $n \rightarrow \infty$. Then, based on the regular structure of the \gls{DGG}, we approximate the eigenvalues of $\mathbf{A}(\mathcal{X}_{n})$ by the eigenvalues of $\mathbf{A}(\mathcal{D}_{n})$ by taking the $d$-dimensional DFT of an $\mathrm{N}^{d}$ tensor of rank $d$ obtained from the first block row of $\mathbf{A}(\mathcal{D}_{n})$.
\section{\bf Acknowledgement}
This research was funded by the French Government through the Investments for
the Future Program with Reference: Labex UCN@Sophia-UDCBWN.
\bibliographystyle{IEEEtran}
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Well, I am not going to lie. It has been a rough re-launch of the Stateside Silver Screen Suppers Campaign. But here is why: Many cookbooks from the early period CLEARLY were intended for those people who are A. naturally gifted in the kitchen or B. had extensive staff who were naturally gifted in the kitchen. Tonight, I set aside some time to focus in on my most favorite task: cooking with the stars. Having bought ingredients for a number of fairly dubious recipes (please stay tuned for Janet Gaynor's cheese fondue), I chickened out (almost literally) by going with a dessert from our own sweetheart of the screen, a tiny package of pep, Shirley Temple. Yes, the title of the recipe is dubious – sure. But the idea sounded great.
ALAS: with very little information to go from, I sadly ended up with Shirley Temple's Mammy's Pecan Soup. Yup, I have eaten it with a spoon rather than cutting into a crisp, ready to pass out at an ice cream social, kind of dessert. NOW, a mighty fine recipe from the standpoint that it is delectable and much like what we might now call a "brownie." But I will get back to you on how to prevent said souplike experience. I am not dismayed, however, but rather invigorated with the challenge. Methinks it may have much to do with picking the right cooking pan. Or the fact that I opened another bottle of red wine with which to cook. This is what following the SSS mantra can do: live, learn, get lit while baking…. I know our little princess would approve.
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\section{Introduction}
The performance of a machine learning algorithm is highly sensitive to the choice of its hyperparameters. Therefore, hyperparameter selection is a crucial task in the optimization of knowledge-aggregation algorithms. Federated Learning (FL) is a recent machine learning approach which aggregates machine learning model parameters between devices (henceforth clients) without sharing their data. The aggregation is coordinated by a server. Industrial Federated Learning (IFL) is a modified approach of FL in an industrial context \cite{c3}. In an FL setting, hyperparameter optimization poses new challenges and is a major open research area \cite{c6}. In this work, we investigate the impact of different hyperparameter optimization approaches in an IFL system. We believe that the data distribution influences the choice of the best hyperparameter configuration and suggest that the best hyperparameter configuration for a client might differ from another client based on individual data properties. Therefore, we investigate a local hyperparameter optimization approach that -- in contrast to a global hyperparameter optimization approach -- allows every client to have its own hyperparameter configuration. The local approach allows us to optimize hyperparameters prior to the federation process reducing communication costs.
Communication is considered a critical bottleneck in FL \cite{c10}. Clients are usually limited in terms of communication bandwidth enhancing the importance of reducing the number of communication rounds or using compressed communication schemes for the model updates to the central server \cite{c10}. Dai et al.\ \cite{c5} introduced \textit{Federated Bayesian Optimization} (FBO) extending Bayesian optimization to the FL setting. However, until now, there is no research on the impact of global and local hyperparameter optimization in FL. Therefore, we compare a local hyperparameter optimization approach to a global hyperparameter optimization approach, optimizing hyperparameters in the federation process.
The aim of this work is to i) analyze challenges and formal requirements in FL, and in particular in IFL, ii) to evaluate the performance of an Internet of Things (IoT) sensor based classification task in an IFL system, iii) to investigate a communication efficient hyperparameter optimization approach, and iv) to compare different hyperparameter optimization algorithms. Therefore, we want to answer the following questions.
\begin{itemize}
\item[Q1:] Does FL work for an IoT sensor based anomaly classification task on industrial assets with non-identically distributed data in an IFL system with a cohort strategy?
\item[Q2:] Can we assume that the global and local hyperparameter optimization approach deliver the same hyperparameter configuration in an i.i.d.\ FL setting?
\item[Q3:] Can we reduce communication costs in the hyperparameter optimization of a non-i.i.d.\ classification task in context of FL by optimizing a hyperparameter locally prior to the federation process?
\item[Q4:] Does Bayesian optimization outperform grid search, both in a global and local approach of a non-i.i.d.\ IoT sensor based classification task?
\end{itemize}
\section{Algorithmic Challenges and Formal Requirements for industrial Assets}
In FL, new algorithmic challenges arise that differentiate the corresponding optimization problem from a distributed optimization problem. In distributed learning settings, major assumptions regarding the training data are made which usually fail to hold in an FL setting \cite{c1}. Moreover, non-i.i.d.\ data, limited communication, and limited and unreliable client availability pose further challenges for optimization problems in FL \cite{c6}. Kairouz et al.\ \cite{c6} considered the need for addressing these challenges as a major difference to distributed optimization problems. The optimization problem in FL is therefore referred to as federated optimization emphasizing the difference to distributed optimization \cite{c1}. In an IFL setting, additional challenges regarding industrial aspects arise \cite{c3}. In this section, we want to formulate the federated optimization problem and discuss the algorithmic challenges of FL in general, and in particular of IFL.
\subsection{Problem Formulation}
We consider a supervised learning task with features $x$ in a sample space $\mathcal{X}$ and labels $y$ in a label space $\mathcal{Y}$. We assume that we have $K$ available clients, $K \in \mathbb{N}_{\ge2}$, with
\begin{displaymath}
D_{k}:=D_{\mathcal{X},k}\times D_{\mathcal{Y},k} \subseteq \mathcal{X} \times \mathcal{Y}
\end{displaymath}
denoting the data set of client $k$ and $n_{k}:=|D_{k}|$ denoting the cardinality of the client's data set. Let $\mathcal{Q}$ denote the distribution over all clients, and let $\mathcal{P}_{k}$ denote the data distribution of client $k$. We can then access a specific data point by first sampling a client $k\sim \mathcal{Q}$ and then sampling a data point $(x,y) \sim \mathcal{P}_{k}$ \cite{c6}. Then, the local objective function is
\begin{align}
F_{k}(w):=\underset{(x,y) \sim \mathcal{P}_{k}}{\mathbb{E}}[f(x,y,w)],
\end{align}
where $w \in \mathbb{R}^{d}$ represents the parameters of the machine learning model and $f(x,y,w)$ represents the loss of the prediction on sample $(x,y)$ for the given parameters $w$. Typically, we wish to minimize
\begin{align}
F(w):=\frac{1}{K} \sum_{k=1}^{K} F_{k}(w).
\end{align}
\subsection{Federated Learning}
One of the major challenges concerns data heterogeneity. In general, we cannot assume that the data is identically distributed over the clients, that is $\mathcal{P}_k = \mathcal{P}_l$ for all~$k$ and~$l$. Therefore, $F_{k}$ might be an arbitrarily bad approximation of~$F$ \cite{c1}.
In the following, we want to analyze different non-identically distributed settings as demonstrated by Hsieh et al.\ \cite{c8} assuming that we have an IoT sensor based anomaly classification task in an industrial context. Given the distribution $\mathcal{P}_{k}$, let $P^{k}_{\mathcal{X},\mathcal{Y}}$ denote the bivariate probability function, let $P^{k}_{\mathcal{X}}$ and $P^{k}_{\mathcal{Y}}$ denote the marginal probability function respectively. Using the conditional probability function $P^{k}_{\mathcal{Y}|\mathcal{X}}$ and $P^{k}_{\mathcal{X}|\mathcal{Y}}$, we can now rewrite the bivariate probability function as
\begin{align}
P^{k}_{\mathcal{X},\mathcal{Y}}(x,y) = P^{k}_{\mathcal{Y}|\mathcal{X}}(y|x) P^{k}_{\mathcal{X}}(x)=P^{k}_{\mathcal{X}|\mathcal{Y}}(x|y) P^{k}_{\mathcal{Y}}(y)
\end{align}
for $(x,y) \in \mathcal{X} \times \mathcal{Y}$. This allows us to characterize different settings of non-identically distributed data:
\textit{Feature distribution skew:}
We assume that $P^{k}_{\mathcal{Y}|\mathcal{X}}=P^{l}_{\mathcal{Y}|\mathcal{X}}$ for all $k$, $l$, but $P^{k}_{\mathcal{X}} \ne P^{l}_{\mathcal{X}}$ for some $k$, $l$. Clients that have the same anomaly classes might still have differences in the measurements due to variations in sensor and machine type.
\textit{Label distribution skew:}
We assume that $P^{k}_{\mathcal{X}|\mathcal{Y}}=P^{l}_{\mathcal{X}|\mathcal{Y}}$ for all $k$, $l$, but $P^{k}_{\mathcal{Y}}\ne P^{l}_{\mathcal{Y}}$ for some $k$, $l$. The distribution of labels might vary across clients as clients might experience different anomaly classes.
\textit{Same label, different features:}
We assume that $P^{k}_{\mathcal{Y}}=P^{l}_{\mathcal{Y}}$ for all $k$, $l$, but $P^{k}_{\mathcal{X}|\mathcal{Y}}\ne P^{l}_{\mathcal{X}|\mathcal{Y}}$ for some $k$, $l$. The same anomaly class can have significantly different features for different clients due to variations in machine type, operational- and environmental conditions.
\textit{Same features, different label:}
We assume that $P^{k}_{\mathcal{X}}=P^{l}_{\mathcal{X}}$ for all $k$ and $l$, but $P^{k}_{\mathcal{Y}|\mathcal{X}}\ne P^{l}_{\mathcal{Y}|\mathcal{X}}$ for some $k$, $l$. The same features can have different labels due to operational- and environmental conditions, variation in manufacturing, maintenance et cetera.
\textit{Quantity skew:}
We cannot assume that different clients hold the same amount of data, that is $n_{k} = n_{l}$ for all $k$, $l$. Some clients will generate more data than others.
In real-world problems, we expect to find a mixture of these non-identically distributed settings. In FL, heterogeneity does not exclusively refer to a non-identical data distribution, but also addresses violations of independence assumptions on the distribution $\mathcal{Q}$ \cite{c6}. Due to limited, slow and unreliable communication on a client, the availability of a client is not guaranteed for all communication rounds. Communication is considered a critical bottleneck in FL \cite{c10}. In each communication round, the participating clients send a full model update $w$ back to the central server for aggregation. In a typical FL setting, however, the clients are usually limited in terms of communication bandwidth \cite{c10}. Consequently, it is crucial to minimize the communication costs.
\subsection{Industrial Federated Learning}
In an industrial setting, FL experiences challenges that specifically occur in an industrial context. Industrial assets have access to a wealth of data suitable for machine learning models, however, the data on an individual asset is typically limited and private in nature. In addition to sharing the model within the company, it can also be shared with an external industry partner \cite{c3}. FL leaves possibly critical business information distributed on the individual client (or within the company). However, Zhao et al.\ \cite{c4} proved that heterogeneity, in particular, a highly skewed label distribution, significantly reduces the accuracy of the aggregated model in FL. In an industrial context, we expect to find heterogeneous clients due to varying environmental and operational conditions on different assets. Therefore, Hiessl et al.\ \cite{c3} introduced a modified approach of FL in an industrial context and termed it \textit{Industrial Federated Learning} (IFL). IFL does not allow arbitrary knowledge exchange between clients. Instead, the knowledge exchange only takes place between clients that have sufficiently similar data. Hiessl et al.\ \cite{c3} refer to this set of clients as a \textit{cohort}. We expect the federated learning approach in a cohort to approximate the corresponding central learning approach.
\section{Hyperparameter Optimization Approaches in an IFL System}
In an FL setting, hyperparameter optimization poses new challenges and is a major open research area \cite{c6}. The performance of a machine learning model is linked to the amount of communication \cite{c9}. In an effort to reduce communication costs, a critical bottleneck in FL \cite{c10}, we investigated a communication efficient hyperparameter optimization approach, a local hyperparameter optimization approach that allows us to optimize hyperparameters prior to the federation process. Kairouz et al.\ \cite{c6} introduced the idea of a separate optimization of hyperparameters and suggest a different hyperparameter choice for dealing with non-i.i.d.\ data.
Dai et al.\ \cite{c5} investigated a communication efficient local hyperparameter optimization approach and introduced Federated Bayesian Optimization (FBO) extending Bayesian optimization to the FL setting. In FBO, every client locally uses Bayesian optimization to find the optimal hyperparameter configuration. Additionally, each client is allowed to request for information from other clients. Dai et al. \cite{c5} proved a convergence guarantee for this algorithm and its robustness against heterogeneity. However, until now, there is no research on the impact of global and local hyperparameter optimization.
In the LocalHPO algorithm \ref{alg: LocalHPO}, we perform local hyperparameter optimization. We optimize the hyperparameter configuration $\lambda^{k}$ for each client $k$. In the GlobalHPO algorithm \ref{alg: GlobalHPO}, we perform global hyperparameter optimization. We optimize the hyperparameter configuration $\lambda$ in the federation process. The LocalOptimization method in the LocalHPO algorithm \ref{alg: LocalHPO} and the GlobalOptimization method in the GlobalHPO algorithm \ref{alg: GlobalHPO} can be based on any hyperparameter optimization algorithm.
\begin{algorithm}\small
\DontPrintSemicolon
\caption{LocalHPO}
\label{alg: LocalHPO}
\SetAlgoLined
\textbf{Server executes:}\;
initialize $w_{0}$\;
\For{each client $k=1,\dots,K$}{
$\lambda^{k} :=$ LocalOptimization$(k, w_{0})$\;
}
return $(\lambda^{k})_{k=1}^{K}$
\end{algorithm}
\begin{algorithm}\small
\DontPrintSemicolon
\caption{GlobalHPO}
\label{alg: GlobalHPO}
\SetAlgoLined
\textbf{Server executes:}\;
$\lambda :=$ GlobalOptimization$()$\;
return $\lambda$
\end{algorithm}
We want to differentiate between a global hyperparameter $\lambda_{i}$ whose value is constant for all clients and a local hyperparameter $\lambda_{i}^{k}$ whose value depends on a client $k$. Here, $\lambda_{i}^{k}$ denotes the hyperparameter $\lambda_{i}$ on client $k$. We notice that this differentiation is only relevant for settings with non-i.i.d.\ data. In an i.i.d.\ setting, we assume that a hyperparameter configuration that works for one client also works for another client. In our experiments, we verified this assumption for a proxy data set.
\section{Data, Algorithms and Experiments}
In the next section, we want to make our benchmark design explicit and present our experimental setup. We will present the machine learning tasks including the data partition of the training data, the machine learning models, the optimization algorithms and our experiments. We considered an image classification task on a data set, the MNIST data set of handwritten digits, and an IoT sensor based anomaly classification task on industrial assets.
\subsection{Data}
In order to test the IFL system on the MNIST data set, we still need to specify on how to distribute the data over artificially designed clients. To systematically evaluate the effectiveness of the IFL system, we simulated an i.i.d.\ data distribution. This refers to shuffling the data and partitioning the data into $10$ clients, each receiving 6\,000 examples. Following the approach of McMahan et al.\ \cite{c1}, we applied a convolutional neural network with the following settings: $2$~convolutional layers with $32$ and $64$ filters of size $5\!\times\!5$ and a ReLu activation function, each followed by a max pooling layer of size $2\!\times\!2$, a dense layer with $512$ neurons and a ReLu activation function, a dense layer with $10$ neurons and a softmax activation function.
The industrial task concerns IoT sensor based anomaly classification on industrial assets. The data was acquired with the SITRANS multi sensor, specifically developed for industrial applications and its requirements \cite{c11}. We considered multiple centrifugal pumps with sensors placed at different positions, in different directions to record three axis vibrational data in a frequency of $6644$\,Hz. Per minute, $512$ samples were collected. We operated the pumps under $6$~varying conditions, including $3$~healthy states and $3$~anomalous states. A client is either assigned data of an asset in a measurement, or data of several assets in a measurement ensuring that each client sees all operating conditions. However, since in the process of measurement, the assets were completely dismantled and rebuilt, we consider the data to be non-i.i.d.\ regarding its feature distribution. We applied an artificial neural network with the following settings: a dense layer with $64$ neurons and a ReLu activation function, a dropout layer with a dropout rate of $0.4$, a dense layer with $6$ neurons and a ReLu activation function, a dropout layer with a dropout rate of $0.4$, and a softmax activation function. We remapped the features using the Kabsch algorithm \cite{c12}, applied a sliding window, extracted the Melfrequency cepstral coefficients, applied the synthetic minority oversampling technique \cite{c12}, and normalized the resulting features.
\subsection{Algorithms}
Our evaluations include the Federated Averaging (FedAvg) algorithm according to McMahan et al.\ \cite{c1}, and the hyperparameter optimization approaches LocalHPO \ref{alg: LocalHPO} and GlobalHPO \ref{alg: GlobalHPO}. We implemented these approaches based on grid search and Bayesian optimization. In this section, we give their pseudocode. We searched for the learning rate $\eta$ with fixed fraction of participating clients $C$, number of communication rounds $R$, number of local epochs $E$, and mini-batch size $B$.
In algorithm \ref{alg: LocalOptimization Grid}, we give the pseudocode of the LocalOptimization method in LocalHPO \ref{alg: LocalHPO} based on the grid search algorithm with a fixed grid $G$. We iterate through the grid~$G$, train the model on the training data of client $k$ based on the ClientUpdate method used in the FedAvg algorithm \cite{c1} with the learning rate $\eta$ as an additional argument, and validate the performance of the model $w_{\eta}$ on the validation data $\mathcal{D}_{\mathrm{valid}}^{k}$ of client $k$. Finally, the learning rate that yields the highest accuracy $A_{\eta}$ on the validation data is selected. Here, $w_{\eta}$ denotes the resulting model trained on the training data with learning rate $\eta$ and $A(\mathcal{D}_{\mathrm{valid}}^{k}, w_{\eta})$ denotes the accuracy of the model tested on the validation data $\mathcal{D}_{\mathrm{valid}}^{k}$ of client $k$.
\begin{algorithm}\small
\DontPrintSemicolon
\caption{Local Grid Search}
\label{alg: LocalOptimization Grid}
\SetAlgoLined
LocalOptimization$(k, w_{0})$:\;
\For{\text{each learning rate} $ \eta \in G$}{
$w_{\eta} :=$ ClientUpdate$(k, w_{0}, \eta)$\;
$A_{\eta} := A(\mathcal{D}_{\mathrm{valid}}^{k}, w_{\eta})$
}
$\eta_{k}^{*} := \underset{\eta \in G}{\arg \max} \hspace{1mm} A_{\eta}$\;
return $\eta_{k}^{*}$
\end{algorithm}
\begin{algorithm}\small
\DontPrintSemicolon
\caption{Global Grid Search}
\label{alg: GlobalOptimization Grid}
\SetAlgoLined
GlobalOptimization$()$:\;
\For{\text{each learning rate} $ \eta \in G$}{
$w_{\eta} :=$ FederatedAveraging$(\eta)$\;
\For{\text{each client} $k=1,\dots,K$}{
$A_{\eta}^{k} := A(\mathcal{D}_{\mathrm{valid}}^{k}, w_{\eta})$
}
$A_{\eta} := \frac{1}{K}\sum_{k=1}^{K}A_{\eta}^{k}$
}
$\eta^{*} := \underset{\eta \in G}{\arg \max} \hspace{1mm} A_{\eta}$\;
return $\eta^{*}$
\end{algorithm}
In algorithm \ref{alg: GlobalOptimization Grid}, we give the pseudocode of the GlobalOptimization method in GlobalHPO \ref{alg: GlobalHPO} based on the grid search algorithm with a fixed grid $G$. We iterate through the grid, perform the FedAvg algorithm \cite{c1} with the learning rate $\eta$ as an additional argument, validate the performance of the model $w_{\eta}$ on the validation data $\mathcal{D}_{\mathrm{valid}}^{k}$ for all clients $k$ and compute the average accuracy of all clients. Finally, the learning rate that yields the highest average accuracy $A_{\eta}$ is selected.
In algorithm \ref{alg: LocalOptimization Bayesian}, we give the pseudocode of the LocalOptimization method in LocalHPO \ref{alg: LocalHPO} based on Bayesian optimization. The objective function $f$ takes the learning rate $\eta$ as an argument, trains the model on the training data of client $k$ based on the ClientUpdate method used in the FedAvg algorithm \cite{c1} with the learning rate $\eta$ as an additional argument, validates the performance of the model $w$ on the validation data $\mathcal{D}_{\mathrm{valid}}^{k}$ of client $k$, and returns the resulting accuracy. We initialize a gaussian process $GP$ for the objective function $f$ with $n_{\mathrm{init}}$ sample points. Then, we find the next sample point $\eta_{n_{\mathrm{init}} + i}$ by maximizing the acquisition function, evaluate $f(\eta_{n_{\mathrm{init}} + i})$, and update the gaussian process $GP$. Finally, we select the learning rate $\eta^{*}$ that yields the highest accuracy. We repeat this for $n_{\mathrm{iter}}$ iterations.
In algorithm \ref{alg: GlobalOptimization Bayesian}, we give the pseudocode of the GlobalOptimization method in GlobalHPO \ref{alg: GlobalHPO} based on Bayesian optimization. The objective function $f$ takes the learning rate $\eta$ as an argument, performs the FedAvg algorithm \cite{c1} with the learning rate $\eta$ as an additional argument, validates the performance of the model $w$ on the validation data $\mathcal{D}_{\mathrm{valid}}^{k}$ for all clients $k$, computes the average accuracy of all clients and returns the resulting accuracy. We initialize a gaussian process $GP$ for the objective function $f$ with $n_{\mathrm{init}}$ sample points. Then, we find the next sample point $\eta_{n_{\mathrm{init}} + i}$ by maximizing the acquisition function, evaluate $f(\eta_{n_{\mathrm{init}} + i})$, and update the gaussian process $GP$. Finally, we select the learning rate $\eta^{*}$ that yields the highest average accuracy. We repeat this for $n_{\mathrm{iter}}$ iterations.
\begin{algorithm}\small
\DontPrintSemicolon
\caption{Local Bayesian Optimization}
\label{alg: LocalOptimization Bayesian}
\SetAlgoLined
LocalOptimization$(k, w_{0})$:\;
initialize a gaussian process $GP$ for $f$\;
evaluate $f$ at $n_{\mathrm{init}}$ initial points\;
\For{$i=1,\dots,n_{\mathrm{iter}}$}{
find sample point $\eta_{n_{\mathrm{init}} + i}$ that maximizes acquisition function\;
evaluate objective function $f$ at $\eta_{n_{\mathrm{init}} + i}$\;
update the gaussian process $GP$\;
}
$\eta^{*} := \underset{i=1, \dots, n_{\mathrm{init}}+n_{\mathrm{iter}}}{\arg \max} \hspace{1mm} f(\eta_{i})$\;
return $\eta^{*}$\;
\textbf{objective function:}\;
$f(\eta)$:\;
$w :=$ ClientUpdate$(k, w_{0}, \eta)$\;
$A := A(\mathcal{D}_{\mathrm{valid}}^{k}, w)$\;
return $A$
\end{algorithm}
\begin{algorithm}\small
\DontPrintSemicolon
\caption{Global Bayesian Optimization}
\label{alg: GlobalOptimization Bayesian}
\SetAlgoLined
GlobalOptimization$()$:\;
initialize a gaussian process $GP$ for $f$\;
evaluate $f$ at $n_{\mathrm{init}}$ initial points\;
\For{$i=1,\dots,n_{\mathrm{iter}}$}{
find sample point $\eta_{n_{\mathrm{init}} + i}$ that maximizes acquisition function\;
evaluate objective function $f$ at $\eta_{n_{\mathrm{init}} + i}$\;
update the gaussian process $GP$\;
}
$\eta^{*} := \underset{i=1,\dots, n_{\mathrm{init}}+n_{\mathrm{iter}}}{\arg \max} \hspace{1mm} f(\eta_{i})$\;
return $\eta^{*}$\;
\textbf{objective function:}\;
$f(\eta)$:\;
$w :=$ FederatedAveraging$(\eta)$\;
\For{\text{each client} $k=1,\dots,K$}{
$A^{k} := A(\mathcal{D}_{\mathrm{valid}}^{k}, w)$\;
}
$A := \frac{1}{K}\sum_{k=1}^{K}A^{k}$\;
return A
\end{algorithm}
\subsection{Experiments}
In order to systematically investigate the impact of global and local hyperparameter optimization, we compared the global and local hyperparameter optimization approach in an i.i.d.\ setting, the MNIST machine learning task, as well as in a non-i.i.d.\ setting, the industrial task. Therefore, we implemented the global and local optimization approach based on grid search with a grid $G:=[0.0001, 0.001, 0.01, 0.1]$, and based on Bayesian optimization with the widely used squared exponential kernel and the upper confidence bound acquisition function. We searched for the learning rate $\eta$ with fixed $R$, $C$, $E$ and $B$.
In order to evaluate the global and local optimization approaches in a direct comparison, we chose the number of epochs $E$ in the local optimization approach as $E=E_{\mathrm{global}}R$, where $E_{\mathrm{global}}$ is the number of epochs in the global optimization approach and $R$ is the number of communication rounds. In the global optimization task, we set $R:=10$, $C:=1$, $E:=1$ and $B:=128$ for the MNIST data, and $R:=10$, $C:=1$, $E:=5$ and $B:=128$ for the industrial data. In the local optimization task, we set $E:=10$ and $B:=128$ for the MNIST data, and $E:=50$ and $B:=128$ for the industrial data. For the evaluation of the global hyperparameter optimization approach, we optimized the learning rate using the global approach, trained the federated model with a global learning rate, and tested the resulting federated model on the cohort test data. Then, we optimized the learning rate using the local approach, trained the federated model with local individual learning rates for each client in the cohort, and tested the resulting federated model on the cohort test data.
\section{Experimental Results}
Following the approach of Hiessl et al.\ \cite{c3}, we demonstrated the effectiveness of the IFL System for the industrial task and showed that the IFL approach performs better than the individual learning approach and approximates the central learning approach. Fig.~\ref{client comparison sp260 grid} shows the test accuracy on the central cohort test data for each client, for i) a model trained on the individual training data of the client, ii) a central model trained on the collected training data of all clients in the cohort, and iii) the federated model trained in the cohort.
\begin{figure}[ht]
\centerline{\includegraphics[width=0.35\textwidth]{fig-1.eps}}
\caption{Comparison of individual learning, central learning, and federated learning on the industrial data set.}
\label{client comparison sp260 grid}
\end{figure}
\begin{figure}[ht]
\centerline{\includegraphics[width=0.4\textwidth]{fig-2.eps}}
\caption{Comparison of the optimization approaches based on a) grid search for the MNIST task, b) grid search for the industrial task, and c) Bayesian optimization for the industrial task.}
\label{hpo comparison}
\end{figure}
Fig.\ \ref{hpo comparison} a) shows the results for the MNIST data. The optimization approaches are based on the grid search algorithm. For the training posterior to the optimization, we set $R:=10$, $C:=1$, $E:=1$, and $B:=128$ in the IFL system. The color indicates the optimized learning rate on the corresponding client. Since the MNIST data is i.i.d., there is only one cohort and all clients have the same federated model and thus the same test accuracy. Our results show that the grid search algorithm selected $10^{-3}$ in the local optimization of the learning rate on each client. According to our expectation, the global optimization approach yielded the same learning rate.
For the industrial task, we evaluated the global and local optimization approach based on grid search and Bayesian optimization. For the training posterior to the optimization, we set $R:=20$, $C:=1$, $E:=5$, and $B:=128$ in the IFL system. Fig.~\ref{hpo comparison}~b) shows the results for the industrial data with the optimization approaches based on the grid search algorithm. The results show that, in all cohorts, the global approach yielded an equal or larger accuracy than the local approach.
Fig.\ \ref{hpo comparison} c) shows the results for the industrial data with the optimization approaches based on the Bayesian algorithm. Note that the search space of the learning rate was $[10^{-4}, 10^{-1}]$ in the optimization while the scale in the plot starts from $10^{-3}$. The results show that the global approach yielded a larger accuracy than the local approach in cohort~$0$ and cohort~$1$.
The local Bayesian approach yielded different learning rates, see Fig.~\ref{hpo comparison}~c), on clients with no difference in data, that is, the same number of samples, the same class distribution, and the same measurement protocol. However, the local grid search approach yielded the same learning rate as the global grid search approach, see Fig.~\ref{hpo comparison}~b). Therefore, we suggest that the reason lies in the implementation of the Bayesian optimization approach and a not sufficiently large number of iterations to guarantee convergence.
In order to compare the optimization approaches for the industrial task, we performed a paired t-test regarding the test accuracy to determine the statistical significance, see table~\ref{tab2}. We observe that the global optimization approach is significantly better than the local approach, both for the grid search approach ($p=0.028$) and for the Bayesian approach ($p=0.012$). Furthermore, the results show that the grid search approach is significantly better than the Bayesian approach, both for the global approach ($p=0.004$) and for the local approach ($p=0.008$). Note that we considered cohort~$2$ an outlier and excluded this cohort from our calculations. Cohort~$2$ only consists of client~$8$, a client whose data was not generated according to the standard measurement protocol. Without outlier removal, the global grid search approach is still significantly better than the local grid search approach ($p=0.032$), and the local grid search approach is significantly better than the local Bayesian approach ($p=0.010$). However, there is no significant difference in the global Bayesian approach vs.\ the local Bayesian approach ($p=0.755$) and in the global grid search approach vs.\ the global Bayesian approach ($p=0.230$).
\section{Conclusion and Future Work}
The results show that the federated learning approach approximates the central learning approach, while outperforming individual learning of the clients. In this work, we investigated the impact of global and local optimization approaches in an IFL System based on a proxy data set and a real-world problem. In our experiments on the industrial data, local optimization yielded different learning rates on different clients in a cohort. However, the results show that a globally optimized learning rate, and thus, a global learning rate for all clients in a cohort improves the performance of the resulting federated model. Therefore, we conclude that the global optimization approach outperforms the local optimization approach resulting in a communication-performance trade-off in the hyperparameter optimization in FL. In our experiments on the proxy data set, however, the local approach achieved the same performance as the global approach.
\begin{table}[t]
\caption{Test accuracy of federated model on central cohort test data posterior to corresponding optimization approach and training}
\begin{center}
\begin{tabular}{ |c|c|c|c|c| }
\hline
client & global grid & local grid & global Bayesian & local Bayesian \\
\hline
$1$ & \textbf{0.7756} & 0.7720 & 0.7659 & 0.6897 \\
\hline
$2$ & \textbf{0.7756} & 0.7720 & 0.7659 & 0.6897 \\
\hline
$3$ & \textbf{0.7756} & 0.7720 & 0.7659 & 0.6897 \\
\hline
$4$ & \textbf{0.7756} & 0.7720 & 0.7659 & 0.6897 \\
\hline
$5$ & \textbf{0.8230} & 0.7921 & 0.7882 & 0.7889 \\
\hline
$6$ & \textbf{0.8230} & 0.7921 & 0.7882 & 0.7889 \\
\hline
$7$ & \textbf{0.8230} & 0.7921 & 0.7882 & 0.7889 \\
\hline
$8$ & 0.9740 & \textbf{0.9749} & 0.3867 & 0.9736\\
\hline
$9$ & \textbf{0.7756} & 0.7720 & 0.7659 & 0.6897 \\
\hline
\end{tabular}
\label{tab2}
\end{center}
\end{table}
A limitation of our study is that we only considered one hyperparameter in our optimization task. Hence it would be interesting to explore whether we can confirm these observations for a hyperparameter configuration of more hyperparameters. The results show that the grid search approaches outperform the Bayesian approaches, both globally and locally. However, we suggest a convergence analysis for the Bayesian approach.
\nocite{*}
|
{
"redpajama_set_name": "RedPajamaArXiv"
}
| 1,175
|
\section{Introduction}\label{sec:intro}
In \cite[Conjecture~4.32]{Bru02a}, Brundan formulated a Kazhdan-Lusztig style (BKL) conjecture on the characters of irreducible modules for the complex general linear Lie superalgebra $\mf{gl}_{m|n}$. The idea was that characters in the integral category $\mathcal{O}$ for $\mf{gl}_{m|n}$ are controlled by certain canonical bases in the $\mf{sl}_{\mathbb{Z}}$-module $V^{\otimes m}\otimes W^{\otimes n}$, where $V=\mathbb{C}^{\mathbb{Z}}$ is the natural $\mf{sl}_{\mathbb{Z}}$-module and $W=V^*$ is its restricted dual. This conjecture admits natural parabolic variants (see e.g. \cite[Conjecture 3.10]{CW07}). The corresponding $\mf{sl}_{\mathbb{Z}}$-modules are of the form
\begin{equation}\label{eq:wedgemodule}
\bigwedge\nolimits^{\underline{m}}V\otimes\bigwedge\nolimits^{\underline{n}}W:=\bigwedge\nolimits^{m_1} V\otimes\cdots\otimes \bigwedge\nolimits^{m_s} V\otimes\bigwedge\nolimits^{n_1} W\otimes\cdots\otimes \bigwedge\nolimits^{n_t} W
\end{equation}
\noindent where $\underline{m}=(m_1,\ldots, m_s)$, $\underline{n}=(n_1,\ldots, n_t)$, $m=\sum m_i$, and $n=\sum n_j$ (in fact the wedges of $V$s and $W$s can be in any order, but we restrict our attention to this case for the introduction).
There is a natural $\mf{sl}_{\mathbb{Z}}$-module isomorphism $\bigwedge^{\infty}V\cong\bigwedge^{\infty}W$ between semi-infinite wedge spaces. In \cite{CW07} the authors considered the induced isomorphism
\begin{equation}\label{eq:combSD}
\bigwedge\nolimits^{\underline{m}}V\otimes\bigwedge\nolimits^{\underline{n}}W\otimes\bigwedge\nolimits^{\infty}V\cong \bigwedge\nolimits^{\underline{m}}V\otimes\bigwedge\nolimits^{\underline{n}}W\otimes\bigwedge\nolimits^{\infty}W.
\end{equation}
\noindent Motivated by this, they defined infinite-rank parabolic categories $\mathcal{O}$, denoted $\mathcal{O}^{++}_0$ and $\mathcal{O}^{++}_1$ respectively, for the corresponding infinite-rank general linear Lie superalgebras and conjectured an equivalence $\mathcal{O}^{++}_0\cong\mathcal{O}^{++}_1$. This is super duality (the special case $s=1$, $t=0$ was first conjectured in \cite{CWZ06}).
Super duality was proved in \cite[Theorem~5.1]{CL09}. It can be regarded as a bridge between categories $\mathcal{O}$ for general linear Lie algebras and superalgebras. Its utility stems from `truncation functors' (see Definition \ref{def:trunc} or \cite{CW07}) from the categories $\mathcal{O}^{++}_{\epsilon}$ (${\epsilon\in\{0,1\}}$) to finite-rank categories $\mathcal{O}$. These allow us to read off information about the finite-rank categories from their infinite-rank counterparts. For example, the BKL conjecture for the special case $t=1$ is an immediate corollary of super duality, as observed in \cite[Remark~4.19]{CW07}. Super duality was also a key component in the first general proof of the BKL conjecture in \cite[Theorem~8.11]{CLW12}.
Starting with an arbitrary Kac-Moody algebra $\mf{g}$ and a tensor product $M$ of integrable highest weight modules for $\mf{g}$, Losev and Webster \cite{LW13} defined what it means for a categorical action of $\mf{g}$ on a category $\mc{C}$ (in the sense of Chuang and Rouquier \cite{CR04}, \cite{Rou08}) to be a \emph{tensor product categorification} (TPC) of $M$. Building on uniqueness for categorifications of integrable highest weight modules in \cite{Rou12} they showed that such TPCs are unique up to equivalence.
For $r\in \mathbb{N}$, let $I_r=\{i\in\mathbb{Z}\mid 1-r\leq i\leq r-1\}$ and let $\mf{sl}_{I_r}$ be the special linear Lie algebra of traceless complex matrices with rows and columns indexed by $I_r^+:=I_r\cup(I_r+1)$. Let $V_r$ be the natural $\mf{sl}_{I_r}$-module and $W_r=V_r^*$ its dual.
In a highly non-trivial extension of the uniqueness result of \cite{LW13}, Brundan, Losev, and Webster proved in \cite[Theorem~2.12]{BLW13} proved that TPCs of $\mf{sl}_{\mathbb{Z}}$-modules of the form \eqref{eq:wedgemodule} are unique up to equivalence. Roughly, they did this by regarding the $\mf{sl}_{\mathbb{Z}}$-module as a union of $\mf{sl}_{I_r}$-modules:
\begin{equation}\label{eq:moduleunion}
\bigwedge\nolimits^{\underline{m}}V\otimes\bigwedge\nolimits^{\underline{n}}W=\bigcup_{r=1}^{\infty}\bigwedge\nolimits^{\underline{m}}V_r\otimes\bigwedge\nolimits^{\underline{n}}W_r.
\end{equation}
\noindent Moreover, they showed in \cite[Theorem~3.10]{BLW13} that translation functors on a finite-rank integral parabolic category $\mathcal{O}$ for $\mf{gl}_{m|n}$ make the category a TPC of the corresponding $\mf{sl}_{\mathbb{Z}}$-module (\ref{eq:wedgemodule}) and that any such TPC possesses a unique Koszul graded lift compatible with its categorification structures.
This paper examines TPCs of modules of the form \eqref{eq:combSD} and applications to the infinite-rank categories $\mathcal{O}^{++}_{\epsilon}$. In Theorem~\ref{thm:uniquenessofTPCs} we show these TPCs are unique up to equivalence. We deal with semi-infinite wedges by regarding them as a direct limit of finite wedges. So the decomposition \eqref{eq:moduleunion} is replaced by the direct limit
\begin{equation}
\bigwedge\nolimits^{\underline{m}}V\otimes\bigwedge\nolimits^{\underline{n}}W\otimes\bigwedge\nolimits^{\infty}V=\lim_{\longrightarrow}~ \bigwedge\nolimits^{\underline{m}}V_r\otimes\bigwedge\nolimits^{\underline{n}}W_r\otimes\bigwedge\nolimits^rV_r,
\end{equation}
\noindent or the analogous limit for $\bigwedge^{\infty} W$.
Take $\epsilon\in\{0,1\}$. In Theorem~\ref{infranktpc} we prove that the infinite-rank category $\mathcal{O}^{++}_{\epsilon}$ is a TPC of the corresponding $\mf{sl}_{\mathbb{Z}}$-module. Super duality follows immediately. Our main tools are the truncation functors already mentioned. These allow us to consider a module in $\mathcal{O}^{++}_{\epsilon}$ as a direct limit of modules for finite-rank general linear Lie superalgebras as the rank goes to infinity. First we need to establish that $\mathcal{O}^{++}_{\epsilon}$ has enough projectives. This is a new result of this paper. We construct projective covers in $\mathcal{O}^{++}_{\epsilon}$ as the direct limit of projective covers in certain subcategories of finite-rank categories $\mathcal{O}$. The key property is that the Verma flags of these projective covers stabilize when the rank is sufficiently large.
An unexpected difficulty occurs in defining the functors $E_j$ on $\mathcal{O}^{++}_{\epsilon}$ lifting the action of the Chevalley generators $e_j$. The corresponding translation functors on finite-rank categories $\mathcal{O}$ are not well behaved with respect to truncation, so we can't define connecting maps for the direct limit in the obvious way. We actually define two sets of connecting maps, leading to isomorphic functors $E_j^{\texttt{L}}$ and $E_j^{\texttt{R}}$ which are naturally left and right adjoint to $F_j$ respectively. Again, these only give well-defined functors on $\mathcal{O}^{++}_{\epsilon}$ because the composition multiplicities eventually stabilize.
Finally we replace $\mf{sl}_{\mathbb{Z}}$-modules with modules over the quantum group $\mc{U}_q\mf{sl}_{\mathbb{Z}}$ and categories with graded categories. Following \cite[Section~5]{BLW13} we show that our $\mf{sl}_{\mathbb{Z}}$-TPCs have unique graded lifts that are $\mc{U}_q\mf{sl}_{\mathbb{Z}}$-TPCs, and these graded categories are Koszul. In particular, the categories $\mathcal{O}^{++}_{\epsilon}$ have Koszul graded lifts and super duality lifts to a graded equivalence between them. This is a new result of this paper.
It is our hope that this work will be useful in the study of the representation theory of quantum supergroups at roots of unity.
This paper is organized as follows. In Section \ref{section:combinatorics} we describe the combinatorics of the wedge spaces. In Section \ref{section:uniquenessofTPCs} we define our TPCs and show that they are unique up to equivalence. In Section \ref{section:catO} we define the infinite-rank categories $\mathcal{O}^{++}_{\epsilon}$, show they have enough projectives, and define the categorical actions on them. We prove they are TPCs and deduce the super duality equivalence. Finally in Section \ref{section:gradings} we establish the existence of graded lifts.
\begin{conv}
By a \emph{Schurian category} we mean an abelian category $\mc{C}$ such that all objects are of finite length, there are enough projectives and injectives, and the endomorphism algebras of the irreducible objects are one dimensional. Let $K_0\left(\mathcal{C}\right)$ denote the split Grothendieck group of the full subcategory of projective objects in $\mc{C}$. Set $[ \mathcal{C}] := \mathbb{C}\otimes_{\mathbb{Z}} K_0(\mathcal{C})$.
If $A$ is an associative algebra we write mod-$A$ for the category of finite-dimensional right $A$-modules. If we have a collection of objects $X_r$ indexed by $\mathbb{N}\cup \{\infty\}$ we will drop the subscript in the $r=\infty$ case and write $X=X_\infty$. If $\mf{a}$ is a Lie superalgebra we will say `$\mf{a}$-module' to mean $\mf{a}$-supermodule.
\end{conv}
\begin{acknowledgements}
The author would like to thank his advisor Weiqiang Wang for suggesting this project and for his generosity with his time and advice.
\end{acknowledgements}
\section{Combinatorics}\label{section:combinatorics}
Take $r\in \mathbb{N}\cup \{\infty\}$. Let
\begin{align}
I_r:=\{ \, i\in\mathbb{Z} \, \mid \, 1-r\leq i\leq r-1 \, \}
\end{align}
\noindent and $I_r^+:=I_r\cup(I_r+1)$. Let $\mathfrak{sl}_{I_r}$ denote the Lie algebra of complex traceless matrices with rows and columns indexed by $I_r^+$ and with only finitely many non-zero entries in each row and column. Let $f_i:=e_{i,i+1}$ (resp. $e_i:=e_{i+1,i}$) denote the matrix unit with 1 in position $(i,\, i+1)$ (resp. $(i+1,\, i)$) and 0s elsewhere. Define the weight and root lattices of $\mf{sl}_{I_r}$ by
\begin{equation}
P_r:=\bigoplus_{i\in I_r} \mathbb{Z} \omega_i \qquad \text{and} \qquad Q_r:=\bigoplus_{i\in I_r} \mathbb{Z} \alpha_i
\end{equation}
\noindent respectively, where $\alpha_i:=2\omega_i-\omega_{i-1}-\omega_{i+1}$ and we interpret $\omega_i$ as 0 if $i\notin I_r$. We will denote the non-degenerate pairing $P_r \times Q_r \to \mathbb{Z}$ by $\left(\omega,\alpha\right)\mapsto \omega\cdot\alpha$.
Let $P_r^+\subseteq P_r$ (resp. $Q_r^+\subseteq Q_r$) denote the $\mathbb{Z}_{\geq 0}$-span of the $\omega_i$ (resp. $\alpha_i$). Define the dominance ordering on $P_r$ by declaring that $\beta\geq \gamma$ if $\beta-\gamma\in Q_r^+$. For $i\in I_r^+$ let $\varepsilon_i:=\omega_i-\omega_{i-1}$ where again we interpret $\omega_i$ as 0 if $i\notin I_r$.
Let $V_r$ be the natural $\mathfrak{sl}_{I_r}$-module of column vectors with standard basis $\{v_i\mid i\in I_r^+\}$. Let $W_r$ be the dual of $V_r$ with dual basis $\{w_i\mid i\in I_r^+\}$. We will denote the exterior powers $\bigwedge^n V_r$ and $\bigwedge^n W_r$ by $\bigwedge^{n,0} V_r$ and $\bigwedge^{n,1} V_r$, respectively. For $n\in \mathbb{N}$ and $\epsilon\in\{0,1\}$ let $\Xi_{r;n,\epsilon}$ be the set of 01-tuples $\lambda=(\lambda_i)_{i\in I_r^+}$ such that
\begin{align}
\left| \left\{ \, i \in I_r^+ \, \middle| \, \lambda_i\neq \epsilon \, \right\} \right| = n.
\end{align}
\noindent This set indexes the monomial basis of $\bigwedge^{n,\epsilon} V_r$: if $\lambda\in \Xi_{r;n,\epsilon}$ and $i_1>\cdots >i_n$ with ${\lambda_{i_1},\ldots,\lambda_{i_n}\neq \epsilon}$ then set
\begin{align} \label{eq:vlam}
v_\lambda:=\begin{cases}
v_{i_1}\wedge \cdots \wedge v_{i_n} & \text{if } \epsilon=0 \\
w_{i_n}\wedge \cdots \wedge w_{i_1} & \text{if } \epsilon=1.
\end{cases}
\end{align}
\noindent The weight of $v_\lambda$ is
\begin{align}
\left| \lambda\right| := \sum_{\substack{i\in I_r^+ \\ \lambda_i\neq \epsilon}} (-1)^{\epsilon} \varepsilon_i\in P_r.
\end{align}
\noindent We wish to consider spaces of semi-infinite wedges. We will construct these as direct limits of the modules above. For $r<s<\infty$ there is an $\mathfrak{sl}_{I_r}$-module embedding ${\bigwedge\nolimits^{r,\epsilon} V_r\hookrightarrow \bigwedge\nolimits^{s,\epsilon} V_s}$ given by linearly extending the assignment
\begin{align} \label{wedgemap}
v_\lambda\longmapsto\begin{cases}
v_\lambda\wedge v_{-r}\wedge v_{-r-1}\wedge\cdots \wedge v_{1-s} & \text{ if } \epsilon=0 \\
v_\lambda\wedge w_{r+1}\wedge w_{r+2}\wedge \cdots \wedge w_s & \text{ if } \epsilon=1.
\end{cases}
\end{align}
\noindent The corresponding embedding $\Xi_{r;r,\epsilon}\hookrightarrow \Xi_{s;s,\epsilon}$ is given by extending a 01-tuple ${\lambda=\left(\lambda_j\right)_{j\in I_r^+}}$ by setting
\begin{align}\label{indexsetwedgemap}
\lambda_j =
\begin{cases}
0 & \text{ if } r<j\leq s \\
1 & \text{ if } 1-s\leq j<1-r.
\end{cases}
\end{align}
\noindent Let $\Xi_{\infty,\epsilon}:=\displaystyle{\lim_{\longrightarrow}} \, \Xi_{r;r,\epsilon}$ and let $\bigwedge\nolimits^{\infty,\epsilon} V:= \displaystyle{\longrightarrow}\textstyle \, \bigwedge\nolimits^{r,\epsilon} V_r$, an $\mathfrak{sl}_\mathbb{Z}$-module. Then $\Xi_{\infty,\epsilon}$ parameterizes the natural monomial basis of $\bigwedge\nolimits^{\infty,\epsilon} V$, the union of the monomial bases of the $\bigwedge\nolimits^{r,\epsilon} V_r$. It is natural to think of an element $\lambda\in\Xi_{\infty,\epsilon}$ as a 01-tuple $\lambda=\left(\lambda_i\right)_{i\in \mathbb{Z}}$ and of the corresponding element $v_\lambda\in\bigwedge\nolimits^{\infty,\epsilon} V$ as a semi-infinite wedge.
\vspace{10pt}
\begin{center}
\framebox(350,40){\emph{Once and for all fix $l\in\mathbb{N}$, $n_1,\ldots, n_l\in \mathbb{N}$, and $c_1,\ldots, c_l\in \left\{ \, 0,1\right\}$.}}
\end{center}
\vspace{10pt}
We will generally suppress dependence on this data in our notation. For $r\in\mathbb{N}\cup\{\infty\}$ and $\epsilon\in\left\{0,1\right\}$ write $\underline{r}=\left(n_1,\ldots, n_l, r\right)$ and $\underline{\epsilon}=\left(c_1,\ldots, c_l,\epsilon\right)$. Our main objects of study will be modules of the form
\begin{align}
\bigwedge\nolimits^{\underline{r},\underline{\epsilon}} V_r:= \bigwedge\nolimits^{n_1,c_1} V_r \otimes\cdots\otimes \bigwedge\nolimits^{n_l,c_l} V_r\otimes \bigwedge\nolimits^{r,\epsilon} V_r.
\end{align}
\noindent This has a monomial basis indexed by the set
\begin{align}
\Xi_{\underline{r},\underline{\epsilon}}:=\Xi_{r;n_1,c_1}\times \cdots\times\Xi_{r;n_l,c_l}\times\Xi_{r;r,\epsilon},
\end{align}
\noindent where for $\lambda=\left(\lambda^i\right)_{1\leq i\leq l+1}\in\Xi_{\underline{r},\underline{\epsilon}}$ we set
\begin{align}
v_{\lambda}:= v_{\lambda^1}\otimes \cdots \otimes v_{\lambda^{l+1}}.
\end{align}
\noindent It will sometimes be convenient to think of $\lambda$ as a 01-matrix $\lambda=(\lambda^i_j)_{1\leq i\leq l+1,j\in I_r^+}$ whose $i^\text{th}$ row is $\lambda^i$.
For $r<\infty$ and $\lambda\in\Xi_{\underline{r},\underline{\epsilon}}$, $v_\lambda$ has weight
\begin{align}
| \lambda | = | \lambda^1 | + \cdots + | \lambda^l |\in P_r
\end{align}
\noindent Define a poset structure on $\Xi_{\underline{r},\underline{\epsilon}}$ by declaring that if $\lambda,\mu\in \Xi_{\underline{r},\underline{\epsilon}}$ then $\lambda\leq \mu$ iff $| \lambda | = | \mu |$ and $| \lambda^1 | + \cdots + | \lambda^i | \geq | \mu^1 | + \cdots + | \mu^i |$ for each $1\leq i\leq l+1$.
For $r<s<\infty$ there are maps $\bigwedge\nolimits^{\underline{r},\underline{\epsilon}}V_r\hookrightarrow\bigwedge\nolimits^{\underline{s},\underline{\epsilon}}V_s$ induced by inclusion on the first $l$ factors and (\ref{wedgemap}) on the last. There is a corresponding map $\Xi_{\underline{r},\underline{\epsilon}}\hookrightarrow\Xi_{\underline{s},\underline{\epsilon}}$ given by setting `new' $\lambda^i_{j}$ equal to $c_i$ if $1\leq i\leq l$ and by (\ref{indexsetwedgemap}) on the last factor. So we have
\begin{align}\label{directlimit}
\bigwedge\nolimits^{\underline{\infty},\underline{\epsilon}}V= \lim_{\longrightarrow} \, \bigwedge\nolimits^{\underline{r},\underline{\epsilon}} V_r, \qquad \qquad \Xi_{\underline{\infty},\underline{\epsilon}}=\lim_{\longrightarrow} \, \Xi_{\underline{r},\underline{\epsilon}}.
\end{align}
\noindent We will freely identify elements of $\Xi_{\underline{r},\underline{\epsilon}}$ with their image in $\Xi_{\underline{\infty},\underline{\epsilon}}$ and write ${\Xi_{\underline{\infty},\underline{\epsilon}}=\bigcup_{r=1}^\infty \Xi_{\underline{r},\underline{\epsilon}}}$. Similarly we will consider the $\bigwedge\nolimits^{\underline{r},\underline{\epsilon}} V_r$ as $\mathfrak{sl}_{I_r}$-submodules of $\bigwedge\nolimits^{\underline{\infty},\underline{\epsilon}} V$.
The maps (\ref{directlimit}) are order preserving so there is an induced partial order on $\Xi_{\underline{\infty},\underline{\epsilon}}$.
\begin{wts}\label{wts}
The maps (\ref{directlimit}) are order preserving but they are \emph{not} weight preserving. If $\lambda\in \Xi_{\underline{r},\underline{\epsilon}}\subseteq \Xi_{\underline{\infty},\underline{\epsilon}}$ we will write $\lvert \lambda \rvert_s~(s\geq r)$ to denote the weight of $v_\lambda$ when considering $\lambda$ as an element of $\Xi_{\underline{s},\underline{\epsilon}}$.
\end{wts}
\begin{rmk:wedgenotationcomp}
Most of our notations match those of \cite[\S2.2]{BLW13}. The only notable differences are that our $V_r$ and $W_r$ correspond to $V_{I_r}$ and $W_{I_r}$ in \emph{loc. cit.} and, when $r<\infty$, our $\Xi_{r;n,\epsilon}$ and $\Xi_{\underline{r},\underline{\epsilon}}$ correspond to their $\Lambda_{I_r;n,\epsilon}$ and $\Lambda_{I_r;\underline{r},\underline{\epsilon}}$ respectively. They do not consider semi-infinite wedges so don't have notation for these indexing sets when $r=\infty$.
\end{rmk:wedgenotationcomp}
\noindent The following straightforward proposition is the basis for super-duality.
\begin{combinatorialsuperduality}\label{combinatorialsuperduality}
We have equality of posets $\Xi_{\underline{\infty},\underline{0}}=\Xi_{\underline{\infty},\underline{1}}$ and this induces an $\mathfrak{sl}_{\mathbb{Z}}$-module isomorphism
%
\begin{align}
\begin{split}
\bigwedge\nolimits^{\underline{\infty}, \underline{0}} V & \longrightarrow\bigwedge\nolimits^{\underline{\infty}, \underline{1}} V \\
v_{\lambda} & \longmapsto v_{\lambda}
\end{split}
\end{align}
\end{combinatorialsuperduality}
\section{Tensor product categorifications}\label{section:uniquenessofTPCs}
\subsection{Recollection of definitions}
We recall some important definitions. See \cite[\S2.3-2.6]{BLW13} for more details.
\begin{HeckeDef}
The (degenerate) \emph{affine Hecke algebra} $AH_k$ is the $\mathbb{C}$-algebra with generators $x_1,\ldots, x_k, t_1,\ldots t_{k-1}$ such that $x_1,\ldots, x_k$ generate a polynomial algebra $\mathbb{C}\left[ x_1,\ldots,x_k\right]$, $t_1,\ldots ,t_{k-1}$ generate a copy of the symmetric group $S_k$ with $t_j$ corresponding to the transposition $(j~j+1)$, and
%
\begin{align}
t_ix_j-x_{t_i(j)}t_i=
\begin{cases}
1 & \text{if } j=i+1\\
-1 & \text{if }j=i \\
0 & \text{otherwise}
\end{cases}
\end{align}
\noindent For $\omega\in P_r^+$, the \emph{cyclotomic affine Hecke algebra} $AH_k^{\omega}$ is the quotient of $AH_k$ by the two-sided ideal generated by $\prod_{i\in I_r}(x_1-i)^{\omega\cdot\alpha_i}$.
\end{HeckeDef}
The image of $\mathbb{C}\left[ x_1,\ldots, x_k\right]$ in $AH_k^{\varpi}$ is a finite-dimensional commutative algebra, so it contains mutually orthogonal idempotents $\left\{ \, 1_{\boldsymbol{i}} \, \middle| \, \boldsymbol{i}\in\mathbb{C}^k \, \right\}$ such that $1_{\boldsymbol{i}}$ acts on any finite-dimensional $AH_k^{\varpi}$-module M as projection onto
\begin{align}
M_{\boldsymbol{i}} = \left\{ \, v\in M \, \middle| \, (x_j-i_j)^Nv=0 \text{ for } 1\leq j\leq k \text{ and } N\gg 0 \, \right\}.
\end{align}
\noindent Define
\begin{align}
AH_{r,k}^{\varpi}:=\bigoplus_{\boldsymbol{i},\boldsymbol{j}\in I_r^k} 1_{\boldsymbol{i}}AH_k^{\varpi} 1_{\boldsymbol{j}}=AH_k^{\varpi}\left.\middle/\right.\langle \, 1_{\boldsymbol{i}} \, | \, \boldsymbol{i}\notin I_r^k \, \rangle.
\end{align}
\begin{QHA}
For consistency we will phrase all categorical actions in this paper in terms of (cyclotomic) affine Hecke algebras, but they could equally be phrased using appropriate (cyclotomic) quiver Hecke algebras (also known as KLR algebras \cite{KL09}, \cite{Rou08}) as described in \cite[Sections 2.3 and 2.4]{BLW13}.
\end{QHA}
\begin{CategoricalAction}
Let $\mathcal{C}$ be a Schurian category with an endofunctor $F\in\text{End}\left(\mathcal{C}\right)$, a right adjoint $E$ to $F$ (with a fixed adjunction), and natural transformations $x\in\text{End}\left(F\right)$ and $t\in\text{End}\left(F^2\right)$. Via the adjunction there are induced natural transformations $x\in\text{End}\left(E\right)$ and $t\in\text{End}\left(E^2\right)$. For $i\in I_r$ let $F_i$ (resp.\;$E_i$) be the endofunctor of $\mathcal{C}$ defined by setting $F_iM$ (resp.\;$E_iM$) equal to the generalized $i$-eigenspace of $x$ on $FM$ (resp.\;$EM$). We say this data defines a \emph{categorical $\mathfrak{sl}_{I_r}$-action} on $\mathcal{C}$ if:
%
\begin{enumerate}[leftmargin=*, align=left, label=(CA\arabic{*}), ref=(CA\arabic{*})]
\item \label{CA1} $F$ decomposes as a direct sum $F=\bigoplus_{i\in I_r}F_i$;
\item \label{CA2} The endomorphisms $x_j:=F^{k-j}xF^{j-1}$ and $t_j:=F^{k-j-1}tF^{j-1}$ of $F^k$ satisfy the relations of the affine Hecke algebra $AH_k$ for all $k\geq 0$;
\item \label{CA3} $F$ is isomorphic to a right adjoint of $E$;
\item \label{CA4} The endomorphisms $f_i$ and $e_i$ of $\left[ \mathcal{C}\right]$ induced by $E_i$ and $F_i$ make it into an integrable $\mathfrak{sl}_{I_r}$-module such that the classes of indecomposable projectives are weight vectors.
\end{enumerate}
\end{CategoricalAction}
As a consequence of these axioms, $E=\bigoplus_{i\in I_r} E_i$ and $E_i$ and $F_i$ are biadjoint for all $i\in I_r$. The data of a categorical $\mf{sl}_{I_r}$-action on $\mc{C}$ implies an action of the associated Kac-Moody 2-category as defined by \cite{Rou08}, \cite{KL10}, and \cite{CL16} (these definitions were shown to be equivalent in \cite{Bru16}).
Recall the definition of a (Schurian) highest weight category $\mathcal{C}$ in the sense of \cite{CPS88}. As in \cite[Definition 2.8]{BLW13} we allow the associated poset $(\Xi, \leq)$ to be infinite as long as it is interval-finite: for $\lambda,\mu\in\Xi$ the set $\left\{ \, \nu\in\Xi \, \middle| \, \lambda\leq\nu\leq\mu \, \right\}$ is finite. We write $L$, $\Delta$, and $P$ for the irreducibles, standards, and projectives in $\mathcal{C}$ respectively. Let $\mathcal{C}^{\Delta}$ be the full subcategory of $\mathcal{C}$ consisting of objects with a $\Delta$-flag and let $\left[\mc{C}^{\Delta}\right]$ denote its complexified Grothendieck group.
\begin{TPCdef}
Take $r\in\mathbb{N}\cup\{\infty\}$ and $\epsilon\in\{0,1\}$. An \emph{$\mathfrak{sl}_{I_r}$-tensor product categorification} (TPC) of type $(\underline{r},\underline{\epsilon})$ is a Schurian highest weight category with poset $\Xi_{\underline{r},\underline{\epsilon}}$ and a categorical $\mathfrak{sl}_{I_r}$-action such that
%
\begin{enumerate}[leftmargin=*, align=left, label=(TPC\arabic{*}), ref=(TPC\arabic{*})]
\item \label{TPC1} $F_i$ and $E_i$ restrict to endofunctors of $\mathcal{C}^{\Delta}$;
\item \label{TPC2} There is a linear isomorphism
%
\begin{align}
\begin{split}
\left[ \mathcal{C}^{\Delta}\right] & \longrightarrow \bigwedge\nolimits^{\underline{r},\underline{\epsilon}} V_r, \\
\left[ \Delta(\lambda)\right] & \longmapsto v_\lambda
\end{split}
\end{align}
intertwining the endomorphisms induced by $E_i$ and $F_i$ and the Chevalley generators $e_i,f_i\in\mathfrak{sl}_{I_r}$.
\end{enumerate}
\end{TPCdef}
\noindent As $\left[\mc{C}\right]\hookrightarrow\left[\mc{C}^{\Delta}\right]$, the axiom \ref{CA4} is actually a consequence of \ref{TPC2}.
The following proposition immediately follows from the definitions and Proposition \ref{combinatorialsuperduality}.
\begin{TPCsuperduality}\label{prop:TPCsuperduality}
Every $\mathfrak{sl}_{\mathbb{Z}}$-TPC of type $(\underline{\infty},\underline{0})$ is also a TPC of type $(\underline{\infty},\underline{1})$ and vice-versa.
\end{TPCsuperduality}
\subsection{Strategy for uniqueness} \label{section:uniqueintro}
The rest of this section will be dedicated to proving the following theorem (see \cite{LW13} or \cite{BLW13} for the definition of a strongly equivariant equivalence):
\begin{uniquenessofTPCs}\label{thm:uniquenessofTPCs}
Suppose that $\mathcal{C}$ and $\mathcal{C'}$ are $\mathfrak{sl}_{I_r}$-TPCs of type $(\underline{r},\underline{\epsilon})$. Then there is a strongly equivariant equivalence $\mathbb{G}:\mathcal{C}\to\mathcal{C'}$ with $\mathbb{G}L(\lambda)=L'(\lambda)$ for all $\lambda\in\Xi_{\underline{r},\underline{\epsilon}}$.
\end{uniquenessofTPCs}
For $r<\infty$ this is a special case of the main result in \cite{LW13} so we will only actually provide a proof for the case $r=\infty$.
To establish the theorem, it suffices to show that for a given type $(\underline{r},\underline{\epsilon})$ there exists a Schurian category $\mathcal{D}$ with a categorical $\mathfrak{sl}_{I_r}$-action such that for any $\mathfrak{sl}_{I_r}$-TPC $\mathcal{C}$ of type $(\underline{r},\underline{\epsilon})$ there is an exact functor $\mathbb{U}:\mathcal{C} \to \mathcal{D}$ satisfying the following:
\begin{enumerate}[label=(U\arabic{*}), ref=(U\arabic{*})]
\item \label{U1} $\mathbb{U}$ is strongly equivariant;
\item \label{U2} $\mathbb{U}$ is fully faithful on projectives;
\item \label{U3} for each $\lambda\in \Xi_{\underline{r},\underline{\epsilon}}$, $Y(\lambda):= \mathbb{U} P(\lambda)$ is independent (up to isomorphism) of the choice of $\mathcal{C}$.
\end{enumerate}
\noindent See \cite[\S2.7]{BLW13} for an explanation of why this is sufficient.
For the rest of Section \ref{section:uniquenessofTPCs} we fix an $\mathfrak{sl}_{\mathbb{Z}}$-TPC $\mc{C}$ of type $(\underline{\infty}, \underline{\epsilon})$. In \S \ref{subsection:truncation} below we define a subquotient $\mathcal{C}_r$ of $\mathcal{C}$ that is an $\mathfrak{sl}_{I_r}$-TPC of type $(\underline{r},\underline{\epsilon})$ and construct the corresponding functors $\mathbb{U}_r$ satisfying \ref{U1}-\ref{U3}. Then in \S \ref{subsection:stablemods} we construct a functor $\mathbb{U}$ from $\mathcal{C}$ to a category of `stable modules' using the functors $\mathbb{U}_r$ and show that $\mathbb{U}$ satisfies \ref{U1}-\ref{U3}, thus establishing the theorem. Our proof of Theorem \ref{thm:uniquenessofTPCs} for $r=\infty$ closely follows the argument in \cite[Section 4]{BLW13}. The reader is referred there for many of the proofs in this section as they pass over with minimal change. Our $\Xi_{\underline{r},\underline{\epsilon}}$ corresponds to $\Lambda_r$ in their notation and we have $I=\mathbb{Z}$.
\subsection{Reduction to finite intervals}\label{subsection:truncation}
Let $r_0:=\max\left\{n_1,\ldots, n_l\right\}$ and take $r$ such that $r_0\leq r<\infty$. Define subsets $\Xi^{\leq}_{\underline{r},\underline{\epsilon}}$ and $\Xi^<_{\underline{r},\underline{\epsilon}}$ of $\Xi_{\underline{\infty},\underline{\epsilon}}$ as follows. Take $\lambda\in \Xi_{\underline{\infty},\underline{\epsilon}}$ and choose $s\geq r$ such that $\lambda\in \Xi_{\underline{s},\underline{\epsilon}}$. Then $\lambda\in \Xi^\leq_{\underline{r},\underline{\epsilon}}$ if it satisfies the following conditions:
\begin{empheq}[left=\empheqlbrace]{align}
\begin{split}
\sum_{i=1}^k \sum_{\substack{j\in I_s \\ j\leq h \\ \lambda^i_{j}\neq c_i}} (-1)^{c_i} \geq 0 & \text{ for all } h< \min (I_r^+) \text{ and } 1\leq k\leq l+1 \\
\sum_{i=1}^k \sum_{\substack{j\in I_s \\ j\geq h \\ \lambda^i_{j}\neq c_i}} (-1)^{c_i} \leq 0 & \text{ for all } h> \max (I_r^+) \text{ and } 1\leq k\leq l+1
\end{split}
\end{empheq}
\noindent (we write $\epsilon$ as $c_{l+1}$ for convenience) and $\lambda\in \Xi^<_{\underline{r},\underline{\epsilon}}$ if at least one of the above inequalities is strict. This definition is independent of the choice of $s$. These are ideals of $\Xi_{\underline{\infty},\underline{\epsilon}}$ and $\Xi_{\underline{r},\underline{\epsilon}}=\Xi^{\leq}_{\underline{r},\underline{\epsilon}}\setminus\Xi^<_{\underline{r},\underline{\epsilon}}$. Moreover the vector subspaces of $\bigwedge\nolimits^{\underline{\infty}, \underline{\epsilon}} V$ spanned by the corresponding $v_{\lambda}$ are $\mathfrak{sl}_{I_r}$-submodules.
Let $\mathcal{C}_{\leq r}$ (resp. $\mathcal{C}_{<r}$) be the Serre subcategory of $\mathcal{C}$ generated by those $L(\lambda)$ with $\lambda\in\Xi^{\leq}_{\underline{r},\underline{\epsilon}}$ (resp. $\Xi^<_{\underline{r},\underline{\epsilon}}$) and let $\mathcal{C}_r$ be the Serre quotient category
\begin{align}
\mathcal{C}_r=\mathcal{C}_{\leq r}\left.\middle/\right.\mathcal{C}_{<r}.
\end{align}
\noindent All three of these are highest weight categories. The functors $F_i$ and $E_i$ with $i\in I_r$ preserve the subcategories $\mathcal{C}_{\leq r}$ and $\mathcal{C}_{<r}$ and thus they have induced actions on $\mathcal{C}_r$. The following proposition is easily established by checking the necessary axioms:
\begin{trunc}
The category $\mathcal{C}_r$ is an $\mathfrak{sl}_{I_r}$-tensor product categorification of type $(\underline{r},\underline{\epsilon})$ under the induced action of $F_{I_r}:=\bigoplus_{i\in I_r} F_i$, together with the restrictions of $x$ and $t$ to $F_{I_r}$ and $F_{I_r}^2$ respectively.
\end{trunc}
Define an equivalence relation `$\sim$' on $\Xi_{\underline{\infty},\underline{\epsilon}}$ as follows. Take $\lambda,\mu \in\Xi_{\underline{\infty},\underline{\epsilon}}$. Take $r<\infty$ such that $\lambda,\mu\in\Xi_{\underline{r},\underline{\epsilon}}$ and write $\lambda\sim \mu$ if $\lvert \lambda\rvert_r=\lvert\mu\rvert_r$ (see Remark~\ref{wts}). This definition is independent of the choice of $r$. For $\lambda\in \Xi_{\underline{\infty},\underline{\epsilon}}$, let $\mathcal{C}_{[\lambda]}$ be the Serre subcategory of $\mathcal{C}$ generated by those $L(\mu)$ with $\mu\sim \lambda$. Then we can decompose
\begin{align} \label{eq:blocks}
\mathcal{C}=\bigoplus_{[\lambda]\in \Xi_{\underline{\infty},\underline{\epsilon}}/\sim} \mathcal{C}_{[\lambda]}
\end{align}
\noindent If $r_0\leq r <\infty$ then $\Xi_{\underline{r},\underline{\epsilon}}$ has a unique maximal element $\kappa_r$. It is the 01-matrix with the 1s in each row as far left as possible. The corresponding vector $v_{\kappa_r}$ is the highest weight vector in $\bigwedge^{\underline{r}, \underline{\epsilon}} V_r$.
\begin{prinj} \label{Lem2.20}
$L(\kappa_r)\in\mathcal{C}$ is both projective and injective.
\end{prinj}
\begin{proof}
This follows from the proof of \cite[Lemma~2.20]{BLW13}, using (\ref{eq:blocks}) above in place of \cite[(2.16)]{BLW13}.
\end{proof}
\noindent For $r_0\leq r<\infty$, define $T_r:=\bigoplus_{k\geq 0}F^k_{I_r}L(\kappa_r)$ and $H_r:=\bigoplus_{k\geq 0} AH^{\lvert \kappa_r\rvert}_{r,k}$.
\begin{hecketensor}\cite[Theorem~4.1]{BLW13}
The action of the affine Hecke algebras on $T_r$ induces a canonical algebra isomorphism $H_r\cong \text{End}_\mathcal{C}(T_r)$.
\end{hecketensor}
\noindent In particular, considering $T_r$ as a left $H_r$-module we can define a functor:
\begin{align}
\mathbb{U}_r:=\text{Hom}_\mathcal{C}(T_r,-):\mathcal{C}\longrightarrow \text{mod-}H_r
\end{align}
\noindent By Lemma \ref{Lem2.20}, $T_r$ is both projective and injective and so $\mathbb{U}_r$ is exact. In the finite interval case, mod-$H_r$ fills the role of the category $\mathcal{D}$ mentioned in Section \ref{section:uniqueintro}; that is, there exists a categorical $\mathfrak{sl}_{I_r}$-action on mod-$H_r$ such that the functor $\mathcal{C}_r\to \text{mod-}H_r$ induced by $\mathbb{U}_r$ satisfies (U1)-(U3) (see \cite[Theorem~2.14 and Lemma~2.16]{BLW13}).
\subsection{Stable modules}\label{subsection:stablemods}
Take $r_0\leq r<\infty$. Then there exist $a\geq 0$, $p_1,\ldots,p_a\in \mathbb{N}$, and $s_1,\ldots,s_a\in I_r$ such that
\begin{align} \label{eq:hwvs}
f^{(p_1)}_{s_1} f^{(p_2)}_{s_2} \cdots f^{(p_a)}_{s_a} v_{\kappa_{r+1}}=v_{\kappa_r}
\end{align}
\noindent in $\bigwedge^{\underline{\infty}, \underline{\epsilon}} V$. Let $p=p_1+\cdots +p_a$. For $i\in \mathbb{Z}$ and $m\geq 1$, let $F^{(m)}_i$ denote the summand of $F^m_i$ that induces $f^{(m)}_i$ on the level of the Grothendieck group.
\begin{Lem4.2}\label{Lem4.2}
There is an algebra embedding $\phi_r:H_r\to H_{r+1}$, independent of the choice of $\mathcal{C}$, such that $e_r:=\phi_r\left(1_{H_r}\right)$ acts as projection
%
\begin{align}
F^p_{I_{r+1}} L(\kappa_{r+1})\to F^{(p_1)}_{s_1} F^{(p_2)}_{s_2} \cdots F^{(p_a)}_{s_a} L(\kappa_{r+1})\cong L(\kappa_r)
\end{align}
\noindent in $\mc{C}$. Moreover there is an isomorphism $\theta_r:T_r\isoto e_r T_{r+1}$ intertwining the action of $H_r$ on $T_r$ with its action on $T_{r+1}$ via $\phi_r:H_r\isoto e_r H_re_r\subseteq H_{r+1}$.
\end{Lem4.2}
\begin{proof}
The assumption $r\geq r_0$ ensures that an identity of the form (\ref{eq:hwvs}) holds. With this, the proof is the same as that of \cite[Lemma 4.2]{BLW13}.
\end{proof}
\begin{Lem4.2rmk}
It is more natural to think of the above map in terms of the diagrammatics of the quiver Hecke algebra as in \cite[Section 4.1]{BLW13}. With this perspective, the map between cyclotomic quotients is induced by tensoring on the left with the diagram that gives projection $F^p_{I_{r+1}} \to F^{(p_1)}_{s_1} F^{(p_2)}_{s_2} \cdots F^{(p_a)}_{s_a}$ in the categorification of the half quantum group $\mc{U}_q^-\mf{sl}_{I_{r+1}}$. This diagram can be given explicitly, see for example \cite[Lemma~4.1]{Rou08}.
\end{Lem4.2rmk}
Since $\phi_r:H_r\isoto e_rH_{r+1}e_r$, we can induct and restrict modules between the $H_r$ for varying $r$. Given a right (resp. left) $H_{r+1}$-module $M$, we consider $Me_r$ (resp. $e_rM$) as a right (resp. left) $H_r$-module via $\phi_r$. For $M\in \text{mod-}H_r$ and $N\in \text{mod-}H_{r+1}$, define
\begin{align}
\begin{gathered}
\text{Ind}_r^{r+1} M:=M\otimes_{H_r} e_r H_{r+1}\in \text{mod-}H_{r+1}\\
\text{Res}^{r+1}_r N:=Ne_r\in \text{mod-}H_r
\end{gathered}
\end{align}
\noindent More generally, we define functors
\begin{align}
\begin{split}
\text{Ind}_r^s & :=\text{Ind}_{s-1}^s \circ\cdots\circ \text{Ind}_r^{r+1} \\
\text{Res}_r^s & :=\text{Res}_r^{r+1}\circ\cdots\circ \text{Res}_{s-1}^s
\end{split}
\end{align}
\noindent for any $s>r$.
\begin{hinfty}
Let mod-$H_{\infty}$ be the category with objects sequences ${M=(M_r, \iota_r)_{r\geq r_0}}$ such that $M_r\in \text{mod-}H_r$ and
%
\begin{equation}
\iota_r:M_r\longrightarrow \text{Res}^{r+1}_r M_{r+1}\subseteq M_{r+1}
\end{equation}
\noindent is an $H_r$-module isomorphism for each $r$. A morphism $f:M\to N$ in mod-$H_{\infty}$ is a sequence $f=(f_r)_{r\geq r_0}$ with $f_r\in \text{Hom}_{H_r}(M_r,N_r)$ such that the following diagram commutes for all $r\geq r_0$:
\begin{equation}
\begin{tikzcd}
M_r \ar[d, "f_r"'] \ar[r, "\iota_r"] & M_{r+1} \ar[d, "f_{r+1}"] \\
N_r \ar[r, "\iota_r"] & N_{r+1}
\end{tikzcd}
\end{equation}
\end{hinfty}
For $r\geq r_0$, define a functor $\text{st}_r: \text{mod-}H_r\to \text{mod-}H_\infty$ by setting $\text{st}_r(M)=(M_s,\iota_s)_{s\geq r_0}$ where
\begin{align}
M_s:=\begin{cases}
\text{Ind}_r^s M & \text{if } s>r \\
M & \text{if } s=r \\
\text{Res}^r_s M & \text{if } r_0\leq s<r.
\end{cases}
\end{align}
\noindent For $r_0\leq s<r$, $M_s=\text{Res}^{s+1}_s M_{s+1}$ so we can take $\iota_s=1_{M_s}$, and for $s\geq r$, $\iota_s$ is defined via the obvious natural isomorphism $1\isoto \text{Res}^{s+1}_s \text{Ind}^{s+1}_s$.
The functor $\text{st}_r$ corresponds to $\text{pr}_r^!$ in \cite[\S4.2]{BLW13}.
\begin{stable}
An object in mod-$H_\infty$ is \emph{$r$-stable} if it is in the essential image of $\text{st}_r$. It is \emph{stable} if it is $r$-stable for some $r\geq r_0$. Let mod-$H$ denote the full subcategory of mod-$H_\infty$ consisting of stable modules.
\end{stable}
Recall the functors $\mathbb{U}_r$ from \S \ref{subsection:truncation}. Define a functor
\begin{align}
\begin{split}
\mathbb{U}:\mathcal{C} & \longrightarrow \text{mod-}H_\infty \\
M & \longmapsto(\mathbb{U}_r M,\iota_r)_{r\geq r_0}
\end{split}
\end{align}
\noindent where
\begin{align}
\begin{split}
\iota_r:\text{Hom}_{H_r}(T_r,M) & \longisoto \text{Hom}_{H_{r+1}}(e_r T_{r+1},M) \\
\phi & \longmapsto \phi\circ (\theta_r)_{-1}
\end{split}
\end{align}
\noindent It is defined on morphisms by setting $\mathbb{U}f=(\mathbb{U}_rf)_{r\geq r_0}$.
\begin{Uprop} \label{thm:Uprop}
The category mod-$H$ is Schurian and $\mathbb{U}M\in \text{mod-}H$ for every $M\in\mathcal{C}$. Moreover, there exists a categorical $\mathfrak{sl}_\mathbb{Z}$-action on mod-$H$ such that $\mathbb{U}$ satisfies (U1)-(U3).
\end{Uprop}
\begin{proof}
The analogous results in \cite{BLW13} comprise Theorems 4.7, 4.9, and 4.10, and \S4.3. The proof is formally identical: our Lemma \ref{Lem2.20} takes the place of \cite[Lemma~2.20]{BLW13} , our Lemma \ref{Lem4.2} takes the place of \cite[Lemma~4.2]{BLW13}, and \cite[Theorem~2.24]{BLW13} and its proof go through unchanged.
\end{proof}
\noindent By the discussion in \S \ref{section:uniqueintro} we have established Theorem \ref{thm:uniquenessofTPCs}.
\begin{rmk:prinjectives}
As mentioned in the proof above, \cite[Theorem~2.24]{BLW13} holds in our setting. This gives a classification of projective-injective objects in $\mc{C}$. Together with Theorem~\ref{infranktpc} this yields a classification on projective-injective modules in the infinite-rank categories $\mathcal{O}^{++}_{\epsilon}$ described in the next section.
\end{rmk:prinjectives}
\section{Categories $\mathcal{O}$}\label{section:catO}
Fix $\epsilon\in\{0,1\}$. The aim of this section is to show that a certain infinite-rank limit $\mathcal{O}_{\epsilon}^{++}$ of parabolic BGG categories of general linear Lie superalgebras is an $\mf{sl}_{\mathbb{Z}}$-tensor product categorification of type $(\underline{\infty}, \underline{\epsilon})$. In \S\ref{subsec:Set-up} we set up the necessary notation and define the category $\mathcal{O}^{++}_{\epsilon}$. In \S\ref{subsec:HWC} we show that it has enough projectives and conclude that it is a highest weight category. Finally in \S\ref{subsec:cataction} we describe the actions of $E$ and $F$ on $\mathcal{O}^{++}_{\epsilon}$ and show that it is an $\mf{sl}_{\mathbb{Z}}$-TPC. This yields the super duality equivalence $\mathcal{O}^{++}_0\cong\mathcal{O}^{++}_1$.
Since $\epsilon$ will be fixed until the discussion of super duality at the end of this section, we will write $\mathcal{O}^{++}$ for $\mathcal{O}^{++}_{\epsilon}$ up to that point. Our constructions also depend on the sequences $n_1,\ldots, n_l\in\mathbb{N}$ and $c_1,\ldots,c_l\in\left\{0,1\right\}$ which we fixed in Section \ref{sec:intro}. For cleanness we will always drop reference to these from our notation.
\subsection{Set up}\label{subsec:Set-up}
Let $m=\sum_{c_i=1} n_i$ and $n=\sum_{c_i=0} n_i$. For notational convenience we will sometimes write $n_{l+1}=r$ and $c_{l+1}=\epsilon$.
For $1\leq j\leq m+n+r$, define $p_j=c_i\in \{0,1\}$, where $1\leq i\leq l+1$ is maximal such that ${n_1+\cdots +n_{i-1}<j}$. For $r<\infty$ let $U_r$ be the vector superspace with basis $u_1,\ldots ,u_{m+n+r}$, where $u_j$ has degree $p_j$. Let $u_1^*\ldots,u_{m+n+r}^*\in U_r^*$ be the dual basis. Let $\mathfrak{g}_r:=\mathfrak{gl}(U_r)$ be the Lie superalgebra of endomorphisms of $U_r$ under the supercommutator bracket. Let $U=U_\infty=\bigcup_{r=1}^\infty U_r$ and let $\mathfrak{g}=\mathfrak{g}_\infty= \displaystyle{\lim_{\longrightarrow}} \, \mathfrak{g}_r$ be the Lie superalgebra of endomorphisms of $U$ that vanish on all but finitely many of the $u_j$.
For $r<\infty$, let $\left\{ \, e_{ij} \,\middle|\, 1\leq i,j\leq m+n+r \, \right\}$ be the basis of matrix units for $\mathfrak{g}_r$. Denote by $\mathfrak{b}_r$ the Borel subalgebra of $\mathfrak{g}_r$ consisting of upper triangular matrices. Let $\mathfrak{h}_r$ be the Cartan subalgebra of $\mathfrak{g}_r$ with basis $\left\{ \, e_{ii} \,\middle|\, 1\leq i\leq m+n+r \, \right\}$ and let $\left\{ \delta_i \,\middle|\, 1\leq i\leq m+n+r\right\}\subseteq\mathfrak{h}_r^*$ be the dual basis. Define a bilinear form $\left(-,-\right)$ on $\mathfrak{h}_r^*$ by declaring that
\begin{equation}
\left( \delta_i,\delta_j \right)=\begin{cases}
(-1)^{p_i} & \text{if } i=j \\
0 & \text{otherwise}
\end{cases}
\end{equation}
\noindent Let $\Phi_r=\left\{ \, \delta_i - \delta_j \,\middle|\, 1\leq i,j\leq m+n+r, \, i\neq j \, \right\}$ be the root system for $\mathfrak{g}_r$. A root $\delta_i-\delta_j$ is even if $p_i=p_j$ and is odd otherwise. It is positive (with respect to $\mathfrak{b}_r$) if $i<j$ and is negative otherwise. Let $\Phi_{r, \overline{0}}$, $\Phi_{r, \overline{1}}$, $\Phi_{r}^+$, and $\Phi_r^-$ be the sets of even, odd, positive, and negative roots respectively and decompose $\Phi_r^+=\Phi_{r, \overline{0}}^+\sqcup \Phi_{r, \overline{1}}^+$ and $\Phi_r^-=\Phi_{r, \overline{0}}^-\sqcup \Phi_{r, \overline{1}}^-$ in the obvious way.
For $r<\infty$, define the Weyl vector
\begin{align}
\overline{\rho}_r = \frac{1}{2} \sum_{\alpha\in \Phi_{r, \overline{0}}^+} \alpha - \frac{1}{2} \sum_{\beta\in\Phi_{r, \overline{1}}^+} \beta \in\mathfrak{h}_r^*
\end{align}
\noindent and the normalized version
\begin{align}
\rho_r=\overline{\rho}_r+\left( \frac{n-m+1-(-1)^{\epsilon} r}{2}\right) \sum_{i=1}^{m+n+r} (-1)^{p_i} \delta_i.
\end{align}
\noindent This has the following properties:
\begin{align} \label{weylprop}
\left( \rho_r,\delta_i-\delta_{i+1} \right) &= \begin{cases}
(-1)^{p_i} & \text{if } p_i=p_{i+1} \\
0 & \text{otherwise}
\end{cases}
&&
\left( \rho_r,\delta_{m+n+r} \right) &=\begin{cases}
1-r & \text{if } \epsilon=0 \\
r & \text{if } \epsilon=1
\end{cases}
\end{align}
\noindent and if $r<s$ then $\rho_r$ is the restriction of $\rho_s$ to $\mathfrak{h}_r$.
For $r<\infty$, let
\begin{equation}
X_r=\bigoplus_{j=1}^{m+n+r} \mathbb{Z}\delta_j
\end{equation}
\noindent be the integral weight lattice for $\mathfrak{g}_r$ and define
\begin{equation*}
\begin{gathered}
X_r^+ = \left\{ \, \lambda\in X_r \,\middle|\, (-1)^{p_j}(\lambda+\rho_r,\delta_j-\delta_{j+1})>0 \text{ unless } j=n_1+\cdots+n_i \text{ for some }i \right\} \vspace{.1in},\\
X_r^{++} = \left\{ \lambda\in X_r^+ \,\middle|\, (-1)^{\epsilon}(\lambda,\delta_{m+n+r})\geq 0\right\}.
\end{gathered}
\end{equation*}
\noindent Using the natural embeddings $X_r^{++}\subseteq X_{r+1}^{++}$, define $X^{++}=X_\infty^{++}=\bigcup \, X_r^{++}$.
We will identify these sets with certain indexing sets for wedges from Section \ref{section:combinatorics}. Take $r<\infty$. Take $\lambda\in X_r$ and define a corresponding 01-matrix $( \lambda^i_{j} )_{1\leq i\leq l+1, j\in \mathbb{Z}}$ as follows. Fix $1\leq i\leq l+1$ and let $k=n_1+\cdots +n_{i-1}$. Set
\begin{align}
\lambda^i_{j} = \begin{cases}
1-c_i & \text{for } j= \left( \lambda+\rho_r,\delta_{k+1} \right),\ldots ,\left( \lambda+\rho_r,\delta_{k+n_i} \right) \\
c_i & \text{otherwise}
\end{cases}
\end{align}
\noindent This provides an identification between $X_r^+$ and the indexing set for the basis of the module
\begin{equation}
\bigwedge\nolimits^{n_1,c_1}V\otimes\cdots\bigwedge\nolimits^{n_l,c_l}V\otimes \bigwedge\nolimits^{r,\epsilon}V.
\end{equation}
\noindent We will freely identify these sets and use the inherited partial order on $X_r^+$. For $r<s$, the linear map
\begin{equation}
\text{span}\left\{ \, v_\lambda \,\middle|\, \lambda\in X_r^{++} \, \right\} \longrightarrow \text{span}\left\{ \, v_\lambda \,\middle|\, \lambda\in X_s^{++} \, \right\}
\end{equation}
\noindent induced by the inclusion $X_r^{++}\subseteq X_s^{++}$ coincides with the map induced by the assignment (\ref{wedgemap}) and the direct limit along these maps is $\bigwedge\nolimits^{\underline{\infty}, \underline{\epsilon}} V$. Thus we can identify $X^{++}$ and $\Xi_{\underline{\infty}, \underline{\epsilon}}$. This induces a partial order on $X^{++}$ compatible with the partial orders on the $X_r^{++}$.
\begin{catOfinitewedges}
For finite $r$, the indexing set $\Xi_{\underline{r},\underline{\epsilon}}$ corresponds to \textbf{a proper subset} of $X_r^{++}$. The former indexes tensor products of wedges of $V_r$s and $W_r$s and the latter indexes tensor products of wedges of $V=V_{\infty}$s and $W=W_{\infty}$s with the wedges in the final tensor factor restricted just enough that the assignment (\ref{wedgemap}) is well behaved.
\end{catOfinitewedges}
For $r\leq\infty$, define a Levi subalgebra $\mathfrak{l}_r$ of $\mathfrak{g}_r$ by
\begin{align}
\mathfrak{l}_r=\mathfrak{gl}_{n_1}\oplus \cdots \mathfrak{gl}_{n_l}\oplus \mathfrak{gl}_r
\end{align}
\noindent and let $\mathfrak{p}_r=\mathfrak{l}_r+\mathfrak{b}_r$ be the corresponding parabolic subalgebra. For $\lambda\in X_r^+$ (or $\lambda\in X^{++}$ if $r=\infty$), let $L_r^0(\lambda)$ be the irreducible $\mathfrak{l}_r$-module of highest weight $\lambda$. The corresponding parabolic Verma module is
\begin{align}
\Delta_r(\lambda)=\mathcal{U}\mathfrak{g}_r\otimes_{\mathcal{U}\mathfrak{p}_r} L_r^0(\lambda)
\end{align}
\noindent It has a unique irreducible quotient $L_r(\lambda)$.
For $r<\infty$, let $\mathcal{O}_r$ be the integral BGG category $\mathcal{O}$ for $\mathfrak{g}_r$; the category of finitely-generated, $\mathfrak{h}_r$-semisimple, integral weight $\mathfrak{g}_r$-modules that are locally $\mathfrak{b}_r$-finite. Morphisms are all (not necessarily even) homomorphisms of $\mf{g}_r$-modules. Let $\mathcal{O}_r^+$ be the parabolic subcategory of $\mathcal{O}^+_r$ associated to $\mathfrak{p}_r$; the full subcategory of $\mathcal{O}_r$ consisting of modules that are $\mathfrak{l}_r$-semisimple and locally $\mathfrak{p}_r$-finite. Equivalently, $\mathcal{O}_r^+$ is the Serre subcategory of $\mathcal{O}_r$ generated by the $L_r(\lambda)$ with $\lambda\in X_r^+$. It contains the parabolic Verma modules $\Delta_r(\lambda)$ for $\lambda \in X_r^+$. Let $\mathcal{O}_r^{++}$ be the Serre subcategory of $\mathcal{O}_r^+$ generated by $\left\{ L_r(\lambda) \,\middle|\, \lambda\in X_r^{++} \right\}$. Finally let $\mathcal{O}^{++}=\mathcal{O}_\infty^{++}$ be the category of finitely generated, finite length, $\mathfrak{h}$-semisimple $\mathfrak{g}$-modules that are locally $\mathfrak{p}_r$-finite for each $r<\infty$ and whose composition factors are of the form $L(\lambda)=L_{\infty}(\lambda)$ with $\lambda\in X^{++}$. It is abelian and contains the parabolic Verma modules $\Delta(\lambda)=\Delta_{\infty}(\lambda)$ for $\lambda\in X^{++}$.
\begin{equivcatOs}
The analogous categories in \cite[Definition~3.1]{BLW13} are constructed slightly differently. They add a parity assumption to the weight spaces that ensures all morphisms are even. The different constructions yield equivalent categories, see e.g. \cite[\S~2.5]{CL09}.
\end{equivcatOs}
Take $r\leq \infty$. The supertranspose $x^{\text{st}}$ of a matrix $x=(x_{ij})\in\mf{g}_r$ is the matrix with $(i,j)$-entry $(-1)^{p_i(p_i+p_j)}x_{ji}$. The assignment $x\mapsto x^{\text{st}}$ defines an anti-automorphism of $\mf{g}_r$. If $M\in\mathcal{O}_r$, define its dual by
\begin{equation}
M^{\vee}=\bigoplus_{\lambda\in X_r}M_{\lambda}^*
\end{equation}
\noindent with $\mf{g}_r$-action given by
\begin{equation}
(x\cdot f)(m):=(-1)^{\lvert x\rvert\cdot \lvert f\rvert}f(x^{st}\cdot m),
\end{equation}
\noindent where $x$ and $f$ are homogeneous and $\lvert \, \cdot \, \rvert$ denotes their parity. This defines exact, contravariant, self-equivalences on $\mathcal{O}_r$, $\mathcal{O}_r^+$, and $\mathcal{O}_r^{++}$. The dual Verma module corresponding to $\lambda\in X_r$ is
\begin{equation}
\nabla_r(\lambda):=\Delta_r(\lambda)^{\vee}.
\end{equation}
The following important functors were first introduced in \cite[Definition~3.4]{CWZ06}.
\begin{def:trunc}\cite[Definition 3.1]{CW07}\label{def:trunc}
For $r<s\leq\infty$ and $M=\displaystyle{\bigoplus_{\lambda\in X_s}} M_{\lambda}\in \mathcal{O}_s^{++}$, define
%
\begin{equation}
\text{tr}_r^s(M) = \bigoplus_{\lambda\in X_r} M_\lambda \in \mathcal{O}_r^{++},
\end{equation}
\noindent where we regard $X_r\subseteq X_s$. This defines an exact \emph{truncation functor} $\text{tr}_r^s:\mathcal{O}_s^{++}\to\mathcal{O}_r^{++}$.
\end{def:trunc}
\noindent We will sometimes drop the sub/superscripts when they are clear from context.
\begin{tilt} \label{tilt}
If $r<s\leq \infty$, $\lambda\in X_s^{++}$, and $Y=L,~\Delta$, or $\nabla$, then
%
\begin{align}
\text{tr}_r^s~Y_s(\lambda)=\begin{cases}
Y_r(\lambda) & \text{if } \lambda\in X_r^{++} \\
0 & \text{otherwise.}
\end{cases}
\end{align}
\end{tilt}
\begin{proof}
For $Y=L$ or $\Delta$ this is \cite[Proposition 7.5]{CLW12}. For $Y=\nabla$ this follows from the $Y=\Delta$ case and the observation that duality commutes with truncation.
\end{proof}
Take $M\in \mathcal{O}^{++}$ and $r'\in\mathbb{N}$ such that if $\lambda\in X^{++}$ with ${\left[ M:L(\lambda)\right]\neq 0}$ then $\lambda\in X_r^{++}$. For $r\in\mathbb{N}$, let $M_r:=\text{tr}^{\infty}_r(M)$. The proposition implies that the composition multiplicities of $M_r$ are independent of $r\geq r'$ in the sense that if $\infty\geq s>r\geq r'$ and $\lambda\in X_s^{++}$ then
\begin{equation}\label{eq:multstable}
\left[ M_s:L_s(\lambda)\right] = \begin{cases}
\left[ M_r:L_r(\lambda)\right] & \text{if } \lambda\in X_r^{++} \\
0 & \text{otherwise.}
\end{cases}
\end{equation}
\noindent The following lemma gives a converse to this statement.
\begin{limitinO}\label{limitinO}
Take $r'\in\mathbb{N}$. Suppose we have modules $M_r\in\mathcal{O}_r^{++}$ and injective $\mf{g}_r$-module maps ${f_r:M_r\to\text{tr}^{r+1}_r(M_{r+1})\subseteq M_{r+1}}$ for all $r\geq r'$. Suppose further that the composition multiplicities of the $M_r$ are independent of $r\geq r'$ as above. Then the $f_r$ are isomorphisms and the direct limit $M:=\displaystyle{\lim_{\longrightarrow}}~M_r$ along the maps $f_r$ is a module in $\mathcal{O}^{++}$.
\end{limitinO}
\begin{proof}
By assumption, $M_r$ and $\text{tr}^{r+1}_r(M_{r+1})$ have the same composition multiplicites when $r\geq r'$. This implies $f_r$ is an isomorphism and $f_r^{-1}\circ \text{tr}^{r+1}_r$ sends a composition series of $M_{r+1}$ to a composition series of $M_r$ with the same ordered sequence of weights. Now since taking direct limits is exact and $L(\lambda)=\displaystyle_{\lim_{\longrightarrow}}~L_r(\lambda)$ for any $\lambda\in X^{++}$ by Proposition~\ref{tilt}, $M$ has a finite composition series with the same ordered sequence of weights as $M_r$ for any $r\geq r'$. This implies $M$ is finitely generated. Truncation to $M_r$ shows that $M$ is $\mf{h}$-semisimple and locally $\mf{p}_r$-finite for any $r$. So $M\in\mathcal{O}^{++}$.
\end{proof}
\begin{rmk:deltamultstable}\label{rmk:deltamultstable}
The same conclusion holds if $M_r\in(\mathcal{O}^{++}_r)^{\Delta}$ for all $r\geq r'$ and we replace composition multiplicities with $\Delta$-multiplicities. Moreover, in this situation we can conclude that $M\in(\mathcal{O}^{++})^{\Delta}$.
\end{rmk:deltamultstable}
\subsection{Highest weight structure}\label{subsec:HWC}
\begin{++hwc}
If $r<\infty$ then $\mathcal{O}_r^{++}$ is a highest weight category with weight poset $(X_r^{++}, \leq)$, standard objects $\Delta_r(\lambda)$, and costandard objects $ \nabla(\lambda)$.
\end{++hwc}
\begin{proof}
The parabolic category $\mathcal{O}_r^+$ is a highest weight category with weight poset $(X_r^+, \leq)$ and standard objects $\left\{ \, \Delta_r(\lambda)\, \middle| \,\lambda \in X_r^+ \, \right\}$ (see e.g. \cite[Theorem 3.8]{BLW13}). Since $X_r^{++}$ is an ideal in $X_r^+$ (an easy generalisation of \cite[Lemma 3.4]{CW07}), the proposition follows from the general theory of highest weight categories.
\end{proof}
\begin{projcover}
We will write $P_r(\lambda)$ for the projective cover of $L_r(\lambda)$ in $\mathcal{O}_r^{++}$. This will generally be a proper quotient of the projective cover of $L_r(\lambda)$ in the larger categories $\mathcal{O}_r^{+}$ and $\mc{O}_r$.
\end{projcover}
We wish to extend this to $r=\infty$. Most of the necessary ingredients are already in the literature, it only remains to establish that $\mathcal{O}^{++}$ has enough projectives. Our main tool will be the truncation functors from Definition~\ref{def:trunc}. We will show that these send $P_s(\lambda)$ to $P_r(\lambda)$ for $\lambda\in X^{++}_r$ and use them to construct projective covers in $\mathcal{O}^{++}$ direct limits of the $P_r(\lambda)$ as in Lemma~\ref{limitinO}.
We will need a left adjoints $(\text{tr}_r^s)^!$ to the $\text{tr}_r^s$. Let $i_r^!:\mathcal{O}_r\to\mathcal{O}_r^{++}$ be the functor that sends a module to its largest quotient in $\mathcal{O}_r^{++}$. It is left adjoint to the inclusion $i_r:\mathcal{O}_r^{++}\to\mathcal{O}_r$. Let $\mathfrak{p}_{r,1}$ be the parabolic subalgebra of $\mathfrak{g}_{r+1}$ corresponding to the Levi subalgebra $\mathfrak{g}_{r,1}:=\mathfrak{g}_r+ \mf{h}_{r+1}$. Take $M\in \mathcal{O}_r^{++}$ and trivially extend the $\mf{g}_r$-action on M to an action of $\mf{p}_{r,1}$. Then $\mc{U}\mf{g}_{r+1}\otimes_{\mc{U}\mf{p}_{r,1}} M\in\mc{O}_{r+1}$. Define
\begin{equation}
(\text{tr}_r^{r+1})^!(M)=i_{r+1}^!\left(\mc{U}\mf{g}_{r+1}\otimes_{\mc{U}\mf{p}_{r,1}}M\right).
\end{equation}
\noindent Now set
\begin{equation}
(\text{tr}_r^s)^!=(\text{tr}_{s-1}^r)^!\circ\cdots (\text{tr}_r^{r+1})^!:\mathcal{O}_r^{++}\to\mathcal{O}_s^{++}
\end{equation}
\noindent for $r<s<\infty$.
\begin{tradj}
If $r<s<\infty$ then $(\text{tr}_r^s)^!$ is left adjoint to $\text{tr}_r^s$.
\end{tradj}
\begin{proof}
It suffices to prove this in the case $s=r+1$. Take $M\in\mathcal{O}_r^{++}$ and $N\in\mathcal{O}_{r+1}^{++}$ and take a $\mathfrak{g}_{r,1}$-module homomorphism $f:M\to N$. We claim this is a homomorphism of $\mathfrak{p}_{r,1}$-modules. Indeed, since all composition factors of $N$ are of the form $L_{r+1}(\lambda)$ with $\lambda\in X_{r+1}^{++}$, all weights of $N$ must have non-negative $\delta_{m+n+r+1}$-component. As $f$ preserves weight spaces and the weight of any root vector in the nilradical of $\mathfrak{p}_{r,1}\subseteq\mathfrak{g}_{r+1}$ has $\delta_{m+n+r+1}$-component -1, the nilradical must act trivially on $\text{im}~f$and therefore $f$ is a homomorphism of $\mathfrak{p}_{r,1}$-modules. Now we have a chain of isomorphisms
\begin{align}
\begin{split}
\text{Hom}_{\mathfrak{g}_r}(M,\text{tr}^{r+1}_r N) & = \text{Hom}_{\mathfrak{g}_{r,1}}(M,N) \\
& = \text{Hom}_{\mathfrak{p}_{r,1}}(M,N) \\
& \cong \text{Hom}_{\mathfrak{g}_{r+1}}(\mc{U}\mathfrak{g}_{r+1}\otimes_{\mc{U}\mathfrak{p}_{r,1}} M,N) \\
& = \text{Hom}_{\mathfrak{g}_{r+1}}((\text{tr}_r^{r+1})^! M,N),
\end{split}
\end{align}
\noindent where the penultimate isomorphism comes from the usual adjunction between induction and restriction.
\end{proof}
\begin{trproj} \label{trproj}
If $r<s<\infty$ and $\lambda\in X_r^{++}$ then
%
\begin{align}
\text{tr}_r^s \, P_s(\lambda)=P_r(\lambda).
\end{align}
\end{trproj}
\begin{proof}
Without loss of generality assume $s=r+1$. Throughout the proof we write $\text{tr}$ for $\text{tr}^{r+1}_r$ and $\text{tr}^!$ for $(\text{tr}^{r+1}_r)^!$. First we claim $\text{tr}^!\text{tr}\tr^!=\text{tr}^!$. Take $M\in\mathcal{O}_r^{++}$. The weight of any root vector in the complement to $\mf{p}_{r,1}$ in $\mf{g}_{r+1}$ has $\delta_{m+n+r+1}$-component 1. So
%
\begin{equation}
\text{tr}\left( \mc{U}\mf{g}_{r+1}\otimes_{\mc{U}\mf{p}_{r,1}}M\right)=M.
\end{equation}
\noindent Hence, since $\text{tr}^!(M)$ is a quotient of $\mc{U}\mf{g}_{r+1}\otimes_{\mc{U}\mf{p}_{r,1}}M$, by exactness of $\text{tr}$ there is a surjection $M\twoheadrightarrow\text{tr}\tr^!(M)$. Left adjoints are right exact so this induces a surjection ${\text{tr}^!(M)\twoheadrightarrow\text{tr}^!\text{tr}\tr^!(M)}$. But by the counit-unit equations, $\text{tr}^!(M)$ is a direct summand of $\text{tr}^!\text{tr}\tr^!(M)$. Thus they are equal.
Take $M=P_r(\lambda)$. A left adjoint to an exact functor sends projectives to projectives, so $\text{tr}^! P_r(\lambda)$ is projective. If $\mu\in X_{r+1}^{++}$, the multiplicity of $P_{r+1}(\mu)$ as a direct summand of $\text{tr}^! P_r(\lambda)$ equals
%
\begin{equation}\label{eq:compmult}
\dim \text{Hom}_{\mathfrak{g}_{r+1}}( \text{tr}^! P_r(\lambda),L_{r+1}(\mu)) = \dim \text{Hom}_{\mathfrak{g}_r}\left( P_r(\lambda), \text{tr} L_{r+1}(\mu)\right) = \delta_{\lambda \mu}
\end{equation}
\noindent by Proposition~\ref{tilt}. So $\text{tr}^!P_r(\lambda)=P_{r+1}(\lambda)$. This implies ${\text{tr}^!\text{tr} P_{r+1}(\lambda)=P_{r+1}(\lambda)}$ and so there is an isomorphism of functors on $\mathcal{O}_{r+1}^{++}$:
%
\begin{equation}\label{eq:trff}
\text{Hom}_{\mf{g}_{r+1}}(P_{r+1}(\lambda),-)\cong \text{Hom}_{\mf{g}_{r+1}}(\text{tr}^!\text{tr} P_{r+1}(\lambda),-)\cong \text{Hom}_{\mf{g}_r}(\text{tr} P_{r+1}(\lambda),\text{tr}(-)).
\end{equation}
\noindent In particular the functor on the right is exact. On can show that this isomorphism is just the map induced by $\text{tr}$.
Now take $\mu\in X_r^{++}\subseteq X_{r+1}^{++}$. There is a short exact sequence
%
\begin{equation}
\begin{tikzcd}
0 \ar[r] &L_{r+1}(\mu) \ar[r] & \nabla_{r+1}(\mu) \ar[r] & C \ar[r] & 0
\end{tikzcd}
\end{equation}
\noindent and applying $\text{tr}$ yields
%
\begin{equation}
\begin{tikzcd}
0 \ar[r] &L_r(\mu) \ar[r] & \nabla_r(\mu) \ar[r] & \text{tr}(C) \ar[r] & 0.
\end{tikzcd}
\end{equation}
\noindent Consider the long exact sequence induced by $\text{Hom}_{\mf{g}_r}(\text{tr} P_{r+1}(\lambda),-)$. By \eqref{eq:trff} the $\text{Hom}$ terms form a short exact sequence and so there is an injection
%
\begin{equation}
\text{Ext}^1_{g_r}(\text{tr} P_{r+1}(\lambda),L_r(\mu))\hookrightarrow\text{Ext}^1_{g_r}(\text{tr} P_{r+1}(\lambda),\nabla_r(\mu)).
\end{equation}
\noindent But $P_{r+1}(\lambda)$ has a $\Delta$-flag, so $\text{tr} P_{r+1}(\lambda)$ does also, and therefore ${\text{Ext}^1_{g_r}(\text{tr} P_{r+1}(\lambda),\nabla_r(\mu))=0}$. So ${\text{Ext}^1_{g_r}(\text{tr} P_{r+1}(\lambda),L_r(\mu))=0}$ and now induction on length shows ${\text{Ext}^1_{g_r}(\text{tr} P_{r+1}(\lambda),N)=}0$ for any $N\in\mathcal{O}_r^{++}$. So $\text{tr} P_{r+1}(\lambda)$ is projective. Arguing as in \eqref{eq:compmult} shows ${\text{tr} P_{r+1}(\lambda)=P_r(\lambda)}$.
\end{proof}
\begin{pinftydef}\label{pinftydef}
Take $\lambda\in X^{++}$. If $s>r\gg 0$ then $\lambda\in X_r^{++}$ so by Proposition \ref{trproj} there is an inclusion of $\mathfrak{g}_r$-modules $P_r(\lambda)=\text{tr}^s_rP_s(\lambda)\hookrightarrow P_s(\lambda)$. Define a $\mf{g}=\mf{g}_{\infty}$-module $P(\lambda)$ by
%
\begin{equation}
P(\lambda)=\lim_{\longrightarrow} \, P_r(\lambda).
\end{equation}
\end{pinftydef}
\begin{pinftythm} \label{pinftythm}
Take $\lambda\in X^{++}$ and let $r_{\lambda}\in\mathbb{N}$ be minimal such that $\lambda\in X_{r_\lambda}^{++}$ and $1-r_\lambda\leq (\lambda+\rho_{r_\lambda},\delta_i)\leq r_\lambda$ for all $i$. Then
%
\begin{enumerate}[label=(\roman*)]
\item \label{deltaflag} the $\Delta$-multiplicities of $P_r(\lambda)$ are independent of $r\geq r_{\lambda}$ in the sense of \eqref{eq:multstable}, so $P(\lambda)\in\mathcal{O}^{++}$ by Remark~\ref{rmk:deltamultstable};
\item \label{projcover} $P(\lambda)$ is a projective cover of $L(\lambda)$ in $\mathcal{O}^{++}$.
\end{enumerate}
\noindent In particular, $\mathcal{O}^{++}$ has enough projectives.
\end{pinftythm}
\begin{Rmk:Chenproj}
While drafting this paper the author was made aware the Chih-Whi Chen and Ngau Lam in Taiwan have independently proved that $\mathcal{O}^{++}$ has enough projectives using a different approach.
\end{Rmk:Chenproj}
\begin{proof}
\ref{deltaflag} Take $s>r\geq r_{\lambda}$. Applying $\text{tr}^s_r$ to a $\Delta$-flag of $P_s(\lambda)$ yields a $\Delta$-flag of $P_r(\lambda)$. In light of Proposition~\ref{tilt} it suffices to show that if $\mu\in X_s^{++}$ and $\left( P_s(\lambda):\Delta_s(\mu)\right)\neq 0$ then $\mu\in X_r^{++}$. But if $\left( P_s(\lambda):\Delta_s(\mu)\right)\neq 0$ then $\mu\geq \lambda$. Thus it suffices to show that if $\mu\in X^{++}$ with $\mu\geq\lambda$ then $\mu\in X_{r_{\lambda}}^{++}$.
Assume $\epsilon=0$ (the case $\epsilon=1$ is similar). Take $r$ minimal such that $\mu\in X_r^{++}$. Suppose for contradiction that $r>r_\lambda$. We have $r,r_{\lambda}\in X_r^{++}$ so by \cite[Lemma 3.9]{BLW13},
\begin{equation}\label{eq:localcoideal}
\sum_{\substack{1\leq i\leq m+n+r\\ (\lambda+\rho_r,\delta_i)\leq 1-r}} (-1)^{p_i} = \sum_{\substack{1\leq i\leq m+n+r\\(\mu+\rho_r,\delta_i)\leq 1-r}} (-1)^{p_i}.
\end{equation}
\noindent Since $r>r_{\lambda}$, $(\lambda+\rho_r,\delta_i)>1-r$ unless $i=m+n+r$ so the left hand side is equal to $(-1)^{\epsilon}=1$. Similarly, $\mu\in X_r^{++}\setminus X_{r-1}^{++}$ implies $(\mu+\rho_r,\delta_i)>1-r$ for $i>m+n$. So the right hand side of \eqref{eq:localcoideal} doesn't change if we restrict the sum to be over $1\leq i\leq m+n$. But
%
\begin{equation}
\sum_{\substack{1\leq i\leq m+n\\(\mu+\rho_r,\delta_i)\leq 1-r}} (-1)^{p_i} \leq \sum_{\substack{1\leq i\leq m+n\\(\lambda+\rho_r,\delta_i)\leq 1-r}} (-1)^{p_i},
\end{equation}
\noindent again by \cite[Lemma 3.9]{BLW13} and the right hand side is equal to 0, a contradiction. So $\mu\in X_{r_{\lambda}}^{++}$ and \ref{deltaflag} holds.
\newline
\noindent \ref{projcover} We claim that $P(\lambda)$ is projective. Take a diagram
\begin{equation} \label{projdiag}
\begin{tikzcd}
& P(\lambda) \ar[d, "f"] & \\
M \arrow[r, "g"] & N \ar[r] & 0
\end{tikzcd}
\end{equation}
\noindent Without loss of generality assume $f\neq 0$. Let $\mu_1,\ldots ,\mu_k\in X_{r_\lambda}^{++}$ be the ordered sequence of weights in a $\Delta$-flag of $P(\lambda)$ and take weight vectors $v_1,\ldots ,v_k\in P(\lambda)$ such that $v_i$ projects onto the highest weight vector of weight $\mu_i$ in the subquotient $\Delta(\mu_i)$ of $P(\lambda)$. Then $v_1,\ldots, v_k$ lie in $P_r(\lambda)$ for any $r\geq r_{\lambda}$ by part \ref{deltaflag}.
If $r\geq r_\lambda$, then applying $\text{tr}_r^\infty$ to \eqref{projdiag} and using projectivity of $P_r(\lambda)$ yields a commutative diagram:
%
\begin{equation}
\begin{tikzcd}
& P_r(\lambda) \ar[ld, "h_r"'] \ar[d, "f_r"] & \\
M_r \ar[r, "g_r"'] & N_r \ar[r] & 0
\end{tikzcd}
\end{equation}
\noindent where $M_r=\text{tr}^{\infty}_r(M)$, $N_r=\text{tr}^{\infty}_r(N)$, and $f_r$ and $g_r$ denote the restrictions of $f$ and $g$ respectively. Write $\underline{v}=(v_1,\ldots,v_k)$ and let
%
\begin{equation}
A_r=\text{span} \big\{ \, h_s(\underline{v})=(h_s(v_1),\ldots ,h_s(v_k)) \, \big| \, s\geq r \, \big\}\leq M_{\mu_1}\times \cdots \times M_{\mu_n},
\end{equation}
\noindent a finite-dimensional vector space with
%
\begin{equation}
\cdots \subseteq A_{r+1}\subseteq A_r\subseteq \cdots
\end{equation}
\noindent If $\underline{w}=(w_1,\ldots,w_k)={\sum_{s\geq r} a_s h_s(\underline{v})} \in A_r$ then $\tilde{h}_r={\sum_{s\geq r} a_s h_s\big|_{P_r(\lambda)}}:P_r(\lambda)\to M_r$ is a $\mf{g}_r$-module map with $\tilde{h}_r(v_i)=w_i$. It is unique with this property. Moreover,
%
\begin{equation} \label{gh=f}
g(\tilde{h}_r(v_i))=\sum_{s\geq r} a_sg(h_s(v_i))=\Big(\sum_{s\geq r} a_s\Big) f(v_i)
\end{equation}
\noindent for all $i$ so that in particular
%
\begin{equation}
\sum_{s\geq r} a_sh_s(v_i)=\sum_{s\geq r} b_sh_s(v_i)\in A_r \quad \Rightarrow \quad \sum_{s\geq r}a_s=\sum_{s\geq r}b_s,
\end{equation}
\noindent since $f\neq 0$ implies that there exists an $i$ with $f(v_i)\neq 0$. We wish to find $\underline{w}\in\bigcap_{r\geq r_{\lambda}} A_r$ with $\sum_{s\geq r}a_s=1$ and define $h:P(\lambda)\to M$ by $h\big|_{P_r(\lambda)}=\tilde{h}_r$.
For $r\geq r_\lambda$ let
%
\begin{equation}
B_r= \Big\{ \, \sum_{s\geq r} a_s h_s(\underline{v}) \, \Big| \, \sum_{s\geq r}a_s=0 \, \Big\} \leq A_r.
\end{equation}
\noindent Since all spaces are finite-dimensional, the short exact sequence of inverse systems
%
\begin{equation}
\begin{tikzcd}
0 \ar[r] & B_{r+1} \ar[d] \ar[r] & A_{r+1} \ar[d] \ar[r] & \left. A_{r+1}\middle/ B_{r+1}\right. \ar[d] \ar[r] & 0 \\
0 \ar[r] & B_r \ar[r] & A_r \ar[r] & \left. A_r\middle/ B_r\right. \ar[r] & 0
\end{tikzcd}
\end{equation}
\noindent induces a short exact sequence of the inverse limits:
%
\begin{equation}
\begin{tikzcd}
0 \ar[r] & \displaystyle{\bigcap_{r\geq r_\lambda} B_r} \ar[r] & \displaystyle{\bigcap_{r\geq r_\lambda} A_r} \ar[r] & \displaystyle{\lim_{\longleftarrow}} \, \left. A_r \middle/ B_r\right. \ar[r] & 0.
\end{tikzcd}
\end{equation}
\noindent Each $A_r \big/ B_r$ is a non-zero, finite-dimensional vector space, so $\displaystyle{\lim_{\longleftarrow}} \, A_r \big/ B_r \neq 0$ and so $\bigcap B_r \subsetneq \bigcap A_r$. Take $\underline{w}\in \bigcap A_r \setminus \bigcap B_r$ such that ${\underline{w}=\sum a_s h_s(\underline{v})}$ implies $\sum a_s=1$. The assignment $v_i\mapsto w_i$ induces a well-defined $\mf{g}_r$-module homomorphism $P_r(\lambda)\to M_r$ for any $r\geq r_\lambda$ and so induces a well-defined $\mf{g}$-module homomorphism $h:P(\lambda)\to M$. Morever, $g(h(v_i))=f(v_i)$ for all $i$ by \eqref{gh=f} and so $g\circ h=f$. Thus $P(\lambda)$ is projective.
Now we claim that $P(\lambda)$ is a projective cover of $L(\lambda)$. Indeed, from the $\Delta$-flag of $P(\lambda)$ there is a surjection $P(\lambda)\twoheadrightarrow \Delta(\lambda)$ and so there is an epimorphism $\pi:P(\lambda)\twoheadrightarrow L(\lambda)$. We claim that $\pi$ is superfluous. Suppose $M\in \mathcal{O}^{++}$ and $f:M\to P(\lambda)$ with $\pi\circ f$ surjective. Then $\text{tr}^{\infty}_r(\pi\circ f)=\text{tr}^{\infty}_r(\pi)\circ f_r$ is surjective for any $r\geq r_{\lambda}$ and so $f_r$ is surjective since $\text{tr}^{\infty}_r(\pi):P_r(\lambda)\twoheadrightarrow L_r(\lambda)$ is a projective cover. But $f=\bigcup f_r$, so $f$ is surjective and thus $\pi$ is superfluous.
\end{proof}
\begin{O++schurcat}
$\mathcal{O}^{++}$ is a highest weight category with weight poset $\left( X^{++} \!, \leq \right)$ and standard objects $\left\{ \, \Delta(\lambda) \, \middle| \, \lambda \in X^{++} \, \right\}$.
\end{O++schurcat}
\begin{proof}
The category $\mathcal{O}^{++}$ is abelian by \cite[\S7.2]{CLW12}, objects have finite length by definition, and $\dim \text{End}(L(\lambda))=1$ for any $\lambda\in X^{++}$. By the theorem, $\mathcal{O}^{++}$ has enough projectives and applying duality shows it has enough injectives. Thus $\mathcal{O}^{++}$ is a Schurian category. The poset $\left( X^{++} \!, \leq \right)$ is interval-finite by Lemma 2.4 in \textit{loc. cit.} and the remaining highest weight conditions follow easily from the theorem.
\end{proof}
\subsection{Categorical action}\label{subsec:cataction}
\begin{not:Mr}
If $M\in\mathcal{O}^{++}$ and $r\in\mathbb{N}$ then we will write $M_r:=\text{tr}^{\infty}_r(M)$.
\end{not:Mr}
\noindent For $r<\infty$ let
\begin{equation}
\Omega_r:=\sum_{k,l=1}^{m+n+r} (-1)^{p_l}e_{kl}\otimes e_{lk}.
\end{equation}
\noindent For $M_r\in\mathcal{O}_r$, let $F_rM_r =M_r\otimes U_r$ and $E_rM_r=M_r\otimes U_r^*$. Let $x_r\in \text{End}\left(F_r\right)$ be given by multiplication by $\Omega_r$ and $t_r\in\text{End}\left(F_r^2\right)$ be induced by the map
\begin{equation}
\begin{aligned}
U_r\otimes U_r & \longrightarrow U_r\otimes U_r \\
u_k\otimes u_l & \longmapsto (-1)^{p_kp_l} u_l\otimes u_k.
\end{aligned}
\end{equation}
\begin{finranktpc}\label{finranktpc}
\cite[Theorem 3.10]{BLW13} With respect to the above actions, $\mathcal{O}_r$ is an $\mf{sl}_{I_r}$-TPC of type $(\underline{r},\underline{\epsilon})$.
\end{finranktpc}
\noindent The fact that the data above defines strong $\mf{sl}_2$-categorifications on $\mathcal{O}_r$ \`{a} la Chuang-Rouquier \cite{CR04} was checked in \cite[Proposition~5.1]{CW07}.
The endomorphism $x_r\in\text{End}\left(F_r\right)$ induces an endomorphism of $E_r$, also denoted $x_r$, given by multiplication by $\left(m-n-(-1)^{\epsilon}r\right)-\Omega_r$. For $j\in\mathbb{Z}$, let $F_{j,r}$ and $E_{j,r}$ denote the generalized $j$-eigenspaces of $x_r$ on $F_r$ and $E_r$ respectively.
For $\lambda\in X_r$, $j\in\mathbb{Z}$, and $1\leq i\leq l+1$, let $t^i_{j}(\lambda)\in X_r$ be obtained from $\lambda$ by applying the transposition $(j~j+1)$ to the $i^{\text{th}}$ row of $\lambda$, considered as a 01-matrix $(\lambda^i_j)$ as described in \S\ref{subsec:Set-up}. Then $F_{j,r}\Delta_r(\lambda)$ has a $\Delta$-flag and
\begin{equation}\label{FDeltamult}
\left[ F_{j,r}\Delta_r(\lambda)\right] =\sum_i \left[ \Delta_r(t^i_j(\lambda))\right]
\end{equation}
\noindent where the sum is taken over all $1\leq i\leq l+1$ with $\lambda^i_{j}=1$ and $\lambda^i_{j+1}=0$. Similarly $E_{j,r}\Delta_r(\lambda)$ has a $\Delta$-flag and
\begin{equation}\label{EDeltamult}
\left[ E_{j,r}\Delta_r(\lambda)\right] =\sum_i \left[ \Delta_r(t^i_j(\lambda))\right].
\end{equation}
\noindent where the sum is taken over all $1\leq i\leq l+1$ with $\lambda^i_{j}=0$ and $\lambda^i_{j+1}=1$.
If $\lambda\in X_r^{++}$ and $r>\left| j\right|$ then $t^i_j(\lambda)\in X_r^{++}$ so $E_{j,r}$ and $F_{j,r}$ restrict to endofunctors of $\mathcal{O}_r^{++}$.
\begin{stablemult} \label{stablemult}
Take $M\in \mathcal{O}^{++}$ and $j\in\mathbb{Z}$. There exists $r_M>\lvert j\rvert$ such that the composition multiplicities of $E_{j,r}M_r$ and $F_{j,r}M_r$ are independent of $r\geq r_M$ in the sense of \eqref{eq:compmult}. We will always assume that $r_M>\lvert j-m+n\rvert$.
\end{stablemult}
\noindent Of course $r_M$ depends on $j$ as well as $M$. But since we rarely vary $j$ we won't record this dependence in our notation.
\begin{proof}
Take $\lambda\in X^{++}$. It suffices to prove the claim for $M=L(\lambda)$. Take $r_M>\lvert j\rvert$ such that $\lambda\in X_{r_M}^{++}$ and if $\mu\in X^{++}$ with $[ \Delta (t^i_j(\lambda)):L(\mu)]\neq 0$ for some $1\leq i\leq l+1$ then $r_M\geq r_{\mu}$ (c.f. Theorem~\ref{pinftythm}).
Take $r\in\mathbb{N}$ and suppose $\mu\in X_r^{++}$ with $[ F_{r,j}L_r(\lambda):L_r(\mu)]\neq 0$. Since $\Delta_r(\lambda)\twoheadrightarrow L_r(\lambda)$, ${[ F_{r,j}\Delta_r(\lambda):L_r(\mu)]\neq 0}$ and so $[ \Delta_r(t^i_j(\lambda)):L_r(\mu)]\neq 0$ for some $1\leq i\leq l+1$ by \eqref{FDeltamult}. This implies $[ \Delta(t^i_j(\lambda)):L(\mu)]\neq 0$ and so $\mu\in X_{r_{\mu}}^{++}\subseteq X_{r_M}^{++}$ by the definition of $r_M$. We have
%
\begin{equation*}
[ F_{r,j}L_r(\lambda):L_r(\mu)] = \dim\text{Hom}_{\mf{g}_r}(P_r(\mu),F_{j,r}L_r(\lambda)) = \dim\text{Hom}_{\mf{g}_r}(E_{j,r}P_r(\mu),L_r(\lambda)),
\end{equation*}
\noindent which is the multiplicity of $P_r(\lambda)$ as a direct summand of $E_{j,r}P_r(\mu)$. As $r_M\geq r_{\mu}$, Theorem~\ref{pinftythm}\ref{deltaflag} implies that the $\Delta$-multiplicities of $P_r(\mu)$ are independent of $r\geq r_M$. So the same is true of $E_{j,r}P_r(\mu)$ by \eqref{EDeltamult}. The decomposition of $E_{j,r}P_r(\mu)$ into indecomposables is uniquely determined by these multiplicities and so $[ F_{r,j}L_s(\lambda):L_r(\mu)]$ is independent of $r\geq r_M$. The analogous proof works for $E_{j,r}M$.
\end{proof}
For $r=\infty$ we define $\Omega$, $F$, $F_j$, $x$, and $t$ analogously. If $M\in \mathcal{O}^{++}$ and $r\in\mathbb{N}$ then $\left(FM\right)_r=F_rM_r$. Moreover, the action of $\Omega$ on $FM$ restricts to the action of $\Omega_r$ on $F_rM_r$ so if $r>\left|j\right|$ then $(F_jM)_r=F_{j,r}M_r$. By the proposition above and Lemma~\ref{limitinO}, $F_jM\in\mathcal{O}^{++}$. By \eqref{FDeltamult}, only finitely many $F_jM$ are non-zero, and so $FM=\bigoplus_j F_jM\in\mathcal{O}^{++}$. So $F$ and $F_j$ are well-defined endofunctors of $\mathcal{O}^{++}$.
It remains to define a two-sided adjoint $E$ to $F$. In general, $M\otimes U^*\notin \mc{O}^{++}$ for $M\in\mc{O}^{++}$ so the obvious definition won't work. This is because Proposition~\ref{stablemult} doesn't hold if we replace $E_{j,r}M_r$ with $E_rM_r$. Instead we will define each $E_jM$ as a direct limit of the $E_{j,r}M_r$ and then set $EM=\bigoplus_j E_jM$. However, the natural inclusion $E_rM_r\hookrightarrow E_{r+1}M_{r+1}$ doesn't restrict to inclusions $E_{j,r}M_r\hookrightarrow E_{j,r+1}M_{r+1}$. To get around this we will define two sets of maps $E_{j,r}M_r\to \text{tr}^{r+1}_r(E_{j,r+1}M_{r+1})$, leading to functors $E_j^{\texttt{L}}$ and $E_j^{\texttt{R}}$ on $\mathcal{O}^{++}$ that are naturally left and right adjoint $F_j$ respectively. Finally we will show that $E_j^{\texttt{L}}\cong E_j^{\texttt{R}}$.
\begin{Ejleft}\label{Ejleft}
Take $j\in \mathbb{Z}$ and $M\in\mathcal{O}^{++}$. For $r\in\mathbb{N}$, let $\psi_r$ be the composition of $\mf{g}_r$-module homomorphisms below:
%
\begin{equation}
E_{j,r}M_r\subseteq E_rM_r\subseteq E_{r+1}M_{r+1}\twoheadrightarrow E_{j,r+1}M_{r+1}.
\end{equation}
\noindent Define $E_j^{\texttt{L}}M=\displaystyle{\lim_{\longrightarrow}} \,E_{j,r}M_r$, where the limit is taken over the maps $\psi_r$ above.
\end{Ejleft}
\begin{EjLinO}\label{EjLinO}
Take $M\in\mathcal{O}^{++}$ and $r\geq r_M$ (see Proposition~\ref{stablemult}). Then $\psi_r$ is an injective $\mf{g}_r$-module homomorphism $E_{j,r}M_r\to\text{tr}^{r+1}_r(E_{j,r+1}M_{r+1})$ and so $E_j^{\texttt{L}}M\in\mathcal{O}^{++}$ by Proposition~\ref{stablemult} and Lemma~\ref{limitinO}.
\end{EjLinO}
\begin{proof}
Take $\alpha\in E_rM_r$ and $d\in\mathbb{Z}$. For $t\in\mathbb{N}$, define
%
\begin{equation}
\beta_t:=(d-(-1)^{\epsilon}-\Omega_{r+1})^t\alpha-(d-\Omega_r)^t\alpha.
\end{equation}
\noindent We claim $\Omega_{r+1}\beta_t=0$. Proceed by induction on $t$. First take $t=1$. We have
%
\begin{equation}
\beta_1=\Omega_r\alpha-\Omega_{r+1}\alpha -(-1)^{\epsilon}\alpha
\end{equation}
\noindent Let $z:=m+n+r+1$. Write $\alpha=\sum_{i=1}^{z-1}m_i\otimes u_i^*$ with $m_i\in M_r$. By direct computation,
%
\begin{align}\label{eq:betainduction1}
\begin{split}
\Omega_{r+1}\alpha & =-\sum_{k=1}^z\left(\sum_{i=1}^{z-1} (-1)^{p_i} e_{ki}m_i\right)\otimes u_k^* \\
& = \Omega_r\alpha-\left(\sum_{i=1}^{z-1} (-1)^{p_i} e_{zi}m_i\right)\otimes u_z^*,
\end{split}
\end{align}
\noindent so
%
\begin{equation}\label{eq:betainduction2}
\Omega_{r+1}(\Omega_r\alpha-\Omega_{r+1}\alpha)=-\sum_{k=1}^z\sum_{i=1}^{z-1}(-1)^{p_i+\epsilon}e_{kz}e_{zi}m_i\otimes u_k^*.
\end{equation}
\noindent By the definition of the supercommutator bracket,
%
\begin{align}\label{eq:supercomm}
\begin{split}
e_{kz}e_{zi}m_i & = (-1)^{(p_i+\epsilon)(p_k+\epsilon)}e_{zi}e_{kz}m_i+\left[ e_{kz},e_{zi}\right]m_i \\
& = (-1)^{(p_i+\epsilon)(p_k+\epsilon)}e_{zi}e_{kz}m_i+e_{ki}m_i-(-1)^{p_i+\epsilon}\delta_{ik}e_{zz}m_i.
\end{split}
\end{align}
\noindent If $k<z$ then applying $e_{kz}$ to a weight vector in $M_r$ yields an element of $M_{r+1}$ whose weight has $\delta_z$-component -1. Since $M_{r+1}\in\mathcal{O}_{r+1}^{++}$, this weight space is zero. So $e_{kz}m_i=0$. By weight considerations, $e_{zz}m_i=0$ also. Therefore \eqref{eq:betainduction2} equals
%
\begin{equation}
-\sum_{k=1}^z\sum_{i=1}^{z-1}(-1)^{p_i+\epsilon} e_{ki}m_i\otimes u_k^*=(-1)^{\epsilon} \Omega_{r+1}\alpha.
\end{equation}
\noindent The claim follows.
Now suppose $\Omega_{r+1}\beta_t=0$ for some $t\in\mathbb{N}$. Let
%
\begin{equation}
\beta_t':=\left( d-(-1)^{\epsilon}-\Omega_{r+1}\right)^t(d-\Omega_r)\alpha-\left(d-\Omega_r\right)^{t+1}\alpha.
\end{equation}
\noindent Note that $\Omega_{r+1}\beta_t'=0$ by the inductive hypothesis applied to $(d-\Omega_r)\alpha\in E_rM_r$. But
%
\begin{align}
\begin{split}
(d-(-1)^{\epsilon}-\Omega_{r+1})^{t+1}\alpha & = \left(d-(-1)^{\epsilon}-\Omega_{r+1}\right)^t\left(d-(-1)^{\epsilon}-\Omega_{r+1}\right)\alpha \\
& = \left(d-(-1)^{\epsilon}-\Omega_{r+1}\right)^t\left((d-\Omega_{r})\alpha+\beta_1\right) \\
& = (d-\Omega_r)^{t+1}\alpha+\left( \beta_t'+(d-(-1)^{\epsilon})^t\beta_1\right).
\end{split}
\end{align}
\noindent So $\beta_{t+1}=\beta_t'+(d-(-1)^{\epsilon})^t\beta_1\in\text{Ker}~\Omega_{r+1}$.
Now take $\alpha\in E_{j,r}M_r$. The module $E_{j,r}M_r$ is defined to be the generalized $j$-eigenspace of ${(m-n-(-1)^{\epsilon}r)-\Omega_r}$, so there exists $t\in\mathbb{N}$ such that
%
\begin{equation}\label{eq:alphainespace}
(d-\Omega_r)^t\alpha=0,
\end{equation}
\noindent where $d=m-n-(-1)^{\epsilon}r-j$. So
%
\begin{equation}
\beta_t=(d-(-1)^{\epsilon}-\Omega_{r+1})^t\alpha\in\text{Ker}~\Omega_{r+1}.
\end{equation}
\noindent Define $\beta$ by the equation $(d-(-1)^{\epsilon}-\Omega_{r+1})^t\beta=\beta_t$. Then $\Omega_{r+1}\beta=0$ and so
%
\begin{equation}
\left( d-(-1)^{\epsilon}-\Omega_{r+1}\right)^t(\alpha-\beta)=\beta_t-(d-(-1)^{\epsilon})^t\beta=0.
\end{equation}
\noindent So $\alpha =(\alpha-\beta)+\beta$ is a decomposition of $\alpha\in E_rM_r\subseteq E_{r+1}M_{r+1}$ into generalized $(d-(-1)^{\epsilon}-\Omega_{r+1})$-eigenvectors and $\alpha-\beta\in E_{j,r+1}M_{r+1}$. So $\psi_r(\alpha)=\alpha-\beta$.
Suppose $\psi_r(\alpha)=0$. Then $\alpha=\beta\in\text{Ker}~\Omega_{r+1}$ so \eqref{eq:betainduction1} implies ${\sum_{i=1}^{z-1} (-1)^{p_i} e_{ki}m_i=0}$ for each $k$ and thus $\Omega_r\alpha=0$. Generalized eigenspaces with different eigenvalues intersect trivially, so if $\alpha\neq 0$ then \eqref{eq:alphainespace} implies $d=0$, so $j=m-n-(-1)^{\epsilon}r$. But this contradicts the assumption $r\geq r_M>\lvert j-m+n\rvert$ made in Proposition~\ref{stablemult}. So $\psi_r$ is injective.
\end{proof}
Now we define the right adjoint $E_j^{\texttt{R}}$ to $F_j$. Take $M\in\mathcal{O}^{++}$, $r\geq r_M$, and an element ${x\in\text{tr}^{r+1}_r(E_{j,r+1}M_{r+1})}$. We can write
\begin{equation}
x=\sum_{i=1}^{m+n+r+1} m_i\otimes u_i^*
\end{equation}
\noindent where $m_i\in M_r$ for $1\leq i\leq m+n+r+1$ and $m_{m+n+r+1}\in M_{r+1}$ is a sum of weight vectors whose weights have $\delta_{m+n+r+1}$-component 1. Define
\begin{equation}\label{phidef}
\begin{aligned}
\phi_r:\text{tr}^{r+1}_r(E_{j,r+1}M_{r+1}) & \longrightarrow E_rM_r \\
\sum_{i=1}^{m+n+r+1} m_i\otimes u_i^* & \longmapsto \sum_{i=1}^{m+n+r} m_i\otimes u_i^*
\end{aligned}
\end{equation}
\noindent This is a homomorphism of $\mathfrak{g}_r$-modules.
\begin{phi11}\label{phi11}
Take $M\in\mathcal{O}$ and $r\geq r_M$. Then
%
\begin{enumerate}[label=(\roman*)]
\item \label{phi11image}$\text{im}~\phi_r\subseteq E_{j,r}M_r$;
\item \label{phi11inj}$\phi_r$ is injective and so is an isomorphism by Proposition \ref{stablemult}.
\end{enumerate}
\end{phi11}
\begin{Ejright}
Let $E_j^{\texttt{R}}M=\displaystyle{\lim_{\longrightarrow}}~E_{j,r}M_r$, where the direct limit is taken along the maps
%
\begin{equation}
E_{j,r}M_r \stackrel{\phi_r^{-1}}{\longrightarrow} \text{tr}^{r+1}_r(E_{j,r+1}M_{r+1})\subseteq E_{j,r+1}M_{r+1}
\end{equation}
\noindent for $r\geq r_M$. We have $E_j^{\texttt{R}}M\in\mathcal{O}^{++}$ by Proposition~\ref{stablemult} and Lemma~\ref{limitinO}.
\end{Ejright}
\begin{proof}[Proof of Lemma~\ref{phi11}]
Take $x\in\text{tr}^{r+1}_r(E_{j,r+1}M_{r+1})$ and write $x=\sum_{i=1}^z m_i\otimes u_i^*$, where $z=m+n+r+1$. Fix $d\in\mathbb{Z}$. For $t\geq 0$, write
%
\begin{equation}\label{eq:mkt}
\left(d-(-1)^{\epsilon}-\Omega_{r+1}\right)^tx=\sum_{k=1}^z m_{kt}\otimes u_k^*
\end{equation}
\noindent so that $m_{k0}=m_k$ for $1\leq k\leq z$. The map $\Omega_{r+1}$ preserves $E_{j,r+1}M_{r+1}$ and preserves weights, so \eqref{eq:mkt} lies in $\text{tr}^{r+1}_r(E_{j,r+1}M_{r+1})$.
We claim that
%
\begin{equation}\label{eq:mktclaim}
m_{k,t+1}-e_{kz}m_{z,t+1}=(d-(-1)^{\epsilon})\left(m_{kt}-e_{kz}m_{zt}\right)
\end{equation}
\noindent for all $1\leq k\leq z$ and $t\geq 0$. By direct computation,
%
\begin{equation}\label{eq:mktrecursion}
m_{k,t+1}=(d-(-1)^{\epsilon})m_{kt}+\sum_{i=1}^z(-1)^{p_i}e_{ki}m_{it}.
\end{equation}
\noindent So
%
\begin{align}
\begin{split}
m_{k,t+1}-e_{kz}m_{z,t+1} = & \,(d-(-1)^{\epsilon})m_{kt}+\sum_{i=1}^z(-1)^{p_i}e_{ki}m_{it} \\
& - (d-(-1)^{\epsilon})e_{kz}m_{zt}+\sum_{i=1}^z(-1)^{p_i}e_{kz}e_{zi}m_{it}.
\end{split}
\end{align}
\noindent But $e_{kz}e_{zz}m_{zt}=e_{kz}m_{zt}$ by the weight of $m_{zt}$, and if $1\leq i\leq z-1$ then $e_{kz}e_{zi}m_{it}=e_{ki}m_{it}$ as in \eqref{eq:supercomm}. The claim follows.
Set $d=m-n-(-1)^{\epsilon}r-j$. Since $x\in E_{j,r+1}M_{r+1}$, we have ${\left( d-(-1)^{\epsilon}-\Omega_{r+1}\right)^tx=0}$ for $t\gg 0$ and so $m_{kt}=0$ for $1\leq k\leq z$ and $t\gg0$. As $r\geq r_M$, the assumption $r_M>\lvert j-m+n\rvert$ in Proposition~\ref{stablemult} means $d-(-1)^{\epsilon}\neq0$ and so \eqref{eq:mktclaim} implies that $e_{kz}m_{zt}=m_{kt}$ for all $k$ and $t$. Now \eqref{eq:mktrecursion} simplifies to
%
\begin{equation}\label{eq:newrecursion}
m_{k,t+1}=dm_{k,t}+\sum_{i=1}^{z-1}e_{ki}m_{i,t}.
\end{equation}
\noindent But for $1\leq k\leq z-1$, this is the same recursive formula as for the terms of $(d-\Omega_r)^t\phi_r(x)$. So
%
\begin{equation}
\phi_r\left( (d-(-1)^{\epsilon}-\Omega_{r+1})^rx\right) = (d-\Omega)^t\phi_r(x)
\end{equation}
\noindent In particular this implies that $(d-\Omega)^t\phi_r(x)=0$ for $t\gg 0$, so $\phi_r(x)\in E_{j,r}M_r$ and \ref{phi11image} holds.
Now suppose $\phi_r(x)=0$. Then $m_i=0$ for $1\leq i\leq z-1$. Equation \eqref{eq:newrecursion} shows that $m_{kt}=0$ for $1\leq k\leq z-1$ and $m_{zt}=d^tm_z$ for all $t\geq 0$. But $m_{zt}=0$ for $t\gg 0$ and $d\neq0$ so this implies $m_z=m_{z0}=0$, and therefore $x=0$.
\end{proof}
\begin{Fjadj}
Take $j\in\mathbb{Z}$. Then
\begin{enumerate}[label=(\roman*)]
\item\label{Ladj} $E_j^{\texttt{L}}$ is left-adjoint to $F_j$;
\item\label{Radj} $E_j^{\texttt{R}}$ is right-adjoint to $F_j$;
\item\label{L=R} $E_j^{\texttt{L}}\cong E_j^{\texttt{R}}$
\end{enumerate}
\end{Fjadj}
\begin{proof}
\ref{Ladj} If $M,N\in\mathcal{O}^{++}$ then
%
\begin{align}
\begin{split}
\text{Hom}_{\mf{g}}( M,F_jN) & = \text{Hom}_{\mf{g}}( \lim_{\longrightarrow}M_r,F_jN) \\
& = \lim_{\longleftarrow} \text{Hom}_{\mf{g}_r}( M_r,F_{j,r}N_r) \\
& = \lim_{\longleftarrow} \text{Hom}_{\mf{g}_r}( E_{j,r}M_r,N_r) \\
& =\text{Hom}_{\mf{g}}(\lim_{\longrightarrow} E_{j,r}M_r,N) \\
\end{split}
\end{align}
\noindent Unravelling these isomorphisms shows that the connecting maps in the final direct limit $\displaystyle{\lim_{\longrightarrow}}~E_{j,r}M_r$ are just the $\psi_r$ from Definition~\ref{Ejleft}. The result follows.
\newline
\noindent\ref{Radj} Similar.
\newline
\noindent\ref{L=R} Take $M\in\mathcal{O}^{++}$ and $r\geq r_M$. Multiplication by $\Omega_r$ is a $\mf{g_r}$-module isomorphism when restricted to $E_{j,r}M_r$, so it suffices to show that the following diagram commutes:
%
\begin{equation}
\begin{tikzcd}
E_{j,r}M_r \ar[d, "\psi_r"] \ar[r, "\Omega_r"] & E_{j,r}M_r \ar[d, leftarrow, "\phi_r"] \\
\text{tr}^{r+1}_r(E_{j,r+1}M_{r+1}) \ar[r, "\Omega_{r+1}"] & \text{tr}^{r+1}_r(E_{j,r+1}M_{r+1})
\end{tikzcd}
\end{equation}
Take $\alpha\in E_{j,r}M_r$. From the proof of Lemma~\ref{EjLinO}, $\psi_r(\alpha)=\alpha-\beta$ for some ${\beta\in \text{Ker}~\Omega_{r+1}}$. So $\Omega_{r+1}\psi_r(\alpha)=\Omega_{r+1}\alpha$. Equation \eqref{eq:betainduction1} implies $\phi_r(\Omega_{r+1}\alpha)=\Omega_r\alpha$, so $\phi_r(\Omega_{r+1}\psi_r(\alpha))=\Omega_r\alpha$ as required.
\end{proof}
Write $E_j=E_j^{\texttt{R}}$ and let $E=\bigoplus_j E_j$. If $M\in\mathcal{O}^{++}$ then only finitely many $E_jM$ are non-zero by $\eqref{EDeltamult}$, so $EM\in\mathcal{O}^{++}$. The biadjunctions between the $F_j$ and $E_j$ induce a biadjunction between $F$ and $E$.
\begin{infranktpc}\label{infranktpc}
With the definitions of $E$, $F$, $x$, and $t$ above, $\mathcal{O}^{++}$ is an $\mf{sl}_{\mathbb{Z}}$-TPC of type $(\underline{\infty},\underline{\epsilon})$.
\end{infranktpc}
\begin{proof}
\ref{CA1} and \ref{CA3} are clear. \ref{CA2} follows from truncation and Theorem~\ref{finranktpc}. \ref{TPC1} and \ref{TPC2} are consequences of \eqref{FDeltamult} and \eqref{EDeltamult} and the identification of $X^{++}$ with $\Xi_{\underline{\infty},\underline{\epsilon}}$ described in \S~\ref{subsec:Set-up}. \ref{CA4} is a consequence of \ref{TPC2}.
\end{proof}
Recall that the category $\mathcal{O}^{++}$ depends on $\epsilon\in\{0,1\}$. We reintroduce the $\epsilon$-dependence and write $\mathcal{O}^{++}$ as $\mathcal{O}^{++}_{\epsilon}$. A less general formulation of the following was conjectured in \cite[Conjecture~6.10]{CWZ06}. It was generalized in \cite[Conjecture~4.18]{CW07} and first proved in \cite[Theorem~5.1]{CL09}.
\begin{superduality}\label{superduality}
There is a strongly equivariant equivalence
%
\begin{align}
\mathbb{S}:\mathcal{O}_0^{++}\longrightarrow \mathcal{O}_1^{++}
\end{align}
\noindent with $\mathbb{S}L(\lambda)\cong L(\lambda)$.
\end{superduality}
\begin{proof}
This follows immediately from Proposition \ref{prop:TPCsuperduality}, Theorem \ref{thm:uniquenessofTPCs}, and Theorem \ref{infranktpc}. The condition on irreducibles shows that this is the same functor as in \cite{CL09}.
\end{proof}
\section{Graded lifts}\label{section:gradings}
We finish by describing how to construct graded lifts of $\mf{sl}_{I_r}$-TPCs and deduce a graded super duality. This section closely follows \cite[Section~5]{BLW13} and we refer the interested reader there for most definitions and proofs.
For $r\in\mathbb{N}\cup\{\infty\}$, let $U_q\mf{sl}_{I_r}$ be the quantum group associated to $\mf{sl}_{I_r}$: a $\mathbb{Q}(q)$-algebra with generators $\left\{ \, e_i, f_i, k_i^{\pm1} \,\middle| \, i\in I_r \, \right\}$ and well-known relations. For $\epsilon\in\{0,1\}$ there is a $U_q\mf{sl}_{I_r}$-module $\bigwedge_q^{\underline{r},\underline{\epsilon}} V_r$ with basis $\left\{ \, v_{\lambda} \, \middle| \, \lambda\in\Xi_{\underline{r},\underline{\epsilon}}\,\right\}$ as before. The action of the generators on this basis is given in \cite[(5.3)-(5.4)]{BLW13}.
Let $\mc{C}$ be a graded category with grading shift functors $Q^{\pm1}$. Write $\widehat{\mc{C}}$ for the category with the same objects as $\mc{C}$ and Hom spaces defined by
\begin{equation}
\text{Hom}_{\widehat{\mc{C}}}(M,N):=\bigoplus_{i\in\mathbb{Z}}\text{Hom}_{\mc{C}}(Q^iM,N).
\end{equation}
\noindent A graded functor $F:\mc{C}\to\mc{C}'$ between graded categories induces a functor $\widehat{F}:\widehat{\mc{C}}\to\widehat{\mc{C}'}$. A graded lift of an (ungraded) Schurian category $\overline{\mc{C}}$ is a graded abelian category $\mc{C}$ with a fully faithful functor $\nu:\widehat{\mc{C}}\to\overline{\mc{C}}$ such that $\nu$ is dense on projectives and $\nu\circ\widehat{Q}\cong\nu$.
We define a \emph{$U_q\mf{sl}_{I_r}$-tensor product categorification} of type $(\underline{r},\underline{\epsilon})$ as in \cite[Definition~5.9]{BLW13}. If $\mc{C}$ is a $U_q\mf{sl}_{I_r}$-TPC of type $(\underline{r},\underline{\epsilon})$ we denote the distinguished set of irreducibles in $\mc{C}$ by $\left\{\, L(\lambda) \,\middle|\, \lambda\in\Xi_{\underline{r},\underline{\epsilon}}\,\right\}$.
\begin{gradedlifts}\label{gradedlifts}
Take $r\in\mathbb{N}\cup\{\infty\}$. Suppose that $\overline{\mathcal{C}}$ is an $\mathfrak{sl}_{I_r}$-TPC of type $(\underline{r},\underline{\epsilon})$.
%
\begin{enumerate}[label=(\roman*)]
\item \label{gradedlifts1} There exists a graded lift $\mc{C}$ of $\overline{\mc{C}}$ such that $\mc{C}$ is a $U_q\mathfrak{sl}_{I_r}$-TPC $\mathcal{C}$ of type $(\underline{r},\underline{\epsilon})$ and the graded functors $E_j$ and $F_j$ and graded natural transformations $x$ and $t$ are all graded lifts of the corresponding data for $\overline{\mathcal{C}}$. Moreover $\mathcal{C}$ is Koszul.
\item If $\mathcal{C}'$ is another such graded lift of $\overline{\mc{C}}$ then there is a strongly equivariant graded equivalence $\mathbb{G}:\mathcal{C}\to \mathcal{C}'$ with $\nu'\circ\widehat{\mathbb{G}}\cong \nu$ and $\mathbb{G} L\left(\lambda\right)\cong L'\left(\lambda\right)$.
\end{enumerate}
\end{gradedlifts}
\begin{proof}
For $r<\infty$ this is covered by \cite[Theorem~5.11]{BLW13}. For $r=\infty$ the proof is formally identical to that outlined in \cite[\S5.7 and \S5.8]{BLW13}. The only small modification needed is the definition of defect. Suppose $\lambda\in\Xi_{\underline{\infty},\underline{\epsilon}}$ and take $r\in\mathbb{N}$ such that $\lambda\in\Xi_{\underline{r},\underline{\epsilon}}$. Define the defect of $\lambda$ by
%
\begin{equation}
\text{def}(\lambda):=\frac{1}{2}(\lvert \kappa_r\rvert\cdot\lvert\kappa_r\rvert-\lvert\lambda\rvert_r\cdot\lvert\lambda\rvert_r)
\end{equation}
\noindent where $\kappa_r\in\Xi_{\underline{r},\underline{\epsilon}}$ is defined as in \S\ref{subsection:truncation}. The proof of \cite[Lemma~2.2]{BLW13} can easily be adapted to show that this is independent of the choice of $r$.
\end{proof}
Recall the $\mathfrak{sl}_{\mathbb{Z}}$-TPC ${\mathcal{O}}_{\epsilon}^{++}$ of type $(\underline{\infty},\underline{\epsilon})$ from Section~\ref{section:catO} and the super duality equivalence ${\mathbb{S}}:{\mathcal{O}}_{0}^{++}\to {\mathcal{O}}_1^{++}$ of Theorem~\ref{superduality}. The following new `graded super duality' is an immediately corollary of the theorem above.
\begin{gradedsuperduality}
For $\epsilon\in\left\{0,1\right\}$, the category ${\mathcal{O}}_{\epsilon}^{++}$ has a unique Koszul graded lift $^{\text{gr}}\mathcal{O}_{\epsilon}^{++}$ as in Theorem \ref{gradedlifts}\ref{gradedlifts1} and ${\mathbb{S}}$ lifts to a strongly equivariant graded equivalence
%
\begin{align}
^\text{gr}\mathbb{S}:\,^\text{gr}\mathcal{O}_0^{++}\longrightarrow\, ^\text{gr}\mathcal{O}_1^{++}
\end{align}
\noindent with $^\text{gr}\mathbb{S} L\left(\lambda\right)\cong L\left(\lambda\right)$.
\end{gradedsuperduality}
|
{
"redpajama_set_name": "RedPajamaArXiv"
}
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Q. Will your product address the symptoms of athletes foot?
A. H-Athlete's Foot Formula will address the symptoms of athletes foot including redness, itching and odor. However, the fungus reproduces itself by spores which are kept in ideal conditions. It is advisable that you replace your socks as the dead skin can contain the fungus and cause it to spread to new areas on the foot. We also suggest that you wrap your shoes in a plastic bag and place them in the freezer for 12 hours.
A. Results vary from person to person, the process may take anywhere from one week to a few weeks. However, most people experience instant relief from the symptoms when using H-Athlete's Foot Formula.
A. This depends on your condtion. It is important that you do not run out of formula and interrupt the program. There is 11ml of H-Athlete's Foot Formula in one bottle, sufficient for over 100 applications. If you have the condition in numerous places on your feet and elsewhere, we suggest you get the large, 33ml bottle (Save 23%).
Q. Can I use your formula for nail fungus.
A. H-Athlete's Foot Formula is formulated specifically for foot fungus however our H-Nail Fungus Formula is formulated specifically for nail fungus.
Q. Can I apply the formula to my groin area?
A. In severe cases of athlete's foot the fungus may find its way to the groin area. Our H-Jock Itch Formula is formulated specifically for this condition.
Q. Is athlete's foot contagious?
A. The fungus is very contagious. We shed skin all the time which usually ends up on the floor. If someone walks on the dead skin, they could be infected with the fungus.
|
{
"redpajama_set_name": "RedPajamaC4"
}
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package org.apache.olingo.odata2.jpa.processor.api.model;
import java.io.InputStream;
/**
* The interface provides methods to extend JPA EDM containers.
*
*
*
*/
public interface JPAEdmExtension {
/**
* The method is used to extend the JPA EDM schema view with custom operations. Use this method to
* register custom operations.
*
* @param view
* is the schema view
* @see org.apache.olingo.odata2.jpa.processor.api.model.JPAEdmSchemaView#registerOperations(Class, String[])
*
*/
public void extendWithOperation(JPAEdmSchemaView view);
/**
* The method is used to extend the JPA EDM schema view with Entities, Entity Sets, Navigation Property and
* Association.
*
* @param view
* is the schema view
*
*/
public void extendJPAEdmSchema(JPAEdmSchemaView view);
/**
* Implement this method to provide a stream of Mapping model.
* @return
* a stream of mapping model XML as per JPAEDMMappingModel.xsd
*/
public InputStream getJPAEdmMappingModelStream();
}
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 5,438
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DARRYL "DMC" MCDANIELS will be at Looney Tunes to celebrate the release of his Record Store Day Black Friday EXCLUSIVE LP release, "BACK FROM THE DEAD, THE LEGEND LIVES!" Darryl will be here on RSD Black Friday (Friday November 24th) @ 3PM to talk to his fans, take photos & do an autograph signing! We are very excited to have the King himself at our store for all of his fans in celebration of this fantastic new release! To get into this event you need a wristband. To get a wristband you must pre order the new LP. You can do that at our store or online here. If you order online there is a $4 paypal fee. Of course there is no fee at the store. If you order online make sure you choose INSTORE PICK UP. Regardless of what shipping option you choose at check out. NO ONLINE ORDERS SHIP. You can pick up your online order any day after you place the order. You can also just pick it up the day of the event here. Thank you and see you at the show!
TO GET INTO THIS EVENT PRE ORDER THE LP TO GET A WRISTBAND!
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 7,851
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Le codex de Lorsch (codex Laureshamensis en latin) est un livre manuscrit de 460 pages écrit à l'abbaye de Lorsch entre 1167 et 1190. Il comprend une histoire détaillée de l'abbaye, un cartulaire de 3 836 documents ainsi que quelques polyptyques. La valeur du cartulaire est particulièrement grande car les originaux ont été perdus. Le codex est actuellement conservé aux archives nationales de Wurtzbourg.
Le codex a été composé au pour documenter les droits et les possessions de l'abbaye alors que la puissance de Lorsch était déjà en train de décliner. Les documents du cartulaire concernent des achats et des donations à partir de 764. Il comprend aussi deux répertoires des bienfaiteurs ainsi qu'une chronique des abbés. Cette chronique sert surtout comme source pour l´histoire des constructions et sur le développement du trésor de l´église. Seule la lettre initiale de la première page est enluminée. Le texte est écrit en minuscule caroline. Les donations des princes et des empereurs sont d´abord mentionnées suivies de celles du peuple, classées par Gau (pays) tels que ceux de Worms où l'abbaye possédait plus de 1 180 biens, de Spire, du Rhin, du Main, du Neckar et du Kraichgau. C'est dans le codex de Lorsch que de nombreuses localités sont mentionnées pour la première fois ; au total, il en nomme plus de 1 000.
Voir aussi
Bibliographie
Karl Glöckner: Codex Laureshamensis, Darmstadt 1929-1936: Le texte du codex en latin
Codex Laureshamensis. Das Urkundenbuch des ehemaligen Reichsklosters Lorch, Neustadt/Aisch 2003,
Articles connexes
L'évangéliaire de Lorsch
L'abbaye de Lorsch
Liens externes
Le texte du codex en allemand
Manuscrit enluminé du XIIe siècle
Chronique médiévale enluminée
Église au Moyen Âge
Histoire de l'Allemagne médiévale
|
{
"redpajama_set_name": "RedPajamaWikipedia"
}
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What Happens When Soft Power Has to Stay at Home?
Edward Elliott
Commentary, 8 June 2020
Coronavirus, UK Integrated Review 2021, Art, Culture and Literature, UK
The coronavirus pandemic has put many of the central sources of the UK's soft power on pause. These must be protected, and new opportunities should be seized, for the UK to remain a global leader in soft power.
Before the coronavirus pandemic struck, the UK's foreign policy focus had largely been on completing Brexit and on trying to provide the substance behind its 'Global Britain' slogan. Soft power, a country's ability to affect others through the power of attraction, was seen as a crucial element of the UK's role in the post-Brexit world. Hence the creation of a soft power strategy by the Foreign Office and the inclusion of soft power in the upcoming but postponed Integrated Review, as well as a growing number of non-governmental initiatives such as the BFPG and British Council's 'UK Soft Power Group'.
Yet, due to the consequences of the pandemic, many of the sources of the UK's soft power (and indeed those of other countries across the world) have been shut down or put on pause. In the UK, for example, we currently have no Premier League, museums across the country are shut, universities face a large drop in expected international students, and international tourism to the UK is effectively non-existent, with inbound tourist numbers predicted to be down 54% for 2020 – a figure that right now feels optimistic.
This is not to say these sectors haven't been responding to this crisis in ways that continue to add value to the UK's soft power: sports across the UK are carrying out charitable initiatives while they look for innovative ways to resume activity; museums have online virtual tours. But their impact is undeniably much less than pre-coronavirus.
How might this reflect on the UK's overall soft power in 2020? Traditionally, the UK has fared well on global soft power rankings, coming second in 2019 in Portland's SoftPower30, one of the most respected soft power rankings. The SoftPower30 identifies a number of different categories of soft power including culture, education, government and more, which are then weighted. The changes brought about by coronavirus will result in the relative importance of each of those categories shifting; some areas have ground to a halt but others – such as technology and science – are thrust to the forefront as countries grapple with the virus and a search for a vaccine. Whether Portland specifically change their own weighting for their 2020 rankings remains to be seen, but either way, the soft power landscape will not look the same by the end of 2020.
Seizing the Opportunity: The Example of China
As this landscape shifts dramatically, the newer opportunities available to build and exert soft power become ever more important. One of the most visible attempts to capture these to date has been by China. Despite its international reputation suffering from perceptions of its initial handling of the virus, China has been busy trying to boost its international image. Initiatives have been numerous, from both the public and private sector, including shipping PPE to the Gulf states, test kits to the African Union, as well as sharing public health expertise. China also supplied PPE and testing kits to Italy, a move that drew public praise from Italy's foreign minister and helped China continue to build its image as a benefactor.
Whilst examples of faulty equipment and pointedly undiplomatic behaviour of Chinese 'wolf warrior diplomats' have undermined these efforts to some extent, China is hoping to come out of 2020 with a more positive international reputation and greater influence. The US has felt threatened by this attempted soft power offensive and has retaliated by upping its diplomatic and trade spats with China. This has ranged from President Trump referring to coronavirus as the 'Wuhan virus', to the White House releasing a 20-page report criticising China's 'malign activities'. It remains to be seen who the winners and losers of this soft power skirmish will be, but what is clear is that new battle lines are being drawn.
Foreign Policy as Soft Power
This brings us to what Portland defines as the most important subjective sub-index of soft power: foreign policy. Former Prime Minister Theresa May recently reminded the UK government of its 'responsibilities on the world stage', criticising its apparent lack of global leadership in dealing with the pandemic at hand. Whilst the UK's domestic handling of the pandemic is open to some criticism, the argument about the international response seems slightly misplaced. The UK has taken an active role in promoting international action – in particular on vaccine research, development and roll-out. And, already a leading aid donor, it has put at least some of its money where its mouth is, with commitments of over $1 billion to the international effort. Recently, the UK co-hosted the Coronavirus Global Response International Pledging Conference, as well as the Global Vaccine Summit.
The UK should continue to lead on initiatives such as these to show its 'Global Britain' credentials, bolster its foreign policy leadership and boost its soft power at a time when many of its traditional soft power sources are on standby.
Protecting the UK's Soft Power Assets
Until the switch can be flipped back on and these soft power assets powered back up, the UK faces the challenge of protecting their survival as many are suffering gaping financial wounds. As well as seizing the new opportunities presented by the crisis, the UK should focus on helping these sources to build the resilience to both withstand the impacts of the pandemic, but also emerge in as strong a position as possible. Depending on the pandemic's progression, these measures could include financial bailouts or other support. As a spokesperson for
London Mayor Sadiq Khan said, culture 'must play a key role in helping us recover from this public health crisis'.
Perhaps the most significant action taken by the UK government has been its extraordinary furlough scheme, which pays the wages of workers on leave because of coronavirus and costs the government about £14 billion a month. The Department for Digital, Culture, Media and Sport has also recently made a positive move and appointed Neil Mendoza as Commissioner for Cultural Recovery, and Arts Council England created a £160 million emergency fund for theatres, galleries, museums and artists affected by the pandemic.
It would be wrong then to say that the government is not taking important measures to support this sector, but will they be enough to counteract the devastating scale of the virus's impact? Recent reports highlight that the British Council, one of the UK's main soft power institutions, may not have a future unless more support is provided.
The UK should double down in its efforts to protect and build its soft power in the midst of a pandemic that is impacting every aspect of our lives. By combining these two approaches of protecting traditional sources and making the most of new opportunities, the UK has the opportunity to remain at the forefront of global soft power in 2020. But, like many other aspects of the response to this pandemic, it is going to require a lot of money.
Edward Elliott is a Senior Associate at the British Foreign Policy Group.
The views expressed in this Commentary are the author's, and do not represent those of RUSI or any other institution.
BANNER IMAGE: Whitehall, London. Courtesy of Pikrepo.
The SCRI and Strategic Advantage for the UK in the Indo-Pacific
RUSI Newsbrief, 15 January 2021
As the UK considers an engagement strategy with the Indo-Pacific after Brexit, the Supply Chain Resilience Initiative offers a chance to build a free-trade bloc amongst 'like-minded nations' and deepen strategic ties in the region.
Tags: China, Japan, RUSI Newsbrief, India, UK, Pacific
Commentary, 14 January 2021
David Hutt
Having failed to beat the EU to the Indo-Pacific, and with US–EU relations less than ideal ahead of Joe Biden's inauguration this month, the UK could carve out a niche in Asia by aligning with US policy.
Tags: United States, UK
Joyce Anelay
The House of Lords International Relations and Defence Committee, which I chair, has just published its report, 'The UK and Afghanistan'. Here are its main findings.
Tags: Afghanistan, UK
Does the Pandemic Tell Us Anything About War Casualties?
Tim Willasey-Wilsey
It has become commonplace to suggest that British people today would not accept the levels of casualties suffered on the Western Front during the First World War. In Afghanistan the loss of 454 soldiers caused deep public unease. Yet already the UK has lost over 80,000 people to coronavirus and people have become accustomed to the tragic daily toll.
Tags: Coronavirus, The Great War, UK
The Long Trail of British China Policy
RUSI Newsbrief, 7 January 2021
Oliver Yule-Smith
Realising a new approach to Beijing following the Integrated Review will require policymakers to acknowledge the significant historical baggage that comes with policy design in this area. Avoiding these pitfalls will be integral to ensuring a clear-eyed strategy for China.
Tags: China, RUSI Newsbrief, UK
Public Communications Leadership: #CrisisComms and the Manchester Arena Attack
Jill S Russell and Pablo de Orellana
Greater Manchester Police's communications strategy is an example of how to respond in the aftermath of an attack.
Tags: RUSI Journal, UK Counter-terrorism, Tackling Extremism, UK, Emergency Response, Terrorism
Are Chinese Companies Taking Advantage of the Coronavirus?
Multimedia, 29 April 2020
Elisabeth Braw, Associate Fellow
The pandemic is affecting Western companies and making them vulnerable for takeover.
Coronavirus, Modern Deterrence
Coronavirus: The Italian Civil Contingencies Agency Response
Elisabeth Braw, Senior Research Fellow, Modern Deterrence, talks to Carmelo Orlando, Protezione Civile, about how Italy has responded to the coronavirus.
Coronavirus, Military Sciences, Modern Deterrence, Europe
The Coronavirus Pandemic: A Boon for Dictators or Democrats?
Dr Jonathan Eyal talks with author and commentator John Kampfner about the impacts of the coronavirus. Has the coronavirus helped discredit populists or will it give them a platform to strengthen...
RUSI and Northumbria University to Research Data-Driven Approaches to Covid-19
News, 4 November 2020
Researchers at RUSI and Northumbria University have secured UK government funding to conduct a major new project in support of the UK's response to Covid-19.
Coronavirus, Organised Crime
RUSI During the Coronavirus Pandemic
News, 30 September 2020
Over the past few months, the UK government has issued a series of guidelines on 'social distancing' to reduce interaction between people. Accordingly, RUSI has taken the following steps to ensure...
Annual Chief of the Defence Staff Lecture 2020
Events, 17 December 2020
General Sir Nick Carter will deliver RUSI's annual lecture covering key topical defence and security issues.
Tags: UK Integrated Review 2021
Ben Wallace on UK Defence Reform
A webinar on defence reform with The Rt Hon Ben Wallace MP, UK Secretary of State for Defence.
Reflections on Assessing National Exposure to Proliferation Financing Risk
Events, 29 October 2020
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\section{Introduction}
One of the main challenges in nuclear structure is to understand the
interplay between single-particle, vibrational and rotational
degrees of excitation modes. Mass $A=120-130$ is one of the regions
where the modes associated with all three degrees of freedom
have been studied quite extensively. High-spin band structure in
this mass region has been experimentally investigated through heavy-ion-induced
reactions (see, for example, refs.
\cite{Pa05,Mason05,Pe96,la05,sa08}). Along with these studies, many
low-lying non-yrast states have also been investigated in the
$\beta$-decay spectroscopic methods \cite{Ga00} and Coulomb
excitations of stable as well as radioactive ions \cite
{Mu06,Ju08,Sa08}. Nuclei in this mass region depict a variety of
band structures which are built on different excitation modes.
Proton and neutron mass distributions develop opposite types of
quadrupole deformations in these nuclei due to the presence of the
proton Fermi surface near the lower end of the $h_{11/2}$ orbitals
and that of neutron near the middle of the $h_{11/2}$ orbitals.
This results in a $\gamma$-instability in these nuclei, and the
$\gamma$-soft behavior is manifested in the observed low-lying
quasi-$\gamma$ bands. This region thus provides an excellent
opportunity to study the effect of rotation and quasiparticle
excitation on the top of $\gamma$-vibrations.
As the aligning neutrons and protons in these rotating systems are
occupying the same intruder orbit $1h_{11/2}$, the neutron and
proton quasiparticle (qp) alignment processes compete in this mass
region. In the majority of the nuclei in this mass region, the proton
alignment occurs earlier than the neutron alignment, which is well
described in the Woods-Saxon TRS framework \cite{Rj88,Wr95}.
However, the neutron alignment is observed to be delayed in many
cases, and the Woods-Saxon TRS analysis always under-predicts this
rotational alignment. There have been other intriguing observations
in this mass region. One problem is in the g-factor measurement in
$^{134}$Ce for the lowest two $I=10$ states, which lie very close to
each other. The issue is that both of these states are shown to have
a neutron character \cite{Ze82} and since these $I=10$ states are
considered to be the bandheads of 2-qp bands, two 2-quasineutron
band structures are observed in $^{134}$Ce. This is quite surprising
as normally lowest-lying two 2-qp states should belong to
2-quasineutron and 2-quasiproton states.
Thus, with the collective and quasiparticle excitations coexisting
in the complex low-lying spectrum in these $\gamma$-soft nuclei, it
is desirable to have a microscopic method that can handle all these
degrees of freedom self-consistently. The early version \cite{SH99}
of the triaxial projected shell model (TPSM) adopted the
triaxially deformed qp vacuum configuration and performed
three-dimensional angular momentum projection. It was shown
\cite{YS02} that one can use this simple configuration to produce
collective multi-phonon $\gamma$-vibrational bands at low spin
states. In this earlier version, mixing with quasiparticle
excitations was neglected and, therefore, it cannot describe
excitation of quasiparticles in a triaxially deformed mean field.
This limitation has been relaxed in our recent development
\cite{Ja08} and the TPSM quasiparticle space for even-even systems
has been considerably extended by inclusion of many 2- and 4-qp
configurations. In a parallel work, a similar extension was done for
odd-odd nuclei \cite{Gao06}. These new developments provide a
suitable shell-model framework to investigate, microscopically, the
current topical issues in nuclear structure that are related to
triaxiality, such as the problem of $\gamma$-bands built on
multi-quasiparticle configurations, discussed in the present work.
They are also applicable to the problems related to the wobbling
motion and to the so-called chiral doublet band structures, which
will be the focus of our future investigations.
The purpose of the present work is to demonstrate that the
traditional picture of $\gamma$-vibration in deformed nuclei, based
on the ground-state configuration, can be generalized to the case of
multi-qp configurations. In the TPSM description, projected states
with $K=0$, 2, and 4 from the 0-qp configuration correspond to
ground, $\gamma$-, and $2\gamma$- bands \cite{YS02}. Similar to
these $\gamma$- and $2\gamma$- bands built on the ground state, new
multi-phonon $\gamma$-bands are based on multi-qp states. For the
multi-qp bands, projection with different $K$-values will correspond
to qp-excited $\gamma$-bands. In particular, we shall show that the
projected $K=1$ and 3 configurations originating from the same
intrinsic neutron 2-qp configuration correspond to the two $I=10$
states observed in $^{134}$Ce. This provides a plausible explanation
to the early observation of the $I=10$ states in this nucleus with
similar intrinsic structure.
The paper is organized as follows: In Section 2, we outline some
basic elements of the TPSM approach. For more details about TPSM, we
refer the reader to ref. \cite{Ja08} and references cited therein. In
Section 3, calculations and discussions on neutron-deficient Ce and
Nd isotopes are presented. Finally in Section 4, we summarize the
present work.
\section{Outline of the Theory}
The extended TPSM qp basis \cite{Ja08} consists of
(angular-momentum) projected qp vacuum (0-qp state), two-proton
($2p$), two-neutron ($2n$), and 4-qp states, i.e.,
\begin{equation}
\{ \hat P^I_{MK}\left|\Phi\right>, \hat P^I_{MK}~a^\dagger_{p_1}
a^\dagger_{p_2} \left|\Phi\right>, \hat P^I_{MK}~a^\dagger_{n_1}
a^\dagger_{n_2} \left|\Phi\right>, \hat P^I_{MK}~a^\dagger_{p_1}
a^\dagger_{p_2} a^\dagger_{n_1} a^\dagger_{n_2} \left|\Phi\right>
\}, \label{basis}
\end{equation}
where the three-dimensional angular-momentum-projection operator is
\begin{equation}
\hat P^I_{MK} = {2I+1 \over 8\pi^2} \int d\Omega\,
D^{I}_{MK}(\Omega)\, \hat R(\Omega), \label{PD}
\end{equation}
with the rotation operator $\hat R(\Omega) = e^{-\imath \alpha \hat
J_z} e^{-\imath \beta \hat J_y} e^{-\imath \gamma \hat J_z}$.
$\left|\Phi\right>$ in (\ref{basis}) is the triaxially-deformed qp
vacuum state. The qp basis chosen above is adequate to describe high-spin
states up to $I\sim 20\hbar$ for nuclei considered in this
work. In the present analysis we shall, therefore, restrict our
discussion to this spin regime.
It is important to note that for the case of axial symmetry, the qp
vacuum state has $K=0$ \cite{KY95}, whereas in the present case of
triaxial deformation, the vacuum state is a superposition of all
possible $K$-values. Rotational bands with the triaxial basis
states, Eq. (\ref{basis}), are obtained by specifying different
values for the $K$-quantum number in the angular-momentum projector
in Eq. (\ref{PD}). The allowed values of the $K$-quantum number for
a given intrinsic state are obtained through the following symmetry
consideration. For $\hat S = e^{-\imath \pi \hat J_z}$, we have
\begin{equation}
\hat P^I_{MK}\left|\Phi\right> = \hat P^I_{MK} \hat S^{\dagger} \hat S
\left|\Phi\right> = e^{\imath \pi (K-\kappa)}
\hat P^I_{MK}\left|\Phi\right>,
\end{equation}
where $\hat S\left|\Phi\right> = e^{-\imath \pi
\kappa}\left|\Phi\right>$. For the self-conjugate vacuum or 0-qp
state, $\kappa=0$ and, therefore, it follows from the above equation
that only $K=$ even values are permitted for this state. For 2-qp
states, $a^\dagger a^\dagger \left|\Phi\right>$, the possible values
for $K$-quantum number are both even and odd, depending on the
structure of the qp state. For example, for a 2-qp state formed from
the combination of the normal and the time-reversed states $\kappa =
0$, only $K$ = even values are permitted. For the combination of the
two normal states, $\kappa=1$ and only $K=$ odd states are permitted.
As in the earlier projected shell-model calculations, we use the
pairing plus quadrupole-quadrupole Hamiltonian \cite{KY95}, with a
quadrupole-pairing term also included:
\begin{equation}
\hat H = \hat H_0 - {1 \over 2} \chi \sum_\mu \hat Q^\dagger_\mu
\hat Q^{}_\mu - G_M \hat P^\dagger \hat P - G_Q \sum_\mu \hat
P^\dagger_\mu\hat P^{}_\mu.
\label{hamham}
\end{equation}
It has been shown by Dufour and Zuker \cite{Dufour96} that these
interaction terms simulate the essence of the important correlations
in nuclei and even the realistic force has to contain, at least,
these basic components implicitly in order to work successfully in
the structure calculations. Some large-scale spherical shell-model
calculations \cite{HK99} also adopt this type of interaction.
The triaxially deformed single-particle basis is obtained from the
Nilsson model \cite{Ni69}. The corresponding triaxial Nilsson
mean-field Hamiltonian is given by
\begin{equation}
\hat H_N = \hat H_0 - {2 \over 3}\hbar\omega\left\{\epsilon\hat Q_0
+\epsilon'{{\hat Q_{+2}+\hat Q_{-2}}\over\sqrt{2}}\right\},
\label{nilsson}
\end{equation}
in which $\epsilon$ and $\epsilon'$ specify the axial and triaxial
deformation, respectively. $\epsilon$ and $\epsilon'$ are related to
the conventional triaxiality parameter by $\gamma =$
tan$^{-1}(\epsilon'/\epsilon)$. In (\ref{nilsson}), $\hat H_0$ is
the spherical single-particle Hamiltonian, which contains a proper
spin-orbit force \cite{Ni69}. The interaction strengths in
(\ref{hamham}) are taken as follows: the $QQ$-force strength $\chi$
is adjusted such that the physical quadrupole deformation $\epsilon$
is obtained as a result of the self-consistent mean-field HFB
calculation \cite{KY95}. The monopole pairing strength $G_M$ is of
the standard form
\begin{equation}
G_M = {{G_1 - G_2{{N-Z}\over A}}\over A} ~{\rm for~neutrons,}~~~~
G_M = {G_1 \over A} ~{\rm for~protons.} \label{pairing}
\end{equation}
In the present calculation, we take $G_1=20.82$ and $G_2=13.58$,
which approximately reproduce the observed odd-even mass difference
in the mass region. This choice of $G_M$ is appropriate for the
single-particle space employed in the model, where three major
shells are used for each type of nucleons ($N=3,4,5$ for both
neutrons and protons). The quadrupole pairing strength $G_Q$ is
assumed to be proportional to $G_M$, and the proportionality
constant being fixed as 0.18.
\section{Results and Discussion}
\begin{table}[t]
\caption{Axial and triaxial quadrupole deformation parameters
$\epsilon$ and $\epsilon^\prime$ employed in the TPSM calculation
for $^{128-134}$Ce and $^{132-138}$Nd isotopes. The corresponding
conventional triaxiality parameter $\gamma$ (in degree) is also
given.}
\begin{tabular*}{105mm}{@{\extracolsep{\fill}}cccc|cccc} \hline\hline
Ce nuclei & $\epsilon$ & $\epsilon'$ & $\gamma$ & Nd nuclei &
$\epsilon$ & $\epsilon'$ & $\gamma$ \\
\hline $^{128}$Ce & 0.250 & 0.120 & 26 & $^{132}$Nd & 0.267 & 0.120 & 24 \\
\hline $^{130}$Ce & 0.225 & 0.120 & 28 & $^{134}$Nd & 0.200 & 0.120 & 31 \\
\hline $^{132}$Ce & 0.183 & 0.100 & 29 & $^{136}$Nd & 0.158 & 0.110 & 35 \\
\hline $^{134}$Ce & 0.150 & 0.100 & 34 & $^{138}$Nd & 0.170 & 0.110 & 33 \\
\hline\hline
\end{tabular*}
\end{table}
\begin{figure}[htb]
\includegraphics[totalheight=8cm]{fig134nd03.eps}
\caption{(Color online) Calculated projected energy-surfaces for the
low spin states in $^{134}$Nd. } \label{fig1}
\end{figure}
TPSM calculations have been performed for four even-even isotopic chains
of $^{128-134}$Ce and
$^{132-138}$Nd nuclei.
As already mentioned in the introduction, the main emphasis of the
present work is to perform a detailed investigation of the yrast-
and $\gamma$-bands beyond the first band crossing. The above-mentioned
nuclei were chosen as they have well-developed
$\gamma$-bands observed experimentally and for some of them up to
high spins. The input parameters in the calculation are the
deformation parameters $\epsilon$ and $\epsilon'$, which are given
in Table 1. The corresponding conventional triaxiality parameter
$\gamma$ (in degree) is also given. The quadrupole deformation
$\epsilon$ in the table are those of M\"oller and Nix \cite{Mn95}
(with exception for $^{138}$Nd, see discussion below) and the
triaxiality parameter $\epsilon'$ have been calculated from the
projected potential energy surface. In Fig. 1, we provide one
example from such calculations, in which projected energies as
functions of $\epsilon'$ for a fixed $\epsilon$ ($\epsilon=0.2$ in
the $^{134}$Nd case) are plotted for the low spin states. In this
figure, the $\gamma$-soft nature of the nucleus is clearly seen
since the curves are all flat with triaxiality, specially for
$\epsilon' > 0.08$. As shown in the inset in Fig. 1, a minimum in
the projected ground-state energy is present at $\epsilon'\approx
0.12$. Thus, projected ground-state energies have been calculated
for a range of $\epsilon'$ values, and the value which gives rise to
the minimum energy is used in all further TPSM calculations. We
would like to mention that in one of the studied nuclei, $^{138}$Nd,
ref. \cite{Mn95} predicted a negative value of $\epsilon$
corresponding to an oblate deformation in its ground state, which is
in disagreement with all other neighboring nuclei. However, the TRS
calculation \cite{Liu08} for this nucleus indicates a large
triaxiality of $\gamma\approx 30^o$. In our calculation, we
therefore take a positive $\epsilon$ with a sizable $\epsilon'$ to
construct the basis.
\begin{figure*}[htb]
\includegraphics[totalheight=12.0cm]{theexptce.eps}
\includegraphics[totalheight=12.0cm]{theexptnd.eps}
\caption{(Color online) Comparison of experimental and
calculated band structures for $^{128-134}$Ce and $^{132-138}$Nd.
Data are taken from ref. \cite{Ep00} ($^{128}$Ce), \cite{Ce130}
($^{130}$Ce), \cite{Pa05} ($^{132}$Ce), \cite{Ce134} ($^{134}$Ce),
\cite{Nd132} ($^{132}$Nd), \cite{Cd96} ($^{134}$Nd), \cite{Od02}
($^{136}$Nd), and \cite{Es02} ($^{138}$Nd).} \label{fig2}
\end{figure*}
The calculations are performed in two stages. In the first step, the
projected states are obtained from the triaxially deformed qp states
by applying the three-dimensional angular-momentum projection
method. The projection is carried out for configurations constructed
from various intrinsic states close to the Fermi surface. We have
performed the angular-momentum projection for all the qp
configurations, which are built by considering the single-particle
states that are within 3 MeV from the Fermi surfaces. In the second
stage, the shell-model Hamiltonian, Eq. (\ref{hamham}), is
diagonalized with the projected states as the basis configurations.
The lowest three bands obtained after diagonalization for each
angular momentum are shown in Fig. 2 for all the studied Ce and Nd
isotopes. These bands have the main component from the 0-qp state
and, therefore, are collective bands in the low-spin regime.
Theoretical $K=0$ and $K=2$ bands are respectively compared to the
data of the yrast and $\gamma$-vibrational (one-phonon) bands, and
the $K=4$ bands are our prediction for possible 2$\gamma$
(two-phonon) bands. It can be seen that, overall, an excellent
reproduction for the known data has been achieved. In particular,
the experimental $\gamma$-band in $^{128}$Ce is well reproduced up
to the highest spin state studied in this work. The calculated
$\gamma$-band in $^{136,138}$Nd is predicted to lie very close in
energy to the yrast band, in agreement with known data, and the two
bands become nearly degenerate at high spins.
It is clearly noted in Fig. 2 that yrast bands for all studied
isotopes have two slopes, corresponding to crossings of bands with
two distinct configurations. The change in slope occurs at spin
$I=8$ or 10. This feature has been well described by the
calculation, for the isotopes $^{128,130}$Ce and $^{132}$Nd where
high-spin data exist. Furthermore, we observe that for the rest of
nuclei, i.e., $^{132,134}$Ce and $^{134,136,138}$Nd, the current
ground-band data are available only before the predicted onset of the
band-crossing at $I=10$. The first and second excited bands at
low-spins are predominantly composed of the collective $\gamma$ and
2$\gamma$ structures, but the high-spin states of these bands have
considerable mixing with the 2-qp states. The calculation also
predicts some energy staggerings in the $\gamma$- and 2$\gamma$-
bands. The staggering divides a rotational band with $\Delta I=1$
into two branches with $\Delta I=2$. In the isotopes
$^{128,130,132}$Ce where high-spin data of the $\gamma$-band are
known, we see that the experimental bands actually belong to one of
the branches of the staggering $\gamma$-bands, namely the
energetically favored one with even spins. The present calculation
further predicts some irregularities in the staggering of $\gamma$-
and 2$\gamma$- bands due to band mixing (e.g. staggering appears in
a certain spin range but diminishes at high spins). We hope that our
results can serve as a guidance for future experiments to identify
$\gamma$- and 2$\gamma$- bands in this mass region.
To extract structure information from the calculation, it is useful
to discuss the energies in terms of band diagrams \cite{KY95}. A
band diagram is an ensemble of projected band energies for intrinsic
configurations, i.e., the diagonal matrix elements before band
mixing. It usually shows crossings of various bands where some
prominent phenomena may take place, and therefore plays a central
role in the interpretation of numerical results. One must keep track
of the configurations of each band when plotting a band diagram. As
already mentioned, with the triaxial basis, the intrinsic states do
not have a well-defined $K$ quantum number. Each triaxial
configuration in (\ref{basis}) is a composition of several $K$
values, and bands in band diagrams are obtained by assigning a given
$K$ value in the projection operator. As in ref. \cite{Ja08}, we
denote a $K$ state of an $i$ configuration as $(K, i)$, with $i = 0,
2n, 2p$, and 4. For example, $K = 0$ state of the 0-qp configuration
is marked as (0, 0) and $K = 1$ of the $2n$-qp configuration as $(1,
2n)$.
\begin{figure*}[htb]
\includegraphics[totalheight=12cm]{bandce_1.eps}
\includegraphics[totalheight=12cm]{bandce_2.eps}
\caption{(Color online) Band diagrams for $^{128-134}$Ce isotopes.}
\label{fig3}
\end{figure*}
Band diagrams of the studied cerium isotopes from $A=128$ to 134 are
presented in Fig. 3. For $^{128,130}$Ce, the $(2,0)$ bandhead energy
is approximately 0.8 MeV and the $(4,0)$ bandhead is slightly
below 2 MeV. Further, in both nuclei, the $2p$ bandhead is slightly
at a lower excitation energy than the $2n$ bandhead, and due to this
difference, the $2p$ band crosses the ground band earlier than the
$2n$ band. The $2p$ band, $(1,2p)$ crosses the ground band $(0,0)$
in both nuclei at $I= 10$ and the proton structure of the first
crossing is validated by the systematics of the band-crossings
\cite{Rg89}. The g-factor measurement has been done for the $I=10^+$
state of $^{126}$Ce and has a very large value of 1.0, therefore
indicating that the first band-crossing is indeed due to the
alignment of protons for this nucleus. From the known experimental
result and from the systematics of the proton crossing as a function
of mass number, it was concluded in ref. \cite{Rg89} that
$^{128-132}$Ce have proton crossing occurring first.
The band diagrams in Fig. 3 depict $(2,0)$ and $(4,0)$ bandheads for
$^{132,134}$Ce at a similar excitation energy as that of lighter
Ce-isotopes. However, it is noted that the $2n$ bandhead is lower than
the $2p$ bandheads as compared to the $^{128,130}$Ce isotopes. Due
to this lowering of the neutron 2-qp band, the band-crossing
features in the two pictures on the right column in Fig. 3 are
qualitatively different from those of the left column. In
$^{132}$Ce, it is observed that the $2n$ state $(1,2n)$ and $2p$
state $(1,2p)$ become yrast at the same angular momentum of $I=10$
with the neutron band slightly lower than the proton band. However,
for higher angular momenta, the proton band is observed to be favored
in energy, and is yrast up to the highest spin value. For
$^{134}$Ce, the neutron-aligned band $(1,2n)$ crosses the ground
band $(0,0)$ at $I=8$, and this band is yrast up to $I=16$. Above
this spin value, it is noted that the 4-qp band $(2,4)$ with both
protons and neutrons aligned becomes favored.
\begin{figure*}[htb]
\includegraphics[totalheight=12cm]{bandnd_1.eps}
\includegraphics[totalheight=12cm]{bandnd_2.eps}
\caption{(Color online) Band diagrams for $^{132-138}$Nd isotopes.}
\label{fig4}
\end{figure*}
Band diagrams of the Nd isotopes are shown in Fig. 4. It is seen
that the $(2,0)$ and $(4,0)$ bandheads are, respectively, at 1 and 2
MeV excitation energy in $^{132}$Nd. The $2p$ aligned bandhead is
lower in energy than the $2n$ band with the result that the proton
band $(1,2p)$ crosses the ground band $(0,0)$ at $I=12$, and becomes
yrast for all the spin values above it. For $^{134}$Nd, the $2n$
bandhead is now lower in energy than the $2p$ one, and at $I=10$
both these aligned bands cross the ground band and it is, therefore
expected that this nucleus should depict forking of the ground state
band into two s-bands. Above the band-crossing region in $^{134}$Nd,
the yrast even-$I$ states originate from the $(1,2p)$ and the
odd-$I$ states arise from the $(3,2p)$ band. The lowest two bands
above $I=12$ originate from the same $2p$ states and, therefore,
will have positive g-factors, opposite to that of the $^{134}$Ce
case.
For $^{136,138}$Nd in Fig. 4, the $\gamma$-bands are very close to
the yrast line. In $^{136}$Nd, the band-crossing occurs at $I=8$,
and for $^{138}$Nd it is at $I=10$. In both nuclei, proton- and
neutron-aligned bands cross the ground band and, therefore, it is
expected that both nuclei should show forking of the ground state
band into two s-bands. Further, it is noted that in $^{138}$Nd the
$(3,2p)$ band is also very low in energy and is the first excited
band above $I=10$ for even-spin states. For odd-spin states, it
forms the yrast band.
In the mass region under investigation, there have been observations
of high-spin states at low excitation energies. We previously
mentioned $^{134}$Ce as a particular example where two lowest $10^+$
states were detected at excitation energy 3.2086 MeV and 3.7193 MeV,
respectively. In Fig. 5, we collect all the experimentally known
$10^+$ states for nuclei studied in this paper. At first glance,
these could be bandheads of some multi-qp bands associated with
high-$K$ configurations. However, a close look indicates that there
are no such high-$K$ configurations available around the Fermi
surfaces. From our band diagrams shown in Figs. 3 and 4, we see that
in nuclei with $N=76$ and 78, more than one band crosses the ground
band at $I=10$. The crossing bands are not high-$K$ bands, but bands
having low-$K$ configurations.
\begin{figure}[t!]
\includegraphics[totalheight=14cm]{alk_theexptcend.eps}
\caption{(Color online) Four theoretical bands with the main
component from $(1,2n)$, $(1,2p)$, $(3,2n)$, and $(3,2p)$,
respectively. Only the spin range from $I=10$ to 20 is shown in
which these bands are low in energy. Available data in
$^{132,134}$Ce and $^{134,136,138}$Nd are compared with the
calculation.} \label{fig5}
\end{figure}
The two $I=10^+$ states in $^{134}$Ce were long ago identified
experimentally. However, the structure of these $10^+$ states
remained a puzzle. The magnetic moment of both states has been
measured, and it has been found that both have negative g-factors
\cite{Ze82}. This suggests that both the $10^+$ states have a
neutron structure. This was a surprising finding because normally
two lowest-lying 2-qp states should separately belong to
2-quasineutron and 2-quasiproton states. In ref. \cite{Rg89}, an
explanation was proposed. Now looking at our Fig. 3, one can easily
see that in $^{134}$Ce, apart from the 2$n$ band $(1,2n)$ and the
2$p$ band $(1,2p)$, the $\gamma$-band built on the $2n$ band
$(3,2n)$ also crosses the ground band $(0,0)$ at $I=10$. Thus at
$I=10$, there are at least three states below that of the ground
band, which are (from lower to higher energies) $(1,2n)$, $(3,2n)$,
and $(1,2p)$. It is very interesting that for this nucleus, the
neutron 2-qp band based on $\gamma$-vibration $(3,2n)$ is predicted
to appear lower in energy than the proton 2-qp band $(1,2p)$.
Therefore, the lowest two $I=10^+$ states, one being a 2-qp state
built on the ground state and the other a 2-qp state on the
$\gamma$-vibration, have both neutron configuration. This is
consistent with the g-factor measurement \cite{Ze82}, and thus
naturally explains the structure of the two $10^+$ bands.
\begin{figure}[t!]
\includegraphics[totalheight=10cm]{theexptCeNd.eps}
\caption{(Color online) Level schemes for $^{132}$Ce and $^{134}$Nd.
Comparison between the calculated levels and experimental data is
made for four bands: the yrast bands, the $\gamma$ bands, and the
$I=10^+$ 2-qp bands based on $\gamma$ vibration.} \label{fig6}
\end{figure}
Fig. 5 summarizes the results regarding the theoretical $\gamma$-
bands built on 2-qp states obtained after diagonalization of the
shell-model Hamiltonian. The calculated bands associated with the
four most relevant and dominant states are displayed: (1) $(1,2n)$,
the 2-qp neutron $K=1$ state built on the qp vacuum state; (2)
$(1,2p)$, the 2-qp proton $K=1$ state on the vacuum state; (3)
$(3,2n)$, the 2-qp neutron $K=3$ state on the collective
$\gamma$-vibration; and (4) $(3,2p)$, the 2-qp proton $K=3$ state on
the $\gamma$-vibration. Only even spin members (energetically
favored) of each band are shown and compared with available data. It
is quite interesting to note that the relative position of the four
bands varies in each nucleus. We have discussed the case of
$^{134}$Ce where the lowest two are both neutron states. From Fig.
5, our calculation further predicts that in $^{136,138}$Nd, one may
observe two lowest $I=10^+$ states but with a proton structure. The
g-factor measurement in these two nuclei is expected to lead to
large, positive values, in sharp contrast to those in $^{134}$Ce.
Finally, in order to depict the comparison between the experimental
and theoretical energies more clearly, we plot in Fig. 6 the
calculated and experimental level energies for the yrast bands, the
$\gamma$ bands, and the $I=10^+$ 2-qp bands based on $\gamma$
vibration. We have chosen two nuclei, $^{132}$Ce and $^{134}$Nd, as
examples and the results are similar for other studied nuclei. It is
quite evident from this figure that not only the levels within each
band, but also the relative positions of the bands, are reasonably
well reproduced by the TPSM approach.
\section{Summary}
The results presented in this work suggest that multi-qp states in a
triaxially deformed well can exhibit much more fruitful band
structures. This is because with triaxiality, a single configuration
contains a rich mixture of many possible $K$-states and after
angular momentum projection, each one of them corresponds to a
rotational band. It was pointed out in ref. \cite{YS02} that the
projected triaxial vacuum state alone can already produce the
collective ground state band, $\gamma$-band, 2$\gamma$-band, etc.
Similarly, a projected 2-qp state can give rise to 2-qp bands with
$K=1,3,5,\cdots$. If the $K=1$ band is a 2-qp band based on the
ground state, then the $K=3$ band can be understood as a 2-qp band
based on the $\gamma$- vibration, and the $K=5$ band as a 2-qp band
based on the 2$\gamma$ state, etc. This pattern can be clearly seen
when multi-qp configurations constructed from a triaxially deformed
well are projected on good angular momentum. The picture thus
extends the simple surface $\gamma$ oscillation in deformed nuclei
where paired nucleons vibrate coherently in the deformed vacuum
state.
Summarizing the present work, multi-qp band structures in some
neutron-deficient Ce and Nd isotopes has been studied using the
extended triaxial projected shell-model approach. It has been
demonstrated that $\gamma$-band built on the 2-qp configurations can
modify the band-crossing features in these nuclei. The 2-qp
$\gamma$-band with $K=3$ are shown to be energetically favored for
some angular-momentum states and form the first excited bands in
nuclei studied in the present work. For $^{134}$Ce, it is shown that
the lowest two $I=10^+$ states originate from the same
2-quasineutron configuration and sheds new light on the observation
of negative g-factors for the two states. Further, it is predicted
that the lowest two $I=10^+$ states in $^{136,138}$Nd originate from the
same $2p$ configuration and both these states should have positive
g-factors. The present results have enriched the concept of
$\gamma$-vibration and we hope that, in the future, more states of such
kind will be identified experimentally.
\section{Acknowlegments}
Research at ORNL is supported by the Division of Nuclear Physics,
U.S. Department of Energy, under Contract DE-AC05-00OR22725 with
UT-Battelle, LLC. Research at SJTU is supported by the National
Natural Science Foundation of China under contract No. 10875077 and
by the Chinese Major State Basic Research Development Program
through grant 2007CB815005.
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\section{Introduction}\label{introduction}}
\nohyphens{\texttt{SemanticModels.jl}}{} facilitates several metamodeling tasks by detecting and exploiting the implicit relationships between the semantically rich, natural language-based representations of scientific knowledge found in academic papers, and the relatively semantically sparse, but modular, precise representations found in code.
We represent this knowledge with categories and support metamodeling tasks that may be exploratory, iterative, and/or inter-disciplinary in nature.
Our theoretical contributions form the basis for analyzing the metamodeling tasks scientists perform, and our software can augment scientific workflows to assist scientists in their day to day work.
\paragraph{Motivation}
Progress in science often comes from adapting and extending models from prior work(s) to address new problems, but current scientific research workflows make leveraging components from existing workflows difficult.
This is due in part to the fact that modern scientific inquiry often lends itself to highly tailored, procedural scripts that are primarily intended to produce and record results, with less attention on software engineering best practices~\cite{deelman2017, wilson2014}.
Scientific code contains a large amount of sophisticated domain knowledge that is known to the author(s), but is not explicitly represented in the code, and is therefore not always clear to a reader or user.
Such semantic modeling information includes principles, rules, and constraints imposed by the physical phenomena being modeled.
For example: (1) stochastic systems are modeled with probability values, which are constrained to be between 0 and 1; (2) physical measurements have units and must obey the laws of dimensional analysis, which prohibits computation such as $3m + 4m/s$; and (3) signal processing algorithms must treat time domain and frequency domain signals differently, even though they are both represented by arrays of floating point numbers. This work is grounded in the belief that a framework that augments scientific workflows without requiring a wholesale reimplementation in a domain specific language is most effective for real world application by scientists.
\paragraph{Significance}
As computational models of physical, biological, and engineered systems grow increasingly sophisticated, program analysis tools must be able to understand and manipulate these models.
We introduce a formalism to study the augmentation of scientific modeling code.
These ideas are implemented in a software package for analyzing and manipulating models written in the Julia programming language~\cite{doi:10.1137/141000671}.
The Julia language is ideal for this problem because it is widely used in scientific computing and includes a capable type system with multiple dispatch.
The Julia type system can encode information about model semantics so that the compiler can understand, enforce, and manipulate these semantics.
These manipulations are studied in the context of epidemiological models, but are broadly applicable to both agent-based and differential equation-driven simulations, as well as statistical and machine learning models.
\section{Body}\label{methodology}}
\paragraph{Theoretical Foundations}
We begin by presenting a formal framework that can be used to represent and reason about these different metamodeling use cases.
We then provide examples from epidemiology to illustrate how this framework, and the associated semantic knowledge graph construction process, can be applied to augment real-world scientific workflows~\cite{epirecipes}.
Our motivation for focusing on epidemiology is twofold: the associated literature demonstrates the use of a shared model structure with many variations.
Furthermore, the math represented therein spans both discrete and continuous systems of equations, and is solved by a diverse set of algorithms.
Scientific programmers represent models at three levels: (1) as a set of domain concepts understood by the developer, but not explicitly stated or encoded; (2) as code implementations in a high-level language; and (3) as an executable program compiled or interpreted on a specific computer system.
We study representations of programs that span level 1 and 2 as categories that represent the knowledge of scientists as expressed in code.
\begin{figure}[hbtp]
\centering
\includegraphics[width=0.9\textwidth]{img/olog_sir.png}
\caption{Ologs can be used to represent the structure of scientific models without the mathematics. Objects are represented by nouns and relationships between objects are represented with verbs.}\label{fig:olog}
\end{figure}
A model \(M=(D,R,f)\) is a tuple containing a set \(D\), the domain, and a set \(R\), the co-domain, with a function \(f:D\mapsto R\).
If \(D\) is the cross product of sets \(D_1 \times D_2 \cdots D_k\), then \(f = f(x_1\dots x_k)\), where \(x\) are the independent variables of \(M\).
If \(R=R_1 \times R_2 \cdots R_d\), then \(R_i\) are the dependent variables of \(M\).
What is intuitively \emph{the same model} can be represented in several different categories.
Each representation considers different aspects of the model's structure.
For example, Figure~\ref{fig:olog} shows the SIR model in the category of ontology logs (ologs), and Figure~\ref{fig:type_ambig} shows the same model in the category of programs.
\begin{figure}[tbh!]
\begin{center}
\begin{subfigure}[tbh!]{0.49\textwidth}
\includegraphics[width=\textwidth]{img/types_sir.png}
\caption{}
\label{fig:type_ambig}
\end{subfigure}
\begin{subfigure}[hbt]{0.49\textwidth}
\includegraphics[width=\textwidth]{img/types_sir_unambig.png}
\caption{}
\label{fig:type_unambig}
\end{subfigure}
\caption{\ref{fig:type_ambig} Type diagram of the SIR model. The red arrows and boxes show that \texttt{Vector\{Float\}} is reused for two semantically different types. \ref{fig:type_unambig} Type diagram of the SIR model with ambiguity resolved by introducing the \texttt{Params} and \texttt{Initial} types. Some type names are abbreviated for clarity i) Int, v) Vector\{Int\}, and vv) Vector\{Vector\{Int\}\}. Functions names starting with a \texttt{"."} are struct field lookups in Julia.}
\label{fig:modeltypes}
\end{center}
\end{figure}
The parsimonious formalization of what constitutes a valid transformation, or set of rules for modifying or combining models, requires us to assess not only mathematical and programmatic behavior of the system, but also the extent to which the resulting set of models are internally consistent and reflective of domain-specific scientific facts.
We address this with multiple representations of program semantics that capture different types of model structure.
A Category $C$ is a set of objects and morphisms, which are structure-preserving functions between the objects.
Common examples of categories include the category of all groups, the set of all finite graphs, and the set of all finite preorders~\cite{Spivak:2014:CTS:2628001}.
Ologs are a diagrammatic approach to formalizing scientific knowledge used to precisely specify a conceptual model of a phenomenon or experiment~\cite{10.1371/journal.pone.0024274}.
An olog is composed of types (boxes) and aspects (edges).
Figure~\ref{fig:olog} represents the susceptible-infected-recovered (SIR) model as an olog.
All programs in a strongly typed language have a set of types and functions that map values between those types.
For example, the Julia program: \texttt{a = 5.0; b = 1; c = 2*a; d = b + c;} has the types \texttt{\{Int, Float\}} and functions \texttt{\{*, +\}}, which are both binary functions.
These programs can be represented as a category, where the objects are the types and the morphisms are the functions.
We refer to the input type of a function as the domain and the output type as the codomain of the function.
Multi-argument functions are represented with tuple types representing their arguments.
For example\footnote{The \texttt{a::A} operator in Julia asserts that the value of \texttt{a} is an instance of type \texttt{A}} \texttt{{+}(a::Int,b::Int)::Int} is a function ${+}: Int\times Int \to Int$.
These type categories are well studied in the field of functional programming.
We apply these categories to the study of mathematical models.
There is a spectrum between conceptual knowledge and compiler knowledge, with ologs lying toward the conceptual end and compiler dataflow graphs at the programmatic end.
Functional programming and category theory are intertwined and base the analysis of programs on the types and functions used in the program~\cite{Wadler:1992:EFP:143165.143169}.
\nohyphens{\texttt{SemanticModels.jl}}{} implements a dynamic analysis tool to extract the runtime type information for every function.
That is, to build a graph where the nodes are types and the edges are functions, where a function $f$ connects types $T,U$ if $T$ is the type of $f$'s arguments and $U$ is the type of $f$'s output values as expressed in \path{julia}{} syntax, \texttt{f(x::T)::U}.
This theoretic approach enables reasoning over the semantics of programs.
The most salient consequence of programming language theory is that the more information a programmer can encode in the type system, the more helpful the programming language can be for improving performance, quality, and correctness.
Haskell programmers often use the type system to encode program semantics to improve software quality~\cite{manzino2014}.
\nohyphens{\texttt{SemanticModels.jl}}{} uses the type system to encode model semantics to improve understanding, adaptability, and extensibility of the modeling code.
Category theory provides a natural vehicle for expressing this information.
\paragraph{Semantic Integrity of Modeling Programs}
Model developers use conventions to encode semantic constraints into their code -- for example, prefacing all variables that refer to time with a \texttt{t\_}, such as \texttt{t\_start, t\_end}.
This semantic constraint that all variables named \texttt{t\_} are temporal variables is not encoded in the type system.
Behavioral subtypes are one way of encoding such information, but they are not widely used in scientific computing.
Another example is that vectors of different lengths are incompatible in the context of arithmetic operations.
In a compartmental model, the number of initial conditions must match the number of compartments.
For example in an SIR model, there are 3 initial conditions, $[S,I,R]$, and there are 2 parameters $[\beta, \gamma]$.
Computational systems employed by scientists will use a runtime check on dimensions to detect malformed linear algebra~\footnote{Julia, Scientific Python, and Matlab use run time checks, the C++ library \href{https://eigen.tuxfamily.org/dox/group__TutorialMatrixArithmetic.html}{Eigen} supports both static and dynamic dimension verification}.
Scientists rely on this limited form of semantic integrity checking provided by the language.
In contrast, \nohyphens{\texttt{SemanticModels.jl}}{} is intended to rigorously apply such integrity checking across the modeling ecosystem.
Our goal is to encode the maximum amount of information from scientific codes into the type system, where algorithms can analyze the integrity of programs in the language of categories.
For example, if there are types $S,T$ and functions $f,g: S\rightarrow T$ such that $Codom(f) = Codom(g)$ but $Range(f) \cap Range(g) = \emptyset$, then we say that the types are \emph{ambiguous}.
In order to more fully encode program semantics into the type system, the programmer (or an automated system) should introduce new types into the program to represent these disjoint subsets.
Category theory shows both why this is a problem for program analysis\footnote{If model transformations are represented as functors in this category, this form of ambiguity prevents the type system from enforcing semantic correctness of model transformations} and how to solve it with \emph{union types}.
Returning to the SIR model example, Figure~\ref{fig:modeltypes} shows how the \texttt{.param} and \texttt{.initial} functions both map \texttt{Problem} to \texttt{Vector\{Float\}} but with disjoint ranges.
The mathematics of the model dictate that parameters and initial conditions have different dimensions and are thus incompatible vectors.
Any program analysis of the model will be hampered by the ambiguity introduced by using the same type to represent two different concepts.
The functions \texttt{.first} and \texttt{.second}, which provide the beginning and end of the time domain of the system, have overlapping ranges and are comparable as times.
This is an example of how programming language ideas can improve the analysis of computational models.
\paragraph{Program Analysis of Models} Static program analysis provides direct access to the function call graph; however, inferred types and runtime values require dynamic analysis.
To do this, we inject metadata collection statements into each program's AST, so that when the AST is evaluated, we are able to dynamically capture variable assignments and function calls.
In practice, scientists prefer dynamic languages that facilitate faster development, but they are challenging for static analysis techniques.
Julia provides a hybrid of static compilation and dynamic execution that is amenable to rapid development, prototyping, and program analysis.
\begin{figure}[bth]
\centering
\begin{subfigure}{0.4\textwidth}
\centering
$ f(a,b) = 2\cdot(a * b) $
\end{subfigure}~
\begin{subfigure}{0.6\textwidth}\centering
$ g(a,b) = 2\cdot(a/b) $
\end{subfigure}
\begin{subfigure}{0.4\textwidth}\centering
\begin{tikzcd}
Z\times Z \arrow[d, "*", olive] \arrow[d, bend right, "\pi_1"] \arrow[d, bend left, "\pi_2"]
\\ Z \arrow[loop right, "2\times", blue]
\end{tikzcd}
\end{subfigure}~
\begin{subfigure}{0.59\textwidth}\centering
\begin{tikzcd}
Z\times Z \arrow[r, "/", olive] \arrow[d, bend right, "\pi_1"] \arrow[d, bend left, "\pi_2"]
& R\oplus \texttt{Error} \arrow[loop right, "2\times", blue] \\
D
\end{tikzcd}
\end{subfigure}
\caption{Programs with the same structure admit a fully faithful functor from one to the other. In this case the functor is shown with color identifying which functions are mapped to each other. The objects are types and the morphisms are functions (subroutines). The morphisms $\pi_i$ represent the projection functions that select the $i$th element from a tuple.}\label{fig:arithcat}
\end{figure}
Model augmentation refers to the set of metamodeling programs where a scientist takes a model, \(M\), and a transformation, \(T\), and uses the transformation to construct a new model, \(T(M)\).
In complex, high performance modeling and simulation software, these changes can be very labor intensive.
To facilitate the identification of program components that are good candidates for modification, \nohyphens{\texttt{SemanticModels.jl}}{} provides a bundle of tools that rely on Julia metaprogramming (e.g., expression manipulation via Lisp-style macros) to modify programs for the purpose of dynamic information extraction.
Model augmentation is implemented via program transformations. Figure~\ref{fig:arithcat} illustrates how programs can be represented as categories and transformations between those programs are functors. Many families of mathematical and scientific models have a separation between structure and values.
For example, in dynamical systems and reaction networks, there is the structure of the equations and then the specific rate parameters.
Representing programs as cateogries and transformations can exploit this notion of ``same structure, but different values'' across a wide class of models.
The simple example in Figure~\ref{fig:arithcat} shows how properties of the functor between two models tell use about the relationship between those two models.
We can illustrate another example of this in a simple yet realistic agent-based model (ABM).
For example, an SIR model can be implemented as an ABM, as depicted in Figure~\ref{src:abm}.
This script defines a basic agent-based model of disease spread called SIRS.
Each agent is in one of 3 states: $S$ Susceptible, $I$ Infected, $R$ Recovered, and the agents transition between states.
By viewing model transformations as functors between model categories, we can implement model transformations that preserve structure while changing the behavior of the model (e.g. by adding or removing capabilities).
Our system includes the capability to add and remove states and change behaviors of the model, while capturing the nature of this change in a data structure, allowing users to probe the relationship between a set of models.
For example, the SIRS model does not have the structure necessary to model a fatal disease as there is no $D$ component, so a scientist would have to change the code.
By representing these changes as model transformations, we are able to add a new state, $D$ Dead, and the necessary transitions to enable the modeling of fatal diseases.
\begin{figure}[htb!]
\lstinputlisting{src/abm.jl}
\caption{A Simple ABM for a SIR modeling. The agents go from $S\mapsto I\mapsto R\mapsto S$ based on random numbers.
The probability of $S\mapsto I$ is dependent on the fraction of agents in state $I$.
The probability of recovering is a constant $\rho$, and the disease confers some temporary immunity with probability $\mu$.
The function definitions for \texttt{step!}, which advances the timesteps of the ABM, and \texttt{describe}, which computes summary statistics for downstream analysis, are omitted for space.}\label{src:abm}
\end{figure}
\begin{figure}[htbp]
\begin{subfigure}{.65\textwidth}
\includegraphics[width=0.98\textwidth]{img/exampletypegraph.png}
\caption{}\label{fig:typegrapha}
\end{subfigure}~
\begin{subfigure}{.32\textwidth}
\includegraphics[width=0.98\textwidth]{img/type_DFA.png}
\caption{}\label{fig:typegraphb}
\end{subfigure}
\begin{subfigure}{.85\textwidth}
\includegraphics[width=0.98\textwidth]{img/typegraphmorphism.png}
\caption{}\label{fig:typegraphc}
\end{subfigure}~
\caption{\ref{fig:typegrapha} The input typegraph of the code corresponding to Figure~\ref{src:abm}.
\ref{fig:typegraphb} The states of the agents as expressed in a typegraph.
\ref{fig:typegraphc} The typegraph of the code refactored to encode model semantics into the type system. Note $S,I,R$ are represented by the singleton types $Susceptible, Infected, Recovered$ respectively, and the colors show a graph homomorphism between the type graphs. The edges showing projection functions are dotted for visual clarity in the diagram, and the boxes labeled transition and distributions are identified as meaningful subgraphs of the program representing the agent-state transitions, and the calculation of population distribution respectively. }\label{fig:typegraph}
\end{figure}
Another type of model transformation includes refactoring models to introduce more structure into the program that can be exploited by program analysis techniques in the compiler.
One can transform the model shown in Figure~\ref{src:abm} by re-factoring the Symbol representation of the states into singleton types, and naming the anonymous functions as \texttt{transition}.
Figure~\ref{fig:typegraph} illustrates how a program transformation aimed at encoding model semantics into the type system can change the typegraph of the program.
The colors in Figure~\ref{fig:typegraph} show a graph homomorphism between the type graphs.
This homomorphism maps concepts from the new model to the old model.
This example illustrates another point: while we naturally think of \emph{model augmentation} as turning a simple model into a more complex model; when applying category reasoning, it is more convenient to think of a transformation $m' = t(m)$ as inducing a functor $\phi:m' \mapsto m$.
This functor, $\phi:m' \mapsto m$, takes a complex model and simplifies it, which provides an interpretation of $m'$ in terms of $m$.
Subsequently, we can also see how models can be represented in different categories, and the notions of category theory in those different contexts allow for different kinds of analysis of the models.
Specifically, Figure~\ref{fig:typegraph} shows a pair of models represented as graphs and a functor between them (graph homomorphism) that relate the types in one model to the types in the other model.
The nature of the functor is determined by the category used and the models' structure.
The program transformation shown in Figure~\ref{fig:typegraph} is best viewed as a refactoring, where the maintainability and robustness of a model was improved without changing its behavior as a mathematical function.
A typical model augmentation does change the behavior of the model as a mathematical function in order to add capabilities or adapt the model to a new physical phenomena.
Given an algorithmic mechanism for changing scientific models, the first question of any scientist will be, ``Which model should I use?'' This question is answered by model selection.
\FloatBarrier
\paragraph{Algebraic Model Selection} When model families are parameterizable by $\mathbb{R}^n$, statistical theory can show how to choose the best model using a regularization process.
Take, for example, polynomial regression: where data is represented by random variable(s).
Define $X\in\mathbb{R}^{n\times d}$ as the independent variables and $y\in \mathbb{R}^n$ as the dependent (target) variable. Polynomial least squares regression solves the optimization problem $\min_p \|y - p(X) \|_2$, where $p(X) = \sum_i \beta_i x^i$ and $\|\cdot\|_2$ is the two norm.
For model selection in polynomial regression, one must choose a polynomial degree and set of non-zero coefficients to define the model. Statisticians use the LASSO to select the best polynomial. LASSO is defined as $min_\beta \sum_j (\sum_i \beta_i x^i_j - y_j)^2 + \sum_i |\beta|$, where $j$ ranges over samples and $i$ ranges over polynomial terms.
Regularization generally works when the space of models can be parameterized by a continuous parameter, and the loss function can be modified to support the regularization penalty.
Meanwhile, for complex models, the space of possible models cannot be parameterized continuously.
Additionally, the inclusion of the regularization penalty often increases the complexity of the solver, because the difficulty of the optimization problem increases (eg, addition of LASSO regularization spoils the quadratic properties of the least squares problem).
Sparse polynomial regression (polynomials where the set of non-zero coefficients is small and known \emph{a priori}) is not continuously parameterizable and we need an algebraic perspective.
\begin{figure}[hbtp]
\centering
\footnotesize
\begin{subfigure}[b]{0.45\textwidth}
\begin{tikzcd}
& & \emptyset \ar[dl, "T_x"]\ar[dr, "T_1"]& \\
& T_x \ar[dl, "T_x"]\ar[d, "T_1"] & & T_1\ar[d, "T_x"]\ar[loop right, "T_1"] \\
T_xT_x \ar[d, "T_1"] & T_xT_1 \ar[d, "T_x"]\ar[loop right, "T_1"]&& T_1T_x \ar[dl, "T_x"]\ar[d, "T_1"] \\
T_xT_xT_1 & T_xT_1T_x & T_1T_xT_x & T_1T_xT_1
\end{tikzcd}
\caption{}\label{fig:monoid_ab}
\end{subfigure}~
\begin{subfigure}[b]{0.45\textwidth}
\begin{tikzcd}
&& & 1\ar[d, "T_x"]\ar[loop right, "T_1"]& \\
&& & x\ar[dl, "T_x"]\ar[d, "T_1"]& \\
&& x^2 \ar[dl, "T_x"]\ar[d, "T_1"] & x+1\ar[d, "T_x"]\ar[loop right, "T_1", distance=2em]& \\
& x^3 & x^2 + 1 & x^2 + x &
\end{tikzcd}
\caption{ }\label{fig:model_selection}
\end{subfigure}\caption{\ref{fig:monoid_ab} Monoid over $\{T_x,T_1\}$ with $T_1T_1=T_1$. \ref{fig:model_selection} Action of $T_x, T_1$ on polynomials.}\label{fig:6}
\end{figure}
The example of sparse polynomial regression model selection can be analyzed in terms of program transformations to illustrate our approach.
Let $M$ be a monoid with two generators, $T_x,T_1$ and one equation $T_1\dot T_1 = T_1$. The elements in this monoid are strings of these two symbols and the multiplication operation is concatenation. Define the action of $M$ on the set of \emph{formal polynomials} in $x$ by the action of the generators.
$T_x$ modifies a polynomial by multiplying by $x$, so that $T_x(p) = xp$ and $T_1$ modifies a polynomial by adding a constant term if it doesn't already exist $T_1(p) = p + 1$, where $1+1=1$.
The set of all polynomial regression models lie in the $M$-orbit of the constant polynomial $p(x) = 1$.
Figure~\ref{fig:6} shows how polynomial regression models can be derived as transformations with $M$.
This method of deriving more complex models from simple models can be generalized and implemented in highly generic software.
In our representation of models as categories and model augmentations as functors between those categories, there is always a model transformation monoid.
If that monoid is finitely generated, we can represent the space of possible transformations with a directed graph, analogous to a Cayley graph. And the set of possible models is the action of the transformation monoid on a \emph{base model}.
This monoidic representation can be further applied to combining models and statistical regression models into workflows using the ideas from Fong and Spivak~\cite{fong2018}.
By representing the workflow as a data structure and the code that defines a workflow as a model, we are able to recursively apply model augmentation and achieve workflow modification using the same tools, now operating on compositions of models.
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COPYRIGHT
ZONDERVAN
_Winter Blessings_
Copyright © 2019 by Amy Clipston
Requests for information should be addressed to:
Zondervan, _3900 Sparks Dr. SE, Grand Rapids, Michigan 49546_
ISBN: 978-0-310-35436-9 (e-book)
Library of Congress Cataloging-in-Publication
CIP data is available upon request.
All Scripture quotations, unless otherwise indicated, are taken from The Holy Bible, _New International Version®, NIV®._ Copyright © 1973, 1978, 1984, 2011 by Biblica, Inc™ Used by permission. All rights reserved worldwide. www.zondervan.com
Any Internet addresses (websites, blogs, etc.) and telephone numbers in this book are offered as a resource. They are not intended in any way to be or imply an endorsement by Zondervan, nor does Zondervan vouch for the content of these sites and numbers for the life of this book.
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means—electronic, mechanical, photocopy, recording, or any other—except for brief quotations in printed reviews, without the prior permission of the publisher.
Publisher's Note: This novel is a work of fiction. Names, characters, places, and incidents are either products of the author's imagination or used fictitiously. All characters are fictional, and any similarity to people living or dead is purely coincidental.
_Printed in the United States of America_
19 20 21 22 23 / LSC / 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1
CONTENTS
1. COPYRIGHT
2. CONTENTS
3. GLOSSARY
4. FAMILY TREE
5. CHAPTER 1
6. CHAPTER 2
7. CHAPTER 3
8. CHAPTER 4
9. CHAPTER 5
10. CHAPTER 6
11. CHAPTER 7
12. CHAPTER 8
13. DISCUSSION QUESTIONS
14. ACKNOWLEDGMENTS
15. ABOUT THE AUTHOR
# Guide
1. Cover
2. Contents
3. CHAPTER 1
_With love and appreciation for Zac Weikal_
_and the members of my Bakery Bunch_
GLOSSARY
_ach:_ oh
_aenti:_ aunt
_appeditlich:_ delicious
_bedauerlich:_ sad
_boppli:_ baby
_brot:_ bread
_bruder:_ brother
_bruders:_ brothers
_bruderskinner:_ nieces/nephews
_bu:_ boy
_buwe:_ boys
_daadi:_ grandfather
_danki:_ thank you
_dat:_ dad
_dochder:_ daughter
_dochdern:_ daughters
_Dummle!:_ Hurry!
_fraa:_ wife
_freind:_ friend
_freinden:_ friends
_froh:_ happy
_gegisch:_ silly
_gern gschehne:_ you're welcome
_Gude mariye:_ Good morning
_gut:_ good
_Gut nacht:_ Good night
_haus:_ house
_Ich liebe dich:_ I love you
_kaffi:_ coffee
_kapp:_ prayer covering or cap
_kichli:_ cookie
_kichlin:_ cookies
_kinner:_ children
_krank:_ ill
_kuche:_ cake
_kuchen:_ cakes
_kumm:_ come
_liewe:_ love, a term of endearment
_maed:_ young women, girls
_maedel:_ young woman
_mamm:_ mom
_mammi:_ grandmother
_mei:_ my
_naerfich:_ nervous
_narrisch:_ crazy
_oncle:_ uncle
_schee:_ pretty
_schmaert:_ smart
_schtupp:_ family room
_schweschder:_ sister
_schweschdere:_ sisters
_sohn:_ son
_Was iss letz?:_ What's wrong?
_Wie geht's:_ How do you do? or Good day!
_wunderbaar:_ wonderful
_ya:_ yes
FAMILY TREE
Featuring _The Christmas Cat_ novella characters from the collection _An Amish Christmas Love._
**Thelma m. Alfred Bender**
Mandy
Rhoda
**Leona m. Marlin Blank**
Darlene m. Uria Swarey
Ephraim
Katie Ann
**Emma m. Henry (deceased) Bontrager**
Hank the Cat
**Darlene m. Uria Swarey**
Savannah
Rebekah
**Marietta m. Roman Hertzler**
Clara
**Gertrude m. Elvin King**
Wayne
**Feenie m. Jeptha Lantz**
Arlan
Christian
**Saloma m. Floyd Petersheim**
Jerry
Biena
CHAPTER 1
Sorry I'm late! But I brought a chicken and rice casserole." Mandy Bender gave a little laugh as she rushed into Emma Bontrager's kitchen carrying a Pyrex portable container.
"Oh, Mandy! That casserole sounds _appeditlich_!" Emma clapped her hands. Although Emma was old enough to be Mandy's grandmother, her dark-brown hair and nearly wrinkle-free skin made her look much younger than her late sixties.
" _Danki._ I hope it tastes as _gut_ as it sounds." Mandy looked down at Emma's large, fat, orange tabby cat as he rubbed her leg and blinked up at her. "Hi, Hank. Do you want to try some chicken casserole?"
"He'd probably love that." Emma held out her hand. "Give me your coat, and I'll hang it in the mudroom."
Clara Hertzler walked over to the counter. "What's in the container Ephraim's carrying?"
"A salad." Mandy spun to face her fiancé, Ephraim Blank.
"The casserole does sound _wunderbaar_." Clara took the salad from Ephraim and set it on the counter. "We were just concluding our meeting."
"Oh no. I was afraid of that." Mandy frowned as she set the casserole next to the stove. Unfortunately, her mother let someone borrow both their insulated carryalls, so she had to warm up the casserole.
"You can tell us what we missed," Ephraim said. "I can't wait to have some of that casserole. My stomach growled all the way here just thinking about it."
Mandy smiled up at him. She loved how he towered over her by nearly one whole foot. Of course, since she was only five feet two, most of her friends were taller than she was. But it wasn't just Ephraim's height that had attracted her. With his light-brown hair that turned golden in the summer, his kind honey-brown eyes, his strong jaw, and his bright, inviting smile, he was the most handsome man she'd never known.
"Are you going to turn on the oven?" He grinned at her.
"Oh, right!" Mandy gave a little giggle as she flipped the dial to preheat, and then she looked toward the table where her group of friends all sat. She knew they'd been discussing the community garden they'd started on Emma's property in memory of her late husband, Henry, just like they did every Sunday afternoon. Along with baked goods and, now, Emma's orchard apples, they sold the fruits and vegetables they grew at a roadside stand in front of Emma's house. Then they donated most of the profits to the Birdin-Hand Shelter for the homeless, Henry's favorite charity. The rest they saved for any other needs.
"So. What did we miss?" Ephraim asked.
"Let's see." Katie Ann, his younger sister, tapped her lip as she looked down at a notebook. "We were just discussing closing the stand for the winter. Since it's getting colder and our only offerings now are winter squash from the garden and Emma's apples, we should probably do it no later than the weekend before Thanksgiving. We have some vegetables left, but Emma, Tena, and Mandy plan to can them this week for Emma and Tena to use all winter."
"I agree," Christian Lantz said with a nod. He'd been Katie Ann's boyfriend for a while now, and Mandy was thrilled for her best friend.
"I do too," Jerry Petersheim chimed in. He'd recently returned to the church, and he and Clara had the chance to rekindle their attraction for each other because of Henry's garden. They planned to date as soon as he was baptized.
_Oh, how this project was bringing couples together!_
"What do you think?" Katie Ann met Mandy's gaze.
" _Ya_ , of course." Mandy shrugged. "Whatever you all decide is fine with me." She watched Ephraim cross the floor to the kitchen table and sink into a chair between Wayne King and Chris.
"We were talking about Alex too," Clara said, referring to Alex McCormack, a homeless veteran who'd helped them manage the garden during the fall. She pulled a stack of paper plates from Emma's cabinet. "I gave everyone some news about him."
"Oh?" Mandy took the stack of plates and delivered them to the table. "What news?"
" _Mei onkel_ interviewed Alex for a job at his nursery and hired him. Also, he offered Alex the suite in the back of his office until he finds an apartment. It has a bedroom, bathroom, and kitchenette, and he's going to move out of Emma's barn tomorrow."
"Really?" Mandy smiled. "That's great news. It has to be getting cold at night in your barn, Emma."
" _Ya_ , it is," she said. "This comes just in time!"
"Are we still going to help him with his security deposit and a couple months' rent?" Ephraim asked.
" _Ya_." Clara nodded. "But _mei onkel_ says there's no hurry."
"That's fantastic," Mandy said.
"I'm glad we were able to help him," Wayne added.
"I agree." Tena Speicher, Emma's great-niece, smiled at him. They were dating now too.
_Another "garden variety" pair._
She put the casserole in the oven to warm.
"So when do we eat?" Ephraim said as Clara carried the container of salad to the table.
"Patience," Mandy said. She followed Clara with disposable bowls, and Tena brought utensils. "Emma, I assumed you'd have some of your fantastic homemade salad dressing. I hope I wasn't wrong."
Emma moved to the refrigerator. "You know I always have some made up. I'll get it."
"I'll get the glasses and a pitcher of water." Katie Ann hopped up and made a couple of trips before she and everyone else sat down.
After a silent prayer, they all filled their bowls with salad and conversation broke out around the table. Mandy smiled as Katie Ann shared a funny story about a customer who'd stopped by the stand yesterday, but although she did her best to seem cheerful and interested, she couldn't stop thinking about everything she had to do for her December wedding. She had only a little more than a month to finish making the dresses, and she also had to plan the menu and make the table decorations.
How was she going to get everything done in only six weeks? It wasn't that she'd waited too long to get started. Ephraim had proposed only two weeks ago!
She had to stop worrying, though. She and Ephraim had so much to look forward to! She'd get it all done somehow.
When everyone had finished eating their salad, Mandy gathered the bowls and tossed them.
"The casserole should be ready now." She flipped off the oven and grabbed two pot holders. "It just needed to be warmed up a bit." She opened the oven, and a wall of warmth hit her face. She hefted the dish onto the counter.
"All right." Mandy smiled at her friends as she carried the casserole to the table. "This is _mei mammi_ 's recipe. I hope you like it."
"It looks amazing." Tena rubbed her hands together.
" _Danki._ " Mandy grinned as she set the platter in the center of the table. Then she sat down beside Ephraim. He gave her a nod, and then scooped some casserole onto his plate.
Mandy sat back in her chair as her friends all filled their plates. The room fell silent as they dug in. When Mandy felt something touch her thigh, she found Hank standing on his back legs with his paws on her lap.
"So you _do_ wish you could have some of this food too?" Mandy touched his nose.
"Oh, Mandy!" Tena gushed. "This is fantastic."
"It's great." Ephraim leaned close to her, his voice low in her ear, sending a flutter low in her belly. " _Wunderbaar_."
" _Danki_." Mandy's chest swelled with warmth as the rest of her friends joined in with praise. "I'm so glad you like it. I made this meal special for us."
Mandy smiled. Sunday nights were her favorite times with her best friends.
Ephraim folded his arms over his heavy coat as he sat on a rocking chair on Emma's back porch and looked toward the garden he and his friends had planted in the spring. His life had changed so much since he'd asked Mandy to be his girlfriend eleven months ago. It was as if their relationship had grown and blossomed like the fruits and vegetables they'd sold at the roadside stand all season long.
He smiled to himself as he imagined her beautiful face, her bright-blue eyes, and her sweet laugh. He'd always considered Mandy to be just another young girl who came over to bake and giggle with his sister. But then one day he saw her in a new light. It was as if she had grown up overnight. Before long she was also his friend, and he wanted to know her better.
Along with Katie Ann, Mandy, and Wayne, he'd visited Emma last Christmas Eve, and his world seemed to shift just as sure as they'd been snowed in. That night he realized he wanted to be more than Mandy's friend. A few days later, he asked her to be his girlfriend, and then two weeks ago he worked up the courage to ask her father's permission to propose. Mandy had said yes, and neither of them wanted to wait for marriage any longer than necessary.
In six weeks, Mandy would be his wife, and they would start a new journey together. His heart thumped as he pictured their bright future. He was blessed to have Mandy in his life, and he would cherish her and take care of her to the best of his ability.
"So you're going to be a married man in less than two months." Wayne, his best friend, patted his shoulder from the rocking chair beside him. "How does that feel?"
"Amazing." Ephraim grinned and glanced at Wayne. "I'm ready."
"You know, you're making the rest of us look bad," Chris teased.
"How so?"
"Now the other _maed_ will want us to propose," Chris said, turning his palms up. "Now they'll all want to get married—soon."
"Not Clara." Jerry smirked. "I can't propose until after I'm baptized next fall, so I'm off the hook for now." He pointed his index fingers at Wayne and Chris. "But you two, well, that's a different story."
Chris groaned. "I don't think I'm ready yet."
"I admit I'm not either," Wayne said. "Tena and I are just getting to know each other better." Then he smiled. "But I'm _froh_ for you." He gave Ephraim a nudge. "You and Mandy will have a _wunderbaar_ life together."
" _Danki_." Ephraim smiled. He couldn't wait to see what God had in store for him with the woman he loved.
"The casserole was _appeditlich_." Emma gave Mandy a warm smile as she held up her clean Pyrex dish.
" _Danki_." Mandy buttoned her coat and then took the dish. "I'm so glad you liked it."
"Are you ready?" Ephraim asked as he lifted the salad container from the counter.
" _Ya_." Mandy said good-bye to her friends, and then she followed Ephraim to his waiting horse and buggy. She shivered as she looked up at the clear sky, taking in the bright stars twinkling above her. "It's such a _schee_ night for early November."
" _Ya_." Ephraim opened the buggy door for her and took the Pyrex dish out of her hands. "It is."
As she climbed into the buggy, she smiled. She'd known Ephraim nearly all her life. Mandy and Katie Ann had declared each other best friends on their first day of school when they were seven years old. Mandy still recalled seeing Ephraim on the playground that first day. He was two years older than she was, and he caught her eye the moment he smiled at her. She'd always had a crush on him, and she never imagined he'd ever see her as more than his little sister's friend.
But everything changed last fall. He seemed to linger and talk to her more often when she visited Katie Ann at their farm. Then he seemed to seek her out at church and at youth group events. He finally asked her to date him shortly after Christmas last year, and her father had readily agreed.
Two weeks ago, he'd proposed, surprising her, and she couldn't contain her happiness! She couldn't wait to take his name and move in with his family until his father built them a house on his dairy farm.
"Can you believe we'll be married in six weeks?" Mandy heard her voice lift with excitement as he handed her the dish and container to hold on her lap. "It's coming so quickly!"
"It is." He closed the door and jogged around to the driver's side.
"But I have so much to do. I still have to finish making my dress. Then I have to make the dress for _mei schweschder._ She has enough to do helping _Mamm_ with her sewing business." She angled her body toward his. "And I have to plan the menu with _mei mamm_ and _schweschder._ "
"It will all come together." He gave a slight nod as he kept his eyes trained on the windshield while guiding the horse toward the road.
"What do you think about having lasagna and garlic bread for our wedding supper?" she asked. " _Mamm_ thought it might be a _gut_ idea since we can prepare the lasagna pans ahead of time."
He gave a shrug. "Anything will be great."
She tilted her head as she studied his profile. "It's just so much. I'm overwhelmed."
"Don't worry. It will all get done."
_But how?_ she wanted to ask him. Not only did she still have responsibilities to her family at home, but she hadn't realized planning and executing a wedding took so much work. That was probably because she was the first to marry among her friends. Maybe her mother had some idea, but Mandy knew she would never want to be anything but optimistic about their plans.
She turned toward Ephraim, who still stared straight ahead without another word. The buggy was filled with the sound of wheels scraping on the road, the _clip-clop_ of the horse's hooves, and the roar of passing traffic. Still, it was too quiet for her, allowing the list of wedding tasks to once again roll inside her head.
"What are you thinking about for table decorations?" Ephraim's voice broke through her thoughts.
"What?" She spun to face him.
"I asked what you're thinking about for table decorations."
"Oh." She forced a smile. " _Mamm_ and I think we should go with a blue candle that matches the dresses, and maybe a little baby's breath. That will be simple but elegant."
"Sounds perfect."
" _Ya_." She blew out a sigh.
"What was that sigh for?"
"The truth is I just don't see how I can accomplish everything I need to do for the wedding in six weeks." She threw up her hands, almost spilling the stack of kitchenware on her lap to the floor.
"Well, both of our _schweschdere_ will help you. Your _mamm,_ too, right?"
"I know, but still, it's hardly enough time." Her shoulders tightened as she awaited his response, even though she wasn't sure what she wanted him to say.
He halted the horse at a red light and faced her. "Would you feel better if we went by to see _mei mamm?_ Maybe she can help make the decorations."
"Really?" Hope lit in Mandy's chest.
"Sure." He smiled. "I bet she'll be thrilled to help."
"Great." She gripped the stack on her lap. If Ephraim's mother agreed to help, surely some of the stress plaguing her would ease.
CHAPTER 2
After Mandy placed the dish and container on the floor of the buggy, Ephraim held out his hand as she climbed out. "Everything will be fine. I promise you."
" _Danki_." She laced her fingers with his and enjoyed the reassurance his hand entangled with hers always gave her.
She allowed him to steer her through the cold air up the path and to the back porch. As they entered the home's back door, voices sounded from the kitchen.
"Do your parents have guests?" she asked Ephraim as she pulled off her coat.
"I wasn't expecting any." Ephraim took her coat and hung it on a peg next to his.
Mandy followed him into the kitchen, where they found Ephraim's parents sitting with his older sister, Darlene. Her husband, Uria, and their young daughters, Savannah and Rebekah, were there too.
"Darlene!" Ephraim said as they walked in. He greeted Uria and the girls. "How are you all doing?"
"Hi, Mandy!" Savannah waved. Seven years old, she had her mother's light-brown hair and honey-brown eyes, so like Ephraim's as well.
"Hi." Mandy waved hello to all of them and then took a seat in the empty chair by Rebekah. She was nine and had the same coloring her sister had. Mandy glanced around the table and took in the adults' expressions.
Something was wrong. Didn't Ephraim notice? His parents' faces looked serious, and Uria looked upset. Had his sister been crying?
"Would you like some _kaffi_?" Ephraim's mother held up a carafe.
" _Ya. Danki_ , Leona." Mandy pushed back her chair.
"Sit. I'll get you a mug." Ephraim retrieved two mugs from a cabinet. "I didn't know you all were coming. I would have stayed home from the meeting at Emma's if I'd known. What brought you here today, Darlene?"
Mandy noticed a look pass between Darlene and her mother, and Darlene dabbed her eyes. What was going on?
Ephraim filled the mugs with coffee before setting one in front of Mandy. After he sat down next to Uria, she saw him take a good look at his parents and then his sister. "What am I missing?"
"I lost my job," Uria said.
"What? When?" Ephraim's handsome face clouded with a scowl.
"Back in August." Uria blew out a deep sigh. "The construction company closed. I've been doing odd jobs and looking for something permanent, but nothing has panned out."
"I'm so sorry to hear that," Ephraim said. "Why didn't you tell us sooner?"
"We were hoping something else would come along," Darlene said. "We hated to burden you all with our problems."
"Do you have a plan?" Ephraim asked.
Mandy sipped her coffee. When she felt something touch her arm, she turned and found Rebekah holding up a chocolate chip cookie.
" _Danki_ ," Mandy whispered as she took the cookie and bit into it.
"We came to ask for help." Darlene looked at her husband and rubbed his arm. "We can't pay our rent anymore, and we've gone through our savings. We have nowhere else to go."
"They're going to move in with us!" Ephraim's father said. "Uria will help Ephraim and me run the dairy farm, and we'll get to spend more time with our granddaughters."
Mandy was glad to hear his cheerful tone. Yet knowing his daughter and her family had come to this point had to be difficult.
Mandy took another drink as she tried to catch Ephraim's eye. The stress in the room was palpable. This felt like a private family discussion. If Ephraim would just look at her, she could motion for him to take her home.
Mandy felt a tug on her sleeve. She turned as Rebekah held out another cookie. While her parents were trying to find stability, the girls just seemed happy to be eating cookies.
" _Danki_ ," Mandy said again as she took the cookie and placed it on a napkin next to her half-eaten first one.
The back door opened and clicked shut, and Katie Ann appeared in the doorway.
"Darlene!" She went to her sister and hugged her. "I didn't know you were coming today. Rebekah! Savannah!" She hugged her nieces next. "What's the occasion?" She sat down next to Savannah and took a cookie from the little girl's plate with a grin.
Darlene cleared her throat. "Well, Uria lost his job in August, and he hasn't found anything permanent. Since then we've depleted our savings."
Katie Ann looked around the table. "Are you moving in, then?"
" _Ya_ ," Leona said. "They are. We were just discussing that. Uria is going to work on the farm with your _dat_ and Ephraim."
"Darlene and Uria can take the sewing room," _Dat_ said.
"And the _maed_ can stay with me." Katie Ann turned to her nieces. "Would you like that? One of you can sleep in my big bed. And we'll get a cot for the other."
"Yay!" Rebekah clapped her hands. "We can stay with _Aenti_ Katie Ann."
"Can I bring my dolls?" Savannah's tone seemed hesitant.
"Of course you can." Katie Ann poised to take a bite of her cookie. "I'll clear some of my shelves. You can both bring your special things."
Savannah seemed satisfied with that.
"Are you really okay with this?" Darlene's eyes glistened.
Katie Ann rubbed Savannah's arm. "I always have room for my favorite nieces."
"We're your only nieces," Rebekah said, and Katie Ann laughed.
"I really appreciate it," Darlene said. "We just don't know what else to do."
"We'll make it work for now." Marlin reached across the table and touched Darlene's hand. "I'll build you all a _haus_ in the spring. We'll just be a little cramped in this _haus_ until then."
" _Danki, Dat._ We hate to be a burden."
"Family is never a burden, _mei liewe_ ," Marlin insisted.
"Would it be all right if we move in this week?" Uria asked. "We have to be out of our rental as soon as possible."
" _Ya_ , of course. We can help you move tomorrow." Marlin turned to Ephraim and Katie Ann. "Right?"
They both nodded.
Mandy shifted on her chair. This conversation felt so personal. She shouldn't be here. She turned to Ephraim, who had finally looked at her. He raised his eyebrows in question. "Why don't you take me home?"
"Okay." Ephraim pushed back his chair.
"It was nice seeing you all," Mandy said.
They all said good-bye, and she followed Ephraim into the mudroom. After they pulled on their coats, they headed into the cold and climbed into his buggy.
They rode in silence as he guided the horse away from the house. Mandy contemplated the family's discussion. The Blanks were facing some big changes. Her heart broke a little as she recalled the sadness on Darlene's face.
"Why didn't Uria tell us when he lost his job?" Ephraim's question broke through their silence. "He and Darlene should have known we wouldn't consider knowing about their troubles a burden."
"Maybe he was embarrassed. I'm sure he feels responsible for taking care of his family, and he never expected to find himself in such dire straits."
"But my parents could have helped them months ago." Ephraim gave her a sideways glance.
"Uria probably thought a job was going to come through." Mandy bit her bottom lip as she suddenly saw her future shifting. How could Marlin build a house for Darlene and her family next spring and build one for Ephraim and Mandy at the same time? It wasn't possible. And how could the family manage with so many people in the house all winter, including her? She wouldn't be a blessing. Even though she knew they'd never think so, she'd be a burden!
Only one solution made sense.
"It will be different having Darlene and her family living with us," Ephraim said, his voice pleasant as he looked out the windshield. "But it will be nice to see my nieces every day."
"The _haus_ will be cramped," Mandy said.
"Cramped?" Ephraim shrugged. " _Ya_ , I suppose so, but we'll make do." He smiled at her. "Just wait until you move in. Then it will really be chaotic."
"You don't honestly think I should still move in?"
"What do you mean?" He halted the horse at a red light and turned toward her. "Why wouldn't you move in?"
She angled her body toward him. "The last thing your parents will need is another mouth to feed. You're already going to have eight people in the _haus_."
"Exactly. That's why it won't make a difference if there's a ninth."
"No." Mandy shook her head. "We need to delay the wedding. Not just because it will be crowded with me there, but to give your family the time they need to adjust. It won't hurt us to wait a few months."
His eyes went wide. "You don't want to marry me as soon as possible?"
"Of course I do. But I think we should delay the wedding for your family's sake. Besides, I'm stressed because I don't have enough time to get everything done. An eight-week engagement has turned out to be too short."
"We have plenty of time," he said, insisting.
"No, we don't. And now your parents have more important things to worry about."
A horn behind them tooted, and Ephraim guided the horse through the intersection.
A heavy silence fell between them, and Mandy racked her brain for how to make Ephraim understand her point of view. Wasn't it obvious that this wasn't the best time to get married?
"Ephraim, please hear me out," she began. "Your parents are under a lot of stress right now. The wedding is the last thing they need to worry about. They need to be concerned about Darlene and her family first."
"I disagree," Ephraim said. "They love you, and they want you to be part of our family."
"I know that," Mandy kept her words measured. "I love your family, too, but things will be better in a few months. Let's wait until everything settles down. We'll still have to wait for our _haus,_ but at least—"
"No." He interrupted her. "I don't want to wait."
Mandy pinched the bridge of her nose. "There's no reason to rush."
"There's no reason to wait," he said, challenging her.
She blew out a frustrated sigh and looked out at the passing traffic.
"You're having doubts, aren't you?" he spat. "That's the real reason you want to put off the wedding. You were going to use the excuse that you had too much to do, but now Darlene has given you an even better excuse."
"What?" She spun to face him. "That's ridiculous!"
"Then why won't you marry me now?"
"I've already explained my reasoning. Why can't you wait a few months?" she said. "What's the hurry? We've been engaged only two weeks. Let's take our time and enjoy our engagement."
"You've known me nearly your whole life. We don't need a long engagement."
She scrunched her eyes shut. "Why are you being so stubborn about this?"
He turned back toward the windshield and stared at the road ahead. A muscle ticked in his tense jaw.
Mandy folded her arms over her chest and sat up straight. They were at a stalemate. She couldn't think of any way to sway him.
They sat in silence as her family's house came into view. If only she could cut the tension pulsing between them.
"Ephraim," she said when they stopped behind her house, "I've loved you since I was a little girl. I always dreamt that someday you would see me as more than Katie Ann's best friend, and that dream came true last Christmas. Then another dream came true when you asked me to be your _fraa_."
She turned to face him and found him staring at his lap. "I do want to marry you, but I think we need to wait a few months. Your family is in turmoil now. Your parents will most likely be relieved if they hear we're going to delay the wedding. That will give your family time to adjust to this new situation without my adding to the crowded conditions, and, yes, it will give me time to prepare for the wedding."
"We'll have my room."
"And four women would be sharing the kitchen instead of three. I think that will be too much for all of us. We'll trip over each other. We didn't even plan for three, since we thought we'd have our own _haus_ next spring. Now your _schweschder_ and her family need one instead."
"I think you've changed your mind about marrying me, but you won't admit it."
"That's not true! I've just realized it's too soon for our wedding, especially since your family is dealing with a crisis. It would be selfish for us to get married now."
"Selfish?"
" _Ya_ , selfish. You need to think about your _schweschder_ and her family. You have to move them in and help rearrange the _haus_. How can you even think about our wedding when they need your help?"
"So you think I'm selfish." He leaned back against the buggy door. "What else do you think about me?"
"You're twisting my words." She threw up her hands and nearly dropped the dish and container still on her lap. "I don't understand why we're arguing about this."
"Maybe we should just break up."
"What?" Her eyes stung, threatening tears. "You want to break up with me just because I want to delay our wedding?" She fought a sob as tears welled.
"Even if you do still want to marry me, you don't seem to want to deal with my family's problems because you'll be inconvenienced. Not just with what you consider a crowd, but because we won't have our own _haus_ as soon as we thought. So maybe we should just forget our plans."
"Ephraim, you're overreacting. Stop and listen to what you're saying."
"I know what I'm saying. My family has a hard time, so you choose to distance yourself."
"I don't want to break up. You're blowing this way out of proportion!" Her voice shook as fear spiraled through her. But she was frustrated too. "Maybe you're too stubborn to think someone else might have a _gut_ idea. You always have to be in control. You always have to make the decisions in our relationship. My opinion matters too!"
"Is that so?" he snapped. "So you think I'm selfish, bossy, _and_ controlling?"
" _Ya_ , I do!"
"Maybe this relationship won't work, then."
"I never said that!"
"We need some space." He turned to stare out the windshield.
"What does that mean?"
"That means we should take a break and talk about this again some other time."
"So you _are_ breaking up with me?" Her voice shook.
"I don't know." Ephraim scrubbed his hand down his face. "This is too much to take in. It's been a crazy night."
"I know." She nodded as her hands trembled. "But I love you. I don't want to take a break. I just want to slow down."
He shook his head. "Well, I do need a break. I'll talk to you tomorrow."
"But you're moving your _schweschder_ and her family tomorrow."
"So we'll talk another day."
Was she dreaming? This felt like a nightmare!
"We'll talk another day," she repeated, trying to make sense of his words. "You just told me you need a break, and you don't know when you want to work it out." Her stomach tightened with growing panic.
"I'm sorry."
"No, Ephraim, I'm sorry." She scooped up the container and dish with one arm, flung open the buggy door, and ran up the path to the back porch. Once in the mudroom, she dropped the containers on the bench, shucked her coat, and hung it on a peg on the wall. Then she sank to the floor, covered her face with her hands, and dissolved into gasping sobs.
CHAPTER 3
Mandy!" _Mamm's_ voice sounded close by.
Mandy tried in vain to get hold of her raging emotions, but her tears continued to fall, rolling down her cheeks, darkening her black apron and the skirt of her favorite green dress. She removed her hands from her face and found her mother squatting in front of her. _Mamm_ pushed back a stray tendril of Mandy's hair that had escaped her prayer covering.
" _Was iss letz?_ " _Mamm_ 's sky-blue eyes were warm and kind, causing more tears to fill Mandy's eyes. _Mamm_ clicked her tongue. " _Ach, mei liewe._ What could possibly have upset you so much?"
"I think it's over," Mandy managed.
"What's over?" _Mamm_ 's eyes searched hers.
"Eph—" Mandy couldn't say the words aloud. Had Ephraim truly broken their engagement? Wasn't she dreaming? But her broken heart was real—so real she thought she could feel the shards cutting her inside.
"Rhoda!" _Mamm_ called. "Grab a box of tissues and bring it to the mudroom. _Dummle!_ " Then she turned back to Mandy and placed her hands on her arms. "Whatever it is, I promise it's going to be okay. We'll get through this together."
Mandy shook her head. No, she'd never get over this. Never.
"What happened?" Rhoda appeared in the doorway holding a box of tissues. At sixteen, her sister was petite like Mandy, and she'd also inherited their mother's same sunshine-colored hair and bright-blue eyes. Those eyes widened as she kneeled beside _Mamm._
Mandy took deep, shuddering breaths, trying to stem her sobs.
"Shh." _Mamm_ mopped up her tears with a tissue. "Just calm down and talk to us. We can help you if you tell us what happened."
"I'll put on tea." Rhoda popped up and hurried into the kitchen.
" _Gut_ idea." _Mamm_ held out her hand to Mandy. " _Kumm_."
Mandy took her mother's extended hand and let her guide her into the kitchen.
"Sit." _Mamm_ nodded to Mandy's usual spot at the table.
Mandy sat down and swiped a few tissues across her face. How had this happened?
Tears filled her eyes anew.
"Mandy." _Mamm_ sat down beside her and took her hands. "Talk to me."
Mandy sucked in a deep breath. "I think Ephraim broke up with me."
"What?" Rhoda came to stand behind their mother.
"We had an argument on the way home from his parents' _haus_. I told him I thought we should delay the wedding. He got upset and accused me of things that aren't true." As she explained everything, it was hard to keep her voice steady, but she managed to keep her tears at bay. "I can't believe it. I just asked to delay the wedding, but he made all kinds of assumptions and blew everything I said out of proportion."
The kettle whistled, and Rhoda poured water over tea bags in three mugs and carried them to the table.
" _Danki_." Mandy wrapped her hands around her mug and stared into the hot liquid.
Rhoda sat down across from her and shook her head. "I don't know what to say, except I know Ephraim loves you. I can tell every time he looks at you. Maybe he needs a day to think about everything, and then he'll realize you're right."
"But I don't understand why he's so upset. What's wrong with waiting a few months until his family has adjusted to their new situation? What's wrong with giving me enough time to get ready? As I thought about both needs, it dawned on me that delaying the wedding made sense. What do you think, _Mamm_?" Mandy looked over at her mother. Surely she would have some words of wisdom to make everything better.
_Mamm_ took a sip of her tea and then set down her mug. "I think you're right."
"So how do I convince Ephraim?"
_Mamm_ tapped her finger against her chin. "What if you propose a new plan to him?"
"What do you mean?"
"I don't think Ephraim realizes how much Darlene's needs change everything for his family. I'd take your concern about moving into Marlin's house further. Even if you delay your wedding for a few months, you still won't have your own _haus_ for some time. Maybe years. And I've always thought privacy is best for a young couple. It's not selfish to want that.
"What if after the wedding Ephraim moved into our home? The one drawback is that he'd no longer be on-site to work on his father's dairy farm, but he could work for your _dat_ 's brickmasonry company. Then I'm sure your _dat_ would want to build a _haus_ for you here."
Mandy blinked. "That's a brilliant idea!" She leaned forward. "Do you think _Dat_ would agree to it?"
"Would I agree to what?"
Mandy turned to find her father stepping into the kitchen. With his light-brown hair and gray-blue eyes, Mandy had always thought he was the most handsome older man she knew.
"Ephraim's older _schweschder_ and her family have fallen on hard times, and they're moving in with Ephraim's parents," Mandy began. "Their _haus_ will be crowded now, and I suggested we delay our wedding, at least until Marlin builds a house for Darlene and her family next spring. Now Ephraim is upset with me."
_Dat_ took a seat across from her at the table. "I don't see why he should be upset. It sounds like a mature idea to me."
" _Danki_." Mandy cupped her hands around her warm mug. "This also means Ephraim and I won't have our own _haus_ for some time. _Mamm_ came up with an idea to make this whole situation a little easier on everybody. What if Ephraim moved in here after we're married and went to work for you?"
_Dat_ nodded as he touched his beard. "Of course. Your husband would always be welcome to live here until you find a place, and I've been thinking about hiring someone else." He looked at _Mamm_. "We could also build them a _haus_ here. We have plenty of land."
" _Ya_." _Mamm_ nodded and smiled. "I thought you'd say that."
"Do you both think Ephraim will agree to this plan?" The question leapt from Mandy's lips before she could stop it.
_Mamm_ ran her fingers over her mug as she nodded. "I think it's a possibility. If Uria and Darlene are going to live there, and Uria will help run the dairy, then his becoming a brickmason is a great plan for him and for you."
_Dat_ 's smile was warm and encouraging. "I'd love to have him as my apprentice."
"I think it's a great idea," Rhoda chimed in.
"You and Ephraim need to calm down and talk this out, though." _Mamm_ 's voice was gentle but firm. "You can't make this decision for him. Really listen to each other and think about your future."
Mandy's lower lip began to tremble, and she held her breath. She wanted to marry Ephraim, raise a family with him, and grow old with him. But she wanted to get married when the time was right. Would he change his mind? Would he even consider living with her family and changing his vocation for her?
"What are you thinking, _mei liewe_?" _Mamm_ rubbed her arm. "I hate to see you so troubled."
"I'm still confused, and anxious." Mandy slumped back in her chair. "It seemed like everything was perfect two weeks ago when Ephraim proposed to me. But now I don't understand why he can't see things from my point of view. Tonight it felt like God was saying we should slow down. But when I suggested it, Ephraim accused me of using Darlene's circumstances as an excuse. He said maybe I'm having doubts about marrying him. Then he said I was just feeling inconvenienced because Marlin's _haus_ would be crowded, plus we wouldn't have our own _haus_ next spring. Why is he making these things up? Why is he so defensive?"
_Dat_ leaned back in his chair. "Probably because all these changes are out of his control. He feels like he should be able to provide a better life for you, but he can't right now. He's doubting himself, not you. Just give him time to think and calm down. Even if he's not willing to move here and work with me, he'll realize delaying the wedding makes _gut_ sense."
"How long do you think that will take?" Mandy rubbed the back of her tightening neck as she waited for her father to calm her worries.
"I think Ephraim can be a bit stubborn," _Dat_ said. "Am I right?"
" _Ya_." Mandy nodded. "He can be very stubborn."
"He might need a few days, but I believe he'll come around." _Dat_ smiled. "Trust God."
"Exactly," _Mamm_ said. "Just pray about it, and then talk to Ephraim. God will lead you both to the right answer."
" _Ya_ , _Mamm_ is right." Rhoda nodded, and the ties to her prayer covering fluttered around her slight shoulders.
"I will." Mandy picked up her mug and took a long sip. She silently prayed her family was right, that Ephraim would agree to delay the wedding rather than throw away their love. But she had to admit, she also hoped he'd be willing to alter their plans and live with her family. That just seemed like the best idea for everyone.
" _Dat?_ " Ephraim's entire body shook as he walked toward the light he saw glowing near the back of his father's largest barn. " _Dat_ , are you in here?"
"Ephraim?" _Dat_ walked toward him, carrying a lantern. "Are you all right?"
"No, I need to talk to you. Are you alone?" Ephraim set his lantern on the ground. Then he lifted his straw hat and pushed his hand through his thick hair.
" _Ya_ , I'm alone. I was just checking on the animals." He pointed toward the stalls. "Darlene, Uria, and the _maed_ went home. What's going on?"
"I think Mandy and I may have just broken up."
"What?" _Dat_ 's dark eyes widened. "Why would you break up? You seemed fine earlier when she stopped by with you."
" _Ya_." Ephraim scowled and looked toward the barn doors as confusion swamped him. Had he made a mistake? None of this made any sense.
"Why?"
"We argued on the way to her _haus._ She wants to delay the wedding. She thinks she doesn't have enough time to get ready. She also thinks our family has too much going on with Darlene and her family moving in, and if she moves in, the _haus_ will be too crowded." Ephraim rubbed at a knot on his shoulder. "I got upset. I don't want to wait a few months to get married. I think we have plenty of time to get ready, and I'm okay if the _haus_ is a little crowded. She disagrees with me. We argued, and we said some horrible things. I told her we both needed some space. I guess we kind of broke up." He grimaced as doubt edged his words.
_Dat_ touched his beard and looked past Ephraim.
"What, _Dat_?" Ephraim touched his father's arm. "Tell me what you're thinking."
"I'm surprised. You two seemed so _froh._ Do you really want to break up over this?"
"I don't know." Ephraim sat down on a hay bale. "There's more. I accused her of making excuses to delay the wedding because she's having doubts about our relationship, and because she's feeling inconvenienced by the prospect of sharing a _haus_ with so many of us. Unless that's true, I just don't understand why she wants to delay the wedding. Her excuses don't make sense to me."
_Dat_ sat down beside him. "Maybe she really does just want to wait for things to settle down."
"Maybe, and maybe she does still want to marry me. But this feels like she doubts the strength of our relationship." Ephraim kicked a stone with his shoe. "Then she said I'm stubborn and bossy and controlling, and that makes me doubt our relationship." He pinched the bridge of his nose, where a headache brewed. "I've been looking forward to starting our life together, but now . . . How did you know when it was time to marry _Mamm_?"
"Well, your _mamm_ and I had known each other for years, like you and Mandy have," _Dat_ began. "We started dating when we were in our early twenties, and then I just knew when it was time."
"You never had any doubts?" Ephraim held his breath in anticipation of the response.
_Dat_ grimaced, and Ephraim groaned, covering his face with his hands.
Ephraim rubbed his eyes as doubt and heartache pummeled his chest. The pain in Mandy's beautiful face and eyes kept replaying in his mind.
Had he just made the biggest mistake of his life?
He thought he heard hay crunch, but he kept his face covered. It must have been one of the horses moving in a nearby stall.
"Talk to me, Ephraim," _Dat_ said. "Holding in your emotions isn't healthy."
"If she means what she says, I think Mandy's overreacting. Her family, our family, and her _freinden_ will help her with wedding preparations." He looked up at his father. "You're going to build a _haus_ for Darlene in the spring, right?"
_Dat_ sighed. "I'm going to have to."
"Will you still build our _haus_ next?"
_Dat_ hesitated. " _Ya_ , but it might be a few years before I can afford it."
"That's what I thought. But we can live with you and _Mamm_ until then, right?"
" _Ya_ , you can. It's going to be chaotic for a while, though."
"Why isn't that _gut_ enough for Mandy?" Ephraim's voice echoed in the barn.
"You need to respect her point of view, even if you don't understand it yet," _Dat_ said. "You've just broken Mandy's heart by breaking your engagement. If you try to apologize now, she may not forgive you. Even if she does forgive you, she might not agree to marry you."
"You broke your engagement?" Katie Ann's voice called from nearby.
Ephraim spun to face his sister. She gaped at him, and he knew his father would elect to stay out of this confrontation. He'd always let his children sort out their own conflicts.
"How could you do that? She loves you."
"It's a long story." Ephraim was suddenly exhausted. All the fight had drained out of him, and he was certain his bed was calling him. "I'll tell you tomorrow."
"No." Katie Ann shook her head. "You'll tell me now." She pointed to the barn floor. "Mandy is my best friend. She adores you. How could you hurt her like that?"
"And I'm your _bruder_ ," Ephraim snapped. "What about my feelings?"
"You loved her yesterday!" Katie Ann pointed at him. "What could she have possibly done to make you break your engagement?"
"It's complicated. We had an argument after we left here earlier. She wants to delay our wedding, and I got upset." Ephraim let his arms fall to his sides. "I'm going to bed." He tried to walk past her, but she blocked his way. "Katie Ann, please let me by."
"Not until you tell me everything that happened." She looked up at him, her eyes looking as if they might spark with her anger.
"It's none of your business." Ephraim picked up his lantern and then slipped past her before stalking toward the house.
"Wait!" Katie Ann rushed after him. "You have to tell me what's going on."
"I don't have to tell you anything." Ephraim marched up the back-porch steps and into the house, where he took off his coat and hung it on a peg. He hung his hat next to it and then carried his lantern into the kitchen.
"Why are you acting like this?" Katie Ann trailed after him. "What's wrong with you?"
He spun to face her. "All I told her is we need a few days to cool off. But I guess she considers that a broken engagement. This is between us. Stay out of it, Katie Ann."
She opened her mouth and then closed it, her face lined with confusion.
Ephraim took a step back. "I'm going to bed. Tomorrow is going to be a long day. We have to move Darlene and her family here. It's going to be exhausting, and we both need rest. _Gut nacht._ "
Before his sister could respond, he jogged up the stairs and into his bedroom, and then he dropped onto his bed as his mind spun with questions.
All he knew for sure was that his heart was breaking. Right now, though, he needed sleep. He'd figure out his problems with Mandy tomorrow.
CHAPTER 4
I'll get it!" Mandy rushed to the back door the following evening, praying the knock she'd heard was Ephraim's. She'd spent all day thinking about him and worrying that their relationship was truly over.
When she pulled open the door, her worries evaporated. Her handsome fiancé stood on the porch, holding a lantern.
"Hi." She pushed the door open wide.
"Hi." Ephraim spun his straw hat in his hands. "Can we talk?"
" _Ya._ Just let me get my coat."
Once outside, she pointed to the glider where they'd spent hours talking. It seemed like just yesterday Ephraim had asked her to be his girlfriend, and now they were facing a crossroads in their relationship—delaying their wedding or calling it off. Her chest constricted at the possibility of losing his love forever.
"How was your day?" she asked. They both sank onto the cool, wooden glider, and then she gave it a gentle push with her toe.
"Long and exhausting." He set his elbow on the arm of the glider and then rested his head on his hand. "Katie Ann helped Uria and Darlene pack at their rental while _Dat_ and I made space for their belongings at our _haus._ Then two men _Dat_ hired met me at the rental while _Dat_ stayed behind to take care of the cows. We had to load it all into their truck, and then unload it." He paused and cupped his hand over his mouth to shield a yawn.
"We had to carry a lot of it up the stairs. We set up Uria and Darlene in the former sewing room, and we got the girls situated in Katie Ann's room. They'll have to finish unpacking all their stuff during the week. We put a lot of boxes in the attic and basement, and what extra furniture didn't fit in the attic or basement had to be transported to one of the barns." He rubbed his eyes and then yawned again. "I think every muscle in my body hurts."
" _Ach_ , Ephraim. You should have gone to bed, then, instead of coming over here." She rubbed his shoulder.
"No." He looked at her, and the intensity in his eyes sent a tremor through her. "I couldn't leave things unsettled between us."
She held her breath, and her pulse tripped.
"You were right. Our _haus_ is not just crowded, but chaotic. But we're family." He swiveled toward her. "I love you, and I can't wait to start the rest of my life with you, to make you part of my family. There's room for you, too, even before _mei dat_ builds Darlene a _haus._ He can't guarantee when he can build our _haus_ , but I don't care where we live. I just want to be with you, Mandy."
She swallowed against a swelling ball of emotion. "If you don't care where we live, then I have an idea for us."
"What?" His expression seemed skeptical.
"What if we lived here instead of at your parents' _haus?_ " She pointed to the porch. "There's plenty of room, and _mei dat_ said—"
"Wait a minute." He held up his hand, silencing her. "I can't live here and work for _mei dat_. It would take me too long to get there for the morning milking, and I'd have to make too many trips back and forth."
"I understand. I have a solution to that too. _Mei dat_ says you can come work for him at his brickmasonry business. You could be his apprentice." When Ephraim looked unconvinced, she spoke faster. " _Dat_ said he'd love to have you work for him, and he would even build us a _haus_ here."
"No." Ephraim's voice was so forceful that she jumped.
"Why not?"
"I don't want to be a brickmason. I want to be a farmer like _mei dat_ and his _dat_ before him. That land has been in our family for generations, and it's my birthright to live on that land and raise my family there. If I have a _sohn_ , he'll inherit that land and run it."
Mandy's shoulders wilted. "You won't even consider another plan for us?"
"That's not what I want," he insisted.
She pointed to her chest. "What about what I want?"
He lifted his hat and held it, leaning forward as if ready to leap up and leave. "So we're back to this again."
"What does that mean?" Her voice vibrated with frustration. "This is a _gut_ plan. We can delay the wedding, and—"
"So not only do you want to still delay the wedding, but you also want to change our plan to live with my family on _mei dat_ 's farm and change my vocation?" He gestured widely. "Why does everything have to change? Why isn't our original plan _gut_ enough for you, even if Darlene and her family are moving in?"
She shook her head as angry tears filled her eyes. "It's not a question of being _gut_ enough for me. It's a question of what makes sense for us. Your _dat_ 's _haus_ is too full of people now, and even though that's temporary, you just said he has no idea when we can build a _haus_ of our own."
She motioned toward the back door. "We have plenty of space here, and room to build another _haus. Mei dat_ 's business is thriving. Why wouldn't you want to work for him, especially now that your _dat_ has Uria's help? Being a brickmason is _gut_ work. Is it not _gut_ enough for you?" She pointed to him.
He snorted. "You're just spoiled."
"What?" She stood up and faced him. "How am I spoiled?"
"Your _haus_ is bigger than mine, and your _dat_ 's business is more successful than _mei dat's_ farm. I'll never be able to satisfy you with the life I can offer you as a farmer. My family isn't _gut_ enough for you. Maybe that's what this is really about." He picked up his lantern, stood, and started toward the porch steps. "Let's just forget it all."
"Wait!" She lurched forward, grabbed his arm, and spun him to face her. "How did we wind up here?" She gestured between them. "I want to marry you. I want to raise a family with you and grow old with you. That has never changed. All I did was suggest we wait a while—"
"And then change _all_ our plans." His expression crumbled into a frown. "It's like I'm not the man you want or need anymore."
"That's not true." She cupped her hand to his cheek. "I want to be your _fraa_ , but I think it might not be best for us to live on your _dat's_ farm. Circumstances have changed. Why is that so difficult for you to see?"
"Because this is who I am." He pointed to his chest. "If that's not what you want, then it's over."
"So that's it." She took a step back and hugged her arms to her chest as if to shield her crumbling heart. "You want to just break our engagement and end it all because I suggested living here and your working for _mei dat?_ "
He shrugged. "I guess so."
Mandy sniffed as her tears broke free. "I'll miss you."
"I'll miss you too." He spun and walked down the steps toward his waiting horse and buggy.
Mandy choked on a sob before stumbling into the house and the family room. Her parents and sister were sitting in their usual spots, reading.
"Mandy?" _Mamm_ set her book on the end table and leaned forward. "Was that Ephraim?"
" _Ya_." Mandy dropped onto the sofa beside Rhoda, her coat still on. "It's really over this time. He doesn't want to delay the wedding, he doesn't want to live here, and he doesn't want to work for _Dat._ He said if their _haus_ and life on his _dat_ 's farm isn't _gut_ enough for me, it's over. He's going to throw it all away because I suggested a different life for us."
Mandy succumbed to sobs as despondency whipped through her. She covered her face with her hands, and her lungs felt as if they would burst with her grief. How could things go so badly so quickly? It felt as if she were stuck in a nightmare!
" _Ach_ , Mandy." Rhoda's voice was close to her ear as she rubbed her back. "It's not over yet."
" _Ya_ , it is." Mandy's words were muffled by her hands. "It's really over. I don't know what I'm going to do. I was so certain he'd agree to live here. He said it didn't matter where we live, but he meant where we live on his farm. He said he can't abandon his family's land. He has to be a farmer like his _dat_ and his _daadi_. Shouldn't it only matter that we're together?" She tried to swallow back more tears, but her sobs overwhelmed her.
"Shh." _Mamm_ appeared beside her and rubbed her shoulder. "Everything will be okay."
"No, it won't." Mandy looked up as _Dat_ sat down on a footstool in front of her and handed her some tissues. She swiped them over her eyes and nose. "Nothing can fix this."
"That's not true." _Dat_ glanced at _Mamm_ , and they shared knowing expressions. "Your _mamm_ and I had a bad argument shortly before we married."
"Really?" Rhoda asked.
"You never told us that." Mandy tossed the crumpled tissues on her lap and shrugged out of her coat.
"We had a few disagreements, and we broke up for a couple of weeks," _Dat_ said. "We took some time to cool off and realized our pride was standing in our way."
"That's true," _Mamm_ agreed. "But then one night your _dat_ came to see me, and we talked for a couple of hours. Then he proposed again, and we were married a couple of months later."
_Dat_ smiled at her, and the love in his eyes made Mandy's chest ache. Would Ephraim ever look at her like that again?
"I realized I wanted to be with your _mamm_ more than I wanted to feel as if I were right about everything." _Dat_ touched Mandy's cheek. "Your _mamm_ and I had to talk it through. I think you need to find out why Ephraim is so upset. There must be more to it. Ask him to share more about how he feels, and listen to him."
"Your _dat_ is right," _Mamm_ chimed in. "You might have hurt his feelings without realizing it."
"What if he won't talk to me?" Mandy felt the tremble in her voice.
"I'm sure he will. You just need to gently push him." _Dat_ brushed a tear from her face. "You and Ephraim love each other, but marriage is a lot of work. You both need to learn how to listen and to respect each other's opinions and feelings. That's a vital part of marriage."
"It's a tough lesson, but it will help you work through any problems you face." _Mamm_ touched her hand.
"Okay." Mandy shuddered as more tears filled her eyes. "I just can't imagine my life without him. I don't want to lose him."
"You won't lose him if you show him you care," _Mamm_ said.
"And take a _gut_ look at what you've said to see if you've accidentally hurt him," _Dat_ said. "You can work this out together if you're both willing to be honest."
Mandy leaned against her mother and hoped her parents were right.
Ephraim felt as if exhaustion and grief might drown him as he made his way from the barn to the house. He was grateful no one was in the barn when he stowed his horse and buggy. Now he just had to make it to his bedroom without a family member questioning him. He wanted to be alone with his confusing and agonizing thoughts.
After hanging his coat and hat in the mudroom, he breathed a sigh of relief. The kitchen and family room were both empty.
As he climbed the stairs, he heard voices echoing from the bedrooms above him. When he hit the second-floor hallway, he slipped into his own bedroom, closed the door, and set his lantern on his dresser. He sank onto the corner of his bed and covered his face with his hands.
He'd never imagined his day would end with truly breaking up with Mandy. As he'd headed to her house, he envisioned they'd repair their relationship and agree to the original plan to marry in six weeks. He'd tell her they could ask some of their friends and other family members to help her with the wedding preparations, and she'd realize it didn't matter if his father's house was crowded for a while or how long it would be before they had a house of their own. Instead, their conversation had gone completely off the rails.
How would he go on without her? She'd been his life, his future, and his heart for almost a year. Now he was left with nothing, alone. His eyes burned.
A knock on his door startled him. He sat up straight and cleared his throat.
"Come in." He hoped his voice sounded stronger than he felt.
The door opened, revealing _Mamm_ standing in the doorway.
"I thought I heard you come home." She stepped inside. "Did you go see Mandy?"
" _Ya_." He tried to sound causal.
"How is she?" _Mamm_ studied him with what looked like suspicion.
"Fine." Ephraim rubbed at the stubble on his chin. "Why?"
_Mamm_ closed the door and leaned against his dresser. "We both know why."
Ephraim blew out a deep sigh. "Did _Dat_ tell you or Katie Ann?"
"They're both concerned." _Mamm_ 's eyes filled with concern too. "Did you work things out with her?"
Ephraim shook his head as a messy knot of grief choked back his words.
_Mamm_ sank onto the bed beside him and looped her arm over his shoulders. "What happened?"
"We broke up for _gut_." He tried in vain to clear his throat. "The wedding is off."
"But you two were so in love, and you had such a strong relationship."
"Everything fell apart." He wiped at his eyes, hoping to keep his emotions at bay until after his mother left. But that was difficult as he told her about Mandy's latest suggestions. "That's not what I want. I don't want to live with her parents, and I don't want to be a brickmason. We argued, and then we broke up."
He paused as he tried to analyze his raging feelings. "I feel like she thinks our life here isn't _gut_ enough for her, as if being a farmer's _fraa_ isn't as _gut_ as being a brickmason's _fraa_. Or maybe it's not her. Maybe I'm worried that our life on the farm is too humble, and I'm projecting that onto her."
"You have no reason to be embarrassed by our life, Ephraim, and I doubt Mandy wouldn't be _froh_ living here. I think you're both reeling from all the changes our family is facing with Darlene's problems, and I'm sure planning a wedding so fast is stressful for her." _Mamm_ shook her head. "I'm sorry all your plans are in question because of your _schweschder_ 's problems."
"It's not your fault or Darlene's fault. It just happened, and Mandy can't adapt to it. That means we're not supposed to be together."
_Mamm_ cringed.
"What?"
"You're permitted to change your plans," _Mamm_ said. "You can become a brickmason if you want."
He shook his head. "No. I told you. That's not what I want. I'm supposed to be here. That's what _Dat_ and _Daadi_ said when I was a _bu_ , and I'm going to stick to that plan."
_Mamm_ gave him a sideways hug. "No one said you couldn't change your plans. We didn't plan for Uria and Darlene to come here, but we're _froh_ to have them. If you want to build a life with Mandy working for her _dat_ , then your _dat_ and I will support you. This is your life, Ephraim. Your _dat_ and I aren't going to dictate it for you. We pray our _kinner_ are healthy, _froh_ , and that they stay in the church and follow God. The rest is up to all of you. These are your lives."
Ephraim contemplated his mother's words and then shook his head. "That's another thing. God wants me here, too, doesn't he? I'm to honor _mei dat_. If Mandy can't live with me on this farm, she can't be _mei fraa_."
"Ephraim," _Mamm_ began, "you need to pray about that. I think you're misinterpreting what I said."
"I'm not." He swiped the back of his hand over his eyes. "I'm certain of it."
_Mamm_ nodded. "If that's what you believe, but I think you need to keep talking to God." She seemed to study him. "Are you all right?"
He gestured toward his pillow. "I just need some sleep."
_Mamm_ stood and faced him. "I'm here if you want to talk more."
" _Danki, Mamm._ "
" _Gut nacht_." She walked into the hallway, gently closing the door behind her.
Ephraim changed into shorts and a T-shirt, and then he climbed into bed. As he stared up at the ceiling, he recalled the pain in Mandy's beautiful face, and grief swelled inside him once again.
He missed her so much his heart ached, but he couldn't allow himself to change his roots for her. If his grandfather's farm wasn't good enough for Mandy, then how could he satisfy her for the rest of their lives? Nothing he could ever give her would be good enough.
Was he just self-conscious about the humble life he and Mandy would have on the farm and projecting that onto her? Was he so immersed in his own hurt that he wasn't thinking clearly?
He groaned and covered his eyes with his forearm. He only knew he missed Mandy and he grieved for the bright future that was at his fingertips a few days ago. It was as if their future had wilted and died like the leftover summer crops faltered when the cold weather invaded Henry's garden. Was it too late to save their relationship, or would it wither as the ground grew colder?
Rolling to his side, he sucked in a deep breath and waited for sleep to find him.
CHAPTER 5
Do you need help?"
Mandy looked at the far end of the porch as Katie Ann walked toward her the following morning. "What are you doing here?"
"Well, that's a nice hello." Katie Ann rested her hands on her hips.
"I'm sorry." Mandy sighed as she hung another pair of her father's trousers on the clothesline that stretched from the porch to the barn. " _Gude mariye_." She frowned. "I didn't get much sleep last night."
"I'm sure you didn't." Katie Ann joined her at the laundry basket, picked up another pair of trousers, and handed them to her. "I'm sorry about what happened. _Mei mamm_ told me the news. Ephraim won't talk to me, but he's talked to both _Mamm_ and _Dat_ , so I know what's been going on. Despite _mei bruder_ telling me to stay out of this, I would have come to offer you my support yesterday. But we had to move Darlene and her family to our _haus_."
"I know. _Danki._ " Mandy's bottom lip quivered as she hung the trousers on the clothesline. "I don't understand it. I thought my solutions made sense, but he got so upset, he broke up with me. As of today, I'm single again, and all my wedding plans were a waste."
" _Mei bruder_ is stubborn, pigheaded, ridiculous, or whatever word you want to use to describe him." Katie Ann handed her the last pair of trousers. "Just give him time to understand what he's done."
Mandy hung the trousers on the line. "He was adamant that he'd never consider living here and working as a brickmason, and then he said I think I'm too _gut_ to be a farmer's _fraa_." She looked down at the empty laundry basket and then at the full clothesline. "That's not true. I can't deny I'd like living here, but that doesn't mean I wouldn't like living with your family. I just thought we had an option for giving you all a less stressful life."
"I believe you, Mandy," Katie Ann said.
"But I also keep thinking maybe this isn't just him. It takes two for a relationship to work. Maybe I made a mistake, but if I did, I don't know how to fix it. If I hurt him by accident, how do I fix what's broken between us? My parents say I should talk to him and really listen, but I don't know when he'll be ready. I've never seen him like this."
"Why don't we go inside and have tea?" Katie Ann rubbed Mandy's arm.
"Okay." Mandy lifted the laundry basket and followed Katie Ann into the house.
After storing the basket in the utility room, Mandy filled the kettle and set it on the stove while Katie Ann took mugs and tea bags out of a cabinet. From upstairs her mother's sewing machine chattered, telling her _Mamm_ and Rhoda were busy working on projects for their customers. She set a container of iced oatmeal cookies on the counter and then pulled out sweetener and milk. Once the kettle whistled, Katie Ann filled the mugs and brought them to the table.
They sipped their tea and ate cookies in silence for a few minutes. Mandy lost herself in regret, analyzing what she'd said, wondering what she could have said to Ephraim that might have changed the outcome of their conversation the night before.
Katie Ann's voice broke through Mandy's mental gymnastics. " _Mei mamm_ said Ephraim was really upset last night. She talked to him when he got home. He was heartbroken, so I think he's going to realize he made a huge mistake."
Mandy fought the tears filling her eyes. "If he regretted it, why didn't he come back to see me last night and make things right? He said some terrible things to me. He even called me spoiled because _mei haus_ is bigger than yours." Mandy wiped her eyes with her fingertips. "He was really mean. It was like he became another person."
Katie Ann pressed her lips together. "He's always had a terrible temper. Do you want me to talk to him? I can try to make him realize how ridiculous he's being."
Mandy shook her head. "I don't think so. He'll think I asked you to, and it might make things worse."
"I don't think it could get any worse." Katie Ann picked up another cookie and took a bite.
"I just don't understand it. I thought I was suggesting great ideas." Mandy waved a cookie around for emphasis as her eyes stung with fresh tears. "Why does it matter where we live if we truly love each other?"
"You're exactly right. I understand he's always wanted to be a farmer, but _mei bruder_ is being a dolt. He's letting his pride get in the way." Katie Ann shook her head as she scowled.
Mandy took a sip of tea. "How is your family adjusting now that Darlene and her family have moved in?"
"It's noisy." Katie Ann crumpled a paper napkin as she spoke. "And it's a little tight in my room with the girls there." She smiled. "But we did a lot of giggling last night. It will take some time to get used to having two people with me, along with two more dressers and a cot. Thankfully, my room is fairly large." She smoothed out the napkin again. " _Mei dat_ said he'll get started on their _haus_ as soon as he can in the spring. This will be temporary. I love _mei bruderskinner._ It's just an adjustment."
"Just like it would be for Ephraim and me if he'd consider what I suggested." Mandy rested her chin on her palm as guilt rained down on her. Maybe she'd made a mistake by suggesting they take another path. Had she not taken everything Ephraim might be feeling into consideration?
She had to find a way to talk to him.
"Hello." Mandy stepped into Emma's kitchen and set a container of lemon bars on the counter. "I brought you a special snack."
"Mandy!" Emma moved across the room's expanse to meet her. "It's so _gut_ to see you. How are you?"
She shrugged as she touched the container. "I've been baking a lot. _Mei schweschder_ says it's a coping mechanism."
"A coping mechanism?" Emma opened the container. "Oh my! Look at those lemon bars."
"Have one. They're pretty _gut_." Mandy leaned back against the counter. "I'm going to try a similar recipe later when I get home. I'll bring you some."
Emma picked up a bar and then looked at Mandy. "What's going on?"
"You haven't heard?" Mandy asked. When a meow sounded, she looked down. Hank was walking back and forth, rubbing against her shins. "Hi, Hank."
"I haven't heard what?" Emma asked.
"Ephraim and I broke up." Mandy went to the table and sat down in a chair. "It's been two days. I feel like I'm going out of my mind. I'm baking to stay busy."
Emma gasped as she sat down across from her. "What happened?"
Mandy told her the entire story while drawing imaginary circles on the tabletop with her fingertip. When she finished, she looked up and found Hank sitting next to her, his attention focused on her.
"What do you think, Hank?" Mandy rubbed the cat's ear, and he tilted his head toward her and purred.
"Hank and I think you shouldn't give up." Emma smiled at her. "The issues may be deeper than what you're seeing on the surface. I think you're feeling overwhelmed, and Ephraim is doubting the wisdom of marrying you because your suggestions may have made him feel less-than. If you take a step back and look at the whole picture, you might agree with me."
"So it's all my fault?" Mandy felt as if the breath rushed out of her lungs at the possibility that she caused the breakup.
"No, no, no." Emma reached for her hands. "Your suggestions are mature. I commend you for wanting to slow down and not rush your wedding. Many young women are so obsessed with the wedding that they lose sight of what's really important—their marriage. That's your future. Taking your time and doing what's right is a grown-up decision. But you also need to look at this from Ephraim's perspective. He loves you so much he doesn't want to wait to marry you. But he comes from a line of farmers. He might have taken your suggestions as an insult to the way of life his family has lived for many generations."
"So I need to forget the idea of living with my parents? And I was wrong to suggest that he learn a new trade?" Mandy's heart ached as she recalled the pain and anger lining Ephraim's handsome face when he told her their relationship was over.
Emma touched one ribbon of her prayer covering and paused as if contemplating the correct response. "No, I don't think you were wrong, but I believe he reacted out of hurt. Married to Henry, I learned I had to take his feelings into consideration, no matter how certain I was that my point of view was right. Two people make a marriage, and the only way it will work is if those two people listen to each other and compromise. Together you and Ephraim can find a solution. Just like our crops in Henry's garden needed both sun and water, you two need to work together to nourish and grow your relationship."
"Oh." Mandy's thoughts were spinning so fast she thought she might pass out. Guilt and shame wrapped around her chest, squeezing at her lungs. "I was selfish and pushy when I insisted he consider my ideas, let alone just go along with them. I didn't consider how he might feel." Her bottom lip trembled. "What if he doesn't forgive me?"
"Everything will be fine, Mandy. You just need to talk to him, calmly." Emma stood and retrieved the lemon bars from the counter. "These are positively scrumptious. _Danki_ for sharing them with me." She set the container in the center of the table and took another bar. "Talk to Ephraim and discuss your options. Also pray for him. Ask God to help him see that you do love him and want to marry him." She smiled at Mandy. "Don't give up hope. You and Ephraim can work it out, but you can only do it together."
"Okay." If their hearts could get past the hurt.
"Now, are we going to get started on canning today?"
" _Ya_ , I'm ready. And Katie Ann and Clara plan to be here a bit later." Soon she and Emma were gathering supplies, and Tena came downstairs to join them. It felt good to talk and even laugh as they started canning the last of the beans, carrots, and corn they'd grown in the garden.
When the back door opened and then clicked closed, Mandy turned her attention to the mudroom doorway.
"Do I smell lemon bars?" Wayne asked.
" _Ya_ , Mandy made them," Tena told him. "Come have one."
Wayne stepped into the kitchen, and Mandy's stomach seemed to drop when Ephraim appeared behind him. He froze in the doorway as his striking brown eyes focused on hers. Then his lips formed a thin line, but his eyes seemed to plead with her. Did he want to fix things between them? Or did he want her to leave? She longed to read his mind as the intensity in his gaze sent goose bumps ripping up her arms.
Wayne took a lemon bar from the container and took a big bite. After swallowing, he turned to Ephraim. "These are fantastic." He held up his half-eaten bar. "You need to try one."
Ephraim took one from the container, bit into it, and nodded at Mandy. "It's _appeditlich_."
" _Danki_." Mandy cleared her throat as she tried to hide the sadness his formal tone caused her.
Ephraim looked at Wayne. "We should get outside and start on our project."
"What project?" Tena asked.
Wayne swiped another bar from the container. "We're going to replace some of the boards on the shed doors. I want to get this done before it gets any colder."
When Mandy felt Ephraim's stare burning into her, she kept her focus on Emma. "Why don't we go through your cookbooks, Emma? We could find something fun to make when we're finished canning."
" _Wunderbaar_." Emma stood and turned to Wayne. " _Danki_ for fixing the shed doors. Let me know what I owe you for supplies."
"It's no problem." Wayne held up his hand. Then he winked at Tena. "See you soon."
" _Ya_ , you will." Tena grinned at him, and the love that passed between them made Mandy's heart crumble even more.
Ephraim gave Mandy a brief glance and then walked out the back door with Wayne.
"Am I missing something?" Tena asked Mandy after the men disappeared outside. "You and Ephraim were a bit cold to each other."
"I'll tell you while we work."
"You're telling me you broke up with Mandy because she suggested you wait a few months to get married, then move in with her parents, build a house on her _dat_ 's land, and have the chance for a new career?" Wayne asked as they removed the old shed door from the hinges.
" _Ya_ , I guess that sums it up." Ephraim shrugged.
"Don't you think you overreacted?" Wayne turned toward him.
"No, I don't." Ephraim looked down at the rotten wood to avoid Wayne's accusing stare. By this morning, he'd decided he hadn't made a mistake. No matter what she said, deep down, Mandy was having doubts about their relationship. He was sure of it, but he didn't want to tell Wayne that. "She knows I've always planned to be a farmer and take over _mei dat_ 's farm someday."
"But plans can change," Wayne said. "Isn't being together the most important plan of all?"
"Why don't we stay focused on this repair instead of my breakup?" He pointed to the door.
"Hey," Jerry said as he and Chris approached. "Are we ready to work on the shed today?"
Ephraim looked past them to where Katie Ann and Clara climbed the porch steps and headed into the house. Why didn't his sister mention this was the canning day at Emma's? In a matter of minutes, all the women would know he and Mandy had broken their engagement and ended their nearly one-year relationship.
Why should he let Wayne make him feel guilty? Mandy was the one who suggested they change their plans. She was the one who was changing her mind about him. This was her fault, not his!
But then why did he lie awake at night, analyzing their argument over and over? Why did he find himself contemplating what life would be like if he became a brickmason?
"Ephraim?"
"What?" He looked up at Jerry.
"What has you so distracted?" Jerry asked, a grin tugging at his lips.
"You haven't heard?" Wayne asked. "Ephraim and Mandy broke up on Tuesday."
Ephraim swallowed a groan. _Here we go. Now they'll all analyze my life and tell me what I've done wrong._
"Are you serious?" Jerry asked. "Katie Ann didn't say anything on the ride over here."
"Katie Ann told me yesterday." Chris frowned at Ephraim. "You're honestly going to let her get away because you're too stubborn to even consider living with her parents and working for her _dat_?"
"That's why you broke up?" Jerry asked.
"Worse," Wayne told him. "This all started just because Mandy suggested they delay the wedding a few months. She had _gut_ reasons too."
"Look. This is my business." Ephraim held up his hands. "I really don't need your opinions."
"That's too bad." Jerry sat down on a plastic crate and looked up at him. "You're going to get our opinions, so take them like a man." His other friends mumbled their agreement. "Don't you love her?"
" _Ya_." Ephraim leaned back against the shed. "Of course I do."
"Then why are you letting a little change of plans ruin your future with the _maedel_ you love?"
"A little change of plans?" Ephraim gestured widely. "Are you kidding me? Moving off my parents' farm would be a huge change. And what do I know about being a brickmason?"
"So you're afraid to learn a new trade?" Jerry snorted. "Do you think I knew anything about being a plumber when I first went to work for _mei onkel?_ Now I'm his assistant manager and working my way up to being his partner. You might like a career change."
"This farm has been in my family for generations. How can I walk away from that?" Ephraim demanded.
"Darlene and her family moved in, and Uria can help run the farm now," Chris said as he sat down beside Jerry. "It's okay to learn a new trade, Ephraim. It's all about finding stability for you and Mandy, and from what I hear, considering what might be best for your parents and older _schweschder_ and her family too. Besides, you could take over her _dat's_ business someday. He has two _dochdern_ , and you'll be his first _sohn_."
"He's right." Wayne shrugged. "You need to think about what you're gaining, not what you're losing."
"That's enough." Ephraim threw down his tool. "I didn't come here today for a lecture. I came here to work on this shed."
"And you wanted to see your ex-fiancée," Wayne muttered.
Ephraim spun and kicked the side of the shed, sending searing pain radiating from his toe up to his shin. "I didn't know she'd be here today."
"I don't think breaking your foot is going to fix things between you and Mandy," Wayne quipped.
"He's right, Ephraim," Jerry added. "You need to relax."
"Can we please fix these shed doors and stop analyzing my life?" He needed them to stop bugging him. How could he share the truth? He was afraid Mandy just didn't love him enough to live on the farm with him, that she didn't think he was worth what she considered a sacrifice. He didn't want to admit how much that possibility hurt.
"Fine, fine." Jerry picked up a hammer. "Let's give Ephraim a break."
As Ephraim turned his attention to the shed, his mind spun with his friends' words and unsolicited advice. He looked toward the house and imagined Mandy sitting at the kitchen table, telling her friends about their breakup. Were they also giving her unsolicited advice? He tried to redirect his thoughts to the task at hand, but his mind lingered on Mandy and the pain he'd seen in her eyes this morning. Did she miss him as much as he missed her?
Then why wouldn't she just agree that their original plan to marry in December and live with his family was best?
He shoved away the thoughts. She was the one who wanted to change their plans. This breakup was _her_ fault.
Still, his heart yearned for her.
"Do you need a ride home?" Katie Ann asked Mandy as they pulled on their coats that afternoon.
" _Ya_ , I guess so. It would save me some money." Mandy buttoned her coat. " _Mei dat_ paid his driver to drop me off since he needed his horse and buggy today."
"You can ride with Chris and me." Katie Ann gestured for Mandy to follow her.
Mandy said good-bye to Emma, Clara, and Tena and then headed outside with Katie Ann. As they walked down the path to the waiting buggies, Mandy slowed her steps when she spotted Ephraim standing with Chris, remembering how uncomfortable he'd made everyone feel as they all gathered around Emma's table for lunch.
"It's okay." Katie Ann took Mandy's arm and guided her toward the buggy. "You don't have to feel awkward around him."
Mandy walked over to Chris's buggy and climbed into the back.
"I'll see you later," Chris told Ephraim.
"All right." Ephraim hesitated, but then he looked into the buggy.
Mandy sucked in a breath as she took in his stoic expression. She lifted her hand to wave to him.
With a frown, Ephraim nodded at her and then walked to his own horse and buggy.
Mandy released the breath she'd been holding and then settled into the back of the buggy as Katie Ann and Chris climbed onto the bench seat in front of her.
As Chris guided the buggy toward the road, she hugged her arms to her chest and recalled her conversation with her friends while they finished canning the vegetables. While they had all offered her kind encouragement and told her to pray and ask God to guide her heart, their words felt empty of hope. Of course she would pray, but she still felt like a third wheel sitting in the back of her best friend's buggy while her ex-fiancé rode home alone. And Ephraim showed no signs of wanting to talk.
Holding back tears, Mandy closed her eyes and asked God to somehow heal their broken relationship. She couldn't do it by herself.
CHAPTER 6
As conversations swirled around him at the breakfast table Saturday morning, Ephraim scooped home fries onto his plate and then forked a few into his mouth.
" _Onkel_ Ephraim?"
He looked to his left, where Rebekah sat. " _Ya?_ "
"Do you like potatoes?"
"I do." He couldn't stop a grin as he pointed to his plate. "This is my second pile of home fries."
"Oh." Rebekah scrunched her nose and then looked back at her eggs.
"Why do you look so disgusted?" he asked.
"Savannah says home fries are gross because potatoes grow in the ground and are dirty," Rebekah said.
"I didn't say that!" Savannah exclaimed from across the table.
"Savannah!" Darlene scolded. "No yelling in the _haus_."
"I never said that," Savannah hissed.
" _Ya_ , you did," Rebekah retorted.
"You know, your _mammi_ washes the potatoes before she makes the home fries, so the potatoes aren't dirty when we eat them." Ephraim tried in vain to hide his smile.
"Oh." Rebekah tapped her finger against her chin as she considered this. "So they aren't yucky when you eat them?"
"No, they aren't." Ephraim scooped another mouthful onto his fork.
"May I please have some?" Rebekah pushed her plate toward Ephraim.
"Of course." Ephraim shifted some onto her plate and then smiled at Darlene.
" _Maed_." Darlene rolled her eyes and then smiled at Uria.
Ephraim stopped chewing as he watched his older sister and brother-in-law grin at each other. The adoration sparking between them stole his breath for a moment. Could he have had that same deep love and affection in marriage with Mandy? The thought felt like a bucket of frigid water drenching him after a long, hot shower.
He turned his attention to his nieces. Would he and Mandy have had children? Would they have had daughters who were as beautiful as Mandy with her golden hair and stunning blue eyes? The potatoes soured in his mouth. How could he have let her slip through his fingers?
"Ephraim, are you going to Emma's today?" Katie Ann's question cut through his thoughts and swelling regret.
"Maybe later." He lifted his glass of orange juice. "I have chores to do first."
"Chris is going to pick me up in about an hour," Katie Ann said. "Maybe I'll see you there."
Ephraim nodded. Part of him wanted to avoid Emma's so he didn't have to see Mandy, but another part of him wanted to go to Emma's every day to sneak a glimpse at Mandy. When would he stop feeling so confused?
When he was finished with his meal, he carried his dishes to the counter. Then he pulled on his hat, coat, and boots in the mudroom and headed out to the barn.
He did his best to push thoughts of Mandy out of his head as he began to muck the horse stalls, but her gorgeous smile crept back in. The muscles in his arms and back burned as he worked harder and harder, trying to erase her from his mind's eye. But she lingered there, taunting him as he raked with all his strength.
"You're going to break that pitchfork in half."
Ephraim turned and found his father standing at the end of the stall. He leaned the pitchfork against the wall and swiped his sleeve over his sweaty brow.
"How are you?" _Dat_ 's dark eyes seemed to study him.
"I'm okay." Ephraim shrugged and picked up the pitchfork again. "I have a lot of work to do."
"Do you miss her?" _Dat_ 's question caught him off guard.
Ephraim froze. Was it that obvious? He returned to work in hopes his father would walk away.
"If you do, maybe you should try talking to her."
Ephraim stopped working and looked at his father. "I've tried talking to her, but we want different things."
"That's the thing about marriage," _Dat_ began as he leaned on the stall door. "It only works if you compromise."
"We're not married." Ephraim shook his head.
"And you never will be if you don't start thinking like a couple."
"What does that mean?"
"When you marry, you become one, but you can't behave as if you're not. Take a step back and think about her point of view. Be careful not to jump to any conclusions about her intentions. Your _mamm_ told me you're afraid Mandy doesn't want to be a farmer's _fraa._ You could be completely wrong about that. Don't fall into the trap of projecting your insecurities onto her. You need to talk this out."
_Dat_ tapped the stall door. "Let me know if you want to talk more about it."
Ephraim watched his father walk away as his words marinated in his mind. Maybe he had misinterpreted Mandy's reasons for suggesting they change their plans. He did owe it to her to try to talk this out, but what if her words just hurt him more? He was still reeling from their last discussion.
His father made it sound so easy, but how could Ephraim even consider just walking away from his family's legacy and starting a new life when it felt so wrong?
Still, he couldn't deny that he missed Mandy, and as much as he tried, he couldn't erase her beautiful face from his mind.
Mandy searched her bedroom as panic dug into her shoulders. Where was her purse? She'd seen it just last night, but it wasn't on her dresser where she always left it. She looked on the floor, under her bed, and on her windowsill. Had she left it downstairs somewhere?
She stepped out into the hallway and into the sewing room, where she spotted her purse on the sewing table. She didn't even recall walking in here yesterday. When she crossed the room and picked up her purse, her eyes focused on the half-finished, baby-blue dress on the table. She froze, cemented in place.
Her wedding dress.
Tears stung her eyes as she ran her fingers over the material. Beside it was a bolt of material to make the dress for Rhoda.
But now the dresses would never be finished. The wedding would never happen.
Mandy wiped away a tear. How she missed Ephraim. She missed his smile, his boisterous laugh, their long talks, their friendship.
"Is there anything I can do to fix it?" She whispered the question as if someone would answer.
Then an idea sparked in her brain. What if she took his favorite cookies—peanut butter—to Emma's today? If he came, she could use them to try to encourage him to talk to her. She'd baked some last night. Baking seemed to be her only solace during this unending and unbearable heartbreak.
Had she subconsciously made the peanut butter cookies because she missed him? Probably.
"Mandy!" _Mamm_ 's voice sounded from downstairs. "Katie Ann is here!"
"Coming!" Mandy touched the dress one last time, and then she hurried down to the kitchen, where she said hello to her friend.
After she grabbed the container of peanut butter cookies and put on her coat, she and Katie Ann stepped outside and she climbed into the back of Chris's buggy.
" _Danki_ for picking me up," Mandy told Chris after she was settled.
" _Gern gschehne_ ," Chris said.
Katie Ann turned around and pointed to the container. "What are those?"
_"Kichlin."_
"What kind?"
"Peanut butter."
"Oh. Are they for _mei bruder_?"
"Maybe." Mandy tried to sound casual. "How is he?"
"Grumpy and mopey." Katie Ann rolled her eyes. "It's so obvious he misses you. If he wasn't so stubborn, you'd be back together already."
Mandy hugged the cookies to her chest. Would they be enough to encourage him to talk through their problems so they could work out a compromise?
"How are you doing, Mandy?" Chris asked.
"I'm getting by. I'm baking a lot." Mandy ran her fingers over the top of the container. " _Mei mamm_ said we should open a bake stand at the _haus_." She gave a little laugh, but it didn't warm her troubled soul.
"Don't give up on Ephraim, okay?" Chris asked.
Mandy nodded.
"We're all working on him," Chris continued.
"You are?" Mandy leaned forward. "What do you mean?"
"Just trust us." Katie Ann smiled at her.
Ephraim leaned on Emma's fence as Jerry told him and Wayne about a plumbing job at a rich _Englisher_ 's house. When a horse and buggy appeared in the driveway, Ephraim stood up straight, and his pulse picked up.
Chris and Katie Ann climbed out, and then Mandy did before turning and removing a large container from the back seat. As she and Katie Ann walked toward the house, Ephraim admired her from afar. He'd always enjoyed seeing her in blue.
Mandy turned toward him, smiled, and lifted her hand in a wave. His heartbeat thumped as he returned the gesture before she disappeared into the house.
"Why don't you go talk to her instead of staring at her like a stalker?" Wayne gave Ephraim a shove.
"Why don't you mind your own business?"
"Who are you trying to kid?" Jerry chimed in. "You still love her, and you miss her. So why are you standing here with us?"
Ephraim scowled. "Why don't you worry about your own relationship?"
"Give it a rest, Blank," Chris added as he came to stand with the rest of them. "Just go talk to Mandy. We're all tired of your moods."
Ephraim divided a look among his friends as they all pointed toward the house. He hated to admit it, but maybe they were right. Perhaps it was time to talk through their problems. "Fine."
They applauded as he walked toward the house, and Ephraim rolled his eyes. Despite the cold weather, his hands began to sweat. What if Mandy refused to talk to him? But she'd waved and smiled at him just now, so that was a good sign. She must still care for him.
Ephraim squared his shoulders as he entered the kitchen, where Mandy stood with Clara and Tena. Her friends turned to look at him, and their eyes rounded.
"Tena," Clara said, "why don't we set up the stand?" They both gripped the handles of two big bags of apples.
" _Gut_ idea." Tena hurried out the back door with Clara close behind.
He glanced at the table, where Katie Ann and Emma weren't even pretending they weren't watching him. Mandy picked up the container he'd seen her carrying and held it up to him. "I brought peanut butter _kichlin_."
"You did?" Warmth filled his chest as he walked over to her.
Mandy nodded. "Your favorite."
"Do you mean you made them for me?"
" _Ya_ , I guess so." She removed the lid. "Try one."
" _Danki_." He took a cookie, and when their hands brushed, he felt electricity spark in the air around them. It suddenly felt as if they were the only two people in the room. He lost himself in the depth of her blue eyes as he bit into the cookie and savored the sweet peanut-buttery taste.
"Do you like them?" Mandy's expression seemed hopeful.
He nodded as he swallowed. " _Ya_ , I do. Can we talk?" He heard the thread of hope in his voice.
Her eyes glistened, and she nodded toward the doorway. "Let's go into the _schtupp_."
Mandy set the container of cookies on the counter, and she and Katie Ann shared a knowing look before they headed out of the room. Were Mandy and his younger sister planning something? The thought sent suspicion curling through him.
He followed Mandy into the family room, where Hank slept curled up in a ball on what used to be Henry's chair. Ephraim shook his head at the cat and then sat down on the sofa.
Mandy lowered herself into a chair across from him. "How's your family?"
"Okay." Ephraim shrugged. "I guess we're all getting used to each other. I have to make a strategic plan to get into the bathroom first in the morning." He gave her a sheepish grin, and she laughed. How he'd missed that sweet lilt. "How are you?"
"I'm surviving." She folded her hands in her lap. "I miss you. I miss us."
"Can't we make this work?" He leaned forward. "We could still get married in December."
Her expression changed. She'd seemed so open, but now she looked . . . determined.
"No. December is still too soon. I walked into the sewing room this morning, and I saw my wedding dress. It's not even half done. I've been telling you I don't have time. Why won't you believe me?"
"I'll get you help. And _mei dat_ thinks Darlene and her family will be in their _haus_ by late spring. The _haus_ would be crowded only for a few months."
"Ephraim, you're not listening to me."
All his hope dissolved as he stared at her. "So you miss me, but you're not willing to compromise?"
She pointed to her chest. "I'm not willing to compromise?" Then she pointed at him. "No, you're the one who isn't willing to compromise. You're just saying we should follow through with the original plan. You won't even consider how I feel and my proposals for our future. You're the one who's stubborn and stuck on only one plan."
He stood. She didn't love him. At least not enough. "This is a waste of time."
"Really, Ephraim?" She stood and jammed her hands on her small hips. "That's how you see me? I'm a waste of time? Do you even love me?"
"Does it matter?" he said, challenging her.
" _Ya_ , it does matter." She lifted her chin. "I want to marry you and build a life together, but you're too obstinate to even consider delaying the wedding, let alone my other suggestions. This can never work if you don't respect my opinions."
He stared at her as his father's words echoed in his mind. Was she right? Did he have to bend to her for their relationship to work?
But Ephraim was a farmer. He came from a line of farmers. How could he abandon his heritage for her? And he still thought delaying the wedding was her way of letting him know she wasn't sure they were right for each other, even if she didn't realize it. Even if she said she loved him.
"Forget it." He waved her off and marched out the front door, the muscles in his back aching with growing frustration, his heart breaking again.
Mandy wilted as Ephraim stalked out of the house.
_Meow?_
Hank stood on his back legs and rested his front paws on her thigh. She wiped away her tears. "He's incorrigible, Hank. I have to face the fact that it's over." She rubbed the cat's chin, and he responded with a purr.
But was it truly all Ephraim's fault? She'd been so incensed when he asked her to stick with the original plan that she hadn't even asked him why he'd been so upset. She hadn't followed Emma's or her parents' suggestions of listening to him and then respecting his opinion. Maybe he wasn't the only one to blame for their problems.
"Don't say it's over." Katie Ann's expression was fierce as she stood in the doorway to the kitchen. "I'll talk to him tonight. I'll tell him he needs to give your relationship another chance."
Mandy nodded, but in her heart, she was certain Katie Ann's efforts would be wasted.
Ephraim walked up his family's back-porch steps later and saw Katie Ann sitting on the glider. He set his lantern on the railing and then leaned against it. "Isn't it late for you to be outside in the cold?"
"I've been waiting for you ever since Chris brought me home." She pushed the glider into motion as she looked up at him. "Where have you been?"
"I took a drive. Why?"
"We need to talk." She pointed at him. "Why are you being such an imbecile?"
"Excuse me?" Irritation colored his words.
"If you keep pushing Mandy away, you'll eventually lose her forever." Katie Ann stood and wagged a finger at him. "You're going to regret it when you realize how stupid you've been."
"I think you need to mind your own business." He picked up the lantern and moved toward the back door.
"It's kind of hard to mind my own business when I care about both of you and want you both to be _froh._ Everyone can see how much you love each other. Why can't you take a step back and listen to what Mandy has to say?"
He spun to face her. "I have listened, and we want different things. That's why it can't work between us."
Katie Ann threw up her hands. "Why does it matter so much where you live or where you work?"
"Because I'm a Blank!" He pointed to the ground. "I belong _here_. And _mei_ future _kinner_ belong here. I don't want to live with Mandy's parents or become a brickmason."
"Do you think Uria wanted to give up working construction to become a dairy farmer?" Katie Ann crossed the porch and stood in front of him. "Darlene and Uria are making the best of a tough situation. Why can't you and Mandy do the same for the sake of your love for each other?"
Ephraim stilled as Katie Ann's words rolled over him, but he didn't want to talk anymore. " _Gut nacht._ "
Yet as he climbed the stairs, he wondered if his sister could be right. _Mamm_ said she and _Dat_ would support whatever he decided. But would he dishonor his grandfather if he abandoned the farm that had sustained and defined his family for generations? He had to think about that too.
CHAPTER 7
Have you talked to Ephraim?" Tena asked as Mandy entered Emma's kitchen Monday afternoon.
"No. He wouldn't even look at me at church yesterday, and you know he didn't come to our garden meeting." Mandy sat down at the table across from Tena and Emma and set a container in the center. "I can't believe we've been apart for more than a week now. It feels like an eternity." She sighed. "I came so you could try my cheesecake. I baked all morning, and even Rhoda and _Dat_ are saying they can't eat it all."
" _Ach, mei liewe_." Emma shook her head. "It's only been eight days. Don't give up yet."
"It's difficult not to. After our argument on Saturday, I've kind of lost hope." Mandy removed the lid from the cake saver, and the sweet smell of the cake filled the kitchen.
"All the guys are trying to make him realize he's made a huge mistake by being so prideful." Tena stood and crossed to the counter, where she took plates from a cabinet and forks from a drawer.
"They're still trying to get through to him?" Mandy heard the thread of hope in her voice.
"Oh _ya_." Tena brought the plates and forks to the table and then returned to the counter. "Even Katie Ann said she's working on him."
"I know." Mandy frowned as her hope deflated like a balloon. "She told me Saturday she was going to talk to him. I was hoping he'd show up at _mei haus_ and ask to talk to me last night. I was imagining us sitting on the back-porch glider despite the cold, working out all our issues. Then he'd propose to me again. But he didn't come. It's just a _gegisch_ dream."
"Don't give up on that dream." Tena brought a knife and cake server to the table. "Someone will get through his stubborn head."
"I hope so." Mandy stared at the cake. "I'll run out of baking supplies."
Emma and Tena laughed, and Mandy felt the corner of her lips turn up into a smile.
"I think that cake is too _schee_ to eat," Emma said.
"No." Tena shook her head. "It's too _schee_ to waste."
As Tena cut into the cake, Mandy smiled. Despite her overwhelming sadness over losing Ephraim, she was so grateful for her wonderful friends.
Ephraim shivered as he walked out to the pasture fence. His father stood looking up as the sunset soaked the sky with shades of orange and yellow. The horizon was like a brilliant watercolor painting.
" _Mamm_ was looking for you." Ephraim stood beside him and leaned on the fence. "What are you doing?"
"Enjoying the sunset." _Dat_ gave him a sideways glance. "Sometimes you have to stop and enjoy the beauty of God's creation."
Ephraim set his foot on the bottom rung of the split-rail fence. Then he rested his chin on his palm and his thoughts turned to Mandy for the hundredth time today. Was she watching the sunset too? He slammed his eyes shut. Why did she invade all his thoughts?
"When your _mamm_ and I first married, we argued nearly all the time."
Ephraim turned toward his father, curious. "Why?"
_Dat_ shrugged. "I think most newlyweds go through a similar phase. You're trying to get used to living together, and you're adjusting to each other's moods. _Mei dat_ used to say love is blind and marriage is the eye-opener." His loud belly laugh echoed throughout the pasture, and Ephraim couldn't stop a smile.
" _Daadi_ really said that?"
"All the time." _Dat_ wiped at his eyes. "Your _mamm_ and I were young, and we had a lot of growing up to do. We didn't have a _haus_ , and we didn't have any money. Your bedroom was our bedroom until your _mammi_ and _daadi_ retired and moved into the _daadihaus_ on _mei bruder_ 's land." He pointed across the pasture toward his younger brother's farm, nearly twenty acres away from them.
"I didn't know that." Ephraim studied his father. "I thought you and _mamm_ moved into this _haus_ after my grandparents retired."
"Sometimes your plans aren't what you expect, but love and faith will get you through." _Dat_ patted Ephraim's shoulder. "Like your _mamm_ told you last week, it's okay if you decide to move off this land. You can decide to learn a new kind of work. Your _mamm_ and I will support you no matter what you decide to do, and I know your _daadi_ would have too. He always cared more about family than he cared about this land. Just don't let your stubborn pride stand in the way of your future with Mandy."
Ephraim stilled as his father's words washed over him. Despite their wisdom, he still had no idea what path he should choose.
He suddenly felt an overwhelming need for God's love and support through all his crushing confusion. Why hadn't he sought that more? As he looked toward the sunset, he opened his heart and silently began to pray.
_God, please lead me on the path you've chosen for me. I love Mandy with all my heart, but I'm confused. Am I supposed to be with her? If so, am I supposed to abandon my dream of running_ mei dat' _s farm and become a brickmason? Please send me a sign._
Mandy leaned her head against the doorframe as the sewing machine hummed while her sister worked. Her eyes moved to the unfinished wedding dress on the table, and renewed regret surged through her.
Rhoda stopped and looked up at her. "How long have you been staring at me?"
"Just a few minutes." Mandy stepped into the room and sat down on a chair next to her. "What are you making?"
"Just a dress." Rhoda held up the light-blue frock. "I thought it would be _schee_ for church."
"It's lovely." Mandy touched the material and then looked again at her unfinished wedding dress. "You should make something out of that. I'll never wear it."
"Stop." Rhoda frowned. "You're giving up too easily."
Mandy tilted her head as she crossed one leg over the other. Maybe she had given up too easily. Maybe she'd been too prideful.
"I think you're right," Mandy whispered.
"Give Ephraim another chance." Rhoda touched Mandy's arm. "And always have faith."
Mandy touched the unfinished dress. Would she ever wear it? Or would it just remain half sewn, sitting patiently on the table, collecting dust? If her sister was right, there was still a chance she and Ephraim could work things out. A tiny seed of hope took root in her chest, but she didn't know where to begin when Ephraim was so angry with her.
Mandy folded her hands as she sat between Katie Ann and Rhoda at church the following Sunday. She stared down at the lap of her pink dress while the bishop preached from the book of John.
She glanced to the far side of the barn where Ephraim sat between Wayne and Jerry. She took in his handsome face with its strong chiseled jaw and his long, thin nose. He was the most handsome man she knew.
When the bishop announced it was time for the fifteen-minute kneeling prayer, she knelt facing the bench and leaned forward on it. Then she opened her heart.
_God, I was blessed when Ephraim asked me to be his girlfriend almost a year ago. I had never been so_ froh _in my life. When he proposed, I felt blessed beyond measure. Please help Ephraim and me find our relationship again. I believe he still loves me, and I know to the depth of my soul that I still love him. Help us find a compromise for our future. Please lead him back to me. Only you can help us mend our broken relationship._
Mandy opened her eyes and felt warmth encircle her like a loving hug. It was as if God were comforting her. She knew then that, somehow, everything was going to be okay. Maybe she could find a way to let Ephraim know she still cared.
"Have you talked to Mandy?" Jerry asked Ephraim as he sat across from him during lunch.
"No." Ephraim stared at the lunch meat and bread on his plate. Mandy looked beautiful today. He'd tried to keep from staring at her across the barn during the service, but his eyes betrayed him. At one point, their gazes collided, and heat crawled up his neck to his cheeks. Had she felt the same heat when she looked at him?
"Why are you avoiding her?" Wayne asked. "Why are you letting her slip through your fingers?"
"Don't you want to work it out?" Jerry added.
"Quit ganging up on me. It's my business." Ephraim looked up as Mandy approached with a carafe.
He swallowed as that familiar heat began traveling up his neck. She was the most beautiful woman in their district, if not the entire state of Pennsylvania. Her pink dress complemented her rosy complexion, and her gorgeous blue eyes sparkled as she filled a man's cup and smiled. How he longed to touch her face and tell her how much she meant to him. He still loved her. He was certain of that.
His father's advice tumbled through his mind. But how could they work out their problems if they didn't agree on their future together?
Mandy filled his friends' cups and then turned to him.
" _Kaffi?_ " Her gaze met his as she held up the carafe.
" _Ya._ Please." He lifted his cup and she filled it. " _Danki_."
" _Gern gschehne_." She lingered for a moment, and he was certain the world had stopped turning just for them.
_I love you, Mandy._
If only he could say the words aloud. Would she say them back to him?
"Could I have some _kaffi_?" A man called from nearby, breaking through their trance.
"Excuse me." Mandy cleared her throat and moved on to the neighboring table.
"You need to talk to her." Jerry's voice was close to Ephraim's ear. "How would you feel if she fell in love with someone else while you were still stuck obsessing about where you want to live? Don't you think you'd feel like a moron for not seeing where God was trying to lead you?"
"It's too late now." Ephraim shook his head. "I think I've missed my chance with her. We've said some horrible things to each other."
"You know that's not true. I saw the way she just looked at you." Wayne's expression was serious. "Listen, I said terrible things to Tena when we argued, and she still forgave me. We all say terrible things out of anger. That's part of being human. We're all taught to forgive, and Mandy will forgive you if you ask her to."
Ephraim picked up his cup, wondering if Wayne could be right, wondering if everyone had been right. Wondering if God would send him that sign. Until he had one, he didn't know what to do.
CHAPTER 8
I can't believe Thanksgiving is this Thursday," Clara said as she sat next to Mandy at Emma's table the following Sunday afternoon. "November has flown by."
Mandy glanced across the table at Ephraim as he sat slumped in his chair between Katie Ann and Wayne. She felt awkward and uncomfortable not sitting beside him. He seemed to feel uncomfortable just being in her presence.
After the intense stare they'd shared after the church service last week, she'd convinced herself he'd appear on her porch one night and beg her to work out their differences. But another week had gone by, and he'd given her only halfhearted hellos and good-byes when they passed each other at Emma's house. All her hopes for their future had evaporated. It was officially over between them. Too many obstacles stood in their way.
"It has flown by," Jerry said. "We took down the roadside stand this morning, and it's stowed in Emma's barn. The garden is closed for the season."
"It's been a great season," Katie Ann chimed in. "We've raised quite a bit of money for the Bird-in-Hand Shelter in memory of Henry." She looked at Emma. "We're so grateful you allowed us to do this."
"No, thank you all. I'm so honored that you want to keep Henry's memory alive in such a _wunderbaar_ way that helps our community." Emma began to clap, and everyone joined in.
Mandy looked over at Ephraim, and he met her gaze. She sucked in a breath as he nodded at her. She returned the nod and then looked down at the table. Would looking into his eyes be painful for the rest of her life? She dreaded the possibility as her chest tightened with grief.
"Should we talk about what we want to plant next year?" Clara asked. "I can get the seeds from _mei onkel_ again."
"That's a _gut_ idea." Katie Ann turned to a fresh page in her notebook. "Let's talk about lessons learned. What worked and didn't work this year?"
For the next hour, Mandy tried to focus on her friends' discussion about the garden's future, but she kept losing herself in thoughts of Ephraim. She breathed a sigh of relief when Tena declared the meeting over and then brought out turkey tetrazzini casserole for supper.
Mandy picked at her food and kept her focus on her plate as everyone ate. The conversations swirled around her, but she responded only when someone said her name. After they had brownies for dessert, she helped the other women clean the kitchen while the men talked in the family room.
"Are you ready to go?" Katie Ann asked Mandy when they were done.
Mandy nodded. " _Ya_."
" _Was iss letz?_ " Emma asked as she joined them.
Mandy looked past Katie Ann to where Ephraim now stood in the kitchen, talking to Wayne. When he turned toward her, she looked away. "I'm just tired."
"I have something for you." Emma pulled a piece of paper out of her apron pocket and slipped it into Mandy's hand. "I found it when I was going through _mei mamm_ 's favorite cookbook. I think it might help you."
"What is it?" Mandy opened the paper and found a recipe for peanut butter pie. She looked up at Emma. "I don't understand."
Emma smiled. "The way to a man's heart—"
"Is through his stomach." Katie Ann finished the statement with a grin.
"Did you two work up this plan together?" Mandy pointed at each of them, and they nodded.
"It was my idea to find a recipe Ephraim might like." Katie Ann pointed to the paper. "If you're not ready to give up, then here's an idea for a conversation opener. He's crazy about peanut butter, so I'm sure he'll love this."
Mandy glanced over at Ephraim, and she felt new hope sprouting like a cornstalk. Maybe this was just what she needed to loosen the tension between them!
Wrapped in his warmest jacket, Ephraim sat on his parents' glider and stared out toward the pasture. He shivered as he pushed it back and forth and watched his father's cows lounge in the pasture.
The back door opened and then clicked closed.
"Happy Thanksgiving."
Ephraim glanced at Uria as he approached. "Happy Thanksgiving."
"May I join you?" Uria pointed to the rocker beside him.
"Of course."
Uria sat down and pushed his chair into motion. They sat in amiable silence as the hum of the rocker and glider filled the air.
"I felt like I was in the way in there," Uria finally said. "All the women are scurrying around the kitchen, barking orders at everyone. And the girls are so excited I can't corral them."
" _Ya_." Ephraim smiled, but it wasn't the chaos of the house that had driven him outside. It was Mandy's absence. They'd planned for her to join his family today, but that plan died along with their breakup. Without her company, the house felt too small, too cold, too dreary. Even with his nieces' laughter.
"How are you doing?" Uria asked.
"Fine. How are you?"
Uria lifted a dark eyebrow as he brought the rocking chair to a halt. "You're fine? Really?"
Ephraim shifted his weight on the glider.
"You miss her." Uria's words were simple, but their meaning ran deep in Ephraim's soul.
He looked straight ahead to avoid his brother-in-law's stare.
"Sometimes our plans for ourselves are different than God's plans," Uria said. "I never imagined I would lose my job and have to uproot my family. But Darlene and I love each other, and we'll always support each other no matter what."
Uria paused for a moment as if gathering his thoughts. "My parents died a long time ago, and I don't have any other family members to lean on. I'm grateful for your family and what you've done for us. And with our love for each other and our family and our faith in God, Darlene and I will get through this and anything else we have to face."
Ephraim rubbed his face as his eyes stung.
Uria leaned toward him. "If your love for Mandy is strong enough, you'll find a way to make things right with her. I know it's none of my business, but I can see how much this breakup is hurting you. It doesn't have to be this difficult, Ephraim. Just let your love for Mandy guide your heart, and you'll find your solution."
Ephraim swallowed against his suddenly dry throat. Did he and Mandy love each other enough to endure all the trials they would face as a couple? Enough to resolve the conflict separating them now?
Suddenly it all clicked in place in his mind. Uria's words were the sign he'd been waiting for! This was what God had been trying to tell him all along. If their love was strong enough—and he believed it was—he and Mandy could make it through any trial or tribulation they encountered. It didn't matter when they married, where they lived, or what he did for a living as long as they had God's blessing and loved each other. The rest would fall into place.
Ephraim leapt to his feet. "I have to go."
"What?" Uria looked up at him.
"I need to go talk to her now."
Uria waved him off with a smile. "Go. I'll tell your parents where you've gone."
" _Danki!_ " Ephraim ran to the barn, praying Mandy would forgive him.
"Are we expecting company?" Rhoda called as she started for the mudroom to answer the back door.
"No." Mandy looked at her mother.
_Mamm_ shrugged. "Not that I know of." She pointed to the stove. "Would you please check the turkey?"
" _Ya_." Mandy opened the oven door, and the succulent aroma of turkey caused her stomach to grumble in delight. How she loved Thanksgiving!
"Mandy."
Mandy turned and gasped as she found Rhoda standing in the doorway with Ephraim close behind her.
"You have a guest." Rhoda smiled and stepped aside, and Ephraim came into full view.
Mandy stilled, confused. She'd planned to ask her father if she could borrow his horse and buggy to visit Ephraim later this afternoon and deliver the pie. She'd never expected him to surprise her with a visit instead.
"Go." _Mamm_ gave Mandy's shoulder a gentle nudge. "I'll take care of the turkey."
Mandy stepped over to Ephraim as Rhoda slipped past her. "Hi."
"Happy Thanksgiving." He fingered the zipper on his jacket, and then he pointed to the back door. "Do you have a moment to spare?"
"Of course." Mandy turned toward the refrigerator. "And I have a gift for you."
"A gift?" His eyebrows lifted.
" _Ya_." She retrieved the peanut butter pie. "I was going to take this to you later."
He took the pie, lifted the plastic wrap, and breathed in its sweetness. "Peanut butter?" He grinned. "You made this for me?"
" _Ya._ It was Emma and Katie Ann's idea. They said the way to a man's heart is through his stomach, so they suggested I make it for you."
He leaned his head back as laughter burst from his mouth. She joined in, and soon they were laughing together. She didn't know why he was here, but hope took center stage in her heart.
_Mamm_ appeared beside her. "Let me put the pie away so you two can go talk alone."
" _Danki_ ," Mandy said.
_Mamm_ winked at her before turning away.
As Mandy walked into the mudroom and pulled on her coat, her pulse galloped. Had her prayers been answered? Would God help them mend their relationship? She held her breath as they moved to the porch and sat down on the glider.
Ephraim angled his body toward her. "Uria said something to me today that made me realize how wrong I've been."
"Oh?" Her heartbeat spiked.
"He said all that matters is that he and Darlene are together." He took a deep breath. "He said they support each other no matter what. I finally realized it doesn't matter when you and I are married, where we live, or what I do for a living as long as I have you by my side. These weeks without you have been pure torture, and I can't stand it anymore. I miss you. I love you, Mandy. I want to be with you, no matter where God leads us. And I do think he's leading us, if we'll only listen."
She took a deep breath as well. "I love you, too, but I owe you an apology. I was so overwhelmed with wedding plans and sure I was right about what we needed to do that I didn't take your feelings into consideration. I never meant to try to force you to do what I thought would work best. I never meant to make you doubt how much I love you and want to marry you." She touched his cheek. "I love you with my whole heart, and I never wanted to hurt you. I don't care where we live or what you do for a living. I never meant to appear spoiled. I could be _froh_ whether I'm a farmer's _fraa_ or a brickmason's _fraa_."
She paused and took a shuddering breath. "Please forgive me for hurting your feelings and pride. You're the man I want to spend my life with. You're the man I believe God has chosen for me. All that matters is that we're together."
A small sound escaped his throat as his eyes glittered. " _Danki._ "
She sucked in a breath as tears filled her eyes. "Let's find a way to work this out, Ephraim. I can't stand this distance between us anymore. I'm ready to listen to you and respect your feelings."
"And I'm sorry for letting our disagreement go on for so long. I want to make up for lost time." He traced his fingertip down her cheek, and she felt a tingling in her chest. "Will you please forgive me?"
" _Ya_ , of course, I will."
He leaned forward, and when his lips brushed hers, her heart took on wings. "Will you marry me when you're ready?"
" _Ya_." She nodded. "I will."
He took her hands in his. "I'll live anywhere you want to live. We can build a _haus_ here on this farm, and we can raise our _kinner_ here if that's what's best. I just want you to be _mei fraa._ I want to take care of you, and I want to spend the rest of my life with you."
As he kissed her again, she closed her eyes and savored the feeling of his lips against hers.
FOUR MONTHS LATER
Mandy smiled as she threaded her fingers with Ephraim's and walked with him from her father's barn to the back porch. She shivered as the cool March air kissed her cheeks, and she pulled her sweater over her baby-blue dress with her free hand. Then she looked up at her husband as happiness fluttered in her chest. They'd had such a wonderful engagement all winter, but now the time was right for marriage.
Mandy reflected on their perfect day. The three-hour ceremony was held in her father's large barn, beginning with the congregation singing hymns from the Amish hymnal, the _Ausbund,_ while she and Ephraim met with the minister.
Then as she and Ephraim sat at the front of the congregation after the meeting, along with their attendants, Rhoda and Wayne, she'd been so grateful her sister had helped her finish the dresses. She thought they were beautiful, and Rhoda looked stunning in that shade of baby blue. Ephraim and Wayne were both handsome in their traditional black Sunday suits and white shirts, but her challenge was keeping her eyes off Ephraim.
She loved him so.
When the ceremony was over, the men began rearranging furniture while some of the women set out the wedding dinner—lasagna and garlic bread, with bountiful desserts.
The tables were decorated with the blue candles and baby's breath decorations Mandy and her friends made. She was so thankful all the plans had come together. Their wedding was exactly as she'd dreamt it would be.
"It's a _schee_ day." She peeked up at the clear blue sky once again.
"It's the _perfect_ day." Ephraim stopped and faced her. "Because you're finally _mei fraa_."
" _Danki_ for waiting for me."
"You were worth the wait."
She smiled as she touched his cheek. "You're going to be even more handsome with a beard." Then she turned toward the porch where their friends all sat. "Everyone looks so _froh_." She grinned as all the "garden couples" laughed together. "I wonder who will be the next to get married."
"I guess we'll see what God has in store for them." Ephraim looped his arm over her shoulders and turned toward the pasture. "I think we're going to start framing this week. The foundation is in."
Excited, she gazed at where their _haus_ would be. "You and _Dat_ did a great job. You're a _wunderbaar_ brickmason."
"I still have a lot to learn." He smiled down at her. "But your _dat_ is a great teacher, and I do like the work. It helps to know Uria and _Dat_ are doing so well at the farm."
"Ephraim! Mandy!" Katie Ann called from the porch. "Come here!"
"Let's go join our _freinden_." Ephraim gave her hand a gentle tug, and they started down the path.
As they climbed the steps to join their friends, she felt so grateful that Henry's garden had brought them all together. Love had grown throughout the seasons, especially for her and Ephraim. She closed her eyes for a moment and thanked God, not just for today's dream come true, but for the winter blessings he'd brought them.
DISCUSSION QUESTIONS
1. Mandy feels overwhelmed with her wedding to Ephraim only six weeks away. When she learns his family is facing a challenge, she feels even more hesitant about rushing their wedding. She suggests they delay it. Do you think her feelings are valid?
2. Ephraim thinks Mandy's complaining about how little time she has to plan the wedding and then her suggesting they delay it is an indication she's doubting their plans to marry. Why do you think he jumps to that conclusion?
3. Mandy is crushed when Ephraim breaks up with her. Have you ever felt utter heartbreak and loss? If so, where did you find your strength to go on? What Bible verses helped you?
4. After the breakup, Mandy finds solace in baking. Have you ever faced a difficult situation? If so, where did you find comfort during that time?
5. Which character can you identify with the most? Which character seemed to carry the most emotional stake in the story? Was it Mandy, Ephraim, or someone else?
6. At the end of the story, Uria shares with Ephraim what he and Darlene have endured in their marriage, and how. Why do you think his story changed Ephraim's ideas about sacrifice and compromise, especially in marriage?
7. How did Henry's garden play a role in all the relationships in this novella collection?
ACKNOWLEDGMENTS
As always, I'm grateful for my loving family, including my mother, Lola Goebelbecker; my husband, Joe; and my sons, Zac and Matt.
Special thanks to my mother and my dear friend Becky Biddy, who graciously proofread the draft and corrected my hilarious typos.
I'm also grateful for my special Amish friend who patiently answers my endless stream of questions. You're a blessing in my life.
Thank you to my wonderful church family at Morning Star Lutheran in Matthews, North Carolina, for your encouragement, prayers, love, and friendship. You all mean so much to my family and me.
Thank you to Zac Weikal and the fabulous members of my Bakery Bunch! I'm so grateful for your friendship and your excitement about my books. You all are awesome!
To my agent, Natasha Kern—I can't thank you enough for your guidance, advice, and friendship. You are a tremendous blessing in my life.
Thank you to my amazing editor, Jocelyn Bailey, for your friendship and guidance. I'm grateful to each and every person at HarperCollins Christian Publishing who helped make this book a reality.
I'm grateful to editor Jean Bloom, who helped me polish and refine the story. Jean, you are a master at connecting the dots and filling in the gaps. I'm so happy we can continue to work together!
Thank you most of all to God—for giving me the inspiration and the words to glorify you. I'm grateful and humbled you've chosen this path for me.
Read more from the Seasons of an Amish Garden collection!
Available as an e-book
ABOUT THE AUTHOR
Dan Davis Photography
Amy Clipston is the award-winning and bestselling author of the Amish Heirloom series and the Kauffman Amish Bakery series. She has sold more than one million books. Her novels have hit multiple bestseller lists, including CBD, CBA, and ECPA. Amy holds a degree in communications from Virginia Wesleyan University and works full-time for the City of Charlotte, North Carolina. Amy lives in North Carolina with her husband, two sons, mom, and three spoiled-rotten cats.
_Visit her online at amyclipston.com_
_Facebook: AmyClipstonBooks_
_Twitter: @AmyClipston_
_Instagram: @amy_clipston_
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Agate: What Good Is a Moose?
Joy Morgan Dey. Illustrated by Nikki Johnson. Agate the moose sees his friends as fabulous gems. He feels like a plain, brown rock. But is he, really? If you've ever hunted agates, you know the thrill of spotting a good one, the anticipation of polishing it to reveal its secret treasures. Agate reminds us to look for the remarkable hidden core in ourselves, and in others. Hardcover. Ages 4 & up. 24 pages.
Agates of Lake Superior: Stunning Varieties and How They are Formed
Dan and Bob Lynch's definitive book on Lake Superior's agates is for casual rock collectors to more advanced hobbyists. It examines the region's strange and unique varieties and theories of formation and includes how to find, identify, and determine the collectability of agates. Paperback. 224 pp.
Fish of Michigan Field Guide
Detailed information about 73 species of Michigan fish, compact size, and waterproof pages make Dave Bosanko's guide perfect for the dock or boat. Read fascinating facts on spawning behavior, feeding habits, and more. Plus, compare your best catches to the state and North American records. Includes inside information for locating fishing hotspots. 174 pp.
Geology of the Lake Superior Region
Full of examples, photographs, maps, and diagrams, "Geology of the Lake Superior Region" integrates a discussion of basic physical geology into a chronological view of the geological processes that formed the Upper Midwest around Lake Superior. In clear, concise, jargon-free prose, Gene LaBerge has written the most accurate, complete, and current book on geology and landforms of the Upper Midwest.
Gleason's Plants of Michigan: A Field Guide
Richard K. Rabeler. A major revision and expansion of The Plants of Michigan by Henry A. Gleason, the 1918 classic field guide to the flowering plants and trees found in Michigan, neighboring Great Lakes States, and southern Ohio. Completely updated family descriptions and added easy-to-use keys. Paper. 398 pages.
Good Boat Speaks for Itself: Isle Royale Fishermen and Their Boats
Tim Cochrane and Hawk Tolson. Isle Royale was home to a vibrant fishing community from its settlement during the 1880s by Norwegian and Swedish immigrants until the collapse of Lake Superior commercial fishing in the 1950s. Full of historical photographs and diagrams of now derelict watercraft, A Good Boat Speaks for Itself tells the history of this community through its wooden boats and the stories of those who built and used them. 208 pages.
Guide to Great Lakes Coastal Plants
Ellen Elliott Weatherbee. Simple yet authoritative descriptions of 67 of the most interesting plants found on the United States and Canadian shores. Each plant is illustrated with color photographs and line drawings for ease in identification. Paper, 180 pages.
Hollowed Ground: Copper Mining and Community Building on Lake Superior, 1840's-1990's
Larry D. Lankton. This book provides an informative and absorbing account of copper mining on Michigan's Keweenaw Peninsula. By focusing on the region's three largest copper producers, it documents the dynamic evolution of the Keweenaw's social and industrial landscapes, giving a context for understanding those landscapes today. Paper. 375 pages.
How the Rock Connects Us: A Geoheritage Guide to Michigan's Keweenaw Peninsula and Isle Royale
Michigan Tech geologists Bill Rose and Erika Vye, with longtime Isle Royale NP interpretive ranger Valerie Martin, provide a comprehensive overview of the underlying geologic features that link both of our national parks and Lake Superior. What you learn about the range of influences they have on human life may surprise you! Also available as a premium for $50+ membership or donation. 64 pp., coil-bound. ISBN 9780935289213
I Spy...Isle Royale
Young explorers, come along and explore Isle Royale, one of the most remote national parks in the Lower 48. Learn about the plants and animals that have made this rugged wilderness island their home. Admire the beautiful scenery and get a glimpse into some of the many adventures to be had on Isle Royale! Former NPS ranger Susanna Ausema introduces children to the wonders of Isle Royale with rhyming verse, watercolor images, and photographs. Older readers will be able to delve deeper into their exploration of Isle Royale through nature notes on each page. Also includes photos of the most commonly seen animal scat and tracks. Also available as a premium for a $50+ membership. 40 pages, paperback cover, full color.
Invaders of the Great Lakes
Aquatic invasive species have invaded the Great Lakes. They are poised to invade thousands of lakes, rivers and streams. Learn how to stop them. This handy guide spotlights 39 invaders and details how they live, grow, reproduce and spread. Armed with this knowledge, you can help protect our inland waters, keeping your favorite fishing spots and lakeshores healthy. ◆Author: Karen Hollingsworth◆ Pages: 152◆ Paperback◆2013◆ Other Books: Critters of Michigan (http://irkpa.org/shop/books/nature-science/critters-michigan)◆
Iron and Water
Grant Merritt, notable environmental protector and member of an Isle Royale family, narrates both a memorable family history and key environmental battles he was involved in to protect Lake Superior and other natural resources.
Is This an Agate?
Susan Robinson. Finally, a book that describes the beach stones found along Lake Superior shorelines. Beautifully illustrated with full color realistic paintings. Small enough to carry in your backpack. 23 pages.
Isle Royale: A Photographic History
Thomas and Kendra Gale. An album that vividly tells the island's history and the stories of the people who worked and played here from 1868 to 1951. 150 photos. Paper. 149 pages.
Grace Lee Nute. The captivating history of the world's largest freshwater lake, this book tells the stories of Native Americans, voyageurs, missionaries, and others who created the way of life that many generations have known on the edge of Lake Superior. B&W photos. 408 pages.
Lake Superior Agates Field Guide
Beginner or expert, this is your guide to Lake Superior agates. The book features four pages of photos and facts for every type of agate found in Michigan, Minnesota, Wisconsin, and southern Ontario. The easy-to-use format provides what you need to know and where to look, while Dan and Bob Lynch's photographs depict the detail needed for identification. 160 pp.
Lake Superior Place Names, by Bernard C. Peters
Exploring the origin and meaning of place names along Michagan's Lake Superior shoreline before Americans came into the region, this book examines the Native American and French names.
Lake Superior Rocks & Minerals: A Field Guide to the Lake Superior Area
This book is a comprehensive guide to common and rare rocks and minerals found in Minnesota, Wisconsin, and Michigan. The easy-to-use format means you'll quickly find what you need to know and where to look, while Dan and Bob Lynch's photographs depict the detail needed for identification 208 pp.
Long-Shining Waters
Danielle Sosin. Three stories of women who live on Lake Superior whose lives are separated by centuries and circumstance, yet connected across time by a shared geography. As these narratives unfold and overlap with the mesmerizing rhythm of waves, a fourth mysterious character gradually comes into stark relief. Rich in historical detail and universal in its exploration of the human desire for meaning when faced with uncertainty. Paper. 275 pages.
Lure of the North Woods, By Aaron Shapiro
Love old advertising? This book, full of colorful old adds and information, is a definitive history of North Woods adverting used to lure folks up to enjoy all that the upper portions of Michigan, Minnesota, and Wisconsin have to offer.
Minong — The Good Place: Ojibwe and Isle Royale
Timothy Cochrane. "At last, an accurate account of the North Shore Ojibwe's relationship with Isle Royale, or Minong — the good place. We now have a clear view of the historic Ojibwe use of Isle Royale — a subject that has been ignored, forgotten, and corrupted for far too long. Cochrane does an excellent job of giving the source and finding out about Ojibwe history from the relatives and descendents of the groups who were actually involved and are still connected to the island today." - Liz Valencia, Historian, Isle Royale National Park. Paper. 285 pages.
Paddle-to-the-Sea
Holling C. Holling. A small canoe carved by an Indian boy makes a journey from Lake Superior all the way to the Atlantic Ocean. Winner of the Caldecott Award. Full page color illustrations, maps. Ages 9-12. 64 pages.
Scats and Tracks of North America
James C. Hafpenny. Illustrated by Todd Telander. Easy-reference descriptions with precise measurements; detailed illustrations of scats, tracks, and gait patterns; an identification key and glossary of tracking terms; and thorough instructions for documenting your finds. 150 pages.
Shipwrecks of Isle Royale National Park: The Archeological Survey
Daniel Lenihan. The revised Submerged Cultural Resources Unit report on the ten shipwrecks of Isle Royale includes the history of the ships as well as maps of the underwater sites. A must for all divers. Color and B&W photos. 210 pages.
Superior Way
Bonnie Dahl. Mariner's guidebook offering tested advice on cruising Lake Superior. Incorporates charts and detailed harbor maps with Loran-C, TD, and GPS data. Over 300 diagrams, charts, and tables. 4th edition. Spiral bound. 426 pages.
Superior Wilderness: Isle Royale National Park
Napier Shelton. A natural history of Isle Royale for the non-scientist. This very readable book reveals the unfolding story of this unique island ecosystem, emphasizing the delicate relationship between its plants, animals, climate, and geology. Beautiful color photographs throughout. NEW LOWER PRICE! Paper. 176 pages.
Tales of the Old North Shore
Howard Sivertson. A collection of paintings and stories revealing the sometimes daring, often humorous, and always poignant adventures of citizens of Lake Superior's North Shore and Isle Royale. Hardcover. 91 pages.
Talking Rocks: Geology and 10,000 Years of Native American Tradition in the Lake Superior Region
Ron Morton and Carl Gawboy. Join the conversation as an earth scientist and a Native American elder — wise men from two cultures — explore the natural history of the Lake Superior region, examining both the science and the spirit of the land. A story of geological history told from two perspectives as well as the chronicle of two people from very different heritages learning to understand and appreciate each other's perspective. 210 pages.
Upper Peninsula of Michigan: A History, by Russell M. Magnaghi
A fascinating look at the sometimes wild history of the Upper Peninsula of Michigan.
Walking Paths and Protected Areas of the Keweenaw, 3rd Ed.
A guide to the paths and protected areas of the Keweenaw and Houghton Counties open to non-motorized recreation by the public. Published by the Michigan Nature Association, the book includes 27 sanctuaries and preserves protected by a variety of non-profit and governmental organizations.
Water Walkers
Winner of the Moonbeam Children's Book Award, this book, lushly illustrated by David Craig, tells the story of a young Ojibway girl as she walks with her grandmother and learns of the importance protecting our Great Lakes. $14.95
Waterfalls of Michigan, Book 3 West Central
Covering Baraga, Houghton, Iron, and Keweenaw Counties, this beautifully photographed book gives maps, driving and hiking information and plenty of data for each waterfall in the area.
Waterfalls of Michigan, Book 4 West
Covering covers waterfalls found in Gogebic and Ontonagon Counties, as well as the Porcupine Mountains this beautifully photographed book gives maps, driving and hiking information and plenty of data for each waterfall in the area.
What's Doin' the Bloomin'?
Clayton Oslund and Michelle Oslund. Comprehensive pictorial guide to wildflowers of the Upper Great Lakes regions, Eastern Canada and Northeastern U.S.A. Over 340 species of native and naturalized plants, with more 620 full color photos. 308 pages.
Wolves of Isle Royale: A Broken Balance
Rolf O. Peterson. Wildlife biologist Peterson's fascinating firsthand account of the relationship that exists between the wolf and the moose on the island. Illustrated with over 100 photographs, this book reveals the true nature of the mysterious and little-understood wolf. Paper. 192 pages.
Wreck Ashore: Stories of Storm Heroes Saving Lives on the Perilous Great Lakes
Frederick Stonehouse. A historic look into our earliest heroes on the Great Lakes. From stormy shipwrecks to catastrophic disasters, the lifesavers were always there, risking their lives to save others. From the mid-1780s until it transformed into the U.S. Coast Guard in 1915, the U.S. Life-Saving Service was responsible for safety on the seas. Illustrated with historic photos. 214 pages.
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Q: Deleting user input and deallocating memory I've got a phonebook app that I've been trying to add malloc to over the last few days, but since I'm new to C and the book I have doesn't go into the detail I would like, I'm not sure of all the tricks. Is it possible to use malloc when the user inputs information, and then use free() as a way to delete user input when the user elects to delete an individual from the phonebook? Right now regardless of whether I use free() or not, after the user deletes an entry and then tries to check the phonebook, the program crashes. I'm assuming(but we know what that means) that it has something to do with improperly freeing or not freeing the memory. Here is the code.
#include <stdio.h>
#include <string.h>
#include <stdlib.h>
#include <conio.h>
#define BUFFER 50
//Structure for contacts
typedef struct friends_contact{
char *First_Name;
char *Last_Name;
char *home;
char *cell;
}fr;
//Function declarations
void menu(fr*friends ,int* counter,int user_entry,int i,char newbuddy[]);
void setFirst(fr*,int *,int i,char newbuddy[]);
char getFirst(fr*,int i);
void setLast(fr*friends, int* counter, int i,char newbuddy[]);
char getLast(fr*friends , int i);
void setHome(fr*friends, int* counter, int i,char newbuddy[]);
char getHome(fr*friends, int i);
void setCell(fr*friends, int* counter, int i,char newbuddy[]);
char getCell(fr*friends, int i);
void add_contact(fr*friends,int* counter,int i,char newbuddy[]);
void print_contact(fr*friends ,int* counter, int i);
char delete_contact(fr*friends ,int* counter, int i);
char show_contact(fr*friends ,int* counter, int i);
int main() {
int user_entry=0;
fr friends[5];
char newbuddy[BUFFER];
int counter=0;
int i=0;
menu(friends, &counter,user_entry,i,newbuddy);
getch();
return 0;
}
//Menu function
void menu(fr*friends,int* counter,int user_entry, int i,char newbuddy[]) {
do{
int result;
printf("\nPhone Book Application\n");
printf("1) Add friend\n2) Delete friend\n3) Show a friend\n4) Show phonebook\n5)Exit\n");
scanf("%d", &user_entry);
if(user_entry==1)
{
add_contact(friends,counter,i,newbuddy);
}
if(user_entry==2)
{
delete_contact(friends ,counter,i);
}
if(user_entry==3)
{
result=show_contact(friends ,counter,i);
if(result==0){
printf("\nName not Found\n");
}else{
result;
}
}
if(user_entry==4)
{
print_contact(friends, counter,i);
}
}while(user_entry!=5);
}
//Start of Set functions. Each entry has its own set function that gathers the data
void setFirst(fr*friends, int* counter, int i,char newbuddy[]) {
printf("Enter a first name \n");
scanf("%s",newbuddy);
friends[*counter].First_Name=malloc(BUFFER*strlen(newbuddy));
strcpy(friends[*counter].First_Name, newbuddy);
}
void setLast(fr*friends, int* counter, int i,char newbuddy[]) {
printf("Enter a last name \n");
scanf("%s",newbuddy);
friends[*counter].Last_Name=malloc(BUFFER*strlen(newbuddy));
strcpy(friends[*counter].Last_Name, newbuddy);
}
void setHome(fr*friends, int* counter, int i,char newbuddy[]) {
printf("Enter a home number \n");
scanf("%s",newbuddy);
friends[*counter].home=malloc(BUFFER*strlen(newbuddy));
strcpy(friends[*counter].home, newbuddy);
}
void setCell(fr*friends, int* counter, int i,char newbuddy[]) {
printf("Enter a cell number \n");
scanf("%s",newbuddy);
friends[*counter].cell=malloc(BUFFER*strlen(newbuddy));
strcpy(friends[*counter].cell, newbuddy);
}
//Start of Get functions. Each function sends the data to the executing function.
char getFirst(fr*friends , int pos) {
printf("%s ", friends[pos].First_Name);
return *friends[pos].First_Name;
}
char getLast(fr*friends , int pos) {
printf("%s\n", friends[pos].Last_Name);
return *friends[pos].Last_Name;
}
char getHome(fr*friends , int pos) {
printf("(Home) ""%s\n", friends[pos].home);
return *friends[pos].home;
}
char getCell(fr*friends , int pos) {
printf("(Cell) ""%s\n", friends[pos].cell);
return *friends[pos].cell;
}
//This function allows for the all the set functions to be added.
void add_contact(fr*friends,int* counter,int i,char newbuddy[]) {
setFirst(friends,counter,i,newbuddy);
setLast(friends,counter,i,newbuddy);
setHome(friends,counter,i,newbuddy);
setCell(friends,counter,i,newbuddy);
(*counter)++;
}
//This is used to delete a name out of the book.
char delete_contact(fr*friends ,int* counter, int i)
{
char name_search[50]={'\0'};
char Delete[5]={'\0'};
printf("Search by last name\n");
scanf("%s",name_search);//Name entry
for(i=0;i<*counter;i++)
{
if(strcmp(name_search,friends[i].Last_Name)==0)//Copys over the name entered
{
strcpy(friends[i].Last_Name,Delete);
(*counter)++;
printf("\nName has been deleted\n");
}
}
}
//This function prints out all the contact information
void print_contact(fr*friends ,int* counter, int i) {
for( i = 0; i < *counter; i++)
if (strlen(friends[i].First_Name) && strlen(friends[i].Last_Name)&& strlen(friends[i].home)&& strlen(friends[i].cell ))
{
getFirst(friends, i);
getLast(friends, i);
getHome(friends, i);
getCell(friends, i);
}
}
//Displays the contact in which you are searching for.
char show_contact(fr*friends ,int* counter, int i)
{
char name_search2[50]={'\0'};
printf("Please enter a last name\n");
scanf("%s",name_search2);
for(i=0;i<*counter;i++)
{
//If the name is found, it reaturns the contact info.
if(strcmp(name_search2,friends[i].Last_Name)==0)
{
return printf("%s " "%s" "(Home)""%s""(Cell)" "%s\n",friends[i].First_Name, friends[i].Last_Name,friends[i].home,friends[i].cell);
}
}
return 0;
}
I didn't add the free() code because regardless it seemed to be getting the same results. Why would the program crash only after I have deleted a name from the list?
A: Step1: Isolating the issue:
//This is used to delete a name out of the book.
char delete_contact(fr*friends ,int* counter, int i)
{
char name_search[50]={'\0'};
char Delete[5]={'\0'};
printf("Search by last name\n");
scanf("%s",name_search);//Name entry
for(i=0;i<*counter;i++)
{
if(strcmp(name_search,friends[i].Last_Name)==0)//Copys over the name entered
{
strcpy(friends[i].Last_Name,Delete);
(*counter)++;
printf("\nName has been deleted\n");
}
}
}
Step2: Possible Problem
(*counter)++ //why do this?
This is executed, when the name to be deleted is found. Why would you increment the count of all names in the list? I think this should be a decrement instead, or shouldn't be done within the loop at all.
|
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"redpajama_set_name": "RedPajamaStackExchange"
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Arab al-Arida (arab. عرب العريضه) – nieistniejąca już arabska wieś, która była położona w Dystrykcie Beisan w Mandacie Palestyny. Wieś została wyludniona i zniszczona podczas I wojny izraelsko-arabskiej, po ataku Sił Obronnych Izraela w dniu 20 maja 1948 roku.
Położenie
Arab al-Arida leżała w południowej części Doliny Bet Sze'an. Wieś była położona w depresji rzeki Jordan na wysokości -200 metrów p.p.m., w odległości 6 kilometrów na południe od miasta Beisan. Według danych z 1945 roku do wsi należały ziemie o powierzchni 228 ha. We wsi mieszkało wówczas 330 osób (w tym 180 Żydów).
Historia
Nie jest znana data powstania wioski Arab al-Arida, jednak sąsiednie wzgórza Tell al-Ru'jan i Tell al-Kurud są stanowiskami archeologicznymi. W okresie panowania Brytyjczyków Arab al-Arida była niewielką wsią, której mieszkańcy utrzymywali się z upraw zbóż.
Przyjęta 29 listopada 1947 roku Rezolucja Zgromadzenia Ogólnego ONZ nr 181 przyznała te tereny państwu żydowskiemu. Podczas I wojny izraelsko-arabskiej, w dniu 20 maja 1948 roku izraelscy żołnierze zajęli wieś. Wysiedlono wówczas wszystkich jej mieszkańców i wyburzono wszystkie domy.
Miejsce obecnie
Na wschód od wsi Arab al-Arida powstał w 1939 roku kibuc Sede Elijjahu. Po wysiedleniu jej mieszkańców i zburzeniu domu, tereny te zajął kibuc. Palestyński historyk Walid Chalidi, tak opisał pozostałości wioski Arab al-Arida: "Brak śladów pozostałych po miejscowości. Cały obszar wioski jest obsadzony pszenicą. Archeologiczne stanowisko Tell al-Ru'jan zostało przekształcone w wysypisko śmieci".
Przypisy
Wsie arabskie w Palestynie wyludnione w 1948 roku (I wojna izraelsko-arabska)
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{
"redpajama_set_name": "RedPajamaWikipedia"
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|
\section{Conclusion}
In recent years, offline approaches that use regression to predict
2D-to-3D correspondences
\cite{Shotton2013,GuzmanRivera2014,Valentin2015RF,Brachmann2016,Massiceti2016}
have achieved state-of-the-art camera relocalisation results, but
their adoption for online relocalisation in practical systems such as InfiniTAM
\cite{Kaehler2015,Kaehler2016} has been hindered by the need to train
extensively on the target scene ahead of time.
We show how to circumvent this limitation by adapting offline-trained regression forests to novel scenes online.
Our adapted forests achieve relocalisation performance on 7-Scenes
\cite{Shotton2013} that is competitive with the offline-trained forests of
existing methods, and our approach runs in under $150$ms, making it competitive
in practice with fast keyframe-based approaches such as random ferns
\cite{Glocker2015,Kaehler2016}. Compared to such approaches, we are also much better
able to relocalise from novel poses, freeing the user from manually searching for known
poses when relocalising.
\section*{Acknowledgements}
\noindent
We would like to thank Victor~Prisacariu and Olaf~K{\"a}hler for providing us with the InfiniTAM source code.
\\
This work was supported by the EPSRC, ERC grant ERC-2012-AdG 321162-HELIOS, EPSRC grant Seebibyte EP/M013774/1 and EPSRC/MURI grant EP/N019474/1.
\section{Experiments}
We perform both quantitative and qualitative experiments to evaluate our
approach. In \S\ref{subsec:adaptationperformance}, we compare our
\emph{adaptive} approach to state-of-the-art \emph{offline} relocalisers
that have been trained directly on the scene of interest. We show that our adapted
forests achieve competitive relocalisation performance despite being trained
on very different scenes, enabling their use for \emph{online}
relocalisation. In \S\ref{subsec:trackinglossrecovery}, we show that we can perform this adaptation on-the-fly from live sequences, allowing us to
support tracking loss recovery in interactive scenarios.
In \S\ref{subsec:novelposes}, we evaluate how well our approach
generalises to novel poses in comparison to a keyframe-based random fern
relocaliser based on \cite{Glocker2015}. This relocaliser is also practical for
on-the-fly relocalisation (hence its use in InfiniTAM \cite{Kaehler2016}), but
its use of keyframes prevents it from generalising well to novel poses.
By contrast, we are able to relocalise well even from poses that are quite far
away from the training trajectory. Finally, in \S\ref{subsec:timings}, we
compare the speed of our approach with random ferns during both normal operation
(i.e.\ when the scene is being successfully tracked) and relocalisation.
Our approach is slower than random ferns, but remains close to real-time
and achieves much higher relocalisation performance.
Further analysis can be found in the supplementary material.
\subsection{Adaptation Performance}
\label{subsec:adaptationperformance}
\begin{table*}[!t]
\centering
\scriptsize
\rowcolors{2}{white}{gray!25}
\begin{tabular}{cccccccccc}
\toprule
~ & & \multicolumn{7}{c}{\textbf{Relocalisation Performance on Test Scene}} \\
\rowcolor{white}
\multirow{-2}{*}{\textbf{Training Scene}} & & \textbf{Chess} & \textbf{Fire} & \textbf{Heads} & \textbf{Office} & \textbf{Pumpkin} & \textbf{Kitchen} & \textbf{Stairs} & \textbf{Average (all scenes)} \\
\midrule
\cellcolor{white} & Reloc & 99.8\% & 95.7\% & 95.5\% & 91.7\% & 82.8\% & 77.9\% & 25.8\% & 81.3\% \\
\cellcolor{white}\multirow{-2}{*}{Chess} & + ICP & 99.9\% & 97.8\% & 99.5\% & 94.1\% & 91.3\% & 83.3\% & 28.4\% & 84.9\% \\
\cellcolor{white} & Reloc & 98.4\% & 96.9\% & 98.2\% & 89.7\% & 80.5\% & 71.9\% & 28.6\% & 80.6\% \\
\cellcolor{white}\multirow{-2}{*}{Fire} & + ICP & 99.1\% & 99.2\% & 99.9\% & 92.1\% & 89.1\% & 81.7\% & 31.0\% & 84.6\% \\
\cellcolor{white} & Reloc & 98.0\% & 91.7\% & 100\% & 73.1\% & 77.5\% & 67.1\% & 21.8\% & 75.6\% \\
\cellcolor{white}\multirow{-2}{*}{Heads} & + ICP & 99.3\% & 92.3\% & 100\% & 81.1\% & 87.7\% & 82.0\% & 31.9\% & 82.0\% \\
\cellcolor{white} & Reloc & 99.2\% & 96.5\% & 99.7\% & 97.6\% & 84.0\% & 81.7\% & 33.6\% & 84.6\% \\
\cellcolor{white}\multirow{-2}{*}{Office} & + ICP & 99.4\% & 99.0\% & 100\% & 98.2\% & 91.2\% & 87.0\% & 35.0\% & 87.1\% \\
\cellcolor{white} & Reloc & 97.5\% & 94.9\% & 96.9\% & 82.7\% & 83.5\% & 70.4\% & 30.7\% & 75.5\% \\
\cellcolor{white}\multirow{-2}{*}{Pumpkin} & + ICP & 98.9\% & 97.6\% & 99.4\% & 86.9\% & 91.2\% & 82.3\% & 32.4\% & 84.1\% \\
\cellcolor{white} & Reloc & 99.9\% & 95.4\% & 98.0\% & 93.3\% & 83.2\% & 86.0\% & 28.2\% & 83.4\% \\
\cellcolor{white}\multirow{-2}{*}{Kitchen} & + ICP & 99.9\% & 98.2\% & 100\% & 94.5\% & 90.4\% & 88.1\% & 31.3\% & 86.1\% \\
\cellcolor{white} & Reloc & 97.3\% & 95.4\% & 97.9\% & 90.8\% & 80.6\% & 74.5\% & 45.7\% & 83.2\% \\
\cellcolor{white}\multirow{-2}{*}{Stairs} & + ICP & 98.0\% & 97.4\% & 99.8\% & 92.1\% & 89.5\% & 81.0\% & 46.6\% & 86.3\% \\
\cellcolor{white} & Reloc & 97.3\% & 95.7\% & 97.3\% & 83.7\% & 85.3\% & 71.8\% & 24.3\% & 79.3\% \\
\cellcolor{white}\multirow{-2}{*}{Ours (Author's Desk)} & + ICP & 99.2\% & 97.7\% & 100\% & 88.2\% & 90.6\% & 82.6\% & 31.0\% & 84.2\% \\
\midrule
\cellcolor{white} & Reloc & 98.4\% & 95.3\% & 97.9\% & 87.8\% & 82.2\% & 75.2\% & 29.8\% & 80.9\% \\
\cellcolor{white}\multirow{-2}{*}{Average} & + ICP & 99.2\% & 97.4\% & 99.8\% & 90.9\% & 90.1\% & 83.5\% & 33.5\% & 84.9\% \\
\bottomrule
\end{tabular}
\vspace{1mm}
\caption{
The performance of our \emph{adaptive} approach after pre-training on various scenes of the 7-Scenes dataset \cite{Shotton2013}.
We show the scene used to pre-train the forest in each version of our approach in the left column. The pre-trained forests are adapted \emph{online} for the test scene, as described in the main text.
The percentages denote proportions of test frames with $\le 5$cm translational error and $\le 5^\circ$ angular error.
}
\label{tbl:adaptationperformance}
\vspace{-\baselineskip}
\end{table*}
In evaluating the extent to which we are able to adapt a regression forest that
has been pre-trained on a different scene to the scene of interest, we seek to
answer two questions. First, how does an adapted forest compare to one that has
been pre-trained offline on the target scene? Second, to what extent does an
adapted forest's performance depend on the scene on which it has been
pre-trained? To answer both of these questions, we compare the performances of
adapted forests pre-trained on a variety of scenes (each scene from the 7-Scenes
dataset \cite{Shotton2013}, plus a novel scene containing the first author's
desk) to the performances of forests trained offline on the scene of interest
using state-of-the-art approaches
\cite{Shotton2013,GuzmanRivera2014,Valentin2015RF,Brachmann2016}.
The exact testing procedure we use for our approach is as follows. First, we
pre-train a forest on a generic scene and remove the contents of its leaves, as
described in \S\ref{sec:method}: this process runs \emph{offline} over a number
of hours or even days (but we only need to do it once). Next, we adapt the
forest by feeding it new examples from a training sequence captured on the scene
of interest: this runs \emph{online} at frame rates (in a real system, this allows
us to start relocalising almost immediately whilst training carries on in the
background, as we show in \S\ref{subsec:trackinglossrecovery}). Finally, we test
the adapted forest by using it to relocalise from every frame of a separate testing
sequence captured on the scene of interest.
As shown in Table~\ref{tbl:adaptationperformance}, the results are very accurate.
Whilst there are certainly some variations in the performance achieved by
adapted forests pre-trained on different scenes (in particular, forests trained
on the \emph{Heads} and \emph{Pumpkin} scenes from the dataset are slightly
worse), the differences are not profound: in particular, relocalisation
performance seems to be more tightly coupled to the difficulty of the scene of
interest than to the scene on which the forest was pre-trained. Notably, all of
our adapted forests achieve results that are within striking distance of the
state-of-the-art \emph{offline} methods (Table~\ref{tbl:comparativeperformance}), and
are considerably better than those that can be achieved by online competitors
such as the keyframe-based random fern relocaliser implemented in InfiniTAM
\cite{Glocker2015,Kaehler2016} (see \S\ref{subsec:novelposes}). Nevertheless,
there is clearly a trade-off to be made here between performance and
practicality: pre-training on the scene of interest is impractical for
on-the-fly relocalisation, but achieves somewhat better results, probably due to
the opportunity afforded to adapt the structure of the forest to the target
scene.
This drop in performance in exchange for practicality can be mitigated to some
extent by refining our relocaliser's pose estimates using the ICP-based tracker
\cite{Besl1992} in InfiniTAM \cite{Kaehler2015}. Valentin et al.\
\cite{Valentin2015RF} observe that the 5cm/5$^\circ$ error metric commonly used
to evaluate relocalisers is `fairly strict and should allow any robust
model-based tracker to resume'. In practice, ICP-based tracking is in many cases
able to resume from initial poses with even greater error: indeed, as
Table~\ref{tbl:adaptationperformance} shows, with ICP refinement enabled, we are
able to relocalise from a significantly higher proportion of test frames. Whilst
ICP could clearly also be used to refine the results of offline methods, what is
important in this case is that ICP is fast and does not add significantly to the
overall runtime of our approach, which remains close to real time. As such,
refining \emph{our} pose estimates using ICP yields a high-quality relocaliser
that is still practical for online use.
\iftrue
\begin{table}[!t]
\centering
\scriptsize
\begin{tabular}{cHcccccc}
\toprule
\textbf{Scene} & \textbf{Testing frames} & \cite{Shotton2013} & \cite{GuzmanRivera2014} & \cite{Valentin2015RF} & \cite{Brachmann2016} & \textbf{Us} & \textbf{Us+ICP} \\
\midrule
Chess & 2000 & 92.6\% & 96\% & 99.4\% & 99.6\% & 99.2\% & 99.4\% \\
Fire & 2000 & 82.9\% & 90\% & 94.6\% & 94.0\% & 96.5\% & 99.0\% \\
Heads & 1000 & 49.4\% & 56\% & 95.9\% & 89.3\% & 99.7\% & 100\% \\
Office & 4000 & 74.9\% & 92\% & 97.0\% & 93.4\% & 97.6\% & 98.2\% \\
Pumpkin & 2000 & 73.7\% & 80\% & 85.1\% & 77.6\% & 84.0\% & 91.2\% \\
Kitchen & 5000 & 71.8\% & 86\% & 89.3\% & 91.1\% & 81.7\% & 87.0\% \\
Stairs & 1000 & 27.8\% & 55\% & 63.4\% & 71.7\% & 33.6\% & 35.0\% \\
\midrule
Average & -- & 67.6\% & 79.3\% & 89.5\% & 88.1\% & 84.6\% & 87.1\% \\
\bottomrule
\end{tabular}
\vspace{1mm}
\caption{Comparing our \emph{adaptive} approach to state-of-the-art
\emph{offline} methods on the 7-Scenes dataset \cite{Shotton2013} (the percentages denote
proportions of test frames with $\le 5$cm translation error and $\le
5^{\circ}$ angular error). For our method, we report the results obtained by
adapting a forest pre-trained on the \emph{Office} sequence (from
Table~\ref{tbl:adaptationperformance}). We are competitive with, and
sometimes better than, the offline methods, without needing to pre-train
on the test scene.}
\label{tbl:comparativeperformance}
\vspace{-\baselineskip}
\end{table}
\fi
\subsection{Tracking Loss Recovery}
\label{subsec:trackinglossrecovery}
In \S\ref{subsec:adaptationperformance}, we investigated our ability to adapt a forest to a new scene by filling its leaves with data from a training sequence for that scene, before testing the adapted forest on a separate testing sequence shot on the same scene.
Here, we quantify our ability to perform this adaptation \emph{on the fly} by filling the leaves frame-by-frame from the testing sequence: this allows recovery from tracking loss in an interactive scenario without the need for prior training on anything other than the live sequence, making our approach extremely convenient for tasks such as interactive 3D reconstruction.
Our testing procedure is as follows: at each new frame (except the first), we assume that tracking has failed, and try to relocalise using the forest we have available at that point; we record whether or not this succeeds. Regardless, we then restore the ground truth camera pose (or the tracked camera pose, in a live sequence) and, provided tracking hasn't actually failed, use examples from the current frame to continue training the forest. As Figure~\ref{fig:trackinglossrecovery} shows, we are able to start relocalising almost immediately in a live sequence (in a matter of frames, typically 4--6 are enough). Subsequent performance then varies based on the difficulty of the sequence, but rarely drops below $80\%$, except for the challenging \emph{Stairs} sequence. This makes our approach highly practical for interactive relocalisation, something we also show in our supplementary video.
\stufig{width=\linewidth}{images/online_relocalization_icp}{The performance of our approach for tracking loss recovery (\S\ref{subsec:trackinglossrecovery}). Filling the leaves of a forest pre-trained on \emph{Office} frame-by-frame \emph{directly} from the \emph{testing} sequence, we are able to start relocalising almost immediately in new scenes. This makes our approach highly practical in interactive scenarios such as 3D reconstruction.}{fig:trackinglossrecovery}{!t}
\subsection{Generalisation to Novel Poses}
\label{subsec:novelposes}
\stufig{width=\linewidth}{images/novelposes-graph}{Evaluating how well our approach generalises to novel poses in comparison to a keyframe-based random fern relocaliser based on \cite{Glocker2015}. The performance decay experienced as test poses get further from the training trajectory is much less severe with our approach than with random ferns.}{fig:novelposes-graph}{!t}
\begin{figure}[!t]
\vspace{\baselineskip}
\includegraphics[width=\linewidth]{images/poses_frustums}
\includegraphics[width=\linewidth]{images/poses_numbered}
\caption{A qualitative example of novel poses from which we are able to
relocalise to within 5cm/5$^\circ$ on the \emph{Fire} sequence from 7-Scenes
\cite{Shotton2013}. Pose novelty measures the distance of a test pose from a
nearby pose (blue) on the training trajectory (yellow). We can relocalise from
both easy poses (up to 35cm/35$^\circ$ from the training trajectory, green) and
hard poses ($>$ 35cm/35$^\circ$, red). The images below the main figure show
views of the scene from the training poses and testing poses indicated.}
\label{fig:novelposes-example}
\vspace{-\baselineskip}
\end{figure}
To evaluate how well our approach generalises to novel poses, we examine how the
proportion of frames we can relocalise decreases as the distance of the (ground
truth) test poses from the training trajectory increases. We compare our
approach with the keyframe-based relocaliser in InfiniTAM \cite{Kaehler2016},
which is based on the random fern approach of Glocker et al.\
\cite{Glocker2015}. Relocalisation from novel poses is a well-known failure case
of keyframe-based methods, so we would expect the random fern approach to
perform poorly away from the training trajectory; by contrast, it is interesting
to see the extent to which our approach can relocalise from a wide range of
novel poses.
We perform the comparison separately for each 7-Scenes sequence, and then
aggregate the results. For each sequence, we first group the test poses into
bins by pose novelty. Each bin is specified in terms of a maximum translation
and rotation difference of a test pose with respect to the training trajectory
(for example, poses that are within 5cm and 5$^\circ$ of any training pose are
assigned to the first bin, remaining poses that are within 10cm and 10$^\circ$
are assigned to the second bin, etc.). We then determine the proportion of the
test poses in each bin for which it is possible to relocalise to within $5$cm
translational error and $5^\circ$ angular error using (a) the random fern
approach, (b) our approach without ICP and (c) our approach with ICP. As shown
in Figure~\ref{fig:novelposes-graph}, the decay in performance experienced as
the test poses get further from the training trajectory is much less severe with
our approach than with random ferns.
A qualitative example of our ability to relocalise from novel poses is shown in
Figure~\ref{fig:novelposes-example}. In the main figure, we show a range of test
poses from which we can relocalise in the \emph{Fire} scene, linking them to
nearby poses on the training trajectory so as to illustrate their novelty in
comparison to poses on which we have trained. The most difficult of these test
poses are also shown in the images below alongside their nearby training poses,
visually illustrating the significant differences between the two.
As Figures~\ref{fig:novelposes-graph} and \ref{fig:novelposes-example}
illustrate, we are already quite effective at relocalising from poses
that are significantly different from those on which we have trained;
nevertheless, further improvements seem possible. For example, one interesting
extension of this work might be to explore the possibility of using
rotation-invariant split functions in the regression forest to improve its
generalisation capabilities.
\subsection{Timings}
\label{subsec:timings}
\begin{table}[!t]
\centering
\begin{tabular}{ccc}
\toprule
& \textbf{Random Ferns} \cite{Glocker2015,Kaehler2016} & \textbf{Us} \\
\midrule
Per-Frame Training & 0.9ms & 9.8ms \\
Relocalisation & 10ms & 141ms \\
\bottomrule
\end{tabular}
\vspace{1mm}
\caption{Comparing the typical timings of our approach vs.\ random ferns during
both normal operation and relocalisation. Our approach is slower than random
ferns, but achieves significantly higher relocalisation performance, especially
from novel poses. All of our experiments are run on a machine with an Intel Core
i7-4960X CPU and an NVIDIA GeForce Titan Black GPU.}
\label{tbl:timings}
\vspace{-\baselineskip}
\end{table}
To evaluate the usefulness of our approach for on-the-fly relocalisation in new
scenes, we compare it to the keyframe-based random fern relocaliser implemented
in InfiniTAM \cite{Glocker2015,Kaehler2016}. To be practical in a real-time
system, a relocaliser needs to perform in real time during normal operation
(i.e.\ for online training whilst successfully tracking the scene), and ideally
take no more than around $200$ms for relocalisation itself (when the system has
lost track). As a result, relocalisers such as
\cite{Shotton2013,GuzmanRivera2014,Valentin2015RF,Brachmann2016,Massiceti2016},
whilst achieving impressive results, are not practical in this context due to
their need for offline training on the scene of interest.
As shown in Table~\ref{tbl:timings}, the random fern relocaliser is fast both
for online training and relocalisation, taking only $0.9$ms per frame to update
the keyframe database, and $10$ms to relocalise when tracking is lost. However,
speed aside, the range of poses from which it is able to relocalise is quite
limited. By contrast, our approach, whilst taking $9.8$ms for online training
and $141$ms for actual relocalisation, can relocalise from a much broader range
of poses, whilst still running at acceptable speeds. Additionally, it should be
noted that our current research-focused implementation is not heavily optimised,
making it plausible that it could be sped up even further with additional
engineering effort.
\section{Introduction}
\stufigstar{width=.8\linewidth}{images/pipeline.pdf}{
\textbf{Overview of our approach}. First, we train a regression forest
\emph{offline} to predict 2D-to-3D correspondences for a generic scene. To
adapt this forest to a new scene, we remove the scene-specific information
in the forest's leaves while retaining the branching structure (with learned split parameters) of the trees;
we then refill the leaves \emph{online} using training examples from the new
scene. The adapted forest can be deployed to predict correspondences for the
new scene that are fed to Kabsch \cite{Kabsch1976} and RANSAC
\cite{Fischler1981} for pose estimation.
}{fig:pipeline}{!t}
Camera pose estimation is an important problem in computer vision, with
applications in simultaneous localisation and mapping (SLAM)
\cite{Newcombe2011,MurArtal2014,Kaehler2015}, virtual and augmented reality
\cite{Bae2016,Castle2008,Golodetz2015SPDEMO,Paucher2010,Rodas2015,Valentin2015SP} and
navigation \cite{Lee2016}. In SLAM, the camera pose is commonly initialised
upon starting reconstruction and then tracked from one frame to the next, but
tracking can easily be lost due to e.g.\ rapid movement or textureless regions
in the scene; when this happens, it is important to be able to relocalise the
camera with respect to the scene, rather than forcing the user to start the
reconstruction again from scratch. Camera relocalisation is also crucial for
loop closure when trying to build globally consistent maps
\cite{Fioraio2015,Kaehler2016,Whelan2015RSS}. Traditional approaches to camera
relocalisation have been based around one of two main paradigms:
\emph{(i) Image matching methods} match the current image from the camera
against keyframes stored in an image database (potentially with some interpolation
between keyframes where necessary). For example, Galvez-Lopez et al.\
\cite{GalvezLopez2011} describe an approach that computes a bag of binary words
based on BRIEF descriptors for the current image and compares it with bags of
binary words for keyframes in the database using an L1 score. Gee et al.\
\cite{Gee2012} estimate camera pose from a set of synthetic (i.e.\ rendered)
views of the scene. Their approach is interesting because unlike many image
matching methods, they are to some extent able to relocalise from novel
poses; however, the complexity increases linearly with the number of synthetic views
needed, which poses significant limits to practical use. Glocker et al.\
\cite{Glocker2015} encode frames using Randomised Ferns, which when evaluated on
images yield binary codes that can be matched quickly by their Hamming
distance: as noted in \cite{Li2015}, this makes their approach much faster than
\cite{Gee2012} in practice.
\emph{(ii) Keypoint-based methods} find 2D-to-3D correspondences between
keypoints in the current image and 3D scene points, so as to deploy e.g.\ a
Perspective-n-Point (PnP) algorithm \cite{Hartley2004} (on RGB data) or
the Kabsch algorithm \cite{Kabsch1976} (on RGB-D data) to generate a
number of camera pose hypotheses that can be pruned to a single hypothesis using
RANSAC \cite{Fischler1981}. For example, Williams et al.\ \cite{Williams2011}
recognise/match keypoints using an ensemble of randomised lists, and exclude
unreliable or ambiguous matches when generating hypotheses. Their approach is
fast, but needs significant memory to store the lists. Li et al.\ \cite{Li2015} use
graph matching to help distinguish between visually-similar keypoints. Their
method uses BRISK descriptors for the keypoints, and runs at around 12 FPS.
Sattler et al.\ \cite{Sattler2016} describe a large-scale localisation approach
that finds correspondences in both the 2D-to-3D and 3D-to-2D directions before
applying a 6-point DLT algorithm to compute pose hypotheses. They use a visual
vocabulary to order potential matches by how costly they will be to establish.
Some hybrid methods use both paradigms. For example, Mur-Artal et al.\
\cite{MurArtal2015} describe a relocalisation approach that initially finds pose
candidates using bag of words recognition \cite{GalvezLopez2012}, which they
incorporate into their larger ORB-SLAM system (unlike \cite{GalvezLopez2011},
they use ORB rather than BRIEF features, which they found to improve
performance). They then refine these candidate poses using PnP and RANSAC.
Valentin et al.\ \cite{Valentin2016} present an approach that finds initial pose
candidates using the combination of a retrieval forest and a multiscale
navigation graph, before refining them using continuous pose optimisation.
Several less traditional approaches have also been tried. Kendall et
al.~\cite{Kendall2015} train a convolutional neural network to directly regress
the 6D camera pose from the current image. Deng et al.~\cite{Deng2016} match a 3D
point cloud representing the scene to a local 3D point cloud constructed from a
set of query images that can be incrementally extended by the user to achieve a
successful match. Lu et al.~\cite{Lu2015} perform 3D-to-3D localisation that
reconstructs a 3D model from a short video using structure-from-motion and
matches that against the scene within a multi-task point retrieval framework.
Recently, Shotton et al.\ \cite{Shotton2013} proposed the use of a regression
forest to directly predict 3D correspondences in the scene for all pixels in the
current image. This has two key advantages over traditional keypoint-based
approaches: (i) no explicit detection, description or matching of keypoints is
required, making the approach both simpler and faster, and (ii) a significantly
larger number of points can be deployed to verify or reject camera pose
hypotheses. However, it suffers from the key limitation of needing to train a
regression forest on the scene \emph{offline} (in advance), which prevents
on-the-fly camera relocalisation.
Subsequent work has significantly improved upon the relocalisation performance
of \cite{Shotton2013}. For example, Guzman-Rivera et al.\
\cite{GuzmanRivera2014} rely on multiple regression forests to generate a number of
camera pose hypotheses, then cluster them and use the mean pose of the cluster
whose poses minimise the reconstruction error as the result. Valentin et al.\
\cite{Valentin2015RF} replace the modes used in the leaves of the forests in
\cite{Shotton2013} with mixtures of anisotropic 3D Gaussians in order to better
model uncertainties in the 3D point predictions, and show that by combining this
with continuous pose optimisation they can relocalise 40\% more frames than
\cite{Shotton2013}.
Brachmann et al.\ \cite{Brachmann2016} deploy a stacked classification-regression
forest to achieve results of a quality similar to \cite{Valentin2015RF} for
RGB-D relocalisation.
Massiceti et al.\ \cite{Massiceti2016} map between regression forests and neural
networks to try to leverage the performance benefits of neural networks for
dense regression while retaining the efficiency of random forests for
evaluation. They use robust geometric median averaging to achieve improvements
of around 7\% over \cite{Brachmann2016} for RGB localisation. However, despite
all of these advances, none of these papers remove the need to train on the
scene of interest in advance.
In this paper, we show that this need for \emph{offline} training on the scene
of interest can be overcome through \emph{online} adaptation to a new scene of a regression forest that has been pre-trained on a generic scene. We achieve genuine
on-the-fly relocalisation similar to that which can be obtained using
keyframe-based approaches \cite{Glocker2015}, but with both significantly higher
relocalisation performance in general, and the specific advantage that we can
relocalise from novel poses. Indeed, our adapted forests achieve relocalisation
performance that is competitive with offline-trained forests, whilst requiring
no pre-training on the scene of interest and relocalising in close to real time.
This makes our approach a practical and high-quality alternative to
keyframe-based methods for online relocalisation in novel scenes.
\section{Method}
\label{sec:method}
\subsection{Overview}
\label{subsec::methodoverview}
\noindent Figure~\ref{fig:pipeline} shows an overview of our approach.
Initially, we train a regression forest \emph{offline} to predict 2D-to-3D
correspondences for a \emph{generic} scene, as per \cite{Valentin2015RF}.
To adapt this forest to a new scene, we remove the
contents of the leaf nodes in the forest (i.e.\ GMM modes and associated covariance matrices)
whilst retaining the branching structure of the trees (including learned split parameters). We then adapt the forest
\emph{online} to the new scene by feeding training examples down the forest to
refill the empty leaves, dynamically learning a set of leaf distributions specific
to that scene. Thus adapted, the forest can then be used to predict
correspondences for the new scene that can be used for camera pose estimation.
Reusing the tree structures spares us from expensive offline learning on
deployment in a novel scene, allowing for relocalisation on the fly.
\subsection{Details}
\label{subsec::methoddetails}
\subsubsection{Offline Forest Training}
\label{subsubsec::forestpretraining}
Training is done as in \cite{Valentin2015RF}, greedily optimising a standard
reduction-in-spatial-variance objective over the randomised parameters of simple
threshold functions. Like \cite{Valentin2015RF}, we make use of `Depth' and
`Depth-Adaptive RGB' (`DA-RGB') features, centred at a pixel $\textbf{p}$, as
follows:
\begin{equation}
f^{\text{Depth}}_\Omega = D(\mathbf{p}) - D\left(\mathbf{p} + \frac{\boldsymbol{\delta}}{D(\mathbf{p})}\right)
\end{equation}
\begin{equation}
f^{\text{DA-RGB}}_\Omega = C(\mathbf{p},c) - C\left(\mathbf{p} + \frac{\boldsymbol{\delta}}{D(\mathbf{p})}, c\right)
\end{equation}
In this, $D(\mathbf{p})$ is the depth at $\mathbf{p}$, $C(\mathbf{p},c)$ is the
value of the $c^{\text{th}}$ colour channel at $\mathbf{p}$, and $\Omega$ is a
vector of randomly sampled feature parameters. For `Depth', the only parameter
is the 2D image-space offset $\boldsymbol{\delta}$, whereas `DA-RGB' adds the
colour channel selection parameter $c \in \{R,G,B\}$. We randomly generate 128
values of $\Omega$ for `Depth' and 128 for `DA-RGB'. We concatenate the
evaluations of these functions at each pixel of interest to yield 256D feature
vectors.
At training time, a set $S$ of training examples, each consisting of such a
feature vector $\mathbf{f} \in \mathbb{R}^{256}$, its corresponding 3D location
in the scene and its colour, is assembled via sampling from a ground truth RGB-D
video with known camera poses for each frame (obtained by tracking from depth camera
input). A random subset of these training examples is selected to train each tree in
the forest, and we then train all of the trees in parallel.
Starting from the root of each tree, we recursively partition the set of training examples in
the current node into two using a binary threshold function. To decide how to split each
node $n$, we randomly generate a set $\Theta_n$ of $512$ candidate split parameter pairs,
where each $\theta = (\phi,\tau) \in \Theta_n$ denotes the binary threshold function
\begin{equation}
\theta(\mathbf{f}) = \mathbf{f}[\phi] \ge \tau.
\end{equation}
In this, $\phi \in [0,256)$ is a randomly-chosen feature index, and $\tau \in \mathbb{R}$
is a threshold, chosen to be the value of feature $\phi$ in a randomly-chosen training example.
Examples that pass the test are routed to the right subtree of $n$; the remainder are routed
to the left.
To pick a suitable split function for $n$, we use exhaustive search to find a $\theta^{*} \in \Theta_n$
whose corresponding split function maximises the information gain that can be achieved by splitting the
training examples that reach $n$. Formally, the information gain corresponding to split parameters
$\theta \in \Theta_n$ is
\begin{equation}
V(S_n) - \displaystyle\sum_{i\in\{\text{L,R}\}} \frac{|S^i_n(\theta)|}{|S_n|} \; V(S^i_n(\theta)),
\end{equation}
in which $V(X)$ denotes the spatial variance of set $X$, and $S^L_n(\theta)$ and
$S^R_n(\theta)$ denote the left and right subsets into which the set $S_n
\subseteq S$ of training examples reaching $n$ is partitioned by the split
function denoted by $\theta$. Spatial variance is defined in terms of the
log of the determinant of the covariance of a fitted 3D Gaussian \cite{Valentin2015RF}.
For a given tree, the above process is simply recursed to a maximum depth of 15.
As in \cite{Valentin2015RF}, we train 5 trees per forest.
The (approximate, empirical) distributions in the leaves are discarded at the end of this process (we replace them during online forest adaptation, as discussed next).
\subsubsection{Online Forest Adaptation}
\label{subsubsec::forestadaptation}
\begin{stusubfig*}{!t}
\begin{subfigure}{.47\linewidth}
\centering
\includegraphics[width=\linewidth]{images/modes-pretrained}
\caption{}
\end{subfigure}%
\hspace{10mm}%
\begin{subfigure}{.47\linewidth}
\centering
\includegraphics[width=\linewidth]{images/modes-adapted}
\caption{}
\end{subfigure}%
\caption{An illustrative example of the effect that online adaptation has on a
pre-trained forest: (a) shows the modal clusters present in a small number of
randomly-selected leaves of a forest pre-trained on the \emph{Chess} scene from
the 7-Scenes dataset \cite{Shotton2013} (the colour of each mode indicates its
containing leaf); (b) shows the modal clusters that are added to the same leaves
during the process of adapting the forest to the \emph{Kitchen} scene.}
\label{fig:modes}
\vspace{-1.5\baselineskip}
\end{stusubfig*}
To adapt a forest to a new environment, we replace the distributions discarded from its leaves at the end of pre-training with dynamically-updated ones drawn entirely from the new scene.
Here, we detail how the new leaf distributions used by the relocaliser are computed and updated online.
We draw inspiration from the use of reservoir sampling \cite{Vitter1985} in SemanticPaint \cite{Valentin2015SP}, which makes it possible to store an unbiased subset of an empirical distribution in a bounded amount of memory.
On initialisation, we allocate (on the GPU) a fixed-size sample reservoir for each leaf of the existing forest.
Our reservoirs contain up to $1024$ entries, each storing a 3D (world coordinate) location and an associated colour.
At runtime, we pass training examples (as per \S\ref{subsubsec::forestpretraining}) down the forest and identify the leaves to which each example is mapped.
We then add the 3D location and colour of each example to the reservoirs associated with its leaves.
To obtain the 3D locations of the training examples, we need to know the transformation that maps points from camera space to world space.
When testing on sequences from a dataset, this is trivially available as the ground truth camera pose, but in a live scenario, it will generally be obtained as the output of a fallible tracker.
To avoid corrupting the reservoirs in our forest, we avoid passing new examples down the forest when the tracking is unreliable.
We measure tracker reliability using the support vector machine (SVM) approach described in \cite{Kaehler2016}.
For frames for which a reliable camera pose \emph{is} available, we proceed as follows:
\begin{enumerate}
\item First, we compute feature vectors for a subset of the pixels in the image, as detailed in \S\ref{subsubsec::forestpretraining}. We empirically choose our subset by subsampling densely on a regular grid with $4$-pixel spacing, i.e.\ we choose pixels $\{(4i,4j) \in [0,w) \times [0,h) : i,j \in \mathbb{N} \}$, where $w$ and $h$ are respectively the width and height of the image.
\item Next, we pass each feature vector down the forest, adding the 3D position and colour of the corresponding scene point to the reservoir of the leaf reached in each tree. Our CUDA-based random forest implementation uses the node indexing described in~\cite{Sharp2008}.
\item Finally, for each leaf reservoir, we cluster the contained points using a CUDA implementation of Really Quick Shift (RQS) \cite{Fulkerson2010} to find a set of modal 3D locations. We sort the clusters in each leaf in decreasing size order, and keep at most $10$ modal clusters per leaf. For each cluster we keep, we compute 3D and colour centroids, and a covariance matrix. The cluster distributions are used when estimating the likelihood of a camera pose, and also during continuous pose optimisation (see \S\ref{subsubsec:poseestimation}).
Since running RQS over all the leaves in the forest would take too long if run in a single frame, we amortise the cost over multiple frames by updating $256$ leaves in parallel each frame in round-robin fashion. A typical forest contains around \num[group-separator={,}]{42000} leaves, so each leaf is updated roughly once every $6$s.
\end{enumerate}
The aforementioned reservoir size, number of modal clusters per leaf and number of leaves to update per frame were determined empirically to achieve online processing rates.
Figure~\ref{fig:modes} illustrates the effect that
online adaptation has on a pre-trained forest: (a) shows the modal clusters
present in a few randomly-selected leaves of a forest pre-trained on
the \emph{Chess} scene from the 7-Scenes dataset \cite{Shotton2013}; (b) shows
the modal clusters that are added to the same leaves during the process of
adapting the forest to the \emph{Kitchen} scene. Note that whilst the positions
of the predicted modes have (unsurprisingly) completely changed, the split
functions in the forest's branch nodes (which we preserve) still do a good
job of routing similar parts of the scene into the same leaves, enabling
effective sampling of 2D-to-3D correspondences for camera pose estimation.
\subsubsection{Camera Pose Estimation}
\label{subsubsec:poseestimation}
As in \cite{Valentin2015RF}, camera pose estimation is based on the preemptive, locally-optimised RANSAC of \cite{Chum2003}.
We begin by randomly generating an initial set of up to $1024$ pose hypotheses.
A pose hypothesis $H \in \mathbf{SE}(3)$ is a transform that maps points in camera space to world space.
To generate each pose hypothesis, we apply the Kabsch algorithm \cite{Kabsch1976} to $3$ point pairs of the form $(\mathbf{x}_i^\mathcal{C}, \mathbf{x}_i^\mathcal{W})$, where $\mathbf{x}_i^\mathcal{C} = D(\mathbf{u}_i) K^{-1} (\mathbf{u}_i^\top,1)$ is obtained by back-projecting a randomly-chosen point $\mathbf{u}_i$ in the live depth image $D$ into camera space, and $\mathbf{x}_i^\mathcal{W}$ is a corresponding scene point in world space, randomly sampled from $M(\mathbf{u}_i)$, the modes of the leaves to which the forest maps $\mathbf{u}_i$.
In this, $K$ is the intrinsic calibration matrix for the depth camera.
Before accepting a hypothesis, we subject it to a series of checks:
\begin{enumerate}
\item First, we randomly choose one of the three point pairs $(\mathbf{x}_i^\mathcal{C},\mathbf{x}_i^\mathcal{W})$ and compare the RGB colour of the corresponding pixel $\mathbf{u}_i$ in the colour input image to the colour centroid of the mode (see \S\ref{subsubsec::forestadaptation}) from which we sampled $\mathbf{x}_i^\mathcal{W}$. We reject the hypothesis iff the L0 distance between the two exceeds a threshold.
\item Next, we check that the three hypothesised scene points are sufficiently far from each other. We reject the hypothesis iff the minimum distance between any pair of points is less than $30$cm.
\item Finally, we check that the distances between all scene point pairs and their corresponding back-projected depth point pairs are sufficiently similar, i.e.\ that the hypothesised transform is `rigid enough'. We reject the hypothesis iff this is not the case.
\end{enumerate}
If a hypothesis gets rejected by one of the checks, we try to generate an alternative hypothesis to replace it.
In practice, we use $1024$ dedicated threads, each of which attempts to generate a single hypothesis.
Each thread continues generating hypotheses until either (a) it finds a hypothesis that passes all of the checks, or (b) a maximum number of iterations is reached.
We proceed with however many hypotheses we obtain by the end of this process.
Having generated our large initial set of hypotheses, we next aggressively cut it down to a much smaller size by scoring each hypothesis and keeping the $64$ lowest-energy transforms (if there are fewer than $64$ hypotheses, we keep all of them).
To score the hypotheses, we first select an initial set $I = \{i\}$ of $500$ pixel indices in $D$, and back-project the denoted pixels $\mathbf{u}_i$ to corresponding points $\mathbf{x}_i^\mathcal{C}$ in camera space as described above.
We then score each hypothesis $H$ by summing the Mahalanobis distances between the transformations of each $\mathbf{x}_i^\mathcal{C}$ under $H$ and their nearest modes:
\begin{equation}
E(H) = \sum_{i \in I} \left( \min_{(\boldsymbol{\mu},\Sigma) \in M(\mathbf{u}_i)} \left\| \Sigma^{-\frac{1}{2}} (H\mathbf{x}_i^\mathcal{C} - \boldsymbol{\mu}) \right\| \right)
\end{equation}
After this initial cull, we use pre-emptive RANSAC to prune the remaining $\le 64$ hypotheses to a single, final hypothesis.
We iteratively (i) expand the sample set $I$ (by adding $500$ new pixels each time), (ii) refine the pose candidates via Levenberg-Marquardt optimisation \cite{Levenberg1944,Marquardt1963} of the energy function $E$, (iii) re-evaluate and re-score the hypotheses, and (iv) discard the worse half.
In practice, the actual optimisation is performed not in $\mathbf{SE}(3)$, where it would be hard to do, but in the corresponding Lie algebra, $\mathfrak{se}(3)$.
The details of this process can be found in \cite{Valentin2015RF}, and a longer explanation of Lie algebras can be found in \cite{Strasdat2012}.
This process yields a single pose hypothesis, which we can then return if desired.
In practice, however, further pose refinement is sometimes possible.
For example, if our relocaliser is integrated into an open-source 3D reconstruction framework such as InfiniTAM \cite{Kaehler2016}, we can attempt to refine the pose further using ICP \cite{Besl1992}.
Since tasks such as 3D reconstruction are one of the key applications of our approach, we report results both with and without ICP in Table~\ref{tbl:adaptationperformance}.
\part*{\textsc{Supplementary Materials}} \vspace{2\baselineskip}]
\input{supplementary_main}
}
\fi
\end{document}
\section{Analysis of Failure Cases}
As shown in the main paper, our approach is able to achieve highly-accurate online relocalisation in under $150$ms, from novel poses and without needing extensive offline training on the target scene.
However, there are inevitably still situations in which it will fail.
In this section, we analyse two interesting failure cases, so as to help the reader understand the underlying reasons in each case.
\subsection{Office}
The first failure case we analyse is from the \emph{Office} scene in the 7-Scenes dataset \cite{Shotton2013}.
This scene captures a typical office that contains a number of desks (see Figure~\ref{fig:officefailure}).
Unfortunately, these desks appear visually quite similar: they are made of the same wood, and have similar monitors and the same associated chairs.
This makes it very difficult for a relocaliser such as ours to distinguish between them: as a result, our approach ends up producing a pose that faces the wrong desk (see Figure~\ref{fig:officefailure}(d)).
On one level, the pose we produce is not entirely unreasonable: indeed, it looks superficially plausible, and is oriented at roughly the right angle with respect to the incorrect desk.
Nevertheless, in absolute terms, the pose is obviously very far from the ground truth.
To pin down what has gone wrong, we visualise the last $16$ surviving camera pose hypotheses for this instance in Figure~\ref{fig:officecandidates}, in descending order (left-to-right, top-to-bottom).
We observe that whilst the top candidate selected by RANSAC relocalises the camera to face the wrong desk, any of the next five candidates would have relocalised the camera successfully.
The problem in this case is that the energies computed for the hypotheses are fairly similar for both the correct and incorrect poses.
Although we do not investigate it here, one potential way of fixing this might be to score the last few surviving hypotheses based on the photometric consistencies between colour raycasts from their respective poses and the colour input image.
\vspace{3cm}\textcolor{white}{.}
\begin{stusubfig}{H}
\begin{subfigure}{\linewidth}
\centering
\includegraphics[width=\linewidth]{images/supplementary/office_mesh}
\caption{}
\end{subfigure}%
\\
\begin{subfigure}{.49\linewidth}
\centering
\includegraphics[width=\linewidth]{images/supplementary/office_train_desk}
\caption{}
\end{subfigure}%
\hspace{1.5mm}%
\begin{subfigure}{.49\linewidth}
\centering
\includegraphics[width=\linewidth]{images/supplementary/office_train_desk_2}
\caption{}
\end{subfigure}%
\\
\begin{subfigure}{\linewidth}
\centering
\includegraphics[width=\linewidth]{images/supplementary/office_reloc_error}
\caption{}
\end{subfigure}%
\caption{The \emph{Office} scene from the 7-Scenes dataset \cite{Shotton2013} (a) contains multiple desks, e.g.\ (b) and (c), that can appear visually quite similar, making it difficult for the relocaliser to distinguish between them. In (d), for example, the relocaliser incorrectly chooses a pose facing the desk in (b), whilst the RGB-D input actually shows the desk in (c).}
\label{fig:officefailure}
\vspace{-1.5\baselineskip}
\end{stusubfig}
\begin{figure*}[!p]
\centering
\includegraphics[height=20.5cm]{images/supplementary/office_candidates}
\caption{The top $16$ pose candidates (left-to-right, top-to-bottom) corresponding to the failure case on the \emph{Office} scene shown in Figure~\ref{fig:officefailure}(d). The coloured points indicate the 2D-to-3D correspondences that are used to generate the initial pose hypotheses. Note that whilst the top candidate selected by RANSAC relocalises the camera to face the wrong desk, any of the next five candidates would have relocalised the camera correctly.}
\label{fig:officecandidates}
\end{figure*}
\clearpage
\subsection{Stairs}
\begin{stusubfig}{!t}
\begin{subfigure}{\linewidth}
\centering
\includegraphics[width=\linewidth]{images/supplementary/stairs_mesh}
\caption{}
\end{subfigure}%
\\
\begin{subfigure}{.49\linewidth}
\centering
\includegraphics[width=\linewidth]{images/supplementary/stairs_train_1}
\caption{}
\end{subfigure}%
\hspace{1.5mm}%
\begin{subfigure}{.49\linewidth}
\centering
\includegraphics[width=\linewidth]{images/supplementary/stairs_train_2}
\caption{}
\end{subfigure}%
\\
\begin{subfigure}{\linewidth}
\centering
\includegraphics[width=\linewidth]{images/supplementary/stairs_reloc_error}
\caption{}
\end{subfigure}%
\caption{The \emph{Stairs} scene from the 7-Scenes dataset \cite{Shotton2013} (a) is notoriously difficult, containing a staircase that consists of numerous visually-identical steps (see (b) and (c)). In (d), many of the 2D-to-3D correspondences predicted by the forest are likely to be of a low quality, since it is hard to distinguish between similar points on different stairs. This significantly reduces the probability of generating good initial hypotheses, leaving RANSAC trying to pick a good hypothesis from an initial set that only contains bad ones.}
\label{fig:stairsfailures}
\vspace{3cm}
\end{stusubfig}
The second failure case we analyse is from the \emph{Stairs} scene in the 7-Scenes dataset \cite{Shotton2013}.
This is a notoriously difficult scene containing a staircase that consists of numerous visually-identical steps (see Figure~\ref{fig:stairsfailures}).
When viewing the scene from certain angles (see Figure~\ref{fig:stairsgood}), the relocaliser is able to rely on points in the scene that can be identified unambiguously to correctly estimate the pose, but from viewpoints such as that in Figure~\ref{fig:stairsfailures}(d), it is forced to use more ambiguous points, e.g.\ those on the stairs themselves or the walls.
When this happens, relocalisation is prone to fail, since the relocaliser finds it difficult to tell the difference between the different steps.
As in the previous section, we can visualise the top $16$ camera pose hypotheses for this instance to pin down what has gone wrong (see Figure~\ref{fig:stairscandidates}).
It is noticeable that in this case, none of the top $16$ hypotheses would have successfully relocalised the camera.
As suggested by the points predicted in the 3D scene for each hypothesis (which are often in roughly the right place but on the wrong stairs), this is because the points at the same places on different stairs tend to end up in similar leaves, making the modes in the leaves less informative (see Figure~\ref{fig:stairsmodes}) and significantly reducing the probability of generating good initial hypotheses.
Unlike in the \emph{Office} case, the problem here cannot be fixed by a late-stage consistency check, since none of the last few surviving hypotheses are of any use.
Instead, one potential way of fixing this might be to improve the way in which the initial set of hypotheses is generated so as to construct a more diverse set and increase the probability of one of the initial poses being in roughly the right place.
An alternative might be to adaptively increase the number of hypotheses generated in difficult conditions.
\clearpage
\begin{stusubfig}{!t}
\begin{subfigure}{.49\linewidth}
\centering
\includegraphics[width=\linewidth]{images/supplementary/candidates_stairs_good}
\end{subfigure}%
\hspace{1.5mm}%
\begin{subfigure}{.48\linewidth}
\centering
\includegraphics[width=\linewidth]{images/supplementary/candidates_stairs_good_2}
\end{subfigure}%
\caption{From certain angles in the \emph{Stairs} scene, the relocaliser is able to rely on points in the scene that can be identified unambiguously to estimate the pose.}
\label{fig:stairsgood}
\vspace{-1.5\baselineskip}
\end{stusubfig}
\begin{figure}[!t]
\centering
\includegraphics[width=\linewidth]{images/supplementary/stairs_candidates_leave_modes}
\caption{The modal clusters contained in the leaves for the points in the optimal camera pose hypothesis from Figure~\ref{fig:stairscandidates}. It is noticeable that points at the same places on different stairs end up in the same leaves, making the distributions in those leaves less informative.}
\label{fig:stairsmodes}
\vspace{6cm}
\end{figure}
\section{Further Successful Examples}
Some further examples of successful relocalisation, this time in the \emph{Fire} scene from the 7-Scenes dataset \cite{Shotton2013}, can be seen in Figure~\ref{fig:firegood}.
As in Figure~\ref{fig:stairsgood}, it is noticeable that the relocaliser tries to rely on points in the scene that can be identified unambiguously where these are available, something that is clearly easier in sequences such as \emph{Fire} that contain many easily-distinguished objects.
\begin{stusubfig}{H}
\begin{subfigure}{.49\linewidth}
\centering
\includegraphics[width=\linewidth]{images/supplementary/candidates_fire_good}
\end{subfigure}%
\hspace{1.5mm}%
\begin{subfigure}{.49\linewidth}
\centering
\includegraphics[width=\linewidth]{images/supplementary/candidates_fire_good_2}
\end{subfigure}%
\caption{Further examples of successful relocalisation in the \emph{Fire} scene from the 7-Scenes dataset \cite{Shotton2013}. To estimate the pose, the relocaliser tries to rely on points in the scene that can be identified unambiguously.}
\label{fig:firegood}
\vspace{-1.5\baselineskip}
\end{stusubfig}
\begin{figure*}[!p]
\centering
\includegraphics[height=20.5cm]{images/supplementary/stairs_candidates_leaves}
\caption{The top $16$ pose candidates (left-to-right, top-to-bottom) corresponding to the failure case on the \emph{Stairs} scene shown in Figure~\ref{fig:stairsfailures}(d). The coloured points indicate the 2D-to-3D correspondences that are used to generate the initial pose hypotheses. Note that in this case, none of the candidates would relocalise the camera successfully. This is likely because the points at the same places on different stairs tend to end up in similar leaves, making the modes in the leaves less informative and significantly reducing the probability of generating good initial hypotheses.}
\label{fig:stairscandidates}
\end{figure*}
|
{
"redpajama_set_name": "RedPajamaArXiv"
}
| 582
|
{"url":"https:\/\/www.tutorialspoint.com\/average-of-ascii-values-of-characters-of-a-given-string","text":"Average of ASCII values of characters of a given string?\n\nCServer Side ProgrammingProgramming\n\nHere we will see how to count the average of the ASCII values of each character in a given string. Suppose the string is \u201cABC\u201d. The asci values are 65, 66, 67. So the average of these three is 66.\n\nAlgorithm\n\nasciiAverage(String)\n\nBegin\nsum := 0\nfor each character c in String, do\nsum := sum + ASCII of c\ndone\nreturn sum\/length of String\nEnd\n\nExample\n\nLive Demo\n\n#include<iostream>\nusing namespace std;\nfloat asciiAverage(string str){\nint sum = 0;\nfor(int i = 0; i<str.size(); i++){\nsum += int(str[i]);\n}\nreturn sum\/str.size();\n}\nmain() {\nstring str;\ncout << \"Enter a string: \";\ncin >> str;\ncout << \"ASCII average is: \" << asciiAverage(str);\n}\n\nOutput\n\nEnter a string: Hello\nASCII average is: 100\nPublished on 26-Jul-2019 14:47:51","date":"2020-06-01 12:03:31","metadata":"{\"extraction_info\": {\"found_math\": true, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 0, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 0, \"mathjax_display_tex\": 0, \"mathjax_asciimath\": 1, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 0, \"wp-katex-eq\": 0, \"align\": 0, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.47645580768585205, \"perplexity\": 11073.414731678478}, \"config\": {\"markdown_headings\": false, \"markdown_code\": true, \"boilerplate_config\": {\"ratio_threshold\": 0.18, \"absolute_threshold\": 20, \"end_threshold\": 15, \"enable\": true}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2020-24\/segments\/1590347417746.33\/warc\/CC-MAIN-20200601113849-20200601143849-00107.warc.gz\"}"}
| null | null |
#include "Script.h"
#include "API/ScriptAPI.h"
#include "Core/Upload/ScriptUploadEngine.h"
#include "Core/Logging.h"
#include "Core/ThreadSync.h"
Script::Script(const std::string& fileName, ThreadSync* serverSync, std::shared_ptr<INetworkClientFactory> networkClientFactory, bool doLoad)
{
m_CreationTime = time(nullptr);
m_bIsPluginLoaded = false;
sync_ = serverSync;
owningThread_ = std::this_thread::get_id();
networkClientFactory_ = std::move(networkClientFactory);
fileName_ = fileName;
if (doLoad) {
load(fileName);
}
}
Script::~Script()
{
ScriptAPI::ClearVmData(vm_);
}
void Script::CompilerErrorHandler(HSQUIRRELVM vm, const SQChar * desc, const SQChar * source, SQInteger line, SQInteger column) {
sq_getprintfunc(vm)(vm, ("Script compilation failed\r\nFile: " + std::string(source) + "\r\nLine: " + IuCoreUtils::int64_tToString(line)
+ " Column: " + IuCoreUtils::int64_tToString(column) + "\r\n\r\n" + desc).c_str() );
}
void Script::InitScriptEngine()
{
ScriptAPI::SetPrintCallback(vm_, std::bind(&Script::PrintCallback, this, std::placeholders::_1));
sqstd_seterrorhandlers(vm_.GetVM());
ScriptAPI::SetScriptName(vm_, fileName_);
sq_setcompilererrorhandler(vm_.GetVM(), CompilerErrorHandler);
}
void Script::DestroyScriptEngine()
{
ScriptAPI::CleanUp();
}
void Script::FlushSquirrelOutput()
{
ScriptAPI::FlushSquirrelOutput(vm_.GetVM());
}
bool Script::preLoad()
{
networkClient_ = networkClientFactory_->create();
networkClient_->setCurlShare(sync_->getCurlShare());
Sqrat::RootTable& rootTable = vm_.GetRootTable();
rootTable.SetInstance("Sync", sync_);
rootTable.SetInstance("nm", networkClient_.get());
return true;
}
bool Script::postLoad()
{
return true;
}
bool Script::isLoaded() const
{
return m_bIsPluginLoaded;
}
time_t Script::getCreationTime() const
{
return m_CreationTime;
}
void Script::switchToThisVM()
{
ScriptAPI::SetCurrentThreadVM(vm_.GetVM());
}
Sqrat::SqratVM& Script::getVM()
{
return vm_;
}
bool Script::load(const std::string& fileName)
{
using namespace Sqrat;
if (!IuCoreUtils::FileExists(fileName))
{
LOG(ERROR) << "Script file doesn't exist: " << fileName;
return false;
}
using namespace ScriptAPI;
try
{
InitScriptEngine();
ScriptAPI::RegisterAPI(vm_);
std::string scriptText;
if (!IuCoreUtils::ReadUtf8TextFile(fileName, scriptText)) {
LOG(ERROR) << "Failed to read script from file " << fileName;
return false;
}
preLoad();
switchToThisVM();
m_SquirrelScript = std::make_unique<Sqrat::Script>(vm_.GetVM());
m_SquirrelScript->CompileString(scriptText, IuCoreUtils::ExtractFileName(fileName));
m_SquirrelScript->Run();
RegisterShortTranslateFunctions(vm_);
postLoad();
m_bIsPluginLoaded = true;
}
catch (std::exception& e)
{
LOG(ERROR)<< "CScriptUploadEngine::Load failed" << std::endl
<< "File: " << IuCoreUtils::ExtractFileName(fileName) << std::endl
<< std::string("Error: ") << e.what();
FlushSquirrelOutput();
return false;
}
FlushSquirrelOutput();
return true;
}
void Script::PrintCallback(const std::string& output)
{
const std::thread::id threadId = std::this_thread::get_id();
LOG(WARNING) << IuCoreUtils::ExtractFileName(fileName_) << " [ThreadId=" << IuCoreUtils::ThreadIdToString(threadId) << "]\r\n" << output;
}
void Script::checkCallingThread() const
{
const std::thread::id threadId = std::this_thread::get_id();
if (threadId != owningThread_)
{
throw std::runtime_error("Script methods should be called only in the owning thread.");
}
}
void Script::setCurrentTopLevelFileName(const std::string& fileName) {
topLevelFileName_ = fileName;
ScriptAPI::SetCurrentTopLevelFileName(vm_, fileName);
}
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 315
|
{"url":"https:\/\/www.r-bloggers.com\/amazons-hanging-cable-problem-golden-gate-edition\/","text":"# Amazon\u2019s Hanging Cable Problem (Golden Gate Edition)\n\nJuly 22, 2018\nBy\n\n(This article was first published on Theory meets practice..., and kindly contributed to R-bloggers)\n\n## Abstract:\n\nIn this post we use R\u2019s capabilities to solve nonlinear equation systems in order to answer an extension of the hanging cable problem to suspension bridges. We then use R and ggplot to overlay the solution to an image of the Golden Gate Bridge in order to bring together theory and practice.\n\n## Introduction\n\nThe so called Amazon\u2019s hanging cable problem explained in this youtube video (watched 2.4 mio times!1) goes as follows:\n\nA cable of 80 meters (m) is hanging from the top of two poles that are both 50 m from the ground. What is the distance between the two poles, to one decimal place, if the center of the cable is:\n\n1. 20 m above the ground?\n2. 10 m above the ground?\n\nAllegedly, (b) has been used as an Amazon interview question, however, the problem is much older and has otherwise nothing to do with Amazon. Can you solve (b)? Or even (a)? The problem can be illustrated as follows:\n\nScreenshot from Presh Talwalkar\u2019s website.\n\nHint: The solution to (a) is concisely described in Chatterjee and Nita (2010) and for (b) you need to do little more than just think. So instead of applying at Amazon, let\u2019s take the question to the next level: Apply for the orange belt in R: How you wouldn\u2019t solve the hanging cable problem by instead solving the hanging cable problem suspension bridge style!\n\nAs explained in the video the catenary curve is the geometric shape, a cable assumes under its own weight when supported only at its ends. If instead the cable supports a uniformly distributed vertical load, the cable has the shape of a parabolic curve. This would for example be the case for a suspension bridge with a horizontal suspended deck, if the cable itself is not too heavy compared to the road sections. A prominent example of a suspension bridges is the Golden Gate Bridge, which we will use as motivating example for this post.\n\n## Solving the Cable Problem\n\n### Parabola Shape\n\nRephrasing the cable problem as the \u2018suspension bridge problem\u2018 we need to solve a two-component non-linear equation system:\n\n1. the first component ensures that the parabolic curve with vertex at $$(0,0)$$ goes through the poles at the x-values $$-x$$ and $$x$$. In other words: the distance between the two poles is $$2x$$. Note that the coordinate system is aligned such that the lowest point of the cable is at the origo.\n\n2. the second component ensures that the arc-length of the parabola is as given by the problem. Since the parabola is symmetric it is sufficient to study the positive x-axis\n\nThe two criteria are converted into an equation system as follows: \\begin{align*} a x^2 &= 50 \u2013 \\text{height above ground} \\\\ \\int_0^x \\sqrt{1 + \\left(\\frac{d}{du} a u^2\\right)^2} du &= 40. \\end{align*}\n\nHere, the general equation for arc-length of a function $$y=f(u)$$ has been used. Solving the arc-length integral for a parabola can either be done by numerical integration or by solving the integral analytically or just look up the resulting analytic expression as eqn 4.25 in Spiegel (1968). Subtracting the RHS from each LHS gives us a non-linear equation system with unknowns $$a$$ and $$x$$ of the form\n\n$\\left[ \\begin{array}{c} y_1(a,x) \\\\ y_2(a,x) \\end{array} \\right] = \\left[ \\begin{array}{c} 0 \\\\ 0 \\end{array} \\right].$\n\nWriting this in R code:\n\n## Height of function at the location x from center is (pole_height - height_above_ground)\ny1_parabola <- function(a, x, pole_height=50, above_ground=20) {\na*x^2 - (pole_height - above_ground)\n}\n\n## Arc-length of the parabola between [-x,x] is given as cable_length\ny2_parabola <- function(a,x, cable_length=80, arc_method=c(\"analytic\",\"numeric\")) {\n\n##Arc-length of a parabola a*u^2 within interval [0,x]\nif(arc_method == \"numeric\") {\nf <- function(u) return( sqrt(1 + (2*a*u)^2))\nhalf_arclength <- integrate(f, lower=0, upper=x)$value } else if (arc_method==\"analytic\") { half_arclength <- 1\/(4*a)*(2*a*x*sqrt(4*a^2*x^2+1) + asinh(2*a*x)) } ##The equation: s = cable_length\/2 half_arclength - cable_length\/2 } ## The non-linear equation system \\bm{y}(\\theta) = \\bm{0}, where the LHS ## is given by a list with two components containing y_1(\\theta) and y_2(\\theta) f_sys <- function(theta, y, pole_height=50, above_ground=20, cable_length=80, ...) { ##Parameters a <- theta[1] x <- exp(theta[2]) ##ensure x is positive c(y[[1]](a,x, pole_height=pole_height, above_ground=above_ground), y[[2]](a,x, cable_length=cable_length, ...)) } ##Helper function to transform theta parameter vector to (a,x)' theta2ax <- function(theta) { c(a=theta[1], x=exp(theta[2])) } To ensure $$x>0$$ we re-parametrized the equations with $$\\theta_2 = \\log(x)$$ and provide the function theta2ax to backtransform the result. We can now use the nleqslv package to solve the non-linear equation system using a one-liner: y_parabola <- list(y1_parabola, y2_parabola) sol_parabola <- nleqslv(x=c(0.1,0.1),f_sys, y=y_parabola, arc_method=\"analytic\") theta2ax(sol_parabola$x)\n## a x\n## 0.05355207 23.66859605\n\nIn other words, for a cable of length 80m the pole of a suspension bridge will be located 23.7m from the origo, which means the two poles of the bridge will be 47.3m apart, which is also the span of the bridge.\n\nUsing arc_method=\"numeric\" instead of the analytic solution gives\n\n## a x\n## 0.05355207 23.66859605\n\nIt is re-assuring to see that the numerical integration method yields the same result as the analytic method. The analytic method has mathematical beauty, the numerical method allows the data scientist to solve the problem without diving into formula compendiums or geometry.\n\n### Catenary Shape\n\nUsing the same code, but with the y-functions formulated for the catenary case we obtain\n\n## Value of y=f(u) evaluated at u=x\ny1_catenary <- function(a,x, pole_height=50, above_ground=20) {\na * cosh(x\/a) - a - (pole_height- above_ground)\n}\n## Arc-length condition\ny2_catenary <- function(a,x, cable_length=80) {\na * sinh(x\/a) - cable_length\/2\n}\n\n## Solve equation system\ny_catenary <- list(y1_catenary, y2_catenary)\nsol_catenary <- nleqslv(x=c(0.1,0.1),f_sys, y=y_catenary, method=\"Newton\")\ntheta2ax(sol_catenary\\$x)\n## a x\n## 11.66667 22.70229\n\nIn other words the solution to the original cable problem is $$x=22.7 m$$ whereas the answer to the suspension bridge version is $$x=23.7m$$. The difference to the parabolic form can be seen from the following graph:\n\n## Testing the theory\n\nWe test our theory by studying the cable of the Golden Gate suspension bridge. Shown below is a photograph by D Ramey Logan available under a CC BY 4.0 license. For presentation in this post the image was tilted by -0.75 degrees (around the camera\u2019s view axis) with the imager package to make sea level approximately horizontal. Parabolic and catenary overlays (no real difference between the two) were done using the theory described above.\n\n##Preprocess image\nimg <- imager::imrotate(img, angle=-0.75, interpolation=1)\nimg <- imager::resize(img,-50,-50, interpolation_type=5)\n\nWe manually identify center, sea level and poles from the image and use annotation_raster to overlay the image on the ggplot of the corresponding parabola and catenary. See the code on github for details.\n\nThe fit is not perfect, which is due to the camera\u2019s direction not being orthogonal to the plane spanned by the bridge \u2013 for example the right pole appears to be closer to the camera than the left pole2. We scaled and \u2018offsetted\u2019 the image so the left pole is at distance 640m from origo, but did not correct for the tilting around the $$y$$-axis. Furthermore, distances are being distorted by the lens, which might explain the poles being too small. Rectification and perspective control of such images is a photogrammetric method beyond the scope of this post!\n\n## Discussion\n\nThis post may not to impress a Matlab coding engineer, but it shows how R has developed into a versatile tool going way beyond statistics: We used its optimization and image analysis capabilities. Furthermore, given an analytic form of $$y(\\theta)$$, R can symbolically determine the Jacobian and, hence, implement the required Newton-Raphson solving of the non-linear equation system directly \u2013 see the Appendix. In other words: R is also a full stack mathematical problem solving tool!\n\nAs a challenge to the interested reader: Can you write R code, for example using imager, which automatically identifies poles and cable in the image and based on the known specification of these parameters of the Golden Gate Bridge (pole height: 230m, span 1280m, clearance above sea level: 67.1m), and perform a rectification of the image? If yes, Stockholm University\u2019s Math Department hires for Ph.D. positions every April! The challenge could work well as pre-interview project. ?\n\n## Appendix \u2013 Newton-Raphson Algorithm\n\nBecause the y_1(a,x) and y_2(a,x) are both available in closed analytic form, one can form the Jacobian of non-linear equations system by combining the two gradients. This can be achieved symbolically using the deriv or Deriv::Deriv functions in R.\n\nGiven starting value $$\\theta$$ the iterative procedure to find the root of the non-linear equation system $$y(\\theta) = 0$$ is given by (Nocedal and Wright 2006, Sect. 11.1)\n\n$\\theta^{(k+1)} = \\theta^k \u2013 J(\\theta^k)^{-1} y(\\theta),$\n\nwhere $$J$$ is the Jacobian of the system, which in this case is a 2\u00d72 matrix.\n\ngradient_y1 <- Deriv::Deriv(y1_parabola, x=c(\"a\",\"x\"))\n\ny2_parabola_analytic <- function(a,x, cable_length=80) {\n1\/(4*a)*(2*a*x*sqrt(4*a^2*x^2+1) + asinh(2*a*x)) - cable_length\/2\n}\n\n##Jacobian\nJ <- function(theta, pole_height=50, above_ground=20, cable_length=80, ...) {\na <- theta[1]\nx <- exp(theta[2]) # x <- exp(theta[2])\n\n##Since we use x = exp(theta[2])=g(theta[2]) we need the chain rule to find the gradient in theta\n##this is g'(theta[2]) = exp(theta[2]) = x\n}\n\nBy iterating Newton-Raphson steps we can find the solution of the equation system manually:\n\n##Start values\ntheta <- c(0.1,log(10))\nthetanew <- c(0.1,log(20))\n##Log with the values\nlog <- t(theta2ax(theta))\n\n##Iterate Newton-Raphson steps until convergence\nwhile ( (sum(thetanew - theta)^2 \/ sum(theta^2)) > 1e-15) {\ntheta <- thetanew\n##Update step\nthetanew <- theta - solve(J(theta=theta)) %*% f_sys(theta, y=y_parabola, arc_method=\"analytic\")\nlog <- rbind(log, theta2ax(thetanew))\n}\n\n##Look at the steps taken\nlog\n## a x\n## [1,] 0.10000000 10.00000\n## [2,] 0.02667392 25.46647\n## [3,] 0.04632177 25.43589\n## [4,] 0.05270610 23.75416\n## [5,] 0.05354318 23.66953\n## [6,] 0.05355207 23.66860\n## [7,] 0.05355207 23.66860\n\nWe show the moves of the algorithm in a 2D contour plot for $$r(a,x) = \\sqrt{y_1(a,x)^2 + y_2(a,x)^2}$$. The solution to the system has $$r(a,x)=0$$. See the code on github for details.\n\n## Literature\n\nChatterjee, N., and B. G. Nita. 2010. \u201cThe Hanging Cable Problem for Practical Applications.\u201d Atlantic Electronic Journal of Mathematics 4 (1): 70\u201377. http:\/\/euclid.trentu.ca\/aejm\/V4N1\/Chatterjee.V4N1.pdf.\n\nNocedal, J., and S. J. Wright. 2006. Numerical Optimization. 2nd ed. Springer-Verlag.\n\nSpiegel, M. R. 1968. Mathematical Handbook of Formulas and Tables. Schaum\u2019s Outline Series. McGraw-Hill Book Company. https:\/\/ia800703.us.archive.org\/23\/items\/MathematicalHandbookOfFormulasAndTables\/Spiegel-MathematicalHandbook_text.pdf.\n\n1. As of 2018-07-23.\n\n2. A manual investigation using the \"Map | Map Object\" Filter in Gimp showed that the angle of tilting around the y-axis is about 20 degrees.\n\nR-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...","date":"2019-08-20 09:51:27","metadata":"{\"extraction_info\": {\"found_math\": true, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 0, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 2, \"mathjax_display_tex\": 1, \"mathjax_asciimath\": 1, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 0, \"wp-katex-eq\": 0, \"align\": 0, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.7231932878494263, \"perplexity\": 1747.3189086767043}, \"config\": {\"markdown_headings\": true, \"markdown_code\": true, \"boilerplate_config\": {\"ratio_threshold\": 0.18, \"absolute_threshold\": 10, \"end_threshold\": 15, \"enable\": true}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2019-35\/segments\/1566027315321.52\/warc\/CC-MAIN-20190820092326-20190820114326-00545.warc.gz\"}"}
| null | null |
The Mount Pleasant Inn is a family run traditional country themed restaurant of 29 years in the heart of the historic village of Repton in DerbyShire. The Mount Pleasant Inn is famous for its steaks, home cooked chips and its Sunday lunch carvery. It also has a extensive board menu that is updated regularly, so there is something for all the family.
The Mount Pleasant Inn is open every evening from 6:00pm and 6:30pm on a Sunday. The Sunday carvery is from 12:00am.
If you have any questions be sure to contact us by completing this form, if you want to book a table visit our booking page, do not use this to book a table. We check our emails regularly, so a reply should follow later that day. If you don't get a reply or want to speak to us be sure to phone us at 01283 701132. We love our customers, so feel free to visit during normal business hours.
Sign up to hear the latest news from us.
Copyright © 2019 Mount Pleasant Inn - All Rights Reserved.
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 5,601
|
Zainab Panjwani Memorial Hospital is a not for profit organisation serving the public since 1994. It operates under the umbrella of Panjwani Foundation which is registered with the Federal Bureau of Revenue, Pakistan Centre for Philanthropy, and Sindh Health Commission. In this website, you can find information about the services offered, details of consultants and specialists, and clinic schedules. Every effort is made to keep the information updated. We recommend to recheck the desired information on phone before visiting.
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 1,318
|
{"url":"https:\/\/eng.libretexts.org\/Under_Construction\/Book%3A_The_Joy_of_Cryptography_(Rosulek)\/2%3A_The_Basics_of_Provable_Security\/2.4%3A_Demonstrating_Insecurity_with_Attacks","text":"# 2.4: Demonstrating Insecurity with Attacks\n\nWe have seen an example of proving the security of a construction. To show that a construction is\u00a0insecure, we demonstrate an\u00a0attack. An attack means a counterexample to the definition of security. Since we define security in terms of two interchangeable libraries, an attack is a\u00a0distinguisher\u00a0(calling program) that behaves as differently as possible when linked to the two libraries.\n\nBelow is an example of an insecure construction:\n\n### Construction $$\\PageIndex{1}$$ :\n\nTo encrypt a plaintext\u00a0$$m$$, the scheme simply rearranges its bits according to the permutation\u00a0$$k$$.\n\n### Claim $$\\PageIndex{1}$$ :\n\nConstruction\u00a0$$\\PageIndex{1}$$ \u00a0does\u00a0not\u00a0have one-time secrecy.\n\n#### Proof:\n\nOur goal is to construct a program ? so that $$Pr[?\\diamondsuit \\mathscr{L}^{\\Sigma}_{ots-L}\\Rightarrow 1]$$ and $$Pr[?\\diamondsuit \\mathscr{L}^{\\Sigma}_{ots-R}\\Rightarrow 1]$$ are different, where $$Sigma$$\u00a0refers to\u00a0Construction\u00a0$$\\PageIndex{1}$$. There are probably many \u201creasons\u201d why this construction is insecure, each of which leads to a different distinguisher ?. We need only demonstrate one such ?, and it\u2019s generally a good habit to try to find one that makes the probabilities $$Pr[?\\diamondsuit \\mathscr{L}^{\\Sigma}_{ots-L}\\Rightarrow 1]$$ and $$Pr[?\\diamondsuit \\mathscr{L}^{\\Sigma}_{ots-R}\\Rightarrow 1]$$ as different as possible.\n\nOne immediate observation about the construction is that it only rearranges bits of the plaintext, without modifying them. In particular, encryption preserves (leaks) the number of 0s and 1s in the plaintext. By counting the number of 0s and 1s in the ciphertext, we know exactly how many 0s and 1s were in the plaintext. Let\u2019s try to leverage this observation to construct an actual distinguisher.\n\nAny distinguisher must use the interface of the $$\\mathscr{L}_{ots-}^{\\ast}$$\u00a0libraries; in other words, we should expect the distinguisher to call the QUERY subroutine with\u00a0some\u00a0choice of $$m_L$$\u00a0and $$m_R$$, and then do something based on the answer that it gets. If we are the ones writing the distinguisher, we must specify how these arguments\u00a0mL\u00a0and\u00a0mR\u00a0are chosen. Following the observation above, we can choose $$m_L$$\u00a0and $$m_R$$\u00a0to have a different number of 0s and 1s. An extreme example (and why not be extreme?) would be to choose $$m_L = 0^{\\lambda}$$\u00a0and $$m_R = 1^{\\lambda}$$. By looking at the ciphertext, we can determine which of $$m_L$$, $$m_R$$\u00a0was encrypted, and hence which of the two libraries we are currently linked with.\n\nPutting it all together, we define the following distinguisher:\n\n$\\mathscr{A}\\\\c\\space\\leftarrow\\space QUERY(0^{\\lambda},1^{\\lambda})\\\\\\text{return}\\space c\\stackrel{?}{=}0^{\\lambda}\\nonumber$\n\nHere is what it looks like when ? is linked to $$\\mathscr{L}^{\\Sigma}_{ots-L}$$\u00a0(we have filled in the details of\u00a0Construction\u00a0$$\\PageIndex{1}$$\u00a0in $$\\mathscr{L}^{\\Sigma}_{ots-L}$$):\n\nWe can see that $$m_L$$\u00a0takes on the value $$0^{\\lambda}$$, so each bit of $$m_L$$\u00a0is 0, and each bit of $$c$$\u00a0is 0.\u00a0Hence, the final output of ?\u00a0is 1 (true). We have:\n\n$Pr[? \\diamondsuit\\mathscr{L}^{\\Sigma}_{ots-L} \\Rightarrow 1] = 1.\\nonumber$\n\nHere is what it looks like when ? is linked to $$\\mathscr{L}^{\\Sigma}_{ots-R}$$:\n\nWe can see that each bit of $$m_R$$, and hence each bit of $$c$$, is 1. So ? will output 0 (false), giving:\n\n$Pr[? \\diamondsuit\\mathscr{L}^{\\Sigma}_{ots-R} \\Rightarrow 1] = 0.\\nonumber$\n\nThe two probabilities are different, demonstrating that ? behaves differently (in fact, as differently as possible) when linked to the two libraries. We conclude that\u00a0Construction\u00a0$$\\PageIndex{1}$$\u00a0does not satisfy the definition of one-time secrecy.","date":"2019-04-21 14:14:23","metadata":"{\"extraction_info\": {\"found_math\": true, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 0, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 1, \"mathjax_display_tex\": 1, \"mathjax_asciimath\": 0, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 0, \"wp-katex-eq\": 0, \"align\": 0, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.9340634942054749, \"perplexity\": 504.4801847325926}, \"config\": {\"markdown_headings\": true, \"markdown_code\": true, \"boilerplate_config\": {\"ratio_threshold\": 0.18, \"absolute_threshold\": 10, \"end_threshold\": 15, \"enable\": true}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2019-18\/segments\/1555578531984.10\/warc\/CC-MAIN-20190421140100-20190421162100-00537.warc.gz\"}"}
| null | null |
package name.onqi;
import org.hibernate.SessionFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;
/**
* @author onqi
*/
@Component
public class BranchDao {
@Autowired
private SessionFactory sessionFactory;
public int countBranches(Long companyId, Long unitId, Long userId, Long deviceId) {
return (Integer) sessionFactory.getCurrentSession().createQuery("SELECT count(*) from Company c").uniqueResult();
}
}
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 7,580
|
Q: golang urfave/cli run another binary with all args and flags I want to invoke other urfave/cli based CLIs, e.g., kubectl with myapp kubectl command. For that, I've a minimal project
.
├── go.mod
├── go.sum
├── main.go
└── pkg
└── cmds
└── kubectl.go
2 directories, 4 files
pkg/cmds/kubectl.go
package cmds
import (
"k8s.io/component-base/cli"
"k8s.io/kubectl/pkg/cmd"
"k8s.io/kubectl/pkg/cmd/util"
_ "k8s.io/client-go/plugin/pkg/client/auth"
)
func Kubectl() {
command := cmd.NewDefaultKubectlCommand()
if err := cli.RunNoErrOutput(command); err != nil {
util.CheckErr(err)
}
}
main.go
package main
import (
"fmt"
"log"
"os"
"strings"
"github.com/user/repo/pkg/cmds"
"github.com/urfave/cli/v2"
)
func main() {
app := &cli.App{
Commands: []*cli.Command{
{
Name: "kubectl",
Aliases: []string{"k"},
Usage: `Should run kubectl with all args and flags`,
Description: `go run . kubectl version
error: unknown command "kubectl" for "kubectl"
exit status 1`,
Action: func(cCtx *cli.Context) error {
strings.Join(cCtx.Args().Slice(), " ")
fmt.Println(strings.Join(cCtx.Args().Slice(), " "))
cmds.Kubectl()
return nil
},
},
{
Name: "get",
Aliases: []string{"v"},
Usage: "Executes `kubectl get` with all args and flags",
Description: `Apparently kubectl runs with root coomand context`,
Action: func(cCtx *cli.Context) error {
fmt.Println(strings.Join(cCtx.Args().Slice(), " "))
cmds.Kubectl()
return nil
},
},
},
}
if err := app.Run(os.Args); err != nil {
log.Fatal(err)
}
}
With this, I can now run go run . get ... and get expected kubectl get ... response. What I want is to run go run . kubectl get ... but this errors
error: unknown command "kubectl" for "kubectl"
exit status 1
How to run NewDefaultKubectlCommand() with kubectl command context (ie remove remove `kubectl from args slice)?
|
{
"redpajama_set_name": "RedPajamaStackExchange"
}
| 1,692
|
Proud to serve the areas of Atlanta, Marietta, Dunwoody. Call or email me today for a personalized insurance review.
Parminder Saini is insurance licensed in the state(s) of Georgia. If you do not reside in the state(s) of Georgia, please go to the Find an Agent section on allstate.com to search for another Allstate Agent or Personal Financial Representative.
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 8,222
|
Q: RichEditBox two-way binbing does not work [Windows Store App] I have RichEditBox and class with DependencyPropert:
public class RichTextC : DependencyObject
{
public static string GetRichText(DependencyObject obj)
{
return (string)obj.GetValue(RichTextProperty);
}
public static void SetRichText(DependencyObject obj, string value)
{
obj.SetValue(RichTextProperty, value);
}
public static readonly DependencyProperty RichTextProperty = DependencyProperty.Register("RichText", typeof(string), typeof(RichTextC), new PropertyMetadata(string.Empty, callback));
private static void callback(DependencyObject d, DependencyPropertyChangedEventArgs e)
{
var reb = (RichEditBox)d;
reb.Document.SetText(TextSetOptions.FormatRtf, (string)e.NewValue);
}
}
And this is my RichEditBox in XAML file:
<RichEditBox local:RichTextC.RichText="{Binding MyRichText, Mode=TwoWay}"/>
Problem is, that View can be notified by the View Model, but when I change text in RichEditBox it not notify View Model. I mean, binding working only in one way, from View Model to View, but from View to View Model does not work.
How can I change it to two-way binding start working?
A: You'll need to wire up code to set the RichText property when the RichEditBox's Document's Text changes. To do this handle the RichEditBox.TextChanged event to update the RichText property. You'll need to include some code to prevent the RichText property from updating the RichEditBox's Document's text when handling the TextChanged event (or vice versa) to prevent looping.
A: Because I cannot comment, I have to rewrite my answer! :-(
*
*Create a class and name it RichEditBoxExtended
*Replace the class code with the code from WinRt: Binding a RTF String to a RichEditBox (please recopy I changed the visibility of the class)
*Go to your XAML and enter:
<local:RichTextBoxExtended RtfText="{Binding MyRichText, Mode=TwoWay}"/>
I hope this helps...
|
{
"redpajama_set_name": "RedPajamaStackExchange"
}
| 2,882
|
Tim Robbins: Hillary Clinton's South Carolina Victory 'as Significant as Winning Guam'
Gregor Fischer/picture-alliance/dpa/AP Images
Daniel Nussbaum
Actor Tim Robbins introduced Democratic presidential contender Bernie Sanders at a rally in Green Bay, Wisconsin, on Monday, where he made an analogy that sought to belittle Hillary Clinton's primary victories in Southern states.
At the beginning of his brief speech, the 57-year-old Shawshank Redemption star said he had come to the rally in Green Bay to address Democrats "who feel Bernie in their hearts, but are supporting Hillary with their pragmatic brains."
The two Democratic presidential contenders are locked in a tight battle for delegates headed into Tuesday's critical Wisconsin primary.
"We've all been fed a steady stream of simplistic propaganda that furthers the establishment's narrative that Hillary's the presumptive nominee. And if we were sheep, if we had gotten in line, there'd be no problem now," he said.
https://www.youtube.com/watch?v=wNfZBm8j_SE
Later in his speech, Robbins sought to downplay Clinton's early primary successes in the South by accusing the media of blowing the significance of her victories out of proportion.
"After the Southern primaries, you had called the election — and who's fooling who?" Robbins said.
"Winning South Carolina in the Democratic primary is about as significant as winning Guam — no Democrat is going to win in South Carolina in the general election," he added.
Of course, based simply on population alone, South Carolina (population 4.8 million) cannot be reasonably compared with Guam (population approx. 165,000). As the Washington Post's Phillip Bump points out, Clinton's margin of victory in South Carolina (roughly 175,000 votes) is itself larger than the population of Guam.
But the argument that Robbins seemed to be making — that a Democrat primary victory in South Carolina means little in the course of the election or is statistically insignificant — could also be construed to carry an unfortunate racial component as well: that somehow, it isn't true that black Southern Democrats strongly prefer Clinton to Sanders, as Bump also notes.
Bump writes:
This is very tricky territory, of course, and I don't want to imply that the wish to dismiss Clinton's Southern victories is motivated by race. But there is often a sense that because Clinton dominated with black voters in the South that somehow makes those votes an anomaly. As though those victories somehow don't represent the Democratic party. Voters in South Carolina may not look much like the folks who came out to caucus in Washington, but their votes count. Those victories are significant because they were big wins in big states — neither of which applies to Guam.
The actor's comments also drew significant backlash on social media, with some users accusing him of belittling the importance of the state's African-American voters:
When black people vote in large numbers, white male privilege like @TimRobbins1 wants to dismiss us, probably want to erase us entirely!
— Mr. Weeks ✊ (@MrDane1982) April 4, 2016
Utah is the most conservative state in the country but I don't see Tim Robbins comparing Bernie's win there to a win in Guam.
— marv (@mrvndn) April 4, 2016
So lib Hollywood elite Sanders' supporter @TimRobbins1 has pissed off Guam, black S. Carolina voters AND sheep. #FeelTheBern !
— Michelle Malkin (@michellemalkin) April 4, 2016
Tim Robbins calling Clinton supporters "sheep" because they don't agree with him is the ultimate KETTLE BLACK. So stupid it burns.
— Sarah Reese Jones (@PoliticusSarah) April 4, 2016
In his speech, Robbins criticized both Clinton and the Democrat National Committee, both of whom have been equal targets for Sanders's more progressive celebrity supporters: "The DNC and the Clintons have a big problem: times have changed."
"Bernie is not the obligatory progressive that will keep the left in line until the presumptive moderate nominee emerges," the actor added. "Bernie is not the Democratic party insider that will bow down to the wishes of the elite of the party. We are done with that patriarchy."
Robbins is just the latest in a long line of celebrities who have introduced the Vermont Senator at campaign stops. On Saturday, Bon Iver frontman Justin Vernon introduced the candidate at another rally in Wisconsin, while actress Rosario Dawson and filmmaker Spike Lee did the same at a rally in the South Bronx last week.
Supermodel-actress Emily Ratajkowski and comedian-actress Sarah Silverman have also introduced Sanders at campaign rallies.
Recent polls in Wisconsin ahead of Tuesday's primary show the rival Democrat contenders battling to open up a lead in the state. RealClearPolitics's polling average over the last week has Sanders up a razor-thin 2.6 points over Clinton.
"The story tomorrow is pretty simple," Sanders said after taking over for Robbins at Monday's rally. "If there is a large voter turnout, I believe we win. If there is low voter turnout, we will probably lose. I think it will be a close election."
Follow Daniel Nussbaum on Twitter: @dznussbaum.
EntertainmentPoliticsBernie SandersBlack VotersDNCGuamRosario DawsonSouth CarolinaTim Robbins
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"redpajama_set_name": "RedPajamaCommonCrawl"
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\section{Introduction}
The transportation of neutrons by different types of guides and components has always been a subject of intense scientific activity \cite{MaierLeibnitz1963,Mildner2008,romain2016}, since the first nuclear fission reactor in the 1940s \cite{1982} to the recent projects \cite{Perrotta2014,Souza2020}, and spallation sources \cite{Garoby2018}. The theories describing the transportation of neutrons were divided into two groups, the deterministic methods that lead to approximations to solve the Boltzmann equation \cite{lamarsh1966introduction} and the stochastic approach, based on the Monte Carlo method \cite{Lewis1993}.
The MCNP (Monte Carlo N Particle) code was a milestone in this scenario, enabling a sophisticated description of reactor cores with different geometries, compositions and particle transport, including neutrons, photons and the neutron-photon channel \cite{Goorley2014}. In the early 1990s, Nielsen and Lefmann created an open access software (MCSTAS), with a friendly interface capable of describing the transport of neutrons through guides and other optical components, making it possible a stochastic simulation of neutron scattering instruments by different materials \cite{Lefmann1999}.
An S-shaped neutron guide has been an element of studies recently \cite{Heinemann2015,DeOliveira2021,deOliveira2020}. The S geometry was the solution found for installing a SANS instrument at the \textit{Forschungs-Neutronenquelle} Heinz Maier-Leibnitz Laboratory from Munich (FRM-II), which has received instruments from the decommissioning of FRJ-2 reactor. In this case, there were different beam hole heights from the level of the instrument's sample site in both reactors \cite{Gilles2006}. In addition to the relative height, the S-guide provided a cutoff in the neutron spectrum, what is impossible to occur in a curved guide only. This geometry, therefore, allows efficient cutting of fast (epithermal) neutrons to a cold (thermal) source, something undesirable for neutron guides and Helium 3 detectors. More recently, this type of guide has been studied and relations among the radius of curvature ($\rho$), the length ($L$), and the super mirrors ($m$) have also been found \cite{deOliveira2020}. The index $m$ that characterizes the super mirrors corresponds to the ratio between the critical angle of the guide material and the critical angle of neutron reflection on a Nickel-58 surface.
In this context, the use of S-shaped guides is based on allocating instruments to different and pre-existent neutron beam holes and tubes. After the decommissioning of the research reactors, we could see many examples of instrument transfer to different facilities, e.g., the installation of the reflectometer SPATZ from HZB BER-II in the OPAL \cite{lebrun2016}. Otherwise, guide systems are designed and optimized just to avoid epithermal neutrons and gamma rays and guarantee a fine neutron flux at the instrument entrance, by means of curved guides or neutron filters for instance. In these terms, an S-shaped guide, which consist of two curved guides connected in different senses, has to exclude the system's line-of-sight (LoS) and keep the same function of a single curved guide.
Many studies in the literature explore different combinations of straight and curved guides that exclude LoS, however, there is no proper approach that considers a guide system minimally excluding LoS \cite{Mildner2008,Mildner1990,Copley1993,Copley1995}. According to some authors, sometimes an extra curved guide length is necessary to guarantee unwanted neutrons and radiation \cite{Copley1993}, nevertheless, here we explore optimized scenarios. Therefore, straight-curved and curved-curved guide configurations to build the minimal S-shaped guide that excludes LoS have been investigated.
According to the literature, there is a minimum curved guide length that ensures every transported neutron touching the inner coat at least once. However, when complex guide systems using straight and curved guides are built, this minimum length is not obtained directly, and even though such geometry is simple, we consider that this approach is not well described in the correspondent bibliography.
Despite the fact that S-shaped guides are first and foremost a specific guide arrangement that provides horizontal or vertical displacement from the entrance and exit guide system, the wavelength cutoff process is the most intriguing property of such a guide \cite{DeOliveira2021,deOliveira2020,Gilles2006}. The appearance of the wavelength cutoff on final flux spectra is not found in any S-shaped model. Such a cutoff depends on curved guide characteristics, which are generally related to their length. However, as it may be seen in this paper, guide length is more important to guarantee available displacement of neutron delivery planes than to cutoff part of the energetic neutrons from the initial spectra.
Here, we have developed a study of an S-shaped guide based on curved guide arcs, which are directly bound to their characteristic angles. In addition, those guides employing LoS of whole systems have been structured to exclude epithermal neutrons and gamma rays with a minimum coating and guide walls.
There are some analyses of the so-called short guides in the literature that do not exclude LoS by their means, but with connections to other straight guides as well as curved ones \cite{Copley1995}. With this goal, we propose the construction of the shortest guide system that guarantees LoS exclusion and relates it to the wavelength cutoff. Notwithstanding, the S-shaped guide flux performance based on the super mirror coat was checked. It has also been developed a proper formalism to build these models based on geometry coming from curved-straight and curved-curved guides.
The formalism of the Acceptance Diagram (AD) and the guidelines for neutron transport by curved direction prescribe different arrangements of super mirror indexes, i.e., from the concave and convex inner surface, with the same neutron flux for a specific wavelength range \cite{Cook2009}. Here, it has been applied the same mechanism to the construction of S-shaped guides and to investigate the relation between wavelength cutoff and neutron transport efficiency guide.
The results of this study could be useful in facilities where instruments are allocated far from the neutron source, such as the European Spallation Source (ESS) \cite{Andersen2020}. According to Zendler and Bentley, a considerable part of the 22 designed instruments is between 75 and 100 m away from the source \cite{Zendler2016}. In this scenario, neutron guide systems, which are composed of many guide sections, might exhibit a transport efficiency decrease due to misaligning sections \cite{Zendler2016,Husgard2020}. In addition, it is expected that the ESS basement foundation may present a gradual sink with time, which could systematically misalign system guide axes. In this sense, large vertical deformations are foreseen with a potential to interfere even with the neutron guides of near-source instruments. Thus, our model analysis may be applied to guide systems present in Figure 4 of Husgard's work, for instance \cite{Husgard2020}. Besides, cold neutron transportation is positively affected by the wavelength cutoff of most energetic neutrons in small-angle neutron scattering, e.g., at LoKI instrument \cite{Andersen2020}.
\section{S-Shaped Guide}
\label{SSG}
The standard guide system that we have used to describe the S-shaped guide consists of four connected guide sections, where the primary and the last are straight and the second and third guides are curved and connected in the opposite sense. Thus, we classify guide variables with the letters $p$ and $s$ referring to primary and secondary, respectively, and with numbers $2$ and $3$ to refer to second and third guides, respectively.
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.5\textwidth]{S_GUIDE.png}
\caption{Side-view sketch of the S-shaped guide system. The arrangement is, sequentially, composed of a primary guide of length $L_P$, two curved guides connected in the opposite sense and with a length and curvature of $L_2$, $L_3$ and $\rho_2$, $\rho_3$, respectively, plus a secondary guide of length $L_S$. The S-shaped guide system provides a vertical (or horizontal) displacement of $Z$.}
\label{S_guide}
\end{figure}
Figure \ref{S_guide} contains the representation of an S-shaped guide system that we use as a basis of the present study. Here, variables $L_p$, $L_2$, $L_3$, and $L_s$ stand for individual guide section length, and $Z$ is the vertical (or horizontal) displacement between the entrance and exit of the guide system.
The construction of any curved guide that excludes LoS passes, necessarily, by definition of a characteristic angle, which consequently describes the characteristic length of such guide. This angle is given by
\begin{ceqn}
\begin{align}
\Psi_c=\sqrt{\frac{2W}{\rho}},
\label{characteristic_ange}
\end{align}
\end{ceqn}
where $W$\footnote[1]{Here, we analyze an S-shaped guide system that can be used to provide vertical as much as horizontal displacement. The variable $W$, which corresponds to the guide width, indicates the length dimension of the guide cross-section on the same plan of curvature. So, considering a vertical displacement would make us refer to this parameter as height, but for simplicity and literature tradition sake, we maintain just $W$.} and $\rho$ stand for guide width and curvature, respectively. It is worth noting that guide width is much smaller than its curvature in a way that the system can be analyzed bidimensionally and guide height is not important in this study.
In this scenario and according to Figure \ref{LoS}, a curved guide that possesses an arc of $2\Psi_c$ has a length $L_c$ and excludes LoS. Its length is written as
\begin{ceqn}
\begin{align}
L_c=2\Psi_c\rho=\sqrt{8W\rho}.
\label{characteristic_length}
\end{align}
\end{ceqn}
\begin{figure}[h]
\centering
\includegraphics[width=0.35\textwidth]{LoS.png}
\caption{A curved guide with a minimum length that allows for Line-of-Sight exclusion, sketched from the side. Guide length, curvature, and width are represented by variables $L$, $\rho$, and $W$, respectively. The arc of the curved guide that excludes Line-of-Sight is given by $2\Psi_C$, where the $\Psi_C$ represents the characteristic guide angle.}
\label{LoS}
\end{figure}
Since neutron guides were developed to carry neutrons away from the reactor face and allow more instrument installation, their inner coating is designed to reflect incident neutrons along their whole length. Critical angles are given by
\begin{ceqn}
\begin{align}
\theta_c=1.73\times 10^{-3}m\lambda,
\label{critic_angle}
\end{align}
\end{ceqn}
where any neutron of $\lambda$ with the wavelength and incident angle less than $\theta_c$ is reflected \cite{romain2016,Cook2009}.
From the definition of critical angle and according to the literature, we define a fundamental parameter that combines aspects of both the inner coating and geometry and its known characteristic wavelength \cite{romain2016,Cook2009}. This parameter, which is also a base for defining neutron flux efficiency in curved guides, is given by
\begin{ceqn}
\begin{align}
\lambda_c=\frac{1}{1.73\times 10^{-3}m}\sqrt{\frac{2W}{\rho}}
\label{characteristic_wavelength}
\end{align}
\end{ceqn}
According to the milestone work of Mildner \cite{Mildner1990}, there is a special formalism to study curved guides and to achieve AD equations. Such an approach depends on describing the neutron path utilizing two points of phase space, which are defined as the neutron radial position and inclination next to the tangential direction. These ordered pairs written as $(\Psi, z)$ and $(\Psi^{\prime},z^{\prime})$, are bound through Equation \ref{parabola_equation}\cite{Mildner1990}.
\begin{ceqn}
\begin{align}
\Psi^2-{\Psi^{\prime}}^{2}=\frac{{\Psi_c}^2}{W}\left(z-z^{\prime}\right).
\label{parabola_equation}
\end{align}
\end{ceqn}
The equation that represents the neutron trajectory, which stands for the LoS in Figure \ref{LoS}, may be achieved by substituting $(\Psi^\prime, z^\prime)$ for $(\Psi_c, W/2)$ or $(0, -W/2)$. Such equation, which has also been developed by Mildner \cite{Mildner1990}, is given by
\begin{ceqn}
\begin{align}
{\Psi^{2}}=\frac{{\Psi_c}^2}{W}\left(z+\frac{W}{2}\right).
\label{LoS_main_eq}
\end{align}
\end{ceqn}
By using Equation \ref{LoS_main_eq}, different expressions that guarantee the LoS exclusion for straight-curved and curved-curved (S-shaped) guide connections have been derived. In the former case, two scenarios that allow avoiding LoS were observed. They depend on the curved section arc, where angle values may be larger or smaller than the characteristic angle. It is worthwhile noting that arcs with the same value of characteristic angle require an infinite straight guide to exclude LoS.
Straight-curved guide systems with arcs larger than $\Psi_{c2}$ are described in Figure \ref{LoS_CR_STR}, while systems with shorter arcs are presented in Figure \ref{LoS_CR_STR_2}. Variables $L_{crv}$ and $L_{str}$ represent, respectively, the length of straight and curved guide sections.
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.4\textwidth]{LoS__CR__STR.png}
\caption{Side-view sketch of a curved-straight guide system connection that excludes Line-of-Sight. The straight guide, according to Figure \ref{LoS}, is attached to the right part of the curved guide, farther from the left edge. Here, the curved guide possesses an arc larger than $\Psi_C$, written as $\Psi_C+\varphi^{\prime\prime}$. Variables $\rho$ and $L_{crv}$ stand for curved guides curvature and length, respectively, $L_{str}$ stands for straight guide length, $W$ represents both guide widths and $\Psi_C$, the characteristic angle of the curved guide. The coordinate point $(\varphi^{\prime\prime},z)$ is a space-phase representation of the Acceptance Diagram formalism.}
\label{LoS_CR_STR}
\end{figure}
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.35\textwidth]{LoS__CR__STR__2.png}
\caption{Side-view sketch of a curved-straight guide system connection that excludes Line-of-Sight. The straight guide, according to Figure \ref{LoS}, is attached to the left part of the curved guide, closer to the left edge. Here, the curved guide possesses an arc smaller than $\Psi_C$, written as $\Psi_C-\varphi^{\prime}$. Variables $\rho$ and $L_{crv}$ stand for curved guides curvature and length, respectively, $L_{str}$ stands for straight guide length, $W$ represents both guide widths and $\Psi_C$, the characteristic angle of the curved guide. The coordinate point $(\varphi^{\prime},z)$ is a space-phase representation of Acceptance Diagram formalism.}
\label{LoS_CR_STR_2}
\end{figure}
On the other hand, angles $\varphi^\prime$ and $\varphi^{\prime\prime}$ stand for main variables which describe both scenarios. Such parameters were obtained from the combination of Equation \ref{LoS_main_eq} and tangent equations derived from virtual triangles, shown in Figures \ref{LoS_CR_STR} and \ref{LoS_CR_STR_2}. Both triangles are formed by vertices given by points $(\varphi^{\prime}, z)$ and $(\varphi^{\prime}, z)$, which also compose opposite catheti in the guide radial direction, and the hypotenuses that are segments of neutron trajectories.
Since $\rho>>W$ one can approximate triangle tangents $\tan{\varphi^{\prime}}$ and $\tan{\varphi^{\prime}}$ to $\varphi^{\prime}$ and $\varphi^{\prime}$, which allows us to write the correspondent tangent equations as
\begin{ceqn}
\begin{align}
\varphi^{\prime(\prime\prime)}=\frac{\frac{W}{2} \pm z}{L_{str}},
\label{tan_varphi_eq}
\end{align}
\end{ceqn}
where the single prime ($^{\prime}$) angle stands for the plus ($+$) sign and the double prime angle ($^{\prime\prime}$) for the minus sign ($-$). In these terms, we substitute $(\Psi, z)$ by $( \varphi^{\prime}, z)$ and $( \varphi^{\prime\prime}, z)$ in Equation \ref{LoS_main_eq} and combine results, respectively, to Equation \ref{tan_varphi_eq} variants to eliminate the $z$ variable. After doing this process, we obtain Equations \ref{varphi_line} and \ref{varphi_lineline}, which are given by
\begin{ceqn}
\begin{align}
\varphi^{\prime}=\frac{2L_{str}}{\rho},
\label{varphi_line}
\end{align}
\end{ceqn}
\begin{ceqn}
\begin{align}
\varphi^{\prime\prime}=\sqrt{{\Psi_c}^2+\frac{L_{str}^2}{\rho^2}}-\frac{L_{str}}{\rho}.
\label{varphi_lineline}
\end{align}
\end{ceqn}
From these two angles, i.e., $\varphi^{\prime}$ and $\varphi^{\prime\prime}$, we can define curved guide arcs, which are preceded or followed by a straight guide and preserve LoS exclusion. Once S-shaped guide edges are characterized, how the curved-curved guide connection affects those arc angles can be analyzed.
In Figure \ref{LoS_CR_CR}, we observe a sketch that represents an S-shaped guide curved connection. In this scenario, there is a mutual angle $\varphi$ that represents the same rotation on curved guides and, consequently, the inclination of neutron trajectory next to both guides reference system. According to geometry, such an angle composes both the angular parts of the ordered pair shown in Figure \ref{LoS_CR_CR}. Here this point, which represents a single point on each curved guide reference, is given as $ (\varphi, z_{2})$ for the first curved guide and $(\varphi, z_{3})$ for the second one.
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.4\textwidth]{LoS_CR_CR_2.png}
\caption{Side-view sketch of a curved-curved guide system connection in the opposite sense and that excludes Line-of-Sight. The curvatures and lengths of curved guides are given by $\rho_1$ and $\rho_2$, and $L_{str1}$ and $L_{str2}$, respectively and sequentially from left to right. Characteristic angles $\Psi_{C1}$ and $\Psi_{C2}$, and coordinates points $(\varphi,z_1)$ and $(\varphi,z_2)$ of Acceptance Diagram formalism, also, correspond sequentially to each curved guide as much as arcs that are written as $\Psi_{C1}+\varphi$ and $\Psi_{C2}+\varphi$. The angle $\varphi$ represents a rotation of curved guides that make their trajectories, as presented in Figure \ref{LoS}, coincide.}
\label{LoS_CR_CR}
\end{figure}
By substituting two points on Equation \ref{LoS_main_eq}, we obtain a pair of equations, namely Equations \ref{varphi_2} and \ref{varphi_3}, representing neutron trajectory according to two curved guides.
\begin{ceqn}
\begin{align}
\varphi^{2}=\frac{{\Psi_{c2}}^2}{W}\left(z_2+\frac{W}{2}\right)
\label{varphi_2}
\end{align}
\end{ceqn}
\begin{ceqn}
\begin{align}
\varphi^{2}=\frac{{\Psi_{c3}}^2}{W}\left(z_3+\frac{W}{2}\right)
\label{varphi_3}
\end{align}
\end{ceqn}
Notwithstanding, and aiming to define the $\varphi$ equation, we are able to correlate variables $z_2$ and $z_3$ by noticing that these values on the interface between guides may be written as $z_2=-z_3$. By means of this relation, Equations \ref{varphi_2} and \ref{varphi_3} can be combined and $\varphi$ then derived, which is given by
\begin{ceqn}
\begin{align}
\varphi=\sqrt{\frac{2W}{\rho_2+\rho_3}}.
\label{varphi}
\end{align}
\end{ceqn}
After defining angles $ \varphi$, $\varphi^{\prime}$ and $\varphi^{\prime\prime}$, described by Equations \ref{varphi}, \ref{varphi_line} and \ref{varphi_lineline} respectively, we can characterize the entire S-shaped guide system that guarantees LoS exclusion. This complete system is shown in Figure \ref{LoS_STR_CR_CR_STR} with their correspondent angles addressed on Equations \ref{varphi_p_line} and \ref{varphi_s_line}.
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.4\textwidth]{LoS_STR_CR_CR_STR.png}
\caption{Side-view sketch of the S-shaped guide system. The arrangement is sequentially composed of a primary guide of length $L_P$, two curved guides connected in the opposite sense and with a length and curvature of $L_2$, $L_3$ and $\rho_2$, $\rho_3$, respectively, and a secondary guide of length $L_S$. The arcs of curved guides are given sequentially by $\varphi+\varphi_{P}^{\prime\prime}$ and $\varphi+\varphi_{S}^{\prime\prime}$. The variable $W$ stands for guide system width.}
\label{LoS_STR_CR_CR_STR}
\end{figure}
It is worth noting that Figure \ref{LoS_STR_CR_CR_STR} is just one of the configurations that exclude LoS. Other scenarios can be obtained by using straight-curved guide combinations of Figure \ref{LoS_CR_STR_2} at one of the S-shaped guide edges. Despite all cases have been investigated, just the ``classical'' S-shaped guide sketch has been presented to simplify. Here we investigate if all these configurations may be called a proper S-shaped guide, i.e., if they impose wavelength cutoff on the transported neutron profile.
\begin{ceqn}
\begin{align}
\varphi_p^{\prime}=\frac{2L_p}{\rho_2}, \quad \varphi_p^{\prime\prime}=\sqrt{{\Psi_{c2}}^2+\frac{L_1^2}{\rho_2^2}}-\frac{L_1}{\rho_2},
\label{varphi_p_line}
\end{align}
\end{ceqn}
\begin{ceqn}
\begin{align}
\varphi_s^{\prime}=\frac{2L_s}{\rho_3}, \quad \varphi_s^{\prime\prime}=\sqrt{{\Psi_{c3}}^2+\frac{L_4^2}{\rho_3^2}}-\frac{L_4}{\rho_3}.
\label{varphi_s_line}
\end{align}
\end{ceqn}
On the basis of these equations, the three scenarios of S-shaped guides according to their curved guide arcs may be defined, where $\gamma_2$ and $\gamma_3$ stand, respectively, at their values. So, the curved guide system is described by
\textbf{
\begin{enumerate}[a.]
\item\label{a} $\gamma_2=\varphi-\varphi_p^{\prime},\quad \gamma_3=\varphi + \varphi_s^{\prime\prime}$
\item\label{b} $ \gamma_2=\varphi + \varphi_p^{\prime\prime},\quad \gamma_3=\varphi- \varphi_s^{\prime}$
\item\label{c} $ \gamma_2=\varphi + \varphi_p^{\prime\prime},\quad \gamma_3 =\varphi + \varphi_s^{\prime\prime}$
\end{enumerate}}
From now on, by this letter classification for identifying simulation cases, where case \textbf{c.} corresponds to, as already mentioned, the ``classical'' S-shaped guide of Figure \ref{LoS_STR_CR_CR_STR}.
Maybe the unique characteristic of an S-shaped guide corresponds to the wavelength cutoff that its geometry imposes on neutron flux spectra. According to AD formalism, there is a theoretical cutoff value, which is proportional to the characteristic wavelength, written as $\frac{\lambda_c}{\sqrt{2}}$ and geometrically indicates a cutoff angle of $\frac{\Psi_c}{\sqrt{2}}$ \cite{Mildner1990,deOliveira2020}. Such a result is coherent with Equation \ref{varphi} when both curved guides possess the same curvature, i.e., when $\rho_2=\rho_3=\rho$ we get $\varphi = \sqrt{\frac{W}{\rho}}=\frac{\Psi_c}{\sqrt{2}}$. Under these conditions, one can write the wavelength cutoff of a ``classical'' S-shaped guide (configuration \textbf{c.}) as
\begin{ceqn}
\begin{align}
\lambda_{cut}=\frac{1}{1.73\times 10^{-3}m}\varphi.
\label{lambda_cut}
\end{align}
\end{ceqn}
Checking the validity of such an expression is one of the scopes present in this work, as much as verifying the conditions of the wavelength cutoff for configurations \textbf{a.} and \textbf{b.}. Another important point to verify is the relation between the wavelength cutoff and the super mirror coating indexes m. In other words, we intend to verify if the same formalism of curved guide inner indexes may be assumed for the S-shaped guides. There is, in the literature, a well-established process dictating that different concave and convex surface mirror indexes allow us, depending on their values, to maintain the same neutron flux in cases of equal indexes \cite{Cook2009}.
Here we define a variable $m_{out}$ as being concave index and variable $m_{in}$ as the convex index surface. The basis of estimating neutron transport by a curved guide is, according to the literature, the characteristic wavelength \cite{romain2016,deOliveira2020,Cook2009}, which is written as
\begin{ceqn}
\begin{align}
\lambda_{c}=\frac{1}{1.73\times 10^{-3}m_{out}}\Psi_c.
\label{lambda_c}
\end{align}
\end{ceqn}
This variable, which represents a hybrid combination of guide geometry and inner coat index values, imposes that the neutrons with lower and higher wavelength values be transmitted by curved guides with efficiencies lower and higher than $66.67$~$\%$. Such information comes from AD formalism and neutron reflection regimes, which can be Garland and Zigzag. The former regime corresponds to neutron reflections only on the concave surface, the latter, on the other hand, indicates neutron reflection on both surfaces. Garland regime represents a neutron transport with efficiency less than $66.67$~$\%$ \cite{romain2016,Mildner1990,Copley1993}.
According to the literature, a super mirror index relation of $m_{out}<m_{in}$ guarantees a wavelength gap, where neutron transport is the same as a guide with $m_{out}=m_{in}$ \cite{Cook2009}. Such range is given by neutrons with wavelength $\lambda$ that satisfy the relation $\lambda_c<\lambda<\lambda^{\prime}$, where the upper variable value is written as
\begin{ceqn}
\begin{align}
\lambda^{\prime}=\frac{m_{out}}{\sqrt{m_{out}^2-m_{in}^2}}\lambda_c.
\label{lambda_prime}
\end{align}
\end{ceqn}
In these terms, we propose an investigation of different index coats next to the wavelength cutoff and the neutron transport efficiency according to three typical reactor sources, i.e., cold, thermal, and hot sources \cite{sourcegen}. The use of convex indexes with lower values other than concave, allows savings on system guide building and it, also, guarantees the tailoring process phase, which provides a homogeneous neutron distribution of overall guide divergences \cite{Mildner2008}.
Here, there is an important detail that it has to be taken into account. Equation \ref{varphi}, and consequently Equation \ref{lambda_cut}, are deduced by considering that all surface coats possess the same index values. Therefore, we would not be able to investigate cases where curved guides of the S-shaped guide system have different index values. We propose a solution based on the $\lambda_c$ central role in neutron transportation efficiency. Since $\lambda_c$ settles the efficiency value of $66.67$~$\%$, it is possible to keep both guide concave indexes with the same value and compensate the characteristic wavelength value by changing the curvature value. Of course, this change is purely virtual, but with it, we are still able to use Equations \ref{varphi} and \ref{lambda_cut} to estimate the wavelength cutoff. Therefore, to keep $\lambda_c$ value it is necessary to follow the relation $\rho m^2=\rho^* m^{*2}$, which can be rewritten into
\begin{ceqn}
\begin{align}
\rho_{i}^{*}=\frac{m_{out,i}^2}{m_{out,i}^{* 2}}\rho_{i},
\end{align}
\end{ceqn}
for $i=2$ or $i=3$ and where the symbol $^{*}$ stands for new variable values. Here we emphasize that this change has to be applied just on one of the curved guides to make both $m_{out}$ values equal, i.e., $m_{out2}=m_{out3}^{*}$ for keeping $m_{out2}$ and $m_{out2}^{*}=m_{out3}$ for a constant $m_{out3}$ value. Therefore, a rewritten version of Equation \ref{varphi}, corresponding to the former case, could be given by
\begin{ceqn}
\begin{align}
\varphi^{*}=\sqrt{\frac{2W}{\rho_{2}+\rho_{3}^{*}}},
\label{new_varphi}
\end{align}
\end{ceqn}
where $ \varphi^{*}$ represents the new value of $\varphi$, giving rise to a new wavelength cutoff expression, described as
\begin{ceqn}
\begin{align}
\lambda_{cut}^{*}=\frac{1}{1.73\times 10^{-3}m}\varphi^{*},
\label{new_lambda_cut}
\end{align}
\end{ceqn}
where $m=m_{out2}=m_{out3}^{*}$.
The last important point to be mentioned is the vertical (or horizontal) displacement that S-shaped guides provide. According to de Oliveira \cite{deOliveira2020}, we observe that the system present in Figure \ref{LoS_STR_CR_CR_STR} possess a $Z$ displacement given by
\begin{ceqn}
\begin{align}
Z=\rho_2\left[1-\cos \left(\frac{L_2}{\rho_2}\right)\right]+\rho_3\left[1-\cos \left(\frac{L_3}{\rho_3}\right)\right]
\label{Z}
\end{align}
\end{ceqn}
Since one of our goals is based on studying S-shaped guide wavelength cutoff properties, we have to compare scenarios of curved guides with different lengths next to cases with $\gamma_2=2\Psi_2$ and $\gamma_3=2\Psi_3$. As previously seen in Figure \ref{LoS_STR_CR_CR_STR}, minimal scenarios that exclude LoS have necessarily lower arc values than $2\Psi_2$ and $2\Psi_3$. By considering this fact, we observe that cases with $\gamma_2<2\Psi_2$ and $\gamma_3<2\Psi_3$, according to Equation \ref{Z} may never have displacements $Z$ higher than $8W$, obtained by substituting $L_2 = \sqrt{8W\rho_2}$ and $L_3 = \sqrt{8W\rho_3}$ on Equations \ref{Z} and assuming that $L_2<<\rho_2$ and $L_3<<\rho_3$.
Considering the curved guide arcs of the S-shaped guide system crucial for investigating its properties, we define the variable R that represents the ratio of the angular arc of both curved guides by two times their corresponding characteristic angle, in agreement with the minimal arc that individually excludes LoS. Such a ratio is given by
\begin{ceqn}
\begin{align}
R_{2/3} = \frac{\gamma_i}{2\Psi_{c2/3}},
\label{R_2_3}
\end{align}
\end{ceqn}
where the lower indexes 2 and 3 stand, respectively, for the first and second curved guide of the system. In Figure \ref{LoS_STR_CR_CR_STR} it is possible to observe that curved guide arcs are important for defining primary and secondary guide lengths, while the minimum LoS criterion is kept. According to the literature, the length of a straight guide located after a curved one is important to keep neutron flux, homogeneously, distributed at the end of the guide system \cite{deOliveira2020}.
In addition, the length of all guides is also important to define an S-shaped guide system project, since available space in nuclear facilities may be a crucial task. In this scenario, Equations \ref{varphi} and \ref{R_2_3} are used to write a straight guide length in terms of other variables. This expression, which is defined according to configuration \textbf{c.}, is written as
\begin{ceqn}
\begin{align}
L_{p/s} = \frac{\rho_{2/3}}{2}\left[\frac{\Psi^2_{c2/3}-\left(2\Psi_{c2/3}R_{2/3}-\varphi\right)^2}{\left(2\Psi_{c2/3}R_{2/3}-\varphi\right)}\right]
\label{L_P_S}
\end{align}
\end{ceqn}
As we can see in Equation \ref{L_P_S}, there is a singularity imposed by the divisor that is composed of two classes of variables, individual guide curvatures $\rho_2$ and $\rho_3$, from characteristic angle $\Psi_{C2/3}$, and mutual curved guide curvature from parameter $\varphi$. When both curvatures are different, the singularity occurs for $R_{2/3}=\frac{1}{2}\sqrt{\frac{\rho_{2/3}}{\rho_2+\rho_3}}$, otherwise for $\rho_2=\rho_3$ we have a fix singularity at ratio $R_{2/3}=35.35$~$\%$.
\section{MCSTAS Simulations}
\label{MS}
In this section, we present relevant information on MCSTAS simulations performed. We intend to investigate three different aspects of the proposed S-shaped guide system, and each case has a corresponding series of simulations.
The very first sequence of simulations is carried out to check the LoS aspects of the wavelength cutoff properties. Here, configurations \textbf{a.}, \textbf{b.}, and \textbf{c.} are tested. The second sequence of simulations consists of exploring Equation \ref{L_P_S} primary and secondary straight guide lengths, intended to define a minimal arc value that guarantees a wavelength cutoff. The third series of simulations consists of exploring configuration \textbf{c.} in scenarios of different concave and convex surface indexes ($m_{out}>m_{in}$). Simulations are performed by taking two cases from the first sequence as the basis. Considering these results, we intend to validate Equation \ref{new_lambda_cut}, which applies a sort of reset on m indexes by equalizing their values through geometrical changing parameters. In addition, and according to these results, we aim at compact S-shaped guides with lower cost, similar properties, and compatible neutron transportation efficiency (similar to the simple curved guide design formalism) \cite{Cook2009}.
Simulations are carried out through MCSTAS 3.0 software and neutron sources are defined using the tool \verb|Source_gen()|, which allows us to mimic different wavelength neutron distributions based on Maxwellian distributions. For simulations, we have picked Maxwellian parameters that correspond to three types of \textit{Institut Laue-Langevin} - ILL sources. Such sources correspond to cold, thermal, and hot neutron wavelength specter profiles \cite{sourcegen}. We use them to test S-shaped guides applicability to different scenarios according to their performance in neutron transportation. The wavelength profiles of three ILL sources are presented in Figure \ref{SOURCE}.
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.7\textwidth]{SOURCE.png}
\caption{Virtual source profiles of the ILL sources from the MCSTAS instrument component. Red, yellow and blue curves stand for ILL hot, thermal, and cold sources, respectively.}
\label{SOURCE}
\end{figure}
Simulation cases depend on geometrical and coating surface parameters. The former is composed of straight guide lengths, $L_{P}$ and $L_{S}$ and curved guide curvatures, $\rho_2$ and $\rho_3$. Here, width and height guides are fixed every $5$~$cm$. On the other hand, coating variables are given by $m_1$ and $m_4$ as indexes of all primary and secondary straight guide surfaces, respectively, $m_{out2}$ and $m_{out3}$ as concave curved guide surfaces, and $m_{in2}$ and $m_{in3}$ correspond to convex curved guide surfaces. In addition, we standardized that lateral curved guide surfaces possess the same mirror index as their concave surfaces, i.e., $m_{out2}$ for the first curved guide and $m_{out3}$ for the second one.
We define simulation cases with different coating indexes by following the relation,
\begin{ceqn}
\begin{align}
m_{1}\geq m_{out2}\geq m_{out3}\geq m_{in2}\geq m_{in3}\geq m_{4},
\label{escala_m}
\end{align}
\end{ceqn}
which guarantees that higher indexes be always located nearer to the source than to the system exit. In addition, this relation provides a phase space tailoring process at the end of the S-shaped guide system. This procedure dictates that $m_{in3}$ should be equal to $m_4$ in order to provide a uniform divergence of neutron distribution at the instrument entrance.
The first series of simulations is composed of multiple cases described in Table \ref{tbl1}. They are made up of twelve cases with different variable combination values $L_{p}$, $L_{s}$, $\rho_{2}$, and $\rho_{3}$, where each one of them is subdivided into configuration \textbf{a.}, \textbf{b.} and \textbf{c.}. We address Roman numbers (\textbf{I} - \textbf{XII}) to identify cases and letters $^{a}$, $^{b}$, and $^{c}$ to specify, respectively, their subcases.
In addition, there are values of curved guide lengths in Table \ref{tbl1}, which are obtained by simply multiplying curved guide arcs by their curvature, i.e., $L_i=\rho_{i}\gamma_{i}$ for $i=2$ or $i=3$.
\begin{table}[hbt!]
\caption{Configurations of the first sequence of simulations. Twelve cases, namely \textbf{I} to \textbf{XII}, are subdivided into three other cases, namely \textbf{a.}, \textbf{b.}, and \textbf{c.}. The main divisions stand for geometrical parameter values, guide curvatures, and lengths, while subdivisions represent geometrical guide disposal.}\label{tbl1}
\begin{tabular*}{\tblwidth}{@{} LLLLLLL@{} }
\toprule
\textbf{Case} & \textbf{$L_p (m)$} & \textbf{$\rho_2 (m)$} & \textbf{$L_2 (m)$} & \textbf{$\rho_3 (m)$} & \textbf{$L_3 (m)$} & \textbf{$L_s (m)$} \\
\midrule
\textbf{I$^a$} & \multirow{3}{*}{1.00} & \multirow{3}{*}{4000.00} & 33.17 & \multirow{3}{*}{4000.00} & 12.14 & \multirow{3}{*}{1.00} \\
\textbf{I$^b$} & & & 12.14 & & 33.17 & \\
\textbf{I$^c$} & & & 33.17 & & 33.17 & \\
\textbf{II$^a$} & \multirow{3}{*}{1.00} & \multirow{3}{*}{4000.00} & 35.35 & \multirow{3}{*}{2000.00} & 6.16 & \multirow{3}{*}{1.00} \\
\textbf{II$^b$} & & & 14.33 & & 21.34 & \\
\textbf{II$^c$} & & & 35.35 & & 21.34 & \\
\textbf{III$^a$} & \multirow{3}{*}{1.00} & \multirow{3}{*}{4000.00} & 36.91 & \multirow{3}{*}{1000.00} & 2.47 & \multirow{3}{*}{1.00} \\
\textbf{III$^b$} & & & 15.89 & & 13.52 & \\
\textbf{III$^c$} & & & 36.91 & & 13.52 & \\
\textbf{IV$^a$} & \multirow{3}{*}{1.00} & \multirow{3}{*}{2000.00} & 23.18 & \multirow{3}{*}{2000.00} & 8.00 & \multirow{3}{*}{1.00} \\
\textbf{IV$^b$} & & & 8.00 & & 23.18 & \\
\textbf{IV$^c$} & & & 23.18 & & 23.18 & \\
\textbf{V$^a$} & \multirow{3}{*}{1.00} & \multirow{3}{*}{2000.00} & 24.72 & \multirow{3}{*}{1000.00} & 3.77 & \multirow{3}{*}{1.00} \\
\textbf{V$^b$} & & & 9.55 & & 14.82 & \\
\textbf{V$^c$} & & & 24.72 & & 14.82 & \\
\textbf{VI$^a$} & \multirow{3}{*}{1.00} & \multirow{3}{*}{1000.00} & 16.12 & \multirow{3}{*}{1000.00} & 5.07 & \multirow{3}{*}{1.00} \\
\textbf{VI$^b$} & & & 5.07 & & 16.12 & \\
\textbf{VI$^c$} & & & 16.12 & & 16.12 & \\
\textbf{VII$^a$} & \multirow{3}{*}{3.00} & \multirow{3}{*}{4000.00} & 31.37 & \multirow{3}{*}{4000.00} & 10.14 & \multirow{3}{*}{2.00} \\
\textbf{VII$^b$} & & & 8.14 & & 32.24 & \\
\textbf{VII$^c$} & & & 31.37 & & 32.24 & \\
\textbf{VIII$^a$} & \multirow{3}{*}{3.00} & \multirow{3}{*}{4000.00} & 33.55 & \multirow{3}{*}{2000.00} & 4.16 & \multirow{3}{*}{2.00} \\
\textbf{VIII$^b$} & & & 10.33 & & 20.45 & \\
\textbf{VIII$^c$} & & & 33.55 & & 20.45 & \\
\textbf{IX$^a$} & \multirow{3}{*}{3.00} & \multirow{3}{*}{4000.00} & 35.11 & \multirow{3}{*}{1000.00} & 0.47 & \multirow{3}{*}{2.00} \\
\textbf{IX$^b$} & & & 11.89 & & 12.67 & \\
\textbf{IX$^c$} & & & 35.11 & & 12.67 & \\
\textbf{X$^a$} & \multirow{3}{*}{3.00} & \multirow{3}{*}{2000.00} & 21.46 & \multirow{3}{*}{2000.00} & 6.00 & \multirow{3}{*}{2.00} \\
\textbf{X$^b$} & & & 4.00 & & 22.28 & \\
\textbf{X$^c$} & & & 21.46 & & 22.28 & \\
\textbf{XI$^a$} & \multirow{3}{*}{3.00} & \multirow{3}{*}{2000.00} & 23.00 & \multirow{3}{*}{1000.00} & 1.77 & \multirow{3}{*}{2.00} \\
\textbf{XI$^b$} & & & 5.55 & & 13.97 & \\
\textbf{XI$^c$} & & & 23.00 & & 13.97 & \\
\textbf{XII$^a$} & \multirow{3}{*}{3.00} & \multirow{3}{*}{1000.00} & 14.51 & \multirow{3}{*}{1000.00} & 3.07 & \multirow{3}{*}{2.00} \\
\textbf{XII$^b$} & & & 1.07 & & 15.27 & \\
\textbf{XII$^c$} & & & 14.51 & & 15.27 & \\
\bottomrule
\end{tabular*}
\vspace{-0.4cm}
\begin{flushleft}
{\footnotesize{$^a$ $\gamma_2=\varphi+\varphi_{p}^{\prime\prime}$, $\gamma_3=\varphi-\varphi_{s}^{\prime}$}}\\
{\footnotesize{$^b$ $\gamma_2=\varphi-\varphi_{p}^{\prime}$, $\gamma_3=\varphi+\varphi_{s}^{\prime\prime}$}}\\
{\footnotesize{$^c$ $\gamma_2=\varphi+\varphi_{p}^{\prime\prime}$, $\gamma_3=\varphi+\varphi_{s}^{\prime\prime}$}}
\end{flushleft}
\end{table}
Cases of Table \ref{tbl1} are carried out and results are disposed of Table \ref{VACA} and compacted on the graphic of Figure \ref{R_CUTOFF}. We note here that most of the good agreement between the theoretical and simulated cutoff corresponds predominantly to configuration \textbf{c.} Such behavior is due to configurations \textbf{a.} and \textbf{b.} principles that always impose shorter arcs than the other one. The second set of simulations explores precisely this aspect because primary and secondary straight guide length variation force curved guide arc variations. Based on these results, we intend to determine minimal arc values that guarantee a wavelength cutoff according to the theoretical value. Further information on these results is presented in Section \ref{RAD}.
We investigate arc properties by picking S-shaped guide systems with equal curvature values, namely $\rho=2000$~$m$ and $\rho = 1000$~$m$. In these scenarios, we simulate arc ratios of different values, by varying from $40$~$\%$ to $80$~$\%$ in a $2$~$\%$ step sequence. These twenty-one proposed cases of simulation, whose values are based on Equation \ref{L_P_S}, are shown in Table \ref{table_L_P_L_S}.
\begin{table}[hbt!]
\caption{Configurations of the second sequence of simulations. Twenty-one cases present correspondent values of arc ratios $R_{2}$ and $R_{3}$, and straight primary and secondary guides, respectively. Simulation ratio values range from $40$~$\%$ to $80$~$\%$ in steps of $2$~$\%$ and corresponds to two different S-shaped guide systems, both with equal curvature values, i.e. $\rho_2=\rho_3$, and given at $2000$~$m$ and $1000$~$m$.}\label{table_L_P_L_S}
\begin{tabular*}{\tblwidth}{@{} LCCLCC@{} }
\toprule
\multirow{1}{*}{$R_{2/3}$} & $\rho = 2000$~$m$ & $\rho = 1000$~$m$ $^{\dagger}$ & \multirow{1}{*}{$R_{2/3}$} & $\rho = 2000$~$m$ & $\rho = 1000$~$m$ $^{\dagger}$ \\
\multirow{1}{*}{$(\%)$} & \multicolumn{2}{c}{$L_{P/S}(m)$} & \multirow{1}{*}{$(\%)$} & \multicolumn{2}{c}{$L_{P/S}(m)$}\\
\midrule
$40$ & $75.46$ & $53.36$ & $62$ & $9.50$ & $6.72$ \\
$42$ & $52.27$ & $36.96$ & $64$ & $8.29$ & $5.86$ \\
$44$ & $39.68$ & $28.06$ & $66$ & $7.20$ & $5.09$ \\
$46$ & $31.71$ & $22.42$ & $68$ & $6.21$ & $4.39$ \\
$48$ & $26.17$ & $18.51$ & $70$ & $5.31$ & $3.75$ \\
$50$ & $22.7$ & $15.61$ & $72$ & $4.47$ & $3.16$ \\
$52$ & $18.89$ & $13.36$ & $74$ & $3.68$ & $2.60$ \\
$54$ & $16.33$ & $11.54$ & $76$ & $2.95$ & $2.09$ \\
$56$ & $14.21$ & $10.05$ & $78$ & $2.26$ & $1.60$ \\
$58$ & $12.41$ & $8.78$ & $80$ & $1.61$ & $1.14$ \\
$60$ & $10.86$ & $7.68$ & $-$ & $-$ & $-$\\
\bottomrule
\end{tabular*}
\vspace{-0.2cm}
\begin{flushleft}
\footnotesize{$^{\dagger}$ $\rho = \rho_2 = \rho_3$}
\end{flushleft}
\end{table}
These scenarios are graphically presented in Figures \ref{IV_L_ps} and \ref{V_L_ps}, where, as mentioned before, a singularity in the primary and secondary straight guides is found at an arc ratio of $35.35$~$\%$ in an equal curvature S-shaped guide system. We took a close-up of the range between $40$~$\%$ and $80$~$\%$ on both figures to stress the simulation cases present in Table \ref{table_L_P_L_S}.
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.7\textwidth]{IV_L_ps.png}
\caption{A plot of primary and secondary straight guide length versus arc ratio values, with values coming from Equation \ref{L_P_S} and correspond to cases with $\rho = 2000$~$m$. Equal curvatures corresponding to denominator singularities at an arc ratio of $35.35\%$. An additional graphic shows a close-up in the $40$~$\%-80$~$\%$ arc ratio range, which configurations have been used in the second set of simulations. }
\label{IV_L_ps}
\end{figure}
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.7\textwidth]{V_L_ps.png}
\caption{A plot of primary and secondary straight guide length versus arc ratio values, which values come from Equation \ref{L_P_S} and correspond to cases with $\rho = 1000$~$m$. Equal curvatures correspond to denominator singularities at an arc ratio of $35.35$~$\%$. An additional graphic shows a close-up in the $40$~$\%-80$~$\%$ arc ratio range, which configurations have been used in the second set of simulations. }
\label{V_L_ps}
\end{figure}
The last sequence of simulations comes from a deeper analysis of cases \textbf{II$^c$} and \textbf{IV$^c$}, in which the main characteristics are in Table \ref{tbl1}. As previously said, simulation cases of Tables \ref{tbl1} and \ref{table_L_P_L_S} are performed by taking all coating indexes as $m=3$ and with a thermal ILL profile as the source. Here, we intend to change these indexes slightly and gradually from end system guides to the primary straight guide, according to the principle described in Equation \ref{escala_m}. We chose three different scenarios with combinations of two values of coating index, i.e., with $m=3.0$ and $m=2.5$, $m=3.0$ and $m=2.0$, and $m=2.5$ and $m=2.0$. Cases of \textbf{II$^c$} are in Table \ref{M_DIF_CASES_II} and of \textbf{IV$^c$} in Table \ref{M_DIF_CASES_IV}. All cases are carried out by those three types of ILL sources, as previously described.
Both tables contain values for each curved guide's characteristic wavelengths and parameters $\lambda^{\prime}$ for each curved guide. Depending on coating index values, parameters $\lambda^{\prime}$ might diverge, otherwise, the AD formalism provides the same guide neutron transport for cases \textbf{A} and \textbf{B} for a specter of a wavelength range between $\lambda_c$ and $\lambda^{\prime}$.
Concerning this aspect, it was observed that among seven coating indexes configurations, case \textbf{D} is the most appropriate scenario to keep neutron transport efficiency using lower super mirror indexes along with an S-shaped guide system. In the next section, there is a comparison of these configurations next to their fluxes at the end of the guide system. In this set of simulations, we also tested wavelength cutoff properties according to Equations \ref{new_lambda_cut}, which allows comparing cutoffs of S-shaped guides with different super mirror indexes.
\begin{table}[hbt!]
\caption{Configuration of the third and last sequence of simulations. They correspond to seven S-shaped guide system coating arrangements, given from \textbf{A} to \textbf{G}. These configurations are then subdivided into the other three series of simulations according to super mirror index values (subcases \textbf{i}, \textbf{ii}, and \textbf{iii}). Columns $m_1$, $m_{out2}$, $m_{out3}$, $m_{in2}$, $m_{in3}$, and $m_{4}$ correspond to index values of primary straight guide all surfaces, first curved guide concave surface, second curved guide concave surface, first curved guide convex surface, second curved guide convex surface and secondary straight guide all surfaces, respectively. Columns of $\lambda_{c1}$, $\lambda_{c1}^{\prime}$, $\lambda_{c2}$ and $\lambda_{c2}^{\prime}$ show values of characteristic wavelength and parameter $\lambda^{\prime}$ values for the first and second curved guide, respectively. These values correspond to configuration \textbf{II} parameters (see Table \ref{tbl1}).}\label{M_DIF_CASES_II}
\begin{tabular*}{\tblwidth}{@{} LLLLLLLLLLL@{} }
\toprule
{\scriptsize\textbf{Case}} & $m_{1}$ & $m_{out2}$ & $m_{out3}$ & $m_{in2}$ & $m_{in3}$ & $m_{4}$ & $\lambda_{c1}${\scriptsize(\AA)} & $\lambda_{c1}^{\prime}${\scriptsize(\AA)} & $\lambda_{c2}${\scriptsize(\AA)} & $\lambda_{c2}^{\prime}${\scriptsize(\AA)} \\
\midrule
\textbf{A$^{i}$} & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 0.96 & $\infty$ & 1.36 & $\infty$ \\
\textbf{B$^{i}$} & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 2.5 & 0.96 & $\infty$ & 1.36 & $\infty$ \\
\textbf{C$^{i}$} & 3.0 & 3.0 & 3.0 & 3.0 & 2.5 & 2.5 & 0.96 & $\infty$ & 1.36 & 2.46 \\
\textbf{D$^{i}$} & 3.0 & 3.0 & 3.0 & 2.5 & 2.5 & 2.5 & 0.96 & 1.74 & 1.36 & 2.46 \\
\textbf{E$^{i}$} & 3.0 & 3.0 & 2.5 & 2.5 & 2.5 & 2.5 & 0.96 & 1.74 & 1.63 & $\infty$ \\
\textbf{F$^{i}$} & 3.0 & 2.5 & 2.5 & 2.5 & 2.5 & 2.5 & 1.16 & $\infty$ & 1.63 & $\infty$ \\
\textbf{G$^{i}$} & 2.5 & 2.5 & 2.5 & 2.5 & 2.5 & 2.5 & 1.16 & $\infty$ & 1.63 & $\infty$ \\
\textbf{A$^{ii}$} & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 0.96 & $\infty$ & 1.36 & $\infty$ \\
\textbf{B$^{ii}$} & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 2.0 & 0.96 & $\infty$ & 1.36 & $\infty$ \\
\textbf{C$^{ii}$} & 3.0 & 3.0 & 3.0 & 3.0 & 2.0 & 2.0 & 0.96 & $\infty$ & 1.36 & 1.83 \\
\textbf{D$^{ii}$} & 3.0 & 3.0 & 3.0 & 2.0 & 2.0 & 2.0 & 0.96 & 1.29 & 1.36 & 1.83 \\
\textbf{E$^{ii}$} & 3.0 & 3.0 & 2.0 & 2.0 & 2.0 & 2.0 & 0.96 & 1.29 & 2.04 & $\infty$ \\
\textbf{F$^{ii}$} & 3.0 & 2.0 & 2.0 & 2.0 & 2.0 & 2.0 & 1.45 & $\infty$ & 2.04 & $\infty$ \\
\textbf{G$^{ii}$} & 2.0 & 2.0 & 2.0 & 2.0 & 2.0 & 2.0 & 1.45 & $\infty$ & 2.04 & $\infty$ \\
\textbf{A$^{iii}$} & 2.5 & 2.5 & 2.5 & 2.5 & 2.5 & 2.5 & 1.16 & $\infty$ & 1.63 & $\infty$ \\
\textbf{B$^{iii}$} & 2.5 & 2.5 & 2.5 & 2.5 & 2.5 & 2.0 & 1.16 & $\infty$ & 1.63 & $\infty$ \\
\textbf{C$^{iii}$} & 2.5 & 2.5 & 2.5 & 2.5 & 2.0 & 2.0 & 1.16 & $\infty$ & 1.63 & 2.72 \\
\textbf{D$^{iii}$} & 2.5 & 2.5 & 2.5 & 2.0 & 2.0 & 2.0 & 1.16 & 1.93 & 1.63 & 2.72 \\
\textbf{E$^{iii}$} & 2.5 & 2.5 & 2.0 & 2.0 & 2.0 & 2.0 & 1.16 & 1.93 & 2.04 & $\infty$ \\
\textbf{F$^{iii}$} & 2.5 & 2.0 & 2.0 & 2.0 & 2.0 & 2.0 & 1.45 & $\infty$ & 2.04 & $\infty$ \\
\textbf{G$^{iii}$} & 2.0 & 2.0 & 2.0 & 2.0 & 2.0 & 2.0 & 1.45 & $\infty$ & 2.04 & $\infty$ \\
\bottomrule
\end{tabular*}
\vspace{-0.4cm}
\begin{flushleft}
{\footnotesize{$^i$ Combination of super mirror indexes of $m=3.0$ and $m=2.5$}}\\
{\footnotesize{$^{ii}$ Combination of super mirror indexes of $m=3.0$ and $m=2.0$}}\\
{\footnotesize{$^{iii}$ Combination of super mirror indexes of $m=2.5$ and $m=2.0$}}
\end{flushleft}
\end{table}
\begin{table}[hbt!]
\caption{Configuration of the third and last sequence of simulations. They correspond to seven S-shaped guide system coating arrangements, given from \textbf{A} to \textbf{G}. These configurations are then subdivided into the other three series of simulations according to super mirror index values (subcases \textbf{i}, \textbf{ii}, and \textbf{iii}). Columns $m_1$, $m_{out2}$, $m_{out3}$, $m_{in2}$, $m_{in3}$, and $m_{4}$ correspond to index values of primary straight guide all surfaces, first curved guide concave surface, second curved guide concave surface, first curved guide convex surface, second curved guide convex surface and secondary straight guide all surfaces, respectively. Columns of $\lambda_{c1}$, $\lambda_{c1}^{\prime}$, $\lambda_{c2}$ and $\lambda_{c2}^{\prime}$ show values of characteristic wavelength and parameter $\lambda^{\prime}$ values for the first and second curved guide, respectively. These values correspond to configuration \textbf{IV} parameters (see Table \ref{tbl1}).}\label{M_DIF_CASES_IV}
\begin{tabular*}{\tblwidth}{@{} LLLLLLLLLLL@{} }
\toprule
{\scriptsize\textbf{Case}} & $m_{1}$ & $m_{out2}$ & $m_{out3}$ & $m_{in2}$ & $m_{in3}$ & $m_{4}$ & $\lambda_{c1}${\scriptsize(\AA)} & $\lambda_{c1}^{\prime}${\scriptsize(\AA)} & $\lambda_{c2}${\scriptsize(\AA)} & $\lambda_{c2}^{\prime}${\scriptsize(\AA)} \\
\midrule
\textbf{A$^{i}$} & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 1.36 & $\infty$ & 1.36 & $\infty$ \\
\textbf{B$^{i}$} & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 2.5 & 1.36 & $\infty$ & 1.36 & $\infty$ \\
\textbf{C$^{i}$} & 3.0 & 3.0 & 3.0 & 3.0 & 2.5 & 2.5 & 1.36 & $\infty$ & 1.36 & 2.46 \\
\textbf{D$^{i}$} & 3.0 & 3.0 & 3.0 & 2.5 & 2.5 & 2.5 & 1.36 & 2.46 & 1.36 & 2.46 \\
\textbf{E$^{i}$} & 3.0 & 3.0 & 2.5 & 2.5 & 2.5 & 2.5 & 1.36 & 2.46 & 1.63 & $\infty$ \\
\textbf{F$^{i}$} & 3.0 & 2.5 & 2.5 & 2.5 & 2.5 & 2.5 & 1.63 & $\infty$ & 1.63 & $\infty$ \\
\textbf{G$^{i}$} & 2.5 & 2.5 & 2.5 & 2.5 & 2.5 & 2.5 & 1.63 & $\infty$ & 1.63 & $\infty$ \\
\textbf{A$^{ii}$} & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 1.36 & $\infty$ & 1.36 & $\infty$ \\
\textbf{B$^{ii}$} & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 2.0 & 1.36 & $\infty$ & 1.36 & $\infty$ \\
\textbf{C$^{ii}$} & 3.0 & 3.0 & 3.0 & 3.0 & 2.0 & 2.0 & 1.36 & $\infty$ & 1.36 & 1.83 \\
\textbf{D$^{ii}$} & 3.0 & 3.0 & 3.0 & 2.0 & 2.0 & 2.0 & 1.36 & 1.83 & 1.36 & 1.83 \\
\textbf{E$^{ii}$} & 3.0 & 3.0 & 2.0 & 2.0 & 2.0 & 2.0 & 1.36 & 1.83 & 2.04 & $\infty$ \\
\textbf{F$^{ii}$} & 3.0 & 2.0 & 2.0 & 2.0 & 2.0 & 2.0 & 2.04 & $\infty$ & 2.04 & $\infty$ \\
\textbf{G$^{ii}$} & 2.0 & 2.0 & 2.0 & 2.0 & 2.0 & 2.0 & 2.04 & $\infty$ & 2.04 & $\infty$ \\
\textbf{A$^{iii}$} & 2.5 & 2.5 & 2.5 & 2.5 & 2.5 & 2.5 & 1.63 & $\infty$ & 1.63 & $\infty$ \\
\textbf{B$^{iii}$} & 2.5 & 2.5 & 2.5 & 2.5 & 2.5 & 2.0 & 1.63 & $\infty$ & 1.63 & $\infty$ \\
\textbf{C$^{iii}$} & 2.5 & 2.5 & 2.5 & 2.5 & 2.0 & 2.0 & 1.63 & $\infty$ & 1.63 & 2.72 \\
\textbf{D$^{iii}$} & 2.5 & 2.5 & 2.5 & 2.0 & 2.0 & 2.0 & 1.63 & 2.72 & 1.63 & 2.72 \\
\textbf{E$^{iii}$} & 2.5 & 2.5 & 2.0 & 2.0 & 2.0 & 2.0 & 1.63 & 2.72 & 2.04 & $\infty$ \\
\textbf{F$^{iii}$} & 2.5 & 2.0 & 2.0 & 2.0 & 2.0 & 2.0 & 2.04 & $\infty$ & 2.04 & $\infty$ \\
\textbf{G$^{iii}$} & 2.0 & 2.0 & 2.0 & 2.0 & 2.0 & 2.0 & 2.04 & $\infty$ & 2.04 & $\infty$ \\
\bottomrule
\end{tabular*}
\vspace{-0.4cm}
\begin{flushleft}
{\footnotesize{$^i$ Combination of super mirror indexes of $m=3.0$ and $m=2.5$}}\\
{\footnotesize{$^{ii}$ Combination of super mirror indexes of $m=3.0$ and $m=2.0$}}\\
{\footnotesize{$^{iii}$ Combination of super mirror indexes of $m=2.5$ and $m=2.0$}}
\end{flushleft}
\end{table}
\section{Results and discussions}
\label{RAD}
The first set of simulations, shown in Table \ref{tbl1}, is carried out and the results are presented in Table \ref{VACA}. In complementarity, wavelength values are displayed graphically in Figure \ref{R_CUTOFF}.
In such a table, we present cases \textbf{I} to \textbf{XII} with triplet subcases that characterize both curved guide arcs. Since configurations, a and b are symmetrical, cases with equal curvature possess the same $Z$ displacement values. The second and third column contains curved guides arc ratios for both arched guides that compose the S-shaped guide. A comparison of theoretical and simulated wavelength cutoff denoted as $\lambda^{T}_{cut}$ and $\lambda^{S}_{cut}$, respectively, is summarized in the last column, through their ratio $R_\lambda$.
Values of $R_\lambda$ are displayed in Figure \ref{R_CUTOFF}, where red, yellow and blue points and lines represent, respectively, subcases \textbf{a.}, \textbf{b.}, and \textbf{c.}. It is tacit that configurations \textbf{a.} and \textbf{b.}, despite their LoS exclusion, do not guarantee the wavelength cutoff properly. Only configuration \textbf{c.} allows arcs long enough to impose the cutoff.
\begin{table}[hbt!]
\caption{The result values and parameters of the first set of simulations. The second and third columns show that arc ratios of the first and second curved guides. The column $Z$ indicates vertical (or horizontal) displacement correspondent to the S-shaped guide configuration case. In the columns $\lambda_{cut}^{T}$ and $\lambda_{cut}^{S}$, theoretical and simulated values of the wavelength cutoff are displayed. Since theoretical values do not depend on arc values, there is only one value for all three cases \textbf{a.}, \textbf{b.}, and \textbf{c.}. The last column shows ratios of the previous two columns parameters, i.e., $\lambda_{cut}^{T}$ and $\lambda_{cut}^{S}$.}\label{VACA}
\begin{tabular*}{\tblwidth}{@{} LCCLLLL@{} }
\toprule
\textbf{Case} & \textbf{$\gamma_2/2\Psi_{c2}$ $(\%)$} & \textbf{$\gamma_3/2\Psi_{c3}$ $(\%)$} & \textbf{$Z(m)$} & \textbf{$\lambda^{T}_{cut}$} (\AA) & \textbf{$\lambda^{S}_{cut}$} (\AA)& \textbf{$R_\lambda$ $(\%)$} \\
\midrule
\textbf{I$^a$} & 82.92 & 30.36 & 0.16 & \multirow{3}{*}{0.68} & 0.56 & 81.61 \\
\textbf{I$^b$} & 30.36 & 82.92 & 0.16 & & 0.57 & 83.39 \\
\textbf{I$^c$} & 82.92 & 82.92 & 0.28 & & 0.71 & 104.95 \\
\textbf{II$^a$} & 88.39 & 21.80 & 0.17 & \multirow{3}{*}{0.79} & 0.49 & 62.82 \\
\textbf{II$^b$} & 35.82 & 75.46 & 0.14 & & 0.64 & 80.95 \\
\textbf{II$^c$} & 88.39 & 75.46 & 0.27 & & 0.79 & 100.26 \\
\textbf{III$^a$} & 92.28 & 12.36 & 0.17 & \multirow{3}{*}{0.86} & 0.51 & 59.37 \\
\textbf{III$^b$} & 39.72 & 67.61 & 0.12 & & 0.98 & 114.14 \\
\textbf{III$^c$} & 92.28 & 67.61 & 0.26 & & 0.93 & 107.92 \\
\textbf{IV$^a$} & 81.94 & 28.28 & 0.15 & \multirow{3}{*}{0.96} & 0.63 & 65.30 \\
\textbf{IV$^b$} & 28.28 & 81.94 & 0.15 & & 0.60 & 62.74 \\
\textbf{IV$^c$} & 81.94 & 81.94 & 0.27 & & 1.04 & 108.18 \\
\textbf{V$^a$} & 87.41 & 18.87 & 0.16 & \multirow{3}{*}{1.11} & 0.63 & 56.98 \\
\textbf{V$^b$} & 33.75 & 74.12 & 0.13 & & 0.86 & 77.53 \\
\textbf{V$^c$} & 87.41 & 74.12 & 0.26 & & 1.17 & 104.80 \\
\textbf{VI$^a$} & 80.60 & 25.36 & 0.14 & \multirow{3}{*}{1.36} & 0.77 & 56.62 \\
\textbf{VI$^b$} & 25.36 & 80.60 & 0.14 & & 0.67 & 49.22 \\
\textbf{VI$^c$} & 80.60 & 80.60 & 0.26 & & 1.38 & 101.52 \\
\textbf{VII$^a$} & 78.41 & 25.36 & 0.14 & \multirow{3}{*}{0.68} & 0.47 & 69.63 \\
\textbf{VII$^b$} & 20.36 & 80.60 & 0.14 & & 0.52 & 76.49 \\
\textbf{VII$^c$} & 78.41 & 80.60 & 0.25 & & 0.77 & 113.07 \\
\textbf{VIII$^a$} & 83.88 & 14.73 & 0.15 & \multirow{3}{*}{0.79} & 0.56 & 71.16 \\
\textbf{VIII$^b$} & 25.82 & 72.29 & 0.12 & & 0.70 & 89.22 \\
\textbf{VIII$^c$} & 83.88 & 72.29 & 0.25 & & 0.85 & 107.75 \\
\textbf{IX$^a$} & 87.78 & 2.36 & 0.15 & \multirow{3}{*}{0.86} & 0.54 & 62.72 \\
\textbf{IX$^b$} & 29.72 & 63.35 & 0.10 & & 0.85 & 98.74 \\
\textbf{IX$^c$} & 87.78 & 63.35 & 0.23 & & 0.89 & 103.80 \\
\textbf{X$^a$} & 75.86 & 21.21 & 0.12 & \multirow{3}{*}{0.96} & 0.65 & 67.20 \\
\textbf{X$^b$} & 14.14 & 78.78 & 0.13 & & 0.57 & 59.60 \\
\textbf{X$^c$} & 75.86 & 78.78 & 0.24 & & 1.01 & 104.89 \\
\textbf{XI$^a$} & 81.33 & 8.87 & 0.13 & \multirow{3}{*}{1.11} & 0.54 & 48.37 \\
\textbf{XI$^b$} & 19.61 & 69.86 & 0.11 & & 0.71 & 64.06 \\
\textbf{XI$^c$} & 81.33 & 69.86 & 0.23 & & 1.09 & 97.58 \\
\textbf{XII$^a$} & 72.56 & 15.36 & 0.11 & \multirow{3}{*}{1.36} & 0.65 & 47.46 \\
\textbf{XII$^b$} & 5.36 & 76.35 & 0.12 & & 0.62 & 45.29 \\
\textbf{XII$^c$} & 72.56 & 76.35 & 0.22 & & 1.36 & 99.86 \\
\bottomrule
\end{tabular*}
\vspace{-0.4cm}
\begin{flushleft}
{\footnotesize{$^a$ $\gamma_2=\varphi+\varphi_{p}^{\prime\prime}$, $\gamma_3=\varphi-\varphi_{s}^{\prime}$}}\\
{\footnotesize{$^b$ $\gamma_2=\varphi-\varphi_{p}^{\prime}$, $\gamma_3=\varphi+\varphi_{s}^{\prime\prime}$}}\\
{\footnotesize{$^c$ $\gamma_2=\varphi+\varphi_{p}^{\prime\prime}$, $\gamma_3=\varphi+\varphi_{s}^{\prime\prime}$}}
\end{flushleft}
\end{table}
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.7\textwidth]{R_CUTOFF.png}
\caption{A plot of wavelength cutoff ratios versus the first sequence of simulation cases from \textbf{I} to \textbf{XII}. The ordinate axis represents ratios of simulated and theoretical wavelength cutoff, with values close to 100$~$\% indicating better fit between proposed simulations and literature. Blue, yellow and red curves stand for subcases \textbf{a.}, \textbf{b.}, and \textbf{c.}, respectively.}
\label{R_CUTOFF}
\end{figure}
According to these results, we have proposed a sequel of simulations to determine which arc ratio imposes wavelength cutoff to transported neutron through an S-shaped guide system. From Equation \ref{L_P_S}, we can get different arc ratios through variation of primary and secondary straight guide lengths or vice versa. A set of simulation cases is in Table \ref{table_L_P_L_S}, where straight guide lengths are obtained for twenty-one arc ratios from $40$~$\%$ to $80$~$\%$ in steps of $2$~$\%$.
Simulations of Table \ref{table_L_P_L_S} are carried out and results are presented in two graphic pairs, each one for a different curved guide curvature, i.e., $\rho = 2000$~$m$ and $\rho = 1000$~$m$, since $\rho_2=\rho_3$. Here, Figures \ref{IV_lambda_cut} and \ref{IV_dentalambda_cut} represent simulations with $\rho = 2000$~$m$ and Figures \ref{V_lambda_cut} and \ref{V_deltalambda_cut} the other with $\rho = 1000$~$m$.
In Figures \ref{IV_lambda_cut} and \ref{V_lambda_cut}, there are horizontal red lines that stand for theoretical wavelength cutoff values of each configuration. Blue dots indicate correspondent cutoff values from simulated cases with different arc ratios. On the other hand, it is observed in Figures \ref{IV_dentalambda_cut} and \ref{V_deltalambda_cut} the modulus of both theoretical and simulated cutoff difference values, i.e., $\Delta\lambda_{cut}=|\lambda^{T}_{cut}-\lambda^{S}_{cut}|$.
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.7\textwidth]{IV_lambda_cut.png}
\caption{A plot of wavelength cutoff values versus arc ratios. The ordinate axis represents wavelength values and the abscissa axis stands for ratios raging from $40$~$\%$ to $80$~$\%$. The results correspond to cases shown in Table \ref{table_L_P_L_S}, where each simulation configuration is gradually modified by an addition of $2\%$ in the ratio value. The red curve stands for a theoretical constant cutoff value, and the blue dots are simulated cutoff data. These results correspond to simulations of cases with $\rho = 2000$~$m$.}
\label{IV_lambda_cut}
\end{figure}
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.5\textwidth]{IV_dentalambda_cut.png}
\caption{A plot of the modular difference between theoretical and simulated wavelength cutoff values versus arc ratios. The ordinate axis represents wavelength values and the abscissa axis stands for ratios from $40$~$\%$ to $80$~$\%$ with steps of $2$~$\%$. Results correspond to cases with $\rho = 2000$~$m$, according to Table \ref{table_L_P_L_S}. The blue curve stands for the modular difference between two values of wavelength cutoff, so that the tendency to decay represents an improved adjustment of the theory and the presented simulations.}
\label{IV_dentalambda_cut}
\end{figure}
Based on these results, it is possible to observe that as much as the arc ratio increases, the simulated wavelength cutoff approaches the theoretical one. In other words, the $\Delta\lambda_{cut}$ tends to zero if $R_\lambda$ goes to one. In this scenario, the relation $\Delta\lambda_{cut}<0.05$ \AA$ $ is guaranteed for $R_\lambda>65$~$\%$. It is worth noting that, according to Figures \ref{IV_L_ps} and \ref{V_L_ps}, higher arc ratio values correspond to shorter primary and secondary straight guides. Therefore, S-shaped guide systems with wavelength cutoff are desirable from a neutron transportation point of view. Figures \ref{V_40_50_60_70_80} and \ref{IV_40_50_60_70_80} show neutron flux profiles at the end of S-shaped guide systems of this set of simulations, but only for cases of arc ratios of $40$~$\%$, $50$~$\%$, $60$~$\%$, $70$~$\%$ and $80$~$\%$.
Table \ref{table_L_P_L_S_FLUX} shows flux values of these profiles. Here, one can see that longer arcs correspond to longer curved guides but to shorter straight guides. However, these cases provide higher flux values since the exclusion of LoS in S-shaped guides forces neutrons to go through longer paths. According to Equation \ref{Z} and Table \ref{table_L_P_L_S_FLUX}, we also note that higher flux cases provide longer vertical (or horizontal) displacement.
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.7\textwidth]{V_lambda_cut.png}
\caption{A plot of wavelength cutoff values versus arc ratios. The ordinate represents wavelength and the abscissa stands for ratios raging from $40$~$\%$ to $80$~$\%$. The results correspond to cases shown in Table \ref{table_L_P_L_S}, where each simulation configuration is gradually modified by an addition of $2$~$\%$ in the ratio value. The red curve stands for a theoretical constant cutoff value, and the blue dots are simulated cutoff data. These results correspond to simulations of cases with $\rho = 1000$~$m$.}
\label{V_lambda_cut}
\end{figure}
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.7\textwidth]{V_deltalambda_cut.png}
\caption{A plot of the modular difference between theoretical and simulated wavelength cutoff values versus arc ratios. The ordinate axis represents wavelength values and the abscissa axis stands for ratios raging from $40$~$\%$ to $80$~$\%$ with steps of $2$~$\%$. The results correspond to the cases with $\rho = 1000$~$m$, according to Table \ref{table_L_P_L_S}. The blue curve stands for the modular difference between two values of wavelength cutoff, so that the tendency to decay represents an improved adjustment of the theory and the presented simulations. }
\label{V_deltalambda_cut}
\end{figure}
\begin{table}[hbt!]
\caption{Flux data results of the second run of simulations. Presented fluxes correspond only to tens of arc ratio whole sequence, i.e., $40$~$\%$, $50$~$\%$, $60$~$\%$, $70$~$\%$ and $80$~$\%$. Fluxes are given on a $\times 10^9 n/cm^2s$ basis and the second and third columns represent, respectively, simulations with $\rho= 2000$~$m$ and $\rho = 1000$~$m$. After flux values and between parenthesis, there are relative percentages of correspondent values next to the highest flux of the simulation series. That is, fluxes of arc ratios of $80$~$\%$ are the top flux values and are taken as $100$~$\%$.}\label{table_L_P_L_S_FLUX}
\begin{tabular*}{\tblwidth}{@{} LCC@{} }
\toprule
\multirow{2}{*}{$R_{2/3}$ $(\%)$} & \multicolumn{2}{c}{Flux $(\times 10^9 n/cm^2s)$} \\
& $\rho = 2000$~$m$ & $\rho = 1000$~$m$ $^{\dagger}$ \\
\midrule
$40$ & $1.588$~$(46.11\%) $ & $ 1.544$~$(50.06\%)$ \\
$50$ & $2.860$~$(83.04\%) $ & $ 2.618$~$(84.89\%)$ \\
$60$ & $3.266$~$(94.83\%) $ & $ 2.954$~$(95.78\%)$ \\
$70$ & $3.431$~$(99.62\%) $ & $ 3.027$~$(98.15\%)$ \\
$80$ & $3.444$~$(100.00\%)$ & $ 3.084$~$(100.00\%)$ \\
\bottomrule
\end{tabular*}
\vspace{-0.2cm}
\begin{flushleft}
\footnotesize{$^{\dagger}$ $\rho = \rho_2 = \rho_3$}
\end{flushleft}
\end{table}
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.7\textwidth]{IV_40_50_60_70_80.png}
\caption{The plot shows respective flux profiles at the end of the S-shaped guide system according to their arc rations. The ordinate and abscissa axes stand for neutron flux in $10^7 n/cm^2s$ units and wavelength in Angstroms, respectively. Red, orange, yellow, green, and blue curves represent arc ratio values of $40$~$\%$, $50$~$\%$, $60$~$\%$, $70$~$\%$, and $80$~$\%$, respectively. The close-up graph indicates that arc ratios $70$~$\%$ and $80$~$\%$ possess their wavelength cutoff values close to $0.96$ \AA, which is the theoretical cutoff according to Figure \ref{IV_lambda_cut}.}
\label{IV_40_50_60_70_80}
\end{figure}
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.7\textwidth]{V_40_50_60_70_80.png}
\caption{The plot shows respective flux profiles at the end of the S-shaped guide system according to their arc rations. The ordinate and abscissa axes stand for neutron flux in $10^7 n/cm^2s$ units and wavelength in Angstroms, respectively. Red, orange, yellow, green, and blue curves represent arc ratio values of $40$~$\%$, $50$~$\%$, $60$~$\%$, $70$~$\%$, and $80$~$\%$, respectively. The close-up graph indicates that arc ratios $70$~$\%$ and $80$~$\%$ possess their wavelength cutoff values close to $1.36$ \AA, which is the theoretical cutoff according to Figure \ref{V_lambda_cut}.}
\label{V_40_50_60_70_80}
\end{figure}
There is in Figure \ref{Zmin_Zmax} a proper interval of arc ratios that guarantees LoS exclusion, between the vertical red and blue curves, corresponding to $35.36$~$\%$ and $85.36$~$\%$, respectively. The S-shaped guide displacement curve follows the equation $Z=8WR^2$ since guide curvatures are way longer than their correspondent lengths, i.e., for ($L_{2/3}~<<~\rho_{2/3}$). In this sense, both scenarios with equal curvature $\rho_2$ and $\rho_3$ possess the same plot to represent minimum and maximum $Z$ displacement values according to a minimal S-shaped guide system. Anyway, the present formalism may be violated if higher displacement values are needed. Otherwise, guide width can be changed to allow modifying the solid black curve parabola inclination of Figure \ref{Zmin_Zmax}, which corresponds to $Z$ displacement with $W = 5$~$cm$ and is a standard value for all accomplished simulation cases of this work. In addition, dashed, dotted-dashed, and dotted curves stand for a vertical (or horizontal) displacement of S-shaped curves with widths of $10$, $15$, and $20$~$cm$, respectively.
In these minimal regimes of LoS exclusion, a flux difference of about 2 times between arc ratios of $40$~$\%$ and $80$~$\%$ was observed. In addition, it is not possible to obtain higher displacements of about $29$~$cm$ as previously mentioned, the only way to obtain larger $Z$ values is by employing wider guides (larger $W$). Otherwise, if minimal LoS exclusion is not required, then longer displacements are available.
\begin{figure}[hbt!]
\centering
\includegraphics[width=0.7\textwidth]{Zmin_Zmax.png}
\caption{The plot of vertical (or horizontal) displacement versus arc ratio. The ordinate axis represents the parameter $Z$ and the abscissa axis the arc ratio. Vertical blue and red curves indicate maximum and minimum ratio values corresponding to the minimal S-shaped guide formalism of the present work. Solid, dashed, dotted-dashed, and dotted black curves stand for vertical (or horizontal) displacements of guide systems with widths of $5$, $10$, $15$, and $20$~$cm$, respectively. }
\label{Zmin_Zmax}
\end{figure}
The last set of simulations corresponds to the cases presented in Tables \ref{M_DIF_CASES_II} and \ref{M_DIF_CASES_IV}, which correspond to unfolding the cases \textbf{II} and \textbf{IV}. Here, we reemphasize two aspects of these simulations. Firstly, we verified simulations from a wavelength cutoff point of view, i.e., the proposed cutoff expression for different surface indexes m WAS tested since we convert engineering aspects of neutron guides into geometrical ones (see Equation \ref{new_varphi}). Secondly, we verified fluxes at the end of simulated guide systems. From these results, we intend to identify super mirror coating arrangements that preserve fluxes close to ideal cases, i.e., all indexes equal and with maximum value.
\begin{table}[hbt!]
\caption{Wavelength cutoff data from the last sequence of simulations. These results come from running Table \ref{M_DIF_CASES_II} cases for three different ILL sources, i.e., with cold, thermal, and hot spectra. The second column contains theoretical values of cutoff, while the posterior columns present simulated wavelength cutoff values for three runs of simulations with each source. Together with all simulated data, there is a percentage between parenthesis that stands for theoretical and simulated ratio percentage. This table of results corresponds to simulation case \textbf{II}, which configurations are in Table \ref{tbl1}}\label{CTH_II}
\begin{tabular*}{\tblwidth}{@{} LLCCC@{} }
\toprule
\multirow{2}{*}{\textbf{Case}} & \multirow{2}{*}{$\lambda_{cut}^{T}$ (\AA)} & \textbf{Cold} & \textbf{Thermal} & \textbf{Hot} \\
& & $\lambda_{cut}^{S}$ (\AA)($R_{\lambda}$) & $\lambda_{cut}^{S}$(\AA)($R_{\lambda}$) & $\lambda_{cut}^{S}$(\AA)($R_{\lambda}$) \\
\midrule
\textbf{A$^{i}$} & 0.79 & 0.95 (120.30\%) & 0.84 (106.36\%) & 0.75 (94.73\%) \\
\textbf{B$^{i}$} & 0.79 & 0.90 (115.04\%) & 0.80 (102.05\%) & 0.83 (105.09\%) \\
\textbf{C$^{i}$} & 0.79 & 0.90 (114.22\%) & 0.90 (114.00\%) & 0.74 (94.09\%) \\
\textbf{D$^{i}$} & 0.79 & 0.94 (119.77\%) & 0.82 (104.21\%) & 0.85 (107.58\%) \\
\textbf{E$^{i}$} & 0.83 & 0.97 (117.02\%) & 0.85 (102.50\%) & 0.82 (99.04\%) \\
\textbf{F$^{i}$} & 0.94 & 1.00 (105.92\%) & 0.97 (102.63\%) & 0.91 (96.69\%) \\
\textbf{G$^{i}$} & 0.94 & 1.00 (106.03\%) & 0.97 (102.78\%) & 0.88 (92.94\%) \\
\textbf{A$^{ii}$} & 0.79 & 0.93 (117.76\%) & 0.82 (104.87\%) & 0.76 (97.18\%) \\
\textbf{B$^{ii}$} & 0.79 & 0.85 (108.47\%) & 0.88 (112.34\%) & 0.80 (101.07\%) \\
\textbf{C$^{ii}$} & 0.79 & 0.91 (115.34\%) & 0.83 (105.67\%) & 0.75 (95.09\%) \\
\textbf{D$^{ii}$} & 0.79 & 0.86 (109.27\%) & 0.84 (107.10\%) & 0.74 (94.63\%) \\
\textbf{E$^{ii}$} & 0.87 & 1.01 (116.10\%) & 0.88 (100.86\%) & 0.99 (113.87\%) \\
\textbf{F$^{ii}$} & 1.18 & 1.29 (109.17\%) & 1.11 (94.21\%) & 1.20 (102.00\%) \\
\textbf{G$^{ii}$} & 1.18 & 1.23 (104.28\%) & 1.17 (98.76\%) & 1.13 (95.39\%) \\
\textbf{A$^{iii}$} & 0.94 & 1.00 (106.28\%) & 0.95 (101.17\%) & 0.95 (100.85\%) \\
\textbf{B$^{iii}$} & 0.94 & 1.01 (107.49\%) & 0.95 (100.25\%) & 0.92 (96.99\%) \\
\textbf{C$^{iii}$} & 0.94 & 1.00 (105.59\%) & 0.93 (98.93\%) & 0.96 (102.06\%) \\
\textbf{D$^{iii}$} & 0.94 & 1.02 (107.55\%) & 0.95 (100.47\%) & 0.96 (102.08\%) \\
\textbf{E$^{iii}$} & 1.01 & 1.10 (109.49\%) & 1.02 (101.52\%) & 1.02 (101.46\%) \\
\textbf{F$^{iii}$} & 1.18 & 1.25 (106.11\%) & 1.17 (99.13\%) & 1.12 (94.97\%) \\
\textbf{G$^{iii}$} & 1.18 & 1.21 (102.45\%) & 1.11 (93.78\%) & 1.14 (96.78\%) \\
\bottomrule
\end{tabular*}
\vspace{-0.4cm}
\begin{flushleft}
{\footnotesize{$^i$ Combination of super mirror indexes of $m=3.0$ and $m=2.5$}}\\
{\footnotesize{$^{ii}$ Combination of super mirror indexes of $m=3.0$ and $m=2.0$}}\\
{\footnotesize{$^{iii}$ Combination of super mirror indexes of $m=2.5$ and $m=2.0$}}
\end{flushleft}
\end{table}
Simulations are carried out and results, which concern wavelength cutoff, are displayed in Tables \ref{CTH_II} and \ref{CTH_IV}, where the former corresponds to \textbf{II} cases and the latter to \textbf{IV} cases. Both tables are composed of one column of theoretical wavelength cutoff, calculated according to Equation \ref{new_lambda_cut}, and three columns of simulation cutoff results. Here, each one of them relate to a different ILL source, namely cold, thermal and hot sources. To simplify data analysis, there are corresponding percentages of simulated cutoffs compared to theoretical ones. Such ratios stay after simulated cutoffs in between parentheses. An additional table is attached to evaluate the validity of Equation \ref{new_lambda_cut} employing compact statistical data. Such results are in Table \ref{STAT}. Results between simulated and theoretical wavelength cutoffs are counted in two ranges, namely, $\pm 5$~$\%$ and $\pm 10$~$\%$, i.e., if cutoff the ratios are between $ 95$~$\%$ and $ 105$~$\%$ or $ 90$~$\%$ and $ 110$~$\%$, respectively.
\begin{table}[hbt!]
\caption{Wavelength cutoff data from the last sequence of simulations. These results come from running Table \ref{M_DIF_CASES_IV} cases for three different ILL sources, i.e., with cold, thermal, and hot spectra. The second column contains theoretical values of cutoff, while the posterior columns present simulated wavelength cutoff values for three runs of simulations with each source. Together with all simulated data, there is a percentage between parenthesis that stands for theoretical and simulated ratio percentage. This table of results corresponds to simulation case \textbf{IV}, which configurations are in Table \ref{tbl1}}\label{CTH_IV}
\begin{tabular*}{\tblwidth}{@{} LLCCC@{} }
\toprule
\multirow{2}{*}{\textbf{Case}} & \multirow{2}{*}{$\lambda_{cut}^{T}$ (\AA)} & \textbf{Cold} & \textbf{Thermal} & \textbf{Hot} \\
& & $\lambda_{cut}^{S}$ (\AA)($R_{\lambda}$) & $\lambda_{cut}^{S}$(\AA)($R_{\lambda}$) & $\lambda_{cut}^{S}$(\AA)($R_{\lambda}$) \\
\midrule
\textbf{A$^{i}$} & 0.96 & 1.02 (105.82\%) & 1.00 (103.59\%) & 0.96 (99.60\%) \\
\textbf{B$^{i}$} & 0.96 & 0.98 (101.93\%) & 0.98 (101.66\%) & 0.96 (99.60\%) \\
\textbf{C$^{i}$} & 0.96 & 0.98 (101.78\%) & 1.01 (104.46\%) & 0.95 (98.60\%) \\
\textbf{D$^{i}$} & 0.96 & 1.01 (105.21\%) & 0.96 (99.63\%) & 0.96 (99.76\%) \\
\textbf{E$^{i}$} & 1.05 & 1.12 (106.82\%) & 1.05 (100.63\%) & 1.03 (98.61\%) \\
\textbf{F$^{i}$} & 1.16 & 1.26 (108.79\%) & 1.16 (99.95\%) & 1.11 (95.93\%) \\
\textbf{G$^{i}$} & 1.16 & 1.19 (102.72\%) & 1.15 (99.37\%) & 1.10 (95.52\%) \\
\textbf{A$^{ii}$} & 0.96 & 1.01 (104.33\%) & 0.98 (102.24\%) & 0.99 (102.87\%) \\
\textbf{B$^{ii}$} & 0.96 & 1.04 (108.30\%) & 0.99 (102.93\%) & 1.00 (103.65\%) \\
\textbf{C$^{ii}$} & 0.96 & 1.05 (108.56\%) & 0.99 (103.12\%) & 0.97 (100.98\%) \\
\textbf{D$^{ii}$} & 0.96 & 1.02 (105.89\%) & 1.03 (106.57\%) & 0.98 (101.92\%) \\
\textbf{E$^{ii}$} & 1.13 & 1.23 (108.87\%) & 1.10 (97.26\%) & 1.05 (92.88\%) \\
\textbf{F$^{ii}$} & 1.45 & 1.49 (103.11\%) & 1.37 (95.04\%) & 1.41 (97.31\%) \\
\textbf{G$^{ii}$} & 1.45 & 1.47 (101.48\%) & 1.42 (98.34\%) & 1.36 (94.04\%) \\
\textbf{A$^{iii}$} & 1.16 & 1.22 (105.48\%) & 1.14 (98.21\%) & 1.19 (102.87\%) \\
\textbf{B$^{iii}$} & 1.16 & 1.25 (108.08\%) & 1.18 (101.70\%) & 1.16 (100.20\%) \\
\textbf{C$^{iii}$} & 1.16 & 1.16 (100.03\%) & 1.15 (99.15\%) & 1.12 (96.77\%) \\
\textbf{D$^{iii}$} & 1.16 & 1.20 (103.98\%) & 1.11 (96.20\%) & 1.13 (97.58\%) \\
\textbf{E$^{iii}$} & 1.28 & 1.32 (103.63\%) & 1.21 (94.74\%) & 1.28 (99.89\%) \\
\textbf{F$^{iii}$} & 1.45 & 1.52 (105.10\%) & 1.39 (96.53\%) & 1.41 (97.53\%) \\
\textbf{G$^{iii}$} & 1.45 & 1.49 (102.99\%) & 1.39 (96.51\%) & 1.35 (93.51\%) \\
\bottomrule
\end{tabular*}
\vspace{-0.4cm}
\begin{flushleft}
{\footnotesize{$^i$ Combination of super mirror indexes of $m=3.0$ and $m=2.5$}}\\
{\footnotesize{$^{ii}$ Combination of super mirror indexes of $m=3.0$ and $m=2.0$}}\\
{\footnotesize{$^{iii}$ Combination of super mirror indexes of $m=2.5$ and $m=2.0$}}
\end{flushleft}
\end{table}
All simulations are carried out using $10^7$ rays in the MCSTAS software. In this scenario, the fluxes present an error of about $3$~$\%$. This percentage concerns the number of neutrons that reach a detector. In addition, our criteria for picking a wavelength cutoff are based on neutron counting of less than $1$~$\%$ from the profile peak. Thus, we consider tests of $5$~$\%$ and $10$~$\%$ a proper method to verify wavelength cutoff equation validity. According to Table \ref{STAT}, we observe that cold source simulations possess less than $50$~$\%$ cutoff value, except simulations of Case IV. We believe that this discrepancy is due to a minor concentration of neutrons in the vicinity of the wavelength cutoff, which diminishes neutron counting and the statistics to determine neutrons of minimal wavelength. In other words, from Figure \ref{SOURCE} it is possible to notice that neutron counting near typical cutoffs, i.e., between $0.8$ and $1.5$ \AA, is much more prevalent for hot and thermal sources than for cold ones. Other scenarios show a good agreement between theory and simulations.
\begin{table}[hbt!]
\caption{Compilation of wavelength cutoff statistical results of \textbf{II} and \textbf{IV} configuration simulations and carried out for three ILL sources. The presented numbers correspond individually for each case and source type, which is displayed in the first and second columns, respectively. The third column indicates that 21 simulations were run for different arrangement parameters. The last two columns show the number of simulated cases, in which wavelength cutoff values differ just $5$~$\%$ and $10$~$\%$ from the theoretical value, respectively. These numbers are followed by a percentage between parenthesis that indicates the percentage of cases of correspondent ranges.}\label{STAT}
\begin{tabular*}{\tblwidth}{@{} LLLLL@{} }
\toprule
\multirow{2}{*}{\textbf{Case}} & \multirow{2}{*}{\textbf{Source}} & \textbf{Number of} & $|\Delta R_\lambda|^{*}<=5\%$ & $|\Delta R_\lambda|^{*}<=10\%$ \\
& & \textbf{Simulations} & (Percentage) & (Percentage) \\
\midrule
\multirow{3}{*}{\textbf{II}} & \textbf{Cold} & 21 & 2 (9.58\%) & 13 (61.90\%) \\
& \textbf{Thermal} & 21 & 14 (66.67\%) & 19 (90.48\%) \\
& \textbf{Hot} & 21 & 13 (61.90\%) & 20 (95.24\%) \\
\multirow{3}{*}{\textbf{IV}} & \textbf{Cold} & 21 & 10 (47.62\%) & 21 (100.00\%) \\
& \textbf{Thermal} & 21 & 19 (90.48\%) & 21 (100.00\%) \\
& \textbf{Hot} & 21 & 18 (85.71\%) & 21 (100.00\%)
\\
\bottomrule
\end{tabular*}
\vspace{-0.4cm}
\begin{flushleft}
{\footnotesize{$^*$ $|\Delta R_\lambda| = |100$~$\%-R_\lambda|$}}
\end{flushleft}
\end{table}
The investigation of neutron transport efficiency is done through Tables \ref{FLUX_II} and \ref{FLUX_IV}, which correspond to cases \textbf{II} and \textbf{IV}, respectively. These tables are composed of three main columns that show neutron flux at the end of the S-shaped guide system and correspond to cold, thermal, and hot simulations. From the neutron intensity point of view, it is verified that colder neutron specters possess higher fluxes, since most of the hot and thermal neutrons are excluded from the profile by wavelength cutoff.
\begin{table}[hbt!]
\caption{Flux data results of the last run of simulations. Configurations of Table \ref{M_DIF_CASES_II} are carried out for three different ILL virtual sources, i.e., with cold, thermal, and hot neutron spectra. Cold and thermal fluxes, described respectively by the second and third columns, are given in $\times 10^9$~$n/cm^2s$, while hot results in the last column are in $\times 10^8$~$n/cm^2s$. Flux values come together with percentages between parenthesis that correspond to the ratio of each flux value next to the case A of each sequence. These percentages are just relative to cases \textbf{A} to \textbf{G} and their respective subcases, i.e., \textbf{i}, \textbf{ii}, and \textbf{iii}, and cases \textbf{A} are the standard comparison value (always with percentage $100$~$\%$). Results correspond to simulations of case \textbf{II} from Table \ref{tbl1}.}\label{FLUX_II}
\begin{tabular*}{\tblwidth}{@{} LLLL@{} }
\toprule
\multirow{3}{*}{\textbf{Case}} & \textbf{Cold} & \textbf{Thermal} & \textbf{Hot} \\
& $F_{cur}(R_{flux}^{abs})$ & $F_{cur}(R_{flux}^{abs})$ & $F_{cur}(R_{flux}^{abs})$ \\
& $ (\times 10^{9} n/cm^2s)$ & $ (\times 10^{9} n/cm^2s)$ & $ (\times 10^{8} n/cm^2s)$ \\
\midrule
\textbf{A$^{i}$} & 8.98 (100.00\%) & 3.40 (100.00\%) & 2.17 (100.00\%) \\
\textbf{B$^{i}$} & 8.99 (100.04\%) & 3.42 (100.50\%) & 2.14 (98.35\%) \\
\textbf{C$^{i}$} & 9.00 (100.22\%) & 3.44 (101.13\%) & 2.08 (95.73\%) \\
\textbf{D$^{i}$} & 9.00 (100.20\%) & 3.37 (99.23\%) & 2.17 (99.77\%) \\
\textbf{E$^{i}$} & 8.79 (97.84\%) & 3.11 (91.45\%) & 1.68 (77.53\%) \\
\textbf{F$^{i}$} & 8.72 (97.05\%) & 2.94 (86.46\%) & 1.50 (69.21\%) \\
\textbf{G$^{i}$} & 8.72 (97.05\%) & 2.95 (86.77\%) & 1.52 (69.78\%) \\
\textbf{A$^{ii}$} & 8.97 (100.00\%) & 3.39 (100.00\%) & 2.09 (100.00\%) \\
\textbf{B$^{ii}$} & 8.98 (100.08\%) & 3.41 (100.44\%) & 2.20 (105.42\%) \\
\textbf{C$^{ii}$} & 9.00 (100.30\%) & 3.36 (99.08\%) & 2.13 (101.99\%) \\
\textbf{D$^{ii}$} & 8.87 (98.82\%) & 3.30 (97.30\%) & 2.07 (99.44\%) \\
\textbf{E$^{ii}$} & 8.24 (91.86\%) & 2.53 (74.57\%) & 1.17 (56.33\%) \\
\textbf{F$^{ii}$} & 8.04 (89.62\%) & 2.35 (69.22\%) & 0.84 (40.13\%) \\
\textbf{G$^{ii}$} & 8.11 (90.45\%) & 2.31 (69.15\%) & 0.85 (40.69\%) \\
\textbf{A$^{iii}$} & 8.73 (100.00\%) & 3.01 (100.00\%) & 1.49 (100.00\%) \\
\textbf{B$^{iii}$} & 8.74 (100.18\%) & 3.01 (99.85\%) & 1.46 (97.70\%) \\
\textbf{C$^{iii}$} & 8.72 (99.93\%) & 3.02 (100.37\%) & 1.43 (95.75\%) \\
\textbf{D$^{iii}$} & 8.64 (99.03\%) & 2.90 (96.40\%) & 1.41 (94.45\%) \\
\textbf{E$^{iii}$} & 8.25 (94.49\%) & 2.48 (82.32\%) & 1.07 (71.77\%) \\
\textbf{F$^{iii}$} & 8.15 (93.35\%) & 2.34 (77.72\%) & 0.85 (57.19\%) \\
\textbf{G$^{iii}$} & 8.17 (93.62\%) & 2.30 (76.32\%) & 0.86 (57.40\%) \\
\bottomrule
\end{tabular*}
\vspace{-0.4cm}
\begin{flushleft}
{\footnotesize{$^i$ Combination of super mirror indexes of $m=3.0$ and $m=2.5$}}\\
{\footnotesize{$^{ii}$ Combination of super mirror indexes of $m=3.0$ and $m=2.0$}}\\
{\footnotesize{$^{iii}$ Combination of super mirror indexes of $m=2.5$ and $m=2.0$}}
\end{flushleft}
\end{table}
\begin{table}[hbt!]
\caption{Flux data results of the last run of simulations. Configurations of Table \ref{M_DIF_CASES_IV} are carried out for three different ILL virtual sources, i.e., with cold, thermal, and hot neutron spectra. Cold and thermal fluxes, described respectively by the second and third columns, are given in $\times 10^9$~$n/cm^2s$, while hot results in the last column are in $\times 10^8$~$n/cm^2s$. Flux values come together with percentages between parenthesis that correspond to the ratio of each flux value next to the case A of each sequence. These percentages are just relative to cases \textbf{A} to \textbf{G} and their respective subcases, i.e., \textbf{i}, \textbf{ii}, and \textbf{iii}, and cases \textbf{A} are the standard comparison value (always with percentage $100$~$\%$). Results correspond to simulations of case \textbf{Iv} from Table \ref{tbl1}.}\label{FLUX_IV}
\begin{tabular*}{\tblwidth}{@{} LLLL@{} }
\toprule
\multirow{3}{*}{\textbf{Case}} & \textbf{Cold} & \textbf{Thermal} & \textbf{Hot} \\
& $F_{cur}(R_{flux}^{abs})$ & $F_{cur}(R_{flux}^{abs})$ & $F_{cur}(R_{flux}^{abs})$ \\
& $ (\times 10^{9} n/cm^2s)$ & $ (\times 10^{9} n/cm^2s)$ & $ (\times 10^{8} n/cm^2s)$ \\
\midrule
\textbf{A$^{i}$} & 9.81 (100.00\%) & 3.54 (100.00\%) & 1.79 (100.00\%) \\
\textbf{B$^{i}$} & 9.87 (100.60\%) & 3.46 (97.64\%) & 1.77 (99.14\%) \\
\textbf{C$^{i}$} & 9.84 (100.34\%) & 3.47 (97.82\%) & 1.76 (98.30\%) \\
\textbf{D$^{i}$} & 9.81 (99.99\%) & 3.43 (96.84\%) & 1.80 (100.74\%) \\
\textbf{E$^{i}$} & 9.65 (98.37\%) & 3.18 (89.79\%) & 1.43 (79.83\%) \\
\textbf{F$^{i}$} & 9.48 (96.62\%) & 2.94 (83.10\%) & 1.21 (67.99\%) \\
\textbf{G$^{i}$} & 9.47 (96.50\%) & 2.95 (83.35\%) & 1.21 (67.72\%) \\
\textbf{A$^{ii}$} & 9.85 (100.00\%) & 3.53 (100.00\%) & 1.79 (100.00\%) \\
\textbf{B$^{ii}$} & 9.87 (100.18\%) & 3.46 (98.19\%) & 1.79 (100.21\%) \\
\textbf{C$^{ii}$} & 9.68 (98.22\%) & 3.35 (95.06\%) & 1.81 (101.25\%) \\
\textbf{D$^{ii}$} & 9.57 (97.14\%) & 3.38 (95.89\%) & 1.79 (99.89\%) \\
\textbf{E$^{ii}$} & 8.92 (90.54\%) & 2.55 (72.36\%) & 0.95 (52.87\%) \\
\textbf{F$^{ii}$} & 8.64 (87.69\%) & 2.24 (63.58\%) & 0.66 (36.76\%) \\
\textbf{G$^{ii}$} & 8.59 (87.69\%) & 2.22 (62.88\%) & 0.67 37.59\%) \\
\textbf{A$^{iii}$} & 9.48 (100.00\%) & 2.90 (100.00\%) & 1.22 (100.00\%) \\
\textbf{B$^{iii}$} & 9.50 (100.27\%) & 2.89 (99.59\%) & 1.20 (98.73\%) \\
\textbf{C$^{iii}$} & 9.39 (99.06\%) & 2.91 (100.49\%) & 1.23 (100.84\%) \\
\textbf{D$^{iii}$} & 9.37 (98.90\%) & 2.92 (100.88\%) & 1.15 (94.65\%) \\
\textbf{E$^{iii}$} & 9.16 (96.63\%) & 2.45 (84.43\%) & 0.85 (69.55\%) \\
\textbf{F$^{iii}$} & 8.57 (90.39\%) & 2.23 (77.04\%) & 0.67 (54.84\%) \\
\textbf{G$^{iii}$} & 8.56 (90.31\%) & 2.21 (76.33\%) & 0.66 (54.45\%) \\
\bottomrule
\end{tabular*}
\vspace{-0.4cm}
\begin{flushleft}
{\footnotesize{$^i$ Combination of super mirror indexes of $m=3.0$ and $m=2.5$}}\\
{\footnotesize{$^{ii}$ Combination of super mirror indexes of $m=3.0$ and $m=2.0$}}\\
{\footnotesize{$^{iii}$ Combination of super mirror indexes of $m=2.5$ and $m=2.0$}}
\end{flushleft}
\end{table}
\begin{figure}[hbt!]
\centering
\begin{subfigure}{.225\textwidth}
\centering
\includegraphics[width=.85\linewidth]{A_IV_HOT_3_2.png}
\caption{Case A$^{ii}$}
\label{case_A_ii_hot}
\end{subfigure}%
\begin{subfigure}{.225\textwidth}
\centering
\includegraphics[width=.85\linewidth]{B_IV_HOT_3_2.png}
\caption{Case B$^{ii}$}
\label{case_B_ii_hot}
\end{subfigure}
\begin{subfigure}{.225\textwidth}
\centering
\includegraphics[width=.85\linewidth]{C_IV_HOT_3_2.png}
\caption{Case C$^{ii}$}
\label{case_C_ii_hot}
\end{subfigure}
\begin{subfigure}{.225\textwidth}
\centering
\includegraphics[width=.85\linewidth]{D_IV_HOT_3_2.png}
\caption{Case D$^{ii}$}
\label{case_D_ii_hot}
\end{subfigure}
\begin{subfigure}{.225\textwidth}
\centering
\includegraphics[width=.85\linewidth]{E_IV_HOT_3_2.png}
\caption{Case E$^{ii}$}
\label{case_E_ii_hot}
\end{subfigure}
\begin{subfigure}{.225\textwidth}
\centering
\includegraphics[width=.85\linewidth]{F_IV_HOT_3_2.png}
\caption{Case F$^{ii}$}
\label{case_F_ii_hot}
\end{subfigure}
\caption{Acceptance diagrams at the end of the S-shaped guide system from simulations of cases $A^{ii}$, $B^{ii}$, $C^{ii}$, $D^{ii}$, $E^{ii}$, and $F^{ii}$ with ILL hot virtual source. Diagrams are obtained by considering the whole spectra, i.e., from $0$ to $20$ \AA. Ordinate and abscissa axes stand for guide width ($cm$) and vertical divergence (degrees). Minimal flux range, which is represented by white color, is fixed between $0$ and $1.40\times 10^5$~$n/cm^2s$, while other fluxes ranges come from ``cold'' colors (blue) to ``hot'' colors (red) in steps of $1.40\times 10^5$~$n/cm^2s$. }
\label{ad_diagram}
\end{figure}
To compare fluxes of different cases, i.e., \textbf{A} to \textbf{G}, percentages of each value next to case one are displayed after their values between parenthesis. Since \textbf{A} cases represent combinations of maximum coating index values, their percentages are always $100$~$\%$. Even though \textbf{A} cases are our standard, it is possible to find higher fluxes in other configurations, i.e., $>100$~$\%$, due to simulation errors. According to AD formalism and space phase tailoring, we consider configurations \textbf{D} the most promising scenario combining flux and divergence with lower coating indexes along with an S-shaped guide system. By checking Tables \ref{FLUX_II} and \ref{FLUX_IV}, it may be observed that cases \textbf{A}$^{ii}$, \textbf{B}$^{ii}$, \textbf{C}$^{ii}$, \textbf{D}$^{ii}$, \textbf{E}$^{ii}$, \textbf{F}$^{ii}$, and \textbf{G}$^{ii}$ of the ILL hot source present the most abrupt fall in neutron flux. ADs of these cases, except case G, are presented in Figure \ref{ad_diagram}. From these diagrams, we confirm that case \textbf{D} presents a similar flux to cases \textbf{A}, \textbf{B}, and \textbf{C}, but with lower coating indexes. By comparing Diagrams \ref{case_A_ii_hot} and \ref{case_D_ii_hot} it is not possible to identify phase space tailoring since the second straight guide is too short compared to the curved ones in the S-shaped guide system, i.e., each curved guide segment is about twenty-three times longer than this straight part.
The identification of the tailoring effect is easily achieved through monochromatic spectra, since every wavelength would possess a specific removal of neutrons of unwanted divergence. Nevertheless, tests with longer secondary guides have been carried out, and results from the process of phase space tailoring could be identified by checking neutron flux strip regularity of analyzed diagrams. Additional simulations are still necessary to investigate this process, but it has been left for future analysis.
\section{Conclusions}
\label{C}
In this work, three different aspects of minimal S-shaped guide systems, based on the shortest length for LoS exclusion, were investigated. The first topic consists of investigating the wavelength cutoff process according to curved guide arc ratios utilizing twelve simulation cases (\textbf{I} - \textbf{XII}) divided into three different scenarios (\textbf{a.}, \textbf{b.} and \textbf{c.}). Here, we propose a series of equations based in combinations of curved-straight and curved-curved guides. Such equations have been used on all simulated S-shaped guide systems taking into account the minimal length that guarantees LoS exclusion. Simulation results have shown that configuration \textbf{c.} is the shortest arrangement of an S-shaped guide system that excludes LoS, and it can maintain wavelength cutoff, which according to Gilles \cite{Gilles2006}, is the classic characteristic of any S-shaped guide. Thus, if wavelength cutoff is unwanted, one can still use configurations \textbf{a.} and \textbf{b.} to build guide systems. Since just configuration \textbf{c.} shows wavelength cutoff, all posterior simulations preserve such an arrangement.
Utilizing another series of simulations of different arc ratios, configuration \textbf{c.} was explored in scenarios with different primary and secondary straight guides and consequently different arc ratios. The results allow us to verify that both curved guides should have about $65$~$\%$ of their respective characteristic wavelength to impose a cutoff on the transported neutron profile. Both runs of simulations have produced results allowing to define the last sequence of tests.
The third and last sequence of simulations explore two aspects of S-shaped guide systems. It is given that a further analysis of the scenario $c$ considering different inner coating indexes is necessary, once in the first set of simulations, all indexes were kept the same, i.e., $m=3$. From this investigation, we intend to find the relation between inner coating indexes and wavelength cutoff. Thus, the validity of another proposed equation was tested, ``normalizing'' all coating indexes at the cost of curvature value changes. Besides, within this last set of simulations, we also intend to make a global comparison of coating index arrangements to define optimized configurations that provide maximum flux (compared with scenarios of the same index values) using lower indexes on some inner surfaces.
The former run of simulations indicates that configurations \textbf{a.} and \textbf{b.} are not able to impose wavelength cutoff on neutron profiles for twelve different S-shaped guide system arrangements. This occurs because both configurations are geometrically built based on taking the inner point of the concave surface as a limit to avoid LoS. This point possesses the same significance as any other in the trajectory that it represents according to AD formalism, however, it imposes an ideally maximum arc ratio of $50$~$\%$ (note that the connection of curved guides reduces the arc to lower values of $\Psi_C$). From this scenario, we conclude that it is impossible to have a system that minimally excludes LoS and also provides a cutoff. In this sense, we assume configuration $c$ as a standard of the minimal S-shaped guide system. Besides, using equal curvatures in \textbf{c.} allows us to possess symmetrical systems with parallel entrance and exit sections, e.g., cases \textbf{I}, \textbf{IV}, \textbf{VI}, \textbf{VII}, \textbf{X}, and \textbf{XII}.
Most simulated wavelength cutoff values of \textbf{c.} cases agree properly with theoretical values according to the present study equations, i.e., in eleven out of twelve cases, the difference between theoretical and simulated values was less than $10\%$. From these results, we have proposed another set of simulations based on a configuration with $\rho_2=2000$~$m$ and $\rho_3=1000$~$m$. Simulations have been carried out for twenty-one different arc ratios, from $40$~$\%$ to $80$~$\%$ in steps of $2$~$\%$. According to Equation \ref{L_P_S}, these number of ratios are the same number for different primary and secondary straight guide lengths in simulations. Results indicate a minimal arc ratio of $65$~$\%$ to an agreement of less than $5$~$\%$ between theoretical and simulated wavelength cutoff.
The last sequence of simulations is based on exploring cases \textbf{II} and \textbf{IV} for seven distinct coating arrangements to test the wavelength cutoff modified equation and also to select an optimized scenario that guarantees the best relation between neutron transportation and proper coating surface system. All simulations have been carried out for each of the ILL sources, i.e., hot, thermal, and cold. Due to the number of simulations, we have displayed statistical information in Table \ref{STAT} and from it, it is possible to verify that there is a good agreement between theoretical and simulated wavelength cutoffs. Considering all cases and sources, we observe a concordance of $60.32$~$\%$, i.e., 76 from 126 cases and $91.27$~$\%$, i.e., 115 from 126 cases for $5$~$\%$ and $10$~$\%$ ranges between theoretical and simulated, respectively.
Here we observe that cold source results, mainly for case \textbf{II}, possess worse agreement compared to others. We believe that is due to the number of rays ($10^7$) used in present MCSTAS simulations, since wavelength cutoff occurs close to thermal and hot spectra peaks, where these profiles have more neutrons than the cold profile. Thus, there are statistically fewer neutrons to determine the wavelength cutoff for cold sources than for hot and thermal ones. Nevertheless, and considering simulation errors, we conclude that these results confirm the validity of the applied equations. Analyzing flux values, we have been able to keep configuration \textbf{D} as a standard configuration since it maintains a slightly lower difference next to configuration \textbf{A}. In this sense, it maintains the phase space tailoring and also represents an optimized configuration as to engineering and financial terms. These aspects are reiterated since the guide design geometrically offers the shortest S-shaped guide systems excluding LoS with, or without, wavelength cutoff. Last, but not least, all the formalism presented in this study allows us to project different guide systems employing curved-straight and curved-curved guides combination, depending on the design requirements.
We finally conclude that the outcome of this study may be applied in many scenarios where guide sections present misalignment or significant vertical or horizontal displacements. The former may be used in the ESS case, where installation ground gradually sinks, and total displacements are tens of centimeters. For this scenario, we presume that the wavelength cutoff and the LoS are essential aspects. The latter case of applications comprehends situations of adapting new instruments in operating facilities or transferring instruments from different center places or inter-centers. In this scenario, we intend to propose an installation of a new SANS instrument at the Brazilian IEA-R1 reactor. There, the neutron hall does not have enough space for long or large instruments, which could be solved by moving the neutron beam exit to the upper floor. The viability of this installation through S-shaped guide systems is left for future works.
\section*{Acknowledgement}
The authors are thankful to the technical coordinator of the Brazilian Multipurpose Reactor (RMB) Project, Dr. J.A. Perrotta. A.P.S. Souza and L.P. de Oliveira also would like to thank CNPq for financial support under grant numbers 381565/2018-1 and 380183/2019-6, respectively.
\bibliographystyle{JHEP2}
\section{Introduction}
Two classfiles namely \file{cas-sc.cls} and \file{cas-dc.cls} were
written for typesetting articles submitted in journals of Elsevier's
Complex Article Service (CAS) workflow.
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and have an option longmktitle to handle long front matter.
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project funded by the National Science Foundation.}
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\author[1,3]{CV Radhakrishnan}[type=editor,
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prefix=Sir,
role=Researcher,
orcid=0000-0001-7511-2910]
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\credit{Conceptualization of this study, Methodology,
Software}
\address[1]{Elsevier B.V., Radarweg 29, 1043 NX Amsterdam,
The Netherlands}
\author[2,4]{Han Theh Thanh}[style=chinese]
\author[2,3]{CV Rajagopal}[%
role=Co-ordinator,
suffix=Jr,
]
\fnmark[2]
\ead{cvr3@sayahna.org}
\ead[URL]{www.sayahna.org}
\credit{Data curation, Writing - Original draft preparation}
\address[2]{Sayahna Foundation, Jagathy, Trivandrum 695014,
India}
\author[1,3]{Rishi T.}
\cormark[2]
\fnmark[1,3]
\ead{rishi@stmdocs.in}
\ead[URL]{www.stmdocs.in}
\address[3]{STM Document Engineering Pvt Ltd., Mepukada,
Malayinkil, Trivandrum 695571, India}
\cortext[cor1]{Corresponding author}
\cortext[cor2]{Principal corresponding author}
\fntext[fn1]{This is the first author footnote. but is common
to third author as well.}
\fntext[fn2]{Another author footnote, this is a very long
footnote and it should be a really long footnote. But this
footnote is not yet sufficiently long enough to make two lines
of footnote text.}
\end{vquote}
\begin{vquote}
\nonumnote{This note has no numbers. In this work we
demonstrate $a_b$ the formation Y\_1 of a new type of
polariton on the interface between a cuprous oxide slab
and a polystyrene micro-sphere placed on the slab.
}
\begin{abstract}[S U M M A R Y]
This template helps you to create a properly formatted
\LaTeX\ manuscript.
\noindent\texttt{\textbackslash begin{abstract}} \dots
\texttt{\textbackslash end{abstract}} and
\verb+\begin{keyword}+ \verb+...+ \verb+\end{keyword}+
which contain the abstract and keywords respectively.
Each keyword shall be separated by a \verb+\sep+ command.
\end{abstract}
\begin{keywords}
quadrupole exciton \sep polariton \sep \WGM \sep \BEC
\end{keywords}
\maketitle
\end{vquote}
\begin{figure}
\includegraphics[width=\textwidth]{sc-sample.pdf}
\caption{Single column output (classfile: cas-sc.cls).}
\end{figure}
\begin{figure}
\includegraphics[width=\textwidth]{dc-sample.pdf}
\caption{Double column output (classfile: cas-dc.cls).}
\end{figure}
\subsection{Title}
\verb+\title+ command have the below options:
\begin{enumerate}
\item \verb+title:+ Document title
\item \verb+alt:+ Alternate title
\item \verb+sub:+ Sub title
\item \verb+trans:+ Translated title
\item \verb+transsub:+ Translated sub title
\end{enumerate}
\begin{vquote}
\title[mode=title]{This is a title}
\title[mode=alt]{This is a alternate title}
\title[mode=sub]{This is a sub title}
\title[mode=trans]{This is a translated title}
\title[mode=transsub]{This is a translated sub title}
\end{vquote}
\subsection{Author}
\verb+\author+ command have the below options:
\begin{enumerate}
\item \verb+auid:+ Author id
\item \verb+bioid:+ Biography id
\item \verb+alt:+ Alternate author
\item \verb+style:+ Style of author name chinese
\item \verb+prefix:+ Prefix Sir
\item \verb+suffix:+ Suffix
\item \verb+degree:+ Degree
\item \verb+role:+ Role
\item \verb+orcid:+ ORCID
\item \verb+collab:+ Collaboration
\item \verb+anon:+ Anonymous author
\item \verb+deceased:+ Deceased author
\item \verb+twitter:+ Twitter account
\item \verb+facebook:+ Facebook account
\item \verb+linkedin:+ LinkedIn account
\item \verb+plus:+ Google plus account
\item \verb+gplus:+ Google plus account
\end{enumerate}
\begin{vquote}
\author[1,3]{Author Name}[type=editor,
auid=000,bioid=1,
prefix=Sir,
role=Researcher,
orcid=0000-0001-7511-2910,
facebook=<facebook id>,
twitter=<twitter id>,
linkedin=<linkedin id>,
gplus=<gplus id>]
\end{vquote}
\subsection{Various Marks in the Front Matter}
The front matter becomes complicated due to various kinds
of notes and marks to the title and author names. Marks in
the title will be denoted by a star ($\star$) mark;
footnotes are denoted by super scripted Arabic numerals,
corresponding author by of an Conformal asterisk (*) mark.
\subsubsection{Title marks}
Title mark can be entered by the command, \verb+\tnotemark[<num>]+
and the corresponding text can be entered with the command
\verb+\tnotetext[<num>]+ \verb+{<text>}+. An example will be:
\begin{vquote}
\title[mode=title]{Leveraging social media news to predict
stock index movement using RNN-boost}
\tnotemark[1,2]
\tnotetext[1]{This document is the results of the research
project funded by the National Science Foundation.}
\tnotetext[2]{The second title footnote which is a longer
text matter to fill through the whole text width and
overflow into another line in the footnotes area of
the first page.}
\end{vquote}
\verb+\tnotetext+ and \verb+\tnotemark+ can be anywhere in
the front matter, but shall be before \verb+\maketitle+ command.
\subsubsection{Author marks}
Author names can have many kinds of marks and notes:
\begin{vquote}
footnote mark : \fnmark[<num>]
footnote text : \fntext[<num>]{<text>}
affiliation mark : \author[<num>]
email : \ead{<emailid>}
url : \ead[url]{<url>}
corresponding author mark : \cormark[<num>]
corresponding author text : \cortext[<num>]{<text>}
\end{vquote}
\subsubsection{Other marks}
At times, authors want footnotes which leave no marks in
the author names. The note text shall be listed as part of
the front matter notes. Class files provides
\verb+\nonumnote+ for this purpose. The usage
\begin{vquote}
\nonumnote{<text>}
\end{vquote}
\noindent and should be entered anywhere before the \verb+\maketitle+
command for this to take effect.
\subsection{Abstract and Keywords}
Abstract shall be entered in an environment that starts
with \verb+\begin{abstract}+ and ends with
\verb+\end{abstract}+. Longer abstracts spanning more than
one page is also possible in Class file even in double
column mode. We need to invoke longmktitle option in the
class loading line for this to happen smoothly.
The key words are enclosed in a \verb+{keyword}+
environment.
\begin{vquote}
\begin{abstract}
This is a abstract. \lipsum[3]
\end{abstract}
\begin{keywords}
First keyword \sep Second keyword \sep Third
keyword \sep Fourth keyword
\end{keywords}
\end{vquote}
\section{Main Matter}
\subsection{Tables}
\subsubsection{Normal tables}
\begin{vquote}
\begin{table}
\caption{This is a test caption.}
\begin{tabular*}{\tblwidth}{@{} LLLL@{} }
\toprule
Col 1 & Col 2\\
\midrule
12345 & 12345\\
12345 & 12345\\
12345 & 12345\\
\bottomrule
\end{tabular*}
\end{table}
\end{vquote}
\subsubsection{Span tables}
\begin{vquote}
\begin{table*}[width=.9\textwidth,cols=4,pos=h]
\caption{This is a test caption.}
\begin{tabular*}{\tblwidth}{@{} LLLLLL@{} }
\toprule
Col 1 & Col 2 & Col 3 & Col4 & Col5 & Col6 & Col7\\
\midrule
12345 & 12345 & 123 & 12345 & 123 & 12345 & 123 \\
12345 & 12345 & 123 & 12345 & 123 & 12345 & 123 \\
12345 & 12345 & 123 & 12345 & 123 & 12345 & 123 \\
\bottomrule
\end{tabular*}
\end{table*}
\end{vquote}
\subsection{Figures}
\subsubsection{Normal figures}
\begin{vquote}
\begin{figure}
\centering
\includegraphics[scale=.75]{Fig1.pdf}
\caption{The evanescent light - $1S$ quadrupole coupling
($g_{1,l}$) scaled to the bulk exciton-photon coupling
($g_{1,2}$). The size parameter $kr_{0}$ is denoted as $x$ and
the \PMS is placed directly on the cuprous oxide sample ($\delta
r=0$, See also Fig. \protect\ref{FIG:2}).}
\label{FIG:1}
\end{figure}
\end{vquote}
\subsubsection{Span figures}
\begin{vquote}
\begin{figure*}
\centering
\includegraphics[width=\textwidth,height=2in]{Fig2.pdf}
\caption{Schematic of formation of the evanescent polariton on
linear chain of \PMS. The actual dispersion is determined by
the ratio of two coupling parameters such as exciton-\WGM
coupling and \WGM-\WGM coupling between the microspheres.}
\label{FIG:2}
\end{figure*}\end{vquote}
\subsection{Theorem and theorem like environments}
CAS class file provides a few hooks to format theorems and
theorem like environments with ease. All commands the
options that are used with \verb+\newtheorem+ command will work
exactly in the same manner. Class file provides three
commands to format theorem or theorem like environments:
\begin{enumerate}
\item \verb+\newtheorem+ command formats a theorem in
\LaTeX's default style with italicized font for theorem
statement, bold weight for theorem heading and theorem
number typeset at the right of theorem heading. It also
optionally accepts an argument which will be printed as an
extra heading in parentheses. Here is an example coding and
output:
\begin{vquote}
\newtheorem{theorem}{Theorem}
\begin{theorem}\label{thm}
The \WGM evanescent field penetration depth into the
cuprous oxide adjacent crystal is much larger than the
\QE radius:
\begin{equation*}
\lambda_{1S}/2 \pi \left({\epsilon_{Cu2O}-1}
\right)^{1/2} = 414 \mbox{ \AA} \gg a_B = 4.6
\mbox{ \AA}
\end{equation*}
\end{theorem}
\end{vquote}
\item \verb+\newdefinition+ command does exactly the same
thing as with except that the body font is up-shape instead
of italic. See the example below:
\begin{vquote}
\newdefinition{definition}{Definition}
\begin{definition}
The bulk and evanescent polaritons in cuprous oxide
are formed through the quadrupole part of the light-matter
interaction:
\begin{equation*}
H_{int} = \frac{i e }{m \omega_{1S}} {\bf E}_{i,s}
\cdot {\bf p}
\end{equation*}
\end{definition}
\end{vquote}
\item \verb+\newproof+ command helps to define proof and
custom proof environments without counters as provided in
the example code. Given below is an example of proof of
theorem kind.
\begin{vquote}
\newproof{pot}{Proof of Theorem \ref{thm}}
\begin{pot}
The photon part of the polariton trapped inside the \PMS
moves as it would move in a micro-cavity of the effective
modal volume $V \ll 4 \pi r_{0}^{3} /3$. Consequently, it
can escape through the evanescent field. This evanescent
field essentially has a quantum origin and is due to
tunneling through the potential caused by dielectric
mismatch on the \PMS surface. Therefore, we define the
\emph{evanescent} polariton (\EP) as an evanescent light -
\QE coherent superposition.
\end{pot}
\end{vquote}
\end{enumerate}
\subsection{Enumerated and Itemized Lists}
CAS class files provides an extended list processing macros
which makes the usage a bit more user friendly than the
default LaTeX list macros. With an optional argument to the
\verb+\begin{enumerate}+ command, you can change the list
counter type and its attributes. You can see the coding and
typeset copy.
\begin{vquote}
\begin{enumerate}[1.]
\item The enumerate environment starts with an optional
argument `1.' so that the item counter will be suffixed
by a period as in the optional argument.
\item If you provide a closing parenthesis to the number in the
optional argument, the output will have closing
parenthesis for all the item counters.
\item You can use `(a)' for alphabetical counter and `(i)' for
roman counter.
\begin{enumerate}[a)]
\item Another level of list with alphabetical counter.
\item One more item before we start another.
\begin{enumerate}[(i)]
\item This item has roman numeral counter.
\end{vquote}
\begin{vquote}
\item Another one before we close the third level.
\end{enumerate}
\item Third item in second level.
\end{enumerate}
\item All list items conclude with this step.
\end{enumerate}
\section{Biography}
\verb+\bio+ command have the below options:
\begin{enumerate}
\item \verb+width:+ Width of the author photo (default is 1in).
\item \verb+pos:+ Position of author photo.
\end{enumerate}
\begin{vquote}
\bio[width=10mm,pos=l]{tuglogo.jpg}
\textbf{Another Biography:}
Recent experimental \cite{HARA:2005} and theoretical
\cite{DEYCH:2006} studies have shown that the \WGM can travel
along the chain as "heavy photons". Therefore the \WGM
acquires the spatial dispersion, and the evanescent
quadrupole polariton has the form (See Fig.\ref{FIG:3}):
\endbio
\end{vquote}
\section[CRediT...]{CRediT authorship contribution statement}
Give the authorship contribution after each author as
\begin{vquote}
\credit{Conceptualization of this study, Methodology,
Software}
\end{vquote}
To print the details use \verb+\printcredits+
\begin{vquote}
\author[1,3]{V. {{\=A}}nand Rawat}[auid=000,
bioid=1,
prefix=Sir,
role=Researcher,
orcid=0000-0001-7511-2910]
\end{vquote}
\begin{vquote}
\cormark[1]
\fnmark[1]
\ead{cvr_1@tug.org.in}
\ead[url]{www.cvr.cc, www.tug.org.in}
\credit{Conceptualization of this study, Methodology,
Software}
\address[1]{Indian \TeX{} Users Group, Trivandrum 695014,
India}
\author[2,4]{Han Theh Thanh}[style=chinese]
\author[2,3]{T. Rishi Nair}[role=Co-ordinator,
suffix=Jr]
\fnmark[2]
\ead{rishi@sayahna.org}
\ead[URL]{www.sayahna.org}
\credit{Data curation, Writing - Original draft preparation}
. . .
. . .
. . .
\printcredits
\end{vquote}
\section{Bibliography}
For CAS categories, two reference models are recommended.
They are \file{model1-num-names.bst} and \file{model2-names.bst}.
Former will format the reference list and their citations according to
numbered scheme whereas the latter will format according name-date or
author-year style. Authors are requested to choose any one of these
according to the journal style. You may download these from
The above bsts are available in the following location for you to
download:
\url{https://support.stmdocs.in/wiki/index.php?title=Model-wise_bibliographic_style_files}
\hfill $\Box$
\end{document}
|
{
"redpajama_set_name": "RedPajamaArXiv"
}
| 291
|
#ifndef MRUBY_GC_H
#define MRUBY_GC_H
#include "common.h"
/**
* Uncommon memory management stuffs.
*/
MRB_BEGIN_DECL
struct mrb_state;
#define MRB_EACH_OBJ_OK 0
#define MRB_EACH_OBJ_BREAK 1
typedef int (mrb_each_object_callback)(struct mrb_state *mrb, struct RBasic *obj, void *data);
void mrb_objspace_each_objects(struct mrb_state *mrb, mrb_each_object_callback *callback, void *data);
MRB_API void mrb_free_context(struct mrb_state *mrb, struct mrb_context *c);
#ifndef MRB_GC_ARENA_SIZE
#define MRB_GC_ARENA_SIZE 100
#endif
typedef enum {
MRB_GC_STATE_ROOT = 0,
MRB_GC_STATE_MARK,
MRB_GC_STATE_SWEEP
} mrb_gc_state;
typedef struct mrb_heap_page {
struct RBasic *freelist;
struct mrb_heap_page *prev;
struct mrb_heap_page *next;
struct mrb_heap_page *free_next;
struct mrb_heap_page *free_prev;
mrb_bool old:1;
void *objects[];
} mrb_heap_page;
typedef struct mrb_gc {
mrb_heap_page *heaps; /* heaps for GC */
mrb_heap_page *sweeps;
mrb_heap_page *free_heaps;
size_t live; /* count of live objects */
#ifdef MRB_GC_FIXED_ARENA
struct RBasic *arena[MRB_GC_ARENA_SIZE]; /* GC protection array */
#else
struct RBasic **arena; /* GC protection array */
int arena_capa;
#endif
int arena_idx;
mrb_gc_state state; /* state of gc */
int current_white_part; /* make white object by white_part */
struct RBasic *gray_list; /* list of gray objects to be traversed incrementally */
struct RBasic *atomic_gray_list; /* list of objects to be traversed atomically */
size_t live_after_mark;
size_t threshold;
int interval_ratio;
int step_ratio;
mrb_bool iterating :1;
mrb_bool disabled :1;
mrb_bool full :1;
mrb_bool generational :1;
mrb_bool out_of_memory :1;
size_t majorgc_old_threshold;
} mrb_gc;
MRB_API mrb_bool
mrb_object_dead_p(struct mrb_state *mrb, struct RBasic *object);
MRB_END_DECL
#endif /* MRUBY_GC_H */
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 9,219
|
Android Studio – the default development environment for Android developers, with an update to 3.2 has brought about interesting changes to the Android Studio ecosystem.
This feature enables developers to snap the recent state of the emulator as and when needed. A snapshot preserves the entire state of the device at the saved time. This includes OS settings, application state and user data. Users can load the saved state by opening the snapshot, thus saving time. Snapping a shot is even faster, comparatively to save and load in this stable release. This is due to the under-the-hood speed enhancements. Therefore developers or testers can accelerate the speed of test run using the Android Emulator Snapshots.
This is one of the vital features in Android 3.2. It helps developers in understanding the energy impact of the application on an Android device. Developers can visualize the estimated energy usage of system components and can inspect background events due to which battery drains. They can effectively manage the power consumption of apps in different scenarios, thus improvising the battery life of the device.
To visualize the look and feel of a layout while designing the app, developers can add sample preview data to TextView, ImageView, or a RecyclerView from within the Layout Editor. This aids in the design of layouts that depend on run time data.
While migrating from the Android Design support library to the new Material Components app theme and library, Android Studio 3.2 will offer access to new and updated widgets such as buttons, card layouts, text views, new font styles and more. Developers can now easily migrate from old library to new AndroidX packages with the refactoring tools.
Android Studio 3.2 comes with Kotlin 1.2.61, with support for the Kotlin-friendly latest Android version – 9 Pie SDK.
This is the new app publishing format that is designed to help deliver smaller APKs to users and to reduce the download size of android application. Google Play's new app serving model, called Dynamic Delivery, processes app bundle to generate and serve optimized APKs for each user's device configuration, so they download only the code and resources they need to run the app. With Android Studio 3.2 or via the command line, we can easily build your code as an app bundle and get the benefit of smaller APKs based on language, screen density, and ABIs with no changes to app code.
Slices are UI templates that embeds portions of app in other user interfaces on android. It displays rich and dynamic content. For example, using Slices it is possible to show app functionality and content in Google Search suggestions. The built in template in android studio 3.2 helps in extending the app with the Slice Provider APIs as well as new lint checks to ensure that you're following best practices when constructing the Slices.
Jetpack has been updated and improved and has made the overall development process much smoother and easier. It minimizes repetitive work and thus helps in streamlining the development workflow.
With these new changes in android studio 3.2, some cool new smart features have been incorporated, which are sure to help the developers create better and faster apps more efficiently and save a lot of their development time.
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 7,249
|
Douglas Turner (Reino Unido, 2 de diciembre de 1966) es un atleta británico retirado especializado en la prueba de 200 m, en la que ha conseguido ser subcampeón europeo en 1998.
Carrera deportiva
En el Campeonato Europeo de Atletismo de 1998 ganó la medalla de plata en los 200 metros, con un tiempo de 20.64 segundos, llegando a meta tras su compatriota Douglas Walker y por delante de otro británico Julian Golding (bronce con 20.72 s).
Referencias
Atletas de Reino Unido
|
{
"redpajama_set_name": "RedPajamaWikipedia"
}
| 2,913
|
{"url":"http:\/\/www.physicsforums.com\/showthread.php?t=135556","text":"# Centripetal Force\n\nby Vesper89\nTags: centripetal, force\n Mentor P: 41,310 There are two equivalent expressions for centripetal force: $$F_c = m v^2\/r$$ or $$F_c = m \\omega^2 r$$ Since $v = \\omega r$, the two expressions are equivalent. ($\\omega$ is the angular speed; it equals the frequency times $2 \\pi$.) Since you are holding the frequency constant while you vary the radius, your results will follow the 2nd equation. If you held the speed constant as you varied the radius, your results would be described by the first equation.","date":"2014-07-29 06:46:39","metadata":"{\"extraction_info\": {\"found_math\": true, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 0, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 1, \"mathjax_display_tex\": 1, \"mathjax_asciimath\": 0, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 0, \"wp-katex-eq\": 0, \"align\": 0, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.8001102209091187, \"perplexity\": 709.9477878750514}, \"config\": {\"markdown_headings\": true, \"markdown_code\": true, \"boilerplate_config\": {\"ratio_threshold\": 0.18, \"absolute_threshold\": 10, \"end_threshold\": 15, \"enable\": true}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2014-23\/segments\/1406510266597.23\/warc\/CC-MAIN-20140728011746-00134-ip-10-146-231-18.ec2.internal.warc.gz\"}"}
| null | null |
#include <sys/cdefs.h>
__FBSDID("$FreeBSD: soc2013/dpl/head/sys/dev/aacraid/aacraid_debug.c 252169 2013-05-24 09:22:43Z achim $");
/*
* Debugging support.
*/
#include "opt_aacraid.h"
#include <sys/param.h>
#include <sys/systm.h>
#include <sys/kernel.h>
#include <sys/conf.h>
#include <sys/bus.h>
#include <machine/resource.h>
#include <machine/bus.h>
#include <dev/aacraid/aacraid_reg.h>
#include <sys/aac_ioctl.h>
#include <dev/aacraid/aacraid_var.h>
#include <sys/param.h>
#include <sys/systm.h>
#include <sys/kernel.h>
#include <sys/conf.h>
#include <sys/bus.h>
#include <sys/rman.h>
#include <machine/resource.h>
#include <machine/bus.h>
#include <machine/stdarg.h>
#include <dev/aacraid/aacraid_debug.h>
#ifdef AACRAID_DEBUG
/*
* Dump the command queue indices
*/
void
aacraid_print_queues(struct aac_softc *sc)
{
device_printf(sc->aac_dev, "AACQ_FREE %d/%d\n",
sc->aac_qstat[AACQ_FREE].q_length, sc->aac_qstat[AACQ_FREE].q_max);
device_printf(sc->aac_dev, "AACQ_READY %d/%d\n",
sc->aac_qstat[AACQ_READY].q_length,
sc->aac_qstat[AACQ_READY].q_max);
device_printf(sc->aac_dev, "AACQ_BUSY %d/%d\n",
sc->aac_qstat[AACQ_BUSY].q_length, sc->aac_qstat[AACQ_BUSY].q_max);
}
/*
* Print a FIB
*/
void
aacraid_print_fib(struct aac_softc *sc, struct aac_fib *fib, const char *caller)
{
if (fib == NULL) {
device_printf(sc->aac_dev,
"aac_print_fib called with NULL fib\n");
return;
}
device_printf(sc->aac_dev, "%s: FIB @ %p\n", caller, fib);
device_printf(sc->aac_dev, " XferState %b\n", fib->Header.XferState,
"\20"
"\1HOSTOWNED"
"\2ADAPTEROWNED"
"\3INITIALISED"
"\4EMPTY"
"\5FROMPOOL"
"\6FROMHOST"
"\7FROMADAP"
"\10REXPECTED"
"\11RNOTEXPECTED"
"\12DONEADAP"
"\13DONEHOST"
"\14HIGH"
"\15NORM"
"\16ASYNC"
"\17PAGEFILEIO"
"\20SHUTDOWN"
"\21LAZYWRITE"
"\22ADAPMICROFIB"
"\23BIOSFIB"
"\24FAST_RESPONSE"
"\25APIFIB\n");
device_printf(sc->aac_dev, " Command %d\n", fib->Header.Command);
device_printf(sc->aac_dev, " StructType %d\n",
fib->Header.StructType);
device_printf(sc->aac_dev, " Size %d\n", fib->Header.Size);
device_printf(sc->aac_dev, " SenderSize %d\n",
fib->Header.SenderSize);
device_printf(sc->aac_dev, " SenderAddress 0x%x\n",
fib->Header.SenderFibAddress);
device_printf(sc->aac_dev, " RcvrAddress 0x%x\n",
fib->Header.u.ReceiverFibAddress);
device_printf(sc->aac_dev, " Handle 0x%x\n",
fib->Header.Handle);
switch(fib->Header.Command) {
case ContainerCommand:
{
struct aac_blockread *br;
struct aac_blockwrite *bw;
struct aac_sg_table *sg;
int i;
br = (struct aac_blockread*)fib->data;
bw = (struct aac_blockwrite*)fib->data;
sg = NULL;
if (br->Command == VM_CtBlockRead) {
device_printf(sc->aac_dev,
" BlockRead: container %d 0x%x/%d\n",
br->ContainerId, br->BlockNumber,
br->ByteCount);
sg = &br->SgMap;
}
if (bw->Command == VM_CtBlockWrite) {
device_printf(sc->aac_dev,
" BlockWrite: container %d 0x%x/%d "
"(%s)\n", bw->ContainerId,
bw->BlockNumber, bw->ByteCount,
bw->Stable == CSTABLE ? "stable" :
"unstable");
sg = &bw->SgMap;
}
if (sg != NULL) {
device_printf(sc->aac_dev,
" %d s/g entries\n", sg->SgCount);
for (i = 0; i < sg->SgCount; i++)
device_printf(sc->aac_dev, " 0x%08x/%d\n",
sg->SgEntry[i].SgAddress,
sg->SgEntry[i].SgByteCount);
}
break;
}
default:
device_printf(sc->aac_dev, " %16D\n", fib->data, " ");
device_printf(sc->aac_dev, " %16D\n", fib->data + 16, " ");
break;
}
}
/*
* Describe an AIF we have received.
*/
void
aacraid_print_aif(struct aac_softc *sc, struct aac_aif_command *aif)
{
switch(aif->command) {
case AifCmdEventNotify:
device_printf(sc->aac_dev, "EventNotify(%d)\n", aif->seqNumber);
switch(aif->data.EN.type) {
case AifEnGeneric: /* Generic notification */
device_printf(sc->aac_dev, "(Generic) %.*s\n",
(int)sizeof(aif->data.EN.data.EG),
aif->data.EN.data.EG.text);
break;
case AifEnTaskComplete: /* Task has completed */
device_printf(sc->aac_dev, "(TaskComplete)\n");
break;
case AifEnConfigChange: /* Adapter configuration change
* occurred */
device_printf(sc->aac_dev, "(ConfigChange)\n");
break;
case AifEnContainerChange: /* Adapter specific container
* configuration change */
device_printf(sc->aac_dev, "(ContainerChange) "
"container %d,%d\n",
aif->data.EN.data.ECC.container[0],
aif->data.EN.data.ECC.container[1]);
break;
case AifEnDeviceFailure: /* SCSI device failed */
device_printf(sc->aac_dev, "(DeviceFailure) "
"handle %d\n",
aif->data.EN.data.EDF.deviceHandle);
break;
case AifEnMirrorFailover: /* Mirror failover started */
device_printf(sc->aac_dev, "(MirrorFailover) "
"container %d failed, "
"migrating from slice %d to %d\n",
aif->data.EN.data.EMF.container,
aif->data.EN.data.EMF.failedSlice,
aif->data.EN.data.EMF.creatingSlice);
break;
case AifEnContainerEvent: /* Significant container
* event */
device_printf(sc->aac_dev, "(ContainerEvent) "
"container %d event "
"%d\n", aif->data.EN.data.ECE.container,
aif->data.EN.data.ECE.eventType);
break;
case AifEnFileSystemChange: /* File system changed */
device_printf(sc->aac_dev, "(FileSystemChange)\n");
break;
case AifEnConfigPause: /* Container pause event */
device_printf(sc->aac_dev, "(ConfigPause)\n");
break;
case AifEnConfigResume: /* Container resume event */
device_printf(sc->aac_dev, "(ConfigResume)\n");
break;
case AifEnFailoverChange: /* Failover space assignment
* changed */
device_printf(sc->aac_dev, "(FailoverChange)\n");
break;
case AifEnRAID5RebuildDone: /* RAID5 rebuild finished */
device_printf(sc->aac_dev, "(RAID5RebuildDone)\n");
break;
case AifEnEnclosureManagement: /* Enclosure management event */
device_printf(sc->aac_dev, "(EnclosureManagement) "
"EMPID %d unit %d "
"event %d\n", aif->data.EN.data.EEE.empID,
aif->data.EN.data.EEE.unitID,
aif->data.EN.data.EEE.eventType);
break;
case AifEnBatteryEvent: /* Significant NV battery
* event */
device_printf(sc->aac_dev, "(BatteryEvent) %d "
"(state was %d, is %d\n",
aif->data.EN.data.EBE.transition_type,
aif->data.EN.data.EBE.current_state,
aif->data.EN.data.EBE.prior_state);
break;
case AifEnAddContainer: /* A new container was
* created. */
device_printf(sc->aac_dev, "(AddContainer)\n");
break;
case AifEnDeleteContainer: /* A container was deleted. */
device_printf(sc->aac_dev, "(DeleteContainer)\n");
break;
case AifEnBatteryNeedsRecond: /* The battery needs
* reconditioning */
device_printf(sc->aac_dev, "(BatteryNeedsRecond)\n");
break;
case AifEnClusterEvent: /* Some cluster event */
device_printf(sc->aac_dev, "(ClusterEvent) event %d\n",
aif->data.EN.data.ECLE.eventType);
break;
case AifEnDiskSetEvent: /* A disk set event occured. */
device_printf(sc->aac_dev, "(DiskSetEvent) event %d "
"diskset %jd creator %jd\n",
aif->data.EN.data.EDS.eventType,
(intmax_t)aif->data.EN.data.EDS.DsNum,
(intmax_t)aif->data.EN.data.EDS.CreatorId);
break;
case AifDenMorphComplete: /* A morph operation
* completed */
device_printf(sc->aac_dev, "(MorphComplete)\n");
break;
case AifDenVolumeExtendComplete: /* A volume expand operation
* completed */
device_printf(sc->aac_dev, "(VolumeExtendComplete)\n");
break;
default:
device_printf(sc->aac_dev, "(%d)\n", aif->data.EN.type);
break;
}
break;
case AifCmdJobProgress:
{
char *status;
switch(aif->data.PR[0].status) {
case AifJobStsSuccess:
status = "success"; break;
case AifJobStsFinished:
status = "finished"; break;
case AifJobStsAborted:
status = "aborted"; break;
case AifJobStsFailed:
status = "failed"; break;
case AifJobStsSuspended:
status = "suspended"; break;
case AifJobStsRunning:
status = "running"; break;
default:
status = "unknown status"; break;
}
device_printf(sc->aac_dev, "JobProgress (%d) - %s (%d, %d)\n",
aif->seqNumber, status,
aif->data.PR[0].currentTick,
aif->data.PR[0].finalTick);
switch(aif->data.PR[0].jd.type) {
case AifJobScsiZero: /* SCSI dev clear operation */
device_printf(sc->aac_dev, "(ScsiZero) handle %d\n",
aif->data.PR[0].jd.client.scsi_dh);
break;
case AifJobScsiVerify: /* SCSI device Verify operation
* NO REPAIR */
device_printf(sc->aac_dev, "(ScsiVerify) handle %d\n",
aif->data.PR[0].jd.client.scsi_dh);
break;
case AifJobScsiExercise: /* SCSI device Exercise
* operation */
device_printf(sc->aac_dev, "(ScsiExercise) handle %d\n",
aif->data.PR[0].jd.client.scsi_dh);
break;
case AifJobScsiVerifyRepair: /* SCSI device Verify operation
* WITH repair */
device_printf(sc->aac_dev,
"(ScsiVerifyRepair) handle %d\n",
aif->data.PR[0].jd.client.scsi_dh);
break;
case AifJobCtrZero: /* Container clear operation */
device_printf(sc->aac_dev,
"(ContainerZero) container %d\n",
aif->data.PR[0].jd.client.container.src);
break;
case AifJobCtrCopy: /* Container copy operation */
device_printf(sc->aac_dev,
"(ContainerCopy) container %d to %d\n",
aif->data.PR[0].jd.client.container.src,
aif->data.PR[0].jd.client.container.dst);
break;
case AifJobCtrCreateMirror: /* Container Create Mirror
* operation */
device_printf(sc->aac_dev,
"(ContainerCreateMirror) container %d\n",
aif->data.PR[0].jd.client.container.src);
/* XXX two containers? */
break;
case AifJobCtrMergeMirror: /* Container Merge Mirror
* operation */
device_printf(sc->aac_dev,
"(ContainerMergeMirror) container %d\n",
aif->data.PR[0].jd.client.container.src);
/* XXX two containers? */
break;
case AifJobCtrScrubMirror: /* Container Scrub Mirror
* operation */
device_printf(sc->aac_dev,
"(ContainerScrubMirror) container %d\n",
aif->data.PR[0].jd.client.container.src);
break;
case AifJobCtrRebuildRaid5: /* Container Rebuild Raid5
* operation */
device_printf(sc->aac_dev,
"(ContainerRebuildRaid5) container %d\n",
aif->data.PR[0].jd.client.container.src);
break;
case AifJobCtrScrubRaid5: /* Container Scrub Raid5
* operation */
device_printf(sc->aac_dev,
"(ContainerScrubRaid5) container %d\n",
aif->data.PR[0].jd.client.container.src);
break;
case AifJobCtrMorph: /* Container morph operation */
device_printf(sc->aac_dev,
"(ContainerMorph) container %d\n",
aif->data.PR[0].jd.client.container.src);
/* XXX two containers? */
break;
case AifJobCtrPartCopy: /* Container Partition copy
* operation */
device_printf(sc->aac_dev,
"(ContainerPartCopy) container %d to "
"%d\n",
aif->data.PR[0].jd.client.container.src,
aif->data.PR[0].jd.client.container.dst);
break;
case AifJobCtrRebuildMirror: /* Container Rebuild Mirror
* operation */
device_printf(sc->aac_dev,
"(ContainerRebuildMirror) container "
"%d\n",
aif->data.PR[0].jd.client.container.src);
break;
case AifJobCtrCrazyCache: /* crazy cache */
device_printf(sc->aac_dev,
"(ContainerCrazyCache) container %d\n",
aif->data.PR[0].jd.client.container.src);
/* XXX two containers? */
break;
case AifJobFsCreate: /* File System Create
* operation */
device_printf(sc->aac_dev, "(FsCreate)\n");
break;
case AifJobFsVerify: /* File System Verify
* operation */
device_printf(sc->aac_dev, "(FsVerivy)\n");
break;
case AifJobFsExtend: /* File System Extend
* operation */
device_printf(sc->aac_dev, "(FsExtend)\n");
break;
case AifJobApiFormatNTFS: /* Format a drive to NTFS */
device_printf(sc->aac_dev, "(FormatNTFS)\n");
break;
case AifJobApiFormatFAT: /* Format a drive to FAT */
device_printf(sc->aac_dev, "(FormatFAT)\n");
break;
case AifJobApiUpdateSnapshot: /* update the read/write half
* of a snapshot */
device_printf(sc->aac_dev, "(UpdateSnapshot)\n");
break;
case AifJobApiFormatFAT32: /* Format a drive to FAT32 */
device_printf(sc->aac_dev, "(FormatFAT32)\n");
break;
case AifJobCtlContinuousCtrVerify: /* Adapter operation */
device_printf(sc->aac_dev, "(ContinuousCtrVerify)\n");
break;
default:
device_printf(sc->aac_dev, "(%d)\n",
aif->data.PR[0].jd.type);
break;
}
break;
}
case AifCmdAPIReport:
device_printf(sc->aac_dev, "APIReport (%d)\n", aif->seqNumber);
break;
case AifCmdDriverNotify:
device_printf(sc->aac_dev, "DriverNotify (%d)\n",
aif->seqNumber);
break;
default:
device_printf(sc->aac_dev, "AIF %d (%d)\n", aif->command,
aif->seqNumber);
break;
}
}
#endif /* AACRAID_DEBUG */
/*
* Debug flags to be put into the HBA flags field when initialized
*/
const unsigned long aacraid_debug_flags = /* Variable to setup with above flags. */
/* HBA_FLAGS_DBG_KERNEL_PRINT_B | */
HBA_FLAGS_DBG_FW_PRINT_B |
/* HBA_FLAGS_DBG_FUNCTION_ENTRY_B | */
HBA_FLAGS_DBG_FUNCTION_EXIT_B |
HBA_FLAGS_DBG_ERROR_B |
HBA_FLAGS_DBG_INIT_B |
/* HBA_FLAGS_DBG_OS_COMMANDS_B | */
/* HBA_FLAGS_DBG_SCAN_B | */
/* HBA_FLAGS_DBG_COALESCE_B | */
/* HBA_FLAGS_DBG_IOCTL_COMMANDS_B | */
/* HBA_FLAGS_DBG_SYNC_COMMANDS_B | */
HBA_FLAGS_DBG_COMM_B |
/* HBA_FLAGS_DBG_AIF_B | */
/* HBA_FLAGS_DBG_CSMI_COMMANDS_B | */
HBA_FLAGS_DBG_DEBUG_B |
/* HBA_FLAGS_DBG_FLAGS_MASK | */
0;
int aacraid_get_fw_debug_buffer(struct aac_softc *sc)
{
u_int32_t MonDriverBufferPhysAddrLow = 0;
u_int32_t MonDriverBufferPhysAddrHigh = 0;
u_int32_t MonDriverBufferSize = 0;
u_int32_t MonDriverHeaderSize = 0;
/*
* Get the firmware print buffer parameters from the firmware
* If the command was successful map in the address.
*/
if (!aacraid_sync_command(sc, AAC_MONKER_GETDRVPROP, 0, 0, 0, 0, NULL, NULL)) {
MonDriverBufferPhysAddrLow = AAC_GET_MAILBOX(sc, 1);
MonDriverBufferPhysAddrHigh = AAC_GET_MAILBOX(sc, 2);
MonDriverBufferSize = AAC_GET_MAILBOX(sc, 3);
MonDriverHeaderSize = AAC_GET_MAILBOX(sc, 4);
if (MonDriverBufferSize) {
unsigned long Offset = MonDriverBufferPhysAddrLow
- rman_get_start(sc->aac_regs_res1);
/*
* See if the address is already mapped in and if so set it up
* from the base address
*/
if ((MonDriverBufferPhysAddrHigh == 0) &&
(Offset + MonDriverBufferSize <
rman_get_size(sc->aac_regs_res1))) {
sc->DebugOffset = Offset;
sc->DebugHeaderSize = MonDriverHeaderSize;
sc->FwDebugBufferSize = MonDriverBufferSize;
sc->FwDebugFlags = 0;
sc->DebugFlags = aacraid_debug_flags;
return 1;
}
}
}
/*
* The GET_DRIVER_BUFFER_PROPERTIES command failed
*/
return 0;
}
#define PRINT_TIMEOUT 250000 /* 1/4 second */
void aacraid_fw_printf(struct aac_softc *sc, unsigned long PrintFlags, const char * fmt, ...)
{
va_list args;
u_int32_t Count, i;
char PrintBuffer_P[PRINT_BUFFER_SIZE];
unsigned long PrintType;
PrintType = PrintFlags &
~(HBA_FLAGS_DBG_KERNEL_PRINT_B|HBA_FLAGS_DBG_FW_PRINT_B);
if (((PrintType!=0) && (sc!=NULL) && ((sc->DebugFlags & PrintType)==0))
|| ((sc!=NULL) && (sc->DebugFlags
& (HBA_FLAGS_DBG_KERNEL_PRINT_B|HBA_FLAGS_DBG_FW_PRINT_B)) == 0))
return;
/*
* Set up parameters and call sprintf function to format the data
*/
va_start(args, fmt);
vsprintf(PrintBuffer_P, fmt, args);
va_end(args);
/*
* Make sure the HBA structure has been passed in for this section
*/
if ((sc != NULL) && (sc->FwDebugBufferSize)) {
/*
* If we are set up for a Firmware print
*/
if ((sc->DebugFlags & HBA_FLAGS_DBG_FW_PRINT_B)
&& ((PrintFlags
& (HBA_FLAGS_DBG_KERNEL_PRINT_B|HBA_FLAGS_DBG_FW_PRINT_B))
!= HBA_FLAGS_DBG_KERNEL_PRINT_B)) {
/*
* Make sure the string size is within boundaries
*/
Count = strlen(PrintBuffer_P);
if (Count > sc->FwDebugBufferSize)
Count = (u_int16_t)sc->FwDebugBufferSize;
/*
* Wait for no more than PRINT_TIMEOUT for the previous
* message length to clear (the handshake).
*/
for (i = 0; i < PRINT_TIMEOUT; ++i) {
if (!AAC_MEM1_GETREG4(sc,
sc->DebugOffset + FW_DEBUG_STR_LENGTH_OFFSET)) {
break;
}
DELAY(1);
}
/*
* If the Length is clear, copy over the message, the
* flags, and the length. Make sure the length is the
* last because that is the signal for the Firmware to
* pick it up.
*/
if (!AAC_MEM1_GETREG4(sc,
sc->DebugOffset + FW_DEBUG_STR_LENGTH_OFFSET)) {
for (i = 0; i < Count; ++i) {
AAC_MEM1_SETREG1(sc, sc->DebugOffset + sc->DebugHeaderSize + i,
PrintBuffer_P[i]);
}
AAC_MEM1_SETREG4(sc, sc->DebugOffset + FW_DEBUG_FLAGS_OFFSET,
sc->FwDebugFlags);
AAC_MEM1_SETREG4(sc, sc->DebugOffset + FW_DEBUG_STR_LENGTH_OFFSET,
Count);
} else
sc->DebugFlags &= ~HBA_FLAGS_DBG_FW_PRINT_B;
}
/*
* If the Kernel Debug Print flag is set, send it off to the
* Kernel debugger
*/
if ((sc->DebugFlags & HBA_FLAGS_DBG_KERNEL_PRINT_B)
&& ((PrintFlags
& (HBA_FLAGS_DBG_KERNEL_PRINT_B|HBA_FLAGS_DBG_FW_PRINT_B))
!= HBA_FLAGS_DBG_FW_PRINT_B)) {
if (sc->FwDebugFlags & FW_DEBUG_FLAGS_NO_HEADERS_B)
printf ("%s\n", PrintBuffer_P);
else
device_printf (sc->aac_dev, "%s\n", PrintBuffer_P);
}
} else {
/*
* No HBA structure passed in so it has to be for the Kernel Debugger
*/
if ((sc != NULL) && (sc->FwDebugFlags & FW_DEBUG_FLAGS_NO_HEADERS_B))
printf ("%s\n", PrintBuffer_P);
else if (sc != NULL)
device_printf (sc->aac_dev, "%s\n", PrintBuffer_P);
else
printf("%s\n", PrintBuffer_P);
}
}
void aacraid_fw_print_mem(struct aac_softc *sc, unsigned long PrintFlags, u_int8_t *Addr, int Count)
{
int Offset, i;
u_int32_t DebugFlags = 0;
char Buffer[100];
char *LineBuffer_P;
/*
* If we have an HBA structure, save off the flags and set the no
* headers flag so we don't have garbage between our lines of data
*/
if (sc != NULL) {
DebugFlags = sc->FwDebugFlags;
sc->FwDebugFlags |= FW_DEBUG_FLAGS_NO_HEADERS_B;
}
Offset = 0;
/*
* Loop through all the data
*/
while (Offset < Count) {
/*
* We will format each line into a buffer and then print out
* the entire line so set the pointer to the beginning of the
* buffer
*/
LineBuffer_P = Buffer;
/*
* Set up the address in HEX
*/
sprintf(LineBuffer_P, "\n%04x ", Offset);
LineBuffer_P += 6;
/*
* Set up 16 bytes in HEX format
*/
for (i = 0; i < 16; ++i) {
/*
* If we are past the count of data bytes to output,
* pad with blanks
*/
if ((Offset + i) >= Count)
sprintf (LineBuffer_P, " ");
else
sprintf (LineBuffer_P, "%02x ", Addr[Offset+i]);
LineBuffer_P += 3;
/*
* At the mid point we will put in a divider
*/
if (i == 7) {
sprintf (LineBuffer_P, "- ");
LineBuffer_P += 2;
}
}
/*
* Now do the same 16 bytes at the end of the line in ASCII
* format
*/
sprintf (LineBuffer_P, " ");
LineBuffer_P += 2;
for (i = 0; i < 16; ++i) {
/*
* If all data processed, OUT-O-HERE
*/
if ((Offset + i) >= Count)
break;
/*
* If this is a printable ASCII character, convert it
*/
if ((Addr[Offset+i] > 0x1F) && (Addr[Offset+i] < 0x7F))
sprintf (LineBuffer_P, "%c", Addr[Offset+i]);
else
sprintf (LineBuffer_P, ".");
++LineBuffer_P;
}
/*
* The line is now formatted, so print it out
*/
aacraid_fw_printf(sc, PrintFlags, "%s", Buffer);
/*
* Bump the offset by 16 for the next line
*/
Offset += 16;
}
/*
* Restore the saved off flags
*/
if (sc != NULL)
sc->FwDebugFlags = DebugFlags;
}
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 5,931
|
The tea party is celebrating its fifth anniversary today, with a celebration on Capitol Hill featuring Sens. Mike Lee of Utah, Rand Paul of Kentucky, and Ted Cruz of Texas. As the tea party prepares to test its clout in upcoming Republican primaries, Washington Wire looks back on the events that led the tea party to where it is today.
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 9,607
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At The Well is an international movement that connects women to body, soul, and community through wellness education and Jewish spirituality. Women can access resources through At The Well's original monthly Moon Manuals and other original content. They connect also with peers through monthly Well Circle gatherings, with support and coaching from At The Well.
We provide resources such as: Monthly Moon Manuals themed to the Hebrew calendar, print books/mags/blog posts on women's health + Jewish spirituality, onboarding guide for new Well Circles, classes and retreats.
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 1,684
|
:orphan: true
.. INTERNAL USE ONLY
The following prerequisites can be copied and pasted into any feature document.
- Licensed, operational BIG-IP :term:`device`.
- Licensed, operational BIG-IP :term:`device service cluster`.
- Licensed, operational BIG-IP :term:`device` or :term:`device service cluster`.
- Licensed, operational BIG-IP :term:`device` and/or :term:`device group`.
- Licensed, operational BIG-IP :term:`vCMP host` chassis with support for vCMP
- Licensed, operational BIG-IP :term:`vCMP guest` running on a vCMP Host
- Operational OpenStack cloud (|openstack| release).
- Administrator access to both the BIG-IP device(s) and the OpenStack cloud.
- Administrative access to the vCMP host(s) and guest(s) you will manage with F5 LBaaSv2.
- Login credentials for user with administrative permissions on BIG-IP device(s).
- F5 :ref:`LBaaSv2 driver <Install the F5 LBaaSv2 Driver>` and :ref:`agent <agent:home>` installed on each server from which BIG-IP LTM services are required.
- F5 :ref:`agent <agent:home>` and :ref:`service provider driver <Install the F5 LBaaSv2 Driver>` installed on the Neutron controller.
- F5 ref:`agent <Install the F5 Agent>` and :ref:`LBaaSv2 driver <Install the F5 LBaaSv2 Driver>` installed on all hosts from which BIG-IP services will be provisioned.
- Basic understanding of OpenStack networking concepts. See the `OpenStack docs <http://docs.openstack.org/mitaka/>`_ for more information.
- Basic understanding of `BIG-IP system configuration <https://support.f5.com/kb/en-us/products/big-ip_ltm/manuals/product/bigip-system-initial-configuration-12-0-0/2.html#conceptid>`_.
- Basic understanding of `BIG-IP Local Traffic Management <https://support.f5.com/kb/en-us/products/big-ip_ltm/manuals/product/ltm-basics-12-0-0.html>`_
- Basic understanding of `BIG-IP device service clustering <https://support.f5.com/kb/en-us/products/big-ip_ltm/manuals/product/bigip-device-service-clustering-admin-12-0-0.html>`_.
- Knowledge of `OpenStack Networking <http://docs.openstack.org/mitaka/networking-guide/>`_ concepts.
- Knowledge of `BIG-IP vCMP <https://support.f5.com/kb/en-us/products/big-ip_ltm/manuals/product/vcmp-administration-appliances-12-1-1/1.html>`_ configuration and administration.
- Knowledge of BIG-IP `system configuration`_, `local traffic management`_, & `device service clustering`_.
.. must include the following at end of document:
.. _system configuration: https://support.f5.com/kb/en-us/products/big-ip_ltm/manuals/product/bigip-system-initial-configuration-12-0-0/2.html#conceptid
.. _local traffic management: https://support.f5.com/kb/en-us/products/big-ip_ltm/manuals/product/ltm-basics-12-0-0.html
.. _device service clustering: https://support.f5.com/kb/en-us/products/big-ip_ltm/manuals/product/bigip-device-service-clustering-admin-12-0-0.html
- :ref:`SSH key(s) <heat:add-ssh-key-horizon>` configured in OpenStack.
- Two (2) VLANs :ref:`configured in Neutron <docs:os-neutron-network-setup>` -- 'mgmt' and 'data' - to be used for system management and data traffic, respectively.
- Two (2) VLANs :ref:`configured in Neutron <docs:os-neutron-network-setup>` to be used for BIG-IP internal and external traffic.
- Three (3) VLANs :ref:`configured in Neutron <docs:os-neutron-network-setup>` -- 'mgmt', 'control', and 'data' -- to be used for system management, high availability (if desired), and data traffic, respectively.
- At least two (2) VLANs :ref:`configured in Neutron <docs:os-neutron-network-setup>` -- 'mgmt' and 'data' - to be used for BIG-IP® system management and client-server data traffic, respectively.
- VLANs :ref:`configured in Neutron <docs:os-neutron-network-setup>` or `on the BIG-IP <https://support.f5.com/kb/en-us/products/big-ip_ltm/manuals/product/tmos-routing-administration-12-0-0/5.html#conceptid>`_, as appropriate for your environment.
- An external network with access to the internet.
- Two (2) licensed, operational BIG-IP devices (hardware or Virtual Edition); both must be connected to the 'control' VLAN.
- BIG-IP `License base key <https://support.f5.com/kb/en-us/solutions/public/7000/700/sol7752.html>`_.
- `OpenStack Barbican <OpenStack Barbican: https://wiki.openstack.org/wiki/Barbican>`_ certificate manager configured and operational.
- Existing `BIG-IP SSL profile <https://support.f5.com/kb/en-us/products/big-ip_ltm/manuals/product/bigip-ssl-administration-12-0-0/5.html#unique_527799714>`_ (*optional*).
- All hosts running F5 LBaaSv2 must have the Neutron and Neutron LBaaS packages installed.
- All hosts running F5 LBaaSv2 must use the same Neutron database.
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 4,094
|
Q: .env file variables access after publish I'm new to react development. I have created .env file(inside root) and got some url for my application. after publish my application to azure my application not getting url values. I have stored it new .env file inside my public folder also. But its not getting values.
.env file(inside root)
REACT_APP_SERVICE_BASE_URL = https://localhost:44385/
REACT_APP_CONFIG_BASE_URL = https://localhost:44354/
js Code
require('dotenv').config()
let SERVICE_BASE_URL = process.env.PUBLIC_URL.REACT_APP_SERVICE_BASE_URL;
Can anyone have an idea to fix my issue. localhost working fine. after publish and change url is not working.
my customers have different Urls. so they need to change with their variables. So I thought if i add .env file inside public folder they can change their Url and use it
Tried this way also. But this also not calling public folder .env Its also taking root folder .env
require('dotenv').config(process.env.PUBLIC_URL+ '/.env')
A: As mentioned, create-react-app creates a static app, so nothing can be read from environment variables dynamically after build. Instead values from your .env file are copied into the static website during build. Any change afterwards won't change your app.
If you're using Azure App Service: Rather than building the app locally, then publishing the pre-built app bundle, you can instead publish the source of the app and have Azure App Service build the app. This way the customer-specific environment variables (App Settings) are present during build and will be set appropriately in your app.
There's two approaches:
*
*Use a custom build script that you publish with your source code to Azure App Service. The documentation on this isn't great, but it works if you prefer to deploy from git or from a zip file. Kudu is the engine behind both of these deployment scenarios, see the wiki for details. See this example deploy script.
*(recommended) Deploy your app using containers, and use an entry point script to replace the environment variables' placeholders with the customer-specific App Service's environment variable values.
Example of #2 (recommended):
Some code examples below. You can also reference this project as a working example of using this approach.
React App code to get the environment variable:
export const getGitHubToken = () => {
if (process.env.NODE_ENV !== 'production') {
if (!process.env.REACT_APP_SERVICE_BASE_URL) throw new Error('Must set env variable $REACT_APP_SERVICE_BASE_URL');
return process.env.REACT_APP_SERVICE_BASE_URL;
}
return '__REACT_APP_SERVICE_BASE_URL__';
};
Entrypoint script run by container:
#!/usr/bin/env bash
# Get environment variables to show up in SSH session
eval $(printenv | sed -n "s/^\([^=]\+\)=\(.*\)$/export \1=\2/p" | sed 's/"/\\\"/g' | sed '/=/s//="/' | sed 's/$/"/' >> /etc/profile)
pushd /home/site/wwwroot/static/js > /dev/null
pattern="main.*.js"
files=( $(compgen -W "$pattern") )
mainFile=$files
sed -i 's|__REACT_APP_SERVICE_BASE_URL__|'"$REACT_APP_SERVICE_BASE_URL"'|g' "$mainFile"
sed -i 's|__REACT_APP_CONFIG_BASE_URL__|'"$REACT_APP_CONFIG_BASE_URL"'|g' "$mainFile"
popd > /dev/null
Dockerfile:
FROM nginx
RUN mkdir -p /home/LogFiles /opt/startup /home/site/wwwroot \
&& echo "root:Docker!" | chpasswd \
&& echo "cd /home" >> /etc/bash.bashrc \
&& apt-get update \
&& apt-get install --yes --no-install-recommends \
openssh-server \
openrc \
yarn \
net-tools \
dnsutils
# init_container.sh is in react app's deploy/startup folder
COPY deploy/startup /opt/startup
COPY build /home/site/wwwroot
RUN chmod -R +x /opt/startup
ENV PORT 8080
ENV SSH_PORT 2222
EXPOSE 2222 8080
ENV WEBSITE_ROLE_INSTANCE_ID localRoleInstance
ENV WEBSITE_INSTANCE_ID localInstance
ENV PATH ${PATH}:/home/site/wwwroot
WORKDIR /home/site/wwwroot
ENTRYPOINT ["/opt/startup/init_container.sh"]
A: let SERVICE_BASE_URL = process.env.REACT_APP_SERVICE_BASE_URL
A: As mentioned here https://create-react-app.dev/docs/adding-custom-environment-variables/ .env file is for development purpose.
I suppose you use create-react-app to build your application. In that case the environment variable is injected in your appication at build time.
When you develop locally .env variables are automatically injected to your code.
In the case of a deploy on azure you shoud define your environment variables in that environment and build you application there.
|
{
"redpajama_set_name": "RedPajamaStackExchange"
}
| 1,578
|
Born to Run is the third studio album by American singer-songwriter Bruce Springsteen, released on August 25, 1975, by Columbia Records. As his effort to break into the mainstream, the album was a commercial success, peaking at number three on the Billboard 200 and eventually selling seven million copies in the United States. Two singles were released from the album: "Born to Run" and "Tenth Avenue Freeze-Out"; the first helped Springsteen to reach mainstream popularity. The tracks "Thunder Road", "She's the One", and "Jungleland" became staples of album-oriented rock radio and Springsteen concert high points.
Born to Run garnered widespread acclaim on release. Many critics have called it one of the greatest rock albums of all time. On November 14, 2005, a 30th Anniversary remaster of the album was released as a box set including two DVDs: a production diary film and a concert movie.
The album was remastered again in 2014 by veteran mastering engineer Bob Ludwig, who has worked on much of Springsteen's audio output since 1982, for release as part of The Album Collection Vol. 1 1973–1984, a boxed set composed of remastered editions of his first seven albums. It was later released in remastered form as a single disc as well.
Recording
Springsteen began work on the album in May 1974. Having been given an enormous budget in a last-ditch effort at a commercially viable record, Springsteen became bogged down in the recording process while striving for a wall of sound production. Fed by the release of an early mix of "Born to Run" to nearly a dozen radio stations, anticipation built toward the album's release.
Springsteen has noted a progression in his songwriting compared to his previous work. Unlike Greetings from Asbury Park, N.J. and The Wild, the Innocent & the E Street Shuffle, Born to Run includes few specific references to places in New Jersey, in an attempt to make the songs more identifiable to a wider audience. Springsteen has also referred to a maturation in his lyrics, calling Born to Run "the album where I left behind my adolescent definitions of love and freedom—it was the dividing line." In addition, Springsteen spent more time in the studio refining songs than he had on the previous two albums.
All in all, the album took more than 14 months to record, with six months alone spent on the song "Born to Run" itself. During this time Springsteen battled with anger and frustration over the album, saying he heard "sounds in [his] head" that he could not explain to the others in the studio.
During the process, Springsteen brought in Jon Landau to help with production, made contractually official on April 13, 1975. Five days later, sessions resumed at The Record Plant, New York City, with Jimmy Iovine as engineer. This was the beginning of the breakup of Springsteen's relationship with producer and manager Mike Appel, after which Landau assumed both roles. The album was Springsteen's first to feature pianist Roy Bittan and drummer Max Weinberg (although David Sancious and Ernest "Boom" Carter played the piano and drums, respectively, on the title track, which was finished August 1974, before they left the band).
The album is noted for its use of introductions to set the tone of each song (all of the record was composed on piano, not guitar), and for the Phil Spector-like "Wall of Sound" arrangements and production. Springsteen has said that he wanted Born to Run to sound like "Roy Orbison singing Bob Dylan, produced by Spector." Most of the tracks were first recorded with a core rhythm section band comprising Springsteen, Weinberg, Bittan, and bassist Garry Tallent, with other members' contributions then added on.
In terms of the original LP's sequencing, Springsteen eventually adopted a "four corners" approach, as the songs beginning each side ("Thunder Road", "Born to Run") were uplifting odes to escape, while the songs ending each side ("Backstreets", "Jungleland") were sad epics of loss, betrayal, and defeat. (Originally, he had planned to begin and end the album with alternative versions of "Thunder Road".)
A few original pressings have "Meeting Across the River" billed as "The Heist", and the original album cover has the title handwritten with a broad-nib pen. These copies, known as the "script cover," are very rare and considered to be the "holy grail" for Springsteen collectors.
Marketing and sales
The album's release was accompanied by a $250,000 promotional campaign by Columbia, directed at both consumers and the music industry, making good use of Landau's "I saw rock and roll future and its name is Bruce Springsteen" quote. With much publicity, Born to Run vaulted into the top 10 in its second week on the charts and soon went Gold. Time and Newsweek magazines put Springsteen on the cover in the same week (October 27, 1975) – in Time, Jay Cocks praised Springsteen, while the Newsweek article took a cynical look at the "next Dylan" hype that haunted Springsteen until his breakthrough. The question of hype became a story in itself, as critics began wondering if Springsteen was for real or the product of record company promotion.
Upset with Columbia's promotion department, Springsteen said the decision to label him as the "future of rock was a very big mistake and I would like to strangle the guy who thought that up." When Springsteen arrived for his first UK concert at the Hammersmith Odeon, he personally tore down the "Finally the world is ready for Bruce Springsteen" posters in the lobby and ordered that the buttons with "I have seen the future of rock 'n' roll at the Hammersmith Odeon" printed on them not be given out. When the hype died down, sales tapered off and the album was off the chart after 29 weeks. However, the album had established a solid national fan base for Springsteen, which he would build on with each subsequent release.
The album first charted at number 84 on the Billboard album chart in the week of September 13, 1975. The following week, it made an impressive increase, entering the top 10 at No. 8, then spent two weeks at No. 4, and finally, during the weeks of October 11 and 18, Born to Run reached its peak position of No. 3. Born to Run continued to be a strong catalog seller through the years, re-entering the Billboard chart in late 1980 after The River was released, and again after the blockbuster success of Born in the U.S.A., spending most of 1985 on the chart. It was certified triple-platinum by the Recording Industry Association of America in 1986, the first year in which pre-1976 releases were eligible for platinum and multi-platinum awards.
Columbia first issued the album on CD in Japan in 1982, and in the US in 1984. It has since been reissued several times, including on vinyl. Several limited edition versions on 12-inch vinyl have been released, including a CBS half-speed master version in 1980 as part of its Mastersound audiophile series, a 1999 QUIEX vinyl LP edition, and a 180g vinyl LP edition, from the same masters used for the 2014 boxed set, was issued in May 2015 in conjunction with Record Store Day.
Critical reception
Born to Run received highly positive reviews from critics. In a rave review for Rolling Stone magazine, Greil Marcus wrote that Springsteen enhances romanticized American themes with his majestic sound, ideal style of rock and roll, evocative lyrics, and an impassioned delivery that defines what is a "magnificent" album: "It is the drama that counts; the stories Springsteen is telling are nothing new, though no one has ever told them better or made them matter more." John Rockwell, writing in The New York Times, said that the "solidly rock 'n' roll" album is more diverse than Springsteen's previous albums, while his detailed lyrics retain a universal quality that transcends the sources and myths he drew upon. Robert Christgau of The Village Voice felt that he condenses a significant amount of American myth into songs, mostly centered on taking a lover for a joyride, and often succeeds in spite of his tendency for histrionics and "pseudotragic beautiful loser fatalism": "Springsteen may well turn out to be one of those rare self-conscious primitives who get away with it." Langdon Winner was less enthusiastic in his review for The Real Paper and argued that, because Springsteen consciously adheres to traditions and standards extolled in rock criticism, Born to Run is "the complete monument to rock and roll orthodoxy".
Born to Run was voted the third best album of 1975 in the Pazz & Jop, an annual critics poll run by The Village Voice. Christgau, the poll's creator, ranked it 12th on his own year-end list. He later wrote that its major flaw was its pompous declaration of greatness, typified by elements such as the "wall-of-sound, white-soul-at-the-opera-house" aesthetic and an "unresolved quest narrative". Nonetheless, he maintained the record was important for how "its class-conscious songcraft provided a relief from the emptier pretensions of late-hippie arena-rock." On the other hand, AllMusic's William Ruhlmann contends that although "some thought it took itself too seriously, many found that exalting."
According to Acclaimed Music, it is the 16th most celebrated album in popular music history. In 1987, it was ranked No. 8 by Rolling Stone in its "100 Best Albums of the Last Twenty Years" and in 2003, the magazine ranked it 18th on its list of The 500 Greatest Albums of All Time, maintaining the rating in a 2012 revision and dropping a few slots to number 21 in the 2020 reboot of the list. In 2001, the TV network VH1 named it the 27th-greatest album of all time, and in 2003, it was ranked as the most popular album in the first Zagat Survey Music Guide. The album was also included in the book 1001 Albums You Must Hear Before You Die. It was voted number 20 in the third edition of Colin Larkin's All Time Top 1000 Albums (2000). Born to Run was also listed in the Library of Congress' National Recording Registry of historic recordings. In December 2005, U.S. Representative Frank Pallone (who represents Asbury Park) and 21 co-sponsors sponsored H.Res. 628, "Congratulating Bruce Springsteen of New Jersey on the 30th anniversary of his masterpiece record album 'Born to Run', and commending him on a career that has touched the lives of millions of Americans." In general, resolutions honoring native sons are passed with a simple voice vote. This bill, however, was referred to the House Committee on Education and the Workforce and died there.
Live performances
Songs from Born to Run were performed live as early as mid-1974, and by 1975, all had made their way into Springsteen's shows and (with the rare exception of "Meeting Across the River") continued to be a regular staple of his concerts on subsequent tours through 2018. Springsteen and the E Street Band performed Born to Run in its entirety and for the first time at a benefit performance at the Count Basie Theatre in Red Bank, New Jersey, on May 7, 2008. It was again performed during their September 20, 2009, show at the United Center in Chicago, Illinois, as well as several other shows on the fall 2009 leg of the Working on a Dream Tour. During the 2013 spring-summer run of his Wrecking Ball Tour, Springsteen again began to perform the album in its entirety although a few times its performance was not included in the actual set lists and it was performed as either a surprise or request.
On June 20, 2013, the full album was performed at the Ricoh Arena, the home of Coventry City F.C. in Coventry, England, and dedicated to the memory of actor James Gandolfini, who died of a heart attack the previous day. On March 2, 2014, the full album was performed at Mt Smart Arena in Auckland, New Zealand for 40,000 fans.
Artwork
The cover art of Born to Run is one of rock music's most recognizable images. It was taken by Eric Meola, who shot 900 frames in his three-hour session. These photos have been compiled in Born to Run: The Unseen Photos.
The photo shows Springsteen holding a Fender Telecaster with an Esquire neck, while leaning against saxophonist Clarence Clemons. That image became famous as the cover art. "Other things happened," says Meola, "but when we saw the contact sheets, that one just sort of popped. During the Born to Run tours, Springsteen and Clemons would occasionally duplicate the pose onstage for several seconds after a song while the stage lights were dim. As soon as the audience recognized and responded to what they were doing, they immediately broke the pose.
The Springsteen and Clemons cover pose has been imitated often, from Cheap Trick on the album Next Position Please, to Tom and Ray Magliozzi on the cover of the Car Talk compilation Born Not to Run: More Disrespectful Car Songs, to Kevin & Kell on a Sunday strip entitled "Born to Migrate" featuring Kevin Dewclaw as Springsteen with a carrot and Kell Dewclaw as Clemons with a pile of bones, to Bert and the Cookie Monster on the cover of the Sesame Street album Born to Add. The Spanish band, Los Secretos, also imitated the pose on the cover of the album, Algo Prestado in 2015.
30th Anniversary Edition and Album Collection releases
On November 14, 2005, Columbia Records released Born to Run 30th Anniversary Edition in box set form. The package included a remastered CD version of the original album. "Born to Run is the one I've remastered several times; most recently for the box set..." recalled Bob Ludwig. "That's the one that Bruce told me sounded closest to the way he'd imagined it in his head, which is the ultimate compliment."
The CD is all black (including playback side), with the label side replicating the original vinyl disc, having four bands (the original LP had four tracks per side), and including a modified red Columbia label listing all eight tracks. The DVD included Wings for Wheels, a lengthy documentary on the making of the album, which later won the 2007 Grammy Award for Best Long Form Music Video, with bonus film of three songs recorded live on May 1, 1973, at the Ahmanson Theatre in Los Angeles. The DVD also included Bruce Springsteen & The E Street Band Hammersmith Odeon, London '75, a full-length concert film recorded on November 18, 1975, at the Hammersmith Odeon in London during the brief European portion of their Born to Run tours. This live recording was subsequently released as the CD Hammersmith Odeon London '75. Packages from retailer Best Buy also included a CD single replica of the original "Born to Run" 45 single.
The box set debuted on the Billboard 200 album chart on December 3, 2005, at number 18 with sales of 53,206 copies.
In November 2014, Columbia Records/Legacy Recordings released The Album Collection Vol. 1 1973–1984, a boxed set composed of remastered editions of Springsteen's first seven albums recorded and released for Columbia Records between 1973 and 1984. Born to Run was one of those seven titles that were released individually on CD, with artwork true to the original LP packaging. Columbia also released it in single CD form in June 2015.
Track listing
Original release
Cassette version
The cassette version has the song order rearranged to save tape space, which was a common practice amongst the record companies. The track listing for the cassette is as follows:
Unreleased outtakes
There are currently seven known outtakes from the album:
"Linda Let Me Be The One"
"Lonely Night in the Park"
"A Love So Fine"
"A Night Like This"
"Janey Needs a Shooter"
"Lovers in The Cold"
"So Young and in Love"
Two of those seven, "Linda Let Me Be the One" and "So Young and in Love" were released on the Tracks box set. Rough mixes of the unreleased songs "Lovers In The Cold" (Walking in the Street) and "Lonely Night in the Park" surfaced in 2005, when they made their debut on E Street Radio. "Lovers In The Cold'" originally contained the closing musical figure that became the anthemic ending to "Thunder Road". The album sequence as of July 2, 1975, included "Linda Let Me Be the One" and "Lonely Night in the Park", and deleted "Born to Run". However, Mike Appel had a personal talk with Springsteen, and on July 7, 1975, an amended final sequence was issued with the released tracklist. "Janey Needs a Shooter" would later be re-worked by Springsteen and Warren Zevon into the track "Jeannie Needs a Shooter," included on Zevon's 1980 album Bad Luck Streak in Dancing School. On October 23, 2020, a 2019 recording of the original "Janey Needs a Shooter" was released on the album Letter to You.
Personnel
Adapted from the liner notes:
Bruce Springsteen – lead vocals, lead and rhythm guitars (tracks 1–6, 8), harmonica (track 1), horn arrangement (track 2)
The E Street Band
Roy Bittan – piano (tracks 2–4, 6–8), glockenspiel (tracks 1, 3), harpsichord (tracks 3, 6), organ (tracks 4, 6), Fender Rhodes (track 1), background vocals (track 1)
Clarence Clemons – saxophones (tracks 1–3, 5, 6, 8)
Garry Tallent – bass guitar (tracks 1–6, 8)
Max Weinberg – drums (tracks 1–4, 6, 8)
Ernest Carter – drums (track 5)
Danny Federici – organ (track 5)
David Sancious – keyboards (track 5)
Steven Van Zandt – background vocals (track 1), horn arrangement (track 2)
Mike Appel – background vocals (track 1)
Randy Brecker – trumpet (tracks 2, 7), flugel horn (track 2)
Michael Brecker – tenor saxophone (track 2)
David Sanborn – baritone saxophone (track 2)
Wayne Andre – trombone (track 2)
Richard Davis – bass (track 7)
Suki Lahav – violin (track 8)
Charles Calello – string arrangements and conductor (track 8)
Technical personnel:
Mike Appel, Bruce Springsteen – production
Jon Landau – production (tracks 1–4, 6–8)
Jimmy Iovine – engineering and mixing
Thom Panunzio, Corky Stasiak, Dave Thoener, Ricke Delena, Angie Arcuri, Andy Abrams – engineering assistants
Louis Lahav – engineering (track 5)
Greg Calbi – mastering
Paul Prestopino – maintenance
John Berg, Andy Engel – album design
Eric Meola – photography
Charts
Certifications and sales
See also
Born to Run
References
External links
Album lyrics and audio samples
Collection of album reviews
Born To Run Photographs
Bruce Springsteen albums
1975 albums
Albums arranged by Charles Calello
Albums produced by Jon Landau
Albums produced by Mike Appel
Albums recorded at Record Plant (New York City)
Columbia Records albums
United States National Recording Registry albums
United States National Recording Registry recordings
|
{
"redpajama_set_name": "RedPajamaWikipedia"
}
| 1,339
|
Owen Teale (born 20 May 1961) is a Welsh character actor having appeared in many films, including Robin Hood (1991), The Hawk (1993), King Arthur (2004), The Last Legion (2007), Tolkien (2019), and Dream Horse (2020). On television, he has appeared in Doctor Who (1985), David Copperfield (1986), The Thin Blue Line (1995), Ballykissangel (1999), Line of Duty (2012), Stella (2012–2013), A Discovery of Witches (2018–2022), and The Rig (2023).
Teale is known mostly for his role as Ser Alliser Thorne in the HBO fantasy TV series Game of Thrones (2011–2016).
Early life
Owen Teale was born on 20 May 1961, in North Cornelly, south Wales, son of Roy and Louise Teale. He attended Cynffig Comprehensive School in Kenfig Hill; he was suspended from the school for disciplinary offences, and credits one of the teachers Mr Davis, with awakening his interest in acting. He trained at the Guildford School of Acting.
Career
In 1984, Teale made his television debut in The Mimosa Boys a film about the Falklands War. in 1985, he appeared in the Doctor Who serial Vengeance on Varos as "Maldak". His film debut was in War Requiem in 1989. He later appeared in Knights of God (1989), Great Expectations (1989), The Fifteen Streets (1989) and Boon (1990) before being cast as Will Scarlet in the 1991 film Robin Hood.
He went on to appear in such series as Dangerfield, Ballykissangel, The Thin Blue Line and the long-running Belonging, and later Spooks and Murphy's Law.
He later appeared as Lophakin in the 1999 adaptation of The Cherry Orchard, opposite Charlotte Rampling as Ranevskaya and Alan Bates as Gayev. He played the infamous Nazi judge Roland Freisler in Conspiracy. He also had parts In Midsomer Murders and Lewis.
In 2005, he played a lead role in Marian, Again, in which he was the abusive husband of Harrison's eponymous character. He also did voice over narration for "Tales from the Green Valley", one of several farm series he has done for the BBC.
In 2006, he appeared in the Torchwood episode "Countrycide". Also in 2006 he had a role in the HBO UK TV movie Tsunami: The Aftermath. In 2007, he guest-starred in the Doctor Who audio drama The Mind's Eye. In the same year, he starred in The Last Legion alongside Ben Kingsley and Colin Firth, and was shot on location in Morocco, Tunisia and Slovakia.
In 2011, Teale appeared as Ser Alliser Thorne in Game of Thrones, the HBO TV adaptation of George R. R. Martin's novel series A Song of Ice and Fire, replacing at short notice Derek Halligan. He reprised this role in Season 4, Season 5, and Season 6.
In 2012, he played Dai in the comedy-drama series Stella, and Robert Holland, the fictional UK Foreign Secretary, in the drama series Kidnap and Ransom. He also played Chief Constable Osborne in the BBC police drama Line of Duty.
Between 2018 and 2022. he played Peter Knox in A Discovery of Witches, a series based on the book of the same name by Deborah Harkness.
In 2020, he starred opposite Toni Collette and Damian Lewis in the Wales based sports comedy-drama film Dream Horse.
In 2023, Teale starred as lars Hutton, causing problems on the Kinloch Bravo oil rig in The Rig, in a cast that included Iain Glen, Emily Hampshire, Mark Addy, and Martin Compston.
He has also worked as a voiceover artist for television advertisements.
Personal life
In 1986, Teale married actress Dilys Watling, with whom he has a son, Ion. They divorced in the mid-1990s. In 2001, he married actress Sylvestra Le Touzel; they have two daughters, Eliza and Grace. He likes to play golf, and was made an honorary member of the Pyle and Kenfig Golf Club.
Awards
Teale won the 1997 Tony Award for Best Featured Actor in a Play for his performance as Torvald opposite Janet McTeer in Ibsen's A Doll's House.
Filmography
Films
Television
Theatre
References
External links
1961 births
Living people
Tony Award winners
Welsh male film actors
Welsh male television actors
Alumni of the Guildford School of Acting
Male actors from Swansea
20th-century Welsh male actors
21st-century Welsh male actors
|
{
"redpajama_set_name": "RedPajamaWikipedia"
}
| 6,925
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Miejscowości w Polsce
Wg TERYT jest ich 3
Przezmark – wieś w woj. pomorskim, w pow. sztumskim, w gminie Stary Dzierzgoń
Przezmark – osada w woj. pomorskim, w pow. sztumskim, w gminie Stary Dzierzgoń
Przezmark – wieś w woj. warmińsko-mazurskim, w pow. elbląskim, w gminie Elbląg
Zobacz też
Zamek krzyżacki w Przezmarku
|
{
"redpajama_set_name": "RedPajamaWikipedia"
}
| 9,604
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package acteve.explorer;
import java.io.File;
import org.apache.tools.ant.Project;
import org.apache.tools.ant.Target;
import org.apache.tools.ant.taskdefs.ExecTask;
import org.apache.tools.ant.types.Commandline;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
public class Z3Task extends ExecTask
{
private static final Logger log = LoggerFactory.getLogger(Z3Task.class);
private static String args;
private final Target target = new Target();
public Z3Task()
{
setExecutable("/bin/sh");
Project project = new Project();
setProject(project);
target.setName("runZ3");
target.addTask(this);
project.addTarget(target);
target.setProject(project);
project.init();
}
public void exec(File outFile, File errFile, String file)
{
log.trace("Executing Z3Task with outfile " + outFile.getAbsolutePath() + " and errFile " + errFile.getAbsolutePath() + " and file " + file);
Commandline.Argument cmdLineArgs = createArg();
String args2 = args + file;
args2 += " 1>"+outFile;
args2 += " 2>"+errFile;
args2 = args2 + "\"";
cmdLineArgs.setLine(args2);
//setError(errFile);
//setOutput(outFile);
log.debug("Running Z3 " + args2);
target.execute();
}
public void execute()
{
super.execute();
}
static void setup(String z3Path)
{
if(z3Path == null)
throw new Error("z3Path is null");
File file = new File(z3Path);
if(!file.exists())
throw new Error("z3Path does not exist. " + z3Path);
args = "-c \"" + file.getAbsolutePath() + " -f ";
}
}
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 3,337
|
ACCEPTED
#### According to
Index Fungorum
#### Published in
null
#### Original name
Agaricus ziziphina Viv.
### Remarks
null
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 2,673
|
Quebec City photographer's shot of Ground Zero chosen out of thousands for publication by National Geographic
By Scott French
This haunting photograph of New York City's Ground Zero by local photographer Jay Ouellet will be featured in a new National Geographic publication in June.
Capturing a haunting night time scene at New York City's Ground Zero during a weekend visit has earned local photographer Jay Ouellet a place in a new publication from National Geographic.
The photograph was recently chosen to be published in the internationally renowned science and culture magazine's first special print edition from its Your Shot website in June.
"It's a fantastic honour to have my photograph published by the magazine," said Ouellet from his home in Sillery.
"National Geographic is the reference for magazines around the world."
"Of the 850 photos, I took that weekend, I knew this one was special," said Ouellet.
Ouellet, 54, an accomplished astronomical photographer by night and a chiropractor by day, travelled to New York City in April 2006, two weeks after launching his architectural photography book Quebec by Night.
While working on that book, he turned his lens from the cosmos to the ground for the first time.
"The idea of using astrophotography techniques to capture Ground Zero at night soon became the focus of the trip to New York," said Ouellet.
"Because of so many spotlights at the Ground Zero site, which normally would have the effect of blotting out everything that falls outside of the source of light, taking an astronomical photo was a technical challenge," said Ouellet.
There was also the challenge of making a statement as a person and an artist.
"I wanted to register my feelings about 9/11," said Ouellet, describing the place where 3,000 people perished during the terrorist attacks on the World Trade Centre towers on Sept. 11, 2001, as both "haunting" and "humbling."
"Capturing a great picture is about how you feel about it," said Ouellet.
"Capturing the mood, that's what it's all about," he added. "What's important is the impact it has on the viewer."
Susan Welchman, photography editor at National Geographic, agreed with Ouellet.
"I don't pick a lot of scenics, but this photo has resonance and meaning," said Welchman of Ouellet's Ground Zero photo.
"Your eye leads you to the woman sitting in front looking at the hole, so you (the observer) look into the hole."
Welchman said Ouellet's photo, first submitted and accepted to the Your Shot section on National Geographic's website in August 2006, was chosen for publication in the magazine this past March out of thousands of entries since the section was created two years ago.
Your Shot solicits photographs from readers and fans of the magazine who might be professional or amateur photographers for a Daily Dozen feature of photos posted to the website every day, 365 days a year.
Ouellet said being published in National Geographic is the second great milestone in a photography career that began when he started to take pictures of the night sky at the age of 15.
His first accomplishment came 10 years ago when a photograph of an eclipse of the sun and the moon he called 'Tango for Two' made the cover of Astronomy in 1999.
Ouellet, meanwhile, believes he has captured what he called another "magical photo" during the Red Bull Crashed Ice event this past January.
The picture, however, has nothing to do with the downhill skating event.
Called L'arbre qui parle (The Tree That Speaks), the photograph shows a frosty tree in Place d'Armes specially lit up for the night time event and contrasted against the Château Frontenac.
"The Château Frontenac might be one of the most photographed buildings in the world," said Ouellet.
"But this tree, which has stood just as long as the Château, has probably never been the focus of a photograph before."
|
{
"redpajama_set_name": "RedPajamaCommonCrawl"
}
| 9,852
|
export const numberInput: string;
export const withSuffix: string;
export const suffix: string;
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 8,448
|
Q: Physical and logical IO counts I would like to be able to run some kind of a show plan (similar to SYBASE) in oracle which will show the following, on each query or stored procedure:
*
*Physical IO's used on each statement.
*Logical IO's used on each statement.
*Indexes used on each statement.
This is very simple for me in sybase. I have an analyzer tool that does that and I spend most of my time actually resolving the high IO items.
I was told to do the following:
set autotrace on statistics;
EXPLAIN PLAN FOR
SELECT * FROM SOMETABLE
SELECT PLAN_TABLE_OUTPUT FROM TABLE(DBMS_XPLAN.DISPLAY());
This is fine but What is ROWS? Is it the Physical or logical IO? Also, what is the Plan hash value: 1611616177? Is that the total IO? I am relatively new to oracle and have lots of queries to investigate.
A: In SQL*Plus, you can do something like
SQL> set autotrace on;
SQL> select empno, ename from emp;
EMPNO ENAME
---------- ----------
7623 PAV
7369 smith
7499 ALLEN
7521 WARD
7566 JONES
7654 MARTIN
7698 BLAKE
7782 CLARK
7788 SCOTT
7839 KING
7844 TURNER
EMPNO ENAME
---------- ----------
7876 ADAMS
7900 SM0
7902 FORD
7934 MILLER
1234 BAR
16 rows selected.
Execution Plan
----------------------------------------------------------
Plan hash value: 3956160932
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 16 | 160 | 3 (0)| 00:00:01 |
| 1 | TABLE ACCESS FULL| EMP | 16 | 160 | 3 (0)| 00:00:01 |
--------------------------------------------------------------------------
Statistics
----------------------------------------------------------
1 recursive calls
0 db block gets
7 consistent gets
0 physical reads
0 redo size
997 bytes sent via SQL*Net to client
535 bytes received via SQL*Net from client
3 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
16 rows processed
Looking at the statistics at the bottom, consistent gets is a measure of logical I/O. Physical reads measures the number of physical reads that were necessary. This also shows the query plan which includes things like the optimizer's estimate of the number of rows that will be returned by each step of the query (i.e. the optimizer correctly estimates that a full scan of the EMP table will return 16 rows comprising 160 bytes of data).
A: If you want even more detail (and can get access to the trace files) then lookup TKPROF
see: http://download.oracle.com/docs/cd/B10500_01/server.920/a96533/sqltrace.htm
|
{
"redpajama_set_name": "RedPajamaStackExchange"
}
| 0
|
A winter weather advisory will be in effect Wednesday night and Thursday morning for areas above 9,000 feet, including Cameron Pass. Accumulation by daybreak Thursday could range from 5 to 10 inches across the northern and central mountains.
The historic average for the season's first measurable snowfall in the city is Oct. 27, based on 1900-2014 data from the Colorado Climate Center. The 10-year average, though, is Nov. 4.
The latest first snowfall on record took place in 1965, when the first flakes of the season fell on Dec. 13. The earliest first snowfall honors go to 1989 and 1974, when summer snow dusted the city on Sept. 12.
Reporter Jason Pohl covers breaking news for the Coloradoan. Follow him on Twitter: @pohl_jason.
|
{
"redpajama_set_name": "RedPajamaCommonCrawl"
}
| 3,023
|
Liverpool beat Genk 4-0 in the Champions League
London-SANA: Liverpool scored a 4-1 win at Genk in the Premier League
London-Sana
LONDON (Reuters) - Liverpool scored a 4-1 win at Genk in the Champions League on Wednesday.
Alex Oxlade Chamberlain scored in the second and 57th minutes, Sadio Mane of Senegal in the 77th minute and Mohamed Salah of Egypt in the 87th minute before Stephen Audi scored Genk's only goal in the 88th minute.
The result raised Liverpool to six points and moved up to second place behind leaders Napoli by seven points after beating the Austrian Red Bull Salzburg 3-2 with a stoppage Genk at one point in the last place.
Liverpool win 4-0 against Salzburg in the Champions League
Champions League: Chelsea draw dramatic draw against Ajax Amsterdam
Champions League: Liverpool still need a point for the knockout stages
Salzburg - Liverpool 0: 0 (Half 1) - Walla! sport
Champions League:
Salzburg in the Champions League: Mozart, Henkel pot and top talent
Liverpool and Napoli qualify for the round of 16 in the Champions League
PSG: Netflix shoots a documentary on Neymar
|
{
"redpajama_set_name": "RedPajamaCommonCrawl"
}
| 7,874
|
package io.opentelemetry.api.internal;
import static org.assertj.core.api.Assertions.assertThat;
import io.github.netmikey.logunit.api.LogCapturer;
import io.opentelemetry.internal.testing.slf4j.SuppressLogger;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.extension.RegisterExtension;
@SuppressLogger(loggerName = ValidationUtil.API_USAGE_LOGGER_NAME)
public class ValidationUtilTest {
@RegisterExtension
LogCapturer apiUsageLogs =
LogCapturer.create().captureForLogger(ValidationUtil.API_USAGE_LOGGER_NAME);
@Test
void checkValidInstrumentName_InvalidNameLogs() {
assertThat(ValidationUtil.checkValidInstrumentName("1", " suffix")).isFalse();
apiUsageLogs.assertContains(
"Instrument name \"1\" is invalid, returning noop instrument. Instrument names must consist of 63 or fewer characters including alphanumeric, _, ., -, and start with a letter. suffix");
}
@Test
void checkValidInstrumentName() {
// Valid names
assertThat(ValidationUtil.checkValidInstrumentName("f")).isTrue();
assertThat(ValidationUtil.checkValidInstrumentName("F")).isTrue();
assertThat(ValidationUtil.checkValidInstrumentName("foo")).isTrue();
assertThat(ValidationUtil.checkValidInstrumentName("a1")).isTrue();
assertThat(ValidationUtil.checkValidInstrumentName("a.")).isTrue();
assertThat(ValidationUtil.checkValidInstrumentName("abcdefghijklmnopqrstuvwxyz")).isTrue();
assertThat(ValidationUtil.checkValidInstrumentName("ABCDEFGHIJKLMNOPQRSTUVWXYZ")).isTrue();
assertThat(ValidationUtil.checkValidInstrumentName("a1234567890")).isTrue();
assertThat(ValidationUtil.checkValidInstrumentName("a_-.")).isTrue();
assertThat(ValidationUtil.checkValidInstrumentName(new String(new char[63]).replace('\0', 'a')))
.isTrue();
// Empty and null not allowed
assertThat(ValidationUtil.checkValidInstrumentName(null)).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("")).isFalse();
// Must start with a letter
assertThat(ValidationUtil.checkValidInstrumentName("1")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName(".")).isFalse();
// Illegal characters
assertThat(ValidationUtil.checkValidInstrumentName("a~")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a!")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a@")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a#")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a$")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a%")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a^")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a&")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a*")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a(")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a)")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a=")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a+")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a{")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a}")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a[")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a]")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a\\")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a|")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a<")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a>")).isFalse();
assertThat(ValidationUtil.checkValidInstrumentName("a?")).isFalse();
// Must be 63 characters or less
assertThat(ValidationUtil.checkValidInstrumentName(new String(new char[64]).replace('\0', 'a')))
.isFalse();
}
@Test
void checkValidInstrumentUnit_InvalidUnitLogs() {
assertThat(ValidationUtil.checkValidInstrumentUnit("日", " suffix")).isFalse();
apiUsageLogs.assertContains(
"Unit \"日\" is invalid. Instrument unit must be 63 or fewer ASCII characters." + " suffix");
}
@Test
void checkValidInstrumentUnit() {
assertThat(ValidationUtil.checkValidInstrumentUnit("a")).isTrue();
assertThat(ValidationUtil.checkValidInstrumentUnit("A")).isTrue();
assertThat(ValidationUtil.checkValidInstrumentUnit("foo129")).isTrue();
assertThat(ValidationUtil.checkValidInstrumentUnit("!@#$%^&*()")).isTrue();
assertThat(ValidationUtil.checkValidInstrumentUnit(new String(new char[63]).replace('\0', 'a')))
.isTrue();
// Empty and null not allowed
assertThat(ValidationUtil.checkValidInstrumentUnit(null)).isFalse();
assertThat(ValidationUtil.checkValidInstrumentUnit("")).isFalse();
// Non-ascii characters
assertThat(ValidationUtil.checkValidInstrumentUnit("日")).isFalse();
// Must be 63 characters or less
assertThat(ValidationUtil.checkValidInstrumentUnit(new String(new char[64]).replace('\0', 'a')))
.isFalse();
}
}
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 1,112
|
Some Housewives could use this vacation.
Yoga, meditation, knitting, healthy meals, and writing workshops — divorcée Amy Koko, who wrote a memoir, There's Been A Change of Plans: Divorce, Dating & Delinquents in Mid-life, is offering that and more to help other women who are going through a divorce. Amy was married for 20 years; her marriage suddenly ended when her husband came clean about an affair he'd been having. They share four kids together.
She said writing helped save her from despair and depression, and wants other women to try writing their feelings down at the three-day "Write Your Divorce Story" retreat in Bradenton, Fla., on February 21-24.
Koko told Personal Space that her divorce "continued to haunt" her for a very long time after it was finalized.
"Divorce is just like that, right? Just when I thought I was moving forward, maybe flapping a new sheet over my new unmarried bed, excited to begin sleeping as a single person, a memory would come up, knocking me a few steps back," she says. "Or when I looked at my bank statement at the end of the month and remembered why it was so very tiny. How, I wondered, can I finally let it go?"
She began writing, and writing, and the experiences that kept reappearing became stories to share with others who were going through what she went through. Her writing turned into a blog called Exwifenewlife.
"After a year or so, I realized there was a book there; I'm not saying you need to write a book to get through your divorce, but I am saying that writing about my divorce was the key to finally letting it go," Koko explained. "Now I want to help other women begin that journey, whether they want to write their own memoir, short story or just gain clarity on their experience."
Along with her friend and fellow author Rebecca Gold, Koko designed the long weekend retreat that will help women writers find their own unique way of telling their story through writing workshops. There will also be daily gentle yoga and meditation and knitting lessons to get the creative juices flowing.
"There will also be time for sharing our work, for anyone who cares to do so," Koko said. "If no one cares to do so, I will share my past work starting with the story about fish having a party that I wrote in third grade. We will go from there."
Ultimately, Koko joked, the women can spend a few days in the Florida sunshine with "no men, no divorce lawyers, no kids, and no calories in any of the food we serve."
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 315
|
{"url":"http:\/\/openstudy.com\/updates\/51d48687e4b08d0a48e50312","text":"## lazy Group Title cos 2x - cos x = 0 one year ago one year ago\n\n\u2022 This Question is Open\n1. swissgirl Group Title\n\nhmmm is it $$\\cos(2x)$$ or $$\\cos^2(x)$$\n\n2. Abhishek619 Group Title\n\nuse $\\cos2x= 2 \\cos ^{2}x-1$","date":"2014-08-01 22:28:58","metadata":"{\"extraction_info\": {\"found_math\": true, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 0, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 1, \"mathjax_display_tex\": 1, \"mathjax_asciimath\": 0, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 0, \"wp-katex-eq\": 0, \"align\": 0, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.64457106590271, \"perplexity\": 9414.543620874014}, \"config\": {\"markdown_headings\": true, \"markdown_code\": true, \"boilerplate_config\": {\"ratio_threshold\": 0.18, \"absolute_threshold\": 10, \"end_threshold\": 5, \"enable\": true}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2014-23\/segments\/1406510275393.46\/warc\/CC-MAIN-20140728011755-00471-ip-10-146-231-18.ec2.internal.warc.gz\"}"}
| null | null |
/*** Autogenerated by WIDL 1.1.36 from objidl.idl - Do not edit ***/
#include <rpc.h>
#include <rpcndr.h>
#ifndef __WIDL_OBJIDL_H
#define __WIDL_OBJIDL_H
#ifdef __cplusplus
extern "C" {
#endif
/* Headers for imported files */
#include <unknwn.h>
/* Forward declarations */
#ifndef __IMarshal_FWD_DEFINED__
#define __IMarshal_FWD_DEFINED__
typedef interface IMarshal IMarshal;
#endif
#ifndef __IMarshal2_FWD_DEFINED__
#define __IMarshal2_FWD_DEFINED__
typedef interface IMarshal2 IMarshal2;
#endif
#ifndef __IStdMarshalInfo_FWD_DEFINED__
#define __IStdMarshalInfo_FWD_DEFINED__
typedef interface IStdMarshalInfo IStdMarshalInfo;
#endif
#ifndef __IExternalConnection_FWD_DEFINED__
#define __IExternalConnection_FWD_DEFINED__
typedef interface IExternalConnection IExternalConnection;
#endif
#ifndef __IMultiQI_FWD_DEFINED__
#define __IMultiQI_FWD_DEFINED__
typedef interface IMultiQI IMultiQI;
#endif
#ifndef __IMalloc_FWD_DEFINED__
#define __IMalloc_FWD_DEFINED__
typedef interface IMalloc IMalloc;
#endif
#ifndef __IMallocSpy_FWD_DEFINED__
#define __IMallocSpy_FWD_DEFINED__
typedef interface IMallocSpy IMallocSpy;
#endif
#ifndef __IInternalUnknown_FWD_DEFINED__
#define __IInternalUnknown_FWD_DEFINED__
typedef interface IInternalUnknown IInternalUnknown;
#endif
#ifndef __IEnumUnknown_FWD_DEFINED__
#define __IEnumUnknown_FWD_DEFINED__
typedef interface IEnumUnknown IEnumUnknown;
#endif
#ifndef __ISurrogate_FWD_DEFINED__
#define __ISurrogate_FWD_DEFINED__
typedef interface ISurrogate ISurrogate;
#endif
#ifndef __IGlobalInterfaceTable_FWD_DEFINED__
#define __IGlobalInterfaceTable_FWD_DEFINED__
typedef interface IGlobalInterfaceTable IGlobalInterfaceTable;
#endif
#ifndef __IBindCtx_FWD_DEFINED__
#define __IBindCtx_FWD_DEFINED__
typedef interface IBindCtx IBindCtx;
#endif
#ifndef __IEnumMoniker_FWD_DEFINED__
#define __IEnumMoniker_FWD_DEFINED__
typedef interface IEnumMoniker IEnumMoniker;
#endif
#ifndef __IRunnableObject_FWD_DEFINED__
#define __IRunnableObject_FWD_DEFINED__
typedef interface IRunnableObject IRunnableObject;
#endif
#ifndef __IRunningObjectTable_FWD_DEFINED__
#define __IRunningObjectTable_FWD_DEFINED__
typedef interface IRunningObjectTable IRunningObjectTable;
#endif
#ifndef __IPersist_FWD_DEFINED__
#define __IPersist_FWD_DEFINED__
typedef interface IPersist IPersist;
#endif
#ifndef __IPersistStream_FWD_DEFINED__
#define __IPersistStream_FWD_DEFINED__
typedef interface IPersistStream IPersistStream;
#endif
#ifndef __IMoniker_FWD_DEFINED__
#define __IMoniker_FWD_DEFINED__
typedef interface IMoniker IMoniker;
#endif
#ifndef __IROTData_FWD_DEFINED__
#define __IROTData_FWD_DEFINED__
typedef interface IROTData IROTData;
#endif
#ifndef __IEnumString_FWD_DEFINED__
#define __IEnumString_FWD_DEFINED__
typedef interface IEnumString IEnumString;
#endif
#ifndef __IClassActivator_FWD_DEFINED__
#define __IClassActivator_FWD_DEFINED__
typedef interface IClassActivator IClassActivator;
#endif
#ifndef __ISequentialStream_FWD_DEFINED__
#define __ISequentialStream_FWD_DEFINED__
typedef interface ISequentialStream ISequentialStream;
#endif
#ifndef __IStream_FWD_DEFINED__
#define __IStream_FWD_DEFINED__
typedef interface IStream IStream;
#endif
#ifndef __IEnumSTATSTG_FWD_DEFINED__
#define __IEnumSTATSTG_FWD_DEFINED__
typedef interface IEnumSTATSTG IEnumSTATSTG;
#endif
#ifndef __IStorage_FWD_DEFINED__
#define __IStorage_FWD_DEFINED__
typedef interface IStorage IStorage;
#endif
#ifndef __IPersistFile_FWD_DEFINED__
#define __IPersistFile_FWD_DEFINED__
typedef interface IPersistFile IPersistFile;
#endif
#ifndef __IPersistStorage_FWD_DEFINED__
#define __IPersistStorage_FWD_DEFINED__
typedef interface IPersistStorage IPersistStorage;
#endif
#ifndef __IRootStorage_FWD_DEFINED__
#define __IRootStorage_FWD_DEFINED__
typedef interface IRootStorage IRootStorage;
#endif
#ifndef __ILockBytes_FWD_DEFINED__
#define __ILockBytes_FWD_DEFINED__
typedef interface ILockBytes ILockBytes;
#endif
#ifndef __IFillLockBytes_FWD_DEFINED__
#define __IFillLockBytes_FWD_DEFINED__
typedef interface IFillLockBytes IFillLockBytes;
#endif
#ifndef __IProgressNotify_FWD_DEFINED__
#define __IProgressNotify_FWD_DEFINED__
typedef interface IProgressNotify IProgressNotify;
#endif
#ifndef __ILayoutStorage_FWD_DEFINED__
#define __ILayoutStorage_FWD_DEFINED__
typedef interface ILayoutStorage ILayoutStorage;
#endif
#ifndef __IBlockingLock_FWD_DEFINED__
#define __IBlockingLock_FWD_DEFINED__
typedef interface IBlockingLock IBlockingLock;
#endif
#ifndef __ITimeAndNoticeControl_FWD_DEFINED__
#define __ITimeAndNoticeControl_FWD_DEFINED__
typedef interface ITimeAndNoticeControl ITimeAndNoticeControl;
#endif
#ifndef __IOplockStorage_FWD_DEFINED__
#define __IOplockStorage_FWD_DEFINED__
typedef interface IOplockStorage IOplockStorage;
#endif
#ifndef __IEnumFORMATETC_FWD_DEFINED__
#define __IEnumFORMATETC_FWD_DEFINED__
typedef interface IEnumFORMATETC IEnumFORMATETC;
#endif
#ifndef __IEnumSTATDATA_FWD_DEFINED__
#define __IEnumSTATDATA_FWD_DEFINED__
typedef interface IEnumSTATDATA IEnumSTATDATA;
#endif
#ifndef __IAdviseSink_FWD_DEFINED__
#define __IAdviseSink_FWD_DEFINED__
typedef interface IAdviseSink IAdviseSink;
#endif
#ifndef __IAdviseSink2_FWD_DEFINED__
#define __IAdviseSink2_FWD_DEFINED__
typedef interface IAdviseSink2 IAdviseSink2;
#endif
#ifndef __IDataObject_FWD_DEFINED__
#define __IDataObject_FWD_DEFINED__
typedef interface IDataObject IDataObject;
#endif
#ifndef __IDataAdviseHolder_FWD_DEFINED__
#define __IDataAdviseHolder_FWD_DEFINED__
typedef interface IDataAdviseHolder IDataAdviseHolder;
#endif
#ifndef __IMessageFilter_FWD_DEFINED__
#define __IMessageFilter_FWD_DEFINED__
typedef interface IMessageFilter IMessageFilter;
#endif
#ifndef __IRpcChannelBuffer_FWD_DEFINED__
#define __IRpcChannelBuffer_FWD_DEFINED__
typedef interface IRpcChannelBuffer IRpcChannelBuffer;
#endif
#ifndef __IRpcChannelBuffer2_FWD_DEFINED__
#define __IRpcChannelBuffer2_FWD_DEFINED__
typedef interface IRpcChannelBuffer2 IRpcChannelBuffer2;
#endif
#ifndef __IRpcChannelBuffer3_FWD_DEFINED__
#define __IRpcChannelBuffer3_FWD_DEFINED__
typedef interface IRpcChannelBuffer3 IRpcChannelBuffer3;
#endif
#ifndef __IAsyncRpcChannelBuffer_FWD_DEFINED__
#define __IAsyncRpcChannelBuffer_FWD_DEFINED__
typedef interface IAsyncRpcChannelBuffer IAsyncRpcChannelBuffer;
#endif
#ifndef __IRpcSyntaxNegotiate_FWD_DEFINED__
#define __IRpcSyntaxNegotiate_FWD_DEFINED__
typedef interface IRpcSyntaxNegotiate IRpcSyntaxNegotiate;
#endif
#ifndef __IRpcProxyBuffer_FWD_DEFINED__
#define __IRpcProxyBuffer_FWD_DEFINED__
typedef interface IRpcProxyBuffer IRpcProxyBuffer;
#endif
#ifndef __IRpcStubBuffer_FWD_DEFINED__
#define __IRpcStubBuffer_FWD_DEFINED__
typedef interface IRpcStubBuffer IRpcStubBuffer;
#endif
#ifndef __IPSFactoryBuffer_FWD_DEFINED__
#define __IPSFactoryBuffer_FWD_DEFINED__
typedef interface IPSFactoryBuffer IPSFactoryBuffer;
#endif
#ifndef __IChannelHook_FWD_DEFINED__
#define __IChannelHook_FWD_DEFINED__
typedef interface IChannelHook IChannelHook;
#endif
#ifndef __IClientSecurity_FWD_DEFINED__
#define __IClientSecurity_FWD_DEFINED__
typedef interface IClientSecurity IClientSecurity;
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#ifndef __IServerSecurity_FWD_DEFINED__
#define __IServerSecurity_FWD_DEFINED__
typedef interface IServerSecurity IServerSecurity;
#endif
#ifndef __IAsyncSetup_FWD_DEFINED__
#define __IAsyncSetup_FWD_DEFINED__
typedef interface IAsyncSetup IAsyncSetup;
#endif
#ifndef __IDirectWriterLock_FWD_DEFINED__
#define __IDirectWriterLock_FWD_DEFINED__
typedef interface IDirectWriterLock IDirectWriterLock;
#endif
#ifndef __ISynchronize_FWD_DEFINED__
#define __ISynchronize_FWD_DEFINED__
typedef interface ISynchronize ISynchronize;
#endif
#ifndef __ISynchronizeHandle_FWD_DEFINED__
#define __ISynchronizeHandle_FWD_DEFINED__
typedef interface ISynchronizeHandle ISynchronizeHandle;
#endif
#ifndef __ISynchronizeEvent_FWD_DEFINED__
#define __ISynchronizeEvent_FWD_DEFINED__
typedef interface ISynchronizeEvent ISynchronizeEvent;
#endif
#ifndef __ISynchronizeContainer_FWD_DEFINED__
#define __ISynchronizeContainer_FWD_DEFINED__
typedef interface ISynchronizeContainer ISynchronizeContainer;
#endif
#ifndef __ISynchronizeMutex_FWD_DEFINED__
#define __ISynchronizeMutex_FWD_DEFINED__
typedef interface ISynchronizeMutex ISynchronizeMutex;
#endif
#ifndef __ICancelMethodCalls_FWD_DEFINED__
#define __ICancelMethodCalls_FWD_DEFINED__
typedef interface ICancelMethodCalls ICancelMethodCalls;
#endif
#ifndef __IAsyncManager_FWD_DEFINED__
#define __IAsyncManager_FWD_DEFINED__
typedef interface IAsyncManager IAsyncManager;
#endif
#ifndef __ICallFactory_FWD_DEFINED__
#define __ICallFactory_FWD_DEFINED__
typedef interface ICallFactory ICallFactory;
#endif
#ifndef __IRpcOptions_FWD_DEFINED__
#define __IRpcOptions_FWD_DEFINED__
typedef interface IRpcOptions IRpcOptions;
#endif
#ifndef __IRpcHelper_FWD_DEFINED__
#define __IRpcHelper_FWD_DEFINED__
typedef interface IRpcHelper IRpcHelper;
#endif
#ifndef __IReleaseMarshalBuffers_FWD_DEFINED__
#define __IReleaseMarshalBuffers_FWD_DEFINED__
typedef interface IReleaseMarshalBuffers IReleaseMarshalBuffers;
#endif
#ifndef __IWaitMultiple_FWD_DEFINED__
#define __IWaitMultiple_FWD_DEFINED__
typedef interface IWaitMultiple IWaitMultiple;
#endif
#ifndef __IUrlMon_FWD_DEFINED__
#define __IUrlMon_FWD_DEFINED__
typedef interface IUrlMon IUrlMon;
#endif
#ifndef __IForegroundTransfer_FWD_DEFINED__
#define __IForegroundTransfer_FWD_DEFINED__
typedef interface IForegroundTransfer IForegroundTransfer;
#endif
#ifndef __IAddrTrackingControl_FWD_DEFINED__
#define __IAddrTrackingControl_FWD_DEFINED__
typedef interface IAddrTrackingControl IAddrTrackingControl;
#endif
#ifndef __IAddrExclusionControl_FWD_DEFINED__
#define __IAddrExclusionControl_FWD_DEFINED__
typedef interface IAddrExclusionControl IAddrExclusionControl;
#endif
#ifndef __IComThreadingInfo_FWD_DEFINED__
#define __IComThreadingInfo_FWD_DEFINED__
typedef interface IComThreadingInfo IComThreadingInfo;
#endif
#ifndef __IProcessInitControl_FWD_DEFINED__
#define __IProcessInitControl_FWD_DEFINED__
typedef interface IProcessInitControl IProcessInitControl;
#endif
#ifndef __IInitializeSpy_FWD_DEFINED__
#define __IInitializeSpy_FWD_DEFINED__
typedef interface IInitializeSpy IInitializeSpy;
#endif
#ifndef __IThumbnailExtractor_FWD_DEFINED__
#define __IThumbnailExtractor_FWD_DEFINED__
typedef interface IThumbnailExtractor IThumbnailExtractor;
#endif
#ifndef __IEnumContextProps_FWD_DEFINED__
#define __IEnumContextProps_FWD_DEFINED__
typedef interface IEnumContextProps IEnumContextProps;
#endif
#ifndef __IContext_FWD_DEFINED__
#define __IContext_FWD_DEFINED__
typedef interface IContext IContext;
#endif
#ifndef __IObjContext_FWD_DEFINED__
#define __IObjContext_FWD_DEFINED__
typedef interface IObjContext IObjContext;
#endif
#ifndef __IStream_FWD_DEFINED__
#define __IStream_FWD_DEFINED__
typedef interface IStream IStream;
#endif
#ifndef __IEnumString_FWD_DEFINED__
#define __IEnumString_FWD_DEFINED__
typedef interface IEnumString IEnumString;
#endif
#ifndef __IRunningObjectTable_FWD_DEFINED__
#define __IRunningObjectTable_FWD_DEFINED__
typedef interface IRunningObjectTable IRunningObjectTable;
#endif
#ifndef __IMoniker_FWD_DEFINED__
#define __IMoniker_FWD_DEFINED__
typedef interface IMoniker IMoniker;
#endif
#ifndef __IAdviseSink_FWD_DEFINED__
#define __IAdviseSink_FWD_DEFINED__
typedef interface IAdviseSink IAdviseSink;
#endif
#ifndef __IAsyncManager_FWD_DEFINED__
#define __IAsyncManager_FWD_DEFINED__
typedef interface IAsyncManager IAsyncManager;
#endif
#ifndef __ISynchronize_FWD_DEFINED__
#define __ISynchronize_FWD_DEFINED__
typedef interface ISynchronize ISynchronize;
#endif
typedef struct _COSERVERINFO {
DWORD dwReserved1;
LPWSTR pwszName;
COAUTHINFO *pAuthInfo;
DWORD dwReserved2;
} COSERVERINFO;
/*****************************************************************************
* IMarshal interface
*/
#ifndef __IMarshal_INTERFACE_DEFINED__
#define __IMarshal_INTERFACE_DEFINED__
typedef IMarshal *LPMARSHAL;
DEFINE_GUID(IID_IMarshal, 0x00000003, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IMarshal : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE GetUnmarshalClass(
REFIID riid,
void *pv,
DWORD dwDestContext,
void *pvDestContext,
DWORD mshlflags,
CLSID *pCid) = 0;
virtual HRESULT STDMETHODCALLTYPE GetMarshalSizeMax(
REFIID riid,
void *pv,
DWORD dwDestContext,
void *pvDestContext,
DWORD mshlflags,
DWORD *pSize) = 0;
virtual HRESULT STDMETHODCALLTYPE MarshalInterface(
IStream *pStm,
REFIID riid,
void *pv,
DWORD dwDestContext,
void *pvDestContext,
DWORD mshlflags) = 0;
virtual HRESULT STDMETHODCALLTYPE UnmarshalInterface(
IStream *pStm,
REFIID riid,
void **ppv) = 0;
virtual HRESULT STDMETHODCALLTYPE ReleaseMarshalData(
IStream *pStm) = 0;
virtual HRESULT STDMETHODCALLTYPE DisconnectObject(
DWORD dwReserved) = 0;
};
#else
typedef struct IMarshalVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IMarshal* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IMarshal* This);
ULONG (STDMETHODCALLTYPE *Release)(
IMarshal* This);
/*** IMarshal methods ***/
HRESULT (STDMETHODCALLTYPE *GetUnmarshalClass)(
IMarshal* This,
REFIID riid,
void *pv,
DWORD dwDestContext,
void *pvDestContext,
DWORD mshlflags,
CLSID *pCid);
HRESULT (STDMETHODCALLTYPE *GetMarshalSizeMax)(
IMarshal* This,
REFIID riid,
void *pv,
DWORD dwDestContext,
void *pvDestContext,
DWORD mshlflags,
DWORD *pSize);
HRESULT (STDMETHODCALLTYPE *MarshalInterface)(
IMarshal* This,
IStream *pStm,
REFIID riid,
void *pv,
DWORD dwDestContext,
void *pvDestContext,
DWORD mshlflags);
HRESULT (STDMETHODCALLTYPE *UnmarshalInterface)(
IMarshal* This,
IStream *pStm,
REFIID riid,
void **ppv);
HRESULT (STDMETHODCALLTYPE *ReleaseMarshalData)(
IMarshal* This,
IStream *pStm);
HRESULT (STDMETHODCALLTYPE *DisconnectObject)(
IMarshal* This,
DWORD dwReserved);
END_INTERFACE
} IMarshalVtbl;
interface IMarshal {
CONST_VTBL IMarshalVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IMarshal_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IMarshal_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IMarshal_Release(This) (This)->lpVtbl->Release(This)
/*** IMarshal methods ***/
#define IMarshal_GetUnmarshalClass(This,riid,pv,dwDestContext,pvDestContext,mshlflags,pCid) (This)->lpVtbl->GetUnmarshalClass(This,riid,pv,dwDestContext,pvDestContext,mshlflags,pCid)
#define IMarshal_GetMarshalSizeMax(This,riid,pv,dwDestContext,pvDestContext,mshlflags,pSize) (This)->lpVtbl->GetMarshalSizeMax(This,riid,pv,dwDestContext,pvDestContext,mshlflags,pSize)
#define IMarshal_MarshalInterface(This,pStm,riid,pv,dwDestContext,pvDestContext,mshlflags) (This)->lpVtbl->MarshalInterface(This,pStm,riid,pv,dwDestContext,pvDestContext,mshlflags)
#define IMarshal_UnmarshalInterface(This,pStm,riid,ppv) (This)->lpVtbl->UnmarshalInterface(This,pStm,riid,ppv)
#define IMarshal_ReleaseMarshalData(This,pStm) (This)->lpVtbl->ReleaseMarshalData(This,pStm)
#define IMarshal_DisconnectObject(This,dwReserved) (This)->lpVtbl->DisconnectObject(This,dwReserved)
#endif
#endif
HRESULT STDMETHODCALLTYPE IMarshal_GetUnmarshalClass_Proxy(
IMarshal* This,
REFIID riid,
void *pv,
DWORD dwDestContext,
void *pvDestContext,
DWORD mshlflags,
CLSID *pCid);
void __RPC_STUB IMarshal_GetUnmarshalClass_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMarshal_GetMarshalSizeMax_Proxy(
IMarshal* This,
REFIID riid,
void *pv,
DWORD dwDestContext,
void *pvDestContext,
DWORD mshlflags,
DWORD *pSize);
void __RPC_STUB IMarshal_GetMarshalSizeMax_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMarshal_MarshalInterface_Proxy(
IMarshal* This,
IStream *pStm,
REFIID riid,
void *pv,
DWORD dwDestContext,
void *pvDestContext,
DWORD mshlflags);
void __RPC_STUB IMarshal_MarshalInterface_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMarshal_UnmarshalInterface_Proxy(
IMarshal* This,
IStream *pStm,
REFIID riid,
void **ppv);
void __RPC_STUB IMarshal_UnmarshalInterface_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMarshal_ReleaseMarshalData_Proxy(
IMarshal* This,
IStream *pStm);
void __RPC_STUB IMarshal_ReleaseMarshalData_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMarshal_DisconnectObject_Proxy(
IMarshal* This,
DWORD dwReserved);
void __RPC_STUB IMarshal_DisconnectObject_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IMarshal_INTERFACE_DEFINED__ */
/*****************************************************************************
* IMarshal2 interface
*/
#ifndef __IMarshal2_INTERFACE_DEFINED__
#define __IMarshal2_INTERFACE_DEFINED__
typedef IMarshal2 *LPMARSHAL2;
DEFINE_GUID(IID_IMarshal2, 0x000001cf, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IMarshal2 : public IMarshal
{
};
#else
typedef struct IMarshal2Vtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IMarshal2* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IMarshal2* This);
ULONG (STDMETHODCALLTYPE *Release)(
IMarshal2* This);
/*** IMarshal methods ***/
HRESULT (STDMETHODCALLTYPE *GetUnmarshalClass)(
IMarshal2* This,
REFIID riid,
void *pv,
DWORD dwDestContext,
void *pvDestContext,
DWORD mshlflags,
CLSID *pCid);
HRESULT (STDMETHODCALLTYPE *GetMarshalSizeMax)(
IMarshal2* This,
REFIID riid,
void *pv,
DWORD dwDestContext,
void *pvDestContext,
DWORD mshlflags,
DWORD *pSize);
HRESULT (STDMETHODCALLTYPE *MarshalInterface)(
IMarshal2* This,
IStream *pStm,
REFIID riid,
void *pv,
DWORD dwDestContext,
void *pvDestContext,
DWORD mshlflags);
HRESULT (STDMETHODCALLTYPE *UnmarshalInterface)(
IMarshal2* This,
IStream *pStm,
REFIID riid,
void **ppv);
HRESULT (STDMETHODCALLTYPE *ReleaseMarshalData)(
IMarshal2* This,
IStream *pStm);
HRESULT (STDMETHODCALLTYPE *DisconnectObject)(
IMarshal2* This,
DWORD dwReserved);
END_INTERFACE
} IMarshal2Vtbl;
interface IMarshal2 {
CONST_VTBL IMarshal2Vtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IMarshal2_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IMarshal2_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IMarshal2_Release(This) (This)->lpVtbl->Release(This)
/*** IMarshal methods ***/
#define IMarshal2_GetUnmarshalClass(This,riid,pv,dwDestContext,pvDestContext,mshlflags,pCid) (This)->lpVtbl->GetUnmarshalClass(This,riid,pv,dwDestContext,pvDestContext,mshlflags,pCid)
#define IMarshal2_GetMarshalSizeMax(This,riid,pv,dwDestContext,pvDestContext,mshlflags,pSize) (This)->lpVtbl->GetMarshalSizeMax(This,riid,pv,dwDestContext,pvDestContext,mshlflags,pSize)
#define IMarshal2_MarshalInterface(This,pStm,riid,pv,dwDestContext,pvDestContext,mshlflags) (This)->lpVtbl->MarshalInterface(This,pStm,riid,pv,dwDestContext,pvDestContext,mshlflags)
#define IMarshal2_UnmarshalInterface(This,pStm,riid,ppv) (This)->lpVtbl->UnmarshalInterface(This,pStm,riid,ppv)
#define IMarshal2_ReleaseMarshalData(This,pStm) (This)->lpVtbl->ReleaseMarshalData(This,pStm)
#define IMarshal2_DisconnectObject(This,dwReserved) (This)->lpVtbl->DisconnectObject(This,dwReserved)
#endif
#endif
#endif /* __IMarshal2_INTERFACE_DEFINED__ */
/*****************************************************************************
* IStdMarshalInfo interface
*/
#ifndef __IStdMarshalInfo_INTERFACE_DEFINED__
#define __IStdMarshalInfo_INTERFACE_DEFINED__
typedef IStdMarshalInfo *LPSTDMARSHALINFO;
DEFINE_GUID(IID_IStdMarshalInfo, 0x00000018, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IStdMarshalInfo : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE GetClassForHandler(
DWORD dwDestContext,
void *pvDestContext,
CLSID *pClsid) = 0;
};
#else
typedef struct IStdMarshalInfoVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IStdMarshalInfo* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IStdMarshalInfo* This);
ULONG (STDMETHODCALLTYPE *Release)(
IStdMarshalInfo* This);
/*** IStdMarshalInfo methods ***/
HRESULT (STDMETHODCALLTYPE *GetClassForHandler)(
IStdMarshalInfo* This,
DWORD dwDestContext,
void *pvDestContext,
CLSID *pClsid);
END_INTERFACE
} IStdMarshalInfoVtbl;
interface IStdMarshalInfo {
CONST_VTBL IStdMarshalInfoVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IStdMarshalInfo_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IStdMarshalInfo_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IStdMarshalInfo_Release(This) (This)->lpVtbl->Release(This)
/*** IStdMarshalInfo methods ***/
#define IStdMarshalInfo_GetClassForHandler(This,dwDestContext,pvDestContext,pClsid) (This)->lpVtbl->GetClassForHandler(This,dwDestContext,pvDestContext,pClsid)
#endif
#endif
HRESULT STDMETHODCALLTYPE IStdMarshalInfo_GetClassForHandler_Proxy(
IStdMarshalInfo* This,
DWORD dwDestContext,
void *pvDestContext,
CLSID *pClsid);
void __RPC_STUB IStdMarshalInfo_GetClassForHandler_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IStdMarshalInfo_INTERFACE_DEFINED__ */
/*****************************************************************************
* IExternalConnection interface
*/
#ifndef __IExternalConnection_INTERFACE_DEFINED__
#define __IExternalConnection_INTERFACE_DEFINED__
typedef IExternalConnection *LPEXTERNALCONNECTION;
typedef enum tagEXTCONN {
EXTCONN_STRONG = 0x1,
EXTCONN_WEAK = 0x2,
EXTCONN_CALLABLE = 0x4
} EXTCONN;
DEFINE_GUID(IID_IExternalConnection, 0x00000019, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IExternalConnection : public IUnknown
{
virtual DWORD STDMETHODCALLTYPE AddConnection(
DWORD extconn,
DWORD reserved) = 0;
virtual DWORD STDMETHODCALLTYPE ReleaseConnection(
DWORD extconn,
DWORD reserved,
BOOL fLastReleaseCloses) = 0;
};
#else
typedef struct IExternalConnectionVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IExternalConnection* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IExternalConnection* This);
ULONG (STDMETHODCALLTYPE *Release)(
IExternalConnection* This);
/*** IExternalConnection methods ***/
DWORD (STDMETHODCALLTYPE *AddConnection)(
IExternalConnection* This,
DWORD extconn,
DWORD reserved);
DWORD (STDMETHODCALLTYPE *ReleaseConnection)(
IExternalConnection* This,
DWORD extconn,
DWORD reserved,
BOOL fLastReleaseCloses);
END_INTERFACE
} IExternalConnectionVtbl;
interface IExternalConnection {
CONST_VTBL IExternalConnectionVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IExternalConnection_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IExternalConnection_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IExternalConnection_Release(This) (This)->lpVtbl->Release(This)
/*** IExternalConnection methods ***/
#define IExternalConnection_AddConnection(This,extconn,reserved) (This)->lpVtbl->AddConnection(This,extconn,reserved)
#define IExternalConnection_ReleaseConnection(This,extconn,reserved,fLastReleaseCloses) (This)->lpVtbl->ReleaseConnection(This,extconn,reserved,fLastReleaseCloses)
#endif
#endif
DWORD STDMETHODCALLTYPE IExternalConnection_AddConnection_Proxy(
IExternalConnection* This,
DWORD extconn,
DWORD reserved);
void __RPC_STUB IExternalConnection_AddConnection_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
DWORD STDMETHODCALLTYPE IExternalConnection_ReleaseConnection_Proxy(
IExternalConnection* This,
DWORD extconn,
DWORD reserved,
BOOL fLastReleaseCloses);
void __RPC_STUB IExternalConnection_ReleaseConnection_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IExternalConnection_INTERFACE_DEFINED__ */
/*****************************************************************************
* IMultiQI interface
*/
#ifndef __IMultiQI_INTERFACE_DEFINED__
#define __IMultiQI_INTERFACE_DEFINED__
typedef IMultiQI *LPMULTIQI;
typedef struct tagMULTI_QI {
const IID *pIID;
IUnknown *pItf;
HRESULT hr;
} MULTI_QI;
DEFINE_GUID(IID_IMultiQI, 0x00000020, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IMultiQI : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE QueryMultipleInterfaces(
ULONG cMQIs,
MULTI_QI *pMQIs) = 0;
};
#else
typedef struct IMultiQIVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IMultiQI* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IMultiQI* This);
ULONG (STDMETHODCALLTYPE *Release)(
IMultiQI* This);
/*** IMultiQI methods ***/
HRESULT (STDMETHODCALLTYPE *QueryMultipleInterfaces)(
IMultiQI* This,
ULONG cMQIs,
MULTI_QI *pMQIs);
END_INTERFACE
} IMultiQIVtbl;
interface IMultiQI {
CONST_VTBL IMultiQIVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IMultiQI_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IMultiQI_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IMultiQI_Release(This) (This)->lpVtbl->Release(This)
/*** IMultiQI methods ***/
#define IMultiQI_QueryMultipleInterfaces(This,cMQIs,pMQIs) (This)->lpVtbl->QueryMultipleInterfaces(This,cMQIs,pMQIs)
#endif
#endif
HRESULT STDMETHODCALLTYPE IMultiQI_QueryMultipleInterfaces_Proxy(
IMultiQI* This,
ULONG cMQIs,
MULTI_QI *pMQIs);
void __RPC_STUB IMultiQI_QueryMultipleInterfaces_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IMultiQI_INTERFACE_DEFINED__ */
/*****************************************************************************
* IMalloc interface
*/
#ifndef __IMalloc_INTERFACE_DEFINED__
#define __IMalloc_INTERFACE_DEFINED__
typedef IMalloc *LPMALLOC;
DEFINE_GUID(IID_IMalloc, 0x00000002, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IMalloc : public IUnknown
{
virtual LPVOID STDMETHODCALLTYPE Alloc(
ULONG cb) = 0;
virtual LPVOID STDMETHODCALLTYPE Realloc(
LPVOID pv,
ULONG cb) = 0;
virtual void STDMETHODCALLTYPE Free(
LPVOID pv) = 0;
virtual ULONG STDMETHODCALLTYPE GetSize(
LPVOID pv) = 0;
virtual int STDMETHODCALLTYPE DidAlloc(
LPVOID pv) = 0;
virtual void STDMETHODCALLTYPE HeapMinimize(
) = 0;
};
#else
typedef struct IMallocVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IMalloc* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IMalloc* This);
ULONG (STDMETHODCALLTYPE *Release)(
IMalloc* This);
/*** IMalloc methods ***/
LPVOID (STDMETHODCALLTYPE *Alloc)(
IMalloc* This,
ULONG cb);
LPVOID (STDMETHODCALLTYPE *Realloc)(
IMalloc* This,
LPVOID pv,
ULONG cb);
void (STDMETHODCALLTYPE *Free)(
IMalloc* This,
LPVOID pv);
ULONG (STDMETHODCALLTYPE *GetSize)(
IMalloc* This,
LPVOID pv);
int (STDMETHODCALLTYPE *DidAlloc)(
IMalloc* This,
LPVOID pv);
void (STDMETHODCALLTYPE *HeapMinimize)(
IMalloc* This);
END_INTERFACE
} IMallocVtbl;
interface IMalloc {
CONST_VTBL IMallocVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IMalloc_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IMalloc_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IMalloc_Release(This) (This)->lpVtbl->Release(This)
/*** IMalloc methods ***/
#define IMalloc_Alloc(This,cb) (This)->lpVtbl->Alloc(This,cb)
#define IMalloc_Realloc(This,pv,cb) (This)->lpVtbl->Realloc(This,pv,cb)
#define IMalloc_Free(This,pv) (This)->lpVtbl->Free(This,pv)
#define IMalloc_GetSize(This,pv) (This)->lpVtbl->GetSize(This,pv)
#define IMalloc_DidAlloc(This,pv) (This)->lpVtbl->DidAlloc(This,pv)
#define IMalloc_HeapMinimize(This) (This)->lpVtbl->HeapMinimize(This)
#endif
#endif
LPVOID STDMETHODCALLTYPE IMalloc_Alloc_Proxy(
IMalloc* This,
ULONG cb);
void __RPC_STUB IMalloc_Alloc_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
LPVOID STDMETHODCALLTYPE IMalloc_Realloc_Proxy(
IMalloc* This,
LPVOID pv,
ULONG cb);
void __RPC_STUB IMalloc_Realloc_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IMalloc_Free_Proxy(
IMalloc* This,
LPVOID pv);
void __RPC_STUB IMalloc_Free_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
ULONG STDMETHODCALLTYPE IMalloc_GetSize_Proxy(
IMalloc* This,
LPVOID pv);
void __RPC_STUB IMalloc_GetSize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
int STDMETHODCALLTYPE IMalloc_DidAlloc_Proxy(
IMalloc* This,
LPVOID pv);
void __RPC_STUB IMalloc_DidAlloc_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IMalloc_HeapMinimize_Proxy(
IMalloc* This);
void __RPC_STUB IMalloc_HeapMinimize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IMalloc_INTERFACE_DEFINED__ */
/*****************************************************************************
* IMallocSpy interface
*/
#ifndef __IMallocSpy_INTERFACE_DEFINED__
#define __IMallocSpy_INTERFACE_DEFINED__
typedef IMallocSpy *LPMALLOCSPY;
DEFINE_GUID(IID_IMallocSpy, 0x0000001d, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IMallocSpy : public IUnknown
{
virtual ULONG STDMETHODCALLTYPE PreAlloc(
ULONG cbRequest) = 0;
virtual LPVOID STDMETHODCALLTYPE PostAlloc(
LPVOID pActual) = 0;
virtual LPVOID STDMETHODCALLTYPE PreFree(
LPVOID pRequest,
BOOL fSpyed) = 0;
virtual void STDMETHODCALLTYPE PostFree(
BOOL fSpyed) = 0;
virtual ULONG STDMETHODCALLTYPE PreRealloc(
LPVOID pRequest,
ULONG cbRequest,
LPVOID *ppNewRequest,
BOOL fSpyed) = 0;
virtual LPVOID STDMETHODCALLTYPE PostRealloc(
LPVOID pActual,
BOOL fSpyed) = 0;
virtual LPVOID STDMETHODCALLTYPE PreGetSize(
LPVOID pRequest,
BOOL fSpyed) = 0;
virtual ULONG STDMETHODCALLTYPE PostGetSize(
ULONG cbActual,
BOOL fSpyed) = 0;
virtual LPVOID STDMETHODCALLTYPE PreDidAlloc(
LPVOID pRequest,
BOOL fSpyed) = 0;
virtual int STDMETHODCALLTYPE PostDidAlloc(
LPVOID pRequest,
BOOL fSpyed,
int fActual) = 0;
virtual void STDMETHODCALLTYPE PreHeapMinimize(
) = 0;
virtual void STDMETHODCALLTYPE PostHeapMinimize(
) = 0;
};
#else
typedef struct IMallocSpyVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IMallocSpy* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IMallocSpy* This);
ULONG (STDMETHODCALLTYPE *Release)(
IMallocSpy* This);
/*** IMallocSpy methods ***/
ULONG (STDMETHODCALLTYPE *PreAlloc)(
IMallocSpy* This,
ULONG cbRequest);
LPVOID (STDMETHODCALLTYPE *PostAlloc)(
IMallocSpy* This,
LPVOID pActual);
LPVOID (STDMETHODCALLTYPE *PreFree)(
IMallocSpy* This,
LPVOID pRequest,
BOOL fSpyed);
void (STDMETHODCALLTYPE *PostFree)(
IMallocSpy* This,
BOOL fSpyed);
ULONG (STDMETHODCALLTYPE *PreRealloc)(
IMallocSpy* This,
LPVOID pRequest,
ULONG cbRequest,
LPVOID *ppNewRequest,
BOOL fSpyed);
LPVOID (STDMETHODCALLTYPE *PostRealloc)(
IMallocSpy* This,
LPVOID pActual,
BOOL fSpyed);
LPVOID (STDMETHODCALLTYPE *PreGetSize)(
IMallocSpy* This,
LPVOID pRequest,
BOOL fSpyed);
ULONG (STDMETHODCALLTYPE *PostGetSize)(
IMallocSpy* This,
ULONG cbActual,
BOOL fSpyed);
LPVOID (STDMETHODCALLTYPE *PreDidAlloc)(
IMallocSpy* This,
LPVOID pRequest,
BOOL fSpyed);
int (STDMETHODCALLTYPE *PostDidAlloc)(
IMallocSpy* This,
LPVOID pRequest,
BOOL fSpyed,
int fActual);
void (STDMETHODCALLTYPE *PreHeapMinimize)(
IMallocSpy* This);
void (STDMETHODCALLTYPE *PostHeapMinimize)(
IMallocSpy* This);
END_INTERFACE
} IMallocSpyVtbl;
interface IMallocSpy {
CONST_VTBL IMallocSpyVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IMallocSpy_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IMallocSpy_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IMallocSpy_Release(This) (This)->lpVtbl->Release(This)
/*** IMallocSpy methods ***/
#define IMallocSpy_PreAlloc(This,cbRequest) (This)->lpVtbl->PreAlloc(This,cbRequest)
#define IMallocSpy_PostAlloc(This,pActual) (This)->lpVtbl->PostAlloc(This,pActual)
#define IMallocSpy_PreFree(This,pRequest,fSpyed) (This)->lpVtbl->PreFree(This,pRequest,fSpyed)
#define IMallocSpy_PostFree(This,fSpyed) (This)->lpVtbl->PostFree(This,fSpyed)
#define IMallocSpy_PreRealloc(This,pRequest,cbRequest,ppNewRequest,fSpyed) (This)->lpVtbl->PreRealloc(This,pRequest,cbRequest,ppNewRequest,fSpyed)
#define IMallocSpy_PostRealloc(This,pActual,fSpyed) (This)->lpVtbl->PostRealloc(This,pActual,fSpyed)
#define IMallocSpy_PreGetSize(This,pRequest,fSpyed) (This)->lpVtbl->PreGetSize(This,pRequest,fSpyed)
#define IMallocSpy_PostGetSize(This,cbActual,fSpyed) (This)->lpVtbl->PostGetSize(This,cbActual,fSpyed)
#define IMallocSpy_PreDidAlloc(This,pRequest,fSpyed) (This)->lpVtbl->PreDidAlloc(This,pRequest,fSpyed)
#define IMallocSpy_PostDidAlloc(This,pRequest,fSpyed,fActual) (This)->lpVtbl->PostDidAlloc(This,pRequest,fSpyed,fActual)
#define IMallocSpy_PreHeapMinimize(This) (This)->lpVtbl->PreHeapMinimize(This)
#define IMallocSpy_PostHeapMinimize(This) (This)->lpVtbl->PostHeapMinimize(This)
#endif
#endif
ULONG STDMETHODCALLTYPE IMallocSpy_PreAlloc_Proxy(
IMallocSpy* This,
ULONG cbRequest);
void __RPC_STUB IMallocSpy_PreAlloc_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
LPVOID STDMETHODCALLTYPE IMallocSpy_PostAlloc_Proxy(
IMallocSpy* This,
LPVOID pActual);
void __RPC_STUB IMallocSpy_PostAlloc_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
LPVOID STDMETHODCALLTYPE IMallocSpy_PreFree_Proxy(
IMallocSpy* This,
LPVOID pRequest,
BOOL fSpyed);
void __RPC_STUB IMallocSpy_PreFree_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IMallocSpy_PostFree_Proxy(
IMallocSpy* This,
BOOL fSpyed);
void __RPC_STUB IMallocSpy_PostFree_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
ULONG STDMETHODCALLTYPE IMallocSpy_PreRealloc_Proxy(
IMallocSpy* This,
LPVOID pRequest,
ULONG cbRequest,
LPVOID *ppNewRequest,
BOOL fSpyed);
void __RPC_STUB IMallocSpy_PreRealloc_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
LPVOID STDMETHODCALLTYPE IMallocSpy_PostRealloc_Proxy(
IMallocSpy* This,
LPVOID pActual,
BOOL fSpyed);
void __RPC_STUB IMallocSpy_PostRealloc_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
LPVOID STDMETHODCALLTYPE IMallocSpy_PreGetSize_Proxy(
IMallocSpy* This,
LPVOID pRequest,
BOOL fSpyed);
void __RPC_STUB IMallocSpy_PreGetSize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
ULONG STDMETHODCALLTYPE IMallocSpy_PostGetSize_Proxy(
IMallocSpy* This,
ULONG cbActual,
BOOL fSpyed);
void __RPC_STUB IMallocSpy_PostGetSize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
LPVOID STDMETHODCALLTYPE IMallocSpy_PreDidAlloc_Proxy(
IMallocSpy* This,
LPVOID pRequest,
BOOL fSpyed);
void __RPC_STUB IMallocSpy_PreDidAlloc_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
int STDMETHODCALLTYPE IMallocSpy_PostDidAlloc_Proxy(
IMallocSpy* This,
LPVOID pRequest,
BOOL fSpyed,
int fActual);
void __RPC_STUB IMallocSpy_PostDidAlloc_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IMallocSpy_PreHeapMinimize_Proxy(
IMallocSpy* This);
void __RPC_STUB IMallocSpy_PreHeapMinimize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IMallocSpy_PostHeapMinimize_Proxy(
IMallocSpy* This);
void __RPC_STUB IMallocSpy_PostHeapMinimize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IMallocSpy_INTERFACE_DEFINED__ */
/*****************************************************************************
* IInternalUnknown interface
*/
#ifndef __IInternalUnknown_INTERFACE_DEFINED__
#define __IInternalUnknown_INTERFACE_DEFINED__
DEFINE_GUID(IID_IInternalUnknown, 0x00000021, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IInternalUnknown : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE QueryInternalInterface(
REFIID riid,
void **ppv) = 0;
};
#else
typedef struct IInternalUnknownVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IInternalUnknown* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IInternalUnknown* This);
ULONG (STDMETHODCALLTYPE *Release)(
IInternalUnknown* This);
/*** IInternalUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInternalInterface)(
IInternalUnknown* This,
REFIID riid,
void **ppv);
END_INTERFACE
} IInternalUnknownVtbl;
interface IInternalUnknown {
CONST_VTBL IInternalUnknownVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IInternalUnknown_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IInternalUnknown_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IInternalUnknown_Release(This) (This)->lpVtbl->Release(This)
/*** IInternalUnknown methods ***/
#define IInternalUnknown_QueryInternalInterface(This,riid,ppv) (This)->lpVtbl->QueryInternalInterface(This,riid,ppv)
#endif
#endif
HRESULT STDMETHODCALLTYPE IInternalUnknown_QueryInternalInterface_Proxy(
IInternalUnknown* This,
REFIID riid,
void **ppv);
void __RPC_STUB IInternalUnknown_QueryInternalInterface_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IInternalUnknown_INTERFACE_DEFINED__ */
/*****************************************************************************
* IEnumUnknown interface
*/
#ifndef __IEnumUnknown_INTERFACE_DEFINED__
#define __IEnumUnknown_INTERFACE_DEFINED__
typedef IEnumUnknown *LPENUMUNKNOWN;
DEFINE_GUID(IID_IEnumUnknown, 0x00000100, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IEnumUnknown : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Next(
ULONG celt,
IUnknown **rgelt,
ULONG *pceltFetched) = 0;
virtual HRESULT STDMETHODCALLTYPE Skip(
ULONG celt) = 0;
virtual HRESULT STDMETHODCALLTYPE Reset(
) = 0;
virtual HRESULT STDMETHODCALLTYPE Clone(
IEnumUnknown **ppenum) = 0;
};
#else
typedef struct IEnumUnknownVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IEnumUnknown* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IEnumUnknown* This);
ULONG (STDMETHODCALLTYPE *Release)(
IEnumUnknown* This);
/*** IEnumUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *Next)(
IEnumUnknown* This,
ULONG celt,
IUnknown **rgelt,
ULONG *pceltFetched);
HRESULT (STDMETHODCALLTYPE *Skip)(
IEnumUnknown* This,
ULONG celt);
HRESULT (STDMETHODCALLTYPE *Reset)(
IEnumUnknown* This);
HRESULT (STDMETHODCALLTYPE *Clone)(
IEnumUnknown* This,
IEnumUnknown **ppenum);
END_INTERFACE
} IEnumUnknownVtbl;
interface IEnumUnknown {
CONST_VTBL IEnumUnknownVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IEnumUnknown_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IEnumUnknown_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IEnumUnknown_Release(This) (This)->lpVtbl->Release(This)
/*** IEnumUnknown methods ***/
#define IEnumUnknown_Next(This,celt,rgelt,pceltFetched) (This)->lpVtbl->Next(This,celt,rgelt,pceltFetched)
#define IEnumUnknown_Skip(This,celt) (This)->lpVtbl->Skip(This,celt)
#define IEnumUnknown_Reset(This) (This)->lpVtbl->Reset(This)
#define IEnumUnknown_Clone(This,ppenum) (This)->lpVtbl->Clone(This,ppenum)
#endif
#endif
HRESULT STDMETHODCALLTYPE IEnumUnknown_RemoteNext_Proxy(
IEnumUnknown* This,
ULONG celt,
IUnknown **rgelt,
ULONG *pceltFetched);
void __RPC_STUB IEnumUnknown_RemoteNext_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumUnknown_Skip_Proxy(
IEnumUnknown* This,
ULONG celt);
void __RPC_STUB IEnumUnknown_Skip_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumUnknown_Reset_Proxy(
IEnumUnknown* This);
void __RPC_STUB IEnumUnknown_Reset_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumUnknown_Clone_Proxy(
IEnumUnknown* This,
IEnumUnknown **ppenum);
void __RPC_STUB IEnumUnknown_Clone_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK IEnumUnknown_Next_Proxy(
IEnumUnknown* This,
ULONG celt,
IUnknown **rgelt,
ULONG *pceltFetched);
HRESULT __RPC_STUB IEnumUnknown_Next_Stub(
IEnumUnknown* This,
ULONG celt,
IUnknown **rgelt,
ULONG *pceltFetched);
#endif /* __IEnumUnknown_INTERFACE_DEFINED__ */
/*****************************************************************************
* ISurrogate interface
*/
#ifndef __ISurrogate_INTERFACE_DEFINED__
#define __ISurrogate_INTERFACE_DEFINED__
typedef ISurrogate *LPSURROGATE;
DEFINE_GUID(IID_ISurrogate, 0x00000022, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface ISurrogate : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE LoadDllServer(
REFCLSID Clsid) = 0;
virtual HRESULT STDMETHODCALLTYPE FreeSurrogate(
) = 0;
};
#else
typedef struct ISurrogateVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
ISurrogate* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
ISurrogate* This);
ULONG (STDMETHODCALLTYPE *Release)(
ISurrogate* This);
/*** ISurrogate methods ***/
HRESULT (STDMETHODCALLTYPE *LoadDllServer)(
ISurrogate* This,
REFCLSID Clsid);
HRESULT (STDMETHODCALLTYPE *FreeSurrogate)(
ISurrogate* This);
END_INTERFACE
} ISurrogateVtbl;
interface ISurrogate {
CONST_VTBL ISurrogateVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define ISurrogate_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define ISurrogate_AddRef(This) (This)->lpVtbl->AddRef(This)
#define ISurrogate_Release(This) (This)->lpVtbl->Release(This)
/*** ISurrogate methods ***/
#define ISurrogate_LoadDllServer(This,Clsid) (This)->lpVtbl->LoadDllServer(This,Clsid)
#define ISurrogate_FreeSurrogate(This) (This)->lpVtbl->FreeSurrogate(This)
#endif
#endif
HRESULT STDMETHODCALLTYPE ISurrogate_LoadDllServer_Proxy(
ISurrogate* This,
REFCLSID Clsid);
void __RPC_STUB ISurrogate_LoadDllServer_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ISurrogate_FreeSurrogate_Proxy(
ISurrogate* This);
void __RPC_STUB ISurrogate_FreeSurrogate_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __ISurrogate_INTERFACE_DEFINED__ */
/*****************************************************************************
* IGlobalInterfaceTable interface
*/
#ifndef __IGlobalInterfaceTable_INTERFACE_DEFINED__
#define __IGlobalInterfaceTable_INTERFACE_DEFINED__
typedef IGlobalInterfaceTable *LPGLOBALINTERFACETABLE;
DEFINE_GUID(IID_IGlobalInterfaceTable, 0x00000146, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IGlobalInterfaceTable : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE RegisterInterfaceInGlobal(
IUnknown *pUnk,
REFIID riid,
DWORD *pdwCookie) = 0;
virtual HRESULT STDMETHODCALLTYPE RevokeInterfaceFromGlobal(
DWORD dwCookie) = 0;
virtual HRESULT STDMETHODCALLTYPE GetInterfaceFromGlobal(
DWORD dwCookie,
REFIID riid,
void **ppv) = 0;
};
#else
typedef struct IGlobalInterfaceTableVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IGlobalInterfaceTable* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IGlobalInterfaceTable* This);
ULONG (STDMETHODCALLTYPE *Release)(
IGlobalInterfaceTable* This);
/*** IGlobalInterfaceTable methods ***/
HRESULT (STDMETHODCALLTYPE *RegisterInterfaceInGlobal)(
IGlobalInterfaceTable* This,
IUnknown *pUnk,
REFIID riid,
DWORD *pdwCookie);
HRESULT (STDMETHODCALLTYPE *RevokeInterfaceFromGlobal)(
IGlobalInterfaceTable* This,
DWORD dwCookie);
HRESULT (STDMETHODCALLTYPE *GetInterfaceFromGlobal)(
IGlobalInterfaceTable* This,
DWORD dwCookie,
REFIID riid,
void **ppv);
END_INTERFACE
} IGlobalInterfaceTableVtbl;
interface IGlobalInterfaceTable {
CONST_VTBL IGlobalInterfaceTableVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IGlobalInterfaceTable_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IGlobalInterfaceTable_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IGlobalInterfaceTable_Release(This) (This)->lpVtbl->Release(This)
/*** IGlobalInterfaceTable methods ***/
#define IGlobalInterfaceTable_RegisterInterfaceInGlobal(This,pUnk,riid,pdwCookie) (This)->lpVtbl->RegisterInterfaceInGlobal(This,pUnk,riid,pdwCookie)
#define IGlobalInterfaceTable_RevokeInterfaceFromGlobal(This,dwCookie) (This)->lpVtbl->RevokeInterfaceFromGlobal(This,dwCookie)
#define IGlobalInterfaceTable_GetInterfaceFromGlobal(This,dwCookie,riid,ppv) (This)->lpVtbl->GetInterfaceFromGlobal(This,dwCookie,riid,ppv)
#endif
#endif
HRESULT STDMETHODCALLTYPE IGlobalInterfaceTable_RegisterInterfaceInGlobal_Proxy(
IGlobalInterfaceTable* This,
IUnknown *pUnk,
REFIID riid,
DWORD *pdwCookie);
void __RPC_STUB IGlobalInterfaceTable_RegisterInterfaceInGlobal_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IGlobalInterfaceTable_RevokeInterfaceFromGlobal_Proxy(
IGlobalInterfaceTable* This,
DWORD dwCookie);
void __RPC_STUB IGlobalInterfaceTable_RevokeInterfaceFromGlobal_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IGlobalInterfaceTable_GetInterfaceFromGlobal_Proxy(
IGlobalInterfaceTable* This,
DWORD dwCookie,
REFIID riid,
void **ppv);
void __RPC_STUB IGlobalInterfaceTable_GetInterfaceFromGlobal_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IGlobalInterfaceTable_INTERFACE_DEFINED__ */
/*****************************************************************************
* IBindCtx interface
*/
#ifndef __IBindCtx_INTERFACE_DEFINED__
#define __IBindCtx_INTERFACE_DEFINED__
typedef IBindCtx *LPBINDCTX;
typedef IBindCtx *LPBC;
typedef struct tagBIND_OPTS {
DWORD cbStruct;
DWORD grfFlags;
DWORD grfMode;
DWORD dwTickCountDeadline;
} BIND_OPTS;
typedef struct tagBIND_OPTS *LPBIND_OPTS;
typedef struct tagBIND_OPTS2 {
DWORD cbStruct;
DWORD grfFlags;
DWORD grfMode;
DWORD dwTickCountDeadline;
DWORD dwTrackFlags;
DWORD dwClassContext;
LCID locale;
COSERVERINFO *pServerInfo;
} BIND_OPTS2;
typedef struct tagBIND_OPTS2 *LPBIND_OPTS2;
typedef enum tagBIND_FLAGS {
BIND_MAYBOTHERUSER = 1,
BIND_JUSTTESTEXISTENCE = 2
} BIND_FLAGS;
DEFINE_GUID(IID_IBindCtx, 0x0000000e, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IBindCtx : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE RegisterObjectBound(
IUnknown *punk) = 0;
virtual HRESULT STDMETHODCALLTYPE RevokeObjectBound(
IUnknown *punk) = 0;
virtual HRESULT STDMETHODCALLTYPE ReleaseBoundObjects(
) = 0;
virtual HRESULT STDMETHODCALLTYPE SetBindOptions(
BIND_OPTS *pbindopts) = 0;
virtual HRESULT STDMETHODCALLTYPE GetBindOptions(
BIND_OPTS *pbindopts) = 0;
virtual HRESULT STDMETHODCALLTYPE GetRunningObjectTable(
IRunningObjectTable **pprot) = 0;
virtual HRESULT STDMETHODCALLTYPE RegisterObjectParam(
LPOLESTR pszKey,
IUnknown *punk) = 0;
virtual HRESULT STDMETHODCALLTYPE GetObjectParam(
LPOLESTR pszKey,
IUnknown **ppunk) = 0;
virtual HRESULT STDMETHODCALLTYPE EnumObjectParam(
IEnumString **ppenum) = 0;
virtual HRESULT STDMETHODCALLTYPE RevokeObjectParam(
LPOLESTR pszKey) = 0;
};
#else
typedef struct IBindCtxVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IBindCtx* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IBindCtx* This);
ULONG (STDMETHODCALLTYPE *Release)(
IBindCtx* This);
/*** IBindCtx methods ***/
HRESULT (STDMETHODCALLTYPE *RegisterObjectBound)(
IBindCtx* This,
IUnknown *punk);
HRESULT (STDMETHODCALLTYPE *RevokeObjectBound)(
IBindCtx* This,
IUnknown *punk);
HRESULT (STDMETHODCALLTYPE *ReleaseBoundObjects)(
IBindCtx* This);
HRESULT (STDMETHODCALLTYPE *SetBindOptions)(
IBindCtx* This,
BIND_OPTS *pbindopts);
HRESULT (STDMETHODCALLTYPE *GetBindOptions)(
IBindCtx* This,
BIND_OPTS *pbindopts);
HRESULT (STDMETHODCALLTYPE *GetRunningObjectTable)(
IBindCtx* This,
IRunningObjectTable **pprot);
HRESULT (STDMETHODCALLTYPE *RegisterObjectParam)(
IBindCtx* This,
LPOLESTR pszKey,
IUnknown *punk);
HRESULT (STDMETHODCALLTYPE *GetObjectParam)(
IBindCtx* This,
LPOLESTR pszKey,
IUnknown **ppunk);
HRESULT (STDMETHODCALLTYPE *EnumObjectParam)(
IBindCtx* This,
IEnumString **ppenum);
HRESULT (STDMETHODCALLTYPE *RevokeObjectParam)(
IBindCtx* This,
LPOLESTR pszKey);
END_INTERFACE
} IBindCtxVtbl;
interface IBindCtx {
CONST_VTBL IBindCtxVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IBindCtx_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IBindCtx_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IBindCtx_Release(This) (This)->lpVtbl->Release(This)
/*** IBindCtx methods ***/
#define IBindCtx_RegisterObjectBound(This,punk) (This)->lpVtbl->RegisterObjectBound(This,punk)
#define IBindCtx_RevokeObjectBound(This,punk) (This)->lpVtbl->RevokeObjectBound(This,punk)
#define IBindCtx_ReleaseBoundObjects(This) (This)->lpVtbl->ReleaseBoundObjects(This)
#define IBindCtx_SetBindOptions(This,pbindopts) (This)->lpVtbl->SetBindOptions(This,pbindopts)
#define IBindCtx_GetBindOptions(This,pbindopts) (This)->lpVtbl->GetBindOptions(This,pbindopts)
#define IBindCtx_GetRunningObjectTable(This,pprot) (This)->lpVtbl->GetRunningObjectTable(This,pprot)
#define IBindCtx_RegisterObjectParam(This,pszKey,punk) (This)->lpVtbl->RegisterObjectParam(This,pszKey,punk)
#define IBindCtx_GetObjectParam(This,pszKey,ppunk) (This)->lpVtbl->GetObjectParam(This,pszKey,ppunk)
#define IBindCtx_EnumObjectParam(This,ppenum) (This)->lpVtbl->EnumObjectParam(This,ppenum)
#define IBindCtx_RevokeObjectParam(This,pszKey) (This)->lpVtbl->RevokeObjectParam(This,pszKey)
#endif
#endif
HRESULT STDMETHODCALLTYPE IBindCtx_RegisterObjectBound_Proxy(
IBindCtx* This,
IUnknown *punk);
void __RPC_STUB IBindCtx_RegisterObjectBound_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IBindCtx_RevokeObjectBound_Proxy(
IBindCtx* This,
IUnknown *punk);
void __RPC_STUB IBindCtx_RevokeObjectBound_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IBindCtx_ReleaseBoundObjects_Proxy(
IBindCtx* This);
void __RPC_STUB IBindCtx_ReleaseBoundObjects_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IBindCtx_RemoteSetBindOptions_Proxy(
IBindCtx* This,
BIND_OPTS2 *pbindopts);
void __RPC_STUB IBindCtx_RemoteSetBindOptions_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IBindCtx_RemoteGetBindOptions_Proxy(
IBindCtx* This,
BIND_OPTS2 *pbindopts);
void __RPC_STUB IBindCtx_RemoteGetBindOptions_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IBindCtx_GetRunningObjectTable_Proxy(
IBindCtx* This,
IRunningObjectTable **pprot);
void __RPC_STUB IBindCtx_GetRunningObjectTable_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IBindCtx_RegisterObjectParam_Proxy(
IBindCtx* This,
LPOLESTR pszKey,
IUnknown *punk);
void __RPC_STUB IBindCtx_RegisterObjectParam_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IBindCtx_GetObjectParam_Proxy(
IBindCtx* This,
LPOLESTR pszKey,
IUnknown **ppunk);
void __RPC_STUB IBindCtx_GetObjectParam_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IBindCtx_EnumObjectParam_Proxy(
IBindCtx* This,
IEnumString **ppenum);
void __RPC_STUB IBindCtx_EnumObjectParam_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IBindCtx_RevokeObjectParam_Proxy(
IBindCtx* This,
LPOLESTR pszKey);
void __RPC_STUB IBindCtx_RevokeObjectParam_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK IBindCtx_SetBindOptions_Proxy(
IBindCtx* This,
BIND_OPTS *pbindopts);
HRESULT __RPC_STUB IBindCtx_SetBindOptions_Stub(
IBindCtx* This,
BIND_OPTS2 *pbindopts);
HRESULT CALLBACK IBindCtx_GetBindOptions_Proxy(
IBindCtx* This,
BIND_OPTS *pbindopts);
HRESULT __RPC_STUB IBindCtx_GetBindOptions_Stub(
IBindCtx* This,
BIND_OPTS2 *pbindopts);
#endif /* __IBindCtx_INTERFACE_DEFINED__ */
/*****************************************************************************
* IEnumMoniker interface
*/
#ifndef __IEnumMoniker_INTERFACE_DEFINED__
#define __IEnumMoniker_INTERFACE_DEFINED__
typedef IEnumMoniker *LPENUMMONIKER;
DEFINE_GUID(IID_IEnumMoniker, 0x00000102, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IEnumMoniker : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Next(
ULONG celt,
IMoniker **rgelt,
ULONG *pceltFetched) = 0;
virtual HRESULT STDMETHODCALLTYPE Skip(
ULONG celt) = 0;
virtual HRESULT STDMETHODCALLTYPE Reset(
) = 0;
virtual HRESULT STDMETHODCALLTYPE Clone(
IEnumMoniker **ppenum) = 0;
};
#else
typedef struct IEnumMonikerVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IEnumMoniker* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IEnumMoniker* This);
ULONG (STDMETHODCALLTYPE *Release)(
IEnumMoniker* This);
/*** IEnumMoniker methods ***/
HRESULT (STDMETHODCALLTYPE *Next)(
IEnumMoniker* This,
ULONG celt,
IMoniker **rgelt,
ULONG *pceltFetched);
HRESULT (STDMETHODCALLTYPE *Skip)(
IEnumMoniker* This,
ULONG celt);
HRESULT (STDMETHODCALLTYPE *Reset)(
IEnumMoniker* This);
HRESULT (STDMETHODCALLTYPE *Clone)(
IEnumMoniker* This,
IEnumMoniker **ppenum);
END_INTERFACE
} IEnumMonikerVtbl;
interface IEnumMoniker {
CONST_VTBL IEnumMonikerVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IEnumMoniker_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IEnumMoniker_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IEnumMoniker_Release(This) (This)->lpVtbl->Release(This)
/*** IEnumMoniker methods ***/
#define IEnumMoniker_Next(This,celt,rgelt,pceltFetched) (This)->lpVtbl->Next(This,celt,rgelt,pceltFetched)
#define IEnumMoniker_Skip(This,celt) (This)->lpVtbl->Skip(This,celt)
#define IEnumMoniker_Reset(This) (This)->lpVtbl->Reset(This)
#define IEnumMoniker_Clone(This,ppenum) (This)->lpVtbl->Clone(This,ppenum)
#endif
#endif
HRESULT STDMETHODCALLTYPE IEnumMoniker_RemoteNext_Proxy(
IEnumMoniker* This,
ULONG celt,
IMoniker **rgelt,
ULONG *pceltFetched);
void __RPC_STUB IEnumMoniker_RemoteNext_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumMoniker_Skip_Proxy(
IEnumMoniker* This,
ULONG celt);
void __RPC_STUB IEnumMoniker_Skip_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumMoniker_Reset_Proxy(
IEnumMoniker* This);
void __RPC_STUB IEnumMoniker_Reset_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumMoniker_Clone_Proxy(
IEnumMoniker* This,
IEnumMoniker **ppenum);
void __RPC_STUB IEnumMoniker_Clone_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK IEnumMoniker_Next_Proxy(
IEnumMoniker* This,
ULONG celt,
IMoniker **rgelt,
ULONG *pceltFetched);
HRESULT __RPC_STUB IEnumMoniker_Next_Stub(
IEnumMoniker* This,
ULONG celt,
IMoniker **rgelt,
ULONG *pceltFetched);
#endif /* __IEnumMoniker_INTERFACE_DEFINED__ */
/*****************************************************************************
* IRunnableObject interface
*/
#ifndef __IRunnableObject_INTERFACE_DEFINED__
#define __IRunnableObject_INTERFACE_DEFINED__
typedef IRunnableObject *LPRUNNABLEOBJECT;
DEFINE_GUID(IID_IRunnableObject, 0x00000126, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IRunnableObject : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE GetRunningClass(
LPCLSID lpClsid) = 0;
virtual HRESULT STDMETHODCALLTYPE Run(
LPBINDCTX pbc) = 0;
virtual BOOL STDMETHODCALLTYPE IsRunning(
) = 0;
virtual HRESULT STDMETHODCALLTYPE LockRunning(
BOOL fLock,
BOOL fLastUnlockCloses) = 0;
virtual HRESULT STDMETHODCALLTYPE SetContainedObject(
BOOL fContained) = 0;
};
#else
typedef struct IRunnableObjectVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IRunnableObject* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IRunnableObject* This);
ULONG (STDMETHODCALLTYPE *Release)(
IRunnableObject* This);
/*** IRunnableObject methods ***/
HRESULT (STDMETHODCALLTYPE *GetRunningClass)(
IRunnableObject* This,
LPCLSID lpClsid);
HRESULT (STDMETHODCALLTYPE *Run)(
IRunnableObject* This,
LPBINDCTX pbc);
BOOL (STDMETHODCALLTYPE *IsRunning)(
IRunnableObject* This);
HRESULT (STDMETHODCALLTYPE *LockRunning)(
IRunnableObject* This,
BOOL fLock,
BOOL fLastUnlockCloses);
HRESULT (STDMETHODCALLTYPE *SetContainedObject)(
IRunnableObject* This,
BOOL fContained);
END_INTERFACE
} IRunnableObjectVtbl;
interface IRunnableObject {
CONST_VTBL IRunnableObjectVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IRunnableObject_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IRunnableObject_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IRunnableObject_Release(This) (This)->lpVtbl->Release(This)
/*** IRunnableObject methods ***/
#define IRunnableObject_GetRunningClass(This,lpClsid) (This)->lpVtbl->GetRunningClass(This,lpClsid)
#define IRunnableObject_Run(This,pbc) (This)->lpVtbl->Run(This,pbc)
#define IRunnableObject_IsRunning(This) (This)->lpVtbl->IsRunning(This)
#define IRunnableObject_LockRunning(This,fLock,fLastUnlockCloses) (This)->lpVtbl->LockRunning(This,fLock,fLastUnlockCloses)
#define IRunnableObject_SetContainedObject(This,fContained) (This)->lpVtbl->SetContainedObject(This,fContained)
#endif
#endif
HRESULT STDMETHODCALLTYPE IRunnableObject_GetRunningClass_Proxy(
IRunnableObject* This,
LPCLSID lpClsid);
void __RPC_STUB IRunnableObject_GetRunningClass_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRunnableObject_Run_Proxy(
IRunnableObject* This,
LPBINDCTX pbc);
void __RPC_STUB IRunnableObject_Run_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRunnableObject_RemoteIsRunning_Proxy(
IRunnableObject* This);
void __RPC_STUB IRunnableObject_RemoteIsRunning_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRunnableObject_LockRunning_Proxy(
IRunnableObject* This,
BOOL fLock,
BOOL fLastUnlockCloses);
void __RPC_STUB IRunnableObject_LockRunning_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRunnableObject_SetContainedObject_Proxy(
IRunnableObject* This,
BOOL fContained);
void __RPC_STUB IRunnableObject_SetContainedObject_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
BOOL CALLBACK IRunnableObject_IsRunning_Proxy(
IRunnableObject* This);
HRESULT __RPC_STUB IRunnableObject_IsRunning_Stub(
IRunnableObject* This);
#endif /* __IRunnableObject_INTERFACE_DEFINED__ */
#ifdef WINE_NO_UNICODE_MACROS
#undef GetObject
#endif
/*****************************************************************************
* IRunningObjectTable interface
*/
#ifndef __IRunningObjectTable_INTERFACE_DEFINED__
#define __IRunningObjectTable_INTERFACE_DEFINED__
typedef IRunningObjectTable *LPRUNNINGOBJECTTABLE;
DEFINE_GUID(IID_IRunningObjectTable, 0x00000010, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IRunningObjectTable : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Register(
DWORD grfFlags,
IUnknown *punkObject,
IMoniker *pmkObjectName,
DWORD *pdwRegister) = 0;
virtual HRESULT STDMETHODCALLTYPE Revoke(
DWORD dwRegister) = 0;
virtual HRESULT STDMETHODCALLTYPE IsRunning(
IMoniker *pmkObjectName) = 0;
virtual HRESULT STDMETHODCALLTYPE GetObject(
IMoniker *pmkObjectName,
IUnknown **ppunkObject) = 0;
virtual HRESULT STDMETHODCALLTYPE NoteChangeTime(
DWORD dwRegister,
FILETIME *pfiletime) = 0;
virtual HRESULT STDMETHODCALLTYPE GetTimeOfLastChange(
IMoniker *pmkObjectName,
FILETIME *pfiletime) = 0;
virtual HRESULT STDMETHODCALLTYPE EnumRunning(
IEnumMoniker **ppenumMoniker) = 0;
};
#else
typedef struct IRunningObjectTableVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IRunningObjectTable* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IRunningObjectTable* This);
ULONG (STDMETHODCALLTYPE *Release)(
IRunningObjectTable* This);
/*** IRunningObjectTable methods ***/
HRESULT (STDMETHODCALLTYPE *Register)(
IRunningObjectTable* This,
DWORD grfFlags,
IUnknown *punkObject,
IMoniker *pmkObjectName,
DWORD *pdwRegister);
HRESULT (STDMETHODCALLTYPE *Revoke)(
IRunningObjectTable* This,
DWORD dwRegister);
HRESULT (STDMETHODCALLTYPE *IsRunning)(
IRunningObjectTable* This,
IMoniker *pmkObjectName);
HRESULT (STDMETHODCALLTYPE *GetObject)(
IRunningObjectTable* This,
IMoniker *pmkObjectName,
IUnknown **ppunkObject);
HRESULT (STDMETHODCALLTYPE *NoteChangeTime)(
IRunningObjectTable* This,
DWORD dwRegister,
FILETIME *pfiletime);
HRESULT (STDMETHODCALLTYPE *GetTimeOfLastChange)(
IRunningObjectTable* This,
IMoniker *pmkObjectName,
FILETIME *pfiletime);
HRESULT (STDMETHODCALLTYPE *EnumRunning)(
IRunningObjectTable* This,
IEnumMoniker **ppenumMoniker);
END_INTERFACE
} IRunningObjectTableVtbl;
interface IRunningObjectTable {
CONST_VTBL IRunningObjectTableVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IRunningObjectTable_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IRunningObjectTable_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IRunningObjectTable_Release(This) (This)->lpVtbl->Release(This)
/*** IRunningObjectTable methods ***/
#define IRunningObjectTable_Register(This,grfFlags,punkObject,pmkObjectName,pdwRegister) (This)->lpVtbl->Register(This,grfFlags,punkObject,pmkObjectName,pdwRegister)
#define IRunningObjectTable_Revoke(This,dwRegister) (This)->lpVtbl->Revoke(This,dwRegister)
#define IRunningObjectTable_IsRunning(This,pmkObjectName) (This)->lpVtbl->IsRunning(This,pmkObjectName)
#define IRunningObjectTable_GetObject(This,pmkObjectName,ppunkObject) (This)->lpVtbl->GetObject(This,pmkObjectName,ppunkObject)
#define IRunningObjectTable_NoteChangeTime(This,dwRegister,pfiletime) (This)->lpVtbl->NoteChangeTime(This,dwRegister,pfiletime)
#define IRunningObjectTable_GetTimeOfLastChange(This,pmkObjectName,pfiletime) (This)->lpVtbl->GetTimeOfLastChange(This,pmkObjectName,pfiletime)
#define IRunningObjectTable_EnumRunning(This,ppenumMoniker) (This)->lpVtbl->EnumRunning(This,ppenumMoniker)
#endif
#endif
HRESULT STDMETHODCALLTYPE IRunningObjectTable_Register_Proxy(
IRunningObjectTable* This,
DWORD grfFlags,
IUnknown *punkObject,
IMoniker *pmkObjectName,
DWORD *pdwRegister);
void __RPC_STUB IRunningObjectTable_Register_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRunningObjectTable_Revoke_Proxy(
IRunningObjectTable* This,
DWORD dwRegister);
void __RPC_STUB IRunningObjectTable_Revoke_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRunningObjectTable_IsRunning_Proxy(
IRunningObjectTable* This,
IMoniker *pmkObjectName);
void __RPC_STUB IRunningObjectTable_IsRunning_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRunningObjectTable_GetObject_Proxy(
IRunningObjectTable* This,
IMoniker *pmkObjectName,
IUnknown **ppunkObject);
void __RPC_STUB IRunningObjectTable_GetObject_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRunningObjectTable_NoteChangeTime_Proxy(
IRunningObjectTable* This,
DWORD dwRegister,
FILETIME *pfiletime);
void __RPC_STUB IRunningObjectTable_NoteChangeTime_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRunningObjectTable_GetTimeOfLastChange_Proxy(
IRunningObjectTable* This,
IMoniker *pmkObjectName,
FILETIME *pfiletime);
void __RPC_STUB IRunningObjectTable_GetTimeOfLastChange_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRunningObjectTable_EnumRunning_Proxy(
IRunningObjectTable* This,
IEnumMoniker **ppenumMoniker);
void __RPC_STUB IRunningObjectTable_EnumRunning_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IRunningObjectTable_INTERFACE_DEFINED__ */
/*****************************************************************************
* IPersist interface
*/
#ifndef __IPersist_INTERFACE_DEFINED__
#define __IPersist_INTERFACE_DEFINED__
typedef IPersist *LPPERSIST;
DEFINE_GUID(IID_IPersist, 0x0000010c, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IPersist : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE GetClassID(
CLSID *pClassID) = 0;
};
#else
typedef struct IPersistVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IPersist* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IPersist* This);
ULONG (STDMETHODCALLTYPE *Release)(
IPersist* This);
/*** IPersist methods ***/
HRESULT (STDMETHODCALLTYPE *GetClassID)(
IPersist* This,
CLSID *pClassID);
END_INTERFACE
} IPersistVtbl;
interface IPersist {
CONST_VTBL IPersistVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IPersist_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IPersist_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IPersist_Release(This) (This)->lpVtbl->Release(This)
/*** IPersist methods ***/
#define IPersist_GetClassID(This,pClassID) (This)->lpVtbl->GetClassID(This,pClassID)
#endif
#endif
HRESULT STDMETHODCALLTYPE IPersist_GetClassID_Proxy(
IPersist* This,
CLSID *pClassID);
void __RPC_STUB IPersist_GetClassID_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IPersist_INTERFACE_DEFINED__ */
/*****************************************************************************
* IPersistStream interface
*/
#ifndef __IPersistStream_INTERFACE_DEFINED__
#define __IPersistStream_INTERFACE_DEFINED__
typedef IPersistStream *LPPERSISTSTREAM;
DEFINE_GUID(IID_IPersistStream, 0x00000109, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IPersistStream : public IPersist
{
virtual HRESULT STDMETHODCALLTYPE IsDirty(
) = 0;
virtual HRESULT STDMETHODCALLTYPE Load(
IStream *pStm) = 0;
virtual HRESULT STDMETHODCALLTYPE Save(
IStream *pStm,
BOOL fClearDirty) = 0;
virtual HRESULT STDMETHODCALLTYPE GetSizeMax(
ULARGE_INTEGER *pcbSize) = 0;
};
#else
typedef struct IPersistStreamVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IPersistStream* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IPersistStream* This);
ULONG (STDMETHODCALLTYPE *Release)(
IPersistStream* This);
/*** IPersist methods ***/
HRESULT (STDMETHODCALLTYPE *GetClassID)(
IPersistStream* This,
CLSID *pClassID);
/*** IPersistStream methods ***/
HRESULT (STDMETHODCALLTYPE *IsDirty)(
IPersistStream* This);
HRESULT (STDMETHODCALLTYPE *Load)(
IPersistStream* This,
IStream *pStm);
HRESULT (STDMETHODCALLTYPE *Save)(
IPersistStream* This,
IStream *pStm,
BOOL fClearDirty);
HRESULT (STDMETHODCALLTYPE *GetSizeMax)(
IPersistStream* This,
ULARGE_INTEGER *pcbSize);
END_INTERFACE
} IPersistStreamVtbl;
interface IPersistStream {
CONST_VTBL IPersistStreamVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IPersistStream_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IPersistStream_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IPersistStream_Release(This) (This)->lpVtbl->Release(This)
/*** IPersist methods ***/
#define IPersistStream_GetClassID(This,pClassID) (This)->lpVtbl->GetClassID(This,pClassID)
/*** IPersistStream methods ***/
#define IPersistStream_IsDirty(This) (This)->lpVtbl->IsDirty(This)
#define IPersistStream_Load(This,pStm) (This)->lpVtbl->Load(This,pStm)
#define IPersistStream_Save(This,pStm,fClearDirty) (This)->lpVtbl->Save(This,pStm,fClearDirty)
#define IPersistStream_GetSizeMax(This,pcbSize) (This)->lpVtbl->GetSizeMax(This,pcbSize)
#endif
#endif
HRESULT STDMETHODCALLTYPE IPersistStream_IsDirty_Proxy(
IPersistStream* This);
void __RPC_STUB IPersistStream_IsDirty_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IPersistStream_Load_Proxy(
IPersistStream* This,
IStream *pStm);
void __RPC_STUB IPersistStream_Load_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IPersistStream_Save_Proxy(
IPersistStream* This,
IStream *pStm,
BOOL fClearDirty);
void __RPC_STUB IPersistStream_Save_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IPersistStream_GetSizeMax_Proxy(
IPersistStream* This,
ULARGE_INTEGER *pcbSize);
void __RPC_STUB IPersistStream_GetSizeMax_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IPersistStream_INTERFACE_DEFINED__ */
/*****************************************************************************
* IMoniker interface
*/
#ifndef __IMoniker_INTERFACE_DEFINED__
#define __IMoniker_INTERFACE_DEFINED__
typedef IMoniker *LPMONIKER;
typedef enum tagMKSYS {
MKSYS_NONE = 0,
MKSYS_GENERICCOMPOSITE = 1,
MKSYS_FILEMONIKER = 2,
MKSYS_ANTIMONIKER = 3,
MKSYS_ITEMMONIKER = 4,
MKSYS_POINTERMONIKER = 5,
MKSYS_CLASSMONIKER = 7
} MKSYS;
typedef enum tagMKREDUCE {
MKRREDUCE_ONE = 3 << 16,
MKRREDUCE_TOUSER = 2 << 16,
MKRREDUCE_THROUGHUSER = 1 << 16,
MKRREDUCE_ALL = 0
} MKRREDUCE;
DEFINE_GUID(IID_IMoniker, 0x0000000f, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IMoniker : public IPersistStream
{
virtual HRESULT STDMETHODCALLTYPE BindToObject(
IBindCtx *pbc,
IMoniker *pmkToLeft,
REFIID riidResult,
void **ppvResult) = 0;
virtual HRESULT STDMETHODCALLTYPE BindToStorage(
IBindCtx *pbc,
IMoniker *pmkToLeft,
REFIID riid,
void **ppvObj) = 0;
virtual HRESULT STDMETHODCALLTYPE Reduce(
IBindCtx *pbc,
DWORD dwReduceHowFar,
IMoniker **ppmkToLeft,
IMoniker **ppmkReduced) = 0;
virtual HRESULT STDMETHODCALLTYPE ComposeWith(
IMoniker *pmkRight,
BOOL fOnlyIfNotGeneric,
IMoniker **ppmkComposite) = 0;
virtual HRESULT STDMETHODCALLTYPE Enum(
BOOL fForward,
IEnumMoniker **ppenumMoniker) = 0;
virtual HRESULT STDMETHODCALLTYPE IsEqual(
IMoniker *pmkOtherMoniker) = 0;
virtual HRESULT STDMETHODCALLTYPE Hash(
DWORD *pdwHash) = 0;
virtual HRESULT STDMETHODCALLTYPE IsRunning(
IBindCtx *pbc,
IMoniker *pmkToLeft,
IMoniker *pmkNewlyRunning) = 0;
virtual HRESULT STDMETHODCALLTYPE GetTimeOfLastChange(
IBindCtx *pbc,
IMoniker *pmkToLeft,
FILETIME *pFileTime) = 0;
virtual HRESULT STDMETHODCALLTYPE Inverse(
IMoniker **ppmk) = 0;
virtual HRESULT STDMETHODCALLTYPE CommonPrefixWith(
IMoniker *pmkOther,
IMoniker **ppmkPrefix) = 0;
virtual HRESULT STDMETHODCALLTYPE RelativePathTo(
IMoniker *pmkOther,
IMoniker **ppmkRelPath) = 0;
virtual HRESULT STDMETHODCALLTYPE GetDisplayName(
IBindCtx *pbc,
IMoniker *pmkToLeft,
LPOLESTR *ppszDisplayName) = 0;
virtual HRESULT STDMETHODCALLTYPE ParseDisplayName(
IBindCtx *pbc,
IMoniker *pmkToLeft,
LPOLESTR pszDisplayName,
ULONG *pchEaten,
IMoniker **ppmkOut) = 0;
virtual HRESULT STDMETHODCALLTYPE IsSystemMoniker(
DWORD *pdwMksys) = 0;
};
#else
typedef struct IMonikerVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IMoniker* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IMoniker* This);
ULONG (STDMETHODCALLTYPE *Release)(
IMoniker* This);
/*** IPersist methods ***/
HRESULT (STDMETHODCALLTYPE *GetClassID)(
IMoniker* This,
CLSID *pClassID);
/*** IPersistStream methods ***/
HRESULT (STDMETHODCALLTYPE *IsDirty)(
IMoniker* This);
HRESULT (STDMETHODCALLTYPE *Load)(
IMoniker* This,
IStream *pStm);
HRESULT (STDMETHODCALLTYPE *Save)(
IMoniker* This,
IStream *pStm,
BOOL fClearDirty);
HRESULT (STDMETHODCALLTYPE *GetSizeMax)(
IMoniker* This,
ULARGE_INTEGER *pcbSize);
/*** IMoniker methods ***/
HRESULT (STDMETHODCALLTYPE *BindToObject)(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
REFIID riidResult,
void **ppvResult);
HRESULT (STDMETHODCALLTYPE *BindToStorage)(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
REFIID riid,
void **ppvObj);
HRESULT (STDMETHODCALLTYPE *Reduce)(
IMoniker* This,
IBindCtx *pbc,
DWORD dwReduceHowFar,
IMoniker **ppmkToLeft,
IMoniker **ppmkReduced);
HRESULT (STDMETHODCALLTYPE *ComposeWith)(
IMoniker* This,
IMoniker *pmkRight,
BOOL fOnlyIfNotGeneric,
IMoniker **ppmkComposite);
HRESULT (STDMETHODCALLTYPE *Enum)(
IMoniker* This,
BOOL fForward,
IEnumMoniker **ppenumMoniker);
HRESULT (STDMETHODCALLTYPE *IsEqual)(
IMoniker* This,
IMoniker *pmkOtherMoniker);
HRESULT (STDMETHODCALLTYPE *Hash)(
IMoniker* This,
DWORD *pdwHash);
HRESULT (STDMETHODCALLTYPE *IsRunning)(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
IMoniker *pmkNewlyRunning);
HRESULT (STDMETHODCALLTYPE *GetTimeOfLastChange)(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
FILETIME *pFileTime);
HRESULT (STDMETHODCALLTYPE *Inverse)(
IMoniker* This,
IMoniker **ppmk);
HRESULT (STDMETHODCALLTYPE *CommonPrefixWith)(
IMoniker* This,
IMoniker *pmkOther,
IMoniker **ppmkPrefix);
HRESULT (STDMETHODCALLTYPE *RelativePathTo)(
IMoniker* This,
IMoniker *pmkOther,
IMoniker **ppmkRelPath);
HRESULT (STDMETHODCALLTYPE *GetDisplayName)(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
LPOLESTR *ppszDisplayName);
HRESULT (STDMETHODCALLTYPE *ParseDisplayName)(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
LPOLESTR pszDisplayName,
ULONG *pchEaten,
IMoniker **ppmkOut);
HRESULT (STDMETHODCALLTYPE *IsSystemMoniker)(
IMoniker* This,
DWORD *pdwMksys);
END_INTERFACE
} IMonikerVtbl;
interface IMoniker {
CONST_VTBL IMonikerVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IMoniker_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IMoniker_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IMoniker_Release(This) (This)->lpVtbl->Release(This)
/*** IPersist methods ***/
#define IMoniker_GetClassID(This,pClassID) (This)->lpVtbl->GetClassID(This,pClassID)
/*** IPersistStream methods ***/
#define IMoniker_IsDirty(This) (This)->lpVtbl->IsDirty(This)
#define IMoniker_Load(This,pStm) (This)->lpVtbl->Load(This,pStm)
#define IMoniker_Save(This,pStm,fClearDirty) (This)->lpVtbl->Save(This,pStm,fClearDirty)
#define IMoniker_GetSizeMax(This,pcbSize) (This)->lpVtbl->GetSizeMax(This,pcbSize)
/*** IMoniker methods ***/
#define IMoniker_BindToObject(This,pbc,pmkToLeft,riidResult,ppvResult) (This)->lpVtbl->BindToObject(This,pbc,pmkToLeft,riidResult,ppvResult)
#define IMoniker_BindToStorage(This,pbc,pmkToLeft,riid,ppvObj) (This)->lpVtbl->BindToStorage(This,pbc,pmkToLeft,riid,ppvObj)
#define IMoniker_Reduce(This,pbc,dwReduceHowFar,ppmkToLeft,ppmkReduced) (This)->lpVtbl->Reduce(This,pbc,dwReduceHowFar,ppmkToLeft,ppmkReduced)
#define IMoniker_ComposeWith(This,pmkRight,fOnlyIfNotGeneric,ppmkComposite) (This)->lpVtbl->ComposeWith(This,pmkRight,fOnlyIfNotGeneric,ppmkComposite)
#define IMoniker_Enum(This,fForward,ppenumMoniker) (This)->lpVtbl->Enum(This,fForward,ppenumMoniker)
#define IMoniker_IsEqual(This,pmkOtherMoniker) (This)->lpVtbl->IsEqual(This,pmkOtherMoniker)
#define IMoniker_Hash(This,pdwHash) (This)->lpVtbl->Hash(This,pdwHash)
#define IMoniker_IsRunning(This,pbc,pmkToLeft,pmkNewlyRunning) (This)->lpVtbl->IsRunning(This,pbc,pmkToLeft,pmkNewlyRunning)
#define IMoniker_GetTimeOfLastChange(This,pbc,pmkToLeft,pFileTime) (This)->lpVtbl->GetTimeOfLastChange(This,pbc,pmkToLeft,pFileTime)
#define IMoniker_Inverse(This,ppmk) (This)->lpVtbl->Inverse(This,ppmk)
#define IMoniker_CommonPrefixWith(This,pmkOther,ppmkPrefix) (This)->lpVtbl->CommonPrefixWith(This,pmkOther,ppmkPrefix)
#define IMoniker_RelativePathTo(This,pmkOther,ppmkRelPath) (This)->lpVtbl->RelativePathTo(This,pmkOther,ppmkRelPath)
#define IMoniker_GetDisplayName(This,pbc,pmkToLeft,ppszDisplayName) (This)->lpVtbl->GetDisplayName(This,pbc,pmkToLeft,ppszDisplayName)
#define IMoniker_ParseDisplayName(This,pbc,pmkToLeft,pszDisplayName,pchEaten,ppmkOut) (This)->lpVtbl->ParseDisplayName(This,pbc,pmkToLeft,pszDisplayName,pchEaten,ppmkOut)
#define IMoniker_IsSystemMoniker(This,pdwMksys) (This)->lpVtbl->IsSystemMoniker(This,pdwMksys)
#endif
#endif
HRESULT STDMETHODCALLTYPE IMoniker_RemoteBindToObject_Proxy(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
REFIID riidResult,
IUnknown **ppvResult);
void __RPC_STUB IMoniker_RemoteBindToObject_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_RemoteBindToStorage_Proxy(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
REFIID riid,
IUnknown **ppvObj);
void __RPC_STUB IMoniker_RemoteBindToStorage_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_Reduce_Proxy(
IMoniker* This,
IBindCtx *pbc,
DWORD dwReduceHowFar,
IMoniker **ppmkToLeft,
IMoniker **ppmkReduced);
void __RPC_STUB IMoniker_Reduce_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_ComposeWith_Proxy(
IMoniker* This,
IMoniker *pmkRight,
BOOL fOnlyIfNotGeneric,
IMoniker **ppmkComposite);
void __RPC_STUB IMoniker_ComposeWith_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_Enum_Proxy(
IMoniker* This,
BOOL fForward,
IEnumMoniker **ppenumMoniker);
void __RPC_STUB IMoniker_Enum_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_IsEqual_Proxy(
IMoniker* This,
IMoniker *pmkOtherMoniker);
void __RPC_STUB IMoniker_IsEqual_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_Hash_Proxy(
IMoniker* This,
DWORD *pdwHash);
void __RPC_STUB IMoniker_Hash_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_IsRunning_Proxy(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
IMoniker *pmkNewlyRunning);
void __RPC_STUB IMoniker_IsRunning_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_GetTimeOfLastChange_Proxy(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
FILETIME *pFileTime);
void __RPC_STUB IMoniker_GetTimeOfLastChange_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_Inverse_Proxy(
IMoniker* This,
IMoniker **ppmk);
void __RPC_STUB IMoniker_Inverse_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_CommonPrefixWith_Proxy(
IMoniker* This,
IMoniker *pmkOther,
IMoniker **ppmkPrefix);
void __RPC_STUB IMoniker_CommonPrefixWith_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_RelativePathTo_Proxy(
IMoniker* This,
IMoniker *pmkOther,
IMoniker **ppmkRelPath);
void __RPC_STUB IMoniker_RelativePathTo_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_GetDisplayName_Proxy(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
LPOLESTR *ppszDisplayName);
void __RPC_STUB IMoniker_GetDisplayName_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_ParseDisplayName_Proxy(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
LPOLESTR pszDisplayName,
ULONG *pchEaten,
IMoniker **ppmkOut);
void __RPC_STUB IMoniker_ParseDisplayName_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IMoniker_IsSystemMoniker_Proxy(
IMoniker* This,
DWORD *pdwMksys);
void __RPC_STUB IMoniker_IsSystemMoniker_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK IMoniker_BindToObject_Proxy(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
REFIID riidResult,
void **ppvResult);
HRESULT __RPC_STUB IMoniker_BindToObject_Stub(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
REFIID riidResult,
IUnknown **ppvResult);
HRESULT CALLBACK IMoniker_BindToStorage_Proxy(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
REFIID riid,
void **ppvObj);
HRESULT __RPC_STUB IMoniker_BindToStorage_Stub(
IMoniker* This,
IBindCtx *pbc,
IMoniker *pmkToLeft,
REFIID riid,
IUnknown **ppvObj);
#endif /* __IMoniker_INTERFACE_DEFINED__ */
/*****************************************************************************
* IROTData interface
*/
#ifndef __IROTData_INTERFACE_DEFINED__
#define __IROTData_INTERFACE_DEFINED__
DEFINE_GUID(IID_IROTData, 0xf29f6bc0, 0x5021, 0x11ce, 0xaa,0x15, 0x00,0x00,0x69,0x01,0x29,0x3f);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IROTData : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE GetComparisonData(
byte *pbData,
ULONG cbMax,
ULONG *pcbData) = 0;
};
#else
typedef struct IROTDataVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IROTData* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IROTData* This);
ULONG (STDMETHODCALLTYPE *Release)(
IROTData* This);
/*** IROTData methods ***/
HRESULT (STDMETHODCALLTYPE *GetComparisonData)(
IROTData* This,
byte *pbData,
ULONG cbMax,
ULONG *pcbData);
END_INTERFACE
} IROTDataVtbl;
interface IROTData {
CONST_VTBL IROTDataVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IROTData_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IROTData_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IROTData_Release(This) (This)->lpVtbl->Release(This)
/*** IROTData methods ***/
#define IROTData_GetComparisonData(This,pbData,cbMax,pcbData) (This)->lpVtbl->GetComparisonData(This,pbData,cbMax,pcbData)
#endif
#endif
HRESULT STDMETHODCALLTYPE IROTData_GetComparisonData_Proxy(
IROTData* This,
byte *pbData,
ULONG cbMax,
ULONG *pcbData);
void __RPC_STUB IROTData_GetComparisonData_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IROTData_INTERFACE_DEFINED__ */
/*****************************************************************************
* IEnumString interface
*/
#ifndef __IEnumString_INTERFACE_DEFINED__
#define __IEnumString_INTERFACE_DEFINED__
typedef IEnumString *LPENUMSTRING;
DEFINE_GUID(IID_IEnumString, 0x00000101, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IEnumString : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Next(
ULONG celt,
LPOLESTR *rgelt,
ULONG *pceltFetched) = 0;
virtual HRESULT STDMETHODCALLTYPE Skip(
ULONG celt) = 0;
virtual HRESULT STDMETHODCALLTYPE Reset(
) = 0;
virtual HRESULT STDMETHODCALLTYPE Clone(
IEnumString **ppenum) = 0;
};
#else
typedef struct IEnumStringVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IEnumString* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IEnumString* This);
ULONG (STDMETHODCALLTYPE *Release)(
IEnumString* This);
/*** IEnumString methods ***/
HRESULT (STDMETHODCALLTYPE *Next)(
IEnumString* This,
ULONG celt,
LPOLESTR *rgelt,
ULONG *pceltFetched);
HRESULT (STDMETHODCALLTYPE *Skip)(
IEnumString* This,
ULONG celt);
HRESULT (STDMETHODCALLTYPE *Reset)(
IEnumString* This);
HRESULT (STDMETHODCALLTYPE *Clone)(
IEnumString* This,
IEnumString **ppenum);
END_INTERFACE
} IEnumStringVtbl;
interface IEnumString {
CONST_VTBL IEnumStringVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IEnumString_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IEnumString_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IEnumString_Release(This) (This)->lpVtbl->Release(This)
/*** IEnumString methods ***/
#define IEnumString_Next(This,celt,rgelt,pceltFetched) (This)->lpVtbl->Next(This,celt,rgelt,pceltFetched)
#define IEnumString_Skip(This,celt) (This)->lpVtbl->Skip(This,celt)
#define IEnumString_Reset(This) (This)->lpVtbl->Reset(This)
#define IEnumString_Clone(This,ppenum) (This)->lpVtbl->Clone(This,ppenum)
#endif
#endif
HRESULT STDMETHODCALLTYPE IEnumString_RemoteNext_Proxy(
IEnumString* This,
ULONG celt,
LPOLESTR *rgelt,
ULONG *pceltFetched);
void __RPC_STUB IEnumString_RemoteNext_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumString_Skip_Proxy(
IEnumString* This,
ULONG celt);
void __RPC_STUB IEnumString_Skip_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumString_Reset_Proxy(
IEnumString* This);
void __RPC_STUB IEnumString_Reset_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumString_Clone_Proxy(
IEnumString* This,
IEnumString **ppenum);
void __RPC_STUB IEnumString_Clone_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK IEnumString_Next_Proxy(
IEnumString* This,
ULONG celt,
LPOLESTR *rgelt,
ULONG *pceltFetched);
HRESULT __RPC_STUB IEnumString_Next_Stub(
IEnumString* This,
ULONG celt,
LPOLESTR *rgelt,
ULONG *pceltFetched);
#endif /* __IEnumString_INTERFACE_DEFINED__ */
/*****************************************************************************
* IClassActivator interface
*/
#ifndef __IClassActivator_INTERFACE_DEFINED__
#define __IClassActivator_INTERFACE_DEFINED__
DEFINE_GUID(IID_IClassActivator, 0x00000140, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IClassActivator : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE GetClassObject(
REFCLSID rclsid,
DWORD dwClassContext,
LCID locale,
REFIID riid,
void **ppv) = 0;
};
#else
typedef struct IClassActivatorVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IClassActivator* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IClassActivator* This);
ULONG (STDMETHODCALLTYPE *Release)(
IClassActivator* This);
/*** IClassActivator methods ***/
HRESULT (STDMETHODCALLTYPE *GetClassObject)(
IClassActivator* This,
REFCLSID rclsid,
DWORD dwClassContext,
LCID locale,
REFIID riid,
void **ppv);
END_INTERFACE
} IClassActivatorVtbl;
interface IClassActivator {
CONST_VTBL IClassActivatorVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IClassActivator_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IClassActivator_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IClassActivator_Release(This) (This)->lpVtbl->Release(This)
/*** IClassActivator methods ***/
#define IClassActivator_GetClassObject(This,rclsid,dwClassContext,locale,riid,ppv) (This)->lpVtbl->GetClassObject(This,rclsid,dwClassContext,locale,riid,ppv)
#endif
#endif
HRESULT STDMETHODCALLTYPE IClassActivator_GetClassObject_Proxy(
IClassActivator* This,
REFCLSID rclsid,
DWORD dwClassContext,
LCID locale,
REFIID riid,
void **ppv);
void __RPC_STUB IClassActivator_GetClassObject_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IClassActivator_INTERFACE_DEFINED__ */
/*****************************************************************************
* ISequentialStream interface
*/
#ifndef __ISequentialStream_INTERFACE_DEFINED__
#define __ISequentialStream_INTERFACE_DEFINED__
DEFINE_GUID(IID_ISequentialStream, 0x0c733a30, 0x2a1c, 0x11ce, 0xad,0xe5, 0x00,0xaa,0x00,0x44,0x77,0x3d);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface ISequentialStream : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Read(
void *pv,
ULONG cb,
ULONG *pcbRead) = 0;
virtual HRESULT STDMETHODCALLTYPE Write(
const void *pv,
ULONG cb,
ULONG *pcbWritten) = 0;
};
#else
typedef struct ISequentialStreamVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
ISequentialStream* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
ISequentialStream* This);
ULONG (STDMETHODCALLTYPE *Release)(
ISequentialStream* This);
/*** ISequentialStream methods ***/
HRESULT (STDMETHODCALLTYPE *Read)(
ISequentialStream* This,
void *pv,
ULONG cb,
ULONG *pcbRead);
HRESULT (STDMETHODCALLTYPE *Write)(
ISequentialStream* This,
const void *pv,
ULONG cb,
ULONG *pcbWritten);
END_INTERFACE
} ISequentialStreamVtbl;
interface ISequentialStream {
CONST_VTBL ISequentialStreamVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define ISequentialStream_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define ISequentialStream_AddRef(This) (This)->lpVtbl->AddRef(This)
#define ISequentialStream_Release(This) (This)->lpVtbl->Release(This)
/*** ISequentialStream methods ***/
#define ISequentialStream_Read(This,pv,cb,pcbRead) (This)->lpVtbl->Read(This,pv,cb,pcbRead)
#define ISequentialStream_Write(This,pv,cb,pcbWritten) (This)->lpVtbl->Write(This,pv,cb,pcbWritten)
#endif
#endif
HRESULT STDMETHODCALLTYPE ISequentialStream_RemoteRead_Proxy(
ISequentialStream* This,
byte *pv,
ULONG cb,
ULONG *pcbRead);
void __RPC_STUB ISequentialStream_RemoteRead_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ISequentialStream_RemoteWrite_Proxy(
ISequentialStream* This,
const byte *pv,
ULONG cb,
ULONG *pcbWritten);
void __RPC_STUB ISequentialStream_RemoteWrite_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK ISequentialStream_Read_Proxy(
ISequentialStream* This,
void *pv,
ULONG cb,
ULONG *pcbRead);
HRESULT __RPC_STUB ISequentialStream_Read_Stub(
ISequentialStream* This,
byte *pv,
ULONG cb,
ULONG *pcbRead);
HRESULT CALLBACK ISequentialStream_Write_Proxy(
ISequentialStream* This,
const void *pv,
ULONG cb,
ULONG *pcbWritten);
HRESULT __RPC_STUB ISequentialStream_Write_Stub(
ISequentialStream* This,
const byte *pv,
ULONG cb,
ULONG *pcbWritten);
#endif /* __ISequentialStream_INTERFACE_DEFINED__ */
/*****************************************************************************
* IStream interface
*/
#ifndef __IStream_INTERFACE_DEFINED__
#define __IStream_INTERFACE_DEFINED__
typedef IStream *LPSTREAM;
typedef struct tagSTATSTG {
LPOLESTR pwcsName;
DWORD type;
ULARGE_INTEGER cbSize;
FILETIME mtime;
FILETIME ctime;
FILETIME atime;
DWORD grfMode;
DWORD grfLocksSupported;
CLSID clsid;
DWORD grfStateBits;
DWORD reserved;
} STATSTG;
typedef enum tagSTGTY {
STGTY_STORAGE = 1,
STGTY_STREAM = 2,
STGTY_LOCKBYTES = 3,
STGTY_PROPERTY = 4
} STGTY;
typedef enum tagSTREAM_SEEK {
STREAM_SEEK_SET = 0,
STREAM_SEEK_CUR = 1,
STREAM_SEEK_END = 2
} STREAM_SEEK;
#undef LOCK_MAND
#undef LOCK_READ
#undef LOCK_WRITE
#undef LOCK_RW
typedef enum tagLOCKTYPE {
LOCK_WRITE = 1,
LOCK_EXCLUSIVE = 2,
LOCK_ONLYONCE = 4
} LOCKTYPE;
DEFINE_GUID(IID_IStream, 0x0000000c, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IStream : public ISequentialStream
{
virtual HRESULT STDMETHODCALLTYPE Seek(
LARGE_INTEGER dlibMove,
DWORD dwOrigin,
ULARGE_INTEGER *plibNewPosition) = 0;
virtual HRESULT STDMETHODCALLTYPE SetSize(
ULARGE_INTEGER libNewSize) = 0;
virtual HRESULT STDMETHODCALLTYPE CopyTo(
IStream *pstm,
ULARGE_INTEGER cb,
ULARGE_INTEGER *pcbRead,
ULARGE_INTEGER *pcbWritten) = 0;
virtual HRESULT STDMETHODCALLTYPE Commit(
DWORD grfCommitFlags) = 0;
virtual HRESULT STDMETHODCALLTYPE Revert(
) = 0;
virtual HRESULT STDMETHODCALLTYPE LockRegion(
ULARGE_INTEGER libOffset,
ULARGE_INTEGER cb,
DWORD dwLockType) = 0;
virtual HRESULT STDMETHODCALLTYPE UnlockRegion(
ULARGE_INTEGER libOffset,
ULARGE_INTEGER cb,
DWORD dwLockType) = 0;
virtual HRESULT STDMETHODCALLTYPE Stat(
STATSTG *pstatstg,
DWORD grfStatFlag) = 0;
virtual HRESULT STDMETHODCALLTYPE Clone(
IStream **ppstm) = 0;
};
#else
typedef struct IStreamVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IStream* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IStream* This);
ULONG (STDMETHODCALLTYPE *Release)(
IStream* This);
/*** ISequentialStream methods ***/
HRESULT (STDMETHODCALLTYPE *Read)(
IStream* This,
void *pv,
ULONG cb,
ULONG *pcbRead);
HRESULT (STDMETHODCALLTYPE *Write)(
IStream* This,
const void *pv,
ULONG cb,
ULONG *pcbWritten);
/*** IStream methods ***/
HRESULT (STDMETHODCALLTYPE *Seek)(
IStream* This,
LARGE_INTEGER dlibMove,
DWORD dwOrigin,
ULARGE_INTEGER *plibNewPosition);
HRESULT (STDMETHODCALLTYPE *SetSize)(
IStream* This,
ULARGE_INTEGER libNewSize);
HRESULT (STDMETHODCALLTYPE *CopyTo)(
IStream* This,
IStream *pstm,
ULARGE_INTEGER cb,
ULARGE_INTEGER *pcbRead,
ULARGE_INTEGER *pcbWritten);
HRESULT (STDMETHODCALLTYPE *Commit)(
IStream* This,
DWORD grfCommitFlags);
HRESULT (STDMETHODCALLTYPE *Revert)(
IStream* This);
HRESULT (STDMETHODCALLTYPE *LockRegion)(
IStream* This,
ULARGE_INTEGER libOffset,
ULARGE_INTEGER cb,
DWORD dwLockType);
HRESULT (STDMETHODCALLTYPE *UnlockRegion)(
IStream* This,
ULARGE_INTEGER libOffset,
ULARGE_INTEGER cb,
DWORD dwLockType);
HRESULT (STDMETHODCALLTYPE *Stat)(
IStream* This,
STATSTG *pstatstg,
DWORD grfStatFlag);
HRESULT (STDMETHODCALLTYPE *Clone)(
IStream* This,
IStream **ppstm);
END_INTERFACE
} IStreamVtbl;
interface IStream {
CONST_VTBL IStreamVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IStream_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IStream_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IStream_Release(This) (This)->lpVtbl->Release(This)
/*** ISequentialStream methods ***/
#define IStream_Read(This,pv,cb,pcbRead) (This)->lpVtbl->Read(This,pv,cb,pcbRead)
#define IStream_Write(This,pv,cb,pcbWritten) (This)->lpVtbl->Write(This,pv,cb,pcbWritten)
/*** IStream methods ***/
#define IStream_Seek(This,dlibMove,dwOrigin,plibNewPosition) (This)->lpVtbl->Seek(This,dlibMove,dwOrigin,plibNewPosition)
#define IStream_SetSize(This,libNewSize) (This)->lpVtbl->SetSize(This,libNewSize)
#define IStream_CopyTo(This,pstm,cb,pcbRead,pcbWritten) (This)->lpVtbl->CopyTo(This,pstm,cb,pcbRead,pcbWritten)
#define IStream_Commit(This,grfCommitFlags) (This)->lpVtbl->Commit(This,grfCommitFlags)
#define IStream_Revert(This) (This)->lpVtbl->Revert(This)
#define IStream_LockRegion(This,libOffset,cb,dwLockType) (This)->lpVtbl->LockRegion(This,libOffset,cb,dwLockType)
#define IStream_UnlockRegion(This,libOffset,cb,dwLockType) (This)->lpVtbl->UnlockRegion(This,libOffset,cb,dwLockType)
#define IStream_Stat(This,pstatstg,grfStatFlag) (This)->lpVtbl->Stat(This,pstatstg,grfStatFlag)
#define IStream_Clone(This,ppstm) (This)->lpVtbl->Clone(This,ppstm)
#endif
#endif
HRESULT STDMETHODCALLTYPE IStream_RemoteSeek_Proxy(
IStream* This,
LARGE_INTEGER dlibMove,
DWORD dwOrigin,
ULARGE_INTEGER *plibNewPosition);
void __RPC_STUB IStream_RemoteSeek_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStream_SetSize_Proxy(
IStream* This,
ULARGE_INTEGER libNewSize);
void __RPC_STUB IStream_SetSize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStream_RemoteCopyTo_Proxy(
IStream* This,
IStream *pstm,
ULARGE_INTEGER cb,
ULARGE_INTEGER *pcbRead,
ULARGE_INTEGER *pcbWritten);
void __RPC_STUB IStream_RemoteCopyTo_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStream_Commit_Proxy(
IStream* This,
DWORD grfCommitFlags);
void __RPC_STUB IStream_Commit_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStream_Revert_Proxy(
IStream* This);
void __RPC_STUB IStream_Revert_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStream_LockRegion_Proxy(
IStream* This,
ULARGE_INTEGER libOffset,
ULARGE_INTEGER cb,
DWORD dwLockType);
void __RPC_STUB IStream_LockRegion_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStream_UnlockRegion_Proxy(
IStream* This,
ULARGE_INTEGER libOffset,
ULARGE_INTEGER cb,
DWORD dwLockType);
void __RPC_STUB IStream_UnlockRegion_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStream_Stat_Proxy(
IStream* This,
STATSTG *pstatstg,
DWORD grfStatFlag);
void __RPC_STUB IStream_Stat_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStream_Clone_Proxy(
IStream* This,
IStream **ppstm);
void __RPC_STUB IStream_Clone_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK IStream_Seek_Proxy(
IStream* This,
LARGE_INTEGER dlibMove,
DWORD dwOrigin,
ULARGE_INTEGER *plibNewPosition);
HRESULT __RPC_STUB IStream_Seek_Stub(
IStream* This,
LARGE_INTEGER dlibMove,
DWORD dwOrigin,
ULARGE_INTEGER *plibNewPosition);
HRESULT CALLBACK IStream_CopyTo_Proxy(
IStream* This,
IStream *pstm,
ULARGE_INTEGER cb,
ULARGE_INTEGER *pcbRead,
ULARGE_INTEGER *pcbWritten);
HRESULT __RPC_STUB IStream_CopyTo_Stub(
IStream* This,
IStream *pstm,
ULARGE_INTEGER cb,
ULARGE_INTEGER *pcbRead,
ULARGE_INTEGER *pcbWritten);
#endif /* __IStream_INTERFACE_DEFINED__ */
/*****************************************************************************
* IEnumSTATSTG interface
*/
#ifndef __IEnumSTATSTG_INTERFACE_DEFINED__
#define __IEnumSTATSTG_INTERFACE_DEFINED__
typedef IEnumSTATSTG *LPENUMSTATSTG;
DEFINE_GUID(IID_IEnumSTATSTG, 0x0000000d, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IEnumSTATSTG : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Next(
ULONG celt,
STATSTG *rgelt,
ULONG *pceltFetched) = 0;
virtual HRESULT STDMETHODCALLTYPE Skip(
ULONG celt) = 0;
virtual HRESULT STDMETHODCALLTYPE Reset(
) = 0;
virtual HRESULT STDMETHODCALLTYPE Clone(
IEnumSTATSTG **ppenum) = 0;
};
#else
typedef struct IEnumSTATSTGVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IEnumSTATSTG* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IEnumSTATSTG* This);
ULONG (STDMETHODCALLTYPE *Release)(
IEnumSTATSTG* This);
/*** IEnumSTATSTG methods ***/
HRESULT (STDMETHODCALLTYPE *Next)(
IEnumSTATSTG* This,
ULONG celt,
STATSTG *rgelt,
ULONG *pceltFetched);
HRESULT (STDMETHODCALLTYPE *Skip)(
IEnumSTATSTG* This,
ULONG celt);
HRESULT (STDMETHODCALLTYPE *Reset)(
IEnumSTATSTG* This);
HRESULT (STDMETHODCALLTYPE *Clone)(
IEnumSTATSTG* This,
IEnumSTATSTG **ppenum);
END_INTERFACE
} IEnumSTATSTGVtbl;
interface IEnumSTATSTG {
CONST_VTBL IEnumSTATSTGVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IEnumSTATSTG_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IEnumSTATSTG_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IEnumSTATSTG_Release(This) (This)->lpVtbl->Release(This)
/*** IEnumSTATSTG methods ***/
#define IEnumSTATSTG_Next(This,celt,rgelt,pceltFetched) (This)->lpVtbl->Next(This,celt,rgelt,pceltFetched)
#define IEnumSTATSTG_Skip(This,celt) (This)->lpVtbl->Skip(This,celt)
#define IEnumSTATSTG_Reset(This) (This)->lpVtbl->Reset(This)
#define IEnumSTATSTG_Clone(This,ppenum) (This)->lpVtbl->Clone(This,ppenum)
#endif
#endif
HRESULT STDMETHODCALLTYPE IEnumSTATSTG_RemoteNext_Proxy(
IEnumSTATSTG* This,
ULONG celt,
STATSTG *rgelt,
ULONG *pceltFetched);
void __RPC_STUB IEnumSTATSTG_RemoteNext_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumSTATSTG_Skip_Proxy(
IEnumSTATSTG* This,
ULONG celt);
void __RPC_STUB IEnumSTATSTG_Skip_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumSTATSTG_Reset_Proxy(
IEnumSTATSTG* This);
void __RPC_STUB IEnumSTATSTG_Reset_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumSTATSTG_Clone_Proxy(
IEnumSTATSTG* This,
IEnumSTATSTG **ppenum);
void __RPC_STUB IEnumSTATSTG_Clone_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK IEnumSTATSTG_Next_Proxy(
IEnumSTATSTG* This,
ULONG celt,
STATSTG *rgelt,
ULONG *pceltFetched);
HRESULT __RPC_STUB IEnumSTATSTG_Next_Stub(
IEnumSTATSTG* This,
ULONG celt,
STATSTG *rgelt,
ULONG *pceltFetched);
#endif /* __IEnumSTATSTG_INTERFACE_DEFINED__ */
/*****************************************************************************
* IStorage interface
*/
#ifndef __IStorage_INTERFACE_DEFINED__
#define __IStorage_INTERFACE_DEFINED__
typedef IStorage *LPSTORAGE;
typedef struct tagRemSNB {
ULONG ulCntStr;
ULONG ulCntChar;
OLECHAR rgString[1];
} RemSNB;
typedef RemSNB *wireSNB;
typedef OLECHAR **SNB;
DEFINE_GUID(IID_IStorage, 0x0000000b, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IStorage : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE CreateStream(
LPCOLESTR pwcsName,
DWORD grfMode,
DWORD reserved1,
DWORD reserved2,
IStream **ppstm) = 0;
virtual HRESULT STDMETHODCALLTYPE OpenStream(
LPCOLESTR pwcsName,
void *reserved1,
DWORD grfMode,
DWORD reserved2,
IStream **ppstm) = 0;
virtual HRESULT STDMETHODCALLTYPE CreateStorage(
LPCOLESTR pwcsName,
DWORD grfMode,
DWORD dwStgFmt,
DWORD reserved2,
IStorage **ppstg) = 0;
virtual HRESULT STDMETHODCALLTYPE OpenStorage(
LPCOLESTR pwcsName,
IStorage *pstgPriority,
DWORD grfMode,
SNB snbExclude,
DWORD reserved,
IStorage **ppstg) = 0;
virtual HRESULT STDMETHODCALLTYPE CopyTo(
DWORD ciidExclude,
const IID *rgiidExclude,
SNB snbExclude,
IStorage *pstgDest) = 0;
virtual HRESULT STDMETHODCALLTYPE MoveElementTo(
LPCOLESTR pwcsName,
IStorage *pstgDest,
LPCOLESTR pwcsNewName,
DWORD grfFlags) = 0;
virtual HRESULT STDMETHODCALLTYPE Commit(
DWORD grfCommitFlags) = 0;
virtual HRESULT STDMETHODCALLTYPE Revert(
) = 0;
virtual HRESULT STDMETHODCALLTYPE EnumElements(
DWORD reserved1,
void *reserved2,
DWORD reserved3,
IEnumSTATSTG **ppenum) = 0;
virtual HRESULT STDMETHODCALLTYPE DestroyElement(
LPCOLESTR pwcsName) = 0;
virtual HRESULT STDMETHODCALLTYPE RenameElement(
LPCOLESTR pwcsOldName,
LPCOLESTR pwcsNewName) = 0;
virtual HRESULT STDMETHODCALLTYPE SetElementTimes(
LPCOLESTR pwcsName,
const FILETIME *pctime,
const FILETIME *patime,
const FILETIME *pmtime) = 0;
virtual HRESULT STDMETHODCALLTYPE SetClass(
REFCLSID clsid) = 0;
virtual HRESULT STDMETHODCALLTYPE SetStateBits(
DWORD grfStateBits,
DWORD grfMask) = 0;
virtual HRESULT STDMETHODCALLTYPE Stat(
STATSTG *pstatstg,
DWORD grfStatFlag) = 0;
};
#else
typedef struct IStorageVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IStorage* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IStorage* This);
ULONG (STDMETHODCALLTYPE *Release)(
IStorage* This);
/*** IStorage methods ***/
HRESULT (STDMETHODCALLTYPE *CreateStream)(
IStorage* This,
LPCOLESTR pwcsName,
DWORD grfMode,
DWORD reserved1,
DWORD reserved2,
IStream **ppstm);
HRESULT (STDMETHODCALLTYPE *OpenStream)(
IStorage* This,
LPCOLESTR pwcsName,
void *reserved1,
DWORD grfMode,
DWORD reserved2,
IStream **ppstm);
HRESULT (STDMETHODCALLTYPE *CreateStorage)(
IStorage* This,
LPCOLESTR pwcsName,
DWORD grfMode,
DWORD dwStgFmt,
DWORD reserved2,
IStorage **ppstg);
HRESULT (STDMETHODCALLTYPE *OpenStorage)(
IStorage* This,
LPCOLESTR pwcsName,
IStorage *pstgPriority,
DWORD grfMode,
SNB snbExclude,
DWORD reserved,
IStorage **ppstg);
HRESULT (STDMETHODCALLTYPE *CopyTo)(
IStorage* This,
DWORD ciidExclude,
const IID *rgiidExclude,
SNB snbExclude,
IStorage *pstgDest);
HRESULT (STDMETHODCALLTYPE *MoveElementTo)(
IStorage* This,
LPCOLESTR pwcsName,
IStorage *pstgDest,
LPCOLESTR pwcsNewName,
DWORD grfFlags);
HRESULT (STDMETHODCALLTYPE *Commit)(
IStorage* This,
DWORD grfCommitFlags);
HRESULT (STDMETHODCALLTYPE *Revert)(
IStorage* This);
HRESULT (STDMETHODCALLTYPE *EnumElements)(
IStorage* This,
DWORD reserved1,
void *reserved2,
DWORD reserved3,
IEnumSTATSTG **ppenum);
HRESULT (STDMETHODCALLTYPE *DestroyElement)(
IStorage* This,
LPCOLESTR pwcsName);
HRESULT (STDMETHODCALLTYPE *RenameElement)(
IStorage* This,
LPCOLESTR pwcsOldName,
LPCOLESTR pwcsNewName);
HRESULT (STDMETHODCALLTYPE *SetElementTimes)(
IStorage* This,
LPCOLESTR pwcsName,
const FILETIME *pctime,
const FILETIME *patime,
const FILETIME *pmtime);
HRESULT (STDMETHODCALLTYPE *SetClass)(
IStorage* This,
REFCLSID clsid);
HRESULT (STDMETHODCALLTYPE *SetStateBits)(
IStorage* This,
DWORD grfStateBits,
DWORD grfMask);
HRESULT (STDMETHODCALLTYPE *Stat)(
IStorage* This,
STATSTG *pstatstg,
DWORD grfStatFlag);
END_INTERFACE
} IStorageVtbl;
interface IStorage {
CONST_VTBL IStorageVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IStorage_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IStorage_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IStorage_Release(This) (This)->lpVtbl->Release(This)
/*** IStorage methods ***/
#define IStorage_CreateStream(This,pwcsName,grfMode,reserved1,reserved2,ppstm) (This)->lpVtbl->CreateStream(This,pwcsName,grfMode,reserved1,reserved2,ppstm)
#define IStorage_OpenStream(This,pwcsName,reserved1,grfMode,reserved2,ppstm) (This)->lpVtbl->OpenStream(This,pwcsName,reserved1,grfMode,reserved2,ppstm)
#define IStorage_CreateStorage(This,pwcsName,grfMode,dwStgFmt,reserved2,ppstg) (This)->lpVtbl->CreateStorage(This,pwcsName,grfMode,dwStgFmt,reserved2,ppstg)
#define IStorage_OpenStorage(This,pwcsName,pstgPriority,grfMode,snbExclude,reserved,ppstg) (This)->lpVtbl->OpenStorage(This,pwcsName,pstgPriority,grfMode,snbExclude,reserved,ppstg)
#define IStorage_CopyTo(This,ciidExclude,rgiidExclude,snbExclude,pstgDest) (This)->lpVtbl->CopyTo(This,ciidExclude,rgiidExclude,snbExclude,pstgDest)
#define IStorage_MoveElementTo(This,pwcsName,pstgDest,pwcsNewName,grfFlags) (This)->lpVtbl->MoveElementTo(This,pwcsName,pstgDest,pwcsNewName,grfFlags)
#define IStorage_Commit(This,grfCommitFlags) (This)->lpVtbl->Commit(This,grfCommitFlags)
#define IStorage_Revert(This) (This)->lpVtbl->Revert(This)
#define IStorage_EnumElements(This,reserved1,reserved2,reserved3,ppenum) (This)->lpVtbl->EnumElements(This,reserved1,reserved2,reserved3,ppenum)
#define IStorage_DestroyElement(This,pwcsName) (This)->lpVtbl->DestroyElement(This,pwcsName)
#define IStorage_RenameElement(This,pwcsOldName,pwcsNewName) (This)->lpVtbl->RenameElement(This,pwcsOldName,pwcsNewName)
#define IStorage_SetElementTimes(This,pwcsName,pctime,patime,pmtime) (This)->lpVtbl->SetElementTimes(This,pwcsName,pctime,patime,pmtime)
#define IStorage_SetClass(This,clsid) (This)->lpVtbl->SetClass(This,clsid)
#define IStorage_SetStateBits(This,grfStateBits,grfMask) (This)->lpVtbl->SetStateBits(This,grfStateBits,grfMask)
#define IStorage_Stat(This,pstatstg,grfStatFlag) (This)->lpVtbl->Stat(This,pstatstg,grfStatFlag)
#endif
#endif
HRESULT STDMETHODCALLTYPE IStorage_CreateStream_Proxy(
IStorage* This,
LPCOLESTR pwcsName,
DWORD grfMode,
DWORD reserved1,
DWORD reserved2,
IStream **ppstm);
void __RPC_STUB IStorage_CreateStream_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_RemoteOpenStream_Proxy(
IStorage* This,
LPCOLESTR pwcsName,
ULONG cbReserved1,
byte *reserved1,
DWORD grfMode,
DWORD reserved2,
IStream **ppstm);
void __RPC_STUB IStorage_RemoteOpenStream_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_CreateStorage_Proxy(
IStorage* This,
LPCOLESTR pwcsName,
DWORD grfMode,
DWORD dwStgFmt,
DWORD reserved2,
IStorage **ppstg);
void __RPC_STUB IStorage_CreateStorage_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_OpenStorage_Proxy(
IStorage* This,
LPCOLESTR pwcsName,
IStorage *pstgPriority,
DWORD grfMode,
SNB snbExclude,
DWORD reserved,
IStorage **ppstg);
void __RPC_STUB IStorage_OpenStorage_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_CopyTo_Proxy(
IStorage* This,
DWORD ciidExclude,
const IID *rgiidExclude,
SNB snbExclude,
IStorage *pstgDest);
void __RPC_STUB IStorage_CopyTo_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_MoveElementTo_Proxy(
IStorage* This,
LPCOLESTR pwcsName,
IStorage *pstgDest,
LPCOLESTR pwcsNewName,
DWORD grfFlags);
void __RPC_STUB IStorage_MoveElementTo_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_Commit_Proxy(
IStorage* This,
DWORD grfCommitFlags);
void __RPC_STUB IStorage_Commit_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_Revert_Proxy(
IStorage* This);
void __RPC_STUB IStorage_Revert_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_RemoteEnumElements_Proxy(
IStorage* This,
DWORD reserved1,
ULONG cbReserved2,
byte *reserved2,
DWORD reserved3,
IEnumSTATSTG **ppenum);
void __RPC_STUB IStorage_RemoteEnumElements_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_DestroyElement_Proxy(
IStorage* This,
LPCOLESTR pwcsName);
void __RPC_STUB IStorage_DestroyElement_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_RenameElement_Proxy(
IStorage* This,
LPCOLESTR pwcsOldName,
LPCOLESTR pwcsNewName);
void __RPC_STUB IStorage_RenameElement_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_SetElementTimes_Proxy(
IStorage* This,
LPCOLESTR pwcsName,
const FILETIME *pctime,
const FILETIME *patime,
const FILETIME *pmtime);
void __RPC_STUB IStorage_SetElementTimes_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_SetClass_Proxy(
IStorage* This,
REFCLSID clsid);
void __RPC_STUB IStorage_SetClass_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_SetStateBits_Proxy(
IStorage* This,
DWORD grfStateBits,
DWORD grfMask);
void __RPC_STUB IStorage_SetStateBits_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IStorage_Stat_Proxy(
IStorage* This,
STATSTG *pstatstg,
DWORD grfStatFlag);
void __RPC_STUB IStorage_Stat_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK IStorage_OpenStream_Proxy(
IStorage* This,
LPCOLESTR pwcsName,
void *reserved1,
DWORD grfMode,
DWORD reserved2,
IStream **ppstm);
HRESULT __RPC_STUB IStorage_OpenStream_Stub(
IStorage* This,
LPCOLESTR pwcsName,
ULONG cbReserved1,
byte *reserved1,
DWORD grfMode,
DWORD reserved2,
IStream **ppstm);
HRESULT CALLBACK IStorage_EnumElements_Proxy(
IStorage* This,
DWORD reserved1,
void *reserved2,
DWORD reserved3,
IEnumSTATSTG **ppenum);
HRESULT __RPC_STUB IStorage_EnumElements_Stub(
IStorage* This,
DWORD reserved1,
ULONG cbReserved2,
byte *reserved2,
DWORD reserved3,
IEnumSTATSTG **ppenum);
#endif /* __IStorage_INTERFACE_DEFINED__ */
/*****************************************************************************
* IPersistFile interface
*/
#ifndef __IPersistFile_INTERFACE_DEFINED__
#define __IPersistFile_INTERFACE_DEFINED__
typedef IPersistFile *LPPERSISTFILE;
DEFINE_GUID(IID_IPersistFile, 0x0000010b, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IPersistFile : public IPersist
{
virtual HRESULT STDMETHODCALLTYPE IsDirty(
) = 0;
virtual HRESULT STDMETHODCALLTYPE Load(
LPCOLESTR pszFileName,
DWORD dwMode) = 0;
virtual HRESULT STDMETHODCALLTYPE Save(
LPCOLESTR pszFileName,
BOOL fRemember) = 0;
virtual HRESULT STDMETHODCALLTYPE SaveCompleted(
LPCOLESTR pszFileName) = 0;
virtual HRESULT STDMETHODCALLTYPE GetCurFile(
LPOLESTR *ppszFileName) = 0;
};
#else
typedef struct IPersistFileVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IPersistFile* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IPersistFile* This);
ULONG (STDMETHODCALLTYPE *Release)(
IPersistFile* This);
/*** IPersist methods ***/
HRESULT (STDMETHODCALLTYPE *GetClassID)(
IPersistFile* This,
CLSID *pClassID);
/*** IPersistFile methods ***/
HRESULT (STDMETHODCALLTYPE *IsDirty)(
IPersistFile* This);
HRESULT (STDMETHODCALLTYPE *Load)(
IPersistFile* This,
LPCOLESTR pszFileName,
DWORD dwMode);
HRESULT (STDMETHODCALLTYPE *Save)(
IPersistFile* This,
LPCOLESTR pszFileName,
BOOL fRemember);
HRESULT (STDMETHODCALLTYPE *SaveCompleted)(
IPersistFile* This,
LPCOLESTR pszFileName);
HRESULT (STDMETHODCALLTYPE *GetCurFile)(
IPersistFile* This,
LPOLESTR *ppszFileName);
END_INTERFACE
} IPersistFileVtbl;
interface IPersistFile {
CONST_VTBL IPersistFileVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IPersistFile_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IPersistFile_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IPersistFile_Release(This) (This)->lpVtbl->Release(This)
/*** IPersist methods ***/
#define IPersistFile_GetClassID(This,pClassID) (This)->lpVtbl->GetClassID(This,pClassID)
/*** IPersistFile methods ***/
#define IPersistFile_IsDirty(This) (This)->lpVtbl->IsDirty(This)
#define IPersistFile_Load(This,pszFileName,dwMode) (This)->lpVtbl->Load(This,pszFileName,dwMode)
#define IPersistFile_Save(This,pszFileName,fRemember) (This)->lpVtbl->Save(This,pszFileName,fRemember)
#define IPersistFile_SaveCompleted(This,pszFileName) (This)->lpVtbl->SaveCompleted(This,pszFileName)
#define IPersistFile_GetCurFile(This,ppszFileName) (This)->lpVtbl->GetCurFile(This,ppszFileName)
#endif
#endif
HRESULT STDMETHODCALLTYPE IPersistFile_IsDirty_Proxy(
IPersistFile* This);
void __RPC_STUB IPersistFile_IsDirty_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IPersistFile_Load_Proxy(
IPersistFile* This,
LPCOLESTR pszFileName,
DWORD dwMode);
void __RPC_STUB IPersistFile_Load_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IPersistFile_Save_Proxy(
IPersistFile* This,
LPCOLESTR pszFileName,
BOOL fRemember);
void __RPC_STUB IPersistFile_Save_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IPersistFile_SaveCompleted_Proxy(
IPersistFile* This,
LPCOLESTR pszFileName);
void __RPC_STUB IPersistFile_SaveCompleted_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IPersistFile_GetCurFile_Proxy(
IPersistFile* This,
LPOLESTR *ppszFileName);
void __RPC_STUB IPersistFile_GetCurFile_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IPersistFile_INTERFACE_DEFINED__ */
/*****************************************************************************
* IPersistStorage interface
*/
#ifndef __IPersistStorage_INTERFACE_DEFINED__
#define __IPersistStorage_INTERFACE_DEFINED__
typedef IPersistStorage *LPPERSISTSTORAGE;
DEFINE_GUID(IID_IPersistStorage, 0x0000010a, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IPersistStorage : public IPersist
{
virtual HRESULT STDMETHODCALLTYPE IsDirty(
) = 0;
virtual HRESULT STDMETHODCALLTYPE InitNew(
IStorage *pStg) = 0;
virtual HRESULT STDMETHODCALLTYPE Load(
IStorage *pStg) = 0;
virtual HRESULT STDMETHODCALLTYPE Save(
IStorage *pStgSave,
BOOL fSameAsLoad) = 0;
virtual HRESULT STDMETHODCALLTYPE SaveCompleted(
IStorage *pStgNew) = 0;
virtual HRESULT STDMETHODCALLTYPE HandsOffStorage(
) = 0;
};
#else
typedef struct IPersistStorageVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IPersistStorage* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IPersistStorage* This);
ULONG (STDMETHODCALLTYPE *Release)(
IPersistStorage* This);
/*** IPersist methods ***/
HRESULT (STDMETHODCALLTYPE *GetClassID)(
IPersistStorage* This,
CLSID *pClassID);
/*** IPersistStorage methods ***/
HRESULT (STDMETHODCALLTYPE *IsDirty)(
IPersistStorage* This);
HRESULT (STDMETHODCALLTYPE *InitNew)(
IPersistStorage* This,
IStorage *pStg);
HRESULT (STDMETHODCALLTYPE *Load)(
IPersistStorage* This,
IStorage *pStg);
HRESULT (STDMETHODCALLTYPE *Save)(
IPersistStorage* This,
IStorage *pStgSave,
BOOL fSameAsLoad);
HRESULT (STDMETHODCALLTYPE *SaveCompleted)(
IPersistStorage* This,
IStorage *pStgNew);
HRESULT (STDMETHODCALLTYPE *HandsOffStorage)(
IPersistStorage* This);
END_INTERFACE
} IPersistStorageVtbl;
interface IPersistStorage {
CONST_VTBL IPersistStorageVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IPersistStorage_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IPersistStorage_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IPersistStorage_Release(This) (This)->lpVtbl->Release(This)
/*** IPersist methods ***/
#define IPersistStorage_GetClassID(This,pClassID) (This)->lpVtbl->GetClassID(This,pClassID)
/*** IPersistStorage methods ***/
#define IPersistStorage_IsDirty(This) (This)->lpVtbl->IsDirty(This)
#define IPersistStorage_InitNew(This,pStg) (This)->lpVtbl->InitNew(This,pStg)
#define IPersistStorage_Load(This,pStg) (This)->lpVtbl->Load(This,pStg)
#define IPersistStorage_Save(This,pStgSave,fSameAsLoad) (This)->lpVtbl->Save(This,pStgSave,fSameAsLoad)
#define IPersistStorage_SaveCompleted(This,pStgNew) (This)->lpVtbl->SaveCompleted(This,pStgNew)
#define IPersistStorage_HandsOffStorage(This) (This)->lpVtbl->HandsOffStorage(This)
#endif
#endif
HRESULT STDMETHODCALLTYPE IPersistStorage_IsDirty_Proxy(
IPersistStorage* This);
void __RPC_STUB IPersistStorage_IsDirty_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IPersistStorage_InitNew_Proxy(
IPersistStorage* This,
IStorage *pStg);
void __RPC_STUB IPersistStorage_InitNew_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IPersistStorage_Load_Proxy(
IPersistStorage* This,
IStorage *pStg);
void __RPC_STUB IPersistStorage_Load_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IPersistStorage_Save_Proxy(
IPersistStorage* This,
IStorage *pStgSave,
BOOL fSameAsLoad);
void __RPC_STUB IPersistStorage_Save_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IPersistStorage_SaveCompleted_Proxy(
IPersistStorage* This,
IStorage *pStgNew);
void __RPC_STUB IPersistStorage_SaveCompleted_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IPersistStorage_HandsOffStorage_Proxy(
IPersistStorage* This);
void __RPC_STUB IPersistStorage_HandsOffStorage_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IPersistStorage_INTERFACE_DEFINED__ */
/*****************************************************************************
* IRootStorage interface
*/
#ifndef __IRootStorage_INTERFACE_DEFINED__
#define __IRootStorage_INTERFACE_DEFINED__
typedef IRootStorage *LPROOTSTORAGE;
DEFINE_GUID(IID_IRootStorage, 0x00000012, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IRootStorage : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE SwitchToFile(
LPOLESTR pszFile) = 0;
};
#else
typedef struct IRootStorageVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IRootStorage* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IRootStorage* This);
ULONG (STDMETHODCALLTYPE *Release)(
IRootStorage* This);
/*** IRootStorage methods ***/
HRESULT (STDMETHODCALLTYPE *SwitchToFile)(
IRootStorage* This,
LPOLESTR pszFile);
END_INTERFACE
} IRootStorageVtbl;
interface IRootStorage {
CONST_VTBL IRootStorageVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IRootStorage_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IRootStorage_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IRootStorage_Release(This) (This)->lpVtbl->Release(This)
/*** IRootStorage methods ***/
#define IRootStorage_SwitchToFile(This,pszFile) (This)->lpVtbl->SwitchToFile(This,pszFile)
#endif
#endif
HRESULT STDMETHODCALLTYPE IRootStorage_SwitchToFile_Proxy(
IRootStorage* This,
LPOLESTR pszFile);
void __RPC_STUB IRootStorage_SwitchToFile_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IRootStorage_INTERFACE_DEFINED__ */
/*****************************************************************************
* ILockBytes interface
*/
#ifndef __ILockBytes_INTERFACE_DEFINED__
#define __ILockBytes_INTERFACE_DEFINED__
typedef ILockBytes *LPLOCKBYTES;
DEFINE_GUID(IID_ILockBytes, 0x0000000a, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface ILockBytes : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE ReadAt(
ULARGE_INTEGER ulOffset,
void *pv,
ULONG cb,
ULONG *pcbRead) = 0;
virtual HRESULT STDMETHODCALLTYPE WriteAt(
ULARGE_INTEGER ulOffset,
const void *pv,
ULONG cb,
ULONG *pcbWritten) = 0;
virtual HRESULT STDMETHODCALLTYPE Flush(
) = 0;
virtual HRESULT STDMETHODCALLTYPE SetSize(
ULARGE_INTEGER cb) = 0;
virtual HRESULT STDMETHODCALLTYPE LockRegion(
ULARGE_INTEGER libOffset,
ULARGE_INTEGER cb,
DWORD dwLockType) = 0;
virtual HRESULT STDMETHODCALLTYPE UnlockRegion(
ULARGE_INTEGER libOffset,
ULARGE_INTEGER cb,
DWORD dwLockType) = 0;
virtual HRESULT STDMETHODCALLTYPE Stat(
STATSTG *pstatstg,
DWORD grfStatFlag) = 0;
};
#else
typedef struct ILockBytesVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
ILockBytes* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
ILockBytes* This);
ULONG (STDMETHODCALLTYPE *Release)(
ILockBytes* This);
/*** ILockBytes methods ***/
HRESULT (STDMETHODCALLTYPE *ReadAt)(
ILockBytes* This,
ULARGE_INTEGER ulOffset,
void *pv,
ULONG cb,
ULONG *pcbRead);
HRESULT (STDMETHODCALLTYPE *WriteAt)(
ILockBytes* This,
ULARGE_INTEGER ulOffset,
const void *pv,
ULONG cb,
ULONG *pcbWritten);
HRESULT (STDMETHODCALLTYPE *Flush)(
ILockBytes* This);
HRESULT (STDMETHODCALLTYPE *SetSize)(
ILockBytes* This,
ULARGE_INTEGER cb);
HRESULT (STDMETHODCALLTYPE *LockRegion)(
ILockBytes* This,
ULARGE_INTEGER libOffset,
ULARGE_INTEGER cb,
DWORD dwLockType);
HRESULT (STDMETHODCALLTYPE *UnlockRegion)(
ILockBytes* This,
ULARGE_INTEGER libOffset,
ULARGE_INTEGER cb,
DWORD dwLockType);
HRESULT (STDMETHODCALLTYPE *Stat)(
ILockBytes* This,
STATSTG *pstatstg,
DWORD grfStatFlag);
END_INTERFACE
} ILockBytesVtbl;
interface ILockBytes {
CONST_VTBL ILockBytesVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define ILockBytes_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define ILockBytes_AddRef(This) (This)->lpVtbl->AddRef(This)
#define ILockBytes_Release(This) (This)->lpVtbl->Release(This)
/*** ILockBytes methods ***/
#define ILockBytes_ReadAt(This,ulOffset,pv,cb,pcbRead) (This)->lpVtbl->ReadAt(This,ulOffset,pv,cb,pcbRead)
#define ILockBytes_WriteAt(This,ulOffset,pv,cb,pcbWritten) (This)->lpVtbl->WriteAt(This,ulOffset,pv,cb,pcbWritten)
#define ILockBytes_Flush(This) (This)->lpVtbl->Flush(This)
#define ILockBytes_SetSize(This,cb) (This)->lpVtbl->SetSize(This,cb)
#define ILockBytes_LockRegion(This,libOffset,cb,dwLockType) (This)->lpVtbl->LockRegion(This,libOffset,cb,dwLockType)
#define ILockBytes_UnlockRegion(This,libOffset,cb,dwLockType) (This)->lpVtbl->UnlockRegion(This,libOffset,cb,dwLockType)
#define ILockBytes_Stat(This,pstatstg,grfStatFlag) (This)->lpVtbl->Stat(This,pstatstg,grfStatFlag)
#endif
#endif
HRESULT STDMETHODCALLTYPE ILockBytes_RemoteReadAt_Proxy(
ILockBytes* This,
ULARGE_INTEGER ulOffset,
byte *pv,
ULONG cb,
ULONG *pcbRead);
void __RPC_STUB ILockBytes_RemoteReadAt_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ILockBytes_RemoteWriteAt_Proxy(
ILockBytes* This,
ULARGE_INTEGER ulOffset,
const byte *pv,
ULONG cb,
ULONG *pcbWritten);
void __RPC_STUB ILockBytes_RemoteWriteAt_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ILockBytes_Flush_Proxy(
ILockBytes* This);
void __RPC_STUB ILockBytes_Flush_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ILockBytes_SetSize_Proxy(
ILockBytes* This,
ULARGE_INTEGER cb);
void __RPC_STUB ILockBytes_SetSize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ILockBytes_LockRegion_Proxy(
ILockBytes* This,
ULARGE_INTEGER libOffset,
ULARGE_INTEGER cb,
DWORD dwLockType);
void __RPC_STUB ILockBytes_LockRegion_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ILockBytes_UnlockRegion_Proxy(
ILockBytes* This,
ULARGE_INTEGER libOffset,
ULARGE_INTEGER cb,
DWORD dwLockType);
void __RPC_STUB ILockBytes_UnlockRegion_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ILockBytes_Stat_Proxy(
ILockBytes* This,
STATSTG *pstatstg,
DWORD grfStatFlag);
void __RPC_STUB ILockBytes_Stat_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK ILockBytes_ReadAt_Proxy(
ILockBytes* This,
ULARGE_INTEGER ulOffset,
void *pv,
ULONG cb,
ULONG *pcbRead);
HRESULT __RPC_STUB ILockBytes_ReadAt_Stub(
ILockBytes* This,
ULARGE_INTEGER ulOffset,
byte *pv,
ULONG cb,
ULONG *pcbRead);
HRESULT CALLBACK ILockBytes_WriteAt_Proxy(
ILockBytes* This,
ULARGE_INTEGER ulOffset,
const void *pv,
ULONG cb,
ULONG *pcbWritten);
HRESULT __RPC_STUB ILockBytes_WriteAt_Stub(
ILockBytes* This,
ULARGE_INTEGER ulOffset,
const byte *pv,
ULONG cb,
ULONG *pcbWritten);
#endif /* __ILockBytes_INTERFACE_DEFINED__ */
/*****************************************************************************
* IFillLockBytes interface
*/
#ifndef __IFillLockBytes_INTERFACE_DEFINED__
#define __IFillLockBytes_INTERFACE_DEFINED__
DEFINE_GUID(IID_IFillLockBytes, 0x99caf010, 0x415e, 0x11cf, 0x88,0x14, 0x00,0xaa,0x00,0xb5,0x69,0xf5);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IFillLockBytes : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE FillAppend(
const void *pv,
ULONG cb,
ULONG *pcbWritten) = 0;
virtual HRESULT STDMETHODCALLTYPE FillAt(
ULARGE_INTEGER ulOffset,
const void *pv,
ULONG cb,
ULONG *pcbWritten) = 0;
virtual HRESULT STDMETHODCALLTYPE SetFillSize(
ULARGE_INTEGER ulSize) = 0;
virtual HRESULT STDMETHODCALLTYPE Terminate(
BOOL bCanceled) = 0;
};
#else
typedef struct IFillLockBytesVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IFillLockBytes* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IFillLockBytes* This);
ULONG (STDMETHODCALLTYPE *Release)(
IFillLockBytes* This);
/*** IFillLockBytes methods ***/
HRESULT (STDMETHODCALLTYPE *FillAppend)(
IFillLockBytes* This,
const void *pv,
ULONG cb,
ULONG *pcbWritten);
HRESULT (STDMETHODCALLTYPE *FillAt)(
IFillLockBytes* This,
ULARGE_INTEGER ulOffset,
const void *pv,
ULONG cb,
ULONG *pcbWritten);
HRESULT (STDMETHODCALLTYPE *SetFillSize)(
IFillLockBytes* This,
ULARGE_INTEGER ulSize);
HRESULT (STDMETHODCALLTYPE *Terminate)(
IFillLockBytes* This,
BOOL bCanceled);
END_INTERFACE
} IFillLockBytesVtbl;
interface IFillLockBytes {
CONST_VTBL IFillLockBytesVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IFillLockBytes_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IFillLockBytes_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IFillLockBytes_Release(This) (This)->lpVtbl->Release(This)
/*** IFillLockBytes methods ***/
#define IFillLockBytes_FillAppend(This,pv,cb,pcbWritten) (This)->lpVtbl->FillAppend(This,pv,cb,pcbWritten)
#define IFillLockBytes_FillAt(This,ulOffset,pv,cb,pcbWritten) (This)->lpVtbl->FillAt(This,ulOffset,pv,cb,pcbWritten)
#define IFillLockBytes_SetFillSize(This,ulSize) (This)->lpVtbl->SetFillSize(This,ulSize)
#define IFillLockBytes_Terminate(This,bCanceled) (This)->lpVtbl->Terminate(This,bCanceled)
#endif
#endif
HRESULT STDMETHODCALLTYPE IFillLockBytes_RemoteFillAppend_Proxy(
IFillLockBytes* This,
const byte *pv,
ULONG cb,
ULONG *pcbWritten);
void __RPC_STUB IFillLockBytes_RemoteFillAppend_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IFillLockBytes_RemoteFillAt_Proxy(
IFillLockBytes* This,
ULARGE_INTEGER ulOffset,
const byte *pv,
ULONG cb,
ULONG *pcbWritten);
void __RPC_STUB IFillLockBytes_RemoteFillAt_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IFillLockBytes_SetFillSize_Proxy(
IFillLockBytes* This,
ULARGE_INTEGER ulSize);
void __RPC_STUB IFillLockBytes_SetFillSize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IFillLockBytes_Terminate_Proxy(
IFillLockBytes* This,
BOOL bCanceled);
void __RPC_STUB IFillLockBytes_Terminate_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK IFillLockBytes_FillAppend_Proxy(
IFillLockBytes* This,
const void *pv,
ULONG cb,
ULONG *pcbWritten);
HRESULT __RPC_STUB IFillLockBytes_FillAppend_Stub(
IFillLockBytes* This,
const byte *pv,
ULONG cb,
ULONG *pcbWritten);
HRESULT CALLBACK IFillLockBytes_FillAt_Proxy(
IFillLockBytes* This,
ULARGE_INTEGER ulOffset,
const void *pv,
ULONG cb,
ULONG *pcbWritten);
HRESULT __RPC_STUB IFillLockBytes_FillAt_Stub(
IFillLockBytes* This,
ULARGE_INTEGER ulOffset,
const byte *pv,
ULONG cb,
ULONG *pcbWritten);
#endif /* __IFillLockBytes_INTERFACE_DEFINED__ */
/*****************************************************************************
* IProgressNotify interface
*/
#ifndef __IProgressNotify_INTERFACE_DEFINED__
#define __IProgressNotify_INTERFACE_DEFINED__
DEFINE_GUID(IID_IProgressNotify, 0xa9d758a0, 0x4617, 0x11cf, 0x95,0xfc, 0x00,0xaa,0x00,0x68,0x0d,0xb4);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IProgressNotify : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE OnProgress(
DWORD dwProgressCurrent,
DWORD dwProgressMaximum,
BOOL fAccurate,
BOOL fOwner) = 0;
};
#else
typedef struct IProgressNotifyVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IProgressNotify* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IProgressNotify* This);
ULONG (STDMETHODCALLTYPE *Release)(
IProgressNotify* This);
/*** IProgressNotify methods ***/
HRESULT (STDMETHODCALLTYPE *OnProgress)(
IProgressNotify* This,
DWORD dwProgressCurrent,
DWORD dwProgressMaximum,
BOOL fAccurate,
BOOL fOwner);
END_INTERFACE
} IProgressNotifyVtbl;
interface IProgressNotify {
CONST_VTBL IProgressNotifyVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IProgressNotify_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IProgressNotify_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IProgressNotify_Release(This) (This)->lpVtbl->Release(This)
/*** IProgressNotify methods ***/
#define IProgressNotify_OnProgress(This,dwProgressCurrent,dwProgressMaximum,fAccurate,fOwner) (This)->lpVtbl->OnProgress(This,dwProgressCurrent,dwProgressMaximum,fAccurate,fOwner)
#endif
#endif
HRESULT STDMETHODCALLTYPE IProgressNotify_OnProgress_Proxy(
IProgressNotify* This,
DWORD dwProgressCurrent,
DWORD dwProgressMaximum,
BOOL fAccurate,
BOOL fOwner);
void __RPC_STUB IProgressNotify_OnProgress_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IProgressNotify_INTERFACE_DEFINED__ */
/*****************************************************************************
* ILayoutStorage interface
*/
#ifndef __ILayoutStorage_INTERFACE_DEFINED__
#define __ILayoutStorage_INTERFACE_DEFINED__
typedef struct tagStorageLayout {
DWORD LayoutType;
OLECHAR *pwcsElementName;
LARGE_INTEGER cOffset;
LARGE_INTEGER cBytes;
} StorageLayout;
DEFINE_GUID(IID_ILayoutStorage, 0x0e6d4d90, 0x6738, 0x11cf, 0x96,0x08, 0x00,0xaa,0x00,0x68,0x0d,0xb4);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface ILayoutStorage : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE LayoutScript(
StorageLayout *pStorageLayout,
DWORD nEntries,
DWORD glfInterleavedFlag) = 0;
virtual HRESULT STDMETHODCALLTYPE BeginMonitor(
) = 0;
virtual HRESULT STDMETHODCALLTYPE EndMonitor(
) = 0;
virtual HRESULT STDMETHODCALLTYPE ReLayoutDocfile(
OLECHAR *pwcsNewDfName) = 0;
virtual HRESULT STDMETHODCALLTYPE ReLayoutDocfileOnILockBytes(
ILockBytes *pILockBytes) = 0;
};
#else
typedef struct ILayoutStorageVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
ILayoutStorage* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
ILayoutStorage* This);
ULONG (STDMETHODCALLTYPE *Release)(
ILayoutStorage* This);
/*** ILayoutStorage methods ***/
HRESULT (STDMETHODCALLTYPE *LayoutScript)(
ILayoutStorage* This,
StorageLayout *pStorageLayout,
DWORD nEntries,
DWORD glfInterleavedFlag);
HRESULT (STDMETHODCALLTYPE *BeginMonitor)(
ILayoutStorage* This);
HRESULT (STDMETHODCALLTYPE *EndMonitor)(
ILayoutStorage* This);
HRESULT (STDMETHODCALLTYPE *ReLayoutDocfile)(
ILayoutStorage* This,
OLECHAR *pwcsNewDfName);
HRESULT (STDMETHODCALLTYPE *ReLayoutDocfileOnILockBytes)(
ILayoutStorage* This,
ILockBytes *pILockBytes);
END_INTERFACE
} ILayoutStorageVtbl;
interface ILayoutStorage {
CONST_VTBL ILayoutStorageVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define ILayoutStorage_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define ILayoutStorage_AddRef(This) (This)->lpVtbl->AddRef(This)
#define ILayoutStorage_Release(This) (This)->lpVtbl->Release(This)
/*** ILayoutStorage methods ***/
#define ILayoutStorage_LayoutScript(This,pStorageLayout,nEntries,glfInterleavedFlag) (This)->lpVtbl->LayoutScript(This,pStorageLayout,nEntries,glfInterleavedFlag)
#define ILayoutStorage_BeginMonitor(This) (This)->lpVtbl->BeginMonitor(This)
#define ILayoutStorage_EndMonitor(This) (This)->lpVtbl->EndMonitor(This)
#define ILayoutStorage_ReLayoutDocfile(This,pwcsNewDfName) (This)->lpVtbl->ReLayoutDocfile(This,pwcsNewDfName)
#define ILayoutStorage_ReLayoutDocfileOnILockBytes(This,pILockBytes) (This)->lpVtbl->ReLayoutDocfileOnILockBytes(This,pILockBytes)
#endif
#endif
HRESULT STDMETHODCALLTYPE ILayoutStorage_LayoutScript_Proxy(
ILayoutStorage* This,
StorageLayout *pStorageLayout,
DWORD nEntries,
DWORD glfInterleavedFlag);
void __RPC_STUB ILayoutStorage_LayoutScript_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ILayoutStorage_BeginMonitor_Proxy(
ILayoutStorage* This);
void __RPC_STUB ILayoutStorage_BeginMonitor_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ILayoutStorage_EndMonitor_Proxy(
ILayoutStorage* This);
void __RPC_STUB ILayoutStorage_EndMonitor_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ILayoutStorage_ReLayoutDocfile_Proxy(
ILayoutStorage* This,
OLECHAR *pwcsNewDfName);
void __RPC_STUB ILayoutStorage_ReLayoutDocfile_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ILayoutStorage_ReLayoutDocfileOnILockBytes_Proxy(
ILayoutStorage* This,
ILockBytes *pILockBytes);
void __RPC_STUB ILayoutStorage_ReLayoutDocfileOnILockBytes_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __ILayoutStorage_INTERFACE_DEFINED__ */
/*****************************************************************************
* IBlockingLock interface
*/
#ifndef __IBlockingLock_INTERFACE_DEFINED__
#define __IBlockingLock_INTERFACE_DEFINED__
DEFINE_GUID(IID_IBlockingLock, 0x30f3d47a, 0x6447, 0x11d1, 0x8e,0x3c, 0x00,0xc0,0x4f,0xb9,0x38,0x6d);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IBlockingLock : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Lock(
DWORD dwTimeout) = 0;
virtual HRESULT STDMETHODCALLTYPE Unlock(
) = 0;
};
#else
typedef struct IBlockingLockVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IBlockingLock* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IBlockingLock* This);
ULONG (STDMETHODCALLTYPE *Release)(
IBlockingLock* This);
/*** IBlockingLock methods ***/
HRESULT (STDMETHODCALLTYPE *Lock)(
IBlockingLock* This,
DWORD dwTimeout);
HRESULT (STDMETHODCALLTYPE *Unlock)(
IBlockingLock* This);
END_INTERFACE
} IBlockingLockVtbl;
interface IBlockingLock {
CONST_VTBL IBlockingLockVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IBlockingLock_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IBlockingLock_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IBlockingLock_Release(This) (This)->lpVtbl->Release(This)
/*** IBlockingLock methods ***/
#define IBlockingLock_Lock(This,dwTimeout) (This)->lpVtbl->Lock(This,dwTimeout)
#define IBlockingLock_Unlock(This) (This)->lpVtbl->Unlock(This)
#endif
#endif
HRESULT STDMETHODCALLTYPE IBlockingLock_Lock_Proxy(
IBlockingLock* This,
DWORD dwTimeout);
void __RPC_STUB IBlockingLock_Lock_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IBlockingLock_Unlock_Proxy(
IBlockingLock* This);
void __RPC_STUB IBlockingLock_Unlock_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IBlockingLock_INTERFACE_DEFINED__ */
/*****************************************************************************
* ITimeAndNoticeControl interface
*/
#ifndef __ITimeAndNoticeControl_INTERFACE_DEFINED__
#define __ITimeAndNoticeControl_INTERFACE_DEFINED__
DEFINE_GUID(IID_ITimeAndNoticeControl, 0xbc0bf6ae, 0x8878, 0x11d1, 0x83,0xe9, 0x00,0xc0,0x4f,0xc2,0xc6,0xd4);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface ITimeAndNoticeControl : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE SuppressChanges(
DWORD res1,
DWORD res2) = 0;
};
#else
typedef struct ITimeAndNoticeControlVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
ITimeAndNoticeControl* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
ITimeAndNoticeControl* This);
ULONG (STDMETHODCALLTYPE *Release)(
ITimeAndNoticeControl* This);
/*** ITimeAndNoticeControl methods ***/
HRESULT (STDMETHODCALLTYPE *SuppressChanges)(
ITimeAndNoticeControl* This,
DWORD res1,
DWORD res2);
END_INTERFACE
} ITimeAndNoticeControlVtbl;
interface ITimeAndNoticeControl {
CONST_VTBL ITimeAndNoticeControlVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define ITimeAndNoticeControl_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define ITimeAndNoticeControl_AddRef(This) (This)->lpVtbl->AddRef(This)
#define ITimeAndNoticeControl_Release(This) (This)->lpVtbl->Release(This)
/*** ITimeAndNoticeControl methods ***/
#define ITimeAndNoticeControl_SuppressChanges(This,res1,res2) (This)->lpVtbl->SuppressChanges(This,res1,res2)
#endif
#endif
HRESULT STDMETHODCALLTYPE ITimeAndNoticeControl_SuppressChanges_Proxy(
ITimeAndNoticeControl* This,
DWORD res1,
DWORD res2);
void __RPC_STUB ITimeAndNoticeControl_SuppressChanges_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __ITimeAndNoticeControl_INTERFACE_DEFINED__ */
/*****************************************************************************
* IOplockStorage interface
*/
#ifndef __IOplockStorage_INTERFACE_DEFINED__
#define __IOplockStorage_INTERFACE_DEFINED__
DEFINE_GUID(IID_IOplockStorage, 0x8d19c834, 0x8879, 0x11d1, 0x83,0xe9, 0x00,0xc0,0x4f,0xc2,0xc6,0xd4);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IOplockStorage : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE CreateStorageEx(
LPCWSTR pwcsName,
DWORD grfMode,
DWORD stgfmt,
DWORD grfAttrs,
REFIID riid,
void **ppstgOpen) = 0;
virtual HRESULT STDMETHODCALLTYPE OpenStorageEx(
LPCWSTR pwcsName,
DWORD grfMode,
DWORD stgfmt,
DWORD grfAttrs,
REFIID riid,
void **ppstgOpen) = 0;
};
#else
typedef struct IOplockStorageVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IOplockStorage* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IOplockStorage* This);
ULONG (STDMETHODCALLTYPE *Release)(
IOplockStorage* This);
/*** IOplockStorage methods ***/
HRESULT (STDMETHODCALLTYPE *CreateStorageEx)(
IOplockStorage* This,
LPCWSTR pwcsName,
DWORD grfMode,
DWORD stgfmt,
DWORD grfAttrs,
REFIID riid,
void **ppstgOpen);
HRESULT (STDMETHODCALLTYPE *OpenStorageEx)(
IOplockStorage* This,
LPCWSTR pwcsName,
DWORD grfMode,
DWORD stgfmt,
DWORD grfAttrs,
REFIID riid,
void **ppstgOpen);
END_INTERFACE
} IOplockStorageVtbl;
interface IOplockStorage {
CONST_VTBL IOplockStorageVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IOplockStorage_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IOplockStorage_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IOplockStorage_Release(This) (This)->lpVtbl->Release(This)
/*** IOplockStorage methods ***/
#define IOplockStorage_CreateStorageEx(This,pwcsName,grfMode,stgfmt,grfAttrs,riid,ppstgOpen) (This)->lpVtbl->CreateStorageEx(This,pwcsName,grfMode,stgfmt,grfAttrs,riid,ppstgOpen)
#define IOplockStorage_OpenStorageEx(This,pwcsName,grfMode,stgfmt,grfAttrs,riid,ppstgOpen) (This)->lpVtbl->OpenStorageEx(This,pwcsName,grfMode,stgfmt,grfAttrs,riid,ppstgOpen)
#endif
#endif
HRESULT STDMETHODCALLTYPE IOplockStorage_CreateStorageEx_Proxy(
IOplockStorage* This,
LPCWSTR pwcsName,
DWORD grfMode,
DWORD stgfmt,
DWORD grfAttrs,
REFIID riid,
void **ppstgOpen);
void __RPC_STUB IOplockStorage_CreateStorageEx_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IOplockStorage_OpenStorageEx_Proxy(
IOplockStorage* This,
LPCWSTR pwcsName,
DWORD grfMode,
DWORD stgfmt,
DWORD grfAttrs,
REFIID riid,
void **ppstgOpen);
void __RPC_STUB IOplockStorage_OpenStorageEx_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IOplockStorage_INTERFACE_DEFINED__ */
/*****************************************************************************
* IEnumFORMATETC interface
*/
#ifndef __IEnumFORMATETC_INTERFACE_DEFINED__
#define __IEnumFORMATETC_INTERFACE_DEFINED__
typedef IEnumFORMATETC *LPENUMFORMATETC;
typedef struct tagDVTARGETDEVICE {
DWORD tdSize;
WORD tdDriverNameOffset;
WORD tdDeviceNameOffset;
WORD tdPortNameOffset;
WORD tdExtDevmodeOffset;
BYTE tdData[1];
} DVTARGETDEVICE;
typedef CLIPFORMAT *LPCLIPFORMAT;
typedef struct tagFORMATETC {
CLIPFORMAT cfFormat;
DVTARGETDEVICE *ptd;
DWORD dwAspect;
LONG lindex;
DWORD tymed;
} FORMATETC;
typedef struct tagFORMATETC *LPFORMATETC;
DEFINE_GUID(IID_IEnumFORMATETC, 0x00000103, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IEnumFORMATETC : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Next(
ULONG celt,
FORMATETC *rgelt,
ULONG *pceltFetched) = 0;
virtual HRESULT STDMETHODCALLTYPE Skip(
ULONG celt) = 0;
virtual HRESULT STDMETHODCALLTYPE Reset(
) = 0;
virtual HRESULT STDMETHODCALLTYPE Clone(
IEnumFORMATETC **ppenum) = 0;
};
#else
typedef struct IEnumFORMATETCVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IEnumFORMATETC* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IEnumFORMATETC* This);
ULONG (STDMETHODCALLTYPE *Release)(
IEnumFORMATETC* This);
/*** IEnumFORMATETC methods ***/
HRESULT (STDMETHODCALLTYPE *Next)(
IEnumFORMATETC* This,
ULONG celt,
FORMATETC *rgelt,
ULONG *pceltFetched);
HRESULT (STDMETHODCALLTYPE *Skip)(
IEnumFORMATETC* This,
ULONG celt);
HRESULT (STDMETHODCALLTYPE *Reset)(
IEnumFORMATETC* This);
HRESULT (STDMETHODCALLTYPE *Clone)(
IEnumFORMATETC* This,
IEnumFORMATETC **ppenum);
END_INTERFACE
} IEnumFORMATETCVtbl;
interface IEnumFORMATETC {
CONST_VTBL IEnumFORMATETCVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IEnumFORMATETC_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IEnumFORMATETC_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IEnumFORMATETC_Release(This) (This)->lpVtbl->Release(This)
/*** IEnumFORMATETC methods ***/
#define IEnumFORMATETC_Next(This,celt,rgelt,pceltFetched) (This)->lpVtbl->Next(This,celt,rgelt,pceltFetched)
#define IEnumFORMATETC_Skip(This,celt) (This)->lpVtbl->Skip(This,celt)
#define IEnumFORMATETC_Reset(This) (This)->lpVtbl->Reset(This)
#define IEnumFORMATETC_Clone(This,ppenum) (This)->lpVtbl->Clone(This,ppenum)
#endif
#endif
HRESULT STDMETHODCALLTYPE IEnumFORMATETC_RemoteNext_Proxy(
IEnumFORMATETC* This,
ULONG celt,
FORMATETC *rgelt,
ULONG *pceltFetched);
void __RPC_STUB IEnumFORMATETC_RemoteNext_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumFORMATETC_Skip_Proxy(
IEnumFORMATETC* This,
ULONG celt);
void __RPC_STUB IEnumFORMATETC_Skip_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumFORMATETC_Reset_Proxy(
IEnumFORMATETC* This);
void __RPC_STUB IEnumFORMATETC_Reset_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumFORMATETC_Clone_Proxy(
IEnumFORMATETC* This,
IEnumFORMATETC **ppenum);
void __RPC_STUB IEnumFORMATETC_Clone_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK IEnumFORMATETC_Next_Proxy(
IEnumFORMATETC* This,
ULONG celt,
FORMATETC *rgelt,
ULONG *pceltFetched);
HRESULT __RPC_STUB IEnumFORMATETC_Next_Stub(
IEnumFORMATETC* This,
ULONG celt,
FORMATETC *rgelt,
ULONG *pceltFetched);
#endif /* __IEnumFORMATETC_INTERFACE_DEFINED__ */
/*****************************************************************************
* IEnumSTATDATA interface
*/
#ifndef __IEnumSTATDATA_INTERFACE_DEFINED__
#define __IEnumSTATDATA_INTERFACE_DEFINED__
typedef IEnumSTATDATA *LPENUMSTATDATA;
typedef enum tagADVF {
ADVF_NODATA = 1,
ADVF_PRIMEFIRST = 2,
ADVF_ONLYONCE = 4,
ADVF_DATAONSTOP = 64,
ADVFCACHE_NOHANDLER = 8,
ADVFCACHE_FORCEBUILTIN = 16,
ADVFCACHE_ONSAVE = 32
} ADVF;
typedef struct tagSTATDATA {
FORMATETC formatetc;
DWORD advf;
IAdviseSink *pAdvSink;
DWORD dwConnection;
} STATDATA;
typedef struct tagSTATDATA *LPSTATDATA;
DEFINE_GUID(IID_IEnumSTATDATA, 0x00000105, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IEnumSTATDATA : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Next(
ULONG celt,
STATDATA *rgelt,
ULONG *pceltFetched) = 0;
virtual HRESULT STDMETHODCALLTYPE Skip(
ULONG celt) = 0;
virtual HRESULT STDMETHODCALLTYPE Reset(
) = 0;
virtual HRESULT STDMETHODCALLTYPE Clone(
IEnumSTATDATA **ppenum) = 0;
};
#else
typedef struct IEnumSTATDATAVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IEnumSTATDATA* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IEnumSTATDATA* This);
ULONG (STDMETHODCALLTYPE *Release)(
IEnumSTATDATA* This);
/*** IEnumSTATDATA methods ***/
HRESULT (STDMETHODCALLTYPE *Next)(
IEnumSTATDATA* This,
ULONG celt,
STATDATA *rgelt,
ULONG *pceltFetched);
HRESULT (STDMETHODCALLTYPE *Skip)(
IEnumSTATDATA* This,
ULONG celt);
HRESULT (STDMETHODCALLTYPE *Reset)(
IEnumSTATDATA* This);
HRESULT (STDMETHODCALLTYPE *Clone)(
IEnumSTATDATA* This,
IEnumSTATDATA **ppenum);
END_INTERFACE
} IEnumSTATDATAVtbl;
interface IEnumSTATDATA {
CONST_VTBL IEnumSTATDATAVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IEnumSTATDATA_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IEnumSTATDATA_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IEnumSTATDATA_Release(This) (This)->lpVtbl->Release(This)
/*** IEnumSTATDATA methods ***/
#define IEnumSTATDATA_Next(This,celt,rgelt,pceltFetched) (This)->lpVtbl->Next(This,celt,rgelt,pceltFetched)
#define IEnumSTATDATA_Skip(This,celt) (This)->lpVtbl->Skip(This,celt)
#define IEnumSTATDATA_Reset(This) (This)->lpVtbl->Reset(This)
#define IEnumSTATDATA_Clone(This,ppenum) (This)->lpVtbl->Clone(This,ppenum)
#endif
#endif
HRESULT STDMETHODCALLTYPE IEnumSTATDATA_RemoteNext_Proxy(
IEnumSTATDATA* This,
ULONG celt,
STATDATA *rgelt,
ULONG *pceltFetched);
void __RPC_STUB IEnumSTATDATA_RemoteNext_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumSTATDATA_Skip_Proxy(
IEnumSTATDATA* This,
ULONG celt);
void __RPC_STUB IEnumSTATDATA_Skip_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumSTATDATA_Reset_Proxy(
IEnumSTATDATA* This);
void __RPC_STUB IEnumSTATDATA_Reset_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumSTATDATA_Clone_Proxy(
IEnumSTATDATA* This,
IEnumSTATDATA **ppenum);
void __RPC_STUB IEnumSTATDATA_Clone_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK IEnumSTATDATA_Next_Proxy(
IEnumSTATDATA* This,
ULONG celt,
STATDATA *rgelt,
ULONG *pceltFetched);
HRESULT __RPC_STUB IEnumSTATDATA_Next_Stub(
IEnumSTATDATA* This,
ULONG celt,
STATDATA *rgelt,
ULONG *pceltFetched);
#endif /* __IEnumSTATDATA_INTERFACE_DEFINED__ */
/*****************************************************************************
* IAdviseSink interface
*/
#ifndef __IAdviseSink_INTERFACE_DEFINED__
#define __IAdviseSink_INTERFACE_DEFINED__
typedef IAdviseSink *LPADVISESINK;
typedef enum tagTYMED {
TYMED_HGLOBAL = 1,
TYMED_FILE = 2,
TYMED_ISTREAM = 4,
TYMED_ISTORAGE = 8,
TYMED_GDI = 16,
TYMED_MFPICT = 32,
TYMED_ENHMF = 64,
TYMED_NULL = 0
} TYMED;
typedef struct tagRemSTGMEDIUM {
DWORD tymed;
DWORD dwHandleType;
ULONG pData;
ULONG pUnkForRelease;
ULONG cbData;
byte data[1];
} RemSTGMEDIUM;
typedef struct tagSTGMEDIUM {
DWORD tymed;
union {
HBITMAP hBitmap;
HMETAFILEPICT hMetaFilePict;
HENHMETAFILE hEnhMetaFile;
HGLOBAL hGlobal;
LPOLESTR lpszFileName;
IStream *pstm;
IStorage *pstg;
} DUMMYUNIONNAME;
IUnknown *pUnkForRelease;
} uSTGMEDIUM;
typedef struct _GDI_OBJECT {
DWORD ObjectType;
union {
wireHBITMAP hBitmap;
wireHPALETTE hPalette;
wireHGLOBAL hGeneric;
} u;
} GDI_OBJECT;
typedef struct _userSTGMEDIUM {
struct {
DWORD tymed;
union {
wireHMETAFILEPICT hMetaFilePict;
wireHENHMETAFILE hHEnhMetaFile;
GDI_OBJECT *hGdiHandle;
wireHGLOBAL hGlobal;
LPOLESTR lpszFileName;
BYTE_BLOB *pstm;
BYTE_BLOB *pstg;
} u;
} DUMMYUNIONNAME;
IUnknown *pUnkForRelease;
} userSTGMEDIUM;
typedef userSTGMEDIUM *wireSTGMEDIUM;
typedef uSTGMEDIUM STGMEDIUM;
typedef userSTGMEDIUM *wireASYNC_STGMEDIUM;
typedef STGMEDIUM ASYNC_STGMEDIUM;
typedef STGMEDIUM *LPSTGMEDIUM;
typedef struct _userFLAG_STGMEDIUM {
LONG ContextFlags;
LONG fPassOwnership;
userSTGMEDIUM Stgmed;
} userFLAG_STGMEDIUM;
typedef userFLAG_STGMEDIUM *wireFLAG_STGMEDIUM;
typedef struct _FLAG_STGMEDIUM {
LONG ContextFlags;
LONG fPassOwnership;
STGMEDIUM Stgmed;
} FLAG_STGMEDIUM;
DEFINE_GUID(IID_IAdviseSink, 0x0000010f, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IAdviseSink : public IUnknown
{
virtual void STDMETHODCALLTYPE OnDataChange(
FORMATETC *pFormatetc,
STGMEDIUM *pStgmed) = 0;
virtual void STDMETHODCALLTYPE OnViewChange(
DWORD dwAspect,
LONG lindex) = 0;
virtual void STDMETHODCALLTYPE OnRename(
IMoniker *pmk) = 0;
virtual void STDMETHODCALLTYPE OnSave(
) = 0;
virtual void STDMETHODCALLTYPE OnClose(
) = 0;
};
#else
typedef struct IAdviseSinkVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IAdviseSink* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IAdviseSink* This);
ULONG (STDMETHODCALLTYPE *Release)(
IAdviseSink* This);
/*** IAdviseSink methods ***/
void (STDMETHODCALLTYPE *OnDataChange)(
IAdviseSink* This,
FORMATETC *pFormatetc,
STGMEDIUM *pStgmed);
void (STDMETHODCALLTYPE *OnViewChange)(
IAdviseSink* This,
DWORD dwAspect,
LONG lindex);
void (STDMETHODCALLTYPE *OnRename)(
IAdviseSink* This,
IMoniker *pmk);
void (STDMETHODCALLTYPE *OnSave)(
IAdviseSink* This);
void (STDMETHODCALLTYPE *OnClose)(
IAdviseSink* This);
END_INTERFACE
} IAdviseSinkVtbl;
interface IAdviseSink {
CONST_VTBL IAdviseSinkVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IAdviseSink_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IAdviseSink_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IAdviseSink_Release(This) (This)->lpVtbl->Release(This)
/*** IAdviseSink methods ***/
#define IAdviseSink_OnDataChange(This,pFormatetc,pStgmed) (This)->lpVtbl->OnDataChange(This,pFormatetc,pStgmed)
#define IAdviseSink_OnViewChange(This,dwAspect,lindex) (This)->lpVtbl->OnViewChange(This,dwAspect,lindex)
#define IAdviseSink_OnRename(This,pmk) (This)->lpVtbl->OnRename(This,pmk)
#define IAdviseSink_OnSave(This) (This)->lpVtbl->OnSave(This)
#define IAdviseSink_OnClose(This) (This)->lpVtbl->OnClose(This)
#endif
#endif
HRESULT STDMETHODCALLTYPE IAdviseSink_RemoteOnDataChange_Proxy(
IAdviseSink* This,
FORMATETC *pFormatetc,
ASYNC_STGMEDIUM *pStgmed);
void __RPC_STUB IAdviseSink_RemoteOnDataChange_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IAdviseSink_RemoteOnViewChange_Proxy(
IAdviseSink* This,
DWORD dwAspect,
LONG lindex);
void __RPC_STUB IAdviseSink_RemoteOnViewChange_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IAdviseSink_RemoteOnRename_Proxy(
IAdviseSink* This,
IMoniker *pmk);
void __RPC_STUB IAdviseSink_RemoteOnRename_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IAdviseSink_RemoteOnSave_Proxy(
IAdviseSink* This);
void __RPC_STUB IAdviseSink_RemoteOnSave_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IAdviseSink_RemoteOnClose_Proxy(
IAdviseSink* This);
void __RPC_STUB IAdviseSink_RemoteOnClose_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void CALLBACK IAdviseSink_OnDataChange_Proxy(
IAdviseSink* This,
FORMATETC *pFormatetc,
STGMEDIUM *pStgmed);
HRESULT __RPC_STUB IAdviseSink_OnDataChange_Stub(
IAdviseSink* This,
FORMATETC *pFormatetc,
ASYNC_STGMEDIUM *pStgmed);
void CALLBACK IAdviseSink_OnViewChange_Proxy(
IAdviseSink* This,
DWORD dwAspect,
LONG lindex);
HRESULT __RPC_STUB IAdviseSink_OnViewChange_Stub(
IAdviseSink* This,
DWORD dwAspect,
LONG lindex);
void CALLBACK IAdviseSink_OnRename_Proxy(
IAdviseSink* This,
IMoniker *pmk);
HRESULT __RPC_STUB IAdviseSink_OnRename_Stub(
IAdviseSink* This,
IMoniker *pmk);
void CALLBACK IAdviseSink_OnSave_Proxy(
IAdviseSink* This);
HRESULT __RPC_STUB IAdviseSink_OnSave_Stub(
IAdviseSink* This);
void CALLBACK IAdviseSink_OnClose_Proxy(
IAdviseSink* This);
HRESULT __RPC_STUB IAdviseSink_OnClose_Stub(
IAdviseSink* This);
#endif /* __IAdviseSink_INTERFACE_DEFINED__ */
/*****************************************************************************
* IAdviseSink2 interface
*/
#ifndef __IAdviseSink2_INTERFACE_DEFINED__
#define __IAdviseSink2_INTERFACE_DEFINED__
typedef IAdviseSink2 *LPADVISESINK2;
DEFINE_GUID(IID_IAdviseSink2, 0x00000125, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IAdviseSink2 : public IAdviseSink
{
virtual void STDMETHODCALLTYPE OnLinkSrcChange(
IMoniker *pmk) = 0;
};
#else
typedef struct IAdviseSink2Vtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IAdviseSink2* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IAdviseSink2* This);
ULONG (STDMETHODCALLTYPE *Release)(
IAdviseSink2* This);
/*** IAdviseSink methods ***/
void (STDMETHODCALLTYPE *OnDataChange)(
IAdviseSink2* This,
FORMATETC *pFormatetc,
STGMEDIUM *pStgmed);
void (STDMETHODCALLTYPE *OnViewChange)(
IAdviseSink2* This,
DWORD dwAspect,
LONG lindex);
void (STDMETHODCALLTYPE *OnRename)(
IAdviseSink2* This,
IMoniker *pmk);
void (STDMETHODCALLTYPE *OnSave)(
IAdviseSink2* This);
void (STDMETHODCALLTYPE *OnClose)(
IAdviseSink2* This);
/*** IAdviseSink2 methods ***/
void (STDMETHODCALLTYPE *OnLinkSrcChange)(
IAdviseSink2* This,
IMoniker *pmk);
END_INTERFACE
} IAdviseSink2Vtbl;
interface IAdviseSink2 {
CONST_VTBL IAdviseSink2Vtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IAdviseSink2_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IAdviseSink2_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IAdviseSink2_Release(This) (This)->lpVtbl->Release(This)
/*** IAdviseSink methods ***/
#define IAdviseSink2_OnDataChange(This,pFormatetc,pStgmed) (This)->lpVtbl->OnDataChange(This,pFormatetc,pStgmed)
#define IAdviseSink2_OnViewChange(This,dwAspect,lindex) (This)->lpVtbl->OnViewChange(This,dwAspect,lindex)
#define IAdviseSink2_OnRename(This,pmk) (This)->lpVtbl->OnRename(This,pmk)
#define IAdviseSink2_OnSave(This) (This)->lpVtbl->OnSave(This)
#define IAdviseSink2_OnClose(This) (This)->lpVtbl->OnClose(This)
/*** IAdviseSink2 methods ***/
#define IAdviseSink2_OnLinkSrcChange(This,pmk) (This)->lpVtbl->OnLinkSrcChange(This,pmk)
#endif
#endif
HRESULT STDMETHODCALLTYPE IAdviseSink2_RemoteOnLinkSrcChange_Proxy(
IAdviseSink2* This,
IMoniker *pmk);
void __RPC_STUB IAdviseSink2_RemoteOnLinkSrcChange_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void CALLBACK IAdviseSink2_OnLinkSrcChange_Proxy(
IAdviseSink2* This,
IMoniker *pmk);
HRESULT __RPC_STUB IAdviseSink2_OnLinkSrcChange_Stub(
IAdviseSink2* This,
IMoniker *pmk);
#endif /* __IAdviseSink2_INTERFACE_DEFINED__ */
/*****************************************************************************
* IDataObject interface
*/
#ifndef __IDataObject_INTERFACE_DEFINED__
#define __IDataObject_INTERFACE_DEFINED__
typedef IDataObject *LPDATAOBJECT;
typedef enum tagDATADIR {
DATADIR_GET = 1,
DATADIR_SET = 2
} DATADIR;
DEFINE_GUID(IID_IDataObject, 0x0000010e, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IDataObject : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE GetData(
FORMATETC *pformatetcIn,
STGMEDIUM *pmedium) = 0;
virtual HRESULT STDMETHODCALLTYPE GetDataHere(
FORMATETC *pformatetc,
STGMEDIUM *pmedium) = 0;
virtual HRESULT STDMETHODCALLTYPE QueryGetData(
FORMATETC *pformatetc) = 0;
virtual HRESULT STDMETHODCALLTYPE GetCanonicalFormatEtc(
FORMATETC *pformatectIn,
FORMATETC *pformatetcOut) = 0;
virtual HRESULT STDMETHODCALLTYPE SetData(
FORMATETC *pformatetc,
STGMEDIUM *pmedium,
BOOL fRelease) = 0;
virtual HRESULT STDMETHODCALLTYPE EnumFormatEtc(
DWORD dwDirection,
IEnumFORMATETC **ppenumFormatEtc) = 0;
virtual HRESULT STDMETHODCALLTYPE DAdvise(
FORMATETC *pformatetc,
DWORD advf,
IAdviseSink *pAdvSink,
DWORD *pdwConnection) = 0;
virtual HRESULT STDMETHODCALLTYPE DUnadvise(
DWORD dwConnection) = 0;
virtual HRESULT STDMETHODCALLTYPE EnumDAdvise(
IEnumSTATDATA **ppenumAdvise) = 0;
};
#else
typedef struct IDataObjectVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IDataObject* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IDataObject* This);
ULONG (STDMETHODCALLTYPE *Release)(
IDataObject* This);
/*** IDataObject methods ***/
HRESULT (STDMETHODCALLTYPE *GetData)(
IDataObject* This,
FORMATETC *pformatetcIn,
STGMEDIUM *pmedium);
HRESULT (STDMETHODCALLTYPE *GetDataHere)(
IDataObject* This,
FORMATETC *pformatetc,
STGMEDIUM *pmedium);
HRESULT (STDMETHODCALLTYPE *QueryGetData)(
IDataObject* This,
FORMATETC *pformatetc);
HRESULT (STDMETHODCALLTYPE *GetCanonicalFormatEtc)(
IDataObject* This,
FORMATETC *pformatectIn,
FORMATETC *pformatetcOut);
HRESULT (STDMETHODCALLTYPE *SetData)(
IDataObject* This,
FORMATETC *pformatetc,
STGMEDIUM *pmedium,
BOOL fRelease);
HRESULT (STDMETHODCALLTYPE *EnumFormatEtc)(
IDataObject* This,
DWORD dwDirection,
IEnumFORMATETC **ppenumFormatEtc);
HRESULT (STDMETHODCALLTYPE *DAdvise)(
IDataObject* This,
FORMATETC *pformatetc,
DWORD advf,
IAdviseSink *pAdvSink,
DWORD *pdwConnection);
HRESULT (STDMETHODCALLTYPE *DUnadvise)(
IDataObject* This,
DWORD dwConnection);
HRESULT (STDMETHODCALLTYPE *EnumDAdvise)(
IDataObject* This,
IEnumSTATDATA **ppenumAdvise);
END_INTERFACE
} IDataObjectVtbl;
interface IDataObject {
CONST_VTBL IDataObjectVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IDataObject_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IDataObject_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IDataObject_Release(This) (This)->lpVtbl->Release(This)
/*** IDataObject methods ***/
#define IDataObject_GetData(This,pformatetcIn,pmedium) (This)->lpVtbl->GetData(This,pformatetcIn,pmedium)
#define IDataObject_GetDataHere(This,pformatetc,pmedium) (This)->lpVtbl->GetDataHere(This,pformatetc,pmedium)
#define IDataObject_QueryGetData(This,pformatetc) (This)->lpVtbl->QueryGetData(This,pformatetc)
#define IDataObject_GetCanonicalFormatEtc(This,pformatectIn,pformatetcOut) (This)->lpVtbl->GetCanonicalFormatEtc(This,pformatectIn,pformatetcOut)
#define IDataObject_SetData(This,pformatetc,pmedium,fRelease) (This)->lpVtbl->SetData(This,pformatetc,pmedium,fRelease)
#define IDataObject_EnumFormatEtc(This,dwDirection,ppenumFormatEtc) (This)->lpVtbl->EnumFormatEtc(This,dwDirection,ppenumFormatEtc)
#define IDataObject_DAdvise(This,pformatetc,advf,pAdvSink,pdwConnection) (This)->lpVtbl->DAdvise(This,pformatetc,advf,pAdvSink,pdwConnection)
#define IDataObject_DUnadvise(This,dwConnection) (This)->lpVtbl->DUnadvise(This,dwConnection)
#define IDataObject_EnumDAdvise(This,ppenumAdvise) (This)->lpVtbl->EnumDAdvise(This,ppenumAdvise)
#endif
#endif
HRESULT STDMETHODCALLTYPE IDataObject_RemoteGetData_Proxy(
IDataObject* This,
FORMATETC *pformatetcIn,
STGMEDIUM *pRemoteMedium);
void __RPC_STUB IDataObject_RemoteGetData_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IDataObject_RemoteGetDataHere_Proxy(
IDataObject* This,
FORMATETC *pformatetc,
STGMEDIUM *pRemoteMedium);
void __RPC_STUB IDataObject_RemoteGetDataHere_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IDataObject_QueryGetData_Proxy(
IDataObject* This,
FORMATETC *pformatetc);
void __RPC_STUB IDataObject_QueryGetData_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IDataObject_GetCanonicalFormatEtc_Proxy(
IDataObject* This,
FORMATETC *pformatectIn,
FORMATETC *pformatetcOut);
void __RPC_STUB IDataObject_GetCanonicalFormatEtc_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IDataObject_RemoteSetData_Proxy(
IDataObject* This,
FORMATETC *pformatetc,
FLAG_STGMEDIUM *pmedium,
BOOL fRelease);
void __RPC_STUB IDataObject_RemoteSetData_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IDataObject_EnumFormatEtc_Proxy(
IDataObject* This,
DWORD dwDirection,
IEnumFORMATETC **ppenumFormatEtc);
void __RPC_STUB IDataObject_EnumFormatEtc_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IDataObject_DAdvise_Proxy(
IDataObject* This,
FORMATETC *pformatetc,
DWORD advf,
IAdviseSink *pAdvSink,
DWORD *pdwConnection);
void __RPC_STUB IDataObject_DAdvise_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IDataObject_DUnadvise_Proxy(
IDataObject* This,
DWORD dwConnection);
void __RPC_STUB IDataObject_DUnadvise_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IDataObject_EnumDAdvise_Proxy(
IDataObject* This,
IEnumSTATDATA **ppenumAdvise);
void __RPC_STUB IDataObject_EnumDAdvise_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT CALLBACK IDataObject_GetData_Proxy(
IDataObject* This,
FORMATETC *pformatetcIn,
STGMEDIUM *pmedium);
HRESULT __RPC_STUB IDataObject_GetData_Stub(
IDataObject* This,
FORMATETC *pformatetcIn,
STGMEDIUM *pRemoteMedium);
HRESULT CALLBACK IDataObject_GetDataHere_Proxy(
IDataObject* This,
FORMATETC *pformatetc,
STGMEDIUM *pmedium);
HRESULT __RPC_STUB IDataObject_GetDataHere_Stub(
IDataObject* This,
FORMATETC *pformatetc,
STGMEDIUM *pRemoteMedium);
HRESULT CALLBACK IDataObject_SetData_Proxy(
IDataObject* This,
FORMATETC *pformatetc,
STGMEDIUM *pmedium,
BOOL fRelease);
HRESULT __RPC_STUB IDataObject_SetData_Stub(
IDataObject* This,
FORMATETC *pformatetc,
FLAG_STGMEDIUM *pmedium,
BOOL fRelease);
#endif /* __IDataObject_INTERFACE_DEFINED__ */
/*****************************************************************************
* IDataAdviseHolder interface
*/
#ifndef __IDataAdviseHolder_INTERFACE_DEFINED__
#define __IDataAdviseHolder_INTERFACE_DEFINED__
typedef IDataAdviseHolder *LPDATAADVISEHOLDER;
DEFINE_GUID(IID_IDataAdviseHolder, 0x00000110, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IDataAdviseHolder : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Advise(
IDataObject *pDataObject,
FORMATETC *pFetc,
DWORD advf,
IAdviseSink *pAdvise,
DWORD *pdwConnection) = 0;
virtual HRESULT STDMETHODCALLTYPE Unadvise(
DWORD dwConnection) = 0;
virtual HRESULT STDMETHODCALLTYPE EnumAdvise(
IEnumSTATDATA **ppenumAdvise) = 0;
virtual HRESULT STDMETHODCALLTYPE SendOnDataChange(
IDataObject *pDataObject,
DWORD dwReserved,
DWORD advf) = 0;
};
#else
typedef struct IDataAdviseHolderVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IDataAdviseHolder* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IDataAdviseHolder* This);
ULONG (STDMETHODCALLTYPE *Release)(
IDataAdviseHolder* This);
/*** IDataAdviseHolder methods ***/
HRESULT (STDMETHODCALLTYPE *Advise)(
IDataAdviseHolder* This,
IDataObject *pDataObject,
FORMATETC *pFetc,
DWORD advf,
IAdviseSink *pAdvise,
DWORD *pdwConnection);
HRESULT (STDMETHODCALLTYPE *Unadvise)(
IDataAdviseHolder* This,
DWORD dwConnection);
HRESULT (STDMETHODCALLTYPE *EnumAdvise)(
IDataAdviseHolder* This,
IEnumSTATDATA **ppenumAdvise);
HRESULT (STDMETHODCALLTYPE *SendOnDataChange)(
IDataAdviseHolder* This,
IDataObject *pDataObject,
DWORD dwReserved,
DWORD advf);
END_INTERFACE
} IDataAdviseHolderVtbl;
interface IDataAdviseHolder {
CONST_VTBL IDataAdviseHolderVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IDataAdviseHolder_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IDataAdviseHolder_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IDataAdviseHolder_Release(This) (This)->lpVtbl->Release(This)
/*** IDataAdviseHolder methods ***/
#define IDataAdviseHolder_Advise(This,pDataObject,pFetc,advf,pAdvise,pdwConnection) (This)->lpVtbl->Advise(This,pDataObject,pFetc,advf,pAdvise,pdwConnection)
#define IDataAdviseHolder_Unadvise(This,dwConnection) (This)->lpVtbl->Unadvise(This,dwConnection)
#define IDataAdviseHolder_EnumAdvise(This,ppenumAdvise) (This)->lpVtbl->EnumAdvise(This,ppenumAdvise)
#define IDataAdviseHolder_SendOnDataChange(This,pDataObject,dwReserved,advf) (This)->lpVtbl->SendOnDataChange(This,pDataObject,dwReserved,advf)
#endif
#endif
HRESULT STDMETHODCALLTYPE IDataAdviseHolder_Advise_Proxy(
IDataAdviseHolder* This,
IDataObject *pDataObject,
FORMATETC *pFetc,
DWORD advf,
IAdviseSink *pAdvise,
DWORD *pdwConnection);
void __RPC_STUB IDataAdviseHolder_Advise_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IDataAdviseHolder_Unadvise_Proxy(
IDataAdviseHolder* This,
DWORD dwConnection);
void __RPC_STUB IDataAdviseHolder_Unadvise_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IDataAdviseHolder_EnumAdvise_Proxy(
IDataAdviseHolder* This,
IEnumSTATDATA **ppenumAdvise);
void __RPC_STUB IDataAdviseHolder_EnumAdvise_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IDataAdviseHolder_SendOnDataChange_Proxy(
IDataAdviseHolder* This,
IDataObject *pDataObject,
DWORD dwReserved,
DWORD advf);
void __RPC_STUB IDataAdviseHolder_SendOnDataChange_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IDataAdviseHolder_INTERFACE_DEFINED__ */
/*****************************************************************************
* IMessageFilter interface
*/
#ifndef __IMessageFilter_INTERFACE_DEFINED__
#define __IMessageFilter_INTERFACE_DEFINED__
typedef IMessageFilter *LPMESSAGEFILTER;
typedef enum tagCALLTYPE {
CALLTYPE_TOPLEVEL = 1,
CALLTYPE_NESTED = 2,
CALLTYPE_ASYNC = 3,
CALLTYPE_TOPLEVEL_CALLPENDING = 4,
CALLTYPE_ASYNC_CALLPENDING = 5
} CALLTYPE;
typedef enum tagSERVERCALL {
SERVERCALL_ISHANDLED = 0,
SERVERCALL_REJECTED = 1,
SERVERCALL_RETRYLATER = 2
} SERVERCALL;
typedef enum tagPENDINGTYPE {
PENDINGTYPE_TOPLEVEL = 1,
PENDINGTYPE_NESTED = 2
} PENDINGTYPE;
typedef enum tagPENDINGMSG {
PENDINGMSG_CANCELCALL = 0,
PENDINGMSG_WAITNOPROCESS = 1,
PENDINGMSG_WAITDEFPROCESS = 2
} PENDINGMSG;
typedef struct tagINTERFACEINFO {
IUnknown *pUnk;
IID iid;
WORD wMethod;
} INTERFACEINFO;
typedef struct tagINTERFACEINFO *LPINTERFACEINFO;
DEFINE_GUID(IID_IMessageFilter, 0x00000016, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IMessageFilter : public IUnknown
{
virtual DWORD STDMETHODCALLTYPE HandleInComingCall(
DWORD dwCallType,
HTASK htaskCaller,
DWORD dwTickCount,
LPINTERFACEINFO lpInterfaceInfo) = 0;
virtual DWORD STDMETHODCALLTYPE RetryRejectedCall(
HTASK htaskCallee,
DWORD dwTickCount,
DWORD dwRejectType) = 0;
virtual DWORD STDMETHODCALLTYPE MessagePending(
HTASK htaskCallee,
DWORD dwTickCount,
DWORD dwPendingType) = 0;
};
#else
typedef struct IMessageFilterVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IMessageFilter* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IMessageFilter* This);
ULONG (STDMETHODCALLTYPE *Release)(
IMessageFilter* This);
/*** IMessageFilter methods ***/
DWORD (STDMETHODCALLTYPE *HandleInComingCall)(
IMessageFilter* This,
DWORD dwCallType,
HTASK htaskCaller,
DWORD dwTickCount,
LPINTERFACEINFO lpInterfaceInfo);
DWORD (STDMETHODCALLTYPE *RetryRejectedCall)(
IMessageFilter* This,
HTASK htaskCallee,
DWORD dwTickCount,
DWORD dwRejectType);
DWORD (STDMETHODCALLTYPE *MessagePending)(
IMessageFilter* This,
HTASK htaskCallee,
DWORD dwTickCount,
DWORD dwPendingType);
END_INTERFACE
} IMessageFilterVtbl;
interface IMessageFilter {
CONST_VTBL IMessageFilterVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IMessageFilter_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IMessageFilter_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IMessageFilter_Release(This) (This)->lpVtbl->Release(This)
/*** IMessageFilter methods ***/
#define IMessageFilter_HandleInComingCall(This,dwCallType,htaskCaller,dwTickCount,lpInterfaceInfo) (This)->lpVtbl->HandleInComingCall(This,dwCallType,htaskCaller,dwTickCount,lpInterfaceInfo)
#define IMessageFilter_RetryRejectedCall(This,htaskCallee,dwTickCount,dwRejectType) (This)->lpVtbl->RetryRejectedCall(This,htaskCallee,dwTickCount,dwRejectType)
#define IMessageFilter_MessagePending(This,htaskCallee,dwTickCount,dwPendingType) (This)->lpVtbl->MessagePending(This,htaskCallee,dwTickCount,dwPendingType)
#endif
#endif
DWORD STDMETHODCALLTYPE IMessageFilter_HandleInComingCall_Proxy(
IMessageFilter* This,
DWORD dwCallType,
HTASK htaskCaller,
DWORD dwTickCount,
LPINTERFACEINFO lpInterfaceInfo);
void __RPC_STUB IMessageFilter_HandleInComingCall_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
DWORD STDMETHODCALLTYPE IMessageFilter_RetryRejectedCall_Proxy(
IMessageFilter* This,
HTASK htaskCallee,
DWORD dwTickCount,
DWORD dwRejectType);
void __RPC_STUB IMessageFilter_RetryRejectedCall_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
DWORD STDMETHODCALLTYPE IMessageFilter_MessagePending_Proxy(
IMessageFilter* This,
HTASK htaskCallee,
DWORD dwTickCount,
DWORD dwPendingType);
void __RPC_STUB IMessageFilter_MessagePending_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IMessageFilter_INTERFACE_DEFINED__ */
/*****************************************************************************
* IRpcChannelBuffer interface
*/
#ifndef __IRpcChannelBuffer_INTERFACE_DEFINED__
#define __IRpcChannelBuffer_INTERFACE_DEFINED__
typedef IRpcChannelBuffer *LPRPCCHANNELBUFFER;
typedef ULONG RPCOLEDATAREP;
typedef struct tagRPCOLEMESSAGE {
void *reserved1;
RPCOLEDATAREP dataRepresentation;
void *Buffer;
ULONG cbBuffer;
ULONG iMethod;
void * reserved2[5];
ULONG rpcFlags;
} RPCOLEMESSAGE;
typedef RPCOLEMESSAGE *PRPCOLEMESSAGE;
DEFINE_GUID(IID_IRpcChannelBuffer, 0xd5f56b60, 0x593b, 0x101a, 0xb5,0x69, 0x08,0x00,0x2b,0x2d,0xbf,0x7a);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IRpcChannelBuffer : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE GetBuffer(
RPCOLEMESSAGE *pMessage,
REFIID riid) = 0;
virtual HRESULT STDMETHODCALLTYPE SendReceive(
RPCOLEMESSAGE *pMessage,
ULONG *pStatus) = 0;
virtual HRESULT STDMETHODCALLTYPE FreeBuffer(
RPCOLEMESSAGE *pMessage) = 0;
virtual HRESULT STDMETHODCALLTYPE GetDestCtx(
DWORD *pdwDestContext,
void **ppvDestContext) = 0;
virtual HRESULT STDMETHODCALLTYPE IsConnected(
) = 0;
};
#else
typedef struct IRpcChannelBufferVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IRpcChannelBuffer* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IRpcChannelBuffer* This);
ULONG (STDMETHODCALLTYPE *Release)(
IRpcChannelBuffer* This);
/*** IRpcChannelBuffer methods ***/
HRESULT (STDMETHODCALLTYPE *GetBuffer)(
IRpcChannelBuffer* This,
RPCOLEMESSAGE *pMessage,
REFIID riid);
HRESULT (STDMETHODCALLTYPE *SendReceive)(
IRpcChannelBuffer* This,
RPCOLEMESSAGE *pMessage,
ULONG *pStatus);
HRESULT (STDMETHODCALLTYPE *FreeBuffer)(
IRpcChannelBuffer* This,
RPCOLEMESSAGE *pMessage);
HRESULT (STDMETHODCALLTYPE *GetDestCtx)(
IRpcChannelBuffer* This,
DWORD *pdwDestContext,
void **ppvDestContext);
HRESULT (STDMETHODCALLTYPE *IsConnected)(
IRpcChannelBuffer* This);
END_INTERFACE
} IRpcChannelBufferVtbl;
interface IRpcChannelBuffer {
CONST_VTBL IRpcChannelBufferVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IRpcChannelBuffer_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IRpcChannelBuffer_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IRpcChannelBuffer_Release(This) (This)->lpVtbl->Release(This)
/*** IRpcChannelBuffer methods ***/
#define IRpcChannelBuffer_GetBuffer(This,pMessage,riid) (This)->lpVtbl->GetBuffer(This,pMessage,riid)
#define IRpcChannelBuffer_SendReceive(This,pMessage,pStatus) (This)->lpVtbl->SendReceive(This,pMessage,pStatus)
#define IRpcChannelBuffer_FreeBuffer(This,pMessage) (This)->lpVtbl->FreeBuffer(This,pMessage)
#define IRpcChannelBuffer_GetDestCtx(This,pdwDestContext,ppvDestContext) (This)->lpVtbl->GetDestCtx(This,pdwDestContext,ppvDestContext)
#define IRpcChannelBuffer_IsConnected(This) (This)->lpVtbl->IsConnected(This)
#endif
#endif
HRESULT STDMETHODCALLTYPE IRpcChannelBuffer_GetBuffer_Proxy(
IRpcChannelBuffer* This,
RPCOLEMESSAGE *pMessage,
REFIID riid);
void __RPC_STUB IRpcChannelBuffer_GetBuffer_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcChannelBuffer_SendReceive_Proxy(
IRpcChannelBuffer* This,
RPCOLEMESSAGE *pMessage,
ULONG *pStatus);
void __RPC_STUB IRpcChannelBuffer_SendReceive_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcChannelBuffer_FreeBuffer_Proxy(
IRpcChannelBuffer* This,
RPCOLEMESSAGE *pMessage);
void __RPC_STUB IRpcChannelBuffer_FreeBuffer_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcChannelBuffer_GetDestCtx_Proxy(
IRpcChannelBuffer* This,
DWORD *pdwDestContext,
void **ppvDestContext);
void __RPC_STUB IRpcChannelBuffer_GetDestCtx_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcChannelBuffer_IsConnected_Proxy(
IRpcChannelBuffer* This);
void __RPC_STUB IRpcChannelBuffer_IsConnected_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IRpcChannelBuffer_INTERFACE_DEFINED__ */
/*****************************************************************************
* IRpcChannelBuffer2 interface
*/
#ifndef __IRpcChannelBuffer2_INTERFACE_DEFINED__
#define __IRpcChannelBuffer2_INTERFACE_DEFINED__
typedef IRpcChannelBuffer2 *LPRPCCHANNELBUFFER2;
DEFINE_GUID(IID_IRpcChannelBuffer2, 0x594f31d0, 0x7f19, 0x11d0, 0xb1,0x94, 0x00,0xa0,0xc9,0x0d,0xc8,0xbf);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IRpcChannelBuffer2 : public IRpcChannelBuffer
{
virtual HRESULT STDMETHODCALLTYPE GetProtocolVersion(
DWORD *pdwVersion) = 0;
};
#else
typedef struct IRpcChannelBuffer2Vtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IRpcChannelBuffer2* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IRpcChannelBuffer2* This);
ULONG (STDMETHODCALLTYPE *Release)(
IRpcChannelBuffer2* This);
/*** IRpcChannelBuffer methods ***/
HRESULT (STDMETHODCALLTYPE *GetBuffer)(
IRpcChannelBuffer2* This,
RPCOLEMESSAGE *pMessage,
REFIID riid);
HRESULT (STDMETHODCALLTYPE *SendReceive)(
IRpcChannelBuffer2* This,
RPCOLEMESSAGE *pMessage,
ULONG *pStatus);
HRESULT (STDMETHODCALLTYPE *FreeBuffer)(
IRpcChannelBuffer2* This,
RPCOLEMESSAGE *pMessage);
HRESULT (STDMETHODCALLTYPE *GetDestCtx)(
IRpcChannelBuffer2* This,
DWORD *pdwDestContext,
void **ppvDestContext);
HRESULT (STDMETHODCALLTYPE *IsConnected)(
IRpcChannelBuffer2* This);
/*** IRpcChannelBuffer2 methods ***/
HRESULT (STDMETHODCALLTYPE *GetProtocolVersion)(
IRpcChannelBuffer2* This,
DWORD *pdwVersion);
END_INTERFACE
} IRpcChannelBuffer2Vtbl;
interface IRpcChannelBuffer2 {
CONST_VTBL IRpcChannelBuffer2Vtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IRpcChannelBuffer2_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IRpcChannelBuffer2_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IRpcChannelBuffer2_Release(This) (This)->lpVtbl->Release(This)
/*** IRpcChannelBuffer methods ***/
#define IRpcChannelBuffer2_GetBuffer(This,pMessage,riid) (This)->lpVtbl->GetBuffer(This,pMessage,riid)
#define IRpcChannelBuffer2_SendReceive(This,pMessage,pStatus) (This)->lpVtbl->SendReceive(This,pMessage,pStatus)
#define IRpcChannelBuffer2_FreeBuffer(This,pMessage) (This)->lpVtbl->FreeBuffer(This,pMessage)
#define IRpcChannelBuffer2_GetDestCtx(This,pdwDestContext,ppvDestContext) (This)->lpVtbl->GetDestCtx(This,pdwDestContext,ppvDestContext)
#define IRpcChannelBuffer2_IsConnected(This) (This)->lpVtbl->IsConnected(This)
/*** IRpcChannelBuffer2 methods ***/
#define IRpcChannelBuffer2_GetProtocolVersion(This,pdwVersion) (This)->lpVtbl->GetProtocolVersion(This,pdwVersion)
#endif
#endif
HRESULT STDMETHODCALLTYPE IRpcChannelBuffer2_GetProtocolVersion_Proxy(
IRpcChannelBuffer2* This,
DWORD *pdwVersion);
void __RPC_STUB IRpcChannelBuffer2_GetProtocolVersion_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IRpcChannelBuffer2_INTERFACE_DEFINED__ */
/*****************************************************************************
* IRpcChannelBuffer3 interface
*/
#ifndef __IRpcChannelBuffer3_INTERFACE_DEFINED__
#define __IRpcChannelBuffer3_INTERFACE_DEFINED__
typedef IRpcChannelBuffer3 *LPRPCCHANNELBUFFER3;
DEFINE_GUID(IID_IRpcChannelBuffer3, 0x25b15600, 0x0115, 0x11d0, 0xbf,0x0d, 0x00,0xaa,0x00,0xb8,0xdf,0xd2);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IRpcChannelBuffer3 : public IRpcChannelBuffer2
{
virtual HRESULT STDMETHODCALLTYPE Send(
RPCOLEMESSAGE *pMsg,
ULONG *pulStatus) = 0;
virtual HRESULT STDMETHODCALLTYPE Receive(
RPCOLEMESSAGE *pMsg,
ULONG ulSize,
ULONG *pulStatus) = 0;
virtual HRESULT STDMETHODCALLTYPE Cancel(
RPCOLEMESSAGE *pMsg) = 0;
virtual HRESULT STDMETHODCALLTYPE GetCallContext(
RPCOLEMESSAGE *pMsg,
REFIID riid,
void **pInterface) = 0;
virtual HRESULT STDMETHODCALLTYPE GetDestCtxEx(
RPCOLEMESSAGE *pMsg,
DWORD *pdwDestContext,
void **ppvDestContext) = 0;
virtual HRESULT STDMETHODCALLTYPE GetState(
RPCOLEMESSAGE *pMsg,
DWORD *pState) = 0;
virtual HRESULT STDMETHODCALLTYPE RegisterAsync(
RPCOLEMESSAGE *pMsg,
IAsyncManager *pAsyncMgr) = 0;
};
#else
typedef struct IRpcChannelBuffer3Vtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IRpcChannelBuffer3* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IRpcChannelBuffer3* This);
ULONG (STDMETHODCALLTYPE *Release)(
IRpcChannelBuffer3* This);
/*** IRpcChannelBuffer methods ***/
HRESULT (STDMETHODCALLTYPE *GetBuffer)(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMessage,
REFIID riid);
HRESULT (STDMETHODCALLTYPE *SendReceive)(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMessage,
ULONG *pStatus);
HRESULT (STDMETHODCALLTYPE *FreeBuffer)(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMessage);
HRESULT (STDMETHODCALLTYPE *GetDestCtx)(
IRpcChannelBuffer3* This,
DWORD *pdwDestContext,
void **ppvDestContext);
HRESULT (STDMETHODCALLTYPE *IsConnected)(
IRpcChannelBuffer3* This);
/*** IRpcChannelBuffer2 methods ***/
HRESULT (STDMETHODCALLTYPE *GetProtocolVersion)(
IRpcChannelBuffer3* This,
DWORD *pdwVersion);
/*** IRpcChannelBuffer3 methods ***/
HRESULT (STDMETHODCALLTYPE *Send)(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg,
ULONG *pulStatus);
HRESULT (STDMETHODCALLTYPE *Receive)(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg,
ULONG ulSize,
ULONG *pulStatus);
HRESULT (STDMETHODCALLTYPE *Cancel)(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg);
HRESULT (STDMETHODCALLTYPE *GetCallContext)(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg,
REFIID riid,
void **pInterface);
HRESULT (STDMETHODCALLTYPE *GetDestCtxEx)(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg,
DWORD *pdwDestContext,
void **ppvDestContext);
HRESULT (STDMETHODCALLTYPE *GetState)(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg,
DWORD *pState);
HRESULT (STDMETHODCALLTYPE *RegisterAsync)(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg,
IAsyncManager *pAsyncMgr);
END_INTERFACE
} IRpcChannelBuffer3Vtbl;
interface IRpcChannelBuffer3 {
CONST_VTBL IRpcChannelBuffer3Vtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IRpcChannelBuffer3_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IRpcChannelBuffer3_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IRpcChannelBuffer3_Release(This) (This)->lpVtbl->Release(This)
/*** IRpcChannelBuffer methods ***/
#define IRpcChannelBuffer3_GetBuffer(This,pMessage,riid) (This)->lpVtbl->GetBuffer(This,pMessage,riid)
#define IRpcChannelBuffer3_SendReceive(This,pMessage,pStatus) (This)->lpVtbl->SendReceive(This,pMessage,pStatus)
#define IRpcChannelBuffer3_FreeBuffer(This,pMessage) (This)->lpVtbl->FreeBuffer(This,pMessage)
#define IRpcChannelBuffer3_GetDestCtx(This,pdwDestContext,ppvDestContext) (This)->lpVtbl->GetDestCtx(This,pdwDestContext,ppvDestContext)
#define IRpcChannelBuffer3_IsConnected(This) (This)->lpVtbl->IsConnected(This)
/*** IRpcChannelBuffer2 methods ***/
#define IRpcChannelBuffer3_GetProtocolVersion(This,pdwVersion) (This)->lpVtbl->GetProtocolVersion(This,pdwVersion)
/*** IRpcChannelBuffer3 methods ***/
#define IRpcChannelBuffer3_Send(This,pMsg,pulStatus) (This)->lpVtbl->Send(This,pMsg,pulStatus)
#define IRpcChannelBuffer3_Receive(This,pMsg,ulSize,pulStatus) (This)->lpVtbl->Receive(This,pMsg,ulSize,pulStatus)
#define IRpcChannelBuffer3_Cancel(This,pMsg) (This)->lpVtbl->Cancel(This,pMsg)
#define IRpcChannelBuffer3_GetCallContext(This,pMsg,riid,pInterface) (This)->lpVtbl->GetCallContext(This,pMsg,riid,pInterface)
#define IRpcChannelBuffer3_GetDestCtxEx(This,pMsg,pdwDestContext,ppvDestContext) (This)->lpVtbl->GetDestCtxEx(This,pMsg,pdwDestContext,ppvDestContext)
#define IRpcChannelBuffer3_GetState(This,pMsg,pState) (This)->lpVtbl->GetState(This,pMsg,pState)
#define IRpcChannelBuffer3_RegisterAsync(This,pMsg,pAsyncMgr) (This)->lpVtbl->RegisterAsync(This,pMsg,pAsyncMgr)
#endif
#endif
HRESULT STDMETHODCALLTYPE IRpcChannelBuffer3_Send_Proxy(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg,
ULONG *pulStatus);
void __RPC_STUB IRpcChannelBuffer3_Send_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcChannelBuffer3_Receive_Proxy(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg,
ULONG ulSize,
ULONG *pulStatus);
void __RPC_STUB IRpcChannelBuffer3_Receive_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcChannelBuffer3_Cancel_Proxy(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg);
void __RPC_STUB IRpcChannelBuffer3_Cancel_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcChannelBuffer3_GetCallContext_Proxy(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg,
REFIID riid,
void **pInterface);
void __RPC_STUB IRpcChannelBuffer3_GetCallContext_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcChannelBuffer3_GetDestCtxEx_Proxy(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg,
DWORD *pdwDestContext,
void **ppvDestContext);
void __RPC_STUB IRpcChannelBuffer3_GetDestCtxEx_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcChannelBuffer3_GetState_Proxy(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg,
DWORD *pState);
void __RPC_STUB IRpcChannelBuffer3_GetState_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcChannelBuffer3_RegisterAsync_Proxy(
IRpcChannelBuffer3* This,
RPCOLEMESSAGE *pMsg,
IAsyncManager *pAsyncMgr);
void __RPC_STUB IRpcChannelBuffer3_RegisterAsync_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IRpcChannelBuffer3_INTERFACE_DEFINED__ */
/*****************************************************************************
* IAsyncRpcChannelBuffer interface
*/
#ifndef __IAsyncRpcChannelBuffer_INTERFACE_DEFINED__
#define __IAsyncRpcChannelBuffer_INTERFACE_DEFINED__
DEFINE_GUID(IID_IAsyncRpcChannelBuffer, 0xa5029fb6, 0x3c34, 0x11d1, 0x9c,0x99, 0x00,0xc0,0x4f,0xb9,0x98,0xaa);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IAsyncRpcChannelBuffer : public IRpcChannelBuffer2
{
virtual HRESULT STDMETHODCALLTYPE Send(
RPCOLEMESSAGE *pMsg,
ISynchronize *pSync,
ULONG *pulStatus) = 0;
virtual HRESULT STDMETHODCALLTYPE Receive(
RPCOLEMESSAGE *pMsg,
ULONG *pulStatus) = 0;
virtual HRESULT STDMETHODCALLTYPE GetDestCtxEx(
RPCOLEMESSAGE *pMsg,
DWORD *pdwDestContext,
void **ppvDestContext) = 0;
};
#else
typedef struct IAsyncRpcChannelBufferVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IAsyncRpcChannelBuffer* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IAsyncRpcChannelBuffer* This);
ULONG (STDMETHODCALLTYPE *Release)(
IAsyncRpcChannelBuffer* This);
/*** IRpcChannelBuffer methods ***/
HRESULT (STDMETHODCALLTYPE *GetBuffer)(
IAsyncRpcChannelBuffer* This,
RPCOLEMESSAGE *pMessage,
REFIID riid);
HRESULT (STDMETHODCALLTYPE *SendReceive)(
IAsyncRpcChannelBuffer* This,
RPCOLEMESSAGE *pMessage,
ULONG *pStatus);
HRESULT (STDMETHODCALLTYPE *FreeBuffer)(
IAsyncRpcChannelBuffer* This,
RPCOLEMESSAGE *pMessage);
HRESULT (STDMETHODCALLTYPE *GetDestCtx)(
IAsyncRpcChannelBuffer* This,
DWORD *pdwDestContext,
void **ppvDestContext);
HRESULT (STDMETHODCALLTYPE *IsConnected)(
IAsyncRpcChannelBuffer* This);
/*** IRpcChannelBuffer2 methods ***/
HRESULT (STDMETHODCALLTYPE *GetProtocolVersion)(
IAsyncRpcChannelBuffer* This,
DWORD *pdwVersion);
/*** IAsyncRpcChannelBuffer methods ***/
HRESULT (STDMETHODCALLTYPE *Send)(
IAsyncRpcChannelBuffer* This,
RPCOLEMESSAGE *pMsg,
ISynchronize *pSync,
ULONG *pulStatus);
HRESULT (STDMETHODCALLTYPE *Receive)(
IAsyncRpcChannelBuffer* This,
RPCOLEMESSAGE *pMsg,
ULONG *pulStatus);
HRESULT (STDMETHODCALLTYPE *GetDestCtxEx)(
IAsyncRpcChannelBuffer* This,
RPCOLEMESSAGE *pMsg,
DWORD *pdwDestContext,
void **ppvDestContext);
END_INTERFACE
} IAsyncRpcChannelBufferVtbl;
interface IAsyncRpcChannelBuffer {
CONST_VTBL IAsyncRpcChannelBufferVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IAsyncRpcChannelBuffer_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IAsyncRpcChannelBuffer_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IAsyncRpcChannelBuffer_Release(This) (This)->lpVtbl->Release(This)
/*** IRpcChannelBuffer methods ***/
#define IAsyncRpcChannelBuffer_GetBuffer(This,pMessage,riid) (This)->lpVtbl->GetBuffer(This,pMessage,riid)
#define IAsyncRpcChannelBuffer_SendReceive(This,pMessage,pStatus) (This)->lpVtbl->SendReceive(This,pMessage,pStatus)
#define IAsyncRpcChannelBuffer_FreeBuffer(This,pMessage) (This)->lpVtbl->FreeBuffer(This,pMessage)
#define IAsyncRpcChannelBuffer_GetDestCtx(This,pdwDestContext,ppvDestContext) (This)->lpVtbl->GetDestCtx(This,pdwDestContext,ppvDestContext)
#define IAsyncRpcChannelBuffer_IsConnected(This) (This)->lpVtbl->IsConnected(This)
/*** IRpcChannelBuffer2 methods ***/
#define IAsyncRpcChannelBuffer_GetProtocolVersion(This,pdwVersion) (This)->lpVtbl->GetProtocolVersion(This,pdwVersion)
/*** IAsyncRpcChannelBuffer methods ***/
#define IAsyncRpcChannelBuffer_Send(This,pMsg,pSync,pulStatus) (This)->lpVtbl->Send(This,pMsg,pSync,pulStatus)
#define IAsyncRpcChannelBuffer_Receive(This,pMsg,pulStatus) (This)->lpVtbl->Receive(This,pMsg,pulStatus)
#define IAsyncRpcChannelBuffer_GetDestCtxEx(This,pMsg,pdwDestContext,ppvDestContext) (This)->lpVtbl->GetDestCtxEx(This,pMsg,pdwDestContext,ppvDestContext)
#endif
#endif
HRESULT STDMETHODCALLTYPE IAsyncRpcChannelBuffer_Send_Proxy(
IAsyncRpcChannelBuffer* This,
RPCOLEMESSAGE *pMsg,
ISynchronize *pSync,
ULONG *pulStatus);
void __RPC_STUB IAsyncRpcChannelBuffer_Send_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IAsyncRpcChannelBuffer_Receive_Proxy(
IAsyncRpcChannelBuffer* This,
RPCOLEMESSAGE *pMsg,
ULONG *pulStatus);
void __RPC_STUB IAsyncRpcChannelBuffer_Receive_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IAsyncRpcChannelBuffer_GetDestCtxEx_Proxy(
IAsyncRpcChannelBuffer* This,
RPCOLEMESSAGE *pMsg,
DWORD *pdwDestContext,
void **ppvDestContext);
void __RPC_STUB IAsyncRpcChannelBuffer_GetDestCtxEx_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IAsyncRpcChannelBuffer_INTERFACE_DEFINED__ */
/*****************************************************************************
* IRpcSyntaxNegotiate interface
*/
#ifndef __IRpcSyntaxNegotiate_INTERFACE_DEFINED__
#define __IRpcSyntaxNegotiate_INTERFACE_DEFINED__
DEFINE_GUID(IID_IRpcSyntaxNegotiate, 0x58a08519, 0x24c8, 0x4935, 0xb4,0x82, 0x3f,0xd8,0x23,0x33,0x3a,0x4f);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IRpcSyntaxNegotiate : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE NegotiateSyntax(
RPCOLEMESSAGE *pMsg) = 0;
};
#else
typedef struct IRpcSyntaxNegotiateVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IRpcSyntaxNegotiate* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IRpcSyntaxNegotiate* This);
ULONG (STDMETHODCALLTYPE *Release)(
IRpcSyntaxNegotiate* This);
/*** IRpcSyntaxNegotiate methods ***/
HRESULT (STDMETHODCALLTYPE *NegotiateSyntax)(
IRpcSyntaxNegotiate* This,
RPCOLEMESSAGE *pMsg);
END_INTERFACE
} IRpcSyntaxNegotiateVtbl;
interface IRpcSyntaxNegotiate {
CONST_VTBL IRpcSyntaxNegotiateVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IRpcSyntaxNegotiate_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IRpcSyntaxNegotiate_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IRpcSyntaxNegotiate_Release(This) (This)->lpVtbl->Release(This)
/*** IRpcSyntaxNegotiate methods ***/
#define IRpcSyntaxNegotiate_NegotiateSyntax(This,pMsg) (This)->lpVtbl->NegotiateSyntax(This,pMsg)
#endif
#endif
HRESULT STDMETHODCALLTYPE IRpcSyntaxNegotiate_NegotiateSyntax_Proxy(
IRpcSyntaxNegotiate* This,
RPCOLEMESSAGE *pMsg);
void __RPC_STUB IRpcSyntaxNegotiate_NegotiateSyntax_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IRpcSyntaxNegotiate_INTERFACE_DEFINED__ */
/*****************************************************************************
* IRpcProxyBuffer interface
*/
#ifndef __IRpcProxyBuffer_INTERFACE_DEFINED__
#define __IRpcProxyBuffer_INTERFACE_DEFINED__
typedef IRpcProxyBuffer *LPRPCPROXYBUFFER;
DEFINE_GUID(IID_IRpcProxyBuffer, 0xd5f56a34, 0x593b, 0x101a, 0xb5,0x69, 0x08,0x00,0x2b,0x2d,0xbf,0x7a);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IRpcProxyBuffer : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Connect(
IRpcChannelBuffer *pRpcChannelBuffer) = 0;
virtual void STDMETHODCALLTYPE Disconnect(
) = 0;
};
#else
typedef struct IRpcProxyBufferVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IRpcProxyBuffer* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IRpcProxyBuffer* This);
ULONG (STDMETHODCALLTYPE *Release)(
IRpcProxyBuffer* This);
/*** IRpcProxyBuffer methods ***/
HRESULT (STDMETHODCALLTYPE *Connect)(
IRpcProxyBuffer* This,
IRpcChannelBuffer *pRpcChannelBuffer);
void (STDMETHODCALLTYPE *Disconnect)(
IRpcProxyBuffer* This);
END_INTERFACE
} IRpcProxyBufferVtbl;
interface IRpcProxyBuffer {
CONST_VTBL IRpcProxyBufferVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IRpcProxyBuffer_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IRpcProxyBuffer_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IRpcProxyBuffer_Release(This) (This)->lpVtbl->Release(This)
/*** IRpcProxyBuffer methods ***/
#define IRpcProxyBuffer_Connect(This,pRpcChannelBuffer) (This)->lpVtbl->Connect(This,pRpcChannelBuffer)
#define IRpcProxyBuffer_Disconnect(This) (This)->lpVtbl->Disconnect(This)
#endif
#endif
HRESULT STDMETHODCALLTYPE IRpcProxyBuffer_Connect_Proxy(
IRpcProxyBuffer* This,
IRpcChannelBuffer *pRpcChannelBuffer);
void __RPC_STUB IRpcProxyBuffer_Connect_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IRpcProxyBuffer_Disconnect_Proxy(
IRpcProxyBuffer* This);
void __RPC_STUB IRpcProxyBuffer_Disconnect_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IRpcProxyBuffer_INTERFACE_DEFINED__ */
/*****************************************************************************
* IRpcStubBuffer interface
*/
#ifndef __IRpcStubBuffer_INTERFACE_DEFINED__
#define __IRpcStubBuffer_INTERFACE_DEFINED__
typedef IRpcStubBuffer *LPRPCSTUBBUFFER;
DEFINE_GUID(IID_IRpcStubBuffer, 0xd5f56afc, 0x593b, 0x101a, 0xb5,0x69, 0x08,0x00,0x2b,0x2d,0xbf,0x7a);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IRpcStubBuffer : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Connect(
IUnknown *pUnkServer) = 0;
virtual void STDMETHODCALLTYPE Disconnect(
) = 0;
virtual HRESULT STDMETHODCALLTYPE Invoke(
RPCOLEMESSAGE *_prpcmsg,
IRpcChannelBuffer *_pRpcChannelBuffer) = 0;
virtual IRpcStubBuffer * STDMETHODCALLTYPE IsIIDSupported(
REFIID riid) = 0;
virtual ULONG STDMETHODCALLTYPE CountRefs(
) = 0;
virtual HRESULT STDMETHODCALLTYPE DebugServerQueryInterface(
void **ppv) = 0;
virtual void STDMETHODCALLTYPE DebugServerRelease(
void *pv) = 0;
};
#else
typedef struct IRpcStubBufferVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IRpcStubBuffer* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IRpcStubBuffer* This);
ULONG (STDMETHODCALLTYPE *Release)(
IRpcStubBuffer* This);
/*** IRpcStubBuffer methods ***/
HRESULT (STDMETHODCALLTYPE *Connect)(
IRpcStubBuffer* This,
IUnknown *pUnkServer);
void (STDMETHODCALLTYPE *Disconnect)(
IRpcStubBuffer* This);
HRESULT (STDMETHODCALLTYPE *Invoke)(
IRpcStubBuffer* This,
RPCOLEMESSAGE *_prpcmsg,
IRpcChannelBuffer *_pRpcChannelBuffer);
IRpcStubBuffer * (STDMETHODCALLTYPE *IsIIDSupported)(
IRpcStubBuffer* This,
REFIID riid);
ULONG (STDMETHODCALLTYPE *CountRefs)(
IRpcStubBuffer* This);
HRESULT (STDMETHODCALLTYPE *DebugServerQueryInterface)(
IRpcStubBuffer* This,
void **ppv);
void (STDMETHODCALLTYPE *DebugServerRelease)(
IRpcStubBuffer* This,
void *pv);
END_INTERFACE
} IRpcStubBufferVtbl;
interface IRpcStubBuffer {
CONST_VTBL IRpcStubBufferVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IRpcStubBuffer_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IRpcStubBuffer_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IRpcStubBuffer_Release(This) (This)->lpVtbl->Release(This)
/*** IRpcStubBuffer methods ***/
#define IRpcStubBuffer_Connect(This,pUnkServer) (This)->lpVtbl->Connect(This,pUnkServer)
#define IRpcStubBuffer_Disconnect(This) (This)->lpVtbl->Disconnect(This)
#define IRpcStubBuffer_Invoke(This,_prpcmsg,_pRpcChannelBuffer) (This)->lpVtbl->Invoke(This,_prpcmsg,_pRpcChannelBuffer)
#define IRpcStubBuffer_IsIIDSupported(This,riid) (This)->lpVtbl->IsIIDSupported(This,riid)
#define IRpcStubBuffer_CountRefs(This) (This)->lpVtbl->CountRefs(This)
#define IRpcStubBuffer_DebugServerQueryInterface(This,ppv) (This)->lpVtbl->DebugServerQueryInterface(This,ppv)
#define IRpcStubBuffer_DebugServerRelease(This,pv) (This)->lpVtbl->DebugServerRelease(This,pv)
#endif
#endif
HRESULT STDMETHODCALLTYPE IRpcStubBuffer_Connect_Proxy(
IRpcStubBuffer* This,
IUnknown *pUnkServer);
void __RPC_STUB IRpcStubBuffer_Connect_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IRpcStubBuffer_Disconnect_Proxy(
IRpcStubBuffer* This);
void __RPC_STUB IRpcStubBuffer_Disconnect_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcStubBuffer_Invoke_Proxy(
IRpcStubBuffer* This,
RPCOLEMESSAGE *_prpcmsg,
IRpcChannelBuffer *_pRpcChannelBuffer);
void __RPC_STUB IRpcStubBuffer_Invoke_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
IRpcStubBuffer * STDMETHODCALLTYPE IRpcStubBuffer_IsIIDSupported_Proxy(
IRpcStubBuffer* This,
REFIID riid);
void __RPC_STUB IRpcStubBuffer_IsIIDSupported_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
ULONG STDMETHODCALLTYPE IRpcStubBuffer_CountRefs_Proxy(
IRpcStubBuffer* This);
void __RPC_STUB IRpcStubBuffer_CountRefs_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcStubBuffer_DebugServerQueryInterface_Proxy(
IRpcStubBuffer* This,
void **ppv);
void __RPC_STUB IRpcStubBuffer_DebugServerQueryInterface_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IRpcStubBuffer_DebugServerRelease_Proxy(
IRpcStubBuffer* This,
void *pv);
void __RPC_STUB IRpcStubBuffer_DebugServerRelease_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IRpcStubBuffer_INTERFACE_DEFINED__ */
/*****************************************************************************
* IPSFactoryBuffer interface
*/
#ifndef __IPSFactoryBuffer_INTERFACE_DEFINED__
#define __IPSFactoryBuffer_INTERFACE_DEFINED__
typedef IPSFactoryBuffer *LPPSFACTORYBUFFER;
DEFINE_GUID(IID_IPSFactoryBuffer, 0xd5f569d0, 0x593b, 0x101a, 0xb5,0x69, 0x08,0x00,0x2b,0x2d,0xbf,0x7a);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IPSFactoryBuffer : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE CreateProxy(
IUnknown *pUnkOuter,
REFIID riid,
IRpcProxyBuffer **ppProxy,
void **ppv) = 0;
virtual HRESULT STDMETHODCALLTYPE CreateStub(
REFIID riid,
IUnknown *pUnkServer,
IRpcStubBuffer **ppStub) = 0;
};
#else
typedef struct IPSFactoryBufferVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IPSFactoryBuffer* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IPSFactoryBuffer* This);
ULONG (STDMETHODCALLTYPE *Release)(
IPSFactoryBuffer* This);
/*** IPSFactoryBuffer methods ***/
HRESULT (STDMETHODCALLTYPE *CreateProxy)(
IPSFactoryBuffer* This,
IUnknown *pUnkOuter,
REFIID riid,
IRpcProxyBuffer **ppProxy,
void **ppv);
HRESULT (STDMETHODCALLTYPE *CreateStub)(
IPSFactoryBuffer* This,
REFIID riid,
IUnknown *pUnkServer,
IRpcStubBuffer **ppStub);
END_INTERFACE
} IPSFactoryBufferVtbl;
interface IPSFactoryBuffer {
CONST_VTBL IPSFactoryBufferVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IPSFactoryBuffer_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IPSFactoryBuffer_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IPSFactoryBuffer_Release(This) (This)->lpVtbl->Release(This)
/*** IPSFactoryBuffer methods ***/
#define IPSFactoryBuffer_CreateProxy(This,pUnkOuter,riid,ppProxy,ppv) (This)->lpVtbl->CreateProxy(This,pUnkOuter,riid,ppProxy,ppv)
#define IPSFactoryBuffer_CreateStub(This,riid,pUnkServer,ppStub) (This)->lpVtbl->CreateStub(This,riid,pUnkServer,ppStub)
#endif
#endif
HRESULT STDMETHODCALLTYPE IPSFactoryBuffer_CreateProxy_Proxy(
IPSFactoryBuffer* This,
IUnknown *pUnkOuter,
REFIID riid,
IRpcProxyBuffer **ppProxy,
void **ppv);
void __RPC_STUB IPSFactoryBuffer_CreateProxy_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IPSFactoryBuffer_CreateStub_Proxy(
IPSFactoryBuffer* This,
REFIID riid,
IUnknown *pUnkServer,
IRpcStubBuffer **ppStub);
void __RPC_STUB IPSFactoryBuffer_CreateStub_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IPSFactoryBuffer_INTERFACE_DEFINED__ */
/*****************************************************************************
* IChannelHook interface
*/
#ifndef __IChannelHook_INTERFACE_DEFINED__
#define __IChannelHook_INTERFACE_DEFINED__
typedef IChannelHook *LPCHANNELHOOK;
typedef struct SChannelHookCallInfo {
IID iid;
DWORD cbSize;
GUID uCausality;
DWORD dwServerPid;
DWORD iMethod;
void *pObject;
} SChannelHookCallInfo;
DEFINE_GUID(IID_IChannelHook, 0x1008c4a0, 0x7613, 0x11cf, 0x9a,0xf1, 0x00,0x20,0xaf,0x6e,0x72,0xf4);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IChannelHook : public IUnknown
{
virtual void STDMETHODCALLTYPE ClientGetSize(
REFGUID uExtent,
REFIID riid,
ULONG *pDataSize) = 0;
virtual void STDMETHODCALLTYPE ClientFillBuffer(
REFGUID uExtent,
REFIID riid,
ULONG *pDataSize,
void *pDataBuffer) = 0;
virtual void STDMETHODCALLTYPE ClientNotify(
REFGUID uExtent,
REFIID riid,
ULONG cbDataSize,
void *pDataBuffer,
DWORD lDataRep,
HRESULT hrFault) = 0;
virtual void STDMETHODCALLTYPE ServerNotify(
REFGUID uExtent,
REFIID riid,
ULONG cbDataSize,
void *pDataBuffer,
DWORD lDataRep) = 0;
virtual void STDMETHODCALLTYPE ServerGetSize(
REFGUID uExtent,
REFIID riid,
HRESULT hrFault,
ULONG *pDataSize) = 0;
virtual void STDMETHODCALLTYPE ServerFillBuffer(
REFGUID uExtent,
REFIID riid,
ULONG *pDataSize,
void *pDataBuffer,
HRESULT hrFault) = 0;
};
#else
typedef struct IChannelHookVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IChannelHook* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IChannelHook* This);
ULONG (STDMETHODCALLTYPE *Release)(
IChannelHook* This);
/*** IChannelHook methods ***/
void (STDMETHODCALLTYPE *ClientGetSize)(
IChannelHook* This,
REFGUID uExtent,
REFIID riid,
ULONG *pDataSize);
void (STDMETHODCALLTYPE *ClientFillBuffer)(
IChannelHook* This,
REFGUID uExtent,
REFIID riid,
ULONG *pDataSize,
void *pDataBuffer);
void (STDMETHODCALLTYPE *ClientNotify)(
IChannelHook* This,
REFGUID uExtent,
REFIID riid,
ULONG cbDataSize,
void *pDataBuffer,
DWORD lDataRep,
HRESULT hrFault);
void (STDMETHODCALLTYPE *ServerNotify)(
IChannelHook* This,
REFGUID uExtent,
REFIID riid,
ULONG cbDataSize,
void *pDataBuffer,
DWORD lDataRep);
void (STDMETHODCALLTYPE *ServerGetSize)(
IChannelHook* This,
REFGUID uExtent,
REFIID riid,
HRESULT hrFault,
ULONG *pDataSize);
void (STDMETHODCALLTYPE *ServerFillBuffer)(
IChannelHook* This,
REFGUID uExtent,
REFIID riid,
ULONG *pDataSize,
void *pDataBuffer,
HRESULT hrFault);
END_INTERFACE
} IChannelHookVtbl;
interface IChannelHook {
CONST_VTBL IChannelHookVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IChannelHook_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IChannelHook_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IChannelHook_Release(This) (This)->lpVtbl->Release(This)
/*** IChannelHook methods ***/
#define IChannelHook_ClientGetSize(This,uExtent,riid,pDataSize) (This)->lpVtbl->ClientGetSize(This,uExtent,riid,pDataSize)
#define IChannelHook_ClientFillBuffer(This,uExtent,riid,pDataSize,pDataBuffer) (This)->lpVtbl->ClientFillBuffer(This,uExtent,riid,pDataSize,pDataBuffer)
#define IChannelHook_ClientNotify(This,uExtent,riid,cbDataSize,pDataBuffer,lDataRep,hrFault) (This)->lpVtbl->ClientNotify(This,uExtent,riid,cbDataSize,pDataBuffer,lDataRep,hrFault)
#define IChannelHook_ServerNotify(This,uExtent,riid,cbDataSize,pDataBuffer,lDataRep) (This)->lpVtbl->ServerNotify(This,uExtent,riid,cbDataSize,pDataBuffer,lDataRep)
#define IChannelHook_ServerGetSize(This,uExtent,riid,hrFault,pDataSize) (This)->lpVtbl->ServerGetSize(This,uExtent,riid,hrFault,pDataSize)
#define IChannelHook_ServerFillBuffer(This,uExtent,riid,pDataSize,pDataBuffer,hrFault) (This)->lpVtbl->ServerFillBuffer(This,uExtent,riid,pDataSize,pDataBuffer,hrFault)
#endif
#endif
void STDMETHODCALLTYPE IChannelHook_ClientGetSize_Proxy(
IChannelHook* This,
REFGUID uExtent,
REFIID riid,
ULONG *pDataSize);
void __RPC_STUB IChannelHook_ClientGetSize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IChannelHook_ClientFillBuffer_Proxy(
IChannelHook* This,
REFGUID uExtent,
REFIID riid,
ULONG *pDataSize,
void *pDataBuffer);
void __RPC_STUB IChannelHook_ClientFillBuffer_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IChannelHook_ClientNotify_Proxy(
IChannelHook* This,
REFGUID uExtent,
REFIID riid,
ULONG cbDataSize,
void *pDataBuffer,
DWORD lDataRep,
HRESULT hrFault);
void __RPC_STUB IChannelHook_ClientNotify_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IChannelHook_ServerNotify_Proxy(
IChannelHook* This,
REFGUID uExtent,
REFIID riid,
ULONG cbDataSize,
void *pDataBuffer,
DWORD lDataRep);
void __RPC_STUB IChannelHook_ServerNotify_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IChannelHook_ServerGetSize_Proxy(
IChannelHook* This,
REFGUID uExtent,
REFIID riid,
HRESULT hrFault,
ULONG *pDataSize);
void __RPC_STUB IChannelHook_ServerGetSize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IChannelHook_ServerFillBuffer_Proxy(
IChannelHook* This,
REFGUID uExtent,
REFIID riid,
ULONG *pDataSize,
void *pDataBuffer,
HRESULT hrFault);
void __RPC_STUB IChannelHook_ServerFillBuffer_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IChannelHook_INTERFACE_DEFINED__ */
extern const FMTID FMTID_SummaryInformation;
extern const FMTID FMTID_DocSummaryInformation;
extern const FMTID FMTID_UserDefinedProperties;
/*****************************************************************************
* IClientSecurity interface
*/
#ifndef __IClientSecurity_INTERFACE_DEFINED__
#define __IClientSecurity_INTERFACE_DEFINED__
typedef struct tagSOLE_AUTHENTICATION_SERVICE {
DWORD dwAuthnSvc;
DWORD dwAuthzSvc;
OLECHAR *pPrincipalName;
HRESULT hr;
} SOLE_AUTHENTICATION_SERVICE;
typedef SOLE_AUTHENTICATION_SERVICE *PSOLE_AUTHENTICATION_SERVICE;
typedef struct tagSOLE_AUTHENTICATION_INFO {
DWORD dwAuthnSvc;
DWORD dwAuthzSvc;
void *pAuthInfo;
} SOLE_AUTHENTICATION_INFO;
#define COLE_DEFAULT_PRINCIPAL ((OLECHAR *)-1)
#define COLE_DEFAULT_AUTHINFO ((void *)-1)
typedef struct tagSOLE_AUTHENTICATION_LIST {
DWORD cAuthInfo;
SOLE_AUTHENTICATION_INFO *aAuthInfo;
} SOLE_AUTHENTICATION_LIST;
typedef enum tagEOLE_AUTHENTICATION_CAPABILITIES {
EOAC_NONE = 0x0,
EOAC_MUTUAL_AUTH = 0x1,
EOAC_SECURE_REFS = 0x2,
EOAC_ACCESS_CONTROL = 0x4,
EOAC_APPID = 0x8,
EOAC_DYNAMIC = 0x10,
EOAC_STATIC_CLOAKING = 0x20,
EOAC_DYNAMIC_CLOAKING = 0x40,
EOAC_ANY_AUTHORITY = 0x80,
EOAC_MAKE_FULLSIC = 0x100,
EOAC_REQUIRE_FULLSIC = 0x200,
EOAC_AUTO_IMPERSONATE = 0x400,
EOAC_DEFAULT = 0x800,
EOAC_DISABLE_AAA = 0x1000,
EOAC_NO_CUSTOM_MARSHAL = 0x2000
} EOLE_AUTHENTICATION_CAPABILITIES;
DEFINE_GUID(IID_IClientSecurity, 0x0000013d, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IClientSecurity : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE QueryBlanket(
IUnknown *pProxy,
DWORD *pAuthnSvc,
DWORD *pAuthzSvc,
OLECHAR **pServerPrincName,
DWORD *pAuthnLevel,
DWORD *pImpLevel,
void **pAuthInfo,
DWORD *pCapabilities) = 0;
virtual HRESULT STDMETHODCALLTYPE SetBlanket(
IUnknown *pProxy,
DWORD AuthnSvc,
DWORD AuthzSvc,
OLECHAR *pServerPrincName,
DWORD AuthnLevel,
DWORD ImpLevel,
void *pAuthInfo,
DWORD Capabilities) = 0;
virtual HRESULT STDMETHODCALLTYPE CopyProxy(
IUnknown *pProxy,
IUnknown **ppCopy) = 0;
};
#else
typedef struct IClientSecurityVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IClientSecurity* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IClientSecurity* This);
ULONG (STDMETHODCALLTYPE *Release)(
IClientSecurity* This);
/*** IClientSecurity methods ***/
HRESULT (STDMETHODCALLTYPE *QueryBlanket)(
IClientSecurity* This,
IUnknown *pProxy,
DWORD *pAuthnSvc,
DWORD *pAuthzSvc,
OLECHAR **pServerPrincName,
DWORD *pAuthnLevel,
DWORD *pImpLevel,
void **pAuthInfo,
DWORD *pCapabilities);
HRESULT (STDMETHODCALLTYPE *SetBlanket)(
IClientSecurity* This,
IUnknown *pProxy,
DWORD AuthnSvc,
DWORD AuthzSvc,
OLECHAR *pServerPrincName,
DWORD AuthnLevel,
DWORD ImpLevel,
void *pAuthInfo,
DWORD Capabilities);
HRESULT (STDMETHODCALLTYPE *CopyProxy)(
IClientSecurity* This,
IUnknown *pProxy,
IUnknown **ppCopy);
END_INTERFACE
} IClientSecurityVtbl;
interface IClientSecurity {
CONST_VTBL IClientSecurityVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IClientSecurity_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IClientSecurity_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IClientSecurity_Release(This) (This)->lpVtbl->Release(This)
/*** IClientSecurity methods ***/
#define IClientSecurity_QueryBlanket(This,pProxy,pAuthnSvc,pAuthzSvc,pServerPrincName,pAuthnLevel,pImpLevel,pAuthInfo,pCapabilities) (This)->lpVtbl->QueryBlanket(This,pProxy,pAuthnSvc,pAuthzSvc,pServerPrincName,pAuthnLevel,pImpLevel,pAuthInfo,pCapabilities)
#define IClientSecurity_SetBlanket(This,pProxy,AuthnSvc,AuthzSvc,pServerPrincName,AuthnLevel,ImpLevel,pAuthInfo,Capabilities) (This)->lpVtbl->SetBlanket(This,pProxy,AuthnSvc,AuthzSvc,pServerPrincName,AuthnLevel,ImpLevel,pAuthInfo,Capabilities)
#define IClientSecurity_CopyProxy(This,pProxy,ppCopy) (This)->lpVtbl->CopyProxy(This,pProxy,ppCopy)
#endif
#endif
HRESULT STDMETHODCALLTYPE IClientSecurity_QueryBlanket_Proxy(
IClientSecurity* This,
IUnknown *pProxy,
DWORD *pAuthnSvc,
DWORD *pAuthzSvc,
OLECHAR **pServerPrincName,
DWORD *pAuthnLevel,
DWORD *pImpLevel,
void **pAuthInfo,
DWORD *pCapabilities);
void __RPC_STUB IClientSecurity_QueryBlanket_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IClientSecurity_SetBlanket_Proxy(
IClientSecurity* This,
IUnknown *pProxy,
DWORD AuthnSvc,
DWORD AuthzSvc,
OLECHAR *pServerPrincName,
DWORD AuthnLevel,
DWORD ImpLevel,
void *pAuthInfo,
DWORD Capabilities);
void __RPC_STUB IClientSecurity_SetBlanket_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IClientSecurity_CopyProxy_Proxy(
IClientSecurity* This,
IUnknown *pProxy,
IUnknown **ppCopy);
void __RPC_STUB IClientSecurity_CopyProxy_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IClientSecurity_INTERFACE_DEFINED__ */
/*****************************************************************************
* IServerSecurity interface
*/
#ifndef __IServerSecurity_INTERFACE_DEFINED__
#define __IServerSecurity_INTERFACE_DEFINED__
DEFINE_GUID(IID_IServerSecurity, 0x0000013e, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IServerSecurity : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE QueryBlanket(
DWORD *pAuthnSvc,
DWORD *pAuthzSvc,
OLECHAR **pServerPrincName,
DWORD *pAuthnLevel,
DWORD *pImpLevel,
void **pPrivs,
DWORD *pCapabilities) = 0;
virtual HRESULT STDMETHODCALLTYPE ImpersonateClient(
) = 0;
virtual HRESULT STDMETHODCALLTYPE RevertToSelf(
) = 0;
virtual BOOL STDMETHODCALLTYPE IsImpersonating(
) = 0;
};
#else
typedef struct IServerSecurityVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IServerSecurity* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IServerSecurity* This);
ULONG (STDMETHODCALLTYPE *Release)(
IServerSecurity* This);
/*** IServerSecurity methods ***/
HRESULT (STDMETHODCALLTYPE *QueryBlanket)(
IServerSecurity* This,
DWORD *pAuthnSvc,
DWORD *pAuthzSvc,
OLECHAR **pServerPrincName,
DWORD *pAuthnLevel,
DWORD *pImpLevel,
void **pPrivs,
DWORD *pCapabilities);
HRESULT (STDMETHODCALLTYPE *ImpersonateClient)(
IServerSecurity* This);
HRESULT (STDMETHODCALLTYPE *RevertToSelf)(
IServerSecurity* This);
BOOL (STDMETHODCALLTYPE *IsImpersonating)(
IServerSecurity* This);
END_INTERFACE
} IServerSecurityVtbl;
interface IServerSecurity {
CONST_VTBL IServerSecurityVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IServerSecurity_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IServerSecurity_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IServerSecurity_Release(This) (This)->lpVtbl->Release(This)
/*** IServerSecurity methods ***/
#define IServerSecurity_QueryBlanket(This,pAuthnSvc,pAuthzSvc,pServerPrincName,pAuthnLevel,pImpLevel,pPrivs,pCapabilities) (This)->lpVtbl->QueryBlanket(This,pAuthnSvc,pAuthzSvc,pServerPrincName,pAuthnLevel,pImpLevel,pPrivs,pCapabilities)
#define IServerSecurity_ImpersonateClient(This) (This)->lpVtbl->ImpersonateClient(This)
#define IServerSecurity_RevertToSelf(This) (This)->lpVtbl->RevertToSelf(This)
#define IServerSecurity_IsImpersonating(This) (This)->lpVtbl->IsImpersonating(This)
#endif
#endif
HRESULT STDMETHODCALLTYPE IServerSecurity_QueryBlanket_Proxy(
IServerSecurity* This,
DWORD *pAuthnSvc,
DWORD *pAuthzSvc,
OLECHAR **pServerPrincName,
DWORD *pAuthnLevel,
DWORD *pImpLevel,
void **pPrivs,
DWORD *pCapabilities);
void __RPC_STUB IServerSecurity_QueryBlanket_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IServerSecurity_ImpersonateClient_Proxy(
IServerSecurity* This);
void __RPC_STUB IServerSecurity_ImpersonateClient_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IServerSecurity_RevertToSelf_Proxy(
IServerSecurity* This);
void __RPC_STUB IServerSecurity_RevertToSelf_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
BOOL STDMETHODCALLTYPE IServerSecurity_IsImpersonating_Proxy(
IServerSecurity* This);
void __RPC_STUB IServerSecurity_IsImpersonating_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IServerSecurity_INTERFACE_DEFINED__ */
/*****************************************************************************
* IAsyncSetup interface
*/
#ifndef __IAsyncSetup_INTERFACE_DEFINED__
#define __IAsyncSetup_INTERFACE_DEFINED__
DEFINE_GUID(IID_IAsyncSetup, 0x00000024, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IAsyncSetup : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE GetAsyncManager(
REFIID riid,
IUnknown *pOuter,
DWORD dwFlags,
IUnknown **ppInner,
IAsyncManager **ppAsyncMgr) = 0;
};
#else
typedef struct IAsyncSetupVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IAsyncSetup* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IAsyncSetup* This);
ULONG (STDMETHODCALLTYPE *Release)(
IAsyncSetup* This);
/*** IAsyncSetup methods ***/
HRESULT (STDMETHODCALLTYPE *GetAsyncManager)(
IAsyncSetup* This,
REFIID riid,
IUnknown *pOuter,
DWORD dwFlags,
IUnknown **ppInner,
IAsyncManager **ppAsyncMgr);
END_INTERFACE
} IAsyncSetupVtbl;
interface IAsyncSetup {
CONST_VTBL IAsyncSetupVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IAsyncSetup_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IAsyncSetup_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IAsyncSetup_Release(This) (This)->lpVtbl->Release(This)
/*** IAsyncSetup methods ***/
#define IAsyncSetup_GetAsyncManager(This,riid,pOuter,dwFlags,ppInner,ppAsyncMgr) (This)->lpVtbl->GetAsyncManager(This,riid,pOuter,dwFlags,ppInner,ppAsyncMgr)
#endif
#endif
HRESULT STDMETHODCALLTYPE IAsyncSetup_GetAsyncManager_Proxy(
IAsyncSetup* This,
REFIID riid,
IUnknown *pOuter,
DWORD dwFlags,
IUnknown **ppInner,
IAsyncManager **ppAsyncMgr);
void __RPC_STUB IAsyncSetup_GetAsyncManager_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IAsyncSetup_INTERFACE_DEFINED__ */
/*****************************************************************************
* IDirectWriterLock interface
*/
#ifndef __IDirectWriterLock_INTERFACE_DEFINED__
#define __IDirectWriterLock_INTERFACE_DEFINED__
DEFINE_GUID(IID_IDirectWriterLock, 0x0e6d4d92, 0x6738, 0x11cf, 0x96,0x08, 0x00,0xaa,0x00,0x68,0x0d,0xb4);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IDirectWriterLock : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE WaitForWriteAccess(
DWORD dwTimeout) = 0;
virtual HRESULT STDMETHODCALLTYPE ReleaseWriteAccess(
) = 0;
virtual HRESULT STDMETHODCALLTYPE HaveWriteAccess(
) = 0;
};
#else
typedef struct IDirectWriterLockVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IDirectWriterLock* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IDirectWriterLock* This);
ULONG (STDMETHODCALLTYPE *Release)(
IDirectWriterLock* This);
/*** IDirectWriterLock methods ***/
HRESULT (STDMETHODCALLTYPE *WaitForWriteAccess)(
IDirectWriterLock* This,
DWORD dwTimeout);
HRESULT (STDMETHODCALLTYPE *ReleaseWriteAccess)(
IDirectWriterLock* This);
HRESULT (STDMETHODCALLTYPE *HaveWriteAccess)(
IDirectWriterLock* This);
END_INTERFACE
} IDirectWriterLockVtbl;
interface IDirectWriterLock {
CONST_VTBL IDirectWriterLockVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IDirectWriterLock_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IDirectWriterLock_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IDirectWriterLock_Release(This) (This)->lpVtbl->Release(This)
/*** IDirectWriterLock methods ***/
#define IDirectWriterLock_WaitForWriteAccess(This,dwTimeout) (This)->lpVtbl->WaitForWriteAccess(This,dwTimeout)
#define IDirectWriterLock_ReleaseWriteAccess(This) (This)->lpVtbl->ReleaseWriteAccess(This)
#define IDirectWriterLock_HaveWriteAccess(This) (This)->lpVtbl->HaveWriteAccess(This)
#endif
#endif
HRESULT STDMETHODCALLTYPE IDirectWriterLock_WaitForWriteAccess_Proxy(
IDirectWriterLock* This,
DWORD dwTimeout);
void __RPC_STUB IDirectWriterLock_WaitForWriteAccess_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IDirectWriterLock_ReleaseWriteAccess_Proxy(
IDirectWriterLock* This);
void __RPC_STUB IDirectWriterLock_ReleaseWriteAccess_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IDirectWriterLock_HaveWriteAccess_Proxy(
IDirectWriterLock* This);
void __RPC_STUB IDirectWriterLock_HaveWriteAccess_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IDirectWriterLock_INTERFACE_DEFINED__ */
/*****************************************************************************
* ISynchronize interface
*/
#ifndef __ISynchronize_INTERFACE_DEFINED__
#define __ISynchronize_INTERFACE_DEFINED__
DEFINE_GUID(IID_ISynchronize, 0x00000030, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface ISynchronize : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Wait(
DWORD dwFlags,
DWORD dwMilliseconds) = 0;
virtual HRESULT STDMETHODCALLTYPE Signal(
) = 0;
virtual HRESULT STDMETHODCALLTYPE Reset(
) = 0;
};
#else
typedef struct ISynchronizeVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
ISynchronize* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
ISynchronize* This);
ULONG (STDMETHODCALLTYPE *Release)(
ISynchronize* This);
/*** ISynchronize methods ***/
HRESULT (STDMETHODCALLTYPE *Wait)(
ISynchronize* This,
DWORD dwFlags,
DWORD dwMilliseconds);
HRESULT (STDMETHODCALLTYPE *Signal)(
ISynchronize* This);
HRESULT (STDMETHODCALLTYPE *Reset)(
ISynchronize* This);
END_INTERFACE
} ISynchronizeVtbl;
interface ISynchronize {
CONST_VTBL ISynchronizeVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define ISynchronize_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define ISynchronize_AddRef(This) (This)->lpVtbl->AddRef(This)
#define ISynchronize_Release(This) (This)->lpVtbl->Release(This)
/*** ISynchronize methods ***/
#define ISynchronize_Wait(This,dwFlags,dwMilliseconds) (This)->lpVtbl->Wait(This,dwFlags,dwMilliseconds)
#define ISynchronize_Signal(This) (This)->lpVtbl->Signal(This)
#define ISynchronize_Reset(This) (This)->lpVtbl->Reset(This)
#endif
#endif
HRESULT STDMETHODCALLTYPE ISynchronize_Wait_Proxy(
ISynchronize* This,
DWORD dwFlags,
DWORD dwMilliseconds);
void __RPC_STUB ISynchronize_Wait_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ISynchronize_Signal_Proxy(
ISynchronize* This);
void __RPC_STUB ISynchronize_Signal_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ISynchronize_Reset_Proxy(
ISynchronize* This);
void __RPC_STUB ISynchronize_Reset_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __ISynchronize_INTERFACE_DEFINED__ */
/*****************************************************************************
* ISynchronizeHandle interface
*/
#ifndef __ISynchronizeHandle_INTERFACE_DEFINED__
#define __ISynchronizeHandle_INTERFACE_DEFINED__
DEFINE_GUID(IID_ISynchronizeHandle, 0x00000031, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface ISynchronizeHandle : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE GetHandle(
HANDLE *ph) = 0;
};
#else
typedef struct ISynchronizeHandleVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
ISynchronizeHandle* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
ISynchronizeHandle* This);
ULONG (STDMETHODCALLTYPE *Release)(
ISynchronizeHandle* This);
/*** ISynchronizeHandle methods ***/
HRESULT (STDMETHODCALLTYPE *GetHandle)(
ISynchronizeHandle* This,
HANDLE *ph);
END_INTERFACE
} ISynchronizeHandleVtbl;
interface ISynchronizeHandle {
CONST_VTBL ISynchronizeHandleVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define ISynchronizeHandle_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define ISynchronizeHandle_AddRef(This) (This)->lpVtbl->AddRef(This)
#define ISynchronizeHandle_Release(This) (This)->lpVtbl->Release(This)
/*** ISynchronizeHandle methods ***/
#define ISynchronizeHandle_GetHandle(This,ph) (This)->lpVtbl->GetHandle(This,ph)
#endif
#endif
HRESULT STDMETHODCALLTYPE ISynchronizeHandle_GetHandle_Proxy(
ISynchronizeHandle* This,
HANDLE *ph);
void __RPC_STUB ISynchronizeHandle_GetHandle_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __ISynchronizeHandle_INTERFACE_DEFINED__ */
/*****************************************************************************
* ISynchronizeEvent interface
*/
#ifndef __ISynchronizeEvent_INTERFACE_DEFINED__
#define __ISynchronizeEvent_INTERFACE_DEFINED__
DEFINE_GUID(IID_ISynchronizeEvent, 0x00000032, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface ISynchronizeEvent : public ISynchronizeHandle
{
virtual HRESULT STDMETHODCALLTYPE SetEventHandle(
HANDLE *ph) = 0;
};
#else
typedef struct ISynchronizeEventVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
ISynchronizeEvent* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
ISynchronizeEvent* This);
ULONG (STDMETHODCALLTYPE *Release)(
ISynchronizeEvent* This);
/*** ISynchronizeHandle methods ***/
HRESULT (STDMETHODCALLTYPE *GetHandle)(
ISynchronizeEvent* This,
HANDLE *ph);
/*** ISynchronizeEvent methods ***/
HRESULT (STDMETHODCALLTYPE *SetEventHandle)(
ISynchronizeEvent* This,
HANDLE *ph);
END_INTERFACE
} ISynchronizeEventVtbl;
interface ISynchronizeEvent {
CONST_VTBL ISynchronizeEventVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define ISynchronizeEvent_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define ISynchronizeEvent_AddRef(This) (This)->lpVtbl->AddRef(This)
#define ISynchronizeEvent_Release(This) (This)->lpVtbl->Release(This)
/*** ISynchronizeHandle methods ***/
#define ISynchronizeEvent_GetHandle(This,ph) (This)->lpVtbl->GetHandle(This,ph)
/*** ISynchronizeEvent methods ***/
#define ISynchronizeEvent_SetEventHandle(This,ph) (This)->lpVtbl->SetEventHandle(This,ph)
#endif
#endif
HRESULT STDMETHODCALLTYPE ISynchronizeEvent_SetEventHandle_Proxy(
ISynchronizeEvent* This,
HANDLE *ph);
void __RPC_STUB ISynchronizeEvent_SetEventHandle_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __ISynchronizeEvent_INTERFACE_DEFINED__ */
/*****************************************************************************
* ISynchronizeContainer interface
*/
#ifndef __ISynchronizeContainer_INTERFACE_DEFINED__
#define __ISynchronizeContainer_INTERFACE_DEFINED__
DEFINE_GUID(IID_ISynchronizeContainer, 0x00000033, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface ISynchronizeContainer : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE AddSynchronize(
ISynchronize *pSync) = 0;
virtual HRESULT STDMETHODCALLTYPE WaitMultiple(
DWORD dwFlags,
DWORD dwTimeOut,
ISynchronize **ppSync) = 0;
};
#else
typedef struct ISynchronizeContainerVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
ISynchronizeContainer* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
ISynchronizeContainer* This);
ULONG (STDMETHODCALLTYPE *Release)(
ISynchronizeContainer* This);
/*** ISynchronizeContainer methods ***/
HRESULT (STDMETHODCALLTYPE *AddSynchronize)(
ISynchronizeContainer* This,
ISynchronize *pSync);
HRESULT (STDMETHODCALLTYPE *WaitMultiple)(
ISynchronizeContainer* This,
DWORD dwFlags,
DWORD dwTimeOut,
ISynchronize **ppSync);
END_INTERFACE
} ISynchronizeContainerVtbl;
interface ISynchronizeContainer {
CONST_VTBL ISynchronizeContainerVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define ISynchronizeContainer_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define ISynchronizeContainer_AddRef(This) (This)->lpVtbl->AddRef(This)
#define ISynchronizeContainer_Release(This) (This)->lpVtbl->Release(This)
/*** ISynchronizeContainer methods ***/
#define ISynchronizeContainer_AddSynchronize(This,pSync) (This)->lpVtbl->AddSynchronize(This,pSync)
#define ISynchronizeContainer_WaitMultiple(This,dwFlags,dwTimeOut,ppSync) (This)->lpVtbl->WaitMultiple(This,dwFlags,dwTimeOut,ppSync)
#endif
#endif
HRESULT STDMETHODCALLTYPE ISynchronizeContainer_AddSynchronize_Proxy(
ISynchronizeContainer* This,
ISynchronize *pSync);
void __RPC_STUB ISynchronizeContainer_AddSynchronize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ISynchronizeContainer_WaitMultiple_Proxy(
ISynchronizeContainer* This,
DWORD dwFlags,
DWORD dwTimeOut,
ISynchronize **ppSync);
void __RPC_STUB ISynchronizeContainer_WaitMultiple_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __ISynchronizeContainer_INTERFACE_DEFINED__ */
/*****************************************************************************
* ISynchronizeMutex interface
*/
#ifndef __ISynchronizeMutex_INTERFACE_DEFINED__
#define __ISynchronizeMutex_INTERFACE_DEFINED__
DEFINE_GUID(IID_ISynchronizeMutex, 0x00000025, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface ISynchronizeMutex : public ISynchronize
{
virtual HRESULT STDMETHODCALLTYPE ReleaseMutex(
) = 0;
};
#else
typedef struct ISynchronizeMutexVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
ISynchronizeMutex* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
ISynchronizeMutex* This);
ULONG (STDMETHODCALLTYPE *Release)(
ISynchronizeMutex* This);
/*** ISynchronize methods ***/
HRESULT (STDMETHODCALLTYPE *Wait)(
ISynchronizeMutex* This,
DWORD dwFlags,
DWORD dwMilliseconds);
HRESULT (STDMETHODCALLTYPE *Signal)(
ISynchronizeMutex* This);
HRESULT (STDMETHODCALLTYPE *Reset)(
ISynchronizeMutex* This);
/*** ISynchronizeMutex methods ***/
HRESULT (STDMETHODCALLTYPE *ReleaseMutex)(
ISynchronizeMutex* This);
END_INTERFACE
} ISynchronizeMutexVtbl;
interface ISynchronizeMutex {
CONST_VTBL ISynchronizeMutexVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define ISynchronizeMutex_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define ISynchronizeMutex_AddRef(This) (This)->lpVtbl->AddRef(This)
#define ISynchronizeMutex_Release(This) (This)->lpVtbl->Release(This)
/*** ISynchronize methods ***/
#define ISynchronizeMutex_Wait(This,dwFlags,dwMilliseconds) (This)->lpVtbl->Wait(This,dwFlags,dwMilliseconds)
#define ISynchronizeMutex_Signal(This) (This)->lpVtbl->Signal(This)
#define ISynchronizeMutex_Reset(This) (This)->lpVtbl->Reset(This)
/*** ISynchronizeMutex methods ***/
#define ISynchronizeMutex_ReleaseMutex(This) (This)->lpVtbl->ReleaseMutex(This)
#endif
#endif
HRESULT STDMETHODCALLTYPE ISynchronizeMutex_ReleaseMutex_Proxy(
ISynchronizeMutex* This);
void __RPC_STUB ISynchronizeMutex_ReleaseMutex_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __ISynchronizeMutex_INTERFACE_DEFINED__ */
/*****************************************************************************
* ICancelMethodCalls interface
*/
#ifndef __ICancelMethodCalls_INTERFACE_DEFINED__
#define __ICancelMethodCalls_INTERFACE_DEFINED__
typedef ICancelMethodCalls *LPCANCELMETHODCALLS;
DEFINE_GUID(IID_ICancelMethodCalls, 0x00000029, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface ICancelMethodCalls : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Cancel(
ULONG ulSeconds) = 0;
virtual HRESULT STDMETHODCALLTYPE TestCancel(
) = 0;
};
#else
typedef struct ICancelMethodCallsVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
ICancelMethodCalls* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
ICancelMethodCalls* This);
ULONG (STDMETHODCALLTYPE *Release)(
ICancelMethodCalls* This);
/*** ICancelMethodCalls methods ***/
HRESULT (STDMETHODCALLTYPE *Cancel)(
ICancelMethodCalls* This,
ULONG ulSeconds);
HRESULT (STDMETHODCALLTYPE *TestCancel)(
ICancelMethodCalls* This);
END_INTERFACE
} ICancelMethodCallsVtbl;
interface ICancelMethodCalls {
CONST_VTBL ICancelMethodCallsVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define ICancelMethodCalls_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define ICancelMethodCalls_AddRef(This) (This)->lpVtbl->AddRef(This)
#define ICancelMethodCalls_Release(This) (This)->lpVtbl->Release(This)
/*** ICancelMethodCalls methods ***/
#define ICancelMethodCalls_Cancel(This,ulSeconds) (This)->lpVtbl->Cancel(This,ulSeconds)
#define ICancelMethodCalls_TestCancel(This) (This)->lpVtbl->TestCancel(This)
#endif
#endif
HRESULT STDMETHODCALLTYPE ICancelMethodCalls_Cancel_Proxy(
ICancelMethodCalls* This,
ULONG ulSeconds);
void __RPC_STUB ICancelMethodCalls_Cancel_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE ICancelMethodCalls_TestCancel_Proxy(
ICancelMethodCalls* This);
void __RPC_STUB ICancelMethodCalls_TestCancel_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __ICancelMethodCalls_INTERFACE_DEFINED__ */
/*****************************************************************************
* IAsyncManager interface
*/
#ifndef __IAsyncManager_INTERFACE_DEFINED__
#define __IAsyncManager_INTERFACE_DEFINED__
typedef enum tagDCOM_CALL_STATE {
DCOM_NONE = 0,
DCOM_CALL_COMPLETE = 1,
DCOM_CALL_CANCELED = 2
} DCOM_CALL_STATE;
DEFINE_GUID(IID_IAsyncManager, 0x0000002a, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IAsyncManager : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE CompleteCall(
HRESULT Result) = 0;
virtual HRESULT STDMETHODCALLTYPE GetCallContext(
REFIID riid,
void **pInterface) = 0;
virtual HRESULT STDMETHODCALLTYPE GetState(
ULONG *pulStateFlags) = 0;
};
#else
typedef struct IAsyncManagerVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IAsyncManager* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IAsyncManager* This);
ULONG (STDMETHODCALLTYPE *Release)(
IAsyncManager* This);
/*** IAsyncManager methods ***/
HRESULT (STDMETHODCALLTYPE *CompleteCall)(
IAsyncManager* This,
HRESULT Result);
HRESULT (STDMETHODCALLTYPE *GetCallContext)(
IAsyncManager* This,
REFIID riid,
void **pInterface);
HRESULT (STDMETHODCALLTYPE *GetState)(
IAsyncManager* This,
ULONG *pulStateFlags);
END_INTERFACE
} IAsyncManagerVtbl;
interface IAsyncManager {
CONST_VTBL IAsyncManagerVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IAsyncManager_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IAsyncManager_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IAsyncManager_Release(This) (This)->lpVtbl->Release(This)
/*** IAsyncManager methods ***/
#define IAsyncManager_CompleteCall(This,Result) (This)->lpVtbl->CompleteCall(This,Result)
#define IAsyncManager_GetCallContext(This,riid,pInterface) (This)->lpVtbl->GetCallContext(This,riid,pInterface)
#define IAsyncManager_GetState(This,pulStateFlags) (This)->lpVtbl->GetState(This,pulStateFlags)
#endif
#endif
HRESULT STDMETHODCALLTYPE IAsyncManager_CompleteCall_Proxy(
IAsyncManager* This,
HRESULT Result);
void __RPC_STUB IAsyncManager_CompleteCall_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IAsyncManager_GetCallContext_Proxy(
IAsyncManager* This,
REFIID riid,
void **pInterface);
void __RPC_STUB IAsyncManager_GetCallContext_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IAsyncManager_GetState_Proxy(
IAsyncManager* This,
ULONG *pulStateFlags);
void __RPC_STUB IAsyncManager_GetState_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IAsyncManager_INTERFACE_DEFINED__ */
/*****************************************************************************
* ICallFactory interface
*/
#ifndef __ICallFactory_INTERFACE_DEFINED__
#define __ICallFactory_INTERFACE_DEFINED__
DEFINE_GUID(IID_ICallFactory, 0x1c733a30, 0x2a1c, 0x11ce, 0xad,0xe5, 0x00,0xaa,0x00,0x44,0x77,0x3d);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface ICallFactory : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE CreateCall(
REFIID riid,
IUnknown *pCtrlUnk,
REFIID riid2,
IUnknown **ppv) = 0;
};
#else
typedef struct ICallFactoryVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
ICallFactory* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
ICallFactory* This);
ULONG (STDMETHODCALLTYPE *Release)(
ICallFactory* This);
/*** ICallFactory methods ***/
HRESULT (STDMETHODCALLTYPE *CreateCall)(
ICallFactory* This,
REFIID riid,
IUnknown *pCtrlUnk,
REFIID riid2,
IUnknown **ppv);
END_INTERFACE
} ICallFactoryVtbl;
interface ICallFactory {
CONST_VTBL ICallFactoryVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define ICallFactory_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define ICallFactory_AddRef(This) (This)->lpVtbl->AddRef(This)
#define ICallFactory_Release(This) (This)->lpVtbl->Release(This)
/*** ICallFactory methods ***/
#define ICallFactory_CreateCall(This,riid,pCtrlUnk,riid2,ppv) (This)->lpVtbl->CreateCall(This,riid,pCtrlUnk,riid2,ppv)
#endif
#endif
HRESULT STDMETHODCALLTYPE ICallFactory_CreateCall_Proxy(
ICallFactory* This,
REFIID riid,
IUnknown *pCtrlUnk,
REFIID riid2,
IUnknown **ppv);
void __RPC_STUB ICallFactory_CreateCall_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __ICallFactory_INTERFACE_DEFINED__ */
/*****************************************************************************
* IRpcOptions interface
*/
#ifndef __IRpcOptions_INTERFACE_DEFINED__
#define __IRpcOptions_INTERFACE_DEFINED__
DEFINE_GUID(IID_IRpcOptions, 0x00000144, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IRpcOptions : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Set(
IUnknown *pPrx,
DWORD dwProperty,
ULONG_PTR dwValue) = 0;
virtual HRESULT STDMETHODCALLTYPE Query(
IUnknown *pPrx,
DWORD dwProperty,
ULONG_PTR *pdwValue) = 0;
};
#else
typedef struct IRpcOptionsVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IRpcOptions* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IRpcOptions* This);
ULONG (STDMETHODCALLTYPE *Release)(
IRpcOptions* This);
/*** IRpcOptions methods ***/
HRESULT (STDMETHODCALLTYPE *Set)(
IRpcOptions* This,
IUnknown *pPrx,
DWORD dwProperty,
ULONG_PTR dwValue);
HRESULT (STDMETHODCALLTYPE *Query)(
IRpcOptions* This,
IUnknown *pPrx,
DWORD dwProperty,
ULONG_PTR *pdwValue);
END_INTERFACE
} IRpcOptionsVtbl;
interface IRpcOptions {
CONST_VTBL IRpcOptionsVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IRpcOptions_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IRpcOptions_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IRpcOptions_Release(This) (This)->lpVtbl->Release(This)
/*** IRpcOptions methods ***/
#define IRpcOptions_Set(This,pPrx,dwProperty,dwValue) (This)->lpVtbl->Set(This,pPrx,dwProperty,dwValue)
#define IRpcOptions_Query(This,pPrx,dwProperty,pdwValue) (This)->lpVtbl->Query(This,pPrx,dwProperty,pdwValue)
#endif
#endif
HRESULT STDMETHODCALLTYPE IRpcOptions_Set_Proxy(
IRpcOptions* This,
IUnknown *pPrx,
DWORD dwProperty,
ULONG_PTR dwValue);
void __RPC_STUB IRpcOptions_Set_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcOptions_Query_Proxy(
IRpcOptions* This,
IUnknown *pPrx,
DWORD dwProperty,
ULONG_PTR *pdwValue);
void __RPC_STUB IRpcOptions_Query_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IRpcOptions_INTERFACE_DEFINED__ */
enum {
COMBND_RPCTIMEOUT = 1,
COMBND_SERVER_LOCALITY = 2
};
enum {
SERVER_LOCALITY_PROCESS_LOCAL = 0,
SERVER_LOCALITY_MACHINE_LOCAL = 1,
SERVER_LOCALITY_REMOTE = 2
};
/*****************************************************************************
* IRpcHelper interface
*/
#ifndef __IRpcHelper_INTERFACE_DEFINED__
#define __IRpcHelper_INTERFACE_DEFINED__
DEFINE_GUID(IID_IRpcHelper, 0x00000149, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IRpcHelper : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE GetDCOMProtocolVersion(
DWORD *pComVersion) = 0;
virtual HRESULT STDMETHODCALLTYPE GetIIDFromOBJREF(
void *pObjRef,
IID **piid) = 0;
};
#else
typedef struct IRpcHelperVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IRpcHelper* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IRpcHelper* This);
ULONG (STDMETHODCALLTYPE *Release)(
IRpcHelper* This);
/*** IRpcHelper methods ***/
HRESULT (STDMETHODCALLTYPE *GetDCOMProtocolVersion)(
IRpcHelper* This,
DWORD *pComVersion);
HRESULT (STDMETHODCALLTYPE *GetIIDFromOBJREF)(
IRpcHelper* This,
void *pObjRef,
IID **piid);
END_INTERFACE
} IRpcHelperVtbl;
interface IRpcHelper {
CONST_VTBL IRpcHelperVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IRpcHelper_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IRpcHelper_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IRpcHelper_Release(This) (This)->lpVtbl->Release(This)
/*** IRpcHelper methods ***/
#define IRpcHelper_GetDCOMProtocolVersion(This,pComVersion) (This)->lpVtbl->GetDCOMProtocolVersion(This,pComVersion)
#define IRpcHelper_GetIIDFromOBJREF(This,pObjRef,piid) (This)->lpVtbl->GetIIDFromOBJREF(This,pObjRef,piid)
#endif
#endif
HRESULT STDMETHODCALLTYPE IRpcHelper_GetDCOMProtocolVersion_Proxy(
IRpcHelper* This,
DWORD *pComVersion);
void __RPC_STUB IRpcHelper_GetDCOMProtocolVersion_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IRpcHelper_GetIIDFromOBJREF_Proxy(
IRpcHelper* This,
void *pObjRef,
IID **piid);
void __RPC_STUB IRpcHelper_GetIIDFromOBJREF_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IRpcHelper_INTERFACE_DEFINED__ */
/*****************************************************************************
* IReleaseMarshalBuffers interface
*/
#ifndef __IReleaseMarshalBuffers_INTERFACE_DEFINED__
#define __IReleaseMarshalBuffers_INTERFACE_DEFINED__
DEFINE_GUID(IID_IReleaseMarshalBuffers, 0xeb0cb9e8, 0x7996, 0x11d2, 0x87,0x2e, 0x00,0x00,0xf8,0x08,0x08,0x59);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IReleaseMarshalBuffers : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE ReleaseMarshalBuffer(
RPCOLEMESSAGE *pMsg,
DWORD dwFlags,
IUnknown *pChnl) = 0;
};
#else
typedef struct IReleaseMarshalBuffersVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IReleaseMarshalBuffers* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IReleaseMarshalBuffers* This);
ULONG (STDMETHODCALLTYPE *Release)(
IReleaseMarshalBuffers* This);
/*** IReleaseMarshalBuffers methods ***/
HRESULT (STDMETHODCALLTYPE *ReleaseMarshalBuffer)(
IReleaseMarshalBuffers* This,
RPCOLEMESSAGE *pMsg,
DWORD dwFlags,
IUnknown *pChnl);
END_INTERFACE
} IReleaseMarshalBuffersVtbl;
interface IReleaseMarshalBuffers {
CONST_VTBL IReleaseMarshalBuffersVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IReleaseMarshalBuffers_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IReleaseMarshalBuffers_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IReleaseMarshalBuffers_Release(This) (This)->lpVtbl->Release(This)
/*** IReleaseMarshalBuffers methods ***/
#define IReleaseMarshalBuffers_ReleaseMarshalBuffer(This,pMsg,dwFlags,pChnl) (This)->lpVtbl->ReleaseMarshalBuffer(This,pMsg,dwFlags,pChnl)
#endif
#endif
HRESULT STDMETHODCALLTYPE IReleaseMarshalBuffers_ReleaseMarshalBuffer_Proxy(
IReleaseMarshalBuffers* This,
RPCOLEMESSAGE *pMsg,
DWORD dwFlags,
IUnknown *pChnl);
void __RPC_STUB IReleaseMarshalBuffers_ReleaseMarshalBuffer_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IReleaseMarshalBuffers_INTERFACE_DEFINED__ */
/*****************************************************************************
* IWaitMultiple interface
*/
#ifndef __IWaitMultiple_INTERFACE_DEFINED__
#define __IWaitMultiple_INTERFACE_DEFINED__
DEFINE_GUID(IID_IWaitMultiple, 0x0000002b, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IWaitMultiple : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE WaitMultiple(
DWORD timeout,
ISynchronize **pSync) = 0;
virtual HRESULT STDMETHODCALLTYPE AddSynchronize(
ISynchronize *pSync) = 0;
};
#else
typedef struct IWaitMultipleVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IWaitMultiple* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IWaitMultiple* This);
ULONG (STDMETHODCALLTYPE *Release)(
IWaitMultiple* This);
/*** IWaitMultiple methods ***/
HRESULT (STDMETHODCALLTYPE *WaitMultiple)(
IWaitMultiple* This,
DWORD timeout,
ISynchronize **pSync);
HRESULT (STDMETHODCALLTYPE *AddSynchronize)(
IWaitMultiple* This,
ISynchronize *pSync);
END_INTERFACE
} IWaitMultipleVtbl;
interface IWaitMultiple {
CONST_VTBL IWaitMultipleVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IWaitMultiple_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IWaitMultiple_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IWaitMultiple_Release(This) (This)->lpVtbl->Release(This)
/*** IWaitMultiple methods ***/
#define IWaitMultiple_WaitMultiple(This,timeout,pSync) (This)->lpVtbl->WaitMultiple(This,timeout,pSync)
#define IWaitMultiple_AddSynchronize(This,pSync) (This)->lpVtbl->AddSynchronize(This,pSync)
#endif
#endif
HRESULT STDMETHODCALLTYPE IWaitMultiple_WaitMultiple_Proxy(
IWaitMultiple* This,
DWORD timeout,
ISynchronize **pSync);
void __RPC_STUB IWaitMultiple_WaitMultiple_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IWaitMultiple_AddSynchronize_Proxy(
IWaitMultiple* This,
ISynchronize *pSync);
void __RPC_STUB IWaitMultiple_AddSynchronize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IWaitMultiple_INTERFACE_DEFINED__ */
/*****************************************************************************
* IUrlMon interface
*/
#ifndef __IUrlMon_INTERFACE_DEFINED__
#define __IUrlMon_INTERFACE_DEFINED__
DEFINE_GUID(IID_IUrlMon, 0x00000026, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IUrlMon : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE AsyncGetClassBits(
REFCLSID rclsid,
LPCWSTR pszTYPE,
LPCWSTR pszExt,
DWORD dwFileVersionMS,
DWORD dwFileVersionLS,
LPCWSTR pszCodeBase,
IBindCtx *pbc,
DWORD dwClassContext,
REFIID riid,
DWORD flags) = 0;
};
#else
typedef struct IUrlMonVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IUrlMon* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IUrlMon* This);
ULONG (STDMETHODCALLTYPE *Release)(
IUrlMon* This);
/*** IUrlMon methods ***/
HRESULT (STDMETHODCALLTYPE *AsyncGetClassBits)(
IUrlMon* This,
REFCLSID rclsid,
LPCWSTR pszTYPE,
LPCWSTR pszExt,
DWORD dwFileVersionMS,
DWORD dwFileVersionLS,
LPCWSTR pszCodeBase,
IBindCtx *pbc,
DWORD dwClassContext,
REFIID riid,
DWORD flags);
END_INTERFACE
} IUrlMonVtbl;
interface IUrlMon {
CONST_VTBL IUrlMonVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IUrlMon_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IUrlMon_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IUrlMon_Release(This) (This)->lpVtbl->Release(This)
/*** IUrlMon methods ***/
#define IUrlMon_AsyncGetClassBits(This,rclsid,pszTYPE,pszExt,dwFileVersionMS,dwFileVersionLS,pszCodeBase,pbc,dwClassContext,riid,flags) (This)->lpVtbl->AsyncGetClassBits(This,rclsid,pszTYPE,pszExt,dwFileVersionMS,dwFileVersionLS,pszCodeBase,pbc,dwClassContext,riid,flags)
#endif
#endif
HRESULT STDMETHODCALLTYPE IUrlMon_AsyncGetClassBits_Proxy(
IUrlMon* This,
REFCLSID rclsid,
LPCWSTR pszTYPE,
LPCWSTR pszExt,
DWORD dwFileVersionMS,
DWORD dwFileVersionLS,
LPCWSTR pszCodeBase,
IBindCtx *pbc,
DWORD dwClassContext,
REFIID riid,
DWORD flags);
void __RPC_STUB IUrlMon_AsyncGetClassBits_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IUrlMon_INTERFACE_DEFINED__ */
/*****************************************************************************
* IForegroundTransfer interface
*/
#ifndef __IForegroundTransfer_INTERFACE_DEFINED__
#define __IForegroundTransfer_INTERFACE_DEFINED__
DEFINE_GUID(IID_IForegroundTransfer, 0x00000145, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IForegroundTransfer : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE AllowForegroundTransfer(
void *lpvReserved) = 0;
};
#else
typedef struct IForegroundTransferVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IForegroundTransfer* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IForegroundTransfer* This);
ULONG (STDMETHODCALLTYPE *Release)(
IForegroundTransfer* This);
/*** IForegroundTransfer methods ***/
HRESULT (STDMETHODCALLTYPE *AllowForegroundTransfer)(
IForegroundTransfer* This,
void *lpvReserved);
END_INTERFACE
} IForegroundTransferVtbl;
interface IForegroundTransfer {
CONST_VTBL IForegroundTransferVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IForegroundTransfer_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IForegroundTransfer_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IForegroundTransfer_Release(This) (This)->lpVtbl->Release(This)
/*** IForegroundTransfer methods ***/
#define IForegroundTransfer_AllowForegroundTransfer(This,lpvReserved) (This)->lpVtbl->AllowForegroundTransfer(This,lpvReserved)
#endif
#endif
HRESULT STDMETHODCALLTYPE IForegroundTransfer_AllowForegroundTransfer_Proxy(
IForegroundTransfer* This,
void *lpvReserved);
void __RPC_STUB IForegroundTransfer_AllowForegroundTransfer_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IForegroundTransfer_INTERFACE_DEFINED__ */
/*****************************************************************************
* IAddrTrackingControl interface
*/
#ifndef __IAddrTrackingControl_INTERFACE_DEFINED__
#define __IAddrTrackingControl_INTERFACE_DEFINED__
typedef IAddrTrackingControl *LPADDRTRACKINGCONTROL;
DEFINE_GUID(IID_IAddrTrackingControl, 0x00000147, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IAddrTrackingControl : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE EnableCOMDynamicAddrTracking(
) = 0;
virtual HRESULT STDMETHODCALLTYPE DisableCOMDynamicAddrTracking(
) = 0;
};
#else
typedef struct IAddrTrackingControlVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IAddrTrackingControl* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IAddrTrackingControl* This);
ULONG (STDMETHODCALLTYPE *Release)(
IAddrTrackingControl* This);
/*** IAddrTrackingControl methods ***/
HRESULT (STDMETHODCALLTYPE *EnableCOMDynamicAddrTracking)(
IAddrTrackingControl* This);
HRESULT (STDMETHODCALLTYPE *DisableCOMDynamicAddrTracking)(
IAddrTrackingControl* This);
END_INTERFACE
} IAddrTrackingControlVtbl;
interface IAddrTrackingControl {
CONST_VTBL IAddrTrackingControlVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IAddrTrackingControl_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IAddrTrackingControl_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IAddrTrackingControl_Release(This) (This)->lpVtbl->Release(This)
/*** IAddrTrackingControl methods ***/
#define IAddrTrackingControl_EnableCOMDynamicAddrTracking(This) (This)->lpVtbl->EnableCOMDynamicAddrTracking(This)
#define IAddrTrackingControl_DisableCOMDynamicAddrTracking(This) (This)->lpVtbl->DisableCOMDynamicAddrTracking(This)
#endif
#endif
HRESULT STDMETHODCALLTYPE IAddrTrackingControl_EnableCOMDynamicAddrTracking_Proxy(
IAddrTrackingControl* This);
void __RPC_STUB IAddrTrackingControl_EnableCOMDynamicAddrTracking_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IAddrTrackingControl_DisableCOMDynamicAddrTracking_Proxy(
IAddrTrackingControl* This);
void __RPC_STUB IAddrTrackingControl_DisableCOMDynamicAddrTracking_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IAddrTrackingControl_INTERFACE_DEFINED__ */
/*****************************************************************************
* IAddrExclusionControl interface
*/
#ifndef __IAddrExclusionControl_INTERFACE_DEFINED__
#define __IAddrExclusionControl_INTERFACE_DEFINED__
typedef IAddrExclusionControl *LPADDREXCLUSIONCONTROL;
DEFINE_GUID(IID_IAddrExclusionControl, 0x00000148, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IAddrExclusionControl : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE GetCurrentAddrExclusionList(
REFIID riid,
void **ppEnumerator) = 0;
virtual HRESULT STDMETHODCALLTYPE UpdateAddrExclusionList(
IUnknown *pEnumerator) = 0;
};
#else
typedef struct IAddrExclusionControlVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IAddrExclusionControl* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IAddrExclusionControl* This);
ULONG (STDMETHODCALLTYPE *Release)(
IAddrExclusionControl* This);
/*** IAddrExclusionControl methods ***/
HRESULT (STDMETHODCALLTYPE *GetCurrentAddrExclusionList)(
IAddrExclusionControl* This,
REFIID riid,
void **ppEnumerator);
HRESULT (STDMETHODCALLTYPE *UpdateAddrExclusionList)(
IAddrExclusionControl* This,
IUnknown *pEnumerator);
END_INTERFACE
} IAddrExclusionControlVtbl;
interface IAddrExclusionControl {
CONST_VTBL IAddrExclusionControlVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IAddrExclusionControl_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IAddrExclusionControl_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IAddrExclusionControl_Release(This) (This)->lpVtbl->Release(This)
/*** IAddrExclusionControl methods ***/
#define IAddrExclusionControl_GetCurrentAddrExclusionList(This,riid,ppEnumerator) (This)->lpVtbl->GetCurrentAddrExclusionList(This,riid,ppEnumerator)
#define IAddrExclusionControl_UpdateAddrExclusionList(This,pEnumerator) (This)->lpVtbl->UpdateAddrExclusionList(This,pEnumerator)
#endif
#endif
HRESULT STDMETHODCALLTYPE IAddrExclusionControl_GetCurrentAddrExclusionList_Proxy(
IAddrExclusionControl* This,
REFIID riid,
void **ppEnumerator);
void __RPC_STUB IAddrExclusionControl_GetCurrentAddrExclusionList_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IAddrExclusionControl_UpdateAddrExclusionList_Proxy(
IAddrExclusionControl* This,
IUnknown *pEnumerator);
void __RPC_STUB IAddrExclusionControl_UpdateAddrExclusionList_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IAddrExclusionControl_INTERFACE_DEFINED__ */
typedef enum _APTTYPE {
APTTYPE_CURRENT = -1,
APTTYPE_STA = 0,
APTTYPE_MTA = 1,
APTTYPE_NA = 2,
APTTYPE_MAINSTA = 3
} APTTYPE;
typedef enum _THDTYPE {
THDTYPE_BLOCKMESSAGES = 0,
THDTYPE_PROCESSMESSAGES = 1
} THDTYPE;
/*****************************************************************************
* IComThreadingInfo interface
*/
#ifndef __IComThreadingInfo_INTERFACE_DEFINED__
#define __IComThreadingInfo_INTERFACE_DEFINED__
DEFINE_GUID(IID_IComThreadingInfo, 0x000001ce, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IComThreadingInfo : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE GetCurrentApartmentType(
APTTYPE *pAptType) = 0;
virtual HRESULT STDMETHODCALLTYPE GetCurrentThreadType(
THDTYPE *pThreadType) = 0;
virtual HRESULT STDMETHODCALLTYPE GetCurrentLogicalThreadId(
GUID *pguidLogicalThreadId) = 0;
virtual HRESULT STDMETHODCALLTYPE SetCurrentLogicalThreadId(
REFGUID rguid) = 0;
};
#else
typedef struct IComThreadingInfoVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IComThreadingInfo* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IComThreadingInfo* This);
ULONG (STDMETHODCALLTYPE *Release)(
IComThreadingInfo* This);
/*** IComThreadingInfo methods ***/
HRESULT (STDMETHODCALLTYPE *GetCurrentApartmentType)(
IComThreadingInfo* This,
APTTYPE *pAptType);
HRESULT (STDMETHODCALLTYPE *GetCurrentThreadType)(
IComThreadingInfo* This,
THDTYPE *pThreadType);
HRESULT (STDMETHODCALLTYPE *GetCurrentLogicalThreadId)(
IComThreadingInfo* This,
GUID *pguidLogicalThreadId);
HRESULT (STDMETHODCALLTYPE *SetCurrentLogicalThreadId)(
IComThreadingInfo* This,
REFGUID rguid);
END_INTERFACE
} IComThreadingInfoVtbl;
interface IComThreadingInfo {
CONST_VTBL IComThreadingInfoVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IComThreadingInfo_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IComThreadingInfo_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IComThreadingInfo_Release(This) (This)->lpVtbl->Release(This)
/*** IComThreadingInfo methods ***/
#define IComThreadingInfo_GetCurrentApartmentType(This,pAptType) (This)->lpVtbl->GetCurrentApartmentType(This,pAptType)
#define IComThreadingInfo_GetCurrentThreadType(This,pThreadType) (This)->lpVtbl->GetCurrentThreadType(This,pThreadType)
#define IComThreadingInfo_GetCurrentLogicalThreadId(This,pguidLogicalThreadId) (This)->lpVtbl->GetCurrentLogicalThreadId(This,pguidLogicalThreadId)
#define IComThreadingInfo_SetCurrentLogicalThreadId(This,rguid) (This)->lpVtbl->SetCurrentLogicalThreadId(This,rguid)
#endif
#endif
HRESULT STDMETHODCALLTYPE IComThreadingInfo_GetCurrentApartmentType_Proxy(
IComThreadingInfo* This,
APTTYPE *pAptType);
void __RPC_STUB IComThreadingInfo_GetCurrentApartmentType_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IComThreadingInfo_GetCurrentThreadType_Proxy(
IComThreadingInfo* This,
THDTYPE *pThreadType);
void __RPC_STUB IComThreadingInfo_GetCurrentThreadType_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IComThreadingInfo_GetCurrentLogicalThreadId_Proxy(
IComThreadingInfo* This,
GUID *pguidLogicalThreadId);
void __RPC_STUB IComThreadingInfo_GetCurrentLogicalThreadId_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IComThreadingInfo_SetCurrentLogicalThreadId_Proxy(
IComThreadingInfo* This,
REFGUID rguid);
void __RPC_STUB IComThreadingInfo_SetCurrentLogicalThreadId_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IComThreadingInfo_INTERFACE_DEFINED__ */
/*****************************************************************************
* IProcessInitControl interface
*/
#ifndef __IProcessInitControl_INTERFACE_DEFINED__
#define __IProcessInitControl_INTERFACE_DEFINED__
DEFINE_GUID(IID_IProcessInitControl, 0x72380d55, 0x8d2b, 0x43a3, 0x85,0x13, 0x2b,0x6e,0xf3,0x14,0x34,0xe9);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IProcessInitControl : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE ResetInitializerTimeout(
DWORD dwSecondsRemaining) = 0;
};
#else
typedef struct IProcessInitControlVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IProcessInitControl* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IProcessInitControl* This);
ULONG (STDMETHODCALLTYPE *Release)(
IProcessInitControl* This);
/*** IProcessInitControl methods ***/
HRESULT (STDMETHODCALLTYPE *ResetInitializerTimeout)(
IProcessInitControl* This,
DWORD dwSecondsRemaining);
END_INTERFACE
} IProcessInitControlVtbl;
interface IProcessInitControl {
CONST_VTBL IProcessInitControlVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IProcessInitControl_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IProcessInitControl_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IProcessInitControl_Release(This) (This)->lpVtbl->Release(This)
/*** IProcessInitControl methods ***/
#define IProcessInitControl_ResetInitializerTimeout(This,dwSecondsRemaining) (This)->lpVtbl->ResetInitializerTimeout(This,dwSecondsRemaining)
#endif
#endif
HRESULT STDMETHODCALLTYPE IProcessInitControl_ResetInitializerTimeout_Proxy(
IProcessInitControl* This,
DWORD dwSecondsRemaining);
void __RPC_STUB IProcessInitControl_ResetInitializerTimeout_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IProcessInitControl_INTERFACE_DEFINED__ */
/*****************************************************************************
* IInitializeSpy interface
*/
#ifndef __IInitializeSpy_INTERFACE_DEFINED__
#define __IInitializeSpy_INTERFACE_DEFINED__
typedef IInitializeSpy *LPINITIALIZESPY;
DEFINE_GUID(IID_IInitializeSpy, 0x00000034, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IInitializeSpy : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE PreInitialize(
DWORD dwCoInit,
DWORD dwCurThreadAptRefs) = 0;
virtual HRESULT STDMETHODCALLTYPE PostInitialize(
HRESULT hrCoInit,
DWORD dwCoInit,
DWORD dwNewThreadAptRefs) = 0;
virtual HRESULT STDMETHODCALLTYPE PreUninitialize(
DWORD dwCurThreadAptRefs) = 0;
virtual HRESULT STDMETHODCALLTYPE PostUninitialize(
DWORD dwNewThreadAptRefs) = 0;
};
#else
typedef struct IInitializeSpyVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IInitializeSpy* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IInitializeSpy* This);
ULONG (STDMETHODCALLTYPE *Release)(
IInitializeSpy* This);
/*** IInitializeSpy methods ***/
HRESULT (STDMETHODCALLTYPE *PreInitialize)(
IInitializeSpy* This,
DWORD dwCoInit,
DWORD dwCurThreadAptRefs);
HRESULT (STDMETHODCALLTYPE *PostInitialize)(
IInitializeSpy* This,
HRESULT hrCoInit,
DWORD dwCoInit,
DWORD dwNewThreadAptRefs);
HRESULT (STDMETHODCALLTYPE *PreUninitialize)(
IInitializeSpy* This,
DWORD dwCurThreadAptRefs);
HRESULT (STDMETHODCALLTYPE *PostUninitialize)(
IInitializeSpy* This,
DWORD dwNewThreadAptRefs);
END_INTERFACE
} IInitializeSpyVtbl;
interface IInitializeSpy {
CONST_VTBL IInitializeSpyVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IInitializeSpy_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IInitializeSpy_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IInitializeSpy_Release(This) (This)->lpVtbl->Release(This)
/*** IInitializeSpy methods ***/
#define IInitializeSpy_PreInitialize(This,dwCoInit,dwCurThreadAptRefs) (This)->lpVtbl->PreInitialize(This,dwCoInit,dwCurThreadAptRefs)
#define IInitializeSpy_PostInitialize(This,hrCoInit,dwCoInit,dwNewThreadAptRefs) (This)->lpVtbl->PostInitialize(This,hrCoInit,dwCoInit,dwNewThreadAptRefs)
#define IInitializeSpy_PreUninitialize(This,dwCurThreadAptRefs) (This)->lpVtbl->PreUninitialize(This,dwCurThreadAptRefs)
#define IInitializeSpy_PostUninitialize(This,dwNewThreadAptRefs) (This)->lpVtbl->PostUninitialize(This,dwNewThreadAptRefs)
#endif
#endif
HRESULT STDMETHODCALLTYPE IInitializeSpy_PreInitialize_Proxy(
IInitializeSpy* This,
DWORD dwCoInit,
DWORD dwCurThreadAptRefs);
void __RPC_STUB IInitializeSpy_PreInitialize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IInitializeSpy_PostInitialize_Proxy(
IInitializeSpy* This,
HRESULT hrCoInit,
DWORD dwCoInit,
DWORD dwNewThreadAptRefs);
void __RPC_STUB IInitializeSpy_PostInitialize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IInitializeSpy_PreUninitialize_Proxy(
IInitializeSpy* This,
DWORD dwCurThreadAptRefs);
void __RPC_STUB IInitializeSpy_PreUninitialize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IInitializeSpy_PostUninitialize_Proxy(
IInitializeSpy* This,
DWORD dwNewThreadAptRefs);
void __RPC_STUB IInitializeSpy_PostUninitialize_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IInitializeSpy_INTERFACE_DEFINED__ */
/*****************************************************************************
* IThumbnailExtractor interface
*/
#ifndef __IThumbnailExtractor_INTERFACE_DEFINED__
#define __IThumbnailExtractor_INTERFACE_DEFINED__
DEFINE_GUID(IID_IThumbnailExtractor, 0x969dc708, 0x5c76, 0x11d1, 0x8d,0x86, 0x00,0x00,0xf8,0x04,0xb0,0x57);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IThumbnailExtractor : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE ExtractThumbnail(
IStorage *pStg,
ULONG ulLength,
ULONG ulHeight,
ULONG *pulOutputLength,
ULONG *pulOutputHeight,
HBITMAP *phOutputBitmap) = 0;
virtual HRESULT STDMETHODCALLTYPE OnFileUpdated(
IStorage *pStg) = 0;
};
#else
typedef struct IThumbnailExtractorVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IThumbnailExtractor* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IThumbnailExtractor* This);
ULONG (STDMETHODCALLTYPE *Release)(
IThumbnailExtractor* This);
/*** IThumbnailExtractor methods ***/
HRESULT (STDMETHODCALLTYPE *ExtractThumbnail)(
IThumbnailExtractor* This,
IStorage *pStg,
ULONG ulLength,
ULONG ulHeight,
ULONG *pulOutputLength,
ULONG *pulOutputHeight,
HBITMAP *phOutputBitmap);
HRESULT (STDMETHODCALLTYPE *OnFileUpdated)(
IThumbnailExtractor* This,
IStorage *pStg);
END_INTERFACE
} IThumbnailExtractorVtbl;
interface IThumbnailExtractor {
CONST_VTBL IThumbnailExtractorVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IThumbnailExtractor_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IThumbnailExtractor_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IThumbnailExtractor_Release(This) (This)->lpVtbl->Release(This)
/*** IThumbnailExtractor methods ***/
#define IThumbnailExtractor_ExtractThumbnail(This,pStg,ulLength,ulHeight,pulOutputLength,pulOutputHeight,phOutputBitmap) (This)->lpVtbl->ExtractThumbnail(This,pStg,ulLength,ulHeight,pulOutputLength,pulOutputHeight,phOutputBitmap)
#define IThumbnailExtractor_OnFileUpdated(This,pStg) (This)->lpVtbl->OnFileUpdated(This,pStg)
#endif
#endif
HRESULT STDMETHODCALLTYPE IThumbnailExtractor_ExtractThumbnail_Proxy(
IThumbnailExtractor* This,
IStorage *pStg,
ULONG ulLength,
ULONG ulHeight,
ULONG *pulOutputLength,
ULONG *pulOutputHeight,
HBITMAP *phOutputBitmap);
void __RPC_STUB IThumbnailExtractor_ExtractThumbnail_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IThumbnailExtractor_OnFileUpdated_Proxy(
IThumbnailExtractor* This,
IStorage *pStg);
void __RPC_STUB IThumbnailExtractor_OnFileUpdated_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IThumbnailExtractor_INTERFACE_DEFINED__ */
#ifdef USE_COM_CONTEXT_DEF
typedef DWORD CPFLAGS;
typedef struct tagContextProperty {
GUID policyId;
CPFLAGS flags;
IUnknown *pUnk;
} ContextProperty;
/*****************************************************************************
* IEnumContextProps interface
*/
#ifndef __IEnumContextProps_INTERFACE_DEFINED__
#define __IEnumContextProps_INTERFACE_DEFINED__
typedef IEnumContextProps *LPENUMCONTEXTPROPS;
DEFINE_GUID(IID_IEnumContextProps, 0x000001c1, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IEnumContextProps : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE Next(
ULONG celt,
ContextProperty *pContextProperties,
ULONG *pceltFetched) = 0;
virtual HRESULT STDMETHODCALLTYPE Skip(
ULONG celt) = 0;
virtual HRESULT STDMETHODCALLTYPE Reset(
) = 0;
virtual HRESULT STDMETHODCALLTYPE Clone(
IEnumContextProps **ppEnumContextProps) = 0;
virtual HRESULT STDMETHODCALLTYPE Count(
ULONG *pcelt) = 0;
};
#else
typedef struct IEnumContextPropsVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IEnumContextProps* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IEnumContextProps* This);
ULONG (STDMETHODCALLTYPE *Release)(
IEnumContextProps* This);
/*** IEnumContextProps methods ***/
HRESULT (STDMETHODCALLTYPE *Next)(
IEnumContextProps* This,
ULONG celt,
ContextProperty *pContextProperties,
ULONG *pceltFetched);
HRESULT (STDMETHODCALLTYPE *Skip)(
IEnumContextProps* This,
ULONG celt);
HRESULT (STDMETHODCALLTYPE *Reset)(
IEnumContextProps* This);
HRESULT (STDMETHODCALLTYPE *Clone)(
IEnumContextProps* This,
IEnumContextProps **ppEnumContextProps);
HRESULT (STDMETHODCALLTYPE *Count)(
IEnumContextProps* This,
ULONG *pcelt);
END_INTERFACE
} IEnumContextPropsVtbl;
interface IEnumContextProps {
CONST_VTBL IEnumContextPropsVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IEnumContextProps_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IEnumContextProps_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IEnumContextProps_Release(This) (This)->lpVtbl->Release(This)
/*** IEnumContextProps methods ***/
#define IEnumContextProps_Next(This,celt,pContextProperties,pceltFetched) (This)->lpVtbl->Next(This,celt,pContextProperties,pceltFetched)
#define IEnumContextProps_Skip(This,celt) (This)->lpVtbl->Skip(This,celt)
#define IEnumContextProps_Reset(This) (This)->lpVtbl->Reset(This)
#define IEnumContextProps_Clone(This,ppEnumContextProps) (This)->lpVtbl->Clone(This,ppEnumContextProps)
#define IEnumContextProps_Count(This,pcelt) (This)->lpVtbl->Count(This,pcelt)
#endif
#endif
HRESULT STDMETHODCALLTYPE IEnumContextProps_Next_Proxy(
IEnumContextProps* This,
ULONG celt,
ContextProperty *pContextProperties,
ULONG *pceltFetched);
void __RPC_STUB IEnumContextProps_Next_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumContextProps_Skip_Proxy(
IEnumContextProps* This,
ULONG celt);
void __RPC_STUB IEnumContextProps_Skip_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumContextProps_Reset_Proxy(
IEnumContextProps* This);
void __RPC_STUB IEnumContextProps_Reset_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumContextProps_Clone_Proxy(
IEnumContextProps* This,
IEnumContextProps **ppEnumContextProps);
void __RPC_STUB IEnumContextProps_Clone_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IEnumContextProps_Count_Proxy(
IEnumContextProps* This,
ULONG *pcelt);
void __RPC_STUB IEnumContextProps_Count_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IEnumContextProps_INTERFACE_DEFINED__ */
/*****************************************************************************
* IContext interface
*/
#ifndef __IContext_INTERFACE_DEFINED__
#define __IContext_INTERFACE_DEFINED__
DEFINE_GUID(IID_IContext, 0x000001c0, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IContext : public IUnknown
{
virtual HRESULT STDMETHODCALLTYPE SetProperty(
REFGUID policyId,
CPFLAGS flags,
IUnknown *pUnk) = 0;
virtual HRESULT STDMETHODCALLTYPE RemoveProperty(
REFGUID policyId) = 0;
virtual HRESULT STDMETHODCALLTYPE GetProperty(
REFGUID guid,
CPFLAGS *pFlags,
IUnknown **ppUnk) = 0;
virtual HRESULT STDMETHODCALLTYPE EnumContextProps(
IEnumContextProps **ppEnumContextProps) = 0;
};
#else
typedef struct IContextVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IContext* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IContext* This);
ULONG (STDMETHODCALLTYPE *Release)(
IContext* This);
/*** IContext methods ***/
HRESULT (STDMETHODCALLTYPE *SetProperty)(
IContext* This,
REFGUID policyId,
CPFLAGS flags,
IUnknown *pUnk);
HRESULT (STDMETHODCALLTYPE *RemoveProperty)(
IContext* This,
REFGUID policyId);
HRESULT (STDMETHODCALLTYPE *GetProperty)(
IContext* This,
REFGUID guid,
CPFLAGS *pFlags,
IUnknown **ppUnk);
HRESULT (STDMETHODCALLTYPE *EnumContextProps)(
IContext* This,
IEnumContextProps **ppEnumContextProps);
END_INTERFACE
} IContextVtbl;
interface IContext {
CONST_VTBL IContextVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IContext_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IContext_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IContext_Release(This) (This)->lpVtbl->Release(This)
/*** IContext methods ***/
#define IContext_SetProperty(This,policyId,flags,pUnk) (This)->lpVtbl->SetProperty(This,policyId,flags,pUnk)
#define IContext_RemoveProperty(This,policyId) (This)->lpVtbl->RemoveProperty(This,policyId)
#define IContext_GetProperty(This,guid,pFlags,ppUnk) (This)->lpVtbl->GetProperty(This,guid,pFlags,ppUnk)
#define IContext_EnumContextProps(This,ppEnumContextProps) (This)->lpVtbl->EnumContextProps(This,ppEnumContextProps)
#endif
#endif
HRESULT STDMETHODCALLTYPE IContext_SetProperty_Proxy(
IContext* This,
REFGUID policyId,
CPFLAGS flags,
IUnknown *pUnk);
void __RPC_STUB IContext_SetProperty_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IContext_RemoveProperty_Proxy(
IContext* This,
REFGUID policyId);
void __RPC_STUB IContext_RemoveProperty_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IContext_GetProperty_Proxy(
IContext* This,
REFGUID guid,
CPFLAGS *pFlags,
IUnknown **ppUnk);
void __RPC_STUB IContext_GetProperty_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
HRESULT STDMETHODCALLTYPE IContext_EnumContextProps_Proxy(
IContext* This,
IEnumContextProps **ppEnumContextProps);
void __RPC_STUB IContext_EnumContextProps_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IContext_INTERFACE_DEFINED__ */
/*****************************************************************************
* IObjContext interface
*/
#ifndef __IObjContext_INTERFACE_DEFINED__
#define __IObjContext_INTERFACE_DEFINED__
DEFINE_GUID(IID_IObjContext, 0x000001c6, 0x0000, 0x0000, 0xc0,0x00, 0x00,0x00,0x00,0x00,0x00,0x46);
#if defined(__cplusplus) && !defined(CINTERFACE)
interface IObjContext : public IContext
{
virtual void STDMETHODCALLTYPE Reserved1(
) = 0;
virtual void STDMETHODCALLTYPE Reserved2(
) = 0;
virtual void STDMETHODCALLTYPE Reserved3(
) = 0;
virtual void STDMETHODCALLTYPE Reserved4(
) = 0;
virtual void STDMETHODCALLTYPE Reserved5(
) = 0;
virtual void STDMETHODCALLTYPE Reserved6(
) = 0;
virtual void STDMETHODCALLTYPE Reserved7(
) = 0;
};
#else
typedef struct IObjContextVtbl {
BEGIN_INTERFACE
/*** IUnknown methods ***/
HRESULT (STDMETHODCALLTYPE *QueryInterface)(
IObjContext* This,
REFIID riid,
void **ppvObject);
ULONG (STDMETHODCALLTYPE *AddRef)(
IObjContext* This);
ULONG (STDMETHODCALLTYPE *Release)(
IObjContext* This);
/*** IContext methods ***/
HRESULT (STDMETHODCALLTYPE *SetProperty)(
IObjContext* This,
REFGUID policyId,
CPFLAGS flags,
IUnknown *pUnk);
HRESULT (STDMETHODCALLTYPE *RemoveProperty)(
IObjContext* This,
REFGUID policyId);
HRESULT (STDMETHODCALLTYPE *GetProperty)(
IObjContext* This,
REFGUID guid,
CPFLAGS *pFlags,
IUnknown **ppUnk);
HRESULT (STDMETHODCALLTYPE *EnumContextProps)(
IObjContext* This,
IEnumContextProps **ppEnumContextProps);
/*** IObjContext methods ***/
void (STDMETHODCALLTYPE *Reserved1)(
IObjContext* This);
void (STDMETHODCALLTYPE *Reserved2)(
IObjContext* This);
void (STDMETHODCALLTYPE *Reserved3)(
IObjContext* This);
void (STDMETHODCALLTYPE *Reserved4)(
IObjContext* This);
void (STDMETHODCALLTYPE *Reserved5)(
IObjContext* This);
void (STDMETHODCALLTYPE *Reserved6)(
IObjContext* This);
void (STDMETHODCALLTYPE *Reserved7)(
IObjContext* This);
END_INTERFACE
} IObjContextVtbl;
interface IObjContext {
CONST_VTBL IObjContextVtbl* lpVtbl;
};
#ifdef COBJMACROS
/*** IUnknown methods ***/
#define IObjContext_QueryInterface(This,riid,ppvObject) (This)->lpVtbl->QueryInterface(This,riid,ppvObject)
#define IObjContext_AddRef(This) (This)->lpVtbl->AddRef(This)
#define IObjContext_Release(This) (This)->lpVtbl->Release(This)
/*** IContext methods ***/
#define IObjContext_SetProperty(This,policyId,flags,pUnk) (This)->lpVtbl->SetProperty(This,policyId,flags,pUnk)
#define IObjContext_RemoveProperty(This,policyId) (This)->lpVtbl->RemoveProperty(This,policyId)
#define IObjContext_GetProperty(This,guid,pFlags,ppUnk) (This)->lpVtbl->GetProperty(This,guid,pFlags,ppUnk)
#define IObjContext_EnumContextProps(This,ppEnumContextProps) (This)->lpVtbl->EnumContextProps(This,ppEnumContextProps)
/*** IObjContext methods ***/
#define IObjContext_Reserved1(This) (This)->lpVtbl->Reserved1(This)
#define IObjContext_Reserved2(This) (This)->lpVtbl->Reserved2(This)
#define IObjContext_Reserved3(This) (This)->lpVtbl->Reserved3(This)
#define IObjContext_Reserved4(This) (This)->lpVtbl->Reserved4(This)
#define IObjContext_Reserved5(This) (This)->lpVtbl->Reserved5(This)
#define IObjContext_Reserved6(This) (This)->lpVtbl->Reserved6(This)
#define IObjContext_Reserved7(This) (This)->lpVtbl->Reserved7(This)
#endif
#endif
void STDMETHODCALLTYPE IObjContext_Reserved1_Proxy(
IObjContext* This);
void __RPC_STUB IObjContext_Reserved1_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IObjContext_Reserved2_Proxy(
IObjContext* This);
void __RPC_STUB IObjContext_Reserved2_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IObjContext_Reserved3_Proxy(
IObjContext* This);
void __RPC_STUB IObjContext_Reserved3_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IObjContext_Reserved4_Proxy(
IObjContext* This);
void __RPC_STUB IObjContext_Reserved4_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IObjContext_Reserved5_Proxy(
IObjContext* This);
void __RPC_STUB IObjContext_Reserved5_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IObjContext_Reserved6_Proxy(
IObjContext* This);
void __RPC_STUB IObjContext_Reserved6_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
void STDMETHODCALLTYPE IObjContext_Reserved7_Proxy(
IObjContext* This);
void __RPC_STUB IObjContext_Reserved7_Stub(
IRpcStubBuffer* This,
IRpcChannelBuffer* pRpcChannelBuffer,
PRPC_MESSAGE pRpcMessage,
DWORD* pdwStubPhase);
#endif /* __IObjContext_INTERFACE_DEFINED__ */
#endif /* defined USE_COM_CONTEXT_DEF */
/* Begin additional prototypes for all interfaces */
ULONG __RPC_USER SNB_UserSize (ULONG *, ULONG, SNB *);
unsigned char * __RPC_USER SNB_UserMarshal (ULONG *, unsigned char *, SNB *);
unsigned char * __RPC_USER SNB_UserUnmarshal(ULONG *, unsigned char *, SNB *);
void __RPC_USER SNB_UserFree (ULONG *, SNB *);
ULONG __RPC_USER CLIPFORMAT_UserSize (ULONG *, ULONG, CLIPFORMAT *);
unsigned char * __RPC_USER CLIPFORMAT_UserMarshal (ULONG *, unsigned char *, CLIPFORMAT *);
unsigned char * __RPC_USER CLIPFORMAT_UserUnmarshal(ULONG *, unsigned char *, CLIPFORMAT *);
void __RPC_USER CLIPFORMAT_UserFree (ULONG *, CLIPFORMAT *);
ULONG __RPC_USER STGMEDIUM_UserSize (ULONG *, ULONG, STGMEDIUM *);
unsigned char * __RPC_USER STGMEDIUM_UserMarshal (ULONG *, unsigned char *, STGMEDIUM *);
unsigned char * __RPC_USER STGMEDIUM_UserUnmarshal(ULONG *, unsigned char *, STGMEDIUM *);
void __RPC_USER STGMEDIUM_UserFree (ULONG *, STGMEDIUM *);
ULONG __RPC_USER ASYNC_STGMEDIUM_UserSize (ULONG *, ULONG, ASYNC_STGMEDIUM *);
unsigned char * __RPC_USER ASYNC_STGMEDIUM_UserMarshal (ULONG *, unsigned char *, ASYNC_STGMEDIUM *);
unsigned char * __RPC_USER ASYNC_STGMEDIUM_UserUnmarshal(ULONG *, unsigned char *, ASYNC_STGMEDIUM *);
void __RPC_USER ASYNC_STGMEDIUM_UserFree (ULONG *, ASYNC_STGMEDIUM *);
ULONG __RPC_USER FLAG_STGMEDIUM_UserSize (ULONG *, ULONG, FLAG_STGMEDIUM *);
unsigned char * __RPC_USER FLAG_STGMEDIUM_UserMarshal (ULONG *, unsigned char *, FLAG_STGMEDIUM *);
unsigned char * __RPC_USER FLAG_STGMEDIUM_UserUnmarshal(ULONG *, unsigned char *, FLAG_STGMEDIUM *);
void __RPC_USER FLAG_STGMEDIUM_UserFree (ULONG *, FLAG_STGMEDIUM *);
ULONG __RPC_USER HBITMAP_UserSize (ULONG *, ULONG, HBITMAP *);
unsigned char * __RPC_USER HBITMAP_UserMarshal (ULONG *, unsigned char *, HBITMAP *);
unsigned char * __RPC_USER HBITMAP_UserUnmarshal(ULONG *, unsigned char *, HBITMAP *);
void __RPC_USER HBITMAP_UserFree (ULONG *, HBITMAP *);
/* End additional prototypes */
#ifdef __cplusplus
}
#endif
#endif /* __WIDL_OBJIDL_H */
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 2,301
|
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