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Coherent control of flexural vibrations in dual-nanoweb fibers using phase-modulated two-frequency light
Coherent control of the resonant response in spatially extended optomechanical structures is complicated by the fact that the optical drive is affected by the back-action from the generated phonons. Here we report a new approach to coherent control based on stimulated Raman-like scattering, in which the optical press...
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Static and Dynamic Magnetic Properties of FeMn/Pt Multilayers
Recently we have demonstrated the presence of spin-orbit toque in FeMn/Pt multilayers which, in combination with the anisotropy field, is able to rotate its magnetization consecutively from 0o to 360o without any external field. Here, we report on an investigation of static and dynamic magnetic properties of FeMn/Pt ...
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Ultraproducts of crossed product von Neumann algebras
We study a relationship between the ultraproduct of a crossed product von Neumann algebra and the crossed product of an ultraproduct von Neumann algebra. As an application, the continuous core of an ultraproduct von Neumann algebra is described.
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Concept Drift Detection and Adaptation with Hierarchical Hypothesis Testing
A fundamental issue for statistical classification models in a streaming environment is that the joint distribution between predictor and response variables changes over time (a phenomenon also known as concept drifts), such that their classification performance deteriorates dramatically. In this paper, we first pres...
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Interval-based Prediction Uncertainty Bound Computation in Learning with Missing Values
The problem of machine learning with missing values is common in many areas. A simple approach is to first construct a dataset without missing values simply by discarding instances with missing entries or by imputing a fixed value for each missing entry, and then train a prediction model with the new dataset. A drawb...
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Methods for Interpreting and Understanding Deep Neural Networks
This paper provides an entry point to the problem of interpreting a deep neural network model and explaining its predictions. It is based on a tutorial given at ICASSP 2017. It introduces some recently proposed techniques of interpretation, along with theory, tricks and recommendations, to make most efficient use of ...
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Passive Classification of Source Printer using Text-line-level Geometric Distortion Signatures from Scanned Images of Printed Documents
In this digital era, one thing that still holds the convention is a printed archive. Printed documents find their use in many critical domains such as contract papers, legal tenders and proof of identity documents. As more advanced printing, scanning and image editing techniques are becoming available, forgeries on t...
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The duration of load effect in lumber as stochastic degradation
This paper proposes a gamma process for modelling the damage that accumulates over time in the lumber used in structural engineering applications when stress is applied. The model separates the stochastic processes representing features internal to the piece of lumber on the one hand, from those representing external...
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Partial Bridging of Vaccine Efficacy to New Populations
Suppose one has data from one or more completed vaccine efficacy trials and wishes to estimate the efficacy in a new setting. Often logistical or ethical considerations make running another efficacy trial impossible. Fortunately, if there is a biomarker that is the primary modifier of efficacy, then the biomarker-con...
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An induced map between rationalized classifying spaces for fibrations
Let $B{ aut}_1X$ be the Dold-Lashof classifying space of orientable fibrations with fiber $X$. For a rationally weakly trivial map $f:X\to Y$, our strictly induced map $a_f: (Baut_1X)_0\to (Baut_1Y)_0$ induces a natural map from a $X_0$-fibration to a $Y_0$-fibration. It is given by a map between the differential gra...
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The Statistical Recurrent Unit
Sophisticated gated recurrent neural network architectures like LSTMs and GRUs have been shown to be highly effective in a myriad of applications. We develop an un-gated unit, the statistical recurrent unit (SRU), that is able to learn long term dependencies in data by only keeping moving averages of statistics. The ...
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Many-body localization in the droplet spectrum of the random XXZ quantum spin chain
We study many-body localization properties of the disordered XXZ spin chain in the Ising phase. Disorder is introduced via a random magnetic field in the $z$-direction. We prove a strong form of dynamical exponential clustering for eigenstates in the droplet spectrum: For any pair of local observables separated by a ...
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FastDeepIoT: Towards Understanding and Optimizing Neural Network Execution Time on Mobile and Embedded Devices
Deep neural networks show great potential as solutions to many sensing application problems, but their excessive resource demand slows down execution time, pausing a serious impediment to deployment on low-end devices. To address this challenge, recent literature focused on compressing neural network size to improve ...
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Robust MPC for tracking of nonholonomic robots with additive disturbances
In this paper, two robust model predictive control (MPC) schemes are proposed for tracking control of nonholonomic systems with bounded disturbances: tube-MPC and nominal robust MPC (NRMPC). In tube-MPC, the control signal consists of a control action and a nonlinear feedback law based on the deviation of the actual ...
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Investigation on the use of Hidden-Markov Models in automatic transcription of music
Hidden Markov Models (HMMs) are a ubiquitous tool to model time series data, and have been widely used in two main tasks of Automatic Music Transcription (AMT): note segmentation, i.e. identifying the played notes after a multi-pitch estimation, and sequential post-processing, i.e. correcting note segmentation using ...
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Network archaeology: phase transition in the recoverability of network history
Network growth processes can be understood as generative models of the structure and history of complex networks. This point of view naturally leads to the problem of network archaeology: Reconstructing all the past states of a network from its structure---a difficult permutation inference problem. In this paper, we ...
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Big Data, Data Science, and Civil Rights
Advances in data analytics bring with them civil rights implications. Data-driven and algorithmic decision making increasingly determine how businesses target advertisements to consumers, how police departments monitor individuals or groups, how banks decide who gets a loan and who does not, how employers hire, how c...
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Global well-posedness for 2-D Boussinesq system with the temperature-dependent viscosity and supercritical dissipation
The present paper is dedicated to the global well-posedness issue for the Boussinesq system with the temperature-dependent viscosity in $\mathbb{R}^2.$ We aim at extending the work by Abidi and Zhang ( Adv. Math. 2017 (305) 1202--1249 ) to a supercritical dissipation for temperature.
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CO~($J = 1-0$) Observations of a Filamentary Molecular Cloud in the Galactic Region Centered at $l = 150\arcdeg, b = 3.5\arcdeg$
We present large-field (4.25~$\times$~3.75 deg$^2$) mapping observations toward the Galactic region centered at $l = 150\arcdeg, b = 3.5\arcdeg$ in the $J = 1-0$ emission line of CO isotopologues ($^{12}$CO, $^{13}$CO, and C$^{18}$O), using the 13.7 m millimeter-wavelength telescope of the Purple Mountain Observatory...
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Leveraging Deep Neural Network Activation Entropy to cope with Unseen Data in Speech Recognition
Unseen data conditions can inflict serious performance degradation on systems relying on supervised machine learning algorithms. Because data can often be unseen, and because traditional machine learning algorithms are trained in a supervised manner, unsupervised adaptation techniques must be used to adapt the model ...
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Asymmetric Preheating
We study the generation of the matter-antimatter asymmetry during bosonic preheating, focusing on the sources of the asymmetry. If the asymmetry appears in the multiplication factor of the resonant particle production, the matter-antimatter ratio will grow during preheating. On the other hand, if the asymmetry does n...
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A multi-device dataset for urban acoustic scene classification
This paper introduces the acoustic scene classification task of DCASE 2018 Challenge and the TUT Urban Acoustic Scenes 2018 dataset provided for the task, and evaluates the performance of a baseline system in the task. As in previous years of the challenge, the task is defined for classification of short audio sample...
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Asymptotically preserving particle-in-cell methods for inhomogenous strongly magnetized plasmas
We propose a class of Particle-In-Cell (PIC) methods for the Vlasov-Poisson system with a strong and inhomogeneous external magnetic field with fixed direction, where we focus on the motion of particles in the plane orthogonal to the magnetic field (so-called poloidal directions). In this regime, the time step can be...
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Cluster Failure Revisited: Impact of First Level Design and Data Quality on Cluster False Positive Rates
Methodological research rarely generates a broad interest, yet our work on the validity of cluster inference methods for functional magnetic resonance imaging (fMRI) created intense discussion on both the minutia of our approach and its implications for the discipline. In the present work, we take on various critique...
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An Integrated Simulator and Dataset that Combines Grasping and Vision for Deep Learning
Deep learning is an established framework for learning hierarchical data representations. While compute power is in abundance, one of the main challenges in applying this framework to robotic grasping has been obtaining the amount of data needed to learn these representations, and structuring the data to the task at ...
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A Recursive Bayesian Approach To Describe Retinal Vasculature Geometry
Demographic studies suggest that changes in the retinal vasculature geometry, especially in vessel width, are associated with the incidence or progression of eye-related or systemic diseases. To date, the main information source for width estimation from fundus images has been the intensity profile between vessel edg...
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Quantum Harmonic Analysis of the Density Matrix: Basics
In this Review we will study rigorously the notion of mixed states and their density matrices. We mostly give complete proofs. We will also discuss the quantum-mechanical consequences of possible variations of Planck's constant h. This Review has been written having in mind two readerships: mathematical physicists an...
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The bromodomain-containing protein Ibd1 links multiple chromatin related protein complexes to highly expressed genes in Tetrahymena thermophila
Background: The chromatin remodelers of the SWI/SNF family are critical transcriptional regulators. Recognition of lysine acetylation through a bromodomain (BRD) component is key to SWI/SNF function; in most eukaryotes, this function is attributed to SNF2/Brg1. Results: Using affinity purification coupled to mass spe...
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A Bayesian Perspective on Generalization and Stochastic Gradient Descent
We consider two questions at the heart of machine learning; how can we predict if a minimum will generalize to the test set, and why does stochastic gradient descent find minima that generalize well? Our work responds to Zhang et al. (2016), who showed deep neural networks can easily memorize randomly labeled trainin...
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Higher Derivative Field Theories: Degeneracy Conditions and Classes
We provide a full analysis of ghost free higher derivative field theories with coupled degrees of freedom. Assuming the absence of gauge symmetries, we derive the degeneracy conditions in order to evade the Ostrogradsky ghosts, and analyze which (non)trivial classes of solutions this allows for. It is shown explicitl...
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3D Morphology Prediction of Progressive Spinal Deformities from Probabilistic Modeling of Discriminant Manifolds
We introduce a novel approach for predicting the progression of adolescent idiopathic scoliosis from 3D spine models reconstructed from biplanar X-ray images. Recent progress in machine learning have allowed to improve classification and prognosis rates, but lack a probabilistic framework to measure uncertainty in th...
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The Galaxy's Veil of Excited Hydrogen
Many of the baryons in our Galaxy probably lie outside the well known disk and bulge components. Despite a wealth of evidence for the presence of some gas in galactic halos, including absorption line systems in the spectra of quasars, high velocity neutral hydrogen clouds in our Galaxy halo, line emitting ionised hyd...
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Photonic-chip supercontinuum with tailored spectra for precision frequency metrology
Supercontinuum generation using chip-integrated photonic waveguides is a powerful approach for spectrally broadening pulsed laser sources with very low pulse energies and compact form factors. When pumped with a mode-locked laser frequency comb, these waveguides can coherently expand the comb spectrum to more than an...
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Endogenizing Epistemic Actions
Through a series of examples, we illustrate some important drawbacks that the action logic framework suffers from in its ability to represent the dynamics of information updates. We argue that these problems stem from the fact that the action model, a central construct designed to encode agents' uncertainty about act...
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The Meaning of Memory Safety
We give a rigorous characterization of what it means for a programming language to be memory safe, capturing the intuition that memory safety supports local reasoning about state. We formalize this principle in two ways. First, we show how a small memory-safe language validates a noninterference property: a program c...
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The Flexible Group Spatial Keyword Query
We present a new class of service for location based social networks, called the Flexible Group Spatial Keyword Query, which enables a group of users to collectively find a point of interest (POI) that optimizes an aggregate cost function combining both spatial distances and keyword similarities. In addition, our que...
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Undersampled windowed exponentials and their applications
We characterize the completeness and frame/basis property of a union of under-sampled windowed exponentials of the form $$ {\mathcal F}(g): =\{e^{2\pi i n x}: n\ge 0\}\cup \{g(x)e^{2\pi i nx}: n<0\} $$ for $L^2[-1/2,1/2]$ by the spectra of the Toeplitz operators with symbol $g$. Using this characterization, we classi...
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Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
Deep learning models are often successfully trained using gradient descent, despite the worst case hardness of the underlying non-convex optimization problem. The key question is then under what conditions can one prove that optimization will succeed. Here we provide a strong result of this kind. We consider a neural...
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Detection of irregular QRS complexes using Hermite Transform and Support Vector Machine
Computer based recognition and detection of abnormalities in ECG signals is proposed. For this purpose, the Support Vector Machines (SVM) are combined with the advantages of Hermite transform representation. SVM represent a special type of classification techniques commonly used in medical applications. Automatic cla...
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On the Lipschitz equivalence of self-affine sets
Let $A$ be an expanding $d\times d$ matrix with integer entries and ${\mathcal D}\subset {\mathbb Z}^d$ be a finite digit set. Then the pair $(A, {\mathcal D})$ defines a unique integral self-affine set $K=A^{-1}(K+{\mathcal D})$. In this paper, by replacing the Euclidean norm with a pseudo-norm $w$ in terms of $A$, ...
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The Gross-Pitaevskii equations of a static and spherically symmetric condensate of gravitons
In this paper we consider the Dvali and Gómez assumption that the end state of a gravitational collapse is a Bose-Einstein condensate of gravitons. We then construct the two Gross-Pitaevskii equations for a static and spherically symmetric configuration of the condensate. These two equations correspond to the constra...
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Stability and instability in saddle point dynamics - Part I
We consider the problem of convergence to a saddle point of a concave-convex function via gradient dynamics. Since first introduced by Arrow, Hurwicz and Uzawa in [1] such dynamics have been extensively used in diverse areas, there are, however, features that render their analysis non trivial. These include the lack ...
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Continual Prediction of Notification Attendance with Classical and Deep Network Approaches
We investigate to what extent mobile use patterns can predict -- at the moment it is posted -- whether a notification will be clicked within the next 10 minutes. We use a data set containing the detailed mobile phone usage logs of 279 users, who over the course of 5 weeks received 446,268 notifications from a variety...
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Extensions of Operators, Liftings of Monads and Distributive Laws
In a previous study, the algebraic formulation of the First Fundamental Theorem of Calculus (FFTC) is shown to allow extensions of differential and Rota-Baxter operators on the one hand, and to give rise to liftings of monads and comonads, and mixed distributive laws on the other. Generalizing the FFTC, we consider i...
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Cascaded Incremental Nonlinear Dynamic Inversion Control for MAV Disturbance Rejection
Micro Aerial Vehicles (MAVs) are limited in their operation outdoors near obstacles by their ability to withstand wind gusts. Currently widespread position control methods such as Proportional Integral Derivative control do not perform well under the influence of gusts. Incremental Nonlinear Dynamic Inversion (INDI) ...
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Numerical Evaluation of Elliptic Functions, Elliptic Integrals and Modular Forms
We describe algorithms to compute elliptic functions and their relatives (Jacobi theta functions, modular forms, elliptic integrals, and the arithmetic-geometric mean) numerically to arbitrary precision with rigorous error bounds for arbitrary complex variables. Implementations in ball arithmetic are available in the...
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In situ Electric Field Skyrmion Creation in Magnetoelectric Cu$_2$OSeO$_3$
Magnetic skyrmions are localized nanometric spin textures with quantized winding numbers as the topological invariant. Rapidly increasing attention has been paid to the investigations of skyrmions since their experimental discovery in 2009, due both to the fundamental properties and the promising potential in spintro...
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An online sequence-to-sequence model for noisy speech recognition
Generative models have long been the dominant approach for speech recognition. The success of these models however relies on the use of sophisticated recipes and complicated machinery that is not easily accessible to non-practitioners. Recent innovations in Deep Learning have given rise to an alternative - discrimina...
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Existence of infinite Viterbi path for pairwise Markov models
For hidden Markov models one of the most popular estimates of the hidden chain is the Viterbi path -- the path maximising the posterior probability. We consider a more general setting, called the pairwise Markov model, where the joint process consisting of finite-state hidden regime and observation process is assumed...
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Coding for Segmented Edit Channels
This paper considers insertion and deletion channels with the additional assumption that the channel input sequence is implicitly divided into segments such that at most one edit can occur within a segment. No segment markers are available in the received sequence. We propose code constructions for the segmented dele...
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Charge compensation at the interface between the polar NaCl(111) surface and a NaCl aqueous solution
Periodic supercell models of electric double layers formed at the interface between a charged surface and an electrolyte are subject to serious finite size errors and require certain adjustments in the treatment of the long-range electrostatic interactions. In a previous publication (C. Zhang, M. Sprik, Phys. Rev. B ...
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CrowdTone: Crowd-powered tone feedback and improvement system for emails
In this paper, we present CrowdTone, a system designed to help people set the appropriate tone in their email communication. CrowdTone utilizes the context and content of an email message to identify and set the appropriate tone through a consensus-building process executed by crowd workers. We evaluated CrowdTone wi...
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A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines
Restricted Boltzmann machines (RBMs) are energy-based neural-networks which are commonly used as the building blocks for deep architectures neural architectures. In this work, we derive a deterministic framework for the training, evaluation, and use of RBMs based upon the Thouless-Anderson-Palmer (TAP) mean-field app...
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Integrability conditions for Compound Random Measures
Compound random measures (CoRM's) are a flexible and tractable framework for vectors of completely random measure. In this paper, we provide conditions to guarantee the existence of a CoRM. Furthermore, we prove some interesting properties of CoRM's when exponential scores and regularly varying Lévy intensities are c...
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Tunable low energy Ps beam for the anti-hydrogen free fall and for testing gravity with a Mach-Zehnder interferometer
The test of gravitational force on antimatter in the field of the matter gravitational field, produced by earth, can be done by a free fall experiment which involves only General Relativity, and with a Mach-Zehnder interferometer which involves Quantum Mechanics. This article presents a new method to produce a tunabl...
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An analysis of incorporating an external language model into a sequence-to-sequence model
Attention-based sequence-to-sequence models for automatic speech recognition jointly train an acoustic model, language model, and alignment mechanism. Thus, the language model component is only trained on transcribed audio-text pairs. This leads to the use of shallow fusion with an external language model at inferenc...
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Multi-Generator Generative Adversarial Nets
We propose a new approach to train the Generative Adversarial Nets (GANs) with a mixture of generators to overcome the mode collapsing problem. The main intuition is to employ multiple generators, instead of using a single one as in the original GAN. The idea is simple, yet proven to be extremely effective at coverin...
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Neural Style Transfer: A Review
The seminal work of Gatys et al. demonstrated the power of Convolutional Neural Networks (CNNs) in creating artistic imagery by separating and recombining image content and style. This process of using CNNs to render a content image in different styles is referred to as Neural Style Transfer (NST). Since then, NST ha...
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Distribution of water in the G327.3-0.6 massive star-forming region
We aim at characterizing the large-scale distribution of H2O in G327.3-0.6, a massive star-forming region made of individual objects in different evolutionary phases. We investigate variations of H2O abundance as function of evolution. We present Herschel continuum maps at 89 and 179 $\mu$m of the whole region and an...
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Straightening rule for an $m'$-truncated polynomial ring
We consider a certain quotient of a polynomial ring categorified by both the isomorphic Green rings of the symmetric groups and Schur algebras generated by the signed Young permutation modules and mixed powers respectively. They have bases parametrised by pairs of partitions whose second partitions are multiples of t...
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Effective Blog Pages Extractor for Better UGC Accessing
Blog is becoming an increasingly popular media for information publishing. Besides the main content, most of blog pages nowadays also contain noisy information such as advertisements etc. Removing these unrelated elements can improves user experience, but also can better adapt the content to various devices such as m...
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The Principle of Similitude in Biology: From Allometry to the Formulation of Dimensionally Homogenous `Laws'
Meaningful laws of nature must be independent of the units employed to measure the variables. The principle of similitude (Rayleigh 1915) or dimensional homogeneity, states that only commensurable quantities (ones having the same dimension) may be compared, therefore, meaningful laws of nature must be homogeneous equ...
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New insight into the dynamics of rhodopsin photoisomerization from one-dimensional quantum-classical modeling
Characterization of the primary events involved in the $cis-trans$ photoisomerization of the rhodopsin retinal chromophore was approximated by a minimum one-dimensional quantum-classical model. The developed mathematical model is identical to that obtained using conventional quantum-classical approaches, and multipar...
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High-order schemes for the Euler equations in cylindrical/spherical coordinates
We consider implementations of high-order finite difference Weighted Essentially Non-Oscillatory (WENO) schemes for the Euler equations in cylindrical and spherical coordinate systems with radial dependence only. The main concern of this work lies in ensuring both high-order accuracy and conservation. Three different...
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Suppressing correlations in massively parallel simulations of lattice models
For lattice Monte Carlo simulations parallelization is crucial to make studies of large systems and long simulation time feasible, while sequential simulations remain the gold-standard for correlation-free dynamics. Here, various domain decomposition schemes are compared, concluding with one which delivers virtually ...
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New bounds on the strength of some restrictions of Hindman's Theorem
We prove upper and lower bounds on the effective content and logical strength for a variety of natural restrictions of Hindman's Finite Sums Theorem. For example, we show that Hindman's Theorem for sums of length at most 2 and 4 colors implies $\mathsf{ACA}_0$. An emerging {\em leitmotiv} is that the known lower boun...
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3D Face Morphable Models "In-the-Wild"
3D Morphable Models (3DMMs) are powerful statistical models of 3D facial shape and texture, and among the state-of-the-art methods for reconstructing facial shape from single images. With the advent of new 3D sensors, many 3D facial datasets have been collected containing both neutral as well as expressive faces. How...
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Image Segmentation to Distinguish Between Overlapping Human Chromosomes
In medicine, visualizing chromosomes is important for medical diagnostics, drug development, and biomedical research. Unfortunately, chromosomes often overlap and it is necessary to identify and distinguish between the overlapping chromosomes. A segmentation solution that is fast and automated will enable scaling of ...
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Implementing Large-Scale Agile Frameworks: Challenges and Recommendations
Based on 13 agile transformation cases over 15 years, this article identifies nine challenges associated with implementing SAFe, Scrum-at-Scale, Spotify, LeSS, Nexus, and other mixed or customised large-scale agile frameworks. These challenges should be considered by organizations aspiring to pursue a large-scale agi...
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On The Limiting Distributions of the Total Height On Families of Trees
A symbolic-computational algorithm, fully implemented in Maple, is described, that computes explicit expressions for generating functions that enable the efficient computations of the expectation, variance, and higher moments, of the random variable `sum of distances to the root', defined on any given family of roote...
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HESS J1826$-$130: A Very Hard $γ$-Ray Spectrum Source in the Galactic Plane
HESS J1826$-$130 is an unidentified hard spectrum source discovered by H.E.S.S. along the Galactic plane, the spectral index being $\Gamma$ = 1.6 with an exponential cut-off at about 12 TeV. While the source does not have a clear counterpart at longer wavelengths, the very hard spectrum emission at TeV energies impli...
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Laser opacity in underdense preplasma of solid targets due to quantum electrodynamics effects
We investigate how next-generation laser pulses at 10 PW $-$ 200 PW interact with a solid target in the presence of a relativistically underdense preplasma produced by amplified spontaneous emission (ASE). Laser hole boring and relativistic transparency are strongly restrained due to the generation of electron-positr...
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Consequentialist conditional cooperation in social dilemmas with imperfect information
Social dilemmas, where mutual cooperation can lead to high payoffs but participants face incentives to cheat, are ubiquitous in multi-agent interaction. We wish to construct agents that cooperate with pure cooperators, avoid exploitation by pure defectors, and incentivize cooperation from the rest. However, often the...
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Casimir free energy of dielectric films: Classical limit, low-temperature behavior and control
The Casimir free energy of dielectric films, both free-standing in vacuum and deposited on metallic or dielectric plates, is investigated. It is shown that the values of the free energy depend considerably on whether the calculation approach used neglects or takes into account the dc conductivity of film material. We...
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Discriminant chronicles mining: Application to care pathways analytics
Pharmaco-epidemiology (PE) is the study of uses and effects of drugs in well defined populations. As medico-administrative databases cover a large part of the population, they have become very interesting to carry PE studies. Such databases provide longitudinal care pathways in real condition containing timestamped c...
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Adversarial Symmetric Variational Autoencoder
A new form of variational autoencoder (VAE) is developed, in which the joint distribution of data and codes is considered in two (symmetric) forms: ($i$) from observed data fed through the encoder to yield codes, and ($ii$) from latent codes drawn from a simple prior and propagated through the decoder to manifest dat...
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The singular locus of hypersurface sections containing a closed subscheme over finite fields
We prove that there exist hypersurfaces that contain a given closed subscheme $Z$ of the projective space over a finite field and intersect a given smooth scheme $X$ off of $Z$ smoothly, if the intersection $V = Z \cap X$ is smooth. Furthermore, we can give a bound on the dimension of the singular locus of the hypers...
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A Statistical Perspective on Inverse and Inverse Regression Problems
Inverse problems, where in broad sense the task is to learn from the noisy response about some unknown function, usually represented as the argument of some known functional form, has received wide attention in the general scientific disciplines. How- ever, in mainstream statistics such inverse problem paradigm does ...
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Model reduction for transport-dominated problems via online adaptive bases and adaptive sampling
This work presents a model reduction approach for problems with coherent structures that propagate over time such as convection-dominated flows and wave-type phenomena. Traditional model reduction methods have difficulties with these transport-dominated problems because propagating coherent structures typically intro...
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Weighted parallel SGD for distributed unbalanced-workload training system
Stochastic gradient descent (SGD) is a popular stochastic optimization method in machine learning. Traditional parallel SGD algorithms, e.g., SimuParallel SGD, often require all nodes to have the same performance or to consume equal quantities of data. However, these requirements are difficult to satisfy when the par...
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Neural Lander: Stable Drone Landing Control using Learned Dynamics
Precise trajectory control near ground is difficult for multi-rotor drones, due to the complex ground effects caused by interactions between multi-rotor airflow and the environment. Conventional control methods often fail to properly account for these complex effects and fall short in accomplishing smooth landing. In...
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Finite-Time Stabilization of Longitudinal Control for Autonomous Vehicles via a Model-Free Approach
This communication presents a longitudinal model-free control approach for computing the wheel torque command to be applied on a vehicle. This setting enables us to overcome the problem of unknown vehicle parameters for generating a suitable control law. An important parameter in this control setting is made time-var...
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Review of Geraint F. Lewis and Luke A. Barnes, A Fortunate Universe: Life in a Finely Tuned Cosmos
This new book by cosmologists Geraint F. Lewis and Luke A. Barnes is another entry in the long list of cosmology-centered physics books intended for a large audience. While many such books aim at advancing a novel scientific theory, A Fortunate Universe has no such scientific pretense. Its goals are to assert that th...
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Introducing SPAIN (SParse Audion INpainter)
A novel sparsity-based algorithm for audio inpainting is proposed by translating the SPADE algorithm by Kitić et. al.---the state-of-the-art for audio declipping---into the task of audio inpainting. SPAIN (SParse Audio INpainter) comes in synthesis and analysis variants. Experiments show that both A-SPAIN and S-SPAIN...
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Palindromic Decompositions with Gaps and Errors
Identifying palindromes in sequences has been an interesting line of research in combinatorics on words and also in computational biology, after the discovery of the relation of palindromes in the DNA sequence with the HIV virus. Efficient algorithms for the factorization of sequences into palindromes and maximal pal...
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End-of-Use Core Triage in Extreme Scenarios Based on a Threshold Approach
Remanufacturing is a significant factor in securing sustainability through a circular economy. Sorting plays a significant role in remanufacturing pre-processing inspections. Its significance can increase when remanufacturing facilities encounter extreme situations, such as abnormally huge core arrivals. Our main obj...
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A temperature-dependent implicit-solvent model of polyethylene glycol in aqueous solution
A temperature (T)-dependent coarse-grained (CG) Hamiltonian of polyethylene glycol/oxide (PEG/PEO) in aqueous solution is reported to be used in implicit-solvent material models in a wide temperature (i.e., solvent quality) range. The T-dependent nonbonded CG interactions are derived from a combined "bottom-up" and "...
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Directional Statistics and Filtering Using libDirectional
In this paper, we present libDirectional, a MATLAB library for directional statistics and directional estimation. It supports a variety of commonly used distributions on the unit circle, such as the von Mises, wrapped normal, and wrapped Cauchy distributions. Furthermore, various distributions on higher-dimensional m...
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A solution of the dark energy and its coincidence problem based on local antigravity sources without fine-tuning or new scales
A novel idea is proposed for a natural solution of the dark energy and its cosmic coincidence problem. The existence of local antigravity sources, associated with astrophysical matter configurations distributed throughout the universe, can lead to a recent cosmic acceleration effect. Various physical theories can be ...
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Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples
Self-paced learning and hard example mining re-weight training instances to improve learning accuracy. This paper presents two improved alternatives based on lightweight estimates of sample uncertainty in stochastic gradient descent (SGD): the variance in predicted probability of the correct class across iterations o...
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Optical signature of Weyl electronic structures in tantalum pnictides Ta$Pn$ ($Pn=$ P, As)
To investigate the electronic structure of Weyl semimetals Ta$Pn$ ($Pn=$P, As), optical conductivity [$\sigma(\omega)$] spectra are measured over a wide range of photon energies and temperatures, and these measured values are compared with band calculations. Two significant structures can be observed: a bending struc...
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A study of cyber security in hospitality industry- threats and countermeasures: case study in Reno, Nevada
The purpose of this study is to analyze cyber security and security practices of electronic information and network system, network threats, and techniques to prevent the cyber attacks in hotels. Helping the information technology directors and chief information officers (CIO) is the aim of this study to advance poli...
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Weak Fraisse categories
We develop the theory of weak Fraisse categories, where the crucial concept is the weak amalgamation property, discovered relatively recently in model theory. We show that, in a suitable framework, every weak Fraisse category has its unique limit, a special object in a bigger category, characterized by certain varian...
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Multiple Stakeholders in Music Recommender Systems
Music recommendation services collectively spin billions of songs for millions of listeners on a daily basis. Users can typically listen to a variety of songs tailored to their personal tastes and preferences. Music is not the only type of content encountered in these services, however. Advertisements are generally i...
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Large time behavior of solution to nonlinear Dirac equation in $1+1$ dimensions
This paper studies the large time behavior of solution for a class of nonlinear massless Dirac equations in $R^{1+1}$. It is shown that the solution will tend to travelling wave solution when time tends to infinity.
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Compositions of Functions and Permutations Specified by Minimal Reaction Systems
This paper studies mathematical properties of reaction systems that was introduced by Enrenfeucht and Rozenberg as computational models inspired by biochemical reaction in the living cells. In particular, we continue the study on the generative power of functions specified by minimal reaction systems under compositio...
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The center problem for the Lotka reactions with generalized mass-action kinetics
Chemical reaction networks with generalized mass-action kinetics lead to power-law dynamical systems. As a simple example, we consider the Lotka reactions and the resulting planar ODE. We characterize the parameters (positive coefficients and real exponents) for which the unique positive equilibrium is a center.
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Recovery of Missing Samples Using Sparse Approximation via a Convex Similarity Measure
In this paper, we study the missing sample recovery problem using methods based on sparse approximation. In this regard, we investigate the algorithms used for solving the inverse problem associated with the restoration of missed samples of image signal. This problem is also known as inpainting in the context of imag...
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Skin cancer reorganization and classification with deep neural network
As one kind of skin cancer, melanoma is very dangerous. Dermoscopy based early detection and recarbonization strategy is critical for melanoma therapy. However, well-trained dermatologists dominant the diagnostic accuracy. In order to solve this problem, many effort focus on developing automatic image analysis system...
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Rescaled extrapolation for vector-valued functions
We extend Rubio de Francia's extrapolation theorem for functions valued in UMD Banach function spaces, leading to short proofs of some new and known results. In particular we prove Littlewood-Paley-Rubio de Francia-type estimates and boundedness of variational Carleson operators for Banach function spaces with UMD co...
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