Download the poster windeurope.org/tech2021 #WindTech21 Power curve documents contain highly sensitive data - access to which should be carefully managed for good commercial and technical reasons. This appears to conflict with the trend toward digitalization, especially seamless data exchange, which enables reduction in: - time-to-market for new wind turbines, - time-to-financial-close for new wind farms, and - workflow friction between internal and external teams. These seemingly opposed considerations can be reconciled (and accesss control enhanced) by adopting a so-called schema - a public description of the data structure – and (pending appropriate access and permissions) delivering power curve data to other stakeholders which conforms to the schema. We here introduce a schema for power curve data, discussing downstream applications and tools together with lessons learned over two years of trials. The resulting schema handles complexities including - multiple operating modes, - multi-dimensional parameter (eg air density, turbulence, wind speed), - different ratings and cut in/out criteria on a per-mode basis - provision of values as absolute or coefficient (P/CP and T/CT) - and many more. The schema has been proven versatile and useful for over two years in a production system for array design, where it has been used to describe >30 power curves over 8 major turbine manufacturers. There are some known limitations (particularly re. certification metadata) and more may emerge - evolution will continue and collaboration is very welcome. Abstract Results Objectives Benefits and downstream tools Method Working with industry partners, we initially gathered 20+ turbine power curve data sheets to which we had been permitted access. In order to automate design processes using them, a consistent data structure was required. Items in the data sheets were evaluated as being common (“all turbine power curves have this”), uncommon (“some turbine power curves have this”) and extraordinary (“rarely seen”). Data was extracted using a mixture of manual and OCR approaches, then iteratively refined toward a common, versatile pattern expressed using the JSONSchema specification. The array ordering was optimized to default to efficient C-style memory access alignment for typical usage patterns in downstream applications. Subsequently, data sheets from many more turbines (as required over a period of two years) were extracted into a compliant form, with minor evolutions of the schema to encompass subtleties encountered. Powerful Power Curves: A production-proven, open-source schema for wind turbine power curves Tom Clark, Octue PO.208 WE’RE RUNNING THE “72 Hours at WindEurope” CHALLENGE – FIND US IN THE HALL! Replace with QR code Replace with QR code We here introduce an open-source JSONSchema to describe a wind turbine power curve and its associated metadata. We will show some downstream tools uses and benefits of the approach, including automated reporting, human-based QC, and generation of web forms for data entry. Finally, the talk will cover opportunities for collaboration and touch on some limitations and areas in which the schema should continue to evolve. See the schema here >>> In a scientific/engineering environment, adopting a JSONSchema allows everybody to get instantly on the same page about what data actually *IS*. The practice: - Dramatically reduces the 45% of working time that typical engineers/scientists spend preparing data (Anaconda, 2020) - Helps teams cross “the technology chasm” to deliver business outcomes, like accelerated time-to-close, by allowing the ecosystem of downstream automations and tools to develop (Gartner, 2019) - Fosters greater control and auditability of data exchange/access (through strict permitting workflows combined with automation) than manually emailing sensitive PDF documents to stakeholders As an example of a useful downstream tool, web forms can be autogenerated for data entry, as can interactiv


STARTUP LONG-TERM AGROFORESTRY RESEARCH PLOT Walnut in silvoarable alley cropping system © Inagro OBJECTIVE Long-term research • Tree-crop interaction & yield • Ecosystem services (soil, water, biodiversity) • Practical feasibility • Profitability in Flemish agricultural context Demonstration • Need for good-example • Share lessons learned on implementing, managing and functioning of an agroforestry system • Main target group: farmers FIRST RESULTS Yield per ha and quality of leek is unaffected • Average yield of 61 tons per ha is comparable to other fields in region • No differences in terms of distance to tree row • Visual inspections confirm good quality and health Design is based on practical feasibility, profitability and reproducibility in the Flemish agricultural context. Authors: Willem Van Colen1, Thomas Van Loo1, Dieter Depraetere1 1 Inagro vzw, Belgium, willem.vancolen@inagro.be This poster is based upon work from the project REFOREST that has received funding from the European Union’s Horizon Europe Programme under Grant Agreement Nr. 101060635. Startup and first results of a long-term practice-oriented agroforestry research field in Flanders, Belgium https://agroreforest.eu Plot design – ‘keep it simple’ • Silvoarable alley cropping system • Conventional farming system • Tree: walnut (Juglans regia ‘Broadview’) • Tree row: perennial flower mix attracting beneficial insects • Intercrop: 6 year crop rotation with arable crops (maize, potatoes, winter cereals, field beans) and vegetables (leeks, carrots, cabbages, celereac) -> In cooperation with local farmers • Mixed hedge: windbreak and habitat for insects and birds Long-term monitoring Improve tailored advice & Increase adoption in Flanders The sampling distance of 10,5 m is considered as the reference situation for now. The number of transects differs per parameter. For some parameters not all distances are included in the transects due to practical considerations. Intercrops • Yield, quality, diseases REGIONAL CHALLENGE Drone picture of the recently established agroforestry research and demonstration plot located on the trial fields of Inagro, West-Flanders. This plot is one of the seven REFOREST living labs across Europe. Trees • Yield, growth, diseases Microclimate • Light (pyranometer) • Rain, wind, temperature & humidity (weather stations) Soil • Chemical soil analysis (0-30 cm) • Organic carbon (0 – 90 cm) • Moisture (20 cm + 60 cm) • Compaction (penetrologger) • Bulk density (Kopecky rings) • Nematods (under development) • Bacteria & fungi (PLFA analysis) • Earthworms Biodiversity • Overwintering soil invertebrates (soil incubations) • Moths (LED buckets) • Surface dwelling arthropodes (pitfall traps) • Flying arthropodes (window traps) • Birds and bats (Audiomoth) Fertile sandy loam soils make the central part of West-Flanders suitable for intensive, highly productive and profitable vegetable growing. As a result, agricultural land prices in West-Flanders are amongst the highest in Europe. Walnuts as high value product. Late-leafing and open crown reduce competition for light with intercrops. Trees need to produce and eventually compensate for relatively high loss of income by loss of cropping area, while impact on yield of intercrops needs to be limited. Financial – ins and outs MONITORING TRANSECTS Establishment costs Loss of cropping area is decisive in early stage • Tree rows and hedge reduce cropping area by 11% • Harvest machinery requires additional uncultivated strips -> 5% extra loss of cropping area • 84% of the plot was cultivated with leek, resulting in a production loss of 13,6 ton = loss of income ± € 2.700 Leeks in (young) agroforestry Impact of tree rows on preparatory soil work and planting of leek is limited WATCH OUR VIDEO! And get inspired… READ MORE? Check our website! STAY UPDATED? Subscribe to our newsletter and be the first to receive future results through our article series ‘Digging Deeper’ ! As an active farmer, you can have you


Fostering resource integration: EarthCube Resource Registry What is the EarthCube Resource Registry? A database of cyberinfrastructure resources with documentation focused on enabling EarthCube users and developers find, understand, get, and use those resources to increase research productivity Resource focus: applications, reusable code components, ontologies, vocabularies, specifications (extending the GeoCODES dataset registry) Why? • Improve discovery of usable resources • Enable seamless connection from discovery environment to working with the data or software. Some usage scenarios: • Identification of resources • Systematic documentation of resource characteristics • Identify gaps or duplicate resources • Find tools, APIs, or data that can work with a given resource • Support maturity assessment The Registry should: • Help researchers connect multiple data types and resources to address a specific research problem; • Enable developers to learn about components they can reuse to increase development efficiency • Enable discovery of components with a particular functionality, that can be used in an existing research workflow • Provide a platform for resource producers to inform the community about products. • Answer the question: “What has EC produced that is of use to my science?” Workflow Resource Type Matching and Exploration: Resource registry Return associated resources based on type (eg software to to work with that data) Query to registry Resource Discovery UI, with an option to open in software application (1) Notebook to retrieve metadata content and examine resource type (2) Notebook to explore the resource using matched software based on resource typeResource IDResource TypeResource IDs Matched resource Link data and applications Resource Registration Web Form An online form generated using Google Forms to submit resource descriptions. • a series of views o First views are for fields that apply to all resources. o User then identifies the kind of resource they are registering, o Subsequent views are specific to that resource. Required fields are indicated with a red asterisk (*) A submitted resource is assigned an ARK URI identifier, Documentation is stored in the EarthCube registry, made available for browsing and discovery via the SuAVE viewer, and accessible via API. Browse and Search registry content: SuAVE Viewer Resource summaryclick Example controlled pick list First page of registration form Stephen M. Richard, LDEO, Columbia University and US Geoscience Information Network (USGIN); Ilya Zaslavsky, San Diego Supercomputer Center; and Ruth Duerr, Ronin Institute for Independent Scholarship SuAVE viewer for EarthCube resources Resource Registration Form for submitting resources: Viewer for adding information Edit view for modifying the form Resource Registry SPARQL endpoint (username/password sent by email) Documentation on mapping resource descriptions to the registry ontology and JSON-LD serialization. Controlled vocabularies Google Sheet (one tab for each vocabulary) EarthCube Resource Registry Presentation - https://drive.google.com/file/d/1dwIUliAurfFstWRSiY74UBoUSaJYlVvc Links Resource Types Bundled Object Catalog Dataset Document Information Model Interchange Format Interface Platform Repository Service Software Specification UseCase This work was supported by funding from the 2019 ESSO EarthCube Office and the 2020 ECO EarthCube office Example search for resources related to SPARQL


The envelopes of low-mass stars: the impact of Coulomb effects on stellar oscillations Ana Brito 1),2) & Ilídio Lopes 2) 2) Centro de Astrofísica e Gravitação - CENTRA, Departamento de Física, Instituto Superior Técnico, IST, Universidade de Lisboa - UL, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal | ilidio.lopes@tecnico.ulisboa.pt 1) Departamento de Matemática, Instituto Superior de Gestão, Av. Marechal Craveiro Lopes, 1700-284, Lisboa, Portugal | anabrito@isg.pt I. Introduction V. Conclusion In this work, we explore the outer layers of stars less massive than the Sun. In particular, we have computed a set of stellar models raging from 0.4 to 0.9 solar masses with the aim at determining the impact on stellar oscillations of two physical processes occurring in the envelopes of these stars. Namely, the partial ionisation of chemical elements and the electrostatic interactions between particles in the outer layers. We find that alongside with partial ionisation, Coulomb effects also impact the acoustic oscillation spectrum. The influence of Coulomb interactions on the sound-speed gradient profile produces a strong oscillatory behaviour with diagnostic potential for the future. We find that, around the value of 0.6 solar masses, the peak/dip in the first adiabatic exponent/acoustic potential corresponding to helium ionisation zones (Fig. 1) vanishes and, consequently, does not produce an oscillatory signature in the seismic diagnostic β(ν). This is thus the reference value, for models with solar metallicity, around which occurs a transition in the characteristics of the oscillatory signal imprinted in the oscillation frequencies by two distinct physical processes. The acoustic spectrum of stars more massive than 0.6 solar masses is mostly impacted by partial ionisation processes, whereas the acoustic spectrum of stars less massive than 0.6 solar masses is predominantly impacted by Coulomb interactions. II. Thermodynamic properties of the turbulent outer regions The behaviour of the first adiabatic The behaviour of the first adiabatic exponent around its monatomic ideal exponent around its monatomic ideal gas value, 5/3, is influenced by two gas value, 5/3, is influenced by two fundamental aspects. First, the increase fundamental aspects. First, the increase of the degree of ionisation decreases of the degree of ionisation decreases the Γ the Γ1 value, causing a known value, causing a known depression in the radial profile of Γ depression in the radial profile of Γ1, , particularly throughout the partial particularly throughout the partial ionisation zones of light elements, ionisation zones of light elements, hydrogen and helium. The second hydrogen and helium. The second aspect that influences the behaviour of aspect that influences the behaviour of the first adiabatic exponent relates to the first adiabatic exponent relates to the electrostatic interactions between the electrostatic interactions between charged particles, known generally as charged particles, known generally as Coulomb effects. Coulomb effects Coulomb effects. Coulomb effects increase the value of Γ increase the value of Γ1 causing it to causing it to become larger than 5/3 in some regions become larger than 5/3 in some regions of the convective zone. Also, the of the convective zone. Also, the acoustic potential is determined by the acoustic potential is determined by the model structure and, therefore, will be model structure and, therefore, will be impacted by physical processes like impacted by physical processes like partial ionisation of atomic species and partial ionisation of atomic species and electrostatic interactions between electrostatic interactions between charged particles. Fig. 1 shows these charged particles. Fig. 1 shows these two profiles for all the models. two profiles for all the models. Fig. 2 The ionic plasma interaction parameter, Γi , as a function of temperature. Also plotted in this figure, with grey colour, is the sound- speed gra


B.L. Moore, S. Aitken and C.A. Semple MRC Human Genetics Unit, Western General Hospital, Edinburgh EH4 2XU Introduction Strong concordance between cell types Prediction of higher-order structure References ‣ Histone modifications ‣ Histone variants ‣ Transcription factors ‣ Dnase hypersensitivity ‣ DNA methylation ‣ Transcription level What's the relationship between these locus-level features and higher-order chromatin? ben.moore@igmm.ed.ac.uk What determines higher-order chromatin? Identification of significantly divergent regions PC eigenvector value −2 −1 0 1 2 10 MB H1 IMR90 K562 GM06990 GM12878 "Open" "Closed" p53 0 1 2 Atf3 0 1 2 Cebpb 0 1 2 Chd1 0 1 2 Chd2 0 1 2 Cmyc 0 1 2 Ctcf 0 1 2 Egr1 0 1 2 Ezh2 0 1 2 Gabp 0 1 2 J und 0 1 2 Mafk 0 1 2 Max 0 1 2 H2az 0 1 2 H3k27ac 0 1 2 H3k27me3 0 1 2 H3k36me3 0 1 2 H3k4me1 0 1 2 H3k4me2 0 1 2 H3k4me3 0 1 2 H3k79me2 0 1 2 H3k9ac 0 1 2 H3k9me3 0 1 2 H4k20me1 0 1 2 Mxi1 0 1 2 Nrsf 0 1 2 Pol2 0 1 2 P300 0 1 2 Six5 0 1 2 Sp1 0 1 2 Taf1 0 1 2 Tbp 0 1 2 Yy1 0 1 2 Znf143 0.30 0.45 gc 1 2 3 4 Dnase −3 −1 1 0 40 80 120 P300 Chd1 Tbp Max Znf143 Mxi Six5 J unD Chd2 H3k9me3 H3k27me3 H4k20me1 Ezh2 Gabp Yy1 Sp1 Rad21 H3k36me3 H3k4me3 H3k4me2 Pol2 H3k9ac Mean decrease in accuracy 0 50 100 150 200 c−Myc P300 Ezh2 H3k9ac H3k79me2 Cebpb Six5 Chd1 Chd2 H2az H3k27me3 Pol2 Atf3 J unD H3k27ac H3k4me1 Gabp H4k20me1 H3k9me3 Mean decrease in accuracy 0 50 100 150 200 J unD Cebpb MafK Chd1 c−Myc Max H2az Egr1 Ezh2 Chd2 Ctcf Atf3 Gabp Mean decrease in accuracy 0 50 100 150 200 Conclusions: • Higher-order chromatin structure can be accurately modelled using locus-level features. • A strong correlation of chromatin structure between cell types was observed, but the determinants appear to vary greatly. • Future work will look at characterising divergent regions and identifying important variables at these sites. Box 1. Hi-C is a method of producing genome-wide measurements of the frequency that genomic regions interact in the nucleus. Hi-C builds upon existing chromosome capture techniques, but uses high- throughput sequencing to output all-vs-all measurements. See [1] for a detailed description. Recent advances in chromosome capture technology have permitted genome-wide assessment of higher-order chromatin structure in a variety of cell types. This data in conjunction with that produced by the ENCODE consortium offers an unprecedented opportunity to investigate the antecedents of higher-order chromatin structure. To address this question I used an integrative modelling approach, whereby the above input variables are considered as predictors of higher-order structure. Hi-C (see box 1) genome-wide interactions can be reduced to an eigenvector summary metric which captures compartmentalisation of the genome into two broad compartments, "open" and "closed". These have been shown to represent gene dense, transcriptionally active and relatively gene poor, inactive regions respectively [1]. Recently modelling techniques were applied to the prediction of transcription and acheived high accuracy [2] so it was of interest to see if this could be replicated with chromatin structure. The resulting model was then compared across cell types and interrogated to reveal the relative importance of the various predictor variables. An arc diagram with edges joining nodes with higher than average interaction frequency as measured by Hi-C. Edge widths are proportional to the number of pairwise interactions recorded. Nodes are coloured by eigenvector (positive or "open" are light blue) and scaled by absolute eigenvector value. Hi-C interaction matrix derived from H1 hESC [1]. Figure 1. Over-represented pairwise interactions on chromosome 1. A correlogram (A) showing scatterplots, kernel density estimates and Pearson correlation of eigenvectors of 1 MB blocks across 11 chromosomes and 5 cell types, with data coming from 3 different experiments. A line plot (B) shows the actual eigenvectors to scale on their respective chromosomes (8 s


Changing Horses in Mid-Stream: The New ADS Michael J. Kurtz Harvard-Smithsonian Center for Astrophysics The Smithsonian/NASA Astrophysics Data System (ADS) is the core digital library for astrophysics. It was built in 1992, put on the Internet for public use in 1993, and moved to the WWW in 1994. It was an immediate success, and has dominated astronomers use of their scholarly literature ever since. By the beginning of the 21st century it was clear the ADS was an important part of the scholarly infrastructure of astronomy. This required that it be rebuilt, from the original ad hoc system to more long-‐ term stable, maintainable, robust and extensible one, while keeping the existing service operating 24/7/365. This has been substantially more difficult than we imagined; finally begun in 2007 the new system was released this spring (2018), to run for a year in parallel with the old, Classic system until next spring, when the Classic system will be turned off, after a quarter of a century of use. The project has taken more than a decade of intense work; it required a change in the management structure, and an eventual doubling of the staff (and thus budget). During this time the technological landscape has changed substantially, many promising directions for the development were taken, only to be later abandoned. Additionally many new capabilities became possible, requiring improvements both to the new design, and where feasible, to the old system as well. We hope the new ADS will enable researchers discovery for the next 25 years. The ADS is at ads.harvard.edu A Decade of Effort


* Diagnosticar la enfermedad antes de tener el primer hijo Ejercer una paternidad informada, sin coacciones Ofrecer las técnicas de reproducción humana asistida que eviten la trasmisión de la enfermedad Identificar y localizar los casos desconocidos Informar de manera adecuada a pacientes y familiares Figura 1: Nuestro modelo de HEXÁGONO PREVENTIVO DE LA PQRAD** *Iconografía de Riñón poliquístico del Biobanco PQRAD del HU Virgen de las Nieves, ibs.GRANADA ** Bravo-Soto JA, Esteban-de-la-Rosa RJ, Morales García AI, García Valverde M, et al. GEEPAD y Asociación Amigos del Riñón Recuperar los casos perdidos para control


MODERNIZING DATA-DELIVERY TECHNOLOGIES Combining Data-User Feedback with User-Support Expertise for Successful Data Tools And Pivoting when Technology Changes! Digital Data Products: Two Key Questions ➊ What problem(s) need to be solved? ➋ How do users want to solve those problems? Unlocking the potential of data tools requires: understanding user needs (talking directly with data users); leveraging existing user support expertise; the pivoting unapologetically if user demands and tech developments shift. Why This Matters to You Elevate your potential to gather effective user feedback when developing digital data products and data-related services: • When resources or time are in short supply • That goes beyond “textbook” or “Google-search” research approaches used in ideal conditions • To see some cool, recently launched products produced by ICPSR that your patrons may have interest in using Before Starting Definitions User Testing: the process of collecting research data from real users while they are using a digital product whether a prototype or fully launched User: an individual that uses or has the propensity to use a digital product; includes the individuals who actually interact with the product as well as those directing/training users to interact with the product User Support: individuals who assist hundreds of users annually who are interacting with a product whether support is for general questions or to solve problems User Research: The Practicalities Purpose: Observe, log, and analyze user interactions with a product, noting successes, challenges, and failures in order to improve user experience on the front-end and content received in the back-office Challenges: • Finding & recruiting “real” users • Expense $$ and time intensive • Live user research is a lab experience; users often act differently in the wild! • Users represent one experience — their own! Is their experience unique or common — that is the question! Process: At-A-Glance 1st Step Define the problem What is the (user) problem(s) to solve? How will it help the producer of the product (it’s okay to help yourself!)? Hint: Key to success — include user support staff in all phases starting with problem definition. 2nd Step Define the user Who is the primary user? Secondary? Hint: Define demographically, experience levels (substantive, technological, methodological) 3rd Step Test, Research, Build, and, if needed, Pivot • Recruit for testing and reward ($) • Conduct research again and again and again • Invite user support to help interpret research Hint: Digital Products — Be prepared to pivot when new technology arrives (AI changes everything!) Real-life Examples from ICPSR Digital Data Product Releases Product Research Data Ecosystem TurboCurator Problem Depositors not often knowledgeable on creating Findable metadata efficiently Solution ICPSR’s TurboCurator — designed to semi-automate the process Pivot Technology-inspired: AI - ChatGPT Identified three key metadata areas (Title, Description, Key Words) • Depositor inputs general information about the study, dataset, or file • TurboCurator, powered in part by AI, outputs accepted formats for title, description, and controlled key words that depositor can cut/paste to describe the data deposit https://myumi.ch/AZwPe Product Research Data Ecosystem Explore Data Problem A need to “look into” the data to learn more about “what’s in there” before downloading it or analyzing it; make data more Accessible Solution ICPSR’s Explore Data Pivot User-inspired: Users advised against another statistical analysis tool; keep it simple https://myumi.ch/G4Gz1 Product Research Data Ecosystem Researcher Passport Authentication & Authorization System Problem A need for an updated authentication and authorization system to exit ICPSR from password management (increase security) and make access to restricted-use data less cumbersome Solution ICPSR’s Researcher Passport — launching in two phases: • Basic Passport — basic acco


AlligatorDAmeriq_1a8c ApelleCebusApell_f4b9 ArtibeusPerspici_2a22 AteleAtelesAter_7245 Atele_6717 AutrucheDAfrique_6973 AyeAyeDaubentoni_cb56 BabouinCercopith_a723 BlaireauAGorgeBl_db3a BlaireauEuropeen_618f Bradypus_5eb1 CaracalLynchusCa_639b CasoarACasqueCas_4dab CasoarEmeuJeuneC_aa2f ChacalThosAureus_6fe4 ChatCyclope_e0cd ChatPecheurPrion_bd43 ChauveSourisChau_a85e ChauveSourisGean_d287 ChienDomestiqueC_8195 ChienViverrinTan_6fe1 ChimereMonstrueu_09b5 CivetteAfricaine_c69f CoatiANezBlancNa_dce3 Coelacanthe_12ea ColobeColobusPol_6118 CoyoteCanisLatra_76cb CrociduraOcciden_3244 CrocodileMarinCr_d96c DauphinAGrosNezB_5aee DauphinDeLaPlata_8197 DingoCanisLupusD_df62 DouroucouliAotus_091c ElephantDAfrique_6308 ElephantDeMerMac_641a EpomophoreDeGamb_9896 FennecVulpesCani_20d4 FossaCryptoproct_9de6 GalagoDemidoviiG_6cf3 GirafeGiradae_f221 GrandRhinopomeRh_0c4e GrizzliUrsusArct_32eb GuepardFelidaeAc_9f0e Gymnure_49a8 HurleurRouxAloua_47da HyeneRayeeHyaene_99d0 KangourouRouxMac_dd51 LangurIndienPith_8390 LemurMongosLemur_b941 LeopardPantheraP_065b LepilemurAQueueR_309f LionPantheraLeo_1799 LoupCanisLupus_dba4 LoutreLutraLutra_7494 LynxFelisRufa_d5e8 MacacaMulatta_875f MacaqueCrabierMa_8f9e MacaqueRhesusMac_bdf8 MakiCattaLemurCa_dec8 MangabeyCercoceb_4458 MangabeyCouronne_6b65 Manis_9475 MarsousetOedipom_e834 MicrocebeDeCoque_e3a9 MicrocebeMignonM_ca6c MicrocebeMignonM_ca6c_head MinioptereDeSchr_5b67 MoustacLasiopygi_23cc NycticebusTardig_08cb NyctimeneAlbiven_5e61 OkapiGiradaeO_a35d Orangoutan_80bb OrnithorynqueOrn_4a62 OtarieDeCaliforn_6095 OtarieDeCaliforn_bae7 OtarieDeKerguele_8bba OuistitiAPinceau_b4aa OursBrunUrsusArc_6caa OursBrunUrsusArc_a916 OursMalaisHelarc_8477 OursNoirUrsusAme_2aed OursNoirUrsusAme_418f OursNoirUrsusAme_d540 OursPolaireThala_2445 PandaGeantAiluro_d4b8 PangolinManis_6a35 PetitRhinolopheR_34a8 PhoqueCommunPhoc_1df3 PhyllorhineDeCom_576f PithecusGermaini_6a2c PithecusGermaini_6a2c_head PumaConcolor_997a RaieBoucleeRajaC_bc9a RatonLaveurProcy_6221 RenardVolantAOre_9f48 RenardVolantMalg_a94e RequinRoussette_e3b7 SaimiriCassiquia_7176 SaimiriCassiquia_eb44 SalamandreGeante_ddc0 SapajouCapucinCe_d971 ServalLeptailuru_2f96 SingeLaineuxLago_0f84 SlothBear_48b3 SolenodonSolenod_fc42 TamanoirMyrmecop_8e13 TamanoirMyrmecop_9b3d TamanoirMyrmecop_e70b TatouDasypusNovi_f181 TaupeCommuneTalp_e3d6 ThylacineThylaci_32df TigreFelisTigris_7ced TortueImbriqueeE_0575 VaranDesSavanesV_dccf VaranDesSavanesV_dccf_head VaranusGriseus_aa49_head VariNoirEtBlancL_4d0e VariNoirEtBlancL_4d0e_body VervetCercopithe_72ae ZebreDeChapmanEq_56cb A The electronic collection of vertebrate brains of the National Natural History Museum of Paris Katja HEUER1,2, Melanie DIDIER3,4, Antoine BURGOS3,4, Stephanie ANASTACIO3,4, Marc HERBIN*5, Mathieu SANTIN*3,4 & Roberto TORO*1,3 1Institut Pasteur 2Max Planck Institute 3Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, APHP GH Pitié-Salpêtrière, Institut du cerveau et de la moelle épinière (ICM) 4Centre de Neuro-Imagerie de Recherche (CENIR) 5UMR7179 MNHN/CNRS, Muséum National d’histoire naturelle de Paris, Dpt AVIV. *Authors contributed equally to this work. katjaqheuer@gmail.com, rto@pasteur.fr King colobus Hanuman langur Loridae Cercopithecini Papionini Lemuriformes Galagonidae Atelidae Cebidae Colobinae Hominoidea 5 cm Human Chimpanzee Bonobo Indochinese lutung Douroucouli Cotton-top tamarin Squirrel monkey Black-pencilled marmoset Red slender loris Gibbon Gorilla Orangutan Hamadryas baboon Grey-cheeked mangabey Sooty mangabey Crab-eating macaque Rhesus monkey Woolly monkey Black spider monkey Green monkey Demidoff's galago Aye-aye Red-tailed sportive lemur Mongoose lemur Black-and-white ruffed lemur Grey mouse lemur Ring-tailed lemur Coquerel's mouse lemur Gorilla Human Bonobo Chimpanzee Orangutan Crab-eating macaque Rhesus macaque Black-and-white ruffed lemur Ring-tailed lemur Coquerel's mouse lemur Tufted capuchin White-faced sapajou Cotton-top tamarin Douroucouli Black spider monkey Ind


) c (MeV/ TT p δ Recon -400-300-200-100 0 100 200 300 400 ) c (MeV/ TT p δ Truth -400 -300 -200 -100 0 100 200 300 400 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 ) c (MeV/ TT p δ Recon -400-300-200-100 0 100 200 300 400 ) c (MeV/ TT p δ True -400 -300 -200 -100 0 100 200 300 400 0 0.2 0.4 0.6 0.8 1 ) c (MeV/ p p Recon 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 3 10 × ) c (MeV/ p p Truth 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 3 10 × ) c (MeV/ p p Recon 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 3 10 × ) c (MeV/ p p Truth 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 3 10 × ) c (MeV/ p p Truth ) c (MeV/ TT p δ -400-300-200-100 0 100 200 300 400 Counts 0 100 200 300 400 500 600 Fake Data Signal and mesons 0 π Charged mesons Zero mesons Other Signal ) c (MeV/ TT p δ -400 -300 -200 -100 0 100 200 300 400 Data/MC Pass Fail Time Slicing Vertex Position Muon Identiﬁcation Proton Selection !0 Identiﬁcation Sample Signal Michel Tagged Low pID Michel Tagged Fail Pass Pass Michel Tagged Signal Low pID ) c (MeV/ γ γ m 0 50100150200250300350400450500 Counts 0 20 40 60 80 100 120 140 160 180 Fake Data Signal and mesons 0 π Charged mesons Zero mesons Other PID ) c (MeV/ γ γ m 0 50100150200250300350400450500 Counts 0 10 20 30 40 50 60 70 80 Fake Data Signal and mesons 0 π Charged mesons Zero mesons Other Michel ) c (MeV/ γ γ m 0 50100150200250300350400450500 Counts 0 20 40 60 80 100 120 140 160 Fake Data Signal and mesons 0 π Charged mesons Zero mesons Other Signal Default True Recon Residual 1 - T µ p -0.5-0.4-0.3-0.2-0.1 0 0.1 0.2 0.3 0.4 0.5 0 100 200 300 400 500 600 700 800 Curvature Fitted Gaussian Mean = -0.02 Width = 0.11 = 153/45 ndf / 2 χ Range Fitted Gaussian Mean = -0.01 Width = 0.07 = 242/45 ndf / 2 χ Measuring nuclear effects in pionic semi-exclusive ﬁnal states using the MINERvA Detector David Coplowe on behalf of the MINERvA Collaboration david.coplowe@physics.ox.ac.uk Introduction The MINERvA Detector nµ Transverse Plane µ− pµ− p0 pp0 p pp pµ− T pp0 T pp T µ− pµ− T p0 pp0 T p pp T Transverse Plane dpTT = pp TT + pp0 TT A = 1 : pp TT = −pp0 TT A > 1 : pp TT 6= −pp0 TT pp0 TT pp TT Reconstruction Improvements Signal Extraction [1] K. Abe et al. (T2K), Phys. Rev. D97 012001 (2018), [2] P. Adamson (NOvA), Phys. Rev. Lett. 118 (2017) no.15, 151802, [3] NOvA Technical Design Report, FERMILAB-DESIGN-2007-01, [4] R. Acciarri et al. (DUNE Collaboration), arXiv:1512.06148, [5] O. Altinok (MINERvA), Phys. Rev. D96, 072003 (2017), [6] X.-G. Lu, D. Coplowe, R. Shah, G. Barr, D. Wark, and A. Weber, Phys. Rev. D92, no. 5, 051302 (2015) 60 < mgg (MeV) < 200 1.5 < Eµ (GeV) < 20.0 • Situated on-axis in NuMI Beam. • Analysis studies low energy dataset peaked at 3.5 GeV. • Active tracker capable of reconstructing low energy (T = 110 MeV) tracks • Precise directionality (within 3 mm), • Particle identiﬁcation and momentum provided by dE/dx proﬁling. • MINOS near detector measures charge and momentum of forward going muons. • ECAL and HCAL aids in full event containment. pp > 450 (MeV/c) c2 pen = (E1−Emeas 1 )2 s2 E1 + (E2−Emeas 2 )2 s2 E2 • Neutral pions identiﬁed via dominant decay (ddidavid). • Kinematics determined using photons energy and direction • Momentum limited by photons calorimetric reconstruction, • Angular resolution is good. • Use precise angular determination to improve calorimetric estimates by ﬁtting iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii using a penalty term p0 ! gg m2 = 2E1E2(1 −cos q12) Kinematic Constraints qµ < 25◦ • Nuclear effects are currently one of the dominant sources of systematic uncertainty in oscillation measurements [1,2]. • Signal and background selection efﬁciencies. • Reconstructed neutrino energy spectra. • Measuring ﬁnal states with exactly one cii, and at least one pii and p. • Will aid in reducing such uncertainties in Multi-GeV oscillation experiments [3,4]. • This work is an extension to the analysis on the ‘delta rich’ sample in [5]. • Nuclear dynamics probed by double transverse momentum (dpiii) — a kinematic imbalance of the hadronic ﬁnal state [6]. µ− p0 p dpT


More details in our publication: Gvaramadze, Maryeva, et al., MNRAS, 2019 I am grateful to grant support from Czech Science Foundation GA18-05665S and RFBR grant 19-02-00779. During our search for massive stars on late evolutionary stages in WISE archive we discovered a high-velocity runaway star CPD-64º 2731, associated with a horseshoe-shaped nebula. Its spectral type is O5.5Vn((f)) and projected rotational velocity is ≈300 km/s, which is extremely high for this spectral type. The kinematic age of ≈ 6 Myr, assuming it was born near the Galactic plane, exceeds its age derived from single star models by a factor of two. These properties suggest that CPD-64º 2731 is a rejuvenated and spun-up binary product. The geometry of the nebula and the almost central location of the star within it argue against a pure bow shock interpretation for it. Instead, we suggest that the binary interaction happened recently, thereby creating the nebula, with a cavity blown by the current fast stellar wind. This conclusion is supported by our results of 2D numerical hydrodynamic modeling. The main goal of our project is the search for evolved massive stars through the detection of their mid-IR circumstellar nebulae in Spitzer and WISE archives. The search has led to the discovery of many dozens of previously unknown nebulae. Some of them were found around newly identified massive stars, such as luminous blue variables and blue supergiants (e.g. Gvaramadze et al. 2010). Some others were interpreted as bow shocks produced by known or newly identified OB stars. During the search we discovered a horseshoe-shaped shell of angular radius of ≈30 arcsec in the Circinus constellation. We identified the nebula with the IRAS source 14032−6515, and found within it a massive star, known as CPD−64º 2731. The nebula has attracted out attention because it is associated with a high-velocity runaway main sequence O star, but does not look like a genuine bow shock. Using proper motion measurements for the star from Gaia DR2 we found that CPD−64º 2731 is a high-velocity (≈160 km/s ) runaway star with the vector of its space velocity inclined to our line of sight by ≈33º. The runaway status of CPD−64º 2731 is also supported by the large separation of this star from the Galactic plane of z≈0.5 kpc. CPD−64º 2731 moves almost perpendicular to the Galactic plane and its past trajectory intersects the Galactic plane at l ≈311.5º. In this direction our line of sight first crosses the Carina-Sagittarius arm at ≈1.5 kpc and then tangentially enters into the Crux-Scutum spiral arm at ≈5 kpc. All distance estimates for CPD−64º 2731 imply that this star was formed in the Crux-Scutum arm. The kinematic age of CPD−64º 2731 of ≈6 Myr, assuming that this star was born near the Galactic plane, exceeds its age derived from single star models by a factor of two. We therefore suggest that CPD−64º 2731 is a rejuvenated and spun- up product of binary interaction (a massive blue straggler). We have modeled the interaction between the stellar wind of CPD−64º 2731 and the ISM. To verify our hypothesis that CPD−64º 2731 is the binary interaction product we performed two types of simulation: - bow shock produced by a runaway star whose wind parameters and space velocity were set to be identical to those of CPD−64º 2731 - runaway star was assumed to be initially composed of two ≈20 M ⊙components with identical mass loss rate and wind velocity. After several thousand years, the wind parameters of the binary product were set to be equal to those of CPD−64º 2731, and the new, much faster, wind started to blow a bubble in the preceding slow wind material bounded in the upstream direction by the bow shock. The second scenario reproduces reasonably well the horseshoe shape of the nebula around CPD−64º 2731 and confirms our hypothesis Spectra were obtained with the SALT High Resolution Spectrograph. For modeling we used the stellar atmosphere code CMFGEN (Hillier & Miller 1998). Spectral analysis of da


Este estudio comparó las características técnicas, prácticas, económicas y ambientales de la producción de biodiésel a partir de materias primas no convencionales, como aceite de linaza y manteca de cerdo. Los reactivos se sometieron a transesterificación en un reactor Batch a 55°C con agitación constante, tomando muestras cada dos horas para estimar la producción de glicerina mediante purga con agua. Los análisis confirmaron la conversión de materiales grasos en ésteres de biodiésel. Los hallazgos indicaron que la producción de biodiésel a partir de materiales alternativos es plausible y sus resultados son acordes al proceso de gran escala en la medida de lo posible, sin embargo, se evidencia una necesidad de adaptación de procesos y materiales para optimizar la obtención de productos. Este estudio incentivo a la búsqueda de alternativas oleo genas a los insumos de fabricación tradicionales para aprovechar estos materiales en un fin útil, reduciendo la contaminación que generan a la vez de ampliar el panorama de los combustibles a largo plazo . Palabras clave: transesterificación; residuos; optimización; biodiesel. Resumen Objetivo General Conclusiones • El estudio demuestra eficacia en el proceso de transesterificación en un porcentaje superior al 90 porciento, siendo positivo para los fines de este proyecto, permitiendo concluir del mismo que es posible utilizar materias no convencionales de tipo oleo gena para producir combustibles tipo diésel natural. Por otra parte, es importante resaltar que el estudio en pequeña escala se ve limitado por las capacidades y compatibilidades del laboratorio que, en su forma, ayudan a realizar de manera más controlada y exacta el experimento. • También es notable destacar que el uso de materias no convencionales en experimentos de escala micro resulta en un gasto masivamente superior que, si fuera a escala macro, principalmente por los procesos "no industrializados" que requieren ser llevados a mano, incrementando significativamente el tiempo en el que los resultados son visibles además del ámbito económico Referencias Llanes Cedeño, E. A., Rocha-Hoyos, J., Salazar Alvear, P., & Medrano Barboza, J. (2017). Producción e Impacto del Biodiesel: Una Revisión. https://dialnet.unirioja.es/descarga/articulo/6069992.pdf. Producción e Impacto del Biodiesel: Una Revisión. (s.f.). https://dialnet.unirioja.es/descarga/articulo/6069992.pdf. Cruz, A. (2018). Producción de Biodiesel. https://www.academia.edu/36006115/Art%C3%ADculo_Producci%C3%B3n_de_Biodiesel. Resultados Comparar las características técnicas, practica, económicas y ambientales de la producción de biodiésel a partir de materias primas no convencionales, como el aceite de linaza y el aceite animal. Escuela de Ciencias Exactas e Ingeniería Ingeniería Ambiental Víctor Augusto Lizcano Sandoval Juan Barrios, Juan Hueso, María Pinzón, Axel Ortiz Gas Oink Lina: Innovación y Eficiencia en el Suministro de Combustible Metodología Preparación de los reactivos: Derretir la manteca de cerdo al baño maría (no superar 55 grados para evitar que las impurezas se friten). Filtrar la grasa derretida usando un colador metálico y un embudo, y transferir en otro vaso de precipitado hasta que se enfríe levemente, permitiendo que pueda ser colocado en el reactor Preparación de los reactores: Introducir la mezcla en el reactor. Ajustar la temperatura del reactor a 55°C utilizando un termómetro. Mantener una agitación constante usando el agitador magnético para asegurar la homogeneidad de la mezcla. Reacción de transesterificación: Introducir la mezcla en el reactor. Ajustar la temperatura del reactor a 55°C. Mantener una agitación constante usando el agitador magnético para asegurar la homogeneidad de la mezcla. Toma de muestras: A intervalos regulares (cada 2 horas para cantidades pequeñas), tomar muestras de la mezcla en un vaso de precipitado para analizar la cantidad de biodiésel producido. Registrar los resultados con la hora y el porcentaje de producción d


The Tools of Open Notebook Science Platforms Supplemental


Making Cultural Heritage Data easier to access, more sustainable, reproducible and citable. Supporting collaboration between all those working with and on digital data originating from Cultural Heritage Institutions Offering a comprehensive framework including all aspects relevant to Cultural Heritage data re-use Which digital data? Which benefits? For which actors? Metadata Annotation can be shared, enriched and disseminated by the Charter partners. All partners in the Charter will benefit equally from the greater visibility and communication made possible by joining forces. Scholars Research Institutions Cultural Heritage Institutions Data Hosting Bodies Cultural Heritage Labs •• Sustainability •• Citation •• Access •• Reproducibility 1. Register according to your personal or institutional profile. 2. Get in touch with the cooperation partners and collections relevant to your activities. 3. Gather information on relevant topics such as licensing. 4. Gain visibility and recognition in the international research ecosystem. As a scholar joining the Charter, you can position yourself in the research eco system by: • • declaring your wil- lingness to follow the requirements of the Cultural He- ritage Institutions and the collections you would like to work with • • declaring the licen ses you use for your work (informa- tion on licensing is provided) • • defining how you want to be cited by the signed-up members of the Charter you work with •• abiding to the Charter Code of Ethics (correct citation of your own work, of your partners, of your image). You can determine the conditions of your public online presence by choo- sing how much infor- mation you wish to share. With a clear and open citability of all the partners, you can benefit from ever-in- creasing resources: • • precise information on the collections that might interest you • • direct contact with the person respon- sible for the collec- tion or topics you are interested in •• new opportunities of cooperations •• better metadata and data quality •• better overall visibi- lity of the actors as well as resources. As a Cultural Herita- ge Institution joining the Charter, you can offer your collections a new visibility by: • • using a platform that allows to co- ordinate with all concerned actors (Cultural Heritage Labs, Data Hosting Bodies, Research) • • defining precisely, for each collection and each type of data associated to them, the condi- tions for their re- use •• addressing ques- tions of hosting and dissemination of data resulting from experiments on Cultural Heri- tage assets within a comprehensive framework. •• Types of primary sources •• Data formats •• Forms of enrichment •• Individuals and institutions •• General and specific declarations •• Possible move to citizen science Text Scans with the support of the H2020 research program of the European Union Cultural Heritage Charter Data Re-Use Anne Baillot (Centre Marc Bloch) Laurent Romary (Inria) Contact charter@dariah.eu licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)


4. Discussion Throughout u3Green, the main advantages and challenges of working in teams with young citizen scientists become visible. Participation of young people introduces new ideas and asks experts to change their perspective. However, it requires comprehensive planning and particular pedagogical skills to keep young people engaged (e.g., keep them interested and motivated) Literatur Fors, H., Hagemann, F.A., Sang, Å. O. & Randrup, T. B. (2021). Striving for inclusion. A systematic review of long-term participation in strategic management of urban green spaces. Frontiers in Sustainable Cities 3:1-27. https://doi.org/10.3389/frsc.2021.572423 Goderbauer, E. (2023). Jugendbeteiligung in der Stadtentwicklung. Ein Blick aus der Stadtforschung. Geographische Rundschau 2023(4):24-29. Vogler, R., Hennig, S., & Albrecht, F. (2023). Urban Green for Child-and Youth-Friendly Cities. GI_Forum 2023(1):118-139. https://doi.org/10.1553/giscience2023_01_s118 Contact u3Green-Team (Tim Schötz, Sabine Hennig, Robert Vogler) Department of Geoinformatics – Z_GIS University of Salzburg tim.schoetz@plus.ac.at 1. Objectives u3Green pursues three objectives: 1. gaining general knowledge about the importance and use of urban green by children and the youth 2. developing a web-based, child- and youth-centred application for collecting and reporting information on urban green spaces (u3Green-app) 3. communication of the findings (i.e., analyze results of the data contributed using the u3Green-app) via suitable geo-visualization products 2. Methods, tools, workflow Based on a basic knowledge, a survey application is created which is then used to survey the locations and characteristics of urban green spaces (Fig. 1). The collected data is then evaluated and communicated. Geomedia products from Esri (e.g., ArcGIS Online, Survey123, Insights, StoryMaps) are used to record, evaluate and communicate the results. Young people, i.e., school students, are involved in all phases of the project through various participation formats. These include school workshops, short and long-term internships. 5. Conclusion, outlook The collected data is analyzed using geomedia (e.g., StoryMaps, ArcGIS Insights) and then communicated to the city in a publicly effective way. u3Green is therefore intended to improve the consideration and participation of young people in urban green planning processes and raise social awareness. 3. Results The data collected via the u3Green-app represent key results focusing on children and young people. An initial analysis of the data shows the following (Fig. 2): 1) Going for a walk is a core activity for the use of urban green spaces; 2) Free Wi-Fi, cleanliness and security, e.g., a ban on alcohol and other drugs, were highlighted as important characteristics of urban green spaces; 3) In addition, the u3Green project provides important insights into the participation of young people in urban planning processes for urban green spaces. u3Green Participation and citizen science with young people u3Green is funded by the Federal Ministry of Education, Science and Research in the Sparkling Science 2.0 program. Going for a walk Wi-Fi Cleanliness Security Fig. 2: Selected results of the u3Green survey The provision of urban green spaces is becoming increasingly important due to the declining living conditions in cities. However, the demands of young people and adults often vary considerably and are not well understood. Furthermore, there are deficits in the participation of children and young people in urban planning, although their involvement in the relevant processes is becoming increasingly important. One of the reasons for this is the specific involvement of young people in citizen science initiatives. The u3Green project addresses these challenges by following the citizen science co- creation approach. Fig. 1: u3Green workflow 1. Understand 2. Develop 4. Analyze 5. Communicate workshops short-term internships long-term internships Basic know


A life expectancy estimator eventually helps personalising care to prevent under- and overuse of preventive care in the growing older population. Abstract citation ID: ckac130.052 Changing epidemiology and trends in incidence of kidney cancer in England, 1985-2019 Anjum Memon Y Salari1, P Bannister1, A Memon1 1Brighton and Sussex Medical School, Department of Primary Care and Public Health, Brighton, UK Contact: a.memon@bsms.ac.uk Background: Kidney cancer is the 7th most common cancer in the UK, accounting for 4% of all new cancer cases. The risk factors for kidney cancer include obesity, smoking, hypertension, and exposure to certain environmental and occupational carcino- gens. We conducted a retrospective population-based cohort study to examine whether there have been changes in the incidence of kidney cancer in England during the past four decades. Methods: Individual level data for patients diagnosed with kidney cancer in England during 1985-2019 were obtained from the Office for National Statistics/Public Health England. Average annual incidence rates were calculated by two age categories (0-49, 50+ years) and all ages combined during the seven five-year time periods (1985-89 to 2015-19). The percentage change in incidence was calculated as change in the average annual incidence rate from the first (1985-89) to the last time period (2015-19). Results: During the 35-year study period, a total of 197,819 new cases of kidney cancer were registered in England (62.4% males, 37.6% females). In young people aged 0-49 years, the average annual incidence rates increased by 164% in males and 144% in females (from 1.4/100,000 in 1985-89 to 3.7/100,000 in 2015-19 in males and from 0.9/100,000 in 1985-89 to 2.2/ 100,000 in 2015-19 in females). In older people aged 50+ years, the rates increased by 129% in males and 147% in females (from 24.5/100,000 in 1985-89 to 56.0/100,000 in 2015-19 in males and from 11.9/100,000 in 1985-89 to 29.4/100,000 in 2015-19 in females). Conclusions: There has been a steady and significant increase in the incidence of kidney cancer in England over the past four decades. The largest increase (164%) was observed in young males aged 0-49 years, which was unexpected. Considering the risk factors for kidney cancer, further research is needed to understand the role of environmental/occupational exposures in causing kidney cancer. Key messages:  About 24% of kidney cancers in the UK are attributed to obesity and 13% to smoking. This research highlights the benefits of reducing the prevalence of obesity and smoking in the general population.  The unexpected significant increase in the incidence of kidney cancer in young people aged 0-49 years needs further investigation. Abstract citation ID: ckac130.053 Changing epidemiology and trends in incidence of thyroid cancer in England, 1985-2019 Anjum Memon R Stonell1, P Bannister1, A Memon1 1Brighton and Sussex Medical School, Department of Primary Care and Public Health, Brighton, UK Contact: a.memon@bsms.ac.uk Background: Thyroid cancer is 2-3 times more common in females and is currently the fastest growing cancer worldwide. Exposure to ionizing radiation is the only established risk factor for thyroid cancer. Other factors include obesity, history of benign thyroid conditions, and family history. We conducted a retrospective population-based cohort study to examine whether there have been changes in the incidence of thyroid cancer in England during the past four decades. Methods: Individual level data for patients diagnosed with thyroid cancer in England during 1985-2019 were obtained from the Office for National Statistics/Public Health England. Average annual incidence rates were calculated by two age categories (0-49, 50+ years) and all ages combined during the seven five-year time periods (1985-89 to 2015-19). The percentage change in incidence was calculated as change in the average annual incidence rate from the first (1985-89) to the last time period


Analítica de Datos en Medidores Inteligentes para la Detección de Robo de Energía Juan C. Olivares-Rojas, Enrique Reyes-Archundia, José A. Gutiérrez-Gnecchi, Johan W. González- Murueta, Adriana Téllez Anguiano Tecnológico Nacional de México / Instituto Tecnológico de Morelia Resumen Resultados Introducción Métodos y Materiales Conclusión Referencias Con los parámetors p, q y d obtenido de los modelos más generales se procede a la elección del modelo definitivo, para ello se utilizó la función auto_arima() de la biblioteca pyramid-arima. Para nuestro ejemplo el modelo seleccionado fue: ARIMA(0, 1, 4). Para la definición del mejor modelo se utlizan métricas como RMSE, MAPE, MAE, AIC y BIC normalizado. Una vez entrenado el modelo se procede finalmente a la predicción de valores futuros. Como puede observarse, el margen de acierto de valores está encima del 95%, por lo que se considera como un buen patrón de perfil de consumo de dicho medidor (Figura 5) El robo de energía es la principal pérdida no técnica de las empresas suministradoras del servicio eléctrico. Con la introducción de medidores inteligentes se registran las lecturas de medición del consumo y producción de energía eléctrica de forma más periódica, lo cual conlleva al posterior uso de esta información. En este trabajo se presenta la analítica de datos de las lecturas de consumo/producción de energía eléctrica de medidores inteligentes que permite determinar un patrón de consumo/producción de energía eléctrica para identificar si los consumos/producción de energía eléctrica pueden ser considerados como robo de energía. Las Redes Generales de Distribución, en CFE Distribución, perdieron en 2017 un 7.96 % de la energía recibida en pérdidas no técnicas con un volumen de 18,268 GWh, esto representó pérdidas económicas significativas para la compañía CFE Distribución [2018]. Tradicionalmente, los medidores de electricidad se instalan en los establecimientos del consumidor y la información de consumo se recopila mediante toma de lecturas a los medidores a través de lecturistas en sus visitas mensuales o bimestrales, dichos medidores son analógicos y presentan ciertas desventajas tanto para el consumidor como para la compañía eléctrica. Al contar con estos medidores, no se puede evitar el error humano en la lectura manual del medidor, existen altas posibilidades de robo de energía eléctrica, ya sea mediante el uso de diablitos, alteración de componentes mecánicos, eléctricos y electrónicos del medidor para cambios de lecturas de los medidores, entre otros. Este trabajo muestra que es posible detectar robos de energía utilizando datos y procesamiento del medidor inteligente. Los resultados indican que la detección de anomalías de consumos/producción de energía eléctrica es adecuada pero que como todo modelo de pronóstico la intervención humana juega un papel relevante en la toma de decisiones. Es importante recalcar que el modelo propuesto ajusta sus parámetros y cantidad de valores de entrenamiento/ajuste a fin de que se ejecuten de forma adecuada en dispositivos embebidos con capacidades de cómputo limitadas. CFE Distribución (2018). Programa de ampliación y modernización de las Redes Generales de Distribución 2018-2032. https://www.cfe.mx/epsdistribucion/cumpliminetoregulatorio/Docu ments/PAM%20de%20las%20RGD%202018-2032.pdf. Fecha de consulta 15 de julio de 2019. Velarde Martínez, A. (2003). Minería de Datos. Una Introducción. Conciencia Tecnológica. (23) Dua, D. and Graff, C. (2019). UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science. https://archive.ics.uci.edu/ml/datasets/Individual+household+electric +power+consumption?. Fecha de consulta 17 de junio de 2019. Se utilizó la metodología tradicional de KDDD listado en la Figura 1. Se tomó un repositorio de la UCI de Dua y Graff [2019] además de las bases de datos de los medidores inteligentes implementados. En primera instancia se hizo una selección de los da


#063E3E Introduction 1. Active Region Detection & Classification 2. Flare Forecasting Results Active Region Detection Automated detection of active regions from full-disk images (right) Active Region Classification Automated classification of active region cutouts (Hale / Zurich) Point-in-Time Flare Forecasts Given observations from a single time (e.g. Magnetogram & EUV) generate a 24 hour forecast flare probability Time Series Flare Forecasts Given a times series of observations forecast time series of flare probabilities (e.g. every 3 hours for next 24 hours) Code releases will be public on GitHub: github.com/arcaff ●Datasets, software (Python packages with documentation), and research findings ●Dataset generation tools & PyTorch “DataLoader” objects will allow for easy benchmarking and direct comparison of models Model Deployment and Monitoring ●Continuous monitoring to track performance metrics and detect data/concept drift ●Results will seamlessly integrate with SolarMonitor.org and PITHIA-NRF.eu The Sun is an enigmatic star that produces the most powerful explosive events in our solar system solar flares and coronal mass ejections. Studying these phenomena can provide a unique opportunity to develop a deeper understanding of fundamental processes on the Sun, and critically, to better forecast space weather. The Active Region Classification and Flare Forecasting (ARCAFF) project will develop a beyond state-of-the-art flare forecasting system utilising end-to-end deep learning models to significantly improve upon traditional flare forecasting capabilities. In particular ARCAFF aim in improve on the accuracy of current methods and introduce the concept of time series forecasts. NOAA AR #: Hale: Zurich: Latitude Longitude 13176 Beta Dki 19° -50° Example training data for NOAA AR 13176 (right) ARCAFF: Active Region Classification & Flare Forecasting Paul Wright, Shane Maloney, Sophie Murray, Peter Gallagher, (Dublin Institute for Advanced Studies) Anna Massone, Michele Piana, Valentina Candiani, Sabrina Guastavino, (University of Genova), Tamas Kiss, Gabriele Pierantoni, Gabor Terstyanszky, (University of Westminster) Robert Lovas, Attila Farkas (Sztaki; Institute for Computer Science and Control) github.com/arcaff www.arcaff.eu @ARCAFF_EU Time Flare Prob (>M) Mockup of time series forecast for at least M class flare Current Time 13171 Beta Cao 23° 39° 13173 Alpha Hsx 25° -10° 13175 Alpha Axx -20° -29° 13169 Beta-Gamma Fkc 22° 60°


What would you do if you lost your research data tomorrow? Take the research data health check… and find help to secure, share and exploit your valuable research. Chances are you could use some helpful pointers in all of these! To find information, support, advice and training, as well as links to external resources, go to www.le.ac.uk/researchdata or email: researchdata@le.ac.uk fully understood your research funders’ data management requirements? Government and funders require that publicly funded research is made available for reuse – are you up to date with their latest policies? Your future funding might depend on it! written a data management plan? Your funder may already require this but build it in from the proposal stage to avoid headaches in the future. gained ethics approval/consent? Writing a data management plan will aid planning and help you to navigate ethics and governance requirements. protected your intellectual property? Leaving intellectual property considerations for a rainy day could lose you appropriate credit, damaging career prospects and perhaps your financial future health! clearly described, in terms of content (using standard metadata)? Ask yourself honestly: is there a danger of data being lost? Will you be able to remember how you generated your data, and will you or anyone else be able to find it in the future when you wish to reuse and share? clearly labelled with versions and dates? How will you remember which was the definitive version and which dataset was used in producing a given research outcome? logically structured and named? Once you’ve remembered how you generated data, can you still find the relevant files? future-proofed against broken links, using persistent identifiers? The persistent identification of digital resources can play a vital role in enabling their accessibility and re-usability over time using recommended data standards. how to restrict access to your research data to the right people? Have you consulted with university or data centre experts so that only the right people have access to your research? which data to keep and which data to discard? Managing research data effectively means being selective: which data to discard and when as well as what to keep and for how long? how securely your data is stored? What happens if your storage media fail? How resilient is it? Could it get left on the train and could somebody else misuse it? how your data is backed-up? Have you made use of university and/or external resources to back up data so that you have multiple copies in case of loss or theft? Organise Create Have you... Are your research files and data... Do you know... Keep find existing information resources related to your research? Where can you find research data that you can repurpose or combine with your own to produce new research? share data with your collaborators securely and effectively? Whether building a collaborative proposal, generating results for others to comment on or sharing the final outputs of your research – how will you link with your colleagues ahead of wider sharing? deposit your research data and outputs in an open repository? Is there an appropriate disciplinary or institutional repository and what do you need to do to deposit your research output? Plan ahead to avoid refactoring... publish your research, and get it cited as well? Institutions and data centres must make research data reusable to others while providing credit to the researchers who did the work. Your future career could depend on it! Find & Share Do you know how to...


Revealing Patterns of Symptomatology in Parkinson's Disease: A Latent Space Analysis with 3D Convolutional Autoencoders E. Delgado de las Heras, F.J. Martinez-Murcia*, I.A. Illán, C. Jiménez-Mesa, D. Castillo-Barnes, J. Ramírez, J.M. Górriz Dpt. Signal Theory, Networking and Communications. University of Granada (Spain) 1. INTRODUCTION 2. METHODOLOGY 2.2 3D CONVOLUTIONAL VAE 3. RESULTS 96 128 3 3 3 3 3 3 3 3 512 σ μ d 32 64 128 256 48 64 24 32 12 16 6 8 96 128 48 64 24 32 12 16 6 8 3 3 3 3 3 3 3 3 SAMPLING 256 128 64 32 ENCODER DECODER Nd(μd,σd) 2.1 DATASET 2.3. EVALUATION 5. CONCLUSIONS This work proposes a novel approach to detect and quantify subtle changes in DaT concentration and distribution in the brain using 3D convolutional variational AEs (CVAEs). The composite variables of the latent space are then modelled using Decission Trees and XGBoost regression, and the spaces are interpreted through visualization and SHAP. Data used for this work was obtained from the Parkinson's Progression Markers Initiative. Speciﬁc cohort from the PPMI database that follows individuals diagnosed with PD and Healthy Control subjects (HC) during 5 years, recording symptomatology via the MDS-UPDRS scale. All the Ioﬂupane I-123 SPECT scans have been intensity normalized to non-speciﬁc areas and a sigmoid function was applied to compress the high-intensity values. - Use the μ parameters of the latent distribution Nd(μd,σd) as features. - K-Means features (KMF) are generated to capture important data characteristics. - Regression using Decision Trees (DT) and XGBoost. - Performance metrics such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and coefﬁcient of determination R2 are computed using 10-fold cross- validation. - SHapley Additive exPlanations (SHAP) is applied to the outputs of each system. Parkinson's disease (PD) affects more than 6.2 million people worldwide. It is characterized by a loss of dopamine-producing neurons in the brain, causing tremors, rigidity, and cognitive decline among other symptoms. Ioﬂupane I-123 binds to the presynaptic dopamine transporters (DaTs), allowing to visualize and quantify DaT concentration at the striata, For top performing 20-D XGB model of UPDRS (total), SHAP reveals: - top-3 features that contribute to the output of the algorithm are latent variables 2, 10 and 0. - Approx. linear dependency between importance to the algorithm output and values of the latent variables. - Composition of variables 2 and 10 accounts for relevant characteristics of Ioﬂupane SPECT imaging: the general intensity of the striata, the separation between them and the uptake ratio between its anterior and posterior parts. - Anterior-posterior uptake ratio more related to progression in the ﬁrst symptoms. Average intensity for the automatic diagnosis of PD. which is key to characterize PD in SPECT imaging. Early detection and monitoring of PD progression could be tackled by modelling a self- supervised, low-dimensional representation of a FPCIT dataset, which enables us to longitudinally compare images and identify patterns of change that are indicative of neurodegeneration. - The latent features of trained CVAEs are related to different aspects of the MDS-UPDRS scale with R2>0.20. - Best performance for UPDRS (total) with latent variables 2 and 10. - Anterior/Posterior ratio are more related to progression of the ﬁrst symptoms. Average striatal intensity for the diagnosis of PD. This work paves the way for exploratory analysis of links between neuroimaging patterns and neurological disorders in an hypothesis-free environment. MANIFOLD EXAMINATION *fjesusmartinez@ugr.es. Signal Processing and Biomedical Applications (SiPBA). Signal Processing and Biomedical Applications http://sipba.ugr.es SiPBA - R2>0 for almost all target UPDRS categories and d- dimensional latent spaces. - Low latent dimensionality (3, 8) is generally for individual perceived symptomatology (UPDRS 1, 2 and 4). - UPDRS - total is better accou


Genetic control of circuit development and function in the zebrafish optic tectum Elena Putti*, Chung-Yuen Chan, Giulia Faini, Dimitrii Tanese, Valentina Emiliani, Filippo Del Bene Neuronal Circuit Development Lab , U968 Inserm – UMR 7210 CNRS Institute de la Vision, PARIS * presenting author, contact: elena.putti@inserm.fr (1) Petros et al., Annu Rev Neurosci, 2008 (2) Gebhardt et al., Nat Comm, 2019 (3) Del Bene et al., Science, 2010 (4) Abdelfattah et al., Science, 2019 (5) Di Donato et al., Genome Research, 2016 Binocular cues can be processed through the direct superposition of ipsi and contralateral retinal inputs1. Although lacking ipsilateral retinal projections, the zebrafish larva shows responses to prey-like stimuli consistent with binocular vision. Previous work of the lab has shown the existence of fundamental neurons essential for this behavior, the intertectal commissural neurons (ITNs)2. ITNs connect tectal hemispheres as a ladder-like array of axonal tracts. These commissural interneurons are key to 3D perception in binocular vision, as they form an intertectal circuit that governs the prey-capture behavior, however their precise function and formation remains elusive. The main goal of this project is to investigate the genetic identity, connectivity and mechanism of action of ITNs. We will take advantage of single cell RNA sequencing in order to dissect the genetic identity of ITNs and further define their role in binocular vision during larval development. Classical molecular biology and behavioral experiments will be used to alter the activity and neuromodulation of these neurons. Moreover, calcium and voltage imaging will be employed to dissect the neuronal circuitry controlled by the ITNs3,4. The hunting sequence in zebrafish larvae is a complex but well characterized behavior. It consists of an initial foraging step where the larva swims in the water, followed by the detection of the prey and its tracking. The larva then fixates on its target before initiating the capture maneuver. When the prey is detected in the strike zone the animal converges its eye in order to increase the binocular field of view. In the zebrafish larva the processing of binocular cues is achieved through the activation of the ITN mediated circuitry by the contralateral RGCs2. 1. from RGCs to ITNs 2. from ITNs to PVNs Dissecting ITNs genetic identity Altering ITNs activity/neuromodulation 2-photon dissection of ITNs neuronal circuitry: The transcriptome profile of ITNs will be established thorugh FACS sorting and single cell RNA sequencing methodologies. The combination of the GAL4 - UAS system with the with the CRISPR/Cas9 technology allows targeted mutagenesis in a tissue specific manner, as previously shown in the lab.5 This tool will be employed to alter ITNs activity and neuromodulation and further assess their involvment in the hunting behavior of larval zebrafish. To characterize the neuronal circuitry controlled by the ITNs we are validating new transgenic lines expressing: 1. an opsin at the presynaptic level 2. GECIs (genetically encoded calcium indicators) or GEVIs (genetically encoded voltage indicators) in the post synaptic cells. With this approach we aim at defining the connectivity between RGCs and ITNs (1) and between ITNs and PVNs (2). a. Tg(vglut:gal4;UAS:opsin;elavl3:gCaMP6s) b. Tg(elavl3:voltageindicator) U6 5xUAS sgRNA1 sgRNA2 Cas9 Tol2 site Tol2 site U6 2a Cre ITN mediated prey – hunting behavior From Di Donato et al., 20165 From Gebhardt et al., 20192 Tg(vglut:gal4;UAS:opsin;elavl3:gCaMP6s) Tg(elavl3:voltageindicator) 3 dpf 4 dpf a) b) 3 dpf This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement #813457.


RE Future Energy Mixture Mohamed Sherwali. Renewable Energy Authority of Libay ( REAOL) 1.Context Contact: Mohamed Sherwali [ msherwali@outlook.com] 5. Policy insights, conclusions and future work 3.Methods & Scenarios Reference Energy System 2.Aim • Libya relying on natural gas and oil to meet the electricity deman. • As there is no renewable is installed yet to the grid, it could be the situation in the future, therefore, the fossil fuel future scenario has been done • In order to reduce CO2 emission and include RE technologies in the power generation mixture as the government set a strategic plan to invest 6 GW in solar and wind technologies by 2035 (1), thus this scenarion has done to investigate CO2 reduction and the needed Dollar investmet • In this study, it has been compared the CO2 emissions and the needed investment between relying just on natural gas and oil to produce electricity in the future, with involving wind and solar technologies for the electricity generation mixture. • Hydro and geothermal sources were not considered as Libya has no potential for these technologies. • Second scenario is to invest about 6 GW in solar and wind by the end of 2035 and what would be the technology to invest more afte 2035 4.Results Country Flag Figure2. Libya Referenve Energy System. 6.References [ 1] The word bank, task D: Strategic Plan for Renewable Energy Development, Least Cost expansion Plan, 12th December, 2017 Mark Howells, Jairo Quiros-Tortos, Robbie Morrison et al. Energy system analytics and good governance -U4RIA goals of Energy Modelling for Policy Support, 10 March 2021, PREPRINT (Version 1) available at Research Square https://doi.org/10.21203/rs.3.rs-311311/v1 Carla Cannone, Lucy Allington, Nicki de Wet et al. clicSAND for OSeMOSYS: a user- friendly interface using open-source optimisation software for energy system modelling analysis, 09 February 2022, PREPRINT (Version 1) available at Research Square https://doi.org/10.21203/rs.3.rs-1338761/v1 Lucy Allington, Carla Cannone et al. Selected ‘Starter kit’ energy system modelling data for selected countries in Africa, East Asia, and South America (#CCG, 2021), Data in Brief, Volume 42, 2022,108021, ISSN 2352-3409, https://doi.org/10.1016/j.dib.2022.108021. … • Is the investment in solar and wind technologies the optimal solution in order to reduce the relying on natural gas and oil to produce electricity? • Its clearly that Fossil fuel scenario is lower cost in term of future investment, on the other hand, the CO2 emissions is very high, as a result this scenario has negatively impact for the environment, also the consequences of future emission penalties • The Government plan to invest 6 GW in solar and wind technology by the end of 2035 is valid in order to reduce CO2 in a lower cost methodology. • Model results suggest to invest in wind technology after year 2035. • Future work: • More assesment for RE scenario. • Flixibilty anaylsis: the impact of the varaible energy to the national grid. • Net Zero scenario by 2070. Map of the country JOINT SUMMER SCHOOL ON MODELLING TOOLS FOR SUSTAINABLE DEVELOPMENT | 2022 Figure1. A Cost-benefit analysis of Policy, Programs and Projects (C3PO) that is Retrievable, Reusable, Repeatable, Reconstructible, Interoperable and Auditable (u4RIA)


A map of genetic variation from 781 soybean genomes Soon-Chun Jeong1,*, Myung-Shin Kim1, Roberto Lozano2, Ji Hong Kim1, Dong Nyuk Bae1, Man Soo Choi3, Soo-Kwon Park3, Michael A. Gore2, and Jung-Kyung Moon4 1Bio-evaluation center, Korea Research Institute of Bioscience and Biotechnology, Cheongju, Korea 2Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, USA 3National Institute of Crop Science, Rural Development Administration, Wanju, Korea 4Agricultural Genome Center, National Academy of Agricultural Sciences, Jeonju, Korea *Corresponding author: scjeong@kribb.re.kr Introduction Soybean (Glycine max [L.] Merr.) is an important crop species. The cultivation of soybean has been historically confined to East Asia. Its cultivation area has been recently expanded to North America, South America, and India, positioning it as one top crop in terms of growing area worldwide. After the release of the draft soybean genome sequence, efforts to map soybean genetic variation by single nucleotide polymorphism (SNP) array genotyping have resulted in the global picture of common and rare SNPs across the genome. However, those data have been poorly used as an integrated manner to serve as haplotype information by imputation approaches that enrich the above SNP genotype data with whole genome SNP data. The resultant genomic data set could also be leveraged as a reference panel to enrich sparse data sets generated from platforms such as low-density SNP array, genotyping- by-sequencing (GBS) or skim sequencing. In addition, genetic variation of wild soybean, which contains a large amount of untapped and unexplored soybean diversity, remains poorly characterized relative to that of domesticated soybean. Here we report genomes of 781 soybean accessions consisting of 418 G. max, 345 G. soja, and 18 hybrid (G. max x G. soja) accessions obtained through high-coverage (> 13x) whole-genome sequence data. We conducted a comprehensive characterization of genetic variation including profiling and functional significance of rare and common genetic variants and detection of domestication-selective sweeps. We are then attempting to show the usefulness of our data in soybean genetics by imputing the SNP data set from 50K US SNP array genotyping using variants identified here for association analyses of protein and oil traits. Materials and Methods Resequencing data from a total of 855 samples were obtained for initial variant calling in this study. We then essentially followed procedures described in the Genome Analysis Toolkit (GATK) Best Practices for data pre-processing and variant calling. Principal component, fastStructure Bayesian clustering, and Neighbor-joining tree construction was used to infer population structure. Historical recombination rate, linkage disequilibrium decay, genomic evolutionary rate profiling, Sorting Intolerant From Tolerant 4G, cross-population composite likelihood ratio test, and genome-wide association studies were performed to infer nucleotide variation pattern, identify selective sweeps, and find association between genotypes and phenotypes. Results and Discussion High heterozygous samples were excluded from further analyses. Distributions of inbreeding coefficient per individuals in subgroups divided by species and heterozygosity indicated that most samples excluded by the high heterozygosity showed an inbreeding coefficient of less than 0.8. Final 781 accessions consisted of 418 G. max, 345 G. soja, and 18 hybrid (G. max x G. soja) accessions. Results and Discussion As observed in the previous study, the 781 accessions were clearly divided into one G. max group and two G. soja groups with a distinct subgroup of G. soja accessions collected from the middle region of the Yellow River basin. Abstract Soybean is an economically and environmentally important major crop worldwide. It is a predominant plant protein and oil source of both food and feed and has capacity to fix atmospheric n


tx 1. Introduction Development and Initial Results from the Inclusion of Evaporation into a 2D dermal absorption model Benjamin Deacon1,2, Samadhi Silva1, Guoping Lian1,2, Marina Evans3, Tao Chen1 b.deacon@surrey.ac.uk 1. University of Surrey, GU2 7XH 2. Unilever, Bedford, 3. US EPA, NC 2. Evaporation 4. Conclusion 3. Model Results References In experimental scenarios, diffusion into the skin is affected by skin and chemical properties; however, in real life scenarios the vehicles' ability to deliver the active into the skin is impacted by the environment. As such evaporation of the vehicle will occur. Where evaporation will depend on the molecular weight, boiling point, vapour pressure and solubility of the solute and the temperature. The main aim is to develop an evaporation code which will be integrated into the Surrey model to improve the finite dose application. Main conclusions: • The model simulated evaporation time course • The model can be applied to a wide range of chemicals • Needs further validation with experimental data Future work includes: • Further application of the model • Experimental work for validation of the model We simulate evaporation of up to three ingredients under ideal and non-ideal conditions. Non-ideal evaporation allows ingredients in the vehicle to interact and this impacts evaporation. The main equations for evaporation of the active ingredients are given below, including calculation of diffusion coefficient and Fick’s law of diffusion: The results shown below have considered a two ingredients vehicle of Water: Diethanolamine at a starting dose of 10.6 ug/L. This dosage is inline with Hewitt et al, 2020. All simulations here have been performed at 32 oc for 24 hours. 𝐷!"#$%& = 𝐵𝑜𝑙𝑡𝑧𝑚𝑎𝑛𝑛𝐶𝑜𝑛𝑠𝑡𝑎𝑛𝑡∗𝑇 6𝜋𝜂𝑟 𝐶𝑜𝑛𝑐!"#$%& = 𝑃'"#$%& × 𝑀𝑜𝑙𝑒𝐹𝑟𝑎𝑐𝑡𝑖𝑜𝑛𝐴𝑐𝑡𝑖𝑣𝑒 𝑅𝑔× 𝑇 𝐽!"#$%& = 𝐷'"#$%&× 𝐶𝑜𝑛𝑐−0 ℎ 𝑑𝑦 𝑑𝑡'"#$%& = −𝐽'"#$%& × 𝐴 The choice of chemicals and the experimental conditions (skin thickness and dosage) have been informed from Hewitt et al., 2020. This poster has shown evaporation for Water: Diethanolamine (MW 105, Solubility 100 g/100ml, Vapour Pressure 0.03 Pa). This model makes the following assumptions: • Condensation has not been considered. • Wind has not been considered • There are no traces of the active present in the atmosphere at t = 0. • The simulation occurs at standard pressure. 0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045 0.005 0.99965 0.9997 0.99975 0.9998 0.99985 0.9999 0.99995 1 Activity Mole Fraction of Water Activity of Diethanolamine Ellison CA, Tankersley KO, Obringer CM, Carr GJ, Manwaring J, Rothe H, et al. (2020) Partition coefficient and diffusion coefficient determinations of 50 compounds in human intact skin, isolated skin layers and isolated stratum corneum lipids. Toxicology in Vitro. Chen, L., G. Lian and L. Han (2008). "Use of “Bricks and Mortar” Model To Predict Transdermal Permeation: Model Development and Initial Validation." Industrial & Engineering Chemistry Research. Hewitt, N. J., S. Grégoire, R. Cubberley, H. Duplan, J. Eilstein, C. Ellison, , et al. (2020). "Measurement of the penetration of 56 cosmetic relevant chemicals into and through human skin using a standardized protocol." Journal of Applied Toxicology Chen, T., G. Lian and P. Kattou (2016). "In silico modelling of transdermal and systemic kinetics of topically applied solutes: model development and initial validation for transdermal nicotine." Pharmaceutical Research Water (mg) Diethanolamine (mg) 0.00E+00 2.00E+05 4.00E+05 6.00E+05 8.00E+05 1.00E+06 1.20E+06 1.40E+06 1.60E+06 1.80E+06 2.00E+06 -1 4 9 14 19 24 Concentration (ug/mL) Time (Hours) Concentration of Diethanolamine Concentration of Diethanolamine Max Solubility of Diethanolamine 0.00E+00 2.00E-03 4.00E-03 6.00E-03 8.00E-03 1.00E-02 1.20E-02 0 5 10 15 20 Volume (uL) Time (Hours) Volume Change of DIethanolamine 0.00E+00 2.00E+00 4.00E+00 6.00E+00 8.00E+00 1.00E+01 1.20E+01 -1 4 9 14 19 24 Amount (mg) Time (Hours) Change in Amount of Diet


Silvia Porporato1, Hamideh Darjazi1, Matteo Gastaldi1, Alessandro Piovano1, Giuseppina Meligrana1, Giuseppe A. Elia1, Claudio Gerbaldi1 1GameLab Group, Department of Applied Science and Technology, Polytechnic of Turin, Corso Duca degli Abruzzi 24, 10129, Turin, Italy Introduction • Large-scale energy storage systems are becoming fundamental for the modern society, particularly to fully exploit major advantages from renewable energy sources, such as wind and solar light. In this respect, secondary sodium-based batteries may represent the key technology since they possess high energy density, low-cost, simple design and easiness in maintenance. Nevertheless, the state of art of the current materials is rather far from a mass commercialization. Beside electrode materials, an essential role is also played by electrolytes and separators, which are deepened in this work. Indeed, many factors must be considered while selecting the best separator, including electronic insulation, low ionic resistance, mechanical stability, chemical resistance to degradation, wettability and uniform thickness [1]. • In this context, we prepared polyurethane-based membranes starting from polyviniyl butyral (PVB) and diisocyanate, by means of a coagulation bath [2,3]. • The choice of PVB as polymer is related to the European project SUNRISE, which aims to find different recycling pathways for this material, normally used as polymeric interlayer into laminated glasses for construction and automotive. At the moment, the PVB fraction collected after consume, that lacks of optical and mechanical requirements for its original purpose, is incinerated or landfilled, causing tons of losses every year, even though it could find a second life within the energy storage panorama [4]. Electrochemical impedance spectroscopy and plating and stripping processes were evaluated, to demonstrate the practical application of the developed materials in laboratory scale Li-based electrochemical cells at various conditions of current rate, temperature and aging. Preliminary results with dense membranes in combination with lithium are highly encouraging for future tests and measurements with sodium, paving the way to the development of more sustainable electrolytes separators for safe, low cost energy storage devices. Conclusions and future perspectives GPC analysis on commercial PVB: Mn (Average, Da) 15˙800 Mw (Weighted Average, Da) 135˙606 Polydispersity index 8 Porous Membrane Dense Membrane Membrane Preparation 4,4′-methylenebis (cyclohexyl isocyanate) H12MDI Solvent NMP 70 °C – 30 min Coagulation bath 1 h 1. Washing process Depending on the coagulation bath, two different materials can be obtained: Polyvinyl butyrral (PVB) Macroscopically identical, but microscopically and operationally diverse FESEM images 2. Drying at 40°C overnight OH concentration determination through IR using 2-ethyl-1-exanol for calibration curve in CHCl3 as solvent: 0.0172 mol OH in 1 g PVB (963 mg of equivalent KOH) 4000 3500 3000 2500 2000 1500 1000 500 0.00 0.05 0.10 0.15 0.20 PVB commercial Porous membrane Dense membrane H12MDI isocianate ATR (a.u.) Wavenumber (cm-1) 0 100 200 300 400 500 600 700 800 -16 -14 -12 -10 -8 -6 -4 -2 0 Derivative Weight Change (%/°C) T (°C) Commercial PVB Porous Membrane Dense Membrane Physico-chemical Membrane Characterization ATR-IR TGA References [1] Arora, P. et al., Chem. Rev., 2004, 104, 4419 [2] Lian, F. et al., J Memb. Sci., 2014, 456, 42 [3] Lv, Z. et al., Chemical Engineering Journal, 2022, 430 [4] F. Duffner et al., Renewable Sustainable Energy Rev., 2020, 127, 10987 [5] Porporato, S. et al., article under submission This work has received funding from the Italian Government (PRIN funding No 2017MCEEY4) and from the European Union's Horizon 2020 R&I program (grant agreements No 958243). 0 100 200 300 400 500 600 700 800 0 100 200 300 400 500 600 700 800 0 50 0 50 Z''/W OCV 5th cycle 10th cycle 15th cycle 20th cycle Z'/W 0 10 20 30 40 50 60 0 10 20 30 40 50


ᚑᚌᚔLinkedOghamStones-SemantischeModellierung undprototypischeAnalyseirischerOgham-Inschriften Timo Homburg, Florian Thiery, Research Squirrel Engineers Einleitung CIIC 81, Macálister CIIC 81, UCC Beispiele von Ogham Wörtern Ogham Umschrift Übersetzung ᚋᚐᚊᚔ MAQI Sohn ᚋᚒᚉᚑᚔ MUCOI Stamm ᚉᚒᚅᚐ CUNA Wolf ᚉᚐᚈᚈᚒ CATTU Schlacht ᚐᚅᚋ ANM Name ᚐᚃᚔ AVI Nachfahre Die Ogham-Schrift ist eine in Irland und im westlichen Teil Britanniens (Wales und Schottland) anzutreffende antike Sammlung von Zeichen, welche überwiegend auf (Grab-)steinen zur Dokumentation von Namen der Verstorbenen, ihrer Verwandtschaften oder auch für kleinere Geschichten verwendet wurde. Nach der Entdeckung der Ogham-Schrift und der anschließenden Erstellung des Ogham-Alphabets datierte MacNeill einige der Ogham-Inschriften. Das wohl kompletteste Standardwerk findet sich in Macálister (1945, 1949). Dieser hat darin das weitverbreitete Nummerierungsschema CIIC etabliert. Das Ogham 3D Projekt scannt derzeit (155 Ogham Steine verfügbar) irische Ogham-Steine und stellt diese als Epidoc zur Verfügung. Semantische Modellierung in Wikidata Integrationsworkflow Wikidata Beispiel Wikidata Ogham Steine Nachdem die Informationen aus analogen Editionen extrahiert und mit Verweisen zu anderen Linked Data Ressourcen verlinkt wurden, können die Daten in Wikidata integriert werden. Hierzu werden die Tools ‘Open Refine‘ und ‘Quick Statements‘ genutzt. Mit der Integration in Wikidata ist nun die Grundlage geschaffen die angereicherten Daten mit Hilfe des SPARQL Unicorn zu verarbeiten. Somit sind weitergehende Analysen mit Open Source Software wie R oder QGIS mit dem ‘SPARQLing Unicorn QGIS Plugin‘ möglich. Analyse Oghamsteine in Irland Ogham Analysen Ogham Density Karte Wir stellen die Ogham-Steine als Linked Data bereit und ermöglichen somit deren Verarbeitung durch eine Reihe von Wissenschafts-Communities. Die Erfassung der Ogham-Steine als Linked Data Ressourcen erlaubt es, durch Verknüpfung von Wissen und dessen Anreicherung folgende Forschungsfragen anzugehen (1) Klassifikation von Steinen (2) Visualisierung von Zusammenhängen wie Verwandtschaftsbeziehungen (3) Formale Erfassung und maschi- nenlesbare Kodierung von Ogham-Zeichen. Als Datenbasis für die Analysen stützen wir uns auf eine Wikidata-Retrodigitalisierung des CIIC Corpus von Macálister (1945,1949), Epidoc-Daten des Ogham in 3D Projekts, sowie auf die Celtic Inscribed Stones Project (CISP) Datenbank. Des Weiteren pflegen wir aktiv fehlende und passende Elemente in Wikidata ein, um so später die Daten der Research Community im Sinne des SPARQL Unicorn bereitzustellen. Erste Extraktionsergebnisse zeigen zunächst die Clusterung der irischen CIIC Oghamsteine in Abbildung links, sowie die räumliche Verteilung von Beziehungen in Abbildung mitte und eine räumliche Vertelung in einer Density Map in Abbildung rechts. Weitere Informationen timo.homburg@hs-mainz.de rse@fthiery.de http://ogham.link


Kwon et al. (2018): Hypothetical reaction on discovery of microbial ETL tends to be positive Bains & Petowski (2021): Astrobiologist adjust probability assessment of ETL but not in a baysian way Routledge et al. (2017): Paranormal belief in ET satisfy the search for meaning Niklas A. Döbler and Claus-Christian Carbon University of Bamberg, Departement of General Psychology and Methodology Exopsychology and the human perspective on the extraterrestrial (mind) Contact: Niklas A. Döbler: niklas.doebler@uni-bamberg.de - https://orcid.org/0000-0001-7935-727X Exopsychology How do extraterrestrials think? Theoretically investigating cognition, behavior, affects, and motives of extraterrestrial agents How do we think extraterrestrials? Empirical focus on human beliefs, attitudes, and representations Exopsychology rejects the notion of intelligence due to the concept‘s inadmissible anthropocentric normativity. Yet, it acknowledges the importance of it when thinking and talking SETI and extraterrestrials Employs admissible over inadmissible anthropocentricism to generalize our condition to the stars but trades definitional acuity for applicability Extraterrestrial intelligence Extraterrestrials seen as: Methods N=75 persons (50F, 24M, 1 NA, MAge = 28.27) rated 54 pictures of cinematic depictions of ETs on different scales (1-5) Prediction of trustworthiness as central outcome Prior µ = 0, SD = 1 Findings Psychological similarity is more important than physical human-likeness Liking as strong positive, aggressiveness as strong negative predictor Intelligence plays subordinate role Limitations Comparability between images Missing values due to decision not to answer (M = 5.30%, SD = 0.54) High-cognitive Cognition as basic mental processes to organize, employ and utilize knowledge Continuum, inherent to every instance of life „Higher“ cognition: Thinking about thinking Meta-cognitive execution of behavioral and mental protocols and monitoring the outcomes Agents „Behavior governed by thought“[2] Purposefully interact and engage with the environment Download Döbler & Raab (2021): „Thinking ET – A discussion of exopsychology“[1] Implications  SETI is first and foremost looking for higher cognition and agency – not plain intelligence  Responsible for any technosignature, extraterrestrials must utilize their knowledge to purposefully adapt the environment to their demands  Success of any first contact requires reciprocal psychological compatibility Mere engagement is not enough. Necessary skills and abilities, depending on socio-material and individual characteristics to exploit multiple relevant affordances must be present to engage with space research Organisms respond to relevant affordances to improve their grip on the situation and reduce an internal disequilibrium[3] Open questions: Which environmental and individual features bring forth relevant affordances for technology and space research? How can METI create a relevant affordance and evoke action readiness to respond? Which quality has the internal disequilibrium? Think about yourself: Why are you interested in space and its inhabitants? What do you need to pursue your research? One small step further Depending on physical attributes, abilities, and social- material environment of ET, a planet affords actions ET picks up affordances and creates behavioral outcomes detectable by SETI  Planet may afford requirements for technologization, but ET does not have relevant skills and abilities or affordances lack relevance  Planet does not afford actions necessary for space research Further research on how we think about ET Information from space exploration and SETI efforts. Edited to be understandable Hypothetical prevalence of extraterrestrial with overwhelmingly unknown characteristics. Information about our existence as cognitive agents in the universe Accessible information, limited by our physical position in the universe and technological and scientific


Main Outputs BE OPEN targets the promotion, regulation and standardization of Open Science in transport research through ➢ developing a framework of common understanding for realizing Open Science services that will provide technical interoperability, data and information interoperability and legal interoperability; ➢ developing the TOPOS forum and observatory for different stakeholders to support an evidence based dialogue; ➢ providing a roadmap and concrete guidelines for operationalizing Open Science services and guide key actors on how to adopt and adapt Open Science services in their research workflows; and ➢ designing a Code of Conduct for adopting them considering the main legal and security issues for their implementation. BE OPEN “European forum and oBsErvatory for OPEN science in transport” Caroline Almeras1 Afroditi Anagnostopoulou2 Maria Boile2 1 European Conference of Transport Research Institutes (ECTRI) 2 Centre for Research and Technology (CERTH)/ Hellenic Institute of Transport (HIT) caroline.almeras@ectri.org, a.anagnostopoulou@certh.gr, boile@certh.gr Abstract The BE OPEN “European forum and oBsErvatory for OPEN science in transport” project aims to create a common understanding on the practical impact of Open Science and to identify and put in place the mechanisms to make it a reality in transport research. Achieving Open Access to publications, making their underlying data FAIR (Findable, Accessible, Interoperable, Reusable) and open where possible, and using open and collaborative processes and infrastructure via the European Open Science Cloud (EOSC) are key factors in making transportation researchers share-reuse-reproduce science and in bringing such a critical sector closer to the society for enabling open innovation and citizen science. Openness, transparency, fairness, reproducibility of science are key aspects around which BE OPEN will seek to establish the ground rules for the transport research communities, ultimately establishing a community of transport research organizations willing to work on the basis of a commonly agreed “Open Science Code of Conduct”. To this end, BE OPEN has brought on board key transport and open science related communities in a two-fold action plan: to engage them in a participatory approach fostering a dialogue on Open Science (what exists, what should be done, how it should be done) among relevant stakeholders in Europe and around the world, and develop a detailed roadmap for the implementation of sustainable open science modules which include key practices, infrastructures, policies and business models, all taking into account the specificities of the transport research domain, and the use and integration of existing-infrastructures and the emerging EOSC initiative. Expected Impacts ❖TOPOS forum and observatory tools will contribute to creating a solid knowledge base on the implementation of Open Science approach in transport research ❖Governance and new operational/business models will be developed for enhancing Open Science by describing the rationale of how to create and capture value in economic and social context ❖The European Code of Conduct on Open Science in transport will be developed proposing recommendations and proper guidelines that allow setting up a community of transport research organizations ❖Awareness and visibility (authorities, Industrial and SMEs Associations in Transport, Publishing Companies, and the various European Technology Platforms, and strong media coverage) will be created ❖International stakeholders will be engaged in mutual learning and sharing experiences Objectives The BE OPEN project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 824323.