dataesr/scientific-paragraphs-categorization huggingface dataset:
Vector boson fusion process selection The VBF process ( pp → W j j → W Z j j) is characterized by the presence of two jets with a large rapidity gap resulting from quarks from which a vector boson has been radiated. To select the signal events, an artificial neural network with a binary classification task is used: events are categorized as belonging either to a VBF process or to the background. The ANN training is implemented using the Keras package  [89]  running on top of the TensorFlow package  [90]. An ANN training region is defined by requiring events to have at least  In order to minimize the statistical uncertainty, a 4-fold cross-validation technique was applied. A rectified linear unit, or a ReLU, was used as an activation function at each node  [91]. The space of hyperparameters was scanned and a final set was chosen to ensure optimal performance of the network.
They are the dominant experimental uncertainties in the VBF selection. Those due to the jet energy scale and resolution are obtained from simulations and in situ techniques  [101]. The uncertainties in the b-tagging efficiency and the mis-tag rate are also taken into account. The effect of jet uncertainties on the expected number of events ranges up to 15% in the VBF selection. Uncertainties in the efficiencies of the lepton triggers are found to be negligible. The uncertainties due to the electron and muon reconstruction, identification and isolation requirements are estimated using tag-and-probe methods in Z → events in data and simulation  [78, 79]. Uncertainties in the lepton energy scale and resolution are also assessed. The impact of lepton uncertainties on the expected number of events is typically below 1%.
Acknowledgements We thank  CERN  for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of  ANPCyT , Argentina; YerPhI, Armenia;  ARC, Australia ;  BMWFW  and  FWF , Austria; ANAS, Azerbaijan;  CNPq  and  FAPESP, Brazil ;  NSERC ,  NRC  and  CFI ,  Canada ; CERN;  ANID, Chile ;  CAS ,  MOST  and  NSFC, China ;  Minciencias , Colombia; MEYS CR, Czech Republic; DNRF and  DNSRC, Denmark ;  IN2P3-CNRS  and  CEA-DRF/IRFU , France; SRNSFG, Georgia; BMBF,  HGF  and  MPG , Germany; GSRI, Greece; RGC and  Hong Kong SAR, China ;  ISF and Benoziyo Center, Israel ;  INFN, Italy ;  MEXT  and  JSPS, Japan ; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DSI/NRF, South Africa; MICINN, Spain;  SRC and Wallenberg Foundation, Sweden ;  SERI ,  SNSF  and  Cantons of Bern and Geneva, Switzerland ; MOST, Taiwan; TENMAK, Türkiye; STFC,  United Kingdom ;  DOE  and  NSF ,  United States of America.
In addition, individual groups and members have received support from  BCKDF ,  CANARIE ,  Compute Canada  and  CRC ,  Canada ;  PRIMUS 21/SCI/017  and  UNCE SCI/013 , Czech Republic; COST,  ERC ,  ERDF ,  Horizon 2020  and  Marie Skłodowska-Curie Actions ,  European Union ;  Investissements d'Avenir Labex, Investissements d'Avenir Idex  and  ANR, France ;  DFG and AvH Foundation ,  Germany; Herakleitos ,  Thales  and  Aristeia  programmes co-financed by  EU-ESF  and the  Greek NSRF, Greece; BSF-NSF  and MINERVA, Israel; Norwegian Financial Mechanism 2014-2021, Norway;  NCN  and  NAWA, Poland ;  La Caixa Banking Foundation ,  CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain ; Göran Gustafssons Stiftelse, Sweden; The  Royal Society and Leverhulme Trust ,  United Kingdom.
4E ). Using non-parametric permutation testing, we found the retrograde spread model with the curated set of seven seed regions significantly (p<0. 01) outperformed both single (dark-gray) and multiple seed (light gray) null models in all age groups regardless of cortical mice inclusion. The retrograde model also significantly (p<0. 05) outperformed the "rewired" network null models at 10 and 11mo with inclusion of cortical brains, and in 10, 11, and 12mo age groups with the three cortical brains excluded. These results further indicated that p-tau spread in PS19 mice was driven specifically from these seven seed regions and was strongly related to the underlying connectome architecture mapped in the Allen Mouse Brain Connectivity Atlas. Overall, these data indicated that neuronal p-tau accumulation patterns across age were primarily propagated via the anatomical connectome as opposed to absolute Euclidean proximity between the regions, and that spread between regions was biased towards the retrograde direction.
Background. Between the various number of different AIDs, the absolute majority remains to be rare, with a single representative among big populations. Project, endorsed by PRES and supported by the EMERGE fellowship program, performed in line with the Metadata registry for the ERN RITA (MeRITA), had an objective to perform data harmonization attempt of the most relevant research questions regarding clinical features, diagnostic strategy, and optimal management of the autoin ammatory diseases. Results. Analysis of 3 large European registries: Eurofever, JIR-cohort, and AID-Net with total coverage of 7825 patients from 278 participating centers all over the world was performed in the context of the epidemiological and clinical data merging. Information summarized in the registries covers not only pediatric patients, but as well adults, with newly diagnosed AID.
The Eurofever registry, a multi-national clinical registry hosted by the Pediatric Rheumatology International Trials Organization (PRINTO; www. printo. it) was held in the context of the Pediatric Rheumatology European Society (PRES) since 2009  [10]. At the same time, a German national database for autoin ammatory diseases, the AID-NET, was set up  [11]. This registry collected information and samples of German patients with SAID for 10 subsequent years, until 2018. In 2013, the JIR Cohort, a multicenter prospective data repository for patients with systemic in ammatory or rheumatological disease, was created in the context of francophone countries, and subsequently extended towards other countries. A speci c module dedicated to AID was developed in 2016, and patients from the main centers of expertise for autoin ammatory diseases in France and Switzerland have been enrolled.
Materials And Methods The three registries (Eurofever, JIRcohort and AID-net) collect information on SAID patients in Europe and in extra-European countries. The list of variables subject to the evaluation of the present study were discussed in a consensus meeting held in Chateau d'Oex (Switzerland) in October 2021 (supplementary table 1). Basic set of the epidemiological data was extracted anonymously by each coordinator, provided and analysed as aggregated data (e. g. no individual patient's data provided). As well, each registry representative provided information about cohort design, duration and procedure of patients follow-up, chapters about main epidemiological, clinical and laboratory information, data collection methods, process of IT-support, etc. This study as well included the review of published articles with studies based on registry data.
Evaluation of the extracted information was descriptive, more than comparative. IBM SPSS (SPSS Inc. Chicago, IL, 29. 0) and excel were used for descriptive statistics including frequencies for categorical variables; median ( rst and third quartiles) for numerical variables. Data analysis was conducted by YV during a 6-months PReS EMERGE fellowship, with attendance at CHUV Lausanne (Switzerland), IRCCS Istituto Giannina Gaslini in Genoa, and UKM in Muenster (Germany), each for 2 months respectively. Origin and structure of the three registries Eurofever The Eurofever project was promoted in 2008 by the SAID working group of the Paediatric Rheumatology European Society (PRES) and supported by the Executive Agency for Health and Consumers (EAHC, project 2007332). The electronic data capturing (EDC) system of the Registry has been developed by PRINTO in November 2009.
All centres belonging to the PRINTO network dealing with AID were offered the possibility to participate to the registry. In addition, adult centres involved in the management of SAID were also invited to participate. The original structure of the registry consisted of 2 parts -demographic information and clinical manifestations. In 2015 a protocol amendment updated the registry with the new AID, and with the elaboration of a longitudinal observational part. The quality control applied to the registry consists of a routinely check of the completeness and coherence of the data by the PRINTO staff; if any relevant query is raised during the check, a question is addressed to the Investigator to con rm or modify the data. Collection of the information has longitudinal prospective design, with regular onsite supervision of the PRINTO technical support.
AID-Net All members of the GKJR (German Society for Pediatric Rheumatology) were invited to participate in the project. In addition, immunological and molecular genetics laboratories had their own access to the online system for documentation of sample management. The online registry was operating by EDC with easy handling. All data were entered via remote data entry software ProMISe (Project Manager Internet Server) version 2. 0, which had been developed by R Brand. Technical and operating support of the registry was provided by Sabrina Fühner and Elke Lainka. Data check and validation were provided on demand within particular scienti c projects.
From the onset, the registry is organized through 3 managing committees -steering, scienti c and executive with members representative from the participating countries. The registry is hosted by the Foundation RES whose goals are to support research and training in pediatric rheumatology. Registry data are collected by the investigating physician or clinical research technician in a prospective manner, and in a few centres the register serves as a medical record. The registry is composed of a common core for all diseases and speci c modules collecting disease-speci c data (autoin ammatory diseases, systemic onset JIA, JIA, uveitis, lupus). All the data before 2013 was collected retrospectively, after 2013 the register functions as a longitudinal observational cohort. The registry works on "OCQMS" -a software developed by Swiss IT company Seantis Gmbh, a software already successfully used by the Swiss adult rheumatology registry (SCQM).
Demographic data In total, all 3 registries cover 7825 patients with different AID from 278 participating centers all over the world (Fig. 1 ). AID-Net is a national registry involving 36 main pediatric rheumatology centers in Germany. JIR and Eurofever are multi-national cohorts, covering about 40 countries in total. Data collection in AID-Net was completed in 2009, but JIR and Eurofever continue active recruitment and follow-up children previously included. Information summarized in the registries covers not only pediatric patients, but as well adults, with newly diagnosed AID and different proportion of the last (table  1 ). The most commonly met AID in the registries are FMF, PFAPA, SURF (Unde ned Recurrent Fever), CRMO, SoJIA, CAPS, TRAPS and MKD, which demonstrates a general trend in the population.
7%), with pathologic ndings in 789 (46. 7%) of the tests performed. Sanger sequencing was performed in the majority -1003 (59. 5%), NGS -193 (11. 4%) tests, and in 491 (29. 1%) the method was unknown. In the AID network, 735 (53. 4%) patients were tested, with most relevant exons in 406 (55. 2%), complete gene screening in 88 (12%), whole exome sequencing in 23 (3. 1%), and most relevant point mutation in 9 (1. 2%). In 209 (28. 4%) results, the testing method was unknown. The process of the clinical data merging among the registries can be more complicated than previously expected, depending on the depth of the information required to be analyzed (Table  4 ). The availability of data related to the treatment was also investigated. Drugs included for treatment of AID were divided for main groups: steroids, synthetic DMARDS, biologic DMARDS and NSAIDs.
Discussion In this study, we provide the evidence on the actual possibility to merge demographic, genetic, and clinical data from different registries on rare conditions taking as an example three "historical" registries in the context of autoin ammatory diseases. The study explores the degree of homogeneity among the three registries and the possibility to retrieve scienti cally relevant information from their demographic part. Many critically important questions arise around clinical features, diagnostic strategy and optimal management of the AID. Due to low incidence of the diseases no single registry will be able to answer all these questions and they must follow de ned purpose that re ects the process of data collection and items being collected. We were able to show in this study that registers for auto-in ammatory diseases, developed independently in speci c contexts and countries, nevertheless present an important homogeneity in the variables recorded: all of them include main epidemiological data (with a focus on the date of diagnosis, age, gender, origin), similar clinical part, involving manifestations from the main systems and organs, part of the laboratory investigations, genetic testing availability, and treatment.
The possibility of data merging is performed at the example of ethnicity characteristic (tabl. 2) and demonstrates, that type of data collection may signi cantly in uence resulting outcome. At the cost of a reclassi cation of some data, we have shown that merging data from different registries is possible and provides cohorts with many patients, even for exceptional diseases (suppl. table  2 ). The main and global problem of the AID is their rarity, which makes patient enrolment and data collection complicated, especially from the point of the treatment strategy evaluation, when medications are new or to perform cohort studies when information should be merged from couple of resources. Two of the three registries continue active recruitment, at the same time availability of the biobank of AID-Net allows them to be counted active as well.
Challenges: Identifying patients that have been entered into different registries is potentially noticeable according to the distribution of the centers (Fig. 1 ). Our study was not aimed to detect possible multiple entries of the same patient into different registries. However, this possibility should mandatory in any process of merging data coming from different registries This issue can be addressed with mechanisms similar to those used by the recent ERN RITA project, named MERITA automatic system that allows to reduce and exclude duplicated data should be used for all studies to provide further more accurate collaborative work. These questions should be addressed to IT support or discussed at the site level, before collaborative studies, because the presence of encrypted information made not possible a manual check.
Very detailed analyses remain di cult. Indeed, the granularity of the data is not identical. It's possible to follow the simplest questions regarding particular clinical signs of the disease or describe the presence of speci c tests. Combining data from different cohorts de nitely increases the statistical power of the results, but must be done carefully, cause usually similar points of view don`t provide similar result outcomes. Different methods of outcome ascertainment (collection of clinical information, symptoms details, results of investigations, treatment) may cause a signi cant difference in results even if the primary working model was similar. Standardization or uni cation of the clinical data on AID will allow overcoming the problems of data merging in future Longitudinal collection of the information should provide correct outcomes over time, identify clinical changes or predict short and long-term outcomes and evaluate treatment effectiveness and safety.
2020; Engel et al. 2021 ). When expertise is not available, we strongly recommend producing at least one DNA barcode sequence for each weevil morphospecies involved in a system and depositing it on international databases (e. g. , de Medeiros et al. 2019), and using images in addition to names to document weevil flower visitors (e. g. ,  Núñez-Avellaneda & Rojas-Robles, 2008; Núñez et al. 2015; Guerrero-Olaya 2017; de Medeiros et al. 2019). The associated voucher specimens should also be deposited in permanent collections of museums or institutions. These two procedures will make it possible to considerably improve species description rates, but also the knowledge on their ecology and distribution.
Acknowledgements We would like to thank all the researchers who have contributed to the recognition of the importance of plant-weevil pollination mutualism through detailed and time-consuming descriptions of the taxonomy, ecology and physiology of these systems. We thank  Z. Dao  ( Joseph Ki-Zerbo   University, Ouagadougou, Burkina Faso ),  M. Gueye  ( UCAD, Dakar, Senegal ) and  R. G. Oberprieler  ( CSIRO, Canberra, Australia ) for providing images of weevils and details on the plant-weevil interactions listed in this article. This work was supported by recurring funding from  CIRAD  ( Julien Haran ) and  INRAE  ( Gael J. Kergoat ). Bruno de Medeiros  was funded by a  STRI  postdoctoral fellowship while writing this manuscript.
Statistical Analysis Statistical analysis was performed with GraphPad Prism 7 (GraphPad Software Inc, Boston, MA, USA). All data are presented as the mean ± standard deviation (S. D. ). Differences between two groups were compared by the Welch-corrected unpaired two-tailed Student's test or by analysis of variance (ANOVA) with Dunett's post hoc test. p-values < 0. 05 were considered statistically significant if not stated otherwise.
The benchmark experiments, covering a wide range of applications, from thermal light water reactors (LWRs) and high temperature reactors (HTRs) to fast reactors of various designs or even special applications, are most often obtained via zero power reactors, many of which have been shut down or are nearing the end of their expected lifetimes. These two exemplary benchmark programs, and their widely utilized handbooks, serve as gold standards to which other databases strive to emulate, such as the OECD NEA Spent Fuel Composition (SFCOMPO) database  (Michel-Sendis, et al. , 2017) , the OECD/IAEA (International Atomic Energy Agency) co-sponsored International Fuel Performance (IFPE) collection  (Menut, et al. , 2000) , the International Experimental Thermal Hydraulics Systems (TIETHYS) database  (Rohatgi, et al.
, 2018) , the collection of multi-physics experiments being created by the NEA Expert Group on Reactor Systems Multi-Physics (EGMUP)  (Valentine, et al. , 2018) , and the OECD-NEA/RSICC (Radiation Safety Information Computational Center) co-sponsored Shielding Integral Benchmark Archive and Database (SINBAD)  (Kodeli and Sartori, 2021). From the inception of the ICSBEP until very recently, both the ICSBEP and IRPhEP have been managed by a single chair, nominated and endorsed by the technical review group (TRG), whom has historically been from the United States (US). Most recently, the management of these projects has been divided into two separate chair and vice chair positions and expanded to include non-US representatives. The purpose of the two projects is to preserve both legacy and current generation experiment data and evaluate it in a standardized handbook format to provide quality benchmarks to support modern and future criticality safety and reactor physics validation.
Enhanced handbook database tools The already extensive and yearly increasing handbooks' content required development of an evolving database structure to collate, organize, and better facilitate their use. The Database for the International Handbook of Evaluated Criticality Safety Benchmark Experiments (DICE)  (Nouri, et al. , 2003)  was developed specifically for the ICSBEP Handbook. This relational database is loaded with preselected information from each of the benchmark evaluations. A users' interface enables querying for specific parameters to identify benchmarks suitable for their respective needs. DICE also includes the ability to plot and compare neutron spectra and sensitivity coefficients for many evaluations. The IRPhEP Database and Analysis Tool (IDAT)  (Hill, et al. , 2014)  was similarly developed for use with the IRPhEP Handbook.
ZPPR-20 phase C: A cylindrical assembly of U metal reflected by beryllium oxide The ZPPR-20 experimental series provided data for development of the SP-100 nuclear power source for space applications. Phase C represents the reference flight configuration. Phases D and E represented water immersion and earth burial accidents and are also available as benchmarks. Benchmark identifiers: ZPPR-SPACE-EXP-001 (IRPhEP)/HEU-MET-FAST-075 (ICSBEP).
Neptunium-237 and highly enriched uranium replacement measurements performed using flattop A high-purity sample worth for 237 Np was evaluated for a replacement measurement performed with the Flattop uranium sphere (MIX-MET-FAST-002 in ICSBEP). Benchmark identifier: SPEC-MET-FAST-003 (ICSBEP). 5. 4. 5. 5 Neptunium-237 sphere surrounded by hemispherical shells of highly enriched uranium A neptunium sphere was encased within matching pairs of HEU shells to decrease the uncertainty in the critical mass of 237 Np for criticality safety and non-proliferation issues (see Figure  12 ). Benchmark identifier: SPEC-MET-FAST-008 (ICSBEP). The Benchmark for Evaluation And Validation of Reactor Simulations (BEAVRS) is a multi-cycle full-core PWR depletion benchmark based upon measurement data from two operational cycles of a commercial nuclear plant.
Reactivity worth measurements of major fission products in MINERVE LWR-Lattice experiment The reactivity worth of major fission products was measured in the MINERVE reactor in Cadarache, France as part of the CERES program between France and the United Kingdom to validate LWR fuel reactivity loss with burnup. The CERES Phase II measurements performed in MINERVE are evaluated in this benchmark for various isotopes including Sm, Nd, Gd, Eu, Rh, Cs, Mo, and Tc. Benchmark identifier: MINERVE-FUND-RESR-001 (IRPhEP). five baseline cases. Benchmark identifier: HEU-MET-MIXED-021 (ICSBEP).
Conclusion The ICSBEP and IRPhEP actively provide international preservation, evaluation, and dissemination of integral benchmark data to support computational validation of models, simulations, and nuclear data in support of criticality safety and reactor physics applications. Annual contributions to their respective handbooks provide an ever-growing resource of evaluated benchmark experiment data that has been assessed qualitatively and quantitatively to provide uncertainties, biases, and established benchmark models within a standardized handbook format. All benchmark evaluations undergo an intensive peer-review process with participants and contributions representing over 20 countries. Experiments were performed historically to support reactor operations, measurements, design, and nuclear safety.
The extensive investments in infrastructure, expertise, and cost are not cheaply reproduced should the information from these legacy experiments become lost. The preservation and evaluation activities of the ICSBEP and IRPhEP provide a means to provide quality nuclear data for current and future needs in computational tools and nuclear data testing. The needs of the nuclear modeling and simulation community continues to expand and evolve. The ICSBEP and IRPhEP provide well-established frameworks to continue to provide high-quality, peer-reviewed benchmark data to serve as the intrinsic backbone of contemporary neutronics methodologies, simulation, and nuclear data. The true value of their handbooks is priceless considering the impact they have in supporting, sustaining, and enabling modern nuclear safety, design, modeling, and simulation.