dataesr/scientific-paragraphs-categorization huggingface dataset:
Average iFC values from clusters exhibiting a puberty-X-sex interaction, or main effects of sex or puberty, were extracted using 3dmaskave. Post hoc comparisons were conducted within SPSS v24 and interactions were probed using the PROCESS v216  88  macro by calculating the beta value for the relationship between puberty and iFC for male and female participants, while controlling for age and scanner site. Levene's test for equality of variances, and measures of skew and kurtosis are reported in Supplemental Table  S2. Importantly, all clusters exhibiting an interaction between puberty and sex are normally distributed. Furthermore, although variance is not equal between groups for all identified clusters, multiple regression analyses, which do not entail equality of variance assumptions, demonstrate that identified interactions remain significant within a multiple regression framework (Supplemental Tables  S3-S4 ).
Brain-behavior analyses based on factorial approach To reduce the number of variables, two sets of principal components using SAS-9. 4 program were extracted from the neural data at baseline (14 years old), and the behavioral data collected at 2-year follow-up (16 years old). All the iFC clusters significantly modulated by puberty and/or sex were entered into one factor analysis, and 15 items of the SDQ into a separate factor analysis. These factor analyses used ones as prior communality estimates. The principal axis method was employed to extract the components, and this was followed by a varimax (orthogonal) rotation. Only two DAWBA bands were retained for this analysis, generalized anxiety disorder and depression, based on our main interest in these frequently comorbid diagnoses  89, 90.
Acknowledgements Dr Stringaris  receives royalties from the  University of Cambridge  for his book. Dr. Banaschewski  served in an advisory or consultancy role for  Actelion, Hexal Pharma, Lilly, Medice ,  Novartis , Oxford outcomes, PCM scientific,  Shire , and  Viforpharma. He  received conference support or speaker's fee by  Medice ,  Novartis , and  Shire. He  is/has been involved in clinical trials conducted by  Shire & Viforpharma. He received royalities from  Hogrefe, Kohlhammer, CIP Medien, Oxford University Press. The present work is unrelated to the above grants and relationships. This work received support from the following funding sources: the  European Union -funded  FP6  Integrated Project IMAGEN (Reinforcementrelated behavior in normal brain function and psychopathology) ( LSHM-CT-2007-037286 ), the  Agence Nationale de la Recherche ANR  (project  AF12-NEUR0008-01-WM2NA , and  ANR-12-SAMA-0004 ), the  Fondation de France  (grants  2012-00033703  and  2017-0008L242 ), the  Fondation pour la Recherche Médicale  (grants  DPA 20140229802  and  DPP20151033945 ), the  Fédération pour la Recherche sur le Cerveau  ( AAP 2014 ), the  Mission Interministérielle de Lutte -contre-les-Drogues-et-les-Conduites-Addictives (MILDECA), and the  INSERM  ( interface grant  to the the  Assistance-Publique-Hôpitaux-de-Paris ); The  Academy of Finland  (grant number  276612  to A.
Further support was provided by grants from: the  National Institutes of Health, Science Foundation Ireland  ( 16/ERCD/3797 ),  USA (Axon, Testosterone , and  Mental Health during Adolescence ;  RO1 MH085772-01A1 ), and by  NIH Consortium  grant  U54 EB020403 , supported by a cross- NIH  alliance that funds Big Data to Knowledge Centres of Excellence. This work was supported by the  European Union -funded  FP6   Integrated  Project  IMAGEN  ( LSHM-CT-2007-037286 ); the  FP7  project  IMAGEMEND  ( 602450 ); the  Innovative Medicine Initiative Project European Autism Interventions-A Multicentre Study for Developing New Medications (EU-AIMS ) ( 115300-2 ); a  Medical Research Council Programme  ( 93558 ); the  Swedish funding agency Formas ; the  Wellcome Trust  ( University of Cambridge ); the  National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London ; the  Department of Health United Kingdom ; the  Bundesministerium für Bildung und Forschung (BMBF)  ( 01GS08152 ,  01EV0711 , eMED SysAlc01ZX1311A,  Forschungsnetz AERIAL ); the  French funding agency Agence Nationale de la Recherche (ANR)  ( ANR-12-SAMA-0004 );  Eranet-Neuron  ( AF12-NEUR0008-01-WM2NA ); the  Assistance-Publique-Hôpitaux-de-Paris and Insitut national de la santé et de la recherché médicale (INSERM , interface grant);  Paris-Descartes-University  (collaborativeproject-2010);  Paris-Sud-University  ( IDEX-2012 ); the  Fondation de France ; the  Fondation pour la Recherche Médicale  ( DPA20140629802 ); the  Mission Interministérielle de Lutte -contre-les-Drogues-et-les-Conduites-Addictives.
Finally, all landmarks were projected on the ovipositor and they slided to minimize bending energy taking into account the ovipositor object symmetry  (Gunz et al. , 2005). In total 529 landmarks described the ovipositor shape for each individual. This process follows the protocol described by  Botton-Divet et al. (2015). The template was created with Meshlab  (Cignoni et al. , 2008)  and the position of these landmarks and the subsequent sliding were performed with the R package Morpho  (Schlager, 2017). To assess the quality of the 3D shape reconstruction we replicated the reconstruction process five times on two individuals from the same geographic population and raised at the same temperature (two Sapporo individuals raised at 16°), so the variance between individuals was minimized as much as possible.
Differences among slopes were tested with an ANOVA. All morphometric tests were applied in the R package geomorph  (Adams et al. , 2018). Finally, we investigated the degree of relative robustness of the ovipositor, by comparing its variation with that of the wing, as assessed on the same samples by  Fraimout et al. (2018). For size, we simply computed the coefficient of variation both within and among temperatures (i. e. among mean centroid sizes per temperature), for both structures. To test for differences in the coefficient of variation of size between structures we used the modified signed-likelihood ratio test, as computed in the R package cvequality  (Krishnamoorthy and Lee, 2014). Comparing the shape variability of two different objects is challenging, because they lie in different shape spaces and no direct multivariate extension of the coefficient of variation can be applied.
We used Mahalanobis distances among temperatures, computed independently for the two structures, as a measure of their relative sensitivity to temperature. Because this distance measures the difference between groups relative to the within group variation  (Klingenberg and Monteiro, 2005) , it could be comparable between structures with a note of caution. Because our hypothesis is that the ovipositor will show more robustness, it may also show lower within-group variation and that would increase distances. In this particular case, this feature makes our estimates more conservative but further applications of this method would require appropriate justification. As distance measures are affected by the data dimensionality, we estimated the Mahalanobis distances on the same number of principal components for each dataset (26 principal components: 100% of the fly shape variation and 96.
Acknowledgements We would like to thank  K. Tamura ,  M. Toda ,  P. Shearer ,  S. Fellous  and  T. Schlenke  for their help during the fly sampling. We also thank  M. Guillaume  for her help with the fly stock maintenance and  F. Peronnet  for the rearing medium we used. ESEM imaging was performed at the  Plateform MEA, University of Montpellier. We also would like to thank  Géraldine Toutirais  of the "  Plateau Technique de Microcopie Electronique du MNHN  " and  Céline Houssin  for her technical expertise in electronic microscopy. S. Gerber  helped with the interpretation of some of the methods. This article was also improved by the comments made during the  SWING  project meetings and the different people attending the seminars where it was presented, as the GDR PlasPhen 2018 in Lyon.
g. , injection drug use, sex work, incarceration, childhood and adulthood violence experiences) with the community of women living with HIV in Canada, and who are familiar with the local HIV-related health and social care priorities for women. PRAs were engaged as equal partners in all stages of the research process: from defining the research question and priorities  [33] , designing and piloting the survey questions  [38] , through to participant recruitment  [39] , data collection and analysis, and the dissemination of findings (including delivering presentations and workshops, coauthoring manuscripts, and engaging with traditional and online media). What follows is a discussion of our approach to meaningfully engaging PRAs in CHIWOS and the challenges and opportunities that emerged.
The collaborative training process generated the co-production of new knowledge and growth for PRAs and researchers alike and allowed PRAs to define what meaningful engagement meant to them. For some participants, their PRA role included participation in manuscript development and presentations as well as the administration of surveys. PRAs who had additional employment were able to complete CHIWOS surveys as they fit within their existing schedule. In addition, the development of computer skills as well as access to laptops made it possible for PRAs to stay in touch with a geographically diverse team via email, social media, and Skype. Computer literacy skills also opened up additional employment opportunities for PRAs within and outside of research. Co-production of innovative solutions to study challenges.
Following the submission of application EFSA-GMO-RX-009 under Regulation (EC) No 1829/2003 from Bayer CropScience N. V. , the Panel on Genetically Modified Organisms of the European Food Safety Authority was asked to deliver a scientific risk assessment on the data submitted in the context of the renewal of authorisation application for the herbicide-tolerant genetically modified soybean A2704-12, for food and feed uses, import and processing, excluding cultivation within the European Union. The data received in the context of this renewal application contained post-market environmental monitoring reports, a systematic search and evaluation of literature, updated bioinformatic analyses, and additional documents or studies performed by or on behalf of the applicant. In addition, the applicant provided sequence data on the soybean A2704-12 event using material from a commercial variety currently on the market and intended to be marketed in the coming years.
1. 2. Terms of Reference as provided by the requestor The GMO Panel was requested to carry out a scientific risk assessment on the data submitted in the context of the renewal of authorisation application for the placing on the market of products containing, consisting of, or produced from GM soybean A2704-12, in accordance with Articles 11 and 23 of Regulation (EC) No 1829/2003. Where applicable, any conditions or restrictions which should be imposed on the placing on the market and/or specific conditions or restrictions for use and handling, including post-market monitoring requirements based on the outcome of the risk assessment and, in the case of GMOs or food and feed containing or consisting of GMOs, conditions for the protection of particular ecosystems/environment and/or geographical areas should be indicated in accordance with Articles 6(5)(e) and 18(5)(e) of Regulation (EC) No 1829/2003.
Data The data for application EFSA-GMO-RX-009 provided by the applicant at the time of submission, or in reply to requests for additional information, are specified below. The applicant submitted sequence data on soybean A2704-12 single event 5  derived from material of an early generation (T4) of soybean A2704-12 (fourth generation after the original transformant) and from material of a commercially available soybean A2704-12 variety currently on the market and indicated that these sequences are identical. The applicant clarified that the soybean A2704-12 commercial variety has been available on the market since 2016 and is intended to be marketed in the coming years. The applicant also clarified that the A2704-12 event sequence reported in this renewal application is the sequence submitted in the original application EFSA-  GMO-NL-2005 -18 (EFSA, 2007) , corrected for eight nucleotides, two of which affect newly created open reading frames (ORFs) within the insert and spanning the junction sites (EFSA, 2018).
Systematic search and evaluation of literature 7 In addition to the eight separate literature searches provided as part of the annual PMEM reports, the applicant performed a systematic literature search for soybean A2704012 and the newly expressed phosphinothricin N-acetyltransferase (PAT) protein covering the period from 1 September 2007 till 10 January 2018, in accordance with the recommendations on literature searching outlined in EFSA  (2010, 2017a). Searches against electronic bibliographic databases and internet searches to specialist databases were performed to identify relevant publications. Altogether, 564 publications were retrieved. After applying the eligibility/inclusion criteria defined a priori by the applicant, six publications were identified as relevant for food and feed safety assessment, molecular characterisation and environmental safety assessment.
Updated bioinformatic data 8 At the time of submission of the renewal dossier, the applicant provided a complete bioinformatic dataset for the soybean A2704-12 event (using the corrected sequence) including an analysis of the insert and flanking sequences, an analysis of the potential similarity to allergens and toxins of the newly expressed protein and of all possible ORFs within the insert and spanning the junction sites, and an analysis of possible horizontal gene transfer (EFSA, 2017b). The outcome of the updated bioinformatic analyses is presented in Section 3. 3. On 8 May 2018, EFSA requested supplementary information on the partial deletion of the endogenous gene previously reported in the frame of the original application EFSA-GMO-NL-2005-18. On 19 June 2018, the applicant provided the supplementary information which included information on the function of the interrupted endogenous gene and a risk assessment of its interruption with respect to the agronomic-phenotypic characteristics and composition of soybean A2704-12.
Evaluation of the updated bioinformatic data The results of the updated bioinformatic analyses of soybean A2704-12 using the corrected event sequence (EFSA, 2018) confirm the previous conclusions on the partial deletion of an endogenous gene. Based on the information from updated databases submitted in the frame of this renewal application, this gene is identified as SEOe, a member of the sieve element occlusion (SEO) multigene family encoding for Glycine max SEO proteins. The SEOe gene is one of four genes in subgroup 5 of the SEO gene family, thereby indicating that functional redundancy for this gene in the soybean genome is likely. In addition, the original agronomic, phenotypic and compositional analyses of soybean A2704-12 (including endpoints that may be relevant to the reported biological role of SEO proteins in photoassimilate translocation via the phloem network such as plant height, yield and fiber content) did not indicate relevant differences as compared to the non-GM comparator.
3‰) were used as primary analytical standards. Sulfanilic acid (Sigma-Aldrich; δ 13 C = -25. 6 ± 0. 4‰; δ 15 N = -0. 13 ± 0. 4‰; δ 34 S = 5. 9 ± 0. 5‰; means ± SD) was used as secondary analytical standard. Standard deviations on multi-batch replicate measurements of secondary and internal lab standards (amphipod crustacean muscle) analysed interspersed with samples (one replicate of each standard every 15 analyses) were 0. 2‰ for both δ 13 C and δ 15 N and 0. 5‰ for δ 34 S. Data treatment. Unless noted otherwise, all values are presented as mean ± SD. Differences in δ 13 C, δ 15 N and δ 34 S were tested using hypothesis-based comparison procedures. D′Agostino & Pearson and Shapiro-Wilk normality tests revealed that several datasets did not follow a Gaussian distribution. Non-parametric procedures (Mann-Whitney U test when 2 groups were compared, Kruskal-Wallis one-way analysis of variance followed by Dunn's post-hoc test when 3 groups or more were compared) were therefore applied.
All statistical analyses were conducted using Prism 6. 05 (GraphPad Software, La Jolla, U. S. A. ). In the vast majority of cases, no inter-site difference in δ 13 C, δ 15 N or δ 34 S of consumers or food items was found, motivating our decision to pool all measurements made in 2014-2015 (Supplementary Information S3; Table  1 ). To quantify resource use by primary consumers and omnivores, we used the Bayesian SIAR (Stable Isotope Analysis in R) mixing model  20. Models were built only for 2014-2015 data, as replication for the 2013-2014 samples was low (Table  1 ). Four food sources were held for modelling purposes: suspended particulate organic matter, benthic biofilm, sympagic algae and Himantothallus grandifolius blades. Phyllophora antarctica blades and Pygoscelis adeliae guano were discarded because of their extreme δ 13 C and δ 15 N values, respectively (see "Results" section for details).
3 ± 1. 6‰ for N and 0. 5 ± 1. 9‰ for S (mean ± SD in each case)  58. Models were run using the SIAR 4. 2 package in R 3. 3. 2  59. Iteration numbers and burn-in size were set at 10 6 and 10 5 , respectively. Two modelling scenarios were considered: one using δ 13 C, δ 15 N and δ 34 S, and the other using only δ 13 C and δ 15 N. Model diagnostics surprisingly indicated that the scenario using all three isotopic ratios showed poorer performance. This might be caused by a combination of factors: 1) δ 34 S values of food items showed a high variability (Table  1 ); 2) δ 34 S values of sympagic algae and biofilm, as well as those of H. grandifolius blades and SPOM were statistically identical (Dunn's post-hoc test, p = 0. 2387 and p > 0. 9999, respectively), leading to poor discrimination of those sources by the model; and 3) experimental measurements of sulfur trophic fractionation in aquatic consumers are extremely scarce, which forced us to use a supposedly generally applicable TEF that might not be fully suitable.
Acknowledgements This research was funded by the  Belgian Science Policy Office (BELSPO)  through the vERSO project (http:// www. rectoversoprojects. be. be, contract nr. BR/132/A1/vERSO ). Access to Dumont-d'Urville station was granted through REVOLTA  1124 , a research program co-funded by the  French Polar Institute Paul-Emile Victor (IPEV) ,  MNHN ,  Sorbonne Université  and  CNRS. P. D. and G. L. are respectively  Belgian Fund for Scientific Research (F. R. S-FNRS ) research director and research associate. Authors warmly thank all involved  IPEV  staff for their efficient logistical support during the planning and execution of the field campaigns. They also thank  Eduardo da Forno  and  Elsa Freschet  for sample collection during the 2013-14 sampling campaign,  Svetlana Vasic  for her help during sample preparation,  Daniela Zeppilli  ( Laboratoire Environnement Profond -Ifremer ) for identifying the nematodes and  Anton P.
Data Availability All data supporting this article are openly available via the Antarctic Biodiversity Information Facility (ANT-ABIF, www. biodiversity. aq) at https://ipt. biodiversity. aq/resource?r=ddu_isotopes_verso_2013_2015. They are also registered at the Global Biodiversity Information Facility (GBIF) under UUID 90f2713a-79ac-4d96-9a66-889a5fb9abb1, and freely accessible at https://doi. org/10. 15468/wgfw0h.
Today's Arabic Handwriting recognition systems are able to recognize arbitrary words over a large but finite vocabulary. Systems operating with a fixed vocabulary are bound to encounter so-called out-of-vocabulary (OOV) words. The aim of this research is to propose a two-step approach that tackles the problem of OOV words in Arabic handwriting. In the first step, we exploit different types of sub-word units to detect the potential OOVs. In the recovery stage, a dynamic dictionary is built to extend the initial static word lexicon in order to cope with the detected OOVs. The recovery includes a selection step in which the best word candidates extracted from the external resource are kept. Experiments were conducted on the public benchmarking KHATT and AHTID/MW databases. The obtained results revealed that sub-word modeling could give cues for improving the detection and that the use of a dynamic dictionary significantly improves the recognition performance compared to one-step approaches that are based on a large static dictionary or the combination of different sub-word units.
The PAWs result from the natural segmentation of words because of the presence of letters that do not connect to their successors in the words. A morpheme can be a prefix, which is added at the beginning of the word, or a suffix, which is added at the end of the word, or a stem. The morphemes result from the morphological structure of the Arabic vocabulary  [16]  [18]  [59]. Other systems rely on a hybrid lexicon combining the different sub-word lexical units and words  [1] [2] [3]. To increase the OOV words recovery rates, several systems have used, in addition to the statistical language models, a text corpus, freely available through the web  [19] [20] [21] [22] [23] [24]. Such text corpus are used to feed the used initial word lexicons with new words and to build new statistical language models whose states, transitions and transition state probabilities are determined on the basis of the ground truth texts of the training parts of the used image databases and the freely available text corpus.
We demonstrate that sub-word modeling could give cues for improving the detection and that the best detection method is the second, which is not based on the confidence score. The second contribution is the use of a dynamic lexicon that extend the initial lexicon in order to cope with the detected OOVs. It includes a selection step in which the best word candidates from the external resource are kept. Finally, the proposed OOV detection and recovery methods are generic and independent of the recognition engine. The obtained results reveal that the proposed method achieves state of the art results on KHATT dataset and significantly improves the recognition performance over the use of reduced and large static dictionaries and the combination of different sub-word modeling approaches. In the remaining of this paper, we first described the system proposed for AHTR and especially the methods suggested for the detection and recovery of the OOV words.
This measure is evaluated without using a lexicon or a language model. The training is stopped if the CER does not improve for 20 epochs. A second recognition engine based on handcrafted features was implemented for comparison. We used the BLSTM classifier with the following learning protocol. The BLSTM learning rate was set to 10 with a momentum equal to 0. 9. The training stops if there is no enhancement of the character error rate on the validation set after 15 epochs. The choice of these parameters is justified by the fact that they provided a good accuracy for similar tasks  [35]. We used the EESEN framework of the BLSTM  [43]. In this framework, the CTC output layer was limited to the character labels of the ground truth texts of the KHATT training set. Since the Arabic script consists of 28 letters and each letter may have from one to four shapes, a set of 150 character shapes can be generated.