dataesr/scientific-paragraphs-categorization huggingface dataset:
7. 1 software  [19]  using the SCWRL 4. 0 tool  [20]  for (i) simple mutant S720N, (ii) double mutants S720N and S723E, and (iii) double mutants K726S and S727I. Amino acid accessibilities were computed using the DSSP 2. 2. 1 tool  [21]  and VLDP webserver  [22]. Figure  2  shows different visualizations of the wild-type structural models and mutants, while Table  1  summarizes the change in the accessibility of the residues in this region (additional visualizations can be seen in Supplementary Figures  S1-S4 ). Table  1. Accessibility of CNF1 for positions 720 to 727 using DSSP  [21]  for the wild-type and three series of mutants. VLDP  [22]  provides equivalent results. A striking first result concerns the wild-type (i. e. , reference sequence). The addition of the translocation domain made it so that residues 720 and 721 are no longer associated with the helical structures (see Figures  2A  and S1 ).
Acknowledgments: A. G. d. B. would like to thank  Wassim El-Nemer  for bringing him this research topic and sharing it with him. This work was supported by grants from the  National Institute for Blood Transfusion (INTS, France)  and  Lab of Excellence GR-Ex , from the  Ministry of Research (France) ,  University Paris Diderot ,  Sorbonne Paris Cite  (France),  National Institute for Health and Medical Research (INSERM, France). The labex  GR-Ex , reference  ANR-11-LABX-0051 , is funded by the program " Investissements d'avenir " of the  French National Research Agency , reference  ANR-11-IDEX-0005-02. A. G. d. B. also acknowledges to  Indo-French Centre for the Promotion of Advanced Research/CEFIPRA  for collaborative grant (number  5302-2 ).
Experiment 3 In the following experiment we performed visual simulations of a child-robot interaction in a Matlab environment, where 3 colored cubes were placed randomly at 3 positions (left, center, right). The objective was for the robot to learn the "Tower of Hanoi" game and build a tower of cubes at the center position by only having a visual feedback from the child to estimate her current engagement (social reward) and a small reward every time the task was com-pleted (non-social reward). The robot's actions consisted in grasping and placing objects. It could also follow the game's rules by not placing a larger cube over a smaller one and had the ability of parameterizing the trajectories of its movements (here the only considered continuous parameter was be the speed of movement). We considered 27 states and used a one-hot representation as a feature vector.
With this simulation, we do not attempt to visualize the whole tower-building game but to show how the robot' s expressive gestures lead to more engaging interactions with human partners. In the pilot version of this joint attention experiments that we performed between a NAO and children (Section 2. 1), we studied how the robot's movements affected the child's engagement. The goal was again the pick-andplace task described above and we observed that when the robot opened and closed its grip or exchanges glances between the child and the object for a period of time while pointing at the object, it contributed to an increase of the child's engagement. Nevertheless, we have yet too little data with this pilot and simulations appear crucial to fine tune the algorithm for this scenario. Inspired by these experiments, we parameterized the simulated pointing action of the robot with low-level features describing the physical aspects of the robot's movements.
Acknowledgement: This research work has been partially supported by the  EU -funded Project  BabyRobot  ( H2020-ICT-24-2015 , grant agreement no. 687831 ), the  Agence Nationale de la Recherche  ( ANR-12-CORD-0030   Roboergosum Project  and  ANR-11-IDEX-0004-02 Sorbonne-Universités SU-15-R-PERSU-14 Robot Parallearning Project ),  Labex SMART  ( ANR-11-LABX-65   Online Budgeted Learning Project ), the  Centre National de la Recherche Scientifique (Mission pour l'Interdisciplinarité   ROBAUTISTE  Project and PICS no. 279521   SocialRobot  Project) and the  Royal Society International Exchange Scheme  (grant no. IE151293 ). and fast adaptations to the local change-points. Nevertheless, the performance is not as good as the one reached by the novel state-speci c active exploration algorithm as illustrated by Figure 5 of the main paper.
Lastly, we undertook a gene set enrichment analysis for immunological gene sets. Results: A linear trend fitted the dataset precisely showing an 8% decrease in risk of BC for each FTP, independent of stratification on other risk factors and lasting for decades after a woman's last FTP. Women with six children demonstrated 48% reduction in the incidence of BC compared to nulliparous. When we looked at gene expression, we found that 756 genes showed linear trends in cancer-free controls (false discovery rate [FDR] 5%), but this was not the case for any of the genes in BC cases. Gene set enrichment analysis of immunologic gene sets (C7 collection in Molecular Signatures Database) revealed 215 significantly enriched human gene sets (FDR 5%).
Statistical methods The first stage of the analysis was to explore the relationship between full-term pregnancies and BC in the whole NOWAC cohort. Based on person-years, the percentage change in incidence rates of BC for each additional child was calculated by using a Poisson linear regression. Each covariate was analyzed separately in a stratified analysis with test for interactions using the Wald test. A Cox proportional semiparametric hazard analysis with attained age as follow-up was used for estimating the overall effect of potential confounders. Then, gene expression profiles were analyzed for BC cases and controls using microarray technology. The dataset with 30,046 probes for each individual was preprocessed as previously described. 21 The dataset was background corrected using negative control probes, log 2 transformed using a variance stabilizing technique,  22  and quantile normalized.
Data from the two Illumina chips (HumanWG-6 v3 and HumanHT-12 v4) were combined on identical nucleotide universal identifiers. 23 We retained probes present in at least 70% of the individuals. If a gene was represented with more than one probe, the average expression level of the probes was used as the expression for the gene, resulting in a dataset with 8155 genes. The probes were translated to genes using the lumiHumanIDMapping database. 24 Finally, the differences in the log 2 gene expression for each case-control pair were computed and used in the statistical analyses. We then excluded 79 case-control pairs in which the case was diagnosed with in situ BC and seven pairs in which the controls were diagnosed with BC before the end of follow-up in 2014. The final preprocessed dataset included 460 case-control pairs.
A nested case-control design was chosen in order to reduce batch effects in the laboratory. In PCA plots, we observed no batch effects in the data that were obtained after we computed differences in log2 gene expression between cases and controls. We used the Bioconductor R-package Limma (linear models for microarrays) to identify the genes that were influenced by parity. 25 In the linear model, the responses were the differences in the log 2 gene expression for each case-control pair, while we included the parity of the control and the parity of the case as covariates. In the analyses, we merged parities 1-3 and 4-6 so that the parity data consisted of three different values: 0, 1-3, and 4-6. The merging was made in order to reduce the effect of the highest parities. The distribution of parities for cases and controls included in this study is shown in Table  S1.
Ethics approval and consent to participate The NOWAC study was approved by the Norwegian Data Inspectorate and the Regional Ethical Committee of North Norway (REK). The study was conducted in compliance with the Declaration of Helsinki, and all participants gave written informed consent. The linkages of the NOWAC database to national registries such as the Cancer Registry of Norway and registries on death and emigration were approved by the Directorate of Health. The women were informed about these linkages. Furthermore, the collection and storing of human biological material was approved by the REK in accordance with the Norwegian Biobank Act. Women were informed in the letter of introduction that the blood samples would be used for gene expression analyses.
Gene set enrichment analysis Table  3  demonstrates the results of gene set enrichment analysis. We identified 588 gene sets from the C7 collection in Molecular Signatures Database (MSigDB; http://software. broadinstitute. org/gsea/index. jsp)  27 that were significantly enriched when the parity of the controls varied (FDR 5%). Note: Numbers represent a percentage of women within the corresponding parity category. Abbreviations: BC, breast cancer; BMI, body mass index; NA, data not available. Experimentally produced gene sets were submitted to MSigDB from researchers using both in vivo and in vitro materials, as well as both human cells or tissues and animal models. Of our 588 enriched gene sets, 215 were derived from human data and 373 were derived mostly from mouse data. Detailed characterization of the top 10 gene sets from each species showed a discrepancy in the tissues analyzed: blood and cord blood in humans versus bone marrow and spleen in mice (Tables  4  and S5 ).
In our gene set enrichment analysis, we observed significant enrichment of numerous gene sets related to the immune system (C7 collection in MSigDB). It is nearly impossible to make an unambiguous conclusion from these results due to the complexity of gene sets' data and lack of essential information in gene sets' description (eg, we were unable to ascertain the gender of blood donors for the majority of human experiments even after contacting the authors of publications). Nevertheless, we observed a clear interspecific difference between components of the immune system: the gene sets were related to (in mice, most of the gene sets were of innate immunity origin, while in humans, they were of adaptive origin) and between the sources of the cells for the experiments. ] [37] [38] [39]  Pregnancy and cancer share multiple characteristics including proliferation, invasion, neoangiogenesis, and modulation of local and systemic immune response.
Acknowledgments We are thankful to and impressed by the women who donated blood to the NOWAC postgenome cohort. Bente Augdal,  Merete Albertsen , and  Knut Hansen  were responsible for all infrastructure and administrative issues. The funders had no role in the design of the study; collection, analyses, and interpretation of the data; writing of the manuscript; or decision to submit for publication. This study was supported by a grant from the  European Research Council  ( ERC-AdG 232997 TICE ). Some of the data in this article are from the  Cancer Registry of Norway. The Cancer Registry of Norway is not responsible for the analysis or interpretation of the data presented. Microarray service was provided by the  Genomics Core Facility ,  Norwegian University of Science and Technology , and  NMC  -a national technology platform supported by the functional genomics program (FUGE) of the  Research Council of Norway.
027 0. 027 Cord blood A NA CD4+ T cells NA GSE29618 -0. 029 0. 027 Blood I NA DC NA GSE17974 0. 028 0. 027 Cord blood A NA CD4+ T cells NA GSE2770 -0. 028 0. 027 Cord blood A NA CD4+ T cells NA GSE29615 0. 038 0. 027 Blood I, A NA PBMCs NA Mouse GSE17721 0. 018 0. 027 Bone marrow I NA DC F GSE14769 0. 032 0. 027 Bone marrow I NA Macrophages NA GSE3691 0. 037 0. 027 Various tissues I NA DC F GSE37301 0. 035 0. 027 Bone marrow I, A NA HSCs, CLPCs NA GSE32034 0. 028 0. 027 Various tissues I NA Monocytes M GSE17721 0. 026 0. 027 Bone marrow I NA DC F GSE21063 0. 036 0. 027 Spleen A NA B cells NA GSE11924 -0. 029 0. 027 Spleen A NA CD4+ T cells NA GSE28237 0. 035 0. 027 Spleen A NA B cells NA GSE13547 0. 034 0. 027 Spleen A NA B cells NA Note: a.
9 meV and a maximum Q of 1. 9 ÅÀ1 were accessed. IN16B was operated in three different modes. First, we examined the intensity in the elastic channel at ħu ¼ 0 (elastic xed window scan; EFWS) and the inelastic channel ħu ¼ 2 meV (inelastic xed window scan; IFWS) of all listed samples upon heating from the base temperature T z 2 K up to about 550 K. The undoped material (BZO), was as well examined in the EFWS mode as the reference sample not exhibiting relaxation processes within the studied T range. By this approach, data on the evolution of the isotropic thermal displacement parameters U iso (T), on the onset temperatures T c of diffusive dynamics and on the intensity of the associated signal in the inelastic regime were gathered. Based on this information, scans of the dynamic structure factor S(Q, ħu) were programmed within the dynamic range of AE25 meV.
Inelastic xed window scans Selected T-and Q-dependent signals registered in IFWS mode at ħu ¼ 2 meV are reported in Fig. 4. The inelastic signal is normalized to the corresponding elastic line intensity at the base temperature as I(Q, 2 meV, T)/I(Q, 0, 2 K). At T # 100 K no signal in the inelastic channel is expected, thus, an averaged background intensity was subtracted from the data sets for convenience. In accordance with the conclusions drawn from the EFWS data an onset of relaxation processes is evidenced by the uptake of the IFWS signal at elevated T. Because of the higher signal contrast in the off-elastic line channel this uptake is indicated already below 200 K, and it is visible also for 10Y:BZO and 10Sc:ZBO. Three prominent features can be seen in the IFWS data: (i) the amplitude of the inelastic signal increases with the sequence of Sc-, Y-, and In-doped compounds as well as with the increase of the nominal doping level of the In-doped series.
(iii) A less obvious feature in the response of the 10% Sc-, Y-, and In-doped materials is a dependence of the maximum on the wave vector Q. Particularly well visible in 10Sc:BZO, this maximum appears to be shied to lower T for higher Q indicating that traces of non-localized, diffusive dynamics are picked up at this early stages of proton relaxation by the highresolution experiment. For localized dynamics this maximum should appear at identical T for different Q. 12, 20, 21  From the present data, it is not readily at hand to draw this conclusion for the higher doped In-containing materials as the signal does not reach a maximum in the examined T range. A diffusive response may not be discarded for the same reason. Nonetheless, up to about 20% In doping the onset of a saturation effect can be observed for the high-Q IFWS data at high T.
However, this approach does not reproduce the prole exactly towards high temperatures captured in Fig. 4. An additional increase in intensity gives evidence of additional relaxation channels activated at elevated T. The experimental signal is not sufficiently specic to judge upon its origin, i. e. whether it is of localized or diffusive character. It is necessary to highlight here that the experimental data visualized as I(Q, 2 meV, T)/I(Q, 0, 2 K) in Fig. 4  are not corrected for the Debye-Waller factor. The moderate reduction of intensity of the maximum in the IFWS signal for higher Q towards high T is expected and should not be mistaken for a characteristic feature. This does not apply to the modeled response as shown in Fig. 5.
Acknowledgements We are grateful for nancial support from the  Swedish Research Council  (grant No. 2010-3519  and  2011-4887 ), the  Swedish Foundation for Strategic Research  (grant No. ICA10-0001 ) and the  ILL  (grant No. ILL1279. 1 ). The ILL is thanked for access to neutron beam facilities (experiment  7-03-126 ). The group of  R. Seshadri  at the  UCSB  and  S. Eriksson  at  Chalmers  are thanked for assistance in the preparation of the samples. R. Ammer  is thanked for technical assistance at the IN16B spectrometer, and for the manufacturing of the sample cells.
The out-of-eld dose in radiation therapy is a growing concern in regards to the late side-eects and 5 secondary cancer induction. In high-energy X-ray therapy, the secondary neutrons generated through pho-6 tonuclear reactions in the accelerator are part of this secondary dose. The neutron dose is currently not 7 estimated by the treatment planning system (TPS) while it appears to be preponderant for distances greater 8 than 50 cm from the isocenter. Monte Carlo (MC) simulation has become the gold standard for accurately 9 calculating the neutron dose under specic treatment conditions but the method is also known for having a 10 slow statistical convergence, which makes it dicult to be used on a clinical basis. The nTLE (neutron TLE), 11 a neutron variance reduction technique inspired by the track length estimator (TLE) method has thus been 12 developped for the rst time in the Monte Carlo code GATE to allow a fast computation of the neutron dose 13 in radiotherapy.
In such a way, we aim to 94 achieve the generation of a dosimetric database on out-of-eld dose that can be used for future epidemiological 95 studies in order to improve low dose-risk models. 96 1. 1 Method 97 1. 1. 1 TLE method in GATE for photons 98 The TLE method has been implemented in GATE for low energy X-rays  (Mittone et al. 2013 ) and prompt γ 99  (Huisman et al. 2016). It allows to calculate the particle uences, kerma and absorbed dose. 100 In charged particle equilibrium (CPE), for a monoenergetic photon beam the absorbed dose is  (Carlsson 101  A c c e p t e d M a n u s c r i p t D = φE µ en ρ (1) with φ the particle uence and µen ρ the mass energy absorption coecient.
For nitrogen and oxygen, 191 uncertainties may be even higher at some energies. 192 An important issue in relation with these neutron kermas is the treatment of neutrons below 0. 0253 eV since 193 this is the lowest reported data point. Indeed, with a neutron capture cross section inversely proportionnal 194 to the neutron kinetic energy (1/v law), the thermal neutron kerma values will increase in the same way as 195 dose  (Valentin 2003 ) that does not include the contribution by photons released in the body by neutrons has 206 been considered. 207 However, for accurate dosimetric studies, the gold standard is to be able to consider every dose component. 208 E -0. To take into account the secondary photon dose in soft tissue mainly due to the 2. 2 MeV photon from the 209 1 H(n,γ) 2 H process, photon kerma factors in our algorithm are based on mass energy absorption coecients 210 (µ en /ρ) data both from the NIST database and for the body parts for which these coecients are not recorded, 211 from the ICRU report 46, which are derived from Hubbell's elemental data  (Hubbell 1982).
and E tr in [MeV/n]. 134 Tables of F n values are found in the 46 ICRU report for energies between 0. 025 eV to 20 MeV (Caswell et al. 135 1980) for several elements, compounds, and mixtures principally calculated from the ENDF/B-IV cross section 136 library. The 63 ICRU report includes kerma coecients determined from the latest ENDF/B-VI evaluated data 137 libraries (Rose 1991) below 20 MeV and uses advanced nuclear model calculations and experimental information 138 from 20 MeV to 150 MeV (the LA150 data library (Chadwick et al. 1999)). However, this update of kerma 139 factors produced only a very small (< 2%) dierence in kerma calculations (Goorley et al. 2002) meaning that 140 nally the use of either kerma databases is suitable 141.
The genetic variability and population structure of introduced species in their native range are potentially important determinants of their invasion success, yet data on native populations are often poorly represented in relevant studies. Consequently, to determine the contribution of genetic structuring in the native range of topmouth gudgeon Pseudorasbora parva to their high invasion success in Europe, we used a dataset comprising of 19 native and 11 nonnative populations. A total of 666 samples were analysed at 9 polymorphic microsatellite loci and sequenced for 597 bp of mitochondrial DNA. The analysis revealed three distinct lineages in the native range, of which two haplogroups were prevalent in China (100%), with a general split around the Qinling Mountains. Dating of both haplogroups closely matched past geological events.
). All the sequences were submitted to Genbank: accession number KR074432 to KR074994. A phylogenetic tree was generated using MrBayes  (Ronquist et al. 2012 ) using the sequences generated in the present study as well as from  Simon et al. (2011)  and  Liu et al. (2010). Gnathopogon elongatus (AB218687) and Gobiocypris rarus (AF309083) were used as outgroups. Substitution model HKY ? I ? G was chosen using jModeltest  (Darriba et al. 2012). The generation number was set at 1000,000 with 250,000 of burnin. The tree was visualized using Figtree v1. 4 (http://tree. bio. ed. ac. uk/software/figtree/). The numbers of haplotypes and haplotype diversity were calculated using DNAsp  (Librado and Rozas 2009). Fst, Tajima's as well as Fu's Fs were calculated using Arlequin ver. 3. 5. 2. 2  (Excoffier and Lischer 2010).
Haplogroup dating Sequences representing two other Pseudorasbora species and other Gobioninae lineages were retrieved from Genbank, as well as genera of Xenocyprinae, Tincinae and Leuscininae used as outgroups. The non Pseudorasbora genera were sampled to represent Gobioninae lineages and to provide calibration intervals (see below). The final alignment comprised of 18 sequences and 597 positions. Accession numbers of Divergence dates were estimated using the relaxed molecular clock approach implemented in BEAST v2. 4. 3  (Bouckaert et al. 2014). MCMC analyses were run for 20 million generations with tree sampled every 1000 generations with the model selected by jModeltest (TN ? I ? G). Convergence was checked and burn-in was estimated with Tracer v1. 6  (Rambaut et al. 2014 ). The trees were combined into a maximum clade credibility tree using TreeAnnotator using a burn-in of 10%, with the estimation of the mean node height and highest posterior density intervals fixed at 95%.
Firstly, discriminant analysis of principal components (DAPC)  (Jombart et al. 2010) , was used to assess the population structure using the complete dataset (i. e. native and invasive populations were combined). This was performed in R using the ADEGENET package  (Jombart 2008). This multivariate analysis derived the probability of individual membership in each different group. The program covered a range of possible clusters from 1 to 31, 31 representing the total number of populations in the dataset. The interaction number used was 1000,000,000. 50 principal components were retained as predictors for discriminant analysis in the 666 individuals studied. In addition, we performed a structure analysis on the dataset. This analysis was performed separately for the Asian and European P. parva populations using STRUCTURE software  (Pritchard et al.
Mitochondrial DNA A total of 874 analysed sequences (597-bp) of the Cytochrome B gene revealed four distinct lineages and 102 haplotypes across the samples (Figure  2 -Supplementary material 1). As expected more synonymous mutations (91) than non-synonymous mutations (22) were found in our dataset. In its native range of China and Japan, P. parva displayed three distinct lineages: (Lineage 1, 2 and 4; Figs. 1, 2 ). Lineage 1 and 2 were found across China, with a north-south distribution in relation to the Yangtze River (Fig. 1 ). Lineage 1 was present in relatively high frequency in the North (93% Lineage 1, 7% Lineage 2), whereas lineage 2 was most prevalent in the South (4% Lineage 1, 96% Lineage 2). Average haplotype diversity was higher in the northern China (i. e. north of the Yangtze River S1, S2, S3, S10, S11, S13, S14, S15, S16 and S17-0.