dataesr/scientific-paragraphs-categorization huggingface dataset:
The description of the signal is taken from simulation while that of the background is taken from the D 0 -mass sidebands in data. The two datasets are split into two independent subsamples for the training and the testing of the classifier. Many kinematic and isolation variables are tested, the set of variables being gradually reduced until the performance of the BDT starts to decrease significantly. The final set of variables used in this analysis contains the mass of the b hadron corrected for the missing particles  [27] , the flight distance of the D 0 candidate, the vertex-fit χ 2 of the decay vertex of the D 0 candidate, particle identification information of the four daughters of the D 0 candidate, the probability of the tracks being reconstructed from random hits  [17] , and isolation variables based on the underlying event.
The first uncertainty is statistical and the second is systematic. Amplitude |c k | arg(c k ) [rad] Fit fraction [%] D 0 → [φ(1020)(ρ -ω) 0 ] L=0 1 D 0 → [K -π + ] L=0 [K + π -] L=0 0. 282 ± 0. 004 ± 0. 008 -0. 60 ± 0. 02 ± 0. 10 18. 46 ± 0. 35 ± 0. 94 D 0 → K 1 (1270) + K - 0. 452 ± 0. 011 ± 0. 017 2. 02 ± 0. 03 ± 0. 05 18. 05 ± 0. 52 ± 0. 98 D 0 → [K * (892) 0 K * (892) 0 ] L=0 0. 259 ± 0. 004 ± 0. 018 -0. 27 ± 0. 02 ± 0. 03 9. 18 ± 0. 21 ± 0. 28 D 0 → K * (1680) 0 [K -π + ] L=0 2 D 0 → [K + K -] L=0 [π + π -] L=0 0. 120 ± 0. 003 ± 0. 018 -2. 49 ± 0. 03 ± 0. 16 3. 14 ± 0. 17 ± 0. 72 amplitudes. Instead, other amplitudes with small fit fractions are uncovered in this analysis, as a consequence of the more than 50 times larger dataset. D 0 → K 1 (1400) -K + 0.
CP -violation results For the CP -violation fit, the dataset is split into two subsets according to the charge of the muon to separate the D 0 and CP -transformed D 0 decays. The CP -violation fit described in Sec. 4. 5 is applied to these two samples. Table  5  shows the resulting CP -violation parameters. The average moduli and phases are not shown in the table as they are identical to the moduli and phases from the CP -averaged fit in Table  2. All the asymmetry parameters are compatible with zero. The most significant deviation, observed for the phase difference for the D 0 → [φ(1020)ρ(1450) 0 ] L=1 component, corresponds to a 2. 8σ statistical fluctuation. To check how likely such a deviation would be in absence of CP violation, the fit is repeated many times, where the data is randomly K 1 (1400) + → [K * (892) 0 π + ] L=0 1 (fixed) 0 (fixed) 100 Table  4 : Parameters of the ρ -ω interference for all relevant amplitudes.
Acknowledgements We express our gratitude to our colleagues in the CERN accelerator departments for the excellent performance of the LHC. We thank the technical and administrative staff at the LHCb institutes. We acknowledge support from  CERN  and from the national agencies:  CAPES ,  CNPq ,  FAPERJ  and  FINEP (Brazil) ;  MOST  and  NSFC (China) ;  CNRS/IN2P3  (France);  BMBF ,  DFG  and  MPG (Germany) ;  INFN (Italy) ;  NWO (Netherlands) ;  MNiSW  and  NCN (Poland) ;  MEN/IFA (Romania) ;  MSHE (Russia) ;  MinECo (Spain) ;  SNSF  and  SER (Switzerland) ;  NASU (Ukraine) ;  STFC  ( United Kingdom );  NSF (USA). We acknowledge the computing resources that are provided by  CERN ,  IN2P3 (France) ,  KIT  and  DESY (Germany) ,  INFN (Italy) ,  SURF (Netherlands) ,  PIC (Spain) ,  GridPP  ( United Kingdom ),  RRCKI and Yandex LLC (Russia) ,  CSCS (Switzerland) ,  IFIN-HH (Romania) ,  CBPF (Brazil) ,  PL-GRID (Poland)  and  OSC (USA).
This was obtained using a customized entrance slit of 5 µm in width and 100 µm in height, and a standard aperture slit of 150 × 150 µm 2. The HMR protocol is detailed in  Slodzian et al. (2014 Slodzian et al. ( , 2017)). Multi-stack scanning images were acquired over a field of view ranging from 25 × 25 µm 2 to 60 × 60 µm 2 area, with a definition of 256 × 256 pixels. The probe dwell time was 0. 5 ms per pixel per stack. We recorded 200-600 stacks for each analysis area. The typical counting rate on the samples was 50 000 c s -1 for CH -. The image processing was performed using the ImageJ software  (Schneider et al. 2012). Usual corrections for both dead time (44 ns) and quasi-simultaneous arrivals (QSA-effect;  Slodzian et al. 2017)  were performed for major isotope species CH -, C - 2 , and CN -, stack by stack, even though their amplitude are well below the variations reported in this work.
On the labelled residue, we defined the bulk ROI as a square centred in the middle of the sample with a total area of 52 900 pixels by avoiding the edges of the image. As the probe eroded the sample, we obtained isotopic data at increasing depth, allowing us to quantify the D/H ratios for the D-rich zones buried inside the sample. The results presented were obtained by selecting a range of stacks between 210 and 330 over which the average D/H ratio of the image was almost constant while the D-rich zones were clearly visible. As for the unlabelled data, we summed 10 consecutive stacks resulting in a set of 12 stacks with an average number of counts per stack in the ROI ranging from about 10 5 of counts in CD -and 10 6 counts in CH -.
Acknowledgements. This work was supported by project grants  ANR IGLIAS  ( ANR-13-BS05-0004 ) and  COMETOR  ( ANR-18-CE31-0011-01 ) of the  French Agence Nationale de la Recherche  and funding from  DIM-ACAV ,  IN 2 P 3  ,  LABEX P2IO ,  Univ. Paris Saclay , and  CNES. E. D. acknowledges financial support by the  French IN 2 P 3 -INSU-CNRS programme "Physique et Chimie du Milieu Interstellaire " (PCMI). We thank  T. Been ,  C. Grygiel ,  T. Madi ,  I. Monnet ,  F. Ropars , and  J. M. Ramillion  for their invaluable support. The authors acknowledge the entire staff of the  GANIL facility  for providing the ion beams essential for these experiments.
Background: Ankylosing spondylitis is a subtype of inflammatory rheumatic disease, affecting predominantly the axial skeleton and sacroiliac joints. The main clinical manifestations are spinal stiffness and inflammatory back pain, which can potentially affect gait ability of patients with ankylosing spondylitis. However, published studies show discrepancies regarding gait characteristics in ankylosing spondylitis and heterogeneity in terms of task requirement, types of equipment, data collection, and analysis techniques used to assess gait ability of patients with ankylosing spondylitis. Objective: This review aimed to determine (1) the consequences of ankylosing spondylitis on gait and (2) how gait is assessed in patients with ankylosing spondylitis. Methods: Three electronic databases-PubMed, Physiotherapy Evidence Database (PEDro), and Cochrane-were searched systematically with no limit on the publication date in order to identify studies satisfying the search criteria.
Data Sources and Search Strategy A computer-aided literature search was conducted in the following electronic databases on June 5, 2018, with no date restrictions: PubMed, Physiotherapy Evidence Database (PEDro), Cochrane library. Consistent with a similar review, search terms included those related to population, ankylosing spondylitis  [16] , and the outcome-gait  [17]. The search strategy included a combination of the following keywords and Medical Subject Headings terms found in the abstract or title: ("gait" OR "walk" OR "walking" OR "locomotor" OR "locomotion") AND ("ankylosing spondylitis" OR "spondyloarthritis").
Data Extraction Following the PRISMA guidelines  [15] , a flow chart of the selection process was created, with the number of citations reviewed at each stage of the review (Figure  1 ). Additionally, the following four sets of data will be extracted from the retrieved articles  [18] : Means and SDs or medians associated with interquartile range or the first and third quartiles will be extracted. Two reviewers will independently extract these data from each enrolled study and compare the data for consistency. Any discrepancies between the two reviewers will be resolved at a consensus meeting. If disagreement persists, a third reviewer will be consulted to achieve a final judgment.
if they reported spatiotemporal, kinematic, kinetic, peak plantar pressure or muscle activity data during gait"  [7] ). Thus, an update of the published literature is needed. A strength of this review protocol is that it includes both clinical and laboratory measurements of gait studies on patients with ankylosing spondylitis, reporting precisely the methodology used in each selected study, as recommended by the PRISMA statement (e. g. "how the data was collected and analysed"  [15] ). Indeed, early identification of gait deficits in patients with ankylosing spondylitis could help us better understand, follow, and predict disease evolution and allow for timely implementation of targeted interventions or treatment to improve gait. Keywords have been chosen based on latest reviews on ankylosing spondylitis  [16]  and gait  [17]  separately and were searched in principal databases, assuring the conduct of a systematic review.
Acknowledgments This study is part of the PhD thesis of the first author JS (AGEIS,  Université Grenoble Alpes, Grenoble, France, and Grenoble Alpes University Hospital, Grenoble, France ). This work is supported by the  French Ministry of Health and Solidarity  with the "Nursing and  Paramedical Hospital Research Program " year 2016 ( PHRIP-16-0528 ) and by the  French National Research Agency  in the framework of the " Investissements d'avenir" program  ( ANR-10-AIRT-05  and  ANR-15-IDEX-02 ). The sponsors had no involvement in the review and approval of the manuscript for publication. This work further forms part of a broader translational and interdisciplinary research program, GaitAlps.
Acknowledgements This work has been conducted in the framework of  Erasmus Mundus Joint Doctorate Project-Sustainable Management and Design for Textiles (SMDTex) , which is financed by the  European Commission  (Grant No. 532704-EM-5-2017-1-FR-ERA ). The authors would like to thank  Christian Catel  from  GEMTex Lab at ENSAIT(France) ,  Anders Persson  from  department of Textile Technology at the University of Borås, Sweden  for their support. Open access funding provided by  University of Boras.
Although the molecular mechanisms underlying these various functions remain largely unknown, numerous genes have been associated to them in the literature and/or using publicly available gene expression databases (i. e. , Allen brain atlas)  (4, 5, 20, 23, 24, 33). Therefore, β tanycytes in direct contact with fenestrated capillaries are the only subtype to express tight junction protein Claudin1 (Cldn1)  (8) (9) (10) , necessary to ensure a tight blood-CSF barrier, and the vascular endothelial growth factor (Vegf )  (10) , necessary to ensure the permeability of ME vessels. In another hand, they specifically express N-Cadherin (Cdh2) and Caveolin-1 (Cav1)  (34) , which are implicated in endocytosis/transcytosis, and/or recycling of cell surface receptors for the regulation of cell signaling.
Supplementary file 1 provides the details of the analytical derivations, the code producing the figures and the simulation code as a Mathematica©. cdf file  (MATHEMATICA v. 11. 3 Wolfram Research 2018)  which can be open using the free "CDF player" available on the Wolfram website. Supplementary file 2 provides the Matlab© (MATLAB 2015a, The MathWorks, Natick, 2015) source code for the curve fitting procedure used for Eq. [8].
Given that first names can have a lifelong impact on the bearer, parents should choose a name based on the impressions they want their offspring to evoke in other people. This name-to-mentalimage association can be mediated through sound symbolism: a natural link between the sounds and meaning of a word. From an evolutionary perspective, parents should pick names which sounds convey traits advantageous in human sexual selection: largeness and masculinity for males through lower-frequency sounds as opposed to smallness and femininity for females through higherfrequency sounds. Using a database of French first names from 1900 to 2009, we observed a sexbiased sound symbolism pattern in the last syllable, which is the perceptually prominent one in French. Male names were more likely to include lower-frequency vowels (e.
Furthermore, to our knowledge, no societies (industrialized or not) currently use, or have been using, the same set of names for males and females. Lastly, it is worth noting that even though cultural evolution drives popularity and the emergence of novel names (e. g. Berger et al. , 2012) , it merely explains why individuals primarily perceive them as either male or female. Sound symbolism has already been observed in the phonetic composition of English first names  (Sidhu and Pexman, 2015; Pitcher et al. , 2013; Cassidy et al. , 1999; Cutler et al. , 1990). So far, only one study has formally tested these evolutionary hypotheses through the lens of sexual selection using a database of the thousand most popular English, American and Australian first names between 2001 and 2010  (Pitcher et al.
Acknowledgments We would like to thank the  Institut National de la Statistique et des Études Économiques  for providing the data on French first names ('Fichier des prénoms' -Edition 2011 [electronic data], INSEE [producer],  Centre Maurice Halbwachs (CMH)  [distributor]). This is a contribution of the  Institut des Sciences de l'Évolution   2019-101. ArXiv: 1208. 0576 ,  7. Zwebner ,  Y. , Sellier , A. -L. , Rosenfeld, N. , Goldenberg,  J. ,  & Mayo , R. (2017). We look like our names: The manifestation of name stereotypes in facial appearance. Journal of Personality and Social Psychology, 112(4),  527-554. https://doi. org/10. 1037/pspa0000076.
Third, the ITS databases are either curated but not exhaustive (such as UNITE) or present a lot of redundancy (such as NCBI). Among plant-fermented food, bread is of importance both from a cultural and a nutritive point of view. Leavened bread can be made using either yeast starter or using sourdough. Three types of sourdoughs are defined. Type I sourdough is a mixture of flour, water, bacteria and yeasts. It is a naturally fermented sourdough and is the traditional sourdough. Type II and type III sourdoughs are industrial types of sourdough. Usually, type I sourdough contains one dominant LAB species and one dominant yeast species, as well as a few other minor microbial species  (Lhomme et al. , 2015a (Lhomme et al. , , 2016;; Minervini et al. , 2015; Zhang et al. , 2011 Zhang et al. , , 2015;; Dertli et al.
Field Survey and Sourdough Collection A total of 14 bakers located in different French regions participated to this study. The study was carried out jointly by two French researcher teams. One worked on bacterial species, the other one on yeasts. The data on bacterial species diversity and biochemical properties of sourdoughs and breads have been previously published  (Lhomme et al. , 2015b). We analyzed the yeast species diversity as well as the bread-making practices. All bakers produce bread in a low-input agro-food ecosystem. They explained their bread-making practices during diverse interviews. The output of these interviews is presented in the results section and provides details on the specific practices of the bakers we studied. Broadly, each bread making process starts from the chief sourdough, which comes either from a piece of dough or a piece of final sourdough from the previous bread-making process.
Choice of primer pairs Pyrosequencing was carried out on the ITS1 rDNA region. Among 29 ITS1 primers published in the literature (Supplementary Table  S3 ), we selected the ITS primers that could specifically amplify fungal DNA but not plant DNA. To do so, we first built an ITS sequences database by blasting  The bakers were either farmer-baker (FB) or baker (B). They all use wheat from low-input farming for making their sourdough. A total of 13 characteristics during the process are documented. Ancient (Anc. ) or modern (Mod. ) wheat varieties were milled with either millstones (Stone) or cylinder (Cylind) mills. The flour was made by the baker (own) or by another miller (miller). The water was either coming from tap or was filtered. The sourdough age in year since the first mix of water and flour was also reported.
The chief sourdough came either from the final sourdough (SD) or from the dough (D) of the last bread making process and was stored at ambient (AT) or cold temperature (Cold). The kneading was either mechanical (mech. ) or manual. The percent of final sourdough was measured as the proportion of sourdough relative to the mass of dough. The number of bread-making process (BM) per week was reported, as well as the number of feeding between bread-making process and per week. In four cases (yes), commercial baker yeast was used regularly for making other bakery's products and in one case it was also added to make bread (Baker 5). the S288C Saccharomyces cerevisiae ITS1-5. 8S-ITS2 sequence against the NCBI non-redundant nucleotide database, including any sequences with both an e-value < 10 -4 and a > 80% identity.
We also added Poaceae ITS sequences. Overall, there were 1995 sequences in this database. Second, we blasted 29 primers from the literature (Supplementary Table  S3 ) on this database (parameters: e-value < 10 - 2  ; > 80% identity). From this analysis, six primers theoretically allowed amplification of fungal but not Poaceae ITS regions: forward primers NSI1  (Gardes and Bruns, 1993)  and NSA3  (Martin and Rygiewicz, 2005) , and reverse primers ITS4 and NLB4  (Gardes and Bruns, 1993) , 58A2R and NLC2  (Martin and Rygiewicz, 2005). Two of these hypothetical fungal-specific primer pairs (NSA3-NLC2 and NSA3-58A2R) were tested on DNA extracted from 17 natural sourdough yeast strains representing the ten species previously identified in natural French organic sourdoughs  (Jacques et al. , 2016; Lhomme et al.
Database UNITE fungal ITS database version 7 (17,421 sequences; downloaded at http://unite. ut. eerelease_01. 08. 2015, Kõljalg et al. , 2013)  was completed with 13 ITS1 Sanger sequences obtained from five natural sourdough strains and eight type strain sequences (Supplementary Table  S5 ) corresponding to 11 previously described bread sourdough species. The additional sequences were non-redundant with the downloaded UNITE database sequences. The UNITE database completed with the sourdough strains contains 432 Saccharomycetes reference sequences. Hereafter in this article, we term the downloaded UNITE database "UNITE only" and the UNITE database completed with the sourdough strain sequences "UNITE completed. ".
Filtering, quality trimming and clustering into OTU To conserve high quality sequences only, we trimmed and filtered the reads. For filtering, raw pyrosequencing fna and quality files were transformed to fastq files. Reads were truncated with the PRINSEQ tool at the 3 position at the quality threshold of 34, and any read <127 bp was discarded. The following steps were performed using QIIME: chimera detection using usearch61 against the uchime_reference dataset 3  ; operational taxonomic unit (OTU) selection using uclust  (Edgar, 2010)  with the open reference OTU-picking workflow and a threshold of 99% pairwise identity; and taxonomy assignment using the RDP Classifier 2. 2  (Wang et al. , 2007)  and using the RDP Classifier 2. 2  (Wang et al. , 2007)  and BLAST against the "UNITE completed" database.
Natural Sourdoughs A total of 689 OTUs corresponding to 202,225 reads were selected for analysis because they were represented by more than five reads after chimera detection. Each sourdough sample contained between 104 (Sourdough 10) and 351 (Sourdough 7) OTUs (Supplementary Table  S6 ). The assignment was done using either RDP or BLAST after completing the UNITE database with ITS sequences obtained from sourdough strains (Table  3 ). Database completion improved the rate of OTU assignment at the species level (data not shown). Most reads were assigned to Ascomycota (99. 0% with RDP, 94. 2% with BLAST) while Basidiomycota (0. 2% with RDP, 1% with BLAST) and Anthophyta (0. 1% with RDP, none with BLAST) were much less represented. A total of 4. 7% (with BLAST) and 0. 7% (with RDP) of the reads remained unidentified at the phylum level.
DISCUSSION In this work, we analyzed the yeast diversity in a collection of 14 sourdoughs collected from bakers with different bread-making practices. We developed a metabarcoding method for analyzing fungal communities in bread sourdough. From our knowledge only two studies have used so far metabarcoding to characterize fungi in sourdoughs made of cereals  (Minervini et al. , 2015; Raimondi et al. , 2017 , see review in Weckx et al. , 2018). They used regions of the LSU rDNA as barcode. We used ITS1 that has been shown to better discriminate closely-related yeast species  (Vu et al. , 2016). We tested our method on a synthetic sourdough composed of flour and known sourdough yeast species in equal proportion. After data analysis of this synthetic sourdough, all the added yeast species were recovered showing that ITS1 barcode allows the discrimination of these yeast species.
By adding sourdough strain sequences to the public database, we improved the rate of OTU assignment at the species level. However, the "UNITE completed" database was not sufficient to assign all OTU reads at the species level. A total of 79. 6% of the total number of reads were assigned to 60 species. The other reads were not assigned at species level. This might be related to a lack of power of ITS1 to discriminate species. It might also be related to a lack of reference sequences in databases. Different databases exist to assign fungal rDNA regions: INSD (international nucleotide sequence database), GenBank  (Benson et al. , 2006) , ENA, DDBJ  (Nakamura et al. , 2013) , SILVA  (Pruesse et al. , 2007) , Ribosomal Database Project II  (Cole et al. , 2014) , FUSARIUM-ID  (Geiser et al. , 2004) , YEASTIP  (Weiss et al.
, 2013)  and UNITE databases. We chose the UNITE database because it is a commonly used and curated database for fungal barcoding. In addition, it contained non-translated parts of the rDNA region (ITS1 -5. 8S-ITS2,  Kõljalg et al. , 2013). The presence of SSU parts in the reference database may alter assignments in favor of sequences containing SSU parts. However, the UNITE database still needs to be improved. For instance, taxonomical definitions need to be modified for "Candida" or "Incertae sedis". More ITS1 sequences still need to be completed to contain sequences corresponding to all of the 100,000 described fungal species  (Ainsworth, 2008). It would be particularly easy to include the 1100 known species of Saccharomycetales (432 in our completed version). Culture-based and non-culture-based approaches gave similar results for the dominant species except for one species, the not-yet described Kazachstania species also discovered in boza from Bulgaria  (Gouliamova et al.
, unpublished) , and identified as K. exigua by the metabarcoding method. We did not add its ITS1 sequence to complete the UNITE database since the species was not described yet. The ITS1 sequence of this species and K. exigua are close, explaining the assignment to K. exigua. Strains of this species were previously identified as K. exigua by a previous publication that used a region of the LSU as barcode  (Gouliamova et al. , 2012). The K. exigua species has been described in many different sourdoughs  (De Vuyst et al. , 2016; Carbonetto et al. , 2018). Based on the partial sequence of the large rDNA subunit (D1D2) and based on the ITS1 sequence, it clustered with this new species, as well as with the recently described species K. saulgeensis  (Jacques et al. , 2016; Carbonetto et al. , 2018).
ACKNOWLEDGMENTS We acknowledge financial support from  ANR   Bakery-13-ALID-0005  ( French National Research Agency) ,  région Ile de France (DIM ASTREA). This work is part of the Ph. D. thesis of  CU  (Urien, 2015). We thank the 14 bakers for their collaboration on the project and for sharing their bread-making knowledge and pleasure in good bread with us. Thanks are also addressed to  Aurélie Bourgais ,  Candice Aulard  and  Stéphane Guezenec  for their technical assistance and to  Laurence Bérard  and  Mathieu Thomas  for their help to study baker's practices.