dataesr/scientific-paragraphs-categorization huggingface dataset:
The optimal number of migration edges was inferred employing the linear method implemented in the optM package (v. 0. 1. 3; Fitak 2021). Bootstrap support for splitting and migration events was inferred from 100 bootstrap replicates. Replicate trees were summarised using SumTrees of the DendroPy package (v. 4. 5. 1; Sukumaran and Holder 2010) and plotted in  FigTree (v. 1. 4. 4. ; Rambaut 2018). The principal components-based algorithm implemented in PCADMIX (v. 1. 0;  Brisbin et al. 2012 ) was used to infer local genomic ancestry in Nustrale pigs, Corsican wild boars, and Sardinian wild boars. The method assigns the most likely ancestry proportion along each chromosomal haplotype in admixed individuals in relation to non-admixed reference populations. Local ancestry inferences therefore rely strongly on the chosen reference populations, theoretically representative of the ancestral populations that contributed to the current genomic composition in the admixed individuals.
We chose 25 samples from continental wild boar (Italy, N = 15; Luxembourg N = 10) and 25 samples from domestic pig breeds 'Large-White', 'Duroc', and Sardinian domestic pigs as putative ancestral reference populations given the putative origin of the insular wild boar populations and documented cross-breeding in the Nustrale breed  (Albarella et al. 2007; Lambert-Derkimba et al. 2011). Chromosomal haplotypes were phased in  FASTPHASE (v. 1. 4. 8; Scheet and Stephens 2006)  using the 50K SNP panel set with default parameters, except for the incorporation of subpopulation labels. Phased haplotypes were pruned for MAF (<0. 01) and LD (r 2 > 0. 8) in PCADMIX. The window size was set to 20 SNPs. Results were plotted in R using a custom script by  Barbato et al. (2017) , retaining ancestry designations above a 90% confidence threshold.
The two-layer hidden Markov model implemented in  ELAI (v. 1. 01; Guan 2014 ) was employed as an additional approach to infer local ancestry and the structure of haplotypes of Corsican wild boars using the 50K SNP panel set. Unlike PCADMIX, ELAI has the advantage that it works directly with diploid data and, therefore, does not require phased haplotypes. We used the same putative ancestral wild boar and domestic pig reference samples as for the PCADMIX analysis. The two-way admixture estimation was based on five independent expectation maximisation (EM) runs each employing 30 steps (-s 30), two upper-layer clusters (-C 2), and 10 lower-layer clusters (-c10). Mixing was assumed to have occurred over 100 and 1000 generations. Chromosomal admixture proportions were averaged over the five independent EM runs.
Individual genome-wide admixture proportions were estimated as weighted averages (weighted by the number of SNPs per chromosome). Individual genome-wide admixture levels in Corsican wild boars, as estimated in STRUCTURE, PCADMIX, and ELAI, were compared between the proposed "pure" and "hybrid" morphological phenotypes using nonparametric Wilcoxon tests. SNP data from Corsican wild boars and domestic pigs were screened for potential selection using the PCA-based method implemented in  PCAdapt (v. 4. 3. 3; Luu et al. 2017). PCAdapt identifies outlier loci that are excessively related to population structure, making them candidate loci for selection. The method does not require a priori definition of parental source populations and accounts for hierarchical population structuring among samples  (Luu et al.
2017). The default method using Mahalanobis distance with K = 1 was employed. We focussed on the first principal component as it reflected the divergence among domestic pig and wild boar samples. Outlier SNPs were identified by transforming P values into q values with a cutoff value of 0. 001, ensuring a false discovery rate lower than 0. 1% using the R package qvalue (v. 2. 18;  Storey et al. 2019).
3  Clustering solutions inferred in STRUCTURE from the 30K SNP panel set at K = 2 and K = 14 for six regional wild boars (WB) populations and six domestic pig (DP) breeds. NU Nustrale, SA Sardinian feral pig, LW Large White, NS Nera Siciliana, MR Mora Romagnola. Fig. 4  Graphical representation of PCADMIX results for Corsican and Sardinian wild boars (WB) and the domestic pig breed Nustrale for chromosomes 1-18 (horizontal bands). Each line within a chromosomal band represents a haploid individual. The horizontal axis represents chromosome size in base pairs. Genomic regions are coloured according to the most likely ancestry assigned by PCADMIX (i. e. , WB in red or DP in yellow). Regions with a posterior probability below 0. 9 are shown in grey. Plots generated with R code provided by  Barbato et al.
ACKNOWLEDGEMENTS The authors are thankful for the support of the  Collectivité de Corse  for collecting samples used in the present study. We also thank the farmers and hunters in Corsica for their participation and  Dr Sandra Cellina  for the collection of Luxembourgish wild boar samples. AS thanks the  Centre for Information Technology of the University of Groningen  for providing access to the Peregrine high-performance computing cluster. We also thank  Dr Laura Iacolina  for answering our questions on her published dataset and  Dr Mario Barbato  for providing advice and R code for Fig. 4. This research was funded by an internal grant from the  Musée National d'Histoire Naturelle, Luxembourg. MM would like to thank the  Luxembourg National Research Fund (FNR)  for the support ( FNR PEARL P16/ BM/11192868  grant).
DATA AVAILABILITY The 48,222 autosomal SNP genotypes for 85 wild boars and 46 domestic pigs (PLINK and TREEMIX file formats) are available from the Dryad Digital Repository https://doi. org/10. 5061/dryad. jq2bvq8bb. Mitochondrial haplotypes are available on Genbank (accession numbers MH746786-MH746796).
black allele of Asian origin (0201/ED1) in one hybrid boar and European alleles for black spotting and recessive red in the domestic pigs (Table2). 148),compared to domestic pig samples (MAF = 0. 191). An exception to this trend was the Mora Romagnola breed, with the lowest levels of heterozygosity and MAF of all samples. SNP summary statistics After merging data libraries and filtering for missing data, genotypes from 131 unrelated individuals genotyped at 48 222 autosomal SNPs (50K SNP panel set) were retained. The data set (Ursing and Arnason, 1998)s putative 'hybrids' based on phenotypic traits in Supplementary Table1. aNucleotidepositions are initially numbered according to the complete pig mtDNA reference sequence(Ursing and Arnason, 1998), but change later due to insertions/deletions; b Genbank accession numbers MH746786-MH746796; c Sequence without complete match on Genbank; d Sequence without complete match on Genbank, but matched a shorter sequence (query cover 83%) from a native Italian pig breed (e.
g. EU362554); e Observed previously in wild boars (e. g. Genbank accession number AY884672) and domestic pig breeds (e. g. AY884778); f Observed previously in wild boars (e. g. KC771440) and domestic pig breeds (e. g. JQ273478); g Observed previously in wild boars (e. g. JQ273229) and domestic pig breeds (e. g. JQ273265); h Observed previously in Corsican wild boars (e. g. AY884681) and domestic pig breeds (e. g. JQ273480); i Sequence of Asian origin; j Observed previously only in domestic pig breeds (e. g. JQ273465, JQ27348). kObservedpreviouslyonly in a Croatian wild boar (MF196767). lPutativehybridboarbased on phenotypic traits outlined in Supplementary Table1. dominantconsisted of 85 wild boars (Fig. 1) and 46 domestic pigs (Table3), with a high genotyping rate of 99. 5%. The LD-and MAF-pruned data set was reduced to a SNP panel set of 28 089 SNPs (30K SNP panel set).
The isolation challenge was video recorded using a camera from the ceiling (CCD colour camera, 480 lines, 1 lux/f2. 0 320 kpix, 200 mA, Velleman, Belgium). A total of five saliva samples were collected to follow the response and recovery of salivary cortisol of the animals: 15 min before the isolation challenge (baseline), and 1, 3, 5, and 21 h after the beginning of the isolation. Pigs were allowed to chew for 1-2 min on the swabs which were held by clamp forceps. Pigs were habituated to the procedure previously. The pigs were equipped with an accelerometer on the left rear leg (Pendant G Acceleration Data Logger, Onset Computer Corporation, Pocasset, MA, USA) to determine their postures; and with a heart rate belt (Zephyr BioHarness 3 TM ). The equipment stayed on the pigs for 5 h after the entrance to isolation.
The accelerometer on the leg was put on the outside of the leg such that the x-axis was parallel to the leg of the pig and pointing down. The tri-axial accelerometers were programmed to log at 1-s intervals on 3 axes. They had a measurement range of ±3 g, an accuracy of ±0. 105 g, and a memory of 21. 8 kB for combined x-, y-, and z-axis readings. For programming and reading out the accelerometers, a coupler, an optical base station with a USB interface, and the HOBOware Pro computer program (Onset Computer Corporation, Pocasset, MA, USA) were used. The data were transformed from g to postures with Microsoft Excel (Microsoft Corporation, Redmond, WA, USA). Postures were determined according to Ringgenberg et al. (41). The following algorithm was used to automatically compute the posture of the pigs: IF (X ≥ 130 • ) THEN posture = standing ELSE posture = lying.
Postures maintained for <20 s were considered as artefact and corrected by the behaviour done by the pig just before. The percentage of time spent in each posture was determined over 15-min intervals. Regarding the heart rate measurement, five sections of 10 min, one per hour, were extracted from the dataset from each pig for time and frequency domain analysis, together with non-linear (including geometric) analysis. The 10 min sections were selected within the first 20 min of each hour paying attention to the quality of the data. The Kubios artefact correction philtre (threshold: very strong) was used and only sections with <25% artefacts corrections were analysed. The Kubios HRV Standard 3. 3. 1. software (Kubios Oy, University of Eastern Finland, Finland)  (42)  was used to obtain the heart rate variability (HRV) variables.
The following three time-domain variables were examined: (1) interbeat interval (IBI) mean (or risk ratio (RR) mean; RR is the interval between successive R peaks of the QRS complex of the Electrocardiogram wave). The RR mean provides information on the heart rate (43); (2) root mean square of successive RR differences (RMSSD), which reflects the integrity of vagus nervemediated autonomic control of the heart; and (3) the SD of all RR intervals of the dataset (SDNN), which is a good predictor of overall variability present at the time of recording. Frequency domain analysis was done using a Fast Fourier Transformation (FFT) obtaining high (HF), and low frequency (LF) bands, expressed in normalised units (n. u. ). Frequency bands widths (LF: 0. 01-0. 09 Hz; HF: 0. 09-2. 0 Hz) were assigned according to pig recommended ranges  (44).
The following two frequency domain variables were examined: (1) LF:HF ratio, also referred to as the Sympathetic Nervous System indicator (SNSI), which reflects sympathetic activity, and (2) HF/total power and pNN50, the Parasympathetic Nervous System indicator (PNSI), used to enumerate vagal activity  (43). For geometric analysis, a Poincaré plot was plotted in Kubios and SD1 (short-term variability) and SD2 (long-term variability) was calculated. The following geometric variable was examined: (1) SD1:SD2 ratio, which is an indicator of sympathetic tone. The software Kubios also estimated Baevsky's stress index, which is a geometric measure of heart rate variability indicative of both sympathetic activity and central regulation [see  Sahoo et al. (45)  for more details about the calculation].
Indicators Measured During the Challenges The pigs were weighed 24 h before and 24 h after the challenge. Relative weight gain was estimated as follows: (Final weight -Initial weight) Initial weight. The feed intake over the 21 h-period was also measured. Photographs of the left eye of each focal pig were taken right before and 24 h after isolation. Measurements of tear staining were made on photographs by a single experienced person, blind to treatment, using the ImageJ software (National Institute of Health, Bethesda, USA)  (46)  to delimit the tear perimeter. The length of the iris was used as a scale to standardise the measurements. All the brownish areas on the direct periphery of the eye (bottom of the upper eyelid, top of the lower eyelid, internal and external corners) were recorded  (33).
Statistical Analyses Statistical analyses were performed with the software R 4. 0. 3. (R Foundation for Statistical Computing, Austria)  (47). The variables' latencies to cross the holes in the maze, tear staining, and saliva cortisol concentration were normalised by logarithmic transformation. Residuals of other variables were normal without transformation. Areas under the recovery curves were approximated from repeated measurements using the trapezoidal rule N k=0 ( f (xk-1)+f (x k ) 2 ) × xk, where f(x) is a function and x k is the length of the k-th subinterval. On focal pigs only, linear mixed models with the function lmer from the R package "lme4, " were used for all variables measured once. In these models, housing and sex (boar vs. gilt) were fixed effects, and batch and pen were random effects.
ACKNOWLEDGMENTS The authors would like to thank the swine farm staff at the  Swine Innovation Centre (Sterksel, The Netherlands ) and at  Carus Research Facilities (Wageningen, the Netherlands ) for daily animal care and the help in the data collection. They would also like to address a special thanks to the technicians and laboratory persons from the  Adaptation Physiology group :  Rudie Koopmanschap ,  Bjorge Laurenssen ,  Manon van Marwijk , and  Monique Ooms. They are also grateful for the invaluable help of the students involved in the project:  Marith Booijen ,  Tao Cui ,  Jori Noordenbos ,  Marloes van Beurden ,  Sandra van Iwaarden , and  Shiv Vasa.
11 C-Flumazenil Positron Emission Tomography (PET) Imaging PET imaging acquisition was performed using an Inveon ® microPET-CT scanner (Siemens, Berlin, Germany)  [66]. Rat anesthesia was induced and thereafter maintained using 3 and 1. 5-2. 5% isoflurane in O 2 , respectively, to insert a catheter in the caudal vein for 11 C-flumazenil injection. Anesthetized rats were placed into the micro-PET-CT and a brain CT-scan was first performed. After CT completion, 90-or 60-min dynamic acquisitions were performed starting at the time of 11 C-flumazenil intravenous (i. v. ) injection, to study (i)the impact of tramadol on the brain binding of 11 C-flumazenil and (ii)-the mechanisms involved in tramadol-induced changes in 11 C-flumazenil brain binding, respectively. PET data were reconstructed using the FORE + OSEM2D algorithm, including normalization, attenuation, scatter and random corrections.
PET images were co-registered using Pmod software (version 3. 6, Zürich, Switzerland) to a brain magnetic resonance imaging (MRI) template published by Schiffer et al. [67]  (normalization of PET-CT on MRI and application of the transformation to the PET images). This template incorporates adult male Sprague-Dawley rats (250-300 g) and implements the Paxinos coordinates. Time activity curves (TACs) were generated in different brain regions predefined in the Schiffer's template. Radioactivity concentration was expressed as the percentage of the injected dose (%ID. mL -  ) versus time (min). The binding potential (BP ND ) of C-flumazenil in selected brain regions (BP ND = B max /K D , where B max represents the total density of receptors in the tissue and K D , the radioligand equilibrium dissociation constant) was estimated using the simplified reference tissue model (SRTM) and the pons as the reference region  [68].
Contributions: N. T. and B. M. designed the study. C. L. , L. C. , H. L. and P. R. performed the study 1. D. V. and G. P. performed the study 2. J. C. measured monoamines in brain. F. C. synthesized 11 C-flumazenil. C. L. and D. V. performed the statistical analysis. C. L. , D. V. , N. T. and B. M. wrote the manuscript. All authors have read and agreed to the published version of the manuscript. Funding: Joined grant from AP-HP and CEA and funding from the French National Research Agency (ANR-16-CE17-0011-001) to D. V. Institutional Review Board Statement: Our experimental protocols were carried out within the ethical guidelines established by the National Institutes of Health and approved by Paris-Descartes University ethics committee for animal experimentation and by the French Ministry of Higher Education and Research (N • -APAFlS#5285-2017031714499381v2 and N • -APAFlS#7466-2016110417049220v2).
Acknowledgments: The authors would like to thank the Animal Platform, CRP2-UMS 3612 CNRS-US25 Inserm-IRD-Faculté de Pharmacie de Paris, Université Paris-Descartes, Paris, France for their technical assistance. They would like also to thank Emilie Jaumain (CEA-SHFJ, Orsay, France) for technical assistance and Alison Good (Scotland, UK) for her helpful review of the manuscript.
Author Contributions: N. T. and B. M. designed the study. C. L. , L. C. , H. L. and P. R. performed the study 1. D. V. and G. P. performed the study 2. J. C. measured monoamines in brain. F. C. synthesized 11 C-flumazenil. C. L. and D. V. performed the statistical analysis. C. L. , D. V. , N. T. and B. M. wrote the manuscript. All authors have read and agreed to the published version of the manuscript. Funding: Joined grant from AP-HP and CEA and funding from the French National Research Agency (ANR-16-CE17-0011-001) to D. V. Institutional Review Board Statement: Our experimental protocols were carried out within the ethical guidelines established by the National Institutes of Health and approved by Paris-Descartes University ethics committee for animal experimentation and by the French Ministry of Higher Education and Research (N • -APAFlS#5285-2017031714499381v2 and N • -APAFlS#7466-2016110417049220v2).
The present study constitutes a review of the scientific articles about animal welfare in terrestrial farmed animals, published in countries of Latin America. The main objectives were to quantify and characterize articles produced between and in farm animals' welfare using "Web of Science [v. ]" and "CAB Abstracts" databases. A total of articles were found for the period analyzed, which were mainly in English ( %). The countries with the most publications were Brazil ( %), México ( %), Chile ( %), Uruguay ( %), Colombia ( %) and Argentina ( %). Cattle was the farm species most considered in the publications ( %), and the studies addressed mostly the on-farm production stage ( %). There was a rapid increase in the number of articles published in the last years, accounting for % of the publications.
Materials and methods The methodology used in this study considered the following steps: behavior" in the area of "terrestrial production animals" corresponding to "Latin America" were selected. The search covered the years 1992 to 2021 in the CAB Abstracts (CAB) and Web of Science Core Collection (WoS) databases of the virtual library system of the Universidad Austral de Chile accessed via the FortClient programme. These databases were chosen because WoS had been used before in similar reviews on animal welfare publications  (13, 14)  and is considered worldwide an important database for scientific articles; CAB database was included because it has more journals indexed that accept articles in Spanish or Portuguese. The search and selected keywords were written according to the following strategy using Boolean search terms (AND, OR, * , ", $):  • CAB Abstract (animal.
Article inclusion/exclusion criteria All types of scientific articles (original articles, short communications and bibliographic reviews) published from 1992 to 2021 were included in the search (done in June 2022), with no language filter, considering journals in the areas of veterinary sciences, animal science, environmental sciences and food science in both databases. From the list of 31 countries that appear as members of the WOAH in the Region of Americas, the name of each of the 19 countries in which Spanish or Portuguese is the main language (Latin American) was selected and included as a filter: Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Dominican Republic, Uruguay, and Venezuela.
Once this was done for both databases, the first raw result was obtained and the references of these 846 articles were saved in a folder on the desktop, using the option to extract in RIS format file offered by CAB and WoS. The Mendeley Desktop program was then used to open the RIS format files and a matrix table with all the information was built using the Microsoft Excel Office Version 2021 program. Based on this selection, 143 publications were manually eliminated, because abstract revealed that the study did not actually correspond to the animal welfare or animal behavior areas (i. e. , were only on productive traits), still referred to non-production animals (companion, sports, laboratory or zoo animals) or non-terrestrial species (fish and other aquatic species). Of the remaining 703 articles, most (n = 507) were found through WoS, and less through CAB (n = 196).
Results A total of 663 published articles on farmed animals' welfare (FAW) were found for the 19 countries of Latin America between 1992 and 2021, considering the search through both databases. Regarding the distribution of the publications during the period analyzed, the earliest publication found was from 1995 by Caballero et al. in CAB (  19 ) and there was an increase during time until 2020. A rapid increase in the total number of articles can be observed between years 2017 and 2020, where a peak of 151 articles was reached, whereas a decrease was observed in 2021 (Figure  1 ). Comparing the first 15-year period analyzed (1992-2006) and the last 15 years (2007-2021), 95% of all the publications was found in the latter period. Considering the total of articles found (663), the countries with most publications on FAW during the period analyzed were Brazil (43%), México (25%), Chile (12%), Uruguay (10%), Colombia (4%), and Argentina (2%) (Figure  2 ).
), or requiring an additional stifle joint procedure (patellar stabilization. ) were excluded. Additional procedures due to complications (septic arthritis, implant explantation, late meniscal tear. ) were not cause for exclusion. Data obtained from the medical records included signalment (breed, age, gender, weight), preoperative radiographs, side of the lesion, type of cruciate ligaments lesions, and type of implant used. For the BioMedtrix™ group, data obtained also included postoperative radiographs, recheck radiographs, and complications. For the control group, additional data only consisted of the occurrence of a SSI and potentially associated implant explantation.
Data analysis Data were analyzed using a statistical software (R 4. 0. 2, The R Foundation for Statistical Computing, Vienna, Austria). Statistical analysis for categorical data used either Chi-squared (breeds) or Fisher's exact (sex, CrCL side, type of CrCL lesion, SSI, implant explantations) tests. For continuous data, after normality evaluation using Shapiro-Wilk test, analysis used either Student's t (age, weight, PreTPA) or Mann-Whitney-Wilcoxon (ModTPA, bone healing) tests. Interobserver variability was estimated by the standard deviation of the observer's mean measurements of TPA per dog. Post hoc power analysis was performed to evaluate potential differences between groups for SSI and implant explantation rates, using α = 0. 05. Statistical significance was set at p < 0. 05.