dataesr/scientific-paragraphs-categorization huggingface dataset:
Cattle inventory dataset description The numbers of cattle farms recorded for 2017 and 2018 are shown in Table  1. Around 70% of the farms were dedicated to mixed production of meat and milk, 17% to milk production, and 13% to meat production. In 2017, the bovine population was slightly higher than in 2018 and the proportion of animals distributed in the different categories of farms followed those of cattle farms. The location of the 63 animal markets recorded in the country is shown in Fig. 1. The cattle farm density was higher in the Sierra region, with some parishes recording up to 178 farms per km 2 (Fig. 2a ). These high densities corresponded mainly to small holdings. Cattle farm density differed per category with beef and mixed farms mainly concentrated in the Coast and Sierra regions (Fig.
Cattle trade dataset description The number of cattle movements and cattle moved were close for both years (Table  2 ). The number of cow movements and cows moved represented 46% of those for all cattle  (441,453 of 952,972 in 2017 and 441,451 of 962,890 in 2018). Seventy percent of the cattle movements originated from farms for both years (675,652 of 952,972 in 2017 and 674,668 of 962,890 in 2018), of these approximately 15% (104,622 in 2017 and 106,660 in 2018) concerned movements to farms, 53% to markets  (353,348 in 2017 and 367,955 in 2018)  and 32% to slaughterhouses  (217,682 in 2017 and 200,053 in 2018). All these proportions were similar for cow movements. The vast majority of movements were carried out between parishes either for all cattle or for cows only (77% in 2017 and 78% in 2017 in both cases).
Discussion In this study, a description of Ecuador's cattle inventory was made using the data collected during the FMD vaccination campaigns. Cattle movement records for 2017 and 2018 were processed and studied using SNA methodology and network indicators. Networks considering parishes as nodes and cattle movements as links were analyzed at the annual and monthly levels. We analyzed (i) the entire cattle movement database to document network characteristics relevant to the early detection and control of an epidemic disease such as FMD, and (ii) cow movement data, to describe network characteristics relevant to the surveillance and control of an endemic disease primarily affecting adult females, such as bovine brucellosis. Ecuadorian cattle population figures estimated in our study from FMD vaccination campaigns were close for 2017 and 2018, and did not differ from those established in the 3rd national livestock census conducted in 2002  (Haro Oñate, 2003).
Design Restraint Magnetic resonance imaging compatibility is provided with 3D printed restraint. All 3D constructions for restraint were designed using Autodesk Fusion 360 software and printed in polyethylene terephthalate glycol (PETG) material on a commercial 3D printer (Prusa I3 MK3S+; Ultimaker B. V. , Utrecht, Germany). Five restraint components are included in the setup: frontal head piece, collar head piece, MRI bed, optical imaging bed, and lid for optical imaging bed (Figure  1 ). The collar head piece and MRI bed were modified from  Han et al. (2019). The frontal head piece (Figure  1A ) provides stability of the anterior region of the head during optical imaging sessions. The frontal head piece is based on and modified from a head holder described by  Kilic et al. (2020). Two protrusions extending from the circular frontal head piece allow fixation to the imaging stage.
Habituation to restraint The protocol for sequential imaging was designed based on training protocols for optical imaging  (Desjardins et al. , 2019)  and in vivo awake MRI imaging  (Lindhardt et al. , 2022). All mice were habituated to restraint in the beds and further trained for acclimation to MRI and optical imaging environments prior to scanning sessions. MRI training occurred in a mock MRI environment, as described in  Lindhardt et al. (2022) , over 10 days, starting with 20 min of restraint and increasing restraint time by 20-min increments daily until 2 h. A mock MRI environment consisted of a 3D printed box, MRI bed compartments, and speakers for transmitting MRI sound recordings of the actual sounds produced from the MRI sequences. Sounds were transmitted via digital audio software (Audacity, Audacity Team), and mice were equipped with earplugs (Ohropax, Graested, Denmark) for training days with MRI sound.
Localizer scans (FLASH) were acquired to determine head positioning in the coronal, sagittal, and axial slice planes. A pCASL program package with parameters based on a prior protocol  (Hirschler et al. , 2018)  was applied for acquisition of echo planar images (EPI) and parameters required for calculation of CBF. Longitudinal relaxation values were mapped using data acquired with Bruker's T1_T2map_TrueFISP sequence. Scan parameters were TE/TR = 2. 2/4. 4 ms, 8 segments, TrueFISP SSFP mode, flip angle 60 • , scan repetition time 18 s. A total of 60 inversion times were used ranging from 90 ms (minimum) to 8. 4 s. An in-plane resolution of 220 µm × 220 µm was used. Total scan time was 2 min and 24 s. T1 was estimated using in-house MATLAB scripts, and the obtained T1 values were in agreement with those reported in rodent brain at our field strength (9.
LED trigger mode enables the camera to determine the switch between colors depending on the desired frame rate. The blue LED (470 nm) was turned off and the corresponding frames were discarded during the scanning sessions. For OISI, the CMOS camera was triggered using HCImage software (Hamamatsu Photonics K. K. , Hamamatsu, Japan) via an external trigger to synchronize with an accelerometer and to trigger the air puff stimulator (Powerlab, National Instruments, Austin, TX, United States). Images of 512 × 512 pixels (6. 5 µm 2 pixel size) were acquired at 30 fps with 20 ms exposure. OISI images were processed with a package to estimate oxy-(HbO) and deoxyhemoglobin (HbR)  (Sunil et al. , 2020). For illumination of the entire window for LSCI, we used a 785 nm laser diode (LPC-785-FC, Thorlabs) controlled by a power unit (LDC205C, Thorlabs).
In vivo two-photon microscopy and analysis A load of 200 µl of 5% (5 ml/ml) solution of Texas-Red dextran 70 KDa was administered via a tail catheter. TPM imaging was performed using an Ultima-IV two-photon system (Bruker Corporation, Billerica, MA, United States) and PrairieView software version 5. 5 (Bruker Corporation). For estimation of pial vessel diameter during functional activation, we used a 25× objective with N. A. 1, 4 mm working distance, and cover glass correction (XLPLN25XSVMP2, Olympus, Shinjuku, Japan). Excitation of the fluorophore was performed with 900 nm using a femtosecond laser (Chameleon Ultra, Coherent, Santa Clara, United States). Emission was detected by a Gallium-Arsenide-Phosphide photomultiplier (GaAsP-PMT, Hamamatsu, H10770PB-40) using a 660/40 nm-emission filter.
Whole-Genome Sequencing and Assembly IFM47072 and IFM59985 were previously sequenced and wholegenome Illumina data is available through the NCBI Sequence Read Archive under run accession numbers SRR11977809 and SRR11977822, respectively  (Zhao et al. , 2021). 150-bp paired-end libraries were constructed and sequenced for IP_23 and IP_24 by Novogene on an Illumina NovaSeq 6000 sequencer. Trim_Galore v0. 4. 2 was used to remove residual adaptor sequences and trim reads at low-quality sites using the parameters "-paired", "stringency 1", "-quality 30" and "-length 50"  (Martin, 2011). Read sets were then error corrected and assembled using SPAdes v3. 13. 1 with the "-careful" parameter and K-mer sizes of 55, 77, and 99  (Bankevich et al. , 2012). Genome assemblies for IP_23 and IP_24 are available through NCBI accession numbers JALLAH000000000 and JALLAI000000000, respectively.
Read Mapping, Variant Detection and Variant Annotation Quality and adapter trimmed read sets from A. fumigatus IP_23, IP_24, IFM47072 and IFM59985 were mapped against the A. fumigatus Af293 reference genome (Genbank Assembly Accession number: GCA_000002655. 1)  (Nierman et al. , 2005)  using BWA-MEM v0. 7. 15  (Li and Durbin, 2009). Joint variant calling (SNVs and indels) was conducted using freebayes v1. 3. 1 with the default settings with the exception of setting ploidy to haploid (-ploidy = 1)  (Garrison and Marth, 2012). While the vast majority of indels consisted of 1 or 2 bps (68%), indels as large as 49 bp were identified. We implemented several filtering steps to prioritize the identification of variants putatively associated with the whitespore phenotype (depicted in Figure  2 ). We identified 51,551 SNVs and 15,183 indels that differed in at least one sample relative to the Af293 reference genome.
Genome Assembly of White-Spore and Green-Spore Isolates Genome assemblies for IP_23 (386. 75), IP_24 (110. 46), IFM47072 and IFM59985 were generated with SPAdes  (Bankevich et al. , 2012). Genome size, as indicated by the cumulative length of the genome assemblies, was highly similar across the four isolates and ranged from 28. 36 Mb -28. 80 Mb (Table  S1 ). We used Augustus to predict gene models in each assembly, and similarly, found highly comparable gene numbers (8,855 -8,908) (Table  S1 ). We used BUSCO to assess genome completeness for each assembly and found that >97% of genes were completely recovered using the eurotiomycetes_odb10 dataset  (Simao et al. , 2015). These results reflect high quality genome assemblies.
These domains include two consecutive PPbinding domains (PF00550) and a thioesterase domain (PF00975) (Figure  3D ). Structural modeling of the PksP protein using AlphaFold2  (Cramer, 2021)  confirms that the truncation removes several highly structured, C-terminal motifs (Figure  4A ). The largest of the structural motifs predicted by AlphaFold2 superimposes over the crystal structure of the thioesterase domain of Aspergillus parasiticus PksA  (Korman et al. , 2010)  to sub-angstrom RMSD (RMSD=0. 987Å; Figure  4B ). The truncation also removes six residues (Lysine 1711, Isoleucine 1710, Threonine 1709, Proline 1708, Tyrosine 1691, Arginine 1690) predicted to participate in hydrogen bonding with residues within the remaining portion of the protein (Figure  4C ). Thus, the AlphaFold2 model not only corroborates the thioesterase predictions, it also suggests that the truncation may affect conformational stability within the remaining protein through the removal of hydrogen bond partners.
Microfluidic chip design The geometrical features of the chips were designed by using COMSOL MULTIPHYSICS (Comsol AB, Stockholm, Sweden) to obtain a single microfluidic chamber The fluid flow was calculated with the microfluidic module using laminar flow conditions assuming a very low Reynolds number (see supplementary Table  S3 ). The 3D FEM model is made of about 2 106 192 degrees of freedom using the predefined 'extra fine' mesh refinement. In the fluid flow model, non-slip initial condition was imposed to all surfaces corresponding to a solid/liquid interface. A fixed flow rate (between 0. 05 and 3. 4 ml. min -1 ) was used for the inlet and a fixed pressure (P = 0 Pa) for the outlet. The equations were solved in 900 s requiring 7. 5 Go using an Intel Core i7-7500U CPU cadenced at 2. 7 Ghz with 16 Go RAM configuration.
min-1. Chips were placed on a heating plate. The detachment of the worms in the microfluidic chip was video-recorded for 1 hour. Components of the microfluidic network are described in Fig. S1. Tables  Table 1:  Residence IC50 values determined in dynamic conditions. These values correspond to the concentration of PZQ or ART that induced 50% of worm detachment from the collagen coated chips after 5, 20, 30 or 50 min of treatment at a flow rate of 1 mL. min -1 in RPMI horse medium. Data are presented with their 95 % confidence intervals (CI).
Statistical Analysis SPSS software (IBM SPSS Statistics for Windows, Version 27. 0. Armonk, NY, USA: IBM Corp) was used to statistically analyze the data as follows. A comparative analysis was performed first by means of Student's t-test for independent samples to compare baseline pain values in males and females and thus to determine whether the sex variable could be eliminated from the analysis. Subsequently, a 2 × 2 analysis of variance (ANOVA) was performed with factor A being the time of assessment (a1 pre-treatment; a2 post-treatment) and factor B type of therapy (b1 RF; b2 M) to compare differences in pain. Finally, a multivariate analysis of variance (MANOVA) was performed. This analysis is used when the design includes more than one dependent variable. In this study, we evaluated the differences between the pre-treatment pain measure and the post-treatment pain measure.
Statistical Analysis SPSS software (IBM SPSS Statistics for Windows, Version 27. 0. Armonk, NY, USA: IBM Corp. ) was used to statistically analyze the data as follows. A comparative analysis was performed first by means of Student's t-test for independent samples to compare baseline pain values in males and females and thus to determine whether the sex variable could be eliminated from the analysis. Subsequently, a 2 × 2 analysis of variance (ANOVA) was performed with factor A being the time of assessment (a1 pre-treatment; a2 post-treatment) and factor B type of therapy (b1 RF; b2 M) to compare differences in pain. Finally, a multivariate analysis of variance (MANOVA) was performed. This analysis is used when the design includes more than one dependent variable. In this study, we evaluated the differences between the pre-treatment pain measure and the post-treatment pain measure.
Statistical significance: ***P < 0. 001, **P < 0. 01, *P < 0. 05, † P ≤ 0. 10. 3  Sire Family × environment effects on feeding behaviour. The effect of the interactions between sire family and environment was significant for all feeding behaviour traits (Table  1 , P < 0. 05). In a previous paper with the same dataset  16  , assessment of each SF sensitivity to HS was performed according to 5 production and thermoregulatory traits and showed that families 7, 1 and 2 were the most robust sire families, i. e. showing the less variation in the 5 traits of interest between the two climates, whereas families 6, 5 and 10 were the most sensitive. The robust and sensitive SF were grouped in robust and sensitive group, respectively, and the feeding behaviour of their progeny was compared (Table  2 ).
RFI and FCR were also positively correlated with other feeding parameters: ADFI, feeding rate, meal size and daily eating time. This is consistent with a study comparing feeding behaviour in a divergent line of pigs selected for RFI where they found that pigs from the low RFI line (which are more efficient) have less meals, lower ADFI, daily eating time and feeding rate  37. In previous studies on the same dataset, significant SFxE interactions were found for performance and thermoregulation traits  16, 29, 41. In particular, re-ranking of performance between TEMP and TROP climate was observed, demonstrating that the best sires for production traits in TEMP would not be the best ones in TROP. With climate change, it becomes crucial to understand and take into account GxE interactions in selection programs  42, 43.
Methods This study was carried out in compliance with the ARRIVE guidelines  48. All measurements and observations on animals were performed in accordance with relevant guidelines and regulations on animal experimentation and ethics (CE2012-9 from the Animal Care and Use Committee of Poitou-Charentes and 69-2012-2 from the Animal Care and Use Committee of French West Indies and Guyana) and the experimental protocol was approved by the French Ministry of Agriculture and Fisheries (authorization number: 17015 and 971-2011-03 7704, respectively) under the direction of Y. Billon (INRAE-GenESI) and J. Fleury (INRAE-PTEA). Experimental design. Data used in the present study were obtained in a backcross (BC) population (3/4   Large White (LW) and ¼ Creole (CR) breed) initially designed to examine the genetic background of heat tolerance in growing pigs.
Pigs were fed ad-libitum with a commercial feed formulated with the same nutritional characteristics in the two farms (15. 7 MJ DE/kg, 170 g CP/kg of Dry Matter). Animals had free access to water. Phenotypic recording. Room ambient temperature (T) and relative humidity (RH) were recorded during the whole duration of the test period. In TEMP conditions, these climatic parameters were obtained every 5 min in the closed experimental facilities using a stand-alone USB data logger (EL-USB-2 + ; DATAQ Instruments, Inc. , Akron, OH) located at the center of the room. In the TROP conditions, the semi-open building was equipped with a Campbell weather station (Campbell Scientific Ltd. , Shepshed, UK) continuously recording ambient T and RH (1 measurement every 30 min) in each room of the experimental farm.
, Stamford, CT) connected to a microprocessor-based handheld thermometer (model HH-21; Omega Engineering Inc. ). The RT and ST measurements were performed on unrestrained animals and with a minimum of stress during the weighing events in the morning. Due to the experimental limitations and to maximize the number of pigs with feeding measurements, during the 12 weeks of test, pigs had access to automatic feeders for three periods of two weeks, which alternated with periods of two weeks fed with conventional collective feeders. Hence, for half of the pigs (defined as period 1), feeding behaviour data was available for week 11-12, week 15-16 and week 19-20 and for the other half (defined as period 2), data was recorder for week 13-14, week 17-18 and week 21-22. During the remaining test weeks, pigs had free access to conventional collective feeders.
Calculations. A temperature-humidity index (THI) was calculated for each day based on the following formula proposed by the National Oceanic and Atmospheric Administration (NOAA 49 ; cited by Zumbach et al. 50 : THI = T -(0. 55 -0. 0055 × RH) × (T -14. 5), in which T is the average daily T (°C) and RH is the average relative humidity. ADFI was calculated from data collected by the electronic feed dispensers by averaging daily feed intake records of the 6 week available for each pig in either period 1 or period 2. We calculated FCR as ADFI divided by ADG. RFI was computed for each animal as the deviation between ADFI and ADFI predicted by a regression of ADFI on ADG between 11 and 23 weeks of age, BFT, and the average metabolic body weight during the test, as proposed by Rose et al. 16. Feeding behaviour traits were calculated from data collected by the electronic feed dispensers of the 6 weeks available for each pig in either period 1 or period 2.
Schulze et al. 51  recommended to exclude the 2 first days of recording to obtain reliable feed intake information. In a preliminary analysis, it has been shown that only the exclusion of the day when the animals switched between single and collective feeding systems is needed because readaptation to electronic feeders was not necessary. Consequently, feeding behaviour traits were estimated with exclusion of the days of switching between electronic feeders and conventional feed dispenser. Visits to the feeder where feed consumption was zero were removed from the dataset. The final dataset consisted of 1,728,688 visit records reporting animal identity, date, entering and exiting times, and feed consumption per visit, which were collected throughout the experiment from the 1,296 animals in the two farms (634 in TEMP and 662 in TROP).
Statistical analysis. As feeding behaviour data was recorded daily for individual pigs, each trait was averaged by pig and was analysed using linear models (GLM procedure; SAS version 9. 4; SAS Inst. Inc. , Cary, NC) with the fixed effects of the environment (TEMP vs. TROP), sex (female vs. castrated male), batch within environment (11 in the TEMP environment and 12 in the TROP environment), SF (10 families), recording period (2 periods) and the following interactions : SF × environment and sex × environment as main effects. Data on production traits and thermoregulatory traits was analysed following the same model  16. Least squares means of the effects were computed, and the differences between the effect levels were tested with a Tukey test. Within each environment, Pearson correlations between traits were computed from residuals of these linear models to adjust the data for the fixed effect of the models.
The G × E interactions were assessed by studying the least squares means from the previous linear models when the interaction between sire family and environment was significant (P < 0. 05). Assessment of robustness and sensitivity between the 10 sire families was performed according to Rosé et al. , (2017)  16  based on production (BW at 23 weeks, BFT at 23 weeks, ADG between 11 and 23 weeks, ADFI between 11 and 23 weeks) and thermoregulatory traits (average RT at test weeks 19, 21, and 23). Based on the 5 traits of interest  16  and consistent with results on the same dataset obtained by Dou et al. (2017)  41  , sire families 1, 2 and 7 were found to be the most robust sire families and formed the "robust group". Conversely, sire families 5, 6 and 10 were the most sensitive sire families and were included in the "sensitive group".
Feeding behaviour traits of the offspring of these six families were analysed again using linear models (GLM procedure; SAS version 9. 4; SAS Inst. Inc. , Cary, NC) with the fixed effects of the group (robust vs. sensitive), environment (TEMP vs. TROP), sex (female vs. castrated male), batch within environment (11 in the TEMP environment and 12 in the TROP environment), sire family within group (3 in each group), recording period (2 periods) and the following interactions : SF(G) × environment, sex × environment and group × environment as main effects. The circadian rhythm of the feeding behaviour data was averaged by animal and by hour and analysed through a repeated measurement analysis of variance with a compound symmetry (CS) covariance structure (Mixed procedure, SAS version 9. 4; SAS Inst.
Acknowledgements The authors would like to thank  K. Benony ,  D. Beramice ,  B. Bocage ,  M. Bructer  et  F. Silou  from the experimental unit  INRAE-PTEA ,  F. Meslier ,  J. Bailly ,  P. Epagneaud  and  C. Lebourhis  from the experimental unit  INRAE-GenESI  and  H. Lagant  for their technical assistance. The financial support of the  French National Agency of Research (ANR PigHeaT ,  ANR-12-ADAP-0015 ), the financial support of the  Department of Animal Genetics of INRAE  ( AO2012   PhenoHeaT ), the financial support of  EU-funds (FEDER, FSE, FEADER)  and the  Region Guadeloupe  (including the  AGROECODIV  project) are gratefully acknowledged.
Study sample The study was conducted from January to June 2019 in the Brittany region, which is a typical western European plain and the main milk production area in France. We selected a study population of dairy farms from a database provided by the private animal health company GDS Bretagne (France) that contains all dairy farms in Brittany (n = 9 525). Only dairy farms with at least 60 cows were selected, in order to ensure that the dairy herd was the main production and thus that farmers were followed by advisory companies and aware of common hypocalcaemia prevention strategies. Additionally, we included only dairy farms with at least 90 % Holstein cows, as Holstein is the main breed in the area and could be considered as high risk for hypocalcaemia because of its high milk yield potential  (N = 4 238).