dataesr/scientific-paragraphs-categorization huggingface dataset:
Probability of Purchasing an Infected Animal In the analysis, using the cattle movement database, the origins of cattle purchased from other farms included France, the Netherlands, Catalonia, Galicia, and the rest of Spain. Accordingly, cattle movements were classified into 1 of these 5 origins. We assumed that the number of cattle purchased in each batch throughout the year had the same number of animals. Therefore, the number of animals purchased each time (i. e. , the size of the batch) from each country/area, group age and farm (data obtained from the biosecurity questionnaires) was calculated using equation [1] (Appendix Table  A2 ). The probability that at least one animal from a batch coming from a single farm of a certain country/ area was already infected with BVDV or BoHV-1 was estimated using equation [2] (Appendix Table  A2 ).
Probability of Infection During Transport from an Infected Animal Uninfected cattle could be infected during transport by sharing the transport vehicle either with a PI (for BVDV) or AcI (for BoHV-1) animal or by being transported in a contaminated vehicle. We excluded TI animals because the probability of transmission from a TI is very low (Table  1 ). The likelihood of contact with other cattle during the transport was obtained from the biosecurity questionnaires. Unfortunately, data on the number of farms attended by the same vehicle per day in the country/area of origin and the average number of animals transported in each movement were not available. Thus, based on group discussion with attending veterinarians, the maximum capacity of the vehicle was 36 animals, and several farms visited in each country/ area of origin ranging between 2 and 4 was considered.
Movements to Cattle Competitions Some study farms moved cattle to national or regional competitions. To participate in these competitions, animals must be certified as having tested negative for BoHV-1 antibodies and BVDV antigen. Therefore, for BVDV, the probability that false-negative PI or TI animals could attend a competition would be negligible (as the sensitivity of antigen detection test is close to 100%). Thus, we decided to only include this scenario in the pathway for BoHV-1. From the movement database, we extracted the number of movements to cattle competitions and the age of moved animals. Herd prevalence was assumed to be that of the region where the study farm was located (i. e. , Galicia or Catalonia). Movement to competitions was assumed to be carried out using external vehicles (from a company) based on discussion with field veterinarians.
For BVDV and BoHV-1, a similar approach to equation [8] (Appendix Table  A2 ) was used to calculate the probability that animals transported to a competition were infected in a contaminated transport vehicle. In this case, animals in a transport vehicle could have 1 or 2 origins, and the maximum number of individuals loaded per farm was considered to be 4. For BoHV-1, the probability that the animals shared the same vehicle with false-negative AcI animals or had direct or indirect contact with false-negative AcI ani-mals at competition was calculated using a similar approach to equation [7] (Appendix Table  A2 ). Animals returning from the competition could enter directly into the farm or be quarantined. These data were obtained from the biosecurity questionnaires to calculate the probability of BVDV and BoHV-1 infection after implementation of biosecurity measures as previously described.
Reared Replacement Heifers Offsite Some study farms bred their own replacements offsite from the milking or lactating cattle farm. The number of these movements and age of moved animals were obtained from the movements database; calculations were performed using a similar approach to equation [8] (Appendix Table  A2 ). When the movement was carried out using the farm's own vehicle, transport was considered to be shared with only one other farm, loading a maximum of 4 heifers. Risk mitigation derived from the quarantine was calculated as previously described. If heifers were reared in a multi-origin farm, these movements were considered as if they were from a different origin. Therefore, calculations described in the pathway for the introduction of reared replacement heifers' offsite were performed using similar approach to equation [9] (Appendix Table  A2 ).
The use of quantitative risk assessment models can be useful to promote the improvement of biosecurity in dairy cattle farms and support disease control programs. However, complexity and lack of understanding of the logic behind development of quantitative risk analysis models by end-users (e. g. , field veterinarians) hampers use of these models in practice, and therefore limits their effects in improving biosecurity or supporting disease control programs. We tried to overcome this issue by using a participative approach with the objective of developing a risk assessment tool that could be adapted to end-user needs. To that end, we invited field veterinarians to identify input parameters of the model, obtain some data (e. g. , that related to animal transport practices), and evaluate the reliability of the obtained results.
, 2009). However, since September 2019, a volun- In relation to cattle transport, we had information only on moved animals but no specific information about routines of the cattle transport vehicle (e. g. , number of farms visited per day, number of animals by transport vehicle). Lack of availability of this data is common in other countries in Europe, as reported previously in other studies  (Bronsvoort et al. , 2008; Santman-Berends et al. , 2018). Consequently, in this study, the information was obtained through discussions held with attending veterinarians. The sensitivity analysis demonstrated that variation in these parameters influenced the model results. Therefore, incorporation of data from animal transport companies in the risk assessment model would increase the accuracy of the estimations.
ACKNOWLEDGMENTS This work was supported by a Grant from the  Ministerio de Ciencia e Innovación of Spain  ( AGL2016-77269-C2-1-R  and  AGL2016-77269-C2-2-R ). The  Universidad de Nariño (Pasto, Colombia)  provided funding to the first author (BBB). The authors extend special thanks to the veterinarians who collaborated in this project. The authors have not stated any conflicts of interest.
g. Oleson et al. , 2013; Lawrence et al. , 2018) , as displayed in observations (e. g. Caldararu et al. , 2012; Zeng et al. , 2013; Tang and Dubayah, 2017). In this framework, the European CRESCENDO project (https://www. crescendoproject. eu/) fostered the development of a new generation of LSMs to be used as the land component of the Earth System Models (e. g. Smith et al. , 2014; Olin et al. , 2015; Cherchi et al. , 2019; Mauritsen et al. , 2019; Sellar et al. , 2020; Seland et al. , 2020; Yool et al. , 2020; Boucher et al. , 2020)  employed in the Coupled Model Intercomparison Project Phase 6 (CMIP6,  Eyring et al. , 2016). In particular, seven novel and a 500 m spatial resolution. SENTINEL LAI dataset is obtained through a neural network applied on top-of-atmosphere input reflectances in red and near-infrared bands derived from PROBA-V.
The instantaneous LAI estimates obtained in this way go through a temporal smoothing and small gap filling, which discriminate between evergreen broadleaf forest and noevergreen broadleaf forest pixels (see  Verger et al. , 2019). It covers the 1999-2019 period with a 10-day temporal frequency and a 1km spatial resolution. Note that SENTINEL has a reduced latitudinal cover compared to MODIS and LAI3g since it covers up to 75 • N versus the 90 • N of the other two products. The 2000-2011 period is common to the three satellite datasets and it is used in the present analysis. The satellite observations are aggregated into monthly values and regridded, by means of a first order conservative remapping scheme  (Jones, 1999) , to a regular 0. 5 • x 0. 5 • grid for consistency with the LSMs' output.
ORCHIDEE The ORCHIDEE model used for the CRESCENDO simulations is the land component of the IPSL (Institut Pierre Simon Laplace) ESM and the version corresponds to the one used for the CMIP6 simulations  (Boucher et al. , 2020). The model https://doi. org/10. 5194/bg-2020-319 Preprint. Discussion started: 4 September 2020 c Author(s) 2020. CC BY 4. 0 License. calculates primarily the fluxes (and stocks) of water, energy, and carbon between the different soil and plant reservoirs and the fluxes with the atmosphere. Since its first description in  Krinner et al. (2005) , the model has substantially evolved; we describe below only the main features relevant for this study. The surface heterogeneity is described with 15 different PFTs that can be mixed in each grid cell. The annual evolution of the PFT distribution is derived from the LUH2 database as described in more details in  Lurton et al.
Growing season analysis The times of start and end of growing season (GSS and GSE, respectively) are evaluated using the Four Growing Season Types when two growing seasons at least three-month-long are detected. Further details can be found in  Peano et al. (2019). Note that in this analysis, the timings of the TGS GSS correspond to the GSS timings of the first growing season cycle, while the GSE are the second GSE timings, as described in  Peano et al. (2019). The 4GST method is applied on monthly LAI data in this work, instead of 15-day time-scale used in  Peano et al. (2019). Given the monthly time window used in this analysis, difference up to one month can descend from the monthly time-frequency, which limits a more detailed bias assessment between LSMs and observations.
Satellite data Satellite-based LAI datasets have been used in this work as a benchmark for the evaluation of the LSMs' phenology performance globally. However, satellite observations present some caveats and uncertainties (e. g. Myneni et al. , 2002; Fang et al. ,  https://doi. org/10. 5194/bg-2020-319 Preprint. Discussion started: 4 September 2020 c Author(s) 2020. CC BY 4. 0 License. 2013;  Jiang et al. , 2017). For this reason, three separate satellite LAI products obtained from different acquisition sensors (namely AVHRR for LAI3g, MODIS for MODIS LAI, and SPOT/PROBA VEGETATION for SENTINEL) have been used in this study. The comparison between these datasets shows major issues associated with LAI products derived from satellite reflectance observations. For example, large differences between LAI3g, MODIS, and SENTINEL occur at high latitudes and in tropical regions (Figure  5 ), where thick clouds and snow cover can affect the data reconstruction (e.
This method improves the multi growing season identification, especially for the crops identified by a strong phenology cycle but may exclude crop characterized by a weak phenological https://doi. org/10. 5194/bg-2020-319 Preprint. Discussion started: 4 September 2020 c Author(s) 2020. CC BY 4. 0 License. cycle. For these reasons, more specific analyses of semi-arid and crop regions based on higher spatial and temporal data are needed and will be the focus of a future study. Besides, LSMs' crop phenology parameterizations require further development to improve the description of each specific crop. LSMs evaluate phenology at PFT level, but the final LAI values are returned at the grid-cell level. For this reason, a more detailed evaluation of the parameterization would require using PFT-level values.
Acknowledgements. This work has received funding from the  European Union 's  Horizon 2020 research and innovation program  under Grant Agreement 641816 (CRESCENDO). DH also received support from the  Met Office Hadley Centre Climate Programme (HCCP)  funded by  BEIS and Defra. DW  acknowledges financial support from the  Strategic Research Area MERGE  (Modeling the Regional and Global Earth System -www. merge. lu. se), and from the  Swedish national strategic e-science research program  eSSENCE (http://essenceofescience. se/) LPJ-GUESS simulations were performed on the Tetralith supercomputer of the  Swedish National Infrastructure for Computing (SNIC) at Linköping University , under project no. SNIC 2018/2-11  (S-CMIP). TP acknowledges support from  NASA 's  Carbon Monitoring System program  ( 80NSSC18K0173-CMS ).
Code and data availability. The LAI3g satellite observation data are available from R. Myneni (http://sites. bu. edu/ cliveg/datacodes/); the MODIS satellite observation data are available from T. Park; the SENTINEL satellite observation data are available from COPERNICUS (https://land. copernicus. eu/global/products/lai); the atmospheric forcing, CRUNCEP v7, are available from N. Viovy (https://rda. ucar. edu/ datasets/ds314. 3/); the land surface models simulations are part of CRESCENDO project and they are stored at the CEDA JASMIN service (http://www. ceda. ac. uk/); the 4GST python script is available online (https://github. com/ CMCC-Foundation/4GST. git).
Discussion Given the global awareness of biodiversity loss with climate changes and anthropogenic pressures, it is not surprising that SDMs have been increasingly used in recent years. It is therefore of great concern how reliable the models are in their utility of predicting species distribution  [47] [48] [49]. Here in this study, we examined the performances of a representative selection of modelling methods for rare species using a typical dataset available in marine fisheries surveys. Our results were generally mixed, that is, most species could be appropriately predicted in terms of occurrence, whereas non-zero abundance tended to be underestimated. Nevertheless, given the rather limited occurrence (mostly less than 10%), such performances were acceptable for rare species in a context of biological conservation.
Methods Study area and data. A marine fisheries survey was conducted in the north Yellow Sea, China to collect data. A modified systematic survey design was implemented with a total of 118 sampling stations in 2017 (Supporting information, Supplementary Fig. S1 ). In each station, an otter trawl which has the net width of 15 m and cod-end mesh size of 20 mm was towed for around 1 h at a speed of nearly 3 knots. Catch data were standardized to the same sampling efforts (trawling speed *time) for modelling. The survey and analysis methods were carried out in accordance with the ethics and guideline of the China law and the experimental protocol is approved by Ethical committee of Ocean University of China. A total of 145 fish, shrimp and cephalopod species, in addition to benthos, were identified in the survey.
The ancillary species were considered in two scenarios, one that ancillary species were observed in all sampling sites, and the other that they were predicted from JSDMs. Obtained from either way, the information of ancillary species were used in SSDMs as predictive variables. To suppress noise and reduce the number of predictive variables, principal component analyses (PCA) were conducted on ancillary species data prior to model fitting, and only PCs with eigenvalues above one were included in the conditional models  70. evaluation procedures. A four-fold cross validation procedure was used to evaluate models' predictive performances. The total data were split into four equal sized subsamples, in which 75% were used for model training and the remaining 25% for testing, iteratively. To avoid potential failures with all-zero training/testing dataset, the nonzero data of rare species were randomly assigned to the four subsamples to ensure that each had equal number of occurrence of target species.
Performances on predicting species occurrence were measured by the area under curve (AUC) of receiver operating characteristic and Cohen's κ coefficient  17. The former has been commonly used for model evaluation of presence-absence, and the latter is used to indicate the chance-corrected agreement between predictions and observations  71. A random guess of occurrence leads to 0. 5 and zero in AUC and Cohen's κ, respectively. Additionally, True Skill Statistics  72  were calculated and shown in the Supporting Information. Given that low detectability of rare species might lead to zero observations, a species-specific threshold, mean abundance in the whole area, was used to determine species occurrence from predicted abundance. Data splitting, model fitting, prediction, and evaluation were conducted for each of the target species, and the processes of cross-validation were repeated 500 times.
Acknowledgements We thank the reviewer for the valuable comments. This work has been partially supported by the  National Key R&D Program of China  under grant No. 2017YFB0203000 , the  National Natural Science Foundation of China  under grant No. 61802187  and  61872223 , the  Natural Science Foundation of Jiangsu  under grant No. BK20170857 , the fundamental research funds for the central universities No. 30918011320  and  ANR  project  ANR-15-CE38-0005  " Materials ".
Methods The data were derived from the study titled ''Health care in households'' carried out by GUS (Statistics Poland). It covered a representative sample of 4658 households of 13,376 members in total in 2010 and 4584 households of 12,532 members in total in 2013. It was conducted by means of a face-to-face survey as part of ''Household budget survey''. The research tool comprised two questionnaires: a common one for a household and an individual one for its respective members. The survey was carried out with a representative method, which enables generalisation, characterised by a certain precision, of the findings with respect to all households in Poland. The scheme applied was stratified two-stage sampling with various probabilities of selection at stage 1. Stage 1 sampling units were area survey points and stage 2 sampling units were dwellings.
Data Collection and Data Variables The sources of data were the individual patient records and the index testing register. Data were collected into a structured questionnaire. Before starting the study, the data collection tool was pretested for 1 day at 1 health facility (National Institute of Public Health, INSP) in Abidjan. Data collectors participated in a 1-day training on data collection procedures. The following variables were collected: For the index case: age at admission (by the time when the patient arrived at the facility), gender, nationality, religion, employment status, level of education, and marital status. For the contact: age, gender, type of contact (conjoint/ spouse, other sexual partner, biological children), HIV status at admission (HIV positive, HIV negative, unknown), HIV partner notification approaches (client referral, contract referral, provider referral, dual referral), HIV results (positive, negative), HIV testing code, linkage to ART, and ART identification code.
Data Analysis and Statistics Data were entered from paper-based registers (index testing register and individual client record) kept at the health centers, in Census and Survey Processing System version 7. Data cleaning was performed to remove inconsistencies, and the database was analyzed using STATA version 14 (Stata Corporation, College Station, TX). Descriptive univariate and bivariate analyses were performed for the index cases and their contacts, stratified by HIV partner notification approach. We calculated the number of persons having been referred, tested, testing positive, linked to care, and initiated on ART, by type of partner notification approaches and by relationship to the index case. All people tested HIV positive are eligible to start ART immediately, according to the "HIV treat all" approach.
Coupled-Channels calculations The experimental data of the two fusion reactions have been compared to the theoretical calculations based on the coupled-channels model. For both systems the CC calculations were performed by means of the CCFULL code  [14]. The ion-ion potential was of Woods-Saxon shape for both systems (V 0 = 85. 3 MeV, r 0 = 1. 16 fm and a = 0. 66 fm for 36 S + 50 Ti, and V 0 = 85. 3 MeV, r 0 = 1. 17 fm and a = 0. 66 fm for 36 S + 51 V). For the 36 S+ 50 Ti, the CC calculations included the collective vibrational excitations of both the target and the projectile nuclei. In particular, the one-phonon excitation of both the lowest quadrupole vibrational state 2 + at 1. 554 MeV of 50 Ti and the first 2 + state at 3. 29 MeV in 36 S, were considered. In the case of the 36 S+ 51 V, the four magnetic substates m = 1/2, 3/2, 5/2 and 7/2 of the 7/2 - ground state of 51 V produce different Coulomb barriers that have to be treated individually in the CC calculations.
Summary The fusion cross sections of the two systems 36 S+ 50 Ti, 51 V have been measured from above the barrier down to 20 -30 µb. The comparison of the two excitation functions and barrier distributions showed a very similar behaviour. A CC analysis was performed in order to highlight differences between the two systems attributable to the non-zero spin ground state of 51 V. The calculations included the low energy excitations of the 36 S beam and of the 50 Ti, 51 V targets. In particular, the CCFULL code has been modified so to enable the treatment of the odd spin states. The theoretical predictions are in very good agreement with the experimental excitation functions of both systems at energies above and below the Coulomb barrier. This may be explained in the weak-coupling scheme where the relatively stiff 50 Ti (close to the double magic 48 Ca) is not significantly influenced by the additional proton to form 51 V.
Firstly, isoenzyme data underlying the current taxonomy (i. e. GOT) were freshly evaluated by MLEE and systematic sequencing of the gene to check for post-translational modifications. Secondly, a global genetic analysis was performed to evaluate the structure of the complex and allele distribution associating the data from the got gene with the previous genetic analysis performed by El  Baidouri et al. (2013) , where no structure was observed for the L. donovani complex using multilocus sequence analysis (MLSA), and the hsp70 gene, the most widely validated species typing marker. Finally, the cultured strains were submitted to mass spectrometry (MALDI-TOF) analysis as an additional approach to achieve a broader perspective on the complex.
6. 3 (Applied Maths, Belgium) and are available in GenBank under the accession numbers MN728685 -MN728796. In addition, for the 56 strains under study, 392 sequences corresponding to seven MLSA loci previously analysed by El  Baidouri et al. (2013)  were extracted from the Gen-Bank database (see Supplementary Table  S2 ). For the clustering analysis, all nucleotides were duplicated to avoid information loss from ambiguous states (e. g. , A to AA or Y to CT). NJ trees were constructed with MEGA-X software using the p-distance method and a bootstrap of 1000 replicates, got and hsp70 genes, the MLSA scheme and got allele 823. In parallel, neighbour-nets (NN) were constructed using Splitstree version 4. 14. 8 software  (Huson and Bryant, 2006)  from MLSA, hsp70 and got datasets using the uncorrected p method and an equal angles representation.
For these analyses, additional sequences from the L. tropica complex (L. tropica and Leishmania aethiopica) and Leishmania major complex (L. major, Leishmania turanica, Leishmania arabica and Leishmania gerbilli) were downloaded from GenBank (see Supplementary Table  S3 ). MLSA, hsp70 and got NN were then built on a total of 132, 90 and 69 strains, respectively.