dataesr/scientific-paragraphs-categorization huggingface dataset:
Limitations and future research The primary limitation of this study lies in the shortcomings of the compositional data. The substitution effect between the different forms of tourism was examined by focusing on the market share. However, this may have caused information contained in the data to have been lost. Information can also be lost in the computation of the raw data (e. g. weighted average of source markets). Future studies should use a combination of absolute data and compositional data to further examine the effects of terrorist attacks on tourism  (Abuza, 2005; Kim & Gu, 2004). Moreover, the secondary dataset used by this study has certain deficiencies, as not all international tourist arrivals were included, not all wine regions/rural regions were taken into consideration, and changes in domestic patterns were not captured.
Observation Simulations of 2000 steps were analysed by summarizing agent size every 10 steps (see Fig. 2 ). For each observation, we summarized data in three groups: i) for all agents (gp1), ii) only grouped agents (gp2) and iii) only lone agents (gp3). For each of these groups we looked at the mean size of gp1, gp2 and gp3 to obtain information about the benefits these agents derived from use of the resource. As an indicator of inequity between agents, we computed the Gini index on the size distributions of gp1, gp2 and gp3. This index could take any value between 0, in the case of perfect equity, and 1 in the case of strong inequity.
Initialisation Our agents were all initialized with the same size (S = 1) and no shared resource stocks (Sc = 0). As our agents were not mobile, their initial positions were maintained within and between the simulations. These individual positions were read from one of 90 different spatial distributions generated to represent random, regular or clustered positions (see simulation plan sect. 2. 4). We used two types of space for the initialization of patches: i) a random distribution of the resource through space based on a uniform distribution and ii) the legacy sugarscape  (Epstein and Axtell, 1996)  resampled with the raster package  (Hijmans, 2015). Once the patches received an initial sugar level (ops), we defined the minimum and maximum amount of the resource for each patch. Once patches and individuals were initialized, a "scaling distance" (Sd) was computed to define the cooperative agents and create groups.
Acknowledgments We would like to thank the Limoges University foundation, Engie, and Société Hydro-Electrique du Midi (S. H. E. M. ) for their financial support. Simulations were performed on the CBGP HPC computational platform and CALI, the computing cluster at Limoges University, funded by the Limousin region, the European Union, the XLIM, IPAM & GEIST institutes and Limoges University. Thanks go to the CALI team and OpenMole team for their technical support, to two anonymous reviewers and Rebecca Tyson (Associate Editor) who greatly improved the manuscript and to Laurence Dedieu and Peter Biggins for remarks and the English editing of the manuscript. Mean number of agents per groups qq q q q q q 100. random.
Combes et al. (2005)  bring this analysis to an intra-national setting to isolate networks effects from other explanations of trade and look at the role of business and social networks in shaping trade between 94 French regions. The impact of social networks is quantified using bilateral migrant stocks, and business network effects are assessed using data on the links between plants belonging to the same business group. The authors estimate the trade-creating effect of business and social ties on bilateral trade based on a traditional gravity equation and expand the estimation to a "structural" specification directly derived from a model of trade characterized by monopolistic competition, home-biased preferences, information, and transport costs. The authors find that compared to a situation without networks, the average bilateral migrant population doubles trade flows between French regions.
They include country of origin and time fixed effects, control for important economic and socio-political covariates such as female education, the type of electoral system, or general wealth in the society, and address reverse causality using a gravity-based model to predict bilateral migration stocks (as in  Ortega and Peri, 2014; Alesina et al. , 2016 or Docquier et al. , 2016). The paper uses information on the gender composition of national parliaments between 1960 and 2003 and bilateral migration data between 1960 and 2000, which they combine with other databases to construct a panel dataset of 170 countries over five decades. Their results suggest that international migration to countries with higher female parliamentary participation has a positive and significant effect on the female parliamentary share at origin (by about 1.
Rapoport et al. (2017)  investigate the role of international migration on the convergence or divergence of attitudes and values between countries. In particular, the authors focus on the question of whether bilateral migration makes sending and receiving countries more similar or dissimilar in terms of political and economic attitudes, trust, attitudes to risk, and religiosity. Their analysis consists of two parts: (i) a theoretical model of migration-based cultural change, and (ii) an empirical analysis for a panel of countries between 1981 and 2014, combining data from rounds of the Word Value Survey and the World Bank's bilateral migration dataset.
The authors construct a global dataset for time-varying bilateral cultural distance measures, making sure that compositional effects (i. e. , changes in the number or types of questions used in the World Value Survey) do not influence the outcomes. Additionally, the analysis incorporates several different statistical distance measures. These distance measures (most prominent measures include the Euclidean distance and the Herfindahl index) capture different aspects of similarity, some of them highlighting the overlap of responses between respondents from different countries, others looking at how similar the most dissimilar people between two countries are (comparing the two extremes). The empirical analysis tests the conditions under which the model predicts cultural convergence or divergence for over 6000 country-pairs between 1981 and 2014.
The authors can only detect an aggregate effect (reduced form), showing which of the two forces (convergence or divergence) dominates. Using a gravity model of cultural convergence with country-pair and time fixed effects, the authors show that bilateral migration leads to cultural convergence and that the diffusion effect dominates. The authors then conduct different analyses that either support the CM or the TM and find evidence for the channels proposed in the TM. The mechanisms themselves are then tested in a heterogeneity analysis, differentiating between country-pairs with high economic versus cultural incentives for migration or identifying respondents in the WVS dataset that are immigrants (this information is available for two waves). Derived from  the TM model, the authors expect convergence to be higher for initially distant country-pairs and for country-pairs with high levels of interaction between the diaspora and the home community, which is confirmed in the data.
Acknowledgments This article has been prepared as background paper for the  UNU-WIDER Development Conference  on "migration and mobility," jointly organized with the  African Research Universities Alliance (ARUA) , which took place on 5-6 October 2017 in Accra,  Ghana , and published as WIDER Working Paper Series  2018-025. It extends earlier published work (Rapoport, 2016(Rapoport, , 2017)). Compared to the latter, I added wherever possible evidence on South-South migration, I considerably extended Section 2. 3, added a new Section 3. 4, and updated the text and references. I am thankful to an anonymous referee and the editor for useful comments. Responsible editor:  Jackline Wahba.
cyaneus after 3-h treatment. Heavy metals are bound by specific proteins, metallothioneins  [20]. Metallothionein (MT)-encoding sequences have been reported from the genome and transcriptome of Hyalella azteca Saussure, 1858  [21]  an the transcriptome of another amphipod species, Grandidierella japonica Stephensen, 1938  [22] ; the abundance of these sequences was approximately two-fold higher in response to zinc exposure (  [21, 22] ) and even 16-fold higher in response to cadmium exposure (  [21] ). Therefore, we looked for transcripts that potentially encoded MT in our full datasets and found from 3 (in G. lacustris) to 13 (in E. cyaneus) such transcripts in our assemblies (Additional file 6). However, none of the transcripts was differentially expressed according to our standards, even though the majority of transcripts in Baikal species had higher median abundance values under cadmium treatment (Additional file 1; Fig.
4d ). Moreover, most of the transcripts had low expression: only six transcripts in E. cyaneus, one transcript in E. verrucosus and no transcripts in G. lacustris had abundance higher than one transcript per million (Additional file 1: Figure  S3 ). Expression levels of the two most abundant transcripts are shown in Fig. 4d. The predicted protein sequences encoded by these transcripts are identical, and the most similar sequence in the NCBI nr database turned out to be the MT of a deep-sea vent brachyuran crab Allograea tomentosa Guinot, Hurtado & Vrijenhoek, 2002. The sequence of A. tomentosa was only 53% identical to those of Eulimnogammarus sp. , but all the Cys residues were conserved within the three proteins (Additional file 1: Figure  S3 ), suggesting that these transcripts indeed encode metallothionein-like proteins.
Read quality control and de novo transcriptome assembly Quality control for the reads was performed with fastQC  [35]  v0. 11. 5, and results were summarized with Mul-tiQC  [36]  v1. 2. Illumina universal adapter sequence was found at the end of up to 10-20% sequences, probably because the insert was below the expected length. These adapter sequences were trimmed with trim_galore  [37]  v0. 4. 1. Moreover, up to approximately 27% of the forward reads and approximately 20% of the reverse reads were assigned to overrepresented sequences. These sequences were analyzed with the NCBI BLAST web interface  [38]  and assigned to ribosomal RNA sequences. To filter out these sequences, a custom database of rRNA sequences of gammarid amphipods Additional file 7 was created. All reads were aligned to this database with bowtie2  [39]  v2.
Assembly quality control, annotation, and filtering Quality control of the assemblies was performed with TransRate  [42]  v1. 0. 3. Assembly completeness was estimated with BUSCO  [13]  v3. 0. 2. Each transcript was annotated with the blastx analog of the accelerated blastp-like program diamond  [43]  v0. 9. 10. 111 against the NCBI non-redundant protein sequence database of Oct 10 2017. It allowed us to assign the best protein hit for transcripts (contigs) and also provide taxonomic assignations based on this best hit. Then, redundant sequences were removed with the Evidentialgene pipeline  [44] , and only the contigs with the best diamond hit to a sequence belonging to a metazoan species were selected. This reduced data set was labeled with ani (e. g. , EveBCdTP1_ani; Fig. 1a ) and served as references for mapping reads in the differential expression analysis.
Differential expression Transcript quantification was performed with salmon  [47]  v0. 9. 1, and subsequent analysis was performed with DESeq2  [48]  v1. 14. 1 and tximport  [49]  v1. 2. 0 packages for R  [50]. The p-values were adjusted according to the Benjamini and Hochberg procedure  [51] , which is the default option in DESeq2  [48]. Only transcripts with the adjusted p-value below 0. 001 and the absolute logarithm of fold change above 3 (i. e. , 8-fold difference) were considered differentially expressed unless stated otherwise. GO term overrepresentation analysis was implemented with the topGO package  [52]  v2. 34. 0 for R. In-house R scripts for data analysis are available at github, see  [53].
eetveldeana De Wild. & Th. Dur. In this paper, we report the isolation and structure elucidation of 2 previously undescribed triterpene saponins together with 4 known ones. Their structures were elucidated by spectroscopic methods including 600 MHz 1D and 2D experiments ( 1 H,  13  C, HSQC, HMBC, COSY, TOCSY, ROESY) in combination with HR-ESIMS and by comparison of their physical and spectral data with literature values. The saponin fraction obtained from the 80% aqueous methanolic extract of the stem bark of P. eetveldeana was fractionated by vacuum liquid chromatography (VLC) on reverse-phase RP-18 silica gel and medium-pressure liquid chromatography (MPLC) yielding 2 previously undescribed saponins 1 and 2 (Figure  1 ) and 4 known ones. The known molecules were identified by comparison of their spectral data with literature values as 3 -O-α-l -rhamnopyrano- syl-(1→2)-[β-d -glucopyranosyl-(1→4)]-α-l-arabinopyrano- syloleanolic acid 7 and 3-O-α-l -rhamnopyranosyl-(1→2)-[β-d -glucopyranosyl-(1→4)]-α-l -arabinopyranosylhederagenin 8 widely distributed, 3-O-β-d -glucopyranosyl-(1→3)-α-l -rhamnopyranosyl-(1→2)-[β-d -glucopyranosyl-(1→4)]-α- l-arabinopyranosyloleanolic acid, 2 and 3-O-β-d -glucopyra- n o s y l -( 1 → 3 ) -α -l -r h a m n o p y r a n o s y l -( 1 → 2 ) - [β-d -glucopyranosyl-(1→4)]-α-l-arabinopyranosylheder- agenin 2 isolated from P.
We employed the data from the groups introduced to dispersal arenas at Day 0 and surveyed until Day 17. For each day, we used the coordinates of four individuals that were drawn randomly from four (out of 10) different arenas to compute the mean nearest-neighbor distance. This procedure was repeated 500 times to obtain the random level of aggregation. The comparison between groups introduced at Day 0 and groups introduced at Days 5 and 10 allowed us to disentangle the possible role of novelty, habituation or the presence of silk from the influence of maturation on the initiation of dispersal.
We used the function Analyze Particles of the software ImageJ 5. 1 to extract automatically the coordinates of each individual from the pictures of dispersal arenas (every picture was then checked by eye to control the accuracy of detection). For single spiders, we calculated the distance covered between two successive photographs considering the presence of walls. In groups, spiderlings were not marked so it was not possible to identify each spider between consecutive pictures and to determine to what extent each individual moved between two timesteps. We estimated the distance covered by each spiderling in groups by assuming that it minimized its displacement between two time steps and we averaged the four measures to obtain the mean individual distance covered in groups. We acknowledge that our approach was rather conservative and underestimated the actual distance covered by spiderlings.
Interattraction To examine whether the strength of interattraction declined over time, we used data on spiderlings from three cocoons (collected in Marquefave) maintained in the incubator since October 10 2016 and opened on January 24 2017. Groups of four siblings (N = 30) were placed in breeding dishes (diameter: 55 mm, height: 15 mm) in a climate-controlled room (24 ± 1˚C, 35% RH) under a 12:12-h light:dark cycle (light at 8:00 and dark at 20:00). Breeding dishes were watered every two days with an atomizer. On the day of testing, spiderlings were removed from the breeding dishes and introduced alone or in pairs (from the same breeding dish) to white PVC circular arenas (diameter: 44 mm, height: 3mm). The arenas were placed on white paper and covered with a glass plate to prevent spiders from escaping.
First, we compared the influence of conspecifics on the probability of moving for a spiderling that was stopped alone or in contact to another spider. Each 24h-movie was analyzed with the tracking software SwisTrack (v4. 0) using the "Nearest Neighbour Tracking" method at a rate of 2. 08 frames per second to extract automatically the coordinates of spiderlings in arenas. For each pair, we calculated the lifetimes of aggregates by considering that two individuals were aggregated if their interindividual distance was less than 10 mm for more than one second  [5]. We deliberately used a larger criterion than the one used to estimate the probability of stopping and the encounter rates (6 mm) because a too stringent criterion could be detrimental for the estimation of the durations of long stops as stopped spiders sometime made very small movements.
The comparison between the lifetimes of aggregates in virtual and real pairs revealed the contribution of social interactions to aggregation. For each day, we compared the survival curves of aggregates' lifetimes between real and virtual pairs using a Cox proportional hazard model (function coxph implemented in the package Survival in R) (Fig  3 ). The Cox proportional hazard model is a semiparametric survival model that necessitates no specification of its baseline hazard function. The hazard ratio estimates the difference in the hazard rate (i. e. , instant probability for the event of occurring at time t) between two samples  [71]. We used the hazard ratio associated with its 95% CI as a proxy to quantify the strength of interattraction. A hazard ratio of 1 indicates similar lifetimes between real and virtual aggregates.
Activity level We compared the level of activity between spiderlings that were maintained alone or in groups. Five to six h after the completion of the trials to estimate the aggressiveness toward a prey (see Aggressiveness toward a prey section), we introduced spiderlings alone to circular arena (transparent plastic dish: diameter: 55 mm, height: 8 mm) to record their activity. After 15 min of acclimation, we recorded the tracks of each spider using a video camera (Sony Handycam HDR-XR350) for 30 min. The tracks were then analyzed with the tracking software SwisTrack to extract automatically the coordinates of the spiderlings in arenas at a sampling rate of 3 frames per second. We compared the fraction of time spent moving (moving threshold = 0. 5 mm) during 30 min between spiderlings raised alone or socially with a t test after square root transformation.
GC-MS analysis was performed in a mass spectrometer ISQQD Single Quadrupole GC-MS System (Thermo Fisher Scientific Inc. , Villebon sur Yvette, France), fitted with a capillary column (Restek RTX-5MS 30 min × 0. 25 mm, 0. 25 μm film thickness, 5% diphenyl and 95% dimethylpolysiloxane) and a splitless injector (300˚C). Ionization was by electron impact (70 eV, source temperature: 250˚C). Helium was the carrier gas (1,2 ml/min). After sample injection (2 μl), the oven temperature was maintained at 100˚C during two min. then programmed at 10˚C/min to 320˚C and held for 5 min. The mass spectra were scanned in full scan mode from 50 to 600 m/z values. Samples were automatically injected using an autosampler AS300 (Thermo Fisher Scientific Inc. , Villebon sur Yvette, France). For each GC sample, peak heights were calculated by manual integration using the Xcalibur software and were then expressed as the percentage of the total peak height.
A total of 55 compounds were considered in the analysis (S5 Table ). A standard mixture of alkanes, from n-C7 to n-C40 (Supelco, Sigma-Aldrich, 10 ng/μL each component), was used as a qualitative reference. The identification of the structure of hydrocarbons was determined using the mass spectral fragmentation patterns, comparison of the retention times with those of injected known compounds and the NIST library spectra. A nonmetric multidimensional scaling (NMDS) based on Bray-Curtis dissimilarities was performed on cuticular hydrocarbons data to visualize the relationships between groups on a two-dimensional layout. The NMDS is an unsupervised technique that ranks the distances to map objects onto a two-dimensional ordination, preserving ranked differences but not the original distances  [76].
The quality of the ordination is given by a value of stress ranging between 0 and 1. A stress value of 0. 05 reveals an excellent ordination and a value of 0. 3 reveals a poor representation. Differences in cuticular lipid profiles between cocoons and treatments were tested using PERMANOVAs (function adonis in the R package vegan, 999 runs  [77] ). For each cocoon, we next calculated the Variable Importance in Projection (VIP) scores (1st and 2nd component) of each compound following a discriminant analysis (Partial Least Squares Discriminant Analysis, PLS-DA  [78] ). High VIP scores indicate highly influential compounds in the discrimination between spiderlings maintained alone or in groups (S9 Fig). The comparison of the compounds with the highest VIP scores between cocoons allowed us to determine whether social isolation induced consistent changes in cuticular profiles.
Funding was provided by  CNRS  (www. cnrs. fr) to RJ; UniversiteToulouse III (www. univ-tlse3. fr)to RJ; and  Ministère de la recherche  (www. enseignementsup-recherche. gouv. fr) to VC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
mattogrossae Brazil, Mato Grosso do Sul, Corumbá 30 (LBCE5690) MN019618 present paper O. mattogrossae Brazil, Mato Grosso do Sul, Corumbá 30 (LBCE5720) MN019619 present paper O. mattogrossae Brazil, Mato Grosso do Sul, Cassilândia 31 (LBCE12111) MN019606 present paper O. mattogrossae Brazil, Mato Grosso do Sul, Corumbá 30 (LBCE5719) MF951057 da Cruz & Weksler, 2018 O. messorius Venezuela, Amazonas, Pozon, 50 Km NE of Puerto Ayacucho 1 ROM107872 EU095455 Borisenko et al. 2008 O. messorius Venezuela, Amazonas, Pozon, 50 Km Ne of Puerto Ayacucho 1 ROM107871 JF491684 GenBank O. messorius Guyana, Upper Takutu-Upper Essequibo, 5 Km Se of Surama 2 ROM103349 JF491726 GenBank O. messorius Guyana, Upper Takutu-Upper Essequibo, 5 Km Se of Surama 2 ROM103348 JF491727 GenBank O. messorius French Guiana, Saul, znieff Coudreau 7 (M829_JAG) MN015520 present paper O.
utiaritensis Brazil, Mato Grosso, Ribeirão Cascalheira 18 (ARB763) MN015490 present paper O. utiaritensis Brazil, Mato Grosso, Sapezal, Fazenda Begolim 19 MN75595 (LBCE12174) MN019598 present paper O. utiaritensis Brazil, Mato Grosso, Sapezal, Fazenda Begolim 19 MN75598 (LBCE12186) MF951074 da Cruz & Weksler, 2018 O. utiaritensis Brazil, Mato Grosso, Sapezal, Fazenda Begolim 19 MN75599 (LBCE12225) MN019599 present paper O. utiaritensis Brazil, Mato Grosso, Campo Novo dos Parecis 20 MN75616 (SVS299) MF951076 da Cruz & Weksler, 2018 O. vegetus Costa Rica, Cartago, Volcan Irazu not plotted ROM113156 EU095457 Borisenko et al. 2008 O. vegetus Nicaragua, Rivas not plotted ROM112192 JF491683 GenBank.
The research of JC was supported by the Hungarian National Research, Development and Innovation Office (Grant Number NKFI-6 K 125265). The Interactions Arbres-Microorganismes (IAM) laboratory of AH is supported by a grant overseen by the French National Research Agency (ANR) as part of the "Investissements d' Avenir" program (ANR-11-LABX-0002-01, Lab of Excellence ARBRE). NL acknowledges the financial support from Bayer CropScience AG through the "Grants4Targets-Novel targets for crop protection" program. DR acknowledges the support by the Agriculture and Food Research Initiative (Competitive Grant No. 2015-67013-22818) of the USDA-National Institute of Food and Agriculture and expresses.