dataesr/scientific-paragraphs-categorization huggingface dataset:
Another important finding from our study relates to the range of pollination systems within large monophyletic groups. Two of the largest subtribes/tribes within Apocynaceae, with 720-730 species each, are characterized by possession of one (Stapeliinae) and ten (Marsdenieae) distinct pollination systems (Fig. 4 ). Stapeliinae is well represented in the Pollinators of Apocynaceae Database (Supplementary Data S2 and 3A) and has diversified rapidly across Africa and Asia over the last 10 million years  (Bruyns et al. , 2015; Fishbein et al. , 2018)  into a species radiation that has involved only fly pollination. Previously, pollinator shifts between major groups of pollinators (e. g. bird to bee) have been suggested as a significant driver of plant diversification and termed the Grant-Stebbins model  (Johnson, 2006).
Strengths and future applications of the Pollinators of Apocynaceae Database The Pollinators of Apocynaceae Database is the largest and most extensive compilation of such data that has ever been assembled for a plant family of this size. It contains a >10 % sample of species within the family with data on flower visitors and pollinators (Supplementary Data S2), with a wide phylogenetic and geographical coverage. As a freely available resource, the database will in the future be used to explore many other questions, such as how evolution of complex flowers, pollinaria and rewards (or rewardlessness) has been influenced by the type of pollinators that a flower attracts and exploits. Additionally, this database will serve to guide efforts in the systematic collection of data in poorly studied parts of the world, and for incompletely known taxa of Apocynaceae.
An important future value of the Pollinators of Apocynaceae Database will be to assess a number of conservation issues. These include the extent to which introduced honey-bees (Apis mellifera) and other pollinators are affecting plant reproduction (and potentially selection on floral traits) as well as the ability of introduced, invasive Apocynaceae to co-opt native pollinators, for example the South American Araujia sericifera that uses honey-bees as its pollinator in South Africa  (Coombs and Peter, 2010). Plant-pollinator interactionspollinator interactions within the family present different degrees of specialization at ecological, functional or phenotypic levels (sensu  Ollerton et al. , 2007). This information could be used to inform conservation of native habitats that maintain populations of Apocynaceae, in which their pollinators can be supported by other plant species and nesting opportunities.
Some of these clades have recently been shown to be of critical importance for understanding the evolution of complex floral characters in the family, for example the Baisseeae which is sister to the Secamonoideae + Asclepiadoideae  (Livshultz et al. , 2007; Fishbein et al. , 2018). Bat pollination has never been confirmed within the family; however, the database contains one record of unidentified Apocynaceae pollen on bats in Brazil, and we are also aware of images circulating on the internet showing bats visiting Apocynaceae flowers in Costa Rica. There are also intriguing flowers such as those of the mass-flowering Mandevilla veraguasensis in Central America that bear some of the hallmarks of specialized bat-pollinated flowers, being dull dusky purplish-brown, large, funnel-shaped and pendant on relatively long pedicels (M.
ACKNOWLEDGEMENTS We offer grateful thanks to all of the authors of studies that we have included in our database, which reflects a research effort that goes back over 100 years. Funding for fieldwork to JO and his group was obtained from The  British Ecological Society , the  Percy Sladen Memorial Fund , the  Royal Society  and the  University of Northampton. JO would like to thank the many field assistants and in-country contacts who helped with data collection, species identification, accommodation and field sites in  Australia, Gabon, Guyana, Namibia, Tanzania, Peru and South Africa. AAC, APW, LG  and  CT thank CONICET, FONCyT and SECyT  for financial support. LPCM thanks  São Paulo Research Foundation -Fapesp  (grants # 2013/50155-0 , # 2010/51307-0 ) and  National Council for Scientific and Technological Development -CNPq  ( PVE 400717/2013-1; PQ 1D Researcher ) for funding, and  PELD-CRSC-17 ,  Serra do Cipó National Park ,  Cedro Company , and  Vellozia Reserve  for supporting fieldwork.
SP acknowledges funding support from the  Science and Engineering Research Board of India for systematic and ecological studies of Indian Ceropegia. MCG thanks Rio de Janeiro Research Foundation -Faperj  (grant  E-26111. 271-2014 ) and  CNPq  (PQ 2 Researcher) and also thanks the following entomologists for identifying specimens:  Gabriel A. R. Melo  and  Brunno B. Rosa  (Hymenoptera),  Diego R. Dolibaina (Lepidoptera ) and  Paschoal C. Grossi  (Coleoptera). LHF was supported by a Masters scholarship from  CAPES. L. Civeyrel was supported by the  French Laboratory of Excellence  project " TULIP"  ( ANR-10 -.
Once within the cell, MCs specifically inhibit eukaryotic serine/threonine protein phosphatases 1 and 2A, which causes the disruption of numerous cellular signals and processes  (Fischer et al. , 2005; MacKintosh et al. , 1990). Although there have been 70 members of OATP superfamily identified in the database from humans, rodents and some additional species  (Hagenbuch and Stieger, 2013) , not all OATPs are capable to transport MCs through cell membranes. The capability of MC-transport has been demonstrated for OATP1A2 (mainly expressed in the vertebrate brain), liver-specific OATP1BA and OATP1B3 in humans  (Fischer et al. , 2005). In fish, liver-specific OATPs, such as OATP1d1 in little skate  (Meier-Abt et al. , 2007)  and rtOATP1d1in rainbow trout  (Steiner et al. , 2014) , have been reported to mediate MC-transport.
Histopathological observation and immunolocalization of microcystins In the platform of ENVA, the liver and gonad samples fixed in formaldehyde fixing solution at 4 °C for 48 h were dehydrated in successive baths of ethanol (from 70 to 100%) and embedded in paraffin. Blocks were cut into 4 µm thick sections. The sections of each sample were deposited on 3 slides. One slide was stained with hematoxylin-eosin-saffron (HES) staining for histopathological observation. Another slide (only liver sample) was stained with periodic acid-Schiff (PAS)/Alcian blue staining for the assessment of hepatic glycogen reserve. The glycogen reserve analysis performed by ImageJ software (version 1. 51d) estimated the hepatic glycogen quantity as a surface percentage of the purple-red pixels on 5 randomly selected photos (200 × magnification, photo size 1388×1040 pixels, as seen in Figure  1 ) per individual.
Acknowledgments This work was supported by grants from the  CNRS   Défi ENVIROMICS "Toxcyfish" project and from the ATM "Cycles biologiques: evolution et adaptation " of the MNHN to  Dr. Benjamin Marie. Qin Qiao PhD  is founded by the  China Scholarship Council. We thank the  Amagen platform  for providing medaka fish Cab strain, the microscopy platform of ENVA and MNHN for the histopathology and immunolocalization techniques. We also thank  Marie-Claude Mercier  for its administrative support.
It controls the energy flux between the metro stations and the demand units. It includes a data communication system, which transfers real-time data of the metro stations (energy source), the demand units, as well as other data such as the weather. The system also collects data from users to improve the quality of the energy supply, as well as the security. The system stores these data in an information system. Based on real-time and historical data, the system allows for the energy flux to be determined, and controls the technical and regulations process to guarantee this flux. The smart system controls also the operational security of the energy transport. The optimization of the energy supply is based on the determination of the real-time global demand (heating or cooling), as well as the thermal energy availability, together with the availability of other energy resources.
Based on economic criteria as well as environmental impact criteria, the system determines the optimal energy flux. The system stores all the data concerning the energy demand, the energy availability, and the energy supply, as well as the weather data and the users' information. These data are used for the development of predictive models that will be used for the preparation of the energy supply program. The exploitation of thermoactive metro stations raises economic and legal questions, which should first be addressed. The supply of the thermal energy from the metro station to a third party should be authorized by the public authority. In February 2017, the "Grand Paris" Agency has been authorized to exploit or delegate the exploitation of the geothermal energy from underground structures (this is Law No.
Assessment of the Geothermal Potential The optimization of the energy supply is based on the determination of the real-time global demand (heating or cooling), as well as the thermal energy availability, together with the availability of other energy resources. Based on economic criteria as well as environmental impact criteria, the system determines the optimal energy flux. The system stores all the data concerning the energy demand, the energy availability, and the energy supply, as well as the weather data and the users' information. These data are used for the development of predictive models that will be used for the preparation of the energy supply program. The exploitation of thermoactive metro stations raises economic and legal questions, which should first be addressed. The supply of the thermal energy from the metro station to a third party should be authorized by the public authority.
It is considered that the heat pump decreases or increases the fluid temperature related to the thermal solicitation. The calculations are driven with the software FLAC3D  [36]. The finite difference mesh is composed by 201,600 hexahedral zones and 209,329 nodes. The mesh is refined in the vicinity of the diaphragm wall to account for the high heat exchanges at the soil-structure interface, and near the surface, because of the seasonal thermal variations. Before thermal activation, the model must be initialised according to the hydraulic and thermal boundary conditions (especially to consider the seasonal temperature variations in the ground). The boundary conditions for both thermal and hydraulic aspects are defined in Table  4. The distances between the boundaries of the numerical model and the diaphragm walls need to be sufficiently large to avoid any interaction.
Monitoring Since the behaviour of thermoactive metro stations is complex, monitoring is required for both assessment and a deep understanding of this complex system. Various types of monitoring could be used to track the thermo-hydro-mechanical behaviour of the stations. In practice, only the thermal and mechanical aspects are monitored. Now, several techniques can be performed: thermal strains, strain gauges, optic fibres, etc. (Figure  9 ). The main objective is to correlate the inlet and outlet temperature of the heat exchanger fluid to the thermal variations, the strains, and the displacements into the diaphragm walls. All these data can be stored and analysed in order to improve the design of this kind of technique. At this stage, the measurements on thermoactive geostructures have not yet started, but other data have been registered on other thermoactive geostructures.
The manifest variables were the validated dimensions of ageing perceptions, coping, psychological distress and quality-of life. The construction of latent variables from these manifest variables was assessed by factor analysis. The structural equations representing hypothesized relationships are tested using a t-statistic computed from the standardized coefficients of patheffect estimates and their standard errors. To assess the global fit of the model, three criteria were used: i) the goodness of fit χ 2 test which is based on the discrepancy between the observed model and a model with perfect fit, ii) the root mean square error approximation (RMSEA), and iii) the Bentler comparative fit index (BCFI)  [21]. The statistical analyses were performed on SAS software version 9. 3 for Windows.
Validation data for segmentation algorithms dedicated to preclinical images is fiercely lacking, especially when compared to the large number of databases of Human brain images and segmentations available to the academic community. Not only is such data essential for validating methods, it is also needed for objectively comparing concurrent algorithms and detect promising paths, as segmentation challenges have shown for clinical images. The dataset we present here is a first step in this direction. It comprises 10 T2-weighted MRIs of healthy adult macaque brains, acquired on a 7 T magnet, along with corresponding manual segmentations into 17 brain anatomic labelled regions spread over 5 hierarchical levels based on a previously published macaque atlas (Calabrese et al. , 2015) [1]. By giving access to this unique dataset, we hope to provide a reference needed by the non-human primate imaging community.
Data MR images of the brain of 10 healthy young adult macaques were acquired on a 7T scanner. In each volume, 15 relevant sections (7 coronal, 5 axial, 3 sagittal, encompassing all the major brain anatomic regions), spanning the whole brain, were selected for manual segmentation. Raw MRIs and manual segmentations are available as NifTi volumes in a NITRC repository (https://www. nitrc. org/projects/ mircen_macset). They will also be available with the next release of BrainVISA (version 4. 6, http:// www. brainvisa. info), through the BrainVISA installer. This dataset is distributed under the CeCILLv2. 1 license (http://www. cecill. info), a GPL-compatible license, and can be freely used for academic work, upon citing this paper. This dataset was used to validate automated segmentations obtained with Primatologist, a pipeline dedicated to macaque brain morphology analysis  [2].
Preprocessing Data format was converted with BrainVISA from Varian FDF, produced by the scanner, to gzipped NifTi. Because Varian's on-disk storage is sequence-dependent and does not provide voxel-to-world transforms, volumes were flipped, and the appropriate voxel-to-world transforms were stored into the NifTi header, with BrainVISA's python tools (pyAIMS) so that volumes can be used with any software able to handle NifTi metadata. Offsets were set so that the origin is the center of the volume. See https://nifti. nimh. nih. gov for additional precisions on the NifTi format and the way it handles transforms.
Classification scores This dataset is provided with a set of python functions, which allow computing classification scores with our manual segmentations as a ground truth. Because scores can only be based on sections that were manually segmented, the corresponding sections in the evaluated 3D segmentations can be automatically extracted. Image segmentation can be seen as a classification problem, a domain where the F 1 score is a widely used metric. The F 1 score is exactly equivalent to the Dice coefficient  [4] , a more common designation in the field of image segmentation. For a given class, let us call P the set of voxels that belong to it and F the set of non-belonging voxels. Then |P| þ|F| ¼ n, the number of voxels in the image. Let us note C P the set of voxels classified as belonging to the class and C F those classified as non-belonging.
Files comprised in the dataset. Subjects are named M01 to M10. MAC[*]_manual_sagittal. nii. gz Manual segmentation of 3 sagittal sections. MAC[*]_manual_merged. nii. gz Fusion of manual segmentations in all three incidences. MAC[*]_manual_[*]_mask. nii. gz Mask of the manually segmented sections. It must be used to compute F 1 scores. hierarchy. csv/. hie Ontology and labels associated with the segmented regions. classificationScores. py Set of python functions allowing computing classification scores.
of 116 fish species in the Tonle Sap over 15 years. The Tonle Sap, at the whole fishery scale, has been shown to employ an amazing amount of fishing gears applied broadly across habitats and seasons in a manner that uniformly catches a high diversity of fishes (see  13  , Fig. 5 ). This approach is highly suggestive of a relatively indiscriminate fishery. The dataset for the study was obtained from a standardized biological catch assessment of an industrial-scale 'Dai fishery' that operates during the dry season in the Tonle Sap River. We explore how temporal trends of fish catch captured by this fishery relate to each species' maximum body size and trophic level. We also examine changes in the body weight and length of individual fish for select species over the assessment period.
Discussion Trends in the seasonal catches of harvested species revealed that 78% of the 116-species are in decline. While we do not have fishery independent data to confirm the large Dai dataset, our results are consistent with the prediction of an intensively exploited indiscriminate fishery. Consistent with indiscriminate fishing theory, a closer examination of the data indicated that the catch declines are disproportionally represented by the larger, slower growing, higher trophic level organisms of the Tonle Sap. By contrast, the 22% of species caught by the Dai fishery that have tended to show increases are disproportionally represented by small-bodied, faster growing lower trophic level organisms. In addition, significant declines of the mean fish size and trophic level were evidenced in the seasonal catches of the fishery over the study period (Fig.
Methods Dai fishery. This study used time series catch weight data of a standardized assessment on an industrial-scale 'Dai fishery' between 2000 and 2015 (see also S1). The fishery seasonally operates between October and March in a specific location along the lower section of the Tonle Sap River, stretching about 4-30 km north of Phnom Penh. All Dai (64 units) are organized into 14 rows (referred to as row 2 to 15, with the most upstream row 15 situated closest to the Tonle Sap Lake; Fig. 6a ) and operated singly or jointly of up to 7 units in a single row (Fig. 6b ). A Dai unit can be uniquely identified through a combined alpha-numeric code of row number and the letter ' A' to 'H' of each individual Dai in that row. For example, Dai 2 A indicates Dai A in row number 2. The transversal position of Dai rows within the river channel changes along up-and downstream axis (Table  S2 ).
Data collection. Catch data from the Dai fishery were made available by the Fisheries Programme of the Mekong River Commission that technically and financially support the catch assessment programme. The catch of the fishery has been routinely assessed by the former Department of Fisheries (currently is the Fisheries Administration -FiA) and later by the Inland Fisheries Research and Development Institute (IFReDI) of the FiA in cooperation with its sub-national counterparts. General concepts and formula for assessing catches and catch composition are outlined in  54  , and these concepts were used to frame the sampling protocols and assessing catches of the fishery. The sampling unit was based on Dai unit and a randomly stratified sampling method was used for this paper. More specifically, Dai units were stratified based on (Fig.
The total catch estimated for a fishing season is the aggregation of the monthly catch estimated for that season. Apart from sampling data on total catch for each species in each season, data were also obtained for the number, weight and length of some common and commercial individual fish caught per day of each fishing season. These species are among the most ecological, sociocultural (food nutrition and security) and economic important species in the region  33, 52, 55. Therefore, they were used to examine the temporal changes in body weight and length for this study (see Figs  4  and 5 ). Further description of the sample sizes, sampling protocols, data collection forms on catch, species composition and fishing effort, the formula for catch estimation as well as the database system to store and manage the collected data of the fishery are given in detail by  53.
The current Dai fishery database contains information on a total of 141 species. However, only 116 fish species were included in the analysis for this paper because data on the seasonal catches of the other species were sporadic throughout the time series. Furthermore, the species dropped from the analysis were quite marginal in terms of overall catch, and the total catch of the 25-fish species not included in this analysis only represented 0. 38% of the total fishery's catch recorded between 2000 and 2015. Of 116 species, the analysis includes 5 endangered and critically endangered species namely Probarbus jullieni, Probarbus labeamajor, Catlocarpio siamensis, Pangasianodon gigas and Pangasius sanitwongsei. In addition to the Dai fishery datasets, data were also obtained on maxTL and trophic level of fish species in the Tonle Sap from FishBase  56.
Linear regressions, and the generation of standardized regression coefficients, were performed using the 'lm' function of 'stats' package and 'lm. beta' function of 'QuantPsyc' package  60. Histograms were used to visualize the distribution of standardized regression coefficient values of all species. Simple linear regressions were used to explore the global trend of the relationships between standardized regressions coefficients and species' maxTL and trophic levels (obtained through FishBase). For all regression analyses, normality was ensured by Shapiro tests (p-value > 0. 05). Log +1 transformation was applied to normalize the skewness of standardized regression coefficients prior to the linear regression analyses. In addition, weighted means of maxTL and trophic level in Dai catches by season were computed to examine trends of mean maxTL and tropical level across the 15-year study period.
To explore temporal trends in the individual weights of the fish constituting the catch, the mean weight of all individuals captured per species per day was calculated and regressed against time. To deal with the data skewness, mean body weight was log-transformed before the analysis, and standard deviation for each species was also computed for each fishing season for the whole study period. This analysis was performed for six common species that spanned a range in standardized regression coefficient values (positive, zero, negative), body sizes and trophic levels, and included large-and medium-sized carps (Cyclocheilichthys enoplos, Osteochilus melanopleurus, and Cirrhinus microlepis), a large-sized river catfish (Pangasianodon hypophthalmus), as well as small-sized and highly productive mud carps (Henicorhynchus lobatus and Labiobarbus lineatus).
Acknowledgements We are grateful to the  Erasmus Plus, Belmont Forum  ( TLSCC  project) and the European Erasmus + credit mobility and capacity building CONSEA Programmes for funding our study. This research was in part funded by  Belmont Freshwater Grant  and  Canada First Research Excellence Fund  to KSM. Cordial thanks to the  Fisheries Programme of the Mekong River Commission , the  Inland Fisheries Research and Development Institute  and the  Fisheries Administration, Cambodia  for making available the Dai fishery datasets used in this study. We would like to thank  Phen Chheng ,  Pengby Ngor ,  Loeung Deap ,  Phalla Tan ,  Yuthy Sar  and numerous data collectors and supervisors contributing to the Dai fishery data collection and database management. Finally, great appreciation is extended to the  Laboratory of Evolution and Biological Diversity (EDB)  supported by ' Investissement d' Avenir' grants (CEBA, ref.