dataesr/scientific-paragraphs-categorization huggingface dataset:
The availability of data on the feeding habits of species of conservation value may be of great importance to develop analyses for both scientific and management purposes. Stomach flushing is a harmless technique that allowed us to collect extensive data on the feeding habits of six Hydromantes species. Here, we present two datasets originating from a three-year study performed in multiple seasons (spring and autumn) on 19 different populations of cave salamanders. The first dataset contains data of the stomach content of 1,250 salamanders, where 6,010 items were recognized; the second one reports the size of the intact prey items found in the stomachs. These datasets integrate considerably data already available on the diet of the European plethodontid salamanders, being also of potential use for large scale metaanalyses on amphibian diet.
Moreover, seasonality may produce food resource fluctuations, forcing species to adapt their feeding habits to the available ones  29, 30. Finally, individual diet can be affected by the presence of competitors  [31] [32] [33]. The availability of exhaustive data on the different species diet may be of fundamental importance for ecological and zoological researches in order to define species patterns and strategies. In the present work, we report a large dataset on the diet of six European Hydromantes species (H. flavus, H. supramontis, H. imperialis, H. sarrabusensis, H. genei and H. ambrosii), considering different seasons and numerous populations. For most of these species, as mentioned above, no data on the diet and feeding behavior are available. During a three-year survey, we analysed the stomach contents of different salamanders populations, sampling individuals from underground environments.
Experimental design We adopted the following methodology to collect the data of the two datasets (Data Citation 1): 1. We sampled at least 3 populations per species, for a total of 19 different underground sites (i. e. , caves) (Fig. 1 ). 2. Multiple sampling was repeated from 2015 to 2017. 3. Sampling was performed in different seasons: May/June 2016 and 2017 (beginning of the hot season; hereafter spring) and early September 2015 and 2016 (end of the hot season; hereafter autumn). In these periods, salamanders intensify their foraging activity in-and outside the caves  10, 11  for both, the upcoming aestivation and to recover after the summer inactivity period 2. 4. For each population, we performed a minimum of 3 samplings, in different years and seasons. 5. We sampled at least 170 individuals per species.
Stomach contents analysis Stomach contents were examined in the lab using an optical microscope. Prey items were recognised (when possible) at the order level, with the exception of the Staphylinidae (among Coleoptera) and Formicidae (among Hymenoptera) which were considered separately because of their peculiar ecology along with easy morphological identification; the general works of Sabelli and Chinery  35, 36  were taken as guiding references for the identification of the different consumed prey items. In some cases, it was also possible to distinguish arthropods' at their different stages of development (for more information see Data Records). We defined three different categories of "stomach content": "empty", without prey; "notidentifiable", when the advanced stage of digestion prevented any identification to at least the order level; "full", when at least one prey item was recognizable.
33 ± 10. 35 individuals per species), divided in a) 319 individuals with empty stomach (average ± SD per species; 53. 17 ± 38. 93), b) 370 with non-recognizable contents (61. 67 ± 39. 93) and c) 561 individuals with full stomach (93. 5 ± 48. 74). Given that each population was sampled up to 4 times, and individuals were not marked, each individual could be present more than once in the dataset. 2. 5,996 recognized invertebrate prey items (average ± ES per individual, 10. 69 ± 0. 70) belonging to 40  different taxa (Pulmonata, Sarcoptiformes, Mesostigmata, Trombidiformes, Araneae, Pseudoscorpiones, Opiliones, Lithobiomorpha, Geophilomorpha, Scolopendromorpha, Julida, Polydesmida, Isopoda, Symphypleona, Poduromorpha, Entomobryomorpha, Zygentoma, Ephemeroptera, Odona-ta_ninfa, Orthoptera, Blattodea, Psocoptera, Hemiptera, Endopterygota_larva, Hymenoptera, Hymenoptera_Formicidae, Coleoptera, Coleoptera_Staphylinidae, Coleoptera_larva, Neuroptera, Trichoptera_larva, Lepidoptera, Lepidoptera_larva, Diptera, Diptera_larva, Archaeognatha, Tricladida, Gordea, Nematoda, Haplotaxida).
3. 10 recognized Vertebrate's prey items: 6 skin residuals, 3 eggs and 1 Hydromantes juvenile (Fig. 2b-d ). 4. NA means no specific data existing. SVL and position were not always recorded; in case of empty stomachs, NA was added to all other columns; if contents were not identifiable, NA was added to all prey typologies. Detailed explanation of dataset "Data on the diet of Hydromantes salamanders" (Data Citation 1) is given in Table  1. The second dataset ("Measures of intact prey items", Data Citation 1) consists of: 1. 352 intact invertebrate prey items measured. Detailed explanation of dataset "Measures of intact prey items" (Data Citation 1) is given in Table  2. Column Data description Typology of data.
Technical Validation Sites were surveyed once per season to avoid individual resampling. During each season, all surveys were performed within 30 days to limit variation of climate conditions, which can in turn affect prey composition. Considering differences in environmental conditions characterizing the studied sites, populations could show different phenology; indeed, during our surveys, within the same period in some cases we observed high population densities while in others no individuals were observed. Surveys on multiple years and season were performed to avoid biased data collection  37. Blinded stomach contents analyses were performed to further reduce any possible bias  38.
16S rRNA gene sequence-based identification of strain Marseille P4006 exhibited a 98. 1% sequence similarity with Lactobacillus farraginis strain JCM8627 (GenBank accession no. AB690214. 1), the phylogenetically closest species with standing in nomenclature (Fig. 1 ). Created in 1901 by Beijerinck, the genus Lactobacillus contains 222 other species isolated in plants and human that are facultative anaerobic or anaerobic bacteria. Lactobacillus farraginis, the phylogenetically closest validated species of strain P4006, was first isolated in 2007 from distilled shochu residue (shochu is a Japanese spirit made from rice, sweet potato, barley or other starchy materials) but was never isolated from humans  [4]. Because the 16S rRNA gene sequence was in the range of 98. 7% to define a new species  [5] , strain Marseille P4006 was considered as a new species within the Lactobacillus genus in the Lactobacillaceae family.
statistical analysis All assays were set up in triplicate and the results were expressed as the mean ± SD of data obtained from three separate experiments. Student's t-test was applied to compare two normally distributed groups and Bonferroni to perform multiple comparisons. P,0. 05 was considered statistically significant. All statistical analyses were evaluated using Statistical Package for the Social Sciences (SPSS) 13. 0 software (SPSS Inc. , Chicago, IL, USA).
δ(ω) + B 1 (Q). S Glob inc (Q, ω) ⊗ S HJ inc (Q, ω) + B 2 (Q). S Con f inc (Q, ω) (50) where B 0 (Q), B 1 (Q) and B 2 (Q) are respectively the intensities of the elastic peak, a narrow and a broad quasi-elastic contribution. It is important to note that by fitting the QENS data with Eq. 50, we impose the time (or equivalently the energy) dependence of the quasi-elastic signal (i. e. the shape of the contributions), but their relative intensities are free parameters. For each Q value, from B 0 (Q), B 1 (Q) and B 2 (Q) we can derive A 0 (Q) and A 1 (Q), the form factors of the conformational changes and of the extension of the HJ motion (Fig. 19 ). We find the Q dependencies of the three correlation times of the model τ 0 , τ 1 and τ 2 , to be respectively consistent with Q 0 , Q -2 and Q -4 power laws (Fig.
The NSE data of the bulk and confined polymer (Fig. 25 ) follow the model Eq. 56. A fit of the I Chain (Q, t) data set provides a very precise determination of both the temporal and structural parameters of Eq. 56. The description of the confined PEO data with the fitted parameters Wσ 4 = 1778 ± 63 Å 4 ns -1 and d Rep = 67 ± 3 Å is very satisfactory (Fig. 25 ). The same data treatment applied to the bulk signal leads to Wσ 4 = 2066 ± 60 Å 4 ns -1 and d Rep = 65 ± 2 Å. Both the dynamics and the reptation diameter of the bulk and confined polymer are indistinguishable (Fig. 25 ). This conclusion is supported by several recent independent results obtained by quasi-elastic neutron scattering (NSE included)  [25, 36, 37]. We should nevertheless stress-out that quasi-elastic neutron scattering is sensitive to both translational and rotational fluctuations.
3 Å -1 region, the polarization of the bulk makes the I(Q, t) accessible, but the polarization of the confined sample is almost null. Altogether, the smallest Q EPJ Web of Conferences 188, 05001 (2018) https://doi. org/10. 1051/epjconf/201818805001 JDN 23 available where the sample dynamics is in the NSE time window and the polarization is not null for both the bulk and the confined polymer is 0. 62 Å -1. The corresponding data are shown on Fig. 22b.
If a local electronic patient record system is available, then a research alert will be placed on this stating that the participant has consented to be part of the IPED study to avoid inadvertent unauthorised co-enrolment with other research studies. If a participant allocated to the intervention arm gets an episode of palpitations or pre-syncope and is able to record an AliveCor Heart Monitor ECG during the episode, the participant will email the ECG recorded by the AliveCor app directly to the coordinating Edinburgh research team at a convenient time to the participant and to a secure nhs. net email address. This email includes a PDF attachment of the ECG tracing along with the participant's AliveCor app login (which will be their IPED study number -no identifiable participant data will leave the local site, only the participants email address and IPED study number will appear), time and date of recording, and ECG recording.
AliveCor collects non-sensitive usage data through a third-party service called Mixpanel. Participants will not be asked to send their ECGs to AliveCor directly for analysis. The Alive-Cor app rhythm analysis algorithm will automatically report any ECG recorded by the AliveCor app as Normal, Atrial Fibrillation or Unclassified. The duty Consultant Emergency Physician at the coordinating Edinburgh centre along with a trial team Emergency Physician will review the ECG and will contact the local study team to arrange follow-up if required. In cases of disagreement, the central cardiology team were contacted for further opinion. If specialist follow-up of the ECG tracing is not required then the local study team will write to the participant informing them of this (Patient ECG follow-up letter normal v2.
Data collection Participants will have a CRF completed during index hospitalisation, comprising demographic, historical and examination characteristics. An ECG will also be taken and stored. Participant contact details will also be confirmed including a telephone number and email address. Once a participant has been randomised, the baseline CRF will be sent to the local study team office. The information on the CRF will be entered into a specially designed password protected online accessed secure database (REDCAP; http://www. project-redcap. org), the server of which is held within the University of Edinburgh. No participant identifiable information will leave the recruiting NHS hospital or be entered onto RED-CAP. Participants will be identified on REDCAP by study number alone.
Reporting, publication and notification of results Ownership of the data arising from this study resides with the study team. On completion of the study, the study data will be analysed and tabulated, and a clinical study report will be prepared in accordance with ICH guidelines. The results of our research will be disseminated in the following ways: The clinical study report will be used for publication and presentation at scientific meetings. Investigators have the right to publish orally or in writing the results of the study.
The present dataset is a compilation of georeferenced occurrences of asteroids (Echinodermata: Asteroidea) in the Southern Ocean. Occurrence data south of 45°S latitude were mined from various sources together with information regarding the taxonomy, the sampling source and sampling sites when available. Records from 1872 to 2016 were thoroughly checked to ensure the quality of a dataset that reaches a total of 13,840 occurrences from 4,580 unique sampling events. Information regarding the reproductive strategy (brooders vs. broadcasters) of 63 species is also made available. This dataset represents the most exhaustive occurrence database on Antarctic and Sub-Antarctic asteroids.
g. , Register of Antarctic Marine Species, De Broyer and Danis 2010; Global Biodiversity Information Facility, http:// www. gbif. org; Ocean Biogeographic Information System http://www. iobis. org/; Van de Putte et al. 2015, http://www. biodiversity. aq). This extensive assessment was pursued by major improvements in methodologies and data analyses. Improvement of dataset completeness and resolution facilitates modelling approaches  (Gutt et al. 2012 ) that provide interesting tools to better understand distribution patterns in this poorly documented part of the world. Among benthic taxonomic groups, Asteroidea (Echinodermata) are well represented in the SO with 12% of the global species richness present in the region  (Mah and Blake 2012). Around 300 species  (Moreau et al. 2015)  were reported at all depths including some potential keystone species in benthic communities  (McClintock et al.
1988 (McClintock et al. , 2008)). As for many taxonomic groups, adaptations of invertebrates to the polar conditions of the SO environments have been widely reported  (Peck 2002 (Peck , 2016) )  and have led to unique biological traits and life-strategies as well as high levels of endemism in the region  (Chown et al. 2015). In particular, reproductive strategies are diversified in the SO with a distinction between brooding and broadcasting species  (Poulin et al. 2002; Pearse et al. 2009). In asteroids, the two distinct reproductive strategies strongly drive species distribution patterns and the biogeography of the class in the SO  (Moreau et al. 2017). The present dataset is a compilation of georeferenced occurrences, at species level, for the whole class Asteroidea in the SO. Records from 1872 to 2016 have been gathered from various open source databases.
Project description Project title: Antarctic and Sub-Antarctic Asteroidea database Personnel: Camille Moreau, Charlène Guillaumot, Quentin Jossart, Antonio Agüera, Guillaume Crokaert, Marc Eléaume, Thomas Saucède, Katrin Linse, Huw Griffiths, Chester Sands, David Barnes, Vladimir Laptikhovsky, Anna Jażdżewska, Jacek Siciński, Noémie Vasset, Lenaïg G. Hemery, Christopher Mah, Nadia Améziane, Stefano. Schiaparelli, Bruno Danis Funding: The work was supported by a "Fonds pour la formation à la Recherche dans l'Industrie et l'Agriculture" (FRIA) grants to C. Moreau. This is contribution no. 16 to the vERSO project (http://www. versoproject. be), funded by the Belgian Science Policy Office (BELSPO, contract n°BR/132/A1/vERSO). This is contribution to the IPEV programs n°1124 REVOLTA and n°1044 PROTEKER and to team SAMBA of the Biogeosciences laboratory.
Study area descriptions / descriptor: This study focuses on the Antarctic and Sub-Antarctic regions located at latitudes south of 45°S. The Southern Ocean is a vast region characterised by the paucity of its scientific data  (Griffiths 2010; Griffiths et al. 2011 ) and available collections are the compilation of several historical campaigns. The objective of this work is to integrate the most complete database of species occurrences for the class Asteroidea in the described geographic extent. Design description: The compilation of occurrence data of asteroid species over the extent of the SO was realised by gathering data available from various biodiversity information systems (OBIS, GBIF, biodiversity. aq, PANGAEA https://www. pangaea. de/) as well as published literature, including original manuscripts (e.
g. ,  Gutt et al. 2014; Moles et al. 2015) , data papers and cruise reports. Compiled occurrences were complemented with data from personal communications of unpublished works and museums registered collections. This extensive dataset was developed to describe distribution patterns in the SO as well as faunal affinities among 25 Antarctic and Sub-Antarctic bioregions (see  Moreau et al. 2017). Several analytical methods such as Bootstrap Spanning Network, non-metrical multidimensional scaling (nMDS) and clustering contributed to highlight the importance of the reproductive strategy on the contemporary observed distribution patterns. The importance of environmental parameters such as influence of Antarctic Circumpolar Current (ACC), the influence of the Polar Front (PF), the pres-ence of gyres or the geographic distance among locations has also been emphasised.
This dataset helped to better describe the different biogeographic patterns within asteroids, which are overall congruent with other taxa and differs according to species reproductive strategy. This suggests a differential influence of dispersal capabilities on species distribution patterns. Analyses at genus levels also revealed the underlying legacy of past oceanographic and geodynamic processes in present-day patterns such as the existence of a trans-Antarctic pathway that split the Antarctic continent into two entities in the past. The detailed results are available from  Moreau et al. (2017). Data description: Asteroids are common invertebrates of Antarctic benthic communities considering the relative high species richness of the group in the region with regards to the world total diversity  (Danis et al.
2014). They play a significant ecological role in Antarctic ecosystems, including in trophic networks (most species being predators)  (Dayton 1972; Lawrence 2013 ). The present dataset, that focuses on regions located at latitudes higher than 45°S, compiles 28 families out of the 39 known worldwide  (Mah 2017)  with 13,840 occurrences gathered from various sources. The time coverage of the collection starts in 1872 with the HMS Challenger expedition and ends in 2016 with sampled collected during the RRS James Clark Ross JR15005 SO-AntEco cruise. Associated to occurrence data, depth, relative position to the PF, taxonomic information and bioregion were implemented when available. Depth data were extracted from www. gebco. net. Information regarding the reproductive strategy (brooding or broadcasting) of 63 species out of the 299 described was included in the database.
Corresponding bioregions of the observed occurrences were specified following  Moreau et al. 2017. A significant part of the specimens is deposited in various institutions: e. g. , National Museum of Natural History (NMNH), Museum national d'Histoire naturelle (MNHN), Museo Nazionale dell'Antartide (MNA), Université Libre de Bruxelles (ULB), Museo Argentino de Ciencias Naturales (MACN), National Institute of Water and Atmospheric Research (NIWA). Quality control description: Data are available at species level. Nomenclature was thoroughly checked using the Taxon Match Tool implemented in the World Register of Marine Species (WoRMS Editorial Board 2016), to delete all potential discrepancies and update the taxonomy determination. All replicates originating from overlapping origins as well as errors regarding the georeferencing, species synonymy, or misspelling were removed.
General taxonomic coverage description The present dataset is the most exhaustive and up-to-date list of available occurrences for the class Asteroidea (Echinodermata), in the entire Southern Ocean. This collection provides information about the occurrence of 28 asteroid families, 118 genera, and 299 species. Occurrence distribution is illustrated on Figure  1. Species richness in the different regions of the SO was estimated based on 1° × 1° grid cell resolution (Figure  2A ). Maximum richness (55 species per cell) was found along the Western Antarctic Peninsula. High richness values were also reported in the Weddell Sea as well as in Sub-Antarctic Islands (Kerguelen, Crozet, Marion, and South Georgia Islands). Richness distribution needs to be interpreted carefully considering the patchy and uneven sampling effort of past oceanographic cruises carried out in the SO (Figure  2B ).
Acknowledgements This work was supported by a " Fonds pour la formation à la Recherche dans l'Industrie et l'Agriculture" (FRIA)  grants to  C. Moreau. C. Mah  was funded by  MNHN  invited researcher grants (2013, 2014, 2015, 2016). This is contribution no. 16  to the vERSO project (www. versoproject. be),funded by the  Belgian Science Policy Office (BELSPO , contract  n°BR/132/A1/vERSO ). This is contribution to the IPEV programs n°1124 RE-VOLTA and n°1044  PROTEKER  and to team SAMBA of the  Biogeosciences laboratory. We are grateful to the crew and participants of all the cruises and research programs involved in the capture of the samples included in this dataset: POKER 2, REVOLTA 1 & 2, CEAMARC,  JR144 ,  JR179 ,  JR230 ,  JR262 ,  JR275 ,  JR287 ,  JR15005. We also thank the following institutions:  California Academy of Sciences ,  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Shallow Marine Surveys Group, University of Lodz ,  Muséum national d'Histoire naturelle and University of Genoa ,  NIWA (National Institute of Water and Atmospheric Research) Invertebrate Collection.
2. 5. There is no simple closed form expression for the power spectrum of a diffused signal under varying diffusion lengths. We thus resort to a Monte Carlo procedure by simulating diffused white noise profiles on a 2 mm resolution, resampling them to the actual resolution of the observed profiles to include the effect of discrete sampling, adding measurement noise and then estimating the spectra on these surrogate data sets using the same method as for the observed profiles. The variance of the diffused white noise signal and the measurement noise are free Table  1. Summary of the drilling and snow-pit sites used in this study. For each site we list latitude, longitude and elevation a. s. l. and for each corresponding record its name, the analysed depth, sampling resolution, measured proxy and original data reference.
8 ). Data availability. The snow trench (T15) isotope data are available in the PANGAEA repository https://doi. org/10. 1594/PANGAEA. 876639 (Münch et al. , 2017b). The snow-pit and firn-core isotope data used are available in the PANGAEA repository https://doi. org/10. 1594/PANGAEA. 883787 (Laepple et al. , 2017). Demonstration of spurious peaks when testing against a white noise null hypothesis. Coloured lines show power spectra for three realisations of purely random firn profiles. The grey horizontal line shows the critical level (p = 0. 05) that has to be overcome to be locally significant against white noise. As the simulated firn profiles are subject to firn diffusion, and thus have a red power spectrum, they show random peaks higher than the critical level.