dataesr/scientific-paragraphs-categorization huggingface dataset:
nov. and Sc. portcrosana Marchán & Decäens sp. nov. and one specimen of Sc. gigas gigas, Sc. gigas mifuga Bouché, 1972 , Sc. gigas heraultensis Qiu & Bouché, 1998 , Sc. rhodana Bouché, 1972 and Sc. monspessulensis idica Bouché,1972  using the polymerase chain reaction (pCr), with primers and conditions described in pérez-Losada et al. (2009, 2015). PCR products were purified and sequenced by the C. A. C. T. I Genomics service (University of Vigo). DNA sequences obtained in this study (including the two new species and the above mentioned Scherotheca spp), as well as their associated meta-data and genBank accession numbers are all available in the public dataset "DS-EWSppCNp" on the BoLD bioinformatics platform (https://doi. org/10. 5883/DS-EWSppCNp). Sequences reported by  Domínguez et al.
(2015 , 2018 ), pérez-Losada et al. (2009 , 2011 , 2015 ), paoletti et al. (2016)  and  De Sosa et al. (2019) , including representatives from most of the Lumbricidae genera and two members of the closest families  (hormogastridae Vejdovsky, 1884 and Criodrilidae Michaelsen, 1900)  were downloaded from genBank and used as a reference dataset. Included species are shown in Appendix 1. Sequences were aligned with MAFFT ver. 7  (Katoh & Standley 2013)  with default settings and concatenated with BioEdit  (Hall 1999) , resulting in a matrix of 3348 bp. The best fitting evolutionary   1978). GTR+I+G was selected as best-fitting evolutionary model for COI, 28S and ND1, and hKY+I+g was selected for 16S. Maximum Likelihood analysis was performed with raxML-hpC ver. 8  (Stamatakis 2014)  as implemented in the CIprES Science gateway ver.
3. 3  (Miller et al. 2010) , using gTr+I+g for each data partition with 10 alternative runs and estimating the support for the resulting topologies by 1000 rapid bootstrap replicates. Bayesian Inference of the phylogeny was estimated with MrBayes ver. 3. 1. 2 (Ronquist & huelsenbeck 2003)  as implemented in the CIprES Science gateway ver. 3. 3. parameters were set to 50 million generations sampling every 5000 th generation (10 000 trees). Two independent runs with four chains each were performed and 20% of the trees were discarded as burn-in. The remaining trees were combined and summarized on a 50% majority-rule consensus tree. Clade support (Bootstrap and Posterior probability) values over 70% and 90% respectively were considered as high (see  Marchán et al. 2018; De Sosa et al. 2019). uncorrected average pairwise distances between the newly described species and their closest relatives for the molecular markers COI and 16S were calculated in MEgA X  (Kumar et al.
Acknowledgments This work was supported by the port-Cros National park (Contract #  17-032 -83400 pC ) and  Xunta de galicia. Consellería de Cultura, Educación e ordenación universitaria, Secretaría Xeral de universidades  under grant  ED431B 2019/038. We are particularly grateful to David geoffroy, pierre Lacosse,  Martine Couturier  and  Johann Cerisier  (port -Cros National park ) for their support, for allowing access to the study sites, and for their help during field sampling. We also thank  Marine Zwicke  for participating in the field work. DF was funded by a  Juan de La Cierva-Formación  grant ( FJCI-2017-32895 ) from the  Spanish Ministry of Sciences, Innovation and universities.
2015; pérez-Losada et al. 2015 Eisenia andrei Bouché, 1972 Domínguez et al. 2015; pérez-Losada et al. 2015 Eisenia balatonica pop, 1943 Domínguez et al. 2015; pérez-Losada et al. 2015 Eisenia fétida Savigny, 1826 Domínguez et al. 2015; pérez-Losada et al. 2015 Eisenia lucens Vaga, 1857 Domínguez et al. 2015; pérez-Losada et al. 2015 Eiseniella tetraedra Savigny, 1826 Domínguez et al. 2015; pérez-Losada et al. 2015Appendix 1 (continued on next page). Species included in the reference dataset.
Experiment. Participants. Nine participants (7 Females, Mean Age = 27. 3, SD = 5. 14) have been recruited from the Laboratoire de Psychologie cognitive et de Psycholinguistique's database (LSCP, DEC, ENS-EHESS-CNRS, PSL, Paris, France). Every subject had normal or corrected-to-normal vision. The participants performed three sessions on three distinct days in the same week for a total duration of about 2 h15. Three participants were excluded. Two of the excluded participants did not complete correctly the experiment and one exhibited substantially asymmetric performance (98% of correct responses for an angle of 0. 2, but 18% at -0. 2 degree). As a result, we analyzed data from 6 participants. Ethics statement. The experiment followed the ethics requirements of the Declaration of Helsinki (2008) and has been approved by the local Ethics Committee (Comité de Protection des Personnes, Ile-de-France VI, Paris, France).
We obtained written informed consent from every participant who received a compensation of 15 euros for their participation. Stimuli and tasks. The stimuli were generated using Matlab along with the Psychophysics Toolbox  69. They were displayed on a monitor at 57. 3 cm of the participants' head. The participants performed the experiment in a quiet and darkened experimental room. Their heads were stabilized thanks to a chin-rest. Trials began with the presentation of a black fixation point (duration = 200 ms). Then the stimulus for the primary decision task was presented, consisting in a circular grating (diameter = 4°, Tukey window, 2 cycles per degree, Michelson contrast = 89%, duration = 100 ms, phase randomly selected at each trial). The grating had eight possible orientations with respect to the vertical meridian, and participants were asked to categorize them as clockwise or anti-clockwise with respect to the vertical meridian by pressing the right-arrow or left-arrow.
Statistical analyses. We used RStudio with the package lme4  70  to perform a linear mixed effects analysis  53  of the history biases of the reaction times, on both the experimental and the numerical simulations data. To perform the comparison between the experimental data and the model results illustrated in Fig. 6 , we first transform the response times of each participant using the z-score  71. This normalization allows analyzing the participants all together. We compared the LMM model described in the main text, Eq. (  1 ), to other ones that do not include all the terms, using the ANOVA function (with the lme4 package  70  ) that performs model comparison based on the Akaike and Bayesian Information Criteria (AIC and BIC)  70. We find that the LMM from Eq. (  1 ) is preferable in all cases (see Supplementary Information Table  S4 ).
Acknowledgements We are grateful to  Laurent Bonnasse-Gahot  for useful discussions and suggestions. We thank  Pascal Mamassian ,  Vincent de Gardelle  and  Xiao-Jing Wang  for stimulating discussions. We thank  Isabelle Brunet  for her help in recruiting the participants and organizing the experimental sessions. We thank the anonymous referees for useful remarks. K. B. acknowledges a fellowship from the  ENS Paris-Saclay.
Other satellite missions primarily designed for terrestrial applications, such as Landsat-8 OLI and Sentinel-2 MSI, can also retrieve chlorophyll a and total suspended matter at even higher spatial resolutions (10-60 m;  Dörnhöfer & Oppelt, 2016). Earth observation of optical water quality, however, only observes the surface layer, so integration of remote sensing datasets with in situ water quality measures is essential, not only to validate surface measures, but also to get a full picture of the water column, particularly for observing impacts in deep lakes. Acquisition of highly resolved spatial data at timescales of 1-3 days across many lakes provides novel opportunities for comparative work. For example, satellite data could be used in a before-after-control-impact design to assess impacts of lakes inside and outside of storm paths.
| Collaboration as a way forward A unified effort by empiricists, theoreticians, modelers, limnologists, and watershed scientists will be required to develop and advance a synthetic framework of storm impacts on phytoplankton. Collaborative projects which make use of existing information and data, and advance new research, will play critical roles to advance our understanding of how storms impact lakes. With the advent of global networks (e. g. , GLEON, NETLAKE, GLOBOLAKES, SITES AquaNet, LakeMIP, ISIMIP, Aquacosm, AEMON, MANTEL), collaborative approaches make coordinated research activities across sites and methods possible. Increased willingness and demand to share data openly  (Hampton et al. , 2015) , accompanied by good data management  (Boland, Karczewski, & Tatonetti, 2017; Wilkinson et al.
ACK N OWLED G EM ENTS The idea to better study and understand the role of storms in limnology originated in the  Storm-Blitz Project within Global Lake Ecological Observatory Network (GLEON). The work was conducted as a part of the  Global Evaluation of the Impacts of Storms on freshwater Habitat and structure of phytoplankton Assemblages (GEISHA) Working Group  supported by the  John Wesley Powell Center for Analysis and Synthesis , funded by the  U. S. Geological Survey  ( G17AC00044 ), and the  Centre de Synthèse et d'Analyse sur la Biodiversité (CESAB)  of the  Fondation pour la recherche sur la Biodiversité  (FRB; www. fonda tionb iodiv ersite. fr). Other support was provided by the  Vermont Water Resources and Lake Studies Center  ( G16AP00087 ) and the  U. S. National Science Foundation  under  VT EPSCoR  ( OIA-1556770 ).
A  Fulbright Award  from the  U. S. Department of State  and the  Commission Franco-Américaine  and a visiting professorship award from  Université Savoie Mont Blanc , both with kind hospitality provided by the  Institut Nationale de la Recherche Agronomique (INRAE) at the Centre Alpin de Recherche sur les Réseaux Trophiques des Ecosystèmes Limniques (CARRTEL) , supported J. D. S. during the development and writing of this paper. L. C. and S. J. T. contributed their time through the  NERC -funded  GloboLakes  Project ( NE/ J024279/1 ). R. A. , N. J. , H. P. G. ,  L. N. D. S. D. , and H. L. W. were supported by the  MANTEL  project ( H2020-MSCA-ITN-2016 ). C. C. C. was supported by the  U. S. National Science Foundation  ( EF-1702506 ,  CNS-1737424 ,  ICER-1517823 ,  DEB-1753639 ). P. U. C.
Population Consecutive patients who were diagnosed with an acute mesenteric ischemia were retrospectively included at the University Hospital of Nice between January 2011 and February 2019. The patients were referred to the surgeons with the diagnoses of acute mesenteric ischemia in the emergency room or in the intensive care unit. The diagnosis of acute mesenteric ischemia was based on the association of clinical symptoms and biological and imaging analyses  (1). Patients without CT-scan images or diagnosed with a chronic mesenteric ischemia or an infectious colitis were excluded from this study. Clinical characteristics were collected and included demographic data and the presence of cardiovascular risk factors. Biological parameters at in-hospital admission were collected. The neutrophil to lymphocyte ratio (NLR) was calculated by dividing the absolute value of neutrophils to lymphocytes; the platelet to lymphocyte ratio by dividing the absolute value of platelets to lymphocytes (PLR).
Data Collection Clinical and procedural characteristics as well as biological parameters were collected using manual and electronic medical records (Clinicom®). The diagnostic code K. K55. 0 "Acute vascular disorders of intestine" was used to extract patients. Imaging data were recorded and extracted from the softwares Picture Archiving and Communication Systems (PACS) and Aquarius iNtuition Edition® version 4. 4. 8 (TeraRecon,Inc. San Mateo). Sarcopenia was assessed by the measurement of the cross-sectional area of the right and left psoas muscles (Total Psoas Area: TPA) on CT-scan images (Figure  1 ). The horizontal sections of the CT images were created by adjusting the sagittal and coronal sections using the software Aquarius. The TPA was measured at the level of the third lumbar vertebra using the software Aquarius® by 3 independent blinded operators.
Statistical analysis Categorical data were expressed as the number of patients and percentage and continuous variables were expressed as the median with interquartile range. Group differences were compared using Fisher's exact test for categorical data and Mann-Whitney test for continuous variables. Correlations were determined by Pearson's correlation coefficient. The reproducibility of TPA/H measurements were evaluated using a graphic analysis with the Bland-Altman plot. A P value <0. 05 was considered as significant. Statistical analyses were performed using GraphPad Prism® software (version 7. 00, La Jolla California USA).
Study design This qualitative study was based on individual, semi-structured in-depth interviews conducted with ten CL patients in Sidi Bouzid and Gafsa, Tunisia. It was part of a large international multicenter study reporting patient-preferred treatment outcomes, where our group was highly involved  [9, 12]. Although related, this Tunisian study therefore differs in its objectives, its analysis methodology, and therefore, its findings and implications, from Erber et al. (2020)  [12]. The data (transcripts and notes) obtained were analyzed independently, using a coding framework developed according to its specific aims and objectives, and a thematic analysis approach based on these coded data (further detailed in the section Data analysis).
Data collection Interviews were conducted by a female epidemiologist (AB) who was introduced to the study area and trained by the principal investigator (ABS), who has a thorough experience in the epidemiology and the control of CL in the local and international context. Additional training and guidance were provided by an experienced qualitative researcher (EP), and support by the research team for analysis. Interviews with duration of about one hour took place in the healthcare facility, except for one patient who was interviewed at home. All interviews were audio recorded and detailed notes taken before, during and after the interview. The interviews were conducted in Arabic, transcribed verbatim, and translated into English.
Data analysis After reading the transcripts twice, individual sections were initially organized into an appropriate coding framework using NVivo 1 11, which was subsequently modified to accommodate the data (Table  1 ). In a second step, themes (as described in Green & Thorogood and Ziebland & McPherson  [14, 15] ) were developed from the coded data by two trained researchers (AB and ACE). Printouts of transcript sections that were coded to relevant nodes were manually arranged into emerging key themes on a single sheet of paper, and consensus achieved through discussion. Patients' socio-demographic data were entered in Excel sheet and we calculated means and medians to analyze age and number of lesions and scars.
Acknowledgments We are particularly grateful to all the CL patients who have contributed so far to the study for their patience and their time. We thank  Dr A. Kidar Head  of the  Dermatology Unit,Hospital of Gafsa , and health care professionals of the  International Research and Training Center of Institut Pasteur in Sidi Bouzid, Tunisia. The present study was supported by grant ID number:  B403556  from the  Special Program for Research and Training in Tropical Diseases (TDR)  (www. who. int/tdr/en/).
With these techniques, it is not necessary to isolate each microorganism beforehand and analyze it individually, since the set of barcodes is amplified in one single reaction. The huge amount of DNA barcodes generated must then be analyzed by bioinformatic processing to clean, sort, cluster, and compare the amplified sequences with reference databases to finally produce an inventory of the biodiversity present in a sample, including pathogens. This non-targeted molecular technique may be used to identify a known forest pathogen, particularly a quarantine organism, by comparing its barcode with reference databases  (Aguayo et al. 2018; Bulman et al. 2018; Català et al. 2016; Chen et al. 2018 ). An additional advantage is that they also make it possible to identify an unknown pathogen, which does not match with any reference sequence in the databases.
Funding information This study was funded by  European Union 's  Horizon 2020 Research and Innovation Programme "HOlistic Management of Emerging forest pests and Diseases" (HOMED)  (grant no. 771271 ). ANSES Plant Health Laboratory  is supported by a grant overseen by the  French National Research Agency (ANR)  as part of the  Investissements d'Avenir programme  ( ANR-11-LABX-0002-01 ,  Laboratory of Excellence ARBRE ). Compliance with ethical standards.
The Mediterranean Large Elasmobranchs Monitoring (MEDLEM) database contains more than 3,000 records (with more than 4,000 individuals) of large elasmobranch species from 21 different countries around the Mediterranean and Black seas, observed from 1666 to 2017. The principal species included in the archive are the devil ray (1,868 individuals), the basking shark (935 individuals), the blue shark (622 individuals), and the great white shark (342 individuals). In the last decades, other species such as the thresher shark (187 individuals), the shortfin mako (180 individuals), and the spiny butterfly ray (138) were reported with increasing frequency. This was possibly due to increased public awareness on the conservation status of sharks, and the consequent development of new monitoring programs.
In this light, the MEDLEM database (Mediterranean Large Elasmobranchs Monitoring) aims at contributing to the improvement of knowledge on the presence, spatial distribution, and bycatch of large elasmobranch species present in the Mediterranean and Black seas. Hence, it may represent a useful tool for national and international organisations involved in the biodiversity management and conservation of this important semi-enclosed basin (e. g. , the Food and Agriculture Organization/General Fisheries Commission for the Mediterranean (FAO-GFCM), the United Nations Environment Programme/Mediterranean Action Plan and IUCN SSC Shark Specialist Group, and the European Community Action Plan). In more detail, the main aims of the MEDLEM programme are (1) collecting information on bycatch, sighting, and stranding events throughout the Mediterranean and Black seas, (2) establishing a common protocol, and (3) recording their spatial occurrence  (Serena et al.
, 2014). As an additional goal, MEDLEM stores scientific papers related to elasmobranchs in the Mediterranean and Black seas as well as any reliable information from newspapers and social media. Established officially in 1985  (Mancusi & Serena, 2014) , it became fully operational in 2000, beginning to record data on elasmobranchs catches, sightings, strandings, and historical records within a single database  (Ben-Tuvia, 1971; Boero & Carli, 1979; Biagi, 1995; Megalofonou et al. , 2000; Lipej et al. , 2000; Bradaï et al. , 2002; Barrul & Mate, 2002; Soldo & Jardas, 2002a; Soldo & Jardas, 2002b; Morey & Massuti, 2003; Kabasakal, 2004; Morey et al. , 2006; Morey et al. , 2008; Ali & Saad, 2010; Kabasakal & De Maddalena, 2011; Kabasakal, 2013a; Kabasakal, 2013b; Carlucci et al. , 2014). The MEDLEM programme directly links up with the FAO IPOA-Sharks and it was submitted to the discussion of the SAC Sub-Committee on Marine Environment and Ecosystems (SCMEE) of the GFCM, Scientific Advisory Committee on Fisheries (SAC)  (Barcelona, 6-9 May 2002)  as "subproject Basking shark".
The MEDLEM database The main features of the MEDLEM Database Application are: (i) the implementation of data collection, especially for bycatch evaluation; (ii) the standardisation of data entry procedures; (iii) effective data sharing among the participating countries, and (iv) free access for participants to the web site. The database was initially created in Oracle. Recently, the application has been written with Apache/Perl technology, allowing interfaces to a MySQL database (version 3. 23. 58); a migration from MySQL to Oracle has been necessary using the technology Zope/Plone or Apache/PHP  (Serena et al. , 2006). The MEDLEM database is organised as shown in Table  1. The protocol characterises the word "large", which defines the nature of the database (Mediterranean Large Elasmobranchs Monitoring database).
This refers to the maximum size reached by each different species: we only consider sharks with more than 100 cm in total length (TL) and batoids with more than 150 cm in disc width (DW)  (Serena et al. , 2014). Applying this rule to our species in the Mediterranean and Black seas, we restricted for MEDLEM protocol the families listed in Table  2. Thanks to the collaboration of several research institutes, military authorities, and professional and recreational fishermen a great amount of valuable information on catches, sightings, and strandings of large cartilaginous fishes has been archived into the MEDLEM database. Furthermore, the database gathered significant observations derived from social media, particularly Facebook and YouTube, with some videos and images allowing species identification.
Thanks to the support of Facebook pages and citizen science platforms such as the "Mediterranean marine life" Facebook group, Shark-Pulse, the "Gruppo Ricercatori Italiani sugli Squali, razze e chimere (GRIS)", the SharksStudiesCenter, etc. , we have been able to obtain valid data. Currently all information is collected by the medlemcontact@gmail. com account or directly on the field. A data quality check is carried out on all newly received information. Unconfirmed information is discarded, and duplicated data is eliminated. The data collected allowed us to create records distribution maps for the most significant species, mad possible using a software called ModestR, which supports arranged databases in providing features to clean, manage, and analyse large species distribution datasets  (García-Roselló et al.
Results and Discussion The data recorded into the MEDLEM database and presented here refer to the period from 1666 to 2017. The archive contains a total of 4,963 specimens corresponding to 3,197 records, obtained from various research institutes belonging to 21 different countries. The higher number of records are mainly from Italy (2,248 records) followed by Palestine (1,084 records, almost entirely matching to exceptional M. mobular catches), Greece (301), Spain (286), Croatia (225), Turkey (159), Egypt (128), France (126), Syria (115), Malta (93), Tunisia (68), followed by the other countries (Fig. 1A ). The MEDLEM database includes 34 species and 2 categories (group of species) belonging to 16 different families and 7 orders (Tab. 2). The most frequent species reported is the devil ray (M.
comm. ). Other records in the database refer to less (I. oxyrinchus, G. altavela, A. vulpinus, H. griseus) or rarely observed species (Alopias superciliosus, Sphyrna zygaena, Squatina squatina, and Squatina oculata). Among the rarely sighted species, some observations can be considered as the first record of the species in the Mediterranean Sea: Sphyrna mokarran  (Boero & Carli, 1977)  and the recently well-documented first occurrence of Galeocerdo cuvier  (Tobuni et al. , 2016). Furthermore, some records reported the first observation of a species in national waters, such as Taeniurops grabatus in Italy and Syria  (Serena et al. , 1999a; Ali et al. , 2013)  and Himantura uarnak in Syria  (Ali et al. , 2010). The database also includes some questionable records of Sphyrna tudes. This species was initially described in the Mediterranean Sea by  Tortonese (1951)  and later confirmed by  McEachran & Séret (1987) , but needs confirmation.