dataesr/scientific-paragraphs-categorization huggingface dataset:
The recent rapid decline in snow accumulation rates could be related to increases in sea ice conditions in the eastern Ross Sea, perhaps marking the modern onset of local sea ice expansion. The modern decadal average  (2002) (2003) (2004) (2005) (2006) (2007) (2008) (2009) (2010) (2011) (2012)  of 20 cm w. e. a -1 lies within the 2σ variability in decadal RICE ice core snow accumulation rates (Fig. 7 ). Talos Dome records its maximum snow accumulation rates at the end of the 13th century and reduced snow accumulation during the Little Ice Age  (Stenni et al. , 2002). Until the 15th century, RICE and WDC snow accumulation and isotope data show an expected positive correlation between their respective isotope and snow accumulation records. Regionally, RICE and WDC isotope and snow accumulation are anti-phased.
Data availability The following new RICE data are made available in this paper: -RICE water stable isotopes (δD) have been archived at the PANGAEA data base: https://doi. org/10. 1594/PANGAEA. 880396 (Bertler et al. , 2017). -GPS and radar data have been archived at the U. S. Antarctic Program Data Center: https://gcmd. gsfc. nasa. gov/search/Metadata. do?entry= USAP-0944307&subset=GCMD  (Kingslake et al. , 2014; Matsuoka et al. , 2015). The following published RICE data used in this paper are accessible in the following way: -RICE17 age scale has been archived at the PANGAEA data base: https://doi. org/10. 1594/PANGAEA. 882202 (Winstrup and Vallelonga, 2017). -RICE snow accumulation data have been archived at the PANGAEA data base: https://doi. org/10. 1594/PANGAEA. 882202 (Winstrup and Vallelonga, 2017).
Sources of published ice core data used in this paper are as follows: -WDC water stable isotopes (δ 18 O) were accessed via https://www. nature. com/articles/nature12376# supplementary-information (WAIS Divide Project Members, 2013). -WDC snow accumulation data were accessed via http: //www. usap-dc. org/view/dataset/601004 (Fudge et al. , 2016). -WDC borehole temperature was accessed via https: //nsidc. org/data/NSIDC-0638/versions/1 (Orsi et al. , 2012). -Talos Dome snow accumulation data were accessed via https://www. ncdc. noaa. gov/paleo/study/22712 (Stenni et al. , 2002). -TALDICE water stable-isotope data (δ 18 O) were accessed via https://www1. ncdc. noaa. gov/pub/data/paleo/ pages2k/stenni2017antarctica/  (Stenni et al. , 2017). -Siple Dome water stable isotopes (δ 18 O) were accessed via https://www.
, 2015)  was accessed via http://www. esrl. noaa. gov/psd/data/timeseries/IPOTPI/. -NB2014 were accessed via http://polarmet. osu. edu/ datasets/Antarctic_recon/  (Nicolas and Bromwich, 2014). Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/cp-14-193-2018-supplement. Competing interests. The authors declare that they have no conflict of interest.
were accessed via the Byrd Polar Research Centre, Polar Meteorological Group, Ohio State University: http://www. polarmet. osu. edu/datasets/Byrd_recon/. -Meteorological data for Ferrell, Gill and Margaret AWS were accessed via the Antarctic Meteorological Research Center and Automatic Weather Station Project https://amrc. ssec. wisc. edu. -Data for McMurdo Station and Scott Base are accessed via the MET-READER: https://legacy. bas. ac. uk/ met/READER/data. html.
Acknowledgements. Funding for this project was provided by the  New Zealand Ministry of Business, Innovation, and Employment Grants through Victoria University of Wellington  ( RDF-VUW-1103 ,  15-VUW-131 ) and  GNS Science  ( 540GCT32 ,  540GCT12 ), and  Antarctica New Zealand  ( K049 ), the  US National Science Foundation (US NSF   ANT-0944021 ,  ANT-0944307 ,  ANT-1443472 ),  British Antarctic Survey Funding (BAS PSPE) , the  Center of Ice and Climate at the Niels Bohr Institute  through the  Carlsberg Foundation 's " North-South Climate Connection " project grant, and the  Major State Basic Research Development Program of China  (Grant No. 2013CBA01804 ). The authors appreciate the support of the  University of Wisconsin-Madison Automatic Weather Station Program  for the data set, data display and information (NSF grant number  ANT-1543305 ).
Model Calibration In this study, the SUFI-2 (sequential uncertainty fitting, ver. 2) algorithm  [64]  was used for calibration and sensitivity analysis for flow and sediment output. This program is currently linked to SWAT in the calibration package SWAT-CUP (SWAT calibration uncertainty procedures) (EAWAG, Zurich, Switzerland. ). The whole simulation was performed daily from January 2000 to December 2013 (excluding a three-year warm-up from 2000 to 2003). Stream flow was calibrated at a monthly time-step because of the lack of good observed daily data from January 2003 to August 2011, while sediments were calibrated at a daily time-step from January 2003 to December 2006 except for station A5, which was from January 2003 to December 2005. 150 simulations were performed for each gauging station by SWAT-CUP.
Acknowledgments: The authors thank the  National Agency of Hydrologic Resources (ANRH) Oran , the Algerian agency in charge of stream gauging, which provided all water flow and nitrate concentration data, especially  Sidi Mohammed Boudaliya  and  Belkacem Sardi. The  National Agency for Dams and Transfers (ANBT) Ain youcef-Tlemcen , which provided all the data on dam management, especially  Bensmaine. Ayoub Bouazzaoui , a PhD student at the  University of Tlemcen-Algeria , in the SVTU faculty, agroforestry department, for his help during the realization of soil map.
Data source and data extraction Physicians practising in Switzerland are required to submit a formal request to the FOPH for each patient they wish to treat with cannabinoids, either with commercially available synthetic THC (dronabinol solution with 2. 5% THC) or a tincture of Cannabis sativa prepared by a pharmacist containing 5% THC  [21]. The physician's request must document the diagnosis of a severe or potentially lifethreatening condition, address the benefit expected from THC treatment, and include the informed consent of the patient. We examined all requests for medical use of cannabinoids sent to the FOPH in 2013 and 2014. We developed, tested and revised a standardised data extraction sheet to extract data from the files of approved requests. We created unique identification (ID) numbers and extracted data on the type of exceptional licence granted, the patient, and the treating physician.
We extracted the duration of the licence, the year it was granted, and the payer for the therapy (out of pocket or insurance). At the level of the patient we collected the date of birth, sex, regional code, diagnosis and indication for THC use, and at the level of the physician the regional code of the surgery and the treating physician's specialisation. We double-entered the data into a dedicated database in Epidata  [22]  and resolved discrepant data entries.
Statistical methods We used descriptive statistics (numbers and percentages) to present results of the requests and the characteristics of patients granted exceptional licences for therapeutic use of cannabinoids. Patient characteristics were taken from the first application for the same patient received in the years 2013 and 2014. We examined patient characteristics by the main symptoms pain and spasticity, and present detailed information on the underlying diagnoses reported for patients granted exceptional licenses for therapeutic use of cannabinoids. Finally, we calculated the rate of patients granted access per 100 000 residents by NUTS II region using the population statistics available from the European Union (Eurostat)  [26]. We used Stata software version 14. 1 (Stata Corporation, College Station, Texas, USA) for all analyses.
Results The FOPH received 1656 requests for initial exceptional licences and licence extensions to prescribe THC during 2013 and 2014. Eight requests from eight patients were rejected and 1648 licences and extensions for 1208 patients were approved. Requests were rejected for incompatibility with the law (for example, requests for "substitution therapy") or for administrative reasons. Fifteen patients were excluded because of missing data in key variables. Thus, during these two years, 1193 unique patients received exceptional licences for treatment with cannabinoids and were included in the analyses (fig. 1 ). During 2013, 542 patients were treated under the exceptional licencing programme, and in 2014 the number rose to 825, including some who continued treatment begun in 2013 or earlier.
This versatility led us to name the device UniveSlide. In this article we describe in detail how to construct and assemble the chamber, and we present two possible applications that illustrate its potentialities in terms of medium/high throughput 3D + time imaging, corresponding to two different 3D samples: alginate capsules  23, 32  filled with a mixture of two fluorescent cells lines, respectively labelled with GFP in the membranes and tdTomato in the nuclei and zebrafish fluorescent transgenic larva. These samples are easily placed in the UniveSlide device, can be imaged for hours, and generate datasets providing high quality images that permit individual cell tracking.
After having loaded the samples within the holes, the chamber can be placed on the stage of the microscope (g). tags (Fig. 3b ). Due to the tiny size of the letters there might be bubbles formed above, but despite of that, the tags are still visible. Second, we used a widefield-epifluorescence videomicroscope to perform overnight time-lapse acquisition (Fig. 3c ). In this case, the stage, which accommodates regular microscopy slides, is also equipped with an insert to control the atmosphere (temperature and gas controlled: 37 °C, 5% C0 2 , from Life Imaging Services, Switzerland). In a series of two different experiments, we imaged 50 individual capsules overnight repeatedly (Fig. 3d ). The axial stepping interval was 8 μ m for both cases. The first dataset (Fig. 3d  upper panels) was acquired with a time interval of 30 min and up to 80 μ m while the second dataset (Fig.
3d  lower panels) was acquired with a time interval of 2 hours and up to 150 μ m. Third, we used a laser scanning microscope ('confocal' , Fig. 3e ) to reach a sufficient optical sectioning amenable for 3D visualization and accurate cell tracking. An insert for controlled environment (37 °C, 5% C0 2 , from Tokai Hit; Japan) was added, and we were able to image typically 30-40 capsules within 45 minutes (28 time-steps, over 20 hours) through 200 μ m with z-sectioning of 5 μ m. (Fig. 3f ). Potentiality for refined 4D image analysis. We focused on the dataset collected by confocal microscopy to perform image analysis. In Fig. 4 , from all the fields of view collected with the same resolution of the whole UniverSlide, we selected three individual wells. For the sake of clarity, we provide composite images composed of a z-projection of the fluorescence channels overlapped with the median plane of the brightfield channel.
We believe that the UniverSlide helps to overcome these difficulties. We analysed the datasets obtained at high resolution in 4D (3D + time) with dedicated tools and extracted the trajectories of a sub-population of individual cells inside multicellular spheroids. We collected data for about 30 capsules within the same run and performed, as an example, tracking for 3 capsules. Tracking was achieved without any problem, and so far, the only limitation seems the microscopy technique itself, e. g. penetration of light and scanning time. This limitation could be eventually overcame with the use of multi-photon microscopy with excitation infrared light to achieve a deeper penetration of light in thick samples and less phototoxicity due to out-of-focus excitation), or light sheet microscopy which consists in rapid scanning of a sheet of light (either real or digitally scanned) to greatly increase scanning speed.
Material and Methods 3D printing and procedure for chamber parts production. Generalities. 3D printing encompasses a large variety of techniques. The chamber we describe in this article was designed to be printed with a low cost Digital Light Processing (DLP) 3D printer. The minimal specification to meet is a voxel resolution smaller than 125,000 μ m 3 (50 μ m in each dimension). The parts were designed and drawn with the Computer Assisted Drawing (CAD) software SolidWorks (Dassault System). The same program was used to generate the 3D renderings of the different parts (Fig. 1a , Supplemental Fig. S2a ) as well as for generating all the STL format files, which is the universal file format input for most of the 3D printers. We used the desktop format Micro Plus Hi-Re 3D printer (Envisiontech, CITY) that provides high resolution (Voxel: 25 μ m in z, 30 μ m in y and 40 μ m in x).
75, WD 1, PlanApo VC, Nikon). All of these scopes are equipped with computer controlled motorized stages (Nikon and Prior) that permit repetitive and reproducible scanning of all the wells within the chambers. All microscopes are equipped with the Nikon NIS Elements package software. Image analysis. The NIS software (Nikon) was used to export the acquired files into tiff format. Pre-processing, denoising, filtering and basic analysis were achieved with Fiji (https://fiji. sc/). 3D renderings were done with the USCF Chimera software (https://www. cgl. ucsf. edu/chimera/). Manual individual cell tracking was done with the standalone version of the MovIT software (http://bioemergences. eu/bioemergences/openworkflow-index. php and ref. 41) developed by the BioEmergences platform (https://bioemergences.
Acknowledgements This work has benefited from: the  BioEmergences platform  ( FBI ANR-10-INSB-04 ) for image analysis and visualization tools and  Nadine Peyriéras  for valuable discussions; the  CNRS/INRA platform AMAGEN (ANR & TEFOR -Investissement d'avenir -ANR-II-INBS-0014 ) for providing the zebrafish transgenic larva; the  Bordeaux Imaging Center  (a service unit of the  CNRS-INSERM and Bordeaux University , member of the national infrastructure France BioImaging) where the pilot experiments were conducted (not shown), and  Christel Poujol  for her technical assistance;  Basile Gurchenkov  ( IGBMC ) for fruitful discussions;  Philippe Teulat  for his technical assistance;  Pierre Bon  and  Laurent Cognet  for sharing equipment and advices;  Nelson Hélaine  for helping with kymographs quantification.
Imaging Acquisition Parameters. Imaging was performed using a 3 Tesla MR scanner (Achieva, Philips Healthcare ® , Best, The Netherlands) and a 32 channels phased array head coil. Anatomical scan of the whole brain was provided by a 3D fast T1-weighted gradient echo sequence with an inversion prepulse [Turbo field echo, time of repetition (TR) = 9 ms, time of echo (TE) = 4. 6, flip angle (FA) = 8°, 150 slices-thickness = 1 mm, field of view (FOV) = 220 × 197 mm 2 giving an in-plane resolution = 0. 81 × 0. 95 mm 2. The SENSE factor (parallel imaging) was set to 1. 5]. Blood oxygen level dependent (BOLD) fMRI data were acquired using a 2D single shot T2*-weighted gradient echo-planar imaging sequence (TR = 2250 ms, TE = 27 ms, FA = 85°, FOV = 220 × 220 mm 2 , scan resolution = 80 × 80, slice thickness = 3 mm with no interslice gap, and SENSE factor = 2.
5). Each volume comprised 41 axial slices acquired in ascending interleaved sequence. Recording comprised one 208-volume run (50 volumes per condition, interleaved by 2 volumes transition periods). Foam pads restrained the head during both the anatomical and functional MRIs. Data Analytic Approach. Preprocessing. Data analysis was performed using the BrainVoyager QX ® Version 2. 3. 1. (Brain Innovation, Maastricht, The Netherlands). The volumes were corrected to minimize effects of slice scan time correction (cubic spline interpolation) and head movements (3D motion correction with trilinear sinc interpolation) was applied. After correction, none of the data included in the study exceeded motion of 2 mm in any given axis or had spike-like motion of more than 1 mm in any direction during a given fMRI session.
Acknowledgements This research was supported by a  Postdoctoral Research Fellowship  from the  "Helaers Foundation -Research in Clinical Neuroscience " (awarded to AH), a  WBI World Excellence Grant  ( sub/2015/228106243177 ) from the " BIOWIN -Innovation in Life Sciences Cluster of Wallonia " (awarded to AH), a Fellowship from the " Foundation Vocatio for Scientific Vocation " (awarded to AH), and a Grant from the  "Belgium National Lottery " (awarded to JB & PM). PM is funded, as a research associate, by the  Belgian National Fund for Scientific Research (F. R. S. -FNRS). PdT is funded by the  "Fonds de Recherche Clinique" of the Université Catholique de Louvain. The authors are also thankful to  Céline Haegeman  and  Charlotte Coussement  for their help with data collection.
Finally, for each pair of populations, we computed the model-averaged support for their being identical, by summing the relative weights of all models in which the two populations were grouped. In this approach, we did not provide information on which populations belonged to different species, but rather sought to determine whether the information contained in the vertical distributions was sufficient to recover the number of different species and assign populations to the correct species. To represent differences between populations, we created a graph with populations as nodes and edge-weights equal to the relative support for grouping. We visualized this graph using a standard attraction-based layout (Gephi software, version 0. 9). For every population (including in the direct-development treatments), we determined whether the final vertical distribution was significantly nonsymmetrical around the central vial (position 0).
The solution was used as drinking water that was changed twice a week. Weights were monitored weekly. After initial training, basal locomotor performances for each mouse were recorded prior to pesticide exposure by performing 2 rotarod tests weekly: endurance (3 Â 5 minutes at 20 RPM) and acceleration (2 minutes at 4-40 RPM). The mean latency to fall was recorded and analyzed. At each end-point, mice were killed by 200 mL of pentobarbital (54. 7 mg/mL) i. p. injection. Intestines were collected from the distal stomach to the distal colon, opened and rinsed in a bath of 0. 1 M PBS, and then rolled in spiral shape directly within an inclusion cassette with the upper section at the center, using a method adapted from Moolenbeek et al  (27)  (Supplementary Data Fig. S1A ). Once postfixed for at least 48 hours in a buffered 10% formalin solution, samples were embedded in paraffin following a routine protocol.
IHC Detection of pSer129 a-Synuclein and GFAP in ENS Identification of the pSer129 a-syn (1/500 ab 51253, AbCam, Cambridge, UK) as a marker of a-synucleinopathy, and the detection of glial fibrillary acidic protein (GFAP) (1/ 500, ab7260, AbCam, Cambridge, UK) as a marker of a reactive gliosis in the ENS was accomplished by IHC. Importantly, if several antiphosphorylated a-synuclein antibodies successfully detect phosphorylated form in the CNS of mouse ([P-syn/81 A] [ab184674], [EP1536Y], and [ab 51253]), only one allows its detection in the ENS (ab 51253) (Supplemen tary Data Fig. S2 ). The IHC procedure applied was similar to that described previously  (26). Briefly, successive slides of gut sections were used to reveal each of the markers. Biotinylated secondary antibodies used at 1/200 (antiRabbit ref.
4010-05 and antimouse ref. 1010-05, Cliniscience, Nanterre, France), combined with avidin biotin complex (Vectastain ABC HRP Kit, Vector Laboratories, Burlingame, CA) and 3, 3 0 -diaminobenzidine peroxidase intensified with nickel (DAB Peroxidase (HRP) Substrate Kit, Vector Laboratories), revealed the specific staining that appeared as dark brown deposits (Supplementary Data Fig. S1C-E ). Finally, the histological organization of each tissue sample was visualized using aqueous hematoxylin staining. To characterize the type of enteric neurons that sustain pSer129 a-synuclein expression, a double-labeling experiment was conducted, as described previously  (28) , using either rabbit polyclonal anti tyrosine hydroxylase (TH) antibodies (1: 200, Abcam) or mouse monoclonal anticholine acetyltransfer-ase (ChAT) antibodies (1: 200, Chemicon, Temecula, CA).
The surrounding background for each image to be analyzed was subtracted systematically and automatically. Densities of phosphorylated a-syn and GFAP in the ENS of the jejunum were assessed using Morpho Strider software (Explora Nova, La Rochelle, France) by measuring the staining inside the region of interest (ROI), the ENS for the gut (Supplementary Data Fig. S1F-I ). The density of staining was calculated by the formula: Density of staining ¼ Surface stained by antibody of interest Surface of the ROI Â 100 Results are expressed as means of density of pSer129 a-syn or GFAP staining within the nervous plexus.
Limitations There are number of limitations of our methodology that should be mentioned. Primarily, our scope is limited to languages that our diverse range of authors speak. We did use search engines and site maps when searching for T&C documents, so while care was taken to retrieve the T&Cs documents of the banks studied, there were a number of banks which did not seem to publicly list their T&Cs. Furthermore, banks regularly update their T&Cs. Our research here presents a snapshot. We have made our dataset publicly available (see the final 'Discussion' section), as outdated T&Cs can be hard to retrieve. In the following section, we explore how individuals interpret and understand these differences.
Materials and Methods Samples and nucleic acid extraction. Plasma samples were obtained from 52 HIV-1-infected patients followed at the Department of Infectious Diseases of Toulouse University Hospital, France. Their HIV-1 tropism was determined during follow-up in accordance with French medical guidelines. The experimental protocol was approved by the Toulouse University Hospital. The patients gave their informed consent for virological studies. Plasmid clones of env obtained from HIV-1 subtype B primary isolates were used to determine the error rates of the deep sequencing systems. Artificial mixtures of X4 and R5 virus clones were used to assess the sensitivity and linearity of assays of minor CXCR4-using variant by these systems. CHS02 (GenBank accession no. DQ136867. 1, X4 phenotype) and CHS11 (GenBank accession no.
GS-Junior/Roche deep sequencing of the HIV-1 V3 env region. A 415-nucleotide long fragment encompassing the V3 env region was generated by nested PCR as previously described  9. The amplified PCR products were purified using Agencourt Ampure PCR purification beads (Beckman Coulter, Brea, CA) and quantified using a Quant-iT Picogreen dsDNA Assay Kit (Invitrogen) on a LightCycler 480 (Roche Diagnostics, Meylan, France). PCR amplicons were combined and clonally amplified on DNA capture beads in water-in-oil emulsion micro-reactors. A total of 500,000 DNA-enriched beads were deposited in the wells of a full GS Junior Titanium PicoTiterPlate device and pyrosequenced in both the forward and reverse directions. The sequences of the V3 env regions were first processed using GS Amplicon Variant Analyzer (AVA) software (Roche).
Genotypic prediction of HIV-1 coreceptor use. The sequence reads were aligned with the BaL consensus sequence (GenBank accession no. AY426110. 1) and processed using an in-house automated data cleaning strategy  9. Non-functional V3 sequences were discarded using biological filters and statistical filters were used to discard sequences with artifactual point mutations. As previously reported 9 , V3 sequences were considered to be non-functional if (i) they did no start and end with the cysteine required for the disulfide bond; (ii) they were not 32-38 amino-acids long; (iii) they contained a stop codon; (iv) they were not sufficiently like the V3 consensus at three typical motifs: a "CTRP"-like signature at the N-terminus, a "GPGR"-like signature at the hairpin crown, or a "QAHC"-like signature at the C-terminus with an identity of 0.