dataesr/scientific-paragraphs-categorization huggingface dataset:
Northern Lowlands Impact Crater Demographics and Mineral Occurrence Statistics We analyzed 2257 images with CRISM L-detector data using the noise-reduction method, covering the central peak, crater wall, crater floor, and/or ejecta blanket of 1045 impact craters in the northern lowlands. The diameters of these impact craters range from 1 to 220 km (Figure  5 ). Mineral detections, categorized into mafic and hydrated minerals, are widespread in the northern lowlands, though there is considerable spatial variability in occurrence not solely related to image availability (Figure  6 ). Here an occurrence is defined as a geologic feature associated with a crater (e. g. , wall, ejecta, and central peak) with a specific mineral detection in an image; e. g. , several regions on the crater wall with the same mineralogy are documented as one occurrence, and each image may have more than one occurrence of each mineral, e.
Crater Modification Impact craters scattered throughout the northern lowlands have been modified due to erosion of crater rims and ejecta and infill of the crater floor, resulting in subdued crater forms with subtle rims, degraded or buried ejecta, and reduced depth to diameter ratios. Such processes mantle bedrock exposure and can prevent detection of the mineralogy of the impacted bedrock. Degradation state was assessed and recorded in a Mars crater database  [Robbins and Hynek, 2012]  as a quantized measure from class 1 to 4 ("1" being most degraded), depending on the sharpness and relief of crater rim, ejecta preservation, floor infilling, and relative depth/diameter ratio. We find that the ratio of detections for both mafic and hydrated minerals increases with the preservation state; i.
Multivariate Statistical Significance of Different Factors To understand the relative importance of the different factors that affect the mineral detections in the northern lowlands, we performed a multivariate statistical analysis on the mafic and hydrated detections as a function of crater size, dust index, and modification using a logistic function fit to evaluate the relative influence of each factor on the probability of detection. We evaluated the data for 487 (out of 1045) observations, filtered to remove craters with missing dust cover index or degradation state. We find that for both mafic and hydrated minerals, all of these factors are important to the identification of a mineral detection with a confidence level of 95%, which confirms that the final detection of a mafic or hydrated mineral is sensitive to dust cover and postimpact modification as well as crater diameter (Table  2 ).
Acknowledgments The data supporting the analysis and conclusions have been included in the supporting information, and the processing details will be provided upon request. This work has been fully supported by NASA Mars Data Analysis Program grant NNX12AJ43G. We would also like to thank the CRISM team for targeting and providing the data set, as well as internal reviews that helped shape the early stages of the manuscript. The author also appreciates help from Kelsey Logan in data processing and insights on the statistics of data from Shasha Tong and Qiong Zhang. This manuscript was improved by thoughtful and constructive reviews from Nicolas Mangold and an anonymous reviewer.
Recording Single-and multiunit extracellular neurophysiological data were recorded using the Multichannel Acquisition Processor (MAP; Plexon). After collecting data, during offline sorting we selected spike wave form features (principal components, peak amplitude, etc. ) that provided optimal separation using Offline Sorter software (Plexon; typically we used the principal components, but sometimes we used other features such as wave form peak or wave form energy). Single-unit quality was determined by separation of the unit from the noise in the 2-or 3-D feature space and the presence of a clear absolute and relative refractory period in the autocorrelogram for the putative unit.
Psychometric curve fitting For the aperture-width discrimination task in which 12 or 14 widths were presented, we fit the behavioral data to a Weibull function: a saturating exponential function with four free parameters. We used Matlab to fit our behavioral data, in the least squares sense, to the following: min ϩ (max Ϫmin)͓1 Ϫ e Ϫ ͩ x ͪ k ͔ , where min is the minimum value, max is the maximum value, k is the shape parameter, and is the scale pa-rameter. This is the standard Weibull curve modified to be constrained to have a minimum and maximum value (it typically varies between zero and one).
05 to be differentially expressed, as previously described  [32]. Microarray data from this article were deposited at Gene Expression Omnibus (http:// www. ncbi. nlm. nih. gov/geo/), accession no. GSE 74857) and at CATdb (http://urgv. evry. inra. fr/CATdb/; Project: ELIM1) according to the "Minimum Information About a Microarray Experiment" standards.
Acknowledgments This work was supported in part by the  ANR   Projects NoStressWall  ( ANR-12-ADAP-0011 ) and by the  BFF  project. We are grateful to  Kyoko Miwa  ( Hokkaido University, Japan ) for providing bor mutants and also to  Mathias Shuetz  ( University of British Columbia, Canada ) for reading the manuscript and providing corrections. We thank our colleagues at the chemistry platform ( Observatoire du Vegetal, Institut Jean-Pierre Bourgin, F-78026 374 Versailles Cedex France ) for allowing the use of the HPLC.
ESTIMATION OF ELASTIC PARAMETERS The elastic parameters of the object are estimated using the point cloud data on the basis of the deformations observed using an RGB-D sensor, and of the force measurements provided by a force sensor. Notice that this force sensor is used only for this preliminary step, and can be unmounted for the second step where, conversely, the estimation of the contact force is made using vision. Here we follow the data-driven approaches described in  (Frank et al. , 2010; Wang et al. , 2015). They consist in minimizing a fitting error between the simulated deformations, actuated by the input operator force provided by the sensor, and the deformations captured by the RGB-D sensor. These two methods also employ finite elements for the deformation model. The work  (Wang et al.
EXPERIMENTAL RESULTS The results presented here involve a deformable object, a stuffed toy undergoing a compression deformation effort applied by a tool fixed on the end-effector of a Kuka LWR arm, equipped with a force sensor at the wrist (see Fig. 2 ). The point clouds of the investigated scenes are acquired using a calibrated RGB-D camera Asus Xtion, 320×240 RGB and depth images being processed. For both the estimation of the elasticity parameters and the applied contact compression force, we process the data of a single RGB-D camera, taken at static equilibrium. To build the deformation model of the stuffed toy, a surface mesh of the undeformed object was reconstructed offline using an RGB-D based dense 3D reconstruction technique  (Newcombe et al. , 2011) , by flying around the object with the Xtion sensor.
The structure of different stereoisomers has been determined from coupling constant of selected hydrogens at the 1 H NMR spectrum according to the data reported in the literature. 15 Thus, the value of coupling constant of the hydrogens in position cis (J > 6 Hz) is always higher than that of hydrogens trans (J < 6 Hz). The 13DC reaction between nitrone 1 and alkene 2c processed with completely meta regioselectivity and leads to the formation of a mixture of two diastereoisomers (trans/cis) in a ratio of 80 : 20 (see Table  1 , entry 3). Note that the diastereoisomeric ratio was determined by integration of the corresponding 1 H NMR signals of the crude mixture spectrum. The two-dimensional NMR ( 1 H-1 H and 1 H-13 C) and HRMS analysis has been also used to conrm the structures of the obtained compounds.
The characterization data and spectroscopic detail for the nitrones 1 are given in ESI. † 4. 3. General procedure for the synthesis of isoxazolidines heterocycles 3a-e An equimolecular amount (1 mmol) of the alkene and the nitrone 1 was introduced on tube of a parallel reactor and dissolved in anhydrous toluene (5 ml) under argon atmosphere. The mixture was reuxed of the solvent with stirring. The reaction evolution was monitored by TLC. Aer completion of the reaction, the reaction mixture was then cooled to room temperature, evaporated of solvent under reduced pressure. The crude product was puried by column chromatography (silica gel) which afforded the corresponding isoxazolidines. The reported yields were determined based on the isolated pure products and in the case of the mixture, the relative proportions were determined from 1 H NMR spectrum.
The sections were incubated in 0. 3% H 2 O 2 in methanol at room temperature for 30 min to block endogenous peroxidase reaction. Subsequent to washing in PBS, sections were incubated with rabbit serum (Nichirei Biosciences Inc. , Tokyo, Japan) at room temperature for 20 min to block non-specific binding. The sections were then incubated overnight in a humid chamber at 4˚C with primary antibodies against ZNF-185 (dilution, 1:200; cat. no. HPA0004000; Sigma-Aldrich; Merck KGaA). Following three washes in PBS, the sections were incubated with a peroxidase-labeled polymer-conjugated rabbit anti-goat antibody (Histofine Simple Stain Max PO; dilution, ready-to-use; cat. no. 414162F; Nichirei Biosciences, Inc. ). The amplified immune products were visualized using the 3,3'-diaminobenzidine tetrahydrochloride reaction as described previously  (19).
By 24 hours after progesterone withdrawal, neutrophils comprised approximately 10% of the endometrial stroma. The human data presented in this report were plotted from individual patient samples, each meticulously characterised and selected to span the days preceding, during and following menstruation, i. e. during the luteo-follicular transition. The histological data were generated from 'full-thickness' endometrial biopsies retaining the myometrial-endometrial junction and uterine lumen architecture, thereby providing more reliable and complete measurements of apoptosis through the entirety of the endometrium than would otherwise have been achieved by other methods of endometrial sampling (e. g. 'Pipelle' tissue biopsies), where the spatial architecture may be lost. The RT-qPCR data were generated from endometrial biopsies collected from women with objectively verified 'normal' menstrual bleeding (i.
Expression was visualised with 3,3′-diaminobenzidine (DAB) chromogen, and Harris' haematoxylin counterstain. A well-established semi-quantitative histoscoring system  [48] [49] [50]  , calculated by multiplying a staining intensity grade of 0-3 (0, no staining; 1, weak staining; 2, moderate staining; 3, strong staining) by an estimation of the percentage of immunopositive tissue within different cellular compartments (to the nearest 10%), was employed, yielding a histoscore of 0-300. Each data point represented an average taken from at least three different tissue section histoscores. Cells of interest were counted by stereological microscopy: the area of tissue sections comprised by endometrium was manually delineated, and counting fields were selected automatically and randomly by the software.
Immunopositive cells were counted from each field manually, while total cell numbers were counted with the assistance of a macro written for the open-source image manipulation software ImageJ1 to allow discrimination of cell nuclei on the basis of colour thresholds and minimum/maximum size criteria. Manual user intervention permitted the elimination of false positives and inclusion of false negatives obtained through this method. Immunopositive cell counts were normalised to total cell nuclei. RNA isolation and RT-qPCR. Total RNA was extracted from endometrial tissues using commercially available RNA extraction kits per the manufacturer's instructions, with additional DNA digestion treatment of samples with DNase I. RNA concentrations were quantified and purities were verified by means of a spectrophotometer, after which RNA was reverse transcribed using commercially available kits (Invitrogen SuperScript Vilo cDNA synthesis kit (#11754-250; Life Technologies Ltd, Paisley, UK).
TaqMan-based RT-qPCR was performed using TaqMan Supermix (Thermo Fisher Scientific, Perth, UK), with three technical replicates. The data were normalised to internal housekeeping controls (ATP5B, human endometrium; Actb, mouse endometrium) which were validated prior to conducting the experiments. Data were analysed and processed with Sequence Detection System v2. 3 software (Applied Biosystems, Foster City, USA).
Statistical analyses. Standard errors for cell counting were calculated according to the equation, =. All other statistical analyses were performed with GraphPad PRISM software (v6. 0; GraphPad Software Inc. , San Diego, CA). Data were analysed using 1-way ANOVA methods with Tukey's or Dunnett's multiple comparisons tests, and represented as the means ± SEM, where p < 0. 05 was considered significant. Data Availability. The datasets generated and analysed during this study are included in this published article (and its Supplementary Information files), and are available from the corresponding author on reasonable request.
Acknowledgements We are grateful to  Sheila Milne  for assistance with manuscript preparation,  Ronnie Grant  for assistance with figure preparation and our clinical research nurses,  Catherine Murray  and  Sharon McPherson  for help with patient recruitment. This work was undertaken in the  MRC Centre for Reproductive Health  which is funded by  MRC Centre  Grant  G1002033  and  MR/N022556/1 ; also in part funded by  MRC Research Grants :  G0600048  and  G0500047  (HODC);  Wellcome Trust   100646/Z/12/Z  (J. A. M. ).
Smartphone scanner application To our knowledge, smartphone scanners have not yet been used for imaging root system growth. We took images using a scanning application on a smartphone (CamScanner INTSIG Information Co. , Ltd, Shanghai, China) (version 3. 9. 5). The CamScanner application automatically detects object borders and removes background noise using image-processing technologies. This software adjusts image details, brightness and contrast and can return processed data in a JPG or PDF format. We also compared several generations of smartphone (iphone6, iphone4, and CAT ® S40) to compare the performance of the smartphone technology. To use the application on a rhizotron in the field, the smartphone must be held at a given distance (68 cm in our case) and a fixed scale (tape measure) must be scanned simultaneously to calibrate the scan (Fig.
Comparison of methods Test 1: previously scanned and measured root systems To allow for a fully comprehensive comparison of data between scanning, manual and automated methods, we tested each method on previously scanned and measured root system (n = 35), and likewise on a measuring tape placed in different positions (Fig. 3 ) of known dimensions in a rhizotron (50 × 50 cm). The scanned root systems were measured using four methods: flatbed scanner, handheld scanner, smartphone scanners and the timelapse camera. Data were imported to the SmartRoot software.
Image analysis Once images of root growth had been acquired, we conducted analyses of images using the semi-automated SmartRoot software  [36]. SmartRoot is an operating system independent freeware based on ImageJ and uses cross-platform standards (RSML, SQL, and Java) for communication with data analysis softwares  [36, 40]. Before analyzing roots with SmartRoot, when necessary, images need "stitching" together (e. g. with Adobe Photoshop CS3 software), if several have been taken (when the rhizotron surface area was greater than the field of the scanner). In our case, we transformed all images to 8 bit gray scale and then inverted them using ImageJ software so that roots were darker than the background of the image. The length and diameter of each root produced during one interval time (i.
Study sites We measured fine root growth in situ in two agroforests. One was located at Le Beil, Madic, in the Cantal region, France (45°22′7. 95″N, 2°28′1. 46″E) at an elevation of 530 m, hereafter termed 'continental' climate. The agroforest comprised three transplanted tree species: hybrid walnut (Juglans major (MJ209) × Juglans regia L. ), cherry (Prunus avium L. ), sycamore maple (Acer pseudoplatanus L. ) at 12 m × 8 m tree spacing and intercropped with permanent pasture (ovine or bovine pasture). All national guidelines and legislation were complied with when using these cultivars. Mean diameter at breast height (DBH) of all walnut trees at the site was 0. 20 ± 0. 02 m and mean height was 12. 09 ± 1. 30 m. Data are mean ± standard error. All trees were planted in 1994 at a density of 100 trees ha -1.
Acknowledgements Thanks are due to  François Pailler  and  Stéphane Fourtier  ( INRA ) for technical assistance, to  Camille Béral  ( Agroof  ) for help finding field sites, to  Jérôme Nespoulous  ( INRA ) for his help with field and laboratory work and to the farmers  M. Queuille  and  M. Becue  for letting us work in their agroforests.
With this objective, we generated and analyzed high-throughput transcriptome sequencing profiles from liver biopsies derived from different categories of HCV-infected and non-infected patients, prior to and during treatment. First, to unveil HCV-induced cell-autonomous effects and to separate them from IFN-induced changes in the transcriptome, we selected liver biopsies from CHC patients without hepatic ISG induction, and compared them with uninfected control biopsies. Second, we examined the transcriptomic changes associated with the endogenous activation of the IFN system in a subset of CHC patients. Finally, we analyzed the gene expression changes resulting from pegIFN-a/ribavirin treatment, by comparing transcriptome data from liver biopsies obtained before treatment and at different time points during the first week of therapy.
Expression patterns of interferon-stimulated genes define two classes of CHC patients Previous studies focusing on the response to interferon (IFN) treatment in chronic hepatitis C (CHC) revealed the existence of a subset of patients with high endogenous levels of interferon-stimulated genes (ISGs;  Sarasin-Filipowicz et al, 2008). This distinction between two categories of CHC patients is highly relevant when seeking to determine the molecular consequences of HCV infection in the human liver, which otherwise can be confounded by the endogenous activation of the IFN system. We thus analyzed the expression levels of ISGs in the examined CHC patients. To do this, we mined a previously published dataset of ISGs  (Dill et al, 2014)  and extracted a set of genes that are strongly up-regulated in the human liver upon pegIFN-a treatment, requiring a minimum expression fold change of 2 across all studied time points.
We thus obtained a set of 20 strong ISGs and we assessed their expression levels in 28 liver biopsies (including control noninfected samples, termed hereafter non-CHC) in our dataset  (Fig 1A, Dataset EV1). A hierarchical clustering approach applied on centered and scaled gene expression levels confirmed the existence of two main groups of patients  (Fig 1A). The first group, characterized by overall low-ISG transcript levels, comprised 21 samples, including all six non-CHC liver biopsies and 15 of the CHC samples. Importantly, no clear distinction was found between the non-CHC and the CHC samples in this group. The second group, consisting of seven CHC samples, displayed higher expression levels across the 20 analyzed ISGs  (Fig 1A). Importantly, we note that this separation between two groups of patients cannot be explained by the HCV genotype carried by the CHC patients, as all four genotypes were found in the seven patients with high-ISG levels  (Fig 1A).
Similarly, analysis of the inflammation and fibrosis METAVIR scores  (Bedossa & Poynard, 1996)   To verify that the clustering of CHC samples was not dependent on the set of genes used as markers, we performed a principal component analysis on 360 genes associated with Gene Ontology (GO) categories related to response to interferon (Materials and Methods). This analysis confirmed that our sample sub-classification is robust with respect to the choice of the ISG input dataset  (Appendix Fig S1).
5  (Fig 2A, Dataset EV2). With the same parameters, we discovered 14 long non-coding RNAs (Materials and Methods) and 43 genes with unclear classification (including pseudogenes and other classes of non-coding RNAs; Materials and Methods) that were robustly differentially expressed between the two sample categories (Fig  2A ). Most differentially expressed protein-coding genes were upregulated in the CHC low-ISG patients compared to controls, reaching a maximum fold change of 8. We next examined the protein-coding genes with the highest absolute fold change between the two groups of samples  (Fig 2B). The strongest up-regulated genes included genes typically expressed in immune system cells, including IGHG1, IGHG3, CD27, and CD5 (Fig  2B ). Genes specifically associated with defense against viral infections, such as OASL, were also strongly up-regulated  (Fig 2B).
A gene ontology (GO) analysis for up-regulated protein-coding genes revealed strong enrichment for biological processes related to lymphocyte and leukocyte activation, including more specific terms such as T-cell and B-cell activation (Dataset EV3). In contrast, down-regulated genes were enriched for processes related to the protein activation cascade, response to stimulus or complement activation, although these patterns were driven by only a few genes (Dataset EV3). We then analyzed the expression patterns of these genes in the broad collection of human tissue transcriptomes of the GTEx consortium  (Mele et al, 2015). In agreement with the GO association with immune system cells, up-regulated genes were most highly expressed in the whole blood, in the lymphocytes, or in the spleen  (Fig 2C) , while down-regulated genes generally reached maximum expression in the liver or in adipose tissue  (Fig 2C).
However, we also found that miR-122 targets have comparable expression fold changes with the targets of other highly expressed miRNAs, such as. Similar conclusions were reached when analyzing a set of miRNA targets identified in Huh7 cells using highthroughput sequencing of RNA isolated by crosslinking immunoprecipitation  (Luna et al, 2015; Appendix Fig S2B, Dataset EV4). Overall, the fold expression change was positively correlated with the number of distinct miRNA families that are predicted to target each gene  (Appendix Fig S2C). This observation cannot be simply explained by the previously reported sequestration of miR-122 by HCV, but may reflect the expression or functional characteristics of genes targeted by multiple miRNA families. Our results thus reveal a potential confounding factor in the up-regulation of miR-122 targets following HCV infection.
Gene expression patterns associated with endogenous IFN system activation We next investigated the gene expression changes driven by the combined effect of HCV infection and endogenous IFN system activation. To do this, we contrasted gene expression levels between non-CHC and CHC high-ISG samples (Materials and Methods). Using the same parameters as above, we observed numerous differentially expressed genes in the high-ISG patients, including 503 protein-coding genes, 80 candidate long non-coding RNAs, and 125 other genes  (Fig 3A, Dataset EV2). The observed expression fold changes and significance levels spanned a wider range than for the comparison between non-CHC and CHC low-ISG patients  (Figs 2A and 3A). As expected, the most highly up-regulated protein-coding genes were known ISGs, including LAMP3, IFI27, and RSAD2 (Fig  3B ).