dataesr/scientific-paragraphs-categorization huggingface dataset:
Introduction The discrete element method (DEM) has become the de facto standard to simulate particulate materials for which the discrete nature of particles and importance of quantifying particle-scale effects cannot be neglected. Consequently, the need for large scale discrete element simulations that can quantify the effect of particle-scale changes on the macro-scale response is becoming increasingly more important in industrial bulk material handling applications, where computational efficient continuum models fail to give reliable predictions  [1]. Established discrete element software frameworks rely mostly on multi-core central processing unit (CPUs) computing platforms  [2]. This is exemplified by the number of commercial and open-source discrete element codes that include PFC by Itasca , EDEM by DEM Solutions, Star-CCM+ by CDAdapco, MecuryDPM by the Univeristy of Twente, BLOCKS3D by the University of Illinois, Y-DEM by Queen Mary University, Millsoft  [3]  by the University of Utah , LIGGGHTS by Johannes Kepler University in Linz, ELLIPSE3H by New Mexico University, YADE by Grenoble University and SAMADII/DEM by MetaRiver Technology.
BlazeDEM3D-GPU BlazeDEM3D-GPU that has been demonstrated to simulate (i) tens of millions of mono-disperse spherical particles and (ii) millions of mono-disperse polyhedral particles within a realistic time frame on a desktop computer using a single or multiple GPUs  [6] [13]  [14]. BlazeDEM3D-GPU is developed for NVIDIA graphics cards using the available CUDA programming framework  [15] , allowing for a wide variety of GPU cards to be considered. BlazeDEM3D-GPU  [13]  has been extensively validated in the simulation of tumbling mills  [14]  and hoppers  [16]. BlazeDEM3D-GPU was designed for the GPU hence the code design is similar to a dynamics engine, so the user is free to build a complex simulation using the various objects provided. This is in contrast to the fixed simulation types offered by commercial codes like Rocky and EDEM, where you can only do a "single" simulation eg ball mills, chutes, hoppers etc as standalone simulations.
Note that any number of vertices can make up a surface provided they are coplanar. While a single surface can still be represented by  a collection of smaller surfaces/triangles we use geometric primitives which we term "macro objects" for higher order surfaces such as cylinders which results in significantly reduced memory storage and computational cost. This approach of minimalistic world geometry representation is now also used in the CPU based open-source code MecuryDPM for spherical particles. The BlazeDEM3D-GPU framework is well documented in  [6, 13, 14]  and is freely available under the modified BSD-3 license  [5].
The difference in response between the 2D and 3D models is evident resulting in an underestimation of the power draw for the simplified 2D model. We obtained a good match with an error of only 5 % for the power draw for the two 3D models further demonstrating the predictive capability of GPU DEM. The simulations in this paper were done using the BlazeDEM3D-GPU code developed by the authors on a   commodity NVIDIA GTX 980Ti graphics card. We required seven hours of wall-time and (900 MB of GPU memory) for a one second simulation time of over a million polyhedral shaped particles in a tightly packed state (before discharge) compared to 18 months using BLOCKS3D and 8. 5 days using an impulse-based DEM approach  [20]  while using a more accurate contact detection resolution. A simulation of over a million spherical particles required just 3 minutes of wall time (300 MB of GPU memory) for one second simulation time.
In order to build a multimodal nonlinear endomicroscope to image brain border during operation, our group is building an optical database on brain biopsy tissues analysis collected with excitation panning from deep UV to near infrared. This paper focuses on the results from deep UV excitation of endogenous fluorescence from glioblastoma and control human brain samples. The samples were imaged and spectrally analysed. The excitation wavelengths were tuned from 275 nm to 340 nm. Two promising indicators to discriminate tumorous tissue from the control were found. A preliminary correspondence between fluorescence images and histological H&E staining open a huge door to confirm results with a medical expertise.
The surgeons today follow the rule of maximum possible resection; stopping before touching any vital functional part of the brain  (Sanai and Berger, 2008). The aim of our project is to give new optical contrast and information on the tissue during the operation in order to identify this infiltrated region. To succeed in such project we are building a new endomicroscopic tool combining different imaging modalities to give the more precise answer to the surgeon. In parallel to the instrumental development, it was crucial to discriminate tissue nature in order to confirm the power of multimodal optical analysis. For that purpose, we are creating a database of optical signature from the different tumour tissue and their corresponding control using different optical contrast. This database will help to give a discriminatory answer on the nature of the tissue and to define different indicators.
This database groups different optical response: (i) fluorescence imaging, (ii) spectroscopy, (iii) lifetime fluorescence analysis and (iv) second harmonic generation imaging. These data were acquired using an excitation ranging from the deep UV to the near infrared. In this article we will focus on the results from the deep UV excitation of tissues. Under this excitation window we were able to make full field imaging and precise spectral measurements. Emission-collection matrixes of different endogenous molecules were measured and analysed. Some molecules of interest were spectrally followed using different excitation wavelength. Fluorescence images were compared to the hemotoxylin and eosin (H&E) staining standard of the Sainte-Anne hospital. Interesting structures were identified in optical images and matched finely with anatomopathologist diagnostic indicator.
Imaging and Spectroscopic Measurements The data have been acquired on the DISCO beamline at the Synchrotron SOLEIL. Two microscopic set-ups are available on the beamline and were used in this study. The samples are excited with the continuous emittance from the DISCO beamline bending magnet at 275nm and between 310 and 340 nm. First the samples were analysed under a full-field microscope (Zeiss Axio-observer Z-1) with a x40 glycerine immersion objective (Zeiss Ultrafluar, NA 0. 6). Emitted fluorescence was collected via a PIXIS 1024 BUV camera (Princeton, USA) through four bandpass filters: , with an integration time of 10s. This set-up is completely controlled by an open source microscopy software Micro-Manager  (Edelstein et al. , 2014). Spectral measurements were recorded with an inverted Olympus IX71 microscope stand with homemade DUV lenses.
Data Analysis Spectral data were acquired with the Labspec software, on each image a square of 12 by 12 points with 5 microns between each points was selected, a spectrum was acquired for every point with a 10s integration time. Preliminary treatments were applied to suppress noise and detector dead pixel using a Matlab script developed by the DISCO team. The treated data are then fitted with a homemade Matlab script. This script was already used and published in the visible  (Haidar et al. , 2015)  and near infrared range and readapted here for the deep UV spectral analysis. Four molecules fluorescence emission were fitted: Tyrosine, tryptophan, collagen and NADH. These molecules were chosen through a complete review of the literature and the expertise of the DISCO scientists  (Croce and Bottiroli, 2014; Jamme et al.
, 2003). In the figure1b, we can hint that the ratio between tryptophan and collagen change with the type of tissue. To precise the tryptophan-collagen ratio, for each type of tissue, we measured it in all the spectra recorded for the five samples. The results were then presented in a boxplot using the software R, the ratio was calculated from the max of emission obtained in the Matlab fit and rearranged in boxplot, see figure  2b. A significant difference appeared between the mean of the two boxplots, to confirm this hypothesis a Mann-Whitney analysis was performed on the ratio data. The hypothesis of identical groups, gave a p value of 3. 6. 10 -  which is lower than 5. 10 -2 and rejected the hypothesis. This statistical result gives more confidence to confirm that the collagen-tryptophan ratio can discriminate glioblastoma from control samples.
ACKNOWLEDGEMENTS This Work as a part of the  MEVO  and  IMOP project was supported by  " Plan Cancer" program  founded by  INSERM (France) , by  CNRS  with  "Défi instrumental" grant , and the  Institut National de Physique Nucléaire et de Physique des Particules  ( IN2P3 ). We would like to thank  Synchrotron SOLEIL  for beamtime under project # 20160206. Thanks also to PIMPA Platform partly funded by the  French program  " Investissement d'Avenir " run by the  "Agence Nationale pour la Recherche"  (grant " Infrastructure d'avenir en Biologie Santé - ANR -11-INBS-0006 ").
Thus, reduced expression of sortilin in NSCLC patients was correlated with increased cellular proliferation, accelerated tumor growth, and TTF-1-negative poorly differentiated tumors. Collectively, the phenotypes of sortilin-downregulated tumors were associated with an NSCLC subtype with poorer prognosis. In light of these results, we performed statistical analysis of publicly available adenocarcinoma data sets from the MSKCC cBioPortal database  47, 48  , based on The Cancer Genome Atlas 1 (TCGA) and the gene expression omnibus (GEO). We manually sorted datasets based on overall survival and expression of SORT1, the gene encoding sortilin. The Kaplan-Meier method was used to plot the overall survival of adenocarcinoma patients (n = 673) stratified by expression of SORT1, and statistical significance was assessed by log-rank test  49, 50.
All cell lines were maintained in Dulbecco's modified Eagle's medium GlutaMAX (Gibco) supplemented with 10% fetal bovine serum (IDbio), 1% non-essential amino acids (Gibco), and antibiotics (IDbio). All cells were cultured in a humidified incubator set at 5% CO 2 and 37 °C. Cells were cultured under serum Magnification ×50, insets ×200. e Kaplan-Meier curves of overall survival were constructed for the following groups of patients with high (black curve, n = 248) or low (orange curve, n = 425) SORT1 expression, using the online tool at kmplot. com. f In silico analysis of SORT1 expression in lung adenocarcinoma with high or low EGFR expression; data were obtained from the MSKCC cBioPortal for Cancer Genomics database or Genome Expression Omnibus. g Quantitative PCR analyses for SORT1 and EGFR expression in a cohort of patients (n = 20) with high or low EGFR expression.
h Kaplan-Meier curves showing the survival benefit provided by high-SORT1 expression (black curve, n = 32) relative to low SORT1 expression (orange curve, n = 30) on a subset patients with high-EGFR expression; data were obtained from the lung adenocarcinoma cohort in the MSKCC cBioPortal database (n = 522). i In silico analysis for SORT1 expression in lung adenocarcinoma with or without EGFR TKI-sensitive mutations, using data from the MSKCC cBioPortal for Cancer Genomics database or Genome Expression Omnibus. For Kaplan-Meier curves, the log-rank (Mantel-cox) is used test to determine the statistical significance of association sortilin high or low expression and overall survival within lung adenocarcinoma patients, *P < 0. 05 **P < 0. 01 ***P < 0. 001, Hazard Ratio (HR) is reported in time-to-event analysis.
Proliferation was assessed by flow cytometry on a FACS Calibur instrument (BD Biosciences), and the data were analyzed using the Cell Quest software (BD Biosciences). Each experiment was repeated at least three times. Expression of cell surface EGFR was monitored by flow cytometry on living cells without permeabilization. After washing in ice-cold PBS, cells were immunolabeled on ice for 10 min with APC-conjugated anti-EGFR (Biolegend, #BLE352906, 1/100, Ozyme) in PBS containing 2% BSA. After two further washes in ice-cold PBS containing 2% BSA and one wash in ice-cold PBS, cells were suspended in PBS and analyzed by flow cytometry on a FACS Calibur instrument; data were analyzed using the Cell Quest software. Measurements were compared to the isotopic control (APC-conjugated anti-mouse IgG1, Biolegend clone MOPC-21 #BLE400122, 1/100, Ozyme) to determine background and positivity thresholds.
Finally, the cells were mounted using Fluoroshield mounting media (Sigma) containing 4ʹ,6-diamidino-2-phenylindole (DAPI) to stain the nuclei. For endocytic assay, biotinylated EGF, complexed to Alexa Fluor 647, was used following manufacturer's instructions (Life Technologies, France, #E35351). Fluorescence images were obtained using epifluorescence microscopes (Zeiss Axiovert) equipped with a laser-scanning confocal imaging system (Zeiss LSM 510 META or LSM800). Mander's coefficients were calculated using the Zeiss LSM 510 META or ZEN software (Zeiss) on non-saturated pictures with an optical slice of 0. 8 µm. At least 30 cells were acquired for each condition. Cell surface expression of either EGFR or sortilin (calculated from the difference between the whole-cell and the intracellular means of fluorescence) were analyzed using the ImageJ software (ImageJ).
Following ligation, the cells were washed in buffer A, and then incubated for 100 min at 37 °C with the Duolink II orange amplification buffer containing polymerase. The cells were then washed three times in buffer B and mounted with in-situ mounting media containing DAPI. Quantitative analyses obtained from each independent sample were performed using the ImageJ software (NIH, Bethesda) based on the mean fluorescence values. At least 50 cells were acquired for each condition, and the results are presented as ratios relative to the control cells. Endosome/subcellular fractionation. Cells were washed with ice-cold PBS (pH 7. 4), rapidly swelled with osmotic buffer (10 mM Tris-HCl (Sigma), pH 7. 4), and scraped into homogenization buffer (10 mM Tris-HCl, pH 7. 4, 1 mM EGTA, 0. 5 mM, EDTA, 0.
For sortilin and EGFR labeling, samples were pretreated with ER1 for 5 min; for Ki-67 labeling, samples were pretreated for 20 min with ER2. Labeling was performed with the same device (Leica Bond-Max), and slides were mounted in a non-aqueous mounting medium. Images were acquired on a Hamamatsu slide scanner. Each image capture was visually quantified by the adapted Hirsh score method  64  , performed in a triple-blind manner. To evaluate the percentage of Ki-67-positive nuclei, the publicly available software Immunoratio 65 was used. Bioinformatic analyses. Overall survival and vital status were obtained using the Kaplan-Meier Plotter for lung cancer (kmplot), and computed as a function of sortilin expression using data extracted from GEO (n = 673 patients) data sets with accession numbers GSE14814, GSE19188, GSE29013, GSE30219, GSE31210, GSE3141, GSE31908, GSE37745, and GSE50081.
Acknowledgements This study was generously supported by  Chaire de Pneumologie Expérimentale from Association Limousine d'Aide aux Insuffisants Respiratoires-Assistance Ventilatoire à Domicile (ALAIR-AVD; Limoges, France) , the  Foundation of the University of Limoges , the  Comité d'Orientation de la Recherche sur le Cancer en Limousin  and the  Ligue Contre le Cancer. H. A. was supported by a doctoral fellowship from  ADER-LPC (Association du Développement Education Recherche-Limousin Poitou-Charentes). We are grateful to all of our colleagues have contributed their time and materials to this study. We thank  Aurélie Lacroix  and  Nicolas Vedrenne  for assistance with experiments on mice and human tissue samples. We are especially grateful to  Alain Chaunavel  for technical support from  "Centre de Ressources Biologiques Biolim," Department of Pathology, University Hospital Limoges , and  Claire Carrion  from the  Imaging Cytometry Platform of the University of Limoges.
Clinical data Baseline (i. e. the first visit to our institution) characteristics were recorded in the medical file at the time of the HRCT used to diagnose ILD and included the following: subtype of systemic sclerosis according to Leroy and Medsger  [15] , presence or history of digital ulcers (DU), arthralgia, synovitis, gastro-oesophageal reflux disease (GERD), New York Heart Association (NYHA) functional class and modified Rodnan skin score (mRSS). Disease durations were measured both from onset of Raynaud's phenomenon (RP) and onset of first non-RP symptom and time of HRCT.
Our study was not designed to study the role of immunosuppressants in the evolution of ILD. However, we assessed wether the use of immunosuppressant during follow-up was associated with any significant change in DLCO. We did not find an association between immunosuppressant use and the slope of DLCO during follow up. As the overall FVC curve was flat, we assessed the immunosuppressants use during follow up as a predictor of confirmed decline in FVC and found that it was a significant predictor. We interpret these data with caution as the study was not designed to assess the role of immunosuppressants in SSc-ILD. The higher risk of decline of FVC with the immunosuppressants use during follow up is probably explained because we usually start these treatments in worsening ILD. Our study has several limitations.
Spatial localization was achieved prior to the spectral acquisition via a LASER module, encompassing three pairs of 5 ms spatially-selective refocusing pulses  [64]. This localization was verified by imaging the voxel directly via a fast low-resolution T 2 -weighted sequence that incorporates a LASER module. Shimming was performed manually using up to 4 th order corrections, with ~30 Hz line widths typically observed on the voxel of interest. Line broadening factors equal to the line widths were applied upon processing the spectra, which were all analysed in magnitude mode to avoid phasing complications and/or the need to do scan-by-scan phase correction (Ligneul and  Valette, 2017). All this led to somewhat broader lines, of ca. 0. 07 ppm FWHHs. The importance of relying on the RE MRS sequence for these experiments was investigated by comparing its non-diffusion-weighted NAA/mI spectra, against counterparts arising from the scanner's built-in STEAM sequence after optimization and incorporation of VAPOR water suppression  [65].
Acquisition parameters were kept identical inasmuch as possible between both sequences (voxel size, voxel location, repetition time, etc) except for the TE, which for STEAM was also explored for potentially shorter values. Fig  3  shows representative results of these comparisons; clearly, the STEAM MRS executed for shorter TEs shows better sensitivity but also a much stronger residual water resonance than the longer TE counterpart-whose SNR would be simply too low for incorporating diffusion-weighting. Our STEAM's poor water suppression performance could likely be improved using outer-volume-suppression and further water suppression modules during the TE; however, RF limitations prevented us from implementing the latter, and so this was not implemented in this study. The RE-MRS trace possesses a flatter baseline than the short-TE STEAM counterpart at the mI resonance position (an essential feature for quantifying diffusion-driven modulations in these long acquisitions) but also a superior SNR: %1.
The ensuing DDE amplitude modulations E(ψ) = S(ψ)/S(q = 0), where S(ψ) describes the signal as function of the relative angle between the gradients and E(ψ) is the relaxation-normalized angular variation, were then compared against a library of signals calculated in MISST  [66] [67] [68] , which include a range of parametric signals. In particular, we used MISST to simulate the signals arising from infinite cylinders; this particular model was chosen after initial tests with finite cylinder models were seen to provide similar results. Diameters were varied between 0. 1-5. 0 μm, and intrinsic diffusivities between 0. 13 and 0. 65 μm 2 /ms. Least square residuals were then computed between the experimental data and simulated dataset, with the minimum residual chosen as the best fit. To compare the statistical significance of differences between NAA and mI, the extracted diameters and intrinsic diffusivities were subject to a paired Student's t-test, with p = 0.
05 thresholding the validity of the null hypothesis. Simulations for gradient dephasing spectra were performed numerically using in-house written code, which performed a numerical evaluation of each gradient waveform as described in Equation  16 of Zheng et al  [69]. In complement to the DDE measurements, diffusion tensor spectroscopy (DTS) measures of macroscopic fractional anisotropy (FA) were performed on a separate set of N = 4 rats, focusing on an identical voxel location as the DDE. The experiments were carried out using the same RE-MRS pulse sequence described above, scanning G 1 in 6 directions to measure while setting |G 2 | = 0, thereby effectively achieving a SDE encoding. The tensor elements were extracted by a nonlinear fit of the data in Matlab 1 (Mathworks Inc. , Nantick MA), and eigenvalues and eigenvectors computed following diagonalization.
All of this paper's DDE data are provided as Supporting Information (S1 File). This DDE MRS data is sorted according to animal and gradient strength/direction, and stored in folders with the format animalX\3Y -where X was the X th animal studied and Y was the Y th experiment performed in that animal. For each animal's folder, the first experiment corresponds to G = 0 and the next experiments are ordered according to psi = 0:45:360. I. e. , in the series 30-39, 30 is the experiment with G = 0 and the variable-angles correspond to experiments 31-39. If an experiment number has the suffix 'o' (e. g. , 35o), it means that an artifact was detected in 35 and that the experiment was repeated. These individual DDE data sets for the various animals scanned, can be found in marked folders of the Supporting Information (S1 File) as individual Bruker-formatted files.
Given the nearly isotropic metabolic diffusion revealed by these SDE measurements, we proceeded to assess what kind of microscopic anisotropy mI experiences compared to NAA, when assessed by DDE. The major DDE "fingerprint" for this μA will be the amplitude modulation of E(ψ), whose depth is dependent on the variance of the diffusion tensor eigenvalues of the principal axis within a compartmental pore, which in turn can reflect the eccentricity of the compartment. In vivo DDE RE-MRS experiments were conducted simultaneously on a number of rat brains. The raw data (Fig  7a ) revealed characteristic signal amplitude modulations for both metabolites, evidencing that mI also undergoes restricted diffusion within anisotropic, albeit randomly oriented, astrocytic environments. Fractional anisotropies (FAs) derived from diffusion tensor spectroscopy analyses at 21.
Acknowledgments This work was performed at the  National High Magnetic Field Laboratory (NHMFL) , which is supported by  NSF   DMR-1157490  and the  State of Florida. Funding was also provided by the  NHMFL User Collaboration Grants Program  (to SCG). The authors also thank the  Israel Science Foundation  (Grant  795/13 ), the  Minerva Foundation  (Grant No. 712277 ) from the  Federal German Ministry for Education and Research , the  Kimmel Institute for Magnetic Resonance  and the generosity of the  Perlman Family Foundation  (to LF). NS greatfully acknowledges a  Visiting Scientist Grant  from  NHMFL , Project Number  12456.