dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements We thank the team of the  DKFZ Virus Production and Development Unit , in particular  Markus Müller ,  Mandy Roscher  and  Barbara Leuchs , for helping with virus production and titration. We are grateful to  Nathalie Salomé ,  Michele Vogel  and  Christiane Dinsart  ( DKFZ, Heidelberg, Germany ) for the anti-NS1 and anti-VP antibodies. We also thank  Nazim El-Andaloussi  and  Anne-Zelie Decrion-Barthod  for first steps into this project,  Natalia Giese  ( University Hospital, Heidelberg, Germany ) for patient tumour samples,  Michael Dahm ,  Ottheinz Krebs  and  Bernard Huber  for fruitful discussion,  Sandra Caldeira  and  Kathleen Broman  for critical reading of the manuscript, our graphic designer  Jutta Jung  for helping us with the figure of the model. This study was initially supported by grants from the  Federal Ministry of Education and Research (BMBF)  and the  Helmholtz Association  in the framework of the  Deutsches Krebsforschungszentrum/ Cancéropôle du Grand-Est Joint Programme in Applied Tumour Virology.
At day 10 postinjection, the luciferase activity was quantitated using Igor Pro software and the results demonstrate that at this MOI, a 3. 5-fold deficit for fAAV transduction, compared with the value determined for intact vector, existed (Figure  3a, c ). The relative luciferase values for both vectors were maintained for >6 months in WT mouse muscle (DNS). Our previous report demonstrated that liver transduction using fAAV-factorVIII (5. 8 kb) corrected the bleeding phenotype  of the hemophilia A dog model. 23 However, the relative transduction efficiency in the liver, compared with intact AAV, was not investigated, which is important for translation of fAAV into the clinic, especially considering the lower production titers (Supplementary Figure  S1 , online). Therefore, fAAV-luciferase or the intact control, packaged in AAV8 capsid, was administered intravenously to 8-week-old WT mice (N = 3).
Mice were first anesthetized using 2. 5% isoflurane in a gas chamber and then injected IP with excess d-luciferin (5 mg in PBS, Caliper). Five minutes after the injection, image analysis was carried out using the Living Image software (Caliper Lifesciences), and luciferase expression is reported in relative light units as described by manufacturer. As shown in Figure  3 , the light intensity scale can be adjusted for image presentation purposes, which is independent of the data analysis by the Living Image software. In vitro luciferase assay for eye and liver transduction. WT mice (N = 3) were injected with 1 × 10 11 vg of intact or fragment AAV8 luciferase reporter vectors. At 15 days postinjection, an equivalent portion of the liver was harvested and analyzed for luciferase activity using standard conditions.
Detection of Dysferlin was performed using standard Odyssey protocol, with primary specific monoclonal anti-Dysferlin antibody (NCL-Hamlet-2, Novocastra) diluted 1:2,000. Blot was probed using the Odyssey secondary antibody DAM 800 diluted 1:5,000, scanned, and quantified using the Odyssey Application Software 2. 1 (LI-COR). For in vivo western blot analysis (N = 3), total protein was recovered from the gastrocnemius muscle using the lysis solution M-PER (Pierce) and a TissueLyser LT (Qiagen, Redwood City, CA) as recommended by the manufacturers. Approximately 30 µg of total protein was separated on a NuPage 4-12% BisTris gel (Invitrogen) and transferred to a nitrocellulose membrane via i-Blot (Invitrogen). The NCL-Hamlet-2 antibody was used at 1:1,000 dilution overnight, and an anti-mouse IgG-horseradish peroxidase secondary antibody was used in conjunction with the Pierce West Pico chemiluminescent detection kit.
qPCR analysis. DNA was extracted from transfected cells by DNeasy Blood and Tissues Kit (Qiagen), according to the manufacturer's instructions, after homogenization with a Microtube Pellet Pestle Motor (Fisher Scientific, Waltham, MA). The quantity and quality of the isolated DNA was determined with NanoDrop ND 1000 (NanoDrop Technologies, Wilmington, DE). The primer pairs and Taqman probe used for enhanced green fluorescent protein (eGFP)-specific detection were as follows: 614GFP. Forward: 5′-AGTCCGCCCTGAGCAAAGA-3′; 680GFP. Re verse: 5′-GCGGTCACGAACTCCAGC-3′; and 636GFP_Probe: 5′-CAA CGAGAAGCGCGATCACATGGTC-3′. The ubiquitous albumin protein was used to normalize the data across samples. Primers and probe used for albumin-specific detection were as follows: Alb. Forward: 5′-GCTGTCATCTCTTGTGGGCTGT-3′; Alb.
ACKNOWLEDGMENTS We thank  Camille Samulski  for reviewing the text and  Eric Horowitz  for qPCR assistance. This work was supported by the  Jain Foundation , the  Northwest Genome Engineering Consortium  and by the  RO1 AI072176  awarded to MLH. NIH  grants  R01 AI080726 ,  DK084033 ,  AI072176 , and  U54 AR056953  awarded to RJS also supported this work.
4. 24  [21]  with tune Z2, while the NLO parton distribution function (PDF) is CT10  [22]. The W+jets and tt background events are generated using MADGRAPH  [23]  and PYTHIA; the TAUOLA package is used to describe τ decays  [24]. Event samples of WW, WZ, ZZ, and QCD multijet backgrounds are generated using PYTHIA. The generated events are processed with the GEANT4-based  [25, 26]  CMS detector simulation and reconstructed with the same software as the collision data. The signal MC samples include pileup conditions (multiple pp interactions occurring in the same bunch crossing) matching those observed in the 2011 data sample. For data taken in the earlier part of 2011, the dimuon analysis is based on triggers that select events containing at least two muons, each with transverse momentum p T of at least 6 or at least 7 GeV, depending on the running period.
Electroweak backgrounds are estimated using MC samples. For both channels, QCD background is estimated from the data under the assumption that same-sign and opposite-sign lepton pairs are equally probable because the misidentification of a charged particle in a jet as a lepton or antilepton is equally likely. Backgrounds are estimated for forward and backward events separately and subtracted bin by bin. The total background contribution to the data ranges from 0. 17% to 0. 21% in the dimuon channel and from 0. 68% to 0. 80% in the dielectron channel. After background subtraction, the numbers of events found in the muon channel in the forward and backward regions are 950 570 and 929 737, respectively. The corresponding numbers in the electron channel are 448 338 and 438 035. All results are given in the phase-space region defined by p T ( ) > 20 GeV and |η( )| < 2.
Acknowledgements We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC machine. We thank the technical and administrative staff at  CERN  and other CMS institutes, and acknowledge support from:  FMSR (Austria) ;  FNRS  and  FWO (Belgium) ;  CNPq ,  CAPES ,  FAPERJ , and  FAPESP (Brazil) ;  MES (Bulgaria) ;  CERN ;  CAS, MoST , and  NSFC (China) ;  COLCIENCIAS (Colombia) ;  MSES (Croatia) ;  RPF (Cyprus) ;  MoER ,.
Primary mouse anti-NeuN (Chemicon International, St Quentin en Yvelines, France 1/300) and rabbit anti-GFAP antibodies (1/1,000; Dako) were diluted in Mouse On Mouse diluent and incubated with the sections overnight at 4 °C. Sections were washed with fluoromount-G (Calbiochem, Fontenay sous Bois, France), observed by confocal microscopy (Axio Imager Z1; Zeiss, Le Pecq, France) and images were analyzed with AxioVision 4. 7 software (Zeiss, Oberkochen, Germany). For GFP immunohistochemistry, the sections were washed in 0. 1% Triton X-100 in PBS and incubated in a PBS solution containing hydrogen peroxide 1%, methanol 20%, and Triton X-100 0. 1% for 20 minutes to block endogenous peroxidase activity. Sections were blocked by incubation in PBS buffer with 4% goat serum (Dako, Trappes, France), 4% bovine serum albumin (Sigma), and 0.
AcKnoWledGMents We thank  GENETHON  for providing us with the adenovirus helper plasmid (pXX6) and the pAAV packaging plasmid ( p5E18-VD2/9 ) and  Yannick Tanguy  for statistical analyses and helpful comments. This work was supported by  SMA-Europe ,  Association Française contre les Myopathies (France)  and  Famiglie SMA (Italy) , the  Université Pierre et Marie Curie (UPMC) , the  Institut National de la Santé et de la Recherche Médicale (INSERM) , the  Centre National de la Recherche Scientifique (CNRS) , and the  Association Institut de Myologie  (A. I. M). The authors declare no conflict of interest.
Despite of the spatial resolution of the ALHAMBRA images (∼ 1 arcsec), for 22,051 galaxies we obtained the contamination by other type of less than 10%. Of those, 1,640 and 10,322 galaxies are classified as early-(down to redshifts ∼ 0. 5) and late-type (down to redshifts ∼ 1. 0), respectively, with magnitudes F613W 22. 0. In addition, for magnitude range 22. 0 < F613W 23. 0 we classified other 10,089 late-type galaxies with redshifts 1. 3. We show that the classified objects populate the expected regions in the colour-mass and colour-magnitude planes. The presented dataset is especially attractive given the homogeneous multi wavelength coverage available in the ALHAMBRA fields, and is intended to be used in a variety of scientific applications. The low-contamination catalogue (< 10%) is made publicly available with the present paper.
General methodology The main tool used in this work to estimate morphologies is galSVM, a non-parametric support vector machine (SVM) based code  (Huertas-Company et al. 2008 , 2009 , 2011). Basically, galSVM uses a training set of local galaxies with known visual morphologies to train the SVM that is then applied to the dataset to be classified (see Sec. 3. 2. 1). Galaxies from the training sample are redshifted and scaled in luminosity to match the magnitude counts and redshift distribution of the ALH sample, resampled with the ALH pixel scale (∼ 0. 222 arcsec/pix), and finally dropped in a real ALH background. Figure  2  shows an example of redshift and magnitude distributions of local sample before and after being redshifted and scaled in luminosity (green and black solid lines), and corresponding distributions of ALH-7 sample (red dashed lines).
We measured 7 morphological parameters on this simulated dataset (and on the ALH sample later on), and use them simultaneously to train the vector machine: • Ellipticity • Abraham concentration index (CABR) -ratio between the fluxes at 30% and 90% of the radius  (Abraham et al. 1996)  • Conselice-Bershady concentration index (CCON) -ratio between circular radii containing 20% and 80% of the total flux  (Bershady et al. 2000)  • Gini (GINI) -cumulative distribution function of galaxy's pixel values  (Abraham et al. 2003)  • Asymmetry (ASYM) -measures the degree of asymmetry in the light distribution  (Conselice et al. 2000)  • Smoothnes (SMOOTH)-measures the relevance of smallscale structures  (Conselice et al. 2000) , and • M 20 moment of light (M20) -flux in each pixel multiplied by the squared distance to the centre of the galaxy, summed over the 20% brightest pixels of the galaxy  (Lotz et al.
For each morphological type from N&A catalogue, we selected randomly 50 sources and we checked (between 4 people) their images in all 5 SDSS bands. In all cases we do not see any differences in galaxy structures between the g, r, and i bands. On the other hand, we do see significant changes between any of these three bands and u or z filters. The selected local dataset is then redshifted, scaled in luminosity and dropped in the ALH fields. To that purpose, galSVM requires the apparent magnitude and photo-z distributions of all sources. To improve statistics, we used for each field the mag and photo-z distributions of the 4 CCDs after checking that these distributions are completely consistent with those of individual fields (individual CCDs). Before dropping the mock galaxies they are resampled with the same pixel scale than the ALH galaxies and convolved with a PSF to match the same spatial resolution.
We also neglect the eventual morphological drift between the morphologies in COSMOS (F814W) and ALHAMBRA (F613W). Again, since we are splitting our galaxies in two classes we do not expect a significant effect. This assumption is indeed confirmed through extensive tests on the SDSS dataset. We compared different morphological parameters of local N&A galaxies between the r and i bands, without finding any significant differences in two bands, independently of the redshift and the Hubble type. for three morphological types classified in the COSMOS/HST survey with galSVM code: E/S0 (red solid lines), spirals (blue dashed lines), and irregulars (green dotted lines). Following these distributions, we look for the probability threshold (p E th , p L th ) to apply to the ALHAMBRA classification so that the resulting classification contains less than 10% contaminations from the neighboring morc 2012 RAS, MNRAS 000, 1-18 The ALHAMBRA survey: morphological classification 7 Comparison between the properties of the full N&A sample (black solid lines) and 3000 galaxies (red dashed lines) selected randomly from the full one to be used in our morphological classification.
0 and 5 -7% between magnitudes 22. 0 and 23. 0. (see Sec. 2. 1). This low-contamination catalogue is the one we are releasing with the present paper. Description of all columns and a sample of catalogue for the first five objects are available in Appendix A. The full p10 catalogue of 22,051 galaxies is available in the electronic version of this paper and through the ALHAMBRA website http://alhambrasurvey. com/. (top, right), 21. 5 (middle, left), 22. 0 (middle, right), 22. 5 (bottom, left), and 23. 0 (bottom, right). In each plot, we compare the distributions of averaged probabilities (PROB AVG) measured in the ALH-4 field for three morphological types classified in the COSMOS field using the HST/ACS imaging data  (Huertas-Company et al. 2009; Tasca et al. 2009 ): elliptical/S0 (red solid lines), spiral (blue dashed lines), and irregular (green dotted lines) galaxies.
Moreover, from the KCORRECT SED fits we obtained the stellar masses and star-formation histories, using the  Chabrier (2003)  stellar initial mass function. We do not have any mid-infrared (MIR) nor far-infrared (FIR) data as an input information for SED fitting, the reddest band we have is K. This means that, following the well known mathe- In all plots, of p10 sources classified down to F613W 22. 0, ET galaxies are marked with red diamonds, and LT with blue triangles (darker and brighter symbols, respectively, when printed in black and white). Boxes marked with dash-dot-dashed black lines define the locus of ∼ 80% and ∼ 20% of galaxies from ET and LT samples, respectively. Top and right histograms: normalised distributions of corresponding parameters represented on the central plots of ET (red solid lines) and LT (blue dashed lines) galaxies.
0, large covered area, and precisely measured photometric redshifts (obtained through SED fittings of 23 point spectra), ALHAMBRA is an ideal survey for tracing the cosmic variance and cosmic evolution. However, morphological properties and classification of galaxies are crucial for any kind of galaxy formation and evolution studies. Lowcontamination, high-populated morphological catalogue presented in this paper, together with the precise measured photometric redshifts and photometric properties of the ALH survey, present an important addition to other datasets for studying the morphological properties of extragalactic sources and their evolution (taking into account the variety of covered ALH fields). Some of these studies include: the evolution of ETs and LTs down to redshifts ∼ 0. 5 and ∼ 1.
ACKNOWLEDGMENTS We thank the referee  Chris Lintott  for constructive comments which improved the paper significantly. This research was supported by the  Junta de Andalucía  through projects  PO8-TIC-03531  and  TIC114 , the  Spanish Ministry of Economy and Competitiveness (MINECO)  through projects  AYA2006-14046 ,  AYA2010-15169 ,  AYA2010-22111-C03-02 ,  AYA2011-29517-C03-01 , and the  Generalitat Valenciana  through project  GV/Prometeo 2009/064. MP acknowledge financial support from  JAE-Doc program  of the  Spanish National Research Council (CSIC) , co-funded by the  European Social Fund. Based on observations collected at the  Centro Astronómico Hispano Alemán (CAHA) at Calar Alto , operated jointly by the  Max-Planck Institut fur Astronomie  and the  Instituto de Astrofísica de Andalucía (CSIC).
The CEFCA is funded by the  Fondo de Inversiones de Teruel , supported by both the  Government of Spain  ( 50% ) and the  regional Government of Aragón  ( 50% ). In this work, we made use of  Virtual Observatory Tool for OPerations on Catalogues And Tables (TOPCAT). We thank the  developers of Ubuntu, Python, Numpy, Scipy, and Matplotlib  for making their work public and available to all scientific community.
Multi-Ethnic Study of Atherosclerosis study population and the analytic sample The Multi-Ethnic Study of Atherosclerosis (MESA) is a multicenter cohort study of 6,814 men and women 45-84 years of age free of known CVD at baseline, recruited from six different communities: Baltimore City and Baltimore County, MD; Chicago, IL; Forsyth County, NC; Los Angeles County, CA; Northern Manhattan and Bronx, NY; and St. Paul, MN. Detailed information about MESA design is provided elsewhere  (19). The current study used MESA baseline data collected between July 2000 and August 2002 and the follow-up exam 2, 3, and 4 data through 2007, and included MESA study participants with normal fasting glucose ,100 mg/dL. Those with type 2 diabetes or fasting glucose between 100 and 125 mg/dL at baseline were excluded.
Data collection and the study variables Information about socioeconomic status, medical history, medication, and tobacco and alcohol use was obtained through a questionnaire. WC at the umbilicus was measured to the nearest 0. 1 cm using a measuring tape. Height and weight was measured by a stadiometer and calibrated scale. BMI was calculated from height and weight as kg/m 2. Resting BP was measured three times, with participants in the seated position, with a Dinamap model Pro 100 automated oscillometric sphygmomanometer (Critikon); the average of the last two measurements was used in the analysis. Fasting TGs were measured in plasma after an 8-h fast using a glycerol-blanked enzymatic method (Trig/GB; Roche Diagnostics, Indianapolis, IN). HDL-C was measured in plasma by the cholesterol oxidase method (Roche Diagnostics) after precipitation of non-HDL-C magnesium/dextran.
AcknowledgmentsdThe MESA study was supported by contracts  N01-HC-95159  through  N01-HC-95169  from the  National Heart, Lung, and Blood Institute. No potential conflicts of interest relevant to this article were reported. S. X. L. conceived and designed the study and researched data. I. B. researched data and participated in the writing of the manuscript. R. Y. , C. T. S. , P. S. , M. S. , and A. G. B. participated in the writing of the manuscript. Z. J. researched data. All authors reviewed and edited the manuscript. S. X. L. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. This study was presented in abstract form at the 72nd Scientific Sessions of the  American Diabetes Association, Philadelphia, Pennsylvania ,  8-12 June 2012.
RNA isolation and quantitative real-time PCR Total RNA was isolated with Trizol (Invitrogen) and quantifi ed using a NanoDrop system (Thermo Fisher Scientifi c, Walthman, MA). One microgram of RNA was reverse-transcribed into cDNA using M-MLV reverse transcriptase, random primers, and RNase-OUT inhibitor (Invitrogen). Real-time quantitative PCR was performed using an ABI PRISM 7700 sequence detection system (Applied Biosystems, Darmstadt, Germany) with the default settings  ( 20 ). Primers were obtained from Invitrogen (Breda, The Netherlands). Fluorogenic probes were synthesized by Eurogentec (Seraing, Belgium). All expression data were subsequently standardized for 18S rRNA analyzed in separate runs and further normalized for the respective expression values of the control groups.
This work was supported by grants from the  Netherlands Organization for Scientifi c Research  ( VIDI Grant   917-56-358  to U. J. F. T. , VIDI Grant  917-36-351  to P. C. N. R. , VIDI Grant  917-66-301  to M. V. E. ); the  Fondation Recherche Médicale  ( FRM SPE20040300452  to T. G. ); the  Institut National de la Santé et de la Recherche Médicale  and the  French National Research Agency  under the program " Investissements d'Avenir"  ( ANR-11-LABX-0021  to T. G. , J. G. , and L. L. ); the  Netherlands Heart Foundation  ( NHS 2003B136  to P. C. N. R. ); and  TopInstitute Pharma  (Project  T2-110  to F. K. and T. J. C. V. B. ). P. C. N. R. (Grant  2009T038 ) and M. V. E. (Grant  2007T56 ) are established investigators of the  Netherlands Heart Foundation.
Statistical analysis Data were entered into an Excel database (Microsoft, Redmond, USA) and then, analysed with STATA version 11. 2 (StataCorp, College Station, USA). Quantitative data for normally distributed variables, as assessed by box plots and skewness, were described using mean, standard deviation (SD) and proportion; and compared using Fisher's exact test. Non-normally distributed variables were described using median and range or proportion. Responses from 5-point rating scales were treated as ordinal data and analyzed using non-parametric tests: Kruskal-Wallis test, Wilcoxon signedrank test or Wilcoxon sum rank test to compare 2 groups and Friedman test to compare more than 2 groups, as appropriate  [11]. P-value < 0. 05 was considered significant for all comparisons. The answers to the open-ended questions of the descriptive test were coded by reported ingredients and then analysed using proportions.
ACKNOWLEDGEMENTS The work was conducted in partial fulfilment of the requirements for  Marlene Hebie's MSc  degree at the  London School of Hygiene and Tropical Medicine. We acknowledge the assistance of  Mette Olsen  and  Daniela Manno  in the design of the sensorial trial. We thank  Rose-Mary Kolela  and  David Mandili  for assistance with field work. We kindly thank the staff of Nyamagana District Hospital where the study was carried out as well as the study participants. Finally, our thanks go to  Mamane Zeilani  and  Marine Le Chatelier  of the external research and nutrition strategies department of  Nutriset SAS  for their support regarding the development and shipment of the nutritional supplements.
Diffusion Weighted Images (DWI) normally shows a low Signal to Noise Ratio (SNR) due to the presence of noise from the measurement process that complicates and biases the estimation of quantitative diffusion parameters. In this paper, a new denoising methodology is proposed that takes into consideration the multicomponent nature of multi-directional DWI datasets such as those employed in diffusion imaging. This new filter reduces random noise in multicomponent DWI by locally shrinking less significant Principal Components using an overcomplete approach. The proposed method is compared with state-of-the-art methods using synthetic and real clinical MR images, showing improved performance in terms of denoising quality and estimation of diffusion parameters.