dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements This work was supported by a  Marie Curie Fellowship  to M. S-A. ( PIEF-GA-2009-236779 ) and  BBSRC  grants  BB/F007582/1  and  BB/J004588/1  (GRO) to M. W. B. We thank  Dr Thomas Simmons  and  Professor Paul Dupree  of the  University of Cambridge  for monosaccharide analyses,  Dr Charlotte Miller  and  Dr Rachel Wells  of the  John Innes Centre  for FTIR analyses,  Dr Kerry Franklin  of the  University of Leicester  for help with plant growth in different light conditions, and  Dr Harry Brumer  of the  University of British Columbia  for providing seeds of an Arabidopsis xth31xth32 double mutant.
The mass flow controllers were used to regulate the flow rate of the pure nitrogen and the solvent vapors. In addition, the electrical valves were controlled by a program developed under the Labview software. The sensing device was operated at room temperature, and the total flow rate was kept constant at 100 cm 3 ⋅min -1 during the measurements. Furthermore, the electrical conductivities of the conductive polymer composite (CPC)-based sensors were recorded with a Keithley 6517A multimeter and these sensors were placed in a 100×10×3 mm chamber during the dynamic vapor sensing measurements. The chemiresistive response of the CPC sensors is determined from the relative amplitude of the electrical signals (A R ). A R is the ratio of the change in resistance upon exposure to solvent vapors, normalized by the initial resistance of the sensor, as indicated in Equation  1 : A R R R R O O = - ( 1 ) where R is the resistance of the sensing materials when exposed to analyte vapors and R O is the initial resistance when exposed to a nitrogen flow.
To evaluate uncertainties due to Planck instrumental noise, we use 500 noise simulations of each map; these are the standard set of time-ordered data noise simulations projected into sky maps (the FFP8 simulations defined in Ref. [33] ). While the Planck maps are filtered only by the instrument beam (the effective beam defined in Refs. [34]  and  [35] ), the BICEP2/Keck maps are in addition filtered due to the observation strategy and analysis process. In particular, large angular scales are suppressed anisotropically in the BICEP2/Keck mapmaking process to avoid atmospheric and ground-fixed contamination; this suppression is corrected in the power spectrum estimate. In order to facilitate comparison, we therefore prepare "Planck as seen by BICEP2/Keck" maps. In the first step we use the anafast, alteralm and synfast routines from the healpix [36] package  [37]  to resmooth the Planck maps with the BICEP2/Keck beam profile, assuming azimuthal symmetry of the beam.
The coordinate rotation from Galactic to celestial coordinates of the T , Q, and U maps is performed using the alteralm routine in the healpix package. The sign of the Stokes U map is flipped to convert from the healpix to the IAU polarization convention. Next we pass these through the "observing" matrix R, described in Section VI. B of BK-I, to produce maps that include the filtering of modes occuring in the data processing pipeline (including polynominal filtering and scan-synchronous template removal, plus deprojection of beam systematics). Figure  1  shows the resmoothed Planck 353 GHz T , Q, and U maps before and after filtering. In both cases the BICEP2/Keck inverse variance apodization mask has been applied. This figure emphasizes the need to account for the filtering before any comparison of maps is attempted, either qualitative or quantitative.
D. Consistency of BICEP2 and Keck Array spectra The BB auto-spectra for BICEP2 and Keck Array in the lower left panel of Fig. 2  appear to differ by more than might be expected, given that the BICEP2 and Keck maps cover almost exactly the same region of sky. However, the error bars in this figure are the standard deviations of lensed-ΛCDM+noise simulations; while the signal is largely common between the two experiments the noise is not, and the signal-noise cross terms produce substantial additional fluctuation of the difference. The correct way to quantify this is to compare the difference of the real data to the pair-wise differences of simulations, using common input skies that have power similar to that observed in the real data. This was done in Section 8 of BK-V and the BICEP2 and Keck maps were shown to be statistically compatible.
ACKNOWLEDGMENTS BICEP2 was supported by the  U. S. National Science Foundation  under Grants No. ANT-0742818  and  ANT-1044978  ( Caltech and Harvard ) and  ANT-0742592  and  ANT-1110087  (Chicago and Minnesota). The development of antenna-coupled detector technology was supported by the  JPL Research and Technology Development Fund  and Grants No. 06-ARPA206-0040  and  10-SAT10-0017  from the  NASA APRA  and SAT programs. The  Keck Array project  was supported by the  National Science Foundation  under Grants  ANT-1145172  and  NSF-1255358  (Harvard),  ANT-1145143  (Minnesota) and  ANT-1145248  (Stanford), and from the  Keck Foundation (Caltech). We thank the staff of the  U. S. Antarctic Program  and in particular the South Pole Station without whose help this research would not have been possible.
New methods also include spectral smoothing, topographic correction, and adjacency effect correction. The combined use of models and empirical procedures has been proposed in a few papers  [14] [15] [16]. The magnitude of aerosol effects in remotely sensed data mainly depends on aerosol type and amount, observation geometry, and the wavelength  [2]. Several studies have shown the crucial role of aerosol optical thickness at 550 nm in atmospheric transfer modelling  [17] [18] [19] [20] [21] [22] [23] [24]  and on the atmospheric correction of multispectral and hyperspectral data for ocean and land properties retrieval  [25] [26] [27] [28] [29] [30] [31]. The combination of satellite hyperspectral data, ground measurements, and model-based analysis allows complete information datasets for accurate surface reflectance retrieval  [32].
The aim of this work is to evaluate the radiative impact of the aerosol model on the results of the atmospheric correction designed for Compact High Resolution Imaging Spectrometer (CHRIS/PROBA) hyperspectral data acquisitions over land. The reflectance is obtained using the CHRIS Atmospherically Corrected Reflectance Imagery (CHRIS@CRI) algorithm  [21, 25] , a physically based atmospheric correction algorithm developed specifically for CHRIS data by adapting the vector version of the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) radiative transfer code  [33] , an improved open-source code of the 6S  [27]. The aerosol radiative impact was investigated, comparing the reflectance obtained by applying the CHRIS@CRI algorithm with different aerosol models: one using AERONET (AERosol RObotic NETwork) sun-photometer retrievals, three standard types implemented in 6SV, and one extracted from the detailed simulations of the chemistry-transport model GEOS-Chem.
The microphysical properties (size distribution, the real and imaginary part of the refractive index) and the optical properties (single scattering albedo and asymmetry parameter) from AERONET are considered the reference to inter-compare results obtained using other models. This paper is organized as follows: in Section 2, an overview of the area test case of this study is presented and a complete description of the data used in the study is provided, while in Section 3, the CHRIS@CRI atmospheric correction is described. In Section 4, the results are shown for the aerosol properties analysis and for the comparison of the reflectance values obtained after the atmospheric correction process. The conclusions are finally summarized in Section 5.
CHRIS Data The CHRIS (Compact High Resolution Imaging Spectrometer) on PROBA satellite is a high resolution multi-angular imaging spectrometer, with a spectral range from 400 to 1050 nm and a spatial resolution of 17 or 34 m. CHRIS provides acquisitions up to 62 narrow and quasi-contiguous spectral bands. The specific feature of CHRIS is that it provides data from five observation angles during the same overpass. One of the main advantages of the CHRIS instrument is the high configurability of its operation mode. CHRIS is characterized by five operational modes, which are associated with the five spectral configurations (Mode 1-5). In particular, in Mode 3 (full swath, full resolution) CHRIS acquires images characterized by 17 m of nominal spatial resolution, 18 spectral bands, and 13 km of nominal swath width.
The combination of the 18 spectral bands typical of this mode is specifically used for land studies. CHRIS data is supplied in HDF (Hierarchical Data Format) data files (version 4. 1r3). The HDF file contains the image file and the ancillary data, such as spectral and geometric parameters. All CHRIS images in this work were acquired in Mode 3. CHRIS images were selected if simultaneous AERONET (Level 2. 0 or Level 1. 5) acquisition data were available. Other specific requirements for imagery acquisition were clear-sky conditions, the aerosol loading defined by an AOT (Aerosol Optical Thickness) value >0. 1, and high solar irradiation (solar zenith angle < 60°). Table  1  shows date and time of selected CHRIS images and of the corresponding atmospheric aerosol data (AOT@550nm, wv, and O3 columnar contents) from simultaneous AERONET measurements.
The value of AOT@550 nm obtained from GEOS-Chem model simulations is also specified. For each case study, the solar zenith angle relative to the two CHRIS overpasses and the AERONET data quality levels are also displayed. These two parameters are important because they were used for the two images selected, as previously mentioned. Table  1. Date and time of the two selected CHRIS images over Cabauw and Brussels (see Figure  1 ) and of the nearly simultaneous AERONET acquisitions. The corresponding values of the solar zenith angle (SZA), the aerosol optical thickness at 550 nm (AOT@550 nm) from AERONET data and from GEOS-Chem simulations, the water vapour (wv) and ozone (O3) columns, and the quality level of AERONET data are also shown.
In the version employed here, the GEOS-Chem model explicitly simulates the mass concentration of the aerosol species, and optical properties are derived from the concentration of six optical aerosol species (inorganic ions (sulfate + nitrate + ammonium), organic carbon, blank carbon, sea salts, and soil dust) assumed as spherical and externally mixed. Each species is assigned relative humidity (RH) dependent log-normal size distributions and refractive indices. Optical properties are then interpolated from the extinction efficiency, the single scattering albedo, and the polynomial expansion terms of the scattering phase function tabulated as a function of RH. The pre-calculated table is computed using the MIE code by  [50]. In this work, the aerosol optical properties are calculated off-line using the post-processing tool FlexAOD  [51].
Model values were calculated capping the ambient relative humidity at 30% in order to be consistent with measurement method  [34]. In Figure  4 , we compare the observed profiles of the scattering and absorption coefficients during the flight shown in Figure  3  with model calculations. The scattering coefficient for dry aerosol at 550 nm was measured by a TSI 3563 integrating nephelometer, while the absorption coefficient at 567 nm was measured by a particle soot absorption photometer (PSAP) and corrected to 550 nm  [34]. For consistency with observations, model optical properties are calculated capping the ambient relative humidity to 30%. These datasets are available only for profiles taken near Cabauw on 8 and 12 May. On 8 May, the model is in the range of the observed scattering coefficient, but the shape of the profile is not accurately reproduced.
It appears spectrally constant for Brussels, while in Cabauw it increases to 1. 54 for wavelengths higher than 0. 7 μm. The GEOS-Chem real part of the refractive index gradually decreases from 1. 52 at 400 nm to 1. 48 near 1 μm. The 6SV continental values are in the same range of AERONET and GEOS-Chem, while urban and maritime are higher and lower, respectively. For the imaginary part, AERONET data show in both sites spectrally constant values near 0. 02. The GEOS-Chem imaginary part is higher, near 0. 03, while the 6SV continental and maritime models are between 0. 01 and 0. 02. The urban model shows values near 0. 1 over the whole spectral range, defining the absorbing behavior of this aerosol type. In Figure  7a ,b, the single scattering albedo (SSA) and asymmetry parameter (g) values are respectively shown for values obtained by AERONET inversion products and for the values simulated with MIE and AEROSOL subroutine of 6SV using microphysical properties alternatively from the five aerosol models considered in this paper.
The analysis of the microphysical aerosol properties, considering data from models (6SV and GEOS-Chem) and ground-measurements (AERONET), shows that they identify aerosol particles that are extremely different in their volume distribution function. Moreover, AERONET and GEOS-Chem show the same scattering behavior but with a higher-absorbing feature for the latter. The optical properties (g and SSA) demonstrate that the AERONET data are comparable with those of a continental aerosol as defined by the 6SV radiative transfer model, while for GEOS-Chem data analysis, the SSA and g behavior does not uniquely identify a standard aerosol, with spectral results varying from continental and urban standard types in both scenes. The analysis of the microphysical and optical properties shows that the most sensitive parameter to determine the aerosol optical properties and consequently, the radiative behavior, is the aerosol complex refractive index.
Reflectance Spectral Behavior To evaluate the capability of the atmospheric correction algorithm to reproduce the reflectance spectral behavior, the surface reflectances obtained using the BEAM tool and applying to the CHRIS@CRI algorithm using AERONET data and are presented for the Cabauw and Brussels images, considering three different targets: a vegetated area, a bare soil area, and an industrial roof (Figure  10 ). images over Cabauw (red) and over Brussels (blue), atmospherically corrected with the CHRIS@CRI algorithm using AERONET data. On the right: the surface reflectance obtained using the BEAM tool (black line) and applying the CHRIS@CRI algorithm using AERONET data (pink line) for three different targets (vegetated area, bare soil area and industrial roof) identified with the associated colored circles in the two images.
Figure10. On the left: the two (R: channel 7; G: channel 4; B: channel 1) CHRIS images over Cabauw (red) and over Brussels (blue), atmospherically corrected with the CHRIS@CRI algorithm using AERONET data. On the right: the surface reflectance obtained using the BEAM tool (black line) and applying the CHRIS@CRI algorithm using AERONET data (pink line) for three different targets (vegetated area, bare soil area and industrial roof) identified with the associated colored circles in the two images.
Acknowledgments This work was carried out as part of the  PRIMES  (contract n. I/017/11/0 ) and CLAM-PHYM (Contract No. I/015/11/0 ) projects, both funded by the  Italian Space Agency (ASI). We are deeply thankful to  Will Morgan ,  Gavin McMeeking , and  Hugh Coe  for having provided the AMS and SP2 measurements and to  Ellie Highwood  for having provided nephelometer and PSAP measurements, all collected during the EUCAARI/LONGREX aircraft campaign.
Genetic analysis In 2012, genomic DNA was extracted from individual samples used for CHNSO analyses. A first primer pair was designed based on the Salmo trutta sdY (sexually dimorphic on the Y-chromosome) malespecific gene (GenBank accession number: JF826019. 1), which has been shown to efficiently identify genetic males as this sex-determining gene is only present in males  [23, 24, 28]. It generates a male-specific amplification product of approximately 170 bp DNA in the genus Salmo. An additional autosomal amplification product serves as a positive control for the polymerase chain reaction (PCR) amplification. This positive control is derived from the eye-specific lactate dehydrogenase sequence gene (GenBank accession numbers AF488539 and AJ277710) and generates an amplification product of approximately 1 kb.
Acknowledgements. The field sampling was realized thanks to  Javier Alvarez  ( GAVRN, Pamplona, Spain ). We thank  Jacques Rives ,  Frédéric Lange  and  François Guéraud  for their technical support. We also thank  Fiona McIntyre  for her comments on the manuscript as well as  Bjarni K Kristjánsson  and an anonymous reviewer for their constructive comments on an earlier version of the manuscript.
Patients All enrolled patients were adult men, aged < 68 years at the time of nsRP, with normal preoperative EF (IIEF-EF domain score ≥ 22)  [9]  who underwent nsRP for organ-confined, non-metastatic prostate cancer (Gleason score ≤ 7, prostate specific antigen <10 ng/mL). These patients were enrolled between November 2009 and August 2011, in 50 centers in 9 European countries and Canada; detailed trial design and eligibility criteria are available at www. clinicaltrials. gov (NCT01026818) and in  [9]. The study was approved by the responsible ethical review boards (Additional file 1: Table  S1 ).
Statistical analysis The planned sample size of 412 patients was based on the primary outcome (proportion of patients achieving IIEF-EF ≥22) at the end of drug-free washout period  [9]. All analyses were based on the intent-to-treat (ITT) population, which included all randomized patients with baseline data and at least 1 post-baseline visit. Prespecified treatment group comparisons were tadalafil OaD versus placebo and tadalafil PRN versus placebo. Changes from baseline in EPIC and SEAR domain scores, and actual EDITS total scores were assessed using a pre-specified mixed model for repeated measures (MMRM), assuming an unstructured covariance matrix and included terms for baseline domain score, treatment, country, visit, visit-by-treatment interaction, age group, and age-group-by treatment interaction (included only if p < 0.
found 3-year EF recovery rates following nsRP of 72% in patients receiving PDE5 inhibitors versus 38% in patients receiving placebo  [1] , and a recent sildenafil study found recovery rates of around 40% following 12 months of treatment  [34]. Second, EPIC scores were not assessed at the end of the drug-free washout period, but only at the end of DBT and OLT. Thus, sexual function and urinary incontinence after treatment cessation could not be assessed. Also, no valid conclusions are possible regarding the patient-partner agreement for EPIC domain scores since only one-third of the partners completed the questionnaire. Finally, the only source for the data on urinary incontinence was the respective EPIC domain score. EPIC data were collected to evaluate patients' disease-specific QoL; standard instruments for assessment of urinary function, such as the International Prostate Symptom Score might be better suited to evaluate the impact of PDE5 inhibitor treatment on urinary function.
Acknowledgements The study was funded by  Eli Lilly and Company. We thank all patients for participating and all trial investigators for their contribution to data acquisition and patient care. We thank  Julia Branicka  and  Tom Clayton , both  Eli Lilly and Company , for supporting the conduct of the trial. We thank  Joaquin Casariego  and  Kraig Kinchen ,  Eli Lilly and Company , for medical advice. We thank  Clare Barker ,  Bruce Basson ,  Ann Gibb ,  Pepa Polavieja , and  Xiao Ni , all from  Eli Lilly and Company , for statistical support. Statistical analyses were programmed by  PSI CRO LTD, St. Petersburg, Russia. We thank  Jasmine Smith  and  Karin Helsberg ,  Trilogy Writing  and  Consulting GmbH, Frankfurt, Germany , for providing medical writing services on behalf of  Eli Lilly.
Microarray analysis of HT-29 cells Raw microarray data have been deposited in the GEO database under accession no. (GSE62311). A total of 28 microarrays were analysed: 8 replicates of HT-29 cells at different passage number for L. rhamnosus CNCMI-4317 treatment, rosiglitazone (positive control) and DMEM (negative control) and four replicates for L. rhamnosus CNCMI-2493. We used the Illumina human genome microarrays (HumanHT_12 v4 Expression BeadChip Kit, SanDiego, USA). For each sample, 750ng of labelled cDNA was synthesized from total RNA using Ovation PicoSL WTA System v2 and Encore BiotinIL Module kits (Nugen Technologies, Inc. Leek, The Netherlands). The slides were scanned with iScan Illumina and data recovered using Gen-omeStudio Illumina software (version 1. 0. 6). All microarray analyses, including pre-processing, normalization and statistical analysis were carried out using 'Bioconductor' packages in R programming language (version 3.
0. 2) (for more detail concerning data normalization, see S1 file). The list of differentially expressed (DE) genes were uploaded into using Ingenuity Software (IPA; version 5. 5, Ingenuity Systems, Redwood City, CA) to identify relevant molecular functions, cellular components and biological processes using a right-tailed Fisher's exact test. IPA computed networks and ranked them following a statistical likelihood approach  [23]. All networks with a score of 25 and at least 30 focus genes were considered to be biologically relevant. Additionally, ErmineJ software program was used as a complementary method to relate changes in gene expression to functional changes. ErmineJ software program is based on overrepresentation of Gene Ontology (GO) terms. GO terms were considered significantly at a FDR < 5%.
70, qvalue = 0. 003), Bhlbh2 (Basic helix loop helix family member 40, FC = 1. 96, qvalue = 0. 0005), Adm (Adrenomedullin, FC = 1. 66, qvalue = 0. 025) and Fiaf (FC = 1. 63, qvalue<0. 00089). To explore the molecular functions modified in response to L. rhamnosus CNCMI-4317, we measured the subsets of DE genes between treatments by using the core analysis function included in IPA software. Most biological functions found to be significantly enriched (P<0. 05), by L. rhamnosus CNCMI-4317 were related to gene expression machinery, cell death/survival, cellular growth/proliferation, cellmediated immune response and lipid metabolism categories (Table  1 ). Interestingly, those functions included canonical pathways associated with PPAR signalling, and HIF1α signalling (P<0. 05) (S2 Fig). Four networks were identified with scores ranging from 41 to 19.
The Fiaf gene was found to play a role in the regulatory network involved in putative functions such as neurological disease, cell cycle and cell development (Fig  4b ). On the contrary, most of the genes regulated by rosiglitazone were involved in lipid or carbohydrate metabolism functions (Table  1 ). In this context, it is no surprisingly that the Fiaf gene was found to play a role in the regulatory network involved in energy production and lipid metabolism putative functions (Fig  4c ). To validate technically the microarray gene expression data, IECs RNA in response to L. rhamnosus CNCMI-4317 were analysed by RT-qPCR for 12 genes (Table B in S1 File). RT-qPCR results confirmed the microarray expression levels with most genes having high r 2 values (Fig  4d ). For physiological relevance, microarray data was also analysed at the level of gene sets that together encoded for particular differentially expressed functional GO terms by ErmineJ.
Acknowledgments The authors are grateful to  Patricia Ancel ,  Nicolas Ventecleff  and  Véronique Pelloux  for helpful expert assistance in the microarray experiments, and to  Florence Levenez ,  Pierre Larauffie  and  Alexandrine Garnier  for their help in the animal experiment. They also acknowledge the contribution of the P3S platform for transcriptomic experiments at  La Pitié-Salpêtrière Hospital, Paris.