dataesr/scientific-paragraphs-categorization huggingface dataset:
Patients AVASTIN OUEST is a multicentric, retrospective observational study. All patients over the age of 18 years having received bevacizumab-FOLFIRI in one of the two regions for the first-line treatment of unresectable mCRC outside of a study in 2006 were included in the cohort. Data collected from medical records of patients included date of diagnosis of cancer, date of diagnosis of metastases, age, gender, potential comorbidities, use or not of adjuvant chemotherapy for locally advanced disease, initial unresectability of metastases, type of conventional chemotherapy regimen combined with bevacizumab, presence of grade III/IV toxicities, presence of adverse events having led to treatment discontinuation, best response rate obtained (as assessed by the multidisciplinary team in charge of the patient and reported in the source file), secondary surgery of initially unresectable metastases, time to progression and OS.
Data collection All TB patients registered at P J Twomey Hospital between 1950 and 2010 were included in this study. TB patient data were sourced from P J Twomey Hospital, with data collection undertaken by three data collectors: data from 1950 to 1988 were collected by allocating each data collector a block of filing cabinets (25 filing cabinets per block), while data from 1989 to 2010 were collected from the TB registers. The following variables were collected for each year of registration: age group, sex, type of TB and smear microscopy result. All patient data were collected onto a standardised paper proforma and then the total numbers for each year and for each variable were entered into a Microsoft Excel database (Microsoft, Redmond, WA, USA) by research assistants under the supervision of the principal investigator.
Data entry did not include patient identifiers. Data were not double-entered and no additional data sources were available to validate the data. Data were reported according to smear result rather than TB type, as discrepancies were noted between sputum smear result and the type of TB recorded, and there was no additional data source to clarify these discrepancies. Data on significant events in the history of TB control were obtained through personal communication with current and previous NTP staff and a review of NTP reports. These data included information on the timing of the introduction of BCG vaccination, the establishment of the NTP, the implementation of the mass radiography screening programme, laboratory training and the start of the DOTS strategy.
The usage of tools from Modern Convex Analysis (and particularly the notion of Moreau's convex superpotential) in electronics for the study of electrical circuits is fairly recent. It is a quite promising topic of research which may help engineers for the simulation of complicated electrical circuits. Due to the lack of smoothness in some circuits, most used softwares like Simulation Program with Integrated Circuits Emphasis (SPICE) can not simulate non-regular circuits without approximation of i-v characteristic of the involved nonlinear electrical devices (Fig. 5 ). A 1 L 1 0 0 L 2 ẋ ẋ1 ẋ2 + A 0 R 1 + R 2 -R 2 -R 2 R 1 + R 2 x x 1 x 2 ∈ -N (C(t); x(t)), ( 3 In the next sections we study and prove existence of solutions of two new variants of Moreau's sweeping process.
g. , quadprog in Matlab). If the set C(t) is described by finitely many nonlinear inequalities and linear equalities C(t)= x ∈ H : g j (t, x) ≤ 0, j=1, 2,. , m and h k (t, x)=0, k = 1, 2,. , p , then we can use any nonlinear programming solver (e. g. , Sequential Quadratic Programming, interior point method or fmincon in Matlab). Example 2 Let H = R 2 , T = 1, u 0 = (0, 0), A 0 = 1 0 0 1 , A 1 = 1 0 0 0 and C(t) = {t} × [t, 1] for 0 ≤ t ≤ 1. For f (t) = (0, 1 2 t 2 ), t ∈ [0, 1], it is easy to check that the unique solution of (5. 1) is given by u(t) = 1 2 t 2 , 1 2 t 2 , t ∈ [0, 1].
VII. SIMULATIONS AND NUMERICAL RESULTS We implemented the ILP model described in section V by using the IBM CPLEX 12 library 4. The program takes several input parameters: 4 http://www-01. ibm. com/software/commerce/optimization/cplex-optimizer/ • The graph modeling the museum as defined in section IV • The interest function f to use. This function produces interest vectors as defined in section VI • The maximum duration that a visitor can spend in the museum It outputs the proposed tour (as defined in section IV).
A. Intrinsic interest As we saw in section III, the Enertex algorithm ranks the sentences of a document. We used Enertex as the following: 1) From the website of the museum, we created an XML file containing the following information for each artwork: the title, the artist name, the year and the description of the artwork. 2) We extracted data from the XML to produce a file where each pseudo sentence is a concatenation of title, artist and description. 3) The latter file is used as an input to Enertex with the query "musée orangerie peinture impressionniste postimpressionniste" to drive the balancing process of the system. It produces a ranking for artworks depending on the information displayed by the museum (for each artwork, the result is a value ranging from 0 to 1). Fig. 3  shows the ranking of the artworks in the Musée de l'Orangerie provided by Enertex.
The PSA thus provides the emerging Stokes vector via its projections onto a basis of four linearly independent Stokes vectors. The polarization basis states of both the PSG and the PSA are determined by a suitable calibration procedure. Finally, for any given sample, 16 intensity images are taken, providing the raw data from which the Mueller matrix M image of the sample can be extracted, provided the instrument is calibrated. The PSG comprises a linear polarizer, two ferroelectric liquid crystal modulators (FLCs) and a true zero order quarter wave plate at 633 nm set between the two FLCs. The PSA is a "mirror image" of the PSG, with the same elements in reverse order. The FLCs are optically equivalent to retardation plates whose orientations can be switched by an electrical signal between two values, separated by 45 •.
In WEAKZEE, the Zeeman components are dressed by a Lorentzian shape with a given width. The later can be obtained from the Stark-B database  [9, 10]. In  [9] , one can find Stark broadening parameters (FWHM: Full Width at Half Maximum) by electrons and ions for few values of the electron density and the electron temperature. For all other temperatures, the Stark widths w (in Å units) can be obtained using the following fit formula  [11] :   , ) ( ) ( ) ( 2 2 1 0 e e T Log a T Log a a w Log    (1) where a 0 , a 1 , and a 2 are fitting parameters depending on the line, perturbers (ions or electrons) and the electron density. In this relation, the electron temperature is expressed in Kelvin. For the present calculations, the Lorentzian width w used by WEAKZEE was calculated using Equation  (1).
More precisely, SIMU is a combination of two codes: a molecular dynamics (MD) simulation of variable complexity and a solver for evolution of an atomic system with the MD field history used as a time-dependent perturbation. INTDPH is another Stark-Zeeman line-shape code using the quasi-static approximation for the ions. In order to account for the electron broadening, the output is convolved with a shifted Lorentzian at the post-processing step. The width and shift of the Lorentzian should be obtained separately from another code or a database. This is a very fast and accurate procedure (when electrons are strictly impact, e. g. , for isolated lines). An application of INTDPH to diagnostics of magnetized plasmas can be found in  [17]. For the calculations presented here, the impact broadening parameters were inferred from the SIMU line shapes obtained assuming B = 0.
It should be noted that the dipole reduced matrix elements are involved through the operator R. R present in relation Equation  (2). As the line considered here is of the same type as the Li-like (Li I, B III, N V) 2s-2p, i. e. , ∆n = 0 transitions, we will not discuss the validity of impact electronic collision operators such the above one. Readers interested by that issue may refer to the discussion found in  [25]. In Figure  8  of  [2] , various experimental and theoretical data representing Stark broadening widths (FWHM) of the C II 723-nm line were fitted with a linear function of the plasma electron density. An electron density n e = 10 17 cm -3 corresponds to a Stark FWHM of about 0. 1 nm or 1. 9 cm -1 in terms of wavenumbers. A very close value can be obtained from the Stark-B database  [9].
The C II 723-nm line profiles calculated by the various codes for n e = 10 17 cm -3 , T e = T iv = 2 eV and B = 0 are shown on Figure  4. As the profile calculated with WEAKZEE was obtained using Lorentzian functions with FWHM taken from the Stark-B database, it can be considered as a "reference" profile with a Stark width ∆σ 0. Several points can be noted from Figure  4. First, the calculations with SIMU and INTDPH as well as PPP-B* (PPP-B code but with MCDF atomic data) give lower Stark widths, i. e. ,    0. Note the agreement between SIMU/INTDPH and PPP-B * despite the differences between the used atomic physics: NIST atomic data for the former and MCDF data for the latter. Second, in term of Stark widths, the profiles obtained with PPP-B slightly higher than (    0 ) while those obtained with SCRAM are very close to (    0 ) the "reference" one.
Comparison to the Experimental Spectra As mentioned previously, the experimental data were obtained during the injection of a carbon pellet in the stellarator LHD. As all details concerning the experimental setup, the measurement system and pellet injection in LHD can be found in  [2] , we give here only the information necessary for the data analysis. The spectra were measured with a very high-resolution visible spectrometer. The instrumental function can be represented by a gaussian function with a FWHM ∆λ 1/2 = 0. 016 nm as compared to that of the high-resolution spectrometer used for the data of reference  [2]  (∆λ 1/2 = 0. 075 nm). The spectra were measured almost perpendicularly to the magnetic field. In addition, thanks to linear polarizers two spectra were obtained: horizontal spectrum (π-polarization) and vertical spectrum (σ-polarization).
However, the former factor has been dismissed by partial comparisons between line-shape codes using the same more accurate atomic physics data, i. e. , from the NIST ASD database. Therefore, the dispersion in Stark widths is attributed to differences in the electron collision operators used by the various line-shape codes. For the case with B = 4 T, the differences in the treatment of the Zeeman effect by the different codes make more difficult the interpretation of the results. However, it is clear that the weak-field approximation adopted by some of the codes is not valid for the upper level of the C II 723-nm line, i. e. , (3d 2 D°). Therefore, codes able to deal with intermediate magnetic fields (comparable Zeeman and fine structure splittings of energy levels) are more suitable. In addition to code-code comparisons, σand π-polarized experimental spectra of the C II 723-nm line, measured from the ablation cloud of a carbon pellet injected in LHD, were fitted using several line-shape codes.
MSG-SEVIRI Data The level-1. 5 image and cloud mask products were downloaded from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Earth Observation Portal (EOP) website (https://eoportal. eumetsat. int/). The level-1. 5 image data were converted into the top-of-the-atmosphere (TOA) brightness temperatures of MSG-SEVIRI channels 9 (10. 8 m) and 10 (12. 0 m) using the SEVIRI Pre-processing Toolbox (SPT) software. The LST retrieval algorithms  [22, 23]  were used to derive LST from the TOA brightness temperatures of MSG-SEVIRI channels 9 and 10. Only the pixels identified as clear sky over land in the cloud mask product were used in this study. To evaluate the performance of the proposed method, MSG-SEVIRI data on 28 January, 9 April, 31 July, and 1 October 2010 were used in this study.
MODIS Data The MODIS/Terra and MODIS/Aqua Land Surface Temperature and Emissivity Daily L3 Global 1-km SIN Grid products (MOD11A1 and MYD11A1, Collection 5) downloaded from the Reverb website (http://reverb. echo. nasa. gov/) were used in this study. The MOD11A1 and MYD11A1 products provide per-pixel LST and emissivity values at 1-km resolution using the generalized split-window algorithm  [24]. LST, observation time (local solar time), and quality control (QC) were extracted from the MOD11A1 and MYD11A1 products. Only the pixels flagged as good quality (i. e. , QC = 0) were used in this study.
Acknowledgments We would like to express sincere thankfulness to each of the persons who have permitted us to display some results of their work for the review paper. We would also acknowledge financial support from the  European community  thanks to the contract  DOTNAC (Development and Optimization of THz NDT of Aeronautics Composite  multilayered structures) -Contract  N 266320 / FP7-AAT-2010-RTD-1  -http://www. Figure 18 Reconstruction of Terakenstein: the original object (a), a detail of the metal screw inside de skull (b), a view from down-top (c) and a 3D reconstructed view (d) [201].
The pressure plate FIGURE 2 | Three water retention curves for each soil. (i) Measured (dark-blue points) using the pressure plate apparatus, (ii) Fitted (red line and crosses) on these measured points using the theoretical equation of the curve and (iii) (green line and black line) fitted on the measured water retention curve using a tensiometer. measurement data are given in Table  4. We can see from Figure  2 , the very good concordance of the curves coming from the two kinds of measurement. This confirms the validity of the relationship Equations (  20 ) and (  22 ) between the applied pressure and the corresponding matric (or pedostructural) water retention h. Moreover, as it can be seen in Table  3 , the fitting using the physical equation of the water retention curve on the points measured with the pressure plate apparatus, provides parameters (lines RpF and Vpf of Table  3 ) that are very close to those of the modeled curve coming from the tensiometer (lines R1, R2, V1, V2).
ACKNOWLEDGMENTS We acknowledge the  CEH (Center for Ecology and Hydrology, UK)  for having supplied the soil water release dataset (Chimney Meadow pF curves) that we used in this paper. We wish also to thank the following scientists for their help in this work:  Alain Betsogo Atoua  ( Master IRD ),  Estelle Hedri  (Valorhiz),  Josh Accola  (Master QEERI), and  Marc Lointier , (IRD).
Because of their ecological importance, amphipod crustacea are employed worldwide as test species in environmental risk assessment. Although proteomics allows new insights into the molecular mechanisms related to the stress response, such investigations are rare for these organisms because of the lack of comprehensive protein sequence databases. Here, we propose a proteogenomic approach for identifying specific proteins of the freshwater amphipod Gammarus fossarum, a keystone species in European freshwater ecosystems. After deep RNA sequencing, we created a comprehensive ORF database. We identified and annotated the most relevant proteins detected through a shotgun tandem mass spectrometry analysis carried out on the proteomes from three major tissues involved in the organism's reproductive function: the male and female reproductive systems, and the cephalon, where different neuroendocrine glands are present.
The interpretation of large-scale MS/MS data is only possible if a highquality database of nucleic acid sequences is available. Homology-driven proteomics using cross-species matching is a first alternative if the genome of interest is unknown, and de novo sequencing (i. e. interpretation of MS/MS data to establish the exact sequence of each peptide from scratch) is another possibility. However, major drawbacks of these two approaches lead to a scarcity of results as soon as a non-model organism, distantly related to a sequenced organism, is analyzed. Indeed, only highly conserved and ubiquitous proteins will be identified and carefully annotated with such approaches. It is noteworthy that lineage-specific genes are more likely to be linked to the organism's unique biology, as demonstrated by the characterization of the genome of Daphnia pulex, the water flea, a freshwater microcrustacean whose orphan genes have been shown to be among the most ecoresponsive  (1).
A novel approach that intimately combines genomics and proteomics, namely, proteogenomics, emerged (reviewed in Refs. 9 -11) after the pioneering work of Yates et al. (12) , which used combined expressed sequence tag (EST) databases translated into six reading frames for the interpretation of MS/MS spectra. Proteogenomics sensu stricto consists of better annotating genomes by means of high-throughput proteomic data, and this approach has been exemplified for several bacteria  (13, 14)  and eukaryotes  (15, 16). Numerous protein-encoding genes can be identified using mass spectrometry data when missed by automatic annotation software programs, or their structures can be corrected through experimental validation of their N-terminal translational starts. Recently, proteogenomics-style approaches in which genomesequencing data are used directly to interpret large proteomic datasets, and vice versa, have flourished, although they are not directly aimed at genome annotation or reannotation  (17) (18) (19).
On this basis, a sensu lato definition of proteogenomics has been discussed to qualify projects based on multi-omics data, with closely linked nucleic acid and protein information, including, typically, the use of six-frame translation  (20). In this vein, Ning and Nesvizhskii  (21) , Nagarai et al. (22) , Wang et al. (23) , and Woo et al. (24)  noted the interest of sample-specific protein databases established from RNA-Seq 1  data, which can enable a straightforward analysis of MS/MS data. Although comprehensive coverage of transcriptomes via RNA-Seq has been achieved for several marine species, studies on amphipods remain scarce and have been restricted to Parhyale hawaiensis  (25, 26)  and Melita plumulosa  (27). Here, we have documented gammarid reproductive function through the identification and characterization of novel proteins.
For this, we used a proteogenomic approach aimed at quickly pinpointing the proteins from G. fossarum, a model of interest in terms of ecotoxicology. After deep RNA-Seq of total RNAs of specific organs from individuals sampled in a wild population of gammarids, we created a six-readingframe translation protein database for interpreting a large shotgun tandem mass spectrometry dataset obtained in G. fossarum specimens. We detail and discuss the proteomes of key physiological organs: the female reproductive system, the male reproductive system, and the cephalon, where several neuroendocrine glands are located. To highlight protein candidates involved in reproductive physiology, we first performed comparative proteomics between the male and female reproductive systems to pinpoint key proteins with strong sexual dimorphism.
EXPERIMENTAL PROCEDURES Sampling and Maintenance of Animals-The amphipods were sampled at La Tour du Pin (latitude, 45°569Ј442Љ; longitude, 5°459Ј115Љ), upstream of the Bourbre River (mid-eastern France). This site has good water quality according to data records from the Reseau National de Bassin (French Watershed Biomonitoring Network) and accommodates high densities of gammarids. Sexually mature organisms were collected by kick sampling using a net. They were sieved (Ͼ2 mm), stored in plastic bottles containing ambient freshwater, and quickly transported to the laboratory. During an acclimatization period of at least 15 days, the organisms were kept in 30-l tanks continuously supplied with aerated, uncontaminated groundwater adjusted to the sampling site conductivity (i. e. 600 S cm Ϫ1 ).
Sequencing was performed on the Illumina/Solexa Genome Analyzer according to the manufacturer's instructions. Contig Assembly and Creation of a Customized Protein Sequence Database-EST sequence analysis and assembly were performed by the Skuldtech, Montpellier, France Company. ESTs were assembled into clusters using the Velvet and MIRA software programs. In order to obtain highly reliable consensus sequences, overlapping identity percentage and minimum overlapping length parameters were set to 90% and 30 bp, respectively. Contigs resulting from the assembly of multiple sequences are referred to as unique sequences, and sequences that do not fit into any assemblies are called singletons. Singletons are mainly chimeras or artifacts from cDNA synthesis, sequencing, or assembly, resulting in an increase of protein sequence errors, inappropriate frameshifts, and premature ORF terminations.
Thus, only the unique sequences were translated into six reading frames, resulting in a customized protein sequence database, named GFOSS, containing 1,311,444 sequences totaling 289,084,257 amino acids. Protein Extraction and Trypsin Digestion-For protein extraction, tissues were disrupted with 2 ml of cold protein lysis buffer with the TissueRuptor instrument (Qiagen). Homogenates were sonicated for 3 min using a Hielscher Compact Lab Homogenizer (amplitude of 30% and cycle 0. 3). Samples were centrifuged for 15 min at 12,000 ϫ g and 4 °C. Clear supernatants were collected and delipidated by the addition of 3 volumes of ethanol/diethylether solution (1:1, v/v) per 1 volume of sample, as previously reported by Simon et al. (29). The mixtures were vortexed and incubated on ice for 10 min. Samples were then centrifuged at 16,000 ϫ g for 15 min at 4 °C.
MASCOT Database Mining-Peak lists were generated with Mascot Daemon software (version 2. 3. 2, Matrix Science, London, United Kingdom) using the extract msn. exe data import filter (Thermo). Data import filter options were set to 400 (minimum mass), 5000 (maximum mass), 0 (grouping tolerance), 0 (intermediate scans), and 1000 (threshold), as described previously by Christie-Oleza et al. (30). MS/MS spectra were assigned to peptide sequences with the Mascot Daemon 2. 3. 2 search engine (Matrix Science) against the NCBInr protein sequence database or the GFOSS database. Searches for tryptic peptides were performed with the following parameters: full-trypsin specificity, mass tolerance of 5 ppm on the parent ion and 0. 5 Da on the MS/MS, static modifications of carboxyamidomethylated Cys (ϩ57.
0215), and dynamic modifications of oxidized Met (ϩ15. 9949). The maximum number of missed cleavages was set at two. All peptide matches with a MAS-COT peptide score less than a p value of 0. 05 were filtered by IRMa 1. 30. 4 software. A protein was considered validated when at least two different peptides were detected in the same experiment. The falsepositive rate for protein identification was estimated, through a search with a reverse decoy database, as less than 0. 1% using the same parameters in both the NCBInr protein sequence database and the GFOSS database. Statistical Data Treatment for Comparative Proteomics-Spectral counts (the number of spectra recorded per protein) were extracted from the spectra-to-peptide dataset, and the normalized spectral abundance factor for each protein was calculated as described previously  (31).
For comparative proteomics between male and female reproductive tissues, the data were analyzed with the Tfold module of the PatternLab software program. No specific normalization of spectral counts was applied, as strictly equal quantities of protein samples were analyzed. Fold change and p value cutoffs were set at 2 and 0. 05, respectively. The false discovery rate (Benjamini-Hochberg q-value) was 10%. The F-Stringency factor was systematically optimized. For analysis of the proteome dynamics along the different spermatogenesis stages, the data were clustered with the TrendQuest module of PatternLab. We retained in the final list of proteins for temporal profiling the proteins validated with at least two distinct peptides when merging all the data. Again, no specific normalization of spectral counts was applied.