dataesr/scientific-paragraphs-categorization huggingface dataset:
Bacterial Isolates The sources and characteristics of S. aureus isolates are provided in Table  S2. Some of these isolates had been included in previous studies as indicated in Table  S2   [16, 19, 22, 32, 39]. To represent global diversity, we included 154 isolates from 27 countries on five continents. Antimicrobial susceptibility was tested by using the microbroth dilution method according to DIN58940 and applying the EUCAST breakpoints. Spa-typing was performed according to the Ridom StaphType standard protocol (www. ridom. org) and spa-types were assigned using the respective StaphType software (Ridom GmbH, Wu ¨rzburg, Germany). MLST was performed as described previously  [40]. Primers for the detection of eta-, etband lukSF-PV-genes are summarized in Table  S8. The different lukSF-PV sequence variants were determined as specified by OHara et al.
Data Analysis Sequences from 115 loci were concatenated for each of 154 isolates, resulting in a 46,811-bp sequence alignment. A maximum likelihood tree based on this alignment was constructed with PhyML 3. 0. 1. The ancestral node was determined by including the genome sequence from distantly related S. aureus N315 (ST5; GenBank accession number BA000018). DnaSP was used to calculate the mean pair-wise distance between alleles at synonymous (Ks) and non-synonymous (Ka) sites and to estimate the nucleotide diversity (p) and nucleotide variation (hw)  [43]. The homoplasy index was estimated with Paup 4. 0. Short-term evolutionary rates and divergence dates were estimated by applying the BEAST software, version 1. 6. 2 (http://beast. bio. ed. ac. uk/)  [24] , dating sequences with the year of isolate sampling, and running 10 8 iterations after a burn-in phase of 10 6 iterations.
BEAST results were virtually independent from applied clock models (strict, relaxed) and tree priors (constant population size, Bayesian skyline). We applied Bayesian tip-association significance testing (BaTS, version 1. 0;  [28] ) to assess phylogeny-trait associations for clinical phenotypes, toxin gene complement, spa types, geographic origin, and antimicrobial resistance, each based on sets of 100 trees sampled from BEAST results. In each case, isolates for which the respective trait information was not available had been excluded from the initial sequence alignments. The association index (AI), the parsimony score (PS), and the maximum monophyletic clade (MC) statistics were computed  [28]. To avoid any inflation of the statistical significance of associations due to multiple, indistinguishable isolates in the dataset, calculations were repeated after excluding redundant isolates, and both sets of statistics are reported (Table  S4 ).
Genome Sequencing Staphylococcal genome sequences were generated commercially (GATC, Konstanz, Germany) on a 454 FLX machine, applying FLX+ chemistry and resulting in 12-to 21-fold average coverage. De-novo assemblies with 454 Newbler software resulted in 68 to 156 contigs (. 500 bp) per genome. Sequence annotation was performed by comparisons to previously published S. aureus genomes, applying the annotation tool implemented in Kodon software (Applied Maths), and by BLAST searches in the GenBank database (http://blast. ncbi. nlm. nih. gov/Blast. cgi). In addition, prophage sequences were identified with PHAST (phage search tool, available at http://phast. wishartlab. com/ [44] ). Genome-wide SNPs were ascertained by mapping the sequencing reads onto the N315 genome sequence (GenBank accession number BA000018), applying SSAHA2 software (available at http://www.
sanger. ac. uk/resources/software/ssaha2/) and filtering the resulting output for SNPs with a minimum consensus quality of 30, a minimum mapping quality of 30, and a minimum coverage of 5. SNPs in mobile genetic elements (SaPIs, prophages, transposons, IS elements), repetitive regions, homopolymeric regions, and within 100 bp from contig ends were removed manually, resulting in a dataset of 1,828 SNPs ascertained in the core genome of 2,208,736 basepairs. An alignment of core genome sequences from ten CC121 isolates and from the reference N315 was used to reconstruct a maximum likelihood phylogenetic tree with PhyML3. 01. The Recombination Detection Program (RDP 3. 44,  [45] ) was applied to screen the alignment for evidence of recombination based on the RDP, Geneconv, Chimaera, MaxChi, Bootscan, and SiScan methods (see RDP manual), applying default parameters and p,0.
Acknowledgments We thank  Mike Henkel ,  Annette Weller , and the staff at our central sequencing lab for excellent technical assistance, and  Elena Fuchs  for PVL sequences. We thank  Emma Nickerson ,  Premjit Amornchai  and  Vanaporn Wuthiekanun  for their assistance in isolating S. aureus in Cambodia and Thailand, and we are grateful to the staff of  Angkor Hospital for Children, Siem Reap, Cambodia.
02% RNase-free bovine serum albumin). Mouse antidigoxin and rabbit anti-HA (Sigma Aldrich) primary antibodies diluted to 1/100 in antibody dilution buffer were added for 2 h at room temperature. After three washes with antibody dilution buffer, cells were incubated for 90 min at room temperature with anti-mouse Alexa 488 and anti-rabbit Alexa 565 antibodies (Molecular Probes) diluted at 1/1000. Cells were washed three times in wash buffer (2Â SSC, 8% formamide and 2 mM vanadyl-ribonucleoside complex), twice with 1Â PBS, incubated with Hoescht (1/10000, Invitrogen Life Technologies) for 5 min at room temperature, washed three times with 1Â PBS, three times with water and mounted with Fluoromount (Invitrogen Life Technologies). Images representative from several cells (usually >100) obtained in independent experiments were obtained with a TCS SP5 AOBS Spectral Confocal Microscope (Leica Microsystems) and recovered and merged using the LAS AF Lite software (Leica Microsystems).
DDX3 and the HIV-1 gRNA form large cytoplasmic granules Our goal was then to determine the molecular mechanism by which DDX3 can affect translation of the HIV-1 gRNA. In particular, we wanted to investigate in which compartment of the cell the gRNA and the DDX3 protein can be found. For this, we carried out RNA in situ hybridization coupled to indirect immunofluorescence [RNA fluorescence in situ hybridization (FISH)-IF] and laser scanning confocal microscopy (LSCM) analyses. It should be mentioned that given the limited cytoplasmic space present in T-cells, we have used the HeLa cells model system. In preliminary experiments, we have checked that siRNA knockdown of DDX3 in HeLa cells resulted in the same effects on HIV-1 translation than those obtained in Jurkat (data not shown). Thus, we first transfected HeLa cells with the NL4-3 molecular clone together with a vector coding HA-DDX3.
The automatic analysis of large 3D point clouds represents a crucial task in photogrammetry, remote sensing and computer vision. In this paper, we propose a new methodology for the semantic interpretation of such point clouds which involves feature relevance assessment in order to reduce both processing time and memory consumption. Given a standard benchmark dataset with 1. 3 million 3D points, we first extract a set of 21 geometric 3D and 2D features. Subsequently, we apply a classifier-independent ranking procedure which involves a general relevance metric in order to derive compact and robust subsets of versatile features which are generally applicable for a large variety of subsequent tasks. This metric is based on 7 different feature selection strategies and thus addresses different intrinsic properties of the given data.
As a consequence, an appropriate interpretation of the captured data has to face certain challenges arising from either low or varying point density. We address the interpretation of large and densely sampled environments, i. e. the analysis of TLS and MLS point clouds, and focus on a detailed description of 3D structures. Hence, the main goal is to assign a semantic label to each 3D point in the scene. For this purpose, it has to be taken into account that 3D point clouds contain valuable geometric information which is implicitly represented by the spatial arrangement of single 3D points. In order to adequately describe this implicit information, the local neighborhood around each 3D point is typically recovered. Subsequently, geometric 3D features are extracted from the spatial arrangement of all 3D points within the neighborhood.
, 2011)  as well as classification trees resulting in sequences of rule-based classifications  (Xu et al. , 2012). Very recently, spatial inference machines have been presented which are based on modeling midrange and long-range dependencies inherent in the data and thus account for spatial semantic context  (Shapovalov et al. , 2013). For modeling context with a graphical model, the contextual relationships among 3D points in a local neighborhood have to be learned from a training set. Hence, exact inference is intractable and therefore only approximate inference techniques can be applied. Investigations show that the performance of recent approaches  (Munoz et al. , 2008; Munoz et al. , 2009b ) can signif-ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume  II-5/W2, 2013 ISPRS Workshop Laser Scanning 2013 , 11 -13 November 2013 , Antalya, Turkey icantly be increased by only introducing improved learning techniques for modeling interactions between single elements  (Munoz et al.
For solving the problem of multi-class classification, a SVM classifier composed of several binary SVMs and provided in the LIBSVM package  (Chang and Lin, 2011)  has been applied which is based on a one-against-one approach. Thus, for each pair of classes, a SVM is trained to distinguish samples of one class from samples of the other class. Since with TLS and MLS, many objects of similar shapes or at least similar geometrical behaviors are typically acquired (e. g. poles, wires, trunks or traffic lights), such a strategy may allow a better training step and subsequent discrimination of classes closely located in the feature space. In order to optimally select the parameter γ representing the width of a (Gaussian) radial basis function (RBF) kernel and the parameter C penalyzing classification errors, a cross-validation based on a grid-search in a suitable subspace (γ, C) is applied.
However, they have a risk of overfitting, require a huge computational effort and provide feature subsets optimized for the specified classifier only. Hence, the selected subset may be less suited in a different context which might for ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-5/W2, 2013 ISPRS Workshop Laser Scanning 2013, 11 -13 November 2013, Antalya, Turkey instance be important for subsequent tasks such as object detection. The embedded methods also provide a classifier-dependent selection which might be less suited for other tasks. Since the filter-based selection evaluates intrinsic properties of the given data, the respective results exhibit more generality. In order to avoid a classifier-dependent solution for deriving compact and robust feature subsets, we apply a filter-based feature selection where relevance is directly calculated from training data without involving learning techniques.
Dataset For evaluation, we use the Oakland 3-D Point Cloud Dataset 2  (Munoz et al. , 2008; Munoz et al. , 2009a)  which is a labeled benchmark MLS dataset representing an urban environment. The dataset has been acquired with a mobile platform equipped with side looking SICK LMS laser scanners used in push-broom mode. A separation into training set Y1, validation set Y2 and test set Y * is provided, and each 3D point is assigned one of the five semantic labels wire, pole/trunk, facade, ground and vegetation.
Microsatellite Genotyping and Analysis Eleven microsatellite loci developed in An. nili s. s. [27, 30]  were used to amplify An. carnevalei, An. ovengensis and An. somalicus DNA. Genotypes were determined for individual mosquitoes as previously described  [18]. Genetic diversity at each microsatellite locus within each sample was characterized by estimates of allelic richness (Rs)  [31]  and unbiased expected heterozygosity (He) under Hardy-Weinberg Equilibrium (HWE), using FSAT V2. 9. 3. 2  [32]. This program was also used to test for conformance of genotype frequencies to HWE for each locus and each sample, and to explore Linkage Disequilibrium (LD) between microsatellite loci. The frequency of null alleles at each locus within each population was determined using GENEPOP V4. 0  [33, 34] , and the allele and genotype frequencies were then adjusted accordingly in MICROCHECKER V2.
2. 3  [35]. The null allele adjusted dataset was compared to the original dataset to explore the effect of null alleles on estimates of genetic differentiation. Heterozygosity tests were implemented in BOTTLENECK V1. 0. 02  [36]  in order to assess deviation from Mutation-Drift Equilibrium (MDE). The tests were performed using the Stepwise Mutation Model (SMM) and the Two Phase Model (TPM), with 10-30% indels larger than one repeat unit. Statistical significance of the tests was assessed for each sample across all loci by the Wilcoxon signed-rank test available in BOTTLENECK. Bayesian clustering analysis was implemented in STRUC-TURE V2. 2  [37]  to estimate the most probable number of discrete populations or genetic clusters (K) in the dataset, while minimizing Hardy-Weinberg and gametic phase disequilibrium between loci within clusters, with no a priori assumptions of population structure.
Genetic Differentiation and Gene Flow The Bayesian clustering analysis using the software STRUC-TURE was implemented in the expectation that the genotypes would segregate into four main clusters corresponding to the four previously recognized species within the An. nili group. The optimal number of clusters detected based on the method of Evano et al. [38]  was K = 8 (Figure  1 ). Anopheles carnevalei, An. somalicus and An. ovengensis samples each formed a distinct and homogeneous genetic cluster, while five clusters were defined within An. nili s. s. Specimens sampled in savannah (Ako) and degraded forest (Nkolbisson) areas were merged together into a single genetic cluster, whereas four clusters were detected among populations sampled within the evergreen forest block: one in High levels of genetic differentiation were recorded between species.
DNA Sequencing Analysis rDNA polymorphism and divergence. The D3 domain of the 28S rDNA was amplified in 90 specimens (10 from each geographic population, and 20 from Moloundou) and the alignment length, including insertions/deletions (indels), was 382 bp (Figure  S1 ). No sequence polymorphism (p = 0) was detected within each geographical population, except in Moloundou where two highly divergent sequence variants were observed (p = 0. 034), corresponding to the Moloundou A and Moloundou B microsatellites clusters. Haplotypes detected in An. carnevalei, An. ovengensis and An. somalicus populations, and in An. nili s. s. from Ako and Nkolbisson were identical to those published by Kengne et al. [8]  and Ndo et al. [18]  (EMBL accession numbers: AJ429053 for An. nili s. s. , AJ429052 for An.
ovengensis, AJ438690 for An. somalicus and AJ429051 for An. carnevalei). The four remaining An. nili s. s. haplotypes were new and found exclusively in deep forest populations (GenBank accession numbers: KC189970-KC189973). They differed from one another, and from the deposited An. nili s. s. haplotype by 13 to 16 fixed nucleotide substitutions and many indels. Genetic distances between species' haplotypes ranged from 0. 3 to 5%. Similar genetic distances were also estimated between An. nili s. s. haplotypes, ranging from 0. 5 to 5. 9% (Table  S2 ). Likewise, there was no intra-population variation for the ITS2 region and the alignment length was 480 bp for An. carnevalei, 503 bp for An. ovengensis, 513 bp for An. somalicus, 451 bp for An. nili s. s. from Ako and Nkolbisson, 445 bp for An.
nili s. s. from Kentzou and Moloundou A and 480 bp for sequences from Ekelemba and Moloundou B (Figure  S2 ). ITS2 sequences also segregated into eight haplotypes, in straight correspondence with the 8 microsatellite clusters and the D3 sequence analysis. Four of these haplotypes were identical to those described earlier (EMBL accession numbers: AJ429048 for An. nili s. s. , AJ429049 for An. ovengensis, AJ438689 for An. somalicus and AJ429050 for An. carnevalei)  [8, 18]. The four new haplotypes were also observed in the deep forest An. nili s. s. populations (GenBank accession numbers: KC189966-KC189969). They differed from one another, and from the deposited An. nili s. s. haplotype by 30 to 95 nucleotide substitutions and many indels, suggesting high genetic divergence (Figure  S2 ). Genetic distances between species    S2 ).
This study was funded by a  UNICEF/United Nations Development Programme/World Bank/World Health Organization/TDR/Molecular Entomology  grant  A60347  to CAN and a  National Institutes of Health  grant  R21 AI079350  to IS. CN was supported by a student fellowship grant from the  French Institut de Recherche pour le Developpement (IRD). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
For primary and outcomes, student t-tests or Wilcoxon test if required, as well as covariance analysis to take the regression to the mean into account, will be used to compare means between experimental and control groups. Percentages will be compared using Chi-Square test, or Fisher's exact test if required. Calculations will be performed using SAS software. " 12a-i) Imputation techniques to deal with attrition / missing values the will be conducted to the intention to treat principle and handle missing data, multiple imputation will be used if the missing at random or missing completely at random hypothesis holds. " 12b) CONSORT: Methods for additional analyses, such as subgroup analyses and adjusted analyses "Percentages be compared using Chi-Square test, or Fisher's exact test if required.
Synchrotron radiation circular dichroism An MTSF1 protein solution at 2. 3 mg/ml was measured in 100 mM Tris-HCl buffer (pH 9. 0), 150 mM Na 2 SO 4 and 0. 05% (w/v) N-lauryl-sarcosine, on DISCO beamline at Soleil synchrotron (Gif-sur-Yvette, France). Four measurements, from 170 to 280 nm, with 1 nm intervals per second, were performed. For data processing, spectra of dialysis buffer were subtracted from those of corresponding samples. Spectra were analyzed down to 175 nm: this corresponds to a photomultiplier high tension remaining below half of its total variation. The 260-270 nm region was set to zero, and the resulting spectrum was calibrated with D-10-camphorsulfonic acid using the CDtool software  (40). Secondary structure determination was performed using ContinLL program in Dichroweb  (41).
Arabidopsis mtsf1 mutants are affected in a mitochondria-targeted P-type PPR protein The mtsf1-1 mutant was originally identified in a series of Arabidopis thaliana T-DNA mutants having insertions in nuclear genes encoding putative mitochondria-targeted PPR proteins. The mtsf1-1 mutant plants were classified among slow-growing mutants that can be cultivated relatively easily on soil under conventional greenhouse conditions (Figure  1A ). The implicated PPR gene corresponds to the AT1G06710 gene and encodes a 111 kDa protein comprising 19 PPR repeats [17 P-type and 2 Stype,  (6) ] according to motif predictions available on the FlagDB+ + database (Figure  1B ). A second mtsf1 mutant allele was identified and mtsf1-2 homozygous plants showed identical phenotypes to those observed in the mtsf1-1 mutant line, confirming that the growth alterations were due to the inactivation of gene AT1G06710 (Figure  1A  and B ).
All plant lines had a similar stomatal conductance (data not shown); therefore, our results suggest that the internal mesophyll CO 2 conductance was lower in mutants. Respiratory activity was measured as CO 2 production and oxygen uptake in the dark (Figure  3A  and B ). In both cases, measurements revealed respiratory activity that was two to three times higher in mtsf1 mutants compared with wild-type plants. To better understand the origin of this increase, the expression of alternative components of the respiratory chain was analyzed. Quantitative RT-PCR was conducted to determine the steady-state levels of mRNAs encoding alternative mitochondrial NAD/ NADH dehydrogenases (NDA and NDB) and oxidases (AOX) in mutant and wild-type plants. Most of these genes were overexpressed between 2 -to 4-fold in the mutants, except for the NDB4 gene, whose mRNA abundance was 60 times higher compared with wild-type plants (Figure  4A ).
FUNDING  Institut National de la Recherche Agronomique [INRA   UMR 1318 ];  Agence National de la Recherche  [ ANR-09-BLAN-0244 ];  French Ministe`re de l'Enseignement et de la Recherche  (to N. H. ). Funding for open access charge: [IJPB, INRA UMR1318].
The database described in this paper is the result of a community effort to produce the best calibration sets from the currently available data. A full list of the IntCal13 and Marine13 data sets, along with information on the online database structure and usage, and access to the database is available at http://intcal. qub. ac. uk/intcal13/. New data sets and changes or additions to data sets used in IntCal09 and Marine09 are summarized in the following sections. The data sets included within the accompanying SHCal13 curve are presented by  Hogg et al. (2013a, this issue).
Terrestrial 14 C Archives Tree rings: The IntCal09 calibration curve update did not include any changes to the IntCal04 treering data sets from 0-12,550 cal BP. For IntCal13, several additional data sets have been included to improve resolution, or to strengthen or extend the curve (Table  1 ). In addition, 1 correction was made to the database: the Swiss Ollon 505 (VOD505) larch tree had been matched to the Preboreal pine chronology (PPC) in order to fill a gap in IntCal04, but the match was later found to be erroneous  (Hogg et al. 2013b, this issue). These measurements have now been removed from the database  (decadal midpoints 11, 127. 5 cal BP). Measurements on an absolutely dendro-dated treering sequence to fill this gap were completed too late for the construction of IntCal13 and will be included within the next iteration of the IntCal curve.
2010). The multiple lake coring also reduces the likelihood of potential problems with slumps or hiatuses, which had additionally limited confidence in the previous chronology  (van der Plicht et al. 2004) , and the calendar age scale has been made more robust with the integration of both thin-section microscopic and µXRF methods  (Marshall et al. 2012; Schlolaut et al. 2012). The SG06 varve chronology and its link to U-series-dated speleothem chronologies is detailed by Bronk  Ramsey et al. (2012) , and the method for linking the SG93 cores is described by  Staff et al. (2013, this issue). Data for the period 10. 2-13. 9 cal kBP from the varved portion of this record have not been included as they would not contribute significantly to the much higher data density available from the tree-ring data sets.
Speleothems: 14 C measurements from 3 U-series-dated speleothems >14 cal kBP have been included in IntCal13 (Bahamas:  Beck et al. 2001 , Hoffmann et al. 2010; Hulu Cave: Southon et al. 2012). Corrections for dead carbon fraction (DCF) in each sample are assumed to be constant and estimated from the period of overlap with the IntCal13 tree-ring data set (10-13. 9 cal kBP). The use of an ultra-low-blank processing line for analysis of Bahamas speleothem  GB-89-25-3 (Hoffmann et al. 2010)  indicated that an incorrect sample-mass 14 C-blank dependence used previously for GB-89-24-1  (Beck et al. 2001 ) had produced artifacts in the older part of that record. Consequently, only data from the 14 to 26 cal kBP section of GB-89-24-1 are included in IntCal13, and a revised blank correction has been implemented for these data.