dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments We thank  Dr. M. Sztiller-Sikorska  and  Dr. J. Jakubowska  for cell isolation and melanosphere/monolayer propagation,  Dr. K. Koprowska  for her help in flow cytometry,  Dr. P. Dessen  for his important contribution to the microarray data analysis,  Dr. M. Duechler  for stimulating discussion and suggestions and  K. Niewinna  for excellent administrative and technical support.
GPS data from 181 permanent stations extracted from different networks covering France and the Italian part of the Alps are used to estimate a homogeneous set of tropospheric parameters over 14 years (from January 1998 to May 2012). The tropospheric zenith delay (ZTD) quantified in the GPS data analysis is closely related to the value of integrated water vapor above each GPS station. GPS ZTD is already successfully used for operational weather prediction and meteorological analyses, providing valuable data to improve our comprehension of the tropospheric water cycle and in particular to improve the prediction of precipitations. Moreover, GPS tropospheric measurements are intrinsically stable, so that long term observations represent a significant contribution to climatological studies. The results of a homogeneous reanalysis of up to 14 years of data with MIT's GAMIT/GLOBK software version 10.
15 old permanent stations (13 IGS and 2 EUREF stations) have been included in the analysis (red circles in Fig. 1 ) to obtain a stable Reference Frame for the entire time span. As one particularity of the RENAG network is site stability over the long term, the total of its present stations is included in the analysis. We also analyzed all stations made available by the Liguria and Piemonte regions. Then, the network coverage was completed in the Alpine and Mediterranean regions by subsets of stations from RGP, AGNES, GEODAF, RING and GAIN. The 181 station names and their coordinates can be found in the Appendix. The data analysis covers the time interval from January 1998 to May 2012, representing more than 14 years of observations. From the 181 stations, 50 stations provide more than 10 years of data and 57 stations between 5 and 10 years of data.
GPS DATA ANALYSIS The software used for the GPS data analysis is GAMIT/GLOBK ver. 10. 4  (Herring et al. , 2010)  developed at the Department of Earth Atmospheric and Planetary Sciences, MIT (Robert W. King -rwk@chandler. mit. edu). The estimated tropospheric parameters are 1 ZTD every 2 hours and one couple of horizontal tropospheric gradients (NS and EW) every 3 hours for each of the 181 stations, simultaneously with a daily positioning solution. The troposphere is modeled using the empirical GMF mapping function  (Boehm et al. , 2006b)  for its homogeneity over the study time span. It is in particular independent from weather models, unlike the VMF1 mapping function  (Boehm et al. , 2004 (Boehm et al. , , 2006a)) , constraint by 6 hourly ECMWF analysis results and nowadays widely used. Moreover, we use the GPT model  (Boehm et al.
ZTD DATA BASE The data that we will make available in the HyMeX data base on www. hymex. org are: full lists of station coordinates, station characteristics according to Table  1 , ZTD time series with formal errors, NS and EW gradient time series with their formal errors. We chose to provide high quality geodetic information with the homogeneously calculated time series using an up-todate data analysis strategy, including a quality control. This information is ready and available for highly precise exploitation. Dependent on the application, users can chose their algorithm for ZTD/gradient trend estimation, conversion from ZTD to PWV using pressure and temperature from synoptic networks or weather models, etc.
CONCLUSIONS GPS data from 181 permanent stations extracted from different networks covering France and the Italian part of the Alps are used to estimate a homogeneous set of tropospheric parameters over 14 years (from January 1998 to May 2012). The quality checked data base of ZTD and gradient values will be published in the framework of the international HyMeX project (www. hymex. org). The tropospheric parameters are obtained in a GPS network that is particularly dense in the Mediterranean region and over the French-Italian Alps. Both are interesting test areas for meteorological and climatological analyses, so that our ZTD/gradient data base will constitute a significant contribution to such studies. Thanks to the length of the data set in time, a regional climatological approach could permit identifying specific patterns of ZTD variation that are related to severe weather events.
ACKNOWLEDGEMENTS Thanks to (in alphabetical order for affiliation)  Ernesto Benazzo  and  Giacomo Refiorentin  ( Arpa Piemonte ),  Marco Mozzon  ( Leica Geosystems ),  Giuliano Molinelli  (Geotop),  Davide Freppaz  and  Claudio Lucianaz  ( Fondazione Montagna Sicura ),  Ambrogio Manzino ,  Chiara Porporato  and  Marco Roggero  ( Politecnico di Torino ),  Anna Cerrato  and  Andrea De Felici  ( Regione Liguria ),  Mattia De Agostino  and  Gianbartolomeo Siletto  ( Regione Piemonte ),  Elmar Brockmann  (Swisstopo),  Vittorio Casella  and  Marica Franzini  ( Università di Pavia ) and many others to make GPS data available. DS' visiting professorship in Grenoble in June/July 2012 was sponsored by  Observatorie des Sciences de l'Université de Grenoble (OSUG).
Genome sequencing of D. solani 3337 Two DNA-libraries were constructed by Eurofins Genomics (France) using the TruSeq(TM) SBS v3 sequencing kit: a shotgun (SG) paired-end library with a fragment size between 150 to 500 bp and a long jumping distance (LJD) mate-pair library with an insert-size average of 5. 7 kbp. The two libraries were sequenced using 2×100 bp paired-end read module of IlluminaHiSeq 2000 by Eurofins Genomics (France). Reads were trimmed on quality and length. Sequence assembly was carried out using the CLC Genomics Workbench v5 (CLC bio, Aarhus, Denmark) with a read length of 0. 5 and a similarity of 0. 8. Forty-two contigs were obtained with a length ranging from 2. 1 to 483 kbp. The scaffolding was processed using SSPACE basic v2. 0  [15].
As the genome annotation of D. dadantii 3937 was performed in 2004 with the version 2 of Glimmer, this genome was also reannotated with the same RAST server in order to compare genes predicted with the same algorithm. In D. solani 3337, the remaining gaps affect 15 genes that were not considered in the subsequent analysis. Synteny analysis was performed by using the MAUVE software  [18]. Average nucleotide identity (ANI blast) was computed using the Jspecies package  [19]. Genome to genome comparison was performed by bi-directional protein-protein BLAST sequence comparison of translated open reading frames (ORFs) with a 10 -5 e-value threshold. Genes of both species were considered as strain-specific if identity of the encoded protein was lower than 80% of full-length amino acids sequence.
8 of identity on 0. 5 of read length). Using such in silico DNA-DNA hybridizations, a high proportion of mapped reads will indicate a strong identity between genome sequences. Then, the mapping files constructed using high stringency parameters were processed for SNP analysis. In addition, the presence of genomic clusters in the D. solani and D. dadantii species was searched with a nucleotide BLAST analysis using the sequences of the specific clusters as queries against a database constituted by the D. solani and D. dadantii genomes (e-value threshold = 10 -50 ). The search for the presence of D. solani-specific and D. dadantii 3937 specific-genes in other Dickeya species was performed by bi-directional protein-protein BLAST sequence comparison (e-value threshold 10 -5 ) with the D. paradisiaca 703 strain (formerly named D.
Genome accession numbers The D. solani 3337 genome sequence has been deposited at DDBJ/EMBL/GenBank under the accession n°A MYI00000000. Sequence data used in this article can be found in the GenBank/EMBL data libraries under the following accession numbers: D. solani strains IPO2222 (CM001859), MK10 (CM001859), MK16 (CM001842), LMG25865 (CM001860), and D. dadantii strains 3937 (CP002038), NCPPB3537 (CM001982), NCPPB898 (CM001976).
General features of the D. solani 3337 genome The published sequence of D. solani 3337 is composed of eleven contigs (from 4. 5 kbp to 1. 11 Mbp) grouped in a single scaffold with 1,075 coverage in average. The in silico approach permits to close 32 gaps and to map the 7 rrs regions. Hence, the D. solani 3337 genome consists of a unique 4. 9 Mb circular chromosome with a 56. 1% GC content and contains no plasmid. These features are in accordance with data of the Dickeya genome and draft genomes that are available in public databases  [7, 21]. Using the RAST server with the Glimmer 3 caller, gene prediction and automatic annotation predicted 4530 protein-coding sequences, 72 tRNA genes and 7 rRNA regions.
Among them, 506 D. solani 3337 and 617 D. dadantii 3937 genes encode hypothetical proteins having no related proteins in databases. It should be noted that 2/3 of them encode peptides of less than 60 amino acids for which transcription and translation is questionable. It should also be noted that only some thirty genes in each genome present sequence changes leading to the production of a truncated or out of phase protein (see Additional file 2: Tables  S2  and S3 ), indicating that only a few strain-specific genes result from mutations in the corresponding gene in the other genome. For 250 and 343 of these strain-specific genes respectively, a function is known or predicted, and for each strain about 200 genes are absent from other sequenced Dickeya species (Table  1 , Additional file 2: Tables  S2  and S3 ).
While about 40% of the D. dadantii 3937 strain-specific genes of known or predicted function (147 genes) are related to mobile elements or phages functions, only 30 such genes were identified in D. solani. This is due in part to the presence of a Tn4371 ICE (Integrative Conjugative Element) family element in GR5 (Additional file 2: Table  S3 )  [42]  and a complete prophage with morphogenesis genes related to Haemophilus HP1 and HP2 genes in D. dadantii 3937       S2 ) encompass 51 genes (solani_g3_4305 to solani_g3_4355), D. dadantii 3937 genomic island (GR17, Figure  1  and Additional file 2: Table  S3 ) encompasses 65 genes (3937_g3_3041 (locus tag Dda3937_00080) to 3937_g3_3105 (locus tag Dda3937_01864)). The purple diagrams represent the gene conservation in one region as compared to the other as calculated by the MAUVE software.
For PKS activity, an acyltransferase (AT) domain is also required. This AT activity may be provided either by an AT domain incorporated in each module or by discrete free-standing acyltransferase enzymes in the case of  trans-AT PKSs. The core module of NRPS consists of an adenylation (A) domain for the selection of one amino acid, a peptidyl carrier protein (PCP) and a condensation domain (C) for catalysing peptide bond formation  [45]. Among the D. solani genomic regions, GR3 regroups 7 genes related to metabolism among which 3 genes encoding NRPS that regroup 4 synthetic modules, one trans-acetyltransferase and a trans-AT PKS of 4 modules. This gene cluster appears to be specific to some Dickeya since it is found only in D. zeae 586 in databases. GR9 regroups 14 metabolic genes among which 7 genes encoding trans-AT PKS modules and two trans-AT encoding genes.
Mapping of the D. solani 3337 reads on the D. solani and D. dadantii present in databases reveals the high similarities of the genomes of the D. solani species (Figure  6A ). This result reinforces the preliminary data obtained using single-gene sequence data  [6]. The same procedure with the generated reads of D. dadantii 3937 revealed that the D. dadantii strains are more diverse in their genomic content (Figure  6B ). These in silico genome-hybridization method clearly separated the two species (Figure  6A  and B ). The high genome similarity among D. solani isolates is confirmed with SNP analysis. Only 200 to 300 SNPs were detected between the genome of D. solani 3337 and the other D. solani genomes (Figure  6C ). In contrast, at least 80,000 SNPs were detected between the D. dadantii 3937 genome and the genome of the other tested D.
Figure4Genetic organisation of the D. solani 3337 and D. dadantii 3937 genomic islands. D. solani 3337 genomic island (GR24, Figure1and Additional file 2: TableS2) encompass 51 genes (solani_g3_4305 to solani_g3_4355), D. dadantii 3937 genomic island (GR17, Figure1and Additional file 2: TableS3) encompasses 65 genes (3937_g3_3041 (locus tag Dda3937_00080) to 3937_g3_3105 (locus tag Dda3937_01864)). The purple diagrams represent the gene conservation in one region as compared to the other as calculated by the MAUVE software. The vertical lines link the conserved parts of the D. solani small region that is split by the insertion of additional genes in D. dadantii.
Acknowledgements This work is supported by  CNRS  ( Gif-sur-Yvette ),  Comité Nord Plants de Pomme de Terre (CNPPT/SIPRE) ,  Fédération Nationale des Producteurs de Plants de Pomme de Terre  ( FN3PT/RD3PT ) and  Association Nationale de la Recherche et de la Technologie  ( ANRT-CIFRE n°1282/2011 ). We thank  Slimane Khayi  ( PhD University Paris Sud-University of Meknes ) for calculating SNP number between D. solani 3337 and Ds0432-1, and  David Bonnaffé  ( ICMMO, University Paris Sud ) for providing galactonate and galactonate γ-lactone. NOTE ADDED IN PROOF: during the submission process of the manuscript, the genome of the D. solani strain Ds0432-1 [47] was released (GenBank  AMWE00000000 ). It exhibits similar genomic characteristics as D. solani 3337. 87 SNPs were detected between the genome of D.
ACKNOWLEDGMENTS We thank  Woodward Fischer  for providing samples crucial to this work. Funding to Lyons from the  NASA   Exobiology Program , the  NASA Astrobiology Institute , and the  National Science Foundation  (NSF) supported this research. Lu is supported by  NSF  grant  OCE 1232620. Bekker's participation was made possible by funding provided via a  Natural Sciences and Engineering Research Council of Canada   Discovery Grant. Philippot acknowledges support from  UnivEarthS LabEx.
doi:10. 1093/molbev/msu305 MBE and Methods). As the patterns between the two distance metrics were highly similar, only raw distances are discussed in this article. With the 100 simulated alignments, the corresponding Sunaware trees were reconstructed either with PhyML  (Guindon et al. 2010 ) and the site-homogeneous LG model  (Le and Gascuel 2008)  or with PhyML-CAT  (Le, Gascuel, et al. 2008 ) and the site-heterogeneous C60 model (originally used to simulate sequences, see Material and Methods). To compute the S-aware trees, that is, reconciled gene trees that maximize the joint sequence-reconciliation likelihood, the amalgamated likelihood estimation (ALE) program (Szo ¨llo 00 si,  Rosikiewicz, et al. 2013 ) was used, with the cyanobacterial species tree computed by Szo ¨llo 00 si et al.
S2 , Supplementary Material online) illustrates that the difference in substrate affinity is considerable. Furthermore, the K M (IPM) of LeuB S-unaw is substantially higher than the highest K M (IPM) value in the BRENDA enzyme database (www. brendaenzyme. org). In terms of turnover rate (k cat ), LeuB S-unaw exhibits a greater than 2-fold higher k cat than LeuB S-aw. Although LeuB S-unaw exhibits a high turnover rate, its high K M for IPM suggests that the substrate would have to be present at a very high concentration inside the cell for binding to actually occur. The thermoactivity profiles of the two resurrected enzymes reveal that they are highly thermophilic with T opt values greater than 75 C (table 1 and fig. 4a ). We also determined the ÁG z NÀU values for these enzymes, as we have previously found this parameter to be a useful measure of a biologically realistic enzyme  (Hobbs et al.
2012) , we cannot exclude that our results are not affected by a similar bias. However, we do not anticipate any reason for which this bias would lead us to question our predictions, as we expect that the increase in ASR accuracy due to the use of S-aware trees would also apply with another ASR method, such as Bayesian Inference. 2) To reconcile species and gene information, we used the ALE program (Szo ¨llo 00 si,  Rosikiewicz, et al. 2013). For the moment, different uncertainties are not accounted for in the reconstruction of ancestral sequences along S-aware trees. For instance, to what extent species tree reconstruction or incomplete lineage sorting impact ASR in our new methodology is currently unknown. Plus, ALE makes use of a time-calibrated species tree to compute the probabilities of horizontal gene transfers during the reconstruction of S-aware trees.
Data Used for In Silico Experiments and Substitution Models To perform in silico experiments to investigate the influence of the phylogenetic tree on ASR, we used the data set from Szo ¨llo 00 si et al. (2012). This data set comprises 1,099 gene families from 36 cyanobacterial genomes available in the HOGENOM database  (Penel et al. 2009 ). The phylogenomic species tree of these 36 species that Szo ¨llo 00 si et al. (2012) reconstructed was also used in the present study. With this species topology and a newly described model of gene tree/ species tree reconciliation, Szo ¨llo 00 si,  Tannier, et al. (2013)  computed the reconciled S-aware trees for the 1,099 families. Here, we randomly chose 100 families out the 1,099 and we simulated sequences along their corresponding S-aware tree topologies, that we considered as true gene trees.
This model is a mixture of profiles, with a single Poisson exchangeability matrix that is assigned to all components (profiles) of the mixture (see supplementary material, Supplementary Material online). Consequently, this model contains 60 Â 19 + 59 = 1,199 empirical parameters to describe the substitution process. Alignments were simulated using the original alignment sizes of the 100 cyanobacterial families. Simulations were performed with our own C++ program depending on Bio++ libraries  (Gu eguen et al. 2013). For a given alignment, because sites are supposed to evolve independently, all 60 components of the mixture were used to simulate subalignments with a number of sites proportional to their empirical weight, with all subalignments being subsequently concatenated to produce the final alignment.
To efficiently explore the space of all reconciled trees according to the joint sequencereconciliation likelihood that combines sequence information and information on the species phylogeny, Szo ¨llo 00 si,  Rosikiewicz, et al. (2013)  proposed the ALE algorithm. ALE makes use of a sample of S-unaware gene trees (for instance, a sample of posterior trees produced by a Bayesian program such as PhyloBayes  (Lartillot et al. 2009 )) to compute conditional clade probabilities (Ho ¨hna and Drummond 2012), which are used to approximate the PP of all gene trees that can be amalgamated from clades present in the sample. ALE was used to perform all S-unaware gene tree/species tree reconciliations for both simulated and biological (see below) data sets. For each simulated alignment, PhyloBayes (version 3.
Acknowledgments The authors are grateful to  Bastien Boussau ,  Laurent Duret ,  Vincent Daubin ,  Eric Tannier , and  Nicolas Lartillot  for fruitful comments and suggestions. This work was supported by the  French Agence Nationale de la Recherche (ANR)  and is a contribution to the  Ancestrome  project ( ANR-10-BINF-01-01 ). G. J. S. was supported by the  Marie Curie CIG 618438 "Genestory"  and the  Albert Szent-Gyo ¨rgyi Call-Home Researcher Scholarship   A1-SZGYA-FOK-13-0005  supported by the  European Union  and the  State of Hungary , cofinanced by the  European Social Fund  in the framework of T  AMOP 4. 2. 4. A/1-11-1-2012-0001  " National Excellence Program. ".
The Mediterranean region is characterized by its vulnerability to changes in the water cycle, with the impact of global warming on the water resources being one of the major concerns in social, economical and scientific ambits. Even if precipitation is the best-known term of the Mediterranean water budget, large uncertainties remain due to the lack of suitable offshore observational data. In this study, we use the data provided by the Advanced Microwave Sounding Unit-B (AMSU-B) on board NOAA satellites to detect and analyze precipitating and convective events over the last decade at spatial resolution of 0. 2° latitude × 0. 2° longitude. AMSU-B observation shows that rain occurrence is widespread over the Mediterranean in wintertime while reduced in the eastern part of the basin in summer.
The spatial resolution (5-60 km) of PMW sensor is constrained by the antenna size, but it still has adequate resolution for global and regional (such as the Mediterranean basin) climatological studies. PMW captures the precipitation characteristics and provides a better measure of precipitation than IR, even if IR tracks faithfully the movement of precipitating system  [9]. Since polar-orbiting satellites that carry microwave sounders overpass the same point on the globe roughly twice daily, infrared observations from geostationary satellites have been consistently used for the characterization of diurnal aspects of precipitation. However, with the launch of a series of Advanced Microwave Sounding Unit (AMSU) instruments on board several platforms, the number of overpasses has increased significantly, providing an unprecedented opportunity to explore microwave-based data to characterize precipitation and convection over the Mediterranean region in a diurnal timescale.
In this paper, we use the data provided by the AMSU-B radiometer (replaced on recent platforms by the Microwave Humidity Sounder, or, MHS), which permits a concomitant observation of convection/precipitation over land and sea at a temporal resolution higher than that of meteorological analyses and with a spatial resolution of roughly 20 km. Brightness temperatures measured since 1999 by channels of the AMSU-B and MHS sensors in the water vapor absorption line (183-191 GHz) allow a screening of precipitation over the whole Mediterranean region, including the sea, where in situ observations are scarce, providing a complementary and completely independent picture from studies based on reanalysis and ground station data. The present work aims at better characterizing the occurrence of precipitation and convection over the Mediterranean basin at a regional scale over the last decade.
Climatological features of precipitation at regional scale will be presented with an emphasis on the Mediterranean Sea, separating moderate rain (MR) and deep convection (DC) occurrences following Funatsu et al. [16]. Comparisons with the widely used HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) observational dataset with a spatial resolution of 0. 5° × 0. 5° latitude-longitude, and with the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis interim (ERA-Interim; resolution of 0. 75° × 0. 75° latitude-longitude) will also be discussed in order to illustrate the advantages and shortcomings of AMSU-B products. The paper is organized as follows. Section 2 describes microwave AMSU-B satellite observations and diagnostics used to detect precipitation and convection occurrences, and the other precipitation datasets considered in this paper.
AMSU-Based Precipitation and Convection Occurrence Since this dataset has been described in details in a recent paper  [17] , we recall here only the most important points. This study mainly uses the AMSU-B sensor, which is a cross-scanning microwave instrument flying on board NOAA sun-synchronous polar-orbiting satellites since late 1998. AMSU-B has three channels (3 to 5) centered around the water vapor absorption line (183 GHz) and has 90 fields of views (FOVs) along a wide (~2300 km) swath. FOV of AMSU-B ranges between 16 km at nadir and 36 km for the largest viewing angles  [18]. This sounder was initially designed for optimal moisture retrieval, but a number of studies have shown its utility for rainfall detection (e. g. ,  [19, 20] ). More details can be found in the NOAA's KLM User's Guide (http://www2.