dataesr/scientific-paragraphs-categorization huggingface dataset:
EST Library Construction and Assembly The transcriptome reported in this study comprises 15,052 sequences, which is less than the estimated number of genes in the cnidarian genomes described to date  (32,338, 27,273 and 23,668  for Hydra magnipapillata, Nematostella vectensis, and Acropora digitifera, respectively). The raw reads were also assembled by MIRA 3. 02 software  [54]  which produced a significantly higher number of contigs (48,075 ), however, a comparison between the two assemblies demonstrated that Newbler assembly was much less fragmented (data not shown), and hence was used for downstream  analysis. We assume that the low number of contigs assembled is due to limited coverage, and that Newbler software produced an uncompleted albeit un-fragmented EST library.
Based on similarity searches performed in an EST library from Acropora millepora  [3, 54] , Reyes-Bermudez et al. [55]  reported the sequences of three genes encoding galaxin-related molecules and their expression patterns during settlement and metamorphosis. A fourth galaxin protein, galaxin 2, has been characterized by Shinzato et al. [7] , based on the sequencing of Acropora digitifera. blastX and blastn searches of the galaxin sequences against the S. pistillata EST library identified two ESTs with strong similarity. A phylogenetic tree generated by MrBayes program classified these ESTs to galaxin 2 and galaxin-like 1 (Figure  7 ). No homolog for Amgalaxin-like 2 was found, probably since its expression is restricted to post-settlement polyps and is not observed in adults  [56]. The presence of an Amgalaxin-like 1 homolog in an adult expression library is surprising, as Reyes-Bermudez et al.
Functional Characterization Concerning the functional classification, half the transcripts show similarity to sequences in the KEGG database (51%). The distribution of functional classes is consistent with those in both the human and fruit fly complete proteomes  [56] , with the most abundant categories being RNA processing and modification (A) signal transduction (T), protein turnover (O), and translation (J), indicating that the coverage of the EST library presented here was adequate (Figure  5 ). We decide to focus on the Wnt and BMP signal transduction pathways because of their importance in coral development  [4]. These two pathways do not share any major components and can function independently of each other, which is accomplished by means of different ligands, different receptors and different cytoplasmic and nuclear signal transducers.
Conclusions Databases of expressed sequence tags have become a widely used tool in fundamental biological research, primarily due to the considerable resources now available for searching novel gene sequences. Our study of the ubiquitous robust coral Stylophora pistillata provides an opportunity to explore a series of questions concerning comparative and functional genomics and the evolutionary relationships among the stony corals and invertebrates in general. In conducting this study, we have been able to investigate the ancestry of several important metazoan genes. The basal phylogenetic position of the anthozoans and the surprising extent to which key genes appear to have been conserved between Cnidaria and chordates implies that further research in corals is likely to provide unique perspectives on common molecular principles of animal development.
Most of our knowledge on the physiology of coral calcification comes from studies in Stylophora pistillata, the present EST library will constitute a valuable tool for determining the molecular mechanisms underlying coral growth and development and the molecular targets of environmental disturbances such as global warming and ocean acidification  [61]. Figure  7. Galaxin phylogenetic tree. Galaxin and Galaxin-like sequences from different species: Spi-Stylophora pistillata, Adi-Acropora digitifera, Ami-Acropora millepora, Gfa-Galaxea fascicularis were used for phylogenetic analysis. The tree was constructed using Mrbayes program  [46]. doi:10. 1371/journal. pone. 0088615. g007.
Acknowledgments We are grateful to  Dominique Desgre  ´for coral maintenance and to  Dr. Tirza Doniger  for assistance in analyzing the data. This study was conducted as part of the  Centre Scientifique de Monaco Research Program , supported by the  Government of the Principality of Monaco. We also would like to thank  The Interuniversity Institute for Marine Sciences in Eilat (IUI)  for the support in this research.
West Pomerania. The University of Greifswald is a member of the 'Center of Knowledge Interchange' program of the Siemens AG and the Cache Ćampus program of the InterSystems GmbH. There are no patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors at the time of submission.
Genotyping and imputation Genotyping was conducted separately in each study using Affymetrix or Illumina platforms and included from ,300,000 to ,1,000,000 genotyped single nucleotide polymorphisms (SNPs). Genotype quality control and data cleaning based on individual call rate, SNP call rate, and/or Hardy-Weinberg equilibrium thresholds, and performed independently by each study. Genotyped data were imputed in each study separately to the ,2. 6 million SNPs identified in the HapMap II Caucasian (CEU) sample from the Centre d'Etude du Polymorphisme Humain  [26, 27]. More details about genotyping and imputation are given in the online supporting information (S1 Methods and S2 Table ).
Estimates of studyspecific genome-wide interactions were then meta-analysed applying inversevariance weighted fixed-effect models. To account for population stratification, study-specific test statistics were corrected using the method of genomic control  [28]. SNPs with a low minor allele frequency (MAF) (,0. 05) and a low imputation quality (observed to expected variance ratio ,0. 3) were omitted from the meta-analyses. The meta-analyses were performed using the software METAL developed for genome-wide data  [29]. To assess heterogeneity, the I 2 index was computed for each interaction estimate assuming that an I 2 index around 25% or below indicates no or low and around 50% moderate heterogeneity as suggested by Higgins et al  [30]. Genome-wide significance of interaction was defined as a p value ,5.
See the supporting information file S1 Funding for the complete funding statement. The authors have the following interests: The  Framingham Heart Study (FHS)  was supported by the  National Heart, Lung and Blood Institute's Framingham Heart Study  (Contract No. N01-HC-25195 ) and its contract with  Affymetrix, Inc  for genotyping services (Contract No. N02-HL-6-4278 ). The  PROSPER/PHASE study  was supported by an investigator initiated grant obtained from  Bristol-Myers Squibb. Dr. Kavousi  is supported by  AXA Research Fund. Oscar H. Franco  works in ErasmusAGE, a center for aging research across the life course funded by  Nestle Nutrition (Nestec Ltd) ,  Metagenics Inc , and AXA. Part of the SHIP study was funded by a joint grant from  Siemens Healthcare, Erlangen, Germany  and the  Federal State of Mecklenburg.
We thank  Christophe Grojean  and  Ennio Salvioni  for many helpful discussions. CW gratefully acknowledges additional funding from the  IPPP  beyond his studentship, and from the  French ANR ,  Project DMAstroLHC ,  ANR-12-BS05-0006. MS acknowledges the hospitality at the  CERN TH division  and the funding of his work by the  Joachim Herz Stiftung. The work of AW was supported in part by the  German Science Foundation (DFG)  under the  Collaborative Research Center  (SFB)  676. This work was supported in part by the  STFC.
LIDAR information is used to calibrate the brightness temperatures with the absolute altitude. Clouds with small optical depths may be observed with temperatures that do not correspond to the actual altitudes. In this case, LIDAR information that aims to distinguish between clear atmosphere and clouds with given thresholds in optical depth may label the EAS events taking place in such regions. For details regarding instrument, operation, data treatment, etc. of the AM system, see Ref. [7, 8, 16, 17]. In the following sections, we estimate the efficiency of the EAS observation in atmospheric conditions, with and without clouds, using dedicated simulation studies for the JEM-EUSO mission. We also analyze the cloud coverage using available databases from meteorological missions. Combining both factors, we estimate the overall observation efficiency with a perspective towards event reconstruction.
They result from a complex system of geographical, eg. land versus ocean, meteorological, and other factors (see Ref. [11, 29]  for discussion). We investigate the TOVS database, covering a period of   As previously mentioned, such conditions do not or only slightly affect the apparent signals of EASs. Therefore, a high occurrence of these conditions is advantageous for EAS observations. In addition to the argument in Table  3 , the global average is 61% for the occurrence of favorable conditions. It is worthwhile to mention that there are regions with distinctly low and high occurrences. The former regions are found in land around equatorial zones that coincide with tropical rainforest climate in Köppen classification  [30]. The latter widely appear above oceans, especially in the South Hemisphere.
High-clouds, with relatively small optical depths, only slightly attenuate the photons from the EAS. In this case, the information on the EAS tracks with its temporal development is obtained with little or no disturbance. This allows for the EAS events obtained in such condition to be used for arrival direction distribution analysis. The estimated energy is potentially affected, seen as if the EAS is of a lower energy. For those atmospheric conditions, the importance of atmospheric monitoring is more pronounced. To tag these kinds of events, the region in the FOV with such an atmospheric condition are identified in the AM system within its sensitivity  [8]. The overall influence of the clouds is more dependent on their climatological properties. The analyses of TOVS and CALIPSO databases show consistent distributions of clouds sorted by the expected degrees of influence to EAS observation.
The average cloud properties from the TOVS database studied in Ref. [11] , is found to be in good agreement with the result from the CALIPSO database. Referring to the TOVS result, the occurrence of clear atmosphere is 32%. One can assume that this case guarantees good condition for both ground-based and spaced-based observations. Moreover, for the space-based observation, the cumulative occurrence increases up to 61% by adding the low-cloud cases. On these conditions, the observed events may be used for arrival direction, spectrum and X max analyses, meeting observational requirements of the mission  [2]. Another 20% case of the cloudy condition still allows a significant fraction of signals from the EAS to reach the JEM-EUSO telescope. Using information of the AM system, triggered events observed un-der such circumstances are clearly labeled to discriminate from those with the above mentioned good condition.
Acknowledgments The present work has been supported in part by the  European Space Agency Top- ical Team activities; for German consortium by  Deutsches Zentrum für Luft-und Raumfahrt ; the  Helmholtz Alliance for Astroparticle Physics  funded by the  Initiative and Networking Fund of the Helmholtz Association , and for  Spanish consortium by Ministerio de Ciencia e Innovación  under projects  AYA2009-06037-E/ESP ,  AYA-ESP 2010-19082 ,  AYA2011-29489-C03-01 ,  AYA2012-39115-C03-01  and  CSD2009-00064  ( Consolider MULTIDARK ) and  Comunidad de Madrid  under project  S2009/ ESP-1496. CALIPSO data used in the present work were obtained from the  NASA Langley Research Center Atmospheric Science Data Center. The authors wish to thank anonymous reviewers for valuable comments to improve the manuscript.
Real time PCR Total RNA purification and cDNA synthesis was performed as previously described  [40]. Real time PCR was performed using a 30 ml reaction mix containing 2 ml cDNA. At least three wells were run for each sample. The amount of speG and speC transcripts was analysed using the 2 2DDCt method  [41]  and the results were indicated as n-fold increase relative to the reference sample. The DCt-values in the Student's t test have been considered to determine whether datasets of relative gene expression were significantly different from those in a chosen calibrator. Primers for the nusA transcript, used as endogenous control, and for the above-mentioned transcripts were experimentally validated for suitability to the 2 2DDCt method. The following oligos (Table  S1 ) were used: rgf/rgr for speG, scf/scr for speC, and nusAF/nusAR for nusA.
Nucleotide sequence accession numbers DNA from plasmids pG13. 80, pG6. 81, pG4608, pG53630, and pG280 was used as template for sequencing the ynfB-speG locus. The sequence data were compared to known nucleotide and protein sequences using the BLAST server (National Center of Biotechnology Information, Bethesda, Md. ). The ynfB-speG sequences were deposited at GeneBank under accession numbers KJ825879; KJ825880; KJ825881; KJ825882; and KJ825883.
The data in figure  3  evidence that under oxidative stress a 53638 speG defective derivative (53638 DG) has a higher survival rate as compared to the parental strain. Finally, to verify whether the lack of the speG gene confers a selective advantage during infection in EIEC, we performed an in vitro competitive assay analyzing the survival within macrophages of strain HN280 transformed with a plasmid harbouring/lacking a functional copy of speG. To this end, HN280 pULS13 and HN280 pACYC184 were grown to OD600 0. 6-0. 7, mixed and used to infect a murine macrophage cell line (J774). Bacterial survival was monitored during two hours after infection by lysing the macrophages and plating appropriate dilutions on LB plates. The resulting competitive index (ratio of survival rates HN280 pULS13/HN280 pACYC184) corresponds to 0.
Interplay between spermidine and cadaverine production Putrescine is found to be approximately 2 to 4-fold higher in EIEC than in E. coli K-12 MG1655 (Table  2 ). Putrescine production (Fig. 1 ) results from direct ornithine decarboxylation, mediated by the SpeC decarboxylase, and from arginine decarboxylation followed by agmantine ureohydrolyzation determined by the SpeA and SpeB proteins, respectively  [24]. To verify whether the increased level of putrescine in EIEC might depend on increased transcription of speA, speB or speC, we monitored mRNA levels in their native backgrounds by Real Time PCR. While no difference is observed in speA and speB transcription between EIEC and MG1655 strains (data not shown), speC transcription is always higher, the increase spanning from 2-to 9fold. (Fig.
coli MG1655 derivative defective in the cadBA operon (ULS86, Table  1 ). Then, we introduced the pCC55 plasmid into ULS655 (cadC) or in ULS86 (cadBA). The expression of the speC gene was monitored by Real Time PCR. The results (Fig. 5C ) show that in a cadC defective background (ULS655) the level of speC transcription is 3-fold higher as compared to wt (MG1655) and to cadC complemented ULS655 strain, and that in a cadBA defective background (ULS86 pCC55) the increase is even higher  (5-fold). These data strongly support the hypothesis that the higher level of putrescine observed in EIEC strains is a consequence of the evolutionary loss of the cad operon.
INTRODUCTION In view of the current context of oil and gas exploration, the discovery of new prospects in underexplored areas or residual reserves in mature areas will depend on our ability to work on deeper and structurally more complex targets such as deep offshore or deeply-buried reservoirs. All these new opportunities stretch the capabilities of currently available 3D basin exploration software, which can not provide accurate structural reconstruction of the basin coupled with the controlling physical processes that lead to the generation and migration of hydrocarbons. Since 2000, 2D software tools like Thrustpack  [1] , Ceres2D  [2]  or TecLink2D  [3, 4]  exist that consider evolving geometry through geological time coupled with reconstruction of timing of hydrocarbon generation and expulsion.
The basin geometry evolves through time as a result of sedimentation, erosion, salt or mud creeping and block displacement along faults. These displacements are accounted for using translation and rotation. Deformation modes are namely flexural slip and simple shear  [1, [5] [6] [7]. 3D software like Temis3D  [8]  or Petromod3D  [7]  simulating fluid flow coupled with evolutionary geometry where paleogeometries are automatically computed by a method called "backstripping" or vertical decompaction  [9]. These methods give a good approximation of the paleogeometries in a basin with limited amounts of faulting, small lateral throws and moderate tectonics. The fault complexity is greatly simplified: a fault is a zone modeled with a series of cells characterised in terms of facies and permeability but lateral fault offset is not considered.
ACKNOWLEDGMENTS The authors would like to thank  IFPEN  for permission to publish this paper. Many thanks to  W. Sassi  and  J. Wendebourg  for their constructive comments. The authors would like to thank  C. Souque ,  F. Roure  for interesting discussions,  G. Rodet  for his participation in the generation of some results published in this paper,  C. Sulzer  in the building of the Gaspe´model,  M. Guiton  for his help in the use of the prototype  KINE3D-3. The work done on the Gaspe´belt has been done in the framework of a methodological project between  IFPEN (France) ,  INRS (Canada)  and  Petrolia (Canada). We wish to thank them for their participation and support from the beginning of the collaboration. We thank colleagues from  Petrolia  and  MRNFQ (Ministe`re des Ressources Naturelles et Faune du Que´bec)  for giving their kind permission to present this material and for providing the data.
In most social and information systems the activity of agents generates rapidly evolving timevarying networks. The temporal variation in networks' connectivity patterns and the ongoing dynamic processes are usually coupled in ways that still challenge our mathematical or computational modelling. Here we analyse a mobile call dataset and find a simple statistical law that characterize the temporal evolution of users' egocentric networks. We encode this observation in a reinforcement process defining a time-varying network model that exhibits the emergence of strong and weak ties. We study the effect of time-varying and heterogeneous interactions on the classic rumour spreading model in both synthetic, and real-world networks. We observe that strong ties severely inhibit information diffusion by confining the spreading process among agents with recurrent communication patterns.
This provides the counterintuitive evidence that strong ties may have a negative role in the spreading of information across networks 1. In the last ten years the access to high resolution datasets from mobile devices, communication, and pervasive technologies has propelled a wealth of developments in the analysis of large-scale networks [1, 2, 3, 4]. A specific effort has been devoted to characterize how network's structure influences the behaviour of dynamical processes evolving on top of them, an extremely important question for the understanding and modelling of the spreading of ideas, diseases, informations, and many others dynamical phenomena  [5, 6, 7, 8, 9]. However, the large majority of approaches put forth so far uses a timeaggregated representation of network's interactions, neglecting the time-varying nature of real systems connectivity patterns.
In this paper we propose an extension of the activity-driven framework to model and capture the emergence of heterogeneous ties in social networks. We perform a thorough analysis of a large-scale mobile phone-call (MPC) dataset containing time-stamped communication events of more than six million individuals (for detailed description see Methods). In this system, the interaction dynamics of a node (ego) can be explained by introducing simple memory effects encoded in a non-Markovian reinforcement process. The introduction of this mechanism in the activity-driven model allows capturing the evolution of the egocentric network of each actor in the system. Within this new framework we study a family of information propagation processes, namely the rumour spreading model  [38, 39]. We tackle the case in which the dynamics of contacts and the spreading process are acting on the same time-scale.
Egocentric network dynamics. In general, social networks are characterized by two types of links. The first class describes strong ties that identify time repeated and frequent interactions among specific couples of agents. The second class characterizes weak ties among agents that are activated only occasionally. It is natural to assume that strong ties are the first to appear in the system, while weak ties are incrementally added to the egonet of each agent 2. This intuition has been recently confirmed  [49]  in a large-scale dataset and indicates a particular egocentric network evolution. In order to quantify it, we measure the probability, p(n), that the next communication event of an agent having n social ties will occur via the establishment of a new (n + 1) th link. We calculate these probabilities in the MPC dataset averaging them for users with the same degree k at the end of the observation time.
In this formulation inactive nodes can receive connections. Different rules can be easily implemented to model different scenarios  [50]. Without loss of generality we fix the parameters η = 1, = 10 -3 , and ∆t = 1. Furthermore, in order to suit the MPC dataset we set m = 1, i. e. each call take place between two people. We consider heavy-tailed distributions of activity i. e. F (x) ∝ x -ν , that reproduce the behaviour observed in real data for a number of real-world networks  [23, 25, 51, 52]. Inspired by measurements in the MCP dataset we set the exponent to ν = 2. 8 (see Fig. 1. c  and f ). In the basic activity-driven model the network dynamics is memoryless (ML). At each time step all connections previously established are removed, and the new one are created with no memory of the past.
Here we extend the modelling framework introducing a simple reinforcement process in which nodes keep remembering who they have connected  [53, 54, 46]. Inspired by the observations in the MCP dataset, we impose a reinforcement mechanism in which an active node with n previously established social ties will contact randomly a new node with probability p(n) = c/(n + c). Otherwise, with probability 1 -p(n) = n/(n + c) it will interact with a node already contacted, thus reinforcing earlier established social ties. In this case, the selection is done randomly among the n neighbours. This model, that in the following we will denote as RP (reinforcement process), is non-Markovian. Memory is explicitly introduced in the egonetwork dynamics as each node keeps remembering the list of already established ties.
Rumour spreading processes on real time-varying networks. To verify the picture emerging from synthetic time-varying networks, we study the properties of rumor spreading processes in a real world time-varying system. In particular, we consider the MPC dataset and simulate the rumor spreading by using the actual sequence of calls (for more details see Methods)  [16]. At the same time to directly contrast the role of memory and repeated interactions we defined a random null model defined by keeping the caller of each event as it appears in the MPC dataset, but selecting a callee randomly. In this way, we obtain a sequence recovering the original activities and shuffled egocentric networks. Furthermore, inter-event correlations are removed. The corresponding simulation results in Fig. 7. a shows a clear difference in the speed of spreading and final density of stifler nodes.