dataesr/scientific-paragraphs-categorization huggingface dataset:
SNP Panel for Analysing Genetic Diversity of Japonica Rice Cultivated in Temperate Regions A custom Infinium SNP genotyping array (Illumina) compiling 2697 SNPs selected out of the polymorphisms identified in the 14 rice cultivars was designed. The SNP panel was generated by selecting bi-allelic polymorphisms with a uniform distribution along the 12 chromosomes, but avoiding centromere regions where gene occurrence is scarce. SNPs that were detected in more than one cultivar were prioritized. These selected SNPs were manually curated using Integrative Genomics Viewer (IGV, Broad Institute) software. The mean interval distance between adjacent SNPs was 137,525 pb. The number of SNPs per chromosome ranged from 163 in chromosome 9 (the shortest one, 23. 0 Mb) to 321 SNPs in chromosome 1 (the largest, 43.
The final libraries were quantified by Library Quantification Kit (Kapa Biosystems). The libraries were sequenced using TruSeq SBS Kit v3-HS (Illumina Inc. ), in paired end mode, 2x101bp, in ½ of a sequencing lane of HiSeq2000 flowcell v3 (Illumina Inc. ) according to standard Illumina operation procedures with the yield of >14Gb and median coverage of 33-41x. Primary data analysis, the image analysis, base calling and quality scoring of the run, was processed using the manufacturer's software Real Time Analysis (RTA 1. 13. 48) and followed by generation of FASTQ sequence files by CASAVA. Data have been deposited at the European Nucleotide Archive (ENA) in the European Bioinformatics Institute (EBI) with the accession number PRJEB13328 (http://www. ebi. ac. uk/ena/data/view/PRJEB13328).
SNP Panel and Genotyping A panel of 2697 SNPs representative of japonica rice cultivated under long day conditions was generated by selecting polymorphisms identified in the 14 cultivars. Bi-allelic polymorphisms with a uniform distribution along the 12 chromosomes SNPs were selected, avoiding centromeric and telomeric regions and maintaining an average distance of 137. 6 kb among them. SNP polymorphisms present in more than one cultivar were prioritized. SNPs were visually inspected using Integrative Genomics Viewer software (IGV, Broad Institute). The adaptability to the Illumina iSelect detection system of the SNPs and their neighbouring sequences was scored and SNPs with a score higher than 0. 4 were selected for the multiplexing Infinium Assay (Illumina Inc. ). The 217 accessions were genotyped with the 2697 SNP array.
Comparison of the called genotypes was performed using GenomeStudio software (Illumina). Low frequency alleles, considered when they were present in less than 5 % of the cultivars, were removed. Genotypes were missing data if they failed in more than 50 % of the cultivars. Genomic variation analysis and classification of SNP according to the TIGR rice gene models was implemented in platform CARMO (Comprehensive Annotation of Rice Multi-Omics data)  (Wang et al. 2015 , http:// bioinfo. sibs. ac. cn/carmo/).
We estimated the optimal alignment for the 20 replicates in CLUMPP  (Jakobsson and Rosenberg 2007) , employing greedy algorithm with 10,000 permutations. Cultivars were subdivided into different subgroups according to their maximum membership probability among the subgroups and the membership probabilities threshold of 0. 80. Pairwise genetic distances between rice cultivars were calculated as implemented in Darwin 6. 0  (Perrier et al. 2003) , by using the Sokal & Michener index and 10,000 bootstrap replicates. Then we obtained a neighbourjoining (NJ) tree, which robustness was assessed again by 10,000 replicate bootstrap analyses. We also used the software STRUCTURE to estimate Fst values for the genetic clusters established for each group, the mean value of 20 runs was calculated. Finally, Fst pairwise values between the subpopulations defined by STRUCTURE analysis were calculated in Arlequin (Excoffier and Lischer 2010) with 10,000 permutations and including only those varieties with membership values > 80 %.
This paper presents an algebra of coloured Petri nets called the Asynchronous Box Calculus with Data, or abcd for short. abcd allows to model complex systems using a user-friendly and high-level syntax. In particular, parts of the model can be directly programmed in Python  [21] , which allows to embed complex computation and data values within a model. A compiler for abcd is shipped with the toolkit snakes  [16, 18]  and abcd has been used for years, which is quickly surveyed. This paper is the first complete and formal presentation of the language and its semantics. It also presents uses cases of abcd for the modelling and analysis of various systems.
A compiler is distributed within the snakes toolkit  [16, 18]  and allows to build a Petri net from abcd source code. This paper provides the first complete and formal definition of abcd, i. e. , its syntax and semantics. Only informal introductions though examples had been published so far, the most complete of which being  [17, pages 30-33]. Other contributions of this paper are: a definition of Python-coloured Petri nets with read/fill/flush-arcs, a presentation of the abcd compiler and simulator, and a short survey of abcd use cases for research and teaching to showcase its usability. The next section presents the syntax of abcd together with its intuitive semantics. The formal semantics is defined in section 3 as a translation of abcd terms into Petri nets. Section 5 describes the compiler and the interactive simulator.
Buffers Resources in abcd are stored in buffers, i. e. , unbounded and unordered data containers that can be accessed from the process that declares the buffer as well as from any of its sub-processes. In the semantics, they correspond to (coloured) places. A buffer is declared using keyword buffer and is given: a name that is an identifier that will be used in process expressions to access the buffer; a type that restricts the values allowed in the buffer; an initial content given as an expression that is interpreted as a series of values initially stored in by the buffer. The following abcd code shows the declarations of two buffers: 1 buffer foo : int = () 2 buffer bar : str = "hello", "world" The first line declares a buffer named "foo", whose type is "int" the set of integers and whose initial content is empty since "()" denotes the empty tuple in Python.
Security Protocols A massively parallel ctl* model-checker for models of security protocols has been developed in  [10] ; a side product of this work has been the actual modelling of a bunch of security protocols, which has been made using abcd. We show here two excerpts of a model of the Needham-Schroeder public key protocol  [13] , it is not needed to present it to understand our purpose, it is enough to know that some agents are exchanging encrypted messages in the presence of an attacker. First, a Python module called "dolev yao" is imported, it contains the definition of various symbols ("CRYPT", "PUB", "PRIV" and "NONCE") used to make a symbolic treatment of cryptography (i. e. , replace actual computation of cryptographic operations with terms that express it, which is a classical treatment of cryptography when modelling protocols) as well as a class "Spy" that implements a Dolev-Yao attacker  [8].
Implementation, Compilation and Simulation abcd is implemented in snakes  [16, 18]  as a compiler that takes abcd source code as its input and has various possible outcomes: pictures, snakes' variant of pnml, 1  or an interactive simulator that allows to execute a model in a user-friendly graphical user-interface. A naive reachability model-checker is also implemented but we will not describe it, and actually we did not describe the related parts in the syntax, because it is intended to be replaced with something more general, robust and efficient. The compiler can be invoked from a command line interface or from a Python program in which case the constructed Petri net object is returned as an instance of snakes' PetriNet class. The compiler is a rather straightforward implementation of the rules presented in Figure  4 , extended with syntactic and semantic constraints checks.
Conclusion We have presented abcd, a modelling language that is mixing the Python programming language and a process algebras. We have defined the Petri nets semantics of abcd, targeting a Python-coloured variant of Petri nets extended with read-, flush-and fill-arcs. All this is implemented and freely available with the toolkit snakes. Use cases of abcd have showed its suitability to qualitative analysis through model-checking as well as to quantitative analysis through statistics on large sets of traces. abcd is also suitable to teach formal modelling to master students and is regularly used for this purpose. Among the numerous languages or notations with a Petri net semantics, apart from the pbc and pna family of which abcd is a member, essentially one can be directly related to abcd: the Basic Petri Net Programming Notation, b(pn) 2  [4] , is also a process algebra and its semantics is expressed in terms of coloured Petri nets.
Data in b(pn) 2 is stored into variables which makes necessary to distinguish the value of a variable before and after the execution of an atomic action. So, a variable x is actually used as x and x within the Boolean expressions that form the atomic actions. After having taught both b(pn) 2 and abcd, it appears that abcd is easier to understand than b(pn) 2 because it is more explicit with respect to data storage through buffer accesses, the latter being clearly distinguished from the guard when b(pn) 2 unifies both aspects. Finally, b(pn) 2 is implemented only in the pep toolkit  [14]  that is not maintained anymore. Future work about abcd will aim at implementing various extensions and improving its connection with analysis tools. Considered extensions include: buffer capacities to block actions that would add (resp.
Two ways are envisaged to improve the usability of abcd for analysis. First, we would like to ease the invocation of Neco-spot  [9]  to support direct modelchecking of ltl formulas on abcd models, this will require some work on Neco itself that currently has a few blocking limitations as explained above. Then, we are already working on a fast multi-core simulation engine coupled with automatic execution-related data collection for statistical analysis. Currently, this is a manual process with an inefficient execution of the traces, and so, building even simple statistics is quite a tedious process. Finally, we will continue to model systems using abcd in the context of research projects as well as for teaching because it has proved to be a good tool for these purposes.
O10 PLHIV over age 40: healthcare experience and comorbidities in 2015, France Mathilde Coudray, Elisabete de Carvalho SIS Observatory Department of Réseau, Montpellier, France In France, 2 people living with HIV (PLHIV) out of 5 are more than 50 years old. This study was performed to know more about healthcare experience of PLHIV aged over 40 years and their worries about ageing. From July to October 2015, a self-administrated questionnaire was available on Sida Info Service, the French HIV/AIDS helpline, web site. 194 questionnaires constitute the sample. Both quantitative and qualitative data were analyzed with Modalisa v6. This abstract presents only results about comorbidities and healthcare. 75. 8% are male. The mean age is 52 years and mean time since HIV diagnosis is 18 years. Almost all participants are on antiretroviral therapy treatment (ART, 97.
T he genus Frankia contains actinobacteria known for their abil- ity to fix nitrogen and to infect the roots of eight actinorhizal plant families  (1) (2) (3). Phylogenetic studies of Frankia strains based on 16S rRNA (4), gyr B (5), gln II  (5, 6)  genes and 16S-23S rRNA Intergenic Spacer Region  (7)  indicate four groups. Group 1 forms nodules on Betulaceae, Myricaceae, and Casuarinaceae. Group 2 contains microsymbionts of Coriariaceae, Datiscaceae, Dryadoideae (Rosaceae), and Ceanothus (Rhamnaceae). Group 3 includes strains associated with Morella (Myricaceae), Colletieae (Rhamnaceae), Elaeagnaceae, and Gymnostoma (Casuarinaceae). Group 4 includes atypical, non-infective (Nod-) and/or ineffective (Fix-) Frankia strains. Our knowledge about the biology of this genus has been well improved due to the information provided by sequenced Frankia genomes  (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) (21).
537,992 bp in size based on 856. 6 Mbp of data with 171. 3 ϫ input read coverage. The genome draft encodes 7,790 protein genes, 47 tRNAs, and 2 rRNA regions, with an overall GϩC content of 70. 9%. Genome annotation was performed as described by Tisa et al. (21). As expected, since Frankia is a nitrogen fixing actinobacterium, six nitrogenase genes, nifH, nifE, nifD, nifK, nifW, and nifN, have been detected. Project information is available in the Genomes Online Database  (33)  and DNA from the DNA Bank Network  (34). Nucleotide sequence accession number. This whole-genome shotgun project has been deposited in DDBJ/EMBL/GenBank under the accession no. FAOZ00000000. The version described in this paper is the first version.
ACKNOWLEDGMENTS This work was conducted under the auspices of  U. S. Department of Energy Office of Science, Biological and Environmental Research Program  and the  University of California ,  Lawrence Berkeley National Laboratory  (under contract  DE-AC02-05CH11231 ). We are grateful to  Marlen Jando  and  Meike Döppner  (both at  DSMZ ) for their contribution to culturing Frankia strains and for DNA extractions and quality control.
A NOBEL LAUREATE? The few editorials in the business paper Dagens Naeringsliv mainly address other issues, while attributing their being on the agenda to the Snowden revelations. One of them concludes that it is time to revise the vote on the Data Retention Directive due to the Snowden revelations: «Edward Snowden's NSA leaks have demonstrated to the world that it is not at all unthinkable for a Western democracy to misuse access to personal information about both one's own and other countries' citizens» («Yes to Play-off», 12. 11. 2013). This article is downloaded from www. idunn. no. © 2015 Author(s). This is an Open Access article distributed under the terms of the Creative Commons CC-BY-NC 4. 0 License (http://creativecommons. org/licenses/by-nc/4. 0/), allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for non-commercial use, provided the original author and source are credited.
On the same day, Klassekampen mentions the «nine eyes», asking what «our contribution to NSA's vast database has been and is» («USA's Eyes», 05. 11. 2013). Another editorial in Dagbladet also took the politicians to task: «Most silent of all are Norwegian politicians. The Prime Minister, the minister of foreign affairs, the minister of justice, who on other occasions do not hesitate to ask for time in front of cameras and microphones, remain mute» («Give Snowden Protection», Dagbladet 04. 07. 2013), after which it recommends Snowden for political asylum in Norway. Klassekampen states that Snowden's revelations «have created remarkably little discussion in Norway», and asks for a largescale official scrutiny of the way in which citizens are surveilled, and how to protect their privacy, freedom of expression and democratic rights.
). This part of the Snowden revelations, including the surveillance of Angela Merkel, may have been an important factor in unifying many Norwegian media and public intellectuals in a critique against the NSA. One of the fundamental questions addressed in the opinion pieces analyzed is the conflictual relation between security and protection of privacy. Professor in media and communication, Liv Hausken, writes that the question of security «[often] has to do with how society can protect itself against individuals or groups, while the question of legal security is rather a question of how individuals and groups may protect themselves against society and the powers that be» (2014: 28). Director of the Norwegian Data Protection Authority (Datatilsynet), Bjørn Erik Thon, while referring to the European Human Rights convention, further emphasizes the foundation of privacy as based on «the idea of the individual's inviolability and demand for respect from fellow human beings, for their own integrity and privacy» (Thon 2014: 104).
EXPANSION MAPS To search for expansive components we analysed the GHαFaS data cube with BUBBLY  (Camps-Fariña et al. 2015) , a program designed to find and fit multi-component spectral line data cubes. The analysis is automatic, using a mathematical property of Gaussians to detect multiple components, which are then fitted (if they are above a threshold signal-to-noise) and checked to look for pairs of components equidistant in velocity (within uncertainty limits) from the central peak representing the bulk of the HII region. These detections are then mapped in expansion velocity giving "expansion maps", which we use to find the bubbles. We used the default configuration in the BUBBLY parameter file with a minimum S:N ratio of 5 to detect the expansion components. Because of the relatively low signal-to-noise ratio threshold we added visual inspection of the expansion maps to ensure that detection was spatially coherent.
ACKNOWLEDGEMENTS We thank  M. Beasley ,  J. E. Dale , and the anonymous referee for useful discussion and comments. This research has been supported by the  Instituto de Astrofísica de Canarias  under project  P/308603. JEB acknowledges financial support to the DAGAL network from the  People Programme  ( Marie Curie Actions ) of the European Union's  Seventh Framework Programme FP7 /2007-2013/ under REA grant agreement number  PITN-GA-2011-289313. Based on observations made with the William Herschel Tele-scope under Director's  Discretionary Time of Spain 's  Instituto de Astrofísica de Canarias. The William Herschel Telescope is operated on the island of  La Palma  by the  Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos  of the  Instituto de Astrofísica de Canarias.
Sampling procedure and colour measurement Blue tits have been monitored in the Rouvière forest (mainland France) since 1991 and at two localities in Corsica since 1976  (Pirio) and 1994 (Muro). Details on these study sites can be found in  (Blondel et al. (2006)  and  Charmantier et al. (2016). Blue tits from Corsica belong to a different subspecies from blue tits found in the French Mediterranean mainland. The distance between Muro and Pirio in Corsica is 25 km. In order to improve our power for quantitative genetic models, individuals from these two valleys were pooled in one common Corsican data set. Supplementary Information A2 provides statistical justification for this choice based on a test for equality of additive genetic variances between the two populations. Each year, breeding parents were captured in nest boxes between April and June.
A small proportion of individuals were caught before the breeding period in  January-March (in 2008 -2009 and 2011 -2013 , n = 577 or 15. 9% of Heredity measures). Each bird was equipped with a uniquely numbered metal ring provided by the Museum National d'Histoire Naturelle in Paris, six blue feathers were collected from the bird's blue crown and eight yellow feathers from the yellow chest to allow colour measurements in the lab. Bird sex and age were determined based on the capture-recapture database or on the colour of wing coverts for unringed birds. Chicks were ringed after 9 days of age that allowed building social pedigrees for each population. Genotyping of parents and offspring in 2000-2003 has shown that up to 29. 3% (annual range: 18. 2-29. 3%, Charmantier et al. , 2004)  of chicks were the result of extra-pair matings in Corsica, and 18.
Quantitative genetics Exploring fixed effects. Previous to conducting quantitative genetic models, we conducted linear mixed models to explore the contribution of fixed effects (year of measure, year of birth, period of measurement and individual age) to the various colour parameters in both data sets. For all traits, only year of measure was retained in all models as a categorical fixed effect (see details in Supplementary Information A1). Univariate animal models. Genetic (co)variances, heritabilities and genetic correlations were estimated using restricted maximum-likelihood (REML) estimation procedures implemented in the software ASReml v3. 0  (Gilmour et al. , 2009). For each data set and colour measure, we first implemented a sex-specific univariate 'animal model' that combined the phenotypic measures for a given sex with the pedigree information to partition the phenotypic variance into an additive genetic variance (V A ), a variance due to permanent environment effects (V PE , based on repeated observations of individuals) and a residual variance (V R ), while controlling for annual fluctuations using year as a single fixed effect.
However, it can fit a cross-sex additive genetic covariance (COV Am;f ) from which we estimate the cross-sex additive genetic correlation: r Am;f ¼ COV Am;f ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi V Am V Af p ð3Þ A bivariate animal model was fitted for each colour trait in each population, with a genetic group specified for Muro and Pirio individuals in the case of the Corsican data set. The additive genetic covariance estimates were tested against a null hypothesis of zero by carrying out a likelihood ratio test using the χ 2 distribution with one degree of freedom. In order to test for a genotype × sex interaction, which occurs when a given genotype has different phenotypic expressions in males versus females, we compared the original model with a model where V Am ¼ V Af ¼ COV Am;f using likelihood ratio tests and the χ 2 distribution with two degrees of freedom.
Within each of these unique combinations, the Z-linked additive genetic variance was set to one of seven values: σ Z-male 2 = 1, 10, 30, 50, 60, 70 or 90 to assess the power at each level. For each of the above parameter combinations, in each of the two data sets (Corsica and Rouvière), we simulated phenotypes for every individual (Supplementary Equation S1 in Supplementary Information) a total of 1000 different times. We used R (R Core Team, 2014) and the R package nadiv  (Wolak, 2012)  to simulate each of the above effects (Supplementary Information A3). We used the model of sex-chromosomal additive genetic variance of  Fernando and Grossman (1990)  that assumes no global sex chromosomal dosage compensation or recombination between the Z and W chromosomes. Simulated phenotypes were analysed with an animal model implemented in the ASReml R package (v3.
ACKNOWLEDGEMENTS We thank all the people who collected feathers in the field and participated to the blue tit long-term program, in particular  P Perret ,  M Lambrechts ,  J Blondel ,  D Réale ,  D Garant ,  M Porlier ,  G Dubuc Meissier ,  P Marrot ,  P Giovanini  and many field assistants. We thank all the people who performed the colour measures, and in particular  Emeline Mourocq ,  Afiwa Midamegbe  and  Maria.
Time-frequency-energy representations For this study, two spectral methods have been employed in order to assess the variability of the SSI. Most notably, analysis techniques that reveal the temporal evolution of the scrutinized data have been privileged. Two such techniques, popular within the geophysics community  (Tary et al. , 2014) , are the Continuous Wavelet Transform (CWT) an the Hilbert-Huang Transform (HHT). The methods are of interest mostly due to their innate ability to offer insight into the processes underlying the data by painting so called time-frequencyenergy representations, i. e. graphical representations depicting the distribution of power, or variance, occurring at specific time instants and specific scales or periods (assuming period 1/frequency). M. Bengulescu et al.