dataesr/scientific-paragraphs-categorization huggingface dataset:
The DETR'PROK workflow A simplified view of the DETR'PROK workflow is shown in Fig. 1. The program requires as input an alignment file in BAM format and an annotation file in GFF format. The BAM alignment file can be produced by any next-generation sequencing read mapper, such as Bowtie  [11]  or BWA  [12]. As our workflow is highly dependent on read orientation to differentiate sense from antisense transcripts, the initial sequencing must be produced using an oriented RNA-seq library preparation protocol. We recommend to run the mapping program in the ''unique match'' mode and/or to discard reads corresponding to highly expressed loci such as rRNA genes. This produces lighter BAM files thus leading to faster runs and file transfers. The annotation file is important, as UTR extensions and novel independent sRNAs will be defined relative to this prior annotation.
2  and Table  1. There are fewer parameters than steps because the same parameter is used at several steps (this is a normal constraint in the Galaxy framework). The first parameter (features_list) is used to specify which initial annotation in the input GFF file should be preserved. By not including ncRNAs or tRNAs at this step, these elements are ignored and possibly re-predicted by the workflow. Note that some GFF annotation files may use other names to describe ncRNAs, such as ''misc_RNA''. Most other parameters cover two types of items: distance constraints between elements to separate or merge elements, and filters to reject ncRNAs based on their sizes or number of mapped reads. Importantly, the default DETR'PROK pipeline requires asRNAs to be covered completely by their antisense transcript (which can be coding or non-coding).
As gene density increases, the gaps (RNA_gap parameter) separating elements should be made shorter to avoid merging different elements together. The ''op_gap'' parameter defining the maximum internal operon spacers is also correlated to gene density. It can be tentatively defined based on the distribution of intergenic distances in the whole genome: multicistronic genes tend to create a peak of short intergenic distances that can be used to set the ''op_gap'' parameter just above this peak (Fig. S1 ). As sequencing depth increases, so does the likelihood of spurious reads in antisense or intergenic regions, therefore requiring that coverage filters (sRNA_min_reads, asRNA_min_reads, UTR5_min_reads) are set higher. The complete pipeline runs fast enough (about 2 h on a standard Linux server with an average sized bacterial genome and 5 M sequencing reads) that parameter values can be improved by trial and error.
Note that genome viewers often require indexed BAM files (. bai format) for displaying NGS reads along the genome sequence. A bai file is automatically created when adding a BAM file to a dataset into Galaxy data libraries. Once a parameter set is deemed satisfying for a given genome and sequencing depth, the workflow can be saved with these parameters by extracting the workflow from the history (select ''Extract Workflow'' from the History menu on top of the right panel). Alternatively, parameters can be hard-coded into the workflow using the workflow editor (Workflow menu, select a workflow, select Edit, then click on a Workflow step and, for a given parameter, change ''to be set at runtime'' with ''set in advance''). In this way, the pipeline can be run again over similar genomes and RNA-seq datasets with a single click.
A test run using a Vibrio splendidus RNA-seq dataset We reanalyzed a RNA-seq dataset obtained for the oyster pathogen V. splendidus, a gamma proteobacteria that contains two chromosomes of size 3. 3 Mb and 1. 7 Mb. Original sequencing conditions were single-end Illumina GA-IIX sequencing, 38 nt reads, 28 M reads overall. This transcriptome was analyzed using an earlier version of our pipeline followed by manual curation  [16]. Here we analyzed again the same dataset using the latest DETR'PROK workflow and no manual curation. We obtained the V. splendidus GFF annotation files directly from the NCBI FTP site using the URL: ftp://ftp. ncbi. nlm. nih. gov/genomes/Bacteria/ Vibrio_splendidus_LGP32_uid59353/ The annotation files NC_011753. gff and NC_011744. gff were imported into Galaxy by selecting ''Get Data'' -''Upload File from your computer''.
The mapping procedure that generates BAM files can be run within Galaxy using a program such as Bowtie. Inputs are the Fasta format genome sequence and the original Fastq file produced by the sequencing machine (here SRA accession SRX272401). This step is not part of the DETR'PROK workflow and we assume it has been performed independently. This resulted in 4. 5 M reads mapping at unique positions  [16]. The corresponding BAM files are available at: http://rna. igmors. u-psud. fr/suppl_data/ The parameter settings for the DETR'PROK workflow are shown in Table  1. These were refined empirically to approximate those used in our previous analysis (see Fig. 2  in Ref. [16] ). The previous workflow and manual curation had identified 250 sRNAs, 471 long 5 0 UTR and 73 asRNAs  [16]. The new DETR'PROK workflow identifies 242 sRNAs, 519 long 5 0 UTR and 86 asRNAs.
Conclusion and further developments We presented a workflow for the annotation of non-coding RNAs in archaeal and bacterial genomes. This workflow requires some user input in order to take genome density and sequencing depth into account. However, we showed that the Galaxy frame-work enables parameters to be fixed permanently for a faster launch procedure. In our final output files, we singled out long 5 0 UTRs, sRNAs and asRNAs because these elements constitute a current focus of the RNA community as they are most likely to harbor functional, regulatory RNAs. However non-coding RNA is also present in the form of 3 0 UTRs and short 5 0 UTRs. These elements are interesting because they redefine the transcription units of coding genes, which is important for transcript quantification and for the study of RNA-RNA interactions.
Workflow installation The workflow should be run on a local Galaxy instance or one hosted on a distant server. Refer to the tutorial (http://wiki. galaxyproject. org/Admin/Get_Galaxy) for creation of a Galaxy instance. As the workflow has several steps running in parallel, the Galaxy instance should use a database management system supporting concurential access such as postgreSQL, instead of the default SQLite system. The DETR'PROK pipeline is obtained from the Galaxy main tool shed (http://toolshed. g2. bx. psu. edu/), or my experiment (http://www. myexperiment. org), searching by name ''detrprok_wf'', and should be installed by the Galaxy instance administrator. DETR'PROK requires installation of the S-MART toolbox  [13]  and the ''detrprok_scripts'', both available in the Galaxy main tool shed.
) which is then transported by wireless and wired access networks to data centres for analysis in order to optimise the use of resources. Ubiquitous wireless broadband and computing access provides all imaginable services to citizens, enterprises and public services, and enables citizens to be well integrated into the life of their community and the city. Our vision is of an information-rich, economically efficient and effective, city that is clean, healthy and aesthetically pleasing. The socioeconomic benefits of Digital Cities are subject to vast literature (see URENIO Intelligent Cities  [9] ). The results of Digital City research are amenable to commercialisation over both short and long terms. Digital Cities are now big business for some major companies-as seen on the websites of IBM (Smarter Cities [10]), Siemens (City of the Future  [11] ) or Philips (Liveable Cities [12])-and commercial interest extends well beyond the electronics industry to include, for example, municipalities, heavy engineering companies and urban furniture manufacturers.
In the case of the University of Ottawa, it was found that a business case for relocation did not exist because the university successfully converts waste energy from ICT into energy needed elsewhere on campus to heat and cool buildings and to provide hot water. This nonintuitive result amply illustrates the need for a whole systems (including socioeconomic factors) approach to the optimization of energy management. The report also illustrated the need for improvements in the granularity of consumption data logging to ensure adequate information for analysis. In the ideal sustainable Digital City, one might envisage wireless sensor networks logging at the granularity of individual outlets.
8 times better in the distributed antenna case (Fig. 2b ). Considering omnidirectional antennas and the characteristic impedance of vacuum, the mean and the maximum strengths of the electric field received in the area are computed in Table  1. When the users are close to the centralised antenna, the maximum strength of the electrical field is three times higher than in the DAS case. A system demonstrator was set up on the CapilR TM platform at Télécom Bretagne to provide enhanced 2. 4 GHz Wi-Fi coverage within an office building (ARAGO Centre) by means of four distributed omnidirectional antennas (Hyperlink model HG2458CU). The antennas are positioned in a way to obtain the best possible coverage in the office spaces. The simulation tool WinProp TM was used with its module WallMan TM to model the office building, taking into account the frequency dependence of the material properties (transmission and reflection losses).
This project is ongoing, and improvements are made as the system components are replaced by next generation components. Figure  6  shows the second generation of the ORIGIN transceiver module. A full description of the architecture and measurement data for different test cases can be found in  [42] [43] [44] [45] [46]. In  [45] , a real-time transmission between two commercial Wireless HD devices at 3 Gbps is achieved with a separation distance of up to 5 m between the access points and the 60-GHz terminals. The fibre used (OM3 multi-mode fibre) can be up to 300 m long, which is far more than one probably ever needs in a domestic case.
Acknowledgments This research was initiated when  Dr. Trevor Hall  was on sabbatical leave hosted by  Télécom Bretagne France  between 1st July 2010 and 30 June 2011, when he held the SISCom International Chair supported by the  Université Européenne de Bretagne. Dr. Hall  is also grateful to the  Canada Research Chairs programme  for their support. Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
An alternative solution could have been to use the multi-parent QTL mapping strategy applied in oil palm by  Billotte et al. (2010) , using in our case pseudo-backcrosses sharing common parents, but no such mating design exists yet. For each palm, two ripe bunches were collected, and 30 random fruits were sampled per bunch (two fruit samples/palm), to provide a good estimate of the palm oil quality  (Wuidart and Gascon 1975) , based on previous experiments of the former "Institut de Recherche des Huiles et des Oléagineux" (I. R. H. O) in France. Palm oil composition analysis was carried out on these two biological replicates per palm, and results are reported as mean values. No phenotypic data were available for the E. guineensis grandparent LM2466P and parent PO3228D. Fruits were boiled (100 °C) in water and then hot-pressed using a screw press to extract the palm oil.
Statistical analysis of phenotypic data An analysis of variance (ANOVA) test (post hoc test of Tukey, α = 0. 05) was realized for all traits to evidence eventual differences between the planting sites LC and IP. If significant differences were detected for a given trait, the individual phenotypic data for the IP site were standardized regarding those of the LC site, by a mean correction for further statistical analyses as follows: IP standardized data = IP raw data +(LC mean -IP mean ). The Gauss distribution of the quantitative data was checked by a normality test of Shapiro-Wilk at an α threshold of 5 %. The relationships between phenotypic traits, at the individual palm level, were estimated by calculating the Pearson's correlation coefficients. The trait heritability h 2 (broad sense) was estimated by ANOVA with one fixed factor (palm) using the two bunches measured per palm assuming that for these oil traits, variability between bunches on the same tree is not far from variability between bunches on separate trees of a clone in the same trial, as follows: model: Y ij =m+A i +E ij , where i (1 to 115) is the palm, j (1 to 2) is the bunch measured, Y ij is the phenotypic value of the palm i for its bunch j, A i is the trait genetic value of the palm, E ij is the error (environment effect on the trait phenotypic value), and h 2 ¼ σG 2 σG 2 þσE 2 ¼ MS P -MS E MS P þMS E , where σ G 2 is the genetic variance, σ E 2 is the error variance, MS P is the mean square for palm, and MS E is the error mean square.
guineensis and Colombia, Brazil, Costa Rica, and Surinam for E. oleifera. These libraries of the International Oil Palm Genome Projects (OPGP) Consortium were sequenced by the Genoscope-CEA (Evry, France) using the 454 Roche/GS-FLX Pyrosequencing technology (1/2 run per library). Each read library was analyzed using the ESTtik tool (Expressed Sequence Tag treatment and investigation kit)  (Argout et al. 2008)  especially modified for the analysis of 454 sequence data. The 454 reads obtained from the eight pulp libraries were assembled using the TGICL  (Pertea et al. 2003)  assembler. Contigs were automatically annotated using the standalone BLAST software  (Altschul et al. 1990 ). We searched for similar sequences on the Oryza sativa japonica proteome TIGR6, the Uniprot Knoledgebase Swiss-Prot and TrEMBL  (Boeckmann et al.
2003) , the GenBank non-redundant protein database NR, and the GenBank nucleotide database NT. We used an evalue cutoff of 1e-5 and retrieve the 10 best hits to annotate each contig. We used the Blast2GO pipeline  (Götz et al. 2008)  to annotate the contigs with the Gene Ontology terms based on our BLAST results. Also, a BLAST analysis was performed with the E. guineensis cDNA libraries of  Bourgis et al. (2011) and Tranbarger et al. (2011). We used the Pro-t4EST pipeline  (Wasmuth and Blaxter 2004)  to obtain a protein prediction from our contig sequences. We used the program IDEG6  (Romualdi et al. 2003)  for data normalization and statistical analysis of the read libraries (general chi-square test applying the Bonferroni correction, p <0. 0001), to test the differential expression of our five genes between the two Elaeis species.
Finally, the ACE assembly output from TGICL was treated to obtain a collection of FASTA alignment using the AceToFastaAlignment script from the SNiPlay utilities  (Dereeper et al. 2011). We used the SNiPlay pipeline on our FASTA alignment collection for single nucleotid polymorphism (SNP) analysis. SNP loci were identified from cDNA reads for our five targeted genes, with eventually several SNPs for a given gene. Designed SNPs were genotyped by the commercial laboratory ADNid (Montpellier, France, http:// www. adnid. fr), combining the GoldenGate Genotyping Assay with the VeraCode technology (Illumina, San Diego, USA) and using the Illumina's BeadXpress Reader System for detection.
Linkage mapping A linkage map of SA569 was constructed based on 115 progenies, without missing data for the polymorphic SSRs, SNPs, and the Sh gene. SSR loci showing a significant distortion (p<0. 01) according to the expected Mendelian segregating ratio of their alleles were removed from the analysis. The linkage phases between SSR marker alleles were determined using the JoinMap v. 4. 0 software (Van Ooijen and Voorrips 2001) in our pseudo-backcross considered to be a double pseudo-test cross  (Grattapaglia and Sederoff 1994). Marker loci with estimated allele phases were then analyzed using the CarthaGene software  (Schiex and Gaspin 1997 ) at LOD 7. 5 with a maximum recombination threshold of 0. 3. The most probable relative linear orders of markers within each linkage group (LG) were estimated using the several multi-point maximum likelihood algorithms of CarthaGene.
The Haldane mapping function was used to convert recombination frequencies into map distances  (Haldane 1919). The chart of the linkage map was generated using BioMERCATOR v. 3. 1  (Arcade et al. 2004 ). QTL analysis QTL analyses using the SSR-SNP linkage map and all available genotypic and phenotypic data were performed with the MapQTL®5 software  (Van Ooijen 2004). As a first step, the non-parametric Kruskal-Wallis (K-W) test was performed to identify significant marker-trait associations at p<0. 005. Subsequently, the interval mapping (IM) method was performed using the LOD statistic test with a mapping step size of 1 cM and a maximum number of 5 neighboring markers. For each trait, threshold LOD values were estimated at the genome-wide (GW) global risk α of 5 and 1 % for declaring the presence of a QTL by the resampling method and permutation of the trait data (1.
For assigning known genes to QTLs and for practical MAS, the next step of our study will be to search all genes known to be involved in fatty acid synthesis, in our Elaeis cDNA libraries of pulp, and to identify and map their polymorphic intra-gene SNPs. On the other hand, it will be possible to anchor the genetic map(s) to a whole-genome sequence of Elaeis guineensis, as soon as this latter will be available, in order to search SSRs and SNPs for a QTL finemapping strategy. Also, such anchoring allows us to identify candidate genes or genes known to be involved in fatty acid synthesis among the genes underlying the fined-mapped QTL regions, for which intra-gene markers may be developed for practical use of MAS (once candidate genes are validated). At the phenotypic level, the individual palms of the mapping population(s) would be characterized for the kinetic of the palm oil biosynthesis, by fatty acid analysis all along the development of ripening fruits, and for the transcript profiles of the related genes, by parallel RT-QPR analysis.
Related Work In the literature, several frameworks  [5, 12, 15, 22, 23, 25, 26]  have been proposed to generalize the operational model of functions to a model of concurrent processes. Most of these proposals work on the encoding of the functional computation model λ-Calculus into the concurrent computation model π-Calculus. In  [22] , Milner showed that λ-Calculus could be precisely encoded into π-Calculus. The Spin tool  [18]  enables the verification of dynamic systems where concurrent processes can be created on the fly. Both creating and created processes progress together. The creation of a new process does not block the creating component execution i. e. , a return is not needed to unlock the creating component. Similarly, the Ada language  [13]  enables the creation of tasks on the fly.
The dynamic instantiation of callable timed automata leads to building the structure of the system on the fly: the system has different numbers of instances on different executions and at different dates. The dynamic feature of such an instantiation is suitable to model objectbased systems, ad-hoc networks, fault tolerant and DataBase Management systems (DBMS) where components (objects, hosts, processes) are created on the fly. For example, in the case of DataBase Management systems, when the execution of a process requires to read data from a database, it calls the Reader module of DBMS by creating an instance of the former to fetch data.
Implementation and Experiments In order to make our extension profitable, we have designed a Python script program converting callable timed automata systems to UPPAAL NTA. In fact, our converter uploads an XML file designed using UPPAAL graphical editor, as an input where the interface of each CTA states a finite number of instances. After performing a deeper analysis of callable automata syntax, in particular template interfaces, call and return transitions, the converter generates the corresponding UPPAAL NTA format, written in a new XML file that will be then reloaded in the UPPAAL tool, as an ordinary system to be analyzed and checked. The interface of each callable TA is given by the number of instances, the type of return, the name of template and the set of parameters. That is an example of a template signature with 3 instances, a void return type, the template name Use Case and a set of parameters.
We present a technique for deriving semantic program analyses from a natural semantics specification of the programming language. The technique is based on a particular kind of semantics called prettybig-step semantics. We present a pretty-big-step semantics of a language with simple objects called O'While and specify a series of instrumentations of the semantics that explicitates the flows of values in a program. This leads to a semantics-based dependency analysis, at the core, e. g. , of tainting analysis in software security. The formalization has been realized with the Coq proof assistant.
In this paper, we will pursue the research agenda set out by Schmidt and investigate further the systematic design of semantics-based program analyses based on big-step semantics. Two important issues here will be those of scalability and mechanization. The approach worked nicely for a language whose semantics could be defined in 8 inference rules. How will it react when applied to full-blown languages where the semantic definition comprises hundreds of rules? Strongly linked to this question is that of how the framework can be mechanized and put to work on larger languages using automated tool support. In the present work, we investigate how the Coq proof assistant can serve as a tool for manipulating the semantic definitions and certifying the correctness of the derived static analyses. Certified static analysis is concerned with developing static analyzers inside proof assistants with the aim of producing a static analyzer and a machine-verifiable proof of its semantic correctness.
One long-term goal of the work reported here is to be able to provide a mechanically verified static analysis for the full JAVASCRIPT language based on the Coq formalization developed in the JSCert project  [1]. JAVASCRIPT, with its rich but also sometimes quirky semantics, is indeed a good raison d'être for studying certified static analysis, in order to ensure that all of the cases in the semantics are catered for. In our development, we shall take advantage of some recent developments in the theory of operational semantics. In particular, we will be using a particular format of natural semantics call "pretty-big-step" semantics  [3]  which is a streamlined form of operational semantics retaining the format of natural semantics while being closer to small-step operational semantics. We will give a high-level introduction to the main features of pretty-big-step semantics in Section 2 Even though it is our ultimate goal, JAVASCRIPT is far too big to begin with as a goal for analysis: its pretty-big-step semantics contains more than half a thousand rules! We will thus start by studying a much simpler language, called O'WHILE, which is basically a WHILE language with simple objects in the form of extensible records.
This language is quite far from JAVASCRIPT, but is big enough to catch some issues of the analyses of JAVASCRIPT objects. We present the language and its pretty-big-step semantics in Section 3. To test the applicability of the approach to defining static analyses, we have chosen to formalize a data flow dependency analysis as used e. g. , in tainting  [12]  or "direct information-flow" analyses of JavaScript  [15, 5]. The property we ensure is defined in Section 4 and the analysis itself is defined in Sections 5. As stated above, the scalability of the approach relies on the mechanization that will enable the developer of the analyses to prove the correctness of analyses with respect to the semantics, and to extract an executable analyzer. We will show how the Coq proof assistant has been used successfully to achieve these objectives as we go along.