dataesr/scientific-paragraphs-categorization huggingface dataset:
One of the first technical decisions was choosing the software platform from which to launch the project. Although a number of possibilities exist, we started with the Greenstone software which is a project out of New Zealand, supported by UNESCO, that seeks to create a free and robust system that can be run on older and slower computer systems with uneven internet connectivity such as might be found in rural Africa. 8 It is also a platform that can be modified and used by people with less specialized knowledge. There are also many other possibilities that have been innovated or used by indigenous communities, and more being developed each year. 9 So in the summer of 2011, with the support of Goshen College, I took the first concrete step forward in contracting a history student with technological skills to investigate and begin to construct the template for the Mara Cultural Heritage Digital Library based on his research on best practices in the field.
10  I also had to work with students on digitizing and converting all of the research material into a digital format that could be used by the Greenstone system, including adding the metadata using a modified form of the standard Dublin Core protocol that makes it searchable and connects related files. With the help of small Goshen College grants, a number of people, including students, have worked on the tedious and time-consuming task of digitally recording all of the old mini-audio-cassettes and video (VCR) tapes that are experiencing rapidly deteriorating sound quality. 11 We have also had to work on converting an older database format that connects all of the pieces of the project together. A huge job for the future will be to insert tags into the oral material to be able to skip to those places based on keywords.
New Electronic Resources for Texts in Manding Languages Valentin Vydrin Introduction 1 Since 2009, there has been continuous work conducted on electronic resources for Manding languages in Western Africa. In 2011, a Bamana Reference Corpus (Corpus Bambara de Référence) was published online  (Vydrin, Maslinsky, Méric et al. 2011 -2017) , and as of March 2017 it accounts for 3,846,094 words, about 700,000 of these being within the disambiguated subcorpus. 2 In November 2014, a Bamana Electronic Library was made available online. 3 A Maninka Corpus was opened to the public in April 2016  (Vydrin, Maslinsky, Rovenchak et al. , 2016 -2017) , and a Maninka Electronic Library was open to the public at the end of 2016. 4   1 This work is supported by a public grant overseen by the French National Research Agency (ANR) as part of the "Investissements d'Avenir" program (reference: ANR-10-LABX-0083).
2 All the texts in the Corpus are automatically annotated for part of speech tags and for French glosses; the automatic annotation is based on a lexical database (electronic dictionary), Bamada, and on a formalized set of morphological rules. Originally, in the automatically analyzed texts, more than 70% of all words were annotated ambiguously (i. e. more than one variant of analysis was produced by the program); recently, thanks to the improvement of our electronic tools, this rate was reduced to 60%. At the next stage, the texts are treated (disambiguated) by human operators who should have a good knowledge of Bamana language and Bamana grammar; they select the correct analyses among those suggested by the automatic analyser, or produce them (if no correct analysis is suggested by the program).
The Bambara Library The availability of texts in Manding languages in Mali is ambiguous. On one hand, Bambara is the country's most prominent language, spoken by 80% of the population, and is well represented in electronic mass media. There is a written press in Bambara: the Kibaru monthly has existed since 1971, the Jεkabaara monthly has existed since 1984, and a number of other periodicals have been launched (but disappeared more or less quickly). The number of books published in Bambara in Mali is considerable: in my bibliographic database, which is not exhaustive, there are five hundred Malian publications. While this may not be very impressive for a language with more than twelve million speakers (and even ridiculous if compared with the written output in any small language of Europe, such as Estonian or Latvian), it is still significant if we take into account the fact that Mali is firmly entrenched in the bottom twenty countries of the Human Development Index.
Bambara does not have official language status in the Republic of Mali, is not used in administration, and is used only marginally in the education system. Among these books, booklets predominate; only around fifty books in my database exceed one hundred pages. Included in these are textbooks and religious books, but also a number of fiction books and collections of oral literature texts. While it is too early to discuss a fullyfledged written literature, an embryo literature does exist. 5 Despite the hundreds of publications in Bambara, it is not an exaggeration to say that the language remains almost exclusively an oral one. Bambara publications are practically invisible in bookshops 5 For a survey of literatures in Manding languages, see the page Littérature en mandingue by Jean Derive on the ELLAF website, http://ellaf.
But will it become popular among the Malians who visit internet cafés in Bamako and Ségou? Or among village dwellers who connect to the internet by the means of a GPRS or 3G modem? I hope that the Bibliothèque will play some role in the preservation of the Manding cultural heritage, and that at least some Malians will read the books and newspapers downloaded from our site. 9   9 We began using Google Analytics to track the number of visitors to the Bambara Electronic Library in February 2016. During one month, more than 3,500 documents The Bibliothèque Électronique Bambara is a small part of a global project of Bambara language documentation. The Corpus Bambara de Référence is the larger component, an annotated electronic corpus of texts: http://cormand. huma-num. fr. So far, to my knowledge, it is the only open-access mid-size corpus of a language from Sub-Sahara Africa.
16 However, there is a written tradition in Nko writing, in which an original alphabet for Manding has existed since 1949 when it was introduced by Solomana Kantè. The alphabet began to flourish after 1984, mainly in Guinea, but also in neighbouring countries. 17 Today, the number of people literate in Nko can be counted in the hundreds of thousands; there are several periodicals in Nko,  18  and there are more than four hundred Nko book titles in my database. In co-operation with Guinean colleagues from the IRLA (Institut de Recherches Linguistiques Appliquées) and Ńkó Dúnbu (the Nko Academy), a Maninka Electronic Library project which includes books and periodicals was open for public at the end of 2016 (http://cormand. huma-num. fr/maninkabiblio/index. jsp). It follows the same model as the Bambara Library.
Kirill Maslinsky and Andrij Rovenchak, who has done excellent work in converting Nko publications into electronic texts, have combined three sources for the development of the Maninka electronic database: an enlarged version of Vydrin's dictionary (Vydrine 1999); a word frequency list generated on the basis of the preliminary version of the Nko Corpus containing two million words; and an electronic version of the French-Nko Dictionary  (Kantè 2012). The resulting electronic dictionary, Malidaba, is used for the morphological analysis of the Maninka/Nko Corpus. A "cleansing" of Malidaba is being carried out, which consists mainly of the elimination of duplicates and providing all the entries with French, English and Russian glosses. In April 2016, when the first version of the Maninka Corpus was published online, some 15% of the Malidaba had been cleansed; in March 2017, when the second update of the Corpus took place, this rate reached 54%.
Today, the production of documents with sound and pictures (documentary films, etc. ) might be a way to recover these texts for the local population. Researchers in anthropology and oral traditions often pose questions about the "restitution" or the "return" of data from field recordings to the communities where they were collected and where the producers or authors live. The debate about"restitution" has recently received a lot of attention  (Glowczewski 2005 (Glowczewski , 2009;; Bell et al. 2013). We aim to illustrate, on the basis of oral literature research in Madagascar, that many of the issues raised are not new; some of the questions even date back to Evans-Pritchard's research in the 1950s (Evans-Pritchard 1969: chapter 6). Oral literature in Madagascar is a valuable case study for an examination of these topics, particularly given the history of literacy, of the collection of traditional heritage, and of book publishing in this country, which has a longer history than publishing in other formerly colonised countries in sub-Sahara Africa.
These systems have revealed similarities between leaf and root responses, but have also revealed major differences. Whole-genome variation studies have shown differences in global genetic programs between roots and shoots during pathogen invasion  [15] [16] [17] [18] [19] [20]. For example, most of the genes activated in beech roots infected with Phytophthora citrocola had no known function or do not match database sequences for genes activated in the aerial parts of plants  [15]. In A. thaliana roots, most of the genes found to be differentially expressed following infection with the fungus Fusarium oxysporum were less strongly expressed than in leaves inoculated with the same fungus and showed tissue-specific regulation  [17, 20]. Moreover, the behavior of the interaction may differ between different types of infected organ  [12, 21].
RT-quantitative PCR Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) experiments were performed with 5 μl of a 1:50 dilution of first-strand cDNA and SYBR Green, according to the manufacturer's instructions (Eurogentec SA, Seraing, Belgium). Gene-specific oligonucleotides (S1 Table ) were designed with Primer3 software (http://frodo. wi. mit. edu), and their specificity was checked by analyzing dissociation curves after each run. Genes encoding a mitochondrial NADH-ubiquinone oxidoreductase subunit (AT5G11770) and a mitochondrial inner membrane translocase (AT5G62050) were selected as constitutive internal controls  [46]. For microarray validation, RNA was isolated from non-inoculated roots (NI), and from roots 2. 5 hours after inoculation (hai), 6 hai, 10. 5 hai and 30 hai with P.
Array hybridization and analysis In two independent experiments, roots from the ecotype N60000 were inoculated with water or with P. parasitica to establish a compatible interaction. Total RNA was extracted as described above, and cDNA synthesis, sample labeling, hybridization procedures and data acquisition were performed at the NASC microarray platform  [47]. The dataset is available from the GEO database at the NCBI under accession number GPL198. The transcriptome statistical analysis was performed as previously described  [30]. After quality control with the Bioconductor package "simpleaffy" (Crisipn Miller), the cel-files were quantile-normalized with the "gcrma" package of Bioconductor  [48]. Then, a quality control filter was performed. If the log2 ratios for the two time series differed by more than 75% of the mean of the two log2 ratios, the gene concerned was removed from subsequent analyses.
Each of the remaining genes was tested for significant up-or downregulation by ANOVA analysis of variance and p-value correction by false discovery rate (FDR)  [49]. Genes with adjusted p-value <0. 05 and an absolute fold-change of 2 or more were considered to be differentially expressed. For clustering, the data were first mean-centered and log-2-transformed with Epclust (http://www. bioinf. ebc. ee/ EP/EP/EPCLUST,  [49]. Hierarchical clustering (Pierson correlations, mean linkage) and kmean clustering (default parameters) were performed with Genesis software (http://genome. tugraz. at/genesisclient/genesisclient_description. shtml). For all cluster analyses, we used Virtual plant 1. 3 programs to assess the overrepresentation of terms from the MIPS Functional Catalogue Database (FunCatDB, http://virtualplant.
Principal functions governed by transiently modulated genes in P. parasitica-infected Arabidopsis roots We investigated the principal functions involved in early root responses to infection with P. parasitica, by identifying the cellular and molecular functions overrepresented among those triggered by the transiently regulated genes from clusters I, III and IV, and by the generally up and downregulated genes of clusters VII and VIII, respectively (S5 and S6 Tables). This analysis was performed with MIPS Functional Catalogue Database (FunCatDB) terminology  [50, 51]. Validation by RT-qPCR of cluster VIII can be considered as sub-optimal. We nevertheless analyzed it and results must be considered with caution. The regulation of primary metabolism, such as amino-acid metabolism, carbon metabolism and polysaccharide metabolism, was significantly modulated during the colonization of Arabidopsis roots by P.
VQ29 encodes a VQ motif domain-containing protein involved in restricting P. parasitica infection In order to validate the role of the genes modulated during early infection in the outcome of the interaction, we performed a functional analysis of a set of genes. We then focused on genes strongly induced upon infection, either transiently during penetration (cluster I), or continuously, throughout the establishment of infection (cluster VII). Candidate genes were selected on the basis of several criteria, including their fold-change expression upon infection (from 2. 2 to 1587). We focused principally on uncharacterized genes, to identify new functions, omitting genes identified with GENEVESTIGATOR software to be activated nonspecifically by foliar biotic stress or by hormone applications, and PAMP or elicitor treatments.
Our results go against this hypothesis, because energy production through glycolysis appeared to be downregulated in infected roots, whereas ATP synthase genes were upregulated during penetration. Glycolysis contributes to ATP production through glucose consumption. Plant defenses to pathogen infection are commonly fuelled by increases in the Analysis of defense-related marker genes expression in roots from wild-type and vq29 mutant plants. RNA was isolated from non-inoculated roots (NI) and from roots 6 hours after infection (6 hai). RT-qPCR data are presented as relative transcript abundance for genes: ACS2 and ACC, two markers for the ET biosynthesis; AOS, a marker for the JA biosynthesis; PR4 and PR3, two marker genes for the ET and JA signaling pathways; ICS1, a marker for the SA biosynthesis; PR2 and PR5, a marker gene for the SA-mediated signaling pathway; WRKY33, involved in the PTI pathway and PAD3, involved in Camalexin biosynthesis.
Acknowledgments We thank the  Microscopy Platform-Sophia Agrobiotech Institut-INRA, UNS , CNRS , UMR 1355-7254 ,  INRA PACA, Sophia Antipolis  for access to instruments and technical advice». The authors thank  Elodie Gaulin  ( UniversitePaul Sabatier, Toulouse, France ) for the help with rapid infection test.
We are currently developing a bio-shape similarity system for supplying high-throughput protein shape similarity applications within massive datasets. The proposed system is powered by a global-to-local shape similarity system which exploits shape elevation and local convexity attributes. In the first step, a global similarity is computed between the shape descriptors associated to each protein input. The procedure outputs best N similarities chosen by the user, within a query-to-cluster approach. The second stage is a patch-based local similarity computation method which is designed to find the best similar target from the cluster for supplying query-to-target protein retrieval applications. The local patch-based similarity comparison benefits of a multi-CPU implementation, offering thus fast query search capabilities within massive datasets.
I. INTRODUCTION AND MOTIVATION Structural biologists face a rapid growing of the number of protein structures in the Protein Data Bank  [1]  (130000 structures in 2017) which induces a considerable need for fast protein similarity search methods able to screen such large databases in a reasonable amount of time. Since protein 3D structures are more conserved during evolution than their respective amino acid sequences  [7] , sequence-based protein similarity search methods fail to retrieve structural homologs that share low sequence homology. Protein structural similarity search methods such as DALI  [11] , CE  [12] , FAST  [13]  or FATCAT  [14]  that use different methods to align protein structures and compute their similarity, notably using the Root Mean Square Deviation of their alpha carbons.
Most of the existing protein comparison methods share the major limitation that they are too computationally expensive to search a large protein structure database in a reasonable amount of time  [15]. In this paper, we introduce a shape-based method which allows to perform high-throughput protein classification without relying on human operator intervention. In addition, the proposed method is designed to perform fast query search within massive datasets. The present research work introduces a global-to-local framework designed in a complementary fashion, along with a multi-CPU implementation, in order to cope with rapidity constraints. Our paper is organized as follows: Section II describes the proposed global-to-local Protein Shape Similarity Search System (PS4), followed by Section III which presents experimental results and the performance evaluation on the SHREC 2017 (SHape REtrieval Contest) BioShape dataset  [4].
III. RESULTS AND PERFORMANCE EVALUATION This section presents the performance evaluation of the proposed framework, PS4, on the dataset made available for the SHape REtrieval Contest (SHREC 2017) BioShape track  [4]. We analyse the proposed system in terms of accuracy, runtime and memory usage. Dataset. The dataset consists in 10 queries (q 11 ,. ,q 20 ) (selected from the molecule of the Month collection  [9] ) and 5484 targets. In order to allow accurate validation, for two queries (q 11 and q 14 ), identic protein were included in the target set. Evaluation measures. In the SHREC 2017 BioShape track, the protein similarity evaluation relies on the 3DZM method  [6]  which measures the accuracy by comparing the correlation coefficients computed between the query and each target. More details about the dataset and the evaluation protocol can be found in the SHREC 2017 BioShape track  [4].
In addition, while for some queries (i. e. q 12 , q 13 , q 17 , q 18 ) the global minimum was lost by the local comparison stage, for the remaining queries (q 15 , q 16 , q 19 , q 20 ), the global minimum was correctly maintained. While providing a rapid protein retrieval framework, there is still room for improving the local patch-based similarity computation stage by searching more stable and intrinsic features w. r. t. the dataset (shape, size, resolution).
B. Runtime and memory usage The proposed algorithm is implemented in C/C++ and runs on a 64b Linux machine equipped with 32Gb of RAM memory and an Intel Xeon running at 2. 3 GHz. Less computationally expensive stages, i. e. the descriptors' computation (MS-DEM, C map ) and the global comparison, are designed for simple-CPU implementation. The most expensive stage, i. e. the pairwise patch-based local comparison of convexity maps benefits of a multi-CPU implementation. Simple-CPU global comparison of MS-DEMs. The first row of Table I resumes the average runtime for extracting the MS-DEM descriptor for one model belonging to the protein pool of the SHREC 2017 BioShape track  [4]. The computation time for comparing one query against the entire protein pool  In order to avoid the computational burden, the pairwise local comparison procedure is implemented on N CP U = 24 cores, taking in average 1 min 15 sec for providing the best similar target.
When compared to the simple-CPU implementation, the parallelization allows to reduce the runtime by an average factor of 46. This result emphasizes the fast query search capability detained by the proposed protein shape similarity search system, PS4. Memory usage. The average memory usage for storing the MS-DEM descriptor is 1. 058 kb. The second row of Table  I  illustrates the memory usage for the target m10001 depicted in Figure  1. The overall memory usage required by the MS-DEM descriptor and the associated convexity map C map is 2. 61 Mb. When compared to the input mesh storage, (Figure  1 b )), the proposed descriptors reduce the memory usage by a factor of 3, being therefore suitable for processing massive datasets.
IV. CONCLUSIONS AND FUTURE WORK This paper presented the Protein Shape Similarity Search System, (PS4), a global-to-local geometric-based protein similarity framework designed for supplying fast query search within massive datasets. The main features which ensure the rapidity of the proposed system operate at two levels: (i) software architecture: global and local shape similarity computation for fast query-to-target computation, and (ii) software implementation: multi-CPU optimization of local comparison. This gives rise to a protein similarity system designed in a complementary fashion: the global comparison stage allows rapid selection of best candidates, while the local stage provides best target selection among them. Experimental results on the SHREC 2017 BioShape dataset  [4] , containing 5484 models, demonstrate that our approach detains fast query search capabilities for supplying high-throughput queryto-target protein retrieval applications.
Findings We therefore developed ASaiM, an Open-Source Galaxy-based framework dedicated to microbiota data analyses. ASaiM provides a curated collection of tools to explore and visualize taxonomic and functional information from raw amplicon, metagenomic or metatranscriptomic sequences. To guide different analyses, several customizable workflows are included. All workflows are supported by tutorials and Galaxy interactive tours to guide the users through the analyses step by step. ASaiM is implemented as Galaxy Docker flavour. It is scalable to many thousand datasets, but also can be used a normal PC. The associated source code is available under Apache 2 license at https://github. com/ASaiM/framework and documentation can be found online ( http://asaim. readthedocs. io/ ).
These techniques are giving insight into phylogenetic properties and metabolic components of microbial communities. However, meta'omic data exploitation is not trivial due to the large amount of data, high variability, incompleteness of reference databases, difficulty to find, configure, use and combine the dedicated bioinformatics tools, etc. Hence, to extract useful information, a sequenced microbiota sample has to be processed by sophisticated workflows with numerous successive bioinformatics steps  [1]. Each step may require execution of several tools or software programs. For example, to extract taxonomic information with the widely used QIIME  [2]  or Mothur  [3]  , at least 10 different tools with at least 4 parameters each are needed. Designed for amplicon data, both QIIME and Mothur can not be directly applied to shotgun metagenomics data.