dataesr/scientific-paragraphs-categorization huggingface dataset:
Identification of over-represented canonical pathways and biological functions Functional enrichment of canonical pathways and biological functions was performed using Ingenuity Pathways Analysis (Ingenuity Systems, Inc. ). Canonical pathways refer to pathways curated by Ingenuity as part of its knowledgebase, based on extensive characterization in the peer-reviewed literature published using human, mouse, and rat experimental models. These typically represent common properties of a particular signaling module, mechanism, or pathway. IPA examines differentially expressed transcripts in the context of known biological functions, mapping each gene identifier to its corresponding molecule in the Ingenuity Pathways Knowledge Base (IPKB). For all analyses, the p-values -representing the statistical over-representation significance -were generated using the right-tailed Fisher's Exact Test  [38]  and were adjusted using the Benjamini-Hochberg Multiple Testing correction  [39].
Phylogenetic tree construction To construct the phylogenetic tree, we used the 611 transcriptomic sequences that have been significantly aligned on the transcriptome reference of the 13 species having the largest numbers of mapped sequences and the largest degrees of shared sequences. Sequences and matched transcripts were aligned using the Needleman-Wunsch multiple alignment algorithm  [42] , using the multialign function in MATLAB (open and extend gap penalties have been taken into consideration). Genomic divergences between sequences were calculated using the Jukes-Cantor method  [43] , based on the 'NUC44' scoring matrix. Indel mismatches have not been taken into consideration for the computation of genomic divergences. The phylogenetic tree was constructed by using the neighbor-joining method (NJ)  [44].
The authors confirm that all data underlying the findings are fully available without restriction. The unassembled reads have been uploaded on the NCBI-SRA database  [45]  and are available via the BioProject SRP032520. Moreover, we released the annotated transcriptome assembly in LabArchives (http://www. labarchives. com/) and are available via the DOI http://dx. doi. org/10. 6070/H4FQ9TKP.
Retrotransposons account for almost half of our genome. They are mobile genetics elements--also known as jumping genes--but only the L1HS subfamily of Long Interspersed Nuclear Elements (LINEs) has retained the ability to jump autonomously in modern humans. Their mobilization in germline--but also some somatic tissues--contributes to human genetic diversity and to diseases, such as cancer. Here, we present euL1db, the European database of L1HS retrotransposon insertions in humans (available at http:// euL1db. unice. fr). euL1db provides a curated and comprehensive summary of L1HS insertion polymorphisms identified in healthy or pathological human samples and published in peer-reviewed journals. A key feature of euL1db is its sample-wise organization. Hence L1HS insertion polymorphisms are connected to samples, individuals, families and clinical conditions.
D44 Nucleic Acids Research, 2015, Vol. 43, Database issue In the past 5 years, advances in deep-sequencing technologies have shed a new light on the extent of L1-mediated genome variation  (20, 21). L1HS represents ∼3. 3 Mb of the reference human genome (∼0. 1%). These L1 copies are often referred to as 'reference L1HS elements'. However, each individual has additional L1HS copies not present in the reference genome, referred to as 'non-reference L1HS elements', which contribute to our genetic diversity  (22) (23) (24) (25) (26) (27). On the average, two human individual genomes differ at 285 sites with respect to L1 insertion presence or absence  (27). These recent studies have also led to the discovery that L1HS is not only able to mobilize in the germline--resulting in inheritable genetic variations (3,28,29)---but can also jump in some somatic tissues, such as brain  (30) (31) (32)  or in many cancers  (26, (33) (34) (35) (36) (37) (38) (39).
DATABASE STRUCTURE AND CONTENT The euL1db database is organized in several tables, which are interconnected in a dynamic way, through the MySQL relational database management system. A simplified view of the object relationships is depicted in Figure  1  and a more detailed view of the underlying database structure is shown in Supplementary Figure  S1. The 'Study' table contains information about the study in which L1HS insertions were cataloged and mapped. Typically, a study will correspond to a single publication. Each study uses a coherent set of methods and analyses. Because these parameters determine to a large extent the variability that exists between data sets, all data in euL1db are organized by study. The 'Individual' table relates to the source individuals from whom the samples were originally taken from.
The total number of SRIPs and MRIPs included for each study is graphed in Supplementary Figure  S3. In addition to these main tables, euL1db uses a 'Method' table, which contains the methods used to call SRIPs in the different studies, and a 'Family' table, which classifies the familial relationships between euL1db individuals (mostly from the 1000 Genomes Project). An individual without known relative in euL1db is not linked to any family. The data contained in euL1db originate from peerreviewed publications and have been manually curated and entered. The source of data and the curation process are detailed in Supplementary Methods and in Supplementary Table  S1. The reference L1HS insertions have been processed from the UCSC RepeatMasker track table. The summary statistics at the time of writing are displayed in Table  1.
DATA ACCESS euL1db can be interrogated through a user-friendly Web Server (http://euL1db. unice. fr). A set of detailed tutorials and examples of use are accessible from the 'Help' tab. The detailed description of the Web Server architecture is described in Supplementary Figure  S1. There are several ways to query euL1db: (i) by searching SRIP or MRIP located in a single locus (genomic region, gene) or in a single individual ('Search' tab); (ii) by browsing the different tables and using filters to select a specific subset of data across and within studies, families, individuals, samples, insertions ('Browse' tab); (iii) by batch query using a list of multiple loci (genomic coordinates) or genes (gene names) ('Utilities' tab). Users can choose to display L1 insertions as SRIP or MRIP in (i) graphical-(UCSC genome browser, dbVar genome browser)  (40, 41) ; (ii) tabular-(sortable html tables); or (iii) text-formats (including in standard BED format for subsequent analyses with other tools).
RELATIONSHIP AND DIFFERENCES WITH OTHER DATABASES Several resources are related to--but distinct from--euL1db. Repbase is a database of consensus repetitive DNA sequence and as such does not contain any localization information  (42). One of its entries is the L1HS consensus sequence and has been subsequently used to annotate the human reference genome and to identify the genomic loci corresponding to L1HS elements   (40). The reference L1HS elements included in the 'Reference' table of euL1db have been processed and annotated using the latter. dbRIP was an early effort to catalog and annotate polymorphic retrotransposon insertions in humans  (43). In contrast to dbRIP, euL1db stores data in a sample-wise manner and contains the most recent data sets obtained by highthroughput sequencing, including those from the 1000 Genomes Project.
Although dbRIP could not be directly included in euL1db since samples are not documented in dbRIP, 94% of dbRIP L1HS records have an MRIP equivalent in euL1db (Figure  1C ). dbRIP has also unique features since it contains non-autonomous human retrotransposons such as Alu or SVA sequences and not only L1HS insertions. As a particular case of structural variation, L1 retrotransposon insertions are also documented in dbVar/DGVa or DGV as mobile element insertions (MEI)  (41). The data structure logics in dbVar/DGVa and euL1db are comparable (sample-wise variants and merged variants). euL1db is specialized for L1HS insertions, while dbVar/DGVa can include any type of structural variants, including MEI. However, the set of information for L1HS insertions provided by euL1db is much more exhaustive, and only a single study (out of 32 at the time of writing) stored in euL1db was also deposited in dbVar/DGVa.
CONCLUDING REMARKS High-throughput sequencing technologies have considerably fostered the study of L1-mediated genomic variation and its impact on human health. We anticipate that this trend will continue in the next years, particularly with the availability of long-reads sequencing approaches, which might greatly facilitate the detection of L1HS insertions and their accurate positioning on the genome by generating reads that span the entire element and both flanking regions. In this respect, euL1db database and server have been tailored to support a considerable increase of SRIP, while keeping a fast-response time. To summarize, euL1db provides a centralized and user-friendly access to known germline and somatic L1HS insertions, which will be critical to elucidate the physiological or pathological impact of novel L1HS insertions.
FUNDING  Institut National de la Santé Et de la Recherche Medicale  and the  Institut National du Cancer  [ 2009-340  to G. C. ]; the  European Research Council  [ 243312  to G. C. ];  Agence Nationale pour la Recherche  [ ANR-11-LABX-0028-01  to G. C. ]. Funding for open access charge:  European Research Council  [ 243312  to G. C. ].
The data obtained will allow us to precisely measure the absolute sky brightness and polarization of all the components of the sky emission in the observed frequency range, separating the primordial and extragalactic components cleanly from the galactic and zodiacal light emissions. The aim of this Extended White Paper is to provide a more detailed overview of the highlights of the new science that will be made possible by PRISM, which include: (1) the ultimate galaxy cluster survey using the Sunyaev-Zeldovich (SZ) effect, detecting approximately 10 6 clusters extending to large redshift, including a characterization of the gas temperature of the brightest ones (through the relativistic corrections to the classic SZ template) as well as a peculiar velocity survey using the kinetic SZ effect that comprises our entire Hubble volume; (2) a detailed characterization of the properties and evolution of dusty galaxies, where the most of the star formation in the universe took place, the faintest population of which constitute the diffuse CIB (Cosmic Infrared Background); (3) a characterization of the B modes from primordial gravity waves generated during inflation and from gravitational lensing, as well as the ultimate search for primordial non-Gaussianity using CMB polarization, which is less contaminated by foregrounds on small scales than the temperature anisotropies; (4) a search for distortions from a perfect blackbody spectrum, which include some nearly certain signals and others that are more speculative but more informative; and (5) a study of the role of the magnetic field in star formation and its interaction with other components of the interstellar medium of our Galaxy.
4 • ) spectrometer that will compare the sky frequency spectrum to a nearly perfect reference blackbody and measure the absolute sky emission over the same frequency range. The data from these two instruments will enable PRISM to carry out breakthrough science by answering key questions in many diverse areas of astrophysics and fundamental science as well as providing the astronomical community with high quality, full sky observations of emission over a large frequency range. Highlights of the new science fromPRISM include: 1. 1 Ultimate galaxy cluster survey and census of structures in our Hubble volume Because of the tight correlation between integrated y-distortion and cluster mass as well as the redshift independence of the surface brightness, the Sunyaev-Zeldovich (SZ) effect offers the best method for assembling a catalog of clusters at high redshift to be used for cosmology.
1. 5 Probing Galactic astrophysics PRISM will have a major impact on Galactic astrophysics by providing a unique set of all-sky maps. ThePRISM data will extend Herschel dust observations to the whole sky, map the absolute sky intensity and polarized emission with high sensitivity in more than 20 different frequency bands, and also map emission lines key to quantifying physical processes in the interstellar medium. The survey will have the sensitivity and angular resolution required to map dust polarization down to sub-arcminute resolution even at the Galactic poles. No other project provides a comparable perspective on interstellar components over such a wide range of scales. ThePRISM data will provide unique clues to study the interstellar medium, the Galactic magnetic field, and star formation, and will address three fundamental questions in Galactic astrophysics: What are the processes that structure the interstellar medium? What role does the magnetic field play in star formation? What are the processes that determine the composition and evolution of interstellar dust?.
Other Galactic foreground emission (synchrotron, free-free, spinning dust, and molecular lines) and radio sources will not contaminate SZ cluster detection significantly after being subtracted out using PRISM's lower frequency data and narrow band observations. They are therefore neglected for this simulation. The SZ thermal emission signal (tSZ) is recovered from the maps using the so-called Internal Linear Combination (ILC) method over a set of spectral windows, which define a set of scales adjusted to match the resolution of the different observed maps. A thermal SZ map is first obtained at 3. 8' resolution using all 15 bands, each smoothed to 3. 8'. Fourteen maps at 3. 2' resolution (corresponding to that of the 160 GHz Hundreds of SZ clusters are detectable on this very small patch (0.
Cluster counts are therefore a powerful probe of neutrino mass  [189] , given constraints from the primary CMB anisotropies. For instance, changing the total neutrino mass from 0. 057 to 0. 096 eV (lower limits for normal and inverted hierarchy respectively) changes the value of σ 8 by 0. 01, three to four times the standard deviation of the contour ellipses in Fig. 4. Despite their simplicity, these examples illustrate the power of thePRISM cluster catalog as a cosmological probe. The above forecasts rely only on the cluster abundance data. However,PRISM will also provide extensive data on the large-scale distribution of detected clusters that can be exploited for correlation analysis on large scales, or a large scale structure (LSS) density distribution reconstruction that has an equivalent and complementary constraining power for cosmological parameters, and hence will improve the overall result.
Synergy of the two instruments There is significant added value to observing with the two instruments together on the same payload. The observed data cubes from the absolute spectrophotometer comprise CMB and foreground emission, mixed and blended by both superposition along the line of sight and averaging across several lines of sights smeared by the 1. 4 • beam. Foreground emissions include galactic dust cirrus, spectral lines in molecular clouds, extragalactic sources, clusters of galaxies, and variable radio sources. To achieve the ambitious precision goals of the spectrophotometer for CMB spectral distortion measurements, it is essential that these sources of foreground emission are characterized and subtracted using the narrow beam imager data. Without the high angular resolution data from the imager, precise measurement of the CMB spectral distortions are possible only on a reduced fraction of clean sky, resulting in significant degradation of its global sensitivity.
These data will be used together to provide a combined constrain on dark energy and the growth of structure from weak lensing, baryon acoustic oscillations and SNIa. Unlike the previous two projects,Euclid is a space-based survey, resulting from the merging of a baryon acoustic oscillation redshift project (SPACE) and a weak lensing photometric project (DUNE) both proposed to ESA. The resulting survey will use these two techniques to constrain the dark universe using the measured redshifts of about 50 million galaxies over 15000 square degrees and the photometric information of about 20 billion sources. The launch date of theEuclid satellite is currently expected to be around 2020. A comparison of these projects was recently compiled by Font-Ribera et al. [76] , who compared the expected constraints on the isotropic measurement of the cosmic distance scale from the spectroscopic DESI andEuclid BAO projects in addition to constraints from other earlier future or ongoing surveys.
Introduction Open archives are less open than they should be. In particular, institutional repositories contain a growing number of metadata without full text or with full text only for authorized users. This is not in line with the underlying principles of the open access (OA) movement that defines open access "as a comprehensive source of human knowledge and cultural heritage that has been approved by the scientific community" 1 and that requires freely available scientific literature provided by open archives (green road) and OA journals (gold road). Freely available means "free of charge, and free of most copyright and licensing restrictions"  (Suber 2012, p. 4). Twenty years after the arrival of the first open repository called arXiv 2 and ten years after the Berlin declaration on open access, the situation is not really satisfying.
Also, their content may include more than current output from faculty. Smith (2008) details a "wide variety of materials in digital form, such as research journal articles, preprints and post prints, digital versions of theses and dissertations, and administrative documents, course notes, or learning objects. " Other repositories include datasets, multimedia or cultural and scientific heritage. The exact number of open archives is unknown. The statistics of the main international directories 5  vary between 2,600 and 3,600 sites but the real number is probably higher. OpenDOAR counts 2,616 repositories of which 2,163 are listed as institutional (83%). The ROAR directory contains 2,388 institutional or multi-institutional repositories, that is 66% of all sites (3,621). In spite of different figures, there is no doubt that these sites represent the most important part of the so-called green road to open access.
Methodology The empirical data in our study are from a sample of 25 institutional repositories. All repositories were selected using the repository search tool OpenDOAR, the authoritative directory of academic open access repositories. The following search criteria were applied:  Repository type: Institutional  Content type: PhD theses and articles (at least)  Size: 10,000+ items The search was conducted by region (Europe, Asia, Africa, Australasia, North America, South America/Central America/Caribbean), and only those repositories that are operational (i. e. recently updated), that contain different document types including non commercial literature (theses, reports etc. ), that allow for filtering by document type and access options (full-text vs. restricted/no access to full-text) as a browse and/or search functionality and that indicate the exact number of results (retrieved items) were selected.
Secondly, we conducted a detailed search and/or browsed on each site for specific document types: articles, books and book chapters, conference proceedings and communications, reports, PhD theses, and working papers (unpublished). We also looked for patents and datasets but did not include them in the global analysis. For each document type, we distinguished the items with free and non-restricted access to the full text (open access) from those with restricted access (embargo, intranet, authorized users, etc. ) or without full text (reference only). Whenever possible, we also made this distinction for the entire repository content. The repositories were selected in February 2014. The analyses of each site were conducted in February and March 2014.
Other results Some institutional repositories contain datasets and patents. We identified nearly 70,000 items in our sample; 60,219 datasets and 8,982 patents. While only 3% of the datasets were freely available, patents are disseminated with a degree of openness of 0. 61, which means that nearly 2/3 of the patents are freely accessible in these repositories. This is surprising for two reasons: the global tendency for open data and the often high protection of patents. Often the real nature of access restriction remains uncertain. Are the documents under embargo and will they be released and openly accessible in the future? Are they restricted to on-campus access only or is it both of these? And what about missing full text, records without documents? From our results we can only make a cautious guess, that embargo periods represent a small part of access restrictions (in our sample only 2%) and that most of the lack of openness is caused by on-campus only access and by the deposit of metadata without a corresponding document.
Finally, our study was not designed as a longitudinal survey to detect developments and tendencies over three years or more. Yet, our data allow for some anecdotal evidence. The degree of openness of the Spanish CSIC repository declined between 2007 and 2014 from 0. 99 to 0. 56, which confirms other observations that with time, the repositories not only contain more and more items and metadata but also become, at least partially, less open.
In the other case, repositories simply have not indexed the document type at all. The second difficulty is the complete lack of standardization or even harmonization. The typologies are more or less detailed, depending on local needs and habits. Some repositories distinguish between three different types of reports or five different theses and dissertations while others do not. Sometimes even the sub-collections of the same institutional repositoryinstitutes, departments, schools and so ondescribe their document types in different ways. Retrieving datasets is particularly difficult. We were looking for research results, raw data or small data, unpublished material that could be reused for verification, replication, datamining or meta-analysis. But only some of the repositories correctly index them as data.
This situation is even less satisfying because the largest part of lack of openness appears not to be due to embargo periods limited in time but to dissemination restricted to on-campus or institution-wide availability, without any specified time limits. So, is the glass half empty or half full? Is this lack of openness a transitory effect, a kind of collateral damage of institutional decisions, individual choices, political strategies and intellectual property laws that will disappear with the advent of full open access? Or on the contrary is it (and will it remain) a basic feature of the new and complex cohabitation of institutional repositories and commercial publishing? The future will tell. In the meantime, what should be expected is that institutions will clarify and be explicit about their open access policy and assure the same level of quality for repositories as they have always done for their catalogues and databases.