dataesr/scientific-paragraphs-categorization huggingface dataset:
41 A closed pattern is a pattern for which no element can be added without decreasing its extent, i. e. the set of molecules in which the molecular pattern occurs. Thus, by retaining only closed FEMPs the authors can condense the important set of FEMPs without losing information. However, closed patterns tend to be very long (number of fragments) since a large part corresponds to subfragments of a larger fragment. These redundant subfragments can be pruned without losing information. These resulting shorter representations have been called Representative Pruned Molecular Patterns (RPMPs). The illustrative example corresponds to a dataset of 295 chemicals annotated by their toxicity to aquatic life (223 toxic and 172 non-toxic chemicals). The Table  2  indicates the evolution of the number and length of the corresponding patterns in function of the growth rate values (minimum frequency threshold of 2.
Conclusion The characterization of a chemical fragment or a chemical pattern associated to a toxicological profile is of first interest by considering the continuous development of chemoinformatics tools around this topic. Owing to the fact that a single chemical fragment is not always responsible for the overall toxicity of a chemical, the present objective is to analyze the combination of chemical fragments (chemical patterns) leading to an increase or a decrease of toxicity starting from a referential toxic fragment. The first described approach corresponds to the Klopmann's method (CASE/MultiCASE) which extracts meaningful chemical fragments (named biophores) in function of their distribution between two datasets. Afterwards, these biophores were associated to QSARs or implemented in classification tools, leading to the first commercialized expert systems.
Concerning the extraction of chemical fragments, a second generation of tools was more recently developed, corresponding to the Pattern Growth-Based algorithms (like Gaston). They led to very interesting results in terms of characterization of the fragments and statistical results for the estimation of the toxicity. The last evolution corresponds to the search of representative subsets of frequent patterns. In this review, we emphasize the notion of Emerging Patterns (EP), whose extraction is based on the notion of contrast (growth rate) between two datasets. We are at the beginning for EPs but, their potential in terms of statistics and interpretability related to the toxicological profile of chemical derivatives is really promising. 43 The size of the EP set (number of patterns) in function of the size of the initial dataset is really an issue, and the notion of border does not seem to be sufficient to solve it.
4 ransitioning content features to metadata to make multimedia content as searchable as text is thus essential for every multimedia information retrieval system. Because the multimedia domain is so broad, multimedia resources are typically indexed using different, divergent standards, which makes retrieving multimedia resources even more difficult. 5 he abundance and diversity of content represented in different formats on the Web thus directly translates into a need for a common framework for describing and representing content by covering essential syntactic and semantic features. Many efforts have attempted to define a common lingua franca for the retrieval of Web-based multimedia resources, starting with the well-known MPEG-7 standard. However, MPEG-7's adoption is still limited because of its complexity and lack of interoperability.
w3. org/2008/WebVideo). 10  Among others, this activity hosts the Media Annotation Working Group (MAWG, www. w3. org/2008/WebVideo/ Annotations), which aims to develop a core vocabulary for retrieving multimedia resources on the Web. This core vocabulary is not just another metadata format; it is envisioned as being able to ensure that the information exchange among different metadata formats used by (canonical) processes or systems follow standardized and clear semantics. This standardization effort can be directly injected into the entire multimedia life-cycle process to improve interoperability with respect to data exchange. The main output of the MAWG is the Ontology for Media Resources 1. 0. 11 The purpose of the ontology is to overcome the current proliferation of multimedia metadata formats.
It addresses the interoperability problem between different metadata formats by providing a common set of properties, agnostic to any representation. It specifies the basic metadata needed for media resources as well as syntactic and semantic links between their values in the existing vocabularies. It is accompanied by the API for Media Resources 1. 0,  12  which provides uniform access to the elements it defines. Furthermore, the API enables the definition of queries irrespective of the underlying format in which the actual media resource is described.
Requirements The requirements for the Ontology for Media Resources and API for Media Resources are derived from two sources. The first is the conclusions from the Multimedia Semantics XG that led to the definition of the MAWG charter. The second is the scientific literature discussing multimedia metadata interoperability issues and their potential solution. Finally, the working group collected a set of use cases, derived a set of requirements from them, and distilled a set of core requirements. (See www. w3. org/TR/media-annot-reqs for use cases and requirements. ) Thus, both specifications are coined by the following requirements: Coverage: The ontology and API are not bound to a specific application domain, media type, or content representation.
Ontology for Media Resources 1. 0 The set of core properties that constitutes this ontology is based on a list of the most commonly used annotation properties from current multimedia metadata schemas. The properties were derived from the Multimedia Vocabularies on the Semantic Web report of the Multimedia Semantics Incubator Group (see www. w3. org/ 2005/Incubator/mmsem/XGR-vocabularies-20070724). We also compiled a list of use cases from a public call. Over the course of the group's work, we have mapped these core properties to more than 15 metadata and container formats from a range of communities. The set of core properties defined in the Ontology for Media Resources 1. 0 consists of 20 descriptive metadata properties (such as identifiers, language, contributors, creation date, genre, and ratings) and eight technical metadata properties (such as frame size, duration, and format).
The descriptive properties are media agnostic and apply to descriptions of multimedia works (such as movies) that are not specific to an instantiation (an AVI file, for example). The technical properties, bound to certain media types, are essential only when describing a particular instantiation of the content. Following the requirements of a core vocabulary, all properties are defined with explicit semantics to clarify and disambiguate their definitions in the context of a media resource description. Whenever these properties exist in other standards, as we outlined earlier, the Ontology   The set of properties modeled in the ontology corresponds to existing metadata formats currently describing media resources published on the Web. These correspondences have been defined in the form of mappings to provide an interoperable set of metadata, thereby enabling different applications to share and reuse metadata.
The selected metadata formats were those we deemed to be the most commonly adopted. Specifically, we selected the 19 media metadata formats and seven media container formats that are listed in Table  1. This list of formats is not closed, nor does it pretend to be exhaustive. A future version of the Ontology for Media Resources 1. 0 may include additional mappings if a new need or use case is identified. In this light, current work focuses on creating additional mappings for Schema. org and Atom. (See www. w3. org/2008/Web Video/Annotations/ drafts/ontologylO/additional-mappings. html for more details. ) The mappings defined between the Ontology for Media Resources 1. 0 properties and those of the selected metadata formats are available in metadata-format-specific mapping tables (see www. w3.
API for Media Resources 1. 0 The API for Media Resources 1. 0 enables interoperable access to metadata information related to media resources on the Web, with the defined core vocabulary as a recommended best practice. The MAWG discussed various design considerations, which led to the specification of global interfaces with specific parameters. This implies a minimal number of exposed interfaces ensuring a broad adoption and fewer security leaks. Furthermore, it reduces implementation work when designing applications or integrating the API into legacy systems. The API can be used in two modes of operation: asynchronous and synchronous. For this API, the asynchronous mode is considered the default, where calls return without waiting for the request to finish its execution. A call-back function is provided to be invoked when the request terminates.
On the other hand, synchronous calls wait for the request to terminate and directly return the result. Figure  2  illustrates the two scenarios for the API's use. In the first scenario, the API is encapsulated in a user agent, whereas in the second, it is implemented as a Web service. This API has two main parts: interfaces to access media resources and a set of core properties describing the information in an interoperable way along with their JavaScript Object Notation (JSON) serialization. The API is defined using WeblDL (www. w3. org/TR/WebIDL), which is an Interface Description Language (IDL) variant explicitly covering programming languages commonly used on the Web (such as ECMAScript). Following the ontology design, every property can carry its metadata information in either an unstructured (single value) or structured way.
Projects and Showcases As we mentioned earlier, the MAWG's goal is unified access to media resources on the Web. Recent works in the social media area heavily utilize media resources in their workflows, aiming to improve interactive communication between peers. This domain consists of three main parties: content providers, portal services, and consumers. Canonical processes define the connection between these parties. Here, the MAWG standardization effort can be directly injected into those processes to improve interoperability with respect to data exchange. In this light, Table  2  gives an overview of current scientific projects implementing.
14 It uses the Ontology for Media Resources as an interoperable target format (see Figure  3 ). The service supports a number of metadata standards, and proprietary formats from archive and broadcast organizations can be added. It is becoming increasingly important to make archive content accessible on the Web together with its metadata, making the Ontology for Media Resources a relevant target format for publication and interoperability with linked data. The Multimedia Metadata Ontology (M30) is a comprehensive model for representing multimedia metadata. 15 It is based on the foundational ontology DOLCE+DnS Ultralight and several ontology design patterns that have been aligned with the Ontology for Media Resources. M30 serves as a generic modeling framework for integrating existing metadata models and metadata standards rather than replacing them, also providing support for the Ontology for Media Resources.
The use of the Ontology for Media Resources is a driver for interoperability and allows the integration of other data sources within NinSuna. EventMedia aggregates a large dataset that consists of event descriptions (from the public event directories last. fm, eventful, and upcoming) together with media descriptions associated with these events and interlinked with the larger Linked Open Data Cloud. 18 A Web-based environment lets users explore and select events and view associated media. The Ontology for Media Resources has been used for representing the metadata of these media and has enabled interlinking with the Linked Open Data cloud (see Figure  6 ). All these projects use the core vocabulary to describe a media resource's information in a unified way. In addition to supporting the core vocabulary, the PrestoPRIME Semantic Converter, LMF, and NinSuna also implement the mappings defined by the MAWG-using Extensible Stylesheet Language Transformations (XSLT), for example.
These applications thus bridge the interoperability gap by providing multimedia metadata published in different source formats in a unified way. LMF further implements the API to enable a unified retrieval over the heterogeneous landscape of metadata formats available in the Linked Data Cloud. In addition to these projects, the following two open source showcases are a starting point for future implementations focusing on the API for Media Resources 1. 0. The first deals with a gallery showing images as well as its metadata information. (Both implementations are available online at http://mawg. joanneum. at. ) Here, the API is implemented as a Web service using the synchronous operation mode. The second showcase utilizes the API in a browser extension following the asynchronous operation mode.
Acknowledgments We thank the W3C MAWG Chairs Soohong Daniel Park and  Joakim Soderberg , the W3C team contact  Thierry Michel , and all the MAWG participants for their contributions as well as  Yiannis Kompatsiaris  for his valuable feedback on this article. This work has been partially supported by the  German Federal Ministry of Economics and Technology  under the  THESEUS Program  and by the  European Union 's  7th Framework Programme  ( FP7/2007-2013)  under grant agreement  231161 , PrestoPRIME.
Hence, VLDPws, based on the Laguerre tessellation, is efficient and precise in computing various protein properties. The good accuracy was previously benchmarked  (8, 22). The computed tessellation can be viewed in a static way owing to PyMOL software, or in an interactive way using Jmol software  (23). Moreover, VLDPws is the only online web server including the protein in a realistic solvent for drawing the tessellation.
Input protein structure and solvation The 3D protein structures must be in classical Protein DataBank format  (24). Preferentially, the structure should be recognized like a monomeric chain (see Figure  1a ). A topology file is created using GROMACS 4. 5. 3 (25). The hydrogens are added using OPLS-AA force field  (26). Finally, the SOLVATE program (  27 ) creates a shell of water around the protein. The SOLVATE parameters are a shell thickness of 5 A ˚, a solvent boundary set up to 2 (ngauss option). This first stage produces a pdb file including the protein and solvent coordinates (see Figure  1b ).
Computational aspect of VLDP outputs The source code of the program VLDP is written in Fortran 90. Several functionalities and output formats are available (see Figure  1e ): (i) Visualization of the tessellation is performed by PyMol (The PyMOL Molecular Graphics System, Version 1. 5, Schro¨dinger, LLC, www. pymol. org) and interactively with Jmol  (23). The output for PyMol is in Compiled Graphics Objects format, whereas the command 'draw' is used for Jmol. (ii) The residue volumes are given as sums of corresponding atomic volumes. An atomic volume is the volume of its corresponding Laguerre polyhedron. The Laguerre polyhedra are subdivided into elementary tetrahedra, the sum of which gives the polyhedral volume  (8). (iii) By definition, the contacts are specified by the Delaunay edges  (22).
DISCUSSION The VLDP program is based on the Laguerre tessellation used for geometrical analyses of protein structures. From this tessellation, both metric and topological measures can be deduced opening the way for finer analyses. The VLDP program performs a panel of analyses, such as (i) the calculation of residue volumes, (ii) the determination of residue contacts, (iii) the residue accessibility and (iv) the organization of the water network. Experimentally, the protein volume is obtained by measurements of partial specific volumes, e. g. by densitometry, or dilatometry, with the help of thermodynamic and hydrodynamic equations. Few developments had been made to compute it through in silico approaches. Only Tsai et al. (28)  gave predictions directly deduced from the sequence information, but this method is not available on any web server.
Web server VLDPws VLDPws provides a user-friendly web interface to the analysis of protein structures that combines metrics and topology. The homepage contains a short summary describing the interest of program and the properties computed. The only input that must be provided is the protein structure (preferentially monomeric or merged into one chain), in PDB format. Two possibilities are offered: either direct download from the Protein Data Bank (http://www. rcsb. org/pdb/home/home. do) (24)  or supply of a file, the filename of which must be given in a second window frame. In both cases, the pdb code and the used chain should be imperatively specified. At the bottom of the page, an example test with an url link is proposed. Additional tabs are as follows: (i) 'Contact', pointing to the authors' homepage; (ii) 'About', giving details on the methodology; (iii) 'Example', explaining or showing, on a concrete case, the input and output of the server (see later in the text).
Background step 'VLDP running' After checking the input PDB format, a shell of water is first computed with SOLVATE software  (27)  (see 'Materials and Methods' section and Figure  1b ). Then, using the atom coordinates of the extended system (protein+solvent), the Delaunay tetrahedra are built (Figure  1c ) by the sequential insertion algorithm (see 'Materials and Methods' section). The Laguerre tessellation is constructed simultaneously as the geometric dual of the Delaunay diagram (Figure  1d ). Then, all the properties of interest are computed by VLDP program (Figure  1e ), e. g. volume and face area of Laguerre polyhedra, inter-atomic and inter-residue contacts, graphical outputs and so forth.
Output Once the job is finished, the home page is updated to show the results. The results are given in various ways. The first information, on the top of the web page, is a global summary on the system under investigation: count of residues, count of protein atoms and the selected protein chain label. The data are confidentially stored during 2 months for later use. Confidentiality is guaranteed by an ID supplied to the user. Three links point to the data available for download: the first place contains a copy of the submitted pdb file; the second one has the solvated protein (pdb format) and the third link is a zip file containing all results. The protein (  29 ) is displayed online through three nice graphical representations generated with PyMol software: cartoon, Connolly's surface and Laguerre surface (see Figure  2a  and b ).
Each image can be zoomed by clicking on it. Another graph displays the inter-residue contact matrix with colour scale representing the contact strength (number of atomic contacts for one given residue, see Figure  2c ); the raw values can also be downloaded in a text file. The 'volume and area' section shows residue volumes (and area) in a partial table. The complete data can be downloaded as a text file. It also gives the volume per protein atom and the volume per water molecule at the solute-solvent interface. The second plot on the Result web page is the PIA accessibility along the sequence. Again, a partial table is displayed, whereas the complete table is available for download. Finally, an interactive visualization can be performed through the Jmol Applet  (25). The Laguerre surface appears by clicking on the 'Show Tessellation' button.
An example Figure  2  illustrates the results of a protein structure analysis of a fibrillarin homologue [PDB code 1FBN (29)], using Laguerre tessellation. As a confidence descriptor, the Laguerre surface is visually compared with Connolly's surface (Figure  2b ). To study the protein folds, the connectivity between residues is shown as a contact matrix indicating the strength of each interresidue contact (Figure  2c ). The contacts along the diagonal indicate, in general, a helix pattern, whereas off-diagonal contacts, parallel or perpendicular to the main diagonal, indicate parallel or anti-parallel strands (most often in b-sheets)  (30). The residue volumes given by VLDPws can be compared with our previous study (8) (Figure  2d ). Finally the surface versus core distribution of the residues can be probed by the accessibility analysis through the PIA measure (Figure  2e ).
ACKNOWLEDGEMENTS Parts of VLDP derive from an earlier Voronoi-based program developed by  Xabier Oyharcabal. FUNDING J. E. acknowledges grants from  Ministry of Research (MESR, France) University Paris Diderot, Sorbonne Paris Cite´(France) ; the  National Institute for Blood Transfusion (INTS, France) ; the  Institute for Health and Medical Research (INSERM, France) ; and  'Investissements d'avenir', Laboratoires of Excellence GR-Ex. (to S. L. and A. dB. ). University of Cergy-Pontoise (France)  and  CNRS (France)  (to J. E. and C. O. ). Funding for open access charge:  National Institute for Blood Transfusion (INTS, France).
Case selection Sixty-three participants were selected from the FRONTIER database resulting in a sample of 18 bvFTD, 17 AD patients and 28 age and education matched controls. All bvFTD patients met current consensus criteria for FTD  (Neary et al. , 1998; Rascovsky et al. , 2007)  with insidious onset, decline in social behaviour and personal conduct, emotional blunting and loss of insight. In light of the recent recognition of the phenocopy syndrome  (Hornberger et al. , 2008 (Hornberger et al. , , 2009) )  only bvFTD patients with evidence of clear decline as reported by the caregivers and atrophy on MRI scans were included in the study. All AD patients met NINCDS-ADRDA diagnostic criteria  (McKhann et al. , 1984)  for probable AD (see Table  1  for demographic details). Age-and education-matched healthy controls were selected from a healthy volunteer panel or were spouses/ carers of patients.
Behavioural analysis Data were analyzed using SPSS17. 0 (SPSS Inc. , Chicago, Ill. , USA). Parametric demographic (age, education), neuropsychological (Iowa Gambling Task, general cognitive tests), disease severity (FRS) and behavioural (CBI) data were compared across the three groups (bvFTD, AD and controls) via one-way ANOVAs followed by Tukey post-hoc tests. A chi-squared test was used to check for significant differences in gender across all groups. In addition, a mixed factorial ANOVA (with the trial as a repeated measures factor and the diagnosis as a between subjects factor) was carried out to analyse IGT block net score data. Another mixed factorial ANOVA with performance on the IGT as an additional between subjects factor was carried out in order to compare AD and bvFTD patients who did well on the IGT with those who did not do well.
Imaging acquisition and voxel-based morphometry (VBM) analysis All patient and controls underwent the same imaging protocol with whole-brain T1-weighted images using a 3T Philips MRI scanner with standard quadrature head coil (8 channels). The 3D T1-weighted sequences were acquired as follows: coronal orientation, matrix 256 × 256, 200 slices, 1 × 1 mm 2 in-plane resolution, slice thickness 1 mm, and TE/TR =2. 6/5. 8 ms. All scans were then visually checked for field inhomogeneity distortions and corrected for eddy current distortions. 3D T1-weighted sequences were analyzed with FSL-VBM, a voxel-based morphometry analysis  (Ashburner and Friston, 2000; Good et al. , 2001)  which is part of the FSL software package http:// www. fmrib. ox. ac. uk/fsl/fslvbm/index. html  (Smith et al. , 2004).