dataesr/scientific-paragraphs-categorization huggingface dataset:
Molecular stress calculation We use the so-called covariant central-force decomposition scheme (CCFD,  [30, 31] ) for the intra-and intermolecular forces, which ensures conservation of linear and angular momentum of the molecular systems under very general conditions. The method is implemented in a special-purpose patch to GROMACS 4. 6, which reads (all or part of) a MD trajectory for the selected subset of atoms for which stress is to be computed, and performs the entire analysis. Since the GROMACS-LS patch  [30, 31]  constrains the code to run in serial rather than in parallel, care must be taken to define properly the subset of interest in order to avoid prohibitive computing times. We prepared simple scripts to extract the principal components of the stress, compare stress fields from different simulations, and write the outputs in the portable Gaussian-cube format for visualization.
This work was funded by  SIRIC OncoLille  under project " ModCel " for 2015 and 2016 and a three-year doctoral grant to FL co-funded by the  President of Lille-I University and the Government of the Region Nord-Pas de Calais  (now Hauts-de-will open up, and thus become accessible to the action of nuclear proteins, or it will rather remain deeply hidden in the chromatin and difficult to repair. France). Computer resources were provided by the  CINES and IDRIS CNRS French Supercomputing Centers  under grants  a0020707225  and  x2016/ 077225. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
To find a quick answer to this question on the web is not that easy, even for a musical librarian. Indeed, musical works and performances are complex information objects, especially in classical or traditional repertoire, due to their multilingual titles, various versions or interpretations and complex structures (mouvements, acts, etc. ). The linked data technologies offer opportunities to improve the description of music on the web by making it easier to link and reuse different sources of data. Several research projects are currently testing their potential, each of them exploring a different part of the musical world. The Listening Experience Database (LED) project 1 focuses on collecting information about people's experience of listening to music. The data comes from sources like the British National Bibliography, MusicBrainz or DBpedia but also from crowdsourcing.
The project brings together experts from various professional backgrounds: libraries (Bibliothèque nationale de France (BnF), Radio France (RF) and Philharmonie de Paris (PP)), computer science laboratory (LIRMM), information and communication technologies laboratory (Eurecom), information science and communication laboratory (GERiiCO) and two private companies (Ourouk, Meaning engines). In this paper, we give an overview of the project with emphasis on the FRBR-oriented data model, the linking and aligning processes, and the prototypes created to consume data. In Section 1, we present the original datasets, the data model of the project -the DOREMUS extension of FRBRooand how the datasets are converted to the RDF format. In Section 2, we present how they are linked and how we will try to refine their structure and to link them with other datasets.
Original Datasets, Authorities and Controlled Vocabularies The data used in the project contains descriptions of different entities related to music: documents (books, music scores, recordings. ) as well as immaterial objects (musical works and performances). According to their origin, the datasets may differ in many ways such as granularity, format, or structure. By converting them into a single and consistent format while preserving their expressiveness is one of the principal issues of the DOREMUS project and a prerequisite for any interlinking attempt. Though the structure of the databases is very different, each one of them uses a system of authorities to link its records. These in-house or standard lists of persons, corporate bodies, or musical concepts will play a vital role in the interlinking process, facilitating the building of bridges between the datasets.
Building a Common FRBR-oriented Data Model In order to achieve its goals, the DOREMUS project needed a data model based on the familiar concepts of the FRBRer model allowing the description of musical works and their publications but also the description of concerts, festivals, and recordings that are part of the activities of Radio France and the Philharmonie de Paris. The most widely used ontology for music (Music Ontology 6 ) could not fulfill this precise requirement since our records cover basically the whole range of music, from popular songs to the most complex music, including the ones that the familiar FRBRer model is not good at describing. Hence, there is the necessity to build our own model. The DOREMUS model was developed as an extension of the FRBRoo model, itself an extension of CIDOC CRM 7 and it can not be used alone.
Converting the Data to RDF Each database differs in how to store information. In particular, there are different file formats used, representation models (meaning of the elements described), style choices (abbreviations, codes, identifiers). For this reason, the conversion of source documents to an RDF graph that follows the DOREMUS model requires different strategies to be applied. So far, three different strategies have been tested in the project. The first consists in the direct conversion of the MARC standard (in its UNIMARC and INTERMARC variants, used by the Philharmonie de Paris and the BnF respectively). Its implementation marc2rdf relies on a set of conversion rules between each field of the MARC file and the RDF triples to generate. For the base of concerts ("documentation sonore") of Radio France, the specificity of the representation required the development of an ad-hoc XML converter.
Finally, an automated query-based SPARQL system is used to retrieve the musical works in the database. Controlled vocabularies 12 play a key role at this stage. The conversion software includes a module that, for each text element, searches, if it exists, the best match among the concepts contained in the vocabularies, replacing literal nodes with appropriate URIs. In this way, the differences in the languages used or in the alternative forms of the labels are exceeded. As additional feature, this component is able to recognize and correct some noise that is present in the source files, like misspelled musical keys, or opus number where a catalog number is expected and vice-versa. An additional challenge is the re-creation of the structure of the content where the information is presented in the form of plain text.
Strategies based on the knowledge of librarian practices, comparison with controlled vocabularies, and text parsing, have been applied in order to extract, for example, the medium of performance from the casting notes, or the date and the publisher from the first publication note. The output of the conversion is a dataset of music linked data available at http://data. doremus. org. 11 https://protege. stanford. edu/. 12 The entire set of DOREMUS controlled vocabularies is available under the following link https://github. com/DOREMUS-ANR/knowledge-base/tree/master/vocabularies.
Linking Highly Heterogeneous Music Data Data linking, or instance matching, is defined as the task of the automated discovery of identical resources across different datasets leading to the establishment of declarative identity relations between resources. Mussorgsky's "Night on Bald Mountain" can be described in two datasets by using different identifiers and complementary information. The goal in that case would be to create a new triple that links the two Mussorgsky resources via the owl:sameAs predicate, hence bridging the two datasets. Recall that, as a result of the data transformation process, an RDF graph based on the DOREMUS model is constructed for each of our databases. Now we would like to establish links between them and, to start with, we focus on linking musical Expressions described in these graphs.
Many off-the-shelf data linking tools exist, 17 a recent survey can be of interest for the curious reader. 18 However, our experience showed that none of these generic tools provides satisfactory results in the world of music data. We will try to explain the major reasons for that in what follows. First and foremost, the data that we deal with is highly heterogeneous. By heterogeneity we mean cross-datasets differences in descriptions of resources assumed to be identical. In Fig. 4  we see subsets of three large datasets: the French National Library's data. bnf and the two well-known knowledge graphs DBpedia and YAGO. The example attempts to illustrate the various heterogeneity types that can be observed when dealing with musical data. We categorize these heterogeneities along three main dimensions.
The Legato Framework The processing pipeline of Legato consists in automatically pre-processing, comparing, repairing and providing a set of identity links (a link set), as shown in Fig. 5. The system takes as an input a source and a target dataset. The following steps are performed. (ii) Instance profiling allos to represent each resource by a sub-graph considered relevant for the comparison task; (iii) Instance indexing and matching. These steps aim at generating a large pool of mapping candidates, guaranteeing high recall (the portion of all correct mappings that has been detected). Indexing techniques are applied on the resources allows to represent them as textual documents containing the values of their properties collected at a given predefined depth of the RDF graph and considered relevant for the description of a resource (Fig.
Ongoing Work and Challenges Remember that in our context we are dealing with five large RDF graphs that need to be integrated. The solution that we opt for is creating a central pivotal graph containing the mathematical union of all music works referenced in the catalogues of the partner institutions -a sixth RDF graph equipped with owl:sameAs links to the local graphs generated by Legato. Further, parts of the DOREMUS graphs potentially overlap with well-established datasets on the web, such as DBpedia or Musicbrainz. We will, therefore, establish links to these knowledge graphs, thus anchoring DOREMUS onto the web of data. Currently, we are working on the extraction of named entities (such as names of composers, editors, cities and orchestras) out of the values of the comment-like properties.
Overture: an Exploratory Search Engine We developed the first version of Overture (Ontology-driVen Exploration and Recommendation of mUsical REcords), a prototype of an exploratory search engine for DOREMUS data. Overture 26  is developed as a modern web app, implemented with Node. JS and Angular. The application makes requests directly to our SPARQL endpoint and provides the information to the end-user with a nice interface. At the top of the user interface, the navigation bar allows the user to navigate between the main concepts of the DOREMUS model: expression, performance, score, recording, and artist. The challenge is in giving to the final user a complete vision on the data of each class and leaving him/her understand how they are connected to each other. about the work, like the musical key, the genres, the intended medium of performance, the opus number.
When these values come from a controlled vocabulary, a link is present in order to search for expressions that share the same value, for example, the same genre or the same musical key. A timeline shows the most important events in the story of the work (the composition, the premiere, the first publication). Other performances and publications can be represented below. The background is a portrait of the composer that comes from DBpedia. It is retrieved thanks to the presence in the DOREMUS database of owl:sameAs links. These links come in part from the International Standard Name Identifier (ISNI) service, in part thanks to an interlinking realised by matching the artist name, birth and death date of artist of DOREMUS with the ones in DBpedia. The page embeds also some structured markup, for helping the search engines to understand and index the content.
Towards Recommendation Systems Our starting point for the study of a suitable algorithm for recommendation consists in two humanmade collections: playlists from Radio France web radios and concert programs from the Philharmonie de Paris. While the latter can reveal very strong connection between works (they are played during the same concert, generally with the same casting), the former is characterized by a logical succession of tracks following an editorial action made by experts for an amateur public and aiming at discovering new works. These collections of works can be used as a ground truth for machine learning algorithm; the goal consists in understanding, starting from a defined work, which features (genre, casting, composer, etc. ) should have the next one to listen. Here again, the richness of DOREMUS data is a good advantage.
From one side, it provides a great number of features to feed the computation. From the other one, it allows to understand how the works in the recommendation path are connected each other, explaining explicitly the provided recommendation. An experiment that involves the recommendation by features and the explanation of the recommendation, has been realised in the CityMUS, 27 a web application that gives to the user the experience of a walk in the city with the most suitable soundtrack, on the base of the urban context. The application relies on a recommender system that searches for paths in a knowledge graph between nearby places and music composers, making use of a combination of DBpedia and domainspecific datasets.
Conclusion As a lot of countries are changing their cataloguing rules for RDA in order to facilitate the search on works and to open up the data of their libraries, we can see that the researches conducted by the DOREMUS team are closely tied to the current concerns of the library world. The first results of the project show that it's possible to make an elaborate knowledge graph from heterogeneous and relatively flat datasets. Using a FRBR and event oriented ontology brings really new and impressive possibilities in manipulating complex datasets such as musical ones. It makes possible to create new kinds of application more accurate for the user. DOREMUS is going to end by the spring 2018. In the meantime, the project ontology should be settled down, every original datasets converted and interlinked, several controlled vocabularies dedicated to music published (including a list of musical work authorities).
: http://data. doremus. org/ontology/. The ontology was also edited on Protégé 11 and a working version in the RDF-Turtle format is available on Github: https://github. com/DOREMUS-ANR/doremus-ontology. wikiwand. com/en/My_Favorite_Things_(song). 10 Further reading: Leresche, F. ; Choffé, P. : DOREMUS: Connecting Sources, Enriching Catalogues and User Experience. IFLA 2016 (Note: the modeling of the Performance is an early stage version, later replaced by the Performed Expression Creation). address.
Response options for all items were: completely agree  (5) , slightly agree (4), neither agree nor disagree, that is neutral  (3) , slightly disagree  (2)  and completely disagree (1). Furthermore, reaction of the respondents observed by the researcher and it was noted under four subheadings like-Alertness, Unpleased, Concerned and Discomfort. Using a four point scale, response was taken and the options were: more (4), moderate  (3) , little (  2 ) and negative answer to the statement (1). Thematic content analysis was performed and SPSS version 22. 0 software was used for data analysis. Results: Of the total respondents 96. 5% were positive about the introduction of plain packaging of tobacco products in Bangladesh. About 94% respondents' perceived that it would reduce the attractiveness and appeal of tobacco products.
Methods: A cross-sectional database of notified policies in FCTC ratified countries (n = 179) was prepared for SLT and CIG. Indicators studied were: Ban on Sale to minors; Treaty requirements (under the Ban on Sale to Minor); ban on sale by minor, prohibition on distribution of free tobacco products and prohibition on sale of loose/individual tobacco products. Countries were categorized according to World Bank Income groups and WHO regions. Data was analyzed using SPSSv17. 0. Results: Unequal implementation of provisions under Article 16 has been implemented for CIG and SLT products (nearly 79% Parties for CIG and 67% for SLT). Most countries have a partial (or none) policy in place (only 12% Parties have notified all provisions under Article 16(1) for CIG, and 10% for SLT). Implementation has been evaluated for CIG through indicators in GYTS, but not for SLT.
Conclusions and key recommendations: Although tobacco control laws were enacted long ago the process of implementation was found to be poor. Tob. Induc. Dis. 2018;16(Suppl 1):A5 DOI:10. 18332/tid/83965 12:30-14:00 PS-505-1 Are strong tobacco control policies associated with bans on the retail sales of electronic nicotine delivery systems? A Liber 1,2 , R Kennedy Methods: A dataset on the policy choices of 79 countries who have adopted formal policies regulating ENDS products was combined with data from the WHO 2015 Global Tobacco Control Report to create a weighted index of tobacco control policy development in a modified version of Joosen and Raw's Tobacco Control Scale (TCS)  (2006). Logistic regression analysis on the final cross-sectional dataset was performed to test the hypothesis that countries with greater levels of overall tobacco control policy development and on subscales corresponding to the MPOWER letters were more likely to ban than regulate retail sales of ENDS.
Conclusions: The '5A' model used in the study for tobacco cessation can have a significant effect in motivating tobacco users to quit tobacco in primary care and may act as a viable option to be included in the routine care practices in primary care settings of India. More large scale studies and studies on the costeffectiveness of the intervention should also be taken up in future. H Mongi 1,2 1 Tanzania Tobacco Control Forum, Dar es Salaam, Tanzania, United Rep. , 2 University of Dodoma, Department of Information Systems, Dodoma, Tanzania, United Rep. Ε-mail: hjmongi@ yahoo. com Background: Measuring the impact of tobacco control initiatives like in other major themes of research relies on the data. Recently, there has been growing interest in the usability of big data which is characterized by large volumes, high computer processing speeds and huge storage networked databases.
Intervention or response: The DATA Project establishes relationships with data producers and obtains permission to share their data on the project's site. The Project documents our experience in securing data and identifies best practices for increasing open access to data. The Project curates all secured data, shares these in researchready datasets, uses metadata to describe data available in external repositories and redirects users to these sites. It also collates time-series data from various publicly available sources into referenced data sheets. Our work saves researchers the time and effort involved in finding and collating data.
Conclusions and key recommendations: Methods: Data on the policy choices of 186 countries to ban retail sales of ENDS was combined with daily cigarette smoking prevalence and death figures from tobacco smoking by country, sex, and year. Countries in 2015, were classified as being in stages 1 to 4 of the Lopez epidemic model, according to whether tobacco smoking prevalence and attributable deaths were rising or falling over the prior decade. Logistic regression analysis on the final cross-sectional dataset was performed to test the hypothesis that countries in the earlier stages of the tobacco epidemic and countries with relatively smaller populations of female smokers were more likely to ban the sale of ENDS. Results: 18. 8% of countries in the total sample banned the retail sale of ENDS. Countries in stages 1, 2, and 3 of the epidemic had odds ratios of 1.
Stage Not Banned Banned Methods: Study was conducted in 8 districts, 7 types of public places like accommodation facilities, eateries, offices, educational institutes ,healthcare facilities , commonly visited places and public transport were observed with point of sale. The sample size was obtained by using The Union & CTFK Compliance Assessment Guide and Open Epi software. Districts were divided into clusters and random sampling was done from each cluster. A total of 57 blocks of 8 districts with sample size of 6544 public places and 1143 Point of Sale were covered doing cross sectional study by trained field investigators. Results: 4 districts Betul,Hoshangabad Sagar and Tikamgarh had more than 80 percent compliance of section 4,6a and 7 of Indian Tobacco control Act. 4 districts Harda,Panna,Damoh and Chhatarpur had more than 80 percent compliance on section 4,5,6a and 7 of Indian tobacco control act.
Methods: We reviewed internal documents dating from the 1980s to understand the industry's influence of NAFTA negotiations and implementation. We also analysed transnational tobacco companies' (TTCs) business strategies among NAFTA countries before and after the agreement using secondary sources, news articles, industry reports and policy documents. We compiled trade data using the UN Comtrade Database and Trade Map Databases. Data was organized by date and company, and iteratively reviewed to build a narrative related to the tobacco industry and NAFTA. Results: TTCs actively lobbied policymakers to include tobacco under NAFTA and specific provisions related to taxation, rules of origin and tariff rate quotas. The industry publicly argued that NAFTA would yield economic benefits to the US and Canada by increasing exports and employment.
Results and lessons learnt: 60 trained female community health workers implemented various tobacco control activities at village level using methods like songs, street plays, puppet shows, antitobacco rallies, and incorporated anti-tobacco messages into their other health activities. Through these activities they reached to 28,000 residents in 60 villages. An evaluation conducted one year after the program revealed that awareness on harmful effects of tobacco use increased up to 90% among the residents of intervention villages and tobacco consumption had reduced. Conclusions and key recommendations: Community health workers are uniquely situated to implement tobacco control programmes due to their access to community members, their role as trusted sources for health information, and their ability to understand the unique issues faced in their communities.
Methods: The Truth Tobacco Industry Documents Archive (http://legacy. library. ucsf. edu), a database compiled by the University of California in San Francisco in 2002, served as the primary source of information for the study. Key Informant Interviews were purposively sampled from relevant government ministries and agencies, civil society and other actors. The findings from the library and the KII, were then triangulated with statements from industry and government officials and other related articles in newspaper stories and publications.