dataesr/scientific-paragraphs-categorization huggingface dataset:
ChCFP and ChYFP represent the signal in the 510-and 530-nm detection channels (Ch); CFP 510 , CFP 530 , YFP 530 , and YFP 510 represent the normalized contributions of CFP and YFP to channels 510-530, as determined from spectral signatures of fluorescent proteins. Results were analyzed by using a 1-way ANOVA followed by Kruskall-Wallis test and a posttest of Dunn's multiple comparison. We used GraphPad Prism 5. 0 (GraphPad Software, La Jolla, CA, USA).
DISCUSSION We report here an unexpected and strong synergistic cooperation between CXCL14 and CXCL12 in controlling ] i concentrations in CXCR4-transfected cells in response to indicated chemokines. All experiments were performed at least twice. B) Polarization of primary T cells was visualized by staining of F-actin and Rac1-GTP followed by confocal microscopy. C ) Rac1 activation was measured in flow cytometry by determining mean fluorescent intensity of Rac1-GTP staining in primary T cells by using an Ab that recognizes active GTP-bound Rac1. For each analysis, 10,000 cells were measured. Data are means + SEM of 5 experiments derived from individual donors. D) CXCR4transfected cells were treated with chemokines as shown and then processed for Western blot analysis. ERK1/2 phosphorylation was determined with a phospho-ERK1/2-specific Ab.
ACKNOWLEDGMENTS This work was supported by the  Medical Research Council  ( MR/L018284/1  to B. M. ), the  Spanish Ministry of Economy and Competitiveness  ( SAF-2014-53416-R ), and the  Networks for Cooperative Research in Health Program  (RETICS;  RD 12/0009/009 RIER  to M. M. , L. M. -M. , and C. S. ). L. M. -M. is supported by the  ComFuturo Program  from the  Spanish Research Council General Foundation , the  Swiss National Science Foundation  ( SNF 31003A_169936  to D. F. L. , and  SNF3100A0-143718/1  to M. U. ), the  Agence Nationale de la Recherche  ( ANR-NT05-4-41968-Chemoglycan  to H. L. -J. ), with additional support from the  Grenoble Instruct Centre  ( UMS 3518 CNRS-CEA-UJF-EMBL ), the  French Infrastructure for Integrated Structural Biology (FRISBI ;  ANR-10-INSB-05-02 ), and  Grenoble Alliance for Structural Biology Funding  ( GRAL ;  ANR-10-LABX-49-01 ).
An analysis of law compliance of the document is carried out thanks to the identification of regulatory detection elements. These are applied to a database of 30 DICRIMs. This analysis leads to a discussion on points such as usefulness of the missing elements. External and internal function analysis permits the identification of the form and content requirements and service and technical functions of the document and its components (here its sections). Their results are used to carry out an FMEA (failure modes and effects analysis), which allows us to define the failure and to identify detection elements. This permits the evaluation of the effectiveness of form and content of each components of the document. The outputs are validated by experts from the different fields investigated. Those results are obtained to build, in future works, a decision support model for the municipality (or specialised consulting firms) in charge of drawing up documents.
Are those preventive tools made to be effective in terms of appropriation by the general public? It is important to evaluate if those preventive communication tools reach their goal while conforming to the law. To rise to this challenge, this article has the objective of proposing an approach capable of analysing preventive communication document, in terms of its effectiveness. The Municipal Information Document on Major Risks (DICRIM) is used as an application of the method proposed. The article is structured according to the following plan: it first examines selected methods for analysing the effectiveness of communication tools, and it then presents the methodology proposed after which the results of its application to the DICRIM are shown. A part of these results is applied to a DICRIM database.
The mayor must also inform the population about major hazards at least every 2 years by way of public meetings. In addition, the safety instructions contained in the DICRIM and those which may be laid down by the operators or owners of the premises and land referred to in Article R. 125-14 of the Environmental Code are made public by means of posters. These posters are made based on a template set by the state. The mayor is also required to establish floodmarks in the municipality and carry out an inventory. They correspond to historical or exceptional new floods. They make it possible to refine the expertise of historical floods, but also to bring to life the memory of flood risk. With regard to residents, there are two distinct obligations regarding preventive information established by the Environmental Code for purchasers and tenants: (i) information on the natural hazards affecting the property and (ii) information on claims resulting from recognised natural disasters which affected all or part of the property concerned.
A database of docu-ments is made and used to apply those regulatory detection elements. In parallel, functions of components are analysed. Functions are systematically characterised, classified and evaluated  (AFNOR, 2014). For the functional analysis we chose to use the APTE method that can be applied successfully to our case study as a quick test, as proposed in  Ghariani et al. (2014). It is one of the most used dependability methods, and it generally provides the basis for a subsequent FMEA which is the next part of the approach. FMEA is an inductive method of analysing potential failures in a system. It systematically considers each system component and its failure modes one after another. Failures are identified by noncompliance with requirements. Detection elements are also listed, allowing the identification of this non-compliance.
System functions: external functional analysis The external functional analysis (EFA) consists of three main steps: system definition, expression of needs and determination of relationships with external environments. 4. 1 System definition and needs satisfied by the system: the DICRIM First, it is necessary to define the system to be studied precisely. Limits are defined, which then lead to considering the interactions with external environments. The system therefore takes into account the document (DICRIM) with its content, form and accessibility as described by the relevant law. The main headings and information to be included in the DICRIM are listed in the National Model for the application of the Environment Code (Articles L 125-2 and R 125-9 to R 125-27) issued by the MTES (Ministry of Ecological and Inclusive Transition; MEDDE, 2013).
Compliance analysis and application to a DICRIM database To analyse its effectiveness, first we must analyse the DI-CRIMs compliance with the law by identifying detection elements. This compliance analysis is based on the National Model. Indeed, it was mentioned earlier that government provides some general instructions regarding the content of DI-CRIM in the form of a National Model. We can think that this model has been strongly discussed in order to make the DICRIM as effective as possible. The regulation detection elements we listed allow the evaluation of the presence or absence of the required content for each component. Components 5 to 10, associated with a given risk, are characterised by 19 detection elements, i. e. 19 elements required by law. With 10 risks being considered here, this gives a total of 190 elements.
The completeness of the DICRIM can be verified thanks to them. In our future works they will be formalised as indicators and their number will be greatly reduced, but they can already be used as they are. To apply those regulatory detection elements, we built a database of 30 DICRIMs. Those DICRIMs were all produced by towns located in the PACA region in France. The DI-CRIMs were retrieved from municipal websites. A variety of DICRIMs were collected, considering the number and types of hazards affecting the town, the size of the town in terms of number of inhabitants or surface area, the environment of the town (mountain, sea, countryside) and criteria regarding the document itself were also considered. The DICRIMs were more or less long (from 5 to 56 pages -not linked with the number of risks identified).
In fact, the existing elements seldom reach half of the total requirements for each DICRIM. For instance, town 1 contains 58 of 128 required elements or town 5 only 40 of 125 required elements; ergo in both cases their number is less than half of the elements needed. In conclusion, Table  9  shows that none of the DICRIMs exposed in the database fulfils the elements' requirements. Elements relative to hazard safety instructions were those which were most present in the DICRIM database. This observation is interesting because safety instructions are major part of one of the two service functions of a DICRIM. The second most common element concerned "the presentation of the DICRIM's role", an important means of capturing readers' attention. This analysis also showed that 19 elements required by the National Model were not present in any DICRIM in the database, 22 are only present in one DICRIM and 18 are present in two DICRIMs.
Indeed, in our opinion they are also important elements for both service functions of the DICRIM. While these observations show interesting results, we must nevertheless remain cautious about such conclusions with regard to the number of DICRIMs contained in the database. This number is sufficient to test the feasibility of the method, but it will be necessary in future work to increase this number for further results. The analysis of the presence of elements allows for evaluating to what extent the DICRIM does or does not comply with the regulations. However, this does not necessarily provide any conclusion on the effectiveness of these DICRIMs. The use of other non-regulatory, formal and substantive detection elements is necessary to achieve such a measure. Determination of formal and substantive detection elements needs to identify functions and dysfunctions of components contained in a DICRIM.
It lies at the interface between several existing approaches, from different fields  (engineering, advertising, etc. ). This method was applied to the DICRIM, one of the main French documents used to inform the general public about risk at a communal level. Results included the identification of regulatory detection elements. These detection elements were then used to analyse existing documents and show their degree of conformity with the regulations. A challenge in the future will be to analyse whether component redundancy is strictly necessary (Table  5 ). Indeed, we observed that some components fulfilled the same function, raising doubts as to their usefulness. Likewise, the application of the database showed that several elements demanded by the regulations were systematically missing from the DICRIMs studied.
In the next step (not presented here), the causes and effects identified with the FMEA method will be used to define models for the quantitative assessment of DICRIM efficiency. Detection elements will become formalised indicators, which will be used as input data in these models. This is an essential step towards the overall goal. Its results are crucial for ensuring the basis of models and for structuring them. The Supplement related to this article is available online at https://doi. org/10. 5194/nhess-18-1201-2018supplement.
Application of regulatory detection elements in an DICRIM database (extract of eight towns and some detection elements)radio with extra batteries, torch, drinking water, food supply, containment equipment, first aid kit, personal papers, emergency medicine, blankets, Earth Syst. Sci. , 18, 1201-1221, 2018 www. nat-hazards-earth-syst-sci. net/18/1201/2018/ L. Ferrer et al. : Analysis of a risk prevention document using dependability techniques 1211 Component 1: cover page (Cp1), -Component 2: editorial from the mayor (Cp2), -Component 3: summary (Cp3), -Component 4: DICRIM presentation (Cp4), -Component 5: presentation of the risk in the town (Cp5), -Component 6: prevention actions at town level (Cp6), -Component 7: police and protection actions (Cp7), -Component 8: general safety instructions (Cp8), -Component 9: specific safety instructions (Cp9), -Component 10: 1 : /25 000 scale mapping (Cp10), -Component 11: communal poster (Cp11), -Component 12: floodmarks and highest known flood zone (Cp12), -Component 13: underground caves and marl pits (Cp13), -Component 14: where to get more information (Cp14), -Component 15: emergency phone numbers (Cp15),.
2) Project description IHU is a worldwide reference for image-guided minimally invasive surgery. As such, it interacts with many specialists including leader experts. Through these interactions and the research programs it conducts, IHU produces and aggregates amounts of advanced information about the field of minimally invasive surgery. This information concerns the whole technology development process, from invention to distribution. This knowledge is a real value for IHU, which wants to leverage it, especially through the creation of a dedicated digital service, designed as a platform composed of three modules. The first module is described as a knowledge base. It allows users to add structured data and link them together in a database. All data inserted within the knowledge base should be categorised using a specific thesaurus.
A search engine is used to search through the database. Users can navigate through data using faceted search, based on the categories described in the thesaurus. The second module is an automated market watch module. Its aim is to harvest information about image-guided minimally invasive surgery in different sources across the Internet. Information coming from this harvesting engine must then be sorted and qualified by IHU experts. The third module concerns social network features. This module aims to ease interactions with experts, companies and medtech stakeholders, in the specific field of minimally invasive surgery. This module lets users comment and share content from the knowledge base or the market watch, and includes several tools to exchange news and information.
Target First, an analysis has been led to identify profiles of the actors of the platform. The following profiles have been selected: -Fellow surgeon (research and innovation) -Senior surgeon -Radio manipulator -Research engineer -Development engineer -Veterinary -External start-up -Simulation researcher -Health economist A campaign of interviews has been conducted with all selected profiles to precise their needs related to the platform. Interviews revealed a lack of databases to pool data and documents. Information is kept by each user on her/his own computer. No tool exists within IHU to share documents and data and centralise them. The second redundant item was the difficulty to identify the right information holder. Employees do not know how to identify a potential contact about a specific field of investigation.
This item does not talk about expertise, but about information available within the IHU and the right person to ask for this information or for additional details concerning this information. For example, if an employee attends a conference and gets some information about a particular technology, this person could not be identified as the one to ask for information about this technology. The third item that has to be taken into account is the lack of information about other teams within IHU, coupled to a lack of visibility of people's own work and needs. IHU employees wish they could share news and articles, or just be informed about current projects running in IHU. An additional study has been conducted to get the most common information that may be searched by users. This study identified several types of content: -Publications, mainly coming from the PubMed 1 repository -Market and medico-economic information (companies, market studies) -Technical medical data (procedures, pathologies) -Intellectual Property data (patents) -Devices information (instruments).
Proof of concept The types of content identified by the analysis have then been implemented in a proof-ofconcept (PoC) platform. The project team identified the metadata than needed to be stored for each entity, leading to the scheme in figure  1. These five main entities compose the first version of the database. Company, Patent and Instrument describe the medico-economic, IP and devices parts of the knowledge base. An instrument can be linked to a procedure which is used for some pathologies, describing the technical medical part. Publications are stored as links (URLs) to resources available on the Internet. All entities can be categorised using specific vocabularies (regulatory status, size, etc) and by using MeSH. MeSH 1  stands for Medical Subject Headings. It is a vocabulary thesaurus used for indexing articles for PubMed, a repository for biomedical and life sciences publications.
The PoC lets the project team validate the choice of Liferay Portal, and check whether out-of-the-box functionalities fulfil the needs or if adaptations or new functionalities should be specifically developed. The PoC uses Liferay's content management for the knowledge base, with specific settings to store the five main entities. Liferay's content management stores content as assets, which can be related to each other. Liferay also includes categories management that can be used to describe assets. These categories can then be used as facets in the internal search engine, with several other metadata, like author, dates, type of content, etc. The market watch and collaboration modules were not included in the PoC. The market watch module had to be fully developed as it does not exist as a plugin or as an out-of-the-box functionality.
II) Knowledge-base: working with CERIF 1) CERIF-structured database With the need for specific development for the knowledge base, the project team had to find a structure to store data in the database. CERIF is a data model that allows to store research information. Information is described as entities that contains specific metadata, for basic concepts (organisation units, project, etc. ), research results (publications, patents and products), infrastructures (equipment, facilities, etc. ) and several secondary entities. A full part of the model also allows to describe measurements. Most of the entities needed for the knowledge base are already available in CERIF. The figure  2  describes the CERIF entities used for each kind of information needed. The only entity that cannot be linked to any CERIF entity is the pathology.
2) Extending CERIF Pathology is a type of content that cannot be represented in CERIF. To complete the CERIF model to fulfil the knowledge base needs, an extension has been designed to integrate a new entity. This part of the model has been built using the standard CERIF model for entities and link-entities. The basic modelling of pathologies is displayed in figure  3. The part of the model uses several principles designed in CERIF. The full text metadata for title and description uses the translation system to allow multiple languages to be used. Links with other entities include the semantic layer to describe their roles. They also implement the starting and ending dates to reflect evolution of this relation. The fraction completes the description of links to integrate the fact that a particular occurrence of a relation may only be a part of the real relation between two entities.
3) CERIF denormalisation In the development process, some changes have been done to the normalised CERIF model. These changes mainly serve two goals. First, this denormalisation improves integration within the Liferay Platform. Liferay comes with an API that eases development, giving developers a lot of tools to automatically generate fullycompatible code. This allows developers to create new types of assets that can take advantage of outof-the-box features, thus saving them a huge amount of time. In this context, Liferay's categorisation has been used to complete the description of entities; CERIF semantic layer is only used to define roles for the relations. Liferay's tagging has also been used instead of CERIF keyword's metadata. Liferay also includes a translation mechanism that has been used for all metadata that use CERIF multilingual system.
The second goal of the denormalisation is to ease the use of CERIF. In this context, the measurement part of the model has been simplified to use the semantic layer (cfClassification and cfClassificationScheme) to store indicators, instead of the dedicated entity cfIndicator. The reason of this choice is that cfIndicator does not provide more (nor different) metadata than cfClassification for the use of the knowledge base. CfIndicator mainly provides a way to identify what the value -stored in cfMeasurement -represents. This could be done using the cfClassificationId foreign key in cfMeasurement as well, as the knowledge base does not need to use this particular metadata for any other use. CERIF denormalised diagrams are available in appendix 2.
4) Overlaying CERIF CERIF is a meta-model that can be used for a wide variety of uses. Thus leading to a complex model that may lead to a complex interface to use it as-is. To ease the look and feel of the software and to improve the user experience, multiple layers of service have been implemented. CERIF is used as the model to structure data in the database. A service layer has been implemented to access this data and manipulate CERIF entities. On top of this service, another service layer has been implemented that allows to manipulate knowledge base entities (company, instrument, patent, procedure and pathology, cf. figure  3 ). This second layer implements the logic that transforms knowledge base entities to CERIF entities, regarding the mapping (cf. appendix 1). This second service layer is then used by the interface layer to display information to the user.
CERIF entities used for company The main entity to represent companies in CERIF is cfOrgUnit. A few additional metadata have been added to the model: -cfOrgUnit. description: this metadata allows users to describe a company -cfOrgUnit. yearOfCreation: this metadata is used to store the creation date of the company; this metadata is a misuse of the CERIF model: it should have been stored as a measurement for the corresponding cfOrgUnit -cfOrgUnit_OrgUnit. amount: this metadata is used to store the acquisition amount of an organisation unit; this metadata is also a misuse of the CERIF model: it should have been stored as a measurement for the corresponding cfOrgUnits (acquired and acquiring companies).
Experimental data on monkeys and functional studies in humans support the existence of a complex frontoparietal system activating for cognitive and motor tasks, which may be anatomically supported by the superior longitudinal fasciculus (SLF). Advanced tractography methods have recently allowed the separation of the three branches of the SLF but are not suitable for their functional investigation. In order to gather comprehensive information about the functional organisation of these fronto-parietal connections, we used an innovative method, which combined tractography of the SLF in the largest dataset so far (129 participants) with 14 metaanalyses of functional magnetic resonance imaging (fMRI) studies. We found that frontal and parietal functions can be clustered into a dorsal spatial/motor network associated with the SLF I, and a ventral non-spatial/motor network associated with the SLF III.