dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements The authors acknowledge the support of the  Queensland Government  through the  Q-CAS Collaborative Science Fund 2016. Some  of the data reported in this paper were obtained at the  Central Analytical Research Facility (CARF)  operated by the  Institute for Future Environments (QUT). Access to CARF is supported by generous funding from the  Science and Engineering Faculty (QUT). This work was supported by the  Ateneo funds of Sapienza Universitá di Roma , the  FATA  project of  Regione Lazio , and partly by  JSPS KAKENHI  Grant Number  JP15H05473  and the  CASIO Science Promotion Foundation. IDB  acknowledges the financial support of the  Australian Government  through the  Endeavour program.
Regional Settings The Independence fjord system lies between Peary Land and Kronprins Christian Land in eastern North Greenland (between ~80°41 0 and 82°27 0 N; 16°36 0 and 32°40 0 W) (Figure  1b ). The fjord system is approximately 150 km long and drains into the Wandel Sea. Two large glaciers, Academy and Hagen, discharge into the head of the Independence and Hagen fjord branches, respectively. The region also supports the largest peripheral ice cap of Greenland, the Flade Isblink ice cap, which covers an area of ~7,500 km 2  (Kelly & Lowell, 2009)  and drains through two outlets (see Figure  1c ) at velocities of a few hundred ma À1  (Higgins, 1991). Limited information is available for the region, but data from the Danish Meteorological Institute indicate that the fjord system was covered by permanent ice from 1950 to 1964  (Rysgaard et al.
The first oceanographic data from the study area are presented in  Bendtsen et al. (2017) ,  Dmitrenko et al. (2017), and Kirillov et al. (2017). Conductivity-temperature-depth (CTD) profiles obtained during spring 2015 revealed the origin of the water masses and the interactions with ambient water in the regions deeper than 10 m of our study area. On the Wandel Sea shelf (Figure  1b ), the water column can generally be divided into six layers of distinct water masses: a low-salinity surface layer (~1. 5-5 m depth) formed by the summer melt of the glaciers and sea ice, a subsurface halocline with a strong vertical salinity gradient down to a depth of 15 m, a Halostad layer of Pacific origin with near freezing temperatures (15-65 m), an Atlantic-modified halocline (65-100 m), Atlantic-modified Polar Water (100-140 m), and relatively warmer and more saline Atlantic bottom waters (>140 m)  (Dmitrenko et al.
, 2017). Accordingly, the deepest sites located North of Princess Dagmar Island (Sites k9-k6; Figure  1c ) are the most affected by halocline disturbance caused by Atlantic water intrusions, whereas the hydrological conditions south of Princess Dagmar Island (Sites k22, k21, and k15) seem to be mainly governed by the fjord's ambient waters, and no intrusion of outer-shelf waters was observed in this region. The local influence of cold and turbid subglacial meltwaters originating from the Flade Isblink ice cap was also observed directly at the outlet of the glacier. It has been suggested that subglacial meltwater discharges from marine-terminating glaciers could help promote primary productivity through increased nutrient supplies (e. g. ,  Meire et al. , 2017). According to the data from  Dmitrenko et al.
Hydrocarbon fractions were analyzed using an Agilent 7890 gas chromatograph (GC) fitted with 30 m fused silica Agilent J&C GC columns (0. 25 mm i. d. and 0. 25 μm phase thickness) and coupled to an Agilent 5975C Series mass selective detector. Oven temperatures were programmed as follows: 40-300°C at 10°C/min, followed by an isothermal interval at 300°C for 10 min. The data were collected using ChemStation and analyzed using MassHunter quantification software. IP 25 was identified on the basis of retention time and comparison of mass spectra with authenticated standards. Abundances were obtained by comparison of individual GC-mass spectrometry responses against those of the internal standard. For both IP 25 and HBI III, data are reported in ng g À1 sediment. Journal of Geophysical Research: Biogeosciences 10.
With the exception of Site k22, samples from the inner part of the study area yielded very low cyst counts and species' relative abundances were therefore not used for further interpretations. Classical cluster analysis using a paired-group clustering algorithm and a Euclidean similarity index was carried on the assemblage data for samples with total cyst counts higher than 60. The resulting dendrogram clearly highlights the important compositional shift in the assemblages for the region north of Princess Dagmar Island (Figure  5a ). Sites located at shallow depths (k11 and k33), close to the Villum Research Station, are the most dissimilar of all sites. These sites are characterized by a striking dominance of the phototrophic species P. glacialis. It is also at these sites that the highest total cyst concentrations were recorded.
Considering the sea ice thickness of the order of 1. 15-1. 25 m for Sites k9 and k6 compared to 3. 10 m for Site k32 measured during the field campaign (late April 2015), our data can be interpreted in different ways: (1) The semipermanent sea ice cover restrains in situ primary production, but tests of planktic foraminifera and dinocysts are advected from the productive offshore open waters via subsurface currents. This would explain why the grazers are found in the sediment, while the primary producers are extremely scarce. Following this line of reasoning, however, one might expect more planktic diatom valves since their size and weight make them more prone to lateral transport than the heavy tests of foraminifera  (de Vernal et al. , 2006). (  2 ) The semipermanent sea ice cover restrains in situ primary production, but food supply is advected from the productive offshore open waters via nutrient-rich subsurface currents.
Exploration of administrative records Besides the administration of questionnaires to staff, existing administrative records in the two sampled facilities were reviewed. This approach was meant to independently ascertain the number of documented cases of exposure to occupational health hazards. Also, at the time of conducting this study there were not many available scientific publications on the topic area, particularly in the context of psychiatric hospitals. In view of this, there was the need to complement the questionnaires administration to review of existing hospital archival records on incidence of exposure to occupational health hazards in the two hospitals. Incidence registers were reviewed in eight (8) out of the twenty one  (21)  wards in Accra psychiatric hospital and eight (8) out of the ten  (10)  wards in Pantang psychiatric hospital throughout the period of the data collection.
Data analysis The data collected from the surveys was analyzed with the Statistical Package for Social Sciences (SPSS) version 22. 0. Relevant frequency distribution tables were generated for the type of occupational health hazards experienced by the frontline health workers. Multivariate Ordinary Least Squares (OLS) regression analysis was performed to determine the associations between individual characteristics and work schedules of health staff and their frequency of exposure to occupational health hazards on daily basis. Prior to the regression analysis, multicollinearity diagnosis was conducted for all the independent variables of interest and none had a Variance Inflation Factor (VIF) up to 10. 0, required for inclusion in the regression model. The first dependent variable was "Exposure to occupational health hazards", dichotomized into 0 = "No" and 1 = "Yes" while the second dependent variable was "Frequency of exposure" which is a continuous variable in terms of number of times of exposure to occupational health hazards on daily basis.
Demographic data and work history of respondents Two hundred and ten (210) questionnaires were administered in the APH and 164 of them were retrieved with complete data, representing a return rate of 78%. However, the return rate at the PPH was 96% out of 140 administered questionnaires. The total valid responses from the two hospitals was thus, 296. The field data showed that females dominated in both hospitals, representing 65%. Professional nurses also dominated, representing 60% while nurse-assistants constituted 39% (see Table  1 ). On the work schedules of respondents, it was found that staff who alternated between day and night work shifts dominated 145 (49%); 142 (48%) worked mainly on day shift; three staff (1%) indicated they run permanent night shift. Thus, it was observed that majority of the staff (97%) either alternated day and night shifts or worked solely on day shift.
International initiatives have been launched and supported by the Food and Agriculture Organization (FAO), the World Health Organization (WHO), and the World Organization for Animal Health (OIE)  [24]. Additionally, some methodologies for the aggregation of existing databases at the human-animal interface have been tested (for example, the Joint FAO-OIE-WHO Global Early Warning System for health threats and emerging risks at the human-animal-ecosystems interface (GLEWS) database)  [25]. Although there are increasing demands on disease surveillance, preparedness, response, and control in the OH context, no standardized methodology exists for controlled comparative cost-efficacy studies and quantitative evaluation of OH activities. New interesting initiatives are ongoing  [26] , but criteria and methods to describe and assess existing levels of integration of surveillance for specific pathogens (including a wide range of individual and environmental exposures) to facilitate the evaluation of the impact and the added value of OH, are still to be defined and tested  [27].
This framework allows for an assessment of the levels of integration through specific criteria, which are presumed to be connected with the operationalization of the OH approach at the country level. For example, the integration at policy and institutional level is expected to facilitate harmonization of activities and programs, leading to a more efficient use of resources; integration at data collection and analysis level is expected to facilitate inter-sectoral coordination and planning and indicates the translation of policy into plans for specific actions  [39]. Articles and documents were included regardless of the country/s involved in their related studies.
Analysis We analyzed all included articles/documents extrapolating the following information in a spreadsheet data collection grid: Exposure, Title, Authors, Journal, Year, Country (or Countries), Intervention: Surveillance (Y/N), Integrated Surveillance (Y/N), Integrated Sector(s) (human and/or animal and/or entomological and/or environmental), Level of Integration (policy and institutional level/data collection and analysis level/dissemination level), and Added Value of Integration (early warning/impact assessment/response).
The Selection Process The extraction was conducted on the four search strings on PubMED on 29 December 2014 and led to the identification of 347 scientific articles (Table  S3 ; PubMed DataBase). Of those, four were duplicates and were excluded. 343 articles' titles and abstracts were assessed. For 72 of the 343 articles, the abstracts were not available, so we assessed their eligibility directly on the full texts. Based on the identified inclusion criteria, we excluded 166 articles on the basis of titles and abstracts and selected 177 (including the 72 without abstracts) for the full text assessment (Figure  1 ). All 177 selected full texts were available. articles, the abstracts were not available, so we assessed their eligibility directly on the full texts. Based on the identified inclusion criteria, we excluded 166 articles on the basis of titles and abstracts and selected 177 (including the 72 without abstracts) for the full text assessment (Figure  1 ).
The articles and documents of this review refer to integrated data collection and analysis but often do not describe the systems in detail. In most cases, each sector seems to collect and analyze its own data, generating results that are then shared with the other sectors. This might be the reason why only 56% of the articles (14/25) reporting integration at the data collection and analysis level mention criteria of integration (e. g. , the existence of a common database or data system) as proposed by our framework. This finding is in line with the results of the survey on integrated surveillance we conducted with 19 countries of the Mediterranean and Black Sea Regions  [40]. This study showed how integration mechanisms were more frequently directed to the joint dissemination of results than to the development of mechanisms/procedures for integrated data collection.
This might indicate that each sector collects surveillance data separately and that results are collated in a second step for coordinated dissemination. Although more than 80% of the articles recognized an early warning as the main added value of integrated surveillance, integration between sectors was mainly described in the context of response activities (e. g. , setting up control measures). It therefore seems that prevention and mitigation of impact through early warning with an integrated inter-sectoral approach still needs attention and consolidation. This study has of course some limits, as the use of a unique electronic database. Additionally, it should be considered that we identified criteria for integration (Tables  S1  and S2 ) by "reading" the papers and not by doing an assessment.
Acknowledgments: We acknowledge the active participation of the members of MediLabSecure Network [34], who, in discussions on integrated surveillance of arboviruses, pointed out the need of this study. The MediLabSecure Project is supported by the  European Commission  ( DEVCO: IFS/21010/23/_194 ). We are grateful to  Caterina Rizzo  and  Christian Napoli , who suggested aspects to consider in studying the integration of vector-borne disease surveillance.
Existence of activation mechanisms of human surveillance based on signals from animal/entomological surveillance 8. Other interoperability mechanisms at data collection level Interoperability mechanisms at data analysis 9. Presence of database exchange/merging/other mechanisms to facilitate joint analysis among sectors. 10. Performance of joint/integrated data analysis among the different surveillance sectors 11. Other interoperability mechanisms at data analysis level Dissemination -12. Existence of joint results dissemination mechanisms (e. g. , bulletins, reports, papers, media reports, websites, etc. ) 2. 1. Inclusion Criteria for Articles and Gray Literature We included studies that • were published in scientific peer-reviewed journals and gray literature for the period 2000-2014; • were in English, French, or Italian; • focused on descriptive/analytical epidemiology and surveillance evaluation; • analyzed the functioning of public health surveillance systems for West Nile virus (WNV), chikungunya virus (CHKV), dengue virus (DENV), and Rift Valley fever virus (RVFV); • reported integration between sectors.
Acknowledgments. We would like to thank  Balthazar Bauer  and  Florian Bourse  for insightful discussions. Rosario Gennaro  was supported by  NSF  Award no. 1565403. Michele Minelli  was supported by  European Union 's  Horizon 2020 research and innovation programme  under grant agreement no. H2020-MSCA-ITN-2014-643161 ECRYPT-NET. Anca Nitulescu  was supported by the  European Research Council  under the European Community's  Seventh Framework Programme  (FP7/2007-2013 Grant Agreement no. 339563   -CryptoCloud). Michele Orrù  was supported by  ERC  grant  639554  (project aSCEND).
Numerical Integration A system with N = 20 oscillators has been chosen for the numerical investigation which yields 2N first order Ordinary Differential Equations (ODEs). The system of ODEs has been integrated using MATLAB R , in particular the function ode23t. This ODE solver use the trapezoidal rule with a "free" interpolant, has no numerical damping and is recommended for moderately stiff problems. The implementation of the friction force required particular attention due to non-smoothness. Two approaches have been tested: smoothing of the signum function and the implementation of the switch model (  [43] ). The best results in term of calculation speed and stability have been obtained using the switch model, where it was assumed that the oscillator sticks to the belt if | v rel | < 10 -4 (see  [43]  for more details).
Acknowledgements We would like to thank members of the  Cossart lab  for helpful discussions. We apologize upon those people who have contributed to advancements in the field of listeriosis but whose work was not cited in our chapter due to size limitations. J. P. C. received support from the  Institut Pasteur 'Transversal Research Program '  PTR521  and from the  National Research Agency (ANR)  grant  ANR-15-CE15-0017  'StopBugEntry'. Work in P. C. laboratory received financial support from  Institut Pasteur ,  INSERM ,  INRA ,  ANR-13-IFEC-0004-02  ' ERANET Infect-ERA PROANTILIS ', the  French Government's 'Investissement d'Avenir' program ,  Laboratoire d'Excellence 'Integrative Biology of Emerging Infectious Diseases'  ( ANR-10-LABX-62-IBEID ), the  European Research Council (ERC)  (Advanced Grant  H2020-ERC-2014-ADG 670823-BacCellEpi ),  Human Frontier Science Program Organization  ( RGP011/2013 ), the  Fondation le Roch les Mousquetaires  and the  Fondation Balzan.
Acknowledgement This research was supported by the  French P2IO Excellence Laboratory , the  French CNRS  via the grants  FCPP-Quarkonium4AFTER & Défi Inphyniti-Théorie LHC France , the  P2I department of the Paris-Saclay University  and by the  COPIN-IN2P3  Agreement. AS acknowledges support from  U. S. Department of Energy  contract  DE-AC05-06OR23177 , under which  Jefferson Science Associates, LLC , manages and operates  Jefferson Lab.
Although schema. org encompasses terms related to data repositories, datasets, citations, events, etc. , it lacks specialized terms for modeling research entities. The Bioschemas community  (Garcia et al. 2017)  aims to extend schema. org to support markup for Life Sciences websites. A major pillar lies in reusing types from schema. org as well as welladopted domain ontologies, while only proposing a limited set of new types. The goal is to enable semantic cross-linking between knowledge graphs extracted from marked-up websites. An overview of the main types is presented in Fig. 1. Bioschemas also provides profiles that specify how to describe an entity of some type. For instance, the protein profile requires a unique identifier, recommends to list transcribed genes and associated diseases, and points to recommended terms from the Protein Ontology and Semantic Science Integrated Ontology.
The success of schema. org lies in its simplicity and the support by major search engines. By extending schema. org, Bioschemas enables life sciences research communities to benefit from a lightweight semantic layer on websites and thus facilitates discoverability and interoperability across them. From an initial pilot including just a few bio-types such as proteins and samples, the Bioschemas community has grown and is now opening up towards other disciplines. The biodiversity domain is a promising candidate for such further extensions. We can think of additional profiles to account for biodiversity-related information. For instance, since taxonomic registers are the backbone of many web portals and databases, new profiles could describe taxa and scientific names while reusing welladopted vocabularies such as Darwin Core terms  (Baskauf et al.
For PSO, inertia weight () = 1, personal learning coefficient (1) = 1, and global learning coefficient (2) = 2; for IWO, minimum number of seeds ( min ) = 0, maximum number of seeds ( max ) = 5, sigma initial ( initial ) = 0. 5, sigma final ( final ) = 0. 01, and nonlinear modulation index () = 2; for BBO, mutation coefficient () = 0. 1. TLBO algorithm does not demand any parameters for its running. This is one of the distinctive features of the TLBO compared with other intelligent algorithms. The chosen number of iterations, for the four considered algorithms, is 1000 and the size of population is 25. Table  1  exhibits a sample of training and testing dataset that is employed in the learning process used by the ANFIS for go to goal and avoidance obstacle behavior. A database of 310 input-output pairs is prepared based on knowledge of Khepera III.
217 datasets are randomly chosen as training patterns and the remaining 93 datasets are employed as testing patterns to confirm the efficiency of the suggested ANFIS structure. Figures  2, 4, 6,  and 8  depict the training results of the angular velocity using PSO, IWO, BBO, and TLBO algorithms, respectively. Figures  3,  5, 7,  and 9  show the testing results of the angular velocity of the mobile robot employing the same four optimization algorithms. The TLBO method gives the outputs with small errors. MSE, RMSE, mean error, and std. dev. of the training and testing data using PSO, IWO, BBO, and TLBO algorithms are summarized in Table  2. When they are compared with each other, it can be clearly observed that the best outcomes are obtained from the ANFIS trained with the Teaching-Learning-Based Optimization (TLBO) algorithm.
Comparative Study with Other Intelligent Algorithms In this section, a comparative study has been made of the suggested evolutionary trained ANFIS controller (TLBO-based ANFIS) and the other intelligent navigational controllers using the PSO, IWO, and BBO algorithms in the graphical mode. We have presented simulations to prove the ability of the developed path planner to lead the navigation of the mobile robot in various situations. All simulations are performed using Matlab environment using sim. I. am simulator which is developed by GRITS Laboratory of Georgia Tech University. Figures  11  and 12  depict the trajectory crossed by the mobile robot using the proposed method and other intelligent methods in two different strange environments. The red line is the path traced by the mobile robot using the  TLBO-based ANFIS controller.
This body of evidence demonstrates that small N7-alkyl/hydroxyalkylguanine adducts are not pro-mutagenic and, therefore, adduct formation alone is not adequate evidence to support a mutagenic mode of action. Quantitative methods for dose-response analysis and derivation of thresholds, benchmark dose (BMD), or other points-of-departure (POD) for genotoxic events are now available. Integration of such analyses of genetox data is necessary to properly assess any role for DNA adducts in risk assessment. Regulatory acceptance and application of these insights remain key challenges that only the regulatory community can address by applying the many learnings from recent research. The necessary tools, such as BMDs and PODs, and the example datasets, are now available and sufficiently mature for use by the regulatory community.