dataesr/scientific-paragraphs-categorization huggingface dataset:
Consequently, in 2015 we consider our primary research driver to be the fostering of a research network with the aim of identifying common ground and reconciling differences. The La Manche Prehistoric research group (LaMP) has been established directly out of our Jersey-based work not only to continue active research in the Channel Islands, but to develop a wider community of cross-channel research with the aim of sharing data and expertise and to work towards unified mapping and resource management frameworks. We see the development of this network as the single most important outcome of our research in Jersey, which has provided a strategic platform, separate from both UK and French systems in which to harmonise research of both countries. As for the archaeology of the submerged English Channel landscapes themselves, this requires more careful consideration.
Acknowledgements Grateful thanks are extended to  Jersey Heritage , the Société Jersiaise, The  National Trust for Jersey , the  States of Jersey Department of Planning and Environment  for their generosity and support; to the  AHRC ,  NERC , the  Leverhulme Foundation  and the  Calleva Foundation ; to  Olga Finch ,  Neil Mahrer ,  Anne Best ,  Sheena Brockie ,  Dominic Jones  and  Charlotte Hotton  for their support on the Island; to  Alan Hubbard  and  Nolwenn Chauche  for their time and the use of the survey ship Gambo. We would also like to thank  Marcus Hatch ,  Joroen Adrianson ,  Jesse Bennett ,  Lucie Bolton ,  James Cole ,  Sam Griffiths ,  Andy Needham ,  Dave Underhill ,  Karen Ruebens ,  Tabitha Paterson ,  Geoff Smith  and  Rebecca Wragg-Sykes  for their contributions to fieldwork and archive reorganisation.
The incubators provide evaluation at set temperatures only, while the use of the hut provides a real-life situation with temperature changing seasonally and diurnally. As reference, RDTs were also kept at approximately +4 C in a laboratory refrigerator. The RDTs were kept in their original packaging. The temperatures in all locations were recorded every 30 minutes using electronic thermometers (Tinytag Ultra 2 data logger All RDTs were from the same manufacturer's lot (Lot No. 146001) and their expiry date was February 9, 2014, which means the study continued for 6 months after the expiry date. Preparation of control sera. To evaluate the RDT performance over time and at differing temperature, duplicates of each sample were tested at each time/temperature point (Figure  2 ) with a total of 88 RDTs per sample tested.
RESULTS Temperature variability. Mean monthly temperatures, with 95% confidence interval (CI), recorded in the refrigerator (4 C), in the incubators (35 C, 45 C, and 60 C), and hut are presented in Figure  4. Refrigerator (4 C). The mean (95% CI) temperature within was 4. 06 C (4. 04-4. 07 C). Sporadic elevation of the temperature was observed due to monthly cleaning of the refrigerator but this was never 18 C and lasted a maximum of 30 minutes. Temperature data were missing for 9 days, as a  Temperature in the hut. The temperature recorded in the hut was unavailable for 11 days as the storage capacity of the temperature logger was exceeded. Minimum and maximum temperatures recorded were 15. 7 C and 42. 0 C, respectively. The numbers of recordings for the five temperature groups are shown in Table  1.
Degradation of the strip itself could also be due to the quality of materials used. The hut used in this study was built to mimic the storage condition in the field, in rural Laos. The temperature recorded exceeded 40 C in March, April, May and June and was higher than that recommended by the RDT manufacturer for approximately 29% of the temperature records during the 2-year study period. The study was performed in Vientiane, in the central region of the country, but it may be expected that the temperatures within houses would be higher in the south. However, the 90-day storage at 45 C and the 2-day storage at 60 C suggest that short-term extreme temperatures do not affect the dengue RDT results. We do not present humidity data as the RDTs were packed in sealed packets, all of which were intact.
Acknowledgments: We are very grateful to the patients and  Bounthaphany Bounxouei , the Director of  Mahosot Hospital ;  Rattanaphone Phetsouvanh , Director of the  Microbiology Laboratory ;  Chanphomma Vongsamphan , the Director of  Department of Health Care, Ministry of Health; and Eksavang Vongvichit, Minister of Health, Lao PDR , for their help and support. Financial support: This work was funded by the  Wellcome Trust of Great Britain and Institut de Recherche pour le Developpement (IRD). The RDTs were a gift from  Standard Diagnostics, Inc. Disclaimer:  Standard Diagnostics  was not involved in any aspects of the study (study design, results analysis, and writing of the article).
g. ata02te9bk29z620-630 is the label of a sample excavated during 2002, in level TE9b, square k29 and at a depth of 620e630 cm, from the level 0 of the excavation), enabling us to maintain rigorous stratigraphic and spatial control throughout. Then, the small fossil remains are extracted from these concentrates by using a hand-held or binocular magnifying glass. Afterwards, in the laboratory of the University of Zaragoza, a preliminary classification of the microfossils is undertaken, and the information recorded in the data base of the microfauna of Atapuerca (Cuenca-Besc os, Atapuerca micro DB, unpublished). The specimens studied for this paper are kept in the Palaeontology Museum of Zaragoza University. After identification and classification of the fossils of small vertebrates, we analyse its distribution along the stratigraphic sequence.
Acknowledgments Mathieu Duval ,  Josep Maria Par  es,  Lee Arnold  and  Dirk Hoffmann , organized the  ESF Earthtime-EU Scientific Meeting  "The Early-Middle Pleistocene transition: Significance of the Jaramillo subchron in the sedimentary record". Over the last 20 years, the Atapuerca excavation team helped with the extraction, sieving and washing of sediments each year. The excavation campaigns and the sorting of material were supported by the  Junta de Castilla y Le on , the  Fundaci on Atapuerca , the  INAEM ,  MICINN  projects  CGL2006-13532-C03-02 ,  CGL2009-12703-C03-01/02/03 ,  CGL2012-38434-C03-01 , and the  University of Zaragoza. J. Rofes  is beneficiary of a (MCA- IEF  Project n  629604 ). J. M. L opez-García is beneficiary of a  Beatriu de Pin os postdoctoral fellowship  ( 2011BP-A00272 ) both grants cofunded by the  European Union  through the  Marie Curie Actions of the 7th Framework Program for RþD.
Study design and population Our data are part of an observational prospective multicenter study conducted from January 2010 to June 2012 in 27 French cancer treatment and research centers and involving 772 young women with diagnoses of nonmetastatic breast cancer. Out of the 772 patients to whom the study was proposed, 546 patients agreed to participate and returned their filled questionnaire (168 undergoing chemotherapy with or without Trastuzumab, 58 undergoing Trastuzumab with or without hormone therapy, 176 patients undergoing hormone therapy only, and 144 under follow-up, after the end of treatment). Patients were included by their oncologist if they were aged less than 45 years at their diagnosis for a nonmetastatic breast cancer, had received or were receiving chemotherapy, and had signed an informed consent form.
Patients with poor knowledge of the French language were not included in the study. The objectives and procedure of the study were explained to the patients during an outpatient appointment. After they had agreed orally and signed the consent form, patients received a questionnaire and a socio-demographic data form. They were asked to complete these documents in a quiet location and to return them in a pre-stamped envelope to the research centers. Conditions of anonymity and confidentiality were guaranteed. At the same time, patients' medical data were collected by each investigator in the participating centers. All women were asked to complete the YW-BCI. To test concurrent validity, 111 women also answered a standard quality of life questionnaire (QLQ-C30 and QLQ-BR23,  [29] ). For the reliability analysis, the YW-BCI was administered two weeks after the baseline measurement in 116 patients.
Statistical analysis The construct validity of the scale was assessed by exploratory and confirmatory analyses. The exploratory principal component analysis (PCA) were conducted on a sample of 304 patients, randomly chosen from the 546 patients who completed the instrument. The confirmatory analyses (CFA) were carried out on a random sample of 250 patients from this initial sample. Descriptive analyses (mean, standard deviation, skewness and kurtosis) were conducted first, in order to eliminate the poorly discriminative items (n = 14). Exploratory principal component analyses using the principal axis factoring method of extraction and Promax rotation were then conducted with the Statistical Package for Social Sciences Version 18 to identify the factor structure of the scale. At this step, items showing cross-loadings or loadings less than 0.
30 were eliminated (n = 32). Items were thus selected with factor loadings of at least 0. 30. Series of confirmatory factor analyses based on a structural equation modeling method were then conducted on the retained items, with LISREL 8. 8 software  [40]. Internal consistency was examined for each subscale of the YW-BCI by using Cronbach's alpha coefficients. Test-retest reliability was investigated using the Bravais-Pearson's correlation coefficient for the sample of patients (n = 116) who completed the YW-BCI questionnaire twice. The convergent validity of our scale was assessed by calculating the Bravais-Pearson's correlation coefficients between the patients' scores in the YW-BCI and their scores in the QLQ-C30 and QLQ-BR23. Given that they were subjective quality of life constructs, quite strong correlations were expected between the subjective dimensions of quality of life measured by the QLQ-C30 and QLQ-BR23 (emotional functioning, social functioning, etc.
Acknowledgements The authors wish to extend their grateful thanks to all the patients of the study, as well as all the investigators:  C. Loustalot ,  C. Guillemmet ,  M. Leclercq ,  C. Levy ,  C. Giraud ,  C. Lefeuvre-Plesse ,  J. S. Frenel ,  H. Simon ,  T. Leroy ,  C. Becuwe ,  S. De Cordoue ,  J. M. Ferrero ,  D. Nierges ,  S. Tiberghien ,  J. Grosjean ,  K. Prulhiere ,  L. Chossiere  for the collected data, and the staff of the  Clinical Research Unit of the Centre Oscar Lambret  for their invaluable assistance when gathering the data. This paper presents independent research funded by the  Ligue Nationale contre le Cancer , the  Conseil Régional du Nord-Pas de Calais , the  Prix Ruban Rose 2010 , and  Sanofi ,  Roche  and  Novartis. The authors also thank the  MESHS USR CNRS  and the  SIRIC ONCOLille, Grant INCa-DGOS-Inserm 6041 , for their help.
Data Numbers of deaths in people aged 18 to 74 years between 1953 and 2010 were obtained from the Ozyorsk cause-of-death register  [3]. They were subdivided into 2 population groups covering the entire closed city: the people ever employed at one of the 3 main Mayak plant types (reactors, radiochemical and reprocessing plants), and the remainder of the Ozyorsk population. The latter also included the other Mayak PA workers not working at any of the 3 plant types. The two groups will be called the "3-plants workers" and the "other residents" for simplicity. For the 3 plants workers, size of the population at risk by 5-years age groups for each 5-year calendar time periods was computed from the Mayak PA employment records. For the other residents, the size was computed from the lists of electors of city and state authority elections containing all the city citizens aged 18 years or older for the period before 1958, and later, from the census information in years  1959, 1970, 1979, 1989, 2002  and 2010 and the local statistics bureau for population information, from which the 3-plant workers population was subtracted.
Only Ozyorsk residents contributed person-years at risk until death, migration or 2010, whichever came first. People working at Mayak PA contributed person-years to the 3-plants workers population from the time when they started working in one of the 3 plant types. For comparison, deaths rates in the Soviet Union until 1991 and in the Russian Federation afterwards were obtained from the WHO database  [6]  for the longest possible period of time. The cause-of-death register of Ozyorsk codes diagnoses according to the Russian version of the ninth revision of the International Classification of Diseases (ICD-9). The register received copies of the original paper death certificate and coding is done manually by registry staff. Mortality from all causes of deaths (ICD-9 codes 001-999) was analysed.
In addition to this charter, similar products are generated by the Emergency Management Service (EMS) of Copernicus. Copernicus is the European Union's Earth Observation program and EMS is one out of six services that integrates satellite-derived data with in situ data for the analysis and the monitoring of issues relevant for environment and security. Hand in hand with the development of these Copernicus Services, the European Commission together with the European Space Agency (ESA) launched its own dedicated constellation of satellites-the Sentinels. It is foreseen to give the user-under certain and still-to-be-defined conditions-free access to Sentinel data. If this is going to be realized, one constraint hampering the wider use of satellite-derived information for disaster risk management will be eliminated: the costs for EO data.
On the other hand, this is, at the same time, a necessary prerequisite for data integration, which is a key opportunity offered by GIS technology to the management of RS data and GIS. Different types of scales (temporal, spatial, administrative, etc. ) and different levels (local, regional, national, international etc. ) have distinct, specific effects on permitting identification and measurement of, for example, social vulnerability  [15, 23]. Opportunities and challenges of scale, up-scaling, dis-aggregation, identification of proper research area boundaries, units or auto-correlation effects and tools to analyze and compensate auto-correlation are beyond the scope here and have been intensively discussed elsewhere  [17, 18, 24, 25].
Some of these effects are the modifiable areal unit problem, ecological fallacy or spatial autocorrelation, but in this paper we will not go deeper in these issues  [26, 27]. On the other hand, the advantage of GIS is to map individual indicators, and to allow for multiple layer representation and analyses depending on how the database is structured. Aggregation methods are rarely considered with adequate care by scholars, often overlooking effects of normalization and internal compensation, and neglecting the opportunities offered by the algorithms developed by the literature on Multi-Criteria Analysis (MCA). Another risk stems from data sharing and communication; from an end-user perspective of civil protection bodies that need to take care of possible theft of data that could be misused by saboteurs for planning attacks on the identified vulnerable hotspots, be it people or critical infrastructure.
A greater awareness and transparency on the pitfalls of the usual methodological approach would be useful for the community applying GIS for DRM. Second, a greater awareness of security concerns of end-users or public bodies, or industry would be instrumental in improving the wider acceptance, and effectiveness of GI and RS data and tools. We believe that GIS and RS are indispensable tools and such pitfalls will and should not delimit their potential. However, a certain awareness of pitfalls and maturity in terms of discussion of challenges will be beneficial especially when it comes to interdisciplinary research projects and transdisciplinary collaborations with policy and practice. In addition to the differences of GIS compared to RS the approach is still technology-driven. Scientists working with these tools, scrutinizing their potential, and developing codes for improved analysis usually do not consider user needs in the first place.
0. Producing maps and Geographic Information by non-expert people without academic studies and with local knowledge about their environment and, generally, the world, is preparing a phenomena that is named in general as "citizen science" and, more specifically, by different terms in geographic researches such as Neogeographic, Public Participation GIS, Ubiquitous cartography and, in general, the collection of spatial data and dissemination of them on the Internet by citizens were named by Goodchild  [34]  as Volunteered Geographic Information (VGI). Web sites such as OpenStreetMap (OSM) and Wikimapia, aiming to produce a free and editable map of the world, are examples of VGI. For the most part, research on disaster response has assumed that states or other quasi-governmental entities (e. g.
, the United Nations) would be the primary actors in disaster relief, with NGOs playing a secondary role. Therefore, it comes as no surprise that the role of IT was primarily viewed as a means to enhance the command, control, and dissemination of information  [35] [36] [37] [38]. First and foremost, there is a need to consider which scientific questions can be answered by citizen science according to the patterns of data collection, the ability to recruit and train volunteers, the suitable participation level, and other aspects of VGI. Second, there is a need to overcome the cultural issues and to develop an understanding and acceptance of citizen science within the scientific community. This will require challenging some of the deeply held views in science, such as viewing uncertainty not as something that can be eliminated through tighter protocols but as an integral part of any data collection and, therefore, developing appropriate methods to deal with it during analysis.
The most significant advantage of VGI is that they can be up-to-date in less time than traditional data, so for the projects that have time limitations, such as updating the streets of a city in few weeks, the local citizens are the best source to collect data and update information about the streets  [42]. On the other hand, some monitoring systems are more and more exposed to the risks of budget cuts and volunteered systems are liable to fluctuations of people and their motivations. Crowdsourced data, in general, and volunteered geographic information, in particular, are becoming the huge source of data. VGI has enormous advantages such as: it's free, has the ability to produce large amounts of data in short period of time, and collect local data that are, in some cases, impossible to obtain by traditional methods of mapping.
Despite its benefits, volunteered geographic information cannot be used in many applications because its quality is not determined and there is vagueness about it. Therefore, much research has been carried out so far to determine the quality of VGI  [43]. In some specific cases, the problem of the VGI quality could be not crucial and the lack of precision can be used for other purposes. For measuring environmental parameters, VGI data usually do not satisfy the requirements of precision, accuracy, and error. Nevertheless, with appropriate means, VGI can become usable and produce relevant environmental data. For example, in case measures from conventional instrumentation are available and, at the same time, a large amount of VGI can be collected, despite the scarce accuracy of the latter, the high accuracy of the standard measurements tool can be used to correct the bias and to use the VGI as a measure of the spatial variability of the measure.
[56]  show how social networking technologies around transport attacks are potentially transmedia orientated and make use of sentiment. In particular, authors in  [56]  specifically looked at the characteristics of daily social media conversation and how this may react to specific events through automated content and sentiment analysis of Twitter data. Geo-tagged social media data was used by Schmidt and Binner  [57]  as a proof of concept for the development of an early warning tool to help first responders and emergency management personnel to quickly assess the scope and location of a current crisis, and to quickly summarize the state of affairs  [57]. A related study by Preston et al. Authors in  [56]  carried out an initial manual content analysis on a Tweet dataset to understand how the attack on Domodedovo airport had been discussed in the UK Twitterverse.
From a dataset of over 300,000 tweets posted from 24 to 27 January 2011, we extracted tweets that contained the following keywords: "bomb", "explosion", "Moscow", "Domodedovo", "airport". Of the 198 posts retrieved, 61 were directly related to the attack, 17 referred to other attacks and 120 were of "conversational" nature (e. g. , "calm as a bomb"). It was noted that all the data directly related to the attack could be grouped into the following four categories: (1) Broadcasting, (2) Fact-finding, (3) Reacting, and (4) Projecting. The categories closely match the three-step cognitive process of SA theory  [58]  as each step seems to emerge in chronological order and it coincides with a deeper understanding of the event. For example, first the news is broadcasted "Russian media reporting that at least 23 people were killed and 100 injured in Moscow airport bombing".
SOCIOPATH metamodel The SOCIOPATH metamodel allows to describe the architecture of a system in terms of the components that enable people to access digital resources. It distinguishes two worlds; the social world and the digital world. In the social world, persons or organizations own any kind of physical resources and data. In the digital world, instances of data (including source codes) are stored and processes are running. Figure  1  shows the graphical representation of SOCIOPATH, that we analyze in the next. The social world includes persons (e. g. , users, enterprises, companies), physical resources, data, and relations among them. -Data represent an abstract notion that exists in real life, and does not necessarily imply a physical instance (e. g. , address, age, software design). -Physical Resource represents any hardware device (e.
g. , PC, USB device). -Person represents a generic notion that defines an individual like Alice or a Legal Entity like Microsoft. The digital world has entities that are defined as follows: -Data Instance is a digital representation of a Data that exists in the social world. For instance, a person has an address (Data) in the social world. Data Instances of her address can be present in different digital documents: letters ((e. g. , encoded using. doc format), contact applications, commercial databases, etc. Even if encoded using different formats, each data instance is a semantically equivalent instance of her address. Similarly, a source code is also a Data Instance implementing a software (text editor, mailer. ) in the digital world. -Artifact represents an abstract notion that describes a "running software".
This can be an Application, an Operating System or a Network Service. It may be a single process or a group of processes that should be distributed on different locations, yet defining a single logically coherent entity. -Digital Resource represents an Artifact or a Data Instance. -Actor represents a Person in the social world or an Artifact in the digital world. This is the core concept of SOCIOPATH. Indeed, only Actors can access or control Digital Resources as presented below. The relations proposed in SOCIOPATH are briefly described next. They have to allow to represent in a non naive way how a system is built. They should also help to highlight the links between the structure of a system and the confidence of a user within this system. We do not claim the proposed list to be exhaustive, and one can think about many other relations to describe a system.