dataesr/scientific-paragraphs-categorization huggingface dataset:
Linked Open Data has more advantages and less limitations and constraints than OD. Currently, the so-called Linked Open Data cloud already provides access to information covering a large set of domains like economy, media, government, life sciences, etc. The value and potential of using all available data is huge. In addition, while the idea behind OD is built on the concept of a social web, the notion of Linked Data is based on the semantic web approach (Bauer and Kaltenböck, 2011) -a movement which promotes the use of common standards on the Web, encourages the inclusion of semantic data in web pages and allows data to be shared and reused by any kind of application in a cost-efficient way. Sir Tim Berners-Lee created a five-star model which describes the different categories going from OD to Linked Open Data  (Höchtl and Reichstädter, 2011) , to help and encourage entities to link their data:  In the field of data management, Linked Open Data is gaining importance.
CKAN Comprehensive Knowledge Archive Network (CKAN) is another project related to the OD integration topic (OpenKnowledgeFoundation, 2014). It is a web-based Open Source data portal platform for data management that provides necessary tools to the public sector, other organizations and companies wanting to publish and open their data. CKAN provides an extensive support for Linked Data and RDF. CKAN is already used by some important data catalogues worldwide (e. g. the official Open Data portal of the UK  Government (Data. gov. uk, 2014) ; the prototype of a pan-European data catalogue (Publicdata, 2014); and Berlin's Open Data Catalogue (Berlin. de, 2014)).
, 2005). The strength and power of Information Visualization is the ability to present information in many and different forms, graphs and shapes (e. g. : Pie charts, Ellimaps -use nested ellipses of various sizes to build graphics  (Otjacques et al. , 2009), Treemaps, Geographical Treemaps, etc. ). Depending on the purpose and meaning of the processed data, one specific graph may be easier to read and understand than another one. The following architecture is presented to understand the manner in which visualization may be an advantage in the way information is selected, viewed and obtained. In the solution presented above, an Information Visualization block is used in the Integration Module as a component in the integration process. It provides a way to visually present the dataset information and apply filters to them in a visual form.
Based on these facts, and because OD deals with different and heterogeneous data sources and multiple types of data, we argue that Information Visualization can ease the manipulation, understanding and integration process of DATA2014-3rdInternationalConferenceonDataManagementTechnologiesandApplications the data that is generated and the data that is provided by new information sources. Information Visualization can be used to analyse and understand raw data and metadata in both internal and external integrations. Problems and difficulties in understanding, filtering and viewing information can be avoided, minimized and/or eliminated by applying this paradigm. An example of how Information Visualization could help a user to quickly visualize external integration issues is presented in figure  3 : The size of each ellipse presented on the graph is proportional to the number of museums in the related city.
First, observing this graph, it is easy for the user to compare cities and identify which one(s) has more museums. This type of data representation is very useful when the goal is to compare the size of datasets for example. Second, it is also possible to analyse more closely the information in the datasets. In this case, for example, we can see that the information about the number of museums in Nantes can be obtained from two different data sources: data. gouv. fr and Nantes Ouverture des Données. This is a typical scenario where specific information can be obtained from different sources. For example, if a user wants to know the number of museums in Nantes, by analyzing quickly the information on the graph, the user can easily see the existence of data incoherence. data. gouv. fr indicates that there are 4 museums in Nantes while Nantes Ouverture des Données demonstrates the existence of 15 museums.
A user will have to choose one data source for this information, which means he or she has to determine which data source is the more reliable, which one has been modified/updated more recently, etc. An Ellimap can be used for this purpose. It is possible to visualize the metadata of datasets (e. g. by the use of tooltips). The example below demonstrates how the user may see additional information to help him to analyse and identify the required information (e. g. identify the more reliable data source compared to another one). Another kind of graph could be used for the same purpose complementing the information with the location of the analysed data sources: the geographicalweighted Map. In Figure  5 , the same example as presented above is shown. The difference is that the information is organized into rectangles which are positioned according to the location of the data sources (e.
Governments, and private and public entities who wish to open their data should do it in an organized and previously agreed manner, furnishing datasets accompanied by metadata describing their content. Due to the use of standards and the application of principles to publish data over the web, Linked Open Data may be a solution to open, share and reuse data in distributed environments in an effective and costefficient way, so that it can be made available and accessed by any kind of application. But even then, for obvious reasons, OD will continue to be a rapidly-evolving and heterogeneous data source. Thus, Information Visualization can be a powerful tool for aiding the OD integration process. Its methods and means may be used to provide mechanisms to analyse and process large datasets rapidly and efficiently, in both internal and external integra-tion, giving a visual overview of the dataset structure and helping the user to understand its content, detect possible errors in datasets and data incoherencies, and show dataset metadata so it can be used for filtering, etc.
The size of each ellipse presented on the graph is proportional to the number of museums in the related city. First, observing this graph, it is easy for the user to compare cities and identify which one(s) has more museums. This type of data representation is very useful when the goal is to compare the size of datasets for example. Second, it is also possible to analyse more closely the information in the datasets. In this case, for example, we can see that the information about the number of museums in Nantes can be.
Introduction From 1998 to 2009 intermittent archaeological site surveys by two of the authors (CSH and KvN) along 60 km of coastline located in the De Hoop Nature Reserve, southern Cape, South Africa (Fig. 1 ) resulted in the detailed mapping of more than 160 archaeological sites. In 2010 two of the sites that comprise the Klipdrift Complex, Klipdrift Shelter (KDS) and Klipdrift Cave (KDC), were selected for test excavations  (Figs. 1e3). The excavations form a part of the Tracsymbols project, funded by a European Research Council FP7 grant (2010e2015) (http://tracsymbols. eu/), with one key aim being to initiate new excavations at Late Pleistocene archaeological sites in southern Africa. The selection of the Klipdrift sites was based on their visible, in situ Later Stone Age (LSA) and Middle Stone Age (MSA) deposits, the preserved fauna and their relative accessibility.
The spatial extent of individual layers varies throughout the excavated area and layer depths range from c. 2e30 cm. The layers were given alphabetically ordered name codes (PAL, PBA, PCA etc. ) (see Fig. 4 ). Name codes that share the two first letters (e. g. PA and subdivisions PAL, PAM etc. ) were interpreted as having close contextual relationships. A micromorphological study of these layers is in progress. Spatial measurements taken during excavation refer to the numerical coordinate and were given a three-dimensional (XYZ) spatial reference. Lithics >20 mm, identifiable bones, ostrich eggshell, ochre and artefacts of special interest were individually recorded with high precision (1/1000 cm) and with an accuracy of AE2 mm. Recovered finds or features were bagged in plastic, labelled with provenance data and given a unique specimen number.
All site maps, cross sections and illustrations of the KDS stratigraphic sequence are geo-referenced within the numerical coordinate system and made by combining photogrammetric methods with topographic data recorded by the total station. The Klipdrift Complex and surrounds were mapped by scanning the site in 3D. The point cloud that was generated (c. 250 000 points) was imported into Trimble RealWorks 6. 5 and converted into a 3D mesh, from which planar maps, cross-section of surface topography and elevation models were produced. These were subsequently exported as CAD files and imported into ESRI ARCGIS 10. 1 for further refinement, map making and for combining with georeferenced images (Figs. 3  and 4 ). Materials recovered from the sites were primarily sorted and washed at the base laboratory situated at Potberg in the De Hoop Nature Reserve.
, 2013). Single-grain dose recovery tests, using the optimal measurement conditions identified by the single-aliquot data, were performed on four samples and yielded dose recovery ratios consistent with unity. Equivalent dose (D e ) measurements were performed using the optimal preheating regime identified for each sample. Data were screened using the grain rejection criteria of  Armitage et al. (2011). In addition, grains were rejected where the sensitivity-corrected natural luminescence intensity exceeded twice the D 0 value of the saturating exponential fit to the growth curve (Wintle and  Murray, 2006; Chapot et al. , 2012). Equivalent doses were calculated for grains which passed these rejection criteria.
Estimation of the sample burial dose All samples yielded sufficient data to calculate a meaningful D e. Where the overdispersion (sd, the relative standard deviation of the true palaeodoses) of single-grain D e values for a sample was 20% or less, all grains were assumed to belong to a single population (following  Olley et al. , 2004) , and the Central Age Model (CAM,  Galbraith et al. , 1999)  was used to calculate an equivalent dose for that sample. Where overdispersion exceeded 20%, it was assumed that more than one dose population was present, and the dataset was analysed using the Finite Mixture Model (FMM,  Roberts et al. , 2000). All datasets to which the FMM was applied were best fitted with two D e populations, and in each case a single dominant population (!87% of accepted grains) was identified.
The D e calculated for this population was considered most appropriate for age determination. In samples KDS-DS7, 10 and 11, the remaining grains belong to a small (2e8%) lower dose population, which was interpreted to indicate the intrusion of lower dose grains from above by bioturbation, though it is noteworthy that samples overlying KDS-DS10 (KDS-DS1, 2 and 9) do not contain similar populations. The small (7e13%) higher dose population present in samples KDS-DS1, 2 and 9 was interpreted as indicating the presence of "partially bleached" grains. Although 20% overdispersion has been widely used as a threshold above which the FMM should be used, it has been argued that this threshold is strictly only applicable to the  Olley et al. (2004)  dataset. In addition, samples which cannot contain more than one equivalent dose population occasionally yield overdispersion values above 20% (e.
g. Armitage and King, 2013). However, inspection of radial plots for samples KDS-DS9 and 10 (Fig. 5a, b ) indicates that both the minor high and low De populations identified by the FMM are clearly distinct from the population containing the majority of the grains. Conversely, radial plots for samples KDS-DS 3 and 12 (Fig. 5c, d ), which were analysed using the CAM, appear to show a single population of grains. These results indicate that, for our dataset, the correct statistical model may accurately be chosen using the overdispersion parameter. Ages for the KDS samples are presented in Table  1.
Shellfish The shellfish data presented are a sample of the material retained in the 3 mm sieve from a number of quadrates (between four and six per layer) spanning the sequence from PCA to PAY. This data represents 32. 4% of the total volume excavated from these layers. Just over 29 kg of shellfish has been analysed from a volume of 0. 51 m 3 and 7 layers. Shells were weighed and quantified by determining the minimum number of individuals (MNI) per layer, based on counting the apices of gastropods, the left and right umbos of bivalves with the most common side taken as the MNI, and the highest number of either front, back or middle valves (middle valve counts were divided by 6) of chitons was taken as the MNI. Both apices and opercula of the giant periwinkle Turbo sarmaticus were counted and the highest count taken as the MNI.
The greatest dimensions of intact limpets and opercula were measured with digital callipers to the nearest millimetre. Shells that were <2 cm (whole) were not considered to be food items and were recorded as incidental shells or juvenile limpets. In total, excluding the incidental and juvenile shells, 14 species of shellfish were identified (Table  8 ). Note that although two periwinkle species, Diloma sinensis and Diloma tigrina, are present, their data have been combined as the countable apices are not identifiable to species level when the shells are broken. Overall, the most common species, in terms of MNI (absolute, per m 3 and in terms of relative frequency), is the giant chiton, Dinoplax gigas, followed by the brown mussel, Perna perna, and T. sarmaticus. By weight, the most common species is the abalone, Haliotis midae, followed by D.
Acknowledgements Financial support for the KDS project was provided to CSH by a  European Research Council  Advanced Grant, TRACSYMBOLS No. 249587 , awarded under the  FP7 programme  at the  University of Bergen , Norway and by a  National Research Foundation/Department of Science and Technology funded Chair at the University of the Witwatersrand, South Africa. Additional funding for the KDS excavations in 2013 was provided by the  National Geographic Expeditions Council , grant number  EC0592-12. We would like to extend thanks to the board of  Cape Nature , and especially  Tierck Hoekstra  and  Callum Beattie , for access to the  Klipdrift Complex  and the facilities at Potberg. We thank  Kurt Muchler  at  NGS , and  John Compton  for useful comments. We thank  Gauthier Devilder  for the lithic drawings.
Method Ethic Statement. The protocol was carried out in accordance with the ethical standards of the Declaration of Helsinki (BMJ 1991; 302: 1194) and approved by the Ethics Committee of the University of Milano Bicocca. All participants signed an informed consent before testing. Participants. The sample included 16 adults (12 females; age: mean 24,44 years, range 20-42). All participants had normal or corrected-to-normal vision. They had no previous experience of eye-movement studies and were naive to the hypotheses of the experiment. Stimuli, apparatus and procedure. Participants were placed 60 cm from the stimulus monitor. Before beginning the experimental trials, the eye tracker was calibrated by presenting animated cartoons at nine different locations on the stimulus monitor. Subsequent eye movement data were calculated from these calibration values.
The experiment consisted of two 60-trial blocks, the first one in which non-symbolic numerical stimuli were presented, the second one in which symbolic numerical stimuli were presented. Each block consisted of 48 experimental trials (2 numerical display 62 target position 612 repetitions), and 12 catch trials. Catch trials were introduced to prevent anticipatory responses, and did not include the target. The magnitude (2 or 9) of the numerical display and the position (left or right) of the target were randomized across trials. The stimuli were presented with E-Prime 2. 0 software on a 240 monitor with a resolution of 160061200 pixels, and eye movements were recorded using an ASL6 remote eye-tracking system at a frequency of 120 Hz (Applied Science Laboratory, MA). To coordinate the eye movement data with the respective stimulus displays, the stimulus-generating computer sent unique, time-stamped numerical codes via a parallel port to the ASL computer, indicating the onset and type of stimulus display.
In turn, the ASL computer sent the coordinates of the eyemovements continuously to the stimulus-generating computer that computed the coordinates of the eye-movements using E-Prime 2. 0. Data analysis. The visual display was virtually divided into 3 areas of interest (AOI), one surrounding the position of the central attention getter, and the other two corresponding to the two peripheral circles where the targets appeared. Each AOI measured approximately 12. 6u in width, and 7. 6u in height. Time to target fixation (TTF) was used as the dependent variable. TTF refers to the time difference between the target onset and the time the participant's gaze entered the target AOI, provided that the AOI was fixated for at least 100 ms. Analyses were performed on the 96 experimental trials. Catch trials were not included in the analyses.
Data Data were extracted from various sources. We consulted the  Beck, Levine, and Loayza (2000)  database on financial structure to collect stock market and financial system indicators from 1960 to 2006. 2  The sample period spans major events that have transformed the economies of the MENA region, reflecting the energy boom and a higher degree of integration into the global economy. Other information related to economic growth, inflation, and openness is collected from IFS (International Financial Statistics) and WDI (World Development Indicators) databases. Our original intention was to include all MENA countries, but given that some countries have not yet created stock markets (e. g. Iraq, Libya, Sudan, and Yemen), and other countries only established stock markets very recently (UAE), the sample covered only twelve countries.
The relevant data are form the  Beck et al. (2000)  database on financial structure database. Macroeconomic data (Macro) is a standard set of conditioning variables that the literature has found to affect financial development. It includes real GDP growth to account for economic development. Furthermore, we include the inflation rate based on a CPI index (IR) and the ratio of government expenditures to GDP (GC) as indicators of macroeconomic stability. Openness variables refer to trade and capital account liberalization measures. We use the ratio of exports plus imports to GDP (TO) to capture the degree of openness of an economy and the ratio of capital inflows (Foreign direct investment and Foreign portfolio investment) to GDP to measure capital account openness  (Chinn & Ito, 2002). In the footstep of  Yartey (2008) , the paper also studies the impact of four of the components of political risk on stock market development: law and order, bureaucratic quality, democratic accountability, and corruption.
Measurements and data collected The interviewers recorded socio-demographic characteristics (household income, education, marital status), smoking status, alcohol dependence according to the CAGE score  [19] , and present and past medical conditions, which were coded using the ICD-10 (international classification of diseases, 10th revision) and used to compute the Elixhauser comorbidity score [unweighted count of present chronic conditions (0 to 30)]  [20]. Smokers and ex-smokers were given a questionnaire to obtain detailed information about smoking history. Present and past average numbers of cigarettes, cigars, or pipes of tobacco smoked per day and duration of smoking was recorded for current and former smokers. Time since quitting was also recorded for ex-smokers. Participants were further classified into never-smokers, ex-(former) smokers, current daily smokers (at least one cigarette [or cigar/ pipe] smoked daily), current occasional (non-daily) smokers and occasional ex-daily smokers.
Due to large differences in the relationships between smoking and HRQoL according to gender and age, all analyses were stratified by gender and age group (25-44 and 45-64 yrs). STATA (Version 8. 0, Stata Corporation, College Station, TX) and SAS statistical software (Version 9. 2 SAS Institute Inc. , Cary, NC) were used. Analyses were conducted in 2013.
g. targeting multiple behaviors and/or facilitating access to mental health services. Several limitations of this study require discussion. First, the cross-sectional design precludes the determination of causal relationships between smoking patterns and HRQoL, despite the chronology of ''exposure'' (smoking being usually a long-lasting behavior) and HRQoL measurement being generally unambiguous. Second, self-reported smoking habits and morbidities elicited by trained lay interviewers (not medical doctors) were used, and no access to medical records to ascertain or complement the data collected was possible. Self-reporting biases tend to give attenuated estimated associations (biased toward null) and limit the control of confounding factors. Third, although we attempted to adjust for a number of potential confounding factors, there may have been residual confounding from unmeasured or incompletely measured underlying socio-economic or behavioral factors.
Current situation of ASD screening studies in Europe To obtain a complete picture of the status of ASD screening in Europe, we used a two-pronged search process (See Fig. 1 ). A search of the scientific literature was made covering the PubMED and PsycINFO databases and using the following search terms: 'autism' OR 'autism spectrum disorder' AND 'screening' or 'identification' or 'detection', with ''1992-2012 Pub-date'' and ''English language'' as advanced filters. This search retrieved over 700 citations. Perusal of the titles, authors and abstracts of these citations to discard any study that had been not undertaken in Europe, yielded a net total of 16 papers. When reviewing these papers, the following additional selection criteria were applied for their final inclusion: (a) design: population based; (b) participants: children under the age of 4 years at first screening and with no prior diagnosis of developmental delay (no school-age tool); and, (c) gold-standard diagnostic procedure: DSM-IV-TR criteria for pervasive developmental disorders (PDDs), also known as autism spectrum disorders (ASDs)  [52]  and the autism diagnostic observation schedule (ADOS;  [24] ).
The reference lists of all relevant studies were checked to identify any additional publications. Using these selection criteria, papers reporting screening at school age, as in Finland  [53, 54]  and the UK  [55] [56] [57] [58] [59] [60] , were excluded. Similarly excluded were the study conducted in Ireland  [61]  because it did not use the DSM-IV as standard diagnostic procedure, and the study undertaken by Allison et al. [20]  because it was not population based. Eight studies reporting 15 screening procedures for young pre-schoolers with ASD in Europe were retained for review. Secondly, researchers within the ESSEA COST action network were approached to ascertain whether there might be any other ongoing, as yet unpublished screening programmes. As a result, a further three screening procedures were identified in France, Italy and Finland, and preliminary data were incorporated into this review, leading to a total of 18 different screening procedures.