dataesr/scientific-paragraphs-categorization huggingface dataset:
Data To study whether bank efficiency affects the cost of credit for firms, both firm-level data and bank-level data need to be collected. The firm-level data come from the Amadeus database provided by Bureau van Dijk, which contains comprehensive financial information on public and private companies across Europe. The vast majority of firms in Amadeus report unconsolidated financial statements; consolidated statements are provided mainly by large companies only. In our dataset, we use unconsolidated financial statements, to avoid double counting firms and subsidiaries or operations abroad, and exclude firms that report only consolidated statements. We exclude firms operating in the financial intermediation sector and insurance industries (NACE codes 64-66), because they have a different liability structure and cannot be similarly taken into account in our investigation explaining the cost of credit.
The bank-level data used to compute bank efficiency come from the Bankscope database. We further match bank-level information to firm-level information by taking advantage of the recent Amadeus update, which includes information about lending banks for each firm. We link both databases by carefully checking the identity of lending banks and matching it to banks available in Bankscope. We focus on nine 'old' EU member countries for our investigation, since they represent a consistent sample of developed countries without the specific characteristics of the more recent EU members. The newer EU countries are former or still transitioning economies with specific populations of firms and particular banking sector features, for example a substantial market share of foreign banks, which can both raise the cost of and impede access to credit.
4 Micro firms (30 %), and small and medium-sized firms (67 %) together represent 97 % of the entire sample. We consider four country-specific control variables. We control for banking development, with Private credit defined as the ratio of private credit by deposit money banks and other financial institutions to GDP, collected from the Global Financial Development Database. GDP per capita and Inflation take into account macroeconomic conditions and are both extracted from the World Development Indicators. Rule of law measures institutional quality and comes from the Worldwide Governance Indicators. After excluding observations for which firm-level information or the identity of the lending bank(s) are not available, we have a sample of 377,925 firm-bank observations for about 240,000 firms.
These estimations are displayed in columns (  1 ) and (  2 ) of Table  8. We observe a significantly negative coefficient for bank efficiency in all estimations, meaning that greater bank efficiency is associated with the lower credit costs for firms. These results are not only consistent with the results obtained on the full sample, but also, as expected, stronger -the estimated coefficient is negative and significant in both specifications. Alternative measure for the cost of credit. Following Fungacova, Shamshur and Weill (2017), we redefine the cost of credit as interest paid divided by total debt, since information on interest paid is available in the Amadeus database for a large number of firms. The results are reported in columns (  3 ) and (  4 ) of Table  8. We still observe that the estimated coefficient of bank efficiency is negative and significant in the specification with country fixed effects.
Using these determinants, authorities can design policies enhancing bank efficiency so as to foster access to credit and thus improve the financing of the economy as a whole. From a positive perspective, our work can help to understand the cross-country differences in the cost of credit. It demonstrates that bank efficiency is one of the important determinants of the cost of credit and as such should be taken into account alongside the degree of competition or the development of banking markets. In addition to these implications, our results are of importance for researchers, since they provide a major reason to investigate the level and the determinants of bank efficiency. Our research is an initial step towards understanding the effects of bank efficiency on the cost of credit. Further work is needed to check the relevance of our results with alternative datasets, in particular in emerging and developing countries, where companies suffer the most from the high cost of credit.
4 5 Within an interoperable system, electronic civil registration and medical records can significantly improve the follow-up of patients. Not only will these tools provide accurate patient data to sustain healthcare in real time, but they will also enable decision-makers and researchers to generate databases at the population and territory level,  6 7  innovate in health impact measurements and remodel health systems. Compounded with this is the necessity to further invest in cybersecurity to allow for a safe use of numeric health data, while ensuring a legal environment to protect the privacy rights of individuals and populations. Second, in the era of the Sustainable Development Goals with the motto 'Leave no one behind', we firmly believe that we can no longer keep unchecked the invisibility-both at theoretical and praxis level-of marginalised populations, such as vulnerable groups of women and girls, people with disabilities, indigenous peoples, sexual minorities, migrants, refugees, etc.
Methodology used To establish a diagnostic of a complex problem with all the stakeholders; • To measure qualitatively and quantitatively the level of the links between stakeholders of a system; • To produce with all stakeholders an action plan to solve the problem. The FAcT Mirror® method is based on a listing of the Fears, the Attractiveness ant the Temptations of treason a party can have in a relation with another stakeholder and towards the project itself Normally the process is based on the organization of workshops where all parties are free to express the FAcT about the relation. After this first phase, all participants are invited to note all the FAcT, the Owner evaluates the importance of its own Fact and he also evaluates the Contractor's FAcT. The notation is based on the security risk assessment system, it means that we combine the probability and the gravity of an item to determine its level of importance The next step consists in structuring the data by classifying the items by thematic.
This methodological choice is shared with many participatory research projects and facilitates reflections on "the" transition. But we can also follow a prospective approach that holds several scenarios and several possible paths  (Delmotte et al. 2017). It can maintain comparability of different options, not necessarily dominated by strong agroecology. In fact, there is a possible contradiction between the need for a strong Ecological Modernization of Agriculture and the ambition to develop participatory approaches. The TATA-BOX approach begins with a diagnosis of the territory and its agriculture, but participation could well result in more than just the capture of knowledge and data from the stakeholders. What happens if they want to deal with "their" problems and propose solutions that are not referring to "strong ecology" or even "weak ecology"? What happens if there is no possible convergence towards a "Territorial Agroecological System"? We agree that AET cannot be promoted without participation, even with more punitive and coercive public policies, but participation does not necessarily create an AET.
Participants and procedure The study population was composed of 15-to 18-year-old secondary education students enrolled in teaching centers in Spain. The sampling size, 1,764 students, was calculated at a confidence level of 95% and an error margin of 2. 3% on the basis of data contributed by the Ministry of Education, Culture and Sports for the academic year 2010-2011. Simple random sampling was used, and the set proportions were conserved in each of the Autonomous Regions and at each of the general tiers of education (67% of students from pre-university -high school-studies; 32. 7% of students from intermediate vocational training cycles; and 10. 3% from basic vocational training). The last sampling units were selected during the 2013-14 academic year by selecting educational centers at random from each Autonomous Region on the basis of two criteria: selection of a rural center in each Autonomous Region and a proportion of one private-state-assisted center for every three public educational centers.
In particular, the following questions were analyzed: In the case of PCA, the new features (principal components) obtained from that re-dimensioning are the result of a linear combination of the original variables and, in turn, will be independent from each other. In present paper, every item in the dataset is visualized through a 2D display where the coordinates are the principal components. Thus, the obtained representation can be visually analyzed in order to get deep knowledge from a previously unknow dataset. This is the usual methodology in the field of Exploratory Projection Pursuit. Q. 1 -Q. PCA was initially developed by Pearson  [82]  at the start of the 20th century and then studied and further developed by Hotelling  [83]. PCA has two possible functions: the optimal projections of a general N-dimensional space onto a space of reduced dimensionality (the principal components are the first step to identify the possible latent or non-observed variables that generate the data) and it permits the transformation of the original and generally correlated variables into new decorrelated variables, facilitating the interpretation of the data.
preprints. org) | NOT PEER-REVIEWED | Posted: 7 January 2019 Preprints (www. preprints. org) | NOT PEER-REVIEWED | Posted: 7 January 2019 doi:10. 20944/preprints201901. 0049. v1 Peer 444, forming part of the thematic section Entrepreneurship (psychological variable), gathered information on the presence of different methodologies and capabilities (psychological variables) in training. It was measured using a 5-point Likert-type scale. Data analysis After selecting the questionnaire questions, a code was used to identify each item, thereby leaving a set of 1,633 items and 92 features per item. In order to analyze such a multidimensional dataset, PCA has been applied. It is a statistical method of data analysis based on re-dimensioning the data (reducing the number of features); in other words, the end-purpose was to reduce the amount of features in a dataset with multiple features, 10, forming part of the thematic section Students (family and demographic variables), where information was gathered on sex; year of birth; people living with you; number of people living in the house; family situation; family relation; country of origin of father, mother, and student; post code; weekly allowance; level of studies; and employment of father and mother.
It was measured using a 5-point Likert Scale. Q. 42, forming part of the thematic section Entrepreneurship (psychological variable), gathered information on the motives for creating a firm. It was measured through the selection of the three most important motives. Q. 43, forming part of the thematic section Entrepreneurship (psychological variable), gathered information on the difficulties of creating a firm. It was measured through the selection of the three most important difficulties. Qseeking to minimize the loss of information, as far as possible, for the new data. Differentiating from feature selection, where the most informative features from the original dataset are selected, PCA lies in the category of feature extraction, where original features are combined to generate a reduced set of new features.
III. GENERAL PRINCIPLE OF THE PROPOSED KBO-PMS USING FANP AND FUZZY TOPSIS In this study, we set up a PD processes-oriented and open resource-based KBO-PMS by implementing a series of experiments on human evaluation. In these experiments, relevant perceptual data on successful product development processes are extracted through interactions with a number of decision-makers (product managers). Fuzzy ANP is applied to model the interactive framework of the decision-making problem. Under this model, different evaluation criteria and their KPIs are defined in order to evaluate alternative garment PD processes by experts and determine their corresponding weights. Also, Fuzzy TOPSIS method is used to rank all the PD processes in order to recommend the most appropriate one, which conforms to the structure of the fashion company.
C. EXPERIMENT III: PERFORMANCE ANALYSIS OF DIFFERENT PD PROCESSES FOR PERSONALIZED GARMENT DESIGN AND FUZZY TOPSIS COMPUTATION Nine personalized shirts (three garments for each process) for the same consumer were designed and produced using three alternative PD processes: Classic 2D-to-3D, Virtual 2Dto-3D and Virtual 3D-to-2D. Several experienced fashion designers, pattern makers and product managers were invited to perform this design and produce process. Experiments data were collected regarding different KPIs of the proposed system. The three sets of experiments were carried out in the same working environment (equipment and software), under the same working pressure. There was a training session about the involved PD processes, equipment and software for all involved designers, pattern makers and sewers before the experiments.
The three sets of experiment were carried out after the involved people were familiar with the required skills (PD process, equipment and software). For each set of experiment, experiments of two different categories were performed regarding quantitative or qualitative attribution in Table  3. For quantitative KPI related data, the involved designers and pattern designers performed different PD processes. Averaged values of experimental data were collected. For qualitative KPI related data, product managers gave subject evaluations, using different linguistic terms in Table  1 , based on the experiment performed by designers and pattern designers. All the raw experimental data were collected in Table  6. For raw experimental data obtained from quantitative KPIs were processed by a nondimensionalization procedure using Equation (  14 ) and  (15).
Virtual Reality technology has been applied successfully in fashion industry, including using Virtual Reality software for building virtual fashion stores, displaying fashion show in Second Life, and creating 3D fashion portfolio  [54] ,  [55]. Using Virtual Reality oriented 3D avatars (virtual humans) to help with clothes design is the new channel for the application of Virtual Reality technology in fashion industry. The virtual 3D-to-2D approach is a 3D virtual garment design method, permitting one to realize and validate design ideas and principles within a very short time  [56] ,  [57]. It speeds up the product development process and shortens the time from design and production to the market of fashion products  [58]. Using Virtual Reality technology, a collaborative PD process based on the Virtual 3D-to-2D method can be realized  [54].
When the data size increase, if this kind of linear relation tends to be more obvious, this algorithm has better scalability. To verify the scalability of the proposed KBO-PMS, a set of experiments were carried out. At the beginning of the Speedup evaluation, a data simulator is firstly developed to create a set of random raw data. The created data are developed based on Table  3 -8, which fully match the data characteristic of real data. Due to the time horizon of the system, we processed all the collected data into four synthetic datasets of different sizes (128M, 256M, 512M and 1G). For each of the synthetic datasets of different sizes, experiments were carried out using processors ranging from 1 to 8 respectively. Figure  12  presents the speedup of the proposed KBO-PMS. From Figure  12 , it can be found that, with the growth of the number of nodes, the speedup of the proposed KBO-PMS algorithm increases relative linearly.
Meanwhile, the dataset with a larger size tends to obtain a better speedup. Specifically, when the data size is 1G and the number of nodes is 8, the speedup value reaches 6. 85, which is 85. 6% (6. 85/8 = 85. 6%) of the ideal speedup. The Speedup evaluation shows that the proposed KBO-PMS has good scalability and performs better with larger datasets. It can be concluded the proposed system is applicable in the big data environment.
Study population We conducted a cross-sectional study of individuals donating blood from January 1st 2018 and December 31st 2018 to the blood bank of Gabriel Toure University teaching hospital in Bamako, Mali. We aimed to estimate HIV, HBV, HCV and syphilis infection prevalence and risk factors of blood donors during this time. The current study included all blood donations during 2018 (n = 8207) and respecting blood donation criteria: age between 18 and 60 years, body weight above 55 kg and physically healthy. Excluded from donation were individuals with known chronic diseases, high blood pressure, anemia, not transfused in the last 10 years, not hospitalized in the last 3 months, and not addicted to intravenous or oral drugs. For each blood donor, socio-demographic data including age, marital status, education level, geographical setting and type of blood donation (volunteer or parental) were collected during a predonation examination.
Socio-demographic data From 8207 blood donors, 148 were excluded due to missing HIV, HBV and HCV status; final analysis included 8059 blood donors with a median age of 30 [25-38] years, 7157 (88. 8%) men, 5500 (68. 2%) married, 6096 (75. 6%) living in Bamako, 4749 (58. 9%) reached primary school or less, and 7898 (98. 0%) parental donors. HIV, HBV and HCV prevalence HIV-seroprevalence was 2. 16% (95% CI: 1. 86-2. 50) with no significant difference between men (2. 15%) and women (2. 22%) (p = 0. 90). HIV-prevalence increased with age (p = 0. 06), from 1. 86% in the youngest category (18-30 years old) to 3. 40% in the oldest (> 50 years old). HIV-prevalence also varied by marital status, with a significantly higher prevalence for those who were married (2. 42%) compared to single (1. 54%) (p = 0.
Data and Measures First, we used the Chinese dataset of the fourth round of the Asian Barometer Survey (ABS) (Data analyzed in this article were collected by the Asian Barometer Project (2013-2016), which was codirected by Professors Fu Hu and Yun-han Chu. The Asian Barometer Project Office (www. asianbarometer. org) is solely responsible for the data distribution. The authors appreciate the assistance in providing data by the institutes and individuals aforementioned. The views expressed herein are the authors' own. ) through July 2015 to March 2016 (The ABS survey in mainland China was conducted by 12 universities. After interviewer training, the field interviewing was launched in full scale on July 1, 2014. There must be at least five more call-backs before declaring the particular respondent as nonresponse.
The quality of data was strictly controlled through three rounds of review. Entry of raw data was performed by specialists, beginning on December of 2015, and data cleansing began on March 15, 2016. The final database and coding manual were completed on 20 June2016. ). In the selection of samples, 125 primary sampling units (PSU) in total were drawn across the whole nation as the Census Yearbook from the National Statistics Bureau served as the primary source. The respondents were randomly selected by a representative sampling method of probability proportional to size (PPS) and only residents aged 18 and above who have resided in the surveyed community for no less than one month were recruited. A total of 7500 samples were drawn in the field; among them, 6013 were eligible, and the response rate was 67.
65%. In mainland China, 4068 valid samples of respondents were obtained. The reliability and validity have been tested. Second, considering the respondents' perceptions were based on previous situations, especially the most recent year i. e. , 2014, and taking the time lag of governmental resources (fiscal expenditures) into account, the data for the province level were from the 2015 China Statistical Yearbook and final accounts of fiscal expenditures of general public services in the provinces in 2015. The yearbook is annually published by the National Bureau of Statistics of China and is a collection of statistics comprehensively reflecting the economic and social development of China. Data in the 2015 China Statistical Yearbook comprise a series of indicators from 2014, covering the nation and its provinces, autonomous regions, and municipalities.
Empirical Analysis and Results Our dataset includes 4068 respondents from 26 provinces on the resident level who are clustered within provinces; individuals within the same province are correlated with each other. If we apply the traditional regression model, the underlying assumption of OLS will be violated. Thus, we analyze the influencing factors by using HLM (Hierarchical Linear Model). With regards to HLM, it is a tool for appropriately analyzing such clustered data  [53]  and can obtain statistically efficient and unbiased regression result estimates  [54]. In our case, we observed significant provincial differences in satisfaction from Table  3 , and there could be effects from provincial variables. Hence, our study applied HLM analysis to study public food safety satisfaction. We began the analysis by observing that there was a significant difference between the individual and the individual's group (i.
This is a more ambitious, long-term approach where Janssen is simultaneously interacting with a variety of partners in shaping and reinvigorating the environment into an open regional innovation ecosystem. The primary data collection method was through in-depth, semi-structured, open-ended interviews in 2017, conducted face to face with five key informants who manage innovation at Janssen. We used the semi-structured approach to make the interviews rather conversation-like to let the interviewees and interviewer discuss the phenomenon in depth and answer additional follow-up probing questions. One of the interviewees was Director of Open Innovation and Networking who was responsible for transforming the Beerse campus and the extensive interview with him (more than 2 h) was the backbone for the case study.
In this descriptive part of the analysis, we bring up examples of how an innovation system is organised and how it works in practice, focusing on the relationship between structure and function. Next, we further analysed the development of the innovation ecosystem at Janssen by searching for generic conceptual items and categorising our data into themes through an open coding procedure. Further, we reflected on the list of emerging themes using three literature streams to explore the connection between the Janssen's practice and the theory. The results of this exercise are presented in Table  1 , which enumerates the elements of the three literature streams about open innovation, innovation ecosystems and regional economics that we found in Janssen's strategy. In the last step, we aggregated the themes to identify key elements of a framework for understanding and analysing the regional innovation ecosystems.
These disciplines provided knowledge and applied skills in database management, computer programming, and statistical techniques in response to the giant strides being made in Genomics and Proteomics research d both important specialities in pharmaceutical research. This strategic complementarity between companies and universities facilitated cooperation between industrial and academic partners (both of which stood to benefit from the external funding available in the region). In this case, the company has been capitalising on generic links and relationships with local universities as suppliers of talent and research services. Janssen Pharmaceuticals played a strategic role by acting as an industrial partner, encouraging academia to deepen and expand knowledge in Bioinformatics and to create a new technology niche that met the company's business needs.