Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Virology
Title: Dynamics of Antibodies to Ebolaviruses in an Eidolon helvum Bat Colony in
Abstract: The ecology of ebolaviruses is still poorly understood and the role of bats in outbreaks needs to be further clarified. Straw-colored fruit bats (Eidolon helvum) are the most common fruit bats in Africa and antibodies to ebolaviruses have been documented in this species. Between December 2018 and November 2019, samples were collected at approximately monthly intervals in roosting and feeding sites from 820 bats from an Eidolon helvum colony. Dried blood spots (DBS) were tested for antibodies to Zaire, Sudan, and Bundibugyo ebolaviruses. The proportion of samples reactive with GP antigens increased significantly with age from 0–9/220 (0–4.1%) in juveniles to 26–158/225 (11.6–70.2%) in immature adults and 10–225/372 (2.7–60.5%) in adult bats. Antibody responses were lower in lactating females. Viral RNA was not detected in 456 swab samples collected from 152 juvenile and 214 immature adult bats. Overall, our study shows that antibody levels increase in young bats suggesting that seroconversion to Ebola or related viruses occurs in older juvenile and immature adult bats. Multiple year monitoring would be needed to confirm this trend. Knowledge of the periods of the year with the highest risk of Ebolavirus circulation can guide the implementation of strategies to mitigate spill-over events.
Extracted statement — has date : between December 2018
Research field: Virology
Title: Full-genome sequences of the first two SARS-CoV-2 viruses from India
Abstract: Background & objectives: Since December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has globally affected 195 countries. In India, suspected cases were screened for SARS-CoV-2 as per the advisory of the Ministry of Health and Family Welfare. The objective of this study was to characterize SARS-CoV-2 sequences from three identified positive cases as on February 29, 2020. Methods: Throat swab/nasal swab specimens for a total of 881 suspected cases were screened by E gene and confirmed by RdRp (1), RdRp (2) and N gene real-time reverse transcription-polymerase chain reactions and next-generation sequencing. Phylogenetic analysis, molecular characterization and prediction of B- and T-cell epitopes for Indian SARS-CoV-2 sequences were undertaken. Results: Three cases with a travel history from Wuhan, China, were confirmed positive for SARS-CoV-2. Almost complete (29,851 nucleotides) genomes of case 1, case 3 and a fragmented genome for case 2 were obtained. The sequences of Indian SARS-CoV-2 though not identical showed high (~99.98%) identity with Wuhan seafood market pneumonia virus (accession number: NC 045512). Phylogenetic analysis showed that the Indian sequences belonged to different clusters. Predicted linear B-cell epitopes were found to be concentrated in the S1 domain of spike protein, and a conformational epitope was identified in the receptor-binding domain. The predicted T-cell epitopes showed broad human leucocyte antigen allele coverage of A and B supertypes predominant in the Indian population. Interpretation & conclusions: The two SARS-CoV-2 sequences obtained from India represent two different introductions into the country. The genetic heterogeneity is as noted globally. The identified B- and T-cell epitopes may be considered suitable for future experiments towards the design of vaccines and diagnostics. Continuous monitoring and analysis of the sequences of new cases from India and the other affected countries would be vital to understand the genetic evolution and rates of substitution of the SARS-CoV-2.
Extracted statement — patient characteristics: case 1
Research field: Virology
Title: Full-genome sequences of the first two SARS-CoV-2 viruses from India
Abstract: Background & objectives: Since December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has globally affected 195 countries. In India, suspected cases were screened for SARS-CoV-2 as per the advisory of the Ministry of Health and Family Welfare. The objective of this study was to characterize SARS-CoV-2 sequences from three identified positive cases as on February 29, 2020. Methods: Throat swab/nasal swab specimens for a total of 881 suspected cases were screened by E gene and confirmed by RdRp (1), RdRp (2) and N gene real-time reverse transcription-polymerase chain reactions and next-generation sequencing. Phylogenetic analysis, molecular characterization and prediction of B- and T-cell epitopes for Indian SARS-CoV-2 sequences were undertaken. Results: Three cases with a travel history from Wuhan, China, were confirmed positive for SARS-CoV-2. Almost complete (29,851 nucleotides) genomes of case 1, case 3 and a fragmented genome for case 2 were obtained. The sequences of Indian SARS-CoV-2 though not identical showed high (~99.98%) identity with Wuhan seafood market pneumonia virus (accession number: NC 045512). Phylogenetic analysis showed that the Indian sequences belonged to different clusters. Predicted linear B-cell epitopes were found to be concentrated in the S1 domain of spike protein, and a conformational epitope was identified in the receptor-binding domain. The predicted T-cell epitopes showed broad human leucocyte antigen allele coverage of A and B supertypes predominant in the Indian population. Interpretation & conclusions: The two SARS-CoV-2 sequences obtained from India represent two different introductions into the country. The genetic heterogeneity is as noted globally. The identified B- and T-cell epitopes may be considered suitable for future experiments towards the design of vaccines and diagnostics. Continuous monitoring and analysis of the sequences of new cases from India and the other affected countries would be vital to understand the genetic evolution and rates of substitution of the SARS-CoV-2.
Extracted statement — patient characteristics: case 2
Research field: Virology
Title: Full-genome sequences of the first two SARS-CoV-2 viruses from India
Abstract: Background & objectives: Since December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has globally affected 195 countries. In India, suspected cases were screened for SARS-CoV-2 as per the advisory of the Ministry of Health and Family Welfare. The objective of this study was to characterize SARS-CoV-2 sequences from three identified positive cases as on February 29, 2020. Methods: Throat swab/nasal swab specimens for a total of 881 suspected cases were screened by E gene and confirmed by RdRp (1), RdRp (2) and N gene real-time reverse transcription-polymerase chain reactions and next-generation sequencing. Phylogenetic analysis, molecular characterization and prediction of B- and T-cell epitopes for Indian SARS-CoV-2 sequences were undertaken. Results: Three cases with a travel history from Wuhan, China, were confirmed positive for SARS-CoV-2. Almost complete (29,851 nucleotides) genomes of case 1, case 3 and a fragmented genome for case 2 were obtained. The sequences of Indian SARS-CoV-2 though not identical showed high (~99.98%) identity with Wuhan seafood market pneumonia virus (accession number: NC 045512). Phylogenetic analysis showed that the Indian sequences belonged to different clusters. Predicted linear B-cell epitopes were found to be concentrated in the S1 domain of spike protein, and a conformational epitope was identified in the receptor-binding domain. The predicted T-cell epitopes showed broad human leucocyte antigen allele coverage of A and B supertypes predominant in the Indian population. Interpretation & conclusions: The two SARS-CoV-2 sequences obtained from India represent two different introductions into the country. The genetic heterogeneity is as noted globally. The identified B- and T-cell epitopes may be considered suitable for future experiments towards the design of vaccines and diagnostics. Continuous monitoring and analysis of the sequences of new cases from India and the other affected countries would be vital to understand the genetic evolution and rates of substitution of the SARS-CoV-2.
Extracted statement — patient characteristics: case 3
Research field: Work, Economy and Organizations
Title: Mining for Computing Jobs
Abstract: A Web content mining approach identified 20 job categories and the associated skills needs prevalent in the computing professions. Using a Web content data mining application, we extracted almost a quarter million unique IT job descriptions from various job search engines and distilled each to its required skill sets. We statistically examined these, revealing 20 clusters of similar skill sets that map to specific job definitions. The results allow software engineering professionals to tune their skills portfolio to match those in demand from real computing jobs across the US to attain more lucrative salaries and more mobility in a chaotic environment.
Extracted statement — result: 20 clusters of similar skill sets that map to specific job definitions
Research field: Work, Economy and Organizations
Title: You will be…: a study of job advertisements to determine employers' requirements for LIS professionals in the UK in 2007
Abstract: Purpose – The purpose of this paper is to investigate what employers seek when recruiting library and information professionals in the UK and whether professional skills, generic skills or personal qualities are most in demand.Design/methodology/approach – A content analysis of a sample of 180 advertisements requiring a professional library or information qualification from Chartered Institute of Library and Information Professional's Library + Information Gazette over the period May 2006‐2007.Findings – The findings reveal that a multitude of skills and qualities are required in the profession. When the results were compared with Information National Training Organisation and Library and Information Management Employability Skills research, customer service, interpersonal and communication skills, and general computing skills emerged as the requirements most frequently sought by employers. Overall, requirements from the generic skills area were most important to employers, but the research also demonstra...
Extracted statement — Data: sample of 180 advertisements
Research field: Work, Economy and Organizations
Title: You will be…: a study of job advertisements to determine employers' requirements for LIS professionals in the UK in 2007
Abstract: Purpose – The purpose of this paper is to investigate what employers seek when recruiting library and information professionals in the UK and whether professional skills, generic skills or personal qualities are most in demand.Design/methodology/approach – A content analysis of a sample of 180 advertisements requiring a professional library or information qualification from Chartered Institute of Library and Information Professional's Library + Information Gazette over the period May 2006‐2007.Findings – The findings reveal that a multitude of skills and qualities are required in the profession. When the results were compared with Information National Training Organisation and Library and Information Management Employability Skills research, customer service, interpersonal and communication skills, and general computing skills emerged as the requirements most frequently sought by employers. Overall, requirements from the generic skills area were most important to employers, but the research also demonstra...
Extracted statement — Material: sample of 180 advertisements
Research field: Agricultural and Resource Economics
Title: Socio-economic Factors Affecting Adoption of Modern Information and Communication Technology by Farmers in India: Analysis Using Multivariate Probit Model
Abstract: Abstract Purpose: The paper analyzes factors that affect the likelihood of adoption of different agriculture-related information sources by farmers. Design/Methodology/Approach: The paper links the theoretical understanding of the existing multiple sources of information that farmer use, with the empirical model to analyze the factors that affect the farmer's adoption of different agriculture-related information sources. The analysis is done using a multivariate probit model and primary survey data of 1,200 farmer households of five Indo-Gangetic states of India, covering 120 villages. Findings: The results of the study highlight that farmer's age, education level and farm size influence farmer's behaviour in selecting different sources of information. The results show that farmers use multiple information sources, that may be complementary or substitutes to each other and this also implies that any single source does not satisfy all information needs of the farmer. Practical implication: If we understand the likelihood of farmer's choice of source of information then direction can be provided and policies can be developed to provide information through those sources in targeted regions with the most effective impact. Originality/Value: Information plays a key role in a farmer's life by enhancing their knowledge and strengthening their decision-making ability. Farmers use multiple sources of information as no one source is sufficient in itself.
Extracted statement — Country of study: India
Research field: Agricultural and Resource Economics
Title: Farm Households' Simultaneous Use of Sources to Access Information on Cotton Crop Production
Abstract: ABSTRACT This study has investigated farm households' simultaneous use of social networks, field extension, traditional media, and modern information and communication technologies (ICTs) to access information on cotton crop production. The study was based on a field survey, conducted in Punjab, Pakistan. Data were collected from 399 cotton farm households using the multistage sampling technique. Important combinations of information sources were found in terms of their simultaneous use to access information. The study also examined the factors influencing the use of various available information sources. A multivariate probit model was used considering the correlation among the use of social networks, field extension, traditional media, and modern ICTs. The findings indicated the importance of different socioeconomic and institutional factors affecting farm households' use of available information sources on cotton production. Important policy conclusions are drawn based on findings.
Extracted statement — Country of study: Pakistan
Research field: Anatomy
Title: Epigenetic Hallmarks of Fetal Early Atherosclerotic Lesions in Humans
Abstract: Importance Although increasingly strong evidence suggests a role of maternal total cholesterol and low-density lipoprotein cholesterol (LDLC) levels during pregnancy as a risk factor for atherosclerotic disease in the offspring, the underlying mechanisms need to be clarified for future clinical applications. Objective To test whether epigenetic signatures characterize early fetal atherogenesis associated with maternal hypercholesterolemia and to provide a quantitative estimate of the contribution of maternal cholesterol level to fetal lesion size. Design, Setting, and Participants This autopsy study analyzed 78 human fetal aorta autopsy samples from the Division of Human Pathology, Department of Advanced Biomedical Sciences, Federico II University of Naples, Naples, Italy. Maternal levels of total cholesterol, LDLC, high-density lipoprotein cholesterol (HDLC), triglycerides, and glucose and body mass index (BMI) were determined during hospitalization owing to spontaneous fetal death. Data were collected and immediately processed and analyzed to prevent degradation from January 1, 2011, through November 30, 2016. Main Outcomes and Measurements Results of DNA methylation and messenger RNA levels of the following genes involved in cholesterol metabolism were assessed: superoxide dismutase 2 (SOD2), low-density lipoprotein receptor (LDLR), sterol regulatory element binding protein 2 (SREBP2), liver X receptor &agr; (LXR&agr;), and adenosine triphosphate–binding cassette transporter 1 (ABCA1). Results Among the 78 fetal samples included in the analysis (59% male; mean [SD] fetal age, 25 [3] weeks), maternal cholesterol level explained a significant proportion of the fetal aortic lesion variance in multivariate analysis (61%; P = .001) independently by the effect of levels of HDLC, triglycerides, and glucose and BMI. Moreover, maternal total cholesterol and LDLC levels were positively associated with methylation of SREBP2 in fetal aortas (Pearson correlation, 0.488 and 0.503, respectively), whereas in univariate analysis, they were inversely correlated with SREBP2 messenger RNA levels in fetal aortas (Pearson correlation, −0.534 and −0.671, respectively). Epivariations of genes controlling cholesterol metabolism in cholesterol-treated human aortic endothelial cells were also observed. Conclusions and Relevance The present study provides a stringent quantitative estimate of the magnitude of the association of maternal cholesterol levels during pregnancy with fetal aortic lesions and reveals the epigenetic response of fetal aortic SREBP2 to maternal cholesterol level. The role of maternal cholesterol level during pregnancy and epigenetic signature in offspring in cardiovascular primary prevention warrants further long-term causal relationship studies.
Extracted statement — Study location: Italy
Research field: Artificial Intelligence
Title: Personalized recommendations in e-participation: offline experiments for the 'Decide Madrid' platform
Abstract: In e-participation platforms, citizens suggest, discuss and vote online for initiatives aimed to address a wide range of issues and problems in a city, such as economic development, public safety, budges, infrastructure, housing, environment, social rights, and health care. For a particular citizen, the number of proposals and debates may be overwhelming, and recommender systems could help filtering and ranking those that are more relevant. Focusing on a particular case, the `Decide Madrid' platform, in this paper we empirically investigate which sources of user preferences and recommendation approaches could be more effective, in terms of several aspects, namely precision, coverage and diversity.
Extracted statement — has been evaluated in the City: Madrid
Research field: Artificial Intelligence
Title: What's going on in my city?: recommender systems and electronic participatory budgeting
Abstract: In this paper, we present electronic participatory budgeting (ePB) as a novel application domain for recommender systems. On public data from the ePB platforms of three major US cities - Cambridge, Miami and New York City-, we evaluate various methods that exploit heterogeneous sources and models of user preferences to provide personalized recommendations of citizen proposals. We show that depending on characteristics of the cities and their participatory processes, particular methods are more effective than others for each city. This result, together with open issues identified in the paper, call for further research in the area.
Extracted statement — has been evaluated in the City: Miami
Research field: Artificial Intelligence
Title: Food Recognition: A New Dataset, Experiments, and Results
Abstract: We propose a new dataset for the evaluation of food recognition algorithms that can be used in dietary monitoring applications. Each image depicts a real canteen tray with dishes and foods arranged in different ways. Each tray contains multiple instances of food classes. The dataset contains 1027 canteen trays for a total of 3616 food instances belonging to 73 food classes. The food on the tray images has been manually segmented using carefully drawn polygonal boundaries. We have benchmarked the dataset by designing an automatic tray analysis pipeline that takes a tray image as input, finds the regions of interest, and predicts for each region the corresponding food class. We have experimented with three different classification strategies using also several visual descriptors. We achieve about 79% of food and tray recognition accuracy using convolutional-neural-networks-based features. The dataset, as well as the benchmark framework, are available to the research community.
Extracted statement — type: Multi
Research field: Artificial Intelligence
Title: Real-Time Mobile Food Recognition System
Abstract: We propose a mobile food recognition system the poses of which are estimating calorie and nutritious of foods and recording a user's eating habits. Since all the processes on image recognition performed on a smart-phone, the system does not need to send images to a server and runs on an ordinary smartphone in a real-time way. To recognize food items, a user draws bounding boxes by touching the screen first, and then the system starts food item recognition within the indicated bounding boxes. To recognize them more accurately, we segment each food item region by GrubCut, extract a color histogram and SURF-based bag-of-features, and finally classify it into one of the fifty food categories with linear SVM and fast 2 kernel. In addition, the system estimates the direction of food regions where the higher SVM output score is expected to be obtained, show it as an arrow on the screen in order to ask a user to move a smartphone camera. This recognition process is performed repeatedly about once a second. We implemented this system as an Android smartphone application so as to use multiple CPU cores effectively for real-time recognition. In the experiments, we have achieved the 81.55% classification rate for the top 5 category candidates when the ground-truth bounding boxes are given. In addition, we obtained positive evaluation by user study compared to the food recording system without object recognition.
Extracted statement — type: Multi
Research field: Artificial Intelligence
Title: The design and implementation of the redland RDF application framework
Abstract: Resource Description Framework (RDF) is a general description technology that can be applied to many application domains. Redland is a exible and eAEcient implementation of RDF that complements this power and provides highlevel interfaces allowing instances of the model to be stored, queried and manipulated in C, Perl, Python, Tcl and other languages. Redland is implemented using an object-based API, providing several of the implementation classes as modules which can be added, removed or replaced to allow di erent functionality or application-speci c optimisations. The framework provides the core technology for developing new RDF applications, experimenting with implementation techniques, APIs and representation issues.
Extracted statement — Engine: Redland
Research field: Bioinformatics
Title: An Affect Prediction Approach Through Depression Severity Parameter Incorporation in Neural Networks
Abstract: Humans use emotional expressions to communicate their internal affective states. These behavioral expressions are often multi-modal (e.g. facial expression, voice and gestures) and researchers have proposed several schemes to predict the latent affective states based on these expressions. The relationship between the latent affective states and their expression is hypothesized to be affected by several factors; depression disorder being one of them. Despite a wide interest in affect prediction, and several studies linking the effect of depression on affective expressions, only a limited number of affect prediction models account for the depression severity. In this work, we present a novel scheme that incorporates depression severity as a parameter in Deep Neural Networks (DNNs). In order to predict affective dimensions for an individual at hand, our scheme alters the DNN activation function based on the subject’s depression severity. We perform experiments on affect prediction in two different sessions of the Audio-Visual Depressive language Corpus, which involves patients with varying degree of depression. Our results show improvements in arousal and valence prediction on both the sessions using the proposed DNN modeling. We also present analysis of the impact of such an alteration in DNNs during training and testing.
Extracted statement — Outcome assessment: Valence