Embiotishu Project Survey Data and System Data
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ABSTRACT:
ORGANISM(S): Homo sapiens (human)
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PROVIDER: S-BSST980 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:Crystallographic fragment screening (CFS) has become one of the major techniques for screening compounds in the early stages of drug-discovery projects. Following the advances in automation and throughput at modern macromolecular crystallography beamlines, the bottleneck for CFS has shifted from collecting data to organizing and handling the analysis of such projects. The complexity that emerges from the use of multiple methods for processing and refinement and to search for ligands requires an equally sophisticated solution to summarize the output, allowing researchers to focus on the scientific questions instead of on software technicalities. FragMAXapp is the fragment-screening project-management tool designed to handle CFS projects at MAX IV Laboratory. It benefits from the powerful computing infrastructure of large-scale facilities and, as a web application, it is accessible from everywhere.
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Project description:This Data in Brief article provides supplementary information about how we explored aid effectiveness of Taiwanese government's horticulture project in the Marshall Islands. The issue of sustainable development in small island developing countries has become increasingly important [1], [2], [3]. Moreover, Non-communicable diseases (NCDs) have become more serious in the Pacific Islands in recent years, adversely affecting people's health. The data will also benefit those interested in understanding the eating habits in the Pacific Islands. We selected and assigned participants (using household as a unit) of the project to the experimental group and non-participants to the control group to evaluate the impact of the horticulture project. As for data collection in the field, we collected data through a structured questionnaire. We recruited one interviewer to conduct household surveys in the field for 40 days from April to June in 2017. A total of 96 valid questionnaires were collected, including 36 participants and 60 non-participants. The average household consumption of vegetables and fruits is 6.18 units (SD=7.84). Comparing project participants with non-participants, consumption of vegetables and fruits of the participants is 1.96 units higher than non-participants (P = 0.062).
| S-EPMC8131889 | biostudies-literature
Project description:This data article presents an expert system and econometric entropy-based informatics model for residential building project for cost judgment and decisions in residential building project. The data was obtained using purposive sampling technique to select projects completed between 2009 and 2011in Lagos state Nigeria, the project were examined for their cost centres. Also, As-built cost of one thousand(1000) samples of trained As-built cost of residential building projects trained with Neural network with Levenberg Marqua after being adjusted and modified with econometric factors like inflation index, cost entropy and entropy factor to stabilized the data and were used to form and train neural network used. Probability technique was used to generate risk impact matrix and influence of entropy on the cost centres. A parametric model similar to hedonic models was generated using the utility parameters within the early and late elemental dichotomy. The model was validated through comparative analysis of the econometric loading attributes using Monte Carlo technique of SPSS software extracting the contingency coefficient. The data of the model can provide solution to the problems of knowing the cost implication of a future project and also enable a builder or contactor load cost implication of an unseen circumstance even on occasion of deferred cost reimbursement.
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Project description:BackgroundThe small sample sizes available within many very preterm (VPT) longitudinal birth cohort studies mean that it is often necessary to combine and harmonise data from individual studies to increase statistical power, especially for studying rare outcomes. Curating and mapping data is a vital first step in the process of data harmonisation. To facilitate data mapping and harmonisation across VPT birth cohort studies, we developed a custom classification system as part of the Research on European Children and Adults born Preterm (RECAP Preterm) project in order to increase the scope and generalisability of research and the evaluation of outcomes across the lifespan for individuals born VPT.MethodsThe multidisciplinary consortium of expert clinicians and researchers who made up the RECAP Preterm project participated in a four-phase consultation process via email questionnaire to develop a topic-specific classification system. Descriptive analyses were calculated after each questionnaire round to provide pre- and post- ratings to assess levels of agreement with the classification system as it developed. Amendments and refinements were made to the classification system after each round.ResultsExpert input from 23 clinicians and researchers from the RECAP Preterm project aided development of the classification system's topic content, refining it from 10 modules, 48 themes and 197 domains to 14 modules, 93 themes and 345 domains. Supplementary classifications for target, source, mode and instrument were also developed to capture additional variable-level information. Over 22,000 individual data variables relating to VPT birth outcomes have been mapped to the classification system to date to facilitate data harmonisation. This will continue to increase as retrospective data items are mapped and harmonised variables are created.ConclusionsThis bespoke preterm birth classification system is a fundamental component of the RECAP Preterm project's web-based interactive platform. It is freely available for use worldwide by those interested in research into the long term impact of VPT birth. It can also be used to inform the development of future cohort studies.
| S-EPMC8742427 | biostudies-literature
Project description:This data article contains a description of a dataset collected by a survey on a traditional communal water irrigation system. This is the Muang fai, a 700-years old communal irrigation system in Northern Thailand. The Muang fai is managed through a series of regulations that are close to Ostrom's principles of effective common property resources (Ostrom, 1990). The survival of this long-standing practice, including its knowledge of the water-flow characteristics of the watershed, is under threat as new technologies, such as groundwater pumping, become increasingly accessible. The target population of the survey was the group of Longan farmers who are located within the 12 villages that are engaged in Muang fai Sop Rong in Chiang Mai Province, Northern Thailand. Information was specifically collected about irrigation practices, farmland characteristics and socio-economic variables from 570 longan (their main crop) farmer households. Roughly half of these sampled farmers practise Muang fai, the other half practise underground pumping irrigation. The irrigation information collected includes type of irrigation (surface or underground), the quantity of water used, pumping methods (if pumps are used). Farming characteristics collected include volume and value of the harvests, land size, and distance to irrigation canal. Socioeconomic characteristics included among others: farmers' income, expenditure, education, off-farm employment and Muang-fai membership. This dataset can be a source of baseline information for future research as well as help preserve the knowledge of this tradition.
| S-EPMC9421289 | biostudies-literature
Project description:ObjectiveAt present, most clinical data are exchanged between organizations within a regional system. However, people traveling abroad may need to visit a hospital, which would make international exchange of clinical data very useful.BackgroundSince 2007, a collaborative effort to achieve clinical data sharing has been carried out at Zhejiang University in China and Kyoto University and Miyazaki University in Japan; each is running a regional clinical information center. Methods An international layer system named Global Dolphin was constructed with several key services, sharing patients' health information between countries using a medical markup language (MML). The system was piloted with 39 test patients.ResultsThe three regions above have records for 966,000 unique patients, which are available through Global Dolphin. Data exchanged successfully from Japan to China for the 39 study patients include 1001 MML files and 152 images. The MML files contained 197 free text-type paragraphs that needed human translation. Discussion The pilot test in Global Dolphin demonstrates that patient information can be shared across countries through international health data exchange. To achieve cross-border sharing of clinical data, some key issues had to be addressed: establishment of a super directory service across countries; data transformation; and unique one-language translation. Privacy protection was also taken into account. The system is now ready for live use.ConclusionThe project demonstrates a means of achieving worldwide accessibility of medical data, by which the integrity and continuity of patients' health information can be maintained.
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Project description:In recent years, the linkage of survey data to health administrative data has increased. This offers new opportunities for research into the use of health services and public health. Building on the HISlink use case, the linkage of Belgian Health Interview Survey (BHIS) data and Belgian Compulsory Health Insurance (BCHI) data, this paper provides an overview of the practical implementation of linking data, the outcomes in terms of a linked dataset and of the studies conducted as well as the lessons learned and recommendations for future links.Individual BHIS 2013 and 2018 data was linked to BCHI data using the national register number. The overall linkage rate was 92.3% and 94.2% for HISlink 2013 and HISlink 2018, respectively. Linked BHIS-BCHI data were used in validation studies (e.g. self-reported breast cancer screening; chronic diseases, polypharmacy), in policy-driven research (e.g., mediation effect of health literacy in the relationship between socioeconomic status and health related outcomes, and in longitudinal study (e.g. identifying predictors of nursing home admission among older BHIS participants). The linkage of both data sources combines their strengths but does not overcome all weaknesses.The availability of a national register number was an asset for HISlink. Policy-makers and researchers must take initiatives to find a better balance between the right to privacy of respondents and society's right to evidence-based information to improve health. Researchers should be aware that the procedures necessary to implement a link may have an impact on the timeliness of their research. Although some aspects of HISlink are specific to the Belgian context, we believe that some lessons learned are useful in an international context, especially for other European Union member states that collect similar data.
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Project description:Integrative modeling methods can now enable macrosystem-level understandings of biodiversity patterns, such as range changes resulting from shifts in climate or land use, by aggregating species-level data across multiple monitoring sources. This requires ensuring that taxon interpretations match up across different sources. While encouraging checklist standardization is certainly an option, coercing programs to change species lists they have used consistently for decades is rarely successful. Here we demonstrate a novel approach for tracking equivalent names and concepts, applied to a network of 10 regional programs that use the same protocols (so-called "Pollard walks") to monitor butterflies across America north of Mexico. Our system involves, for each monitoring program, associating the taxonomic authority (in this case one of three North American butterfly fauna treatments: Pelham, 2014; North American Butterfly Association, Inc., 2016; Opler & Warren, 2003) that shares the most similar overall taxonomic interpretation to the program's working species list. This allows us to define each term on each program's list in the context of the appropriate authority's species concept and curate the term alongside its authoritative concept. We then aligned the names representing equivalent taxonomic concepts among the three authorities. These stepping stones allow us to bridge a species concept from one program's species list to the name of the equivalent in any other program, through the intermediary scaffolding of aligned authoritative taxon concepts. Using a software tool we developed to access our curation system, a user can link equivalent species concepts between data collecting agencies with no specialized knowledge of taxonomic complexities.
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Project description:Synthetic lethality is a type of genetic interaction in which two non-lethal mutations acting together result in a loss of viability. Such interactions are important for the insights they may offer into how gene functions are organized into distinct cellular processes. The datasets in this Series represent an effort to identify synthetic lethal genetic interactions in the yeast Saccharomyces cerevisiae on a genome-wide scale.
2013-02-28 | GSE14217 | GEO
Project description:This document outlines the types of data collected for the Digital Ludeme Project, an ERC-funded research project that aims to improve our understanding of the development of games throughout human history through computational analysis of the available (partial) historical data of games. This document outlines how this data is collected, formatted and stored, and how it can be accessed. It is the aim of the Digital Ludeme Project to provide a data resource of unprecedented depth and scope for the benefit of historical games researchers worldwide. Special attention is paid to the FAIR Guiding Principles for scientific data management and stewardship.
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