cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10427807
title: Knowledge of Primary Health Care Nurses at Selected Public Institutions Regarding Prescription of Antihypertensive Drugs

description: Hypertension has been among the most studied topics of the previous century and has been one of the most significant comorbidities contributing to the development of stroke, myocardial infarction, heart failure, and renal failure. In the mist of that, there is limited data on nurses’ knowledge regarding prescription of antihypertensive drugs in Lesotho. The aim of this study was to assess primary health care nurses’ knowledge regarding prescription of antihypertensive drugs. Quantitative descriptive cross-sectional study of primary health care nurses recruited by purposive sampling was conducted. An electronic questionnaire was used to collect data and data were analyzed using descriptive statistics. Most participants were females and had attained diploma in general nursing and midwifery. A proportion of 26% fully knew the steps to be followed for diagnosing hypertension and only 23% felt highly confident to initiate patients on antihypertensive drugs. Moreover, knowledge on mechanism of action of antihypertensive drugs was poor and less than half only knew antihypertensive drug of choice when there is comorbidity. The study identified that nurses have knowledge deficit regarding prescription of antihypertensive drugs. There is a need for interventions to improve nurses’ knowledge so as to curb hypertension burden.
DOI: 10.6084/m9.figshare.24899511
title: Metagenome example subsamples

description: Example dataset, six subsamples of 100 k shotgun sequences
DOI: 10.6084/m9.figshare.24899511.v2
title: Metagenome example subsamples

description: Example dataset, six subsamples of 100 k shotgun sequences
DOI: 10.6084/m9.figshare.24899511.v1
title: Metagenome example subsamples

description: Example dataset, six subsamples of 100 k shotgun sequences
DOI: 10.5517/ccdc.csd.cc2fdwwm
title: CCDC 2246721: Experimental Crystal Structure Determination

description: Related Article: Yongzhuo Xu, Boqiang Wang, Jiajia Wang, Xuan Zhou, Jiaxing Chen, Xinjia Guo, Guo-Jun Deng, Wen Shao|2023|Org.Lett.|25|8716|doi:10.1021/acs.orglett.3c03642
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2g60wl
title: CCDC 2269909: Experimental Crystal Structure Determination

description: Related Article: Yang Jiao, Zuobang Sun, Zhiheng Wang, Yubin Fu, Fan Zhang|2023|Org.Lett.|25|8766|doi:10.1021/acs.orglett.3c03800
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2g610r
title: CCDC 2269913: Experimental Crystal Structure Determination

description: Related Article: Yang Jiao, Zuobang Sun, Zhiheng Wang, Yubin Fu, Fan Zhang|2023|Org.Lett.|25|8766|doi:10.1021/acs.orglett.3c03800
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.10427810
title: Comparative Evaluation of Body Mass Index, Waist Circumference and Waist-To-Hip Ratio as Correlates of Glucose Intolerance among Rural Dwellers in Nigeria

description: This research investigates the comparative efficacy of Body Mass Index (BMI), Waist Circumference (WC), and Waist-to-Hip Ratio (WHR) as correlates of glucose intolerance among rural dwellers in Nigeria. Conducted as a descriptive cross-sectional study in Oyo State, Nigeria, the research involved adults aged 18 years and above. The study employed a multi-stage cluster sampling technique, selecting participants from rural communities. Exclusion criteria included pregnant women and those with known diabetes or medications affecting glucose metabolism. Anthro-pometric indices and blood glucose levels were determined using Hanson's weighing scale, a meter rule, and biochemical auto-analyzers. The BMI, WC, and WHR were utilized to assess obesity and abdominal adiposity. Blood glucose levels were measured for fasting and 2-hour post-prandial samples. Data analysis involved descriptive statistics and chi-square tests using SPSS version 26. Results from the study revealed demographic characteristics and medical history of participants. Findings indicated a significant association between anthropometric parameters and gender. Notably, WHR exhibited a strong correlation with glucose intolerance, emphasizing its potential as a predictor. The study also presented the correlation of BMI, WC, and WHR with blood glucose levels, categorizing participants into different risk groups based on these indices. This research contributes valuable insights into the effectiveness of BMI, WC, and WHR in predicting glucose intolerance among rural dwellers in Nigeria. The findings underscore the importance of tailored interventions for specific populations, considering regional variations in health determinants. Future research can build upon these results to develop targeted strategies for diabetes prevention and management in rural communities.
DOI: 10.5281/zenodo.10427811
title: Comparative Evaluation of Body Mass Index, Waist Circumference and Waist-To-Hip Ratio as Correlates of Glucose Intolerance among Rural Dwellers in Nigeria

description: This research investigates the comparative efficacy of Body Mass Index (BMI), Waist Circumference (WC), and Waist-to-Hip Ratio (WHR) as correlates of glucose intolerance among rural dwellers in Nigeria. Conducted as a descriptive cross-sectional study in Oyo State, Nigeria, the research involved adults aged 18 years and above. The study employed a multi-stage cluster sampling technique, selecting participants from rural communities. Exclusion criteria included pregnant women and those with known diabetes or medications affecting glucose metabolism. Anthro-pometric indices and blood glucose levels were determined using Hanson's weighing scale, a meter rule, and biochemical auto-analyzers. The BMI, WC, and WHR were utilized to assess obesity and abdominal adiposity. Blood glucose levels were measured for fasting and 2-hour post-prandial samples. Data analysis involved descriptive statistics and chi-square tests using SPSS version 26. Results from the study revealed demographic characteristics and medical history of participants. Findings indicated a significant association between anthropometric parameters and gender. Notably, WHR exhibited a strong correlation with glucose intolerance, emphasizing its potential as a predictor. The study also presented the correlation of BMI, WC, and WHR with blood glucose levels, categorizing participants into different risk groups based on these indices. This research contributes valuable insights into the effectiveness of BMI, WC, and WHR in predicting glucose intolerance among rural dwellers in Nigeria. The findings underscore the importance of tailored interventions for specific populations, considering regional variations in health determinants. Future research can build upon these results to develop targeted strategies for diabetes prevention and management in rural communities.
DOI: 10.21227/e1xm-ve27
title: Automated Analysis of Web Accessibility Across 20 MOOCs Platforms

description: In the dynamic world of digital education, particularly due to recent global events, there has been an increasing reliance on e-learning tools and platforms, including Massive Open Online Courses (MOOCs). However, not all these platforms cater to the diverse needs of learners, especially learners with disabilities. Accessibility in MOOC platforms can significantly ensure inclusivity and improve the learning experience. This study focuses on the critical aspect of accessibility in the most popular MOOC platforms. Despite the ongoing advancements in this field, MOOC platforms still present considerable accessibility challenges for users with disabilities. To bridge this gap, our research focuses on evaluating the accessibility features of 20 selected MOOC platforms. Based on the Web Content Accessibility Guidelines (WCAG) 2.1, we shed light on the areas of improvement harnessing emerging technologies towards ensuring inclusive and accessible online educational environments.
DOI: 10.6073/pasta/82d334e74866175c791e557d8c303a62
title: Canopy invertebrate responses to Hurricane Hugo

description: We study long-term responses of insects and other arthropods to various disturbances and environmental changes, as well as important roles in ecosystem processes. Five tree species in 1991, six during 1992-1995, and seven since 1997 were selected to represent early and late successional forests at El Verde. These trees were sampled in both gap and non-gap plots resulting from Hurricane Hugo.  During the past 27 years, these plots have been subjected to multiple disturbances, including Hurricane Georges in 1998 and major droughts in 1994, 1997 and 2002, in addition to several minor hurricanes and droughts.  Each of these disturbances has influenced the arthropod community.  This project is ongoing.
DOI: 10.6073/pasta/ec9d524b8f13c000e8e8a225d5a23c7b
title: Long-term mid-marsh grasshopper abundance and species diversity at eight GCE-LTER sampling sites

description: Grasshopper abundance and species diversity were investigated at eight sampling sites within the Georgia Coastal Ecosystems (GCE) LTER study area during July or August from 2000 to 2016. Visual surveys were conducted along 8-10 2m by 10m transects randomly allocated within the mid-marsh zone at each site. All grasshoppers observed within each transect were counted and identified to species, if possible. These surveys were conducted as part of the GCE invertebrate monitoring program, and are performed annually to assess long-term changes in relative species abundances across the GCE study area.
DOI: 10.6073/pasta/c4963aa3363d18ac99bd40307db2249d
title: Small Mammal Exclosure Study (SMES) Ant Data from Chihuahuan Desert Grassland and Shrubland at the Sevilleta National Wildlife Refuge, New Mexico (1995-2005)

description: Animal consumers have important roles in ecosystems, determining plant species composition and structure, regulating rates of plant production and nutrients, and altering soil structure and chemistry. This is data for numbers and species of seed harvester ant nests mapped from each of the SMES study plots. Seed harvester ant nests were mapped on each of the study plots once each year in the autumn. Ant nest maps were drawn on to pre-designed plot diagrams. Each nest was located on the diagram in reference to one of the 36 vegetation quadrat marker posts. The distance from the post, direction from the post, and species name were plotted on the map diagram. Data such as total numbers of nests of each ant species, and spatial arrangement of nests, were then taken from the diagram maps. The following question was asked: Do small mammals interact with other herbivore and granivore consumers enough to affect the species composition and abundances of other consumers such as ants?
DOI: 10.6073/pasta/74d30fdbb17e0f76b54548ce74bf27e4
title: Long-term monitoring of ground-dwelling arthropods in central Arizona–Phoenix, ongoing since 1998

description: The Central Arizona–Phoenix Long-Term Ecological Research (CAP LTER)
 program has been monitoring ground-dwelling arthropods (e.g., insects,
 ararchnids) at locations throughout the greater Phoenix metropolitan
 area (GPMA) and surrounding Sonoran desert region since 1998.
 Monitoring locations span a diversity of habitat types, including
 mesic and xeric residential yards, commercial areas, agricultural
 fields, desert locations within the GPMA (desert remnant), and
 undisturbed desert locations. Organisms are collected quarterly using
 unbaited pitfall traps, typically ten per location but with some
 variation, exposed for approximately seventy-two hours. Organisms are
 identified to the lowest practical taxonomic level and enumerated.
 Many of the sampling locations established at the beginning of the
 monitoring project were relocated in 2001-2002 to overlap with the CAP
 LTER's Ecological Survey of Central Arizona (ESCA; formerly named
 Survey200) long-term monitoring sites, although within the same
 general landscape categories.
DOI: 10.6084/m9.figshare.22587018
title: Pay Attention to the Ignorable Missing Data Mechanisms! An Exploration of Their Impact on the Efficiency of Regression Coefficients

description: The use of modern missing data techniques has become more prevalent with their increasing accessibility in statistical software. These techniques focus on handling data that are <i>missing at random</i> (MAR). Although all MAR mechanisms are routinely treated as the same, they are not equal. The impact of missing data on the efficiency of parameter estimates can differ for different MAR variations, even when the amount of missing data is held constant; yet, in current practice, only the rate of missing data is reported. The impact of MAR on the loss of efficiency can instead be more directly measured by the <i>fraction of missing information</i> (FMI). In this article, we explore this impact using FMIs in regression models with one and two predictors. With the help of a <i>Shiny</i> application, we demonstrate that efficiency loss due to missing data can be highly complex and is not always intuitive. We recommend substantive researchers who work with missing data report estimates of FMIs in addition to the rate of missingness. We also encourage methodologists to examine FMIs when designing simulation studies with missing data, and to explore the behavior of efficiency loss under MAR using FMIs in more complex models.
DOI: 10.6084/m9.figshare.22760113
title: Unique Variable Analysis: A Network Psychometrics Method to Detect Local Dependence

description: The local independence assumption states that variables are unrelated after conditioning on a latent variable. Common problems that arise from violations of this assumption include model misspecification, biased model parameters, and inaccurate estimates of internal structure. These problems are not limited to latent variable models but also apply to network psychometrics. This paper proposes a novel network psychometric approach to detect locally dependent pairs of variables using network modeling and a graph theory measure called weighted topological overlap (wTO). Using simulation, this approach is compared to contemporary local dependence detection methods such as exploratory structural equation modeling with standardized expected parameter change and a recently developed approach using partial correlations and a resampling procedure. Different approaches to determine local dependence using statistical significance and cutoff values are also compared. Continuous, polytomous (5-point Likert scale), and dichotomous (binary) data were generated with skew across a variety of conditions. Our results indicate that cutoff values work better than significance approaches. Overall, the network psychometrics approaches using wTO with graphical least absolute shrinkage and selector operator with extended Bayesian information criterion and wTO with Bayesian Gaussian graphical model were the best performing local dependence detection methods overall.
DOI: 10.6084/m9.figshare.22760113.v1
title: Unique Variable Analysis: A Network Psychometrics Method to Detect Local Dependence

description: The local independence assumption states that variables are unrelated after conditioning on a latent variable. Common problems that arise from violations of this assumption include model misspecification, biased model parameters, and inaccurate estimates of internal structure. These problems are not limited to latent variable models but also apply to network psychometrics. This paper proposes a novel network psychometric approach to detect locally dependent pairs of variables using network modeling and a graph theory measure called weighted topological overlap (wTO). Using simulation, this approach is compared to contemporary local dependence detection methods such as exploratory structural equation modeling with standardized expected parameter change and a recently developed approach using partial correlations and a resampling procedure. Different approaches to determine local dependence using statistical significance and cutoff values are also compared. Continuous, polytomous (5-point Likert scale), and dichotomous (binary) data were generated with skew across a variety of conditions. Our results indicate that cutoff values work better than significance approaches. Overall, the network psychometrics approaches using wTO with graphical least absolute shrinkage and selector operator with extended Bayesian information criterion and wTO with Bayesian Gaussian graphical model were the best performing local dependence detection methods overall.
DOI: 10.6084/m9.figshare.22587018.v1
title: Pay Attention to the Ignorable Missing Data Mechanisms! An Exploration of Their Impact on the Efficiency of Regression Coefficients

description: The use of modern missing data techniques has become more prevalent with their increasing accessibility in statistical software. These techniques focus on handling data that are <i>missing at random</i> (MAR). Although all MAR mechanisms are routinely treated as the same, they are not equal. The impact of missing data on the efficiency of parameter estimates can differ for different MAR variations, even when the amount of missing data is held constant; yet, in current practice, only the rate of missing data is reported. The impact of MAR on the loss of efficiency can instead be more directly measured by the <i>fraction of missing information</i> (FMI). In this article, we explore this impact using FMIs in regression models with one and two predictors. With the help of a <i>Shiny</i> application, we demonstrate that efficiency loss due to missing data can be highly complex and is not always intuitive. We recommend substantive researchers who work with missing data report estimates of FMIs in addition to the rate of missingness. We also encourage methodologists to examine FMIs when designing simulation studies with missing data, and to explore the behavior of efficiency loss under MAR using FMIs in more complex models.
DOI: 10.15156/bio/sh1426376.08fu
title: SH1426376.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.25549/one-c4-33436
title: K. B., letters (1958/1963)

description: K. B., envelope; forms, letters, notes (1958/1963)
DOI: 10.15156/bio/sh1426377.08fu
title: SH1426377.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1426378.08fu
title: SH1426378.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1426379.08fu
title: SH1426379.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.