cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/jyp4jg3zxm.1
title: Active Insufficiency 

description: Previous studies have suggested that ankle position and hip position can influence hamstring strength, but none have considered the influence of both joint positions at the same time. The aim of the study was to investigate the effect of ankle and hip position on peak torque (PT), normalized PT (NPT), angle of PT (APT) and electromyographic (EMG) activity during isokinetic knee flexion. Thirteen physically active men performed three maximal isokinetic unilateral knee flexion repetitions at angular velocities of 60 and 180°/s on the isokinetic dynamometer. The individual EMG activity of the gastrocnemius (GL), biceps femoris (BFl) and semitendinosus (ST) muscles was detected using wireless SEMG system. Ankle and hip position had a significant impact on the PT and NPT (p < .05). Specifically, the highest PT and NPT were produced in the dorsal-flexion sitting position, then in the plantarflexion sitting position, followed by the dorsal-flexion in the supine position, while the lowest PT and NPT were produced in the supine position with plantarflexion for both angular velocities. Ankle and hip position and angular velocity have a significant impact on the APT: the PT occurred between 25 and 41° at 60°/s, and between 40 and 62° at 180°/s. Neither ankle nor hip position affected SEMG activity of BFl, ST and GL muscles for both angular velocities. Hip and ankle position influence the passive tension and active insufficiency, which ultimately affects hamstrings PT, but not muscle activity.
DOI: 10.17632/py4d9nz8zz.1
title: SLR Web Design for Elderly Accessibility

description: Contains the results of two Systematic Literature Reviews focused on Web Design for Elderly Accessibility. 
We proposed a SLR to identify the main problems of older adults related to web navigation and another SLR to determine the design actions to be applied to improve the accessibility of web interfaces focused on the elderly.
We identified 30 accessibility problems, 49 proposed solutions, 16 accessible design alternatives, 12 ways to evaluate the proposals and 5 adaptation models for older adults. The data obtained were classified and grouped into categories.
DOI: 10.17632/py4d9nz8zz.2
title: Web Design for Elderly Accessibility: A Systematic Literature Review 

description: Contains the results of two Systematic Literature Reviews focused on Web Design for Elderly Accessibility. 
We proposed a SLR to identify the main problems of older adults related to web navigation and another SLR to determine the design actions to be applied to improve the accessibility of web interfaces focused on the elderly.
We identified 30 accessibility problems, 49 proposed solutions, 16 accessible design alternatives, 12 ways to evaluate the proposals and 5 adaptation models for older adults. The data obtained were classified and grouped into categories.
DOI: 10.17632/rschxhwgvw.2
title: Understory species map in Connecticut US

description: We created maps of four understory classes (i.e., barberry, greenbriar, mountain laurel, and one assemblage of mixed invasive) at 10 m resolution in Connecticut’s deciduous forest in 2020. A harmonic time series model and three years of Sentinel-2 time series from 2019 to 2021 were used to classify understory species based on their unique, intra-annual phenology characteristics. The time series model coefficients captured the subtle phenology differences and created synthetic cloud-free images within a short temporal window (e.g., on the 100th and 120th day of year) in the early spring (hereafter called ‘observe window’), in which Sentinel-2 data penetrated the deciduous overstory canopy and observed the unique trajectories of different understory species due to their phenology differences. As the different conditions of leaf growth in the observe window presented distinct spatial patterns within deciduous forests, we also calculated multiple texture features (i.e., mean, second moment, and contrast from gray level co-occurrence matrix) based on the synthetic images created within the observe window. By using the spectral, temporal, and spatial features as input variables from dense Sentinel-2 data, auxiliary data (i.e., LiDAR and soil drainage layer), a random forest classifier, and a new strategy to iteratively select representative samples (namely ISRS), understory species maps were created with an overall accuracy of approximately 93%, and the user’s and producer’s accuracies varied from 39% to 99% for the three mapped understory species and one assemblage of species. The proposed method created an accurate binary map of understory presence with an overall accuracy of 95%, a producer’s accuracy of 84%, and user’s accuracy of 68%. Additionally, we separated the invasive (i.e. barberry and mixed invasive of multi-flora rose, oriental bittersweet, honeysuckle, winged euonymus, and autumn olive) and native (greenbriar and mountain laurel) species with an overall accuracy of 94%. We estimated that the invasive species cover an area of 649.33±140.59 km2, which occupies a large proportion (~53%) of the shrub understory in Connecticut’s deciduous forests. With enough accurate training data collected, this classification strategy has the potential to be applied at a much larger spatial extent than Connecticut within the Sentinel-2 era.
DOI: 10.17632/rschxhwgvw.1
title: Understory species map in Connecticut US

description: We created understory species maps (i.e., barberry, greenbriar, mixed invasive and mountain laurel) at 10 m resolution in Connecticut’s deciduous forest in 2020. Harmonic time series model and three years of Sentinel-2 time series from 2019 to 2021 were used to classify understory species based on their unique intra-annual phenology characteristics. The time series model coefficients could not only capture the subtle phenology differences, but also create synthetic cloud-free images within a short temporal window (e.g., on the 100th and 120th day of year) in the early spring (hereafter called ‘observe window’), in which Sentinel-2 data can penetrate the deciduous overstory canopy and observe the unique trajectories of different understory species due to their phenology differences. As the different conditions of leaf growth in the observe window present distinct spatial patterns within deciduous forests, we also calculated multiple texture features (i.e., mean, second moment, and contrast from gray level co-occurrence matrix) based on the synthetic images created within the observe window. By using the spectral, temporal, and spatial features as input variables from dense Sentinel-2 data, auxiliary data (i.e., LiDAR and drainage soil layer), a random forest classifier, and a new strategy to iteratively select representative samples (namely ISRS), accurate understory species maps were created with an overall accuracy of approximately 93%, and the user’s and producer’s accuracies varied from 39% to 99% for the four mapped understory species. The proposed method can also create an accurate binary map of understory with an overall accuracy of 95%, a producer’s accuracy of 84%, and user’s accuracy of 68%. Besides, we can separate the invasive and native species with an overall accuracy of 94%. We estimated that the invasive species cover an area of 741.16±173.99 km2, which occupies a large proportion (~65%) of the shrub understory in Connecticut’s deciduous forests. With enough accurate training data collected, this classification strategy has the potential to be applied at a much larger scale within the Sentinel-2 era.
DOI: 10.17632/rschxhwgvw.3
title: Understory species map in Connecticut US

description: We created maps of four understory classes (i.e., native shrubs of greenbrier and mountain laurel, and invasive shrubs of barberry and the assemblage of mixed invasive) at 10 m resolution in Connecticut’s deciduous forest in 2020. A harmonic time series model and three years of Sentinel-2 time series from 2019 to 2021 were used to classify understory species based on their unique, intra-annual phenology characteristics. The time series model coefficients captured the subtle phenology differences and created synthetic cloud-free images within a short temporal window (e.g., on the 100th and 120th day of year) in the spring prior to canopy leaf-on (hereafter called ‘observe window’), in which Sentinel-2 data penetrated the deciduous overstory canopy and observed the unique trajectories of different understory species due to their phenology differences. As the different conditions of leaf growth in the observation window presented distinct spatial patterns within deciduous forests, we also calculated multiple texture features (i.e., mean, second moment, and contrast from gray level co-occurrence matrix) based on the synthetic images created within the observation window. By using the spectral, temporal, and spatial features as input variables from dense Sentinel-2 data, auxiliary data (i.e., LiDAR and soil drainage layer), a random forest classifier, and a new strategy to iteratively select representative samples (namely ISRS), understory species maps were created with an overall accuracy of approximately 93%, and the user’s and producer’s accuracies varied from 39% to 99% for the three mapped understory species and one assemblage of species. The proposed method created an accurate binary map of understory presence with an overall accuracy of 95%, a producer’s accuracy of 84%, and user’s accuracy of 68%. Additionally, we separated the invasive (i.e. barberry and mixed invasive of multi-flora rose, oriental bittersweet, honeysuckle, winged euonymus, and autumn olive) and native (greenbrier and mountain laurel) species with an overall accuracy of 94%. We estimated that the invasive species cover an area of 649.33±140.59 km2, which occupies a large proportion (~53%) of the shrub understory in Connecticut’s deciduous forests. With enough accurate training data collected, this classification strategy has the potential to be applied at a much larger spatial extent than Connecticut within the Sentinel-2 era.
DOI: 10.17632/yrff9vxcd3.1
title: Students' reluctance to use social media for speaking activities

description: This dataset contains data coding from eight participants about their reluctance to use social media for speaking activities
DOI: 10.17632/4pntcf4sp9.1
title: Qualification of a Liquid Chromatography/Mass Spectrometry (LC/MS) Semi-quantitative Screening Method used for Analysis of Extractables and Leachables from Medical Devices, Medical Device Componentry and Other Associated Materials

description: This technical note summarizes the qualification of a LC-MS method qualification for use in general screening of extractables from medical devices.
DOI: 10.17632/4pntcf4sp9.2
title: Qualification of a Liquid Chromatography/Mass Spectrometry (LC/MS) Semi-quantitative Screening Method used for Analysis of Extractables and Leachables from Medical Devices, Medical Device Componentry and Other Associated Materials

description: This technical note summarizes the qualification of a LC-MS method qualification for use in general screening of extractables from medical devices.
DOI: 10.17632/4pntcf4sp9.3
title: Qualification of a Liquid Chromatography/Mass Spectrometry (LC/MS) Semi-quantitative Screening Method used for Analysis of Extractables and Leachables from Medical Devices, Medical Device Componentry and Other Associated Materials

description: This technical note summarizes the qualification of a LC-MS method qualification for use in general screening of extractables from medical devices.
DOI: 10.17632/495334579x.1
title: Database for the cross-sectional study: Seroprevalence and associated risk factors of Hepatitis C infection among Diabetic patients in South-Kivu, Eastern of the Democratic Republic of Congo

description: This data provide from two diabetic healthcare centers of Bukavu City in the eastern part of the DRC, from December 2020 to December 2022. A questionnaire was submitted to diabetic patients in order to collect socio-demographic data, anamnestic data on risk factors for HCV infection, and clinical data on Diabetes Mellitus. These factors were analyzed based on their anti-HCV serological results.
Microsoft Excel software was used to collect data and IBM SPPS 26 to make some analysis.
Among 180 selected patients, 19 (10.6 %) tested positive for anti-HCV antibodies. After multivariate analysis, identified factors influencing these outcomes were male sex (ORa: 3.5, P=0.027), dental extraction (Ora: 7.6, P=0.001), and living in a privileged environment (ORa: 0.29, P=0.03). Factors related to DM as the type, the disease duration, or the usual type of treatment did not influence serological results.
DOI: 10.17632/dgh97xfxvj.1
title: Complementary material

description: Tabla resumen de las referencias revisadas y las principales características de modelamiento tenidas en cuenta por cada estudio citado en este paper.
DOI: 10.17632/vg7c8dh365.1
title: HPD TF3+

description: High precision laboratory dryer HPD TF3+ for characterization of the drying behavior of food products
DOI: 10.17632/vg7c8dh365.2
title: HPD TF3+

description: High precision laboratory dryer HPD TF3+ for characterization of the drying behavior of food products
DOI: 10.17632/b2yhc95rnx.1
title: A Novel Dataset for Aspect-based Sentiment Analysis for Teacher Performance Evaluation

description: The dataset was created by collecting student feedback from American International University-Bangladesh and then labelled by undergraduate-level students into three sentiment classes: positive, negative, and neutral. The dataset was then cleaned and preprocessed to ensure data quality and consistency. The final dataset contains more than 2,000,000 student feedback instances related to teacher performance. This dataset can be used to develop and evaluate ABSA models for teacher performance evaluation.
DOI: 10.17632/f887wrzymk.1
title: LEARNING ATTITUDES OF JHS STUDENTS

description: This dataset includes the data collected to measure the learning attitudes of high school students enrolled in 42 secondary schools in Zamboanga City, Philippines, SY 2020-2021. It includes data across gender, grade level, age, and socio-economic status.
DOI: 10.17632/rkz3pvxmmn.1
title: Visibilidad de la producción científica

description: Webinar sobre visibilidad de la producción cientifica diseñado para investigadores en economia con especila foco en Banco de la República de Colombia.
DOI: 10.17632/hwmnnmmjcd.1
title: DOE MARCUS Campaign Model Simulations by E3SMv1 and EMC2

description: The two datasets in this repository contain the results of the E3SMv1 simulation and the EMC2 instrument simulator results in NetCDF format. These results were used to compare with MARCUS remote sensing observations in the Desai et al. (2023) paper entitled "Ship-based Observations and Climate Model Simulation of Cloud Phase over the Southern Ocean".

E3SMv1:
The file MARCUS.int_1min.2017-04-01-00000.nc contains the E3SMv1 results for the entire MARCUS campaign from 2017_10_30 to 2018_03_23 in one file. It also contains all the relevant variables such as CLDICE, CLDLIQ, RAINQM, SNOWQM which were used to obtain cloud ice, liq, rain and snow respectively.
The file MARCUS_flight_addOUT_HM100.cam.MARCUS_addOUT.int_1min.2017-04-01-00000 contains the same E3Smv1 simulation but with the Hallett Mossop term increased by 100 times.

EMC2:
The EMC2_micro.zip folder contains the simulator results for each day of the campaign from 2017_10_30 to 2018_03_23. Each file contains variables such as phase_mask_HSRL_all_hyd and phase_mask_WACR_sounding_all_hyd which were used to obtain lidar and radar phase respectively from the simulator results for each day.
DOI: 10.5281/zenodo.7872741
title: OpenMM simulations of DPPC using the CHARMM Drude2023 force field

description: The dataset contains a PSF, a formatted coordinate file (CRD), and DCD files with the final 200 ns from<br> each of 3 replicate simulations from the paper <br> <strong>Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion:<br> Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids</strong><br> Yalun Yu, Richard M. Venable, Jonathan Thirman, Payal Chatterjee, Anmol Kumar, Richard W. Pastor,*<br> Benoît Roux,* Alexander D. MacKerell, Jr.,* and Jeffery B. Klauda*<br> https://doi.org/10.1021/acs.jctc.3c00203 <br> DCD file names indicate the lipid, replica number, and the time point of the final coordinate set in the file; each file has frames spaced at 10 ps over a 50 ns interval.
description: The data files contain additional atom types for the Drude particles and oxygen lone pairs
DOI: 10.5281/zenodo.7872740
title: OpenMM simulations of DPPC using the CHARMM Drude2023 force field

description: The dataset contains a PSF, a formatted coordinate file (CRD), and DCD files with the final 200 ns from<br> each of 3 replicate simulations from the paper <br> <strong>Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion:<br> Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids</strong><br> Yalun Yu, Richard M. Venable, Jonathan Thirman, Payal Chatterjee, Anmol Kumar, Richard W. Pastor,*<br> Benoît Roux,* Alexander D. MacKerell, Jr.,* and Jeffery B. Klauda*<br> https://doi.org/10.1021/acs.jctc.3c00203 <br> DCD file names indicate the lipid, replica number, and the time point of the final coordinate set in the file; each file has frames spaced at 10 ps over a 50 ns interval.
description: The data files contain additional atom types for the Drude particles and oxygen lone pairs
DOI: 10.17632/hgdv28fzvh.2
title: ASSESSMENT OF STAKEHOLDER PERCEPTIONS OF OCEAN HAZARD RISK FOR COASTAL INFRASTRUCTURE/ROADWAYS, MAUI COUNTY, HAWAI‘I

description: *Specific use of any data requires authorization from the authors.

Coastal roads in Maui County are at-risk of sea level rise and coastal hazards. These roads are often the only way people travel, so the inundation and deterioration of coastal roads increases communities’ vulnerability and negatively impacts the everyday life of residents. Recognizing the urgency of this issue, Maui County and HDOT asked the Department of Civil and Environmental Engineering Coastal Hydraulics Engineering Resilience lab at University of Hawai‘i at Mānoa to help adapt coastal county roads for future coastal hazard scenarios. 

To inform this project’s engineering design, a stakeholder assessment was conducted to ensure the most sustainable and culturally-sensitive development option is recommended. The assessment also helps Maui and the State of Hawaii Department of Transportation (HDOT) identify stakeholder needs. In addition to semi-structured interviews, a questionnaire ranking all possible coastal adaptation options was given. This project is focused on the islands of Maui and Molokai. Lāna‘i is not included, as the island does not have any coastal county roads. 

During the summer of 2021, a total of 112 subjects were interviewed and 102 stakeholders responded to the survey. This dataset contains the results from the study, along with information on stakeholder and respondent characteristics and represented areas. Results of the stakeholder assessment contain 1) stakeholder preferences of coastal road adaptation options, 2) areas and roads of stakeholder concern, 3) stakeholder desires surrounding coastal issues, 4) tools and information needed for stakeholders to prepare for coastal disasters and road disruptions, 5) identified barriers and limitations to adaptation, 6) information on current and upcoming stakeholder and government actions to increase resilience, and 7) information on government-resident experiences. 

Disclaimer: The results from the oral interviews were obtained through a series of extensive open-ended questions; meaning the answers depended on how the respondent chose to answer the question based on their priorities rather than being given a predetermined set of statements to agree or disagree with. Therefore, the actual number of respondents that agree with a statement may be higher if they were to be prompted with those statements than those that voluntarily indicated the response. Additionally, interview questions were customized based on stakeholder types, available time, and length of responses, meaning not all 112 subjects were asked the same questions. More information on the interview methodology can be found in the written thesis below. 

If you'd like to read the thesis associated with this dataset or learn more about the methods, here is the link: https://www.researchgate.net/publication/362196742_Assessment_of_Stakeholder_Perceptions_of_Ocean_Hazard_Risk_for_Coastal_InfrastructureRoadways_Maui_County_Hawai'i
DOI: 10.17632/hgdv28fzvh.3
title: ASSESSMENT OF STAKEHOLDER PERCEPTIONS OF OCEAN HAZARD RISK FOR COASTAL INFRASTRUCTURE/ROADWAYS, MAUI COUNTY, HAWAI‘I

description: *Specific use of any data requires authorization from the authors.

Coastal roads in Maui County are at-risk of sea level rise and coastal hazards. These roads are often the only way people travel, so the inundation and deterioration of coastal roads increases communities’ vulnerability and negatively impacts the everyday life of residents. Recognizing the urgency of this issue, Maui County and HDOT asked the Department of Civil and Environmental Engineering Coastal Hydraulics Engineering Resilience lab at University of Hawai‘i at Mānoa to help adapt coastal county roads for future coastal hazard scenarios. 

To inform this project’s engineering design, a stakeholder assessment was conducted to ensure the most sustainable and culturally-sensitive development option is recommended. The assessment also helps Maui and the State of Hawaii Department of Transportation (HDOT) identify stakeholder needs. In addition to semi-structured interviews, a questionnaire ranking all possible coastal adaptation options was given. This project is focused on the islands of Maui and Molokai. Lāna‘i is not included, as the island does not have any coastal county roads. 

During the summer of 2021, a total of 112 subjects were interviewed and 102 stakeholders responded to the survey. This dataset contains the results from the study, along with information on stakeholder and respondent characteristics and represented areas. Results of the stakeholder assessment contain 1) stakeholder preferences of coastal road adaptation options, 2) areas and roads of stakeholder concern, 3) stakeholder desires surrounding coastal issues, 4) tools and information needed for stakeholders to prepare for coastal disasters and road disruptions, 5) identified barriers and limitations to adaptation, 6) information on current and upcoming stakeholder and government actions to increase resilience, and 7) information on government-resident experiences. 

Disclaimer: The results from the oral interviews were obtained through a series of extensive open-ended questions; meaning the answers depended on how the respondent chose to answer the question based on their priorities rather than being given a predetermined set of statements to agree or disagree with. Therefore, the actual number of respondents that agree with a statement may be higher if they were to be prompted with those statements than those that voluntarily indicated the response. Additionally, interview questions were customized based on stakeholder types, available time, and length of responses, meaning not all 112 subjects were asked the same questions. More information on the interview methodology can be found in the written thesis below. 

If you'd like to read the thesis associated with this dataset or learn more about the methods, here is the link: https://www.researchgate.net/publication/362196742_Assessment_of_Stakeholder_Perceptions_of_Ocean_Hazard_Risk_for_Coastal_InfrastructureRoadways_Maui_County_Hawai'i