cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/69zj8vg6f2.1
title: Psychosocial Mental Health Analysis

description: In this research, we strive to delve into the intricacies of individuals' psychosocial mental health challenges by engaging directly with their narratives. By allowing participants to articulate their experiences in their own language and manner, we aim to capture the nuances and complexities of their struggles authentically.

The process of translating and shaping these descriptions into English not only facilitates analysis but also ensures accessibility and consistency in understanding across diverse audiences. Through the summarization of each description, we condense the rich and varied accounts into concise representations while preserving the essence of the participants' experiences.

Categorizing the problems into distinct categories enables us to organize and analyze the data effectively. The delineation into problem and psychological categories provides a structured framework for understanding the multifaceted nature of mental health challenges. Moreover, recording demographic information such as age and gender allows for demographic-specific analyses and insights.

By focusing on a broad spectrum of issues—from common stressors like work-related pressures to more complex interpersonal dynamics such as marital conflicts—we aim to capture the breadth and depth of psychological distress experienced by individuals. Recognizing the significance of these challenges in contemporary society, our research endeavors to contribute to the body of knowledge surrounding mental health and well-being.

Through our systematic approach to data collection, analysis, and interpretation, we seek to offer valuable insights into the prevalence, patterns, and underlying factors of psychosocial mental health issues. By amplifying the voices of those directly impacted, we hope to foster greater empathy, understanding, and support for individuals navigating these challenges.

Ultimately, our research aspires to inform evidence-based interventions, policies, and initiatives aimed at promoting mental health and enhancing the quality of life for individuals worldwide. Through collaborative efforts and interdisciplinary dialogue, we endeavor to advance the field of mental health research and social change.

Our commitment to understanding and addressing psychosocial mental health issues extends beyond mere observation. We recognize the imperative to translate our findings into actionable insights that can inform interventions, programs, and policies aimed at alleviating mental distress. By grounding our research in the lived experiences of individuals, we aim to bridge the gap between academic inquiry and real-world impact. 

In conclusion, our research endeavors to go beyond the surface level of understanding to illuminate the complexities of psychosocial mental health. By leveraging data-driven insights and fostering collaborative partnerships, we aim to drive meaningful progress towards a society where mental well-being is prioritized, supported, and safeguarded
DOI: 10.17632/7yc4c3pmtp.2
title: New Jersey's Waste and Recycling Data: 1993-2016

description: Reliable data about collection, volume, tonnage, stream composition, and disposal price have long been described as key components of successful solid waste management planning. Yet, concerns about data quality and quantity have continued to limit even the most sincere, progressive waste management schemes. The paper associated with this dataset examines solid waste management data that has been collected in the US state of New Jersey starting in the 1960s. We present the origins of waste management data collection in New Jersey and trace some of the applications that have been made with the data over time. We compare the New Jersey dataset to waste management data that has been collected in other US states. We then describe our work collecting, cleaning, and preparing for public dissemination and use in a geospatial visualization exercise a digital version of the data spanning approximately 1993 to 2016, before presenting some illustrations of the type of modeling and analysis that researchers or the concerned public would be able to undertake now that the dataset is available. We argue that the New Jersey waste management dataset is much better than most other waste datasets in the US, but despite this fairly high quality, there remain significant gaps which inhibit the ability of planners to design and implement comprehensive waste management plans. That there are limits inherent to the New Jersey dataset suggests, we argue, a ceiling to the usefulness of waste management data as a category of environmental knowledge with possible implications for ‘big’ environmental data more broadly. The dataset includes solid waste tonnage data by county and disposal facility, and recycling tonnage data by municipality, for the years 1993-2016. It also includes a brief essay explaining the types of modeling that could be undertaken using the dataset. Finally, several geospatial data files are included that will allow users to visualize some of the solid waste data using ESRI products. Portions of the project data can also be examined on a web-based platform, NJ Map, at www.njmap2.com/waste
DOI: 10.17632/p7n6ktjdx7.1
title: Agriculture_Forest_Hyperspectral_Data

description: Maintaining rich biodiversity and being a habitat and resource for humans, tropical forests are one of the most important global biomes. These forest ecosystems have been experiencing a host of unregulated anthropogenic activities including illegal tourism and shifting cultivation. The presence of human-habitats in the restricted zones of forest ecosystems is a direct indicator of the human activities that may drive the future deterioration of forest quality by area and tree species composition. Remote sensing data have been extensively for mapping forest types, and biophysical characterization at various spatial scales. Several remote sensing datasets from multispectral, hyperspectral and LIDAR sensors acquired from airborne and satellite platforms are available for developing and validating a host of methodologies for remote sensing application in forestry. However, quantifying the quality of forest stands and detecting potential threats from the sporadic and small-scale human activities requires sub-pixel level remote sensing data analysis methods such as spectral mixture modelling. Generally, most of the studies employ pixel-level supervised learning-based analysis techniques to detect infrastructure and settlements. However, if the settlements are smaller than the ground sampling distance and are under the canopy, pixel-based techniques are not suitable. Reinvigorated with progressive availability of hyperspectral imagery, spectral mixture modelling based sub-pixel image analysis is gaining prominence in the contemporary remote sensing application development. However, there is a paucity of high-resolution hyperspectral imagery and associated ground truth spectral measurements for assessing various methodological approaches on studies related to anthropogenic activities and forest disturbance. Most of the studies have relied upon simulating and synthesising the hyperspectral imagery and its associated ground truth spectra for implementation of methods and algorithms. This article presents a distinct dataset of high-resolution hyperspectral imagery and associated ground truth spectra of various vegetable crops acquired over a tropical forest ecosystem. The dataset is valuable for research on developing new discrimination models of forest and cultivated vegetation, classification methods, spectral matching analysis techniques and sub-pixel target detection methods.
DOI: 10.17632/vb2m5x5xhr.3
title: Survey Dataset on Face to Face Students' intention to use Social Media and Emerging Technologies for Continuous Learning

description: One of the sectors that felt the impact of the Corona Virus Disease 2019 (COVID-19) pandemic was the educational sector. The outbreak led to the immediate closure of schools at all levels thereby sending billions of students away from their various institutions of learning. However, the shut down of academic institutions was not a total one as some institutions that were solely running online programmes were not affected. Those who were running face to face and online modes quickly switched over to the online mode. Unfortunately, institutions that have not fully embraced online mode of study were greatly affected. 85% of academic institutions in Nigeria are operating face to face mode of study, therefore, majority of Nigerian students at all levels were affected by the COVID-19 lockdown. Social media platforms and emerging technologies were the major backbones of institutions that are running online mode of study, therefore, this survey uses the unified theory of acceptance and use of technology (UTAUT) model to capture selected Face to face Nigerian University students accessibility, usage, intention and willingness to use these social media platforms and emerging technologies for learning. The challenges that could mar the usage of these technologies were also revealed. Eight hundred and fifty undergraduate students participated in the survey. The dataset includes the questionnaire used to retrieve the data, the responses obtained in spreadsheet format, the charts generated from the responses received, the Statistical Package of the Social Sciences (SPSS) file and the descriptive statistics for all the variables captured. This second version contains the reliability statistics of the UTAUT variables using Cronbach's alpha. This measured the reliability as well as the internal consistency of the UTAUT variables. This was measured in terms of the reliability statistics, inter-item correlation matrix and item-total statistics. Authors believed that the dataset will enhance understanding of how face to face students use social media platforms and how these platforms could be used to engage the students outside their classroom activities. Also, the dataset exposes how familiar face to face University students are to these emerging teaching and learning technologies. In this version 3, the SPSS file in SAV format was made available in csv format. Also, the .rar file was made opened to make data accessibility easier.
DOI: 10.17632/24795594tj.1
title: The Global Factor Structure of Exchange Rates Code & Data

description: Replication code and data for "Global Factor Structure of Exchange Rates"
DOI: 10.17632/3vczb7hhzk.1
title: QMMMW: A wrapper for QM/MM simulations with Quantum ESPRESSO  and LAMMPS

description: This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018) Abstract We present QMMMW, a new program aimed at performing Quantum Mechanics/Molecular Mechanics (QM/MM) molecular dynamics. The package operates as a wrapper that patches PWscf code included in the Quantum ESPRESSO  distribution and LAMMPS Molecular Dynamics Simulator. It is designed with a paradigm based on three guidelines: (i) minimal amount of modifications on the parent codes, (ii) flexibility and computational efficiency of the communication layer and (iii) accuracy of the Hamiltonian describ... Title of program: QMMMW Catalogue Id: AEWS_v1_0 Nature of problem Calculation of the hybrid quantum mechanics / molecular mechanics of molecular systems. Versions of this program held in the CPC repository in Mendeley Data AEWS_v1_0; QMMMW; 10.1016/j.cpc.2015.04.024
DOI: 10.17632/7xtpbv27zh.3
title: Synthetic analysis of trophic diversity and evolution in Enantiornithes with new insights from Bohaiornithidae

description: Version 1 accompanies the reviewed preprint of this work, Version 2 accompanies the revised work, Version 3 reflects changes made during the editorial process.

Extended abstract:
The “opposite birds” Enantiornithines were the dominant birds of the Mesozoic, but our understanding of their ecology is still tenuous. In particular, diets of enantiornithine species have remained speculative until recently. We introduce new data on the enantiornithine family Bohaiornithidae, famous for their large size and strong teeth and claws. Alongside previously-published data on the earlier-diverging pengornithids and later-diverging longipterygids, we comment on the breadth of enantiornithine ecology and potential patterns in which it evolved.
Body mass, mechanical advantage, finite element analysis, and traditional morphometrics are compared between bohaiornithids and living birds. We find bohaiornithids ecologically diverse: Bohaiornis and Parabohaiornis resemble living plant-eating birds; Longusunguis resembles raptorial carnivores; Zhouornis resembles both fruit-eating birds and generalist feeders; and Shenqiornis and Sulcavis plausibly ate fish, plants, or a mix of both. This ecological diversity is wider than any other enantiornithine family studied previously.
With these new data, there is support for enantiornithines inhabiting nearly every trophic level. We predict the ancestral enantiornithine bird to have been a generalist. This suggests the ecological diversity of enantiornithine birds represents specialisation in taking foods their ancestors were already eating, rather than many dramatic changes in diet. However, more quantitative data from across the enantiornithine tree is needed to refine this prediction. By the Early Cretaceous, enantiornithine birds had diversified into a variety of ecological niches in a similar way to crown birds after the K-Pg extinction, adding to the body of evidence that traits unique to crown birds cannot completely explain their ecological success.
DOI: 10.17632/vm8rg6rvsw.1
title: Data for: Supervised physical therapy versus home exercise for patients with lumbar spinal stenosis: a randomized controlled trial

description: This data is a single-center, open-label, randomized controlled trial comparing supervised physical therapy (PT) with home exercise (HE) for patients with lumbar spinal stenosis. The purposes of this study were to identify which types of exercise are effective and quantify physical activity using a pedometer to confirm compliance with the home exercise program. At baseline, there were no significant differences in age, sex, body mass index, duration of symptoms, MRI findings, and the outcome measures between groups (P &gt; 0.05). At 6 weeks, compared with the HE group, the PT group showed significant improvements in ZCQ symptom severity (mean difference –0.4; 95% confidence interval [CI]: –0.6 to –0.2, P = 0.001), ZCQ physical function (mean difference –0.4; 95% CI: –0.6 to –0.2, P &lt; 0.001), walking distance on the SPWT (mean difference 455.9 m; 95% CI: 308.5 to 603.2, P &lt; 0.001), leg pain (mean difference –1.4; 95% CI: –2.5 to –0.3, P = 0.013) on the NRS, gait disturbance (mean difference 16.0; 95% CI: 5.4 to 26.7, P = 0.004) on the JOABPEQ, physical functioning (mean difference 9.2; 95% CI: 2.1 to 16.3, P = 0.012) and bodily pain (mean difference 10.4; 95% CI: 3.3 to 17.5, P = 0.005) on the SF-36, the TSK-11 (mean difference –2.1; 95% CI: –3.9 to –0.2, P = 0.027), and number of daily steps (mean difference 723.4 steps/day; 95% CI: 199.1 to 1283.5, P = 0.008). Twenty-seven of 43 patients (62.8%) in the PT group reached a threshold of MCID of 0.36 for ZCQ symptom severity scale compared with 14 of 43 patients (32.6%) in the HE group (P = 0.009). The Fragility Index value was 3 which indicates that if 3 patients in PT group did not reach a threshold of MCID, the difference between groups lose statistical significance (P &gt; 0.05). The self-reported home exercise compliance did not differ significantly between the two groups during the 6-week treatment period (PT group 39.1/42 days, HE group 39.1/42 days, P = 0.985). We found that supervised physical therapy resulted in significant short-term improvements in symptom severity, physical function, walking distance, pain, and physical activity compared with unsupervised exercise.
DOI: 10.17632/5prc54r4rt.1
title: DeepFruits: Dataset of Fruits Images with different combinations for Fruit Recognition and Calories Estimation

description: A new labeled dataset consists of 21,122 fruit images of 20 diverse kinds of Fruits based on 8 different fruit set combinations. The number of images per class differs from one class to another. Sample images of all Fruit combinations are also attached. The train and test CSV files contain the Label of each corresponding Fruit class in each image based on the image file name.
DOI: 10.17632/kbvcdw5b4m.1
title: Data for: Clinical Mastitis in Cows based on Udder Parameter using Internet of Things (IoT)

description: The data is collected from the udder of a cow to detect clinical mastitis. The four flex sensors and a temperature sensor are used to collect the udder data. Milk image is processed to find the quality of milk which also affects clinical mastitis. In the milk quality attribute, 0 indicates the normal milk and 1 indicates the abnormal milk. The data attributes are Cow_ID, Day, Breed, Month after giving birth, previous occurrence of mastitis, size of an udder (udder front left inhale and exhale limit, udder front right inhale and exhale limit, udder rear left inhale and exhale limit, udder rear right inhale and exhale limit), the temperature of a cow, the hardness of an udder from user input via a switch, and pain due to swelling of an udder. There are two class normal cows indicated as 0 and mastitis cow indicated as 1. By analyzing the data using an efficient algorithm faster track of clinical mastitis in the cow is provided. The SAC is designed to deploy flex sensors and temperature sensor, using raspberry pi and analog to digital converter data from the sensors are wirelessly collected. As sensors are connected to the internet the IoT is in the picture to gather data. The IoT is used to monitor animal health so the concept is called the Internet of Animal Health Things (IoAHT).
DOI: 10.17632/p3n7k6hxgw.1
title: Gas concentration prediction dataset

description: This dataset contains downhole multidimensional data, which is part of the dataset used for the study, and this dataset was used to make predictions of gas concentrations.
DOI: 10.17632/cwb3y6v3rz.1
title: luoboreguanzhuzhichangchanggengzu

description: dannangzaoloushujuku
DOI: 10.17632/cfjst82z93.1
title: Trifarotene phase 3 study supplemental information

description: Trifarotene phase 3 study supplemental information to accompany JAAD publication 2019
DOI: 10.17632/ydpn8xnx24.1
title: Data for 3D reconstruction and Point Cloud classification using Machine Learning in Cultural Heritage environment

description: The dataset contains UAV images of an archaeological site for analysis and management in software based on Close Range Photogrammetry algorithms. In addition, the dataset contains the 3D point cloud and text files useful for its semantic classification.
DOI: 10.17632/pd83pj4jh3.1
title: Data for: A stochastic prepositioning model for distribution of disaster supplies considering lateral transshipment

description: This is the research data for paper "A stochastic prepositioning model for distribution of disaster supplies considering lateral transshipment" by Yusheng Wang, Zhijie (Sasha) Dong, and Shaolong Hu
DOI: 10.17632/2sfz4tt88g.1
title: Age dataset: A structured general-purpose dataset on life, work, and death of 1.22 million distinguished people

description: We developed a five-step method and inferred birth and death years, binary gender, and occupation from community-submitted data to all language versions of the Wikipedia project. The dataset is the largest on notable deceased people and includes individuals from a variety of social groups, including but not limited to 107k females, 124 non-binary people, and 90k researchers, who are spread across more than 300 contemporary or historical regions.

Related paper accepted to the ICWSM Workshop on Data for the Wellbeing of Most Vulnerable.
DOI: 10.17632/63yhdn29v3.1
title: Barbie Fashionistas: da retórica da diversidade aos modelos de feminilidade e padrões estéticos normativos na educação das meninas

description: Este trabalho objetivou analisar as representações simbólicas implícitas/explícitas nos modelos de feminilidade e padrões estéticos propalados pela coleção Barbie Fashionistas, os quais afetavam a educação das meninas. Pra concretizar este estudo, realizou-se uma pesquisa qualitativa, de natureza bibliográfica, fundamentada no referencial teórico-metodológico da Psicologia Histórico-Cultural (Vigotski, 2009). No escopo do trabalho investigativo, indicadores de análise revelaram que, em um cenário (aparentemente) inovador, sob a retórica da diversidade e da inclusão, padrões de beleza, de comportamento e de feminilidade estavam sendo impostos não apenas para impulsionar o mercado de bens e produtos da marca Barbie, mas sobretudo para legitimar estereótipos femininos, chancelando a alienação em uma sociedade capitalista marcada pelo ideário neoliberal e afetando incontestavelmente, de maneira opressora, a educação das meninas.
DOI: 10.17632/jjyp9m4wrp.1
title: Student Covid Stress 

description: The dataset contains the stress level of students and the Big 5 Dimensions and Facets data collected from students. The study used the COVID Student Stress Questionnaire (CSSQ) developed by Zurlo, Volta & Vallone (2020) because it was built with COVID-specific latent constructs. To measure personality, the study used the IPIP framework with 3 facets per dimension proposed by Han and Carole Pistole, (2017) and two questions per facet (both positively and negatively worded). The dimension score is the sum of the facet scores of the respective dimension. Both instruments used a 5-point Likert scale from fully agree to fully disagree. The data was collected using an online survey, and 420 usable responses were received.
DOI: 10.17632/8j4r5tswnm.1
title: Green HRM, Innovation and Environmental Performance

description: This is a dataset for a quantitative research work
DOI: 10.17632/yj5gyjjwrs.1
title: Indian traffic sign videos of hump and pedestrian crossing at various speeds 

description:  following videos are captured by gopro ( 4k 24 fps ) of hump ahead and pedestrian crossing sign boards near Bangalore, Karnataka, India.
DOI: 10.17632/2djnts9skc.1
title: NEW DYNAMIC SCORING METHOD FOR DEEP EVALUATION OF NALOXEGOL AS Β-TUBULIN BINDING INHIBITOR

description: Dataset of Computer Aided Drug Design (CADD) and Molecular Dynamics (MD) operations for the article, titled "NEW DYNAMIC SCORING METHOD FOR DEEP EVALUATION OF NALOXEGOL AS Β-TUBULIN BINDING INHIBITOR"
DOI: 10.15468/dl.9jde9u
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((84.31725 -0.72792,120.68275 -0.72792,120.68275 24.72792,84.31725 24.72792,84.31725 -0.72792))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Maclurochloa K.M.Wong"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009341-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/f78jsh6zp9.2
title: Keystroke and Mouse Dynamics for UEBA Dataset

description: Behavioural dynamics gathered from a webchat app. EVTRACKINFO: 347 records. Static behaviour information. EVTRACKTRACK: 142691 records. 113471 for keystroke dynamics and 29220 for mouse dynamics. 11 users. A mean of 28524 +-18541 records has been obtained per user.
DOI: 10.15468/dl.thxa2x
title: Occurrence Download

description: A dataset containing 1008 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Prunus sargentii Rehder",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 1008 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009343-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.