cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/5kcgj69fxs
title: Factors Determining Bangladeshi University Students' Perception, Knowledge and Attitude About Climate Change: A Cross-Sectional Study

description: This dataset is generated during the research article "Factors Determining Bangladeshi University Students' Perception, Knowledge and Attitude About Climate Change: A Cross-Sectional Study" (DOI: 10.1002/hsr2.70722). It contains comprehensive data collected from 1,500 university students across Bangladesh and is structured to explore the determinants of students’ knowledge, perception, and attitude toward climate change.

Dataset Structure
The Excel file comprises three sheets:

1. raw Sheet
Contains 34 categorical variables, including:

Socio-demographic characteristics: Gender, educational level, study discipline, individual monthly expenditure, residency, and parental education levels.

Information sources: Where students primarily learn about climate change.

Knowledge and perception indicators: Students’ awareness of climate change, beliefs about local manifestations (e.g., extreme weather, floods, droughts, riverbank erosion), and perceived health impacts.

Attitudinal components: Opinions on media's role, necessity for climate education, and willingness to stay informed.

2. coded Sheet
A quantitatively transformed version of the raw data with 40 columns.

Includes:

Recoded responses into numerical formats (e.g., Agree = 1, Neutral = 0.5, Disagree = 0).

Composite indicators:

Total Knowledge Score and Knowledge Level (Good vs. Poor)

Total Attitude Score and Attitude Classification

Ready for statistical analysis including regression, correlation, and ANOVA.

3. codebook Sheet
Provides the labeling scheme and coding guide.

Maps variable names to simplified labels (e.g., K1 for the first knowledge item) and outlines the numerical values assigned to Likert-scale responses.

Study Background
The dataset originates from a cross-sectional survey aimed at understanding how various factors shape Bangladeshi university students’ awareness and attitude toward climate change, with implications for future education and policy initiatives. The associated article investigates the interplay between socio-demographic traits and climate literacy and offers insights for integrating climate topics into higher education curricula in low- and middle-income countries.

Applications
This dataset is suitable for:

Descriptive analysis of climate change awareness among youth.

Inferential analysis (e.g., binary logistic regression, t-tests) of determinants influencing knowledge and attitudes.

Modeling the role of socioeconomic and educational background in shaping climate perceptions.

It serves as a valuable resource for public health researchers, environmental educators, and policymakers interested in climate education and youth engagement in climate resilience efforts in Bangladesh and similar contexts.
DOI: 10.17632/fxr568hfc3
title: Code and Data accompanying a paper entitled "An Extended Microphysical Friction Model for Variable Normal Stress Conditions"

description: This dataset gives the code and dataset accompanying a submitted paper entitled "An Extended Microphysical Friction Model for Variable Normal Stress Conditions". In this study, we extend a microphysical friction model, initially designed for constant normal stress conditions, to account for varying normal stress, by including the effects of fault gouge and system elasticity. We tested the model against different lab experiments with changing normal stress, and it successfully captured the key responses observed. Unlike traditional models, our model inherently includes a gouge plasticity term that directly relates to normal stress, allowing for immediate and temporary changes in the density of the gouge and influencing steady-state friction. Importantly, the model does not require an additional factor to explain how shear stress changes with normal stress adjustments. We believe this model could be useful for understanding real-world effects of changes in normal stress, such as the relationship between local earthquakes and solid tides, and the induced seismic risks posed by reservoir exploitation and stimulation. 
This is a theoretical paper and no experimental data is being produced. The code, which uses the solvers embedded in the finite element package Comsol (Version 3.5a), and the numerical results for plotting the graphs, are included in this dataset. The former (code) is given in a file (.mph) and the produced data are given in four zip files (.rar). The four files are "Normal stress oscillations.rar", "Normal stress pulse.rar", "Normal stress stepping tests.rar", and "SHS Test with Modulated Normal Stress.rar". Note that "SHS" refers to a special test called "slide-hold-slide" test.
DOI: 10.17632/hjbsn4h77c
title: Data for: Phylogenomics within the Anthonotha clade (Detarioideae, Leguminosae) reveals a high diversity in floral trait shifts and a general trend towards organ number reduction

description: Peptide sequences of six Legumes used in the design of the exome capture in Detarioideae Sequences of the targeted regions used to develop the bait
DOI: 10.17632/xhr9vytdzw
title: RELATIONS BETWEEN EMOTIONAL INTELLIGENCE AND INVESTMENT DECISION – AN EXTENTION OF THEORY OF PLANNED BEHAVIOUR.

description: Emotional intelligence plays vital role in making decision. We conducted a survey, to
understand how investor’s emotional intelligence influences the investment decision. The
survey was conducted using structured questionnaire to identify how investors understand
their own and other’s emotions, how they use and regulate that emotions. The data collected
from 346 investors who already invested in different avenues by using convenience sampling
technique. Relationship between theory of planned behaviour, emotional intelligence and
investment decision is examined with correlation analysis. The data will be used by
researchers who want to identify the impact of investors’ emotional intelligence, theory of
planned behaviour on investment decision.
DOI: 10.6084/m9.figshare.14727177.v1
title: Cat Origins STRs SNPs

description: STR and SNP genotypes for publication on the origins of cat domestication<br>
DOI: 10.6084/m9.figshare.15307182.v1
title: Supplementary Material for: Development of Skin Rash Predicts Outcome of Anti-PD-1- and Anti-CTLA4-Based Immune Checkpoint Inhibitor Therapy in Non-Small Cell Lung Cancer or Squamous Cell Carcinoma of the Head and Neck: A Single-Center Analysis

description: <b><i>Objective:</i></b> We report the spectrum of immune-related adverse effects (irAEs) and outcome observed in a single-center cohort of 100 patients treated with immune checkpoint inhibitors in a routine clinical setting. <b><i>Methods:</i></b> Tumor entities included non-small cell lung cancer (<i>n</i> = 28), head and neck squamous cell carcinoma (<i>n</i> = 28), urothelial carcinoma (<i>n</i> = 7), and others (<i>n</i> = 37). <b><i>Results:</i></b> irAEs were documented in 49% of cases analyzed, and the most frequent manifestation consisted of immune-mediated skin rash (28%), colitis (9%), pneumonitis (8%), hypothyroidism (7%), or hepatitis (6%). Skin rash correlated with improved progression-free survival. <b><i>Conclusion:</i></b> Development of immune-related skin rash was found to correlate with favorable outcome, suggesting its practical feasibility as a potential predictive surrogate marker.
DOI: 10.17632/kxkzfn8ms5
title: Public Charging Infrastructure and Electric Vehicles in Norway: Replication Files

description: This repository allows for the replication of all calculations presented in "Public Charging Infrastructure and Electric Vehicles in Norway", written by Schulz, F. and Rode, J., forthcoming in Energy Policy (doi: TBD).

We study whether public charging infrastructure drives battery electric vehicle adoption. The data provided includes granular, annual information on the location of public charging infrastructure and the battery electric vehicle ownership rate across 356 Norwegian LAU-2 municipalities between 2009 and 2019. We find, on average, an increase of the local electric vehicle ownership rate by 1.5 percentage points or 200% over 5 years. While we cannot fully rule out reverse effects, we identify public charging infrastructure to serve as a stimulus to the diffusion of battery electric vehicles.

Further information on how one can use the scripts provided can be found in the readme-file.
DOI: 10.6084/m9.figshare.3102781.v1
title: Snodgrass & Vanderwart 'Like' Objects

description: <b>NOTE THAT THE LICENSE IS</b> <i>Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License</i><br>This is a set of 260 colored objects created by Rossion & Pourtois (2004), which is loosely based on the original dataset by Snodgrass & Vanderwart (1980) and provided by Tarr Lab (see the link below).<br>The version provided here converted images from PCT to PNG. Moreover, a description of each image is provided in the definitions.csv file, including WordNet synset, definition, and synonyms (obtained from Snodgrass & Vanderwart, 1980, plus several new ones, namely, baby carriage: stroller, pram; doorknob: doorhandle; rabbit: bunny, hare; refrigerator: fridge).<br>Please cite the following paper when using the dataset:<br><i>Rossion, B., & Pourtois, G. (2004). Revisiting Snodgrass and Vanderwart's object set: The role of surface detail in basic-level object recognition. Perception, 33, 217-236.</i><br>Also, please include the following statement in the paper:<br><i>Stimulus images courtesy of Michael J. Tarr, Center for the Neural Basis of Cognition and Department of Psychology, Carnegie Mellon University, http://www.tarrlab.org/</i>
DOI: 10.6084/m9.figshare.3749790.v3
title: Comparative group from a Brazilian DIPG clinical trial

description: Group of patients with DIPG (symptoms for less than 6 months, involvement of more than 50% of a pontine segment or two or more segments), treated with radiation (54 to 60 Gy) and tamoxifen during and after RT (200mg/m<sup>2</sup>) at the AC Camargo Hospital in Sao Paulo. The graph shows the estimated probability of survival calculated by the Kaplan-Meier method, using the R programming language, *survival* package. The package *RCurl* was used to capture the data from the .csv file stored on github repository. The graph also shows the 95% confidence interval.(Excerpt)
DOI: 10.6084/m9.figshare.28253939.v1
title: Biocrust-covered soil C fluxes.xlsx

description: Here, we measure C fluxes to examine C dynamics in a stable-state coexistence of <i>Artemisia ordosica</i> and cyanobacterial-moss biocrusts in a semiarid dryland ecosystem. The influence of the shrub canopy on C exchange was determined through comparing C fluxes under the canopy to those in areas where the canopy was recently removed but the roots were retained.
DOI: 10.17632/hmyhtxppvn
title: Improving learning achievement and self-regulated learning through AI-enabled formative assessment and visual reports: An experimental study

description: A total of 125 participants enrolled in ninth-grade biology courses participated in the experimental study and were assigned to one of two groups: a treatment group (n = 63), who received AI-enabled formative assessment in a visual format, and a control group (n = 62), who received a traditional assessment in the form of test scores and teacher feedback. Repeated-measures analysis of variance and nonparametric test results showed that the visual reports effectively improved students’ learning achievement. The results provide important implications for designing and implementing effective formative assessments supported by AI and visualization
DOI: 10.17632/vtgpd3zkm5
title: Artifical Intelligence

description: AI-СИСТЕМА БИРЖЕВОГО ТОРГОВОГО РОБОТА ДЛЯ ХЕДЖИРОВАНИЯ ФИНАНСОВОГО РИСКА
DOI: 10.6084/m9.figshare.12277427.v2
title: Updating and backdating analyses for mitigating uncertainties in land change modeling: A case study of the Ci Kapundung upper water catchment area, Java Island, Indonesia - Data

description: This is the dataset used in a study, which was written in a paper entitled: "Updating and backdating analyses for mitigating uncertainties in land change modeling: A case study of the Ci Kapundung upper water catchment area, Java Island, Indonesia". <br> The dataset contains samples of raw data and the raster files for the case study area, which have been projected and clipped, and the workflow. The analyses were conducted using the graphical user interface from ArcGIS 10.7.1, Land Change Modeler (LCM) module from Terrset, QGIS and SAGA. No codes were retrieved during the process. <br>
DOI: 10.6084/m9.figshare.16679665.v1
title: Source Data for Acid Anion Electrolyte Effects on Platinum for Oxygen and Hydrogen Electrocatalysis

description: Source (main text) Data for Acid Anion Electrolyte Effects on Platinum for Oxygen and Hydrogen Electrocatalysis
DOI: 10.6084/m9.figshare.25199789.v1
title: Forest & Sparse Woody Cover in HIR Projects

description: Forest and sparse woody vegetation cover in human-induced regeneration ACCU projects and 3km buffer areas around the boundaries of projects, 1988-2022. Data were used to analyse the performance of one of the world’s largest nature-based offset types: human-induced regeneration projects under Australia’s carbon offset scheme. The projects are supposed to involve the human-induced regeneration of permanent even-aged native forests through changes in land management. We analysed 182 projects and found the credited regeneration has largely not occurred. Changes in woody vegetation cover within the areas that have been credited also largely mirror changes in adjacent comparison areas, outside the projects, suggesting the changes are attributable to factors other than the project activities.
DOI: 10.6084/m9.figshare.25778682.v1
title: Appendix tables 1, 3 and 4

description: Appendixes 1, 3 and 4
DOI: 10.17632/7b5mmdjpt3
title: Gargano Promontory (Italy) microseismicity (2013-2018): waveform data and earthquake catalogue

description: Database of the collected waveforms of microearthquakes occurred in the Gargano region (Southern Italy), recorded by the stations of the National Seismic Network (RSN-INGV) and by the Gargano seismic network (OTRIONS) in the period 2013/04/15 to 2018/08/05, and that integrates the INGV catalogue (http://cnt.rm.ingv.it/). Database of the recognized earthquakes. The University of Bari (Italy) in cooperation with the National Institute of Geophysics and Volcanology (INGV) (Italy), deployed, in 2013, the OTRIONS micro-earthquake network aiming to better understand the active tectonics of the Gargano promontory (Southern Italy). The network consists of 12 short period 3 component seismic stations located in the Apulian territory (Southern Italy). This data releases regards the waveform database collected from 2013 up to 2018. At the end of 2018, we implemented a cloud infrastructure to make more robust the acquisition and storage system of the network through a collaboration with the RECAS-Bari computing centre of the University of Bari (Italy) and of the National Institute of Nuclear Physics (Italy). From the beginning of 2019 waveform dataset and the station metadata are accessible through the European Integrated Data Archive.
DOI: 10.17632/bvts42fpfb
title: VTAR11

description: Advances in Artificial Intelligence and Computer Vision have made automation systems popular in a variety of fields. One of these is Human Activity Recognition, which has a number of novel, practical and innovative applications. Because the HAR is a complex system, many issues and challenges need to be addressed. One of the most challenging research areas under HAR is identifying toddler activities from various vision input devices. In order to enhance the safety and wellness of toddlers, their behavior has to be studied separately. For this, a comprehensive understanding of existing toddler activity systems, available datasets to conduct experiments, challenges involved, and potential societal applications must be explored. Toddler activity recognition is a specialized subfield of computer vision and machine learning that focuses on automatically identifying and classifying activities performed by toddlers or young children. Vision-based toddler activity recognition plays a crucial role in monitoring developmental milestones, detecting anomalies, and supporting research in child development studies. Current human activity recognition primarily emphasizes adult activities. However, toddler activities, while sharing similarities with those of adults, exhibit significant variations in execution. Consequently, there exists ample opportunity to explore toddler activities as a distinct and separate research domain. This paper presents an image dataset designed for the purpose of recognizing toddler activities. The dataset consists of 2,389 raw images distributed across 11 distinct activity classes. Each activity class contains over 195 images, ensuring a well-balanced distribution within the classes. The considered toddler activity categories for experimentation encompass crying, eating, drinking, smiling, sleeping, yawning, W-sitting, playing on a swing, playing with stacking rings, toddlers on a staircase, and toddlers with a knife. The dataset was meticulously compiled, merging images obtained from Google with manually collected photographs. The dataset undergoes image preprocessing on the raw images as part of the model building process. This preprocessing involves auto orientation, contrast stretching, and resizing the images to 320x320 pixels while accommodating white edges. To enhance the diversity of the original images, image augmentation techniques were employed. These techniques included horizontal flipping, the application of grayscale to 10% of the images, brightness adjustments with variations ranging from -25% to +25%, up to 1-pixel blurring, and the addition of noise to up to 3% of the pixels. As a result, a comprehensive training dataset was created, consisting of 12,331 images. Subsequently, the resulting dataset was utilized for model construction. The authors leveraged the RoboFlow AutoML model, achieving a validation accuracy of 93.2%.
DOI: 10.17632/c7c84cxx3h
title: Weight Gain Secondary to the Use of Oral Janus Kinase Inhibitors: A Systematic Review and Meta-analysis

description: This systematic review and meta-analysis aims to describe the incidence and characteristics of weight changes secondary to the use of various Janus kinase inhibitors for all, including dermatologic, indications.
DOI: 10.17632/f4ky6ks248
title: Sen-2 LULC

description: The "Sen-2 LULC Dataset" is a collection of 2,13,750+ pre-processed 10 m resolution images representing 7 distinct classes of Land Use Land Cover. The 7 classes are water, Dense forest, Sparse forest, Barren land, Built up, Agriculture land and Fallow land. Multiple classes are present in the single image of the dataset. The Sentinel-2 images of Central India are taken from Copernicus Open Access Hub (https://scihub.copernicus.eu/) with cloud clover percentage ranging from 0 to 0.5%. The images are combination of bands B4, B3 and B2 constituting the red, green and blue bands with spectral resolution of 10m. The images are taken within the months of February and March 2021. The images used in the dataset belongs to Sentinel-2 Level-2A product (https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-2-msi/product-types/level-2a#:~:text=The%20Level%2D2A%20product%20provides,(UTM%2FWGS84%20projection).). The dataset contains equal number of mask images. The dataset contains 6 folders with train, test and validate images and train, test and validate masks. This dataset can be used for Land Use Land Cover Classification (LULC) of Indian region to build the deep learning models. This dataset is beneficial for LULC classification research.
 [The related article is available at: Sen-2 LULC: Land use land cover dataset for deep learning approaches. Cite the article as : Sawant, S., Garg, R. D., Meshram, V., & Mistry, S. (2023). Sen-2 LULC: Land use land cover dataset for deep learning approaches. Data in Brief, 51, 109724, https://doi.org/10.1016/j.dib.2023.109724. ]
DOI: 10.25421/yorksj.29037116.v1
title: LM case control ITBS data.xlsx

description: This file contains the full data set for the case control study 'A sex-specific case-control analysis of iliotibial band syndrome in recreational runners comparing muscle function, gait analysis, training behaviours, psychological factors and sleep quality'. It includes each participants complete individual data, including demographics.
DOI: 10.6084/m9.figshare.22129127.v1
title: Mapa Interativo do Mosaico de Áreas Protegidas do baixo Rio Negro (MBRN)

description: O Mapa Interativo do Mosaico de Áreas Protegidas do Baixo Rio Negro (MBRN) é uma iniciativa realizada como parte do projeto de pesquisa “<em>Populações Tradicionais em Áreas Protegidas – dinâmicas socioambientais e gestão de Unidades de Conservação no Mosaico Baixo Rio Negro” </em>(FAPESP 2020/08242-7 / FAPEAM 01.02.016301.00266/2021) com o propósito de disponibilizar alguns indicadores relevantes aos comunitários e às instâncias envolvidas na gestão do Mosaico. <br> <strong>Aqui estão compilado os dados sobre o MBRN:</strong> 1. Tutorial descritivo sobre a plataforma interativa; 2. Dados das comunidades visitadas no âmbito do projeto supracitado (shapefile e planilha); 3. Dados de todas comunidades mapeadas (shapefile) 4. Limites das Unidades de Conservação que compõem o MBRN (shapefile); 5. Grade Estatística do IBGE com dados sobre população (shapefile); 6. Uso e cobertura da terra no MBRN 1985 e 2020 (shapefile); <br> Para atendermos as dúvidas, sugestões, parcerias, atualização e inclusão de novos dados, encaminhe-nos uma mensagem: <br> E-mail: lum.unicamp@gmail.com Instagram: @lum_unicamp Página Oficial: https://www.fca.unicamp.br/l-um/
DOI: 10.17632/395w6dcws7
title: PASS Participants Psychological and Emotional Experiences 

description: Background.  There are growing number of pathway programs, with an early assurance of admission, that target undergraduate students from groups underrepresented in medicine (URiM) to enable their competitiveness for and matriculation to medical school, including the Penn Access Summer Scholars (PASS) program.  The psychological and emotional experiences of students in these programs, however, have not been previously described.
Methods.  Students from the summer 2021 cohort of the PASS program were interviewed using a structured set of questions that explored four specific areas: (i) the application process; (ii) the benefits and value of being in the PASS program; (iii) the emotional and psychological challenges and stresses of being in the PASS program; (iv) feelings and emotions about not taking the MCAT or having to interview at multiple schools. The transcribed, de-identified interviews were then subjected to a qualitative analysis.
Results.  Students in PASS reported that the program was valuable to them in that it reduced the stress of the pre-medical process; relieved worry and anxiety surrounding the MCAT; enabled development of supportive relationships and provided meaningful exposures to the medical profession and biomedical research.  Despite this, students reported feelings of imposterism, guilt, and fear of disappointing, along with varying degrees of regret over not taking the MCAT and not interviewing at more than one medical school.
Conclusions.  URiM and other marginalized students participating in early assurance admissions programs likely enter medical school with a range of positive and negative emotions as a result of their participation in these programs.  These data can be used to inform the development of programing and other initiatives that further support the success of these students in medical school.