cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/5fjwb9hfpm
title: Supplementary Data and Code: Forest variables from LiDAR: Drone flight parameters impact the detection of tree stems and diameter estimates

description: The dataset consists of five individual LiDAR point cloud of a part of the LMU managed forest, located close to Landshut Germany. The data was recorded in May and July of 2024 and was used to analyse how different flight parameters influence the data for the estimation of forest structural parameters. The LiDAR data was collected using a GeoSun GS-100C+ LiDAR Scanner (Wuhan Geosun Navigation Technology Co., Ltd) on a DJI Matrice M300 Drone (SZ DJI Technology Co., Ltd.) and processed using Geosun's software shipped with the device. Further, all datasets were corrected for intensity and geolocation. Naming: H indicates flight height in meters, S flight speed in meters per second divided by 10, and O the overlap in percent, N denotes the flight being performed at night. 
The data was used to develop new methods for the delineation of stems from the point cloud, the estimation of understory vegetation, and the estimation of tree DBH values. We have found the best functioning of both stem delineation and DBH estimation under the densely overlapped data of H50 S60 O60. The added code for R presents the three methods for stem delineation, DBH estimation, and understory vegetation segmentation.
DOI: 10.17632/wnpk4dgpdy
title: The potential impact data of Tylosin and Enrofloxacin veterinary antibiotics on germination and accumulation in barley seed as a forage crop and good dietary sources using LC/MS-MS.

description: The dataset was used to investigate the potential impact of Tylosin and Enrofloxacin veterinary antibiotics on the seed germination percentage, root and shoot length, roots, and shoots over control percent, elongation, fresh weight, and dry weight of seedling. The uptake concentrations were detected and quantified using LC-NS/MS system to assist known the effect of antibiotics accumulation on the seed germination. The data were analyzed statistically to find out the significance of variation between treatments using IBM-SPSS statistic 25.
DOI: 10.6084/m9.figshare.28111991.v1
title: Depressive symptoms, sleep problems and quality of life in health professionals and health system users: a cross-sectional study

description: Objective: To determine whether significant differences exist in presenting depressive symptoms, sleep problems, and quality of life between healthcare workers and healthcare users in Peru. Methods: Our study is cross-sectional. A multiple linear regression analysis was performed to determine differences between groups, and an exploratory network analysis model was applied. Results: Our study included 340 participants, of whom 56% were healthcare workers. Healthcare workers reported lower scores for depressive symptoms (coefficient: -1.13, p &lt; 0.001) and higher scores for quality of life (coefficient: 0.22, p &lt; 0.001) compared to healthcare system users. However, healthcare workers exhibited higher scores for sleep problems than healthcare system users (coefficient: 11.88, p &lt; 0.001). Our analysis revealed differences in the correlation between certain items related to depressive symptoms and sleep problems in healthcare system users and healthcare workers. Conclusions: This study revealed a high prevalence of sleep problems and lower quality of life among healthcare workers compared to the general population. While depressive symptoms were present in both groups, sleep problems showed a significant difference. Our study demonstrates that healthcare workers exhibit a more interconnected network of depressive symptoms, sleep problems, and quality of life, suggesting that these issues tend to manifest together and more intensely.
DOI: 10.17632/hjd4bdtpry
title: Problem behaviours and caregiver burden among children with Autism Spectrum Disorder in Kuching, Sarawak

description: Objective: Caregivers of children with Autism Spectrum Disorder (ASD) often experience emotional and psychological distress, as well as disruptions to family life and employment due to the challenges of caring for children with ASD. This study examines the relationship between problem behaviours and caregiver burden among children with ASD.

Method: A cross-sectional study using convenience sampling recruited 230 caregivers of children with ASD aged 4 to 18 years from selected autism centres in Kuching, Sarawak. The caregivers completed the Aberrant Behaviour Checklist-2 and the Zarit Burden Interview.

Results: Univariate analysis revealed a significant difference in caregiver burden for children with ASD receiving medications (p = 0.013), registered with the Social Welfare Department (p = 0.036), and having siblings with ASD (p = 0.046). About 40% of the children exhibited at least one domain of problem behaviour. More than half of the caregivers (53.9%) experienced burden, with the majority experiencing mild burden. Positive associations were seen between irritability (r = 0.458, p &lt; 0.01), social withdrawal (r = 0.439, p &lt; 0.01), stereotypic behaviour (r = 0.392, p &lt; 0.01), hyperactivity/non-compliance (r = 0.467, p &lt; 0.01), and caregiver burden. Child factors, including the duration of problem behaviour (r = 0.182, p = 0.007), medication use (eta = 0.187, p = 0.005), Social Welfare Department registration (eta = 0.138, p = 0.036), and the presence of siblings with ASD (eta = 0.130, p = 0.046) were associated with caregiver burden. Multiple linear regression showed that hyperactivity/noncompliance significantly predicted caregiver burden.

Conclusion: Specific problem behaviours in children with ASD were associated with caregiver burden. These results highlight the need for interventions for the child with ASD and their caregivers.
DOI: 10.17632/ss7b7b3xp9
title: Prevalence of schistosomiasis in south-west Nigeria, a call for action

description: Schistosomiasis is a neglected tropical disease that affects over 200 million people worldwide, particularly in low-income countries. It is endemic to Nigeria, with the highest prevalence in the southwestern region, recent studies show. The purpose of this study is to examine the public knowledge in the six southwestern states of Nigeria on schistosomiasis etiology, transmission, pathology, risk factors and prevention in order to create awareness for public health interventions. An online questionnaire with 13 epidemiologically-oriented questions was distributed in six states - Osun, Ogun, Lagos, Ondo, Ekiti and Oyo - to assess the current state of knowledge on schistosomiasis dynamics. The retrieved data was sorted, analyzed and visualized using IBM SPSS and Microsoft Excel. The results of the analysis were compared to previous publications on the incidence of schistosomiasis in Nigeria. This study shows that a large percentage of the population lacks basic knowledge about schistosomiasis and the informed population tends towards those in scientific disciplines. Our results underscore the need to raise public awareness of schistosomiasis prevention and control. To achieve this, we recommend that the government formulates and implements appropriate public awareness strategies. In addition, educational institutions should include teaching on schistosomiasis and other neglected tropical diseases as part of general studies.
DOI: 10.17632/87njz3ys7m
title: Classification method of coal mine gas explosion accident

description: This supplementary material records the principles, methods, concepts and the specific subcategories of coal mine gas explosion accident classification methods in the main text. The content is arranged as follows: The first section introduces the principles, methods, and concepts used to construct classification. The construction of classification relies on the constraints of principles, the guidance of methods, and the reuse of basic concepts; Section 2, 3 and 4 respectively introduce the subclasses of individual action causes, management system causes and other accident causes; Section 5 describes how to use the classification.
DOI: 10.17632/8p866htg4g
title: Perception of Risk Towards Environmental Unsustainability Scale (PREUS)

description: Here you can found the two SPSS database to replicate the analyses for the validation of the Perception of Risk Towards Environmental Unsustainability Scale (PREUS), validated in a paper Design and Validation of the Perception of Risk Towards Environmental Unsustainability Scale (PREUS) published at the Evironment, Development and Sustainability
DOI: 10.17632/wmgtzw2w8f
title: Deep Machine Learning of High Dimensional Peripheral Blood Flow Cytometric Phenotyping Data for identifying Prostate Cancer and its Clinical Risk in Asymptomatic Men

description: The peripheral blood of 130 asymptomatic men having elevated Prostate-Specific Antigen (PSA) levels was immune profiled using multiparametric whole blood flow cytometry. Of these men, 42 were subsequently diagnosed as having benign prostate disease and 88 as having PCa on biopsy-based evidence.

We built a bidirectional Long Short-Term Memory Deep Neural Network (biLSTM) model for detecting the presence of PCa in men which combined the previously-identified phenotypic features (CD8+CD45RA-CD27-CD28- (CD8+ Effector Memory cells), CD4+CD45RA-CD27-CD28- (CD4+ Effector Memory cells), CD4+CD45RA+CD27-CD28- (CD4+ Terminally Differentiated Effector Memory Cells re-expressing CD45RA), CD3-CD19+ (B cells), CD3+CD56+CD8+CD4+ (NKT cells) with Age. The performance of the PCa presence ‘detection’ model was: Acc: 86.79 (±0.10), Sensitivity: 82.78% (± 0.15); Specificity: 95.83% (± 0.11) on the test set (test set that was not used during training and validation); AUC: 89.31% (± 0.07), ORP-FPR: 7.50% (± 0.20), ORP-TPR: 84.44% (± 0.14).

A second biLSTM ‘risk’ model combined the immunophenotypic features with PSA to predict whether a patient with PCa has high-risk disease (defined by the D'Amico Risk Classification) achieved the following: Acc: 94.90% (± 6.29), Sensitivity: 92% (± 21.39); Specificity: 96.11 (± 0.00); AUC: 94.06% (± 10.69), ORP-FPR: 3.89% (± 0.00), ORP-TPR: 92% (± 21.39). The ORP-FPR for predicting the presence of PCa when combining FC+PSA was lower than that of PSA alone.

This study demonstrates that AI approaches based on peripheral blood phenotyping profiles can distinguish between benign prostate disease and PCa and predict clinical risk in asymptomatic men having elevated PSA levels.
DOI: 10.17632/z38f3jzhbg
title: BioInks Characterization DataSet

description: This study investigated BioInks that have been tuned to be photo-sensitive to a range of wavelengths using a panel of photo-initiator and photo-absorber additives. Modifying viscoelastic and UV-sensitive properties yields cross-platform bio-ink compositions that can be printed across stereolithography (SLA), digital light processing (DLP), and direct ink extrusion technologies.
DOI: 10.17632/4tbhw6s7xg
title: Brand Recall and customer loyalty metrics

description: The dataset data_loyalty is designed to simulate key metrics associated with brand loyalty and customer retention. It consists of four primary variables, each representing a different aspect of customer engagement and loyalty:
Brand Recall: This variable measures the ability of consumers to remember a brand when prompted. It is generated using a normal distribution with a mean of 50 and a standard deviation of 15, indicating that most values will cluster around the average, with some variability reflecting differences in consumer memory.
Customer Retention Rate (CRR): This metric quantifies the percentage of customers who continue to engage with the brand over time. It is also simulated using a normal distribution, with a mean of 65 and a standard deviation of 10. This suggests that while many customers remain loyal, there is variability in retention rates across the sample.
Net Promoter Score (NPS): The NPS is a widely used metric that gauges customer loyalty based on their likelihood to recommend the brand to others. In this dataset, NPS values are generated as random integers ranging from 1 to 10, providing a straightforward measure of customer sentiment.
Customer Lifetime Value (CLV): This variable estimates the total revenue that a business can expect from a single customer account throughout their relationship. It is simulated using a normal distribution with a mean of $20,000 and a standard deviation of $5,000, reflecting the potential variability in customer value.
The dataset comprises 100 observations for each variable, providing a robust foundation for analysis.
DOI: 10.17632/yzd5w5w833
title: Wire Rope Dataset

description: We use industrial cameras to take images of steel wire ropes under different conditions. We put the images of steel wire ropes in five folders, named as：Camera position step up_1; Camera position step up_2; From dark to light; Rotate(360 degrees); Rotate(360 degrees). Images in different folders come from different sources, explained below: Camera position step up_1：Move the camera from bottom to top to obtain images of different positions of the wire rope.  Camera position step up_2: The camera rotates at a certain angle with the wire rope as the axis and then moves the camera from bottom to top to obtain images of different positions of the wire rope.  From dark to light:Adjust the brightness of the light source to obtain the images of the wire rope under different brightness. Rotate(360 degrees)： Rotate the wire rope 360 degrees and randomly take images of the wire rope at different angles. Rotation(free)：Apply a certain torque to both ends of the wire rope and then suddenly remove the torque applied to both ends of the wire rope, and randomly take images during the rotation of the wire rope.In addition, the dataset also provides the json file generated manually using labelme. Note: If the network model fails to be trained using the json file, you can consider converting the Chinese in the json file to English. Finally, we also provide dataset usage instructions in the wire rope dataset folder.
DOI: 10.17632/bg3js4z2xt
title: Indian Fruits-40

description: Indian Fruits-40 image data set contain five most popular Indian fruits i.e. Apple, Orange, Mango,Pomegranate and Tomato. The data set includes all the varieties which are cultivated in India and available in India market. The total data set contain 23, 848 images. Cite as: Behera, Santi Kumari; Rath, Amiya Kumar; and Sethy, Prabira Kumar (2020) "Fruit Recognition using Support Vector Machine based on Deep Features," Karbala International Journal of Modern Science: Vol. 6: Iss. 2 , Article 16. DOI: 10.33640/2405-609X.1675
DOI: 10.17632/54hr8zjx8r
title: Code-switching in ESL classrooms of Malaysian Premier Polytechnics

description: The data was collected using a mixed method study of convergent parallel design, conducted using classroom observations, interviews and questionnaires to triangulate the data obtained from the three Premier Polytechnics in Malaysia, which involved nine lecturers and 183 students.
DOI: 10.17632/cttkm2b9rp
title: Data for: Revisiting the equable climate problem during the Late Cretaceous greenhouse using paleosol carbonate clumped isotope temperatures from the Campanian Western Interior Basin, USA

description: These files contain data and supplementary data including stable and clumped isotope replicate data for paleosol carbonates collected from the Late Cretaceous Kaiparowits (Utah, USA) and Two Medicine (Montana, USA) formations. Also includes reconstructed warmest month mean temperatures, mean annual range in temperature, and estimated coldest month mean temperatures for the two study areas.
DOI: 10.6084/m9.figshare.24949470.v1
title: The Volebny Kompas Datasets on Slovak Voter and Party Positions

description: Three decades after the fall of socialist regimes in Central Europe, the successes of democratic transition face threats from broader trends toward skepticism, disengagement and distrust across Europe, though perhaps more intensively in the East. This backdrop, especially evident in Slovakia, underscores the need for comprehensive data on voter and political party positions during elections, a key opportunity for democratic renewal. Our article introduces two datasets from the Volebný Kompas project: the first, is a collection of 134,699 voter responses on 39 key issues, obtained through the Volebný Kompas voting advisory application for the 2023 snap Slovak Parliamentary Elections. The second dataset details the positions of 11 political parties on the same issues. Together, they provide a comprehensive view of Slovakia's political landscape before a pivotal election which resulted in a dramatic change in government composition. As freely available and validated resources, these datasets can serve as an essential resource for understanding and navigating the evolving landscape of post-socialist democracies.
DOI: 10.17632/5thd2k26sz
title: Global Ski Resort Rankings Dataset

description: A comprehensive dataset containing crowdsourced rankings of nearly all ski resorts worldwide. The dataset includes detailed information on each resort, such as location, snowfall, number of lifts and slopes, total slope length, and vertical drop. The dataset is updated regularly as more votes are collected.
DOI: 10.17632/p5r92rmjng
title: Sample XRD Data for Computation of Retained Austenite Phase Fraction

description: This dataset exists to store supplementary data to a thesis by C.B. Finfrock, Colorado School of Mines, 2022. The two excel files in this dataset are example XRD data, which are intended to provide examples for the use of a Matlab function. The Matlab function "RA_calc.m" is also attached.
DOI: 10.17632/p9ky37n727
title: CORONET and PANEUR topologies

description: Information regarding CORONET and PANEUR topologies.
DOI: 10.17632/tc9vf5jb6m
title: Data for: Sex-Age Stereotyping: Social Perceivers as Lay Adaptationists

description: SPSS data files and syntax for all studies
DOI: 10.17632/szzb3bw7mh
title: Shear strength characteristics for hydrate-bearing sediments with the effect of unhydrated water and hydrate saturation

description: The shear strength behavior of hydrate-bearing sediment under partial dissociation conditions was carefully investigated.
DOI: 10.17632/858352hkxh
title: Code for "The Big Three and Board Gender Diversity: The Effectiveness of Shareholder Voice" paper

description: The enclosed code produces the figures and tables reported in the paper. Instructions are provided in the "readme.txt" file. The data sources are described in the paper.
DOI: 10.17632/hytc559th5
title: Raw data set total, direct and difuse radiations in Cesar, La Guajira y Magdalena

description: The data obtained by these stations correspond to measurements from 1984 to 2014 allowed the parameters estimation of the total, direct and diffuse solar radiation for Cesar, Magdalena and La Guajira (Colombia), by mean of the Bird & Hulstrom model and parameterizations of the Mächler and Iqbal model. In addition, the total, direct and diffuse radiations in five climatological scenarios that could occur with these data were calculated.
DOI: 10.17632/mv3s66nkmb
title: Dataset for 'The Impact of a Western Diet High in Phosphate on the CKD-MBD in an Alport Syndrome Model'

description: This dataset contains the raw data supporting all figures used in the manuscript "The Impact of a Western Diet High in Phosphate on the CKD-MBD in an Alport Syndrome Model". A mouse model of Alport CKD and wild type littermates are fed either a Western-type high-phosphate diet or a standard vegetable-based diet. Data includes serum biochemistries, plasma protein levels, kidney histology quantifications, kidney mRNA and protein expression levels, and aorta mRNA expression levels.
DOI: 10.17632/2wnf2s35bc
title: Data for: X-ray tomography and numerical study on low-velocity impact damages of three-dimensional angle-interlock woven composites

description: Impact test data and finite element analyses modeling information have been uploaded in the zip file.
DOI: 10.17632/f7hbp4ykpb
title: Data for: Experimental Investigation of Surface Adhesion of Titan Analog Materials: Mitigation by Dust-Repellent Coatings

description: Raw data for particle accumulation on transparent windows with different dust-repellant coatings.
DOI: 10.17632/m4669v7cgw
title: Comparative Effectiveness of Short Contact (30-minute) Lidocaine-Prilocaine versus Lidocaine-Tetracaine Topical Anesthetic Mixtures for Cutaneous Pain Relief: A Randomized Controlled Trial

description: Supplemental Figure 1 and Supplemental Table 1 for "Comparative Effectiveness of Short Contact (30-minute) Lidocaine-Prilocaine versus Lidocaine-Tetracaine Topical Anesthetic Mixtures for Cutaneous Pain Relief: A Randomized Controlled Trial"
DOI: 10.17632/x6z969jwrj
title: Religious commitment on tolerance of homosexuality

description: Dataset on the relationship between religious commitment, tolerance of homosexuality, attitude towards advertisement, brand attitude and purchase intention
DOI: 10.17632/byjnr4kz5v
title: CNNpred: CNN-based stock market prediction using a diverse set of variables

description: This dataset contains several daily features of S&P 500, NASDAQ Composite, Dow Jones Industrial Average, RUSSELL 2000, and NYSE Composite from 2010 to 2017. It covers features from various categories of technical indicators, futures contracts, price of commodities, important indices of markets around the world, price of major companies in the U.S. market, and treasury bill rates. Sources and thorough description of features have been mentioned in the paper of "CNNpred: CNN-based stock market prediction using a diverse set of variables".
DOI: 10.17632/j3k2mctbnv
title: Semi-automatic crown delineation of abandoned orange trees - point cloud, Matlab source code, tree parameters

description: This dataset contains an algorithm (Matlab source code) for semi-automatic crown delineation of abandoned orange trees. Related data set, i.e. point cloud, is provided. Intermediate steps and final products are visualized. Reference data and parameters derived from 3D point clouds of abandoned orange groves are also provided with a detailed description.
DOI: 10.17632/k7c2sgmsj5
title: Rice Supply Chain in West Java Province, Indonesia

description: Data used to develop the DEA Model of the rice supply chain in West Java Province, Indonesia. The data is collected from five supply chain actors (farmers, rice millers, middlemens, wholesalers, and retails) in five regency in the West Java Province. The study that utilizes this data, aims to analyze the efficiency of the rice supply chain in West Java using the data envelopment analysis (DEA) method . The analysis shows that inefficiency exists in all supply chain points of the rice supply chain . Furthermore, the results show that various internal and environmental factors may be responsible for inefficiency at each point along the supply chain. Each obstacle is unique to the specific point within the supply chain.
DOI: 10.17632/vj3gv97fdv
title: CGE Model Data.

description: Simulating the impact effects of market-based electricity price increases on core 3E system variables (Zhang et al., JCP 2025):
1. Micro Social Accounting Matrix (SAM) Data for 2020.
2. Economic System Simulation Analysis Data.
Industry prices. Industry output. Corporate investment. Household consumption. Key macroeconomic variables.
3. Energy System Simulation Analysis Data.
Energy consumption. Energy intensity.
4. Environmental System Simulation Analysis Data.
Carbon emissions.
5. Sensitivity Analysis Data.
 The impact effects of electricity market reform under two policy scenarios, assuming a 20% increase in energy-capital substitution elasticity.
Sensitivity analysis-Industry prices. Sensitivity analysis-Industry output. Sensitivity analysis-Energy consumption. Sensitivity analysis-Carbon emissions.