cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/dwj7hg3dt2
title: FORECASTING MODEL OF VIETNAMESE CONSUMERS’ PURCHASE BEHAVIOR OF DOMESTIC APPAREL

description: The study of the determinants of consumer purchase decisions of domestic goods is necessary in the context of Vietnams’ international integration in order to support domestic firms improve their competitiveness. This study aims to analyze factors influencing Vietnamese consumers’ purchase decision of domestic apparel based on Binary Logistic regression model. This study uses survey data gathered from 240 consumers in Vietnam in 2019. Research results showed that i) Perceived price, ii) Perceived quality, iii) Consumer ethnocentrism, and iv) Demographic variables (age; the family with child; the level of education; income; and sex) have significant influences on the consumer purchase decision of domestic products in Vietnam.
DOI: 10.17632/fp6fryn7h3
title: Data and code for "Equity duration and predictability"

description: This folder contains data and code from the replication package of the paper "Equity duration and predictability'' by Benjamin Golez and Peter Koudijs.
DOI: 10.17632/nyxndvwfsh
title: Large Language Model-Driven Narrative Generation Study Data: ChatGPT-Generated Narratives, Real Tweets, and Source Code

description: In the interests of advancing Large Language Models (LLMs) usage in engineering, science, and medicine, and other fields, we provide the data sets and code associated with the Structured Narrative Prompt for LLMs Study. Data for this study was generated using an Agent-Based Model (ABM), the LLM ChatGPT, and using a set of tweets previously collected from Twitter. To facilitate reproducibility, transparency, and reuse of our work, this repository includes: 
 (1) Simulation-related code and data for generating simulated agents' life events
 (a) output from the Java ABM simulation, including the ABM-generated narratives and associated life-event information
 (2) ChatGPT-related code and data
 (a) the Python script that generates structured prompts for ChatGPT from the ABM-generated life events
 (b) the set of generated structured prompts (inputs) for ChatGPT, (used to generate the LLM narratives)
 (c) the Python script that submits the structured prompts to ChatGPT via the API
 (d) the set of ChatGPT-generated narratives
 (e) the Python script that combines ChatGPT (output) narratives with the ABM simulation narratives, in preparation for PANAS sentiment analysis
 (3) Analysis-related code and data
 (a) the PANAS sentiment analysis R scripts
 (b) the statistical significance test R scripts (Chi-squared test and Fisher's exact test), used for finding significant differences in sentiment scoring among ABM-generated narratives, LLM-generated narratives, and the real tweets
 (a) the PANAS lexicon used for the sentiment analysis
 (b) the set of utilized tweets with PII removed
 (c) the approved IRB documentation for collecting those tweets

Folder Names/Breakdown for Data File section:
1. LLM-related Scripts and Data: LLM_Phase_Scripts_and_Data.zip
2. Analysis-related Scripts and Data: Analysis_Phase_Scripts_and_Data.zip
DOI: 10.17632/r2f8g2v272
title: Experimental Investigation of Innovative Layered Design for Moisture-Resistant Multi-Material Additive Manufacturing

description: Moisture Absorption Analysis
Table shows the moisture absorption behavior of five different material configurations (A–E) subjected to two environmental conditions—elevated temperature (70°C) and room temperature (23°C)—over a 7-day exposure period. The results indicate significant differences in moisture uptake patterns across configurations and temperatures. Configuration A at 70°C exhibited the highest moisture absorption, reaching 10.00 units by Day 7, while Configuration B showed the lowest at 0.59 units, suggesting a relatively hydrophobic nature or protective structure. In general, all configurations absorbed more moisture at 70°C compared to 23°C, highlighting the temperature's accelerating effect on diffusion and hygroscopic activity. Notably, the absorption trends for each configuration appear linear or quasi-linear over the duration, particularly for configurations with higher uptake.
DOI: 10.17632/tdx3h2fn9v
title: Mammogram Density Assessment Dataset

description: GENERAL OVERVIEW
This dataset was compiled to address the limitations of current methods for breast density assessment in mammograms, especially the challenges of:
• Shortage of radiologists: There are not enough radiologists to efficiently analyze the large number of mammograms needed for screening.
• Subjectivity: Radiologist assessments of breast density can vary, leading to inconsistencies.
• Limitations of existing tools: Current CAD tools for breast density estimation often have limitations, such as restricted functionality to specific mammogram views and difficulties with accurate segmentation.

This dataset offers a unique solution by expanding the original mammogram images with:
• Binary masks of the breast area: These expert-annotated masks precisely delineate the entire breast region in each mammogram, providing valuable ground truth data for segmentation methods.
• Binary masks of dense tissue: Similarly, these masks accurately identify areas of dense tissue within each mammogram, further enhancing the dataset's utility for training and evaluating segmentation algorithms.

The dataset facilitates the development of automated breast density estimation with deep learning. It also serves as a valuable tool for researchers developing and benchmarking medical image segmentation methods specifically focused on breast tissue analysis in mammograms. 

DATA DESCRIPTION
This dataset consists of segmentation masks for dense tissue and breast area as well as area-based breast density percentage values from the VinDr-Mammo public dataset accessible from [3]. All annotations were performed and validated by an expert radiologist.
Files:
The data is provided in two compressed archives, ‘train.zip’ and ‘test.zip’.
• train.zip: This archive contains two sub-folders:
 - breast_masks: This sub-folder contains the ground truth segmentation masks for the breast area, also in JPG format.
- dense_masks: This sub-folder contains the ground truth segmentation masks for the dense tissue, again in JPG format.
 The segmentation masks have the dimensions of 2800×3518 pixels.

File Lists:
Two CSV files are provided alongside the compressed archives:
• train.csv: This file contains information about the training set with two columns:
- Filename: This column contains the filenames of the training set images. These images can be directly downloaded from the VinDr-Mammo dataset, https://physionet.org/content/vindr-mammo/1.0.0/.
- Density: This column provides the ground truth continuous breast density value for each mammogram in the training set, intended for the breast density estimation task.

• test.csv: This file contains a single column, “Filename”, listing the filenames of the test set. No ground truth information is provided for the test set. Ground truths are intentionally kept private for Breast Density Kaggle Challenge https://www.kaggle.com/competitions/breast-density-prediction, however, will be eventually open to public in the dataset repository.
DOI: 10.17632/nyf3pcc7bx
title: Whole exome sequencing of apocrine adenocarcinoma

description: Whole exome sequencing of apocrine adenocarcinoma
DOI: 10.17632/sx23zmtcxv
title: MAMA : MAternal Mood Assessment survey for healthcare professionals

description: The Maternal Mood Assessment (MAMA) is a thorough evaluation tool aimed at healthcare professionals for measuring their know-how, attitudes, and experiences about perinatal depression. The survey is broken down into different sections, each zeroing in on a specific aspect of the topic. The first part gathers basic info like age, gender, and career credentials of the healthcare workers, along with where and how long they've been practicing. Section two focuses on training and hands-on experience dealing with perinatal depression. This covers whether their workplace has a set care path for such cases, if they've had specialized training, and how often they've seen diagnosed mothers. The third section is about understanding and attitudes toward perinatal depression. It asks about definitions, perceived prevalence, risk factors, and best practices for a good relationship with affected mothers. The fourth section gets into the healthcare pros' own experiences and feelings when handling these cases. Questions look at their initial reactions, interactions with the family, and thoughts on effective support methods. The final part asks for opinions on various management aspects, like breastfeeding, dad's role, involvement of different healthcare roles, and the need for guidelines. Overall, the MAMA survey offers valuable insights into healthcare professionals' views and experiences, useful for shaping interventions and training.
DOI: 10.6084/m9.figshare.3546873.v1
title: Appendix B. Results of the one-factor ANOVA among different desirable states on the density of the nine common bird species.

description: Results of the one-factor ANOVA among different desirable states on the density of the nine common bird species.
DOI: 10.17632/m594s3s5h7
title: Cyclic uniaxial cell stretching in tissue culture using a LEGO®-based mechanical stretcher and a polydimethylsiloxane stretchable vessel (STAR-PROTOCOLS-D-20-00412)
DOI: 10.17632/tgy3v7syct
title: Data for: Modelling and field testing of back-flow fracturing fluid after acid fracturing in Oil Shale reservoirs

description: In the field experiment site of the in-situ pyrolysis of oil shale, there are three wells. One well is used to inject high temperature and high-pressure nitrogen gas. The other one, named FK-2, is a well that is used to produce oil and gas products. The last well is a monitoring well named M1 for the real-time monitoring of the underground temperature and water inflow. According to the microseismic monitoring at the fracturing site, we have determined that the fracturing may have formed two fractures in the oil shale formation. Because the in situ pyrolysis process of oil shale requires nitrogen injection at a high temperature and pressure, we must monitor the connectivity between the two fractures. There is no need to use high temperature gas to determine the formation connectivity, so we only use high-pressure nitrogen gas. First, the backflow of the fracturing fluid is conducted. After the fracturing fluid backflow, we can determine the connectivity and water inflow of the formation. Based on the microseismic monitoring data, we built a three-dimensional model. The flow field of the high-pressure nitrogen injection into well FK-1 and the gas production from well FK-2 were simulated using the finite element software COMSOL Multiphysics 5.3. The results show that the outlet pressure at the FK-2 well can reach 2.8 MPa when well FK-1 is used as a high-pressure nitrogen injection well and gas is continuously injected at 8.5 MPa. Part of the fracturing fluid flows out of well FK-2, but some of fluid can flow into the formation. When high-pressure nitrogen is injected into the FK-2 well, the result is also the same. To verify the accuracy of the simulation results, experiments were carried out involving high-pressure nitrogen injection into well FK-1. The fracturing fluid volume was monitored while the fracturing fluid flowed back, and the pressure change in well FK-2 was monitored in real time. Finally, the pressure in well FK-2 could reach 2.8 MPa, which proved the connectivity between the two wells. It also confirmed the accuracy of the numerical simulation. In addition, we monitored the pressure changes in the FK-2 well by means of active pressure relief in FK-1 well. The results show that the pressure in the FK-2 well would also decrease, which once again confirms the connectivity status of the two wells.
DOI: 10.6084/m9.figshare.6373757.v1
title: Data for Comparison of OTFS and OFDM in sub-6GHz and mmWave Line-of-Sight Mobility Channels

description: Data set for "Comparison of OTFS and OFDM in sub-6GHz and mmWave Line-of-Sight Mobility Channels"
DOI: 10.17632/cdyygzjcky
title: Hajj Dataset 2021-2024: Ministry of Religious Affairs Malang City

description: The Hajj Dataset 2021-2024: Ministry of Religious Affairs Malang City contains comprehensive data on the Hajj pilgrimage process for 2021 through 2024, gathered explicitly from the Malang City branch of Indonesia's Ministry of Religious Affairs (Kemenag). This dataset captures key information about the Hajj pilgrimage, including payment records, associated costs, and demographic details of the pilgrims, providing valuable insights into the financial aspects and trends over the four years.
Key Data Features:
Yearly Hajj Costs: Information on the financial breakdown of Hajj costs for each year, covering all components, including transportation, accommodation, and other mandatory fees.
Pilgrim Demographics: Data on the number and characteristics of pilgrims from Malang City, including age, gender, and other socioeconomic indicators.
Payment Status and History: Records of payments made by the pilgrims detailing the timing, amount, and any outstanding balances.
Regulatory Changes: Information on changes in the regulations and policies of the Ministry of Religious Affairs (Kemenag) that may have impacted the cost structure or payment schedule during this period.
Inflation and Currency Impact: Data reflecting the impact of national inflation rates or currency fluctuations, particularly the value of the Indonesian Rupiah (IDR) relative to the Saudi Riyal (SAR), on the overall pilgrimage cost.
Hajj Quota and Registrations: The number of Hajj applicants from Malang City and the annual quota allocated to the region, including details on the selection process and waiting periods.
Potential Use Cases:
Cost Prediction: Analyze cost trends and predict future financial needs for the Hajj pilgrimage.
Policy Analysis: Assess the impact of government policies on the affordability and accessibility of Hajj for pilgrims.
Economic Analysis: Understand how national economic factors (inflation and and exchange rates) affect pilgrimage costs.
Social Research: Study demographic patterns and regional participation in Hajj from Malang City.
This dataset provides an essential resource for anyone interested in the economic, social, and policy dimensions of the Hajj pilgrimage in Indonesia, particularly in the context of Malang City's unique data.
DOI: 10.17632/d5gkm3tk6p
title: JAAD-D-21-00201 Supplemental Materials

description: Supplemental Material for JAAD-D-21-00201. (Bittar et al. Systematic Review and Meta-Analysis of Local Recurrence Rates of Head and Neck Cutaneous Melanomas after Wide Local Excision, Mohs Micrographic Surgery, or Staged Excision. J Am Acad Dermatol. 2021)
DOI: 10.17632/h2tvxc7svd
title: Evidence of motor resonance in stroke patients with severe upper limb function impairments: stimuli and data

description: Patients with severe upper limb function impairments and matched controls were presented with videos showing grasping movements, and requested to press a key at the contact time between the hand and the object (i.e., action prediction time). In half of the trials the kinematics of the videos was kept unchanged and the object replaced with an ungraspable one. The instant in which the hand touched the object in the different videos was always the same.

This experimental paradigm has proved capable of providing neurophysiological and behavioural indices of the presence of motor resonance (i.e., sub-threshold simulation of the observed action) in healthy individuals. Specifically, corticospinal activation was present only when the observed movement was suitable to grasp the object, and in the same trials the response times were more accurate (i.e., the time lag between the instant the agent touched the object and the response was shorter), an index of action prediction (Craighero et al., 2014, doi.org/10.1080/13506285.2014.904460). It is assumed that a modulation of response times in this experimental paradigm is an indirect evidence of motor resonance.

All participants were asked to perform the task with both hands. Despite the serious difficulty of movement, 8 out of 18 patients were able to perform the task with their impaired hand. We found that the responses given by the paretic hand showed a modulation of the action prediction time no different from that showed by the no paretic hand, which, in turn, did not differ from that showed by the matched control participants. 

These results indicate that action observation involves the efferent motor system even when the hand used to respond is unable to perform the observed action due to a cortical lesion.
DOI: 10.17632/hgvxn3rck7
title: Raw data for Comparison of Self-reported Measures of Hearing to an Objective Audiometric Measure in Adults in the English Longitudinal Study of Ageing (ELSA)

description: Raw data, computed data and statistical code for all main analyses and subgroup analyses presented in JAMA Netw Open. 2020;3(8):e2015009. doi:10.1001/jamanetworkopen.2020.15009 Data sharing statement: Access to The English Longitudinal Study of Ageing (ELSA) dataset is publicly available via the UK Data Service (https://www.ukdataservice.ac.uk) Note: Statistical code to create the subcategories of some demographic variables included in the analyses (e.g. age categories of participants) may not be available in the current dataset. Additional statistical code is available from the corresponding author upon reasonable request at: dialechti.tsimpida@manchester.ac.uk
DOI: 10.17632/hgwshjbcw6
title: JAX-FEM: A differentiable GPU-accelerated 3D finite element solver for automatic inverse design and mechanistic data science

description: This paper introduces JAX-FEM, an open-source differentiable finite element method (FEM) library. Constructed on top of Google JAX, a rising machine learning library focusing on high-performance numerical computing, JAX-FEM is implemented with pure Python while scalable to efficiently solve problems with moderate to large sizes. For example, in a 3D tensile loading problem with 7.7 million degrees of freedom, JAX-FEM with GPU achieves around 10× acceleration compared to a commercial FEM code depending on platform. Beyond efficiently solving forward problems, JAX-FEM employs the automatic differentiation technique so that inverse problems are solved in a fully automatic manner without the need to manually derive sensitivities. Examples of 3D topology optimization of nonlinear materials are shown to achieve optimal compliance. Finally, JAX-FEM is an integrated platform for machine learning-aided computational mechanics. We show an example of data-driven multi-scale computations of a composite material where JAX-FEM provides an all-in-one solution from microscopic data generation and model training to macroscopic FE computations. The source code of the library and these examples are shared with the community to facilitate computational mechanics research.
DOI: 10.17632/jrhww36ccv
title: A transferrable machine learning interatomic potential for nanoporous carbon nitride nanosheets

description: The "P.mtp" is the trained MTP, in which atomic types of 1, 2 and 3, refer to: C, N and H, respectively, in the LAMMPS input-data. 
The "Light_P.mtp" is a MTP with a lower computational cost, which can be used for the large scale calculations at high temperatures. 
The "Train.cfg" and "Train.xyz" are the complete dataset in the "cfg" and "xyz" formats. In the "cfg" format, the atomic types of 1, 6 and 7, refer respectively to, H, C and N.
DOI: 10.17632/4ztc7yxngf
title: MEA data

description: GENERAL INFORMATION: The L_0*.zip folders contain data from thousands of seconds (each) recording sessions. Unzip these folders to individual sessions of spontaneous activity recordings (L_Prg034, L_Prg035, …). Continuously recorded sessions are indexed consecutively; together, the zipped folders give access to data sampled over several days from rat cortical neurones in culture, 2-3 weeks following plating day (1st day postpartum). Detailed instructions in "readme Data 1.0 .rtf"
DOI: 10.17632/mmnbt5b64j
title: Sustainable Blood Supply Chain Network Design Problem

description: Sustainable Blood Supply Chain Network Design Problem, the small-size data set
DOI: 10.17632/nnsf5n3wht
title: PumpKin: A tool to find principal pathways in plasma chemical models

description: Abstract PumpKin is a software package to find all principal pathways, i.e. the dominant reaction sequences, in chemical reaction systems. Although many tools are available to integrate numerically arbitrarily complex chemical reaction systems, few tools exist in order to analyze the results and interpret them in relatively simple terms. In particular, due to the large disparity in the lifetimes of the interacting components, it is often useful to group reactions into pathways that recycle the fastest... Title of program: PumpKin Catalogue Id: AETG_v1_0 Nature of problem Analyzing complex chemical models. Versions of this program held in the CPC repository in Mendeley Data AETG_v1_0; PumpKin; 10.1016/j.cpc.2014.05.019 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)
DOI: 10.17632/v3sz8rd2w3
title: Video-1

description: Demonstration of earlobe piercing using an intravenous catheter and procedure to secure the ends by an elastic adhesive bandage
DOI: 10.17632/8265mvnfxg
title: "Firm Input Choice Under Trade Policy Uncertainty", JIE 2023, Kyle Handley, Nuno Limão, Rodney D. Ludema and Zhi Yu

description: Replication Package for “Firm Input Choice Under Trade Policy Uncertainty” By Kyle Handley , Nuno Limão , Rodney D. Ludema and Zhi Yu November 2023
DOI: 10.17632/vpfjk6vysb
title: Theoretical framework of the two-stage MCDM, belongs to the article "Sustainable Development of Electricity Charging and Hydrogen Fueling Stations for Pakistan: A Multi-Criteria Decision-Making Approach"

description: The attached file contains the theoretical framework of the two-stage MCDM, which belongs to our manuscript "Sustainable Development of Electricity Charging and Hydrogen Fueling Stations for Low Carbon Cities: A Multi-Criteria Decision-Making Approach"
DOI: 10.17632/6w8g5vxndr
title: Herding and Divergent Behaviors in Competition: An Experimental Study

description: The dataset consists of three files:

The "Jane and Jill" oTree experiment data
The Prolific demographic data
The Coin Lab experiment data
DOI: 10.17632/n88z47fvc8
title: Seascape_I_DS_v010720

description: 1. 'Seascape_esl_v010720.xls': Generalised Pareto Distribution segment parameters with confidence interval estimates 2. 'Seascape_DIVAdb_v010720.xls': area01-20: segment area for 1 metre elevation bins 0-1 m,1-2 m etc., lati: latitude, length: segment length (km), longi: longitude, pop01:20: population number at elevations, uplift: vertical land movement rate, dikeheight_xxx: dike height (m), tide_gauge: closest tide gauge, floplidXXm: floodplain ID, duneheights_XX: dune heights (m), primary_defence: max(dikeheight, duneheight) 3. 'Floodplains_v010720.xls': rID: floodplain ID, rFLOPLID: corresponding 4-metre FLOPLID, rFSID: state identified, poprXX: aggregated segment population of elevation bin, assetrXX: monetary floodplain assets at elevation, hmin: minimum flood defence height, havr: average flood defence height, hmax: maximum flood defence heigth, lenghtr: floodplain length (km), H200k_X: 200-year return level estimates, upliftr: floodplain uplift rate 4. 'Strategies_v010720.mat': delta: discount rate, hAftAll: optimal floodplain strategies, 249 rID x 45 scenarios x 177 years 5. 'PVI_PVD_v010720': PVIall, present value of investment & maintenance costs of 249 optimal floodplain strategies x 45 scenarios, PVDall, present value of expected flood damages of 249x45 optimal scenario strategies under 45 scenarios (249x45x45), scencombi: scenario combination of socioeconomic uncertainty, extreme sea-level uncertainty, SLR uncertainty