cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/j5sj9wg2ym.1
title: Depression and coping strategies among parents of children with cancer

description: Background: Depressive symptoms have been reported to be more prominent in parents of children with cancer. This study aimed to determine the prevalence of major depressive disorder (MDD) and its association with socio-demographic factors and coping strategies among parents of children with cancer at Universiti Kebangsaan Malaysia Medical Centre (UKMMC) and Penang General Hospital (PGH). Methods: This was a cross-sectional study. Participants were enrolled according to inclusion and exclusion criteria and assessed on their socio-demographic profiles and children’s details. Patient Health Questionnaire (PHQ-9) was used to screen participants with high risk of depression. The diagnosis of MDD for those with high risk was established using the Mini International Neuropsychiatric Interview (M.I.N.I.), and coping strategies were assessed using Brief COPE scale. Results: A total of 162 parents participated in this study. 17.3% of participants screened high risk for depression were further assessed with M.I.N.I. The prevalence of MDD was 7.4%. Participants in the depressed group used denial (p= 0.000), behavioural disengagement (p= 0.002) and self-blame (p= 0.002) as their coping strategies more frequently than participants without depression. Use of denial was found to be the predictor of MDD (OR=2.12, p=0.008, CI=1.22, 3.68). Conclusion: Screening of parents of children with cancer for depression should not be overlooked.
DOI: 10.17632/4s7dncy6xb.1
title: Causality relationship between economic policy uncertainty and tourism in Mediterranean countries: evidence from dynamic symmetric and asymmetric bootstrap panel causality tests

description: Causality relationship between economic policy uncertainty and tourism in Mediterranean countries: evidence from dynamic symmetric and asymmetric bootstrap panel causality tests for this data set
DOI: 10.17632/sjp82gkxgz.1
title: Optuna Tuning Results PPO Reinforcement Learning Hyperparameters Performance

description: Systematic hyperparameter tuning using Optuna was expected to improve PPO model performance in a multi-microgrid environment. We hypothesized that optimizing hyperparameters like learning rate and network architecture would enhance model performance, reflected in increased mean reward and training stability.

Data Overview:

 Dataset: Results from hyperparameter tuning of a PPO model in a multi-microgrid environment
 Contents: Hyperparameter settings and performance metrics.

Data Collection Process:

 Sampling: Hyperparameters sampled by Optuna and tested by training PPO for 500,000 timesteps

Use the command tensorboard --logdir=./Logs/PPO_1 to visualize the data with TensorBoard.
DOI: 10.17632/m482gb564t.1
title: Heart disease

description: Acute myocardial infarction (AMI) is the main cause of death in developed and developing countries. AMI is a serious medical problem that necessitates hospitalization and sometimes results in death. Patients hospitalized in the emergency department (ED) should therefore receive an immediate diagnosis and treatment. Many studies have been conducted on the prognosis of AMI with hemogram parameters. However, no study has investigated potential hemogram parameters for the diagnosis of AMI using an interpretable artificial intelligence-based clinical approach. The purpose of this research is to implement the principles of explainable artificial intelligence (XAI) in the analysis of hematological predictors for AMI. In this retrospective analysis, 477 (48.6%) patients with AMI and 504 (51.4%) healthy individuals were enrolled and assessed in predicting AMI. Of the patients with AMI, 182 (38%) had an ST-segment elevation MI (STEMI), and 295 (62%) had a non-ST-segment elevation MI (NSTEMI). Demographic and hematological information of the patients was analyzed to determine AMI. The XAI approach combined with machine learning approaches (Extreme Gradient Boosting, XGB; Adaptive Boosting, AB; Light Gradient Boosting Machine, LGBM) was applied for the estimation of AMI and distinguishing subgroups of AMI (STEMI and NSTEMI). The SHAP approach was used to explain the predictions intuitively. After selecting the 10 most important hematological parameters for AMI, the LGBM model achieved 83% and 74% accuracy for prediction of AMI, and distinguishing subgroups of AMI (STEMI and NSTEMI), respectively. SHAP results showed that neutrophil (NEU), white blood cell (WBC), platelet width of distribution (PDW), and basophil (BA) were the most important for AMI prediction. Mean corpuscular volume (MCV), BA, monocytes (MO), and lymphocytes (LY) were the most important hematological parameters that distinguish STEMI from NSTEMI. The proposed model serves as a valuable tool for physicians, facilitating the diagnosis, treatment, and follow-up of patients with AMI and distinguishing subgroups of AMI (STEMI and NSTEMI). Analyzing readily accessible hemogram parameters empowers medical professionals to make informed decisions and provide enhanced care to a wide range of individuals.
DOI: 10.17632/9z52fv8ghd.1
title: Lunar Boulder Distribution Database

description: Version 1.0, September 9, 2019 Purpose: Created as part of a project funded by NASA’S Lunar Data Analysis Program (LDAP), the purpose of this dataset is to provide locations and diameters of boulders around small, young impact craters on the Moon. These boulder counts were conducted as part of a study aimed at determining regolith production rates and assessing landing site hazards, as discussed in the associated publications. Researchers are encouraged to read the publications and data description document to understand how the data was acquired and used. This database contains boulder distributions around small (&lt; 1 km), young (&lt; 200 Ma) lunar impact craters located near spacecraft landing sites. The most up-to-date database contains boulder diameters and coordinates for counts around Surveyor (Apollo 12), Cone (Apollo 14), North Ray (Apollo 16), South Ray (Apollo 16), Camelot (Apollo 17), and Zi Wei (Chang’e-3) craters. Boulders were manually identified and measured on Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images (Robinson et al., 2010) at scales of ~0.5-2 m/pixel. LROC NAC images allow for boulders ~1-2m in size and larger to be identified and measured. The tools for measuring boulders were CraterTools (Kneissl et al., 2011) and Crater Helper Tools (Nava, 2011), both developed for the ArcMap GIS platform. These boulder distributions are being used to understand boulder degradation rates on the lunar surface, and to assess landing site hazards for future surface missions to the Moon. This dataset is being archived in Mendeley Data and at the Planetary Data System (PDS) Cartography and Imaging Node for use in future boulder distribution and landing hazard studies. Future boulder counts and any refinements to existing measurements will be uploaded into subsequent versions of this dataset here and at the PDS IMG Annex: https://astrogeology.usgs.gov/search/map/Moon/Research/Regolith/lunar_boulder_data_bundle
DOI: 10.17632/xt5bjdhy5g.1
title: Speed Hump/Bump Dataset

description: The dataset consist of speed hump, bumps which has no markings and markings.
DOI: 10.17632/7bcdy75r2s.1
title: Supporting Data - Decision support for pest management: Using field data for optimizing temperature-dependent population dynamics models

description: This dataset contains all raw results, input data, algorithms and code scripts used in the making of the article named "Decision support for pest management: Using field data for optimizing temperature-dependent population dynamics models" published at Ecological Modelling.
DOI: 10.17632/rknjxtg2vn.1
title: High-Resolution Annotated Concrete Column Images for Object Detection

description: This dataset contains 501 high-resolution images of concrete columns captured from real buildings under construction in Iran. The photos were taken from approximately direct angles, providing clear views of the buildings' exteriors and focusing on the concrete columns located on the outer layer. Each image has been annotated with rectangular bounding boxes to highlight the exterior layer columns, which are at the built stage. The dataset is intended to facilitate detection tasks in machine learning and computer vision applications. The annotations, created using CVAT, are provided in YOLO format. This dataset is particularly valuable for researchers and practitioners working on object detection models, specifically in the fields of structural engineering, construction, and automated inspection systems.
Dataset Details:
• Total Images: 501
• Image Formats: JPEG and PNG
• Annotations: Each image is annotated with a single class representing the boundary box of the concrete columns on the exterior layer of the building. The annotations are provided in YOLO format, with labels as rectangular bounding boxes.
• Class: Outer Layer Concrete Column (Built Stage): 8,588 instances
• Bounding Box Format: YOLO (x_center, y_center, width, height, normalized by image dimensions)
DOI: 10.17632/dfj4f7fww4.1
title: Numerical analysis of heat flux through a double skin façade with controlled cavity temperature

description: This data set includes the hourly heat flux for variant boundary conditions of a double skin façade (DSF) with controlled- cavity temperature in a two- dimensional time- dependent study. The building element is subjected to varying boundary conditions, including different orientations (azimuth 0°, 90°, 180°, 270°) and weather conditions. This data set provides detailed numerical data on the hourly heat flux, temperatures attained at the exterior and within the building element for six different geometries and for the variant boundary conditions . The external boundary conditions were determined with the use of the PVGIS tool, whereas for the external surface temperature the sol-air temperature equation was applied. The numerical simulation was performed with the use of the finite element (FE) tool Comsol Multiphysics.
DOI: 10.17632/w3gztgrbjm.1
title: Electroencephalogram (EEG) dataset with internet addiction and healthy teenagers under rest and executive function task

description: A set of electroencephalogram (EEG) signals data obtained from NeuroSky. There are 30 participants (female = 15, male = 15) join the data collection.The EEG data were recorded through 6 protocols and 11 tasks. The six protocols are baseline(2 tasks), emotional state(4 tasks), memorize task, executive task, recall task, and baseline extension(2 tasks). We collected 12 minutes for each participant and separated the data into different tasks. The obtained data is used for analyzing the pattern of internet addiction. Further analysis of pre-processing, feature extraction and classification will be applied to the data.
DOI: 10.17632/58rydc6vwc.1
title: An EEG Dataset for Brainwave Recording During Emotion Elicitation via Video Clips

description: An EEG dataset for Recording Brain Electroencephalography Signals Based on Emotion Elicitation Video Clip with voice or without voice. unicorn hybrid black EEG device (8 channel) is used to record the data. of 30 participants (20 male and 10 female). In a research on emotion recognition, 30 participants—10 females and 20 males—were shown four different video clips that were intended to elicit different emotions: fear, sorrow, happiness, and neutrality. EEG signals were continuously captured for the whole two minutes of each movie. This recorded each subject's EEG activity for two minutes throughout each mood, showing how their brains responded to the emotional cues. Apart from regular sound-assisted movies, the research also featured four specially made emotion-transmitting videos for those who are deaf. This made it possible to analyze brain activity in great detail in response.
Data sets consist three folder namely EEG signals (RAW Data) , Participants information and Video clips.
DOI: 10.17632/rryh4gbp7g.1
title: Simultaneously acquired data from contactless and wearable devices for direct and indirect heart-rate measurement

description: Simultaneously acquired data from contactless and wearable devices for direct and indirect heart-rate measurement. For more details see related publication in Data in Brief journal by P.Pierleoni et al.
DOI: 10.17632/bh6x3z5gnj.1
title: Novel use of unique minerals to reveal an intensified methane seep during the Last Glacial Period in the South China Sea

description: Globally, research aiming to reveal the unique biogeochemical processes and gas hydrate potential in methane-seep areas is well established. Furthermore, the methane seeps discovered in the South China Sea (SCS) are widely studied and have achieved considerable results. In this study, we discovered a methane seep that was once active during the Last Glacial Period, particularly during the Last Glacial Maximum (LGM), and fixed at the seafloor for approximately 10 ka. This study integrated the features of glauconite fillings in foraminifera chamber, different morphologies of pyrites, unique framboid goethites (pyrite pseudomorphs), high chromium reducible sulfur content and extremely negative δ34S values between 121 and 231 cmbsf, molybdenum content and its correlation between TS and TOC, TS/TOC ratio of sediment, and results of AMS14C dating and carbon as well as oxygen isotopes of planktonic foraminifera analysis. The glauconite, usually regarded as a product associated with transgressive deposits and condensed sections, is widely found in the warm climatic intervals, such as the Paleocene Eocene Thermal Maximum. However, these intervals are generally associated with the methane emission events. Thus, our results demonstrated another mechanism for the formation of glauconite in methane seeps even during the LGM. Furthermore, the existence of framboid goethites implies that this methane seep has been subsiding since the end of LGM and few pyrites formed previously were reoxidized. Moreover, the crucial factor responsible for the aforementioned phenomenon is that the elevated hydrostatic pressure caused by the rising sea level, thereby promoting the gas hydrate potential to become stable again. Thus, the methane fluxes reduced and seep activity subsequently decreased. Notably, this study is the first to report a systematic investigation of methane-seep activity during the Last Glacial Period by the presence of authigenic minerals, such as glauconite and framboid goethite in SCS. Overall, our results showed a direct relation between methane-seep activity and climatic variation.
DOI: 10.17632/wt4s58xwj3.5
title: Tablets Manufacturing Processes: Multi-level multi-item capacitated lot-sizing with linked lot sizes and backlogging

description: This dataset contains anonymized data of nine tablets manufacturing processes. The dataset was created in June 2021 based on the research activities of the publisher's dissertation. Moreover, the dataset is stored in Excel and contains eleven sheets which contain all required information for capacitated lot-sizing. This data model for capacitated lot-sizing is generic and is able to store information for single- and multi-level problem instances. Furthermore, each tab consists of one table that maps to certain fields corresponding data. In particular, the provided problem instances can be translated into MIP coefficients of a problem instance for the single- and multi-level capacitated lot-sizing problem with linked lot sizes and backorders (CLSP-L-B and MLCLSP-L-B).
The problem instances MODEL001, MODEL002, MODEL003 and MODEL004 represent four CLSP-L-B. SET1, SET2, SET3, SET4 and SET5 represent five MLCLSP-L-B.

The four problem instances MODEL001 till MODEL004 are outlined and used in the article
M. Simonis and S. Nickel. A simulation–optimization approach for a cyclic production scheme in a tablets packaging process, Computers & Industrial Engineering 181 (2023) 109304. https://doi.org/10.1016/j.cie.2023.109304. 

The five problem instances SET1 till SET5 are outlined and used in the article
M. Simonis and S.Nickel, Integrated shelf-life rules for multi-level pharmaceutical tablets manufacturing processes, International Journal of Production Research (2024): 1-21. https://www.tandfonline.com/doi/pdf/10.1080/00207543.2024.2370510.


Data source files:
- data.xlsx: Anonymized real-world tablets manufacturing data
 - MODEL001: Single-level packaging robot (1)
 - MODEL002: Single-level packaging robot (2)
 - MODEL003: Single-level packaging robot (3)
 - MODEL004: Single-level packaging robot (4)
 - SET1: Two-level packaging robots (1 & 5)
 - SET2: Two-level bulking mixer with packaging robot (3 & 7)
 - SET3: Two-level bulking mixer with packaging robot (4 & 8)
 - SET4: Two-level packaging robots (2 & 6)
 - SET5: Three-level API/bulking and packaging machines (1 & 5 & 2 & 6 & 14)
DOI: 10.17632/6ydbk4f8kn.1
title: Data and Code for "Size-Adapted Bond Liquidity Measures and Their Assets Pricing Implications"

description: SAS code to calculate size-adapted bond liquidity measures.
The data set provides monthly functional forms and normalization factors that allow to calculate size-adapted liquidity measures for individual bonds without running the iterative procedure described in the paper.
DOI: 10.17632/k6v83s2xdm.1
title: NMC cell 2600 mAh cyclic aging data

description: The dataset contains the results of aging measurements of lithium-ion cells (NMC with a capacity of 2600 mAh) operating under various load and temperature conditions during full equivalent cycle. The data shows the influence of the cyclic operation parameters (ambient temperature, discharging current, depth of discharge, average charging current and actual state of health) on cell aging. Use of this data for publication purposes should include reference to the following article that describe the experiments conducted for generating the data: "A Novel Method for the Modelling of the State of Health of Lithium-Ion Cells Using Machine Learning for Practical Applications" Burzynski D., Kasprzyk L.
DOI: 10.17632/54htxm94bv.1
title: Temperature and Humidity Dataset of an East-Facing South African Greenhouse Tunnel

description: The aim of this study was to model the thermal characteristics of an east-facing greenhouse tunnel in South Africa. The tunnel used has a fan and wet wall on opposite ends and is used to cool the tunnel when temperatures reach a certain threshold. In this study, the authors' research hypothesis was the development of accurate empirical and analytical thermal models that would be validated using the available measured data. Three temperature and humidity sensors were placed near the fan, the wet wall, and in the middle of the 29-meter-long tunnel. The middle sensor's temperature measurements were used to control when the fan turned on and off. When the temperature reached above 30 degrees Celcius the fan was turned on, and when the temperature reached 22 degrees Celcius the fan was turned off. This created an 8-degree Celcius hysteresis band in which the fan and wet wall was controlled. The ``Training Set.csv`` file was used to train a Support Vector Regression (SVR) model to predict and simulate temperatures an hour in advance using previous predictions. ''Test Set.csv'' was used to validate and measure the accuracy of the SVR model. Also, the analytical model's accuracy was measured using the ``Test Set.csv`` file to quantitatively compare the two models. The test set and training set encompasses 42 days of measurements, aggregated with solar radiation and ambient temperature measurements that were captured by MeteoBlue (www.meteoblue.com). As this weather data was in an hourly format and the three temperature and humidity sensor data was in 5-minute intervals, the data from MeteoBlue was linearly interpolated for improved model training. For the ``Full Data Set.csv``, the data includes 162 days of only the three sensor's temperature and humidity measurements, and the fan and wet wall state.
DOI: 10.17632/ksvb32cvw6.1
title: Geopolymer Concrete Compressive Strength Data Set for ML

description: this data set was prepared as part of a scientific paper conducted on the prediction of geopolymer concrete compressive strength using NNs. the data includes various input features such as fly ash amount, NaOH amount, GGBFS amount, recycled aggregate amount and ... against compressive strength. the data was gathered through experimental means in the laboratory with same ingredient, equipment and operators thus may include high bias against more variant data sets. this data set can be used in AI and Machine Learning models to further study the properties of geopolymer concrete.
DOI: 10.17632/sm7fvt8hsg.2
title: A stromal cell-neutrophil axis promotes tumor-supportive bone marrow inflammation in newly diagnosed and treated myeloma

description: Cellranger output files (after soupx) and .RDS integrated datasets of single-cell RNA sequencing from: - the bone marrow myeloid compartment of newly diagnosed and treated individuals with multiple myeloma, as well as non-cancer controls - the bone marrow non-hematopoietic compartment of treated individuals with multiple myeloma, and previously published non-cancer controls
DOI: 10.17632/w26g5fkdx8.1
title: Vollger MR, Logsdon GA, et al. Ann Hum Genet. 2019

description: Vollger MR, Logsdon GA, Audano PA, et al. Improved assembly and variant detection of a haploid human genome using single-molecule, high-fidelity long reads. Ann Hum Genet. 2019; 1–16. https://doi.org/10.1111/ahg.12364
DOI: 10.17632/ysjwjvpnh3.1
title: augmentation data for DAISM

description: The purified dataset for data augmentation for DAISM-DNNXMBD can be downloaded from this repository.

The pbmc8k dataset downloaded from 10X Genomics were processed and uesd for data augmentation to create training datasets for training DAISM-DNN models. pbmc8k.h5ad contains 5 cell types (B.cells, CD4.T.cells, CD8.T.cells, monocytic.lineage, NK.cells), and pbmc8k_fine.h5ad cantains 7 cell types (naive.B.cells, memory.B.cells, naive.CD4.T.cells, memory.CD4.T.cells,naive.CD8.T.cells, memory.CD8.T.cells, regulatory.T.cells, monocytes, macrophages, myeloid.dendritic.cells, NK.cells).

For RNA-seq dataset, it contains 5 cell types (B.cells, CD4.T.cells, CD8.T.cells, monocytic.lineage, NK.cells). Raw FASTQ reads were downloaded from the NCBI website, and transcription and gene-level expression quantification were performed using Salmon (version 0.11.3) with Gencode v29 after quality control of FASTQ reads using fastp. All tools were used with default parameters.
DOI: 10.17632/8zh498bznr.1
title: MFT Framing Supplementary Material

description: Supplementary material
DOI: 10.17632/fpbfmc9vnm.2
title: Soil moisture and temperature data in agricultural soil

description: This data set contains measurements of soil moisture and temperature collected at a sugar cane crop field in Paraguay, 2022.

Data collected from 13:00:00 (UTC) on March 09th 2022 until 03:00:00 March 31st 2022 is presented. In the database, the time coordinate is expressed in hours, relative to the first measurement. It contains 15776 data points. The data is structured in two CSV files, defined as follows:

- First table: measurement data, with the following fields:
    - Timestamp 't', with format DD-MMM-YYYY HH:mm:ss.
    - Node identifier 'Node_ID', which is an integer from 1 to 12.
    - Temperature 'z_T', measured in Celsius degrees.
    - Soil moisture 'z_M', measured as a percentage.

- Second table: context data, with the following fields:
    - Node identifier 'Node_ID'.
    - Coordinate x measured in meters.
    - Coordinate y measured in meters.

According to the manufacturer's specifications, the noise in the measurements is less than 2%. The dataset is open to be used by any researcher, in studies related to machine learning, agricultural soil monitoring or estimation, and Spatio-temporal dynamics or processes governed by partial differential equations, among others.