cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/s62jkk3fkt
title: ACTi graphs: Datasets of physiological experiments associated with measurement on stress and energy expenditure

description: The database presented combines the data from the ActiGraphs worn by the test participants. During these tests, the participants wore three ActiGraphs placed on their ankle, waist and wrist. The published data is pre-processed data that has been processed in the ActiLife software. This database made it possible to compare energy expenditure with the number of mistakes made and with the participants' perception of stress.
The data is divided into folders, with each folder referring to a participant. Within each participant folder there are three folders and a file. Each folder stores the pre-processed data from the ACTiGraphs and is divided by the body zones where the sensors are placed (ankle, waist and wrist). The "performance.xlsx" file details the participant's performance during the test.
The pre-processed ACTiGraphs files show the counts of the sensor axis. These counts are calculated by the ACTiLife software, and the method of calculation is something that the company does not make public. There is also other information in these files, such as the indication of inclinometers and step counts, data that was not used in this study.
The "performace.xlsx" file describes the conditions and results of the tasks that each participant had to carry out. It details the start and end time of each task, the number of errors made while performing the task, and the environmental and noise conditions ("Temperature" and "Noise"). This file also records the answers to a stress questionnaire that was applied at the end of each task. This questionnaire can be found in the attached documents under "Stress Questionnaire.pdf". The "NoStress_Processing.py" is a python script that allow to process the data.
DOI: 10.17632/swx34r8gr4
title: Destination Image

description: the destination image is a key factor in the process of selecting destinations among tourists (Gunn, 1988; Hunt, 1975).
What are the components of destination image?
Components of destination image. In the article “Image Formation Process,” Gartner (1994) proposed that three components – cognitive, affective, and conative – compose a hierarchical causal model of destination image.
DOI: 10.17632/x29jnn8ppj
title: Master dataset

description: Guidelines recommend using a peripherally inserted central catheter for treatments ≥14 days; however, short peripheral catheters are often used instead. There is a lack of cost-effectiveness studies on their use and associated complications. Our aim was to conduct an economic analysis for this purpose. An economic evaluation study was conducted following local guidelines. A literature search was performed to assess the frequencies of catheter complications, resulting in 1053 papers, narrowing down the selection to 18 articles after independent peer review. Subsequently, experts on each complication were consulted, and a list of necessary items for catheter use was compiled to determine costs. A decision tree strategy model was designed using the TreeAge Pro2015 software tool. For each VAD, branches were constructed including probability nodes with the frequencies of major and minor complications, as well as the costs obtained. The results were measured using the incremental cost-effectiveness ratio. A univariate sensitivity analysis was performed using a tornado diagram, and a multivariate sensitivity analysis was conducted using Monte Carlo simulation. Higher costs were associated with catheter material and insertion by a radiologist. PICC appeared to be more effective for preventing minor complications. Total costs showed a tendency to decrease with nurse-led insertions and lower costs of catheter material in the two-way sensitivity analysis. Data suggests that PICCs are more effective in managing minor complications but come with higher costs. Increasing the utilization of these catheters for extended treatments could lead to reduced overall costs, and a decrease in the incremental cost-effectiveness ratio can be anticipated.
DOI: 10.6084/m9.figshare.26808055.v2
title: SLR Tables.xlsx

description: This systematic literature review addresses a crucial knowledge gap in research concerning the practical implementation of a Deep Learning model within the construction industry. Cost prediction models aim to provide Main Contractors with a reliable means to accurately estimate construction project costs. This research gains paramount importance considering the industry’s persistent inefficiencies which exhibit detrimental ripple effects on global markets. By adopting a systematic literature review approach, we have uncovered significant challenges related to the integration of the above-said ML-cost models in construction projects. The research also highlights relevant limitations, both systemic, and structural, and elucidates unbiased perceptions of this technology from the viewpoint of the Main Contractor.
DOI: 10.17632/jdw2mntc4s
title: Data for: Rainfall recharge thresholds in a subtropical climate determined using a regional cave drip water monitoring network

description: Observational dataset
DOI: 10.6084/m9.figshare.23138210.v1
title: Deep audio embeddings for vocalisation clustering

description: This dataset includes embeddings of animal vocalisations from different feature extraction methods (auto-encoder embeddings, predefined acoustic features, whole spectrograms). Each vocalisation has been assigned a label by an expert which describe its unit type (vocalisations of these animals come in discrete classes from a fixed repertoire). With this data, we study the relevance of vocalisation representations to cluster them by type, proposing methods to help in repertoire discovery and animal communication studies in general.<br> <br>
DOI: 10.17632/8d7pjd7f86
title: Data for: Operational processing of big satellite data for monitoring glacier dynamics. Case study Muldrow Glacier 

description: The four-dimensional flow displacement and flow velocity time series for Muldrow Glaciers in Alaska during October 2014 - November 2021 from Sentinel-1 SAR data.
DOI: 10.17632/mth8s8s6ww
title: i-CBM and OGM

description: The dataset includes data from three different tasks administered after priming participants for either global or local processing. In each file, the "group" variable represents the participant's priming condition: either global or local. The file "Demo+STAI+CAARS" provides demographic and clinical characteristics of the sample, including relevant measures. The file "GLTT" presents participant performance in the Global-Local Tendency Task, while the file "Rorschach" includes their responses in the Rorschach inkblot task. The "melodic global-local task" file details performance in the similarly named auditory processing task. The accompanying code file shows the analysis conducted across these datasets. As the code demonstrates, we found that global versus local priming had a significant impact on task performance across all three tasks.
DOI: 10.17632/f4fcrh4tn9
title: Data for: Short-term load forecasting by using a combined method of convolutional neural networks and fuzzy time series

description: This is hourly load data of the power supply company of the city of Johor in Malaysia generated in 2009 and 2010. This data has been used in the paper "Short-term load forecasting by using a combined method of convolutional neural networks and fuzzy time series", for Energy: The International Journal.
DOI: 10.17632/s4g2y7c7c7
title: Legacy and Emerging Plasticizers and Stabilizers in PVC Floorings - Rawdata

description: This dataset contains data acquisition methods, measured raw data, and processing scripts for the study "Legacy and emerging plasticizers and stabilizers in PVC floorings and implications for recycling". This study is published in ES&T (DOI: 10.1021/acs.est.3c04851).

Specifically these data are given:
• Supporting Information File 4 (SI4): Zip file containing Agilent method files for the GC-MS analyses.
• Supporting Information File 5 (SI5): Zip file containing python scripts for data analysis
• Supporting Information File 6 (SI6): Zip file containing the raw data from all conducted ATR FTIR measurements, as csv, spa, spc and dx files for each spectrum
• Supporting Information File 7 (SI7): Zip file containing the raw data from all GC-MS or-tho-phthalate quantification runs, as Agilent files for each run and Excel files from Mas-shunter quantification
• Supporting Information File 8 (SI8): Zip file containing the raw data from all GC-MS suspect screening runs, as Agilent files for each run and Excel files from Masshunter identification, Python semi-quantification and substance table
DOI: 10.17632/wc898ff5pj
title: Design of Mechanical Strength, Creep, and Triaxial Shear of Recycled Aggregate Concrete - Data-Driven Method Database

description: Dataset 1 includes data from 400 RAC samples, recording parameters compressive strength of RAC, and elastic modulus of aggregates.
 Dataset 2 comprises 238 data points obtained from measuring sample dimensions and temperature, confining pressure, back pressure applied during triaxial shear tests. 
 Dataset 3 collects 234 data points on the variation of elastic modulus of RAC concrete over curing time.
 Dataset 4 consists of 956 data entries documenting mix proportions It also records the compressive strength.
This data will be used to write review articles, research papers, case studies, and commentaries, and the source of the data is noted in the data set.
DOI: 10.6084/m9.figshare.1169941.v1
title: F# Data: Making structured data first-class

description: Accessing data in structured formats such as XML, CSV and JSON in statically typed languages is difficult, because the languages do not understand the structure of the data. Dynamically typed languages make this syntactically easier, but lead to error-prone code. Despite numerous efforts, most of the data available on the web do not come with a schema. The only information available to developers is a set of examples, such as typical server responses. We describe an inference algorithm that infers a type of structured formats including CSV, XML and JSON. The algorithm is based on finding a common supertype of types representing individual samples (or values in collections). We use the algorithm as a basis for an F# type provider that integrates the inference into the F# type system. As a result, users can access CSV, XML and JSON data in a statically-typed fashion just by specifying a representative sample document.
DOI: 10.17632/wf93wvy2vz
title: Model of the Bacillus anthracis S-layer EA1

description: The Gram-positive and spore-forming bacterium Bacillus anthracis is the etiological agent of anthrax, a deadly disease that today affects mostly wildlife and livestock. Its vegetative cells are covered in a surface layer or S-layer composed of two mutually excluding proteins, Sap and EA1, present in the exponential and stationary growth phases respectively. Using X-ray crystallography we generate a model of the EA1 monomer (PDB ID: 8OPR) that shows the EA1 S-layer assembly domain consists of a beads-on-a-string architecture of 6 immunoglobulin-like domains (D1 - D6), where calcium binding structures interdomain contact loops and allows the protomers to adopt their assembly-competent conformation. Here we deposit the 3D coordinates of the EA1 S-layer model, generated based on a low resolution 3D cryoEM map, and docking of the EA1 X-ray structure and rigid body domain reorganisation of EA1 domain D2 (res 292-396), and validation by directed mutagenesis. See Sogues et al. 2023 "Structure and function of the EA1 surface layer of Bacillus anthracis" for experimental details and full description of biological data.
DOI: 10.17632/zsvnzhf4hv
title: Lipidomics analysis in subcutaneous white adipose tissue from adipose-selective FASN-KO, ACC1-KO and MCD-KO and their respective flex/flox controls mice

description: Lipidomic analysis in inguinal white adipose tissue (iWAT) from adipocyte selective FASN, ACC1 and MCD KO mice and their respective controls. 
The results indicate the reduction of free palmitate by FASN and ACC1 deletion, but not MCD inactivation in adipocytes. Both FASN and ACC1 are key enzymes in de novo fatty acid biosynthesis in adipocytes. In addition, mass spectrometry analyses indicated the levels of acyl-CoAs and acyl-carnitines in iWAT from cAdFASN-KO, cAdACC1-KO, cAdMCD-KO and control mice.
DOI: 10.17632/9yfxj896mr
title: Data for: Access to resources to treat major trauma in low- and middle-income settings: a self-reported survey of acute care providers

description: Injury and violence is a neglected global health problem, despite being largely predictable and therefore preventable. This study aimed to indirectly describe and compare the availability of resources to manage major trauma between high-income, and low- to middle-income countries, as self-reported by delegates at the 2016 International Conference on Emergency Medicine held in Cape Town, South Africa. A survey was distributed to delegates at the International Conference on Emergency Medicine 2016, Cape Town to achieve the study aim. The survey instrument was based on the 2016 NICE guidelines for the management of patients with major trauma. It captured responses from participants working in both pre- and in-hospital settings. Responses were grouped according to income group (either high-income or low- to middle-income) based on the responding delegate’s nationality (using the World Bank definition for income group). A Fisher’s Exact test was conducted to compare delegate responses.
DOI: 10.6084/m9.figshare.4588525.v1
title: Supplementary Material for: Insights from Screening a Racially and Ethnically Diverse Population for Chronic Kidney Disease

description: <b><i>Background:</i></b> The value of chronic kidney disease (CKD) screening in the general population remains unclear but may be beneficial in populations with high disease prevalence. We examined risk factors for albuminuria among participants in a state-wide CKD screening program in Hawaii. <b><i>Methods:</i></b> The National Kidney Foundation of Hawaii Kidney Early Detection Screening (NKFH-KEDS) program held 19 CKD screening events from 2006 to 2012. Participants rotated through 5 stations during which sociodemographic, blood glucose, urine albumin-to-creatinine ratio (ACR), and spot urine albumin data were collected. Multivariate logistic regression analyses (adjusted for age, sex, race/ethnicity, body mass index [BMI]) were used to identify clinical predictors of abnormal ACR (≥30 μg/mg) and abnormal spot urine albumin (&gt;20 mg/L) levels. <b><i>Results:</i></b> Among 1,190 NKFH-KEDS participants who met eligibility criteria, 13 and 49% had abnormal ACR and urine albumin levels, respectively. In multivariate logistic regression analyses, participants of older age (&gt;65 years), Asian and Pacific Islander race/ethnicity, BMI ≥30 kg/m<sup>2</sup>, and with hypertension had higher risk of abnormal ACR. Being of older age; Asian, Pacific Islander, and Mixed race/ethnicity; and having diabetes was associated with higher risk of abnormal urine albumin levels in adjusted analyses. <b><i>Conclusions:</i></b> NKFH-KEDS participants of older age; Asian and Pacific Islander race/ethnicity; and with obesity, hypertension, and diabetes had higher risk of kidney damage defined by elevated ACR and urine albumin levels. Further studies are needed to determine whether targeted screening programs can result in timely identification of CKD and implementation of interventions that reduce cardiovascular disease, death, and progression to end-stage renal disease.
DOI: 10.17632/dxpymzkzzc
title: Data for: The dynamic relationship among environmental regulation, innovation, CO2 emissions, population, and economic growth in OECD countries: A panel investigation

description: Data on the Co2, Pop and GDPpc are from the World Development Indicators (The World Bank, 2018), and data on the rest of the variables are from OECD statistics (OECD, 2018).
DOI: 10.17632/pdnjz7zz5x
title: Data for: Modern day monitoring and control challenges outlined on an industrial-scale benchmark fermentation process

description: This data was generated using an advanced mathematical simulation of a 100,000 litre penicillin fermentation system referenced as IndPenSim. All details describing the simulation are available on the following website: www.industrialpenicillinsimulation.com. IndPenSim is the first simulation to include a realistic simulated Raman spectroscopy device for the purpose of developing, evaluating and implementation of advanced and innovative control solutions applicable to biotechnology facilities. This data set generated by IndPenSim represents the biggest data set available for advanced data analytics and contains 100 batches with all available process and Raman spectroscopy measurements (~2.5 GB). This data is highly suitable for the development of big data analytics, machine learning (ML) or artificial intelligence (AI) algorithms applicable to the biopharmaceutical industry. The 100 batches are controlled using different control strategies and different batch lengths representing a typical Biopharmaceutical manufacturing facility: Batches 1-30: Controlled by recipe driven approach Batches 31-60: Controlled by operators Batches 61:90: Controlled by an Advanced Process Control (APC) solution using the Raman spectroscopy Batches 91:100: Contain faults resulting in process deviations. A Jupyter-notebook can be found here that downloads and plots the data: https://github.com/StephenGoldie/indpensim-notebook.git Batch reference of data is found under: 2-PAT control(PAT_ref:PAT ref) Please reference: Goldrick S., Stefan, A., Lovett D., Montague G., Lennox B. (2015) The development of an industrial-scale fed-batch fermentation simulation Journal of Biotechnology, 193:70-82. and Goldrick S., Duran-Villalobos C., K. Jankauskas, Lovett D., Farid S. S, Lennox B., (2019) Modern day control challenges for industrial-scale fermentation processes. Computers and Chemical Engineering. Additionally help publicise this work on the following platforms: Twitter: @Stephen_Goldric Github: StephenGoldie LinkenIn: Stephen Goldrick - Post Doc @UCL Biochemical Socitey
DOI: 10.17632/jmhghbpvjb
title: Dataset on Higher Education Access and Population Distribution in Seven Campuses in Colombia.

description: This dataset presents demographic information of 16,012 students admitted to various regional campuses of the Universidad Nacional de Colombia. The data are compared against departmental population statistics from the Colombian National Administrative Department of Statistics (DANE). 

The dataset enables comparative analysis of higher education access gaps by employing Gini index calculations to quantify inequality and examine the impact of students’ school background, age, and socioeconomic status. The objective is to identify disparities in access among citizens aged 20–39 compared to the population admitted to higher education programs.
DOI: 10.17632/8cmtngfjx7
title: Grantha binarization dataset

description: The dataset includes 10 images of Grantha palm images and the corresponding ground truth created for binarization purpose.
DOI: 10.17632/bzst5thr89
title: Data for: Survey dataset on the level of sustainable consumption of Malaysian households from the perspective of income and consumption expenditure

description: Dataset for sustainable consumption of Malaysian households
DOI: 10.17632/xrszyw6xk2
title: Mediating Role of Consumer Innovativeness toward Health Protective Behaviours in Private Healthcare

description: Data was analysed by using both SPSS and PLS-SEM.
DOI: 10.6084/m9.figshare.4468583.v3
title: Sistem Persamaan Linier Dua Variabel

description: SPLDV
DOI: 10.15468/dl.t6tff2
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Morina chinensis (Batalin ex Diels) Y.Y.Bai",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 32 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012885-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/fs7mtkg2wk
title: Dataset of Deep Learning from Landsat-8 Satellite Images for Estimating Burned Areas in Indonesia

description: The dataset consist of three categories; image subsets, burned area masks and quicklooks. The image subsets are derived from Landsat-8 scenes taken during the years 2019 and 2021. Each image has a size of 512x512 pixels and consists of 8 multispectral. The sequence of band names from band 1 to band 7 of the image subset is same as the sequence of band names of landsat-8 scene, except for band 8 of the image subset which is band 9 (cirrus band) in the original landsat-8 scene. The image subsets are saved in GeoTIFF file format with the latitude longitude coordinate system and WGS 1984 as the datum. The spatial resolution of image subsets is 0.00025 degree and the pixel values are stored in 16 bit unsigned integer with the range of value from 0 to 65535. The total of the dataset is 227 images which containing object of burned area surrounded by various ecological diversity backgrounds such as forest, shrub, grassland, waterbody, bare land, settlement, cloud and cloud shadow. In some cases, there are some image subsets with the burned areas covered by smoke due to the fire is still active. Some image subsets also overlap each other to cover the area of burned scar which the area is too large.
The burned area mask is a binary annotation image which consists of two classes; burned area as the foreground and non-burned area as the background. These binary images are saved in 8 bit unsigned integer where the burned area is indicated by the pixel value of 1, whereas the non-burned area is indicated by 0. The burned area masks in this dataset contain only burned scars and are not contaminated with thick clouds, shadows, and vegetation. Among 227 images, 206 images contain burned areas whereas 21 images contain only background. The highest number of images in this dataset is dominated by images with coverage percentage of burned area between 0 and 10 percent.
Our dataset also provides quicklook image as a quick preview of image subset. It offers a fast and full size preview of image subset without opening the file using any GIS software. The quicklook images can also be used for training and evaluating the model as a substitute of image subsets. The image size is 512x512 pixels same as the size of image subset and annotation image. It consists of three bands as a false color composite quicklook images, with combination of band 7 (SWIR-2), band 5 (NIR), and band 4 (red). These RGB composite images have been performed contrast stretching to enhance the images visualizations. The quicklook images are stored in GeoTIFF file format with 8 bit unsigned integer.

This work was financed by Riset Inovatif Produktif (RISPRO) fund through Prioritas Riset Nasional (PRN) project, grant no. 255/E1/PRN/2020 for 2020 - 2021 contract period.
DOI: 10.17632/n9t823m5c8
title: Catenary action in strip-reinforced wood beams

description: This study evaluated the catenary action in strip-reinforced wood beams, with tests carried out on carbon-fibre reinforced beech clearwood beams in a three-point bending setup. Experimental data for this study are available for download here.