cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/btdpmw96hg
title: Reliability of visual observation to classify continuous wavelet transforms of signals of extremity movements

description: This dataset accompanies the research study titled "Reliability of visual observation to classify continuous wavelet transforms of signals of extremity movements." The primary aim of this work is to investigate the feasibility and consistency of human visual assessment of accelerometer-derived time-frequency signals in evaluating motor abnormalities, particularly in individuals diagnosed with Parkinson’s disease (PD) compared to healthy individuals with typical development (TD).

The dataset comprises continuous wavelet transform (CWT) images that were generated from raw accelerometer signals collected during a series of standardized motor tasks. These tasks, adapted from the Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), included repetitive movements such as finger tapping, toe tapping, pronation-supination, hand movements, and leg agility. Participants were equipped with low-cost wearable sensors, taped directly to their extremities, as described by McKay et al. (2019). These sensors captured high-resolution, continuous movement data during in-person clinical assessments.

The raw accelerometer signals were processed and converted into continuous wavelet transforms, creating two-dimensional time-frequency images that visualize the movement patterns. These CWT images served as the basis for a blinded observational analysis. A group of 31 trained raters—who were blinded to all participant-specific information, including age, sex, clinical diagnosis, and which limb the signal was collected from—systematically scored each image for signs of motor dysfunction. Specifically, raters evaluated each image for abnormalities across three parameters: amplitude, frequency, and interruptions in the movement signal.

This methodology builds upon and extends previous research by Hernandez et al. (2022) and Ziegelman et al. (2023), who demonstrated that visual interpretation of wavelet-transformed sensor data could be a viable remote assessment tool for movement disorders. Statistical validation of inter-rater reliability was carried out using Cronbach’s alpha and intraclass correlation coefficients (ICC), with analysis performed using IBM SPSS Statistics version 30.0.0. The high ICC values observed in this study support the reproducibility and reliability of this visual classification approach.

Moreover, this work reinforces and expands upon findings by Elshourbagy et al. (2023), who previously assessed the feasibility of using similar low-cost, sensor-based technologies for remote motor evaluations. It also complements the clinically validated MDS-UPDRS framework outlined by Goetz et al. (2008), by offering a more accessible, potentially scalable method for motor assessment using visual data derived from wearable devices.
DOI: 10.17632/btdpmw96hg.1
title: Reliability of visual observation to classify continuous wavelet transforms of signals of extremity movements

description: This dataset accompanies the research study titled "Reliability of visual observation to classify continuous wavelet transforms of signals of extremity movements." The primary aim of this work is to investigate the feasibility and consistency of human visual assessment of accelerometer-derived time-frequency signals in evaluating motor abnormalities, particularly in individuals diagnosed with Parkinson’s disease (PD) compared to healthy individuals with typical development (TD).

The dataset comprises continuous wavelet transform (CWT) images that were generated from raw accelerometer signals collected during a series of standardized motor tasks. These tasks, adapted from the Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), included repetitive movements such as finger tapping, toe tapping, pronation-supination, hand movements, and leg agility. Participants were equipped with low-cost wearable sensors, taped directly to their extremities, as described by McKay et al. (2019). These sensors captured high-resolution, continuous movement data during in-person clinical assessments.

The raw accelerometer signals were processed and converted into continuous wavelet transforms, creating two-dimensional time-frequency images that visualize the movement patterns. These CWT images served as the basis for a blinded observational analysis. A group of 31 trained raters—who were blinded to all participant-specific information, including age, sex, clinical diagnosis, and which limb the signal was collected from—systematically scored each image for signs of motor dysfunction. Specifically, raters evaluated each image for abnormalities across three parameters: amplitude, frequency, and interruptions in the movement signal.

This methodology builds upon and extends previous research by Hernandez et al. (2022) and Ziegelman et al. (2023), who demonstrated that visual interpretation of wavelet-transformed sensor data could be a viable remote assessment tool for movement disorders. Statistical validation of inter-rater reliability was carried out using Cronbach’s alpha and intraclass correlation coefficients (ICC), with analysis performed using IBM SPSS Statistics version 30.0.0. The high ICC values observed in this study support the reproducibility and reliability of this visual classification approach.

Moreover, this work reinforces and expands upon findings by Elshourbagy et al. (2023), who previously assessed the feasibility of using similar low-cost, sensor-based technologies for remote motor evaluations. It also complements the clinically validated MDS-UPDRS framework outlined by Goetz et al. (2008), by offering a more accessible, potentially scalable method for motor assessment using visual data derived from wearable devices.
DOI: 10.17632/fs2snmcsff.1
title: Geopolitical

description: This data allows to analyze the performance of funds representing clean energy and carbon energy sectors, alongside two geopolitical risk indices, over roughly fifteen and a half years.
DOI: 10.17632/9zwh75gc5f.1
title: Energy and Alternative Energy ETFs

description: This data allows to calculate daily, overnight and intraday returns from 1 January 2013 to 31 December 2024 (amounting to 3,131 usable observations) of twelve Exchange Trade Funds, ETFs, six Energy ETFs and six Alternative Energy ETFs.
DOI: 10.17632/c95gfh2nwf
title: Preços de transferencia

description: Artigos - Preços de transferência deste 2018, até 2022
DOI: 10.17632/c95gfh2nwf.1
title: Preços de transferencia

description: Artigos - Preços de transferência deste 2018, até 2022
DOI: 10.17632/bpkxp8vnrr
title: Time to Diagnose for Adolescent Endometriosis in West Java, Indonesia Population; A Single Centre 3 Years Cohort Retrospective Study

description: Data was taken from post operative endometriosis patient on Hasan Sadikin Hospital in the span of 3 years (2021 - 2024).
DOI: 10.17632/bpkxp8vnrr.1
title: Time to Diagnose for Adolescent Endometriosis in West Java, Indonesia Population; A Single Centre 3 Years Cohort Retrospective Study

description: Data was taken from post operative endometriosis patient on Hasan Sadikin Hospital in the span of 3 years (2021 - 2024).
DOI: 10.17632/pbwc2n7p5m.1
title: Dataset for Probabilistic Ultimate Strength Analysis of Cracked Marine-Grade Aluminum Stiffened Plates Using Non-Intrusive Chaotic Radial Basis Function

description: This dataset supports the research article titled "Probabilistic Ultimate Strength Analysis of Cracked Marine-Grade Aluminum Stiffened Plates Using Non-Intrusive Chaotic Radial Basis Function (NICRBF)". The central hypothesis of the study is that the ultimate strength of marine aluminum stiffened plates with pre-existing cracks, subjected to uncertain operational and material parameters, can be effectively quantified through a probabilistic computational framework combining nonlinear finite element analysis (NLFEA) with NICRBF-based uncertainty modeling.

The dataset includes input parameters, output results, finite element mesh files, and post-processed simulation data generated during the probabilistic analysis of aluminum stiffened plates with varying crack lengths, orientations, and locations. All simulations are based on a stiffened panel geometry representative of high-speed aluminum catamarans and consider realistic imperfections and mechanical properties of Aluminum 5083-H116.

Key findings derived from this dataset include:

Crack length significantly affects ultimate strength variability, with a coefficient of variation (COV) ranging from 0.27 to 0.35.

Crack orientation exhibits a non-monotonic influence on mean strength and variability, revealing complex stress redistribution mechanisms.

Crack location impacts failure probability, especially near mid-span positions.

Under sagging and hollow landing conditions, the probability of structural failure escalates with vessel speed and wave height, reaching near-certainty at design conditions in severe seas.

How the data was gathered: The ultimate strength simulations were performed using ABAQUS for NLFEA, with geometric imperfections introduced following established models (e.g., Paik’s approach). A non-intrusive uncertainty propagation framework using Chaotic Radial Basis Functions was developed in MATLAB to perform stochastic analysis on hundreds of scenarios.

How to use and interpret the data:

Files include input configurations (material properties, geometry, crack definitions), output stress-strain results, and probabilistic distribution files.

Researchers can replicate or extend the analysis by varying key parameters or integrating alternative crack modeling techniques.

Educators and students may use it to study the impact of uncertainty in marine structural design.

Designers can reference the results to develop safety criteria or operational guidelines for high-speed vessels.

This dataset provides a valuable resource for advancing reliability-based design and safety assessment of marine aluminum structures under real-world uncertainties.
DOI: 10.17632/7s56h4bc7r.1
title: Replication Package for "The Role of Currencies in External Balance Sheets"

description: This replication package includes all the public data and STATA code files to reproduce the figures and tables presented in the main text and the appendix.
DOI: 10.17632/3h74ktng2s.1
title: Dynamic Capabilities -Digital Innovation and Responsible Innovation

description: Data research: The effect of dynamic capabilities and digital innovation on competitiveness mediated by responsible innovation
DOI: 10.15468/dl.2bu5wz
title: Occurrence Download

description: A dataset containing 322 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((174.38646 -36.31423,174.58168 -36.32563,174.39234 -35.5912,174.18388 -35.67845,174.38646 -36.31423))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Araneae"
 ]
}

 The dataset includes 322 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017277-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/br9dx4xh6n.1
title: Análisis Comparado de la Compra Pública de Innovación en Iberoamérica y Europa (2024)

description: Este conjunto de datos presenta un análisis comparativo de la normativa, plataformas electrónicas, criterios de evaluación y procedimientos asociados a la Compra Pública de Innovación (CPI) en diez países: España, Portugal, Italia, Costa Rica, Perú, Chile, Panamá, México, entre otros. La información fue recolectada mediante revisión documental de portales oficiales, leyes nacionales y directivas regionales.
DOI: 10.17632/wsknnntzwj
title: Dockers Data

description: The data were collected through surveys administered to 190 individuals working in 5 different port operations across 5 different regions in Türkiye. There are three sections to the survey. Questions about some of the workers' occupational and demographic traits are included in the first part. These include the number of Occupational Health and Safety (OHS) professionals employed by the workplace's OHS unit, as well as factors like gender, age, marital status, education level, position, work experience, and employment status with the primary employer or subcontractor.
DOI: 10.17632/wsknnntzwj.1
title: Dockers Data

description: The data were collected through surveys administered to 190 individuals working in 5 different port operations across 5 different regions in Türkiye. There are three sections to the survey. Questions about some of the workers' occupational and demographic traits are included in the first part. These include the number of Occupational Health and Safety (OHS) professionals employed by the workplace's OHS unit, as well as factors like gender, age, marital status, education level, position, work experience, and employment status with the primary employer or subcontractor.
DOI: 10.15468/dl.2f6hpp
title: Occurrence Download

description: A dataset containing 814 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Acacia abyssinica Hochst. ex Benth."
 ]
}

 The dataset includes 814 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017278-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/6742m6tsct.1
title: Modified Looping Technique to Control Suture Line, Facilitate Knots, and Protect the Suture Needle

description: Needlestick injuries and contamination from loose sutures are surgical challenges. In this video, we demonstrate a modified controlled suture looping technique that enhances safety and efficiency. By organizing excess suture into tensioned loops, this method minimizes contamination risk, prevents tangling, and improves knot security. It also enables solo suture cutting, which is practical for settings with limited assistance. A practical solution to improve sterility and reduce sharps injuries in the operating room.
DOI: 10.15468/dl.epqeqp
title: Occurrence Download

description: A dataset listing the 18 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Observation)",
 "Country is Saudi Arabia",
 "GadmGid is SAU.11_1",
 "Geometry POLYGON((39.77534 21.39053,39.88221 21.3819,39.89525 21.47096,39.83141 21.47193,39.78713 21.47353,39.77534 21.39053))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (CR, EN, VU, NT, LC)",
 "OccurrenceStatus is Present",
 "PublishingOrg is 28eb1a3f-1c15-4a95-931a-4af90ecb574d",
 "Year 2010-2025"
 ]
}

 The dataset's 18 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017272-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/jpr6zghy8w.1
title: Normograma histórico de políticas públicas y marco regulatorio sobre innovación y Compra Pública de Innovación (CPI) en Colombia (1990–2025)

description: Este conjunto de datos recoge, ordena y analiza las principales normas, políticas públicas y disposiciones regulatorias emitidas en Colombia entre 1990 y 2025, relacionadas con la ciencia, tecnología, innovación y específicamente con la Compra Pública de Innovación (CPI). Incluye documentos CONPES, leyes, decretos y circulares, cada uno con un análisis sobre su impacto o relación con la CPI.
DOI: 10.17632/fdxst56tcj.1
title: InGesture: An Eight-Class Inertial Sensor Dataset for Fluid Intake and Hand-Gesture Recognition

description: Data are organized into a hierarchical folder structure designed for easy access and efficient use. At the top level, the dataset is divided into subject-specific folders labeled sequentially (e.g., Subject01, Subject02). Each subject folder contains data collected across one or more sessions, organized systematically. Within each session folder, there are two primary data formats: segmented gesture instances and continuous full-session recordings.

Segmented gesture instance CSV files contain data corresponding exclusively to individual gestures. Each file features columns for timestamp (time of data capture), three-axis accelerometer readings (x, y, z), and gyroscope readings (gx, gy, gz). These files isolate gesture events from continuous recordings, capturing only the precise interval of each gesture. File naming conventions include critical metadata: gesture type, occurrence number, segment length, subject identifier, dominant hand, and container type used (e.g., fluid_intake_1_900.csv, answering_phone_1_800.csv). Approximately 5400 segmented files result from this structure (four occurrences of each of the eight gesture types across 65 sessions).

The continuous full-session CSV files provide comprehensive raw sensor data annotated over approximately ten-minute recording periods. Each continuous file includes columns for timestamp, accelerations (accX, accY, accZ), angular velocities (asX, asY, asZ), magnetometer readings (hX, hY, hZ), and explicit gesture labels. Labels range from 0 to 7: 0 represents free activity (no gesture), 1 is fluid intake, 2 answering the phone, 3 scratching the head, 4 passing hand over face, 5 adjusting glasses, 6 holding the chin, and 7 stretching hands behind the neck. This labeling enables precise identification of intervals for each gesture occurrence.

Annotations for continuous data were collected in real-time via a synchronized application marking the exact start and end of gestures. Hence, continuous session files accurately represent gesture sequences as performed, including natural transitions and variations in duration. A typical session begins in a free state (label 0), progressing sequentially through multiple gestures as defined by the experimental protocol.
DOI: 10.17632/fdxst56tcj.2
title: InGesture Dataset

description: Data are organized in a clear, hierarchical folder structure under a single root directory named InGesture. At the top level, each participant has a dedicated folder (e.g., Subject01, Subject02, …), and within those, one or more session subfolders contain the raw recordings and segmented gesture files. Two complementary formats are provided:

Segmented gesture files

Each CSV file corresponds to a single occurrence of a specific gesture.

Filenames encode the gesture label, repetition index, and sample count (for example, fluid_intake_1_900.csv).

Columns include:

timestamp (sensor capture time)

x, y, z (accelerometer readings in m/s²)

gx, gy, gz (gyroscope readings in °/s)

Because each file contains only one gesture class, no label column is needed—classification can be inferred from the filename or parent folder.

Continuous session files

Each file captures an uninterrupted ~10-minute recording at 200 Hz, yielding about 120,000 samples per session.

Columns include:

timestamp

accX, accY, accZ (linear acceleration)

gyrX, gyrY, gyrZ (angular velocity)

label (integer code 0–7 denoting the current gesture)

Gesture codes map as follows:
0 – free activity
1 – fluid intake
2 – answering phone
3 – scratching head
4 – passing hand over face
5 – adjusting glasses/touching temples
6 – holding chin
7 – stretching hands behind neck

Across 65 sessions (most participants contributed one session, some two or more), there are roughly 2,080 segmented files (8 gestures × 4 repetitions × 65 sessions) and 65 continuous recordings. All data were acquired with a WT901BLECL5 inertial measurement unit secured on the dominant wrist and sampled at 200 Hz. Real-time gesture boundaries were annotated via a synchronized mobile app, ensuring that each sensor sample aligns precisely with its gesture label.
DOI: 10.17632/fdxst56tcj.3
title: InGesture Dataset

description: Data are organized in a clear, hierarchical folder structure under a single root directory named InGesture. At the top level, each participant has a dedicated folder (e.g., Subject01, Subject02, …), and within those, one or more session subfolders contain the raw recordings and segmented gesture files. Two complementary formats are provided:

Segmented gesture files

Each CSV file corresponds to a single occurrence of a specific gesture.

Filenames encode the gesture label, repetition index, and sample count (for example, fluid_intake_1_900.csv).

Columns include:

timestamp (sensor capture time)

x, y, z (accelerometer readings in m/s²)

gx, gy, gz (gyroscope readings in °/s)

Because each file contains only one gesture class, no label column is needed—classification can be inferred from the filename or parent folder.

Continuous session files

Each file captures an uninterrupted ~10-minute recording at 200 Hz, yielding about 120,000 samples per session.

Columns include:

timestamp

accX, accY, accZ (linear acceleration)

gyrX, gyrY, gyrZ (angular velocity)

label (integer code 0–7 denoting the current gesture)

Gesture codes map as follows:
0 – free activity
1 – fluid intake
2 – answering phone
3 – scratching head
4 – passing hand over face
5 – adjusting glasses/touching temples
6 – holding chin
7 – stretching hands behind neck

Across 65 sessions (most participants contributed one session, some two or more), there are roughly 2,080 segmented files (8 gestures × 4 repetitions × 65 sessions) and 65 continuous recordings. All data were acquired with a WT901BLECL5 inertial measurement unit secured on the dominant wrist and sampled at 200 Hz. Real-time gesture boundaries were annotated via a synchronized mobile app, ensuring that each sensor sample aligns precisely with its gesture label.
DOI: 10.17632/svhprd6wym.1
title: Seasonal changes in physio-biochemical responses of the xerophytic dwarf shrub Haloxylon salicornicum in the Kuwait desert

description: Raw and processed data, including statistical analysis, of physio-biochemical parameters of Haloxylon salicornicum shoots in response to a combined high temperature and drought in the field.
DOI: 10.17632/svhprd6wym.2
title: Seasonal changes in physio-biochemical responses of the xerophytic dwarf shrub Haloxylon salicornicum in the Kuwait desert

description: Raw and processed data, including statistical analysis, of physio-biochemical parameters of Haloxylon salicornicum shoots in response to combined high temperatures and drought conditions in the field.