cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/sbzxm5rydj
title: Development of an open source soil water potential management system for horticultural applications, “Open_Irr”.

description: ABSTRACT:
Development of data driven, sensor-based irrigation has become possible with recent advancements in technology, yet due to a cost-barrier to entry, equitable adoption remains out of reach. Therefore, a simple microcontroller based LoRa platform, Open_Irr, was developed in the Arduino IDE to record resistive measures of soil matric potential and automate irrigation events. A single Open_Irr Node may connect with ≤ 16 Watermark® soil sensors and manage 4 irrigation settings; Node sampling frequency, irrigation settings, and radio transmission settings are end-user adjustable without programming knowledge. Multiple Nodes may connect with a single Gateway to provide a scale-neutral solution for irrigation automation. A preliminary trial was conducted in Spring 2022 to validate the performance of the Open_Irr platform in water deficit scenarios. Open_Irr recorded soil matric potentials in line with a commercial Watermark® sensor reader (n=655); regression analysis yielded a coefficient of determination of 0.91 with Bland-Altman estimated fixed bias of ~2 kPa. The Open_Irr platform was demonstrated to automate dripline irrigation events at several matric potential thresholds through connection to external solenoid valves. This demonstration directly conveys suitability for commercial and academic horticultural applications where automation of irrigation events or imposition of drought stress is desired.

SOURCE FILES:
Open_Irr_Node_copy: Open_Irr Node program written in the Arduino IDE, uploaded to Moteino-Mega microcontroller in the Node unit. Should only be altered by advanced users. 

Open_Irr_Gateway_copy: Open_Irr Gateway program written in the Arduino IDE, uploaded to Moteino-Mega microcontroller in the Gateway unit. Should only be altered by advanced users.

Gerber_HardwareX_Open_Irr_Node_PCB.zip: Open_Irr Node gerber zip file. Provide to PCB manufacturers to obtain PCB.

Gerber_HardwareX_Open_Irr_Gateway_PCB.zip: Open_Irr Gateway gerber zip file. Provide to PCB manufacturers to obtain PCB.

Schematic_HardwareX_Open_Irr_Node.pdf: Open_Irr Node electrical schematic of included components.

Schematic_HardwareX_Open_Irr_Gateway.pdf: Open_Irr Gateway electrical schematic of included components.
DOI: 10.17632/9mh4dg4rfn
title: Data on departure reasons in US CEO turnover over fiscal years 1992-2020

description: We present a dataset of US CEO turnover types created with manual data collection through searches of news stories related to CEO turnover. The data identify the fiscal year of turnover and its type for top managers in publicly-traded US firms. We identify turnover cases based on changes in the CEO of the firm as recorded in secondary data sources of Compustat and Execucomp, and then we classify turnover types based on the examination of full-text news. 
 
We start dataset construction with the ExecuComp executive-level data for the fiscal years from 1992 through 2020. These data are merged with the CompuStat dataset of financial variables. As the dataset is intended for research on CEO turnover, we exclude observations in which the CEO at the start of the fiscal year is not well-defined. The data set also excludes firm/year combinations that involve a restructuring of the firm – spinoff, buyout, merger, or bankruptcy. 
 
We identify the CEO at the start of each year for each firm. To identify CEO turnover based on changes in the CEO from year to year, we require firm observations to extend over at least six contiguous years. Cases involving the last year the firm is in the sample are excluded. We also exclude from the dataset cases when there was an interim CEO who stayed in the position for less than 2 years. This results in a sample of 3,100 firms reflecting 41,773 firm/year combinations. 
 
For this sample, we examine news articles related to CEO turnover to confirm the reasons for each CEO departure case. We use the ProQuest full-text news database and search for the company name, the executive name, and the departure year. We identify news articles mentioning the turnover case and then classify the explanation of each CEO departure case into one of five categories of turnover. These categories represent CEOs who resigned, were fired, retired, left due to illness or death, and those who left the position but stayed with the firm in a change of duties, respectively. 

The published data file does not include proprietary data from ExecuComp and CompuStat such as executive names and firm financial data. These data fields may be merged with the current data file using the provided ExecuComp and CompuStat identifiers.
 
The dataset consists of a single table containing the following fields:
• gvkey – unique identifier for the firms retrieved from CompuStat database
• firmid – unique firm identifier to distinguish distinct contiguous time periods created by breaks in a firm’s presence in the dataset
• coname – company name as listed in the CompuStat database
• execid – unique identifier for the executives retrieved from ExecuComp database
• year – fiscal year
• reason – reason for the eventual departure of the CEO executive from the firm, this field is blank for executives who did not leave the firm during the sample period
• ceo_departure – dummy variable that equals 1 if the executive left the firm in the fiscal year, and 0 otherwise
DOI: 10.17632/b35mv8nwmw
title: Data for "Petrogenesis, Sampling Depth, Thermal and Redox Evolution of Spinel Peridotite Xenoliths From Jiaohe, NE China: Insights From Trace Elements in All Rock-Forming Silicate Minerals" 

description: This file includes Supplementary Tables S1 to S6 for the publication "Petrogenesis, Sampling Depth, Thermal and Redox Evolution of Spinel Peridotite Xenoliths From Jiaohe, NE China: Insights From Trace Elements in All Rock-Forming Silicate Minerals" (submitted to Journal of Geophysical Research: Solid Earth in June 2023).
Table S1. Salient previously published data for whole rocks and minerals.
Table S2. Trace element compositions of orthopyroxene and olivine as well as reference materials measured as unknowns.
Table S3. Major element compositions and Fe3+/ΣFe of standard and sample spinel, along with TOl-Sp and ƒO2.
Table S4. Reconstructed whole-rock trace element compositions and inter-mineral distribution coefficients.
Table S5. Summary of temperatures and pressures for xenoliths in this study and recalculated for literature data.
Table S6. Correction for Ca content in olivine.
DOI: 10.17632/b4t2wxhn2y
title: CMAB-The World's First National-Scale Multi-Attribute Building Dataset

description: This data is the building dataset with a total rooftop area of 23.6 billion square meters in 3,667 natural cities in China, including the attribute of building rooftop, height, structure, function, age, style and quality, as well as the code files used to calculate these data. The deep learning models used are OCRNet, XGBoost, fine-tuned CLIP and Yolo-v8. Please refer to the paper and README file for details of specific parameters. This building data is the original version, and the processed version can be viewed here: 10.6084/m9.figshare.27992417. Related papers are published in Scientific Data.
DOI: 10.17632/kdgw4mn2vh
title: Global Impacts of Introduced Ungulates on Wetland Carbon and Biodiversity: A review

description: This file contains all of the information extracted from studies included in the review titled, 'Global Impacts of Introduced Ungulates on Wetland Carbon and Biodiversity: A review'.
DOI: 10.17632/nzv32s3v35
title: EMG signals and leg hemodynamic parameters

description: Surface EMG (sEMG) activity of right lower limb muscles was recorded from the muscle bellies of gluteus maximus (GM), rectus femoris (RF), vastus medialis (VM), vastus lateralis (VL), biceps femoris (BF), tibialis anterior (TA), lateral gastrocnemius (LG), medial gastrocnemius (MG), and soleus (SO) using parallel-bar sEMG sensors (Trigno standard EMG sensor, Delsys Inc., Boston, MA, USA) at 2000Hz, after removal of hair and cleaning with alcohol swipes. The portable NIRS apparatus was attached to the motor point of the right vastus lateralis muscle along the vertical axis of the thigh, approximately 10 cm from the knee joint.
DOI: 10.17632/33nrrzs45r
title: Data for: The prediction of ship added resistance at the preliminary design stage by the use of an artificial neural network

description: AddedResistance (MAC/WIN) program was developed for added resistance estimation on head waves by the use of an MLP artificial neural network. In order to create a reliable model, only experimental data determined through model tests measurements was used to train this neural network. The following model tests results of these vessels were used in the development of this software: • Van der stel (Gerritsma and Beukelman , 1972; Journee 1976), • S175 containership (Nakamura, 1976), • Series 60 CB=0.6, CB=0.65, CB=0.7, CB=0.75, CB=0.8, Strøm-Tejsen (1973), • WILS II containership (Söding et al., 2014), DTC containership (Sprenger et al. , 2015), • Cruise ship (Ley et al., 2014), Bulk carrier (Kadomatsu, 1988), • RoPax (Sprenger et al., 2015), • KVLCC2 tanker (Guo & Steen, 2010; Sadat-Hosseini et al., 2013), • KRISO containership (Simones et al. 2014). AddedResistance program could have practical application at the preliminary design stage. But this computer program might have two limitations. Firstly, the program may be inaccurate in the design of an innovative ship. This results from the data used to train the network which was measured on standard ship hulls. Secondly, the neural network was developed using the model test data with limited parameter ranges. Therefore, AddedResistance might only be used to estimate added wave resistance for ships with the following design characteristic ranges: • length between perpendiculars LBP from 90 m to 335 m, • breadth B from 16.25 m to 58 m, • draught d from 4.2 to 20.8 m, • block coefficient CB from 0.503 to 0.829, • Froude number Fn from 0.087 to 0.3, • LBP/B ratio from 5 to 7.5, • B/d ratio from 2.5 to 4.5. The application of this computer software to calculate ship resistance with design characteristics outside these ranges might be associated with the risk of low accuracy estimations. The total mean added resistance of sailing ship in irregular waves is calculated by the use of the wave energy spectrum. A common ITTC spectrum based on Bretschneider wave energy spectrum was used here to calculate the mean added resistance in irregular wave. Lazarus IDE software (Lazarus 2.0.0, 2019) with a Free Pascal compiler was used to develop the AddedResistnace program.
DOI: 10.17632/hcytmbcngg
title: Research data for the research article "Vortex ratchet effect in superconductor open nanotubes and nanopetals"

description: Research data underlying research article arXiv:2407.20780 "Vortex ratchet effect in superconductor open nanotubes and nanopetals" by I. Bogush, R. H. de Bragança, V. M. Fomin, O. V. Dobrovolskiy, obtained in the Cryogenic Quantum Electronics Division, EMG and LENA, TU Braunschweig, as part of the CA project "3DSuper" within the EXC-2123 QuantumFrontiers 390837967 funded by the German Research Foundation (DFG)
DOI: 10.17632/3c72y8p2tp
title: Dataset of Attitude towards Anti-Sexual Harassment

description: Dataset of Indonesia’s Gen Z This dataset becomes the basis of a psychological model contains predictive relationships between eight variables. The eight variables are (I) four predictors/independent variables, i.e. (1) Peer influence/PR, (2) Power distance-at the individual level/PD, (3) Masculinity-at the individual level/MS, (4) Sexual harassment knowledge/SK; (II) three mediators, i.e. (1) Moral disengagement/MD, (2) Belief on myths of sexual harassment/MY, (3) Identification with patriarchal culture/PT; and (III) one criterion/dependent variable, i.e. Attitude towards anti-sexual harassment/ASH. Province_Origins 1 = Nanggroe Aceh Darussalam, Sumatera Island, Indonesia 2 = East Java, Java Island, Indonesia Sex 1 = Male 2 = Female ASH = Attitude towards anti-sexual harassment Response options: from “Does not describe me very well” (scored 1) to “Describes me very well” (scored 6). PR = Peer influence Response options: from “Strongly disagree” (scored 1) to “Strongly agree” (scored 6). PD = Power distance-at the individual level Response options: from “Strongly disagree” (scored 1) to “Strongly agree” (scored 6). MS = Masculinity-at the individual level Response options: from “Strongly disagree” (scored 1) to “Strongly agree” (scored 6). SK = Sexual harassment knowledge Response options: “True” (scored 1) or “False” (scored 0). MD = Moral disengagement Response options: from “Strongly disagree” (scored 1) to “Strongly agree” (scored 6). MY = Belief on myths of sexual harassment Response options: from “Strongly disagree” (scored 1) to “Strongly agree” (scored 6). PT = Identification with patriarchal culture Response options: from “Strongly disagree” (scored 1) to “Strongly agree” (scored 6).
DOI: 10.17632/pjnkwwzn9x
title: Dali_MEG_CurrentBiology

description: In each of five subject folders: 1. *_PixelBehMI_nuns_not.mat • “Ipixe_beh” stores the pixel-wise MI value . • “TH” is the statistic threshold for the pixel-wise MI (FWER p &lt; 0.001, one-tailed). • We downsample the bubbles for each spatial frequency band, so the pixel-wise MI is a 5456-d vector (i.e. 64x64 pixels in SF1 + 32x32 pixels in SF2 + 16x16 pixels in SF3 + 8x8 pixels in SF4 + 4x4 pixels in SF5 = 5456 pixels) 2. *_PixelBehMI_volt_not.mat • “Ipixe_beh” stores the pixel-wise MI value . • “TH” is the statistical threshold for the pixel-wise MI (FWER p &lt; 0.001, one-tailed). 3. *_FeatureMegMI.mat • “Ifeat” is the 3D time-by-feature-by-voxel MI matrix. • “TH” is the statistical threshold (FWER p &lt; 0.05, one-tailed). 4. *_BrainFeatures.mat • ‘nuns_feat’: Indices of diagnostic brain features for the perception of “the nuns”. • ‘volt_feat’.: Indices of diagnostic brain features for the perception of “Voltaire”. • ‘nondiag_feat’: Indices of nondiagnostic brain features. 5. *_FullICA_LP_B_NMF_*.PDF • Brain features obtained from the NMF analysis. 6. *_Redundancy_nuns_volt_not.mat • “Ired” is the 3D redundancy matrix (time point x feature × voxel), using all trials. • “TH” is the statistical threshold (FWER p &lt; 0.05, one-tailed). • “time” stores the post-stimulus time (in seconds) for each time point. 7. *_Redundancy_nuns_not.mat • “Ired” is the 3D redundancy matrix (time point x feature × voxel), using “the nuns” and “don’t know” trials. • “TH” is the statistical threshold (FWER p &lt; 0.05, one-tailed). 8. *_Redundancy_volt_not.mat • “Ired” is the 3D redundancy matrix (time point x feature × voxel), using “Voltaire” and “don’t know” trials. • “TH” is the statistical threshold (FWER p &lt; 0.05, one-tailed).
DOI: 10.17632/s9438vb5xd
title: Data for: Single Tracks Data obtained by Selective Laser Melting of Ti6Al4V with a Small Laser Spot Diameter

description: The copressed folder contains SEM images as well as geoemtrical data (numerical values in the *.xlsx file) of top and cross section views of single tracks obtained by Selective Laser melting of Ti6Al4V Titanium powder by suing a small laser spot diameter of 50 micrometers.
DOI: 10.17632/bdng756rgw
title: FLAAP: An open Human Activity Recognition (HAR) dataset for learning and finding the associated activity patterns 

description: The purpose of this research is to propose a dataset for Human Activity Recognition (HAR) utilizing smartphone sensors. The dataset consists of 10 activities that were completed throughout three trials by eight different people. After examining the results of each experiment, the dataset only contains one of the optimal activity patterns. For intelligent learning algorithms to detect and understand the related activity patterns, this time-series data collected from smartphone-embedded (accelerometer and gyroscope) sensors provided valuable information. With the growing need for context-aware apps relating to people depending on their activities such as sports, health care, surveillance, yoga, the gym, and many more. The creation of solutions for these kinds of problems depends on the availability of such data. To collect data while doing the human activities indicated in this article, we give a HAR dataset of measurements taken from smartphone sensors targeted at the subject's body. Millions of raw sensor activity data samples were continuously collected between February 1st and May 31st of 2022 at sampling speeds of 100 Hz. The performance evaluation of various machine and deep learning algorithms for the learning and identification of activity patterns might benefit from this dataset. The performance of the learning algorithms while using various data preprocessing methods, knowledge transfer to target domains, and other methods may be of special interest to the research community. Such learning algorithms may also be used with HAR data that has been gathered over a long period. This makes it possible to determine activity patterns for a certain period. After that, after a predetermined period, we can detect changes. For patients with dementia, the physically challenged, the elderly, and youngsters who care for others, among others, this can assist in recognizing abnormalities and delivering early therapies.
DOI: 10.17632/8sxvv3mvm5
title: Complex angular momentum methods for elastic scattering with an optical potential

description: Title of program: REGGE Catalogue Id: ABNF_v1_0 Nature of problem The computer program REGGE solves the radial part of the Schrodinger equation for a central complex potential. It locates the poles and zeros of the scattering S-matrix in a complex angular momentum plane, and also computes the residues of the poles. The pole terms thus obtained are combined with the background integral term and the sum, after being projected on to physical (real integer) angular momentum space, is used to calculate cross sections. Versions of this program held in the CPC repository in Mendeley Data ABNF_v1_0; REGGE; 10.1016/0010-4655(79)90012-2 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)
DOI: 10.17632/6574nhzm8x
title: FabricSpotDefect: An Annotated Dataset for Identifying Spot Defects in Different Fabric Types

description: Content: This FabricSpotDefect dataset is designed to improve fabric spot defect detection using computer vision. It includes various types of fabrics such as cotton, linen, silk, denim, and both plain and patterned textiles, featuring spot defects like stains, discolorations, oil marks, and more.

Format: The images are in 2D RGB .jpg format of varying sizes.

Original Images: 1,014 raw images with 3,286 spot defect labels.

Augmented Images: After applying six types of augmentation techniques, the dataset expands to 2,300 images with 7,641 labeled spots. 

Data Features: The dataset features both original and augmented images organized into “original” and “augmented” folders, each containing subfolders for training, validation, and testing. All images are resized to 416×416 pixels and undergo six augmentation techniques: flipping, rotation, shearing, saturation, brightness, and noise addition.

How data are acquired: The FabricSpotDefect dataset images were collected from everyday home fabrics under natural lighting using three smartphones( Samsung Galaxy Note20, Samsung Galaxy S20 FE, and Samsung Galaxy A53 5G).

Use Case: To develop an AI model that will identify spot defects in fabrics, so that the model could be used to improve the quality control process in textile production.
DOI: 10.17632/kwm8ym42bp
title: Experience of Physical Rehabilitation Among Individuals with Brain Injury: A Scoping Review

description: This scoping review explores the experiences of individuals with brain injury during the course of physical rehabilitation, drawing insights from a diverse range of qualitative studies. Through a thematic synthesis of existing literature, the study aims to identify and analyze how patients perceive and navigate the rehabilitation process. It seeks to uncover recurring themes related to perceived challenges, the effectiveness of interventions, and the emotional and psychological responses that emerge throughout recovery. In doing so, the review addresses notable gaps in the current body of research and highlights areas requiring further scholarly attention. Ultimately, by centering the voices of those directly affected, this study contributes to the advancement of patient-centered rehabilitation practices and offers evidence-informed recommendations for enhancing care delivery contexts.
DOI: 10.17632/hxmhmfgsdb
title: Video-1

description: Demonstration of surgical scraping of the affected nail plate subungual hematoma using a punch biopsy instrument.
DOI: 10.17632/c5n4k6ddw7
title: Atmospheric methane concentrations in the urban core of a medium-sized city

description: Data shows the seasonal spatial variation in atmospheric methane (CH4) concentrations during a year (June 1st, 2017 - May 31st, 2018) at ten sampling sites in the urban core of Tandil (37°19′ S, 59°08′ W), a medium-sized city in Buenos Aires province (Argentina). Also, contain meteorological data. During a study period integrated air samples were collected in 0.5 liter stainless steel canisters with an inlet valve and an air flow controller calibrated for the desired sampling period (Gere and Gratton 2010) in consecutive 15-day periods. The air samples were analyzed for CH4 concentration by gas chromatography (CG Agilent 7890A) (De Bernardi et al. 2019). Basic descriptive statistical analyses, ANOVA Test and a Fisher’s LSD test (p &lt; 0.05) were performed to assess the relative incidence of biogenic and non biogenic sources in the atmospheric CH4 concentrations. Infostat Statistical software was used for all statistical analyses. Spatial analysis tools (ArcGIS 10.5®) (Exploratory Regression and Ordinary Least Squares) were used to identify the independent variables that account for the mean CH4 values obtained. These analyses highlight the contribution of the wastewater treatment plant, CNG stations, artifical lake and homes connected to the gas natural network to the spatial variability of the atmospheric CH4 concentrations in the urban core of the studied city.
DOI: 10.17632/hnw9f7svvm
title: cHL and HIV

description: Outcomes of first-line treatment in patients with advanced clinical stage classic Hodgkin lymphoma and human immunodeficiency virus infection.
DOI: 10.17632/tz6vfjm93h
title: Malware analytics Dataset

description: Malware analytics Dataset
DOI: 10.17632/jnjwjxgyd7
title: Data of L2 motivation comparison of Spanish and Japanese high school students

description: This is the data of the project which explored the motivational behaviour of L2 high school students from Spain and Japan. Time period of data collection: November 2021 – February 2022. The tool of analysis: MFQ, Likert-scale (1-5). The data collected was exported to the statistical software SPSS version 24.
DOI: 10.17632/5hppr8mtry
title: Replication Package for "Surges and Instability: The Maturity Shortening Channel"

description: Replication folder for the paper entitled "Surges and Instability: The Maturity Shortening Channel" by Xiang Li and Dan Su
DOI: 10.15468/dl.9khebs
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Argentina Linnaeus, 1758",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((44.9648 1.2321,45.9851 1.8496,44.9648 1.8496,44.9648 1.2321))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012872-250525065834625/datasets/export for details.