cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/jd64t5prvn.1
title: Macro- and microhabitat predictors of nest success and hatchling survival in  eastern box turtles (Terrapene carolina carolina) and spotted turtles (Clemmys guttata) in oak savanna landscapes

description: Characteristics of nest sites of eastern box turtles (Terrapene carolina carolina) and spotted turtles (Clemmys guttata) in northwestern Ohio and southern Michigan in 2018-2019.  Nest sites were located by radio-tracking gravid female turtles to nest sites, nests were monitored until hatchling emergence (HatchDate), and radio-transmitters were attached to hatchlings, which were then monitored via radio-telemetry to determine whether they survived to enter overwintering.  Macrohabitat data were collected for the land cover patch within 10 m of the nest site and included distance to nearest road (m) and distance to nearest habitat edge (m).  Microhabitat data were recorded within 1 m of the nest site and included date of nest construction (DayOfYear), % shade cover over the nest (Shade), and total depth of the nest cavity (Depth; mm).  Macrohabitat and microhabitat variables were used as predictors in separate models of nest success and juvenile (i.e., hatchling) survival to overwintering for each species.  Alternate nests were caged to prevent predation by mammals (Caged).  We also recorded female plastron length (mm), number of eggs (ClutchSize), number of surviving hatchlings (AliveHatchlings), and whether the nest was depredated (Predated).  In the “SWGTurtles” file, for each nest, NestSuccess was assigned as 1 if any live hatchlings were recovered from the nest.  NestSuccess was 0 if no live hatchlings were recovered and there was evidence of predation or egg mortality as described above.  In the “SWGHatchlings” file, hatchlings that were either found dead or whose transmitters were recovered with damage consistent with a predator attack were assigned a survival value (i.e., PresumedSurv) of 0.  Hatchlings that were known to have entered hibernation were assigned a PresumedSurv of 1.  Hatchlings for which we lost the radio signal more than three days from predicted transmitter battery expiration (TransmExpiry) were assumed to have been depredated (i.e., the transmitter was either broken or carried out of signal range by a predator) and were assigned PresumedSurv of 0.  The final group of hatchlings were those whose radio signals were lost within three days of predicted transmitter battery expiration.  For these hatchlings, if transmitter expiration (EndDate) occurred after 1 October (the date at which most surviving hatchlings had reached the location at which they subsequently overwintered), we presumed the hatchling had survived to enter hibernation and assigned a PresumedSurv of 1.  If transmitter expiration occurred before 1 October for hatchlings in this group, we assigned the hatchling an “unknown fate” and excluded it from analysis (data for this group not included in the manuscript and not shown here)..
DOI: 10.17632/jvs782kvw8.2
title: Health-related quality of life (EuroQol 5D-5L) in patients with autoimmunity in the context of immunotherapy: a large dataset comprising cancer patients after cessation of checkpoint inhibitor therapy and patients with autoimmune diseases

description: This dataset contains demographic, clinical, and health-related quality of life (HRQoL) data from 2905 patients including 200 cancer patients after immune checkpoint inhibitor (ICI) cessation and 2705 patients with a wide variety of autoimmune diseases.
DOI: 10.17632/p746j38z8b.1
title: Integrating Power Human Values into Requirements Engineering Practices--Primary Studies

description: This data set containt the list of Primary studies used in our paper titled "Integrating Power Human Values into Requirements Engineering Practices"
DOI: 10.17632/4rpbz7vpcn.1
title: Heikamp et al.

description: Immunoblot images for Heikamp et al. manuscript submission
DOI: 10.17632/csb6dbssdp.3
title: MAREEA - Evaluation Model of Mobile Augmented Reality Educational Approaches

description: The insertion of technologies in the educational scope has fomented new educational resources and experiences to its users, able to aid in the process of teaching and learning in different areas. Among emerging technologies, the use of augmented reality on mobile devices has stood out because of the combination of enhanced multimedia features and mobile learning. However, it is essential that these educational approaches are properly evaluated in order to obtain evidence of their quality. This paper aims to present the proposal of a model of evaluation of educational approaches in mobile augmented reality, developed from previous studies and a methodology for the definition of the objective of evaluation, quality factors, dimensions, and evaluation items. The model was evaluated by 15 experts related to the area of concentration of the instrument and validated based on its assertions. The results were satisfactory and allowed to validate the construction of the model for future applications in the educational scope.
DOI: 10.17632/djvfpvvdbj.2
title: Internationalization of Intrastate Armed Conflicts Dataset v.2.0-2020 (RFBR 18-314-00006\18)

description: This dataset is part of the research project on internationalization of intrastate armed conflicts funded by the Russian Foundation for Basic Research (RFBR) according to the research project № 18-314-00006\18. It proceeds from an alternative expanded conceptualization of the phenomenon of internationalized internal conflict which argues that accounting for involvement of external state-based actors into intrastate conflict is insufficient for understanding the complex interplay between various international, transnational and cross-border processes that form multiple reinforcing and counterbalancing links and feedback loops. To this end, we offer re-operationalization of the internationalization phenomenon based on an integrated three-dimensional framework which differentiates between three dimensions of internationalization (interpreted in a broader sense). The horizontal dimension (horizontal escalation) represents varied processes through which the spatial spread of organized violence (often originated on the sub-state level) affects the territory of other (usually neighboring) countries leading to consequences (usually destabilizing) for both the source state and the recipient state. The vertical dimension (vertical escalation) covers the processes by which either the structure of a conflict gets expanded to involve outside (foreign) actors, normally as secondary (supporting) parties, or (often as a result of the former) the nominal level of conflict gets upgraded from intrastate to interstate. Vertical escalation is enabled either through an attack by a source state on the territory or subjects of one or more of its neighbors (outward-directed vertical escalation), or alternatively through intervention by a state-based external actor into the original internal conflict (inward-directed vertical escalation). Finally, the systemic dimension (systemic escalation) denotes the expansion of international systemic limits of original conflict by increased political stake, interest and/or attention of various international actors vis-à-vis the conflict in question, through its “proxy-fication” or connectedness with other conflicts in the neighborhood. The proposed dimensions are conceptual constructs aimed at facilitating the analysis of conflict dynamics and are not intended to be interpreted literally. This current version of the dataset (2.0) covers the universe of armed conflicts in the regions of Europe (excl. FSU), Former Soviet Union (FSU), and Asia for the period from 1975 to 2018, and the Middle East and North Africa region for the period from 1989 to 2018.
DOI: 10.17632/v7tdcnzpv2.1
title: Data for: Pelagic clays as archives of marine iron isotope chemistry

description: Results, including Fe and Os isotopes as well as element concentrations, of the leach experiment and downcore samples from Site U1366.
DOI: 10.17632/5gzyzffcyw.1
title: Code Availability

description: Code Availability: umap_on_bulk_transcriptomic_analysis and transcriptomic_analysis_DGE_and_GSEA
DOI: 10.17632/xvhrhbpc8v.1
title: data of patients heart failure in sinus rhythm

description: A total of 264 patients were selected from patients with chronic heart failure in sinus rhythm hospitalized in Renmin Hospital from September 2016 to December 2018. All the patients were divided into two groups according to the presence or absence of left ventricular intracardiac thrombosis. There were 212 patients without intracardiac thrombosis and 52 patients with intracardiac thrombosis. Univariate analysis was used to compare the general data, laboratory test results and echocardiographic results of the two groups. Factors that represented statistically significant differences between the two groups were further analysed by binary logistic regression to identify the risk factors for intracardiac thrombosis in patients with chronic heart failure in sinus rhythm.
DOI: 10.17632/7mwfftd2x4.2
title: DAMQT 3.2

description: New version of program DAMQT for the analysis of molecular electron density and related properties, with new applications including an entirely new 3D viewer based on new OpenGL (3.3 or higher). The tarball includes a MSwindows installer in the "windows" directory and a manual in PDF format in "doc/manual" directory. A "samples" directory is included with files coming from different suites for molecular calculations that can be directly processed by DAMQT as commented in the manual. Installation on Unix systems can be made through cmake as indicated in the manual.
DOI: 10.17632/5n2s4fkhz6.2
title: Uncovering Test Pilots' Risk Framework

description: Survey and interview data collected from experimental flight test crews in late 2022. Data reports the risk management framework used by experimental flight test crews in undertaking uniquely hazardous activities that include the consequence of death - precluding any ability to learn in subsequent iterations of the activity. Data was used to investigate the risk management framework adopted by the flight test crews to risk manage their work, with the objective of generalising this knowledge for application beyond the flight test profession.
DOI: 10.17632/csd32bm8zx.1
title: Dataset for Drone-based Inspection of Road Pavement Structures for Cracks

description: The dataset is available online as a benchmarking dataset for drone-based inspection of pavement structures. The data were acquired in an experimental road with a length of 386 meters, belonging to Montmorency Forest laboratory of Université Laval, located in North of Quebec City, on 2021/06/16. The road is mainly used for testing pavement paints, laying techniques, and inspection simulations. A DJI MINI 2 drone was employed to collect images for this dataset. The drone has a 12 megapixels camera with an 83 degrees field of view, capturing 1920 x 1080 images in the continuous recording mode. The drone performs six passes on an experimental road at different altitudes and horizontal speeds. The drone was controlled manually, and the footage was acquired using the embedded camera that stabilized and controlled using the drone's gimbal. Moreover, after data acquisition, the length and width of some cracks and road landmarks were measured for evaluating crack characterization. 

**** In case of any use, please cite this dataset and our paper ****
DOI: 10.17632/ct79299k27.1
title: Indoor Plant Varieties for Computer Vision Applications: A Diverse Image Dataset

description: The Indoor Plant Varieties Dataset is a valuable asset for researchers, plant care specialists, and AI developers, offering essential tools for the accurate identification and classification of common indoor plant species. This dataset supports the development of computer vision models tailored to indoor plant recognition, enabling users to create applications that simplify plant identification and care. 

Collected between October 28 and November 20, 2023, the dataset consists of 1172 high-resolution images (3000x3000 pixels, JPG format) across seven plant classes: Aglaonema, Cryptanthus, Devil’s Ivy, Heartleaf Philodendron, N-Joy Pothos, Rhaphidophora, and ZZ Plant. Each class represents unique indoor plant species frequently found in homes and offices, collected from BADC (Bangladesh Agricultural Development Corporation) in Kashimpur and nearby nurseries. Images were captured using a Xiaomi M2101K61 smartphone, ensuring consistency in quality. Domain experts (agronomists from BADC) confirmed the class labels, adding reliability to the dataset. To enhance the dataset further, Data Augmentation techniques were applied, including flipping, rotation, zoom, shear, brightness adjustments, and noise reduction. This augmentation expanded the dataset to 7000 images (1000 per class), enhancing the effectiveness of deep learning models for accurate plant classification.

1. Original Data:
 Number of datasets: 1172 
 Data format: .jpg

2. Augmented Data:
 Number of datasets: 7000 
 Data format: .jpg
DOI: 10.17632/vdr3bhc8dj.1
title: Data for: How Fast Does Product Market Reform Pay Off? New Evidence from Non-Manufacturing Industry Deregulation in Advanced Economies

description: Stata files for estimation and Word Read Me document.
DOI: 10.17632/scy82bdkh4.1
title: Is US Trade Policy Reshaping Global Supply Chains?

description: Replication files for "Is US Trade Policy Reshaping Global Supply Chains?" 
Caroline Freund, Aaditya Mattoo, Alen Mulabdic, Michele Ruta
DOI: 10.17632/r33j559s62.1
title: OpenSMOKE++: An object-oriented framework for the numerical modeling of reactive systems with detailed kinetic mechanisms

description: This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018) Abstract OpenSMOKE++ is a general framework for numerical simulations of reacting systems with detailed kinetic mechanisms, including thousands of chemical species and reactions. The framework is entirely written in object-oriented C++ and can be easily extended and customized by the user for specific systems, without having to modify the core functionality of the program. The OpenSMOKE++ framework can handle simulations of ideal chemical reactors (plug-flow, batch, and jet stirred reactors), shock-tu... Title of program: OpenSMOKE++ Catalogue Id: AEVY_v1_0 Nature of problem Evolution of reacting gas mixtures with detailed description of thermodynamic, kinetic and transport data. Versions of this program held in the CPC repository in Mendeley Data AEVY_v1_0; OpenSMOKE++; 10.1016/j.cpc.2015.02.014
DOI: 10.17632/443scrjx2v.1
title: IoT and AI in supply chain

description: Dataset of publication details in IoT and AI in supply chain operations
DOI: 10.17632/fshsssd6s9.1
title: Data for: ON THE IMPERFECTION SENSITIVITY AND DESIGN OF SPHERICAL DOMES UNDER EXTERNAL PRESSURE

description: This archieve included ABAQUS inp files for the Inner Dome of the Ariane 5 and the SC shells from the corresponding article. Also, the excel sheet "LRSM Sphere_data_005.xlsx" includes a collection of over 800 experimental results from literature with reference. Also, new design lower-bound for spherical shells under external pressure are included.
DOI: 10.17632/rgn5brrgrn.5
title: Vibration and Current Dataset of Three-Phase Permanent Magnet Synchronous Motors with Stator Faults

description: This dataset provides vibration and motor current data for fault diagnosis of motor winding faults.

Vibration data is acquired with a sampling frequency of 25.6 kHz, and current data is acquired with a sampling frequency of 100 kHz.
In order to acquire the data, a testbed with motor winding faults was used.


---- Description of vibration file format ----
aaaaW_bb_cc_vibration_dddd.tdms : This file includes "dddd" short circuit fault vibration data of z-direction with "bb.cc" % severity acquired from the motor whose capacity is "aaaa" W.
For examples, "1000W_0_00_vibration_interturn.tdms" means healthy inter-turn short circuit vibration data of z-direction acquired from the motor whose capacity is 1.0 kW and "1500W_5_70_vibration_intercoil.tdms" means coil-coil short circuit fault vibration data of z-direction with 5.70 % severity acquired from the motor whose capacity is 1.5 kW.

---- Description of motor current file format ----
aaaaW_bb_cc_current_dddd.tdms : This file includes "dddd" short circuit fault motor current data of three phases with "bb.cc" % severity acquired from the motor whose capacity is "aaaa" W.
For examples, "1000W_0_00_current_interturn.tdms" means healthy inter-turn short circuit motor current data of three phases acquired from the motor whose capacity is 1.0 kW and "1500W_5_70_current_intercoil.tdms" means coil-coil short circuit fault motor current data of three phases with 5.70 % severity acquired from the motor whose capacity is 1.5 kW.

For more detailed information about this dataset, please check our article published in "Data in Brief".
Title: Vibration and Current Dataset of Three-Phase Permanent Magnet Synchronous Motors with Stator Faults
Link: https://www.sciencedirect.com/journal/data-in-brief
DOI: 10.17632/9rfc9zf3p2.4
title: Survey data to evaluate consumer behaviour and pattern of consumption of sustainable apparel: A study on consumer awareness level

description: This data set contains respondent awareness level, consumption pattern, source of information from sample and could provide insight for another researcher.
DOI: 10.17632/5djwvf5x5k.1
title: Celeris: A GPU-accelerated open source software with a Boussinesq-type wave solver for real-time interactive simulation and visualization

description: In this paper, we introduce an interactive coastal wave simulation and visualization software, called Celeris. Celeris is an open source software which needs minimum preparation to run on a Windows machine. The software solves the extended Boussinesq equations using a hybrid finite volume–finite difference method and supports moving shoreline boundaries. The simulation and visualization are performed on the GPU using Direct3D libraries, which enables the software to run faster than real-time. Celeris provides a first-of-its-kind interactive modeling platform for coastal wave applications and it supports simultaneous visualization with both photorealistic and colormapped rendering capabilities. We validate our software through comparison with three standard benchmarks for non-breaking and breaking waves.
DOI: 10.17632/gdgysh7dx3.1
title: The H3.3 K36M oncohistone disrupts the establishment of epigenetic memory through loss of DNA methylation

description: This repository contains both raw and cropped/processed westernblot images for the manuscript "The H3.3 K36M oncohistone disrupts the establishment of epigenetic memory through loss of DNA methylation". See manuscript for details.
DOI: 10.17632/h8mmnthn5w.1
title: GreEn-ER - Electricity Consumption Data of a Tertiary Building

description: This dataset provides electricity consumption data collected from the building management system of GreEn-ER. This building, located in Grenoble, hosts Grenoble-INP Ense³ Engineering School and the G2ELab (Grenoble Electrical Engineering Laboratory). It brings together in one place the teaching and research actors around new energy technologies. The electricity consumption of the building is highly monitored with plus than 300 meters. The data from each meter is available in one csv file, which contains two columns. One contains the Timestamp and the other contains de electricity consumption in kWh. The sampling rate for all data is 10 min. There are data available for 2017 and 2018. The dataset also contains data of the external temperature for 2017 and 2018. The files are structured as follows: - The main folder called "Data" contains 2 sub-folders, each one corresponding to one year (2017 and 2018). - Each sub-folder contains 3 other sub-folders, each one corresponding to a sector of the building. - The main folder "Data" also contains the csv files with the electricity consumption data of the whole building and a file called "Temp.csv" with the temperature data. - The separator used in the csv files is ";". - The sampling rate is 10 min and the unity of the consumption is kWh. It means that each sample corresponds to the energy consumption in these 10 minutes. So if the user wants to retrieve the mean power in this period (that corresponds to each sample), the value must be multiplied by 6. - Four Jupyter Notebook files, a format that allows combining text, graphics and code in python are also available. These files allow exploring all the data within the dataset. - These jupyter notebook files contains all the metadata necessary for understanding the system, like drawings of the system design, of the building etc. - Each file is named by the number of its meter. These numbers can be retrieved in tables and drawings available in the Jupyter Notebooks. - A couple of csv files with the system design are also available. They are called "TGBT1_n.csv", "TGBT2_n.csv" and "PREDIS-MHI_n.csv".
DOI: 10.17632/bhcznf2m7v.1
title: Monthly average remote sensing dataset of phytoplankton pigment concentrations in the Bohai Sea, Yellow Sea and East China Sea during 1998-2020

description: The Monthly average dataset of 16 phytoplankton pigment concentrations mainly includes chlorophyll b (Chlb), chlorophyll c2 (Chlc2), chlorophyll c3 (Chlc3), fucoxanthin (Fuco), peridinin (Perid), 19'-butanoyloxy-fucoxanthin (19'-but), 19'-hexanoyloxy-fucoxanthin (19'-hex), prasinoxanthin (Prasin), α-carotene (α-carotene, α-caro), β-carotene (β-caro), diadinoxanthin (Diad), diatoxanthin(Diato), alloxathin (Allo), zeaxanthin (Zea), neoxanthin (Neo) and violaxanthin (Viol) in the Bohai Sea, Yellow Sea and East China Sea (27°-41°N, 117°-127°E). The time coverage of the dataset is from January 1998 to December 2020. There are 276 files for each pigment dataset. The data is stored in NetCDF (network common data form) format. The data file includes pigment concentration (unit: mg m-3) , longitude and latitude information, with a spatial resolution of 9 km. Non-water and invalid pixels are represented by NaN.

The naming format of the data file is "data source identification_original data identification_month and year_pigment abbreviation_spatial resolution_data production time.nc". Examples are as follows:

SW_ S20020012002031_ 200201_ Fuco_ 9km_ 20220422.nc
MO_ A20200012020031_ 202001_ Fuco_ 9km_ 20220422.nc

Where, 'SW' represents SeaWiFS satellite; 'MO' is MODIS-Aqua satellite. The original data identification is the date label of the original data. '200201' represents January 2002. Use 'hex' and 'but' to abbreviate "19'-hex" and "19'-but". '9km' means that the spatial resolution is 9 km. The data production time is expressed as "month, month, day  day, year". '.nc' is the suffix of the NetCDF data file.