cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7680090
title: Hydrodynamic data of Hailing Island

description: This dataset records water dynamics data (water depth, wave parameters) collected during the landing period of Typhoon Chaba at the Hailing Island, Guangdong province, China. There are three observation stations, p1, p2, and p3, located at coordinates (111.9665, 21.6498), (111.9652, 21.648), and (111.9667, 21.6504), respectively. Each station is equipped with pressure sensors (RBR solo3). The data covers the period from June 30, 2022 to July 6, 2022.
DOI: 10.34740/kaggle/dsv/5072825
title: Elon Musk Tweets
DOI: 10.25381/cput.22121426
title: Relationship buying - a new paradigm in business-to-business marketing

description: Ethical clearance 2007FOBREC208 <br> The data provides an overview of over 400 South African business characteristics, demographic and experience factors, procurement strategies, and policies and procedures. The data also identifies a number of constructs, viz. preference of suppliers’ salespeople, Black Economic Empowerment status; service quality; relationship; environment sustainability; culture, employment equity and affirmative action; personal relationships, the provision of gifts; access to management and exceeding expectations, which were used to propose a new supplier preference model.
DOI: 10.5281/zenodo.6874728
title: 4-component relativistic Hamiltonian with effective QED Potentials for molecular calculations: Dataset

description: This dataset collects the unprocessed (= outputs from calculations) results discussed in the paper titled "4-component relativistic Hamiltonian with effective QED Potentials for molecular calculations", by Ayaki Sunaga, Maen Salman and Trond Saue.
DOI: 10.5281/zenodo.7597582
title: Data Set for Predicting the Performance of ATL Model Transformations

description: Model transformation languages are special-purpose languages, which are designed to define transformations as comfortably as possible, i.e., often in a declarative way. With the increasing use of transformations in various domains, the complexity and size of input models are also increasing. However, developers often lack suitable models for performance testing. We have therefore conducted experiments in which we predict the performance of model transformations based on characteristics of input models using machine learning approaches. This dataset contains our raw and processed input data, the scripts necessary to repeat our experiments, and the results we obtained. Our input data consists of the time measurements for six different transformations defined in the Atlas Transformation Language (ATL), as well as the collected characteristics of the real-world input models that were transformed. We provide the script that implements our experiments. We predict the execution time of ATL transformations using the machine learning approaches linear regression, random forests and support vector regression using a radial basis function kernel. We also investigate different sets of characteristics of input models as input for the machine learning approaches. These are described in detail in the provided documentation.pdf. The results of the experiments are provided as raw data in individual cvs files. Additionally, we calculated the mean absolute percentage error in % and the 95th percentile of the absolute percentage error in % for each experiment and provide these results. Furthermore, we provide our Eclipse plugin, which collects the characteristics for a set of given models, the Java projects used to measure the execution time of the transformations, and other supporting scripts, e.g. for the analysis of the results. A short introduction with a quick start guide can be found in README.md and a detailed documentation in documentaion.pdf.
description: This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Ti 803/4-1. The authors acknowledge support by the state of Baden-Württemberg through bwHPC.
DOI: 10.5281/zenodo.7510273
title: Data Set for Predicting the Performance of ATL Model Transformations

description: Model transformation languages are special-purpose languages, which are designed to define transformations as comfortably as possible, i.e., often in a declarative way. With the increasing use of transformations in various domains, the complexity and size of input models are also increasing. However, developers often lack suitable models for performance testing. We have therefore conducted experiments in which we predict the performance of model transformations based on characteristics of input models using machine learning approaches. This dataset contains our raw and processed input data, the scripts necessary to repeat our experiments, and the results we obtained. Our input data consists of the time measurements for six different transformations defined in the Atlas Transformation Language (ATL), as well as the collected characteristics of the real-world input models that were transformed. We provide the script that implements our experiments. We predict the execution time of ATL transformations using the machine learning approaches linear regression, random forests and support vector regression using a radial basis function kernel. We also investigate different sets of characteristics of input models as input for the machine learning approaches. These are described in detail in the provided documentation.pdf. The results of the experiments are provided as raw data in individual cvs files. Additionally, we calculated the mean absolute percentage error in % and the 95th percentile of the absolute percentage error in % for each experiment and provide these results. Furthermore, we provide our Eclipse plugin, which collects the characteristics for a set of given models, the Java projects used to measure the execution time of the transformations, and other supporting scripts, e.g. for the analysis of the results. A short introduction with a quick start guide can be found in README.md and a detailed documentation in documentaion.pdf.
description: This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Ti 803/4-1. The authors acknowledge support by the state of Baden-Württemberg through bwHPC.
DOI: 10.5281/zenodo.7677650
title: Dataset: "The challenge of ionisation chamber dosimetry in ultra-short pulsed high dose-rate Very High Energy Electron beams"

description: Dataset for the paper entitled "The challenge of ionisation chamber dosimetry in ultra-short pulsed high dose-rate Very High Energy Electron beams"
DOI: 10.5281/zenodo.7677651
title: Dataset: "The challenge of ionisation chamber dosimetry in ultra-short pulsed high dose-rate Very High Energy Electron beams"

description: Dataset for the paper entitled "The challenge of ionisation chamber dosimetry in ultra-short pulsed high dose-rate Very High Energy Electron beams"
DOI: 10.5281/zenodo.7675484
title: Dataset for Charge collection efficiency, underlying recombination mechanisms, and the role of electrode distance of vented ionization chambers under ultra-high dose-per-pulse conditions

description: Dataset for paper: Kranzer et al., Physica Medica Volume 104, December 2022, Pages 10-17 https://doi.org/10.1016/j.ejmp.2022.10.021
description: This project 18HLT04 UHDpulse has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.
description: {"references": ["Kranzer et al.,\u00a0Physica Medica\u00a0Volume 104,\u00a0December 2022, Pages 10-17"]}
DOI: 10.5281/zenodo.7675485
title: Dataset for Charge collection efficiency, underlying recombination mechanisms, and the role of electrode distance of vented ionization chambers under ultra-high dose-per-pulse conditions

description: Dataset for paper: Kranzer et al., Physica Medica Volume 104, December 2022, Pages 10-17 https://doi.org/10.1016/j.ejmp.2022.10.021
description: This project 18HLT04 UHDpulse has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.
description: {"references": ["Kranzer et al.,\u00a0Physica Medica\u00a0Volume 104,\u00a0December 2022, Pages 10-17"]}
DOI: 10.15151/esrf-es-1090034042
title: Measurement of some glasses

description: RT measurements of some glasses
DOI: 10.5281/zenodo.7627689
title: Local ground-based geophysical observation data (Borehole tilt, broadband seismic, and infradound) accomanying the 2018 phreatic eruption at Kusatsu-Shirane volcano (Motoshirane)

description: A geophysical observation dataset (borehole tilt, broadband seismic, and infrasound) accompanying the 2018 phreatic eruption at the Motoshirane cone of the Kusatsu-Shirane volcano. The data is from the local geophysical observation network operated by Kusatsu-Shirane Volcano Observatory, Tokyo Institute of Technology. All time is JST (UTC+9). Terada et al. (2021) and Yamada et al. (2021) describe station locations and instrumentations. Tilt (text files: 20190123_stn_1_Hz.txt) format: yy/mm/dd hour:min sec NS tilt EW tilt Broadband seismic and infrasound waveforms (sac files) (1801230950_stn_cmp.s) *stn: station name *cmp: component References Terada, A., Kanda, W., Ogawa, Y., Yamada, T., Yamamoto, M., Ohkura, T., et al. (2021). The 2018 phreatic eruption at Mt . Motoshirane of Kusatsu – Shirane volcano, Japan: Eruption and intrusion of hydrothermal fluid observed by a borehole tiltmeter network. Earth, Planets and Space, 73. https://doi.org/10.1186/s40623-021-01475-4 Yamada, T., Kurokawa, A. K., Terada, A., Kanda, W., Ueda, H., Aoyama, H., et al. (2021). Locating hydrothermal fluid injection of the 2018 phreatic eruption at Kusatsu-Shirane volcano with volcanic tremor amplitude. Earth, Planets and Space, 73(1), 1–15. https://doi.org/10.1186/s40623-020-01349-1
DOI: 10.6069/yahe-fr49
title: Dynamic monitoring of myeloma minimal residual disease with targeted mass spectrometry

description: Serum samples from multiple myeloma (MM) patients are collected regularly for conventional tests to quantify the M-protein longitudinally. However, the limited sensitivity of conventional tests makes quantification of minimal residual disease (MRD) difficult. MRD can be quantified with highly sensitive molecular techniques on bone marrow, but bone marrow procedures are invasive and cannot be performed regularly. In this study, we introduce highly sensitive targeted mass spectrometry (MS-MRD) to quantify M-protein from patient serum. Therefore, we can follow each patient’s course of disease and dynamically measure MRD.
DOI: 10.5281/zenodo.6624935
title: Global River Morphology (GRM)

description: The Global River Morphology (GRM) map shows the global distribution of rivers and their channel belt deposits by morphology. The data are derived based on a VGG-19 modified CNN classifying 2020 Landsat-8 imagery at a 30m global resolution.
DOI: 10.5281/zenodo.7657182
title: Global Channel Belt (GCB)

description: The Global Channel Belt (GCB) map show the global extent of river channel belts and the morphology of the river channel as either single- or multi-threaded. The data are derived based on a VGG-19 modified CNN classifying 2020 Landsat-8 imagery at a 30 m global resolution.
DOI: 10.5281/zenodo.7680163
title: Global Channel Belt (GCB)

description: The Global Channel Belt (GCB) map show the global extent of river channel belts and the morphology of the river channel as either single- or multi-threaded. The data are derived based on a VGG-19 modified CNN classifying 2020 Landsat-8 imagery at a 30 m global resolution.
DOI: 10.6084/m9.figshare.22179916
title: 1_雙重作業運動研究資料_刪除E13-博士.zip

description: The effect of dual-task exercise on cognitive functions and fitness in older adults
DOI: 10.6084/m9.figshare.22179916.v1
title: 1_雙重作業運動研究資料_刪除E13-博士.zip

description: The effect of dual-task exercise on cognitive functions and fitness in older adults
DOI: 10.5281/zenodo.7677337
title: DATASET: ACOUSTIC SUBJECTIVE TEST DATABASE

description: This database is the result of a survey carried out among more than one hundred professional musicians, music students, teachers and aficionados, to determine which configuration of the theatre "Banda Primitiva de Lliria" had a better acoustic performance. It was made up using Filemaker format and is related to the studies carried out in the frame of the PhD dissertation "Revisión de los valores del espectro de absorción de la caja de escena en teatros, mediante la aplicación del método de superficies de respuesta.", by Blanca Pérez-Aguilar
DOI: 10.5281/zenodo.7677338
title: DATASET: ACOUSTIC SUBJECTIVE TEST DATABASE

description: This database is the result of a survey carried out among more than one hundred professional musicians, music students, teachers and aficionados, to determine which configuration of the theatre "Banda Primitiva de Lliria" had a better acoustic performance. It was made up using Filemaker format and is related to the studies carried out in the frame of the PhD dissertation "Revisión de los valores del espectro de absorción de la caja de escena en teatros, mediante la aplicación del método de superficies de respuesta.", by Blanca Pérez-Aguilar
DOI: 10.6084/m9.figshare.21707588
title: questionnaire data

description: low-speed driving questionnaire<strong> </strong>data
DOI: 10.21961/mdm:27640
title: MSTS untere Extremitaet ORTH MS University Hospital Muenster (UKM)

description: Hospital Routine Documentation Form at the University Hospital Muenster. Original Form name: MSTS untere Extremitaet ORTH MS.
DOI: 10.34740/kaggle/dsv/5073093
title: AutoXGB
DOI: 10.17632/cp6fjtnw24.2
title: PDPSLT instances

description: The instances at hand constitute problem instances for the Pickup and Delivery Problem with split loads and transshipments. They have been used for the computational experiments in "Wolfinger, D., Salazar-González, J.J., 2020. The Pickup and Delivery Problem with Split Loads and Transshipments: A Branch-and-Cut Solution Approach. European Journal of Operational Research. To appear."
DOI: 10.17632/cp6fjtnw24.3
title: PDPSLT instances

description: The instances at hand constitute problem instances for the Pickup and Delivery Problem with split loads and transshipments. They have been used for the computational experiments in "Wolfinger, D., & Salazar-González, J. J. (2021). The pickup and delivery problem with split loads and transshipments: A branch-and-cut solution approach. European Journal of Operational Research, 289(2), 470-484."
DOI: 10.34740/kaggle/dsv/5073096
title: LUFlow Network Intrusion Detection Data Set
DOI: 10.25345/c5s46hg6p
title: MassIVE MSV000091368 - Zone of Inhibition Study with Tetromadurin Isolation
title: Isolation and dereplication of antitubercular compounds produced by South African fila-mentous actinobacteria by HPLC-MS/MS anal-ysis of their zones of growth inhibition
DOI: 10.5281/zenodo.7586039
title: Bioenergy-Technology-Database (BET.db)

description: Bioenergy is a crucial element of the future energy system with range of applications in the electricity, heat and transport sectors. One major challenge for the analysis and optimisation of the bioenergy system is the degree of diversity and complexity compared to wind or solar energy. A coherent data base needs to encompass the different entities such as bioresources, conversation process and process chains. Thus Bio-Energy Technology database (BET.db) was developed by merging various existing datasets into a SQLite database. The resulting BET.db provides consistent sets for 141 biogenic raw materials as well as energy carriers, 259 conversation technologies and 134 supply concepts for energy provision . BET.db was developed as part of a non-public research project for system optimal biomass allocation (SoBio). We have valiate the usability of BET.db by connecting the Bioenergy Optimisation Model (BENOPT). For this use case we can ensure a transparent and reproducible data source for such modeling tasks.
description: The primary data comes mainly from three existing datasets for which the references are given here. The database contains an integrated referencing system. Each individual data point is thus traceable, regardless of whether it comes from the primary sources mentioned above or was researched elsewhere.
description: {"references": ["V. Lenz, M. Jordan, Technical and economic data of renewable heat supply systems for different heat sub-sectors.: Supplementary material, 2019. https://data.mendeley.com/datasets/v2c93n28rj/2", "K. Meisel, M. Millinger, K. Naumann, F. M\u00fcller-Langer, S. Majer, D. Thr\u00e4n, Future Renewable Fuel Mixes in Transport in Germany under RED II and Climate Protection Targets, Energies 13 (7) (2020) 1712. https://doi.org/10.3390/en13071712", "M. Lauer, M. Dotzauer, M. Millinger, K. Oehmichen, M. Jordan, J. Kalcher, S. Majer, D. Thraen, The Crucial Role of Bioenergy in a Climate\u2010Neutral Energy System in Germany, Chem Eng & Technol 90 (1) (2022) 68. https://doi.org/10.1002/ceat.202100263"]}
DOI: 10.5281/zenodo.7586038
title: Bioenergy-Technology-Database (BET.db)

description: Bioenergy is a crucial element of the future energy system with many applications in the electricity, heat or transport sector. A major challenge for the analysis and optimisation of bioenergy systems is the degree of diversity and complexity compared to other energy technology domains like wind or solar energy. Bio-Energy Technology database (BET.db) should be a coherent data base to encompass the different entities such as bioresources, conversation process and process chains. BET.db was developed by merging various existing datasets into a SQLite database. The resulting BET.db provides consistent sets for 141 biogenic raw materials as well as energy carriers, 259 conversation technologies and 134 supply concepts for energy provision as well as many other items. We have valiate the usability of BET.db by connecting the Bioenergy Optimisation Model (BENOPT). For this use case we can ensure a transparent and reproducible data source for such modeling tasks. <br> This is an update of the intial version 0.1. Major revisions was made on changing tables and attribute names and subsequently affected views. Also the layout of the database schema was refurbished, were graphical connections between foreign and primary keys are altered to the crow's foot notation, according to Crow's_foot_notation in wikipedia.org or rather the Crow’s Feet Are Best - blog post .
description: The primary data comes mainly from three existing datasets for which the references are given . The database contains an integrated referencing system itself, where each single data point has a reference. Each individual data point is thus traceable, regardless of whether it comes from the primary sources mentioned above or was researched elsewhere.
description: {"references": ["V. Lenz, M. Jordan, Technical and economic data of renewable heat supply systems for different heat sub-sectors.: Supplementary material, 2019. https://data.mendeley.com/datasets/v2c93n28rj/2", "K. Meisel, M. Millinger, K. Naumann, F. M\u00fcller-Langer, S. Majer, D. Thr\u00e4n, Future Renewable Fuel Mixes in Transport in Germany under RED II and Climate Protection Targets, Energies 13 (7) (2020) 1712. https://doi.org/10.3390/en13071712", "M. Lauer, M. Dotzauer, M. Millinger, K. Oehmichen, M. Jordan, J. Kalcher, S. Majer, D. Thraen, The Crucial Role of Bioenergy in a Climate\u2010Neutral Energy System in Germany, Chem Eng & Technol 90 (1) (2022) 68. https://doi.org/10.1002/ceat.202100263"]}
DOI: 10.6084/m9.figshare.22182007.v1
title: grape_flavor_data.xlsx

description: We select the fresh grapes from June 2021 to April 2022, mainly including 15 varieties such as Kyoho, Summer black, Shine Muscat, etc., a total of 126 batches of samples. The juice is extracted and filtered as a sample, and the physical and chemical indicators of the grape pulp are tested . <br> we provide sensory training to teachers and students in our school who voluntarily participate in the evaluation. The evaluation criteria and the meanings of score intervals are explained explicitly. And their scores were provided in the data set.
DOI: 10.5281/zenodo.7680248
title: dataset of papers from PubMed related to Dendritic potential as immune contraception

description: This is the dataset from PubMed. It consist of two files: 1. Abstract of each previous studies used in form of txt file 2. Details of each previous studies used in form of CSV file
DOI: 10.5281/zenodo.7680247
title: dataset of papers from PubMed related to Dendritic potential as immune contraception

description: This is the dataset from PubMed. It consist of two files: 1. Abstract of each previous studies used in form of txt file 2. Details of each previous studies used in form of CSV file
DOI: 10.5281/zenodo.7679164
title: Signs of life detection behind obstacles using an UWB radar sensor

description: The "Signs of life detection behind obstacles using an UWB radar sensor" dataset was created by University of West Attica, by collecting data from 9 people using an UWB sensor, which was the X4M200 UWB radar sensor by Novelda, with and without the existence of a wall between the subject and the radar for the purposes of RESCUER project (https://rescuerproject.eu/ - a Horizon 2020 Research & Innovation Programme under Grant Agreement No.101021836). In all cases, the subject was lying down in the same stance for about 1 min and the radar was placed in four different positions: a) 0.2 m from the ground, b) 0.5 m from the ground, c) 1 m from the ground, d) 1 m from the ground and with a 45 degree angle. For comparison purposes, we also include in the dataset the case where no human is present within the radar's detection area. The subjects were placed in a distance between 0.5 and 5 metres from the radar and different stances were considered, while data were collected both for the amplitude (designated as abs) and the phase of the signal (designated as angle). This information is designated in each filename. For example, the filename "2 facing radar abs.csv", indicates that the subject is placed in 2 metres away from the radar, he/she is facing the radar and the file contains the signal's amplitude. The sampling rate of the radar was set to 17 samples per second and a distance step of about 0.05144 m was also considered.
DOI: 10.6084/m9.figshare.21136579.v6
title: Placental volume or area? Which is the most accurate method for diagnosing the placenta accreta spectrum in pregnant women with placenta previa?

description: Supplementary contents 1 and 2 PAS videos Excel Data
DOI: 10.6084/m9.figshare.22182142
title: Nanoindentation test results

description: Mudstone nanoindentation test results
DOI: 10.6084/m9.figshare.16870948
title: Entomological origin detection of honey from <i>Apis mellifera</i> and <i>Apis cerana javana</i> in Indonesia based on the Major Royal Jelly Protein 2 (mrjp2) gene

description: The entomological origin of honey was detected in the subtropical <i>Apis cerana cerana</i> using two sets of <i>Major Royal Jelly Protein 2</i> (<i>mrjp2</i>) primers. Due to the high genetic divergence of <i>A. cerana</i>, this study aimed to confirm that the primers can be used to detect honey origin from <i>A c. javana</i> and <i>Apis mellifera</i> in Indonesia. The <i>mrjp2</i> gene was amplified using M-F M-R and C-F C-R primers at various annealing temperatures to find the optimal temperature based on the presence-absence of the amplicon. Honey was successfully differentiated from 11 colonies of <i>A. mellifera</i> and <i>A. c. javana</i> using M-F and M-R primers at annealing temperatures of 50 °C, 53 °C, 55 °C, 57 °C, and 59 °C. However, caution should be placed on using these primers when used to amplify <i>A. cerana</i> at 47 °C. This study confirmed that C-F and C-R primers are specifically applicable when amplifying <i>A. c. javana</i>.