cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/dh3hjdf4fc.1
title: Equilibrium point defect and charge carrier concentrations in a material determined through calculation of the self-consistent Fermi energy

description: A concise procedure to determine the self-consistent Fermi energy and defect and carrier concentrations in an extended crystalline system is presented. It is assumed that the formation enthalpies of a set of variously charged point defects in thermodynamic equilibrium are known, as well as the density of electronic states in the defect-free system. By applying the constraint of overall charge neutrality, the self-consistent Fermi energy is determined using an iterative searching routine. The procedure is incorporated within a Fortran code ‘SC-FERMI’: the input consists of the defect formation energies, density of sites where they can form, and the degeneracy of each charge state; the material band gap; and the calculated density of states of the pristine system. The output is the self-consistent Fermi energy, the total concentrations of each defect as well as the concentration of its individual charge states, and the free carrier concentrations. Furthermore, the procedure facilitates fixing the concentration of one or more defects and determining the resulting self-consistent Fermi energy and concentrations of other defects (performed using the related code ‘FROZEN-SC-FERMI’), thus modelling ‘frozen-in’ defects which may form by kinetic, rather than thermodynamic, processes. One can fix the total concentration or the concentration of a particular charge state; it is also possible to introduce new defects with a fixed concentration, but here the charge state must be specified. The background theory is discussed in some detail, and the operation of the program is demonstrated by some examples.
DOI: 10.17632/fvz9mrnjzy.1
title: Dataset containing posts and comments from university publics on the social media VKontakte (2022-2023)

description: The dataset consists of content published in groups of Russian universities on the social media VKontakte. The dataset contains posts and comments from 9,215 university publics from June 2022 to August 2023.
DOI: 10.17632/35mkyzcc7p.4
title: Moderate Aerobic Exercise in combination with metformin in Intermuscular Adipose Tissue (IMAT) and its Functional MRI in Non-Streptozotocin Prediabetic Rats

description: Original dataset of the manuscript "Moderate Aerobic Exercise in combination with metformin in Intermuscular Adipose Tissue (IMAT) and its Functional MRI in Non-Streptozotocin Prediabetic Rats"
DOI: 10.15468/dl.f8ma5z
title: Occurrence Download

description: A dataset containing 9686 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Picea abies (L.) H.Karst.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 9686 records from 216 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009166-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/j8d8pfkvj2.1
title: Vibration and Motor Current Dataset of Rolling Element Bearing Under Varying Speed Conditions for Fault Diagnosis: Part 3

description: Rolling element bearing utilized for the wind turbine, electric vehicles are often operated under varying speed conditions other than constant speed due to external wind or load variations. It is very difficult to diagnose a rolling element bearing under varying speed conditions because changing the rotational speed means that the fault-related features are variable. To solve this problem, a lot of data are needed, however, rolling element bearing under time-varying speed conditions is difficult to secure a large amount of data due to the complexity of experimental setups. Therefore, many datasets for diagnosing rolling element bearing under constant speed conditions have been distributed, but there is no dataset under variable speed conditions. This article discloses vibration and motor current data for bearing faults under varying speed conditions from 680 RPM to 2460 RPM. Dataset are acquired using four ceramic shear ICP-based accelerometers, three current transformers (CT), and one laser-based tachometer with SIEMENS and National Instruments (NI) data acquisition (DAQ) board. The bearing conditions include healthy bearing, bearings with inner race faults, and bearings with outer race faults. For each faulty bearing condition, the three-phase induction motor is operated under randomly varying speed conditions. The speed information can extract from not only motor current data but also the tachometer. This data can be used for research that can diagnose under varying speed conditions where time-frequency analysis cannot be performed because of the frequency changes.




---- Description of vibration file format ----
Vibration data file contains five columns namely ‘Time Stamp’, ‘x_direction_housing_A’, ‘y_direction_housing_A’, ‘x_direction_housing_B’, and ‘y_direction_housing_B’. The unit of the vibration is ‘gravitational constant (g)’. 

vibration_aaaa_bbbb.csv : This file is "bbbb"-th vibration data includes rotating speed data of the condition of "aaaa".



---- Description of motor current file format ----
Motor current data file contains five columns namely ‘Time Stamp’, ‘R_phase’, ‘S_phase’, and ‘T_phase’. The unit of the motor current is ‘Ampare (A)’.

current_aaaa_bbbb.csv : This file is "bbbb"-th motor current data includes rotating speed data of the condition of "aaaa".



---- Description of rotating speed file format ----
Rotating speed data file contains two columns namely ‘Time Stamp’, and ‘speed’. The unit of the acoustic is revolutions per minute (RPM)’.

rpm_aaaa_bbbb.csv : This file is "bbbb"-th speed data includes rotating speed data of the condition of "aaaa".


Datasets are divided into three parts because of storage limitations (part1, part2, and part3). For more details, please refer to the "Data in Brief" journal (will be submitted until Aug. 31, 2022).
DOI: 10.17632/zcgw2n5bjf.1
title: VAN-DAMME: GPU-accelerated and symmetry-assisted quantum optimal control of multi-qubit systems

description: We present an open-source software package, VAN-DAMME (Versatile Approaches to Numerically Design, Accelerate, and Manipulate Magnetic Excitations), for massively-parallelized quantum optimal control (QOC) calculations of multi-qubit systems. To enable large QOC calculations, the VAN-DAMME software package utilizes symmetry-based techniques with custom GPU-enhanced algorithms. This combined approach allows for the simultaneous computation of hundreds of matrix exponential propagators that efficiently leverage the intra-GPU parallelism found in high-performance GPUs. In addition, to maximize the computational efficiency of the VAN-DAMME code, we carried out several extensive tests on data layout, computational complexity, memory requirements, and performance. These extensive analyses allowed us to develop computationally efficient approaches for evaluating complex-valued matrix exponential propagators based on Padé approximants. To assess the computational performance of our GPU-accelerated VAN-DAMME code, we carried out QOC calculations of systems containing 10 - 15 qubits, which showed that our GPU implementation is 18.4× faster than the corresponding CPU implementation. Our GPU-accelerated enhancements allow efficient calculations of multi-qubit systems, which can be used for the efficient implementation of QOC applications across multiple domains.
DOI: 10.17632/dtzfwv5vf2.1
title: Data for: Valuing the Urban Hukou in China:Evidence from a Regression Discontinuity Design for Housing Price
DOI: 10.17632/g2p7vwxyn2.4
title: Young Adult's Affective Data (YAAD) Using ECG and GSR Signals

description: We present the young adult's data set of Electrocardiograms (ECG) and Galvanic Skin Response (GSR) for the emotion recognition task, helpful in human-computer interaction for individuals with cognitive and physical disorders. Wearable shimmer3 ECG and GSR sensors were used to acquire data from a total of 25 participants. The dataset consists of three parts, raw data, extracted features for ECG, and self-annotation labels. Raw data consists of multimodal data and single modal data in .mat format. Multimodal data consists of ECG and GSR for 12 participants, provided with 21 stimulus videos divided into three sessions. Similarly, single modal data consists of ECG data acquired from 13 other participants. These physiological signals correlate with the six basic emotions of surprise, anger, fear, happiness, sadness, disgust, and the addition of a neutral state. Each of these seven states was further divided into five levels of intensity of felt emotion, making a total of 35 emotional states.  Self annotation was performed by participants for these emotional states as well as scores of valence, arousal, and dominance. Twenty emotion-related features were extracted from each ECG sample and also provided as supplementary material for further analysis. This data provides a valuable addition to the physiological signal-based emotion recognition for the larger set of emotions and young adults.
DOI: 10.17632/skjvm46zn7.1
title: RADAR Pulse Repetition Interval Modulation Recognition 

description: This dataset was developed to prepare a novel PRI radar signal dataset. The experiment was conducted at Imam Khomeini marine university, Nowshahr, between September and December 2020. For this purpose, the required system was designed and placed in an environment with a high density of radar signals for eight months. To achieve the desired capabilities and meet the requirements, designed electronic support systems have general sections: radio antennas and receivers; hardware, control, and power supply units; processing units (processor, software, and processor units); and user consoles.
The list of selected equipment for designing the desired system is given in Table 1. This passive system receives, detects, processes, and analyzes radar signals in the frequency range of 2-18 GHz. According to the tasks and requirements, the system consists of two general parts: the external part (i.e., antennas and radio receivers) and the internal part (i.e., processor set and hardware units), and the connection between these two parts via cable interfaces are established. The antenna arrangement pattern according to each antenna’s radiation pattern and coverage and selecting the required number of antennas is designed as an array to cover the entire 360 degrees. Depending on the type of receivers, the system processor can process the output signals of the receivers in real-time.
DOI: 10.17632/6nf4pcydtw.1
title: An annotated bibliography showing 51 continuous centuries that recognize “democracy”’s definitional, conceptual, and practiced pluralism

description: 510 Years of acknowledgements, from multilinguistic literature, demonstrating that “democracy” means more than one thing and has been practiced in more than one place
DOI: 10.17632/yf2dgcfmmh.4
title: mHeart - mHealthCare Platform Adapted to the Heart Transplant Population - Technical Specifications and Software Source Code

description: The information is provided to increase the data transparency and the scalability of eHealth research and particularly the mHeart studies scalability. This dataset contains relevant information on: - The mHealthCare Platform Technological Description and Specifications. This file aims to describe the general mHealthcare Platform developed by the private firm which has been thereafter adapted to the heart transplant specifications (mHeart System). - The mHeart source code description of the 3 applications (website, app Android, app Apple) and storage location. - A video of the clinical use of the mHeart mobile application. - An apk file with a DEMO (Spain Version 2015). Please, notice that this is a dynamic process. Multiples versions will be uploaded since mHeart was developed. Consult the DEMO access directly on Stores. - User Guidelines (Spain Version 2015) - Scientific Authorship Statement - mHeart trademark - the mHeart System funding and reimbursement model. The mHealthCare Platform is an internet-based system to carry out integral healthcare for disease and therapy management in any population. The first version uploaded in Hospital de la Santa Creu i Sant Pau (HSCSP) was directed at transplant populations and was specifically adapted to the heart transplant population in the ambulatory setting. The mHeart program has been classified by authors as a Behavior Intervention Technology (BIT) to facilitate the following overall clinical goals: (1) health behavior change (i.e. increase patients’ healthy behaviors and prevent the onset of disease); and (2) targeted disease management (i.e. facilitate therapeutic interventions and improve patient’s self-management). The mHeart tool is a mobile phone app connected to a website for use by providers and patients. The tool can be used simultaneously on distinct devices to facilitate caregiver and guardian support. The mobile application can be downloaded for free from the Google and Apple online stores. The website link is salud.trilema.es. The system was developed by Socioemprende SL Technical Team. Scientific advice was provided by the heart transplant interdisciplinary healthcare team and directed by the Pharmacy Department, HSCSP. For further questions about the System, please contact with the scientific coordinator Mar Gomis-Pastor: mar@margomis.com
DOI: 10.17632/cj4hc9f2g4.3
title: Prediction of narrow HT-SMA thermal hysteresis using machine learning: A data file

description: These data are reported in a research article entitled “Prediction of narrow HT-SMA thermal hysteresis behaviour using explainable machine learning” [1].

Reference:
[1]	Ronald Machaka, Precious M. Radingoana, Prediction of narrow HT-SMA thermal hysteresis behaviour using explainable machine learning, Mater. Today Commun. 35 (2023) 105806. https://doi.org/10.1016/j.mtcomm.2023.105
DOI: 10.17632/4ckb278tpw.1
title: UASB reactor and AGS-SBR contaminant removals and components specifications

description: This data set includes the influent and effluent concentrations and removal percentages of contaminants and components specifications for a UASB reactor and AGS-SBR used for greywater treatment in a decentralized approach.
DOI: 10.17632/ht4r76w989.1
title: Boosting methods for multi‑class imbalanced data classification

description: Since canonical machine learning algorithms assume that the dataset has equal number of samples in each class, binary classification became a very challenging task to discriminate the minority class samples efficiently in imbalanced datasets. For this reason, researchers have been paid attention and have proposed many methods to deal with this problem, which can be broadly categorized into data level and algorithm level. Besides, multi-class imbalanced learning is much harder than binary one and is still an open problem. Boosting algorithms are a class of ensemble learning methods in machine learning that improves the performance of separate base learners by combining them into a composite whole. This paper’s aim is to review the most significant published boosting techniques on multi-class imbalanced datasets. A thorough empirical comparison is conducted to analyze the performance of binary and multi-class boosting algorithms on various multi-class imbalanced datasets. In addition, based on the obtained results for performance evaluation metrics and a recently proposed criteria for comparing metrics, the selected metrics are compared to determine a suitable performance metric for multi-class imbalanced datasets. The experimental studies show that the CatBoost and LogitBoost algorithms are superior to other boosting algorithms on multi-class imbalanced conventional and big datasets, respectively. Furthermore, the MMCC is a better evaluation metric than the MAUC and G-mean in multi-class imbalanced data domains.
DOI: 10.17632/v6p265xv5v.1
title: tDCS, Exercise and BBB Permeability

description: This study aimed to assess the unique and combined effect of tDCS and exercise on BBB permeability, as assessed through changes in salivary S100B. It was hypothesised that active tDCS would induce a significant increase in S100B when compared to sham stimulation and no stimulation. It was also hypothesised that the increase in S100B concentration would be greater following active tDCS and exercise compared to tDCS or exercise alone. Regarding the effects of exercise, a significant increase in S100B following the cycling task was hypothesised.
DOI: 10.17632/wkc7882548.1
title: Data for: A harmonized calculation model for transforming EU bottom-up energy efficiency indicators into empirical estimates of policy impacts

description: Abstract of associated article: This study is an impact analysis of European Union (EU) energy efficiency policy that employs both top-down energy consumption data and bottom-up energy efficiency statistics or indicators. As such, it may be considered a contribution to the effort called for in the EU's 2006 Energy Services Directive (ESD) to develop a harmonized calculation model. Although this study does not estimate the realized savings from individual policy measures, it does provide estimates of realized energy savings for energy efficiency policy measures in aggregate. Using fixed effects panel models, the annual cumulative savings in 2011 of combined household and manufacturing sector electricity and natural gas usage attributed to EU energy efficiency policies since 2000 is estimated to be 1136PJ; the savings attributed to energy efficiency policies since 2006 is estimated to be 807PJ, or the equivalent of 5.6% of 2011 EU energy consumption. As well as its contribution to energy efficiency policy analysis, this study adds to the development of methods that can improve the quality of information provided by standardized energy efficiency and sustainable resource indexes.
DOI: 10.17632/mjhr46dkj6.1
title: Development of Anomaly Detectors for HVAC Systems using Machine Learning

description: The dataset refers to the operating parameters of an HVAC system that controls the environmental comfort of a non-residential building located in Turin (Italy).
The dataset contains 11 variables:
1. timestamp;
2. temperatures of return, supply and outdoor air [°C];
3. relative humidities of return, supply and outdoor air [%];
4. the temperature setpoint of the return air [°C];
5. the saturation temperature in the humidifier [°C];
6.  power required by the fans [kW];
7. energy required by the fans [kWh].
The data refer to the winters 2019-2020 and 2020-2021. The data is acquired every 15 minutes.
DOI: 10.17632/tt5ntb4zyv.1
title: Centrifuge database

description: The Centrifuge database was built by 16s rRNA sequencing of the type strain from the National Center for Biotechnology Information. This database can be used to do taxonomic classification of bacterial groups.
DOI: 10.17632/6j69bc2mdx.2
title: Performance Evaluation of Discharged Wastewater Quality from Guna water Treatment Plant for Potable Purpose

description: Water is one of the most crucial and non substitutable environmental resources. Adequate, quality, safe and affordable supply of drinking water is a basic need for human life. Guna Spring Water Bottling Factory (GSWBF) is one of the major water industries in Ethiopia characterized by excess water discharged to the nearest river considered as wastewater. Yet no study was conducted to evaluate the status of discharged wastewater and its impact to the environment and the downstream people though the factory does not use toxic chemical as the source of raw water is not exposed to any waste. The effect of operational factors such as flow arte, discharge time with in different unit process such as softener, sand filter, activated Carbone and ultra filter were investigate. The discharged water quality analysis was conducted by physical, chemical and biological parameters of water in association with set of standards. These parameters are directly related to the safety of drinking water to human use. The physical analyses of all parameters were within the recommended range. Investigation of phosphate has shown values ranging between 0.01 mg/l to 0.72 mg/l. The laboratory result on bacteriological analysis has shown no indicator organism (total coli form, feacal coli form and Escherichia coli tye1) at the discharged water which the factory. Regarding washing time rate there was no significant change on physico-chemical and bacteriological parameters after 10 minutes at 4m3/hr flow rate during surface wash time.
DOI: 10.17632/ybr3pr7bz8.1
title: Machine Learning-Based Prediction of Acoustic Indicators for Enhanced Educational Building Comfort

description: The dataset comprises two types: numerical data and heat maps. The numerical dataset includes extensive parametric simulations of acoustic indicators in different geometric configurations using the Grasshopper and Pachyderm plugins. These datasets were utilized to predict both numerical and visual acoustic indicators using the CatBoost algorithm and the pix2pix algorithm. The results demonstrate remarkable accuracy, ranging from 89% to 99% in the numerical portion using CatBoost, with PSNR indices ranging from 0.817 to 0.970, and SSIM indices ranging from 15.56 to 31.57 in the visual section.
DOI: 10.17632/z87gvghpdp
title: Indoor spatial tracking of users

description: The monitoring system used for the spatial acquisition of air temperatures was realised by installing a grid of 20 T-type thermocouples spaced 0.25m from the ceiling and with an interspace of 0.60m (the picture of the thermocouple arrangement is attached to the data). In order to measure the correct air temperature at each point, the thermocouples were connected to the Kaye K170 Ice Point Reference for the absolute zero reference, the Agilent 34420A voltmeter for measuring voltages and the Hewlett-Packard HP34901A acquisition module for reading each value.