cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/w9hdbnrk85.1
title: Repositório de Questões do ENADE - Bacharelado em Ciência da Computação (2005 até 2021)

description: Este dataset reúne todas as questões das provas do Exame Nacional de Desempenho dos Estudantes (ENADE) para o curso de Bacharelado em Ciência da Computação, abrangendo todas as edições do exame desde 2005 até 2021. O ENADE, promovido pelo INEP (Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira), avalia o desempenho dos estudantes em relação aos conteúdos programáticos, habilidades e competências previstas nas diretrizes curriculares nacionais para o curso de Ciência da Computação.

Este dataset fornece uma base completa para análises quantitativas e qualitativas sobre a formação acadêmica em Ciência da Computação no Brasil, além de permitir comparações entre diferentes períodos e temas de avaliação. 
O dataset esta composto por pastas representando os anos (2005, 2008, etc), onde em cada pasta contem a prova completa e uma pasta chamada "Questoes" com um print de cada questão separada.
DOI: 10.17632/zmj566r6m4.2
title: Trace elements in zircon record the multi-step buildup of Archean protocontinental crust in the Barberton Greenstone Belt

description: Supplementary Material 2: Trace and rare earth element data from the SUMAC SHRIMP-RG facility.
Supplementary Material 3: Lu-Hf isotope data from the LaserChon Lab
Supplementary Material 4: O isotope data from the GFZ Potsdam
Supplementary Material 5: All accepted data used in publication
DOI: 10.17632/87rs7mv2ws.1
title: P- and S-receiver function data in the western part of the Makran Subduction Zone

description: This dataset consists of the P- and S-receiver functions and the waveforms for seismic stations located in the western part of the Makran Subduction Zone.
DOI: 10.17632/f2v94hj7jm.1
title: Brugge_Breast_Atlas_CyTOF_Organoids

description: A Breast Atlas Integrating Single-Cell Proteomics and Transcriptomics, Developmental Cell, 2022

Raw, processed, and final organoid CyTOF data (relating to Figures 7/S7)
DOI: 10.17632/tnsjfb86vy.2
title: Energy and parametric analysis of solar absorption cooling systems for an office building: A case study

description: Figures describing the climate situation in Souk Ahras Revised version
DOI: 10.17632/xt69cnwh56.1
title: 1Hz GPS Tracking Data on Minibus Taxi Paratransit Vehicles in South Africa

description: To date, GPS tracking data for minibus taxis has only been captured at a sampling frequency of once per minute. This is the first GPS tracking data captured on a per-second (1 Hz) basis.  Minibus taxi paratransit vehicles in South Africa are notorious for their aggressive driving behaviour characterised by rapid acceleration/deceleration events, which can have a large effect on vehicle energy consumption. Infrequent sampling cannot capture these micro-mobility patterns, thus missing out on their effect on vehicle energy consumption (kWh/km). We hypothesised that to construct high fidelity estimates of vehicle energy consumption, higher resolution data that captures several samples per movement would be needed. Estimating the energy consumption of an electric equivalent (EV) to an internal combustion engine (ICE) vehicle is requisite for stakeholders to plan an effective transition to an EV fleet. Energy consumption was calculated following the kinetic model outline in "The bumpy ride to electrification: High fidelity energy consumption estimates for minibus taxi paratransit vehicles in South Africa". 

Six tracking devices were used to record GPS data to an SD card at a frequency of 1Hz. The six recording devices are based on the Arduino platform and powered from alkaline battery packs. The device can therefore operate independently of any other device during tests. The acquired data is separately processed after the completion of data recording.  Data captured is initiated with the press of a button, and terminated once the vehicle reached the destination. Each recorded trip creates an isolated file. This allows for different routes to be separately investigated and compared to other recordings made on the same route. 

There are 62 raw trip files, all found in the attached 'raw data' folder under the corresponding route and time of day in which they were captured. The raw data includes date, time, velocity, elevation, latitude, longitude, heading, number of satellites connected, and signal quality. Data was recorded on three routes, in both directions, for a total of six distinct routes. Each route had trips recorded in the morning (before 11:30AM) , afternoon (11:30AM-4PM) and evening (after 4PM). 

The processed data is available in the 'Processed Data' folder. In addition to the raw data, these processed data files include the displacement between observations, calculated using Geopy's geodesic package, and the estimated energy provided by the vehicle's battery for propulsion, braking, and offload work.  The python code for the kinetic model can be found in the attached GitHub link https://github.com/ChullEPG/Bumpy-Ride.

Future research can use this data to develop standard driving cycles for paratransit vehicles, and to improve the validity of micro-traffic simulators that are used to simulate per-second paratransit vehicle drive cycles between minutely waypoints.
DOI: 10.17632/fgvscdjsmt.4
title: FlameVision : A new dataset for wildfire classification and detection using aerial imagery 

description: The FlameVision dataset is a comprehensive aerial image dataset designed specifically for detecting and classifying wildfires. It consists of a total of 8600 high-resolution images, with 5000 images depicting fire and the remaining 3600 images depicting non-fire scenes. The images are provided in PNG format for classification tasks and JPG format for detection tasks. The dataset is organized into two primary folders, one for detection and the other for classification, with further subdivisions into train, validation, and test sets for each folder. To facilitate accurate object detection, the dataset also includes 4500 image annotation files. These annotation files contain manual annotations in XML format, which specify the exact positions of objects and their corresponding labels within the images. The annotations were performed using Roboflow, ensuring high quality and consistency across the dataset. One of the notable features of the FlameVision dataset is its compatibility with various convolutional neural network (CNN) architectures, including EfficientNet, DenseNet, VGG-16, ResNet50, YOLO, and R-CNN. This makes it a versatile and valuable resource for researchers and practitioners in the field of wildfire detection and classification, enabling the development and evaluation of sophisticated ML models.
DOI: 10.17632/zm45zhp8z5.1
title: Hyundai Cars Maintenance Dataset

description: he "Hyundai Cars Maintenance Dataset" is a comprehensive dataset containing information related to maintenance aspects of Hyundai cars. It consists of 1100 entries, each representing a Hyundai car, with details on various parameters relevant to maintenance. Below is a detailed description of each variable included in the dataset:

Engine Temperature (°C): This variable represents the temperature of the engine of each car, measured in degrees Celsius. Engine temperature is a critical parameter to monitor as it can indicate potential issues with the cooling system or engine performance.

Brake Pad Thickness (mm): This variable indicates the thickness of the brake pads of each car, measured in millimeters. Brake pad thickness is essential for ensuring effective braking performance and safety on the road.

Tire Pressure (PSI): This variable represents the pressure of the tires of each car, measured in pounds per square inch (PSI). Proper tire pressure is crucial for optimal fuel efficiency, tire longevity, and vehicle handling.

Maintenance Type: This categorical variable indicates the type of maintenance performed on each car. It includes three categories:

Routine Maintenance: Regular maintenance tasks such as oil changes, fluid checks, and filter replacements.
Component Replacement: Replacement of worn-out or damaged components such as brake pads, tires, or belts.
Repair: Repairs undertaken to fix specific issues or faults identified during inspections or diagnostics.
Anomaly Indication: This binary variable indicates the presence or absence of anomalies detected during maintenance checks or sensor readings. Anomaly indication can flag potential issues or abnormalities in the car's systems, prompting further investigation or corrective action.

The dataset is designed to facilitate analysis and modeling for predictive maintenance purposes. It provides a rich source of information for studying the relationship between maintenance parameters and the overall health and performance of Hyundai cars. Researchers and analysts can use this dataset to develop predictive maintenance models, identify maintenance patterns, optimize maintenance schedules, and improve the reliability and efficiency of Hyundai vehicles.
DOI: 10.17632/tbnhg37jxx.1
title: Informasi Kejadian Bencana Dan Dampak Bencana Gempa Ambon 2019 (Field survey report)

description: These data files consist of Decision Letters published by three local governments of Central Maluku, West Seram, dan Ambon respectively. They provide detailed information about damage to houses that classified into three categories, i.e.: severely damaged houses (“Rusak Berat/RB”), moderately damaged houses (“Rusak Sedang/RS”), and minor damaged houses (“Rusak Ringan/RR”)
DOI: 10.17632/stcppt2r68.1
title: LiPo Battery LP-503562-IS-3 EIS, Capacity, ECM Data

description: BAK Technology LiPo Battery model LP-503562-IS-3

Data acquisition described in M. Galeotti et al., Energy, 2015, doi.org/10.1016/j.energy.2015.05.148 

CAPACITY DATA
Standard Charge:
1) Constant current 1 A until voltage = 4.2 V
2) Constant voltage 4.2 V until current = 0.2 A
Standard discharge: 
1) Constant current 1 A until voltage = 2.75 V

Data:

Folder: ./LiPO_#/EIS_Charge_discharge/
Files: 
0_x_0_stdcharge.csv
0_x_1_stddischarge.csv
0_x_2_stdcharge.csv
(x: cycle number)
Columns: 1) Time [s] 2) Current [A] 3) Voltage [V]

Folder: ./LiPO_#/Discharge_curve/
Files:  
x_Discharge_std.csv
(x: cycle number)
Columns: 1) Extracted Charge [Ah] 2) Voltage [V]

Folder: ./LiPO_#/Capacity/
File:
Capacity_std.csv
Columns: 1) Cycle number 2) Capacity [Ah]

EIS DATA

Folder: ./LiPO_#/EIS_Charge_discharge/
File: 
EIS_cycles.csv
Columns: 1) Cycle number in which EIS is performed
Files:
1_x_y_pardisch.csv
(x: Cycle number in which EIS is performed)
(y: SOC index)
Columns: 1) Time [s] 2) Current [A] 3) Voltage [V]

Folder: ./LiPO_#/EIS_Charge_discharge/EIS_x/
File: 
SOC.csv
(x: Cycle number in which EIS is performed)
Columns: 1) SOC values
Files: 
y_EIS.csv
(y: SOC index)
Columns: 1) Frequency [Hz] 2) Re(Z) [W] 3) Im(Z) [W]

STRESS DISCHARGE DATA

Stress (=standard) charge: 
1) Constant current 1 A until voltage = 4.2 V
2) Constant voltage 4.2 V until current = 0.2 A
Stress discharge: 
1) Constant current 3 A until voltage = 2.75 V

Data: 

Folder: ./LiPO_#/EIS_Charge_discharge/
Files: 	
2_x_stresscharge.csv 
2_x_stressdischarge.csv
(x: Cycle number)
Columns: 1) Time [s] 2) Current [A] 3) Voltage [V]

Folder: ./LiPO_#/Discharge_curve/
Files: 
x_Discharge_stress.csv
(x: Cycle number)
Columns: 1) Extracted Charge [Ah] 2) Voltage [V]

Folder: ./LiPO_#/Capacity/
File: Capacity_stress.csv
Columns: 1) Cycle number 2) Capacity [Ah]

EQUIVALENT CIRCUIT MODEL

Impedance spectra have been fitted by using the impedance model:

Z_\left(s\right) = R_0 + sL + \frac{R_1}{1 + R_1 Q_1 s^{\alpha_1}} + \frac{R_2}{1 + R_2 Q_2 s^{\alpha_2}} + \frac{1}{Q s^{0.5}}

s = i \omega (\omega is the angular frequency)

Data:

Fitted parameters:
Folder: ./LiPO_#_fit/
Files:
model_fit_cycle_x.csv
(x: Cycle number)
Columns: SOC, R_0, R_1, Q_1, a_1, R_2, Q_2, a_2, Q, L

Standard deviation of fitted parameters:
Folder: ./LiPO_#_fit/
Files:
model_fit_err_cycle_x.csv
(x: Cycle number)
Columns: SOC, R_0, R_1, Q_1, a_1, R_2, Q_2, a_2, Q, L
DOI: 10.17632/58n8gf59wg.1
title: Precise calculation of the local pressure tensor in Cartesian and spherical coordinates in LAMMPS

description: Abstract An accurate and efficient algorithm for calculating the 3D pressure field has been developed and implemented in the open-source molecular dynamics package, LAMMPS. Additionally, an algorithm to compute the pressure profile along the radial direction in spherical coordinates has also been implemented. The latter is particularly useful for systems showing a spherical symmetry such as micelles and vesicles. These methods yield precise pressure fields based on the Irving–Kirkwood contour integrat... Title of program: Compute stress spatial Catalogue Id: AEVH_v1_0 Nature of problem A precise calculation of the pressure (stress) field requires the implementation of the contour integration [2] for each pair in the cluster potentials. Versions of this program held in the CPC repository in Mendeley Data AEVH_v1_0; Compute stress spatial; 10.1016/j.cpc.2014.11.017 AEVH_v1_0; Compute stress spatial; 10.1016/j.cpc.2014.11.017 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)
DOI: 10.17632/fptxw8cynv.1
title: Wind Turbine Blade SfM Image Capturing Setups

description: The dataset contains 18 image datasets of a wind turbine blade section in an outdoor environment that are used for SfM reconstruction. The images are separated depending on the image capturing setup. The different setups are as follows: - Distance from camera to blade - 2m, 4m, 6m - Horizontal image overlap - number of images taken in a semi-circle around the wind turbine blade in vertical direction - 9, 17, 33 images - Vertical image angle change - number of bands of images, where the height is changed - each band contains an additional semi-circle of horizontal images - 1 or 2 vertical bands Images are taken with a Canon 6D DSLR camera and each image contains EXIF data about the camera settings used to capture it. From the 18 image datasets, 15 were reconstructed correctly using Agisoft Metashape and the resultant 3D meshes are added in .obj format. In addition, a horizontal 2D slice is taken from each 3D reconstruction for testing the captured blade's overall shape.
DOI: 10.17632/spkmxfsmhv.1
title: Skin Temperature Football Players during a season

description: A descriptive and longitudinal study in a professional football team from the Russian Premier league that employs a rigorous evaluation methodology collects and analyses player temperatures using validated software between 36 to 24 hours before the match and between 24 and 36 hours after the match. Additionally, locomotor values provided by a GPS positioning system are recorded through individual devices.
DOI: 10.17632/ydnrzzndhy.1
title: Diagnóstico y Valoración Financiera de una Empresa Comercializadora de Productos de Belleza

description: La valoración financiera dentro de las organizaciones es crucial por varias razones. En primer lugar, proporciona una evaluación objetiva del desempeño y la salud financiera de la empresa, lo que permite a los líderes empresariales tomar decisiones fundamentadas sobre inversiones, financiamiento y estrategias de crecimiento. Además, la valoración financiera ayuda a identificar áreas de mejora y oportunidades de optimización de recursos. También es fundamental para evaluar el valor de la empresa en caso de fusiones, adquisiciones o ventas. En resumen, la valoración financiera es una herramienta fundamental para la toma de decisiones estratégicas y la maximización del valor para los accionistas y todas las partes interesadas de la organización.

Palabras Clave: estados financieros, valor agregado, riesgo, rentabilidad, liquidez, flujos de efectivo, comparables.

Financial valuation within organizations is crucial for several reasons. Firstly, it provides an objective assessment of the company’s performance and financial health, allowing business leaders to make informed decisions about investments, financing, and growth strategies. Additionally, financial valuation helps identify areas for improvement and opportunities for resource optimization. It is also essential for evaluating the company’s value in the event of mergers, acquisitions, or sales. In summary, financial valuation is a fundamental tool for strategic decision-making and maximizing value for shareholders and all stakeholders of the organization.

Keywords: financial statements, added value, risk, profitability, liquidity, cash flows, comparables.
DOI: 10.15468/dl.k2uaey
title: Occurrence Download

description: A dataset containing 3743 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Populus deltoides W.Bartram ex Marshall",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 3743 records from 218 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009287-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/bdc7cg7b5s.1
title: Data and code for: Global patterns of nitrogen saturation in forests

description: Since the industrial revolution, accelerated atmospheric nitrogen (N) deposition by human activities have increased N availability in forest ecosystems close to human settlements, potentially causing nitrogen-limited forests to become nitrogen-saturated. In N-saturated forests, oversupply of N leads to higher N losses as compared to N-limited forests, suggesting that the sensitivity of soil N2O emission to N deposition (sN) might indicate N saturation. In this study, we modeled the sN of global forests using N addition experimental data. Testing with previous field observations of N-saturated forests, the global patterns of N-limited and N-saturated forests indicated by sN show an accuracy above 80% on global and geographic-regional scales. Our results suggest that 47.5% of global forests are N-saturated. The produced global map of N-saturated forests reveals the spatially varying N status of forests, which is useful for predicting forest greenhouse gas emissions and productivity, facilitating optimized environmental management practices for different regions.
DOI: 10.17632/f3v73r2wn9.1
title: Data for: Multivariate Probability Distribution of Shanghai Clay Properties

description: A database for 11 clay parameters covering 50 sites in Shanghai with 4051 data points is compiled. These sites are distributed in 8 Districts of Shanghai covering approximately 145 km2 in area. This is the first sizeable multivariate soil database compiled at the municipal level. The data points are collected from site investigation reports of Shanghai. Soil properties which are measured in close proximity are selected to constitute a set of data points. This database is useful for studies of the soil properties about Shanghai clay. It also enriches the information of soil properties from a global perspective and will contribute to the development of machine learning algorithm for geotechnical problems.
DOI: 10.17632/tgv3zb82nd.1
title: JMuBEN2

description: Datasets were taken from Arabica coffee plantation using a camera and with the help of a plant pathologist. The images were then cropped to focus on the region of interest . Image augmentation was done with the aim of increasing the dataset size and preventing over-fitting problems during model training and validation. The images are in different folders containing annotated images of healthy and Miner
DOI: 10.17632/jt9hbs4fkr.1
title: Data for: Responses of litter decomposition and nutrient release to N addition: a meta-analysis of terrestrial ecosystems

description: Meta data for this meta-analysis from 55 papers
DOI: 10.17632/fpskhsp6bw.1
title: Dataset of Pattern of Deaths Among Women of Reproductive Age in Major Autopsy Centers of Capital Cities of the Seven Provinces of Nepal

description: The females in the reproductive are vulnerable to traditional pregnancy-related complications along with injuries and diseases. The number of unnatural deaths in a locality reflects the social and mental wellbeing of a society and in addition, it also represents the prevalence of fatal violence and injuries of various kinds. Particularly, in relation to the unnatural deaths of females, this can reflect the violence of different kinds in society and their deprivation of socio-economic and human rights. 
This is the dataset of the study to explore the causes of unnatural deaths among the females of reproductive age groups in Nepal. There was a significant variation in the manner of deaths among the females of hill caste and terai, with the frequency of intentional deaths higher among the hill caste. Likewise, the females of the younger age group and unmarried females had died of intentional deaths more often. The females had mostly died of suicide, with hanging being the commonest cause and homicide was not common.
DOI: 10.17632/m7r4msjb4c.2
title: A compendium of mutational signatures of environmental agents Kucab et al.

description: Whole-genome-sequencing (WGS) of human tumours has revealed distinct mutation patterns that hint at the causative origins of cancer. We examined mutational signatures in 324 WGS human induced pluripotent stem cells exposed to 79 known or suspected environmental carcinogens. 41 yielded characteristic substitution mutational signatures. Some were similar to signatures found in human tumours. Additionally, 6 agents produced double-substitution signatures and 8 produced indel signatures. Investigating mutation asymmetries across genome topography revealed fully functional mismatch and transcription-coupled repair pathways. DNA damage induced by environmental mutagens can be resolved by disparate repair/replicative pathways, resulting in an assortment of signature outcomes even for a single agent. This compendium of experimentally-induced mutational signatures permits further exploration of roles of environmental agents in cancer aetiology, and underscores how human stem cell DNA is directly vulnerable to environmental agents.
DOI: 10.17632/hxt48yk462.1
title: Panoramic Dental X-rays With Segmented Mandibles

description: This dataset consists of anonymized and deidentified panoramic dental X-rays of 116 patients, taken at Noor Medical Imaging Center, Qom, Iran. The subjects cover a wide range of dental conditions from healthy, to partial and complete edentulous cases. The mandibles of all cases are manually segmented by two dentists. This dataset is used as the basis for the article by Abdi et al [1]. [1] A. H. Abdi, S. Kasaei, and M. Mehdizadeh, “Automatic segmentation of mandible in panoramic x-ray,” J. Med. Imaging, vol. 2, no. 4, p. 44003, 2015.