cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/2r232jpfb2.1
title: Dataset of Indoor Air Pollutants using Low-Cost Sensors

description: Indoor air pollutant concentration data is collected for all the seasons in Pune city, India, from internet of things-based system built using low-cost sensors. The raw data contains 1,73,468 records collected from Nov 2020 to July 2022. Air pollutant PM2.5 (Particulate Matter) is measured using GP2Y1010AU0F Dust Smoke Particle Sensor, NO2 (Nitrogen Dioxide), NH3 (Ammonia) and CO (Carbon Monoxide) pollutant measured using MICS-6814 sensor. Ozone (O3) measured using MQ131 Semiconductor Sensor. Temperature, Humidity measured using BME 280 sensor. Measurement units of NH3 is PPM, NO2 in PPM, CO in PPM, PM2.5 in ug/m3, Temperature in Celsius, Pressure in hPa, Humidity in RH, Ozone in PPB. This data can be used for study and evaluations of prediction models, low-cost sensor data and calibration. It can be used for the study of the pollutant’s patterns in COVID-19 pandemic.  It will help policymakers to develop policies to monitor air pollution impact.
DOI: 10.17632/wvg9jg8j8w.1
title: Dataset of Numerical Study of the Impact of Two-Step Injection (Direct and Port) of Hydrogen-Enriched and Natural Gas Mixtures on Engine Efficiency and Exhaust Emissions

description: This data survey numerical Study of the Impact of Two-Step Injection (Direct and Port) of Hydrogen-Enriched and Natural Gas Mixtures on Engine Efficiency and Exhaust Emissions in international combustion engines
DOI: 10.17632/zcvgc6m58h.1
title: World Development indicators

description: This data file is about world development indicators from world bank database.
DOI: 10.15468/dl.bxjqys
title: Occurrence Download

description: A dataset containing 667 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Otatea (McClure & E.W.Sm.) C.E.Calderón ex Soderstr."
 ]
}

 The dataset includes 667 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009377-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/nrywwbx6fm.2
title: The genetic evolution of melanoma: 48 case studies
DOI: 10.17632/dzw8x5vyrv.1
title: PyLlama: A stable and versatile Python toolkit for the electromagnetic modelling of multilayered anisotropic media

description: PyLlama is a handy Python toolkit to compute the electromagnetic reflection and transmission properties of arbitrary multilayered linear media, including the case of anisotropy. Relying on a 4x4-matrix formalism, PyLlama implements not only the transfer matrix method, that is the most popular choice in existing codes, but also the scattering matrix method, which is numerically stable in all situations (e.g., thick, highly birefringent cholesteric structures at grazing incident angles). PyLlama is also designed to suit the practical needs by allowing the user to create, edit and assemble layers or multilayered domains with great ease. In this article, we present the electromagnetic theory underlying the transfer matrix and scattering matrix methods and outline the architecture and main features of PyLlama. Finally, we validate the code by comparison with available analytical solutions and demonstrate its versatility and numerical stability by modelling cholesteric media of varying complexity. A detailed documentation and tutorial are provided in a separate user manual. Applications of PyLlama range from the design of optical components to the modelling of polaritonic effects in polar crystals, to the study of structurally coloured materials in the living world.
DOI: 10.17632/s3wjhzzdr3.2
title: Dataset for: Predictive analysis of gas holdup in bubble column using machine learning methods

description: Dataset for: Predictive analysis of gas holdup in bubble column using machine learning methods
The dataset used for the prediction of gas holdup in bubble column using machine learning methods: Artificial Neural Network, Extra Trees, Random Forest, and Support Vector Regression. Data is extracted from literature with the help of the Engauge Digitizer extraction tool. Data contains gas holdup as the target/dependent variable and 14 independent variables which are used for the prediction of the gas holdup. A detailed description of the methods used with optimized hyperparameters is published in Chemical Engineering Research and Design. DOI: https://doi.org/10.1016/j.cherd.2022.06.007
DOI: 10.17632/2svx788ddf.1
title: KimLabDevCCFv001

description: This package is the version 001 release of the Kim Lab Developmental CCF (KimLabDevCCFv001).
KimLabDevCCF is a 3D whole mouse brain multimodal common coordinate framework. v001 includes multimodal templates (STPT, LSFM, and MRI) 
for the adult mouse brain (P56) as well as continuous 3D annotations segmented according to Luis Puelles' Developmental Vertebrate Ontology.

The package contains the following files representative of the P56 mouse brain at 10um, 25um, and 50um isotropic resolution:

	- The CCFv3 Template:
		CCFv3_average_template_ASL_Oriented_u16_10um.nii.gz
		
	- Developmental Atlas segmentations based on the Developing Mouse Brain Atlas:	
		KimLabDevCCFv001_Annotations_ASL_Oriented_10um.nii.gz
		
	- LSFM average template registered to the Allen CCFv3 Space:	
		KimLabDevCCFv001_iDiscoLSFM2CCF_avgTemplate_ASL_Oriented_10um.nii.gz
	
	- The Allen Developing Mouse Brain Atlas Ontology Structure modified to include labels present in the KimLabDevCCFv001 that are not present in the Allen ontology:
		KimLabDevCCFv001_MouseOntologyStructure.csv	
		(additional labels 

	- MRI average templates of 6 contrasts (a0, adc, dwo, fa, MTR, T2) registered to the Allen CCFv3 Space:
		KimLabDevCCFv001_P56_MRI-a02CCF_avgTemplate_ASL_Oriented_10um.nii.gz
		KimLabDevCCFv001_P56_MRI-adc2CCF_avgTemplate_ASL_Oriented_10um.nii.gz
		KimLabDevCCFv001_P56_MRI-dwi2CCF_avgTemplate_ASL_Oriented_10um.nii.gz
		KimLabDevCCFv001_P56_MRI-fa2CCF_avgTemplate_ASL_Oriented_10um.nii.gz
		KimLabDevCCFv001_P56_MRI-MTR2CCF_avgTemplate_ASL_Oriented_10um.nii.gz
		KimLabDevCCFv001_P56_MRI-T22CCF_avgTemplate_ASL_Oriented_10um.nii.gz


	*Note: All data in this release version are registered to the Allen Institute CCFv3 morphological space.
DOI: 10.17632/hsgymx6zf8.2
title: Work, Stress, and Life Satisfaction

description: These data are from a cross-sectional study examining whether people in larger companies are more stressed and experience different levels of life satisfaction than people working in smaller companies. The study also examines differences in stress and life satisfaction between those who work as employees and those who work as managers. Finally, the study looks at whether people in larger companies do more or less regular exercise and whether the latter is related to childhood exercise habits.
DOI: 10.17632/y3g8bx3vb4.1
title: Pricing of Sustainability-Linked Bonds

description: This package provides code and describes how to replicate the results of the paper "Pricing of Sustainability-Linked Bonds".
DOI: 10.17632/gkjfkrzrs7.1
title: Australian HCP Acceptance of SIV March 23

description: The aim of this qualitative research was to understand the attitudes and behaviours, enablers and barriers of Seasonal Influenza Vaccination among Australian healthcare personnel (HCP-nurses, midwives, doctors and pharmacists) in the context of Covid 19. Utilising a question guide underpinned by the Triandis Theory of Interpersonal Behaviour, and an Intergrative Review, we conducted 14 semi-structured interviews with Australian HCP. Application of Braun and Clarke’s reflective thematic analysis facilitated the identification and exploration of 6 pertinent themes. Most significantly professional responsibility and identity appeared highly associated with positive vaccine intention. Protection particularly of others, habit, risk perception, experience and knowledge, and convenience and ease of access were also found to influence HCP decision making around SIV. Vaccination complacency, not hesitancy, was found to impede the progress of vaccination intention (acceptance) to vaccine behaviours (uptake).  Interventions targeting professional identity and social norms may overcome vaccine complacency to nudge vaccination intention to vaccination positive behaviour.
DOI: 10.17632/2hrdtby549.1
title: Replication Folder

description: Replication folder of the paper "Securitisation, shadow banking system, and macroprudential regulation: A DSGE Approach". F. Lubello and A. Rouabah (2023).
DOI: 10.17632/ndrczc35bt.1
title: HANDS: a dataset of static Hand-Gestures for Human-Robot Interaction

description: The HANDS dataset has been created for human-robot interaction research, and it is composed of spatially and temporally aligned RGB and Depth frames. It contains 12 static single-hand gestures performed with both the right-hand and the left-hand, and 3 static two-hands gestures for a total of 29 unique classes. Five subjects (2 females and 3 males) performed the gestures, each of them with a different background and light conditions. For each subject, 150 RGB frames and their corresponding 150 depth frames per gesture have been collected, for a total of 2400 RGB frames and 2400 depth frames per subject. Data has been collected using a Kinect v2 camera intrinsically calibrated to spatially align RGB data to depth data. The temporal alignment has been performed offline using MATLAB, aligning frames with a maximum temporal distance of 66 ms. We provide our MATLAB scripts to process similar rosbags and align the streams, elaborate a MATLAB Labeling Session, and create the same Annotation files we provide. For users who want to use the annotated data for research, we also provide a Python script showing how to convert the Annotation files into a TensorFlow record. The data is valuable for the field of Computer Vision, especially for the tasks of hand-gesture recognition, human-machine interaction, and hand-pose recognition. The dataset can be used to train Deep Learning models to recognize the gestures in the dataset using only a single modality (RGB or depth) or both at the same time. It is also useful as a reference dataset for benchmarking models. If you use this dataset for your work, please cite the related papers: - https://doi.org/10.1016/j.dib.2021.106791 - https://doi.org/10.1016/j.rcim.2020.102085
DOI: 10.15468/dl.75ga93
title: Occurrence Download

description: A dataset containing 2327 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Punica granatum L.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 2327 records from 318 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009378-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/37t2d6xmy2.1
title: Histopathological image patches from colorectal cancer with three classes: tumor, stroma and other

description: This dataset includes 2770 image patches (224 x 224 px^2, 0.5 MPP) from hematoxylin and eosin-stained tissue samples of colorectal cancer from 17 patients from the Central Finland Healthcare District. Image patches can be utilized e.g. as an external test set for deep learning model. Dataset has three classes: tumor, stroma and other. Patches were tiled from annotated areas, annotations were made by pathologist Juha P. Väyrynen. The class other includes debris, lymphocytes, mucus, normal epithelium and smooth muscle.

Tiling was performed with a sliding window procedure with 64 pixels overlapping. If less than 75\% of the patch area included annotated pixels, the patch was discarded. All patches were color normalized by Macenko's method (see "A method for normalizing histology slides for quantitative analysis" by Macenko et al., 2009).
DOI: 10.17632/jc39rkk4g8.1
title: Skin Cancer Screening Supplemental Material

description: A Cross-Sectional Study on Skin Cancer Screening Behaviors in Sexual Minorities Among Adults in the United States - Supplemental Materials
DOI: 10.17632/y63frd6pmf.7
title: Multimodal Hinglish Tweet Dataset for Deep Pragmatic Analysis

description: This dataset was meticulously curated to encapsulate tweets that vividly express raw emotions, sentiments, feelings, and textual gestures related to various situations of conflict. This includes, but is not limited to, wars, crises, civil unrest, and world wars I, II, III, etc. The fundamental objective of creating this dataset is to enable the development of digital applications capable of discerning the genuine emotional pulse of digitally empowered citizens. In essence, these tools aim to empower both the general public and government authorities with real-time insights into public sentiment, enhancing their understanding and responsiveness to critical situations.
DOI: 10.17632/ch3sydbbrg.3
title: [OLD] Data For: Dataset on broadband Electrochemical Impedance Spectroscopy of Lithium-Ion Batteries for Different Values of the State of Charge

description:  === NEW DATASET NOTICE =====
We published a new dataset obtained with an improved data acquisition protocol and new measurements. 
We suggest considering the new dataset. 

===============================

Electrochemical impedance spectroscopy (EIS) on rechargeable lithium-Ion batteries. 
The EIS were measured on ten brand new Samsung cylindrical  ICR18650-26J  lithium-Ion batteries at SoC 100%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, and 10%. For three of the batteries, the measurements were repeated twice. (13 CSV files ,130 EIS in total).

File               :  Data Source
-------------------------------------------           
EIS_BATT_1: Battery 1 Measurement 1
EIS_BATT_2: Battery 1 Measurement 2
EIS_BATT_3: Battery 2 Measurement 1
EIS_BATT_4: Battery 2 Measurement 2
EIS_BATT_5: Battery 3 Measurement 1
EIS_BATT_6: Battery 4 Measurement 1
EIS_BATT_7: Battery 5 Measurement 1
EIS_BATT_8: Battery 5 Measurement 1
EIS_BATT_9: Battery 6 Measurement 1
EIS_BATT_10: Battery 7 Measurement 1
EIS_BATT_11: Battery 8 Measurement 1
EIS_BATT_12: Battery 9 Measurement 1
EIS_BATT_13: Battery 10 Measurement 1

Each CSV file contains ten columns. Each column in the CSV file contains data of an EIS spectrum measured at one specific SoC. The first column is for SoC 100%. The last column is for SoC 10%. SoC Columns headers row (non included in the file) is:  ['100','090','080','070','060','050','040','030','020','010']

All EIS spectrum was computed measuring impedance at frequencies  [ 0.05, 0.1, 0.2, 0.4, 1, 2, 4, 10, 20, 40, 100, 200, 400, 1000] Hz.  
Impedance values are in the format:  Re{Z}+Im{Z}i
One impedance value for each row:  

Row #1: 0.05 Hz
Row #2: 0.1 Hz
Row #3: 0.2 Hz
 ... 
Row 14: 1000 Hz.
DOI: 10.17632/gv5wpbryn2.5
title: Data and code for the article "Per capita reproductive success decreases with group size in a communally breeding bird"

description: Data and code necessary to replicate the analyses done for the article "Per capita reproductive success decreases with group size in a communally breeding bird". Including supplemental material.
DOI: 10.17632/y6d3z6f8z9.1
title: Cucumber Disease Recognition Dataset

description: (1) Crop disease is a widespread problem in the productivity and quality of agricultural production. It adversely affects the quality of crops. The cucumber is a frequently grown creeping vine plant that has few calories but is high in water and several vital vitamins and minerals. Due to the non-biological circumstances, cucumber diseases will adversely harm the yield and quality of cucumber and cause heavy economic losses to farmers. The traditional diagnosis of crop diseases is often time-consuming, laborious, ineffective, and subjective. 

(2) In the recent era, computer vision approaches are very promising for handling these kinds of classification and detection tasks.

(3) To develop machine vision-based algorithms, a major cucumber dataset is illustrated containing eight types of cucumber classes, namely Anthracnose, Bacterial Wilt, Belly Rot, Downy Mildew, Pythium Fruit Rot, Gummy Stem Blight, Fresh leaves, and Fresh cucumber. Cucumber disease classifications are done with the cooperation of an expert from an agricultural institute.

(4) A total of 1280 images of cucumbers are collected from real fields. Then from these original images, a total of 6400 augmented images are produced using flipping, shearing, zooming, and rotation techniques to increase the data number.
DOI: 10.17632/8pk4wmv9jj.2
title: Data User QRIS Adoption in West Java, Indonesia

description: The data represent the business owners in West Java, Indonesia regarding to QRIS Adoption
DOI: 10.17632/br2psms8b9.1
title: Climate-driven changes of global marine mercury cycles in 2100

description: This data deposit includes the data accompanying the paper with the same title published in PNAS. Provided here contains the data for seawater inorganic mercury and monomethylmercury in seawater, phytoplankton, and zooplankton. We include the data for present-day condition and future scenarios. The data is in NetCDF format, and the codes to process these data are also provided.
DOI: 10.17632/gtn4dswnfw.1
title: Data for: Potassium infusion increases the likelihood of conversion of recent-onset atrial fibrillation - a single-blinded, randomized clinical trial

description: Excel file and Readme file for the data.
DOI: 10.17632/468j46mzdv.1
title: N-MNIST

description: Recording of the MNIST dataset displayed on a screen as viewed by a dynamic vision sensor moving through a fixed trajectory on a pan-tilt unit. Details are in the listed paper.
DOI: 10.17632/69p62ksdh6.6
title: A human consciousness questionnaire dataset

description: This dataset contains key information concerning important aspects of human consciousness from 800 adolescents. The consciousness composes of four subscales with 46 indicators, namely (1) the senses (i.e. hearing, touching, tasting, and smelling) with 14 indicators, (2) the reasoning abilities of the mind (i.e. reasoning ability in learning and in problem-solving) with 13 indicators, (3) Imagination and emotion with 11 indicators, and (4) memory with 8 indicators. Furthermore, the current dataset also provides sample characteristics, that is, gender, age, and faculty.
DOI: 10.17632/92jk3fchm2.4
title: This Person Does Not Exist CLIP classification

description: 10000 fake portrait photographs generated with thispersondoesnotexist.com and their probabilistic classification, using CLIP (Contrastive Language–Image Pretraining) according to the following labels: White person/Person of Color, Male/Female, Attractive/Unattractive, Intelligent/Unintelligent, Rich/Poor, Friendly/Unfriendly.
DOI: 10.17632/fr9t5fkkvz.2
title: Olive oil geography by GC-IMS analysis

description: 53 olive oils from Spain (20), Italy (20) and Greece (13) of extra virgin quality, harvested during the 2014/2015 season, were kindly supplied by Coop Switzerland (Basel, Switzerland). Authenticity was verified by the supplier by chemical and isotope analysis.
Olive oil samples were analysed by headspace GC-IMS. The setup includes an Agilent 6890N gas chromatograph (Agilent Technologies, Palo Alto, USA), coupled with a standalone ion mobility spectrometer (Gesellschaft für Analytische Sensorsysteme mbH, Dortmund, Germany). Measurements were carried out in triplicates.
Binary files (*.mea format G.A.S. Sensorsysteme m.b.H., Dortmund, Germany)
DOI: 10.17632/5kbjrgsncf.3
title: Medical Imagining (CT scan, MRI, X-ray, and Microscopic Imagery) Data

description: The respective data is comprised of 5 different datasets of medical images collected by the contributors, which can be used for classifying Lung Cancer, Bone Fracture, Brain tumor, Skin Lesions, and Renal Malignancy, respectively. The data also includes multiple disease and malignancy images for the respective dataset. 
The classification for the diseases can be done by using ResNet50 CNN architecture and other DCNN models. This data is also been used in a research article by the contributor.
DOI: 10.17632/smgx6s5pwr.1
title: Iraqi Student Performance Prediction

description: Iraqi dataset is collected through applying (or submitting) questionnaire in three Iraqi secondary schools for both applicable and biology branches of the final stage during the second semester of the 2018 year. Initially, the questionnaire contains 56 questions in three A4 sheets and it is answered by 250 students (samples). Latter, 130 samples are discarded due to lack of information since pre-processing is applied to obtain the most complete information of students. After removing inconsistencies and incompleteness in the dataset, this study considers 120 samples instances with 55 features for experiment purposes. The features are distributed into five main categories: Demographic, Economic, Educational, Time, and Marks. Table (1) shows the dataset’s attributes/features and their description. As illustrated in this table, new features are introduced, such as holiday and worrying effects. The relationships between parents with schools and use of books and references by the student are also considered.
DOI: 10.17632/vx4vg47hzg.1
title: BESLE: Boundary element software for 3D linear elasticity

description: BESLE is the first available parallel open-source code to analyse the mechanical behaviour of heterogeneous materials using the boundary element method (BEM) in 3D and in both an elastostatic and elastodynamic setting. Unlike all the other codes that are presently available, the software presented here is capable of simulating both isotropic and anisotropic materials comprised of single or multiple domains. Furthermore, the user-interface has been designed to provide a convenient way for configuring simulations involving many complex material constituents. Results are described by the displacement and traction fields, also, the stress and strain tensors are available for post-processing. BESLE is largely implemented in Fortran-MPI, but some of the sub-packages are based on other languages such as C and C++, and as such a the software is best used on a multi-core architecture where the parallelisation can be fully exploited. The main features and functionality of BESLE are presented here, and the User's Guide, available from the repository listed below, gives further details and outlines how users can carry out bespoke simulations.