cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/85t28npyv7
title: Data for: Predictive Modeling of Forest Fires: A New Dataset and Machine Learning Approach

description: This Dataset was created based on Remote Sensing data to predict the occurrence of wildfires, it contains Data related to the state of crops (NDVI: Normalized Difference Vegetation Index), meteorological conditions (LST: Land Surface Temperature) as well as the fire indicator “Thermal Anomalies”. All three parameters were collected from MODIS (Moderate Resolution Imaging Spectroradiometer), an instrument carried on board the Terra platform. The collected data went through several preprocessing techniques before building the final Dataset. The experimental Dataset is considered as a case study to illustrate what can be done at larger scales. The Data contains parameters with high influence of wildfires occurrence collected using remote sensing. The Dataset is composed of four columns, the first three columns are NDVI, LST, and Thermal Anomalies and the fourth column represents the corresponding class (fire or no_fire), the Dataset contains 804 rows: 386 instances of the class “fire” and 418 instances of the class “no fire” with 418 rows. Each row contains the collected data and its class. The data were downloaded from the official website of NASA's Land Processes Distributed Active Archive Center (LP DAAC), and then we preprocessed them using multiple preprocessing techniques to remove noises and correct inconsistencies, and finally extracting useful information. The study area is composed of multiple zones located in the center of Canada. The surface of this area is approximately 2 million hectares. These zones differ in their size, burn period, date of burn and extent. We have chosen to apply the experiment in a big region of Canada's forests because it is known for its high rate of wildfires and also for the availability of fire information (start and end fire date, cause of fire and the surface of the burned area in hectares), these information were acquired from The Canadian Wild-land Fire Information System (CWFIS) which creates daily fire weather and fire behavior maps year-round and hot spot maps throughout the forest fire season
DOI: 10.17632/8pk4wmv9jj
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: 10.17632/9gy6k69hph
title: Pastoral land use and livestock

description: Datasets include pastoral mobility, land use, livestock, household data from Turgen soum of Uvs and Delgertsogt soum of Dundgovi aimag in Mongolia. Data were gathered over the course of the period between July and September, 2019 in Mongolia using a survey questionnaire containing questions related to the movement pattern of animals. The design of the questionnaire was based on the indicators of pastoral land use and mobilities such as grazing orbit, lenght of daily herding movement, and number of camps. From each soum, 100 households, in total 200 responses were collected.
DOI: 10.17632/j2t5ph46nk
title: NIHSS - Paramedics dataset

description: Dataset used in the NIHSS - Paramedics study (“Teaching NIHSS to paramedics, e-learning vs video: a randomized controlled trial”)
DOI: 10.17632/h8sr7pz87p
title: Willingness to pay for green buildings among urban residents in emerging first-tier cities in China: A multigroup analysis

description: With the persistent growing trend of building energy consumption in China, the nation has made the decision that has more conducive to carbon emissions reduction and its sustainable developing by launching the measures of developing green buildings. Nevertheless, little is known about the determinants of consumer willingness to pay for green building in the New Tier 1 (NT1) cities of China, as current literature lacks studies targeting this market. The paper attempts to bridge this gap by investigating how the psychological factors that underpin consumers’ willingness to pay for green buildings can be understood in three NT1 cities—Chengdu, Wuhan, and Xi'an—via the extended Theory of Planned Behavior (TPB) model. Recognizing these psychological drivers of change is critical to facilitating green building adoption and meeting China’s sustainability commitments. Partial Least Squares—Structural Equation Modeling (PLS-SEM) and Multi-Group Analysis (MGA) were applied for model testing. The findings show that for the three cities, the determinants affecting consumers' preferences regarding their willingness to pay for green buildings differ greatly. In Wuhan, consumers are more strongly influenced by their attitudes, while environmental awareness has a weaker impact. Chengdu consumers are more affected by social norms, with moral norms playing a lesser role. Meanwhile, in Xi'an, environmental concern has a weaker impact on attitudes compared to Chengdu and Wuhan. Consequently, to effectively promote green buildings, governments, property developers, and stakeholders should develop tailored approaches specific to each city's unique characteristics.
DOI: 10.15468/dl.hw3uzy
title: Occurrence Download

description: A dataset containing 266 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Nassella leucotricha (Trin. & Rupr.) R.W.Pohl",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 266 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012902-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/67s685m8m8
title: ATRU-1 fault diagnosis

description: Fifteen health conditions were collected from avionics 24-pulse ATRU-2. The health conditions of avionics ATRUs include healthy, faulty with main rectifier bridges, faulty with assist rectifier bridges, faulty with the wind, and faulty with the input voltage.The data contain output voltage signal and the input current signal collected from ATRUs under different health conditions.
DOI: 10.17632/f8zr2kzrcx
title: Hyperspectral data of albino rice seedlings.

description: This dataset is an additional data to the following article: Temporal Changes of Leaf Spectral Properties and Rapid Chlorophyll—A Fluorescence under Natural Cold Stress in Rice Seedlings, Plants, 2023, DOI: 10.3390/plants12132415 . The dataset contains absorbance, reflectance and transmittance data of albino seedlings, measured by handheld leaf spectrometer (CI-710s SpectraVue Leaf Spectrometer; Cid-Bioscience, Camas, WA, U.S.A.). The albino plants were established in the temperate rice growing area in spring under the influence of natural cold temperatures. These data can be used as a reference to estimate the rate of chlorophyll degradation.
DOI: 10.17632/g82zmwvh8n
title: Predictive Analytics for Mitigating Supply Chain Disruptions

description: These are the initial dataset used to predict disruptions in the supply chain. There is yet a lot of other factors that need to be considered but as a MVP of such an ML model i have taken these and normalized and cleaned them
DOI: 10.6084/m9.figshare.25705947.v1
title: Figure 3b Distribution of the coverage of enriched pathways between the CML module and drug modules.

description: This dataset contains percentage of randomly selected drug modules overlapping with functional pathways that were enriched in the CML. This consists of 12 list type object. In the each list, 1001 of numeric vector are contained. Each list means ranking. Each vector shows the percentage of overlapping. Run "Scripto_for_Figure3b.R" for making figure 3b in the manuscript.1st list: the overlap rates for the groups with the highest overlap rates from 1 to 1001<br>2nd list: the overlap rates for the groups with the highest overlap rates from 100000 to 1010013rd list: the overlap rates for the groups with the highest overlap rates from 200000 to 201001<br>4th list: the overlap rates for the groups with the highest overlap rates from 300000 to 301001<br>5th list: the overlap rates for the groups with the highest overlap rates from 400000 to 401001<br>6rd list: the overlap rates for the groups with the highest overlap rates from 500000 to 501001<br>7th list: the overlap rates for the groups with the highest overlap rates from 600000 to 601001<br>8th list: the overlap rates for the groups with the highest overlap rates from 700000 to 701001<br>9rd list: the overlap rates for the groups with the highest overlap rates from 800000 to 801001<br>10th list: the overlap rates for the groups with the highest overlap rates from 900000 to 901001<br>11th list: the overlap rates for the groups with the highest overlap rates from 100000 to 100100112th list: the overlap rates for the groups with the highest overlap rates from 100000 to 1101001<br><br>
DOI: 10.6084/m9.figshare.28876178.v1
title: THE IMPACT TECHNOLOGICAL INNOVATION IN MODERN FAST.pdf

description: Technological innovation has significantly transformed the fast-food industry, introducing self-service kiosks as a solution to enhance customer experience and streamline operations. The increasing adoption of digital solutions in fast food reflects broader societal shifts towards automation and self-service. Modern consumers have become accustomed to seamless, technology-enabled experiences in various sectors, from retail to banking. These kiosks offer customers the convenience of customizing their orders, reducing wait times, and minimizing human error in transactions, thereby improving overall satisfaction (Baskerville et al., 2020). For fast food chains, the adoption of self-service kiosks has the potential to increase operational efficiency by optimizing staff allocation and expediting service delivery (McKinsey & Company, 2021). In the fast-food context, self-service kiosks are part of a larger digital ecosystem that includes mobile ordering apps, contactless payments, and integrated loyalty programs. These systems cater to a growing demand for convenience, personalization, and speed in service.
DOI: 10.17632/585d2wdmtd
title: The longitudinal health behaviours of European study abroad students sampled from forty-two countries and across three-waves

description: Research on travelling populations, indicates that geographic mobility is associated with changes in health behaviours. However, there is currently little longitudinal data recording study abroad students' health behaviours other than alcohol use, and that includes a variety of risk and protective factors related to students' demographics and their experiences abroad. The present dataset contains the original longitudinal data from a study of European study abroad students' and includes information on participants health-related behaviour: including physical exercise, diet, alcohol and drug use, and unprotected casual sex. Self-reported data were collected across three waves: on arrival in the host country, to assess pre-departure behaviour (T1), four months through the period abroad (T2), and four months after returning home (T3). Data on factors related to participants' demographics and their abroad experience, including motivations to study abroad, acculturation orientation and adjustment to the host environment, and perceptions regarding different referent peers’ drinking behaviour were also collected. Data were collected in the 2015-2016 academic year. At T1 students in 200 cities from more than 40 European countries were approached by representatives from an international student association. Participants who completed at least two surveys were included (N = 908). The T1 survey was completed by 899 students (nine students provided an e-mail address but did not complete the survey at T1), 785 (86.5%) completed T2 survey, and 438 (48.2%) the T3 survey. The data article presents tables charting variables measured by survey wave and participants' socio-demographic and study abroad experience characteristics. With an acceptable drop-out across the three waves, these data may be of interest to researchers who wish to understand factors related to changes in health behaviours in this population and develop targeted health promotion interventions. Other stakeholders such as policy makers, international offices, health professionals in counselling service, student associations may also use these data to develop communication campaigns and intervene with reference to relevant risk and protective factors.
DOI: 10.17632/dz62s4p7mj
title: Covidtestasymptomaticpregnant

description: test results in asymptomatic pregnant women
DOI: 10.17632/fhx5zgx2zj
title: Data for: Gene Selection and Classification of Microarray Data Method Based on Mutual Information and Moth Flame Algorithm.

description: Microarray Dataset gene selection
DOI: 10.17632/m4bzmhy2kb
title: Enhanced photocatalytic dye degradation and hydrogen evolution performance of Cu encapsulated BiVO4 under visible light irradiation

description:  XRD data Enhanced photocatalytic dye degradation and hydrogen evolution performance of Cu encapsulated BiVO4 under visible light irradiation
DOI: 10.17632/n2mcbbhx37
title: Marketing Development: A Study of Food and Beverages Business Promotion Using Key Opinion Leader (KOL) Method

description: This study analyzes the impact of KOL collaborations on the promotion of F&B businesses, identifying the key factors that contribute to their success. Using a qualitative descriptive methodology, the research highlights that credible and relatable KOLs can significantly enhance brand awareness, consumer engagement, and purchase intentions. Furthermore, the study discusses how strategic KOL selection, content creativity, platform choice, and audience alignment are crucial for achieving higher marketing effectiveness and Return on Investment (ROI).
DOI: 10.6084/m9.figshare.6864542.v1
title: Additional file 1 of phylotree.js - a JavaScript library for application development and interactive data visualization in phylogenetics

description: Latest release of source code. A zip file of the source code from release 0.1.8. Accessed 4 May 2018. (ZIP 3513 kb)
DOI: 10.17632/9xd46s6hjv
title: Dataset to Identify Behavioral Disorder

description: The purpose of the present data set is to detect positive or negative thoughts to identify behavioral disorders of individuals via a combination of Natural Language Processing (NLP) mechanisms. Negative thinking refers to a pattern of thinking negatively about yourself and your surroundings. While everyone experiences negative thoughts now and again, negative thinking seriously affects the way you feel about yourself and the world; it even interferes with work/study and everyday functioning. That could be a symptom of a mental illness, such as depression, anxiety, disorders, personality disorders, anger, sadness, frustration, guilt, embarrassment, irritation, jealousy, or fear and schizophrenia. Positive thinking is like an optimistic person who sees good things everywhere and is generally confident and hopeful of the future. From the optimist's point of view, the world is full of potential opportunities. 

Individuals’ statuses were collected using Online Social Networks (OSN) like Facebook, Twitter, Instagram, and Reddit, matching both positive and negative thinking. For research purposes, thoughts were collected using specific positive keywords such as #Success, #Life, #Happiness, #Dream, etc. and negative keywords such as #Difficulties, #Feeling, #Failure, #Worry and many more. To find these keywords, as a reference, I have used a dataset [1] of 150 positive and 150 negative adjectives describing personality characters and another database [2] of English EMOtional TErms (EMOTE), which provides positive and negative subjective ratings for 1287 nouns and 985 adjectives.

References:
[1] Raslescu, Andreea; Kreicker, Sophie; Gillespie, Amy; Berners-Lee, William; Murphy, Susannah E; Harmer, Catherine J (2022), “UK dataset of valence, imageability and frequency ratings of 300 adjectives for use in cognitive-emotional tasks”, Mendeley Data, V1, doi: 10.17632/kgk3jbx9xb.1
[2] Grühn, D. (2016). An English Word Database of EMOtional TErms (EMOTE). Psychological Reports, 119(1), 290-308. https://doi.org/10.1177/0033294116658474
DOI: 10.17632/hn4v58fkkz
title: Vietnamese General School Teachers and Administrators': Job Satisfaction and Happiness

description: This data was collected through a questionnaire for Vietnamese teachers. Description of their level of happiness and job satisfaction based on the differences between the factors and the level of support for teachers by stakeholders
DOI: 10.17632/k49x47v732
title: Indian Coin Currency Dataset

description: Currency recognition and classification is one essential task to do. Both paper and coin currency play important role in transactions in everyday life. But provided there are many datasets available for paper currency, and very less datasets are available for coin currency.  Coin currency recognition becomes important because even though the amount for which people do coin transactions is small but inaccuracy in recognition can lead to huge loss. Following are the objectives to create this dataset:

·        Create a dataset of old and new Indian coin currency.

·        Dataset of good quality images with properly fixed dimensions of 256*256 pixels.

·        Dataset is in two formats, Yolo and PASCAL(VOC).

This image dataset consists of 1907 images, having 4 classes: Re 1 coin, Rs 2 coins, Rs 5 coins, and Rs 10 coins. The images were taken by the mobile phone’s rear camera. They were taken under different conditions like light differences, and different backgrounds, also each class has a different type of coin, for example, a 1re coin has 3 types of different coins based on its design and structure.
DOI: 10.17632/k9kvm5tn3f
title: Data repository for Camargo, et. al. A comprehensive, open-source dataset of lower limb biomechanics. Part 2 of 3

description: Part 2/3 of the dataset for "Camargo, et. al. A comprehensive, open-source dataset of lower limb biomechanics in multiple conditions of stairs, ramps, and level-ground ambulation and transitions." Dataset linked from https://doi.org/10.1016/j.jbiomech.2021.110320 (2021-02-24)
DOI: 10.17632/448d7kts3k
title: PT-EN Zomato dataset

description: The PT-EN Zomato Dataset is a set of half a million Portuguese restaurant reviews and approximately 24 thousand English reviews reviews. The dataset has a total of 1192173 rows with information about the restaurant where the review was given and a rating score from 1 to 5 stars. Not all the entries provide a text review. 

These data was collected by Zomato Portugal (now known as Dig-In) and made available during a founded research. The data corresponds to the period from April 1st, 2014 to September 2nd, 2022. 

The dataset provides the following columns:
review_id; user_pt_id; user_pt_name; user_in_id; user_in_name; text; rating; created_at; res_id; res_name; res_location; res_rating; res_price; res_zomato_id; res_lat; res_lng; res_address_full; res_address_city; res_about; res_group_name; res_group_type; res_priority; res_chain_id; res_menu_id; res_et; res_time_slot; res_company_name; res_seats_exterior; res_seats_interior; res_kitchen_Types; res_infos; res_delivery_Methods; text_language; text_translation_pt; text_translation_en.

The last three columns were obtained after data collection, using Google Translate Python API for language detection and text translation.
DOI: 10.17632/y2hhsygy49
title: Crohn's Disease Treatment Prediction Model

description: DB for Machine learning using clinical data at baselines. Used to predicts the medium-term efficacy of biologic therapies for in patients with Crohn's Disease.

1. Data Collection Sources
- Electronic Health Records (EHR)
- Clinical trials and studies
- Genetic data
- Patient-reported outcomes
- Medical imaging

Types of Data
- Demographic information
- Clinical data (symptoms, disease severity, treatment history)
- Genetic data (SNPs, mutations)
- Lab results (CRP levels, fecal calprotectin)
- Imaging data (MRI, endoscopy)
- Lifestyle data (diet, smoking status)

2. Data Preprocessing Steps
- Data Cleaning: Handle missing values, remove duplicates, correct errors.
- Data Normalization/Standardization: Normalize lab results, standardize imaging data.
- Feature Engineering: Create new features from existing data, e.g., calculate disease activity scores.
- Encoding Categorical Data: Convert categorical variables to numerical ones using one-hot encoding or label encoding.
- Data Splitting: Split data into training, validation, and test sets.
DOI: 10.17632/k46z9fzs6s
title: Data for: Feasible and pure P2O5-CaO nanoglasses: an in-depth NMR study of synthesis for the modulation of the bioactive ion-release

description: The different involved experimental datasets included in the article.
DOI: 10.17632/y8yrky75b2
title: Data on drying kinetics, moisture sorption isotherm, composition study of Ethiopian oyster mushroom (Pleurotus ostreatus mushroom) drying in tray dryer

description: The data included in this dataset are drying parameter optimization using RSM-BBD, which describes an experiment where Response Surface Methodology (RSM) with a Box-Behnken Design (BBD) was used to find the optimal drying conditions (temperature, air speed, and mass) for minimizing the moisture content of dried oyster mushrooms, and the description of drying kinetics data presents data on how the moisture content of oyster mushrooms changes over time at different drying temperatures. The drying kinetics data includes figures and tables with parameters derived from a drying kinetics model. The data also presents the description of moisture sorption data, which focuses on the relationship between moisture content and water activity in oyster mushrooms at different temperatures, and the description of mineral composition, proximate analysis, and functional group data, which presents data on the composition of fresh and dried oyster mushrooms.
DOI: 10.17632/trn8z8wxg6
title: Dataset on religiosity on the acceptance of Islamic microfinance in Kano State, Nigeria.

description: The present data from 194 customers of small and medium enterprises (SMEs) tell us about their acceptance of Islamic microfinance in Kano State, Nigeria. The dataset includes variables such as gender, age, marital status, duration as customer, account operate, annual income, type of business, service quality, perceived value, corporate image and religiosity of customers in Kano State. We fielded a survey from March to June 2019, self administered questionnaires were used for data collection. This data may help scholars to understand how people of Kano State accept Islamic microfinance interacted with service quality, customer perceived value, corporate image and religiosity.
DOI: 10.17632/zp9fh6scw9
title: A Generic Machine Learning Model for Spatial Query Optimization based on Spatial Embeddings (Datasets)

description: Datasets related to the source code in the GitHub repository: https://github.com/smigliorini/spatial-embedding