cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/hd5y556xht.1
title: SPSS Dataset: Assessment of the High Performance Cycle with U.S. Workers

description: Data collected from U.S. workers. Survey delivered and sample obtained using Prolific (https://www.prolific.co/), with a sample representative of the U.S. population across age, gender and ethnicity. The high performance cycle questionnaire was developed by Borgogni and Dello Russo (2012). A self-report questionnaire developed by Onwezen, van Veldhoven and Biron (2014) was used to assess job performance. Data was transferred to SPSS AMOS for structural equation modeling analysis.
DOI: 10.17632/8ng58jj2vp.1
title: Evaluation of the Effects of Learning Activities towards Student’s Performance using ANN dataset

description: This is the dataset for the paper titled "Evaluation of the Effects of Learning Activities towards Student’s Performance using ANN"

Students of a specific class in a specific semester were asked to participate.

It includes the responses to the questions of:
Research done on the subject
Asking questions about what was taught in class
Studying the material before class
Interest in the subject
Stress affecting classroom
Quality of sleep affecting you in the classroom
Not attending classes
How many subjects did you have during the semester?
A split of effort in learning between theoretical/practical/internet sources
What was your final result for the subject?

It is scaled from 0-100 with 100 being heavy in agreement and 0 being heavy in disagreement.
DOI: 10.17632/js2nzwf5md.2
title: Dataset for "XRF and XRPD data sets in ternary mixtures with high level micro-absorption and/or preferred orientations problems for phase quantification analysis"

description: XRF and XRPD data were collected on four different mixture experimental domain, each containing one or more common issues for phase quantification: micro-absorption and preferred orientations. Simplex-Centroid experimental design was used to homogeneously explore the experimental domain. Microabsorption and preferred orientations were included in a controlled way, by choosing the appropriate components each time. The datasets are respectively: - D1: A three component mixture containing bismuth oxide (MM: 208.980 g/mol, density: 8.93 g/cm^3, Z of the heaviest element: 83), barium sulfate (MM: 137.327 g/mol, density: 4.48 g/cm^3, Z of the heaviest element: 56) and sieved graphite (MM: 12.01 g/mol, density: 2.23 g/cm^3, Z of the heaviest element: 6) with a particle size lower than 90 micrometers (non-oriented). - D2: A three component mixture containing bismuth oxide (MM: 208.980 g/mol, density: 8.93 g/cm^3, Z of the heaviest element: 83), barium sulfate (MM: 137.327 g/mol, density: 4.48 g/cm^3, Z of the heaviest element: 56) and sieved graphite (MM: 12.01 g/mol, density: 2.23 g/cm^3, Z of the heaviest element: 6), divided in about 70 % sieved graphite with a particle size lower than 90 micrometers (non-oriented) and 30% sieved graphite with particle size higher than 90 micrometers (oriented). - D3: A three component mixture containing bismuth oxide (MM: 208.980 g/mol, density: 8.93 g/cm^3, Z of the heaviest element: 83), barium sulfate (MM: 137.327 g/mol, density: 4.48 g/cm^3, Z of the heaviest element: 56) and zinc acetate (MM: 219.528 g/mol, density: 1.74 g/cm^3, Z of the heaviest element: 30). - D4: A three component mixture containing bismuth oxide (MM: 208.980 g/mol, density: 8.93 g/cm^3, Z of the heaviest element: 83), barium sulfate (MM: 137.327 g/mol, density: 4.48 g/cm^3, Z of the heaviest element: 56) and urea (MM: 60.06 g/mol, density: 1.32 g/cm^3, Z of the heaviest element: 8). The aim of this datasets is to provide an open-source collection data on which perform quantification analysis by both traditional and innovative methods. More informations are detailed in the data paper "XRF and XRPD data sets in ternary mixtures with high level micro-absorption and/or preferred orientations problems for phase quantification analysis".
DOI: 10.17632/nz252wbjyn.1
title: Country Matrixes for QCA Analysis

description: Assessment of key enabling factors for smallholder commercial tree growing in Indoensia (Java and Kalimantan & Sumatra), Tanzania, Uganda and Vietnam between 1990-2015. Factors cover remote conditions (Land and forest tenure TEN; Wood demand and supply balance (demographic factors, industry and trade) DEMSUP; Land use pressures and competition with agriculture AGR; Macroeconomic environment (GDP/GNI per capita, economic growth and stability); and political stability MACRO) and proximate conditions (Wood markets and pricing MAR; Capacity and knowledge in tree growing KNOW; Direct incentives (goods and materials; grants; tax reliefs, concessions; differential fees etc. DIRINC ; and Indirect incentives (advisory services and trainings, stronger tenure rights on land etc. INDIRINC). The data has been collected through a desk review and it analyzed extensive amount of relevant previous research and existing documentation from all case-study countries to answer the questions related to factors and their indicators in the data matrix. Studies and documents were searched by country with Google Scholar, Web of Science and Google for each enabling factor with specific key words. Document relevance was assessed based on the abstracts or summaries of the documents, and presumptive reliability of the source as not all the documents were from peer reviewed journals. The data for Laos and Tanzania was completed with field research findings. Data collection for Vietnam was mainly carried out by research partners from CIFOR. All country matrixes were reviewed by highly recognized partners with in-depth knowledge of the country and the sector to increase the level of objectivity in the data interpretation. Analysis of the Indonesia data showed significant regional differences in the enabling factors between Java and Kalimantan and Sumatra. Each factor consists of several indicators ranked as POS if they can be considered being supportive for smallholder tree growing and NEG if they have a negative impact. Once a pre-set number of indicators are positive the factor can also be considered POSITIVE, i.e. supportive for smallholder commercial tree growing.
DOI: 10.17632/t4zm24zdty.1
title: Effect of Equity Checks and Balances on Corporate Social Responsibility: The Mediation and Moderator Roles of Green Innovation Performance and Environmental Uncertainty

description: In order to explore the interaction between internal factors of corporate governance, this study combined with principal-agent theory and stakeholder theory,  using a sample of Chinese A-share listed companies on Shanghai and Shenzhen stock exchanges from 2012 to 2019, constructs a regulated mediation effect model, empirically examines the impact of equity checks and balances on corporate social responsibility and the mediation and mediator roles of green innovation performance and environmental uncertainty. The results show that: (1) Equity checks and balances among shareholders have a significant positive impact on corporate social responsibility; (2) Equity checks and balances have a positive impact on green innovation performance, green innovation performance has a positive impact on corporate social responsibility, and green innovation performance plays a partial mediation effect between equity checks and balances and corporate social responsibility; (3) Additionally, environmental uncertainty not only moderates the relationship between Green Innovation Performance and CSR, but also moderates the direct effect between equity balance and CSR, which verifies the existence of a moderated mediation effect. The effect of the robustness test is significant. These results can be used as a reference for corporate governance, improving innovation performance, and fulfilling CSR.
DOI: 10.17632/y4bwcfwryj.2
title: Efficacy and safety of dual biologic therapy in inflammatory skin diseases: A systematic review

description: Supplemental Files for Efficacy and safety of dual biologic therapy in inflammatory skin diseases: A systematic review
DOI: 10.17632/958wvr38gy.5
title: Android Malware and Normal permissions dataset

description: This dataset contains 18,850 normal android application packages and 10,000 malware android packages which are used to identify the behaviour of malware application on permission they need at run-time.
DOI: 10.17632/nwwvh8nt63.2
title: electricity consumption invoice data

description: This is pre-processed data of fraud detection in electricity and gas consumption obtained from Kaggle, an open-source website for data. There are two datasets. The first dataset is the pre-processed data where the duplicates and missing values have already been removed. The data had also been filtered to consist of only rows of data for electricity consumption, client category of 11, the counter coefficient is one and lastly, invoices dated in 2019 are included for model training.
DOI: 10.17632/4rws4ts48y.1
title: Data for: A Systematic Literature Review of Supply Chain Decision Making supported by the Internet of Things and Big Data Analytics

description: Data extraction forms for the IoT, BDA, and SCM research disciplines, plus a fourth category to gain insight into the supply chain performances enabled by the IoT’s analytical capabilities within SCM and logistics operations. The filled-in data extraction forms for all four categories are also added to the main manuscript (see appendix C up to and including appendix F).
DOI: 10.17632/237462r82r.1
title: Economic complexity, shadow economy, and income inequality: fresh evidence from panel data

description: Panel dataset for examining the relationship between economic complexity, shadow economy, and income inequality
DOI: 10.17632/5sr3hhmft3.1
title: A dataset for validation of the stages of concerns questionnaire (SoCQ) – an instrument to measure the concerns of using e-learning platform in Malaysia.

description: This data set is aimed to be published in Data In Brief. This dataset contains the feedback from 7 experts on the evaluation of Stages of Concern Questionnaire (SoCQ) – an instrument measuring the concerns of teachers during the adoption process of an innovation implemented. Four categories were evaluated for each of the items, namely relevance, clarity, ambiguity and simplicity. This dataset also includes an excel file where it could be replicated for future use in terms of determining the content validity index of other instruments. Researchers that are keen in establishing content validity index of other instrument may make use of the dataset. The dataset includes also 30 responses from a pilot study, where the data is used for the reliability test of SoCQ.
DOI: 10.17632/p5hvjzsvn8.1
title: Data for: Wild blueberry yield prediction using a combination of computer simulation and machine learning algorithms

description: A number of research is underway in the agricultural sector to better predict crop yield using machine learning algorithms. Many machine learning algorithms require large amounts of data in order to give useful results. One of the major challenges in training and experimenting with machine learning algorithms is the availability of training data in sufficient quality and quantity remains a limiting factor. In the paper, “Wild blueberry yield prediction using a combination of computer simulation and machine learning algorithms”, we used dataset generated by the Wild Blueberry Pollination Model, a spatially explicit simulation model validated by field observation and experimental data collected in Maine USA during the last 30 years. The blueberry yields predictive models require data that sufficiently characterize the influence of plant spatial traits, bee species composition, and weather conditions on production. In a multi-step process, we designed simulation experiments and conducted the runs on the calibrated version of the blueberry simulation model. The simulated dataset was then examined, and important features were selected to build four machine-learning-based predictive models. This simulated data provides researchers who have actual data collected from field observation and those who wants to experiment the potential of machine learning algorithms response to real data and computer simulation modelling generated data as input for crop yield prediction models.
DOI: 10.17632/29ntw7sh4r.5
title: Human breast cancer in situ capturing transcriptomics

description: Triplicates from 23 breast cancer patients with luminal a, luminal b, triple-negative, and HER2-positive subtypes. Please refer to metadata.csv for patient, replicate, and subtype associations.

All samples were produced using the protocol described in [1].

[1]: http://doi.org/10.1126/science.aaf2403

Changes in Version 4 and 5:
- Attempt to fix misordered contributors list

Changes in Version 3:
- Added tumor annotation files

Changes in Version 2:
- Added indices to spot files
- Dropped sample with bad spot data (23901_C1)
DOI: 10.5061/dryad.j6c3v
title: Data from: Oral administration of Polymyxin B modulates the activity of Lipooligosaccharide E. coli B against lung metastases in murine tumor models
DOI: 10.17632/v9wnr4bft9.1
title: Data for: Wind turbine fault diagnosis based on ReliefF-PCA and DNN

description: There are 4 databases, which includes four wind turbines' fault data.
DOI: 10.17632/nhw8ztfb63.3
title: Bangla GHQ-12 validation

description: The Bangla-translated 12-item General Health Questionnaire (GHQ-12) has been used to assess mental health issues among Bangladeshi nationals without being appropriately validated. Hence, we examined the item quality of this questionnaire, its latent structure, and measurement invariance across gender and psychiatric sub-groups. A community sample of 788 adults (249 females) aged between 18 and 69 years completed the questionnaire.
DOI: 10.17632/5d3nkyhsrf.1
title: Amharic Sign Language Data Sets

description: Hearing-impaired people use Sign Language to communicate with each other as well as with other communities. Usually, they are unable to communicate with normal people. Most of the people without hearing disability do not understand the Sign Language and unable to understand hearing-impaired people. So, they need recognition of Sign Language to text. A data set is collected from different teachers of sign language for recognition of Amharic Sign Language to Amharic characters. After gathering data with different backgrounds and positions of hands, the data is prepared for feeding to machine learning. The initial step for preprocessing data is frame extraction of video followed by resizing data and feature extraction. By using the LabelImg tool we annotated this frame of data to create XML, TFrecord, and CSV. Finally, we fed the data into two different models: Faster R-CNN and Single-Shot Multibox (SSD) detector. From the result of the models, we justified for Amharic Sign Language recognition to characters the SSD better in accuracy than Faster R-CNN but Faster RCNN is good with accuracy. Anyone can use the data for recognizing Amharic Sign Language to Amharic characters from the image, video, and Real-time. We used 10 class for recognizing the characters, the research will continue to include the remaining six orders, words, and sentences used in Sign Language to have a full-fledged Sign Language recognition model to a complete system.
DOI: 10.15468/dl.yenbdr
title: Occurrence Download

description: A dataset containing 1518 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pinus pinaster Aiton",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 1518 records from 104 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009232-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/4mcc9rg4k5.1
title: HEPASS algorithm dataset

description: This repository contains the image dataset and the manual annotations used to develop the HEPASS algorithm for automated liver steatosis quantification: - Salvi M., Molinaro M., Metovic J., Patrono D., Romagnoli R., Papotti M, and Molinari F., "Fully Automated Quantitative Assessment of Hepatic Steatosis in Liver Transplants", Computers in Biology and Medicine 2020 (DOI: 10.​1016/​j.​compbiomed.​2020.​103836) ABSTRACT Background: The presence of macro- and microvesicular steatosis is one of the major risk factors for liver transplantation. An accurate assessment of the steatosis percentage is crucial for determining liver graft transplantability, which is currently based on the pathologists’ visual evaluations on liver histology specimens. Method: The aim of this study was to develop and validate a fully automated algorithm, called HEPASS (HEPatic Adaptive Steatosis Segmentation), for both micro- and macro-steatosis detection in digital liver histological images. The proposed method employs a hybrid deep learning framework, combining the accuracy of an adaptive threshold with the semantic segmentation of a deep convolutional neural network. Starting from all white regions, the HEPASS algorithm was able to detect lipid droplets and classify them into micro- or macrosteatosis. Results: The proposed method was developed and tested on 385 hematoxylin and eosin (H&E) stained images coming from 77 liver donors. Automated results were compared with manual annotations and nine state-of-the-art techniques designed for steatosis segmentation. In the TEST set, the algorithm was characterized by 97.27% accuracy in steatosis quantification (average error 1.07%, maximum average error 5.62%) and outperformed all the compared methods. Conclusions: To the best of our knowledge, the proposed algorithm is the first fully automated algorithm for the assessment of both micro- and macrosteatosis in H&E stained liver tissue images. Being very fast (average computational time 0.72 seconds), this algorithm paves the way for automated, quantitative and real-time liver graft assessments.
DOI: 10.17632/g2p7vwxyn2.1
title: ECG and GSR Data for Emotion Recognition during Covid-19 Epidemic

description: We present the 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 for the epidemic stressed situation of Covid-19.
DOI: 10.15468/dl.bwr5sq
title: Occurrence Download

description: A dataset containing 106240 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is International Barcode of Life project (iBOL)",
 "GadmLevel0Gid is NOR"
 ]
}

 The dataset includes 106240 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009220-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/55hzsxrv7y.1
title: River and Ocean Water Quality in Bali, Indonesia

description: Various water quality parameters in three rivers and ocean water around Bali, Indonesia. Parameters tested include salinity, pH, phosphates, and nitrates. Land use areas and percentage of total areas in a five km buffer zone around three rivers in Bali, Indonesia.
DOI: 10.17632/g7kf8x38ym.1
title: Hematological Dataset

description: - Researchers Information 
Safa S. Abdul-Jabbar, Alaa k. Farhan
1Computer Science Dept., College of Science for Women, University of Baghdad, Baghdad, Iraq
2Computer Science Dept., University of Technology, Baghdad, Iraq

-Context
This is the first Dataset for various Hematology patients in Iraq. The Dataset provides the patients’ Cell Blood Count test information that can be used to create a Hematology diagnosis/prediction system. Also, this Data was collected in 2022 from the Medial City / Hematology Center and can be cleaned & analyzed using any programming language because it is provided in an excel file that can be accessed and manipulated easily. 
- Content
This Dataset contains 300 rows. For each row (patient information), there are 28 columns containing CBC test features that can be described as follows:
1.	ID: Patients Identifier
2.	Gender: Patient sex (0 for Female and 1 for Male)
3.	DevTyp: Device Type (1 or 2)
4.	WBC: White Blood Cell 
5.	LYMp: Lymphocytes percentage, which is a type of white blood cell
6.	MONp: Monocytes percentage, which is a type of white blood cell
7.	NEUp: Neutrophils percentage, which is a type of white blood cell
8.	EOSp: Eosinophils percentage, which is a type of white blood cell
9.	BASOp: Basophils percentage, which is a type of white blood cell
10.	LYMn: Lymphocytes Number
11.	MONn: Monocytes Number
12.	NEUn: Neutrophils Number
13.	EOSn: Eosinophils Number
14.	BASOn: Basophils Number
15.	RBC: Red Blood Cell
16.	HGB: Hemoglobin
17.	HCT: Hematocrit is the proportion, by volume, of the Blood that consists of red blood cells
18.	MCV: Mean Corpuscular Volume
19.	MCH: Mean Corpuscular Hemoglobin is the average amount of haemoglobin in the average red cell 
20.	MCHC: Mean Corpuscular Hemoglobin Concentration.
21.	RDWSD: Red Blood Cell Distribution Width
22.	RDWCV: Red blood cell distribution width
23.	PLT: Platelet Count
24.	MPV: Mean Platelet Volume
25.	PDW: Red Cell Distribution Width
26.	PCT: The level of Procalcitonin in the Blood
27.	PLCR: Platelet Large Cell Ratio
28.	PLCC: Platelet Large Cell Count
- Acknowledgements
We thank the entire Medial City / Hematology Center team, especially ( Dr Mohammed Saleem Abbas) the director of the Hematology Center, for cooperating with us in collecting this data while maintaining patients' confidentiality.
DOI: 10.17632/jpsxp7dwds.4
title: Management of Juvenile-Onset Systemic Sclerosis with Systemic Immunosuppressive Therapies: An Evidence-Based Review

description: Juvenile-onset systemic sclerosis (JSSc) is a rare debilitating autoimmune condition resulting from inflammation, vascular abnormality, and progressive fibrosis. It affects connective tissue in multiple organ systems. This systematic review examines the use of systemic immunosuppressive therapies in JSSc, with a focus on its cutaneous manifestations.
DOI: 10.17632/vhm4vk46ck.1
title: Data and Codes

description: This folder contains the data used in the paper titled "World Prices and Business Cycles in a Small Open Input-Output Economy". It also contains the replication files and codes.