cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/js4sst2jc6.1
title: Influence of Scenario-based Learning on problem-solving using critical thinking analysis approach in medical and health science education.

description: Introduction: With the abrupt changes in educational systems, the educational sectors and teachers tried to develop new skills and practice toward students’ understanding of new skills and knowledge. So, there were some ways to encourage students to use their critical thinking and brainstorming to identify the problem or issues when providing scenarios based on clinical experience. Objective: the aim of this research study is to assess and explore the Influence of scenario-based learning on a critical thinking analysis approach in medical and health science education.. Method: This research study was a descriptive systematic review with meta-analyses for randomized control trials and quasi-experimental research studies that were conducted from the period of 2008 to 2022. The main themes of the research study were scenario-based learning on problem-solving by using a critical thinking approach abilities, the tutor’s role in solving the struggles that students faced during the application of scenario-based learning, and the strategical plan of the medical and health professional education toward scenario-based learning. The subthemes from the theme of scenario-based learning on problem-solving by using a critical thinking approach ability were problem-solving techniques and the plan of action during patient care with the implementation of the plan of care provided during clinical practice. The meta-analyses were done for 15 research studies in the medical and health science education specialist. This research examined the analyses from these studies by using Revman Review Manager 5.4 software. Result: The result of the study showed that all the research participants were 5265 at 100% weightage and risk ratio, M-H, random, and 95% CI were 0.78(0.69, 0.89), with heterogeneity Tau²= 0.05, chi ² = 164.88, and df= 14 (p=0.00001) that is highly significant( p &lt; 0.05). And the total effect was Z= 3.59 (p= 0.0003). conclusion: In conclusion, the study is supporting the research study with homogeneity results and is highly significant. Also, most of the research studies supported research studies that scenario-based learning is highly important in learning and teaching medical and health science specialties and this can help them before going to the training in the hospitals.
DOI: 10.17632/xmjfkvrfwb.1
title: Soundscape.The impact of natural (ambient) sounds above the water and on air.

description: The impact and differences of sounds above the sea water and on air.Field experiment.
DOI: 10.17632/9jvm25xv5d.1
title: Assessing Environmental, Social, And Governance (ESG) Performance of Global Electronics Industry: An Integrated MCDM Approach-Based Spherical Fuzzy Sets

description: Data for ESG assessment
DOI: 10.5281/zenodo.10035659
title: Reinforcement learning prioritizes general applicability in reaction optimization - optimization data logs

description: A zipped file of all optimization data logs for publication "Reinforcement learning prioritizes general applicability in reaction optimization". Included in the files are: acquisition logs for simulation testing with synthetic data, simulation testing with various chemistry datasets and a real time amide coupling optimization
DOI: 10.5281/zenodo.8170874
title: Reinforcement learning prioritizes general applicability in reaction optimization - optimization data logs

description: A zipped file of all optimization data logs for publication "Reinforcement learning prioritizes general applicability in reaction optimization". Included in the files are: acquisition logs for simulation testing with synthetic data, simulation testing with various chemistry datasets and a real time amide coupling optimization
DOI: 10.5281/zenodo.10035697
title: FS_Ontogeny_Coded_Data

description: The README file describes the samples and data collection procedures for archived data associated with the grant listed below, specifically regarding the coded data related to frontal sinus ontogeny.  Dataset contains age of stabilization data for frontal sinus traits of 146 individuals.
description: Grant Funding: National Institute of Justice (NIJ) Award # 2020-75-CX-0013; awarded to PI Lauren N Butaric.
DOI: 10.5281/zenodo.10035696
title: FS_Ontogeny_Coded_Data

description: The README file describes the samples and data collection procedures for archived data associated with the grant listed below, specifically regarding the coded data related to frontal sinus ontogeny.  Dataset contains age of stabilization data for frontal sinus traits of 146 individuals.
description: Grant Funding: National Institute of Justice (NIJ) Award # 2020-75-CX-0013; awarded to PI Lauren N Butaric.
DOI: 10.5281/zenodo.10035703
title: FS_PopFreq_Data

description: The current associated dataset includes coded frontal sinus traits and measurements of 409 adult individuals. Associated README file describes the samples and data collection procedures for archived data associated with the grant listed below, specifically regarding the coded and metric data related to population variation and frequencies for forensic identification purposes. 
description: Grant Funding: National Institute of Justice (NIJ) Award # 2020-75-CX-0013; awarded to PI Lauren N Butaric.
DOI: 10.5281/zenodo.10035702
title: FS_PopFreq_Data

description: The current associated dataset includes coded frontal sinus traits and measurements of 409 adult individuals. Associated README file describes the samples and data collection procedures for archived data associated with the grant listed below, specifically regarding the coded and metric data related to population variation and frequencies for forensic identification purposes. 
description: Grant Funding: National Institute of Justice (NIJ) Award # 2020-75-CX-0013; awarded to PI Lauren N Butaric.
DOI: 10.17632/hfbn66sgw5.1
title: Supplementary Table 2

description: Treatment response summary of patients with GGA
DOI: 10.17632/583wdgfzjs.1
title: Solar interfacial evaporation for efficient treatment of sewage containing volatile organic compounds and toxic heavy metal ions: a sequential process of adsorption, coagulation, and evaporation

description: Original Data and some origin data graphs
DOI: 10.17632/8p7x4xmc2s.1
title: Management of business sustainability during digital transformation on the basis of big data and artificial intelligence

description: The dataset systematizes and presents in tabular form official international IMD statistics for 2023 for 62 countries. В датасете систематизирована и приведена в табличном виде официальная международная статистика IMD за 2023 г. по 62 странам мира. Data sources (источники данных): 1) IMD World Competitiveness Booklet 2023. URL: https://imd.cld.bz/IMD-World-Competitiveness-Booklet-2023/58/ 2) IMD World Competitiveness Online. URL: https://worldcompetitiveness.imd.org/Copyright?returnUrl=%2F 3) IMD World Talent Ranking 2023. URL: https://imd.cld.bz/IMD-World-Talent-Report-20232/40/#zoom=true
DOI: 10.17632/bhmthf6vhd.1
title: Relationship among folate deficiency, appetite and ovarian health

description: Supplementary file for Manuscript
DOI: 10.17632/9cbw2b7h57.1
title: Hausa Lexicon-based Sentiment Analysis Dataset for NLP

description: NLP Data for the Hausa Language
DOI: 10.17632/r4y4jhr572.1
title: Impact of communication skills of staff on Passenger Satisfaction: A study on Pakistani Airlines

description: The data was collected from Airlines staff working on airport
DOI: 10.17632/gywf9n8d5t.1
title: the effect of HD-tDCS on posture control

description: 1=right HD-tDCS; 2=left HD-tDCS；3=bilateral HD-tDCS； 4=sham stimulation. The main purpose of this study is to explore whether HD-tDCS of the left-, right- or bilateral-parietal lobes would improve the ability of posture control and response, and whether they would improve the ability of visual, somatosensory and vestibular system to maintain posture control. The hypothesis of this study was that HD-tDCS of the unilateral and bilateral parietal lobes could improve the posture control and response. The right stimulation could promote the ability of visual system, and the left stimulation could promote the ability of somatosensory system to maintain stability. All participants completed the sensory organization test (SOT) and motor control test (MCT) on the Bertec® Balance Advantage®. SOT is a method to quantify the ability of the sensory system (visual, proprioception and vestibular system) to maintain balance by changing the reference conditions, which is composed of 6 conditions. The main outcome of SOT were equilibrium (ES), composite (CS) and sensory scores (visual VIS, somatosensory SOM ,vestibular VEST and visual preference PREF score). ES is generated for each condition and CS is a comprehensive score calculated based on the scores of each condition. A higher value representing greater balance performance. The CS is the most commonly used SOT score to assess postural control. The sensory score is a ratio calculated from the ES under different conditions. The SOM, VIS and VEST scores are used to assess the ability of each respective sensory system to maintain stability, and the PREF score assesses an individual’s reliance on visual information to control balance. MCT is designed to assess the latency and response strength of automatic response to horizontal platform translations in both forward and backward directions at three distinct magnitudes (mall, medium, and large). The main outcome of MCT were latency and response strength. The latency records the time from perturbation onset to mechanical response of each leg. The response strength is the instrument to quantify the force of the posture response. All data were averaged across the three successful trials completed by each participant.
DOI: 10.17632/vmwgtj58xs.1
title: Physical fitness feature of athletes 

description: This dataset is based on physical fitness tests of athletes who competed nationally and won national sports events. They received gold, silver, and bronze medals. Athletes' information for a wide variety of sports can be found here. Those interested in in-depth information can analyze and test it for further research. This dataset has already been cleaned up to eliminate errors in the data recorded.
DOI: 10.17632/vmwgtj58xs.2
title: Physical fitness feature of athletes 

description: This dataset is based on physical fitness tests of athletes who competed nationally and won national sports events. They received gold, silver, and bronze medals. Athletes' information for a wide variety of sports can be found here. Those interested in in-depth information can analyze and test it for further research. This dataset has already been cleaned up to eliminate errors in the data recorded.
DOI: 10.17632/vmwgtj58xs.3
title: Physical fitness feature of athletes

description: This dataset is based on physical fitness tests of athletes who competed nationally and won national sports events. They received gold, silver, and bronze medals. Athletes' information for a wide variety of sports can be found here. Those interested in in-depth information can analyze and test it for further research. This dataset has already been cleaned up to eliminate errors in the data recorded.
DOI: 10.17632/z5m4fwkhgf.1
title: Study on the mechanism of Myh3 gene affecting intramuscular fat content in Beijing Black pigs through MAPK signaling pathway Supplementary Figure

description: Original Images
DOI: 10.17632/mb74wszvdd.1
title: Study IL- 35 level and Fibronectin type Ⅲ domain containing protein 5 \ Irisin (FNDC5 rs3480) gene variations in chronic hepatitis B.

description: This is a case-control study that included eighty patients with CHB and LC and eighty healthy controls. For each patient, a history was taken, a full clinical assessment was done, and an abdominal US, HBAg, FNDC5 (rs3480), and IL-35 assay were performed. We use Statistical Program for Social Science (SPSS) version 26(Armonk, NY: IBM Corp). The gathering of data was recorded and evaluated on an IBM-compatible computer. Tests of significance such as the CHI square test, Mann-Whitney, and Kruskal-Wallis H test were utilized for comparing different parameters in our participants.
DOI: 10.17632/3mtfszhkjc.1
title: data.dta

description: All the original data come from the Statistical Yearbook of China City, the Statistical Yearbook of China City Construction and the statistical yearbooks of provinces and cities. Considering the availability of some data, the time period is 2006-2020, which can be used to analyze the relationship between urbanization, economic agglomeration and economic growth.
DOI: 10.17632/z3g26tphnv.3
title: Physiological Signals Based Mental Fatigue Analysis & Recognition: MEFAR

description: The dataset was created specifically for analyzing mental fatigue based on physiological signals. It includes the following signals:

EEG (Electroencephalography): Measures the electrical activity of the brain.
BVP (Blood Volume Pulse): Captures changes in blood volume in peripheral blood vessels.
EDA (Electrodermal Activity): Tracks changes in the electrical conductance of the skin.
HR (Heart Rate): Records the number of heartbeats per minute.
TEMP (Temperature): Monitors the body temperature of the participants.
ACC (Acceleration): Measures the acceleration experienced by the participants.
The measurements were collected from 23 participants in both the morning and evening sessions. To evaluate the participants' mental fatigue levels, the Chalder Fatigue Scale was utilized. This scale assigns a score to each participant based on their responses, with a score of 12 or higher indicating a positive mental fatigue condition.

The dataset includes both raw and processed data. Raw data refers to the original recorded signals, while processed data typically involves signal preprocessing techniques such as filtering, artifact removal, and feature extraction.The processed data includes processed data based on different sampling frequencies (1 Hz, 32 Hz, and 64 Hz). These operations include downsampling, midsampling, and upsampling. The processed datasets are named MEFAR_DOWN, MEFAR_MID, and MEFAR_UP, corresponding to the processed data with downsampling, midsampling, and upsampling, respectively.This way, it was possible to analyze and compare data with different sampling frequencies.

The dataset has been used for training deep learning and transfer learning models, which suggests that it may be suitable for developing machine learning algorithms for mental fatigue detection based on physiological signals.

Additionally, demographic information about the participants is available in an Excel file called "general_info." It is important to ensure that the participants' anonymity and privacy are maintained in accordance with ethical guidelines.

By sharing this dataset, researchers interested in mental fatigue analysis can utilize it for further investigations, algorithm development, and validation.
DOI: 10.17632/z3g26tphnv.1
title: MEFAR

description: The dataset was created specifically for analyzing mental fatigue based on physiological signals. It includes the following signals:

EEG (Electroencephalography): Measures the electrical activity of the brain.
BVP (Blood Volume Pulse): Captures changes in blood volume in peripheral blood vessels.
EDA (Electrodermal Activity): Tracks changes in the electrical conductance of the skin.
HR (Heart Rate): Records the number of heartbeats per minute.
TEMP (Temperature): Monitors the body temperature of the participants.
ACC (Acceleration): Measures the acceleration experienced by the participants.
The measurements were collected from 23 participants in both the morning and evening sessions. To evaluate the participants' mental fatigue levels, the Chalder Fatigue Scale was utilized. This scale assigns a score to each participant based on their responses, with a score of 12 or higher indicating a positive mental fatigue condition.

The dataset includes both raw and processed data. Raw data refers to the original recorded signals, while processed data typically involves signal preprocessing techniques such as filtering, artifact removal, and feature extraction.The processed data includes processed data based on different sampling frequencies (1 Hz, 32 Hz, and 64 Hz). These operations include downsampling, midsampling, and upsampling. The processed datasets are named MEFAR_DOWN, MEFAR_MID, and MEFAR_UP, corresponding to the processed data with downsampling, midsampling, and upsampling, respectively.This way, it was possible to analyze and compare data with different sampling frequencies.

The dataset has been used for training deep learning and transfer learning models, which suggests that it may be suitable for developing machine learning algorithms for mental fatigue detection based on physiological signals.

Additionally, demographic information about the participants is available in an Excel file called "general_info." It is important to ensure that the participants' anonymity and privacy are maintained in accordance with ethical guidelines.

By sharing this dataset, researchers interested in mental fatigue analysis can utilize it for further investigations, algorithm development, and validation.
DOI: 10.17632/rrrj2m5zjv.1
title: Allosterically inhibited PFKL via Prostaglandin E2 Withholds Glucose Metabolism and  Ovarian Cancer Invasiveness

description: partial raw data in this research article，Allosterically inhibited PFKL via Prostaglandin E2 Withholds Glucose Metabolism and  Ovarian Cancer Invasiveness，which published in CELL REPORTS
DOI: 10.17632/rrrj2m5zjv.2
title: Allosterically inhibited PFKL via Prostaglandin E2 Withholds Glucose Metabolism and  Ovarian Cancer Invasiveness

description: partial raw data in this research article，Allosterically inhibited PFKL via Prostaglandin E2 Withholds Glucose Metabolism and  Ovarian Cancer Invasiveness，which published in CELL REPORTS
DOI: 10.17632/rrrj2m5zjv.3
title: Allosterically inhibited PFKL via Prostaglandin E2 Withholds Glucose Metabolism and  Ovarian Cancer Invasiveness

description: raw data in this research article，Allosterically inhibited PFKL via Prostaglandin E2 Withholds Glucose Metabolism and  Ovarian Cancer Invasiveness，which published in CELL REPORTS
DOI: 10.17632/rrrj2m5zjv.4
title: Allosterically inhibited PFKL via Prostaglandin E2 Withholds Glucose Metabolism and Ovarian Cancer Invasiveness

description: raw data in this research article，Allosterically inhibited PFKL via Prostaglandin E2 Withholds Glucose Metabolism and Ovarian Cancer Invasiveness，which published in CELL REPORTS
DOI: 10.17632/xzjsxxk56t.1
title: Supplemental material: Rivaroxaban in the Treatment of Livedoid Vasculopathy

description: Supplementary Figure: Leision of livedoid vasculopathy before and after rivaroxaban treatment of partial patients. Supplementary Table: Patient data
DOI: 10.17632/4scgpfrr6x.1
title: GRL_Paper_Das_2023
DOI: 10.17632/f7dk2yknff.1
title: fig leaves dataset

description: a primary data set collected from various geographic locations in Iraq for healthy and Infected fig’s leaves with Ficus leafworm. This worm causes major economic damage, and infection may result in trees being stripped of their leaves, leading to a lack of production. The classes included in the dataset are: infected and healthy. Leaves of each class in the fruiting season photographed with high-resolution device as specified . A total of 2321 images (i.e., 1350 infected images and 971 healthy images) were captured using random sampling approach while maintaining the balance and diversity within one fig's tree images data and a different fig's trees. The proposed dataset is of significant potential impact and usefulness with features including (but not limited to) 2 classes, infected and healthy that can support the pest control industry in agriculture and food manufactures.
DOI: 10.17632/nvs7g8y49t.1
title: Dataset on the impact of microbes on enhanced oil recovery

description: Physiochemical data on the effect of biosurfactant (Bacillus letus and Pseudomonas aeruginosa) on enhanced oil recovery
DOI: 10.17632/6j57cjkd6t.1
title: EMIRS water ice cloud effective radius retrievals for one martian year

description: Approximately one Martian year (roughly solar longitude, L_s = 130 degrees from Mars Year 36 to 37; November 2021–September 2023) of thermal infrared spectra from the Emirates Mars Infrared Spectrometer (EMIRS) were utilized for this dataset. Retrieval output for each spectrum is stored as a self describing NetCDF4 file (https://www.unidata.ucar.edu/software/netcdf/). Variable descriptions are included in the file archive. Coordinate variables associated with the observation are latitude, longitude, solar longitude, local true solar time, emission angle of the observation, and the spacecraft clock timestamp when the observation was made. Output from the aerosol retrieval are stored as data variables and include the surface temperature, water-ice optical depth, water-ice optical depth uncertainty, water-ice effective radius, water-ice effective radius uncertainty, surface anisothermality "slope" correction parameter, surface emissivity correction parameter, estimated water condensation level, and a boolean flag indicating the effective radius retrieval passed quality checks and was considered valid. Each data point in this archive is associated with one unique EMIRS spectrum as indicated by the onboard spacecraft clock. Data points included here are those which passed quality checks for water-ice cloud optical depth. Data points which did not pass quality checks for the effective radius retrieval are indicated with the "refficevalid" flag. Description of the retrieval and data in this archive can be found in the manuscript "Spatial and temporal variability of martian water-ice cloud effective radius in EMIRS thermal infrared observations" by Samuel A. Atwood, Michael D. Smith, Michael J. Wolff, Khalid Badri, Christopher S. Edwards, Philip R. Christensen, Alain SJ. Khayat, and M. R. El-Maarry, submitted to Icarus.
DOI: 10.17632/r3cybcfphf.1
title: Artificial coral and non coral Mediterranean Reefs.A threat or a solution?

description: Artificial coral and non coral Mediterranean Reefs.A threat or a solution?
DOI: 10.17632/5tp2p84mzc.1
title: From Climate to Crop: Unveiling the Impact of Agro-Climate Dataset on Rice Yield in Cotabato Province

description: The data was collected from the Office of the Provincial Agriculturist and NASA Power dataset agro-climate dataset from 2007 to 2021. The data was processed using ETL, and multivariate linear regression analysis was conducted to identify the agro-climates that significantly influence the production of irrigated and rainfed rice.
The dataset provides information on various agro-climatic factors such as temperature, rainfall, solar radiation, and humidity, along with the production of irrigated and rainfed rice. The dataset also includes explanatory factors that significantly influence the production of rice, which are presented in an Analytical Dashboard.The dataset can be used for predictive analytics research at the municipal level to provide more detailed insights into the agro-climates of different municipalities in Cotabato Province. It can also be used to distribute different varieties of rice that can withstand the effects of climate change to the municipalities of Cotabato.
Overall, the dataset provides valuable insights into the relationship between agro-climate and rice production in Cotabato Province, and can inform future decision-making and resource allocation in the region.