cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/5jk24v47zp
title: Secondary school teachers' and students' perceptions of teaching-learning activities used in biology classrooms

description: The data on teachers' and students' perceptions of teaching-learning activities used in Zambian secondary school biology classrooms were collected between February and May 2022 using two separate survey questionnaires administered to 57 secondary school biology teachers selected from 16 secondary schools and students (469) selected from eight secondary schools. Both instruments were five-point Likert-scale questionnaires measuring participants' perceptions of teaching-learning activities used in biology classrooms. The data includes respondents' gender and their responses to statements on teaching-learning activities used in biology classrooms. Furthermore, students' data on grade level and age were also collected. Respondents (subjects) indicated the degree to which they agreed with 26 teaching-learning activities related to (a) students' prior knowledge and misconceptions, (b) making teaching-learning easy, (c) biology curriculum, (d) teaching strategies, and (d) representations and analogies. The responses ranged from strongly disagree (1), representing disagreement/negative perception, to strongly agree (5), representing agreement/positive perception. Therefore, 1 and 2 represent disagreement/negative perception, 3 represents neutral perception, while 4 and 5 represent agreement/positive perception. The dataset is accompanied by an Excel file named "Dateset on teachers’ and students’ perceptions of biology teaching-learning activities" with five sheets: Sheet 1 (Teaching-learning activities), Sheet 2 (Raw data for teachers), Sheet 3 (Raw data for students), Sheet 4 (Combined raw data) and Sheet 5 (Analysed data). The data were analysed using SPSS version 25, and the results suggest significant differences between teachers' and students' perceptions about teaching-learning activities used in biology classrooms.
DOI: 10.17632/hsgzz6zd4z
title: Diagnosis and Impact of Migraine among the students of Chandigarh university: An Observational Study

description: The study titled "Diagnosis and Impact of Migraine among the Students of Chandigarh University: A Cross-sectional Observational Study" aims to investigate the prevalence, diagnosis, and impact of migraine headaches among students at Chandigarh University.
DOI: 10.17632/rpztyz22df
title: A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer’s disease

description: The clinical, radiomics and genetic data to reproduce the key findings in "A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer’s disease".

Alzheimer’s disease is the most common cause of dementia. It is a neurodegenerative disorder characterized by gradually progressive cognitive and functional deficits, as well as behavioral changes. The diagnosis of Alzheimer’s disease is often challenging leading to suboptimal patient care. In this study, we develop a new unsupervised analytic method based on the extraction of statistical features from multiple brain regions identified through structural magnetic resonance imaging data, which is able to reliably discriminate people with Alzheimer’s disease-related pathologies from those without. We provide a diagnostic tool that is ready to be integrated into the clinical decision support system without the need for additional sampling or patient testing.
DOI: 10.17632/t4twwtvv7r
title: Transcriptomic Similarities and Differences in Host Response between SARS-CoV-2 and Other Viral Infections

description: Supplementary material for "Transcriptomic Similarities and Differences in Host Response between SARS-CoV-2 and Other Viral Infections".
DOI: 10.17632/6pzp98jn3f
title: Source Code of Machine Learning Algorithm

description: Machine learning was used to model associations between exercise performance and metabolite responses. Model variables included metabolite response to exercise expressed as log2([post-exercise]/[pre-exercise]) (independent variable), VO2max, and RQ. Due to small sample size, samples were randomly sampled without replacement for 5 unique training and testing sets of combined RT and CT (80/20 split). Gradient boosting regression tree (GBRT) was used for machine learning analyses (https://scikit-learn.org/stable/modules/ensemble.html#gradient-tree-boosting). For each training/testing set split, the lambda parameter was tuned based on the training set only using 10-fold cross-validation. All correlation analyses with model predictions are based on testing set predicted values. Predictive performance was evaluated based on the Pearson correlation coefficient between the predicted values and actual values. The SHAP (SHapley Additive exPlanations) feature values provided multiple explanation for the models, and were calculated to evaluate the interpretation of top 20 metabolites contributed significantly to the predicted models. The Force plot algorithm was used to calculate the coefficients of potential markable contributors to predict VO2max or RQ. All these calculations and analyses were performed in Python using Scikit-learn database (https://scikit-learn.org).
DOI: 10.17632/j6xjfk3vcy
title: CHAT GPT: A GAME-CHANGER IN THE EDUCATIONAL SECTOR.

description: The emergence of Artificial Intelligence has led to a drastic change on how things are done in the world. It has even been projected that artificial intelligence will take over 85 percent of jobs. The transition to Artificial intelligence is inevitable and therefore, it is necessary for lawyers and clients alike to familiarise themselves with the operations of it. This Article seeks to highlight the benefits of ChatGPT as it relates to distance learning in Nigeria.
DOI: 10.6084/m9.figshare.23782893.v1
title: Dataset supporting the Burkina Faso refugees health needs study

description: Dataset from the Burkina Faso refugees health needs study,. Some identifying information has been redacted from this version of the dataset (e.g. community), and years of age has been recoded in age bands. This is an Excel file.
DOI: 10.17632/sz26wc9k7z
title: Teacher Retention Survey

description: Teacher Retention April 24, 2020 Topics: Teacher Perception, Teacher Retention, Teacher Dissatisfaction, Teacher Empowerment, Teaching Attitudes, Teacher Resilience To cement the reality that there are data-supported issues that exist beyond the teacher, which result in teacher attrition and dissatisfaction within the field of education, the following are a few statistics that have driven our resolve and fueled the need for solutions: “Roughly half a million US teachers leave the profession each year -- a turnover rate of over 20% [Alliance for Excellent Education, 2014]” (Aguilar, 2018). “Teacher attrition among first-year teachers has increased about 40% in the past two decades (Ingersoll, Merrill, and Stuckey, 2014). A range of factors , such as morale, accountability, expectations, and salaries, certainly contribute to the attrition problems, but stress and poor management of stressors are also rated as a top reason why teachers leave the profession (Carver-Thomas and Darling-Hammond, 2017)” (Aguilar, 2018). “The rate of attrition is roughly 50 percent higher in poor schools than in wealthier ones” (Alliance for Excellent Education). “This [teacher attrition] rate is much higher in urban areas, in secondary classrooms, and in hard-to-staff content areas such as special education, math, science, and foreign languages (Carver-Thomas and Darling-Hammond, 2017)” (Aguilar, 2018). “It is estimated that teacher turnover costs school districts upwards of $2.2 billion per year (Alliance for excellent education, 2014) and the cost of replacing a teacher in an urban district exceeds $20,000 per teacher (Carver-Thomas and Darling-Hammond, 2017). For site administrators, turnover rates may be comparable, particularly in urban areas, but the data is not systematically collected as it is for teacher attrition” (Aguilar, 2018). “Of the 3,377,900 public school teachers who were teaching during the 2011–12 school year, 84 percent remained at the same school ("stayers"), 8 percent moved to a different school ("movers"), and 8 percent left the profession ("leavers") during the following year” (National Center for Education Statistics, 2014). “Among public school teachers with 1–3 years of experience, 80 percent stayed in their base-year school, 13 percent moved to another school, and 7 percent left teaching in 2012–13” (National Center for Education Statistics, 2014). “Among public school teacher movers, 59 percent moved from one public school to another public school in the same district, 38 percent moved from one public school district to another public school district, and 3 percent moved from a public school to a private school between 2011–12 and 2012–13” (National Center for Education Statistics, 2014).
DOI: 10.17632/v9c5bsfz7t
title: Dataset for "Bidisperse micro fluidized beds: Effect of bed inclination on mixing"

description: Code to process images of a bidisperse micro fluidized bed to extract measures such as: mixing, granular temperature, bed height and particle velocity. Videos of selected cases that illustrate the observed phenomena. There is also the text files with data from all experiments that can be processed with the Jupyter Notebook to replicate the figures in the article. We present a few selected pictures of each experimental case as well.
DOI: 10.6084/m9.figshare.12720392.v1
title: A Gd@C82 single-molecule electret

description: <b>This is the data for "A Gd@C<sub>82</sub> single-molecule electret"</b>
DOI: 10.6084/m9.figshare.28734674.v1
title: <b>PREDICTION OF THE CHEMICAL COMPOSITION AND RUMINAL DEGRADABILITY OF </b><b><i>Urochloa</i></b><b>, </b><b><i>Megathyrsus</i></b><b>, AND </b><b><i>Pennisetum</i></b><b> GENUS FORAGES USING NEAR-INFRARED SPECTROSCOPY AND MULTIVARIATE REGRESSION</b>

description: Data DescriptionThis dataset contains the chemical composition and ruminal degradability data of tropical forages from the Urochloa, Megathyrsus, and Pennisetum genera, used to develop and evaluate predictive models based on near-infrared spectroscopy (NIR).The dataset includes:<b>Forage Samples:</b> A total of 291 forage samples were analyzed, distributed as follows:<i>Urochloa genus</i> (181 samples): Urochloa decumbens (n=56), Urochloa brizantha cv. Marandu (n=30), Urochloa hybrid cv. Mulato II (n=27), Urochloa hybrid cv. Sabiá (n=27), Urochloa ruziziensis cv. Ruziziensis (n=27), and Urochloa humidicola (n=14).<i>Megathyrsus maximus</i> (88 samples): Megathyrsus maximus cv. Mombaça (n=32), Megathyrsus maximus cv. Miyagui (n=28), Megathyrsus maximus cv. Massai (n=28).<i>Pennisetum purpureum Schum cv. Capiaçu</i> (22 samples).<b>Chemical Composition:</b> The chemical composition of the forages was determined using standard laboratory methods and includes variables such as:Dry Matter (DM)Organic Matter (OM)Crude Protein (CP)Neutral Detergent Fiber (NDF)Acid Detergent Fiber (ADF)Lignin (LIG)Ash content<b>Ruminal Degradability:</b> A subset of 32 forage samples was used to determine in situ ruminal degradation parameters, including:Degradation rate (k)Potential degradability (PD)Effective degradability (ED) at different rumen passage rates<b>Spectral Data:</b> NIR spectra were collected using a portable spectrophotometer (poliSPECNIR 900–1700 model, ITPhotonics S.r.l, Breganze, IT.) on dried and ground forage samples.The dataset supports the development of multivariate regression models to predict forage composition and ruminal degradability using NIR spectroscopy. It is intended for use in precision nutrition and rapid forage quality assessment in the field.
DOI: 10.17632/7zd2p5dhdf
title: Dataset of Business Simulation Games (BSGs) thematic categories from interviews

description: Contains the archive (RAR) of the dataset of thematic categories extracted from interviews with professors on the use of business simulation games (BSGs)
DOI: 10.6084/m9.figshare.28547021.v1
title: Supplementary File 3: 100taxa_test

description: Supplementary File 3: 100taxa_test
DOI: 10.17632/7hwj4bf7jm
title: Supplementary materials 1 and 2- An expert consensus-based checklist for quality appraisal of educational resources on First-Aid for Snakebites: a Delphi study

description: Supplementary Material 1. Baseline checklist for appraising educational resources on first aid for snakebites.
Supplementary Material 2. Final expert consensus-based checklist for appraising educational resources on first aid for snakebites.
DOI: 10.17632/b4n9vpxzcd
title: Data from: Spider webs capture environmental DNA from terrestrial vertebrates

description: eDNA sequence data obtained form spider webs, showing there ability to act as passive biofilters capturing eDNA from vertebrates present in the local environment. Raw sequencing results (fastq) and information for demultiplexing reads (.txt) to assess vertebrate DNA extracted from spiderwebs. Metadata from sample sites is also included for analysis.
DOI: 10.17632/w8yw2c92jg
title: Tany-Seq: Integrated Analysis of the Mouse Tanycyte Transcriptome

description: Abstract: The ability to maintain energy homeostasis is necessary for survival. Recently, an emerging role for ependymogial cells, which line the third ventricle in the hypothalamus in the regulation of energy homeostasis, has been appreciated. These cells are called tanycytes and are physically at the interface of brain communication with peripheral organs and have been proposed to mediate the transport of circulating hormones from the third ventricle into the parenchyma of the hypothalamus. Despite the important role tanycytes have been proposed to play in mediating communication from the periphery to the brain, we understand very little about the ontology and function of these cells due to their limited abundance and lack of ability to genetically target this cell population reliably. To overcome these hurdles, we integrated existing hypothalamic single cell RNA sequencing data, focusing on tanycytes, to allow for more in-depth characterization of tanycytic cell types and their putative functions. Overall, we expect this dataset to serve as a resource for the research community.
DOI: 10.17632/55jb65dx3p
title: RESinvANFIS v1.0 - A Versatile MATLAB Tool for Inverting Geoelectrical Resistivity Sounding Data using Neuro Fuzzy Technique

description: RESinvANFIS is a standalone application that provides the output subsurface layer model (e.g. True resistivity and Thickness). The software module runs in MATLAB 2012 or newer version installation. If MATLAB software is not available then install MCR (Matlab run time environment) installer to run the software for the system without MATLAB.
DOI: 10.17632/8nc275rmt3
title: Data for: Trade-off between the economic and ecological impact of different decarbonisation strategies for residential buildings

description: “E3 - A parametric model to evaluate trade-offs between the Energetic, Economic, and Environmental lifecycle performance of building projects” is a spreadsheet tool for the calculation of the environmental and economic lifecycle impact, as well as the Pareto optimal evaluation method, of strategies for residential buildings. Quantities of the building´s components (building geometry, materials or assembly types and their sizes, number of flats, number of tenants, and so on) are retrieved from technical plans. Calculation of quantities is performed according to the definitions described in DIN 277-1. Quantities and parameters for the building services components are determined by balancing all energy load (demand) profiles with energy generation profiles. Energy profiles are modelled in the E3 tool on an hourly basis (that is, using 8,790 points) for a typical year of operation. Energy load profiles determine the peak load for building services, which is used to determine each component´s required size. For photovoltaic cells and solar thermal collectors, peak load and size are constrained by the available surface. All other components can be modularly scaled to any size. Finally, energy generation profiles are used to determine primary energy use for building operation. Energy load profiles include heating energy demand, warm water demand, user power demand, and auxiliary power demand. Heating energy demand is calculated by assessing the thermal quality of the building envelope as a factor of temperature (W/K) over time (h). The thermal quality of the building envelope is found by balancing transmission losses through the building envelope and ventilation losses against solar thermal energy gains and internal heat gains. Energy generation profiles are modelled using factors to represent the efficiency of transforming a primary energy source (photons, solar thermal energy, gas, or grid power) in delivered energy (thermal energy or electricity).
DOI: 10.17632/bkym8ksp3h
title: Hyndai Car Dataset

description: Description:
The dataset contains information on 100 cars, with each row representing a single car. The data was generated to simulate various characteristics and maintenance aspects of cars, including engine temperature, brake pad thickness, tire pressure, maintenance type, and anomaly indication variables.

Variables:

Engine Temperature (Continuous):
Represents the temperature of the engine in degrees Celsius.
Values range from approximately 70 to 100 degrees Celsius.
Brake Pad Thickness (Continuous):
Indicates the thickness of brake pads in millimeters.
Values range from approximately 5 to 15 millimeters.
Tire Pressure (Continuous):
Represents the pressure of tires in pounds per square inch (PSI).
Values range from approximately 28 to 36 PSI.
Maintenance Type (Categorical):
Indicates the type of maintenance performed on the car.
Categories include "routine maintenance," "component replacement," and "repair."
Anomaly Indication (Binary):
Indicates the presence or absence of anomalies detected in sensor readings.
Binary variable where 0 represents the absence of anomalies, and 1 represents the presence of anomalies.
Usage:

This dataset can be used for various analytical purposes, including exploratory data analysis, predictive modeling, and anomaly detection.
Researchers and analysts can analyze the relationships between different variables to identify patterns and insights related to car maintenance and performance.
Machine learning models can be trained using this data to predict maintenance requirements, detect anomalies in sensor readings, or optimize maintenance schedules for improved efficiency and cost-effectiveness.
DOI: 10.17632/gbvh8rjwhc
title: Prevalence of Ankle-foot pain and associated factors among medical and physiotherapy students in MM(DU) Mullana, Haryana, India

description: Ankle-foot pain a common musculoskeletal problem that affects people of any age, including health care providers like medical and physiotherapy students. Due to the nature of the careers, they have, require lengthy standing, prolonged walking, long hours of posting, and low shoe comfort, these people are more likely to get ankle-foot pain. Ankle-foot pain may have a major impact on a person's quality of life and may make it difficult for them to carry out daily tasks, including studies.
DOI: 10.17632/gy7gwk98bx
title: Data for: Measurement of methane solubility in pure water in equilibrium with hydrate by using high–pressure optical capillary cell
DOI: 10.17632/phytb2kc4s
title: Excel SAMR and Creativity (Fluency)

description: Excel data from SAMR and creativity (fluency). data obtained from 175 students. collected using a questionnaire and observation
DOI: 10.6084/m9.figshare.3517220.v1
title: Appendix A. Calculations, assumptions, and values used to determine stocks and fluxes of phosphorus in Phoenix, Arizona, USA.

description: Calculations, assumptions, and values used to determine stocks and fluxes of phosphorus in Phoenix, Arizona, USA.
DOI: 10.6084/m9.figshare.6890945.v3
title: Earth Analytics Bootcamp | Numpy Arrays Teaching Subset

description: This is a teaching data subset that contains data for monthly precipitation (inches) for Boulder, CO. Data included:<br>1. Average monthly precipitation (inches) derived from monthly precipitation between 1971 and 2000 (avg-monthly-precip.txt): 12 records/rows representing one value for each month from January through December<br>2. Total monthly precipitation (inches) for 2002 and 2013 (monthly-precip-2002-2013.csv): 2 rows (one for 2002 followed by one for 2013) and 12 columns (one for each month from January through December). <br>3. List of month names (months.txt).<br>Source: NOAA.
DOI: 10.17632/2z97z3bcw6
title: Untargeted lipidomics of corona plasma samples

description: Untargeted lipidomics of corona plasma samples
DOI: 10.6084/m9.figshare.27080566.v2
title: CCLMoff: A CRISPR/Cas9 System Off-target Prediction Tool Using Language Model

description: We incorporated 13 genome-wide deep sequencing techniques, including GUIDE-seq, CIRCLE-seq, SITE-seq, DISCOVER-seq, DISCOVER-seq+, CHANGE-seq, Digenome-seq, DIG-seq, HT-GTS, IDLV and BLESS to construct a comprehensive off-target dataset.
DOI: 10.17632/z676zksb96
title: Underinvestment and Capital Misallocation Under Sovereign Risk

description: Replication materials for "Underinvestment and Capital Misallocation Under Sovereign Risk" by Carlos Esquivel.
DOI: 10.6084/m9.figshare.25200956.v1
title: Raw Data - Martial Arts Schools.xlsx

description: The raw data for a research article entitled "Indonesian Martial Artists’ Preferences in Martial Arts Schools: Sustaining Business Competitiveness through Conjoint Analysis"
DOI: 10.6084/m9.figshare.9633104.v1
title: data for A prospective, randomized, double-blind trial to compare body weight-adjusted and fixed doses of palonosetron for preventing postoperative nausea and vomiting in obese female patients

description: the file has the demographic data, patient´s ASA status and associated diseases and the incidence of nausea, vomiting postoperative.
DOI: 10.17632/mn5f2cfphr
title: An updated Axiom buffalo genotyping array map and mapping of cattle quantitative trait loci to the new water buffalo reference genome assembly - Supplementary material

description: Supplementary material from the paper "An updated Axiom buffalo genotyping array map and mapping of cattle quantitative trait loci to the new water buffalo reference genome assembly" accepted by Animal Genetics. SUMMARY - The objectives of this study were to provide the buffalo research community with an updated SNP map for the Axiom Buffalo Genotyping (ABG) array with genomic positions for SNP currently unmapped and to map all cattle QTL from the CattleQTLdb onto the buffalo reference assembly. To update the ABG array map, all SNP probe sequences from the ABG array were re‐aligned against the UOA_WB_1 assembly. With the new map, the number of mapped markers increased by approximately 10% and went from 106 778 to 116 708, which reduced the average marker spacing by approximately 2 kb. A comparison of results between signatures of autozygosity study using the ABG and the new map showed that, when the additional markers were used there was an increase in the autozygosity peaks and additional peaks in BBU5 and BBU11 could be identified. After sequence alignment and quality control, 64 650 (UMD3.1) and 76 530 (ARS_UCD1.2) cattle QTL were mapped onto the buffalo genome. The mapping of the bovine QTL database onto the buffalo genome should be useful for genome‐wide association studies in buffalo and, given the high homology between the two species, the positions of cattle QTL on the buffalo genome can serve as a stepping stone towards a water buffalo QTL database.