cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/j7648r5v9r.3
title: Dataset of medicinal plants used by traditional medicine practitioners to treat malaria and HIV/AIDS in the districts of Meconta, Murrupula, and Ribaue, northern Mozambique

description: The folder named Database-Ethnopharmacological study-Nampula Province-MOZAMBIQUE contains 8 files from three districts, and 3 folders (each one with particular data). The files named 1-Demographic data AND Perceptions about Malaria-Meconta, Murrupula, and Ribaue District,2022-2023 and 2-Demographic data AND Perceptions about HIVAIDS-Meconta, Murrupula, and Ribaue District,2022-2023 contain socio-demographic details of the traditional medicine practitioners and their perceptions about malaria and HIV/AIDS such as their age, gender, marital status, level of education, ethnicity, years of experience, area of study, type of disease, causes, symptons and signs, respectively. The file named 3-Medicinal plants-malaria AND HIV-Meconta, Murrupula, and Ribaue district-2022-2023 contains information about medicinal plants used to treat malaria and HIV/AIDS such as their family, scientific name, local name, area of collection, therapeutic indication, the parts of the plant used to prepare the remedies, mode of preparation, dosage, mode of administration, adverse effect, other traditional use, mixed plants to prepare the remedies and their frequency of citation. The file named 4-Medicinal plant and RFC, FL, UV and ICF-Meconta, Murrupula and Ribaue contains medicinal plants used by traditional medicine practitioners to treat Malaria and HIV/AIDS and their relative frequency of citation (RFC), fidelity level (FL), Use Value (UV) and Informant Consensus Factory (ICF). And, there is a consent form, a questionnaire, a Visual-abstract-2024, and a figure from the study area. And, some files have their respective English version and Portuguese version. The folder named 1-Dataset-Meconta district-2022 contains 4 files of data from Meconta district. The folders 2-Dataset-Murrupula district-2023 and 3-Dataset-Ribaue district-2023 contain 3 files per folder from Murrupula and Ribaue districts.
DOI: 10.17632/8jsxnwvbhp.5
title: Supplemental Material for manuscript named "Genetic Analysis and Quantitative Trait Loci Detection of Udder Traits in Jersey Cattle"

description: Supplementary Materials-Figure S1, Figure S2, Table S1, and Table S2 for manuscript named "Comprehensive Genetic Analysis and Quantitative Trait Loci Detection of Udder Traits in Jersey Cattle"
DOI: 10.17632/ggbkd8ck3x.1
title: E-Commerce Dataset

description: This dataset contains 100,000 records of customer orders from a large e-commerce retailer in South Asia. There are six columns - rec_id, order_id, order_date, shipped_at, prod_sku, and prod_qty in the dataset. The first two columns, "rec_id" and "order_id" provide unique identifiers of the record and the customer order, respectively. Columns "order_date" and "shipped_at" give the time and date of the order generation (by the customer) and order shipping from the fulfillment center, respectively. Columns "prod_sku" and "prod_qty" capture the requested SKU (product type or item class) and the corresponding quantity required to fulfill the customer order. We use this dataset to gain insights into the distribution of customer orders in a typical e-commerce fulfillment center. We classify orders into two categories: single-line and multi-line orders. A single-line order is defined as a customer order which requires exactly one SKU, while a multi-line order requires more than one SKU. We conclude from this dataset that single-line orders often dominate e-commerce fulfillment requests.
DOI: 10.17632/7ppcf7cs27.1
title: Exploring Phononic Properties of Two-Dimensional Materials using Machine Learning Interatomic Potentials

description: In this manual we provide a guide on the practical implementation and reproduction of the results presented in our publication entitled: "Exploring Phononic Properties of Two-Dimensional Materials using Machine Learning Interatomic Potentials". We specifically discuss the repository https://gitlab.com/ivannovikov/mlip_phonopy with the MLIP_PHONOPY code—a C++ interface between the MLIP code and the PHONOPY software—which allows one to calculate phonon spectra, group velocities, thermal properties, etc., of a two-dimensional material. Along with the repository description, this manual contains an instruction on quick installation of the stable branch of the MLIP code, a description of VASP input files for ab initio molecular dynamics (AIMD) calculations (namely, the folders Structures and VASP-inputs) and training set preparation, an instruction on passive training of MomentTensor Potentials (MTPs) using the MLIP code. Finaly, we describe the folders Untrained-MTPs and Exampleswith the additional files available here: http://dx.doi.org/10.17632/7ppcf7cs27.1.
DOI: 10.17632/k55b8mvs84.1
title: Dataset of Vis-NIR spectra for intact cucurbitaceae fruits

description: This dataset contains spectroscopic data (Raw Spectrum) obtained for a total of 300 samples from 6 commodities. Data are available as XLS and UNSB file extension formats.
DOI: 10.17632/85vrrttt4y.1
title: LGR-1 pretreatment and autism-like behaviors

description: This is an updated version of raw data in the related manuscript.
DOI: 10.17632/jwch9gpc3c.1
title: The dataset for validation of TPACK framework in affecting teachers' ICT integration: Malaysian context

description: This dataset describes the technological pedagogical and content knowledge (TPACK) framework that may affect teachers’ ICT integration. Primary data is retrieved from 292 Malaysian teachers. The data was examined mainly through the procedures of content validity ratio (CVR) and confirmatory composite analysis (CCA).
DOI: 10.17632/6kstf78rvt.1
title: Fast, Personal, and AI-Powered: The Future of Customer Experience

description: This research provides valuable insights into customer preferences for live chat support within the SaaS sector, revealing key areas for improvement and potential strategies for enhancing customer satisfaction. By leveraging the data collected, businesses can make informed decisions about their customer support approaches, ultimately leading to improved user experiences and greater customer loyalty.
DOI: 10.17632/cdfbftykp7.2
title: Dataset Measuring organizational culture, motivation, and interpersonal communication based on the multicultural teacher performance

description: In the datasets, the scale of organizational culture based on eleven items of primary cultural values (PCV) and nine items of secondary cultural values (SCV). Work motivation variables in the datasets used four items of motive motivation (MM), seven items of expectation motivation (ME), and with nine items of incentive motivation (IM). Interpersonal communication variables were seven items of social sensitivity (SS), nine items of social insight (SI), and four items of social communication skills (SCM). The items, including labels and ratings, will be explained later, with more comprehensive details as supplementary material (see "Annotated Questionnaire" in supplementary material). This was because each item had different rankings and choices. To measure teacher performance used three scales from the book of effective teacher performance. The teacher performance scale used three variables of thirteen items of the learning process (LL), four items of scientific work (SW), and three items of service (S).
DOI: 10.15468/dl.gf8jf9
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ahmosia galbinea Heinrich, 1926"
 ]
}

 The dataset includes 20 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009336-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/ph47c6gcpx.1
title: Examining Business Cycles and Optimal Monetary Policy in a Regional DSGE Model

description: The Replication file includes the data used for the model, the code to estimate the regional model and code to replicate the figures and tables of the published paper, abstract below. 

I construct a dynamic stochastic general equilibrium (DSGE) model consisting of geographic regions and use state level data to estimate the effects that monetary policy and financial shocks have on the four census regions of the United States. The DSGE model I use is constructed around a centralized monetary authority and financial market with regional output, labor and investment markets. I find significant heterogeneity amongst the regional structural parameters of the model, creating different business cycle dynamics for the four regions. The estimated model aligns with other economic studies that suggest that monetary shocks have a greater impact in certain geographic regions in terms of employment, inflation, wages, and consumption. Simulating the estimated model, I find that monetary policy that considers the regional variation in output and inflation can significantly lower the volatility around national output and inflation. The paper’s results suggest that regional macroeconomic conditions should be considered in monetary policy decisions.
DOI: 10.17632/6fjdddntkg.1
title: Data for: The propulsion mechanism and tiny particles removal investigation based on the “micro-gun” propulsion system

description: Removal of microsphere particles from the surface of the substrate by the directional shockwave induced by the laser pulse emitted from the “micro-gun” propulsion system tip
DOI: 10.15468/dl.a3jvtb
title: Occurrence Download

description: A dataset containing 1759 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Panthera onca (Linnaeus, 1758)"
 ]
}

 The dataset includes 1759 records from 66 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009335-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/crjv374mn7.1
title: Comparative analysis of hydrosols volatile components of Citrus aurantium 'Daidai' and Citrus aurantium L. dried buds with different extraction processes on HS-SPME-GC-MS

description: In order to provide theoretical support for the in-depth exploration of the basis of medicine and food homology properties of CAVA, and to improve the utilization rate of waste resources, CAVA and CADB were carried out in two pre-treatment methods, namely, immersion and ultrasonic-microwave synergy, and were extracted by steam distillation to collect the hydrosol. The volatile components in the hydrosol were enriched and characterized by HS-SPME-GC-MS, with a view to filling the gaps in the relevant research, enhancing the utilization of resources, reducing the wastage of resources, and ultimately laying theoretical foundations for the deep and intensive processing of hydrosols.
The experimental materials were harvested on April 20, 2022 from the Citrus aurantium L. planting base of Sichuan Shugeng Agricultural Development Co., Ltd. in Sanbanqiao village, Guanyinqiao town, Linshui county, Guang'an city, Sichuan province. It was identified by associate researcher Zhou Xianjian of the Sichuan Academy of Traditional Chinese Medicine as the dried flower buds of Citrus aurantium L., a citrus plant of the rutaceae family, and its variant Citrus aurantium 'Daidai'.
DOI: 10.17632/sdxrxf68jg.1
title: Shifted hopscotch numerical experiments

description: Title of the submitted paper: "New stable, explicit, shifted-hopscotch algorithms for the heat equation" Subsection 3.2 a moderately stiff system and Subsection 3.3, a very stiff system.
DOI: 10.17632/kzyfgkz8xw.1
title: Performance Evaluation In Internet Of Things Dataset Using Machine

description: Many Internet of Things (IoT) applications face significant hurdles in terms of data
security. Machine Learning (ML)-based intrusion detection systems (IDS) claim to be effective
and accurate at analysing network data and detecting threats. Our suggested technique, nweighted-univariate feature selection, creates a threshold value that serves as a weight, from
which critical features are extracted and then used to machine learning algorithms like support
vector machine (SVM) and decision tree (DT). These models were trained using the UNSWNB-
15 dataset, which was developed in the Australian Center for Cyber Security's Cyber Range Lab
using an IXIA PerfectStrom tool (ACCS). It has a mix of realistic modern normal and
contemporary network traffic assault characteristics. Accuracy, precision, and recall were used to
evaluate the performance of our suggested model. In DT, the proposed model has a greater
accuracy of 96.4 than SVM, which has an accuracy of 89.1.
DOI: 10.15468/dl.u33r88
title: Occurrence Download

description: A dataset containing 72 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Kuruna Attigala, Kaththr. & L.G.Clark"
 ]
}

 The dataset includes 72 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009337-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/jh4wt3wbbw.1
title: Data for: Landslide mobilization rates: a global analysis and model

description: Compiled dataset of observed landslide mobilization rates (LMR, [m³/km/y]) and map of the predicted global patterns of LMR (GeoTiff Format). Details on the procedures used are discussed in the paper.
DOI: 10.17632/mbv3bx847g.3
title: Dataset on broadband Electrochemical Impedance Spectroscopy of Lithium-Ion Batteries for Different Values of the State of Charge

description: The Electrochemical impedance spectroscopy (EIS) were measured on four brand new Samsung cylindrical  ICR18650-26J rechargeable  lithium-Ion batteries at SoC 100%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, and 10%.  The measurements were repeated six times for each battery. Measurements on other batteries will be added to the dataset when available.
Please note that the measurements in the present dataset are NOT included in the previous (linked) dataset from the same authors.

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

IMPEDANCE.CSV FILE
------------------------

MEASURE_ID: the unique identification code of each EIS measurement 
SOC: state of charge of the battery
BATTERY_ID: the unique identification code of the battery 
FREQUENCY_ID: frequency id. Lookup into the frequencies.csv file to get the value in Hertz
IMPEDANCE_VALUE: measured complex impedance value in Ohm in the format:  (Re{Z}+Im{Z}j)

6  measurements x 4 batteries x 10 SOC  x 14 fequencies = 3360 impedance values (rows)

FREQUENCIES.CSV FILE
---------------------------

FREQUENCY_ID: frequency identification code
FREQUENCY_VALUE: frequency value in Hertz
DOI: 10.17632/pvtjfmmm3j.1
title: Effect of footcore exercises on navicular drop and plantar pressure distribution in asymptomatic individual with flatfoot

description: This study is RCT in which 10 asymptomatic flatfoot individual was recruited . The group is divided into two groups i.e., experimental group and control group . Footcore exercises protocol was made and given to experimental group and conventional therapy was given to control group.
DOI: 10.17632/vbgywdcdjp.1
title: Supplementary Data for "Machine Learning-informed Ensemble Framework for Evaluating Shale Gas Production Potential: Case Study in the Marcellus Shale"
DOI: 10.17632/x5pj7zdnxs.2
title: Data Set: Improving Access to Cognitive Behavioural Therapy Groups for Postnatal Women following Partnership Work: A Service Evaluation

description: Data set from service evaluation
DOI: 10.17632/ys7pxfx2pr.1
title: Dataset for estimating the sharing economy impact on enterprises’ value

description: The dataset responds to the growing concern of the researchers worldwide about the phenomenon of sharing economy and approaches to formalized evaluation of its impact. It contains time series of the existing sharing economy indices (STOXX Global sharing economy indices, Solactive Sharing Economy Index and INDXX US Sharing Economy Index) that are contrasted to the World’s major stock indices selected discretionarily. The three-step procedure was taken to obtain the data: indices selection, data arrangement, retriever algorithm design and implementation. The data are arranged in different spreadsheets to harmonize the countries’ trading calendar mismatch. The spreadsheets have uniform design to allow data aggregation and to increase usability. Together with the data we provide the adjustable retriever code to enable customization of the set of indices and the length of their time series. The data is provided in the two MS Excel spreadsheets: “EOM data”, “EOD data”. The “EOM” files contain end-of-month closing values of indices (the last trading day of a month), the “EOD” – end of a trading day closing values respectively. Each spreadsheet contains 13 tabs. Three tabs are delegated for composite sharing economies indices, all the rest are for the national indices. Tab 1 “Sharing STOXX” contains values of the following STOXX indices, related to the sharing economy or to the overall market performance: STOXX Global Sharing Economy Price USD Index; STOXX Global Sharing Economy Price EUR Index; STOXX Global Sharing Economy Drivers Price USD Index; STOXX Global Sharing Economy Drivers Price JPY Index; STOXX Global Sharing Economy Drivers Price EUR Index; STOXX Europe 600 EUR Price Index; EURO STOXX 50 EUR Price Index. Tab 2 “Sharing SOLACTIVE” contains values of the Solactive Sharing Economy (Total Return) Index. Tab 3 “Sharing Indxx” contains values of the INDXX US Sharing Economy Index. Tabs 4-13 contain selected national indices of the following countries: the USA (US), Germany (DE), France (FR), the United Kingdom (UK), Russia (RU) broad market and Russia specific market segments, Honk-Kong (HK), Japan (JP), the Netherlands (NED), Switzerland (CH). The data can be used to analyze patterns of value dynamics of specific enterprises – the sharing economy drivers and beneficiaries compared to the broad market. The dataset can be instrumental in country-specific research to draft a strategy and design, to formulate and test hypotheses with subsequent adjustments to the data if the ideas show proper evidence of plausibility.
DOI: 10.17632/dn4pxx6b3m.1
title: FEM simulation results

description: The dataset contains the relative frequency shift values for the first eight weak-axis bending vibration modes obtained by simulation using Ansys, for a cantilever beam with the following dimensions: length 1000 mm, width 50 mm, and thickness 5 mm. The elements are hexahedral and have a 1 mm maximum edge size. The beam is fixed at the left end.
DOI: 10.17632/prvx2pmxy6.2
title: Data about Financial Literacy, Financial Constraints and Technological Innovation on SMEs

description: These data were obtained from a questionnaire regarding the relationship between CEO's financial literacy, firm's allevion of financial constraints, and firm's technological innovation outcomes, as well as the firm's financial statements. We controlled for CEO's risk orientation; firm's age, size (employees), industry (2-digit NACE code), ROA (EBIT/Total Assets), and leverage (Total Debt / Total Assets); as well as CEO's age, gender and education level. Questions: Please rate from 1 (absolutely disagree) to 5 (absolute agree) the following sentences: V Description fl1 I and the rest of the TMT have updated information regarding economic and financial industry data fl2 I am well informed about the economy evolution and of the national and international monetary and financial policies fl3 I am well informed about alternative financial sources (equity loans, venture capital, MAB, business angels, etc.) rather than bank financing fl4 I am well informed about the financial assets in which I can invest financial slack fl5 I and the rest of the TMT use economic and financial information in the decision-making fl6 The training of the administration and finance department staff is very relevant for establishing effective financial policies Please rate from 1 (very bad) to 5 (very good) the evolution during the last 2 years regarding: afc1 the indebtedness offered to the firm afc2 the costs and commissions required afc3 the guarantees needed afc4 the interest rate afc5 the time-lapse response of the financial institution afc6 the debt maturity Please rate from 1(very bad) to 5 (very good) the evolution of your company related to the competitors during the last 2 years regarding: ips1 the number of new products or services introduced by your company per year ips2 the pioneering character of your company when introducing new products or services ips3 the speed in response to the introduction of new products or services by other companies in the industry ipp1 the number of changes in the processes introduced by your company per year ipp2 the pioneering character of your company when introducing new processes ipp3 the speed in response to the introduction of new processes by other companies in the industry Control variables Please rate from 1 (absolutely disagree) to 5 (absolute agree) the following sentences: ro1 I have a strong propensity to projects with high risk ro2 I believe that understanding brave far-reaching environment actions is necessary to reach the companies objectives ro3 When I make decisions under uncertainty conditions I usually adopt a strong and aggressive position to maximize the probability of exploiting the potential opportunities Other type of data: cv2 Firm age* cv3 Firm size* cv4 Industry: 2-digits NACE code* cv5 ROA (EBIT / Total Assets)* cv6 Leverage (Total Debt / Total Assets)* cv7 CEO Age cv8 CEO gender cv9 CEO education *: Data obtained from Financial Statements and other information publicly available.
DOI: 10.17632/6p5y7rgzjz.1
title: Gearbox Dateset for Transfer Learning Fault Diagnosis

description: This dataset is for the paper "Domain Adaptation with Multilayer Adversarial Learning for Fault Diagnosis of Gearbox under Multiple Operating Conditions", one can find the code on GitHub: https://github.com/mingzhangPHD/Transfer-Learning-for-Fault-Diagnosis/tree/master/MAAN