cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/7vdnrdbdj9.1
title: Replication data for Imports and the CO2 Emissions of Firms

description: This repository contains replication material for the paper Imports and the CO2 Emissions of Firms in Journal of International Economics.

Upon opening the zip file Replication.zip, please follow the instructions in Readme.rdf.
DOI: 10.17632/ywsxzx5v88.1
title: Banana Project Dataset

description: Dataset used for the Banana Grading System Project.
DOI: 10.17632/cwjw9jc8dt.1
title: Relationships between student cognitive engagement and their academic achievement

description: This is the raw data collected from students in junior secondary school in China 1) To investigate whether cognitive engagement predicts student academic achievement; 2) To investigate whether student gender has the moderating role on the relationship between cognitive engagement and academic achievement. In the Excel sheet it shows the demographic Information of participants, and the items related to cognitive engagement and student academic achievement. The first 3 items are the demographic information including student gender, Grade, and age. The following four items(1,2,3,4) are for measuring cognitive engagement, and student academic achievement was measured by the examination scores which showed the fifth item(5) in this data. All the raw data was collected face to face, after the screening, the researcher entered the data into the Excel sheet for analysis.
DOI: 10.17632/4prc7fy4zm.1
title: Raw mass spectrometry data files of lipidomics and oxo-lipidomics.

description: Raw mass spectrometry data files of lipidomics and oxo-lipidomics in <7-Dehydrocholesterol dictates ferroptosis sensitivity and surveillance.>
DOI: 10.17632/jx5tddtcs6.1
title: Health Insurance Dataset

description: This dataset contains information about more than 1300 beneficiaries
DOI: 10.17632/ckhp24wpx3.1
title: A new theoretical finding relating subatomic particles' mass to the square of the magnetic flux quantum provides a new interpretation for mass.

description: The motivation for investigating the issues presented in this article stemmed from a need to understand better the relationship in long-established physics formulas and extract the information they provided using conventional methods. Based on the definition of magnetic flux quantization, which is based on a combination of fundamental physical constants, the Planck constant, and the particle’s elementary charge, this work explores the results that arise when this equation is combined with the equation of the Bohr-level electrostatic force acting on the electron, which leads to a new mathematical relationship between the combined expressions. The new relationship yields novel theoretical findings related to the known universal constants. Following this insight, the formalism developed in this paper indicates that the mass of the electron and other subatomic particles is associated with the magnitude of the square of the magnetic flux quantum, which makes up the particle. This conclusion is not as strange as it may seem, as the square of the magnetic flux quantum appears in the context of magnetic energy in a current loop and, according to Einstein’s special theory of relativity, energy is equivalent to mass. The theoretical results are in full accordance with experimental results published by NIST CODATA 2018 that I’ve used, which validates the existence of the relationship. The distinction between gravitational and inertial mass, which are ultimately equivalent, indicates that the relationship between the particle’s mass and the square of the magnetic flux quantum is another aspect of mass originating from the particle’s interaction with the Higgs field.
DOI: 10.17632/v7ndvxcjj5.1
title: Data for: Effect of bitumen properties in the induction healing capacity of asphalt mixes

description: Results of thermal properties of 5 binders used in the present investigation
DOI: 10.17632/xrk5rfcpvg.2
title: A soil moisture dataset over the Brazilian semiarid region

description: This dataset contains soil moisture measured over the Brazilian Semiarid region from August 2015 to April 2019. An observational network of automatic ground stations was established by the National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN) with the aim of supporting monitoring activities over the driest and most drought-affected region in the country. The sites are mostly characterised by family farming and rainfed agriculture. Soil volumetric water content is obtained by measuring the dielectric constant of the soil at 70 MHz frequency, which minimizes salinity and textural effects (model EC-5, Decagon Devices, Pullman, WA, USA). Probes use the default calibration, resulting in a precision of approximately ±0.03 m3 m-3. Measurements were made hourly at 0.1 m and 0.2 m depths; a subset of stations (10% of the original network, evenly distributed) had measurements at 0.1 m, 0.2 m, 0.3 m, and 0.4 m depths. Rainfall measurements are also included in this version of the dataset. Measurements were accumulated hourly. A total of 360 stations were selected after a quality control process. Data availability is approximately 2 years long on average, reaching up to 4 years in some stations. Gaps caused by instrument malfunction or data transmission problems are occasional on the data. Validation and consistency were assessed by comparing trends in soil vertical neighbour data and rainfall records collected by each station. Stations with at least two months of soil moisture data were kept on the database. Each file available here contains the time series and the metadata with information on the city, the Brazilian state, the geographic coordinates, and the soil texture (fraction of sand, silt and clay). Soil information was derived from 1 kg disturbed samples collected at each site. Data for individual stations are in the compressed file PCDs_.zip while a list summarising stations information is found in the file _Stations.xlsx. First applications of this dataset and further details on methodology and site can be found in Zeri et al. (2018, https://doi.org/10.3390/w10101421). Version 2 of the dataset includes rainfall measurements, 3 new stations, and the inclusion of records incorrectly removed during the quality control of version 1.
DOI: 10.17632/zfcd4bny82.1
title: Dataset of Indian face images with various expressions

description: Fast and precise human emotion classification and detection is a quality parameter in various industries and research areas. This is a continuously evolving research area that consistently garners attention from researchers. Machine Learning (ML), deep learning, and Artificial Intelligence (AI) methods have demonstrated considerable potential in solving classification and object detection challenges. A pristine and well-curated dataset stands as the fundamental prerequisite for constructing precise and resilient ML and AI models suitable for real-time applications. With this objective in mind, compiled an image dataset consisting of Indian facial expressions with Happiness, Thoughtfulness, Anger, Surprise, Sadness, Fear, and Excited and these facial expressions are captured in three directions front, left side, and right side. The dataset has been segregated into six folders: 1) Happiness 2) Thoughtfulness 3) Anger 4) Surprise 5) Sadness 6) Fear 7) Excited. The dataset comprises over 6,000+ images in raw format. We believe that this raw dataset will significantly aid in training, testing, and validating machine learning models for facial expression classification or recognition.
DOI: 10.17632/235y5c368v.1
title: RSD2013_v3/SiMTra_v2.2 - Simulation files of the examples in 'Modeling reactive magnetron sputtering: Opportunities and challenges'

description: A set of input files for the simulation software RSD2013 v3 and SiMTra v2.2 which generate the data used for the figures in the paper 'Modeling reactive magnetron sputtering: opportunities and challenges', published in Thin Solid Films (Elsevier) DOI:10.1016/j.tsf.2019.05.045. Also the set of experimental data for the current-voltage-pressure curves are included. Four examples are illustrated by simulation: 1) Redeposition of sputtered atoms - (SiMTra) Figure 1: Influence of working (Ar) pressure and the sputtered element (Li, Al, Ti, Y, Ta) on the fraction of sputtered material redeposited on the target. - (RSD/SiMTra) Figure 2a: Hysteresis behaviour of reactive pressure afo reactive flow, varying the redeposition fraction of the sputtered material Al. - (RSD/SiMTra) Figure 2b: Comparison of the critical points behaviour afo the redeposition fraction with a reduction of the sputter yield. 2) IV-characteristics - (RSD/SiMTra) Figure 3a: IV-characteristic of a simplified Ti/O2 system (only one oxidation state). - (RSD/SiMTra) Figure 3a: IV-characteristic of an Al/O2 system. - (Experimental) Figure 4: Experimental IVP-characteristics fo an Al/O2 system. 3) Sample rotation - (RSD/SiMTra) Figure 6a: Behaviour of the critical points afo the rotation speed of a substrate plate. - (RSD/SiMTra) Figure 6b: Time evolution of the reactive gas pressure for two rotation speeds of the substrate plate. 4) Pulsing discharge current - (RSD/SiMTra) Figure 7a: Behaviour of the critical points afo the pulsing frequency of the current. - (RSD/SiMTra) Figure 7b: Time evolution of the target state by pulsing the current.
DOI: 10.17632/dzkkv87njb.1
title: Data for: Equivalent Circuit Model Recognition of Electrochemical Impedance Spectroscopy via Machine Learning

description: 1. EIS-Data.csv: The original EIS is extracted from the literature and discretized into readable data points. All these EIS come from electrochemical energy storage devices, especially lithium-ion batteries and supercapacitors. 2. Test-Data-Prob.csv: The probability for each model type samples in test data.
DOI: 10.17632/5bdc36jmdd.1
title: water, sanitation and hygiene among families living in semi urban part of metro city from south India

description: these data show the analysis and development of this study
DOI: 10.17632/t88jjxkkkp.1
title: Infantile masturbation in a Nigerian child (video clips)

description: Video clips of a 1 year old female Nigerian child who presented with a month history of abnormal body movements characterised by intermittent rocking or thrusting of the pelvis which usually aborts with distraction. She was initially diagnosed with seizure disorder which was changed to INFANTILE MASTURBATION (GRATIFICATION DISORDER) after reviewing a video clip of the episodes. It resolved with simple behavioural therapy entailing the parents consistently distracting the child during the episodes (video were provided by parents and shared with their permission for publication/educational purposes).
DOI: 10.17632/2gkg7vvcrm.1
title: A Brazilian dataset for screening the risk of the Chronic Kidney Disease

description: We collected the medical data (60 real-world medical records) from physical medical records of adult subjects (age ≥ 18) under the treatment of University Hospital Prof. Alberto Antunes of the UFAL, Brazil. The data collection was approved by the Brazilian ethics committee of the Federal University of Alagoas, approval number 47350313.9.0000.5013. The 60 real-world medical records are related to the four risk classes: low risk (30 records), moderate risk (11 records), high risk (16 records), and very high risk (3 records). An experienced nephrologist, with more than 30 years of CKD treatment and diagnosis in Brazil, labeled the risk classification based on the KDIGO guideline. We only translated the dataset to English and converted the gender of subjects from string to a binary representation to enable the usage of the J48 decision tree classifier. We augmented the dataset to decrease the impact of imbalanced data and improve the data analysis (more 54 records) by duplicating real-world medical records and carefully modifying the attributes, i.e., increasing each CKD biomarker by 0.5. We selected the constant 0.5 with no other purpose than differ the instances and maintain the new one with the same label as the original. The augmented data was also reviewed by the experienced nephrologist to increase confidence in the data augmentation. The dataset does not contain duplicated and missing values. Therefore, we provide two datasets: original and augmented.
DOI: 10.17632/d5gxv5tc8b.2
title: Moral Preferences of Investors : Experimental Evidence -- Replication Package

description: This package allows to replicate the results of "The Moral Preferences of Investors: Experimental Evidence", by Bonnefon, Landier, Sastry and Thesmar. 
It contains codes and experimental data. Please read the readme file in the root of the folder for details.
DOI: 10.17632/z7swdm243y.1
title: ReconGPT

description: Supplemental data for methodology and test set of ReconGPT
DOI: 10.17632/t7cj26kzxf.1
title: Chemoprevention of cutaneous squamous cell carcinoma and its precursors in solid organ transplant recipients using topical sirolimus: a randomized, double-blind, placebo-controlled pilot trial - Supplementary materials

description: The files below contain the supplemental methods outlining ethics statement, study design & intervention, outcome measures, and statistical analysis. The results for recruitment, compliance, and rention as well as the safety of topical sirolimus in solid organ transplant patients (SOTRs) are also included.

Immunosuppression in solid organ transplant recipients (SOTR) greatly increases the risk of keratinocyte cancer (KC), indisputably a significant burden in terms of morbidity, mortality and cost. Switching calcineurin inhibitors to sirolimus is a major strategy that has resulted in a two-fold reduction in the risk of SCC, but is poorly tolerated with many serious adverse events 1, 2. 
To circumvent these, we explored whether topical sirolimus applied topically could safely reduce the incidence of KC in the field of cancerisation in a randomized, double-blind, placebo-controlled, single-arm trial whereby patients received intervention on the dorsum of one hand and forearm and placebo on the dorsum of the contralateral hand and forearm chosen randomly. 
At 12 weeks, the number of keratotic lesions was reduced in each patient by 31+/-5% (from an average of 9.7 to 7.9, p=0.0001) in the treated side whereas it increased marginally on the vehicle side (6+/-6%, p=0.0006).
DOI: 10.15468/dl.htxa42
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Karenia brevis (C.C.Davis) G.Hansen & Ø.Moestrup, 2000"
 ]
}

 The dataset's 1 records were derived from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009203-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/8pz43nvvxh.3
title: MHCflurry: open-source class I MHC binding affinity prediction

description: Predicting the binding affinity of major histocompatibility complex I (MHC I) proteins and their peptide ligands is important for vaccine design. We introduce an open-source package for MHC I binding prediction, MHCflurry. The software implements allele-specific neural networks that use a novel architecture and peptide encoding scheme. When trained on affinity measurements, MHCflurry outperformed the standard predictors NetMHC 4.0 and NetMHCpan 3.0 overall and particularly on non-9-mer peptides in a benchmark of ligands identified by mass spectrometry. The released predictor, MHCflurry 1.2.0, uses mass spectrometry datasets for model selection and showed competitive accuracy with standard tools, including the recently released NetMHCpan 4.0, on a small benchmark of affinity measurements. MHCflurry’s prediction speed exceeded 7,000 predictions per second, 396 times faster than NetMHCpan 4.0. MHCflurry is freely available to use, retrain, or extend, includes Python library and command line interfaces, may be installed using package managers, and applies software development best practices. DEPOSITED DATA ---------------------- * Curated training and model selection dataset: data_curated.20180219.tar.bz2 , derived from IEDB and other sources * MS benchmark dataset: abelin_peptides.mhcflurry_no_mass_spec.csv.bz2 , derived from Abelin et al. Immunity 2017. * HPV benchmark dataset: hpv_predictions.csv. The study that generated this dataset has now been published (Bonsack et al 2019, DOI: 10.1158/2326-6066.CIR-18-0584), and the authors request that any work based on the HPV dataset cite this paper. * MHCflurry 1.2.0 models: models_class1.20180225.tar.bz2 * MHCflurry (no MS) models: models_class1_selected_no_mass_spec.20180225.tar.bz2 * MHCflurry (train-MS) models: models_class1_trained_with_mass_spec.20180228.tar.bz2 See also: https://github.com/openvax/mhcflurry/ UPDATES ---------------------- * Version 3: Release of the HPV benchmark dataset * Version 2: The abelin_peptides.all_predictions.csv.bz2 given in Version 1 corresponded to an earlier preprint of the MHCflurry paper, not the final version published in Cell Systems. This file has been replaced with abelin_peptides.mhcflurry_no_mass_spec.csv.bz2, which gives the predictions analyzed in the Cell Systems paper.
DOI: 10.17632/m5s4ntv53w.1
title: Updates on Coding in Dermatology: Supplemental Material

description: Supplementary Material
DOI: 10.17632/4sr32jktn6.1
title: SoC ChatGPT Supplemental Material

description: Differential and most likely diagnoses for conditions that ChatGPT struggled to diagnose
DOI: 10.17632/xsbtkpknf7.1
title: HP – A code for the calculation of Hubbard parameters using density-functional perturbation theory

description: We introduce HP, an implementation of density-functional perturbation theory, designed to compute Hubbard parameters (on-site U and inter-site V) in the framework of DFT+U and DFT+U+V. The code does not require the use of computationally expensive supercells of the traditional linear-response approach; instead, unit cells are used with monochromatic perturbations that significantly reduce the computational cost of determining Hubbard parameters. HP is an open-source software distributed under the terms of the GPL as a component of Quantum ESPRESSO. As with other components, HP is optimized to run on a variety of different platforms, from laptops to massively parallel architectures, using native mathematical libraries (LAPACK and FFTW) and a hierarchy of custom parallelization layers built on top of MPI. The effectiveness of the code is showcased by computing Hubbard parameters self-consistently for the phospho-olivine LixMn1/2Fe1/2PO4 (x = 0, 1/2, 1) and by highlighting the accuracy of predictions of the geometry and Li intercalation voltages.
DOI: 10.17632/nshyw24427.1
title: The Ultimate Laboratory Guide: Determining Vitamin C levels through Iodine Titration

description: Ascorbic acid, also known as vitamin C, is a crucial water-soluble vitamin that plays a vital role incollagen production, neurotransmitter production, and antioxidant activity. It is essential for determiningfood's nutritional value and understanding potential health benefits. Iodine titration is a widely used methodfor determining vitamin C content, as it relies on the ascorbic acid and iodine oxidation-reduction reaction inan acidic environment. Iodine is reduced to iodide ions during the reaction, resulting in the formation ofdehydroascorbic acid and iodide ions. The color change is primarily due to the formation of a complex between iodine and starch, which serves as an indicator in the titration. In the presence of iodine, starchforms a deep blue-black complex, and the disappearance of the blue-black color at the end of the titrationindicates the completion of the reaction between Vitamin C and iodine. This method is useful for routineanalysis in educational and industrial contexts due to its simplicity, precision, and cost-effectiveness. The aimof this experiment is to measure the amount of ascorbic acid in a sample using iodine titration, providingcrucial information about the nutritional makeup of the material beingstudied.
DOI: 10.17632/zfcv9fmrgv.3
title: Blackgram Plant Leaf Disease Dataset

description: The Dataset is having five categories of 1000 images (Four most common leaf diseases of Blackgram crop such are Anthracnose, Leaf Crinkle, Powdery Mildew, Yellow Mosaic &  healthy category). The dataset is collected from the cultivation fields at Nagayalanka, Krishna (d.t), Andhra Pradesh, India.  The aim of collecting the dataset is to design an automated blackgram plant leaf disease identification and classification systems based on Computer Vision algorithms.
DOI: 10.17632/mwchxw4hnp.2
title: Low-cost automated call box system to conduct playback experiments for wildlife research and management

description: Acoustic cues (e.g., vocalizations or ‘calls’ in wildlife) may be effective in changing behavioral patterns in certain species. There are few published methods papers to create a device at a low cost that can automatically reproduce acoustic cues to carry on wildlife playback experiments or management. Therefore, we developed the Automated Call Box (ACB) based on an open-source Arduino-compatible microcontroller that attaches to a speaker system that costs less than the most common game caller used by researchers. The unit can be used to test the social information influence on habitat choices and other management applications. We field-tested the ACB successfully to assess the effect of conspecific cues on the habitat settlement of a migratory bird and to increase detectability on other songbird species. Data on this repository describes the materials used to build this system, and the code to program it, which can provide an overview as a reference for further research. This ACB allows researchers to conduct experiments on wildlife in inclement weather and complex environments, even in remote locations, with minimum or no necessity for the researcher to be present to reset the equipment.
DOI: 10.17632/byx7sztj59.1
title: Short-term electricity load forecasting (Panama case study)

description: This is a useful dataset to train and test Machine Learning forecasting algorithms and compare results with the official forecast from weekly pre-dispatch reports. The following considerations should be kept to compare forecasting results with the weekly pre-dispatch forecast: 1. Saturday is the first day of each weekly forecast; for instance, Friday is the last day. 2. A 72 hours gap of unseen records should be considered before the first day to forecast. In other words, next week forecast should be done with records until each Tuesday last hour. Data sources provide hourly records. The data composition is the following: 1. Historical electricity load, available on daily post-dispatch reports, from the grid operator (CND). 2. Historical weekly forecasts available on weekly pre-dispatch reports, both from CND. 3. Calendar information related to school periods, from Panama's Ministery of Education. 4. Calendar information related to holidays, from "When on Earth?" website. 5. Weather variables, such as temperature, relative humidity, precipitation, and wind speed, for three main cities in Panama, from Earthdata. The original data sources provide the post-dispatch electricity load in individual Excel files on a daily basis and weekly pre-dispatch electricity load forecast data in individual Excel files on a weekly basis, both with hourly granularity. Holidays and school periods data is sparse, along with websites and PDF files. Weather data is available on daily NetCDF files. For simplicity, the published datasets are already pre-processed by merging all data sources on the date-time index: 1. A CSV file containing all records in a single continuous dataset with all variables. 2. A CSV file containing the load forecast from weekly pre-dispatch reports. 3. Two Excel files containing suggested regressors and 14 training/testing datasets pairs as described in the PDF file.