cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14552136.v12
title: Gun Violence - Mass Shootings

description: The data on mass shootings is from https://www.gunviolencearchive.org/ . This dataset on mass shootings for the period 2014-2023 was provided on Feb 19, 2024 by the Data Manager (Ms. Sharon Williams) at the Gun Violence Archive (https://www.gunviolencearchive.org/) on a data request. Minimal curation was done on this data – the date variable was split into year, month and day. See the codebook for full details.A mass shooting is defined as four or more people injured or killed, because of firearms, excluding the shooter.<br>The curated datasets are included here along with a research question and guiding questions.<br><br>For information of how this data is collected, go to: https://www.gunviolencearchive.org/explainerDefinition for mass shooting and mass murder from the above website is given verbatim below:<br><br><b>Mass Shooting Methodology and Reasoning</b>: Mass Shootings are, for the most part an American phenomenon. While they are generally grouped together as one type of incident they are several different types including public shootings, bar/club incidents, family annihilations, drive-by, workplace and those which defy description but with the established foundation definition being that they have a minimum of four victims shot, either injured or killed, not including any shooter who may also have been killed or injured in the incident. GVA also presents the count of Mass Murder which, like the FBI's definition is four or more victims, killed, not including the shooter. Mass Murder by gun is a subset of the Mass Shooting count.<br><br><br>
DOI: 10.6084/m9.figshare.1495503.v1
title: A Retrospective Analysis of the Effect of Discussion in Teleconference and Face-to-Face Scientific Peer Review Panels

description: This fileset contains the anonymized dataset for the BMJ Open article titled "A Retrospective Analysis of the Effect of Discussion in Teleconference and Face-to-Face Scientific Peer Review Panels".
DOI: 10.6084/m9.figshare.26029459.v1
title: Input files for DeSeq2 analysis

description: Input files for DeSeq2 analysis - Download all the folder and place them in a folder called "input_kallisto".
DOI: 10.6084/m9.figshare.7387703.v1
title: Supplementary Material for: Competitive Testing of the WHO 2010 versus the WHO 2017 Grading of Pancreatic Neuroendocrine Neoplasms: Data from a Large International Cohort Study

description: <b><i>Background:</i></b> The World Health Organization (WHO) and the American Joint Cancer Committee (AJCC) modified the grading of pancreatic neuroendocrine neoplasms from a three-tier (WHO-AJCC 2010) to a four-tier system by introducing the novel category of NET G3 (WHO-AJCC 2017). <b><i>Objectives:</i></b> This study aims at validating the WHO-AJCC 2017 and identifying the most effective grading system. <b><i>Method:</i></b> A total of 2,102 patients were enrolled; entry criteria were: (i) patient underwent surgery; (ii) at least 2 years of follow-up; (iii) observation time up to 2015. Data from 34 variables were collected; grading was assessed and compared for efficacy by statistical means including Kaplan-Meier method, Cox regression analysis, Harrell’s C statistics, and Royston’s explained variation in univariable and multivariable analyses. <b><i>Results:</i></b> In descriptive analysis, the two grading systems demonstrated statistically significant differences for the major category sex but not for age groups. In Cox regression analysis, both grading systems showed statistically significant differences between grades for OS and EFS; however, no statistically significant difference was observed between the two G3 classes of WHO-AJCC 2017. In multivariable analysis for the two models fitted to compare efficacy, the two grading systems performed equally well with substantially similar optimal discrimination and well-explained variation for both OS and EFS. The WHO-AJCC 2017 grading system retained statistically significant difference between the two G3 classes for OS but not for EFS. <b><i>Conclusions:</i></b> The WHO-AJCC 2017 grading system is at least equally performing as the WHO-AJCC 2010 but allows the successful identification of the most aggressive PanNET subgroup. Grading is confirmed as probably the most powerful tool for predicting patient survival.
DOI: 10.17632/39bktnk7jf
title: THz CSRR CST 400 material

description: THz measurement is a worldwide issue due to its broad range of practicability in miscellaneous real-world problems. We present a new brand strategy working at the terahertz range with potential for manufacturing high sensitive sensors. This is a simple technique for measuring loss tangent in this frequency band, while previous models have not triumphed to precisely measure tangent loss like dielectric constant. Moreover, a reliable method for explaining the structure’s behavior is essential, which has been done by automatic programming algorithms. ABCEP and GEP are those algorithms that have been used. This is the dataset which has been used to train the algorithms to find a precise function to represent the structure's behavior in response to different materials. This is produced by CST simulations.
DOI: 10.17632/xn2wy75f8m
title: Deep Potato

description: Deep Potato - hyperspectral imagery of potato leaves with reference measurements dataset: towards potato physiological features modeling.

The dataset contains 8 high-resolution hyperspectral orthophoto maps for deep learning modeling, stored in the "orthophoto_maps" folder. The maps are encoded in ENVI format. For each map 2 files: HDR file with the necessary information and BSQ file with imagery data are provided. The BSQ files are compressed as ZIP.
- for reference, there are 60 lab measurements supplemented as well as 74 physiological measurements based on collected plants' material, both with precise geolocation data linking the measurements and the orthophoto maps. Those files are stored in the "measurements" folder,
- hyperspectral images, extracted from orthophoto maps, stored in the "images" folder - you will find 84 different images there, stored in binary format (could be easily opened using python numpy library).
- a "dataset_presentation.html" file with a brief presentation of the dataset.

This data repository contains analytical data for the following submitted publication:
- Ruszczak B., Boguszewska-Mańkowska D.: Deep Potato – the hyperspectral imagery of potato cultivation with reference agronomic measurements dataset: towards potato physiological features modeling, 
Data in Brief, 2022, 108087, ISSN 2352-3409, https://doi.org/10.1016/j.dib.2022.108087
DOI: 10.6084/m9.figshare.20740132.v1
title: Andean bear microsatellite genotypes and D-loop sequences dataset from Ecuador

description: Dataset sequences from the hypervariable region 1 of the D-loop, and eleven species-specific microsatellite markers from Ecuadorian Andean bears. Alignment for previous (heterologous) microsatellite markers and newly designed markers are presented using two reference genomes. The Rscript for data analysis developed and implemented for this study is presented as well.
DOI: 10.6084/m9.figshare.21298179.v1
title: Shallow water dataset for DINo

description: This data is used for DINo (https://arxiv.org/abs/2209.14855) to perform experiments on sphere. The dataset is generated with Dedalus (https://dedalus-project.org/).
DOI: 10.6084/m9.figshare.25533367.v20
title: Coastal oceanographic connectivity at global scale: A dataset of pairwise probabilities and travel times derived from biophysical modeling

description: The dataset encompasses two components: (1) a GeoPackage file (referencePolygons.gpkg) designed for geographic information systems (GIS), containing the spatial distribution of the hexagon-shaped coastal sites, each with a unique identifier (id), and (2) a comma-separated values compressed file (oceanographicConnectivity.csv.zip) containing a matrix detailing the realized connections between pairs of sites. This matrix includes information on the source site (id), sink site (id), date of particle release (day, month, year), and the corresponding travel time expressed in days.Users have two primary options for utilizing the dataset: they can either work directly with the geospatial vector for GIS, paired with the corresponding matrix of realized connections, to retrieve pairwise connectivity estimates between coastal sites globally, or they can use the coastalNet R package for streamlined access and analysis.For users opting to work within a GIS environment, the geospatial vector file contains the spatial distribution of the coastal hexagons, each identified by a unique ID. By identifying the source and sink sites of interest within the spatial data, users can retrieve the corresponding hexagon IDs. These IDs can then be cross-referenced with the matrix of realized connectivity events, which includes information on particle release date, source ID, sink ID, and travel time. This allows users to easily extract the specific connectivity events between selected sites, providing a flexible and detailed approach to analyzing connectivity patterns directly within GIS.For users opting to work within R, the coastalNet package can facilitate the use of the provided oceanographic connectivity estimates. It offers a comprehensive suite of functions for accessing, analyzing, and visualizing connectivity data. Check https://github.com/jorgeassis/coastalNet for additional information.
DOI: 10.6084/m9.figshare.27376851.v1
title: IWHR_AI_Lable_Floater_V1: An annotated Dataset and Benchmark for Detecting Floating Debris in Inland Waters

description: Marine litter is a serious threat to marine ecosystems, and the timely removal of floating waste from inland waters is effective in preventing floating debris from entering the sea. An accurate object detection system is a prerequisite for efficiently clearing floaters. However, complex light conditions in the water, small size objects and other factors pose a huge challenge for floating object detection. In order to facilitate the solution of the floating object pollution problem and promote the application of AI technology in the water industry, we proposed the first floater dataset of waters collected from real water scenarios based on shore-based filming equipment, IWHR_AI_Lable_Floater_V1. The dataset consists of 3000 images containing accurate annotation information to support vision-based water surface floater detection tasks. We conducted a number of baseline experiments to evaluate the performance of mainstream object detection algorithms on this dataset. The results show that the detection accuracies of the models, including the state-of-the-art model YOLOv9, are all low, which also indicates that floating object detection is a challenging task.
DOI: 10.6084/m9.figshare.4238990.v2
title: ViewBS - Tools for exploring and visualizing bisulfite sequencing (BS-seq) data.

description: These files are the test data for ViewBS
DOI: 10.6084/m9.figshare.21732548.v2
title: Rhythmic gymnastics traditional warm-up (control group)

description: The rhythmic gymnastics traditional warm-up that the control group performed while the experimental group underwent the core and plyometric functional training. Time from 40 to 45 min.
DOI: 10.6084/m9.figshare.28990745.v1
title: msigdbr data

description: Data for msigdbr R package
DOI: 10.17632/yxc57jsm3p
title: JIE_export_replication

description: Replication files
DOI: 10.6084/m9.figshare.14286648.v1
title: MULTICRITERIA APPROACH TO PROSPECT THEORY: FUNDAMENTALS AND APPLICATION

description: ABSTRACT This paper compares the use of two multicriteria decision analytical methods used for military material selection. In the decision analysis the Analytic Hierarchy Process - AHP was initially used first in order to rank the alternatives in the presence of multiple criteria. This study was conducted in the Army Evaluation Center, a unit of the Brazilian Army. The other decision analysis method employed was TODIM, which is based on Prospect Theory, thus allowing to take risks into account in the modeling stage. Although the two multi-criteria methods rely on different decision paradigms, this application study showed that results were quite similar to justify the use of either method in the practice of similar military decisionmaking processes.
DOI: 10.6084/m9.figshare.7763570.v2
title: Global Native Alien Richness (NAR) relationship meta-analysis - Ecology Letters 2019

description: Data from: Tomasetto, F., Duncan, R.P., Hulme P.E. (2019). Resolving the invasion paradox: pervasive scale and study dependence in the native-alien species richness relationship. <i>Ecology Letters</i>.<br><br>All explanations for the data are provided in the MS and associated SI.<br>
DOI: 10.17632/8gz7673s8f
title: Data for: Activated olive mill waste-based hydrochars as selective adsorbents for CO2 capture under postcombustion conditions

description: Raw data for CO2 and N2 isotherms is included as well as the results from the TGA experiments and the calculations of the Toth adjustments.
DOI: 10.17632/4wd9scvdvk
title: Assessing recovery-related behaviors, emotions, and cognitions among members of Alcoholics Anonymous over 7 days: A quantitative daily diary study

description: The main purpose of this research study was to investigate the relationship between selfishness, helping behavior, and gratitude among members of the 12-step program Alcoholics Anonymous. The research hypotheses centered around ideas discussed at length in 12-step literature- When people in AA spend more time helping others and feeling grateful, they think less about their own cares and concerns. The data provides preliminary evidence of this relationship: significant daily associations were uncovered between helping behavior, gratitude and selfishness. Participants reported less self-absorption on days when they helped more people and were more grateful. A number of additional control variables were collected at baseline and throughout the study that may be of interest to other researchers. This was a quantitative daily dairy study that consisted of an initial baseline assessment followed by 7 nightly reports that were collected each evening at 8pm. Participants (N = 113) were recruited through social media networks (e.g., large recovery-related facebook groups, twitter, Instagram, etc.) as well as an email list from people in recovery who had previously participated in research and had provided consent to be contacted in the future. After the baseline survey, participants were sent a reminder to fill out the survey each evening at 8 pm in their respective time zones via text and email. This data is well-suited for multilevel modeling analyses for all daily variables. A complete list of the measures is below. Baseline: Addiction Severity - Short Inventory of Problems-Revised (SIP-R) Adult Attachment - Experiences in Close Relationships Scale - Short (ECR-S) Trait Narcissism - Narcissistic Personality Inventory (NPI-13) Altruism - Altruistic Personality Scale (APS) Trait Gratitude - Gratitude, Resentment, and Appreciation Test (GRAT) Personality - Ten-Item Personality Inventory (TIPI) Psychological Distress - Kessler Psychological Distress Scale (K-6) Social Desirability - Marlow Crowne Social Desirability Scale (SDS) Locus of Control - Alcohol-Related God Locus of Control Scale (AGLOC) Self-Esteem - Rosenberg Self-Esteem Scale (RSE) Recovery Capital - Brief Assessment of Recovery Capital (BARC) Daily: Self-Absorption - Self-Absorption Scale (SAS) Narcissism - Hypersensitive Narcissism Scale (HSNS) Mood - Positive/Negative Affect (PANAS) Helping Behavior - Service to Others in Sobriety (SOS) State Gratitude - Gratitude Checklist (3-item Daily Gratitude) Self-Efficacy - Self-Efficacy Scale (SES)
DOI: 10.17632/5c9f3mctgv
title: Supplemental Materials: Leveraging Artificial Intelligence Large Language Models for Writing Clinical Trial Proposals in Dermatology

description: Supplementary Materials (Methods and Results) for "Leveraging Artificial Intelligence Large Language Models for Writing Clinical Trial Proposals in Dermatology"
DOI: 10.6084/m9.figshare.7512605.v1
title: Diametric Distribution Projection of Ecological Groups in a Mixed Tropical Forest

description: ABSTRACT This study aimed to evaluate the ecological and successional aspects of a subtropical forest fragment by projection of the diameter distribution of different ecological groups, using transition matrix model. Based on measurements of 2009 and 2012 of all trees above 10 cm of DBH, projection of the diameter distribution as well as analysis of forest dynamic were made for three species groups: Pioneer; Non Pioneers, and the whole forest. Simulations of the dynamics of the groups were made until 2027 after method validation. The projection method was adherent in all cases, with higher precision when using the 5cm class interval. The analysis made indicated a gradual substitution tendency of the pioneer species, suggesting a successional advance in the forest fragment under study, as well as an efficiency of the projection method for dynamics analysis of the ecological groups studied.
DOI: 10.17632/cknp9djpzp
title: Nanostores’ Competitiveness and Sustainability Impact on Communities in Emerging Countries, An Interview with Microsoft Copilot

description: This interview with Microsoft Copilot delves into exploring strategy alternatives for nanostores, as small independent grocery retailers, to enhance their economic competitiveness in retail landscapes while positively impacting the sustainability of their local communities in emerging countries.
DOI: 10.17632/d9f44dspd5
title: Optimizing the Combination of Natural Pigments for Co-Sensitization of Panchromatic TiO2 Dye Sensitized Solar Cells

description: Note: The Proquest link to the M.S. Thesis with a more complete description of this work is provided under the "Related Links" header at the bottom of this page.

This repository contains UV/VIS and JV measurement .csv files for DSSC’s produced with a variety of natural dye combinations of Anthocyanins (A), Betalins (B), Chlorophyll (C), Xanthonoids (M), Curcuminoids (K) and Phycobilins (P). Note: A 1:1 combination of A & B is denoted as “AB”. Data is available for 42 unique combinations, plus 6 so-called “absorbance optimized combinations” that exhibit light harvesting efficiency (LHE) profiles which are highly commensurable with the AM1.5G solar irradiance spectrum (data courtesy of NREL). This work hypothesizes that dye combinations exhibiting these highly commensurable LHE spectra will also exhibit characteristically high DSSC performance. For convenience, both of these .csv files have been plotted to make the data available in a graphical format.

The repository also contains the original .py file used to perform the Radial Basis Function (RBF) interpolation for analysis of a further 2,568 dye combinations. For example, given a set of 6 constituent dyes, this script yields a surface in R7 which interpolates all measured absorbance data at a given wavelength. Assuming that absorbance data is available for n combinations of these 6 constituent dyes, this would be a function interpolating n points in R7. This process is repeated for all wavelengths for which data is available allowing each interpolation function to be sampled and concatenated to yield a spectrum for an arbitrary dye combination. The script then samples many arbitrary combinations using this method and prints to the terminal the combinations which maximize each of the 3 objective functions uses to assess AM1.5G commensurability. The input data to this script can be modified allowing for similar analysis of proprietary data. Specifically, this can be achieved by the appropriate modification of the “Empirical_Dye_Solutions_Volume_Fractions.csv” and either of the “UV/VIS_Absorbance_Anode_Adsorbed.csv” or “UV/VIS_Absorbance_Bulk_Solution.csv” files. 

The following videos (uploaded to YouTube) have been produced to assist readers in understanding the purpose of both the RBF interpolation and the differences of the 3 objective functions:

https://www.youtube.com/watch?v=KSHNrELYn9g
https://www.youtube.com/watch?v=D9Z7w32d_Ts

The results obtained in this work indicate that panchromaticity alone is not sufficient to predict DSSC performance. However, a 1:1 combination of a-Mangostin and Curcuminoids was found to exhibit much higher DSSC efficiency (TiO2 anode, Pt-counter electrode, I-/I3- electrolyte) compared to any of the other analyzed combinations. This combination was successfully co-adsorbed with CDCA and exhibited strong UV stability over time.
DOI: 10.6084/m9.figshare.12571547.v1
title: The data output from the probit regression analysis to determine the safety of antivenom in brine shrimp

description: This data set contains the following:<br>1. Summary output of probit regression analysis to determine the safety of Vins Bioproducts antivenom in brine shrimp<br>2. Summary output of probit regression analysis to determine the safety of PAN Africa antivenom in brine shrimp<br><br>
DOI: 10.6084/m9.figshare.26986738.v1
title: Additional file 13 of A translatome-transcriptome multi-omics gene regulatory network reveals the complicated functional landscape of maize

description: Additional file 13. Merged regulatory pairs predicted by Union GRN.
DOI: 10.17632/h8mvg73p9t
title: Western blots (uncropped) for Stolp et al. Cell Reports 2022

description: AP-3-dependent yeast cell death pathway. 
This file contains the uncropped, unlabeled immunoblots for all Western blot panels presented in Stolp et al. Cell Reports, 2022, which includes Figures 3F, 4C, 5C, and Supplemental Figure S2D and S2H.
DOI: 10.6084/m9.figshare.16641043.v2
title: anxiety

description: It contains data on anxiety.
DOI: 10.15468/dl.5bsvgr
title: Occurrence Download

description: A dataset containing 61886 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Potentilla reptans L.",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 61886 records from 256 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013371-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.25943361.v1
title: Supplementary Material from A social learning primacy trend in mate-copying; an experiment in Drosophila melanogaster

description: data_primacy.csv
DOI: 10.6084/m9.figshare.26044609.v1
title: Identified labels

description: Выборк данных с метками, включающую индексы различных ключевых точек (Q, R, S, T и P) в данных ЭКГ. Эти данные используются для анализа и идентификации различных фаз сердечного цикла. Эти данные используются для анализа характеристик ЭКГ сигнала и классификации различных фаз сердечного цикла.
DOI: 10.6084/m9.figshare.1296323.v1
title: Blood pressure

description: Test data set to be linked to an iPython notebook I am working on
DOI: 10.6084/m9.figshare.16592678.v1
title: Dataset for Soft Elasticity Optimises Dissipation in 3D-Printed Liquid Crystal Elastomers

description: Contains data used and published in our paper:<br><br>