cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24040515.v1
title: Human Brands: The Oprah Winfrey Effect

description: This conceptual paper aims to argue that human traits are biographical and not biological by highlighting the traits of five people who I considered human brands because they changed American society. The Allport (1897 – 1967) trait theory was the lens used in searching for data on these individuals, and the 5-Factor Model of Personality theory was applied when organizing and analyzing how their traits where developed. Certain human traits (i.e., being articulate) can be considered a stimulus for behavior-change. Human brands can influence automatic behavior reaction. In reviewing narratives of previously published studies that focus was on the lives of these five human brands that changed the world, traits are identified and in conclusion compared to those traits of Oprah Winfrey for differences as to why she is considered the most powerful human brand in the world. One of the individuals is the richest man in the world, so I wondered what trait she possesses the others did not. To highlight the differences in trait influences the Thorndike (1874 – 1949) stimulus–response theory was applied in conclusion. It is my aim that this paper creates dialogue on predicting, constructing, or ensuring through life experiences human traits that will create a person that can be identified as one that will have a major influence on society. Human attributes are scientifically linked with human influence and social change. My argument is supported by the common traits found in the five human brands.
DOI: 10.6084/m9.figshare.3562680.v1
title: Appendix A. Supporting methods and results for ecological explanations to island gigantism.

description: Supporting methods and results for ecological explanations to island gigantism.
DOI: 10.6084/m9.figshare.951004.v3
title: Smoking Cessation RCT 1-yr Results

description: This is the data for the one-year results for a previously-published smoking cessation RCT. See http://dx.doi.org/10.6084/m9.figshare.682404 for the main results published in 2013.
DOI: 10.17632/h44s9t39hd
title: The antimonite-thioantimonates-antimonate pathway: insights from sulfidic hot springs and microbial culture experiments for a novel mechanism of abiotic antimonite oxidation

description: The data package provides access in a numerical, text-based format to the data that appear in both the main manuscript and the supplementary material of the paper “The antimonite-thioantimonates-antimonate pathway: insights from sulfidic hot springs and microbial culture experiments for a novel mechanism of abiotic antimonite oxidation”.
DOI: 10.6084/m9.figshare.28451135.v2
title: <b>Whole-body visualization of SARS-CoV-2 biodistribution </b><b><i>in vivo</i></b><b> by immunoPET imaging in non-human primates</b>, Source data.

description: Source data from <b>Whole-body visualization of SARS-CoV-2 biodistribution </b><b><i>in vivo</i></b><b> by immunoPET imaging in non-human primates</b> manuscript (Nature Communications)
DOI: 10.6084/m9.figshare.29124458.v1
title: Apex predator loss drives trophic downgrading in China’s protected areas

description: We compiled a dataset on terrestrial wildlife of PAs in China from camera trap studies.
DOI: 10.6084/m9.figshare.23251328.v1
title: Gobius incognitus_J1914_NMP6V 146149.tif

description: X-ray data set used in "Skeletal traits and otoliths can unravel the relationships within European Gobiidae (Gobius lineage sensu lato)" Bettina Reichenbacher, Jasna Vukić, Radek Šanda, Ulrich K. Schliewen, Hamid R. Esmaeili, Abderrahmane Kassar, IN: Zoological Journal of the Linnean Society, 2023, XX, 1–32 https://doi.org/10.1093/zoolinnean/zlad058 <br> scale bar of X-ray images = 1 cm
DOI: 10.17632/f4xz5d4fzd
title: ALERT (Analysis of Linguistic Extremism in Religious Text)

description: The widespread dissemination of religiously aggressive content on social media platforms poses significant threats to social cohesion and communal harmony. Social media has emerged as a prevalent venue for discussing diverse topics, including religion which frequently result in debates. These debates often fuel animosity, incite violence, and spread life-threatening messages that disrupt societal peace and security. To address this challenge, we developed a novel Bengali dataset, ALERT, accompanied by English translations, to identify and classify religious aggression in texts. 

The dataset was obtained from several online platforms, including Facebook, YouTube, blogs, online news portals, and group discussions. We executed multiple stages for data preprocessing, including the elimination of duplicates, special characters, emoji to improve the coherence of the dataset. Each instance in the dataset was annotated by two of the lists of four annotators with diverse academic, religious, and racial backgrounds, with any discrepancies resolved by expert review.

The ALERT dataset is a collection of 4,027 Bangla texts categorized as 
1. Hate speech (995), 
2. Vandalism (909), 
3. Atrocity (1117), 
4. No aggression (1,006). 
The dataset is structured with the following fields:
• Final Annotation
• Text
• English Translation 
Our developed dataset contains a mix of formal and informal Bangla texts, reflecting how people communicate in real life. Instead of simply labeling content as aggressive or not, it offers more detailed categories, helping with more precise content moderation. The dataset is publicly accessible for research purposes to promote innovation and collaboration within the Bengali NLP community.
DOI: 10.17632/fspx44mwfp
title: Image Dataset for Detection and classification of Diseases of Guava Fruits and Leaves

description: The Guava Disease Detection Dataset provides annotated images of guava fruits and leaves, covering both healthy and disease-affected samples. It includes 3432 original images (1119 of fruits and 2313 of leaves) and an augmented set totaling 20344 images. Disease types for fruits include anthracnose, scab, and styler end rot, while leaves exhibit anthracnose, canker, dot, and rust. This dataset supports the development of machine learning models for precise disease detection in guava crops, enabling early interventions and improved disease management in agriculture.
#Total Original Images: 3432 images (1119 fruits, 2313 leaves)
#Augmented Images: 20344 images (10145 fruits, 10199 leaves)

#Fruit Dataset:
Healthy: 470 images
Anthracnose: 263 images
Styler End Rot: 262 images
Scab: 119 images

#Leaf Dataset:
Healthy: 1498 images
Anthracnose: 237 images
Canker: 192 images
Dot: 219 images
Rust: 167 images

#Purpose: Enables the creation of machine learning models for early guava disease detection, promoting efficient disease management and reducing crop loss.
DOI: 10.17632/g739z29fc5
title: Fully 3D-printed, nonelectric, spring-powered syringe pump for operating microfluidic devices

description: The STL files are for building a fully 3D-printed, nonelectric, spring-powered syringe pump.
DOI: 10.6084/m9.figshare.20006109.v1
title: Relationships between Cultural Adaptation and Immigrants’ Well-Being

description: Abstract The present study aimed to evaluate the predictive relationship of socio-demographic variables, cultural adaptation and hope on general well-being (GWB), subjective (SWB), social (SoWB) and psychological (PWB) and in the meaning of life. The participants consisted of 108 immigrants. The instruments used were: bio sociodemographic questionnaire, Mental Health Continuum - Short Form, Dispositional Hope Scale, Acculturation Measures and Meaning of Life Questionnaire. In general, only sociocultural adaptation showed a positive predictive relationship with all types of well-being studied, nonetheless this measure presented a negative predictive relationship regarding the presence of meaning in life. Psychological adaptation was predictively and positively related only to SWB. The perception of cultural distance negatively affected SoWB. The presence of meaning was also negatively predicted by the type of immigration and age. The search for meaning was negatively predicted only by income. The results are important for a better understanding of factors that influence the experience of immigrants in Brazil.
DOI: 10.6084/m9.figshare.28835765.v1
title: spatial_with_images.h5ad

description: Run a deep learning model on spatial transcriptomics dataset.
DOI: 10.6084/m9.figshare.4789759.v3
title: rRNA gene sequence data and scripts used for PLOS Biology submission "Nitrogen fixation in a landrace of maize is supported by a mucilage-associated diazotrophic microbiota"

description: Scripts and data used for metagenomics and 16s amplicon analysis of bacterial communities from Maize populations.<br><br>Authors: Allen Van Deynze<sup>1</sup>,*, Pablo Zamora<sup>1</sup>,*, Pierre-Marc Delaux<sup>2</sup>,*, Cristobal Heitmann<sup>1</sup>*, Donald Gibson<sup>1</sup>, Kevin D. Schwartz<sup>1</sup>, Alison M. Berry<sup>1</sup>, Danielle Graham<sup>2</sup>, Dhileepkumar Jayaraman<sup>2</sup>, Shanmugam Rajasekar<sup>2</sup>, Junko Maeda<sup>3</sup>, Srijak Bhatnagar<sup>4</sup>, Guillaume Jospin<sup>4</sup>, Aaron Darling<sup>4</sup>, Richard Jeannotte<sup>5</sup>, Javier Lopez<sup>6</sup>, Bart C. Weime<sup>r5</sup>, Jonathan A. Eisen<sup>4</sup>, Howard-Yana Shapiro<sup>1,6</sup>, Jean-Michel Ané<sup>2,3</sup> Alan B. Bennett<sup>1</sup><br>Affiliations:1 Department of Plant Sciences, University of California, Davis, California 95616.2 Department of Agronomy, University of Wisconsin, Madison, Wisconsin 537063 Department of Bacteriology, University of Wisconsin, Madison, Wisconsin 537064 Genome Center, University of California, Davis, California 95616.5 Department of Population Health and Reproduction, University of California, Davis, California 95616 6 Mars, Incorporated*These authors contributed equally to the results
DOI: 10.17632/5n2jf32kx5
title: Data for: Rapid nanofabrication via UV-assisted selective etching on GaAs without templates

description: All datas were performed on AFM
DOI: 10.17632/ymg9nsn6kn
title: Higher Education Students' Early Perceptions of ChatGPT: Global Survey Data

description: The introduction of ChatGPT in November 2022 marked a significant milestone in the application of artificial intelligence in higher education. Due to its advanced natural language processing capabilities, ChatGPT quickly became popular among students worldwide. However, the increasing acceptance of ChatGPT among students has attracted significant attention, sparking both excitement and scepticism globally. In order to capture early students' perceptions about ChatGPT, the most comprehensive and large-scale global survey to date was conducted between the beginning of October 2023 and the end of February 2024. The questionnaire was prepared in seven different languages: English, Italian, Spanish, Turkish, Japanese, Arabic, and Hebrew. It covered several aspects relevant to ChatGPT, including sociodemographic characteristics, usage, capabilities, regulation and ethical concerns, satisfaction and attitude, study issues and outcomes, skills development, labour market and skills mismatch, emotions, study and personal information, and general reflections. The survey targeted higher education students who are currently enrolled at any level in a higher education institution, are at least 18 years old, and have the legal capacity to provide free and voluntary consent to participate in an anonymous survey. Survey participants were recruited using a convenience sampling method, which involved promoting the survey in classrooms and through advertisements on university communication systems. The final dataset consists of 23,218 student responses from 109 different countries and territories. The data may prove useful for researchers studying students' perceptions of ChatGPT, including its implications across various aspects. Moreover, also higher education stakeholders may benefit from these data. While educators may benefit from the data in formulating curricula, including designing teaching methods and assessment tools, policymakers may consider the data when formulating strategies for higher education system development in the future.
DOI: 10.6084/m9.figshare.12420968.v8
title: Benchmarking atlas-level data integration in single-cell genomics - integration task datasets

description: Pancreas, Lung atlas, human immune cell, and human and mouse immune cell integration RNA integration tasks, and all ATAC mouse brain integration tasks from the manuscript "Benchmarking atlas-level data integration in single-cell genomics". <br><br>These datasets were aggregated from public datasets, cell annotations were harmonized or reannotated, and the data was consistently preprocessed using scran pooling and log+1 transformation (for RNA tasks). In the immune cell datasets an erythrocyte development trajectory was also annotated. Details on dataset preprocessing can be found in the paper and in the accompanying Github at https://www.github.com/theislab/scib.<br><br>Please cite the paper and the papers the individual datasets were aggregated from when using this data.<br>
DOI: 10.6084/m9.figshare.1460722.v1
title: Modest reproducibility success: a reanalysis of two early branching Metazoa datasets using ReproPhylo

description: This is an html file of the blog post "Modest reproducibility success: a reanalysis of two early branching Metazoa datasets using ReproPhylo" as in the link below.
DOI: 10.17632/nzyntpcm6k
title: Data Set: Deep learning-assisted appointment scheduling under uncertainty

description: This repository includes ten test instances (each compromising ten variations), one real instance, and an InputReader Python file used in the "Deep learning-assisted appointment scheduling under uncertainty." This data set can be used for future comparisons of the optimization algorithms developed for similar problems.
DOI: 10.6084/m9.figshare.25047371.v1
title: Enhancing ecosystem productivity and stability with increasing canopy structural complexity in global forests

description: Forest canopy structural complexity (CSC) plays a crucial role in shaping forest ecosystem productivity and stability, but the precise nature of their relationships remains controversial. Here, we provided the datasets and codes for investigating this issue at a global scale.Researchers utilizing these datasets and codes should cite the following paper:Liu, X., Feng, Y., Hu, T., Luo, Y., Zhao, X., Wu, J., Maeda, E. E., Ju, W., Liu, L., Guo, Q., & Su, Y. (2024). Enhancing ecosystem productivity and stability with increasing canopy structural complexity in global forests. Science Advances, 10, eadl1947.
DOI: 10.6084/m9.figshare.27308133.v1
title: GastroHUN an Endoscopy Dataset of Complete Systematic Screening Protocol for the Stomach

description: The dataset is organized into three catalogs:
1) Labeled Images: Contains 8,834 labeled images from 387 patients.
2) Labeled Sequences (Group 1-7): Includes 4,729 video sequences grouped by patient ranges (e.g., Patients 7-113, 115-191, etc.), covering 223 patients.
3) Videoendoscopies (Group 1-7): Comprises 237 videos grouped similarly by patient ranges (e.g., Patients 7-103, 104-133, etc.), representing 233 patients.

The first two catalogs feature labels provided by four expert gastroenterologists who followed a systematic stomach screening protocol. The third catalog includes diagnostic information derived from endoscopy and histopathology data.
DOI: 10.6084/m9.figshare.5414755.v4
title: Example dataset for bibrep.ado

description: The data file contains the publication set of the author which can be used for testing the bibrep.ado command in Stata.<br>
DOI: 10.17632/pgrvssrwy6
title: Human Wellbeing and Machine Learning

description: Supplementary Material for

Human Wellbeing and Machine Learning

by Ekaterina Oparina (r) Caspar Kaiser (r) Niccolò Gentile; Alexandre Tkatchenko, Andrew E. Clark, Jan-Emmanuel De Neve and Conchita D'Ambrosio

This repository contains the list of variables that are used in the Extended Set analysis for the German Socio-Economic Panel, the UK Household Longitudinal Study, and the American Gallup Daily Poll. The variables are grouped into categories, the summary table is reported at the beginning of the document. We use the 2013 Wave of Gallup and SOEP, and Wave 3 of the UKHLS (which covers 2011-2012). Our dataset includes all of the available variables, apart from direct measures of subjective wellbeing (such as domain satisfaction, happiness, or subjective health) or mental health and technical variables (e.g. id numbers). We also exclude variables with more than 50% missing values.

The presented lists include the variables before processing. For the analysis, we convert categorical variables into a set of dummies, one for each category. We then drop all perfectly collinear variables.
DOI: 10.6084/m9.figshare.19722505.v2
title: Kilpisjärvi MAGs

description: FASTA files for 796 metagenome-assembled genomes (MAGs) recovered from soils in Kilpisjärvi, northern Finland.
DOI: 10.6084/m9.figshare.24042891.v1
title: Dataset from "In-situ Monitoring of Image Texturing via Random Forests and Clustering with applications to Additive Manufacturing"

description: This is the dataset associated to the following paper: Caltanissetta, F., Bertoli, L., Colosimo, B.M. (2023). <i><b>In-situ Monitoring of Image Texturing via Random Forests and Clustering with applications to Additive Manufacturing</b></i>, IISE TransactionsThe attention toward in-situ monitoring in Additive Manufacturing (AM) has significantly increased over the last years, paving the way to a paradigm shift for quality monitoring and control via big data analysis of signals, images, and videos. In-situ quality monitoring represents an opportunity for waste reduction and first-time-right production via inline detection of process flaws, which allows early identification of scraps and the possibility of correcting actions for first-time-right production. This paper presents a solution for in-situ monitoring of images taken layerwise in material extrusion AM. Compared with the existing solutions, mainly focusing on monitoring the shape deviation observed at each layer with respect to the nominal shape, this paper focuses on monitoring the internal surface texture with the aim of detecting over- and under-extrusion flaws. Inspired by an approach developed by Bui and Apley for textile image monitoring, we propose a solution for in-situ monitoring of textured surfaces which is based on combining Random Forests with clustering to automatically identify defective locations layerwise. A real case study based on Fused Filament Fabrication is used to compare the performance of the novel proposed solution with the original one and identify an appropriate direction for future research.https://www.ic.polimi.it/publications/
DOI: 10.15468/dl.ztngg3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Argentina silus (Ascanius, 1775)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((54.0145 -15.8532,54.1138 -16.1504,54.9312 -16.1504,55.0218 -15.961,54.8989 -15.5532,54.5521 -15.3811,54.2381 -15.4633,54.0145 -15.8532))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013335-250525065834625/datasets/export for details.
DOI: 10.17632/t3mkw334b6
title: Mukoyama-Takayama-Tanaka 2025

description: Replication materials for Mukoyama, Takayama, and Tanaka "Occupational Reallocation Within and Across Firms: Implications for Labor-Market Polarization" Journal of Monetary Economics 2025.
DOI: 10.17632/yfj23j4wy2
title: Data Penjualan Kain Mingguan (Transformasi Skala 0,1)

description: Data penjualan kain mingguan Toko Cahaya Sandang yang telah ditransformasi ke dalam rentang 0 sampai dengan 1
DOI: 10.17632/z6m5ynr4wf
title: UAVs

description: Data for UAV trade
DOI: 10.6084/m9.figshare.14448249.v1
title: Phylogenomic disentangling of the Bifidobacterium longum subsp. infantis taxon

description: Supplementary Material for ‘Phylogenomic disentangling of the Bifidobacterium longum subsp. infantis taxon’ as published in <i>Microbial Genomics</i>.<br>
DOI: 10.6084/m9.figshare.23739690.v1
title: Dataset for "Photo identification for sea turtles: Flipper scales more accurate than head scales using APHIS"

description: Photo ID database of 51 individuals, each with two complete sets of photos. All turtles were juveniles or sub-adults with straight carapace lengths (notch to notch) ranging from 23 to 61 cm (41 ± 1.2 cm; mean ± sd).
DOI: 10.6084/m9.figshare.28521613.v1
title: Supplementary Material from Insufficient wing development possibly contributes to flightlessness of the silkworm Bombyx mori during domestication

description: Wang_et_al_Supplementary figures_tables_videos_ESM for_Insufficient wing development possibly contributes to flightlessness of the silkworm Bombyx mori during domestication.pdf.rar
DOI: 10.17632/7x5t3rxx5f
title: Production data from a small bakery manufacturing line

description: Finding an optimal production schedule is a crucial part in improving manufacturing efficiency. Data collected from a real production line serves as the process's starting point. It provides details on the products, the processing procedures, how long they take, and the machines needed to carry out these steps. The production schedule is simulated using a flow shop model. The manufacturing environment determines the sort of flow shop model. The simplest model is a permutation flow shop, where all products are processed by machines in the same order. The majority of production systems in practice contain numerous distinctive constraints that make models quite complex. The "no-wait" flow shop model refers to a particular type of flow shop model where no waiting period is permitted between two successive stages of a product.
A hybrid no-wait flow shop scheduling model can be used to explain the production environment in bakeries. Multiple machines are accessible here for a single processing stage, such as oven A or oven B for baking a product. Products' processing stages may not be organized in the same order depending on the recipe. Occasionally, the same dough is used to make several different bakery products. In these situations, bakers divide the dough after a few preliminary processing steps and carry out the remaining steps independently in accordance with the product recipes. Baking ovens need a lot of energy, and using them even when only partially occupied wastes energy. Therefore, in order to conserve energy, baking of a number of products may occasionally be conducted together that followed separate processing paths. The products are arranged into groups based on their inherent interdependence, such as baking or beginning steps being performed concurrently. At any stage of the production process, one product from this group may be processed. However, it influences the start time for the remaining products in the same group. Small and medium-sized bakeries rely on manual operation for many processing tasks. Therefore, manual tasks must be distributed among staff in order to continue the production without interruption. Some processing tasks need the use of two machines, or one machine and one employee at the same time. To prevent ingredient mixing, a machine may need to be cleaned after processing a product. For instance, after kneading dough containing oil seeds, a kneader is cleaned.