cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.25517224.v1
title: Gun Violence - All Shootings

description: The data on all shootings is from https://www.gunviolencearchive.org/ . This dataset on all shootings for the period 2014-2023 was provided on March 25, 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. The variables are self-explanatory.<br><br>For information of how this data is collected, go to: https://www.gunviolencearchive.org/explainer<br>
DOI: 10.6084/m9.figshare.28985708.v1
title: Results Table – Systematic Mapping Study on Low-Fidelity Prototyping Tools

description: This table presents the results of a Systematic Mapping Study (SMS) focused on identifying and characterizing low-fidelity prototyping tools in terms of their functionalities, limitations, and applicability. The study reviewed 1493 publications retrieved from Scopus, IEEE Xplore, ACM Digital Library, and ScienceDirect, from which 37 studies were selected based on inclusion and exclusion criteria. A total of 22 tools were identified, with Figma, Balsamiq, and PowerPoint being the most frequently cited. The table summarizes key findings, including the limited integration of emerging technologies such as artificial intelligence, reduced functionality in tools dedicated solely to low-fidelity prototyping, and the lack of structured design guidelines, which often leaves quality assurance to the discretion of software professionals.
DOI: 10.6084/m9.figshare.28991807.v2
title: Whole-Slide CD8 IHC Data and Tissue Annotation Data (HALO)

description: The enclosed folders contain <b>CD8 IHC data for</b> <b>each</b> <b>whole-slide specimen</b> included in the present study. Cases are distinguished <i>numerically</i>, while redundant tissue blocks from a given case are distinguished <i>alphabetically</i>.Each whole-slide tissue specimen has a folder that contains CD8 IHC positive cell coordinates obtained from HALO (<b>Object_Data.csv</b>) and annotation data exported from HALO (<b>Annotations.annotations</b>). Annotation data can be read as XML files and interpreted in well-known text format.The HALO output for the corresponding TMA is included, alongside a map of the core positions relative to the whole-slide tumour border.
DOI: 10.6084/m9.figshare.5885215.v1
title: Data Director Guide

description: Data directory
DOI: 10.17632/5vcxb928rz
title: Impact of GenAI on ideation and innovation team performance

description: This dataset accompanies the study titled "The Impact of Generative Artificial Intelligence on Ideation and the Performance of Innovation Teams" by Michael Gindert and Marvin Lutz Müller. The research investigates how a Generative AI (GenAI)-augmented ideation tool affects ideation quality, efficiency, and team dynamics within a structured innovation process. Utilizing the Knowledge Spillover Theory of Entrepreneurship (KSTE) as a framework, the data highlights the influence of AI on knowledge generation, transfer, and application during the ideation phase. A framed field experiment has been conducted. Two groups (experiment and control) had to ideate on two destinct innovation tasks. The experiment group used an AI augmented ideation tool, that has been developed for the study.

Hypotheses: The dataset supports the testing of six main hypotheses concerning the application of large language models (LLMs) during ideation in team settings:

H1: AI-augmented teams will produce higher-quality ideas due to enhanced knowledge spillover.
H2: AI support will accelerate the ideation process.
H3: Teams using AI will exhibit greater efficiency in idea generation.
H4: AI-assisted teams will produce a more diverse set of ideas, in terms of novelty and feasibility.
H5: AI-enhanced ideation increases the likelihood of generating revolutionary ideas.
H6: AI-supported ideation will positively impact team satisfaction and engagement.
Data Highlights and Findings:

Idea Quality: The dataset includes quality assessments of ideas based on originality, feasibility, and clarity, revealing that AI-augmented teams consistently generated higher-quality ideas across various dimensions.
Process Speed and Efficiency: Time measurements show that teams with AI support completed ideation tasks significantly faster than the control group, reducing ideation time by up to 30%.
Diversity and Novelty: Evaluations indicate that ideas produced with AI support exhibited greater diversity in both approach and innovation potential, contributing to more revolutionary solutions, especially for complex problems in healthcare and automotive sectors.
Team Satisfaction: Survey data suggest that team members in the AI-augmented condition reported higher levels of engagement and satisfaction, with a 23.3% increase in positive feedback compared to the control group.
DOI: 10.17632/xz6c2bp5d8
title: Pairs Trading: Replicating Gatev, Goetzmann and Rouwenhorst (2006) published at Open Code Community

description: Material published at https://opencodecom.net/
DOI: 10.6084/m9.figshare.13022837.v1
title: CESM-RESFire climate sensitivity results

description: The data with corresponding NCL/Python scripts used for generating figures in the main text of our manuscript have been archived and deposited here for the purpose of reproduction and evaluation. The raw modeling outputs are too large to be deposited to this repository. These data are archived on the High Performance Storage System (HPSS) managed by the National Energy Research Scientific Computing Center (NERSC). Only indexing files of the compressed raw modeling outputs are deposited here for reference purposes. Please contact the corresponding authors of the manuscript to get access to the raw modeling data if needed.
DOI: 10.6084/m9.figshare.21280152.v7
title: Raw Data

description: the data contains raw data as values of depth of sealer penetration into the dentinal tubules measured by an in built ruler in mm in Confocal Laser Scanning Microscopy. <br> The data contains an image of coronal, middle and apical third sections of the root specimen.
DOI: 10.6084/m9.figshare.24199176.v7
title: Abundance of ground-level ice-nucleating particle and aerosol properties during autumn at contrasting marine and terrestrial locations

description: The ambient concentration data of ice-nucleating particles was collected at two contrasting sites, one in the Southern Great Plains region of the United States with a substantial terrestrially influenced aerosol population, and one in the Eastern North Atlantic area with a primarily marine-influenced aerosol population. The 6-hour time-averaged data was collected from each site, the first from October 1 – November 15, 2019, in Oklahoma, USA, and the second from October 1, 2020 – November 30, 2020, on Graciosa Island, Azores. These datasets were collected to comprehensively understand the difference or similarity in the particle source(s) as well as aerosol-cloud interactions in the atmosphere in association with other ambient observations at these sites. For both sites, the abundance data was taken with online monitors and complementary measurements of ice-nucleating particles by means of offline droplet freezing assay. A total of 10 datasets is provided (the metadata and data matrices are separated). An individual method-oriented data abstract is available in each metadata.
DOI: 10.6084/m9.figshare.15132081.v4
title: Tyrosine_ExcitedStates

description: Data set to train 29 spin-mixed excited states of tyrosine. Reference method is ADC(2)/cc-pVDZ. The data includes augmented data based on CASPT2(12,11)/ano-rcc-pVDZ.initconds.excited for initiating dynamics of tyrosine according to Ref. https://arxiv.org/abs/2108.04373
DOI: 10.6084/m9.figshare.6292187.v1
title: The relationship of ungulate δ13C and environment in the temperate biome of southern Africa, and its palaeoclimatic application

description: Supporting dataset for <b>"The relationship of ungulate d13C and environment in the temperate biome of Southern Africa, and its palaeoclimatic application" </b><b><br></b><i>Paleoclimatology, Paleoecology, Paleogeography </i>Vol 514, pp. 282-291<br><i><br></i>Julie Luyt*<sup>#</sup>, Vincent J. Hare*, Judith Sealy*<br>*Department of Archaeology, University of Cape Town<sup>#</sup>NRF-DST Centre of Excellence in Palaeosciences
DOI: 10.17632/b46c6c9fj9
title: Synthetic Optical Network Dataset with Q-Factor, BER, and Receiver Sensitivity Metrics under EDFA-FBG Conditions

description: This dataset presents a large-scale synthetic simulation of performance parameters in fiber-optic communication systems, specifically designed to evaluate the impact of EDFA (Erbium-Doped Fiber Amplifier) and FBG (Fiber Bragg Grating) components under varying transmission distances and conditions. The dataset comprises 1,000,000 rows of simulated records, each capturing key optical network metrics including Q-Factor, Bit Error Rate (BER), and Receiver Sensitivity for both downstream and upstream transmission directions.

The core objective of this dataset is to provide a controlled and reproducible framework for studying how signal quality degrades or improves under different fiber distances and the presence or absence of EDFA/FBG devices. The dataset generation process was carefully crafted using stochastic modeling based on empirical trends observed in real-world optical experiments. The following parameters are included in the dataset:

- Distance_km: The length of the optical fiber in kilometers. Values include typical transmission spans (0, 10, 20, 40, 45, 70, and 75 km).
- Q_Factor_Downstream and Q_Factor_Upstream: Quality factor metrics for downstream and upstream channels respectively. These values are adjusted based on the transmission distance and the presence of EDFA/FBG to reflect signal integrity.
- BER_Downstream and BER_Upstream: Bit Error Rates computed from the Q-factor using an exponential decay model that mimics realistic signal degradation in optical fibers.
- Receiver_Sensitivity_Downstream and Receiver_Sensitivity_Upstream: Values representing how sensitive the receiver is to signal quality degradation at different distances, influenced by the transmission condition.
- Power_Level_dBm: Simulated variation in power levels (in dBm) to account for fluctuations due to hardware or environmental conditions.
-mNoise_Factor: A synthetic noise parameter that introduces random variations to simulate physical imperfections and disturbances in signal transmission.
Condition: Indicates whether the data point is simulated under "No_EDFA_FBG" or "With_EDFA_FBG" conditions.


The dataset serves as a valuable resource for research in several domains including:

- Optical Network Simulation and Modeling
- Machine Learning for Optical Systems
- Performance Prediction and Optimization in Fiber-Optic Networks
- Benchmarking of AI-based Diagnostic Tools in Telecommunications

Researchers can use this dataset to train, validate, and benchmark machine learning models for signal classification, fault detection, adaptive modulation, or link quality prediction. The inclusion of both amplified and unamplified scenarios makes the dataset versatile for comparative studies and ablation analysis.

This synthetic dataset is fully reproducible, extendable, and free from real-world acquisition constraints, making it suitable for academic and industrial experimentation, prototyping, and algorithm development in next-generation optical communication systems.
DOI: 10.17637/rh.7499396.v1
title: Annealed YbTO

description: Crystal structure of pristine ytterbium titanate
DOI: 10.6084/m9.figshare.29122703.v1
title: Per-and Polyfluoroalkyl Substances (PFAS) detections in water and dragonfly samples collected in protected areas in the United States

description: We sought to address the prevalence of PFAS on protected lands and its geographic extent and to identify the ecologically relevant PFAS mixtures occurring in biota. To accomplish this, we leveraged a prominent monitoring and surveillance network in the US (the Dragonfly Mercury Project; DMP) to evaluate PFAS exposure across Federally protected lands.
DOI: 10.17632/5y2fypw75g
title: Se in soil by LIBS calibration

description: This data is intended for LIBS determination of selenium in soil on the following types of samples: loose soil powder, soil fixed on adhesive tape and soil tablets. The LIBS spectra of soil samples with selenium content &lt;0.5 and 5, 15, 40, 115, 230, 460 mg/kg are presented here. File names content the following designations: 0.00%Se means that sample content &lt;0.5 mg/kg of Se; 0.001%, 0.003%, 0.008%, 0.025%, 0.050%, 0.100% mean that sample content 5, 15, 40, 115, 230, 460 mg/kg of Se respectively.
DOI: 10.17632/6zpxp6rxsx
title: Source Files for Compressive Creep Test Rig for Thermoplastic Samples

description: These data are source files associated with the HardwareX journal article "Compressive Creep Test Rig for Thermoplastic Samples." The repository includes one Fusion360 CAD file and six .svg files. The Fusion360 CAD file depicts the assembled creep test rig and each object's name begins with the ID number from the bill of materials in the journal article. The .svg files are patterns that can be used with a laser cutter to make the creep test rig's acrylic panels.
DOI: 10.17632/tydm5585bj
title: COPUS Data from Rwandan Secondary Schools

description: This Dataset is associated with the Classroom Observation Protocol for Undergraduate STEM (COPUS) collected from Rwandan secondary schools in 2019. Three files show the reliability analysis between two observers while another file contains raw and analyzed data.
DOI: 10.6084/m9.figshare.16615951.v1
title: DSP analysis - Stroma Areactive Invasion Front Areas (SARIFA) – a new prognostic biomarker in gastric cancer related to tumor-promoting adipocytes

description: DSP transcriptome analysis: Stroma Areactive Invasion Front Areas (SARIFA) - ein neuer prognostischer Biomarker bei Magenkrebs im Zusammenhang mit tumorpromovierenden Adipozyten
DOI: 10.6084/m9.figshare.27255417.v1
title: Supplementary Material for: Perceptions and responses to diseases among patients with inflammatory bowel disease: text-mining analysis of posts on a Japanese patient community website

description: Introduction: Patients with inflammatory bowel disease (IBD) are increasingly using online platforms to communicate with other patients and healthcare professionals seeking disease-related information and support. Free-text posts on these platforms could provide insights into patients’ everyday lives, which could help to improve patient care. In this proof-of-concept study, we applied text-mining to extract patient needs from free-text posts on a community forum in Japan, and holistically visualized the patients’ perceptions and their connections, and explored the patient characteristic-dependent trends in the use of words.
Methods: Free-text posts written between May 11, 2020 and May 31, 2022 on the community forum were retrieved and subjected to text-mining analysis. Trends in the use of words were extracted from the posts for correspondence and co-occurrence network analyses using KH Coder open-source text-mining software.
Results: Seventy-four posts were analyzed. Using text mining methods, we successfully extracted and visualized a variety of patient concerns and their connections. The correspondence and co-occurrence analyses revealed patient segment-dependent trends in the use of words. For example, patients with a disease duration of ≤5 yrs were more likely to use words related to emotions or their desire to change or quit their job, such as ‘anxiety’ and ‘resignation.’ Patients with a disease duration of &gt;10 yrs were more likely to use words showing that they are finding ways to live with or accept their disease, and are getting used to the lifestyle but some patients continued to experience worsening disease.
Conclusions: We found that free texts posted on an IBD community forum can be a useful source of information to capture the wide variety of thoughts of patients. Text mining procedures can help to visualize the relative importance of the topics identified from free text posts. Our findings of this proof-of-concept study will be useful for generating new hypotheses to better understand and address the needs of patients with IBD.
DOI: 10.6084/m9.figshare.28536497.v1
title: Figure 4. Downstream Genes

description: <i>Hydroides elegans</i> RNAi
DOI: 10.6084/m9.figshare.29091176.v1
title: Social media & POIs data

description: Social media data of 50 IFSs, and their pois.
DOI: 10.6084/m9.figshare.7265564.v2
title: Bridging the gaps: using an NHP model to predict single dose radiation absorption in humans

description: <b>Purpose:</b> Design and characterization of a radiation biodosimetry device are complicated by the fact that the requisite data are not available in the intended use population, namely humans exposed to a single, whole-body radiation dose. Instead, one must turn to model systems. We discuss our studies utilizing healthy, unexposed humans, human bone marrow transplant patients undergoing total body irradiation (TBI), non-human primates subjected to the same irradiation regimen received by the human TBI patients and NHPs given a single, whole-body dose of ionizing radiation. <b>Materials and Methods:</b> We use Bayesian linear mixed models to characterize the association between NHP and human expression patterns in radiation response genes when exposed to a common exposure regimen and across exposure regimens within the same species. <b>Results:</b> We show that population average differences in expression of our radiation response genes from one to another model system are comparable to typical differences between two randomly sampled members of a given model system and that these differences are smaller, on average, for linear combinations of the probe data and for the model-based combinations employed for dose prediction as part of a radiation biodosimetry device. <b>Conclusions:</b> Our analysis suggests that dose estimates based on our gene list will be accurate when applied to humans who have received a single, whole-body exposure to ionizing radiation.
DOI: 10.17632/v36y3kd8zg
title: Data for: Enhanced online model identification and state of charge estimation for lithium-ion battery under noise corrupted measurements by bias compensation recursive least squares
DOI: 10.6084/m9.figshare.14406995.v3
title: Data Dictionary

description: Data dictionary for the study of factors predicting hospital readmission among Thais with post myocardial infarction<b><br></b><br>
DOI: 10.17632/b2nzxmr56s
title: Certified perovskite device data for "A data review on certified perovskite solar cells efficiency and I-V metrics: insights into materials selection and process scaling up"

description: This is the certified perovskite efficiency and I-V data set that accompanies the review "A data review on certified perovskite solar cells efficiency and I-V metrics: insights into materials selection and process scaling up". The data set contains the collected 69 certified devices in a total of 63 publications in the public domain from 2013 to 2020. The data set contains only independently certified Pb-based perovskite solar cells summarizing their efficiency, relevant I-V metrics, manufacturing processes and materials used. The authors intend to updating the data set when more certified devices results are avilable.
DOI: 10.17632/w7sdx55m7z
title: A Comprehensive Image Dataset of Plum Leaf and Fruit for Disease Detection and Classification

description: The Plum Leaf and Fruit Disease Dataset is a comprehensive collection of images designed to facilitate research in computer vision, machine learning, and deep learning for plant disease identification and classification. This dataset includes images of plum leaves and fruits affected by various diseases, enabling researchers to develop automated detection systems for early diagnosis and prevention in agriculture.

Original Dataset: 
- Number of images: 3,554
- Data format: .jpeg, .jpg

Processed Dataset: 
- Number of images: 3,554
- Data format: .jpg

Augmented Dataset: 
- Number of images: 18,000
- Data format: .jpg

Augmentation Techniques: 
1. Rotation; 2. Flipping; 3. Brightness; 4. Contrast adjustments; 5. Blurring; 6. Shearing; and 7. Scaling

Impact on Agricultural Disease Diagnosis:
- Early Disease Detection: Automating disease detection reduces dependency on manual inspection, allowing farmers to take preventive measures promptly.
- Precision Agriculture: AI-driven models assist in targeted pesticide application, reducing environmental impact and costs.
- Scalability & Deployment: The dataset can be used to develop real-time mobile applications for farmers, integrated with IoT-based smart farming systems.
DOI: 10.6084/m9.figshare.5127166.v1
title: Supplementary Material for: Anti-Tumor Necrosis Factor Therapy Inhibits Lung Metastasis in an Osteosarcoma Cell Line

description: <b><i>Background:</i></b> Osteosarcoma is the most common primary malignancy of bone, and patients often develop pulmonary metastases. In a previous study, tumor necrosis factor (TNF)-α treatment of human osteosarcoma cells increases their metastatic ability in an animal model. TNF-α can act as a tumor necrosis factor and also as a tumor-promoting factor. In the present study, the effect of a TNF-α inhibitor on osteosarcoma aggressiveness and pulmonary metastases was investigated in vitro and in vivo. <b><i>Methods:</i></b> The effect of infliximab, a TNF-α inhibitor, on a metastatic osteosarcoma 143B cell growth and motility was investigated in vitro. An orthotopic xenograft model of 143B cell growth and spontaneous metastasis in SCID mice was used to assess the in vivo effect of infliximab. <b><i>Results:</i></b> Infliximab greatly reduced cell motility and pulmonary metastases in 143B cells. The mechanism of pulmonary metastasis inhibition involved decreased expression of CXC chemokine receptor 4 (CXCR4), Rho (small GTPase protein), and its effector. <b><i>Conclusions:</i></b> These results suggest a novel role for TNF-α inhibition in the reduction or prevention of pulmonary metastases of osteosarcoma in this animal model. TNF-α inhibition may become a preventive therapeutic option for the pulmonary metastases of osteosarcoma. © 2014 S. Karger AG, Basel
DOI: 10.17632/6h69hdh5bg
title: Data for "Faithful interpretation of protein structures through weighted persistent homology improves evolutionary distance estimation"

description: Refers to the data used for the article identified in this title. The data consists of 518 protein families from ten major prokaryotic taxa (Bacillales, Bacteroidales, Corynebacteriales, Enterobacterales, Escherichia, Hyphomicrobiales, Methanococcales, Pseudomonadales, Sulfolobales, and Thermococcales), corresponding to 22,940 protein sequences and structures. More details on the content of each directory is provided in the readme.txt.
DOI: 10.6084/m9.figshare.1529824.v1
title: GCMS HepG2

description: GCMS data
DOI: 10.6084/m9.figshare.c.3796345_d11.v1
title: DD3 DD4 ablations raw videos (mock/DD3/DD4)

description: Raw videos of mock-, DD3- and DD4-ablated animals freely-moving on a bacterial lawn for 15 minutes, for the DD3/DD4-ablation experiment.
DOI: 10.17632/dpjtd87c2r
title: Data for: The Relationship between Crude Oil Exports, Crude Oil Prices and Military Expenditures in some OPEC Countries

description: Our data used in the study
DOI: 10.6084/m9.figshare.25009406.v1
title: Rapid Literature Review

description: Rapid Literature Review
DOI: 10.6084/m9.figshare.29067467.v1
title: American Mineralogical Crystal Structure Database in SQlite

description: This file contains CIF data from the American Mineralogical Crystal Structure database in SQLIte format for use by the Python libraries and applications larixite and xraylarch, see https://github.com/xraypy/larixite/
DOI: 10.6084/m9.figshare.5519992.v1
title: DMNH #35746

description: Fossil Ginkgo (CR 125) from Castle Rock
DOI: 10.6084/m9.figshare.7260965.v1
title: spectrophotometric data

description: Tables with spectrophotometric data of four Saffron Finches' body region<br>