cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19726945.v1
title: Improving Spectrum-Based Localization of Multiple Faults by Iterative Test Suite Reduction

description: Artifact and replication package for "Improving Spectrum-Based Localization of Multiple Faults by Iterative Test Suite Reduction" (ISSTA 2023).
DOI: 10.6084/m9.figshare.21173860.v1
title: Supplementary Table 5

description: Screening candidate robust, mouse-preference and rat-preference DEGs in rodent DRGs following peripheral nerve injury
DOI: 10.6084/m9.figshare.29114567.v2
title: <b>How do Large Language Models Understand Trajectory Data? Insights from Various Trajectory Formats</b><b>and Response Strategies for Transportation Mode Detection</b>

description: The effectiveness of large language models (LLMs) in transportation mode detection remains underexplored, creating a significant research gap in understanding how these models process trajectory data. This study uses the Geolife dataset to investigate the ability of pre-trained and fine-tuned LLMs to detect transportation modes across 14 trajectory formats, categorized into overview information, coordinate-based, and spatial encoding. Meanwhile , two response strategies are compared: direct answer and Chain-of-Thought (CoT) reasoning. The results show that fine-tuning significantly enhances the classification performance for all trajectory formats. Among the evaluated formats, the coordinate-based format with timestamps achieves the highest accuracy of 85.2% after fine-tuning using the direct answer strategy. The direct answer strategy proves to be more effective than the CoT strategy, reaching an average 49.0% improvement in accuracy via fine-tuning. Additionally, the model exhibits systematic misclassification patterns, reflecting challenges in distinguishing between transportation modes with similar movement characteristics. Furthermore, our analysis reveals that hallucinations are prevalent in CoT responses, particularly of the types of input-conflicting hallucinations and factual inaccuracies, which increase the likelihood of misclassification. These findings highlight the potential of LLMs in transportation mode detection while emphasizing the need for enhanced trajectory formats, improved response strategies, and strategies to mitigate hallucinations.
DOI: 10.17632/p365kxw2wm
title: Data for: Multivariate interpolation and machine learning models for extreme defects-based fatigue life prediction of Ti6Al4V specimens fabricated by SLM

description: Data for the paper:

"Multivariate interpolation and machine learning models for extreme defects-based fatigue life prediction of Ti6Al4V specimens fabricated by SLM"
by: J. Horňas, A. Materna, J. Glinz, M. Yosifov, S. Senck

DOI: https://doi.org/10.1016/j.engfracmech.2024.110756

The paper proposed a novel methodology for extreme defects-based fatigue life prediction of Ti6Al4V specimens fabricated by selective laser melting (SLM) technique. The introduced framework is represented by a combination of a traditional ranking method based on the extreme values of stress intensity factor with related defect parameters (size, distance from the free surface, sphericity and compactness), training set augmentation using variational autoencoder (VAE) and various data-driven models (multivariate interpolation and machine learning algorithms). The defects were observed using micro-computed tomography (µ-CT) prior to the fatigue tests. 

The following data are shared:

1) Experimental (raw) dataset:
 Experimnetal_Raw_Dataset.csv

2) Experimental (features scaled by Min-Max normalization) dataset:
 Experimnetal_Scaled_Dataset.csv 

3) Experimental training set (features scaled by Min-Max normalization):
 Experimental_Training_Set.csv

4) Augmented training set generated by variational autoencoder (VAE):
 Augmented_Training_Set_by_VAE.csv

5) Final training set (experimental + augmented):
 Final_Training_Set.csv

6) Training subsets for features (X) and target (y) during hyperparameters tuning using tree-structured Parzen estimator (TPE) with 23-fold cross-validation (CV):
 X_Training_Subset_Cross_Validation_Number_01.csv,
 ... ,
 X_Training_Subset_Cross_Validation_Number_23.csv

 y_Training_Subset_Cross_Validation_Number_01.csv,
 ... ,
 y_Training_Subset_Cross_Validation_Number_23.csv

7) Validation subsets for features (X) and target (y) during hyperparameters tuning using tree-structured Parzen estimator (TPE) with 23-fold cross-validation (CV):
 X_Validation_Subset_Cross_Validation_Number_01.csv,
 ... ,
 X_Validation_Subset_Cross_Validation_Number_23.csv

 y_Validation_Subset_Cross_Validation_Number_01.csv,
 ... ,
 y_Validation_Subset_Cross_Validation_Number_23.csv

8) Training sets of features (X) and target (y) for models with tuned hyperparamaters:
 X_Training_Set.csv
 y_Training_Set.csv

9) Test sets (unseen data) of features (X) and target (y) for final evaluation of prediction accuracy:
 X_Test_Set.csv
 y_Test_Set.csv
DOI: 10.6084/m9.figshare.12226826.v1
title: Thompson et al. 2020. Ethology Data

description: Datasets to reproduce results from: Thompson, MJ. Pearse, KA. Foote, JR. 2020. Ethology. Seasonal and diel plasticity of song type use in individual ovenbirds (Seiurus aurocapilla).
DOI: 10.6084/m9.figshare.22262545.v7
title: A history reconstructed time series (1992-2011) of annual global NPP-VIIRS-like nighttime light data through a super-resolution U-Net model

description: The dataset is an extend time series of the Version 2 annual NPP-VIIRS nighttime light composites. 

 The dataset contains (1) simulated NPP-VIIRS NTL time series from the DMSP-OLS NTL data (1992-2011) based on a super-resolution U-Net method; and (2) the version 2 annual NPP-VIIRS NTL data (2012-2020), which were obtained from the academic sector at the Colorado School of Mines (https://eogdata.mines.edu/products/vnl/). The pixels of which value less than zero were set to zero. 
 The dataset are 15 arc second grids, spanning -180 to 180 degrees longitude and -65 to 75 degrees latitude.
 Each zip file contains an NTL image in geotiff format. The filename of each image is "SRUNet_NPP_VIIRS_V2_Like_yyyy", where "yyyy" is the year of the image.
 The simulated NPP-VIIRS NTL data converted from the DMSP-OLS NTL data in 2012 and 2013 are also uploaded, which named "simulated_NPP_VIIRS_V2_yyyy".
 Based on the super-resolution deep learning technology, the dataset using DMSP-OLS NTL data and Landsat NDVI to reconstruct the NPP-VIIRS NTL data in the early years (1992-2011). The dataset could be easily updated by downloading the version 2 annual NPP-VIIRS NTL data in later years from the academic sector at the Colorado School of Mines (https://eogdata.mines.edu/products/vnl/). The dataset has good spatial pattern and temporal consistency, and is highly consistent with NPP-VIIRS NTL data. It provide a longer time period compared to existing products.
 Compared with the annual NPP-VIIRS NTL data in 2012, the dataset shows a good consistency at the pixel, city, province and nation levels with R2 of 0.617, 0.747, 0.874, and 0.964, respectively, while the R2 of the NPP-VIIRS-like NTL product provide by Chen (2020) is 0.512, 0.694, 0.86, and 0.966, respectively.
DOI: 10.6084/m9.figshare.24919956.v1
title: raw_count_table_COMMON_GN.txt

description: Raw count table of the included samples of our publication "<b>Identification of conserved gene expression changes across common glomerular diseases by spatial transcriptomics</b>"
DOI: 10.6084/m9.figshare.25377766.v2
title: Variation in self-directed behaviors prior to acting offers insights into decision-making and social style in wild Tibetan macaques

description: An ability to recognize individuals and effectively manage social relationships is critical for species living in a complex social environment. Here, we used a focal sampling method to record and analyze rates of self-directed behavior (hereafter SDB, an indicator of anxiety, frustration, and stress that includes self-scratching) in wild Tibetan macaques (<i>Macaca thibetana</i>) prior to approaching another group member. Our goal was to examine the ability of Tibetan macaques to retain and use information on rank and kinship in social decision-making. Specifically, we examined the five minute period prior to approaching a conspecific in order to determine (1) whether individuals who make a decision to approach a conspecific were characterized by an increase in SDB compared to individuals who did not approach a conspecific; (2) the degree to which rank, sex, and kinship had an effect on making a decision to approach, and (3) whether individuals who waited longer to make a decision to approach were characterized by an increase in SDBs. Our results indicate that: (1) individuals who approached a conspecific were characterized by higher rates of SDBs compared to social settings in which a Tibetan macaque did not approach another group member; (2) prior to approaching a higher-ranking group member of the same sex, both the males and females exhibited higher rates of SDBs than when approaching a lower-ranking group member; (3) Females showed no differences in the rate of SDBs prior to approaching a female close kin (sister or mother/daughter) compared to approaching an unrelated or distantly related female; (4) lower-ranking adult males were found to exhibit higher rates of SDBs before approaching a receptive female than did higher ranking males; (5) adult females did not exhibit increased rates of SDBs during the first four minutes prior to approaching a higher-ranking female regardless of kinship, however, their rate of SDBs did increase significantly in the last minute (minute 5) prior to an approach. These results indicate that the social decision-making in both adult male and female Tibetan macaques is associated with a increase in rates of SDBs. Given differences in patterns of social decision-making it appears that Tibetan macaques have sex-specific social styes, with males exhibiting a moderately despotic social hierarchy and females exhibiting a moderately tolerant social hierarchy.
DOI: 10.6084/m9.figshare.26788981.v1
title: Supplementary Material for: Exploring the Impact of Age and Pre-Stroke Modified Rankin Scale in Elderly Thrombectomy: a 15-year Single Center Experience

description: Introduction: The selection of endovascular treatment (EVT) for acute ischemic stroke in the elderly remains challenging due to the underrepresentation of these patients in landmark randomized trials. The aim of this study was to assess the association between age and the pre-stroke modified Rankin scale score with functional outcomes after EVT in elderly patients aged ≥80 years.
Methods: We prospectively collected data from consecutive elderly patients who underwent EVT of the anterior or posterior circulation at our institution between 2007 and 2022. Clinical and radiological parameters were analyzed using a fair outcome (mRS ≤ 3 or retained pre-stroke mRS score of 4) as the primary outcome.
Results: In total, 307 elderly patients were included in the analysis. Fair functional outcomes were achieved in 162 (53%) patients. Eighty-four (27.4%) patients were deceased at 3-month follow-up and the mortality rate increased to 37.1% (114 deceased) at 1-year follow-up. The likelihood of achieving fair functional outcome decreased by 8% for every 1-year age increase (OR 0.81, 95% CI 0.73-0.90). Lower National Institutes of Health Stroke Scale (OR 0.89, 95% CI 0.85-0.93, p&lt;0.001) and pre-stroke mRS (OR 0.67, 95% CI 0.53-0.84, p&lt;0.001) were associated with fair outcomes.
Conclusion: EVT in elderly patients with stroke is beneficial in selected cases. Increasing age was associated with an increased risk of an mRS change to 4 or worse and death within 1 year. The pre-stroke mRS may aid clinicians in the selection of elderly patients for EVT.
DOI: 10.17632/ndyy8nz77x
title: Ocean Hazards Database (OHD) for the State of Hawaii Maui County Coastal Roads Report

description: This Maui County-adapted Ocean Hazards Database (OHD) contains all relevant geographic information system (GIS) layers, maps, and tables from the Maui County-adapted Ocean Hazards Classification Scheme (OHCS) assessments of 157 CRESI transects across coastal roads on the islands of Maui and Molokai. As a part of the State of Hawaii Maui County Coastal Roads Report, the Maui County-adapted OHCS assesses and ranks shoreline roadway exposure to ocean hazards based on the variables of historical sea-level rise (SLR) rates (in/yr), projected SLR rates by 2060 and 2100 (in/yr), mean tidal ranges (ft), maximum annually recurring peak wave periods (sec) and significant wave heights (ft), mean projected shoreline change rates (ft/yr), historical and hypothetical tsunami flow depths (ft), and modeled category 1-4 storm surge inundation heights (ft). Maui County-adapted OHCS ranking criteria and methods are described in Chapter 3 of the State of Hawaii Maui County Coastal Road Report (Francis et al., 2024). Maui County-adapted OHD materials are organized into Maui County Coastal Digital Elevation Models, Maui County Ocean Hazard Map Packages, Maui County Ocean Hazard Maps, Maui County Ocean Hazard Tables, and Maui County Coastal Roads Report 'CRESI Transect Locations'. 

How to Download:

Maui County Coastal Digital Elevation Models: Please refer to the 'Maui County Coastal Digital Elevation Models-README.docx'.

Maui County Ocean Hazard Maps: Please refer to the 'Maui County Ocean Hazard Maps-README.docx'.

Maui County Ocean Hazard Map Packages (.mpkx), below, contain GIS layers for the assessments of SLR inundation, wave properties, projected shoreline change, modeled storm surge inundation, and topo-bathymetric transects. 

Maui County Ocean Hazard Tables (.pdf), below, contain Maui County-adapted OHCS measurements for 157 CRESI transects across coastal roads on Maui and Molokai. Representative dataset references are included in table footnotes. 

Maui County Coastal Roads Report 'CRESI Transect Locations' (.kmz, .xlsx, .mpkx), below, contains the location information, in different formats, of the 157 CRESI transects. 

This project was funded by the Hawaii Department of Transportation, HWY-L 2.3089.

References
Francis, O., Zhang, G., Ma, D., Robertson, I., Togia, H., Yang, L., Eyre, K., Rossi, C., Martinez, B.A., Han, R., Hataishi, M., Hunter, N., Takahashi, C., Wang, Y., Yang, H., Zhou, S., & Yuan. R. (2024). State of Hawaii Maui County coastal roads report. Prepared for the Maui County and State of Hawaii Department of Transportation, Project number HWY-L 2.3089, February 26, 2024.
DOI: 10.17632/ttbtymk4gm
title: Moralization of Obesity

description: This data corresponds to 3 studies conducted on moral attitudes toward obesity and the consequences of moral attitudes in this area.
DOI: 10.17632/zwshr65gnc
title: A Data-set about Surface Damage Identification for Heritage Site Protection: A Mobile Crowdsensing Solution Based on Deep Learning

description: The dataset has been collected to address the general problem of built heritage protection against both deterioration and loss. In order to continuously monitor and update the structural health status, a crowd-sensing solution based on powerful and automatic deep learning technique is proposed. The aim of this solution is to get rid of the limitations of manual and visual damage detection methods that are costly and time consuming. Instead, automatic visual inspection for damage detection on walls is efficiently and effectively performed using an embedded Convolutional Neural Network (CNN). 
This CNN detects the most frequent types of surface damage on wall photos. The study has been conducted in the Kasbah of Algiers where the four following types of damage have been considered: Efflorescence, Spall, Crack, and Mold. The CNN is designed and trained to be integrated into a mobile application for a participatory crowd-sensing solution. The application should be widely and freely deployed, so that any user can take a picture of a suspected damaged wall, and get an instant and automatic diagnosis, through the embedded CNN. 
In this context, we have used MobileNetV2 with a transfer learning approach. A set of real images have been collected and manually annotated, and have been used for training, validation, and test. Extensive experiments have been conducted in order to assess the efficiency and the effectiveness of the proposed solution, using a 5 fold cross validation procedure. 
Obtained results show in particular a mean weighted average precision of 0.868±0.00862 (with a 99% of confidence level) and a mean weighted average recall of 0.84±0.00729 (with a 99% of confidence level). Obtained results show that our method remains effective even when using a small network and medium to low resolution images. 

In order to provide the CNN to be deployed, as well as the dataset used for the test, to the researchers, we have made them available online. Also a source code to perform a quick test on Google Collaboratry is available. The model has been saved in Keras "h5" format, and also in a TensorFlow Lite "tflite" format, ready to be deployed on a mobile application. 

Files published are:
 - "Test_Kasbah_damage.ipynb": python source code to perform the test, in Google Collaboratry.
 - "multi_label_CV_final.h5": the CNN saved in a h5 keras format, to be used for the test, and other purposes. 
 - "test_multi_label.zip": the test dataset used in the paper, saved in a zip compressed file (634 images). 
 - "multi_label_CV_final.tflite" : the CNN saved in a tflite format, ready for deployment in a mobile application.
DOI: 10.6084/m9.figshare.10253291.v2
title: TOFF Data Release

description: The data release of behavioral, morphological, phenological, and physiological (BMPP) traits and associated environmental characteristics available in TOFF. Retrieved 2019-07-16.<br>The archive includes three files:<br>- The file Data_Release_TOFF_1.csv displays BMPP information- The file Data_Release_TOFF_2.csv displays environmental characteristic information- The file R-Script_TOFF_Data_Release.r displays the R-script used to produce the data release
DOI: 10.6084/m9.figshare.26394561.v1
title: CIF file of complex 2 from Ruthenium(II) complexes of curcumin and β-diketone derivatives: Effect of structural modifications on their cytotoxicity

description: CIF_Ru2.cif
DOI: 10.6084/m9.figshare.7938500.v1
title: gVCF_NA12156

description: 1000 Genomes gVCF mapped to hs37d5 for NA12156. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
DOI: 10.17632/kc963nv55y
title: Import Substitution in Illicit Methamphetamine Markets Replication Package

description: Files necessary to replicate "Import Substitution in Illicit Methamphetamine Markets," by Leandro Freylejer and Scott Orr. Replication folder includes all code and data that may be shared publicly, as well as a "Read me" (readme.pdf) which describes how to use the replication file, and how to request any data that cannot be shared publicly.
DOI: 10.6084/m9.figshare.12292490.v3
title: fortedata-1.0.1

description: This repo contains all level one (formatted for broad audience use) data products associated with version 1.0.1 of the fortedata package (https://github.com/FoRTExperiment/fortedata)--which contains data from The Forest Resilience and Threshold Experiment (FoRTE).<br><br>* This repo has been updated with a readme file that fully details the files contained within. <br><br><br>
DOI: 10.6084/m9.figshare.19601689.v3
title: Hydrogen Combustion using IRC, AIMD and normal modes

description: The generation of reference data for deep learning models is challenging for reactive systems, and more so for combustion reactions due to the extreme conditions that create radical species and alternative spin states during the combustion process. Here, we extend intrinsic reaction coordinate (IRC) calculations with <em>ab initio </em>Molecular dynamics (AIMD) simulations and normal mode displacement calculations to more extensively cover the potential energy surface for 19 key reaction channels involved in hydrogen combustion. A total of ~290,000 potential energies and ~1,260,000 nuclear force vectors are evaluated with a high quality range-separated hybrid density functional, ωB97X-V, to construct the reference data set, including transition state ensembles, for the deep learning models to study hydrogen combustion reaction.
DOI: 10.6084/m9.figshare.21786005.v2
title: Smart Elderly Care Review Data

description: The data extracted from WOS and CNKI The data processed by CiteSpace
DOI: 10.6084/m9.figshare.24029778.v1
title: Strong ethanol- and frequency-dependent ecological interactions in a community of wine-fermenting yeasts

description: 1 – All pairwise coculture outcomes in gewürztraminer and the pairwise competitive scores calculated from those outcomes. The number represents the final fraction of the species in the first column when co-cultured as the initially dominant species (99% of cells) with the species in the second column. Each outcome is replicated across three different experiments.2 – All five-species co-culture results in gewürztraminer and merlot, including raw counts and percent abundance data. DF is the dilution factor used before plating (i.e. DF 4 means the community was diluted by a factor of 10-4 before plating).3 – Growth rate and carrying capacity data for each species at each ethanol percentage alongside the pairwise and five-species competitive scores.FiguresCode: The R code used to produce each main text figureInputData: A zip file of the all the input files for FiguresCodeSource Data for Figures 2-6: An Excel file with all of the source data for the figures
DOI: 10.6084/m9.figshare.28268504.v1
title: Sustainable Supply Chains Papers indexed in Scopus (2002-2024)

description: Database with 1501 publications indexed in Scopus (2002–2024) on Sustainable Supply Chains.
DOI: 10.17632/9y7x95kcyn
title: The Climate Change Risk Awareness Scale

description: Items were created for the development of the Climate Change Risk Awareness Scale. The content of the scale was created in 3 dimensions as ‘Safety and Health Awareness’ (8 statements), ‘Productivity and Stress Awareness’ (6 statements), ‘Adaptation and Adaptation Awareness’ (7 statements). The created items were brought together with the users on the online platform and this table was obtained.
DOI: 10.6084/m9.figshare.1451426.v1
title: netflix.part02.rar

description: This dataset was constructed to support participants in the Netflix Prize.
DOI: 10.6084/m9.figshare.20381274.v2
title: Gapless genome assembly of East Asian finless porpoise, Neophocaena asiaeorientalis sunameri

description: There are the genome sequence, gene set, coding sequence and protein sequence of Neophocaena asiaeorientalis sunameri.
DOI: 10.6084/m9.figshare.22691215.v2
title: Untitled Item

description: The MIDOG++ dataset represents an extension of the data set used in the MIDOG 2021 and 2022 challenges. We provide region of interest images from 503 histological specimens of seven different tumor types with variable morphology: breast carcinoma, lung carcinoma, lymphosarcoma, neuroendocrine tumor, cutaneous mast cell tumor, cutaneous melanoma, and (sub)cutaneous soft tissue sarcoma. The human and canine samples were processed and stained at different human and veterinary pathology laboratories with standard H&E dye and digitized with different digital whole slide image scanners. We provide labels for 11,937 mitotic figures that have been differentiated against 14,351 imposter cells in a blinded consensus by two pathologists and a final decision by a third pathologist for disagreed labels.
DOI: 10.6084/m9.figshare.24993570.v1
title: Table 2.docx

description: <b>Table 2. Primers used for PCR.</b>
DOI: 10.6084/m9.figshare.27960579.v1
title: Supplementary material

description: Supplementary materials linked to upcoming publication "Molecular Markers Enhance Substantially the Distinctness of Alfalfa Varieties for Registration and Protection", on The Plant Genome
DOI: 10.6084/m9.figshare.28190393.v3
title: Ormosia_boluoensis_genome

description: Ormosia boluoensis genome, annotation and SNP
DOI: 10.6084/m9.figshare.7667732.v1
title: Chapter 2

description: Tables S1-6<br>