cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/ydskdv2vrz
title: Transcriptomic, epigenomic and spatial metabolomic cell profiling redefines regional human kidney anatomy

description: Supporting figures and data to our manuscript entitled "Transcriptomic, epigenomic and spatial metabolomic cell profiling redefines regional human kidney anatomy".

Deposited files:
 Mendeley_Data_figures.pdf: Supporting figures related to main figures and supplementary figures.
 DEG_list.zip: DEG lists.
 MALDI_data.zip: Data matrices of our spatial metabolomics data.
 2111genes_metabolism_gene_list.txt: 2111 genes used that are associated with metabolic processes.
 RSEQC_log.txt: RSeQC output file in data preprocessing.
 macs2_output.zip: Peak calling output files (both for 189184 features and for peak calling on individual clusters).
DOI: 10.6084/m9.figshare.14534088.v2
title: Anemone nemorosa Norway data (NJB)

description: Dataset used for the manuscript 'Functional trait variation of <i>Anemone nemorosa</i> along macro- and microclimatic gradients close to the northern range edge', submitted to Nordic Journal of Botany
DOI: 10.17632/xr8fw85n65
title: Skin Diseases and Skin Cancer Recognition Dataset

description: • Skin diseases encompass a broad spectrum of conditions affecting the largest organ of the human body, ranging from common dermatological issues to more severe and potentially life-threatening disorders. Skin cancers, a subset of skin diseases, specifically involve the abnormal and uncontrolled growth of skin cells, often triggered by exposure to ultraviolet (UV) radiation, genetic factors, or environmental influences. Skin cancers, including melanoma, basal cell carcinoma, and squamous cell carcinoma, pose a significant health concern globally due to their prevalence and potential for metastasis. On the other hand, non-cancerous skin diseases, such as eczema, psoriasis, and acne, impact millions, affecting quality of life and sometimes leading to complications if left untreated. Research in this field is vital for understanding the complexities of skin diseases and cancers, developing effective detection methods, advancing treatment options, and ultimately improving outcomes for individuals affected by these conditions. • Early detection, accurate diagnosis, and targeted interventions are key elements in the ongoing efforts to mitigate the impact of skin diseases and cancers on public health. • In recent times, computer vision has shown great promise in conducting the classification and identification tasks of this kind. • Fifty seven distinct kinds of skin diseases and skin cancer are shown in this large dataset, which can be used to develop machine vision-based techniques. • In this dataset, there are 978 (primary source 90, secondary source 888) original images of skin diseases and skin cancer. Then, in order to increase the number of data points, shifting, flipping, zooming, shearing, brightness enhancement, and rotation techniques are used to create a total of 630 augmented images from these original images (primary source).
DOI: 10.6084/m9.figshare.1328636.v1
title: Study I - BFF data

description: The data from the Big Five Frequency Scales, as described in study I of Warfel (2015).
DOI: 10.6084/m9.figshare.16643302.v1
title: Supplementary Material for: Surgery for Combined Hamartoma of the Retina and Retinal Pigment Epithelium

description: There is no consensus on whether and when surgical treatment is indicated for combined hamartoma of the retina and retinal pigment epithelium (CHRRPE). We aim to discuss the benefits of surgical intervention and techniques that may improve the outcome. A 24-year-old man experienced progressive visual loss for 6 months in his left eye due to CHRRPE. At presentation, visual acuity was 1.3 LogMAR and fundoscopy revealed extensive tractional pre- and epiretinal membranes, subretinal exudation, and a vasoproliferative tumor in the inferior periphery. A complete vitrectomy was performed, while paying special attention to vitreous shaving at the vitreous base and removal of vitreoschisis-induced vitreous cortex remnants (VCR) from the retinal surface posterior to the vitreous base. Tractional membranes and internal limiting membrane were peeled, and the vasoproliferative tumor was excised. Silicone oil tamponade was removed 11 weeks after surgery. No intra- or postoperative complications occurred. Visual acuity improved to 0.8 LogMAR and remained stable for 48-month follow-up. Vitreoretinal surgery can prevent complications that occur with CHRRPE. In addition, visual function may improve even if the initial visual acuity is low. Timely and complete vitrectomy with extensive membranectomy and detection and removal of VCR is recommended to avoid complications in challenging CHRRPE.
DOI: 10.6084/m9.figshare.23997693.v1
title: Questionnaire.docx

description: Questionnaire of sleep study
DOI: 10.17632/fd5wd6wmdj
title: Parkinson’s Disease Detection Using Spiral Images (Hand Drawings)

description: Parkinson’s disease (PD), or simply Parkinson’s, is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. The symptoms usually emerge slowly, and as the disease worsens, non-motor symptoms become more common. The most obvious early symptoms are tremor, rigidity, slowness of movement, and difficulty with walking. Parkinson’s Disease can cause slow motor movements, depression, anxiety, sleep and sensory system disorders, behaviour changes etc. Environmental factors and Genetic Inheritance are amongst the major contributing factors for Parkinson’s disease. Spiral drawing is a skilled and complex coordinated motor activity. Therefore, it is treated as a sensitive motor assessment and a preliminary test for early symptoms of Parkinson’s disease. This article presents a solution for detecting Parkinson’s disease using Spiral Drawings and Convolutional Neural Networks (CNN). The Cainvas Platform is used for implementation, which provides seamless execution of python notebooks for building AI systems that can eventually be deployed on edge (i.e. an embedded system such as compact MCUs). The notebook can be found here. The flow of the article is as follows — Description of the Problem Statement The Dataset Data Augmentation CNN Model Architecture Training the Model Performance of Model Testing models on Images Conclusion Description of the Problem Statement The project aims at presenting a solution for Parkinson’s disease detection using Spiral Drawings and CNN. The main idea behind the implementation is to classify a person as Healthy or having Parkinson’s disease by looking at the Spiral Drawing made by the person. The Spiral Drawing created by a healthy person will look almost similar to a standard spiral shape. However, a spiral drawn by a person with Parkinson’s disease will highly deviate from a perfect spiral shape and look distorted due to slow motor movements and decreased coordination between hand and brain. The Dataset The dataset used here is the Parkinson’s Drawing Dataset present on Kaggle. The dataset can be accessed through this link. The dataset contains Spiral and Waves drawings made by healthy people and Parkinson’s disease infected people. In this article, only Spiral Drawings are used for classification. The dataset already contains the Train Set and the Test Set, so no need to manually split the dataset.
DOI: 10.17632/gtk67w9kp7
title: Exact shell solutions for conical springs. III.  Belleville springs with variable thickness

description: In the current dataset, we examine the Belleville spring with the variable thickness. The thickness is assumed to be variable along the meridional and parallel coordinates of conical coordinate system. The calculation of the Belleville springs includes the cases of the free gliding edges and the edges on cylindric curbs, which constrain the radial movement. The equations developed here are based on common assumptions and are applicable to the industrial calculations. There are 10 models with the different thickness distributions of the material thickness over the radius of the surface. For each model, the three load cases were simulated. One load case represents the freely gliding edges of the spring. Another load cases constrain the radial movement of inner or outer edge of the middle surface. The input files in ANSYS APDL language are saved for each model and each load condition. All APDL files are in the archive ANSYS.zip. The APDL files are used for the simulation with program ANSYS. The EXCEL files in the archive telle3.1.zip represent the results of finite-element simulations with the program ANSYS 2023.R2. The vertical reactions on the inner edge are stored in the file telle3.1.zip. These EXCEL data will be imported in MAPLE source file. With this MAPLE source file the comparison between the closed form solutions and finite-element analysis is performed.
DOI: 10.17632/pt32rrncdm
title: Modelling earthquake rupture rates in fault systems for seismic hazard assessment: the Eastern Betics Shear Zone.

description: This zip file contains all input files necessary to run the SHERIFS calculation performed in this study as well as the outputs (txt files, figures, etc.). This study was done with the latest SHERIFS version (1.1) available for free download and use at: https://github.com/tomchartier/SHERIFS. The file is structured in different folders as follows: Inputs such as fault geometry and properties, earthquake catalogue and completeness are located in the 'data' folder (SHERIFS-master\SHERIFS_V1_1\data). The parameters of the models set in our study (scaling laws, background seismicity ratio, fault rupture hypotheses, etc.) are located in the 'Model_EBSZ_1' folder (SHERIFS-master\SHERIFS_V1_1\Complete_EBSZ\Model_EBSZ_1). The different fault rupture hypotheses are separated in different folders named 'sc_Set_1' for hyp. 1, 'sc_Set_5' for hyp. 2, 'sc_Set_6' for hyp. 3 and 'sc_Set_7' for hyp. 4. All fault and multi-fault ruptures of each hypothesis are specified in the 'faults_n_scenarios.txt' file. The different source models (.xml) used to build the MFD of each hypothesis are located in the 'MFD_GR' folder of each set (SHERIFS-master\SHERIFS_V1_1\Complete_EBSZ\Model_EBSZ_1\bg_BG_1\WC1994_A_a\sc_Set_1\bmin_0.8_bmax_1.2\MFD_GR). Txt files of the sampling process and figures of the MFD target fitting of each hypothesis are also visibile in the 'Log' folder of each set (i.e. SHERIFS-master\SHERIFS_V1_1\Complete_EBSZ\Model_EBSZ_1\bg_BG_1\WC1994_A_a\sc_Set_1\bmin_0.8_bmax_1.2\MFD_GR\Log). Outputs of the calculations are located in the 'analysis' folder (SHERIFS-master\SHERIFS_V1_1\Complete_EBSZ\analysis). Inside this, the 'figures' folder is the one that contains the main figures of this study such as the MFDs of each hypothesis, the catalogue MFD, maps of the multi_fault ruptures (FtF) and their NMS distribution. Figures such as participation rates and comparison with paleoseismic data are included (i.e. 'rupture_rate_for_each_fault_cum' folder) as well as additional figures that have not been used in our study. The 'txt_files' folder contains raw data on the MFDs of the different models, slip rate distribution on the different faults for each hypothesis, performance of the models in terms on fit with the catalogue, etc. Read the SHERIFS user manual available in the ‘SHERIFS-master’ folder for more details on the structure of this type of calculation, the content of the files, etc. * The folder structure is set in the correct SHERIFS format so anyone can reproduce or modify the calculation of our study.
DOI: 10.17632/7bt2d592b9
title: Face Mask Dataset 2022

description: Masks are one of the few preventative measures that can be taken against COVID-19 in the absence of immunization, so it is imperative that people wear them whenever they are in an environment where they may be exposed to respiratory infections. Using this dataset, it is possible to develop a model that can differentiate between individuals who are wearing masks and individuals who are not wearing masks. This dataset contains a total of 20,347 images belonging to the 2 classes.
DOI: 10.6084/m9.figshare.28077731.v1
title: Code and data for the manuscript Piironen et al. (2024) "Environmental drivers of productivity explain population patterns of an Arctic-nesting bird across a half-century"

description: This repository includes the R code and data to reproduce the analysis in the manuscript Piironen et al. (2025): Environmental drivers of productivity explain population patterns of an Arctic-nesting bird across a half-century
DOI: 10.6084/m9.figshare.5284492.v1
title: nirK

description: This folder contains alignments (nucleotide and protein) and tree files for <i>nirK</i> genes detected in fungal genomes. <br>
DOI: 10.6084/m9.figshare.11726517.v4
title: CUBEMS, a smart building electricity consumption and indoor environmental sensor dataset.

description: This is the release of the detailed building operation data, including electricity consumption and indoor environmental data, of the seven-story 11,700m2 office building located in Bangkok, Thailand. The electricity consumption data (kW) are that of individual air conditioning units, lighting, and plug loads in each of the 33 zones of the building. The indoor environmental sensor data comprise temperature (degree C), relative humidity (%), and ambient light (lux) measurements of the same zones. The entire datasets are available at one-minute intervals for the period for 18 months from July 1, 2018, to December 31, 2019. <br>
DOI: 10.6084/m9.figshare.1546770.v2
title: The Affect of Age and Gender on Favorite Color

description: Sept 17, 2015 at 3pm Alexander, Amandeep, Stephanie and Vivian conducted a survey in Lab 118. The purpose was to see if age and gender affected fellow labmates favorite color.
DOI: 10.6084/m9.figshare.25956739.v1
title: Financial, Commodity and House Price Index Data

description: Time Series data of the S&P500, US 10 Year government bond, S&P GSCI, S&P Case-Shiller Home price Index, USD Index, US-EPU, and CBOE-VIX.
DOI: 10.6084/m9.figshare.26089383.v1
title: HiGTS_2023s2

description: HiGTS is a high temporal resolution global gridded dataset of human thermal stress metrics. Derived using climate variables from ERA5-Land and ERA5, the HiGTS consists of hourly gridded maps of Universal Thermal Climate Index (UTCI), Universal Thermal Stress (UTS), and daily Thermal Stress Duration (TSD) at 0.1° × 0.1° spatial resolution over the global land surface.HiGTS_2023s2 contains the data from April 1, 2023 to June 30, 2023.
DOI: 10.6084/m9.figshare.28119947.v2
title: Dataset for Real-Time Large-Scale Ridesharing with Flexible Meeting Points

description: The dataset includes maps for two test cases used in our study. It also included distance data for each origin-destination pair, coordinate data, and all of the results of our numerical experiment.
DOI: 10.6084/m9.figshare.29061749.v1
title: ACEM NMR RawData

description: NMR RawData
DOI: 10.6084/m9.figshare.c.3614981_d2.v1
title: Additional file 3: of Strong ground motion in the Kathmandu Valley during the 2015 Gorkha, Nepal, earthquake

description: PTN001504250611.dat. Strong motion acceleration data at PTN station. (DAT 606 kb)
DOI: 10.17632/4fgys3cj58
title: Light Sources & Shadow Detection Dataset

description: This dataset was produced to investigate shadows detection in terrestrial images and light-sources interpolation methods. Source code for reproducing the results described in the published articles is also included.
DOI: 10.17632/k3tm724j2c
title: Dados modelo COVID-19 - vacinas

description: Dados do modelo de custo-efetividade da vacina contra o COVID-19 elaborado pela equipe do Núcleo de Avaliação de Tecnologias em Saúde do Instituto Nacional de Cardiologia (NATS-INC)
DOI: 10.17632/tt2tndygxy
title: Academic Staff Emotional Intelligence Questionnaire (ASEIQ)

description: This questionnaire is designed to assess your emotional intelligence. Emotional intelligence is defined as the ability to identify, understand, and manage one's own emotions, as well as the emotions of others. Please answer the questions below based on your own experiences and feelings. Select the response option for each statement that most accurately represents your feelings about the statement. There are no right or wrong answers and no time limit for completing the questionnaire.
DOI: 10.6084/m9.figshare.12115935.v1
title: Experiment 3: Distorted Visual Space Modifies Object Appearance

description: Experiment 3 Data: distortion indices and perceived size (PSEs) for all 3 subjects.
DOI: 10.6084/m9.figshare.24422293.v1
title: Extrinsic period of Incubation of T. cruzi inside of T. infesting

description: T cruzi positve feces from Triatoma infestan aclimated to 4 diferent thermal treatments.
DOI: 10.6084/m9.figshare.25656966.v1
title: Datasets Repository

description: The NSL-KDD and CICIDS2017 datasets used on the research.
DOI: 10.6084/m9.figshare.26510275.v1
title: COF-300_repository.zip

description: Repository for COF-300 calculations in paper "Temperature-dependent structural dynamics in covalent organic frameworks observed by cryogenic infrared spectroscopy", by Silas O. Frimpong, Nathan McLane, Matthew Dietrich, Garrison A. Bauer, Michael R. Baptiste, Leah G. Dodson, Mercedes K. Taylor published in Phys. Chem. Chem. Phys. DOI: 10.1039/d4cp02338b.
DOI: 10.6084/m9.figshare.8298035.v1
title: Supplemental Table 2_APAH vs Ctrl gene list.xlsx

description: <b>Supplemental Table 2_APAH vs Ctrl gene list</b>
DOI: 10.17632/gnkgbjpc2x
title: CRISPR/Cas9-Mediated SHP-1-Knockout T Cells Combined with Simvastatin Exhibit Enhanced Anti-Tumor Activity in Hepatocellular Carcinoma

description: Sample at figure 6 and supplementary figure 10
DOI: 10.17632/khhdrs48m2
title: F.Al-Rashed Peroxisome proliferator-activated receptor delta (PPARδ): a key modulator in the pathogenesis of diabetes mellitus and mycobacterium tuberculosis co-morbidity

description: Original WB immunoblots images
DOI: 10.6084/m9.figshare.27368762.v1
title: Additional file 5 of Characterization of gut microbiota dynamics in an Alzheimer’s disease mouse model through clade-specific marker-based analysis of shotgun metagenomic data

description: Supplementary Material 5: Table 5- Table listing the log2FC of each statistically significant taxon between sample groups, as calculated by DESeq2.
DOI: 10.6084/m9.figshare.29019539.v1
title: Yemen and Regional Maritime Geostrategy to Create a Maritime Security Strategy by Using GISand Modern Technology

description: Generated informative that have led to Yemen and regional maritime security and sustainable developmentstrategic management at the Red Sea and Indian Ocean. Considering the absence of intellectual development inachieving regional strategic management, the region has become a place of ambition and a conflict zonefor the international factors and constituted a source of threat to maritime security. Study aimed at applyingmaritime and geographic information systems in discovering, understand and knowledge’s the YemenRegional geographical strategic characteristics to help formulate the Yemeni maritime strategy and achieveregional maritime strategic management to create a new Yemen, Arab and regional maritime securitysystem. Mixed of geographical approaches were used in GIS and remote sensing, information technology,marine geopolitics, marine regional geographical approach, marine spatial planning approach to study,Describe, explore, collect information, analyze, and manage a modern database. The experiences of applyingof GIS, marine studies, as well as the experiences of the EU and IORA, besides that the relations betweenTUOAA, Yemeni Geographical Society and their membership in the Asian Geographical Society to collectdata. The importance of the study comes in raising awareness the importance of geographical applicationsto assist the political and strategic planning team and the political decision-maker in understanding theYemeni maritime domain in order to formulate the precise maritime strategic decision and plans tocontribute to the achievement of Yemeni maritime development and benefit from the geographicalconference in the importance of regional cooperation and partnership in achieving regional maritimeplanning. The study divided into three levels. First, the definition of the importance of applications of GISin exploring and collecting information, analyzing and managing data to formulate maritime strategic plans.Second, the role of geographical conferences, Yemeni & regional maritime alliances such as Arab-Chinesepartnerships in applying the regional marine spatial planning in achieving strategic management Regionaland strengthening maritime security. Third, analysis and discussion of maritime problems and conflicts. Thestudy is expected to unify Yemen's maritime policy that build comprehensive modern maritime strategy, aswell as supporting Yemen, Arab and IORA maritime diplomacy that working with Arab and IORA forconducting spatial marine planning that contributes to achieve regional maritime strategy for marinedevelopment, as well as to build Arab and regional maritime power for protection maritime and nationalsecurity in the Red Sea and Indian Ocean region.
DOI: 10.6084/m9.figshare.5048608.v1
title: Supplemental Table 4 from Topological features of a gene co-expression network predict patterns of natural diversity in environmental response

description: GO Functional enrichments for the largest over-enriched Cold module
DOI: 10.17632/fvcmb2c44s
title: NHANES III Public-use Linked Mortality Files

description: The NHANES III public use-related mortality file as of December 31, 2019, linked to the U.S. National Death Index (NDI) by National Center for Health Statistics (NCHS) via a probabilistic matching algorithm. The files include a limited set of mortality variables for adult participants only. The public-use versions of the NCHS Linked Mortality Files were subjected to data perturbation techniques to reduce the risk of participant re-identification. For select records, synthetic data were substituted for follow-up time or underlying cause of death. Information regarding vital status was not perturbed.
DOI: 10.6084/m9.figshare.16897018.v1
title: April 2021 Covid-19 Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in <b>April, 2021</b> from <b>Twitter's COVID-19 Streaming Endpoint </b>via a custom script developed by the <b>Social Media Lab (https://socialmedialab.ca/)</b>.<br>Visit <b>our interactive dashboard at https://stream.covid19misinfo.org</b>/ for a preview and some general stats about this COVID-19 Twitter streaming dataset.<br>For more info about <b>Twitter's COVID-19 Streaming Endpoint</b>, visit <b>https://developer.twitter.com/en/docs/labs/covid19-stream/overview</b><br><b>Note</b>: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.28703135.v4
title: 1jailbreak

description: none
DOI: 10.6084/m9.figshare.20439318.v1
title: WEMWBS (Sinhala) Dataset

description: The dataset of validation of WEMWBS Sinhala version
DOI: 10.6084/m9.figshare.26084710.v1
title: Primary cilia are required for cell-type determination and angiogenesis in the pituitary development

description: Supplemental information for "Primary cilia are required for cell-type determination and angiogenesis in the pituitary development"