cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.17012675.v1
title: Supplementary Material for: Profiling and Bioinformatics Analysis Revealing Differential Circular RNA Expression about Storage Lesion Regulatory in Stored Red Blood Cells

description: <b><i>Introduction:</i></b> Circular RNA (circRNA) plays an important role in regulating metabolism of red blood cells (RBCs) and their storage lesions, but the study of how circRNA expression changes in stored RBCs has rarely been conducted. <b><i>Methods:</i></b> The expression change of circRNA was systemically evaluated via high-throughput sequencing on healthy RBCs on day 0, 20, and 40. And then we confirmed the reliability of the high-throughput sequencing analysis by RT-qPCR characterization on selected circRNAs. A higher parental gene enrichment was used to explore circRNA function in pathways. In addition, we deciphered a dysregulated circRNA-related ceRNAs network, and identified three circRNA-miRNA-mRNA regulatory axes related to storage lesion. <b><i>Results:</i></b> We identified 2,586 known and 6,216 putative novel circRNAs, more than 100 circRNAs expression levels were shifted, and the number of downregulated circRNAs was greater with longer storage time. Furthermore, a higher parental gene enrichment related to circRNA was found in pathways, including cAMP signaling pathway, ubiquitin-mediated proteolysis, apoptosis, adhesion, MAPK signaling pathway, cystine methionine metabolism, RNA degradation, RNA transport, TGF-β, and actin regulatory pathway. hsa_circ_0007127-miR-513a-5p-SMAD4, hsa_circ_0000033-miR-19a-3p-VAMP3, and hsa_circ_0005546-miR-4720-CCND3 regulatory axes related to storage lesion was found. <b><i>Conclusions:</i></b> Through investigation in circRNAs profile and circRNA-miRNA-mRNA interactions, this study provides insights on stored RBC circRNA expression changes, which closely relate to the storage lesion of RBCs and their physiological functions.
DOI: 10.6084/m9.figshare.19920662.v1
title: A high-resolution climate simulation dataset for the past 540 million years

description: Here we perform 55 snapshot simulations for the past 540 million years, with a 10-million-year interval, using the Community Earth System Model version 1.2.2 (CESM1.2.2). The climate simulation dataset includes global distributions of monthly surface temperatures and precipitation, with a 1° horizontal resolution of 0.9° × 1.25° in latitude and longitude. This open access climate dataset is useful for multidisciplinary research, such as paleoclimate, geology, geochemistry, and paleontology. <br> Climate variables include monthly surface temperatures (T; unit: °C; Not surface air temperatures), precipitation (P; unit: mm month–1), fraction of surface land area (LANDFRAC; unit: fraction), surface geopotential (PHIS; unit: m2 s–2), surface albedo (SALB; unit: fraction), and zonal (U; unit: m s–1) and meridional (V; unit: m s–1) winds at 1000 hPa, averaged over the last 60 model years. T, P, SALB, U, and V have the dimensions of 55 (simulation) × 12 (month) × 192 (latitude) × 288 (longitude). LANDFRAC and PHIS have the dimensions of 55 (simulation) × 192 (latitude) × 288 (longitude).
DOI: 10.6084/m9.figshare.23790705.v2
title: Data and code of the spherical harmonic forward modeling method

description: <i>The storage</i> here is all the data and codes of fast and high-precision forward modeling of gravity field in spherical harmonic domain.
DOI: 10.6084/m9.figshare.24265498.v2
title: Natural movies

description: Description of the data and file structureVarious types of natural scenes were obtained, categorized as flow (camera moving through space), pan (camera panning through space), still (fixed camera recording a still scene) and still moving (fixed camera recording an active scene). A total of 39 clips of 9.6 second duration were recorded at a frame rate of 120 FPS and a spatial extent of 720 × 1280. The dataset is divided into a training and validation set, both containing a balanced number of the different recording types (training set: 12 flow, 8 pan, 3 still and 8 still moving clips; validation set: 3 flow, 2 pan, 1 still and 2 still moving clips). All clips were preprocessed by converting the RGB channels to grayscale and bilinearly downsampling the spatial dimensions to 144 × 256.Download contains the natural and corresponding filtered clips.Code/SoftwareData is stored h5py format and can be accessed in Python as follows:<pre><pre>import h5py<br><br>root = "" # path to data<br>hf = h5py.File(f"{root}/natural.hdf5", "r") # or filtered_natural.hdf5<br>dataset_name = "train" # or "test"<br>dataset = np.array(hf.get(dataset_name))<br>hf.close()</pre></pre>
DOI: 10.17632/h9wnjk7x39
title: Финансовая модель Джуссоева А.

description: Для стран с развитой минерально-сырьевой базой горнопромышленный комплекс является одной из важнейших отраслей народного хозяйства, он является ключевым звеном в разработке национальных промышленных процессов России. Несмотря на растущую популярность рационального использования ресурсов, альтернативных источников энергии и экологически чистых производств, добывающая отрасль неизменно остается одним из основных секторов экономики. Добавленная стоимость добычи полезных ископаемых продолжает стремительно расти: в 2021 году она возросла на 4,2% в сравнении с 2020 годом. А индекс-дефляторы валовой добавленной стоимости в добывающих производствах увеличились в полтора раза, что составляет 57,1% в сравнении с предыдущим годом .
Даже под влиянием последних трендов, заданных пандемией коронавируса и закрытием границ, горнорудные компании сумели адаптироваться к новым условиям и внести коррективы в цепочки сбыта. Однако, существенным риском, не зависящим от внешних обстоятельств, является полное истощение резерва ранее разведанных месторождений. Поэтому собственники горного бизнеса вынуждены покупать лицензии на месторождения, которым только предстоит геологическая разведка, а также учитывать принципы устойчивого развития и следовать тенденциям по сохранению окружающей среды. 
По данным Seldon.News, инвестиции в топ-5 основных месторождений, расположенных в Краснодарском крае, Якутии, Хакасии, Иркутской и Мурманской областях составят от 60 млрд до 240 млрд рублей в ближайшие пять лет.  В связи с этим, вопросы финансирования компаний в горнодобывающем производстве на ранних этапах развития представляются актуальными и востребованными.
Если рассмотреть развитие горнодобывающей отрасли в историческом контексте, можно заметить, как ее значение возрастало по мере развития научно-технического прогресса и промышленности в целом. Особенный рост данной отрасли был вызван промышленной революцией XVIII века и стремительной индустриализацией общества: спрос на такое сырье как уголь и железо, стремительно рос.
На сегодняшний день все большую актуальность в данной отрасли набирает также проблема ухудшения горно-геологических условий разработки, которая возникает с увеличением их глубины и сопутствующими суровыми климатическими условиями.
Технологическая сложность горнорудной отрасли обуславливает осторожность заинтересованных лиц в инвестировании в горнопромышленный комплекс. 
Актуальность работы - в условиях макроэкономических рисков и нестабильности экономический обстановки обеспечить минимизацию рисков на этапе финансирования для реализации целей на ранних стадиях развития проекта.
Целью работы является разработка рекомендаций для выбора механизма финансирования проекта горнодобывающей отрасли с учётом рисков. 
Для достижения цели были поставлены и решены следующие задачи:
1	Проведение классификации источников финансирования инвестиционной деятельности горнодобывающей компании и анализ управления их структурой
2.	Анализ методов оценки эффективности проекта с учетом р
DOI: 10.6084/m9.figshare.19341533.v1
title: Temperature-Dependent Thermal IR Optical Constants of Water from Data Archaeology (v1.0)

description: <b>Temperature-Dependent Thermal IR Optical Constants of Water from Data Archaeology</b> <b>(v1.0)</b><br><br>OVERVIEW:<br>These files contain temperature-dependent thermal IR optical constants of water derived from a data archaeology and rescue of reflectance data originally published by <i>Pinkley et al.</i> (1977).<br>The six (6) NetCDF files contain lookup tables (LUT) of the temperature-dependent optical constants for each of the 6 previously published datasets referenced, namely <i>Hale & Querry,</i> (25<sup>o</sup>C, 298 K); <i>Bertie & Lan </i>(25<sup>o</sup>C, 298 K); <i>Downing & Williams </i>(27<sup>o</sup>C, 300 K); <i>Pontier & Dechambenoy</i> (27<sup>o</sup>C, 300 K); <i>Segelstein</i> (30<sup>o</sup>C, 303 K); and<i> Wieliczka et al. </i>(30<sup>o</sup>C, 303 K).<br><br>These data are described in the companion paper "Temperature-dependent optical constants of water in the thermal infrared derived from data archaeology" (<i>Nalli et al.,</i> <i>Optics Continuum,</i> 2022, doi:10.1364/OPTCON.450833).<br><br>NETCDF VARIABLE DEFINITIONS:<br><i><b>T:</b></i> Temperature (K) [1 x <i>n</i><sub>temp</sub>]<br><i><b>v:</b></i> Wavenumber (cm<sup>-1</sup>) [<i>n</i><sub>chan</sub> x 1]<br><i><b>n:</b></i> Refractive Index, Re(<i>N<sub>v</sub></i>) [<i>n</i><sub>chan</sub> x <i>n</i><sub>temp</sub>]<br><i><b>k:</b></i> Extinction Coefficient, Im(<i>N<sub>v</sub></i>) [<i>n</i><sub>chan</sub> x <i>n</i><sub>temp</sub>]<br><b>d<i>n:</i></b> Friedman Salinity Correction for <i>n</i> [<i>n</i><sub>chan</sub> x 1]<br><b>d<i>k:</i></b> Friedman Salinity Correction for <i>k</i> [<i>n</i><sub>chan</sub> x 1]<br>CONTACT<b>:</b><br>Dr. Nicholas R. Nalli<br>IMSG, Inc. at NOAA/NESDIS/STAR<br>NCWCP E/RA2<br>5830 University Research Court #2841<br>College Park, MD 20740-3818 USA<br>E-mail: Nick.Nalli@noaa.gov<br>
DOI: 10.6084/m9.figshare.24747375.v3
title: Citation count CSV dataset of all bibliographic resources in OpenCitations Index

description: A CSV dataset containing the number of incoming citations to each bibliographic entity identified by an OMID in the OpenCitations Index (https://opencitations.net/index).The dataset is based on the last release of the OpenCitations Index (https://opencitations.net/download) – July 1, 2024. The size of the zipped archive is 0.4 GB, while the size of the unzipped CSV file is 1.1 GB.The CSV dataset contains the citation count of 74,235,294 bibliographic entities. The first column (<i>omid</i>) lists the entities, while the second column (<i>citations</i>) indicates the corresponding number of incoming citations.
DOI: 10.6084/m9.figshare.28557692.v3
title: Rawdata for AI Non-Contact ECG

description: <br>Thank you very much for your interest in our work!This repository contains raw data for AI Radar ECG.Thank you!Wishing you happiness every day.
DOI: 10.6084/m9.figshare.29140502.v1
title: Jibo's User Study Complete Dataset

description: Social robots are increasingly expected to engage with users; however, the extent to which users accurately perceive these expressions remains uncertain, particularly across different cultural and developmental backgrounds. This study explores how users of varying ages and ethnicities interpret the emotional expressions of Jibo, a social robot that relies on abstract motion rather than facial or vocal cues. Participants (N = 36) engaged with Jibo across three modalities (physical, digital avatar, and video-based) and attempted to recognize six robot-displayed emotions. Quantitative analysis using MANOVA and Kruskal-Wallis tests revealed no significant differences in emotion recognition across ethnic groups and modalities. A modest age effect was observed in the digital condition only, with middle-aged adults outperforming younger adults. Qualitative feedback supported these findings, with most participants citing the lack of facial features, sound cues, and motion clarity as barriers to interpretation. Despite limited recognition accuracy, the physical robot was rated as the most emotionally engaging. These results suggest that while physical embodiment may enhance perceived connection, it does not guarantee improved communication and comprehension. The study highlights the limitations of motion-only expression and reinforces the importance of clearer, multimodal cues in social robot design for broader and more inclusive user understanding.These datasets were collected as part of the user study conducted to obtain results for this research. The datasets were preprocessed, cleaned, and organized using Python libraries to ensure consistency and ease of use throughout statistical analyses.
DOI: 10.17632/76z794cxdg
title: Survey dataset of Dynamic Capabilities for leading and managing Digital Transformation initiatives

description: The dataset presented in this article originates from a study aimed at developing a Dynamic Capabilities (DC) framework for managing Digital Transformation (DT) initiatives in organizations, integrating Change Management (CM). 
The data were collected using a mixed-methods approach, which included qualitative expert interviews and two quantitative surveys. The two surveys that were conducted: Expert Survey and Mass Survey. The first (Expert Survey) consisted of 130 questions and included responses from 31 DT experts, assessing their expertise in DT and the importance, difficulty, and extent performed of DC (Sensing , Seizing, and Transforming) routine activities. The second survey (Mass Survey) consisted of 38 questions and comprised 446 responses from professionals across fifty-one countries and various industries; it evaluated the framework’s applicability in real-world organizational contexts. The Mass Survey included the DT challenges, organizational culture profiles, dynamic capabilities, and demographic details such as level of focus and organization size. Both surveys asked participants to rate their level of DT success and specify their organisation’s industry type.
The data from both surveys are structured into categorical and Likert scale responses. The dataset can be used for further analysis, including comparative studies of DT strategies across sectors or regions, and for developing tools for managing DT. Additionally, it holds potential for reuse in training and educational materials for managers and practitioners overseeing DT projects.
The Excel sheet has four tabs: (1) Variables Expert Survey, (2) Expert Survey Data, (3) Variable Mass Survey, and (4) Mass Survey Data. The Variable tabs (1 and 3) provide the variables that were used in the Expert and Mass Surveys respectively. The Data sheets (2 and 4) are the raw datasets that were collected from participants.
DOI: 10.6084/m9.figshare.27753255.v2
title: Experimental data for memory superiority effect of chunk restructuring in insight

description: 1-The data for 48 participants2- The data for two types of solution characters across six conditions3, the label has been described in the file.4, the original data has been uploaded.
DOI: 10.17632/pbb76sbbrg
title: Wireless Sensor Network Based Drinking-Water Quality Monitoring and Notification System Dataset

description: This project presents the collected experimental data for drinking-water quality monitoring which was conducted in ten experiments by using five different common sources of water contaminants namely soil, chlorine, salt, washing powder, vinegar and their combination. The data were collected indoors at room temperature during the day for several days using sensors that measure pH, turbidity, flow rate, and conductivity in water. The water consumption risk (CR) was calculated as deviation based on the water quality parameters standards proposed by the World Health Organization (WHO) and the South African Department of Water Affairs (DWA), with respect to the sensor measurement readings obtained. While the error measurements were calculated based on the expected parameter measurement per conducted experiment and repeated for 26 measurements. Pure tap water was the benchmark of water safe for human consumption. The first five experiments were performed by introducing each contaminant into the water and thereafter, two contaminants in the sixth experiment and their additions until all different contaminants were experimented at once in the last experiment. The first being data for pure tap water and the rest being data for contaminated water using the different contaminants and their additions until all different contaminants were experimented at once.
DOI: 10.17632/wm4gzhy7pd
title: Drug Survival of Biologics in Hidradenitis Suppurativa: A Systematic Review and Meta-Analysis (Supplementary Material)

description: Supplementary Materials for 'Drug Survival of Biologics in Hidradenitis Suppurativa: A Systematic Review and Meta-Analysis' by Pham et al., published in the Journal of the American Academy of Dermatology (2024).
DOI: 10.26180/17108447.v1
title: From planes to pipes: The emplacement of elongate intrusions in shallow magma plumbing systems – Supplemental Material

description: Supplemental Material 2 and 3 to the PhD thesis titled "From planes to pipes: The emplacement of elongate intrusions in shallow magma plumbing systems" (https://doi.org/10.26180/19365134) <br>The folder structure and containing files of Supplemental Material 2 and 3 are outlined in <i>Suppl_Material_folder_structure.pdf .</i>
DOI: 10.6084/m9.figshare.13259858.v1
title: codex-s.tar.gz

description: The smallest of the three CoDEx knowledge graph datasets (relational triples only) from https://github.com/tsafavi/codex.
DOI: 10.6084/m9.figshare.14976744.v1
title: RMES_input

description: SNP converted to RMES format to estimate selfing on the sampling site and region scales for <i>A. cotula </i>in the Pacific Northwest and Kashmir Valley India.
DOI: 10.6084/m9.figshare.24720501.v1
title: Data Repository

description: These are data collected during an investigation of single-neuronal activity in the human language-dominant prefrontal cortex during speech production. We sought to characterize the neuronal dynamics that underlie planning of phonemes and related sub-lexical components of speech.
DOI: 10.6084/m9.figshare.27282723.v3
title: Voxel-wise maps of Figure 3 and Extended data figure 2-3.

description: Voxel-wise maps of Figure 3 and Extended data figure 2-3.
DOI: 10.6084/m9.figshare.28120349.v1
title: <b>Quantification of nutrients and dissolved organic carbon transport in the mesoscale eddies: Insights from dual water isotopes</b>

description: To date, no quantitative studies about material transport in the mesoscale eddies were reported. Therefore, combining water isotopes with on-site hydrological and physicochemical parameters to quantify mesoscale processes and the vertical transport of substances in the region is of great significance for deepening the eco-environmental effects and efficient carbon output mechanisms caused by mesoscale processes. To achieve this goal, this study combined satellite altimeter datasets to capture a cold eddy and a warm eddy during field voyage surveys in the wNPO, investigating dual water isotopes, hydrology, and other chemical parameters (including nutrients and dissolved organic carbon) in the water column.
DOI: 10.6084/m9.figshare.29092517.v1
title: BigWig files with all reads

description: BigWig files for the read pile-ups of all samples with all QCed reads
DOI: 10.6084/m9.figshare.5235823
title: SocialLink: knowledge transfer between social media and linked open data

description: This dataset contains canonical citations (DOIs) for the SocialLink dataset (15th May 2017 release), alignment data and code and entity data in .csv and .json format.SocialLink is a publicly-available Linked Open Data dataset that matches social media accounts on Twitter to the corresponding entities in multiple language chapters of DBpedia. By effectively bridging the Twitter social media world and the Linked Open Data cloud, SocialLink enables knowledge transfer between the two: on the one hand, it supports Semantic Web practitioners in better harvesting the vast amounts of valuable, up-to-date information available in Twitter; on the other hand, it permits Social Media researchers to leverage DBpedia data when processing the noisy, semi-structured data of Twitter. The SocialLink dataset is created by the SocialLink Pipeline, which aligns 271,000 DBpedia persons and organisations to their Twitter profiles via data acquisition, candidate acquisition and candidate selection phases. Data files are stored in compressed .gz format that can be uncompressed using standard compression utilities. Diagrams are presented in .pdf format, .csv, .json and .java files can be accessed via text edit programs, .tql files can be accessed via MS SQL Server.<b>Format descriptions:</b><br><b>JSON</b> JSON file is a single array containing an object for each DBpedia entity with similar structure.Where <b>candidates </b>property contain the list of candidate IDs for each entity, while <b>scores </b>property contains a confidence score for each candidate reported by our candidate selection algorithm.<b>twitter_id</b> might be present in case a certain threshold is met (thresholds are selected according to the high F1 setup from our paper)<b>CSV</b>For each row of our CSV file contains info about a certain entity. Each row looks like this:http://dbpedia.org/resource/MoShang,"[6887052,26735153,302784580,1331809652,2275404837,2597365788,1516978014,753046765809508356,1512300530,255873440]","[1.579205048600787,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]",6887052The columns contain the same data as in JSON format. If the Twitter ID can't be determined — 0 is used in the last column instead.<b>approach.pdf </b>and <b>rdf.pdf</b> provide visual representations of the SocialLink pipeline and RDF alignments. For more detailed information on the RDF modeling choices see the associated publication, while extensive documentation is available via the SocialLink website (url below), covering: (i) dataset scope, format, statistics, and access mechanisms; (ii) instructions for deploying and running the SocialLink pipeline to recreate the resource; (iii) example applications using the dataset; and, (iv) links to external resources like the GitHub repository and issue tracker.Code: https://github.com/Remper/sociallinkSocialLink Website: http://sociallink.futuro.media/
DOI: 10.17632/5vgstskp2n
title: GetFEM: Automated FE Modeling of Multiphysics Problems Based on a Generic Weak Form Language - Numerical Examples' Source Code

description: This release contains the source code for the two numerical examples from: Renard, Y., & Poulios, K. (2020). GetFEM: Automated FE Modeling of Multiphysics Problems Based on a Generic Weak Form Language. Acm Transactions on Mathematical Software, 47(1), 3412849. https://doi.org/10.1145/3412849 The released Python codes demonstrate the use of the high level modeling language (GWFL) in the GetFEM finite element library for solving advanced continuum mechanics and multiphysics problems.
DOI: 10.6084/m9.figshare.20445915.v7
title: Water quality and interview survey data

description: This dataset is the result of the interview survey and water monitoring in the slums area of Bandung City, Indonesia. The interview data consists of water sources used (for drinking, cooking, and other purposes), water consumption, satisfaction, and water expenditure to assess the slum upgrading program in providing water for the households. The water sample was measured for several parameters, namely pH, TDS, Nitrate, Iron, E. coli, and Total Coliform. The survey was conducted from August to October 2021.