cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26095369.v1
title: Supplementary Material for: Idiopathic Vitreopapillary Traction: Case Report and Literature Review

description: We describe the presentation and management of case of idiopathic vitreopapillary traction in a healthy 40‑year‑old male who presented with decreased vision and visual field changes corresponding to the area of retinal traction. This case was managed with surgery including removal of the tractional membrane
DOI: 10.6084/m9.figshare.28831850.v1
title: High Temperature Superconducting AC Losses - BSCCO and ReBCO Tapes

description: Experimental tests were carried out to measure the AC losses of ReBCO and BSCCO tapes at 77 K. The used experimental setup comprises a sinusoidal voltage source (Keysight AC6804B) connected to a step-down transformer, with the secondary connected to the HTS tapes. Voltage taps are soldered to both sides of the HTS tape sample. A cancellation coil is employed to align the tape’s voltage and current, thereby reducing errors in computing the active power. The voltage signal undergoes an 80-fold amplification stage in the Low Noise Amplifier (LNA) before being visualized and acquired by an oscilloscope. For each current step, a 5-period signal is acquired 20 times, from which an average 5-period signal is derived. Each measurement step is repeated five times to mitigate noise. From these tests, AC voltage-current (V-I) characteristics and total AC losses are experimentally determined. In addition to the cancelation coil method, the voltage was also measured using a Lock-in amplifier, using the current as a phase reference.In these database it is provided the voltage-time and current-time curves and AC losses measurements. In addition, an Excel file with AC losses analytical models is provided to help characterise the HTS tapes' parameters under AC regime.Information from the Manufacturer of the HTS 1<sup>st</sup> gen. BSCCO and 2<sup>nd</sup> gen. ReBCO Tapes:<b>Characteristic</b><b>BSCCO </b><b>(1</b><sup><strong>st</strong></sup><b> gen.)</b><b>ReBCO </b><b>(2</b><sup><strong>nd</strong></sup><b> gen.)</b><b>ReBCO </b><b>(2</b><sup><strong>nd</strong></sup><b> gen.)</b><i>I</i><sub><em>c</em></sub> (77K) @ dc160-180A155-175A83-85A<i>n </i>(77K) @ dc10-1330-3529-30<i>B</i><sub><em>0 </em></sub>(77K) @ dc0.1 - 0.14 T0.1 - 0.14 T0.1 - 0.14 TGeometryEllipticalThin stripThin strip<i>w</i><sub><em>sc</em></sub> (<i>w</i><sub><em>sc</em></sub> = 2a)3.5 mm4.01 mm2.04 mm<i>h</i><sub><em>sc</em></sub> (<i>h</i><sub><em>sc</em></sub> = 2b)0.12 mm0.095 mm0.095 mm<i>l</i><sub><em>sc </em></sub>(length)120 mm100 mm95 mmManufacturerNexans SuperConductorsBSCCO-2212 C01-207SuperPowerSCS4050-APSuperPowerSCS2050-AP<br><br>To use this data, please cite:https://iopscience.iop.org/article/10.1088/1361-6668/ad1f7c/metahttps://doi.org/10.54499/2023.11458.PEX
DOI: 10.6084/m9.figshare.29104871.v2
title: Electronic Appendix A. Figures for "Climate change and ecological challenges in European regions analogous to Hungary's current climate"

description: This dataset contains supplementary figures referenced in the thesis "Climate change and ecological challenges in European regions analogous to Hungary's current climate". Each figure is described below.Figures 1-19. Bioclimatic variables.<br>Figure 1. Annual mean temperature (BCV1).<br>Figure 2. Mean diurnal range (BCV2).<br>Figure 3. Isothermality (BCV3).<br>Figure 4. Temperature seasonality (BCV4).<br>Figure 5. Maximum temperature of the warmest month (BCV5).<br>Figure 6. Minimum temperature of the coldest month (BCV6).<br>Figure 7. Temperature annual range (BCV7).<br>Figure 8. Mean temperature of the wettest quarter (BCV8).<br>Figure 9. Mean temperature of the driest quarter (BCV9).<br>Figure 10. Mean temperature of the warmest quarter (BCV10).<br>Figure 11. Mean temperature of the coldest quarter (BCV11).<br>Figure 12. Annual precipitation (BCV12).Figure 13. Precipitation of the wettest month (BCV13).<br>Figure 14. Precipitation of the driest month (BCV14).<br>Figure 15. Precipitation seasonality (BCV15).<br>Figure 16. Precipitation of the wettest quarter (BCV16).<br>Figure 17. Precipitation of the driest quarter (BCV17).<br>Figure 18. Precipitation of the warmest quarter (BCV18).<br>Figure 19. Precipitation of the coldest quarter (BCV19).<br>Figures 20-27. Specific climate periods.<br>Figure 20. Coldest month.Figure 21. Coldest quarter.<br>Figure 22. Driest month.<br>Figure 23. Driest quarter.<br>Figure 24. Warmest month.<br>Figure 25. Warmest quarter.<br>Figure 26. Wettest month.<br>Figure 27. Wettest quarter.<br>Figures 28-29. Analogy of all points to Hungarian points.<br>Figure 28. Geographical distance of the most similar Hungarian point.Figure 29. Latitudinal distance of the most similar Hungarian point.Figures 30-36. Analogy of Hungarian points to all/foreign points<br>Figure 30. Geographical distance of the most similar point.<br>Figure 31. Geographical distance of the most similar foreign point.<br>Figure 32. Latitudinal distance of the most similar point.<br>Figure 33. Latitudinal distance of the most similar foreign point.<br>Figure 34. Mean similarity of all points.<br>Figure 35. Similarity of the most similar point.Figure 36. Country of the most similar point.
DOI: 10.17632/9xjhgd87d3
title: Semantic Textual Similarity Kurdish

description: To create a Kurdish paraphrase dataset, the PAWS dataset (Zhang et al., 2019) is translated into Central Kurdish using the Google Translate API, followed by a human review to ensure linguistic accuracy and cultural relevance. Human reviewers refine translations to align with Kurdish syntax and semantics, correct machine errors, and adapt cultural references for Kurdish-speaking audiences. Shown summarized in Table 2.


TABLE 1. Example English-to-Kurdish Translations with Cultural Adaptations
Original English Pair Translated and Culturally Adapted Kurdish Pair
Flights from New York to Florida. فڕۆکەکان لە هەولێر بۆ سلێمانی.
Which is the cheapest flight from NYC to Florida? کە هەرزانترین گەشتەی فڕۆکە لە هەولێر بۆ سلێمانی؟
Can a bad person become good? ئایا مرۆڤی خراپ دەتوانێت ببێتە مرۆڤێكی باش؟
Thanksgiving dinner was the best event of the year. ئێوارەخوانی جەژنی نەورۆزی كوردان باشترین بۆنەی ساڵ بوو..

This process ensures the development of a high-quality dataset tailored to Kurdish linguistic and cultural contexts, improving NLP applications for Kurdish-speaking users.
DOI: 10.4121/16691500.v3
title: Dataset of continuous human activities performed in arbitrary directions collected with a distributed radar network of five nodes

description: Please review the document README_v2.pdf<br> The data can be extracted with the MATLAB Live Script dataread.mlx. Referencing the dataset Guendel, Ronny Gerhard; Unterhorst, Matteo; Fioranelli, Francesco; Yarovoy, Alexander (2021): Dataset of continuous human activities performed in arbitrary directions collected with a distributed radar network of five nodes. 4TU.ResearchData. Dataset. https://doi.org/10.4121/16691500.v3 <br> <pre><code><strong>@misc</strong>{Guendel2022, </code></pre> <pre><code>author = "Ronny Gerhard Guendel and Matteo Unterhorst and Francesco Fioranelli and Alexander Yarovoy", </code></pre> <pre><code>title = "{Dataset of continuous human activities performed in arbitrary directions collected with a distributed radar network of five nodes}", </code></pre> <pre><code>year = "2021", </code></pre> <pre><code>month = "Nov", </code></pre> <pre><code>url = "https://data.4tu.nl/articles/dataset/Dataset_of_continuous_human_activities_performed_in_arbitrary_directions_collected_with_a_distributed_radar_network_of_five_nodes/16691500", </code></pre> <pre><code>doi = "10.4121/16691500.v3" } </code></pre> <br> Paper references are: Guendel, R.G., Fioranelli, F.,Yarovoy, A.: <em>Distributed radar fusion and recurrent networks for classification of continuous human activities</em>. IET Radar Sonar Navig. 1–18 (2022). https://doi.org/10.1049/rsn2.12249 <br> R. G. Guendel, F. Fioranelli and A. Yarovoy, "<em>Evaluation Metrics for Continuous Human Activity Classification Using Distributed Radar Networks</em>," 2022 IEEE Radar Conference (RadarConf22), 2022, pp. 1-6, doi: 10.1109/RadarConf2248738.2022.9764181. <br> R. G. Guendel, M. Unterhorst, E. Gambi, F. Fioranelli and A. Yarovoy, "<em>Continuous human activity recognition for arbitrary directions with distributed radars</em>," 2021 IEEE Radar Conference (RadarConf21), 2021, pp. 1-6, doi: 10.1109/RadarConf2147009.2021.9454972. <br>
DOI: 10.6084/m9.figshare.12479306.v2
title: India's elevation profile in a GeoTIFF file

description: India's elevation data as a single TIFF file. See https://github.com/dilawar/map-india-center for more details.<br>MD5 checksum: <br><br>97dcbee8b20f3b4de3036cfb9701a5e7 india.clipped.tif<br><br># Credits<br>File `india-composite.geojson` is from datameet repository https://github.com/datameet/maps/tree/master/Country (Release under http://creativecommons.org/licenses/by-sa/2.5/in/ )<br><br><br><br>
DOI: 10.6084/m9.figshare.23607699.v1
title: patient52.rar

description: A Patient with fundus images that taken by Ret-cam.
DOI: 10.6084/m9.figshare.24516340.v1
title: CellChat objects of scRNA-seq data of human skin from patients with atopic dermatitis

description: This is the CellChat objects after running the scRNA-seq data of non-lesional and lesional human skin from patients with atopic dermatitis in the main CellChat tutorial entitled "CellChat-vignette" (Inference and analysis of cell-cell communication using CellChat (htmlpreview.github.io)), and another tutorial entitled "Comparison_analysis_of_multiple_datasets.Rmd" (Comparison analysis of multiple datasets using CellChat (htmlpreview.github.io))
DOI: 10.6084/m9.figshare.24581193.v1
title: CAM5 model data

description: 1、Globalsst_P1_U.0001-0020，Globalsst_P1_V.0001-0020,Globalsst_P2_U.0001-0020, and Globalsst_P2_V.0001-0020 are for CAM5_SST_P1 (1988-2001) and CAM5_SST_P2 (2002-2018) simulated by the NCAR CAM5 model with a horizontal resolution of 2.5°´1.89° in longitude and latitude and prescribed SST during 20 years.
DOI: 10.6084/m9.figshare.25837021.v1
title: Supplementary Material for: Validation of a Risk Prediction Equation for Incident Chronic Kidney Disease in a Hypertensive Non-Diabetes Cohort in Singapore Primary Care Patients

description: <b><i>Background:</i></b> Accurate identification of individuals at risk of developing chronic kidney disease (CKD) may improve clinical care. Nelson et al. developed prediction equations to estimate the risk of incident eGFR of less than 60 mL/min/1.73 m<sup>2</sup> in diabetic and non-diabetes patients using data from 34 multinational cohorts. We aim to validate the non-diabetes equation in our local multi-ethnic cohort and develop further prediction models. <b><i>Methods:</i></b> Demographics, clinical and laboratory data of hypertensive non-diabetes patients with baseline eGFR ≥60 mL/min/1.73 m<sup>2</sup> on follow-up with primary care clinics between 2010 and 2015 were collected. Follow-up was 5 years from entry to study. We validated Nelson’s equation and developed our own model which we subsequently validated. The developmental cohort included patients between 2010 and 2014 while the validation cohort included patients in 2015. Variables included age, sex, eGFR, history of cardiovascular disease, ever smoker, body mass index, albuminuria, cholesterol, and treatment. Primary outcome was incident eGFR &lt;60/min/1.73 m<sup>2</sup> within 5 years. Model performance was evaluated by C-statistics and calibration was assessed. <b><i>Results:</i></b> In the developmental cohort of 27,800 patients, 2823 (10.2%) developed the outcome during a mean follow-up of 4.4 years while 638 (12.8%) patients developed the outcome in the validation cohort of 4,994 patients. Applicability of Nelson’s equation was limited by missing albuminuria, absence of black race, and exclusion of non-hypertensive patients in our cohort. Nonetheless, the modified Nelson’s model demonstrated C-statistic of 0.85 (95% CI: 0.84–0.86). The C-statistic of our bespoke model was 0.85 (0.85–0.86) and 0.87 (0.85–0.88) for the developmental cohort and validation cohort, respectively. Calibration was suboptimal as the predicted risk exceeded the observed risk. <b><i>Conclusions:</i></b> The modified Nelson’s equation and our locally derived novel model demonstrated high discrimination. Both models may potentially be used in predicting risk of CKD in hypertensive patients who are managed in primary care, allowing for early interventions in high-risk population.
DOI: 10.6084/m9.figshare.28748621.v1
title: Exploring cultural significance of banana leaf as traditional food packaging and improving the biofunctional feature with propolis and zinc oxide nanoparticles coating

description: Exploring cultural significance of banana leaf as traditional food packaging and improving the biofunctional feature with propolis and zinc oxide nanoparticles coating
DOI: 10.17632/4m6mzbyh48
title: land use/land cover transition related to agricultural lands

description: The figure shows the agricultural land abandonment and the decrease in agricultural land use intensity detected in the Romanian Carpathians during the period 1990-2018.
DOI: 10.6084/m9.figshare.25002131.v5
title: Water Quality Monitoring Dataset (Ireland)

description: This study utilizes water quality data from <b>Cork Harbour, Moy Killala, and 15 other coastal locations in Ireland</b>. The Environmental Protection Agency (EPA) of Ireland manages and evaluates this dataset as part of their monitoring program. The extracted data comprises 445,125 entries from Cork Harbour, 722,532 entries from Moy Killala, and 15 other randomly selected locations, all stored in .csv format. Upon merging these disparate .csv files, the dataset expanded to 1,276,654 entries. Following a pivot operation on <b>11 parameters</b> (<b>Alkalinity-total (as CaCO3), Ammonia-Total (as N), BOD - 5 days (Total), Chloride, Conductivity @25°C, Dissolved Oxygen, ortho-phosphate (as P) - unspecified, pH, Temperature, Total Hardness (as CaCO3), True Colour</b>), the dataset was reduced to <b>29,159 rows</b>. The selection of parameters was based on their availability across the entire dataset and aimed at encompassing fundamental measurements of water quality.This repository has two csv files:Water Quality Monitoring Dataset_ Ireland.csv - with Raw Water Quality DataWQI Results on Dataset - Which has the calculated Water Quallity Indices (CCME, WAWQI, Horton, SRDD, Brown) results of water quality
DOI: 10.6084/m9.figshare.3026863.v1
title: Surface model of the T2 theropod dinosaur trackway (T2/11 to T2/16) at Münchehagen (Lower Cretaceous, Germany)

description: Surface model of the T2 theropod dinosaur trackway (T2/11 to T2/16) at Münchehagen (Lower Cretaceous, Germany), at it was in situ after excavation.
DOI: 10.6084/m9.figshare.4308215.v1
title: Vehicle Aerodynamics

description: Typical structures seen in the flow around passenger cars.<br>(1) Flow_Diagram_Fig_1.emfFlow over the front end of an SUV illustrated by surface static pressure and flow streamlines coloured by velocity magnitude, from a commercial Lattice Boltzmann based CFD solver (Exa PowerFLOW). Main features include: plenum vortex, a-pillar vortex, wind screen flow and door mirror wake.
DOI: 10.6084/m9.figshare.17168960.v1
title: PFAS_tables

description: Tables for our publication Extracting and Comparing PFAS from Literature and Patent Documents using Open Access Chemistry Toolkits<br>Shadrack J. Barnabas1, Timo Böhme1, Stephen Boyer2, Matthias Irmer1, Christoph Ruttkies1, Ian Wetherbee3, Emma L. Schymanski4*, Lutz Weber1,*<br>
DOI: 10.6084/m9.figshare.27803934.v1
title: Metabolomic data

description: The untargeted and targeted metabolomic data for human participants.
DOI: 10.6084/m9.figshare.5442142.v2
title: Interactive and Sculptural Printmaking in the Renaissance Catalogues A and B

description: European Single-Sheet Interactive Prints 1450-1700 Accompanying <i>Interactive and Sculptural Printmaking in the Renaissance </i>
DOI: 10.17632/5pg9xfpj4h
title: 042125 Calciphylaxis Presentation and Outcomes Supplemental Table 1

description: 042125 Calciphylaxis Presentation and Outcomes Supplemental Table 1
DOI: 10.17632/67kfh6fwkg
title: Data for: Demand for Decision Autonomy and the Desire to Avoid Responsibility in Risky Environments: Experimental Evidence

description: data for: Demand for Decision Autonomy and the Desire to Avoid Responsibility in Risky Environments: Experimental Evidence
DOI: 10.17632/k5b2zmr4kp
title: A unique environmental augmented household-level livelihood dataset from Nepal

description: A primary household-level panel data for investigation of rural livelihoods dynamics in Nepal, with particular emphasis on allowing analysis of the economic importance of environmental products. The main variables included are: household demographics (individual’s age, gender, educational status, marital status), assets (livestock, implements, land, jewellery, saving, debt), income (from the environment, crop production, livestock rearing, business ownership, wage employment, remittances, and other sources), and household shock experiences (e.g., crop failure or livestock loss). Please refer to the data dictionary and the questionnaire for details.
DOI: 10.17632/m63khkz63j
title: Indonesian Public Opinion on Palestine and Israeli Conflict By SVM and Naive Bayes Approach

description: According to this research, the majority of the Indonesian public, 85%, supports Palestine, while only 4% have negative opinions. The study suggests that Indonesian public opinion about the Palestine-Israel conflict is closely linked to Indonesia's foreign policy. Indonesia has consistently maintained a stance of ending diplomatic relations with Israel and advocating for Palestinian independence in international forums. These findings indicate that public opinion in international relations studies has been influential in shaping a country's foreign policy.
DOI: 10.17632/z4ccb9hcwx
title: The impact of CEO’s social media posts on stock price fluctuations and investor expectations

description: In finance, an abnormal return is the difference between the actual return of a security and the expected return. Abnormal returns are sometimes triggered by "events." Events can include mergers, dividend announcements, company earning announcements, interest rate increases, lawsuits, or tweets on social networks. Previous research has clearly shown a link between company’s communication through social networks with investors and the prediction of company shares.

This research aims to determine how large companies from the USA and Germany and their chief executive officer’s use the social interaction via the social networks Twitter and LinkedIN to affects the company’s abnormal returns and investors’ expectations. This retrospective study aims to investigate the influence of social media namely company’s and CEOs in two different societies that behave differently toward social media.

The sample contains data of twenty companies and the tweets of their CEOs over the period of 2021 – 2023. The results show consistent effects of tweeting of CEOs on the abnormal returns. These results apply to opinions that convey authentic opinions that convey direct information about the company's performance, successes, or failures, as well as opinions that disseminate existing information or replicate and are directly related to the company's business strategy. The quantitative technique employed to collect data is data analysis with programming language Python. Regarding the data processing and analysis, the methods include Sentiment analysis, Granger causality tests and event study.

This paper concludes that sentiment in CEOs tweets has a direct imapct on stock returns of the same companies, but the effect is very small. Also, the effects of the tweets are reflected equally in USA and Germany, but on the other hand, investors and stock markets in these two countries react differently due to the difference in the perception of social networks, the size of the market or because of themselves events that were investigated.

Keywords: Twitter, LinkedIn, social networs, abnormal returns, Granger casualuty test, Pearson correlation, event study.
DOI: 10.6084/m9.figshare.1305052.v1
title: iPads_versus_traditional_media

description: Data set iPads versus traditional media
DOI: 10.6084/m9.figshare.28423703.v1
title: Hourly SIF and ET

description: Sample data of our dataset
DOI: 10.6084/m9.figshare.6427334.v2
title: Multi-channel EEG recordings during a sustained-attention driving task

description: This project adopted an event-related lane-departure paradigm in a virtual-reality (VR) dynamic driving simulator to quantitatively measure brain EEG dynamics along with the fluctuation of task performance throughout the experiment.All subjects were required to have driving license. None of the participants had a history of psychological disorders. All participants were instructed to sustain their attention to perform the task during the experiment, and the 32-ch EEG signals and the vehicle position were recorded simultaneously.Prior to the experiment, all participants completed a consent form stating their clear understanding of the experimental protocol which had been approved by Institutional Review Broad of Taipei Veterans General Hospital, Taiwan.<b>Experiment:</b> <br>All subjects participated in the sustained-attention driving experiment for 1.5 hours in the afternoon (13:00-14:00) after lunch, and all of them were asked to keep their attention focused on driving during the entire period. There was no break or resting session. At the beginning of the experiment (without any recordings), a five-minute pre-test was performed to ensure that every subject understood the instructions and they did not suffer from simulator-induced nausea. To investigate the effect of kinesthesia on brain activity in the sustained-attention driving task, each subject was asked to participate at least two driving sessions on different days. Each session lasted for about 90 min. One was the driving session with a fixed-based simulator but with no kinesthetic feedback, so subject had to monitor the vehicle deviation visually from the virtual scene.The other driving session involved a motion-based simulator with a six degree-of-freedom Stewart platform to simulate the dynamic response of the vehicle to the deviation event or steering. The visual and kinesthetic inputs together aroused the subject to attend to the deviation event and take action to correct the driving trajectory Data Requirement.A wired EEG cap with 32 Ag/AgCl electrodes, including 30 EEG electrodes and two reference electrodes (opposite lateral mastoids) was used to record the electrical activity of the brain from the scalp during the driving task. The EEG electrodes were placed according to a modified international 10-20 system. The contact impedance between all electrodes and the skin was kept &lt;5kΩ. The EEG recordings and the vehicle trajectory amplified by Scan SynAmps2 Express system (Compumedics Ltd., VIC, Australia) were digitized at 500 Hz (resolution: 16 bits) simultaneously.
DOI: 10.6084/m9.figshare.8014727.v1
title: Subject data

description: Clinical, TCR and viral data of the cohort
DOI: 10.6084/m9.figshare.26492932.v2
title: Transcriptomics and metabolomics additional file

description: Additional file 1: Table S1. Complete list of the transcriptome data.Additional file 2: Table S2. Gene-specific primers.Additional file 3: Table S3. Complete list of the lipidomic data.Additional file 4: Table S4. List of GO terms and Functional enrichment analyses using the KEGG pathways.Additional file 5: Table S5. Transcript-lipidomic correlation network.<br>
DOI: 10.6084/m9.figshare.28704256.v1
title: Supplementary Material from Multispecies entanglements and stable isotope signals (δ13C and δ15N) in modern reindeer-herding communities of boreal Northeast Asia

description: Windle et al. Appendix C Supplementary Table 3.xlsx