cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8287928
title: RVD: A Handheld Device-Based Fundus Video Dataset for Retinal Vessel Segmentation

description: We introduce the first video-based <strong>retinal vessel dataset (RVD)</strong>, a collection of 635 smartphone-based videos with detailed vessel annotation. All captured videos have a frame rate of 25 frames per second, with the duration varying between 2 to 30 seconds. The total number of frames in our dataset is over 130,000. These videos are recorded from four clinics, including patients from 50 to 75 years old. More specifically, 264 males and 151 females are included in the collection process. The annotations provided in our dataset span two dimensions: spatial and temporal. In the spatial dimension, we offer three distinct levels of annotations: binary vessel masks, general vein-artery masks, and fine-grained vein-artery masks. Each kind of annotation is tailored to specific clinical purposes. In the temporal dimension, we focus on the optic disk regions of videos where the retinal vessel fluctuation normally occurs. We select and annotate frames with the maximal and minimal pulse widths as well as label the existence of spontaneous retinal venous pulsations (SVP). More detailed information can also be found on our website: https://uq-cvlab.github.io/Retinal-Video-Dataset/ If you find our RVD dataset is useful in your research, please consider cite: <pre><code>@article{MD2023RVD, title={RVD: A Handheld Device-Based Fundus Video Dataset for Retinal Vessel Segmentation}, author={MD WAHIDUZZAMAN KHAN, Hongwei Sheng, Hu Zhang, Heming Du, Sen Wang, Minas Theodore Coroneo, Farshid Hajati, Sahar Shariflou, Michael Kalloniatis, Jack Phu, Ashish Agar, Zi Huang, Mojtaba Golzan, Xin Yu}, journal={arXiv preprint arXiv:2307.06577}, year={2023} } </code></pre>
DOI: 10.5281/zenodo.8287927
title: RVD: A Handheld Device-Based Fundus Video Dataset for Retinal Vessel Segmentation

description: We introduce the first video-based <strong>retinal vessel dataset (RVD)</strong>, a collection of 635 smartphone-based videos with detailed vessel annotation. All captured videos have a frame rate of 25 frames per second, with the duration varying between 2 to 30 seconds. The total number of frames in our dataset is over 130,000. These videos are recorded from four clinics, including patients from 50 to 75 years old. More specifically, 264 males and 151 females are included in the collection process. The annotations provided in our dataset span two dimensions: spatial and temporal. In the spatial dimension, we offer three distinct levels of annotations: binary vessel masks, general vein-artery masks, and fine-grained vein-artery masks. Each kind of annotation is tailored to specific clinical purposes. In the temporal dimension, we focus on the optic disk regions of videos where the retinal vessel fluctuation normally occurs. We select and annotate frames with the maximal and minimal pulse widths as well as label the existence of spontaneous retinal venous pulsations (SVP). More detailed information can also be found on our website: https://uq-cvlab.github.io/Retinal-Video-Dataset/ If you find our RVD dataset is useful in your research, please consider cite: <pre><code>@article{MD2023RVD, title={RVD: A Handheld Device-Based Fundus Video Dataset for Retinal Vessel Segmentation}, author={MD WAHIDUZZAMAN KHAN, Hongwei Sheng, Hu Zhang, Heming Du, Sen Wang, Minas Theodore Coroneo, Farshid Hajati, Sahar Shariflou, Michael Kalloniatis, Jack Phu, Ashish Agar, Zi Huang, Mojtaba Golzan, Xin Yu}, journal={arXiv preprint arXiv:2307.06577}, year={2023} } </code></pre>
DOI: 10.57841/casdc.0001978
title: 基于表面织构技术改善摩擦学性能的研究进展
DOI: 10.5281/zenodo.8018293
title: Test upload

description: This is a test upload
DOI: 10.5281/zenodo.8018292
title: New name

description: This is a test upload, nothing useful
DOI: 10.5281/zenodo.8293878
title: New name

description: This is a test upload, nothing useful
DOI: 10.5517/ccdc.csd.cc2d1ljl
title: CCDC 2206069: Experimental Crystal Structure Determination

description: Related Article: Zhen-Gang Liang, Gang-Mei Li, Xin-Ye Ren, Jin-Hua Li, Jie Pan, Song-De Han|2023|Inorg.Chem.|62|8663|doi:10.1021/acs.inorgchem.3c00835
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d1lhk
title: CCDC 2206068: Experimental Crystal Structure Determination

description: Related Article: Zhen-Gang Liang, Gang-Mei Li, Xin-Ye Ren, Jin-Hua Li, Jie Pan, Song-De Han|2023|Inorg.Chem.|62|8663|doi:10.1021/acs.inorgchem.3c00835
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.23866962
title: Development of global monthly dataset of CMIP6 climate variables for estimating evapotranspiration

description: Regridding Global CMIP6 GCMs dataset(0.5 degree)Historical dataset: 14 CMIP6 GCMs (1850-2014)Future dataset: 14 CMIP6 GCMs and 4 SSP scenarios (2015-2100)Code: PET code(Python)Composition of dataset: Average temperature, Maximum temperature, Minimum temperature, Wind speed, Relative humidity, Solar radiation<br>If you are using our codes and dataset, please use the following references:Song, Y.H., Chung, ES., Shahid, S. et al. Development of global monthly dataset of CMIP6 climate variables for estimating evapotranspiration. Sci Data 10, 568 (2023). https://doi.org/10.1038/s41597-023-02475-7
DOI: 10.6084/m9.figshare.23866962.v46
title: Untitled Item

description: Regridding Global CMIP6 GCMs dataset(0.5 degree)Historical dataset: 7 CMIP6 GCMs (1850-2014, ACCESS-CM2 to GFDL-ESM4)Future dataset: 7 CMIP6 GCMs and 4 SSP scenarios (2015-2100)Composition of dataset: Average temperature, Maximum temperature, Minimum temperature, Windspeed, Relative humidity, Solar radiationIf you are using our codes and dataset, please use the following references:Song, Y.H., Chung, E.S., Shahid, S., Kim, Y.J., Kim, D.K. 2023. Development of global monthly dataset of CMIP6 climate variables for estimating evapotranspiration. Scientific Data.<br>
DOI: 10.5281/zenodo.8293869
title: Personalized Audio Quality Preference Prediction Dataset

description: Dataset for the following paper. Please cite this paper if our dataset is used in your research. Chung-Che Wang, Yu-Chun Lin, Yu-Teng Hsu, and Jyh-Shing Roger Jang, "Personalized Audio Quality Preference Prediction", APSIPA ASC 2023. Here is a brief description of our dataset. For more details, please see our paper. This dataset is designed for personalized audio quality preference prediction. It includes recordings from 5 different mobile phones playing 7 distinct song segments at 2 volume settings. The played audio is recorded by using a binaural microphone and a computer interface. For each volume type, 70 pairs of recorded audio files are formed, where each of the two audio files in one pair corresponds to same song segment played by different mobile phones. For each volume type, each subject is asked to compare at least 14 of the 70 pairs. Subject information, which includes age, gender, and headphone/earphone specifications such as impedance, frequency response range, and sensitivity, are also collected.
DOI: 10.5281/zenodo.8293868
title: Personalized Audio Quality Preference Prediction Dataset

description: Dataset for the following paper. Please cite this paper if our dataset is used in your research. Chung-Che Wang, Yu-Chun Lin, Yu-Teng Hsu, and Jyh-Shing Roger Jang, "Personalized Audio Quality Preference Prediction", APSIPA ASC 2023. Here is a brief description of our dataset. For more details, please see our paper. This dataset is designed for personalized audio quality preference prediction. It includes recordings from 5 different mobile phones playing 7 distinct song segments at 2 volume settings. The played audio is recorded by using a binaural microphone and a computer interface. For each volume type, 70 pairs of recorded audio files are formed, where each of the two audio files in one pair corresponds to same song segment played by different mobile phones. For each volume type, each subject is asked to compare at least 14 of the 70 pairs. Subject information, which includes age, gender, and headphone/earphone specifications such as impedance, frequency response range, and sensitivity, are also collected.
DOI: 10.6084/m9.figshare.24040563.v3
title: <b>BigDataAD Benchmark Dataset</b>

description: The largest real-world dataset for multivariate time series anomaly detection (MTSAD) from the Hologres AIOps system in the Alibaba Cloud platform.All the metrics and labels in our dataset are derived from real-world scenarios. All metrics were obtained from the Hologres instance monitoring system and cover a rich variety of metric types, including <b>CPU usage, queries per second (QPS) and latency</b>, which are related to many important modules within Hologres. We obtain labels from the ticket system, which integrates three main sources of instance anomalies: user service requests, instance unavailability and fault simulations . User service requests refer to tickets that are submitted directly by users, whereas instance unavailability is typically detected through existing monitoring tools or discovered by Site Reliability Engineers (SREs). Since the system is usually very stable, we augment the anomaly samples by conducting fault simulations. Fault simulation refers to a special type of anomaly, planned beforehand, which is introduced to the system to test its performance under extreme conditions. All records in the ticket system are subject to follow-up processing by engineers, who meticulously mark the start and end times of each ticket. This rigorous approach ensures the accuracy of the labels in our dataset.
DOI: 10.5281/zenodo.8294076
title: CP_test_V2.4_New

description: CP_test_V2.4_New
DOI: 10.5281/zenodo.8294075
title: CP_test_V2.4_New

description: CP_test_V2.4_New
DOI: 10.6084/m9.figshare.24045375
title: High-Performance Landscapes: Re-thinking Design and Management Choices to Enhance Ecological Benefits in Urban Environments

description: Pollinators, water, maintenance, visual ratings, and plot design variables for High-Performance Landscapes research in Fort Worth, Texas
DOI: 10.6084/m9.figshare.24045375.v1
title: High-Performance Landscapes: Re-thinking Design and Management Choices to Enhance Ecological Benefits in Urban Environments

description: Pollinators, water, maintenance, visual ratings, and plot design variables for High-Performance Landscapes research in Fort Worth, Texas
DOI: 10.6084/m9.figshare.24038871
title: Chromosomal-scale genome assembly and annotation of the land slug (<i>Meghimatium bilineatum</i>)

description: Those genome data will be an important resource for understanding the ecological adaptation and potential medicinal molecular basis of <i>Meghimatium bilineatum</i>. They also provide valuable information for studying the evolutionary history of terrestrial gastropod mollusks.
DOI: 10.11578/1367547
title: Energy Exchange Dynamics across L-H Transitions in NSTX

description: We studied the energy exchange dynamics across the low-to-high-confinement (L-H) in NSTX discharges using the gas-puff imaging (GPI) diagnotic. The investigation focused on the energy exchange between flows and turbulence, to help clarify the mechanism of the L-H transition. We apply this study to three type of heating schemes, including a total of 17 shots from the NSTX 2010 campaign run. Results show that the edge fluctuation characteristics (fluctuation levels, radial and poloidal correlation lengths) measured using GPI do not vary just prior to the H-mode transition, but change after the transition. Using a velocimetry approach (orthogonal-programming decomposition), velocity fields of a 24 $\times$ 30 cm GPI view during the L-H transition were obtained with good spatial ($\sim$1 cm) and temporal ($\sim$2.5 $\mu$s) resolutions. Analysis using these velocity fields shows that the production term is systematically negative just prior to the L-H transition indicating transfer from mean flows to turbulence, which is inconsistent with the predator-prey paradigm. Moreover, using the inferred absolute value of the production term, an estimate of the L-H transition duration is found to be 25 ms, which is much larger than the measured duration. These discrepancies are further reinforced by consideration of the ratio between the kinetic energy in the mean flow to the thermal free energy, which is estimated to be much less than 1, suggesting again that turbulence depletion mechanism may not be playing an important role in the transition to the H-mode. Although the Reynolds work is too small to directly deplete the turbulent free energy reservoir, order-of-magnitude analysis shows that the Reynolds stress may still make a non-negligible contribution to the observed poloidal flows.
DOI: 10.6084/m9.figshare.24040563.v4
title: <b>BigDataAD Benchmark Dataset</b>

description: The largest real-world dataset for multivariate time series anomaly detection (MTSAD) from the Hologres AIOps system in the Alibaba Cloud platform.All the metrics and labels in our dataset are derived from real-world scenarios. All metrics were obtained from the Hologres instance monitoring system and cover a rich variety of metric types, including <b>CPU usage, queries per second (QPS) and latency</b>, which are related to many important modules within Hologres. We obtain labels from the ticket system, which integrates three main sources of instance anomalies: user service requests, instance unavailability and fault simulations . User service requests refer to tickets that are submitted directly by users, whereas instance unavailability is typically detected through existing monitoring tools or discovered by Site Reliability Engineers (SREs). Since the system is usually very stable, we augment the anomaly samples by conducting fault simulations. Fault simulation refers to a special type of anomaly, planned beforehand, which is introduced to the system to test its performance under extreme conditions. All records in the ticket system are subject to follow-up processing by engineers, who meticulously mark the start and end times of each ticket. This rigorous approach ensures the accuracy of the labels in our dataset.
DOI: 10.5281/zenodo.7955323
title: Dataset and code for the manuscript 'Parameterizing Vertical Mixing Coefficients in the Ocean Surface Boundary Layer using Neural Networks'

description: This repository contains the code and data used in the manuscript 'Parameterizing Vertical Mixing Coefficients in the Ocean Surface Boundary Layer using Neural Networks'. <br> Manuscript authors: Dr. Aakash Sane, Dr. Brandon G. Reichl, Dr. Alistair Adcroft, Dr. Laure Zanna<br> Manuscript preprint link: https://doi.org/10.48550/arXiv.2306.09045
DOI: 10.5281/zenodo.8293998
title: Dataset and code for the manuscript 'Parameterizing Vertical Mixing Coefficients in the Ocean Surface Boundary Layer using Neural Networks'

description: This repository contains the code and data used in the manuscript 'Parameterizing Vertical Mixing Coefficients in the Ocean Surface Boundary Layer using Neural Networks'. <br> Manuscript authors: Dr. Aakash Sane, Dr. Brandon G. Reichl, Dr. Alistair Adcroft, Dr. Laure Zanna<br> Manuscript preprint link: https://doi.org/10.48550/arXiv.2306.09045
DOI: 10.15121/1809083
title: Utah FORGE 2020-2021 Geothermal Energy/EGS Survey and Results

description: The Utah FORGE project collaborated with the University of Utahs Department of Communication on a Capstone course during Fall Semester 2020. The course created a survey to gauge the general populations knowledge of geothermal energy and Enhanced Geothermal Systems (EGS). The survey was distributed through Qualtrics, an experience management company, in late 2020 and early 2021 to respondents in 11 western states (AZ, CA, CO, ID, MT, NM, NV, OR, UT, WA, WY). Approximately 1,000 responses were received. The Code Book (the consent form and the questions themselves) and the raw data results in a spreadsheet are included in the data resources.
DOI: 10.5519/qd.mimrkhkv
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (3461 records)
DOI: 10.5439/1996748
title: skyrad20s (a1)

description: The sky radiation (SKYRAD) collection of radiometers provides continuous measurements of broadband shortwave (solar) and longwave (infrared) irradiances for downwelling components. These 1-minute data are collected from a network of stations to help determine the total radiative energy exchange and ultraviolet exposure at any deployment site. At SKYRAD sites, collocated upwelling shortwave and longwave irradiance measurements are also normally performed (see GNDRAD).
DOI: 10.5439/1996749
title: skyrad60s (a1)

description: The sky radiation (SKYRAD) collection of radiometers provides continuous measurements of broadband shortwave (solar) and longwave (infrared) irradiances for downwelling components. These 1-minute data are collected from a network of stations to help determine the total radiative energy exchange and ultraviolet exposure at any deployment site. At SKYRAD sites, collocated upwelling shortwave and longwave irradiance measurements are also normally performed (see GNDRAD).
DOI: 10.5439/1996752
title: mergesonde1mace (c1)

description: mergesonde1mace
DOI: 10.5439/1996753
title: aipavg1ogren (c1)

description: aipavg1ogren
DOI: 10.5439/1996754
title: aipavg1ogren (s1)

description: aipavg1ogren
DOI: 10.5439/1996755
title: aip1ogren (c1)

description: aip1ogren
DOI: 10.5439/1996756
title: aip1ogren (s1)

description: aip1ogren
DOI: 10.5439/1996757
title: noaaaosavg (b0)

description: The aerosol observing system (AOS) is the primary platform for in situ aerosol measurements at Earth’s surface. Each AOS has a different complement of instruments, which are selected to ensure the best measurements at each deployment site. The AOS measures aerosol optical properties to better understand how particles interact with solar radiation and influence the Earth's radiation balance. These measurements are useful for calculating parameters used in radiative forcing calculations, such as the aerosol single scattering albedo, asymmetry parameter, mass scattering efficiency, and hygroscopic growth. Measurements made with the AOS form a long-term record at the ARM fixed sites. Shorter measurement records are available from mobile deployments in a wide variety of geographical regions. These measurements are valuable for: identifying long-term changes in aerosol properties identifying atmospheric processes controlling aerosol life cycle and their influence on clouds providing experimental data for developing and testing atmospheric climate models.
DOI: 10.6084/m9.figshare.24045984
title: forest_WDX_figshare.csv

description: this data contains investigative data from six forest plot
DOI: 10.6084/m9.figshare.24045984.v1
title: forest_WDX_figshare.csv

description: this data contains investigative data from six forest plot
DOI: 10.6084/m9.figshare.24045981
title: G002_SupplementaryData

description: Dataset and statistical analysis for the paper "Robust Control Chart Application in Semiconductor Manufacturing Process" submitted to ICoAIMS 2023: 4th International Conference on Applied & Industrial Mathematics and Statistics 2023.
DOI: 10.5281/zenodo.8294483
title: pretrained model for TDiffDe

description: Please put the model into /Checkpoints/HS/
DOI: 10.5281/zenodo.8294482
title: pretrained model for TDiffDe

description: Please put the model into /Checkpoints/HS/
DOI: 10.5281/zenodo.8124808
title: Epitranscriptomic subtyping, visualization, and denoising by global motif visualization

description: The Analysis of large clusters with density histogram based approximate clustering.
DOI: 10.5281/zenodo.8124807
title: Epitranscriptomic subtyping, visualization, and denoising by global motif visualization

description: The Analysis of large clusters with density histogram based approximate clustering.
DOI: 10.6084/m9.figshare.24045993
title: Aburra Valley Colombia wMel Wolbachia release and monitoring data

description: Data on the wMel Wolbachia releases and monitoring in the cities of Bello, Medellin and Itagui in the Aburra Valley, Colombia, aggregated by release area and month. This data underlies the analyses and figures in the manuscript 'Large-scale releases and establishment of <i>w</i>Mel <i>Wolbachia </i>in <i>Aedes aegypti</i> mosquitoes throughout the Cities of Bello, Medellín and Itagüí, Colombia' published in PLoS Neglected Tropical Diseases in 2023.
DOI: 10.5281/zenodo.7545452
title: Data from: Hemispherically-Symmetric Strategies for Stratospheric Aerosol Injection

description: Data in support of research: Stratospheric aerosol injection (SAI) comes with a wide range of possible design choices, such as where and when to inject aerosols. Different injection strategies can yield different climate responses; therefore, making informed future decisions on SAI requires an understanding of the range of possible climate outcomes. Yet to date, there has been no systematic exploration of a comprehensive set of SAI strategies. This limits the ability to determine what effects are robust across different strategies and what depend on specific injection choices, or to determine if there are underlying trade-offs between different climate goals. <br> This study systematically explores how the choice of SAI strategy affects climate responses. Here, we introduce four hemispherically-symmetric injection strategies, all of which are designed to maintain the same global mean surface temperature: an annual injection at the equator (EQ), an annual injection of equal amounts of SO2 at 15N and 15S (15N+15S), an annual injection of equal amounts of SO2 at 30N and 30S (30N+30S), and a polar injection strategy that injects equal amounts of SO2 at 60N and 60S only during spring in each hemisphere (60N+60S). We compare these four hemispherically-symmetric SAI strategies with a more complex injection strategy that injects different quantities of SO2 at 30N, 15N, 15S, and 30S in order to maintain not only the global mean surface temperature but also its large scale horizontal gradients. We find that the choice of SAI strategies notably affects the spatial distribution of aerosol optical depth (AOD), injection efficiency, and various surface climate responses. Among other findings, injecting at mid-latitudes produces more global cooling per unit injection, with the EQ and the 60N+60S cases requiring, respectively, 59% and 50% more injection than the 30N+30S case to meet the same global mean temperature target. Injecting at higher latitudes results in larger equator-to-pole temperature gradients. While all five strategies restore September Arctic sea ice, the high-latitude injection one is more effective due to the SAI-induced cooling more focused at higher latitudes.