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2,170 results for “clouds”
Word Cloud of BBC UK's Video Comments
<div> <p>Word Cloud graph created on Python with a Google Colab Notebook. Dataset of YouTube comments of BBC UK's video about France's Abortion Law made as a constitutional right, collected from Communalytic. This Image is for a Group Work Assignment for the course Digital Methods in Utrecht University. </p> <p> </p> </div>
The Roles of Shallow Convection and Cloud Radiative Feedback in Convectively-Coupled Kelvin Wave: MPAS-aquaplanet Model configuration
<p>We provide the model configuration for the MPAS-A aquaplanet used in our journal article titled <em>“The Roles of Shallow Convection and Cloud Radiative Feedback in Convectively-Coupled Kelvin Waves”</em> by Hsu et al., submitted to the <em>Journal of Climate</em> in 2024.</p>
Data for "The role of cloud in the transportation of dust into basin area: a case study in Sichuan Basin, southwesten China" submitted to Geophysical Research Letters
<p>Data for "The role of cloud in the transportation of dust into basin area: a case study in Sichuan Basin, southwesten China" submitted to Geophysical Research Letters.</p>
Data for "Different types of corona discharges associated with high-altitude positive Narrow Bipolar Events nearby cloud top"
<p>The VLF/LF radio data at Malaysia station support the findings of the paper "Different types of corona discharges associated with high-altitude positive Narrow Bipolar Events nearby cloud top " is presented here. </p> <p>Each file includes three columns: time(seconds), azimuthal magnetic field Bø (nT) and radial magnetic field Br (nT).</p>
Exploiting data in the cloud
<p>Audio recording of presentation which cannot be published due to copyright issues.</p>
1986.69 Jar with Dragon and Clouds Design
You can copy, modify, and distribute this work, even for commercial purposes, all without asking permission. Learn more about The Cleveland Museum of Art's Open Access initiative: http://www.clevelandart.org/open-access-faqs Jar with Dragon and Clouds Design, late 1600s. Korea, Joseon dynasty (1392-1910). Porcelain with underglaze iron; diameter of base: 13.7 cm (5 3/8 in.); overall: 34.7 cm (13 11/16 in.). The Cleveland Museum of Art, Leonard C. Hanna, Jr. Fund 1986.69 Learn more on The Cleveland Museum of Art's Collection Online: https://www.clevelandart.org/art/1986.69 Source: Objaverse 1.0 / Sketchfab
Scottish Boatbuilding School: point cloud (I)
The Scottish Boatbuilding School at the Scottish Maritime Museum in Irvine was established in 2014 to provide education and qualification in both traditional and modern boat building, as well as vessel conservation and restoration. This pointcloud generated from photogrammetry as a part of 'Scanning the Horizon' project, provides a unique glimpse into the school's boatbuilding workshop, which is not accessible for the public. Listen to Martin, the Boatbuilding School Manager as he talks about current restoration work happening at the workshop and unique tools of the traditional boatbuilding trade. To discover more about the boatbuilding workshop at the Scottish Maritime Museum visit: https://skfb.ly/6MyMF Source: Objaverse 1.0 / Sketchfab
South Entrance, British Museum [point cloud]
Quick scan of the Museum's iconic South entrance. 25 photos, Canon g7x, Agisoft PhotoScan Source: Objaverse 1.0 / Sketchfab
L'Arc by Urs Fischer (Point cloud)
This is a point cloud of the monumental statue l'Arc by Urs Fischer. This 11 meters high arch in sparkling aluminum, with an undulatory shape, now stands in front of Station F the world's biggest startup campus. This point cloud has been created with and [Ouster](https://ouster.com/) OS1 3D LiDAR sensor with [Exwayz](https://www.exwayz.fr/) SLAM software. Source: Objaverse 1.0 / Sketchfab
Figure 1 from: Catenazzi A, Ttito A, Diaz MI, Shepack A (2017) Bryophryne phuyuhampatu sp. n., a new species of Cusco Andes frog from the cloud forest of the eastern slopes of the Peruvian Andes (Amphibia, Anura, Craugastoridae). ZooKeys 685: 65-81. https://doi.org/10.3897/zookeys.685.12152
Figure 1 - Map of Peru indicating the type localities of species of Bryophryne.
Point clouds (LAZ): Towards a spatial data repository for archaeological research in the Romanian Mostiștea Basin and Danube Valley
<p>Spatial data are crucial in archaeological research, where orthophotos, digital elevation models, and 3D models are widely used for mapping, documenting, and monitoring archaeological sites. The introduction of affordable and compact unmanned aerial vehicles (UAVs) has significantly advanced the use of UAV-based photogrammetry in the past 20 years. Recently, compact airborne systems have also enabled the capture of thermal, multispectral, and aerial laser scanning data. This study presents the data acquired with different platforms and sensors at Chalcolithic archaeological sites in Romania's Mostiștea Basin and Danube Valley. Since laser scanning and photogrammetry generate large data volumes, data storage and dissemination must also be carefully considered. Based on a thorough study of system performance, data acquisition and processing methods, and data outputs, a workflow for the systematic mapping and documentation of sites has been proposed. Given the experience obtained in the last 5 summer campaigns (2018-2023), 19 sites have been accurately mapped, of which 5 sites are mapped using airborne laser scanning. 18 sites are documented using multispectral photogrammetry, and for 17 sites, interactive image-based 3D models are acquired using true-color photogrammetry. All data are stored on a publicly accessible website for visualization, as well as on an open-data platform for data exchange. For the multispectral data, a raster tile service has been implemented, allowing the use of the data in a GIS environment.</p>
Towards Secure Management of Edge-Cloud IoT Microservices using Policy as Code
<p>This repository contains high quality images of all the Figures included in the paper "<span>Towards Secure Management of Edge-Cloud IoT </span><span>Microservices using Policy as Code".</span></p>
General Instability of Dipeptides in Concentrated Sulfuric Acid as Relevant for the Venus Cloud Habitability
<p>Supplementary Datasets for the paper accepted to Scientific Reports: "General Instability of Dipeptides in Concentrated Sulfuric Acid as Relevant for the Venus Cloud Habitability". <br><br><em>Supplementary Dataset S1:</em> The original 1D <sup>1</sup>H and <sup>13</sup>C NMR data collected in 81% w/w and 98% w/w concentrated sulfuric acid, at all tested time intervals, for all 20 homodipeptides. The NMR measurements in sulfuric acid at different concentrations follows the following naming convention. Different concentrations (by weight) of sulfuric acid in water are denoted by two different letters H and K: K refers to 98% D<sub>2</sub>SO<sub>4</sub>/2% D<sub>2</sub>O and H refers to 81% D<sub>2</sub>SO<sub>4</sub>/19% D<sub>2</sub>O at room temperature.</p> <p><em>Supplementary Dataset S2:</em> The original 1D <sup>1</sup>H and <sup>13</sup>C NMR data collected in D<sub>2</sub>O, for all 20 homodipeptides. </p>
Figures 55-57 from: Jordal BH, Kirkendall LR (2019) Rainforest and cloud forest Scolytodes (Curculionidae, Scolytinae, Hexacolini) from the Arthropods of La Selva inventory in Costa Rica: new species, new synonymy, new records. ZooKeys 863: 1-34. https://doi.org/10.3897/zookeys.863.33183
Figures 55-57 Dorsal, lateral and frontal view of a female Scolytodesminutissimus.
Data and Codes for "Clouds Attenuate the Increase of Downwelling Longwave Radiation Over Land in Climate Warming"
<p>This folder contains the data and codes generated for the manuscript titled "Clouds Attenuate the Increase of Downwelling Longwave Radiation Over Land in Climate Warming."</p>
Quantifying the informativity of emission lines to infer physical conditions in giant molecular clouds
<p>Supplementary figures for Einig et al (2024).</p>
Benchmarking Turbulence Models to Represent Cloud-Edge Mixing
<p>This is the simulation output of the submitted manuscript "Benchmarking Turbulence Models to Represent Cloud-Edge Mixing" to the Journal of Atmospheric Sciences. </p> <p>Abstract: Considering turbulence is crucial to understand clouds. However, covering all scales involved in the turbulent mixing of clouds with their environment is computationally challenging, urging the need for simple models to represent some of the involved processes. By using full direct numerical simulations as a reference, this study compares several statistical approaches for representing small-scale turbulent mixing. All models use a comparable Lagrangian representation of cloud microphysics, and simulate the same cases of cloud edge mixing, covering different ambient humidities and turbulence intensities. It is demonstrated that all statistical models represent the evolution of thermodynamics successfully, but not all models capture the changes in cloud microphysics (cloud droplet number concentration, droplet mean radius, and spectral width). Implications of these results for using the presented models as subgrid-scale schemes are discussed.</p> <p>The raw data presented here was produced by five different models and is completely available. For information on how the dataset is structured, see the readme.txt.</p>
Plot-level semantically labelled terrestrial laser scanning point clouds
<p><strong>Abstract</strong></p> <p>Point clouds from Terrestrial Laser Scanning (TLS) are an increasingly popular source of data for studying plant structure and function. However, unlocking their full potential currently requires extensive manual processing to extract ecologically important information. One key task is the accurate semantic segmentation of different plant material within point clouds, particularly wood and leaves, which is required to understand plant productivity, architecture, competition, space optimisation and physiology, and is a key step in common approaches to individual tree extraction. Existing automated semantic segmentation methods are primarily developed for single ecosystem types, and whilst they show good accuracy for biomass assessment from the trunk and large branches, often perform less well within the crown. In this study, we demonstrate a new framework that uses a deep learning architecture developed from PointNet++ and pointNEXT for processing 3D point clouds to provide a reliable semantic segmentation of wood and leaf in TLS point clouds from the tree base to branch tips, applied to diverse natural European forests. Our model combines meticulously labelled data with voxel-based sampling and a novel gated reflectance integration module embedded throughout the feature extraction layers. We evaluate its performance across an extensive dataset, encompassing diverse ecosystem types and sensor characteristics. Our results show consistent outperformance against the most widely used PointNet++-based approach for leaf/wood segmentation on a high-density TLS dataset collected across diverse mixed forest plots across all major biomes in Europe. We tested our model against others’ open data from China, Eastern Cameroon, Germany and Finland, collected using both time-of-flight and phase-shift sensors, finding consistently strong performance, showcasing the transferability of our model to a wide range of ecosystems and sensors. Our newly developed evaluation metric for assessing performance in the outer parts of the canopy, such as in twigs and small branches, found our model to clearly outperform the most widely used approach.</p> <p><strong>Methods</strong></p> <p>Within each country, we scanned a subset of the 30 m x 30 m FUNDIV plots using a Riegl VZ400i TLS instrument (RIEGL Gmbh, Horn, Austria), scanning at 600MHz and with an angular resolution of 0.04 mrad. All plots were scanned following a 10m grid system with a minimum of 16 upright and 16 tilt scans (following Wilkes et al. 2017), with additional scans to minimise occlusion in dense areas, and on the plot perimeter. To ensure high-quality data with minimal noise, scanning was paused when wind conditions rose above 5 m/s (measured with an anemometer on the ground) or when gusts were visually evident. In order to create our labelled dataset, we used a semi-automated approach informed by existing approaches followed by significant manual cleaning. Vicari et al. (2019) found anisotropy, verticality and linearity to be informative features for leaf-wood separation, so we created these geometric features at spatial scales of approx. 5 cm - 0.5 m (using CloudCompare, 2023). Alongside these, we used reflectance and xyz information for each point and labelled leaf-wood by thresholding these features. We followed this with intensive manual checking and cleaning to ensure high label quality, especially in the smaller branches and twigs. Our dense scanning and labelling strategy means that this dataset is an ideal candidate for training and testing the capabilities of processing algorithms. Our dataset comprises nine 10 m x 10 m blocks of x, y, z coordinates with corresponding reflectance values and labels, all at 1 cm resolution achieved through voxel downsampling. This data was used for training and validation. For comprehensive evaluation, we incorporated additional openly available datasets, which we cropped to reduce size and cleaned to rectify erroneous labels. The original, unmodified versions of these datasets can be accessed as follows:</p> <div> <p>*Mspace Lab (2024) ‘ForestSemantic: A Dataset for Semantic Learning of Forest from Close-Range Sensing’, Geo-spatial Information Science. Zenodo. <a href="https://doi.org/10.5281/zenodo.13285640">https://doi.org/10.5281/zenodo.13285640</a>. Distributed under a Creative Commons Attribution Non Commercial No Derivatives 4.0 International licence.</p> <p>Wang, Di; Takoudjou, Stéphane Momo; Casella, Eric (2021). LeWoS: A universal leaf‐wood classification method to facilitate the 3D modelling of large tropical trees using terrestrial LiDAR [Dataset]. Dryad. <a href="https://doi.org/10.5061/dryad.np5hqbzp6">https://doi.org/10.5061/dryad.np5hqbzp6</a>. Distributed under a Creative Commons 0 1.0 Universal licence.</p> <p>Wan, Peng; Zhang, Wuming; Jin, Shuangna (2021). Plot-level wood-leaf separation for terrestrial laser scanning point clouds [Dataset]. Dryad. <a href="https://doi.org/10.5061/dryad.rfj6q5799">https://doi.org/10.5061/dryad.rfj6q5799</a>. Distributed under a Creative Commons CC0 1.0 Universal licence.</p> <p>Weiser, Hannah; Ulrich, Veit; Winiwarter, Lukas; Esmorís, Alberto M.; Höfle, Bernhard, 2024, "Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation", <a href="https://doi.org/10.11588/data/UUMEDI">https://doi.org/10.11588/data/UUMEDI</a>, heiDATA, V1, UNF:6:9U7BGTgjjsWd1GduT1qXjA== [fileUNF]. Distributed under a Creative Commons Attribution 4.0 International Deed.</p> </div> <p>*For licensing reasons these data re not included in this repository but can be downladed from the doi provided. </p> <p> </p> <p> </p>
ReportFlow: an application for EEG visualization and reporting using cloud platform
<p>Background</p> <p>The cloud is a promising resource for data sharing and computing. It can optimize several legacy processes involving different units of a company or more companies. Recently, cloud technology applications are spreading out in the healthcare setting as well, allowing to cut down costs for physical infrastructures and staff movements. In a public environment the main challenge is to guarantee the patients’ data protection. We describe a cloud-based system, named ReportFlow, developed with the aim to improve the process of reporting and delivering electroencephalograms.</p> <p>Methods</p> <p>We illustrate the functioning of this application through a use-case scenario occurring in an Italian hospital, and describe the corresponding key encryption and key management used for data security guarantee. We used the X<sup>2</sup> test or the unpaired Student <em>t</em> test to perform pre-post comparisons of some indexes, in order to evaluate significant changes after the application of ReportFlow.</p> <p>Results</p> <p>The results obtained through the use of ReportFlow show a reduction of the time for exam reporting (<em>t</em> =&thinsp;19.94; <em>p</em> < 0.001) and for its delivering (<em>t</em> =&thinsp;14.95; <em>p</em> < 0.001), as well as an increase of the number of neurophysiologic examinations performed (about 20%), guaranteeing data integrity and security. Moreover, 68% of exam reports were delivered completely digitally.</p> <p>Conclusions</p> <p>The application resulted to be an optimal solution to optimize the legacy process adopted in this scenario. The comparative pre-post analysis showed promising preliminary results of performance. Future directions will be the creation and release of certificates automatically.</p>
Data for Significant influence of topography and the aerosol under special terrain on cloud-to-ground lightning in Sichuan Basin
<p>1. CG lightning data for June-August during the years of 2010-2018 used in the paper were detected by the China Lightning Detection Network and the spatial resolution is 0.01º×0.01º. This dataset describes lightning frequency in the area around the Sichuan Basin (25°-35°N, 100°-110°E).</p> <p>2. Terrain data is obtained from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) in version 3 and the spatial resolution of terrain data is 0.02º×0.02º. The dataset describes terrain data in the area around the Sichuan Basin (25°-35°N, 100°-110°E).</p> <p>3. Aerosol optical depth (AOD) data for June-August during the years of 2010-2018 are taken from the measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) products MOD08 D3 aboard the Terra and Aqua satellites in the version of 6.1 with a spatial resolution of 1º×1º. This dataset describes the AOD value of the area around the Sichuan Basin (25°-35°N, 100°-110°E).</p> <p>4. The wind field data and mid-level relative humidity used are from the ERA5 hourly data on pressure levels of the European Center for Medium Range Weather Forecasting (ECMWF) with a spatial resolution of 0.25º×0.25º. U is the eastward component of the wind. It is the horizontal speed of air moving towards the east. A negative sign indicates air moving towards the west. V is the northward component of the wind. It is the horizontal speed of air moving towards the north. A negative sign indicates air moving towards the south. The dataset describes wind field in the area around the Sichuan Basin (25°-35°N, 100°-110°E).</p> <p>5. Convective available potential energy (CAPE) data used in the study are from the ERA5 hourly data on single levels of Medium Range Weather Forecasting (ECMWF) with a spatial resolution of 0.25º×0.25º. This dataset describes the CAPE value of the area around the Sichuan Basin (25°-35°N, 100°-110°E).</p> <p>6.The surface temperature data for June-August during the years of 2010-2018 are from the measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) products MOD11 C1 with a spatial resolution of 0.05º×0.05º.<br> This dataset describes the surface temperature of the area around the Sichuan Basin (25°-35°N, 100°-110°E).</p> <p>7. Mid-level relative humidity data used are from the ERA5 hourly data on pressure levels of the European Center for Medium Range Weather Forecasting (ECMWF) with a spatial resolution of 0.25º×0.25º. This dataset describes the mid-level relative humidity of the area around the Sichuan Basin (25°-35°N, 100°-110°E).</p> <p> </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.