By April 2020, Zoom Video Communications had 300 million daily meeting participants worldwide. Only six months before that, at the end of 2019, this number stood at ** million meeting participants. The outbreak of the COVID-19 pandemic led businesses around the world to adopt Zoom as a solution to stay connected to employees and customers when working from different locations. This increased usage of the platform in 2020. Additionally, individuals use the Zoom video platform to stay connected to friends and family.

Image-based study of surface waves is a long lasting topic in ocean science and remote sensing. We believe that modern computers and new programming techniques can make a break-through in this area.

This dataset provides some video files of surface wind waves of two kinds. First is a video snapshot of a quite large area. Second one is a zoom-in video of a spar-buoy (a stick) located in this field. According to the zoom-in video we may see the actual height of the wave in this particular point. This should be treated as a reliable data and so it can be used to calibrate the brightness field. I.e. the users of this dataset are welcome to train their model to obtain the height of the wave out of its brightness on the zoom-out large-area videos.

All video files are readable by a conventional software. Records were taken at mild wind conditions in a gulf (fjord or skerry) of the Ladoga Lake. See "readme.pdf" for the details

World Wind allows any user to zoom from satellite altitude into any place on Earth, leveraging high resolution LandSat imagery and SRTM elevation data to experience Earth in visually rich 3D, just as if you were really there.

Here are a few use cases for this project:

1. Board Game Assistants: This Dice model can be used in a digital assistant for board games. It would help users track dice results automatically, thereby enhancing the experience for games involving dice such as Monopoly, Yahtzee, or Dungeons and Dragons.

2. Educational Games Development: Educational organizations and ed-tech companies can use this model to develop interactive learning games or applications that teach probability, math or statistics through a dice game.

3. Gambling Supervision: Casinos or online gambling platforms can apply the model to monitor dice games and ensure fair play, automatically and meticulously track game statistics, and verify or dispute any contentious throws.

4. Virtual Reality Gaming: The Dice model can be integrated into VR gaming systems to interact with physical dice. For instance, in a VR board game setup, the model can compute the numbers rolled on the dice and translate that into the virtual game.

5. Assistive Technology for Visually-Impaired: Application for visually impaired people, where the app can detect the number rolled on a dice and communicate it via audio, enabling visually impaired people to participate in dice-based games.

Use the 3D Viewer template to showcase your scene with default 3D navigation tools, including zoom controls, pan, rotate, and compass. Include a locator map and bookmarks to provide context to your scene and guide app viewers to points of interest. Line of sight, measure, and slice tools allow viewers to interpret 3D data. Set the option to disable scrolling in the app to seamlessly embed this app in another app or site. Examples: Present a detailed 3D view of a mountainous region at a large scale while the 2D inset map provides context of where you are in the world. Display a 3D plan for new urban development that app viewers can explore with slice and measurement tools. Allow users to visualize the impact of shadows on a scene using daylight animation. Data requirements The 3D Viewer template requires a web scene. Key app capabilities 3D navigation and Compass tool - Allow app users to pan or rotate the scene and orient their view to north. Locator map - Display an inset map with the app's map area in the context of a broader area. Line of sight - Visualize whether one or multiple targets are visible from an observer point. Measurement tools - Provide tools that measure distance and area and find and convert coordinates. Slice - Excludes specific layers to change the view of a scene. Bookmarks - Provide a collection of preset extents that are saved in the scene to which users can navigate the map. Disable scroll - Prevent the map from zooming when app users scroll Language switcher - Provide translations for custom text and create a multilingual app. Home, Zoom controls, Legend, Layer List, Search Supportability This web app is designed responsively to be used in browsers on desktops, mobile phones, and tablets. We are committed to ongoing efforts towards making our apps as accessible as possible. Please feel free to leave a comment on how we can improve the accessibility of our apps for those who use assistive technologies.

Multiplexed 3D atlas of state transitions and immune interaction in colorectal cancer
Jia-Ren Lin*, Shu Wang*, Shannon Coy*, Yu-An Chen, Clarence Yapp, Madison Tyler, Maulik K. Nariya, Cody N. Heiser, Ken S. Lau, Sandro Santagata†, and Peter K. Sorger†

Associated publication DOI: 10.1016/J.CELL.2022.12.028
Learn more: tissue-atlas.org/atlas-datasets/lin-wang-coy-2021/

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VIEW IMAGE DATA ONLINE

Some data is available as narrated data explorations (with text and audio narration) for anonymous on-line browsing using MINERVA software (Rashid et al., 2022), which allows users to pan and zoom through the images without requiring any software installation.

To view the Minerva stories, please visit tissue-atlas.org/atlas-datasets/lin-wang-coy-2021/#data-explorations.

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ACCESS THE DATA

The dataset consists of 47 CRC1 images (2.1 TB) and CRC2-17 images (4.4 TB). All full resolution images, derived image data (e.g., segmentation masks), and cell count tables have been released via the NCI-sponsored repository for Human Tumor Atlas Network (HTAN; humantumoratlas.org/explore).

The dataset is also available through Amazon Web Services S3 in the following bucket: s3://lin-2021-crc-atlas/data/

The list of S3 objects in the bucket can be accessed at https://lin-2021-crc-atlas.s3.amazonaws.com/

For instructions on how to access primary image data through AWS, see "Access Laboratory of Systems Pharmacology Datasets on AWS," DOI: 10.5281/zenodo.10223573.

LIST OF ALL FILES:

The tables below inventory the dataset, which includes:

CRC1 images and image metadata
CRC2-17 images and image metadata
Spatial features tables
Single-cell sequencing data and GeoMX count tables

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CRC1 Images

The following table contains summary biospecimen and file metadata for all 47 sections.

A-CAP is a geo-visualization and data download tool developed at the NSIDC Antarctic Glaciological Data Center (AGDC). A-CAP provides access to AGDC data and other Antarctic parameters including glaciology, ice core data, snow accumulation, satellite imagery, digital elevation models (DEMs), sea ice concentration, and many other cryosphere-related measurements. A-CAP is an interactive map interface that allows users to zoom in and out, overlay coastlines, place names, latitude/longitude, and other geographic information, and access data. A-CAP map images and source data are also accessible via the Open Geospatial Consortium (OGC) Web Map Service (WMS), Web Feature Service (WFS), and Web Coverage Service (WCS).

Use the Chart Viewer template to display bar charts, line charts, pie charts, histograms, and scatterplots to complement a map. Include multiple charts to view with a map or side by side with other charts for comparison. Up to three charts can be viewed side by side or stacked, but you can access and view all the charts that are authored in the map. Examples: Present a bar chart representing average property value by county for a given area. Compare charts based on multiple population statistics in your dataset. Display an interactive scatterplot based on two values in your dataset along with an essential set of map exploration tools. Data requirements The Chart Viewer template requires a map with at least one chart configured. Key app capabilities Multiple layout options - Choose Stack to display charts stacked with the map, or choose Side by side to display charts side by side with the map. Manage chart - Reorder, rename, or turn charts on and off in the app. Multiselect chart - Compare two charts in the panel at the same time. Bookmarks - Allow users to zoom and pan to a collection of preset extents that are saved in the map. Home, Zoom controls, Legend, Layer List, Search Supportability This web app is designed responsively to be used in browsers on desktops, mobile phones, and tablets. We are committed to ongoing efforts towards making our apps as accessible as possible. Please feel free to leave a comment on how we can improve the accessibility of our apps for those who use assistive technologies.

The Terrestrial 30x30 Conserved Areas map layer was developed by the CA Nature working group, providing a statewide perspective on areas managed for the protection or enhancement of biodiversity. Understanding the spatial distribution and extent of these durably protected and managed areas is a vital aspect of tracking and achieving the “30x30” goal of conserving 30% of California's lands and waters by 2030.Terrestrial and Freshwater Data• The California Protected Areas Database (CPAD), developed and managed by GreenInfo Network, is the most comprehensive collection of data on open space in California. CPAD data consists of Holdings, a single parcel or small group of parcels, such that the spatial features of CPAD correspond to ownership boundaries. • The California Conservation Easement Database (CCED), managed by GreenInfo Network, aggregates data on lands with easements. Conservation Easements are legally recorded interests in land in which a landholder sells or relinquishes certain development rights to their land in perpetuity. Easements are often used to ensure that lands remain as open space, either as working farm or ranch lands, or areas for biodiversity protection. Easement restrictions typically remain with the land through changes in ownership. • The Protected Areas Database of the United States (PAD-US), hosted by the United States Geological Survey (USGS), is developed in coordination with multiple federal, state, and non-governmental organization (NGO) partners. PAD-US, through the Gap Analysis Project (GAP), uses a numerical coding system in which GAP codes 1 and 2 correspond to management strategies with explicit emphasis on protection and enhancement of biodiversity. PAD-US is not specifically aligned to parcel boundaries and as such, boundaries represented within it may not align with other data sources. • Numerous datasets representing designated boundaries for entities such as National Parks and Monuments, Wild and Scenic Rivers, Wilderness Areas, and others, were downloaded from publicly available sources, typically hosted by the managing agency.Methodology1. CPAD and CCED represent the most accurate location and ownership information for parcels in California which contribute to the preservation of open space and cultural and biological resources.2. Superunits are collections of parcels (Holdings) within CPAD which share a name, manager, and access policy. Most Superunits are also managed with a generally consistent strategy for biodiversity conservation. Examples of Superunits include Yosemite National Park, Giant Sequoia National Monument, and Anza-Borrego Desert State Park. 3. Some Superunits, such as those owned and managed by the Bureau of Land Management, U.S. Forest Service, or National Park Service , are intersected by one or more designations, each of which may have a distinct management emphasis with regards to biodiversity. Examples of such designations are Wilderness Areas, Wild and Scenic Rivers, or National Monuments.4. CPAD Superunits and CCED easements were intersected with all designation boundary files to create the operative spatial units for conservation analysis, henceforth 'Conservation Units,' which make up the Terrestrial 30x30 Conserved Areas map layer. Each easement was functionally considered to be a Superunit. 5. Each Conservation Unit was intersected with the PAD-US dataset in order to determine the management emphasis with respect to biodiversity, i.e., the GAP code. Because PAD-US is national in scope and not specifically parcel aligned with California assessors' surveys, a direct spatial extraction of GAP codes from PAD-US would leave tens of thousands of GAP code data slivers within the 30x30 Conserved Areas map. Consequently, a generalizing approach was adopted, such that any Conservation Unit with greater than 80% areal overlap with a single GAP code was uniformly assigned that code. Additionally, the total area of GAP codes 1 and 2 were summed for the remaining uncoded Conservation Units. If this sum was greater than 80% of the unit area, the Conservation Unit was coded as GAP 2. 6. Subsequent to this stage of analysis, certain Conservation Units remained uncoded, either due to the lack of a single GAP code (or combined GAP codes 1&2) overlapping 80% of the area, or because the area was not sufficiently represented in the PAD-US dataset. 7. These uncoded Conservation Units were then broken down into their constituent, finer resolution Holdings, which were then analyzed according to the above workflow. 8. Areas remaining uncoded following the two-step process of coding at the Superunit and then Holding levels were assigned a GAP code of 4. This is consistent with the definition of GAP Code 4: areas unknown to have a biodiversity management focus. 9. Greater than 90% of all areas in the Terrestrial 30x30 Conserved Areas map layer were GAP coded at the level of CPAD Superunits intersected by designation boundaries, the coarsest land units of analysis. By adopting these coarser analytical units, the Terrestrial 30X30 Conserved Areas map layer avoids hundreds of thousands of spatial slivers that result from intersecting designations with smaller, more numerous parcel records. In most cases, individual parcels reflect the management scenario and GAP status of the umbrella Superunit and other spatially coincident designations.Tracking Conserved AreasThe total acreage of conserved areas will increase as California works towards its 30x30 goal. Some changes will be due to shifts in legal protection designations or management status of specific lands and waters. However, shifts may also result from new data representing improvements in our understanding of existing biodiversity conservation efforts. The California Nature Project is expected to generate a great deal of excitement regarding the state's trajectory towards achieving the 30x30 goal. We also expect it to spark discussion about how to shape that trajectory, and how to strategize and optimize outcomes. We encourage landowners, managers, and stakeholders to investigate how their lands are represented in the Terrestrial 30X30 Conserved Areas Map Layer. This can be accomplished by using the Conserved Areas Explorer web application, developed by the CA Nature working group. Users can zoom into the locations they understand best and share their expertise with us to improve the data representing the status of conservation efforts at these sites. The Conserved Areas Explorer presents a tremendous opportunity to strengthen our existing data infrastructure and the channels of communication between land stewards and data curators, encouraging the transfer of knowledge and improving the quality of data. CPAD, CCED, and PAD-US are built from the ground up. Data is derived from available parcel information and submissions from those who own and manage the land. So better data starts with you. Do boundary lines require updating? Is the GAP code inconsistent with a Holding’s conservation status? If land under your care can be better represented in the Terrestrial 30X30 Conserved Areas map layer, please use this link to initiate a review. The results of these reviews will inform updates to the California Protected Areas Database, California Conservation Easement Database, and PAD-US as appropriate for incorporation into future updates to CA Nature and tracking progress to 30x30.

The California Department of Transportation (Caltrans) and the California Energy Commission (CEC) are partnering to implement the federal National Electric Vehicle Infrastructure (NEVI) Program, which allocates $5 billion to the states to create a nationwide, interconnected network of DC fast chargers along the National Highway Systems. California's share will be $384 million over 5 years. This map was developed to help prospective applicants and interested parties identify eligible areas for infrastructure deployment.InstructionsViewers can display corridor groups, corridor segments, electric vehicle (EV) charging stations, Justice40 disadvantaged communities, Tribal lands, California-designated low-income or disadvantaged communities, metropolitan planning organizations, regional transportation planning agencies, California state legislative districts, counties, Caltrans districts, utility districts, and congressional districts in this interactive map. The map initially displays corridor groups and their corridor segments included in the Round 2 NEVI solicitation. Viewers can toggle individual layers on and off using the map layers menu located to the right of the map. Some layers are organized into groups; viewers can toggle all layers within a group or select specific ones. The legend to the left of the map will show the layers that have been turned on. There is a search tool to the right of the map that enables viewers to type in an address and locate the address on the map. A basemap selector allows viewers to view road detail. Additional information on the map can be found under the information icon. Viewers can download the map files by clicking on the Data and Supplemental Links icon. Map layers include:A Corridor groups layer that shows designated corridor groups for California's NEVI funding program. Users can click on a corridor segment to view the start and end of each segment within a corridor group. When selected, a pop-up window will appear that identifies the corridor group number, corridor segment, corridor name, minimum number of charging stations required, minimum number of ports required, and needed locations, if applicable, for the corridor segment. Corridor group labels for enhanced accessibility. Note that labels are only visible at certain ranges (zoom in and out to view labels). A NEVI 2 corridors layer shows corridor groups eligible for Round 2 of California's NEVI funding program. NEVI 2 corridor group labels for enhanced accessibility. Note that labels are only visible at certain ranges (zoom in and out to view labels). NEVI 2 corridor segment labels for enhanced accessibility. Note that labels are only visible at certain ranges (zoom in and out to view labels). A Round 1 solicitation corridor groups layer that shows corridor groups eligible for Round 1 of California's NEVI funding program. A layer showing California and Justice40 disadvantaged or low-income communities. A layer showing California-designated disadvantaged or low-income communities. A layer showing Justice40-designated disadvantaged communities. A layer showing California Federally Recognized Tribal Lands. A layer showing Metropolitan Planning Organizations. A layer showing Regional Transportation Planning Agencies. A layer showing California State Senate Districts. A layer showing California State Assembly Districts. A layer showing California Counties. EV charging stations layers (existing DC fast charging stations that are located within one mile of a NEVI-eligible corridor offramp). One layer shows locations of EV charging stations with DC fast charging capabilities that meet the NEVI power level and four-port minimum requirement and could likely become part of the NEVI network if these stations became compliant with other NEVI program requirements such as data reporting. The other layer shows DC fast charging stations that do not meet NEVI power-level or port count requirements but could be upgraded to be NEVI-compliant. Users can click on EV charging stations and a pop-up window will appear with more information on the station (i.e., station address, total port count, minimum NEVI standard, etc.). These data were last updated in March 2024. Please refer to the Department of Energy's Alternative Fuels Data Center and PlugShare for up-to-date existing and planned DC fast charger site information. A layer showing Caltrans Districts. A layer showing Electric Utilities (IOUs and POUs). A layer showing California Congressional Districts. BackgroundThe $5 billion NEVI Program is part of the $1.2 trillion Infrastructure Investment and Jobs Act (IIJA) signed into law by President Biden in November 2021. IIJA commits significant federal funding to clean transportation and energy programs throughout the U.S. to reduce climate changing greenhouse gas emissions. Caltrans is the designated lead agency for NEVI. The CEC is their designated state energy partner. Caltrans and the CEC have partnered to create California's Deployment Plan for the National Electric Vehicle Infrastructure Program that describes how the state plans to allocate its $384 million share of federal NEVI funds to build out a network of modern, high-powered DC fast chargers along federally designated Alternative Fuel Corridors throughout California. California's latest NEVI Deployment Plan was submitted to the Joint Office of Energy and Transportation on August 1, 2023 and approved on September 29, 2023. The Plans must be updated each year over 5 years.NEVI funds must be used initially on federally-designated Alternative Fuel Corridors (shown on the map).Each NEVI-funded DC fast charge station will have a minimum of four 150 kW Combined Charging System (CCS) connectors. Stations will be located no more than 50 miles apart along freeways and highways and no more than 1 mile from a freeway exit or highway roadway. States are required to emphasize equity, with at least 40 percent of NEVI benefits going to disadvantaged, low income, rural and Tribal communities.Data SourcesData are from the Federal Highway Administration's Alternative Fuel Corridors website, the U.S. Department of Energy's Alternative Fuels Data Center Station Data for Alternative Fuel Corridors (as of September 2022), Argonne National Laboratory's Electric Vehicle Charging Justice40 Map, and the California Air Resources Board's Map of California Climate Investments Priority Populations 2022 CES 4.0. ContactPlease submit questions and comments to mediaoffice@energy.ca.gov