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Rapid (formerly RapiD) is a web-based modern editor for OpenStreetMap. Rapid integrates advanced mapping tools, authoritative geospatial open data, and cutting-edge technology to empower mappers at all levels to get started quickly, making accurate and fresh edits.
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Rapid is an open source project developed by Meta. It originated as RapiD, a modified and forked version of the popular OSM editing tool, iD editor, with tools to add and edit map features generated by AI predictions. While initially designed as a tool to add roads, Rapid has subsequently been used to add buildings and various open data layers such as sidewalks, address points, and trees. Rapid includes validation checks (in addition to checks within iD) to detect potential errors.
Users can click the "Rapid Assist" button to see a catalog of open data, and search for various categories. These open data features can be accepted or rejected similar to the machine learning suggestions.
There is a JOSM plugin called "mapwithai", which includes data from Microsoft Building footprints and Facebook roads. This tool is not part of Rapid editor by name or codebase, but uses the same APIs to retrieve the machine learning generated datasets. This plugin also retrieves the open datasets that Rapid displays.
Rapid incorporates road features generated through an artificial intelligence (AI) process. This process was developed by Facebook (now called Meta) using a deep neural net model and Maxar satellite imagery to predict road features. The roads are now available for most regions of the world. This page maintains the up-to-date list of countries with AI-generated roads available. Users can submit a request for road features to be generated in a new region or have data refreshed.
Beware, these building footprints most likely will not terrace buildings properly. Please check the buildings before uploading them. Like all external sources, this dataset has quality that requires reviewing every single building before potential use: users should take care to ensure adjustments and corrections are made as needed before submitting a change set.
Users can rapidly use local authoritative information provided by governments to assist in the evaluating accuracy of the current OSM features, along with other assistive data such as reference imagery layers and other AI-generated datasets mentioned above. Then users can add, edit or supplement features with building outlines, house numbers, sidewalks, and other address information using Rapid.
Read more about the available ArcGIS datasets and Esri's process through its Community Maps program for selecting, evaluating and processing those datasets prior to making them available for assistive editing within Rapid.
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In this work, we executed a workflow to generate in vitro and in vivo models in order to develop and validate a corrective therapeutic for the PAH P281L variant. After screening candidate adenine base editors (ABEs) and guide RNAs (gRNAs) for corrective editing efficacy and off-target editing using an in vitro P281L cellular model, we demonstrated rapid and definitive treatment of PKU in homozygous and compound heterozygous humanized P281L mouse models with two ABE/gRNA combinations, delivered via lipid nanoparticles (LNPs) into the liver.
a Sanger sequencing chromatograms showing the generation of a humanized mouse model via Cas9-mediated homology-directed repair in mouse zygotes. At the top is the sequence from a wild-type C57BL/6J mouse. At the bottom is the sequence from a mouse homozygous for the humanized Pah P281L allele. The red arrow indicates the site of the P281L variant, and the black arrows indicate the sites of synonymous changes that humanize the local region of the mouse Pah gene. b Age-matched colonymates that are homozygous or heterozygous for the humanized P281L allele. The left picture shows two homozygous mice with PKU as evidenced by hypopigmentation of the fur and two control heterozygous mice with normal fur color, immediately prior to treatment. The right picture shows the two homozygous mice and two heterozygous mice 8 weeks after the homozygous mice received LNP treatment, with normalization of fur color.
The research described here complied with all relevant regulations. All recombinant DNA research was approved by the Institutional Biosafety Committee at the University of Pennsylvania, where the studies were performed, and were consistent with local, state, and federal regulations as applicable, including the National Institutes of Health Guidelines for Research Involving Recombinant or Synthetic Nucleic Acid Molecules. All procedures used in animal studies were approved by the Institutional Animal Care and Use Committee at the University of Pennsylvania (protocol #805887), where the studies were performed, and were consistent with local, state, and federal regulations as applicable, including the National Institutes of Health Guide for the Care and Use of Laboratory Animals.
Mice were euthanized by CO2 inhalation at the time of tissue collection. Organs were harvested and fixed in 4% paraformaldehyde. After serial dehydration in ascending concentrations of ethanol and xylene, organs were paraffin-embedded and sectioned, and hematoxylin/eosin staining was performed.
K.M., M.-G.A., and X.W. supervised the work with intellectual input on experimental design and data analysis from W.H.P. and R.C.A.-N. D.L.B., M.C., P.Q., K.M., M.-G.A., and X.W. contributed to web laboratory experiments. K.M. performed bioinformatic analyses. M.C. and M.-G.A. contributed to mRNA production and LNP formulation. D.L.B., K.M., and X.W. drafted the manuscript, and all authors contributed to the editing of the manuscript.
K.M. is an advisor to and holds equity in Verve Therapeutics and Variant Bio and is an advisor to LEXEO Therapeutics. M.-G.A. is a co-founder of and an advisor to AexeRNA Therapeutics. The University of Pennsylvania has filed a patent application related to the use of base editing for the treatment of phenylketonuria (inventors D.L.B., K.M., and X.W.). The remaining authors declare no competing interests.
PS: Oh, later today might be fun! We are looking into trying to do aHome Assistant live stream / mini-release party / Q&A on theHome Assistant YouTube channel.So, keep an eye on our social media for the announcement.
It can be launched anywhere in Home Assistant; with the keyboard shortcutse for entities and c for commands. You can switch between the entities andcommand modes by removing or adding the > at the start of the search input.
The commands are currently limited to reloading YAML configuration andrestarting Home Assistant, but expect this to grow rapidly!The same goes for the keyboard shortcuts; the plan is to add more so you canquickly perform actions and navigate Home Assistant from anywhere witha couple of key presses!
He combined the two bars we had in 1 by replacing the dashboard title with thetabs that used to be shown below it. He did a lot of work to make thetabs take up the least amount of space, while still being user friendly.
This is the perfect blend for people that want the best of both worlds, editingin the UI with the normal UI editor and for some more complicated automations,maybe edit it directly in YAML, all from the UI.
He also added a very useful copy button to make it easy to share yourautomation with the community. You can then easily paste it back in theYAML editor and continue editing after switching to the UI mode.
Ever tried to make a list of entities or set a RGB color via an template?If so, you probably would have learned, that it is not that simple. In HomeAssistant, the result of a template always have been a piece of text (a string),even if you made a list.
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