Google Base Map content for Mohave County, Arizona.

Development based on the following article: Add Google Maps to ArcMap and Pro

Google Base Map content for Mohave County, Arizona.

Development based on the following article: Add Google Maps to ArcMap and Pro

BackgroundVirtual multidisciplinary team meetings (VMDTM) provide a standard of care that is not limited by physical distance or social restrictions. And so, when the COVID-19 pandemic imposed irrefutable social restrictions and made in-person meetings impossible, many hospitals switched to the VMDTMs. Although the pandemic might have highlighted the ease of VMDTMs, these virtual meetings have existed over the past decade, albeit less in importance. Despite their recent importance, no review has previously assessed the feasibility of VMDTMs through the eyes of the participants, the barriers participants face, nor their comparison with the in-person format. We undertook this scoping review to map existing literature and assess the perspectives of VMDTM participants.Material and methodsWe searched MEDLINE, Embase, CINAHL, and Google Scholar from inception till July 1st, 2023 to select studies that evaluated the perspectives of participants of VMDTMs regarding the core components that make up a VMDMT. Four authors, independently, extracted data from all included studies. Two authors separated data into major themes and sub-themes.ResultsWe identified six core, intrinsic aspects of a VMDTM that are essential to its structure: (1) organization, (2) case discussion and decision-making, (3) teamwork and communication, (4) training and education, (5) technology, and (6) patient-related aspect. VMDTMs have a high overall satisfaction rating amongst participants. The preference, however, is for a hybrid model of multidisciplinary teams. VMDTMs offer support to isolated physicians, help address complex cases, and offer information that may not be available elsewhere. The periodical nature of VMDTMs is appropriate for their consideration as CMEs. Adequate technology is paramount to the sustenance of the format.ConclusionVMDTMs are efficient and offer a multidisciplinary consensus without geographical limitations. Despite certain technical and social limitations, VMDTM participants are highly satisfied with the format, although the preference lies with a hybrid model.

This repository provides extended documentation, code, and updated links to access the Soil Landscapes of the United States (SOLUS) 100-meter soil property maps. It provides supporting materials for a peer reviewed paper (Nauman et al., Soil Science Society of America Journal, 1–20. https://doi.org/10.1002/saj2.20769) documenting the theory and novel application of hybridized legacy training datasets used to inform the machine learning models used to create the new soil property maps presented here. The SOLUS dataset includes 20 different soil properties (listed below) with most properties predicted for seven standard depths (0, 5, 15, 30, 60, 100, and 150 cm). Further details on these properties and all included files are available in the README.docx document. Also included is a git repository formatted as a hybrid R package that includes all code used to create the soil property maps. All SOLUS100 mapping layers are available as cloud optimized geotiffs at: https://storage.googleapis.com/solus100pub/index.html Metadata: https://storage.googleapis.com/solus100pub/SOLUS100_metadata_pub.html List of files at this URL are listed at: https://storage.googleapis.com/solus100pub/Final_Layer_Table_20231215.csv Note that many of the raster files are scaled by multipliers of 10, 100, or 1000 to store the values as integers to decrease file size. The ‘scalar’ field of the file list table (Final_Layer_Table_20231215.csv) files provide those values. The actual rasters must be divided by the scalars to get the actual units of the properties. To download files, simply concatenate the google API URL with a forward slash and the file name listed in the table into a browser (e.g. EC at 0 cm would be https://storage.googleapis.com/solus100pub/ec_15_cm_p.tif). To automate downloads, a loop in python, R or your language of choice that builds file download urls from the file list in the csv can be implemented. Alternatively, some GIS programs (e.g. QGIS) will let you visualize and interact with the files without downloading the files by entering the URL. All raster environmental covariates used in mapping are available here: https://storage.googleapis.com/cov100m/index.html Properties included in SOLUS100:

Bulk density (oven dry) Calcium carbonate Cation Exchange Capacity (pH 7) Clay Coarse sand Electrical Conductivity (sat. paste) Effective cation exchange capacity Fine sand Gypsum (in

Theme-wise segregation of findings in included studies.

Limitations for VMDTMs reported across included studies.

On Premise - hybrid mobile/web-based application developed using Web AppBuilder with custom widgets. The application can be downloaded from the Apple or Google mobile stores.For questions, please contact Miami-Dade County GIS.