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On November 7, 2021, Governor Kathy Hochul signed legislation requiring the Department of State to hold a public hearing and conduct an investigation to determine if additional real estate cease and desist zones should be established in all or part of Brooklyn. Cease and desist zones are designed to help prevent aggressive real estate solicitation from brokers, agents, or real estate speculators that target private residences.
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On November 7, 2022, the Department filed a Notice of Proposed Rule Making to establish an additional Cease and Desist Zone for Part of Community Board 17 in Brooklyn. Upon holding the above-posted public hearings and receiving substantial evidence from many homeowners, over the course of many months, the Secretary of State determined that homeowners within the zone proposed by this rule making are subject to the types of solicitations that cease-and-desist lists are intended to guard against. Accordingly, this rule advances the legislative intent and strengthens the policies sought by legislative enactment. The proposed rule text is available at -proposals.
Section 207(f)(2) of the E-Government Act of 2002 requires federal agencies to develop an inventory of information to be published on their Web sites, establish a schedule for publishing information, make those schedules available for public comment, and post the schedules and priorities on the Web site.
National CDL's:Download the national 2022 CDL zipped file 2022 National CDL (2.0 GB)
Download the national 2021 CDL zipped file 2021 National CDL (2.0 GB)
Download the national 2020 CDL zipped file 2020 National CDL (2.0 GB)
Download the national 2019 CDL zipped file 2019 National CDL (1.9 GB)
Download the national 2018 CDL zipped file 2018 National CDL (1.8 GB)
Download the national 2017 CDL zipped file 2017 National CDL (1.7 GB)
Download the national 2016 CDL zipped file 2016 National CDL (1.8 GB)
Download the national 2015 CDL zipped file 2015 National CDL (1.8 GB)
Download the national 2014 CDL zipped file 2014 National CDL (1.8 GB)
Download the national 2013 CDL zipped file 2013 National CDL (1.8 GB)
Download the national 2012 CDL zipped file 2012 National CDL (1.8 GB)
Download the national 2011 CDL zipped file 2011 National CDL (1.8 GB)
Download the national 2010 CDL zipped file 2010 National CDL (1.8 GB)
Download the national 2009 CDL zipped file 2009 National CDL (1.8 GB)
Download the national 2008 CDL zipped file 2008 National CDL (1.8 GB)
National Cultivated Layer:Download the national 2022 cultivated layer zipped file 2022 National Cultivated Layer (300 MB). The Cultivated Layer is based on the most recent five years (2018-2022).
National Frequency Layer:Download the national crop frequency layer zipped file 2022 National Frequency Layer (1.8 GB)
The 2022 Crop Frequency Layer identifies crop specific planting frequency and are based on land cover information derived from the 2008 through 2022 CDL's. There are currently four individual crop frequency data layers that represent four major crops: corn, cotton, soybeans, and wheat.
National Confidence Layer: The following description of the confidence layer is from the document titled 'MDA_NLCD_User_Guide.doc' which is available free for download with the NLCD Mapping Tool at The Confidence Layer "spatially represents the predicted confidence that is associated with that output pixel, based upon the rule(s) that were used to classify it. This is useful in that the user can see the spatial representation of distribution and magnitude of error or confidence for a given classification... This error layer represents a percent confidence associated with each rule and output categorical, classified value. It is expressed as a percentage of confidence. A value of zero would therefore have a low confidence (always wrong), while a value of 100 would have a very high confidence (always right)." For more information on the use of confidence layers please refer to the following paper: Liu, Weiguo, Sucharita Gopal and Curtis E. Woodcock, 2004. Uncertainty and confidence in land cover classification using a hybrid classifier approach, Photogrammetric Engineering & Remote Sensing, 70(8):963-971. Ultimately, however, the confidence value is not a measure of accuracy for a given pixel but rather how well it fit within the decision tree ruleset.
If Microsoft Defender Antivirus reports malware, then the rule is not working. If there is no report of malware and the downloaded file exists, then the exclusion is working. You can open the file to confirm the contents are the same as what is described on the EICAR test file website.
You can also use the following PowerShell code, which calls the .NET WebClient class to download the test file - as with the Invoke-WebRequest cmdlet; replace c:\test.txt with a file that conforms to the rule you are validating:
NiceHash Miner can be flagged by AV (anti-virus) software. This is normal, as almost every mining software on the market is blacklisted by AV. Just make an exception in your AV software to enable the proper operation of NHM.
If auto-download fails, download the miner bins manually and unzip them to the miner plugin bins path. Miner binary package sources are in nhm\miner_plugins\XPlugin\internals\MinersBinsUrlsSettings.json for XPlugin.
This version is intended for experienced miners. Components of NHM may get flagged by anti-virus software (see here). Users should be comfortable managing AV/Firewall exceptions.
NiceHash Miner is usually flagged by AV (anti-virus) software. This is normal, as almost every mining software on the market is blacklisted by AV. Just make an exception in your AV software to enable the proper operation of NHML.
If autodownload fails, download the miner bins manually and unzip them to the miner plugin bins path. Miner binary package sources are in nhm\miner_plugins\XPlugin\internals\MinersBinsUrlsSettings.json for XPlugin.
Although automatic updating is the best way to stay protected, you can update Avira antivirus manually anytime. For Windows users, the easiest way is to right-click the Avira icon in the taskbar and select Start update. 041b061a72