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I am attempting to load a GeoTiff into a PostgreSQL database using the PostGIS extension raster2pgsql. When running the executable, I receive the following error: "Error 1: PROJ: Cannot find proj.db."

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The only file with that name resides in the path "C:\Program Files\PostgreSQL\13\share\contrib\postgis-3.0\proj." I've added that path to my "Path" variable in my environment settings, but running raster2pgsql still returns the same error. I then get a message saying the program raster2pgsql has stopped working.

I'm using MacPorts for various other bits needed by sf. In the current version of proj (proj8), the proj_api.h file has been removed. The previous version (proj7) has it. I've installed that version and verified that the two header files live in /opt/local/lib/proj7.

The primary responsibilities of the Pest Detection/Emergency Projects Branch (PD/EP) are the early detection and prompt eradication of serious agricultural pests from California. This is accomplished through the operation of a statewide detection trapping program, special detection surveys, and the maintenance of emergency projects response teams.

The Branch administers the statewide detection trapping program through trapping contracts with 46 county departments of agriculture. State personnel conduct trapping in Orange, San Francisco, Santa Barbara, Ventura, Riverside, Santa Clara, Marin, Mendocino, Yolo, and Yuba Counties. Functionally, Branch activities may be divided into the following four components: Managerial, Operations Center, Pest Detection, and Emergency Projects.

Insects targeted for detection by the statewide network of traps include exotic fruit flies (particularly species of Bactrocera, Dacus, Ceratitis, and Anastrepha), Japanese beetle, light brown apple moth, khapra beetle, spongy moth and flighted spongy moth, European corn borer, and European pine shoot moth.

The primary objective of the emergency project component is to quickly and efficiently eradicate incipient infestations of serious agricultural pests, thereby preventing permanent establishment and subsequent spread in California. Other activities include:

How do you spot a DeepFake? How good are DeepFake videos? How well can ordinary people tell the difference between a video manipulated by AI and a normal, non-altered video? Rather than try to explain in words, we built the Detect Fakes website so you can see the answer for yourself. Detect Fakes is a research project designed to answer these questions and identify techniques to counteract AI-generated misinformation. It turns out there are many subtle signs that a video has been algorithmically manipulated. Some subtleties are explained in detail below.

We hypothesized that the exposure of how DeepFakes look and the experience of detecting subtle computational manipulations will increase people's ability to discern a wide-range of video manipulations in the future. As such, we hosted a website called Detect Fakes to display thousands of the curated, high-quality DeepFake and real videos from the DFDC dataset publicly. The latest version of the website shows 32 videos that were produced as part of the Presidential Deepfakes Dataset.

These eight questions are intended to help guide people looking through DeepFakes. High-quality DeepFakes are not easy to discern, but with practice, people can build intuition for identifying what is fake and what is real. You can practice trying to detect DeepFakes at Detect Fakes.

Abstract. Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of future climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratospheric-ozone-only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing.

The command line applications that come with PROJ only support textinput and output (apart from proj which accepts a simple binary datastream as well). proj, cs2cs and cct expectstext files with one coordinate per line with each coordinate dimension in aseparate column.

Probably. PROJ supports transformations between most coordinate reference systemsregistered in the EPSG registry, as well as a number of other coordinate referencesystems. The best way to find out is to test it with the projinfoapplication. Here's an example checking if there's a transformation betweenETRS89/UTM32N (EPSG:25832) and ETRS89/DKTM1 (EPSG:4093):

You can use the webpageCRS Explorerto view a list of all coordinate reference systems in proj.db, andfilter by type, authority, name and location (clicking on the map). It providesWKTs for every coordinate reference system and quick links to epsg.org.

In most cases coordinate reference systems with geodetic coordinates expect theinput ordered as latitude/longitude (typically with the EPSG dataset), however,internally PROJ expects an longitude/latitude ordering for all projections. Thisis generally hidden for users but in a few cases it is exposed at the surfacelevel of PROJ, most prominently in the proj utility which expectslongitude/latitude ordering of input date (unless proj -r is used).

The first incarnation of PROJ saw the light of day in 1983. Back then itwas simply known as PROJ. Eventually a new version was released, knownas PROJ.2 in order to distinguish between the two versions. Later on bothPROJ.3 and PROJ.4 was released. By the time PROJ.4 was released thesoftware had matured enough that a new major version release wasn't animmediate necessity. PROJ.4 was around for more than 25 years before itagain became time for an update. This left the project in a bit of aconundrum regarding the name. For the majority of the life-time of the product it was known as PROJ.4, but with the release of version 5 the namewas no longer aligned with the version number. As a consequence, it wasdecided to decouple the name from the version number and once again simplycall the software PROJ.

The project plans to partner with up to 12 targeted countries in Africa, Asia and Latin America to carry out large-scale animal surveillance programs within their own countries, safely, using their own laboratory facilities.

The project will focus on finding previously unknown pathogens from three viral families that have a large potential for viral spillover from animals to humans: coronaviruses, the family that includes SARS-CoV-2 the virus that causes COVID-19; filoviruses, such as the Ebola virus; and paramyxoviruses which includes the viruses that cause measles and Nipah.

The goals are ambitious: to collect over 800,000 samples in the five years of the project, most of which will come from wildlife; then to detect whether viruses from the target families are present in the samples. When those are found, the researchers will determine the zoonotic potential of the viruses, or the ability to transfer from animals to humans.

Dependency-check has a command line interface, a Maven plugin, an Ant task, and a Jenkins plugin. The core engine contains a series of analyzers that inspect the project dependencies, collect pieces of information about the dependencies (referred to as evidence within the tool). The evidence is then used to identify the Common Platform Enumeration (CPE) for the given dependency. If a CPE is identified, a listing of associated Common Vulnerability and Exposure (CVE) entries are listed in a report. Other 3rd party services and data sources such as the NPM Audit API, the OSS Index, RetireJS, and Bundler Audit are utilized for specific technologies.

(In contrast, the eight controller setup works as intended when targeting the MonoGame Windows 10 universal project which builds the game as a Windows Store app. However, I would like to stick with the cross platform desktop project so migration to Mac or Linux is smooth.)

The project has been tested with the latest version of MonoGame (v3.8.1.303) and this issue has finally been resolved! Six to eight XBox Controller all connected at once on a Windows machine using OpenGL.

Working on multiple projects can require interacting with multiple versions of the Java language.Even within a single project different parts of the codebase may be fixed to a particular language level due to backward compatibility requirements.This means different versions of the same tools (a toolchain) must be installed and managed on each machine that builds the project. ff782bc1db