Donald Trump just won “bigly” in Iowa‚ but the Deep State is already working overtime to make sure that it doesn’t matter. In perhaps the most brazen show of power yet‚ the Deep State has openly…

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In this video‚ J.J. goes over his top ten essential items for survival. He starts with the things that are hardest to recreate in nature‚ followed by what supports his priorities of survival and finally‚ that which instills confidence and a positive mental attitude. If being prepared is the name of your game‚ this video is for you! When you support our sponsors it allows us to produce more high quality content for you ... Switch It Up … Your National Level Grid-Down Service Provider Request your Solar PV system &; battery backup quote today ⚡️ https://switchitupinc.com/ William Tell Archery Supplies home of the Mini Striker Crossbow 🏹 https://williamtellarcherysupplies.com/ Nutrient Survival: The best EDC food packs‚ MREs &; brain food 🍱 https://nutrientsurvival.com/pages/survival-dispatch Contingency Medical: Emergency antibiotic kits 🏥 https://contingencymedical.com/?ref=17 Get the CONFLICTED games ☣️ https://www.conflictedthegame.com/ For ad-free‚ uncensored videos and exclusive content please subscribe to a Survival Dispatch Insider membership ... 🔥 https://tinyurl.com/mtna4n3v #survival #urbansurvival #shtfsurvival #prepping #gear Get the SD weekly Situation Report ✅ https://SurvivalDispatch.com/sitrep-signup/ ‼️Please check your spam folder if you’re subscribed to our SITREP Survival Dispatch Store 💥 https://SurvivalDispatchStore.com Survival Dispatch Website 🇺🇸 http://SurvivalDispatch.com All SD Links In One Place 💯 https://linktr.ee/SurvivalDispatch Do you want your product(s) reviewed‚ or would you like to be a guest on our channel? 📧 Support@SurvivalDispatch.com DISCLAIMER: The materials published on Survival Dispatch’s YouTube channel‚ Rumble Channel‚ CloutHub channel‚ social media accounts‚ and website (including any show‚ episode‚ guest appearance‚ etc. appearing within) are for informational and entertainment purposes only. The opinions expressed through this video or podcast are the opinions of the individual author(s) and are for educational and documentary purposes only. Please note‚ we have affiliate partnerships with some brands mentioned on our YouTube channel and Rumble and we may get a small portion of the revenue when you purchase an item using the links provided. FAIR USE: In the rare instance that we include someone else’s footage it is covered under Fair Use for Documentary and Educational purposes with the intention of driving commentary and allowing freedom of speech. IMPORTANT: All firearms footage is produced in a safe environment by highly trained professionals with decades of experience. These videos are strictly for educational and entertainment purposes only. Imitation or the use of anything demonstrated in our videos is done AT YOUR OWN RISK. Do not attempt to replicate the actions featured in our videos without the proper training‚ licensing‚ and medical professionals present. We are not attempting to sell you firearms featured in our videos. We are not instructing our viewers on how to modify firearms‚ accessories‚ or otherwise change their basic legal function. All firearms and accessories are legal products commonly available in retail stores across the United States. Our videos are for entertainment purposes only. We are not an FFL and DO NOT sell or deal in firearms. Such practice is heavily regulated and subject to applicable laws. We DO NOT sell firearms‚ parts‚ or magazines. © 2023 Survival Dispatch

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The surface of Mars is hostile and unforgiving. But put a few meters of regolith between you and the Martian sky‚ and the place becomes a little more habitable. Cave entrances from collapsed lava tubes could be some of the most interesting places to explore on Mars‚ since not only would they provide shelter for future human explorers‚ but they could also be a great place to find biosignatures of microbial life on Mars. But cave entrances are difficult to spot‚ especially from orbit‚ as they blend in with the dusty background. A new machine learning algorithm has been developed to quickly scan images of the Martian surface‚ searching for potential cave entrances. Researchers Thomas Watson and James Baldini from Durham University in the UK used a convolutional neural network (CNN)‚ trained to identify potential cave entrances (PCEs) from images of the Martian surface to locate new potential caves. It was able to identify 61 new cave entrances from images in four different regions on Mars.   Previously‚ most detections of Martian PCEs have come from a manual review of visible satellite imagery‚ with images taken by the Mars Reconnaissance Orbiter’s (MRO) Context Camera (CTX) and High-Resolution Imaging Science Experiment (HiRISE) cameras. A database from that manual review called the Mars Global Candidate Cave Catalogue (MGC3) contains the coordinates and brief descriptions of over one thousand identified PCEs on Mars. The circular black features in this 2007 figure are caves formed by the collapse of lava tubes on Mars. Image credit: NASA/JPL-Caltech/ASU/USGS “Manual review of satellite imagery for Martian cave detection is far from efficient on a planet-wide scale‚” wrote Watson and Baldini in their paper‚ published in the journal Icarus‚ “due to the time constraints associated with reviewing such a large dataset. Machine learning presents an intriguing solution to this problem‚ reducing the dataset to only include imagery computationally determined to contain a PCE.” The caves on Mars are created by lava tubes‚ which were formed by flowing lava on ancient Mars. As the outside of the flowing lava cooled and solidified into a ceiling and walls‚ the interior stayed molten and kept flowing. Eventually‚ the lava flowed out of the tube in a downslope direction‚ leaving the tube intact and open. Sometimes these lava tubes are apparent from linear pit chains on the surface – many of which are likely connected linearly underground. But more commonly‚ they are found by locating a “skylight” or collapsed lava tube ceiling in an orbital image. That skylight provides an entrance to the underground cave. This is a collapsed ceiling of a Martian lava tube. It measures 50 meters (150 ft) across‚ much larger than any Earth lava tubes. Image Credit: NASA/JPL/University of Arizona Lava tubes can be found on Earth‚ the Moon‚ and Mars. Even though Earth is larger than Mars‚ some incredibly large lava tubes have been found on Mars‚ bigger than those found on Earth. On Earth‚ lava tubes are usually only as large as 14–15 meters (46–49 ft) wide – and typically much narrower. In 2020‚ the HiRISE (High-Resolution Imaging Science Experiment) camera on NASA’s Mars Reconnaissance Orbiter (MRO) took a picture of a collapsed lava tube ceiling that is pit crater is 50 m (150 ft) across. The subsurface lava tube cave is likely larger than that. Regular neural networks are commonly used for natural language processing and speech recognition. But CNNs or ConvNets are more often utilized for classification and computer vision tasks. CNNs can recognize patterns in images and provide image classification and object recognition to projects both large and small. For example‚ in a previous study‚ CNNs were trained to recognize Martian surface features‚ such as craters‚ and achieved accuracies of more 90% Watson and Baldini created and trained their CNN model‚ called CaveFinder by having it look at images from the MGC3 catalog from the Tharsis and Elysium regions on Mars‚ which has the highest concentrations of volcanoes. Elevation map of Martian surface with five survey regions highlighted. The Tharsis and Elysium Bulges and the Hellas Basin are also highlighted. Map created using MOLA Shaded relief/ colorized digital elevation map from JMARS. Credit: Watson and Baldini/Icarus. After the training period‚ CaveFinder achieved a test accuracy of 77%. It found four PCEs that Watson and Baldini highlighted for having specific qualities that make them interesting for further research‚ including one PCE nicknamed Marvin‚ which was the largest PCE identified‚ as well as another they called Emily‚ whose low altitude could enable surveyance by drone. Additionally‚ CaveFinder identified twelve regions that appear to have multiple PCEs‚ which the authors say be a great place to explore multiple caves with a future mission‚ due to the proximity and abundance of PCEs. But the researchers say that CaveFinder needs more work before being used on a large‚ planet-wide database. It had a large number of false positives‚ and it appears to have a limited ability to identify “lone small cave types‚ such as skylights and pinholes.” “CaveFinder is still not considered appropriate for detection on a planet-wide scale‚ due to the high number of false positive outputs requiring manual assessment‚” Watson and Baldini wrote. “However‚ it could prove effective in smaller regions perhaps already known to contain PCEs.” For future tests‚ they plan to increase the size of the training dataset used. Other ideas for improving CaveFinder’s accuracy is to use thermal imagery alongside the visible data. Higher resolution images from a future Mars orbiter would also be beneficial for CaveFinder’s increased detection and accuracy. “Overall‚ this survey’s findings indicate that‚ with these additions‚ machine learning has a great potential to advance remote cave detection‚ which is key to future Martian exploration‚” the researchers concluded. The post Machine Learning Could Find all the Martian Caves We Could Ever Want appeared first on Universe Today.

There’s a galaxy out there without apparent stars but largely chock full of dark matter. What’s that you say? A galaxy without stars? Isn’t that an impossibility? Not necessarily‚ according to the astronomers who found it and are trying to explain why it appears starless. “What we do know is that it’s an incredibly gas-rich galaxy‚” said Green Bank Observatory’s Karen O’Neil‚ an astronomer studying this primordial galactic object. “It’s not demonstrating star formation like we’d expect‚ probably because its gas is too diffuse.” O’Neil and a team of colleagues found this odd‚ seemingly starless object called J0613+52‚ while they were doing a sky survey. Their target was a set of so-called “Low Surface Brightness” galaxies (LSBG) They used the Green Bank Telescope‚ the Arecibo Telescope (before its untimely end)‚ and the Nançay Radio Telescope to look at 350 of these dim‚ diffuse objects. The idea was to survey them and determine their gas content and dynamic masses. J0613+52 wasn’t one of the team’s original targets. Instead‚ they stumbled across it while trying to figure out why some of the data from Green Bank and Nançay didn’t match‚ according to O’Neil. “The GBT was accidentally pointed to the wrong coordinates and found this object‚” she explained‚ noting that this galaxy was new and unknown. There are no galaxies within 112 parsecs‚ making it a pretty isolated target. Interestingly‚ based on their observations‚ the team found that J0613+52 has about the same characteristics of mass and gas content as a normal spiral. Yet‚ it has no stars. That poses a mystery they’d like to solve. What’s a Low Surface Brightness Galaxy? The type of galaxy represented by J0613+52 is an odd one when you compare it to the more familiar types such as the star-filled spirals and ellipticals. For one thing‚ it’s a dwarf galaxy with an irregular shape. Without any obvious stars‚ it’s quite dim. The most unusual thing about objects like this one is that dark matter appears to dominate their compositions. If J0613+52 is like others‚ it could have up to 95 percent dark matter constraining the neutral gaseous hydrogen that we can detect. So‚ why no stars in J0613+52? O’Neil describes it as an “unevolved” dwarf. That’s because the neutral hydrogen gas component is too diffuse‚ and too spread out. LSBG generally have less gravity and that makes it tough to form stars on their own. So‚ they evolve very gradually. If they do start to convert gas to stars‚ it takes a long time for that to happen. Some astronomers suggest that LSBG are late-forming objects in cosmic time. That might explain the presence of this one in relatively “modern” times. In addition‚ J0613+52 lies too far from any neighboring galaxies to interact with them gravitationally. That means they can’t trigger star formation through any possible mergers or collisions. “J0613+52 appears to be both undisturbed and underdeveloped‚” she said. “This could be our first discovery of a nearby galaxy made up of primordial gas.” That means its gas content is largely unchanged over time. J0613+52 and Dark Matter J0613+52 is fascinating on its own‚ but it also has something to say about dark matter. We can’t see this unknown “stuff” but we can measure its gravitational effects. It seems to dominate in regions where these dwarf LSBG form and that gives astronomers insight into how this stuff is distributed in the Universe. Dark matter content may also explain why galaxies like J0613+52 don’t easily interact with others. Dark matter “halos” act like gatekeepers to keep them apart. That lack of “contact” may kept it from forming giant stars as a result of collisions. Those kinds of stars are among the first to form. They ultimately die in supernova explosions and seed their environments with the heavy elements needed for ongoing star and planet formation. J0613+52 and others don’t have those heavy elements‚ which is another clue that stars aren’t forming inside them. Any Other Ones Like this Dark Matter Galaxy? It’s not the first time someone has stumbled across a “dark” galaxy like this one. There are certainly other candidates. Astronomers found what a dark galaxy called VIRGOH1 21 in 2005 in the Virgo Cluster. One consensus is that it’s made largely of dark matter. That describes J0613+52 as well. VIRGOH1 21 was found using radio telescopes‚ too‚ looking for the vibrations of hydrogen gas molecules. Since its discovery‚ however‚ some astronomers have suggested that this dark galaxy could be part of a tidal tail of gas and debris generated by a long-ago galactic collision. That uncertainty is why further observations of J0613+52 will be crucial. A radio view tracing out gas in the so-called “dark matter galaxy” VIRGOH121. Made from data collected by the Arecibo Radio Telescope. In her presentation at AAS‚ O’Neil pointed out that it will take high-sensitivity instruments to explore J0613+52 and understand its characteristics. There is a new one about to be installed at Green Bank‚ called ALPACA (Advanced L-Band Phased Array Camera for Astronomy). Once it’s up and running‚ ALPACA will extend the field of view of the telescope‚ allowing astronomers to probe further into J0613+52 and other low surface brightness galaxies like it. For More Information Astronomers Accidentally Discover Dark Primordial GalaxyLow Surface Brightness Galaxies Green Bank Observatory: Technology in the Next Decade The post A Primordial Dark Matter Galaxy Found Without Stars appeared first on Universe Today.