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Cannonfired shock wave could stun kill people

first_img More information: More information: ArmyTec.netvia: Defense News and Gizmodo Space cannon to shoot payloads into orbit (w/ Video) Originally, the Thunder Generator was used by farmers in Israel to scare away birds that might eat their crops. Recently, Israel’s Ministry of Defense has approved a license for the Israeli technology company ArmyTec to market military and paramilitary versions of the Thunder Generator. The company hopes that the cannon, which was originally developed by Israeli company PDT Agro, could have applications in crowd control and border security.”Anyone within 30 to 50 meters from the cannon will feel like he’s standing in front of a firing squad,” said Igor Fridman, president of PDT Agro, who developed the system. “He’ll feel and hear the blast, but he won’t be hurled to the ground. He’ll be able to run away unharmed … and that’s the point of this application.”Maintaining a safe firing distance is important, though, since if a person is standing within 10 meters of the cannon, the shock wave could inflict permanent damage or even kill them. Rather, the device is intended for longer distances. Fridman estimates that by increasing the current five-inch diameter of the barrel, the cannon could have a range of up to 100 meters.To generate the shock waves, the cannon uses a mixture of liquefied petroleum, cooking gas, and air. As the fuel travels through the cannon barrel, it detonates and intensifies until it exits, producing a series of rapid-fire, high-velocity shock bursts. The shock bursts can be calibrated and programmed for different purposes. According to the company, the system can generate 60-100 bursts per minute, with each burst traveling at about 2,000 meters per second and lasting up to 300 milliseconds. The resulting extreme air pressure and sonic boom effect create a double deterrent to rioters and intruders.”It’s all done in a controlled and safe manner, using the cheapest, cleanest fuel available,” said Fridman, noting that a standard 12-kilogram canister of liquefied petroleum can produce about 5,000 shock bursts at a cost of about $25. “The trick is to cause it not to burn, but to explode.”In agriculture, the shock waves have provided a cleaner alternative to hazardous chemicals that farmers might use to keep pests away. For police and military uses, the system could offer a safer, cheaper and more politically acceptable weapon than other explosive materials or lethal force. Over the past two years, about a dozen systems have been operating at Israeli farms and fisheries, with no accidents.ArmyTec plans to modify the single-barrel cannon for different applications. The company has proposed a multi-barrel design and synchronized networks of multiple cannons to simulate a battlefield experience. The cannons could also be mounted on vehicles and operated via remote control. Plus, by using a curved barrel design, the cannon could produce shock waves at 90-degree angles to bend around walls or other obstacles. Explore further The Thunder Generator produces shock waves that result in a loud sonic boom and extreme air pressure, which can be heard and felt by people up to 100 meters away. Image credit: Army Tec. This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only. © 2010 PhysOrg.com (PhysOrg.com) — Police and military forces around the world may soon have a new non-lethal weapon at their hands. Called the Thunder Generator, the device is a cannon that fires shock waves that pass through people and objects. Although the shock waves are harmless, they give people the impression of standing in front of a firing squad, according to the cannon’s developers. Citation: Cannon-fired shock wave could stun, kill people (2010, January 19) retrieved 18 August 2019 from https://phys.org/news/2010-01-cannon-fired-stun-people.htmllast_img read more

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Redis 5 is now out

first_imgAfter announcing Redis 5 RC1 in May earlier this year, the stable version of Redis 5 was released yesterday. This release comes with a new Stream data type, LFU/LRU info in RDB, active defragmentation version 2, HyperLogLogs improvements and many other improvements. What is new in Redis 5? Redis 5 comes with a new data type called Stream, which models a log data structure in a more abstract way. Three new modules got important APIs: Cluster API, Timer API, Dictionary API. With these APIs, you can now build a distributed system with Redis using it just as a framework, creating your own protocols. To provide better-caching accuracy after a restart or when a slave does a full sync, RDB now stores the LFU and LRU information. In the future releases, we are likely to see a new feature that sends TOUCH commands to slaves to update their information about hot keys. The cluster manager is now ported from Ruby to C and is integrated with redis-cli. Because of this change, it is faster and no longer has any dependency. To learn more about the cluster manager, you can run the redis-cli –cluster help command. Also, many commands with subcommands have a HELP subcommand. Sorted set commands, ZPOPMIN/MAX, and blocking variants are introduced. These commands are used in applications such as time series and leaderboards. With active defragmentation version 2, the process of defragmenting the memory of a running server is better than before. This will be very useful for long-running workloads that tend to fragment Jemalloc. Jemalloc is now upgraded to version 5.1 Improvements are made in the implementations of the HyperLogLog data structure with refined algorithms to offer a more accurate cardinality estimation. This version comes with better memory reporting capabilities. Redis 5 provides improved networking especially related to emitting large objects, CLIENT UNBLOCK and CLIENT ID for useful patterns around connection pools and blocking commands. Read the full Redis 5 release notes on GitHub. Read Next MongoDB switches to Server Side Public License (SSPL) to prevent cloud providers from exploiting its open source code Facebook open sources LogDevice, a distributed data store for logs RxDB 8.0.0, a reactive, offline-first, multiplatform database for JavaScript released!last_img read more

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2018 prediction Was reinforcement learning applied to many realworld situations

first_imgBack in 2017, we predicted that reinforcement learning would be an important subplot in the growth of artificial intelligence. After all, a machine learning agent that adapts and ‘learns’ according to environmental changes has all the makings of an incredibly powerful strain of artificial intelligence. Surely, then, the world was going to see new and more real-world uses for reinforcement learning. But did that really happen? You can bet it did. However, with all things intelligent subsumed into the sexy, catch-all term artificial intelligence, you might have missed where reinforcement learning was used. Let’s go all the way back to 2017 to begin. This was the year that marked a genesis in reinforcement learning. The biggest and most memorable event was perhaps when Google’s AlphaGo defeated the world’s best Go player. Ultimately, this victory could be attributed to reinforcement learning; AlphaGo ‘played’ against itself multiple times, each time becoming ‘better’ at the game, developing an algorithmic understanding of how it could best defeat an opponent. However, reinforcement learning went well beyond board games in 2018. Reinforcement learning in cancer treatment MIT researchers used reinforcement learning to improve brain cancer treatment. Essentially, the reinforcement learning system is trained on a set of data on established treatment regimes for patients, and then ‘learns’ to find the most effective strategy for administering cancer treatment drugs. The important point is that artificial intelligence here can help to find the right balance between administering and withholding the drugs. Reinforcement learning in self-driving cars In 2018, UK self-driving car startup Wayve trained a car to drive using its ‘imagination’. Real world data was collected offline to train the model, which was then used to observe and predict the ‘motion’ of items in a scene and drive on the road. Even though the data was collected in sunny conditions, the system can also drive in rainy situations adjusting itself to reflections from puddles etc. As the data is collected from the real world, there aren’t any major differences in simulation versus real application. UC Berkeley researchers also developed a deep reinforcement learning method to optimize SQL joins. The join ordering problem is formulated as a Markov Decision Process (MDP). A method called Q-learning is applied to solve the join-ordering MDP. The deep reinforcement learning optimizer called DQ offers out solutions that are close to an optimal solution across all cost models. It does so without any previous information about the index structures. Robot prosthetics OpenAI researchers created a robot hand called Dactyl in 2018. Dactyl has human-like dexterity for performing complex in hand manipulations, achieved through the use of reinforcement learning. Finally, it’s back to Go. Well, not just Go – chess, and a game called Shogi too. This time, Deepmind’s AlphaZero was the star. Whereas AlphaGo managed to master Go, AlphaZero mastered all three. This was significant as it indicates that reinforcement learning could help develop a more generalized intelligence than can currently be developed through artificial intelligence. This is an intelligence that is able to adapt to new contexts and situations – to almost literally understand the rules of very different games. But there was something else impressive about AlphaZero – it was only introduced to a set of basic rules for each game. Without any domain knowledge or examples, the newer program outperformed the current state-of-the-art programs in all three games with only a few hours of self-training. Reinforcement learning: making an impact irl These were just some of the applications of reinforcement learning to real-world situations to come out of 2018. We’re sure we’ll see more as 2019 develops – the only real question is just how extensive its impact will be. Read next This AI generated animation can dress like humans using deep reinforcement learning Deep reinforcement learning – trick or treat? DeepMind open sources TRFL, a new library of reinforcement learning building blockslast_img read more

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SAINTS have named their 19man squad for Fridays

first_imgSAINTS have named their 19-man squad for Friday’s Dacia World Club Series match with Sydney Roosters.Travis Burns and Dominique Peyroux have been added to the line-up but James Roby misses out with a rib injury.Keiron Cunningham will select his 17 from:2. Tommy Makinson, 3. Jordan Turner, 5. Adam Swift, 6. Travis Burns, 7. Luke Walsh, 8. Alex Walmsley, 10. Kyle Amor, 11. Atelea Vea, 12. Jon Wilkin, 13. Louie McCarthy-Scarsbrook, 14. Lama Tasi, 15. Greg Richards, 16. Andre Savelio, 17. Luke Thompson, 18. Dominique Peyroux, 19. Theo Fages, 20. Joe Greenwood, 22. Jack Owens, 28. Morgan Knowles.Trent Robinson will choose his Roosters’ side from:Aidan Guerra, Blake Ferguson, Brendan Elliot, Dale Copley, Daniel Tupou, Dylan Napa, Ian Henderson, Isaac Liu, Jackson Hastings, Jake Friend, Jayden Nikorima, Joe Burgess, Kane Evans, Latrell Mitchell, Mitchell Aubusson, Mitchell Frei, Sam Moa, Shaun Kenny-Dowall, Siua Taukeiaho, Tyler Cornish, Vincent Leuluai.The game kicks off at 8pm and the referee will be Ben Thaler.Ticket details for the game can be found here.last_img read more

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Increasing LNG exports marginally positive for US economy

first_imgAddThis ShareNEWS RELEASEDavid [email protected] LNG exports ‘marginally positive’ for US economy  HOUSTON – (Dec. 29, 2015) – Increasing the United States’ export of liquefied natural gas (LNG) above 12 billion cubic feet per day (Bcf/d) would allow the U.S. to continue to provide a competitive advantage for domestic natural-gas-intensive industries relative to their counterparts overseas, according to a new report presented to the U.S. Department of Energy from the Center for Energy Studies at Rice University’s Baker Institute for Public Policy and Oxford Economics.The study, “The Macroeconomic Impact of Increasing U.S. LNG Exports,” was co-authored by Kenneth Medlock, senior director for the Center for Energy Studies.“The dramatic growth in shale gas production in the United States has presented a number of opportunities and challenges for the U.S. economy,” Medlock said. “To begin, shale gas production has lowered the domestic price of natural gas so that the United States now has among the lowest prices in the world and shifted the U.S. from emerging as a significant importer to a pending exporter of LNG. This has benefitted consumers and led to gains in competitiveness for U.S. manufacturers.“Low natural gas prices in the United States negatively impact the profitability of domestic upstream activities, which has, in fact, been a primary driver of interest in exporting LNG as suppliers seek new demands in higher-priced markets. While selling natural gas at higher prices on the world market would increase profits for U.S. gas producers, the price gap between the United States and the rest of the world will shrink, thereby eroding some of the benefits that have accrued to U.S. consumers and manufacturers. So the net balance of the gains and losses associated with trade are at the core of the analysis. In sum, the balance is positive for the U.S. economy.”For the report, the Center for Energy Studies used the Rice World Gas Trade Model to simulate alternative futures to assess natural gas production, demand and, more generally, the international gas market based on a range of projections of U.S. resource endowments. Oxford Economics addressed the macroeconomic impact of the center’s market analysis.A comprehensive set of scenarios was developed in the analysis – including U.S. natural gas recovery, international and domestic demand, and natural-gas supply opportunities in the rest of the world – to examine the impact on energy markets and the U.S. macroeconomy.Key findings from the report include:LNG exports are associated with a net increase in domestic natural gas production. Medlock said the study found that “the majority of the increase in LNG exports is accommodated by expanded domestic production rather than reductions in domestic demand, a result that reflects the very elastic long-run supply curve in North America.”As exports increase, the spread between U.S. domestic prices and international benchmarks narrows. In every case, greater LNG exports raised domestic prices somewhat and lowered prices internationally. The majority of the price movement (in absolute terms), however, occurs in Asia.The overall macroeconomic impacts of higher LNG exports are marginally positive, a result that is robust under alternative assumptions. With external demand for U.S. LNG exports at 20 Bcf/d, the impact of increasing exports from 12 Bcf/d is between $7 billion to $20 billion annually from 2026 to 2040 in today’s prices.Medlock said that the impact from added LNG exports will not be felt until after 2025 due to the large amount of LNG supply that is coming online globally in the next few years. The global market simply cannot accommodate U.S. volumes in excess of 12 Bcf/d before 2025 in any of the scenarios considered. Accordingly, while international demand continues to increase, the market must first work through a large amount of available LNG supply before turning to U.S.-sourced LNG.The reference case forecasts U.S. LNG exports of around 6.5 Bcf/d as there are abundant, competitive resources around the world that can be delivered to international markets via LNG or pipelines. Higher U.S. LNG exports require a variety of factors that limit the otherwise competitive production of natural gas outside of the U.S. Moreover, those factors must become increasingly restrictive to raise U.S. LNG exports over 12 Bcf/d.Across all of the scenarios assessed, “the macroeconomic impacts of LNG exports are marginally positive,” Medlock said. “Across the domestic cases, the positive impact of higher U.S. gas production exceeds the negative impacts of higher domestic natural gas prices associated with increased LNG exports. The overall macroeconomic impacts of increasing U.S. LNG exports to 20 Bcf/d from 12 Bcf/d are small, reflecting the small size of the natural gas sector and supporting industries relative to the over $13 trillion U.S. economy.”The full report is available here.-30-For more information or to schedule an interview with Medlock, contact David Ruth, director of national media relations at Rice, at [email protected] or 713-348-6327.Related materials:The full report is available at http://energy.gov/sites/prod/files/2015/12/f27/20151113_macro_impact_of_lng_exports_0.pdf.Medlock’s biography is available at http://bakerinstitute.org/experts/kenneth-b-medlock-iii/.Follow the Baker Institute on Twitter @BakerInstitute.Follow Rice News and Media Relations via Twitter @RiceUNews.Founded in 1993, Rice University’s Baker Institute ranks among the top 10 university-affiliated think tanks in the world. As a premier nonpartisan think tank, the institute conducts research on domestic and foreign policy issues with the goal of bridging the gap between the theory and practice of public policy. The institute’s strong track record of achievement reflects the work of its endowed fellows, Rice University faculty scholars and staff, coupled with its outreach to the Rice student body through fellow-taught classes — including a public policy course — and student leadership and internship programs. Learn more about the institute at www.bakerinstitute.org or on the institute’s blog, http://blogs.chron.com/bakerblog.last_img read more

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