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🔗 Climate change 🔗 Engineering

Cold district heating is a technical variant of a district heating network that operates at low transmission temperatures well below those of conventional district heating systems and can provide both space heating and cooling. Transmission temperatures in the range of approx. 10 to 25 °C are common, allowing different consumers to heat and cool simultaneously and independently of each other. Hot water is produced and the building heated by water heat pumps, which obtain their thermal energy from the heating network, while cooling can be provided either directly via the cold heat network or, if necessary, indirectly via chillers. Cold local heating is sometimes also referred to as an anergy network. The collective term for such systems in scientific terminology is 5th generation district heating and cooling. Due to the possibility of being operated entirely by renewable energies and at the same time contributing to balancing the fluctuating production of wind turbines and photovoltaic systems, cold local heating networks are considered a promising option for a sustainable, potentially greenhouse gas and emission-free heat supply.

🔗 Aviation 🔗 Military history 🔗 Military history/Military aviation 🔗 Military history/North American military history 🔗 Military history/United States military history 🔗 Military history/Military science, technology, and theory 🔗 Aviation/aircraft 🔗 Military history/Cold War

The Ryan Model 147 Lightning Bug is a jet-powered drone, or unmanned aerial vehicle, produced and developed by Ryan Aeronautical from the earlier Ryan Firebee target drone series.

Beginning in 1962, the Model 147 was introduced as a reconnaissance RPV (Remotely Piloted Vehicle, nomenclature of that era) for a United States Air Force project named Fire Fly. Over the next decade — assisted with secret funding from the recently formed National Reconnaissance Office along with support of the Strategic Air Command and Ryan Aeronautical's own resources — the basic Model 147 design would be developed into a diverse series of variants configured for a wide array of mission-specific roles, with multiple new systems, sensors and payloads used, modified and improved upon during the operational deployment of these drones in Southeast Asia. Missions performed by the Model 147 series RPVs included high- and low-altitude photographic and electronic aerial reconnaissance, surveillance, decoy, electronic warfare, signals intelligence, and psychological warfare.

The Ryan drones were designed without landing gear for simplicity and to save weight. Like its Firebee predecessor, the Model 147 could either be air-launched from a larger carrier aircraft or launched from the ground using a solid rocket booster; at completion of its mission the drone deployed its own recovery parachute which could be snatched in mid-air by a recovery helicopter (in a combat environment it was naturally not desired to recover the drone on, from or near enemy territory and ground or water impact could also cause damage to or loss of the drone or its payload).

At the end of the Vietnam War in 1975 the U.S. military's available funding and need for combat drones severely declined, even as Teledyne Ryan introduced further advanced developments of the Model 147 series such as the BGM-34 strike and defense suppression RPVs. Costs of maintaining the Lightning Bugs at full readiness could no longer be justified. Only by the 1990s did substantial interest, organization and funding again emerge from the U.S. Air Force and intelligence agencies to develop, acquire and widely deploy combat UAVs.

🔗 Judaism

Sabbath mode, also known as Shabbos mode (Ashkenazi pronunciation) or Shabbat mode, is a feature in many modern home appliances, including ovens and refrigerators, which is intended to allow the appliances to be used (subject to various constraints) by Shabbat-observant Jews on the Shabbat and Jewish holidays. The mode usually overrides the usual, everyday operation of the electrical appliance and makes the operation of the appliance comply with the rules of Halakha (Jewish law).

🔗 Ancient Near East 🔗 Meteorology 🔗 Meteorology/droughts and fire events 🔗 Ancient Egypt

The 4.2-kiloyear BP aridification event was one of the most severe climatic events of the Holocene epoch. It defines the beginning of the current Meghalayan age in the Holocene epoch. Starting in about 2200 BC, it probably lasted the entire 22nd century BC. It has been hypothesised to have caused the collapse of the Old Kingdom in Egypt as well as the Akkadian Empire in Mesopotamia, and the Liangzhu culture in the lower Yangtze River area. The drought may also have initiated the collapse of the Indus Valley Civilisation, with some of its population moving southeastward to follow the movement of their desired habitat, as well as the migration of Indo-European-speaking people into India.

Some scientists disagree with this conclusion and point out that the event was neither a global drought nor did it happen in a clear timeline.

🔗 Economics 🔗 Law Enforcement

The iron law of prohibition is a term coined by Richard Cowan in 1986 which posits that as law enforcement becomes more intense, the potency of prohibited substances increases. Cowan put it this way: "the harder the enforcement, the harder the drugs."

This law is an application of the Alchian–Allen effect; Libertarian judge James P. Gray calls the law the "cardinal rule of prohibition", and notes that is a powerful argument for the legalization of drugs. It is based on the premise that when drugs or alcohol are prohibited, they will be produced in black markets in more concentrated and powerful forms, because these more potent forms offer better efficiency in the business model—they take up less space in storage, less weight in transportation, and they sell for more money. Economist Mark Thornton writes that the iron law of prohibition undermines the argument in favor of prohibition, because the higher potency forms are less safe for the consumer.

🔗 Disambiguation

A rat king is a rare phenomenon where a group of rats' tails become entangled.

Rat King or Ratking may also refer to:

🔗 Electronics 🔗 Electrical engineering

A thyratron is a type of gas-filled tube used as a high-power electrical switch and controlled rectifier. Thyratrons can handle much greater currents than similar hard-vacuum tubes. Electron multiplication occurs when the gas becomes ionized, producing a phenomenon known as a Townsend discharge. Gases used include mercury vapor, xenon, neon, and (in special high-voltage applications or applications requiring very short switching times) hydrogen. Unlike a vacuum tube (valve), a thyratron cannot be used to amplify signals linearly.

In the 1920s, thyratrons were derived from early vacuum tubes such as the UV-200, which contained a small amount of argon gas to increase its sensitivity as a radio signal detector, and the German LRS relay tube, which also contained argon gas. Gas rectifiers, which predated vacuum tubes, such as the argon-filled General Electric "Tungar bulb" and the Cooper-Hewitt mercury-pool rectifier, also provided an influence. Irving Langmuir and G. S. Meikle of GE are usually cited as the first investigators to study controlled rectification in gas tubes, about 1914. The first commercial thyratrons appeared circa 1928.

The term "thyratron" is derived from Ancient Greek "θύρα" ("thyra"), meaning "door" or "valve". The term "thyristor" was further derived from a combination of "thyratron" and "transistor". Since the 1960s thyristors have replaced thyratrons in most low- and medium-power applications.

🔗 Computing 🔗 Computer science 🔗 Mathematics 🔗 Physics 🔗 Statistics

Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic in principle. They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to use other approaches. Monte Carlo methods are mainly used in three problem classes: optimization, numerical integration, and generating draws from a probability distribution.

In physics-related problems, Monte Carlo methods are useful for simulating systems with many coupled degrees of freedom, such as fluids, disordered materials, strongly coupled solids, and cellular structures (see cellular Potts model, interacting particle systems, McKean–Vlasov processes, kinetic models of gases).

Other examples include modeling phenomena with significant uncertainty in inputs such as the calculation of risk in business and, in mathematics, evaluation of multidimensional definite integrals with complicated boundary conditions. In application to systems engineering problems (space, oil exploration, aircraft design, etc.), Monte Carlo–based predictions of failure, cost overruns and schedule overruns are routinely better than human intuition or alternative "soft" methods.

In principle, Monte Carlo methods can be used to solve any problem having a probabilistic interpretation. By the law of large numbers, integrals described by the expected value of some random variable can be approximated by taking the empirical mean (a.k.a. the sample mean) of independent samples of the variable. When the probability distribution of the variable is parameterized, mathematicians often use a Markov chain Monte Carlo (MCMC) sampler. The central idea is to design a judicious Markov chain model with a prescribed stationary probability distribution. That is, in the limit, the samples being generated by the MCMC method will be samples from the desired (target) distribution. By the ergodic theorem, the stationary distribution is approximated by the empirical measures of the random states of the MCMC sampler.

In other problems, the objective is generating draws from a sequence of probability distributions satisfying a nonlinear evolution equation. These flows of probability distributions can always be interpreted as the distributions of the random states of a Markov process whose transition probabilities depend on the distributions of the current random states (see McKean–Vlasov processes, nonlinear filtering equation). In other instances we are given a flow of probability distributions with an increasing level of sampling complexity (path spaces models with an increasing time horizon, Boltzmann–Gibbs measures associated with decreasing temperature parameters, and many others). These models can also be seen as the evolution of the law of the random states of a nonlinear Markov chain. A natural way to simulate these sophisticated nonlinear Markov processes is to sample multiple copies of the process, replacing in the evolution equation the unknown distributions of the random states by the sampled empirical measures. In contrast with traditional Monte Carlo and MCMC methodologies, these mean-field particle techniques rely on sequential interacting samples. The terminology mean field reflects the fact that each of the samples (a.k.a. particles, individuals, walkers, agents, creatures, or phenotypes) interacts with the empirical measures of the process. When the size of the system tends to infinity, these random empirical measures converge to the deterministic distribution of the random states of the nonlinear Markov chain, so that the statistical interaction between particles vanishes.

Despite its conceptual and algorithmic simplicity, the computational cost associated with a Monte Carlo simulation can be staggeringly high. In general the method requires many samples to get a good approximation, which may incur an arbitrarily large total runtime if the processing time of a single sample is high. Although this is a severe limitation in very complex problems, the embarrassingly parallel nature of the algorithm allows this large cost to be reduced (perhaps to a feasible level) through parallel computing strategies in local processors, clusters, cloud computing, GPU, FPGA, etc.

🔗 Aviation 🔗 Military history 🔗 Military history/Military aviation 🔗 Military history/Military science, technology, and theory 🔗 Military history/Weaponry 🔗 Aviation/aircraft 🔗 Military history/World War II 🔗 Military history/European military history 🔗 Military history/British military history

A bouncing bomb is a bomb designed to bounce to a target across water in a calculated manner to avoid obstacles such as torpedo nets, and to allow both the bomb's speed on arrival at the target and the timing of its detonation to be pre-determined, in a similar fashion to a regular naval depth charge. The inventor of the first such bomb was the British engineer Barnes Wallis, whose "Upkeep" bouncing bomb was used in the RAF's Operation Chastise of May 1943 to bounce into German dams and explode underwater, with effect similar to the underground detonation of the Grand Slam and Tallboy earthquake bombs, both of which he also invented.

🔗 United States 🔗 Biography 🔗 Florida 🔗 Crime and Criminal Biography 🔗 Firefighting

Joseph "Bum" Farto (July 3, 1919 – February 16, 1976) was a fire chief and convicted drug dealer in Key West, Florida who disappeared in 1976.