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πŸ”— Atmos Clock

πŸ”— Brands πŸ”— Time

Atmos is the brand name of a mechanical torsion pendulum clock manufactured by Jaeger-LeCoultre in Switzerland which does not need to be wound manually. It gets the energy it needs to run from temperature and atmospheric pressure changes in the environment, and can run for years without human intervention.

The clock is driven by a mainspring, which is wound by the expansion and contraction of liquid and gaseous ethyl chloride in an internal hermetically sealed bellows. The ethyl chloride vaporises into an expansion chamber as the temperature rises, compressing a spiral spring; with a fall in temperature the gas condenses and the spring slackens. This motion constantly winds the mainspring. A temperature variation of only one degree in the range between 15Β Β°C (59Β Β°F) and 30Β Β°C (86Β Β°F), or a pressure variation of 3 mmHg, is sufficient for two days' operation.

In order to run the clock on this small amount of energy, everything inside the Atmos has to work in as friction-free a manner as possible. For timekeeping it uses a torsion pendulum, which consumes less energy than an ordinary pendulum. The torsion pendulum has a period of precisely one minute; thirty seconds to rotate in one direction and thirty seconds to return to the starting position. This is thirty times slower than the 0.994 m (39.1 in) seconds pendulum typically found in a longcase clock, where each swing (or half-period) takes one second.

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πŸ”— List of countries by tax revenue to GDP ratio

πŸ”— Taxation

This article lists countries alphabetically, with total tax revenue as a percentage of gross domestic product (GDP) for the listed countries. The tax percentage for each country listed in the source has been added to the chart.

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πŸ”— Immortal Game

πŸ”— Chess

The Immortal Game was a chess game played by Adolf Anderssen and Lionel Kieseritzky on 21 June 1851 in London, during a break of the first international tournament. The bold sacrifices made by Anderssen to secure victory have made it one of the most famous chess games of all time. Anderssen gave up both rooks and a bishop, then his queen, checkmating his opponent with his three remaining minor pieces. In 1996, Bill Hartston called the game an achievement "perhaps unparalleled in chess literature".

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πŸ”— Tobler's First Law of Geography

πŸ”— Geography

The First Law of Geography, according to Waldo Tobler, is "everything is related to everything else, but near things are more related than distant things." This first law is the foundation of the fundamental concepts of spatial dependence and spatial autocorrelation and is utilized specifically for the inverse distance weighting method for spatial interpolation and to support the regionalized variable theory for kriging. It is a modern formulation of David Hume's principle of contiguity.

Tobler first presented his seminal idea during a meeting of the International Geographical Union's Commission on Qualitative Methods held in 1969 and later published by him in 1970. Though simple in its presentation, this idea is profound. Without it, "the full range of conditions anywhere on the Earth's surface could in principle be found packed within any small area. There would be no regions of approximately homogeneous conditions to be described by giving attributes to area objects. Topographic surfaces would vary chaotically, with slopes that were everywhere infinite, and the contours of such surfaces would be infinitely dense and contorted. Spatial analysis, and indeed life itself, would be impossible."

Less well known is his second law, which complements the first: "The phenomenon external to an area of interest affects what goes on inside".

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πŸ”— Enteric nervous system

πŸ”— Animal anatomy πŸ”— Neuroscience πŸ”— Anatomy πŸ”— Anatomy/Neuroanatomy

The enteric nervous system (ENS) or intrinsic nervous system is one of the main divisions of the autonomic nervous system (ANS) and consists of a mesh-like system of neurons that governs the function of the gastrointestinal tract. It is capable of acting independently of the sympathetic and parasympathetic nervous systems, although it may be influenced by them. The ENS is also called the second brain.It is derived from neural crest cells.

The enteric nervous system is capable of operating independently of the brain and spinal cord, but does rely on innervation from the autonomic nervous system via the vagus nerve and prevertebral ganglia in healthy subjects. However, studies have shown that the system is operable with a severed vagus nerve. The neurons of the enteric nervous system control the motor functions of the system, in addition to the secretion of gastrointestinal enzymes. These neurons communicate through many neurotransmitters similar to the CNS, including acetylcholine, dopamine, and serotonin. The large presence of serotonin and dopamine in the gut are key areas of research for neurogastroenterologists.

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πŸ”— The Indiana Pi Bill

πŸ”— United States πŸ”— Mathematics πŸ”— Law πŸ”— History of Science πŸ”— United States/Indiana

The Indiana Pi Bill is the popular name for bill #246 of the 1897 sitting of the Indiana General Assembly, one of the most notorious attempts to establish mathematical truth by legislative fiat. Despite its name, the main result claimed by the bill is a method to square the circle, rather than to establish a certain value for the mathematical constant Ο€, the ratio of the circumference of a circle to its diameter. The bill, written by the crank Edward J. Goodwin, does imply various incorrect values of Ο€, such as 3.2. The bill never became law, due to the intervention of Professor C. A. Waldo of Purdue University, who happened to be present in the legislature on the day it went up for a vote.

The impossibility of squaring the circle using only compass and straightedge constructions, suspected since ancient times, was rigorously proven in 1882 by Ferdinand von Lindemann. Better approximations of Ο€ than those implied by the bill have been known since ancient times.

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πŸ”— Intel iAPX 432

πŸ”— Computing πŸ”— Computing/Computer hardware

The iAPX 432 (Intel Advanced Performance Architecture) is a discontinued computer architecture introduced in 1981. It was Intel's first 32-bit processor design. The main processor of the architecture, the general data processor, is implemented as a set of two separate integrated circuits, due to technical limitations at the time. Although some early 8086, 80186 and 80286-based systems and manuals also used the iAPX prefix for marketing reasons, the iAPX 432 and the 8086 processor lines are completely separate designs with completely different instruction sets.

The project started in 1975 as the 8800 (after the 8008 and the 8080) and was intended to be Intel's major design for the 1980s. Unlike the 8086, which was designed the following year as a successor to the 8080, the iAPX 432 was a radical departure from Intel's previous designs meant for a different market niche, and completely unrelated to the 8080 or x86 product lines.

The iAPX 432 project is considered a commercial failure for Intel, and was discontinued in 1986.

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πŸ”— Disneyland with Death Penalty

πŸ”— Freedom of speech πŸ”— Journalism πŸ”— Singapore

"Disneyland with the Death Penalty" is a 4,500-word article about Singapore written by William Gibson. His first major piece of non-fiction, it was first published as the cover story for Wired magazine's September/October 1993 issue (1.4).

The article follows Gibson's observations of the architecture, phenomenology and culture of Singapore, and the clean, bland and conformist impression the city-state conveys during his stay. Its title and central metaphorβ€”Singapore as Disneyland with the death penaltyβ€”is a reference to the authoritarian artifice the author perceives the city-state to be. Singapore, Gibson details, is lacking any sense of creativity or authenticity, absent of any indication of its history or underground culture. He finds the government to be pervasive, corporatist and technocratic, and the judicial system rigid and draconian. Singaporeans are characterized as consumerists of insipid taste. The article is accentuated by local news reports of criminal trials by which the author illustrates his observations, and bracketed by contrasting descriptions of the Southeast Asian airports he arrives and leaves by.

Though Gibson's first major piece of non-fiction, the article had an immediate and lasting impact. The Singaporean government banned Wired upon the publication of the issue. The phrase "Disneyland with the death penalty" came to stand internationally for an authoritarian and austere reputation that the city-state found difficult to shake off.

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πŸ”— IBM 5100

πŸ”— Computing

The IBM 5100 Portable Computer is a portable computer (one of the first) introduced in September 1975, six years before the IBM Personal Computer. It was the evolution of a prototype called the SCAMP (Special Computer APL Machine Portable) that was developed at the IBM Palo Alto Scientific Center in 1973. In January 1978, IBM announced the IBM 5110, its larger cousin, and in February 1980 IBM announced the IBM 5120. The 5100 was withdrawn in March 1982.

When the IBM PC was introduced in 1981, it was originally designated as the IBM 5150, putting it in the "5100" series, though its architecture was unrelated to the IBM 5100's.

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πŸ”— Extreme Learning Machine

πŸ”— Statistics

Extreme learning machines are feedforward neural networks for classification, regression, clustering, sparse approximation, compression and feature learning with a single layer or multiple layers of hidden nodes, where the parameters of hidden nodes (not just the weights connecting inputs to hidden nodes) need not be tuned. These hidden nodes can be randomly assigned and never updated (i.e. they are random projection but with nonlinear transforms), or can be inherited from their ancestors without being changed. In most cases, the output weights of hidden nodes are usually learned in a single step, which essentially amounts to learning a linear model. The name "extreme learning machine" (ELM) was given to such models by its main inventor Guang-Bin Huang.

According to their creators, these models are able to produce good generalization performance and learn thousands of times faster than networks trained using backpropagation. In literature, it also shows that these models can outperform support vector machines (SVM) and SVM provides suboptimal solutions in both classification and regression applications.

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