Have a deep view into what people are curious about.

🔗 Africa 🔗 Africa/Tanzania 🔗 Primates

The Gombe Chimpanzee War was a violent conflict between two communities of chimpanzees in Gombe Stream National Park in Tanzania lasting from 1974 to 1978. The two groups were once unified in the Kasakela community. By 1974, researcher Jane Goodall noticed the community splintering. Over a span of eight months, a large party of chimpanzees separated themselves into the southern area of Kasakela and were renamed the Kahama community. The separatists consisted of six adult males, three adult females and their young. The Kasakela was left with eight adult males, twelve adult females and their young.

During the four-year conflict, all males of the Kahama community were killed, effectively disbanding the community. The victorious Kasakela then expanded into further territory but were later repelled by another community of chimpanzees.

🔗 Biography 🔗 Soviet Union 🔗 Russia 🔗 Biology 🔗 Biography/science and academia 🔗 Russia/science and education in Russia 🔗 Genetics 🔗 Russia/physical geography of Russia

Dmitry Konstantinovich Belyayev (Russian: Дми́трий Константи́нович Беля́ев, 17 July 1917 – 14 November 1985) was a Russian geneticist and academician who served as director of the Institute of Cytology and Genetics (IC&G) of the USSR Academy of Sciences, Novosibirsk, from 1959 to 1985. His decades-long effort to breed domesticated foxes was described by The New York Times as “arguably the most extraordinary breeding experiment ever conducted.” A 2010 article in Scientific American stated that Belyayev “may be the man most responsible for our understanding of the process by which wolves were domesticated into our canine companions.”

Beginning in the 1950s, in order to uncover the genetic basis of the distinctive behavioral and physiological attributes of domesticated animals, Belyayev and his team spent decades breeding the wild silver fox (Vulpes vulpes) and selecting for reproduction only those individuals in each generation that showed the least fear of humans. After several generations of controlled breeding, a majority of the silver foxes no longer showed any fear of humans and often wagged their tails and licked their human caretakers to show affection. They also began to display spotted coats, floppy ears, curled tails, as well as other physical attributes often found in domesticated animals, thus confirming Belyayev’s hypothesis that both the behavioral and physical traits of domesticated animals could be traced to "a collection of genes that conferred a propensity to tameness—a genotype that the foxes perhaps shared with any species that could be domesticated".

Belyayev’s experiments were the result of a politically motivated demotion, in response to defying the now discredited non-Mendellian theories of Lysenkoism, which were politically accepted in the Soviet Union at the time. Belyayev has since been vindicated in recent years by major scientific journals, and by the Soviet establishment as a pioneering figure in modern genetics.

🔗 Computer science

In computing, aspect-oriented programming (AOP) is a programming paradigm that aims to increase modularity by allowing the separation of cross-cutting concerns. It does so by adding behavior to existing code (an advice) without modifying the code itself, instead separately specifying which code is modified via a "pointcut" specification, such as "log all function calls when the function's name begins with 'set'". This allows behaviors that are not central to the business logic (such as logging) to be added to a program without cluttering the code core to the functionality.

AOP includes programming methods and tools that support the modularization of concerns at the level of the source code, while aspect-oriented software development refers to a whole engineering discipline.

Aspect-oriented programming entails breaking down program logic into distinct parts (so-called concerns, cohesive areas of functionality). Nearly all programming paradigms support some level of grouping and encapsulation of concerns into separate, independent entities by providing abstractions (e.g., functions, procedures, modules, classes, methods) that can be used for implementing, abstracting and composing these concerns. Some concerns "cut across" multiple abstractions in a program, and defy these forms of implementation. These concerns are called cross-cutting concerns or horizontal concerns.

Logging exemplifies a crosscutting concern because a logging strategy necessarily affects every logged part of the system. Logging thereby crosscuts all logged classes and methods.

All AOP implementations have some crosscutting expressions that encapsulate each concern in one place. The difference between implementations lies in the power, safety, and usability of the constructs provided. For example, interceptors that specify the methods to express a limited form of crosscutting, without much support for type-safety or debugging. AspectJ has a number of such expressions and encapsulates them in a special class, an aspect. For example, an aspect can alter the behavior of the base code (the non-aspect part of a program) by applying advice (additional behavior) at various join points (points in a program) specified in a quantification or query called a pointcut (that detects whether a given join point matches). An aspect can also make binary-compatible structural changes to other classes, like adding members or parents.

🔗 Physics 🔗 Electronics 🔗 Professional sound production

Pink noise or ​¹⁄_f noise is a signal or process with a frequency spectrum such that the power spectral density (energy or power per frequency interval) is inversely proportional to the frequency of the signal. In pink noise, each octave (halving or doubling in frequency) carries an equal amount of noise energy.

Pink noise is one of the most common signals in biological systems.

The name arises from the pink appearance of visible light with this power spectrum. This is in contrast with white noise which has equal intensity per frequency interval.

🔗 Biography 🔗 Internet culture 🔗 Comedy 🔗 Biography/arts and entertainment

@dril is a pseudonymous Twitter user best known for his idiosyncratic style of absurdist humor and non sequiturs. The account, its author, and the character associated with the tweets are all commonly referred to as dril (the handle without the at sign) or wint (the account's display name), both rendered lowercase but often capitalized by others. Since his first tweet in 2008, dril has become a popular and influential Twitter user with more than one million followers.

dril is one of the most notable accounts associated with "Weird Twitter", a subculture on the site that shares a surreal, ironic sense of humor. The character associated with dril is highly distinctive, often described as a bizarre reflection of a typical male American Internet user. Other social media users have repurposed dril's tweets for humorous or satiric effect in a variety of political and cultural contexts. Many of dril's tweets, phrases, and tropes have become familiar parts of Internet slang.

The author behind dril remained unknown for years, with the few available details about the author's life fueling speculation about his identity. In 2017, dril's author was "doxxed" (in other words, his identity was exposed) in a post that went viral and received media attention. After the doxxing, many Twitter users and journalists preferred to preserve dril's pseudonymity out of respect for the author's personal privacy and the character's mystique.

Beyond tweeting, dril has created animated short films and contributed illustrations and writing to other artists' collaborative projects. His first book, Dril Official "Mr. Ten Years" Anniversary Collection (2018), is a compilation of the account's "greatest hits" alongside new illustrations. In 2019 he announced the launch of a streaming web series called Truthpoint: Darkweb Rising, an InfoWars parody co-created with comedian Derek Estevez-Olsen for Adult Swim. Writers have praised dril for the originality and humor of his tweets; for example, the poet Patricia Lockwood called dril "a master of tone [and] character," and The A.V. Club dubbed him "arguably the most iconic Twitter account in the history of social media."

🔗 Mammals

The nocturnal bottleneck hypothesis is a hypothesis to explain several mammalian traits. In 1942, Gordon Lynn Walls described this concept which states that placental mammals were mainly or even exclusively nocturnal through most of their evolutionary story, starting with their origin 225 million years ago, and only ending with the demise of the non-avian dinosaurs 66 million years ago. While some mammal groups have later evolved to fill diurnal niches, the approximately 160 million years spent as nocturnal animals has left a lasting legacy on basal anatomy and physiology, and most mammals are still nocturnal.

Reasons for my No consensus closure of Wikipedia:Articles for deletion/Dwm (2nd nomination)

If you want to make any comments or ask questions about this closure, please use User talk:Flyguy649/Dwm rather than my talk page. I hope the community can live with my decision; if not, there is deletion review.

🔗 Computing

The MicroVAX 78032 (otherwise known as the DC333) is a microprocessor developed and fabricated by Digital Equipment Corporation (DEC) that implemented a subset of the VAX instruction set architecture (ISA). The 78032 was used exclusively in DEC's VAX-based systems, starting with the MicroVAX II in 1985. When clocked at a frequency of 5 MHz, the 78032's integer performance is comparable to the original VAX-11/780 of 1977. The microprocessor could be paired with the MicroVAX 78132 floating point accelerator for improved floating point performance.

The 78032 represented a number of firsts for DEC. It was DEC's first single-chip microprocessor implementation of the VAX ISA and DEC's first self-fabricated microprocessor. The MicroVAX 78032 is also notable as it was the first semiconductor device to be registered for protection under the Semiconductor Chip Protection Act of 1984.

The MicroVAX 78032 contains 125,000 transistors on an 8.7 by 8.6 mm (74.82 mm²) die that was fabricated in DEC's ZMOS process, a 3.0 µm NMOS logic process with two layers of aluminum interconnect. The die is packaged in a 68-pin surface-mounted leaded chip carrier.

🔗 Computer science 🔗 Systems 🔗 Systems/Scientific modeling

In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. Artificial Ants stand for multi-agent methods inspired by the behavior of real ants. The pheromone-based communication of biological ants is often the predominant paradigm used. Combinations of Artificial Ants and local search algorithms have become a method of choice for numerous optimization tasks involving some sort of graph, e.g., vehicle routing and internet routing. The burgeoning activity in this field has led to conferences dedicated solely to Artificial Ants, and to numerous commercial applications by specialized companies such as AntOptima.

As an example, Ant colony optimization is a class of optimization algorithms modeled on the actions of an ant colony. Artificial 'ants' (e.g. simulation agents) locate optimal solutions by moving through a parameter space representing all possible solutions. Real ants lay down pheromones directing each other to resources while exploring their environment. The simulated 'ants' similarly record their positions and the quality of their solutions, so that in later simulation iterations more ants locate better solutions. One variation on this approach is the bees algorithm, which is more analogous to the foraging patterns of the honey bee, another social insect.

This algorithm is a member of the ant colony algorithms family, in swarm intelligence methods, and it constitutes some metaheuristic optimizations. Initially proposed by Marco Dorigo in 1992 in his PhD thesis, the first algorithm was aiming to search for an optimal path in a graph, based on the behavior of ants seeking a path between their colony and a source of food. The original idea has since diversified to solve a wider class of numerical problems, and as a result, several problems have emerged, drawing on various aspects of the behavior of ants. From a broader perspective, ACO performs a model-based search and shares some similarities with estimation of distribution algorithms.