New Articles (Page 21)
To stay up to date you can also follow on Mastodon.
π Rat King
A rat king is a collection of rats or mice whose tails are intertwined and bound together in some way. This could be a result of an entangling material like hair, a sticky substance such as sap or gum, or the tails being tied together.
A similar phenomenon with squirrels has been observed, which has had modern documented examples.
Discussed on
- "Rat King" | 2026-03-22 | 10 Upvotes 1 Comments
π Ant mill
An ant mill is an observed phenomenon in which a group of army ants are separated from the main foraging party, lose the pheromone track and begin to follow one another, forming a continuously rotating circle, commonly known as a "death spiral" because the ants might eventually die of exhaustion. It has been reproduced in laboratories and has been produced in ant colony simulations. The phenomenon is a side effect of the self-organizing structure of ant colonies. Each ant follows the ant in front of it, which works until a slight deviation begins to occur, typically by an environmental trigger, and an ant mill forms. An ant mill was first described in 1921 by William Beebe, who observed a mill 1200Β ft (~370 m) in circumference. It took each ant 2.5 hours to make one revolution. Similar phenomena have been noted in processionary caterpillars and fish.
Discussed on
- "Ant Mill" | 2026-03-22 | 42 Upvotes 6 Comments
- "Ant mill" | 2022-01-22 | 251 Upvotes 154 Comments
π Albert's Swarm
Albert's swarm was an immense concentration of the Rocky Mountain locust that swarmed the Western United States in 1875. It was named after Albert Child, a physician interested in meteorology, who calculated the size of the swarm to 198,000 square miles (510,000Β km2) by multiplying the swarm's estimated speed with the time it took for it to move through southern Nebraska.
The 1875 swarm is referred to repeatedly in a western Missouri historical record that explains:
It was the year 1875 that will long be remembered by the people of at least four states, as the grasshopper year. The scourge struck Western Missouri April, 1875, and commenced devastating some of the fairest portions of our noble commonwealth. They gave Henry [County] an earnest and overwhelming visitation, and demonstrated with an amazing rapidity that their appetite was voracious, and that everything green belonged to them for their sustenance.
One estimate numbers the locusts in the swarm at 3.5 trillion. Another estimate numbers the swarm at 12.5 trillion, which is the greatest concentration of animals ever speculatively guessed, according to Guinness World Records.
Discussed on
- "Albert's Swarm" | 2026-03-21 | 16 Upvotes 3 Comments
π American cover-up of Japanese war crimes
The occupying United States government undertook the selective cover-up of some Japanese war crimes after the end of World War II in Asia, granting political immunity to military personnel who had engaged in human experimentation and other crimes against humanity, predominantly in mainland China. The pardon of Japanese war criminals, among whom were Unit 731's commanding officers General ShirΕ Ishii and General Masaji Kitano, was overseen by General of the Army Douglas MacArthur in September 1945. While a series of war tribunals and trials was organized, many of the high-ranking officials and doctors who devised and respectively performed the experiments were pardoned and never brought to justice due to the US government both classifying incriminating evidence, as well as blocking the prosecution access to key witnesses. As many as 12,000 people, most of them Chinese, died in Unit 731 alone and many more died in other facilities, such as Unit 100 and in field experiments throughout Manchuria.
Discussed on
- "American cover-up of Japanese war crimes" | 2026-03-21 | 42 Upvotes 10 Comments
π Wikipedia RFC on banning LLM contributions
Discussed on
- "Wikipedia RFC on banning LLM contributions" | 2026-03-20 | 48 Upvotes 2 Comments
π Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo
"Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo" is a grammatically correct sentence in American English, often presented as an example of how homonyms and homophones can be used to create complicated linguistic constructs through lexical ambiguity. It has been discussed in literature in various forms since 1967, when it appeared in Dmitri Borgmann's Beyond Language: Adventures in Word and Thought.
The sentence employs three distinct meanings of the word buffalo:
- as a proper noun to refer to a specific place named Buffalo, the city of Buffalo, New York, being the most notable;
- as a verb (uncommon in regular usage) to buffalo, meaning "to bully, harass, or intimidate" or "to baffle"; and
- as a noun to refer to the animal, bison (often called buffalo in North America). The plural is also buffalo.
An expanded form of the sentence which preserves the original word order is: "Buffalo bison, that other Buffalo bison bully, also bully Buffalo bison."
Discussed on
- "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo" | 2026-03-16 | 14 Upvotes 3 Comments
- "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo" | 2025-03-01 | 19 Upvotes 3 Comments
- "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo" | 2023-09-07 | 178 Upvotes 95 Comments
- "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo" | 2023-06-24 | 17 Upvotes 4 Comments
- "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo" | 2023-05-22 | 19 Upvotes 5 Comments
- "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo" | 2020-02-10 | 29 Upvotes 19 Comments
- "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo" | 2018-11-06 | 18 Upvotes 6 Comments
- "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo" | 2016-05-08 | 52 Upvotes 17 Comments
- "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo" | 2010-02-03 | 174 Upvotes 69 Comments
π Kangina
Kangina (Dari: Ϊ©ΩΪ―ΫΩΩ, lit.β'treasure'), also called Gangina, is the traditional Afghan technique of preserving fresh fruit, particularly grapes, in airtight discs formed from mud and straw. The centuries-old technique is indigenous to Afghanistan's rural center and north, where remote communities that cannot import fresh fruit eat kangina-preserved fresh grapes throughout the winter, and merchants use kangina to safely store and transport grapes for sale at market. Grapes preserved using kangina in modern Afghanistan are typically of the thick-skinned Taifi or Kishmishi varieties, which are harvested later in the season and remain fresh in the mud vessels for up to six months.
The method, a form of passive controlled-atmosphere storage, works by sealing fruit in the clay-rich mud, restricting flow of air, moisture and microbes, much as a plastic bag would. Discs are formed from two bowl-shaped pieces, which are sculpted from mud and straw, and baked in the sun before being filled with up to 1β2 kilograms (2.2β4.4Β lb) of un-bruised fruit and sealed with more mud. They are kept dry and cool, away from direct sunlight. Gradual permeation of gas through the clay barrier allows oxygen to enter the container, keeping the grapes alive, while the elevated concentration of carbon dioxide inside the package inhibits the grapes' metabolism and prevents the growth of fungus. The grapes are prevented from drying out, and the mud absorbs liquid which would otherwise lead to bacterial and fungal growth.
The practice of storing grapes in mud and straw has been recorded as far back as the 12th century: in his Book of Agriculture, Sevillan agronomist Ibn al-'Awwam noted layering grapes with straw in mud-sealed glass containers or "cowpat bowls" as an extant technique of preservation in Andalusia.
Kangina are inexpensive, eco-friendly, and effective vessels for the preservation of fresh fruit. A 2023 study found kangina and polystyrene foam boxes to be the most effective vessels for preserving grapes. The containers are, however, heavy, unwieldy, and prone to absorbing moisture.
Discussed on
- "Kangina" | 2026-03-15 | 117 Upvotes 9 Comments
π 1997 KylβBingaman Amendment prohibits high res satellite imagery of Israel
The KylβBingaman Amendment (Public Law 104-201, Section 1064) is a United States law. It was put into force by the Military Defense National Defense Authorization Act for 1997.
The KylβBingaman Amendment (KBA) prohibits US authorities from granting a license for collecting or disseminating high resolution satellite imagery of Israel at a higher resolution than is available from other commercial sources, that is, from companies outside of the United States. An exception exists if this is done by a US federal agency, or if it is done in order to abolish the secrecy of such recordings.
U.S. law mandates U.S. government censorship of American commercial satellite images of no country in the world besides that of Israel. The largest and most important global sources of commercial satellite imagery, such as Maxar Technologies, Capella, and Umbra, and the largest and widely-used online resources, such as Google and Bing, are American and this makes KBA a powerful instrument of U.S. government suppression of information. For example, as a result of KBA, images on internet platforms such as Google Earth have been deliberately blurred.
π Nagle's Algorithm
Nagle's algorithm is a means of improving the efficiency of TCP/IP networks by reducing the number of packets that need to be sent over the network. It was defined by John Nagle while working for Ford Aerospace. It was published in 1984 as a Request for Comments (RFC) with title Congestion Control in IP/TCP Internetworks in RFCΒ 896.
The RFC describes what he called the "small-packet problem", where an application repeatedly emits data in small chunks, frequently only 1 byte in size. Since TCP packets have a 40-byte header (20 bytes for TCP, 20 bytes for IPv4), this results in a 41-byte packet for 1 byte of useful information, a huge overhead. This situation often occurs in Telnet sessions, where most keypresses generate a single byte of data that is transmitted immediately. Worse, over slow links, many such packets can be in transit at the same time, potentially leading to congestion collapse.
Nagle's algorithm works by combining a number of small outgoing messages and sending them all at once. Specifically, as long as there is a sent packet for which the sender has received no acknowledgment, the sender should keep buffering its output until it has a full packet's worth of output, thus allowing output to be sent all at once.
Discussed on
- "Nagle's Algorithm" | 2026-03-12 | 10 Upvotes 1 Comments
- "Nagle's Algorithm" | 2022-12-30 | 25 Upvotes 2 Comments
π Elite Overproduction
Elite overproduction is a concept developed by Peter Turchin, which describes the condition of a society which is producing too many potential elite-members relative to its ability to absorb them into the power structure. This, he hypothesizes, is a cause for social instability, as those left out of power feel aggrieved by their relatively low socioeconomic status.
Turchin said that this situation explained social disturbances during the late Roman empire and the French Wars of Religion, and predicted in 2010 that this situation would cause social unrest in the United States of America during the 2020s. According to Turchin and Jack Goldstone, periods of political instability have throughout human history been due to the purely self-interested behavior of the elite. When the economy faced a surge in the workforce, which exerted a downward pressure on wages, the elite generally kept much of the wealth generated to themselves, resisting taxation and income redistribution. In the face of intensifying competition, they also sought to restrict the window of opportunity, to preserve their power and status for their descendants. These actions exacerbated inequality, a key driver of sociopolitical turbulence due to the proneness of the relatively well-off to radicalism. Widespread progressive political beliefs among university graduates, for instance, can be due to widespread underemployment rather than from exposure to progressive ideas or experiences during their studies.
In the case of the United States, by the 2010s, it became clear that the cost of higher education has ballooned over the previous three to four decadesβfaster than inflation, in factβthanks to growing demand. For this prediction, Turchin used current data and the structural-demographic theory, a mathematical model of how population changes affect the behavior of the state, the elite, and the commons, created by Jack Goldstone. Goldstone himself predicted using his model that in the twenty-first century, the United States would elect a national populist leader. Elite overproduction has been cited as a root cause of political tension in the U.S., as so many well-educated Millennials are either unemployed, underemployed, or otherwise not achieving the high status they expect. Even then, the nation continued to produce excess PhD holders before the COVID-19 pandemic hit, especially in the humanities and social sciences, for which employment prospects were dim. Moreover, according to projections by the U.S. Census Bureau, the share of people in their 20s continued to grow till the end of the 2010s, meaning the youth bulge would likely not fade away before the 2020s. As such the gap between the supply and demand in the labor market would likely not fall before then, and falling or stagnant wages generate sociopolitical stress.
In the United Kingdom, there was simply not enough working-class Britons disenchanted with the status quo to support the Brexit movement, which was also buoyed by many highly educated voters.
However, Turchin's model cannot foretell precisely how a crisis will unfold; it can only yield probabilities. Turchin likened this to the accumulation of deadwood in a forest over many years, paving the way for a cataclysmic forest fire later on. It is possible to predict a massive conflagration, but not what causes it.
Discussed on
- "Elite Overproduction" | 2026-03-06 | 82 Upvotes 97 Comments
- "Elite Overproduction" | 2024-11-13 | 54 Upvotes 14 Comments
- "Elite Overproduction" | 2021-11-18 | 11 Upvotes 2 Comments