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Cookie Run: Kingdom
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Gameplay
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Cookies can be powered up by various means. General stats, which are HP, CRIT%, Attack, and Defense, are upgraded by leveling up the characters, which is primarily done through EXP Jellies. EXP Jellies are obtained from playing through the game's multiple modes or from Cookie Houses that give EXP Jellies over time. The power of a skill can be increased with skill powders, which are obtained through daily bounties that give a specific type of skill powder. Toppings can be put on a cookie to improve other stats, such as how long it takes for a skill to cool down or how much a cookie will be affected by a debuff. Up to 5 can be equipped, and they have to be upgraded using coins and topping pieces. Some cookies can be given items called Magic Candies that power up and give new effects to their skill. Magic Candies require a specific type of crystal and resonant ingredient to upgrade. Cookies are obtained through soulstones, or the Cookie Gacha, and obtaining a certain amount of soulstones for a cookie if you already have it will give you a chance to promote it up to 5 stars, which greatly increases HP, Attack, and Defense. After a cookie has reached 5 stars, they can be upgraded further through Ascension, which requires Soulcores (a version of Soulstones that is unlocked after promoting a cookie to 5 stars) and Soul Essences.
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Cookie Run: Kingdom
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Gameplay
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The main story mode, known as "World Exploration," contains lots of levels that are played in order. Each level is played by using a team of Cookies to attack multiple enemies and, on some levels, making their cookies jump to collect coins, similar to previous Cookie Run games. Another major game mode is Kingdom Arena, where players can advance their tier by battling other players. Over time, other modes are added that function in a similar way but with different approaches.
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Cookie Run: Kingdom
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Story
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In a world populated with anthropomorphized dessert items (created by witches using cookie batter and Life Powder), the 5 Ancient Cookies - Pure Vanilla, White Lily, Hollyberry, Dark Cacao, and Golden Cheese - created their own kingdoms and were given Soul Jams, which granted them special powers and immortality. One day, a certain cookie wanted to know about the origin and creation of cookies and tried to contact the witches to seek an answer. Upon learning the horrible truth that cookies were meant to be eaten, the cookie falls into the ultimate dough and is re-baked as Dark Enchantress Cookie, who planned to use Cake Monsters to create a new world order. Pure Vanilla was forced to seal Dark Enchantress Cookie away and have the Ancient Cookies fall into hiding, leaving their kingdoms in disarray.
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Cookie Run: Kingdom
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Story
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A long time after Dark Enchantress Cookie is sealed away, GingerBrave was baked by a witch and escaped. He later learns that his friends, Wizard Cookie and Strawberry Cookie, has escaped from the witch too. They were found by the Sugar Gnomes and they started to rebuild a long-forgotten kingdom and explore Earthbread, the Cookie world.
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Cookie Run: Kingdom
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Reception
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The game had gained massive popularity in the wake of Genshin Impact's anniversary rewards controversy and the similar free-to-play gacha model featured in both of the games.Cookie Run: Kingdom is ranked 31st in the Free Role-Playing Game category in Thailand. In terms of free games, Japan ranked 1st on the Apple App Store and Google Play and 3rd in the Free Role-Playing game category in the United States. It was also ranked 1st in South Korea, 2nd in Taiwan, 3rd in Thailand, and 5th in Hong Kong in the Free Game on Apple App Store category in January 2021. In South Korea, Taiwan, and Thailand, the game's revenue is ranked 1st on the Apple App Store, and in Hong Kong and Singapore, it is ranked 3rd in January 2021. Cookie Run: Kingdom had 10 million downloads in the first two months after its release and has been downloaded over 150 million times as of June 2021.
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Carbon-14
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Carbon-14
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Carbon-14, C-14, 14C or radiocarbon, is a radioactive isotope of carbon with an atomic nucleus containing 6 protons and 8 neutrons. Its presence in organic materials is the basis of the radiocarbon dating method pioneered by Willard Libby and colleagues (1949) to date archaeological, geological and hydrogeological samples. Carbon-14 was discovered on February 27, 1940, by Martin Kamen and Sam Ruben at the University of California Radiation Laboratory in Berkeley, California. Its existence had been suggested by Franz Kurie in 1934.There are three naturally occurring isotopes of carbon on Earth: carbon-12 (12C), which makes up 99% of all carbon on Earth; carbon-13 (13C), which makes up 1%; and carbon-14 (14C), which occurs in trace amounts, making up about 1 or 1.5 atoms per 1012 atoms of carbon in the atmosphere. Carbon-12 and carbon-13 are both stable, while carbon-14 is unstable and has a half-life of 5700±30 years. Carbon-14 has a maximum specific activity of 62.4 mCi/mmol (2.31 GBq/mmol), or 164.9 GBq/g. Carbon-14 decays into nitrogen-14 (14N) through beta decay. A gram of carbon containing 1 atom of carbon-14 per 1012 atoms will emit ~0.2 beta particles per second. The primary natural source of carbon-14 on Earth is cosmic ray action on nitrogen in the atmosphere, and it is therefore a cosmogenic nuclide. However, open-air nuclear testing between 1955 and 1980 contributed to this pool.
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Carbon-14
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Carbon-14
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The different isotopes of carbon do not differ appreciably in their chemical properties. This resemblance is used in chemical and biological research, in a technique called carbon labeling: carbon-14 atoms can be used to replace nonradioactive carbon, in order to trace chemical and biochemical reactions involving carbon atoms from any given organic compound.
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Carbon-14
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Radioactive decay and detection
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Carbon-14 goes through radioactive beta decay: 146C → 147N + e− + νe + 156.5 keVBy emitting an electron and an electron antineutrino, one of the neutrons in the carbon-14 atom decays to a proton and the carbon-14 (half-life of 5,730 ± 40 years) decays into the stable (non-radioactive) isotope nitrogen-14.
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Carbon-14
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Radioactive decay and detection
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As usual with beta decay, almost all the decay energy is carried away by the beta particle and the neutrino. The emitted beta particles have a maximum energy of about 156 keV, while their weighted mean energy is 49 keV. These are relatively low energies; the maximum distance traveled is estimated to be 22 cm in air and 0.27 mm in body tissue. The fraction of the radiation transmitted through the dead skin layer is estimated to be 0.11. Small amounts of carbon-14 are not easily detected by typical Geiger–Müller (G-M) detectors; it is estimated that G-M detectors will not normally detect contamination of less than about 100,000 disintegrations per minute (0.05 µCi). Liquid scintillation counting is the preferred method although more recently, accelerator mass spectrometry has become the method of choice; it counts all the carbon-14 atoms in the sample and not just the few that happen to decay during the measurements; it can therefore be used with much smaller samples (as small as individual plant seeds), and gives results much more quickly. The G-M counting efficiency is estimated to be 3%. The half-distance layer in water is 0.05 mm.
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Carbon-14
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Radiocarbon dating
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Radiocarbon dating is a radiometric dating method that uses (14C) to determine the age of carbonaceous materials up to about 60,000 years old. The technique was developed by Willard Libby and his colleagues in 1949 during his tenure as a professor at the University of Chicago. Libby estimated that the radioactivity of exchangeable carbon-14 would be about 14 disintegrations per minute (dpm) per gram of pure carbon, and this is still used as the activity of the modern radiocarbon standard. In 1960, Libby was awarded the Nobel Prize in chemistry for this work.
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Carbon-14
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Radiocarbon dating
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One of the frequent uses of the technique is to date organic remains from archaeological sites. Plants fix atmospheric carbon during photosynthesis, so the level of 14C in plants and animals when they die approximately equals the level of 14C in the atmosphere at that time. However, it decreases thereafter from radioactive decay, allowing the date of death or fixation to be estimated. The initial 14C level for the calculation can either be estimated, or else directly compared with known year-by-year data from tree-ring data (dendrochronology) up to 10,000 years ago (using overlapping data from live and dead trees in a given area), or else from cave deposits (speleothems), back to about 45,000 years before the present. A calculation or (more accurately) a direct comparison of carbon-14 levels in a sample, with tree ring or cave-deposit carbon-14 levels of a known age, then gives the wood or animal sample age-since-formation. Radiocarbon is also used to detect disturbance in natural ecosystems; for example, in peatland landscapes, radiocarbon can indicate that carbon which was previously stored in organic soils is being released due to land clearance or climate change.Cosmogenic nuclides are also used as proxy data to characterize cosmic particle and solar activity of the distant past.
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Carbon-14
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Origin
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Natural production in the atmosphere Carbon-14 is produced in the upper troposphere and the stratosphere by thermal neutrons absorbed by nitrogen atoms. When cosmic rays enter the atmosphere, they undergo various transformations, including the production of neutrons. The resulting neutrons (n) participate in the following n-p reaction (p is proton): 147N + n → 146C + pThe highest rate of carbon-14 production takes place at altitudes of 9 to 15 kilometres (30,000 to 49,000 ft) and at high geomagnetic latitudes.
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Carbon-14
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Origin
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The rate of 14C production can be modelled, yielding values of 16,400 or 18,800 atoms of 14C per second per square meter of the Earth's surface, which agrees with the global carbon budget that can be used to backtrack, but attempts to measure the production time directly in situ were not very successful. Production rates vary because of changes to the cosmic ray flux caused by the heliospheric modulation (solar wind and solar magnetic field), and, of great significance, due to variations in the Earth's magnetic field. Changes in the carbon cycle however can make such effects difficult to isolate and quantify.
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Carbon-14
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Origin
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Occasional spikes may occur; for example, there is evidence for an unusually high production rate in AD 774–775, caused by an extreme solar energetic particle event, the strongest such event to have occurred within the last ten millennia. Another "extraordinarily large" 14C increase (2%) has been associated with a 5480 BC event, which is unlikely to be a solar energetic particle event.Carbon-14 may also be produced by lightning but in amounts negligible, globally, compared to cosmic ray production. Local effects of cloud-ground discharge through sample residues are unclear, but possibly significant.
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Carbon-14
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Origin
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Other carbon-14 sources Carbon-14 can also be produced by other neutron reactions, including in particular 13C(n,γ)14C and 17O(n,α)14C with thermal neutrons, and 15N(n,d)14C and 16O(n,3He)14C with fast neutrons. The most notable routes for 14C production by thermal neutron irradiation of targets (e.g., in a nuclear reactor) are summarized in the table.
Carbon-14 may also be radiogenic (cluster decay of 223Ra, 224Ra, 226Ra). However, this origin is extremely rare.
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Carbon-14
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Origin
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Formation during nuclear tests The above-ground nuclear tests that occurred in several countries between 1955 and 1980 (see nuclear test list) dramatically increased the amount of carbon-14 in the atmosphere and subsequently in the biosphere; after the tests ended, the atmospheric concentration of the isotope began to decrease, as radioactive CO2 was fixed into plant and animal tissue, and dissolved in the oceans.
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Carbon-14
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Origin
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One side-effect of the change in atmospheric carbon-14 is that this has enabled some options (e.g., bomb-pulse dating) for determining the birth year of an individual, in particular, the amount of carbon-14 in tooth enamel, or the carbon-14 concentration in the lens of the eye.In 2019, Scientific American reported that carbon-14 from nuclear bomb testing has been found in the bodies of aquatic animals found in one of the most inaccessible regions of the earth, the Mariana Trench in the Pacific Ocean.
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Carbon-14
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Origin
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Emissions from nuclear power plants Carbon-14 is produced in coolant at boiling water reactors (BWRs) and pressurized water reactors (PWRs). It is typically released to the atmosphere in the form of carbon dioxide at BWRs, and methane at PWRs. Best practice for nuclear power plant operator management of carbon-14 includes releasing it at night, when plants are not photosynthesizing. Carbon-14 is also generated inside nuclear fuels (some due to transmutation of oxygen in the uranium oxide, but most significantly from transmutation of nitrogen-14 impurities), and if the spent fuel is sent to nuclear reprocessing then the carbon-14 is released, for example as CO2 during PUREX.
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Carbon-14
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Occurrence
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Dispersion in the environment After production in the upper atmosphere, the carbon-14 atoms react rapidly to form mostly (about 93%) 14CO (carbon monoxide), which subsequently oxidizes at a slower rate to form 14CO2, radioactive carbon dioxide. The gas mixes rapidly and becomes evenly distributed throughout the atmosphere (the mixing timescale in the order of weeks). Carbon dioxide also dissolves in water and thus permeates the oceans, but at a slower rate. The atmospheric half-life for removal of 14CO2 has been estimated to be roughly 12 to 16 years in the northern hemisphere. The transfer between the ocean shallow layer and the large reservoir of bicarbonates in the ocean depths occurs at a limited rate.
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Carbon-14
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Occurrence
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In 2009 the activity of 14C was 238 Bq per kg carbon of fresh terrestrial biomatter, close to the values before atmospheric nuclear testing (226 Bq/kg C; 1950).
Total inventory The inventory of carbon-14 in Earth's biosphere is about 300 megacuries (11 EBq), of which most is in the oceans.
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Carbon-14
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Occurrence
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The following inventory of carbon-14 has been given: Global inventory: ~8500 PBq (about 50 t) Atmosphere: 140 PBq (840 kg) Terrestrial materials: the balance From nuclear testing (until 1990): 220 PBq (1.3 t) In fossil fuels Many human-made chemicals are derived from fossil fuels (such as petroleum or coal) in which 14C is greatly depleted because the age of fossils far exceeds the half-life of 14C. The relative absence of 14CO2 is therefore used to determine the relative contribution (or mixing ratio) of fossil fuel oxidation to the total carbon dioxide in a given region of the Earth's atmosphere.Dating a specific sample of fossilized carbonaceous material is more complicated. Such deposits often contain trace amounts of carbon-14. These amounts can vary significantly between samples, ranging up to 1% of the ratio found in living organisms, a concentration comparable to an apparent age of 40,000 years. This may indicate possible contamination by small amounts of bacteria, underground sources of radiation causing the 14N(n,p)14C reaction, direct uranium decay (although reported measured ratios of 14C/U in uranium-bearing ores would imply roughly 1 uranium atom for every two carbon atoms in order to cause the 14C/12C ratio, measured to be on the order of 10−15), or other unknown secondary sources of carbon-14 production. The presence of carbon-14 in the isotopic signature of a sample of carbonaceous material possibly indicates its contamination by biogenic sources or the decay of radioactive material in surrounding geologic strata. In connection with building the Borexino solar neutrino observatory, petroleum feedstock (for synthesizing the primary scintillant) was obtained with low 14C content. In the Borexino Counting Test Facility, a 14C/12C ratio of 1.94×10−18 was determined; probable reactions responsible for varied levels of 14C in different petroleum reservoirs, and the lower 14C levels in methane, have been discussed by Bonvicini et al.
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Carbon-14
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Occurrence
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In the human body Since many sources of human food are ultimately derived from terrestrial plants, the relative concentration of carbon-14 in human bodies is nearly identical to the relative concentration in the atmosphere. The rates of disintegration of potassium-40 and carbon-14 in the normal adult body are comparable (a few thousand disintegrated nuclei per second). The beta decays from external (environmental) radiocarbon contribute approximately 0.01 mSv/year (1 mrem/year) to each person's dose of ionizing radiation. This is small compared to the doses from potassium-40 (0.39 mSv/year) and radon (variable).
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Carbon-14
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Occurrence
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Carbon-14 can be used as a radioactive tracer in medicine. In the initial variant of the urea breath test, a diagnostic test for Helicobacter pylori, urea labeled with approximately 37 kBq (1.0 μCi) carbon-14 is fed to a patient (i.e., 37,000 decays per second). In the event of a H. pylori infection, the bacterial urease enzyme breaks down the urea into ammonia and radioactively-labeled carbon dioxide, which can be detected by low-level counting of the patient's breath.
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Calendar spread
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Calendar spread
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In finance, a calendar spread (also called a time spread or horizontal spread) is a spread trade involving the simultaneous purchase of futures or options expiring on a particular date and the sale of the same instrument expiring on another date. These individual purchases, known as the legs of the spread, vary only in expiration date; they are based on the same underlying market and strike price.
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Calendar spread
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Calendar spread
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The usual case involves the purchase of futures or options expiring in a more distant month--the far leg--and the sale of futures or options in a more nearby month--the near leg.
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Calendar spread
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Uses
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The calendar spread can be used to attempt to take advantage of a difference in the implied volatilities between two different months' options. The trader will ordinarily implement this strategy when the options they are buying have a distinctly lower implied volatility than the options they are writing (selling).
In the typical version of this strategy, a rise in the overall implied volatility of a market's options during the trade will tend very strongly to be to the trader's advantage, and a decline in implied volatility will tend strongly to work to the trader's disadvantage.
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Calendar spread
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Uses
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If the trader instead buys a nearby month's options in some underlying market and sells that same underlying market's further-out options of the same striking price, this is known as a reverse calendar spread. This strategy will tend strongly to benefit from a decline in the overall implied volatility of that market's options over time. The calendar spread is mostly neutral with regard to the price of the underlying. The short calendar spread has net negative theta.
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Calendar spread
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Futures pricing
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Futures calendar spreads or switches represent simultaneous purchase and sales in different delivery months, and are quoted as the difference in prices. If gold for August delivery is bid $1601.20 asking $1601.30, and gold for October delivery is bid $1603.20 asking $1603.30, then the calendar spread would be bid -$2.10 asking -$1.90 for August–October.
Calendar spreads or switches are most often used in the futures markets to 'roll over' a position for delivery from one month into another month.
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Calendar spread
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Trading strategies
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Pick expiration months as for a covered call When trading a calendar spread, try to think of this strategy as a covered call. The only difference is that you do not own the underlying stock, but you do own the right to purchase it. By treating this trade like a covered call, it will help you pick expiration months quickly. When selecting the expiration date of the long option, it is wise to go at least two to three months out. This will depend largely on your forecast. However, when selecting the short strike, it is a good practice to always sell the shortest dated option available. These options lose value the fastest, and can be rolled out month-to-month over the life of the trade.
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Calendar spread
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Trading strategies
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Leg into a calendar spread For traders who own calls or puts against a stock, they can sell an option against this position and "leg" into a calendar spread at any point. For example, if you own calls on a particular stock and it has made a significant move to the upside but has recently leveled out, you can sell a call against this stock if you are neutral over the short term. Traders can use this legging-in strategy to ride out the dips in an upward trending stock.
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Calendar spread
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Trading strategies
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Manage risk Plan your position size around the max loss of the trade and try to cut losses short when you have determined that the trade no longer falls within the scope of your forecast.
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Calendar spread
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What to avoid
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Limited upside in the early stages This trade has limited upside when both legs are in play. However, once the short option expires, the remaining long position has unlimited profit potential. In the early stages of this trade, it is a neutral trading strategy. If the stock starts to move more than anticipated, this is what can result in limited gains.
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Calendar spread
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What to avoid
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Be aware of expiration dates As the expiration date for the short option approaches, action needs to be taken. If the short option expires out of the money, then the contract expires worthless. If the option is in the money, then the trader should consider buying back the option at the market price. After the trader has taken action with the short option, he or she can then decide whether to roll the long option position.
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Calendar spread
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What to avoid
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Time your entry well The last risk to avoid when trading calendar spreads is an untimely entry. In general, market timing is much less critical when trading spreads, but a trade that is very ill-timed can result in a max loss very quickly. Therefore, it is important to survey the condition of the overall market and to make sure you are trading within the direction of the underlying trend of the stock.
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Calendar spread
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Conclusion
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In summary, it is important to remember that a long calendar spread is a neutral – and in some instances a directional – trading strategy that is used when a trader expects a gradual or sideways movement in the short term and has more direction bias over the life of the longer-dated option. This trade is constructed by selling a short-dated option and buying a longer-dated option, resulting in a net debit. This spread can be created with either calls or puts, and therefore can be a bullish or bearish strategy. The trader wants to see the short-dated option decay at a faster rate than the longer-dated option.
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Calendar spread
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Conclusion
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When trading this strategy here are a few key points: Can be traded as either a bullish or bearish strategy Generates profit as time decays Risk is limited to the net debit Benefits from an increase in volatility If assigned, the trader loses the time value left in the position Provides additional leverage in order to make excess returns Losses are limited if the stock price moves dramatically
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Radar altimeter
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Radar altimeter
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A radar altimeter (RA), also called a radio altimeter (RALT), electronic altimeter, reflection altimeter, or low-range radio altimeter (LRRA), measures altitude above the terrain presently beneath an aircraft or spacecraft by timing how long it takes a beam of radio waves to travel to ground, reflect, and return to the craft. This type of altimeter provides the distance between the antenna and the ground directly below it, in contrast to a barometric altimeter which provides the distance above a defined vertical datum, usually mean sea level.
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Radar altimeter
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Principle
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As the name implies, radar (radio detection and ranging) is the underpinning principle of the system. The system transmits radio waves down to the ground and measures the time it takes them to be reflected back up to the aircraft. The altitude above the ground is calculated from the radio waves' travel time and the speed of light. Radar altimeters required a simple system for measuring the time-of-flight that could be displayed using conventional instruments, as opposed to a cathode ray tube normally used on early radar systems.
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Radar altimeter
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Principle
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To do this, the transmitter sends a frequency modulated signal that changes in frequency over time, ramping up and down between two frequency limits, Fmin and Fmax over a given time, T. In the first units, this was accomplished using an LC tank with a tuning capacitor driven by a small electric motor. The output is then mixed with the radio frequency carrier signal and sent out the transmission antenna.Since the signal takes some time to reach the ground and return, the frequency of the received signal is slightly delayed relative to the signal being sent out at that instant. The difference in these two frequencies can be extracted in a frequency mixer, and because the difference in the two signals is due to the delay reaching the ground and back, the resulting output frequency encodes the altitude. The output is typically on the order of hundreds of cycles per second, not megacycles, and can easily be displayed on analog instruments. This technique is known as Frequency Modulated Continuous-wave radar.
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Radar altimeter
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Principle
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Radar altimeters normally work in the E band, Ka band, or, for more advanced sea-level measurement, S band. Radar altimeters also provide a reliable and accurate method of measuring height above water, when flying long sea-tracks. These are critical for use when operating to and from oil rigs.The altitude specified by the device is not the indicated altitude of the standard barometric altimeter. A radar altimeter measures absolute altitude - the height Above Ground Level (AGL). Absolute altitude is sometimes referred to as height because it is the height above the underlying terrain.
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Radar altimeter
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Principle
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As of 2010, all commercial radar altimeters use linear frequency modulation - continuous wave (LFM-CW or FM-CW).
As of 2010, about 25,000 aircraft in the US have at least one radio altimeter.
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Radar altimeter
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History
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Original concept The underlying concept of the radar altimeter was developed independent of the wider radar field, and originates in a study of long-distance telephony at Bell Labs. During the 1910s, Bell Telephone was struggling with the reflection of signals caused by changes in impedance in telephone lines, typically where equipment connected to the wires. This was especially significant at repeater stations, where poorly matched impedances would reflect large amounts of the signal and made long-distance telephony difficult.Engineers noticed that the reflections appeared to have a "humpy" pattern to them; for any given signal frequency, the problem would only be significant if the devices were located at specific points in the line. This led to the idea of sending a test signal into the line and then changing its frequency until significant echos were seen. This would reveal the approximate distance to the device, allowing it to be identified and fixed.Lloyd Espenschied was working at Bell Labs when he conceived using this same phenomenon to measure distances in a wire. One of his first developments in this field was a 1919 patent (granted 1924) on the idea of sending a signal into railway tracks and measuring the distance to discontinuities. These could be used to detect broken tracks, or if the distance was changing more rapidly than the speed of the train, other trains on the same line.
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Radar altimeter
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History
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Appleton's ionosphere measurements During this same period there was a great debate in physics over the nature of radio propagation. Guglielmo Marconi's successful trans-Atlantic transmissions appeared to be impossible. Studies of radio signals demonstrated they travelled in straight lines, at least over long distances, so the broadcast from Cornwall should have disappeared into space instead of being received in Newfoundland. In 1902, Oliver Heaviside in the UK and Arthur Kennelly in the USA independently postulated the existence of an ionized layer in the upper atmosphere that was bouncing the signal back to the ground so it could be received. This became known as the Heaviside layer.While an attractive idea, direct evidence was lacking. In 1924, Edward Appleton and Miles Barnett were able to demonstrate the existence of such a layer in a series of experiments carried out in partnership with the BBC. After scheduled transmissions had ended for the day, a BBC transmitter in Bournemouth sent out a signal that slowly increased in frequency. This was picked up by Appleton's receiver in Oxford, where two signals appeared. One was the direct signal from the station, the groundwave, while the other was received later in time after it travelled to the Heaviside layer and back again, the skywave.The trick was how to accurately measure the distance travelled by the skywave to demonstrate it was actually in the sky. This was the purpose of the changing frequency. Since the ground signal travelled a shorter distance, it was more recent and thus closer to the frequency being sent at that instant. The skywave, having to travel a longer distance, was delayed, and was thus the frequency as it was some time ago. By mixing the two in a frequency mixer, a third signal is produced that has its own unique frequency that encodes the difference in the two inputs. Since in this case the difference is due to the longer path, the resulting frequency directly reveals the path length. Although technically more challenging, this was ultimately the same basic technique being used by Bell to measure the distance to the reflectors in the wire.
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Radar altimeter
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History
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Everitt and Newhouse In 1929, William Littell Everitt, a professor at Ohio State University, began considering the use of Appleton's basic technique as the basis for an altimeter system. He assigned the work to two seniors, Russell Conwell Newhouse and M. W. Havel. Their experimental system was more in common with the earlier work at Bell, using changes in frequency to measure the distance to the end of wires. The two used it as the basis for a joint senior thesis in 1929.Everitt disclosed the concept to the US Patent Office, but did not file a patent at that time. He then approached the Daniel Guggenheim Fund for the Promotion of Aeronautics for development funding. Jimmy Doolittle, secretary of the Foundation, approached Vannevar Bush of Bell Labs to pass judgment. Bush was skeptical that the system could be developed at that time, but nevertheless suggested the Foundation fund development of a working model. This allowed Newhouse to build an experimental machine which formed the basis of his 1930 Master's thesis, in partnership with J. D. Corley.The device was taken to Wright Field where it was tested by Albert Francis Helgenberger, a noted expert in aircraft navigation. Hegenberger found that the system worked as advertised, but stated that it would have to work at higher frequencies to be practical.
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Radar altimeter
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History
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Espenschied and Newhouse Espenschied had also been considering the use of Appleton's idea for altitude measurement. In 1926 he suggested the idea both as a way to measure altitude as well as a forward-looking system for terrain avoidance and collision detection. However, at that time the frequency of available radio systems even in what was known as shortwave was calculated to be fifty times lower than what would be needed for a practical system.Espenschied eventually filed a patent on the idea in 1930. By this time, Newhouse had left Ohio State and taken a position at Bell Labs. Here he met Peter Sandretto, who was also interested in radio navigation topics. Sandretto left Bell in 1932 to become the Superintendent of Communications at United Air Lines (UAL), where he led the development of commercial radio systems.Espenschied's patent was not granted until 1936, and its publication generated intense interest. Around the same time, Bell Labs had been working on new tube designs that were capable of delivering between 5 and 10 Watts at up to 500 MHz, perfect for the role. This led Sandretto to contact Bell about the idea, and in 1937 a partnership between Bell Labs and UAL was formed to build a practical version. Led by Newhouse, a team had a working model in testing in early 1938, and Western Electric (Bell's manufacturing division) was already gearing up for a production model. Newhouse also filed several patents on improvements in technique based on this work.
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Radar altimeter
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History
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Commercial introduction The system was publicly announced on 8 and 9 October 1938. During World War II, mass production was taken up by RCA, who produced them under the names ABY-1 and RC-24. In the post-war era, many companies took up production and it became a standard instrument on many aircraft as blind landing became commonplace.A paper describing the system was published jointly by Espenschied and Newhouse the next year. The paper explores sources of error and concludes that the worst-case built-in scenario was on the order of 9%, but this might be as high as 10% when flying over rough terrain like the built-up areas of cities.During early flights of the system, it was noticed that the pattern of the returns as seen on an oscilloscope was distinct for different types of terrain below the aircraft. This opened the possibility of all sorts of other uses for the same technology, including ground-scanning and navigation. However, these concepts were not able to be explored by Bell at the time.
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Radar altimeter
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History
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Use as general purpose radar It had been known since the late 1800s that metal and water made excellent reflectors of radio signals, and there had been a number of attempts to build ship, train and iceberg detectors over the years since that time. Most of these had significant practical limitations, especially the use of low-frequency signals that demanded large antennas in order to provide reasonable performance. The Bell unit, operating at a base frequency of 450 MHz, was among the highest frequency systems of its era.In Canada, the National Research Council began working on an airborne radar system using the altimeter as its basis. This came as a great surprise to British researchers when they visited in October 1940 as part of the Tizard Mission, as the British believed at that time that they were the only ones working on the concept. However, the Canadian design was ultimately abandoned in favour of building the fully developed British ASV Mark II design, which operated at much higher power levels.In France, researchers at IT&T's French division were carrying out similar experiments when the German invasion approached the labs in Paris. The labs were deliberately destroyed to prevent the research falling into German hands, but German teams found the antennas in the rubble and demanded an explanation. The IT&T director of research deflected suspicion by showing them the unit on the cover of a magazine and admonishing them for not being up-to-date on the latest navigation techniques.
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Radar altimeter
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Applications
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In civil aviation Radar altimeters are frequently used by commercial aircraft for approach and landing, especially in low-visibility conditions (see instrument flight rules) and automatic landings, allowing the autopilot to know when to begin the flare maneuver. Radar altimeters give data to the autothrottle which is a part of the Flight Computer.
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Radar altimeter
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Applications
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Radar altimeters generally only give readings up to 2,500 feet (760 m) above ground level (AGL). Frequently, the weather radar can be directed downwards to give a reading from a longer range, up to 60,000 feet (18,000 m) above ground level (AGL). As of 2012, all airliners are equipped with at least two and possibly more radar altimeters, as they are essential to autoland capabilities. (As of 2012, determining height through other methods such as GPS is not permitted by regulations.) Older airliners from the 1960s (such as the British Aircraft Corporation BAC 1-11) and smaller airliners in the sub-50 seat class (such as the ATR 42 and BAe Jetstream series) are equipped with them.
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Radar altimeter
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Applications
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Radar altimeters are an essential part in ground proximity warning systems (GPWS), warning the pilot if the aircraft is flying too low or descending too quickly. However, radar altimeters cannot see terrain directly ahead of the aircraft, only that below it; such functionality requires either knowledge of position and the terrain at that position or a forward looking terrain radar. Radar altimeter antennas have a fairly large main lobe of about 80° so that at bank angles up to about 40°, the radar detects the range from the aircraft to the ground (specifically to the nearest large reflecting object). This is because range is calculated based on the first signal return from each sampling period. It does not detect slant range until beyond about 40° of bank or pitch. This is not an issue for landing as pitch and roll do not normally exceed 20°.
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Radar altimeter
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Applications
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Radio altimeters used in civil aviation operate in the IEEE C-band between 4.2 and 4.4 GHz.In early 2022, potential interference from 5G cell phone towers caused some flight delays and a few flight cancellations in the United States.
In military aviation Radar altimeters are also used in military aircraft to fly quite low over the land and the sea to avoid radar detection and targeting by anti-aircraft guns or surface-to-air missiles. A related use of radar altimeter technology is terrain-following radar, which allows fighter bombers to fly at very low altitudes.
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Radar altimeter
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Applications
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The F-111s of the Royal Australian Air Force and the U.S. Air Force have a forward-looking, terrain-following radar (TFR) system connected via digital computer to their automatic pilots. Beneath the nose radome are two separate TFR antennae, each providing individual information to the dual-channel TFR system. In case of a failure in that system, the F-111 has a back-up radar altimeter system, also connected to the automatic pilot. Then, if the F-111 ever dips below the preset minimum altitude (for example, 15 meters) for any reason, its automatic pilot is commanded to put the F-111 into a 2G fly-up (a steep nose-up climb) to avoid crashing into terrain or water. Even in combat, the hazard of a collision is far greater than the danger of being detected by an enemy. Similar systems are used by F/A-18 Super Hornet aircraft operated by Australia and the United States.
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Radar altimeter
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International regulation
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The International Telecommunication Union (ITU) defines radio altimeters as “radionavigation equipment, on board an aircraft or spacecraft, used to determine the height of the aircraft or the spacecraft above the Earth's surface or another surface" in article 1.108 of the ITU Radio Regulations (RR). Radionavigation equipment shall be classified by the radiocommunication service in which it operates permanently or temporarily. The use of radio altimeter equipment is categorised as a safety-of-life service, must be protected for interferences, and is an essential part of navigation.
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Accordion (GUI)
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Accordion (GUI)
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The accordion is a graphical control element comprising a vertically stacked list of items, such as labels or thumbnails. Each item can be "expanded" or "collapsed" to reveal the content associated with that item. There can be zero expanded items, exactly one, or more than one item expanded at a time, depending on the configuration.
The term stems from the musical accordion in which sections of the bellows can be expanded by pulling outward.
A common example of an accordion is the Show/Hide operation of a box region, but extended to have multiple sections in a list.
An accordion is similar in purpose to a tabbed interface, a list of items where exactly one item is expanded into a panel (i.e. list items are shortcuts to access separate panels).
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Accordion (GUI)
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User definition
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Several windows are stacked on each other. All of them are "shaded", so only their captions are visible. If one of them is clicked, to make it active, it is "unshaded" or "maximized". Other windows in accordion are displaced around top or bottom edge.
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Accordion (GUI)
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Examples
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A common example using a GUI accordion is the Show/Hide operation of a box region, but extended to have multiple sections in a list.
SlideVerse is an accordion interface providing access to web content.The list view of Google Reader also features this.
In an early example, Apple's download page used roll-over accordions in 2008. In this example, captured in the Wayback Machine in the Internet Archive, the left column of the page includes three categories that expand on roll-over: "All Downloads", "Top Apple Downloads", and "Top Downloads".
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Appendix H
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Appendix H
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Appendix H is the name of an infamous appendix in Pentium Processor Family Developer's Manual, Volume 3. This appendix contained reference to documentation only available under a legally binding NDA.
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Appendix H
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Appendix H
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This NDAed documentation described various new features introduced in the Pentium processor, notably Virtual Mode Extensions (VME) and 4 MB paging. VME added an additional feature to the existing virtual 8086 mode (which was introduced with the 80386 processor), and included optimized handling and delivery of interrupts to and from virtual machines by reducing the number of traps required. VME should not be confused with the later Intel VT virtualization technology aiming at full virtualization of the CPU, rather than just the 8086 mode.
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Appendix H
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Appendix H
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The appendix was referenced by the official chapters in the documentation, provoking irritation among the public who was not allowed to access the detailed descriptions. This started a movement with observers trying to reverse-engineer the information in various ways. Notably, Robert Collins (writing in Dr. Dobb's Journal) and Christian Ludloff (owner of the sandpile.org website) played a major role in this. From the Pentium Pro, the information in Appendix H was moved to the main documentation chapters, making the features publicly documented.
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ICD-11
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ICD-11
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The ICD-11 is the eleventh revision of the International Classification of Diseases (ICD). It replaces the ICD-10 as the global standard for recording health information and causes of death. The ICD is developed and annually updated by the World Health Organization (WHO). Development of the ICD-11 started in 2007 and spanned over a decade of work, involving over 300 specialists from 55 countries divided into 30 work groups, with an additional 10,000 proposals from people all over the world. Following an alpha version in May 2011 and a beta draft in May 2012, a stable version of the ICD-11 was released on 18 June 2018, and officially endorsed by all WHO members during the 72nd World Health Assembly on 25 May 2019.The ICD-11 is a large taxonomy consisting of about 85,000 entities, also called classes or nodes. An entity can be anything that is relevant to health care. It usually represents a disease or a pathogen, but it can also be an isolated symptom or (developmental) anomaly of the body. There are also classes for reasons for contact with health services, social circumstances of the patient, and external causes of injury or death. The ICD-11 is part of the WHO-FIC, a family of medical classifications. The WHO-FIC contains the Foundation Component, which comprises all entities of all classifications endorsed by the WHO. The Foundation is the common core from which all classifications are derived. For example, the ICD-O is a derivative classification optimized for use in oncology. The primary derivative of the Foundation is called the ICD-11 MMS, and it is this system that is commonly referred to as simply "the ICD-11". MMS stands for Mortality and Morbidity Statistics. The ICD-11 is distributed under a Creative Commons BY-ND license.The ICD-11 officially came into effect on 1 January 2022. On 11 February, the WHO claimed that 35 countries were using the ICD-11. In the United States, an expected implementation year of 2025 has been given, but if a clinical modification is determined to be needed (similar to the ICD-10-CM), ICD-11 implementation might not begin until 2027.The ICD-11 MMS can be viewed online on the WHO's website. Aside from this, the site offers two maintenance platforms: the ICD-11 Maintenance Platform, and the WHO-FIC Foundation Maintenance Platform. Users can submit evidence-based suggestions for the improvement of the WHO-FIC, i.e. the ICD-11, the ICF, and the ICHI.
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ICD-11
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Structure
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WHO-FIC The WHO Family of International Classifications (WHO-FIC), also called the WHO Family, is a suit of classifications used to describe various aspects of the health care system in a consistent manner, with a standardised terminology. The abbreviation is variously written with or without a hyphen ("WHO-FIC" or "WHOFIC"). The WHO-FIC consists of four components: the WHO-FIC Foundation, the Reference Classifications, the Derived Classifications, and the Related Classifications. The WHO-FIC Foundation, also called the Foundation Component, represents the entire WHO-FIC universe. It is a collection of over hundred thousand entities, also called classes or nodes. Entities are anything relevant to health care. They are used to describe diseases, disorders, body parts, bodily functions, reasons for visit, medical procedures, microbes, causes of death, social circumstances of the patient, and much more.The Foundation Component is a multidimensional collection of entities. An entity can have multiple parents and child nodes. For example, pneumonia can be categorized as a lung infection, but also as a bacterial or viral infection (i.e. by site or by etiology). Thus, the node Pneumonia (entity id: 142052508) has two parents: Lung infections (entity id: 915779102) and Certain infectious or parasitic diseases (entity id: 1435254666). The Pneumonia node in turn has various children, including Bacterial pneumonia (entity id: 1323682030) and Viral pneumonia (entity id: 1024154490).
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ICD-11
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Structure
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The Foundation Component is the common core on which all Reference and Derived Classifications are based. The WHO-FIC contains three Reference Classifications: the ICD-11 MMS (see below), the ICF, and the ICHI. Derived Classifications are based on the three Reference Classifications, and are usually tailored for a particular specialty. For example, the ICD-O is a Derived Classification used in oncology. Each node of the Foundation has a unique entity id, which remains the same in all Reference and Derived Classifications, guaranteeing consistency. Related Classifications are complementary, and cover specialty areas not covered elsewhere in the WHO-FIC. For example, the International Classification of Nursing Practice (ICNP), draws on terms from the Foundation Component, but also uses terms specific for nursing not found in the Foundation.A classification can be represented as a tabular list, which is a "flat" hierarchical tree of categories. In this tree, all entities can only have a single parent, and therefore must be mutually exclusive of each other. Such a classification is also called a linearization.
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ICD-11
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Structure
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ICD-11 MMS The ICD-11 MMS is the main Reference Classification of the WHO-FIC, and the primary linearization of the Foundation Component. The ICD-11 MMS is commonly referred to as simply "the ICD-11". The "MMS" was added to differentiate the ICD-11 entities in the Foundation from those in the Classification. The ICD-11 MMS does not contain all classes from the Foundation ICD-11, and also adds some classes from the ICF. MMS stands for Mortality and Morbidity Statistics. The abbreviation is variously written with or without a hyphen between 11 and MMS ("ICD-11 MMS" or "ICD-11-MMS").
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ICD-11
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Structure
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The ICD-11 MMS consists of approximately 85,000 entities. Entities can be chapters, blocks or categories. A chapter is a top level entity of the hierarchy; the MMS contains 28 of them (see Chapters section below). A block is used to group related categories or blocks together. A category can be anything that is relevant to health care. Every category has a unique, alphanumeric code called an ICD-11 code, or just ICD code. Chapters and blocks never have ICD-11 codes, and therefore cannot be diagnosed. An ICD-11 code is not the same as an entity id.
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ICD-11
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Structure
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The ICD-11 MMS takes the form of a "flat" hierarchical tree. As aforementioned, the entities in this linearization can only have a single parent, and therefore must be mutually exclusive of each other. To make up for this limitation, the hierarchy of the MMS contains gray nodes. These nodes appear as children in the hierarchy, but actually have a different parent node. They originally belong to a different block or chapter, but are also listed elsewhere because of overlap. For example, Pneumonia (CA40) has two parents in the Foundation: "Lung infections" (site) and "Certain infectious or parasitic diseases" (etiology). In the MMS, Pneumonia is categorized in the "Lung infections", with a gray node in "Certain infectious or parasitic diseases". The same goes for injuries, poisonings, neoplasms, and developmental anomalies, which can occur in almost any part of the body. They each have their own chapters, but their categories also have gray nodes in the chapters of the organs they affect. For instance, the blood cancers, including all forms of leukemia, are in the "Neoplasms" chapter, but they are also displayed as gray nodes in the chapter "Diseases of the blood or blood-forming organs".
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ICD-11
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Structure
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The ICD-11 MMS also contains residual categories, or residual nodes. These are the "Other specified" and "Unspecified" categories, miscellaneous classes which can be used to code conditions that do not fit with any of the more specific MMS entities. In the ICD-11 Browser, residual nodes are displayed in a maroon color. Residual categories are not in the Foundation, and therefore are the only classes with derivative entity IDs: their IDs are the same as their parent nodes, with "/mms/otherspecified" or "/mms/unspecified" tagged at the end. Their ICD codes always end with Y for "Other specified" categories, or Z for "Unspecified" categories (e.g. 1C4Y and 1C4Z).
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ICD-11
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Structure
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Health informatics The ICD-11, both the ICD-11 Foundation and the MMS, can be accessed using a multilingual REST API. Documentation on the ICD API and some additional tools for integration into third-party applications can be found at the ICD API home page.The WHO has released a map that can be used to link and convert ICD-10 terms to those of the ICD-11. It can be downloaded from the ICD-11 MMS browser. In 2017, SNOMED International announced plans to release a SNOMED CT to ICD-11 MMS map.The ICD-11 Foundation, and consequently the MMS, are updated annually, similarly to the ICD-10. As of February 2023, six versions of the Foundation and MMS have been released.
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ICD-11
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Chapters
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Below is a list of all chapters of the ICD-11 MMS, the primary linearization of the Foundation Component.
Unlike the ICD-10 codes, the ICD-11 MMS codes never contain the letters I or O, to prevent confusion with the numbers 1 and 0.
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ICD-11
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Changes
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Below is a summary of notable changes in the ICD-11 MMS compared to the ICD-10.
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ICD-11
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Changes
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General The ICD-11 MMS features a more flexible coding structure. In the ICD-10, every code starts with a letter, indicating the chapter. This is followed by a two digit number (e.g. P35), creating 99 slots per chapter, excluding subcategories and blocks. This proved enough for most chapters, but four are so voluminous that they span two letters: chapter 1 (A00–B99), chapter 2 (C00.0–D48.9), chapter 19 (S00–T98), and chapter 20 (V01–Y98). In the ICD-11 MMS, there is a single first character for every chapter. The codes of the first nine chapters begin with the numbers 1 to 9, while the next nineteen chapters start with the letters A to X. The letters I and O are not used, to prevent confusion with the numbers 1 and 0. The chapter character is then followed by a letter, a number, and a fourth character that starts as a number (0–9, e.g. KA80) and may then continue as a letter (A–Z, e.g. KA8A). The WHO opted for a forced number as the third character to prevent the spelling of "undesirable words". In the ICD-10, each entity within a chapter either has a code (e.g. P35) or a code range (e.g. P35–P39). The latter is a block. In the ICD-11 MMS, blocks never have codes, and not every entity necessarily has a code, although each entity does have a unique id.In the ICD-10, the next level of the hierarchy is indicated in the code by a dot and a single number (e.g. P35.2). This is the lowest available level in the ICD-10 hierarchy, causing an artificial limitation of 10 subcategories per code (.0 to .9). In the ICD-11 MMS, this limitation no longer exists: after 0–9, the list may continue with A–Z (e.g. KA62.0 – KA62.A). Then, following the first character after the dot, a second character may be used in the next level of the hierarchy (e.g. KA40.00 – KA40.08). This level is currently the lowest appearing in the MMS. The large amount of unused coding space in the MMS allows for updates to be made without having to change the other categories, ensuring that codes remain stable.The ICD-11 features five new chapters. The third chapter of the ICD-10, "Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism", has been split in two: "Diseases of the blood or blood-forming organs" (chapter 3) and "Diseases of the immune system" (chapter 4). The other new chapters are "Sleep-wake disorders" (chapter 7), "Conditions related to sexual health" (chapter 17, see section), and "Supplementary Chapter Traditional Medicine Conditions - Module I" (chapter 26, see section).
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ICD-11
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Changes
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Mental disorders Overview The following mental disorders have been newly added to the ICD-11, but were already included in the American ICD-10-CM adaption: Binge eating disorder (ICD-11: 6B82; ICD-10-CM: F50.81), Bipolar type II disorder (ICD-11: 6A61; ICD-10-CM: F31.81), Body dysmorphic disorder (ICD-11: 6B21; ICD-10-CM: F45.22), Excoriation disorder (ICD-11: 6B25.1; ICD-10-CM: F42.4), Frotteuristic disorder (ICD-11: 6D34; ICD-10-CM: F65.81), Hoarding disorder (ICD-11: 6B24; ICD-10-CM: F42.3), and Intermittent explosive disorder (ICD-11: 6C73; ICD-10-CM: F63.81).The following mental disorders have been newly added to the ICD-11, and are not in the ICD-10-CM: Avoidant/restrictive food intake disorder (6B83), Body integrity dysphoria (6C21), Catatonia (486722075), Complex post-traumatic stress disorder (6B41), Gaming disorder (6C51), Olfactory reference disorder (6B22), and Prolonged grief disorder (6B42).Other notable changes include: Distinct personality disorders have been collapsed into a single Personality disorder diagnosis, using a dimensional (as opposed to categorical) model; see Personality disorders section.
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ICD-11
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Changes
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All subtypes of Schizophrenia (e.g. paranoid, hebephrenic, catatonic) have been removed. Instead, a dimensional model is used with the category Symptomatic manifestations of primary psychotic disorders (6A25), which allows the coding for Positive symptoms (6A25.0), Negative symptoms (6A25.1), Depressive symptoms (6A25.2), Manic symptoms (6A25.3), Psychomotor symptoms (6A25.4), and Cognitive symptoms (6A25.5).
Persistent mood disorders (F34), which consists of Cyclothymia (F34.0) and Dysthymia (F34.1), have been deleted.
The ICD-10 differentiates between Phobic anxiety disorders (F40), such as Agoraphobia (F40.0), and Other anxiety disorders (F41), such as Generalized anxiety disorder (F41.1). The ICD-11 merges both groups together as Anxiety or fear-related disorders (1336943699).
All Pervasive developmental disorders (F84) are merged into one category, Autism spectrum disorder (6A02), except for Rett syndrome, which is moved to the developmental anomalies chapter (LD90.4).
Hyperkinetic disorders (F90) is renamed Attention deficit hyperactivity disorder (6A05), and a distinction in subtypes is made between predominantly inattentive (6A05.0), predominantly hyperactive-impulsive (6A05.1), and combined (6A05.2). Hyperkinetic conduct disorder (F90.1) has been removed.
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ICD-11
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Changes
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Acute stress reaction (F43.0) has been moved out of the mental disorder chapter, and placed in the chapter "Factors influencing health status or contact with health services" (QE84). Thus, in the ICD-11, Acute stress reaction is no longer considered a mental disorder.Aside from the updates made for the ICD-11, the WHO has developed an ICD-11 subset of the Clinical descriptions and diagnostic guidelines (CDDG), although it has not yet been published. A book of the same name was released in 1992 for the ICD-10, which was also known as the "Blue Book". It contains expanded definitions and diagnostic criteria for the mental disorders, whereas the ICD-10/-11 mental disorders chapters contain only short summaries. The ICD chapters are meant as a quick reference point, whereas the CDDG is meant for extensive diagnosing by health care professionals. To differentiate the old and the new version, the newest revision is called the ICD-11 CDDG. The WHO described the development of the ICD-11 CDDG as "the most global, multilingual, multidisciplinary and participative revision process ever implemented for a classification of mental disorders", involving nearly 15,000 clinicians from 155 countries. As of February 2023, the WHO has not made the ICD-11 CDDG publicly available.
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ICD-11
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Changes
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Personality disorder The personality disorder (PD) section has been completely revamped. All distinct PDs have been merged into one: Personality disorder (6D10), which can be coded as Mild (6D10.0), Moderate (6D10.1), Severe (6D10.2), or severity unspecified (6D10.Z). There is also an additional category called Personality difficulty (QE50.7), which can be used to describe personality traits that are problematic, but do not rise to the level of a PD. A personality disorder or difficulty can be specified by one or more Prominent personality traits or patterns (6D11). The ICD-11 uses five trait domains: (1) Negative affectivity (6D11.0); (2) Detachment (6D11.1), (3) Dissociality (6D11.2), (4) Disinhibition (6D11.3), and (5) Anankastia (6D11.4). Listed directly underneath is Borderline pattern (6D11.5), a category similar to Borderline personality disorder. This is not a trait in itself, but a combination of the five traits in certain severity.
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ICD-11
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Changes
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Described as a clinical equivalent to the Big Five model, the five-trait system addresses several problems of the old category-based system. Of the ten PDs in the ICD-10, two were used with a disproportionate high frequency: Emotionally unstable personality disorder, borderline type (F60.3) and Dissocial (antisocial) personality disorder (F60.2). Many categories overlapped, and individuals with severe disorders often met the requirements for multiple PDs, which Reed et al. (2019) described as "artificial comorbidity". PD was therefore reconceptualized in terms of a general dimension of severity, focusing on five negative personality traits which a person can have to various degrees.There was considerable debate regarding this new dimensional model, with many believing that categorical diagnosing should not be abandoned. In particular, there was disagreement about the status of Borderline personality disorder. Reed (2018) wrote: "Some research suggests that borderline PD is not an independently valid category, but rather a heterogeneous marker for PD severity. Other researchers view borderline PD as a valid and distinct clinical entity, and claim that 50 years of research support the validity of the category. Many – though by no means all – clinicians appear to be aligned with the latter position. In the absence of more definitive data, there seemed to be little hope of accommodating these opposing views. However, the WHO took seriously the concerns being expressed that access to services for patients with borderline PD, which has increasingly been achieved in some countries based on arguments of treatment efficacy, might be seriously undermined." Thus, the WHO believed the inclusion of a Borderline pattern category to be a "pragmatic compromise".The Alternative DSM-5 Model for Personality Disorders (AMPD) included near the end of the DSM-5 is similar to the PD-system of the ICD-11, although much larger and more comprehensive. It was considered for inclusion in the ICD-11, but the WHO decided against it because it was considered "too complicated for implementation in most clinical settings around the world", since an explicit aim of the WHO was to develop a simple and efficient method that could also be used in low-resource settings.
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ICD-11
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Changes
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Gaming disorder Gaming disorder (6C51) has been newly added to the ICD-11, and placed in the group "Disorders due to addictive behaviours", alongside Gambling disorder (6C50). The latter was called Pathological gambling (F63.0) in the ICD-10. Aside from Gaming disorder, the ICD-11 also features Hazardous gaming (QE22), an ancillary category that can be used to identify problematic gaming which does not rise to the level of a disorder.
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ICD-11
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Changes
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Although a majority of scholars supported the inclusion of Gaming disorder (GD), a significant number did not. Aarseth et al. (2017) stated that the evidence base which this decision relied upon is of low quality, that the diagnostic criteria of gaming disorder are rooted in substance use and gambling disorder even though they are not the same, that no consensus exist on the definition and assessment of GD, and that a pre-defined category would lock research in a confirmatory approach. Rooij et al. (2017) questioned if what was called "gaming disorder" is in fact a coping strategy for underlying problems, such as depression, social anxiety, or ADHD. They also asserted moral panic, fueled by sensational media stories, and stated that the category could be stigmatizing people who are simply engaging in a very immersive hobby. Bean et al. (2017) wrote that the GD category caters to false stereotypes of gamers as physically unfit and socially awkward, and that most gamers have no problems balancing their expected social roles outside games with those inside.In support of the GD category, Lee et al. (2017) agreed that there were major limitations of the existing research, but that this actually necessitates a standardized set of criteria, which would benefit studies more than self-developed instruments for evaluating problematic gaming. Saunders et al. (2017) argued that gaming addiction should be in the ICD-11 just as much as gambling addiction and substance addiction, citing functional neuroimaging studies which show similar brain regions being activated, and psychological studies which show similar antecedents (risk factors). Király and Demetrovics (2017) did not believe that a GD category would lock research into a confirmatory approach, noting that the ICD is regularly revised and characterized by permanent change. They wrote that moral panic around gamers does indeed exist, but that this is not caused by a formal diagnosis. Rumpf et al. (2018) noted that stigmatization is a risk not specific to GD alone. They agreed that GD could be a coping strategy for an underlying disorder, but that in this debate, "comorbidity is more often the rule than the exception". For example, a person can have an alcohol dependence due to PTSD. In clinical practice, both disorders need to be diagnosed and treated. Rumpf et al. also warned that the lack of a GD category might jeopardize insurance reimbursement of treatments.The DSM-5 (2013) features a similar category called Internet Gaming Disorder (IGD). However, due to the controversy over its definition and inclusion, it is not included in its main body of mental diagnoses, but in the additional chapter "Conditions for Further Study". Disorders in this chapter are meant to encourage research and are not intended to be officially diagnosed.
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ICD-11
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Changes
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Burn-out In May 2019, a number of media incorrectly reported that burn-out was newly added to the ICD-11. In reality, burn-out is also in the ICD-10 (Z73.0), albeit with a short, one-sentence definition only. The ICD-11 features a longer summary, and specifically notes that the category should only be used in an occupational context. Furthermore, it should only be applied when mood disorders (6A60–6A8Z), Disorders specifically associated with stress (6B40–6B4Z), and Anxiety or fear-related disorders (6B00–6B0Z) have been ruled out.
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ICD-11
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Changes
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As with the ICD-10, burn-out is not in the mental disorders chapter, but in the chapter "Factors influencing health status or contact with health services", where it is coded QD85. In response to media attention over its inclusion, the WHO emphasized that the ICD-11 does not define burn-out as a mental disorder or a disease, but as an occupational phenomenon that undermines a person's well-being in the workplace.
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ICD-11
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Changes
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Sexual health Conditions related to sexual health is a new chapter in the ICD-11. The WHO decided to put the sexual disorders in a separate chapter due to "the outdated mind/body split". A number of ICD-10 categories, including sex disorders, were based on a Cartesian separation of "organic" (physical) and "non-organic" (mental) conditions. As such, the sexual dysfunctions that were considered non-organic were included in the mental disorder chapter, while those that were considered organic were for the most part listed in the chapter on diseases of the genitourinary system. In the ICD-11, the brain and the body are seen as an integrate whole, with sexual dysfunctions considered to involve an interaction between physical and psychological factors. Thus, the organic/non-organic distinction was abolished.
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ICD-11
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Changes
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Sexual dysfunctions Regarding general sexual dysfunction, the ICD-10 has three main categories: Lack or loss of sexual desire (F52.0), Sexual aversion and lack of sexual enjoyment (F52.1), and Failure of genital response (F52.2). The ICD-11 replaces these with two main categories: Hypoactive sexual desire dysfunction (HA00) and Sexual arousal dysfunction (HA01). The latter has two subcategories: Female sexual arousal dysfunction (HA01.0) and Male erectile dysfunction (HA01.1). The difference between Hypoactive sexual desire dysfunction and Sexual arousal dysfunction is that in the former, there is a reduced or absent desire for sexual activity. In the latter, there is insufficient physical and emotional response to sexual activity, even though there still is a desire to engage in satisfying sex. The WHO acknowledged that there is an overlap between desire and arousal, but they are not the same. Management should focus on their distinct features.The ICD-10 contains the categories Vaginismus (N94.2), Nonorganic vaginismus (F52.5), Dyspareunia (N94.1), and Nonorganic dyspareunia (F52.6). As the WHO aimed to steer away from the aforementioned "outdated mind/body split", the organic and nonorganic disorders were merged. Vaginismus has been reclassified as sexual pain-penetration disorder (HA20). Dyspareunia (GA12) has been retained. A related condition is Vulvodynia, which is in the ICD-9 (625.7), but not in the ICD-10. It has been re-added to the ICD-11 (GA34.02).Sexual dysfunctions and Sexual pain-penetration disorder can be coded alongside a temporal qualifier, "lifelong" or "acquired", and a situational qualifier, "general" or "situational". Furthermore, the ICD-11 offers five aetiological qualifiers, or "Associated with..." categories, to further specify the diagnosis. For example, a woman who experiences sexual problems due to adverse effects of an SSRI antidepressant may be diagnosed with "Female sexual arousal dysfunction, acquired, generalised" (HA01.02) combined with "Associated with use of psychoactive substance or medication" (HA40.2).
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ICD-11
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Changes
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Compulsive sexual behaviour disorder Excessive sexual drive (F52.7) from the ICD-10 has been reclassified as Compulsive sexual behaviour disorder (CSBD, 6C72) and listed under Impulse control disorders. The WHO was unwilling to overpathologize sexual behaviour, stating that having a high sexual drive is not necessarily a disorder, so long as these people do not exhibit impaired control over their behavior, significant distress, or impairment in functioning. Kraus et al. (2018) noted that several people self-identify as "sex addicts", but on closer examination do not actually exhibit the clinical characteristics of a sexual disorder, although they may have other mental health problems, such as anxiety or depression. Experiencing shame and guilt about sex is not a reliable indicator of a sex disorder, Kraus et al. stated.There was debate on whether CSBD should be considered a (behavioral) addiction. It has been claimed that neuroimaging shows overlap between compulsive sexual behavior and substance-use disorder through common neurotransmitter systems. Nonetheless, it was ultimately decided to place the disorder in the Impulse control disorders group. Kraus et al. wrote that, for the ICD-11, "a relatively conservative position has been recommended, recognizing that we do not yet have definitive information on whether the processes involved in the development and maintenance of [CSBD] are equivalent to those observed in substance use disorders, gambling and gaming".
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ICD-11
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Changes
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Paraphilic disorders Paraphilic disorders, called Disorders of sexual preference in the ICD-10, have remained in the mental disorders chapter, although they have gray nodes in the sexual health chapter. The ICD-10 categories Fetishism (F65.0) and Fetishistic transvestism (F65.1) were removed because, if they don't cause distress or harm, they are not considered mental disorders. Frotteuristic disorder (6D34) has been newly added.
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ICD-11
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Changes
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Gender incongruence Transgenderism and gender dysphoria are called Gender incongruence in the ICD-11. In the ICD-10, the group Gender identity disorders (F64) consisted of three main categories: Transsexualism (F64.0), Dual-role transvestism (F64.1), and Gender identity disorder of childhood (F64.2). In the ICD-11, Dual-role transvestism was deleted due to a lack of public health or clinical relevance. Transsexualism was renamed Gender incongruence of adolescence or adulthood (HA60), and Gender identity disorder of childhood was renamed Gender incongruence of childhood (HA61).
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ICD-11
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Changes
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In the ICD-10, the Gender identity disorders were placed in the mental disorders chapter, following what was customary at the time. Throughout the 20th century, both the ICD and the DSM approached transgender health from a psychopathological position, as transgender identity presents a discrepancy between someone's assigned sex and their gender identity. Since this may cause mental distress, it was consequently considered a mental disorder, with distress or discomfort being a core diagnostic feature. In the 2000s and 2010s, this notion became increasingly challenged, as the idea of viewing transgender people as having a mental disorder was believed by some to be stigmatizing. It has been suggested that distress and dysfunction among transgender people should be more appropriately viewed as the result of social rejection, discrimination, and violence toward individuals with gender variant appearance and behavior. Studies have shown transgender people to be at higher risk of developing mental health problems than other populations, but that health services aimed at transgender people are often insufficient or nonexistent. Since an official ICD code is usually needed to gain access to and reimbursement for therapy, the WHO found it ill-advised to remove transgender health from the ICD-11 altogether. It was therefore decided to transpose the concept from the mental disorders chapter to the new sexual health chapter.
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ICD-11
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Changes
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Antimicrobial resistance and GLASS The group related to coding antimicrobial resistance has been significantly expanded: compare U82-U85 in the ICD-10 to 1882742628 in the ICD-11. Also, the ICD-11 codes are more closely in line with the WHO's Global Antimicrobial Resistance Surveillance System (GLASS). Launched in October 2015, this project aims to track the worldwide immunity of malicious microbes (viruses, bacteria, fungi, and protozoa) against medication.
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ICD-11
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Changes
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Traditional medicine "Supplementary Chapter Traditional Medicine Conditions - Module I" is an additional chapter in the ICD-11. It consists of concepts that are commonly referred to as Traditional Chinese Medicine (TCM), although the WHO prefers to use the more general and neutral sounding term Traditional Medicine (TM). Many of the traditional therapies and medicines that originally came from China also have long histories of usage and development in Japan (Kampo), Korea (TKM), and Vietnam (TVM). Medical procedures that can be labeled as "traditional" continue to be used all over the world, and are an integral part of health services in some countries. A 2008 survey by the WHO found that "[i]n some Asian and African countries, 80% of the population depend on traditional medicine for primary health care". Also, "[i]n many developed countries, 70% to 80% of the population has used some form of alternative or complementary medicine (e.g. acupuncture)".From approximately 2003 to 2007, a group of experts from various countries developed the WHO International Standard Terminologies on Traditional Medicine in the Western Pacific Region, or simply IST. In the following years, based on this nomenclature, the group created the International Classification of Traditional Medicine, or ICTM. As of February 2023, Module I, also called TM1, is the only module of the ICTM to have been released. Morris, Gomes, & Allen (2012) have stated that Module II will cover Ayurveda, that Module III will cover homeopathy, and that Module IV will cover "other TM systems with independent diagnostic conditions in a similar fashion". However, these modules have yet to be made public, and Singh & Rastogi (2018) noted that this "keeps the speculations open for what actually is encompassing under the current domain [of the ICTM]".The decision to include T(C)M in the ICD-11 has been criticized, because it is often alleged to be pseudoscience. Editorials by Nature and Scientific American admitted that some TM techniques and herbs have shown effectiveness or potential, but that others are pointless, or even outright harmful. They wrote that the inclusion of the TM-chapter is at odds with the scientific, evidence-based methods usually employed by the WHO. Both editorials accused the government of China of pushing the WHO to incorporate TCM, a global, billion-dollar market in which China plays a leading role. The WHO has stated that the categories of TM1 "do not refer to – or endorse – any form of treatment", and that their inclusion is primarily intended for statistical purposes. The TM1 codes are recommended to be used in conjunction with the Western Medicine concepts of ICD-11 chapters 1-25.
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ICD-11
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Changes
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Other changes Other notable changes in the ICD-11 include: Stroke is now classified as a neurological disorder instead of a disease of the circulatory system.
Allergies are now coded under diseases of the immune system.
In the ICD-10, a distinction was made between Sleep disorders (G47), included in nervous system diseases chapter, and Nonorganic sleep disorders (F51), included in the mental disorders chapter. In the ICD-11, they are merged and placed into a new chapter called Sleep-wake disorders, since the separation between organic (physical) and non-organic (mental) disorders is considered obsolete.
"Supplementary section for functioning assessment" is an additional chapter that provides codes for use in the WHO Disability Assessment Schedule 2.0 (WHODAS 2.0), the Model Disability Survey (MDS), and the ICF.
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ABLIM1
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ABLIM1
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Actin binding LIM protein 1, also known as ABLIM1, is a protein which in humans is encoded by the ABLIM1 gene.
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ABLIM1
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Function
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This gene encodes a cytoskeletal LIM protein that binds to actin filaments via a domain that is homologous to erythrocyte dematin. LIM domains, found in over 60 proteins, play key roles in the regulation of developmental pathways. LIM domains also function as protein-binding interfaces, mediating specific protein-protein interactions. The protein encoded by this gene could mediate such interactions between actin filaments and cytoplasmic targets. Alternatively spliced transcript variants encoding different isoforms have been identified.
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ABLIM1
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Interactions
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ABLIM1 has been shown to interact with LDOC1.
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ACTA2
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ACTA2
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ACTA2 (actin alpha 2) is an actin protein with several aliases including alpha-actin, alpha-actin-2, aortic smooth muscle or alpha smooth muscle actin (α-SMA, SMactin, alpha-SM-actin, ASMA). Actins are a family of globular multi-functional proteins that form microfilaments. ACTA2 is one of 6 different actin isoforms and is involved in the contractile apparatus of smooth muscle. ACTA2 (as with all the actins) is extremely highly conserved and found in nearly all mammals.
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ACTA2
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ACTA2
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In humans, ACTA2 is encoded by the ACTA2 gene located on 10q22-q24. Mutations in this gene cause a variety of vascular diseases, such as thoracic aortic disease, coronary artery disease, stroke, Moyamoya disease, and multisystemic smooth muscle dysfunction syndrome.ACTA2 (commonly referred to as alpha-smooth muscle actin or α-SMA) is often used as a marker of myofibroblast formation. Studies have shown that ACTA2 is associated with TGF-β pathway that enhances contractile properties of hepatic stellate cells leading to liver fibrosis and cirrhosis.
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Petya and NotPetya
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Petya and NotPetya
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Petya is a family of encrypting malware that was first discovered in 2016. The malware targets Microsoft Windows–based systems, infecting the master boot record to execute a payload that encrypts a hard drive's file system table and prevents Windows from booting. It subsequently demands that the user make a payment in Bitcoin in order to regain access to the system.
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Petya and NotPetya
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Petya and NotPetya
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Variants of Petya were first seen in March 2016, which propagated via infected e-mail attachments. In June 2017, a new variant of Petya was used for a global cyberattack, primarily targeting Ukraine. The new variant propagates via the EternalBlue exploit, which is generally believed to have been developed by the U.S. National Security Agency (NSA), and was used earlier in the year by the WannaCry ransomware. Kaspersky Lab referred to this new version as NotPetya to distinguish it from the 2016 variants, due to these differences in operation. It looked like ransomware, but without functioning recovery feature it was equivalent to a wiper. The NotPetya attacks have been blamed on the Russian government, specifically the Sandworm hacking group within the GRU Russian military intelligence organization, by security researchers, Google, and several governments.
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Petya and NotPetya
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History
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Petya was discovered in March 2016; Check Point noted that while it had achieved fewer infections than other ransomware active in early 2016, such as CryptoWall, it contained notable differences in operation that caused it to be "immediately flagged as the next step in ransomware evolution". Another variant of Petya discovered in May 2016 contained a secondary payload used if the malware cannot achieve administrator-level access.The name "Petya" is a reference to the 1995 James Bond film GoldenEye, wherein Petya is one of the two Soviet weapon satellites which carry a "Goldeneye"—an atomic bomb detonated in low Earth orbit to produce an electromagnetic pulse. A Twitter account that Heise suggested may have belonged to the author of the malware, named "Janus Cybercrime Solutions" after Alec Trevelyan's crime group in GoldenEye, had an avatar with an image of GoldenEye character Boris Grishenko, a Russian hacker and antagonist in the film played by Scottish actor Alan Cumming.On 30 August 2018, a regional court in Nikopol in the Dnipropetrovsk Oblast of Ukraine convicted an unnamed Ukrainian citizen to one year in prison after pleading guilty to having spread a version of Petya online.
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Petya and NotPetya
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2017 cyberattack
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On 27 June 2017, a major global cyberattack began (Ukrainian companies were among the first to state they were being attacked), utilizing a new variant of Petya. On that day, Kaspersky Lab reported infections in France, Germany, Italy, Poland, the United Kingdom, and the United States, but that the majority of infections targeted Russia and Ukraine, where more than 80 companies were initially attacked, including the National Bank of Ukraine. ESET estimated on 28 June 2017 that 80% of all infections were in Ukraine, with Germany second hardest hit with about 9%. Russian president Vladimir Putin's press secretary, Dmitry Peskov, stated that the attack had caused no serious damage in Russia. Experts believed this was a politically-motivated attack against Ukraine, since it occurred on the eve of the Ukrainian holiday Constitution Day.Kaspersky dubbed this variant "NotPetya", as it has major differences in its operations in comparison to earlier variants. McAfee engineer Christiaan Beek stated that this variant was designed to spread quickly, and that it had been targeting "complete energy companies, the power grid, bus stations, gas stations, the airport, and banks".It was believed that the software update mechanism of M.E.Doc—a Ukrainian tax preparation program that, according to F-Secure analyst Mikko Hyppönen, "appears to be de facto" among companies doing business in the country—had been compromised to spread the malware. Analysis by ESET found that a backdoor had been present in the update system for at least six weeks prior to the attack, describing it as a "thoroughly well-planned and well-executed operation". The developers of M.E.Doc denied that they were entirely responsible for the cyberattack, stating that they too were victims.On 4 July 2017, Ukraine's cybercrime unit seized the company's servers after detecting "new activity" that it believed would result in "uncontrolled proliferation" of malware. Ukraine police advised M.E.Doc users to stop using the software, as it presumed that the backdoor was still present. Analysis of the seized servers showed that software updates had not been applied since 2013, there was evidence of Russian presence, and an employee's account on the servers had been compromised; the head of the units warned that M.E.Doc could be found criminally responsible for enabling the attack because of its negligence in maintaining the security of their servers.
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Petya and NotPetya
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Operation
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Petya's payload infects the computer's master boot record (MBR), overwrites the Windows bootloader, and triggers a restart. Upon startup, the payload encrypts the Master File Table of the NTFS file system, and then displays the ransom message demanding a payment made in Bitcoin. Meanwhile, the computer's screen displays a purportedly output by chkdsk, Windows' file system scanner, suggesting that the hard drive's sectors are being repaired.The original payload required the user to grant it administrative privileges; one variant of Petya was bundled with a second payload, Mischa, which activated if Petya failed to install. Mischa is a more conventional ransomware payload that encrypts user documents, as well as executable files, and does not require administrative privileges to execute. The earlier versions of Petya disguised their payload as a PDF file, attached to an e-mail. United States Computer Emergency Response Team (US-CERT) and National Cybersecurity and Communications Integration Center (NCCIC) released Malware Initial Findings Report (MIFR) about Petya on 30 June 2017.The "NotPetya" variant used in the 2017 attack uses EternalBlue, an exploit that takes advantage of a vulnerability in Windows' Server Message Block (SMB) protocol. EternalBlue is generally believed to have been developed by the U.S. National Security Agency (NSA); it was leaked in April 2017 and was also used by WannaCry. The malware harvests passwords (using tweaked build of open-source Mimikatz) and uses other techniques to spread to other computers on the same network, and uses those passwords in conjunction with PSExec to run code on other local computers. Additionally, although it still purports to be ransomware, the encryption routine was modified so that the malware could not technically revert its changes. This characteristic, along with other unusual signs in comparison to WannaCry (including the relatively low unlock fee of US$300, and using a single, fixed Bitcoin wallet to collect ransom payments rather than generating a unique ID for each specific infection for tracking purposes), prompted researchers to speculate that this attack was not intended to be a profit-generating venture, but to damage devices quickly, and ride off the media attention WannaCry received by claiming to be ransomware.
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Petya and NotPetya
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Mitigation
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It was found that it may be possible to stop the encryption process if an infected computer is immediately shut down when the fictitious chkdsk screen appears, and a security analyst proposed that creating read-only files named perfc and/or perfc.dat in the Windows installation directory could prevent the payload of the current strain from executing. The email address listed on the ransom screen was suspended by its provider, Posteo, for being a violation of its terms of use. As a result, infected users could not actually send the required payment confirmation to the perpetrator. Additionally, if the computer's filesystem was FAT based, the MFT encryption sequence was skipped, and only the ransomware's message was displayed, allowing data to be recovered trivially.Microsoft had already released patches for supported versions of Windows in March 2017 to address the EternalBlue vulnerability. This was followed by patches for unsupported versions of Windows (such as Windows XP) in May 2017, in the direct wake of WannaCry. Wired believed that "based on the extent of damage Petya has caused so far, though, it appears that many companies have put off patching, despite the clear and potentially devastating threat of a similar ransomware spread." Some enterprises may consider it too disruptive to install updates on certain systems, either due to possible downtime or compatibility concerns, which can be problematic in some environments.
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Petya and NotPetya
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Impact
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In a report published by Wired, a White House assessment pegged the total damages brought about by NotPetya to more than $10 billion. This assessment was repeated by former Homeland Security advisor Tom Bossert, who at the time of the attack was the most senior cybersecurity focused official in the US government.During the attack initiated on 27 June 2017, the radiation monitoring system at Ukraine's Chernobyl Nuclear Power Plant went offline. Several Ukrainian ministries, banks and metro systems were also affected. It is said to have been the most destructive cyberattack ever.Among those affected elsewhere included British advertising company WPP, Maersk Line, American pharmaceutical company Merck & Co. (internationally doing business as MSD), Russian oil company Rosneft (its oil production was unaffected), multinational law firm DLA Piper, French construction company Saint-Gobain and its retail and subsidiary outlets in Estonia, British consumer goods company Reckitt Benckiser, German personal care company Beiersdorf, German logistics company DHL, United States food company Mondelez International, and American hospital operator Heritage Valley Health System. The Cadbury's Chocolate Factory in Hobart, Tasmania, is the first company in Australia to be affected by Petya. On 28 June 2017, JNPT, India's largest container port, had reportedly been affected, with all operations coming to a standstill. Princeton Community Hospital in rural West Virginia will scrap and replace its entire computer network on its path to recovery.The business interruption to Maersk, the world's largest container ship and supply vessel operator, was estimated between $200m and $300m in lost revenues.The business impact on FedEx is estimated to be $400m in 2018, according to the company's 2019 annual report.Jens Stoltenberg, NATO Secretary-General, pressed the alliance to strengthen its cyber defenses, saying that a cyberattack could trigger the Article 5 principle of collective defense.Mondelez International's insurance carrier, Zurich American Insurance Company, has refused to pay out a claim for cleaning up damage from a Notpetya infection, on the grounds that Notpetya is an "act of war" that is not covered by the policy. Mondelez sued Zurich American for $100 million in 2018; the suit was settled in 2022 with the terms of the settlement remaining confidential.
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