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the Amazon rainforest could shift to a savannah-type mixture of trees and grass within 50 years and the Caribbean coral reefs could collapse within 15 years once a state of collapse has been reached. Another indicated that large ecosystem disruptions will occur earlier under more intense climate change: under the high-emissions RCP8.5 scenario, ecosystems in the tropical oceans would be the first to experience abrupt disruption before 2030, with tropical forests and polar environments following by 2050. In total, 15% of ecological assemblages would have over 20% of their species abruptly disrupted if as warming eventually reaches 4 °C (7.2 °F); in contrast, this would happen to fewer than 2% if the warming were to stay below 2 °C (3.6 °F). === Rainforest collapse === Rainforest collapse refers to the actual past and theoretical future ecological collapse of rainforests. It may involve habitat fragmentation to the point where little rainforest biome is left, and rainforest species only survive in isolated refugia. Habitat fragmentation can be caused by roads. When humans start to cut down the trees for logging, secondary roads are created that will go unused after its primary use. Once abandoned, the plants of the rainforest will find it difficult to grow back in that area. Forest fragmentation also opens the path for illegal hunting. Species have a hard time finding a new place to settle in these fragments causing ecological collapse. This leads to extinction of many animals in the rainforest. A classic pattern of forest fragmentation is occurring in many rainforests including those of the Amazon, specifically a 'fishbone' pattern formed by the development of roads into the forest. This is of great concern, not only because of the loss of a biome with many untapped resources and wholesale death of living organisms, but also because plant
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{
"page_id": 58458383,
"source": null,
"title": "Ecosystem collapse"
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and animal species extinction is known to correlate with habitat fragmentation. In the year 2022, research found that more than three-quarters of the Amazon rainforest has been losing resilience due to deforestation and climate change since the early 2000s as measured by recovery-time from short-term perturbations (the critical slowing down), reinforcing the theory that it is approaching a critical transition. Another study from 2022 found that tropical, arid and temperate forests are substantially losing resilience. === Coral reefs === A major concern for marine biologists is the collapse of coral reef ecosystems.). An effect of global climate change is the rising sea levels which can lead to reef drowning or coral bleaching. Human activity, such as fishing, mining, deforestation, etc., serves as a threat for coral reefs by affecting the niche of the coral reefs. For example, there is a demonstrated correlation between a loss in diversity of coral reefs by 30-60% and human activity such as sewage and/or industrial pollution. == Conservation and reversal == As of now there is still not much information on effective conservation or reversal methods for ecosystem collapse. Rather, there has been increased focus on the predictability of ecosystem collapse, whether it is possible, and whether it is productive to explore. This is likely because thorough studies of at-risk ecosystems are a more recent development and trend in ecological fields, so collapse dynamics are either too recent to observe or still emerging. Since studies are not yet long term, conclusions about reversibility or transformation potential are often hard to draw from newer, more focused studies. == See also == Arctic shrinkage Ecological resilience Ecosystem services Environmental degradation Overshoot (ecology) Tipping points in the climate system == References ==
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{
"page_id": 58458383,
"source": null,
"title": "Ecosystem collapse"
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Crenobacter cavernea Cave-375 is a gram-negative bacterium that is closely related to a previously discovered Crenobacter cavernae strain K1W11S-77ͭ. C. cavernea Cave-375 has not directly been described morphologically, however the related strain K1W11S-77ͭ is a "rod-shaped, motile, and strictly aerobic novel bacteria". Its metabolism has not yet been determined. C. cavernea Cave-375 was first identified from a water sample coming from a dripping stalactite. This stalactite was located in the Algar do Pena cave in the karst Estremadura Limestone Massif in central western Portugal. C. cavernea Cave-375 was first isolated and "grown on nutrient agar at 25 degrees Celsius". Its ecology is not yet known. With the sequencing of the genome of C. cavernea Cave-375, the ecological impact should be able to be identified. == Diversity == C. cavernea Cave-375 belongs in the Proteobacteria phylum, Neisseriaceae family, and Crenobacter cavernea species. By comparing the 16s rRNA of the CAVE-375 stain to Crenobacter cavernea species, a 99% similarity value was calculated. When comparing DNA-DNA hybridization using a Genome-to-Genome Distance Calculator, a 62.66% hybridization percentage was found. == Genome == "Genomic DNA was extracted from C. cavernea Cave-375 using an NZY microbial gDNA isolation kit (NZYTech, Portugal)". The whole genome was then sequenced using whole genome shotgun sequencing method. With this, "17,325,372 high-quality raw sequences were assembled into 15 contigs with an N50 value of 323,281 and a total genome size of 2,273,143 base pairs (2.9 Mb)". NCBI Prokaryotic Genome Annotation Pipeline was able to identify a 65.9% GC content and sequencing coding for proteins and tRNA. "2,779 protein coding sequences and 63 tRNA sequences" were identified using this method. == References ==
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{
"page_id": 60621073,
"source": null,
"title": "Crenobacter cavernea"
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A hook is a hand tool used for securing and moving loads. It consists of a round wooden handle with a strong metal hook about 20 cm (8 inches) long projecting at a right angle from the center of the handle. The appliance is held in a closed fist with the hook projecting between two fingers. This type of hook is used in many different industries, and has many different names. It may be called a box hook, cargo hook, loading hook, docker's hook when used by longshoremen, and a baling hook, bale hook, or hay hook in the agricultural industry. Other variants exist, such as in forestry, for moving logs, and a type with a long shaft, used by city workers to remove manhole covers. Smaller hooks may also be used in food processing and transport. == Dockwork == The longshoreman's hook was historically used by longshoremen (stevedores). Before the age of containerization, freight was moved on and off ships with extensive manual labor, and the longshoreman's hook was the basic tool of the dockworker. The hook became an emblem of the longshoreman's profession in the same way that a hammer and anvil are associated with blacksmiths, or the pipe wrench with pipefitters, sprinklerfitters and plumbers. When longshoremen went on strike or retired, it was known as "hanging up the hook" or "slinging the hook", and the newsletter for retired members of the International Longshore and Warehouse Union's Seattle Local is called The Rusty Hook. A longshoreman's hook was often carried by hooking it through the belt. Longshoremen carried various types of hooks depending on the cargo they would handle. Cargo could come in the form of bales, sacks, barrels, wood crates, or it could be stowed individually in the cargo hold of the ship. The primary function of
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{
"page_id": 10027284,
"source": null,
"title": "Hook (hand tool)"
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the hook was to protect the hands of the longshoreman from being injured while handling the cargo. Hooks also improved the reach of the worker and allowed greater strength and handling of the cargo. Some cargo items are liable to be damaged if pulled at with a longshoreman's hook: hence the "Use No Hooks" warning sign. A longshoreman's hook looks somewhat intimidating, and as it was also associated with strong, tough dockworkers, it became a commonly used weapon in crime fiction, similar to the ice pick. For example, in an episode of Alfred Hitchcock Presents entitled Shopping for Death, a character is murdered (off-screen) using a longshoreman's hook. It was sometimes used as a weapon and means of intimidation in real life as well; the book Joey the Hit Man: The Autobiography of a Mafia Killer states "One guy who used to work on the docks was called Charlie the Hook. If he didn't like you he would pick you up with his hook." In the 1957 New York drama film Edge of the City, two longshoremen settle their dispute in a deadly baling hook fight. They are also the primary weapon of Spider Splicers in the BioShock series, so named due to their use of the hooks to crawl on ceilings and attack unexpectedly. == Haying == A hay hook is slightly different in design from a longshoreman's hook, in that the shaft is typically longer. It is used in hay bucking on farms to secure and move bales of hay, which are otherwise awkward to pick up manually. == Gardening == In gardening and agriculture, a variant with a long shaft is used to move large plants. A hook is placed in either side of the baled roots, allowing workers to carry or place the heavy load. ==
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{
"page_id": 10027284,
"source": null,
"title": "Hook (hand tool)"
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Forestry == Called a "Packhaken", "Hebehaken", or "Forsthaken" in German, this type is used in forestry mainly to lift or move firewood. In Sweden, this tool, though slightly different, is called a "timmerkrok", which translates as "timberhook". It is used mainly by two people to move logs by hooking them in each end. == See also == Cant hook Fishing gaff Pickaroon Prosthetic hook == References == == External links == Media related to Hooks (hand tools) at Wikimedia Commons Smithsonian Institution exhibit on the mechanization of the cargo shipping industry. prohandymantools.com Images of longshoreman's hooks: [2] [3] [4]
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{
"page_id": 10027284,
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"title": "Hook (hand tool)"
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Lorentz invariance follows from two independent postulates: the principle of relativity and the principle of constancy of the speed of light. Dropping the latter while keeping the former leads to a new invariance, known as Fock–Lorentz symmetry or the projective Lorentz transformation. The general study of such theories began with Fock, who was motivated by the search for the general symmetry group preserving relativity without assuming the constancy of c. This invariance does not distinguish between inertial frames (and therefore satisfies the principle of relativity) but it allows for a varying speed of light in space, c; indeed it allows for a non-invariant c. According to Maxwell's equations, the speed of light satisfies c = 1 ε 0 μ 0 , {\displaystyle c={\frac {1}{\sqrt {\varepsilon _{0}\mu _{0}}}},} where ε0 and μ0 are the electric constant and the magnetic constant. If the speed of light depends upon the spacetime coordinates of the medium, say x, then c ( x ) = 1 χ ( x ) , {\displaystyle c(x)={\frac {1}{\sqrt {\chi (x)}}},} where χ ( x ) {\displaystyle \chi (x)} represents the vacuum as a variable medium. == See also == Doubly special relativity Orders of magnitude (length) Planck scale Planck units Quantum gravity Planck epoch == References == == Further reading == Giovanni Amelino-Camelia; Jerzy Kowalski-Glikman; Gianluca Mandanici; Andrea Procaccini (2005). "Phenomenology of Doubly Special Relativity". Int. J. Mod. Phys. A. 20 (26): 6007. arXiv:gr-qc/0312124. Bibcode:2005IJMPA..20.6007A. doi:10.1142/S0217751X05028569. S2CID 119340651. João Magueijo; Lee Smolin (2002). "Lorentz invariance with an invariant energy scale". Phys. Rev. Lett. 88 (19): 190403. arXiv:hep-th/0112090. Bibcode:2002PhRvL..88s0403M. doi:10.1103/PhysRevLett.88.190403. PMID 12005620. S2CID 14468105. J Kowalski-Glikman (2004). "Introduction to doubly special relativity". In Giovanni Amelino-Camelia; Jerzy Kowalski-Glikman (eds.). Planck Scale Effects in Astrophysics and Cosmology. Springer. pp. 131ff. ISBN 978-3-540-25263-4. 40th Winter School on Theoretical Physics
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{
"page_id": 21496085,
"source": null,
"title": "Fock–Lorentz symmetry"
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Kepler-283 c is an exoplanet orbiting the K-type star Kepler-283 every 93 days in the circumstellar habitable zone, discovered by the Kepler space telescope in 2014. == Characteristics == === Mass, radius and temperature === It has a surface equilibrium temperature of 238.5 K (−34.6 °C; −30.4 °F). Its radius is 1.82 R🜨. Its orbit is circular with an eccentricity of 0. === Host star === The planet orbits a late orange dwarf star called Kepler-283, spectral type K7V, about 1,596 light years from Earth in the constellation of Cygnus. === Orbit === The planet orbits its star every 93 days, at a distance of around 0.336 AU. == References ==
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"page_id": 47644950,
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This is a list of common affixes used when scientifically naming species, particularly extinct species for whom only their scientific names are used, along with their derivations. a-, an-: Pronunciation: /ə/, /a/, /ən/, /an/. Origin: Ancient Greek: ἀ-, ἀν- (a, an-). Meaning: a prefix used to make words with a sense opposite to that of the root word; in this case, meaning "without" or "-less". This is usually used to describe organisms without a certain characteristic, as well as organisms in which that characteristic may not be immediately obvious. Examples: Anurognathus ("tailless jaw"); Apus ("footless"); Apteryx ("wingless"); Pteranodon ("wings without teeth"); Anura ("tailless"); Anophthalmus ("eyeless") -acanth, acantho-: Pronunciation: /eɪkænθ/, /eɪkænθoʊ/. Origin: Ancient Greek: ἄκανθα (ákantha). Meaning: spine. Examples: Acanthodes ("spiny base"); Acanthostega ("spine roof"); coelacanth ("hollow spine"); Acrocanthosaurus ("high-spined lizard"); Acanthoderes ("spiny neck"); Acanthamoeba ("spiny amoeba"); Metriacanthosaurus ("moderately-spined lizard"); Holacanthus ("full spine") aeto-: Pronunciation: /aɛto/. Origin: Ancient Greek: ἀετός (aetós). Meaning: eagle. Examples: Aetonyx ("eagle claw"); Aetobatus ("eagle ray"); Aetosauria ("eagle lizard") afro-: Pronunciation: /ˈafro/. Origin: Latin: afro-. Meaning: African. Examples: Afrovenator (African hunter); Afropithecus (African ape); Afrotheria (African beasts) -ales: Pronunciation: /ˈa.lis/. Origin: Latin: -ālis. Meaning: Used to form taxonomic names of orders. Examples: Enterobacterales ("Order of Intestinal Bacteria"); Nitrosomonadiales ("Nitrogen fixing bacteria order"); Chromatiales ("Purple Sulfur Fixing Bacteria Order") amphi-: Pronunciation: /amfiː/, /amfɪ/. Origin: Ancient Greek: ἀμφί (amphí). Meaning: both. Examples: Amphibia ("two types of life"); Amphicoelias ("hollow at both ends"); Amphicyon ("ambiguous dog") -anthus, antho-: Pronunciation: /anθəs/, /anθoʊ/. Origin: Ancient Greek: ἄνθος (ánthos). Meaning: flower. Examples: Helianthus ("sunflower"); Anthophila ("flower-loving"); Dianthus ("Zeus flower"/"godly flower") arch-, archi-, archo-, -archon, -archus: Pronunciation: /ark/, /arkoʊ/, /arkɪ/, /arkɒn/, /arkəs/. Origin: Ancient Greek: ἀρχός (arkhós), meaning: ruler; ἀρχικός (arkhikós), meaning: ruling. Used for exceptionally large or widespread animals. Examples: Archelon ("ruling turtle"); Architeuthis ("ruling squid"); Thalattoarchon ("sea ruler"); Archosaur ("ruling lizard"); Andrewsarchus
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("ruler of Andrews") archaeo-: Pronunciation: /arkiːɒ/, /arkiːoʊ/ . Origin: Ancient Greek: ἀρχαῖος (arkhaîos). Meaning: ancient. Used for early versions of animals and plants. Examples: Archaeopteryx ("ancient wing"); Archaeoindris ("ancient Indri"); Archaeopteris ("ancient fern"); Archaeanthus ("ancient flower") -arctos, arcto-: Pronunciation: /arktoʊz/, /arktoʊ/. Origin: Ancient Greek: ἄρκτος (árktos). Meaning: bear. Examples: Phascolarctos ("pouch bear"); Arctodus ("bear tooth"); Arctocyon ("bear dog") arthro-: /arθroʊ/. Origin: Ancient Greek: ἄρθρον (árthron). Meaning: joint. Often used for animals with exoskeletons. Examples: Arthrospira ("jointed coil"); Arthropleura ("jointed rib"); arthropod ("jointed foot") aspido-, -aspis: Pronunciation: /aspɪdoʊ/, /aspɪs/. Origin: Ancient Greek: ἀσπίς (aspís). Meaning: shield. The suffix "-aspis" is used to describe armored fish. Examples: Aspidochelone ("shield turtle"); Cephalaspis ("head shield"); Sacabambaspis ("shield from Sacabamba"); Brindabellaspis ("shield from the Brindabella Ranges") -avus: Pronunciation: /avus/. Origin: Latin: avus. Meaning: grandfather. Examples: Coelurosauravus ("hollow lizard grandfather"); Plateosauravus ("grandfather of Plateosaurus") -avis: Pronunciation: /əvɪs/. Origin: Latin: avis. Meaning: bird. Examples: Protoavis ("first bird"); Argentavis ("bird from Argentina"); Eoalulavis ("little-winged dawn bird") -bates: Pronunciation: /bætiz/. Origin: Ancient Greek: βάτης. Meaning: wanderer, one that treads. Examples: Hylobates ("forest wanderer"); Dendrobates ("tree wanderer") brachi-, brachy-: pronunciation: /brækɪ/. Origin: Ancient Greek: βραχύς, βραχίων (brakhús, brakhíōn). Meaning: short, and the short part of the arm, or upper arm, respectively. Used in its original meaning, and also to mean "arm". Examples: Brachylophosaurus ("short-crested lizard"); Brachiosaurus ("arm lizard"); Brachyceratops ("short-horned face") bronto-: Pronunciation: /brɒntoʊ/. Origin: Ancient Greek: βροντή (brontḗ). Meaning: thunder. Used for large animals. Examples: Brontosaurus ("thunder lizard"), Brontotherium ("thunder beast"), Brontoscorpio ("thunder scorpion"); Brontochelys ("thunder turtle") -canth, cantho-: see -acanth, acantho-. carcharo-: Pronunciation: /kərkæro/. Origin: Ancient Greek: κάρχαρος (kárkharos). Meaning: sharp, jagged; extended via Ancient Greek: καρχαρίας (karkharías) to mean "shark". Examples: Carcharodon ("jagged tooth"), Carcharocles ("glorious shark"), Carcharodontosaurus ("shark toothed lizard") -cephalus, cephalo-, -cephale, -cephalian: Pronunciation: /sɛfələs/, /sɛfəloʊ̯/, /sɛfəli:/ /sɛfeɪliːən/. Origin: Ancient Greek: κεφαλή (kephalḗ). Meaning: head.
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Examples: Sclerocephalus ("hard head"); Euoplocephalus ("well-armored head"), Pachycephalosaurus ("thick headed lizard"), Amtocephale ("head from Amtgai"); Therocephalian ("beast-headed"); Cephalocarida ("head shrimp") -ceras, cerat-, -ceratus: Pronunciation: /sɛrəs/, /sɛrət/, /sɛrətəs/. Origin: Ancient Greek: κέρας (kéras). Meaning: horn. Used for many horned animals, but most notably ceratopsians. Examples: Stegoceras ("roof horn"); Triceratops ("three-horned face"), Orthoceras ("straight horn"); Megaloceras ("big horn"); Ceratosaurus ("horned lizard"); Microceratops ("small horned face"); rhinoceros ("nose horn"); Albertoceras ("horn from Alberta"); Aepyceros ("high horn"); Lophoceros ("crest horn"); Buceros ("ox horn"); Dinocerata ("terrible horn") cetio-, -cetus: Pronunciation: /sɛtɪoʊ/, /siːtəs/. Origin: Ancient Greek κῆτος (kētos). Meaning: sea-monster. The suffix "-cetus" is used for whales or whale ancestors, while the prefix "cetio-" is used for whale-like or large animals. Examples: Peregocetus ("travelling whale"); Cetiosaurus ("whale lizard"); Ambulocetus ("walking whale"); Pakicetus ("whale from Pakistan"), "Perucetus" ("whale from Peru") -cheirus: Pronunciation: /kaɪrəs/. Origin: Ancient Greek: χείρ (kheír). Meaning: hand. Examples: Deinocheirus ("terrible hand"); Ornithocheirus ("bird hand"); Austrocheirus ("southern hand"); Haplocheirus ("simple hand"); Chiroptera ("hand wing") chloro-: Pronunciation: /kloroʊ/. Origin: Ancient Greek: χλωρός (khlōrós). Meaning: green. Examples: Chlorophyta ("green plant"); Chlorophyll ("green leaf") choer-, choero-: Pronunciation: /koɪr/, /koɪroʊ/. Origin: Ancient Greek: χοίρος (koíros). Meaning: pig. Examples: Choeroichthys ("pig-fish"); Choerophryne ("frog pig"); Choerodon ("pig tooth"); Hydrochoerus ("water pig") coel-: Pronunciation: /siːl/ or /sɛl/ . Origin: Ancient Greek: κοῖλος (koîlos). Meaning: hollow. Examples: coelacanth ("hollow spine"); Coelodonta ("hollow tooth"); Coelophysis ("hollow form"); Amphicoelias ("hollow at both ends") cyan-, cyano-: Pronunciation: /saɪæno/. Origin: Ancient Greek: κυάνεος (kuáneos). Meaning: dark blue, blue, dark blue-green. Examples: Cyanocitta ("blue jay"); Cyanobacteria ("blue bacteria"); Cyanocorax ("blue raven") cyclo-: Pronunciation: /saɪkloʊ/ (or /saɪklɒ/). Origin: Ancient Greek: κύκλος (kúklos). Meaning: circle. Examples: Cyclomedusa ("circle Medusa"); Cyclostomata ("circle mouth") cyn-, -cyon: Pronunciation: /saɪn/, /saɪɒn/. Origin: Ancient Greek: κύων (kúon). Meaning: dog. Used for dogs or dog-like creatures. Examples: Cynodont ("dog tooth"); Cynognathus ("dog jaw"); Cynopterus ("dog wing");
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"page_id": 48955671,
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"title": "List of commonly used taxonomic affixes"
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Arctocyon ("bear dog"); Procyonidae ("before the dog"); Cynocephalus ("dog head") -dactyl, -dactylus: Pronunciation: /dæktəl/, /dæktələs/. Origin: Ancient Greek: δάκτυλος (dáktulos). Meaning: finger, toe. Examples: artiodactyl ("even toe"); Pterodactylus ("wing finger"); perissodactyl ("uneven toe"); Ctenodactylus ("comb finger") -deres: Origin: Ancient Greek: δέρη (dére). Meaning: neck, collar. Examples: Acanthoderes ("spiny neck") -derm: Pronunciation: /dɜrm/. Origin: Ancient Greek: δέρμα (dérma). Meaning: animal hide. Used for skin. Examples: placoderm ("plated skin"); echinoderm ("hedgehog skin"); ostracoderm ("shell skin") -delphys, -delphis, delpho-: Pronunciation: /dɜlfɪs/, /dɜlfʊ/. Origin: Ancient Greek: δελφύς ( delphis). Meaning: womb. Used for therian mammals. Examples: Sinodelphys ("Chinese womb"); Didelphis ("two wombs"); Didelphodon ("two-womb [ie opossum] tooth"); Delphinius ("with a womb") dendro-, -dendron, -dendrum: Pronunciation: /dɛn.dɹoʊ/, /ˈdɛndɹən/, /dɛndɹəm/. Origin: Ancient Greek: δένδρον (déndron). Meaning: tree. Examples: Rhododendron ("rose tree"); Liriodendron ("lily tree"); Dendrocnide ("tree nettle"); Epidendrum ("above tree"); Lepidodendron ("scaled tree") di-: Pronunciation: /daɪ/. Origin: Ancient Greek: δίς (dís). Meaning: twice. Used to indicate two of something. Examples: Dilophosaurus ("two crested lizard"); Diceratops ("two-horned face"); diapsid ("two arches") dino-, deino-: Pronunciation: /daɪnoʊ/. Origin: Ancient Greek: δεινός (deinós). Meaning: "terrible", "formidable". Used for presumably fearfully large or dangerous animals or animal parts. Examples: dinosaur ("terrible lizard"), Dinofelis ("terrible cat"), Dinornis ("terrible bird"); Deinonychus ("terrible claw"), Deinocheirus ("terrible hand"); Dinodocus ("terrible beam"); Deinosuchus ("terrible crocodile"), Dinohippus ("terrible horse"), Dinosorex ("terrible shrew"); Deinococcus ("terrible grannule"); Dinocerata ("terrible horn") diplo-: Pronunciation: /dɪploʊ/, /dɪplo/. Origin: Ancient Greek: διπλόος, διπλοῦς (diplóos, diploûs). Meaning: double. Examples: Diplodocus ("double beam"); Diplopoda ("double feet"); Diplomonad ("double unit"); Diplovertebron ("double vertebra") -don, -dont, -donto-: see -odon, -odont, -odonto-. draco-, -draco: Pronunciation: /dreɪkoʊ/ Origin: Latin draco. Meaning: dragon. Examples: Dracophyllum ("dragon race"); Dracocephalum ("dragon head"); Dracaena ("female dragon"), Tethydraco ("Tethys dragon"), Phosphatodraco ("phosphates dragon"). dromaeo-, dromeo-, -dromeus: Pronunciation: /droʊmɪoʊ/, /droʊmɪəs/ Origin: Ancient Greek: δρομαῖος (dromaîos). Meaning: runner. Examples: Dromaeosaurus ("running lizard"); Kulindadromeus ("runner from Kulinda");
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"page_id": 48955671,
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"title": "List of commonly used taxonomic affixes"
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Thalassodromeus ("sea runner"); Eodromaeus ("dawn runner") elasmo-: Pronunciation: /əl:æzːmoʊ/. Origin: Ancient Greek: ἐλασμός (elasmos). Meaning: plate. Examples: elasmobranch ("plated gill"); Elasmosaurus ("plated lizard"); Elasmotherium ("plated beast") eo-: Pronunciation: /iːoʊ̯/. Origin: Ancient Greek: ἠώς (ēṓs). Meaning: dawn. Used for very early appearances of animals in the fossil record. Examples: Eohippus ("dawn horse"); Eomaia ("dawn Maia"); Eoraptor ("dawn thief") -erpeton: Pronunciation: /ɜrpətɒn/. Origin: Ancient Greek: ἑρπετόν (herpetón). Meaning: reptile (literally, "creeping thing"); used for amphibians. Examples: Hynerpeton ("creeper from Hyner"); Greererpeton ("creeper from Greer"); Arizonerpeton ("creeper from Arizona"); Albanerpeton ("creeper of La Grive Saint Alban") eu-: Pronunciation: /iːu̟/. Origin: Ancient Greek: εὖ (eû). Meaning: "good", "well"; also extended via Neo-Latin to mean "true". Used in a variety of ways, often to indicate well-preserved specimens, well-developed bones, "truer" examples of fossil forms, or simply admiration on the part of the discoverer. Examples: Euparkeria ("good one of Parker's"); Euhelopus ("good marsh foot"); Eustreptospondylus ("well-curved vertebrae"); Eucoelophysis ("truly hollow form") -felis: Pronunciation: /fiːlɪs/. Origin: Latin: felis, feles. Meaning: cat. "Felis" alone is the genus name for the group that includes the domestic cat. Examples: Dinofelis ("terrible cat"); Eofelis ("dawn cat"); Pardofelis ("leopard cat") -form, -formes: Pronunciation: /foʊrm/, /foʊrms/. Origin: Latin: forma. Meaning: shape, form. Used for large groups of animals that share similar characteristics; also used in names of bird and fish orders. Examples: Galliformes ("chicken form"); Anseriformes ("goose form"); Squaliformes ("shark form") giga-, gigant-, giganto-: Pronunciation: /gi:gə/, /d͡ʒaɪgænt/, /d͡ʒaɪgæntoʊ/. Origin: Ancient Greek: γίγας, γῐ́γᾰντος (gígas, gigantos). Meaning: giant, of a giant, respectively. Used for large species. Examples: Giganotosaurus ("giant southern lizard"); Gigantopithecus ("giant ape"); Gigantoraptor ("giant seizer"); Gigantopterus ("giant fin"); Gigantspinosaurus ("giant-spined lizard") -gnath-, gnatho-, -gnathus: Pronunciation: /neɪθ/, /neɪθoʊ/, /neɪθəs/ (or /gneɪθəs/). Origin: Ancient Greek: γνάθος (gnáthos). Meaning: jaw. Examples: Caenagnathasia ("recent jaw from Asia"); Gnathostoma ("jaw mouth"); Cynognathus ("dog jaw"); Compsognathus ("elegant jaw");
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"page_id": 48955671,
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"title": "List of commonly used taxonomic affixes"
}
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Gnathosaurus ("jaw lizard"); Gnathostomata ("jaw mouth"); Entognatha ("inner jaw") haplo-: Pronunciation: /hæplə/. Origin: Ancient Greek: ἁπλός (haplós). Meaning: simple. Examples: Haplorhini ("simple-nosed"); Haplocheirus ("simple hand") hemi-: Pronunciation: /hɛmi/. Origin: Ancient Greek: ἡμι- (hēmi-). Meaning: half. Examples: Hemicyon ("half-dog"); hemichordate ("half-chordate"); Hemiptera ("half-wing") hespero-: Pronunciation: /hɛspəroʊ/. Origin: Ancient Greek: ἕσπερος (hésperos). Meaning: western (originally, "evening"). Examples: Hesperornis ("western bird"); Hesperocyon ("western dog"); Hesperosaurus ("western lizard") hippus, hippo-: Pronunciation: /hɪpəs/, /hɪpoʊ/. Origin: Ancient Greek: ἵππος (híppos). Meaning: horse. Examples: Eohippus ("dawn horse"); Hippodraco ("horse dragon"); Hippopotamus ("river horse"); Hippocampus ("sea-monster horse"); Hippophae ("horse light") hyl-, hylo-: Pronunciation: /haɪl/, /haɪloʊ/ (or /haɪlɒ/). Origin: Ancient Greek: ὕλη ("húlē"). Meaning: wood, forest. Examples: Hylonomus ("forest dweller"); Hylobates ("forest walker"); Hylarana ("forest frog") -ia: Pronunciation: /iːə/. Origin: Ancient Greek: -ια, -εια (-ia, -eia). Meaning: an abstraction usually used as an honorific for a person or place. Examples: Dickinsonia ("for Dickinson"); Cooksonia ("for Cookson"); Coloradia ("for Colorado"); Edmontonia ("for Edmonton"); Thomashuxleya ("for Thomas Huxley") ichthyo-, -ichthys: Pronunciation: /ɪkθioʊs/, /ɪkθis/. Origin: Ancient Greek: ἰχθῦς (ikhthûs). Meaning: fish. The suffix "-ichthys" is used for fish, while the prefix "ichthyo-", while used for fish, is also used for fish-like creatures. Examples: Ichthyosaurus ("fish lizard"); Leedsichthys ("fish from Leeds"); Haikouichthys ("fish from Haikou"); Ichthyostega ("fish roof"); Osteichthyes ("bony fish"); Chondrichthyes ("cartilaginous fish") -lania, Pronunciation: /læniːə/, Origin: Ancient Greek: ἀλαίνειν (alaínein): Meaning: to wander. Used for animals that are found in most places around continents. Examples: Meiolania ("weak wanderer"); Megalania ("great wanderer") leo-: Pronunciation: /lɛʊ/. Origin: Ancient Greek: λέων (léon): Meaning: lion. Examples: Leopardus ("spotted lion"); Leontopodium ("lion foot"); Leontopithecus ("lion ape") lio-: Pronunciation: /liː.oː/. Origin: Ancient Greek: λειόω (leióō): Meaning: Make smooth Examples: Liogramma ("smooth writing"); Liopleurodon ("smooth-sided teeth") -lepis, lepido-: Pronunciation: /lɛpɪs/ /lɛpɪdoʊ/ (or /lɛpɪdɒ/). Origin: Ancient Greek: λεπίς (lepis). Meaning: scale. Examples: Mongolepis ("Mongolian scale"); Stagonolepis ("ornamented scale"); Polymerolepis
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("many part scale"); Lepidosauria ("scaled lizards"); Lepidoptera ("scaled wing"); Lepidodendron ("scaled tree") -lestes: Pronunciation: /lɛstiːz/. Origin: Ancient Greek: λῃστής (lēistḗs). Meaning: robber. Examples: Carpolestes ("fruit robber"); Ornitholestes ("bird robber"); Sarcolestes ("flesh robber"); Necrolestes ("grave robber") long: Pronunciation: /lʊng/. Origin: simplified Chinese: 龙; traditional Chinese: 龍. Meaning: dragon. Used for dinosaur finds in China. Examples: Mei long ("sleeping dragon"); Bolong ("small dragon"); Zuolong ("dragon of Zuo"); Shaochilong ("shark toothed dragon") -lopho-, -lophus: Pronunciation: /lɒfoʊ/, /ləfəs/. Origin: Ancient Greek: λόφος (lóphos). Meaning: A bird's crest. Used for animals with crests on their heads. Examples: Dilophosaurus ("two-crested lizard"); Brachylophosaurus ("short-crested lizard"); Saurolophus ("lizard crest"); Teinolophos ("extended crest") lyco-: Pronunciation: /lɪkoʊ/. Origin: Ancient Greek: λύκος (lýkos). Meaning: wolf. Examples: Lycopodium ("wolf foot"); Lycodon ("wolf tooth"); Lycoperdon ("wolf fart") macro-: Pronunciation: /mækroʊ/. Origin: Ancient Greek: μακρός (makrós). Meaning: (correctly) long; (usually) large. Examples: macropod ("big foot"); Macrodontophion ("big tooth snake"); Macrogryphosaurus ("big enigmatic lizard") -maia, maia-: Pronunciation: /meiə/ Origin: Ancient Greek: Μαῖα (Maîa). Meaning: Originally the mother of Hermes in Greek mythology and the goddess of growth in Roman mythology, alternatively spelled Maja. Frequently used to indicate maternal roles, this word should not be construed as translating directly to "mother" (Latin māter; Ancient Greek μήτηρ mḗtēr); aside from being a proper name, in Ancient Greek "maîa" can translate to "midwife" or "foster mother" and was used as an honorific address for older women, typically translated into English as "Good Mother". Examples: Maiasaura ("Good Mother/Maia's lizard"); Eomaia ("dawn Maia"); Juramaia ("Jurassic Maia"); Maiacetus ("mother whale") mega-, megalo-: Pronunciation: /mɛga/, /mɛgaloʊ̯/. Origin: Ancient Greek: μέγας, μεγάλη (mégas, megálē). Meaning: big/great. Examples: Megarachne ("great spider"); Megalosaurus ("great lizard"); megalodon ("great tooth") micro-: Pronunciation: /maɪkroʊ̯/. Origin: Ancient Greek: μικρός (mikrós). Meaning: "small". Examples: Microraptor ("small thief"); Microvenator ("small hunter"); Microceratops ("small horned face") mimo-, -mimus: /maɪmoʊ̯/, /maɪməs/. Origin: Latin:
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"page_id": 48955671,
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mimus. Meaning: actor. Used for creatures that resemble others. Examples: Struthiomimus; ("ostrich mimic"); Ornithomimus ("bird mimic"); Gallimimus ("chicken mimic"); Ornithomimosauria ("bird mimic lizard") -monas, -monad: Pronunciation: /moʊnas/, /monas/, /moʊnad/, /monad/. Origin: Ancient Greek: μονάς (monás). Meaning: unit. Used for single-celled organisms. Examples: Chlamydomonas ("cloak unit"); Pseudomonas ("false unit"); Metamonad ("encompassing unit") -morph: Pronunciation: /moʊrf/. Origin: Ancient Greek: μορφή (morphḗ). Meaning: form, shape. Used for large groups of animals which share a common genetic lineage Examples: Crocodylomorpha ("crocodile form"); Sauropodomorpha ("sauropod form"); Muscomorpha ("fly form"); Dimorphodon ("two shaped teeth") -nax, -anax-: Pronunciation: /nax/, /ænax/. Origin: Ancient Greek: ἄναξ (ánax). Meaning: king. Examples: Lythronax ("gore lord"); Saurophaganax ("lizard eating lord") -noto-: Pronunciation: /notoʊ/. Origin: Ancient Greek: νότος. Meaning: south, southern wind. Used for organisms found in the Southern Hemisphere. Examples: Giganotosaurus ("giant southern lizard"); Notosuchus ("southern crocodile"); Notopalaeognathae ("southern old jaws") -nych, nycho-, -nyx: see -onych, onycho-, -onyx. -odon, -odont, -odonto-, -odus: Pronunciation: /oʊdɒn/, /oʊdɒnt/, /oʊdɒntoʊ/, /oʊdəs/. Origin: Ancient Greek: ὀδούς, ὀδόντος (odoús, odontos). Meaning: tooth, of a tooth, respectively. Examples: Dimetrodon ("two-measures of teeth"), cynodont ("dog tooth"); Carcharodontosaurus ("shark tooth lizard"), Otodus ("ear tooth"), Arctodus ("bear tooth"); Tetraodon ("four tooth") -oides, -odes: Pronunciation: /oiːdiːz/, /oʊːdiːz/. Origin: Ancient Greek: εἶδος (eîdos). Meaning: likeness. Used for species that resemble other species. Examples: Hypocnemoides ("like Hypocnemis"); Aetobarbakinoides ("like the long-legged buzzard"); Callianthemoides ("like Callianthemum"); Argyrodes ("like silver") onycho-, -onychus, -onyx: /ɒnikoʊ/, /ɒnikəs/ (or /ɒnaɪkoʊ/, ɒnaɪkəs/), /ɒniks/. Origin: Ancient Greek: ὄνυξ (ónux). Meaning: claw. Examples: Deinonychus ("terrible claw"); Euronychodon ("European claw tooth"); Nothronychus ("sloth claw"), Baryonyx ("heavy claw") ophi-: Pronunciation: /ɒfɪs/. Origin: Ancient Greek: ὄφις (óphis). Meaning: snake. Used for Ophidia or snake-like animals. Examples: Ophiacodon ("snake tooth"); Ophisaurus ("snake lizard"); Ophiopogon ("snake beard") -ops: Pronunciation: /ɒps/. Origin: Ancient Greek: ὄψ (óps). Meaning: face, eye. Examples: Triceratops ("three-horned face"); Lycaenops ("wolf face"); Moschops ("calf face");
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Spinops ("spine face"); Triops ("three eyes"); -ornis, ornith-, ornitho-: Pronunciation: /oʊ̯rnɪs/, /oʊ̯rnɪθ/, /oʊ̯rnɪθoʊ̯/. Origin: Ancient Greek: ὄρνις, ὄρνιθος (órnis, órnithos). Meaning: bird, of a bird respectively. "ornith-" and "ornitho-" are generally used for animals with birdlike characteristics; the suffix "-ornis" is generally applied to fossil bird species. Examples: ornithischian ("bird-hipped"); Ornithocheirus ("bird-hand"); Eoconfuciusornis ("dawn bird of Confucius") orth-, ortho-: Pronunciation: /oʊ̯rθ/, /oʊ̯rθoʊ̯/. Origin: Ancient Greek: ὄρθος (órthos). Meaning: straight. Examples: Orthocone ("straight cone"); Orthoceras ("straight horn"); Orthacanthus ("straight spine") pachy-: Pronunciation: /pæki/ Origin: Ancient Greek: παχύς (pakhús). Meaning: thick. Examples: Pachycephalosaurus ("thick-headed lizard"); Pachylemur ("thick lemur"); Pachyuromys ("thick tailed mouse"); Pachydermata ("thick skin") para-: Pronunciation: /pærɑː/ Origin: Ancient Greek: παρά (pará). Meaning: near. Used for species that resemble previously named species. Examples: Paranthodon ("nearly flower tooth"); Pararhabdodon ("near fluted tooth"); Parasaurolophus ("near lizard crest") -pelta: Pronunciation: /pɛltə:/ Origin: Ancient Greek: πέλτη (péltē). Meaning: shield. Frequently used for ankylosaurs. Examples: Sauropelta ("lizard shield"); Dracopelta ("dragon shield"); Cedarpelta ("shield from the Cedar Mountains") -phagus, -phagan-: Pronunciation: /feɪgəs/, /feɪgən/. Origin: Ancient Greek: φάγος (phágos). Meaning: eater, eating, glutton. Used for organisms perceived as eating a particular type of thing. Examples: Saurophaganax ("lord of the lizard-eaters"); Ophiophagus ("snake-eating"); Myrmecophaga ("ant-eater") -philus, -phila, philo-: Pronunciation: /fiːləs/, /fiːlə/, /fiːloʊ/. Origin: Ancient Greek: φίλος (phílos). Meaning: dear, beloved, loving. Used for organisms perceived as having a fondness for a particular thing. Examples: Sarcophilus ("flesh-loving"); Drosophila ("dew-loving"); Anthophila ("flower-loving"); Philodendron ("loving trees") -phyton, -phyta, phyto-, -phyte: Pronunciation: /faɪtən/, /faitə/, /faɪtoʊ/, /faɪt/. Origin: Ancient Greek: φυτόν (phutón). Meaning: plant. Examples: Spermatophyta ("seed plant"); Rhyniophyte ("plant of the Rhynie chert"); Phytophthora ("plant destroyer"); Phytolacca ("plant lac") -pithecus, pitheco-: Pronunciation: /piθəkəs/, /piθəkoʊ/, //piθəkə/. Origin: Ancient Greek: πίθηκος (píthēkos). Meaning: ape, monkey. Examples: Australopithecus ("southern ape"); Ardipithecus ("floor ape"); Gigantopithecus ("giant ape"); Pithecellobium ("monkey earring") platy-: Pronunciation: /ˈplætɪ/. Origin: Ancient Greek πλατύς
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(platús). Meaning: flat. Used for creatures that are flat or have flat parts. Examples: Platyhelminthes ("flat worm"); Platybelodon ("flat spear-tusk"); Platycodon ("flat bell"); Platypus ("flat foot") plesio-, plesi-: Pronunciation: /pliːziːoʊ/, /pliːz/ (or pliːʒ/). Origin: Ancient Greek πλησίον (plēsíon). Meaning: near. Used for species that bear similarities to other species. Examples: Plesiosaurus ("near lizard"); Plesiorycteropus ("near aardvark"); Plesiobaena ("near Baena"); Plesiadapis ("near Adapis") -pod, podo-, -pus: Pronunciation: /pɒd/, /pɒdoʊ/, /pʊs/. Origin: Ancient Greek πούς, ποδός (poús, podós). Meaning: foot, of the foot, respectively. Examples: Ornithopod ("bird foot"); Brachypodosaurus ("short footed lizard"); Moropus ("slow foot"); Octopus ("eight foot"); Platypus ("flat foot"); Orycteropus ("burrowing foot"); Decapoda ("ten foot") -prion: Pronunciation: /prɪɒn/. Origin: Ancient Greek πριὢν. Meaning: saw. Examples: Helicoprion ("spiral saw"); Ornithoprion ("bird saw"); Onychoprion ("claw saw"); Suchoprion ("crocodile saw"). Prions are a subfamily of saw-beaked petrels. pro-, protero-: pronunciation: /proʊ̯/, /proʊ̯tεroʊ̯/. Origin: Ancient Greek πρό, πρότερος (pró, próteros). Meaning: before. Usually used for ancestral forms. Examples: Proterosuchus ("early crocodile"); Procompsognathus ("early elegant jaw"); Prosaurolophus ("early lizard crest") proto-: Pronunciation: /proʊtoʊ/. Origin: Ancient Greek πρῶτος (prōtos). Meaning: first. Used for early appearances in the fossil record. Examples: Protoceratops ("first horned face"); Protognathosaurus ("first jaw lizard"); Protohadros ("first hadrosaur") psittaco-, -psitta: Pronunciation: /sitɑːkoʊ/, /psitə/. Origin: Ancient Greek ψιττακός (psittakós). Meaning: parrot. "Psittaco-" is used for parrot-like creatures, while the suffix "psitta" is used for parrots. Examples: Psittacosaurus ("parrot lizard"); Cyclopsitta ("Cyclops parrot"); Xenopsitta ("strange parrot"). pter-, ptero-, -pterus, pteryg-, -ptera, -pteryx. Pronunciation: /ter/, /teroʊ/, /pterəs/, /terɪg/, /pterə/, /pterɪx/. Origin: Ancient Greek πτέρυξ, πτέρυγος (pterux, ptérugos). Meaning: wing, of a wing, respectively. Used for many winged creatures, but also expanded to mean "fin", and used for many undersea arthropods. The suffix "-ptera" is also used in orders of winged insects. Examples: Bolivaria brachyptera ("short winged mantis"); Pteranodon ("toothless wing"); Pterodactylus ("winged finger"); Eurypterus ("wide wing"
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or fin); Pterygotus ("winged" or finned); Coleoptera ("sheathed wing"); Archaeopteryx ("ancient wing"); Stenopterygius ("narrow finned"); Lepidoptera ("scaled wing"); Chiroptera ("hand wing"); Dermoptera ("skin wing") -pus: see -pod, -podo-, -pus. -raptor, raptor-: Pronunciation: /ræptər/. Origin: Latin raptor. Meaning: "robber, thief". Frequently used for dromaeosaurids or similar animals. The term "raptor" by itself may also be used for a dromeosaurid, a Velociraptor, or originally, a bird of prey. Examples: Velociraptor ("speedy thief"); Utahraptor ("thief from Utah"); Raptorex ("thief king") -rex: Pronunciation: /rεks/. Origin: Latin rex. Meaning: king. Often used for large or impressive animals. Examples: Raptorex ("thief king"); Dracorex ("dragon king"); Tyrannosaurus rex ("tyrant lizard king") -rhina, rhino-, -rhinus: Pronunciation: /raɪnə/ /raɪnoʊ̯/, /raɪnəs/. Origin: Ancient Greek ῥίς (rhís). Meaning: nose. Examples: Altirhinus ("high nose"); Pachyrhinosaurus ("thick-nosed lizard"); Lycorhinus ("wolf nose"); Arrhinoceratops ("noseless horned face"); Cretoxyrhina ("Cretaceous sharp nose"); Rhinoceros ("nose horn") rhodo-: Pronunciation: /roʊdoʊ/, /rodoʊ/. Origin: Ancient Greek ῥόδον (rhódon). Meaning: "rose". Used for red-colored or otherwise rose-like organisms. Examples: Rhododendron ("rose tree"); Rhodophyta ("rose plant"); Rhodomonas ("rose unit") rhynco-, -rhynchus: Pronunciation: /rɪnkoʊ/, /rɪnkəs/. Origin: Ancient Greek ῥύγχος (rhúnkhos). Meaning: "beak", "snout". Examples: Rhamphorhynchus ("beak snout"); Aspidorhynchus ("shield snout"); Ornithorhynchus ("bird snout"); rhynchosaur ("beaked lizard"); Rhynchocephalia ("beaked head"); Oncorhynchus ("bent snout") sarco-: Pronunciation: /sɑːrkʊ/. Origin: Ancient Greek σάρξ (sárx). Meaning: flesh. Used for flesh-eating animals or animals and plants with fleshy parts Examples: Sarcophilus ("flesh-loving"); Sarcopterygii ("fleshy fin"); Sarcosuchus ("flesh crocodile") saur, sauro-, -saurus, -saura: Pronunciation: /sɔər/, /sɔəroʊ/, /sɔərəs/, /sɔəra/. Origin: Ancient Greek σαυρος (sauros). Meaning: lizard. Used for dinosaurs and other extinct reptiles. Examples: Dinosaur ("terrible lizard"); Mosasaur ("lizard from the Meuse River"), Tyrannosaurus ("tyrant lizard"), Allosaurus ("other lizard"), Sauroposeidon ("lizard of Poseidon"), Maiasaura ("caring mother lizard"), Bonitasaura ("lizard from La Bonita"), Pleurosaurus ("rib lizard") sin-, sino-: Pronunciation; /sɪn/, /saɪnoʊ̯/. Origin: Latin: Sina. Meaning: from China. Examples: Sinornithosaurus; ("Chinese bird-lizard"); Sinosauropteryx
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("Chinese lizard wing"); Sinoceratops ("Chinese horned face"); Sinraptor ("Chinese thief") smilo-, -smilus: Pronunciation: /smaɪloʊ/, /smaɪləs/. Origin: Ancient Greek σμίλη (smílē). Meaning: a carving knife or chisel. Used for animals with sabre teeth. Examples: Smilodon ("knife tooth"); Smilosuchus ("knife crocodile"); Thylacosmilus ("pouched knife"); Xenosmilus ("strange knife") spino-, -spino-, -spinax, -spinus: Pronunciation: /spaɪnə/, /spaɪnæks/, /spaɪnəs/. Origin: Latin: spīna. Meaning: a thorn, a spine. Examples: Altispinax ("with high spines"); Gigantspinosaurus ("giant-spined lizard"); Iberospinus ("Iberian spine"); Spinops ("spine face"); Spinosaurus ("spine lizard") -spondylus: Pronunciation: /spɒndələs/. Origin: Ancient Greek σπόνδυλος (spóndulos). Meaning: vertebra. Examples: Streptospondylus ("curved vertebrae"); Massospondylus ("massive vertebrae"); Bothriospondylus ("excavated vertebrae") squali-, squalo-: Pronunciation: /skweɪlɪ/, /skweɪloʊ/ . Origin: Latin squalus. Meaning: a kind of sea fish. Used for shark-like creatures. Examples: Squalodon ("shark tooth"); Squaliformes ("shark form"); Squalicorax ("shark raven"); Squalomorphi ("shark shape") stego-, -stega: Pronunciation: /stɛgoʊ/, /stɛgə/. Origin: Ancient Greek στέγη (stégē). Meaning: roof. Used for armoured or plated animals. Examples: Stegosaurus ("roofed lizard"); Ichthyostega ("roofed fish"); Acanthostega ("spine roof") strepto-: Pronunciation: /streptoʊ/, /strepto/. Origin: Ancient Greek στρεπτός (streptós). Meaning: twisted, bent. Examples: Streptophyta ("twisted plant"); Streptococcus ("twisted granule"); Streptospondylus ("twisted vertebrae"); Streptomyces ("twisted fungus") -stoma, -stome, -stomus: Pronunciation: /stoʊma/, /stoʊm/, /stoʊməs/. Origin: Ancient Greek στόμα (stóma). Meaning: mouth. Examples: Deuterostomia ("second mouth"); Gnathostoma ("jaw mouth"); Anastomus ("on mouth"); Cyclostomi ("circle mouth") sucho-, -suchus: Pronunciation: /sjuːkoʊ/, /sjuːkəs/. Origin: Ancient Greek σούχος (soúkhos). Meaning:: Originally the Ancient Greek name for the Ancient Egyptian crocodile-headed god, Sobek. Used to denote crocodilians or crocodile-like animals. Examples: Deinosuchus ("terrible crocodile"); Anatosuchus ("duck crocodile"); Suchomimus ("crocodile mimic"); Sarcosuchus ("flesh crocodile") tauro-: /taərəs/. Origin: Latin: taurus. Meaning: bull. Examples: Taurotragus ("male goat-bull"); Taurovenator ("bull hunter"); Carnotaurus ("meat bull") -teuthis: Pronunciation: /tjuːθɪs/. Origin: Ancient Greek τευθίς (teuthís). Meaning: squid. Used for squids and similar cephalopods. Examples: Gonioteuthis ("narrow squid"); Architeuthis ("ruling squid"); Vampyroteuthis ("vampire squid"); Cylindroteuthis ("cylindrical squid") thalatto-.
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Pronunciation: /θəlatoʊ/. Origin: Ancient Greek θᾰ́λᾰττᾰ (thalatta). Meaning: sea. Examples: Thalattosaurus ("sea lizard"); Thalattoarchon ("sea ruler"); Thalattosuchus ("sea crocodile"). thero-, -therium. Pronunciation: /θɛroʊ/, /θiːrɪəm/. Origin: Ancient Greek θηρίον (theríon). Meaning: beast. Used for supposedly monstrous animals. The suffix "-therium" is often used to denote extinct mammals. Examples: theropod ("beast foot"), Deinotherium ("terrible beast"); Megatherium ("big beast"); Brontotherium ("thunder beast"); Uintatherium ("beast from the Uinta Mountains"); Anthracotherium ("coal beast"); Nototherium ("southern beast"); thylac-: Pronunciation: /θaɪlæk/. Origin: Ancient Greek θύλακος (thúlakos). Meaning: a sack. In the sense of "pouch", used for marsupials. Examples: Thylacine ("pouched one"); Thylacoleo ("pouched lion"); Thylacosmilus ("pouched knife") tri-: Pronunciation: /traɪ/. Origin: Ancient Greek τρία (tría). Meaning: three. Examples: Triceratops ("three-horned face"); Triconodon ("three coned teeth"); Trilobita ("three lobes"); Triops ("three eyes") titano-, -titan: Pronunciation: /taɪtænoʊ/, /taɪtən/. Origin: Ancient Greek Τιτάν, Τιτᾶνος (Titán, Titânos). Meaning: Titan, of the Titan, respectively. Used for large animals. Examples: Titanosaurus ("Titan lizard"); Giraffatitan ("giraffe Titan"); Anatotitan ("duck Titan"); Titanotherium ("Titan beast"); Titanoboa ("Titanic boa") tyranno-, -tyrannus: Pronunciation: /taɪrænoʊ/, /taɪrænəs/. Origin: Ancient Greek τύραννος (túrannos). Meaning: tyrant. Used for animals similar to Tyrannosaurus. Examples: Zhuchengtyrannus ("tyrant from Zhucheng"); Tyrannosaurus ("tyrant lizard"); Nanotyrannus ("dwarf tyrant"); Tyrannotitan ("Titanic tyrant"); Sinotyrannus ("Chinese tyrant"); Suskityrannus ("coyote tyrant") -urus, -uro-: Pronunciation: /uːrəs/, /uːroʊ/. Origin: Ancient Greek: οὐρά (ourá). Meaning: tail. Examples: Dasyurus ("hairy tail"); Coelurosauria ("hollow tail lizards"); Uromastyx ("tail scourge") veloci-: Pronunciation: /vəlɑsɪ/. Origin: Latin velox. Meaning: speed. Example: Velociraptor ("speedy thief"); Velocisaurus ("speedy lizard") -venator: Pronunciation: /vɛnətər/. Origin: Latin venator. Meaning: hunter. Examples: Afrovenator ("African hunter"); Juravenator ("hunter from the Jura Mountains"); Scorpiovenator ("scorpion hunter"); Neovenator ("new hunter"); Concavenator ("hunter of Cuenca") xeno-: Pronunciation: /zinoʊ/. Origin: Ancient Greek ξένος (xénos). Meaning: strange, stranger. Used for organisms that exhibit unusual traits for their class. Examples: Xenosmilus ("strange knife"); Xenotarsosaurus ("strange ankled lizard"); Xenopsitta ("strange parrot"); Xenocyon ("strange
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dog"); Xenokeryx ("strange horn"); Xenostega ("strange roof"); Xenohyla ("strange hynadae"); Xenozancla ("strange animal"); Xenodermus ("strange skin") -zoon, -zoa: Pronunciation: /zoʊɑːn/, /zoʊə/. Origin: Ancient Greek ζῷον (zōion). Meaning: animal. Used for broad categories of animals, or in certain names of animals. Examples: Metazoa ("encompassing animals"); Parazoa ("near animals"); Ecdysozoa ("moulting animals"); Yunnanozoon ("animal from Yunnan"); Yuyuanozoon ("animal from Yu Yuan"); Hydrozoa ("water animals") == See also == List of Latin and Greek words commonly used in systematic names List of Greek and Latin roots in English List of Latin words with English derivatives List of medical roots, suffixes and prefixes Latin names of cities
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"page_id": 48955671,
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The molecular formula C4H5N3O (molar mass: 111.10 g/mol, exact mass: 111.0433 u) may refer to: Cytosine (Cyt) Imexon Isocytosine, or 2-aminouracil
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{
"page_id": 23527703,
"source": null,
"title": "C4H5N3O"
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A Fresnel rhomb is an optical prism that introduces a 90° phase difference between two perpendicular components of polarization, by means of two total internal reflections. If the incident beam is linearly polarized at 45° to the plane of incidence and reflection, the emerging beam is circularly polarized, and vice versa. If the incident beam is linearly polarized at some other inclination, the emerging beam is elliptically polarized with one principal axis in the plane of reflection, and vice versa. The rhomb usually takes the form of a right parallelepiped, or in other words, a solid with six parallelogram faces (a square is to a cube as a parallelogram is to a parallelepiped). If the incident ray is perpendicular to one of the smaller rectangular faces, the angle of incidence and reflection at both of the longer faces is equal to the acute angle of the parallelogram. This angle is chosen so that each reflection introduces a phase difference of 45° between the components polarized parallel and perpendicular to the plane of reflection. For a given, sufficiently high refractive index, there are two angles meeting this criterion; for example, an index of 1.5 requires an angle of 50.2° or 53.3°. Conversely, if the angle of incidence and reflection is fixed, the phase difference introduced by the rhomb depends only on its refractive index, which typically varies only slightly over the visible spectrum. Thus the rhomb functions as if it were a wideband quarter-wave plate – in contrast to a conventional birefringent (doubly-refractive) quarter-wave plate, whose phase difference is more sensitive to the frequency (color) of the light. The material of which the rhomb is made – usually glass – is specifically not birefringent. The Fresnel rhomb is named after its inventor, the French physicist Augustin-Jean Fresnel, who developed the device
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in stages between 1817 and 1823. During that time he deployed it in crucial experiments involving polarization, birefringence, and optical rotation, all of which contributed to the eventual acceptance of his transverse-wave theory of light. == Operation == Incident electromagnetic waves (such as light) consist of transverse vibrations in the electric and magnetic fields; these are proportional to and at right angles to each other and may therefore be represented by (say) the electric field alone. When striking an interface, the electric field oscillations can be resolved into two perpendicular components, known as the s and p components, which are parallel to the surface and the plane of incidence, respectively; in other words, the s and p components are respectively square and parallel to the plane of incidence. Light passing through a Fresnel rhomb undergoes two total internal reflections at the same carefully chosen angle of incidence. After one such reflection, the p component is advanced by 1/8 of a cycle (45°; π/4 radians) relative to the s component. With two such reflections, a relative phase shift of 1/4 of a cycle (90°; π/2) is obtained. The word relative is critical: as the wavelength is very small compared with the dimensions of typical apparatus, the individual phase advances suffered by the s and p components are not readily observable, but the difference between them is easily observable through its effect on the state of polarization of the emerging light. If the incoming light is linearly polarized (plane-polarized), the s and p components are initially in phase; hence, after two reflections, "the p component is 90° ahead in phase", so that the polarization of the emerging light is elliptical with principal axes in the s and p directions (Fig. 1). Similarly, if the incoming light is elliptically polarized with axes in
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the s and p directions, the emerging light is linearly polarized. In the special case in which the incoming s and p components not only are in phase but also have equal magnitudes, the initial linear polarization is at 45° to the plane of incidence and reflection, and the final elliptical polarization is circular. If the circularly polarized light is inspected through an analyzer (second polarizer), it seems to have been completely "depolarized", because its observed brightness is independent of the orientation of the analyzer. But if this light is processed by a second rhomb, it is repolarized at 45° to the plane of reflection in that rhomb – a property not shared by ordinary (unpolarized) light. == Related devices == For a general input polarization, the net effect of the rhomb is identical to that of a birefringent (doubly-refractive) quarter-wave plate, except that a simple birefringent plate gives the desired 90° separation at a single frequency, and not (even approximately) at widely different frequencies, whereas the phase separation given by the rhomb depends on its refractive index, which varies only slightly over a wide frequency range (see Dispersion). Two Fresnel rhombs can be used in tandem (usually cemented to avoid reflections at their interface) to achieve the function of a half-wave plate. The tandem arrangement, unlike a single Fresnel rhomb, has the additional feature that the emerging beam can be collinear with the original incident beam. == Theory == In order to specify the phase shift on reflection, we must choose a sign convention for the reflection coefficient, which is the ratio of the reflected amplitude to the incident amplitude. In the case of the s components, for which the incident and reflected vibrations are both normal (perpendicular) to the plane of incidence, the obvious choice is to say
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that a positive reflection coefficient, corresponding to zero phase shift, is one for which the incident and reflected fields have the same direction (no reversal; no "inversion"). In the case of the p components, this article adopts the convention that a positive reflection coefficient is one for which the incident and reflected fields are inclined towards the same medium. We may then cover both cases by saying that a positive reflection coefficient is one for which the direction of the field vector normal to the plane of incidence (the electric vector for the s polarization, or the magnetic vector for the p polarization) is unchanged by the reflection. (But the reader should be warned that some authors use a different convention for the p components, with the result that the stated phase shift differs by 180° from the value given here.) With the chosen sign convention, the phase advances on total internal reflection, for the s and p components, are respectively given by and where θi is the angle of incidence, and n is the refractive index of the internal (optically denser) medium relative to the external (optically rarer) medium. (Some authors, however, use the reciprocal refractive index, so that their expressions for the phase shifts look different from the above.) The phase advance of the p component relative to the s component is then given by δ = δ p − δ s . {\displaystyle \delta =\delta _{p\!}-\delta _{s}.} This is plotted in black in Fig. 2, for angles of incidence exceeding the critical angle, for three values of the refractive index. It can be seen that a refractive index of 1.45 is not enough to give a 45° phase difference, whereas a refractive index of 1.5 is enough (by a slim margin) to give a 45° phase difference
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at two angles of incidence: about 50.2° and 53.3°. For θi greater than the critical angle, the phase shifts on total reflection are deduced from complex values of the reflection coefficients. For completeness, Fig. 2 also shows the phase shifts on partial reflection, for θi less than the critical angle. In the latter case, the reflection coefficients for the s and p components are real, and are conveniently expressed by Fresnel's sine law and Fresnel's tangent law where θi is the angle of incidence and θt is the angle of refraction (with subscript t for transmitted), and the sign of the latter result is a function of the convention described above. (We can now see a disadvantage of that convention, namely that the two coefficients have opposite signs as we approach normal incidence; the corresponding advantage is that they have the same signs at grazing incidence.) By Fresnel's sine law, rs is positive for all angles of incidence with a transmitted ray (since θt > θi for dense-to-rare incidence), giving a phase shift δs of zero. But, by his tangent law, rp is negative for small angles (that is, near normal incidence), and changes sign at Brewster's angle, where θi and θt are complementary. Thus the phase shift δp is 180° for small θi but switches to 0° at Brewster's angle. Combining the complementarity with Snell's law yields θi = arctan(1/n) as Brewster's angle for dense-to-rare incidence. That completes the information needed to plot δs and δp for all angles of incidence in Fig. 2, in which δp is in red and δs in blue. On the angle-of-incidence scale (horizontal axis), Brewster's angle is where δp (red) falls from 180° to 0°, and the critical angle is where both δp and δs (red and blue) start to rise again. To
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the left of the critical angle is the region of partial reflection; here both reflection coefficients are real (phase 0° or 180°) with magnitudes less than 1. To the right of the critical angle is the region of total reflection; there both reflection coefficients are complex with magnitudes equal to 1. In Fig. 2, the phase difference δ is computed by a final subtraction; but there are other ways of expressing it. Fresnel himself, in 1823, gave a formula for cos δ. Born and Wolf (1970, p. 50) derive an expression for tan(δ/2), and find its maximum analytically. (For derivations of Eqs. (1) to (4) above, see Total internal reflection, especially § Derivation of evanescent wave and § Phase shifts.) == History == === Background === Augustin-Jean Fresnel came to the study of total internal reflection through his research on polarization. In 1811, François Arago discovered that polarized light was apparently "depolarized" in an orientation-dependent and color-dependent manner when passed through a slice of birefringent crystal: the emerging light showed colors when viewed through an analyzer (second polarizer). Chromatic polarization, as this phenomenon came to be called, was more thoroughly investigated in 1812 by Jean-Baptiste Biot. In 1813, Biot established that one case studied by Arago, namely quartz cut perpendicular to its optic axis, was actually a gradual rotation of the plane of polarization with distance. He went on to discover that certain liquids, including turpentine (térébenthine), shared this property (see Optical rotation). In 1816, Fresnel offered his first attempt at a wave-based theory of chromatic polarization. Without (yet) explicitly invoking transverse waves, this theory treated the light as consisting of two perpendicularly polarized components. === Stage 1: Coupled prisms (1817) === In 1817, Fresnel noticed that plane-polarized light seemed to be partly depolarized by total internal reflection, if initially
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polarized at an acute angle to the plane of incidence. By including total internal reflection in a chromatic-polarization experiment, he found that the apparently depolarized light was a mixture of components polarized parallel and perpendicular to the plane of incidence, and that the total reflection introduced a phase difference between them. Choosing an appropriate angle of incidence (not yet exactly specified) gave a phase difference of 1/8 of a cycle. Two such reflections from the "parallel faces" of "two coupled prisms" gave a phase difference of 1/4 of a cycle. In that case, if the light was initially polarized at 45° to the plane of incidence and reflection, it appeared to be completely depolarized after the two reflections. These findings were reported in a memoir submitted and read to the French Academy of Sciences in November 1817. In a "supplement" dated January 1818, Fresnel reported that optical rotation could be emulated by passing the polarized light through a pair of "coupled prisms", followed by an ordinary birefringent lamina sliced parallel to its axis, with the axis at 45° to the plane of reflection of the prisms, followed by a second pair of prisms at 90° to the first. This was the first experimental evidence of a mathematical relation between optical rotation and birefringence. === Stage 2: Parallelepiped (1818) === The memoir of November 1817 bears the undated marginal note: "I have since replaced these two coupled prisms by a parallelepiped in glass." A dated reference to the parallelepiped form – the form that we would now recognize as a Fresnel rhomb – is found in a memoir which Fresnel read to the Academy on 30 March 1818, and which was subsequently lost until 1846. In that memoir, Fresnel reported that if polarized light was fully "depolarized" by a rhomb, its
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properties were not further modified by a subsequent passage through an optically rotating medium, whether that medium was a crystal or a liquid or even his own emulator; for example, the light retained its ability to be repolarized by a second rhomb. === Interlude (1818–1822) === As an engineer of bridges and roads, and as a proponent of the wave theory of light, Fresnel was still an outsider to the physics establishment when he presented his parallelepiped in March 1818. But he was increasingly difficult to ignore. In April 1818 he claimed priority for the Fresnel integrals. In July he submitted the great memoir on diffraction that immortalized his name in elementary physics textbooks. In 1819 came the announcement of the prize for the memoir on diffraction, the publication of the Fresnel–Arago laws, and the presentation of Fresnel's proposal to install "stepped lenses" in lighthouses. In 1821, Fresnel derived formulae equivalent to his sine and tangent laws (Eqs. (3) and (4), above) by modeling light waves as transverse elastic waves with vibrations perpendicular to what had previously been called the plane of polarization. Using old experimental data, he promptly confirmed that the equations correctly predicted the direction of polarization of the reflected beam when the incident beam was polarized at 45° to the plane of incidence, for light incident from air onto glass or water. The experimental confirmation was reported in a "postscript" to the work in which Fresnel expounded his mature theory of chromatic polarization, introducing transverse waves. Details of the derivation were given later, in a memoir read to the academy in January 1823. The derivation combined conservation of energy with continuity of the tangential vibration at the interface, but failed to allow for any condition on the normal component of vibration. (The first derivation from electromagnetic principles
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was given by Hendrik Lorentz in 1875.) Meanwhile, by April 1822, Fresnel accounted for the directions and polarizations of the refracted rays in birefringent crystals of the biaxial class – a feat that won the admiration of Pierre-Simon Laplace. === Use in experiments (1822–1823) === In a memoir on stress-induced birefringence (now called photoelasticity) read in September 1822, Fresnel reported an experiment involving a row of glass prisms with their refracting angles in alternating directions, and with two half-prisms at the ends, making the whole assembly rectangular. When the prisms facing the same way were compressed in a vise, objects viewed through the length of the assembly appeared double. At the end of this memoir he proposed a variation of the experiment, involving a Fresnel rhomb, for the purpose of verifying that optical rotation is a form of birefringence: he predicted that if the compressed glass prisms were replaced by (unstressed) monocrystalline quartz prisms with the same direction of optical rotation and with their optic axes aligned along the row, an object seen by looking along the common optic axis would give two images, which would seem unpolarized if viewed through an analyzer alone; but if viewed through a Fresnel rhomb, they would be polarized at ±45° to the plane of reflection. Confirmation of this prediction was reported in a memoir read in December 1822, in which Fresnel coined the terms linear polarization, circular polarization, and elliptical polarization. In the experiment, the Fresnel rhomb revealed that the two images were circularly polarized in opposite directions, and the separation of the images showed that the different (circular) polarizations propagated at different speeds. To obtain a visible separation, Fresnel needed only one 14°–152°–14° prism and two half-prisms. He found, however, that the separation was improved if the glass half-prisms were replaced by
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quartz half-prisms whose direction of optical rotation was opposite to that of the 14°–152°–14° prism. Thus, although we now think of the Fresnel rhomb primarily as a device for converting between linear and circular polarization, it was not until the memoir of December 1822 that Fresnel himself could describe it in those terms. In the same memoir, Fresnel explained optical rotation by noting that linearly-polarized light could be resolved into two circularly-polarized components rotating in opposite directions. If these components propagated at slightly different speeds (as he had demonstrated for quartz), then the phase difference between them – and therefore the orientation of their linearly-polarized resultant – would vary continuously with distance. === Stage 3: Calculation of angles (1823) === The concept of circular polarization was useful in the memoir of January 1823, containing the detailed derivations of the sine and tangent laws: in that same memoir, Fresnel found that for angles of incidence greater than the critical angle, the resulting reflection coefficients were complex with unit magnitude. Noting that the magnitude represented the amplitude ratio as usual, he guessed that the argument represented the phase shift, and verified the hypothesis by experiment. The verification involved calculating the angle of incidence that would introduce a total phase difference of 90° between the s and p components, for various numbers of total internal reflections at that angle (generally there were two solutions), subjecting light to that number of total internal reflections at that angle of incidence, with an initial linear polarization at 45° to the plane of incidence, and checking that the final polarization was circular. This procedure was necessary because, with the technology of the time, one could not measure the s and p phase-shifts directly, and one could not measure an arbitrary degree of ellipticality of polarization, such as
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might be caused by the difference between the phase shifts. But one could verify that the polarization was circular, because the brightness of the light was then insensitive to the orientation of the analyzer. For glass with a refractive index of 1.51, Fresnel calculated that a 45° phase difference between the two reflection coefficients (hence a 90° difference after two reflections) required an angle of incidence of 48°37' or 54°37'. He cut a rhomb to the latter angle and found that it performed as expected. Thus the specification of the Fresnel rhomb was completed. Similarly, Fresnel calculated and verified the angle of incidence that would give a 90° phase difference after three reflections at the same angle, and four reflections at the same angle. In each case there were two solutions, and in each case he reported that the larger angle of incidence gave an accurate circular polarization (for an initial linear polarization at 45° to the plane of reflection). For the case of three reflections he also tested the smaller angle, but found that it gave some coloration due to the proximity of the critical angle and its slight dependence on wavelength. (Compare Fig. 2 above, which shows that the phase difference δ is more sensitive to the refractive index for smaller angles of incidence.) For added confidence, Fresnel predicted and verified that four total internal reflections at 68°27' would give an accurate circular polarization if two of the reflections had water as the external medium while the other two had air, but not if the reflecting surfaces were all wet or all dry. === Significance === In summary, the invention of the rhomb was not a single event in Fresnel's career, but a process spanning a large part of it. Arguably, the calculation of the phase shift on
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total internal reflection marked not only the completion of his theory of the rhomb, but also the essential completion of his reconstruction of physical optics on the transverse-wave hypothesis (see Augustin-Jean Fresnel). The calculation of the phase shift was also a landmark in the application of complex numbers. Leonhard Euler had pioneered the use of complex exponents in solutions of ordinary differential equations, on the understanding that the real part of the solution was the relevant part. But Fresnel's treatment of total internal reflection seems to have been the first occasion on which a physical meaning was attached to the argument of a complex number. According to Salomon Bochner, We think that this was the first time that complex numbers or any other mathematical objects which are "nothing-but-symbols" were put into the center of an interpretative context of "reality", and it is an extraordinary fact that this interpretation, although the first of its kind, stood up so well to verification by experiment and to the later "maxwellization" of the entire theory. In very loose terms one can say that this was the first time in which "nature" was abstracted from "pure" mathematics, that is from a mathematics which had not been previously abstracted from nature itself. == See also == == Notes == == References == == Bibliography == S. Bochner (June 1963), "The significance of some basic mathematical conceptions for physics", Isis, vol. 54, no. 2, pp. 179–205; jstor.org/stable/228537. M. Born and E. Wolf, 1970, Principles of Optics, 4th ed., Oxford: Pergamon Press. J. Z. Buchwald, 1989, The Rise of the Wave Theory of Light: Optical Theory and Experiment in the Early Nineteenth Century, University of Chicago Press, ISBN 0-226-07886-8. O. Darrigol, 2012, A History of Optics: From Greek Antiquity to the Nineteenth Century, Oxford, ISBN 978-0-19-964437-7. A. Fresnel,
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1866 (ed. H. de Senarmont, E. Verdet, and L. Fresnel), Oeuvres complètes d'Augustin Fresnel, Paris: Imprimerie Impériale (3 vols., 1866–1870), vol. 1 (1866) (in French). E. Hecht, 2002, Optics, 4th ed., Addison Wesley, ISBN 0-321-18878-0. F. A. Jenkins and H. E. White, 1976, Fundamentals of Optics, 4th ed., New York: McGraw-Hill, ISBN 0-07-032330-5. N. Kipnis, 1991, History of the Principle of Interference of Light, Basel: Birkhäuser, ISBN 978-3-0348-9717-4. H. Lloyd, 1834, "Report on the progress and present state of physical optics", Report of the Fourth Meeting of the British Association for the Advancement of Science (held at Edinburgh in 1834), London: J. Murray, 1835, pp. 295–413. J. A. Stratton, 1941, Electromagnetic Theory, New York: McGraw-Hill. W. Whewell, 1857, History of the Inductive Sciences: From the Earliest to the Present Time, 3rd ed., London: J. W. Parker & Son, vol. 2. E. T. Whittaker, 1910, A History of the Theories of Aether and Electricity: From the Age of Descartes to the Close of the Nineteenth Century, London: Longmans, Green, & Co. == External links == For some photographs of (antique) Fresnel rhombs, see T. B. Greenslade, Jr., "Fresnel's rhomb", Instruments for Natural Philosophy, Kenyon College (Gambier, OH), accessed 4 March 2018; archived 28 August 2017. (Erratum, confirmed by the author: The words "at Brewster's angle" should be deleted.)
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David G. Blair (born 1946) is an Australian physicist and professor at the University of Western Australia and Director of the Australian International Gravitational Research Centre. Blair works on methods for the detection of gravitational waves. He developed the niobium bar gravitational wave detector NIOBE, which achieved the lowest observed noise temperature, and participated in a worldwide collaboration that set the best limit on the burst events in 2001. He has been responsible for numerous innovations including the 1984 invention of the first sapphire clock, a super-precise timepiece designed for space, as well as underpinning the research of the Frequency Stability Group at The University of Western Australia. In 2003, together with Prof. John de Laeter, Blair founded the Gravity Discovery Centre, a major centre for the promotion of science in Western Australia. In 2010, Blair and collaborating partners developed an educational research program called the Science Education Enrichment Project, to research the benefits of specialist exhibition centres such as the Gravity Discovery Centre. In 2014, Blair led the Einstein-First Project which aims to introduce Einsteinian Physics at an early age. The project partners included Curtin University, Edith Cowan University, Graham (Polly) Farmer Foundation, U.S. Air Force Academy and the Gravity Discovery Centre. == Honours and recognition == In 2013 Blair was elected Fellow of the American Physical Society; 2007 Western Australian (WA) Premier's Science Award for Scientist of the Year; 2005 World Year of Physics, Blair was awarded the ANZAAS Medal as well as a WA Government Centre of Excellence Grant to develop the Australian International Gravitational Research Centre; 2004 Learning Links Certificate, Minister for Education and Training; 2003 National Medal for Community Service; 2003 Centenary Medal (for Promotion of Science); 2003 Clunies Ross Medal for Science and Technology and in 1995 Blair won the Walter Boas Medal of
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the Australian Institute of Physics. In 2018 Blair was elected Fellow of the Australian Academy of Science. == Publications == Professor Blair is the co-author of Ripples on a Cosmic Sea: The Search for Gravitational Waves, and the editor of the book The Detection of Gravitational Waves. == References ==
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Neutron capture therapy (NCT) is a type of radiotherapy for treating locally invasive malignant tumors such as primary brain tumors, recurrent cancers of the head and neck region, and cutaneous and extracutaneous melanomas. It is a two-step process: first, the patient is injected with a tumor-localizing drug containing the stable isotope boron-10 (10B), which has a high propensity to capture low energy "thermal" neutrons. The neutron cross section of 10B (3,837 barns) is 1,000 times more than that of other elements, such as nitrogen, hydrogen, or oxygen, that occur in tissue. In the second step, the patient is radiated with epithermal neutrons, the sources of which in the past have been nuclear reactors and now are accelerators that produce higher energy epithermal neutrons. After losing energy as they penetrate tissue, the resultant low energy "thermal" neutrons are captured by the 10B atoms. The resulting decay reaction yields high-energy alpha particles that kill the cancer cells that have taken up enough 10B. All clinical experience with NCT to date is with boron-10; hence this method is known as boron neutron capture therapy (BNCT). Use of another non-radioactive isotope, such as gadolinium, has been limited to experimental animal studies and has not been done clinically. BNCT has been evaluated as an alternative to conventional radiation therapy for malignant brain tumors such as glioblastomas, which presently are incurable, and more recently, locally advanced recurrent cancers of the head and neck region and, much less often, superficial melanomas mainly involving the skin and genital region. == Boron neutron capture therapy == === History === James Chadwick discovered the neutron in 1932. Shortly thereafter, H. J. Taylor reported that boron-10 nuclei had a high propensity to capture low energy "thermal" neutrons. This reaction causes nuclear decay of the boron-10 nuclei into helium-4 nuclei (alpha particles)
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and lithium-7 ions. In 1936, G.L. Locher, a scientist at the Franklin Institute in Philadelphia, Pennsylvania, recognized the therapeutic potential of this discovery and suggested that this specific type of neutron capture reaction could be used to treat cancer. William Sweet, a neurosurgeon at the Massachusetts General Hospital, first suggested the possibility of using BNCT to treat malignant brain tumors to evaluate BNCT for treatment of the most malignant of all brain tumors, glioblastoma multiforme (GBMs), using borax as the boron delivery agent in 1951. A clinical trial subsequently was initiated by Lee Farr using a specially constructed nuclear reactor at the Brookhaven National Laboratory in Long Island, New York, U.S.A. Another clinical trial was initiated in 1954 by Sweet at the Massachusetts General Hospital using the Research Reactor at the Massachusetts Institute of Technology (MIT) in Boston. A number of research groups worldwide have continued the early ground-breaking clinical studies of Sweet and Farr, and subsequently the pioneering clinical studies of Hiroshi Hatanaka (畠中洋) in the 1960s, to treat patients with brain tumors. Since then, clinical trials have been done in a number of countries including Japan, the United States, Sweden, Finland, the Czech Republic, Taiwan, and Argentina. After the nuclear accident at Fukushima (2011), the clinical program there transitioned from a reactor neutron source to accelerators that would produce high energy neutrons that become thermalized as they penetrate tissue. == Basic principles == Neutron capture therapy is a binary system that consists of two separate components to achieve its therapeutic effect. Each component in itself is non-tumoricidal, but when combined they can be highly lethal to cancer cells. BNCT is based on the nuclear capture and decay reactions that occur when non-radioactive boron-10, which makes up approximately 20% of natural elemental boron, is irradiated with neutrons of the
|
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appropriate energy to yield excited boron-11 (11B*). This undergoes radioactive decay to produce high-energy alpha particles (4He nuclei) and high-energy lithium-7 (7Li) nuclei. The nuclear reaction is: 10B + nth → [11B] *→ α + 7Li + 2.31 MeV Both the alpha particles and the lithium nuclei produce closely spaced ionizations in the immediate vicinity of the reaction, with a range of 5–9 μm. This approximately is the diameter of the target cell, and thus the lethality of the capture reaction is limited to boron-containing cells. BNCT, therefore, can be regarded as both a biologically and a physically targeted type of radiation therapy. The success of BNCT is dependent upon the selective delivery of sufficient amounts of 10B to the tumor with only small amounts localized in the surrounding normal tissues. Thus, normal tissues, if they have not taken up sufficient amounts of boron-10, can be spared from the neutron capture and decay reactions. Normal tissue tolerance, however, is determined by the nuclear capture reactions that occur with normal tissue hydrogen and nitrogen. A wide variety of boron delivery agents have been synthesized. The first, which has mainly been used in Japan, is a polyhedral borane anion, sodium borocaptate or BSH (Na2B12H11SH), and the second is a dihydroxyboryl derivative of phenylalanine, called boronophenylalanine or BPA. The latter has been used in many clinical trials. Following administration of either BPA or BSH by intravenous infusion, the tumor site is irradiated with neutrons, the source of which, until recently, has been specially designed nuclear reactors and now is neutron accelerators. Until 1994, low-energy (< 0.5 eV) thermal neutron beams were used in Japan and the United States, but since they have a limited depth of penetration in tissues, higher energy (> .5eV < 10 keV) epithermal neutron beams, which have a greater
|
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depth of penetration, were used in clinical trials in the United States, Europe, Japan, Argentina, Taiwan, and China until recently when accelerators replaced the reactors. In theory BNCT is a highly selective type of radiation therapy that can target tumor cells without causing radiation damage to the adjacent normal cells and tissues. Doses up to 60–70 grays (Gy) can be delivered to the tumor cells in one or two applications compared to 6–7 weeks for conventional fractionated external beam photon irradiation. However, the effectiveness of BNCT is dependent upon a relatively homogeneous cellular distribution of 10B within the tumor, and more specifically within the constituent tumor cells, and this is still one of the main unsolved problems that have limited its success. == Radiobiological considerations == The radiation doses to tumor and normal tissues in BNCT are due to energy deposition from three types of directly ionizing radiation that differ in their linear energy transfer (LET), which is the rate of energy loss along the path of an ionizing particle: 1. Low-LET gamma rays, resulting primarily from the capture of thermal neutrons by normal tissue hydrogen atoms [1H(n,γ)2H]; 2. High-LET protons, produced by the scattering of fast neutrons and from the capture of thermal neutrons by nitrogen atoms [14N(n,p)14C]; and 3. High-LET, heavier charged alpha particles (stripped down helium [4He] nuclei) and lithium-7 ions, released as products of the thermal neutron capture and decay reactions with 10B [10B(n,α)7Li]. Since both the tumor and surrounding normal tissues are present in the radiation field, even with an ideal epithermal neutron beam, there will be an unavoidable, non-specific background dose, consisting of both high- and low-LET radiation. However, a higher concentration of 10B in the tumor will result in it getting a higher total dose than that of adjacent normal tissues, which is
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the basis for the therapeutic gain in BNCT. The total radiation dose in Gy delivered to any tissue can be expressed in photon-equivalent units as the sum of each of the high-LET dose components multiplied by weighting factors (Gyw), which depend on the increased radiobiological effectiveness of each of these components. == Clinical dosimetry == Biological weighting factors have been used in all of the more recent clinical trials in patients with high-grade gliomas, using boronophenylalanine (BPA) in combination with an epithermal neutron beam. The 10B(n,α)7Li part of the radiation dose to the scalp has been based on the measured boron concentration in the blood at the time of BNCT, assuming a blood: scalp boron concentration ratio of 1.5:1 and a compound biological effectiveness (CBE) factor for BPA in skin of 2.5. A relative biological effectiveness (RBE) or CBE factor of 3.2 has been used in all tissues for the high-LET components of the beam, such as alpha particles. The RBE factor is used to compare the biologic effectiveness of different types of ionizing radiation. The high-LET components include protons resulting from the capture reaction with normal tissue nitrogen, and recoil protons resulting from the collision of fast neutrons with hydrogen. It must be emphasized that the tissue distribution of the boron delivery agent in humans should be similar to that in the experimental animal model in order to use the experimentally derived values for estimation of the radiation doses for clinical radiations. For more detailed information relating to computational dosimetry and treatment planning, interested readers are referred to a comprehensive review on this subject. == Boron delivery agents == The development of boron delivery agents for BNCT began in the early 1960s and is an ongoing and difficult task. A number of boron-10 containing delivery agents have been synthesized
|
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for potential use in BNCT. The most important requirements for a successful boron delivery agent are: low systemic toxicity and normal tissue uptake with high tumor uptake and concomitantly high tumor: to brain (T:Br) and tumor: to blood (T:Bl) concentration ratios (> 3–4:1); tumor concentrations in the range of ~20-50 μg 10B/g tumor; rapid clearance from blood and normal tissues and persistence in tumor during BNCT. However, as of 2021 no single boron delivery agent fulfills all of these criteria. With the development of new chemical synthetic techniques and increased knowledge of the biological and biochemical requirements needed for an effective agent and their modes of delivery, a wide variety of new boron agents has emerged (see examples in Table 1). However, only one of these compounds has ever been tested in large animals, and only boronophenylalanine (BPA) and sodium borocaptate (BSH), have been used clinically. aThe delivery agents are not listed in any order that indicates their potential usefulness for BNCT. None of these agents have been evaluated in any animals larger than mice and rats, except for boronated porphyrin (BOPP) that also has been evaluated in dogs. However, due to the severe toxicity of BOPP in canines, no further studies were carried out. bSee Barth, R.F., Mi, P., and Yang, W., Boron delivery agents for neutron capture therapy of cancer, Cancer Communications, 38:35 (doi:10.1186/s40880-018-0299-7), 2018 for an updated review. cThe abbreviations used in this table are defined as follows: BNCT, boron neutron capture therapy; DNA, deoxyribonucleic acid; EGF, epidermal growth factor; EGFR, epidermal growth factor receptor; MoAbs, monoclonal antibodies; VEGF, vascular endothelial growth factor. The major challenge in the development of boron delivery agents has been the requirement for selective tumor targeting in order to achieve boron concentrations (20-50 μg/g tumor) sufficient to produce therapeutic doses of radiation
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at the site of the tumor with minimal radiation delivered to normal tissues. The selective destruction of infliltrative tumor (glioma) cells in the presence of normal brain cells represents an even greater challenge compared to malignancies at other sites in the body. Malignant gliomas are highly infiltrative of normal brain, histologically diverse, heterogeneous in their genomic profile and therefore it is very difficult to kill all of them. == Gadolinium neutron capture therapy (Gd NCT) == There also has been some interest in the possible use of gadolinium-157 (157Gd) as a capture agent for NCT for the following reasons: First, and foremost, has been its very high neutron capture cross section of 254,000 barns. Second, gadolinium compounds, such as Gd-DTPA (gadopentetate dimeglumine Magnevist), have been used routinely as contrast agents for magnetic resonance imaging (MRI) of brain tumors and have shown high uptake by brain tumor cells in tissue culture (in vitro). Third, gamma rays and internal conversion and Auger electrons are products of the 157Gd(n,γ)158Gd capture reaction (157Gd + nth (0.025eV) → [158Gd] → 158Gd + γ + 7.94 MeV). Though the gamma rays have longer pathlengths, orders of magnitude greater depths of penetration compared with alpha particles, the other radiation products (internal conversion and Auger electrons) have pathlengths of about one cell diameter and can directly damage DNA. Therefore, it would be highly advantageous for the production of DNA damage if the 157Gd were localized within the cell nucleus. However, the possibility of incorporating gadolinium into biologically active molecules is very limited and only a small number of potential delivery agents for Gd NCT have been evaluated. Relatively few studies with Gd have been carried out in experimental animals compared to the large number with boron containing compounds (Table 1), which have been synthesized and evaluated in experimental
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animals (in vivo). Although in vitro activity has been demonstrated using the Gd-containing MRI contrast agent Magnevist as the Gd delivery agent, there are very few studies demonstrating the efficacy of Gd NCT in experimental animal tumor models, and, as evidenced by a lack of citations in the literature, Gd NCT has not, as of 2019, been used clinically in humans. == Neutron sources == === Clinical Studies Using Nuclear reactors as Neutron Sources === Until 2014, neutron sources for NCT were limited to nuclear reactors. Reactor-derived neutrons are classified according to their energies as thermal (En < 0.5 eV), epithermal (0.5 eV < En < 10 keV), or fast (En >10 keV). Thermal neutrons are the most important for BNCT since they usually initiate the 10B(n,α)7Li capture reaction. However, because they have a limited depth of penetration, epithermal neutrons, which lose energy and fall into the thermal range as they penetrate tissues, are now preferred for clinical therapy, other than for skin tumors such as melanoma. A number of nuclear reactors with very good neutron beam quality have been developed and used clinically. These include: Kyoto University Research Reactor Institute (KURRI) in Kumatori, Japan; the Massachusetts Institute of Technology Research Reactor (MITR); the FiR1 (Triga Mk II) research reactor at VTT Technical Research Centre, Espoo, Finland; the RA-6 CNEA reactor in Bariloche, Argentina; the High Flux Reactor (HFR) at Petten in the Netherlands; and Tsing Hua Open-pool Reactor (THOR) at the National Tsing Hua University, Hsinchu, Taiwan. JRR-4 at Japan Atomic Energy Agency, Tokai, JAPAN A compact In-Hospital Neutron Irradiator (IHNI) in a free-standing facility in Beijing, China. As of May 2021, only the reactors in Argentina, China, and Taiwan are still being used clinically. It is anticipated that, beginning some time in 2022, clinical studies in Finland will
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utilize an accelerator neutron source designed and fabricated in the United States by Neutron Therapeutics, Danvers, Massachusetts. == Clinical studies of BNCT for brain tumors == === Early studies in the US and Japan === It was not until the 1950s that the first clinical trials were initiated by Farr at the Brookhaven National Laboratory (BNL) in New York and by Sweet and Brownell at the Massachusetts General Hospital (MGH) using the Massachusetts Institute of Technology (MIT) nuclear reactor (MITR) and several different low molecular weight boron compounds as the boron delivery agent. However, the results of these studies were disappointing, and no further clinical trials were carried out in the United States until the 1990s. Following a two-year Fulbright fellowship in Sweet's laboratory at the MGH, clinical studies were initiated by Hiroshi Hatanaka in Japan in 1967. He used a low-energy thermal neutron beam, which had low tissue penetrating properties, and sodium borocaptate (BSH) as the boron delivery agent, which had been evaluated as a boron delivery agent by Albert Soloway at the MGH. In Hatanaka's procedure, as much as possible of the tumor was surgically resected ("debulking"), and at some time thereafter, BSH was administered by a slow infusion, usually intra-arterially, but later intravenously. Twelve to 14 hours later, BNCT was carried out at one or another of several different nuclear reactors using low-energy thermal neutron beams. The poor tissue-penetrating properties of the thermal neutron beams necessitated reflecting the skin and raising a bone flap in order to directly irradiate the exposed brain, a procedure first used by Sweet and his collaborators. Approximately 200+ patients were treated by Hatanaka, and subsequently by his associate, Nakagawa. Due to the heterogeneity of the patient population, in terms of the microscopic diagnosis of the tumor and its grade, size, and the
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ability of the patients to carry out normal daily activities (Karnofsky performance status), it was not possible to come up with definitive conclusions about therapeutic efficacy. However, the survival data were no worse than those obtained by standard therapy at the time, and there were several patients who were long-term survivors, and most probably they were cured of their brain tumors. === Further clinical studies in the United States and Japan === ==== USA (2003) ==== BNCT of patients with brain tumors was resumed in the United States in the mid-1990s by Chanana, Diaz, and Coderre and their co-workers at the Brookhaven National Laboratory using the Brookhaven Medical Research Reactor (BMRR) and at Harvard/Massachusetts Institute of Technology (MIT) using the MIT Research Reactor (MITR). For the first time, BPA was used as the boron delivery agent, and patients were irradiated with a collimated beam of higher energy epithermal neutrons, which had greater tissue-penetrating properties than thermal neutrons. A research group headed up by Zamenhof at the Beth Israel Deaconess Medical Center/Harvard Medical School and MIT was the first to use an epithermal neutron beam for clinical trials. Initially patients with cutaneous melanomas were treated and this was expanded to include patients with brain tumors, specifically melanoma metastatic to the brain and primary glioblastomas (GBMs). Included in the research team were Otto Harling at MIT and the Radiation Oncologist Paul Busse at the Beth Israel Deaconess Medical Center in Boston. A total of 22 patients were treated by the Harvard-MIT research group. Five patients with cutaneous melanomas were also treated using an epithermal neutron beam at the MIT research reactor (MITR-II) and subsequently patients with brain tumors were treated using a redesigned beam at the MIT reactor that possessed far superior characteristics to the original MITR-II beam and BPA as the
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capture agent. The clinical outcome of the cases treated at Harvard-MIT has been summarized by Busse. Although the treatment was well tolerated, there were no significant differences in the mean survival times (MSTs)of patients that had received BNCT compared to those who received conventional external beam X-irradiation. ==== Japan (2009) / Glioblastomas ==== Shin-ichi Miyatake and Shinji Kawabata at Osaka Medical College in Japan have carried out extensive clinical studies employing BPA (500 mg/kg) either alone or in combination with BSH (100 mg/kg), infused intravenously (i.v.) over 2 h, followed by neutron irradiation at Kyoto University Research Reactor Institute (KURRI) on patients with newly diagnosed and recurrent glioblastomas. The Mean Survival Time (MST) of 10 patients with recurrent high grade gliomas in the first of their trials was 15.6 months, with one long-term survivor (>5 years). Based on experimental animal data, which showed that BNCT in combination with X-irradiation produced enhanced survival compared to BNCT alone, in another study, Miyatake and Kawabata combined BNCT, as described above, with an X-ray boost. A total dose of 20 to 30 Gy was administered, divided into 2 Gy daily fractions. The MST of this group of patients (with newly diagnosed glioblastomas) was 23.5 months and no significant toxicity was observed, other than hair loss (alopecia). However, a significant subset of these patients, a high proportion of which had small cell variant glioblastomas, developed cerebrospinal fluid dissemination of their tumors. ==== Japan (2011) / Glioblastomas ==== In another Japanese trial with patients with newly diagnosed glioblastomas, carried out by Yamamoto et al., BPA and BSH were infused over 1 h, followed by BNCT at the Japan Research Reactor (JRR)-4 reactor. Patients subsequently received an X-ray boost after completion of BNCT. The overall median survival time (MeST) was 27.1 months, and the 1 year and
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2-year survival rates were 87.5 and 62.5%, respectively. Based on the reports of Miyatake, Kawabata, and Yamamoto, combining BNCT with an X-ray boost can produce a significant therapeutic gain. However, further studies are needed to optimize this combined therapy alone or in combination with other approaches including chemo- and immunotherapy, and to evaluate it using a larger patient population. ==== Japan (2021) / Meningiomas ==== Miyatake and his co-workers also have treated a cohort of 44 patients with recurrent high grade meningiomas (HGM) that were refractory to all other therapeutic approaches. The clinical regimen consisted of intravenous administration of boronophenylalanine two hours before neutron irradiation at the Kyoto University Research Reactor Institute in Kumatori, Japan. Effectiveness was determined using radiographic evidence of tumor shrinkage, overall survival (OS) after initial diagnosis, OS after BNCT, and radiographic patterns associated with treatment failure. The median OS after BNCT was 29.6 months and 98.4 months after diagnosis. Better responses were seen in patients with lower grade tumors. In 35 of 36 patients, there was tumor shrinkage, and the median progression-free survival (PFS) was 13.7 months. There was good local control of the patients' tumors, as evidenced by the fact that only 22.2% of them experienced local recurrence of their tumors. From these results, it was concluded that BNCT was effective in locally controlling tumor growth, shrinking tumors, and improving survival with acceptable safety in patients with therapeutically refractory HGMs. === Clinical studies in Finland === The technological and physical aspects of the Finnish BNCT program have been described in considerable detail by Savolainen et al. A team of clinicians led by Heikki Joensuu and Leena Kankaanranta and nuclear engineers led by Iro Auterinen and Hanna Koivunoro at the Helsinki University Central Hospital and VTT Technical Research Center of Finland have treated approximately 200+ patients
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with recurrent malignant gliomas (glioblastomas) and head and neck cancer who had undergone standard therapy, recurred, and subsequently received BNCT at the time of their recurrence using BPA as the boron delivery agent. The median time to progression in patients with gliomas was 3 months, and the overall MeST was 7 months. It is difficult to compare these results with other reported results in patients with recurrent malignant gliomas, but they are a starting point for future studies using BNCT as salvage therapy in patients with recurrent tumors. Due to a variety of reasons, including financial, no further studies have been carried out at this facility, which has been decommissioned. However, a new facility for BNCT treatment has been installed using an accelerator designed and fabricated by Neutron Therapeutics. This accelerator was specifically designed to be used in a hospital, and the BNCT treatment and clinical studies will be carried out there after dosimetric studies have been completed in 2021. Both Finnish and foreign patients are expected to be treated at the facility. === Clinical studies in Sweden === To conclude this section on treating brain tumors with BNCT using reactor neutron sources, a clinical trial that was carried out by Stenstam, Sköld, Capala and their co-workers in Studsvik, Sweden, using an epithermal neutron beam produced by the Studsvik nuclear reactor, which had greater tissue penetration properties than the thermal beams originally used in the United States and Japan, will be briefly summarized. This study differed significantly from all previous clinical trials in that the total amount of BPA administered was increased (900 mg/kg), and it was infused i.v. over 6 hours. This was based on experimental animal studies in glioma bearing rats demonstrating enhanced uptake of BPA by infiltrating tumor cells following a 6-hour infusion. The longer infusion time
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of the BPA was well tolerated by the 30 patients who were enrolled in this study. All were treated with 2 fields, and the average whole brain dose was 3.2–6.1 Gy (weighted), and the minimum dose to the tumor ranged from 15.4 to 54.3 Gy (w). There has been some disagreement among the Swedish investigators regarding the evaluation of the results. Based on incomplete survival data, the MeST was reported as 14.2 months and the time to tumor progression was 5.8 months. However, more careful examination of the complete survival data revealed that the MeST was 17.7 months compared to 15.5 months that has been reported for patients who received standard therapy of surgery, followed by radiotherapy (RT) and the drug temozolomide (TMZ). Furthermore, the frequency of adverse events was lower after BNCT (14%) than after radiation therapy (RT) alone (21%) and both of these were lower than those seen following RT in combination with TMZ. If this improved survival data, obtained using the higher dose of BPA and a 6-hour infusion time, can be confirmed by others, preferably in a randomized clinical trial, it could represent a significant step forward in BNCT of brain tumors, especially if combined with a photon boost. == Clinical Studies of BNCT for extracranial tumors == === Head and neck cancers === The single most important clinical advance over the past 15 years has been the application of BNCT to treat patients with recurrent tumors of the head and neck region who had failed all other therapy. These studies were first initiated by Kato et al. in Japan. and subsequently followed by several other Japanese groups and by Kankaanranta, Joensuu, Auterinen, Koivunoro and their co-workers in Finland. All of these studies employed BPA as the boron delivery agent, usually alone but occasionally in combination
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with BSH. A very heterogeneous group of patients with a variety of histopathologic types of tumors have been treated, the largest number of which had recurrent squamous cell carcinomas. Kato et al. have reported on a series of 26 patients with far-advanced cancer for whom there were no further treatment options. Either BPA + BSH or BPA alone were administered by a 1 or 2 h i.v. infusion, and this was followed by BNCT using an epithermal beam. In this series, there were complete regressions in 12 cases, 10 partial regressions, and progression in 3 cases. The MST was 13.6 months, and the 6-year survival was 24%. Significant treatment related complications ("adverse" events) included transient mucositis, alopecia and, rarely, brain necrosis and osteomyelitis. Kankaanranta et al. have reported their results in a prospective Phase I/II study of 30 patients with inoperable, locally recurrent squamous cell carcinomas of the head and neck region. Patients received either two or, in a few instances, one BNCT treatment using BPA (400 mg/kg), administered i.v. over 2 hours, followed by neutron irradiation. Of 29 evaluated patients, there were 13 complete and 9 partial remissions, with an overall response rate of 76%. The most common adverse event was oral mucositis, oral pain, and fatigue. Based on the clinical results, it was concluded that BNCT was effective for the treatment of inoperable, previously irradiated patients with head and neck cancer. Some responses were durable but progression was common, usually at the site of the previously recurrent tumor. As previously indicated in the section on neutron sources, all clinical studies have ended in Finland, for variety of reasons including economic difficulties of the two companies directly involved, VTT and Boneca. However, clinical studies using an accelerator neutron source designed and fabricated by Neutron Therapeutics and installed at the
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Helsinki University Hospital should be fully functional by 2022. Finally, a group in Taiwan, led by Ling-Wei Wang and his co-workers at the Taipei Veterans General Hospital, have treated 17 patients with locally recurrent head and neck cancers at the Tsing Hua Open-pool Reactor (THOR) of the National Tsing Hua University. Two-year overall survival was 47% and two-year loco-regional control was 28%. Further studies are in progress to further optimize their treatment regimen. === Other types of tumor === ==== Melanoma and extramammary Paget's disease ==== Other extracranial tumors that have been treated with BNCT include malignant melanomas. The original studies were carried out in Japan by the late Yutaka Mishima and his clinical team in the Department of Dermatology at Kobe University using locally injected BPA and a thermal neutron beam. It is important to point out that it was Mishima who first used BPA as a boron delivery agent, and this approach subsequently was extended to other types of tumors based on the experimental animal studies of Coderre et al. at the Brookhaven National Laboratory. Local control was achieved in almost all patients, and some were cured of their melanomas. Patients with melanoma of the head and neck region, vulva, and extramammary Paget's disease of the genital region have been treated by Hiratsuka et al. with promising clinical results. The first clinical trial of BNCT in Argentina for the treatment of melanomas was performed in October 2003 and since then several patients with cutaneous melanomas have been treated as part of a Phase II clinical trial at the RA-6 nuclear reactor in Bariloche. The neutron beam has a mixed thermal-hyperthermal neutron spectrum that can be used to treat superficial tumors. The In-Hospital Neutron Irradiator (IHNI) in Beijing has been used to treat a small number of patients with
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cutaneous melanomas with a complete response of the primary lesion and no evidence of late radiation injury during a 24+-month follow-up period. ==== Colorectal cancer ==== Two patients with colon cancer, which had spread to the liver, have been treated by Zonta and his co-workers at the University of Pavia in Italy. The first was treated in 2001 and the second in mid-2003. The patients received an i.v. infusion of BPA, followed by removal of the liver (hepatectomy), which was irradiated outside of the body (extracorporeal BNCT) and then re-transplanted into the patient. The first patient did remarkably well and survived for over 4 years after treatment, but the second died within a month of cardiac complications. Clearly, this is a very challenging approach for the treatment of hepatic metastases, and it is unlikely that it will ever be widely used. Nevertheless, the good clinical results in the first patient established proof of principle. Finally, Yanagie and his colleagues at Meiji Pharmaceutical University in Japan have treated several patients with recurrent rectal cancer using BNCT. Although no long-term results have been reported, there was evidence of short-term clinical responses. == Accelerators as Neutron Sources == Accelerators now are the primary source of epithermal neutrons for clinical BNCT. The first papers relating to their possible use were published in the 1980s, and, as summarized by Blue and Yanch, this topic became an active area of research in the early 2000s. However, it was the Fukushima nuclear disaster in Japan in 2011 that gave impetus to their development for clinical use. Accelerators also can be used to produce epithermal neutrons. Today several accelerator-based neutron sources (ABNS) are commercially available or under development. Most existing or planned systems use either the lithium-7 reaction, 7Li(p,n)7Be or the beryllium-9 reaction,9Be(p,n)9B, to generate neutrons, though other
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nuclear reactions also have been considered. The lithium-7 reaction requires a proton accelerator with energies between 1.9 and 3.0 MeV, while the beryllium-9 reaction typically uses accelerators with energies between 5 and 30 MeV. Aside from the lower proton energy that the lithium-7 reaction requires, its main benefit is the lower energy of the neutrons produced. This in turn allows the use of smaller moderators, "cleaner" neutron beams, and reduced neutron activation. Benefits of the beryllium-9 reaction include simplified target design and disposal, long target lifetime, and lower required proton beam current. Since the proton beams for BNCT are quite powerful (~20-100 kW), the neutron generating target must incorporate cooling systems capable of removing the heat safely and reliably to protect the target from damage. In the case of the lithium-7, this requirement is especially important due to the low melting point and chemical volatility of the target material. Liquid jets, micro-channels and rotating targets have been employed to solve this problem.Several researchers have proposed the use of liquid lithium-7 targets in which the target material doubles as the coolant. In the case of beryllium-9, "thin" targets, in which the protons come to rest and deposit much of their energy in the cooling fluid, can be employed. Target degradation due to beam exposure ("blistering") is another problem to be solved, either by using layers of materials resistant to blistering or by spreading the protons over a large target area. Since the nuclear reactions yield neutrons with energies ranging from < 100keV to tens of MeV, a Beam Shaping Assembly (BSA) must be used to moderate, filter, reflect and collimate the neutron beam to achieve the desired epithermal energy range, neutron beam size and direction. BSAs are typically composed of a range of materials with desirable nuclear properties for each function.
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A well-designed BSA should maximize neutron yield per proton while minimizing fast neutron, thermal neutron and gamma contamination. It should also produce a sharply delimited and generally forward directed beam enabling flexible positioning of the patient relative to the aperture. One key challenge for an ABNS is the duration of treatment time: depending on the neutron beam intensity, treatments can take up to an hour or more. Therefore, it is desirable to reduce the treatment time both for patient comfort during immobilization and to increase the number of patients that could be treated in a 24-hour period. Increasing the neutron beam intensity for the same proton current by adjusting the BSA is often achieved at the cost of reduced beam quality (higher levels of unwanted fast neutrons or gamma rays in the beam or poor beam collimation). Therefore, increasing the proton current delivered by ABNS BNCT systems remains a key goal of technology development programs. The table below summarizes the existing or planned ABNS installations for clinical use (Updated November, 2024). == Clinical Studies Using Accelerator Neutron Sources == Treatment of Recurrent Malignant Gliomas The single greatest advance in moving BNCT forward clinically has been the introduction of cyclotron-based neutron sources (c-BNS) in Japan. Shin-ichi Miyatake and Shinji Kawabata have led the way with the treatment of patients with recurrent glioblastomas (GBMs). In their Phase II clinical trial, they used the Sumitomo Heavy Industries accelerator at the Osaka Medical College, Kansai BNCT Medical Center to treat a total of 24 patients. These patients ranged in age from 20 to 75 years, and all previously had received standard treatment consisting of surgery followed by chemotherapy with temozolomide (TMZ) and conventional radiation therapy. They were candidates for treatment with BNCT because their tumors had recurred and were progressing in size. They received
|
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an intravenous infusion of a proprietary formulation of 10B-enriched boronophenylalanine ("Borofalan," StellaPharma Corporation, Osaka, Japan) prior to neutron irradiation. The primary endpoint of this study was the 1-year survival rate after BNCT, which was 79.2%, and the median overall survival rate was 18.9 months. Based on these results, it was concluded that c-BNS BNCT was safe and resulted in increased survival of patients with recurrent gliomas. Although there was an increased risk of brain edema due to re-irradiation, this was easily controlled. As a result of this trial, the Sumitomo accelerator was approved by the Japanese regulatory authority having jurisdiction over medical devices, and further studies are being carried out with patients who have recurrent, high-grade (malignant) meningiomas. However, further studies for the treatment of patients with GBMs have been put on hold pending additional analysis of the results. Treatment of Recurrent or Locally Advanced Cancers of the Head and Neck Katsumi Hirose and his co-workers at the Southern Tohoku BNCT Research Center in Koriyama, Japan, recently have reported on their results after treating 21 patients with recurrent tumors of the head and neck region. All of these patients had received surgery, chemotherapy, and conventional radiation therapy. Eight of them had recurrent squamous cell carcinomas (R-SCC), and 13 had either recurrent (R) or locally advanced (LA) non-squamous cell carcinomas (nSCC). The overall response rate was 71%, and the complete response and partial response rates were 50% and 25%, respectively, for patients with R-SCC and 80% and 62%, respectively, for those with R or LA SCC. The overall 2-year survival rates for patients with R-SCC or R/LA nSCC were 58% and 100%, respectively. The treatment was well tolerated, and adverse events were those usually associated with conventional radiation treatment of these tumors. These patients had received a proprietary formulation of 10B-enriched
|
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boronophenylalanine (Borofalan), which was administered intravenously. Although the manufacturer of the accelerator was not identified, it presumably was the one manufactured by Sumitomo Heavy Industries, Ltd., which was indicated in the Acknowledgements of their report. Based on this Phase II clinical trial, the authors suggested that BNCT using Borofalan and c-BENS was a promising treatment for recurrent head and neck cancers, although further studies would be required to firmly establish this. == The Future == Clinical BNCT first was used to treat highly malignant brain tumors and subsequently for melanomas of the skin that were difficult to treat by surgery. Later, it was used as a type of "salvage" therapy for patients with recurrent tumors of the head and neck region. The clinical results were sufficiently promising to lead to the development of accelerator neutron sources, which will be used almost exclusively in the future. Challenges for the future clinical success of BNCT that need to be met include the following: Optimizing the dosing and delivery paradigms and administration of BPA and BSH. The development of more tumor-selective boron delivery agents for BNCT and their evaluation in large animals and ultimately in humans. Accurate, real time dosimetry to better estimate the radiation doses delivered to the tumor and normal tissues in patients with brain tumors and head and neck cancer. Further clinical evaluation of accelerator-based neutron sources for the treatment of brain tumors, head and neck cancer, and other malignancies. Reducing the cost. == See also == Particle therapy, Neutrons, protons, or heavy ions (e.g. carbon) Fast neutron therapy Proton therapy == References == == External links == Boron and Gadolinium Neutron Capture Therapy for Cancer Treatment Destroying Cancer with Boron and Neutrons - Medical Frontiers - NHK February 21, 2022
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RNA velocity is based on bridging measurements to an underlying mechanism, mRNA splicing, with two modes indicating the current and future state. It is a method used to predict the future gene expression of a cell based on the measurement of both spliced and unspliced transcripts of mRNA. RNA velocity could be used to infer the direction of gene expression changes in single-cell RNA sequencing (scRNA-seq) data. It provides insights into the future state of individual cells by using the abundance of unspliced to spliced RNA transcripts. This ratio can indicate the transcriptional dynamics and potential fate of a cell, such as whether it is transitioning from one cell type to another or undergoing differentiation. == Software usage == There are several software tools available for RNA velocity analysis.Each of these tools has its own strengths and applications, so the choice of tool would depend on the specific requirements of your analysis: === velocyto === Velocyto is a package for the analysis of expression dynamics in single cell RNA seq data. In particular, it enables estimations of RNA velocities of single cells by distinguishing unspliced and spliced mRNAs in standard single-cell RNA sequencing protocols. It is the first paper proposed the concept of RNA velocity. velocyto predicted RNA velocity by solving the proposed differential equations for each gene. The authors envision future manifold learning algorithms that simultaneously fit a manifold and the kinetics on that manifold, on the basis of RNA velocity. === scVelo === scVelo is a method that solves the full transcriptional dynamics of splicing kinetics using a likelihood-based dynamical model. This generalizes RNA velocity to systems with transient cell states, which are common in development and in response to perturbations. scVelo was applied to disentangling subpopulation kinetics in neurogenesis and pancreatic endocrinogenesis. scVelo demonstrate the capabilities of
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"page_id": 73793820,
"source": null,
"title": "RNA velocity"
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the dynamical model on various cell lineages in hippocampal dentate gyrus neurogenesis and pancreatic endocrinogenesis. === cellDancer === cellDancer is a scalable deep neural network that locally infers velocity for each cell from its neighbors and then relays a series of local velocities to provide single-cell resolution inference of velocity kinetics. cellDancer improved the extisting hypothesis of kinetic rates of velocyto and scVelo, transcription rate was either a constant (velocyto model) or binary values (scVelo model), splicing and degradation rates were shared by all the genes and cells, which may have unpredictable performance, while cellDancer can predict the specific transcription, splicing and degradation rates of each gene in each cell through deep learning. === MultiVelo === MultiVelo is a differential equation model of gene expression that extends the RNA velocity framework to incorporate epigenomic data. MultiVelo uses a probabilistic latent variable model to estimate the switch time and rate parameters of chromatin accessibility and gene expression . === DeepVelo === DeepVelo is a neural network–based ordinary differential equation that can model complex transcriptome dynamics by describing continuous-time gene expression changes within individual cells. DeepVelo has been applied to public datasets from different sequencing platforms to (i) formulate transcriptome dynamics on different time scales, (ii) measure the instability of cell states, and (iii) identify developmental driver genes via perturbation analysis. === UnitVelo === UnitVelo is a statistical framework of RNA velocity that models the dynamics of spliced and unspliced RNAs via flexible transcription activities. UnitVelo supports the inference of a unified latent time across the transcriptome. == References ==
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{
"page_id": 73793820,
"source": null,
"title": "RNA velocity"
}
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A selenonic acid is an organoselenium compound containing the −SeO3H functional group. The formula of selenonic acids is R−Se(=O)2−OH, where R is organyl group. Selenonic acids are the selenium analogs of sulfonic acids. Examples of the acid are rare. Benzeneselenonic acid PhSeO3H (where Ph stands for phenyl) is a white solid. It can be prepared by the oxidation of benzeneselenol. == See also == Selenenic acid Seleninic acid == References ==
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{
"page_id": 11665692,
"source": null,
"title": "Selenonic acid"
}
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The molecular formula C9H15NO2 (molar mass: 169.22 g/mol) may refer to: Aceclidine, a parasympathomimetic miotic agent used in the treatment of narrow angle glaucoma Piperidione, a sedative drug
|
{
"page_id": 23920927,
"source": null,
"title": "C9H15NO2"
}
|
The molecular formula C5H7NO2 may refer to: Ethyl cyanoacetate Piperidinediones 2,3-Piperidinedione 2,4-Piperidinedione 2,5-Piperidinedione 2,6-Piperidinedione 3,4-Piperidinedione 3,5-Piperidinedione 1-Pyrroline-5-carboxylic acid
|
{
"page_id": 23920929,
"source": null,
"title": "C5H7NO2"
}
|
The molecular formula C34H22O22 (molar mass: 782.52 g/mol, exact mass: 782.060272 u) may refer to: Punicalin, an ellagitannin found in pomegranates 4,6-isoterchébuloyl-D-glucose, an ellagitannin found in Terminalia macroptera
|
{
"page_id": 35324195,
"source": null,
"title": "C34H22O22"
}
|
The molecular formula C4H10O2S2 (molar mass: 154.25 g/mol, exact mass: 154.0122 u) may refer to: Dithioerythritol (DTE) Dithiothreitol (DTT)
|
{
"page_id": 23986469,
"source": null,
"title": "C4H10O2S2"
}
|
Gates of Heaven is a 1978 American independent documentary film produced, directed, and edited by Errol Morris about the pet cemetery business. It was made when Morris was unknown and did much to launch his career. == Production == After a trip to Florida where he tried and failed to make a film about the residents of the town of Vernon, Errol Morris read a San Francisco Chronicle article with the headline: "450 Dead Pets Going to Napa Valley." This story about dead pets being exhumed from one pet cemetery and reburied in another became the basis for Gates of Heaven. For financing Morris borrowed money from family and friends, and the film was shot throughout the spring and summer of 1977, with the total budget estimated at $125,000. Production was difficult at times, with Morris frequently clashing with his cinematographer over the film's visual style. Morris ultimately ended up firing three cinematographers before finally settling on Ned Burgess, with whom he would work again on his second film Vernon, Florida. Morris had a falling out with his sound-woman when one of his subjects, Florence Rasmussen, said "Here today, gone tomorrow, right?" and she said "Wrong." Morris couldn't decide which had offended him more, that his sound-woman had interrupted Rasmussen or that she had said she was "Wrong." == Release == Gates of Heaven had its premiere at the 1978 New York Film Festival, and would play at various other festivals around the world before being picked up for a limited theatrical run by New Yorker Films in 1981. == Synopsis == The film, like Morris's other works, is unnarrated and the stories are told purely through interviews. It is divided into two main sections. The first concerns Floyd "Mac" McClure and his lifelong quest to allow pets to have
|
{
"page_id": 1311015,
"source": null,
"title": "Gates of Heaven"
}
|
a graceful burial. McClure's business associates and his competitor, a manager of a rendering plant, are interviewed. Morris reveals that McClure's business has failed. Dividing the two sections is an interview with Florence Rasmussen, an elderly woman whose home overlooked the cemetery. After this, Morris follows the 450 dead pets to the Bubbling Well Pet Memorial Park. This operation is run by John "Cal" Harberts and his two sons, Dan and Phil. This business is far more successful, and continues to operate today, run by Cal's son Dan Harberts. Throughout the film, the speakers touch on philosophical themes, as when McClure says "Death is for the living and not for the dead so much" or a grieving pet owner says "There's your dog, your dog's dead. But where's the thing that made it move? It had to be something, didn't it?" == Reception and legacy == Noted director Werner Herzog pledged that he would eat the shoe he was wearing if Morris's film on this improbable subject was completed and shown in a public theater. When the film was released, Herzog lived up to his wager and the consumption of his footwear was made into the short film Werner Herzog Eats His Shoe. At a seminar at the Telluride Film Festival, Herzog praised Gates of Heaven as "a very, very fine film, and it was made with no money, only guts." Morris recalls showing a rough cut of the movie to Wim Wenders, who called it a masterpiece. It also aired as an episode of P.O.V. In an interview on the Criterion DVD, Morris recalls that he showed Gates of Heaven to Douglas Sirk at the Berlin Film Festival. Sirk warned Morris that "There's a danger that somebody might find this movie to be ironic." People are often unsure of
|
{
"page_id": 1311015,
"source": null,
"title": "Gates of Heaven"
}
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the film's tone: is it sincere or satirical? Morris says he "loves the absurd" and that "to love the absurdity of people is not to ridicule them, it's to embrace, on some level, how desperate life is for each and every one of us, including me." Gates of Heaven launched Morris's career and is now considered a classic. In 1991, film critic Roger Ebert named it one of the ten best films ever made in his list for the Sight & Sound poll. Ebert's television partner Gene Siskel shared his enthusiasm for the film. Ebert wrote that the film is an "underground legend," and in 1997 put it in his list of The Great Movies. Ebert wrote that Gates of Heaven "is surrounded by layer upon layer of comedy, pathos, irony, and human nature. I have seen this film perhaps 30 times, and am still not anywhere near the bottom of it: All I know is, it's about a lot more than pet cemeteries." == Home media == The film was initially released on DVD by MGM in 2005. In 2015 The Criterion Collection made it available as part of a new special edition DVD and Blu-Ray that also included Morris's second film Vernon, Florida. == References == == External links == Gates of Heaven from ErrolMorris.com Gates of Heaven at IMDb Gates of Heaven at Rotten Tomatoes Bubbling Well Pet Memorial Park. Gates of Heaven and Vernon, Florida: Bullshitting a Bullshitter an essay by Eric Hynes at the Criterion Collection POV trailer of Gates of Heaven on PBS
|
{
"page_id": 1311015,
"source": null,
"title": "Gates of Heaven"
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Permutationally invariant quantum state tomography (PI quantum state tomography) is a method for the partial determination of the state of a quantum system consisting of many subsystems. In general, the number of parameters needed to describe the quantum mechanical state of a system consisting of N {\displaystyle N} subsystems is increasing exponentially with N . {\displaystyle N.} For instance, for an N {\displaystyle N} -qubit system, 2 ( N + 1 ) − 2 {\displaystyle 2^{(N+1)}-2} real parameters are needed to describe the state vector of a pure state, or 2 2 N − 1 {\displaystyle 2^{2N}-1} real parameters are needed to describe the density matrix of a mixed state. Quantum state tomography is a method to determine all these parameters from a series of measurements on many independent and identically prepared systems. Thus, in the case of full quantum state tomography, the number of measurements needed scales exponentially with the number of particles or qubits. For large systems, the determination of the entire quantum state is no longer possible in practice and one is interested in methods that determine only a subset of the parameters necessary to characterize the quantum state that still contains important information about the state. Permutationally invariant quantum tomography is such a method. PI quantum tomography only measures ϱ P I , {\displaystyle \varrho _{\rm {PI}},} the permutationally invariant part of the density matrix. For the procedure, it is sufficient to carry out local measurements on the subsystems. If the state is close to being permutationally invariant, which is the case in many practical situations, then ϱ P I {\displaystyle \varrho _{\rm {PI}}} is close to the density matrix of the system. Even if the state is not permutationally invariant, ϱ P I {\displaystyle \varrho _{\rm {PI}}} can still be used for entanglement detection and
|
{
"page_id": 72614183,
"source": null,
"title": "Permutationally invariant quantum state tomography"
}
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computing relevant operator expectations values. Thus, the procedure does not assume the permutationally invariance of the quantum state. The number of independent real parameters of ϱ P I {\displaystyle \varrho _{\rm {PI}}} for N {\displaystyle N} qubits scales as ∼ N 3 . {\displaystyle \sim N^{3}.} The number of local measurement settings scales as ∼ N 2 . {\displaystyle \sim N^{2}.} Thus, permutationally invariant quantum tomography is considered manageable even for large N {\displaystyle N} . In other words, permutationally invariant quantum tomography is considered scalable. The method can be used, for example, for the reconstruction of the density matrices of systems with more than 10 particles, for photonic systems, for trapped cold ions or systems in cold atoms. == The permutationally invariant part of the density matrix == PI state tomography reconstructs the permutationally invariant part of the density matrix, which is defined as the equal mixture of the quantum states obtained after permuting the particles in all the possible ways ϱ P I = 1 N ! ∑ k Π k ϱ Π k † , {\displaystyle \varrho _{\rm {PI}}={\frac {1}{N!}}\sum _{k}\Pi _{k}\varrho \Pi _{k}^{\dagger },} where Π k {\displaystyle \Pi _{k}} denotes the kth permutation. For instance, for N = 2 {\displaystyle N=2} we have two permutations. Π 1 {\displaystyle \Pi _{1}} leaves the order of the two particles unchanged. Π 2 {\displaystyle \Pi _{2}} exchanges the two particles. In general, for N {\displaystyle N} particles, we have N ! {\displaystyle N!} permutations. It is easy to see that ϱ P I {\displaystyle \varrho _{\rm {PI}}} is the density matrix that is obtained if the order of the particles is not taken into account. This corresponds to an experiment in which a subset of N {\displaystyle N} particles is randomly selected from a larger ensemble. The state
|
{
"page_id": 72614183,
"source": null,
"title": "Permutationally invariant quantum state tomography"
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of this smaller group is of course permutationally invariant. The number of degrees of freedom of ϱ P I {\displaystyle \varrho _{\rm {PI}}} scales polynomially with the number of particles. For a system of N {\displaystyle N} qubits (spin- 1 / 2 {\displaystyle 1/2} particles) the number of real degrees of freedom is ( N + 3 N ) − 1 = 1 6 ( N 3 + 6 N 2 + 11 N ) . {\displaystyle {\binom {N+3}{N}}-1={\frac {1}{6}}(N^{3}+6N^{2}+11N).} == The measurements needed to determine the permutationally invariant part of the density matrix == To determine these degrees of freedom, ( N + 2 N ) = ( N + 2 ) ( N + 1 ) 2 = 1 2 ( N 2 + 3 N + 2 ) {\displaystyle {\binom {N+2}{N}}={\frac {(N+2)(N+1)}{2}}={\frac {1}{2}}(N^{2}+3N+2)} local measurement settings are needed. Here, a local measurement settings means that the operator A j {\displaystyle A_{j}} is to be measured on each particle. By repeating the measurement and collecting enough data, all two-point, three-point and higher order correlations can be determined. == Efficient determination of a physical state == So far we have discussed that the number of measurements scales polynomially with the number of qubits. However, for using the method in practice, the entire tomographic procedure must be scalable. Thus, we need to store the state in the computer in a scalable way. Clearly, the straightforward way of storing the N {\displaystyle N} -qubit state in a 2 N × 2 N {\displaystyle 2^{N}\times 2^{N}} density matrix is not scalable. However, ϱ P I {\displaystyle \varrho _{\rm {PI}}} is a blockdiagonal matrix due to its permutational invariance and thus it can be stored much more efficiently. Moreover, it is well known that due to statistical fluctuations and systematic errors the density
|
{
"page_id": 72614183,
"source": null,
"title": "Permutationally invariant quantum state tomography"
}
|
matrix obtained from the measured state by linear inversion is not positive semidefinite and it has some negative eigenvalues. An important step in a typical tomography is fitting a physical, i. e., positive semidefinite density matrix on the tomographic data. This step often represents a bottleneck in the overall process in full state tomography. However, PI tomography, as we have just discussed, allows the density matrix to be stored much more efficiently, which also allows an efficient fitting using convex optimization, which also guarantees that the solution is a global optimum. == Characteristics of the method == PI tomography is commonly used in experiments involving permutationally invariant states. If the density matrix ϱ P I {\displaystyle \varrho _{\rm {PI}}} obtained by PI tomography is entangled, then density matrix of the system, ϱ {\displaystyle \varrho } is also entangled. For this reason, the usual methods for entanglement verification, such as entanglement witnesses or the Peres-Horodecki criterion, can be applied to ϱ P I {\displaystyle \varrho _{\rm {PI}}} . Remarkably, the entanglement detection carried out in this way does not assume that the quantum system itself is permutationally invariant. Moreover, the expectation value of any permutaionally invariant operator is the same for ϱ {\displaystyle \varrho } and for ϱ P I . {\displaystyle \varrho _{\rm {PI}}.} Very relevant examples of such operators are projectors to symmetric states, such as the Greenberger–Horne–Zeilinger state, the W state and symmetric Dicke states. Thus, we can obtain the fidelity with respect to the above-mentioned quantum states as the expectation value of the corresponding projectors in the state ϱ P I . {\displaystyle \varrho _{\rm {PI}}.} The quantum fidelity of ϱ P I {\displaystyle \varrho _{\rm {PI}}} and ϱ {\displaystyle \varrho } can be bounded from below as F ( ϱ , ϱ P I ) ≥
|
{
"page_id": 72614183,
"source": null,
"title": "Permutationally invariant quantum state tomography"
}
|
⟨ P s ⟩ ϱ 2 , {\displaystyle F(\varrho ,\varrho _{\rm {PI}})\geq \langle P_{s}\rangle _{\varrho }^{2},} where P s {\displaystyle P_{s}} is the projector to the symmetric subspace. For symmetric states, ⟨ P s ⟩ = 1 {\displaystyle {\langle }P_{s}\rangle =1} holds. This way, we can lower bound the difference knowing only ϱ P I . {\displaystyle \varrho _{\rm {PI}}.} == Links to other approaches == There are other approaches for tomography that need fewer measurements than full quantum state tomography. As we have discussed, PI tomography is typically most useful for quantum states that are close to being permutionally invariant. Compressed sensing is especially suited for low rank states. Matrix product state tomography is most suitable for, e.g., cluster states and ground states of spin models. Permutationally invariant tomography can be combined with compressed sensing. In this case, the number of local measurement settings needed can even be smaller than for permutationally invariant tomography. == Experiments == Permutationally invariant tomography has been tested experimentally for a four-qubit symmetric Dicke state, and also for a six-qubit symmetric Dicke in photons, and has been compared to full state tomography and compressed sensing. A simulation of permutationally invariant tomography shows that reconstruction of a positive semidefinite density matrix of 20 qubits from measured data is possible in a few minutes on a standard computer. The hybrid method combining permutationally invariant tomography and compressed sensing has also been tested. == References ==
|
{
"page_id": 72614183,
"source": null,
"title": "Permutationally invariant quantum state tomography"
}
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In machine learning, feature selection is the process of selecting a subset of relevant features (variables, predictors) for use in model construction. Feature selection techniques are used for several reasons: simplification of models to make them easier to interpret, shorter training times, to avoid the curse of dimensionality, improve the compatibility of the data with a certain learning model class, to encode inherent symmetries present in the input space. The central premise when using feature selection is that data sometimes contains features that are redundant or irrelevant, and can thus be removed without incurring much loss of information. Redundancy and irrelevance are two distinct notions, since one relevant feature may be redundant in the presence of another relevant feature with which it is strongly correlated. Feature extraction creates new features from functions of the original features, whereas feature selection finds a subset of the features. Feature selection techniques are often used in domains where there are many features and comparatively few samples (data points). == Introduction == A feature selection algorithm can be seen as the combination of a search technique for proposing new feature subsets, along with an evaluation measure which scores the different feature subsets. The simplest algorithm is to test each possible subset of features finding the one which minimizes the error rate. This is an exhaustive search of the space, and is computationally intractable for all but the smallest of feature sets. The choice of evaluation metric heavily influences the algorithm, and it is these evaluation metrics which distinguish between the three main categories of feature selection algorithms: wrappers, filters and embedded methods. Wrapper methods use a predictive model to score feature subsets. Each new subset is used to train a model, which is tested on a hold-out set. Counting the number of mistakes made on
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{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
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that hold-out set (the error rate of the model) gives the score for that subset. As wrapper methods train a new model for each subset, they are very computationally intensive, but usually provide the best performing feature set for that particular type of model or typical problem. Filter methods use a proxy measure instead of the error rate to score a feature subset. This measure is chosen to be fast to compute, while still capturing the usefulness of the feature set. Common measures include the mutual information, the pointwise mutual information, Pearson product-moment correlation coefficient, Relief-based algorithms, and inter/intra class distance or the scores of significance tests for each class/feature combinations. Filters are usually less computationally intensive than wrappers, but they produce a feature set which is not tuned to a specific type of predictive model. This lack of tuning means a feature set from a filter is more general than the set from a wrapper, usually giving lower prediction performance than a wrapper. However the feature set doesn't contain the assumptions of a prediction model, and so is more useful for exposing the relationships between the features. Many filters provide a feature ranking rather than an explicit best feature subset, and the cut off point in the ranking is chosen via cross-validation. Filter methods have also been used as a preprocessing step for wrapper methods, allowing a wrapper to be used on larger problems. One other popular approach is the Recursive Feature Elimination algorithm, commonly used with Support Vector Machines to repeatedly construct a model and remove features with low weights. Embedded methods are a catch-all group of techniques which perform feature selection as part of the model construction process. The exemplar of this approach is the LASSO method for constructing a linear model, which penalizes the regression coefficients
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{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
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with an L1 penalty, shrinking many of them to zero. Any features which have non-zero regression coefficients are 'selected' by the LASSO algorithm. Improvements to the LASSO include Bolasso which bootstraps samples; Elastic net regularization, which combines the L1 penalty of LASSO with the L2 penalty of ridge regression; and FeaLect which scores all the features based on combinatorial analysis of regression coefficients. AEFS further extends LASSO to nonlinear scenario with autoencoders. These approaches tend to be between filters and wrappers in terms of computational complexity. In traditional regression analysis, the most popular form of feature selection is stepwise regression, which is a wrapper technique. It is a greedy algorithm that adds the best feature (or deletes the worst feature) at each round. The main control issue is deciding when to stop the algorithm. In machine learning, this is typically done by cross-validation. In statistics, some criteria are optimized. This leads to the inherent problem of nesting. More robust methods have been explored, such as branch and bound and piecewise linear network. == Subset selection == Subset selection evaluates a subset of features as a group for suitability. Subset selection algorithms can be broken up into wrappers, filters, and embedded methods. Wrappers use a search algorithm to search through the space of possible features and evaluate each subset by running a model on the subset. Wrappers can be computationally expensive and have a risk of over fitting to the model. Filters are similar to wrappers in the search approach, but instead of evaluating against a model, a simpler filter is evaluated. Embedded techniques are embedded in, and specific to, a model. Many popular search approaches use greedy hill climbing, which iteratively evaluates a candidate subset of features, then modifies the subset and evaluates if the new subset is an improvement
|
{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
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over the old. Evaluation of the subsets requires a scoring metric that grades a subset of features. Exhaustive search is generally impractical, so at some implementor (or operator) defined stopping point, the subset of features with the highest score discovered up to that point is selected as the satisfactory feature subset. The stopping criterion varies by algorithm; possible criteria include: a subset score exceeds a threshold, a program's maximum allowed run time has been surpassed, etc. Alternative search-based techniques are based on targeted projection pursuit which finds low-dimensional projections of the data that score highly: the features that have the largest projections in the lower-dimensional space are then selected. Search approaches include: Exhaustive Best first Simulated annealing Genetic algorithm Greedy forward selection Greedy backward elimination Particle swarm optimization Targeted projection pursuit Scatter search Variable neighborhood search Two popular filter metrics for classification problems are correlation and mutual information, although neither are true metrics or 'distance measures' in the mathematical sense, since they fail to obey the triangle inequality and thus do not compute any actual 'distance' – they should rather be regarded as 'scores'. These scores are computed between a candidate feature (or set of features) and the desired output category. There are, however, true metrics that are a simple function of the mutual information; see here. Other available filter metrics include: Class separability Error probability Inter-class distance Probabilistic distance Entropy Consistency-based feature selection Correlation-based feature selection == Optimality criteria == The choice of optimality criteria is difficult as there are multiple objectives in a feature selection task. Many common criteria incorporate a measure of accuracy, penalised by the number of features selected. Examples include Akaike information criterion (AIC) and Mallows's Cp, which have a penalty of 2 for each added feature. AIC is based on information theory, and is
|
{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
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effectively derived via the maximum entropy principle. Other criteria are Bayesian information criterion (BIC), which uses a penalty of log n {\displaystyle {\sqrt {\log {n}}}} for each added feature, minimum description length (MDL) which asymptotically uses log n {\displaystyle {\sqrt {\log {n}}}} , Bonferroni / RIC which use 2 log p {\displaystyle {\sqrt {2\log {p}}}} , maximum dependency feature selection, and a variety of new criteria that are motivated by false discovery rate (FDR), which use something close to 2 log p q {\displaystyle {\sqrt {2\log {\frac {p}{q}}}}} . A maximum entropy rate criterion may also be used to select the most relevant subset of features. == Structure learning == Filter feature selection is a specific case of a more general paradigm called structure learning. Feature selection finds the relevant feature set for a specific target variable whereas structure learning finds the relationships between all the variables, usually by expressing these relationships as a graph. The most common structure learning algorithms assume the data is generated by a Bayesian Network, and so the structure is a directed graphical model. The optimal solution to the filter feature selection problem is the Markov blanket of the target node, and in a Bayesian Network, there is a unique Markov Blanket for each node. == Information Theory Based Feature Selection Mechanisms == There are different Feature Selection mechanisms around that utilize mutual information for scoring the different features. They usually use all the same algorithm: Calculate the mutual information as score for between all features ( f i ∈ F {\displaystyle f_{i}\in F} ) and the target class (c) Select the feature with the largest score (e.g. argmax f i ∈ F ( I ( f i , c ) ) {\displaystyle {\underset {f_{i}\in F}{\operatorname {argmax} }}(I(f_{i},c))} ) and add
|
{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
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it to the set of selected features (S) Calculate the score which might be derived from the mutual information Select the feature with the largest score and add it to the set of select features (e.g. argmax f i ∈ F ( I d e r i v e d ( f i , c ) ) {\displaystyle {\underset {f_{i}\in F}{\operatorname {argmax} }}(I_{derived}(f_{i},c))} ) Repeat 3. and 4. until a certain number of features is selected (e.g. | S | = l {\displaystyle |S|=l} ) The simplest approach uses the mutual information as the "derived" score. However, there are different approaches, that try to reduce the redundancy between features. === Minimum-redundancy-maximum-relevance (mRMR) feature selection === Peng et al. proposed a feature selection method that can use either mutual information, correlation, or distance/similarity scores to select features. The aim is to penalise a feature's relevancy by its redundancy in the presence of the other selected features. The relevance of a feature set S for the class c is defined by the average value of all mutual information values between the individual feature fi and the class c as follows: D ( S , c ) = 1 | S | ∑ f i ∈ S I ( f i ; c ) {\displaystyle D(S,c)={\frac {1}{|S|}}\sum _{f_{i}\in S}I(f_{i};c)} . The redundancy of all features in the set S is the average value of all mutual information values between the feature fi and the feature fj: R ( S ) = 1 | S | 2 ∑ f i , f j ∈ S I ( f i ; f j ) {\displaystyle R(S)={\frac {1}{|S|^{2}}}\sum _{f_{i},f_{j}\in S}I(f_{i};f_{j})} The mRMR criterion is a combination of two measures given above and is defined as follows: m R M R = max S [ 1 |
|
{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
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S | ∑ f i ∈ S I ( f i ; c ) − 1 | S | 2 ∑ f i , f j ∈ S I ( f i ; f j ) ] . {\displaystyle \mathrm {mRMR} =\max _{S}\left[{\frac {1}{|S|}}\sum _{f_{i}\in S}I(f_{i};c)-{\frac {1}{|S|^{2}}}\sum _{f_{i},f_{j}\in S}I(f_{i};f_{j})\right].} Suppose that there are n full-set features. Let xi be the set membership indicator function for feature fi, so that xi=1 indicates presence and xi=0 indicates absence of the feature fi in the globally optimal feature set. Let c i = I ( f i ; c ) {\displaystyle c_{i}=I(f_{i};c)} and a i j = I ( f i ; f j ) {\displaystyle a_{ij}=I(f_{i};f_{j})} . The above may then be written as an optimization problem: m R M R = max x ∈ { 0 , 1 } n [ ∑ i = 1 n c i x i ∑ i = 1 n x i − ∑ i , j = 1 n a i j x i x j ( ∑ i = 1 n x i ) 2 ] . {\displaystyle \mathrm {mRMR} =\max _{x\in \{0,1\}^{n}}\left[{\frac {\sum _{i=1}^{n}c_{i}x_{i}}{\sum _{i=1}^{n}x_{i}}}-{\frac {\sum _{i,j=1}^{n}a_{ij}x_{i}x_{j}}{(\sum _{i=1}^{n}x_{i})^{2}}}\right].} The mRMR algorithm is an approximation of the theoretically optimal maximum-dependency feature selection algorithm that maximizes the mutual information between the joint distribution of the selected features and the classification variable. As mRMR approximates the combinatorial estimation problem with a series of much smaller problems, each of which only involves two variables, it thus uses pairwise joint probabilities which are more robust. In certain situations the algorithm may underestimate the usefulness of features as it has no way to measure interactions between features which can increase relevancy. This can lead to poor performance when the features are individually useless, but are useful when combined (a
|
{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
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pathological case is found when the class is a parity function of the features). Overall the algorithm is more efficient (in terms of the amount of data required) than the theoretically optimal max-dependency selection, yet produces a feature set with little pairwise redundancy. mRMR is an instance of a large class of filter methods which trade off between relevancy and redundancy in different ways. === Quadratic programming feature selection === mRMR is a typical example of an incremental greedy strategy for feature selection: once a feature has been selected, it cannot be deselected at a later stage. While mRMR could be optimized using floating search to reduce some features, it might also be reformulated as a global quadratic programming optimization problem as follows: Q P F S : min x { α x T H x − x T F } s.t. ∑ i = 1 n x i = 1 , x i ≥ 0 {\displaystyle \mathrm {QPFS} :\min _{\mathbf {x} }\left\{\alpha \mathbf {x} ^{T}H\mathbf {x} -\mathbf {x} ^{T}F\right\}\quad {\mbox{s.t.}}\ \sum _{i=1}^{n}x_{i}=1,x_{i}\geq 0} where F n × 1 = [ I ( f 1 ; c ) , … , I ( f n ; c ) ] T {\displaystyle F_{n\times 1}=[I(f_{1};c),\ldots ,I(f_{n};c)]^{T}} is the vector of feature relevancy assuming there are n features in total, H n × n = [ I ( f i ; f j ) ] i , j = 1 … n {\displaystyle H_{n\times n}=[I(f_{i};f_{j})]_{i,j=1\ldots n}} is the matrix of feature pairwise redundancy, and x n × 1 {\displaystyle \mathbf {x} _{n\times 1}} represents relative feature weights. QPFS is solved via quadratic programming. It is recently shown that QFPS is biased towards features with smaller entropy, due to its placement of the feature self redundancy term I ( f i ; f i
|
{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
}
|
) {\displaystyle I(f_{i};f_{i})} on the diagonal of H. === Conditional mutual information === Another score derived for the mutual information is based on the conditional relevancy: S P E C C M I : max x { x T Q x } s.t. ‖ x ‖ = 1 , x i ≥ 0 {\displaystyle \mathrm {SPEC_{CMI}} :\max _{\mathbf {x} }\left\{\mathbf {x} ^{T}Q\mathbf {x} \right\}\quad {\mbox{s.t.}}\ \|\mathbf {x} \|=1,x_{i}\geq 0} where Q i i = I ( f i ; c ) {\displaystyle Q_{ii}=I(f_{i};c)} and Q i j = ( I ( f i ; c | f j ) + I ( f j ; c | f i ) ) / 2 , i ≠ j {\displaystyle Q_{ij}=(I(f_{i};c|f_{j})+I(f_{j};c|f_{i}))/2,i\neq j} . An advantage of SPECCMI is that it can be solved simply via finding the dominant eigenvector of Q, thus is very scalable. SPECCMI also handles second-order feature interaction. === Joint mutual information === In a study of different scores Brown et al. recommended the joint mutual information as a good score for feature selection. The score tries to find the feature, that adds the most new information to the already selected features, in order to avoid redundancy. The score is formulated as follows: J M I ( f i ) = ∑ f j ∈ S ( I ( f i ; c ) + I ( f i ; c | f j ) ) = ∑ f j ∈ S [ I ( f j ; c ) + I ( f i ; c ) − ( I ( f i ; f j ) − I ( f i ; f j | c ) ) ] {\displaystyle {\begin{aligned}JMI(f_{i})&=\sum _{f_{j}\in S}(I(f_{i};c)+I(f_{i};c|f_{j}))\\&=\sum _{f_{j}\in S}{\bigl [}I(f_{j};c)+I(f_{i};c)-{\bigl (}I(f_{i};f_{j})-I(f_{i};f_{j}|c){\bigr )}{\bigr ]}\end{aligned}}} The score uses the conditional mutual information and
|
{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
}
|
the mutual information to estimate the redundancy between the already selected features ( f j ∈ S {\displaystyle f_{j}\in S} ) and the feature under investigation ( f i {\displaystyle f_{i}} ). == Hilbert-Schmidt Independence Criterion Lasso based feature selection == For high-dimensional and small sample data (e.g., dimensionality > 105 and the number of samples < 103), the Hilbert-Schmidt Independence Criterion Lasso (HSIC Lasso) is useful. HSIC Lasso optimization problem is given as H S I C L a s s o : min x 1 2 ∑ k , l = 1 n x k x l HSIC ( f k , f l ) − ∑ k = 1 n x k HSIC ( f k , c ) + λ ‖ x ‖ 1 , s.t. x 1 , … , x n ≥ 0 , {\displaystyle \mathrm {HSIC_{Lasso}} :\min _{\mathbf {x} }{\frac {1}{2}}\sum _{k,l=1}^{n}x_{k}x_{l}{\mbox{HSIC}}(f_{k},f_{l})-\sum _{k=1}^{n}x_{k}{\mbox{HSIC}}(f_{k},c)+\lambda \|\mathbf {x} \|_{1},\quad {\mbox{s.t.}}\ x_{1},\ldots ,x_{n}\geq 0,} where HSIC ( f k , c ) = tr ( K ¯ ( k ) L ¯ ) {\displaystyle {\mbox{HSIC}}(f_{k},c)={\mbox{tr}}({\bar {\mathbf {K} }}^{(k)}{\bar {\mathbf {L} }})} is a kernel-based independence measure called the (empirical) Hilbert-Schmidt independence criterion (HSIC), tr ( ⋅ ) {\displaystyle {\mbox{tr}}(\cdot )} denotes the trace, λ {\displaystyle \lambda } is the regularization parameter, K ¯ ( k ) = Γ K ( k ) Γ {\displaystyle {\bar {\mathbf {K} }}^{(k)}=\mathbf {\Gamma } \mathbf {K} ^{(k)}\mathbf {\Gamma } } and L ¯ = Γ L Γ {\displaystyle {\bar {\mathbf {L} }}=\mathbf {\Gamma } \mathbf {L} \mathbf {\Gamma } } are input and output centered Gram matrices, K i , j ( k ) = K ( u k , i , u k , j ) {\displaystyle K_{i,j}^{(k)}=K(u_{k,i},u_{k,j})} and L i , j = L ( c i , c
|
{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
}
|
j ) {\displaystyle L_{i,j}=L(c_{i},c_{j})} are Gram matrices, K ( u , u ′ ) {\displaystyle K(u,u')} and L ( c , c ′ ) {\displaystyle L(c,c')} are kernel functions, Γ = I m − 1 m 1 m 1 m T {\displaystyle \mathbf {\Gamma } =\mathbf {I} _{m}-{\frac {1}{m}}\mathbf {1} _{m}\mathbf {1} _{m}^{T}} is the centering matrix, I m {\displaystyle \mathbf {I} _{m}} is the m-dimensional identity matrix (m: the number of samples), 1 m {\displaystyle \mathbf {1} _{m}} is the m-dimensional vector with all ones, and ‖ ⋅ ‖ 1 {\displaystyle \|\cdot \|_{1}} is the ℓ 1 {\displaystyle \ell _{1}} -norm. HSIC always takes a non-negative value, and is zero if and only if two random variables are statistically independent when a universal reproducing kernel such as the Gaussian kernel is used. The HSIC Lasso can be written as H S I C L a s s o : min x 1 2 ‖ L ¯ − ∑ k = 1 n x k K ¯ ( k ) ‖ F 2 + λ ‖ x ‖ 1 , s.t. x 1 , … , x n ≥ 0 , {\displaystyle \mathrm {HSIC_{Lasso}} :\min _{\mathbf {x} }{\frac {1}{2}}\left\|{\bar {\mathbf {L} }}-\sum _{k=1}^{n}x_{k}{\bar {\mathbf {K} }}^{(k)}\right\|_{F}^{2}+\lambda \|\mathbf {x} \|_{1},\quad {\mbox{s.t.}}\ x_{1},\ldots ,x_{n}\geq 0,} where ‖ ⋅ ‖ F {\displaystyle \|\cdot \|_{F}} is the Frobenius norm. The optimization problem is a Lasso problem, and thus it can be efficiently solved with a state-of-the-art Lasso solver such as the dual augmented Lagrangian method. == Correlation feature selection == The correlation feature selection (CFS) measure evaluates subsets of features on the basis of the following hypothesis: "Good feature subsets contain features highly correlated with the classification, yet uncorrelated to each other". The following equation gives the merit of a feature subset S consisting
|
{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
}
|
of k features: M e r i t S k = k r c f ¯ k + k ( k − 1 ) r f f ¯ . {\displaystyle \mathrm {Merit} _{S_{k}}={\frac {k{\overline {r_{cf}}}}{\sqrt {k+k(k-1){\overline {r_{ff}}}}}}.} Here, r c f ¯ {\displaystyle {\overline {r_{cf}}}} is the average value of all feature-classification correlations, and r f f ¯ {\displaystyle {\overline {r_{ff}}}} is the average value of all feature-feature correlations. The CFS criterion is defined as follows: C F S = max S k [ r c f 1 + r c f 2 + ⋯ + r c f k k + 2 ( r f 1 f 2 + ⋯ + r f i f j + ⋯ + r f k f k − 1 ) ] . {\displaystyle \mathrm {CFS} =\max _{S_{k}}\left[{\frac {r_{cf_{1}}+r_{cf_{2}}+\cdots +r_{cf_{k}}}{\sqrt {k+2(r_{f_{1}f_{2}}+\cdots +r_{f_{i}f_{j}}+\cdots +r_{f_{k}f_{k-1}})}}}\right].} The r c f i {\displaystyle r_{cf_{i}}} and r f i f j {\displaystyle r_{f_{i}f_{j}}} variables are referred to as correlations, but are not necessarily Pearson's correlation coefficient or Spearman's ρ. Hall's dissertation uses neither of these, but uses three different measures of relatedness, minimum description length (MDL), symmetrical uncertainty, and relief. Let xi be the set membership indicator function for feature fi; then the above can be rewritten as an optimization problem: C F S = max x ∈ { 0 , 1 } n [ ( ∑ i = 1 n a i x i ) 2 ∑ i = 1 n x i + ∑ i ≠ j 2 b i j x i x j ] . {\displaystyle \mathrm {CFS} =\max _{x\in \{0,1\}^{n}}\left[{\frac {(\sum _{i=1}^{n}a_{i}x_{i})^{2}}{\sum _{i=1}^{n}x_{i}+\sum _{i\neq j}2b_{ij}x_{i}x_{j}}}\right].} The combinatorial problems above are, in fact, mixed 0–1 linear programming problems that can be solved by using branch-and-bound algorithms. == Regularized trees == The features from a
|
{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
}
|
decision tree or a tree ensemble are shown to be redundant. A recent method called regularized tree can be used for feature subset selection. Regularized trees penalize using a variable similar to the variables selected at previous tree nodes for splitting the current node. Regularized trees only need build one tree model (or one tree ensemble model) and thus are computationally efficient. Regularized trees naturally handle numerical and categorical features, interactions and nonlinearities. They are invariant to attribute scales (units) and insensitive to outliers, and thus, require little data preprocessing such as normalization. Regularized random forest (RRF) is one type of regularized trees. The guided RRF is an enhanced RRF which is guided by the importance scores from an ordinary random forest. == Overview on metaheuristics methods == A metaheuristic is a general description of an algorithm dedicated to solve difficult (typically NP-hard problem) optimization problems for which there is no classical solving methods. Generally, a metaheuristic is a stochastic algorithm tending to reach a global optimum. There are many metaheuristics, from a simple local search to a complex global search algorithm. === Main principles === The feature selection methods are typically presented in three classes based on how they combine the selection algorithm and the model building. ==== Filter method ==== Filter type methods select variables regardless of the model. They are based only on general features like the correlation with the variable to predict. Filter methods suppress the least interesting variables. The other variables will be part of a classification or a regression model used to classify or to predict data. These methods are particularly effective in computation time and robust to overfitting. Filter methods tend to select redundant variables when they do not consider the relationships between variables. However, more elaborate features try to minimize this problem
|
{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
}
|
by removing variables highly correlated to each other, such as the Fast Correlation Based Filter (FCBF) algorithm. ==== Wrapper method ==== Wrapper methods evaluate subsets of variables which allows, unlike filter approaches, to detect the possible interactions amongst variables. The two main disadvantages of these methods are: The increasing overfitting risk when the number of observations is insufficient. The significant computation time when the number of variables is large. ==== Embedded method ==== Embedded methods have been recently proposed that try to combine the advantages of both previous methods. A learning algorithm takes advantage of its own variable selection process and performs feature selection and classification simultaneously, such as the FRMT algorithm. === Application of feature selection metaheuristics === This is a survey of the application of feature selection metaheuristics lately used in the literature. This survey was realized by J. Hammon in her 2013 thesis. == Feature selection embedded in learning algorithms == Some learning algorithms perform feature selection as part of their overall operation. These include: l 1 {\displaystyle l_{1}} -regularization techniques, such as sparse regression, LASSO, and l 1 {\displaystyle l_{1}} -SVM Regularized trees, e.g. regularized random forest implemented in the RRF package Decision tree Memetic algorithm Random multinomial logit (RMNL) Auto-encoding networks with a bottleneck-layer Submodular feature selection Local learning based feature selection. Compared with traditional methods, it does not involve any heuristic search, can easily handle multi-class problems, and works for both linear and nonlinear problems. It is also supported by a strong theoretical foundation. Numeric experiments showed that the method can achieve a close-to-optimal solution even when data contains >1M irrelevant features. Recommender system based on feature selection. The feature selection methods are introduced into recommender system research. == See also == Cluster analysis Data mining Dimensionality reduction Feature extraction Hyperparameter optimization
|
{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
}
|
Model selection Relief (feature selection) == References == == Further reading == Guyon, Isabelle; Elisseeff, Andre (2003). "An Introduction to Variable and Feature Selection". Journal of Machine Learning Research. 3: 1157–1182. Harrell, F. (2001). Regression Modeling Strategies. Springer. ISBN 0-387-95232-2. Liu, Huan; Motoda, Hiroshi (1998). Feature Selection for Knowledge Discovery and Data Mining. Springer. ISBN 0-7923-8198-X. Liu, Huan; Yu, Lei (2005). "Toward Integrating Feature Selection Algorithms for Classification and Clustering". IEEE Transactions on Knowledge and Data Engineering. 17 (4): 491–502. doi:10.1109/TKDE.2005.66. S2CID 1607600. == External links == Feature Selection Package, Arizona State University (Matlab Code) NIPS challenge 2003 (see also NIPS) Naive Bayes implementation with feature selection in Visual Basic Archived 2009-02-14 at the Wayback Machine (includes executable and source code) Minimum-redundancy-maximum-relevance (mRMR) feature selection program FEAST (Open source Feature Selection algorithms in C and MATLAB)
|
{
"page_id": 1179950,
"source": null,
"title": "Feature selection"
}
|
The NONCODE database is a collection of expression and functional lncRNA data obtained from re-annotated microarray studies. == See also == lncRNA == References == == External links == http://www.noncode.org
|
{
"page_id": 34275630,
"source": null,
"title": "NONCODE"
}
|
An octadecatrienoic acid is a chemical compound with formula C18H30O2, a polyunsaturated fatty acid whose molecule has an 18-carbon unbranched backbone with three double bonds. The name refers to many different structural and configurational isomers, that differ in the position of the double bonds along the backbone and on whether they are in cis (Z) or trans (E) configuration. Some isomers have considerable biological, pharmaceutical, or industrial importance, such as: α-Linolenic acid (9Z,12Z,15Z), found in many cooking oils γ-Linolenic acid (6Z,9Z,12Z), found in the evening primrose (Oenothera biennis) Pinolenic acid (5Z,9Z,12Z), found in the seeds of pines (Pinus species) Columbinic acid (5E,9Z,12Z), found in Thalictrum seed oils α-Eleostearic acid (9Z,11E,13E), the main component of tung oil, produced from the nuts of tung tree (Vernicia fordii) β-Eleostearic acid (9E,11E,13E) Catalpic acid (9E,11E,13Z), found in the seeds of yellow catalpa (Catalpa ovata) and southern catalpa (Catalpa bignonioides) Punicic acid (9Z,11E,13Z), found in pomegranate (Punica granatum) seed oil α-Calendic acid (8E,10E,12Z), found in the pot marigold (Calendula officinalis) β-Calendic acid (8E,10E,12E), found in the pot marigold (Calendula officinalis) in small or trace amounts, less than 2% of total lipids Jacaric acid (8Z,10E,12Z), found in the blue jacaranda (Jacaranda mimosifolia) == References ==
|
{
"page_id": 30212398,
"source": null,
"title": "Octadecatrienoic acid"
}
|
In the fields of chemical graph theory, molecular topology, and mathematical chemistry, a topological index, also known as a connectivity index, is a type of a molecular descriptor that is calculated based on the molecular graph of a chemical compound. Topological indices are numerical parameters of a graph which characterize its topology and are usually graph invariant. Topological indices are used for example in the development of quantitative structure-activity relationships (QSARs) in which the biological activity or other properties of molecules are correlated with their chemical structure. == Calculation == Topological descriptors are derived from hydrogen-suppressed molecular graphs, in which the atoms are represented by vertices and the bonds by edges. The connections between the atoms can be described by various types of topological matrices (e.g., distance or adjacency matrices), which can be mathematically manipulated so as to derive a single number, usually known as graph invariant, graph-theoretical index or topological index. As a result, the topological index can be defined as two-dimensional descriptors that can be easily calculated from the molecular graphs, and do not depend on the way the graph is depicted or labeled and no need of energy minimization of the chemical structure. == Types == The simplest topological indices do not recognize double bonds and atom types (C, N, O etc.) and ignore hydrogen atoms ("hydrogen suppressed") and defined for connected undirected molecular graphs only. More sophisticated topological indices also take into account the hybridization state of each of the atoms contained in the molecule. The Hosoya index is the first topological index recognized in chemical graph theory, and it is often referred to as "the" topological index. Other examples include the Wiener index, Randić's molecular connectivity index, Balaban’s J index, and the TAU descriptors. The extended topochemical atom (ETA) indices have been developed based on
|
{
"page_id": 14221614,
"source": null,
"title": "Topological index"
}
|
refinement of TAU descriptors. === Global and local indices === Hosoya index and Wiener index are global (integral) indices to describe entire molecule, Bonchev and Polansky introduced local (differential) index for every atom in a molecule. Another examples of local indices are modifications of Hosoya index. === Discrimination capability and superindices === A topological index may have the same value for a subset of different molecular graphs, i.e. the index is unable to discriminate the graphs from this subset. The discrimination capability is very important characteristic of topological index. To increase the discrimination capability a few topological indices may be combined to superindex. === Computational complexity === Computational complexity is another important characteristic of topological index. The Wiener index, Randic's molecular connectivity index, Balaban's J index may be calculated by fast algorithms, in contrast to Hosoya index and its modifications for which non-exponential algorithms are unknown. === List of topological indices === Wiener index Hosoya index Hyper-Wiener index Estrada index Randić index Zagreb indices Szeged index Padmakar–Ivan index Gutman index sombor index Harmonic index Arithmetic index Atom bond connectivity index Merrifield-Simmons index == Application == === QSAR === QSARs represent predictive models derived from application of statistical tools correlating biological activity (including desirable therapeutic effect and undesirable side effects) of chemicals (drugs/toxicants/environmental pollutants) with descriptors representative of molecular structure and/or properties. QSARs are being applied in many disciplines for example risk assessment, toxicity prediction, and regulatory decisions in addition to drug discovery and lead optimization. For example, ETA indices have been applied in the development of predictive QSAR/QSPR/QSTR models. == References == == Further reading == == External links == Software for calculating various topological indices: GraphTea.
|
{
"page_id": 14221614,
"source": null,
"title": "Topological index"
}
|
LiMETER stands for light-inducible membrane-tethered peripheral endoplasmic reticulum (ER). LiMETER is an optogenetics tool designed to reversibly label cortical ER or the apposition between plasma membrane (PM) and endoplasmic reticulum (ER) membranes (termed as ER-PM junctions). == Design == The ER luminal domain of LiMETER contains a signal peptide and the transmembrane domain derived from STIM1, with GFP placed in between as a reporter. STIM1 is an ER-resident calcium sensor protein responsible for sensing calcium changes in internal calcium stores and communicate with ORAI calcium channels in the plasma membrane. The cytoplasmic region of LiMETER contains a flexible linker and a genetically encoded lightswitch LOV2 domain (light oxygen voltage-sensing domain, residues 404–546) derived from Avena sativa phototropin 1, followed by a C-terminal PM-targeting polybasic tail that associates with negative charged phosphoinositides in the inner half of the leaflet of plasma membrane. == Function == In the dark, the Jα helix docks to the LOV2 domain and cages the polybasic tail to prevent its interaction with negatively charged PM-resident phosphoinositides. Following blue light illumination, photoexcitation generates a covalent adduct between a cysteine residue and the flavin cofactor in LOV2, and subsequently promotes the undocking and unwinding of the Jα helix, thereby exposing the polybasic C-tail to enable translocation of the protein towards PM to form puncta-like structures. As a result, LiMETER undergoes photo-inducible translocation toward ER–PM junctions to specifically label cER. This process can be reversibly repeated with multiple light–dark cycles without significant loss in the magnitude of response. This optical tool enables cell biologists to quantitatively examine the effect of regulators that modulate the dynamics of cER accumulation at defined spatiotemporal resolution in living cells. == References ==
|
{
"page_id": 47907122,
"source": null,
"title": "LiMETER"
}
|
During pregnancy changes in the placenta involve the disappearance of the greater portion of the stratum compactum, but the deeper part of this layer persists and is condensed to form what is known as the basal plate. Between this plate and the uterine muscular fibres are the stratum spongiosum and the boundary layer; through these and the basal plate the uterine arteries and veins pass to and from the intervillous space. Decidual septum is one of the structures derived from basal plate. == References == This article incorporates text in the public domain from page 63 of the 20th edition of Gray's Anatomy (1918) == External links == Slide at uottawa.ca
|
{
"page_id": 5046579,
"source": null,
"title": "Basal plate (placenta)"
}
|
The Dukhin number (Du) is a dimensionless quantity that characterizes the contribution of the surface conductivity to various electrokinetic and electroacoustic effects, as well as to electrical conductivity and permittivity of fluid heterogeneous systems. The number was named after Stanislav and Andrei Dukhin. == Overview == It was introduced by Lyklema in “Fundamentals of Interface and Colloid Science”. A recent IUPAC Technical Report used this term explicitly and detailed several means of measurement in physical systems. The Dukhin number is a ratio of the surface conductivity κ σ {\displaystyle \kappa ^{\sigma }} to the fluid bulk electrical conductivity Km multiplied by particle size a: D u = κ σ K m a . {\displaystyle {\rm {Du}}={\frac {\kappa ^{\sigma }}{{\mathrm {K} _{m}}a}}.} There is another expression of this number that is valid when the surface conductivity is associated only with ions motion above the slipping plane in the double layer. In this case, the value of the surface conductivity depends on ζ-potential, which leads to the following expression for the Dukhin number for symmetrical electrolyte with equal ions diffusion coefficient: D u = 2 ( 1 + 3 m / z 2 ) κ a ( c o s h z F ζ 2 R T − 1 ) , {\displaystyle {\rm {Du}}={\frac {2(1+3m/z^{2})}{{\kappa }a}}\left(\mathrm {cosh} {\frac {zF\zeta }{2RT}}-1\right),} where the parameter m characterizes the contribution of electro-osmosis into motion of ions within the double layer m = 2 ε 0 ε m R 2 T 2 3 η F 2 D . {\displaystyle m={\frac {2\varepsilon _{0}\varepsilon _{m}R^{2}T^{2}}{3\eta F^{2}D}}.} F is Faraday constant T is absolute temperature R is gas constant C is ions concentration in bulk z is ion valency ζ is electrokinetic potential ε0 is vacuum dielectric permittivity εm is fluid dielectric permittivity η is dynamic viscosity D is
|
{
"page_id": 13566263,
"source": null,
"title": "Dukhin number"
}
|
diffusion coefficient == References ==
|
{
"page_id": 13566263,
"source": null,
"title": "Dukhin number"
}
|
There are several methods currently used by astronomers to detect distant exoplanets from Earth. Theoretically, some of these methods can be used to detect Earth as an exoplanet from distant star systems. == History == In June 2021, astronomers identified 1,715 stars (with likely related exoplanetary systems) within 326 light-years (100 parsecs) that have a favorable positional vantage point—in relation to the Earth Transit Zone (ETZ)—of detecting Earth as an exoplanet transiting the Sun since the beginnings of human civilization (about 5,000 years ago); an additional 319 stars are expected to arrive at this special vantage point in the next 5,000 years. Seven known exoplanet hosts, including Ross 128, may be among these stars. Teegarden's Star and Trappist-1 may be expected to see the Earth in 29 and 1,642 years, respectively. Radio waves, emitted by humans, have reached over 75 of the closest stars that were studied. In June 2021, astronomers reported identifying 29 planets in habitable zones that may be capable of observing the Earth. Earlier, in October 2020, astronomers had initially identified 508 such stars within 326 light-years (100 parsecs) that would have a favorable positional vantage point—in relation to the Earth Transit Zone (ETZ)—of detecting Earth as an exoplanet transiting the Sun. Transit method is the most popular tool used to detect exoplanets and the most common tool to spectroscopically analyze exoplanetary atmospheres. As a result, such studies, based on the transit method, will be useful in the search for life on exoplanets beyond the Solar System by the SETI program, Breakthrough Listen Initiative, as well as upcoming exoplanetary TESS mission searches. Detectability of Earth from distant star-based systems may allow for the detectability of humanity and/or analysis of Earth from distant vantage points such as via "atmospheric SETI" for the detection of atmospheric compositions explainable only
|
{
"page_id": 65667384,
"source": null,
"title": "Detecting Earth from distant star-based systems"
}
|
by use of (artificial) technology like air pollution containing nitrogen dioxide from e.g. transportation technologies. The easiest or most likely artificial signals from Earth to be detectable are brief pulses transmitted by anti-ballistic missile (ABM) early-warning and space-surveillance radars during the Cold War and later astronomical and military radars. Unlike the earliest and conventional radio- and television-broadcasting which has been claimed to be undetectable at short distances, such signals could be detected from very distant, possibly star-based, receiver stations – any single of which would detect brief episodes of powerful pulses repeating with intervals of one Earth day – and could be used to detect both Earth as well as the presence of a radar-utilizing civilization on it. Studies have suggested that radio broadcast leakage – with the program material likely not being detectable – may be a technosignature detectable at distances of up to a hundred light years with technology equivalent to the Square Kilometer Array if the location of Earth is known. Likewise, if Earth's location can be and is known, it may be possible to use atmospheric analysis to detect life or favorable conditions for it on Earth via biosignatures, including MERMOZ instruments that may be capable of remotely detecting living matter on Earth. == Experiments == In 1980s, astronomer Carl Sagan persuaded NASA to perform an experiment of detecting life and civilization on Earth using instruments of the Galileo spacecraft. It was launched in December 1990, and when it was 960 km (600 mi) from the planet's surface, Galileo turned its instruments to observe Earth. Sagan's paper was titled "A search for life on Earth from the Galileo spacecraft"; he wrote that "high-resolution images of Australia and Antarctica obtained as Galileo flew overhead did not yield signs of civilization"; other measurements showed the presence of vegetation
|
{
"page_id": 65667384,
"source": null,
"title": "Detecting Earth from distant star-based systems"
}
|
and detected radio transmissions. == See also == == References == == External links == Extrasolar Planets Encyclopaedia by the Paris Observatory
|
{
"page_id": 65667384,
"source": null,
"title": "Detecting Earth from distant star-based systems"
}
|
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