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that using it, shifts are linear transformations: f ( t + Δ t ) = d i a g ( f ( Δ t ) ) f ( t ) {\displaystyle f(t+\Delta t)=\mathrm {diag} (f(\Delta t))f(t)} where Δ t ∈ R {\displaystyle \Delta t\in \mathbb {R} } is the distance one wishes to shift. This allows the transformer to take any encoded position, and find th...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
each encoder layer is to create contextualized representations of the tokens, where each representation corresponds to a token that "mixes" information from other input tokens via self-attention mechanism. Each decoder layer contains two attention sublayers: (1) cross-attention for incorporating the output of encoder (...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
{\displaystyle W^{Q}} , the key weights W K {\displaystyle W^{K}} , and the value weights W V {\displaystyle W^{V}} . The module takes three sequences, a query sequence, a key sequence, and a value sequence. The query sequence is a sequence of length ℓ seq, query {\displaystyle \ell _{\text{seq, query}}} , and each ent...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
(i.e. q i ⋅ k j {\displaystyle q_{i}\cdot k_{j}} is large), this does not necessarily mean that token j {\displaystyle j} will attend to token i {\displaystyle i} (i.e. q j ⋅ k i {\displaystyle q_{j}\cdot k_{i}} could be small). The output of the attention unit for token i {\displaystyle i} is the weighted sum of the v...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
X query = X key = X value {\displaystyle X_{\text{query}}=X_{\text{key}}=X_{\text{value}}} . If the attention head is used in a cross-attention fashion, then usually X query ≠ X key = X value {\displaystyle X_{\text{query}}\neq X_{\text{key}}=X_{\text{value}}} . It is theoretically possible for all three to be differen...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
indexed by i {\displaystyle i} , then we have MultiheadedAttention ( Q , K , V ) = Concat i ∈ [ n heads ] ( Attention ( Q W i Q , K W i K , V W i V ) ) W O {\displaystyle {\text{MultiheadedAttention}}(Q,K,V)={\text{Concat}}_{i\in [n_{\text{heads}}]}({\text{Attention}}(QW_{i}^{Q},KW_{i}^{K},VW_{i}^{V}))W^{O}} where the ...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
j>=i} (as it naturally is the case for time step t = i {\displaystyle t=i} , when tokens j > t {\displaystyle j>t} are not yet calculated). This behavior may be accomplished before the softmax stage by adding a mask matrix M {\displaystyle M} that is − ∞ {\displaystyle -\infty } at entries where the attention link must...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
given input vectors h 0 , h 1 , … combine them into a matrix H = [ h 0 h 1 ⋮ ] EncoderLayer ( H ) = [ FFN ( MultiheadedAttention ( H , H , H ) 0 ) FFN ( MultiheadedAttention ( H , H , H ) 1 ) ⋮ ] {\displaystyle {\begin{aligned}{\text{given input vectors }}&h_{0},h_{1},\dots \\{\text{combine them into a matrix }}H&={\be...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
must not use the current or future output to predict an output, so the output sequence must be partially masked to prevent this reverse information flow. This allows for autoregressive text generation. For decoding, all-to-all attention is inappropriate, because a token cannot attend to tokens not yet generated. Thus, ...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
are the residual connections and layer normalization (LayerNorm, or LN), which while conceptually unnecessary, are necessary for numerical stability and convergence. The residual connection, which is introduced to avoid vanishing gradient issues and stabilize the training process, can be expressed as follows: y = F(x) ...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
input t_e Decoder input t_d output: Array of probability distributions, with shape (decoder vocabulary size x length(decoder output sequence)) /* encoder */ z_e ← encoder.tokenizer(t_e) for each t in 1:length(z_e) do z_e[t] ← encoder.embedding(z_e[t]) + encoder.positional_embedding(t) for each l in 1:length(encoder.lay...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
applications. BERT is encoder-only. They are less often used currently, as they were found to be not significantly better than training an encoder-decoder Transformer, then taking just the encoder. A "decoder-only" Transformer is not literally decoder-only, since without an encoder, the cross-attention mechanism has no...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
series and PaLM used SwiGLU; both GPT-1 and BERT used GELU. Alternative activation functions are often used in combination with Gated Linear Units in the feedforward module. === Alternative normalizations === The normalization used in the Transformer can be different from LayerNorm. One example is RMSNorm which is used...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
m\theta \end{pmatrix}}{\begin{pmatrix}x_{m}^{(1)}\\x_{m}^{(2)}\\\end{pmatrix}}={\begin{pmatrix}x_{m}^{(1)}\cos m\theta -x_{m}^{(2)}\sin m\theta \\x_{m}^{(2)}\cos m\theta +x_{m}^{(1)}\sin m\theta \\\end{pmatrix}}} Equivalently, if we write the 2-dimensional vectors as complex numbers z m := x m ( 1 ) + i x m ( 2 ) {\dis...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
⋮ ⋱ ) {\displaystyle B={\begin{pmatrix}0&1&2&3&\cdots \\-1&0&1&2&\cdots \\-2&-1&0&1&\cdots \\-3&-2&-1&0&\cdots \\\vdots &\vdots &\vdots &\vdots &\ddots \\\end{pmatrix}}} in other words, B i , j = j − i {\displaystyle B_{i,j}=j-i} . The idea being that the linear bias matrix is a softened mask. Just as 0 {\displaystyle ...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
caching method saves the computed key and value vectors at each attention block, so that they are not recomputed at each new token. PagedAttention applies memory paging to KV caching. If a transformer is used with a baked-in prompt, such as ["You are a customer support agent..."], then the key and value vectors can be ...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
∈ [ n heads ] ( Attention ( X W i Q , X W i K , X W i V ) ) W O {\displaystyle {\text{MultiheadedAttention}}(Q,K,V)={\text{Concat}}_{i\in [n_{\text{heads}}]}\left({\text{Attention}}(XW_{i}^{Q},XW_{i}^{K},XW_{i}^{V})\right)W^{O}} with Multi-Query Attention, there is just one W K , W V {\displaystyle W^{K},W^{V}} , thus:...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
x 512 {\displaystyle x_{1},x_{2},...,x_{512}} , taking time 512 T GPT-3 {\displaystyle 512T_{\text{GPT-3}}} . However, if we had some educated guess for the values of these tokens, we could verify all of them in parallel, in one run of the model, by checking that each x t {\displaystyle x_{t}} is indeed the token with ...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
for arbitrarily many steps into the future. This trades off accuracy for speed, since each new token costs just one more Transformer block, rather than the entire stack. === Sub-quadratic transformers === Training transformer-based architectures can be expensive, especially for long inputs. Many methods have been devel...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
⟩ ] T {\displaystyle \varphi (x)={\frac {1}{\sqrt {D}}}[\cos \langle w_{1},x\rangle ,\sin \langle w_{1},x\rangle ,\cdots \cos \langle w_{D},x\rangle ,\sin \langle w_{D},x\rangle ]^{T}} where w 1 , . . . , w D {\displaystyle w_{1},...,w_{D}} are independent samples from the normal distribution N ( 0 , σ 2 I ) {\displays...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
This approximation can be computed in linear time, as we can compute the matrix φ ( k i ) v i T {\displaystyle \varphi (k_{i})v_{i}^{T}} first, then multiply it with the query. In essence, we have managed to obtain a more precise version of Attention ( Q , K , V ) = softmax ( Q K T d k ) V ≈ Q ( K T V / d k ) {\display...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
Perceivers are a variant of Transformers designed for multimodality. For image generation, notable architectures are DALL-E 1 (2021), Parti (2022), Phenaki (2023), and Muse (2023). Unlike later models, DALL-E is not a diffusion model. Instead, it uses a decoder-only Transformer that autoregressively generates a text, f...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
for vision processing Large language model – Type of machine learning model BERT (language model) – Series of language models developed by Google AI Generative pre-trained transformer – Type of large language model T5 (language model) – Series of large language models developed by Google AI == Notes == == References ==...
{ "page_id": 61603971, "source": null, "title": "Transformer (deep learning architecture)" }
Eerik Kumari born Erik Mathias Sits (7 March 1912 – 8 January 1984) was a biologist, and pioneer of ornithology and nature conservation in Estonia. He was born in Kirbla, Lihula Parish. He was the director of the Institute of Zoology and Botany at the Estonian Academy of Sciences from 1952 to 1977. He was the president...
{ "page_id": 13697159, "source": null, "title": "Eerik Kumari" }
The one gene–one enzyme hypothesis is the idea that genes act through the production of enzymes, with each gene responsible for producing a single enzyme that in turn affects a single step in a metabolic pathway. The concept was proposed by George Beadle and Edward Tatum in an influential 1941 paper on genetic mutation...
{ "page_id": 20971660, "source": null, "title": "One gene–one enzyme hypothesis" }
the transformations at a different points in the series. Thus, Beadle reasoned that each gene was responsible for an enzyme acting in the metabolic pathway of pigment synthesis. However, because it was a relatively superficial pathway rather than one shared widely by diverse organisms, little was known about the bioche...
{ "page_id": 20971660, "source": null, "title": "One gene–one enzyme hypothesis" }
Further evidence obtained soon after the initial findings tended to show that generally only a single step in the pathway is blocked. Following their first report of three such auxotroph mutants in 1941, Beadle and Tatum used this method to create series of related mutants and determined the order in which amino acids ...
{ "page_id": 20971660, "source": null, "title": "One gene–one enzyme hypothesis" }
of the Proceedings of the National Academy of Sciences, Beadle and Tatum noted that it was "entirely tenable to suppose that these genes which are themselves a part of the system, control or regulate specific reactions in the system either by acting directly as enzymes or by determining the specificities of enzymes", a...
{ "page_id": 20971660, "source": null, "title": "One gene–one enzyme hypothesis" }
consistent with other work, such as studies of the reproduction of tobacco mosaic virus (which was known to have heritable variations and which followed the same pattern of autocatalysis as many enzymatic reactions) and the crystallization of that virus as an apparently pure protein. At the start of the 1950s, the Neur...
{ "page_id": 20971660, "source": null, "title": "One gene–one enzyme hypothesis" }
gene–one polypeptide" hypothesis instead. According to geneticist Rowland H. Davis, "By 1958 – indeed, even by 1948 – one gene, one enzyme was no longer a hypothesis to be resolutely defended; it was simply the name of a research program." Presently, the one gene–one polypeptide perspective cannot account for the vario...
{ "page_id": 20971660, "source": null, "title": "One gene–one enzyme hypothesis" }
1462495. PMID 12663526. Horowitz NH (1995). "One-Gene-One-Enzyme: Remembering Biochemical Genetics". Protein Science. 4 (5): 1017–1019. doi:10.1002/pro.5560040524. PMC 2143113. PMID 7663338.
{ "page_id": 20971660, "source": null, "title": "One gene–one enzyme hypothesis" }
Post-transcriptional regulation is the control of gene expression at the RNA level. It occurs once the RNA polymerase has been attached to the gene's promoter and is synthesizing the nucleotide sequence. Therefore, as the name indicates, it occurs between the transcription phase and the translation phase of gene expres...
{ "page_id": 16908428, "source": null, "title": "Post-transcriptional regulation" }
Therefore, it helps to select the mRNA that is going to be translated. RNA splicing removes the introns, noncoding regions that are transcribed into RNA, in order to make the mRNA able to create proteins. Cells do this by spliceosomes binding on either side of an intron, looping the intron into a circle and then cleavi...
{ "page_id": 16908428, "source": null, "title": "Post-transcriptional regulation" }
occurs in velocardiofacial syndrome (22q11) and which is linked to psychosis. RNA editing is extensively studied in relation to infectious diseases, because the editing process alters viral function. mRNA Stability can be manipulated in order to control its half-life, and the poly(A) tail has some effect on this stabil...
{ "page_id": 16908428, "source": null, "title": "Post-transcriptional regulation" }
factor-dependent termination. - In the intrinsic termination mechanism, also known as Rho-independent termination, the RNA chain forms a stable transcript hairpin structure at the 3'end of the genes that cause the RNA polymerase to stop transcribing. The stem-loop is followed by a run of U's (poly U tail) which stalls ...
{ "page_id": 16908428, "source": null, "title": "Post-transcriptional regulation" }
than 60% of protein coding genes of the human genome. If an miRNA is abundant it can behave as a "switch", turning some genes on or off. However, altered expression of many miRNAs only leads to a modest 1.5- to 4-fold change in protein expression of their target genes. Individual miRNAs often repress several hundred ta...
{ "page_id": 16908428, "source": null, "title": "Post-transcriptional regulation" }
so they are in control of their own actions. Furthermore, they use both negative feedback, to maintain homeostasis, and positive feedback, to create binary genetic changes in the cell. In metazoans and bacteria, many genes involved in post-post transcriptional regulation are regulated post transcriptionally. For Drosop...
{ "page_id": 16908428, "source": null, "title": "Post-transcriptional regulation" }
unknown. Although RNA binding proteins may regulate post transcriptionally large amount of the transcriptome, the targeting of a single gene is of interest to the scientific community for medical reasons, this is RNA interference and microRNAs which are both examples of posttranscriptional regulation, which regulate th...
{ "page_id": 16908428, "source": null, "title": "Post-transcriptional regulation" }
showed, in leukemias, that constitutive expression of c-Myc, leading to down-regulation of miR-150 and miR-22, allowed increased expression of Lig3 and Parp1. This generates genomic instability through increased inaccurate MMEJ DNA repair, and likely contributes to progression to leukemia. To show the frequent ability ...
{ "page_id": 16908428, "source": null, "title": "Post-transcriptional regulation" }
Mycobiota (plural noun, no singular) are a group of all the fungi present in a particular geographic region (e.g. "the mycobiota of Ireland") or habitat type (e.g. "the mycobiota of cocoa"). An analogous term for Mycobiota is funga. == Human mycobiota == Mycobiota exist on the surface and in the gastrointestinal system...
{ "page_id": 40239247, "source": null, "title": "Mycobiota" }
Protein electrophoresis is a method for analysing the proteins in a fluid or an extract. The electrophoresis may be performed with a small volume of sample in a number of alternative ways with or without a supporting medium, namely agarose or polyacrylamide. Variants of gel electrophoresis include SDS-PAGE, free-flow e...
{ "page_id": 589968, "source": null, "title": "Gel electrophoresis of proteins" }
Blue native PAGE === BN-PAGE is a native PAGE technique, where the Coomassie brilliant blue dye provides the necessary charges to the protein complexes for the electrophoretic separation. The disadvantage of Coomassie is that in binding to proteins it can act like a detergent causing complexes to dissociate. Another dr...
{ "page_id": 589968, "source": null, "title": "Gel electrophoresis of proteins" }
fractions can be specifically determined by solution NMR spectroscopy. == Buffer systems == Most protein separations are performed using a "discontinuous" (or DISC) buffer system that significantly enhances the sharpness of the bands within the gel. During electrophoresis in a discontinuous gel system, an ion gradient ...
{ "page_id": 589968, "source": null, "title": "Gel electrophoresis of proteins" }
cysteine residues in the proteins because the pKa of cysteine ranges from 8-9 and because reducing agent present in the loading buffer doesn't co-migrate with the proteins. Recent advances in buffering technology alleviate this problem by resolving the proteins at a pH well below the pKa of cysteine (e.g., bis-tris, pH...
{ "page_id": 589968, "source": null, "title": "Gel electrophoresis of proteins" }
popular protein stain is Coomassie brilliant blue. It is an anionic dye, which non-specifically binds to proteins. Proteins in the gel are fixed by acetic acid and simultaneously stained. The excess dye incorporated into the gel can be removed by destaining with the same solution without the dye. The proteins are detec...
{ "page_id": 589968, "source": null, "title": "Gel electrophoresis of proteins" }
or body chemicals can cause their own band, but it usually is small. Abnormal bands (spikes) are seen in monoclonal gammopathy of undetermined significance and multiple myeloma, and are useful in the diagnosis of these conditions. The globulins are classified by their banding pattern (with their main representatives): ...
{ "page_id": 589968, "source": null, "title": "Gel electrophoresis of proteins" }
The Camille and Henry Dreyfus Foundation is a New York City-based foundation founded in 1946 by chemist and investor Camille Dreyfus in honour of his brother, Henry Dreyfus. The two men invented the acetate yarn Celanese, and Henry Dreyfus was founder and chairman of British Celanese, parent of the Celanese Corporation...
{ "page_id": 26804367, "source": null, "title": "The Camille and Henry Dreyfus Foundation" }
the program was divided into two parallel awards: The Camille Dreyfus Teacher-Scholar Awards Program, aimed at research universities, and the Henry Dreyfus Teacher-Scholar Awards Program, directed at primarily undergraduate institutions. The annually presented awards consist of a monetary prize of $75,000, which was in...
{ "page_id": 26804367, "source": null, "title": "The Camille and Henry Dreyfus Foundation" }
The Storm Book is a 1952 picture book written by Charlotte Zolotow and illustrated by Margaret Bloy Graham. The book tells the story of a summer storm from the perspective of a young boy. The book was a recipient of a 1953 Caldecott Honor for its illustrations. == References ==
{ "page_id": 62521490, "source": null, "title": "The Storm Book" }
Edward Lawrie Tatum (December 14, 1909 – November 5, 1975) was an American geneticist. He shared half of the Nobel Prize in Physiology or Medicine in 1958 with George Beadle for showing that genes control individual steps in metabolism. The other half of that year's award went to Joshua Lederberg. Tatum was an elected ...
{ "page_id": 917655, "source": null, "title": "Edward Tatum" }
causing mutations. In a series of experiments, they showed that these mutations caused changes in specific enzymes involved in metabolic pathways. This led them to propose a direct link between genes and enzymatic reactions, known as the "one gene, one enzyme" hypothesis. Tatum spent his career studying biosynthetic pa...
{ "page_id": 917655, "source": null, "title": "Edward Tatum" }
The molecular formula C8H13NO2 (molar mass: 155.19 g/mol, exact mass: 155.0946 u) may refer to: Arecoline Bemegride Scopine Retronecine
{ "page_id": 23920792, "source": null, "title": "C8H13NO2" }
The MANIAC is a 2023 novel by Chilean author Benjamín Labatut, written in English. It is a fictionalised biography of polymath John von Neumann, whom Labatut calls "the smartest human being of the 20th century". The book focuses on von Neumann, but is also about physicist Paul Ehrenfest, the history of artificial intel...
{ "page_id": 75694234, "source": null, "title": "The MANIAC" }
the same thing as saying kingly," he explained); because of its physicality; and because you can do almost anything with verbs and prepositions. Labatut was inspired to write The MANIAC by George Dyson's book Turing's Cathedral. == Synopsis == The book has three chapters. The first chapter, "Paul or the Discovery of th...
{ "page_id": 75694234, "source": null, "title": "The MANIAC" }
creation of the MANIAC I computer and the von Neumann architecture (as told by Julian Bigelow). In Part III, "Ghosts in the Machine", Sydney Brenner discusses von Neumann's contributions to biology, his theoretical work on self-replicating and self-repairing machines, and his vision of Von Neumann probes exploring the ...
{ "page_id": 75694234, "source": null, "title": "The MANIAC" }
eerie and singular beauty." She noted that the book "can also be difficult to read" because of its unusual narrative structure: "The book is narrated by a cluttered polyphony of characters, among them both of von Neumann's wives and a number of his teachers and colleagues. ... Like von Neumann, The MANIAC strives to ad...
{ "page_id": 75694234, "source": null, "title": "The MANIAC" }
the book as a biography. In an essay for the Cleveland Review of Books, Ben Cosman juxtaposes the book with Christopher Nolan's biopic Oppenheimer, and writes that it "follows the development of artificial intelligence—first as an idea at the beginning of the twentieth century, and then as a practicality at the beginni...
{ "page_id": 75694234, "source": null, "title": "The MANIAC" }
connects the story of AI and von Neumann to an old story of "manufactured men, from Rabbi Judah Loew ben Bezalel's golem to Mary Shelley's monster in Frankenstein ... humanity was haunted by the possibility of artificial intelligence before it ever existed". Simon notes von Neumann's obscurity: If it's true that von Ne...
{ "page_id": 75694234, "source": null, "title": "The MANIAC" }
"That the editors at Penguin were agreeable with Labatut's novel ending in an 84-page (admittedly riveting) synopsis of the strategies that underlie a complex 3,000-year-old Chinese game speaks to an admirable conception of what novels can do, the way that they can be pushed and can in turn push our conceptions." As La...
{ "page_id": 75694234, "source": null, "title": "The MANIAC" }
Vanishing-dimensions theory is a particle physics theory suggesting that systems with higher energy have a smaller number of dimensions. For example, the theory implies that the Universe had fewer dimensions after the Big Bang when its energy was high. Then the number of dimensions may have increased as the system cool...
{ "page_id": 39452826, "source": null, "title": "Vanishing dimensions theory" }
The International Institute of Agriculture (IIA) was the first organization to systematically produce and exchange global data on crops, cultivated land, and trade flows. The late 19th century called for a demand in worldwide data on production, stocks, and consumption, as a rise in agricultural commoditities emerged i...
{ "page_id": 10158236, "source": null, "title": "International Institute of Agriculture" }
an international centralization initiative to promote the welfare of farmers. Its initial task consisted of gathering annual crop production statistics from nations worldwide, presenting this data as a “single numeric statement,” which indicated the year’s anticipated harvests as a percentage of the previous year’s har...
{ "page_id": 10158236, "source": null, "title": "International Institute of Agriculture" }
of the IIA was the Ottoman Empire. In the early activities of the institute, the most active participants were representatives from this region. The contributions and participation from the Ottoman Empire allowed its political officials to assert their position on creating a global standard for data collection, while a...
{ "page_id": 10158236, "source": null, "title": "International Institute of Agriculture" }
and published information regarding the progress of scientific and experimental investigations and practical experience in agriculture throughout the world and, as a branch of this work, gives special attention to the diseases of plants and to entomology. Bureau of economic and social institutions collected and publish...
{ "page_id": 10158236, "source": null, "title": "International Institute of Agriculture" }
Congress of the United States made an annual appropriation of $5,000 (c. 1915) for translating and printing the English edition, the rest of the expense being borne by Great Britain and her colonies. == Library == The IIA collected a great library of agricultural literature. As the IIA became more firmly established an...
{ "page_id": 10158236, "source": null, "title": "International Institute of Agriculture" }
Grazing marsh is a British Isles term for flat, marshy grassland in polders. It consists of large grass fields separated by fresh or brackish ditches, and is often important for its wildlife. == History == Grazing marshes were created from medieval times by building sea walls (earth banks) across tidal mudflats and sal...
{ "page_id": 14680221, "source": null, "title": "Grazing marsh" }
redshank, Eurasian curlew, snipe, and northern lapwing breed. The ditches often have a range of salinity, depending on how close to the sea wall they are. The more saline ditches host specialist brackish-water plants and animals. These include, for example, the rare brackish amphipod Gammarus insensibilis and sea club-...
{ "page_id": 14680221, "source": null, "title": "Grazing marsh" }
The molecular formula C10H13N (molar mass 147.219 g/mol, exact mass: 147.1048 u) may refer to: Actinidine 2-Aminotetralin (2-AT or THN) NM-2-AI, or N-methyl-2-aminoindane Phenylbutenamine
{ "page_id": 23920796, "source": null, "title": "C10H13N" }
The molecular formula C16H10O6 (molar mass: 298.24 g/mol, exact mass: 298.0477 u) may refer to: Irilone Fallacinal
{ "page_id": 26345629, "source": null, "title": "C16H10O6" }
Count Noble (August 1, 1879 – January 20, 1891) was a dog English Setter. He was so well known that when he died in 1891, The New York Times ran an obituary. He was popularly known as the "$10,000 hunting dog." He was described as a "national symbol of what was great in bird dogs." His owner, Captain Benjamin Frederick...
{ "page_id": 30605472, "source": null, "title": "Count Noble" }
The molecular formula C13H9NO (molar mass: 195.22 g/mol, exact mass: 195.0684 u) may refer to: Acridone CR gas, or dibenzoxazepine
{ "page_id": 23920799, "source": null, "title": "C13H9NO" }
In molecular biology mir-3 microRNA is a short RNA molecule. MicroRNAs function to regulate the expression levels of other genes by several mechanisms. == See also == MicroRNA == References == == Further reading == == External links == Page for mir-3 microRNA precursor family at Rfam
{ "page_id": 36372646, "source": null, "title": "Mir-3 microRNA precursor family" }
The molecular formula C7H8N2 (molar mass: 120.15 g/mol, exact mass: 120.0687 u) may refer to: Benzimidazoline Benzamidine
{ "page_id": 23920806, "source": null, "title": "C7H8N2" }
The molecular formula C14H18O3 (molar mass : 234.29 g/mol) may refer to: Gyrinal, a powerful antiseptic and fish and mammal toxin Stiripentol, an anticonvulsant drug used in the treatment of epilepsy
{ "page_id": 23986346, "source": null, "title": "C14H18O3" }
The molecular formula C17H26O4 (molar mass 294.38 g/mol, exact mass: 294.1831 u) may refer to: Embelin (2,5-dihydroxy-3-undecyl-1,4-benzoquinone) Gingerol Cineromycin B
{ "page_id": 23986347, "source": null, "title": "C17H26O4" }
The molecular formula C8H7NS (molar mass: 149.21 g/mol, exact mass: 149.0299 u) may refer to: Benzyl isothiocyanate (BITC) Benzothiazine 2-Mercaptoindole
{ "page_id": 23920812, "source": null, "title": "C8H7NS" }
Agricultural chemistry is the chemistry, especially organic chemistry and biochemistry, as they relate to agriculture. Agricultural chemistry embraces the structures and chemical reactions relevant in the production, protection, and use of crops and livestock. Its applied science and technology aspects are directed tow...
{ "page_id": 5111982, "source": null, "title": "Agricultural chemistry" }
Fertilizers are a major consideration. While organic fertilizers are time-honored, their use has largely been displaced by chemicals produced from mining (phosphate rock) and the Haber-Bosch process. The use of these materials dramatically increased the rate at which crops are produced, which is able to support the gro...
{ "page_id": 5111982, "source": null, "title": "Agricultural chemistry" }
more technology and infrastructure developed, a decreased cost, and an advance in research. Since the early 1980s, genetically-modified crops have been incorporated. Increased biotechnological work calls for the union of biology and chemistry to produce improved crops, a main reason behind this being the increasing amo...
{ "page_id": 5111982, "source": null, "title": "Agricultural chemistry" }
Monte Carlo in statistical physics refers to the application of the Monte Carlo method to problems in statistical physics, or statistical mechanics. == Overview == The general motivation to use the Monte Carlo method in statistical physics is to evaluate a multivariable integral. The typical problem begins with a syste...
{ "page_id": 8519857, "source": null, "title": "Monte Carlo method in statistical mechanics" }
Monte Carlo method, which is used to simulate molecular chains) is generally employed. The main motivation for its use is the fact that, with the Monte Carlo integration, the error goes as 1 / N {\displaystyle 1/{\sqrt {N}}} , independently of the dimension of the integral. Another important concept related to the Mont...
{ "page_id": 8519857, "source": null, "title": "Monte Carlo method in statistical mechanics" }
→ ) {\displaystyle p({\vec {r}})} is a distribution that chooses the states that are known to be more relevant to the integral. The mean value of A {\displaystyle A} can be rewritten as ⟨ A ⟩ = ∫ P S p − 1 ( r → ) A r → p − 1 ( r → ) e − β E r → / Z d r → = ∫ P S p − 1 ( r → ) A r → ∗ e − β E r → / Z d r → {\displaysty...
{ "page_id": 8519857, "source": null, "title": "Monte Carlo method in statistical mechanics" }
E_{\vec {r}}}}{Z}}} be the distribution to use. Substituting on the previous sum, ⟨ A ⟩ ≃ 1 N ∑ i = 1 N A r → i ∗ {\displaystyle \langle A\rangle \simeq {\frac {1}{N}}\sum _{i=1}^{N}A_{{\vec {r}}_{i}}^{*}} . So, the procedure to obtain a mean value of a given variable, using metropolis algorithm, with the canonical dis...
{ "page_id": 8519857, "source": null, "title": "Monte Carlo method in statistical mechanics" }
energy is treated equally. The major drawback of this choice is the fact that, on most systems, Ω ( E ) {\displaystyle \Omega (E)} is unknown. To overcome this, the Wang and Landau algorithm is normally used to obtain the DOS during the simulation. Note that after the DOS is known, the mean values of every variable can...
{ "page_id": 8519857, "source": null, "title": "Monte Carlo method in statistical mechanics" }
( r → ) = ∑ i = 1 N σ i {\displaystyle M({\vec {r}})=\sum _{i=1}^{N}\sigma _{i}} . === Canonical === First, the system must be initialized: let β = 1 / k b T {\displaystyle \beta =1/k_{b}T} be the system's Boltzmann temperature and initialize the system with an initial state (which can be anything since the final resul...
{ "page_id": 8519857, "source": null, "title": "Monte Carlo method in statistical mechanics" }
M + Δ M {\displaystyle M=M+\Delta M} after TT times, the system is considered to be not correlated from its previous state, which means that, at this moment, the probability of the system to be on a given state follows the Boltzmann distribution, which is the objective proposed by this method. step 2: perform the measu...
{ "page_id": 8519857, "source": null, "title": "Monte Carlo method in statistical mechanics" }
introduced and then gradually lowered. == See also == Monte Carlo integration Metropolis algorithm Importance sampling Quantum Monte Carlo Monte Carlo molecular modeling == References == Allen, M.P. & Tildesley, D.J. (1987). Computer Simulation of Liquids. Oxford University Press. ISBN 0-19-855645-4. Frenkel, D. & Smit...
{ "page_id": 8519857, "source": null, "title": "Monte Carlo method in statistical mechanics" }
Ungiminorine is an acetylcholinesterase inhibitor isolated from Narcissus. == References ==
{ "page_id": 40632497, "source": null, "title": "Ungiminorine" }
In molecular biology mir-5 microRNA is a short RNA molecule. MicroRNAs function to regulate the expression levels of other genes by several mechanisms. mir-5 has been implicated in regulation of VEGF in an experiment where a plasmid containing a cluster of mir-5, mir-10 and mir-7 was shown to down-regulate VEGF by 75%....
{ "page_id": 36372665, "source": null, "title": "Mir-5 microRNA precursor family" }
Annihilation is a 2014 novel by Jeff VanderMeer. It is the first entry in VanderMeer's Southern Reach Series and follows a team of four women (a biologist, an anthropologist, a psychologist, and a surveyor) who set out into an area known as Area X, which is abandoned and cut off from the rest of civilization; they are ...
{ "page_id": 42008766, "source": null, "title": "Annihilation (VanderMeer novel)" }
previous expedition, from which he had returned home unexpectedly without the memory or ability to explain his reappearance. The other members of the eleventh expedition showed up similarly, and her husband and the others all died of cancer a few months later. In Area X during the present moment, the four women come up...
{ "page_id": 42008766, "source": null, "title": "Annihilation (VanderMeer novel)" }
to them and, returning to the top, they find that she has disappeared. The biologist is conscious of a "brightness" growing within herself, which she attributes to the spores, and she leaves to explore a distant lighthouse; the surveyor stays behind to protect their campsite. Inside the lighthouse, the biologist discov...
{ "page_id": 42008766, "source": null, "title": "Annihilation (VanderMeer novel)" }
returns to the Tower to confront the Crawler directly, meeting it on the spiral staircase and finding it almost impossible to describe; it is a rapidly shapeshifting entity of blinding lights and shattering noises, which paralyzes the biologist in an agonizing loop of losing and regaining consciousness. It tosses her d...
{ "page_id": 42008766, "source": null, "title": "Annihilation (VanderMeer novel)" }
gothic horror novel set in a not-too-distant future" while The Daily Telegraph said that it "shows signs of being the novel that will allow VanderMeer to break through to a new and larger audience". Entertainment Weekly gave Annihilation a B+ rating. The novel won the 2014 Nebula Award for Best Novel and the 2014 Shirl...
{ "page_id": 42008766, "source": null, "title": "Annihilation (VanderMeer novel)" }
In immunology, clonal deletion is the process of removing T and B lymphocytes from the immune system repertoire. The process of clonal deletion helps prevent recognition and destruction of the self host cells, making it a type of negative selection. Ultimately, clonal deletion plays a role in central tolerance. Clonal ...
{ "page_id": 17301695, "source": null, "title": "Clonal deletion" }
immunology and transplantation for the past decades. == Function == There are millions of B and T lymphocytes within the immune system. As a T or B lymphocyte develops, they can rearrange their genome in order to express a unique antigen that will recognize a specific epitope on a pathogen. There is a large diversity o...
{ "page_id": 17301695, "source": null, "title": "Clonal deletion" }
and some autoreactive lymphocytes can find their way into circulation. However, the immune system has secondary defenses within the periphery to protect against this, referred to as peripheral tolerance. === B Lymphocytes === Regulation of auto-reactive B lymphocytes can occur at many different stages during B cell dev...
{ "page_id": 17301695, "source": null, "title": "Clonal deletion" }
to be responsible for the apoptotic signals sent to autoreactive T cells in the thymic cortex. ==== Thymic medulla ==== T cells also have the opportunity to undergo clonal deletion within the thymic medulla. Here the T lymphocytes undergo negative selection. At this point they encounter MHC I/II complexes presenting se...
{ "page_id": 17301695, "source": null, "title": "Clonal deletion" }
are composed of viral or bacterial proteins and can hijack the clonal deletion process when expressed in the thymus because they resemble the T-cell receptor (TCR) interaction with self MHC/peptides. Thus, through this process, superantigens can effectively prevent maturation of cognate T cells. == References == == Ext...
{ "page_id": 17301695, "source": null, "title": "Clonal deletion" }
5α-Reductases, also known as 3-oxo-5α-steroid 4-dehydrogenases, are enzymes involved in steroid metabolism. They participate in three metabolic pathways: bile acid biosynthesis, androgen and estrogen metabolism. There are three isozymes of 5α-reductase encoded by the genes SRD5A1, SRD5A2, and SRD5A3. 5α-Reductases cata...
{ "page_id": 1245377, "source": null, "title": "5α-Reductase" }