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16,600 | These models will be deposited in an internet database from which Blue Brain software can extract and connect models together to build brain regions and begin the first whole brain simulations.Genes to Cognition Project Genes to Cognition Project, a neuroscience research programme that studies genes, the brain and beha... | Neuroinformatics | 0.813594 |
16,601 | The project involves: Databases: 3D reconstructed model neurons, synapses, synaptic pathways, microcircuit statistics, computer model neurons, virtual neurons. Visualization: microcircuit builder and simulation results visualizator, 2D, 3D and immersive visualization systems are being developed. Simulation: a simulatio... | Neuroinformatics | 0.813594 |
16,602 | This lab facilitates neuroscientists and computer scientists in Pakistan to conduct their experiments and analysis on the data collected using state of the art research methodologies without investing in establishing the experimental neuroscience facilities. The key goal of this lab is to provide state of the art exper... | Neuroinformatics | 0.813594 |
16,603 | Laboratory for Mathematical Neuroscience, RIKEN Brain Science Institute (Wako, Saitama) The target of Laboratory for Mathematical Neuroscience is to establish mathematical foundations of brain-style computations toward construction of a new type of information science. Led by Shun-ichi Amari.Netherlands state program i... | Neuroinformatics | 0.813594 |
16,604 | Current research programmes within the group are focused on the improvement of man-machine-interfaces, robot-force-control, eye-tracking experiments, machine vision, virtual reality and distributed systems.Laboratory of Computational Embodied Neuroscience (LOCEN) This group, part of the Institute of Cognitive Sciences ... | Neuroinformatics | 0.813594 |
16,605 | Led by Andreas VM Herz. The Neuroinformatics Group in Bielefeld Active in the field of Artificial Neural Networks since 1989. | Neuroinformatics | 0.813594 |
16,606 | The Portal Pilot is promoted by the German Ministry for Science and Education. Computational Neuroscience, ITB, Humboldt-University Berlin This group focuses on computational neurobiology, in particular on the dynamics and signal processing capabilities of systems with spiking neurons. | Neuroinformatics | 0.813594 |
16,607 | The MCIN community, together with the Ludmer Centre for Neuroinformatics and Mental Health, collaborates with a broad range of researchers and increasingly focuses on open data sharing and open science, including for the Montreal Neurological Institute.The THOR Center for Neuroinformatics Established April 1998 at the ... | Neuroinformatics | 0.813594 |
16,608 | Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology The main activity of the group is development of computational tools and models, and using them to understand brain structure and function.Neuroimaging & Neuroinformatics, Howard Florey Institute, University of Melbourne Institute scientists utili... | Neuroinformatics | 0.813594 |
16,609 | The INCF contributes to the development and maintenance of database and computational infrastructure and support mechanisms for neuroscience applications. The system is expected to provide access to all freely accessible human brain data and resources to the international research community. The more general task of IN... | Neuroinformatics | 0.813594 |
16,610 | Institute of Neuroinformatics, University of Zurich The Institute of Neuroinformatics was established at the University of Zurich and ETH Zurich at the end of 1995. The mission of the Institute is to discover the key principles by which brains work and to implement these in artificial systems that interact intelligentl... | Neuroinformatics | 0.813594 |
16,611 | In November 2007, the project reported the end of its first phase, delivering a data-driven process for creating, validating, and researching the neocortical column. An artificial neural network described as being "as big and as complex as half of a mouse brain" was run on an IBM Blue Gene supercomputer by the Universi... | Neuroinformatics | 0.813594 |
16,612 | In November 2007, the project reported the end of its first phase, delivering a data-driven process for creating, validating, and researching the neocortical column. An artificial neural network described as being "as big and as complex as half of a mouse brain" was run on an IBM Blue Gene supercomputer by the Universi... | Neuroinformatics | 0.813594 |
16,613 | Neuroinformatics is the field that combines informatics and neuroscience. Neuroinformatics is related with neuroscience data and information processing by artificial neural networks. There are three main directions where neuroinformatics has to be applied: the development of computational models of the nervous system a... | Neuroinformatics | 0.813594 |
16,614 | This means that the observed number of changes is no longer linear with time, but instead flattens out. Even at intermediate genetic distances, with phylogenetic data still sufficient to estimate topology, signal for the overall scale of the tree can be weak under complex likelihood models, leading to highly uncertain ... | Molecular clocks | 0.813588 |
16,615 | Researchers such as Francisco J. Ayala have more fundamentally challenged the molecular clock hypothesis. According to Ayala's 1999 study, five factors combine to limit the application of molecular clock models: Changing generation times (If the rate of new mutations depends at least partly on the number of generations... | Molecular clocks | 0.813588 |
16,616 | In chemistry, a reagent ( ree-AY-jənt) or analytical reagent is a substance or compound added to a system to cause a chemical reaction, or test if one occurs. The terms reactant and reagent are often used interchangeably, but reactant specifies a substance consumed in the course of a chemical reaction. Solvents, though... | Chemical reagent | 0.813587 |
16,617 | In organic chemistry, the term "reagent" denotes a chemical ingredient (a compound or mixture, typically of inorganic or small organic molecules) introduced to cause the desired transformation of an organic substance. Examples include the Collins reagent, Fenton's reagent, and Grignard reagents. | Chemical reagent | 0.813587 |
16,618 | It only should resolve the geometry. Fine structural details can be resolved, in contrast to SEA which gives only one number per subsystem. Greater flexibility for the models usable by DEA. No implicit assumptions (equilibrium in weakly coupled subsystems) as in SEA. | Dynamical energy analysis | 0.813586 |
16,619 | Simulations of the vibro-acoustic properties of complex structures (such as cars, ships, airplanes,...) are routinely carried out in various design stages. For low frequencies, the established method of choice is the finite element method (FEM). But high frequency analysis using FEM requires very fine meshes of the bod... | Dynamical energy analysis | 0.813586 |
16,620 | A probabilistic logic network (PLN) is a conceptual, mathematical and computational approach to uncertain inference; inspired by logic programming, but using probabilities in place of crisp (true/false) truth values, and fractional uncertainty in place of crisp known/unknown values. In order to carry out effective reas... | Probabilistic logic network | 0.813584 |
16,621 | PLN begins with a term logic foundation and then adds on elements of probabilistic and combinatory logic, as well as some aspects of predicate logic and autoepistemic logic, to form a complete inference system, tailored for easy integration with software components embodying other (not explicitly logical) aspects of in... | Probabilistic logic network | 0.813584 |
16,622 | In solid state physics the electronic specific heat, sometimes called the electron heat capacity, is the specific heat of an electron gas. Heat is transported by phonons and by free electrons in solids. For pure metals, however, the electronic contributions dominate in the thermal conductivity. In impure metals, the el... | Electron heat capacity | 0.813582 |
16,623 | There are several algorithms for solving lexicographic optimization problems. | Lexicographic optimization | 0.813578 |
16,624 | A leximin optimization problem with n objectives can be solved using a sequence of n single-objective optimization problems, as follows:: Alg.1 For t = 1,...,n do Solve the following single-objective problem: If the problem is infeasible or unbounded, stop and declare that there is no solution. Otherwise, put the value... | Lexicographic optimization | 0.813578 |
16,625 | (2) Partial sums. Given a vector f 1 , … , f n {\displaystyle f_{1},\ldots ,f_{n}} of functions to optimize, for all t in 1,...,n, define f 1.. t := ∑ i = 1 t f i {\displaystyle f_{1..t}:=\sum _{i=1}^{t}f_{i}} = the sum of all functions from the most important to the t-th most important one. Then, the original lexicogr... | Lexicographic optimization | 0.813578 |
16,626 | (1) Uniqueness. In general, a lexicographic optimization problem may have more than one optimal solution. However, If x 1 {\displaystyle x^{1}} and x 2 {\displaystyle x^{2}} are two optimal solutions, then their value must be the same, that is, f i ( x 1 ) = f i ( x 2 ) {\displaystyle f_{i}(x^{1})=f_{i}(x^{2})} for all... | Lexicographic optimization | 0.813578 |
16,627 | This guarantees that maximizing the weighted sum ∑ t w t f t ( x ) {\displaystyle \sum _{t}w_{t}f_{t}(x)} is equivalent to lexicographic maximization. Cococcioni, Pappalardo and Sergeyev show that, given a computer that can make numeric computations with infinitesimals, it is possible to choose weights that are infinit... | Lexicographic optimization | 0.813578 |
16,628 | Sherali and Soyster prove that, for any linear lexicographic optimization problem, there exist a set of weights w 1 > w 2 > ⋯ > w n {\displaystyle w_{1}>w_{2}>\cdots >w_{n}} such that the set of lexicographically-optimal solutions is identical to the set of solutions to the following single-objective problem:One way to... | Lexicographic optimization | 0.813578 |
16,629 | Linear lexicographic optimization is a special case of lexicographic optimization in which the objectives are linear, and the feasible set is described by linear inequalities. It can be written as:where c 1 , … , c n {\displaystyle c_{1},\ldots ,c_{n}} are vectors representing the linear objectives to maximize, ordered... | Lexicographic optimization | 0.813578 |
16,630 | It wants to maximize the safety of its workers and customers. Subject to attaining the maximum possible safety, it wants to maximize profits. This firm performs lexicographic optimization, where f 1 {\displaystyle f_{1}} denotes safety and f 2 {\displaystyle f_{2}} denotes profits. As another example, in project manage... | Lexicographic optimization | 0.813578 |
16,631 | Lexicographic optimization is sometimes called preemptive optimization, since a small increase in one objective value preempts a much larger increase in less important objective values. As an example, consider a firm which puts safety above all. | Lexicographic optimization | 0.813578 |
16,632 | Lexicographic optimization is a kind of Multi-objective optimization. In general, multi-objective optimization deals with optimization problems with two or more objective functions to be optimized simultaneously. Often, the different objectives can be ranked in order of importance to the decision-maker, so that objecti... | Lexicographic optimization | 0.813578 |
16,633 | In mathematics and particularly in topology, pairwise Stone space is a bitopological space ( X , τ 1 , τ 2 ) {\displaystyle \scriptstyle (X,\tau _{1},\tau _{2})} which is pairwise compact, pairwise Hausdorff, and pairwise zero-dimensional. Pairwise Stone spaces are a bitopological version of the Stone spaces. Pairwise ... | Pairwise Stone space | 0.813578 |
16,634 | This result was derived by Britney Gallivan, a high schooler from California, in December 2001. In January 2002, she folded a 4,000-foot-long (1,200 m) piece of toilet paper twelve times in the same direction, debunking a long-standing myth that paper cannot be folded in half more than eight times.The fold-and-cut prob... | Mathematics of paper folding | 0.813573 |
16,635 | Computational origami has contributed to applications in robotics, biotechnology & medicine, industrial design. Applications for origami have also been developed in the study of programming languages and programming paradigms, particular in the setting of functional programming.Robert Lang participated in a project wit... | Mathematics of paper folding | 0.813573 |
16,636 | The discipline of origami or paper folding has received a considerable amount of mathematical study. Fields of interest include a given paper model's flat-foldability (whether the model can be flattened without damaging it), and the use of paper folds to solve up-to cubic mathematical equations.Computational origami is... | Mathematics of paper folding | 0.813573 |
16,637 | Fairly straightforward statistics provide estimates of whether associations between genes on lists are greater than what one would expect by chance. These statistics are interesting, even if they represent a substantial oversimplification of what is really going on. Here is an example. | Digital gene expression profiling | 0.81357 |
16,638 | While the statistics may identify which gene products change under experimental conditions, making biological sense of expression profiling rests on knowing which protein each gene product makes and what function this protein performs. Gene annotation provides functional and other information, for example the location ... | Digital gene expression profiling | 0.81357 |
16,639 | In the field of molecular biology, gene expression profiling is the measurement of the activity (the expression) of thousands of genes at once, to create a global picture of cellular function. These profiles can, for example, distinguish between cells that are actively dividing, or show how the cells react to a particu... | Digital gene expression profiling | 0.81357 |
16,640 | Science-Enabling Technologies for Heliophysics (SETH) is a proposed space mission by NASA's Goddard Space Flight Center to launch a small satellite that would demonstrate new technologies to detect solar energetic particles, and demonstrate an optical communication system based on laser pulses.The Principal Investigato... | Science-Enabling Technologies for Heliophysics | 0.813568 |
16,641 | Its science payload would be a novel detector of solar energetic neutral atoms (ENA), as well as an array of waves and other Solar energetic particles (SEP) that erupt from the Sun. The instrument is called the HELio Energetic Neutral Atom (HELENA) detector. This technology could enable advanced warnings of potential s... | Science-Enabling Technologies for Heliophysics | 0.813568 |
16,642 | In particular, any group topology on a topological group is completely determined by any neighborhood basis at the identity element. If S {\displaystyle S} is any subset of G {\displaystyle G} and U {\displaystyle U} is an open subset of G , {\displaystyle G,} then S U := { s u: s ∈ S , u ∈ U } {\displaystyle SU:=\{su:... | Continuous group | 0.813567 |
16,643 | Every topological group's topology is translation invariant, which by definition means that if for any a ∈ G , {\displaystyle a\in G,} left or right multiplication by this element yields a homeomorphism G → G . {\displaystyle G\to G.} Consequently, for any a ∈ G {\displaystyle a\in G} and S ⊆ G , {\displaystyle S\subse... | Continuous group | 0.813567 |
16,644 | Information about convergence of nets and filters, such as definitions and properties, can be found in the article about filters in topology. | Continuous group | 0.813567 |
16,645 | Delayed Q-learning is an alternative implementation of the online Q-learning algorithm, with probably approximately correct (PAC) learning.Greedy GQ is a variant of Q-learning to use in combination with (linear) function approximation. The advantage of Greedy GQ is that convergence is guaranteed even when function appr... | Deep Q-learning | 0.813562 |
16,646 | The DeepMind system used a deep convolutional neural network, with layers of tiled convolutional filters to mimic the effects of receptive fields. Reinforcement learning is unstable or divergent when a nonlinear function approximator such as a neural network is used to represent Q. This instability comes from the corre... | Deep Q-learning | 0.813562 |
16,647 | The standard Q-learning algorithm (using a Q {\displaystyle Q} table) applies only to discrete action and state spaces. Discretization of these values leads to inefficient learning, largely due to the curse of dimensionality. However, there are adaptations of Q-learning that attempt to solve this problem such as Wire-f... | Deep Q-learning | 0.813562 |
16,648 | For γ = 1 {\displaystyle \gamma =1} , without a terminal state, or if the agent never reaches one, all environment histories become infinitely long, and utilities with additive, undiscounted rewards generally become infinite. Even with a discount factor only slightly lower than 1, Q-function learning leads to propagati... | Deep Q-learning | 0.813562 |
16,649 | CAA computes state values vertically and actions horizontally (the "crossbar"). Demonstration graphs showing delayed reinforcement learning contained states (desirable, undesirable, and neutral states), which were computed by the state evaluation function. This learning system was a forerunner of the Q-learning algorit... | Deep Q-learning | 0.813562 |
16,650 | Q-learning can be combined with function approximation. This makes it possible to apply the algorithm to larger problems, even when the state space is continuous. One solution is to use an (adapted) artificial neural network as a function approximator. Another possibility is to integrate Fuzzy Rule Interpolation (FRI) ... | Deep Q-learning | 0.813562 |
16,651 | Since analytic varieties may have singular points, not all analytic varieties are manifolds. Modern analytic geometry is essentially equivalent to real and complex algebraic geometry, as has been shown by Jean-Pierre Serre in his paper GAGA, the name of which is French for Algebraic geometry and analytic geometry. Neve... | Algebraic Geometry | 0.813561 |
16,652 | An analytic variety is defined locally as the set of common solutions of several equations involving analytic functions. It is analogous to the included concept of real or complex algebraic variety. Any complex manifold is an analytic variety. | Algebraic Geometry | 0.813561 |
16,653 | Algebraic geometry now finds applications in statistics, control theory, robotics, error-correcting codes, phylogenetics and geometric modelling. There are also connections to string theory, game theory, graph matchings, solitons and integer programming. | Algebraic Geometry | 0.813561 |
16,654 | In other words, a projective variety is a projective algebraic set, whose homogeneous coordinate ring is an integral domain, the projective coordinates ring being defined as the quotient of the graded ring or the polynomials in n + 1 variables by the homogeneous (reduced) ideal defining the variety. Every projective al... | Algebraic Geometry | 0.813561 |
16,655 | This allows us to define a projective algebraic set in Pn as the set V(f1, ..., fk), where a finite set of homogeneous polynomials {f1, ..., fk} vanishes. Like for affine algebraic sets, there is a bijection between the projective algebraic sets and the reduced homogeneous ideals which define them. The projective varie... | Algebraic Geometry | 0.813561 |
16,656 | Furthermore, the introduction of projective techniques made many theorems in algebraic geometry simpler and sharper: For example, Bézout's theorem on the number of intersection points between two varieties can be stated in its sharpest form only in projective space. For these reasons, projective space plays a fundament... | Algebraic Geometry | 0.813561 |
16,657 | The consideration of the projective completion of the two curves, which is their prolongation "at infinity" in the projective plane, allows us to quantify this difference: the point at infinity of the parabola is a regular point, whose tangent is the line at infinity, while the point at infinity of the cubic curve is a... | Algebraic Geometry | 0.813561 |
16,658 | Just as the formulas for the roots of second, third, and fourth degree polynomials suggest extending real numbers to the more algebraically complete setting of the complex numbers, many properties of algebraic varieties suggest extending affine space to a more geometrically complete projective space. Whereas the comple... | Algebraic Geometry | 0.813561 |
16,659 | The regular maps are also called morphisms, as they make the collection of all affine algebraic sets into a category, where the objects are the affine algebraic sets and the morphisms are the regular maps. The affine varieties is a subcategory of the category of the algebraic sets. Given a regular map g from V to V′ an... | Algebraic Geometry | 0.813561 |
16,660 | We define a regular map f from V to Am by letting f = (f1, ..., fm). In other words, each fi determines one coordinate of the range of f. If V′ is a variety contained in Am, we say that f is a regular map from V to V′ if the range of f is contained in V′. The definition of the regular maps apply also to algebraic sets. | Algebraic Geometry | 0.813561 |
16,661 | This implies that, unless if most polynomials appearing in the input are linear, it may not solve problems with more than four variables. Since 1973, most of the research on this subject is devoted either to improving CAD or finding alternative algorithms in special cases of general interest. As an example of the state... | Algebraic Geometry | 0.813561 |
16,662 | The complexity of CAD is doubly exponential in the number of variables. This means that CAD allows, in theory, to solve every problem of real algebraic geometry which may be expressed by such a formula, that is almost every problem concerning explicitly given varieties and semi-algebraic sets. While Gröbner basis compu... | Algebraic Geometry | 0.813561 |
16,663 | CAD is an algorithm which was introduced in 1973 by G. Collins to implement with an acceptable complexity the Tarski–Seidenberg theorem on quantifier elimination over the real numbers. This theorem concerns the formulas of the first-order logic whose atomic formulas are polynomial equalities or inequalities between pol... | Algebraic Geometry | 0.813561 |
16,664 | The second early 19th century development, that of Abelian integrals, would lead Bernhard Riemann to the development of Riemann surfaces. In the same period began the algebraization of the algebraic geometry through commutative algebra. The prominent results in this direction are Hilbert's basis theorem and Hilbert's N... | Algebraic Geometry | 0.813561 |
16,665 | By the end of the 19th century, projective geometers were studying more general kinds of transformations on figures in projective space. Rather than the projective linear transformations which were normally regarded as giving the fundamental Kleinian geometry on projective space, they concerned themselves also with the... | Algebraic Geometry | 0.813561 |
16,666 | It took the simultaneous 19th century developments of non-Euclidean geometry and Abelian integrals in order to bring the old algebraic ideas back into the geometrical fold. The first of these new developments was seized up by Edmond Laguerre and Arthur Cayley, who attempted to ascertain the generalized metric propertie... | Algebraic Geometry | 0.813561 |
16,667 | However, this is only a worst case complexity, and the complexity bound of Lazard's algorithm of 1979 may frequently apply. Faugère F5 algorithm realizes this complexity, as it may be viewed as an improvement of Lazard's 1979 algorithm. It follows that the best implementations allow one to compute almost routinely with... | Algebraic Geometry | 0.813561 |
16,668 | A Gröbner basis is a system of generators of a polynomial ideal whose computation allows the deduction of many properties of the affine algebraic variety defined by the ideal. Given an ideal I defining an algebraic set V: V is empty (over an algebraically closed extension of the basis field), if and only if the Gröbner... | Algebraic Geometry | 0.813561 |
16,669 | To understand the biological mechanisms which underlie the great importance of diatoms in geochemical cycles, scientists have used the Phaeodactylum tricornutum and Thalassiosira spp. species as model organisms since the 90's. Few molecular biology tools are currently available to generate mutants or transgenic lines: ... | Diatom morphology | 0.813559 |
16,670 | Diatoms, and their shells (frustules) as diatomite or diatomaceous earth, are important industrial resources used for fine polishing and liquid filtration. The complex structure of their microscopic shells has been proposed as a material for nanotechnology.Diatomite is considered to be a natural nano material and has m... | Diatom morphology | 0.813559 |
16,671 | The long-known function of the urea cycle in animals is to excrete excess nitrogen produced by amino acid catabolism; like photorespiration, the urea cycle had long been considered a waste pathway. However, in diatoms the urea cycle appears to play a role in exchange of nutrients between the mitochondria and the cytopl... | Diatom morphology | 0.813559 |
16,672 | The deposition of silica by diatoms may also prove to be of utility to nanotechnology. Diatom cells repeatedly and reliably manufacture valves of various shapes and sizes, potentially allowing diatoms to manufacture micro- or nano-scale structures which may be of use in a range of devices, including: optical systems; s... | Diatom morphology | 0.813559 |
16,673 | Planktonic diatoms in freshwater and marine environments typically exhibit a "boom and bust" (or "bloom and bust") lifestyle. When conditions in the upper mixed layer (nutrients and light) are favourable (as at the spring), their competitive edge and rapid growth rate enables them to dominate phytoplankton communities ... | Diatom morphology | 0.813559 |
16,674 | FASTpp measures the quantity of protein that resists digestion under various conditions. To this end, a thermostable protease is used, which cleaves specifically at exposed hydrophobic residues. The FASTpp assay combines the thermal unfolding, specificity of a thermostable protease for the unfolded fraction with the se... | Fast parallel proteolysis | 0.813554 |
16,675 | Proteolysis is widely used in biochemistry and cell biology to probe protein structure. In "limited trypsin proteolysis", low amounts of protease digest both folded and unfolded protein but at largely different rates: unstructured proteins are cut more rapidly, while structured proteins are cut at a slower rate (someti... | Fast parallel proteolysis | 0.813554 |
16,676 | The most important room is known as the "bridge", which contains a large statue of the Celestial Arishem and pattern-covered walls which generate the Eternals' suits; Eternals production designer Eve Stewart explained that the room was designed to look like mosques, synagogues, churches, and temples, and the set was co... | Mirror Dimension | 0.813554 |
16,677 | In the mathematical discipline of graph theory, a wheel graph is a graph formed by connecting a single universal vertex to all vertices of a cycle. A wheel graph with n vertices can also be defined as the 1-skeleton of an (n – 1)-gonal pyramid. Some authors write Wn to denote a wheel graph with n vertices (n ≥ 4); othe... | Wheel graph | 0.813553 |
16,678 | In around the 17th century physicians started to apply use methods to study traditional remedies, although they still lacked methods to test the hypotheses they had about how drugs worked.By the late 18th century and early 19th century, methods of experimental physiology and pharmacology began to be developed by scient... | Clinical pharmacology | 0.81355 |
16,679 | In a series of works, al-Rifaie et al. have successfully used two swarm intelligence algorithms—one mimicking the behaviour of one species of ants (Leptothorax acervorum) foraging (stochastic diffusion search, SDS) and the other algorithm mimicking the behaviour of birds flocking (particle swarm optimization, PSO)—to d... | Swarm intelligence | 0.81355 |
16,680 | Swarm grammars are swarms of stochastic grammars that can be evolved to describe complex properties such as found in art and architecture. These grammars interact as agents behaving according to rules of swarm intelligence. Such behavior can also suggest deep learning algorithms, in particular when mapping of such swar... | Swarm intelligence | 0.81355 |
16,681 | Self-propelled particles (SPP), also referred to as the Vicsek model, was introduced in 1995 by Vicsek et al. as a special case of the boids model introduced in 1986 by Reynolds. A swarm is modelled in SPP by a collection of particles that move with a constant speed but respond to a random perturbation by adopting at e... | Swarm intelligence | 0.81355 |
16,682 | In mathematics, a piecewise algebraic space is a generalization of a semialgebraic set, introduced by Maxim Kontsevich and Yan Soibelman. The motivation was for the proof of Deligne's conjecture on Hochschild cohomology. Robert Hardt, Pascal Lambrechts, Victor Turchin, and Ismar Volić later developed the theory. | Piecewise algebraic space | 0.813545 |
16,683 | For geometries, bond lengths can be predicted within a few picometers and bond angles within 0.5 degrees. The treatment of larger molecules that contain a few dozen atoms is computationally tractable by more approximate methods such as density functional theory (DFT). There is some dispute within the field whether or n... | Computational Chemistry | 0.813542 |
16,684 | Furthermore, cheminformatics uses even more empirical (and computationally cheaper) methods like machine learning based on physicochemical properties. One typical problem in cheminformatics is to predict the binding affinity of drug molecules to a given target. Other problems include predicting binding specificity, off... | Computational Chemistry | 0.813542 |
16,685 | Annual Reports in Computational Chemistry Computational and Theoretical Chemistry Computational and Theoretical Polymer Science Computers & Chemical Engineering Journal of Chemical Information and Modeling Journal of Chemical Information and Modeling Journal of Chemical Software Journal of Chemical Theory and Computati... | Computational Chemistry | 0.813542 |
16,686 | Semi-empirical quantum chemistry methods are based on the Hartree–Fock method formalism, but make many approximations and obtain some parameters from empirical data. They were very important in computational chemistry from the 60s to the 90s, especially for treating large molecules where the full Hartree–Fock method wi... | Computational Chemistry | 0.813542 |
16,687 | Computational studies, used to predict the possibility of so far entirely unknown molecules or to explore reaction mechanisms not readily studied via experiments.Thus, computational chemistry can assist the experimental chemist or it can challenge the experimental chemist to find entirely new chemical objects. Several ... | Computational Chemistry | 0.813541 |
16,688 | The term theoretical chemistry may be defined as a mathematical description of chemistry, whereas computational chemistry is usually used when a mathematical method is sufficiently well developed that it can be automated for implementation on a computer. In theoretical chemistry, chemists, physicists, and mathematician... | Computational Chemistry | 0.813541 |
16,689 | The stationary points of the surface lead to predictions of different isomers and the transition structures for conversion between isomers, but these can be determined without full knowledge of the complete surface. A particularly important objective, called computational thermochemistry, is to calculate thermochemical... | Computational Chemistry | 0.813541 |
16,690 | Here, the coefficients of the configurations, and of the basis functions, are optimized together. The total molecular energy can be evaluated as a function of the molecular geometry; in other words, the potential energy surface. Such a surface can be used for reaction dynamics. | Computational Chemistry | 0.813541 |
16,691 | The programs used in computational chemistry are based on many different quantum-chemical methods that solve the molecular Schrödinger equation associated with the molecular Hamiltonian. Methods that do not include any empirical or semi-empirical parameters in their equations – being derived directly from theoretical p... | Computational Chemistry | 0.813541 |
16,692 | Significant errors can present themselves in ab initio models comprising many electrons, due to the computational cost of full relativistic-inclusive methods. This complicates the study of molecules interacting with high atomic mass unit atoms, such as transitional metals and their catalytic properties. Present algorit... | Computational Chemistry | 0.813541 |
16,693 | Computational chemistry is not an exact description of real-life chemistry, as our mathematical models of the physical laws of nature can only provide us with an approximation. However, the majority of chemical phenomena can be described to a certain degree in a qualitative or approximate quantitative computational sch... | Computational Chemistry | 0.813541 |
16,694 | In principle, ab initio methods eventually converge to the exact solution of the underlying equations as the number of approximations is reduced. In practice, however, it is impossible to eliminate all approximations, and residual error inevitably remains. The goal of computational chemistry is to minimize this residua... | Computational Chemistry | 0.813541 |
16,695 | Computational chemistry methods range from very approximate to highly accurate; the latter is usually feasible for small systems only. Ab initio methods are based entirely on quantum mechanics and basic physical constants. Other methods are called empirical or semi-empirical because they use additional empirical parame... | Computational Chemistry | 0.813541 |
16,696 | Computational chemistry is a branch of chemistry that uses computer simulation to assist in solving chemical problems. It uses methods of theoretical chemistry, incorporated into computer programs, to calculate the structures and properties of molecules, groups of molecules, and solids. It is essential because, apart f... | Computational Chemistry | 0.813541 |
16,697 | Computational chemical methods can be applied to solid-state physics problems. The electronic structure of a crystal is in general described by a band structure, which defines the energies of electron orbitals for each point in the Brillouin zone. Ab initio and semi-empirical calculations yield orbital energies; theref... | Computational Chemistry | 0.813541 |
16,698 | (2011). Computational Chemistry. Heidelberg: Springer. Bibcode:2011coch.book.....L. doi:10.1007/978-90-481-3862-3. ISBN 978-90-481-3860-9. | Computational Chemistry | 0.813541 |
16,699 | D. Young Computational Chemistry: A Practical Guide for Applying Techniques to Real World Problems, John Wiley & Sons (2001). D. Young's Introduction to Computational Chemistry. Lewars, Errol G. | Computational Chemistry | 0.813541 |
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