Loop optimizationIn compiler theory, loop optimization is the process of increasing execution speed and reducing the overheads associated with loops. It plays an important role in improving cache performance and making effective use of parallel processing capabilities. Most execution time of a scientific program is spent on loops; as such, many compiler optimization techniques have been developed to make them faster. Since instructions inside loops can be executed repeatedly, it is frequently not possible to give a bound on the number of instruction executions that will be impacted by a loop optimization.
Enteric nervous systemThe enteric nervous system (ENS) or intrinsic nervous system is one of the main divisions of the autonomic nervous system (ANS) and consists of a mesh-like system of neurons that governs the function of the gastrointestinal tract. It is capable of acting independently of the sympathetic and parasympathetic nervous systems, although it may be influenced by them. The ENS is nicknamed the "second brain". It is derived from neural crest cells.
NeurostimulationNeurostimulation is the purposeful modulation of the nervous system's activity using invasive (e.g. microelectrodes) or non-invasive means (e.g. transcranial magnetic stimulation or transcranial electric stimulation, tES, such as tDCS or transcranial alternating current stimulation, tACS). Neurostimulation usually refers to the electromagnetic approaches to neuromodulation.
Nervous systemIn biology, the nervous system is the highly complex part of an animal that coordinates its actions and sensory information by transmitting signals to and from different parts of its body. The nervous system detects environmental changes that impact the body, then works in tandem with the endocrine system to respond to such events. Nervous tissue first arose in wormlike organisms about 550 to 600 million years ago. In vertebrates it consists of two main parts, the central nervous system (CNS) and the peripheral nervous system (PNS).
Computational chemistryComputational 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 from relatively recent results concerning the hydrogen molecular ion (dihydrogen cation, see references therein for more details), the quantum many-body problem cannot be solved analytically, much less in closed form.
Computational economicsComputational Economics is an interdisciplinary research discipline that involves computer science, economics, and management science. This subject encompasses computational modeling of economic systems. Some of these areas are unique, while others established areas of economics by allowing robust data analytics and solutions of problems that would be arduous to research without computers and associated numerical methods.
Cranial nervesCranial nerves are the nerves that emerge directly from the brain (including the brainstem), of which there are conventionally considered twelve pairs. Cranial nerves relay information between the brain and parts of the body, primarily to and from regions of the head and neck, including the special senses of vision, taste, smell, and hearing. The cranial nerves emerge from the central nervous system above the level of the first vertebra of the vertebral column. Each cranial nerve is paired and is present on both sides.
Computational neuroscienceComputational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematical models, computer simulations, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system. Computational neuroscience employs computational simulations to validate and solve mathematical models, and so can be seen as a sub-field of theoretical neuroscience; however, the two fields are often synonymous.
Evolutionary algorithmIn computational intelligence (CI), an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses mechanisms inspired by biological evolution, such as reproduction, mutation, recombination, and selection. Candidate solutions to the optimization problem play the role of individuals in a population, and the fitness function determines the quality of the solutions (see also loss function).
Object code optimizerAn object code optimizer, sometimes also known as a post pass optimizer or, for small sections of code, peephole optimizer, forms part of a software compiler. It takes the output from the source language compile step - the object code or - and tries to replace identifiable sections of the code with replacement code that is more algorithmically efficient (usually improved speed). The earliest "COBOL Optimizer" was developed by Capex Corporation in the mid 1970s for COBOL.
