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The switching behavior of individual non-volatile memory devices thus cannot be described within the mathematical framework proposed for memristor/memristive systems. An extra thermodynamic curiosity arises from the definition that memristors/memristive devices should energetically act like resistors.
An example of a bio-MEMS device is this automated FISH microchip, which integrates a reagent multiplexer, a cell chamber with a thin-film heater layer, and a peristaltic pump. [1] Bio-MEMS is an abbreviation for biomedical (or biological) microelectromechanical systems.
While the memristor is defined in terms of a two-terminal circuit element, there was an implementation of a three-terminal device called a memistor developed by Bernard Widrow in 1960. Memistors formed basic components of a neural network architecture called ADALINE developed by Widrow. [1] [2] The memistor was also used in MADALINE.
An early example of a MEMS device is the resonant-gate transistor, an adaptation of the MOSFET, developed by Robert A. Wickstrom for Harvey C. Nathanson in 1965. [4] Another early example is the resonistor, an electromechanical monolithic resonator patented by Raymond J. Wilfinger between 1966 and 1971.
Systems biology can be considered from a number of different aspects. As a field of study, particularly, the study of the interactions between the components of biological systems, and how these interactions give rise to the function and behavior of that system (for example, the enzymes and metabolites in a metabolic pathway or the heart beats).
A ribosome is a biological machine that utilizes protein dynamics. At the first C.E.C. Workshop, in Brussels in November 1991, bioelectronics was defined as 'the use of biological materials and biological architectures for information processing systems and new devices'.
Neuromorphic engineering is an interdisciplinary subject that takes inspiration from biology, physics, mathematics, computer science, and electronic engineering [4] to design artificial neural systems, such as vision systems, head-eye systems, auditory processors, and autonomous robots, whose physical architecture and design principles are ...
Modelling biological systems is a significant task of systems biology and mathematical biology. [ a ] Computational systems biology [ b ] [ 1 ] aims to develop and use efficient algorithms , data structures , visualization and communication tools with the goal of computer modelling of biological systems.