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A memristor (/ ˈ m ɛ m r ɪ s t ər /; a portmanteau of memory resistor) is a non-linear two-terminal electrical component relating electric charge and magnetic flux linkage.It was described and named in 1971 by Leon Chua, completing a theoretical quartet of fundamental electrical components which also comprises the resistor, capacitor and inductor.
In one of the technical reports [3] the memistor was described as follows: . Like the transistor, the memistor is a 3-terminal element. The conductance between two of the terminals is controlled by the time integral of the current in the third, rather than its instantaneous value as in the transistor.
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'.
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 .
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 mnemonic is a memory aid used to improve long-term memory and make the process of consolidation easier. Many chemistry aspects, rules, names of compounds, sequences of elements, their reactivity, etc., can be easily and efficiently memorized with the help of mnemonics.
A biological systems engineer will often address the solution to a problem from the perspective of employing living systems to enact change. For example, biological treatment methodologies can be applied to provide access to clean drinking water [7] or for sequestration of carbon dioxide. [8]
These types of devices would allow for a synapse model that could realise a learning rule, by which the synaptic efficacy is altered by voltages applied to the terminals of the device. An example of such a learning rule is spike-timing-dependant-plasticty by which the weight of the synapse, in this case the conductivity, could be modulated ...