MAPPING THE BCPNN LEARNING RULE TO A MEMRISTOR MODEL

Mapping the BCPNN Learning Rule to a Memristor Model

The Bayesian Confidence Propagation Neural Network (BCPNN) has been implemented in a way that allows mapping to neural and synaptic processes in the human cortexandhas been used extensively in detailed spiking models of cortical associative memory function and recently also for machine learning applications.In conventional digital implementations o

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Sulforaphane exposure impairs contractility and mitochondrial function in three-dimensional engineered heart tissue

Sulforaphane (SFN) is a phytochemical compound extracted from cruciferous plants, like broccoli or cauliflower.Its isothiocyanate group renders SFN reactive, thus allowing post-translational modification of cellular proteins to regulate their function with the potential for biological and therapeutic actions.SFN and stabilized variants recently rec

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Transcriptional portrait of Actinobacillus pleuropneumoniae during acute disease--potential strategies for survival and persistence in the host.

BACKGROUND: Gene expression profiles of bacteria in their natural hosts can provide novel insight into the host-pathogen interactions and molecular determinants of bacterial infections.In the present study, the transcriptional profile of the porcine lung pathogen Actinobacillus pleuropneumoniae was monitored during the acute phase of infection in i

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Development and validation of a postgraduate anaesthesiology core curriculum based on Entrustable Professional Activities: a Delphi study

Background: Postgraduate training curricula should not be based on time-spans or predefined numbers of performed procedures.One approach to link competencies to clinical tasks is the concept of Entrustable Professional Activities (EPA).The goal of this study was the definition, Extension Leads ranking and validation of EPAs for anaesthesiology post

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