An Intelligent Decision Support System for the Detection of Meat Spoilage using Multispectral Images

In food industry, quality and safety are considered important issues worldwide that are directly related to health and social progress. The use of vision technology for quality testing of food production has the obvious advantage of being able to continuously monitor a production using non-destructive methods, thus increasing the quality and minimizing cost. The performance of an intelligent decision support system has been evaluated in monitoring the spoilage of minced beef stored either aerobically or under modified atmosphere packaging, at different storage temperatures (0, 5, 10, and 15 °C) utilising multispectral imaging information. This paper utilises a neuro-fuzzy model which incorporates a clustering pre-processing stage for the definition of fuzzy rules, while its final fuzzy rule base is determined by competitive learning. Initially, meat samples are classified according to their storage conditions, while identification models are then utilised for the prediction of the Total Viable Counts of bacteria. The innovation of the proposed approach is further extended to the identification of the temperature used for storage, utilizing only imaging spectral information. Results indicated that spectral information in combination with the proposed modelling scheme could be considered as an alternative methodology for the accurate evaluation of meat spoilage

Time-optimal Hamiltonian simulation and gate synthesis using homogeneous local unitaries

Motivated by experimental limitations commonly met in the design of solid state quantum computers, we study the problems of non-local Hamiltonian simulation and non-local gate synthesis when only homogeneous local unitaries are performed in order to tailor the available interaction. Homogeneous (i.e. identical for all subsystems) local manipulation implies a more refined classification of interaction Hamiltonians than the inhomogeneous case, as well as the loss of universality in Hamiltonian simulation. For the case of symmetric two-qubit interactions, we provide time-optimal protocols for both Hamiltonian simulation and gate synthesis

Glucagon-like peptide I increases cytoplasmic calcium in insulin-secreting beta TC3-cells by enhancement of intracellular calcium mobilization.

In the insulin-secreting beta-cell line beta TC3, stimulation with 11.2 mmol/l glucose caused a rise in the intracellular free Ca2+ concentration ([Ca2+]i) in only 18% of the tested cells. The number of glucose-responsive cells increased after pretreatment of the cells with glucagon-like peptide I (GLP-I)(7-36)amide and at 10(-11) mol/l; 84% of the cells responded to glucose with a rise in [Ca2+]i. GLP-I(7-36)amide induces a rapid increase in [Ca2+]i only in cells exposed to elevated glucose concentrations (> or = 5.6 mmol/l). The action of GLP-I(7-36)amide and forskolin involved a 10-fold increase in cytoplasmic cAMP concentration and was mediated by activation of protein kinase A. It was not associated with an effect on the membrane potential but required some (small) initial entry of Ca2+ through voltage-dependent L-type Ca2+ channels, which then produced a further increase in [Ca2+]i by mobilization from intracellular stores. The latter effect reflected Ca(2+)-induced Ca2+ release and was blocked by ryanodine. Similar increases in [Ca2+]i were also observed in voltage-clamped cells, although there was neither activation of a background (Ca(2+)-permeable) inward current nor enhancement of the voltage-dependent L-type Ca2+ current. These observations are consistent with GLP-I(7-36) amide inducing glucose sensitivity by promoting mobilization of Ca2+ from intracellular stores. We propose that this novel action of GLP-I(7-36)amide represents an important factor contributing to its insulinotropic action