Properties and applications of β‐glycosidase from Bacteroides thetaiotaomicron that specifically hydrolyses isoflavone glycosides

To modify the glycan part of glycosides, the gene encoding β‐glycosidase was cloned from Bacteroides thetaiotaomicron VPI‐5482. The cloned gene, bt_1780, was expressed in Escherichia coli MC1061 and the expressed enzyme was purified using Ni‐NTA affinity chromatography. The purified enzyme, BTBG, showed optimal activity at 50 °C and pH 5.5. Interestingly, this enzyme did not have any hydrolysing activity on ordinary β‐linkage–containing substrates such as xylobiose, lactose and cello‐oligosaccharide, but specifically hydrolysed isoflavone glycosides such as daidzin, genistin and glycitin. Compared to a commercial beta glucosidase, BTBG selectively hydrolysed isoflavone glycosides in soybean extract mixture solution. These results suggest that BTBG may be a specialized enzyme for the hydrolysis of glycosides and that the substrate specificity of BTBG is applicable for the bioconversion of isoflavone glycosides in the food industry.     

Effects of breed and age at slaughter on degradation of muscle lipids during processing of dry‐cured hams

Hams from Landrace, Duroc and Hampshire pigs slaughtered at ages 6, 7.5 and 9 months were processed to generate Norwegian Parma‐style hams. Lipid contents and the compositions of fatty acid classes (ΣSFA, ΣMUFA, ΣPUFA) within neutral lipids, phospholipids and free fatty acids were determined. Small differences in lipid degradation and composition of the classes were revealed. However, significant sensory differences related to lipids were observed. Breed was more important than age. Dry‐cured Hampshire hams gave a more intense mature odour that may be associated with higher overall lipid degradation. Unexpectedly, these hams also demonstrated high juiciness and tenderness, which could be related to the melting characteristics of the fat. Dry‐cured Duroc hams showed a higher susceptibility towards rancidity, presumably associated with preferential oxidation of n‐6 fatty acids relative to C18:1 n‐9. Dry‐cured Landrace hams showed the lowest juiciness and tenderness, likely due to their lower fat content (marbling).     

Physical Stability of Octenyl Succinate–Modified Polysaccharides and Whey Proteins for Potential Use as Bioactive Carriers in Food Systems

The high cost and potential toxicity of biodegradable polymers like poly(lactic‐co‐glycolic)acid (PLGA) has increased the interest in natural and modified biopolymers as bioactive carriers. This study characterized the physical stability (water sorption and state transition behavior) of selected starch and proteins: octenyl succinate–modified depolymerized waxy corn starch (DWxCn), waxy rice starch (DWxRc), phytoglycogen, whey protein concentrate (80%, WPC), whey protein isolate (WPI), and α‐lactalbumin (α‐L) to determine their potential as carriers of bioactive compounds under different environmental conditions. After enzyme modification and particle size characterization, glass transition temperature and moisture isotherms were used to characterize the systems. DWxCn and DWxRc had increased water sorption compared to native starch. The level of octenyl succinate anhydrate (OSA) modification (3% and 7%) did not reduce the water sorption of the DWxCn and phytoglycogen samples. The Guggenheim–Andersen–de Boer model indicated that native waxy corn had significantly (P < 0.05) higher water monolayer capacity followed by 3%‐OSA‐modified DWxCn, WPI, 3%‐OSA‐modified DWxRc, α‐L, and native phytoglycogen. WPC had significantly lower water monolayer capacity. All Tg values matched with the solid‐like appearance of the biopolymers. Native polysaccharides and whey proteins had higher glass transition temperature (Tg) values. On the other hand, depolymerized waxy starches at 7%‐OSA modification had a “melted” appearance when exposed to environments with high relative humidity (above 70%) after 10 days at 23 °C. The use of depolymerized and OSA‐modified polysaccharides blended with proteins created more stable blends of biopolymers. Hence, this biopolymer would be suitable for materials exposed to high humidity environments in food applications.     

Experimental and numerical analysis of the influence of cable tray arrangements on the resulting mass loss rate and fire spreading

In the context of industrial buildings and power plants, electrical installations and cable trays represent a main fuel load and a potential initial fire source due to possible short circuits or comparable malfunction. Furthermore, a fire can spread from one tray to additional trays mounted above and/or horizontally on one tray. Because of the high significance of cable fires, several research projects have been carried out, investigating the fire behaviour of cables from small‐scale tests, eg, the cone calorimeter, up to large‐scale tests, analysing complete cable tray constructions. The goal of the work presented in this paper is the extension of the knowledge regarding the influence of geometrical parameters like the packing density and tray distance on the burning behaviour and fire spread of cable tray installations. The results are considered, together with test results from the literature, to quantify the main physical parameters describing the burning behaviour. In a next step, the general applicability of these parameters as input data for the parametrization of the source term of numerical simulations is shown. The test results show that the burning behaviour and the fire spreading highly depend on the cable arrangement of the cables on the cable tray, in combination with other boundary conditions. By applying the results as input for a fire simulation, the mass loss rate is considered appropriately.     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.