Dynabeads protein G antibody conjugates combined with modified brain heart infusion broth for the enrichment and separation of Bacillus cereus in artificially contaminated vegetables

Food Science and Biotechnology - A modified brain heart infusion (MBHI) broth and a protocol of immunomagnetic separation (IMS) using antibody-coated Dynabeads® protein G were developed for...     

Characterization of metal pollution in soils under two landuse patterns in the Angouran region, NW Iran; a study based on multivariate data analysis

The study presents the application of selected multivariate statistical methods (multivariate analysis of variance, discriminant analysis, principal component analysis) and geostatistical techniques to evaluate soil pollution status in arable lands of the Angouran region, NW Iran. Two representative landuse patterns, cropland and grassland, were selected for the purpose of this study. Seventy soil samples (35 topsoils and 35 subsoils) were collected from the two landuse types and 21 soil parameters including total element content and physicochemical properties were also determined. Results from application of the multivariate analysis of variance showed that the two landuse patterns were not statistically differentiated by subsoil variables, whereas significant differences existed between the two landuse patterns with respect to topsoil variables. Discriminant analysis rendered seven variables (Cu, As, Cd, OM, P, K and total N) as indicator parameters responsible for the discrimination between the two landuse types. Using the principal component analysis (PCA), two main components (PCs) explaining 71.71% of total variance were extracted. PC1, with a high contribution of Ni, Cr, Fe, Mn and clay content was hypothesized as lithogenic component and PC2, with high loadings for the seven discerning variables (Cu, As, Cd, OM, P, K and total N), was considered as an agrogenic component. Geostatistical analyses, including the calculation of semivariogram parameters and model fitting, further supported the PCA results. PC1 was generally characterized by moderate spatial dependence and long-range spatial variation (8000 m) influenced by soil parent martial composition, while PC2 was modelled by pure nugget effect probably reflecting the influences of agrogenic activities. The findings of this study could not only expand our knowledge regarding the soil pollution status in the study area, but would also provide decision makers with the information to manage the agrochemical application in the arable lands to improve the sustainability and safety of intensive-farming activities in the study area.     

A new method for online identification of civil structures: Virtual synchronization

This paper presents a new approach, named Virtual Synchronization Method (VSM), for online identification of stiffness and viscous damping in a civil structure while it is subjected to a harmonic ground motion acceleration. It is assumed that displacement and velocity of the structure relative to the ground are measured in real time. They are used to define a virtual system similar to the actual structure. Proper controllers and estimation functions are designed to force the states of this virtual system to follow those of the actual structure. Theoretical results are derived to study on what conditions, after the two systems synchronized, the estimation functions converge to the true stiffness and damping of the actual structure. Provided numerical examples show that VSM is a promising method for online identification of civil structures and should be the subject of further studies.     

Ultrasonication enhanced low concentration electrolyzed water efficacy on bacteria inactivation and shelf life extension on lettuce

Effect of ultrasonication (40 kHz) to enhance low concentration electrolyzed water (LcEW) efficacy for microbial decontamination on lettuce leaves was investigated. Lettuce was separately treated with LcEW, ultrasonication, LcEW combined with ultrasonication, LcEW followed by ultrasonication, and ultrasonication followed by LcEW for 1, 3, and 5 min for each step at room temperature. The highest reduction (2.3 log CFU/g) in total bacteria count (TBC) was resulted from ultrasonication followed by LcEW. Subsequently, the effect of temperature was studied resulting in 2.6 and 3.18 log CFU/g reduction of TBC and Escherichia coli O157:H7 respectively, in 3 min ultrasonication followed by 3 min LcEW treatment at 40°C. This optimum treatment also prevented lettuce from reaching 7.0 log CFU/g in TBC until the end of the 6 day storage at 10°C. Therefore, this newly developed approach may result in improved microbiological safety and enhanced shelf life of produce.     

Robust Support Vector Machines with Low Test Time

The robust support vector machines (RoSVM) for ellipsoidal data is difficult to solve. To overcome this difficulty, its primal form has been approximated with a second‐order cone programming (SOCP) called approximate primal RoSVM. In this article, we show that the primal RoSVM is equivalent to an SOCP and name it accurate primal RoSVM. The optimal weight vector of this model is not sparse necessarily. The sparser the weight vector, the less time the test phase takes. Hence, to reduce the test time, first, we obtain its dual form and then prove the sparsity of its optimal solution. Second, we show that some parts of the optimal decision function can be computed in the training phase instead of the test phase. This can decrease the test time further. However, training time of the dual model is more than that of the primal model, but the test time is often more critical than the training time because the training is often an off‐line procedure while the test procedure is performed online. Experimental results on benchmark data sets show the superiority of the proposed models.     

Increasing the speed of fuzzy k‐nearest neighbours algorithm

Fuzzy k‐nearest neighbour (FKNN) is one of the most convenient classification approaches. The main challenge of this method is associated with finding the optimal values of its two hyperparameters. The present study attempts to decrease the running time of this approach by reducing the number of its hyperparameters through omitting the hyperparameter k. In the training phase of FKNN approach, the membership degree of each training data is refined by crisp KNN voting whereas a fuzzy voting is used in the training phase of our proposed approach. Training and test phases time complexities of our proposed approach are better than those of FKNN approach. The experiments on real data sets indicate that the accuracy of our proposed approach called ultra FKNN is higher than FKNN approach due to applying fuzzy voting instead of crisp voting in training phase. In addition, the training, test, and running time of our proposed approach are considerably less than those of FKNN.     

Microstructural characteristics and second-phase particles in yttrium-bearing Fe-10Ni-7Mn martensitic steels

In this study, the microstructure and second-phase particles in yttrium （0.05 wt.%and 0.8 wt.%） bearing Fe-10Ni-7Mn steels were characterized. The results of X-ray analysis as well as scanning electron microscopy coupled with energy dispersive X-ray spectroscopy indicated the formation of （Fe, Ni, Mn）17Y2 precipitates with hexagonal structure in a Fe-10Ni-7Mn-0.8Y （wt.%） alloy. Lattice parameters of these precipitates were calculated as follows：a=0.8485 nm and c=0.8274 nm. Formation of Y2O3 sub-micron particles was also confirmed in both yttrium bearing steels via electrolytic phase extraction method. The effect of these precipitates on the prior austenite grain size was investigated. The results revealed that these precipitates had an effective role in controlling the prior austenite grain size.     

Optimal control of structures under earthquake excitation based on the colonial competitive algorithm

The active control of engineering structures is one of the best methods to reduce structural responses under seismic excitation for the best performance of structures. This study presents an effective approach for the optimal control of structures under strong ground motion using the colonial competitive algorithm. The colonial competitive algorithm was developed over the last few years in an attempt to overcome the inherent limitations of traditional optimize method. The colonial competitive algorithm has been applied due to its ideal performance in optimal control problem. The effectiveness and performance of the proposed method have been investigated through two numerical examples for the response control of earthquake‐excited structures. The obtained results have been compared with the Linear Quadratic Regulator (LQR) control algorithm, and the performance of the proposed control approach has been found to be better than the LQR controller. Copyright © 2012 John Wiley & Sons, Ltd.     

Enhancement of gasoline production in a novel hydrogen-permselective membrane reactor in Fischer–Tropsch synthesis of GTL technology

In this work a novel reactor configuration with hydrogen-permselective membrane is proposed for Fischer–Tropsch synthesis. In this configuration the synthesis gas is fed to the tube side and flows in co-current mode with reacting gas mixture that enters in the shell side of the reactor. In this way, the synthesis gas is heated by heat of reaction which is produced in the reaction side. Hydrogen can penetrate from the feed synthesis gas side into the reaction side as a result of a hydrogen partial pressure difference. The outlet synthesis gas from tube side is recycled to shells and the chemical reaction is initiated in catalytic bed. Therefore, the reacting gas in shell side is cooled simultaneously with passing gas in tube and saturated water in outer shell. In this study, the results of novel membrane reactor (MR) are compared with a conventional Fischer–Tropsch synthesis reactor (CR) at identical process conditions in terms of temperature, gasoline and CO₂ yields, H₂ and CO conversion as well as selectivity.This novel membrane Fischer–Tropsch reactor improves the selectivity of hydrogenation with hydrogen passing through membrane and increases production of high octane gasoline from synthesis gas on bifunctional Fe-HZSM5 catalyst. The model was checked against conventional Fischer–Tropsch synthesis reactor (CR) in pilot plant of Research Institute of Petroleum Industry. Simulation results show 4.45% enhancement in the yield of gasoline production, 6.16% decrease in the undesired product formations, and a favorable temperature profile along the membrane Fischer–Tropsch reactor in comparison with conventional reactor.