A modified Hestenes–Stiefel conjugate gradient method with an optimal property

In this paper, based on the numerical efficiency of Hestenes–Stiefel (HS) method, a new modified HS algorithm is proposed for unconstrained optimization. The new direction independent of the line search satisfies in the sufficient descent condition. Motivated by theoretical and numerical features of three-term conjugate gradient (CG) methods proposed by Narushima et al., similar to Dai and Kou approach, the new direction is computed by minimizing the distance between the CG direction and the direction of the three-term CG methods proposed by Narushima et al. Under some mild conditions, we establish global convergence of the new method for general functions when the standard Wolfe line search is used. Numerical experiments on some test problems from the CUTEst collection are given to show the efficiency of the proposed method.     

New neural network-based response surface method for reliability analysis of structures

Neural Computing and Applications - In this paper, a new algorithm is introduced for reliability analysis of structures using response surface method based on a group method of data handling-type...     

Evaluation and prediction of flyrock resulting from blasting operations using empirical and computational methods

Mines, quarries and construction sites face environmental impacts, such as flyrock, due to blasting operations. Flyrock may cause damage to structures and injury to human. Therefore, flyrock prediction is required to determine safe blasting zone. In this regard, 232 blasting operations were investigated in five granite quarries, Malaysia. Blasting parameters comprising maximum charge per delay and powder factor were prepared to predict flyrock using empirical and intelligent methods. An empirical graph was proposed to predict flyrock distance for different powder factor values. In addition, using the same datasets, two intelligent systems, namely artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were used to predict flyrock. Considering some model performance indices including coefficient of determination (R ²), value account for and root mean squared error and also using simple ranking procedure, the best flyrock prediction models were selected. It was found that the ANFIS model can predict flyrock with higher performance capacity compared to ANN predictive model. R ² values of testing datasets are 0.925 and 0.964 for ANN and ANFIS techniques, respectively, suggesting the superiority of the ANFIS technique in predicting flyrock.     

Incorporation of Propionibacteria in Fermented Milks as a Probiotic

Propionibacteria are mainly found in dairy products and fermented milks but are found in other foods as well. Dairy propionibacteria have recently shown to exert potential probiotic activities such as production of propionic acid, vitamins, bacteriocins, essential enzymes, and other vital metabolites. Furthermore, stimulating the immune system and lowering the blood cholesterol level are some of their favorable effects. They have a wide spectrum of antimicrobial activities, inhibiting the growth of gram-positive and some gram-negative bacteria, as well as some yeasts and molds. At industrial scale, they are used in cheese making, especially Swiss (hard) cheeses, as dominant starter cultures. There is a rising trend to use propionibacteria in fermented milks as probiotic. The current paper reviews the characteristics of propionibacteria related to their use in fermented milks either as starter culture or probiotic, methods for the enumeration of propionibacteria, and their functional (in vivo) efficiency.     

Air pollution forecasting application based on deep learning model and optimization algorithm

Air pollution monitoring is constantly increasing, giving more and more attention to its consequences on human health. Since Nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) are the major pollutants, various models have been developed on predicting their potential damages. Nevertheless, providing precise predictions is almost impossible. In this study, a new hybrid intelligent model based on long short-term memory (LSTM) and multi-verse optimization algorithm (MVO) has been developed to predict and analysis the air pollution obtained from Combined Cycle Power Plants. In the proposed model, long short-term memory model is a forecaster engine to predict the amount of produced NO₂ and SO₂ by the Combined Cycle Power Plant, where the MVO algorithm is used to optimize the LSTM parameters in order to achieve a lower forecasting error. In addition, in order to evaluate the proposed model performance, the model has been applied using real data from a Combined Cycle Power Plant in Kerman, Iran. The datasets include wind speed, air temperature, NO₂, and SO₂ for five months (May–September 2019) with a time step of 3-h. In addition, the model has been tested based on two different types of input parameters: type (1) includes wind speed, air temperature, and different lagged values of the output variables (NO₂ and SO₂); type (2) includes just lagged values of the output variables (NO₂ and SO₂). The obtained results show that the proposed model has higher accuracy than other combined forecasting benchmark models (ENN-PSO, ENN-MVO, and LSTM-PSO) considering different network input variables.

Graphic abstract

     

Toxicological assessment of 3-monochloropropane-1,2-diol (3-MCPD) as a main contaminant of foodstuff in three different in vitro models: Involvement of oxidative stress and cell death signaling pathway

3-Monochloropropane-1,2-diol (3-MCPD) as a main source of food contamination has always been known as a carcinogenic agent. Kidney, liver, testis, and heart seem to be the main target organs for 3-MCPD. Because oxidative stress and mitochondrial dysfunction have been realized to be involved in 3-MCPD-induced cytotoxicity, the present study aimed to investigate the probable toxicity mechanisms of 3-MCPD in isolated mitochondria, HEK-293 cell line, and cell isolated from the rats’ liver and kidney through measuring multiparametric oxidative stress assay. Based on the data indicating no significant difference between 3-MCPD-treated groups and control group, metabolites of 3-MCPD have a key role in organ toxicity caused by them. To further investigating the suggested hypothesis, the effect of 3-MCPD toxicity on HEK-293 cell line was examined. Although the proliferation declined after exposure to a low dose of 3-MCPD (10 to 200 µM), controversial responses in higher concentration (2 to 10 mM) have led to studies on the effect of oxidative stress and cell death signaling on isolated kidney and liver cells. Treatment of the isolated kidney and liver cells with 3-MCPD resulted in an increase in the level of reactive oxygen species (ROS), the collapse of mitochondrial membrane potential (MMP), and activation of cell death signaling without creating any significant difference in the amount of reduced glutathione. In fact, 3-MCPD can disrupt the mitochondrial electron transfer in isolated cells, which is correlated with the impairment of mitochondrial oxidative phosphorylation system, the rise of ROS level, and the failure of MMP, leading to the release of cytochrome c from mitochondria to cytosol and finally the activation of cell death signaling.     

Numerical simulation of geometry effect on mixing performance in L-shaped micromixers

Abstract

This study accomplishes a numerical analysis of mixing in a microchannel with repeating L-shaped units in order to research the effect of the extension of L-shaped units in a three-dimensional (3D) space and the angle of repeating units on the process of mixing. In the first part, Geometry 2 and Geometry 3 are designed by extending the units of Geometry 1 in a 3D space. In the second part, an L-shaped micromixer, a 90° V-shaped micromixer, and a 60° V-shaped micromixer are analyzed. It is observed that Geometry 1 and Geometry 2 perform better than Geometry 3 in terms of mixing due to the spiral path with 360° rotation of the flow. The L-shaped micromixer is more efficient than the 90° and 60° V-shaped micromixers. A maximum mixing index of about 88% is achieved in all serpentine microchannels at the following Reynolds numbers: Re = 150 and Re = 200.     

Influence of Ag mid-layer in the optical and thermal properties of ZnO/Ag/ZnO thin films on the glass used in Buildings as insulating glass unit (IGU)

The low-emissivity (low-E) coatings are multiple ultra thin layers on glass used for producing spectrally selective glazing. The use of low-E glazing in building windows makes it possible limit the radiative heat transfer without reducing the visible transmittance perceptibly and accordingly alter the necessary natural lighting in low energy buildings. In this study, we investigate ZnO/Ag/ZnO thin films deposited on glass substrate via RF and DC sputtering by ZnO and Ag targets respectively, in various deposition time of Ag layer. We tried to diminish the NIR transmittance by using a feasible and affordable method with a low number of ultra thin layers and by reducing the cost of the vacuum.Presented results are related to electrical, optical and thermal properties for tri-layers based on sandwiched Ag by ZnO in deposition time of 10–45?s at room temperature.     

A de novo formulation of metformin using chitosan-based nanomicelles for potential diabetes therapy

A de novo formulation of metformin (MET) was developed through the physical loading of drug into a chitosan-grafted-[poly(acryl amide)-block-poly(acrylic acid)] [CS-g-(PAAm-b-PAA)] terpolymer. For this purpose, CS was functionazed with phthalic anhydride followed by 4-cyano, 4-[(phenylcarbothioyl)sulfanyl]pentanoic acid to produc a macro-RAFT agent (CS-CTA). Afterward, acryl amide and acrylic acid monomers were graft and block copolymerized onto the synthesized CS-CTA through a reversible addition–fragmentation chain transfer (RAFT) polymerization technique to afford CS-g-PAAm copolymer and CS-g-(PAAm-b-PAA) terpolymer, respectively. The fabricated CS-g-(PAAm-b-PAA) terpolymer was loaded with MET as an anti-diabetic drug, and its drug release behavior was evaluated in the body simulated environment. As results, it was concluded that the fabricated CS-g-(PAAm-b-PAA) nanosystem has high potential as de novo drug delivery system (DDS) for diabetes therapy, mainly due to controlled drug release profile in comparison with conventional formulations of MET. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48037.