Physicochemical stability of antilisterial proteins from P. polymyxa Kp10 as potential food biopreservative

Listeria monocytogenes has continuously become a significant threat to consumers worldwide. The use of chemical-derived preservatives that are commonly associated with safety and nutritional issues has prompted the use of natural-based preservatives as a better alternative. Many bacterial strains including Paenibacillus polymyxa Kp10 have been reported to produce various antimicrobial proteins and compounds that are considered more natural. However, their stability in various physicochemical conditions should be examined before being applied in various types of food. In this study, the stability of four previously identified antilisterial proteins in P. polymyxa Kp10 upon exposure to several physicochemical conditions was examined. More than 80% residual antilisterial activity is conserved upon heat and proteinase K treatment. But, sensitivity to 24 h trypsin digestion has been observed. P1 and P2 proteins (histone-like DNA binding proteins HU) were sensitive to alkaline pH (pH 10-12) as compared with other proteins. More than 70% and 97% residual antilisterial activity were recovered after incubation in raw beef homogenates and simulated meat gravy model, respectively. However, the antilisterial activity of most proteins was highly compromised in chicken and salmon meat homogenates, and UHT cow milk. Inoculation of these proteins into Listeria-contaminated simulated meat gravy showed that all proteins exerted a bactericidal action against L. monocytogenes. P1 and P2 shared almost similar antilisterial activity rates, while P4 was the most potent antilisterial protein. The findings in this study could provide important preliminary data for future applications of these proteins as preservative in food products especially beef-based meat products.     

On optimal control of mean-field stochastic systems driven by Teugels martingales via derivative with respect to measures

ABSTRACT

This paper deals with partial information stochastic optimal control problem for general controlled mean-field systems driven by Teugels martingales associated with some Lévy process having moments of all orders, and an independent Brownian motion. The coefficients of the system depend on the state of the solution process as well as of its probability law and the control variable. We establish a set of necessary conditions in the form of Pontryagin maximum principle for the optimal control. We also give additional conditions, under which the necessary optimality conditions turn out to be sufficient. The proof of our result is based on the derivative with respect to the probability law by applying Lions derivatives and a corresponding Itô formula. As an application, conditional mean-variance portfolio selection problem in incomplete market, where the system is governed by some Gamma process is studied to illustrate our theoretical results.     

A self-immune to 3D masks attacks face recognition system

Due to their advantages, facial recognition systems are among the most widely used biometric systems in recent years. However, their drawback is that they can easily be deceived by using 3D masks, which are replicas of real faces. To confirm this fact, we have tested the vulnerability to 3D masks attacks of the already approved Legendre moments invariants (LMI)-based face recognition method. This has been achieved by using the 3D mask attack database (3DMAD), which consists of real faces and faces with 3D masks. The obtained spoof false acceptance rate (SFAR) was close to 65%, which proves that this recognition system is vulnerable to 3D masks attacks. This is generally the case of other face recognition systems, with no anti-spoofing provision. In this paper, a face recognition method is proposed to prevent hackers from deceiving face recognition systems by using 3D masks of people belonging to the system database. This method combines the LMI and the linear discriminant analysis for characteristic features extraction, and the maximum likelihood for classification. With a 97.6% recognition rate and a SFAR equal to 0.83%, the results obtained may be considered as very satisfactory. These results, while obtained with a lower computational time, compare favorably with those of the state-of-the-art method that uses the same 3DMAD database.     

Experimental Investigation on the Effect of Tool Rotational Speed on Mechanical Properties of AA6082-T6 Friction Stir-Welded Butt Joints

Journal of Failure Analysis and Prevention - In this study, the effect of tool rotational speed on mechanical properties of AA 6082-T6 aluminum alloy was investigated. Different welded joints were...     

Performance of Gradient-Based Optimizer for Optimum Wind Cube Design

Renewable energy is a safe and limitless energy source that can be utilized for heating, cooling, and other purposes. Wind energy is one of the most important renewable energy sources. Power fluctuation of wind turbines occurs due to variation of wind velocity. A wind cube is used to decrease power fluctuation and increase the wind turbine’s power. The optimum design for a wind cube is the main contribution of this work. The decisive design parameters used to optimize the wind cube are its inner and outer radius, the roughness factor, and the height of the wind turbine hub. A Gradient-Based Optimizer (GBO) is used as a new metaheuristic algorithm in this problem. The objective function of this research includes two parts: the first part is to minimize the probability of generated energy loss, and the second is to minimize the cost of the wind turbine and wind cube. The Gradient-Based Optimizer (GBO) is applied to optimize the variables of two wind turbine types and the design of the wind cube. The metrological data of the Red Sea governorate of Egypt is used as a case study for this analysis. Based on the results, the optimum design of a wind cube is achieved, and an improvement in energy produced from the wind turbine with a wind cube will be compared with energy generated without a wind cube. The energy generated from a wind turbine with the optimized cube is more than 20 times that of a wind turbine without a wind cube for all cases studied.     

Correction to: Automatic COVID-19 detection mechanisms and approaches from medical images: a systematic review

Multimedia Tools and Applications -     

An Enhanced Cooperative Communication Scheme for Physical Uplink Shared Channel in NB-IoT

Wireless Personal Communications - Smart Home is one of the most established applications of the Internet of Things. Almost every equipment we use in our daily life—appliances, electric...     

Chemometric Characterization of Eight Monovarietal Algerian Virgin Olive Oils

Differences in triacylglycerol, fatty acid, squalene, and tocopherol compositions were demonstrated between 8 varieties of virgin olive oils (Aberkane, Aguenaou, Aharoun, Aimel, Bouchouk Guergour, Bouichret, Chemlal, and Sigoise) from Petite Kabylie area, north eastern Algeria. Fatty acid and triacylglycerol morphotypes characterized each variety. A principal component analysis, based on triacylglycerol, fatty acid, and squalene compositions, differentiates between varieties. Minor fatty acids and squalene, usually not taken into account individually in authentication studies, are strongly involved in this differentiation, whereas the discriminant power of tocopherols is weak. Soft Independent Modeling of Class Analogy classification using chemical compositions as variables showed a high potential to authenticate the varietal origin of Algerian virgin olive oils.     

Photocatalytic degradation of agricultural N-heterocyclic organic pollutants using immobilized nanoparticles of titania

Degradation and mineralization of two agricultural organic pollutants (Diazinon and Imidacloprid as N-heterocyclic aromatics) in aqueous solution by nanophotocatalysis using immobilized titania nanoparticles were investigated. Insecticides, Diazinon and Imidacloprid, are persistent pollutants in agricultural soil and watercourses. A simple and effective method was developed to immobilization of titania nanoparticles. UV-vis, ion chromatography (IC) and chemical oxygen demand (COD) analyses were employed. The effects of operational parameters such as H(2)O(2) and inorganic anions (NO(3)(-), Cl(-) and SO(4)(2-)) were investigated. The mineralization of Diazinon and Imidacloprid was evaluated by monitoring of the formed inorganic anions. The selected pollutants are effectively degraded following first order kinetics model. Results show that the nanophotocatalysis using immobilized titania nanoparticle is an effective method for treatment Diazinon and Imidacloprid from contaminated water.