Improvements and limitation of soy protein-based adhesive: A review

Soy protein is known for its eco-friendly, sustainable, and biodegradable qualities that are likely used as raw material in producing bioadhesive. However, soy protein-based adhesive are lacking in terms of adhesive strength and water-resistance compared to commercial formaldehyde-based adhesives such as phenol and urea-formaldehyde resin. Therefore, continuous research has been done to improve adhesive performance. This can be done via physical or modification methods, including the usage of cross-linking agents, structural modification, enzymatic modification, and the addition of additives. This review will cover these modification methods that give significant enhancement to the water-resistance and adhesive strength of soy protein-based adhesives.     

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.     

Electro-osmotic flow of fractional second-grade fluid with fractional Cattaneo heat flux through a vertical microchannel

This study investigates the unsteady electro-osmotic flow (EOF) of a fractional second-grade fluid through a vertical microchannel with convection heat transfer. The fractional Cattaneo heat flux model will be used to modify the heat equation. The solutions for the velocity and the temperature have been derived by employing the Laplace and finite Fourier sine transforms and their numerical inverses. The results show that at the beginning of the time period, the fractional parameter postpones the movement of the fluid. Furthermore, the results show that at the high values of retardation time (non-Newtonian case), the required time for the velocity and the flow rate to reach the steady state increases. Moreover, the heat relaxation time reduces the heat transfer until a critical time, and then the effect reverses.     

NS-2 based simulation framework for cognitive radio sensor networks

In this paper, we propose a simulation model for cognitive radio sensor networks (CRSNs) which is an attempt to combine the useful properties of wireless sensor networks and cognitive radio networks. The existing simulation models for cognitive radios cannot be extended for this purpose as they do not consider the strict energy constraint in wireless sensor networks. Our proposed model considers the limited energy available for wireless sensor nodes that constrain the spectrum sensing process—an unavoidable operation in cognitive radios. Our model has been thoroughly tested by performing experiments in different scenarios of CRSNs. The results generated by the model have been found accurate which can be considered for realization of CRSNs.     

Neuro-adaptive cooperative tracking control with prescribed performance of unknown higher-order nonlinear multi-agent systems

This paper is concerned with the design of a distributed cooperative synchronisation controller for a class of higher-order nonlinear multi-agent systems. The objective is to achieve synchronisation and satisfy a predefined time-based performance. Dynamics of the agents (also called the nodes) are assumed to be unknown to the controller and are estimated using neural networks. The proposed robust neuro-adaptive controller drives different states of nodes systematically to synchronise with the state of the leader node within the constraints of the prescribed performance. The nodes are connected through a weighted directed graph with a time-invariant topology. Only few nodes have access to the leader. Lyapunov-based stability proofs demonstrate that the multi-agent system is uniformly ultimately bounded stable. Highly nonlinear heterogeneous networked systems with uncertain parameters and external disturbances were used to validate the robustness and performance of the new novel approach. Simulation results considered two different examples: single-input single-output and multi-input multi-output, which demonstrate the effectiveness of the proposed controller.     

Dye-tolerant marine Acinetobacter baumannii-mediated biodegradation of reactive red

The objective of this study was to isolate a potent dye-degrading microbe that can be used to reduce the pollution caused by industrial dyes.Reactive red 198 is an extensively used textile dye and is a major environmental pollutant in water bodies. In this study, a bacterial strain was isolated from sea sediments and identified as Acinetobacter baumannii with 16S rRNA sequencing. The isolated bacteria were immobilized in calcium alginate and decolorization studies were carried out to determine the optimum pH, temperature, dye concentration, inoculum volume,and static/agitated condition using the one factor at a time(OFAT) approach. The Box-Behnken design, a type of response surface methodology,was adopted to improve the degradation efficiency. At 37℃ using an inoculum volume of six beads, 96.20% decolorization was observed in 500 mg/L of reactive red 198 after 72 h. Dye degradation was confirmed with UV-visible spectroscopy and Fourier-transform infrared(FTIR)spectroscopy studies of the dye and degraded metabolites. Microbial toxicity studies using Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa and phytotoxicity studies using Vigna radiata proved that the toxicity of the dye was significantly reduced after degradation. We can conclude that the isolated A. baumannii strain is an efficient dye-degrading microbe that can be used to reduce the pollution caused by industrial dyes.     

Dynamical Comparison of Several Third-Order Iterative Methods for Nonlinear Equations

There are several ways that can be used to classify or compare iterative methods for nonlinear equations, for instance; order of convergence, informational efficiency, and efficiency index. In this work, we use another way, namely the basins of attraction of the method. The purpose of this study is to compare several iterative schemes for nonlinear equations. All the selected schemes are of the third-order of convergence and most of them have the same efficiency index. The comparison depends on the basins of attraction of the iterative techniques when applied on several polynomials of different degrees. As a comparison, we determine the CPU time (in seconds) needed by each scheme to obtain the basins of attraction, besides, we illustrate the area of convergence of these schemes by finding the number of convergent and divergent points in a selected range for all methods. Comparisons confirm the fact that basins of attraction differ for iterative methods of different orders, furthermore, they vary for iterative methods of the same order even if they have the same efficiency index. Consequently, this leads to the need for a new index that reflects the real efficiency of the iterative scheme instead of the commonly used efficiency index.     

A Highly Efficient Algorithm for Phased-Array mmWave Massive MIMO Beamforming

With the rapid development of the mobile internet and the internet of things (IoT), the fifth generation (5G) mobile communication system is seeing explosive growth in data traffic. In addition, low-frequency spectrum resources are becoming increasingly scarce and there is now an urgent need to switch to higher frequency bands. Millimeter wave (mmWave) technology has several outstanding features—it is one of the most well-known 5G technologies and has the capacity to fulfil many of the requirements of future wireless networks. Importantly, it has an abundant resource spectrum, which can significantly increase the communication rate of a mobile communication system. As such, it is now considered a key technology for future mobile communications. MmWave communication technology also has a more open network architecture; it can deliver varied services and be applied in many scenarios. By contrast, traditional, all-digital precoding systems have the drawbacks of high computational complexity and higher power consumption. This paper examines the implementation of a new hybrid precoding system that significantly reduces both calculational complexity and energy consumption. The primary idea is to generate several sub-channels with equal gain by dividing the channel by the geometric mean decomposition (GMD). In this process, the objective function of the spectral efficiency is derived, then the basic tracking principle and least square (LS) techniques are deployed to design the proposed hybrid precoding. Simulation results show that the proposed algorithm significantly improves system performance and reduces computational complexity by more than 45% compared to traditional algorithms.