Effects of Nonthermal Plasma Technology on Functional Food Components

Understanding the impact of nonthermal plasma (NTP) technology on key nutritional and functional food components is of paramount importance for the successful adoption of the technology by industry. NTP technology (NTPT) has demonstrated marked antimicrobial efficacies with good retention of important physical, chemical, sensory, and nutritional parameters for an array of food products. This paper presents the influence of NTPT on selected functional food components with a focus on low‐molecular‐weight bioactive compounds and vitamins. We discuss the mechanisms of bioactive compound alteration by plasma‐reactive species and classify their influence on vitamins and their antioxidant capacities. The impact of NTP on specific bioactive compounds depends both on plasma properties and the food matrix. Induced changes are mainly associated with oxidative degradation and cleavage of double bonds in organic compounds. The effects reported to date are mainly time‐dependent increases in the concentrations of polyphenols, vitamin C, or increases in antioxidant activity. Also, improvement in the extraction efficiency of polyphenols is observed. The review highlights future research needs regarding the complex mechanisms of interaction with plasma species. NTP is a novel technology that can both negatively and positively affect the functional components in food.     

Comparative physicochemical stability and efficacy study of lipoid S75-biopeptides nanoliposome composite produced by conventional and direct heating methods

Liposomes are used as effective nanodelivery devices to improve the physicochemical stability and biological efficacy of the encapsulated peptides and proteins. In this study, nanoliposome composite of lipoid S75-entrapped angiotensin I-converting enzyme (ACE)-inhibitory biopeptides was prepared by conventional (BLS75-CM) and direct heating (BLS75-DHM) methods. The nanoliposomes (BLS75-CM and BLS75-DHM) were stored at 4^°C for 8 weeks and evaluated for physicochemical stability in terms of particle size, polydispersity index (pdi), zeta potential, and encapsulation efficiency (EE). These were also studied for residual ACE-inhibitory efficacy following their digestion under simulated gastrointestinal tract condition. The BLS75-CM was found to maintain higher physicochemical stability in terms of particle size, pdi, and zeta potential compared to BLS75-DHM. However, the BLS75-DHM indicated higher EE and efficacy with greater residual ACE-inhibitory activity of 47.37% compared to 44.18% and 36.84% that were obtained for the digested BLS75-CM and digested biopeptides without encapsulation, respectively. In vitro release study showed a cumulative biopeptides release of 66.41% and 69.00% from BLS75-CM and BLS75-DHM, respectively. The results of transmission electron microscopy showed spherical appearance of the nanoliposome capsules while Fourier Transform Infrared spectroscopy indicated the presence of ionic complexation and hydrogen bonds between the biopeptides and their phospholipid matrix.     

Solution of Algebraic Lyapunov Equation on Positive-Definite Hermitian Matrices by Using Extended Hamiltonian Algorithm

This communique is opted to study the approximate solution of the Algebraic Lyapunov equation on the manifold of positive-definite Hermitian matrices. We choose the geodesic distance between -AHX - XA and P as the cost function, and put forward the Extended Hamiltonian algorithm (EHA) and Natural gradient algorithm (NGA) for the solution. Finally, several numerical experiments give you an idea about the effectiveness of the proposed algorithms. We also show the comparison between these two algorithms EHA and NGA. Obtained results are provided and analyzed graphically. We also conclude that the extended Hamiltonian algorithm has better convergence speed than the natural gradient algorithm, whereas the trajectory of the solution matrix is optimal in case of Natural gradient algorithm (NGA) as compared to Extended Hamiltonian Algorithm (EHA). The aim of this paper is to show that the Extended Hamiltonian algorithm (EHA) has superior convergence properties as compared to Natural gradient algorithm (NGA). Upto the best of author’s knowledge, no approximate solution of the Algebraic Lyapunov equation on the manifold of positive-definite Hermitian matrices is found so far in the literature.     

Coverless Steganography for Digital Images Based on a Generative Model

In this paper, we propose a novel coverless image steganographic scheme based on a generative model. In our scheme, the secret image is first fed to the generative model database, to generate a meaning-normal and independent image different from the secret image. The generated image is then transmitted to the receiver and fed to the generative model database to generate another image visually the same as the secret image. Thus, we only need to transmit the meaning-normal image which is not related to the secret image, and we can achieve the same effect as the transmission of the secret image. This is the first time to propose the coverless image information steganographic scheme based on generative model, compared with the traditional image steganography. The transmitted image is not embedded with any information of the secret image in this method, therefore, can effectively resist steganalysis tools. Experimental results show that our scheme has high capacity, security and reliability.     

Enzymolysis reaction kinetics and thermodynamics of rapeseed protein with sequential dual‐frequency ultrasound pretreatment

We evaluated the effect of sequential dual‐frequency ultrasound (SDFU) pretreatments on rapeseed protein enzymolysis, using alcalase as a model enzyme. Hydrolysed protein concentrations, enzymolysis kinetics and thermodynamic parameters were investigated. The results showed that the hydrolysed rapeseed protein concentration following SDFU pretreatments was higher compared to that of the control for up to 75 min of enzymolysis at various substrate concentrations of 5–25 g L^?1; both control and SDFU pretreatment groups showed first‐order reaction kinetics. Compared to the control, the Michaelis–Menten constant (K_M) value decreased remarkably by 17.61%, while an increase in the binding frequency between enzyme and substrate (K_A) by 10.47% was observed. The thermodynamic parameters, enthalpy, entropy and activation energy were reduced in the SDFU pretreatment group compared to the control by 31.78%, 18.0% and 29.56%, respectively. SDFU pretreatment showed little effect on Gibbs free energy at the various temperatures studied.     

Thermodynamic Properties of Magnesium-Boron Binary Alloys Determined Using Solid-State Electrochemical Measurements

Metallurgical and Materials Transactions B - This study provides the thermodynamic properties of the Mg-B binary alloys. Experiments were performed to measure the electromotive force (emf) as a...     

Proteome Based Approach Defines Candidates for Designing a Multitope Vaccine against the Nipah Virus

Nipah virus is one of the most harmful emerging viruses with deadly effects on both humans and animals. Because of the severe outbreaks, in 2018, the World Health Organization focused on the urgent need for the development of effective solutions against the virus. However, up to date, there is no effective vaccine against the Nipah virus in the market. In the current study, the complete proteome of the Nipah virus (nine proteins) was analyzed for the antigenicity score and the virulence role of each protein, where we came up with fusion glycoprotein (F), glycoprotein (G), protein (V), and protein (W) as the candidates for epitope prediction. Following that, the multitope vaccine was designed based on top-ranking CTL, HTL, and BCL epitopes from the selected proteins. We used suitable linkers, adjuvant, and PADRE peptides to finalize the constructed vaccine, which was analyzed for its physicochemical features, antigenicity, toxicity, allergenicity, and solubility. The designed vaccine passed these assessments through computational analysis and, as a final step, we ran a docking analysis between the designed vaccine and TLR-³ and validated the docked complex through molecular dynamics simulation, which estimated a strong binding and supported the nomination of the designed vaccine as a putative solution for Nipah virus. Here, we describe the computational approach for design and analysis of this vaccine.     

A survey on trust based detection and isolation of malicious nodes in ad-hoc and sensor networks

Mobile ad-hoc networks (MANETs) and wireless sensor networks (WSNs) have gained remarkable appreciation and technological development over the last few years. Despite ease of deployment, tremendous applications and significant advantages, security has always been a challenging issue due to the nature of environments in which nodes operate. Nodes’ physical capture, malicious or selfish behavior cannot be detected by traditional security schemes. Trust and reputation based approaches have gained global recognition in providing additional means of security for decision making in sensor and ad-hoc networks. This paper provides an extensive literature review of trust and reputation based models both in sensor and ad-hoc networks. Based on the mechanism of trust establishment, we categorize the stateof-the-art into two groups namely node-centric trust models and system-centric trust models. Based on trust evidence, initialization, computation, propagation and weight assignments, we evaluate the efficacy of the existing schemes. Finally, we conclude our discussion with identification of some unresolved issues in pursuit of trust and reputation management.