Improved physical stability of docosahexaenoic acid and eicosapentaenoic acid encapsulated using nanoliposome containing α‐tocopherol

This study aimed to develop a nanoliposomal formulation containing α‐tocopherol loaded with eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) and to characterise the formulation by its physical stability. For this purpose, different nanoliposomal formulations with dipalmitoyl phosphocholine were prepared using a modified thin‐film hydration method and evaluated by particle size, polydispersity index (PDI), transmission electron microscopy, differential scanning calorimetry and determining the encapsulation efficiencies of DHA and EPA. A physical stability study was conducted by investigating the change in the vesicle encapsulation efficiency, particle size, PDI and shape when stored at 4, 30 and 40 °C for 3 months. High encapsulation efficiency of DHA and EPA (89.1% ± 0.6% and 81.9% ± 1.4%) and appropriate particle size (82 ± 0.8 nm) were obtained for liposomes composed of α‐tocopherol. The optimum formulation was stable for 90 days when kept at 4 °C. This study demonstrated that α‐tocopherol had a protective effect on the physical stability of the nanoliposomes containing DHA and EPA.     

Electrical double-layer capacitors: evaluation of ageing phenomena during cycle life testing

This paper represents an assessment of the main ageing phenomena in electrical double-layer capacitors (EDLCs). In this study the cycle life of the EDLC cells with a rated capacitance of 1,600 F has been investigated at different ambient temperatures and current rates. From the experimental results we can observe that the impact of the high ambient temperature is significant on the cycle life of the cells. Moreover, the results also show the negative impact of the current rate. The internal resistance tests showed that the increase of the resistance is much higher than the decrease of the capacitance. Thus, the ageing of the EDLC during cycling was clearly non-linear. Further the EIS measurements indicated the higher increase of the imaginary part of the impedance at low frequencies during cycling, which indicates the capacitance fade.     

Influence of Electron Beam Irradiation on High‐Temperature Mechanical Properties of Ethylene Vinyl Acetate/Carbon Fibers Composites

The purpose of this study was to investigate the effect of carbon fiber (CF) and electron‐beam (EB) radiation on high‐temperature mechanical properties of ethylene‐vinyl acetate (EVA). Polymer composites were prepared by mixing on a two‐roll mill. After compression molding, the samples were irradiated between 60 and 180 kGy, and dynamic mechanical analysis (DMA) was used to characterize physical properties. The effects of filler content and radiation level on the mechanical properties of EVA/CF were evaluated. The shear stress and modulus were observed to increase with increasing of the filler level. However, there was a dramatic decrease in creep compliance. It was also shown that introduction of irradiation on EVA composite increases the shear stress and the real part of the dynamic shear modulus G' due to the increase in molecular weight and cross‐linking of the polymer after irradiation. J. VINYL ADDIT. TECHNOL., 26:325–335, 2020. © 2019 Society of Plastics Engineers     

An improved cluster formation process in wireless sensor network to decrease energy consumption

Wireless sensor network has special features and many applications, which have attracted attention of many scientists. High energy consumption of these networks, as a drawback, can be reduced by a hierarchical routing algorithm. The proposed algorithm is based on the Low Energy Adaptive Clustering Hierarchy (LEACH) and Quadrant Cluster based LEACH (Q-LEACH) protocols. To reduce energy consumption and provide a more appropriate coverage, the network was divided into several regions and clusters were formed within each region. In selecting the cluster head (CH) in each round, the amount of residual energy and the distance from the center of each node were calculated by the base station (including the location and residual energy of each node) for all living nodes in each region. In this regard, the node with the largest value had the highest priority to be selected as the CH in each network region. The base station calculates the CH due to the lack of energy constraints and is also responsible for informing it throughout the network, which reduces the load consumption and tasks of nodes in the network. The information transfer steps in this protocol are similar to the LEACH protocol stages. To better evaluate the results, the proposed method was implemented with LEACH LEACH-SWDN, and Q-LEACH protocols using MATLAB software. The results showed better performance of the proposed method in network lifetime, first node death time, and the last node death time.

     

A new synthetic metamodel methodology for liquid‐propellant engine's cooling system optimization

The present paper strives for optimization of the cooling system of a liquid‐propellant engine (LPE). To this end, the new synthetic metamodel methodology utilizing the design of experiment method and the response surface method was developed and implemented as two effective means of designing, analyzing, and optimizing. The input variables, constraints, objective functions, and their surfaces were identified. Hence, the design and development strategy of combustion chamber and nozzle was clarified, and 64 different experiments were carried out on the RD‐161 propulsion system, of which 47 experiments were approved and compatible with the problem constraints. This engine used all three modes of cooling: the radiation cooling, the regenerative cooling, and the film cooling. The response surface curves were drawn and the related objective function equations were obtained. The analysis of variance results indicate that the developed synthetic model is capable to predict the responses adequately within the limits of input parameters. The three‐dimensional response surface curves and contour plots have been developed to find out the combined effects of input parameters on responses. In addition, the precision of the models was assessed and the output was interpreted and analyzed, which showed high accuracy. Therefore, the desirability function analysis has been applied to LPE's cooling system for multiobjective optimization to maximize the total heat transfer and minimize the cooling system pressure loss simultaneously. Finally, confirmatory tests have been conducted with the optimum parametric conditions to validate the optimization techniques. In conclusion, this methodology optimizes the LPE's cooling system, a 2% increase in the total heat transfer, and a 38% decrease in the pressure loss of the cooling system. These values are considerably large for the LPE design.     

Silicene Nanoribbons on an Insulating Thin Film

Silicene, a new 2D material has attracted intense research because of the ubiquitous use of silicon in modern technology. However, producing free-standing silicene has proved to be a huge challenge. Until now, silicene could be synthesized only on metal surfaces where it naturally forms strong interactions with the metal substrate that modify its electronic properties. Here, the authors report the first experimental evidence of silicene nanoribbons on an insulating NaCl thin film. This work represents a major breakthrough, for the study of the intrinsic properties of silicene, and by extension to other 2D materials that have so far only been grown on metal surfaces.     

Telesurgery QoS improvement over SDN based on a Type‐2 fuzzy system and enhanced cuckoo optimization algorithm

Telemedicine is a new area based on the information and communication technology for collecting, storing, organizing, retrieving and exchanging medical information. One of the most important applications of telemedicine is indeed telesurgery in which an efficient telecommunication infrastructure between the surgery room and remote surgeons need to be established. One of the most important issues to be tackled in telesurgery is to find favorable links for routing as well as providing high Quality of Service (QoS). In this paper, an efficient model based on the hybridization of Type‐2 Fuzzy System (T2FS) and Cuckoo Optimization Algorithm (COA) over the Software Defined Networks (SDN) is proposed in order to achieve optimal and reliable routes for telesurgery application. Using T2FS, the fitness of the links is determined; then, a COA is conducted over the Constraint Shortest Path (CSP) problem to find the best routes. Delay is considered as a CSP problem which is satisfied by trying to find the paths with minimum cost. Due to the NP‐completeness of the CSP problem, an Enhanced COA (so‐called E‐COA) is proposed and utilized as a metaheuristic solver. To the best of our knowledge, this paper is the first SDN‐based communication model that applies both T2FS and E‐COA for assigning proper costs to the network's links, and solves the consequence CSP problem according to the QoS requirement for telesurgery. The model also recognizes and preserves the second‐best routes in order to keep the reliability for such a critical application. In addition to the simulations, the performance evaluation is also conducted on a real experimental scenario. Many comparisons are carried out between the proposed model and other conventional methods, and the evaluation study shows the superiority of the proposed model on all the three QoS‐related metrics, i.e. average end‐to‐end delay, packet loss ratio and PSNR.     

Adaptive robust control-based energy management of hybrid PV-Battery systems with improved transient performance

Energy management of hybrid photovoltaic (PV)-battery systems still serve as a challenging task owing to their complex and nonlinear characteristics, multicomponent structures, and the extensive range of environmental factors disturbing their nominal performance. The hybrid energy system developed in this study encompasses PV arrays, a battery component, one boost converter, and one bidirectional boost converter. In this paper, we propose a novel adaptive robust control framework for the optimal energy management of the PV-battery systems under many operating conditions and subject to unmodelled dynamics. An improved exponential-like adaptive integral sliding mode (EISM) control coupled to neural network approximator is introduced using a multi-rate convergence tweaking mechanism for the sliding surface to improve the transient performance of the closed-loop system. Furthermore, the entire dynamics of the hybrid energy system is considered unknown, unlike the previous studies that only assumed the parametric uncertainties. The global asymptotic stability of the system is guaranteed, and the effectiveness of this novel framework is compared to benchmark studies.