Optimising the ice cream formulation using basil seed gum (Ocimum basilicum L.) as a novel stabiliser to deliver improved processing quality

Mixture design was used to determine the optimum ratio as well as concentration of basil seed gum (BSG), guar gum (GG) and carboxymethyl cellulose (CMC) in the formulation of ice cream stabilisers. Predicted equations and contour plots of physicochemical responses were also generated. Generally, increasing the ratio of BSG in gums mixture increased the apparent viscosity of ice cream mixes and decreased the melting rate. Increasing the proportion of GG at concentration of 0.35% enhanced overrun of samples. High ratios of BSG at concentration of 0.35% and CMC at concentration of 0.15% increased the fat destabilisation in ice creams. Combination of 84.31% BSG and 15.69% CMC at concentration of 0.35% proposed as optimum formulation which verified in practice. Introducing BSG as a novel source of stabiliser could be promising as alternative and improve the quality and diversity of ice cream and related products.     

A robust weakly compressible SPH method and its comparison with an incompressible SPH

This paper presents a comparative study for the weakly compressible (WCSPH) and incompressible (ISPH) smoothed particle hydrodynamics methods by providing numerical solutions for fluid flows over an airfoil and a square obstacle. Improved WCSPH and ISPH techniques are used to solve these two bluff body flow problems. It is shown that both approaches can handle complex geometries using the multiple boundary tangents (MBT) method, and eliminate particle clustering‐induced instabilities with the implementation of a particle fracture repair procedure as well as the corrected SPH discretization scheme. WCSPH and ISPH simulation results are compared and validated with those of a finite element method (FEM). The quantitative comparisons of WCSPH, ISPH and FEM results in terms of Strouhal number for the square obstacle test case, and the pressure envelope, surface traction forces, and velocity gradients on the airfoil boundaries as well as the lift and drag values for the airfoil geometry indicate that the WCSPH method with the suggested implementation produces numerical results as accurate and reliable as those of the ISPH and FEM methods. Copyright © 2011 John Wiley & Sons, Ltd.     

The influence of low- and high-linear energy transfers on some physical properties of poly(methyl-methacrylate) samples

Clear poly(methyl-methacrylate)—PMMA—dosimeter is widely used in food irradiations. Positron annihilation lifetime spectroscopy (PALS) is one of the unique tools used for studying free-volumes and open-volume type defects in solid media. The Vicker's microhardness measurements offer a simple and nondestructive tool for investigating the mechanical behavior of polymer materials. PALS as well as microhardness measurements were carried out for PMMA samples, irradiated with low- and high-linear energy transfers (LET). The low-LET irradiations were provided at lethal doses of gamma radiations for vegetative bacteria. Such irradiations showed a chain scission in the PMMA samples. High-LET irradiations showed behavior different from the low-LET ones. The observed behavior depends on the alpha particle fluence. The microhardness testing was carried out for virgin and irradiated PMMA samples at high-LET. A negative correlation was found between PALS measurements and microhardness results. The optical characteristics and structural studies for the virgin and irradiated PMMA samples were in agreement with the PALS and microhardness measurements. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Full-duplex overlay cognitive wireless powered communication network using RF energy harvesting

In this paper, a novel full-duplex overlay cognitive wireless powered communication network (FD-OCWPCN) is proposed where a full-duplex (FD) hybrid-access point (H-AP) supports the full access of all battery-free secondary users (SUs). The H-AP broadcasts wireless power to empower the nearby SUs in the downlink (DL) phase while decoding the information transmitted uplink (UL) phase by the SUs, simultaneously. To overcome the self-interference (SI) phenomenon in FD-OCWPCN, the problem of maximizing the system sum-throughput with optimal UL-DL transmission/reception time and H-AP’s transmit power allocation is considered. This problem is non-convex under perfect/imperfect SI cancelation (SIC), so we employ the active interference temperature control and the gradient projection techniques to effectively reduce it into a convex problem. Closed-form expressions for the perfect/imperfect SIC cases are also derived. To assess the performance of the FD-OCWPCN, a comparison with a half-duplex OCWPCN (HD-OCWPCN) is provided. The achievable average sum-throughput for different FD/HD-OCWPCN is compared in the context of the average and peak transmit power at the H-AP, the number of SUs, path loss exponent and fairness metric. The simulation results depict the superiority of the FD-OCWPCN over the HD-OCWPCN for the perfect SIC and the effective imperfect SIC.

     

An E-Business Event Stream Mechanism for Improving User Tracing Processes

With the rapid development in business transactions, especially in recent years, it has become necessary to develop different mechanisms to trace business user records in web server log in an efficient way. Online business transactions have increased, especially when the user or customer cannot obtain the required service. For example, with the spread of the epidemic Coronavirus (COVID-19) throughout the world, there is a dire need to rely more on online business processes. In order to improve the efficiency and performance of E-business structure, a web server log must be well utilized to have the ability to trace and record infinite user transactions. This paper proposes an event stream mechanism based on formula patterns to enhance business processes and record all user activities in a structured log file. Each user activity is recorded with a set of tracing parameters that can predict the behavior of the user in business operations. The experimental results are conducted by applying clustering-based classification algorithms on two different datasets; namely, Online Shoppers Purchasing Intention and Instacart Market Basket Analysis. The clustering process is used to group related objects into the same cluster, then the classification process measures the predicted classes of clustered objects. The experimental results record provable accuracy in predicting user preferences on both datasets.     

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.

     

Performance improvement of microbial fuel cell through artificial intelligence

The current work introduces an enhancement in the performance of the microbial fuel cell through estimating the optimal set of controlling parameters. The maximization of both power density (PD) and the percentage of chemical oxygen demand (COD) removal were considered as the enhancement in the cell's performance. Three main parameters in terms of performance as well as commercialization are the system's inputs; the Pt which takes the range of 0.1‐0.5 mg/cm², the degree of sulphonation in sulfonated‐poly‐ether‐ether‐ketone that changes in the range of 20‐80%, and the rate of aeration of cathode which varies between 10 and 150 mL/min. From the experimental dataset, two robust adaptive neuro‐fuzzy inference system models based on the fuzzy logic technique have been constructed. The comparisons between the models' outputs and the experimental data showed well‐fitting in both training and testing datasets. The mean squared errors of the PD model, for testing and whole datasets, were found 2.575 and 0.909 while for the COD model it showed 19.242 and 6.791, respectively. Then, based on the two fuzzy models, a Particle Swarm Optimization algorithm has been used to determine the best parameters that maximize both of the PD and the COD removal of the cell. The optimization process was utilized for single and multi‐object optimization processes. In the single optimization, the resulting maximums of the PD and the COD removal were found 62.844 (mW/m²) and 99.99 (%), respectively. Whereas, in the multi‐object optimization, the values of 61.787 (mW/m²) and 96.21 (%) were reached as the maximums for the PD and COD, respectively. This implies that, in both cases of optimization processes, the adopted methodology can efficiently enhance the microbial fuel cell performances than the previous work.