Impact of Soret and Dufour on MHD mixed convective flow of non-Newtonian fluid over a coagulated surface

In the present study, we investigated the steady, two-dimensional mixed convective stagnation point flow of an electrically conducting micropolar fluid due to stretching of a variable thicked surface in the attendance of viscous dissipation. The flow is incompressible and laminar. The combined heat and mass transfer features are investigated. Convective and diffusion conditions are considered. The nonlinear thermal radiation, thermo-diffusion, and diffusion thermal effects are considered. The governing partial differential equations are converted to ordinary differential equations by using the appropriate similarity transformations. The obtained nonlinear and coupled ordinary differential equations are elucidated numerically using the fourth-order Runge–Kutta based shooting technique. The influence of various nondimensional parameters on the flow field like velocity, microrotation, temperature, and concentration is examined with the assistance of graphs. Results indicate that the Dufour number has a proclivity to increase the distributions of concentration and temperature correspondingly. Also, fluid temperature and concentration enhance for increasing values of the wall thickness parameter.     

Optimisation of a process for production of pomegranate pulp and flaxseed powder fortified probiotic Greek dahi

Fortified probiotic Greek dahi was formulated with pomegranate pulp (PP) and flaxseed powder (FP). The product variables, viz. PP, FP and incubation time, were optimised based on chemical, sensory and textural attributes. The study revealed that PP significantly affected the acidity and antioxidant content, while FP influenced the sensory and textural properties of the product. The optimum conditions were 15% PP, 2% FP and 12‐h incubation time. The developed fortified probiotic Greek dahi is a potential synbiotic food.     

Optimization of the Cascade Feed Forward Back Propagation network for defect classification in ultrasonic images

Ultrasonic Time of Flight Diffraction (TOFD) is now a well established NDE technique finding wide applications in the industry for inspection during manufacture, pre-service and also inservice. While conventionally interpretations of UT images are done by the inspector, a need has always been felt for automated evaluation and interpretation especially when large inspection volumes are involved. Apart from enhancing the speed of inspection, automated evaluation and interpretation provides better reliability of inspection. A number of approaches based on signal analysis coupled with artificial neural networks (ANN) are being tried internationally and limited success has also been obtained. This paper focuses on the development of a semi automatic toolbox for reliable and fast flaw classification in TOFD images using ANN. TOFD images are first acquired and statistical parameters such as mean, standard deviation, energy, skewness and kurtosis are calculated for the region of interest in the images. The classification of the flawed region like Crack, Lack of Fusion, Lack of Penetration, Porosity and Slag Inclusion was materialized using different ANN approaches which made use of these statistical parameters as their input. The process of optimization of a network involves comparison of classification accuracy and the sensitivity of the selected networks. The Cascade Feed Forward Back Propagation (CFBP) network with log sigmoidal activation function proved to be the optimized network model for the data set considered in this study.     

EVA copolymer matrix for intra-oral delivery of antimicrobial and antiviral agents

Biocompatible ethylene vinyl acetate copolymer (EVA) was utilized to study the release of an antiviral drug (acyclovir (ACY)) and an antimicrobial drug (doxycycline hyclate (DOH)). Release of both drugs from EVA was measured individually and in combination. The effect of drug combination of DOH and ACY is presented. Additionally, the release rate of DOH after coating of the matrix with a different copolymer, in drug-loading with increasing loads of DOH, and with increases in temperature are also presented. The drugs incorporated in EVA films were prepared from the dry sheet obtained by solvent evaporation of polymer casting solutions with drugs. Drug release from the films was examined for about 12 days in distilled water at 37 °C. Changes in optical density were followed spectrophotometrically. The combination of ACY and DOH resulted in an increased release of ACY by about three times (P < 0.001) while DOH showed a decrease in rate of about two times compared to the individual release rates (P = 0.008). Increases in drug levels of DOH resulted in increases in drug release rates (P = 0.001). The release rate of DOH increased with temperature (P = .001; 27, 32, 37 and 42 °C were studied) and the energy of activation (ΔE ^≠ = 56.69 kJ/mol) was calculated using the Arrhenius equation for the diffusion of DOH molecules. Thus, the release rates of drugs were influenced by many factors: drug combination, coating the device, drug-loading, and temperature variation. Therefore it is proposed that controlling these variables should make it possible to obtain therapeutic levels of drugs released from drug loaded polymer, which may be beneficial in treating oral infections.     

Chaotic Sandpiper Optimization Based Virtual Machine Scheduling for Cyber-Physical Systems

Recently, with the growth of cyber physical systems (CPS), several applications have begun to deploy in the CPS for connecting the cyber space with the physical scale effectively. Besides, the cloud computing (CC) enabled CPS offers huge processing and storage resources for CPS that finds helpful for a range of application areas. At the same time, with the massive development of applications that exist in the CPS environment, the energy utilization of the cloud enabled CPS has gained significant interest. For improving the energy effectiveness of the CC platform, virtualization technologies have been employed for resource management and the applications are executed via virtual machines (VMs). Since effective scheduling of resources acts as an important role in the design of cloud enabled CPS, this paper focuses on the design of chaotic sandpiper optimization based VM scheduling (CSPO-VMS) technique for energy efficient CPS. The CSPO-VMS technique is utilized for searching for the optimum VM migration solution and it helps to choose an effective scheduling strategy. The CSPO algorithm integrates the concepts of traditional SPO algorithm with the chaos theory, which substitutes the main parameter and combines it with the chaos. In order to improve the process of determining the global optimum solutions and convergence rate of the SPO algorithm, the chaotic concept is included in the SPO algorithm. The CSPO-VMS technique also derives a fitness function to choose optimal scheduling strategy in the CPS environment. In order to demonstrate the enhanced performance of the CSPO-VMS technique, a wide range of simulations were carried out and the results are examined under varying aspects. The simulation results ensured the improved performance of the CSPO-VMS technique over the recent methods interms of different measures.