Entropy analysis of unsteady MHD three-dimensional flow of Williamson nanofluid over a convectively heated stretching sheet

This article addresses an investigation of the entropy analysis of Williamson nanofluid flow in the presence of gyrotactic microorganisms by considering variable viscosity and thermal conductivity over a convectively heated bidirectionally stretchable surface. Heat and mass transfer phenomena have been incorporated by taking into account the thermal radiation, heat source or sink, viscous dissipation, Brownian motion, and thermophoretic effects. The representing equations are nonlinear coupled partial differential equations and these equations are shaped into a set of ordinary differential equations via a suitable similarity transformation. The arising set of ordinary differential equations was then worked out by adopting a well-known scheme, namely the shooting method along with the Runge-Kutta-Felberge integration technique. The effects of flow and heat transfer controlling parameters on the solution variables are depicted and analyzed through the graphical presentation. The survey finds that magnifying viscosity parameter, Weissenberg number representing the non-Newtonian Williamson parameter cause to retard the velocity field in both the directions and thermal conductivity parameter causes to reduce fluid temperature. The study also recognizes that enhancing magnetic parameters and thermal conductivity parameters slow down the heat transfer rate. The entropy production of the system is estimated through the Bejan number. It is noticeable that the Bejan number is eminently dependent on the heat generation parameter, thermal radiation parameter, viscosity parameter, thermal conductivity parameter, and Biot number. The skillful accomplishment of the present heat and mass transfer system is achieved through the exteriorized choice of the pertinent parameters.     

Icy affairs: Understanding recent advancements in the freezing and frozen storage of fish

Freezing methods have evolved over the last 30 years. This review states the effect of various freezing methods on the quality of fish and seafood. Freezing temperatures, freezing, and frozen storage temperatures were also analyzed and reviewed. The changes in the ice crystal, protein, and lipid affect the fish quality and nutritional value during freezing and frozen storage. Freezing methods when combined with various additives or preprocessing approaches help improve the efficacy of freezing and frozen storage. Several experimental or emerging methods also have positive effects on the products' quality. According to the metadata reanalysis of quality markers, freshly frozen fish using different freezing methods may vary much in terms of ice diameter, but not others. High pressure freezing or immersion freezing-derived fish retains the best quality through frozen storage. More data are required on freezing methods (electrical-assisted freezing, microwave-assisted freezing, magnetic-assisted freezing, radiofrequency-assisted freezing, and the commercial's application and investment should be considered in the future. This review sheds light on finding a balanced initial shear force during freezing and the use of certain additives to control freezing-related damages. Focusing on ice diameter alone may be futile (e.g., liquid N₂ freezing). Future optimization of technologies should be in a way that several processes along the farm to fork such as freezing, frozen storage, thawing, thermal processing of fish, and even refabrication of food should mutually complement each other's needs to deliver safe and high-quality fish to the consumer's plate, even after a prolonged shelf-life.     

Interfacial interactions and properties of cellular structured polyurethane nanocomposite based on carbonaceous nano-fillers

In this article, we have studied the effect of carbonaceous nanofillers viz. fullerenol (0D), carboxylated multi-wall carbon nanotube (MWCNT, 1D), hydroxylated graphene (2D) and combination of carboxylated CNT and hydroxylated graphene as 3D in thermoplastic polyurethane on the tensile properties of the fabricated cellular structures. The concentration of nano-fillers was varied as 0.1, 1, and 5 wt%. Tensile properties of the nanocomposite cellular structures were measured as per ASTM D882 at 20°C (below glass transition temperature, T_g) and 40°C (above T_g). The results have shown that the tensile strength was found to increase by 200%–300% and the tensile modulus was found to increase by 150%–300% for 2D and 3D nano-fillers while significantly poor results were observed for 0D. However, the test data tensile strength and modulus showed marginal increase at 20°C and marginally low at 40°C for 1D filler. The interfacial adhesion was calculated by using experimental tensile data and the predictive models. The interfacial adhesion parameter (B_σ) calculated using Pukanszky equation was found significantly higher value for 2D (B_σ20 = 195.8) and 3D (B_σ20 = 192.0) fillers while poor adhesion was observed for 0D (B_σ20 = −81.6) fillers. The developed cellular structured materials were also evaluated by attenuated total reflection Fourier transform IR spectra, differential scanning calorimetry, X-ray diffraction, scanning electron microscope, and transmission electron microscope.     

In vitro and in vivo degradability,biocompatibility and antimicrobial characteristics of Cu added iron-manganese alloy

In recent years,iron(Fe)based degradable metal is explored as an alternative to permanent fracture fixation devices.In the present work,copper(Cu)is added in Fe-Mn system to enhance the degradation rate and antimicrobial properties.Fe-Mn-xCu(x=0.9,5 and 10 wt.％)alloys are prepared by the melting-casting-forging route.XRD analysis confirms austenite phase stabilization due to the presence of Mn and Cu.As predicted by Thermo-Calc calculations,Cu rich phase precipitations are noticed along the austen-ite grain boundaries.Degradation behaviours of Cu added Fe-Mn alloys are investigated through static immersion and electrochemical polarization where enhanced degradation is found for higher Cu added alloys.When challenged against E.Coli bacteria,the Fe-Mn-Cu alloy media extract shows a significant bac-tericidal effect compare to the base alloy.In vitro cytocompatibility studies,as determined using MG63 and MC3T3-E1 cell lines,indicate increased cell density as a function of time for all the alloys.When implanted in rabbit femur,the newly developed alloy does not show any kind of tissue necrosis around the implants.Better osteogenesis and higher new bone formation are observed with Fe-Mn-10Cu alloy as evident from micro-computed tomography(μ-CT)and fluorochrome labelling.     

Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

Novel model reference adaptive control architecture using semi‐initial excitation‐based switched parameter estimator

This paper is a generalization of the recently developed techniques of initial excitation (IE)–based adaptive control with an introduction to the definition of semi‐initial excitation (semi‐IE), a still more relaxed notion than IE. Classical adaptive controllers typically ensure Lyapunov stability of the extended error dynamics (tracking error + parameter estimation error) and asymptotic tracking, while requiring a stringent condition of persistence of excitation (PE) for parameter convergence. Of late, the authors have proposed a new adaptive control architecture, which guarantees parameter convergence under the online‐verifiable IE condition leading to exponential stability of the extended error dynamics. In earlier works, it has been established that the IE condition is significantly milder than the classical PE condition. The current work further slackens the excitation condition by proposing the concept of semi‐IE. The proposed adaptive controller is proved to ensure convergence of the parameter estimation error to a lower‐dimensional manifold under the weaker semi‐IE condition, while the stronger condition of IE guarantees convergence of the parameter estimation error to zero. The designed algorithm is shown to improve transient response of tracking error sufficiently in contrast to conventional adaptive controllers.     

Detecting DDoS Attacks in Cloud Computing Using Extreme Learning Machine and Adaptive Differential Evolution

Wireless Personal Communications - Distributed denial of service (DDoS) attacks disrupt the availability of cloud services. The detection of these attacks is a major challenge in the cloud...     

An embedded FPGA-SoC framework and its usage in moving object tracking application

Design Automation for Embedded Systems - Moving object tracking is a computation-intensive operation that requires accelerating hardware solution. In this work, a high-performance design for mean...