Habeeb A. Babatunde

Protein content variation in milk can impact the quality and consistency of dairy products, necessitating access to in-line real time monitoring. Here, we present a chemometric approach for the qualitative and quantitative monitoring of β-lactoglobulin and α-lactalbumin, using mid-infrared spectroscopy (MIR). In this study, we employed Hotelling T2 and Q-residual for outlier detection, automated preprocessing using nippy, conducted wavenumber selection with genetic algorithms, and evaluated four chemometric models, including partial least squares, support vector regression (SVR), ridge, and logistic regression to accurately predict the concentrations of β-lactoglobulin and α-lactalbumin in milk. For the quantitative analysis of these two whey proteins, SVR performed the best to interpret protein concentration from 197 MIR spectra originating from 42 Cornell University samples of preserved pasteurized modified milk. The R2 values obtained for β-lactoglobulin and α-lactalbumin using leave one out cross-validation (LOOCV) are 92.8% and 92.7%, respectively, which is the highest correlation reported to date. Our approach introduced a combination of preprocessing automation, genetic algorithm-based wavenumber selection, and used Optuna to optimize the framework for tuning hyperparameters of the chemometric models, resulting in the best chemometric analysis of MIR data to quantitate β-lactoglobulin and α-lactalbumin to date.

Decline in the theoretical and empirical review of Brownian motion is worth noticing, not just because its relevance lies in the field of mathematical physics but due to unavailability of statistical technique. The ongoing debate on transport phenomenon and thermal performance of various fluids in the presence of haphazard motion of tiny particles as explained by Albert Einstein using kinetic theory and Robert Brown is further clinched in this report. This report presents the outcome of detailed inspections of the significance of Brownian motion on the flow of various fluids as reported in forty-three (43) published articles using the method of slope linear regression through the data point. The technique of slope regression through the data points of each physical property of the flow and Brownian motion parameter was established and used to generate four forest plots. The outcome of the study indicates that an increase in Brownian motion corresponds to an enhancement of haphazard motion of tiny particles. In view of this, there would always be a significant difference between the corresponding effects when Brownian motion is small and large in magnitude. Maximum heat transfer rate can be achieved due to Brownian motion in the presence of thermal radiation, thermal convective and mass convective at the wall in three-dimensional flow. In the presence of heat convective and mass convective at the wall, and thermal radiation, a significant increase in Nusselt number due to Brownian motion is guaranteed. A decrease in the concentration of fluid substance due to an increase in Brownian motion is bound to occur. This is not achievable in the case of high entropy generation and homogeneous-heterogeneous quartic autocatalytic kind of chemical reaction.

White crystalline powder (aluminum oxide) and water are the products often formed after the heating of aluminum hydroxide. In this report, boundary layer flow of two different nanofluids (i.e., 36 nm -water and 47 nm -water) over an upper horizontal surface of a paraboloid of revolution under the influence of magnetic field is presented. The combined influence of magnetic field strength, electric current density, electric charge, electron collision time, and the mass of an electron in the flows are considered in the governing equations. Three-dimensional transport phenomenon was considered due to the influence of the Lorentz force along the z-direction as in the case of Hall currents. In this study, the dynamic viscosity and density of the nanofluids are assumed to vary with the volume fraction . The dimensional governing equations were non-dimensionalization and parametrization using similarity variables. The corresponding boundary value problem was transformed into initial value problem using the method of superposition and solved numerically using fourth-order Runge–Kutta method with shooting technique (RK4SM). Magnetic field parameter is seen to have dual effects on the cross-flow velocity profiles of both nanofluids. The maximum cross-flow velocity is attained within the fluid domain when 36 nm nanoparticles alumina is used. The cross-flow velocity gradient at the wall increases with magnetic field parameter (M) and also increases significantly with Hall parameter at larger values of M.

Differential equations, heat transfer, and fluid dynamics are few among the fundamental subjects in mechanical sciences. Considering the contributions of published articles to the body of knowledge on boundary layer analysis together with heat and mass transfer, it is noteworthy that validation of results, theoretical/conceptual review and empirical review have been on decreasing trends in quality. In this report, a systematic review procedure on the effects of Grashof number and mixed convection parameter on the flow of various fluids is presented. After searching through the relevant literature systematically, 30 relevant articles were screened and reviewed for the study. Each of the accepted articles was coded using study characteristics and corresponding effects of the parameter were scrutinized. In each of the selected article, the optimal level(s) of the effect(s) of the parameter on the physical properties of the flow was marked and the slope of the linear regression line through data points in known physical property and/or properties of each article and Grashof number/buoyancy parameter was estimated. The outcomes of the systematic reviews of the parameter and forest plot are illustrated. An increase in the magnitude of buoyancy parameter corresponds to a moderate increase in the velocity but a decrease in the temperature distribution becomes apparent. Also, buoyancy parameter has negligible positive effect on the local Nusselt number, Sherwood number, Bejan Number, Entropy generation, Stanton Number and pressure gradient are increasing properties of buoyancy related parameter while concentration profiles, frictional force, and motile microorganism are decreasing properties.