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In various kinds of materials processes, heat and mass transfer control in nuclear phenomena, constructing buildings, turbines and electronic circuits, etc., there are numerous problems that cannot be enlightened by uniform wall temperature. To explore such physical phenomena researchers incorporate non-uniform or ramped temperature conditions at the boundary, the purpose of this paper is to achieve the closed-form solution of a time-dependent magnetohydrodynamic (MHD) boundary layer flow with heat and mass transfer of an electrically conducting non-Newtonian Casson fluid toward an infinite vertical plate subject to the ramped temperature and concentration (RTC). The consequences of chemical reaction in the mass equation and thermal radiation in the energy equation are encompassed in this analysis. The flow regime manifests with pertinent physical impacts of the magnetic field, thermal radiation, chemical reaction and heat generation/absorption. A first-order chemical reaction that is proportional to the concentration itself directly is assumed. The Rosseland approximation is adopted to describe the radiative heat flux in the energy equation.

The problem is formulated in terms of partial differential equations with the appropriate physical initial and boundary conditions. To make the governing equations dimensionless, some suitable non-dimensional variables are introduced. The resulting non-dimensional equations are solved analytically by applying the Laplace transform method. The mathematical expressions for skin friction, Nusselt number and Sherwood number are calculated and expressed in closed form. Impacts of various associated physical parameters on the pertinent flow quantities, namely, velocity, temperature and concentration profiles, skin friction, Nusselt number and Sherwood number, are demonstrated and analyzed via graphs and tables.

Graphical analysis reveals that the boundary layer flow and heat and mass transfer attributes are significantly varied for the embedded physical parameters in the case of constant temperature and concentration (CTC) as compared to RTC. It is worthy to note that the fluid velocity is high with CTC and lower for RTC. Also, the fluid velocity declines with the augmentation of the magnetic parameter. Moreover, growth in thermal radiation leads to a declination in the temperature profile.

The proposed model has relevance in numerous engineering and technical procedures including industries related to polymers, area of chemical productions, nuclear energy, electronics and aerodynamics. Encouraged by such applications, the present work is undertaken.

Literature review unveils that sundry studies have been carried out in the presence of uniform wall temperature. Few studies have been conducted by considering non-uniform or ramped wall temperature and concentration. The authors are focused on an analytical investigation of an unsteady MHD boundary layer flow with heat and mass transfer of non-Newtonian Casson fluid past a moving plate subject to the RTC at the plate. Based on the authors’ knowledge, the present study has, so far, not appeared in scientific communications. Obtained analytical solutions are verified by considering particular cases of the published works.

Providing online news recommendations to users has become an important trend for online media platforms, enabling them to attract more users. The purpose of this paper is to propose an online news recommendation system for recommending news articles to users when browsing news on online media platforms.

A Collaborative Semantic Topic Modeling (CSTM) method and an ensemble model (EM) are proposed to predict user preferences based on the combination of matrix factorization with articles’ semantic latent topics derived from word embedding and latent topic modeling. The proposed EM further integrates an online interest adjustment (OIA) mechanism to adjust users’ online recommendation lists based on their current news browsing.

This study evaluated the proposed approach using offline experiments, as well as an online evaluation on an existing online media platform. The evaluation shows that the proposed method can improve the recommendation quality and achieve better performance than other recommendation methods can. The online evaluation also shows that integrating the proposed method with OIA can improve the click-through rate for online news recommendation.

The novel CSTM and EM combined with OIA are proposed for news recommendation. The proposed novel recommendation system can improve the click-through rate of online news recommendations, thus increasing online media platforms’ commercial value.

Lung cancer is the leading cause of death worldwide. Physical and chemical agents such as tobacco smoke are the leading cause of various lung cancers. The intrinsic heterogeneity of normal lung tissue may be affected in different ways, giving rise to different types of lung cancers classified as either small‐cell lung cancer (SCLC) or non‐small cell lung cancer (NSCLC). Adenocarcinoma, a NSCLC, accounts for 40 percent of all lung cancer cases and the incidence is increasing worldwide, especially among women. The survival rate and prognosis is poorest for adenocarcinoma. Therefore, diagnosis at the earliest stage (Stage I, localized) is critical for increasing survival rates of those suffering from lung cancer. However, many factors affect early diagnosis including the variable natural growth of tumors plus technological and human factors associated with manipulation of tissue samples and interpretation of results. This article reviews potential problems associated with diagnosing lung cancer and considers future directions of diagnostic technology.

This paper aims to incorporate a hybridized advanced sine-cosine algorithm (ASCA) and advanced ant colony optimization (AACO) technique for optimal path search with control over multiple mobile robots in static and dynamic unknown environments.

The controller for ASCA and AACO is designed and implemented through MATLAB simulation coupled with real-time experiments in various environments. Whenever the sensors detect obstacles, ASCA is applied to find their global best positions within the sensing range, following which AACO is activated to choose the next stand-point. This is how the robot travels to the specified target point.

Navigational analysis is carried out by implementing the technique developed here using single and multiple mobile robots. Its efficiency is authenticated through the comparison between simulation and experimental results. Further, the proposed technique is found to be more efficient when compared with existing methodologies. Significant improvements of about 10.21 per cent in path length are achieved along with better control over these.

Systematic presentation of the proposed technique attracts a wide readership among researchers where AI technique is the application criteria.

Bitcoin (BTC) is significantly correlated with global financial assets such as crude oil, gold and the US dollar. BTC and global financial assets have become more closely related, particularly since the outbreak of the COVID-19 pandemic. The purpose of this paper is to formulate BTC investment decisions with the aid of global financial assets.

This study suggests a more accurate prediction model for BTC trading by combining the dynamic conditional correlation generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model with the artificial neural network (ANN). The DCC-GARCH model offers significant input information, including dynamic correlation and volatility, to the ANN. To analyze the data effectively, the study divides it into two periods: before and during the COVID-19 outbreak. Each period is then further divided into a training set and a prediction set.

The empirical results show that BTC and gold have the highest positive correlation compared with crude oil and the USD, while BTC and the USD have a dynamic and negative correlation. More importantly, the ANN-DCC-GARCH model had a cumulative return of 318% before the outbreak of the COVID-19 pandemic and can decrease loss by 50% during the COVID-19 pandemic. Moreover, the risk-averse can turn a loss into a profit of about 20% in 2022.

The empirical analysis provides technical support and decision-making reference for investors and financial institutions to make investment decisions on BTC.

The purpose of this study is the empirical measurement and analysis of economic size and performance of dispersed and clustered small‐scale enterprises (SSEs) in India.

Methodology is descriptive and comparative, using a combination of different official databases. Economic size is measured by distribution of SSEs by employment, output, fixed capital investment, and export variables. Measurement of economic performance is focused on output/capital ratio, output/labour ratio, and labour/capital ratio.

The results offer evidence for economic diversity in the size compositions and performance variations of dispersed and clustered SSEs; and bigger economic size and higher economic performance of clustered than dispersed SSEs.

Subject to the comparability of economic structure, the results and implications for India are of relevance for promotion and development of clustered SSEs in other developing countries.

From the viewpoint of policy formulation, the results offer a strong empirical basis for a cluster approach rather than a dispersed approach for promotion and development of SSEs in India. The cluster approach has implications for establishing linkages between formal and informal SSEs and for elimination of smallness of dispersed SSEs.

The paper provides a comparative analysis of economic size and performance of the dispersed and clustered SSEs by consolidating the diverse databases in India.

This study aims to investigate the buoyancy-induced heat and mass transfer phenomena in a backward-facing-step (BFS) channel subjected to applied magnetic field using different types of nanofluid.

Conservation equations of mass, momentum, energy and concentration are used through velocity-vorticity form of Navier–Stokes equations and solved using Galerkin’s weighted residual finite element method. The density variation is handled by Boussinesq approximation caused by thermo-solutal buoyancy forces evolved at the channel bottom wall having high heat and concentration. Simulations were carried out for the variation of Hartmann number (0 to 100), buoyancy ratio (−10 to +10), three types of water-based nanofluid i.e. Fe₃O₄, Cu, Al₂O₃ at χ = 6%, Re = 200 and Ri = 0.1.

The mutual interaction of magnetic force, inertial force and nature of thermal-solutal buoyancy forces play a significant role in the heat and mass transport phenomena. Results show that the size of the recirculation zone increases at N = 1 for aiding thermo-solutal buoyancy force, whereas the applied magnetic field dampened the fluid-convection process. With an increase in buoyancy ratio, Al₂O₃ nanoparticle shows a maximum 54% and 67% increase in convective heat and mass transfer, respectively at Ha = 20 followed by Fe₃O₄ and Cu. However, with increase in Ha the Nuavg and Shavg diminish by maximum 62.33% and 74.56%, respectively, for Fe₃O₄ nanoparticles at N = 5 followed by Al₂O₃ and Cu.

This research study numerically examines the sensitivity of Fe₃O₄, Cu and Al₂O₃ nanoparticles in a magnetic field for buoyancy-induced mixed convective heat and mass transfer phenomena in a BFS channel, which was not analyzed earlier.

The purpose of this review is to narrate the microbiological quality of variety of street foods which are largely consumed by the Bangladeshi people of all ages. However, these foods are prone to microbial contamination. Most of the vendors lack the awareness on hygiene during preparing, processing or handling the foods. The insufficiency in regular microbiological analysis further casts the possibility of disease onset. The need of microbial analyses of these foods also remains unclear to the consumers, which, in turn, results in microbial infections and intoxications remaining unnoticed.

The present review focused on the microbiological quality of the street foods projected from the locally conducted researches on street foods, and pondered on the possible management from a microbiological perspective for ensuring consumer safety.

This paper provides comprehensive information on the microbiological quality of street foods, requirement of maintenance of hygiene by the vendors and consumers and the necessity of adopting proper management during food preparation.

Demonstration of microbial prevalence in the street foods may bring imperative information on food safety and security. The conclusive message of this review is about the general consciousness on the microbiological aspects of street food contamination.

This study aims to provide empirical evidence on the return and volatility spillover effects between Southeast Asian stock markets, bitcoin and gold in the periods before and during the COVID-19 pandemic. The interdependence among different asset classes, the two leading stock markets in Southeast Asia (Singapore and Thailand), bitcoin and gold, is analyzed for diversification opportunities.

The vector autoregressive-Baba, Engle, Kraft, and Kroner-generalized autoregressive conditional heteroskedasticity model is used to capture the return and volatility spillover effects between different financial assets. The data cover the period from October 2013 to May 2021. The full period is divided into two sub-sample periods, the pre-pandemic period and the during-pandemic period, to examine whether the financial turbulence caused by COVID-19 affects the interconnectedness between the assets.

The stocks in Southeast Asia, bitcoin and gold become more interdependent during the pandemic. During turbulent times, the contagion effect is inevitable regardless of region and asset class. Furthermore, bitcoin does not provide protection for investors in Southeast Asia. The pricing mechanism and technology behind bitcoin are different from common stocks, yet the results indicate the co-movement of bitcoin and the Singaporean and Thai stocks during the crisis. Finally, risk-averse investors should ensure that gold constitutes a significant proportion of their portfolio, approximately 40%–55%. This strategy provides the most effective hedge against risk.

The mean return and volatility spillover is analyzed between bitcoin, gold and two preeminent stock markets in Southeast Asia. Most prior studies test the spillover effect between the same asset classes such as equities in different regions or different commodities, currencies and cryptocurrencies. Moreover, the time-series data are divided into two groups based on the structural break caused by the COVID-19 pandemic. The findings of this study offer practical implications for risk management and portfolio diversification. Diversification opportunities are becoming scarce as different financial assets witness increasing integration.

Whilst a modest number of investigations have been undertaken concerning nanofluids (NFs), the exploration of fluid flow under exponentially stretching velocities using NFs remains comparatively uncharted territory. This work presents a distinctive contribution through the comprehensive examination of heat and mass transfer phenomena in the NF ND–Cu/H₂O under the influence of an exponentially stretching velocity. Moreover, the investigation delves into the intriguing interplay of gyrotactic microorganisms and convective boundary conditions within the system.

Similarity transformations have been used on PDEs to convert them into dimensionless ODEs. The solution is derived by using the homotopy analysis method (HAM). The pictorial notations have been prepared for sundry flow parameters. Furthermore, some engineering quantities are calculated in terms of the density of motile microbes, Nusselt and Sherwood numbers and skin friction, which are presented in tabular form.

The mixed convection effect associated with the combined effect of the buoyancy ratio, bioconvection Rayleigh constant and the resistivity due to the magnetization property gives rise to attenuating the velocity distribution significantly in the case of hybrid nanoliquid. The parameters involved in the profile of motile microorganisms attenuate the profile significantly.

The current simulations have uncovered fascinating discoveries about how metallic NFs behave near a stretched surface. These insights give us valuable information about the characteristics of the boundary layer close to the surface under exponential stretching.

The novelty of the current investigation is the analysis of NF ND–Cu/H₂O along with an exponentially stretching velocity in a system with gyrotactic microorganisms. The investigation of fluid flow at an exponentially stretching velocity using NFs is still relatively unexplored.