Browsing by Author "Dhlamini, M."

Now showing 1 - 6 of 6
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    A mathematical model for bioconvection flow with activation energy for chemical reaction and microbial activity
    (Indian Academy of Sciences, 2022-01-23) Dhlamini, M.; Mondal, H.; Sibanda, P.; Mosta, S.S.; Shaw, S.
    In most of the industrial processes, it is of paramount importance to control the heat and mass transfer rates to ensure high-quality products. Using nanofluids instead of ordinary fluids and using motile micro-organisms are some of the techniques to control heat and mass transfer rates. In some recent studies of bioconvection flow, activation energy, Brownian motion and thermophoretic effects are considered only for the solute and not for the microbes. Our current study incorporates these effects for the motile micro-organisms too. Few, if any results of this nature exist in literature. A system of partial differential equations is formulated to incorporate the effects of these parameters. The system of equations are solved numerically using the spectral quasi-linearisation method to gain an insight into the influence of key parameters on the fluid and flow properties. The thermophoretic force, the Brownian motion and activation energy are significant contributors in the microbes’ dynamics. The concentration of microbes decreases with an increase in the thermophoretic force and increases with increasing microbe’s Brownian motion parameter. Based on our results, we conclude that increasing activation energy leads to a decrease in microbes’ velocity. The inclusion of the microbes’ Brownian motion proved to be significant as this was shown to have an impact on the temperature, solute concentration and microbes’ concentration in the boundary layer.
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    An Analysis of Eccentricity-Based Invariants for Biochemical Hypernetworks
    (Wiley, 2021-10-06) Rashid, M.A.; Ahmad, S.; Siddiqui, M.K.; Manzoor, S.; Dhlamini, M.
    Biological proceedings are well characterized by solid illustrations for communication networks. The framework of biological networks has to be considered together with the expansion of infectious diseases like coronavirus. Also, the graph entropies have established themselves as the information theoretic measure to evaluate the architectural information of biological networks. In this article, we examined conclusive biochemical networks like t‐level hypertrees along with the corona product of hypertrees with path. We computed eccentricity‐based indices for the depiction of aforementioned theoretical frameworks of biochemical networks. Furthermore, explicit depiction of the graph entropies with these indices is also measured.
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    Modelling an Optimal Climate-Driven Malaria Transmission Control Strategy to Optimise the Management of Malaria in Mberengwa District, Zimbabwe: A Multi-Method Study Protocol
    (MDPI, 2025-03-29) Dhlamini, M.; Chivasa, T.; Maviza, A.; Nunu, W. N.; Tsoka-Gwegweni, J.
    Malaria is a persistent public health problem, particularly in sub-Saharan Africa where its transmission is intricately linked to climatic factors. Climate change threatens malaria elimination efforts in limited resource settings, such as in the Mberengwa district. However, the role of climate change in malaria transmission and management has not been adequately quantified to inform interventions. This protocol employs a multi-method quantitative study design in four steps, starting with a scoping review of the literature, followed by a multi-method quantitative approach using geospatial analysis, a quantitative survey, and the development of a predictive Susceptible-Exposed-Infected-Recovered-Susceptible Geographic Information System model to explore the link between climate change and malaria transmission in the Mberengwa district. Geospatial overlay, Getis–Ord Gi* spatial autocorrelation, and spatial linear regression will be applied to climate (temperature, rainfall, and humidity), environmental (Land Use–Land Cover, elevations, proximity to waterbodies, and Normalised Difference Vegetation Index), and socio-economic (Poverty Levels and Population Density) data to provide a comprehensive understanding of the spatial distribution of malaria in Mberengwa District. The predictive model will utilise historical data from two decades (2003–2023) to simulate near- and mid-century malaria transmission patterns. The findings of this study will be used to inform policies and optimise the management of malaria in the context of climate change.
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    Numerical Analysis of Couple Stress Nanofluid in Temperature Dependent Viscosity and Thermal Conductivity
    (Springer Nature, 2021-02-24) Dhlamini, M.; Mondal, H.; Sibanda, P.; Motsa, S.
    This communication reports on an innovative study of two-dimensional couple stress fluid 3 with effect of viscosity and conductivity. We proposed a new model based on temperature dependent variable thermal conductivity on kinetic theory. Our model assumes that thermal conductivity is a decreasing function of temperature rather than an increasing function. The effect of the three key parameters, viscosity, thermal conductivity and couple stress parameter are analyzed. The coupled non-linear system is further validated numerically using the spectral quasilinearization method. The method is found to be accurate and convergent. Increasing the temperature dependent parameter for viscosity is shown to reduce the heat mass transfer rates at the surface. Increasing thermal conductivity and the couple stress parameter increased the heat mass transfer rates on the boundary surface.
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    On Degree-Based Topological Indices for Strong Double Graphs
    (Hindawi, 2021-02-02) Rafiullah, M.; Siddiqui, H.M.A.; Siddiqui, M.K.; Dhlamini, M.
    A topological index is a characteristic value which represents some structural properties of a chemical graph. We study strong double graphs and their generalization to compute Zagreb indices and Zagreb coindices. We provide their explicit computing formulas along with an algorithm to generate and verify the results. We also find the relation between these indices. A 3D graphical representation and graphs are also presented to understand the dynamics of the aforementioned topological indices.
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    On Topological Analysis of Entropy Measures for Silicon Carbides Networks
    (Wiley, 2021-11-05) Wang, X.L.; Siddiqui, M.K.; Kirmani, S.A.K.; Manzoor, S.; Ahmad, S.; Dhlamini, M.
    The silicon material has provoked and stimulated significant research concern to a considerable extent taking into account its marvelous mechanical, optical, and electronic properties. Naturally, silicons are semiconductors and are utilized in the formation of various materials. For example, it is used in assembling the electronic based gadgets. In this article, we have studied the 2D structure of silicon carbide Si2C3 − I[m, n] and Si2C3 − II[m, n] and then continued to discuss some degree grounded topological descriptors in association with their corresponding entropy measures. We extend this computation to the quantitative and pictorial comparisons which could be beneficial in the structure amendment for effective implementation.