http://repository.must.ac.ke/handle/123456789/12 All theses and dissertations by bona fide master & Phd students of Meru University of Science and Technology. 2026-07-06T15:36:54Z http://repository.must.ac.ke/handle/123456789/1640 Physicochemical and Phytochemical Characterization of Dovyalis caffra and Dovyalis abyssinica Fruits Mwangi, Waweru Daniel 2023-01-01T00:00:00Z http://repository.must.ac.ke/handle/123456789/1638 Meerkat-Based Multi-Wavelength Study of Supernova Remnant SN386 (G7.7-3.7) ; Mwaniki, Patrick Njoroge Supernova remnant SN386(G7.7-3.7) presented captivating attention for multi-wavelength observation. In this study, we investigated the structural characteristics of G7.7-3.7 with higher resolution MeerKAT observation at 1284 MHz, revealing intricate details of its morphology and emission mechanisms. MeerKAT observations revealed G7.7-3.7 as an almost circular structure with filamentary features, manifesting in various blowouts. The western boundary exhibited a strong bright blowout, while the southern perimeter show cased extended bright filaments with feather-like structures, seemingly disconnected from the western blowout. Moreover, the eastern region presented a faint blowout with a cen tralized bright point source, while faint elongated filaments traversed the northwest, linked the eastern point source and western blowout and progressed outward uniformly. Spectral index analysis indicated a steep spectrum (𝛼 ranged ∼ 0 to ∼-3), suggesting a combination of synchrotron and few traces of thermal emissions at the edges of bright blowouts. Bright blowouts with a less steep spectrum ranging from ∼-0.5 to ∼-1.5 were dominated by shock-accelerated particles encountering irregularities and weakening in magnetic fields. Spectral index values close to 𝛼 = 0, showed the presence of traces of thermal emissions from shock-heated gases, especially at the edge of the bright blowout. However, the faint emissions along the filaments connecting the eastern and western blowouts with a very steep spectral index of ∼-3 comprised synchrotron emissions from aged particles that had dissipated energy due to turbulent re-acceleration. Analysis of MeerKAT and VLA data gave an expansion of Δ𝜃 = 9 ± 0.45 arcsec over a period of Δt = 31.907 yr corresponding to an expansion rate 𝜃 = 0.282 ± 0.014 arcsec yr−1 . The data recorded a shock speed of 5883 ± 294 km s−1 and an age of 1636 ± 115 years. The revised age fitted with the explo sion event of 386 CE and the observed data in 2023. Furthermore, our multi-wavelength investigation unveiled an intriguing structure within the southern radio blowout exhibiting a convergence of features such as the bright radio blowout, a prominent X-ray arc and two faint optical filaments aligned with the X-ray bright arc. We attributed the bright radio blowouts to the non-uniform mass outflow from the localized high-density population of the shock-accelerated particles and the weakening of magnetic fields along its perimeter. Thermal emissions traces along the edges of blowouts resulted from shock-heated gases intensifying in the south due to the presence of high-density ISM. Thus, we proposed that the supernova of G7.7-3.7 occurred in an environment of varying densities of interstellar medium (ISM). Consequently, this environment facilitated X-ray emissions and the forma tion of faint optical filaments due to collisions with the ISM and the circumstellar materials from the progenitor star respectively. Our findings shed light on the complex interplay of physical processes within G7.7-3.7, offering valuable insights into the dynamics and evo lution of supernova remnants 2025-01-01T00:00:00Z http://repository.must.ac.ke/handle/123456789/1637 Deterministic and Stochastic Modeling of Clinical Dynamics of HIV-HBV Co-Infection with Optimality Mirchigan, James Khobocha HIV and HBV infections are viral infections with the same route of transmission through sexual intercourse with an infected person and mother-to-child transmission among other means of transmission. Over the decades, these mono infections have led to the deaths of millions of people around the world despite increased access to prevention, diagnosis, treatment, and care. Yet, there have been no conclusive findings in the hunt for HIV/AIDS cure or vaccine. However, the hepatitis B vaccine is available, though not easily acces sible. Consequently, HIV and HBV co-infection is equally a major global health burden that has attracted limited research interest. The interactions and synergistic relationship between these viruses are not well understood and documented. The co-infection presents complex transmission dynamics within a population. Few mathematical models of HIV and HBV co-infection are available that include risk factors and control measures. The effect of variability in predicting infection outcomes is also not captured in deterministic models. In addition, optimality conditions in co-infection models are not explored. This study sought to model HIV and HBV co-infection with optimal control interventions. This study set out to develop and examine a deterministic model of HIV-HBV co-infection, for mulate an optimal control problem for the deterministic model and determine the optimal controls and finally convert the deterministic model into a stochastic model that accounts for variability and uncertainties in infection outcomes. The deterministic model formu lation is based on SI and SIRS epidemic model framework. The theories of calculus are applied to analyze the deterministic model based on reproduction numbers. The thresh old parameter; the basic and control reproduction number is obtained using the Jacobian NGM and survival function approaches. Co-infection-free and endemic equilibrium points are determined and it’s local and global stability analysis established using Routh-Hurwitz criterion and Metzler matrix method respectively. The local sensitivity analysis of the model parameters on R0 and A0 are determined by use of forward normalized sensitivity index method. Using Pontryagin’s Maximum Principle, an optimal control problem is for mulated. The stochastic model is developed by extending the deterministic model using SDEs. The three models are implemented using MATLAB solver based on Runge-Kutta and Euler-Maruyama numerical schemes. The normalized sensitivity analysis of model parameters showed that co-infection transmission rate, β4 and recruitment rate, π con tribute the highest to R0 and A0. Numerical simulations of deterministic model revealed that the combined effect of clinical and non-clinical control interventions led to the re duction in infection rates with time. The effect of HIV and HBV viral loads on infection progression pointed out that the progression is faster at high levels of viral loads. Further, numerical results of optimal controls exhibited a gradual decrease in co-infection of HIV HBV. The sample paths of SDEs showed variations in infection outcomes due to random noise transmission. Thus, this study recommends that focus should be directed towards reducing co-infection rate and vertical transmission to mitigate the co-infection, while re inforcing policies relating to both clinical and non-clinical control interventions at optimal conditions 2025-01-01T00:00:00Z http://repository.must.ac.ke/handle/123456789/1636 Uptake of Digital Innovation Strategy on Financial Performance of Commercial Banks In Kenya Kimathi, Doris Kagendo Rapid evolution of digital innovations globally, has seen Kenyan banking sector incorporate innovation strategy in its operations. Despite these momentous advancements, the extent to which the digital innovation strategy translate into improved financial performance of commercial banks in Kenya remains uncertain. Lack of extensive empirical studies on how key variables-process, product, marketing and organizational innovation strategy relates to regulatory environment exacerbates the gap further. The study sought to assess the effect of the uptake of digital innovation strategy on the financial performance of commercial banks in Kenya, specifically on Return on Equity (ROE). The specific objectives were to assess the effect of uptake of process, investigate the effect of uptake of product, establish the effect of uptake of marketing and analyze the effect of uptake of organizational innovation strategy on financial performance of commercial banks in Kenya. Government policies moderated the relationship between the independent and dependent variables while the hypotheses were derived from the study objectives. The study was guided by Rogers’ Diffusion of Innovation Theory, the Evolutionary Theory of Economic Change, Disruptive Innovation Theory, Theory of Dynamic Capabilities and the Institutional Theory. The study adopted a positivist research philosophy. Using stratified random sampling, a sample size of 315 was used from a target population of 1470 employees derived from 38 commercial banks, with pilot test carried out in Kingdom Bank. Primary data was gathered using structured questionnaires, while secondary data on ROE was obtained from banking sector supervisory and innovation reports. Reliability was estimated using Cronbach’s Coefficient Alpha, while content validity was assessed through the Kaiser-Mayer-Olkin (KMO) measure and Bartlett’s test of sphericity. A descriptive study design was employed, and data analyzed using frequency tables, pie charts, mean, standard deviation, and bar graphs for descriptive statistics. A panel linear regression model was utilized where a simple linear regression model was used for each independent variable, followed by a joint model to determine the combined effect. The study accounted for assumptions of linearity, normality, heteroscedasticity, and multicollinearity. The study realized a significant and positive correlation (P˂0.05) between digital innovation strategy and financial performance of commercial banks in Kenya. The study reveals that process innovation strategy, which includes ideation, routine automation, and creativity leads to operational efficiency, cost saving, revenue growth and customer satisfaction. The study recommends that commercial banks enhance their talent development strategies, engage in strategic collaborations, prioritize customer centrality, and adopt agile management practices to drive financial performance. Further, banks can invest in Greentech products, innovation labs, decentralize decision-making and stay abreast of regulatory requirements to positively improve financial performance. The study contributes to the understanding of how digital innovation strategy directly affect financial performance within Kenyan banking sector. By proposing comparative studies across diverse contexts, it offers a basis for assessing the generalizability of these findings to other industries and regions. 2025-01-01T00:00:00Z