Mbeya University of Science and Technology (MUST) is a public university in Mbeya, southern Tanzania.
Solar-powered irrigation Systems (SPIS) are critical for agricultural production enhancement, food security and climate change adaptation, especially in Arid and Semi-Arid Lands (ASAL). There is increased attention towards shifting to more abundant and cleaner energy potential sources for revitalising irrigation strategies in ASAL areas. This study employed a geospatial approach to identify suitable locations for solar-powered irrigation systems (SPIS) in Baringo County, Kenya. Based on an integrated use of GIS spatial analysis and analytical hierarchy procedure (AHP), suitable locations for solar-powered irrigation were mapped. Precipitation, irrigated areas, proximity to rivers, slope, and solar radiation were analysed and processed to derive spatially explicit SPIS suitability classes ranging from very low to very high suitability. The thematic layers were assigned weights based on Saaty’s AHP method, where weights for each factor were determined from a pairwise comparison matrix, and a Weighted Linear Combination (WLC) approach was used to derive the final suitability classes for the county. The findings reveal that approximately 58
Land Use and Land Cover (LULC) changes due to human activities and natural factors significantly influence the variation in Ecosystem Service Values (ESVs). This study assessed the spatio-temporal dynamics of ESVs in Baringo, an Arid and Semi-Arid Land (ASAL) county located in Kenya’s Great Rift Valley, over 24 years (2000–2024). The Benefit Transfer Method (BTM) was employed to estimate ESV changes using LULC data for the years 2000, 2014, and 2024, alongside updated valuation coefficients from the Ecosystem Services Valuation Database (ESVD) published by de Groot and others in 2020. The analysis revealed a substantial decline in the total ESVs in Baringo County, from United States Dollars (US) 25.70 billion in 2000 to US14.92 billion in 2024, representing a loss of US-10.78 billion (-41.9
An optimal control model for rotavirus transmission was formulated to minimize both the cost of implementing interventions and the burden of infection among children and caregivers. The model integrates five time-dependent control functions: vaccination of children (u1), public health education (u2), treatment of infected children (u3), water treatment and sanitation (u4), and hygiene promotion (u5). Pontryagin’s Maximum Principle was applied to derive the necessary conditions for optimality, and numerical simulations were conducted using the Runge–Kutta method to determine the optimal time-dependent control profiles and corresponding epidemiological outcomes. Simulation results at t=220 days indicate a substantial reduction in rotavirus infections among children and caregivers when integrated controls are applied. The number of infected and hospitalized children (Ib and Hb) approach zero, while the vaccinated population (Vb) reaches approximately 2.58×107, confirming the central role of vaccination in suppressing new infections. The concentration of environmental rotavirus particles (Cr) also tends to zero, highlighting the combined efficacy of hygiene and sanitation interventions in reducing environmental transmission. Among the evaluated control strategies, the combination of vaccination, treatment, and hygiene (S13) emerges as both the most cost-effective and epidemiologically impactful strategy. This approach achieves near-complete elimination of child infections at a moderate total cost of approximately $6.17×1011, yielding the best balance between health outcomes and economic feasibility. In contrast, the single-control strategies (S1–S5) achieve minimal infection reduction despite lower costs, while multi-control strategies involving all five interventions (S17) provide marginal epidemiological improvement at substantially higher cost. The cost-effectiveness analysis, expressed as cost per health unit reduced, identifies vaccination (u1) and treatment (u3) as the primary contributors to financial cost, while hygiene adherence (u5), sanitation (u4), and education (u2) offer strong epidemiological benefits with minimal marginal cost. This demonstrates that optimal disease control is achieved when vaccination and treatment are combined with sustained hygiene practices rather than through expensive full scale interventions. Overall, the results confirm that targeted multi control strategies particularly S13p rovide the most practical and sustainable pathway for reducing rotavirus transmission, minimizing infections, and optimizing public health expenditure.
Qualitative data saturation is a critical concept that underpins the rigor, trustworthiness, and completeness of qualitative research, yet interaction of its determinants remains inconsistently defined and operationalized across disciplines. This meta-analytical review synthesizes empirical and methodological evidence from 18 studies (2012–2024) to identify and analyze the determinants of qualitative data saturation, a critical benchmark for methodological rigor and trustworthiness in qualitative research. Specifically, this study aimed to (i) to identify and synthesize empirical studies that assess saturation in qualitative research, (ii) to identify the factors (determinants) that influence how and when data saturation is achieved in qualitative research, (iii) to determine the sample size required to assess the level of saturation, the approaches used to assess the level of saturation, and (iv) suggest the guidelines that can be drawn from these studies. The analysis reveals that data saturation is not determined by isolated factors but emerges from the dynamic interplay of five primary determinants, namely sample size, participant heterogeneity, study design complexity, data collection methods, and researcher experience. Also, it was revealed that the sampling method and the nature of the recruited interviewees (homogeneity) had no significant effect on saturation. In contrast, datasets collected via the same sampling method exhibited outliers in data saturation. By reviewing existing literature, this study identified common methods for assessing data saturation and determined the corresponding sample sizes. These approaches bolster the credibility of small-sample (n = 20) studies by ensuring data saturation, particularly within homogeneous research populations. This study successfully addressed qualitative sample size saturation but overlooked its application in focus group discussions (FGDs). Additionally, because the variables affecting maximum saturation were not evaluated, further research is warranted to provide a more comprehensive understanding.
In this article, we study asymptotically regular interpolative omega-Proinov-Kannan and omega-Proinov-Hardy-Rogers contraction mappings and establish new fixed point results for these mappings in the setting of orthogonal quasi-partial b-metric spaces. Unlike many existing approaches, the class of mappings considered here is not necessarily continuous on their domains. To demonstrate the validity and applicability of our results, we provide illustrative examples that extend and generalize the classical Banach contraction principle. Furthermore, we present applications to fractional differential equations by employing the variational iteration method (VIM). In particular, we establish the existence of fixed point theorems for solving the wave equation, investigate the existence of solutions to time-fractional diffusion equations, and provide further applications of our results to fractional differential equations within orthogonal quasi-partial b-metric spaces.
