Scientific African最新文献

Malaria remains a significant public health challenge globally, particularly affecting children under-5 years of age due to their underdeveloped immune systems. Identifying the risk factors associated with malaria infection in this vulnerable group is crucial for improving policy formulation and creating effective training programs. However, there is limited information on how the relationship between malaria risk and associated factors varies across different regions, especially among children in Ghana. This is important because understanding these spatial variations can enhance targeted interventions including area remediation and resource allocation. To address this gap, a geographically weighted logistic regression (GWLR) model was developed to identify spatially varying risk factors for malaria infection among children under five in Ghana. The model was built on the premise that the relationship between malaria and potential risk factors is not uniform across geographic areas. Data from the Ghana Malaria Indicator Survey collected through the demographic and health survey program were used for analysis. The study found that the GWLR model fit the data better than the conventional binary logistic regression (BLR) model, based on the information criterion used and mode evaluation metrics. The results indicated that risk factors for malaria such as a child's age, anaemia status, dwellings sprayed, place of residence, electricity access, NHIS (National Health Insurance Scheme) coverage, age of the household head, and household wealth index, were non-stationary across the study area. These findings underscore the importance of spatially tailored interventions to reduce malaria risk in children under-5. The results contribute to the body of literature on malaria risk factors and provide valuable insights for Ghana's national malaria control policies, potentially enhancing the effectiveness of future public health strategies.

Skin aging is a common issue that is linked to changes in skin physiology, hydration, and barrier function. Dietary fatty acids (FA), particularly poly-unsaturated fatty acids (PUFA), can influence skin characteristics. It is reported that a deficiency of fatty acids in the skin is associated with skin aging. Therefore, the goal of the current study is to evaluate the antiaging effect of flaxseed oil or mustard oil-based nanoemulsion gel rich in fatty acids such as omega 3 on D-galactose-induced skin aging. N-hexane was used to extract the oils of black mustard and flax seed from their seeds, and the oils' fatty acid composition was then determined. A full factorial design was created to assess the impact of three variables: oil type, oil concentration, and S:Cos ratio, on various responses: globule size, zeta potential, and emulsification time of the self-nanoemulsifying system. Additionally, the polydispersity index, transmittance percentage, refractive index, cloud point, and viscosity were also estimated. TEM of the optimized formulations revealed a spherical form of oil globules with nanosize. The values for the zeta potential ranged from -12 to -34.2 mV. The optimized formulations were incorporated into a hydroxypropyl methyl cellulose solution to form a nanoemulsion gel. Skin aging was induced using the D-galactose model, and the impact of topical skin application of the optimized formulation gels on different biomarkers such as amino acids, B5, oxidative stress markers, inflammatory mediators and histopathological examination was evaluated. The results showed a considerable improvement in the evaluated parameters of the treated groups when compared to the untreated D-galactose group. The findings suggest that the nanoemulsifying system utilizing high doses of fixed plant oils could serve as a promising vehicle for enhancing skin rejuvenation. Flaxseed oil formulation showed greater potential compared to mustard oil formulation as skin antiaging.

Traditional clustering algorithms have often been used to categorize farmers but tend to overlook the underlying reasons for these groupings. Typically, clusters are formed based on common metrics such as dispersal and centrality, which provide limited insights into the relationships among key attributes. This study introduces an innovative approach using pattern and association rules analysis to better understand the characteristics of dairy production clusters. Focusing on Tanzanian smallholder farmers, the research moves beyond identifying clusters to uncovering the hidden relationships within them. Through pattern analysis, the study logically examines the behavioral mechanisms that define these clusters, highlighting service gaps that, if addressed, could enhance smallholder dairy farmers' productivity. Frequent patterns with support ranging from 57 % to 93 % and confidence levels between 85 % and 100 % were identified, revealing critical challenges faced by these farmers. For instance, farmers using Artificial Insemination—typically younger or new entrants—face constraints related to farm size, land holdings, fodder production, lack of farmer groups, and insufficient formal training in dairy care. Meanwhile, seasoned farmers deal more with institutional barriers such as limited access to marketplaces, extension services, and distant water sources. The study highlights the diverse challenges faced by different farmer groups and provides strategic recommendations for improving dairy productivity. Enhancing access to formal training, improving fodder production, supporting the formation of farmer groups, and addressing institutional barriers are key actions that could help Tanzanian smallholder dairy farmers increase milk yield and overall productivity.

This paper explores the hybridization of a five-phase permanent magnet synchronous generator integrated with a photovoltaic generator. The hybrid configuration aims to maximize overall energy production and optimize system performance. The distinctive feature of the proposed structure lies in the parallel connection of a five-phase machine with a Vienna rectifier and a PV system directly linked to the inverter. This novel integration, associated with the designed controllers, significantly reduces switching losses, enhancing system efficiency and demonstrating robust performance despite the complexities associated with the control strategy. The paper delves into the design and evaluation of this nonlinear hybrid system, shedding light on its potential to contribute to sustainable and efficient renewable energy solutions.

This study provides a thorough analysis of unit commitment (UC) formulations in the context of low-inertia power systems, which are increasingly prevalent as the transition to Renewable Energy Sources (RES) gain momentum. Given the move towards more sustainable energy models, incorporating RES presents unique challenges in maintaining grid stability due to their inherent lack of synchronous inertia. This review examined the intricacies of modelling energy market designs and UC strategies to tackle these challenges. The study explores the expansion of frequency response services, emphasizing the increasing dependence on ancillary services, particularly in markets with a substantial presence of RES, attention is focused on the unique operating challenges in regions like Sub-Saharan Africa, where dispersed grid networks and generation inadequacies compound the problem. The paper delves into different methodologies and modelling approaches used in frequency-constrained optimization, shedding light on the strengths and weaknesses of current practices. A crucial outcome of our study is that the use of uniform frequency response models to deduce post-fault frequency parameters will not give adequate results in sparsely connected power system networks. Also, studies primarily focus on generation adequacy and the reliability criterion of the largest generator outage, overlooking the potential impact of network constraints and congestions in their formulation. Our analysis provides valuable insights into creating market frameworks that optimize energy and ancillary services, ensuring a stable and efficient grid operation in a power system dominated by RES. Based on our findings, it is essential to establish electricity market frameworks that can effectively maximize the utilization of energy resources and address the specific regional challenges associated with frequency regulation services in the future.

Tabernaemontana crassa is a native plant indigenous to Ghana which has garnered local recognition for its purported efficacy against ringworm, wounds, abscesses, and antibacterial infections. However, the antibacterial and resistance modifying effects of the crude extracts and isolated compounds have not been investigated. Consequently, this study aims to evaluate the antimicrobial and resistance modifying effects of the extracts and affinine, a monoterpene indole alkaloid, from T. crassa. Four extracts, namely the crude, alkaloidal, glycosidic and triterpene fractions were prepared by solvent-solvent extraction from the stem bark of T. crassa. Using chromatographic and spectroscopic techniques, affinine was isolated and identified from the alkaloidal fraction. The effects of the extracts and affinine were investigated using the micro dilution, efflux pump and biofilm inhibition assays against Staphylococcus aureus and Pseudomonas aeruginosa. The crude extracts were effective against the two bacteria strains at a concentration of 500 µg/ml. Affinine was without activity in the in vitro antimicrobial assays with MIC >1000 µg/ml. However, affinine possessed anti-efflux and antibiofilm activity against the test microorganisms which was confirmed with in silico studies. The study showed the efficacy of the extracts against the two microbes associated with wound healing. Affinine, not previously described from T. crassa, may contribute to the anti-infective effects of the plant.