Scientific African最新文献

The study investigated the moderating role of public indebtedness on the relationship between per capita income and government healthcare financing in Sub-Saharan Africa (SSA). Based on panel data for 35 SSA countries over the period 2010 – 2020, the panel quantile Autoregressive Distributed Lag (ARDL) model with dynamic fixed effects was applied. Robustness analysis was performed using the panel Fully Modified Ordinary Least Squares (FMOLS) approach. It was established that income per capita positively influenced per capita government health spending while the debt burden had a negative effect. The coefficient for the interaction term was negative and significant, affirming the hypothesis that indebtedness distorts the positive impact of per capita income on government healthcare financing. To mitigate the adverse effects of indebtedness on healthcare financing, there is a need for SSA countries to maintain public debt at appropriate levels and allocate borrowed funds to projects that stimulate economic growth.

Soil nutrient deficiency poses great challenge to efforts aimed at improving agricultural productivity in Southern Africa. Agroforestry fertilizer tree technologies have potential to improve soil productivity in cropping systems. As such understanding the socio-economic and biophysical drivers in promoting adoption, and use of Tephrosia vogelii (T. vogelii) would provide requisite knowledge to stakeholders who promote integration of fertilizer tree technologies. This study conducted an analysis of effectiveness of by-laws, other socio-economic drivers, and biophysical factors in promoting the adoption and use of T. vogelii in Kasungu district in the central region of Malawi. The study used multistage sampling technique and data from 432 farmers. A Double Hurdle model was used where Probit regression and Truncated regression models were incorporated in the first and second hurdle, respectively. The study found that by-laws, seed availability, frequency of extension officer's visits before planting, technology provider and field characteristics influenced adoption and utilization intensity of T. vogelii in Kasungu district, Malawi. Awareness creation on developed by-laws and enforcement, promoted the adoption of intercropping of T. vogelii in the maize-based cropping system.

The paper introduced a novel family of distributions, called the Kumaraswamy Ramos-Louzada-G (KumRL-G) class, focusing on the five-parameter Kumaraswamy Ramos-Louzada Weibull (KumRLW) distribution. This new family of distributions, which includes existing and numerous new sub-models, offers improved flexibility and accuracy in modeling and analyzing survival data. Key statistical properties, including quantile function, moments, and entropy measures underlying the distribution have been derived, and characterizations have also been provided based on the ratio of two truncated moments and the hazard rate function. The maximum likelihood estimation (MLE) is employed to estimate the parameters of the proposed probability distribution, and Monte Carlo simulation analysis is performed to demonstrate the effectiveness of this method. The significance and adaptability of the new family of distributions are revealed through applications to COVID-19 and survival rate to age 65 of male cohort datasets from Ghana, Nigeria, and Canada. A new location-scale regression model was subsequently formulated from the new KumRLW distribution. Its practicality was demonstrated using survival data on hypertension from Ghana with gender as a covariate. The regression analysis showed that gender is a significant factor in the length of time before hypertension develops. The new KumRL-G family with baseline Weibull distributions provides more flexibility and improved fit in modeling various shapes and behaviors in the survival datasets surpassing its existing sub-models and other notable distributions.

We introduce and study a new generalized family of distributions herein referred to as the Marshall–Olkin Exponentiated Half Logistic-Generalized-G (MO-EHL-GG). A generalized distribution is a broader class of probability distributions that includes various specific distributions. It has parameters that allow for flexibility in modeling different types of data. By combining the Marshall–Olkin generator, the exponentiated half logistic generator and the generalized generator, the MO-EHL-GG family of distributions is developed. The primary objective behind introducing this new distribution is its enhanced flexibility and the ability of its hazard rate function to exhibit diverse shapes, making it valuable for statistical analysis and modeling purposes. Special cases of the new model are presented. Mathematical and statistical properties of the distribution are investigated. Estimates of the parameters are provided and simulation studies are conducted to examine the consistency of the model’s estimates. The significance of the new model is finally investigated through applications to real-life data sets. Three datasets were analyzed, demonstrating superior performance of our proposed distribution compared to competing models with the same number of parameters.

Coastal wetlands play a crucial role in supporting biodiversity, providing valuable ecosystem services, and contributing to the resilience of coastal ecosystems, making the preservation and restoration of these wetlands essential for sustainable development in coastal regions. This study focuses on Lake Manzala, a coastal wetland located on the Mediterranean Coast of Egypt, highlighting the significance of conserving and managing this unique environment. The objective of this research was to evaluate the water quality and phytoplankton structure of Lake Manzala and establish an updated long-term ecological database for the region, specifically evaluating the effectiveness of development plans that were carried out in 2017. Surface water samples were collected seasonally at eleven sites between 2010 to 2022. The findings revealed that prior to the development plans, the phytoplankton abundance in Lake Manzala exhibited high levels of eutrophication, characterized by increased abundance and species richness. The dominant phytoplankton classes in Lake Manzala were Bacillariophyceae, Chlorophyceae, and Cyanophyceae. Prior to development plans, they accounted for 46.5% and 45.0% respectively. Post-development, Bacillariophyceae increased to 62.8%, while Chlorophyceae decreased to 25.1%. Dinophyceae increased from 1.3% to 9.04%, while Cyanophyceae decreased from 6.1% to 1.6%. Based on the Trophic State Index for chlorophyll a, Lake Manzala underwent a shift from predominantly hypertrophic to eutrophic conditions. The study explored the relationship between biological factors and environmental conditions using principal component analysis, cluster analysis, and the modified water quality index (WQI). The results indicated positive signs of improvement in Lake Manzala during the post-development phase, as it transitioned from a poor to a moderate state. This research emphasizes the need for integrated land and water management approaches. By informing policy direction and development, this research underscores the importance of preserving and restoring ecosystems for the long-term well-being of both local communities and the global environment.

Richards Bay Harbour is South Africa's largest and busiest deep-water port by tonnage, and this ongoing shipping and port activities will expectedly result in metal contamination issues. The adjacent Mhlathuze Estuary is a nature reserve with a long history with Richards Bay Harbour and may be prone to metal contamination from multiple sources. The study investigates the sources of contaminated sediments in these two South African estuaries arising from their proximity to various anthropogenic activities. Investigating these sources of contamination is crucial for developing effective pollution control strategy since Richards Bay Harbour and Mhlathuze Estuary are regarded as estuaries of national conservation importance in South Africa. To provide further insights, sediment samples were acid digested and quantified for metal concentrations using Inductively coupled plasma-optical emission spectrometry (ICP-OES). Multivariate (SIMPROF and cluster) analysis was used to identify how sampling sites in Richards Bay Harbour and Mhlathuze Estuary were grouped based on sediment metal concentrations. Results of pollution load index for Richards Bay Harbour showed site 4 to be heavily polluted, while site 3 in Mhlathuze Estuary showed moderate pollution. Multivariate analysis (SIMPROF and cluster) further revealed sites related to anthropogenic activities and those that were unpolluted. Engaging this advanced analysis enhanced the ability to delineate potential pollution sources and further helped in the identification of the main contributors to sediment pollution. The findings indicate that port and industrial activities are the major contributors to sediment contamination at the estuaries. The results provide specific insights into the sources of pollution, informing targeted environmental management and policy-making efforts to protect and improve the estuarine environments.

In most developing countries, rural women are still marginalized in many domains to work in the non-farm economy, partly because the persistent unequal division of domestic burdens leaves rural women time-constrained. Yet, time poverty has received little consideration in the context of women's participation in non-farm work. This study presents evidence on the effect of time poverty on rural women's participation in non-farm work based on cross-sectional data collected from 300 rural women. We use two-stage residual inclusion instrumental variable (2SRI-IV) and recursive bivariate probit methods to address potential endogeneity. We find that time poverty is prevalent with 6 out of 10 women having insufficient time for non-farm work. The empirical results indicate that time poverty reduces women's participation in non-farm work in rural Ethiopia. This study suggests that relaxing women's time constraints coupled with meaningful rural education and infrastructure access might be vital in spurring their participation in the non-farm sector.

Rapid urbanisation has put farming systems under stress. Yet, conservation agriculture promotes environmentally friendly and productive agriculture. This paper therefore aims at estimating the effects of urbanisation on the adoption of soil conservation practices (SCPs) in urban and peri‑urban vegetable production in Yaoundé, Cameroon. Data from a survey conducted by the World Vegetable Center among 185 vegetable producers and Google Maps were analysed using a Multivariate Probit model with robust standard errors to investigate the adoption of four interdependent SCPs. Descriptive results showed that the most SCP adopted was organic manure (85 %), the least adopted was mulching (61 %), and that the adoption intensity was relatively high as the mean number of SCPs adopted was 2.87 out of 4. In addition, the regression results showed that urbanisation reduces the adoption of SCPs; in particular, proximity to city centre reduces the adoption of crop rotation, organic manure, mulching, and fallow, while population density decreases the practice of fallow. Henceforth, to ease the perverse effects of urbanisation on the adoption of SCPs, decision-makers and local authorities should ensure the preservation of productive agricultural zones by elaborating urban master and zoning plans that take into account agricultural purposes, and by formalising property rights on agricultural lands in urbanising areas.