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Introduction: Diabetes mellitus or diabetes is a metabolic ailment which occurs as a result of insulin insufficiency or defect in insulin function, or both that leads to ihyperglycemia. Diabetes mellitus is a worldwide disease even though its prevalence in other countries vary. Kalanchoe crenata belongs to the family crassulaceae. It is also known locally as miracle plant and often utilized in Africa for medicinal purposes. The study was designed to ascertain the antidiabetic and dyslipidemic activity and effects of the ethanolic extract of both leaves and stem of Kalanchoe crenata on istreptozotocin incite diabetic rats for three (3) weeks. Methodology: 6-8 weeks old Sprague dawley rats received multiple injection of streptozotocin intraperitoneally (40mg/kg body weight) to induce diabetes melitus. Diabetes mellitus was observed and confirmed after six days of induction. The rats were given ethanolic extract of Kalanchoe crenata remarkably (10, 30 and 100mg/kg) and 5mg/kg glibenclamide orally twice daily for three weeks. Blood glucose, lipids, creatinine, urea, were then determined. Results: After week three of treatment 5mg/kg glibenclamide, 30 and 100mg/kg ethanolic extract of Kalanchoe crenata remarkably (p

Introduction: The breakthrough in the treatment of pathogenic diseases was the unearthing of naturally occurring antipathogenic agents or antibiotics. There have been upsurges in antibiotic-resistant strains of clinically important pathogens, which made way to the emergence of new-fangled bacterial strains that are multi-resistant. The major aim of scientists is to develop new antibiotics or other therapeutic strategies at a pace greater than that at which bacteria are developing resistance. The development of resistance to first-line antimicrobial therapies made way to recommendations for combination therapies for the treatment of some infections and some of this form of chemotherapy seems to be very successful. Objectives: This research was carried out to determine the effect of Kalanchoe crenata extracts on Salmonella typhi load. Also, to assess the potency of the extract of Vernonia amygdalina on Salmonella typhi and finally to ascertain the effect of the combined extract of Kalanchoe crenata and Vernonia amygdalina on Salmonella typhi. Methods: In this research, Salmonella typhi was exposed to a crude extract of Kalanchoe crenata and Vernonia amygdalina and also the combination of the two extracts. Agar wells diffusion method was employed. Results: The combined effect was not sensitive to the Salmonella strain. The Salmonella strain was resistant to V. amygdalina than to K. crenata. K. cranata had the strongest activity against S. typhi with its highest zone of growth inhibition of 20 mm and lowest zone of inhibition of 7 mm while V. amygdalina produced a consistent zone of growth inhibition of 5-6 mm; The combined effect produced a zone inhibition diameter only at the 100 mg/ml with a zone of inhibition value of 14 mm. The subsequent lower concentrations did not show any activity against the microbes. At P-value = 0.05 two-way ANOVA statistics exhibited significant differences amongst the effects produced by the different extracts, though there were no substantial differences in the effects produced by the various concentrations. Conclusion: The Salmonella strain was resistant to V. amygdalina than to K. crenata. At P-value = 0.05 there was a substantial difference in the sensitivity of the bacteria to the different extracts.

Village savings and loans has become a prominent financing option for micro and small enterprises in the Lilongwe District, Malawi. Despite this, its impact on the performances of micro and small e...

PurposeThis paper aims to analyze the effects of crop specialization on agricultural productivity and commercialization for farmers who produce high-value crops in the Northern Savannah Ecological Zone of Ghana.Design/methodology/approachThe study used the USAID/Ghana Feed the Future (FTF) survey, which collected data on high-value crops (i.e. maize, rice and soya). Data for the analysis consists of 2,903 farm households. The study utilized the three-stage generalized method of moment estimation technique to deal with the potential endogeneity of crop specialization within the context of productivity and commercialization and heteroscedasticity issues in the data.FindingsThe study found that crop specialization positively relates to agricultural productivity and commercialization, suggesting that increased crop specialization in the production of high-value stimulates productivity and opens market opportunities for farm households. These findings imply that crop specialization seems more beneficial to farmers as it significantly improves productivity and commercialization.Research limitations/implicationsThe study was conducted in the Northern Savannah Ecological Zone of Ghana and not the entire country.Originality/valueTo the best of the authors' knowledge, this study is the first to have jointly modeled crop specialization, agricultural productivity and commercialization. The main advantage of using this system approach is that it uses more information, thereby providing more precise parameter estimates.

This study investigated Bacillus subtilis ATCC13952 as an adsorbent for arsenic in groundwater. Batch experiments were used to determine the effect of contact time, adsorbent dose, arsenic (III) concentration, pH, and temperature on the process. The percentage of arsenic (III) removed was high at a contact time of four days, 3.0 mL of Bacillus subtilis ATCC13952, pH 8 and temperature of 35°C. The kinetics of the process showed the Elovich kinetics model as the best fit for the process. This indicates that arsenic removal was by chemisorption. The analysis of the nonlinear equilibrium isotherms and the error functions showed the Langmuir isotherm as best fit for the process. Mechanistic study of the process indicated bulk diffusion to be the rate-determining step. Thermodynamically, the process was favourable, spontaneous and feasible. When the community water samples were treated with the Bacillus subtilis ATCC13952 at the optimum contact time, adsorbent dose, pH and temperature, 99.96% - 99.97% of arsenic was removed across all sampling points within the studied communities. Hence, the results show that Bacillus subtilis ATCC13952 is an efficient adsorbent for arsenic in aqueous systems and the organism appears to hold the key to purging the environment of arsenic contamination.

IntroductionThe major breakthrough in the treatment of pathogenic diseases was the unearthing of naturally occurring antipathogenic agents or antibiotics. There have been upsurges in antibiotic-resistant strains of clinically important pathogens, which made way to the emergence of new-fangled bacterial strains that are multi-resistant. The major aim of scientists is to develop new antibiotics or other therapeutic strategies at a pace greater than that at which bacteria are developing resistance. Development of resistance to first-line antimicrobial therapies made way to recommendations for combination therapies for the treatment of some infections and some of this form of chemotherapy seems to be very successful.ObjectivesThis research was carried out the determine the effect of Kalanchoe crenata extract on salmonella Tyhi load. It was carried out to also assess the potency of the extract of Vernonia amygdalina on Salmonella typhi and also to ascertain the effect of the combined extract of Kalanchoe crenata and Vernonia amygdalina on salmonella typhi.MethodIn this research, Salmonella typhi was exposed to a crude extract of Kalanchoe crenata and Vernonia amygdalina and also the combination of the two extracts. Agar wells diffusion method was employed.ResultsThe combined effect was not sensitive to the Salmonella strain. The Salmonella strain was resistant to V. amygdalina than to K. crenata. K. cranata had the strongest activity against S. typhi with its highest zone of growth inhibition of 20 mm and lowest zone of inhibition of 7 mm while V. amygdalina produced consistent zone of growth inhibition of 5–6 mm; The combined effect produced a zone inhibition diameter only at the 100 mg/ml with zone of inhibition value of 14 mm. The subsequent lower concentrations did not show any activity against the microbes. At P-value = 0.05 two-way ANOVA statistics exhibited significant difference amongst the effects produced by the different extracts, though there were no substantial differences in the effects produced by the various concentrations.ConclusionThe salmonella strain was resistant to V. amygdalina than to K. crenata. At P-value = 0.05 there was a substantial difference in the sensitivity of the bacteria to the different extracts.

Trade openness is an important determinant of Foreign Direct Investment (FDI) inflows into Sub-Saharan Africa (SSA). Consequently, studies have examined the relationship between FDI inflows and trade openness. This study develops a new measure of trade openness to re-examine the relationship between FDI inflows and trade policy openness using principal component analysis. This new measure captures the ease of trading activities and trade tariffs. Dynamic panel estimation technique was employed to analyze the relationship between trade policy openness and FDI inflows in SSA countries. The results indicate that an open economy attracts FDI. The study recommends efforts at reducing cost of trade.

Conventional satellite sensors provide periodic data for monitoring Artisanal and Small-Scale Mining (ASM). Incorporating Unmanned Aerial Vehicle (UAV) sensors in monitoring ASM can increase data availability and also mitigate the challenge of cloud cover that causes data gaps in satellite data availability. However, most UAV sensors measure only in the Red-Green-Blue (RGB) bands and the utility of RGB for Land Use Land Cover (LULC) mapping is still in the preliminary stages. This study contributes to research by examining the accuracies of true color RGB images for mapping ASM, using the Birim Basin in Ghana as a case study. The study first compared Landsat 8 (L8) and Sentinel-2 (S2) full reflective bands for LULC mapping of the basin. The study then used true color RGB from UAV, L8 and S2 to map a subsection of the basin where there was active ASM. A test experiment was also performed in which other band combinations, single band, and indices were used to map ASM. From the results, the L8 and S2 full reflective bands attained Overall accuracy (OA) and User Accuracy (UA) over 97%, with less than 1% difference between their accuracies. All stand-alone RGB precisely mapped ASM with accuracies of 90% and above, indicating their fit for mapping ASM. However, the effect of image resolution caused differences in the surface area of the ASM estimated from the different sensors. Also, the different band combinations and indices could not accurately map ASM. Nonetheless, the results of the study showed increased scientific grounds for using UAV for mapping ASM. The overall results showed the capabilities of remote sensors in providing frequent and sustainable data for mapping ASM. Additionally, the results from the three images (L8, S2 and UAV) reavelaed much destruction of the forest cover due ASM. These results would be relevant in monitoring and managing the natural resources, which will help achieve environmental sustainability in meeting the SDG goals in 2030.

This paper employs the Bayesian Model Selection (BMS) to determine the link between Foreign Direct Investment (FDI) and export performance in Ghana. The BMS enables us to consider a large number of potential explanatory variables and deal with the issue of model uncertainty. The study revealed positive effect of FDI on export performance but not as a major driver of export growth in Ghana. However, the effect of domestic savings, trade liberalisation and infrastructure development are found to have stronger effect on export performance than FDI inflows. The study recommends government policies should be geared towards improving domestic savings and the liberalization of the economy towards international trade.

Artisanal and Small-Scale Mining (ASM) landscapes form integral part of the Land use land cover (LULC) in the developing worlds. However, the spatial, spectral, and temporal footprints of ASM present some challenges for using most of the freely available optical satellite sensors for change analysis. The challenge is even profound in tropical West African countries like Ghana where there is prolonged cloud cover. Whiles very few studies have used Sentinel-2 data to map change analysis in ASM landscape, none examined the contribution of individual S2 bands to the ASM classifications. Also, despite the capabilities of Machine Learning (ML) and Deep Learning (DL) models for LULC classifications, few studies have compared the performances of different classifiers in mapping ASM landscape. This study utilized Sentinel-2 data, four ML and DL models (Artificial Neural Network –ANN, Random Forest – RF, Support Vector Machines –SVM, a pixel-based Convolutional Neural Network-CNN) and image segmentation to examine the performance of S2 bands and ML and DL algorithms for change analysis in ASM landscape, with the Birim Basin in Ghana as a study area. The result of the change analysis was used to assess changes in LULC during the recent ban on the expansion of ASM in the country. It was found out that ANN is a better classifier of ASM achieving the highest overall accuracy (OA) of 99.80% on the segmented Sentinel-2 bands. The study also found out that the Band 5 Vegetation Red Edge (VRE) 1 contributed most to classifying ASM, with the segmented VRE 1 being superlative over the other predictors. In terms of expansion, ASM increased by 59.17 km2 within the period of the study (January 2017 to December 2018), suggesting that ASM still took place under the watch of the ban. The classification results showed that most of the peripheral of forest and farmland have been converted to ASM with little disturbance within the interior of the forest reserves. The study revealed that, the ban was yielding very little or no results due to a number of policy deficiencies including low staff strength, lack of logistics and low remuneration. Enforcement of legal instruments against ASM and farming activities within the forest reserves, improvement in the monitoring systems and intensification of public education on the value of forest and the need to protect it are some of the major recommendations that could control encroachment on the forest reserves.

Unsustainable anthropogenic activities such as indiscriminate logging of trees, mineral exploitation, conversion of forest into agricultural lands are known to cause major environmental changes, thereby triggering a chain of irreversible forest depletion. This has called an urgent need by government and private agencies to institute policies and programs to curtail the destruction of the ecosystem due to the pressure on the available land. In this study, the Land use/land cover changes between the period of 1986 and 2020 in the tropical rainforest of Ghana was considered. A combination of machine learning and Markov chain approach was adopted to project future LULC for 2040 and 2060.The results showed that area covered by Open Forest declined from 21,531.87 km2 to 14,518.82 km2 and Dense Forest also declined from 14,313 km2 to 8202.98 km2 over a period of 34 years. The CA-Markov model was used to predict the future land use land cover, and it was observed that the total forest cover could decline to 15,551.79 km2 in 2040 and further decrease to 13,401.79 km2 in 2060. It was also found that settlement, mining and agricultural land, which is be driven by rapid population increase, has contributed significantly to the rapid declining forest cover. The results of this study have demonstrated the impact of unsustainable use of natural resources in these three regions. It also highlights the need for concerted effort to develop comprehensive environmental policies to encapsulate sustainable conversion and utilisation of natural resources by focusing on water-energy-food nexus.

Population growth coupled with economic, housing and environmental factors have significantly contributed into accelerated land use change in the New Juaben Municipality of Ghana. These factors have caused destruction of natural habitat and increased natural hazards such as flooding in the Municipality. Monitoring land use/land cover change is essential in respect to the dynamics of both human and natural factors that affect the biophysical and biochemical properties of the land surface. This research investigates the transitions among the major land use/land cover categories in the Municipality as a highly populated urban region that is facing some environmental challenges such as deforestation and degradation of the environment. Random Forest was adopted for the classification of 1985, 1991, 2002 and 2015 land cover maps while the analysis of the dynamics was conducted using intensity analysis. The unique contribution of this article is the combine usage of machine learning algorithm and intensity analysis to assess the changes in land use/land cover. The results showed that 1985–1991 and 2002–2015 periods experience fast change and the land use transformation has been accelerating over the whole period. The major changes were caused by the Built-up and Agricultural activities constituting 21.24 % and 13.19 % respectively in the category level. It is recommended that, authorities should consider several structural transformation measures within Ghana, including inter-sectoral land use harmonization policies (e.g. the Land Use and Spatial Planning Act 2016), land use planning and legal reforms to help address the underlying drivers of urban led deforestation.

This study contributes to the explanation to growing informality by proposing and testing a simple framework that link income insecurity to the proliferation of informal enterprise through job insecurity in selected SSA countries. The study adopted a quantitative approach and used ANOVA analysis to analyze a uniform firm level data on informal enterprises in Ghana, Kenya and the DRC. The analyses suggested that income insecurity exist in the form of significant seasonal variations in sales returns. Enterprises that employ more than one worker, on the average, cut employment significantly during the slowest months as compared to employment in the busiest months. Thus a link is established between income insecurity and job insecurity which deters the informal enterprises from increasing permanent employment and hence remains small overtime. Instead firms resort to casual workers and unpaid workers to facilitate production. The insecurity in the informal sector paid employment drive paid employees into self-employment after learning the employer’s trade and hence multiply the number of enterprises in a locality which in turn keep returns fairly normal in the sector. The major recommendation of that study is that owners of informal enterprises must be regulated in their current jobs and assisted to build capacity to deal with sales variations and other employment uncertainty after which the demand for formality and growth in decent employment shall be a natural course of action to the firms.

In contrast to previous studies on the relationship between trade openness and FDI inflows, this study develops a new measure of trade openness. Principal component analysis was employed to generate an index to capture trade policy openness. The study used cost of exporting and importing as well as the number of days and the number of documentation it takes to complete a trade transaction (both import and export) in the doing business indicators dataset to create an index for trade policy openness. This provides a better measure of trade openness compared with the traditional measure of trade openness which takes into the volume of trade. The traditional measure of trade openness may be affected by more than ordinary trade policy of an economy. Other factors such as access to foreign markets, the size of the internal market and the size of the an ecnomy can probably affect the trade to GDP ratio. However trade policy openness is free of these problems. The study employed both static and dynamic panel estimation technique to analyse the relationship between trade policy openness and FDI inflow for 29 sub Saharan African countries. The result from the study indicates that, policy openness affect FDI inflows positively. The study recommends that, more efforts should be targeted at reducing cost of trade and also increases the ease of cross boarder trading activities. This would ensure the flow of required level of FDI to the region for economic transformation.