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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.

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.

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.

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.

xii, 158p, ills., Watermelon fruits and soil samples (depth of 0 – 20 cm) were analysed for pesticide residues. Residues were extracted from 10.0 g of watermelon fruit using a multi-residue method for extracting pesticides from non fatty foods with acetone as the extracting solvent. Soil and okro from a nearby okro farm which were used as control to study the effect of pesticides on non-target crops were also analysed. Extract cleanup was done using a 10 mm chromatographic column with a 1:1 solvent mixture of Cyclohexane and Dichloromethane as the eluting solvent. Organophosphate pesticides (OPPs), organochlorine pesticides (OCPs) and synthetic pyrethroid pesticides were detected in all the samples. The OPPs levels ranged from 0.90 - 4383.20 μg/kg. OCPs residues occurred in the fruits at levels between 0.70 - 34.50 μg/kg. Synthetic pyrethroid pesticides fell in the range 0.10 - 6.40μg/kg. Non-target crop had residue levels ranging from 2.80 - 2016.80 μg/kg for OPPs, 1.20 - 15.83 μg/kg for OCPs and 3.10 - 7.60 μg/kg for synthetic pyrethroid pesticides. Soil residue levels were in the range 2.0 - 4121.70 μg/kg for OPPs, 1.10 - 12.90 μg/kg for OCPs and 1.10 - 8.20 μg/kg for synthetic pyrethroid pesticides. OPPs levels were appreciably high in all the samples followed by organochlorines and the synthetic pyrethroids. In general, organophosphate pesticides (OPPs) and the organochlorine pesticides (OCPs) levels were significantly higher than the WHO/FAO allowable levels. These show that watermelon fruits were contaminated to significant levels with organochlorine and organophosphate pesticides.