The role of macrophytes in the economy of the lower Sondu-Miriu river of Lake Victoria

This paper highlights the results of a 12 month's ecological study of macrophytes and their role in the economy of the lower Sondu-Miriu river of Lake Victoria. A total of 34 species of aquatic macrophytes were identified. These were grouped as emergent, floating leaved, free floating and submersed. The major community type identified were dominated by Cladium jamaicanse (Crantz) Kurk., Cyperus paprus (L.) and Cyperus latifolius (Poir). The study observed an over dependence on macrophytes by the local community for the supply of bedding, grazing fields, fuel, roofing and other building materials. The white (heart) of Typha shoot, Nile cabbage (Pistia stratiotes and a legume solanum nigrum traditionally known as "osuga" are used as vegetables by local community. The only source of protein in this arid region is the fish caught in the swamps and birds which inhabit the swamp. The swamp provides the only source of green pasture in the dry season for the animals. An export oriented economy has developed involving mat making and basket weaving with exports reaching as far as Japan. The study proposes a rational and sustainable exploitation of the littoral zone to support the adjacent rural community

Siblings, asthma, rhinoconjunctivitis and eczema: a worldwide perspective from the International Study of Asthma and Allergies in Childhood.

BACKGROUND: Associations of larger families with lower prevalences of hay fever, eczema and objective markers of allergic sensitization have been found fairly consistently in affluent countries, but little is known about these relationships in less affluent countries. METHODS: Questionnaire data for 210,200 children aged 6-7 years from 31 countries, and 337,226 children aged 13-14 years from 52 countries, were collected by Phase Three of the International Study of Asthma and Allergies in Childhood (ISAAC). Associations of disease symptoms and labels of asthma, rhinoconjunctivitis and eczema were analysed by numbers of total, older and younger siblings, using mixed (multi-level) logistic regression models to adjust for individual covariates and at the centre level for region, language and national affluence. RESULTS: In both age groups, inverse trends (P < 0.0001) were observed for reported 'hay fever ever' and 'eczema ever' with increasing numbers of total siblings, and more specifically older siblings. These inverse associations were significantly (P < 0.005) stronger in more affluent countries. In contrast, symptoms of severe asthma and severe eczema were positively associated (P < 0.0001) with total sibship size in both age groups. These associations with disease severity were largely independent of position within the sibship and national GNI per capita. CONCLUSIONS: These global findings on sibship size and childhood asthma, rhinoconjunctivitis and eczema suggest at least two distinct trends. Inverse associations with older siblings (observations which prompted the 'hygiene hypothesis' for allergic disease) are mainly a phenomenon of more affluent countries, whereas greater severity of symptoms in larger families is globally more widespread

Antifungal activity of crude extracts of Gladiolus dalenii van Geel (Iridaceae)

Bulb extracts of Gladiolus dalenii reportedly used in the treatment of fungal infections in HIV/AIDS patients in the Lake Victoria region were tested for antifungal activity using the disc diffusion assay technique. Commercially used antifungal drugs, Ketaconazole and Griseofulvin (Cosmos Pharmaceuticals) were used as standards. Dichloromethane (CH2CL2)/Methanol (MeOH) in the ratio 1:1. Soluble extracts showed antifungal activity against Aspergillus niger. Direct bioautography on silica gel Thin Layer Chromatography (TLC) and appropriate spraying agents were used to identify the active component in the extract. The activities of both the extracts were higher than that of Griseofulvin. CH2CL2 soluble extract in addition showed ability to delay sporulation in A.niger. The active group of compounds in the extracts was identified as alkaloids, which offer immense potential for development of new and valuable pharmaceutical products.Key words: G. dalenii, Aspergillus niger, Antifungal activit

Spatial and temporal dynamics of malaria transmission in rural western Kenya

ABSTRACT: BACKGROUND: Understanding the impact of reducing Plasmodium falciparum malaria transmission requires estimates of the relationship between health outcomes and exposure to infectious mosquitoes. However, measures of exposure such as mosquito density and entomological inoculation rate (EIR) are generally aggregated over large areas and time periods, biasing the outcome-exposure relationship. There are few studies examining the extent and drivers of local variation in malaria exposure in endemic areas. METHODS: We describe the spatio-temporal dynamics of malaria transmission intensity measured by mosquito density and EIR in the KEMRI/CDC health and demographic surveillance system using entomological data collected during 2002-2004. Geostatistical zero inflated binomial and negative binomial models were applied to obtain location specific (house) estimates of sporozoite rates and mosquito densities respectively. Model-based predictions were multiplied to estimate the spatial pattern of annual entomological inoculation rate, a measure of the number of infective bites a person receive per unit of time. The models included environmental and climatic predictors extracted from satellite data, harmonic seasonal trends and parameters describing space-time correlation. RESULTS: Anopheles gambiae s.l was the main vector species accounting for 86% (n=2309) of the total collected mosquitoes with the remainder being Anopheles funestus. Sixty eight percent (757/1110) of the surveyed houses had no mosquitoes. Distance to water bodies, vegetation and day temperature were significantly associated with mosquito density. Overall annual point estimates of EIR were 6.7, 9.3 and 9.6 infectious bites per annum for 2002, 2003 and 2004 respectively. Monthly mosquito density and EIR varied over the study period peaking in May during the wet season. The predicted and observed densities and EIR showed a strong seasonal and spatial pattern over the study area. CONCLUSIONS: Spatio-temporal maps of malaria transmission intensity obtained in this study are not only useful in understanding variability in malaria epidemiology over small areas but also provides a high resolution exposure surface that can be used to analyse the impact of malaria exposure on mortalit

Intra-myocardial Bullet causing heart block in a patient with multiple gunshot wounds: Case Report

Elective removal of intra-myocardial bullet remains a controversial subject. A non-operative approach has been recommended as appropriate for a stable asymptomatic patient. In the presence of complications such as bleeding, perforation leading to cardiac tamponade, thrombus formation, embolization, rhythm disturbances and infections, surgical removal may be advised. We present a patient who survived multiple gunshot wounds with a bullet lodged in the wall of the left ventricle of the heart. Details of the injuries sustained, operative removal of the bullet and the challenges that ensued are illustrated

Directly observed road safety compliance by Motor Cycle Riders after a 5- Year Road Safety Campaign in Naivasha, Kenya

Objective: To assess the extent of compliance with road safety regulations by  motorcycle riders following a five year road safety campaign in Naivasha town, Kenya.Design: A cross sectional study.Setting: Naivasha town, Nakuru county, Kenya.Results: A total of 9,280 MCs ferrying 13,733 people were observed. Less than 1% complied with all the four road safety  requirements. The overall helmet wearing compliance was 31%. MC driver helmet compliance was 42% which was five timeshigher than passenger helmet compliance. Female passengers were twice less likely to wear helmet than males.Conclusion: Despite the five-year road safety campaign, compliance among MC users remains low particularly among the passengers and more so female passengers. Does Kenya need to rethink the motor cycle road safety policy

Application of Fuzzy-Neural Network in Classification of Soils using Ground-penetrating Radar Imagery

Errors associated with visual inspection and interpretation of radargrams often inhibits the intensive surveying of widespread areas using ground-penetrating radar (GPR). To automate the interpretive process, this paper presents an application of a fuzzy-neural network (F-NN) classifier for unsupervised clustering and classification of soil profile using GPR imagery. The classifier clusters and classifies soil profiles strips along a traverse based on common pattern similarities that can relate to physical features of the soil (e.g., number of horizons; depth, texture and structure of the horizons; and relative arrangement of the horizons, etc). This paper illustrates this classification procedure by its application on GPR data, both simulated and actual real-world. Results show that the procedure is able to classify the profile into zones that corresponded with those obtained by visual inspection and interpretation of radargrams. Results indicate that an F-NN model can supply real-time soil profile clustering and classification during field surveys

Optimization Of Fuzzy Evapotranspiration Model Through Neural Training With Input–Output Examples

In a previous study, we demonstrated that fuzzy evapotranspiration (ET) models can achieve accurate estimation of daily ET comparable to the FAO Penman–Monteith equation, and showed the advantages of the fuzzy approach over other methods. The estimation accuracy of the fuzzy models, however, depended on the shape of the membership functions and the control rules built by trial–and–error methods. This paper shows how the trial and error drawback is eliminated with the application of a fuzzy–neural system, which combines the advantages of fuzzy logic (FL) and artificial neural networks (ANN). The strategy consisted of fusing the FL and ANN on a conceptual and structural basis. The neural component provided supervised learning capabilities for optimizing the membership functions and extracting fuzzy rules from a set of input–output examples selected to cover the data hyperspace of the sites evaluated. The model input parameters were solar irradiance, relative humidity, wind speed, and air temperature difference. The optimized model was applied to estimate reference ET using independent climatic data from the sites, and the estimates were compared with direct ET measurements from grass–covered lysimeters and estimations with the FAO Penman–Monteith equation. The model–estimated ET vs. lysimeter–measured ET gave a coefficient of determination (r2) value of 0.88 and a standard error of the estimate (Syx) of 0.48 mm d–1. For the same set of independent data, the FAO Penman–Monteith–estimated ET vs. lysimeter–measured ET gave an r2 value of 0.85 and an Syx value of 0.56 mm d–1. These results show that the optimized fuzzy–neural–model is reasonably accurate, and is comparable to the FAO Penman–Monteith equation. This approach can provide an easy and efficient means of tuning fuzzy ET models

Application of Fuzzy-Neural Network in Classification of Soils using Ground-penetrating Radar Imagery

Errors associated with visual inspection and interpretation of radargrams often inhibits the intensive surveying of widespread areas using ground-penetrating radar (GPR). To automate the interpretive process, this paper presents an application of a fuzzy-neural network (F-NN) classifier for unsupervised clustering and classification of soil profile using GPR imagery. The classifier clusters and classifies soil profiles strips along a traverse based on common pattern similarities that can relate to physical features of the soil (e.g., number of horizons; depth, texture and structure of the horizons; and relative arrangement of the horizons, etc). This paper illustrates this classification procedure by its application on GPR data, both simulated and actual real-world. Results show that the procedure is able to classify the profile into zones that corresponded with those obtained by visual inspection and interpretation of radargrams. Results indicate that an F-NN model can supply real-time soil profile clustering and classification during field surveys