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                <text>Imoro Abubakari Zarouk, Iddrisu Wahab Abdul, Abubakari Issah</text>
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                <text>At five levels of Bile (No bile, 1.2 ml, 1.4 ml, 1.6 ml and 1.8 ml) and two nutrient levels (Nutrient medium and No Nutrients) the effect of Bile and Nutrients on microbes and the evolution of temperature, electrical conductivity, surface tension and pH were studied and modeled during the bioremediation of a petroleum hydrocarbon contaminated water. Analysis of variance (ANOVA) for α= 0.05 was used to show the variations in parameter values according to the levels of Bile and Nutrients. Microbial colony numbers and pH generally did not show a uniform evolution trend as the level of Bile increased but showed an increasing trend with increment in Nutrients level. Temperature increased with increasing Bile and Nutrients levels only when either Bile or Nutrients Medium was the lone supplement in the experiment. Electrical conductivity increased with increasing levels of Bile whiles surface tension decreased with increasing levels of Bile and</text>
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                <text>Modelling the effects of feed moisture and ingredient variations on the physical properties and functional characteristics of extruded sorghum-groundnut-cowpea blends using …</text>
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                <text>Central composite rotatable design for k = 3 was used to study the combined effect of feed moisture (12-44%), cowpea concentration (0-20%) and groundnut concentration (0-10%) on the physical and functional properties of extruded sorghum-legume blends in a single screw extruder using response surface methodology. Product expansion ratio, bulk density, total colour change, water absorption capacities at 27°C and 90°C and swelling capacities were determined on the products using standard analytical methods. Expansion ratio, bulk density and total colour of extrudates from the sorghum-legume blends decreased with increasing feed moisture. Increasing the concentration of legumes in the product increased the water absorption capacities at 27°C and 70°C and increased swelling capacities due to the gel forming ability of the macromolecules (proteins and starch) in the products and availability of …</text>
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                <text>De Gruyter</text>
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                <text>Modelling the Impact and Effects of Climatic Variability on Electricity Energy Consumption in the Yendi Municipality of Ghana</text>
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                <text>Wahab A Iddrisu, Sampson T Appiah, Khalid Abdul-Mumin, Abdul-Rahman Abdul-Samed</text>
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                <text>One of the cherished assets of every economy is electricity since it has proven to be the major source of energy for industrialization. Developing economies like Ghana have suffered the downside of poor management of the already inadequate electrical energy at its disposal. This is as a result of limited research into factors that influences electricity energy consumption, most importantly, the effects of climatic variables on electricity energy consumption. This research work explores the causal connection between climatic variables and electricity energy consumption, and develops a Vector Auto Regression (VAR) model to determine the influence of the climatic variables in forecasting electricity energy consumption in Yendi Municipality in the northern region of Ghana. The climatic factors considered in this work are; Rainfall (Rain), maximum temperature (Tmax), Sunshine (Sun), Wind (wind) and Relative Humidity (RH). The Granger causality tests employed in this work revealed that aside from Relative Humidity, the end energy consumption is affected by the other four climatic factors under consideration. The impulse response was used to ascertain the active interaction among electricity energy consumption and the climatic variables. The impulse response of electricity energy consumption to the climatic variables indicates a maximum positive effect of Temperature and Sunshine on electricity energy consumption in March and September respectively. The VAR model was also used in forecasting future consumption of electricity energy. The results indicate excellent forecasts of electricity</text>
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                <text>Modelling the Trend of Flows with Respect to Rainfall Variability Using Vector Autoregression</text>
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                <text>Iddrisu Wahab Abdul, Nokoe Kaku Sagary, Akoto Isaac</text>
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                <text>Malaria is considered endemic in over hundred countries across the globe. Many cases of malaria and deaths due to malaria occur in Sub‐Saharan Africa. The disease is of great public health concern since it affects people of all age groups more especially pregnant women and children because of their vulnerability. This study sought to use vector autoregression (VAR) models to model the impact of climatic variability on malaria. Monthly climatic data (rainfall, maximum temperature, and relative humidity) from 2010 to 2015 were obtained from the Ghana Meteorological Agency while data on malaria for the same period were obtained from the Ghana Health Service. Results of the Granger and instantaneous causality tests led to a conclusion that malaria is influenced by all three climatic variables. The impulse response analyses indicated that the highest positive effect of maximum temperature, relative humidity …</text>
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                <text>&#13;
Hindawi</text>
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