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                <text>Investigations were conducted to dete rmine changes in souring/acidification and starch behaviour during co-fermentation of cassava and soybean into gari, ‘farina’ an African fermented product. A 3 x 4 factorial experiment was performed with fermentation time (0, 24 and 48 h) and soybean conce ntration (0, 10, 20 and 30%) as variables. Titratable acidity, pH and starch content were studied using standard analytical methods. Starch breakdown and pasting characteristics were also evaluated . The results revealed that pH decreased with concomitant increases in titratable acidity during co -fermentation of the cassava dough. Soy - fortification up to 30% caused significant (p&lt;0.05) effects on the pH, titratable acidity and starch content during the fermentation period with only minimal and insignificant (p&lt;0.05) effect noted at 20% soy level. Fermentation caused significant differences (p&lt;0.05) in the pH, titratable acidity and starch concentration. Starch content decreased from 69.8% to 60.4% within the 48 h fermentation time in the unfortified sample with similar trends noted at all levels of fortification. Starch pasting characteristics showed that the pasting temperature significantly increased with increasing fermentation time and soybean concentration. Contrary to this, viscosity at 95°C and at 50°C HOLD decreased with increasing fermentation time and soybean concentration. Peak viscosity decreased from 1150 BU to 820 BU and 750 BU after 48 hours of fermentation, with 0% and 30% soybean levels respectively. Cassava could be cofermented with soybean up to 20% concentration during gari processing, without significant effect on its process and …</text>
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                <text>https://scholar.google.com/citations?view_op=view_citation&amp;amp;hl=en&amp;amp;user=EZuX1N8AAAAJ&amp;amp;cstart=100&amp;amp;pagesize=100&amp;amp;citation_for_view=EZuX1N8AAAAJ:SdhP9T11ey4C</text>
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                <text>Space-time analysis and mapping of prevalence rate of tuberculosis in Ghana</text>
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                <text>Iddrisu Wahab Abdul, Sylvia Ankamah, Abdul-Karim Iddrisu, Evans Danso</text>
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                <text>Background&#13;
Global fight against tuberculosis (TB) has received increasing attention over the years. However, the disease remains one of the top-most global health problems, especially in Sub-Saharan Africa and Ghana.&#13;
Aims&#13;
This paper examined geographical (regional) and seasonal distribution of TB cases providing relative risk of TB exposure in Ghana and step by step procedure to perform the analysis.&#13;
Methods and material&#13;
We modelled reported TB cases between 2015 and 2018 using wavelet analysis and applied maximum covariance analysis (MCA) to determine regional and seasonal patterns and the risk of TB exposure in Ghana. This study is based on the old administrative regions of Ghana.</text>
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                <text>Elsevier</text>
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                  <text>Faculty of Computing and Information Systems</text>
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                <text>Spatial analysis of the prevalence of obesity and overweight among women in Ghana</text>
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              <elementText elementTextId="11853">
                <text>Killian Asampana Asosega, Atinuke Olusola Adebanji, Iddrisu Wahab Abdul</text>
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                <text>Objective&#13;
Identifying hot spots for the overweight aids in effective public health interventions due to the associated public health burden and morbidities. This study, therefore aimed to explore and determine the spatial disparities in the overweight/obesity prevalence among women in Ghana. The study also aims at modelling the average body mass index (BMI) values using the spatial regression and the performance compared with the standard regression model.</text>
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              <elementText elementTextId="11855">
                <text>British Medical Journal Publishing Group</text>
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            <name>Date</name>
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                <text>2021</text>
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                  <text>Faculty of Computing and Information Systems</text>
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                <text>Spatial bayesian methods of flow forecasting in the Black Volta river</text>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
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              <elementText elementTextId="12042">
                <text>Iddrisu Wahab Abdul, Kaku Sagary Nokoe, Frank Badu Osei, Eric Ofosu Antwi</text>
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            <description>An account of the resource</description>
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                <text>The use of Spatial Bayesian Vector Autoregressive (SBVAR) models for river flow forecasting is studied in this paper. SBVAR models based on both the First Order Spatial Contiguity (FOSC) and the Random-Walk Averaging (RWA) priors were estimated and compared in terms of forecast performance. Monthly data on river flows from January 2000 to December 2009 for the four gauge stations along the Black Volta River namely, Lawra, Chache, Bui and Bamboi was obtained from the hydrological services department of Ghana and used for model fitting. The estimation and forecasting procedure was conducted using the Econometrics Toolbox in MATLAB. Mean Absolute Percentage Errors (MAPEs) were calculated for all models considered. The results indicated very good forecasts for all the models considered. However, a comparison among them clearly indicated a much better performance by the SBVAR model based on the RWA prior which considered flows from only the immediate upstream gauge station as important while flows from all other gauge stations were considered unimportant.</text>
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                <text>European journal of scientific research</text>
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                <text>2016</text>
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