Saccharomyces Cerevisiae cells were immobilized in calcium alginate beads and activated charcoal for use in the
production of ethanol from batch fermentation of sugar beet waste. Treatment of the waste with NaOH to increase the
ability of lignocellulose material to hydrolysis by acid (2N H2SO4) to monosaccharide and disaccharide (mainly glucos).
The high reducing sugar concentration obtained was equal to 9.2gm/100ml (10Brix) after treatment. Fermentation
parameters, are (pH, glucose concentration (2.5-25 gm/100ml), immobilized agent concentration (2.5-25 gm/100ml)
were studied to find the optimum physiological condition. And the highest ethanol concentration obtained from the
fermentation in the presence of 20%(wt/v) calcium alginate was (9.322%(wt/v)) at 13.75%(wt/v) glucose concentration
and pH 5 .The experimental results were correlated by empirical second order polynomial equation with correlation
coefficient 96.734% and variance 93.574%
Purpose: To contribute to the development of an appropriate program for the management of medical waste based on clear-cut principles in order to reach the overall goal of improving the public health and environment of the population in our country.
Design / Approach / Introduction: The research is based on the analytical descriptive approach as a method of study in the field of data collection using a check list and analysis of the data through the use of some statistical treatments.
Results: The need is to establish a medical waste management in hospitals and follow international standards in all stages of waste management from sorting, collection, transportation and treat
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... Show MoreThe efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in
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