Untreated produced water contains numerous substances that can cause harm to the environment such as dispersed and dissolved oil, heavy metals, and production chemicals. Dispersed oil content in produced water may vary with different oil wells. Dispersed oil in water is classified as toxicants to human beings and marine life. The focus of doing this research is to study the oil adsorption characteristics of dried Khaya Senegalensis leaves in produced water and to investigate the effect of temperature on oil adsorption efficiency of the dried leaves. Khaya Senegalensis dried leaves were chosen for the research because they are considered as natural waste that exist in abundance in the environment. The results from SEM analysis showed that adsorbed oil patches appeared on the surface of the leaves. This is due to the leaves' rich phytochemical constituents which is lipophilic in nature. However, an increase in temperature of the solution will result in the decrease in the number of adsorbed oil patches on the surface of the leaves. This is due to the leaching of these phytochemical constituents into the surrounding solution which reduces oil adsorption efficiency of the dried leaves.
The population of many countries might undergo dramatic changes in the coming decades due to continuous increases in life expectancy. The sustained reduction in mortality rates and its systematic underestimation has been attracting the significant interest of researchers in recent years because of its potential impact on population size and structure, social security systems, and (from an actuarial perspective) the life insurance and pensions industry worldwide. Among all projection methods, the Lee-Carter method has been widely accepted by the actuarial community. This paper explores the use of the Lee-Carter method to forecast the mortality rates for Malaysian population. The index of the level of mortality for each gender, and the shape and sensitivity coefficients for 18 age groups were obtained through the Lee-Carter method. The Singular Values Decomposition (SVD) is used to forecast the general index for the time period that goes from 2011 to 2030. Since the model involves nonlinear equations that are explicitly difficult to solve, the Matrix Laboratory Version 7.0 (MATLAB 7.0) software will be used in the study. The empirical data sets of Malaysia population for the period of 1981-2010 and for both genders will be considered.
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