Archives-January 2016

A carbon based (Graphene) working electrode containing enzyme alkaline phosphatase, cellulose acetate and Poly Vinyl Pyrolidone (PVP), Ferrocene, Horseradish peroxidise and aq. KOH was specially designed and fabricated. It is then combined with Ag/AgCl reference and a platinum electrode to form a three electrode based amperometric biosensor for the electrochemical detection of Enterobacter aerogenes as biological warfare agent (BWA) in the presence and absence of Fe3O4 nanoparticles. Fe3O4 nanoparticles were synthesized by sol-gel technique and were characterized by UV-visible, FTIR, TEM and XRD techniques. Change in current response and OCP values helps in the detection of BWA in presence and absence of Fe3O4 nanoparticles. Effects of temperature, stirring and Fe3O4 nanoparticles on the BWA have also been investigated.

Assessment of climate variability at local level, where the driver of the economy is agriculture, has enormous advantage in Ethiopia, . This study was then initiated to analyze the variability of rainfall features and their likely implications on long season growing crop; sorghum in Alamata Wereda. Daily climate data was obtained from the National Meteorological Agency of Ethiopia (NMA) and the historical temporal variability of the rainfall features was assessed using Instat and Mann-Kendall statistical softwares. Apart from the interannual variability (26.2%), the annual rainfall has also revealed a decreasing trend. Similarly, the Belg (FMAM) rainfall demonstrated a significant decreasing trend with a very high seasonal variability (53.1%). The Markov chain first order model indicates that the probability of 15 and 20 days consecutive dry spell occurrence on May (90%) and June (75%) were very high signaling that sowing on these months could possibly lead to complete or partial failure of seedling establishments. Even though the correlations between yield and monthly rainfalls was positive, only April (r=0.48) and September (r=0.55) rainfall was statistically significant. This indicates that for sorghum production, rainfall during April (for seedling establishment) and September (grain filling) appears to be particularly important (sensitive). Hence, as there is early cessation and high rainfall variability during the Belg season (part of sowing period for sorghum), different adaptation strategies such as soil moisture conservation and early maturing cultivars should be practiced to minimize the impact of rainfall variability on sorghum production.

Nanocrystallites of Cadmium oxide (CdO) thin films with different gelation time were deposited by sol-gel spin coating method on a glass substrate. A comparative analysis of the effect of viscosity of sol-gel on the structural, electrical, and optical properties of as deposited films was made. Films were grown with gelation time of one to four days and optimum gelation time of third day of sol-gel viscosity of 3.28 x 10-3 Nsm-2 was determined. From the X-ray diffraction studies the polycrystalline nature of the grown film with a preferential orientation (1 1 1) was analyzed. The resistivity of the material decreases with the increase of gelation time and then increases after the optimum value of gelation time. The films showed resistivity of 2.16 x 10-4 ? m with an optical transmission of 80 % at the wavelength of 625 nm. The observed band gap of the developed film was found to be 2.25 eV. Also optical studies confirm that the optical transmittance was decreased when the viscosity was increased.

Co-curricular activities are defined as those activities that improve and develop the student academic performance. In Malaysia co-curricular plays an important role which students are evaluated in both academic examination and co-curriculum participation. Therefore, this aims to identify the relationship between school co-curricular activities and student academic performance among secondary school students. 300 students will be used as a sample size of this study. The statistical analysis is expected to be positive for secondary school student’s involvement in co-curricular activities and academic performance. Hence, school management or parents could collaborate and put effort to increase student’s interest on co-curricular activities.

The purpose of this study was to identify concepts of terminology in science and technology field especially in renewable energy. There are almost no definitions of the term in Mongolian. According to data aggregated by the International Panel on Climate Change, life-cycle global warming emissions associated with renewable energy including manufacturing, installation, operation and maintenance, and dismantling and decommissioning are minimal. (IPCC, 2011, pp. 1075). Therefore, it is essential to develop renewable terminology to analyze its modern aspects. We need terminology standardization to express individual terms in single definitions and understandings of concepts throughout the world. But in most of our professional fields, there is no standard of term translated and interpreted. It is really important to have standards of education terms and determine the definitions in Mongolia. Formulating model of terminology standardization is the framework for this study. English data were collected from Canadian glossary of terminology and Mongolian data were collected from dictionaries. As for Mongolian terminology, almost 89% of 1300 were without any definition of concept and 99% were not standardized

Benzimidazoles and their derivatives play very important role in the medical field with useful therapeutic activities like antiviral, anti-histaminic, anticancer, antiulcer, antihypertensive, antidiabetic, antifungal, and antimicrobial activity. The most prominent benzimidazole compound in nature is N-riosyldimethylbenzimidazole, which serves as an axial ligand for cobalt in vitamin B12. The potency of these useful derivatives in treatment of microbial infections encouraged the development of some more potent and pharmacologically efficient compounds. This review summarizes the synthesis of different derivatives of benzimidazole and their biological activities.

The study of stochastic phenomena has increased dramatically and intensified research activity in this area has been stimulated by the need to take into account random effects in complicated dynamical systems. Dynamical systems are ubiquitous and are considered to be stochastic processes. In this study, a nonlinear dynamical system was modeled as a solution to an Ito stochastic differential equation . Where denotes a Wiener or Brownian motion process while and are deterministic functions. The Ito Stochastic Differential Equation was applied to characterize the important functional of the solution process in some intervals [0,t],X(t) which satisfies the integral equation, X(t)=X(0)+?_0^t??f(s,X(s))ds?+?_0^t??g(s,X(s) )dW(s)?. The solution of the integral equation is a Lagenvin equation which is an Ornstein-Uhlenbeck (O-U) process dX_t=?(?-X_t )dt+?dW_t. The O-U process which is a Gaussian process was related to the world of time series analysis. The model was applied to Nigerian monetary exchange rate and compared with the existing models of monetary exchange rate. R package and the Akaike Information Criteria (AIC) were used to provide the model of best fit for the Nigerian monetary exchange rate as an autoregressive moving average of order one which is given to be? S?_t=0.4287S_(t-1)+?0.2099e?_(t-1)+e_t. The results obtained revealed that the structural diffusion model approach gives a first-order autoregressive moving average process in continuous time with differentiation in continuous time corresponding to differencing in discrete time. The derived structural diffusion model has the least AIC value of 1482.61 as compared to the AIC value of 2198.86 from the existing diffusion and normal models. Keywords: Nonlinear Model, Dynamical System, Diffusion Model,

Nigeria is classified as a mixed economy emerging market, and has already reached middle income status according to the World Bank, with its abundant supply of natural resource, well developed financial, legal, communications, transport sectors and stock exchange which is the second largest in Africa. The main purpose of this research is to build a model that can capture the best variables that predict the Gross Domestic Product (GDP) of Nigeria. Correlation matrix was used to know the degree of relationship that exists between the pairs of predictors of GDP. The principal component analysis was employed to reduce the multidimensional data. Scree plot was used to determine the spread of the trend of the components and bi plot was used to determine the degree of closeness of Agriculture, oil Export, External Reserves, Exchange Rate, Transportation, Education, and Communication. There is a strong relationship between pairs of Agriculture, oil Export, External Reserves, Exchange Rate, Transportation, Education, and Communication. The proportion of variance accounted for by the first component is 92%. This implied that only component 1 is sufficient to explain GDP. The Scree plot showed that the best component is component 1. The bi plot showed that Agriculture, oil Export, External.Reserves, Exchange.Rate, Transportation, Education, and Communication are closely related and stand as good predictors of GDP. Keyword: Gross Domestic Product, Principal Components, Bi plot, Scree plot

Abstract Thomas Robert Malthus Theory of population highlighted the potential dangers of over population. He stated that while the populations of the world would increase in geometric proportions, the food resources available for them would increase in arithmetic proportions. This study was carried out to find the trend, fit a model and forecast for the population growth rate of Nigeria.The data were based on the population growth rate of Nigeria from 1982 to 2012 obtained from World Bank Data (data.worldbank.org). Both time and autocorrelation plots were used to assess the Stationarity of the data. Dickey-Fuller test was used to test for the unit root. Ljung box test was used to check for the fit of the fitted model. Time plot showed that the random fluctuations of the data are not constant over time. There was an initial decrease in the trend of the growth rate from 1983 to 1985 and an increase in 1986 which was constant till 1989 and then slight fluctuations from 1990 to 2004 and a general increase in trend from 2005 to 2012. There was a slow decay in the correlogram of the ACF and this implied that the process is non stationary. The series was stationary after second differencing, Dickey-Fuller = -4.7162, Lag order = 0, p-value = 0.01 at ?= 0.05. The p-value (0.01) and concluded that there is no unit root i.e the series is stationary having d=2. Correlogram and partial correlogram for the second-order differenced data showed that the ACF at lag 1 and lag 5 exceed the significant bounds and the partial correlogram tailed off at lag 2.The identified order for the ARIMA(p,d,q) model was ARIMA(2,2,1). The estimate of AR1 co-efficient =1.5803 is observed to be statistically significant but the estimated value does not conforms strictly to the bounds of the stationary parameter hence was excluded from the model. =-0.9273 is observed to be statistically significant and conformed strictly to the bounds of the stationary parameter , hence was maintained in the model. The estimate of MA1 co-efficient = - 0.1337 was observed to be statistically significant conformed strictly to the bounds of the parameter invertibility. For ARIMA (2, 2, 0) the estimate of AR1 co-efficient =1.5430 was observed to be statistically significant and not conformed strictly to the bounds of the parameter stationary, hence excluded from the model. The estimate of AR 2 co-efficient =-0.9000 is observed to be statistically significant and conformed strictly to the bounds of the parameter stationary, hence retained in the model. The ARIMA (2, 2, 0) is considered the best model. It has the smallest AIC. The Ljung test showed that residuals are random and implies that the model is fit enough for the data. The forecast Arima function gives us a forecast of the Population Growth Rate in the next thirty eight (38) years, as well as 80% and 95% prediction intervals for those predictions i.e up to 2050. Keywords: Modelling, ARIMA Model, Parameter, Dickey-Fuller, Stationarity

This paper presents the non-linear control of an induction motor (IM). The objective of nonlinear control is to can control separately flux and the speed, several techniques of control are used for (IM), The technique of control oriented flux (FOC) which permits the decoupling between input and output variables, so (IM) is assimilate to continuous current motor , this method has a problem is how exactly oriented the axis d on the flux .However, feedback linearization amounts to cancelling the nonlinearities in a nonlinear system so that the closed- loop (CL) dynamics is in a linear form . A goal of feedback linearization is to can controlled separately flux and the speed ,the motor model is strongly nonlinear then it’s composed to the autonomous and mono-variables too under systems so every under system presented an independence loop of control for each variables is given . The space vector modulation [SVM] method gives a good tracking for the non linear control, SVM became a standard for the switching power converters and important research effort has been dedicated, tens of papers, research reports and patents were developed in the theory of space vector modulation.