Lipase was extracted by Sodium acetate buffer (pH=6; 0.05M) Containing 0.1M NaCl. Enzyme content of crude extract was concentrated by gradual addition of ammonium sulfate at 30-60% saturation. The dialyzed extract was purified on ion-exchange chromatography through DEAE–Cellulose and gel-filtration chromatography through sephacryl S-200 column. The specific activity, enzyme yield and fold purification were 54.06 unit/mg, 42.6% and 10.88 respectively. The molecular weight of the Lipase was 43.651 KDa as determined by gel-filtration chromatography through sephacryl S-200 column. Partial purified lipase used for the improvement of the flavor of butter fat after 12 hours for storage.

In this paper, the maximum likelihood estimates for parameter ( ) of two parameter's Weibull are studied, as well as white estimators and (Bain & Antle) estimators, also Bayes estimator for scale parameter ( ), the simulation procedures are used to find the estimators and comparing between them using MSE. Also the application is done on the data for 20 patients suffering from a headache disease.

The art of theater penetrated various scientific and human fields, as well as touching the facts and events surrounding it, and scientific innovations had a wide field, so it adopted feedback in interactive theater performances, especially the theater of the oppressed. Then came the indicators that resulted from the theoretical framework for the formation of the tool by which the research sample is analyzed, and then the chapter concluded with previous studies. As for the third chapter, it involved the research procedures, and through the research tool and the research method, and by selecting the intentional sample, the sample represented by a play (the story of Shahrour) was analyzed. As for the fourth chapter, it included the results

In this work we reported the synchronization delay in
semiconductor laser (SL) networks. The unidirectional
configurations between successive oscillators and the correlation
between them are achieved. The coupling strength is a control
parameter so when we increase coupling strength the dynamic of the
system has been change. In addition the time required to synchronize
network components (delay of synchronization) has been studied as
well. The synchronization delay has been increased by mean of
increasing the number of oscillators. Finally, explanation of the time
required to synchronize oscillators in the network at different
coupling strengths.

This paper addresses the use of adaptive sliding mode control for the servo actuator system with friction. The adaptive sliding mode control has several advantages over traditional sliding mode control method. Firstly, the magnitude of control effort is reduced to the minimal admissible level defined by the conditions for the sliding mode to exist. Secondly, the upper bounds of uncertainties are not required to be known in advance. Therefore, adaptive sliding mode control method can be effectively implemented. The numerical simulation via MATLAB 2014a for servo actuator system with friction is investigated to confirm the effectiveness of the proposed robust adaptive sliding mode control scheme. The results clarify, after

In this paper, a robust adaptive sliding mode controller is designed for a mobile platform trajectory tracking.  The mobile platform is an example of a nonholonomic mechanical system. The presence of holonomic constraints reduces the number of degree of freedom that represents the system model, while the nonholonomic constraints reduce the differentiable degree of freedom. The mathematical model was derived here for the mobile platform, considering the existence of one holonomic and two nonholonomic constraints imposed on system dynamics. The partial feedback linearization method was used to get the input-output relation, where the output is the error functions between the position of a certain point on the platform

L1 adaptive controller has proven to provide fast adaptation with guaranteed transients in a large variety of systems. It is commonly used for controlling systems with uncertain time-varying unknown parameters. The effectiveness of  L1 adaptive controller for position control of single axis has been examined and compared with Model Reference Adaptive Controller (MRAC). The Linear servo motor is one of the main constituting elements of the x-y table which is mostly used in automation application. It is characterized by time-varying friction and disturbance.

    The tracking and steady state performances of both controllers have been assessed fo

In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl