Vitamin A, namely retinol is still the most proper agent for modulating so many biochemical reactions and biological functions in different tissues and organs. In addition to the provitamins A and α, βand γ-carotenoids that are present in various foods from either animal or plant origin, retinoids and rexinoids form the natural and synthetic analogs that are chemically related or unrelated and can be added as food supplements for deficiency disorders of vitamin A or used to alleviate or treat certain health problems such as skin carcinoma, acne, skin aging and dermatitis.

Due to increased consumption of resources, especially energy it was necessary to find alternatives characterized by the same quality as well as being of less expensive, and most important of these alternatives are characterized by waste and the fact that humancannot stop consumption. So we  have consideredwaste as an  alternative and cheap economic resources and by using environmental index the MIP (input materials per unit ,unit / service) is based on the grounds that the product is not the end of itselfit is a product to meet the need  of a product or service, awarded a resource input and output within the five basic elements are the raw materials is ecological, Raw materials ecological, water, air and soil erosion for a

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

Because of its importance in the world, Middle East area is one of the competition areas between the major and great powers. Among those powers are Russia and United states of America. The competition between these two powers to control Syria is greatly clear since 2011. It is also one of the most important subject in the international politics. This importance comes from the importance of Russia and the United States of America besides importance of the Middle East. At the end of the cold war, United States of America maintained its role in the international system and became the only pole that dominated the international affairs while Russia tried to overcome the challenges inherited from the former Soviet Union, and it succeeded in th

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

Ball and Plate (B&P) system is a benchmark system in the control engineering field that has been used to verify many control methods. In this paper the design of a sliding mode . controller has been investigated and verified in real-time via implementation on a real ball and plate system hardware. The mathematical model has been derived and the necessary parameters have been measured. The sliding mode controller has been designed based on the obtained mathematical model. The resulting controller has been implemented using the Arduino Mega 2560 and a ball and plate system built completely from scratch. The Arduino has been programmed by the Arduino support target for Simulink. Three test signals has been used for verification purposes

A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton

This paper presents L₁-adaptive controller for controlling uncertain parameters and time-varying unknown parameters to control the position of a DC servomotor. For the purpose of comparison, the effectiveness of L₁-adaptive controller for position control of studied servomotor has been examined and compared with another adaptive controller; Model Reference Adaptive Controller (MRAC). Robustness of both L₁-adaptive controller and model reference adaptive controller to different input reference signals and different structures of uncertainty were studied. Three different types of input signals are taken into account; ramp, step and sinusoidal. The L₁-adaptive controller ensured uniformly bounded

The blade pitch angle (BPA) controller is key factor to improve the power generation of wind turbine (WT). Due to the aerodynamic structural behavior of the rotor blades, wind turbine system performance is influenced by pitch angle and environmental conditions such as wind speed, which fluctuate throughout the day. Therefore, to overcome the pitch angle control (PAC) problem, high wind speed conditions, and due to type-1 and type-2 fuzzy logic limitations for handling high levels of uncertainty, the newly proposed optimal hybrid type-3 fuzzy logic controller has been applied and compared since type-3 fuzzy controllers utilize three-dimensional membership functions, unlike type-2 and type-1 fuzzy logic controllers. In this paper six differen

Econazole nitrate (EN) is considered as the most effective agent for the treatment of all forms of dermatomycosis caused by dernatophytes. It was formulated as a topical solution in our laboratories. This study was designed to evaluate the effectiveness of Econazol Nitrate in the prepared formula and compared with that of commercial brand, Pevaryl®. A total of 104 patient suffering from dermatomycoses were involved in this investigation. Both formula were applied to the affected skin region in the morning and evening from week to 16 weeks with light massage until complete healing effect was achieved. The data revealed that the percentage of cured patient treated with the prepared formula and reference formula of Ecanozol Nitrate 1% so