Improved oral bioavailability of lipophilic substances can be achieved using self-emulsifying drug delivery systems. However, because the properties of self-emulsifying are greatly influenced by surfactant amount and type, type of oil used, droplet size, charge, cosolvents, and physiological variables, the synthesis of self-emulsifying is highly complex; consequently, only a small number of excipient self-emulsifying formulations has been developed so far for clinical use. This study reports a highly effective procedure for developing self-emulsifying formulations using a novel approach based on the hydrophilic-lipophilic difference theory. Microemulsion characteristics, such as the constituents and amounts of oil and surfactant electrolyte

The aim of this study is to design a proposed model for a document to insure the mistakes of the medical profession in estimating the compensation for medical errors. The medical profession is an honest profession aimed primarily at serving human and human beings. In this case, the doctor may be subject to error and error , And the research has adopted the descriptive approach and the research reached several conclusions, the most prominent of which is no one to bear the responsibility of medical error, although the responsibility shared and the doctor contributes to them, doctors do not deal with patients according to their educational level and cultural and there are some doctors do not inform patients The absence of a document to insu

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

The aim of this study is to highlight on the concept of joint arrangements and projects in accordance with IFRS 11, in addition, the study also focuses on accounting standards and IFRSs which are relevant to this standard.  With a description of the legislative and accounting challenges in the Iraqi environment facing the application of IFRS 11, as well as studying the reality of accounting in such economic activity of companies operating in this sector.

In order to achieve the study objectives, the researcher conducted a comparative analysis between IFRS 11 (Joint Arrangements) and the Iraqi Unified Accounting System, In the second step, IFRS 11 is applied to the Basrah Gas Company's (research sampl

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha