Abstract: The article aimed to formulate an MLX binary ethosome hydrogel for topical delivery to escalate MLX solubility, facilitate dermal permeation, avoid systemic adverse events, and compare the permeation flux and efficacy with the classical type. MLX ethosomes were prepared using the hot method according to the Box–Behnken experimental design. The formulation was implemented according to 16 design formulas with four center points. Independent variables were (soya lecithin, ethanol, and propylene glycol concentrations) and dependent variables (vesicle size, dispersity index, encapsulation efficiency, and zeta potential). The design suggested the optimized formula (MLX−Ethos−OF) with the highest desirability to perform the

Background: Frovatriptan succinate (FVT) is an effective medication used to treat migraines; however, available oral formulations suffer from low permeability; accordingly, several formulations of FVT were prepared. Objective: Prepare, optimize, and evaluate FVT-BE formulation to develop enhanced intranasal binary nano-ethosome gel. Methods: Binary ethosomes were prepared using different concentrations of phospholipid PLH90, ethanol, propylene glycol, and cholesterol by thin film hydration and characterized by particle size, zeta potential, and entrapment efficiency. Furthermore, in-vitro, in-vivo, ex-vivo, pharmacokinetics, and histopathological studies were done. Results: Regarding FVT-loaded BE, formula (F9) demonstrated the best paramet

Nowadays, it is quite usual to transmit data through the internet, making safe online communication essential and transmitting data over internet channels requires maintaining its confidentiality and ensuring the integrity of the transmitted data from unauthorized individuals. The two most common techniques for supplying security are cryptography and steganography. Data is converted from a readable format into an unreadable one using cryptography. Steganography is the technique of hiding sensitive information in digital media including image, audio, and video. In our proposed system, both encryption and hiding techniques will be utilized. This study presents encryption using the S-DES algorithm, which generates a new key in each cyc

This work aims to develop a secure lightweight cipher algorithm for constrained devices. A secure communication among constrained devices is a critical issue during the data transmission from the client to the server devices. Lightweight cipher algorithms are defined as a secure solution for constrained devices that require low computational functions and small memory. In contrast, most lightweight algorithms suffer from the trade-off between complexity and speed in order to produce robust cipher algorithm. The PRESENT cipher has been successfully experimented on as a lightweight cryptography algorithm, which transcends other ciphers in terms of its computational processing that required low complexity operations. The mathematical model of

Broyden update is one of the one-rank updates which solves the unconstrained optimization problem but this update does not guarantee the positive definite and the symmetric property of Hessian matrix.

In this paper the guarantee of positive definite and symmetric property for the Hessian matrix will be established by updating the vector  which represents the difference between the next gradient and the current gradient of the objective function assumed to be twice continuous and differentiable .Numerical results are reported to compare the proposed method with the Broyden method under standard problems.

In this paper a decoder of binary BCH code is implemented using a PIC microcontroller for code length n=127 bits with multiple error correction capability, the results are presented for correcting errors up to 13 errors. The Berkelam-Massey decoding algorithm was chosen for its efficiency. The microcontroller PIC18f45k22 was chosen for the implementation and programmed using assembly language to achieve highest performance. This makes the BCH decoder implementable as a low cost module that can be used as a part of larger systems. The performance evaluation is presented in terms of total number of instructions and the bit rate.

Abstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.

In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained