Alzheimer’s disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have n

This research involves the synthesis of some sulphanyl benzimidazole derivatives (Ia-c), which were prepared from reaction of 2-mercaptobenzimidazole substituted benzyl halide, and structures were identified by spectral methods[FTIR, 1H-NMR and 13C-NMR].These compounds were investigated as corrosion inhibitors for carbon steel in 1M H2SO4 solution using weight loss, potentiostatic polarization methods; obtained results showed that the sulphanyl benzimidazole derivatives retard both cathodic and anodic reactions in acidic media, by virtue of adsorption on the carbon steel surface. This adsorption obeyed Langmuir’s adsorption isotherm. The inhibition efficiency of (Ia-c) ranging between (65-92) %. By using different Ib derivative conc

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

The current research aims to prepare a proposed Programmebased sensory integration theory for remediating some developmental learning disabilities among children, researchers prepared a Programme based on sensory integration through reviewing studies related to the research topic that can be practicedby some active teaching strategies (cooperative learning, peer learning, Role-playing, and educational stories). The Finalformat consists of(39) training sessions.

The objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost, loss etc. while maintaining an acceptable system performance in terms of limits on generators real and reactive powers, line flow limits etc. The OPF solution includes an objective function. A common objective function concerns the active power generation cost. A Linear programming method is proposed to solve the OPF problem. The Linear Programming (LP) approach transforms the nonlinear optimization problem into an iterative algorithm that in each iteration solves a linear optimization problem resulting from linearization both the objective function and constrains. A computer program, written in MATLAB environme

This research deals with process of artistic conception of nature's images between becoming and buration, as an attempt to transfer the philosophical concepts to art via it's structural applications in forming the picture, due to the importance of these concepts which might be engaged with the vision of the artist in his own and subjective contention with the nature. The research consists of four chapters, first one included the problem of the research, importance, need to the research and the aim of the research represented by process of artistic conception of nature's images between becoming  and buration. Also included the limits of research and most important terms. Second chapter included theoretical frame that consists of thre

One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed