Background:Wilson’s disease (WD) is an inherited
disorder of copper metabolism that is characterized
by tremendous variation in the clinical presentation.
Objective: To assess demographic distribution,
clinical presentations, diagnostic evaluation, and any
association between clinical presentations and other
studied variables of a sample of Iraqi patients with
WD.
Methods: A descriptive cross sectional study with
analytic elements was conducted during 2011, from
the 1st of February till the 10th of June. The sampling
method was a convenient non-random one, carried
out through consecutive pooling of registered WD
patients. A questionnaire-form paper had been
developed for the process of data col

Objectives: To determine the effectiveness of the instructional program on patients’ knowledge about home safety while receiving anti-cancer treatment at  Al- Karama Teaching Hospital in Al-Kut City.

Methodology:   A quasi-experimental design is conducted through the application of a pre-test and post-test approach for the study and control groups from February 5^th, 2020 to April 25^th, 2020. A non–probability (purposive) sample of (50) patients treated at the Blood Disease and Oncology Center is selected and divided into two groups. Each group contains (25) patients as control and study groups. An instrument is constructed that is comprised of two parts; t

In this research want to make analysis for some indicators and it's classifications that related with the teaching process and the            scientific level for graduate studies in the university by using analysis of variance for ranked data for repeated measurements instead of the ordinary analysis of variance . We reach many conclusions  for the                         

important classifications for each indicator that has affected on   the teaching process.         &nb

Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E