have suffered from deteriorating residential neighborhoods, poor economic, social and urban living conditions of the population and deteriorating the infrastructural and superior services. These problems were the secretions of these cities' rapid urbanization. Based on the principles of sustainable urban planning and in order to achieve adequate opportunities for the lives of the population and provide them with sustainable livelihoods, policies have emerged to upgrade along the lines of community participation and programmes to reform and develop those neighbourhoods, raise their efficiency and make them livable. Thus, the problem of research was identified "The absence of a comprehensive cognitive perception of the most prominent factors influencing community participation and its role in upgrading degraded neighborhoods". Accordingly, the research objective was set to activate community participation mechanisms to identify the most important factors influencing community participation and their impact on the development of degraded residential areas. While the main research hypothesis is (There are a range of factors influencing the activation of community participation to upgrade degraded residential areas). On one hand, the research included a theoretical aspect addressing the concept of community participation, the factors affecting it, the importance, objectives, benefits and patterns of community participation, and the concept, types and characteristics of degraded residential areas. On the other hand, the practical aspect included studying Imam district in Nasiriyah, where a questionnaire was conducted for a sample of residents in the neighborhood. The practical aspect included the study of Imam neighbourhood area of Nasiriyah, where a questionnaire was conducted for a sample of residents in the neighbourhood. The research, using the logistical regression model, found that stimulating the desire to participate through advisory and consultation has a moral and positive effect in activating community participation. In addition, empowering the community through their participation in workshops and training contributes to job creation, reducing unemployment and enabling participation in the upgrading of the residential area.The research also found that there were other influential factors but that their impact was not moral such as sex, age, length of stay, property and trust in the local authority. The research concluded that upgrading degraded residential areas can be done by engaging individuals and increasing their desire to develop their neighborhoods. Also, by social development and social inclusion through workshops, consultation and training in order to enhance their skills and enhance their participation in achieving the goal of improving urban and living standards.
The increasing availability of computing power in the past two decades has been use to develop new techniques for optimizing solution of estimation problem. Today's computational capacity and the widespread availability of computers have enabled development of new generation of intelligent computing techniques, such as our interest algorithm, this paper presents one of new class of stochastic search algorithm (known as Canonical Genetic' Algorithm ‘CGA’) for optimizing the maximum likelihood function strategy is composed of three main steps: recombination, mutation, and selection. The experimental design is based on simulating the CGA with different values of are compared with those of moment method. Based on MSE value obtained from bot
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In this paper a prey - predator model with harvesting on predator species with infectious disease in prey population only has been proposed and analyzed. Further, in this model, Holling type-IV functional response for the predation of susceptible prey and Lotka-Volterra functional response for the predation of infected prey as well as linear incidence rate for describing the transition of disease are used. Our aim is to study the effect of harvesting and disease on the dynamics of this model.
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This study was conducted to evaluate the efficacy of Saccharomyces cerevesiae as a growth promoting agent in tomato. Soaking the seeds in yeast suspension at 5 g/L for 12h increased germination percentage, root length, root fresh and dry weight, plant height, foliage fresh and dry weight, attained 88.5% ; 8.1 cm ; 84.3 mg ; 7.03 mg ; 10.75 cm ; 839 mg and 37.75 mg compared with 80% ; 5.33 cm ; 39 mg ; 4.8 mg ; 7.35 cm ; 608 mg and 25.5 mg in seedlings grown from non treated seeds respectively. Similar results were obtained with seedling from seeds soaked in S. cerevesiae filtrate for 12 hrs. with values of 77.5% ; 6.875 cm ; 91.5 mg ; 7.5 mg ; 9.5 cm ; 777 mg and 40.35 mg compared to 66% ; 5.8 cm ; 57.7 mg ; 5.03 mg ; 5.9 cm ; 493 mg
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Around fifty isolates of Salmonella enterica serovar Typhi were isolated from blood specimens of patients referring to several hospitals in Kirkuk province, Iraq. The results revealed that all isolates developed resistance to trimethoprim-sulfamethoxazole and chloramphenicol. However, neither sul2 nor tem genes were detected. Moreover, only ten isolates were positive for catP. Our data suggested participation of other genes or mechanisms allow these multidrug isolates to resist the antibiotics in question.
In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo
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Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Erro
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