Three plant species were picked randomly and their alcoholic extracts have been screened to know their effects on the phagocytic capability and intracellular killing of yeast by human peripheral macrophages. Macrophage cultures were incubated with different concentration of each plant extract: for 15 min., 30 min .and 45 min. The phagocytes activity in Iresine herbstii extract was significantly (p?0.05) increased with increasing dose and time of incubation. In Mentha piperita extract, increasing in dose and time of incubation leads to elevate phagocytic capbility, especially in the dose of 20% and 25% of plant extract, perhaps because the antimicrobial and antiviral activities of this plant, as well as strong antioxidant and antitumor act

A Pap test can identify the pre-cancerous and cancerous problem in the vagina and uterine cervix. Cervical tumour is the easiest gynecologic disease to be diagnosed, treated and prevented using regular screening tests and follow-up. This review aimed to explore the opinion of specialists about cytological changes and the precancerous lesions with Pap smear test and visual inspection of the cervices, also to determine the relationship of this malignancy with demographic characteristics of patients. Results showed that few cervical cancer and pre-cancer were with women in postmenopausal period, but more were with women in the premenopausal period. Visual inspection of the cervix can show erosion lesions by gross inspection. Upon cytology exam

Aggregate production planning (APP) is one of the most significant and complicated problems in production planning and aim to set overall production levels for each product category to meet fluctuating or uncertain demand in future. and to set decision concerning hiring, firing, overtime, subcontract, carrying inventory level. In this paper, we present a simulated annealing (SA) for multi-objective linear programming to solve APP. SA is considered to be a good tool for imprecise optimization problems. The proposed model minimizes total production and workforce costs. In this study, the proposed SA is compared with particle swarm optimization (PSO). The results show that the proposed SA is effective in reducing total production costs and req

In this investigative endeavor, a novel concrete variety incorporating sulfur-2,4-dinitrophenylhydrazine modification was developed, and its diverse attributes were explored. This innovative concrete was produced using sulfur-2,4-dinitrophenylhydrazine modification and an array of components. The newly created sulfur-2,4-dinitrophenylhydrazine modifier was synthesized. The surface texture resulting from this modifier was examined using SEM and EDS techniques. The component ratios within concrete, chemical and physical traits derived from the sulfur-2,4-dinitrophenylhydrazine modifier, chemical and corrosion resistance of concrete, concrete stability against water absorption, concrete resilience against freezing, physical and mechanical p

The Ant System Algorithm (ASA) is a member of the ant colony algorithms family in swarm intelligence methods (part of the Artificial Intelligence field), which is based on the behavior of ants seeking a path and a source of food in their colonies. The aim of This algorithm is to search for an optimal solution for Combinational Optimization Problems (COP) for which is extremely difficult to find solution using the classical methods like linear and non-linear programming methods. 

The Ant System Algorithm was used in the management of water resources field in Iraq, specifically for Haditha dam which is one of the most important dams in Iraq. The target is to find out an efficient management system for

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others