A total of 437 individuals of Turbellarin Platyhelminthes were sorted from benthic samples collected monthly for a period of seven months( April to November 2013 ) from AL-Dalmage lake, a part of middle section for main outfall drain south of Baghdad. They were identified as Gyratrix hermaphroditus, Stenostomum leucops ,Stenostomum unicolar and Stenostomum bryophilum ,The relative abundance of worms decreased during hot season which (May to September) ,where they start rising again. The species were studied alive , the identification criteria were illustrated by photos. G. hermaphroditus was the most abundant species among the four species.

The soil acari fauna of Citrus orchards of Baghdad in Jadiriya area was studied in a total
of forty-eight samples. Twenty-two species were recorded during the present study of which
eight species were first records to Iraq. The ordinal composition of the soil acari fauna was
predominantly Mesostigmata.
This fauna represents diverse trophic groups. The most abundant groups were the
predacious and the Microphytophagus, while the less abundant groups were the predacious/
Microphytophagus, Macrophytophagus, and Panaphytophagus. The most abundant and
frequent species were Rhizoglyphus sp. Tyrophagus putrescentiea (Scrank), Pachylaelaps
longisetis Halbt. and Stratiolaelaps miles Berl.

A new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever

This paper presents an improved technique on Ant Colony Optimization (ACO) algorithm. The procedure is applied on Single Machine with Infinite Bus (SMIB) system with power system stabilizer (PSS) at three different loading regimes. The simulations are made by using MATLAB software. The results show that by using Improved Ant Colony Optimization (IACO) the system will give better performance with less number of iterations as it compared with a previous modification on ACO. In addition, the probability of selecting the arc depends on the best ant performance and the evaporation rate.

planning is among the most significant in the field of robotics research.  As it is linked to finding a safe and efficient route in a cluttered environment for wheeled mobile robots and is considered a significant prerequisite for any such mobile robot project to be a success. This paper proposes the optimal path planning of the wheeled mobile robot with collision avoidance by using an algorithm called grey wolf optimization (GWO) as a method for finding the shortest and safe. The research goals in this study for identify the best path while taking into account the effect of the number of obstacles and design parameters on performance for the algorithm to find the best path. The simulations are run in the MATLAB environment to test the

    In this study, the dung beetles Aphodius (Bodilus) ictericus (Laicharting, 1781) and Aphodius (Planolinellus) vittatus Say, 1825 which belongs to the family of Aphodiidae (Order: Coleoptera) are redscribed here as to being found for the first time in Iraq.

    The specimens were collected from different regions in the middle of Iraq; the main diagnostic characters and some morphological features of males were drawn and pictured.

Sustainable plant protection and the economy of plant crops worldwide depend heavily on the health of agriculture. In the modern world, one of the main factors influencing economic growth is the quality of agricultural produce. The need for future crop protection and production is growing as disease-affected plants have caused considerable agricultural losses in several crop categories. The crop yield must be increased while preserving food quality and security and having the most negligible negative environmental impact. To overcome these obstacles, early discovery of satisfactory plants is critical. The use of Advances in Intelligent Systems and information computer science effectively helps find more efficient and low-cost solutions. Thi