A seasonal study of periphytic algae attached to the surface of river boats was conducted in Tigris river in Al Aadhamiya site for the period from October 2016 to May 2017. A total of 107 taxa of periphytic algae were identified belonging to the four classes of algae. The periphytic algae community dominated by Bacillariophyceae was (60.7%) followed by Chlorophyceae (20.5%) and Cyanophyceae (17.7%) Chrysophyceae was constituted (0.9%) of the total number. During the whole period of study filamentous taxa such as Oscillatoria amphibian, Phormidium spp., Spirulinagigantean, Cladophoreglomerata and Melosira roeseana remained the dominant colonizer which may be reflect the ability of this species to grow multiplies under different environmental

Background: Data on the impact of neonatal and total pediatric admissions volume on neonatal mortality are sparse. Objectives: This study is done to estimate the neonatal mortality in relation to neonatal admissions and to total hospital admissions in Al-Alwyia Pediatric Teaching Hospital through years 2005-2012 Type of the study: A retrospective study.Methods: statistical records of all cases admitted to APTH were studied during 2005-2012.Results: Neonatal mortality decreased to the nadir at last year of study period (2012) and reached 6.1% of neonatal admissions compared to 2005 level which was 9.7 %. Mortality rate among premature and low birth weight (LBW) infants decreased also. The study also reveals that neonatal mortality constit

Objectives: The study aims at:
1- Measuring the level of lead in workers’ saliva and blood in the factory.
2- Studying the correlation between the saliva lead level and the infection that caused by microorganisms, isolation and
identification.
3-Studying the influence of high blood lead level on the total white blood cells.
Methodology: This study has been conducted for the period from March 15th, 2010 to May, 20th
, 2010. A total of (60)
saliva and blood samples were collected from workers in batteries industry factory in Baghdad and another (20) samples
were collected as a control group. Lead level had been measured in blood and saliva samples, then microorganisms were
isolated the from the saliva samples.

Shaky Baghdad heavy crude oil 22 API is processed by distillation and solvent extraction. The purpose of distillation is to separate the light distillates    (light fractions) which represent 35% of heavy crude oil, and to obtain the reduced crude oil. The heavy residue (9 API) is  extracted with Iraqi light naphtha to get the deasphaltened oil (DAO), the extraction carried out with temperature range of 20-75 ^oC, solvent to oil ratio 5-15:1(ml:g) and a mixing time of 15 minutes. In general, results show that API of DAO increased twice the API of reduced crude oil while sulfur and metals content decreased 20% and 50% respectively. Deasphaltened oil produced from various operating conditions blended with the

Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

     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

Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15