Summary The aim of this study is the evaluation the resistance of S. marcescence obtained from soil and water to metals chlorides (Zn+2, Hg+2, Fe+2, Al+3, and Pb+2). Four isolates, identified as Serratia marcescence and S. marcescena (S4) were selected for this study according to their resistance to five heavy metals. The ability of S. marcescena (S4) to grow in different concentrations of metals chloride (200-1200 µg/ml) was tested, the highest concentration that S. marcescence (S4) tolerate was 1000 µg/ml for Zn+2, Hg+2, Fe+2, AL+3, pb+2 and 300 µg/ml for Hg+2 through 24 hrs incubation at 37 Co. The effects of temperature and pH on bacteria growth during 72 hrs were also studied. S. marcescence (S4) was affected by ZnCl2, PbCl2, FeC12, and AlCl3 during 24 hrs, while mercury causes no bacterial growth. S. marcescence (S4) showed growth in temperature range of 30-50 Co in presence of 4 metals. The isolates showed the ability to grow in different pH values (4, 7 and 9) in presence of four metals in all pH values (1000 µg/ml) and un-ability to grow with 300 µg/ml Hg+2. The highest Zn+2 removal ratio was 75% then Pb+2 55% while Fe+2 has the lowest removal ratio (48%). The study was conducted in the central lab of College of sciences/University of Baghdad/Iraq in 2011-2012. It was conclude that the identified heavy metal resistant bacteria could be useful for bioremediation of heavy metals in the contaminated soil and water.
The experiment was carried out in the field of botanical garden belonging to the Department of Biology Sciences, College of Education for Pure Science -Ibn AL-Haitham ,Baghdad University. for the growing season. 2014 -2013 to study the effect of the electromagnetic field which included five different intensities (0,5,10,15,20) MT and three periods of time, namely, (1,2,3) an hour and their interaction on some of the morphological characteristics of the safflower plant . designed experiment by Randomized Complete Block Design (RCBD) and three replicates per treatment, compared to the average using less significant difference at the level of probability (0.05) , the results showed the following:- 1-Exposing seeds to diffe
... Show MoreAbstract: Urinary Tract Infections (UTIs) are the most common bacterial infection in humans and a major cause of morbidity and they are the most common cause of hospital visits worldwide. Proper knowledge in identifying factors associated with urinary tract infection may allow the intervention to easily control of the disease in a timely manner. Therefore, the purpose of the study is determining the prevalence of UTI, diagnosis of causative bacterial agents and identifying the factors associated to the urinary tract infection among patients attending Medical City Hospital in Baghdad, Iraq. A total of 237, morning mid-stream urine samples were collected aseptically and the samples were diagnosed according to the standard methods. I
... Show MoreIdentification of complex communities in biological networks is a critical and ongoing challenge since lots of network-related problems correspond to the subgraph isomorphism problem known in the literature as NP-hard. Several optimization algorithms have been dedicated and applied to solve this problem. The main challenge regarding the application of optimization algorithms, specifically to handle large-scale complex networks, is their relatively long execution time. Thus, this paper proposes a parallel extension of the PSO algorithm to detect communities in complex biological networks. The main contribution of this study is summarized in three- fold; Firstly, a modified PSO algorithm with a local search operator is proposed
... Show MoreIdentification of complex communities in biological networks is a critical and ongoing challenge since lots of network-related problems correspond to the subgraph isomorphism problem known in the literature as NP-hard. Several optimization algorithms have been dedicated and applied to solve this problem. The main challenge regarding the application of optimization algorithms, specifically to handle large-scale complex networks, is their relatively long execution time. Thus, this paper proposes a parallel extension of the PSO algorithm to detect communities in complex biological networks. The main contribution of this study is summarized in three- fold; Firstly, a modified PSO algorithm with a local search operator is proposed to d
... Show MoreMost Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mo
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