Monitoring lotic ecosystems is vital for addressing sustainability issues. The Al-Shamiyah River is the primary source of water for various daily activities in the Al-Shamiyah district. This study assessed the pollution levels of the river by measuring the concentration and distribution of heavy metals—specifically chromium, cadmium, manganese, copper, zinc, and lead—in both the river's water and sediments. The concentrations of heavy metals in the water ranged from 0.05 to 1.44µg/ L for copper (Cu), 1.57 to 7.25µg/ L for manganese (Mn), 0 to 1.7µg/ L for cadmium (Cd), 0.02 to 1.33µg/ L for lead (Pb), 0.08 to 2.74µg/ L for zinc (Zn), and 0.44 to 1.84µg/ L for chromium (Cr). In the particulate phase, the concentrations ranged from

The heavy metals Cd, Cu, Fe, pb, and Zn were determined in dissolved and particulate phases of the water,in addition to exchangeable and residual phases of the sediment and in the selected organs of the fish Cyprinus carpio collected from the Euphrates River near Al-Nassiriya city center south of Iraq during the summer period / 2009 .Also sediment texture and total organic carbon(TOC) were measured. Analysis emploing a flam Atomic Absorption Spectrophotometers . The mean regional concentrations of the heavy metals in dissolved (µg/l) and particulate phases (µg/gm) dry weight were Cd (0.15,16.13) ,Cu (0.59,24.48) ,Fe (726,909.4) ,Pb (0.20, 49.95) and Zn (2.5,35.62) respectively,and those for exchangeable and residual phases of the

The current study aimed to determine the relation between the lead levels in the blood traffic men and the nature of their traffic work in Baghdad governorate. Blood samples were collected from 10 traffic men and the age about from 20-39 year from Directorate of Traffic Al Rusafa/ Baghdad and 10 samples another control from traffic men too with age 30-49 year and they livedrelatively in the clear cities or contained of Very few traffic areas. The levels of lead in blood estimated by used Atomic Absorption Spectrometry.
The result stated that there is no rising of the levels of lead in blood of traffic men Lead concentration was with more a range from 14 ppm in Traffic police are not healthy They are within the permissible limits, Ap

Tigris River is the lifeline that supplies a great part of Iraq with water from north to south. Throughout its entire length, the river is battered by various types of pollutants such as wastewater effluents from municipal, industrial, agricultural activities, and others. Hence, the water quality assessment of the Tigris River is crucial in ensuring that appropriate and adequate measures are taken to save the river from as much pollution as possible. In this study, six water treatment plants (WTPs) situated on the two-banks of the Tigris within Baghdad City were Al Karkh; Sharq Dijla; Al Wathba; Al Karama; Al Doura, and Al Wahda from northern Baghdad to its south, that selected to determine the removal efficiency of turbidity and

This study was conducted from February 2010 to December 2010. Water Samples were collected every two months in three stations in Baghdad city. The study involved the assessment of concentrations of some heavy metals such as: Chromium, Cadmium, Copper, Iron, Lead, Manganese, Nickel and Zinc. the values of chromium were undetected for the entire of the study, while the rest of the heavy metal were ranged between 0.001 -0.438 mg / l, ND -0.077 mg / L, ND -0.778 mg / l, 0.36 - 0.011 mg / l, 0.011-0 .08mg/ l, ND - 0.1985 mg / l, ND -0.0416 mg / l, respectively. The results showed that the concentrations of heavy metals were fluctuated during the study period, except Lead which have high concentrations and exceeded the permit limits in all statio

The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

Concentrations of heavy metals (Copper Cu, Iron Fe, Manganese Mn, Cadmium Cd, and Lead Pb) have been studied in river crab Sesarma boulengeri (Outer part of the shield and interior tissues) which caught from two stations in Shatt Al – Arab river (Salhia and Aldeir areas). Elements concentrations were measured by Flame Atomic Absorption Spectrophotometer, concentration of heavy metals in the internal tissues was higher than in the outer shield in both of the stations with the highest value of the elements was to iron 95.21 mg\ kg during the spring as well as copper was 55 mg\kg and manganese was 39.09 mg\kg. The study showed the presence of seasonal changes in the studied heavy metals concentrations values in the tissues of river crab;

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data