Background: since the occurrence of transient bacteraemia is fatal following different dental procedures in patients at-risk of bacterial endocarditis, the purpose of this research was to estimate the percentage and nature of bacteraemia following four orthodontic treatment procedures which were: an upper alginate impression, separator placement, band fitting or placement, and arch wire adjustment on a fixed appliance.Materials and methods: the study group consisted of 40 patients (25 females and 15 males) ranging from 17-25 years of age attending Orthodontic Department in the College of Dentistry/Baghdad University, and out patients department from private clinic. The 40 patients were divided into four groups (10 patients each). A cannula was inserted into either the left or right antecubital fossa using an aseptic technique. A 5ml of blood was taken immediately before orthodontic treatment procedure and a second 5ml sample was taken 1-2 minutes after the procedure.Results: the blood samples showed a percentage of bacteraemia of 50%, 40%, 30%, and 20% in cases of post-band placement, post-separator placement, post-arch wire adjustment, and post-alginate impression procedures respectively.Conclusion: this investigation demonstrated that the placement of separator and fitting of band procedures could cause a significant bacteraemia, thus these procedures for patients at–risk of bacterial endocarditis should be placed in consideration, and prescribe the necessarily antibiotic coverage.
In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe
... Show MoreIn this research, the removal of cadmium (Cd) from simulated wastewater was investigated by using a fixed bed bio-electrochemical reactor. The effects of the main controlling factors on the performance of the removal process such as applied cell voltage, initial Cd concentration, pH of the catholyte, and the mesh number of the cathode were investigated. The results showed that the applied cell voltage had the main impact on the removal efficiency of cadmium where increasing the applied voltage led to higher removal efficiency. Meanwhile increasing the applied voltage was found to be given lower current efficiency and higher energy consumption. No significant effect of initial Cd concentration on the removal efficie
... Show MoreThis study focusing on river water quality as a source of raw water, efficiencies of water treatment plants, the goodness of transporting water pipes in the water networks and drinking water quality as consumed within certain city residential sectors, in addition to seasonal variation. The following water quality parameters were studied: Electrical Conductivity, Turbidity, Dissolved oxygen, Biochemical oxygen demand, the concentration of nutrients like nitrogen and phosphate, the residual chlorine in addition to total bacterial count and total colon bacteria of raw water, and treated water of four selected water treatment plants in Mosul city. These plants are : the right united scheme, the new left scheme ,the old left scheme and the Gh
... Show MoreIn this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi
... Show MoreThis work presents an approach to deal with modelling a decision support system framework to introduce an application for decisions in medical knowledge system analysis. First aid is extremely important worldwide and, hence, a decision support framework, know as First Aid Decision Support System (FADSS), was designed and implemented to access experimental cases exerting danger to the general population, offering advanced conditions for testing abilities in research and arranging an emergency treatment through the graphical user interface (UI). The design of first aid treatment in FADSS depends on the general cases in first aid. We presented a strategy to manage first aid treatment by modelling an application (FADSS) that assists pe
... Show MoreThree isolated bacteria were examined to remove heavy metals from the industrial wastewater of the Diala State Company of Electrical Industries, Diyala-Iraq. The isolated bacteria were identified as Pseudomonas aeruginosa, Escherichia coli and Sulfate Reducing Bacteria (SRB). The three isolates were used as an adsorption factor for different concentrations of Lead and Copper (100, 150, and 200 ppm.), in order to examine the adsorption efficiency of these isolates. In addition, the effect of three factors on heavy metals adsorption were examined; temperature (25, 30, and 37 ?C), pH (3 and 4.5) and contact time (2 and 24 hrs). The results showed that the highest level of lead adsorption was obtained at 37 ?C by E. coli, P, aerugenosa and
... Show MoreThe efficient removal of dissolved organic compounds (DOC) from wastewater has become a major environmental concern because of its high toxicity even at low concentrations. Therefore, a technique was needed to reduce these pollutants. Ion exchange technology (IE) was used with AmberliteTM IR120 Na, AmberliteTM IR96RF, and AmberliteTM IR402, firstly by using anion and mixed bed system, where the following variables are investigated for the process of adsorption: The height of the bed in column (8,10 and 14 cm), different concentrations of (DOC) content at constant flow rate. The use of an ion exchanger unit (continuous system) with three columns (cation, anion, and mixed bed) was studied.
... Show MoreThe brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition s
... Show MoreRealistic implementation of nanofluids in subsurface projects including carbon geosequestration and enhanced oil recovery requires full understanding of nanoparticles (NPs) adsorption behaviour in the porous media. The physicochemical interactions between NPs and between the NP and the porous media grain surface control the adsorption behavior of NPs. This study investigates the reversible and irreversible adsorption of silica NPs onto oil-wet and water-wet carbonate surfaces at reservoir conditions. Each carbonate sample was treated with different concentrations of silica nanofluid to investigate NP adsorption in terms of nanoparticles initial size and hydrophobicity at different temperatures, and pressures. Aggregation behaviour and the
... Show MoreThis research utilized natural asphalt (NA) deposits from sulfur springs in western Iraq. Laboratory tests were conducted to evaluate the performance of an asphalt mixture incorporating NA and verify its suitability for local pavement applications. To achieve this, a combination of two types of NA, namely soft SNA and hard HNA, was blended to create a binder known as Type HSNA. The resulting HSNA exhibited a penetration grade that adhered to Iraqi specifications. Various percentages of NA (20%, 40%, 60%, and 80%) were added to petroleum asphalt. The findings revealed enhanced physical properties of HSNA, which also satisfied the requirements outlined in the Iraqi specifications for asphalt cement.
Consequently, HS
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