To reduce the effects of discharging heated water disposed into a river flow by a single thermal source, two parameters were changed to get the minimum effect using optimization. The first parameter is to distribute the total flow of the heated water between two disposal points (double source) instead of one and the second is to change the distance between these two points. In order to achieve the solution, a two dimensional numerical model was developed to simulate and predict the changes in temperature distribution in the river due to disposal of the heated water using these two points of disposal.
MATLAB-7 software was used to build a program that could solve the governing partial equations of thermal pollution in rivers by using the finite difference technique. The distribution of temperature in the river was presented by using the SURFER software that was used to draw the temperature contour lines and computing the areas of critical temperature (The area where the temperature exceed a certain selected value, which is believed to be critical for aquatic life). The optimum case was that which gave the minimum critical area.
The decision variables are the subdivided flow of the two disposal points, and the distance between these two points. The result had indicated that the optimum case can be achieved when the flow of first point was 0.1 from the total flow of heated water and the second was 0.9 from this total flow. The optimal distance between the two points was found to be 30 m.
A simple, precise, and sensitive spectrophotometric method has been established for the analysis of doxycycline. The method includes direct charge transfer complexation of doxycycline withp-Bromanil in acetonitrileto form a colored complex. The intensely colored product formed was quantified based on the absorption band at 377 nm under optimum condition. Beer’s law is obeyed in the concentration range of 1–50 μg.mL-1 with molar absorptivity of 1.5725x104 L.mol-1.cm-1, Sandell's sensitivity index (0.0283) μg.cm-2, detection limit of 0.1064 μg.mL-1, quantification limit 0.3224 μg.mL-1 and association constant of the formed complex (0.75x103). The developed method could find application in routine quality control of doxycycline and has
... Show MoreReservoir characterization plays a crucial role in comprehending the distribution of formation properties and fluids within heterogeneous reservoirs. This knowledge is instrumental in constructing an accurate three-dimensional model of the reservoir, facilitating predictions regarding porosity, permeability, and fluid flow distribution. Among the various methods employed for reservoir characterization, the hydraulic flow unit stands out as a widely adopted approach. By effectively subdividing the reservoir into distinct zones, each characterized by unique petrophysical and geological properties, hydraulic flow units enable comprehensive reservoir analysis. The concept of the flow unit is closely tied to the flow zone indicator, a cr
... Show MoreBackground: Characterization of the ovarian masses preoperatively is important to inform the surgeon about the possible management strategies. MRI may be of great help in identifying malignant lesion before surgery. Diffusion Weighted Imaging (DWI) is a sensitive method for changes in proton of water mobility caused by pathological alteration of tissue cellularity, cellular membrane integrity, extracellular space perfusion, and fluid viscosity.
Objective: to study the diagnostic accuracy of DWI in differentiation between benign and malignant ovarian masses.
Type of the study:Cross-sectional study.
Methods: this study included 53with complex
... Show MoreKE Sharquie, HM Al-Hamamy, AA Noaimi, IA Al-Shawi, Journal of the Saudi Society of Dermatology & Dermatologic Surgery, 2011 - Cited by 9
The present study was aimed to find out the role of humoral immunity in the pathogenesis of psoriasis. Complements C3, C4 and immunoglobulin IgE .The study included 55 Iraqi patients with psoriasis 30 (15 females ,15 males) were untreated with any drugs. The other patient group consisted of 25 (9 female and 16 male) treated with a biological treatment (infliximab) ,and 30 (13 males ,12 females) healthy control group. Blood sample were withdrawn (5) ml of venous blood for both patients and members of the control ,to conduct the Immunological tests to determine the quantitative for each of total IgE by using (ELISA) and C3,C4 by Single Radial Immunodiffuse (SIRD). The results showed significant increase in the level of probability (P <0.0
... Show MoreThe aim of this work was to estimate the concentrations of natural and artificial nuclides in some fertilized and unfertilized plant samples. These samples were collected and prepared in a petri dish for the measurements using gamma spectroscopy. The average values of 238U, 232Th, 40K, and 137Cs for the unfertilized plant samples were (11.964 ± 3.226, 8.273 ± 2.639, 402.436 ± 18.099, and 2.761 ± 1.613) respectively, and for the fertilized plant samples were (30.434 ± 5.282, 22.584 ± 4.620, 711.332 ± 25.806, and 6.986 ± 2.542) respectively. The average values of radiological hazard indices, Raeq, D, D for 137Cs, (AEDE)in, (AEDE)out, Iγ, Hin, and Hout for the unfertilized plant samples were (54.782 ± 7.216, 27.306, 0.469, 0.
... Show MoreOsteoblast and osteoclast activity is disrupted in post-menopausal osteoporosis. Thus, to fully address this imbalance, therapies should reduce bone resorption and promote bone formation. Dietary factors such as phyto-oestrogens and Zn have beneficial effects on osteoblast and osteoclast activity. However, the effect of combinations of these factors has not been widely studied. We therefore examined the effect of coumestrol, daidzein and genistein in the presence or absence of zinc sulphate (Zn) on osteoclast and osteoblast activity. Osteoclast differentiation and bone resorption were significantly reduced by coumestrol (10- 7 m), daidzein (10- 5 m) and genistein (10- 7 m); and this direct anti-osteoclastic action was unaffected by Zn (10-
... Show MoreThe successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
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