An integrated GIS-VBA (Geographical Information System – Visual Basic for Application), model is developed for selecting an optimum water harvesting dam location among an available locations in a watershed. The proposed model allows quick and precise estimation of an adopted weighted objective function for each selected location. In addition to that for each location, a different dam height is used as a nominee for optimum selection. The VBA model includes an optimization model with a weighted objective function that includes beneficiary items (positive) , such as the available storage , the dam height allowed by the site as an indicator for the potential of hydroelectric power generation , the rainfall rate as a source of water . In addition to that (negative) penalty items are also included such as surface area, evaporation rate.
In order to obtain precise results, an Artificial Neural Network (ANN) model was formulated and applied to correct the elevations of the Digital Elevation Model (DEM) map using real and DEM elevations of available selected control points.
The application of the model is tested using a case study of a catchment area in Diyala and Wasit Governorate. The DEM file was corrected for elevations, using the developed ANN model .This model is found using SPSS – software. The correlation coefficient of this model is found to be (0.97) , with 3- hidden nodes and hyperbolic tangent and identity activation functions. Different weight scenarios for the objective function of the optimization model were adopted. The results indicate that different optimum dam locations can be observed for each case. Results indicate also that sometimes equal objective can be obtained but each has different reservoir volume and surface area.
Evaluation of the Antibacterial Efficacy of Electrolyzed Oxidizing Water as an Irrigant against Enterococcus faecalis (An In vitro Study), Noor A Khait*, Muna Saleem Kalaf
A field experiment was conducted during the autumn of 2021 at the Agricultural Research Department station / Abu Ghraib to evaluate the soil moisture, water potential distribution, and growth factors of maize crops under alternating and constant partial drip irrigation methods. In the experiment, two irrigation systems were used, surface drip irrigation (DI) and subsurface irrigation (SD); under each irrigation system, five irrigation methods were: conventional irrigation (CI), and 75 and 50% of the amount of water of CI of each of the alternating partial irrigation APRI75 and APRI50 and the constant partial irrigation FPRI75 and FPRI50 respectively. The results showed that the water depth for conventional irrigation (C1) was 658.3
... Show MoreTwo years field experiment was carried out at Agricultural Fields, College of Agriculture, Baghdad University, Al-Jadriya during 2014-2015 and 2015-2016 to determine the effect of salinity of irrigation water on growth and grain yield of three oat cultivars. The experiments were laid out according to randomized complete blocks design having split plot arrangements with two factors; first factor included three oat cultivars (Shifaa, Hamel and Pimula) while the second factor included three levels of salinity of irrigation water (3, 6 and 9 dS.m-1 ) in addition to the control (river water with salinity level of 1.164 dS.m-1 ) with three replicates. Results revealed a significant effect of salinity of irrigation water on all studied traits. Mea
... Show MoreThis study experimentally investigated Free-Fall Gravity Drainage (FFGD) under combination-drive conditions in a two-dimensional Hele-Shaw model representing a water-drive reservoir. An initially high gravity potential from the oil column enabled early oil drainage before aquifer support became dominant. Three water-drive strengths were tested, demonstrating that a stronger aquifer (1.15 psig) accelerated oil recovery to approximately 75% of the original oil in place (OOIP) within 60 minutes, resulting in a final recovery of 79.5%. However, this was accompanied by rapid water breakthrough after 2.5 minutes and high-water cuts exceeding 90%. In contrast, a weaker aquifer (0.725 psig) stabilized the oil–water contact, delaying w
... Show MoreDuring the study the current selection seven stations in the Zab River bottom and the Tigris River took samples a month to study the signs of bacterial contamination study coliform and colon fecal Almsobhaat and Almsobhaat Bazah and the total number of bacteria and bacterial gangrene gas causing Knkeran as well as a study to isolate and diagnose some races and types of bacterial pathogens in water or intensityusing the traditional system and the system of intestinal bacteria
Therapeutic contact lenses TCLs is an approach used to enhance corneal residence time and reduce frequent instillation, which is a problem with eye drops. The problem with CLs is loading of hydrophobic drugs. In this research the CLs were prepared with molecular imprinting MI to enhance the loading of itraconazole, which is used as antifungal drug for fungal keratitis. CLs using different concentration of hydroxyethyl methacrylate HEMA and methacrylic acid MAA were prepared with and without MI using PEGDA (25 μL) and AIBN (37 mg) as crosslinker and initiator respectively. All the prepared CLs were clear and have good folding endurance. MICLs had significantly higher drug loading compared to conventional CLs. The release of i
... Show MoreThe aim of this work is to evaluate some mechanical and physical
properties (i.e. the impact strength, hardness, flexural strength,
thermal conductivity and diffusion coefficient) of
(epoxy/polyurethane) blend reinforced with nano silica powder (2%
wt.). Hand lay-up technique was used to manufacture the composite
and a magnetic stirrer for blending the components. Results showed
that water had affected the bending flexural strength and hardness,
while impact strength increased and thermal conductivity decreased.
In addition to the above mentioned tests, the diffusion coefficient
was calculated using Fick’s 2nd law.
The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA
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