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Constructed Wetland Units Filled with Waterworks Sludge for Remediating of Wastewater Contaminated with Congo Red Dye
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The disposal of textile effluents to the surface water bodies represents the critical issue especially these effluents can have negative impacts on such bodies due to the presence of dyes in their composition. Biological remediation methods like constructed wetlands are more cost-effective and environmental friendly technique in comparison with traditional methods. The ability of vertical subsurface flow constructed wetlands units for treating of simulated wastewater polluted with Congo red dye has been studied in this work. The units were packed with waterworks sludge bed that either be unplanted or planted with Phragmites australis and Typha domingensis. The efficacy of present units was evaluated by monitoring of DO, Temperature, COD and dye concentration in the effluents under the variation of detention time (1-5 day) and dye concentration (10-40 mg/L). The maximum removal of dye and COD were 98 and 82% respectively for 10 mg/L of Congo red dye after five-day hydraulic retention time (HRT). The results have shown that the removal of COD and dye concentration significantly increased with higher contact time and lower dye concentration. The values of monitored parameters adopted to evaluate the wastewater quality (i.e. DO, COD and Congo red dye) are satisfied the requirements of irrigation water. The dye concentration variation in the effluent with contact time was formulated efficiently by Grau kinetic model. Functional groups (specified by FT-IR analysis) have a remarkable role in the entrapment of dye on the waterworks sludge bed.

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Publication Date
Thu Jun 01 2023
Journal Name
Science Of The Total Environment
Sustainable application of tubular photosynthesis microbial desalination cell for simultaneous desalination of seawater for potable water supply associated with sewage treatment and energy recovery
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Publication Date
Tue Mar 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Semi-parametric regression function estimation for environmental pollution with measurement error using artificial flower pollination algorithm
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Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Spectrophotometric Method Combined with HPLC for Bisphenol F Determination in Plastic Bottled Water and Thermal Paper
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Based on the diazotization-coupling reaction, a new, simple, and sensitive spectrophotometric method for determining of a trace amount of (BPF) is presented in this paper. Diazotized metoclopramide reagent react with bisphenol F produces an orange azo-compound with a maximum absorbance at 461 nm in alkaline solution. The experimental parameters were optimized such as type of alkaline medium, concentration of NaOH, diazotized metoclopramide amount, order additions, reaction time, temperature, and effect of organic solvents to achieve the optimal performance for the proposed method. The absorbance increased linearly with increasing bisphenol F concentration in the range of 0.5-10 μg mL-1 under ideal conditions, with a correlati

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Finding the Best Route for Connecting Citizens with Service Centers in Baghdad Based on NN Technology
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     A geographic information system (GIS) is a very effective management and analysis tool. Geographic locations rely on data. The use of artificial neural networks (ANNs) for the interpretation of natural resource data has been shown to be beneficial. Back-propagation neural networks are one of the most widespread and prevalent designs. The combination of geographic information systems with artificial neural networks provides a method for decreasing the cost of landscape change studies by shortening the time required to evaluate data. Numerous designs and kinds of ANNs have been created; the majority of them are PC-based service domains. Using the ArcGIS Network Analyst add-on, you can locate service regions around any network

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Analytical Solutions for Advanced Functional Differential Equations with Discontinuous Forcing Terms and Studying Their Dynamical Properties
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This paper aims to find new analytical closed-forms to the  solutions of the nonhomogeneous functional differential equations of the nth order with finite and constants delays and various initial delay conditions in terms of elementary functions using Laplace transform method. As well as, the definition of dynamical systems for ordinary differential equations is used to introduce the definition of dynamical systems for delay differential equations which contain multiple delays with a discussion of their dynamical properties: The exponential stability and strong stability

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Publication Date
Thu Nov 01 2018
Journal Name
International Journal Of Biomathematics
A non-conventional hybrid numerical approach with multi-dimensional random sampling for cocaine abuse in Spain
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This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

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Publication Date
Sun Sep 01 2019
Journal Name
Gazi University Journal Of Science
Reliable Iterative Methods for Solving Convective Straight and Radial Fins with Temperature-Dependent Thermal Conductivity Problems
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In our article, three iterative methods are performed to solve the nonlinear differential equations that represent the straight and radial fins affected by thermal conductivity. The iterative methods are the Daftardar-Jafari method namely (DJM), Temimi-Ansari method namely (TAM) and Banach contraction method namely (BCM) to get the approximate solutions. For comparison purposes, the numerical solutions were further achieved by using the fourth Runge-Kutta (RK4) method, Euler method and previous analytical methods that available in the literature. Moreover, the convergence of the proposed methods was discussed and proved. In addition, the maximum error remainder values are also evaluated which indicates that the propo

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
A comparison among Different Methods for Estimating Regression Parameters with Autocorrelation Problem under Exponentially Distributed Error
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Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

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Publication Date
Wed Mar 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
Complete Blood Count and saliva parameters as an indicator for infected patients with coronavirus covid-19
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Background: Coronavirus, which causes respiratory illness, has been a public health issue in recent decades. Because the clinical symptoms of infection are not always specific, it is difficult to expose all suspects to qualitative testing in order to confirm or rule out infection as a test. Methods: According to the scientific studies and investigations, seventy-three results of scientific articles and research  were obtained using PubMed, Medline, Research gate and Google Scholar. The research keywords used were COVID-19, coronavirus, blood parameters, and saliva. Results: This review provides a report on the changes in the blood and saliva tests of those who are infected with the COVID-19.COVID-19 is a systemic infection that has

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Publication Date
Sat Dec 01 2012
Journal Name
Iraqi Journal Of Physics
The transition rates for 232Th using the two component particle-hole state density with different corrections
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The particle-hole state densities have been calculated for 232Th in
the case of incident neutron with  ,  1 Z Z T T T T and   2 Z T T .
The finite well depth, surface effect, isospin and Pauli correction are
considered in the calculation of the state densities and then the
transition rates. The isospin correction function ( ) iso f has been
examined for different exciton configurations and at different
excitation energies up to 100 MeV. The present results are indicated
that the included corrections have more affected on transition rates
behavior for        , , and    above 30MeV excitation energy

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