A field-pilot scale slow sand filter (SSF) was constructed at Al-Rustamiya Sewage Treatment Plant (STP) in Baghdad city to investigate the removal efficiency in terms of Biochemical Oxygen Demand (BOD5), Chemical oxygen demand (COD), Total Suspended Solids (TSS) and Chloride concentrations for achieving better secondary effluent quality from this treatment plant. The SSF was designed at a 0.2 m/h filtration rate with filter area 1 m2 and total filter depth of 2.3 m. A filter sand media 0.35 mm in size and 1 m depth was supported by 0.2 m layer of gravel of size 5 mm. The secondary effluent from Al-Rustamiya STP was used as the influent to the slow sand filter. The results showed that the removal of BOD5, COD, TSS, and Chloride were 73.84%, 73.01%, 63.71% and 49.80%, respectively after 28 days of the SSF operation. The overall removal efficiency of Al-Rustamiya STP has been improved by this tertiary treatment reaching to 91.15% for BOD, 86.84% for COD, 86.55% for TSS, and 59.50% for chloride which indicated that the final effluent became acceptable to the Iraqi regulations for disposal.
Objective: The goal of this research is to load Doxorubicin (DOX) on silver nanoparticles coupled with folic acid and test their anticancer properties against breast cancer. Methods: Chitosan-Capped silver nanoparticles (CS-AgNPs) were manufactured and loaded with folic acid as well as an anticancer drug, Doxorubicin, to form CS-AgNPs-DOX-FA conjugate. AFM, FTIR, and SEM techniques were used to characterize the samples. The produced multifunctional nano-formulation served as an intrinsic drug delivery system, allowing for effective loading and targeting of chemotherapeutics on the Breast cancer (AMJ 13) cell line. Flowcytometry was used to assess therapy efficacy by measuring apoptotic induction. Results: DOX and CS-Ag
... Show Moreان تصنيع رمال مطلية بأوكسيد الحديد من خلال ترسيب الجزيئات النانوية لذلك الاوكسيد على سطوح الرمال واستخدامها في الحاجز التفاعلي النفاذ لإزالة ايونات الكادميوم والنحاس من المياه الجوفية الملوثة الهدف الرئيسي للدراسة الحالية. تم توصيف بيانات الامتزاز نتيجة تفاعل المادة المازة مع المادة الممتزة قيد الدراسة بشكل جيد من خلال نموذج لانكمير والذي كان أفضل من نموذج فراندلش. لقد وجد ان اعلى قيم لقابلية الامتزاز با
... Show MoreCoronary heart disease (CHD) is the leading cause of death in United State (U.S.). Controlling of modifiable risk factors such as smoking, hypertension (HT), diabetes mellitus (D.M.), dyslipidemia, physical inactivity & obesity will prevent other serious cardiovascular complications
Most of drinking water consuming all over the world has been treated at the water treatment plant (WTP) where raw water is abstracted from reservoirs and rivers. The turbidity removal efficiency is very important to supply safe drinking water. This study is focusing on the use of multiple linear regression (MLR) and artificial neural network (ANN) models to predict the turbidity removal efficiency of Al-Wahda WTP in Baghdad city. The measured physico-chemical parameters were used to determine their effect on turbidity removal efficiency in various processes. The suitable formulation of the ANN model is examined throughout many preparations, trials, and steps of evaluation. The predict
One of the most important problems facing the world today is the energy problem. The solution was in finding renewable energy sources such as solar energy. The solar energy applications in Iraq is facing many problems . One of the most important problems is the accumulation of dust on the solar panels surface which causes decreasing its performance sharply. In the present work, a new technique was presented by using two-axis solar tracking system to reduce the accumulated dust on the solar panel surface and compared it with the fixed solar panels which installed at tilt angles 30° and 45°. The results indicated that the maximum losses of the output power due to accumulation of dust on the fixed solar panels is about 31.4% and 23.1% res
... Show MoreAssessing water quality provides a scientific foundation for the development and management of water resources. The objective of the research is to evaluate the impact treated effluent from North Rustumiyia wastewater treatment plant (WWTP) on the quality of Diyala river. The model of the artificial neural network (ANN) and factor analysis (FA) based on Nemerow pollution index (NPI). To define important water quality parameters for North Al-Rustumiyia for the line(F2), the Nemerow Pollution Index was introduced. The most important parameters of assessment of water variation quality of wastewater were the parameter used in the model: biochemical oxygen demand (BOD), chemical oxygen dem
The issue of the prisoners' rights and the way of dealing with them is not just a minor or
primary issue according to the contemporary attitudes to deal with criminals, but it is a fatal
issue that goes with the development of life and comprehension of human rights. As the
criminal is considered as a human-being who can be reformed and qualified, according to the
aims of the contemporary social service the prisoner is regarded as an idle human source who
can be reformed, treated and qualified so as to make him participate to improve his family and
society in the end.
This study aims at reconstructing the prisons bases when applying the laws of the lowest
level of treatment through the research of oppositions, atti
Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies. In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul
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