Effluent from incompetent wastewater treatment plants (WWTPs) contains a great variety of pollutants so support water treatments are essential. The present work studies the removal of phosphate species from aqueous solutions by adsorption on to spherical Calcined Sand -Clay mixture (CSCM) used a natural, local and low-cost adsorbent. Batch experiments were performed to estimate removal efficiency of phosphate. The adsorption experiments were carried out as function of pH, dose of adsorbent, initial concentration, temperature and time of adsorption. The efficient removal was accomplished for pH between 10 and 12. The experimental results also showed that the removal of phosphate by (CSCM) was rapid (the % removal 98.9%, 92%, 90%, 89% in 60 min) when the initial phosphate concentrations were at 5, 10, 15, 20 mg/l, respectively at optimum PH 10-12 and optimum dose was 5 gm/200ml. The adsorption process is time dependent. Thermodynamic studies showed that phosphate adsorption was exothermic. The effect of temperature range of 15-30 °C has been investigated. The results indicated that the temperature significantly affected phosphate adsorption on (CSCM) adsorbent. Langmuir and Freundlich isotherms models indicated that both isotherms were proper to describe the adsorption characteristics of (CSCM), with Langmuir being more fit. Adsorption capacity of phosphate had equal to 0.835 mg phosphorous/g adsorbent. The study reveal that calcined sand-clay mixture is an excellent low cost material for phosphate removal in wastewater treatment process .
One of the most important techniques for preparing nanoparticle material is Pulsed Laser Ablation in Liquid technique (PLAL). Carbon nanoparticles were prepared using PLAL, and the carbon target was immersed in Ultrapure water (UPW) then irradiated with Q-switched Nd:YAG laser (1064 nm) and six ns pulse duration. In this process, an Nd:YAG laser beam was focused near the carbon surface. Nanoparticles synthesized using laser irradiation were studied by observing the effects of varying incident laser pulse intensities (250, 500, 750, 1000) mJ on the particle size (20.52, 36.97, 48.72, and 61.53) nm, respectively. In addition, nanoparticles were characterized by means of the Atomic Force Microscopy (AFM) test, pH easurement
... Show MoreThe eggshell cuticle is the proteinaceous outermost layer of the eggshell which regulates water exchange and protects against entry of micro-organisms. Outer eggshell and cuticle protein was extracted from domestic chicken. The aim of the research is to find out the effect of the treated and untreated nano particles of egg shells with micro wave cold plasma on the effectiveness of E. coli (negative bacteria) that infect the skin and measure the diameter of bacterial inhibition zone, the eggshell has been prepared by a chemical method (sol gel) and measure the level of acidity and the PH is neutral. The result of Atomic Force Microscope (AFM) shows that the particles diameters become smaller with nano-particles solution than for egg
... Show MoreThis investigation presents an experimental and analytical study on the behavior of reinforced concrete deep beams before and after repair. The original beams were first loaded under two points load up to failure, then, repaired by epoxy resin and tested again. Three of the test beams contains shear reinforcement and the other two beams have no shear reinforcement. The main variable in these beams was the percentage of longitudinal steel reinforcement (0, 0.707, 1.061, and 1.414%). The main objective of this research is to investigate the possibility of restoring the full load carrying capacity of the reinforced concrete deep beam with and without shear reinforcement by using epoxy resin as the material of repair. All be
... Show MorePesticide biodegradation can be accomplished by the technique of bioremediation, which makes use of microorganisms’ ability to degrade pesticide residues. This study aimed to separate and identify imidacloprid-biodegradable from botanical fields soil of greenhouses in the Plant Protection Directorate /Ministry of Agriculture in Baghdad, which has been using imidacloprid pesticides for many years. Using high-performance liquid chromatography, residual imidacloprid concentrations in MSM medium at a concentration of 25 mg/L after 21 days were measured to identify the best degrading bacterial isolates. Isolate No.37 the best bacterial isolate was able to degrade 63% of imidacloprid. was
Leishmaniasis is endemic ofIraq in both cutaneous and visceral form. The available tools for diagnosis and detection of Leishmaniaare nonspecific and may interfere with other species. In this study, Polymerase Chain Reaction (PCR) has been used to identify Iraqi isolate of visceral leishmaniasis (MHOM/ IQ/2005/MRU15) which a previously diagnosed by classical serological tests. PCR amplificationwas carried out using species-specific primers of Leishmania donovani. Four primer pairs of mini-circle DNA and ITS-1 were used.13A/13B, which is used to identify Leishmaniaas a genus, NM12, LITSR/L5.8S and BHUL18S, were used to detect the sub species of L. donovani.The result ofPCR
... Show Moreِabstract:In this research we prepared nanofibers by electrospinning from poly (Vinyl Alcohol) /TiO2. The spectrum of the solution (Emission) was studied and found to be at 772 nm, several process parameters were such as concentration of TiO2 , and the effect of distance from nozzle tip to the grounded collector (gap distance). The result of the lower concentration of, the smaller the diameter of nanofiber is. Increasing the gap distance will affect nanofibers diameter.
In this paper the behavior of the quality of the gradient that implemented on an image as a function of noise error is presented. The cross correlation coefficient (ccc) between the derivative of the original image before and after introducing noise error shows dramatic decline compared with the corresponding images before taking derivatives. Mathematical equations have been constructed to control the relation between (ccc) and the noise parameter.
Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w
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