Several industrial wastewater streams may contain heavy metal ions, which must be effectively removal
before the discharge or reuse of treated waters could take place. In this paper, the removal of copper( II)
by foam flotation from dilute aqueous solutions was investigated at laboratory scale. The effects of
various parameters such as pH, collector and frother concentrations, initial copper concentration, air flow
rate, hole diameter of the gas distributor, and NaCl addition were tested in a bubble column of 6 cm inside
diameter and 120 cm height. Sodium dodecylsulfate (SDS) and Hexadecyl trimethyl ammonium bromide
(HTAB) were used as anionic and cationic surfactant, respectively. Ethanol was used as frothers and the
optimal removal conditions have been established. Successful removals about (98%) and (76%) could be
achieved for copper ions with SDS and HTAB, respectively. Copper removal reached about 80% under
the optimum conditions at low pH; at high pH it became as high as 98% probably due to the contribution
from the flotation of precipitated copper. It was found that the presence of NaCl in the solution reduced
the recoveries. Adding ethanol at 1% concentration increased the removal efficiency. From the results the
rate of flotation was found to be first order.
Eight patients (3 male and 5 female) were treated in this study by Endovenous Laser Ablation (EVLA); Mathematical models are proposed to estimate the applied laser power and to assess the recovery period. The estimations of the applied laser power and recovery period in these models will be depended mainly on the diameter of the incompetent vein. In addition, Excel Program was utilized to find the proposed models. A 1470 nm diode laser up to 15W continuous power (CW) was used in the treatment of venous ulcers by EVLA procedure. Following up by duplex ultrasound was started in the 1st week after the first session until the vein is completely closed. The present study concluded that the relationship both between
... Show MoreIn this research, the one of the most important model and widely used in many and applications is linear mixed model, which widely used to analysis the longitudinal data that characterized by the repeated measures form .where estimating linear mixed model by using two methods (parametric and nonparametric) and used to estimate the conditional mean and marginal mean in linear mixed model ,A comparison between number of models is made to get the best model that will represent the mean wind speed in Iraq.The application is concerned with 8 meteorological stations in Iraq that we selected randomly and then we take a monthly data about wind speed over ten years Then average it over each month in corresponding year, so we g
... Show MoreIn all applications and specially in real time applications, image processing and compression plays in modern life a very important part in both storage and transmission over internet for example, but finding orthogonal matrices as a filter or transform in different sizes is very complex and importance to using in different applications like image processing and communications systems, at present, new method to find orthogonal matrices as transform filter then used for Mixed Transforms Generated by using a technique so-called Tensor Product based for Data Processing, these techniques are developed and utilized. Our aims at this paper are to evaluate and analyze this new mixed technique in Image Compression using the Discrete Wavelet Transfo
... Show MoreThe aesthetic and technical expertise help in producing the artistic work and achieving results in aesthetic formulations that reflect the aesthetic and expressive dimensions and the reflective dimensions of the pottery, surpassing its traditions, asserting its active presence in life, cherishing it even when it breaks or get damaged by employing techniques that are originated from the Japanese environment.
The research problem is to study how ( Kintsugi) technique and similar techniques are used to create new rebirths of pottery piec
... Show MoreThis paper is concerned with combining two different transforms to present a new joint transform FHET and its inverse transform IFHET. Also, the most important property of FHET was concluded and proved, which is called the finite Hankel – Elzaki transforms of the Bessel differential operator property, this property was discussed for two different boundary conditions, Dirichlet and Robin. Where the importance of this property is shown by solving axisymmetric partial differential equations and transitioning to an algebraic equation directly. Also, the joint Finite Hankel-Elzaki transform method was applied in solving a mathematical-physical problem, which is the Hotdog Problem. A steady state which does not depend on time was discussed f
... Show MoreIdentifying phenolic compounds in some genera belonging in the Amaranthaceae family by HPLC technique
The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T
... Show MoreIn this paper we use Bernstein polynomials for deriving the modified Simpson's 3/8 , and the composite modified Simpson's 3/8 to solve one dimensional linear Volterra integral equations of the second kind , and we find that the solution computed by this procedure is very close to exact solution.
Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
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