The current study investigated the stability and the extraction efficiency of emulsion liquid membrane (ELM) for Abamectin pesticide removal from aqueous solution. The stability was investigated in terms of droplet emulsion size distribution and emulsion breakage percent. The proposed ELM included a mixture of corn oil and kerosene (1:1) as a diluent, Span 80 (sorbitan monooleate) as a surfactant and hydrochloric acid (HCl) as a stripping agent without utilizing a carrier agent. Parameters such as homogenizer speed, surfactant concentration, emulsification time and internal to organic volume ratio (I/O) were evaluated. Results show that the lower droplet size of 0.9 µm and higher stable emulsion in terms of breakage percent of 1.12 % were formed at 5800 rpm of homogenizer speed, 4 v% of span 80 surfactant, 8 min of emulsification time and 1:1 (I/O) ratio while 86.4% of Abamectin pesticides were extracted under these conditions. Extraction kinetics and mass transfer study were also accomplished. The outcome of this study can be extended to the removal of other type of pesticides from water and wastewater.
Key words:Jasminumsambac, Volatile oil, Antioxidant.
Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
... Show MoreIn this paper, the peristaltic flow under the impact of heat transfer, rotation and induced magnetic field of a two dimensional for the Bingham plastic fluid is discussed. The coupling among of momentum with rotational, energy and the induced magnetic field equations are achieved by the perturbation approximation method and the mathematica software to solve equations that are nonlinear partial differential equations. The fluid moves in an asymmetric channel, and assumption the long wavelength and low Reynolds number, approximation are used for deriving a solution of the flow. Expression of the axial velocity, temperature, pressure gradient, induced magnetic field, magnetic force, current density are developed the eff
... Show MoreThe Boltzmann transport equation is solved by using two- terms approximation for pure gases . This method of solution is used to calculate the electron energy distribution function and electric transport parameters were evaluated in the range of E/N varying from . 172152110./510.VcmENVcm
From the results we can conclude that the electron energy distribution function of CF4 gas is nearly Maxwellian at (1,2)Td, and when E/N increase the distribution function is non Maxwellian. Behavior of electrons transport parameters is nearly from the experimental results in references. The drift velocity of electron in carbon tetraflouride is large compared with other gases
The research aims to recognize the impact of the training program based on integrating future thinking skills and classroom interaction patterns for mathematics teachers and providing their students with creative solution skills. To achieve the goal of the research, the following hypothesis was formulated: There is no statistically significant difference at the level (0.05) between the mean scores of students of mathematics teachers whose teachers trained according to the proposed training program (the experimental group) and whose teachers were not trained according to the proposed training program (the control group) in Pre-post creative solution skills test. Research sample is consisted of (31) teachers and schools were distribut
... Show MoreThe behaviour of Np-239 during the Continuous extraction and stripping was followed . Three Continuous extraction experiments were carried out . In the first experiment the extraction and stripping were carried out by using Tributyl Phosphate / treated odorless kerosene as the organic phase , while the aqueous phase was uranium and neptunium-239 dissolved in 3M HNO3 . In the second experiment irradiation of organic phase up to 30 M rad were carried out , while keeping the aqueous phase as it is in the first experiment. In the third experiment , the acidity of the aqueous phase was 1.5M instead of 3M and keeping the organic phase as it is in experiment 1. The results obtained in tables 1-3 show the possibility of
... Show MoreThe emergence of mixed matrix membranes (MMMs) or nanocomposite membranes embedded with inorganic nanoparticles (NPs) has opened up a possibility for developing different polymeric membranes with improved physicochemical properties, mechanical properties and performance for resolving environmental and energy-effective water purification. This paper presents an overview of the effects of different hydrophilic nanomaterials, including mineral nanomaterials (e.g., silicon dioxide (SiO2) and zeolite), metals oxide (e.g., copper oxide (CuO), zirconium dioxide (ZrO2), zinc oxide (ZnO), antimony tin oxide (ATO), iron (III) oxide (Fe2O3) and tungsten oxide (WOX)), two-dimensional transition (e.g., MXene), metal–organic framework (MOFs), c
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