Collapse of the vapor  bubble condensing  in an immiscible  is investigated for  n-pentane and n-hexane vapors condensing in cold water and n-pentane in two different compositions of glycerin- water mixture. The rise velocity and the drag coefficient of the two-phase bubble are measured.

The study's objective is to produce Nano Graphene Oxide (GO) before using it for batch adsorption to remove heavy metals (Cadmium Cd⁺², Nickel Ni⁺², and Vanadium V⁺⁵) ions from industrial wastewater. The temperature effect (20-50) °C and initial concentration effect (100-800) mg L^-1 on the adsorption process were studied. A simulation aqueous solution of the ions was used to identify the adsorption isotherms, and after the experimental data was collected, the sorption process was studied kinetically and thermodynamically. The Langmuir, Freundlich, and Temkin isotherm models were used to fit the data. The results showed that Cd, Ni, and V ions on the GO adsorbing surface matched the Langmuir mo

The study's objective is to produce Nano Graphene Oxide (GO) before using it for batch adsorption to remove heavy metals (Cadmium Cd+2, Nickel Ni+2, and Vanadium V+5) ions from industrial wastewater. The temperature effect (20-50) °C and initial concentration effect (100-800) mg L-1 on the adsorption process were studied. A simulation aqueous solution of the ions was used to identify the adsorption isotherms, and after the experimental data was collected, the sorption process was studied kinetically and thermodynamically. The Langmuir, Freundlich, and Temkin isotherm models were used to fit the data. The results showed that Cd, Ni, and V ions on the GO adsorbing surface matched the Langmuir model with correlation coefficients (R2)

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  This study is concerned with the estimation of constant  and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to es

The purpose of this research was to evaluate rice husk functionalized with Mg-Fe-layered double hydroxide (RH-Mg/Fe-LDH) as an adsorbent for the removal of meropenem antibiotic (MA) from an aqueous solution. Several batch experiments were undertaken using various conditions. Based on the results, the optimal Mg/Fe-LDH adsorbent with a pH of 9 and an M2+/M3+ ratio of 0.5 was associated with the lowest particle size (specifically. 11.1 nm). The Langmuir and Freundlich models were consistent with the experimental isotherm data (R2 was 0.984 and 0.993, respectively), and MA’s highest equilibrium adsorption capacity was 43.3 mg/g. Additionally, the second-order model was consistent with the adsorption kinetic results.

The world is confronted with the twin crisis of fossil fuel depletion and environmental degradation caused by fossil fuel usage. Biodiesel produced from renewable feedstocks such as Jatropha seed oil or animal fats by transesterification offers a solution. Although biodiesel has been produced from various vegetable oils such as Jatropha seed oil, the reaction kinetics studies are very few in literature, hence the need for this study. Jatropha curcas seed oil was extracted and analyzed to determine its free fatty acid and fatty acid composition. The oil was transesterified with methanol at a molar ratio of methanol to oil 8:1, using 1% sodium hydroxide catalyst, at different temperature

Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.

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