This study used deep eutectic solvent (DES) as the liquid membrane in a bulk liquid membrane system (BLM) to remove glycerol from waste cooking oil‐based biodiesel. The DES was prepared from choline chloride and tetraethylene glycol at a molar ratio of 1:5. Diethyl ether was employed as a novel strip phase for the glycerol in BLM. The effects of the DES: biodiesel ratio, stirring speed, and extraction time on the extraction and stripping efficiencies were investigated. The results showed that BLM could give better glycerol removal from biodiesel than mechanical shaking. Increasing the DES: biodiesel ratio, stirring speed, and extraction time can enhance glycerol removal from the feed phase, achieving purified biodiesel that complies with biodiesel international standards. The purified biodiesel met the ASTM D6751 and EN 14214 international standards requirement for glycerol content of less than 0.24% under the following conditions of DES: biodiesel ratio of 1:1, stirring speed of 200 rpm, and extraction time of 240 min. The transport mechanisms of glycerol in the system were postulated based on two consecutive irreversible first‐order extraction and stripping. The kinetic study shows that the extraction and stripping processes in this system could be explained by a first‐order kinetic model, as the experimental results fitted into the model showed
Membrane manufacturing system was operated using dry/wet phase inversion process. A sample of hollow fiber membrane was prepared using (17% wt PVC) polyvinyl chloride as membrane material and N, N Dimethylacetamide (DMAC) as solvent in the first run and the second run was made using (DMAC/Acetone) of ratio 3.4 w/w. Scanning electron microscope (SEM) was used to predict the structure and dimensions of hollow fiber membranes prepared. The ultrafiltration experiments were performed using soluble polymeric solute poly ethylene glycol (PEG) of molecular weight (20000 Dalton) 800 ppm solution 25 °C temperature and 1 bar pressure. The experimental results show that pure water permeation increased from 25.7 to 32.2 (L/m2.h.bar) by adding aceton
... Show MoreIn this study, polymeric ultrafiltration (UF) membranes were prepared by phase inversion method to obtain both antibacterial and organic antifouling properties. The membranes were cast from a solution of polyvinylidene fluoride (PVDF) and formative silver (Ag) nanoparticles were successfully immobilized on a polymer. This was done using a solvent N, N-dimethylformamide (DMF) which is a solvent for the PVDF polymer meanwhile it is a reducing agent for silver ion. The effect of silver nanoparticles additives on the performance of polymeric ultrafiltration membrane was verified. Chemical composition and morphology of the surfaces of the membranes were characterized by Fourier transform infrared spectroscopy
... Show MoreThis study aimed to determine the measurements and classification of Schneider membrane thickness correlated to age and sex factors using cone beam computed tomography (CBCT). Methods: The study included CBCT images for 100 maxillary sinuses of 50 consecutive patients, and the thickness of the maxillary sinus membrane (Schneiderian membrane) was measured in coronal view from the lowest point in the floor of the maxillary sinus to the highest point. The thickness of the Schneiderian membrane was classified into 4 types. Results: The study result revealed that out of the total cases, 45% of sinus membranes were classified as type 2, while only 10% were classified as type 4. The most frequent type of membrane thickness diagnosed in the age gro
... Show MoreThis study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (
Breast cancer is highlighted in recent research as one of the most prevalent types of cancer. Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. Grading breast cancer properly, especially evaluating nuclear atypia, is difficult owing to faults and inconsistencies in slide preparation and the intricate nature of tissue patterns. This work explores the capability of deep learning to extract characteristics from histopathology photos of breast cancer. The research introduces a new method called SMOTE-based Convolut
... Show MoreBinary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin
... Show MoreLeap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F
... Show MoreThe virtual decomposition control (VDC) is an efficient tool suitable to deal with the full-dynamics-based control problem of complex robots. However, the regressor-based adaptive control used by VDC to control every subsystem and to estimate the unknown parameters demands specific knowledge about the system physics. Therefore, in this paper, we focus on reorganizing the equation of the VDC for a serial chain manipulator using the adaptive function approximation technique (FAT) without needing specific system physics. The dynamic matrices of the dynamic equation of every subsystem (e.g. link and joint) are approximated by orthogonal functions due to the minimum approximation errors produced. The contr