An investigation was conducted to suggest relations for estimating yield and properties of the improved light lubricating oil fraction produced from furfural extraction process by using specified regression.

Mass transfer in mixer-settler has been studied. Mass transfer coefficient of continuous phase, mass transfer coefficient of dispersed phase and the overall mass transfer coefficient extraction of light lubes oil distillate fraction by furfural are calculated in addition to all physical properties of individual components and the extraction mixtures.

The effect of extraction variables were studied such as extraction temperature which ranges from 70 to 110°C and solvent to oil ratio which ranges from 1:1 to 4:1 (wt/wt

The effective surface area of drug particle is increased by a reduction in the particle size. Since dissolution takes place at the surface of the solute, the larger the surface area, the further rapid is the rate of drug dissolution. Ketoprofen     is class II type drug according to (Biopharmaceutics Classification System BCS) with low solubility and high permeability. The aim of this investigation was to increase the solubility and hence the dissolution rate by the preparation of ketoprofen     nanosuspension using solvent evaporation method. Materials like PVP K30, poloxamer 188, HPMC E5, HPMC E15, HPMC E50, Tween 80 were used as stabilizers in perpetration of differ

The new media scene reveals that the unprecedented overlap of a number of technical, economic, and political factors has made the new media a very complicated issue; and the focus of specialized and public debates about its impact on traditional means of communication and forms of social media and social relations. Then, the same scene discloses the reality of the relationship between the new and the traditional. These are the axes that will be will be discussed in this study.

<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in

Thermal decomposition of used tires was studied under atmospheric pressure and thermal heating program up to 350 °C for 110-120 min in a glass reactor. The effects of using MgO or SiO2 as catalyst in the thermal pyrolysis of tires waste on the yield ratio, reaction time, initial degree of decomposition also the contents of BTEX compounds in resulting pyrolytic oil was estimated via GC-FID. The results showed that the MgO catalyst gave a gas output in proportion of 17.063%, a liquid in a proportion of 38.245% and a solid product in proportion of 44.733%, while the SiO2 catalyst gave proportions of 14.308%, 40.161% and 45.448% for gas, liquid and solid products respectively. The results revealed that the thermal pyrolysis produced minor cont

This study investigated a novel application of forward osmosis (FO) for oilfield produced water treatment from the East Baghdad oilfield affiliated to the Midland Oil Company (Iraq). FO is a part of a zero liquid discharge system that consists of oil skimming, coagulation/flocculation, forward osmosis, and crystallization. Treatment of oilfield produced water requires systems that use a sustainable driving force to treat high-ionic-strength wastewater and have the ability to separate a wide range of contaminants. The laboratory-scale system was used to evaluate the performance of a cellulose triacetate hollow fiber CTA-HF membrane for the FO process. In this work, sodium chloride solution was used as a feed solution (FS) with a concentratio

Problem: 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

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k