The catalytic cracking of three feeds of extract lubricating oil, that produced as a by-product from the process of furfural extraction of lubricating oil base stock in AL-Dura refinery at different operating condition, were carried out at a fixed bed laboratory reactor. The initial boiling point for these feeds was 140 ºC for sample (1), 86 ºC for sample (2) and 80 ºC for sample (3). The catalytic cracking processes were carried out at temperature range 325-400 ºC and initially at atmospheric pressure after 30 minutes over 9.88 % HY-zeolite catalyst load. The comparison between the conversion at different operating conditions of catalytic cracking processes indicates that a high yield was obtained at 375°C, according to gasoline pr

Background: A review of articles of method in treating compound phalangeal fractures by using mini-external fixator, elaborating the anatomy, mechanics, modalities of treatment, and complications of these types of fractures. Also, it compares between different studies regarding the functional results and final outcome. External fixation of phalangeal fractures is a good method for osteo synthesis in certain situations. The simplicity of the surgical procedure and the minimal disruption of the normal bone architecture also make it appealing.Objectives: Evaluating the functional results of the use of mini-external fixator for the treatment of compound fractures of phalangeal bones of the hand.Method: Our study consists of 15 patients, 12 w

The research aims to identify how to enhance the quality of the human resources, focusing on four dimensions (efficiency, effectiveness, flexibility, and reliability), by adopting an adventure learning method that combines theoretical and applied aspects at the same time, when developing human resources and is applied using information technology, and that Through its dimensions, which are (cooperation, interaction, communication, and understanding), as the research problem indicated a clear deficiency in the cognitive perception of the mechanism of employing adventure learning dimensions in enhancing human resources quality, so the importance of research was to present treatments and proposals to reduce this problem. To achieve

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

The present work involved preparation of new substituted and unsubstituted and poly imides (1-17) using reaction of acryloyl chloride with different amides (aliphatic ,aromatic) in the presence of a suitable solvent and amount tri ethyl amine (Et3N) with heating – the structure confirmation of all polymers were proved using FT-IR,1H-NMR,C13NMR and UV spectroscopy ,thermal analysis (TG) for some polymers confirmed their thermal stabilities . Other physical properties including softening and melting points, PH and solubility of the polymers were also measured

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo