The aim of this work is to study the factors that affect the welding joint of dissimilar metals. Austenitic stainless steel-type AISI (316L) with a thickness of (2mm) was welded to carbon steel (1mm) using an MIG spot welding.  The filler metal is a welding wire of the type E80S-G (according to AWS) is used with (1.2mm) diameter and CO₂ is used as shielding gas with flow rate (7L/min) for all times was used in this work.

        The results indicate that the increase of the welding current tends to increase the size of spot weld, and also increases the sheer force.  Whereas the sheer force increased inversely with the time of welding. Furthermore, the results indicate that i

Background: Gingival crevice fluid (GCF) is a mixture of substances derived from serum, leukocytes, and structural cells of periodontium and oral bacteria. These substances possess a great potential for serving as indicators of periodontal disease and healing after therapy the main purpose of this study was to find if there is a difference in albumin concentration between healthy and diseased periodontal tissues and to compare between diseased group according to pocket depth Materials and methods: total sample composed of 60 pockets found in 35 patients all of them had no history of any systemic disease, The samples were divided in to three main group that include two diseased groups divided according to the depth of the periodontal pocket

Background: Coronary artery disease (CAD) is a major contributor to morbidity and mortality worldwide. Early-onset CAD, also known as PCAD, is a severe form of CAD associated with high mortality and a poor prognosis. Early diagnosis is crucial to reducing complications. While hsCRP is an established biomarker for CAD, kalirin is a potential novel biomarker due to its role in promoting smooth muscle proliferation and endothelial dysfunction. Objective: To evaluate the relationship between serum kalirin and hsCRP levels with the presence and severity of PCAD and to compare the diagnostic value of both biomarkers. Method: The study recruited 92 participants into two groups: the PCAD group (46) included patients with confirmed CAD by an

There is a theoretical controversy in the books of Usul al-Fiqh, in the past and the present, about whether the ruling should be attached to its reason (al-Hikmah), or its apparent and stable cause (al-Illah). Looking at the practical cases of the jurists, we found them sometimes attaching rulings to its reason, and sometimes to its cause, so there is a need to know the factors that affect their choices. By extrapolation, the researcher reached at nine factors that affect referring the ruling to its cause or to its reason in jurisprudential cases.

The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material

Background: Acne is a common disorder experienced by adolescents and persists into adulthood in approximately 12%–14% of cases with psychological and social implications of high gravity. Fractional resurfacing employs a unique mechanism of action that repairs a fraction of skin at a time. The untreated healthy skin remains intact and actually aids the repair process, promoting rapid healing with only a day or two of downtime. Aims: This study, was designed to evaluate the safety and effectiveness of fractional photothermolysis (fractionated Er: YAG laser 2940nm) in treating atrophic acne scars. Methods: 7 females and 3 males with moderate to severe atrophic acne scarring were enrolled in this study that attained private clinic for Derm

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.