ABSTRACT: BACKGROUND: The main goal of facelift surgery is to reduce the effect of aging by reposition of face soft tissue in to more youthful orientation. There are many methods for SMAS plication which had different design and vector of pull. AIM OF STUDY: To evaluate the effectiveness and longitivity of 7 shaped SMAS plication in facelift. PATIENT AND METHODS: From January 2020 to march 2021, 10 female patients with age (45-60) years were presented with facial sagging, those patients were subjected to subcutaneous facelift with 7 shaped SMAS plication with fat greft in Al-Shaheed Ghazi Al-Harri Hospital and Baghdad burn medical center at Baghdad medical complex. RESULTS: The average follow up period was 6 to 12 months. The mean operative time was 1 hour and 30 minutes. Additional facial procedures were later done which including: fat injection (all patients), brow lift (one patient), facial scar subcision with fat grafting (one patient) and sub mental liposuction with platysma plication (2 patient). All of our patients demonstrate high level of subjective satisfaction with quick recovery with no major or minor complications CONCLUSION: The subcutaneous facelift with 7 shaped SMAS plication is simple to learn with high patients satisfaction and long lasting result.
The current study deals with host-guest complex formation between cucurbit [7] urils as host and lansoprazole as guesti using PM3 (semi empirical molecules orbital calculations) also DFT calculations. In this complex, the formation of hydrogen bonding may be occurred through portal oxygen atoms(O2) of cucurbit [7] urils and amine groups (NH 2 )of the drug. The energies of HOMO and LUMO orbital’s have been computed for the host guest complex and its components. The result of the stabilization energy explained a complex formation.
Background: Periodontal diseases are inflammatory disorders caused by the accumulation of oral biofilm and the host response to this accumulation which characterized by exaggerated leukocytes and neutrophils attraction to the sites of inflammation by chemoattractants which are a very important part of the pathogenesis of periodontal diseases. This study aimed to determine and compare the clinical periodontal parameters and the leukocyte cell types in the peripheral blood between patients with gingivitis and periodontitis with different severities compared to healthy controls. Materials and methods: This study included 150 male subjects aged between 35-50 years. They were divided into three groups: gingivitis group (n=30), periodontitis p
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreThere are many techniques for face recognition which compare the desired face image with a set of faces images stored in a database. Most of these techniques fail if faces images are exposed to high-density noise. Therefore, it is necessary to find a robust method to recognize the corrupted face image with a high density noise. In this work, face recognition algorithm was suggested by using the combination of de-noising filter and PCA. Many studies have shown that PCA has ability to solve the problem of noisy images and dimensionality reduction. However, in cases where faces images are exposed to high noise, the work of PCA in removing noise is useless, therefore adding a strong filter will help to im
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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