Background: Nasopharyngeal carcinoma (NPC) is one of the most challenging tumors because of their relative inaccessibility and that their spread can occur without significant symptoms with few signs, but Radiotherapy (RT) has a role in treatment of it.
Objectives: To show that RT is still the modality of choice in the treatment of NPC, to study modes of presentations, commonest histopathological types and their percentages, to show differences in the sensitivities of these types to RT and to find out a 5 year survival rate(5YSR) and its relation with lymph node involvement.
Methods: This is a retrospective study of 44 patients with NPC who were treated with routine RT from 1988-2007 at the institute of radiology and nuclear medicine. All patients were treated with megavoltage x-ray with a total dose to the primary lesion was 60-70 Grays (1 Gray = 100 Rads) so we gave 6000-7000 Rads in 6-8 weeks and 50 Grays were applied to the cervical lymphatic chain bilaterally.
Results: 10 out of 44 patients treated have survived more than 5 years (with a 5YSR of 22.7%). In this series of cases, the 5- year overall survival rate is: 60% with stage I, 33.3% with stage II, 28.5% with stage III and 13.7% with stage IV. But, it should be noted that most of them were advanced with stages III and IV accounting for 36 patients i.e 81.8%.
Conclusion: Radiotherapy (RT) is the modality of choice in the treatment of NPC and we must irradiate areas of probable spread with the primary lesion because spread can occur without significant signs and symptoms .The most common histopathological type is undifferentiated carcinoma which is more sensitive to RT than squamous cell carcinoma (scc) or other types of carcinoma.
Also we see that stages III and IV NPC (advanced) comprises high number of the total and the 5-YSR decreases as the patient advances from stage I to stage IV, therefore, early detection and diagnosis is very important.
During 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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During 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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When laser light incident on biological tissue, it is either reflected from the
surface of the tissue (e.g. the skin) or scattered inside the tissue or absorbed .The laser light will be
absorbed by water, hemoglobin and melanin. Absorption is also highly dependent on wave-length of
laser radiation. The absorbed light is converted into kinetic energy leading to laser effect that when
appropriately applied can produce reaction ranging from incision, vaporization to coagulation. Aim of
the study: To evaluate the efficiency of diode Laser 810 ± 20nm in treatment of oral lesions. Methods:
6 patients (2 females and 4 males) with different oral lesions were treated in the hospital of specialized
surgeries by the use of dio
AG Al-Ghazzi, 2009
Petroleum is one of the most important substances consumed by man at present times, a major energy source in this century, petroleum oils can cause environmental pollution during various stages of production, transportation, refining and use, petroleum hydrocarbons pollutions ranging from soil, ground water to marine environment, become an inevitable problem in the modern life, current study focused on bioremediation process of hydrocarbons contaminants that remaining in the bottom of gas cylinders and discharged to the soil. Twenty-four bacterial isolates were isolated from contaminated soils all of them gram negative bacteria, bacterial isolates screening to investigate the ability of biodegradation of hydrocarbons, these isolates
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The objective of this study is to investigate the application of advanced oxidation processes (AOPs) in the treatment of wastewater contaminated with furfural. The AOPs investigated is the homogeneous photo-Fenton (UV/H2O2/Fe+2) process. The experiments were conducted by using cylindrical stainless steel batch photo-reactor. The influence of different variables: initial concentration of H2O2 (300-1300mg/L), Fe+2(20-70mg/L), pH(2-7) and initial concentration of furfural (50-300 mg/L) and their relationship with the mineralization efficiency were studied.
Complete mineralization for the system UV/H2O2/Fe+2 was achieved at: initi
... Show MoreBreast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep
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Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th
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Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai
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