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Early detection of periodontitis among young adult cigarette smokers and non-smokers using cone beam computed tomography
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Background: Periodontitis is an inflammatory disease that affects the supporting tissues of the teeth; Smoking is an important risk factor for periodontitis induces alveolar bone loss and cause an imbalance between bone resorption and bone deposition. The purpose of this study is to detect and compare the presence of incipient periodontitis among young smokers and non-smokers by measuring the distance between cement-enamel junction and alveolar crest (CEJ-Ac) using Cone Beam Computed Tomography (CBCT). Material and methods: The total sample composed of fifty two participants, thirty one smokers and twenty one non-smokers (age range 14-22 years). Periodontal parameters: plaque index (PLI), gingival index (GI) were recorded for all teeth except the third molar while the radiographic analysis using CBCT was recorded on the Ramfjord teeth, the unit of measurement was from cement-enamel junction to alveolar crest distance (CEJ-Ac distance) per site in millimeters. Results: The results obtained were a non significant difference for PLI, a significant difference of mean of GI between young smokers and non smokers. There was a highly significant difference in the general mean of CEJ-Ac distance between both groups. There was a significant difference between maxillary and mandibular teeth, a non significant difference between right and left sides among young smokers and non smokers. Conclusion: The CBCT device plays an important role in detection the incipient form of periodontitis among young smokers and non-smokers, so we concluded that there is a highly significant difference in the general mean CEJ-Ac distance between young smokers and non smokers with increase distance in the maxillary teeth than that in the mandibular teeth.

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Publication Date
Thu May 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Numerical Study of Crack Effect on Frequency of Simple Supported Beam
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In this research the natural frequency of a cracked simple supported beam (the crack is in many places and in different depths) is investigated analytically, experimentally and numerically by ANSYS program, and the results are compared. The beam is made of iron with dimensions of L*W*H= (0.84*0.02* 0.02m), and density = 7680kg/m3, E=200Gpa. A comparison made between analytical results from ANSYS with experimental results, where the biggest error percentage is about (7.2 %) in crack position (42 cm) and (6 mm) depth. Between Rayleigh method with experimental results the biggest error percentage is about (6.4 %) for the same crack position and depth. From the error percentages it could be concluded that the Rayleigh method gives

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Publication Date
Thu May 15 2025
Journal Name
Journal Of Animal Health And Production
Functional and Histological Study of Liver in Adult Rats Treated with Different Doses of Melatonin
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his study aimed to evaluate the effects of different doses of melatonin on liver function in adult rats. Eighteen Wistar adult albino rats (Rattus norvegicus), approximately 13–16 weeks old and weighing 230 ± 10 g, were randomly divided into three groups (n=6 per group) and treated orally for 30 days as follows: Group A1 received 10 mg/kg body weight (B.W) of melatonin; Group A2 received 20 mg/kg B.W of melatonin; and the control group (Group A) received distilled water. At the end of the treatment period, blood samples were collected via cardiac puncture, and serum was separated for biochemical analysis. Parameters assessed included oxidative stress markers (malondialdehyde (MDA), reduced glutathione (GSH)) and liver enzymes (aspa

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Non-linear support vector machine classification models using kernel tricks with applications
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The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

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Publication Date
Sat Jun 30 2007
Journal Name
Al-kindy College Medical Journal
Early Laparoscopic Versus Open Cholecystectomy for Acute Cholecystitis
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Background: Acute cholecystitis is common surgical
problem, which was treated previously by conservative
treatment .Later early open has been introduced as an
alternative to interval for treatment of acute cholecystitis.
Early open was found to be a safe, successful with
comparable postoperative complication rate. With the
advent of laparoscopy laparoscopic have been used for
chronic cholecystitis and became the first line of
treatment. New reports have shown that laparoscopic can
be used as an alternative to open for surgical treatment of
acute cholecystitis.
Objectives: to compare the success, safety of early
laparoscopic versus early open as a primary treatment of
acute cholecystitis.
Methods:

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Heating and Melting Model Induced by Laser Beam in Solid Material
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An analytical method and a two-dimensional finite element model for treating the problem of laser heating and melting has been applied to aluminum 2519T87and stainless steel 304. The time needed to melt and vaporize and the effects of laser power density on the melt depth for two metals are also obtained. In addition, the depth profile and time evolution of the temperature before melting and after melting are given, in which a discontinuity in the temperature gradient is obviously observed due to the latent heat of fusion and the increment in thermal conductivity in solid phase. The analytical results that induced by  laser irradiation is in good agreement with numerical results.

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
Big data analysis by using one covariate at a time multiple testing (Ocmt) method: Early school dropout in iraq
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Publication Date
Fri Feb 13 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Effect of Periodontal Therapy on Serum and Salivary Interleukin-2 Levels in Chronic Periodontitis
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Background: Interleukine-2 is a multifunctional cytokine, considered a central regulator of host resistance against a variety of pathogens and has been recently demonstrated to exert an active role in the pathogenesis of periodontal diseases. The purpose of this study was to evaluate the effect of scaling and root planning on level of IL-2 in serum and saliva of patients with chronic generalized periodontitis, in relation to clinical parameters. Materials and Methods: A total of 50 subjects were enrolled, of which 25 had chronic generalized periodontitis and 25 periodontally healthy subjects as control. The clinical parameters included: gingival index, pocket probing depth, clinical attachment level and bleeding on probing. The level of

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Publication Date
Fri Dec 22 2017
Journal Name
Pakistan Journal Of Biotechnology
THE ROLE OF HLA-DRB 1 ALLELE IN HYPOTHYROID PATIENTS WITH AND WITHOUT PERIODONTITIS
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Hypothyroidism is a frequent disorder in the general population, especially among women, is defined as adeficiency of thyroid activity that results from insufficient production or action of thyroid hormones leading to a totaldecrease of metabolic. Human leukocyte antigen is the most polymorphic genetic system in man. Genes of this regioninfluence susceptibility to certain diseases.Objectives: The purpose of the present study is to investigate the role of HLA-DRB1 genotyping in hypothyroidpatients with and without periodontitis. Sixty hypothyroid patients 30 of patients were with periodontitis and 30without periodontitis compare with 30 healthy subjects as control enrolled in this study. DNA was extracted fromblood samples, then HLA- genotyp

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