Background: Orthodontic mini-implants are increasingly used in orthodontics and the bone density is a very important factor in stabilization and success of mini-implant. The aim of this study was to observe the relationship among maximum bite force (MBF); body mass index (BMI); face width, height and type; and bone density in an attempt to predict bone density from these variables to eliminate the need for CT scan which have a highly hazard on patient. Materials and Methods: Computed tomographic (CT) images were obtained for 70 patients (24 males and 46 females) with age range 18-30 years. The maxillary and mandibular buccal cortical and cancellous bone densities were measured between 2nd premolar and 1st molar at two levels from the alveolar crest (3 and 6 mm). Face height and width were measured from CT. Clinically; Maximum bite force was measured on first molar region unilaterally by a digital device. The sample was divided into two groups according to the body mass index into; normal and overweight. Results: The results obtained showed that there were no statistical significant differences in MBF or bone density in both genders. Only the cortical bone density in maxilla in overweight group tended to be higher than normal BMI group. The face width and height correlated significantly negatively with MBF which correlated significantly positively with cortical bone density. Conclusions: It was concluded that a prediction of cortical bone density of preselected areas can be made from maximum bite force, body mass index and inter-zygomatic width.
The problem of the study and its significance:
Due to the increasing pressures of life continually, and constant quest behind materialism necessary and frustrations that confront us daily in general, the greater the emergence of a number of cases of disease organic roots psychological causing them because of severity of a lack of response to conventional treatments (drugs), and this is creating in patients a number of emotional disorders resulting from concern the risk of disease
That is interested psychologists and doctors searchin
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... Show MoreBackground: Assessment of function of the right side of the heart in cases of left ventricular dysfunction has been widely studied but the sensitive and specific echocardiographic parameter to be tested is still a matter of controversy. Right ventricular function is related to left ventricular function by ventricular independence so function of both should be assessed carefully. The objective of this study was to evaluate the effects of left ventricular systolic dysfunction on right ventricular systolic and diastolic functions and pulmonary pressure using conventional and tissue Doppler echocardiography. Patients and Methods: Sixty patients (39 males and 21 females) with heart failure due to left ventricular systolic dysfunction
... Show MoreDeficiencies in revenue-related accounting standards, including American accounting standards as well as international accounting standards, prompted the issuance of the International Financial Reporting Standard IFRS 15 "Revenue from contracts with customers" as part of the convergence plan between the FASB and the International Accounting Standards Board (IASB) according to the requirements of The joint venture between the two councils, whereby the standard aims to define the basis for reporting useful information to the users of the financial statements about the nature, amount, timing and uncertainty about the revenues and cash flows arising from a contract with the customer, The standard is base
... Show MoreDeep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
... Show MoreBinary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin
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