Background: Tumors of the oral cavity are under
estimated in general dental and medical practice,
some authors describe it as the forgetting disease,
others wondering if the attention paid to this disease
compared to its fatality (The 5-year survival rate is
about 50%) is enough for disease control? However;
this disease deserves a comprehensive assessment by
all dental and medical fields assumed to examine the
oral cavity regularly, especially otolaryngologist.
Objectives: To find out the sensitivity and specificity
of clinical examination in diagnosing oral tumors and
premalignant conditions by otolaryngologist.
Methods: Across sectional retrospective study was
conducted in the:
-study design: Cross sectional.
-settings: Ear Nose Throat (ENT)departments in
Al-kindy Teaching Hospital
and Al-Yarmouk Teaching Hospital.
On Patients attending ENT department with oral
presentation.
The outcome variables includes: The sensitivity,
specificity, positive predictive value (Pv+ve), negative
predictive value (PV-ve), and the accuracy of clinical
examination in diagnosing oral tumors and
premalignant conditions in ENT clinic.
Results: The results revealed a high sensitivity and
specificity for otolaryngologist in diagnosing
malignant conditions and premalignant lesions of the
oral cavity.
Conclusion: The study highlights the need for fixed
clinical criteria for early diagnosis of premalignant
conditions and oral tumors
In the present work, the behavior of thick-walled cylinder of elasto-plastic material (polymeric material) has been studied analytically. The study is based on modified Von-Mises yield criterion (for non metallic material). The equations of stress distribution are obtained for the cylinder under general cases of elastic expansion, plastic initiation and elastic-plastic expansion.
A computer program is developed for evaluating the stress distribution. The solution is carried out for worst boundary conditions when the cylinder is subjected to the combination of pressure load, inertia load, and temperature gradient.
The results are presente
... Show MoreAn integrated GIS-VBA (Geographical Information System – Visual Basic for Application), model is developed for selecting an optimum water harvesting dam location among an available locations in a watershed. The proposed model allows quick and precise estimation of an adopted weighted objective function for each selected location. In addition to that for each location, a different dam height is used as a nominee for optimum selection. The VBA model includes an optimization model with a weighted objective function that includes beneficiary items (positive) , such as the available storage , the dam height allowed by the site as an indicator for the potential of hydroelectric power generation , the rainfall rate as a source of water . In a
... Show MoreThis study aimed to investigate the feasibility of treatment actual potato chips processing wastewater in a continuously operated dual chambers microbial fuel cell (MFC) inoculated with anaerobic sludge. The results demonstrated significant removal of COD and suspended solids of more than 99% associated with relatively high generation of current and power densities of 612.5 mW/m3 and 1750 mA/m3, respectively at 100 Ω external resistance.
Single Point Incremental Forming (SPIF) is a forming technique of sheet material based on layered manufacturing principles. The sheet part is locally deformed through horizontal slices. The moving locus of forming tool (called as toolpath) in these slices constructed to the finished part was performed by the CNC technology. The toolpath was created directly from CAD model of final product. The forming tool is a Ball-end forming tool, which was moved along the toolpath while the edges of sheet material were clamped rigidly on fixture.
This paper presented an investigation study of thinning distribution of a conical shapes carried out by incremental forming and the validation of finite element method to evaluate the limits of the p
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat
... Show MoreTrip generation is the first phase in the travel forecasting process. It involves the estimation of the
total number of trips entering or leaving a parcel of land per time period (usually on a daily basis);
as a function of the socioeconomic, locational, and land-use characteristics of the parcel.
The objective of this study is to develop statistical models to predict trips production volumes for a
proper target year. Non-motorized trips are considered in the modeling process. Traditional method
to forecast the trip generation volume according to trip rate, based on family type is proposed in
this study. Families are classified by three characteristics of population social class, income, and
number of vehicle ownersh
The present work aims to improve the flux of forward osmosis with the use of Thin Film Composite membrane by reducing the effect of polarization on draw solution (brine solution) side.This study was conducted in two parts. The first is under the effect of polarization in which the flux and the water permeability coefficient (A) were calculated. In the second part of the study the experiments were repeated using a circulating pump at various speeds to make turbulence and reduce the effect of polarization on the brine solution side.
A model capable of predicting water permeability coefficient has been derived, and this is given by the following equations:
Z=Z0 +C.R.T/9.8(d2/D2+1) [Exp. [-9.8(d