Background: Type two diabetic patients have higher risk of cardiovascular and periodontal disease. Furthermore, patients with more severe periodontal disease have higher incidence of cardiovascular disease. This study aimed to assess the association between periodontal health status and the risk of vascular disease in type 2 diabetic patients. Materials and Methods: One hundred type 2 diabetes mellitus patients and fifty apparently healthy males were enrolled in this study. Oral examinations conducted were; plaque Index, calculus index, gingival index, probing pocket depth, and clinical attachment level. For the assessment of vascular risk, arterial stiffness index was used. Results: According to arterial stiffness index, type 2 diabetic patients were categorized into two groups: Group A: type 2 diabetic patients without vascular disease risk. Group B: type 2 diabetic patients with vascular disease risk. The periodontal disease parameters including gingival index, probing pocket depth, and clinical attachment level were higher in healthy controls in comparison to diabetics and in group B in comparison to group A. The difference between group A vs. group B for probing pocket depth is of highly significant (P<0.01) and for clinical attachment level is statistically significant (P<0.05). Conclusion: The increase in severity of periodontal disease can be used as an indicator for the increase of risk for vascular disease in type 2 diabetes patients.
This paper presents a hybrid approach called Modified Full Bayesian Classifier (M-FBC) and Artificial Bee Colony (MFBC-ABC) for using it to medical diagnosis support system. The datasets are taken from Iraqi hospitals, these are for the heart diseases and the nervous system diseases. The M-FBC is depended on common structure known as naïve Bayes. The structure for network is represented by D-separated for structure's variables. Each variable has Condition Probability Tables (CPTs) and each table for disease has Probability. The ABC is easy technique for implementation, has fewer control parameters and it could be easier than other swarm optimization algorithms, so that hybrid with other algorithms to reach the optimal structure. In the
... Show MorePoetry is regarded an interesting area of inquiry in linguistic studies due to its eccentric and aesthetic use of language. A lot of studies have been carried out so far for the analysis of poetry, yet few have dealt with pastoral poetry. The present research attempts to investigate the language of pastoral poetry in two different languages i.e. English and Arabic with the aim of finding similarities and differences. The data of the study consists of one English and one Arabic pastoral poems. Leech and Short's (2007) checklist is used as a model for analysis. The findings of the study reveal that there are more similarities than differences between English and Arabic pastoral poems as the poems rely on contrast
... Show MoreThe organizational culture is considered as an important topic. In this research, this topic was studied in modern paints Industries Company to assess its role in job performance and to show if there is this relationship between them or no. it is, also, attempted to measure this strength of this relationship if any. The 40 cases research sample was chosen. This sample included the chief executive, his assistants, key managers, and their assistants. The questioner consists of two sets of questions : the first set ( concerning the organizational culture) covers six variables (Physical structures , Symbols
... Show MoreThe objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost, loss etc. while maintaining an acceptable system performance in terms of limits on generators real and reactive powers, line flow limits etc. The OPF solution includes an objective function. A common objective function concerns the active power generation cost. A Linear programming method is proposed to solve the OPF problem. The Linear Programming (LP) approach transforms the nonlinear optimization problem into an iterative algorithm that in each iteration solves a linear optimization problem resulting from linearization both the objective function and constrains. A computer program, written in MATLAB environme
... Show MoreAn impressed current cathodic protection system (ICCP) requires measurements of extremely low-level quantities of its electrical characteristics. The current experimental work utilized the Adafruit INA219 sensor module for acquiring the values for voltage, current, and power of a default load, which consumes quite low power and simulates an ICCP system. The main problem is the adaptation of the INA219 sensor to the LabVIEW environment due to the absence of the library of this sensor. This work is devoted to the adaptation of the Adafruit INA219 sensor module in the LabVIEW environment through creating, developing, and successfully testing a Sub VI to be ready for employment in an ICCP system. The sensor output was monitored with an Ardui
... Show MoreBackground: The main objective was to compare the outcome of single layer interrupted extra-mucosal sutures with that of double layer suturing in the closure of colostomies.
Subjects and Methods: Sixty-seven patients with closure colostomy were assigned in a prospective randomized fashion into either single layer extra-mucosal anastomosis (Group A) or double layer anastomosis (Group B). Primary outcome measures included mean time taken for anastomosis, immediate postoperative complications, and mean duration of hospital stay. Secondary outcome measures assessed the postoperative return of bowel function, and the overall mean cost. Chi-square test and student t-test did the statistical analysis..
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... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
Our aim was to investigate the inclusion of sexual and reproductive health and rights (SRHR) topics in medical curricula and the perceived need for, feasibility of, and barriers to teaching SRHR. We distributed a survey with questions on SRHR content, and factors regulating SRHR content, to medical universities worldwide using chain referral. Associations between high SRHR content and independent variables were analyzed using unconditional linear regression or χ2 test. Text data were analyzed by thematic analysis. We collected data from 219 respondents, 143 universities and 54 countries. Clinical SRHR topics such as safe pregnancy and childbirth (95.7%) and contraceptive methods
Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
... Show MoreThis review will focus on protein and peptide separation studies of the period 1995 to 2010. Peptide and protein analysis have developed dramatically after applying mass spectrometry (MS) technology and other related techniques, such as two-dimensional liquid chromatography and two-dimensional gel electrophoresis. Mass spectrometry involves measurements of mass-to-charge ratios of the ionized sample. High-performance liquid chromatography (HPLC) is an important technique that is usually applied before MS is conducted due to its efficient separation. Characterization of proteins provides a foundation for the fundamental understanding of biology aspects. In this review, instrumentation, principle, applications, developments, and accuracy o
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