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The relation of salivary glucose with dental caries and Mutans Streptococci among type1 diabetic mellitus patients aged 18-22 years
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Background: Diabetic is a chronic systemic disorder of glucose metabolism. That could be diagnosed using fasting and/or random plasma glucose and Glycated Haemoglobin (HbA1c). Several biochemical and microbial alterations of saliva could affect dental caries occurrence and severity among diabetic patients. The aim of the present study was to assess the relation of salivary glucose with severity of dental caries and Mutans Streptococci, among uncontrolled and controlled diabetic groups in comparison with non-diabetic control group. Materials and Methods: The total sample composed of adults aged (18-22) years. Divided into 25 uncontrolled diabetic patients (HbA1c > 7), 25 controlled diabetic patients (HbA1c ≤ 7), in addition to 25 non-diabetic healthy looking individuals. Fasting blood sugar was determined for the diabetic patients. The diagnosis and recording of dental caries was according to severity of dental caries lesion through the application of D1_4MFS (Manji et al, 1989) and stimulated salivary samples were collected under standardized condition (Tenovuo and Lagerlöf, 1994). Salivary glucose was estimated using spectrophotometric analysis. Viable count of mutans streptococci (on Mitis- Salivarius Bacitracin Agar) was determined. Results: salivary glucose among uncontrolled diabetic group and controlled diabetic group were highly significant higher than control group (p0.05). The correlation between salivary glucose and Mutans Streptococci among three groups was highly significant in positive direction (p<0.01). Conclusion: There are significant correlations between salivary glucose, severity of dental caries and mutans streptococci in uncontrolled diabetic group.

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
The Organizational Climate Development in the Light of Job Stress Treatment: A Field Study in Governmental Sheltered Accommodation Houses in the Ministry of Labour and Social Affairs
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        Job stress is considered one of the most important obstacles that may appear in the work field. In order to deal with the obstacles and challenges , the idea to deal with job stress has come to address job stress as one of the most important trends that enable organizations to face those challenges through focusing on the role of job stress and the organizational climate of the organization.

       The research deals with two variables: the job stress as an independent variable, and the organizational climate as a dependent one. Each variable includes five sub-dimensions. These dimensions have been involved in an interaction to form

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Publication Date
Mon Dec 21 2020
Journal Name
2020 Emerging Technology In Computing, Communication And Electronics (etcce)
An Integrated Grey Wolf Optimizer with Nelder-Mead Method for Workflow Scheduling Problem
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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
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A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

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Publication Date
Wed Dec 01 2010
Journal Name
Iraqi Journal Of Physics
Particle-Hole State Density Calculations with Non-Equidistant Spacing Model: I. Basic Derivation
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The basic analytical formula for particle-hole state densities is derived based on the non-Equidistant Spacing Model (non-ESM) for the single-particle level density (s.p.l.d.) dependence on particle excitation energy u. Two methods are illustrated in this work, the first depends on Taylor series expansion of the s.p.l.d. about u, while the second uses direct analytical derivation of the state density formula. This treatment is applied for a system composing from one kind of fermions and for uncorrected physical system. The important corrections due to Pauli blocking was added to the present formula. Analytical comparisons with the standard formulae for ESM are made and it is shown that the solution reduces to earlier formulae providing m

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Publication Date
Tue Jun 21 2022
Journal Name
Azerbaijan Medical Journal
Factors contributed to dehiscent uterine scar in women with previous one cesarean section
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Publication Date
Sun Jan 01 2017
Journal Name
Iec2017 Proceedings Book
Improving TF-IDF with Singular Value Decomposition (SVD) for Feature Extraction on Twitter
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Publication Date
Mon Jun 11 2018
Journal Name
Internationaljournalofresearchinpharmaceuticalsciences
Treatment satisfaction with disease-modifying therapy in relapsing-remit-tingmultiple sclerosis in Iraq
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Multiplesclerosis(MS)isachronic,inflammatory,immune-mediateddiseaseof the central nervous system (CNS). More than 2 million people worldwidehave MS. The goal of the present study was to compare Iraqi patients' treat-ment satisfaction with three different disease-modifying therapies (DMTs),administeredorally,subcutaneously,andbyslowinfusion;namely,fin-golimod, interferon beta-1b (IFNβ-1b), and natalizumab, respectively. Aswell as to assess the individual differences among these therapies about theireffectiveness, convenience and global satisfaction also to assess the role ofcertain predictors on treatment satisfaction. Patient satisfaction with medi-cation assessed by the Treatment Satisfaction Questi

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Publication Date
Sat Aug 01 2020
Journal Name
Computational Biology And Chemistry
A graph-based multi-sample test for identifying pathways associated with cancer progression
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Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei

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Publication Date
Wed Sep 27 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Insulin Resistance in Association with Metabolic Syndrome in Wasit University Students in Iraq
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In Iraq 1.4 million of people have diabetes, the prevalence of T2DM was ranged (8.5%—13.9%), and the cluster of metabolic abnormalities has long been identified as the risk factors for type 2 diabetes and is now commonly described as metabolic syndrome/MetS. Insulin resistance takes a key role in the process of the MetS and has even been hypothesized as its underlying cause. Clinical and epidemiologic studies also indicate that obesity and life style habit might be correlated with IR. This study examined the relationship between IR and MetS in a sample of young, healthy university students in Iraq. It discovered that the severity of IR is positively correlated with the clustering of MetS risk factors in Iraqi students, suggesting

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm with Gene Ontology-Aware Crossover Operator for Protein Complex Detection
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     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

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