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Salivary lactate dehydrogenase and salivary total protein as potential biomarkers for screening periodontal disease
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Abstract Background: Timely diagnosis of periodontal disease is crucial for restoring healthy periodontal tissue and improving patients’ prognosis. There is a growing interest in using salivary biomarkers as a noninvasive screening tool for periodontal disease. This study aimed to investigate the diagnostic efficacy of two salivary biomarkers, lactate dehydrogenase (LDH) and total protein, for periodontal disease by assessing their sensitivity in relation to clinical periodontal parameters. Furthermore, the study aimed to explore the impact of systemic disease, age, and sex on the accuracy of these biomarkers in the diagnosis of periodontal health. Materials and methods: A total of 145 participants were categorized into three groups based on their basic periodontal examination index, with 20 in the periodontally healthy group, 50 in the gingivitis group, and 75 in the periodontitis group. Salivary LDH was measured using the rate of nicotinamide adenine dinucleotide (NADH) oxidation, to measure the kinetics of LDH activity, while total protein was measured using the Lowry method. Descriptive and analytical statistical analyses were performed to examine the associations between the variables and biomarkers. Results: The results of the study demonstrated that salivary LDH was 72% sensitive, while salivary total protein was 78% sensitive in correlation to clinical periodontal parameters. The accuracy of the test was not influenced by sex, but age had a significant effect on both biomarkers, particularly LDH. Systemic disease was another factor that significantly affected the accuracy of the test. Conclusions: Although salivary LDH and total protein show promise as biomarkers for screening periodontal disease, their interpretation may be impacted by age and systemic disease.

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Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Modeling the trend of Iraqi GDP for 1970-2020
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The study of economic growth indicators is of fundamental importance in estimating the effectiveness of economic development plans, as well as the great role it plays in determining appropriate economic policies in order to optimally use the factors that lead to the dynamics of growth in Iraq, especially during a certain period of time. The gross domestic product (GDP) at current prices), which is considered a part of the national accounts, which is considered as an integrated dynamic of statistics that produces in front of policy makers the possibility of determining whether the economy is witnessing a state of expansion or evaluating economic activity and its efficiency in order to reach the size of the overall economy. The research aims

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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi National Journal Of Nursing Specialties
Spiritual Coping Strategies for Patients with Chronic Renal Failure
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Abstract:
Objectives: This study aims to (1) find out the association between patients' age, years of getting the disease, and their spiritual coping ability, and (2) investigate the differences in illness perception and spiritual coping ability between gender groups, level of education groups, monthly income groups, residence groups and satisfaction with health services groups.
Methodology
A descriptive correlational design is used in this study. The study sample includes a convenience sample of (158) patients with chronic kidney failure.
The study instrument consists of two parts; the first one focuses on participants’ sociodemographic characteristics, and the second part deals with participants’ spiritual coping by us

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Publication Date
Mon Apr 01 2013
Journal Name
Journal Of Mathematical Analysis And Applications
Strong duality for generalized monotropic programming in infinite dimensions
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Publication Date
Sat Aug 21 2021
Journal Name
Electronics
An Efficient Distributed Elliptic Positioning for Underground Remote Sensing
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Remote surveying of unknown bound geometries, such as the mapping of underground water supplies and tunnels, remains a challenging task. The obstacles and absorption in media make the long-distance telecommunication and localization process inefficient due to mobile sensors’ power limitations. This work develops a new short-range sequential localization approach to reduce the required amount of signal transmission power. The developed algorithm is based on a sequential localization process that can utilize a multitude of randomly distributed wireless sensors while only employing several anchors in the process. Time delay elliptic and frequency range techniques are employed in developing the proposed algebraic closed-form solution.

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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of The College Of Education For Women
The Quantitative Analysis for Road networks in Karbala Governorate
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The road networks is considered to be one of the determinants that controls to specify the areas of human activities, which it depend on to specify the arrival cost , in addition it is useful to achieve the connectivity for interaction and human activities , and shorten the distance and time between the population and places of service. The density of the road network in any space directly affected by the density of population and the type of economic activities and administrative functions performed by the space. On this basis, the subject of this study is reflected in the quantitative analysis of the roads network in the Governorate of Karbala. The study consists the quantitative analysis for the roads network and the Urban Nodes in th

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Block-Iterative Frequency-Domain Equalizations for SC-IDMA Systems
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In wireless broadband communications using single-carrier interleave division multiple access (SC-IDMA) systems, efficient multiuser detection (MUD) classes that make use of joint hybrid decision feedback equalization (HDFE)/ frequency decision-feedback equalization (FDFE) and interference cancellation (IC) techniques, are proposed in conjunction with channel coding to deal with several users accessing the multipath fading channels. In FDFE-IDMA, the feedforward (FF) and feedback (FB) filtering operations of FDFE, which use to remove intersymbol interference (ISI), are implemented by Fast Fourier Transforms (FFTs), while in HDFE-IDMA the only FF filter is implemented by FFTs. Further, the parameters involved in the FDFE/

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Publication Date
Sat Mar 01 2025
Journal Name
Al-khwarizmi Engineering Journal
Deep-Learning-Based Mobile Application for Detecting COVID-19
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Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

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Publication Date
Mon Aug 28 2023
Journal Name
Cureus
The Enigma of the Impervious Nobel Prize for Neurosurgeons
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Publication Date
Thu Sep 01 2022
Journal Name
Journal Of Engineering
Methods for Removing Dyes from Polluted Water; A Review
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Most of the water pollutants with dyes are leftovers from industries, including textiles, wool and others. There are many ways to remove dyes such as sorption, oxidation, coagulation, filtration, and biodegradation, Chlorination, ozonation, chemical precipitation, adsorption, electrochemical processes, membrane approaches, and biological treatment are among the most widely used technologies for removing colors from wastewater. Dyes are divided into two types: natural dyes and synthetic dyes.

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Publication Date
Thu May 28 2020
Journal Name
Applied Sciences
THz-TDS for Detecting Glycol Contamination in Engine Oil
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There continues to be a need for an in-situ sensor system to monitor the engine oil of internal combustion engines. Engine oil needs to be monitored for contaminants and depletion of additives. While various sensor systems have been designed and evaluated, there is still a need to develop and evaluate new sensing technologies. This study evaluated Terahertz time-domain spectroscopy (THz-TDS) for the identification and estimation of the glycol contamination of automotive engine oil. Glycol contamination is a result of a gasket or seal leak allowing coolant to enter an engine and mix with the engine oil. An engine oil intended for use in both diesel and gasoline engines was obtained. Fresh engine oil samples were contaminated with fou

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