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Microbiological and Salivary Biomarkers Successfully Predict Site-Specific and Whole-Mouth Outcomes of Nonsurgical Periodontal Treatment
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Background/Objectives: Nonsurgical periodontal treatment (NSPT) is the gold-standard technique for treating periodontitis. However, an individual’s susceptibility or the inadequate removal of subgingival biofilms could lead to unfavorable responses to NSPT. This study aimed to assess the potential of salivary and microbiological biomarkers in predicting the site-specific and whole-mouth outcomes of NSPT. Methods: A total of 68 periodontitis patients exhibiting 1111 periodontal pockets 4 to 6 mm in depth completed the active phase of periodontal treatment. Clinical periodontal parameters, saliva, and subgingival biofilm samples were collected from each patient at baseline and three months after NSPT. A quantitative PCR assay was used to detect the presence of Fusobaterium nucleatum and Porphyromonas gingivalis in the biofilm samples. Salivary biomarkers including matrix metalloproteinase (MMP)-9, glutathione S-transferase (GST), and Annexin-1 were assayed both qualitatively (Western blot analysis) and quantitively (ELISA). Results: NSPT yielded significant improvements in all clinical parameters, including a reduction in bacterial load and decreased levels of MMP-9 together with increased concentrations of GST and Annexin-1. The binary logistic regression suggested that the overall accuracy of P. gingivalis identification, probing pocket depth, and interproximal sites was 71.1% in predicting successful site-specific outcomes. The salivary biomarker model yielded an overall accuracy of 79.4% in predicting whole-mouth outcomes following NSPT. Conclusions: At baseline, the presence of shallow periodontal pockets at interdental locations with a lower abundance of P. gingivalis is predictive of a favorable response to NSPT at the site level. Decreased salivary MMP-9 associated with increased GST and Annexin-1 levels can predict successful whole-mouth outcomes following NSPT.

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Publication Date
Mon Jul 27 2020
Journal Name
Water
Groundwater Flow-Modeling and Sensitivity Analysis in a Hyper Arid Region
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Groundwater modelling is particularly challenging in arid regions where limited water recharge is available. A fault zone will add a significant challenge to the modelling process. The Western Desert in Iraq has been chosen to implement the modelling concept and calculate the model sensitivity to the changes in aquifer hydraulic properties and calibration by researching 102 observations and irrigation wells. MODFLOW-NWT, which is a Newtonian formulation for MODFLOW-2005 approaches, have been used in this study. Further, the simulation run has been implemented using the Upstream-Weighting package (UPW) to treat the dry cells. The results show sensitivity to the change of the Kx value for the major groundwater discharge flow. Only abo

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Publication Date
Sat Dec 01 2018
Journal Name
Fuel
Biodiesel from batch and continuous oleic acid esterification using zeolite catalysts
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Publication Date
Wed Aug 26 2020
Journal Name
Journal Of Engineering
Groundwater Simulation and Wells Distribution at Qazaniyah City in Diyala Governorate
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In recent years, there is more interest in water sources availability, including groundwater due to an increase in demand for water because of the increasing population in the world, and the water recedes due to climate change also. Therefore, the study of groundwater has required more attention. The aim of the present study is to establish a MODFLOW model in the groundwater modeling system software to simulate the movement of groundwater in the Turssaq alluvial fan which is located in the Qazaniyah city, east of Diyala Governorate. The solid model was used to define the aquifer in the study area. Using the GIS software, mapping and preparing the data needed to create a conceptual model were carried out. The data of the

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
On Faintly θ- Semi-Continuous and Faintly δ-Semi-Continuous Functions
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      Faintly continuous (FC) functions, entitled faintly S-continuous and faintly δS-continuous functions have been introduced and investigated via a -open and -open sets. Several characterizations and properties of faintly S-continuous and faintly -Continuous functions were obtained. In addition, relationships between faintly s- Continuous and faintly S-continuous function and other forms of FC function were investigated. Also, it is shown that every faintly  S-continuous is weakly S-continuous. The Convers is shown to be satisfied only if the co-domain of the function is almost regular.

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Publication Date
Tue Jun 01 2021
Journal Name
Ieee Systems Journal
Intelligent Traffic Management and Load Balance Based on Spike ISDN-IoT
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An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Regression shrinkage and selection variables via an adaptive elastic net model
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Abstract<p>In this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in </p> ... Show More
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Publication Date
Wed Jul 01 2020
Journal Name
International Journal Of Drug Delivery Technology
Gold nanoparticle: Synthesis, functionalization, enhancement, drug delivery and therapy: A review
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Publication Date
Mon Jan 01 2024
Journal Name
Explainable Artificial Intelligence In The Digital Sustainability Administration
Artificial Intelligence and Trends Using in Sustainability Audit: A Bibliometric Analysis
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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Comparison among variable selection models and its application to health dataset
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Ontological Methodologies for Counselling Intervention: Do’a and Zikr Al-Mā’thur Corpus
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Do’a and Zikr al-Mā’thur (authentic supplications and remembrance of ALLAH ‘Azza wa Jalla) can be suggested to Muslims to help them deal with challenges or issues in life. Counselling cases affect a person’s feelings. Do’a and Zikr al-Mā’thur are often applied as a counselling intervention. Unfortunately, the authentic Do’a and Zikr al-Mā’thur are dispersed in many resources not visible to users, and the fact that not all online resources offer access to accurate Do’a and Zikr al-Mā’thur to users and the dubious Do’a and Zikr al-Mā’thur frequently credited to the Prophet (pbuh). The goal of this research is to develop an ontology

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