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Salivary E‐cadherin as a biomarker for diagnosis and predicting grade of periodontitis
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Abstract<sec><title>Objectives

To determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.

Background

E‐cadherin is the main protein responsible for maintaining the integrity of epithelial‐barrier function. Disintegration of this protein is one of the events associated with the destructive forms of periodontal disease leading to increase concentration of E‐cadherin in the oral biofluids.

Materials and Methods

A total of 63 patients with periodontitis (case) and 35 periodontally healthy subjects (control) were included. For each patient, periodontal parameters including bleeding on probing (BOP), probing pocket depth (PPD), and clinical attachment level (CAL) were recorded. Concentration of salivary E‐cadherin was determined by ELISA. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to determine the diagnostic potentials of E‐cadherin.

Results

Level of salivary E‐cadherin was significantly higher in periodontitis cases than controls. The ROC analysis showed that salivary E‐cadherin exhibits excellent sensitivity and specificity (AUC 1.000) to differentiate periodontal health from periodontitis with a cutoff concentration equal to 1.325 ng/mL. The AUCs of E‐cadherin to differentiate grade A from grade B and C periodontitis were 0.731 (cutoff point = 1.754 ng/mL) and 0.746 (cutoff point = 1.722 ng/mL), respectively. However, the AUC of salivary E‐cadherin to differentiate grade B from grade C periodontitis was lower (0.541). Additionally, BOP and PPD were significantly and positively correlated with the concentration of salivary E‐cadherin.

Conclusion

Salivary E‐cadherin exhibited excellent sensitivity and specificity to differentiate periodontitis from a healthy periodontium. The level of accuracy of E‐cadherin was also sufficient to recognize grade A periodontitis from grade B and C periodontitis.

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
K-Nearest Neighbor Method with Principal Component Analysis for Functional Nonparametric Regression
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This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

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Publication Date
Mon Aug 01 2022
Journal Name
Water, Air And Soil Pollution
Cladophora Algae Modified with CuO Nanoparticles for Tetracycline Removal from Aqueous Solutions
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Modified algae with nano copper oxide (CuO) were used as adsorption media to remove tetracycline (TEC) from aqueous solutions. Functional groups, morphology, structure, and percentages of surfactants before and after adsorption were characterised through Fourier-transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Several variables, including pH, connection time, dosage, initial concentrations, and temperature, were controlled to obtain the optimum condition. Thermodynamic studies, adsorption isotherm, and kinetics models were examined to describe and recognise the type of interactions involved. Resultantly, the best operation conditions were at pH 7, contact time

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Publication Date
Thu Apr 20 2023
Journal Name
Fire
An Efficient Wildfire Detection System for AI-Embedded Applications Using Satellite Imagery
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

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Publication Date
Sun Jul 01 2018
Journal Name
Ieee Transactions On Intelligent Transportation Systems
Real-Time Intersection-Based Segment Aware Routing Algorithm for Urban Vehicular Networks
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High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

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Publication Date
Wed Feb 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Diagnose COVID-19 by using hybrid CNN-RNN for Chest X-ray
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<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

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Publication Date
Sun Feb 05 2017
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
STUDY THE OPTIMUM CONDITIONS FOR THE REMOVAL OF HEAVY METAL ELEMENTS FROM AQUEOUS SOLUTIONS USING CONTAMINATED BACTERIA Bacillus subtilis LOCALLY ISOLATED: STUDY THE OPTIMUM CONDITIONS FOR THE REMOVAL OF HEAVY METAL ELEMENTS FROM AQUEOUS SOLUTIONS USING CONTAMINATED BACTERIA Bacillus subtilis LOCALLY ISOLATED
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We studied the effect of certain environmental conditions for removing heavy metal elements from contaminated aqueous solutions (Cd, Cu, Pb, Fe, Zn, Ni, Cr) using the bacterium Bacillus subtilis to appoint the optimal conditions for removal ,The best optimum temperature range for two isolate was 30-35○C while the hydrogen number for the maximum mineral removal range was 6-7. The best primary mineral removal was 100 mg/L, while the maximum removal for all minerals was obtained after 6 hrs of Cu element time and the maximum removal efficiency was obtained after 24 hrs of Cu element. The results have proved that the best aeration for maximum removal was obtained at rotation speed of 150 rpm/minute. Inoculums of 5ml/100ml which contained 1

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
The role of determining the economic quantity of the demand in reducing the total costs of inventory A case study in the Institute of Technical Management / Baghdad
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ABSTRACT

The research aims to identify the role of scientific planning of inventory by determining the quantity of economic demand and the number of times of purchase and associated annual total costs to achieve a sufficient and appropriate level of inventory . The research was based on the case study methodology. Materials of increasing demand in the Institute of Technical Management and knowledge of the degree of conformity of the procurement plan with the standard indicators adopted in a scientific method ,its include economic order quantity and number of purchasing times .
one of The main results  of the research was  the existence of a large difference between the quantity of the economic purchase of ea

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Publication Date
Wed May 05 2021
Journal Name
Journal Of Petroleum Research And Studies
The Role of Chemistry of the Oil-Field Water in the Distribution of Reservoir Pressures: A Case Study of Mishrif Reservoir in the Southern Oil-Fields, Iraq
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Mishrif Formation is the main reservoir in oil-fields (North Rumaila, South Rumaila, Majnoon, Zubair and West Qurna) which located at Basrah southern Iraq. The Inductively coupled plasma-Mass spectrometer (ICP-MS) was used for the water chemistry analysis and Scanning Electron Microprobe (SEM) for the purpose of mineralogy diagnosis. A weak acidic water of salinity six-time greater than seawater plays a role in generating the formation pressure and controlling the fluid flow. The potentiometric subsurface maps were modeled and the direction of super-pressure sites that are of a great importance in the oil exploration were marked to pay attention during future drilling.

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
The effect of increasing the volume of debt on the volume of trading (applied research on a sample of private banks listed on the Iraq Stock Exchange)
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This research worked on identifying the effect of increasing the volume of indebtedness by companies listed on the Iraq Stock Exchange on the trading volume of those companies, and this research included some theoretical concepts related to both debt financing and trading volume, and it represents the research community of the joint-stock companies listed in The Iraq Stock Exchange (the banking sector). As for the research sample, it was deliberately chosen represented by companies with continuous trading without stopping, which reached 10 joint-stock companies, and the period of research was extended during the period 2011-2015, and a set of indicators and financial methods were used In measuring research v

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The impact of electronic banking transactions to increase the net revenue of the Bank of paypal in United States of America for Period ( 2010-2016 )
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Abstract

   It is clear to everyone how important it is to implement transactions electronically, as it facilitates the provision of services to beneficiaries, whether individuals or institutions, to achieve many benefits that are not exclusive to the beneficiary or the applicant, but extends to the governmental and international bodies. And the number of users has reached millions since its emergence in 1995, because the concepts of electronic transactions have great advantages for the economy in general and the banking sector in particular, so cooperation in various fields with the aim of becoming an information society has become paramount, It allows customers to pay money to any company they want t

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