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The Effect of Addition of Zirconium Nano Particles on Antifungal Activity and Some Properties of Soft Denture Lining Material
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Background Microorganisms and fungal growth especially Candida albicans, on soft denture lining material are the most common problem which can lead to chronic mucosal inflammation. The aim of this study was to evaluate the effect of zirconium nanoparticles into acrylic-based heat cured soft denture lining material against Candida albicans, and the amount of zirconium ion release of soft liner/ZrNPs composite. Furthermore, evaluate shear bond strength after ZrNPs addition to soft liner. Materials and methods: Zirconium nanoparticles were added into acrylic-based soft denture liner in various percentages (1%, and 1.5% by weight). Two hundred and fifty specimens were arranged and isolated into four groups as per the test to be done The antifungal activity of the soft liner/ZrNPs composite was assessed in three different periods by using two methods (viable count of C. albicans and disk-diffusion test). In two distinct periods, amount of zirconium released in artificial saliva was detected by atomic absorption spectroscopy. Instron testing machine was used to test the shear bond strength of the soft liner to the acrylic denture base material. Results: A highly significant decrease in colony forming units of C. albicans in experimental groups (1% and 1.5%ZrNPs) contrast with control group. There was no inhibition zone around any specimen of any test group. In artificial saliva there was no zirconium distinguished to be released at any incubation period. There was a highly significant increase in the mean value of shear bonding strength after incorporation of ZrNPs at 1.5% percentage into soft liner. Conclusion: The addition of ZrNPs into acrylic-based soft denture lining material helps to provide soft denture liner with antifungal properties, thus reducing the susceptibility to develop denture-induced stomatitis. There is no zirconium has been detected at any incubation period and there is increased in the shear bond strength of the soft lining material.

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Publication Date
Wed Dec 08 2021
Journal Name
Scientific Reports
Weakly Supervised Sensitive Heatmap framework to classify and localize diabetic retinopathy lesions
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Abstract<p>Vision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase may help medical doctors to make better decisions. DR is considered one of the main risks, leading to blindness. Computer-Aided Diagnosis systems play an essential role in detecting features in fundus images. Fundus images may include blood vessels, exudates, micro-aneurysm, hemorrhages, and neovascularization. In this paper, our model combines automatic detection for the diabetic retinopathy classification with localization methods depending on weakly-supervised learning. The model has four stages; in stage one, various preprocessing techniques are app</p> ... Show More
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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Steganography and Cryptography Techniques Based Secure Data Transferring Through Public Network Channel
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Attacking a transferred data over a network is frequently happened millions time a day. To address this problem, a secure scheme is proposed which is securing a transferred data over a network. The proposed scheme uses two techniques to guarantee a secure transferring for a message. The message is encrypted as a first step, and then it is hided in a video cover.  The proposed encrypting technique is RC4 stream cipher algorithm in order to increase the message's confidentiality, as well as improving the least significant bit embedding algorithm (LSB) by adding an additional layer of security. The improvement of the LSB method comes by replacing the adopted sequential selection by a random selection manner of the frames and the pixels wit

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Mining categorical Covid-19 data using chi-square and logistic regression algorithms
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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Small Horizontal Wind Turbine Design and Aerodynamic Analysis Using Q-Blade Software
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Wind energy is one of the most common and natural resources that play a huge role in energy sector, and due to the increasing demand to improve the efficiency of wind turbines and the development of the energy field, improvements have been made to design a suitable wind turbine and obtain the most energy efficiency possible from wind. In this paper, a horizontal wind turbine blade operating under low wind speed was designed using the (BEM) theory, where the design of the turbine rotor blade is a difficult task due to the calculations involved in the design process. To understand the behavior of the turbine blade, the QBlade program was used to design and simulate the turbine rotor blade during working conditions. The design variables suc

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Publication Date
Sat Jun 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Thickening Time and Compressive Strength Correlations for Bentonitic- Class "G" Cement Slurries
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Empirical equations for estimating thickening time and compressive strength of bentonitic - class "G" cement slurries were derived as a function of water to cement ratio and apparent viscosity (for any ratios). How the presence of such an equations easily extract the thickening time and compressive strength values of the oil field saves time without reference to the untreated control laboratory tests such as pressurized consistometer for thickening time test and Hydraulic Cement Mortars including water bath ( 24 hours ) for compressive strength test those may have more than one day.

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation
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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

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Publication Date
Fri Jul 01 2016
Journal Name
Composite Structures
Bond behaviour between CFRP laminates and steel members under different loading rates
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Carbon fibre reinforced polymers are widely used to strengthen steel structural elements. These structural elements are normally subjected to static, dynamic and fatigue loadings during their life-time. A number of studies have focused on the characteristics of CFRP sheets bonded to steel members under static, dynamic and fatigue loadings. However, there is a gap in understanding the bonding behaviour between CFRP laminates and steel members under impact loading. This paper shows the effect of different load rates from quasi-static to 300 × 103 mm/min on this bond. Two types of CFRP laminate, CFK 150/2000 and CFK 200/2000, were used to strengthen steel joints using Araldite 420 epoxy. The results show a significant bond strength enhancemen

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Publication Date
Sun Jun 01 2025
Journal Name
Methodsx
How mathematical models might predict desertification from global warming and dust pollutants
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Publication Date
Sat Mar 14 2020
Journal Name
Medico-legal Update,
Fasting Versus Non-Fasting in Assessing Lipid Profile and Complete Blood Picture
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