Abstract Rasha Hameid Jehad Baghdad University Background: The high reactivity of hydrogen peroxide used in bleaching agents have raised important questions on their potential adverse effects on physical properties of restorative materials. The purpose of this in vitro study was to evaluate the effect of in-office bleaching agents on the microhardness of a new Silorane-based restorative material in comparison to methacrylate-based restorative material. Materials and method: Forty specimens of Filtek™ P90 (3M ESPE,USA) and Filtek™ Supreme XT (3M ESPE, USA) of (8mm diameter and 3m height) were prepared. All specimens were polished with Sof-Lex disks (3M ESPE, USA). All samples were rinsed and stored in incubator 37˚C for 24 hours in DDW. Ten sample of each material were subjected to 37.5% hydrogen peroxide gel (Pola office +, SDI)for 8 minutes while exposed to light curing device, this step was repeated three times for 3 weeks. While the other ten samples for each material was served as control. All specimens were subjected to microhardness test using digital microhardness tester to determine the VHN (Vickers Hardness Number) Results : The Filtek™ P90 exhibited higher microhardness value than Filtek™ Supreme XT. After hydrogen peroxide treatment, both types of composites exhibited low microhardness values but still Filtek™ P90 is harder than Filtek™ Supreme XT. Conclusion : In-office hydrogen peroxide bleaching agent resulted in reduction in microhardness values for both composite materials. Silorane- based composite is more affected by the bleaching agent than methacrylate-based composite.
Background: obesity is a major global health problem with more than 200 million obese men and almost 300 million obese women. Melatonin is a well-known molecule for its involvement in circadian rhythm regulation and has multiple pathological actions including control of appetite, sleep wake cycle and metabolic syndrome.
Aim: to estimate the effect of melatonin supplements on obese patients on a calorie restricted diet in comparison to patients on lifestyle measures only in the form of weight loss, waist circumference and sleep quality.
Subjects and Method: one hundred patients with body mass index > 24 were collected, fifty patients were starte
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The introduction of concrete damage plasticity material models has significantly improved the accuracy with which the concrete structural elements can be predicted in terms of their structural response. Research into this method's accuracy in analyzing complex concrete forms has been limited. A damage model combined with a plasticity model, based on continuum damage mechanics, is recommended for effectively predicting and simulating concrete behaviour. The damage parameters, such as compressive and tensile damages, can be defined to simulate concrete behavior in a damaged-plasticity model accurately. This research aims to propose an analytical model for assessing concrete compressive damage based on stiffness deterioration. The prop
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Software Defined Network (SDN) is a new technology that separate the control plane from the data plane. SDN provides a choice in automation and programmability faster than traditional network. It supports the Quality of Service (QoS) for video surveillance application. One of most significant issues in video surveillance is how to find the best path for routing the packets between the source (IP cameras) and destination (monitoring center). The video surveillance system requires fast transmission and reliable delivery and high QoS. To improve the QoS and to achieve the optimal path, the SDN architecture is used in this paper. In addition, different routing algorithms are used with different steps. First, we eva
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The key objective of the study is to understand the best processes that are currently used in managing talent in Australian higher education (AHE) and design a quantitative measurement of talent management processes (TMPs) for the higher education (HE) sector.
The three qualitative multi-method studies that are commonly used in empirical studies, namely, brainstorming, focus group discussions and semi-structured individual interviews were considered. Twenty
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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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