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.
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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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 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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Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
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Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system
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Merging biometrics with cryptography has become more familiar and a great scientific field was born for researchers. Biometrics adds distinctive property to the security systems, due biometrics is unique and individual features for every person. In this study, a new method is presented for ciphering data based on fingerprint features. This research is done by addressing plaintext message based on positions of extracted minutiae from fingerprint into a generated random text file regardless the size of data. The proposed method can be explained in three scenarios. In the first scenario the message was used inside random text directly at positions of minutiae in the second scenario the message was encrypted with a choosen word before ciphering
... Show MoreBackground: The purpose of the current study was to evaluate the efficacy of a new orthodontic bonding system (Beauty Ortho Bond) involving the shear bond strength in dry and wet environments, and adhesion remnant index (ARI) scores evaluation in regard to other bonding systems (Heliosit and Resilience Orthodontic Adhesives). Materials and methods: Sixty defect free extracted premolars were randomly divided into six groups of 10 teeth each, mounted in acrylic resin, three groups for a dry environment and three for a wet one. Shear bond strength test was performed with a cross head speed of 0.5 mm/min, while surfaces of enamel and bracket-adhesive-enamel surfaces were examined with stereomicroscope For ARI scores evaluation. Data were analyz
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