Background: With the increase in composite material use in posterior teeth, the concerns about the polymerization shrinkage has increased with the concerns about the formation of marginal gaps in the oral cavity environment. New generation of adhesives called universal adhesive have been introduced to the market in order to reduce the technique sensitive bonding procedures to give the advantage of using the bonding system in any etching protocol without compromising the bonding strength. The aim of the study was to study marginal adaptation of two universal adhesives (Single bond™ Universal and Prime and Bond elect) using 3 etching techniques under thermal cycling aging. Materials and Methods: Forty-eight sound maxillary first premolar teeth were included in the study. Teeth were divided into two groups according to the universal adhesive used then each group was subdivided into 3 subgroups according to the etching protocol used. Standardized class I cavities were prepared in the teeth followed by the restoration of teeth using Filtek™ Bulk Fill Posterior Restorative composite material. After finishing and polishing, teeth were subjected to 500 thermal cycles in 55º-5ºC bath with dwell time of 30 seconds. Teeth then were examined using SEM to measure the marginal gap at 12 points. Data obtained were analyzed using one-way ANOVA and LSD test for each group and with student t-test to compare the two adhesives. Results: The result of this study the showed that etch and rinse technique showed significantly the least marginal gap width for both adhesive types. The selective etch technique showed lower gaps compared to the self-etch technique with no significant difference. The result showed that single bond universal showed significantly the least marginal gap for the all etching techniques compared to Prime and bond elect. Conclusion: The etch and rinse technique remains the most suitable technique for adhesive restoration. The type of adhesive plays an important role in adhesion.
In this work, measurements of activity concentration of naturally occurring radioactive materials (NORM) isotopes and their related hazard indices for several materials such as crude oil, sludge and water in Ahdeb oil fields in Waste governorate using high pure germanium coaxial detection technique. The average values for crude oil samples were174.72Bq/l, 43.46Bq/l, 355.07Bq/l, 264.21Bq/l, 122.52nGy/h, 0.7138, 1.1861, 0.601 mSv/y, 0.1503mSv/y and 1.8361 for Ra-226, Ac-228, K-40, Ra eq, D, H-external and H-internal respectively. According to the results; the ratio between 238U to 232Th was 4, which represents the natural ratio in the crust earth; therefore, one can be strongly suggested that the geo-stricture of the
... Show MoreThe research aimed: 1. Definition of family climate for the university students. 2. Definition of statistical significance of differences in family climate variable depending on the sex (males - females) and specialization (Scientific - humanity). 3. Definition of academic adjustment for university students. 4. Definition of correlation between climate and academic adjustment. The research sample formed of (300) male and female students by (150) male of scientific and humanitarian specialization and (150) female of scientific and humanitarian specialization randomly selected from the research community. To achieve the objectives of the research the researcher prepared a tool to measure family climate. And adopted the measure (Azzam 2010)
... Show MoreNew trends in teaching and learning theory are considered a theoretical axis
from which came the background that depends on any source, or practice sample or
teaching plane, accuracy and simplicity prevent the development of the teaching
process. Many attempts have come to scene to illuminate the teaching background,
but they have not exceed those remarkable patterns and methods. Thus, the
appearance of the teaching theory have been hindered.
This led to the need for research and development in the field of teaching to
find out a specific teaching theory according to the modern trends and concepts.
Teaching is regarded a humanitarian process which aims at helping those who
want to acquire knowledge, since teach
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
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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Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar & Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to
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