• Restorative Dentistry and Endodontics
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• v.27 no.2
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• pp.150-157
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• 2002

One of the latest concepts in bonding are "total etch", in which both enamel and dentin are etched with an acid to remove the smear layers, and "wet dentin" in which the dentin is not dry but left moist before application of the bonding primer Ideally the application of a bonding agent to tooth structure should be insensitive to minor contamination from oral fluids. Clinically, contaminations such as saliva, gingival fluid, blood and handpiece lubricant are often encountered by dentists during cavity preparation. The aim of this study was to evaluate the effect of contamination by hemostatic agents on shear bond strength of compomer restorations. One hundred and ten extracted human maxillary and mandibular molar teeth were collected. The teeth were removed soft tissue remnant and debris and stored in physiologic solution until they were used. Small flat area on dentin of the buccal surface were wet ground serially with 400, 800 and 1200 abrasive papers on automatic polishing machine. The teeth were randomly divided into 11 groups. Each group was conditioned as follows : Group 1: Dentin surface was not etched and not contaminated by hemostatic agents. Group 2: Dentin surface was not etched but was contaminated by Astringedent$^{\circledR}$(Ultradent product Inc., Utah, U.S.A.) Group 3: Dentin surface was not etched but was contaminated by Bosmin$^{\circledR}$(Jeil Pharm, Korea.). Group 4: Dentin surface was not etched but was contaminated by Epri-dent$^{\circledR}$(Epr Industries, NJ, U.S.A.). Group 5: Dentin surface was etched and not contaminated by hemostatic agents. Group 6: Dentin sorface was etched and contaminated by Astringedent$^{\circledR}$. Group 7 : Dentin surface was etched and contaminated by Bosmin$^{\circledR}$. Group 8: Dentin surface was etched and contaminated by Epri-dent$^{\circledR}$. Group 9: Dentin surface was contaminated by Astringedent$^{\circledR}$. The contaminated surface was rinsed by water and dried by compressed air. Group 10: Dentin surface was contaminated by Bosmin$^{\circledR}$. The contaminated surface was rinsed by water and dried by compressed air. Group 11 : Dentin surface was contaminated by Epri-dent$^{\circledR}$. The contaminated surface was rinsed by water and dried by compressed air. After surface conditioning, F2000$^{\circledR}$ was applicated on the conditoned dentin surface The teeth were thermocycled in distilled water at 5$^{\circ}C$ and 55$^{\circ}C$ for 1,000 cycles. The samples were placed on the binder with the bonded compomer-dentin interface parallel to the knife-edge shearing rod of the Universal Testing Machine(Zwick Z020, Zwick Co., Germany) running at a cross head speed or 1.0 mm/min. Group 2 showed significant decrease in shear bond strength compared with group 1 and group 6 showed significant decrease in shear bond strength compared with group 5. There were no significant differences in shear bond strength between group 5 and group 9, 10 and 11.

• Journal of the Korean Society of Propulsion Engineers
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• v.20 no.2
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• pp.86-93
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• 2016

Performance tests of a 75-tonf liquid rocket engine turbopump were conducted. The performance of sub-components - two pumps and a turbine - and their power matching were measured and examined firstly near the design speed under the LN2 and kerosene environment. In the real propellant - LOX and kerosene - environment tests, design and off-design performance of turbopump were fully verified in regime of the rocket engine operation. During the off-design performance tests, turbopump running time was set longer than the engine operating time to verify the pump operability and set the pump inlet pressure close to design NPSHr to investigate pump suction capability in parallel. It has been found that developed-turbopump satisfied all of the engine required performances.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.