Search

Abstract Existing studies have relied on the notion of developmentalism to explain key aspects of the tax policies in Japan and Korea. However, limited efforts have been made to explore [...]

Background: Recent studies have reported the inhomogeneity in the light emitted by dental light-curing units (LCUs). It is essential to understand how this uneven light distribution affects the physical properties of resin-based composites (RBCs) at various points across their surfaces. This study aimed to evaluate the effect of LCU beam's inhomogeneity on the microhardness of RBCs with different shades and thicknesses. Methods: Four body (A1B, A2B, A3B, and A4B), one dentin (A3D), and one enamel shade (A3E) of RBC (Filtek Z350 XT) were examined. The specimens were fabricated in four thicknesses (1, 2, 3, and 4 mm) and subjected to a 40-second light-curing. Vickers microhardness testing was performed at the center point, and 3 mm left and right from the center at the bottom surface of each sample. The LCU beam profile was characterized using a beam profiler, while irradiance after specimen passage was measured using a spectrometer. One-way analysis of variance (ANOVA) and Tukey's post-hoc tests were used to analyze the effects of shades and thicknesses on irradiance and microhardness, respectively. One-way repeated-measures ANOVA was used to compare the microhardness across different points. Pearson's correlation analysis examined the relationship between irradiance and microhardness. Results: The beam profile of LCU revealed inhomogeneous light distribution. Light irradiance was decreased with both the increase in thickness and darker shade of the specimens (p < 0.05). Microhardness was found to decline with an increase in sample thickness (p < 0.05), and was consistently higher at the center point compared to the periphery, particularly in thicker (3 and 4 mm) and darker shades (A3B, A4B, and A3D). A positive correlation was found between the irradiance and microhardness across all evaluated points (p < 0.05). Conclusions: Inhomogeneous light emission from LCU significantly influences the microhardness of RBC samples, depending on the thicknesses and shades. The findings underline the importance of considering LCU beam inhomogeneity in clinical settings to ensure optimal polymerization of RBC. [ABSTRACT FROM AUTHOR]

This paper describes the development of an in-pipe inspection robot system designed for large-diameter water pipes. The robot is equipped with a Magnetic Flux Leakage (MFL) sensor module. The robot system is intended for pipes with diameters ranging from 900 mm to 1200 mm. The structure of the in-pipe inspection robot consists of the front and rear driving parts, with the inspection module located centrally. The robot is powered by 22 motors, including eight wheels with motors positioned at both the bottom and the top for propulsion. To ensure that the robot's center aligns with that of the pipeline during operation, lifting units have been incorporated. The robot is equipped with cameras and LiDAR sensors at the front and rear to monitor the internal environment of the pipeline. Pipeline inspection is conducted using the MFL inspection modules, and the robot's driving mechanism is designed to execute spiral maneuvers while maintaining contact with the pipeline surface during rotation. The in-pipe inspection robot is configured with wireless communication modules and batteries, allowing for wireless operation. Following its development, the inspection robot underwent driving experiments in actual pipelines to validate its performance. The field test bed used for these experiments is approximately 1 km in length. Results from the driving experiments on the field test bed confirmed the robot's ability to navigate various curvatures and obstacles within the pipeline. It is posited that the use of the developed in-pipe inspection robot can reduce economic costs and enhance the safety of inspectors when examining aging pipes. [ABSTRACT FROM AUTHOR]

This paper studies the implications of globalization for the dynamics of macroeconomic variables over the business cycle for a small open trade-dependent economy, such as South Korea.We study the impact of globalization through the lens of a structural model. Globalization is modeled as a time-varying degree of openness in the economy. We estimate the model allowing for non-fully rational expectations, learning by economic agents, and incomplete international financial markets.The empirical results show that globalization led to important changes in the macroeconomic environment. Domestic variables have become much more sensitive toward global measures over the 1991-2012 sample. In particular, domestic output and inflation are significantly affected by global output. Fluctuations in Korean output, inflation, and interest rates, which were driven for the most part by domestic shocks in the early 1990s, are, by the end of the sample, due in large part (roughly 70%) to global shocks (and shocks that are open-economy in nature).

Hardware neuromorphic systems are crucial for the energy‐efficient processing of massive amounts of data. Among various candidates, hafnium oxide ferroelectric tunnel junctions (FTJs) are highly promising for artificial synaptic devices. However, FTJs exhibit non‐ideal characteristics that introduce variations in synaptic weights, presenting a considerable challenge in achieving high‐performance neuromorphic systems. The primary objective of this study is to analyze the origin and impact of these variations in neuromorphic systems. The analysis reveals that the major bottleneck in achieving a high‐performance neuromorphic system is the dynamic variation, primarily caused by the intrinsic 1/f noise of the device. As the device area is reduced and the read bias (VRead) is lowered, the intrinsic noise of the FTJs increases, presenting an inherent limitation for implementing area‐ and power‐efficient neuromorphic systems. To overcome this limitation, an adaptive read‐biasing (ARB) scheme is proposed that applies a different VRead to each layer of the neuromorphic system. By exploiting the different noise sensitivities of each layer, the ARB method demonstrates significant power savings of 61.3% and a scaling effect of 91.9% compared with conventional biasing methods. These findings contribute significantly to the development of more accurate, efficient, and scalable neuromorphic systems. [ABSTRACT FROM AUTHOR]