• Molecules and Cells
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• v.46 no.6
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• pp.329-336
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• 2023

Reactive oxygen species (ROS) serve as secondary messengers that regulate various developmental and signal transduction processes, with ROS primarily generated by NADPH OXIDASEs (referred to as RESPIRATORY BURST OXIDASE HOMOLOGs [RBOHs] in plants). However, the types and locations of ROS produced by RBOHs are different from those expected to mediate intracellular signaling. RBOHs produce O₂^•- rather than H₂O₂ which is relatively long-lived and able to diffuse through membranes, and this production occurs outside the cell instead of in the cytoplasm, where signaling cascades occur. A widely accepted model explaining this discrepancy proposes that RBOH-produced extracellular O₂^•- is converted to H₂O₂ by superoxide dismutase and then imported by aquaporins to reach its cytoplasmic targets. However, this model does not explain how the specificity of ROS targeting is ensured while minimizing unnecessary damage during the bulk translocation of extracellular ROS (eROS). An increasing number of studies have provided clues about eROS action mechanisms, revealing various mechanisms for eROS perception in the apoplast, crosstalk between eROS and reactive nitrogen species, and the contribution of intracellular organelles to cytoplasmic ROS bursts. In this review, we summarize these recent advances, highlight the mechanisms underlying eROS action, and provide an overview of the routes by which eROS-induced changes reach the intracellular space.

• Geomechanics and Engineering
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• v.35 no.5
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• pp.487-497
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• 2023

Penetration rate (PR) and penetration depth (Pe) are crucial parameters for estimating the cost and time required in tunnel construction using tunnel boring machines (TBMs). This study focuses on investigating the impact of rock strength on PR and Pe through full-scale experiments. By conducting controlled tests on rock-like specimens, the study aims to understand the contributions of various ground parameters and machine-operating conditions to TBM excavation performance. An earth pressure balanced (EPB) TBM with a sectional diameter of 3.54 m was utilized in the experiments. The TBM excavated rocklike specimens with varying uniaxial compressive strength (UCS), while the thrust and cutterhead rotational speed were controlled. The results highlight the significance of the interplay between thrust, cutterhead speed, and rock strength (UCS) in determining Pe. In high UCS conditions exceeding 70 MPa, thrust plays a vital role in enhancing Pe as hard rock requires a greater thrust force for excavation. Conversely, in medium-to-low UCS conditions less than 50 MPa, thrust has a weak relationship with Pe, and Pe becomes directly proportional to the cutterhead rotational speed. Furthermore, a strong correlation was observed between Pe and cutterhead torque with a determination coefficient of 0.84. Based on these findings, a predictive model for Pe is proposed, incorporating thrust, TBM diameter, number of disc cutters, and UCS. This model offers a practical tool for estimating Pe in different excavation scenarios. The study presents unprecedented full-scale TBM excavation results, with well-controlled experiments, shedding light on the interplay between rock strength, TBM operational variables, and excavation performance. These insights are valuable for optimizing TBM excavation in grounds with varying strengths and operational conditions.

• Journal of the Korean Geosynthetics Society
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• v.23 no.1
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• pp.17-25
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• 2024

The Voids in the Mineral Aggregate (VMA) within asphalt mixtures play a crucial role in defining the mixture's structural integrity, durability, and resistance to environmental factors. Accurate prediction and optimization of VMA are essential for enhancing the performance and longevity of asphalt pavements, particularly in varying climatic and environmental conditions. This study introduces a novel machine learning framework leveraging ensemble machine learning model for predicting VMA in asphalt mixtures. By analyzing a comprehensive set of variables, including aggregate size distribution, binder content, and compaction levels, our framework offers a more precise prediction of VMA than traditional single-model approaches. The use of advanced machine learning techniques not only surpasses the accuracy of conventional empirical methods but also significantly reduces the reliance on extensive laboratory testing. Our findings highlight the effectiveness of a data-driven approach in the field of asphalt mixture design, showcasing a path toward more efficient and sustainable pavement engineering practices. This research contributes to the advancement of predictive modeling in construction materials, offering valuable insights for the design and optimization of asphalt mixtures with optimal void characteristics.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1310-1319
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• 2024

The reactor cavity cooling system (RCCS) is a passive reactor safety system commonly present in the designs of High-Temperature Gas-cooled Reactors (HTGR) that removes heat from the reactor pressure vessel by means of natural convection and radiation. It is one of the factors responsible for ensuring that the reactor does not melt down under any plausible accident scenario. For the simulation of accident scenarios, which are transient phenomena unfolding over a span of up to several days, intermediate fidelity methods and system codes must be employed to limit the models' execution time. These models can quantify radiation heat transfer well, but heat transfer caused by natural convection must be quantified with the use of correlations for the heat transfer coefficient. It is difficult to obtain reliable correlations for HTGR RCCS heat transfer coefficients experimentally due to such a system's size. They could, however, be obtained from high-fidelity steady-state simulations of RCCSs. The Rayleigh number in RCCSs is too high for using a Direct Numerical Simulation (DNS) technique; thus, a Reynolds-Averaged Navier-Stokes (RANS) approach must be employed. There are many RANS models, each performing best under different geometry and fluid flow conditions. To find the most suitable one for simulating an RCCS, the RANS models need to be validated. This work benchmarks various RANS models against three experiments performed on the HTTR RCCS Mockup by the Japanese Atomic Energy Agency (JAEA) in 1993. This facility is a 1/6 scale model of a vessel cooling system (VCS) for the High Temperature Engineering Test Reactor (HTTR), which is operated by JAEA. Multiple RANS models were evaluated on a simplified 2d-axisymmetric geometry. They were found to reproduce the experimental temperature profiles with errors of up to 22% for the lowest temperature benchmark and 15% for the higher temperature benchmarks. The results highlight that the pragmatic turbulence models need to be validated for high Rayleigh natural convection-driven flows and improved accordingly, more publicly available experimental data of RCCS resembling experiments is needed and indicate that a 2d-axisymmetric geometry approximation is likely insufficient to capture all the relevant phenomena in RCCS simulations.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.307-321
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• 2024

This paper delves into the critical assessment of predicting sidewall displacement in underground caverns through the application of nine distinct machine learning techniques. The accurate prediction of sidewall displacement is essential for ensuring the structural safety and stability of underground caverns, which are prone to various geological challenges. The dataset utilized in this study comprises a total of 310 data points, each containing 13 relevant parameters extracted from 10 underground cavern projects located in Iran and other regions. To facilitate a comprehensive evaluation, the dataset is evenly divided into training and testing subset. The study employs a diverse array of machine learning models, including recurrent neural network, back-propagation neural network, K-nearest neighbors, normalized and ordinary radial basis function, support vector machine, weight estimation, feed-forward stepwise regression, and fuzzy inference system. These models are leveraged to develop predictive models that can accurately forecast sidewall displacement in underground caverns. The training phase involves utilizing 80% of the dataset (248 data points) to train the models, while the remaining 20% (62 data points) are used for testing and validation purposes. The findings of the study highlight the back-propagation neural network (BPNN) model as the most effective in providing accurate predictions. The BPNN model demonstrates a remarkably high correlation coefficient (R2 = 0.99) and a low error rate (RMSE = 4.27E-05), indicating its superior performance in predicting sidewall displacement in underground caverns. This research contributes valuable insights into the application of machine learning techniques for enhancing the safety and stability of underground structures.

• Journal of Global Scholars of Marketing Science
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• v.12
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• pp.99-119
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• 2003

A model is proposed for the role of emotional intensity of a web site, and the moderating influence of product involvement, in the Integrative Framework of persuasion (Meyers-Levy and Malvaiya 1999). The model also appropriately operationalizes the constructs emotional intensity of a web site and product involvement The three routes to persuasion, Central, Peripheral, and Experiential correspond to high, moderate, and low involvement (Meyers-Levy and Malaviya 1999). The involvement construct is measured from message recipients using the Personal Product Inventory (Pill, which was developed to capture the concept of product involvement (Zaichkowsky 1985). The conceptualization of the Personal Product Inventory is a contextrree measure that also has robust psychometric properties when applied to advertisements (Zaichkowsky 1994). The propositions highlight the expected importance of emotional intensity of a web site. The moderating influence of product involvement is also proposed. Specifically, what this work proposes is that the emotional intensity of a product site has a larger impact on attitude change under low product involvement, as opposed to moderate product involvement. Support for this reasoning can be found in the persuasion literature (Petty et al 1986). The Petty et al (1986) frame work is a dual process descriptive and predictive frame work in the area of altitude formation and change. Recently, Myers Levy and Malaviya (1999) have proposed a tri-process framework. This is in tum based on the dual process model of Petty et al. (1986). The study outlined in this paper aims to deepen the Meyers Levy and Malaviya (1999) and frame work. The propositions outlined in the model are empirically tested using a repeated measures experimental design. The emotional intensity is measured using a scale that is based on experts judgments. Using a paired comparison t-test two sites are determined to be of high and low emotional intensity. The model is tested using a repeated measures experimental design. The first independent variable Emotional Intensity of the site is manipulated. The Second independent variable, Personal Product Inventory is measured. While, the dependent variable, product altitude change will also be measured. Utilizing Analysis of Variance (ANOVA) the data is analyzed using SPSS. The results suggest that besides the rational content of messages their emotional content can also influence attitude change. Specifically, it is proposed that the manipulation of emotional intensity of a product Web site has a greater impact on product altitudes under high and low product involvement conditions, rather than moderate product involvement. However, the results for product involvement as a continuous variable has a p value of 0.09. Further, the results for three levels of product involvement were far from significant. For two levels of product involvement also, the results were insignificant, the p value approached 0.20. This evidence indicates that it is premature to conclude that there are three routes to persuasion. A caveat, however, must be added, in that the manipulations may not have been strong enough to test the proposed hypotheses. Further, undoubtedly, there is unequivocal evidence the emotional intensity of a product Web site, as measured here, has a direct impact on product attitudes.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.201-215
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• 2020

We conducted the analysis using the data of the '2019 Korean Middle and Elderly Technology Acceptance Survey' to verify the comprehensive senior technology acceptance model. In this study, we examined the significant effect the relationship between behavioral intention to use the diital health devices and perceived usefulness, perceived ease of use, gerontechnology self-efficacy, gerontechnology anxiety, facilitating conditions, attitude to life and satisfaction through the structural equation. The results of the research model are as follows. First, the usefulness and ease of use had significant effects on intention to use. Second, the self-efficacy had significant effects on the intention to use. But they had negative effect. Third, perceived usefulness, self-efficacy and anxiety had significant effects on ease of use. Lastly, self-efficacy, facilitating conditions, attitude to life and satisfaction had significant effects on perceived usefulness. These findings highlight that verified the comprehensive senior technology acceptance model in Korea.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.126-146
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• 2022

With the development of IT technology, consumers' shopping behaviors have diversified, and O2O services that remove the boundary between online and offline are increasing. With the development of O2O services, it is bringing about new changes in offline retailers that are facing limitations against the continuous growth of online. Drawing upon Technology Acceptance Model, this study investigates the effect of service quality perceived by O2O service users on consumers' intention to use O2O services. The result confirmed that the perceived quality, an external variable, affects the perceived usefulness and perceived ease of use, which are the main variables of the Technology Acceptance Model, and the perceived usefulness and perceived ease of use in turn have a significant effect on attitude and behavioral intention. In particular, it was found that the higher the perceived ease of use of the user, the higher the perceived usefulness and positive influence on the attitude. The results of this study suggest that in order to increase the utilization of O2O service by users, it is necessary to highlight the perceived quality of service and at the same time manage convenience and usefulness. This is expected to provide meaningful directions for companies attempting to advance O2O services.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.37-44
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• 2006

Specular reflections provide the visual feedback that describes the material type of an object, its local shape, and lighting environment. In photorealistic rendering, there have been a number of research available to render specular reflections effectively based on a local reflection model. In traditional cel animations and cartoons, specular reflections plays important role in representing artistic intentions for an object and its related environment reflections, so the shapes of highlights are quite stylistic. In this paper, we present a method to render and control stylized specular reflections using projective textures based on principal curvature analysis. Specifying a texture as a pattern of a highlight and projecting the texture on the specular region of a given 3D model, we can obtain a stylized representation of specular reflections. For a given polygonal model, a view point, and a light source, we first find the maximum specular intensity point, and then locate the texture projector along the line parallel to the normal vector and passing through the point. The orientation of the projector is determined by the principal directions at the point. Finally, the size of the projection frustum is determined by the principal curvatures corresponding to the principal directions. The proposed method can control the position, orientation, and size of the specular reflection efficiently by translating the projector along the principal directions, rotating the projector about the normal vector, and scaling the principal curvatures, respectively. The method is be applicable to real-time applications such as cartoon style 3D games. We implement the method by Microsoft DirectX 9.0c SDK and programmable vertex/pixel shaders on Nvidia GeForce FX 7800 graphics subsystems. According to our experimental results, we can render and control the stylized specular reflections for a 3D model of several ten thousands of triangles in real-time.

• The Journal of Engineering Geology
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• v.32 no.4
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• pp.467-482
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• 2022

The Yeonghae basin is located at the northeastern part of the Yangsan fault (YSF; a potentially active fault). The study of the architecture of the Yeonghae basin is important to understand the activity of the Yangsan fault system (YSFS) as well as the basin formation mechanism and the activity of the YSFS. For this study, Digital Elevation Model (DEM) was used to highlight the marginal faults, and structural fieldwork was performed to understand the geometry of the intra-basinal structures and the nature of the bounding faults. DEM analysis reveals that the eastern margin is bounded by the northern extension of the YSF whereas the western margin is bounded by two curvilinear sub-parallel faults; Baekseokri fault (BSF) and Gakri fault (GF). The field data indicate that the YSF is striking in the N-S direction, steeply dipping to the east, and experienced both sinistral and dextral strike-slip movements. Both the BSF and GF are characterized dominantly by an oblique right-lateral strike-slip movement. The stress indicators show that the maximum horizontal compressional stress was in NNE to NE and NNW-SSE, which is consistent with right-lateral and left-lateral movements of the YSFS, respectively. The plotted structural data show that the NE-SW is the predominant direction of the structural elements. This indicates that the basin and marginal faults are mainly controlled by the right-lateral strike-slip movements of the YSFS. Based on the structural architecture of the Yeonghae basin, the study area represents a contractional zone rather than an extensional zone in the present time. We proposed two models to explain the opening and developing mechanism of the Yeonghae basin. The first model is that the basin developed as an extensional pull-apart basin during the left-lateral movement of the YSF, which has been reactivated by tectonic inversion. In the second model, the basin was developed as an extensional zone at a dilational quadrant of an old tip zone of the northern segment of the YSF during the right-lateral movement stage. Later on, the basin has undergone a shortening stage due to the closing of the East Sea. The second model is supported by the major trend of the collected structural data, indicating predominant right-lateral movement. This study enables us to classify the Yeonghae basin as an inverted strike-slip basin. Moreover, two opposite strike-slip movement senses along the eastern marginal fault indicate multiple deformation stages along the Yangsan fault system developed along the eastern margin of the Korean peninsula.