• Molecules and Cells
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• v.39 no.1
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• pp.65-71
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• 2016

A challenge in the redox field is the elucidation of the molecular mechanisms, by which $H_2O_2$ mediates signal transduction in cells. This is relevant since redox pathways are disturbed in some pathologies. The transcription factor OxyR is the $H_2O_2$ sensor in bacteria, whereas Cys-based peroxidases are involved in the perception of this oxidant in eukaryotic cells. Three possible mechanisms may be involved in $H_2O_2$ signaling that are not mutually exclusive. In the simplest pathway, $H_2O_2$ signals through direct oxidation of the signaling protein, such as a phosphatase or a transcription factor. Although signaling proteins are frequently observed in the oxidized state in biological systems, in most cases their direct oxidation by $H_2O_2$ is too slow ($10^1M^{-1}s^{-1}$ range) to outcompete Cys-based peroxidases and glutathione. In some particular cellular compartments (such as vicinity of NADPH oxidases), it is possible that a signaling protein faces extremely high $H_2O_2$ concentrations, making the direct oxidation feasible. Alternatively, high $H_2O_2$ levels can hyperoxidize peroxiredoxins leading to local building up of $H_2O_2$ that then could oxidize a signaling protein (floodgate hypothesis). In a second model, $H_2O_2$ oxidizes Cys-based peroxidases that then through thiol-disulfide reshuffling would transmit the oxidized equivalents to the signaling protein. The third model of signaling is centered on the reducing substrate of Cys-based peroxidases that in most cases is thioredoxin. Is this model, peroxiredoxins would signal by modulating the thioredoxin redox status. More kinetic data is required to allow the identification of the complex network of thiol switches.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.4
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• pp.485-493
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• 2019

Objective: This study was undertaken to investigate the genetic characteristics of Berkshire (BS), Landrace (LR), and Yorkshire (YS) pig breeds raised in the Great Grandparents pig farms using the single nucleotide polymorphisms (SNP) information. Methods: A total of 25,921 common SNP genotype markers in three pig breeds were used to estimate the expected heterozygosity ($H_E$), polymorphism information content, F-statistics ($F_{ST}$), linkage disequilibrium (LD) and effective population size ($N_e$). Results: The chromosome-wise distribution of $F_{ST}$ in BS, LR, and YS populations were within the range of 0-0.36, and the average $F_{ST}$ value was estimated to be $0.07{\pm}0.06$. This result indicated some level of genetic segregation. An average LD ($r^2$) for the BS, LR, and YS breeds was estimated to be approximately 0.41. This study also found an average $N_e$ of 19.9 (BS), 31.4 (LR), and 34.1 (YS) over the last 5th generations. The effective population size for the BS, LR, and YS breeds decreased at a consistent rate from 50th to 10th generations ago. With a relatively faster $N_e$ decline rate in the past 10th generations, there exists possible evidence for intensive selection practices in pigs in the recent past. Conclusion: To develop customized chips for the genomic selection of various breeds, it is important to select and utilize SNP based on the genetic characteristics of each breed. Since the improvement efficiency of breed pigs increases sharply by the population size, it is important to increase test units for the improvement and it is desirable to establish the pig improvement network system to expand the unit of breed pig improvement through the genetic connection among breed pig farms.

• Journal of the Korean Geotechnical Society
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• v.19 no.2
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• pp.267-278
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• 2003

Artificial neural networks are efficient computing techniques that are widely used to solve complex problems in many fields. In this study, in order to predict tunnel-induced ground movements, Tunnel Behavior Prediction System (TBPS) was developed by using these artificial neural networks model, based on a Held instrumentation database (i.e. crown settlement, convergence, axial force of rock bolt, compressive and shear stress of shotcrete, stress of concrete lining etc.) obtained from 193 location data of 31 different tunnel sites where works are completed. The study and test of the network were performed by Back Propagation Algorithm which is known as a systematic technique for studying the multi-layer artificial neural network. The tunnel behaviors predicted by TBPS were compared with monitored data in the tunnel sites and numerical analysis results. This study showed that the values obtained from TBPS were within allowable limits. It is concluded that this system can effectively estimate the tunnel ground movements and can also be used f3r tunneling feasibility study, and basic and detailed design and construction of tunnel.

• 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 The Korean Association For Science Education
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• v.38 no.4
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• pp.565-574
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• 2018

The purpose of this study is to investigate the features of science classes of Science Core Schools (SCSs) perceived by students. 654 students from 14 SCSs were surveyed with two open-ended questions on the features of science classes. The students' responses were analyzed with NetMiner 4.5, in terms of the centrality (of betweenness and of degree) analysis and the community analysis. The results of the research are as follows: (1) the science classes of SCSs were perceived by students to be of the environment of free questioning, active participation and communication, caring teacher, more science experiments and advanced contents, and knowledge sharing; (2) science classes in SCSs were perceived to be different from those of ordinary high schools because SCSs provide more opportunities for science-related special courses (like project work, advanced science subjects), extra-curricular activities, inquiry and research activities, school supports, hard-working classroom environment, longer studying hours, R&E and club activities. The students' perceptions of SCS science classes appear to be in line with the characteristics of 'good' science lessons from previous studies. The SCS project itself and the features of SCS science classes would help us to see how we introduce educational innovations into actual schools.

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.55-67
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• 2016

Global courier companies have been devoting to get more customers and profits with different service because of the worse profits from price competition. So, the effort of improving satisfaction of customers through improving courier service qualities is more important than any other time. However, the previous way to measure courier service has limitation that costs lots of time and money from off-line survey. This limitation could be overcome with less effort and costs if utilizing on-line social big data analysis and it is so helpful to improve competitiveness of courier companies. Therefore, I have collected comments from domestic and international courier companies from big data on social network service, analyzed the satisfaction of customers by R and verified the result by comparing with American Customer Satisfaction Index (ACSI) and Korea National Customer Index (NCSI) in this research. I found out the result depicts clear correlation between SNS analysis and customer satisfaction. This study can be the foundation to predict customer satisfaction easily by utilizing real time SNS information.

• Journal of Life Science
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• v.23 no.3
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• pp.347-354
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• 2013

Innate immunity is the ability to differentiate infectious agents from self. The innate immune system is comprised of a complicated network of recognition and effector molecules that act together to protect the host in the early stage of an infectious challenge. Mannose-binding lectin (MBL or mannose-binding protein, MBP) belongs to the family of $Ca^{2+}$-dependent lectins (C-type lectin with a collagen-like domain), which are considered an important component of innate immunity. While it is associated with increased risk and severity of infections and autoimmunity, the most frequent immuno-deficiency syndrome was reported to be low MBL level in blood. Deficiency of human MBL is caused by mutations in the coding region of the MBL gene. Rat homologue gene of human MBL gene was used to study functions of wild type and mutant MBL proteins. Although extensive studies have yielded the structural information of MBL, the functions of MBL, especially mutant MBL, still require investigation. We previously reported the cloning of rat wild-type MBL gene and the production of a truncated form of MBL protein and its antibody. Here, we present the cloning of mutant MBL cDNA in collagen-like domain (R40C, G42D, and G45E) using site-directed mutagenesis and differential behaviors of wild type and mutant MBL in cells. The major difference between wild type and mutant MBL was that while wild type MBL was secreted, mutant MBL was inhibited for secretion, retained in endoplasmic reticulum, and still functioned as a lectin.

• Journal of Korea Technology Innovation Society
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• v.22 no.3
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• pp.362-381
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• 2019

The purpose of this study is to examine how two factors among various affecting factors of technological innovation, i.e. sectoral system of innovation and R&D support service, were actually applied in the case of NUC Electronics. This company has achieved high level of innovation performance through change of injection port and improvement of extracting rate. This was possible because each component of sectoral system of innovation system was matched with the innovation activity. The improvement of the performance in NUC Electronics was attributable to its own innovation efforts and R&D support service of government research institute. In the process of technological innovation, the company could receive high-level services in areas such as product design and virtual experiments that companies can not solve themselves. It can be said that the role of government and public institutions to support the shortage of SMEs was important. In terms of each component of sectoral system of innovation, we found that there were many opportunities of new technology; sustainability was low; imitation was easy; appropriability was low but it has dualily; accumulation of technology was relatively high, availability of external knowledge was high. At the same time, both of the company and the network played an important role, and market conditions were very favorable. In terms of R&D support services, it is a direct effect that a great deal of time and cost savings have been achieved through virtual experiments on the material and shape of the screw. As an indirect effect, the core competence of the company has been greatly strengthened by utilizing the momentum of technology development through external support, hence the company could establish the structure of virtuous circle of innovation.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2479-2484
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• 2018

The filter bank multicarrier modulation (FBMC) technique is one of multicarrier modulation technique (MCM), which is mainly used to improve channel capacity of cognitive radio (CR) network and frequency spectrum access technique. The existing FBMC System contains serial to parallel converter, normal QAM modulation, Radix2 inverse FFT, parallel to serial converter and poly phase filter. It needs high area, delay and power consumption. To further reduce the area, delay and power of FBMC structure, a new clock gating technique is applied in the QAM modulation, radix2 multipath delay commutator (R2MDC) based inverse FFT and unified addition and subtraction (UAS) based FIR filter with parallel asynchronous self time adder (PASTA). The clock gating technique is mainly used to reduce the unwanted clock switching activity. The clock gating is nothing but clock signal of flip-flops is controlled by gate (i.e.) AND gate. Hence speed is high and power consumption is low. The comparison between existing QAM and proposed QAM with clock gating technique is carried out to analyze the results. Conversely, the proposed inverse R2MDC FFT with clock gating technique is compared with the existing radix2 inverse FFT. Also the comparison between existing poly phase filter and proposed UAS based FIR filter with PASTA adder is carried out to analyze the performance, area and power consumption individually. The proposed FBMC with clock gating technique offers low power and high speed than the existing FBMC structures.

• Journal of The Korean Astronomical Society
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• v.36 no.spc1
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• pp.83-91
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• 2003

There are terrestrial signatures of the solar activity cycle in ice core data (Ram & Stoltz 1999), but the variations in the sun's irradiance over the cycle seem too small to account for the signature (Lean 1997; Goode & Dziembowski 2003). Thus, one would expect that the signature must arise from an indirect effect(s) of solar activity. Such an indirect effect would be expected to manifest itself in the earth's reflectance. Further, the earth's climate depends directly on the albedo. Continuous observations of the earthshine have been carried out from Big Bear Solar Observatory since December 1998, with some more sporadic measurements made during the years 1994 and 1995. We have determined the annual albedos both from our observations and from simulations utilizing the Earth Radiation Budget Experiment (ERBE) scene model and various datasets for the cloud cover, as well as snow and ice cover. With these, we look for inter-annual and longer-term changes in the earth's total reflectance, or Bond albedo. We find that both our observations and simulations indicate that the albedo was significantly higher during 1994-1995 (activity minimum) than for the more recent period covering 1999-2001 (activity maximum). However, the sizes of the changes seem somewhat discrepant. Possible indirect solar influences on the earth's Bond albedo are discussed to emphasize that our earthshine data are already sufficiently precise to detect, if they occur, any meaningful changes in the earth's reflectance. Still greater precision will occur as we expand our single site observations to a global network.