• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• The Korean Society of Law and Medicine
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• v.21 no.2
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• pp.209-244
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• 2020

TMS and tDCS are non-invasive devices that treat the diseases of patients or individual users, and manage or improve their health by applying stimulation to a brain through magnetism and electricity. The effect and safety of these devices have proved to be valid in several diseases, but research in this area is still much going on. Despite increasing cases of their application, legislations directly regulating TMS and tDCS are hard to find. Legal regulation regarding TMS and tDCS in the United States, Germany and Japan reveals that while TMS has been approved as a medical device with a moderate risk, tDCS has not yet earned approval as a medical device. However, the recent FDA guidance, European MDR changes, recalls in the US, and relevant legal provisions of Germany and Japan, as well as recommendations from expert groups all show signs of tDCS growing closer to getting approved as a medical device. Of course, safety and efficacy of tDCS can still be regulated as a general product instead of as a medical device. Considering multiple potential impacts on a human brain, however, the need for independent regulation is urgent. South Korea also lacks legal provisions explicitly regulating TMS and tDCS, but they fall into the category of the grade 3 medical devices according to the notifications of the Korean Ministry of Food and Drug Safety. And safety and efficacy of TMS are to be evaluated in compliance with the US FDA guidance. But no specific guidelines exist for tDCS yet. Given that tDCS devices are used in some hospitals in reality, and also at home by individual buyers, such a regulatory gap must quickly be addressed. In a longer term, legal system needs to be in place capable of independently regulating non-invasive brain stimulating devices.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.215-235
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• 2024

As artificial intelligence (AI) technology is recognized as a key technology that will determine future national competitiveness, competition for AI technology and industry promotion policies in major countries is intensifying. This study aims to present implications for domestic policy making by analyzing the policies of major countries on the start-up of AI companies, which are the basis of the AI industry ecosystem. The top four countries and the EU for the number of new investment attraction companies in the 2023 AI Index announced by the HAI Research Institute at Stanford University in the United States were selected, The United States enacted the National AI Initiative Act (NAIIA) in 2021. Through this law, The US Government is promoting continued leadership in the United States in AI R&D, developing reliable AI systems in the public and private sectors, building an AI system ecosystem across society, and strengthening DB management and access to AI policies conducted by all federal agencies. In the 14th Five-Year (2021-2025) Plan and 2035 Long-term Goals held in 2021, China has specified AI as the first of the seven strategic high-tech technologies, and is developing policies aimed at becoming the No. 1 AI global powerhouse by 2030. The UK is investing in innovative R&D companies through the 'Future Fund Breakthrough' in 2021, and is expanding related investments by preparing national strategies to leap forward as AI leaders, such as the implementation plan of the national AI strategy in 2022. Israel is supporting technology investment in start-up companies centered on the Innovation Agency, and the Innovation Agency is leading mid- to long-term investments of 2 to 15 years and regulatory reforms for new technologies. The EU is strengthening its digital innovation hub network and creating the InvestEU (European Strategic Investment Fund) and AI investment fund to support the use of AI by SMEs. This study aims to contribute to analyzing the policies of major foreign countries in making AI company start-up policies and providing a basis for Korea's strategy search. The limitations of the study are the limitations of the countries to be analyzed and the failure to attempt comparative analysis of the policy environments of the countries under the same conditions.

• The Korean Journal of Nuclear Medicine
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• v.37 no.6
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• pp.382-392
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• 2003

Purpose: Uptakes of Tc-99m MIBI (MIBI) and Tc-99m tetrofosmin (tetrofosmin) in human non-small cell lung cancer A549, multidrug-resistance associated protein (MRP) expressing cell, were investigated in vitro and in vivo. Materials and Methods: Western blot analysis and immunohistochemistry were used for detection of MRP in A549 cells with anti-MRPr1 antibody. Cellular uptakes of two tracers were evaluated at $100{\mu}M$ of verapamil (Vrp), $50{\mu}M$ of cyclosporin A (CsA) and $25{\mu}M$ of butoxysulfoximide (BSO) after incubation with MIBI and tetrofosmin for 30 and 50 min at $37^{\circ}C$, using single cell suspensions at $1{\times}10^6cells/ml$. Radioactivities in supernatants and pellets were measured with gamma well counter. A549 cells were inoculated in each flanks of 24 nude mice. Group 1 (Gr1) and Gr3 mice were treated with only MIBI or tetrofosmin, and Gr2 and Gr4 mice were treated with 70mg/kg of CsA i.p. for 1 hour before injection of 370KBq of MIBI or tetrofosmin. Mice were sacrificed at 10, 60 and 240 min. Radioactivities of organs and tumors were expressed as percentage injected dose per gram of tissue (%ID/gm). Results: Western blot analysis of the A549 cells detected expression of MRPr1 (190 kDa) and immunohistochemical staining of tumor tissue for MRPr1 revealed brownish staining in cell membrane but not P-gp. Upon incubating A549 cells for 60 min with MIBI and tetrofosmin, cellular uptake of MIBI was higher than that of tetrofosmin. Coincubation with modulators resulted in an increase in cellular uptakes of MIBI and tetrofosmin. Percentage increase of MIBI was higher than that of tetrofosmin with Vrp by 623% and 427%, CsA by 753% and 629% and BSO by 219% and 140%, respectively. There was no significant difference in tumoral uptakes of MIBI and tetrofosmin between Gr1 and Gr3. Percentage increases in MIBI (114% at 10 min, 257% at 60 min, 396% at 240 min) and tetrofosmin uptake (110% at 10 min, 205% at 60 min, 410% at 240 min) were progressively higher by the time up to 240 min with CsA. Conclusion: These results indicate that MIBI and tetrofosmin are suitable tracers for imaging MRP-mediated drug resistance in A549 tumors. MIBI may be a better tracer than tetrofosmin for evaluating MRP reversal effect of modulators.

• The Korean Journal of Nuclear Medicine
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• v.39 no.1
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• pp.34-43
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• 2005

Purpose: $^{99m}Tc$-sestamibi(MIBI) and $^{99m}Tc$-tetrofosmin have been used as substrates for P-glycoprotein (Pgp) and multidrug resistance associated protein (MRP), which are closely associated with multidrug resistance of the tumors. To understand different handling of radiotracers in cancer cell lines expressing Pgp and MRP, we compared cellular uptakes of $^{99m}Tc$-MIBI and $^{99m}Tc$-tetrofosmin. The effects of cyclosporin A (CsA), well-known multidrug resistant reversing agent, on the uptake of both tracers were also compared. Materials and Methods: HCT15/CL02 human colorectal cancer cells for Pgp expressing cells, and human non-small cell lung cancer A549 cells for MRP expressing cells, were used for in vitro and in vivo studies. RT-PCR, western blot analysis and immunohistochemistry were used for detection of Pgp and MRP. MDR-reversal effect with CsA was evaluated at different drug concentrations after incubation with MIBI or tetrofosmin. Radioactivities of supernatant and pellet were measured with gamma well counter. Tumoral uptake of the tracers were measured from tumor bearing nude mice treated with or without CsA. Results: RT-PCR, western blot analysis of the cells and irnrnunochemical staining revealed selective expression of Pgp and MRP for HCY15/CL02 and A549 cells, respectively. There were no significant difference in cellular uptakes of both tracers in HCT15/CL02 cells, but MIBI uptake was slightly higher than that of tetrofosmin in A549 cells. Co-incubation with CsA resulted in a increase in cellular uptakes of MIBI and tetrofosmin. Uptake of MIBI or tetrofosmin in HCT15/CL02 cells was increased by 10- and 2.4-fold, and by 7.5 and 6.3-fold in A549 cells, respectively. Percentage increase of MIBI was higher than that of tetrofosmin with CsA for both cells (p<0.05). In vivo biodistribution study showed that MIBI (114% at 10 min, 257% at 60 min, 396% at 240 min) and tetrofosmin uptake (110% at 10 min, 205% at 60 min, 410% at 240 min) were progressively increased by the time, up to 240 min with CsA. But increases in tumoral uptake were not significantly different between MIBI and tetrofosmin for both tumors. Conclusion: MIBI seems to be a better tracer than tetrofosmin for evaluating MDR reversal effect of the modulators in vitro, but these differences were not evident in vivo tumoral uptake. Both MIBI and tetrofosmin seem to be suitable tracers for imaging Pgp- and MRP-mediated drug resistance in tumors.