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A Study on the Countermeasures Taken By the Korean Healthcare and Life Sciences Industry Regarding U.S. Import Refusals: Focus on the Analysis of FDA Violation Codes (한국 바이오헬스 산업의 미국 수입거부 대응 방안 연구 : FDA 위반코드 분석을 중심으로)

  • Yu-Han Lee;Hag-Min Kim
    • Korea Trade Review
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    • v.48 no.3
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    • pp.131-150
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    • 2023
  • The purpose of this study was to find a countermeasure to the U.S. import refusals for the Korean healthcare and life sciences industry. To this end, an analysis of trends during the pandemic was conducted using the KITA Border Rejection Database, which includes information on items and types of import refusals. The reason for rejection was also analyzed according to the FDA violation codes. The degree of countermeasure for import refusals was identified by measuring the unit rejection rate (URR). The results of the analysis showed that the major U.S. import refusals for the Korean healthcare and life sciences industry had expanded from contact lenses to COVID-19 diagnostic kits and drugs after the pandemic broke out. The major reasons for import refusals were non-compliance with the Predicate Device and Drugs Act and non-approval by the FDA for products and facilities. On the other hand, the unit rejection rate (URR) of major items in the Korean healthcare and life sciences industry was measured higher than the industry average. The results therefore showed a low level of response to U.S. import refusals. The results of the analysis of reasons for import refusals by item according to FDA violation codes were as follows. First of all, the main violation for contact lenses and COVID-19 diagnostic kits corresponded to misbranding. This was often due to the fact that Korean companies did not provide the relevant notices and information required by the FDA. Many cases also failed to demonstrate a substantial equivalency compared to predicate devices already on the market. On the other hand, applications for new unapproved drugs were not accepted as they had yet to pass relevant regulations that would prove their safety and efficacy. In conclusion, import refusals for the Korean healthcare and life sciences industry were found to be closely related to technical barriers to trade (TBT).

Size-dependent Transcriptional Modulation of Genes Involved in Cytochrome P450 Family in the Brackish Water Flea Diaphanosoma celebensis Exposed to Polystyrene Beads (기수산물벼룩 Diaphanosoma celebensis의 미세플라스틱 노출에 따른 크기 의존적 Cytochrome P450 유전자의 발현 양상)

  • Min Jeong Jeon;Je-Won Yoo;Young-Mi Lee
    • Journal of Marine Life Science
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    • v.8 no.2
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    • pp.104-114
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    • 2023
  • As plastic usage increases globally, the amount of plastic waste entering the marine environment is steadily rising. Microplastics, in particular, can be ingested by marine organisms and accumulated in their digestive tracts, causing harmful effects on their growth and reproduction. Cytochrome P450 (CYP) enzymes are known to metabolize various environmental pollutants as detoxification enzymes, but their role in crustaceans is not well understood. In this study, sequences of nine CYP genes (CYP370A4, CYP370C5 from clan 2; CYP350A1, CYP350C5, CYP361A1 from clan 3; CYP4AN-like, CYP4AP2, CYP4AP3, CYP4C33-like1 from clan 4) were analyzed using conserved domains in the brackish water flea Diaphanosoma celebensis. Additionally, after exposure to three different sizes of polystyrene beads (0.05-, 0.5-, 6-㎛ PS beads; 0.1, 1, and 10 mg/L) for 48 hours, the expression of these nine CYP genes were investigated using real-time reverse transcription polymerase chain reaction (RT-PCR). The results showed that all CYP genes possessed conserved motifs, indicating that D. celebensis CYP has evolutionarily conserved functions. Among these CYP genes, the expression of CYP370C5, CYP360A1, and CYP4C122 showed a significant increase after exposure to 0.05-㎛ PS beads, suggesting their involvement in PS metabolism. This research will contribute to understanding the molecular mode of actions of microplastics on marine invertebrates.

Effects of Korean Goldenbell (Forsythia koreana) Leaf on the Growth, Body Color and Hepatopancreatic Structure of Giant Freshwater Prawn (Macrobrachium rosenbergii) (큰징거미새우(Macrobrachium rosenbergii)의 성장, 체색 및 간췌장 구조에 미치는 개나리(Forsythia koreana) 잎의 영향)

  • Dong Woo Kim;Jeong Hee Yoon;Ji Eun Ha;Jeong Hee Min;Bo Ryung Park;Joon Yeong Kwon
    • Journal of Marine Life Science
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    • v.8 no.2
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    • pp.166-177
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    • 2023
  • The giant freshwater prawn (Macrobrachium rosenbergii) suffers economic losses in aquaculture facilities due to problems such as poor body color and carapace weakness. While this species is farmed on an animal-based diet, in the wild it consumes a detritus diet with a high proportion of plant matter. The plant matter they consume in the wild is not only a source of basic nutrients, but also carotenoids, which are responsible for body color. Korean goldenbell (Forsythia koreana) is a flowering tree widely distributed in Korea, and its leaves contain carotenoids comparable to yellow carrots. In this study, we investigated the effects of feeding Forsythia leaves to M. rosenbergii on their body color and health. The experimental diets were 100% commercial feed (control), CON, 80% commercial feed plus 20% Forsythia leaf powder, FP, and 80% commercial feed plus 20% unprocessed Forsythia leaves, FL, and each diet was fed to juvenile prawn with an average weight of 1.1 ± 0.2 g for 10 weeks. In terms of body color, the CON prawn were consistently clear ivory in color, while the FP and FL prawn changed from blue to dark brown as the days of rearing progressed. Survival and growth were not significantly different between CON and FP or FL. Histological comparison of the hepatopancreas revealed that the vacuole size of B cells, the constituent cells of the hepatopancreatic tubule, was significantly larger in FP and FL compared to CON. The vacuoles of B cells are responsible for the absorption and digestion of nutrients, suggesting that the supply of Forsythia leaves may have had a positive effect on the health of the M. rosenbergii. The above results show that the use of Forsythia leaves in the aquaculture of M. rosenbergii can be expected to improve body color and health without inhibiting growth.

A Study on the Bioactivity Exploration of the Collected Marine Microorganisms and Microalgaes in Korea (우리나라에서 확보한 해양미생물과 미세조류에 대한 기초생리활성 연구)

  • Seung Sub Bae;Yong Min Kwon;Dawoon Chung;Woon-Jong Yu;Kichul Cho;Eun-Seo Cho;Yoon-Hee Jung;Yun Gyeong Park;Hyemi Ahn;Dae-Sung Lee;Jin-Soo Park;Jaewook Lee;Dong-Chan Oh;Ki-Bong Oh;EunJi Cho;Sang-Ik Park;You-Jin Jeon;Hyo-Geun Lee;Keun-Yong Kim;Sang-Jip Nam;Hyukjae Choi;Cheol Ho Pan;Grace Choi
    • Journal of Marine Life Science
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    • v.8 no.2
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    • pp.136-149
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    • 2023
  • Basic bioactivities (antioxidant, anti-inflammatory, antibacterial, anticancer, antiviral) were investigated from 370 strains of marine bacteria, fungi, and microalgae obtained from various marine environmental regions in Korea, and the activity results were obtained at the collection site, isolation source, and species level was compared. In the case of marine bacteria, strains belonging to the generally useful genera Streptomyces and Bacillus were observed to have particularly strong efficacy and useful resources were mainly isolated from marine sediments. In the case of marine fungi and microalgae, results showing strong species-specific activity were confirmed, and results showing efficacy-specific activity were also obtained. Based on these results, it is a research result that can facilitate priority access as a strategic material for industrial revitalization and the establishment of a strategy to secure resources based on usefulness when conducting research on chemicals that are selectively effective against specific diseases or when conducting resource-based research. In addition, we believe that by using these results as material for sale through the Marine BioBank (MBB), academia and industry can use them to help accelerate the revitalization of the marine bio industry.

Changes in Soil Physiochemcial Properties Over 11 Years in Larix kaempferi Stands Planted in Larix kaempferi and Pinus rigida Clear-Cut Sites (낙엽송과 리기다소나무 벌채지에 조성된 낙엽송 임분의 11년간 토양 물리·화학적 특성 변화)

  • Nam Jin Noh;Seung-hyun Han;Sang-tae Lee;Min Seok Cho
    • Journal of Korean Society of Forest Science
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    • v.112 no.4
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    • pp.502-514
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    • 2023
  • This study was conducted to understand the long-term changes in soil physiochemical properties and seedling growth in Larix kaempferi (larch) stands planted in clear-cut larch and Pinus rigida (pine) forest soils over an 11-year period after reforestation. Two-year-old bare-root larch seedlings were planted in 2009-2010 at a density of 3,000 seedlings ha-1 in clear-cut areas that harvested larch (Chuncheon and Gimcheon) and pine (Wonju and Gapyeong) stands. We analyzed the physiochemical properties of the mineral soils sampled at 0-20 cm soil depths in the planting year, and the 3rd, 7thand 11th years after planting, and we measured seedling height and root collar diameter in those years. We found significant differences in soil silt and clay content, total carbon and nitrogen concentration, available phosphorus, and cation exchangeable capacity between the two stands; however, seedling growth did not differ. The mineral soil was more fertile in Gimcheon than in the other plantations, while early seedling growth was greatest in Gapyeong. The seedling height and diameter at 11 years after planting were largest in Wonju (1,028 tree ha-1) and Chuncheon (1,359 tree ha-1) due to decreases in stand density after tending the young trees. The soil properties in all plantations were similar 11 years after larch planting. In particular, the high sand content and high available phosphorus levels (caused by soil disturbance during clear-cutting and planting) showed marked decreases, potentially due to soil organic matter input and nutrient uptake, respectively. Thus, early reforestation after clear-cutting could limit nutrient leaching and contribute to soil stabilization. These results provide useful information for nutrient management of larch plantations.

Comparison of NDVI in Rice Paddy according to the Resolution of Optical Satellite Images (광학위성영상의 해상도에 따른 논지역의 정규식생지수 비교)

  • Jeong Eun;Sun-Hwa Kim;Jee-Eun Min
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1321-1330
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    • 2023
  • Normalized Difference Vegetation Index (NDVI) is the most widely used remote sensing data in the agricultural field and is currently provided by most optical satellites. In particular, as high-resolution optical satellite images become available, the selection of optimal optical satellite images according to agricultural applications has become a very important issue. In this study, we aim to define the most optimal optical satellite image when monitoring NDVI in rice fields in Korea and derive the resolution-related requirements necessary for this. For this purpose, we compared and analyzed the spatial distribution and time series patterns of the Dangjin rice paddy in Korea from 2019 to 2022 using NDVI images from MOD13, Landsat-8, Sentinel-2A/B, and PlanetScope satellites, which are widely used around the world. Each data is provided with a spatial resolution of 3 m to 250 m and various periods, and the area of the spectral band used to calculate NDVI also has slight differences. As a result of the analysis, Landsat-8 showed the lowest NDVI value and had very low spatial variation. In comparison, the MOD13 NDVI image showed similar spatial distribution and time series patterns as the PlanetScope data but was affected by the area surrounding the rice field due to low spatial resolution. Sentinel-2A/B showed relatively low NDVI values due to the wide near-infrared band area, and this feature was especially noticeable in the early stages of growth. PlanetScope's NDVI provides detailed spatial variation and stable time series patterns, but considering its high purchase price, it is considered to be more useful in small field areas than in spatially uniform rice paddy. Accordingly, for rice field areas, 250 m MOD13 NDVI or 10 m Sentinel-2A/B are considered to be the most efficient, but high-resolution satellite images can be used to estimate detailed physical quantities of individual crops.

A Study on Estimation of Forest Burn Severity Using Kompsat-3A Images (Kompsat-3A호 영상을 활용한 산불피해 강도 산정에 관한 연구)

  • Minsun Yang;Min-A Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1299-1308
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    • 2023
  • Forest fires are becoming more frequent and larger around the world due to climate change. Remote sensing such as satellite images can be used as an alternative or assistance data because it reduces various difficulties of field survey. Forest burn severity (differenced normalized burn ratio, dNBR) is calculated through the difference in normalized burn ratio (NBR) before and after a forest fire. The images used in the NBR formula are based on Landsat's near-infrared (NIR) and short-wavelength infrared (SWIR) bands. South Korea's satellite images don't have a SWIR band. So domestic studies related to forest burn severity calculated dNBR using overseas images or indirectly using the normalized difference vegetation index (NDVI) using South Korea's satellite images. Therefore, in this study, dNBR was calculated by substituting the mid-wavelength infrared (MWIR) band of Kompsat-3A (K3A) instead of the SWIR band in the NBR formula. The results were compared with the dNBR results obtained through Landsat which is the standard for dNBR formula. As a result, it was shown that dNBR using K3A's MWIR band has a wider range of values and can be expressed in more detail than dNBR using Landsat's SWIR band. Therefore, it is considered that K3A images will be highly useful in surveying burn areas and severity affected by forest fires. In addition, this study used the K3A's MWIR band images degraded to 30 m. It is considered that much better results will be obtained if a higher-resolution MWIR band is used.

Performance Evaluation of Monitoring System for Sargassum horneri Using GOCI-II: Focusing on the Results of Removing False Detection in the Yellow Sea and East China Sea (GOCI-II 기반 괭생이모자반 모니터링 시스템 성능 평가: 황해 및 동중국해 해역 오탐지 제거 결과를 중심으로)

  • Han-bit Lee;Ju-Eun Kim;Moon-Seon Kim;Dong-Su Kim;Seung-Hwan Min;Tae-Ho Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.6_2
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    • pp.1615-1633
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    • 2023
  • Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.

Necessity to incorporate XR-based Training Contents Focused on Cable pulling using Winches in the Shipbuilding (윈치를 활용한 케이블 포설을 중심으로 고찰한 XR 기반 훈련 콘텐츠 도입의 필요성)

  • JongMin Lee;JongSeong Kim
    • Journal of Korea Society of Industrial Information Systems
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    • v.28 no.6
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    • pp.53-62
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    • 2023
  • This paper has suggested the necessity of introducing training contents using XR(Extended reality) technology as a way to lower the high rate of nursing accidents among unskilled technical personnel in domestic shipbuilding industry, focusing on cable pulling using winch. The occurrence rate of nursing accidents in the domestic shipbuilding industry was almost double(197.4%) (2017~2020) when compared with other manufacturing industries. In particular, it is worth noting that more than 31.8% of nursing accidents in the shipbuilding industry occurred among workers whose job experience is no more than 6 months. Most of new workers are seen to have hard time due to several factors such as lack of work information, inexperience, and unfamiliarity with the working environments. This indicates that it is essential to incorporate more effective training method that could help new workers become familiar with technical skills as well as working environments in a short period of time. Currently, education/training at the domestic shipyard is biased toward technical skills such as welding, painting, machine installation, and electrical installation. Contrary, even more important training required to get new workers used to the working environment has remained at a superficial level such as explaining ship building processes using 2D drawings. This may be the reason why it is inevitable to repeat similar training at OJT (On-the-Job Training) even at the leading domestic companies. Domestic shipbuilding industries have been attracting a lot of new workers thanks to recent economic recovery, which is very likely to increase the occurrence of disasters. In this paper, the introduction of training using XR technology was proposed, and as a specific example, the process of pulling cables using winches on ships was implemented as XR-based training content by using Unity. Using the developed content, it demonstrated that new workers can experience the actual work process in advance through simulation in a virtual space, thereby becoming more effective training content that can help new workers become familiar with the work environment.

Efficient Deep Learning Approaches for Active Fire Detection Using Himawari-8 Geostationary Satellite Images (Himawari-8 정지궤도 위성 영상을 활용한 딥러닝 기반 산불 탐지의 효율적 방안 제시)

  • Sihyun Lee;Yoojin Kang;Taejun Sung;Jungho Im
    • Korean Journal of Remote Sensing
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    • v.39 no.5_3
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    • pp.979-995
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    • 2023
  • As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.