We assessed the pesticide residues in the medicinal agricultural products distributed in Korea. Pesticide residues in 72 samples were analyzed using the QuECheRS method for 339 pesticides, using GC-MS/MS and LC-MS/MS. The pesticide residues were below the maximum residues limit (MRL) in 42 samples (58.3%); however, they exceeded the MRL in 5 samples (6.9%). These included 43 types of pesticides; 20 fungicides and 23 insecticides were detected 75 times and 58 times, respectively. Tebuconazole and carbendazim were the most detected fungicides, each 11 times. The levels of acetamiprid, cadusafos, chlorpyrifos, flubendiamide, fluopyram, and triazophos exceeded the MRL in Gogi berry, Omija, and Reishi mushroom. All of them were positive list system (PLS) items that lacked pesticide residue standards. Therefore, authorities should monitor the distributed medicinal agricultural products.
Purpose: The balance between synthesis and degradation of proteins plays a critical role in the maintenance of skeletal muscle mass. Mitochondrial dysfunction has been closely associated with skeletal muscle atrophy caused by aging, cancer, and chemotherapy. Polygalacin D is a saponin derivative isolated from Platycodon grandiflorum (Jacq.) A. DC. This study aimed to investigate the effects of polygalacin D on myoblast differentiation and muscle atrophy in association with mitochondrial function in in vitro and in zebrafish models in vivo. Methods: C2C12 myoblasts were cultured in differentiation media containing different concentrations of polygalacin D, followed by the immunostaining of the myotubes with myosin heavy chain (MHC). The mRNA expression of markers related to myogenesis, muscle atrophy, and mitochondrial function was determined by real-time quantitative reverse transcription polymerase chain reaction. Wild type AB* zebrafish (Danio rerio) embryos were treated with 5-fluorouracil, leucovorin, and irinotecan (FOLFIRI) with or without polygalacin D, and immunostained to detect slow and fast types of muscle fibers. The Tg(Xla.Eef1a1:mitoEGFP) zebrafish expressing mitochondria-targeted green fluorescent protein was used to monitor mitochondrial morphology. Results: The exposure of C2C12 myotubes to 0.1 ng/mL of polygalacin D increased the formation of MHC-positive multinucleated myotubes (≥ 8 nuclei) compared with the control. Polygalacin D significantly increased the expression of MHC isoforms (Myh1, Myh2, Myh4, and Myh7) involved in myoblast differentiation while it decreased the expression of atrophic markers including muscle RING-finger protein-1 (MuRF1), mothers against decapentaplegic homolog (Smad)2, and Smad3. In addition, polygalacin D promoted peroxisome proliferator-activated receptor-gamma coactivator (Pgc1α) expression and reduced the level of mitochondrial fission regulators such as dynamin-1-like protein (Drp1) and mitochondrial fission 1 (Fis1). In a zebrafish model of FOLFIRI-induced muscle atrophy, polygalacin D improved not only mitochondrial dysfunction but also slow and fast muscle fiber atrophy. Conclusion: These results demonstrated that polygalacin D promotes myogenesis and alleviates chemotherapy-induced muscle atrophy by improving mitochondrial function. Thus, polygalacin D could be useful as nutrition support to prevent and ameliorate muscle wasting and weakness.
Over the past 20 years, Korea's overall import and export cargo volume has increased at an average annual rate of approximately 5.3%. About 99% of the cargo is still being transported by sea. Due to recent increases in maritime cargo volume, congestion in maritime logistics has become challenging due to factors such as the COVID-19 pandemic and conflicts. Continuous monitoring of ports has become crucial. Various ground observation systems and Automatic Identification System (AIS) data have been utilized for monitoring ports and conducting numerous preliminary studies for the efficient operation of container terminals and cargo volume prediction. However, small and developing countries' ports face difficulties in monitoring due to environmental issues and aging infrastructure compared to large ports. Recently, with the increasing utility of artificial satellites, preliminary studies have been conducted using satellite imagery for continuous maritime cargo data collection and establishing ocean monitoring systems in vast and hard-to-reach areas. This study aims to visually detect ships docked at berths in the Busan New Port using high-resolution satellite imagery and quantitatively evaluate berth utilization rates. By utilizing high-resolution satellite imagery from Compact Advanced Satellite 500-1 (CAS500-1), Korea Multi-Purpose satellite-3 (KOMPSAT-3), PlanetScope, and Sentinel-2A, ships docked within the port berths were visually detected. The berth utilization rate was calculated using the total number of ships that could be docked at the berths. The results showed variations in berth utilization rates on June 2, 2022, with values of 0.67, 0.7, and 0.59, indicating fluctuations based on the time of satellite image capture. On June 3, 2022, the value remained at 0.7, signifying a consistent berth utilization rate despite changes in ship types. A higher berth utilization rate indicates active operations at the berth. This information can assist in basic planning for new ship operation schedules, as congested berths can lead to longer waiting times for ships in anchorages, potentially resulting in increased freight rates. The duration of operations at berths can vary from several hours to several days. The results of calculating changes in ships at berths based on differences in satellite image capture times, even with a time difference of 4 minutes and 49 seconds, demonstrated variations in ship presence. With short observation intervals and the utilization of high-resolution satellite imagery, continuous monitoring within ports can be achieved. Additionally, utilizing satellite imagery to monitor changes in ships at berths in minute increments could prove useful for small and developing country ports where harbor management is not well-established, offering valuable insights and solutions.
Wooden architectural cultural heritages are one of the visible legacies that show the national's identity. Even when the concept of 'the original' of cultural heritages was not accurately understood, the emphasis of preservation and management of cultural heritages was placed on 'preservation of the original form' or 'maintenance of the original form'. Moreover, these days, following the trend of international preservation principles, cultural heritages are considered important as "values as historical objects." This paper is the result of an attempt to determine the scope and content of what parts should be monitored to maintain the original form of wooden architectural cultural heritage. The first thing to be done in monitoring wooden architectural cultural heritage is to check the condition of the ground and foundation. The second is the column. This is because the instability of the column causes damage to the joint with each member and the fitting part, resulting in physical changes leading to damage to the wall. The third is monitor the roof tiles. If the leak continues into the building due to the separation or damage of the roof, the defect should be partially dismantled and repaired, so it should be monitored to maintain its original shape as much as possible. The monitoring range of the base, column, and roof serves as a reference point for identifying what damage is being done to the relevant cultural heritages. In other words, the data at the time when monitoring began becomes the 'original' for the year. Alternatives based on the analysis of monitoring for the preservation of original cultural heritages should be actively introduced. In addition, by sharing the current state and situation of cultural heritages as a result of monitoring with various related organizations, preventive preservation should be established rather than preservation of cultural heritages by "intervention."
The normalized difference vegetation index (NDVI) derived from satellite images is a crucial tool to monitor forests and agriculture for broad areas because the periodic acquisition of the data is ensured. However, optical sensor-based vegetation indices(VI) are not accessible in some areas covered by clouds. This paper presented a synthetic aperture radar (SAR) based approach to retrieval of the optical sensor-based NDVI using machine learning. SAR system can observe the land surface day and night in all weather conditions. Radar vegetation indices (RVI) from the Sentinel-1 vertical-vertical (VV) and vertical-horizontal (VH) polarizations, surface elevation, and air temperature are used as the input features for an automated machine learning (AutoML) model to conduct the gap-filling of the Sentinel-2 NDVI. The mean bias error (MAE) was 7.214E-05, and the correlation coefficient (CC) was 0.878, demonstrating the feasibility of the proposed method. This approach can be applied to gap-free nationwide NDVI construction using Sentinel-1 and Sentinel-2 images for environmental monitoring and resource management.
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.
Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R2=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.
Hyun-Seung Cho;Jin-Hee Yang;Sang-Yeob Lee;Jeong-Whan Lee;Joo-Hyeon Lee;Hoon Kim
Science of Emotion and Sensibility
/
v.26
no.3
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pp.149-160
/
2023
This study develops a time-varying system-based noncontact fabric sensor that can measure cerebral blood-flow signals to explore the possibility of brain blood-signal detection and emotional evaluation. The textile sensor was implemented as a coil-type sensor by combining 30 silver threads of 40 deniers and then embroidering it with the computer machine. For the cerebral blood-flow measurement experiment, subjects were asked to attach a coil-type sensor to the carotid artery area, wear an electrocardiogram (ECG) electrode and a respiration (RSP) measurement belt. In addition, Doppler ultrasonography was performed using an ultrasonic diagnostic device to measure the speed of blood flow. The subject was asked to wear Meta Quest 2, measure the blood-flow change signal when viewing the manipulated image visual stimulus, and fill out an emotional-evaluation questionnaire. The measurement results show that the textile-sensor-measured signal also changes with a change in the blood-flow rate signal measured using the Doppler ultrasonography. These findings verify that the cerebral blood-flow signal can be measured using a coil-type textile sensor. In addition, the HRV extracted from ECG and PLL signals (textile sensor signals) are calculated and compared for emotional evaluation. The comparison results show that for the change in the ratio because of the activation of the sympathetic and parasympathetic nervous systems due to visual stimulation, the values calculated using the textile sensor and ECG signals tend to be similar. In conclusion, a the proposed time-varying system-based coil-type textile sensor can be used to study changes in the cerebral blood flow and monitor emotions.
Coniferous species in subalpine ecosystems are known to be highly sensitive to climate change. Therefore, it is becoming increasingly important to monitor community and population dynamics. This study monitored 37 plots within the distribution area of Abies koreana on Mt. Jirisan for a period of eight years. We analyzed the importance value, density of living stems, mortality rate, recruitment rate, basal area, DBH (diameter of breast height) class distribution, and tree health status. Our results showed changes in the importance value based on the tree stratum, with A. koreana decreasing by 3.6% and Tripterygium regelii increasing by 2.5% in the tree layer. Between 2015 and 2023, there were 149 dead trees/ha (17.99% mortality rate) and 12 living trees/ha (1.02% recruitment rate) of A. koreana. The decrease in basal area was attributed to a decrease in the number of living trees. Tree mortality occurred in all DBH classes, with a particularly high decline in the <10 cm class (65 trees/ha reduced). In terms of changes in tree health status, the population of alive standing (AS) type trees, initially consisting of 539 trees/ha, has been transformed into alive standing (AS), alive lean (AL), and death standing (DS), accounting for 69.7%, 0.5%, and 13.8%, respectively. Meanwhile, DS-type trees have transitioned into dead broken (DB) and dead fallen (DF) types. This phenomenon is believed to be caused by strong winds in the subalpine region that pull up the rootlets from the soil. Further research on this finding is recommended.
Soon Jik Kwon;Hyeok Yeong Kwon;In Chul Hwang;Chang Su Lee;Tae Geun Kim;Jae Heung Park;Yung Chul Jun
Journal of Wetlands Research
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v.26
no.1
/
pp.21-31
/
2024
Macromia daimoji Okumura, 1949 was designated as an endangered species and also categorized as Class II Endangered wildlife on the International Union for Conservation of Nature (IUCN) Red List in Korea. The spatial distribution of this species ranged within a region delimited by northern latitude from Sacheon-si(35.1°) to Yeoncheon-gun(38.0°) and eastern longitude from Yeoncheon-gun(126.8°) to Yangsan-si(128.9°). They generally prefer microhabitats such as slowly flowing littoral zones of streams, alluvial stream islands and temporarily formed puddles in the sand-based lowland streams. The objectives of this study were to analyze the similarity of benthic macroinvertebrate communities in M. daimoji habitats, to predict the current potential distribution patterns as well as the changes of distribution ranges under global climate change circumstances. Data was collected both from the Global Biodiversity Information Facility (GBIF) and by field surveys from April 2009 to September 2022. We adopted MaxEnt model to predict the current and future potential distribution for M. daimoji using downloaded 19 variables from the WorldClim database. The differences of benthic macroinvertebrate assemblages in the mainstream of Nakdonggang were smaller than those in its tributaries and the other streams, based on the surrounding environments and stream sizes. MaxEnt model presented that potential distribution displayed high inhabiting probability in Nakdonggang and its tributaries. Applying to the future scenarios by Intergovernmental Panel on Climate Change (IPCC), SSP1 scenario was predicted to expand in a wide area and SSP5 scenario in a narrow area, comparing with current potential distribution. M. daimoji is not only directly threatened by physical disturbances (e.g. river development activities) but also vulnerable to rapidly changing climate circumstances. Therefore, it is necessary to monitor the habitat environments and establish conservation strategies for preserving population of M. daimoji.
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