• The Korean Journal of Physiology
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• v.2 no.1
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• pp.23-30
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• 1968

Tissue homogenates of 12 kinds of human cancer tissues were incubated separately in medium containing $C^{14}-1-glucose$ and $C^{14}-6-glucose$ as a substrate in order to observe the oxidative pathway of glucose in the tumor tissues. At the end of 3 hours incubation in the Dubnuff metabolic shaking incubator, respiratory $CO_2$ samples trapped by alkaling which was placed in the center well of incubation flask were analysed for total $CO_2$ production rates and their radioactivities. The tissue homogenate samples after incubation were analyzed for their concentrations of glucose, lactate and pyruvate. Calculations were made on the glucose consumption rate and accumulation rates of lactate and pyruvate. Fractionation of oxidative pathway of glucose was carried out by calculating $C^{14}O_2 yields from C-1 and C-6 carbon of glucose. The following results were obtained. 1. In 12 kinds of human cancer, total $CO_2$ production rates were less than $8{\mu}M/gm$ except 2 cases. These lower values impressed that oxidative metabolism in the tumor tissues generally inhibited as compared with that in normal tissues. On the other hand, fractions of $CO_2$ derived from glucose to total $CO_2$ production rates (RSA) were less than 10% in every case. These facts showed that oxidation of glucose into $CO_2$ was remarkably inhibited in the tumor tissues. 2. Factions of glucose disappeared into $CO_2\;(RGD_{CO_2})$, lactate $(RGD_L)$, pyruvate $(RGD_P)$ to glucose consumption rates were as follows. $RGD_{CO_2}$ were less than 2% in cases of in this experiment and $RGD_L$ showed more than 5% except in 2 cases. These facts showed that anaerobic degradation of glucose into 3 carbon compounds was easily proceeded but further degradation into $CO_2$ via the TCA cycle was greatly inhibited resulting in accumulation of lactate. There are large variation in values of $RGD_P$ in different kinds of tumor tissue but relatively higher values in $RGD_{CO_2}$ were obtained in the tumor tissues as compared with those of normal tissues. 3. The oxidative pathway of glucose in tumor tissues were analyzed from the values of RSA which were obtained in $C^{14}-1\;and\;C^{14}-6-glucose$ incubation experiments. It was found that 3% of $CO_2$ derived from glucose were oxidized via the principal EMP-TCA cycle and the remainder were via alternate pathway such as HMP in the liver cancer and values in other cancer tissues were as follows; 4% in the tongue cancer, 6% in the colon cancer, 6% in the lung cancer, 9% in the stomach cancer, 11% in the ovarian cancer, 12% in the neck tumor, 22% in the uterine cancer, 22% in the bladder tumor, 32% in the spindle cell sarcoma and 65% in the brain tumor. These values except later 2 cases showed less than 30% which is the lowest value among the normal tissues. Even in the brain tumor in which showed highest value in the tumor group. It is reasonable to suppose that this fraction was remarkably decreased because values in normal brain tissue was more than 90%. From the above data, it was concluded that in tumor tissues, oxidation of glucose via TCA cycle was greatly inhibited but correlation between degree of inhibited oxidation of glucose via TCA cycle and malignancy of tumor were not clarified in this experiments.

• Journal of Life Science
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• v.33 no.3
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• pp.242-251
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• 2023

The purpose of this study was to investigate the effects of 8-week β-hydroxybutyrate (β-HB) administration with and without endurance exercise training on endurance exercise performance and skeletal muscle protein synthesis and degradation using a mouse model. Forty-eight male wild-type ICR mice (8 weeks old) were randomly divided into four groups: sedentary control (Sed+Con), (Sed+Con), sedentary β-HB (Sed+β-HB), exercise control (Exe+Con), and exercise β-HB (Exe+β-HB). β-HB was dissolved in PBS (150 mg/ml) and injected subcutaneously daily (250 mg/kg) for 8 weeks. Mice performed 5 days/week of a 20 min treadmill running exercise for 8 weeks. The running exercise was carried out at a speed of 10 m/min at a 10° incline for 5 min, and then the speed was increased by 1 m/min for every 1 min of the remaining 15 min. Following 8 weeks of treatments, visceral fat mass and skeletal muscle mass, blood parameters, and the markers for autophagy and protein synthesis were analyzed. The data were analyzed with one-way ANOVA (p<0.05) using the SPSS 21 program. Eight weeks of Exe+β-HB treatment significantly lowered blood lactate levels compared with the other three groups (Sed+Con, Sed+β-HB, and Exe+β-HB) Exe+β-HB) (p<0.05). Eight weeks of Exe+β-HB significantly increased maximal running time (time to exhaustion) compared with the Sed+Con and Exe+Con groups (p<0.05). Eight weeks of β-HB administration significantly decreased autophagy flux and autophagy-related proteins in the skeletal muscle of mice (p<0.05). Conversely, the combined treatment of β-HB and endurance exercise training increased protein synthesis (mTOR signaling and translation) (p<0.05). The 8-week β-HB treatment and endurance exercise training had synergistic effects on the increase in endurance performance, increase in protein synthesis, and decrease in protein degradation in the skeletal muscle of mice.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.193-205
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• 2023

A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.

• Journal of the Korean earth science society
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• v.36 no.2
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• pp.139-157
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• 2015

We investigated the relative errors of satellite-observed Surface Skin Temperature (SST) data caused by sea ice in the northern hemispheric ocean ($30-90^{\circ}N$) during April 16-24, 2003-2014 by intercomparing MODerate Resolution Imaging Spectroradiometer (MODIS) Ice Surface Temperature (IST) data with two types of Atmospheric Infrared Sounder (AIRS) SST data including one with the AIRS/Advanced Microwave Sounding Unit-A (AMSU) and the other with 'AIRS only'. The MODIS temperatures, compared to the AIRS/AMSU, were systematically up to ~1.6 K high near the sea ice boundaries but up to ~2 K low in the sea ice regions. The main reason of the difference of skin temperatures is that the MODIS algorithm used infrared channels for the sea ice detection (i.e., surface classification), while microwave channels were additionally utilized in the AIRS/AMSU. The 'AIRS only' algorithm has been developed from NASA's Goddard Space Flight Center (NASA/GSFC) to prepare for the degradation of AMSU-A by revising part of the AIRS/AMSU algorithm. The SST of 'AIRS only' compared to AIRS/AMSU showed a bias of 0.13 K with RMSE of 0.55 K over the $30-90^{\circ}N$ region. The difference between AIRS/AMSU and 'AIRS only' was larger over the sea ice boundary than in other regions because the 'AIRS only' algorithm utilized the GCM temperature product (NOAA Global Forecast System) over seasonally-varying frozen oceans instead of the AMSU microwave data. Three kinds of the skin temperatures consistently showed significant warming trends ($0.23-0.28Kyr^{-1}$) in the latitude band of $70-80^{\circ}N$. The systematic disagreement among the skin temperatures could affect the discrepancies of their trends in the same direction of either warming or cooling.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Journal of Microbiology
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• v.44 no.6
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• pp.622-631
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• 2006

In this study we purified a fibrinolytic enzyme from Cordyceps militaris using a combination of ion-exchange chromatography on a DEAE Sephadex A-50 column, gel filtration chromatography on a Sephadex G-75 column, and FPLC on a HiLoad 16/60 Superdex 75 column. This purification protocol resulted in a 191.8-fold purification of the enzyme and a final yield of 12.9 %. The molecular mass of the purified enzyme was estimated to be 52 kDa by SDS-PAGE, fibrin-zymography, and gel filtration chromatography. The first 19 amino acid residues of the N-terminal sequence were ALTTQSNV THGLATISLRQ, which is similar to the subtilisin-like serine protease PR1J from Metarhizium anisopliae var. anisopliase. This enzyme is a neutral protease with an optimal reaction pH and temperature of 7.4 and $37^{\circ}C$, respectively. Results for the fibrinolysis pattern showed that the enzyme rapidly hydrolyzed the fibrin $\alpha$-chain followed by the $\gamma$-$\gamma$ chains. It also hydrolyzed the $\beta$-chain, but more slowly. The A$\alpha$, B$\beta$, and $\gamma$ chains of fibrinogen were also cleaved very rapidly. We found that enzyme activity was inhibited by $Cu^{2+}$ and $Co^{2+}$, but enhanced by the additions of $Ca^{2+}$ and $Mg^{2+}$ ions. Furthermore, fibrinolytic enzyme activity was potently inhibited by PMSF and APMSF. This enzyme exhibited a high specificity for the chymotrypsin substrate S-2586 indicating it's a chymotrypsin-like serine protease. The data we present suggest that the fibrinolytic enzyme derived from the edible and medicinal mushroom Cordyceps militaris has fibrin binding activity, which allows for the local activation of the fibrin degradation pathway.

• IMMUNE NETWORK
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• v.4 no.1
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• pp.23-30
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• 2004

Background: A human orthologue of mouse S100A6-binding protein (CacyBP), Siah-1-interacting protein (SIP) had been shown to be a component of novel ubiquitinylation pathway regulating $\beta$-catenin degradation. The role of the protein seems to be important in cell proliferation and cancer evolution but the expression pattern of SIP in actively dividing cancer tissues has not been known. For the elucidation of the role of SIP protein in carcinogenesis, it is essential to produce monoclonal antibodies specific to the protein. Methods: cDNA sequence coding for ORF region of human SIP gene was amplified and cloned into an expression vector to produce His-tag fusion protein. Recombinant SIP protein and monoclonal antibody to the protein were produced. The N-terminal specificity of anti-SIP monoclonal antibody was conformed by immunoblot analysis and enzyme linked immunosorbent assay (ELISA). To study the relation between SIP and colon carcinogenesis, the presence of SIP protein in colon carcinoma tissues was visualized by immunostaining using the monoclonal antibody produced in this study. Results: His-tag-SIP (NSIP) recombinant protein was produced and purified. A monoclonal antibody (Korea patent pending; #2003-45296) to the protein was produced and employed to analyze the expression pattern of SIP in colon carcinoma tissues. Conclusion: The data suggested that anti-SIP monoclonal antibody produced here was valuable for the diagnosis of colon carcinoma and elucidation of the mechanism of colon carcinogenesis.

• Korean Journal of Environment and Ecology
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• v.27 no.3
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• pp.344-356
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• 2013

This study is a continuation of the 22 year consecutive study (1972~1993) to monitor community dynamics of forest in Mt. Kwanak. This study was intended to provide basic data for urban forest management in the future by analyzing actual changes in vegetation structure of forest in Mt. Kwanak caused by urban environmental changes. For the past 39 years (1972~2010), average temperature increased by approximate between 1.1 and $1.7^{\circ}C$ and soil acidification (pH $5.40{\rightarrow}4.50$) and contents of $K^+$ ($0.67{\rightarrow}0.25$) and $Ca^{{+}{+}}$ ($3.20{\rightarrow}0.87$) apparently tended to decrease. According to analysis importance percentage and DBH class of community types classified based on DCA, the succession stopped at Quercus mongolica for 39 years. In addition, the succession was expected to be held at Q. mongolica or to shift from Pinus densiflora to Q. mongolica and from Q. acutissima to Q. serrata. Size of trees growing in forest of Mt. Kwanak increased but the number of species and population of trees showed a downward trend for the 39 years and Styrax japonica and Sorbus alnifolia, which are indicator species, increased their dominance continuously. Decrease in contents of $K^+$, $Ca^{{+}{+}}$, and $Mg^{{+}{+}}$ and soil acidification for the past 39 years was found to affect degradation of vegetation structure in Mt. Kwanak.

• Journal of the Korean GEO-environmental Society
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• v.13 no.11
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• pp.81-91
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• 2012

This paper mainly deals with the analysis of probabilistic characteristics of the disturbed function proposed to predict dynamic behavior of Geosynthetic-soil interface as the lining and cover systems used in waste landfills. Calibration and statistical property estimation of the parameters in the disturbed function model were first performed using many experimental data obtained from a new multi-purpose interface apparatus (M-PIA). In order to analyze the effect due to changes in chemical degradation and normal loads condition, probabilistic properties such as mean, coefficient of variation and distribution type of the disturbed function were evaluated using both the LHS method known to be a very efficient sampling scheme and the estimated statistical property of A and Z. As a result, variation of the disturbed function is found to range approximately from 10~28% according to the level of ${\xi}_D$ and Weibull appears to be the most adequate distribution type at almost all levels of ${\xi}_D$. It is concluded that a probabilistic safety assessment method for Geosynthetic-soil interface considering uncertainty in shear strength can be developed by utilizing probabilistic properties of the disturbed function obtained in this study.

• Journal of the Korean Society of Propulsion Engineers
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• v.2 no.2
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• pp.14-23
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• 1998

The present study investigates numerically particle laden flow through compressor cascade. In general, a lot of turbine engines are affected by various particles which are suspending in the atmosphere. Especially in the case of aircraft aviating in volcanic, industrial and desert region including many particles, each components of engine system are damaged severely. That damage modes are erosion of compressor binding and rotor path components, partial or total blockage of cooling passage and engine control system degradation.. Initial damages can not be serious but cumulation of damages influences on safety of aircraft control and economical maintenance cost of engine system can be increased. When dust, materials and volcanic particles in the atmosphere flow in the compressor, it is necessary to predict damaged and deposited region of compressor blades. To the various flow inlet angle, predictions of particles trajectory in compressor cascade by Lagrangian method are presented and impulses by impaction of particles at blade surface are calculated. By the definition of particle deposition efficiency, characteristics of particles impact are considered quantitatively. With these prediction and experimental data, erosion rates are predicted for two materials - ceramic, soft metal - on compressor blade surface. Improvements like coating of blade surface could be found, by above prediction.