• Journal of Microbiology and Biotechnology
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• v.33 no.12
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• pp.1635-1647
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• 2023

Muscle atrophy, which is defined as a decrease in muscle mass and strength, is caused by an imbalance between the anabolism and catabolism of muscle proteins. Thus, modulating the homeostasis between muscle protein synthesis and degradation represents an efficient treatment approach for this condition. In the present study, the protective effects against muscle atrophy of ethanol extracts of Morus alba L. (MA) and Angelica keiskei Koidz. (AK) leaves and their mixtures (MIX) were evaluated in vitro and in vivo. Our results showed that MIX increased 5-aminoimidazole-4-carboxamide ribonucleotide-induced C2C12 myotube thinning, and enhanced soleus and gastrocnemius muscle thickness compared to each extract alone in dexamethasone-induced muscle atrophy Sprague Dawley rats. In addition, although MA and AK substantially improved grip strength and histological changes for dexamethasone-induced muscle atrophy in vivo, the efficacy was superior in the MIX-treated group. Moreover, MIX further increased the expression levels of myogenic factors (MyoD and myogenin) and decreased the expression levels of E3 ubiquitin ligases (atrogin-1 and muscle-specific RING finger protein-1) in vitro and in vivo compared to the MA- and AK-alone treatment groups. Furthermore, MIX increased the levels of phosphorylated phosphoinositide 3-kinase (PI3K), protein kinase B (Akt), and mammalian target of rapamycin (mTOR) that were reduced by dexamethasone, and downregulated the expression of forkhead box O3 (FoxO3a) induced by dexamethasone. These results suggest that MIX has a protective effect against muscle atrophy by enhancing muscle protein anabolism through the activation of the PI3K/Akt/mTOR signaling pathway and attenuating catabolism through the inhibition of FoxO3a.

• Journal of Life Science
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• v.34 no.3
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• pp.153-159
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• 2024

Dioscorea alata L, commonly known as "tropical yam" is the most widely consumed yam species among the 650 yam species belonging to the Dioscoreacea family. It is extensively cultivated in tropical and subtropical regions and is a major food source in Africa and India. Also, it is used for medicinal purposes, particularly in China and Taiwan, for its anti-inflammatory properties. In comparison to other yam varieties such as D. batatas or D. opposita, the tropical yam has gained popularity in Korea due to its higher yield per unit area. In this study, the nutritional characteristics and anti-thrombosis activity of the aerial bulbils of D. alata L. tropical yam were compared to those of D. opposita. The results showed that the aerial bulbils of tropical yam exhibited nutritional characteristics and potent anticoagulant activity compared to those of domestic yam varieties. The bulbils extract of tropical yam showed superior anticoagulant activities against thrombin, prothrombin and blood coagulation factors. Furthermore, the bulbils extract of tropical yam exhibited strong platelet aggregation inhibition at 0.25 mg/ml and showed no hemolytic activity up to a concentration of 2.5 mg/ml. These findings suggest the potential development of high-value anti-thrombosis agents utilizing the aerial bulbils of tropical yam.

• Korean Journal of Optics and Photonics
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• v.35 no.4
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• pp.150-156
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• 2024

One of the key factors in research regarding long-distance laser beam propagation, as in free-space optical communication or laser power transmission, is the transmission efficiency of the laser beam. As a way to improve efficiency, we perform extensive numerical simulations of the effect of modifying the laser beam's profile, especially replacing the fundamental Gaussian beam with a super-Gaussian beam. Numerical simulations of the transmitted power in the ideal diffraction-limited beam diameter determined by the optical system of the transmitter, after about 1-km propagation, reveal that the second-order super-Gaussian beam can yield superior performance to that of the fundamental Gaussian beam, in both single-channel and coherently combined multi-channel laser transmitters. The improvement of the transmission efficiency for a 1-km propagation distance when using a second-order super-Gaussian beam, in comparison with a fundamental Gaussian beam, is estimated at over 1.2% in the singlechannel laser transmitter, and over 4.2% and over 4.6% in coherently combined 3- and 7-channel laser transmitters, respectively. For a range of the propagation distance varying from 750 to 1,250 m, the improvement in transmission efficiency by use of the second-order super-Gaussian beam is estimated at over 1.2% in the single-channel laser transmitter, and over 4.1% and over 4.0% in the coherently combined 3- and 7-channel laser transmitters, respectively. These simulation results will pave the way for future advances in the generation of higher-order super-Gaussian beams and the development of long-distance optical energy-transfer technology.

• Journal of the Society of Disaster Information
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• v.20 no.3
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• pp.549-562
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• 2024

Purpose: In this study, numerical analysis was conducted to verify the vibration reduction effect of installing vibration barriers under various installation conditions to mitigate train-induced vibrations from the GTX. Method: To identify the factors influencing vibration reduction among the installation conditions, the stiffness ratio of the filling material and the installation depth of the barrier were varied. Result: The study results indicated that using ductile filling materials provided superior vibration reduction compared to hard filling materials. The vibration reduction effect was found to be more significant when the stiffness ratio between the ground and the filling material was closer to zero. Additionally, the deeper the installation depth of the barrier, the better the vibration reduction effect. Conversely, if the barrier was installed too shallowly, vibration at the measurement point was amplified. Conclusion: The optimal installation condition for vibration reduction was found to be a stiffness ratio of 0.08 and an installation depth of 15 meters, resulting in a vibration reduction rate of 60.34% at a measurement point 10 meters away from the vibration source.

• Journal of Periodontal and Implant Science
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• v.54 no.4
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• pp.236-252
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• 2024

Purpose: Enamel matrix derivative (EMD) has demonstrated beneficial effects on wound healing following surgery. However, the effects of recombinant human fibroblast growth factor 2 (rhFGF-2) in periodontal regeneration therapy have not been extensively studied. This retrospective study was conducted to compare the wound healing outcomes of the modified papilla preservation technique (mPPT) between EMD and rhFGF-2 therapies. Methods: A total of 79 sites were evaluated for early wound healing using the modified early wound healing index (mEHI), which included 6 items: incision, fibrin clotting, step, redness, swelling, and dehiscence. A numeric analog scale, along with postoperative images of the 6 mEHI items, was established and used for the evaluations. The inter-rater reliability of the mEHI was assessed via intraclass correlation coefficients (ICCs). After adjusting for factors influencing the mPPT, the differences in mEHI scores between the EMD and rhFGF-2 groups were statistically analyzed. Additionally, radiographic bone fill (RBF) was evaluated 6 months after surgery. Results: The ICC of the mEHI was 0.575. The mEHI, redness score, and dehiscence scores were significantly higher in the rhFGF-2 group (n=33) than in the EMD group (n=46). Similar results were observed in the subgroup of patients aged 50 years or older, but not in those younger than 50 years. In the subgroup with non-contained bone defects, related results were noted, but not in the subgroup with contained bone defects. However, early wound healing did not correlate with RBF at 6 months after surgery. Conclusions: Within the limitations of this study, the findings suggest that early wound healing following the use of mPPT with rhFGF-2 is somewhat superior to that observed after mPPT with EMD. However, mEHI should be improved for use as a predictive tool for early wound healing and to reflect clinical outcomes after surgery.

• The Transactions of the Korea Information Processing Society
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• v.13 no.9
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• pp.395-403
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• 2024

Recently, with the advancement of technology, the automotive industry has seen an increase in network connectivity. CAN (Controller Area Network) bus technology enables fast and efficient data communication between various electronic devices and systems within a vehicle, providing a platform that integrates and manages a wide range of functions, from core systems to auxiliary features. However, this increased connectivity raises concerns about network security, as external attackers could potentially gain access to the automotive network, taking control of the vehicle or stealing personal information. This paper analyzed abnormal messages occurring in CAN and confirmed that message occurrence periodicity, frequency, and data changes are important factors in the detection of abnormal messages. Through DBC decoding, the specific meanings of CAN messages were interpreted. Based on this, a model for classifying abnormalities was proposed using the GRU model to analyze the periodicity and trend of message occurrences by measuring the difference (residual) between the predicted and actual messages occurring within a certain period as an abnormality metric. Additionally, for multi-class classification of attack techniques on abnormal messages, a Random Forest model was introduced as a multi-classifier using message occurrence frequency, periodicity, and residuals, achieving improved performance. This model achieved a high accuracy of over 99% in detecting abnormal messages and demonstrated superior performance compared to other existing models.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.5
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• pp.519-532
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• 2024

Anomaly detection for the penetration rate of tunnel boring machines (TBMs) is crucial for effective risk management in TBM tunnel projects. However, previous machine learning models for predicting the penetration rate have struggled with imbalanced data between normal and abnormal penetration rates. This study aims to enhance the performance of machine learning-based anomaly detection for the penetration rate by utilizing a data augmentation technique to address this data imbalance. Initially, six input features were selected through correlation analysis. The lowest and highest 10% of the penetration rates were designated as abnormal classes, while the remaining penetration rates were categorized as a normal class. Two prediction models were developed, each trained on an original training set and an oversampled training set constructed using SMOTE (synthetic minority oversampling technique): an XGB (extreme gradient boosting) model and an XGB-SMOTE model. The prediction results showed that the XGB model performed poorly for the abnormal classes, despite performing well for the normal class. In contrast, the XGB-SMOTE model consistently exhibited superior performance across all classes. These findings can be attributed to the data augmentation for the abnormal penetration rates using SMOTE, which enhances the model's ability to learn patterns between geological and operational factors that contribute to abnormal penetration rates. Consequently, this study demonstrates the effectiveness of employing data augmentation to manage imbalanced data in anomaly detection for TBM penetration rates.

• Korean Chemical Engineering Research
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• v.58 no.2
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• pp.197-208
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• 2020

This study was carried out to analyze spatial and temporal incidence characteristics of scrub typhus and predict the future incidence of scrub typhus since the incidences of scrub typhus have been rapidly increased among vector-borne diseases. A maximum entropy (MaxEnt) ecological model was implemented to predict spatial distribution and incidence rate of scrub typhus using spatial data sets on environmental and social variables. Additionally, relationships between the incidence of scrub typhus and critical spatial data were analyzed. Elevation and temperature were analyzed as dominant spatial factors which influenced the growth environment of Leptotrombidium scutellare (L. scutellare) which is the primary vector of scrub typhus. A temporal number of diseases by scrub typhus was predicted by a deep neural network (DNN). The model considered the time-lagged effect of scrub typhus. The DNN-based prediction model showed that temperature, precipitation, and humidity in summer had significant influence factors on the activity of L. scutellare and the number of diseases at fall. Moreover, the DNN-based prediction model had superior performance compared to a conventional statistical prediction model. Finally, the spatial and temporal models were used under climate change scenario. The future characteristics of scrub typhus showed that the maximum incidence rate would increase by 8%, areas of the high potential of incidence rate would increase by 9%, and disease occurrence duration would expand by 2 months. The results would contribute to the disease management and prediction for the health of residents in terms of public health.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.93-100
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• 2010

Trip generation is the first step in the conventional four-step model and has great effects on overall demand forecasting, so accuracy really matters at this stage. A linear regression model is widely used as a current trip generation model for such plans as urban transportation and SOC facilities, assuming that the relationship between each socio-economic index and trip generation stays linear. But when rapid urban development or an urban planning structure has changed, socio-economic index data for trip estimation may be lacking to bring many errors in estimated trip. Hence, instead of assuming that a socio-economic index widely used for a general purpose, this study aims to develop a new trip generation model by type based on the market separation for the variables to reflect the characteristics of various zones. The study considered the various characteristics (land use, socio-economic) of zones to enhance the forecasting accuracy of a trip generation model, the first-step in forecasting transportation demands. For a market separation methodology to improve forecasting accuracy, data mining (CART) on the basis of trip generation was used along with a regression analysis. Findings of the study indicated as follows : First, the analysis of zone characteristics using the CART analysis showed that trip production was under the influence of socio-economic factors (men-women relative proportion, age group (22 to 29)), while trip attraction was affected by land use factors (the relative proportion of business facilities) and the socio-economic factor (the relative proportion of third industry workers). Second, model development by type showed as a result that trip generation coefficients revealed 0.977 to 0.987 (trip/person) for "production" 0.692 to 3.256 (trip/person) for "attraction", which brought the necessity for type classifications. Third, a measured verification was conducted, where "production" and "attraction" showed a higher suitability than the existing model. The trip generation model by type developed in this study, therefore, turned out to be superior to the existing one.

• The Korean Journal of Food And Nutrition
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• v.28 no.2
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• pp.228-240
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• 2015

This study was conducted to investigate the dietary and other factors affecting bone mineral density (BMD) in older Korean women. A total of 340 women aged 65 to 74 were recruited from the Kugoksoondam area (Kurye, Goksung, Soonchang and Damyang counties), known as the longevity-belt region in Jeonla province, Korea. They were categorized into two groups according to bone status by T-score : a nonosteoporotic group and an osteoporotic group. Demographic characteristics were collected, as well as information on physical measurements, blood tests for biochemical indicators, health status health-related life style, dietary behavior, favorite food groups, nutrient intake and mini nutrition assessment (MNA). The results are as follows: The mean age of 185 nonosteoporotic women was 69.6 years and that of 155 osteoporotic women was 70.9 years (p<0.001). The mean T-score of the nonosteoporotic group was $-1.5mg/cm^3$ and that of theosteoporotic group was $-3.2mg/cm^3$ (p<0.001). Height and body weight in the nonosteoporotic group were significantly higher than in the osteoporotic group (p<0.001, respectively). There was no significant difference in BMI, although the BMI in the nonosteoporotic group was slightly higher. Waist and hip circumferences in the nonosteoporotic group were significantly higher than in the osteoporotic group (p<0.01, respectively), and the mid upper arm and calf circumferences were also significantly higher than in the osteoporotic group (p<0.001, p<0.01, respectively). The 5 m walking ability was significantly superior compared to the osteoporotic group. Serum levels did not show any significant differences between the groups and were within normal range. The serum total protein, albumin and Insulin-like growth factor (IGFs) levels of the nonosteoporotic group were significantly higher than those of the osteoporotic group (p<0.05, p<0.05, p<0.001, respectively). IGF was 104.7 ng/mL for the nonosteoporotic group and 88.1 ng/mL for the osteoporotic group. Physical activity and appetite in the nonosteoporotic group were significantly higher (p<0.01, p<0.05, respectively). The favorite food groups of the nonosteoporotic group comprised more meats and fish than those of the osteoporotic group (p<0.05, respectively). Nutrient intake was not significantly different, with the exception of niacin intake (p<0.05), but the nutrient intake of the nonosteoporotic group was slightly higher than that of the osteoporotic group. The niacin intake of the nonosteoporotic group and the osteoporotic group were 11.4 mgNE and 10.0 mgNE, corresponding to 103.6% and 90.9% of the Korean EAR, respectively. The MNA score of the nonosteoporotic group was significantly more favorable than for the osteoporotic group. In conclusion, it is necessary to maintain adequate body weight and muscle mass. Habitual physical activity may have a beneficial effect on BMD for older women. Dietary factors, such as meat and fish, higher intake of niacin rich foods and nutrient status for older women also appear to have favorable effects on bone mineral density.