• Title/Summary/Keyword: Heterogeneous conditions

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Altered Gene Expression Profiles in the Lungs of Streptozotocin-induced Diabetic Mice

  • Kim, Jung-Hyun;Rasaei, Roya;Park, Sujin;Kim, Ji-Young;Na, Sunghun;Hong, Seok-Ho
    • Development and Reproduction
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    • v.24 no.3
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    • pp.197-205
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    • 2020
  • Diabetes mellitus is a common heterogeneous metabolic disorder, characterized by deposition of extracellular matrix, oxidative stress, and vascular dysfunction, thereby leading to gradual loss of function in multiple organs. However, little attention has been paid to gene expression changes in the lung under hyperglycemic conditions. In this study, we found that diabetes inuced histological changes in the lung of streptozotocin-induced diabetic mice. Global gene expression profiling revealed a set of genes that are up- and down-regulated in the lung of diabetic mice. Among these, expression of Amigo2, Adrb2, and Zbtb16 were confirmed at the transcript level to correlate significantly with hyperglycemia in the lung. We further evaluated the effect of human umbilical cord-derived perivascular stem cells (PVCs) on these gene expression in the lung of diabetic mice. Our results show that administration of PVC-conditioned medium significantly suppressed Amig2, Adrb2, and Zbtb16 upregulation in these mice, suggesting that these genes may be useful indicators of lung injury during hyperglycemia. Furthermore, PVCs offer a promising alternative cell therapy for treating diabetic complications via regulation of gene expression.

A Study on the Electrochemical Synthesis of L-DOPA Using Oxidoreductase Enzymes: Optimization of an Electrochemical Process

  • Rahman, Siti Fauziyah;Gobikrishnan, Sriramulu;Indrawan, Natarianto;Park, Seok-Hwan;Park, Jae-Hee;Min, Kyoungseon;Yoo, Young Je;Park, Don-Hee
    • Journal of Microbiology and Biotechnology
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    • v.22 no.10
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    • pp.1446-1451
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    • 2012
  • Levodopa or L-3,4-dihydroxyphenylalanine (L-DOPA) is the precursor of the neurotransmitter dopamine. L-DOPA is a famous treatment for Parkinson's disease symptoms. In this study, electroenzymatic synthesis of L-DOPA was performed in a three-electrode cell, comprising a Ag/AgCl reference electrode, a platinum wire auxiliary electrode, and a glassy carbon working electrode. L-DOPA had an oxidation peak at 376 mV and a reduction peak at -550 mV. The optimum conditions of pH, temperature, and amount of free tyrosinase enzyme were pH 7, $30^{\circ}C$, and 250 IU, respectively. The kinetic constant of the free tyrosinase enzyme was found for both cresolase and catacholase activity to be 0.25 and 0.4 mM, respectively. A cyclic voltammogram was used to investigate the electron transfer rate constant. The mean heterogeneous electron transfer rate ($k_e$) was $5.8{\times}10^{-4}$ cm/s. The results suggest that the electroenzymatic method could be an alternative way to produce L-DOPA without the use of a reducing agent such as ascorbic acid.

An Algorithm For Load-Sharing and Fault-Tolerance In Internet-Based Clustering Systems (인터넷 기반 클러스터 시스템 환경에서 부하공유 및 결함허용 알고리즘)

  • Choi, In-Bok;Lee, Jae-Dong
    • The KIPS Transactions:PartA
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    • v.10A no.3
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    • pp.215-224
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    • 2003
  • Since there are various networks and heterogeneity of nodes in Internet, the existing load-sharing algorithms are hardly adapted for use in Internet-based clustering systems. Therefore, in Internet-based clustering systems, a load-sharing algorithm must consider various conditions such as heterogeneity of nodes, characteristics of a network and imbalance of load, and so on. This paper has proposed an expanded-WF algorithm which is based on a WF (Weighted Factoring) algorithm for load-sharing in Internet-based clustering systems. The proposed algorithm uses an adaptive granularity strategy for load-sharing and duplicate execution of partial job for fault-tolerance. For the simulation, the to matrix multiplication using PVM is performed on the heterogeneous clustering environment which consists of two different networks. Compared to other algorithms such as Send, GSS and Weighted Factoring, the proposed algorithm results in an improvement of performance by 55%, 63% and 20%, respectively. Also, this paper shows that It can process the fault-tolerance.

QARA: Quality-Aware Rate Adaptation for Scalable Video Multicast in Multi-Rate Wireless LANs (다중 전송율 무선랜에서의 스케일러블 비디오 멀티캐스트를 위한 품질 기반 전송 속도 적응 기법)

  • Park, Gwangwoo;Jang, Insun;Pack, Sangheon
    • KIPS Transactions on Computer and Communication Systems
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    • v.1 no.1
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    • pp.29-34
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    • 2012
  • Wireless multicast service can be used for video streaming service to save the network resources by sending the same popular multimedia contents to a group of users at once. For better multimedia streaming multicast service, we propose a quality-aware rate adaptation (QARA) scheme for scalable video multicast in rate adaptive wireless networks. In QARA, transmission rate is determined depending on the content's type and users' channel conditions. First, the base layer is transmitted by a low rate for high reliability. That means we provide basic service quality to all users. On the contrary, the transmission rate for enhancement layer is adapted by using channel condition feedback from a randomly selected node. So, the enhancement layer frames in a multimedia content is sent with various transmission rates. Therefore, each node can be provided with differentiated quality services. Consequently, QARA is capable of serving heterogeneous population of mobile nodes. Moreover, it can utilize network resources more efficiently. Our simulation results show that QARA outperforms utilization of the available transmission rate and reduces the data transmission time.

A review on deep learning-based structural health monitoring of civil infrastructures

  • Ye, X.W.;Jin, T.;Yun, C.B.
    • Smart Structures and Systems
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    • v.24 no.5
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    • pp.567-585
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    • 2019
  • In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

The Effects of Sectoral Composition on the Consumption Risk-Sharing via Capital Market for the US case (미국의 주별 산업구조가 소비위험 분산에 미치는 영향에 관한 연구)

  • Lee, Jaehwa;Song, Jeongseok
    • International Area Studies Review
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    • v.13 no.3
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    • pp.51-71
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    • 2009
  • We pursue empirically influential determinants of risk-sharing across various groups in the United States. We consider all the possible combinations out of the eight BEA economic regions and relate the risk-sharing measure for each group to sectoral composition difference under the control of the state-level macroeconomic and financial characteristics. Our results show that more active risk-sharing via cross-ownership market is observed in groups exhibiting more different sectoral composition. The evidence implies that, given other economic and financial conditions equal, economic union tends to share more consumption risk among its members that are more heterogeneous in their sectoral composition. These days, many countries aim to form FTA and other forms of economic integration. We suggest that they should pay attention to sectoral composition for member countries to minimizes income shock in the integrated economy.

A Study on the Mechanical Properties of Interfacial Transition Zone (ITZ) of Lightweight High Strength Concrete Via Nanoindentation (나노 인덴테이션을 통한 경량 고강도 콘크리트 Interfacial Transition Zone (ITZ)의 역학적 특성에 관한 연구)

  • Im, Su-Min;Bae, Sung-Chul
    • Journal of the Korean Recycled Construction Resources Institute
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    • v.8 no.4
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    • pp.537-544
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    • 2020
  • The interfacial transition zone(ITZ) which is the boundary layer between cement composites and aggregates is considered to be the region of gradual transition, heterogeneous, and the weakest part of concrete. For the development of lightweight high strength concrete, it is essential to evaluate the mechanical properties of ITZ between high strength concrete with low water-binder ratio and lightweight aggregates. However, the mechanical properties of ITZ are not well established due to its high porosity and complex structure. Furthermore, the properties of ITZ in concrete using lightweight aggregates are dominated by more various variations (e.g. water-binder ratio, water absorption capacity of aggregate, curing conditions) than normal-weight aggregate concrete. This study aims to elucidate the mechanical properties of ITZ in lightweight high-strength cement composites according to the types of aggregates and the aggregate sizes. Nanoindentation analysis was used to evaluate the elastic modulus of ITZ between high strength cement composites with the water-binder ratio of 0.2 and normal sand, lightweight aggregate with different aggregate siz es of 2mm and 5mm in this study.

Structural Controls on Crustal Fluid Redistribution and Hydrothermal Gold Deposits: A Review on the Suction Pump and Fault Valve Models (지각 내 열수 재분배와 금광상 형성의 구조적 제어: 석션 펌프 및 단층 밸브 모델에 대한 리뷰)

  • Kwak, Yujung;Park, Seung-Ik;Park, Changyun
    • Economic and Environmental Geology
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    • v.55 no.2
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    • pp.183-195
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    • 2022
  • Hydrothermal gold deposits are evidence of intensive fluid flow through fault zones, and the resultant vein structures and textures reflect the fluid redistribution mechanism. This review introduces the suction pump and fault valve models as fluid circulation mechanisms causing hydrothermal gold deposits in the frameworks of the concepts of fault mechanics. The suction pump and fault valve models describe faulting-driven heterogeneous fluid flow and related vein formation mechanisms, accompanied by the cycles of (1) stress accumulation and fluid pressure build-up and (2) seismic rupture and stress/fluid pressure release. The models are available under different geological environments (stress conditions), and the vein structures and textures representing the mechanisms have similarities and differences. The suction pump and fault valve models must help better to interpret the origins of hydrothermal gold deposits in Korea and improve the efficiency of further exploration.

The RNA Base Over 95% of Onju Citrus and Coffee Genes Cut & Paste Based on The BCJM Matrix with Chargaff-Shannon Entropy (BCJM 행렬 및 Chargaff 법칙과 Shannon Entropy에 의한 RNA 유전자 비율이 95%이상인 온주감귤과 귤의 유전자 조합)

  • Lee, Sung Kook;Kim, Jeong Su;Lee, Moon Ho
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.4
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    • pp.415-422
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    • 2022
  • The heterogeneous Onju citrus genes (A=20.57, C=32.71, G=30.01, U=16.71%) and coffee genes (A=20.66, C=31.76, G=30.187, U=16.71%) have the same genetic ratio of 95% or more. It is known that gene compatibility is generally not possible with this group. However, it can be grafted if the conditions of Chargaff rule and Shannon Entropy are met with gene functional-similarity of more than 95%, and it becomes a new breed of Coffrange. We calculated the world's first BCJM matrix for DNA-RNA and published it in US patents and international journals. All animals and viruses are similar to human genes. Based on this, it was announced in June in the British matrix textbook by solving the genetic characteristics of COVID-19 and the human body. In plants, it is treated with BCJM-Transposon treatment, a technique that easily changes gene location. Simulation predicted that the matrix could be successful with Cut & Paste and Transpose.

Barthel's Index: A Better Predictor for COVID-19 Mortality Than Comorbidities

  • da Costa, Joao Cordeiro;Manso, Maria Conceicao;Gregorio Susana;Leite, Marcia;Pinto, Joao Moreira
    • Tuberculosis and Respiratory Diseases
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    • v.85 no.4
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    • pp.349-357
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    • 2022
  • Background: The most consistently identified mortality determinants for the new coronavirus 2019 (COVID-19) infection are aging, male sex, cardiovascular/respiratory diseases, and cancer. They were determined from heterogeneous cohorts that included patients with different disease severity and previous conditions. The main goal of this study was to determine if activities of daily living (ADL) dependence measured by Barthel's index could be a predictor for COVID-19 mortality. Methods: A prospective cohort study was performed with a consecutive sample of 340 COVID-19 patients representing patients from all over the northern region of Portugal from October 2020 to March 2021. Mortality risk factors were determined after controlling for demographics, ADL dependence, admission time, comorbidities, clinical manifestations, and delay-time for diagnosis. Central tendency measures were used to analyze continuous variables and absolute numbers (proportions) for categorical variables. For univariable analysis, we used t test, chi-square test, or Fisher exact test as appropriate (α=0.05). Multivariable analysis was performed using logistic regression. IBM SPSS version 27 statistical software was used for data analysis. Results: The cohort included 340 patients (55.3% females) with a mean age of 80.6±11.0 years. The mortality rate was 19.7%. Univariate analysis revealed that aging, ADL dependence, pneumonia, and dementia were associated with mortality and that dyslipidemia and obesity were associated with survival. In multivariable analysis, dyslipidemia (odds ratio [OR], 0.35; 95% confidence interval [CI], 0.17-0.71) was independently associated with survival. Age ≥86 years (pooled OR, 2.239; 95% CI, 1.100-4.559), pneumonia (pooled OR, 3.00; 95% CI, 1.362-6.606), and ADL dependence (pooled OR, 6.296; 95% CI, 1.795-22.088) were significantly related to mortality (receiver operating characteristic area under the curve, 82.1%; p<0.001). Conclusion: ADL dependence, aging, and pneumonia are three main predictors for COVID-19 mortality in an elderly population.