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Chondrogenesis of periodontal ligament stem cells by transforming growth factor-β3 and bone morphogenetic protein-6 in a normal healthy impacted third molar

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International Journal of Oral Science 2013年第1期5卷 7-13页

作者： Sunyoung Choi Tae-Jun Cho Soon-Keun Kwon Gene Lee Jaejin Cho Laboratory of Developmental Biology and Stem Cell Differentiation/Transplantation Department of Dental Regenerative BiotechnologySchool of DentistrySeoul National University Dental Research Institute School of DentistrySeoul National University Laboratory of Molecular Genetics School of DentistrySeoul National University

The periodontal ligament-derived mesenchymal stem cell is regarded as a source of adult stem cells due to its ***, the proof of chondrogenic potential of the cells is ***,we investigated the chondrogenic differentiation capacity of periodontal ligament derived mesenchymal stem cells induced by transforming growth factor(TGF)-p3 and bone morphogenetic protein(BMP)-*** isolation of periodontal ligament stem cells(PDLSCs) from human periodontal ligament,the cells were cultured in Dulbecco’s modified Eagle’s medium(DMEM) with 20%fetal bovine serum(FBS).A mechanical force initiated chondrogenic differentiation of the *** chondrogenic differentiation,10μg·LTGF-β3 or 100μg·LBMP-6 and the combination treating group for synergistic effect of the growth *** analyzed the PDLSCs by fluorescence-activated cell sorting and chondrogenesis were evaluated by glycosaminoglycans assay,histology,immunohistochemistry and genetic *** showed mesenchymal stem cell properties proved by FACS *** contents were increased 217%by TGF-β3 and 220%by BMP-6. The synergetic effect of TGF-β3 and BMP-6 were shown up to 281%compared to *** combination treatment increased Sox9, aggrecan and collagen II expression compared with not only controls,but also TGF-P3 or BMP-6 single treatment *** histological analysis also indicated the chondrogenic differentiation of PDLSCs in our *** results of the present study demonstrate the potential of the dental stem cell as a valuable cell source for chondrogenesis,which may be applicable for regeneration of cartilage and bone fracture in the field of cell therapy.

关键词： bone morphogenetic protein-6 chondrogenesis growth factor periodental ligament cell stem cell transforming growth factor-β3

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Effect of Length Scale Tuning of Background Error in WRF-3DVAR System on Assimilation of High-Resolution Surface Data for Heavy Rainfall Simulation

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Advances in Atmospheric Sciences 2012年第6期29卷 1142-1158页

作者： Ji-Hyun HA Dong-Kyou LEE Atmospheric Sciences Program School of Earth and Environmental SciencesSeoul National UniversitySeoul 151-747Korea

We investigated the impact of tuning the length scale of the background error covariance in the Weather Research and Forecasting （WRF） three-dimensional variational assimilation （3DVAR） system. In particular, we studied the effect of this parameter on the assimilation of high-resolution surface data for heavy rainfall forecasts associated with mesoscale convective systems over the Korean Peninsula. In the assimilation of high-resolution surface data, the National Meteorological Center method tended to exaggerate the length scale that determined the shape and extent to which observed information spreads out. In this study, we used the difference between observation and background data to tune the length scale in the assimilation of high-resolution surface data. The resulting assimilation clearly showed that the analysis with the tuned length scale was able to reproduce the small-scale features of the ideal field effectively. We also investigated the effect of a double-iteration method with two different length scales, representing large and small-length scales in the WRF-3DVAR. This method reflected the large and small-scale features of observed information in the model fields. The quantitative accuracy of the precipitation forecast using this double iteration with two different length scales for heavy rainfall was high; results were in good agreement with observations in terms of the maximum rainfall amount and equitable threat scores. The improved forecast in the experiment resulted from the development of well-identified mesoscale convective systems by intensified low-level winds and their consequent convergence near the rainfall area.

关键词： WRF 3DVAR tuning surface data heavy rainfall

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Machine Learning-Based Two-Stage Data Selection Scheme for Long-Term Influenza Forecasting

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Computers, Materials & Continua 2021年第9期68卷 2945-2959页

作者： Jaeuk Moon Seungwon Jung Sungwoo Park Eenjun Hwang school of Electrical Engineering Korea UniversitySeoul02841Korea

One popular strategy to reduce the enormous number of illnesses and deaths from a seasonal influenza pandemic is to obtain the influenza vaccine on ***,vaccine production preparation must be done at least six months in advance,and accurate long-term influenza forecasting is essential for *** diverse machine learning models have been proposed for influenza forecasting,they focus on short-term forecasting,and their performance is too dependent on input *** a country’s longterm influenza forecasting,typical surveillance data are known to be more effective than diverse external data on the *** propose a two-stage data selection scheme for worldwide surveillance data to construct a longterm forecasting model for influenza in the target *** the first stage,using a simple forecasting model based on the country’s surveillance data,we measured the change in performance by adding surveillance data from other countries,shifted by up to 52 *** the second stage,for each set of surveillance data sorted by accuracy,we incrementally added data as input if the data have a positive effect on the performance of the forecasting model in the first *** the selected surveillance data,we trained a new longterm forecasting model for influenza and perform influenza forecasting for the target *** conducted extensive experiments using six machine learning models for the three target countries to verify the effectiveness of the proposed *** report some of the results.

关键词： Influenza data selection machine learning forecasting

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Effective Denoising Architecture for Handling Multiple Noises

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Computer Systems Science & Engineering 2023年第3期44卷 2667-2682页

作者： Na Hyoun Kim Namgyu Kim The Graduate school of Business IT of Kookmin University Seoul02707Korea

Object detection,one of the core research topics in computer vision,is extensively used in various industrial *** there have been many studies of daytime images where objects can be easily detected,there is relatively little research on nighttime *** the case of nighttime,various types of noises,such as darkness,haze,and light blur,deteriorate image ***,an appropriate process for removing noise must precede to improve object detection *** there are many studies on removing individual noise,only a few studies handle multiple noises *** this paper,we pro-pose a convolutional denoising autoencoder(CDAE)-based architecture trained on various types of *** also present various composing modules for each noise to improve object detection performance for night *** the exclusively dark(ExDark)Image dataset,experimental results show that the Sequentialfiltering architecture showed superior mean average precision(mAP)compared to other architectures.

关键词： Object detection computer vision nighttime multiple noises convolutional denoising autoencoder

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Regional Economic Development Trend Prediction Method Based on Digital Twins and Time Series Network

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Computers, Materials & Continua 2023年第8期76卷 1781-1796页

作者： Runguo Xu Xuehan Yu Xiaoxue Zhao school of International Relations Yonsei UniversitySeoul03722Korea

At present,the interpretation of regional economic development(RED)has changed from a simple evaluation of economic growth to a focus on economic growth and the optimization of economic structure,the improvement of economic relations,and the change of institutional *** article uses the RED trend as the research object and constructs the RED index to conduct the theoretical *** this paper uses the attention mechanism based on digital twins and the time series network model to verify the actual ***,the regional economy is predicted according to the theoretical *** specific research work mainly includes the following aspects:1)This paper introduced the development status of research on time series networks and economic forecasting at home and abroad.2)This paper introduces the basic principles and structures of long and short-term memory(LSTM)and convolutional neural network(CNN),constructs an improved CNN-LSTM model combined with the attention mechanism,and then constructs a regional economic prediction index system.3)The best parameters of the model are selected through experiments,and the trained model is used for simulation experiment *** results show that the CNN-LSTM model based on the attentionmechanism proposed in this paper has high accuracy in predicting regional economies.

关键词： Regional economic development attention mechanism digital twins time series network

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Graph Construction Method for GNN-Based Multivariate Time-Series Forecasting

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Computers, Materials & Continua 2023年第6期75卷 5817-5836页

作者： Wonyong Chung Jaeuk Moon Dongjun Kim Eenjun Hwang school of Electrical Engineering Korea UniversitySeoul02841Korea

Multivariate time-series forecasting(MTSF)plays an important role in diverse real-world *** achieve better accuracy in MTSF,time-series patterns in each variable and interrelationship patterns between variables should be considered ***,graph neural networks(GNNs)has gained much attention as they can learn both patterns using a *** accurate forecasting through GNN,a well-defined graph is ***,existing GNNs have limitations in reflecting the spectral similarity and time delay between nodes,and consider all nodes with the same weight when constructing *** this paper,we propose a novel graph construction method that solves aforementioned *** first calculate the Fourier transform-based spectral similarity and then update this similarity to reflect the time ***,we weight each node according to the number of edge connections to get the final graph and utilize it to train the GNN *** experiments on various datasets,we demonstrated that the proposed method enhanced the performance of GNN-based MTSF models,and the proposed forecasting model achieve of up to 18.1%predictive performance improvement over the state-of-the-art model.

关键词： Deep learning graph neural network multivariate time-series forecasting

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DAVS:Dockerfile Analysis for Container Image Vulnerability Scanning

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Computers, Materials & Continua 2022年第7期72卷 1699-1711页

作者： Thien-Phuc Doan Souhwan Jung school of Electronic Engineering Soongsil UniversitySeoul06978Korea

Container technology plays an essential role in many Information and Communications Technology(ICT)***,containers face a diversity of threats caused by vulnerable packages within container *** vulnerability scanning solutions for container images are *** solutions entirely depend on the information extracted from package *** a result,packages installed directly from the source code compilation,or packages downloaded from the repository,etc.,are *** introduce DAVS–A Dockerfile analysis-based vulnerability scanning framework for OCI-based container images to deal with the limitations of existing *** performs static analysis using file extraction based on Dockerfile information to obtain the list of Potentially Vulnerable Files(PVFs).The PVFs are then scanned to figure out the vulnerabilities in the target container *** experimental shows the outperform of DAVS on detecting Common Vulnerabilities and Exposures(CVE)of 10 known vulnerable images compared to Clair–the most popular container image scanning ***,DAVS found that 68%of real-world container images are vulnerable from different image registries.

关键词： Container security vulnerability scanning OCI image analysis

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FET-based nanobiosensors for the detection of smell and taste

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Science China(Life Sciences) 2020年第8期63卷 1159-1167页

作者： Dongseok Moon Yeon Kyung Cha So-ong Kim Seongyeon Cho Hwi Jin Ko Tai Hyun Park school of Chemical and Biological Engineering Institute of Chemical ProcessesSeoul National UniversitySeoul 08826Republic of Korea Interdisciplinary Program for Bioengineering Seoul National UniversitySeoul 08826Republic of Korea

Various nanobiosensors composed of biomaterials and nanomaterials have been developed,due to their demonstrated advantage of showing high *** various biomaterials for biological recognition elements of the nanobiosensor,sensory receptors,such as olfactory and taste receptors,are promising biomaterials for developing nanobiosensors,because of their high selectivity to target ***-effect transistors(FET)with nanomaterials such as carbon nanotube(CNT),graphene,and conducting polymer nanotube(CPNT),can be combined with the biomaterials to enhance the sensitivity of ***,many efforts have been made to develop nanobiosensors using biomaterials,such as olfactory receptors and taste receptors for detecting various smells and *** review focuses on the biomaterials and nanomaterials used in nanobiosensor systems and studies of various types of nanobiosensor platforms that utilize olfactory receptors and taste receptors which could be applied to a wide range of industrial fields,including the food and beverage industry,environmental monitoring,the biomedical field,and anti-terrorism.

关键词： nanobiosensor olfactory receptor taste receptor field-effect transistor(FET)

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Fatigue strength evaluation of self-piercing riveted joints of AZ31 Mg alloy and cold-rolled steel sheets

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Journal of Magnesium and Alloys 2020年第1期8卷 241-251页

作者： Se-Hyung Kang Dong-Woon Han Ho-Kyung Kim Graduate school Seoul National University of Science and TechnologySeoul01811South Korea Department of Mechanical and Automotive Engineering Seoul National University of Science and TechnologySeoul01811 South Korea

The application of magnesium alloys to automobiles is increasing due to their superior specific strength and specific *** this study,an upper sheet of AZ31 magnesium alloy and a lower sheet of cold-rolled steel were joined by self-piercing riveting(SPR),a method commonly used to join automotive panels.A cross-shaped specimen was fabricated with a punching force of 35 kN,which exhibited the best joint strength for the SPR joint specimen *** and fatigue strengths were evaluated using cross-shaped specimens at loading angles of 0°,45°,and 90°.The load amplitude corresponding to the fatigue endurance limit was assumed to be at 106 cycles,and the fatigue ratios(=fatigue endurance limit/static strength)at the loading angles of 0°,45°,and 90°are 22%,13%,and 9%,*** all three loading angle specimens,fatigue cracks initiated at the triple point where the rivet shank,the upper sheet and the lower sheet are in contact with each other,with the cracks propagating through the thickness of the upper sheet and ultimately leading to *** fatigue lifetimes were evaluated through the von-Mises stress,maximum principal stress,and equivalent stress intensity *** was found that the fatigue lifetimes could be evaluated most appropriately through the maximum principal stress.

关键词： Self-piercing riveting Magnesium alloy Fatigue strength Maximum principal stress Fatigue lifetime

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Efficient Autonomous Defense System Using Machine Learning on Edge Device

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Computers, Materials & Continua 2022年第2期70卷 3565-3588页

作者： Jaehyuk Cho school of Electronic Engineering Soongsil UniversitySeoul06978Korea

As a large amount of data needs to be processed and speed needs to be improved,edge computing with ultra-low latency and ultra-connectivity is emerging as a new *** changes can lead to new cyber risks,and should therefore be considered for a security threat *** this end,we constructed an edge system to study security in two directions,hardware and ***,on the hardware side,we want to autonomically defend against hardware attacks such as side channel attacks by configuring field programmable gate array(FPGA)which is suitable for edge computing and identifying communication status to control the communication method according to *** addition,on the software side,data collected on the server performs end-to-end encryption via symmetric encryption ***,we modeled autonomous defense systems on the server by using machine learning which targets to incoming and outgoing *** log utilizes existing intrusion detection datasets that should be used in real-world *** log was used to detect intrusion early by modeling an intrusion prevention system to identify behaviors that violate security policy,and to utilize the existing intrusion detection data set that should be used in a real *** this,we designed an efficient autonomous defense system that can provide a stable system by detecting abnormal signals from the device and converting them to an effective method to control edge computing,and to detect and control abnormal intrusions on the server side.

关键词： Autonomous defense side channel attack intrusion prevention system edge computing machine learning

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