• Title/Summary/Keyword: Function-Network Matrix

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Differential Gene Expression Common to Acquired and Intrinsic Resistance to BRAF Inhibitor Revealed by RNA-Seq Analysis

  • Ahn, Jun-Ho;Hwang, Sung-Hee;Cho, Hyun-Soo;Lee, Michael
    • Biomolecules & Therapeutics
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    • v.27 no.3
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    • pp.302-310
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    • 2019
  • Melanoma cells have been shown to respond to BRAF inhibitors; however, intrinsic and acquired resistance limits their clinical application. In this study, we performed RNA-Seq analysis with BRAF inhibitor-sensitive (A375P) and -resistant (A375P/Mdr with acquired resistance and SK-MEL-2 with intrinsic resistance) melanoma cell lines, to reveal the genes and pathways potentially involved in intrinsic and acquired resistance to BRAF inhibitors. A total of 546 differentially expressed genes (DEGs), including 239 up-regulated and 307 down-regulated genes, were identified in both intrinsic and acquired resistant cells. Gene ontology (GO) analysis revealed that the top 10 biological processes associated with these genes included angiogenesis, immune response, cell adhesion, antigen processing and presentation, extracellular matrix organization, osteoblast differentiation, collagen catabolic process, viral entry into host cell, cell migration, and positive regulation of protein kinase B signaling. In addition, using the PAN-THER GO classification system, we showed that the highest enriched GOs targeted by the 546 DEGs were responses to cellular processes (ontology: biological process), binding (ontology: molecular function), and cell subcellular localization (ontology: cellular component). Ingenuity pathway analysis (IPA) network analysis showed a network that was common to two BRAF inhibitorresistant cells. Taken together, the present study may provide a useful platform to further reveal biological processes associated with BRAF inhibitor resistance, and present areas for therapeutic tool development to overcome BRAF inhibitor resistance.

A study on the User Experience at Unmanned Checkout Counter Using Big Data Analysis (빅데이터를 활용한 편의점 간편식에 대한 의미 분석)

  • Kim, Ae-sook;Ryu, Gi-hwan;Jung, Ju-hee;Kim, Hee-young
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.4
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    • pp.375-380
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    • 2022
  • The purpose of this study is to find out consumers' perception and meaning of convenience store convenience food by using big data. For this study, NNAVER and Daum analyzed news, intellectuals, blogs, cafes, intellectuals(tips), and web documents, and used 'convenience store convenience food' as keywords for data search. The data analysis period was selected as 3 years from January 1, 2019 to December 31, 2021. For data collection and analysis, frequency and matrix data were extracted using TEXTOM, and network analysis and visualization analysis were conducted using the NetDraw function of the UCINET 6 program. As a result, convenience store convenience foods were clustered into health, diversity, convenience, and economy according to consumers' selection attributes. It is expected to be the basis for the development of a new convenience menu that pursues convenience and convenience based on consumers' meaning of convenience store convenience foods such as appropriate prices, discount coupons, and events.

Comprehensive proteome analysis using quantitative proteomic technologies

  • Kamal, Abu Hena Mostafa;Choi, Jong-Soon;Cho, Yong-Gu;Kim, Hong-Sig;Song, Beom-Heon;Lee, Chul-Won;Woo, Sun-Hee
    • Journal of Plant Biotechnology
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    • v.37 no.2
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    • pp.196-204
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    • 2010
  • With the completion of genome sequencing of several organisms, attention has been focused to determine the function and functional network of proteins by proteome analysis. The recent techniques of proteomics have been advanced quickly so that the high-throughput and systematic analyses of cellular proteins are enabled in combination with bioinformatics tools. Furthermore, the development of proteomic techniques helps to elucidate the functions of proteins under stress or diseased condition, resulting in the discovery of biomarkers responsible for the biological stimuli. Ultimate goal of proteomics orients toward the entire proteome of life, subcellular localization, biochemical activities, and their regulation. Comprehensive analysis strategies of proteomics can be classified as three categories: (i) protein separation by 2-dimensional gel electrophoresis (2-DE) or liquid chromatography (LC), (ii) protein identification by either Edman sequencing or mass spectrometry (MS), and (iii) quanitation of proteome. Currently MS-based proteomics turns shiftly from qualitative proteome analysis by 2-DE or 2D-LC coupled with off-line matrix assisted laser desorption ionization (MALDI) and on-line electrospray ionization (ESI) MS, respectively, to quantitative proteome analysis. Some new techniques which include top-down mass spectrometry and tandem affinity purification have emerged. The in vitro quantitative proteomic techniques include differential gel electrophoresis with fluorescence dyes, protein-labeling tagging with isotope-coded affinity tag, and peptide-labeling tagging with isobaric tags for relative and absolute quantitation. In addition, stable isotope labeled amino acid can be in vivo labeled into live culture cells through metabolic incorporation. MS-based proteomics extends to detect the phosphopeptide mapping of biologically crucial protein known as one of post-translational modification. These complementary proteomic techniques contribute to not only the understanding of basic biological function but also the application to the applied sciences for industry.

Surface-modified Nanoparticle Additives for Wear Resistant Water-based Coatings for Galvanized Steel Plates

  • Becker-Willinger, Carsten;Heppe, Gisela;Opsoelder, Michael;Veith, H.C. Michael;Cho, Jae-Dong;Lee, Jae-Ryung
    • Corrosion Science and Technology
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    • v.9 no.4
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    • pp.147-152
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    • 2010
  • Conventional paints for conversion coating applications in steel production derived mainly from water-based polymer dispersions containing several additives actually show good general performance, but suffer from poor scratch and abrasion resistance during use. The reason for this is because the relatively soft organic binder matrix dominates the mechanical surface properties. In order to maintain the high quality and decorative function of coated steel sheets, the mechanical performance of the surface needs to be improved significantly. In fact the wear resistance should be enhanced without affecting the optical appearance of the coatings by using appropriate nanoparticulate additives. In this direction, nanocomposite coating compositions (Nanomer$^{(R)}$) have been derived from water-based polymer dispersions with an increasing amount of surface-modified nanoparticles in aqueous dispersion in order to monitor the effect of degree of filling with rigid nanoparticles. The surface of nanoparticles has been modified for optimum compatibility with the polymer matrix in order to achieve homogeneous nanoparticle dispersion over the matrix. This approach has been extended in such a way that a more expanded hybrid network has been condensed on the nanoparticle surface by a hydrolytic condensation reaction in addition to the quasi-monolayer type small molecular surface modification. It was expected that this additional modification will lead to more intensive cross-linking in coating systems resulting in further improved scratch-resistance compared to simple addition of nanoparticles with quasi-monolayer surface modification. The resulting compositions have been coated on zinc-galvanized steel and cured. The wear resistance and the corrosion protection of the modified coating systems have been tested in dependence on the compositional change, the type of surface modification as well as the mixing conditions with different shear forces. It has been found out that for loading levels up to 50 wt.-% nanoparticles, the mechanical wear resistance remains almost unaffected compared to the unmodified resin. In addition, the corrosion resistance remained unaffected even after $180^{\circ}$ bending test showing that the flexibility of coating was not decreased by nanoparticle addition. Electron microscopy showed that the inorganic nanoparticles do not penetrate into the organic resin droplets during the mixing process but rather formed agglomerates outside the polymer droplet phase resulting in quite moderate cross linking while curing, because of viscosity. The proposed mechanisms of composite formation and cross linking could explain the poor effect regarding improvement of mechanical wear resistance and help to set up new synthesis strategies for improved nanocomposite morphologies, which should provide increased wear resistance.

A Searching Technique of the Weak Connectivity Boundary using Small Unmanned Aerial Vehicle in Wireless Tactical Data Networks (무선 전술 데이터 네트워크에서 소형 무안항공기를 이용한 연결성 약화 지역 탐색 기법)

  • Li, Jin;Song, Ju-Bin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.1C
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    • pp.89-96
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    • 2012
  • Since tactical robots are going to be grown and tactical data communications will be more network-centric, the reliability of wireless tactical data networks is going to be very important in the future. However, the connectivity of such wireless tactical data networks can be extremely uncertain in practical circumstances. In this paper, we propose a searching technique to find out the weak boundary area of the network connectivity using a small UAV(unmanned aerial vehicle) which has a simple polling access function to wireless nodes on the ground in wireless tactical data networks. The UA V calculates the network topology of the wireless tactical data networks and coverts it to the Lapalcian matrix. In the proposed algorithm, we iteratively search the eigenvalues and find a minimum cut in the network resulting in finding the weak boundary of the connectivity for the wireless tactical data networks. If a UAV works as a relay nodes for the weak area, we evaluate that the throughput performance of the proposed algorithm outperforms star connection method and MST(minimum Spanning Tree) connection method. The proposed algorithm can be applied for recovering the connectivity of wireless tactical data networks.

A Study of Quality Metrics Process Design Methodology for Field Application Encryption under Network Security Environment (네트워크 보안 환경에서의 현장적용 중심 암호품질 만족도 평가 메트릭스 설계 프로세스)

  • Noh, SiChoon;Kim, Jeom goo
    • Convergence Security Journal
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    • v.15 no.5
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    • pp.29-35
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    • 2015
  • The network security encryption type is divided into two, one is point-to-point, second method is link type. The level of security quality attributes are a system security quality requirements in a networked environment. Quality attributes can be observed and should be able to be measured. If the quality requirements can be presented as exact figures, quality requirements are defined specifically setting quality objectives. Functional requirements in the quality attribute is a requirement for a service function which can be obtained through the encryption. Non-functional requirements are requirements of the service quality that can be obtained through the encryption. Encryption quality evaluation system proposed in this study is to derive functional requirements and non-functional requirements 2 groups. Of the calculating measure of the evaluation index in the same category, the associated indication of the quality measure of each surface should be created. The quality matrix uses 2-factor analysis of the evaluation for the associated surface quality measurements. The quality requirements are calculated based on two different functional requirements and non-functional requirements. The results are calculated by analyzing the trend of the average value assessment. When used this way, it is possible to configure the network security encryption based on quality management.

A 2×2 MIMO Spatial Multiplexing 5G Signal Reception in a 500 km/h High-Speed Vehicle using an Augmented Channel Matrix Generated by a Delay and Doppler Profiler

  • Suguru Kuniyoshi;Rie Saotome;Shiho Oshiro;Tomohisa Wada
    • International Journal of Computer Science & Network Security
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    • v.23 no.10
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    • pp.1-10
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    • 2023
  • This paper proposes a method to extend Inter-Carrier Interference (ICI) canceling Orthogonal Frequency Division Multiplexing (OFDM) receivers for 5G mobile systems to spatial multiplexing 2×2 MIMO (Multiple Input Multiple Output) systems to support high-speed ground transportation services by linear motor cars traveling at 500 km/h. In Japan, linear-motor high-speed ground transportation service is scheduled to begin in 2027. To expand the coverage area of base stations, 5G mobile systems in high-speed moving trains will have multiple base station antennas transmitting the same downlink (DL) signal, forming an expanded cell size along the train rails. 5G terminals in a fast-moving train can cause the forward and backward antenna signals to be Doppler-shifted in opposite directions, so the receiver in the train may have trouble estimating the exact channel transfer function (CTF) for demodulation. A receiver in such high-speed train sees the transmission channel which is composed of multiple Doppler-shifted propagation paths. Then, a loss of sub-carrier orthogonality due to Doppler-spread channels causes ICI. The ICI Canceller is realized by the following three steps. First, using the Demodulation Reference Symbol (DMRS) pilot signals, it analyzes three parameters such as attenuation, relative delay, and Doppler-shift of each multi-path component. Secondly, based on the sets of three parameters, Channel Transfer Function (CTF) of sender sub-carrier number n to receiver sub-carrier number l is generated. In case of n≠l, the CTF corresponds to ICI factor. Thirdly, since ICI factor is obtained, by applying ICI reverse operation by Multi-Tap Equalizer, ICI canceling can be realized. ICI canceling performance has been simulated assuming severe channel condition such as 500 km/h, 8 path reverse Doppler Shift for QPSK, 16QAM, 64QAM and 256QAM modulations. In particular, 2×2MIMO QPSK and 16QAM modulation schemes, BER (Bit Error Rate) improvement was observed when the number of taps in the multi-tap equalizer was set to 31 or more taps, at a moving speed of 500 km/h and in an 8-pass reverse doppler shift environment.

Face Recognition using Eigenfaces and Fuzzy Neural Networks (고유 얼굴과 퍼지 신경망을 이용한 얼굴 인식 기법)

  • 김재협;문영식
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.41 no.3
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    • pp.27-36
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    • 2004
  • Detection and recognition of human faces in images can be considered as an important aspect for applications that involve interaction between human and computer. In this paper, we propose a face recognition method using eigenfaces and fuzzy neural networks. The Principal Components Analysis (PCA) is one of the most successful technique that have been used to recognize faces in images. In this technique the eigenvectors (eigenfaces) and eigenvalues of an image is extracted from a covariance matrix which is constructed form image database. Face recognition is Performed by projecting an unknown image into the subspace spanned by the eigenfaces and by comparing its position in the face space with the positions of known indivisuals. Based on this technique, we propose a new algorithm for face recognition consisting of 5 steps including preprocessing, eigenfaces generation, design of fuzzy membership function, training of neural network, and recognition. First, each face image in the face database is preprocessed and eigenfaces are created. Fuzzy membership degrees are assigned to 135 eigenface weights, and these membership degrees are then inputted to a neural network to be trained. After training, the output value of the neural network is intupreted as the degree of face closeness to each face in the training database.

Performance Evaluation of Loss Functions and Composition Methods of Log-scale Train Data for Supervised Learning of Neural Network (신경 망의 지도 학습을 위한 로그 간격의 학습 자료 구성 방식과 손실 함수의 성능 평가)

  • Donggyu Song;Seheon Ko;Hyomin Lee
    • Korean Chemical Engineering Research
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    • v.61 no.3
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    • pp.388-393
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    • 2023
  • The analysis of engineering data using neural network based on supervised learning has been utilized in various engineering fields such as optimization of chemical engineering process, concentration prediction of particulate matter pollution, prediction of thermodynamic phase equilibria, and prediction of physical properties for transport phenomena system. The supervised learning requires training data, and the performance of the supervised learning is affected by the composition and the configurations of the given training data. Among the frequently observed engineering data, the data is given in log-scale such as length of DNA, concentration of analytes, etc. In this study, for widely distributed log-scaled training data of virtual 100×100 images, available loss functions were quantitatively evaluated in terms of (i) confusion matrix, (ii) maximum relative error and (iii) mean relative error. As a result, the loss functions of mean-absolute-percentage-error and mean-squared-logarithmic-error were the optimal functions for the log-scaled training data. Furthermore, we figured out that uniformly selected training data lead to the best prediction performance. The optimal loss functions and method for how to compose training data studied in this work would be applied to engineering problems such as evaluating DNA length, analyzing biomolecules, predicting concentration of colloidal suspension.

Expression and Function of Calcineurin in Inflammatory Arthritis (류마티스 관절염에서 칼시뉴린의 발현과 기능)

  • Park, Bo-Hyoung;Yoo, Seung-Ah;Hong, Kyung-Hee;Hyoung, Bok-Jin;Hwang, Yu-Na;Cho, Chul-Soo;Park, Won;Kim, Wan-Uk
    • IMMUNE NETWORK
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    • v.6 no.1
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    • pp.33-42
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    • 2006
  • Background: Calcineurin plays a crucial role in T cell activation, cell growth, apoptosis, and angiogenesis, and its over-expression has been implicated in the pathogenesis of cardiomyopathy and stroke. However, the expression and function of calcineurin in the pathologic lesion of chronic inflammatory diseases, like rheumatoid synovium, remain to be defined. This study was aimed to determine the role of calcineurin in inflammatory arthritis and investigate the expression and function of calcineurin in the rheumatoid synovium and synoviocytes, the actual site of chronic inflammation. Methods: Immuno-histochemical staining using specific antibody to calcineurin was perfomed in the synovium of rheumatoid arthritis (RA). Fibroblast-like synoviocytes (FLS) from RA and osteoarthritis (OA) patients were isolated from RA and OA patients, and cultured with IL-1${\beta}$ and TNF-${\alpha}$ in the presence or absence of cyclosporin A, a calcineurin inhibitor. The calcineurin expression was assessed by phosphatase assay and Western blotting analysis. IL-6, -10, -17, matrix metalloproteinase (MMP)-1, -2, -3, and -9 released into the culture supernatants were measured by ELISA. After transfection with GFP-Cabin 1 gene into synoviocytes, the levels of IL-6 and MMPs were measured by ELISA. Results: Calcineurin was highly expressed in the lining layer of synovium and cultured synoviocytes of RA patients. The elevated calcineurin activity in the rheumatoid synoviocytes was triggered by proin flammatory cytokines such as IL-1${\beta}$ and TNF-${\alpha}$. In contrast, IL-10, an anti-inflammatory cytokine, failed to increase the calcineurin activity. The targeted inhibition of calcineurin by the over-expression of Cabin 1, a natural calcineurin antagonist, inhibited the production of IL-6 and MMP-2 by rheumatoid synoviocytes in a similar manner to the calcineurin inhibitor, cyclosporin A. Conclusion: These data suggest that abnormal activation of calcineurin in the synoviocytes may contribute to the pathogenesis of chronic arthritis, and thus provide a potential target for controlling inflammatory arthritis.