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Differentiation of acute and chronic hepatitis B in IgM antiHBc positive patients

World Journal of Gastroenterology 2015年第13期21卷 3953-3959页

作者： Ji Won Park Kyeong Min Kwak Sung Eun kim myoung Kuk Jang Dong joon kim Myung Seok Lee Hyoung Su kim Choong Kee Park Department of Internal Medicine Hallym University Medical CenterAnyang 431-070South Korea Department of Occupational and Environmental Medicine Hallym University Medical CenterAnyang 431-070South Korea Department of Internal Medicine Hallym University Sacred Heart Hospital of Hallym University Medical Center Seoul 134-701South Korea Department of Internal Medicine Hallym University Medical CenterChuncheon 200-704South Korea

AIM: To identify the factors that differentiate acute hepatitis B(AHB) from chronic hepatitis B with acute exacerbation(CHB-AE).METHODS: From 2004 to 2013, a total of 82 patients(male n = 52, 63.4%; female n = 30, 36.6%) with clinical features of acute hepatitis with immunoglobulin M antibodies to the hepatitis B core antigen(Ig M antiHBc) were retrospectively enrolled and divided into two groups; AHB(n = 53) and CHB-AE(n = 29). The AHB group was defined as patients without a history of hepatitis B virus(HBV) infection before the episode and with loss of hepatitis B surface antigen within 6 mo after onset of acute hepatitis. Biochemical and virological profiles and the sample/cutoff(S/CO) ratio of Ig M anti-HBc were compared to determine the differential diagnostic ***: The multivariate analysis demonstrated that, the S/CO ratio of Ig M anti-HBc and HBV DNA levels were meaningful factors. The S/CO ratio of Ig M anti-HBc was significantly higher in the AHB group, while the HBV DNA level was significantly higher in the CHB-AE group. The optimal cutoff values of Ig M anti-HBc and HBV DNA levels for differentiating the two conditions were 8 S/CO ratio and 5.5 log10 IU/m L, respectively. The sensitivity and specificity were 96.2% and 89.7% for the S/CO ratio of Ig M anti-HBc and 81.1% and 72.4% for HBV DNA levels, respectively. The area under receiver operating characteristic curves of both the S/CO ratio of Ig M anti-HBc and HBV DNA levels were not significantly different(0.933 vs 0.844, P = 0.105). When combining Ig M anti-HBc and HBV DNA, the diagnostic power significantly improved compared to HBV DNA alone(P = 0.0056). The combination of these factors yielded a sensitivity and specificity of 98.1% and 86.2%, ***: The combination of the S/CO ratio of Ig M anti-HBc and HBV DNA levels was a useful tool for differentiating AHB from CHB-AE in patients with positive Ig M anti-HBc.

关键词： Acute hepatitis Differential diagnosis Chronic hep

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Effect of BainiticTreatment on Microstructure and Mechanical Properties of TRIP Cold-Rolled Steel Sheets

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Journal of Iron and Steel Research International 2011年第S1期18卷 1004-1007页

作者： kim Sung-joon Korea Institute of Machinery Science Changwon 641010Korea

The effects of bainitic treatment on microstructure and mechanical properties of 0.10C-1.5Mn-l.5Al TRIP-aided cold-rolled steels have been *** samples were heated by intercritical annealing at 820℃for 2 min and quenched in banitic temperature with different hoding time for 5 to 300s,two salt bath were used for the heat *** results show that the yield strength and elongation increase with the increasing of bainitic holding time,while the tensile strength *** volume fraction of retained austenite rise at the beginning of bainitic holding and then reduce,the carbon content of retained austenite increase during the bainitic *** tensile strengthen multiply elongation reaches the highest value at *** mechanical stability of retained austenite fits well with strain hardening during deformation.

关键词： TRIP bainitic treatment microstructure mechanical properties retained austenite

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Targeting the RAS/RAF/MAPK pathway for cancer therapy: from mechanism to clinical studies

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Signal Transduction and Targeted Therapy 2024年第1期9卷 173-210页

作者： Md Entaz Bahar Hyun joon kim Deok Ryong kim Department of Biochemistry and Convergence Medical Sciences and Institute of Medical Science Gyeongsang National UniversityCollege of MedicineJinjuSouth Korea Department of Anatomy and Convergence Medical Sciences and Institute of Medical Science Gyeongsang National UniversityCollege of MedicineJinjuSouth Korea

Metastatic dissemination of solid tumors,a leading cause of cancer-related mortality,underscores the urgent need for enhanced insights into the molecular and cellular mechanisms underlying metastasis,chemoresistance,and the mechanistic backgrounds of individuals whose cancers are prone to *** most prevalent signaling cascade governed by multi-kinase inhibitors is the mitogen-activated protein kinase(MAPK)pathway,encompassing the RAS–RAF–MAPK kinase(MEK)–extracellular signal-related kinase(ERK)*** kinase is a primary mediator of the MAPK pathway,responsible for the sequential activation of downstream targets,such as MEK and the transcription factor ERK,which control numerous cellular and physiological processes,including organism development,cell cycle control,cell proliferation and differentiation,cell survival,and *** in this signaling cascade are associated with diseases such as *** inhibitors(RAFi)combined with MEK blockers represent an FDAapproved therapeutic strategy for numerous RAF-mutant cancers,including melanoma,non-small cell lung carcinoma,and thyroid ***,the development of therapy resistance by cancer cells remains an important ***,an intracellular lysosome-dependent catabolic recycling process,plays a critical role in the development of RAFi resistance in ***,targeting RAF and autophagy could be novel treatment strategies for RAF-mutant *** this review,we delve deeper into the mechanistic insights surrounding RAF kinase signaling in tumorigenesis and ***,we explore and discuss the ongoing development of next-generation RAF inhibitors with enhanced therapeutic ***,this review sheds light on the functional interplay between RAF-targeted therapies and autophagy in cancer.

关键词： RAF insight mechanism

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Byte Frequency Based Indicators for Crypto-Ransomware Detection from Empirical Analysis

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Journal of Computer Science & Technology 2022年第2期37卷 423-442页

作者： Geun Yong kim joon-Young Paik Yeongcheol kim Eun-Sun Cho Department of Computer Science and Engineering Chungnam National UniversityDaejeon 34134South Korea School of Computer Science and Technology Tiangong UniversityTianjin 300387China

File entropy is one of the major indicators of crypto-ransomware because the encryption by ransomware increases the randomness of file ***,entropy-based ransomware detection has certain limitations;for example,when distinguishing ransomware-encrypted files from normal files with inherently high-level entropy,misclassification is very *** addition,the entropy evaluation cost for an entire file renders entropy-based detection impractical for large *** this paper,we propose two indicators based on byte frequency for use in ransomware detection;these are termed EntropySA and DistSA,and both consider the interesting characteristics of certain file subareas termed“sample areas”(SAs).For an encrypted file,both the sampled area and the whole file exhibit high-level randomness,but for a plain file,the sampled area embeds informative structures such as a file header and thus exhibits relatively low-level randomness even though the entire file exhibits high-level *** and DistSA use“byte frequency”and a variation of byte frequency,respectively,derived from sampled *** indicators cause less overhead than other entropy-based detection methods,as experimentally proven using realistic ransomware *** evaluate the effectiveness and feasibility of our indicators,we also employ three expensive but elaborate classification models(neural network,support vector machine and threshold-based approaches).Using these models,our experimental indicators yielded an average Fl-measure of 0.994 and an average detection rate of 99.46%for file encryption attacks by realistic ransomware samples.

关键词： computer security cryptography machine learning ransomware

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A mass and energy estimation for the hydrogen utilization in the iron-making process

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Science China(Technological Sciences) 2011年第7期54卷 1655-1660页

作者： Wan Ho kim Dong joon MIN Department of Materials Science and Engineering YONSEI University

The possibility of using hydrogen to lower CO 2 emissions in the iron-making process was confirmed by the heat and mass balances in the blast furnace operation. The mass and heat balances for hydrogen utilization in the blast furnace were estimated by using the basic concept of RIST operating diagram. In this study, the RIST operating diagram was modified to be suitable for representing the operation with respect to hydrogen, where the RIST operating diagram is a graphical representation of heat and mass balance in blast furnace operation. RIST operating diagram was applied here to some individual parameters of interest such as H 2 injection in blast furnace process to reduce coke (carbon consumption). It was observed that the point W moved to the right in the RIST operating diagram under the condition of increasing hydrogen injection at tuyere, which originates from the contribution of gas composition (O/H 2 ) equilibrated with Fe/FeO at a certain temperature. Point P also moved downward due to heat requirement with respect to hydrogen utilization, by which the new RIST operating diagram for hydrogen utilization was able to be constructed. Under the condition of hydrogen injection, the expected overall carbon consumption in the blast furnace decreased due to the contribution of hydrogen.

关键词： hydrogen carbon consumption (CO2 emission) mass and heat balances RIST operating diagram blast furnace

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A Universal Activation Function for Deep Learning

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Computers, Materials & Continua 2023年第5期75卷 3553-3569页

作者： Seung-Yeon Hwang Jeong-joon kim Department of Computer Engineering Anyang UniversityAnyang-si14028Korea Department of ICT Convergence Engineering Anyang UniversityAnyang-si14028Korea

Recently,deep learning has achieved remarkable results in fields that require human cognitive ability,learning ability,and reasoning *** functions are very important because they provide the ability of artificial neural networks to learn complex patterns through *** activation functions are being studied to solve problems such as vanishing gradients and dying nodes that may occur in the deep learning ***,it takes a lot of time and effort for researchers to use the existing activation function in their ***,in this paper,we propose a universal activation function(UA)so that researchers can easily create and apply various activation functions and improve the performance of neural *** can generate new types of activation functions as well as functions like traditional activation functions by properly adjusting three *** famous Convolutional Neural Network(CNN)and benchmark datasetwere used to evaluate the experimental performance of the UA proposed in this *** compared the performance of the artificial neural network to which the traditional activation function is applied and the artificial neural network to which theUA is *** addition,we evaluated the performance of the new activation function generated by adjusting the hyperparameters of *** experimental performance evaluation results showed that the classification performance of CNNs improved by up to 5%through the UA,although most of them showed similar performance to the traditional activation function.

关键词： Deep learning activation function convolutional neural network benchmark datasets universal activation function

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Data Augmentation Using Contour Image for Convolutional Neural Network

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Computers, Materials & Continua 2023年第6期75卷 4669-4680页

作者： Seung-Yeon Hwang Jeong-joon kim Department of Computer Engineering Anyang UniversityAnyang-si14058Korea Department of ICT Convergence Engineering Anyang UniversityAnyang-si14058Korea

With the development of artificial intelligence-related technologies such as deep learning,various organizations,including the government,are making various efforts to generate and manage big data for use in artificial ***,it is difficult to acquire big data due to various social problems and restrictions such as personal information *** are many problems in introducing technology in fields that do not have enough training data necessary to apply deep learning ***,this study proposes a mixed contour data augmentation technique,which is a data augmentation technique using contour images,to solve a problem caused by a lack of ***,a famous convolutional neural network(CNN)architecture,and CIFAR-10,a benchmark data set,are used for experimental performance evaluation to prove the superiority of the proposed *** to prove that high performance improvement can be achieved even with a small training dataset,the ratio of the training dataset was divided into 70%,50%,and 30%for comparative *** a result of applying the mixed contour data augmentation technique,it was possible to achieve a classification accuracy improvement of up to 4.64%and high accuracy even with a small amount of data *** addition,it is expected that the mixed contour data augmentation technique can be applied in various fields by proving the excellence of the proposed data augmentation technique using benchmark datasets.

关键词： Data augmentation image classification deep learning convolutional neural network mixed contour image benchmark dataset

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A Deep Learning Hierarchical Ensemble for Remote Sensing Image Classification

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Computers, Materials & Continua 2022年第8期72卷 2649-2663页

作者： Seung-Yeon Hwang Jeong-joon kim Department of Computer Engineering Anyang UniversityAnyang-si14028Korea Department of ICT Convergence Engineering Anyang UniversityAnyang-si14028Korea

Artificial intelligence,which has recently emerged with the rapid development of information technology,is drawing attention as a tool for solving various problems demanded by society and *** particular,convolutional neural networks(CNNs),a type of deep learning technology,are highlighted in computer vision fields,such as image classification and recognition and object *** these CNN models requires a large amount of data,and a lack of data can lead to performance degradation problems due to *** CNN architecture development and optimization studies become active,ensemble techniques have emerged to perform image classification by combining features extracted from multiple CNN *** this study,data augmentation and contour image extraction were performed to overcome the data shortage *** addition,we propose a hierarchical ensemble technique to achieve high image classification accuracy,even if trained from a small amount of ***,we trained the UCMerced land use dataset and the contour images for each image on pretrained VGGNet,GoogLeNet,ResNet,DenseNet,and *** then apply a hierarchical ensemble technique to the number of cases in which each model can be *** experiments were performed in cases where the proportion of training datasets was 30%,50%,and 70%,resulting in a performance improvement of up to 4.68%compared to the average accuracy of the entire model.

关键词： Image classification deep learning CNNs hierarchical ensemble UC-Merced land use dataset contour image

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Is the filamentary dark cloud GF 6 a star forming region?--Stability analysis and infrared properties

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Research in Astronomy and Astrophysics 2017年第12期17卷 77-88页

作者： Jaeheon kim Hyun-Goo kim Sang joon kim Bo Zhang Shanghai Astronomical Observatory Chinese Academy of SciencesShanghai 200030China Korea Astronomy and Space Science Institute Daejeon 34055Korea Department of Astronomy and Space Science Kyung Hee UniversityYongin 17104Korea

We present the results of mapping observations and stability analyses toward the filamentary dark cloud GF 6. We investigate the internal structures of a typical filamentary dark cloud GF 6 to know whether the filamentary dark cloud will form stars. We perform radio observations with both 12CO（J =1–0） and 13CO（J =1–0） emission lines to examine the mass distribution and its evolutionary *** 13CO gas column density map shows eight subclumps in the GF 6 region with sizes on a sub-pc scale. The resulting local thermodynamic equilibrium masses of all the subclumps are too low to form stars against the turbulent dissipation. We also investigate the properties of embedded infrared point sources to know whether they are newly formed stars. The infrared properties also indicate that these point sources are not related to star forming activities associated with GF 6. Both radio and infrared properties indicate that the filamentary dark cloud GF 6 is too light to contract gravitationally and will eventually be dissipated away.

关键词： ISM:clouds ISM:molecules radio lines:ISM infrared:ISM Instabilities Turbulence

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Fe_(3)GeTe_(2):a site-differentiated Hund metal

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npj Computational Materials 2022年第1期8卷 2355-2360页

作者： Taek Jung kim Siheon Ryee Myung joon Han Department of Physics KAISTDaejeon34141Republic of Korea I.Institute of Theoretical Physics University of HamburgNotkestrasse 9-11Hamburg22607Germany

Magnetism in two-dimensional(2D)van der Waals(vdW)materials has lately attracted considerable attention from the point of view of both fundamental science and device ***,establishing a detailed and solid understanding of their magnetism is the key first step toward various *** Fe_(3)GeTe_(2)is a representative ferromagnetic(FM)metal in this family,many aspects of its magnetic and electronic behaviors still remain ***,we report our new finding that Fe_(3)GeTe_(2)is a special type of correlated metal known as“Hund metal”.Furthermore,we demonstrate that Hund metallicity in this material is quite unique by exhibiting remarkable site dependence of Hund correlation strength,hereby dubbed“site-differentiated Hund metal”.Within this new picture,many of the previous experiments can be clearly understood,including the ones that were seemingly contradictory to one another.

关键词： strength establishing metallic

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