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Zan, Hong,Zhang, Jinsong,Ardeshna, Sona,Xu, Zhenming,Park, Seok-Rae,Casali, Paolo Harwood 2009 Autoimmunity Vol.42 No.2
<P>Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by the production of an array of pathogenic autoantibodies, including high-affinity anti-dsDNA IgG antibodies. These autoantibodies are mutated and class-switched, mainly to IgG, indicating that immunoglobulin (Ig) gene somatic hypermutation (SHM) and class switch DNA recombination (CSR) are important in their generation. Lupus-prone MRL/fas(lpr/lpr) mice develop a systemic autoimmune syndrome that shares many features with human SLE. We found that Ig genes were heavily mutated in MRL/fas(lpr/lpr) mice and contained long stretches of DNA deletions and insertions. The spectrum of mutations in MRL/fas(lpr/lpr) B cells was significantly altered, including increased dG/dC transitions, increased targeting of the RGYW/WRCY mutational hotspot and the WGCW AID-targeting hotspot. We also showed that MRL/fas(lpr/lpr) greatly upregulated CSR, particularly to IgG2a and IgA in B cells of the spleen, lymph nodes and Peyer's patches. In MRL/fas(lpr/lpr) mice, the significant upregulation of SHM and CSR was associated with increased expression of activation-induced cytidine deaminase (AID), which mediates DNA lesion, the first step in SHM and CSR, and translesion DNA synthesis (TLS) polymerase (pol) theta, pol eta and pol zeta, which are involved in DNA synthesis/repair process associated with SHM and, possibly, CSR. Thus, in lupus-prone MRL/fas(lpr/lpr) mice, SHM and CSR are upregulated, as a result of enhanced AID expression and, therefore, DNA lesions, and dysregulated DNA repair factors, including TLS polymerases, which are involved in the repair process of AID-mediated DNA lesions.</P>
Zan Wang(왕잔),Jae Kyung Pan(반재경) 한국통신학회 2008 韓國通信學會論文誌 Vol.33 No.12A
Diffuse wireless optical communication offers more robust optical links in terms of coverage and shadowing than line-of-sight links. However, traditional diffuse wireless infrared (IR) transceiver systems are more susceptible to multi-path distortion and great power decrease, which results in limiting high-speed performance. Multi-beam is an effective technique to compensate for multi-path distortion in a wireless infrared environment. The goal of this paper is to analyze the transmission characteristics by replacing traditional diffuse system (TDS) which contains single wide angle transmitter and single element receiver by system consisting of three-beam transmitter and non-imaging receiver (TNS) attached with compound parabolic concentrator (CPC). In the simulation, we use the recursive model developed by Barry and Kahn and build the scenario based on 10 different cases which have been listed in Table 1. Moreover, we also check the reliability of the TNS diffuse link channel by BER test on the basis of different receiver positions and room sizes. The simulation results not only show the basic transmission characteristics of TNS diffuse link, but also are references to design more efficient and reliable indoor infrared transmission systems.
Zan Zhang,Su-Ling Tsai,Tsangyao Chang 연세대학교 동서문제연구원 2017 Global economic review Vol.46 No.2
We adopt the newly developed nonlinear autoregressive distributed lag model, advanced by Shin, Yu and Greenwood-Nimmo [(2014) Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework, in: Festschrift in Honor of Peter Schmidt, pp. 281–314 (New York: Springer)], to investigate the interest rate(IR) pass-through (IRPT) mechanism in Taiwan from 1971 M07 to 2014 M11. We find that the incomplete IRPT mechanism of deposit markets shows an asymmetric adjustment in the short run and symmetric adjustments in the long run. The deposit rate is rigid downward, which supports the customer reaction hypothesis. Moreover, we find that both the short-run and the long-run IRPT channels from the policy rate to the lending rate are also incomplete in the short run but not in the long run. The purpose of this paper is to provide accurate assessment criteria for the central bank to understand the nonlinear dynamics among the policy IR and the retail IR, thus leading to more efficient policy-making and forecasting for the Taiwanese government.
Active Queue Management Algorithm for TCP Networks with Integral Backstepping and Minimax
Zan-Hua Li,Yang Liu,Yuan-Wei Jing 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.4
A novel active queue management (AQM) approach is considered for a class of TCP network systems inthis paper. A sufficient condition is given and the corresponding control is obtained based on integral back-steppingtechnique (IB) and minimax method. The presented results not only are used to deal with the disturbances producedby UDP flows, but also can shorten the convergent time of the signals. Simulation examples are carried out to verifythe effectiveness and superiority of the proposed algorithm.
Zan Wang,Chaofei Gao,Liwei Zheng,Jikun Ren,Wei Wang,Yushuai Zhang,Shijie Han 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.1
Ultrasonic signals will be generated when partial discharge occurs in internal insulation faults in large oil immersed power transformers: because the ultrasonic signal has strong anti-interference ability and has no direct electromagnetic contact with the equipment, it is widely used in transformer fault detection and positioning. In this paper, the fi nite element method (FEM) is used to simulate the ultrasonic signal in a 35 kV power transformer. The infl uence of transformer case on ultrasonic signal propagation is considered, and the propagation law of the ultrasonic signal inside the transformer is obtained. Fabry–Pérot (F–P) fi bre acoustic sensors with a centre frequency of 28 kHz were fabricated. A partial discharge detection test was carried out in a 35 kV transformer winding model using the F–P sensors. The test results show that the ultrasonic waveform detected by the F–P sensors are in good agreement with the simulation results, and the propagation of the ultrasonic wave inside the transformer is verifi ed. It lays a foundation for detecting and locating PDs in power transformer by F–P acoustic sensors.
An Antitumor Component from Fomitiporia ellipsoidea
( Zan Lifeng ),( Haiying Bao ),( Tolgor Bau ),( Hanbin Liu ),( Baokai Cui ) 한국미생물 · 생명공학회 2012 Journal of microbiology and biotechnology Vol.22 No.11
A natural furan derivative was isolated from the methanolic extract of the fruit bodies of Fomitiporia ellipsoidea. Its chemical structure was elucidated as methyl 3,5-dioxo- 1,3,5,7-tetrahydrobenzo[1,2-c:4,5-c`]difuran-4-carboxylate by means of extensive NMR and MS data analysis, and named as fomitiporiaester A (1). Compound 1 showed significant antitumor activity to hepatoma H22 in vivo, and the inhibition rates were 42.94%, 49.17%, and 58.15% at concentrations of 5, 10, and 20 mg/kg, respectively. Compound 1 showed weak cytotoxic activities against the human hepatoblastoma (HepG-2) and human oophoroma (Skov 3) cell lines with IC50 values of more than 100 ?M.
( Zan Gao ),( Hua Zhang ),( An-an Liu ),( Yan-bing Xue ),( Guang-ping Xu ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.2
In this paper, human action recognition using pyramid histograms of oriented gradients and collaborative multi-task learning is proposed. First, we accumulate global activities and construct motion history image (MHI) for both RGB and depth channels respectively to encode the dynamics of one action in different modalities, and then different action descriptors are extracted from depth and RGB MHI to represent global textual and structural characteristics of these actions. Specially, average value in hierarchical block, GIST and pyramid histograms of oriented gradients descriptors are employed to represent human motion. To demonstrate the superiority of the proposed method, we evaluate them by KNN, SVM with linear and RBF kernels, SRC and CRC models on DHA dataset, the well-known dataset for human action recognition. Large scale experimental results show our descriptors are robust, stable and efficient, and outperform the state-of-the-art methods. In addition, we investigate the performance of our descriptors further by combining these descriptors on DHA dataset, and observe that the performances of combined descriptors are much better than just using only sole descriptor. With multimodal features, we also propose a collaborative multi-task learning method for model learning and inference based on transfer learning theory. The main contributions lie in four aspects: 1) the proposed encoding the scheme can filter the stationary part of human body and reduce noise interference; 2) different kind of features and models are assessed, and the neighbor gradients information and pyramid layers are very helpful for representing these actions; 3) The proposed model can fuse the features from different modalities regardless of the sensor types, the ranges of the value, and the dimensions of different features; 4) The latent common knowledge among different modalities can be discovered by transfer learning to boost the performance.
Human Action Recognition Via Multi-modality Information
Zan Gao,Jian-ming Song,Hua Zhang,An-An Liu,Yan-bing Xue,Guang-ping Xu 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.2
In this paper, we propose pyramid appearance and global structure action descriptors on both RGB and depth motion history images and a model-free method for human action recognition. In proposed algorithm, we firstly construct motion history image for both RGB and depth channels, at the same time, depth information is employed to filter RGB information, after that, different action descriptors are extracted from depth and RGB MHIs to represent these actions, and then multimodality information collaborative representation and recognition model, in which multi-modality information are put into object function naturally, and information fusion and action recognition also be done together, is proposed to classify human actions. To demonstrate the superiority of the proposed method, we evaluate it on MSR Action3D and DHA datasets, the well-known dataset for human action recognition. Large scale experiment shows our descriptors are robust, stable and efficient, when comparing with the-state-of-the-art algorithms, the performances of our descriptors are better than that of them, further, the performance of combined descriptors is much better than just using sole descriptor. What is more, our proposed model outperforms the state-of-the-art methods on both MSR Action3D and DHA datasets.