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Characterization of a Late Gene, ORF60 from Bombyx mori Nucleopolyhedrovirus
Du, Meng-Fang,Yin, Xin-Ming,Guo, Zhong-Jian,Zhu, Liang-Jun Korean Society for Biochemistry and Molecular Biol 2006 Journal of biochemistry and molecular biology Vol.39 No.6
Open reading frame 60 of Bombyx mori nucleopolyhedrovirus (Bm60) is located between 56,673 and 57,479 bp in the BmNPV genome which encodes 268 amino acid residues with predicted molecular weight of 31.0 kDa. Bm60 and its homologues have been identified in 11 completely sequenced lepidopteran NPVs. The transcript of Bm60 was detected by RT-PCR at 18-72 h post-infection (p.i.), while the corresponding protein could be detected at 24-72 h p.i. in BmNPV-infected BmN cells by Western blot analysis using a polyclonal antibody against Bm60. The expression of Bm60 was inhibited in the presence of Ara-c, an inhibitor of viral DNA synthesis. These results together indicated that Bm60 was a late gene. The size of Bm60 product was found to be a 31 kDa in BmNPV-infected BmN cells, consistent with predicted molecular weight. Immuno-fluoresence analysis showed that the Bm60 product was first detected in the cytoplasm at 24 h p.i and also located in nucleus during later infection. In conclusion, the available data suggest that Bm60 is a functional ORF of BmNPV and encodes a 31kDa protein expressed in the later stage of infection cycle.
The AVS/RS Scheduling Optimization Based on Improved AFSA
Yanjun Fang,Meng Tang 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.10
This paper addresses the problem of the autonomous vehicle storage and retrieval system (AVS/RS) scheduling optimization. AVS/RS relies on rail guide vehicle (RGV) to provide horizontal movement within a tier and uses lifts to provide vertical movement between tiers. Firstly, the process of RGVs’ compound operation is analyzed, and the corresponding mathematical model is established. Then, an improved artificial fish swarm algorithm (IAFSA) is proposed to solve the model. According to the characteristics of the storage and retrieval operation in the system, an encoding and decoding method is designed, which contains RGV task allocation and elevator selection information. The tabu list and the optimal strategy are introduced into this algorithm, coupled with memory action and communication action to avoid the algorithm to trap in local optimal solution. Meanwhile, the adaptive step and visual are used to increase the late convergence of this algorithm. Finally, simulations based on the concrete living example of AVS/RS in a provincial verification center are given.The results obtained by the proposed algorithm are compared with another two optimization algorithm. Analysis shows that the proposed algorithm has the characteristics of fast convergence and the best solution, so as to improve the practicality and robustness of the algorithm.
Meng Lei,Feng Bin,Luan Liming,Fang Zhihao,Zhao Guangyu 생화학분자생물학회 2022 Experimental and molecular medicine Vol.54 No.-
Methyl CpG binding protein 2 (MeCP2) is involved in nerve regeneration following ischemic stroke, but the related mechanism remains unclear. Here, we found low MeCP2 expression in hippocampal tissues. Using functional analysis, we demonstrated that MeCP2 accelerated FOXO3a methylation and subsequently inhibited its expression, thus repressing the apoptosis of neuronal cells. Mechanistically, FOXO3a could bind to the promoter region of SPRY2, consequently inducing its transcription and promoting the expression of the downstream target gene ZEB1. Altogether, our study revealed that overexpression of MeCP2 can protect mice against ischemic brain injury via disruption of the FOXO3a/SPRY2/ZEB1 signaling axis. Our results identify ectopic expression of MeCP2 as a therapeutic target in ischemic stroke.
Fang, Xiaonan,Ye, Linbai,Timani, Khalid Amine,Li, Shanshan,Zen, Yingchun,Zhao, Meng,Zheng, Hong,Wu, Zhenghui Korean Society for Biochemistry and Molecular Biol 2005 Journal of biochemistry and molecular biology Vol.38 No.4
Severe acute respiratory syndrome (SARS) is an emerging infectious disease associated with a novel coronavirus (CoV) that was identified and molecularly characterized in 2003. Previous studies on various coronaviruses indicate that protein-protein interactions amongst various coronavirus proteins are critical for viral assembly and morphogenesis. It is necessary to elucidate the molecular mechanism of SARS-CoV replication and rationalize the anti-SARS therapeutic intervention. In this study, we employed an in vitro GST pull-down assay to investigate the interaction between the membrane (M) and the nucleocapsid (N) proteins. Our results show that the interaction between the M and N proteins does take place in vitro. Moreover, we provide an evidence that 12 amino acids domain (194-205) in the M protein is responsible for binding to N protein. Our work will help shed light on the molecular mechanism of the virus assembly and provide valuable information pertaining to rationalization of future anti-viral strategies.
Online health estimation strategy with transfer learning for operating lithium‑ion batteries
Fang Yao,Defang Meng,Youxi Wu,Yakun Wan,Fei Ding 전력전자학회 2023 JOURNAL OF POWER ELECTRONICS Vol.23 No.6
Complex power supply operation conditions complicate the degradation process of lithium batteries, which makes the charge–discharge cycle incomplete and the maximum available capacity not easily accessible. Besides, data-driven methods suffer from limited adaptation and possible overfi tting. This paper proposes an online health estimation strategy with transfer learning for estimating the state of health (SOH) of batteries under varying charge–discharge depths and current rates. It aims to alleviate the diffi culty in estimating SOH for operating batteries, and broaden the application range of the training model. The core of this strategy is a two-domain transfer CNN-LSTM model that estimates targets by transferring the battery degradation trends of multiple constant conditions. First, health indicators (HIs) with relatively high correlations and wide application ranges are extracted from the voltage and current data of the daily charge process. Then HI-based source domain selection criteria are designed. Since the battery experiences full and incomplete-discharged cases leading to various aging rates, a two-domain transfer CNN-LSTM model is designed. Each subnet includes a CNN and an LSTM to accomplish feature adaptation and time series forecasting. The weights of the sub-nets are updated online to track the drift of the time series covariates. Finally, the proposed strategy is verifi ed on target batteries with varying cut-off voltages and currents, which demonstrates notable accuracy and reliability.
Understanding innovations in Malaysia’s construction industry: a study of four large national firms
Yean Fang Chang,Rajah Rasiah,Wai Meng Chan 기술경영경제학회 2016 ASIAN JOURNAL OF TECHNOLOGY INNOVATION Vol.24 No.3
Little published work exists on innovation in construction, which is not helped by the diverse setof activities that characterise the industry. The early attempt to category sources of innovation inthe industry depicted it as a supplier driven industry using large data sets from secondary sources. Given the lack of profound firm-level research in the industry, this paper uses four case studies ofnational firms in Malaysia to examine innovation in the industry. The evidence shows that majorinnovations in these firms evolve as a crystallization of project demand that drives firms to seekexternal sources of knowledge that is adapted to meet the construction demand of clients. Indoing so two firms demonstrated radical innovations as its diffusion has transformedconstruction in Malaysia. The remaining two firms are engaged in incremental engineeringactivities. Also, innovations in two firms were led by their own managements, while theremaining two were supplier-led. In addition, while innovations in all four firms arecharacterised by re-conceptualisation of foreign sources of knowledge, innovation in one firminvolved architectural designing and another modularisation. A blend of institutionsconstituted by government policy, in-house command, trust and collaborative practices,markets, and industry standards have shaped these innovations.
Low-Cost Camera Based Laser Power Monitoring and Stabilizing for Micro-Hole Drilling
Chien-Fang Ding,Meng-Shiou Lee,Kuan-Ming Li 한국정밀공학회 2017 International Journal of Precision Engineering and Vol.18 No.9
In this study, a laser power monitoring and stabilizing system for micro-hole drilling based on optical outputs of a CMOS sensor is presented. The correlation between the laser power and the average brightness of the beam spots on the images was investigated. The estimated laser power was used to build an on-line closed loop control of micro-hole drilling. Experimental results showed that the shortest response time of the laser monitoring system was only 30 ms, which was much faster than a thermopile power meter. The average measuring error was 3%, compared with thermopile power meter. In the PCB drilling experiments of 30 kHz pulse repetition frequency, the PID controller could compensate the power disturbances from 38.4% to 1.8%, and the aspect ratio from 20% to 5%. This study demonstrates the feasibility to develop a low-cost laser power monitoring and stabilizing system in laser micromachining processes.
A Rapid Life Cycle Assessment Method based on Green Features in Supporting Conceptual Design
Qiang Meng,Fang-yi Li,Li-rong Zhou,Jing Li,Qin-qin Ji,Xiaodong Yang 한국정밀공학회 2015 International Journal of Precision Engineering and Vol.2 No.2
A Rapid Life Cycle Assessment (RLCA) method based on Green features is proposed in order to solve the inherent limitations of conventional Life Cycle Assessment (LCA), such as long period, massive data requirement, which result in difficulties in supporting product conceptual design. Firstly, Green Feature is proposed in supporting the LCA in conceptual design, where a mapping relationship is established between green feature and design information to achieve the transformation from the design information to green features. Secondly, product conceptual design model is proposed based on modular configuration. The approximate products program will be obtained through retrieval and matching of each module of product using the knowledge base and case base. Thirdly, Intuitionistic Fuzzy theory and Monte Carlo method are respectively used to process the qualitative and quantitative uncertain information of green features in order to ensure the accuracy of the evaluation results. Besides, the appropriate life cycle impact assessment method is selected to complete the life cycle impact assessment and obtain the LCA results. Consequently, the RLCA of product design program is completed to support product green design. Finally, a fan of a ventilation system is studied as an example to verify the proposed RLCA theory.