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2,069 results on '"Xu, Jianping"'

4. Accelerating Chemical Exchange Saturation Transfer Imaging Using a Model-based Deep Neural Network With Synthetic Training Data

Author

Xu, Jianping, Zu, Tao, Hsu, Yi-Cheng, Wang, Xiaoli, Chan, Kannie W. Y., and Zhang, Yi

Subjects
Physics - Medical Physics
Abstract

Purpose: To develop a model-based deep neural network for high-quality image reconstruction of undersampled multi-coil chemical exchange saturation transfer (CEST) data. Theory and Methods: Inspired by the variational network, the CEST image reconstruction equation is unrolled into a deep neural network (CEST-VN) with a k-space data-sharing block that takes advantage of the inherent redundancy in adjacent CEST frames and 3D spatial-frequential convolution kernels that exploit correlations in the x-{\omega} domain. Additionally, a new pipeline based on multiple-pool Bloch-McConnell simulations is devised to synthesize multi-coil CEST data from publicly available anatomical MRI data. The proposed neural network is trained on simulated data with a CEST-specific loss function that jointly measures the structural and CEST contrast. The performance of CEST-VN was evaluated on three healthy volunteers and five brain tumor patients using retrospectively undersampled data with various acceleration factors, and compared with other state-of-the-art reconstruction methods. Results: The proposed CEST-VN method generated high-quality CEST source images and APT-weighted (APTw) maps in healthy and brain tumor subjects, consistently outperforming GRAPPA, blind compressed sensing, and the original variational network. With the acceleration factors increasing from 3 to 6, CEST-VN with the same hyperparameters yielded similar and accurate reconstruction without apparent loss of details or increase of artifacts. The ablation studies confirmed the effectiveness of the joint CEST-specific loss function and data-sharing block used. Conclusions: The proposed CEST-VN method can offer high-quality CEST source images and APTw maps from highly undersampled multi-coil data by integrating the deep-learning prior and multi-coil sensitivity encoding model., Comment: 31 pages, 12 figures, 3 tables

Published
2022

12. Research on transient synchronous stability of integrated grid-forming converters using power synchronization control

Author

XIANG Zhongming, NI Qiulong, LI Zhenhua, XU Jianping, LI Sixun, ZHANG Zheren, and XU Zheng

Subjects
transient synchronization stability, psc, grid-forming converter, pdc, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

The proportion of the integrated converters using PSC （power synchronization control） in power systems is increasing year by year， but there is a lack of in-depth research on the transient synchronization stability. Therefore， the transient synchronization stability mechanism of integrated grid-forming converters using PSC is analyzed， and measures to improve the transient stability of the converter are proposed. First， the transient stability model of the grid-forming converters with PSC during grid fault is established. Subsequently， based on the phase diagram curve （PDC） method， the destabilization mechanism of the converters and the effect of voltage coupling on the transient synchronous stability are investigated. Moreover， a control strategy to improve the transient synchronous stability by dynamically adjusting the active power command value is proposed based on the effect of voltage coupling. Finally， the electromagnetic transient simulation model of an equivalent system in a city is constructed by using PSCAD/EMTDC， which verifies the correctness of the transient stabilization mechanism of the converter-connected power system and the effectiveness of the stabilization enhancement measures under different fault conditions.

Published
2023
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14. Gut microbiota and metabolite insights into anti-obesity effect of carboxymethyl pachymaran in high-fat diet mice

Author

Wang Gangzheng, Chen Xianglian, Sun Chengyuan, Huang Qiuju, Zhang Chenghua, Lin Min, Xu Jianping, Huang Xueshuang, and Deng Wangqiu

Subjects
Poria cocos polysaccharides, Dyslipidemia, Gut microbiota, Butyric acid, Bile acids, Nutrition. Foods and food supply, TX341-641
Abstract

Poria cocos, a well-known traditional Chinese edible-medicinal mushroom, has shown many beneficial health effects. In this study, we investigated the anti-obesity and hyperlipidemia effect of carboxymethyl pachymaran (CMP) in high-fat diet mice, with a focus on gut microbiota and their metabolites. Results demonstrated that CMP notably decreased fat weights and serum lipid, improved glucose tolerance, and reduced lipid droplet level in hepatic tissue. CMP markedly reduced the ratio between Firmicutes and Bacteroidetes, decreased the abundances of Dubosiella newyorkensis and Faecealibaculum rodentium, but increased the abundances of Akkermansia muciniphila and Bifidobacterium pseudolongum. In addition, CMP significantly promoted the production of butyric acid (BA) while decreased the levels of hepatic bile acids. Association analysis showed that physio-biochemical traits were negatively associated with A. muciniphila and BA, whereas showed a positive correlation to F. rodentium and differential bile acids. Together, CMP can alleviate obesity and related complications by modulating gut microbiota and metabolites.

Published
2023
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15. Three-Mode Peak Current Control Strategy for the Four-Switch Buck-Boost Converter

Author

Deng, Kai, Xu, Jianping, Liu, Feiming, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Yang, Qingxin, editor, Dong, Xuzhu, editor, and Ma, Weiming, editor

Published
2023
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16. Large Signal Stability Analysis of Pulse Power Load Based on Hamiltonian Energy Function

Author

Qi, Jin, Chen, Zhengge, Chen, Xu, Yang, Ping, Chen, Jian, Xu, Jianping, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Xie, Kaigui, editor, Hu, Jianlin, editor, Yang, Qingxin, editor, and Li, Jian, editor

Published
2023
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17. Multilevel Pulse Train Control Three-Phase Inverter Based on Power Reference

Author

Wang, Zhifu, Xu, Jianping, Wang, Yifan, Jing, Yuxi, Chen, Xin, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Ma, Chengbin, editor, Zhang, Yiming, editor, Li, Siqi, editor, Zhao, Lei, editor, Liu, Ming, editor, and Zhang, Pengcheng, editor

Published
2023
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18. Research on Automatic Assembly Technology for Spacecraft System

Author

Chen, Zejian, Yang, Jizhi, Xu, Jianping, Zhang, Yangcheng, Li, Yongliang, Yue, Yi, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Wang, Yue, editor, Liu, Yuyang, editor, Zou, Jiaqi, editor, and Huo, Mengyao, editor

Published
2023
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22. Multi-Stage Transmission Line Flow Control Using Centralized and Decentralized Reinforcement Learning Agents

Author

Shang, Xiumin, Yang, Jinping, Zhu, Bingquan, Ye, Lin, Zhang, Jing, Xu, Jianping, Lyu, Qin, and Diao, Ruisheng

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control
Abstract

Planning future operational scenarios of bulk power systems that meet security and economic constraints typically requires intensive labor efforts in performing massive simulations. To automate this process and relieve engineers' burden, a novel multi-stage control approach is presented in this paper to train centralized and decentralized reinforcement learning agents that can automatically adjust grid controllers for regulating transmission line flows at normal condition and under contingencies. The power grid flow control problem is formulated as Markov Decision Process (MDP). At stage one, centralized soft actor-critic (SAC) agent is trained to control generator active power outputs in a wide area to control transmission line flows against specified security limits. If line overloading issues remain unresolved, stage two is used to train decentralized SAC agent via load throw-over at local substations. The effectiveness of the proposed approach is verified on a series of actual planning cases used for operating the power grid of SGCC Zhejiang Electric Power Company., Comment: This work is accepted by NeurIPS ML4Eng workshop 2020, please refer to https://ml4eng.github.io/camera_readys/56.pdf

Published
2021

23. Mean Trajectories of Multiple Tracking Points on A Brownian Rigid Body: Convergence, Alignment and Twist

Author

Xu, Jianping

Subjects
Condensed Matter - Statistical Mechanics
Abstract

We consider mean trajectories of multiple tracking points on a rigid body that conducts Brownian motion in the absence and presence of an external force field. Based on a na\"{\i}ve representation of rigid body - polygon and polyhedron where hydrodynamic interactions are neglected, we study the Langevin dynamics of these Brownian polygons and polyhedra. Constant force, harmonic force and an exponentially decaying force are investigated as examples. In two dimensional space, depending on the magnitude and form of the external force and the isotropy and anisotropy of the body, mean trajectories of these tracking points can exhibit three regimes of interactions: convergence, where the mean trajectories converge to either a point or a single trajectory; alignment, where the mean trajectories juxtapose in parallel; twist, where the mean trajectories twist and intertwine, forming a plait structure. Moreover, we have shown that in general a rigid body can sample from these regimes and transit between them. And its Brownian behavior could be modified during such transition. Notably, from a polygon in two dimensional space to a polyhedron in three dimensional space, the alignment and twist regimes disappear and there is only the convergence regime survived, due to the two more rotational degrees of freedom in three dimensional space.

Published
2021

28. Draft Genome Sequences of the Black Truffles Tuber brumale Vittad. and Tuber indicum Cook & Massee

Author

Morin, Emmanuelle, Murat, Claude, Cichocki, Nicolas, De la Varga, Herminia, Kohler, Annegret, Xu, Jianping, Grigoriev, Igor V, and Martin, Francis M

Subjects
Microbiology, Biological Sciences, Genetics, Human Genome
Abstract

Tuber brumale and Tuber indicum (Pezizomycetes) are two edible black truffles establishing ectomycorrhizal symbiosis with trees and shrubs. T. brumale is ubiquitous in Europe, and T. indicum is mainly found in China. Here, we present the draft genome sequences of T. brumale and T. indicum.

Published
2021

34. Large-scale genome sequencing of mycorrhizal fungi provides insights into the early evolution of symbiotic traits.

Author

Miyauchi, Shingo, Kiss, Enikő, Kuo, Alan, Drula, Elodie, Kohler, Annegret, Sánchez-García, Marisol, Morin, Emmanuelle, Andreopoulos, Bill, Barry, Kerrie W, Bonito, Gregory, Buée, Marc, Carver, Akiko, Chen, Cindy, Cichocki, Nicolas, Clum, Alicia, Culley, David, Crous, Pedro W, Fauchery, Laure, Girlanda, Mariangela, Hayes, Richard D, Kéri, Zsófia, LaButti, Kurt, Lipzen, Anna, Lombard, Vincent, Magnuson, Jon, Maillard, François, Murat, Claude, Nolan, Matt, Ohm, Robin A, Pangilinan, Jasmyn, Pereira, Maíra de Freitas, Perotto, Silvia, Peter, Martina, Pfister, Stephanie, Riley, Robert, Sitrit, Yaron, Stielow, J Benjamin, Szöllősi, Gergely, Žifčáková, Lucia, Štursová, Martina, Spatafora, Joseph W, Tedersoo, Leho, Vaario, Lu-Min, Yamada, Akiyoshi, Yan, Mi, Wang, Pengfei, Xu, Jianping, Bruns, Tom, Baldrian, Petr, Vilgalys, Rytas, Dunand, Christophe, Henrissat, Bernard, Grigoriev, Igor V, Hibbett, David, Nagy, László G, and Martin, Francis M

Subjects
Fungi, Mycorrhizae, Plants, Fungal Proteins, Ecosystem, Evolution, Molecular, Phylogeny, Symbiosis, Genome, Fungal, Plant Physiological Phenomena, Genetics, Biotechnology
Abstract

Mycorrhizal fungi are mutualists that play crucial roles in nutrient acquisition in terrestrial ecosystems. Mycorrhizal symbioses arose repeatedly across multiple lineages of Mucoromycotina, Ascomycota, and Basidiomycota. Considerable variation exists in the capacity of mycorrhizal fungi to acquire carbon from soil organic matter. Here, we present a combined analysis of 135 fungal genomes from 73 saprotrophic, endophytic and pathogenic species, and 62 mycorrhizal species, including 29 new mycorrhizal genomes. This study samples ecologically dominant fungal guilds for which there were previously no symbiotic genomes available, including ectomycorrhizal Russulales, Thelephorales and Cantharellales. Our analyses show that transitions from saprotrophy to symbiosis involve (1) widespread losses of degrading enzymes acting on lignin and cellulose, (2) co-option of genes present in saprotrophic ancestors to fulfill new symbiotic functions, (3) diversification of novel, lineage-specific symbiosis-induced genes, (4) proliferation of transposable elements and (5) divergent genetic innovations underlying the convergent origins of the ectomycorrhizal guild.

Published
2020

36. Tackling the emerging threat of antifungal resistance to human health

Author

Fisher, Matthew C., Alastruey-Izquierdo, Ana, Berman, Judith, Bicanic, Tihana, Bignell, Elaine M., Bowyer, Paul, Bromley, Michael, Brüggemann, Roger, Garber, Gary, Cornely, Oliver A., Gurr, Sarah. J., Harrison, Thomas S., Kuijper, Ed, Rhodes, Johanna, Sheppard, Donald C., Warris, Adilia, White, P. Lewis, Xu, Jianping, Zwaan, Bas, and Verweij, Paul E.

Published
2022
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37. Effect and correlation of Cordyceps guangdongensis ethanolic extract on obesity, dyslipidemia and gut microbiota dysbiosis in high-fat diet mice

Author

Wang Gangzheng, Sun Chengyuan, Huang Qiuju, Zhang Chenghua, Lin Min, Li Taihui, Xu Jianping, and Deng Wangqiu

Subjects
Obesity, Dyslipidemia, Gut microbiota, Butyric acid, Correlation analysis, Nutrition. Foods and food supply, TX341-641
Abstract

Edible-medicinal fungi have shown many beneficial health effects. Cordyceps guangdongensis is a novel edible-medicinal fungus in China. In this study, we investigated the effects of ethanolic extract from C. guangdongensis fruiting bodies (CGE), and comprehensively dissected the effects of CGE on fat accumulation, dyslipidemia, gut microbial composition, and short chain fatty acids (SCFAs). Results showed that CGE markedly inhibited body weight gain, decreased fat accumulation in various tissues, and significantly improved glucose tolerance and hyperlipidemia. CGE notably restored high-fat diet induced microbial shift from Bacteroidetes to Firmicutes, and markedly increased the abundances of beneficial gut microbiota (such as Akkermansia muciniphila and Bifidobacterium animalis). Interestingly, CGE also significantly promoted butyric acid (BA) production. Pairwise correlation analysis found that A. muciniphila, B. animals and BA were negatively associated with several fat-related parameters and blood lipid indicators. Together, our results suggested that CGE represented a potential novel supplement to treat obesity and related complications.

Published
2023
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42. Research on Intelligent Intrusion Detection Method of Power Information Network Under Cloud Computing

Author

Xia, Chenyi, Ao, Feixiang, Xu, Jianping, Yao, Baoming, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Sun, Songlin, editor, Hong, Tao, editor, Yu, Peng, editor, and Zou, Jiaqi, editor

Published
2022
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44. A fast evaluation method of power limit of transmission section based on hybrid supervised learning

Author

ZHANG Jing, YE Lin, DIAO Ruisheng, XU Jianping, and LYU Qin

Subjects
ai, transmission section, machine learning, power limit forecast, grid operation condition, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

The quick， accurate and instantaneous evaluation of power limit of transmission section is of great significance to safe， stable and economic operation of power grid. The paper proposes an adaptive method based on a hybrid supervised learning algorithm. Through numerous simulations and analysis of historic operation modes， characteristic extraction， training， and regular updating of AI model， the correct matching relationship between grid operation status and power limit is established for fast， accurate and instantaneous power limit evaluation of the transmission section. The proposed method employs multiple supervised learning forecast algorithms， including deep neural networks， support vector regression， gradient boosting decision tree， and random forest. The hybrid models for power limit forecasting can make best of the advantages of the algorithms. The effectiveness of the method is verified on a 500-bus transmission model with real operation characteristics.

Published
2022
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48. An Operating Condition Adjustment Method for Power Grid Using Multi-DRL-Agent Architecture

Author

YE Lin, XIANG Zhongming, ZHANG Jing, XU Jianping, LYU Qin, SHANG Xiumin, YANG Jingping, and DIAO Ruisheng

Subjects
artificial intelligence, grid dispatch and control, deep reinforcement learning, multi-agent, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

As the planning and dispatching of new types of power systems become increasingly complicated， dynamic and dubious， it is very challenging to lay down operating mode for power grid that satisfies both security and economic constraints. This process typically requires intensive manual tuning and simulation calculations to search for feasible solutions in a high-dimensional action space that fulfills the requirements on safety and economy of the grid in ground state and fault conditions. Therefore， an approach based on multi-DRL-agent architecture is proposed to describe the problem as a Markov decision process （MDP）. The approach automatically adjusts different types of controllable grid resources by training centralized and distributed multi-DRL-agent to control the power of transmission lines， thus complying with various safety indicators of grid operation. The method is proved to be effective in a power grid model.

Published
2022
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