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SAC-Based Computation Offloading for Reconfigurable Intelligent Surface-Aided Mobile Edge Networks

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China Communications 2024年第6期21卷 261-270页

作者： li Bin qian zhen Fei Zesong School of Computer Science Nanjing University of Information Science&TechnologyNanjing 210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing 210044 School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China

In this paper,we concentrate on a reconfigurable intelligent surface(RIS)-aided mobile edge computing(MEC)system to improve the offload efficiency with moving user equipments(UEs).We aim to minimize the energy consumption of all UEs by jointly optimizing the discrete phase shift of RIS,UEs’transmitting power,computing resources allocation,and the UEs’task offloading strategies for local computing and *** formulated problem is a sequential decision making across multiple coherent time ***,the mobility of UEs brings uncertainties into the decision-making *** cope with this challenging problem,the deep reinforcement learning-based Soft Actor-Critic(SAC)algorithm is first proposed to effectively optimize the discrete phase of RIS and the UEs’task offloading ***,the transmitting power and computing resource allocation can be determined based on the *** results demonstrate that the proposed algorithm can be trained more stably and perform approximately 14%lower than the deep deterministic policy gradient benchmark in terms of energy consumption.

关键词： MEC RIS soft actor-critic user mobility

Phosphorylated cellulose nanofibers establishing reliable ion-sieving barriers for durable lithium-sulfur batteries

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Journal of Energy Chemistry 2024年第5期92卷 619-628页

作者： Zihao li Pengsen qian Hongyang li He Xiao Jun Chen Gaoran li School of Materials Science and Engineering Nanjing University of Science and TechnologyNanjing 210094JiangsuChina National Forestry and Grassland Administration Key Laboratory of Plant Fiber Functional Materials Fuzhou 350108FujianChina

The shuttle effect is among the most characteristic and formidable challenges in the pursuit of high-performance lithium-sulfur(li-S)***,phosphorylated cellulose nanofibers(pCNF)are intentionally engineered to establish an ion-sieving barrier against polysulfide shuttling and thereby improve battery *** phosphorylation,involving the grafting of phosphate groups onto the cellulose backbone,imparts an exceptional electronegativity that repels the polysulfide anions from penetrating through the ***,the electrolyte wettability and li^(+)transfer can be significantly promoted by the polar nature of pCNF and the facile li^(+)*** such,rational ion management is realized,contributing to enhanced reversibility in both sulfur and lithium *** a result,li-S cells equipped with the self-standing pCNF separator demonstrate outstanding long-term cyclability with a minimum fading rate of 0.013%per cycle over 1000 cycles at 1 C,and a decent areal capacity of 5.37 mA h cm^(-2) even under elevated sulfur loading of 5.0 mg cm^(-2) and limited electrolyte of 6.0 mL g^(-1).This work provides a facile and effective pathway toward the well-tamed shuttle effect and highly durable li-S batteries.

关键词： lithium-sulfur batteries Cellulose Phosphorylation Ion-sieving Shuttle effect

Novel high-safety aeroengine performance predictive control method based on adaptive tracking weight

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Chinese Journal of Aeronautics 2024年第7期37卷 352-374页

作者： qian CHEN Hanlin SHENG Jie zhANG Jiacheng li College of Energy and Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

Increasing attention has been attracted to the dynamic performance and safety of advanced performance predictive control systems of the next-generation *** latest research demonstrates that Subspace-based Improved Model Predictive Control(SIMPC)can overcome the difficulty in solving the predictive model in MPC/NMPC ***,applying constant design parameters cannot maintain consistent control effects in all ***,the designed system relies too much on sensor-measured data,and thus it is difficult to thoroughly validate the safety of the system because of its high *** means that any potential hardware/software faults will endanger the ***,this paper first presents a novel nonlinear mapping relationship to adaptively tune the tracking weight online with the change of Power Lever Angle(PLA)and real-time relative tracking ***,without introducing additional design parameters,an Adaptive Tracking Weight-based SIMPC(ATW-SIMPC)controller is designed to improve the control performance in all operating states ***,a Primary/Backup Hybrid Control(PBHC)strategy with the ATW-SIMPC controller as the primary system and the traditional speed(Nf)controller as the backup system is proposed to ensure *** designed affiliated switching controller and the real-time monitor therein can be used to realize reasonable and smooth switching between primary/backup systems,so as to avoid bump *** PBHC system switches to the Nf controller when the ATW-SIMPC controller is wrong because of potential hardware/software faults;otherwise,the ATW-SIMPC controller keeps acting on the *** main results prove that the ATW-SIMPC controller with the optimal nonlinear mapping relationship,compared with the existing SIMPC controller,uplifts the dynamic control performance by 32%and reduces overshoots to an allowable limit,resulting in a better control effect in full *** comparison results consistently i

关键词： Aeroengine Model predictive control Hybrid system Adaptive weight Safety

Probabilistic seismic inversion based on physics-guided deep mixture density network

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Petroleum Science 2024年第3期21卷 1611-1631页

作者： qian-Hao Sun zhao-Yun Zong Xin li National Key Laboratory of Deep Oil and Gas China University of Petroleum(East China)Qingdao266580ShandongChina Laoshan Laboratory Qingdao266580ShandongChina CNOOC Research Institute Ltd. Beijing100028China

Deterministic inversion based on deep learning has been widely utilized in model parameters *** by logging data,seismic data,wavelet and modeling operator,deterministic inversion based on deep learning can establish nonlinear relationships between seismic data and model ***,seismic data lacks low-frequency and contains noise,which increases the non-uniqueness of the *** conventional inversion method based on deep learning can only establish the deterministic relationship between seismic data and parameters,and cannot quantify the uncertainty of *** order to quickly quantify the uncertainty,a physics-guided deep mixture density network(PG-DMDN)is established by combining the mixture density network(MDN)with the deep neural network(DNN).Compared with Bayesian neural network(BNN)and network dropout,PG-DMDN has lower computing cost and shorter training time.A low-frequency model is introduced in the training process of the network to help the network learn the nonlinear relationship between narrowband seismic data and low-frequency *** addition,the block constraints are added to the PG-DMDN framework to improve the horizontal continuity of the inversion *** illustrate the benefits of proposed method,the PG-DMDN is compared with existing semi-supervised inversion *** synthetic data examples of Marmousi II model are utilized to quantify the influence of forward modeling part,low-frequency model,noise and the pseudo-wells number on inversion results,and prove the feasibility and stability of the proposed *** addition,the robustness and generality of the proposed method are verified by the field seismic data.

关键词： Deep learning Probabilistic inversion Physics-guided Deep mixture density network

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light(Science & Applications) 2024年第2期13卷 333-346页

作者： Yifan Sun qian li ling-Jun Kong Xiangdong zhang Key Laboratory of advanced optoelectronic quantum architecture and measurements of Ministry of Education Beijing Key Laboratory of Nanophotonics&Ultrafine Optoelectronic SystemsSchool of PhysicsBeijing Institute of Technology100081BeijingChina

Compared with electrical neural networks,optical neural networks(ONNs)have the potentials to break the limit of the bandwidth and reduce the consumption of energy,and therefore draw much attention in recent *** far,several types of ONNs have been ***,the current ONNs cannot realize the acceleration as powerful as that indicated by the models like quantum neural *** to construct and realize an ONN with the quantum speedup is a huge ***,we propose theoretically and demonstrate experimentally a new type of optical convolutional neural network by introducing the optical *** is called the correlated optical convolutional neural network(COCNN).We show that the COCNN can exhibit“quantum speedup”in the training *** character is verified from the two *** is the direct illustration of the faster convergence by comparing the loss function curves of the COCNN with that of the traditional convolutional neural network(CNN).Such a result is compatible with the training performance of the recently proposed quantum convolutional neural network(QCNN).The other is the demonstration of the COCNN’s capability to perform the QCNN phase recognition circuit,validating the connection between the COCNN and the ***,we take the COCNN analog to the 3-qubit QCNN phase recognition circuit as an example and perform an experiment to show the soundness and the feasibility of *** results perfectly match the theoretical *** proposal opens up a new avenue for realizing the ONNs with the quantum speedup,which will benefit the information processing in the era of big data.

关键词： process quantum convolution

Optimal Operation with Dynamic Partitioning Strategy for Centralized Shared Energy Storage Station with Integration of Large-scale Renewable Energy

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 359-370页

作者： Jianlin li zhijin Fang qian Wang Mengyuan zhang Yaxin li Weijun zhang Beijing Future Technology Innovation Centre for Electrochemical Energy Storage System Integration North China University of Technology Beijing China State Grid Fujian Electric Power Research Institute Fuzhou China

As renewable energy continues to be integrated into the grid,energy storage has become a vital technique supporting power system *** effectively promote the efficiency and economics of energy storage,centralized shared energy storage(SES)station with multiple energy storage batteries is developed to enable energy trading among a group of *** this paper,we propose the optimal operation with dynamic partitioning strategy for the centralized SES station,considering the day-ahead demands of large-scale renewable energy power *** implement a multi-entity cooperative optimization operation model based on Nash bargaining *** model is decomposed into two subproblems:the operation profit maximization problem with energy trading and the leasing payment bargaining *** distributed alternating direction multiplier method(ADMM)is employed to address the subproblems *** reveal that the optimal operation with a dynamic partitioning strategy improves the tracking of planned output of renewable energy entities,enhances the actual utilization rate of energy storage,and increases the profits of each participating *** results confirm the practicality and effectiveness of the strategy.

关键词： Shared energy storage(SES) dynamic partitioning strategy optimal operation Nash bargaining theory actual utilization rate of energy storage

Efflcient machining of a complex blisk channel using a disc cutter

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Chinese Journal of Aeronautics 2024年第1期37卷 414-437页

作者： Xiangyu li zhaoyu li Dong HE Junxue REN qian FENG Kai TANG Department of Mechanical and Aerospace Engineering Hong Kong University of Science and TechnologyHong Kong 999077China Key Laboratory of High Performance Manufacturing for Aero Engine(Northwestern Polytechnical University) Ministry of Industry and Information TechnologyXi’an 710072China Xi’an Sanhang Power Technology Co. LtdXi’an 710000China HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute FutianShenzhen 518057China HKUST Shenzhen Research Institute Shenzhen 518057China

For rough machining of a complex narrow cavity,e.g.,a complex blisk channel on an aero-engine,the typically used cutting tools are the slender cylindrical cutter and conical ***,as neither of the two is particularly suited for rough machining,wherein the main purpose is to remove a large volume as quickly as possible,the machining efficiency is low,especially when the part materials are of hard-to-cut types(e.g.,Titanium-alloy)for which it often takes days to rough machine a ***,disc machining provides a new and efficient roughing solution,since a disc cutter with a large radius enables a much larger cutting speed and thus a larger material removal ***,due to the large radius of the disc cutter,its potential collision with narrow and twisted channels becomes a serious *** this paper,we propose a novel twophase approach for efficiently machining a complex narrow cavity workpiece using a disc-shaped cutter,i.e.,3+2-axis disc-slotting of the channel by multiple layers(rough machining)+five-axis disc-milling of the freeform channel side surfaces(semi-finish machining).Both simulation and physical cutting experiments are conducted to assess the effectiveness and advantages of the proposed *** experimental results show that,with respect to a same cusp-height threshold on the channel side surfaces,the total machining time of the tested part by the proposed method is about only 36%of that by the conventional approach of plunging-milling(for roughing)plus milling by a slender cylindrical cutter(for semi-finishing).

关键词： Blisk channel CNC machining Disc cutter Roughing efficiency Tool path planning

Wheat morphological and biochemical responses to copper oxide nanoparticles in two soils

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Pedosphere 2024年第4期34卷 814-825页

作者： qian YANG Haipeng li Yuqing zhANG Yinghao liU Helian li School of Water Conservancy and Environment University of JinanJinan 250022China

The widespread application of copper oxide nanoparticles(CuO NPs)in agricultural production has caused growing concerns about their impact on *** this study,wheat root elongation was used to evaluate the toxic effect concentrations of CuO NPs in two soils with differing properties,collected from farmlands in Guangdong(GD)and Shandong(SD)provinces,*** morphological and biochemical properties were also assessed to explore the toxicity mechanism of CuO NPs on wheat *** root elongation results revealed lower toxic effect concentration values in the plants grown in GD soil than in SD ***,the treatment with CuO NPs at 200 mg Cu kg^(-1) significantly reduced wheat root and shoot biomass by 35.8%and 15.8%,respectively,in GD *** microscopy showed that CuO NPs deformed wheat roots and entered leaf cells,causing deformation and damaging the cell *** CuO NP treatments also decreased chlorophyll content,increased antioxidant enzyme activity,and increased membrane lipid peroxidation in wheat *** addition of CuO NPs significantly reduced the Zn(by 17.3%)and Fe(by 26.9%)contents in the leaves of plants grown in GD and SD soils,***,the contents of Cu,Mg,and Mn were increased by 27.4%–52.5%in GD soil and by 17.9%–71.6%in SD *** results suggested that CuO NPs showed greater toxicity to wheat plants grown in acidic soil than in alkaline soil and that the adverse effects of CuO NP treatments on wheat seedlings were due to a combination of CuO NPs and released Cu^(2+).

关键词： antioxidant enzyme activity chlorophyll content CuO nanoparticles element accumulation membrane lipid peroxidation root elongation toxic effectconcentration

USP45 acts as an oncogene to regulate the proliferation of esophageal cancer cells

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Genes & Diseases 2024年第5期11卷 44-47页

作者： Kai li qian Wang Hua Bian zhang zhongjing College of Chinese Medicine Henan Key Laboratory of Zhang Zhongjing Formulae and Herbs for ImmunoregulationNanyang Institute of TechnologyNanyangHenan 473004China College of Orthopaedics and Traumatology Henan University of Chinese MedicineZhengzhouHenan 450046China

Deubiquitinases(DUBs)are a class of enzymes that are able to reverse the process of ubiquitination.1 Extensive research has revealed that there are more than 100 DUBs found in humans,which are classified into seven main families:ubiquitin-specific proteases(USPs),ubiquitin carboxyl-terminal hydrolases,the Machado-Joseph disease domain superfamily,the otubain/ovarian tumor-domain containing proteins,the ZUFSP(Zinc finger with UFM1-specific peptidase domain protein)family,the JAB1/MPN/MOV34 proteases,and the novel motif interacting with ubiquitin-containing DUB *** DUBs are cysteine proteases,except the JAB1/MPN/MOV34 proteases,which are Zn^(2+) metalloproteases.

关键词： esophageal cancer Zinc