Tongji University
  • Shanghai, China
Recent publications
The emergence of the fifth-generation (5G) New Radio (NR) technology has provided unprecedented opportunities for vehicle-to-everything (V2X) networks, enabling enhanced quality of services. However, high-mobility V2X networks require frequent handovers and acquiring accurate channel state information (CSI) necessitates the utilization of pilot signals, leading to increased overhead and reduced communication throughput. To address this challenge, integrated sensing and communications (ISAC) techniques have been employed at the base station (gNB) within vehicle-to-infrastructure (V2I) networks, aiming to minimize overhead and improve spectral efficiency. In this study, we propose novel frame structures that incorporate ISAC signals for three crucial stages in the NR-V2X system: initial access, connected mode, and beam failure and recovery. These new frame structures employ 75% fewer pilots and reduce reference signals by 43.24%, capitalizing on the sensing capability of ISAC signals. Through extensive link-level simulations, we demonstrate that our proposed approach enables faster beam establishment during initial access, higher throughput and more precise beam tracking in connected mode with reduced overhead, and expedited detection and recovery from beam failures. Furthermore, the numerical results obtained from our simulations showcase enhanced spectrum efficiency, improved communication performance and minimal overhead, validating the effectiveness of the proposed ISAC-based techniques in NR V2I networks.
Effective Service Function Chains (SFCs) mapping and Virtual Network Functions (VNFs) scheduling are crucial to ensure high-quality service provision for Internet of Things (IoT) tasks. Meeting the varying demands of multiple SFCs poses a significant challenge, particularly when working with the limited resources available in edge computing networks. Most existing working focuses on uniformly mapping and scheduling service requests in a batch processing manner within a given time period, without taking the diversity and priority of VNFs into account. When there is a sudden surge in demand, the issues of VNF queueing waiting and resources imbalance become prominent. To address the mentioned issues, this paper proposes a Deep Reinforcement Learning (DRL)-based VNF cooperative scheduling framework with priority-weighted delay. In light of the urgency of VNFs with higher priorities and the limitations of available resources, we begin by modeling an average queuing delay with priority weight based on the shortest remaining time priority technique. We then formulate a mathematical optimization problem to minimize the modeled delay in VNF scheduling process while providing suitable multidimensional resources in the edge network. Finally, a DRL method with experience replay and target Q-network is designed to effectively obtain the optimal solutions of the optimization problem from experience. The experimental results show that our proposed method outperforms its peers in terms of SFC request acceptance, delay, load balance, and resource utilization.
To raise the real-time performance of the path tracking controller based on nonlinear model predictive control (NMPC), this article presents a parallel NMPC controller based on Newton optimization algorithm and field programmable gate array (FPGA) implementation for path tracking control of autonomous vehicle. First, a nonlinear vehicle dynamics model is established to represent the nonlinear and coupling properties of vehicle system, and an integrated NMPC controller relies that on a single controller is designed for path tracking. Second, software and hardware parallel calculations are utilized to accelerate the online computation speed of NMPC controller. One is using a parallel Newton algorithm to reduce the complexity of the NMPC optimization problem by utilizing reasonable approximations of the coupling variables to break down the recursion process. The other one is the FPGA hardware acceleration of NMPC. Through analyzing different FPGA design schemes, the most suitable implementation is chosen with the tradeoff between hardware resource and achievable speed. Finally, simulations and hardware-in-theloop experiment are conducted to validate the effectiveness and real-time performance of the proposed parallel NMPC path tracking controller.
This article investigates two-player attack-defense (AD) games involving players with bounded rationality, where the defender aims to intercept the attacker, while the attacker aims to invade the protected area and avoid interception. We first set path planning optimization problems in a receding horizon fashion for each player and formulate the AD game. Then, using the level- k model of behavioral game theory, we specify the decision mechanisms for players with bounded rationality. We propose an adaptive path planning strategy, coupled with the Bayesian learning method, for the defender to counter the attacker with an unknown reasoning level of the decision mechanism. The Bayesian inference algorithm, which combines current observation information and historical receding horizon prediction trajectories to form the belief on the attacker’s reasoning level, allows the defender to generate an adaptive interception trajectory with the multimodel strategy. Finally, both numerical simulations and experiments confirm the effectiveness of the proposed algorithm.
The suppression of high-frequency (HF) common-mode (CM) switching oscillations in inverter-fed machine systems is a critical yet challenging task, primarily due to the presence of self-resonance in CM propagation paths, such as parasitic parameters of the filter. This article presents a novel approach based on parity-time (PT) symmetry to mitigate HFCM switching oscillation by utilizing a magnetically coupled external resonator to efficiently transfer transient oscillation energy. First, the HFCM switching oscillation in an inverter-fed machine system, treated as an internal resonator, is analyzed along with its modal characteristics. Subsequently, an external resonator is designed to operate at the exceptional point (EP) of PT symmetry for the suppression of oscillation modes. Experimental results obtained from a 380 V/3 kW variable-frequency drive (VFD) test rig demonstrate that the specially designed external reactor can effectively reduce the HFCM oscillation mode at 3 MHz by approximately 45% and attenuate the resonance spike in the CM spectrum by up to 13 dB. This solution is characterized by noncontact safety, compact size, excellent attenuation, and configurable flexibility.
bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C loud- a ided m obile e dge n etworks (CAMENs) allow edge servers (ESs) to purchase resources from remote cloud servers (CSs), while overcoming resource shortage when handling computation-intensive tasks of mobile users (MUs). Conventional trading mechanisms (e.g., onsite trading) confront many challenges, including decision-making overhead (e.g., latency) and potential trading failures. This paper investigates a series of cross-layer matching mechanisms to achieve stable and cost-effective resource provisioning across different layers (i.e., MUs, ESs, CSs), seamlessly integrated into a novel hybrid paradigm that incorporates futures and spot trading. In futures trading, we explore an o verbooking-driven a forehand c ross- l ayer m atching (OA-CLM) mechanism, facilitating two future contract types: contract between MUs and ESs, and contract between ESs and CSs, while assessing potential risks under historical statistical analysis. In spot trading, we design two backup plans respond to current network/market conditions: determination on contractual MUs that should switch to local processing from edge/cloud services; and an o n s ite c ross- l ayer m atching (OS-CLM) mechanism that engages participants in real-time practical transactions. We next show that our matching mechanisms theoretically satisfy stability, individual rationality, competitive equilibrium, and weak Pareto optimality. Comprehensive simulations in real-world and numerical network settings confirm the corresponding efficacy, while revealing remarkable improvements in time/energy efficiency and social welfare.
In this paper, we study the collaborative detection problem in a multi-agent environment. By exploiting onboard range-bearing sensors, mobile agents make sequential control decisions such as moving directions to gather information of movable targets. To estimate target states, i.e., target location and velocity, the classic works such as Kalman Filter (KF) and Extended Kalman Filter (EKF) impractically assume that the underlying state space model is fully known, and some recent learning-based works, i.e., KalmanNet, estimate target states alone but without estimation uncertainty, and cannot make robust control decision. To tackle such issues, we first propose a neural network-based state estimator, namely T W o-phase K AL ma n Filter with U ncertainty quan T ification (WALNUT), to explicitly give both target states and estimation uncertainty. The developed multi-agent reinforcement learning (MARL) model then takes the learned target states and uncertainty as input and makes robust actions to track movable targets. Our extensive experiments demonstrate that our work outperforms the state-of-the-art by higher tracking ability and lower localization error.
Advanced sensors based on electrochemical impedance spectroscopy (EIS) are essential for fuel cell system state estimation, fault diagnosis, and health management. However, traditional EIS methods are unsuitable for real-time state management due to high costs, large sizes, and long acquisition times, limiting their online industrial application. To enhance onboard EIS application, this study proposes a novel multi-stage and multi-sine (MSS) injection method to improve wideband frequency sweeping, balancing EIS quality and measurement time using a four-phase floatinginterleaving parallel DC-DC converter prototype with EIS injection functions. Additionally, a fuel cell coupled with a fourphase floating-interleaving parallel DC-DC equivalent circuit model is established for comprehensive performance analysis in impedance calculation with different excitation methods. Experimental validation showed an impedance magnitude error within 3.2% from 1kHz to 0.1Hz, and the implementation reduces EIS measurement time from 900s to approximately 150s. Furthermore, a case study on fuel cell EIS sensitivity under dynamic conditions indicates that the proposed prototype can capture dynamic EIS variations using local multi-frequency points.
This two-part paper focuses on the system design and performance analysis for a point-to-point resonant beam communication (RBCom) system under both the quasi-static and mobile scenarios. Part I of this paper proposes a synchronization-based information transmission scheme and derives the capacity upper and lower bounds for the quasi-static channel case. In Part II, we address the mobile scenario, where the receiver is in relative motion to the transmitter, and derive a mobile RBCom channel model that jointly considers the Doppler effect, channel variation, and echo interference. With the obtained channel model, we prove that the channel gain of the mobile RBCom decreases as the number of transmitted frames increases, and thus show that the considered mobile RBCom terminates after the transmitter sends a certain number of frames without frequency compensation. By deriving an upper bound on the number of successfully transmitted frames, we formulate the throughput maximization problem for the considered mobile RBCom system, and solve it via a sequential parametric convex approximation (SPCA) method. Finally, simulation results validate the analysis of our proposed method in some typical scenarios.
This letter proposes a novel demagnetization fault diagnosis scheme for the interior permanent magnet (IPM) motor without parameter estimation. Firstly, a feature enhancement-based disturbance observer is proposed, which incorporates the estimation error and the sliding mode surface as reinforcement factors for fault characteristics. Then, a sliding mode assessment-based demagnetization fault diagnosis method is developed, which takes the sliding mode variable structure signal of the disturbance observer as the carrier of demagnetization fault. Finally, the proposed method is validated by the hardware-in-the-loop (HIL)-based platform and the real hardware platform. The test results show that the proposed method can achieve millisecond-level demagnetization fault diagnosis without being affected by mismatch in stator resistance of the IPM motor.
Bezafibrate (BZF), an extensively used lipid-regulating agent, has been frequently detected in aqueous environments. In this work, we systematically investigated the Fe(II)/sulfite process for degrading BZF and its impact on disinfection byproducts (DBPs) during postchlorination. Degradation conditions were optimized by adjusting the pH, sulfite concentration, Fe(II), and BZF concentration. Under the conditions of pH = 4, [BZF]0 = 5 μM, [Fe(II)]0 = 25 μM, and [sulfite]0 = 250 μM, the BZF removal efficiency reaches 97.9% in 15 min. Sulfate radicals (SO4●–) and singlet oxygen (1O2) are recognized as the main reactive agents, with Fe(IV) also contributing to the removal of BZF. Common anions (Cl− and HCO3−) and humic acid generally impede the degradation process, except that trace amounts of Cl− can slightly accelerate BZF degradation. A total of ten products are recognized by ultra high performance liquid chromatography and quadrupole time-of-flight mass spectrometry, and four major degradation pathways are proposed: hydroxylation, cleavage of amino bonds, removal of fibrate chains, and dechlorination. Meanwhile, the toxicity assessment shows that the majority of products exhibit lower biological toxicity and less bioaccumulation potential than BZF itself. The Fe(II)/sulfite pretreatment alters the DBP formation potential, especially when Br− is present. The formation of trichloromethane (TCM) is diminished following pretreatment with the Fe(II)/sulfite process, whereas a noticeable increase in the formation of dichloroacetonitrile (DCAN) is found. Moreover, Fe(II)/sulfite pretreatment enhances the formation of brominated DBPs. Therefore, special consideration should be given to DBP formation when a Fe(II)/sulfite system is employed as a pretreatment for the removal of BZF in water.
The conversion of 5‐hydroxymethylfurfural (HMF) to 2,5‐diformylfuran (DFF) is a promising approach for enhancing biomass utilization. Nevertheless, traditional methods using noble metal catalysts face challenges due to high costs and poor selectivity towards DFF. Herein, we developed a novel catalytic electrode integrating N‐hydroxyphthalimide (NHPI) into a metal‐organic framework on a hydrophilic carbon cloth. This design significantly enhances the selective adsorption of HMF due to stronger hydrogen‐bond interaction between the electrode's hydrophilic surface and the C(sp³)−OH group in HMF compared to the C(sp²)=O in DFF. Additionally, the electro‐driven dissociation of the NHPI‐linker generates stabilized N‐Oxyl radicals that promote selective semi‐oxidation of HMF under neutral conditions. As a result, this approach achieves a high yield rate of 138.2 mol molcat⁻¹ h⁻¹ with a selectivity of 96.7 % for the HMF‐to‐DFF conversion. This work introduces a novel strategy for designing catalytic electrodes with stabilized N‐Oxyl radicals, and offers a promising method for electrocatalytic DFF synthesis, leveraging hydrogen‐bond interaction between electrode surface and HMF.
  • Lishu Zhao
    Lishu Zhao
  • Jianxian Ge
    Jianxian Ge
  • Ruru Zhang
    Ruru Zhang
  • [...]
  • Mingyuan Gao
    Mingyuan Gao
Immunotherapy has significantly improved cancer patient survival, while its efficacy remains limited due to the reliance on a single marker like PD‐L1 as well as its spatiotemporal heterogeneity. To address this issue, combining lymphocyte activation gene‐3 (LAG‐3) with PD‐L1 is proposed for identifying immunotypes and monitoring immunotherapy through nuclear imaging. In short, 99mTc‐HYNIC‐αLAG‐3 and 99mTc‐HYNIC‐αPD‐L1 probes are synthesized using anti‐human LAG‐3 and PD‐L1 antibodies, respectively. With high radiochemical purity and in vitro stability, these probes are confirmed to specifically bind to LAG‐3 or PD‐L1 in LAG3⁺ A549, LAG3⁻ A549, and H1975 cells. SPECT/CT imaging of both probes showed specific in vivo tumor uptake in multiple lung cancer models, with significant linear correlation with ex vivo tumor uptake and immunohistochemical expression levels of LAG‐3/PD‐L1. Based on this, dual‐index imaging was performed to simultaneously quantify LAG‐3 and PD‐L1. SPECT/CT imaging of 99mTc‐HYNIC‐αLAG‐3 and ¹²⁵I‐αPD‐L1 successfully distinguished four immunotypes. In addition, SPECT/CT imaging revealed LAG‐3 upregulation in LLC‐bearing LAG‐3 humanized mice resistant to immunotherapy. In conclusion, this study demonstrates the feasibility of nuclear imaging of LAG‐3 and PD‐L1 for both noninvasive immunotyping and immunotherapy monitoring, thus offering novel perspectives on forecasting immunotherapy response, uncovering resistance mechanism, and optimizing combination treatment regimens.
  • Penghui Li
    Penghui Li
  • Yantan Zhou
    Yantan Zhou
  • Yiwei Zhen
    Yiwei Zhen
  • [...]
  • Xiangyong Meng
    Xiangyong Meng
In order to ensure the safety of urban drainage and alleviate urban waterlogging, this study focuses on the impact of dynamic river water levels on pipeline drainage. The region south of Yiwu River in Yiwu City was selected as the study area. Utilizing the Mike modeling platform, simulations were conducted to assess pipeline drainage outlets under heavy rainfall conditions with return periods of 2-year, 3-year, and 5-year. These simulations considered connections to both the river's normal water level and various flood scenarios based on different design frequencies. The study also analyzed the influence of changes in river water levels on the drainage capacity of the pipeline network and their impact on urban waterlogging. This research provides a reference basis for understanding the causes of urban waterlogging in the study area and its mitigation.
  • Deyou Yin
    Deyou Yin
  • Xiuyong Shi
    Xiuyong Shi
  • Jimin Ni
    Jimin Ni
  • Hua Liu
    Hua Liu
Lithium-ion power batteries have become integral to the advancement of new energy vehicles. However, their performance is notably compromised by excessive temperatures, a factor intricately linked to the batteries’ electrochemical properties. To optimize lithium-ion battery pack performance, it is imperative to maintain temperatures within an appropriate range, achievable through an effective cooling system. This paper delves into the heat dissipation characteristics of lithium-ion battery packs under various parameters of liquid cooling systems, employing a synergistic analysis approach. The findings demonstrate that a liquid cooling system with an initial coolant temperature of 15 °C and a flow rate of 2 L/min exhibits superior synergistic performance, effectively enhancing the cooling efficiency of the battery pack. The highest temperatures are 34.67 °C and 34.24 °C, while the field synergy angles are 79.3° and 67.9°, achieved by optimizing the initial coolant temperature and flow rate. The structure of the 10 coolant pipes has a good consistency. As the charge/discharge rate increases, battery heating power escalates, resulting in a notable rise in temperature and synergy angle. Optimal cooling efficiency is achieved with three cooling channel inlets, minimizing the temperature difference across the battery pack.
  • Xiao‐Zhong Jing
    Xiao‐Zhong Jing
  • Gai‐Ying Li
    Gai‐Ying Li
  • Yu‐Peng Wu
    Yu‐Peng Wu
  • [...]
  • Jian‐Qi Li
    Jian‐Qi Li
Background Diffusion tensor imaging (DTI) is susceptible to partial volume effects from free water, which can be corrected by using bi‐tensor free water imaging (FWI). This approach may improve the evaluation of microstructural changes associated with Wilson's disease (WD). Purpose To investigate microstructural changes in white matter of WD using DTI and FWI. Study Type Prospective. Subjects Nineteen neurological WD (7 female, 31.68 ± 7.89 years), 10 hepatic WD (3 female, 29.67 ± 13.37 years), and 25 healthy controls (13 female, 29.5 ± 7.7 years). Field Strength/Sequence 3‐T, spin‐echo echo‐planar imaging diffusion‐weighted imaging, T1‐weighted, T2‐weighted, fluid‐attenuated inversion recovery. Assessment Various diffusion metrics, including mean diffusivity (MD), radial diffusivity (RD), fractional anisotropy (FA), axial diffusivity (AD), free water, and free water‐corrected metrics (MD T , RD T , FA T , and AD T ) were estimated and compared across entire white matter skeleton among neurological WD, hepatic WD, and controls. Voxel‐wise tract‐based spatial statistics and region of interest (ROI) analysis based on white matter atlas were performed. Additionally, partial correlation analysis was conducted to assess the relationship between FWI indices in ROIs and clinical indicators. Statistical Tests One‐way analysis of variance, family‐wise error correction for multiple comparisons, and Bonferroni correction for post hoc comparisons. A P ‐value <0.05, corrected for multiple comparisons, was considered statistically significant. Results Our study found significantly lower FA and higher MD, AD, and RD across most of white matter skeleton in neurological WD. Decreased FA T and increased MD T , AD T , and RD T were observed only in limited white matter areas compared to DTI indices. Additionally, a significant relationship was found between Unified WD Rating Scale neurological subscale of neurological WD and free water ( r = 0.613) in middle cerebellar peduncle, AD T ( r = −0.555) in superior cerebellar peduncle, RD T ( r = 0.655), and FA T ( r = −0.660) in posterior limb in internal capsule. Data Conclusion FWI may allow a more precise evaluation of microstructural changes in WD than conventional DTI, with FWI metrics potentially correlating with clinical severity scores of WD patients. Level of Evidence 2 Technical Efficacy Stage 2
  • Fengshou Zhang
    Fengshou Zhang
  • Wenzhi Zhao
    Wenzhi Zhao
  • Mengke An
    Mengke An
  • [...]
  • Manchao He
    Manchao He
The projected evolutionary history of the Moon and observed occurrence of moonquakes suggest that brittle faulting is present in the shallow lunar crust. The main component of the lunar crust, plagioclase, shows velocity‐strengthening behavior in the range of crustal temperatures. Chang'e 5 samples of lunar regolith show a mineral composition almost identical to basaltic bedrock. We measured the friction‐stability characteristics of dry synthetic gouges representative of basaltic faults assumed to be present in the lunar crust. Frictional strengths are ∼0.7 and exhibit an overall velocity‐strengthening response but transition to velocity‐weakening at intermediate temperatures (∼200–300°C) and stresses (∼25–100 MPa). Bounding temperature profiles representative of the lunar crust suggest that moonquakes are feasible in the lunar crust. The rheological heterogeneity of mineral fragments in basalt is a potential cause of unstable sliding on faults with the related steady‐state stress drop close to the minimum of the estimated dynamic stress drop. This suggests that some events with small stress drops are associated with the instability of mature basalt faults. However, observations of shallow moonquakes with high stress drop but merely moderate magnitude suggest that high degrees of healing on immature faults, small seismic nucleation lengths, or the failure of intact crust are present. We emphasize that moonquakes may arise from stress transfer and accumulation due to processes such as cooling contraction.
  • Yao Wang
    Yao Wang
  • Jiahui Ling
    Jiahui Ling
This paper explores the classification, formation, measurement, evolution, and influencing factors of land dividends in China.It analyzes the nature of land value dividends and efficiency dividends, examines their spatio-temporal evolution, and investigates influencing factors via a regression model, providing insights for future development. The paper posits that changes in land use patterns primarily contribute to land value dividends, while efficiency dividends stem from improving land use efficiency within existing patterns. Presently, China is transitioning from a phase dominated by land value dividends to one marked by efficiency dividends. In terms of spatio-temporal dynamics, efficiency dividends display a fluctuating upward trajectory, whereas land value dividends and the overall quantity of land dividends demonstrate an initial ascent followed by a gradual decline, with the central region exhibiting the most pronounced changes. The analysis of influencing factors reveals a significant positive correlation between value dividends, the overall quantity of land dividends, and factors such as land transfer and capital investment, while efficiency dividends exhibit a significant positive correlation with urbanization. Consequently, the government should implement measures to sensibly regulate land quantity and layout, promote intensive and efficient land use, activate dormant land resources, and propel the optimization and high-quality development of land dividends.
Sodium‐ion batteries (SIBs) have demonstrated significant potential as alternatives to conventional lithium‐ion batteries (LIBs) for modern grid and mobile energy storage applications, due to the abundant natural resources and low cost of sodium. Layered transition metal oxides (LTMOs) have attracted much attention due to their high specific capacities, energy densities as well as the compatible preparation processes with those of LIBs cathode materials. Among these, Ni/Mn‐based LTMOs (NMLOs) are particularly noteworthy for their cost‐effectiveness and superior electrochemical performance, such as excellent capacity retention, voltage stability, high operating voltage and rate capability. In this review, we briefly introduce the synthesis methods of NMLOs, discuss the challenges, and summarize the solutions. The insights presented may contribute to the development of NMLOs based SIBs.
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23,117 members
Zhanju Liu
  • Shanghai No.10 People's Hospital
Zhe Liang
  • Department of Management Science and Engineering
Qinghui Huang
  • Department of Environmental Science
Wenxin Niu
  • Medical School
Fang Liu
  • College of Civil Engineering
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Shanghai, China