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Sensing matrix Optimization for Random Stepped-Frequency Signal Based on Two-Dimensional Ambiguity Function

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Chinese Journal of Electronics 2024年第1期33卷 161-174页

作者： mingjiu LYU Hao CHEN jun YANG Xia WU ming ZHOU Xiaoyan ma Radar NCO School Air Force Early Warning Academy Department of Early Warning Technology Air Force Early Warning Academy

Compressive sensing technique has been widely applied to achieve range-Doppler reconstruction of high frequency radar by utilizing sparse random stepped-frequency(SRSF) signal, which can suppress the complex electromagnetic interference and greatly reduce the coherent processing interval. An important way to improve the performance of sparse signal reconstruction is to optimize the sensing matrix(SM). However, the existing research on the SM optimization needs to design a measurement matrix with superior performance, which needs a large amount of computation and does not consider the influence of the waveform parameters design. In order to improve the superior reconstruction performance, a novel SM optimization approach for SRSF signal is proposed by using two-dimensional ambiguity function(TDAF) in this paper. Firstly, based on the two-dimensional sparse reconstruction model of the SRSFs, the internal relationship between the waveform parameters and the SM was derived. Secondly, the SM optimization problem was directly transformed into the waveform design of SRSFs. Furthermore, on the basis of analyzing the relationship between the mutual coherence matrix of SM and the TDAF matrix of SRSFs, the purpose of optimizing the SM can be achieved by designing the TDAF of the SRSFs. Based on this analysis, a sparse waveform optimization method with joint constraints of maximum and mean sidelobes of the TDAF by using the genetic algorithm was derived. Compared with the traditional SM optimization method, our method not only avoids generating a new measurement matrix, but also further reduces the complexity of the waveform optimization. Simulation experiments verified the effectiveness of the proposed method.

关键词： Sparse random stepped-frequency signal Two-dimensional ambiguity function Waveform design Compressed sensing Sensing matrix optimization

High-entropy oxide-supported platinum nanoparticles for efficient hydrogen evolution reaction

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Rare Metals 2024年第4期43卷 1537-1546页

作者： ming-Yu Fan Jia-jun Wang jun Zhao Hong Zhang Tian-Yi ma Xiao-Peng Han Wen-Bin Hu School of materials Science and Engineering Tianjin Key Laboratory of Composite and Functional Materials Key Laboratory of Advanced Ceramics and Machining Technology Tianjin University School of National University of Singapore and Tianjin University International Campus of Tianjin University School of Science RMIT University

High-entropy oxides（HEOs） are a new class of single-phase structures with unique electronic and catalytic properties;therefore,it is worthwhile to explore their applications in electrocatalysis.In this study,a Pt/（FeCoNiCrAl）3O4nanohybrid using HEO as a support was developed as an efficient catalyst for the hydrogen evolution reaction（HER）.Pt/（FeCoNiCrAl）3O4exhibited high HER activity with a low overpotential of 22 mV at10 ma·cm-2,outperforming other binary,ternary,and quaternary supports.The HER activity of Pt/（FeCoNiCrAl）3O4was higher than that of a commercial Pt/C with a significantly lower Pt loading.The catalyst exhibited good activity and long-term stability（60 h） in an electrolytic water-splitting device.This good activity can be attributed to the fact that the introduction of Pt effectively facilitates electronic interactions between Pt and the HEO.In addition,the HEO substrate was more favorable for dispersing Pt particles,optimizing the electrochemical specific surface area,and significantly reducing the charge resistance of the HER.This study extends the application of HEOs in electrocatalysis and demonstrates the promising prospects of HEOs as supports for electrocatalysts.

关键词： High-entropy oxides Hydrogen evolution reaction Nanohybrid Water electrolysis

Deciphering and integrating invariants for neural operator learning with various physical mechanisms

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National Science Review 2024年第4期11卷 111-122页

作者： Rui Zhang Qi Meng Zhi-ming ma Academy of mathematics and Systems Science Chinese Academy of Sciences(CAS) Microsoft Research

Neural operators have been explored as surrogate models for simulating physical systems to overcome the limitations of traditional partial differential equation(PDE) solvers. However, most existing operator learning methods assume that the data originate from a single physical mechanism, limiting their applicability and performance in more realistic scenarios. To this end, we propose the physical invariant attention neural operator(PIANO) to decipher and integrate the physical invariants for operator learning from the PDE series with various physical mechanisms. PIANO employs self-supervised learning to extract physical knowledge and attention mechanisms to integrate them into dynamic convolutional layers.Compared to existing techniques, PIANO can reduce the relative error by 13.6%–82.2% on PDE forecasting tasks across varying coefficients, forces or boundary conditions. Additionally, varied downstream tasks reveal that the PI embeddings deciphered by PIANO align well with the underlying invariants in the PDE systems, verifying the physical significance of PIANO.

关键词： neural operator PDE solver contrastive learning physical invariants

Gradient sparsification for efficient wireless federated learning with differential privacy

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Science China(Information Sciences) 2024年第4期67卷 272-288页

作者： Kang WEI jun LI Chuan ma ming DING Feng SHU Haitao ZHAO Wen CHEN Hongbo ZHU School of Electronic and Optical Engineering Nanjing University of Science and Technology Zhejiang Lab Key Laboratory of Computer Network and Information Integration(Southeast University) Ministry of Education Data61 Commonwealth Scientific and Industrial Research Organisation School of Information and Communication Engineering Hainan University School of Communications and Information Engineering Nanjing University of Posts and Telecommunications School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University

Federated learning(FL) enables distributed clients to collaboratively train a machine learning model without sharing raw data with each other. However, it suffers from the leakage of private information from uploading models. In addition, as the model size grows, the training latency increases due to the limited transmission bandwidth and model performance degradation while using differential privacy(DP)protection. In this paper, we propose a gradient sparsification empowered FL framework with DP over wireless channels, to improve training efficiency without sacrificing convergence performance. Specifically, we first design a random sparsification algorithm to retain a fraction of the gradient elements in each client’s local model, thereby mitigating the performance degradation induced by DP and reducing the number of transmission parameters over wireless channels. Then, we analyze the convergence bound of the proposed algorithm, by modeling a non-convex FL problem. Next, we formulate a time-sequential stochastic optimization problem for minimizing the developed convergence bound, under the constraints of transmit power, the average transmitting delay, as well as the client’s DP requirement. Utilizing the Lyapunov drift-plus-penalty framework, we develop an analytical solution to the optimization problem. Extensive experiments have been implemented on three real-life datasets to demonstrate the effectiveness of our proposed algorithm. We show that our proposed algorithms can fully exploit the interworking between communication and computation to outperform the baselines, i.e., random scheduling, round robin, and delay-minimization algorithms.

关键词： federated learning differential privacy gradient sparsification Lyapunov drift convergence analysis

Investigation on UV-curing Reprocessable Thermosets Bearing Hindered Urea Bonds and Their Composites with Modified Zinc Oxide Nanoparticles

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Chinese Journal of Polymer Science 2024年第6期42卷 751-765页

作者： jun-Hao Zhou Li-ming Tang Key Laboratory of Advanced materials of Ministry of Education of China Department of Chemical EngineeringTsinghua UniversityBeijing100084China

In this study,a series of hindered urea bond(HUB)containing polyurethane-urea methacrylate prepolymers and a none HUB containing polyurethane methacrylate prepolymer were prepared using isobornyl methacrylate as the reactive diluent via one-pot procedure.The prepolymers were characterized fully by various techniques.Then,their thermosets were fabricated via UV curing in presence of a photo initiator,and their mechanical property and thermal behavior were investigated and compared.Different from the none HUB containing thermoset,the HUB containing thermosets(defined as PUT)could be recycled and reprocessed by hot press under relatively mild conditions with high recovery ratio of mechanical property.Furthermore,zinc oxide(ZnO)nanoparticles were modified with 3-(trimethoxysilyl)propyl methacrylate and the modified ZnO(defined as ZnO-TPM)was dispersed and polymerized into PUT matrix to prepare their nanocomposites.The influence of ZnO-TPM on the mechanical performance of the composites was evaluated,which indicated that the Young’s modulus and tensile strength increased gradually to the maximum values at ZnO-TPM content of 1 wt%and then decreased.The composites also displayed good reprocessability with improved recovery ratio compared to the pure PUT sample.In addition,the composite materials exhibited strong UV absorption capacity,implying their potential application in the circumstance where UV-shielding was required.

关键词： Polyurethane-urea methacrylate Hindered urea bond ZnO nanoparticles Reprocessing UV curing

A general synthetic strategy for N, P co-doped graphene supported metal-rich noble metal phosphides for hydrogen generation

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Green Energy & Environment 2024年第1期9卷 152-162页

作者： Jingwen ma Xiang Li Guangyu Lei jun Wang Juan Wang Jian Liu ming Ke Yang Li Chunwen Sun School of Chemical and Environmental Engineering China University of Mining and Technology(Beijing)Beijing100083China State Key Laboratory of Heavy Oil Processing China University of PetroleumBeijing102249China Lab of Advanced Nano-structures&Transfer Processes Department of Chemical EngineeringTianjin UniversityTianjin300354China PetroChina Planning and Engineering Institute Beijing100083China

The exploitation of electrocatalysts with high activity and durability for HER is desirable for future energy systems,but it is still a challenge.NMPs have attracted increasing attentions,but the preparation process often needs toxic regents or dangerous reaction conditions.Herein,we develop a general green method to fabricate metal-rich NMPs anchored on NPG through pyrolyzing DNA cross-linked complexes.The obtained Ru_(2) P-NPG exhibits an ultrasmall overpotential of 7 mV at 10 ma cm^(2) and ultralow Tafel slope of 33 mV dec^(-1) in 1.0 mol L?1 KOH,even better than that of commercial Pt/C.In addition,Ru 2 P-NPG also shows low overpotentials of 29 and 78 mV in 0.5 mol L^(-1) H_(2)SO_(4) and 1.0 mol L^(-1) PBS,respectively.The superior activity can be attributed to the ultrafine dispersion of Ru 2 P nanoparticles for more accessible sites,more defects formed for abundant active sites,the two-dimensional plane structure for accelerated electron transfer and mass transport,as well as the regulation of electron distribution of the catalyst.Moreover,the synthetic method can also be applied to prepare other metal-rich noble metal phosphides(Pd_(3)P-NPG and Rh_(2)P-NPG),which also exhibits high activity for HER.This work provides an effective strategy for designing NMP-based electrocatalysts.

关键词： Noble metal phosphides Electrocatalyst Deoxyribonucleic acid Hydrogen evolution pH universal

The diagnostic value of tenascin-C in acute aortic syndrome

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Journal of Geriatric Cardiology 2024年第3期21卷 359-368页

作者： ming ma Wei CHEN Hai-Long CAO jun PAN Qing ZHOU Xin-Long TANG Dong-Jin WANG Department of Thoracic and Cardiovascular Surgery Nanjing Drum Tower Hospital Clinical College of Nanjing Medical UniversityNanjingChina Department of Thoracic and Cardiovascular Surgery Nanjing Drum Tower HospitalAffiliated Hospital of Medical SchoolNanjing UniversityNanjingChina Department of Thoracic surgery Kunshan Hospital of Traditional Chinese MedicineJiangsuChina

OBJECTIVES Misdiagnosis of acute aortic syndrome(AAS)significantly increases mortality.Tenascin-C(TN-C)is an extracellular matrix glycoprotein related to cardiovascular injury.The elevation of TN-C in AAS and whether it can discriminate suddenonset of acute chest pain in Chinese remains unclear.METHODS We measured the plasma concentration of TN-C by ELISA in a cohort of 376 patients with chest or back pain.Measures to discriminate AAS from acute coronary syndrome(ACS)were compared and calculated.RESULTS From October 2016 to September 2021,376 undiagnosed patients with chest or back pain were enrolled.166 of them were finally diagnosed as AAS,100 were ACS and 110 without cardiovascular diseases(NCV).TN-C was significantly elevated in AAS at 18.18 ng/mL(IQR:13.10–27.68)compared with 7.51 ng/mL(IQR:5.67–11.38)in ACS(Pmance of TN-C was superior to D-dimer and hs-cTnT.CONCLUSIONS The concentration of serum TN-C in AAS patients was significantly higher than that in ACS patients and NCV.TN-C could be a new biomarker to distinguish AAS patients in the early stage after symptoms onset from other pain diseases.

关键词： acute cardiovascular elevated

Numerical simulations for radon migration and exhalation behavior during measuring radon exhalation rate with closed-loop method

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Nuclear Science and Techniques 2024年第1期35卷 81-95页

作者： ming Xia Yong-jun Ye Shu-Yuan Liu School of Resources Environment and Safety Engineering University of South ChinaHengyang 421001China Key Discipline Laboratory for National Defense for Biotechnology in Uranium Mining and Hydrometallurgy University of South ChinaHengyang 421001China

Accurate measurements of the radon exhalation rate help identify and evaluate radon risk regions in the environment.Among these measurement methods,the closed-loop method is frequently used.However,traditional experiments are insufficient or cannot analyze the radon migration and exhalation patterns at the gas–solid interface in the accumulation chamber.The CFD-based technique was applied to predict the radon concentration distribution in a limited space,allowing radon accumulation and exhalation inside the chamber intuitively and visually.In this study,three radon exhalation rates were defined,and two structural ventilation tubes were designed for the chamber.The consistency of the simulated results with the variation in the radon exhalation rate in a previous experiment or analytical solution was verified.The effects of the vent tube structure and flow rate on the radon uniformity in the chamber;permeability,insertion depth,and flow rate on the radon exhalation rate and the effective diffusion coefficient on back-diffusion were investigated.Based on the results,increasing the inser-tion depth from 1 to 5 cm decreased the effective decay constant by 19.55%,whereas the curve-fitted radon exhalation rate decreased(lower than the initial value)as the deviation from the initial value increased by approximately 7%.Increasing the effective diffusion coefficient from 2.77×10^(-7) to 7.77×10^(-6) m^(2) s^(-1) made the deviation expand from 2.14 to 15.96%.The conclusion is that an increased insertion depth helps reduce leakage in the chamber,subject to notable back-diffusion,and that the closed-loop method is reasonably used for porous media with a low effective diffusion coefficient in view of the back-diffusion effect.The CFD-based simulation is expected to provide guidance for the optimization of the radon exhalation rate measurement method and,thus,the accurate measurement of the radon exhalation rate.

关键词： Radon exhalation Numerical simulation Accumulation chamber

An adaptive energy regulation in a memristive map linearized from a circuit with two memristive channels

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Communications in Theoretical Physics 2024年第3期76卷 42-50页

作者： Feifei Yang Ping Zhou jun ma School of Science Chongqing University of Posts and TelecommunicationsChongqing 430065China College of Electrical and Information Engineering Lanzhou University of TechnologyLanzhou 730050China Department of Physics Lanzhou University of TechnologyLanzhou 730050China

Nonlinear circuits can show multistability when a magnetic flux-dependent memristor(MFDM) or a charge-sensitive memristor(CSM) is incorporated into a one branch circuit,which helps estimate magnetic or electric field effects.In this paper,two different kinds of memristors are incorporated into two branch circuits composed of a capacitor and a nonlinear resistor,thus a memristive circuit with double memristive channels is designed.The circuit equations are presented,and the dynamics in this oscillator with two memristive terms are discussed.Then,the memristive oscillator is converted into a memristive map by applying linear transformation on the sampled time series for the memristive oscillator.The Hamilton energy function for the memristive oscillator is obtained by using the Helmholtz theorem,and it can be mapped from the field energy of the memristive circuit.An energy function for the dual memristive map is suggested by imposing suitable weights on the discrete energy function.The dynamical behaviors of the new memristive map are investigated,and an adaptive law is proposed to regulate the firing mode in the memristive map.This work will provide a theoretical basis and experimental guidance for oscillator-to-map transformation and discrete map energy calculation.

关键词： Hamilton energy dual memristive map adaptive energy regulation