In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the d...In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the direction of the self-mixing fringes accurately and quickly.In the process of measurement,the measurement signal can be normalized and then the neural network can be used to discriminate the direction.Simulation and experimental results show that the proposed method is suitable for self-mixing interference signals with noise in the whole weak feedback regime,and can maintain a high discrimination accuracy for signals interfered by 5 dB large noise.Combined with fringe counting method,accurate and rapid displacement reconstruction can be realized.展开更多
Accurate measurements of dual parameters of phase retardance and retardance axis of birefringent materials are of fundamental importance to their fabrication and applications.However,current techniques typically exhib...Accurate measurements of dual parameters of phase retardance and retardance axis of birefringent materials are of fundamental importance to their fabrication and applications.However,current techniques typically exhibit limited versatility,suffering from high complexity,insufficient accuracy,and low efficiency.In this study,we propose and demonstrate the anisotropic laser feedback polarization effect for birefringent measurement,featuring simultaneous dual-parameter demodulation,unified polarization modulation-analysis architecture,high detection sensitivity,user-friendly operation,and versatile functionality.Importantly,such system can be self-calibrated with its own physical phenomena to reduce the installation derivation.To showcase the powerful effectiveness,we perform the static birefringence,dynamic birefringence variation,and spatial birefringence distribution,which remarkably exhibits the standard deviation of 0.0453°and 0.0939°for phase retardance and retardance axis azimuth,with the limit allowable sample transmittance around 10^(–5).This work demonstrates comprehensive applicability across diverse birefringence scenarios,extending the application of anisotropic laser feedback polarization effect,while establishing a novel strategy for birefringence measurement.展开更多
To achieve the potential performance gain of massive multiple-input multiple-output(MIMO)systems,base stations(BS)require downlink channel state information(CSI)fed back by users to execute beamforming design,especial...To achieve the potential performance gain of massive multiple-input multiple-output(MIMO)systems,base stations(BS)require downlink channel state information(CSI)fed back by users to execute beamforming design,especially in the frequency division duplex(FDD)systems.However,due to the enormous number of antennas in massive MIMO systems,the feedback overhead of downlink CSI acquisition is extremely large.To address this issue,deep learning(DL)techniques have been introduced to de velop high-accuracy feedback strategies under limited backhaul constraints.In this paper,we provide an overview of DL-based CSI compression and feedback approaches in massive MIMO systems.Specifically,we introduce the conventional CSI compression and feedback schemes and the existing problems.Besides,we elaborate on various DL techniques employed in CSI compression from the perspective of network architecture and analyze the advantages of different techniques.We also enumerate the applications of DL-based methods for solving practical challenges in CSI compression and feedback.In addition,we brief the remaining issues in deep CSI compression and indicate potential directions in future wireless networks.展开更多
Energy-regenerative suspension combined with piezoelectric and electromagnetic transduction has evolved into a core technological pathway in advancing automotive design paradigms.With the aim of improving energy harve...Energy-regenerative suspension combined with piezoelectric and electromagnetic transduction has evolved into a core technological pathway in advancing automotive design paradigms.With the aim of improving energy harvesting performance,time-delayed feedback control is widely used in an energy-regenerative suspension system under different external disturbances in this paper.Meanwhile,limited research has addressed the stochastic dynamics of time-delayed nonlinear energy-regenerative suspension systems.Different from previous studies,this work studies the stochastic response and P-bifurcation of the nonlinear energy-regenerative suspension system with time-delayed feedback control.Firstly,an approximately equivalent dimension reduction system is established by the variable transformation method,and then the stationary probability density function of amplitude is obtained by the stochastic averaging method.Secondly,the precision of the method used in this work is verified by comparing the numerical solutions with the analytical results.Finally,based on the stationary probability density function,the influence of system parameters on stochastic P-bifurcation and the mean output power is discussed.展开更多
This study investigates the impact of vegetation-climate feedback on the global land monsoon system during the Last Interglacial(LIG,127000 years BP)and the mid-Holocene(MH,6000 years BP)using the earth system model E...This study investigates the impact of vegetation-climate feedback on the global land monsoon system during the Last Interglacial(LIG,127000 years BP)and the mid-Holocene(MH,6000 years BP)using the earth system model EC-Earth3.Our findings indicate that vegetation changes significantly influence the global monsoon area and precipitation patterns,especially in the North African and Indian monsoon regions.The North African monsoon region experienced the most substantial increase in vegetation during both the LIG and MH,resulting in significant increases in monsoonal precipitation by 9.8%and 6.0%,respectively.The vegetation feedback also intensified the Saharan Heat Low,strengthened monsoonal flows,and enhanced precipitation over the North African monsoon region.In contrast,the Indian monsoon region exhibited divergent responses to vegetation changes.During the LIG,precipitation in the Indian monsoon region decreased by 2.2%,while it increased by 1.6%during the MH.These differences highlight the complex and region-specific impacts of vegetation feedback on monsoon systems.Overall,this study demonstrates that vegetation feedback exerts distinct influences on the global monsoon during the MH and LIG.These findings highlight the importance of considering vegetation-climate feedback in understanding past monsoon variability and in predicting future climate change impacts on monsoon systems.展开更多
The performance of lithium-sulfur batteries(LSBs)is severely limited by a detrimental negative feedback loop:sluggish polysulfide conversion kinetics lead to Li_(2)S accumulation,which further hinders lithiumion trans...The performance of lithium-sulfur batteries(LSBs)is severely limited by a detrimental negative feedback loop:sluggish polysulfide conversion kinetics lead to Li_(2)S accumulation,which further hinders lithiumion transport and exacerbates capacity decay.To address this,we propose a positive feedback strategy that simultaneously enhances lithium polysulfides(LiPSs)conversion and lithium-ion diffusion through a rationally designed separator.By modifying the separator with phosphorus-doped two-dimensional hollow holey carbon nanosheets(Hollow HCNS),we establish an interconnected network where rapid LiPSs confinement and conversion within the hollow cavities promote efficient lithium-ion transport,while the improved ion flux further accelerates reaction kinetics.This mutual reinforcement mechanism ensures stable cycling by suppressing the shuttle effect and promoting uniform Li_(2)S deposition,as verified by in situ spectroscopic and electrochemical analysis.The resulting LSBs exhibit high-rate capability,ultralow capacity decay,and exceptional stability under high sulfur loading.This work presents a general approach to overcoming the persistent negative feedback problem in high-energy battery systems by synergistically optimizing catalytic conversion and ionic transport.展开更多
The development of electrocatalysts that both work effectively at industrial current density and resist chloride ion(Cl^(-))corrosion remains a key challenge for hydrogen production from Cl^(-)-rich alkaline water.Her...The development of electrocatalysts that both work effectively at industrial current density and resist chloride ion(Cl^(-))corrosion remains a key challenge for hydrogen production from Cl^(-)-rich alkaline water.Herein,we report a CrO_(x)-engineered nickel-based oxide catalyst(FeCoCrO_(x)/NF)that achieves exceptional activity and stability through a dual-functional interfacial mechanism.Combing in situ Raman spectroscopy,18O isotopic labeling,and electrochemical analysis,we demonstrate that the oxygen evolution reaction follows a lattice oxygen-mediated mechanism.The CrO_(x)layer selectively adsorbs hydroxide ions,forming a dynamic interfacial barrier that electrostatically repels Cl^(-)ingress,thereby mitigating Cl^(-)corrosion.Through enthalpy-based analysis,we demonstrate that electronic redistribution via Cr-O-Fe bonding increases the vacancy formation energy of Fe,thereby suppressing its dissolution.In alkaline electrolyte containing 0.5 M Cl^(-)(1.0 M KOH),the catalyst is operating continuously for 1400 h at an industrial current density of 1000 mA cm^(-2).Furthermore,the catalyst retains 99.5%of its initial activity under fluctuating current density(100-1000 mA cm^(-2)),demonstrating robustness required for industrial electrolyzers.This study establishes a paradigm for designing corrosion-resistant electrocatalysts through the synergistic modulation of interfacial ion selectivity and bulk lattice oxygen activation,advancing the application of green hydrogen production in Cl^(-)-rich alkaline water.展开更多
This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loo...This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loop EIV system and its coprime factor(CF)uncertainty description is first derived,based on which the FR measurements suitable for plant CF identification are able to be generated.Different factorizations of a given controller in the closed-loop system can be made best use to adjust right coprime factors(RCFs)of the plant so as to realize an improvement on the signal-to-noise ratio of identification experimental data.Subsequently,a nominal RCF model is estimated by linear matrix inequalities from the applicable FR measurements and its associated worst-case errors are quantified from a priori and a posteriori information on the underlying system.A resulting RCF perturbation model set can then be described by the nominal RCF model and its worst-case error bounds.Such a model set capable of being stabilized by the given controller is ready for its robust stabilizing controller redesign and robust performance analysis.Finally,a numerical simulation is given to show the efficacy of the proposed identification method.展开更多
Online programming platforms are popular in programming education.However,there has been no research investigating students’real opinions and expectations of the error feedback mechanisms,leaving educators without a ...Online programming platforms are popular in programming education.However,there has been no research investigating students’real opinions and expectations of the error feedback mechanisms,leaving educators without a solid data foundation when attempting to improve the error feedback mechanisms.This paper makes a survey of 834 students across various programming courses and investigates student perceptions of error feedback mechanisms on online programming platforms.It explores the effectiveness of existing feedback,student satisfaction,and preferences for potential improvements,focusing on automatic error localization and program repair mechanisms.Results reveal a significant portion of students are dissatisfied with current feedback due to its limited informativeness.Students also express a clear demand for stronger feedback mechanisms,such as error localization and repair hints.Nevertheless,they prefer feedback that subtly guides them toward solutions,rather than providing direct and explicit answers,valuing the opportunity to enhance their debugging skills.The findings suggest a need for balanced,educational-focused feedback mechanisms that aid learning while promoting independent problem-solving.展开更多
In massive multiple-input multiple-output(MIMO)systems utilizing frequency division duplexing,optimizing system performance requires user equipment(UE)to compress downlink channel state information(CSI)and transmit it...In massive multiple-input multiple-output(MIMO)systems utilizing frequency division duplexing,optimizing system performance requires user equipment(UE)to compress downlink channel state information(CSI)and transmit it to the base station(BS).As the number of antennas increases,there is a significant rise in the overhead related to CSI feedback,posing considerable challenges to the precise acquisition of CSI by the BS.Existing approaches to CSI feedback utilizing deep learning techniques face challenges such as significant feedback overhead and limited precision in the reconstruction process.This study presents a novel lightweight CSI feedback framework known as the dual attention neural network(DANet).Within the DANet architecture,a dual attention module(DAM)is designed to enhance the network's performance.This DAM includes both channel attention blocks and spatial attention blocks.The channel attention blocks direct the model's focus toward channel features rich in information content while simultaneously suppressing less significant features.This approach enables the extraction of temporal correlations within the CSI matrix.The spatial attention block aids in extracting the correlation between the delay domain and the angle domain in the CSI matrix.By enhancing neural network performance,the DAM reduces information dispersion while enhancing the representation of global interactions.Simulation results demonstrate that DANet exhibits superior normalized mean square error and cosine similarity with comparable complexity compared to existing advanced CSI feedback methods.展开更多
Self-trapped excitons(STEs),known for their unique radiative properties,have been harnessed in diverse photonic devices;however,their comprehensive understanding and manipulation remain elusive.In this study,we presen...Self-trapped excitons(STEs),known for their unique radiative properties,have been harnessed in diverse photonic devices;however,their comprehensive understanding and manipulation remain elusive.In this study,we present novel experimental and theoretical evidence revealing the hybrid nature and optical tunability of STE state in Cs_(2)Ag_(0.4)Na_(0.6)InCl_(6).The detection of the Fano resonance in laser energy-dependent Raman and photoluminescence spectra indicates the emergence of an exciton-phonon hybrid state,arising from robust quantum interference between the discrete phonon and continuum exciton states.Moreover,we demonstrate continuous tuning of this hybrid state with the energy and intensity of the laser field.These findings lay the foundation for a comprehensive understanding of the nature of STE and their potential for state control.展开更多
Self-supported nanoarrays have emerged as a promising alternative electrocatalyst for alkaline H_(2)O splitting,owing to their accessible active sites and strongly coupled interfaces with current collectors for improv...Self-supported nanoarrays have emerged as a promising alternative electrocatalyst for alkaline H_(2)O splitting,owing to their accessible active sites and strongly coupled interfaces with current collectors for improved mass transfer and stability.Herein,self-supported crystalline/amorphous NiO/Ni(OH)_(2)nanosheet arrays on nickel foam(NF)are fabricated via an in-situ dissolution-deposition hydrothermal growing of Ni(OH)_(2)nanosheets without additional metal sources assisted by a common Lewis base,EDTA,followed by a rapid calcination at 300℃in air.The as-prepared EDTA-NF-12 h exhibits high OER and HER performance under alkaline conditions,requiring 235 mV and 158 mV,respectively,to reach 10 mA cm^(-2),and the decent performance can be maintained for 24 h without obvious degradation.The dual interfaces,i.e.,the dense crystalline/amorphous interfaces within the NiO/Ni(OH)_(2)nanosheet arrays,as well as the intimate interfaces between nanoarrays and NF,both serve as reaction active sites,facilitate electron transfer,and endow the catalyst with high activity and stability.Furthermore,by applying EDTA-Ni^(2+)and other Lewis bases with varying basicities instead of EDTA,the interfaces with the NF substrate are found to promote the formation of crystalline/amorphous interfaces within the nanosheets.This study offers appealing opportunities for tailoring the electrocatalytic performance of self-supported electrodes via dual interface engineering.展开更多
Self-modeling(SM)and self-control(SC)feedback can be presented as two solutions for learning improvement.Therefore,the aim of the present study was to investigate the effects of SM and SC feedback on 100-m freestyle p...Self-modeling(SM)and self-control(SC)feedback can be presented as two solutions for learning improvement.Therefore,the aim of the present study was to investigate the effects of SM and SC feedback on 100-m freestyle performance of professional swimmers and waterpolo players.25 elite male swimmers and waterpolo players,were randomly assigned to four groups:swimmer group with SM,swimmer group with SM and SC feedback,waterpolo players group with SM,and waterpolo players group with SM and SC feedback.100-m freestyle times and performance were recorded.SM and SC feedback for the participants were utilized at the acquisition stage.The device used included a Lenovo B570 laptop and an Exilim ZR200 canon camcorder.SM and SC feedback presented to the swimmers and waterpolo players led to improved speed and results,and the effect of presenting SM with SC feedback to swimmers had better results.In conclusion,the present study indicates that SC modeling of watching video is a suitable method for professional swimmers.Water polo trainers can also use SM and SC feedback to enhance their players'swimming technique.展开更多
Corrective feedback is crucial for pronunciation teaching.However,in current pronunciation teaching practice,the corrective feedback provided usually fails to locate pronunciation problems and inform learners of the d...Corrective feedback is crucial for pronunciation teaching.However,in current pronunciation teaching practice,the corrective feedback provided usually fails to locate pronunciation problems and inform learners of the differences between their mispronunciations and the correct form.Based on the motor theory,this study attempted to explore a new way of corrective feedback for pronunciation teaching.Specifically,the learners’ speech output was modified and then was played back to them as an input model for learning.In this way,the learners can imitate the pronunciation model of their own voices,achieving self-imitation.This study included two experiments.The first explored the viability of obtaining one’s self-perceived voice through delayed feedback paradigm.The second experiment examined the effectiveness of self-imitation for English intonation learning.Results showed that imitating the pronunciation model of one’s own voice can reduce the learners’ phonological memory load,assist critical listening and facilitate accurate phonetic realizations of the target intonation.展开更多
In energy constrained application scenarios, self‐powered systems (SPSs) are gradually emerging as a core technological pathway for enabling distributed intelligent sensing. High‐entropy energy, such as micro‐wind,...In energy constrained application scenarios, self‐powered systems (SPSs) are gradually emerging as a core technological pathway for enabling distributed intelligent sensing. High‐entropy energy, such as micro‐wind, vibrations, water motion, and human activity, is widely available but difficult to harness due to its low density, randomness, and spatiotemporal fragmentation. Triboelectric nanogenerators (TENGs), with high efficiency to low‐frequency and irregular mechanical stimuli, offer a promising solution for efficient energy harvesting, driving the advancement of SPSs with high‐entropy distribution. This review outlines the basic concepts and recent developments of TENG‐driven SPSs, focusing on strategies for energy harvesting, power management, and system integration. It highlights structural optimization and performance enhancement under typical highentropy scenarios and analyzes key challenges in energy conversion, power regulation, and load management. Finally, the potential applications of TENG‐driven SPSs are discussed in emerging smart fields such as infrastructure monitoring, lowaltitude economy, mobile intelligent devices, and ocean sensing networks.展开更多
文摘In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the direction of the self-mixing fringes accurately and quickly.In the process of measurement,the measurement signal can be normalized and then the neural network can be used to discriminate the direction.Simulation and experimental results show that the proposed method is suitable for self-mixing interference signals with noise in the whole weak feedback regime,and can maintain a high discrimination accuracy for signals interfered by 5 dB large noise.Combined with fringe counting method,accurate and rapid displacement reconstruction can be realized.
基金National Natural Science Foundation of China(62405292)Fundamental Research Program of Shanxi Province(202403021222184)Postdoctoral Fellowship Program of CPSF(GZC20240802).
文摘Accurate measurements of dual parameters of phase retardance and retardance axis of birefringent materials are of fundamental importance to their fabrication and applications.However,current techniques typically exhibit limited versatility,suffering from high complexity,insufficient accuracy,and low efficiency.In this study,we propose and demonstrate the anisotropic laser feedback polarization effect for birefringent measurement,featuring simultaneous dual-parameter demodulation,unified polarization modulation-analysis architecture,high detection sensitivity,user-friendly operation,and versatile functionality.Importantly,such system can be self-calibrated with its own physical phenomena to reduce the installation derivation.To showcase the powerful effectiveness,we perform the static birefringence,dynamic birefringence variation,and spatial birefringence distribution,which remarkably exhibits the standard deviation of 0.0453°and 0.0939°for phase retardance and retardance axis azimuth,with the limit allowable sample transmittance around 10^(–5).This work demonstrates comprehensive applicability across diverse birefringence scenarios,extending the application of anisotropic laser feedback polarization effect,while establishing a novel strategy for birefringence measurement.
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.IA20240319003the NSFC under Grant No.62571112。
文摘To achieve the potential performance gain of massive multiple-input multiple-output(MIMO)systems,base stations(BS)require downlink channel state information(CSI)fed back by users to execute beamforming design,especially in the frequency division duplex(FDD)systems.However,due to the enormous number of antennas in massive MIMO systems,the feedback overhead of downlink CSI acquisition is extremely large.To address this issue,deep learning(DL)techniques have been introduced to de velop high-accuracy feedback strategies under limited backhaul constraints.In this paper,we provide an overview of DL-based CSI compression and feedback approaches in massive MIMO systems.Specifically,we introduce the conventional CSI compression and feedback schemes and the existing problems.Besides,we elaborate on various DL techniques employed in CSI compression from the perspective of network architecture and analyze the advantages of different techniques.We also enumerate the applications of DL-based methods for solving practical challenges in CSI compression and feedback.In addition,we brief the remaining issues in deep CSI compression and indicate potential directions in future wireless networks.
基金Project supported by the National Natural Science Foundation of China(Grant No.12002089)the Science and Technology Projects in Guangzhou(Grant No.2023A04J1323)UKRI Horizon Europe Guarantee(Marie SklodowskaCurie Fellowship)(Grant No.EP/Y016130/1)。
文摘Energy-regenerative suspension combined with piezoelectric and electromagnetic transduction has evolved into a core technological pathway in advancing automotive design paradigms.With the aim of improving energy harvesting performance,time-delayed feedback control is widely used in an energy-regenerative suspension system under different external disturbances in this paper.Meanwhile,limited research has addressed the stochastic dynamics of time-delayed nonlinear energy-regenerative suspension systems.Different from previous studies,this work studies the stochastic response and P-bifurcation of the nonlinear energy-regenerative suspension system with time-delayed feedback control.Firstly,an approximately equivalent dimension reduction system is established by the variable transformation method,and then the stationary probability density function of amplitude is obtained by the stochastic averaging method.Secondly,the precision of the method used in this work is verified by comparing the numerical solutions with the analytical results.Finally,based on the stationary probability density function,the influence of system parameters on stochastic P-bifurcation and the mean output power is discussed.
基金supported by the Swedish Research Council(Vetenskapsradet,Grant No.202203129)the Project of Youth Science and Technology Fund of Gansu Province(Grant No.24JRRA439)partially funded by the Swedish Research Council(Vetenskapsradet,Grant No.2022-06725)。
文摘This study investigates the impact of vegetation-climate feedback on the global land monsoon system during the Last Interglacial(LIG,127000 years BP)and the mid-Holocene(MH,6000 years BP)using the earth system model EC-Earth3.Our findings indicate that vegetation changes significantly influence the global monsoon area and precipitation patterns,especially in the North African and Indian monsoon regions.The North African monsoon region experienced the most substantial increase in vegetation during both the LIG and MH,resulting in significant increases in monsoonal precipitation by 9.8%and 6.0%,respectively.The vegetation feedback also intensified the Saharan Heat Low,strengthened monsoonal flows,and enhanced precipitation over the North African monsoon region.In contrast,the Indian monsoon region exhibited divergent responses to vegetation changes.During the LIG,precipitation in the Indian monsoon region decreased by 2.2%,while it increased by 1.6%during the MH.These differences highlight the complex and region-specific impacts of vegetation feedback on monsoon systems.Overall,this study demonstrates that vegetation feedback exerts distinct influences on the global monsoon during the MH and LIG.These findings highlight the importance of considering vegetation-climate feedback in understanding past monsoon variability and in predicting future climate change impacts on monsoon systems.
基金the support from the National Science Foundation of China(22471226,22272142)the 111 Project(B16029)。
文摘The performance of lithium-sulfur batteries(LSBs)is severely limited by a detrimental negative feedback loop:sluggish polysulfide conversion kinetics lead to Li_(2)S accumulation,which further hinders lithiumion transport and exacerbates capacity decay.To address this,we propose a positive feedback strategy that simultaneously enhances lithium polysulfides(LiPSs)conversion and lithium-ion diffusion through a rationally designed separator.By modifying the separator with phosphorus-doped two-dimensional hollow holey carbon nanosheets(Hollow HCNS),we establish an interconnected network where rapid LiPSs confinement and conversion within the hollow cavities promote efficient lithium-ion transport,while the improved ion flux further accelerates reaction kinetics.This mutual reinforcement mechanism ensures stable cycling by suppressing the shuttle effect and promoting uniform Li_(2)S deposition,as verified by in situ spectroscopic and electrochemical analysis.The resulting LSBs exhibit high-rate capability,ultralow capacity decay,and exceptional stability under high sulfur loading.This work presents a general approach to overcoming the persistent negative feedback problem in high-energy battery systems by synergistically optimizing catalytic conversion and ionic transport.
基金supported by the National Nature Science Foundation of China under Grant No.22269021the Tianshan Talent Project of Xinjiang Uygur Autonomous Region:2023TSYCQNTJ0039the Open project of Key Laboratory in Xinjiang Uygur Autonomous Region of China:2023D04027。
文摘The development of electrocatalysts that both work effectively at industrial current density and resist chloride ion(Cl^(-))corrosion remains a key challenge for hydrogen production from Cl^(-)-rich alkaline water.Herein,we report a CrO_(x)-engineered nickel-based oxide catalyst(FeCoCrO_(x)/NF)that achieves exceptional activity and stability through a dual-functional interfacial mechanism.Combing in situ Raman spectroscopy,18O isotopic labeling,and electrochemical analysis,we demonstrate that the oxygen evolution reaction follows a lattice oxygen-mediated mechanism.The CrO_(x)layer selectively adsorbs hydroxide ions,forming a dynamic interfacial barrier that electrostatically repels Cl^(-)ingress,thereby mitigating Cl^(-)corrosion.Through enthalpy-based analysis,we demonstrate that electronic redistribution via Cr-O-Fe bonding increases the vacancy formation energy of Fe,thereby suppressing its dissolution.In alkaline electrolyte containing 0.5 M Cl^(-)(1.0 M KOH),the catalyst is operating continuously for 1400 h at an industrial current density of 1000 mA cm^(-2).Furthermore,the catalyst retains 99.5%of its initial activity under fluctuating current density(100-1000 mA cm^(-2)),demonstrating robustness required for industrial electrolyzers.This study establishes a paradigm for designing corrosion-resistant electrocatalysts through the synergistic modulation of interfacial ion selectivity and bulk lattice oxygen activation,advancing the application of green hydrogen production in Cl^(-)-rich alkaline water.
文摘This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loop EIV system and its coprime factor(CF)uncertainty description is first derived,based on which the FR measurements suitable for plant CF identification are able to be generated.Different factorizations of a given controller in the closed-loop system can be made best use to adjust right coprime factors(RCFs)of the plant so as to realize an improvement on the signal-to-noise ratio of identification experimental data.Subsequently,a nominal RCF model is estimated by linear matrix inequalities from the applicable FR measurements and its associated worst-case errors are quantified from a priori and a posteriori information on the underlying system.A resulting RCF perturbation model set can then be described by the nominal RCF model and its worst-case error bounds.Such a model set capable of being stabilized by the given controller is ready for its robust stabilizing controller redesign and robust performance analysis.Finally,a numerical simulation is given to show the efficacy of the proposed identification method.
基金supported by the National Natural Science Foundation of China under Grant No.92582204,No.62577007,and No.62177003the Fundamental Research Funds for the Central Universities under Grant No.JKF-2025011975129.
文摘Online programming platforms are popular in programming education.However,there has been no research investigating students’real opinions and expectations of the error feedback mechanisms,leaving educators without a solid data foundation when attempting to improve the error feedback mechanisms.This paper makes a survey of 834 students across various programming courses and investigates student perceptions of error feedback mechanisms on online programming platforms.It explores the effectiveness of existing feedback,student satisfaction,and preferences for potential improvements,focusing on automatic error localization and program repair mechanisms.Results reveal a significant portion of students are dissatisfied with current feedback due to its limited informativeness.Students also express a clear demand for stronger feedback mechanisms,such as error localization and repair hints.Nevertheless,they prefer feedback that subtly guides them toward solutions,rather than providing direct and explicit answers,valuing the opportunity to enhance their debugging skills.The findings suggest a need for balanced,educational-focused feedback mechanisms that aid learning while promoting independent problem-solving.
基金National Natural Science Foundation of China(12005108)。
文摘In massive multiple-input multiple-output(MIMO)systems utilizing frequency division duplexing,optimizing system performance requires user equipment(UE)to compress downlink channel state information(CSI)and transmit it to the base station(BS).As the number of antennas increases,there is a significant rise in the overhead related to CSI feedback,posing considerable challenges to the precise acquisition of CSI by the BS.Existing approaches to CSI feedback utilizing deep learning techniques face challenges such as significant feedback overhead and limited precision in the reconstruction process.This study presents a novel lightweight CSI feedback framework known as the dual attention neural network(DANet).Within the DANet architecture,a dual attention module(DAM)is designed to enhance the network's performance.This DAM includes both channel attention blocks and spatial attention blocks.The channel attention blocks direct the model's focus toward channel features rich in information content while simultaneously suppressing less significant features.This approach enables the extraction of temporal correlations within the CSI matrix.The spatial attention block aids in extracting the correlation between the delay domain and the angle domain in the CSI matrix.By enhancing neural network performance,the DAM reduces information dispersion while enhancing the representation of global interactions.Simulation results demonstrate that DANet exhibits superior normalized mean square error and cosine similarity with comparable complexity compared to existing advanced CSI feedback methods.
基金funding support from the National Natural Science Foundation of China(Grant No.12525405)funding support from the National Natural Science Foundation of China(Grant No.12393831)the CAS Project for Young Scientists in Basic Research(Grant No.YSBR-120)。
文摘Self-trapped excitons(STEs),known for their unique radiative properties,have been harnessed in diverse photonic devices;however,their comprehensive understanding and manipulation remain elusive.In this study,we present novel experimental and theoretical evidence revealing the hybrid nature and optical tunability of STE state in Cs_(2)Ag_(0.4)Na_(0.6)InCl_(6).The detection of the Fano resonance in laser energy-dependent Raman and photoluminescence spectra indicates the emergence of an exciton-phonon hybrid state,arising from robust quantum interference between the discrete phonon and continuum exciton states.Moreover,we demonstrate continuous tuning of this hybrid state with the energy and intensity of the laser field.These findings lay the foundation for a comprehensive understanding of the nature of STE and their potential for state control.
基金the foundation of Guangdong Engineering Technology Research Center for Hydrogen Energy and Fuel Cells,the Guangdong Provincial Department of Education Innovation Project(No.2022KQNCX056)the Guangdong Basic and Applied Basic Research Foundation(Nos.2022A1515110354 and 2021A1515110582)。
文摘Self-supported nanoarrays have emerged as a promising alternative electrocatalyst for alkaline H_(2)O splitting,owing to their accessible active sites and strongly coupled interfaces with current collectors for improved mass transfer and stability.Herein,self-supported crystalline/amorphous NiO/Ni(OH)_(2)nanosheet arrays on nickel foam(NF)are fabricated via an in-situ dissolution-deposition hydrothermal growing of Ni(OH)_(2)nanosheets without additional metal sources assisted by a common Lewis base,EDTA,followed by a rapid calcination at 300℃in air.The as-prepared EDTA-NF-12 h exhibits high OER and HER performance under alkaline conditions,requiring 235 mV and 158 mV,respectively,to reach 10 mA cm^(-2),and the decent performance can be maintained for 24 h without obvious degradation.The dual interfaces,i.e.,the dense crystalline/amorphous interfaces within the NiO/Ni(OH)_(2)nanosheet arrays,as well as the intimate interfaces between nanoarrays and NF,both serve as reaction active sites,facilitate electron transfer,and endow the catalyst with high activity and stability.Furthermore,by applying EDTA-Ni^(2+)and other Lewis bases with varying basicities instead of EDTA,the interfaces with the NF substrate are found to promote the formation of crystalline/amorphous interfaces within the nanosheets.This study offers appealing opportunities for tailoring the electrocatalytic performance of self-supported electrodes via dual interface engineering.
基金Acknowledgements： This work is supported by A Foundation of National Excellent Doctoral Dissertation of China （No. 200250）, Natural Science Foundation of Henan Province China （No. 411012400） and National Science Foundation of China （No. 60871080）.
文摘Self-modeling(SM)and self-control(SC)feedback can be presented as two solutions for learning improvement.Therefore,the aim of the present study was to investigate the effects of SM and SC feedback on 100-m freestyle performance of professional swimmers and waterpolo players.25 elite male swimmers and waterpolo players,were randomly assigned to four groups:swimmer group with SM,swimmer group with SM and SC feedback,waterpolo players group with SM,and waterpolo players group with SM and SC feedback.100-m freestyle times and performance were recorded.SM and SC feedback for the participants were utilized at the acquisition stage.The device used included a Lenovo B570 laptop and an Exilim ZR200 canon camcorder.SM and SC feedback presented to the swimmers and waterpolo players led to improved speed and results,and the effect of presenting SM with SC feedback to swimmers had better results.In conclusion,the present study indicates that SC modeling of watching video is a suitable method for professional swimmers.Water polo trainers can also use SM and SC feedback to enhance their players'swimming technique.
文摘Corrective feedback is crucial for pronunciation teaching.However,in current pronunciation teaching practice,the corrective feedback provided usually fails to locate pronunciation problems and inform learners of the differences between their mispronunciations and the correct form.Based on the motor theory,this study attempted to explore a new way of corrective feedback for pronunciation teaching.Specifically,the learners’ speech output was modified and then was played back to them as an input model for learning.In this way,the learners can imitate the pronunciation model of their own voices,achieving self-imitation.This study included two experiments.The first explored the viability of obtaining one’s self-perceived voice through delayed feedback paradigm.The second experiment examined the effectiveness of self-imitation for English intonation learning.Results showed that imitating the pronunciation model of one’s own voice can reduce the learners’ phonological memory load,assist critical listening and facilitate accurate phonetic realizations of the target intonation.
基金supported by The National Key Research and Development Program of China(Grant No.2023YFB2604600).
文摘In energy constrained application scenarios, self‐powered systems (SPSs) are gradually emerging as a core technological pathway for enabling distributed intelligent sensing. High‐entropy energy, such as micro‐wind, vibrations, water motion, and human activity, is widely available but difficult to harness due to its low density, randomness, and spatiotemporal fragmentation. Triboelectric nanogenerators (TENGs), with high efficiency to low‐frequency and irregular mechanical stimuli, offer a promising solution for efficient energy harvesting, driving the advancement of SPSs with high‐entropy distribution. This review outlines the basic concepts and recent developments of TENG‐driven SPSs, focusing on strategies for energy harvesting, power management, and system integration. It highlights structural optimization and performance enhancement under typical highentropy scenarios and analyzes key challenges in energy conversion, power regulation, and load management. Finally, the potential applications of TENG‐driven SPSs are discussed in emerging smart fields such as infrastructure monitoring, lowaltitude economy, mobile intelligent devices, and ocean sensing networks.
