Dear Editor,The Cay2.1 channel,also known as the P/Q-type Ca^(2+) channel,is a particular type of voltage-gated Ca^(2+) channel primarily expressed on the presynaptic membrane in the brain[1].It serves as an essential...Dear Editor,The Cay2.1 channel,also known as the P/Q-type Ca^(2+) channel,is a particular type of voltage-gated Ca^(2+) channel primarily expressed on the presynaptic membrane in the brain[1].It serves as an essential part of the precisely orchestrated neurotransmitter release machinery.展开更多
In multi-modal emotion recognition,excessive reliance on historical context often impedes the detection of emotional shifts,while modality heterogeneity and unimodal noise limit recognition performance.Existing method...In multi-modal emotion recognition,excessive reliance on historical context often impedes the detection of emotional shifts,while modality heterogeneity and unimodal noise limit recognition performance.Existing methods struggle to dynamically adjust cross-modal complementary strength to optimize fusion quality and lack effective mechanisms to model the dynamic evolution of emotions.To address these issues,we propose a multi-level dynamic gating and emotion transfer framework for multi-modal emotion recognition.A dynamic gating mechanism is applied across unimodal encoding,cross-modal alignment,and emotion transfer modeling,substantially improving noise robustness and feature alignment.First,we construct a unimodal encoder based on gated recurrent units and feature-selection gating to suppress intra-modal noise and enhance contextual representation.Second,we design a gated-attention crossmodal encoder that dynamically calibrates the complementary contributions of visual and audio modalities to the dominant textual features and eliminates redundant information.Finally,we introduce a gated enhanced emotion transfer module that explicitly models the temporal dependence of emotional evolution in dialogues via transfer gating and optimizes continuity modeling with a comparative learning loss.Experimental results demonstrate that the proposed method outperforms state-of-the-art models on the public MELD and IEMOCAP datasets.展开更多
Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical si...Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.展开更多
Field-effect nanofluidic transistors(FENTs),biomimicking the structure and functionality of neuron,act as biological transistors with the ability to gate switching responses to external stimuli.The switching ratio has...Field-effect nanofluidic transistors(FENTs),biomimicking the structure and functionality of neuron,act as biological transistors with the ability to gate switching responses to external stimuli.The switching ratio has been verified to evaluate the performance of FENTs,but until recently,the response time,another crucial indicator,has been ignored.Employing finite-element method,we investigated the relationship among gate charge,switching ratio and response time by divisionally manipulating gate charge,including entrance surface and the surface of confinement space,for ion transport to optimize switching capability.The dual-split gate charge on FENTs exhibits synergistic effect on switching response.Based on the two regional gate charge on FENTs,multivalence ions in lower concentration,high aspect ratio and single channel show higher switching ratio but longer response time compared to monovalent ions.The findings highlight the necessity of balancing these two signals in FENTs and offer insights for optimizing their design and expanding applications to dual-signal-detection iontronics.展开更多
The design of casting gating system directly determines the solidification sequence,defect severity,and overall quality of the casting.A novel machine learning strategy was developed to design the counter pressure cas...The design of casting gating system directly determines the solidification sequence,defect severity,and overall quality of the casting.A novel machine learning strategy was developed to design the counter pressure casting gating system of a large thin-walled cabin casting.A high-quality dataset was established through orthogonal experiments combined with design criteria for the gating system.Spearman’s correlation analysis was used to select high-quality features.The gating system dimensions were predicted using a gated recurrent unit(GRU)recurrent neural network and an elastic network model.Using EasyCast and ProCAST casting software,a comparative analysis of the flow field,temperature field,and solidification field can be conducted to demonstrate the achievement of steady filling and top-down sequential solidification.Compared to the empirical formula method,this method eliminates trial-and-error iterations,reduces porosity,reduces casting defect volume from 11.23 cubic centimeters to 2.23 cubic centimeters,eliminates internal casting defects through the incorporation of an internally cooled iron,fulfilling the goal of intelligent gating system design.展开更多
Attosecond light pulses have revolutionized the study of electron dynamics in materials by enabling the observation of ultrafast processes with unprecedented attosecond temporal resolution.They are primarily generated...Attosecond light pulses have revolutionized the study of electron dynamics in materials by enabling the observation of ultrafast processes with unprecedented attosecond temporal resolution.They are primarily generated through the process of high-order harmonic generation.This paper presents a comprehensive setup for attosecond pulse generation and measurement.Using a 900 nm,7 mJ,and 7 fs femtosecond laser with stabilized carrier-envelope phase,we employ polarization gating to generate a near single-cycle,linearly polarized pulse that interacts with neon gas to produce a broadband extreme-ultraviolet continuum with a cutoff photon energy of∼120 eV.The temporal and spectral characteristics of the generated single attosecond pulses are measured using an attosecond streak camera,and the pulse duration is determined to be 59 as through the frequency-resolved optical gating for complete reconstruction of attosecond bursts retrieval algorithm.As part of the Synergetic Extreme Condition User Facility,this setup will facilitate ultrafast research in transient absorption and photoelectron spectroscopy,providing global users with a powerful tool for studying electron dynamics in various materials.展开更多
In multi-domain neural machine translation tasks,the disparity in data distribution between domains poses significant challenges in distinguishing domain features and sharing parameters across domains.This paper propo...In multi-domain neural machine translation tasks,the disparity in data distribution between domains poses significant challenges in distinguishing domain features and sharing parameters across domains.This paper proposes a Transformer-based multi-domain-aware mixture of experts model.To address the problem of domain feature differentiation,a mixture of experts(MoE)is introduced into attention to enhance the domain perception ability of the model,thereby improving the domain feature differentiation.To address the trade-off between domain feature distinction and cross-domain parameter sharing,we propose a domain-aware mixture of experts(DMoE).A domain-aware gating mechanism is introduced within the MoE module,simultaneously activating all domain experts to effectively blend domain feature distinction and cross-domain parameter sharing.A loss balancing function is then added to dynamically adjust the impact of the loss function on the expert distribution,enabling fine-tuning of the expert activation distribution to achieve a balance between domains.Experimental results on multiple Chinese-to-English and English-to-French datasets demonstrate that our proposed method significantly outperforms baseline models in both BLEU,chrF,and COMET metrics,validating its effectiveness in multi-domain neural machine translation.Further analysis of the probability distribution of expert activations shows that our method achieves remarkable results in both domain differentiation and cross-domain parameter sharing.展开更多
Multi-valued quantum adder circuits,based on multi-valued logic,are significant components in numerous quantum algorithms.Their low-cost implementations can enhance the efficiency of these algorithms.In this paper,inn...Multi-valued quantum adder circuits,based on multi-valued logic,are significant components in numerous quantum algorithms.Their low-cost implementations can enhance the efficiency of these algorithms.In this paper,innovative universal architectures for d(d>3)-level quantum half-adder,full-adder,parallel adder,and parallel adder/subtractor circuits are designed using d-level 1-qudit(quantum digit)and M-S gates.To demonstrate the effectiveness of these architectures,quaternary adder circuits derived from them are displayed and compared with several existing counterparts.Judging by the results,these circuits exhibit reductions in quantum cost(QC),hardware complexity(HC),number of constant inputs(NCIs),and number of garbage outputs(NGOs).展开更多
Regulation of apoptosis represents a key parameter in all living organisms.In this paper,an input-induced logic-gated modular nanocalculator is designed to regulate cancer cell apoptosis by programmatically combining ...Regulation of apoptosis represents a key parameter in all living organisms.In this paper,an input-induced logic-gated modular nanocalculator is designed to regulate cancer cell apoptosis by programmatically combining and connecting logic gate modules with different functions.Via rational design of the various logic gate modules of the nanocalculator,different apoptosis related operations including cancer cell targeting,apoptosis induction,and apoptosis monitoring could be performed.Importantly,each of these logic gate modules could independently perform apoptosis related YES logic operations when ran separately.After combining each YES logic gate module into a logic circuit and connecting it to the GO scaffold to construct a logic-gated nanocalculator,the input-induced logic-gated modular nanocalculator could selectively enter cancer cells and control the drug release to logically apoptosis(output),by performing AND logic gate operations when inputs(nucleolin and H^(+)) were included at the same time.Moreover,evidence suggests that these efficient logical calculations proceed in cancer cell apoptosis regulation without the general limiations of lithography in nanotechnology.As such,this work provides a new vision for the construction of a logic-gated modular nanocalculator with logical calculation proficiency potentially useful in cancer therapy and the regulation of life.展开更多
In this paper,a comprehensive evaluation on the silicon/silicon carbide(Si/SiC)hybrid switch is performed through experimental tests in terms of both electrical performance and robustness under extreme stresses.Based ...In this paper,a comprehensive evaluation on the silicon/silicon carbide(Si/SiC)hybrid switch is performed through experimental tests in terms of both electrical performance and robustness under extreme stresses.Based on the optional turn-on and turn-off delay times under the efficiency control mode obtained from the double-pulse test(DPT),both nondestructive and destructive single-pulse avalanche tests are conducted on the Si/SiC hybrid switch as well as on the two discrete device branches inside the hybrid switch.In addition,the avalanche voltage,critical avalanche energy,and peak avalanche current,which intrinsically characterize the unclamped-inductive-switching(UIS)avalanche characteristics,are carefully examined.In this way,the physical factors dominating the UIS characteristics of the hybrid switch,thus limiting its single-pulse avalanche withstand capability,are specifically and comprehensively identified;the underlying physical mechanisms are analyzed and revealed in depth,and how the gate control sequence affects the UIS characteristics of the hybrid switch is extensively investigated.We additionally carry out short-circuit(SC)tests under the fault-under-load(FUL)condition and perform a parallel in-depth analysis to experimentally determine which branch dominates the SC withstand capability of the hybrid switch.Our experimental study indicates that,for both SC robustness and single-pulse avalanche capability,the limiting factor is a single device branch among the two parallel discrete devices,and the UIS behavior is sensitive to the variation of the gate turn-off delay time Toff_delay.The study conducted in this paper not only provides deep academic insights into the electrical performance and reliability of the Si/SiC hybrid switch,but also offers fundamental theoretical principles and technical evidence to support its more efficient and long-term reliable applications of the hybrid switch in the industrial fields.展开更多
Wearable sensors have revolutionized health monitoring by transitioning from clinical diagnostics to continuous,real-time applications in daily life.The oral cavity,rich in saliva containing over 1,000 biomarkers that...Wearable sensors have revolutionized health monitoring by transitioning from clinical diagnostics to continuous,real-time applications in daily life.The oral cavity,rich in saliva containing over 1,000 biomarkers that reflect systemic health(e.g.,glucose,cortisol,and inflammatory markers)[1],offers the advantage of non-invasive sampling.Its superior environmental stability and strong connection to key physiological processes make it an ideal candidate in the field of digital medicine,serving as a natural gateway to personalized health monitoring.Therefore,the oral cavity represents not only a convenient sampling site but also a strategic interface for realizing the vision of continuous,personalized digital health monitoring.展开更多
The accurate state of health(SOH)estimation in lithium-ion batteries represents a critical technological challenge with profound implications for electric vehicle performance and user experience.Precise SOH assessment...The accurate state of health(SOH)estimation in lithium-ion batteries represents a critical technological challenge with profound implications for electric vehicle performance and user experience.Precise SOH assessment not only enables reliable mileage prediction but also ensures operational safety.However,the complex and non-linear capacity fading process during battery cycling poses a challenge to obtaining accurate SOH.To address this issue,this study proposes an effective health factor derived from the local voltage range during the battery charging phase.First,the battery charging phase is divided evenly with reference to voltage intervals,and an importance analysis is conducted on each voltage interval.From these,the voltage interval with the strongest correlation to State of Health(SOH)is extracted as the feature interval.Then,a data-driven framework integrating variational mode decomposition(VMD)with gated recurrent unit(GRU)neural networks enables comprehensive multi-scale temporal feature analysis for enhanced SOH estimation.The methodology begins with rigorous feature engineering to identify and extract optimal health indicators demonstrating superior correlation.Subsequently,the VMD algorithm performs sophisticated signal processing to decompose both the measured capacity and derived health indicators into their constituent intrinsic mode functions and residual components.Finally,a GRU-based neural network is implemented to establish a robust SOH estimation model.Experimental validation using cycling data from different datasets shows that the root mean square error of the estimation results is consistently below 3%,demonstrating the good accuracy and generalisation of the proposed method,using only local data from the charging phase.展开更多
Quantum control allows a wide range of quantum operations employed in molecular physics,nuclear magnetic resonance and quantum information processing.Thanks to the existing microelectronics industry,semiconducting qub...Quantum control allows a wide range of quantum operations employed in molecular physics,nuclear magnetic resonance and quantum information processing.Thanks to the existing microelectronics industry,semiconducting qubits,where quantum information is encoded in spin or charge degree freedom of electrons or nuclei in semiconductor quantum dots,constitute a highly competitive candidate for scalable solid-state quantum technologies.In quantum information processing,advanced control techniques are needed to realize quantum manipulations with both high precision and noise resilience.In this review,we first introduce the basics of various widely-used control methods,including resonant excitation,adabatic passage,shortcuts to adiabaticity,composite pulses,and quantum optimal control.Then we review the practical aspects in applying these methods to realize accurate and robust quantum gates for single semiconductor qubits,such as Loss–DiVincenzo spin qubit,spinglet-triplet qubit,exchange-only qubit and charge qubit.展开更多
With the widespread adoption of digital equipment in intelligent substations,testing digital signals in power systems has become an important role for relay protection test equipment.Testing and calibrating digital si...With the widespread adoption of digital equipment in intelligent substations,testing digital signals in power systems has become an important role for relay protection test equipment.Testing and calibrating digital signals require high accuracy.However,existing methods have low precision,cannot be calibrated at full range for all indexes,and have complex configuration,making them unsuitable for routine calibration work.To solve the above problems,a novel calibration method is designed and implemented using field programmable gate array(FPGA)to achieve accurate input and output time control.Accurate calibration relies on multiple forms of traceability including theoretical value traceability based on waveform comparison,time scale value traceability based on accurate time stamps,and algorithm traceability based on typical algorithms.Compared with other existing methods,the proposed approach reduces the mean absolute error of action time and time measurement by 92.88%,effectively addressing a key industry challenge and offering a valuable reference for further research,application,and standardization.展开更多
Advanced technologies like Cyber-Physical Systems(CPS)and the Internet of Things(IoT)have supported modernizing and automating the transportation region through the introduction of Intelligent Transportation Systems(I...Advanced technologies like Cyber-Physical Systems(CPS)and the Internet of Things(IoT)have supported modernizing and automating the transportation region through the introduction of Intelligent Transportation Systems(ITS).Integrating CPS-ITS and IoT provides real-time Vehicle-to-Infrastructure(V2I)communication,supporting better traffic management,safety,and efficiency.These technological innovations generate complex problems that need to be addressed,uniquely about data routing and Task Scheduling(TS)in ITS.Attempts to solve those problems were primarily based on traditional and experimental methods,and the solutions were not so successful due to the dynamic nature of ITS.This is where the scope of Machine learning(ML)and Swarm Intelligence(SI)has significantly impacted dealing with these challenges;in this line,this research paper presents a novel method for TS and data routing in the CPS-ITS.This paper proposes using a cutting-edge ML algorithm for data transmission from CPS-ITS.This ML has Gated Linear Unit-approximated Reinforcement Learning(GLRL).Greedy Iterative-Particle Swarm Optimization(GI-PSO)has been recommended to develop the Particle Swarm Optimization(PSO)for TS.The primary objective of this study is to enhance the security and effectiveness of ITS systems that utilize CPS-ITS.This study trained and validated the models using a network simulation dataset of 50 nodes from numerous ITS environments.The experiments demonstrate that the proposed GLRL reduces End-toEnd Delay(EED)by 12%,enhances data size use from 83.6%to 88.6%,and achieves higher bandwidth allocation,particularly in high-demand scenarios such as multimedia data streams where adherence improved to 98.15%.Furthermore,the GLRL reduced Network Congestion(NC)by 5.5%,demonstrating its efficiency in managing complex traffic conditions across several environments.The model passed simulation tests in three different environments:urban(UE),suburban(SE),and rural(RE).It met the high bandwidth requirements,made task scheduling more efficient,and increased network throughput(NT).This proved that it was robust and flexible enough for scalable ITS applications.These innovations provide robust,scalable solutions for real-time traffic management,ultimately improving safety,reducing NC,and increasing overall NT.This study can affect ITS by developing it to be more responsive,safe,and effective and by creating a perfect method to set up UE,SE,and RE.展开更多
Automatic segmentation of landslides from remote sensing imagery is challenging because traditional machine learning and early CNN-based models often fail to generalize across heterogeneous landscapes,where segmentati...Automatic segmentation of landslides from remote sensing imagery is challenging because traditional machine learning and early CNN-based models often fail to generalize across heterogeneous landscapes,where segmentation maps contain sparse and fragmented landslide regions under diverse geographical conditions.To address these issues,we propose a lightweight dual-stream siamese deep learning framework that integrates optical and topographical data fusion with an adaptive decoder,guided multimodal fusion,and deep supervision.The framework is built upon the synergistic combination of cross-attention,gated fusion,and sub-pixel upsampling within a unified dual-stream architecture specifically optimized for landslide segmentation,enabling efficient context modeling and robust feature exchange between modalities.The decoder captures long-range context at deeper levels using lightweight cross-attention and refines spatial details at shallower levels through attention-gated skip fusion,enabling precise boundary delineation and fewer false positives.The gated fusion further enhances multimodal integration of optical and topographical cues,and the deep supervision stabilizes training and improves generalization.Moreover,to mitigate checkerboard artifacts,a learnable sub-pixel upsampling is devised to replace the traditional transposed convolution.Despite its compact design with fewer parameters,the model consistently outperforms state-of-the-art baselines.Experiments on two benchmark datasets,Landslide4Sense and Bijie,confirm the effectiveness of the framework.On the Bijie dataset,it achieves an F1-score of 0.9110 and an intersection over union(IoU)of 0.8839.These results highlight its potential for accurate large-scale landslide inventory mapping and real-time disaster response.The implementation is publicly available at https://github.com/mishaown/DiGATe-UNet-LandSlide-Segmentation(accessed on 3 November 2025).展开更多
The South Central Axis in Beijing showcases China’s image and highlights its cultural confidence.THE Central Axis is the centerpiece of the Chinese capital’s urban spatial layout.The southern extended section of the...The South Central Axis in Beijing showcases China’s image and highlights its cultural confidence.THE Central Axis is the centerpiece of the Chinese capital’s urban spatial layout.The southern extended section of the Central Axis,or the South Central Axis,stretches from the Yongdingmen Gate Tower in the north to the South Fifth Ring Road in the south.While being a strategic transport link facilitating the coordinated development of the Beijing-Tianjin-Hebei region,it also showcases China’s vision for the future and highlights its cultural confidence.展开更多
In recent years,acoustic logic gates has attracted growing interest in acoustics due to their promising applications in acoustic communication and signal processing.For practical implementation,these logic gates must ...In recent years,acoustic logic gates has attracted growing interest in acoustics due to their promising applications in acoustic communication and signal processing.For practical implementation,these logic gates must operate over a certain bandwidth to ensure reliable performance.However,current experimental realizations have predominantly been confined to single-frequency or narrowband operation,leaving their broadband capabilities largely unverified.To address this gap,we present both numerical and experimental demonstrations of three basic acoustic logic gates(OR,NOT,and AND)using a phased unit cell composed of a central channel flanked by two arrays of semicircular cavities.By leveraging phase modulation of the unit cells and linear interference of sound,we achieve these logic operations with a uniform threshold of I_(t)=0.25.Remarkably,the measured fractional bandwidths(bandwidth relative to center frequency)reach approximately 111.5%(OR),37.2%(NOT),and 48.5%(AND),demonstrating ultra-broadband functionality.The proposed logic gates combine exceptional bandwidth with structural simplicity,offering significant potential for applications in acoustic computing,information processing,and integrated acoustic systems.展开更多
基金supported by the National Natural Science Foundation of China(32100773 and U20A6005)the National Science and Technology Innovation 2030-Major Project of China(2021ZD0202500)+4 种基金Shenzhen Medical Research Fund(B2402024)China Postdoctoral Science Foundation(2021M693296)Shenzhen Science and Technology Program(JCYJ20230807093815032)Guangdong High-level Hospital Construction Fund(ynkt2021-zz33 and LCYJ2022093)the Natural Science Foundation of Guangdong Province,China(2022A1515010297).
文摘Dear Editor,The Cay2.1 channel,also known as the P/Q-type Ca^(2+) channel,is a particular type of voltage-gated Ca^(2+) channel primarily expressed on the presynaptic membrane in the brain[1].It serves as an essential part of the precisely orchestrated neurotransmitter release machinery.
基金funded by“the Fanying Special Program of the National Natural Science Foundation of China,grant number 62341307”“the Scientific research project of Jiangxi Provincial Department of Education,grant number GJJ200839”“theDoctoral startup fund of JiangxiUniversity of Technology,grant number 205200100402”.
文摘In multi-modal emotion recognition,excessive reliance on historical context often impedes the detection of emotional shifts,while modality heterogeneity and unimodal noise limit recognition performance.Existing methods struggle to dynamically adjust cross-modal complementary strength to optimize fusion quality and lack effective mechanisms to model the dynamic evolution of emotions.To address these issues,we propose a multi-level dynamic gating and emotion transfer framework for multi-modal emotion recognition.A dynamic gating mechanism is applied across unimodal encoding,cross-modal alignment,and emotion transfer modeling,substantially improving noise robustness and feature alignment.First,we construct a unimodal encoder based on gated recurrent units and feature-selection gating to suppress intra-modal noise and enhance contextual representation.Second,we design a gated-attention crossmodal encoder that dynamically calibrates the complementary contributions of visual and audio modalities to the dominant textual features and eliminates redundant information.Finally,we introduce a gated enhanced emotion transfer module that explicitly models the temporal dependence of emotional evolution in dialogues via transfer gating and optimizes continuity modeling with a comparative learning loss.Experimental results demonstrate that the proposed method outperforms state-of-the-art models on the public MELD and IEMOCAP datasets.
基金financially supported by the National Key Research and Development Program of China (2022YFB3706802)。
文摘Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.
基金supported by the Natural Science Foundation of Guangdong Province,China (No.2025A1515011654)the National Natural Science Foundation of China (No.22090053)+3 种基金the Fundamental Research Funds for National Universities,China University of Geosciences (Wuhan)support from the program of China Scholarships Council (No.202406410155)Young Elite Scientists Sponsorship Program by CAST-Doctoral Student Special Plansupport from the S&T Special Program of Huzhou (No.2024GZ07)。
文摘Field-effect nanofluidic transistors(FENTs),biomimicking the structure and functionality of neuron,act as biological transistors with the ability to gate switching responses to external stimuli.The switching ratio has been verified to evaluate the performance of FENTs,but until recently,the response time,another crucial indicator,has been ignored.Employing finite-element method,we investigated the relationship among gate charge,switching ratio and response time by divisionally manipulating gate charge,including entrance surface and the surface of confinement space,for ion transport to optimize switching capability.The dual-split gate charge on FENTs exhibits synergistic effect on switching response.Based on the two regional gate charge on FENTs,multivalence ions in lower concentration,high aspect ratio and single channel show higher switching ratio but longer response time compared to monovalent ions.The findings highlight the necessity of balancing these two signals in FENTs and offer insights for optimizing their design and expanding applications to dual-signal-detection iontronics.
基金supported by the National Natural Science Foundation of China(Nos.52074246,52275390,52375394)the National Defense Basic Scientific Research Program of China(No.JCKY2020408B002)the Key R&D Program of Shanxi Province(No.202102050201011).
文摘The design of casting gating system directly determines the solidification sequence,defect severity,and overall quality of the casting.A novel machine learning strategy was developed to design the counter pressure casting gating system of a large thin-walled cabin casting.A high-quality dataset was established through orthogonal experiments combined with design criteria for the gating system.Spearman’s correlation analysis was used to select high-quality features.The gating system dimensions were predicted using a gated recurrent unit(GRU)recurrent neural network and an elastic network model.Using EasyCast and ProCAST casting software,a comparative analysis of the flow field,temperature field,and solidification field can be conducted to demonstrate the achievement of steady filling and top-down sequential solidification.Compared to the empirical formula method,this method eliminates trial-and-error iterations,reduces porosity,reduces casting defect volume from 11.23 cubic centimeters to 2.23 cubic centimeters,eliminates internal casting defects through the incorporation of an internally cooled iron,fulfilling the goal of intelligent gating system design.
基金supported by the National Natural Science Foundation of China(Grant Nos.12174435,12034020,and 92250303)the Chinese Academy of Sciences Project for Young Scientists in Basic Research(Grant No.YSBR-091)the National Key R&D Program of China(Grant No.2022YFA1604200).
文摘Attosecond light pulses have revolutionized the study of electron dynamics in materials by enabling the observation of ultrafast processes with unprecedented attosecond temporal resolution.They are primarily generated through the process of high-order harmonic generation.This paper presents a comprehensive setup for attosecond pulse generation and measurement.Using a 900 nm,7 mJ,and 7 fs femtosecond laser with stabilized carrier-envelope phase,we employ polarization gating to generate a near single-cycle,linearly polarized pulse that interacts with neon gas to produce a broadband extreme-ultraviolet continuum with a cutoff photon energy of∼120 eV.The temporal and spectral characteristics of the generated single attosecond pulses are measured using an attosecond streak camera,and the pulse duration is determined to be 59 as through the frequency-resolved optical gating for complete reconstruction of attosecond bursts retrieval algorithm.As part of the Synergetic Extreme Condition User Facility,this setup will facilitate ultrafast research in transient absorption and photoelectron spectroscopy,providing global users with a powerful tool for studying electron dynamics in various materials.
基金supported by the NationalNatural Science Foundation of China(U2004163)Key Research and Development Program of Henan Province(No.251111211200).
文摘In multi-domain neural machine translation tasks,the disparity in data distribution between domains poses significant challenges in distinguishing domain features and sharing parameters across domains.This paper proposes a Transformer-based multi-domain-aware mixture of experts model.To address the problem of domain feature differentiation,a mixture of experts(MoE)is introduced into attention to enhance the domain perception ability of the model,thereby improving the domain feature differentiation.To address the trade-off between domain feature distinction and cross-domain parameter sharing,we propose a domain-aware mixture of experts(DMoE).A domain-aware gating mechanism is introduced within the MoE module,simultaneously activating all domain experts to effectively blend domain feature distinction and cross-domain parameter sharing.A loss balancing function is then added to dynamically adjust the impact of the loss function on the expert distribution,enabling fine-tuning of the expert activation distribution to achieve a balance between domains.Experimental results on multiple Chinese-to-English and English-to-French datasets demonstrate that our proposed method significantly outperforms baseline models in both BLEU,chrF,and COMET metrics,validating its effectiveness in multi-domain neural machine translation.Further analysis of the probability distribution of expert activations shows that our method achieves remarkable results in both domain differentiation and cross-domain parameter sharing.
基金supported by the Natural Science Foundation of Sichuan Province(No.25QNJJ4066)Academic Degree and Post graduate Education Reform Project of Sichuan Province(Grants:YJGXM24-C017)。
文摘Multi-valued quantum adder circuits,based on multi-valued logic,are significant components in numerous quantum algorithms.Their low-cost implementations can enhance the efficiency of these algorithms.In this paper,innovative universal architectures for d(d>3)-level quantum half-adder,full-adder,parallel adder,and parallel adder/subtractor circuits are designed using d-level 1-qudit(quantum digit)and M-S gates.To demonstrate the effectiveness of these architectures,quaternary adder circuits derived from them are displayed and compared with several existing counterparts.Judging by the results,these circuits exhibit reductions in quantum cost(QC),hardware complexity(HC),number of constant inputs(NCIs),and number of garbage outputs(NGOs).
基金financially supported by the National Natural Science Foundation of China (NSFC,Nos.22134005 and 22074124)Chongqing Talents Program for Outstanding Scientists (No.cstc2021ycjh-bgzxm0178)+1 种基金Natural Science Foundation of Chongqing (No.CSTB2022NSCQ-MSX0521)the Chongqing Graduate Student Scientific Research Innovation Project (No.CYB21119)。
文摘Regulation of apoptosis represents a key parameter in all living organisms.In this paper,an input-induced logic-gated modular nanocalculator is designed to regulate cancer cell apoptosis by programmatically combining and connecting logic gate modules with different functions.Via rational design of the various logic gate modules of the nanocalculator,different apoptosis related operations including cancer cell targeting,apoptosis induction,and apoptosis monitoring could be performed.Importantly,each of these logic gate modules could independently perform apoptosis related YES logic operations when ran separately.After combining each YES logic gate module into a logic circuit and connecting it to the GO scaffold to construct a logic-gated nanocalculator,the input-induced logic-gated modular nanocalculator could selectively enter cancer cells and control the drug release to logically apoptosis(output),by performing AND logic gate operations when inputs(nucleolin and H^(+)) were included at the same time.Moreover,evidence suggests that these efficient logical calculations proceed in cancer cell apoptosis regulation without the general limiations of lithography in nanotechnology.As such,this work provides a new vision for the construction of a logic-gated modular nanocalculator with logical calculation proficiency potentially useful in cancer therapy and the regulation of life.
基金supported in part by the Anhui Provincial Natural Science Foundation Youth Project(Category C)under Grant No.2508085QE184the Opening Project of Key Laboratory of Power Electronics and Motion Control of Anhui Higher Education Institutions under Grant No.PEMC24004+1 种基金the Anhui University of Technology Young Teachers Research Fund under Grant No.QZ202412the Scientific Research Startup Fund for Introduced Talents of Anhui University of Technology under Grant No.QD202340.
文摘In this paper,a comprehensive evaluation on the silicon/silicon carbide(Si/SiC)hybrid switch is performed through experimental tests in terms of both electrical performance and robustness under extreme stresses.Based on the optional turn-on and turn-off delay times under the efficiency control mode obtained from the double-pulse test(DPT),both nondestructive and destructive single-pulse avalanche tests are conducted on the Si/SiC hybrid switch as well as on the two discrete device branches inside the hybrid switch.In addition,the avalanche voltage,critical avalanche energy,and peak avalanche current,which intrinsically characterize the unclamped-inductive-switching(UIS)avalanche characteristics,are carefully examined.In this way,the physical factors dominating the UIS characteristics of the hybrid switch,thus limiting its single-pulse avalanche withstand capability,are specifically and comprehensively identified;the underlying physical mechanisms are analyzed and revealed in depth,and how the gate control sequence affects the UIS characteristics of the hybrid switch is extensively investigated.We additionally carry out short-circuit(SC)tests under the fault-under-load(FUL)condition and perform a parallel in-depth analysis to experimentally determine which branch dominates the SC withstand capability of the hybrid switch.Our experimental study indicates that,for both SC robustness and single-pulse avalanche capability,the limiting factor is a single device branch among the two parallel discrete devices,and the UIS behavior is sensitive to the variation of the gate turn-off delay time Toff_delay.The study conducted in this paper not only provides deep academic insights into the electrical performance and reliability of the Si/SiC hybrid switch,but also offers fundamental theoretical principles and technical evidence to support its more efficient and long-term reliable applications of the hybrid switch in the industrial fields.
基金support from the Guangdong Basic and Applied Basic Research Foundation(Nos.2021A1515110388,2024A1515011707)Science and Technology Projects in Guangzhou(No.2024A04J5195)Shenzhen Natural Science Foundation(Nos.JCYJ20230807111120043).
文摘Wearable sensors have revolutionized health monitoring by transitioning from clinical diagnostics to continuous,real-time applications in daily life.The oral cavity,rich in saliva containing over 1,000 biomarkers that reflect systemic health(e.g.,glucose,cortisol,and inflammatory markers)[1],offers the advantage of non-invasive sampling.Its superior environmental stability and strong connection to key physiological processes make it an ideal candidate in the field of digital medicine,serving as a natural gateway to personalized health monitoring.Therefore,the oral cavity represents not only a convenient sampling site but also a strategic interface for realizing the vision of continuous,personalized digital health monitoring.
基金supported by the Scientific Research Program Funded by Shaanxi Provincial Education Department(Program No.23JP100)the Key Natural Science Research Project of Shaanxi Energy Institute:Comprehensive Characterization Study of Lithium-Ion Batteries for New Energy Vehicles(Project No.23QNZRZ01).
文摘The accurate state of health(SOH)estimation in lithium-ion batteries represents a critical technological challenge with profound implications for electric vehicle performance and user experience.Precise SOH assessment not only enables reliable mileage prediction but also ensures operational safety.However,the complex and non-linear capacity fading process during battery cycling poses a challenge to obtaining accurate SOH.To address this issue,this study proposes an effective health factor derived from the local voltage range during the battery charging phase.First,the battery charging phase is divided evenly with reference to voltage intervals,and an importance analysis is conducted on each voltage interval.From these,the voltage interval with the strongest correlation to State of Health(SOH)is extracted as the feature interval.Then,a data-driven framework integrating variational mode decomposition(VMD)with gated recurrent unit(GRU)neural networks enables comprehensive multi-scale temporal feature analysis for enhanced SOH estimation.The methodology begins with rigorous feature engineering to identify and extract optimal health indicators demonstrating superior correlation.Subsequently,the VMD algorithm performs sophisticated signal processing to decompose both the measured capacity and derived health indicators into their constituent intrinsic mode functions and residual components.Finally,a GRU-based neural network is implemented to establish a robust SOH estimation model.Experimental validation using cycling data from different datasets shows that the root mean square error of the estimation results is consistently below 3%,demonstrating the good accuracy and generalisation of the proposed method,using only local data from the charging phase.
基金support by the National Natural Science Foundation of China(Nos.12174379,E31Q02BG)the Chinese Academy of Sciences(Nos.E0SEBB11,E27RBB11)+1 种基金the Innovation Program for Quantum Science and Technology(No.2021ZD0302300)Chinese Academy of Sciences Project for Young Scientists in Basic Research(No.YSBR-090)。
文摘Quantum control allows a wide range of quantum operations employed in molecular physics,nuclear magnetic resonance and quantum information processing.Thanks to the existing microelectronics industry,semiconducting qubits,where quantum information is encoded in spin or charge degree freedom of electrons or nuclei in semiconductor quantum dots,constitute a highly competitive candidate for scalable solid-state quantum technologies.In quantum information processing,advanced control techniques are needed to realize quantum manipulations with both high precision and noise resilience.In this review,we first introduce the basics of various widely-used control methods,including resonant excitation,adabatic passage,shortcuts to adiabaticity,composite pulses,and quantum optimal control.Then we review the practical aspects in applying these methods to realize accurate and robust quantum gates for single semiconductor qubits,such as Loss–DiVincenzo spin qubit,spinglet-triplet qubit,exchange-only qubit and charge qubit.
基金supported by the Key Technologies R&D Program of Henan Province(No.242102211065)Postgraduate Education Reform and Quality Im-provement Project of Henan Province(No.YJS2025GZZ36).
文摘With the widespread adoption of digital equipment in intelligent substations,testing digital signals in power systems has become an important role for relay protection test equipment.Testing and calibrating digital signals require high accuracy.However,existing methods have low precision,cannot be calibrated at full range for all indexes,and have complex configuration,making them unsuitable for routine calibration work.To solve the above problems,a novel calibration method is designed and implemented using field programmable gate array(FPGA)to achieve accurate input and output time control.Accurate calibration relies on multiple forms of traceability including theoretical value traceability based on waveform comparison,time scale value traceability based on accurate time stamps,and algorithm traceability based on typical algorithms.Compared with other existing methods,the proposed approach reduces the mean absolute error of action time and time measurement by 92.88%,effectively addressing a key industry challenge and offering a valuable reference for further research,application,and standardization.
基金funded by Taif University,Taif,Saudi Arabia,project number(TU-DSPP-2024-17)。
文摘Advanced technologies like Cyber-Physical Systems(CPS)and the Internet of Things(IoT)have supported modernizing and automating the transportation region through the introduction of Intelligent Transportation Systems(ITS).Integrating CPS-ITS and IoT provides real-time Vehicle-to-Infrastructure(V2I)communication,supporting better traffic management,safety,and efficiency.These technological innovations generate complex problems that need to be addressed,uniquely about data routing and Task Scheduling(TS)in ITS.Attempts to solve those problems were primarily based on traditional and experimental methods,and the solutions were not so successful due to the dynamic nature of ITS.This is where the scope of Machine learning(ML)and Swarm Intelligence(SI)has significantly impacted dealing with these challenges;in this line,this research paper presents a novel method for TS and data routing in the CPS-ITS.This paper proposes using a cutting-edge ML algorithm for data transmission from CPS-ITS.This ML has Gated Linear Unit-approximated Reinforcement Learning(GLRL).Greedy Iterative-Particle Swarm Optimization(GI-PSO)has been recommended to develop the Particle Swarm Optimization(PSO)for TS.The primary objective of this study is to enhance the security and effectiveness of ITS systems that utilize CPS-ITS.This study trained and validated the models using a network simulation dataset of 50 nodes from numerous ITS environments.The experiments demonstrate that the proposed GLRL reduces End-toEnd Delay(EED)by 12%,enhances data size use from 83.6%to 88.6%,and achieves higher bandwidth allocation,particularly in high-demand scenarios such as multimedia data streams where adherence improved to 98.15%.Furthermore,the GLRL reduced Network Congestion(NC)by 5.5%,demonstrating its efficiency in managing complex traffic conditions across several environments.The model passed simulation tests in three different environments:urban(UE),suburban(SE),and rural(RE).It met the high bandwidth requirements,made task scheduling more efficient,and increased network throughput(NT).This proved that it was robust and flexible enough for scalable ITS applications.These innovations provide robust,scalable solutions for real-time traffic management,ultimately improving safety,reducing NC,and increasing overall NT.This study can affect ITS by developing it to be more responsive,safe,and effective and by creating a perfect method to set up UE,SE,and RE.
基金funded by the National Natural Science Foundation of China,grant number 62262045the Fundamental Research Funds for the Central Universities,grant number 2023CDJYGRH-YB11the Open Funding of SUGON Industrial Control and Security Center,grant number CUIT-SICSC-2025-03.
文摘Automatic segmentation of landslides from remote sensing imagery is challenging because traditional machine learning and early CNN-based models often fail to generalize across heterogeneous landscapes,where segmentation maps contain sparse and fragmented landslide regions under diverse geographical conditions.To address these issues,we propose a lightweight dual-stream siamese deep learning framework that integrates optical and topographical data fusion with an adaptive decoder,guided multimodal fusion,and deep supervision.The framework is built upon the synergistic combination of cross-attention,gated fusion,and sub-pixel upsampling within a unified dual-stream architecture specifically optimized for landslide segmentation,enabling efficient context modeling and robust feature exchange between modalities.The decoder captures long-range context at deeper levels using lightweight cross-attention and refines spatial details at shallower levels through attention-gated skip fusion,enabling precise boundary delineation and fewer false positives.The gated fusion further enhances multimodal integration of optical and topographical cues,and the deep supervision stabilizes training and improves generalization.Moreover,to mitigate checkerboard artifacts,a learnable sub-pixel upsampling is devised to replace the traditional transposed convolution.Despite its compact design with fewer parameters,the model consistently outperforms state-of-the-art baselines.Experiments on two benchmark datasets,Landslide4Sense and Bijie,confirm the effectiveness of the framework.On the Bijie dataset,it achieves an F1-score of 0.9110 and an intersection over union(IoU)of 0.8839.These results highlight its potential for accurate large-scale landslide inventory mapping and real-time disaster response.The implementation is publicly available at https://github.com/mishaown/DiGATe-UNet-LandSlide-Segmentation(accessed on 3 November 2025).
文摘The South Central Axis in Beijing showcases China’s image and highlights its cultural confidence.THE Central Axis is the centerpiece of the Chinese capital’s urban spatial layout.The southern extended section of the Central Axis,or the South Central Axis,stretches from the Yongdingmen Gate Tower in the north to the South Fifth Ring Road in the south.While being a strategic transport link facilitating the coordinated development of the Beijing-Tianjin-Hebei region,it also showcases China’s vision for the future and highlights its cultural confidence.
基金Project supported by the National Natural Science Foundation of China(Grant No.12174159)。
文摘In recent years,acoustic logic gates has attracted growing interest in acoustics due to their promising applications in acoustic communication and signal processing.For practical implementation,these logic gates must operate over a certain bandwidth to ensure reliable performance.However,current experimental realizations have predominantly been confined to single-frequency or narrowband operation,leaving their broadband capabilities largely unverified.To address this gap,we present both numerical and experimental demonstrations of three basic acoustic logic gates(OR,NOT,and AND)using a phased unit cell composed of a central channel flanked by two arrays of semicircular cavities.By leveraging phase modulation of the unit cells and linear interference of sound,we achieve these logic operations with a uniform threshold of I_(t)=0.25.Remarkably,the measured fractional bandwidths(bandwidth relative to center frequency)reach approximately 111.5%(OR),37.2%(NOT),and 48.5%(AND),demonstrating ultra-broadband functionality.The proposed logic gates combine exceptional bandwidth with structural simplicity,offering significant potential for applications in acoustic computing,information processing,and integrated acoustic systems.
