Microsphere and microcylinder-assisted microscopy(MAM)has grown steadily over the last decade and is still an intensively studied optical far-field imaging technique that promises to overcome the fundamental lateral r...Microsphere and microcylinder-assisted microscopy(MAM)has grown steadily over the last decade and is still an intensively studied optical far-field imaging technique that promises to overcome the fundamental lateral resolution limit of microscopy.However,the physical effects leading to resolution enhancement are still frequently debated.In addition,various configurations of MAM operating in transmission mode as well as reflection mode are examined,and the results are sometimes generalized.We present a rigorous simulation model of MAM and introduce a way to quantify the resolution enhancement.The lateral resolution is compared for microscope arrangements in reflection and transmission modes.Furthermore,we discuss different physical effects with respect to their contribution to resolution enhancement.The results indicate that the effects impacting the resolution in MAM strongly depend on the arrangement of the microscope and the measurement object.As a highlight,we outline that evanescent waves in combination with whispering gallery modes also improve the imaging capabilities,enabling super-resolution under certain circumstances.This result is contrary to the conclusions drawn from previous studies,where phase objects have been analyzed,and thus further emphasizes the complexity of the physical mechanisms underlying MAM.展开更多
We present a unified electromagnetic modeling of coherence scanning interferometry,confocal microscopy,and focus variation microscopy as the most common techniques for surface topography inspection with micro-and nano...We present a unified electromagnetic modeling of coherence scanning interferometry,confocal microscopy,and focus variation microscopy as the most common techniques for surface topography inspection with micro-and nanometer resolution.The model aims at analyzing the instrument response and predicting systematic deviations.Since the main focus lies on the modeling of the microscopes,the light–surface interaction is considered,based on the Kirchhoff approximation extended to vectorial imaging theory.However,it can be replaced by rigorous methods without changing the microscope model.We demonstrate that all of the measuring instruments mentioned above can be modeled using the same theory with some adaption to the respective instrument.For validation,simulated results are confirmed by comparison with measurement results.展开更多
In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniq...In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniques and tries to combine nodes’textual content for modelling.They still do not,however,directly simulate many interactions in network learning.In order to address these issues,we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations.Specifically,we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles in the citation network.Then,the Commuting Matrix for massive node pair paths is used to improve computational performance.Finally,the two commonalities mentioned above are combined with the interaction paper labels based on the additivity of Poisson distribution.In addition,we also consider solving the model’s parameters by applying variational inference.Experimental results demonstrate that our suggested framework agrees and significantly outperforms the state-of-the-art baseline on two real datasets by efficiently merging the three relational data.Based on the Area Under Curve(AUC)and Mean Average Precision(MAP)analysis,the performance of the suggested task is evaluated,and it is demonstrated to have a greater solving efficiency than current techniques.展开更多
With the rapid development of artificial intelligence(AI)technology,the demand for high-performance and energyefficient computing is increasingly growing.The limitations of the traditional von Neumann computing archit...With the rapid development of artificial intelligence(AI)technology,the demand for high-performance and energyefficient computing is increasingly growing.The limitations of the traditional von Neumann computing architecture have prompted researchers to explore neuromorphic computing as a solution.Neuromorphic computing mimics the working principles of the human brain,characterized by high efficiency,low energy consumption,and strong fault tolerance,providing a hardware foundation for the development of new generation AI technology.Artificial neurons and synapses are the two core components of neuromorphic computing systems.Artificial perception is a crucial aspect of neuromorphic computing,where artificial sensory neurons play an irreplaceable role thus becoming a frontier and hot topic of research.This work reviews recent advances in artificial sensory neurons and their applications.First,biological sensory neurons are briefly described.Then,different types of artificial neurons,such as transistor neurons and memristive neurons,are discussed in detail,focusing on their device structures and working mechanisms.Next,the research progress of artificial sensory neurons and their applications in artificial perception systems is systematically elaborated,covering various sensory types,including vision,touch,hearing,taste,and smell.Finally,challenges faced by artificial sensory neurons at both device and system levels are summarized.展开更多
Data clustering is an essential technique for analyzing complex datasets and continues to be a central research topic in data analysis.Traditional clustering algorithms,such as K-means,are widely used due to their sim...Data clustering is an essential technique for analyzing complex datasets and continues to be a central research topic in data analysis.Traditional clustering algorithms,such as K-means,are widely used due to their simplicity and efficiency.This paper proposes a novel Spiral Mechanism-Optimized Phasmatodea Population Evolution Algorithm(SPPE)to improve clustering performance.The SPPE algorithm introduces several enhancements to the standard Phasmatodea Population Evolution(PPE)algorithm.Firstly,a Variable Neighborhood Search(VNS)factor is incorporated to strengthen the local search capability and foster population diversity.Secondly,a position update model,incorporating a spiral mechanism,is designed to improve the algorithm’s global exploration and convergence speed.Finally,a dynamic balancing factor,guided by fitness values,adjusts the search process to balance exploration and exploitation effectively.The performance of SPPE is first validated on CEC2013 benchmark functions,where it demonstrates excellent convergence speed and superior optimization results compared to several state-of-the-art metaheuristic algorithms.To further verify its practical applicability,SPPE is combined with the K-means algorithm for data clustering and tested on seven datasets.Experimental results show that SPPE-K-means improves clustering accuracy,reduces dependency on initialization,and outperforms other clustering approaches.This study highlights SPPE’s robustness and efficiency in solving both optimization and clustering challenges,making it a promising tool for complex data analysis tasks.展开更多
Personalized health services are of paramount importance for the treatment and prevention of cardiorespiratory diseases,such as hypertension.The assessment of cardiorespiratory function and biometric identification(ID...Personalized health services are of paramount importance for the treatment and prevention of cardiorespiratory diseases,such as hypertension.The assessment of cardiorespiratory function and biometric identification(ID)is crucial for the effectiveness of such personalized health services.To effectively and accurately monitor pulse wave signals,thus achieving the assessment of cardiorespiratory function,a wearable photonic smart wristband based on an all-polymer sensing unit(All-PSU)is proposed.The smart wristband enables the assessment of cardiorespiratory function by continuously monitoring respiratory rate(RR),heart rate(HR),and blood pressure(BP).Furthermore,it can be utilized for biometric ID purposes.Through the analysis of pulse wave signals using power spectral density(PSD),accurate monitoring of RR and HR is achieved.Additionally,utilizing peak detection algorithms for feature extraction from pulse signals and subsequently employing a variety of machine learning methods,accurate BP monitoring and biometric ID have been realized.For biometric ID,the accuracy rate is 98.55%.Aiming to monitor RR,HR,BP,and ID,our solution demonstrates advantages in integration,functionality,and monitoring precision.These enhancements may contribute to the development of personalized health services aimed at the treatment and prevention of cardiorespiratory diseases.展开更多
While Metaheuristic optimization techniques are known to work well for clustering and large-scale numerical optimization,algorithms in this category suffer from issues like reinforcement stagnation and poor late-stage...While Metaheuristic optimization techniques are known to work well for clustering and large-scale numerical optimization,algorithms in this category suffer from issues like reinforcement stagnation and poor late-stage refinement.In this paper,we propose the Improved Geyser-Inspired Optimization Algorithm(IGIOA),an enhancement of the Geyser-Inspired Optimization Algorithm(GIOA),which integrates two primary components:the Adaptive Turbulence Operator(ATO)and the Dynamic Pressure Equilibrium Operator(DPEO).ATO allows IGIOA to periodically disrupt stagnation and explore different regions by using turbulence,while DPEO ensures refinement in later iterations by adaptively modulating convergence pressure.We implemented IGIOA on 23 benchmark functions with both unimodal and multimodal contours,in addition to eight problems pertaining to cluster analysis at the UCI.IGIOA,out of all the tested methods,was able to converge most accurately while also achieving a stable convergence rate.The mitigation of premature convergence and low-level exploitation was made possible by the turbulence and pressure-based refinements.The findings from the tests confirm that the adaptation of baseline strategies by IGIOA helps deal with complex data distributions more effectively.However,additional hyperparameters which add complexity are introduced,along with increased computational cost.These include automatic tuning of parameters,ensemble or parallel variations,and hybridization with dedicated local search strategies to extend the reach of IGIOA for general optimization while also specializing it for clustering focused tasks and applications.展开更多
Wireless information and powered transfer networks(WIPT) has recently been implemented in 5th generation wireless networks. In this paper, we consider half-duplex relaying system in which the energy constrained relay ...Wireless information and powered transfer networks(WIPT) has recently been implemented in 5th generation wireless networks. In this paper, we consider half-duplex relaying system in which the energy constrained relay node collects energy via radio frequency(RF) signals from the surrounding resources. Regarding energy harvesting protocol, we propose power time switching-based relaying(PTSR) architecture for both amplify-and-forward(AF) and decode-and-forward(DF). Especially, we reveal the analytical expressions of achievable throughput, ergodic capacity and energy-efficient in case of imperfect channel state information(CSI) for both AF and DF network. Through numerical analysis, we analyse the throughput performance, energy-efficient and ergodic capacity for different parameters, including power splitting ratio and energy harvesting time. Moreover, we also depict the performance comparison between AF and DF network with perfect and imperfect CSI. The results in numerical analysis reveal that the result of AF relaying network is less significant than DF relaying network in the various scenarios.展开更多
This paper deals with the adaptive control mechanism management meant for shunt active power filters (SAPF). Systems driven this way are designed to improve the quality of electric power (power quality) in industrial ...This paper deals with the adaptive control mechanism management meant for shunt active power filters (SAPF). Systems driven this way are designed to improve the quality of electric power (power quality) in industrial networks. The authors have focused on the implementation of two basic representatives of adaptive algorithms, first, the algorithm with a stochastic LMS (least mean square) gradient adaptation and then an algorithm with recursive RLS (recursive least square) optimal adaptation. The system examined by the authors can be used for non-linear loads for appliances with rapid fluctuations of the reactive and active power consumption. The proposed system adaptively reduces distortion, falls (dip) and changes in a supply voltage (flicker). Real signals for measurement were obtained at a sophisticated, three-phase experimental workplace. The results of executed experiments indicate that, with use of the certain adaptive algorithms, the examined AHC system shows very good dynamics, resulting in a much faster transition during the AHC connection-disconnection or during a change in harmonic load on the network. The actual experiments are evaluated from several points of view, mainly according to a time convergence (convergence time) and mistakes in a stable state error (steady state error) of the investigated adaptive algorithms and finally as a total harmonic distortion (THD). The article presents a comparison of the most frequently used adaptive algorithms.展开更多
Highly crystalline β-type strontium hydrogen phosphate （β-SrHPO4） nanosheets were prepared by a hydro- thermal method and used for the immobilization of lead ions （Pb2＋） from acidic aqueous solution. The effect...Highly crystalline β-type strontium hydrogen phosphate （β-SrHPO4） nanosheets were prepared by a hydro- thermal method and used for the immobilization of lead ions （Pb2＋） from acidic aqueous solution. The effects of various parameters on the immobilization process, including solution pH value, contact time, initial ion concentrations, and coexistent competing cations, were studied to optimize the conditions for maximum immobilization. The β-SrHPO4 nanosheets exhibited a capacity of （1,120 ± 22） mg/g toward Pb2＋ in acidic solution （pH value is 3.0）, and the equilibrium was achieved within 8 rain. The competing cations such as Cu2＋, Zn2＋, Cd2＋, and Co2＋ affected slightly on the selective immobilization of Pb2＋. The results revealed that the removal mechanism of Pb2＋ by the β-SrHPO4 nanosheets was the dissolution/precipitation process in the acidic solution.展开更多
Antimony selenide(Sb2Se3) films are widely used in phase change memory and solar cells due to their stable switching effect and excellent photovoltaic properties. These properties of the films are affected by the film...Antimony selenide(Sb2Se3) films are widely used in phase change memory and solar cells due to their stable switching effect and excellent photovoltaic properties. These properties of the films are affected by the film thickness. A method combining the advantages of Levenberg–Marquardt method and spectral fitting method(LM–SFM) is presented to study the dependence of refractive index(RI), absorption coefficient, optical band gap, Wemple–Di Domenico parameters, dielectric constant and optical electronegativity of the Sb2Se3films on their thickness. The results show that the RI and absorption coefficient of the Sb2Se3films increase with the increase of film thickness, while the optical band gap decreases with the increase of film thickness. Finally, the reasons why the optical and electrical properties of the film change with its thickness are explained by x-ray diffractometer(XRD), energy dispersive x-ray spectrometer(EDS), Mott–Davis state density model and Raman microstructure analysis.展开更多
Due to growing numbers of sold HEV （hybrid electric vehicles）, PHEV （plug-in hybrid electric vehicles）, and BEV （battery electric vehicles）, new market opportunities to reuse or recycle old lithium ion batteries...Due to growing numbers of sold HEV （hybrid electric vehicles）, PHEV （plug-in hybrid electric vehicles）, and BEV （battery electric vehicles）, new market opportunities to reuse or recycle old lithium ion batteries arise. Thus, a forecast of available batteries caused by accidents or from end-of-life vehicles was carried out using a mathematical model. Input data were obtained from an estimate of newly registered hybrid and electric vehicles in Germany from 2010 until 2030, from the accident rate of cars in Germany, and from the average cars’ lifetime. The results indicate that （a） the total amount of available second use batteries in 2030 will be between 130,000 units/year and 500,000 units/year, （b） the highest amount of batteries will be obtained from end-of-life vehicles not from accident vehicles, although most batteries from accident vehicles will be suitable for 2nd use, and （c） the quantity of hybrid, plug-in hybrid, and electric car batteries available for reuse will continue to rise after 2030.展开更多
CsPbI_(3)perovskite quantum dots(QDs)are ideal materials for the next generation of red light-emitting diodes.However,the low phase stability of CsPbI_(3)QDs and long-chain insulating capping ligands hinder the improv...CsPbI_(3)perovskite quantum dots(QDs)are ideal materials for the next generation of red light-emitting diodes.However,the low phase stability of CsPbI_(3)QDs and long-chain insulating capping ligands hinder the improvement of device performance.Traditional in-situ ligand replacement and ligand exchange after synthesis were often difficult to control.Here,we proposed a new ligand exchange strategy using a proton-prompted insitu exchange of short 5-aminopentanoic acid ligands with long-chain oleic acid and oleylamine ligands to obtain stable small-size CsPbI_(3)QDs.This exchange strategy maintained the size and morphology of CsPbI_(3)QDs and improved the optical properties and the conductivity of CsPbI_(3)QDs films.As a result,high-efficiency red QD-based light-emitting diodes with an emission wavelength of 645 nm demonstrated a record maximum external quantum efficiency of 24.45%and an operational half-life of 10.79 h.展开更多
The usability assessment of a pacemaker is a complex task where the dedicated programmer for testing programmed algorithms is necessary.This paper provides the outcomes of development and complex testing of the artifi...The usability assessment of a pacemaker is a complex task where the dedicated programmer for testing programmed algorithms is necessary.This paper provides the outcomes of development and complex testing of the artificial cardiac system to evaluate the pacemaker’s functionality.In this work,we used the modular laboratory platform ELVIS II and created graphical user interface in LabVIEW programming environment.The electrical model of the heart allows signals generation(right atrium,right ventricle)and the monitoring of the stimulation pulses.The LabVIEW user interface allows to set the parameters of the generated signals and the simulation of the cardiac rhythm disorders as well as the monitoring and visualization of the pacemaker behavior in real-time.The results demonstrate the capability of proposed system to evaluate the paced and sensed pulses.The proposed solution allows the scientists to test the behavior of any cardiac pacemaker for its pre-programmed settings and pacing mode.In addition,the proposed system can simulate various disorders and test cardiac pacemakers in different working modes.展开更多
Catalysis of molecular radicals is often performed in interesting experimental configurations.One possible configuration is tubular geometry.The radicals are introduced into the tubes on one side,and stable molecules ...Catalysis of molecular radicals is often performed in interesting experimental configurations.One possible configuration is tubular geometry.The radicals are introduced into the tubes on one side,and stable molecules are exhausted on the other side.The penetration depth of radicals depends on numerous parameters,so it is not always feasible to calculate it.This article presents systematic measurements of the penetration depth of oxygen atoms along tubes made from nickel,cobalt,and copper.The source of O atoms was a surfatron-type microwave plasma.The initial density of O atoms depended on the gas flow and was 0.7×10^(21)m^(-3),2.4×10^(21)m^(-3),and 4.2×10^(21)m^(-3)at the flow rates of 50,300,and 600 sccm,and pressures of 10,35,and 60 Pa,respectively.The gas temperature remained at room temperature throughout the experiments.The dissociation fraction decreased exponentially along the length of the tubes in all cases.The penetration depths for well-oxidized nickel were 1.2,1.7,and 2.4 cm,respectively.For cobalt,they were slightly lower at 1.0,1.3,and 1.6 cm,respectively,while for copper,they were 1.1,1.3,and 1.7 cm,respectively.The results were explained by gas dynamics and heterogeneous surface association.These data are useful in any attempt to estimate the loss of molecular fragments along tubes,which serve as catalysts for the association of various radicals to stable molecules.展开更多
The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance;however, there remains room for improvement in convergence and practical applications. This study intro...The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance;however, there remains room for improvement in convergence and practical applications. This study introduces a hybrid optimization algorithm, named the adaptive inertia weight whale optimization algorithm and gannet optimization algorithm (AIWGOA), which addresses challenges in enhancing handwritten documents. The hybrid strategy integrates the strengths of both algorithms, significantly enhancing their capabilities, whereas the adaptive parameter strategy mitigates the need for manual parameter setting. By amalgamating the hybrid strategy and parameter-adaptive approach, the Gannet Optimization Algorithm was refined to yield the AIWGOA. Through a performance analysis of the CEC2013 benchmark, the AIWGOA demonstrates notable advantages across various metrics. Subsequently, an evaluation index was employed to assess the enhanced handwritten documents and images, affirming the superior practical application of the AIWGOA compared with other algorithms.展开更多
Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causin...Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causing magnetic storms.Consequently,it is very important to accurately predict the time period of solar flares.This paper proposes a flare prediction model,based on physical images of active solar regions.We employ X-ray flux curves recorded directly by the Geostationary Operational Environmental Satellite,used as input data for the model,allowing us to largely avoid the influence of accidental errors,effectively improving the model prediction efficiency.A model based on the X-ray flux curve can predict whether there will be a flare event within 24 hours.The reverse can also be verified by the peak of the X-ray flux curve to see if a flare has occurred within the past 24 hours.The True Positive Rate and False Positive Rate of the prediction model,based on physical images of active regions are 0.6070 and 0.2410 respectively,and the accuracy and True Skill Statistics are 0.7590 and 0.5556.Our model can effectively improve prediction efficiency compared with models based on the physical parameters of active regions or magnetic field records,providing a simple method for solar flare prediction.展开更多
The Traveling Salesman Problem(TSP)is a well-known NP-Hard problem,particularly challenging for conventional solving methods due to the curse of dimensionality in high-dimensional instances.This paper proposes a novel...The Traveling Salesman Problem(TSP)is a well-known NP-Hard problem,particularly challenging for conventional solving methods due to the curse of dimensionality in high-dimensional instances.This paper proposes a novel Double-stage Surrogate-assisted Pigeon-inspired Optimization algorithm(DOSA-PIO)to address this issue.DOSA-PIO integrates the ordering points to identify the clustering structure method for data clustering and employs a local surrogate model to assist the evolution of the Pigeon-inspired Optimization(PIO)algorithm.This combination enhances the algorithm’s ability to explore the solution space and converge to optimal solutions more effectively.Additionally,two novel approaches are introduced to extend the generalizability of continuous algorithms for solving discrete problems,enabling the adaptation of continuous optimization techniques to the discrete nature of TSP.Extensive experiments using benchmark functions and high-dimensional TSP instances demonstrate that DOSA-PIO significantly outperforms comparative algorithms in various dimensions(10D,20D,30D,50D,and 100D).The proposed algorithm provides superior solutions compared to traditional methods,highlighting its potential for solving high-dimensional TSPs.By leveraging advanced data clustering techniques and surrogate-assisted optimization,DOSA-PIO offers an effective solution for high-dimensional TSP instances,with experimental results confirming its superior performance and potential for practical applications in complex optimization problems.展开更多
In the 6G era,Space-Air-Ground Integrated Network(SAGIN)are anticipated to deliver global coverage,necessitating support for a diverse array of emerging applications in high-mobility,hostile environments.Under such co...In the 6G era,Space-Air-Ground Integrated Network(SAGIN)are anticipated to deliver global coverage,necessitating support for a diverse array of emerging applications in high-mobility,hostile environments.Under such conditions,conventional orthogonal frequency division multiplexing(OFDM)modulation,widely employed in cellular and Wi-Fi communication systems,experiences performance degradation due to significant Doppler shifts.To overcome this obstacle,a novel twodimensional(2D)modulation approach,namely orthogonal time frequency space(OTFS),has emerged as a key enabler for future high-mobility use cases.Distinctively,OTFS modulates information within the delay-Doppler(DD)domain,as opposed to the timefrequency(TF)domain utilized by OFDM.This offers advantages such as Doppler and delay resilience,reduced signaling latency,a lower peak-to-average ratio(PAPR),and a reduced-complexity implementation.Recent studies further indicate that the direct interplay between information and the physical world in the DD domain positions OTFS as a promising waveform for achieving integrated sensing and communications(ISAC).In this article,we present an in-depth review of OTFS technology in the context of the 6G era,encompassing fundamentals,recent advancements,and future directions.Our objective is to provide a helpful resource for researchers engaged in the field of OTFS.展开更多
The use of magnetic nanoparticle(MNP)-labeled immunochromatography test strips(ICTSs) is very important for point-ofcare testing(POCT). However, common diagnostic methods cannot accurately analyze the weak magnetic si...The use of magnetic nanoparticle(MNP)-labeled immunochromatography test strips(ICTSs) is very important for point-ofcare testing(POCT). However, common diagnostic methods cannot accurately analyze the weak magnetic signal from ICTSs, limiting the applications of POCT. In this study, an ultrasensitive multiplex biosensor was designed to overcome the limitations of capturing and normalization of the weak magnetic signal from MNPs on ICTSs. A machine learning model for sandwich assays was constructed and used to classify weakly positive and negative samples, which significantly enhanced the specificity and sensitivity. The potential clinical application was evaluated by detecting 50 human chorionic gonadotropin(HCG) samples and 59 myocardial infarction serum samples. The quantitative range for HCG was 1–1000 mIU mL^(-1) and the ideal detection limit was 0.014 mIU mL^(-1), which was well below the clinical threshold. Quantitative detection results of multiplex cardiac markers showed good linear correlations with standard values. The proposed multiplex assay can be readily adapted for identifying other biomolecules and also be used in other applications such as environmental monitoring, food analysis, and national security.展开更多
基金supported by the German Research Foundation(DFG)(Grant Nos.LE 992/14-3 and LE 992/15-3).
文摘Microsphere and microcylinder-assisted microscopy(MAM)has grown steadily over the last decade and is still an intensively studied optical far-field imaging technique that promises to overcome the fundamental lateral resolution limit of microscopy.However,the physical effects leading to resolution enhancement are still frequently debated.In addition,various configurations of MAM operating in transmission mode as well as reflection mode are examined,and the results are sometimes generalized.We present a rigorous simulation model of MAM and introduce a way to quantify the resolution enhancement.The lateral resolution is compared for microscope arrangements in reflection and transmission modes.Furthermore,we discuss different physical effects with respect to their contribution to resolution enhancement.The results indicate that the effects impacting the resolution in MAM strongly depend on the arrangement of the microscope and the measurement object.As a highlight,we outline that evanescent waves in combination with whispering gallery modes also improve the imaging capabilities,enabling super-resolution under certain circumstances.This result is contrary to the conclusions drawn from previous studies,where phase objects have been analyzed,and thus further emphasizes the complexity of the physical mechanisms underlying MAM.
基金support of the following research Projects (Nos.GZ:LE 992/14-3 and LE 992/18-1)by the Deutsche Forschungsgemeinschaft and the EMPIR program (project TracOptic,20IND07)co-financed by the European Union’s Horizon 2020 Research and Innovation Program.
文摘We present a unified electromagnetic modeling of coherence scanning interferometry,confocal microscopy,and focus variation microscopy as the most common techniques for surface topography inspection with micro-and nanometer resolution.The model aims at analyzing the instrument response and predicting systematic deviations.Since the main focus lies on the modeling of the microscopes,the light–surface interaction is considered,based on the Kirchhoff approximation extended to vectorial imaging theory.However,it can be replaced by rigorous methods without changing the microscope model.We demonstrate that all of the measuring instruments mentioned above can be modeled using the same theory with some adaption to the respective instrument.For validation,simulated results are confirmed by comparison with measurement results.
基金supported by the National Natural Science Foundation of China(No.62271274).
文摘In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniques and tries to combine nodes’textual content for modelling.They still do not,however,directly simulate many interactions in network learning.In order to address these issues,we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations.Specifically,we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles in the citation network.Then,the Commuting Matrix for massive node pair paths is used to improve computational performance.Finally,the two commonalities mentioned above are combined with the interaction paper labels based on the additivity of Poisson distribution.In addition,we also consider solving the model’s parameters by applying variational inference.Experimental results demonstrate that our suggested framework agrees and significantly outperforms the state-of-the-art baseline on two real datasets by efficiently merging the three relational data.Based on the Area Under Curve(AUC)and Mean Average Precision(MAP)analysis,the performance of the suggested task is evaluated,and it is demonstrated to have a greater solving efficiency than current techniques.
基金supported by the National Natural Science Foundation of China(Nos.U20A20209 and 62304228)the China National Postdoctoral Program for Innovative Talents(No.BX2021326)+3 种基金the China Postdoctoral Science Foundation(No.2021M703310)the Zhejiang Provincial Natural Science Foundation of China(No.LQ22F040003)the Ningbo Natural Science Foundation of China(No.2023J356)the State Key Laboratory for Environment-Friendly Energy Materials(No.20kfhg09).
文摘With the rapid development of artificial intelligence(AI)technology,the demand for high-performance and energyefficient computing is increasingly growing.The limitations of the traditional von Neumann computing architecture have prompted researchers to explore neuromorphic computing as a solution.Neuromorphic computing mimics the working principles of the human brain,characterized by high efficiency,low energy consumption,and strong fault tolerance,providing a hardware foundation for the development of new generation AI technology.Artificial neurons and synapses are the two core components of neuromorphic computing systems.Artificial perception is a crucial aspect of neuromorphic computing,where artificial sensory neurons play an irreplaceable role thus becoming a frontier and hot topic of research.This work reviews recent advances in artificial sensory neurons and their applications.First,biological sensory neurons are briefly described.Then,different types of artificial neurons,such as transistor neurons and memristive neurons,are discussed in detail,focusing on their device structures and working mechanisms.Next,the research progress of artificial sensory neurons and their applications in artificial perception systems is systematically elaborated,covering various sensory types,including vision,touch,hearing,taste,and smell.Finally,challenges faced by artificial sensory neurons at both device and system levels are summarized.
文摘Data clustering is an essential technique for analyzing complex datasets and continues to be a central research topic in data analysis.Traditional clustering algorithms,such as K-means,are widely used due to their simplicity and efficiency.This paper proposes a novel Spiral Mechanism-Optimized Phasmatodea Population Evolution Algorithm(SPPE)to improve clustering performance.The SPPE algorithm introduces several enhancements to the standard Phasmatodea Population Evolution(PPE)algorithm.Firstly,a Variable Neighborhood Search(VNS)factor is incorporated to strengthen the local search capability and foster population diversity.Secondly,a position update model,incorporating a spiral mechanism,is designed to improve the algorithm’s global exploration and convergence speed.Finally,a dynamic balancing factor,guided by fitness values,adjusts the search process to balance exploration and exploitation effectively.The performance of SPPE is first validated on CEC2013 benchmark functions,where it demonstrates excellent convergence speed and superior optimization results compared to several state-of-the-art metaheuristic algorithms.To further verify its practical applicability,SPPE is combined with the K-means algorithm for data clustering and tested on seven datasets.Experimental results show that SPPE-K-means improves clustering accuracy,reduces dependency on initialization,and outperforms other clustering approaches.This study highlights SPPE’s robustness and efficiency in solving both optimization and clustering challenges,making it a promising tool for complex data analysis tasks.
基金funded by the National Key R&D Program of China(2022YFE0140400)the National Natural Science Foundation of China(62405027, 62111530238, 62003046)+3 种基金Supporting project of major scientific research projects of Beijing Normal University at Zhuhai (ZHPT2023007)supported by the Tang Scholar of Beijing Normal Universityco-funded by the financial support of the European Union under the REFRESH-Research Excellence For REgion Sustainability and High-tech Industries project number CZ.10.03.01/00/22003/0000048 via the Operational Programme Just Transitionthe scope of the projects CICECO-Aveiro Institute of Materials, UIDB/50011/2020 (DOI 10.54499/UIDB/50011/2020), UIDP/50011/2020 (DOI 10.54499/UIDP/50011/2020) & LA/P/0006/2020 (DOI 10.54499/LA/P/0006/2020) financed by national funds through the FCT/MCTES (PIDDAC)
文摘Personalized health services are of paramount importance for the treatment and prevention of cardiorespiratory diseases,such as hypertension.The assessment of cardiorespiratory function and biometric identification(ID)is crucial for the effectiveness of such personalized health services.To effectively and accurately monitor pulse wave signals,thus achieving the assessment of cardiorespiratory function,a wearable photonic smart wristband based on an all-polymer sensing unit(All-PSU)is proposed.The smart wristband enables the assessment of cardiorespiratory function by continuously monitoring respiratory rate(RR),heart rate(HR),and blood pressure(BP).Furthermore,it can be utilized for biometric ID purposes.Through the analysis of pulse wave signals using power spectral density(PSD),accurate monitoring of RR and HR is achieved.Additionally,utilizing peak detection algorithms for feature extraction from pulse signals and subsequently employing a variety of machine learning methods,accurate BP monitoring and biometric ID have been realized.For biometric ID,the accuracy rate is 98.55%.Aiming to monitor RR,HR,BP,and ID,our solution demonstrates advantages in integration,functionality,and monitoring precision.These enhancements may contribute to the development of personalized health services aimed at the treatment and prevention of cardiorespiratory diseases.
基金King Saud University for funding this work through Researchers Supporting Project number(RSPD2024R697),King Saud University,Riyadh,Saudi Arabiafinancial support European Union under the REFRESH-Research Excellence For REgion Sustainability and High-tech Industries project number CZ.10.03.01/00/22_/0000048 via the Operational Programme Just Transition.
文摘While Metaheuristic optimization techniques are known to work well for clustering and large-scale numerical optimization,algorithms in this category suffer from issues like reinforcement stagnation and poor late-stage refinement.In this paper,we propose the Improved Geyser-Inspired Optimization Algorithm(IGIOA),an enhancement of the Geyser-Inspired Optimization Algorithm(GIOA),which integrates two primary components:the Adaptive Turbulence Operator(ATO)and the Dynamic Pressure Equilibrium Operator(DPEO).ATO allows IGIOA to periodically disrupt stagnation and explore different regions by using turbulence,while DPEO ensures refinement in later iterations by adaptively modulating convergence pressure.We implemented IGIOA on 23 benchmark functions with both unimodal and multimodal contours,in addition to eight problems pertaining to cluster analysis at the UCI.IGIOA,out of all the tested methods,was able to converge most accurately while also achieving a stable convergence rate.The mitigation of premature convergence and low-level exploitation was made possible by the turbulence and pressure-based refinements.The findings from the tests confirm that the adaptation of baseline strategies by IGIOA helps deal with complex data distributions more effectively.However,additional hyperparameters which add complexity are introduced,along with increased computational cost.These include automatic tuning of parameters,ensemble or parallel variations,and hybridization with dedicated local search strategies to extend the reach of IGIOA for general optimization while also specializing it for clustering focused tasks and applications.
文摘Wireless information and powered transfer networks(WIPT) has recently been implemented in 5th generation wireless networks. In this paper, we consider half-duplex relaying system in which the energy constrained relay node collects energy via radio frequency(RF) signals from the surrounding resources. Regarding energy harvesting protocol, we propose power time switching-based relaying(PTSR) architecture for both amplify-and-forward(AF) and decode-and-forward(DF). Especially, we reveal the analytical expressions of achievable throughput, ergodic capacity and energy-efficient in case of imperfect channel state information(CSI) for both AF and DF network. Through numerical analysis, we analyse the throughput performance, energy-efficient and ergodic capacity for different parameters, including power splitting ratio and energy harvesting time. Moreover, we also depict the performance comparison between AF and DF network with perfect and imperfect CSI. The results in numerical analysis reveal that the result of AF relaying network is less significant than DF relaying network in the various scenarios.
文摘This paper deals with the adaptive control mechanism management meant for shunt active power filters (SAPF). Systems driven this way are designed to improve the quality of electric power (power quality) in industrial networks. The authors have focused on the implementation of two basic representatives of adaptive algorithms, first, the algorithm with a stochastic LMS (least mean square) gradient adaptation and then an algorithm with recursive RLS (recursive least square) optimal adaptation. The system examined by the authors can be used for non-linear loads for appliances with rapid fluctuations of the reactive and active power consumption. The proposed system adaptively reduces distortion, falls (dip) and changes in a supply voltage (flicker). Real signals for measurement were obtained at a sophisticated, three-phase experimental workplace. The results of executed experiments indicate that, with use of the certain adaptive algorithms, the examined AHC system shows very good dynamics, resulting in a much faster transition during the AHC connection-disconnection or during a change in harmonic load on the network. The actual experiments are evaluated from several points of view, mainly according to a time convergence (convergence time) and mistakes in a stable state error (steady state error) of the investigated adaptive algorithms and finally as a total harmonic distortion (THD). The article presents a comparison of the most frequently used adaptive algorithms.
基金financially supported by the National Natural Science Foundation of China (No.21377063)K.C.Wong Magna Fund in Ningbo University
文摘Highly crystalline β-type strontium hydrogen phosphate （β-SrHPO4） nanosheets were prepared by a hydro- thermal method and used for the immobilization of lead ions （Pb2＋） from acidic aqueous solution. The effects of various parameters on the immobilization process, including solution pH value, contact time, initial ion concentrations, and coexistent competing cations, were studied to optimize the conditions for maximum immobilization. The β-SrHPO4 nanosheets exhibited a capacity of （1,120 ± 22） mg/g toward Pb2＋ in acidic solution （pH value is 3.0）, and the equilibrium was achieved within 8 rain. The competing cations such as Cu2＋, Zn2＋, Cd2＋, and Co2＋ affected slightly on the selective immobilization of Pb2＋. The results revealed that the removal mechanism of Pb2＋ by the β-SrHPO4 nanosheets was the dissolution/precipitation process in the acidic solution.
基金supported by the National Natural Science Foundation of China (Grant Nos. 62075109, 62135011, 62075107, and 61935006)K. C. Wong Magna Fund in Ningbo University。
文摘Antimony selenide(Sb2Se3) films are widely used in phase change memory and solar cells due to their stable switching effect and excellent photovoltaic properties. These properties of the films are affected by the film thickness. A method combining the advantages of Levenberg–Marquardt method and spectral fitting method(LM–SFM) is presented to study the dependence of refractive index(RI), absorption coefficient, optical band gap, Wemple–Di Domenico parameters, dielectric constant and optical electronegativity of the Sb2Se3films on their thickness. The results show that the RI and absorption coefficient of the Sb2Se3films increase with the increase of film thickness, while the optical band gap decreases with the increase of film thickness. Finally, the reasons why the optical and electrical properties of the film change with its thickness are explained by x-ray diffractometer(XRD), energy dispersive x-ray spectrometer(EDS), Mott–Davis state density model and Raman microstructure analysis.
文摘Due to growing numbers of sold HEV （hybrid electric vehicles）, PHEV （plug-in hybrid electric vehicles）, and BEV （battery electric vehicles）, new market opportunities to reuse or recycle old lithium ion batteries arise. Thus, a forecast of available batteries caused by accidents or from end-of-life vehicles was carried out using a mathematical model. Input data were obtained from an estimate of newly registered hybrid and electric vehicles in Germany from 2010 until 2030, from the accident rate of cars in Germany, and from the average cars’ lifetime. The results indicate that （a） the total amount of available second use batteries in 2030 will be between 130,000 units/year and 500,000 units/year, （b） the highest amount of batteries will be obtained from end-of-life vehicles not from accident vehicles, although most batteries from accident vehicles will be suitable for 2nd use, and （c） the quantity of hybrid, plug-in hybrid, and electric car batteries available for reuse will continue to rise after 2030.
基金This work was financially supported by the National Key Research and Development Program of China(2022YFB3602902)the Key Projects of National Natural Science Foundation of China(62234004)+5 种基金Innovation and Entrepreneurship Team of Zhejiang Province(2021R01003)Science and Technology Innovation 2025 Major Project of Ningbo(2022Z085)Ningbo 3315 Programme(2020A-01-B)YONGJIANG Talent Introduction Programme(2021A-038-B)Flexible Electronics Zhejiang Province Key Laboratory Fund Project(2022FEO02)Zhejiang Provincial Natural Science Foundation of China(LR21F050001).
文摘CsPbI_(3)perovskite quantum dots(QDs)are ideal materials for the next generation of red light-emitting diodes.However,the low phase stability of CsPbI_(3)QDs and long-chain insulating capping ligands hinder the improvement of device performance.Traditional in-situ ligand replacement and ligand exchange after synthesis were often difficult to control.Here,we proposed a new ligand exchange strategy using a proton-prompted insitu exchange of short 5-aminopentanoic acid ligands with long-chain oleic acid and oleylamine ligands to obtain stable small-size CsPbI_(3)QDs.This exchange strategy maintained the size and morphology of CsPbI_(3)QDs and improved the optical properties and the conductivity of CsPbI_(3)QDs films.As a result,high-efficiency red QD-based light-emitting diodes with an emission wavelength of 645 nm demonstrated a record maximum external quantum efficiency of 24.45%and an operational half-life of 10.79 h.
基金Thework and the contributions were supported by the project SV4502261/SP2022/98‘Biomedical Engineering systems XVIII’.
文摘The usability assessment of a pacemaker is a complex task where the dedicated programmer for testing programmed algorithms is necessary.This paper provides the outcomes of development and complex testing of the artificial cardiac system to evaluate the pacemaker’s functionality.In this work,we used the modular laboratory platform ELVIS II and created graphical user interface in LabVIEW programming environment.The electrical model of the heart allows signals generation(right atrium,right ventricle)and the monitoring of the stimulation pulses.The LabVIEW user interface allows to set the parameters of the generated signals and the simulation of the cardiac rhythm disorders as well as the monitoring and visualization of the pacemaker behavior in real-time.The results demonstrate the capability of proposed system to evaluate the paced and sensed pulses.The proposed solution allows the scientists to test the behavior of any cardiac pacemaker for its pre-programmed settings and pacing mode.In addition,the proposed system can simulate various disorders and test cardiac pacemakers in different working modes.
基金funded by the Slovenian Research Agency,Core Funding(No.P2-0082)and Project(No.L24487)。
文摘Catalysis of molecular radicals is often performed in interesting experimental configurations.One possible configuration is tubular geometry.The radicals are introduced into the tubes on one side,and stable molecules are exhausted on the other side.The penetration depth of radicals depends on numerous parameters,so it is not always feasible to calculate it.This article presents systematic measurements of the penetration depth of oxygen atoms along tubes made from nickel,cobalt,and copper.The source of O atoms was a surfatron-type microwave plasma.The initial density of O atoms depended on the gas flow and was 0.7×10^(21)m^(-3),2.4×10^(21)m^(-3),and 4.2×10^(21)m^(-3)at the flow rates of 50,300,and 600 sccm,and pressures of 10,35,and 60 Pa,respectively.The gas temperature remained at room temperature throughout the experiments.The dissociation fraction decreased exponentially along the length of the tubes in all cases.The penetration depths for well-oxidized nickel were 1.2,1.7,and 2.4 cm,respectively.For cobalt,they were slightly lower at 1.0,1.3,and 1.6 cm,respectively,while for copper,they were 1.1,1.3,and 1.7 cm,respectively.The results were explained by gas dynamics and heterogeneous surface association.These data are useful in any attempt to estimate the loss of molecular fragments along tubes,which serve as catalysts for the association of various radicals to stable molecules.
文摘The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance;however, there remains room for improvement in convergence and practical applications. This study introduces a hybrid optimization algorithm, named the adaptive inertia weight whale optimization algorithm and gannet optimization algorithm (AIWGOA), which addresses challenges in enhancing handwritten documents. The hybrid strategy integrates the strengths of both algorithms, significantly enhancing their capabilities, whereas the adaptive parameter strategy mitigates the need for manual parameter setting. By amalgamating the hybrid strategy and parameter-adaptive approach, the Gannet Optimization Algorithm was refined to yield the AIWGOA. Through a performance analysis of the CEC2013 benchmark, the AIWGOA demonstrates notable advantages across various metrics. Subsequently, an evaluation index was employed to assess the enhanced handwritten documents and images, affirming the superior practical application of the AIWGOA compared with other algorithms.
基金partially supported by the National Key R&D Program of China (2022YFE0133700)the National Natural Science Foundation of China(12273007)+4 种基金the Guizhou Provincial Excellent Young Science and Technology Talent Program (YQK[2023]006)the National SKA Program of China (2020SKA0110300)the National Natural Science Foundation of China(11963003)the Guizhou Provincial Basic Research Program (Natural Science)(ZK[2022]143)the Cultivation project of Guizhou University ([2020]76).
文摘Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causing magnetic storms.Consequently,it is very important to accurately predict the time period of solar flares.This paper proposes a flare prediction model,based on physical images of active solar regions.We employ X-ray flux curves recorded directly by the Geostationary Operational Environmental Satellite,used as input data for the model,allowing us to largely avoid the influence of accidental errors,effectively improving the model prediction efficiency.A model based on the X-ray flux curve can predict whether there will be a flare event within 24 hours.The reverse can also be verified by the peak of the X-ray flux curve to see if a flare has occurred within the past 24 hours.The True Positive Rate and False Positive Rate of the prediction model,based on physical images of active regions are 0.6070 and 0.2410 respectively,and the accuracy and True Skill Statistics are 0.7590 and 0.5556.Our model can effectively improve prediction efficiency compared with models based on the physical parameters of active regions or magnetic field records,providing a simple method for solar flare prediction.
基金funded by National Natural Science Foundation of China(Project No.52072314,52172321,52102391)China Shenhua Energy Co.,Ltd.,Science and Technology Program(Project No.GJNY-22-7)+2 种基金China State Railway Group Co.,Ltd.Science and Technology Program(P2022×013,K2023×030)Key science and technology projects in the transportation industry of the Ministry of Transport(2022-ZD7-131)the fundamental research funds for the central universities(2682022ZTPY068).
文摘The Traveling Salesman Problem(TSP)is a well-known NP-Hard problem,particularly challenging for conventional solving methods due to the curse of dimensionality in high-dimensional instances.This paper proposes a novel Double-stage Surrogate-assisted Pigeon-inspired Optimization algorithm(DOSA-PIO)to address this issue.DOSA-PIO integrates the ordering points to identify the clustering structure method for data clustering and employs a local surrogate model to assist the evolution of the Pigeon-inspired Optimization(PIO)algorithm.This combination enhances the algorithm’s ability to explore the solution space and converge to optimal solutions more effectively.Additionally,two novel approaches are introduced to extend the generalizability of continuous algorithms for solving discrete problems,enabling the adaptation of continuous optimization techniques to the discrete nature of TSP.Extensive experiments using benchmark functions and high-dimensional TSP instances demonstrate that DOSA-PIO significantly outperforms comparative algorithms in various dimensions(10D,20D,30D,50D,and 100D).The proposed algorithm provides superior solutions compared to traditional methods,highlighting its potential for solving high-dimensional TSPs.By leveraging advanced data clustering techniques and surrogate-assisted optimization,DOSA-PIO offers an effective solution for high-dimensional TSP instances,with experimental results confirming its superior performance and potential for practical applications in complex optimization problems.
基金supported in part by National Natural Science Foundation of China under Grant 62101232in part by Guangdong Provincial Natural Science Foundation under Grant 2022A1515011257in part by Shenzhen Science and Technology Program under Grant JCYJ20220530114412029。
文摘In the 6G era,Space-Air-Ground Integrated Network(SAGIN)are anticipated to deliver global coverage,necessitating support for a diverse array of emerging applications in high-mobility,hostile environments.Under such conditions,conventional orthogonal frequency division multiplexing(OFDM)modulation,widely employed in cellular and Wi-Fi communication systems,experiences performance degradation due to significant Doppler shifts.To overcome this obstacle,a novel twodimensional(2D)modulation approach,namely orthogonal time frequency space(OTFS),has emerged as a key enabler for future high-mobility use cases.Distinctively,OTFS modulates information within the delay-Doppler(DD)domain,as opposed to the timefrequency(TF)domain utilized by OFDM.This offers advantages such as Doppler and delay resilience,reduced signaling latency,a lower peak-to-average ratio(PAPR),and a reduced-complexity implementation.Recent studies further indicate that the direct interplay between information and the physical world in the DD domain positions OTFS as a promising waveform for achieving integrated sensing and communications(ISAC).In this article,we present an in-depth review of OTFS technology in the context of the 6G era,encompassing fundamentals,recent advancements,and future directions.Our objective is to provide a helpful resource for researchers engaged in the field of OTFS.
基金support by the National Key Research and Development Program of China (Grant Nos. 2017FYA0205301, and 2017FYA0205303)the National Natural Science Foundation of China (Grant Nos. 81571835 and 81672247)+3 种基金National Key Research and Development Program of China (No. 2017YFA0205303)National Key Basic Research Program (973 Project) (No. 2015CB931802)"13th Five-Year Plan" Science and Technology Project of Jilin Province Education Department (No. JJKH20170410K)Shanghai Science and Technology Fund (No. 15DZ2252000)
文摘The use of magnetic nanoparticle(MNP)-labeled immunochromatography test strips(ICTSs) is very important for point-ofcare testing(POCT). However, common diagnostic methods cannot accurately analyze the weak magnetic signal from ICTSs, limiting the applications of POCT. In this study, an ultrasensitive multiplex biosensor was designed to overcome the limitations of capturing and normalization of the weak magnetic signal from MNPs on ICTSs. A machine learning model for sandwich assays was constructed and used to classify weakly positive and negative samples, which significantly enhanced the specificity and sensitivity. The potential clinical application was evaluated by detecting 50 human chorionic gonadotropin(HCG) samples and 59 myocardial infarction serum samples. The quantitative range for HCG was 1–1000 mIU mL^(-1) and the ideal detection limit was 0.014 mIU mL^(-1), which was well below the clinical threshold. Quantitative detection results of multiplex cardiac markers showed good linear correlations with standard values. The proposed multiplex assay can be readily adapted for identifying other biomolecules and also be used in other applications such as environmental monitoring, food analysis, and national security.
