The increasing demands of multifunctional organic electronics require advanced organic semiconducting materials to be developed and significant improvements to be made to device performance. Thus, it is necessary to g...The increasing demands of multifunctional organic electronics require advanced organic semiconducting materials to be developed and significant improvements to be made to device performance. Thus, it is necessary to gain an in-depth understanding of the film growth process, electronic states, and dynamic structure-property relationship under realistic operation conditions, which can be obtained by in-situ/operando characterization techniques for organic devices. Here, the up-todate developments in the in-situ/operando optical, scanning probe microscopy, and spectroscopy techniques that are employed for studies of film morphological evolution, crystal structures, semiconductor-electrolyte interface properties, and charge carrier dynamics are described and summarized. These advanced technologies leverage the traditional static characterizations into an in-situ and interactive manipulation of organic semiconducting films and devices without sacrificing the resolution, which facilitates the exploration of the intrinsic structure-property relationship of organic materials and the optimization of organic devices for advanced applications.展开更多
The structure and function of brain networks have been altered in patients with end-stage renal disease(ESRD).Manifold regularization(MR)only considers the pairing relationship between two brain regions and cannot rep...The structure and function of brain networks have been altered in patients with end-stage renal disease(ESRD).Manifold regularization(MR)only considers the pairing relationship between two brain regions and cannot represent functional interactions or higher-order relationships between multiple brain regions.To solve this issue,we developed a method to construct a dynamic brain functional network(DBFN)based on dynamic hypergraph MR(DHMR)and applied it to the classification of ESRD associated with mild cognitive impairment(ESRDaMCI).The construction of DBFN with Pearson’s correlation(PC)was transformed into an optimization model.Node convolution and hyperedge convolution superposition were adopted to dynamically modify the hypergraph structure,and then got the dynamic hypergraph to form the manifold regular terms of the dynamic hypergraph.The DHMR and L_(1) norm regularization were introduced into the PC-based optimization model to obtain the final DHMR-based DBFN(DDBFN).Experiment results demonstrated the validity of the DDBFN method by comparing the classification results with several related brain functional network construction methods.Our work not only improves better classification performance but also reveals the discriminative regions of ESRDaMCI,providing a reference for clinical research and auxiliary diagnosis of concomitant cognitive impairments.展开更多
Organic light-emitting diode(OLED)is an electroluminescent technology that relies on charge-carrier dynamics and is a potential light source for variable environmental conditions.Here,by exploiting a self-developed lo...Organic light-emitting diode(OLED)is an electroluminescent technology that relies on charge-carrier dynamics and is a potential light source for variable environmental conditions.Here,by exploiting a self-developed low-temperature testing system,we investigated the characteristics of hole/electron transport,electro-optic conversion efficiency,and operation lifetime of OLEDs at low-temperature ranging from-40℃to 0℃and room temperature(25℃).Compared to devices operating at room temperature,the carrier transport capability is significantly decreased with reducing temperature,and especially the mobility of the hole-transporting material(HTM)and electron-transporting material(ETM)at-40℃decreases from 1.16×10-6 cm2/V·s and 2.60×10-4 cm2/V·s to 6.91×10-9 cm2/V·s and 1.44×10-5 cm2/V·s,respectively.Indeed,the temperature affects differently on the mobilities of HTM and ETM,which favors unbalanced charge-carrier transport and recombination in OLEDs,thereby leading to the maximum current efficiency decreased from 6.46 cd·A-1 at 25℃to 2.74 cd·A-1 at-40℃.In addition,blue fluorescent OLED at-20℃has an above 56%lifetime improvement(time to 80%of the initial luminance)over the reference device at room temperature,which is attributed to efficiently dissipating heat generated inside the device by the low-temperature environment.展开更多
We fabricated monolayer n-type two-dimensional crystalline semiconducting films with millimeter-sized areas and remarkable morphological uniformity using an antisolvent-confined spin-coating method.The antisolvent can...We fabricated monolayer n-type two-dimensional crystalline semiconducting films with millimeter-sized areas and remarkable morphological uniformity using an antisolvent-confined spin-coating method.The antisolvent can cause a downstream Marangoni flow,which improves the film morphologies.The deposited crystalline monolayer films exhibit excellent thermal stabilities after annealing,which reveals the annealing-induced enhancement of crystallinity.The transistors based on the n-type monolayer crystalline films show linear output characteristics and superior electron mobilities.The improved charge injection between monolayer films and Au electrodes results from the energy level shift as the films decrease to the monolayer,which leads to a lower injection barrier.This work demonstrates a promising method for fabricating air-stable,low-cost,high-performance,and large-area organic electronics.展开更多
Real-time detection of unhealthy fish remains a significant challenge in intensive recirculating aquaculture.Early recognition of unhealthy fish and the implementation of appropriate treatment measures are crucial for...Real-time detection of unhealthy fish remains a significant challenge in intensive recirculating aquaculture.Early recognition of unhealthy fish and the implementation of appropriate treatment measures are crucial for preventing the spread of diseases and minimizing economic losses.To address this issue,an improved algorithm based on the You Only Look Once v5s(YOLOv5s)lightweight model has been proposed.This enhanced model incorporates a faster lightweight structure and a new Convolutional Block Attention Module(CBAM)to achieve high recognition accuracy.Furthermore,the model introduces theα-SIoU loss function,which combines theα-Intersection over Union(α-IoU)and Shape Intersection over Union(SIoU)loss functions,thereby improving the accuracy of bounding box regression and object recognition.The average precision of the improved model reaches 94.2%for detecting unhealthy fish,representing increases of 11.3%,9.9%,9.7%,2.5%,and 2.1%compared to YOLOv3-tiny,YOLOv4,YOLOv5s,GhostNet-YOLOv5,and YOLOv7,respectively.Additionally,the improved model positively impacts hardware efficiency,reducing requirements for memory size by 59.0%,67.0%,63.0%,44.7%,and 55.6%in comparison to the five models mentioned above.The experimental results underscore the effectiveness of these approaches in addressing the challenges associated with fish health detection,and highlighting their significant practical implications and broad application prospects.展开更多
The field of terahertz devices is important in terahertz technology.However,most of the current devices have limited functionality and poor performance.To improve device performance and achieve multifunctionality,we d...The field of terahertz devices is important in terahertz technology.However,most of the current devices have limited functionality and poor performance.To improve device performance and achieve multifunctionality,we designed a terahertz device based on a combination of VO_(2)and metamaterials.This device can be tuned using the phase-transition characteristics of VO_(2),which is included in the triple-layer structure of the device,along with SiO_(2)and Au.The terahertz device exhibits various advantageous features,including broadband coverage,high absorption capability,dynamic tunability,simple structural design,polarization insensitivity,and incidentangle insensitivity.The simulation results showed that by controlling the temperature,the terahertz device achieved a thermal modulation range of spectral absorption from 0 to 0.99.At 313 K,the device exhibited complete reflection of terahertz waves.As the temperature increased,the absorption rate also increased.When the temperature reached 353 K,the device absorption rate exceeded 97.7%in the range of 5-8.55 THz.This study used the effective medium theory to elucidate the correlation between conductivity and temperature during the phase transition of VO_(2).Simultaneously,the variation in device performance was further elucidated by analyzing and depicting the intensity distribution of the electric field on the device surface at different temperatures.Furthermore,the impact of various structural parameters on device performance was examined,offering valuable insights and suggestions for selecting suitable parameter values in real-world applications.These characteristics render the device highly promising for applications in stealth technology,energy harvesting,modulation,and other related fields,thus showcasing its significant potential.展开更多
Based on the two-dimensional(2D)discrete Rulkov model that is used to describe neuron dynamics,this paper presents a continuous non-autonomous memristive Rulkov model.The effects of electromagnetic induction and exter...Based on the two-dimensional(2D)discrete Rulkov model that is used to describe neuron dynamics,this paper presents a continuous non-autonomous memristive Rulkov model.The effects of electromagnetic induction and external stimulus are simultaneously considered herein.The electromagnetic induction flow is imitated by the generated current from a flux-controlled memristor and the external stimulus is injected using a sinusoidal current.Thus,the presented model possesses a line equilibrium set evolving over the time.The equilibrium set and their stability distributions are numerically simulated and qualitatively analyzed.Afterwards,numerical simulations are executed to explore the dynamical behaviors associated to the electromagnetic induction,external stimulus,and initial conditions.Interestingly,the initial conditions dependent extreme multistability is elaborately disclosed in the continuous non-autonomous memristive Rulkov model.Furthermore,an analog circuit of the proposed model is implemented,upon which the hardware experiment is executed to verify the numerically simulated extreme multistability.The extreme multistability is numerically revealed and experimentally confirmed in this paper,which can widen the future engineering employment of the Rulkov model.展开更多
Visible light communication(VLC)is an emerging technology employing light-emitting diodes(LEDs)to provide illumination and wireless data transmission simultaneously.Harnessing cost-efficient printable organic LEDs(OLE...Visible light communication(VLC)is an emerging technology employing light-emitting diodes(LEDs)to provide illumination and wireless data transmission simultaneously.Harnessing cost-efficient printable organic LEDs(OLEDs)as environmentally friendly transmitters in VLC systems is extremely attractive for future applications in spectroscopy,the internet of things,sensing,and optical ranging in general.Here,we summarize the latest research progress on emerging semiconductor materials for LED sources in VLC,and highlight that OLEDs based on nontoxic and cost-efficient organic semiconductors have great opportunities for optical communication.We further examine efforts to achieve high-performance white OLEDs for general lighting,and,in particular,focus on the research status and opportunities for OLED-based VLC.Different solution-processable fabrication and printing strategies to develop high-performance OLEDs are also discussed.Finally,an outlook on future challenges and potential prospects of the next-generation organic VLC is provided.展开更多
This study introduces an innovative dual-tunable absorption film with the capability to switch between ultra-wideband and narrowband absorption.By manipulating the temperature,the film can achieve multi-band absorptio...This study introduces an innovative dual-tunable absorption film with the capability to switch between ultra-wideband and narrowband absorption.By manipulating the temperature,the film can achieve multi-band absorption within the 30-45 THz range or ultra-wideband absorption spanning 30-130 THz,with an absorption rate exceeding 0.9.Furthermore,the structural parameters of the absorption film are optimized using the particle swarm optimization(PSO)algorithm to ensure the optimal absorption response.The absorption response of the film is primarily attributed to the coupling of guided-mode resonance and local surface plasmon resonance effects.The film's symmetric structure enables polarization incoherence and allows for tuning through various means such as doping/voltage,temperature and structural parameters.In the case of a multi-band absorption response,the film exhibits good sensitivity to refractive index changes in multiple absorption modes.Additionally,the absorption spectrum of the film remains effective even at large incidence angles,making it highly promising for applications in fields such as biosensing and infrared stealth.展开更多
Graph filtering is an important part of graph signal processing and a useful tool for image denoising.Existing graph filtering methods,such as adaptive weighted graph filtering(AWGF),focus on coefficient shrinkage str...Graph filtering is an important part of graph signal processing and a useful tool for image denoising.Existing graph filtering methods,such as adaptive weighted graph filtering(AWGF),focus on coefficient shrinkage strategies in a graph-frequency domain.However,they seldom consider the image attributes in their graph-filtering procedure.Consequently,the denoising performance of graph filtering is barely comparable with that of other state-of-the-art denoising methods.To fully exploit the image attributes,we propose a guided intra-patch smoothing AWGF(AWGF-GPS)method for single-image denoising.Unlike AWGF,which employs graph topology on patches,AWGF-GPS learns the topology of superpixels by introducing the pixel smoothing attribute of a patch.This operation forces the restored pixels to smoothly evolve in local areas,where both intra-and inter-patch relationships of the image are utilized during patch restoration.Meanwhile,a guided-patch regularizer is incorporated into AWGF-GPS.The guided patch is obtained in advance using a maximum-a-posteriori probability estimator.Because the guided patch is considered as a sketch of a denoised patch,AWGF-GPS can effectively supervise patch restoration during graph filtering to increase the reliability of the denoised patch.Experiments demonstrate that the AWGF-GPS method suitably rebuilds denoising images.It outperforms most state-of-the-art single-image denoising methods and is competitive with certain deep-learning methods.In particular,it has the advantage of managing images with significant noise.展开更多
A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain struc...A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain structure of the ADN power transaction is built and the transaction information is kept in blocks.Secondly,considering the transaction needs between users and power suppliers in ADN,an energy request mechanism is proposed,and the optimization objective function is designed by integrating cost aware requests and storage aware requests.Finally,the particle swarm optimization algorithm is used for multi-objective optimal search to find the power trading scheme with the minimum power purchase cost of users and the maximum power sold by power suppliers.The experimental demonstration of the proposed method based on the experimental platform shows that when the number of participants is no more than 10,the transaction delay time is 0.2 s,and the transaction cost fluctuates at 200,000 yuan,which is better than other comparison methods.展开更多
Inspired by basic circuit connection methods,memristors can also be utilized in the construction of complex discrete chaotic systems.To investigate the dynamical effects of hybrid memristors,we propose two hybrid tri-...Inspired by basic circuit connection methods,memristors can also be utilized in the construction of complex discrete chaotic systems.To investigate the dynamical effects of hybrid memristors,we propose two hybrid tri-memristor hyperchaotic(HTMH)mapping structures based on the hybrid parallel/cascade and cascade/parallel operations,respectively.Taking the HTMH mapping structure with hybrid parallel/cascade operation as an example,this map possesses a spatial invariant set whose stability is closely related to the initial states of the memristors.Dynamics distributions and bifurcation behaviours dependent on the control parameters are explored with numerical tools.Specifically,the memristor initial offset-boosting mechanism is theoretically demonstrated,and memristor initial offset-boosting behaviours are numerically verified.The results clarify that the HTMH map can exhibit hyperchaotic behaviours and extreme multistability with homogeneous coexisting infinite attractors.In addition,an FPGA hardware platform is fabricated to implement the HTMH map and generate pseudorandom numbers(PRNs)with high randomness.Notably,the generated PRNs can be applied in Wasserstein generative adversarial nets(WGANs)to enhance training stability and generation capability.展开更多
In this work, we propose a novel approach that combines a bidirectional deep neural network(BDNN) with a multifunctional metasurface absorber(MMA) for inverse design, which can effectively address the challenge of on-...In this work, we propose a novel approach that combines a bidirectional deep neural network(BDNN) with a multifunctional metasurface absorber(MMA) for inverse design, which can effectively address the challenge of on-demand customization for absorbers. The inverse design of absorption peak frequencies can be achieved from 0.5 to 10 terahertz(THz), covering the quasi-entire THz band. Based on this, the BDNN is extended to broadband absorption, and the inverse design yields an MMA at the desired frequency. This work provides a broadly applicable approach to the custom design of multifunctional devices that can facilitate the evaluation and design of metasurfaces in electromagnetic absorption.展开更多
Bursting is a diverse and common phenomenon in neuronal activation patterns and it indicates that fast action voltage spiking periods are followed by resting periods.The interspike interval(ISI)is the time between suc...Bursting is a diverse and common phenomenon in neuronal activation patterns and it indicates that fast action voltage spiking periods are followed by resting periods.The interspike interval(ISI)is the time between successive action voltage spikes of neuron and it is a key indicator used to characterize the bursting.Recently,a three-dimensional memristive Hindmarsh-Rose(mHR)neuron model was constructed to generate hidden chaotic bursting.However,the properties of the discrete mHR neuron model have not been investigated,yet.In this article,we first construct a discrete mHR neuron model and then acquire different hidden chaotic bursting sequences under four typical sets of parameters.To make these sequences more suitable for the application,we further encode these hidden chaotic sequences using their ISIs and the performance comparative results show that the ISI-encoded chaotic sequences have much more complex chaos properties than the original sequences.In addition,we apply these ISI-encoded chaotic sequences to the application of image encryption.The image encryption scheme has a symmetric key structure and contains plain-text permutation and bidirectional diffusion processes.Experimental results and security analyses prove that it has excellent robustness against various possible attacks.展开更多
It has been documented that a cyclic three-neuron-based neural network with resistive synaptic weights cannot exhibit chaos.Towards this end,a memristive cyclic three-neuron-based neural network is presented using a m...It has been documented that a cyclic three-neuron-based neural network with resistive synaptic weights cannot exhibit chaos.Towards this end,a memristive cyclic three-neuron-based neural network is presented using a memristive weight to substitute a resistive weight.The memristive cyclic neural network always has five equilibrium points within the parameters of interest,and their stability analysis shows that they are one index-2 saddle-focus,two index-1 saddle-foci,and two stable node-foci,respectively.Dynamical analyses are performed for the memristive cyclic neural network by several numerical simulation methods.The results demonstrate that the memristor synapse-based neural network with the simplest cyclic connection can not only exhibit chaos,but also present global coexisting attractors composed of stable points and unstable periodic or chaotic orbits under different initial conditions.Besides,with the designed implementation circuit,Multisim circuit simulations and hardware experiments are executed to validate the numerical simulations.展开更多
Electromagnetic induction effect caused by neuron potential can be mimicked using memristor.This paper considers a fluxcontrolled memristor to imitate the electromagnetic induction effect of adapting feedback synapse ...Electromagnetic induction effect caused by neuron potential can be mimicked using memristor.This paper considers a fluxcontrolled memristor to imitate the electromagnetic induction effect of adapting feedback synapse and presents a memristive neuron model with the adapting synapse.The memristive neuron model is three-dimensional and non-autonomous.It has the time-varying equilibria with multiple stabilities,which results in the global coexistence of multiple firing patterns.Multiple numerical plots are executed to uncover diverse coexisting firing patterns in the memristive neuron model.Particularly,a nonlinear fitting scheme is raised and a fitting activation function circuit is employed to implement the memristive mono-neuron model.Diverse coexisting firing patterns are observed from the hardware experiment circuit and the measured results verify the numerical simulations well.展开更多
Extreme multistability has seized scientists’ attention due to its rich diversity of dynamical behaviors and great flexibility in engineering applications. In this paper, a four-dimensional(4D) memcapacitive oscillat...Extreme multistability has seized scientists’ attention due to its rich diversity of dynamical behaviors and great flexibility in engineering applications. In this paper, a four-dimensional(4D) memcapacitive oscillator is built using four linear circuit elements and one nonlinear charge-controlled memcapacitor with a cosine inverse memcapacitance. The 4D memcapacitive oscillator possesses a line equilibrium set, and its stability periodically evolves with the initial condition of the memcapacitor. The 4D memcapacitive oscillator exhibits initial-condition-switched boosting extreme multistability due to the periodically evolving stability. Complex dynamical behaviors of period doubling/halving bifurcations, chaos crisis, and initial-condition-switched coexisting attractors are revealed by bifurcation diagrams, Lyapunov exponents, and phase portraits. Thereafter, a reconstructed system is derived via integral transformation to reveal the forming mechanism of the initial-condition-switched boosting extreme multistability in the memcapacitive oscillator. Finally, an implementation circuit is designed for the reconstructed system, and Power SIMulation(PSIM) simulations are executed to confirm the validity of the numerical analysis.展开更多
Human nervous system,which is composed of neuron and synapse networks,is capable of processing information in a plastic,dataparallel,fault-tolerant,and energy-efficient approach.Inspired by the ingenious working mecha...Human nervous system,which is composed of neuron and synapse networks,is capable of processing information in a plastic,dataparallel,fault-tolerant,and energy-efficient approach.Inspired by the ingenious working mechanism of this miraculous biological data processing system,scientists have been devoting great efforts to ar-tificial neural systems based on synaptic devices in recent decades.The continuous development of bioinspired sensors and synaptic devices in recent years have made it possible that artificial sensory neural systems are capable of capturing and processing stimuli informa-tion in real time.The progress of biomimetic sensory neural systems could provide new methods for next-generation humanoid robotics,human-machine interfaces,and other frontier applications.Herein,this review summarized the recent progress of synaptic devices and biomimetic sensory neural systems.Additionally,the opportunities and remaining challenges in the further development of biomimetic sensory neural systems were also outlined.展开更多
The steering vectors estimated by the existing beamforming methods generally depart from their ground-truth values when they are inffuenced by both steering deviation and random error. To solve this problem, a steerin...The steering vectors estimated by the existing beamforming methods generally depart from their ground-truth values when they are inffuenced by both steering deviation and random error. To solve this problem, a steering vector random error modification robust beamforming method is proposed. The steering vector is divided into both inside and outside parts of the pre-defined sector feature subspace, and then the robust beamforming for steering deviation is employed to estimate the component of the steering vector inside the pre-defined sector feature subspace. After that, the uncertainty set constraint is further added to estimate the component of the steering vector outside the pre-defined observation subspace, which then brings high accuracy in steering vector estimation. Simulation results indicate that the proposed method possesses a more stable signal-to-interference-plus-noise ratio and higher steering vector estimation accuracy than the existing robust beamforming methods under both steering deviation and random error. Additionally, the peak of the steering vector beam response is an unbiased estimation of the target direction. Furthermore, sea–trial results illustrate the outstanding robustness of the proposed method in low signal-to-noise-ratio conditions.展开更多
Metal halide perovskite materials have rapidly advanced in the perovskite solar cells and lightemitting diodes due to their superior optoelectronic properties.The structure of perovskite optoelectronic devices include...Metal halide perovskite materials have rapidly advanced in the perovskite solar cells and lightemitting diodes due to their superior optoelectronic properties.The structure of perovskite optoelectronic devices includes the perovskite active layer,electron transport layer,and hole transport layer.This indicates that the optimization process unfolds as a complex interplay between intricate chemical crystallization processes and sophisticated physical mechanisms.Traditional research in perovskite optoelectronics has mainly depended on trial-and-error experimentation,a less efficient approach.Recently,the emergence of machine learning(ML)has drastically streamlined the optimization process.Due to its powerful data processing capabilities,ML has significant advantages in uncovering potential patterns and making predictions.More importantly,ML can reveal underlying patterns in data and elucidate complex device mechanisms,playing a pivotal role in enhancing device performance.We present the latest advancements in applying ML to perovskite optoelectronic devices,covering perovskite active layers,transport layers,interface engineering,and mechanisms.In addition,it offers a prospective outlook on future developments.We believe that the deep integration of ML will significantly expedite the comprehensive enhancement of perovskite optoelectronic device performance.展开更多
基金support from Natural Science Foundation of Jiangsu Province (grant number BK20211507)National Natural Science Foundation of China (grant number 61774080)the start-up funds from Changzhou University。
文摘The increasing demands of multifunctional organic electronics require advanced organic semiconducting materials to be developed and significant improvements to be made to device performance. Thus, it is necessary to gain an in-depth understanding of the film growth process, electronic states, and dynamic structure-property relationship under realistic operation conditions, which can be obtained by in-situ/operando characterization techniques for organic devices. Here, the up-todate developments in the in-situ/operando optical, scanning probe microscopy, and spectroscopy techniques that are employed for studies of film morphological evolution, crystal structures, semiconductor-electrolyte interface properties, and charge carrier dynamics are described and summarized. These advanced technologies leverage the traditional static characterizations into an in-situ and interactive manipulation of organic semiconducting films and devices without sacrificing the resolution, which facilitates the exploration of the intrinsic structure-property relationship of organic materials and the optimization of organic devices for advanced applications.
基金supported by the National Natural Science Foundation of China (No.51877013),(ZJ),(http://www.nsfc.gov.cn/)the Jiangsu Provincial Key Research and Development Program (No.BE2021636),(ZJ),(http://kxjst.jiangsu.gov.cn/)+1 种基金the Science and Technology Project of Changzhou City (No.CE20205056),(ZJ),(http://kjj.changzhou.gov.cn/)by Qing Lan Project of Jiangsu Province (no specific grant number),(ZJ),(http://jyt.jiangsu.gov.cn/).
文摘The structure and function of brain networks have been altered in patients with end-stage renal disease(ESRD).Manifold regularization(MR)only considers the pairing relationship between two brain regions and cannot represent functional interactions or higher-order relationships between multiple brain regions.To solve this issue,we developed a method to construct a dynamic brain functional network(DBFN)based on dynamic hypergraph MR(DHMR)and applied it to the classification of ESRD associated with mild cognitive impairment(ESRDaMCI).The construction of DBFN with Pearson’s correlation(PC)was transformed into an optimization model.Node convolution and hyperedge convolution superposition were adopted to dynamically modify the hypergraph structure,and then got the dynamic hypergraph to form the manifold regular terms of the dynamic hypergraph.The DHMR and L_(1) norm regularization were introduced into the PC-based optimization model to obtain the final DHMR-based DBFN(DDBFN).Experiment results demonstrated the validity of the DDBFN method by comparing the classification results with several related brain functional network construction methods.Our work not only improves better classification performance but also reveals the discriminative regions of ESRDaMCI,providing a reference for clinical research and auxiliary diagnosis of concomitant cognitive impairments.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61775130 and 11974236)the Science and Technology Commission of Shanghai Municipality Program,China(Grant Nos.19DZ2281000 and 17DZ2281000)the Research Innovation Program for College Graduates of Jiangsu Province,China(Grant Nos.KYCX202545 and KYCX202549)。
文摘Organic light-emitting diode(OLED)is an electroluminescent technology that relies on charge-carrier dynamics and is a potential light source for variable environmental conditions.Here,by exploiting a self-developed low-temperature testing system,we investigated the characteristics of hole/electron transport,electro-optic conversion efficiency,and operation lifetime of OLEDs at low-temperature ranging from-40℃to 0℃and room temperature(25℃).Compared to devices operating at room temperature,the carrier transport capability is significantly decreased with reducing temperature,and especially the mobility of the hole-transporting material(HTM)and electron-transporting material(ETM)at-40℃decreases from 1.16×10-6 cm2/V·s and 2.60×10-4 cm2/V·s to 6.91×10-9 cm2/V·s and 1.44×10-5 cm2/V·s,respectively.Indeed,the temperature affects differently on the mobilities of HTM and ETM,which favors unbalanced charge-carrier transport and recombination in OLEDs,thereby leading to the maximum current efficiency decreased from 6.46 cd·A-1 at 25℃to 2.74 cd·A-1 at-40℃.In addition,blue fluorescent OLED at-20℃has an above 56%lifetime improvement(time to 80%of the initial luminance)over the reference device at room temperature,which is attributed to efficiently dissipating heat generated inside the device by the low-temperature environment.
基金the National Natural Science Foundation of China(Grant No.62206030)the Natural Science Foundation of Jiangsu(Grant Nos.BK20220624 and BK20220620)+2 种基金the Scientific Research Foundation of Jiangsu Provincial Education Department(Grant No.21KJB510010)the Changzhou Sci&Tech Program(Grant No.CJ20220085)the Leading Innovative Talents Introduction and Cultivation Project of Changzhou(Grant No.CQ20210084)。
文摘We fabricated monolayer n-type two-dimensional crystalline semiconducting films with millimeter-sized areas and remarkable morphological uniformity using an antisolvent-confined spin-coating method.The antisolvent can cause a downstream Marangoni flow,which improves the film morphologies.The deposited crystalline monolayer films exhibit excellent thermal stabilities after annealing,which reveals the annealing-induced enhancement of crystallinity.The transistors based on the n-type monolayer crystalline films show linear output characteristics and superior electron mobilities.The improved charge injection between monolayer films and Au electrodes results from the energy level shift as the films decrease to the monolayer,which leads to a lower injection barrier.This work demonstrates a promising method for fabricating air-stable,low-cost,high-performance,and large-area organic electronics.
基金supported by The Agricultural Science and Technology Independent Innovation Fund Project of Jiangsu Province(CX(22)3111)the National Natural Science Foundation of China Project(62173162)partly by the Changzhou Science and Technology Support Project(CE20225016).
文摘Real-time detection of unhealthy fish remains a significant challenge in intensive recirculating aquaculture.Early recognition of unhealthy fish and the implementation of appropriate treatment measures are crucial for preventing the spread of diseases and minimizing economic losses.To address this issue,an improved algorithm based on the You Only Look Once v5s(YOLOv5s)lightweight model has been proposed.This enhanced model incorporates a faster lightweight structure and a new Convolutional Block Attention Module(CBAM)to achieve high recognition accuracy.Furthermore,the model introduces theα-SIoU loss function,which combines theα-Intersection over Union(α-IoU)and Shape Intersection over Union(SIoU)loss functions,thereby improving the accuracy of bounding box regression and object recognition.The average precision of the improved model reaches 94.2%for detecting unhealthy fish,representing increases of 11.3%,9.9%,9.7%,2.5%,and 2.1%compared to YOLOv3-tiny,YOLOv4,YOLOv5s,GhostNet-YOLOv5,and YOLOv7,respectively.Additionally,the improved model positively impacts hardware efficiency,reducing requirements for memory size by 59.0%,67.0%,63.0%,44.7%,and 55.6%in comparison to the five models mentioned above.The experimental results underscore the effectiveness of these approaches in addressing the challenges associated with fish health detection,and highlighting their significant practical implications and broad application prospects.
基金support from the National Natural Science Foundation of China(Nos.51606158,11604311,and 12074151)Sichuan Science and Technology Program(No.2021JDRC0022)+3 种基金Natural Science Foundation of Fujian Province(No.2021J05202)Research Project of Fashu Foundation(No.MFK23006)Open Fund of the Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education in Wuhan University of Science and Technology(No.MECOF2022B01)the project supported by Guangxi Key Laboratory of Precision Navigation Technology and Application,Guilin University of Electronic Technology(No.DH202321).
文摘The field of terahertz devices is important in terahertz technology.However,most of the current devices have limited functionality and poor performance.To improve device performance and achieve multifunctionality,we designed a terahertz device based on a combination of VO_(2)and metamaterials.This device can be tuned using the phase-transition characteristics of VO_(2),which is included in the triple-layer structure of the device,along with SiO_(2)and Au.The terahertz device exhibits various advantageous features,including broadband coverage,high absorption capability,dynamic tunability,simple structural design,polarization insensitivity,and incidentangle insensitivity.The simulation results showed that by controlling the temperature,the terahertz device achieved a thermal modulation range of spectral absorption from 0 to 0.99.At 313 K,the device exhibited complete reflection of terahertz waves.As the temperature increased,the absorption rate also increased.When the temperature reached 353 K,the device absorption rate exceeded 97.7%in the range of 5-8.55 THz.This study used the effective medium theory to elucidate the correlation between conductivity and temperature during the phase transition of VO_(2).Simultaneously,the variation in device performance was further elucidated by analyzing and depicting the intensity distribution of the electric field on the device surface at different temperatures.Furthermore,the impact of various structural parameters on device performance was examined,offering valuable insights and suggestions for selecting suitable parameter values in real-world applications.These characteristics render the device highly promising for applications in stealth technology,energy harvesting,modulation,and other related fields,thus showcasing its significant potential.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12172066,61801054,and 51777016)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20160282)the Postgraduate Research and Practice Innovation Program of Jiangsu Province,China(Grant No.KYCX212823)。
文摘Based on the two-dimensional(2D)discrete Rulkov model that is used to describe neuron dynamics,this paper presents a continuous non-autonomous memristive Rulkov model.The effects of electromagnetic induction and external stimulus are simultaneously considered herein.The electromagnetic induction flow is imitated by the generated current from a flux-controlled memristor and the external stimulus is injected using a sinusoidal current.Thus,the presented model possesses a line equilibrium set evolving over the time.The equilibrium set and their stability distributions are numerically simulated and qualitatively analyzed.Afterwards,numerical simulations are executed to explore the dynamical behaviors associated to the electromagnetic induction,external stimulus,and initial conditions.Interestingly,the initial conditions dependent extreme multistability is elaborately disclosed in the continuous non-autonomous memristive Rulkov model.Furthermore,an analog circuit of the proposed model is implemented,upon which the hardware experiment is executed to verify the numerically simulated extreme multistability.The extreme multistability is numerically revealed and experimentally confirmed in this paper,which can widen the future engineering employment of the Rulkov model.
基金funding from the Royal Society through a Newton International Fellowship,the Key Research and Development Program of Shaanxi Province(Grant No.2023-YBGY-198)the Doctoral Scientific Research Start-up Foundation of Shaanxi University of Science and Technology(Grant No.126022255)+3 种基金T.X.was supported by the National Natural Science Foundation of China(Grant No.51802184)X.W.was supported by the Shaanxi Province Innovation Capability Support Plan-Youth Science and Technology Nova Project(Grant No.2023KJXX-141)the National Natural Science Foundation of China(Grant No.62004120)F.Z.was supported by the Education Department of Shaanxi Province Serves the Local Special Plan Project(Grant No.17JF006).
文摘Visible light communication(VLC)is an emerging technology employing light-emitting diodes(LEDs)to provide illumination and wireless data transmission simultaneously.Harnessing cost-efficient printable organic LEDs(OLEDs)as environmentally friendly transmitters in VLC systems is extremely attractive for future applications in spectroscopy,the internet of things,sensing,and optical ranging in general.Here,we summarize the latest research progress on emerging semiconductor materials for LED sources in VLC,and highlight that OLEDs based on nontoxic and cost-efficient organic semiconductors have great opportunities for optical communication.We further examine efforts to achieve high-performance white OLEDs for general lighting,and,in particular,focus on the research status and opportunities for OLED-based VLC.Different solution-processable fabrication and printing strategies to develop high-performance OLEDs are also discussed.Finally,an outlook on future challenges and potential prospects of the next-generation organic VLC is provided.
基金support by the National Natural Science Foundation of China(Nos.51606158,11604311,12074151)funding from the Sichuan Science and Technology Program(No.2021JDRC0022)+3 种基金funding from the Natural Science Foundation of Fujian Province(No.2021J05202)funding from the Research Project of Fashu Foundation(No.MFK23006)funding from the Open Fund of the Key Laboratory for Metallurgical Equipment and Control Technology of Ministry of Education in Wuhan University of Science and Technology,China(No.MECOF2022B01)funding by the project supported by Guangxi Key Laboratory of Precision Navigation Technology and Application,Guilin University of Electronic Technology(No.DH202321).
文摘This study introduces an innovative dual-tunable absorption film with the capability to switch between ultra-wideband and narrowband absorption.By manipulating the temperature,the film can achieve multi-band absorption within the 30-45 THz range or ultra-wideband absorption spanning 30-130 THz,with an absorption rate exceeding 0.9.Furthermore,the structural parameters of the absorption film are optimized using the particle swarm optimization(PSO)algorithm to ensure the optimal absorption response.The absorption response of the film is primarily attributed to the coupling of guided-mode resonance and local surface plasmon resonance effects.The film's symmetric structure enables polarization incoherence and allows for tuning through various means such as doping/voltage,temperature and structural parameters.In the case of a multi-band absorption response,the film exhibits good sensitivity to refractive index changes in multiple absorption modes.Additionally,the absorption spectrum of the film remains effective even at large incidence angles,making it highly promising for applications in fields such as biosensing and infrared stealth.
基金This work is supported by Natural Science Foundation of Jiangsu Province,China[BK20170306]National Key R&D Program,China[2017YFC0306100].The initials of authors who received these grants are YZ and JL,respectively.It is also supported by Fundamental Research Funds for Central Universities,China[B200202217]Changzhou Science and Technology Program,China[CJ20200065].The initials of author who received these grants are YT.
文摘Graph filtering is an important part of graph signal processing and a useful tool for image denoising.Existing graph filtering methods,such as adaptive weighted graph filtering(AWGF),focus on coefficient shrinkage strategies in a graph-frequency domain.However,they seldom consider the image attributes in their graph-filtering procedure.Consequently,the denoising performance of graph filtering is barely comparable with that of other state-of-the-art denoising methods.To fully exploit the image attributes,we propose a guided intra-patch smoothing AWGF(AWGF-GPS)method for single-image denoising.Unlike AWGF,which employs graph topology on patches,AWGF-GPS learns the topology of superpixels by introducing the pixel smoothing attribute of a patch.This operation forces the restored pixels to smoothly evolve in local areas,where both intra-and inter-patch relationships of the image are utilized during patch restoration.Meanwhile,a guided-patch regularizer is incorporated into AWGF-GPS.The guided patch is obtained in advance using a maximum-a-posteriori probability estimator.Because the guided patch is considered as a sketch of a denoised patch,AWGF-GPS can effectively supervise patch restoration during graph filtering to increase the reliability of the denoised patch.Experiments demonstrate that the AWGF-GPS method suitably rebuilds denoising images.It outperforms most state-of-the-art single-image denoising methods and is competitive with certain deep-learning methods.In particular,it has the advantage of managing images with significant noise.
基金supported by the Postdoctoral Research Funding Program of Jiangsu Province under Grant 2021K622C.
文摘A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain structure of the ADN power transaction is built and the transaction information is kept in blocks.Secondly,considering the transaction needs between users and power suppliers in ADN,an energy request mechanism is proposed,and the optimization objective function is designed by integrating cost aware requests and storage aware requests.Finally,the particle swarm optimization algorithm is used for multi-objective optimal search to find the power trading scheme with the minimum power purchase cost of users and the maximum power sold by power suppliers.The experimental demonstration of the proposed method based on the experimental platform shows that when the number of participants is no more than 10,the transaction delay time is 0.2 s,and the transaction cost fluctuates at 200,000 yuan,which is better than other comparison methods.
基金supported by the National Natural Science Foundation of China(Grant Nos.62271088,62201094,and 62071142)the Scientific Research Foundation of Jiangsu Provincial Education Department of China(Grant No.22KJB510001)。
文摘Inspired by basic circuit connection methods,memristors can also be utilized in the construction of complex discrete chaotic systems.To investigate the dynamical effects of hybrid memristors,we propose two hybrid tri-memristor hyperchaotic(HTMH)mapping structures based on the hybrid parallel/cascade and cascade/parallel operations,respectively.Taking the HTMH mapping structure with hybrid parallel/cascade operation as an example,this map possesses a spatial invariant set whose stability is closely related to the initial states of the memristors.Dynamics distributions and bifurcation behaviours dependent on the control parameters are explored with numerical tools.Specifically,the memristor initial offset-boosting mechanism is theoretically demonstrated,and memristor initial offset-boosting behaviours are numerically verified.The results clarify that the HTMH map can exhibit hyperchaotic behaviours and extreme multistability with homogeneous coexisting infinite attractors.In addition,an FPGA hardware platform is fabricated to implement the HTMH map and generate pseudorandom numbers(PRNs)with high randomness.Notably,the generated PRNs can be applied in Wasserstein generative adversarial nets(WGANs)to enhance training stability and generation capability.
基金supported by the National Natural Science Foundation of China (No.61705058)。
文摘In this work, we propose a novel approach that combines a bidirectional deep neural network(BDNN) with a multifunctional metasurface absorber(MMA) for inverse design, which can effectively address the challenge of on-demand customization for absorbers. The inverse design of absorption peak frequencies can be achieved from 0.5 to 10 terahertz(THz), covering the quasi-entire THz band. Based on this, the BDNN is extended to broadband absorption, and the inverse design yields an MMA at the desired frequency. This work provides a broadly applicable approach to the custom design of multifunctional devices that can facilitate the evaluation and design of metasurfaces in electromagnetic absorption.
基金supported by the National Natural Science Foundation of China(Grant Nos.51777016,51607013 and 62071142).
文摘Bursting is a diverse and common phenomenon in neuronal activation patterns and it indicates that fast action voltage spiking periods are followed by resting periods.The interspike interval(ISI)is the time between successive action voltage spikes of neuron and it is a key indicator used to characterize the bursting.Recently,a three-dimensional memristive Hindmarsh-Rose(mHR)neuron model was constructed to generate hidden chaotic bursting.However,the properties of the discrete mHR neuron model have not been investigated,yet.In this article,we first construct a discrete mHR neuron model and then acquire different hidden chaotic bursting sequences under four typical sets of parameters.To make these sequences more suitable for the application,we further encode these hidden chaotic sequences using their ISIs and the performance comparative results show that the ISI-encoded chaotic sequences have much more complex chaos properties than the original sequences.In addition,we apply these ISI-encoded chaotic sequences to the application of image encryption.The image encryption scheme has a symmetric key structure and contains plain-text permutation and bidirectional diffusion processes.Experimental results and security analyses prove that it has excellent robustness against various possible attacks.
基金supported by the National Natural Science Foundation of China(Grant Nos.62201094,62271088 and 12172066)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20210850)+1 种基金the Scientific Research Foundation of Jiangsu Provincial Education Department,China(Grant No.22KJB510001)。
文摘It has been documented that a cyclic three-neuron-based neural network with resistive synaptic weights cannot exhibit chaos.Towards this end,a memristive cyclic three-neuron-based neural network is presented using a memristive weight to substitute a resistive weight.The memristive cyclic neural network always has five equilibrium points within the parameters of interest,and their stability analysis shows that they are one index-2 saddle-focus,two index-1 saddle-foci,and two stable node-foci,respectively.Dynamical analyses are performed for the memristive cyclic neural network by several numerical simulation methods.The results demonstrate that the memristor synapse-based neural network with the simplest cyclic connection can not only exhibit chaos,but also present global coexisting attractors composed of stable points and unstable periodic or chaotic orbits under different initial conditions.Besides,with the designed implementation circuit,Multisim circuit simulations and hardware experiments are executed to validate the numerical simulations.
基金supported by the National Natural Science Foundation of China(Grant Nos.51777016 and 61801054)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20191451)。
文摘Electromagnetic induction effect caused by neuron potential can be mimicked using memristor.This paper considers a fluxcontrolled memristor to imitate the electromagnetic induction effect of adapting feedback synapse and presents a memristive neuron model with the adapting synapse.The memristive neuron model is three-dimensional and non-autonomous.It has the time-varying equilibria with multiple stabilities,which results in the global coexistence of multiple firing patterns.Multiple numerical plots are executed to uncover diverse coexisting firing patterns in the memristive neuron model.Particularly,a nonlinear fitting scheme is raised and a fitting activation function circuit is employed to implement the memristive mono-neuron model.Diverse coexisting firing patterns are observed from the hardware experiment circuit and the measured results verify the numerical simulations well.
基金Project supported by the National Natural Science Foundation of China (Nos. 51777016 and 61801054)the Natural Science Foundation of Jiangsu Province,China (No. BK20191451)+2 种基金the Natural Science Foundation of Changzhou,Jiangsu Province,China (No. CJ20190037)the Open Research Fund of Key Laboratory of MEMS of Ministry of EducationSoutheast University,China。
文摘Extreme multistability has seized scientists’ attention due to its rich diversity of dynamical behaviors and great flexibility in engineering applications. In this paper, a four-dimensional(4D) memcapacitive oscillator is built using four linear circuit elements and one nonlinear charge-controlled memcapacitor with a cosine inverse memcapacitance. The 4D memcapacitive oscillator possesses a line equilibrium set, and its stability periodically evolves with the initial condition of the memcapacitor. The 4D memcapacitive oscillator exhibits initial-condition-switched boosting extreme multistability due to the periodically evolving stability. Complex dynamical behaviors of period doubling/halving bifurcations, chaos crisis, and initial-condition-switched coexisting attractors are revealed by bifurcation diagrams, Lyapunov exponents, and phase portraits. Thereafter, a reconstructed system is derived via integral transformation to reveal the forming mechanism of the initial-condition-switched boosting extreme multistability in the memcapacitive oscillator. Finally, an implementation circuit is designed for the reconstructed system, and Power SIMulation(PSIM) simulations are executed to confirm the validity of the numerical analysis.
基金This work was supported by the National Key Research and Development Program of China(2021YFA1401103)the National Natu-ral Science Foundation of China(61825403,61921005,and 61674078)the Priority Academic Program Development of Jiangsu Higher Education Insti-tutions.The Postgraduate Research&Innovation Program of Jiangsu Province(KYCX21_0049 to J.-H.Z.).
文摘Human nervous system,which is composed of neuron and synapse networks,is capable of processing information in a plastic,dataparallel,fault-tolerant,and energy-efficient approach.Inspired by the ingenious working mechanism of this miraculous biological data processing system,scientists have been devoting great efforts to ar-tificial neural systems based on synaptic devices in recent decades.The continuous development of bioinspired sensors and synaptic devices in recent years have made it possible that artificial sensory neural systems are capable of capturing and processing stimuli informa-tion in real time.The progress of biomimetic sensory neural systems could provide new methods for next-generation humanoid robotics,human-machine interfaces,and other frontier applications.Herein,this review summarized the recent progress of synaptic devices and biomimetic sensory neural systems.Additionally,the opportunities and remaining challenges in the further development of biomimetic sensory neural systems were also outlined.
文摘The steering vectors estimated by the existing beamforming methods generally depart from their ground-truth values when they are inffuenced by both steering deviation and random error. To solve this problem, a steering vector random error modification robust beamforming method is proposed. The steering vector is divided into both inside and outside parts of the pre-defined sector feature subspace, and then the robust beamforming for steering deviation is employed to estimate the component of the steering vector inside the pre-defined sector feature subspace. After that, the uncertainty set constraint is further added to estimate the component of the steering vector outside the pre-defined observation subspace, which then brings high accuracy in steering vector estimation. Simulation results indicate that the proposed method possesses a more stable signal-to-interference-plus-noise ratio and higher steering vector estimation accuracy than the existing robust beamforming methods under both steering deviation and random error. Additionally, the peak of the steering vector beam response is an unbiased estimation of the target direction. Furthermore, sea–trial results illustrate the outstanding robustness of the proposed method in low signal-to-noise-ratio conditions.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFA1204800)the National Natural Science Foundation of China(Grant Nos.62288102,52373220,62375124,62134007,and 52233011).
文摘Metal halide perovskite materials have rapidly advanced in the perovskite solar cells and lightemitting diodes due to their superior optoelectronic properties.The structure of perovskite optoelectronic devices includes the perovskite active layer,electron transport layer,and hole transport layer.This indicates that the optimization process unfolds as a complex interplay between intricate chemical crystallization processes and sophisticated physical mechanisms.Traditional research in perovskite optoelectronics has mainly depended on trial-and-error experimentation,a less efficient approach.Recently,the emergence of machine learning(ML)has drastically streamlined the optimization process.Due to its powerful data processing capabilities,ML has significant advantages in uncovering potential patterns and making predictions.More importantly,ML can reveal underlying patterns in data and elucidate complex device mechanisms,playing a pivotal role in enhancing device performance.We present the latest advancements in applying ML to perovskite optoelectronic devices,covering perovskite active layers,transport layers,interface engineering,and mechanisms.In addition,it offers a prospective outlook on future developments.We believe that the deep integration of ML will significantly expedite the comprehensive enhancement of perovskite optoelectronic device performance.
