Astrocytes,the main population of glial cells in the central nervous system(CNS),exert essential tasks for the control of brain tissue homeostasis,supporting neuron and other glial cell activity from the developmental...Astrocytes,the main population of glial cells in the central nervous system(CNS),exert essential tasks for the control of brain tissue homeostasis,supporting neuron and other glial cell activity from the developmental stage to adult life.To maintain the optimal functionality of the brain,astroglial cells are particularly committed to reacting to every change in tissue homeostatic conditions,from mild modifications of the physiological environment,a process called astrocyte activation,to the more severe alterations occurring in pathological situations causing astrocyte reactivity or reactive astrogliosis(Escartin et al.,2021).During these reactive states,astrocytes mount an active,progressive response encompassing morphological,molecular,and interactional remodeling,leading to the acquisition of new functions and the loss of others,whose intensity,duration,and reversibility are dependent on the nature of the stimulus and regulated in a context-specific manner.展开更多
El Niño-Southern Oscillation(ENSO)is a major driver of climate change in middle and low latitudes and thus strongly influences the terrestrial carbon cycle through land-air interaction.Both the ENSO modulation an...El Niño-Southern Oscillation(ENSO)is a major driver of climate change in middle and low latitudes and thus strongly influences the terrestrial carbon cycle through land-air interaction.Both the ENSO modulation and carbon flux variability are projected to increase in the future,but their connection still needs further investigation.To investigate the impact of future ENSO modulation on carbon flux variability,this study used 10 CMIP6 earth system models to analyze ENSO modulation and carbon flux variability in middle and low latitudes,and their relationship,under different scenarios simulated by CMIP6 models.The results show a high consistency in the simulations,with both ENSO modulation and carbon flux variability showing an increasing trend in the future.The higher the emissions scenario,especially SSP5-8.5 compared to SSP2-4.5,the greater the increase in variability.Carbon flux variability in the middle and low latitudes under SSP2-4.5 increases by 30.9%compared to historical levels during 1951-2000,while under SSP5-8.5 it increases by 58.2%.Further analysis suggests that ENSO influences mid-and low-latitude carbon flux variability primarily through temperature.This occurrence may potentially be attributed to the increased responsiveness of gross primary productivity towards regional temperature fluctuations,combined with the intensified influence of ENSO on land surface temperatures.展开更多
Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the p...Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.展开更多
This paper investigates the bit-interleaved coded generalized spatial modulation(BICGSM) with iterative decoding(BICGSM-ID) for multiple-input multiple-output(MIMO) visible light communications(VLC). In the BICGSM-ID ...This paper investigates the bit-interleaved coded generalized spatial modulation(BICGSM) with iterative decoding(BICGSM-ID) for multiple-input multiple-output(MIMO) visible light communications(VLC). In the BICGSM-ID scheme, the information bits conveyed by the signal-domain(SiD) symbols and the spatial-domain(SpD) light emitting diode(LED)-index patterns are coded by a protograph low-density parity-check(P-LDPC) code. Specifically, we propose a signal-domain symbol expanding and re-allocating(SSER) method for constructing a type of novel generalized spatial modulation(GSM) constellations, referred to as SSERGSM constellations, so as to boost the performance of the BICGSM-ID MIMO-VLC systems.Moreover, by applying a modified PEXIT(MPEXIT) algorithm, we further design a family of rate-compatible P-LDPC codes, referred to as enhanced accumulate-repeat-accumulate(EARA) codes,which possess both excellent decoding thresholds and linear-minimum-distance-growth property. Both analysis and simulation results illustrate that the proposed SSERGSM constellations and P-LDPC codes can remarkably improve the convergence and decoding performance of MIMO-VLC systems. Therefore, the proposed P-LDPC-coded SSERGSM-mapped BICGSMID configuration is envisioned as a promising transmission solution to satisfy the high-throughput requirement of MIMO-VLC applications.展开更多
The clinical application of magnesium(Mg)and its alloys for bone fractures has been well supported by in vitro and in vivo trials.However,there were studies indicating negative effects of high dose Mg intake and susta...The clinical application of magnesium(Mg)and its alloys for bone fractures has been well supported by in vitro and in vivo trials.However,there were studies indicating negative effects of high dose Mg intake and sustained local release of Mg ions on bone metabolism or repair,which should not be ignored when developing Mg-based implants.Thus,it remains necessary to assess the biological effects of Mg implants in animal models relevant to clinical treatment modalities.The primary purpose of this study was to validate the beneficial effects of intramedullary Mg implants on the healing outcome of femoral fractures in a modified rat model.In addition,the mineralization parameters at multiple anatomical sites were evaluated,to investigate their association with healing outcome and potential clinical applications.Compared to the control group without Mg implantation,postoperative imaging at week 12 demonstrated better healing outcomes in the Mg group,with more stable unions in 3D analysis and high-mineralized bridging in 2D evaluation.The bone tissue mineral density(TMD)was higher in the Mg group at the non-operated femur and lumbar vertebra,while no differences between groups were identified regarding the bone tissue volume(TV),TMD and bone mineral content(BMC)in humerus.In the surgical femur,the Mg group presented higher TMD,but lower TV and BMC in the distal metaphyseal region,as well as reduced BMC at the osteotomy site.Principal component analysis(PCA)-based machine learning revealed that by selecting clinically relevant parameters,radiological markers could be constructed for differentiation of healing outcomes,with better performance than 2D scoring.The study provides insights and preclinical evidence for the rational investigation of bioactive materials,the identification of potential adverse effects,and the promotion of diagnostic capabilities for fracture healing.展开更多
Two-terminal(2-T)perovskite(PVK)/CuIn(Ga)Se_(2)(CIGS)tandem solar cells(TSCs)have been considered as an ideal tandem cell because of their best bandgap matching regarding to Shockley–Queisser(S–Q)limits.However,the ...Two-terminal(2-T)perovskite(PVK)/CuIn(Ga)Se_(2)(CIGS)tandem solar cells(TSCs)have been considered as an ideal tandem cell because of their best bandgap matching regarding to Shockley–Queisser(S–Q)limits.However,the nature of the irregular rough morphology of commercial CIGS prevents people from improving tandem device performances.In this paper,D-homoserine lactone hydrochloride is proven to improve coverage of PVK materials on irregular rough CIGS surfaces and also passivate bulk defects by modulating the growth of PVK crystals.In addition,the minority carriers near the PVK/C60 interface and the incompletely passivated trap states caused interface recombination.A surface reconstruction with 2-thiopheneethylammonium iodide and N,N-dimethylformamide assisted passivates the defect sites located at the surface and grain boundaries.Meanwhile,LiF is used to create this field effect,repelling hole carriers away from the PVK and C60 interface and thus reducing recombination.As a result,a 2-T PVK/CIGS tandem yielded a power conversion efficiency of 24.6%(0.16 cm^(2)),one of the highest results for 2-T PVK/CIGS TSCs to our knowledge.This validation underscores the potential of our methodology in achieving superior performance in PVK/CIGS tandem solar cells.展开更多
Enhancing both the number of active sites available and the intrinsic activity of Co-based electrocatalysts simultaneously is a desirable goal.Herein,a ZIF-67-derived hierarchical porous cobalt sulfide decorated by Au...Enhancing both the number of active sites available and the intrinsic activity of Co-based electrocatalysts simultaneously is a desirable goal.Herein,a ZIF-67-derived hierarchical porous cobalt sulfide decorated by Au nanoparticles(NPs)(denoted as HP-Au@CoxSy@ZIF-67)hybrid is synthesized by low-temperature sulfuration treatment.The well-defined macroporous-mesoporous-microporous structure is obtained based on the combination of polystyrene spheres,as-formed CoxSy nanosheets,and ZIF-67 frameworks.This novel three-dimensional hierarchical structure significantly enlarges the three-phase interfaces,accelerating the mass transfer and exposing the active centers for oxygen evolution reaction.The electronic structure of Co is modulated by Au through charge transfer,and a series of experiments,together with theoretical analysis,is performed to ascertain the electronic modulation of Co by Au.Meanwhile,HP-Au@CoxSy@ZIF-67 catalysts with different amounts of Au were synthesized,wherein Au and NaBH4 reductant result in an interesting“competition effect”to regulate the relative ratio of Co^(2+)/Co^(3+),and moderate Au assists the electrochemical performance to reach the highest value.Consequently,the optimized HP-Au@CoxSy@ZIF-67 exhibits a low overpotential of 340 mV at 10 mA cm^(-2)and a Tafel slope of 42 mV dec-1 for OER in 0.1 M aqueous KOH,enabling efficient water splitting and Zn-air battery performance.The work here highlights the pivotal roles of both microstructural and electronic modulation in enhancing electrocatalytic activity and presents a feasible strategy for designing and optimizing advanced electrocatalysts.展开更多
The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-n...The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.展开更多
In recent years,notable progress has been achieved in both the hardware and algorithms of structured illumination microscopy(SIM).Nevertheless,the advancement of three-dimensional structured illumination microscopy(3D...In recent years,notable progress has been achieved in both the hardware and algorithms of structured illumination microscopy(SIM).Nevertheless,the advancement of three-dimensional structured illumination microscopy(3DSIM)has been impeded by challenges arising from the speed and intricacy of polarization modulation.We introduce a high-speed modulation 3DSIM system,leveraging the polarizationmaintaining and modulation capabilities of a digital micromirror device(DMD)in conjunction with an electrooptic modulator.The DMD-3DSIM system yields a twofold enhancement in both lateral(133 nm)and axial(300 nm)resolution compared to wide-field imaging and can acquire a data set comprising 29 sections of 1024 pixels×1024 pixels,with 15 ms exposure time and 6.75 s per volume.The versatility of the DMD-3DSIM approach was exemplified through the imaging of various specimens,including fluorescent beads,nuclear pores,microtubules,actin filaments,and mitochondria within cells,as well as plant and animal tissues.Notably,polarized 3DSIM elucidated the orientation of actin filaments.Furthermore,the implementation of diverse deconvolution algorithms further enhances 3D resolution.The DMD-based 3DSIM system presents a rapid and reliable methodology for investigating biomedical phenomena,boasting capabilities encompassing 3D superresolution,fast temporal resolution,and polarization imaging.展开更多
Emission of matter-wave jets from a parametrically driven condensate has attracted significant experimental and theoretical attention due to the appealing visual effects and potential metrological applications.In this...Emission of matter-wave jets from a parametrically driven condensate has attracted significant experimental and theoretical attention due to the appealing visual effects and potential metrological applications.In this work,we investigate the collective particle emission from a Bose-Einstein condensate confined in a one-dimensional lattice with periodically modulated interparticle interactions.We give the regimes for discrete modes,and find that the emission can be distinctly suppressed.The configuration induces a broad band,but few particles are ejected due to the interference of the matter waves.We further qualitatively model the emission process and demonstrate the short-time behaviors.This engineering provides a way to manipulate the propagation of particles and the corresponding dynamics of condensates in lattices,and may find application in the dynamical excitation control of other nonequilibrium problems with time-periodic driving.展开更多
Plasmonic modes within metal nanostructures play a pivotal role in various nanophotonic applications.However,a significant challenge arises from the fixed shapes of nanostructures post-fabrication,resulting in limited...Plasmonic modes within metal nanostructures play a pivotal role in various nanophotonic applications.However,a significant challenge arises from the fixed shapes of nanostructures post-fabrication,resulting in limited modes under ordinary illumination.A promising solution lies in far-field control facilitated by spatial light modulators(SLMs),which enable on-site,real-time,and non-destructive manipulation of plasmon excitation.Through the robust modulation of the incident light using SLMs,this approach enables the generation,optimization,and dynamic control of surface plasmon polariton(SPP)and localized surface plasmon(LSP)modes.The versatility of this technique introduces a rich array of tunable degrees of freedom to plasmon-enhanced spectroscopy,offering novel approaches for signal optimization and functional expansion in this field.This paper provides a comprehensive review of the generation and modulation of SPP and LSP modes through far-field control with SLMs and highlights the diverse applications of this optical technology in plasmon-enhanced spectroscopy.展开更多
In order to avoid the complexity of Gaussian modulation and the problem that the traditional point-to-point communication DM-CVQKD protocol cannot meet the demand for multi-user key sharing at the same time, we propos...In order to avoid the complexity of Gaussian modulation and the problem that the traditional point-to-point communication DM-CVQKD protocol cannot meet the demand for multi-user key sharing at the same time, we propose a multi-ring discrete modulation continuous variable quantum key sharing scheme(MR-DM-CVQSS). In this paper, we primarily compare single-ring and multi-ring M-symbol amplitude and phase-shift keying modulations. We analyze their asymptotic key rates against collective attacks and consider the security key rates under finite-size effects. Leveraging the characteristics of discrete modulation, we improve the quantum secret sharing scheme. Non-dealer participants only require simple phase shifters to complete quantum secret sharing. We also provide the general design of the MR-DM-CVQSS protocol.We conduct a comprehensive analysis of the improved protocol's performance, confirming that the enhancement through multi-ring M-PSK allows for longer-distance quantum key distribution. Additionally, it reduces the deployment complexity of the system, thereby increasing the practical value.展开更多
With the successive application of deep learning(DL)in classification tasks,the DL-based modulation classification method has become the preference for its state-of-the-art performance.Nevertheless,once the DL recogni...With the successive application of deep learning(DL)in classification tasks,the DL-based modulation classification method has become the preference for its state-of-the-art performance.Nevertheless,once the DL recognition model is pre-trained with fixed classes,the pre-trained model tends to predict incorrect results when identifying incremental classes.Moreover,the incremental classes are usually emergent without label information or only a few labeled samples of incremental classes can be obtained.In this context,we propose a graphbased semi-supervised approach to address the fewshot classes-incremental(FSCI)modulation classification problem.Our proposed method is a twostage learning method,specifically,a warm-up model is trained for classifying old classes and incremental classes,where the unlabeled samples of incremental classes are uniformly labeled with the same label to alleviate the damage of the class imbalance problem.Then the warm-up model is regarded as a feature extractor for constructing a similar graph to connect labeled samples and unlabeled samples,and the label propagation algorithm is adopted to propagate the label information from labeled nodes to unlabeled nodes in the graph to achieve the purpose of incremental classes recognition.Simulation results prove that the proposed method is superior to other finetuning methods and retrain methods.展开更多
Controlling the local electronic structure of active ingredients to improve the adsorption desorption characteristics of oxygen-containing intermediates over the electrochemical liquid-solid interfaces is a critical c...Controlling the local electronic structure of active ingredients to improve the adsorption desorption characteristics of oxygen-containing intermediates over the electrochemical liquid-solid interfaces is a critical challenge in the field of oxygen reduction reaction(ORR)catalysis.Here,we offer a simple approach for modulating the electronic states of metal nanocrystals by bimetal co-doping into carbon-nitrogen substrate,allowing us to modulate the electronic structure of catalytic active centers.To test our strategy,we designed a typical bimetallic nanoparticle catalyst(Fe-Co NP/NC)to flexibly alter the reaction kinetics of ORR.Our results from synchrotron Xray absorption spectroscopy and X-ray photoelectron spectroscopy showed that the co-doping of iron and cobalt could optimize the intrinsic charge distribution of Fe-Co NP/NC catalyst,promoting the oxygen reduction kinetics and ultimately achieving remarkable ORR activity.Consequently,the carefully designed Fe-Co NP/NC exhibits an ultra-high kinetic current density at the operating voltage(71.94 mA/cm^(2)at 0.80 V),and the half-wave potential achieves 0.915 V,which is obviously better than that of the corresponding controls including Fe NP/NC,Co NP/NC.Our findings provide a unique perspective for optimizing the electronic structure of active centers to achieve higher ORR catalytic activity and faster kinetics.展开更多
In view of low recognition rate of complex radar intra-pulse modulation signal type by traditional methods under low signal-to-noise ratio(SNR),the paper proposes an automatic recog-nition method of complex radar intr...In view of low recognition rate of complex radar intra-pulse modulation signal type by traditional methods under low signal-to-noise ratio(SNR),the paper proposes an automatic recog-nition method of complex radar intra-pulse modulation signal type based on deep residual network.The basic principle of the recognition method is to obtain the transformation relationship between the time and frequency of complex radar intra-pulse modulation signal through short-time Fourier transform(STFT),and then design an appropriate deep residual network to extract the features of the time-frequency map and complete a variety of complex intra-pulse modulation signal type recognition.In addition,in order to improve the generalization ability of the proposed method,label smoothing and L2 regularization are introduced.The simulation results show that the proposed method has a recognition accuracy of more than 95%for complex radar intra-pulse modulation sig-nal types under low SNR(2 dB).展开更多
Constructing the efficacious and applicable bifunctional electrocatalysts and establishing out the mechanisms of organic electro-oxidation by replacing anodic oxygen evolution reaction(OER) are critical to the develop...Constructing the efficacious and applicable bifunctional electrocatalysts and establishing out the mechanisms of organic electro-oxidation by replacing anodic oxygen evolution reaction(OER) are critical to the development of electrochemicallydriven technologies for efficient hydrogen production and avoid CO_(2) emission. Herein, the hetero-nanocrystals between monodispersed Pt(~ 2 nm) and Ni_(3)S_(2)(~ 9.6 nm) are constructed as active electrocatalysts through interfacial electronic modulation, which exhibit superior bi-functional activities for methanol selective oxidation and H_(2) generation. The experimental and theoretical studies reveal that the asymmetrical charge distribution at Pt–Ni_(3)S_(2) could be modulated by the electronic interaction at the interface of dual-monodispersed heterojunctions, which thus promote the adsorption/desorption of the chemical intermediates at the interface. As a result, the selective conversion from CH_(3)OH to formate is accomplished at very low potentials(1.45 V) to attain 100 m A cm^(-2) with high electronic utilization rate(~ 98%) and without CO_(2) emission. Meanwhile, the Pt–Ni_(3)S_(2) can simultaneously exhibit a broad potential window with outstanding stability and large current densities for hydrogen evolution reaction(HER) at the cathode. Further, the excellent bi-functional performance is also indicated in the coupled methanol oxidation reaction(MOR)//HER reactor by only requiring a cell voltage of 1.60 V to achieve a current density of 50 m A cm^(-2) with good reusability.展开更多
Modulated electro-hyperthermia (mEHT) is one of the novel oncological treatments with many preclinical and clinical results showing its advantages. The basis of the method is the synergy of thermal and nonthermal effe...Modulated electro-hyperthermia (mEHT) is one of the novel oncological treatments with many preclinical and clinical results showing its advantages. The basis of the method is the synergy of thermal and nonthermal effects, similar to the thermal action of conventional hyperthermia combined with ionizing radiation (radiotherapy). The electric field and the radiofrequency current produced both the thermal and nonthermal processes. The thermal effects produce the elevated temperature as a thermal background to optimize the nonthermal impacts. The low frequency amplitude modulation ensures accurate targeting and promotes immunogenic cell death to develop the tumor specific memory T cells disrupting the malignant cells by immune surveillance. This process (abscopal effect) works like a vaccination. The low frequency amplitude modulation is combined in the new method with the high power pulses for short time, increasing the tumor distortion ability of the electric field. The new modulation combination has much deeper penetration triplicating the active thickness of the effective treatment. The short pulse absorption increases the safety and decreases the thermal toxicity of the treatment, making the treatment safer. The increased power allows for reduced treatment time with the prescribed dose.展开更多
Directional modulation(DM)is one of the most promising secure communication techniques.However,when the eavesdropper is co-located with the legitimate receiver,the conventional DM has the disadvantages of weak anti-sc...Directional modulation(DM)is one of the most promising secure communication techniques.However,when the eavesdropper is co-located with the legitimate receiver,the conventional DM has the disadvantages of weak anti-scanning capability,anti-deciphering capability,and low secrecy rate.In response to these problems,we propose a twodimensional multi-term weighted fractional Fourier transform aided DM scheme,in which the legitimate receiver and the transmitter use different transform terms and transform orders to encrypt and decrypt the confidential information.In order to further lower the probability of being deciphered by an eavesdropper,we use the subblock partition method to convert the one-dimensional modulated signal vector into a twodimensional signal matrix,increasing the confusion of the useful information.Numerical results demonstrate that the proposed DM scheme not only provides stronger anti-deciphering and anti-scanning capabilities but also improves the secrecy rate performance of the system.展开更多
Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the ...Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.展开更多
Due to the limited computational capability and the diversity of the Internet of Things devices working in different environment,we consider fewshot learning-based automatic modulation classification(AMC)to improve it...Due to the limited computational capability and the diversity of the Internet of Things devices working in different environment,we consider fewshot learning-based automatic modulation classification(AMC)to improve its reliability.A data enhancement module(DEM)is designed by a convolutional layer to supplement frequency-domain information as well as providing nonlinear mapping that is beneficial for AMC.Multimodal network is designed to have multiple residual blocks,where each residual block has multiple convolutional kernels of different sizes for diverse feature extraction.Moreover,a deep supervised loss function is designed to supervise all parts of the network including the hidden layers and the DEM.Since different model may output different results,cooperative classifier is designed to avoid the randomness of single model and improve the reliability.Simulation results show that this few-shot learning-based AMC method can significantly improve the AMC accuracy compared to the existing methods.展开更多
基金supported by funds from the Italian Ministry of Health,Ricerca Finalizzata,(Grant N.GR-2013-02355882 and GR-2021-12373946 to AL)5x1000 Project of the Istituto Superiore di Sanità(Project code:ISS5x1000_21-949432e8c9be to AL)the European Union–NextGeneration EU through the Italian Ministry of University and Research under PNRR-M4C2-I1.3 Project PE_00000019“HEAL ITALIA”to EA(CUP I83C22001830006)。
文摘Astrocytes,the main population of glial cells in the central nervous system(CNS),exert essential tasks for the control of brain tissue homeostasis,supporting neuron and other glial cell activity from the developmental stage to adult life.To maintain the optimal functionality of the brain,astroglial cells are particularly committed to reacting to every change in tissue homeostatic conditions,from mild modifications of the physiological environment,a process called astrocyte activation,to the more severe alterations occurring in pathological situations causing astrocyte reactivity or reactive astrogliosis(Escartin et al.,2021).During these reactive states,astrocytes mount an active,progressive response encompassing morphological,molecular,and interactional remodeling,leading to the acquisition of new functions and the loss of others,whose intensity,duration,and reversibility are dependent on the nature of the stimulus and regulated in a context-specific manner.
基金jointly supported by projects of the National Natural Science Foundation of China [grant numbers 42141017 and 41975112]。
文摘El Niño-Southern Oscillation(ENSO)is a major driver of climate change in middle and low latitudes and thus strongly influences the terrestrial carbon cycle through land-air interaction.Both the ENSO modulation and carbon flux variability are projected to increase in the future,but their connection still needs further investigation.To investigate the impact of future ENSO modulation on carbon flux variability,this study used 10 CMIP6 earth system models to analyze ENSO modulation and carbon flux variability in middle and low latitudes,and their relationship,under different scenarios simulated by CMIP6 models.The results show a high consistency in the simulations,with both ENSO modulation and carbon flux variability showing an increasing trend in the future.The higher the emissions scenario,especially SSP5-8.5 compared to SSP2-4.5,the greater the increase in variability.Carbon flux variability in the middle and low latitudes under SSP2-4.5 increases by 30.9%compared to historical levels during 1951-2000,while under SSP5-8.5 it increases by 58.2%.Further analysis suggests that ENSO influences mid-and low-latitude carbon flux variability primarily through temperature.This occurrence may potentially be attributed to the increased responsiveness of gross primary productivity towards regional temperature fluctuations,combined with the intensified influence of ENSO on land surface temperatures.
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.
基金supported in part by the NSF of China under Grant 62322106,62071131the Guangdong Basic and Applied Basic Research Foundation under Grant 2022B1515020086+2 种基金the International Collaborative Research Program of Guangdong Science and Technology Department under Grant 2022A0505050070in part by the Open Research Fund of the State Key Laboratory of Integrated Services Networks under Grant ISN22-23the National Research Foundation,Singapore University of Technology Design under its Future Communications Research&Development Programme“Advanced Error Control Coding for 6G URLLC and mMTC”Grant No.FCP-NTU-RG-2022-020.
文摘This paper investigates the bit-interleaved coded generalized spatial modulation(BICGSM) with iterative decoding(BICGSM-ID) for multiple-input multiple-output(MIMO) visible light communications(VLC). In the BICGSM-ID scheme, the information bits conveyed by the signal-domain(SiD) symbols and the spatial-domain(SpD) light emitting diode(LED)-index patterns are coded by a protograph low-density parity-check(P-LDPC) code. Specifically, we propose a signal-domain symbol expanding and re-allocating(SSER) method for constructing a type of novel generalized spatial modulation(GSM) constellations, referred to as SSERGSM constellations, so as to boost the performance of the BICGSM-ID MIMO-VLC systems.Moreover, by applying a modified PEXIT(MPEXIT) algorithm, we further design a family of rate-compatible P-LDPC codes, referred to as enhanced accumulate-repeat-accumulate(EARA) codes,which possess both excellent decoding thresholds and linear-minimum-distance-growth property. Both analysis and simulation results illustrate that the proposed SSERGSM constellations and P-LDPC codes can remarkably improve the convergence and decoding performance of MIMO-VLC systems. Therefore, the proposed P-LDPC-coded SSERGSM-mapped BICGSMID configuration is envisioned as a promising transmission solution to satisfy the high-throughput requirement of MIMO-VLC applications.
文摘The clinical application of magnesium(Mg)and its alloys for bone fractures has been well supported by in vitro and in vivo trials.However,there were studies indicating negative effects of high dose Mg intake and sustained local release of Mg ions on bone metabolism or repair,which should not be ignored when developing Mg-based implants.Thus,it remains necessary to assess the biological effects of Mg implants in animal models relevant to clinical treatment modalities.The primary purpose of this study was to validate the beneficial effects of intramedullary Mg implants on the healing outcome of femoral fractures in a modified rat model.In addition,the mineralization parameters at multiple anatomical sites were evaluated,to investigate their association with healing outcome and potential clinical applications.Compared to the control group without Mg implantation,postoperative imaging at week 12 demonstrated better healing outcomes in the Mg group,with more stable unions in 3D analysis and high-mineralized bridging in 2D evaluation.The bone tissue mineral density(TMD)was higher in the Mg group at the non-operated femur and lumbar vertebra,while no differences between groups were identified regarding the bone tissue volume(TV),TMD and bone mineral content(BMC)in humerus.In the surgical femur,the Mg group presented higher TMD,but lower TV and BMC in the distal metaphyseal region,as well as reduced BMC at the osteotomy site.Principal component analysis(PCA)-based machine learning revealed that by selecting clinically relevant parameters,radiological markers could be constructed for differentiation of healing outcomes,with better performance than 2D scoring.The study provides insights and preclinical evidence for the rational investigation of bioactive materials,the identification of potential adverse effects,and the promotion of diagnostic capabilities for fracture healing.
基金supported by“National Natural Science Foundation of China(U21A20171,U20A20245)”“Hubei Provincial Natural Science Foundation of China(2023AFA010)”+1 种基金“Independent Innovation Projects of the Hubei Longzhong Laboratory(2022ZZ-09)”“Social Public Welfare and Basic Research Special Project of Zhongshan(2020B2015).”。
文摘Two-terminal(2-T)perovskite(PVK)/CuIn(Ga)Se_(2)(CIGS)tandem solar cells(TSCs)have been considered as an ideal tandem cell because of their best bandgap matching regarding to Shockley–Queisser(S–Q)limits.However,the nature of the irregular rough morphology of commercial CIGS prevents people from improving tandem device performances.In this paper,D-homoserine lactone hydrochloride is proven to improve coverage of PVK materials on irregular rough CIGS surfaces and also passivate bulk defects by modulating the growth of PVK crystals.In addition,the minority carriers near the PVK/C60 interface and the incompletely passivated trap states caused interface recombination.A surface reconstruction with 2-thiopheneethylammonium iodide and N,N-dimethylformamide assisted passivates the defect sites located at the surface and grain boundaries.Meanwhile,LiF is used to create this field effect,repelling hole carriers away from the PVK and C60 interface and thus reducing recombination.As a result,a 2-T PVK/CIGS tandem yielded a power conversion efficiency of 24.6%(0.16 cm^(2)),one of the highest results for 2-T PVK/CIGS TSCs to our knowledge.This validation underscores the potential of our methodology in achieving superior performance in PVK/CIGS tandem solar cells.
基金National Natural Science Foundation of China,Grant/Award Numbers:52102260,52171211,51972220,61903235,U22A20145Shandong Provincial Natural Science Foundation,Grant/Award Numbers:ZR2020QB069,ZR2022ME051+4 种基金National Key Research and Development Program of China,Grant/Award Number:2022YFB4002004Scientific and Technological Innovation Ability Improvement Project of Minor Enterprises in Shandong Province,Grant/Award Number:2022TSGC1021Announce the List and Take Charge Project in Jinan,Grant/Award Number:202214012Major innovation project for integrating science,education and industry of Qilu University of Technology (Shandong Academy of Sciences),Grant/Award Numbers:2022JBZ01-07,2022PY044China Postdoctoral Science Foundation,Grant/Award Number:2022M711545。
文摘Enhancing both the number of active sites available and the intrinsic activity of Co-based electrocatalysts simultaneously is a desirable goal.Herein,a ZIF-67-derived hierarchical porous cobalt sulfide decorated by Au nanoparticles(NPs)(denoted as HP-Au@CoxSy@ZIF-67)hybrid is synthesized by low-temperature sulfuration treatment.The well-defined macroporous-mesoporous-microporous structure is obtained based on the combination of polystyrene spheres,as-formed CoxSy nanosheets,and ZIF-67 frameworks.This novel three-dimensional hierarchical structure significantly enlarges the three-phase interfaces,accelerating the mass transfer and exposing the active centers for oxygen evolution reaction.The electronic structure of Co is modulated by Au through charge transfer,and a series of experiments,together with theoretical analysis,is performed to ascertain the electronic modulation of Co by Au.Meanwhile,HP-Au@CoxSy@ZIF-67 catalysts with different amounts of Au were synthesized,wherein Au and NaBH4 reductant result in an interesting“competition effect”to regulate the relative ratio of Co^(2+)/Co^(3+),and moderate Au assists the electrochemical performance to reach the highest value.Consequently,the optimized HP-Au@CoxSy@ZIF-67 exhibits a low overpotential of 340 mV at 10 mA cm^(-2)and a Tafel slope of 42 mV dec-1 for OER in 0.1 M aqueous KOH,enabling efficient water splitting and Zn-air battery performance.The work here highlights the pivotal roles of both microstructural and electronic modulation in enhancing electrocatalytic activity and presents a feasible strategy for designing and optimizing advanced electrocatalysts.
基金National Natural Science Foundation of China under Grant No.61973037China Postdoctoral Science Foundation 2022M720419 to provide fund for conducting experiments。
文摘The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.
基金supported by the National Key R&D Program of China (Award No.2022YFC3401100)the National Natural Science Foundation of China。
文摘In recent years,notable progress has been achieved in both the hardware and algorithms of structured illumination microscopy(SIM).Nevertheless,the advancement of three-dimensional structured illumination microscopy(3DSIM)has been impeded by challenges arising from the speed and intricacy of polarization modulation.We introduce a high-speed modulation 3DSIM system,leveraging the polarizationmaintaining and modulation capabilities of a digital micromirror device(DMD)in conjunction with an electrooptic modulator.The DMD-3DSIM system yields a twofold enhancement in both lateral(133 nm)and axial(300 nm)resolution compared to wide-field imaging and can acquire a data set comprising 29 sections of 1024 pixels×1024 pixels,with 15 ms exposure time and 6.75 s per volume.The versatility of the DMD-3DSIM approach was exemplified through the imaging of various specimens,including fluorescent beads,nuclear pores,microtubules,actin filaments,and mitochondria within cells,as well as plant and animal tissues.Notably,polarized 3DSIM elucidated the orientation of actin filaments.Furthermore,the implementation of diverse deconvolution algorithms further enhances 3D resolution.The DMD-based 3DSIM system presents a rapid and reliable methodology for investigating biomedical phenomena,boasting capabilities encompassing 3D superresolution,fast temporal resolution,and polarization imaging.
基金supported by the China Scholarship Council(Grant No.201906130092)the Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(Grant No.NY223065)the Natural Science Foundation of Sichuan Province(Grant No.2023NSFSC1330).
文摘Emission of matter-wave jets from a parametrically driven condensate has attracted significant experimental and theoretical attention due to the appealing visual effects and potential metrological applications.In this work,we investigate the collective particle emission from a Bose-Einstein condensate confined in a one-dimensional lattice with periodically modulated interparticle interactions.We give the regimes for discrete modes,and find that the emission can be distinctly suppressed.The configuration induces a broad band,but few particles are ejected due to the interference of the matter waves.We further qualitatively model the emission process and demonstrate the short-time behaviors.This engineering provides a way to manipulate the propagation of particles and the corresponding dynamics of condensates in lattices,and may find application in the dynamical excitation control of other nonequilibrium problems with time-periodic driving.
基金supported by the Guangdong Major Project of Basic and Applied Basic Research(Grant No.2020B0301030009)the National Key Research and Development Program of China(Grant No.2022YFA1604304)the National Natural Science Foundation of China(Grant No.92250305).
文摘Plasmonic modes within metal nanostructures play a pivotal role in various nanophotonic applications.However,a significant challenge arises from the fixed shapes of nanostructures post-fabrication,resulting in limited modes under ordinary illumination.A promising solution lies in far-field control facilitated by spatial light modulators(SLMs),which enable on-site,real-time,and non-destructive manipulation of plasmon excitation.Through the robust modulation of the incident light using SLMs,this approach enables the generation,optimization,and dynamic control of surface plasmon polariton(SPP)and localized surface plasmon(LSP)modes.The versatility of this technique introduces a rich array of tunable degrees of freedom to plasmon-enhanced spectroscopy,offering novel approaches for signal optimization and functional expansion in this field.This paper provides a comprehensive review of the generation and modulation of SPP and LSP modes through far-field control with SLMs and highlights the diverse applications of this optical technology in plasmon-enhanced spectroscopy.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61971348 and 61201194)。
文摘In order to avoid the complexity of Gaussian modulation and the problem that the traditional point-to-point communication DM-CVQKD protocol cannot meet the demand for multi-user key sharing at the same time, we propose a multi-ring discrete modulation continuous variable quantum key sharing scheme(MR-DM-CVQSS). In this paper, we primarily compare single-ring and multi-ring M-symbol amplitude and phase-shift keying modulations. We analyze their asymptotic key rates against collective attacks and consider the security key rates under finite-size effects. Leveraging the characteristics of discrete modulation, we improve the quantum secret sharing scheme. Non-dealer participants only require simple phase shifters to complete quantum secret sharing. We also provide the general design of the MR-DM-CVQSS protocol.We conduct a comprehensive analysis of the improved protocol's performance, confirming that the enhancement through multi-ring M-PSK allows for longer-distance quantum key distribution. Additionally, it reduces the deployment complexity of the system, thereby increasing the practical value.
基金supported in part by the National Natural Science Foundation of China under Grant No.62171334,No.11973077 and No.12003061。
文摘With the successive application of deep learning(DL)in classification tasks,the DL-based modulation classification method has become the preference for its state-of-the-art performance.Nevertheless,once the DL recognition model is pre-trained with fixed classes,the pre-trained model tends to predict incorrect results when identifying incremental classes.Moreover,the incremental classes are usually emergent without label information or only a few labeled samples of incremental classes can be obtained.In this context,we propose a graphbased semi-supervised approach to address the fewshot classes-incremental(FSCI)modulation classification problem.Our proposed method is a twostage learning method,specifically,a warm-up model is trained for classifying old classes and incremental classes,where the unlabeled samples of incremental classes are uniformly labeled with the same label to alleviate the damage of the class imbalance problem.Then the warm-up model is regarded as a feature extractor for constructing a similar graph to connect labeled samples and unlabeled samples,and the label propagation algorithm is adopted to propagate the label information from labeled nodes to unlabeled nodes in the graph to achieve the purpose of incremental classes recognition.Simulation results prove that the proposed method is superior to other finetuning methods and retrain methods.
基金supported by the Natural Science Foundation of Anhui Province(No.2208085J01 and No.2208085QA28).
文摘Controlling the local electronic structure of active ingredients to improve the adsorption desorption characteristics of oxygen-containing intermediates over the electrochemical liquid-solid interfaces is a critical challenge in the field of oxygen reduction reaction(ORR)catalysis.Here,we offer a simple approach for modulating the electronic states of metal nanocrystals by bimetal co-doping into carbon-nitrogen substrate,allowing us to modulate the electronic structure of catalytic active centers.To test our strategy,we designed a typical bimetallic nanoparticle catalyst(Fe-Co NP/NC)to flexibly alter the reaction kinetics of ORR.Our results from synchrotron Xray absorption spectroscopy and X-ray photoelectron spectroscopy showed that the co-doping of iron and cobalt could optimize the intrinsic charge distribution of Fe-Co NP/NC catalyst,promoting the oxygen reduction kinetics and ultimately achieving remarkable ORR activity.Consequently,the carefully designed Fe-Co NP/NC exhibits an ultra-high kinetic current density at the operating voltage(71.94 mA/cm^(2)at 0.80 V),and the half-wave potential achieves 0.915 V,which is obviously better than that of the corresponding controls including Fe NP/NC,Co NP/NC.Our findings provide a unique perspective for optimizing the electronic structure of active centers to achieve higher ORR catalytic activity and faster kinetics.
文摘In view of low recognition rate of complex radar intra-pulse modulation signal type by traditional methods under low signal-to-noise ratio(SNR),the paper proposes an automatic recog-nition method of complex radar intra-pulse modulation signal type based on deep residual network.The basic principle of the recognition method is to obtain the transformation relationship between the time and frequency of complex radar intra-pulse modulation signal through short-time Fourier transform(STFT),and then design an appropriate deep residual network to extract the features of the time-frequency map and complete a variety of complex intra-pulse modulation signal type recognition.In addition,in order to improve the generalization ability of the proposed method,label smoothing and L2 regularization are introduced.The simulation results show that the proposed method has a recognition accuracy of more than 95%for complex radar intra-pulse modulation sig-nal types under low SNR(2 dB).
基金the financial support of Guangdong Basic and Applied Basic Research Foundation (No. 2023A1515010940)Shenzhen Natural Science Fund (the Stable Support Plan Program No. 20220809160022001)the Shenzhen Science and Technology Programs (No. ZDSYS20220527171401003, KQTD20190929173914967)。
文摘Constructing the efficacious and applicable bifunctional electrocatalysts and establishing out the mechanisms of organic electro-oxidation by replacing anodic oxygen evolution reaction(OER) are critical to the development of electrochemicallydriven technologies for efficient hydrogen production and avoid CO_(2) emission. Herein, the hetero-nanocrystals between monodispersed Pt(~ 2 nm) and Ni_(3)S_(2)(~ 9.6 nm) are constructed as active electrocatalysts through interfacial electronic modulation, which exhibit superior bi-functional activities for methanol selective oxidation and H_(2) generation. The experimental and theoretical studies reveal that the asymmetrical charge distribution at Pt–Ni_(3)S_(2) could be modulated by the electronic interaction at the interface of dual-monodispersed heterojunctions, which thus promote the adsorption/desorption of the chemical intermediates at the interface. As a result, the selective conversion from CH_(3)OH to formate is accomplished at very low potentials(1.45 V) to attain 100 m A cm^(-2) with high electronic utilization rate(~ 98%) and without CO_(2) emission. Meanwhile, the Pt–Ni_(3)S_(2) can simultaneously exhibit a broad potential window with outstanding stability and large current densities for hydrogen evolution reaction(HER) at the cathode. Further, the excellent bi-functional performance is also indicated in the coupled methanol oxidation reaction(MOR)//HER reactor by only requiring a cell voltage of 1.60 V to achieve a current density of 50 m A cm^(-2) with good reusability.
文摘Modulated electro-hyperthermia (mEHT) is one of the novel oncological treatments with many preclinical and clinical results showing its advantages. The basis of the method is the synergy of thermal and nonthermal effects, similar to the thermal action of conventional hyperthermia combined with ionizing radiation (radiotherapy). The electric field and the radiofrequency current produced both the thermal and nonthermal processes. The thermal effects produce the elevated temperature as a thermal background to optimize the nonthermal impacts. The low frequency amplitude modulation ensures accurate targeting and promotes immunogenic cell death to develop the tumor specific memory T cells disrupting the malignant cells by immune surveillance. This process (abscopal effect) works like a vaccination. The low frequency amplitude modulation is combined in the new method with the high power pulses for short time, increasing the tumor distortion ability of the electric field. The new modulation combination has much deeper penetration triplicating the active thickness of the effective treatment. The short pulse absorption increases the safety and decreases the thermal toxicity of the treatment, making the treatment safer. The increased power allows for reduced treatment time with the prescribed dose.
基金supported by National Natural Science Foundation of China(No.62171445)。
文摘Directional modulation(DM)is one of the most promising secure communication techniques.However,when the eavesdropper is co-located with the legitimate receiver,the conventional DM has the disadvantages of weak anti-scanning capability,anti-deciphering capability,and low secrecy rate.In response to these problems,we propose a twodimensional multi-term weighted fractional Fourier transform aided DM scheme,in which the legitimate receiver and the transmitter use different transform terms and transform orders to encrypt and decrypt the confidential information.In order to further lower the probability of being deciphered by an eavesdropper,we use the subblock partition method to convert the one-dimensional modulated signal vector into a twodimensional signal matrix,increasing the confusion of the useful information.Numerical results demonstrate that the proposed DM scheme not only provides stronger anti-deciphering and anti-scanning capabilities but also improves the secrecy rate performance of the system.
基金National Natural Science Foundation of China under Grant No.61973037China Postdoctoral Science Foundation under Grant No.2022M720419。
文摘Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.
基金supported in part by National Key Research and Development Program of China under Grant 2021YFB2900404.
文摘Due to the limited computational capability and the diversity of the Internet of Things devices working in different environment,we consider fewshot learning-based automatic modulation classification(AMC)to improve its reliability.A data enhancement module(DEM)is designed by a convolutional layer to supplement frequency-domain information as well as providing nonlinear mapping that is beneficial for AMC.Multimodal network is designed to have multiple residual blocks,where each residual block has multiple convolutional kernels of different sizes for diverse feature extraction.Moreover,a deep supervised loss function is designed to supervise all parts of the network including the hidden layers and the DEM.Since different model may output different results,cooperative classifier is designed to avoid the randomness of single model and improve the reliability.Simulation results show that this few-shot learning-based AMC method can significantly improve the AMC accuracy compared to the existing methods.