Numerous pathological states of the nervous system involve alterations in neuronal excitability and synaptic dysfunction,which depend on the function of ion channels.Due to their critical involvement in health and dis...Numerous pathological states of the nervous system involve alterations in neuronal excitability and synaptic dysfunction,which depend on the function of ion channels.Due to their critical involvement in health and disease,the search for new compounds that modulate these proteins is still relevant.Traditional medicine has long been a rich source of neuroactive compounds.For example,the indigenous Mapuche people have used the leaves and bark of the Drimys winteri tree for centuries to treat various diseases.Consequently,several studies have investigated the biological effects of compounds in Drimys winteri,highlighting sesquiterpenes such asα-humulene,drimenin,polygodial,andα-,β-,γ-eudesmol.However,there is currently no literature review focusing on the ability of these sesquiterpenes to modulate ion channels.This review summarizes the current knowledge about neuroactive compounds found in Drimys winteri,with special emphasis on their direct actions on neuronal ion channels.Several Drimys winteri sesquiterpenes modulate a diverse array of neuronal ion channels,including transient receptor potential channels,gamma-aminobutyric acid A receptors,nicotinic acetylcholine receptors,and voltage-dependent Ca^(2+)and Na^(+)channels.Interestingly,the modulation of these molecular targets by Drimys winteri sesquiterpenes correlates with their therapeutic actions.The promiscuous pharmacological profile of Drimys winteri sesquiterpenes suggests they modulate multiple protein targets in vivo,making them potentially useful for treating complex,multifactorial diseases.Further studies at the molecular level may aid in developing multitargeted drugs with enhanced therapeutic effects.展开更多
The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential sc...The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential scenarios is vexed by the need for more theoretical support.This paper mainly studies the communication channel between the Tx at semibasement and receiver(Rx)at outdoor.The design of an effective communication system relies on an accurate understanding of channel characteristics.Channel measurements and ray-tracing channel modeling are conducted to obtain channel data.The influence of different positions at same semi-basement is studied.Typical channel characteristics are analyzed,such as power delay profile(PDP),power angular profile(PAP),root-mean-square(RMS)delay spread(DS),channel capacity,received power,and path loss.The influence of different semi-basement placements and different floor heights is also compared.Besides,the channel measurements and simulation data fit well,which can illustrate the validity and reliability of the acquired channel data.This paper can provide theoretical support for the design and optimization of smart meter communication systems in semi-basement scenarios.展开更多
(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbi...(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.展开更多
Ischemia–reperfusion injury is a common pathophysiological mechanism in retinal degeneration.PANoptosis is a newly defined integral form of regulated cell death that combines the key features of pyroptosis,apoptosis,...Ischemia–reperfusion injury is a common pathophysiological mechanism in retinal degeneration.PANoptosis is a newly defined integral form of regulated cell death that combines the key features of pyroptosis,apoptosis,and necroptosis.Oligomerization of mitochondrial voltage-dependent anion channel 1 is an important pathological event in regulating cell death in retinal ischemia–reperfusion injury.However,its role in PANoptosis remains largely unknown.In this study,we demonstrated that voltage-dependent anion channel 1 oligomerization-mediated mitochondrial dysfunction was associated with PANoptosis in retinal ischemia–reperfusion injury.Inhibition of voltage-dependent anion channel 1 oligomerization suppressed mitochondrial dysfunction and PANoptosis in retinal cells subjected to ischemia–reperfusion injury.Mechanistically,mitochondria-derived reactive oxygen species played a central role in the voltagedependent anion channel 1-mediated regulation of PANoptosis by promoting PANoptosome assembly.Moreover,inhibiting voltage-dependent anion channel 1 oligomerization protected against PANoptosis in the retinas of rats subjected to ischemia–reperfusion injury.Overall,our findings reveal the critical role of voltage-dependent anion channel 1 oligomerization in regulating PANoptosis in retinal ischemia–reperfusion injury,highlighting voltage-dependent anion channel 1 as a promising therapeutic target.展开更多
The orthogonal time frequency space(OTFS)modulation is a novel modulation scheme that can effectively cope with the high Doppler expansion caused by high mobility.Since it modulates data on delay-Doppler(DD)domain and...The orthogonal time frequency space(OTFS)modulation is a novel modulation scheme that can effectively cope with the high Doppler expansion caused by high mobility.Since it modulates data on delay-Doppler(DD)domain and makes full use of the sparse characteristics of DD domain,it has been widely studied to design efficient channel estimation and signal detection schemes.In this paper,we design a novel superimposed pilot pattern with transition band,which replaces the traditional embedded pilot(EP)guard zero-symbols,and perform a two-stage channel estimation.In the first stage,we fully utilize the dispersion characteristics of OTFS signal in DD domain,and use threshold decision to make coarse channel estimation.In the second stage,we use the results of the coarse estimation for iterative signal detection and accurate channel estimation.During the second stage,we make full use of the sparsity of the channel in DD domain,remodel the received signal into the form of sparse channel vector multiplied by channel coefficient matrix,and introduce Doppler index segmentation factor(DISF)to subdivide the Doppler index to solve the problem of fractional Doppler.Simulations reveal that,the scheme proposed in this paper has higher spectral efficiency compared with traditional EP scheme and lower peak-to-average power ratio(PAPR)compared with traditional superimposed pilot scheme.展开更多
Einstein–Podolsky–Rosen(EPR)steering is an important resource for one-sided device-independent quantum information processing.This steering property can be destroyed by the interaction between a quantum system and i...Einstein–Podolsky–Rosen(EPR)steering is an important resource for one-sided device-independent quantum information processing.This steering property can be destroyed by the interaction between a quantum system and its environment in practical applications.In this paper,we employ the characteristic function representation of probability distributions to investigate the quantum steering of two-mode continuous-variable states in a laser channel,where both the gain factor and the loss effect are taken into account.Firstly,we analyse the steering time of the two-mode squeezed vacuum state under one-mode and two-mode laser channels,respectively.We find that the gain process introduces additional noise into the two-mode squeezed vacuum state,thereby reducing the steerable time.Secondly,by quantifying EPR steering,we show that two-side loss exhibits smaller steerability than one-side loss,although they share the same two-way steerable time.In addition,we find that the more-gained party can steer the other party’s state,whereas the other party cannot steer the gained party beyond a certain threshold value.In this sense,the gain effect in one party appears to be equivalent to the loss effect in the other party.Our results pave the way for the distillation of EPR steering and quantum information processing in practical quantum channels.展开更多
Split Learning(SL)has been promoted as a promising collaborative machine learning technique designed to address data privacy and resource efficiency.Specifically,neural networks are divided into client and server subn...Split Learning(SL)has been promoted as a promising collaborative machine learning technique designed to address data privacy and resource efficiency.Specifically,neural networks are divided into client and server subnetworks in order to mitigate the exposure of sensitive data and reduce the overhead on client devices,thereby making SL particularly suitable for resource-constrained devices.Although SL prevents the direct transmission of raw data,it does not alleviate entirely the risk of privacy breaches.In fact,the data intermediately transmitted to the server sub-model may include patterns or information that could reveal sensitive data.Moreover,achieving a balance between model utility and data privacy has emerged as a challenging problem.In this article,we propose a novel defense approach that combines:(i)Adversarial learning,and(ii)Network channel pruning.In particular,the proposed adversarial learning approach is specifically designed to reduce the risk of private data exposure while maintaining high performance for the utility task.On the other hand,the suggested channel pruning enables the model to adaptively adjust and reactivate pruned channels while conducting adversarial training.The integration of these two techniques reduces the informativeness of the intermediate data transmitted by the client sub-model,thereby enhancing its robustness against attribute inference attacks without adding significant computational overhead,making it wellsuited for IoT devices,mobile platforms,and Internet of Vehicles(IoV)scenarios.The proposed defense approach was evaluated using EfficientNet-B0,a widely adopted compact model,along with three benchmark datasets.The obtained results showcased its superior defense capability against attribute inference attacks compared to existing state-of-the-art methods.This research’s findings demonstrated the effectiveness of the proposed channel pruning-based adversarial training approach in achieving the intended compromise between utility and privacy within SL frameworks.In fact,the classification accuracy attained by the attackers witnessed a drastic decrease of 70%.展开更多
[Objective]As wireless power transfer(WPT)technology is increasingly deployed in scenarios such as electric vehicles,metallic foreign objects in the WPT area may cause local overheating and energy loss.Existing method...[Objective]As wireless power transfer(WPT)technology is increasingly deployed in scenarios such as electric vehicles,metallic foreign objects in the WPT area may cause local overheating and energy loss.Existing methods still suffer from poor edge/corner sensitivity,misjudgment due to fixed thresholds,and limited ability to extract position information.This work proposes a wireless power transfer-foreign object detection(WPT-FOD)method based on channel differential response and a dynamic-threshold corner-enhancement strategy,aiming to improve detection sensitivity,localization accuracy,and robustness without altering the overall coil layout.[Method]A multi-channel detection coil array is designed,and the self-inductance disturbance response of each channel coil is modeled.A channel-difference mapping mechanism is introduced to build a 2-D sensitivity matrix to characterize spatial position correlation.A corner-enhancement algorithm is developed to weight and amplify the collaborative response of adjacent channels,and a dynamic threshold adjustment mechanism is integrated to adapt to varying interference levels.Validation is carried out on a self-built 64-channel FOD platform by moving a typical metallic foreign object across central,edge,and corner regions,and by conducting comparative tests under different interference intensities.[Result]When a typical metallic foreign object moves to corner regions,the self-inductance disturbance of the detection coil increases from less than 0.02μH to more than 0.06μH,significantly enhancing the discrimination capability at corners.Under varying interference strengths,the dynamic threshold mechanism reduces the number of false positives from 13 to 2,demonstrating good environmental adaptability and stability.[Conclusion]By combining channel differential response,corner enhancement,and dynamic thresholding,the proposed WPT-FOD effectively mitigates edge/corner blind spots and fixed-threshold misjudgment,while providing localization capability and robustness.It markedly improves the accuracy of metallic foreign object detection in WPT systems and offers a feasible path and method reference for the safe application and engineering deployment of WPT systems.展开更多
The present study investigates the flow,heat,and mass transfer analysis in the bioconvection of nanofluid containing motile gyrotactic microorganisms through a semi-porous curved oscillatory channel with a magnetic fi...The present study investigates the flow,heat,and mass transfer analysis in the bioconvection of nanofluid containing motile gyrotactic microorganisms through a semi-porous curved oscillatory channel with a magnetic field.These microorganisms produce density gradients by swimming,which induces macroscopic convection flows in the fluid.This procedure improves the mass and heat transfer,illustrating the interaction between biological activity and fluid dynamics.Furthermore,instead of considering traditional Fourier's and Fick's law the energy and concentration equations are developed by incorporating Cattaneo-Christov double diffusion theory.Moreover,to examine the influence of thermophoresis and Brownian diffusions in the fluid we have adopted the Buongiorno nanofluid model.Due to the oscillation of the surface of the channel,the mathematical development of the considered flow problem is obtained in the form of partial differential equations via the curvilinear coordinate system.The convergent series solution of the governing flow equations is obtained after applying the homotopy analysis method(HAM).The effects of different pertinent flow parameters on velocity,motile microorganism density distribution,concentration,pressure,temperature,and skin friction coefficient are examined and discussed in detail with the help of graphs and tables.It is observed during the current study that the density of microorganisms is enhanced for higher values of Reynolds number,Peclet number,radius of curvature variable,and Lewis number.展开更多
With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State I...With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State Information(CSI)offers fine-grained temporal,frequency,and spatial insights into multipath propagation,making it a crucial data source for human-centric sensing.Recently,the integration of deep learning has significantly improved the robustness and automation of feature extraction from CSI in complex environments.This paper provides a comprehensive review of deep learning-enhanced human sensing based on CSI.We first outline mainstream CSI acquisition tools and their hardware specifications,then provide a detailed discussion of preprocessing methods such as denoising,time–frequency transformation,data segmentation,and augmentation.Subsequently,we categorize deep learning approaches according to sensing tasks—namely detection,localization,and recognition—and highlight representative models across application scenarios.Finally,we examine key challenges including domain generalization,multi-user interference,and limited data availability,and we propose future research directions involving lightweight model deployment,multimodal data fusion,and semantic-level sensing.展开更多
Photocatalysis uses solar energy to convert nitrogen and water directly into ammonia,helping reduce dependence on fossil fuels and offering a way to integrate the nitrogen cycle into a clean energy network.Ohmic junct...Photocatalysis uses solar energy to convert nitrogen and water directly into ammonia,helping reduce dependence on fossil fuels and offering a way to integrate the nitrogen cycle into a clean energy network.Ohmic junctions between metals and semiconductors have demonstrated significant advantages in enhancing stability and reducing carrier recombination,but their application in photocatalytic nitrogen fixation is limited due to the difficulty of work function matching and the complexity of fabrication processes.In this study,density functional theory(DFT) calculations were used to confirm the work function matching between Bi and Bi_(2)Ti_(2)O_(7)(BTO),ensuring the formation of an Ohmic junction.A Bi-Bi_(2)Ti_(2)O_(7)(B-BTO) composite was successfully synthesized via a one-step hydrothermal method,using bismuth nitrate and titanium sulfate as precursors.Compared to pure BTO,the B-BTO heterojunction,driven by dual electron injection from both metal Bi and BTO,significantly increased the ammonia synthesis rate to 686.95 μmol g^(-1)h^(-1),making it the most active nitrogen fixation material among similar pyrochlorebased catalysts to date.The differential charge density calculations,photocurrent(i-t) measurements,and photoluminescence(PL) tests further validate the role of Ohmic contacts in enhancing charge transfer and prolonging carrier lifetimes.This research provides valuable insight into the application of Ohmic junctions in photocatalytic nitrogen fixation and contributes to advancements in this field.展开更多
Along with the proliferating research interest in semantic communication(Sem Com),joint source channel coding(JSCC)has dominated the attention due to the widely assumed existence in efficiently delivering information ...Along with the proliferating research interest in semantic communication(Sem Com),joint source channel coding(JSCC)has dominated the attention due to the widely assumed existence in efficiently delivering information semantics.Nevertheless,this paper challenges the conventional JSCC paradigm and advocates for adopting separate source channel coding(SSCC)to enjoy a more underlying degree of freedom for optimization.We demonstrate that SSCC,after leveraging the strengths of the Large Language Model(LLM)for source coding and Error Correction Code Transformer(ECCT)complemented for channel coding,offers superior performance over JSCC.Our proposed framework also effectively highlights the compatibility challenges between Sem Com approaches and digital communication systems,particularly concerning the resource costs associated with the transmission of high-precision floating point numbers.Through comprehensive evaluations,we establish that assisted by LLM-based compression and ECCT-enhanced error correction,SSCC remains a viable and effective solution for modern communication systems.In other words,separate source channel coding is still what we need.展开更多
The central nervous system, information integration center of the body, is mainly composed of neurons and glial cells. The neuron is one of the most basic and important structural and functional units of the central n...The central nervous system, information integration center of the body, is mainly composed of neurons and glial cells. The neuron is one of the most basic and important structural and functional units of the central nervous system, with sensory stimulation and excitation conduction functions. Astrocytes and microglia belong to the glial cell family, which is the main source of cytokines and represents the main defense system of the central nervous system. Nerve cells undergo neurotransmission or gliotransmission, which regulates neuronal activity via the ion channels, receptors, or transporters expressed on nerve cell membranes. Ion channels, composed of large transmembrane proteins, play crucial roles in maintaining nerve cell homeostasis. These channels are also important for control of the membrane potential and in the secretion of neurotransmitters. A variety of cellular functions and life activities, including functional regulation of the central nervous system, the generation and conduction of nerve excitation, the occurrence of receptor potential, heart pulsation, smooth muscle peristalsis, skeletal muscle contraction, and hormone secretion, are closely related to ion channels associated with passive transmembrane transport. Two types of ion channels in the central nervous system, potassium channels and calcium channels, are closely related to various neurological disorders, including Alzheimer's disease, Parkinson's disease, and epilepsy. Accordingly, various drugs that can affect these ion channels have been explored deeply to provide new directions for the treatment of these neurological disorders. In this review, we focus on the functions of potassium and calcium ion channels in different nerve cells and their involvement in neurological disorders such as Parkinson's disease, Alzheimer's disease, depression, epilepsy, autism, and rare disorders. We also describe several clinical drugs that target potassium or calcium channels in nerve cells and could be used to treat these disorders. We concluded that there are few clinical drugs that can improve the pathology these diseases by acting on potassium or calcium ions. Although a few novel ion-channelspecific modulators have been discovered, meaningful therapies have largely not yet been realized. The lack of target-specific drugs, their requirement to cross the blood–brain barrier, and their exact underlying mechanisms all need further attention. This review aims to explain the urgent problems that need research progress and provide comprehensive information aiming to arouse the research community's interest in the development of ion channel-targeting drugs and the identification of new therapeutic targets for that can increase the cure rate of nervous system diseases and reduce the occurrence of adverse reactions in other systems.展开更多
Channel characterization and modeling are fundamental to communication system design,development,testing,and deployment.As the innate digital twins of wireless channels,channel models replicate real-world channel beha...Channel characterization and modeling are fundamental to communication system design,development,testing,and deployment.As the innate digital twins of wireless channels,channel models replicate real-world channel behaviors,e.g.,large-scale/small-scale fading,spatio-temporal-frequency non-stationarity,through mathematical and data-driven methods.This enables simulation-based validation across system development stages—from protocol design to network optimization-without costly physical testing.展开更多
With the development of wireless communication,the fifth generation mobile communication technology(5G)has emerged as a hot topic in highspeed railway communication system and has moved towards industrial application....With the development of wireless communication,the fifth generation mobile communication technology(5G)has emerged as a hot topic in highspeed railway communication system and has moved towards industrial application.Investigating the radio propagation characteristics in 5G high-speed train(HST)scenarios is essential for enhancing wireless coverage and overall system performance.We propose a novel 5G passive sounding scheme to extract channel impulse responses(CIRs)using channel state information reference signals(CSI-RS)from the target 5G base station(BS).Detailed procedures for timefrequency synchronization,CSI-RS detection and extraction are presented through simulations.Through the laboratory work involving absolute power calibration,phase coherence calibration and power delay profile(PDP)validation,we validate the accuracy and performance of the developed platform.Furthermore,a measurement campaign was conducted in HST scenarios encompassing both residential and undeveloped areas.The path loss(PL)model and the channel characteristics including stationarity interval(SI),multipath components(MPCs),shadow fading(SF),Rician K-factor,root mean square(RMS)delay spread and received correlation coefficients are analyzed and fitted.The estimated channel characteristics and the statistical model presented in this paper will contribute to the research on HST radio propagation and the development of 5G railway communication systems.展开更多
Reliable channel data helps characterize the limitations and performance boundaries of communication technologies accurately.However,channel measurement is highly costly and time-consuming,and taking actual measuremen...Reliable channel data helps characterize the limitations and performance boundaries of communication technologies accurately.However,channel measurement is highly costly and time-consuming,and taking actual measurement as the only channel data source may reduce efficiency because of the constraints of high testing difficulty and limited data volume.Although existing standard channel models can generate channel data,their authenticity and diversity cannot be guaranteed.To address this,we use deep learning methods to learn the attributes of limited measured data and propose a generative model based on generative adversarial networks to rapidly synthesize data.A software simulation platform is also established to verify that the proposed model can generate data that are statistically similar to the measured data while maintaining necessary randomness.The proposed algorithm and platform can be applied to channel data enhancement and serve channel modeling and algorithm evaluation applications with urgent needs for data.展开更多
With increasing density and heterogeneity in unlicensed wireless networks,traditional MAC protocols,such as Carrier Sense Multiple Access with Collision Avoidance(CSMA/CA)in Wi-Fi networks,are experiencing performance...With increasing density and heterogeneity in unlicensed wireless networks,traditional MAC protocols,such as Carrier Sense Multiple Access with Collision Avoidance(CSMA/CA)in Wi-Fi networks,are experiencing performance degradation.This is manifested in increased collisions and extended backoff times,leading to diminished spectrum efficiency and protocol coordination.Addressing these issues,this paper proposes a deep-learning-based MAC paradigm,dubbed DL-MAC,which leverages spectrum data readily available from energy detection modules in wireless devices to achieve the MAC functionalities of channel access,rate adaptation,and channel switch.First,we utilize DL-MAC to realize a joint design of channel access and rate adaptation.Subsequently,we integrate the capability of channel switching into DL-MAC,enhancing its functionality from single-channel to multi-channel operations.Specifically,the DL-MAC protocol incorporates a Deep Neural Network(DNN)for channel selection and a Recurrent Neural Network(RNN)for the joint design of channel access and rate adaptation.We conducted real-world data collection within the 2.4 GHz frequency band to validate the effectiveness of DL-MAC.Experimental results demonstrate that DL-MAC exhibits significantly superior performance compared to traditional algorithms in both single and multi-channel environments,and also outperforms single-function designs.Additionally,the performance of DL-MAC remains robust,unaffected by channel switch overheads within the evaluation range.展开更多
Integrated Sensing and Communication(ISAC)is considered a key technology in 6G networks.An accurate sensing channel model is crucial for the design and sensing performance evaluation of ISAC systems.The widely used Ge...Integrated Sensing and Communication(ISAC)is considered a key technology in 6G networks.An accurate sensing channel model is crucial for the design and sensing performance evaluation of ISAC systems.The widely used Geometry-Based Stochastic Model(GBSM),typically applied in standardized channel modeling,mainly focuses on the statistical fading characteristics of the channel.However,it fails to capture the characteristics of targets in ISAC systems,such as their positions and velocities,as well as the impact of the targets on the background.To address this issue,this paper proposes an Extended-GBSM(E-GBSM)sensing channel model that incorporates newly discovered channel characteristics into a unified modeling framework.In this framework,the sensing channel is divided into target and background channels.For the target channel,the model introduces a concatenated modeling approach,while for the background channel,a parameter called the power control factor is introduced to assess impact of the target on the background channel,making the modeling framework applicable to both mono-static and bi-static sensing modes.To validate the proposed model’s effectiveness,measurements of target and background channels are conducted across a wide range of indoor and outdoor scenarios,covering various sensing targets such as metal plates,reconfigurable intelligent surfaces,human bodies,unmanned aerial vehicles,and vehicles.The experimental results provide important theoretical support and empirical data for the standardization of ISAC channel modeling.展开更多
基金supported by ANID-FONDECYT 1200908(to JF),ANID-FONDECYT 1211082 and 1250856(to GEY)by the Millennium Nucleus for the Study of Pain NCN19_038(Mi Nu SPain)(to GEY)funded by the ANID scholarship 21201176。
文摘Numerous pathological states of the nervous system involve alterations in neuronal excitability and synaptic dysfunction,which depend on the function of ion channels.Due to their critical involvement in health and disease,the search for new compounds that modulate these proteins is still relevant.Traditional medicine has long been a rich source of neuroactive compounds.For example,the indigenous Mapuche people have used the leaves and bark of the Drimys winteri tree for centuries to treat various diseases.Consequently,several studies have investigated the biological effects of compounds in Drimys winteri,highlighting sesquiterpenes such asα-humulene,drimenin,polygodial,andα-,β-,γ-eudesmol.However,there is currently no literature review focusing on the ability of these sesquiterpenes to modulate ion channels.This review summarizes the current knowledge about neuroactive compounds found in Drimys winteri,with special emphasis on their direct actions on neuronal ion channels.Several Drimys winteri sesquiterpenes modulate a diverse array of neuronal ion channels,including transient receptor potential channels,gamma-aminobutyric acid A receptors,nicotinic acetylcholine receptors,and voltage-dependent Ca^(2+)and Na^(+)channels.Interestingly,the modulation of these molecular targets by Drimys winteri sesquiterpenes correlates with their therapeutic actions.The promiscuous pharmacological profile of Drimys winteri sesquiterpenes suggests they modulate multiple protein targets in vivo,making them potentially useful for treating complex,multifactorial diseases.Further studies at the molecular level may aid in developing multitargeted drugs with enhanced therapeutic effects.
基金supported by the Natural Science Foundation of Shandong Province under Grant ZR2024MF062the open research fund of National Mobile Communications Research Laboratory,Southeast University under Grants 2025D03+1 种基金the Future Plan Program for Young Scholars of Shandong University,and the Innovation and Technology Support Program for Young Scholars of Colleges and Universities in Shandong Province under Grant 2022KJ009The B6G R&D Group in Shandong University is greatly thanked for channel measurements.
文摘The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential scenarios is vexed by the need for more theoretical support.This paper mainly studies the communication channel between the Tx at semibasement and receiver(Rx)at outdoor.The design of an effective communication system relies on an accurate understanding of channel characteristics.Channel measurements and ray-tracing channel modeling are conducted to obtain channel data.The influence of different positions at same semi-basement is studied.Typical channel characteristics are analyzed,such as power delay profile(PDP),power angular profile(PAP),root-mean-square(RMS)delay spread(DS),channel capacity,received power,and path loss.The influence of different semi-basement placements and different floor heights is also compared.Besides,the channel measurements and simulation data fit well,which can illustrate the validity and reliability of the acquired channel data.This paper can provide theoretical support for the design and optimization of smart meter communication systems in semi-basement scenarios.
基金supported in part by the National Key Research and Development Program of China(2021YFB2900501)in part by the Shaanxi Science and Technology Innovation Team(2023-CX-TD-03)+3 种基金in part by the Science and Technology Program of Shaanxi Province(2021GXLH-Z-038)in part by the Natural Science Foundation of Hunan Province(2023JJ40607 and 2023JJ50045)in part by the Scientific Research Foundation of Hunan Provincial Education Department(23B0713 and 24B0603)in part by the National Natural Science Foundation of China(62401371,62101275,and 62372070).
文摘(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.
基金supported by the National Natural Science Foundation of China,Nos.82172196(to KX),82372507(to KX)the Natural Science Foundation of Hunan Province,China,No.2023JJ40804(to QZ)the Key Laboratory of Emergency and Trauma(Hainan Medical University)of the Ministry of Education,China,No.KLET-202210(to QZ)。
文摘Ischemia–reperfusion injury is a common pathophysiological mechanism in retinal degeneration.PANoptosis is a newly defined integral form of regulated cell death that combines the key features of pyroptosis,apoptosis,and necroptosis.Oligomerization of mitochondrial voltage-dependent anion channel 1 is an important pathological event in regulating cell death in retinal ischemia–reperfusion injury.However,its role in PANoptosis remains largely unknown.In this study,we demonstrated that voltage-dependent anion channel 1 oligomerization-mediated mitochondrial dysfunction was associated with PANoptosis in retinal ischemia–reperfusion injury.Inhibition of voltage-dependent anion channel 1 oligomerization suppressed mitochondrial dysfunction and PANoptosis in retinal cells subjected to ischemia–reperfusion injury.Mechanistically,mitochondria-derived reactive oxygen species played a central role in the voltagedependent anion channel 1-mediated regulation of PANoptosis by promoting PANoptosome assembly.Moreover,inhibiting voltage-dependent anion channel 1 oligomerization protected against PANoptosis in the retinas of rats subjected to ischemia–reperfusion injury.Overall,our findings reveal the critical role of voltage-dependent anion channel 1 oligomerization in regulating PANoptosis in retinal ischemia–reperfusion injury,highlighting voltage-dependent anion channel 1 as a promising therapeutic target.
基金supported by National Natural Science Foundation(NNSF)of China under Grant 62001351the Foundation of National Key Laboratory of Electromagnetic Environment(6142403220202)the Stability Support Fund for Basic Military Industrial Research Institutes(A240104130).
文摘The orthogonal time frequency space(OTFS)modulation is a novel modulation scheme that can effectively cope with the high Doppler expansion caused by high mobility.Since it modulates data on delay-Doppler(DD)domain and makes full use of the sparse characteristics of DD domain,it has been widely studied to design efficient channel estimation and signal detection schemes.In this paper,we design a novel superimposed pilot pattern with transition band,which replaces the traditional embedded pilot(EP)guard zero-symbols,and perform a two-stage channel estimation.In the first stage,we fully utilize the dispersion characteristics of OTFS signal in DD domain,and use threshold decision to make coarse channel estimation.In the second stage,we use the results of the coarse estimation for iterative signal detection and accurate channel estimation.During the second stage,we make full use of the sparsity of the channel in DD domain,remodel the received signal into the form of sparse channel vector multiplied by channel coefficient matrix,and introduce Doppler index segmentation factor(DISF)to subdivide the Doppler index to solve the problem of fractional Doppler.Simulations reveal that,the scheme proposed in this paper has higher spectral efficiency compared with traditional EP scheme and lower peak-to-average power ratio(PAPR)compared with traditional superimposed pilot scheme.
基金supported by the National Natural Sci-ence Foundation of China(Grant Nos.12404410,12564049,11964013,61975077)the National Key Research and De-velopment Program of China(Grant No.2024ZD0300900)the Jiangxi Provincial Natural Science Foundation(Grant No.20242BAB26009).
文摘Einstein–Podolsky–Rosen(EPR)steering is an important resource for one-sided device-independent quantum information processing.This steering property can be destroyed by the interaction between a quantum system and its environment in practical applications.In this paper,we employ the characteristic function representation of probability distributions to investigate the quantum steering of two-mode continuous-variable states in a laser channel,where both the gain factor and the loss effect are taken into account.Firstly,we analyse the steering time of the two-mode squeezed vacuum state under one-mode and two-mode laser channels,respectively.We find that the gain process introduces additional noise into the two-mode squeezed vacuum state,thereby reducing the steerable time.Secondly,by quantifying EPR steering,we show that two-side loss exhibits smaller steerability than one-side loss,although they share the same two-way steerable time.In addition,we find that the more-gained party can steer the other party’s state,whereas the other party cannot steer the gained party beyond a certain threshold value.In this sense,the gain effect in one party appears to be equivalent to the loss effect in the other party.Our results pave the way for the distillation of EPR steering and quantum information processing in practical quantum channels.
基金supported by a grant(No.CRPG-25-2054)under the Cybersecurity Research and Innovation Pioneers Initiative,provided by the National Cybersecurity Authority(NCA)in the Kingdom of Saudi Arabia.
文摘Split Learning(SL)has been promoted as a promising collaborative machine learning technique designed to address data privacy and resource efficiency.Specifically,neural networks are divided into client and server subnetworks in order to mitigate the exposure of sensitive data and reduce the overhead on client devices,thereby making SL particularly suitable for resource-constrained devices.Although SL prevents the direct transmission of raw data,it does not alleviate entirely the risk of privacy breaches.In fact,the data intermediately transmitted to the server sub-model may include patterns or information that could reveal sensitive data.Moreover,achieving a balance between model utility and data privacy has emerged as a challenging problem.In this article,we propose a novel defense approach that combines:(i)Adversarial learning,and(ii)Network channel pruning.In particular,the proposed adversarial learning approach is specifically designed to reduce the risk of private data exposure while maintaining high performance for the utility task.On the other hand,the suggested channel pruning enables the model to adaptively adjust and reactivate pruned channels while conducting adversarial training.The integration of these two techniques reduces the informativeness of the intermediate data transmitted by the client sub-model,thereby enhancing its robustness against attribute inference attacks without adding significant computational overhead,making it wellsuited for IoT devices,mobile platforms,and Internet of Vehicles(IoV)scenarios.The proposed defense approach was evaluated using EfficientNet-B0,a widely adopted compact model,along with three benchmark datasets.The obtained results showcased its superior defense capability against attribute inference attacks compared to existing state-of-the-art methods.This research’s findings demonstrated the effectiveness of the proposed channel pruning-based adversarial training approach in achieving the intended compromise between utility and privacy within SL frameworks.In fact,the classification accuracy attained by the attackers witnessed a drastic decrease of 70%.
文摘[Objective]As wireless power transfer(WPT)technology is increasingly deployed in scenarios such as electric vehicles,metallic foreign objects in the WPT area may cause local overheating and energy loss.Existing methods still suffer from poor edge/corner sensitivity,misjudgment due to fixed thresholds,and limited ability to extract position information.This work proposes a wireless power transfer-foreign object detection(WPT-FOD)method based on channel differential response and a dynamic-threshold corner-enhancement strategy,aiming to improve detection sensitivity,localization accuracy,and robustness without altering the overall coil layout.[Method]A multi-channel detection coil array is designed,and the self-inductance disturbance response of each channel coil is modeled.A channel-difference mapping mechanism is introduced to build a 2-D sensitivity matrix to characterize spatial position correlation.A corner-enhancement algorithm is developed to weight and amplify the collaborative response of adjacent channels,and a dynamic threshold adjustment mechanism is integrated to adapt to varying interference levels.Validation is carried out on a self-built 64-channel FOD platform by moving a typical metallic foreign object across central,edge,and corner regions,and by conducting comparative tests under different interference intensities.[Result]When a typical metallic foreign object moves to corner regions,the self-inductance disturbance of the detection coil increases from less than 0.02μH to more than 0.06μH,significantly enhancing the discrimination capability at corners.Under varying interference strengths,the dynamic threshold mechanism reduces the number of false positives from 13 to 2,demonstrating good environmental adaptability and stability.[Conclusion]By combining channel differential response,corner enhancement,and dynamic thresholding,the proposed WPT-FOD effectively mitigates edge/corner blind spots and fixed-threshold misjudgment,while providing localization capability and robustness.It markedly improves the accuracy of metallic foreign object detection in WPT systems and offers a feasible path and method reference for the safe application and engineering deployment of WPT systems.
文摘The present study investigates the flow,heat,and mass transfer analysis in the bioconvection of nanofluid containing motile gyrotactic microorganisms through a semi-porous curved oscillatory channel with a magnetic field.These microorganisms produce density gradients by swimming,which induces macroscopic convection flows in the fluid.This procedure improves the mass and heat transfer,illustrating the interaction between biological activity and fluid dynamics.Furthermore,instead of considering traditional Fourier's and Fick's law the energy and concentration equations are developed by incorporating Cattaneo-Christov double diffusion theory.Moreover,to examine the influence of thermophoresis and Brownian diffusions in the fluid we have adopted the Buongiorno nanofluid model.Due to the oscillation of the surface of the channel,the mathematical development of the considered flow problem is obtained in the form of partial differential equations via the curvilinear coordinate system.The convergent series solution of the governing flow equations is obtained after applying the homotopy analysis method(HAM).The effects of different pertinent flow parameters on velocity,motile microorganism density distribution,concentration,pressure,temperature,and skin friction coefficient are examined and discussed in detail with the help of graphs and tables.It is observed during the current study that the density of microorganisms is enhanced for higher values of Reynolds number,Peclet number,radius of curvature variable,and Lewis number.
基金supported by National Natural Science Foundation of China(NSFC)under grant U23A20310.
文摘With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State Information(CSI)offers fine-grained temporal,frequency,and spatial insights into multipath propagation,making it a crucial data source for human-centric sensing.Recently,the integration of deep learning has significantly improved the robustness and automation of feature extraction from CSI in complex environments.This paper provides a comprehensive review of deep learning-enhanced human sensing based on CSI.We first outline mainstream CSI acquisition tools and their hardware specifications,then provide a detailed discussion of preprocessing methods such as denoising,time–frequency transformation,data segmentation,and augmentation.Subsequently,we categorize deep learning approaches according to sensing tasks—namely detection,localization,and recognition—and highlight representative models across application scenarios.Finally,we examine key challenges including domain generalization,multi-user interference,and limited data availability,and we propose future research directions involving lightweight model deployment,multimodal data fusion,and semantic-level sensing.
基金supported by the Natural Science Foundation of China (NSFC,No.52372212)。
文摘Photocatalysis uses solar energy to convert nitrogen and water directly into ammonia,helping reduce dependence on fossil fuels and offering a way to integrate the nitrogen cycle into a clean energy network.Ohmic junctions between metals and semiconductors have demonstrated significant advantages in enhancing stability and reducing carrier recombination,but their application in photocatalytic nitrogen fixation is limited due to the difficulty of work function matching and the complexity of fabrication processes.In this study,density functional theory(DFT) calculations were used to confirm the work function matching between Bi and Bi_(2)Ti_(2)O_(7)(BTO),ensuring the formation of an Ohmic junction.A Bi-Bi_(2)Ti_(2)O_(7)(B-BTO) composite was successfully synthesized via a one-step hydrothermal method,using bismuth nitrate and titanium sulfate as precursors.Compared to pure BTO,the B-BTO heterojunction,driven by dual electron injection from both metal Bi and BTO,significantly increased the ammonia synthesis rate to 686.95 μmol g^(-1)h^(-1),making it the most active nitrogen fixation material among similar pyrochlorebased catalysts to date.The differential charge density calculations,photocurrent(i-t) measurements,and photoluminescence(PL) tests further validate the role of Ohmic contacts in enhancing charge transfer and prolonging carrier lifetimes.This research provides valuable insight into the application of Ohmic junctions in photocatalytic nitrogen fixation and contributes to advancements in this field.
基金supported in part by the National Key Research and Development Program of China under Grant No.2024YFE0200600the Zhejiang Provincial Natural Science Foundation of China under Grant No.LR23F010005the Huawei Cooperation Project under Grant No.TC20240829036。
文摘Along with the proliferating research interest in semantic communication(Sem Com),joint source channel coding(JSCC)has dominated the attention due to the widely assumed existence in efficiently delivering information semantics.Nevertheless,this paper challenges the conventional JSCC paradigm and advocates for adopting separate source channel coding(SSCC)to enjoy a more underlying degree of freedom for optimization.We demonstrate that SSCC,after leveraging the strengths of the Large Language Model(LLM)for source coding and Error Correction Code Transformer(ECCT)complemented for channel coding,offers superior performance over JSCC.Our proposed framework also effectively highlights the compatibility challenges between Sem Com approaches and digital communication systems,particularly concerning the resource costs associated with the transmission of high-precision floating point numbers.Through comprehensive evaluations,we establish that assisted by LLM-based compression and ECCT-enhanced error correction,SSCC remains a viable and effective solution for modern communication systems.In other words,separate source channel coding is still what we need.
基金supported by the National Natural Science Foundation of China,Nos.81901098(to TC),82201668(to HL)Fujian Provincial Health Technology Project,No.2021QNA072(to HL)。
文摘The central nervous system, information integration center of the body, is mainly composed of neurons and glial cells. The neuron is one of the most basic and important structural and functional units of the central nervous system, with sensory stimulation and excitation conduction functions. Astrocytes and microglia belong to the glial cell family, which is the main source of cytokines and represents the main defense system of the central nervous system. Nerve cells undergo neurotransmission or gliotransmission, which regulates neuronal activity via the ion channels, receptors, or transporters expressed on nerve cell membranes. Ion channels, composed of large transmembrane proteins, play crucial roles in maintaining nerve cell homeostasis. These channels are also important for control of the membrane potential and in the secretion of neurotransmitters. A variety of cellular functions and life activities, including functional regulation of the central nervous system, the generation and conduction of nerve excitation, the occurrence of receptor potential, heart pulsation, smooth muscle peristalsis, skeletal muscle contraction, and hormone secretion, are closely related to ion channels associated with passive transmembrane transport. Two types of ion channels in the central nervous system, potassium channels and calcium channels, are closely related to various neurological disorders, including Alzheimer's disease, Parkinson's disease, and epilepsy. Accordingly, various drugs that can affect these ion channels have been explored deeply to provide new directions for the treatment of these neurological disorders. In this review, we focus on the functions of potassium and calcium ion channels in different nerve cells and their involvement in neurological disorders such as Parkinson's disease, Alzheimer's disease, depression, epilepsy, autism, and rare disorders. We also describe several clinical drugs that target potassium or calcium channels in nerve cells and could be used to treat these disorders. We concluded that there are few clinical drugs that can improve the pathology these diseases by acting on potassium or calcium ions. Although a few novel ion-channelspecific modulators have been discovered, meaningful therapies have largely not yet been realized. The lack of target-specific drugs, their requirement to cross the blood–brain barrier, and their exact underlying mechanisms all need further attention. This review aims to explain the urgent problems that need research progress and provide comprehensive information aiming to arouse the research community's interest in the development of ion channel-targeting drugs and the identification of new therapeutic targets for that can increase the cure rate of nervous system diseases and reduce the occurrence of adverse reactions in other systems.
文摘Channel characterization and modeling are fundamental to communication system design,development,testing,and deployment.As the innate digital twins of wireless channels,channel models replicate real-world channel behaviors,e.g.,large-scale/small-scale fading,spatio-temporal-frequency non-stationarity,through mathematical and data-driven methods.This enables simulation-based validation across system development stages—from protocol design to network optimization-without costly physical testing.
基金supported by Fundamental Research Funds for the Central Universities(No.2024YJS078)the National Natural Science Foundation of China(No.62341127,62221001 and 62171021)+1 种基金the Fundamental Research Funds for the Natural Science Foundation of Jiangsu Province,Major Project(No.BK2021200)the Key Research and Development Program of Zhejiang Province(No.2023C01003)。
文摘With the development of wireless communication,the fifth generation mobile communication technology(5G)has emerged as a hot topic in highspeed railway communication system and has moved towards industrial application.Investigating the radio propagation characteristics in 5G high-speed train(HST)scenarios is essential for enhancing wireless coverage and overall system performance.We propose a novel 5G passive sounding scheme to extract channel impulse responses(CIRs)using channel state information reference signals(CSI-RS)from the target 5G base station(BS).Detailed procedures for timefrequency synchronization,CSI-RS detection and extraction are presented through simulations.Through the laboratory work involving absolute power calibration,phase coherence calibration and power delay profile(PDP)validation,we validate the accuracy and performance of the developed platform.Furthermore,a measurement campaign was conducted in HST scenarios encompassing both residential and undeveloped areas.The path loss(PL)model and the channel characteristics including stationarity interval(SI),multipath components(MPCs),shadow fading(SF),Rician K-factor,root mean square(RMS)delay spread and received correlation coefficients are analyzed and fitted.The estimated channel characteristics and the statistical model presented in this paper will contribute to the research on HST radio propagation and the development of 5G railway communication systems.
基金supported by the National Key R&D Program of China under Grant No.2023YFB2904802National Natural Science Foundation of China under Grant Nos.62301022,62221001,62431003,and 62101507+1 种基金Young Elite Scientists Sponsorship Program by CAST under Grant No.2022QNRC001Program for Science&Technology R&D Plan Joint Fund of Henan Province under Grant No.225200810112。
文摘Reliable channel data helps characterize the limitations and performance boundaries of communication technologies accurately.However,channel measurement is highly costly and time-consuming,and taking actual measurement as the only channel data source may reduce efficiency because of the constraints of high testing difficulty and limited data volume.Although existing standard channel models can generate channel data,their authenticity and diversity cannot be guaranteed.To address this,we use deep learning methods to learn the attributes of limited measured data and propose a generative model based on generative adversarial networks to rapidly synthesize data.A software simulation platform is also established to verify that the proposed model can generate data that are statistically similar to the measured data while maintaining necessary randomness.The proposed algorithm and platform can be applied to channel data enhancement and serve channel modeling and algorithm evaluation applications with urgent needs for data.
基金supported in part by the National Key R&D Program of China under Grant 2021YFB1714100in part by the Shenzhen Science and Technology Program,China,under Grant JCYJ20220531101015033.
文摘With increasing density and heterogeneity in unlicensed wireless networks,traditional MAC protocols,such as Carrier Sense Multiple Access with Collision Avoidance(CSMA/CA)in Wi-Fi networks,are experiencing performance degradation.This is manifested in increased collisions and extended backoff times,leading to diminished spectrum efficiency and protocol coordination.Addressing these issues,this paper proposes a deep-learning-based MAC paradigm,dubbed DL-MAC,which leverages spectrum data readily available from energy detection modules in wireless devices to achieve the MAC functionalities of channel access,rate adaptation,and channel switch.First,we utilize DL-MAC to realize a joint design of channel access and rate adaptation.Subsequently,we integrate the capability of channel switching into DL-MAC,enhancing its functionality from single-channel to multi-channel operations.Specifically,the DL-MAC protocol incorporates a Deep Neural Network(DNN)for channel selection and a Recurrent Neural Network(RNN)for the joint design of channel access and rate adaptation.We conducted real-world data collection within the 2.4 GHz frequency band to validate the effectiveness of DL-MAC.Experimental results demonstrate that DL-MAC exhibits significantly superior performance compared to traditional algorithms in both single and multi-channel environments,and also outperforms single-function designs.Additionally,the performance of DL-MAC remains robust,unaffected by channel switch overheads within the evaluation range.
基金supported in part by the Young Scientists Fund of the National Natural Science Foundation of China(No.62201087)in part by the National Natural Science Foundation of China(No.62525101,62341128)+3 种基金in part by the National Key R&D Program of China(No.2023YFB2904803)in part by the Guangdong Major Project of Basic and Applied Basic Research(No.2023B0303000001)in part by the Beijing Natural Science Foundation(No.L243002)in part by the Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint innovation Center.
文摘Integrated Sensing and Communication(ISAC)is considered a key technology in 6G networks.An accurate sensing channel model is crucial for the design and sensing performance evaluation of ISAC systems.The widely used Geometry-Based Stochastic Model(GBSM),typically applied in standardized channel modeling,mainly focuses on the statistical fading characteristics of the channel.However,it fails to capture the characteristics of targets in ISAC systems,such as their positions and velocities,as well as the impact of the targets on the background.To address this issue,this paper proposes an Extended-GBSM(E-GBSM)sensing channel model that incorporates newly discovered channel characteristics into a unified modeling framework.In this framework,the sensing channel is divided into target and background channels.For the target channel,the model introduces a concatenated modeling approach,while for the background channel,a parameter called the power control factor is introduced to assess impact of the target on the background channel,making the modeling framework applicable to both mono-static and bi-static sensing modes.To validate the proposed model’s effectiveness,measurements of target and background channels are conducted across a wide range of indoor and outdoor scenarios,covering various sensing targets such as metal plates,reconfigurable intelligent surfaces,human bodies,unmanned aerial vehicles,and vehicles.The experimental results provide important theoretical support and empirical data for the standardization of ISAC channel modeling.
