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
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
The advent of 6G wireless networks promises unprecedented connectivity,supporting ultra-high data rates,low latency,and massive device connectivity.However,these ambitious goals introduce significant challenges,partic...The advent of 6G wireless networks promises unprecedented connectivity,supporting ultra-high data rates,low latency,and massive device connectivity.However,these ambitious goals introduce significant challenges,particularly in channel estimation due to complex and dynamic propagation environments.This paper explores the concept of channel knowledge maps(CKMs)as a solution to these challenges.CKMs enable environment-aware communications by providing location-specific channel information,reducing reliance on real-time pilot measurements.We categorize CKM construction techniques into measurement-based,model-based,and hybrid methods,and examine their key applications in integrated sensing and communication(ISAC)systems,beamforming,trajectory optimization of unmanned aerial vehicles(UAVs),base station(BS)placement,and resource allocation.Furthermore,we discuss open challenges and propose future research directions to enhance the robustness,accuracy,and scalability of CKM-based systems in the evolving 6G landscape.展开更多
Channel state information(CSI)is very important to sparse code multiple access combined with orthogonal frequency division multiplexing(SCMA-OFDM)systems for data detection.The main goal of this paper is to tackle the...Channel state information(CSI)is very important to sparse code multiple access combined with orthogonal frequency division multiplexing(SCMA-OFDM)systems for data detection.The main goal of this paper is to tackle the computational complexity and pilot overhead issues when estima-ting and tracking the channel frequency response of each user in uplink SCMA-OFDM systems.To this end,a new binary pilot structure is first designed to realize the initial channel estimation with significantly reduced computational complexity.Then,a channel tracking method is proposed to update the channel estimation in time-varying channels,which exploits a modified least mean square(LMS)technique with the feedback from the detector.Simulation results show that the pro-posed pilot structure can provide accurate channel estimation results.Moreover,the average bit error rate(BER)performance of the modified LMS algorithm can approach that of a detector with perfect CSI within 2 dB at the normalized Doppler frequency up to 6×10^(-6).展开更多
Wireless communication systems that incorporate digital twin(DT)alongside artificial intelligence(AI)are expected to transform 6G networks by providing advanced features for predictive modeling and decision making.The...Wireless communication systems that incorporate digital twin(DT)alongside artificial intelligence(AI)are expected to transform 6G networks by providing advanced features for predictive modeling and decision making.The key component is the creation of DT channels,which form the basis for upcoming applications.However,the existing work of channel predictive generation only considers time dimension,distribution-oriented or multi-step slidingwindow prediction schemes,which is not accurate and efficient for real-time DT communication systems.Therefore,we propose the wireless channel generative adversarial network(WCGAN)to tackle the issue of generating authentic long-batch channels for DT applications.The generator based on convolutional neural networks(CNN)extracts features from both the time and frequency domains to better capture the correlation.The loss function is designed to ensure that the generated channels consistently match the physical channels over an extended period while sharing the same probability distributions.Meanwhile,the accumulating error from the slicing window has been alleviated.The simulation demonstrates that an accurate and efficient DT channel can be generated by employing our proposed WCGAN in various scenarios.展开更多
Reconfigurable intelligent surface(RIS)is a promising candidate technology of the upcoming Sixth Generation(6G)communication system for its ability to provide unprecedented spectral and energy efficiency increment thr...Reconfigurable intelligent surface(RIS)is a promising candidate technology of the upcoming Sixth Generation(6G)communication system for its ability to provide unprecedented spectral and energy efficiency increment through passive beamforming.However,it is challenging to obtain instantaneous channel state information(I-CSI)for RIS,which obliges us to use statistical channel state information(S-CSI)to achieve passive beamforming.In this paper,RIS-aided multiple-input single-output(MISO)multi-user downlink communication system with correlated channels is investigated.Then,we formulate the problem of joint beamforming design at the AP and RIS to maximize the sum ergodic spectral efficiency(ESE)of all users to improve the network capacity.Since it is too hard to compute sum ESE,an ESE approximation is adopted to reformulate the problem into a more tractable form.Then,we present two joint beamforming algorithms,namely the singular value decomposition-gradient descent(SVD-GD)algorithm and the fractional programming-gradient descent(FP-GD)algorithm.Simulation results show the effectiveness of our proposed algorithms and validate that 2-bits quantizer is enough for RIS phase shifts implementation.展开更多
Aiming at the problems of low detection accuracy and large model size of existing object detection algorithms applied to complex road scenes,an improved you only look once version 8(YOLOv8)object detection algorithm f...Aiming at the problems of low detection accuracy and large model size of existing object detection algorithms applied to complex road scenes,an improved you only look once version 8(YOLOv8)object detection algorithm for infrared images,F-YOLOv8,is proposed.First,a spatial-to-depth network replaces the traditional backbone network's strided convolution or pooling layer.At the same time,it combines with the channel attention mechanism so that the neural network focuses on the channels with large weight values to better extract low-resolution image feature information;then an improved feature pyramid network of lightweight bidirectional feature pyramid network(L-BiFPN)is proposed,which can efficiently fuse features of different scales.In addition,a loss function of insertion of union based on the minimum point distance(MPDIoU)is introduced for bounding box regression,which obtains faster convergence speed and more accurate regression results.Experimental results on the FLIR dataset show that the improved algorithm can accurately detect infrared road targets in real time with 3%and 2.2%enhancement in mean average precision at 50%IoU(mAP50)and mean average precision at 50%—95%IoU(mAP50-95),respectively,and 38.1%,37.3%and 16.9%reduction in the number of model parameters,the model weight,and floating-point operations per second(FLOPs),respectively.To further demonstrate the detection capability of the improved algorithm,it is tested on the public dataset PASCAL VOC,and the results show that F-YOLO has excellent generalized detection performance.展开更多
In this paper,a physical model of RIS of bistatic polarized radar cross section is derived starting from the Stratton-Chu equations under the assumptions of physical optics,PEC,far field and rectangular RIS element.In...In this paper,a physical model of RIS of bistatic polarized radar cross section is derived starting from the Stratton-Chu equations under the assumptions of physical optics,PEC,far field and rectangular RIS element.In the context of important physical characteristics of the backscattering polarization of RIS,the modeling of the RIS wireless channel requires a tradeoff between complexity and accuracy,as well as usability and simplicity.For channel modeling of RIS systems,RIS is modelled as multi-equivalent virtual base stations(BSs)induced by multi polarized electromagnetic waves from different incident directions.The comparison between test and simulation results demonstrates that the proposed algorithm effectively captures the key characteristics of the general RIS element polarization physical model and provides accurate results.展开更多
As important infrastructure for airborne communication platforms,unmanned aerial vehicles(UAVs)are expected to become a key part of 6G wireless networks.Thus,modeling low-and medium-altitude propagation channels has a...As important infrastructure for airborne communication platforms,unmanned aerial vehicles(UAVs)are expected to become a key part of 6G wireless networks.Thus,modeling low-and medium-altitude propagation channels has attracted much attention.Air-to-ground(A2G)propagation channel models vary in different scenarios,requiring accurate models for designing and evaluating UAV communication links.Unlike terrestrial models,A2G channel models lack detailed investigation.Therefore,this paper provides an overview of existing A2G channel measurement campaigns,different types of A2G channel models for various environments,and future research directions for UAV airland channel modeling.This study focuses on the potential of millimeter-wave technology for UAV A2G channel modeling and highlights nonsuburban scenarios requiring consideration in future modeling efforts.展开更多
This research study focuses on addressing the limitations of current neuropathic pain(NP)treatments by developing a novel dual-target modulator,E0199,targeting both Na_(V)1.7,Na_(V)1.8,and Na_(V)1.9 and K_(V)7 channel...This research study focuses on addressing the limitations of current neuropathic pain(NP)treatments by developing a novel dual-target modulator,E0199,targeting both Na_(V)1.7,Na_(V)1.8,and Na_(V)1.9 and K_(V)7 channels,a crucial regulator in controlling NP symptoms.The objective of the study was to synthesize a compound capable of modulating these channels to alleviate NP.Through an experimental design involving both in vitro and in vivo methods,E0199 was tested for its efficacy on ion channels and its therapeutic potential in a chronic constriction injury(CCI)mouse model.The results demonstrated that E0199 significantly inhibited Na_(V)1.7,Na_(V)1.8,and Na_(V)1.9 channels with a particularly low half maximal inhibitory concentration(IC50)for Na_(V)1.9 by promoting sodium channel inactivation,and also effectively increased K_(V)7.2/7.3,K_(V)7.2,and K_(V)7.5 channels,excluding K_(V)7.1 by promoting potassium channel activation.This dual action significantly reduced the excitability of dorsal root ganglion neurons and alleviated pain hypersensitivity in mice at low doses,indicating a potent analgesic effect without affecting heart and skeletal muscle ion channels critically.The safety of E0199 was supported by neurobehavioral evaluations.Conclusively,E0199 represents a ground-breaking approach in NP treatment,showcasing the potential of dual-target small-molecule compounds in providing a more effective and safe therapeutic option for NP.This study introduces a promising direction for the future development of NP therapeutics.展开更多
The distribution of the sediment material storage quantity along the debris flow channels(SMSQ_DFC)can provide a foundation for runoffgenerated debris flow prediction or susceptibility assessment.Current models for es...The distribution of the sediment material storage quantity along the debris flow channels(SMSQ_DFC)can provide a foundation for runoffgenerated debris flow prediction or susceptibility assessment.Current models for estimating SMSQ_DFC do not consider the capacity of the channel cross-section to accommodate sediment materials.This accommodation condition serves as a limiting factor in determining whether the expected surplus of sediment materials can ultimately be stored.To address this issue,a mass-conservative index was used to represent the balance of deposit materials at any cross-section,considering the influx from upstream,outflux to downstream,and accommodation capacity.Based on this index,a new model for estimating SMSQ_DFC was developed and subsequently evaluated.The evaluation results show that the model meets the accuracy requirements with average error rates of 14.06%for self-validation and 14.81%for generalization ability validation.To assess its practical applications,the model was applied to the Yeniu Gully in Wenchuan County,Sichuan Province,an area with detailed field survey data.The results show that the model exhibits a commendable performance.Compared to traditional theoretical and semi-theoretical statistical models,our model is easier to use(input parameters can be obtained using Geographic Information Systems(GIS)).The modeling parameters chosen in this study have more theoretical significance than those used in existing purely statistical models,offering more effective technical support for estimating SMSQ_DFC.展开更多
Deep learning-based semantic communication has achieved remarkable progress with CNNs and Transformers.However,CNNs exhibit constrained performance in high-resolution image transmission,while Transformers incur high c...Deep learning-based semantic communication has achieved remarkable progress with CNNs and Transformers.However,CNNs exhibit constrained performance in high-resolution image transmission,while Transformers incur high computational cost due to quadratic complexity.Recently,VMamba,a novel state space model with linear complexity and exceptional long-range dependency modeling capabilities,has shown great potential in computer vision tasks.Inspired by this,we propose MNTSCC,an efficient VMamba-based nonlinear joint source-channel coding(JSCC)model for wireless image transmission.Specifically,MNTSCC comprises a VMamba-based nonlinear transform module,an MCAM entropy model,and a JSCC module.In the encoding stage,the input image is first encoded into a latent representation via the nonlinear transformation module,which is then processed by the MCAM for source distribution modeling.The JSCC module then optimizes transmission efficiency by adaptively assigning transmission rate to the latent representation according to the estimated entropy values.The proposedMCAMenhances the channel-wise autoregressive entropy model with attention mechanisms,which enables the entropy model to effectively capture both global and local information within latent features,thereby enabling more accurate entropy estimation and improved rate-distortion performance.Additionally,to further enhance the robustness of the system under varying signal-to-noise ratio(SNR)conditions,we incorporate SNR adaptive net(SAnet)into the JSCCmodule,which dynamically adjusts the encoding strategy by integrating SNRinformationwith latent features,thereby improving SNR adaptability.Experimental results across diverse resolution datasets demonstrate that the proposed method achieves superior image transmission performance compared to existing CNN-and Transformer-based semantic communication models,while maintaining competitive computational efficiency.In particular,under an Additive White Gaussian Noise(AWGN)channel with SNR=10 dB and a channel bandwidth ratio(CBR)of 1/16,MNTSCC consistently outperforms NTSCC,achieving a 1.72 dB Peak Signal-to-Noise Ratio(PSNR)gain on the Kodak24 dataset,0.79 dB on CLIC2022,and 2.54 dB on CIFAR-10,while reducing computational cost by 32.23%.The code is available at https://github.com/WanChen10/MNTSCC(accessed on 09 July 2025).展开更多
From the perspective of state-channel interaction,standard quantum teleportation can be viewed as a communication process characterized by both input and output,functioning as a quantum depolarizing channel.To achieve...From the perspective of state-channel interaction,standard quantum teleportation can be viewed as a communication process characterized by both input and output,functioning as a quantum depolarizing channel.To achieve a precise quantification of the quantumness introduced by this channel,we examine its uncertainties,which encompass both statedependent and state-independent uncertainties.Specifically,for qudit systems,we provide general formulas for these uncertainties.We analyze the uncertainties associated with standard quantum teleportation when induced by isotropic states,Werner states,and X-states,and we elucidate the correlation between these uncertainties and the parameters of the specific mixed states.Our findings demonstrate the validity of quantifying these uncertainties.展开更多
We propose a photon-photon collider based on synchrotron gamma sources driven by relativistic electron beams in hollow plasma channels.The collimated(with a divergence angle of~1 mrad)and ultrabrilliant(>10^(28)pho...We propose a photon-photon collider based on synchrotron gamma sources driven by relativistic electron beams in hollow plasma channels.The collimated(with a divergence angle of~1 mrad)and ultrabrilliant(>10^(28)photons s^(-1)·mrad^(-2)·mm^(-2)per 0.1% bandwidth at 0.6 MeV)photon beams are generated by strong electromagnetic fields induced by current filamentation instability,and up to~10^(6) Breit-Wheeler(BW)pairs can be created per shot.Notably,the usage of hollow plasma channels not only enhances synchrotron radiation,but also allows flexible control of the produced photon beams,ensuring the alignment of the two colliding beams and maximizing the two-photon BW process.This setup has the advantage of a clean background by eliminating the yield from the nonlinear BW process,and the signal-to-noise ratio is higher than 10^(2).展开更多
This study numerically examines the heat and mass transfer characteristics of two ternary nanofluids via converging and diverg-ing channels.Furthermore,the study aims to assess two ternary nanofluids combinations to d...This study numerically examines the heat and mass transfer characteristics of two ternary nanofluids via converging and diverg-ing channels.Furthermore,the study aims to assess two ternary nanofluids combinations to determine which configuration can provide better heat and mass transfer and lower entropy production,while ensuring cost efficiency.This work bridges the gap be-tween academic research and industrial feasibility by incorporating cost analysis,entropy generation,and thermal efficiency.To compare the velocity,temperature,and concentration profiles,we examine two ternary nanofluids,i.e.,TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O and TiO_(2)+SiO_(2)+Cu/H_(2)O,while considering the shape of nanoparticles.The velocity slip and Soret/Dufour effects are taken into consideration.Furthermore,regression analysis for Nusselt and Sherwood numbers of the model is carried out.The Runge-Kutta fourth-order method with shooting technique is employed to acquire the numerical solution of the governed system of ordinary differential equations.The flow pattern attributes of ternary nanofluids are meticulously examined and simulated with the fluc-tuation of flow-dominating parameters.Additionally,the influence of these parameters is demonstrated in the flow,temperature,and concentration fields.For variation in Eckert and Dufour numbers,TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O has a higher temperature than TiO_(2)+SiO_(2)+Cu/H_(2)O.The results obtained indicate that the ternary nanofluid TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O has a higher heat transfer rate,lesser entropy generation,greater mass transfer rate,and lower cost than that of TiO_(2)+SiO_(2)+Cu/H_(2)O ternary nanofluid.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 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 by the National Natural Science Foundation of China under Grants Nos.62431014 and 62271310the Fundamental Research Funds for the Central Universities of China。
文摘The advent of 6G wireless networks promises unprecedented connectivity,supporting ultra-high data rates,low latency,and massive device connectivity.However,these ambitious goals introduce significant challenges,particularly in channel estimation due to complex and dynamic propagation environments.This paper explores the concept of channel knowledge maps(CKMs)as a solution to these challenges.CKMs enable environment-aware communications by providing location-specific channel information,reducing reliance on real-time pilot measurements.We categorize CKM construction techniques into measurement-based,model-based,and hybrid methods,and examine their key applications in integrated sensing and communication(ISAC)systems,beamforming,trajectory optimization of unmanned aerial vehicles(UAVs),base station(BS)placement,and resource allocation.Furthermore,we discuss open challenges and propose future research directions to enhance the robustness,accuracy,and scalability of CKM-based systems in the evolving 6G landscape.
基金Supported by the National Natural Science Foundation of China(No.62171135)the Natural Science Foundation of Fujian Province(No.2023J01399)。
文摘Channel state information(CSI)is very important to sparse code multiple access combined with orthogonal frequency division multiplexing(SCMA-OFDM)systems for data detection.The main goal of this paper is to tackle the computational complexity and pilot overhead issues when estima-ting and tracking the channel frequency response of each user in uplink SCMA-OFDM systems.To this end,a new binary pilot structure is first designed to realize the initial channel estimation with significantly reduced computational complexity.Then,a channel tracking method is proposed to update the channel estimation in time-varying channels,which exploits a modified least mean square(LMS)technique with the feedback from the detector.Simulation results show that the pro-posed pilot structure can provide accurate channel estimation results.Moreover,the average bit error rate(BER)performance of the modified LMS algorithm can approach that of a detector with perfect CSI within 2 dB at the normalized Doppler frequency up to 6×10^(-6).
文摘Wireless communication systems that incorporate digital twin(DT)alongside artificial intelligence(AI)are expected to transform 6G networks by providing advanced features for predictive modeling and decision making.The key component is the creation of DT channels,which form the basis for upcoming applications.However,the existing work of channel predictive generation only considers time dimension,distribution-oriented or multi-step slidingwindow prediction schemes,which is not accurate and efficient for real-time DT communication systems.Therefore,we propose the wireless channel generative adversarial network(WCGAN)to tackle the issue of generating authentic long-batch channels for DT applications.The generator based on convolutional neural networks(CNN)extracts features from both the time and frequency domains to better capture the correlation.The loss function is designed to ensure that the generated channels consistently match the physical channels over an extended period while sharing the same probability distributions.Meanwhile,the accumulating error from the slicing window has been alleviated.The simulation demonstrates that an accurate and efficient DT channel can be generated by employing our proposed WCGAN in various scenarios.
基金partially supported by the National Key Research and Development Project under Grant 2020YFB1806805Science and Technology on Communication Networks Laboratorysupported by China Scholarship Council.
文摘Reconfigurable intelligent surface(RIS)is a promising candidate technology of the upcoming Sixth Generation(6G)communication system for its ability to provide unprecedented spectral and energy efficiency increment through passive beamforming.However,it is challenging to obtain instantaneous channel state information(I-CSI)for RIS,which obliges us to use statistical channel state information(S-CSI)to achieve passive beamforming.In this paper,RIS-aided multiple-input single-output(MISO)multi-user downlink communication system with correlated channels is investigated.Then,we formulate the problem of joint beamforming design at the AP and RIS to maximize the sum ergodic spectral efficiency(ESE)of all users to improve the network capacity.Since it is too hard to compute sum ESE,an ESE approximation is adopted to reformulate the problem into a more tractable form.Then,we present two joint beamforming algorithms,namely the singular value decomposition-gradient descent(SVD-GD)algorithm and the fractional programming-gradient descent(FP-GD)algorithm.Simulation results show the effectiveness of our proposed algorithms and validate that 2-bits quantizer is enough for RIS phase shifts implementation.
基金supported by the National Natural Science Foundation of China(No.62103298)。
文摘Aiming at the problems of low detection accuracy and large model size of existing object detection algorithms applied to complex road scenes,an improved you only look once version 8(YOLOv8)object detection algorithm for infrared images,F-YOLOv8,is proposed.First,a spatial-to-depth network replaces the traditional backbone network's strided convolution or pooling layer.At the same time,it combines with the channel attention mechanism so that the neural network focuses on the channels with large weight values to better extract low-resolution image feature information;then an improved feature pyramid network of lightweight bidirectional feature pyramid network(L-BiFPN)is proposed,which can efficiently fuse features of different scales.In addition,a loss function of insertion of union based on the minimum point distance(MPDIoU)is introduced for bounding box regression,which obtains faster convergence speed and more accurate regression results.Experimental results on the FLIR dataset show that the improved algorithm can accurately detect infrared road targets in real time with 3%and 2.2%enhancement in mean average precision at 50%IoU(mAP50)and mean average precision at 50%—95%IoU(mAP50-95),respectively,and 38.1%,37.3%and 16.9%reduction in the number of model parameters,the model weight,and floating-point operations per second(FLOPs),respectively.To further demonstrate the detection capability of the improved algorithm,it is tested on the public dataset PASCAL VOC,and the results show that F-YOLO has excellent generalized detection performance.
基金supported by Ministry of Science and Technology of the People’s Republic of China(2020YFB1808101)the Project“5G evolution wireless air interface intelligent R&D and verification public platform project”supported by Ministry of Industry and Information Technology of the People’s Republic of China(TC220A04M).
文摘In this paper,a physical model of RIS of bistatic polarized radar cross section is derived starting from the Stratton-Chu equations under the assumptions of physical optics,PEC,far field and rectangular RIS element.In the context of important physical characteristics of the backscattering polarization of RIS,the modeling of the RIS wireless channel requires a tradeoff between complexity and accuracy,as well as usability and simplicity.For channel modeling of RIS systems,RIS is modelled as multi-equivalent virtual base stations(BSs)induced by multi polarized electromagnetic waves from different incident directions.The comparison between test and simulation results demonstrates that the proposed algorithm effectively captures the key characteristics of the general RIS element polarization physical model and provides accurate results.
基金supported by the National Natural Science Foundation of China under Grant No.42176190Fundamental Research Funds for the Central Universities,CHD under Grant Nos.300102243401 and 300102244203Research Funds for the Interdisciplinary Projects,CHU under Grant Nos.300104240912 and 300104240922。
文摘As important infrastructure for airborne communication platforms,unmanned aerial vehicles(UAVs)are expected to become a key part of 6G wireless networks.Thus,modeling low-and medium-altitude propagation channels has attracted much attention.Air-to-ground(A2G)propagation channel models vary in different scenarios,requiring accurate models for designing and evaluating UAV communication links.Unlike terrestrial models,A2G channel models lack detailed investigation.Therefore,this paper provides an overview of existing A2G channel measurement campaigns,different types of A2G channel models for various environments,and future research directions for UAV airland channel modeling.This study focuses on the potential of millimeter-wave technology for UAV A2G channel modeling and highlights nonsuburban scenarios requiring consideration in future modeling efforts.
基金funded by the Key Project from the Hebei Provincial Department of Science and Technology,China(Grant No.:21372601D)the Foundation Postdoctoral Mobile Station of Basic Medical Sciences,Hebei Medical University,China(Grant No.:20123120019)+4 种基金the Natural Science Foundation of Hebei Province,China(Grant No.:H2021206352)the Science and Technology Research Project of Colleges and Universities in Hebei Province,China(Grant No.:QN2023197)Hebei Medical University,Science and Technology,China(Grant No.:CYQD2023014)Hebei Provincial Department of Human Resources and Social Security,China(Grant No.:B2023003034)the Consultative Foundation from Hebei Province,China(Grant No.:2020TXZH01).
文摘This research study focuses on addressing the limitations of current neuropathic pain(NP)treatments by developing a novel dual-target modulator,E0199,targeting both Na_(V)1.7,Na_(V)1.8,and Na_(V)1.9 and K_(V)7 channels,a crucial regulator in controlling NP symptoms.The objective of the study was to synthesize a compound capable of modulating these channels to alleviate NP.Through an experimental design involving both in vitro and in vivo methods,E0199 was tested for its efficacy on ion channels and its therapeutic potential in a chronic constriction injury(CCI)mouse model.The results demonstrated that E0199 significantly inhibited Na_(V)1.7,Na_(V)1.8,and Na_(V)1.9 channels with a particularly low half maximal inhibitory concentration(IC50)for Na_(V)1.9 by promoting sodium channel inactivation,and also effectively increased K_(V)7.2/7.3,K_(V)7.2,and K_(V)7.5 channels,excluding K_(V)7.1 by promoting potassium channel activation.This dual action significantly reduced the excitability of dorsal root ganglion neurons and alleviated pain hypersensitivity in mice at low doses,indicating a potent analgesic effect without affecting heart and skeletal muscle ion channels critically.The safety of E0199 was supported by neurobehavioral evaluations.Conclusively,E0199 represents a ground-breaking approach in NP treatment,showcasing the potential of dual-target small-molecule compounds in providing a more effective and safe therapeutic option for NP.This study introduces a promising direction for the future development of NP therapeutics.
基金supported by Geological Disaster Patterns and Mitigation Strategies Under River-Reservoir Hydrodynamics in the Three Gorges Reservoir Fluctuation Zone(5000002024CC20004)the National Key Research and Development Program of China(2023YFC3007205)+1 种基金the National Natural Science Foundation of China(No.42271013)the West Light Foundation of the Chinese Academy of Sciences.
文摘The distribution of the sediment material storage quantity along the debris flow channels(SMSQ_DFC)can provide a foundation for runoffgenerated debris flow prediction or susceptibility assessment.Current models for estimating SMSQ_DFC do not consider the capacity of the channel cross-section to accommodate sediment materials.This accommodation condition serves as a limiting factor in determining whether the expected surplus of sediment materials can ultimately be stored.To address this issue,a mass-conservative index was used to represent the balance of deposit materials at any cross-section,considering the influx from upstream,outflux to downstream,and accommodation capacity.Based on this index,a new model for estimating SMSQ_DFC was developed and subsequently evaluated.The evaluation results show that the model meets the accuracy requirements with average error rates of 14.06%for self-validation and 14.81%for generalization ability validation.To assess its practical applications,the model was applied to the Yeniu Gully in Wenchuan County,Sichuan Province,an area with detailed field survey data.The results show that the model exhibits a commendable performance.Compared to traditional theoretical and semi-theoretical statistical models,our model is easier to use(input parameters can be obtained using Geographic Information Systems(GIS)).The modeling parameters chosen in this study have more theoretical significance than those used in existing purely statistical models,offering more effective technical support for estimating SMSQ_DFC.
文摘Deep learning-based semantic communication has achieved remarkable progress with CNNs and Transformers.However,CNNs exhibit constrained performance in high-resolution image transmission,while Transformers incur high computational cost due to quadratic complexity.Recently,VMamba,a novel state space model with linear complexity and exceptional long-range dependency modeling capabilities,has shown great potential in computer vision tasks.Inspired by this,we propose MNTSCC,an efficient VMamba-based nonlinear joint source-channel coding(JSCC)model for wireless image transmission.Specifically,MNTSCC comprises a VMamba-based nonlinear transform module,an MCAM entropy model,and a JSCC module.In the encoding stage,the input image is first encoded into a latent representation via the nonlinear transformation module,which is then processed by the MCAM for source distribution modeling.The JSCC module then optimizes transmission efficiency by adaptively assigning transmission rate to the latent representation according to the estimated entropy values.The proposedMCAMenhances the channel-wise autoregressive entropy model with attention mechanisms,which enables the entropy model to effectively capture both global and local information within latent features,thereby enabling more accurate entropy estimation and improved rate-distortion performance.Additionally,to further enhance the robustness of the system under varying signal-to-noise ratio(SNR)conditions,we incorporate SNR adaptive net(SAnet)into the JSCCmodule,which dynamically adjusts the encoding strategy by integrating SNRinformationwith latent features,thereby improving SNR adaptability.Experimental results across diverse resolution datasets demonstrate that the proposed method achieves superior image transmission performance compared to existing CNN-and Transformer-based semantic communication models,while maintaining competitive computational efficiency.In particular,under an Additive White Gaussian Noise(AWGN)channel with SNR=10 dB and a channel bandwidth ratio(CBR)of 1/16,MNTSCC consistently outperforms NTSCC,achieving a 1.72 dB Peak Signal-to-Noise Ratio(PSNR)gain on the Kodak24 dataset,0.79 dB on CLIC2022,and 2.54 dB on CIFAR-10,while reducing computational cost by 32.23%.The code is available at https://github.com/WanChen10/MNTSCC(accessed on 09 July 2025).
基金Project supported by the National Natural Science Foundation of China(Grant No.12201300).
文摘From the perspective of state-channel interaction,standard quantum teleportation can be viewed as a communication process characterized by both input and output,functioning as a quantum depolarizing channel.To achieve a precise quantification of the quantumness introduced by this channel,we examine its uncertainties,which encompass both statedependent and state-independent uncertainties.Specifically,for qudit systems,we provide general formulas for these uncertainties.We analyze the uncertainties associated with standard quantum teleportation when induced by isotropic states,Werner states,and X-states,and we elucidate the correlation between these uncertainties and the parameters of the specific mixed states.Our findings demonstrate the validity of quantifying these uncertainties.
基金supported by the Fund of the National Key Laboratory of Plasma Physics(Grant No.6142A04230204)the National Natural Science Foundation of China(Project No.12075046).
文摘We propose a photon-photon collider based on synchrotron gamma sources driven by relativistic electron beams in hollow plasma channels.The collimated(with a divergence angle of~1 mrad)and ultrabrilliant(>10^(28)photons s^(-1)·mrad^(-2)·mm^(-2)per 0.1% bandwidth at 0.6 MeV)photon beams are generated by strong electromagnetic fields induced by current filamentation instability,and up to~10^(6) Breit-Wheeler(BW)pairs can be created per shot.Notably,the usage of hollow plasma channels not only enhances synchrotron radiation,but also allows flexible control of the produced photon beams,ensuring the alignment of the two colliding beams and maximizing the two-photon BW process.This setup has the advantage of a clean background by eliminating the yield from the nonlinear BW process,and the signal-to-noise ratio is higher than 10^(2).
基金supported by DST-FIST(Government of India)(Grant No.SR/FIST/MS-1/2017/13)and Seed Money Project(Grant No.DoRDC/733).
文摘This study numerically examines the heat and mass transfer characteristics of two ternary nanofluids via converging and diverg-ing channels.Furthermore,the study aims to assess two ternary nanofluids combinations to determine which configuration can provide better heat and mass transfer and lower entropy production,while ensuring cost efficiency.This work bridges the gap be-tween academic research and industrial feasibility by incorporating cost analysis,entropy generation,and thermal efficiency.To compare the velocity,temperature,and concentration profiles,we examine two ternary nanofluids,i.e.,TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O and TiO_(2)+SiO_(2)+Cu/H_(2)O,while considering the shape of nanoparticles.The velocity slip and Soret/Dufour effects are taken into consideration.Furthermore,regression analysis for Nusselt and Sherwood numbers of the model is carried out.The Runge-Kutta fourth-order method with shooting technique is employed to acquire the numerical solution of the governed system of ordinary differential equations.The flow pattern attributes of ternary nanofluids are meticulously examined and simulated with the fluc-tuation of flow-dominating parameters.Additionally,the influence of these parameters is demonstrated in the flow,temperature,and concentration fields.For variation in Eckert and Dufour numbers,TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O has a higher temperature than TiO_(2)+SiO_(2)+Cu/H_(2)O.The results obtained indicate that the ternary nanofluid TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O has a higher heat transfer rate,lesser entropy generation,greater mass transfer rate,and lower cost than that of TiO_(2)+SiO_(2)+Cu/H_(2)O ternary nanofluid.
