Dear Editor,I am Dr.Ji-Hong Wu,from the Department of Ophthalmology,Eye&ENT Hospital of Fudan University,China.I write to present a case report of retinitis pigmentosa(RP)caused by novel digenic heterozygous mutati...Dear Editor,I am Dr.Ji-Hong Wu,from the Department of Ophthalmology,Eye&ENT Hospital of Fudan University,China.I write to present a case report of retinitis pigmentosa(RP)caused by novel digenic heterozygous mutations in a Chinese family.展开更多
Electrochemical impedance spectroscopy(EIS)flow cytometry offers the advantages of speed,affordability,and portability in cell analysis and cytometry applications.However,the integration challenges of microfluidic and...Electrochemical impedance spectroscopy(EIS)flow cytometry offers the advantages of speed,affordability,and portability in cell analysis and cytometry applications.However,the integration challenges of microfluidic and EIS read-out circuits hinder the downsizing of cytometry devices.To address this,we developed a thermal-bubble-driven impedance flow cytometric application-specific integrated circuit(ASIC).The thermal-bubble micropump avoids external piping and equipment,enabling high-throughput designs.With a total of 36 cell counting channels,each measuring 884×220μm^(2),the chip significantly enhances the throughput of flow cytometers.Each cell counting channel incorporates a differential trans-impedance amplifier(TIA)to amplify weak biosensing signals.By eliminating the parasitic parameters created at the complementary metal-oxidesemiconductor transistor(CMOS)-micro-electromechanical systems(MEMS)interface,the counting accuracy can be increased.The on-chip TIA can adjust feedback resistance from 5 to 60 kΩto accommodate solutions with different impedances.The chip effectively classifies particles of varying sizes,demonstrated by the average peak voltages of 0.0529 and 0.4510 mV for 7 and 14μm polystyrene beads,respectively.Moreover,the counting accuracies of the chip for polystyrene beads and MSTO-211H cells are both greater than 97.6%.The chip exhibits potential for impedance flow cytometer at low cost,high-throughput,and miniaturization for the application of point-of-care diagnostics.展开更多
Early warning of thermal runaway(TR)of lithium-ion batteries(LIBs)is a significant challenge in current application scenarios.Timely and effective TR early warning technology is urgently required considering the curre...Early warning of thermal runaway(TR)of lithium-ion batteries(LIBs)is a significant challenge in current application scenarios.Timely and effective TR early warning technology is urgently required considering the current fire safety situation of LIBs.In this work,we report an early warning method of TR with online electrochemical impedance spectroscopy(EIS)monitoring,which overcomes the shortcomings of warning methods based on traditional signals such as temperature,gas,and pressure with obvious delay and high cost.With in-situ data acquisition through accelerating rate calorimeter(ARC)-EIS test,the crucial features of TR were extracted using the RReliefF algorithm.TR mechanisms corresponding to the features at specific frequencies were analyzed.Finally,a three-level warning strategy for single battery,series module,and parallel module was formulated,which can successfully send out an early warning signal ahead of the self-heating temperature of battery under thermal abuse condition.The technology can provide a reliable basis for the timely intervention of battery thermal management and fire protection systems and is expected to be applied to electric vehicles and energy storage devices to realize early warning and improve battery safety.展开更多
To facilitate emerging applications and demands of edge intelligence(EI)-empowered 6G networks,model-driven semantic communications have been proposed to reduce transmission volume by deploying artificial intelligence...To facilitate emerging applications and demands of edge intelligence(EI)-empowered 6G networks,model-driven semantic communications have been proposed to reduce transmission volume by deploying artificial intelligence(AI)models that provide abilities of semantic extraction and recovery.Nevertheless,it is not feasible to preload all AI models on resource-constrained terminals.Thus,in-time model transmission becomes a crucial problem.This paper proposes an intellicise model transmission architecture to guarantee the reliable transmission of models for semantic communication.The mathematical relationship between model size and performance is formulated by employing a recognition error function supported with experimental data.We consider the characteristics of wireless channels and derive the closed-form expression of model transmission outage probability(MTOP)over the Rayleigh channel.Besides,we define the effective model accuracy(EMA)to evaluate the model transmission performance of both communication and intelligence.Then we propose a joint model selection and resource allocation(JMSRA)algorithm to maximize the average EMA of all users.Simulation results demonstrate that the average EMA of the JMSRA algorithm outperforms baseline algorithms by about 22%.展开更多
基金Supported by National Natural Science Foun-dation of China(No.81470623No.81470624+1 种基金No.81470625)National Key Basic Research Program of China(No.2013 CB967503)
文摘Dear Editor,I am Dr.Ji-Hong Wu,from the Department of Ophthalmology,Eye&ENT Hospital of Fudan University,China.I write to present a case report of retinitis pigmentosa(RP)caused by novel digenic heterozygous mutations in a Chinese family.
基金supported by the Key Project of the National Natural Science Foundation of China(Grant No.82130069).
文摘Electrochemical impedance spectroscopy(EIS)flow cytometry offers the advantages of speed,affordability,and portability in cell analysis and cytometry applications.However,the integration challenges of microfluidic and EIS read-out circuits hinder the downsizing of cytometry devices.To address this,we developed a thermal-bubble-driven impedance flow cytometric application-specific integrated circuit(ASIC).The thermal-bubble micropump avoids external piping and equipment,enabling high-throughput designs.With a total of 36 cell counting channels,each measuring 884×220μm^(2),the chip significantly enhances the throughput of flow cytometers.Each cell counting channel incorporates a differential trans-impedance amplifier(TIA)to amplify weak biosensing signals.By eliminating the parasitic parameters created at the complementary metal-oxidesemiconductor transistor(CMOS)-micro-electromechanical systems(MEMS)interface,the counting accuracy can be increased.The on-chip TIA can adjust feedback resistance from 5 to 60 kΩto accommodate solutions with different impedances.The chip effectively classifies particles of varying sizes,demonstrated by the average peak voltages of 0.0529 and 0.4510 mV for 7 and 14μm polystyrene beads,respectively.Moreover,the counting accuracies of the chip for polystyrene beads and MSTO-211H cells are both greater than 97.6%.The chip exhibits potential for impedance flow cytometer at low cost,high-throughput,and miniaturization for the application of point-of-care diagnostics.
基金supported by the National Natural Science Foundation of China(U2033204,51976209)the Natural Science Foundation of Hefei(2022019)supported by Youth Innovative Promotion Association CAS(Y201768)。
文摘Early warning of thermal runaway(TR)of lithium-ion batteries(LIBs)is a significant challenge in current application scenarios.Timely and effective TR early warning technology is urgently required considering the current fire safety situation of LIBs.In this work,we report an early warning method of TR with online electrochemical impedance spectroscopy(EIS)monitoring,which overcomes the shortcomings of warning methods based on traditional signals such as temperature,gas,and pressure with obvious delay and high cost.With in-situ data acquisition through accelerating rate calorimeter(ARC)-EIS test,the crucial features of TR were extracted using the RReliefF algorithm.TR mechanisms corresponding to the features at specific frequencies were analyzed.Finally,a three-level warning strategy for single battery,series module,and parallel module was formulated,which can successfully send out an early warning signal ahead of the self-heating temperature of battery under thermal abuse condition.The technology can provide a reliable basis for the timely intervention of battery thermal management and fire protection systems and is expected to be applied to electric vehicles and energy storage devices to realize early warning and improve battery safety.
基金supported in part by the National Key R&D Program of China No.2020YFB1806905the National Natural Science Foundation of China No.62201079+1 种基金the Beijing Natural Science Foundation No.L232051the Major Key Project of Peng Cheng Laboratory(PCL)Department of Broadband Communication。
文摘To facilitate emerging applications and demands of edge intelligence(EI)-empowered 6G networks,model-driven semantic communications have been proposed to reduce transmission volume by deploying artificial intelligence(AI)models that provide abilities of semantic extraction and recovery.Nevertheless,it is not feasible to preload all AI models on resource-constrained terminals.Thus,in-time model transmission becomes a crucial problem.This paper proposes an intellicise model transmission architecture to guarantee the reliable transmission of models for semantic communication.The mathematical relationship between model size and performance is formulated by employing a recognition error function supported with experimental data.We consider the characteristics of wireless channels and derive the closed-form expression of model transmission outage probability(MTOP)over the Rayleigh channel.Besides,we define the effective model accuracy(EMA)to evaluate the model transmission performance of both communication and intelligence.Then we propose a joint model selection and resource allocation(JMSRA)algorithm to maximize the average EMA of all users.Simulation results demonstrate that the average EMA of the JMSRA algorithm outperforms baseline algorithms by about 22%.