Yongtao Yu,Yuelin Yu et al.Solvent-Resistant Wearable Triboelectric Nanogenerator for Energy-Harvesting and Self-Powered Sensors.Energy Environ.Mater.2024,7,e12700.On page 4 of this article,the first paragraph of 2.4,...Yongtao Yu,Yuelin Yu et al.Solvent-Resistant Wearable Triboelectric Nanogenerator for Energy-Harvesting and Self-Powered Sensors.Energy Environ.Mater.2024,7,e12700.On page 4 of this article,the first paragraph of 2.4,line 14(PDF version,same below),there is a spelling mistake of“sui,”.It should be changed to“suitable”.The denominator“dt”in the Equation(3)should be changed to“dt”.展开更多
Approximately 30%of the global population struggles with access to potable water,and 60%lacks adequate sanitation.Effective disinfection is crucial,however,heterogeneous systems,despite their benefits,often exhibit lo...Approximately 30%of the global population struggles with access to potable water,and 60%lacks adequate sanitation.Effective disinfection is crucial,however,heterogeneous systems,despite their benefits,often exhibit lower efficacy compared to homogeneous method,presenting a significant challenge[1].In heterogeneous catalysis,photocatalytic disinfection holds immense promise for various applications.However,two key factors significantly impact the efficacy of photocatalytic disinfection:the generation of reactive oxygen species(ROSs)by the photocatalyst and the interaction between ROS and bacteria.展开更多
In energy constrained application scenarios, self‐powered systems (SPSs) are gradually emerging as a core technological pathway for enabling distributed intelligent sensing. High‐entropy energy, such as micro‐wind,...In energy constrained application scenarios, self‐powered systems (SPSs) are gradually emerging as a core technological pathway for enabling distributed intelligent sensing. High‐entropy energy, such as micro‐wind, vibrations, water motion, and human activity, is widely available but difficult to harness due to its low density, randomness, and spatiotemporal fragmentation. Triboelectric nanogenerators (TENGs), with high efficiency to low‐frequency and irregular mechanical stimuli, offer a promising solution for efficient energy harvesting, driving the advancement of SPSs with high‐entropy distribution. This review outlines the basic concepts and recent developments of TENG‐driven SPSs, focusing on strategies for energy harvesting, power management, and system integration. It highlights structural optimization and performance enhancement under typical highentropy scenarios and analyzes key challenges in energy conversion, power regulation, and load management. Finally, the potential applications of TENG‐driven SPSs are discussed in emerging smart fields such as infrastructure monitoring, lowaltitude economy, mobile intelligent devices, and ocean sensing networks.展开更多
Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric lea...Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric leakage are big risk factors for human health.It remains challenging to develop self‐powered and wearable safety hazard sensors that could not only be able to monitor human motions but also have functions for detecting potential hazards.In this work,we fabricated a self‐powered,shapeable,and wearable magnetic triboelectric nanogenerator(MTENG)based on ferrofluid,Ecoflex,and carbonized silk fabric that possessed effective hazard prevention and biomechanical motion sensing ability.A peak open‐circuit voltage of 0.7 V and short‐circuit current of 10μA m^(−2)can be achieved when magnetic field is changed between 3.5 and 37.1 mT.As a component of triboelectric layer of the MTENG,ferrofluid can substantially extend the range of its sensing capabilities to many hazardous cues such as dangerous magnetic field.Furtherly,the developed multifunctional and self‐powered sensor can be used to monitor human activities such as drinking water and bending finger.This effort opens up a new design opportunity for hazard avoidance wearable electronics and self‐powered sensors.展开更多
Colorectal cancer is a major cause of cancer-related mortality worldwide,under-scoring the importance of early and effective colorectal cancer screening to im-prove survival rates.Traditional colorectal cancer screeni...Colorectal cancer is a major cause of cancer-related mortality worldwide,under-scoring the importance of early and effective colorectal cancer screening to im-prove survival rates.Traditional colorectal cancer screening methods include non-invasive tests,such as the fecal immunochemical test(FIT),as well as diagnostic procedures like colonoscopy.Colonoscopy remains the gold standard for detec-ting and treating precancerous polyps and early-stage cancer,regardless of whe-ther it is used as the first screening test or the second test following a positive FIT.However,its effectiveness can be affected by factors such as operator skill,patient variability,and limited lesion visibility,resulting in a significant rate of missed lesion rates and highlighting the need for more efficient and accurate screening techniques.This review is aimed to assess the current challenges of traditional screening methods with the impact of artificial intelligence(AI)in the diagnostic flow.The literature on AI-powered tools for colorectal cancer screening,including novel applications,emerging programs,and recent guidelines,has been reviewed to highlight both the advantages and limitations of implementing this technology in healthcare.Recent advances in AI have introduced soft AI colonoscopy,with the purpose of improving lesion recognition(computer-aided detection)and/or improving optical diagnosis(computer-aided diagnosis).AI-powered colono-scopy systems employ deep learning algorithms to analyze real-time endoscopic images,enhancing detection rates for adenomas,serrated lesions and cancer by reducing human error.AI-assisted colonoscopy enhances adenoma detection,enabling earlier intervention and improved patient outcomes.The benefits are particularly pronounced for less-experienced practitioners,as the detection rates for AI-assisted colonoscopy are similar to experts.AI integration also helps in the teaching process,in developing standardized procedures,and improving screening procedure accuracy and efficiency across different healthcare providers.However,there are challenges and limitations,such as the cost of AI implementation,data privacy concerns,and the need for extensive clinical validation.As AI technology continues to evolve,its transformation of the colorectal cancer screening system could revolutionize the field,making early detection more accessible and reducing mortality,on the condition that the above issues are addressed before widespread use.展开更多
According to the second law of thermodynamics,spontaneous chemical processes will ultimately reach the equilibrium state with the lowest energy.However,in biological systems,there are numerous highenergy states far fr...According to the second law of thermodynamics,spontaneous chemical processes will ultimately reach the equilibrium state with the lowest energy.However,in biological systems,there are numerous highenergy states far from equilibrium.One typical example is the transmembrane ion-concentration gradient,which plays crucial roles in maintaining homeostasis,regulating cell volume,and enabling cell signaling.Transmembrane ion-concentration gradient is achieved by an active transport process that requires the input of energy and the action of pump proteins.Replicating this process with synthetic supramolecular systems is particularly challenging,requiring both the input of energy and very specific,spatiotemporal control over ion uptake and release.In nature,pump proteins,such as protein-based ion channels,have evolved highly intricate architectures to perform this function.In contrast,Aprahamian and coworkers recently developed a much simpler smallmolecule system that functions as a molecular ion pump,utilizing light energy to pump chloride ions across a hydrophobic barrier against the concentration gradient[1].展开更多
The intelligent operation management of distribution services is crucial for the stability of power systems.Integrating the large language model(LLM)with 6G edge intelligence provides customized management solutions.H...The intelligent operation management of distribution services is crucial for the stability of power systems.Integrating the large language model(LLM)with 6G edge intelligence provides customized management solutions.However,the adverse effects of false data injection(FDI)attacks on the performance of LLMs cannot be overlooked.Therefore,we propose an FDI attack detection and LLM-assisted resource allocation algorithm for 6G edge intelligenceempowered distribution power grids.First,we formulate a resource allocation optimization problem.The objective is to minimize the weighted sum of the global loss function and total LLM fine-tuning delay under constraints of long-term privacy entropy and energy consumption.Then,we decouple it based on virtual queues.We utilize an LLM-assisted deep Q network(DQN)to learn the resource allocation strategy and design an FDI attack detection mechanism to ensure that fine-tuning remains on the correct path.Simulations demonstrate that the proposed algorithm has excellent performance in convergence,delay,and security.展开更多
The global healthcare landscape is increasingly challenged by the rising prevalence of chronic diseases and the demographic shift towards an aging population,necessitating the development of innovative and sustainable...The global healthcare landscape is increasingly challenged by the rising prevalence of chronic diseases and the demographic shift towards an aging population,necessitating the development of innovative and sustainable healthcare solutions.In this context,the emergence of triboelectric energy harvesters as a key technological breakthrough offers a viable pathway towards self-powered,efficient,and sustainable personal health management.This review critically examines the transformative potential of triboelectric nanogenerators(TENGs)in addressing the pressing challenges of modern healthcare,underscoring their unique benefits such as being battery-free,easy to fabricate,and cost-efficient.We begin by reviewing the fundamental mechanisms of triboelectrification at the atomic scale and presenting the contact electrification among various materials,such as metals,polymers,and semiconductors.The discussion subsequently extends to the commonly used materials for TENGs and explores advancements in their design and functionality,with an emphasis on structural and chemical innovations.Furthermore,the application spectrum of TENGs in personal health management is extensively reviewed,covering aspects including health monitoring,therapeutic intervention,health protection,and device powering,while highlighting their capacity for self-sustainability.The review concludes by addressing existing challenges while mapping out the latest significant contributions and prospective directions in TENG-based healthcare innovations.By facilitating a paradigm shift towards a more autonomous,cost-effective,and personalized healthcare model,independent of external power sources,TENGs are poised to markedly enhance the quality of care and overall well-being,marking the dawn of a new era in integrated personal health management.展开更多
To address the challenges of long commuting times,traffic congestion,high energy consumption,and emissions in inter-city travel,a new type of flying coach has been developed.This innovation aims to significantly short...To address the challenges of long commuting times,traffic congestion,high energy consumption,and emissions in inter-city travel,a new type of flying coach has been developed.This innovation aims to significantly shorten inter-city commuting times,enhance travel efficiency,and simultaneously reduce energy consumption and emissions.The flying coach integrates rail power supply technology,an intelligent operating system,and advanced new materials,comprising a catenary power supply guide rod and various sensor components.Based on analysis of traditional aircraft design principles,the research team simulated the design of the rail-powered flying coach using software such as AutoCAD and SolidWorks for three-dimensional modeling.The analysis results indicate that,compared to traditional aircraft and rail trains,the design of the new flying coach reduces its overall weight while maintaining carrying capacity,thereby improving commuting efficiency and environmental performance.This development lays a solid foundation for creating a greener,more efficient,and convenient inter-city transportation network.展开更多
The need for efficient thermal energy systems has gained significant attention due to the growing global concern about renewable energy resources,particularly in residential buildings.One of the biggest challenges in ...The need for efficient thermal energy systems has gained significant attention due to the growing global concern about renewable energy resources,particularly in residential buildings.One of the biggest challenges in this area is capturing and converting solar energy at maximum efficiency.This requires the use of strong materials and advanced fluids to enhance conversion efficiency while minimizing energy losses.Despite extensive research on thermal energy systems,there remains a limited understanding of how the combined effects of thermal radiation,irreversibility processes,and advanced heat flux models contribute to optimizing solar power performance in residential applications.Addressing these knowledge gaps is critical for advancing the design and implementation of highly efficient thermal energy systems.Owing to its usage,this study investigates the thermal energy and irreversibility processes in the context of solar power systems for residential buildings.Specifically,it explores the influence of thermal radiation and the Cattaneo–Christov heat flux model,considering the interactions over a stretching surface.The study incorporates cross fluid and Maxwell fluid effects into the governing model equations.Utilizing the Galerkin-weighted residual method,the transformed model is solved to understand the impacts on heat distribution.The findings reveal that increased thermal radiation and thermal conductivity significantly enhance heat distribution,offering valuable insights for optimizing solar power system efficiency in residential applications.展开更多
Driven by rapid advancements in smart wearable technologies and perovskite photovoltaics,flexible perovskite solar cells(FPSCs)have emerged as highly promising autonomous power sources,poised to transform the next gen...Driven by rapid advancements in smart wearable technologies and perovskite photovoltaics,flexible perovskite solar cells(FPSCs)have emerged as highly promising autonomous power sources,poised to transform the next generation of mobile energy systems,portable electronics,and integrated wearable devices.For successful deployment in real-world scenarios,FPSCs must exhibit a combination of key attributes,including high power conversion efficiency,lightweight architecture,environmental robustness,and mechanical adaptability-encompassing flexibility,stretchability,and twistability.This review provides a detailed examination of the evolution,current state,and practical deployment of FPSCs,emphasizing their potential as efficient,portable energy solutions.It investigates advanced strategies for improving environmental resilience and mechanical recoverability,including the engineering of flexible substrates,deposition of high-quality perovskite films,and optimization of charge-selective interfaces.Additionally,it offers a systematic analysis of device design,fabrication protocols,scalable printing techniques,and standardized performance evaluation methods tailored for wearable FPSCs.Recent progress in enhancing the optoelectronic properties and mechanical durability of FPSCs is also critically reviewed.Ultimately,this work delivers a comprehensive perspective on FPSCs from both optoelectronic and mechanical viewpoints,identifies key challenges,and outlines future research pathways toward the seamless integration of FPSCs into multifunctional,next-generation wearable systems.展开更多
With the rapid advancement of robotics and Artificial Intelligence(AI),aerobics training companion robots now support eco-friendly fitness by reducing reliance on nonrenewable energy.This study presents a solar-powere...With the rapid advancement of robotics and Artificial Intelligence(AI),aerobics training companion robots now support eco-friendly fitness by reducing reliance on nonrenewable energy.This study presents a solar-powered aerobics training robot featuring an adaptive energy management system designed for sustainability and efficiency.The robot integrates machine vision with an enhanced Dynamic Cheetah Optimizer and Bayesian Neural Network(DynCO-BNN)to enable precise exercise monitoring and real-time feedback.Solar tracking technology ensures optimal energy absorption,while a microcontroller-based regulator manages power distribution and robotic movement.Dual-battery switching ensures uninterrupted operation,aided by light and I/V sensors for energy optimization.Using the INSIGHT-LME IMU dataset,which includes motion data from 76 individuals performing Local Muscular Endurance(LME)exercises,the system detects activities,counts repetitions,and recognizes human movements.To minimize energy use during data processing,Min-Max normalization and two-dimensional Discrete Fourier Transform(2D-DFT)are applied,boosting computational efficiency.The robot accurately identifies upper and lower limb movements,delivering effective exercise guidance.The DynCO-BNN model achieved a high tracking accuracy of 96.8%.Results confirm improved solar utilization,ecological sustainability,and reduced dependence on fossil fuels—positioning the robot as a smart,energy-efficient solution for next-generation fitness technology.展开更多
A set of water powered excavation test system was developed for the comprehensive performance testing and evaluation of water powered percussive rock drill indoors. The whole system contains hydraulic power section, e...A set of water powered excavation test system was developed for the comprehensive performance testing and evaluation of water powered percussive rock drill indoors. The whole system contains hydraulic power section, electronic control system, test and data acquisition system, and assistant devices, such as guideway and drilling bench. Parameters of the water powered percussive rock drill can be obtained by analyzing testing data, which contain impact energy, front and back cavity pressure, pressure and flow in each working part, drilling velocity, frequency and energy efficiency etc. The system is applied to test the self-designed water powered percussive rock drill SYYG65. The parameters of water powered percussive rock drill with impact pressure of about 8.9 MPa are 58.93 J for impact energy, and 8.97% for energy efficiency, which prove the effectiveness of system.展开更多
High-Altitude Long-Endurance(HALE)solar-powered Unmanned Aircraft Vehicles(UAVs)can utilize solar energy as power source and maintain extremely long cruise endurance,which has attracted extensive attentions from resea...High-Altitude Long-Endurance(HALE)solar-powered Unmanned Aircraft Vehicles(UAVs)can utilize solar energy as power source and maintain extremely long cruise endurance,which has attracted extensive attentions from researchers.Trajectory optimization is a promising way to achieve superior flight time because of the finite solar energy absorbed in a day.In this work,a method of trajectory optimization and guidance for HALE solar-powered aircraft based on a Reinforcement Learning(RL)framework is introduced.According to flight and environment information,a neural network controller outputs commands of thrust,attack angle,and bank angle to realize an autonomous flight based on energy maximization.The validity of the proposed method was evaluated in a 5-km radius area in simulation,and results have shown that after one day-night cycle,the battery energy of the RL-controller was improved by 31%and 17%compared with those of a Steady-State(SS)strategy with a constant speed and a constant altitude and a kind of statemachine strategy,respectively.In addition,results of an uninterrupted flight test have shown that the endurance of the RL controller was longer than those of the control cases.展开更多
A novel framework is established for accurate modeling of Powered Parafoil Unmanned Aerial Vehicle(PPUAV). The model is developed in the following three steps: obtaining a linear dynamic model, simplifying the model s...A novel framework is established for accurate modeling of Powered Parafoil Unmanned Aerial Vehicle(PPUAV). The model is developed in the following three steps: obtaining a linear dynamic model, simplifying the model structure, and estimating the model mismatch due to model variance and external disturbance factors. First, a six degree-of-freedom linear model, or the structured model, is obtained through dynamic establishment and linearization. Second, the data correlation analysis is adopted to determine the criterion for proper model complexity and to simplify the structured model. Next, an active model is established, combining the simplified model with the model mismatch estimator. An adapted Kalman filter is utilized for the real-time estimation of states and model mismatch. We finally derive a linear system model while taking into account of model variance and external disturbance. Actual flight tests verify the effectiveness of our active model in different flight scenarios.展开更多
The in-core self-powered neutron detector(SPND)acts as a key measuring device for the monitoring of parameters and evaluation of the operating conditions of nuclear reactors.Prompt detection and tolerance of faulty SP...The in-core self-powered neutron detector(SPND)acts as a key measuring device for the monitoring of parameters and evaluation of the operating conditions of nuclear reactors.Prompt detection and tolerance of faulty SPNDs are indispensable for reliable reactor management.To completely extract the correlated state information of SPNDs,we constructed a twin model based on a generalized regression neural network(GRNN)that represents the common relationships among overall signals.Faulty SPNDs were determined because of the functional concordance of the twin model and real monitoring sys-tems,which calculated the error probability distribution between the model outputs and real values.Fault detection follows a tolerance phase to reinforce the stability of the twin model in the case of massive failures.A weighted K-nearest neighbor model was employed to reasonably reconstruct the values of the faulty signals and guarantee data purity.The experimental evaluation of the proposed method showed promising results,with excellent output consistency and high detection accuracy for both single-and multiple-point faulty SPNDs.For unexpected excessive failures,the proposed tolerance approach can efficiently repair fault behaviors and enhance the prediction performance of the twin model.展开更多
The trajectory related and Direct Current(DC)Electromagnetic Interference(EMI)of lithium battery,fuel cell and photovoltaic modules has a great influence on the small-scale Unmanned Aerial Vehicle(UAV)airborne magneto...The trajectory related and Direct Current(DC)Electromagnetic Interference(EMI)of lithium battery,fuel cell and photovoltaic modules has a great influence on the small-scale Unmanned Aerial Vehicle(UAV)airborne magnetometer and is hard to be shielded,calibrated or filtered.Besides,the mechanisms underlying the DC EMI have been rarely investigated yet.To cope with this problem,this paper systematically studies the EMI models,and proposes an online 3-layer EMI reduction scheme.First,EMI coupled with UAV motion model and hybrid power system is established.Second,the mechanism EMI models of hybrid power system are established and verified based on the proposed concept“equivalent current”.Third,an online 3-layer EMI reduction scheme is proposed,including battery layer,trajectory planning layer and energy management layer.In the first main layer,EMI self-cancellation is realized by rotating battery inclinations and symmetrical circuits.In response to errors,the trajectory planning layer reduces the EMI intensity by optimizing an optimal trajectory,while the energy management layer prioritizes power allocation to power sources that can produce small and stable EMI.Simulation results of climb,level flight and descent illustrate the efficaciousness and applicability of the proposed online 3-layer EMI reduction scheme.展开更多
One of the primary difficulties in using powered parafoil(PPF) systems is the lack of effective trajectory tracking controllers since the trajectory tracking control is the essential operation for PPF to accomplish au...One of the primary difficulties in using powered parafoil(PPF) systems is the lack of effective trajectory tracking controllers since the trajectory tracking control is the essential operation for PPF to accomplish autonomous tasks. The characteristic model(CM) based all-coefficient adaptive control(ACAC) designed for PPF systems in horizontal and vertical trajectory control is proposed. The method is easy to use and convenient to adjust and test. Just a few parameters are adapted during the control process. In application, vertical and horizontal CMs are designed and ACAC controllers are constructed to control vertical altitude and horizontal trajectory of PPF based on the proposed CMs, respectively. Result analysis of different simulations shows that the applied ACAC control method is effective for trajectory tracking of the PPF systems and the approach guarantees the transient performance of the PPF systems with better disturbance rejection ability.展开更多
Battery powered vertical takeoff and landing(VTOL) aircraft attracts more and more interests from public, while limited hover endurance hinders many prospective applications. Based on the weight models of battery, mot...Battery powered vertical takeoff and landing(VTOL) aircraft attracts more and more interests from public, while limited hover endurance hinders many prospective applications. Based on the weight models of battery, motor and electronic speed controller, the power consumption model of propeller and the constant power discharge model of battery, an efficient method to estimate the hover endurance of battery powered VTOL aircraft was presented. In order to understand the mechanism of performance improvement, the impacts of propulsion system parameters on hover endurance were analyzed by simulations, including the motor power density, the battery capacity, specific energy and Peukert coefficient. Ground experiment platform was established and validation experiments were carried out, the results of which showed a well agreement with the simulations. The estimation method and the analysis results could be used for optimization design and hover performance evaluation of battery powered VTOL aircraft.展开更多
In order to improve the Energy Efficiency(EE)and spectrum utilization of Cognitive Wireless Powered Networks(CWPNs),a combined spatial-temporal Energy Harvesting(EH)and relay selection scheme is proposed.In the propos...In order to improve the Energy Efficiency(EE)and spectrum utilization of Cognitive Wireless Powered Networks(CWPNs),a combined spatial-temporal Energy Harvesting(EH)and relay selection scheme is proposed.In the proposed scheme,for protecting the Primary User(PU),a two-layer guard zone is set outside the PU based on the outage probability threshold of the PU.Moreover,to increase the energy of the CWPNs,the EH zone in the two-layer guard zone allows the Secondary Users(SUs)to spatially harvest energy from the Radio Frequency(RF)signals of temporally active PUs.To improve the utilization of the PU spectrum,the guard zone outside the EH zone allows for the constrained power transmission of SUs.Moreover,the relay selection transmission is designed in the transmission zone of the SU to improve the EE of the CWPNs.In addition to the EE of the CWPNs,the outage probabilities of the SU and PU are derived.The results reveal that the setting of a two-layer guard zone can effectively reduce the outage probability of the PU and improve the EE of CWPNs.Furthermore,the relay selection transmission decreases the outage probabilities of the SUs.展开更多
文摘Yongtao Yu,Yuelin Yu et al.Solvent-Resistant Wearable Triboelectric Nanogenerator for Energy-Harvesting and Self-Powered Sensors.Energy Environ.Mater.2024,7,e12700.On page 4 of this article,the first paragraph of 2.4,line 14(PDF version,same below),there is a spelling mistake of“sui,”.It should be changed to“suitable”.The denominator“dt”in the Equation(3)should be changed to“dt”.
基金supported by the Taishan Scholar Project of Shandong Province(tsqn202211168)the National Natural Science Foundation of China(52422213,52272212)the Natural Science Foundation of Shandong Province(ZR2022JQ20).
文摘Approximately 30%of the global population struggles with access to potable water,and 60%lacks adequate sanitation.Effective disinfection is crucial,however,heterogeneous systems,despite their benefits,often exhibit lower efficacy compared to homogeneous method,presenting a significant challenge[1].In heterogeneous catalysis,photocatalytic disinfection holds immense promise for various applications.However,two key factors significantly impact the efficacy of photocatalytic disinfection:the generation of reactive oxygen species(ROSs)by the photocatalyst and the interaction between ROS and bacteria.
基金supported by The National Key Research and Development Program of China(Grant No.2023YFB2604600).
文摘In energy constrained application scenarios, self‐powered systems (SPSs) are gradually emerging as a core technological pathway for enabling distributed intelligent sensing. High‐entropy energy, such as micro‐wind, vibrations, water motion, and human activity, is widely available but difficult to harness due to its low density, randomness, and spatiotemporal fragmentation. Triboelectric nanogenerators (TENGs), with high efficiency to low‐frequency and irregular mechanical stimuli, offer a promising solution for efficient energy harvesting, driving the advancement of SPSs with high‐entropy distribution. This review outlines the basic concepts and recent developments of TENG‐driven SPSs, focusing on strategies for energy harvesting, power management, and system integration. It highlights structural optimization and performance enhancement under typical highentropy scenarios and analyzes key challenges in energy conversion, power regulation, and load management. Finally, the potential applications of TENG‐driven SPSs are discussed in emerging smart fields such as infrastructure monitoring, lowaltitude economy, mobile intelligent devices, and ocean sensing networks.
基金financially supported by the National Natural Science Foundation of China(No.52125201)Beijing Natural Science Foundation(No.Z240025)and the Beijing Municipal Science and Technology(No.Z221100002722015).
文摘Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric leakage are big risk factors for human health.It remains challenging to develop self‐powered and wearable safety hazard sensors that could not only be able to monitor human motions but also have functions for detecting potential hazards.In this work,we fabricated a self‐powered,shapeable,and wearable magnetic triboelectric nanogenerator(MTENG)based on ferrofluid,Ecoflex,and carbonized silk fabric that possessed effective hazard prevention and biomechanical motion sensing ability.A peak open‐circuit voltage of 0.7 V and short‐circuit current of 10μA m^(−2)can be achieved when magnetic field is changed between 3.5 and 37.1 mT.As a component of triboelectric layer of the MTENG,ferrofluid can substantially extend the range of its sensing capabilities to many hazardous cues such as dangerous magnetic field.Furtherly,the developed multifunctional and self‐powered sensor can be used to monitor human activities such as drinking water and bending finger.This effort opens up a new design opportunity for hazard avoidance wearable electronics and self‐powered sensors.
文摘Colorectal cancer is a major cause of cancer-related mortality worldwide,under-scoring the importance of early and effective colorectal cancer screening to im-prove survival rates.Traditional colorectal cancer screening methods include non-invasive tests,such as the fecal immunochemical test(FIT),as well as diagnostic procedures like colonoscopy.Colonoscopy remains the gold standard for detec-ting and treating precancerous polyps and early-stage cancer,regardless of whe-ther it is used as the first screening test or the second test following a positive FIT.However,its effectiveness can be affected by factors such as operator skill,patient variability,and limited lesion visibility,resulting in a significant rate of missed lesion rates and highlighting the need for more efficient and accurate screening techniques.This review is aimed to assess the current challenges of traditional screening methods with the impact of artificial intelligence(AI)in the diagnostic flow.The literature on AI-powered tools for colorectal cancer screening,including novel applications,emerging programs,and recent guidelines,has been reviewed to highlight both the advantages and limitations of implementing this technology in healthcare.Recent advances in AI have introduced soft AI colonoscopy,with the purpose of improving lesion recognition(computer-aided detection)and/or improving optical diagnosis(computer-aided diagnosis).AI-powered colono-scopy systems employ deep learning algorithms to analyze real-time endoscopic images,enhancing detection rates for adenomas,serrated lesions and cancer by reducing human error.AI-assisted colonoscopy enhances adenoma detection,enabling earlier intervention and improved patient outcomes.The benefits are particularly pronounced for less-experienced practitioners,as the detection rates for AI-assisted colonoscopy are similar to experts.AI integration also helps in the teaching process,in developing standardized procedures,and improving screening procedure accuracy and efficiency across different healthcare providers.However,there are challenges and limitations,such as the cost of AI implementation,data privacy concerns,and the need for extensive clinical validation.As AI technology continues to evolve,its transformation of the colorectal cancer screening system could revolutionize the field,making early detection more accessible and reducing mortality,on the condition that the above issues are addressed before widespread use.
基金financial supports of National Natural Science Foundation of China(22171226)Natural Science Basic Research Program of Shaanxi(2022JC-06).
文摘According to the second law of thermodynamics,spontaneous chemical processes will ultimately reach the equilibrium state with the lowest energy.However,in biological systems,there are numerous highenergy states far from equilibrium.One typical example is the transmembrane ion-concentration gradient,which plays crucial roles in maintaining homeostasis,regulating cell volume,and enabling cell signaling.Transmembrane ion-concentration gradient is achieved by an active transport process that requires the input of energy and the action of pump proteins.Replicating this process with synthetic supramolecular systems is particularly challenging,requiring both the input of energy and very specific,spatiotemporal control over ion uptake and release.In nature,pump proteins,such as protein-based ion channels,have evolved highly intricate architectures to perform this function.In contrast,Aprahamian and coworkers recently developed a much simpler smallmolecule system that functions as a molecular ion pump,utilizing light energy to pump chloride ions across a hydrophobic barrier against the concentration gradient[1].
基金supported by the Science and Technology Project of State Grid Corporation of China under Grant Number 52094021N010(5400-202199534A-0-5-ZN).
文摘The intelligent operation management of distribution services is crucial for the stability of power systems.Integrating the large language model(LLM)with 6G edge intelligence provides customized management solutions.However,the adverse effects of false data injection(FDI)attacks on the performance of LLMs cannot be overlooked.Therefore,we propose an FDI attack detection and LLM-assisted resource allocation algorithm for 6G edge intelligenceempowered distribution power grids.First,we formulate a resource allocation optimization problem.The objective is to minimize the weighted sum of the global loss function and total LLM fine-tuning delay under constraints of long-term privacy entropy and energy consumption.Then,we decouple it based on virtual queues.We utilize an LLM-assisted deep Q network(DQN)to learn the resource allocation strategy and design an FDI attack detection mechanism to ensure that fine-tuning remains on the correct path.Simulations demonstrate that the proposed algorithm has excellent performance in convergence,delay,and security.
基金supported by the National Research Foundation of Korea(NRF)Grant funded by the Korea government(MSIT)(Nos.2020R1A5A1019131 and 2022M3D1A2054488)。
文摘The global healthcare landscape is increasingly challenged by the rising prevalence of chronic diseases and the demographic shift towards an aging population,necessitating the development of innovative and sustainable healthcare solutions.In this context,the emergence of triboelectric energy harvesters as a key technological breakthrough offers a viable pathway towards self-powered,efficient,and sustainable personal health management.This review critically examines the transformative potential of triboelectric nanogenerators(TENGs)in addressing the pressing challenges of modern healthcare,underscoring their unique benefits such as being battery-free,easy to fabricate,and cost-efficient.We begin by reviewing the fundamental mechanisms of triboelectrification at the atomic scale and presenting the contact electrification among various materials,such as metals,polymers,and semiconductors.The discussion subsequently extends to the commonly used materials for TENGs and explores advancements in their design and functionality,with an emphasis on structural and chemical innovations.Furthermore,the application spectrum of TENGs in personal health management is extensively reviewed,covering aspects including health monitoring,therapeutic intervention,health protection,and device powering,while highlighting their capacity for self-sustainability.The review concludes by addressing existing challenges while mapping out the latest significant contributions and prospective directions in TENG-based healthcare innovations.By facilitating a paradigm shift towards a more autonomous,cost-effective,and personalized healthcare model,independent of external power sources,TENGs are poised to markedly enhance the quality of care and overall well-being,marking the dawn of a new era in integrated personal health management.
基金College Student Innovation Training Program Project(S202410225147)。
文摘To address the challenges of long commuting times,traffic congestion,high energy consumption,and emissions in inter-city travel,a new type of flying coach has been developed.This innovation aims to significantly shorten inter-city commuting times,enhance travel efficiency,and simultaneously reduce energy consumption and emissions.The flying coach integrates rail power supply technology,an intelligent operating system,and advanced new materials,comprising a catenary power supply guide rod and various sensor components.Based on analysis of traditional aircraft design principles,the research team simulated the design of the rail-powered flying coach using software such as AutoCAD and SolidWorks for three-dimensional modeling.The analysis results indicate that,compared to traditional aircraft and rail trains,the design of the new flying coach reduces its overall weight while maintaining carrying capacity,thereby improving commuting efficiency and environmental performance.This development lays a solid foundation for creating a greener,more efficient,and convenient inter-city transportation network.
基金funded by Universiti Teknikal Malaysia Melaka through the Tabung Penerbitan Jurnal(S11017).
文摘The need for efficient thermal energy systems has gained significant attention due to the growing global concern about renewable energy resources,particularly in residential buildings.One of the biggest challenges in this area is capturing and converting solar energy at maximum efficiency.This requires the use of strong materials and advanced fluids to enhance conversion efficiency while minimizing energy losses.Despite extensive research on thermal energy systems,there remains a limited understanding of how the combined effects of thermal radiation,irreversibility processes,and advanced heat flux models contribute to optimizing solar power performance in residential applications.Addressing these knowledge gaps is critical for advancing the design and implementation of highly efficient thermal energy systems.Owing to its usage,this study investigates the thermal energy and irreversibility processes in the context of solar power systems for residential buildings.Specifically,it explores the influence of thermal radiation and the Cattaneo–Christov heat flux model,considering the interactions over a stretching surface.The study incorporates cross fluid and Maxwell fluid effects into the governing model equations.Utilizing the Galerkin-weighted residual method,the transformed model is solved to understand the impacts on heat distribution.The findings reveal that increased thermal radiation and thermal conductivity significantly enhance heat distribution,offering valuable insights for optimizing solar power system efficiency in residential applications.
基金supported by the Commercialization Promotion Agency for R&D Outcomes(COMPA)grant funded by the Korea government(Ministry of Science and ICT)(RS-2025-02311658)supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2023R1A2C2008017)Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-2020R1A6A1A03043435).
文摘Driven by rapid advancements in smart wearable technologies and perovskite photovoltaics,flexible perovskite solar cells(FPSCs)have emerged as highly promising autonomous power sources,poised to transform the next generation of mobile energy systems,portable electronics,and integrated wearable devices.For successful deployment in real-world scenarios,FPSCs must exhibit a combination of key attributes,including high power conversion efficiency,lightweight architecture,environmental robustness,and mechanical adaptability-encompassing flexibility,stretchability,and twistability.This review provides a detailed examination of the evolution,current state,and practical deployment of FPSCs,emphasizing their potential as efficient,portable energy solutions.It investigates advanced strategies for improving environmental resilience and mechanical recoverability,including the engineering of flexible substrates,deposition of high-quality perovskite films,and optimization of charge-selective interfaces.Additionally,it offers a systematic analysis of device design,fabrication protocols,scalable printing techniques,and standardized performance evaluation methods tailored for wearable FPSCs.Recent progress in enhancing the optoelectronic properties and mechanical durability of FPSCs is also critically reviewed.Ultimately,this work delivers a comprehensive perspective on FPSCs from both optoelectronic and mechanical viewpoints,identifies key challenges,and outlines future research pathways toward the seamless integration of FPSCs into multifunctional,next-generation wearable systems.
文摘With the rapid advancement of robotics and Artificial Intelligence(AI),aerobics training companion robots now support eco-friendly fitness by reducing reliance on nonrenewable energy.This study presents a solar-powered aerobics training robot featuring an adaptive energy management system designed for sustainability and efficiency.The robot integrates machine vision with an enhanced Dynamic Cheetah Optimizer and Bayesian Neural Network(DynCO-BNN)to enable precise exercise monitoring and real-time feedback.Solar tracking technology ensures optimal energy absorption,while a microcontroller-based regulator manages power distribution and robotic movement.Dual-battery switching ensures uninterrupted operation,aided by light and I/V sensors for energy optimization.Using the INSIGHT-LME IMU dataset,which includes motion data from 76 individuals performing Local Muscular Endurance(LME)exercises,the system detects activities,counts repetitions,and recognizes human movements.To minimize energy use during data processing,Min-Max normalization and two-dimensional Discrete Fourier Transform(2D-DFT)are applied,boosting computational efficiency.The robot accurately identifies upper and lower limb movements,delivering effective exercise guidance.The DynCO-BNN model achieved a high tracking accuracy of 96.8%.Results confirm improved solar utilization,ecological sustainability,and reduced dependence on fossil fuels—positioning the robot as a smart,energy-efficient solution for next-generation fitness technology.
基金Project(2006AA06Z134) supported by the National High Technology Research and Development Program of ChinaProjects(50934006, 50904079) supported by the National Natural Science Foundation of China
文摘A set of water powered excavation test system was developed for the comprehensive performance testing and evaluation of water powered percussive rock drill indoors. The whole system contains hydraulic power section, electronic control system, test and data acquisition system, and assistant devices, such as guideway and drilling bench. Parameters of the water powered percussive rock drill can be obtained by analyzing testing data, which contain impact energy, front and back cavity pressure, pressure and flow in each working part, drilling velocity, frequency and energy efficiency etc. The system is applied to test the self-designed water powered percussive rock drill SYYG65. The parameters of water powered percussive rock drill with impact pressure of about 8.9 MPa are 58.93 J for impact energy, and 8.97% for energy efficiency, which prove the effectiveness of system.
基金Foundation of the Special Research Assistant of Chinese Academy of Sciences(No.E0290A0301)。
文摘High-Altitude Long-Endurance(HALE)solar-powered Unmanned Aircraft Vehicles(UAVs)can utilize solar energy as power source and maintain extremely long cruise endurance,which has attracted extensive attentions from researchers.Trajectory optimization is a promising way to achieve superior flight time because of the finite solar energy absorbed in a day.In this work,a method of trajectory optimization and guidance for HALE solar-powered aircraft based on a Reinforcement Learning(RL)framework is introduced.According to flight and environment information,a neural network controller outputs commands of thrust,attack angle,and bank angle to realize an autonomous flight based on energy maximization.The validity of the proposed method was evaluated in a 5-km radius area in simulation,and results have shown that after one day-night cycle,the battery energy of the RL-controller was improved by 31%and 17%compared with those of a Steady-State(SS)strategy with a constant speed and a constant altitude and a kind of statemachine strategy,respectively.In addition,results of an uninterrupted flight test have shown that the endurance of the RL controller was longer than those of the control cases.
基金co-supported by the National Nature Sciences Foundation of China (Nos. 61503369 and 61528303)the State Key Laboratory of Roboticsthe Chinese National Key Technology R&D Program (No. Y4A12081010)
文摘A novel framework is established for accurate modeling of Powered Parafoil Unmanned Aerial Vehicle(PPUAV). The model is developed in the following three steps: obtaining a linear dynamic model, simplifying the model structure, and estimating the model mismatch due to model variance and external disturbance factors. First, a six degree-of-freedom linear model, or the structured model, is obtained through dynamic establishment and linearization. Second, the data correlation analysis is adopted to determine the criterion for proper model complexity and to simplify the structured model. Next, an active model is established, combining the simplified model with the model mismatch estimator. An adapted Kalman filter is utilized for the real-time estimation of states and model mismatch. We finally derive a linear system model while taking into account of model variance and external disturbance. Actual flight tests verify the effectiveness of our active model in different flight scenarios.
基金supported by the Natural Science Foundation of Fujian Province,China(No.2022J01566).
文摘The in-core self-powered neutron detector(SPND)acts as a key measuring device for the monitoring of parameters and evaluation of the operating conditions of nuclear reactors.Prompt detection and tolerance of faulty SPNDs are indispensable for reliable reactor management.To completely extract the correlated state information of SPNDs,we constructed a twin model based on a generalized regression neural network(GRNN)that represents the common relationships among overall signals.Faulty SPNDs were determined because of the functional concordance of the twin model and real monitoring sys-tems,which calculated the error probability distribution between the model outputs and real values.Fault detection follows a tolerance phase to reinforce the stability of the twin model in the case of massive failures.A weighted K-nearest neighbor model was employed to reasonably reconstruct the values of the faulty signals and guarantee data purity.The experimental evaluation of the proposed method showed promising results,with excellent output consistency and high detection accuracy for both single-and multiple-point faulty SPNDs.For unexpected excessive failures,the proposed tolerance approach can efficiently repair fault behaviors and enhance the prediction performance of the twin model.
文摘The trajectory related and Direct Current(DC)Electromagnetic Interference(EMI)of lithium battery,fuel cell and photovoltaic modules has a great influence on the small-scale Unmanned Aerial Vehicle(UAV)airborne magnetometer and is hard to be shielded,calibrated or filtered.Besides,the mechanisms underlying the DC EMI have been rarely investigated yet.To cope with this problem,this paper systematically studies the EMI models,and proposes an online 3-layer EMI reduction scheme.First,EMI coupled with UAV motion model and hybrid power system is established.Second,the mechanism EMI models of hybrid power system are established and verified based on the proposed concept“equivalent current”.Third,an online 3-layer EMI reduction scheme is proposed,including battery layer,trajectory planning layer and energy management layer.In the first main layer,EMI self-cancellation is realized by rotating battery inclinations and symmetrical circuits.In response to errors,the trajectory planning layer reduces the EMI intensity by optimizing an optimal trajectory,while the energy management layer prioritizes power allocation to power sources that can produce small and stable EMI.Simulation results of climb,level flight and descent illustrate the efficaciousness and applicability of the proposed online 3-layer EMI reduction scheme.
基金Project(61273138)supported by the National Natural Science Foundation of ChinaProject(14JCZDJC39300)supported by the Key Fund of Tianjin,China
文摘One of the primary difficulties in using powered parafoil(PPF) systems is the lack of effective trajectory tracking controllers since the trajectory tracking control is the essential operation for PPF to accomplish autonomous tasks. The characteristic model(CM) based all-coefficient adaptive control(ACAC) designed for PPF systems in horizontal and vertical trajectory control is proposed. The method is easy to use and convenient to adjust and test. Just a few parameters are adapted during the control process. In application, vertical and horizontal CMs are designed and ACAC controllers are constructed to control vertical altitude and horizontal trajectory of PPF based on the proposed CMs, respectively. Result analysis of different simulations shows that the applied ACAC control method is effective for trajectory tracking of the PPF systems and the approach guarantees the transient performance of the PPF systems with better disturbance rejection ability.
文摘Battery powered vertical takeoff and landing(VTOL) aircraft attracts more and more interests from public, while limited hover endurance hinders many prospective applications. Based on the weight models of battery, motor and electronic speed controller, the power consumption model of propeller and the constant power discharge model of battery, an efficient method to estimate the hover endurance of battery powered VTOL aircraft was presented. In order to understand the mechanism of performance improvement, the impacts of propulsion system parameters on hover endurance were analyzed by simulations, including the motor power density, the battery capacity, specific energy and Peukert coefficient. Ground experiment platform was established and validation experiments were carried out, the results of which showed a well agreement with the simulations. The estimation method and the analysis results could be used for optimization design and hover performance evaluation of battery powered VTOL aircraft.
文摘In order to improve the Energy Efficiency(EE)and spectrum utilization of Cognitive Wireless Powered Networks(CWPNs),a combined spatial-temporal Energy Harvesting(EH)and relay selection scheme is proposed.In the proposed scheme,for protecting the Primary User(PU),a two-layer guard zone is set outside the PU based on the outage probability threshold of the PU.Moreover,to increase the energy of the CWPNs,the EH zone in the two-layer guard zone allows the Secondary Users(SUs)to spatially harvest energy from the Radio Frequency(RF)signals of temporally active PUs.To improve the utilization of the PU spectrum,the guard zone outside the EH zone allows for the constrained power transmission of SUs.Moreover,the relay selection transmission is designed in the transmission zone of the SU to improve the EE of the CWPNs.In addition to the EE of the CWPNs,the outage probabilities of the SU and PU are derived.The results reveal that the setting of a two-layer guard zone can effectively reduce the outage probability of the PU and improve the EE of CWPNs.Furthermore,the relay selection transmission decreases the outage probabilities of the SUs.
