This review paper examines the various types of electrical generators used to convert wave energy into electrical energy.The focus is on both linear and rotary generators,including their design principles,operational ...This review paper examines the various types of electrical generators used to convert wave energy into electrical energy.The focus is on both linear and rotary generators,including their design principles,operational efficiencies,and technological advancements.Linear generators,such as Induction,permanent magnet synchronous,and switched reluctance types,are highlighted for their direct conversion capability,eliminating the need for mechanical gearboxes.Rotary Induction generators,permanent magnet synchronous generators,and doubly-fed Induction generators are evaluated for their established engineering principles and integration with existing grid infrastructure.The paper discusses the historical development,environmental benefits,and ongoing advancements in wave energy technologies,emphasizing the increasing feasibility and scalability of wave energy as a renewable source.Through a comprehensive analysis,this review provides insights into the current state and future prospects of electrical generators in wave energy conversion,underscoring their potential to significantly reduce reliance on fossil fuels and mitigate environmental impacts.展开更多
With the growing importance of wearable and portable electronics in modern society and industry,researchers from all over the world have reported on advances in energy harvesting and self-powered sensing technologies....With the growing importance of wearable and portable electronics in modern society and industry,researchers from all over the world have reported on advances in energy harvesting and self-powered sensing technologies.The current review discusses recent developments in triboelectric platforms from a manufacturing perspective,including material,design,application,and industrialization.Manufacturing is an essential component of both industry and technology.The use of a proper manufacturing process enables cutting-edge technology in a lab-scale stage to progress to commercialization and popularization with scalability,availability,commercial advantage,and consistent quality.Furthermore,much literature has emphasized that the most powerful advantage of the triboelectric platform is its wide range of available materials and simple working mechanism,both of which are important characteristics in manufacturing engineering.As a result,different manufacturing processes can be implemented as needed.Because the practical process can have a synergetic effect on the fundamental development,resulting in the growth of both,the development of the triboelectric platform from the standpoint of manufacturing engineering can be further advanced.However,research into the development of a productive manufacturing process is still in its early stages in the field of triboelectric platforms.This review looks at the various manufacturing technologies used in previous studies and discusses the potential benefits of the appropriate process for triboelectric platforms.Given its unique strength,which includes a diverse material selection and a simple working mechanism,the triboelectric platform can use a variety of manufacturing technologies and the process can be optimized as needed.Numerous research groups have clearly demonstrated the triboelectric platform's advantages.As a result,using appropriate manufacturing processes can accelerate the technological advancement of triboelectric platforms in a variety of research and industrial fields by allowing them to move beyond the lab-scale fabrication stage.展开更多
This review provides an insightful and comprehensive exploration of the emerging 2D material borophene,both pristine and modified,emphasizing its unique attributes and potential for sustainable applications.Borophene...This review provides an insightful and comprehensive exploration of the emerging 2D material borophene,both pristine and modified,emphasizing its unique attributes and potential for sustainable applications.Borophene’s distinctive properties include its anisotropic crystal structures that contribute to its exceptional mechanical and electronic properties.The material exhibits superior electrical and thermal conductivity,surpassing many other 2D materials.Borophene’s unique atomic spin arrangements further diversify its potential application for magnetism.Surface and interface engineering,through doping,functionalization,and synthesis of hybridized and nanocomposite borophene-based systems,is crucial for tailoring borophene’s properties to specific applications.This review aims to address this knowledge gap through a comprehensive and critical analysis of different synthetic and functionalisation methods,to enhance surface reactivity by increasing active sites through doping and surface modifications.These approaches optimize diffusion pathways improving accessibility for catalytic reactions,and tailor the electronic density to tune the optical and electronic behavior.Key applications explored include energy systems(batteries,supercapacitors,and hydrogen storage),catalysis for hydrogen and oxygen evolution reactions,sensors,and optoelectronics for advanced photonic devices.The key to all these applications relies on strategies to introduce heteroatoms for tuning electronic and catalytic properties,employ chemical modifications to enhance stability and leverage borophene’s conductivity and reactivity for advanced photonics.Finally,the review addresses challenges and proposes solutions such as encapsulation,functionalization,and integration with composites to mitigate oxidation sensitivity and overcome scalability barriers,enabling sustainable,commercial-scale applications.展开更多
DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in...DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.展开更多
Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on society.Extracellular vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent bioc...Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on society.Extracellular vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent biocompatibility in vivo and have significant advantages in the management of ischemic stroke.However,the uncertain distribution and rapid clearance of extracellular vesicles impede their delivery efficiency.By utilizing membrane decoration or by encapsulating therapeutic cargo within extracellular vesicles,their delivery efficacy may be greatly improved.Furthermore,previous studies have indicated that microvesicles,a subset of large-sized extracellular vesicles,can transport mitochondria to neighboring cells,thereby aiding in the restoration of mitochondrial function post-ischemic stroke.Small extracellular vesicles have also demonstrated the capability to transfer mitochondrial components,such as proteins or deoxyribonucleic acid,or their sub-components,for extracellular vesicle-based ischemic stroke therapy.In this review,we undertake a comparative analysis of the isolation techniques employed for extracellular vesicles and present an overview of the current dominant extracellular vesicle modification methodologies.Given the complex facets of treating ischemic stroke,we also delineate various extracellular vesicle modification approaches which are suited to different facets of the treatment process.Moreover,given the burgeoning interest in mitochondrial delivery,we delved into the feasibility and existing research findings on the transportation of mitochondrial fractions or intact mitochondria through small extracellular vesicles and microvesicles to offer a fresh perspective on ischemic stroke therapy.展开更多
Zn anode-based electrochromic devices(ZECDs)stand out as a highly promising technology in the upcoming era of multifunctional electronic devices,offering a blend of electrochromic capabilities and energy storage funct...Zn anode-based electrochromic devices(ZECDs)stand out as a highly promising technology in the upcoming era of multifunctional electronic devices,offering a blend of electrochromic capabilities and energy storage functions within a single transparent platform.However,significant challenges persist in achieving efficient patterning,ensuring long-term stability,and fast color-switching kinetics for these devices.In this study,heterogeneous tungsten oxide nanowires(W_(17)O_(47)/Na_(0.1)WO_(3),WNOs)are formulated into inkjet printing ink to assemble patternable ZECDs.The heterogeneous electrode structure of WNO enables a highly capacitive-controlled mechanism that promotes fast electrochromic/electrochemical behavior.Notably,by utilizing a three-dimensional MXene mesh modified substrate,the inkjet-printed ZECDs exhibit a wide optical modulation range of 69.13%,rapid color-changing kinetics(t_(c)=4.1 s,t_(b)=5.4 s),and highly reversible capacities of 70 mAh cm^(-2)over 1000 cycles.This scalable strategy develops the patterned electrodes with a wide optical modulation range and substantial energy storage properties,offering promising prospects for their application in next-generation smart electronics.展开更多
This paper presents a design method to implement an antenna array characterized by ultra-wide beam coverage,low profile,and low Sidelobe Level(SLL)for the application of Unmanned Aerial Vehicle(UAV)air-to-ground commu...This paper presents a design method to implement an antenna array characterized by ultra-wide beam coverage,low profile,and low Sidelobe Level(SLL)for the application of Unmanned Aerial Vehicle(UAV)air-to-ground communication.The array consists of ten broadside-radiating,ultrawide-beamwidth elements that are cascaded by a central-symmetry series-fed network with tapered currents following Dolph-Chebyshev distribution to provide low SLL.First,an innovative design of end-fire Huygens source antenna that is compatible with metal ground is presented.A low-profile,half-mode Microstrip Patch Antenna(MPA)is utilized to serve as the magnetic dipole and a monopole is utilized to serves as the electric dipole,constructing the compact,end-fire,grounded Huygens source antenna.Then,two opposite-oriented end-fire Huygens source antennas are seamlessly integrated into a single antenna element in the form of monopole-loaded MPA to accomplish the ultrawide,broadside-radiating beam.Particular consideration has been applied into the design of series-fed network as well as antenna element to compensate the adverse coupling effects between elements on the radiation performance.Experiment indicates an ultrawide Half-Power Beamwidth(HPBW)of 161°and a low SLL of-25 dB with a high gain of 12 d Bi under a single-layer configuration.The concurrent ultrawide beamwidth and low SLL make it particularly attractive for applications of UAV air-to-ground communication.展开更多
Recycling plastic waste into triboelectric nanogenerators(TENGs)presents a sustainable approach to energy harvesting,self-powered sensing,and environmental remediation.This study investigates the recycling of polyviny...Recycling plastic waste into triboelectric nanogenerators(TENGs)presents a sustainable approach to energy harvesting,self-powered sensing,and environmental remediation.This study investigates the recycling of polyvinyl chloride(PVC)pipe waste polymers into nanofibers(NFs)optimized for TENG applications.We focused on optimizing the morphology of recycled PVC polymer to NFs and enhancing their piezoelectric properties by incorporating ZnO nanoparticles(NPs).The optimized PVC/0.5 wt%ZnO NFs were tested with Nylon-6 NFs,and copper(Cu)electrodes.The Nylon-6 NFs exhibited a power density of 726.3μWcm^(-2)—1.13 times higher than Cu and maintained 90%stability after 172800 cycles,successfully powering various colored LEDs.Additionally,a 3D-designed device was developed to harvest energy from biomechanical movements such as finger tapping,hand tapping,and foot pressing,making it suitable for wearable energy harvesting,automatic switches,and invisible sensors in surveillance systems.This study demonstrates that recycling polymers for TENG devices can effectively address energy,sensor,and environmental challenges.展开更多
Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the...Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.展开更多
In this paper,we investigate a Recofigurable Intelligent Surface(RIS)-assisted Free-Space Optics-Radio Frequency(FSO-RF)mixed dual-hop communication system for Unmanned Aerial Vehicles(UAVs).In the first hop,a source ...In this paper,we investigate a Recofigurable Intelligent Surface(RIS)-assisted Free-Space Optics-Radio Frequency(FSO-RF)mixed dual-hop communication system for Unmanned Aerial Vehicles(UAVs).In the first hop,a source UAV transmits data to a relay UAV using the FSO technique.In the second hop,the relay UAV forwards data to a destination Mobile Station(MS)via an RF channel,with the RIS enhancing coverage and performance.The relay UAV operates in a Decode-and-Forward(DF)mode.As the main contribution,we provide a mathematical performance analysis of the RIS-assisted FSO-RF mixed dual-hop UAV system,evaluating outage probability,Bit-Error Rate(BER),and average capacity.The analysis accounts for factors such as atmospheric attenuation,turbulence,geometric losses,and link interruptions caused by UAV hovering behaviors.To the best of our knowledge,this is the first theoretical investigation of RIS-assisted FSO-RF mixed dual-hop UAV communication systems.Our analytical results show strong agreement with Monte Carlo simulation outcomes.Furthermore,simulation results demonstrate that RIS significantly enhances the performance of UAV-aided mixed RF/FSO systems,although performance saturation is observed due to uncertainties stemming from UAV hovering behavior.展开更多
This paper presents an advanced control strategy for DC-DC buck converters utilizing Non-Minimal State Space (NMSS) representation combined with Proportional-Integral-Plus (PIP) control, optimized through Linear Quadr...This paper presents an advanced control strategy for DC-DC buck converters utilizing Non-Minimal State Space (NMSS) representation combined with Proportional-Integral-Plus (PIP) control, optimized through Linear Quadratic Regulator (LQR) design. The proposed approach leverages NMSS to eliminate the need for state observers, enhancing robustness against model mismatch and improving overall system performance. The PIP controller extends traditional PI control by incorporating additional dynamic feedback. Experimental results demonstrate that the NMSS-PIP-LQR controlled buck converter achieves excellent dynamic performance. The design procedure is fully documented, and microcontroller implementation issues are discussed.展开更多
Air pollution,specifically fine particulate matter(PM2.5),represents a critical environmental and public health concern due to its adverse effects on respiratory and cardiovascular systems.Accurate forecasting of PM2....Air pollution,specifically fine particulate matter(PM2.5),represents a critical environmental and public health concern due to its adverse effects on respiratory and cardiovascular systems.Accurate forecasting of PM2.5 concentrations is essential for mitigating health risks;however,the inherent nonlinearity and dynamic variability of air quality data present significant challenges.This study conducts a systematic evaluation of deep learning algorithms including Convolutional Neural Network(CNN),Long Short-Term Memory(LSTM),and the hybrid CNN-LSTM as well as statistical models,AutoRegressive Integrated Moving Average(ARIMA)and Maximum Likelihood Estimation(MLE)for hourly PM2.5 forecasting.Model performance is quantified using Root Mean Squared Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),and the Coefficient of Determination(R^(2))metrics.The comparative analysis identifies optimal predictive approaches for air quality modeling,emphasizing computational efficiency and accuracy.Additionally,CNN classification performance is evaluated using a confusion matrix,accuracy,precision,and F1-score.The results demonstrate that the Hybrid CNN-LSTM model outperforms standalone models,exhibiting lower error rates and higher R^(2) values,thereby highlighting the efficacy of deep learning-based hybrid architectures in achieving robust and precise PM2.5 forecasting.This study underscores the potential of advanced computational techniques in enhancing air quality prediction systems for environmental and public health applications.展开更多
This study investigates the stabilization challenge at the boundaries of a type II thermoelastic network with n-star configuration and terminal masses,which experiences non-uniform bounded external disturbances at its...This study investigates the stabilization challenge at the boundaries of a type II thermoelastic network with n-star configuration and terminal masses,which experiences non-uniform bounded external disturbances at its control boundary.This research employs an advanced active disturbance rejection control framework,incorporating an innovative observer with adaptive gain characteristics for precise disturbance estimation,coupled with a robust feedback control mechanism for disturbance compensation.The theoretical analysis establishes rigorous convergence proofs for the proposed time-dependent extended state observer.Furthermore,this investigation utilizes semigroup theory to validate the closed-loop system’s well-posed.Through comprehensive Lyapunov-based analysis,this study confirms the system’s capability to achieve exponential convergence of tracking errors while effectively mitigating disturbance effects.Extensive numerical experiments corroborate the theoretical findings,demonstrating the control scheme’s practical efficacy.展开更多
The application of generative artificial intelligence(AI)is bringing about notable changes in anime creation.This paper surveys recent advancements and applications of diffusion and language models in anime generation...The application of generative artificial intelligence(AI)is bringing about notable changes in anime creation.This paper surveys recent advancements and applications of diffusion and language models in anime generation,focusing on their demonstrated potential to enhance production efficiency through automation and personalization.Despite these benefits,it is crucial to acknowledge the substantial initial computational investments required for training and deploying these models.We conduct an in-depth survey of cutting-edge generative AI technologies,encompassing models such as Stable Diffusion and GPT,and appraise pivotal large-scale datasets alongside quantifiable evaluation metrics.Review of the surveyed literature indicates the achievement of considerable maturity in the capacity of AI models to synthesize high-quality,aesthetically compelling anime visual images from textual prompts,alongside discernible progress in the generation of coherent narratives.However,achieving perfect long-form consistency,mitigating artifacts like flickering in video sequences,and enabling fine-grained artistic control remain critical ongoing challenges.Building upon these advancements,research efforts have increasingly pivoted towards the synthesis of higher-dimensional content,such as video and three-dimensional assets,with recent studies demonstrating significant progress in this burgeoning field.Nevertheless,formidable challenges endure amidst these advancements.Foremost among these are the substantial computational exigencies requisite for training and deploying these sophisticated models,particularly pronounced in the realm of high-dimensional generation such as video synthesis.Additional persistent hurdles include maintaining spatial-temporal consistency across complex scenes and mitigating ethical considerations surrounding bias and the preservation of human creative autonomy.This research underscores the transformative potential and inherent complexities of AI-driven synergy within the creative industries.We posit that future research should be dedicated to the synergistic fusion of diffusion and autoregressive models,the integration of multimodal inputs,and the balanced consideration of ethical implications,particularly regarding bias and the preservation of human creative autonomy,thereby establishing a robust foundation for the advancement of anime creation and the broader landscape of AI-driven content generation.展开更多
Spin-momentum locking is widely regarded as an inherent property of evanescent waves,where the transverse spin angular momentum is intrinsically tied to the wave's polarization.This principle is well established i...Spin-momentum locking is widely regarded as an inherent property of evanescent waves,where the transverse spin angular momentum is intrinsically tied to the wave's polarization.This principle is well established in systems such as surface plasmon polaritons,surface elastic waves,and other evanescent modes.Here,we theoretically unveil an anomalous breakdown of spin-momentum locking in evanescent electromagnetic waves at a metalgyromagnetic interface.We show that the hybrid polarization of the field induces two successive reversals of transverse spin near the interface—directly violating the conventional locking between spin and momentum.As a result,identical chiral sources placed at different heights above the interface excite evanescent waves propagating in opposite directions,defying standard expectations.This discovery challenges the presumed universality of spin-momentum locking and opens new degrees of freedom for controlling wave propagation in photonic and plasmonic systems.展开更多
Cyber-Physical System (CPS) devices are increasing exponentially. Lacking confidentiality creates a vulnerable network. Thus, demanding the overall system with the latest and robust solutions for the defence mechanism...Cyber-Physical System (CPS) devices are increasing exponentially. Lacking confidentiality creates a vulnerable network. Thus, demanding the overall system with the latest and robust solutions for the defence mechanisms with low computation cost, increased integrity, and surveillance. The proposal of a mechanism that utilizes the features of authenticity measures using the Destination Sequence Distance Vector (DSDV) routing protocol which applies to the multi-WSN (Wireless Sensor Network) of IoT devices in CPS which is developed for the Device-to-Device (D2D) authentication developed from the local-chain and public chain respectively combined with the Software Defined Networking (SDN) control and monitoring system using switches and controllers that will route the packets through the network, identify any false nodes, take preventive measures against them and preventing them for any future problems. Next, the system is powered by Blockchain cryptographic features by utilizing the TrustChain features to create a private, secure, and temper-free ledger of the transactions performed inside the network. Results are achieved in the legitimate devices connecting to the network, transferring their packets to their destination under supervision, reporting whenever a false node is causing hurdles, and recording the transactions for temper-proof records. Evaluation results based on 1000+ transactions illustrate that the proposed mechanism not only outshines most aspects of Cyber-Physical systems but also consumes less computation power with a low latency of 0.1 seconds only.展开更多
The sinkhole attack is one of the most damaging threats in the Internet of Things(IoT).It deceptively attracts neighboring nodes and initiates malicious activity,often disrupting the network when combined with other a...The sinkhole attack is one of the most damaging threats in the Internet of Things(IoT).It deceptively attracts neighboring nodes and initiates malicious activity,often disrupting the network when combined with other attacks.This study proposes a novel approach,named NADSA,to detect and isolate sinkhole attacks.NADSA is based on the RPL protocol and consists of two detection phases.In the first phase,the minimum possible hop count between the sender and receiver is calculated and compared with the sender’s reported hop count.The second phase utilizes the number of DIO messages to identify suspicious nodes and then applies a fuzzification process using RSSI,ETX,and distance measurements to confirm the presence of a malicious node.The proposed method is extensively simulated in highly lossy and sparse network environments with varying numbers of nodes.The results demonstrate that NADSA achieves high efficiency,with PDRs of 68%,70%,and 73%;E2EDs of 81,72,and 60 ms;TPRs of 89%,83%,and 80%;and FPRs of 24%,28%,and 33%.NADSA outperforms existing methods in challenging network conditions,where traditional approaches typically degrade in effectiveness.展开更多
Structured illumination,a wide-field imaging approach used in microscopy to enhance image resolution beyond the system's diffraction limits,is a well-studied technique that has gained significant traction over the...Structured illumination,a wide-field imaging approach used in microscopy to enhance image resolution beyond the system's diffraction limits,is a well-studied technique that has gained significant traction over the last two decades.However,when translated to endoscopic systems,severe deformations of illumination patterns occur due to the large depth of field(DOF)and the 3D nature of the targets,introducing significant implementation challenges.Hence,this study explores a speckle-based system that best suits endoscopic practices to enhance image resolution by using random illumination patterns.The study presents a prototypic model of an endoscopic add-on,its design,and fabrication facilitated by using the speckle structured illumination endoscopic(SSIE)system.The imaging results of the SSIE are explained on a colon phantom model at different imaging planes with a wide field of view(FOV)and DOF.The obtained imaging metrics are elucidated and compared with state-of-the-art(SOA)high-resolution endoscopic techniques.Moreover,the potential for a clinical translation of the prototypic SSIE model is also explored in this work.The incorporation of the add-on and its subsequent results on the colon phantom model could potentially pave the way for its successful integration and use in futuristic clinical endoscopic trials.展开更多
1.Introduction.In recent decades,the pursuit of miniaturization has been crucial in nanofabrication,fostering innovation,and enabling novel applications in chip manufacturing,nanophotonics,and quantum devices[1,2].Adv...1.Introduction.In recent decades,the pursuit of miniaturization has been crucial in nanofabrication,fostering innovation,and enabling novel applications in chip manufacturing,nanophotonics,and quantum devices[1,2].Advancements in nanofabrication technology are driven by the demand for higher component density and performance,necessitating precise material processing in atmospheric environments.展开更多
Rail defects can pose significant safety risks in railway operations, raising the need for effective detection methods. Acoustic Emission (AE) technology has shown promise for identifying and monitoring these defects,...Rail defects can pose significant safety risks in railway operations, raising the need for effective detection methods. Acoustic Emission (AE) technology has shown promise for identifying and monitoring these defects, and this study evaluates an advanced on-vehicle AE detection approach using bone-conduct sensors—a solution to improve upon previous AE methods of using on-rail sensor installations, which required extensive, costly on-rail sensor networks with limited effectiveness. In response to these challenges, the study specifically explored bone-conduct sensors mounted directly on the vehicle rather than rails by evaluating AE signals generated by the interaction between rails and the train’s wheels while in motion. In this research, a prototype detection system was developed and tested through initial trials at the Nevada Railroad Museum using a track with pre-damaged welding defects. Further testing was conducted at the Transportation Technology Center Inc. (rebranded as MxV Rail) in Colorado, where the system’s performance was evaluated across various defect types and train speeds. The results indicated that bone-conduct sensors were insufficient for detecting AE signals when mounted on moving vehicles. These findings highlight the limitations of contact-based methods in real-world applications and indicate the need for exploring improved, non-contact approaches.展开更多
文摘This review paper examines the various types of electrical generators used to convert wave energy into electrical energy.The focus is on both linear and rotary generators,including their design principles,operational efficiencies,and technological advancements.Linear generators,such as Induction,permanent magnet synchronous,and switched reluctance types,are highlighted for their direct conversion capability,eliminating the need for mechanical gearboxes.Rotary Induction generators,permanent magnet synchronous generators,and doubly-fed Induction generators are evaluated for their established engineering principles and integration with existing grid infrastructure.The paper discusses the historical development,environmental benefits,and ongoing advancements in wave energy technologies,emphasizing the increasing feasibility and scalability of wave energy as a renewable source.Through a comprehensive analysis,this review provides insights into the current state and future prospects of electrical generators in wave energy conversion,underscoring their potential to significantly reduce reliance on fossil fuels and mitigate environmental impacts.
基金supported by the National Research Foundation of Korea(NRF)(No.2021R1C1C2009703)supported by the National Research Foundation of Korea(NRF)Grant funded by the Korea government(MSIT)(RS-2024-00344920)supported by the Human Resources Development of the Korea Institute of Energy Technology Evaluation and Planning(KETEP)Grant funded by the Ministry of Trade,Industry and Energy of Korea(No.RS2023-00244330)。
文摘With the growing importance of wearable and portable electronics in modern society and industry,researchers from all over the world have reported on advances in energy harvesting and self-powered sensing technologies.The current review discusses recent developments in triboelectric platforms from a manufacturing perspective,including material,design,application,and industrialization.Manufacturing is an essential component of both industry and technology.The use of a proper manufacturing process enables cutting-edge technology in a lab-scale stage to progress to commercialization and popularization with scalability,availability,commercial advantage,and consistent quality.Furthermore,much literature has emphasized that the most powerful advantage of the triboelectric platform is its wide range of available materials and simple working mechanism,both of which are important characteristics in manufacturing engineering.As a result,different manufacturing processes can be implemented as needed.Because the practical process can have a synergetic effect on the fundamental development,resulting in the growth of both,the development of the triboelectric platform from the standpoint of manufacturing engineering can be further advanced.However,research into the development of a productive manufacturing process is still in its early stages in the field of triboelectric platforms.This review looks at the various manufacturing technologies used in previous studies and discusses the potential benefits of the appropriate process for triboelectric platforms.Given its unique strength,which includes a diverse material selection and a simple working mechanism,the triboelectric platform can use a variety of manufacturing technologies and the process can be optimized as needed.Numerous research groups have clearly demonstrated the triboelectric platform's advantages.As a result,using appropriate manufacturing processes can accelerate the technological advancement of triboelectric platforms in a variety of research and industrial fields by allowing them to move beyond the lab-scale fabrication stage.
基金the Engineering and Physical Sciences Research Council(EPSRC)for funding the researchUK India Education Research Initiative(UKIERI)for funding support.
文摘This review provides an insightful and comprehensive exploration of the emerging 2D material borophene,both pristine and modified,emphasizing its unique attributes and potential for sustainable applications.Borophene’s distinctive properties include its anisotropic crystal structures that contribute to its exceptional mechanical and electronic properties.The material exhibits superior electrical and thermal conductivity,surpassing many other 2D materials.Borophene’s unique atomic spin arrangements further diversify its potential application for magnetism.Surface and interface engineering,through doping,functionalization,and synthesis of hybridized and nanocomposite borophene-based systems,is crucial for tailoring borophene’s properties to specific applications.This review aims to address this knowledge gap through a comprehensive and critical analysis of different synthetic and functionalisation methods,to enhance surface reactivity by increasing active sites through doping and surface modifications.These approaches optimize diffusion pathways improving accessibility for catalytic reactions,and tailor the electronic density to tune the optical and electronic behavior.Key applications explored include energy systems(batteries,supercapacitors,and hydrogen storage),catalysis for hydrogen and oxygen evolution reactions,sensors,and optoelectronics for advanced photonic devices.The key to all these applications relies on strategies to introduce heteroatoms for tuning electronic and catalytic properties,employ chemical modifications to enhance stability and leverage borophene’s conductivity and reactivity for advanced photonics.Finally,the review addresses challenges and proposes solutions such as encapsulation,functionalization,and integration with composites to mitigate oxidation sensitivity and overcome scalability barriers,enabling sustainable,commercial-scale applications.
基金the National Natural Science Foundation of China(62271485,61903363,U1811463,62103411,62203250)the Science and Technology Development Fund of Macao SAR(0093/2023/RIA2,0050/2020/A1)。
文摘DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.
基金supported by the grants from University of Macao,China,Nos.MYRG2022-00221-ICMS(to YZ)and MYRG-CRG2022-00011-ICMS(to RW)the Natural Science Foundation of Guangdong Province,No.2023A1515010034(to YZ)。
文摘Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on society.Extracellular vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent biocompatibility in vivo and have significant advantages in the management of ischemic stroke.However,the uncertain distribution and rapid clearance of extracellular vesicles impede their delivery efficiency.By utilizing membrane decoration or by encapsulating therapeutic cargo within extracellular vesicles,their delivery efficacy may be greatly improved.Furthermore,previous studies have indicated that microvesicles,a subset of large-sized extracellular vesicles,can transport mitochondria to neighboring cells,thereby aiding in the restoration of mitochondrial function post-ischemic stroke.Small extracellular vesicles have also demonstrated the capability to transfer mitochondrial components,such as proteins or deoxyribonucleic acid,or their sub-components,for extracellular vesicle-based ischemic stroke therapy.In this review,we undertake a comparative analysis of the isolation techniques employed for extracellular vesicles and present an overview of the current dominant extracellular vesicle modification methodologies.Given the complex facets of treating ischemic stroke,we also delineate various extracellular vesicle modification approaches which are suited to different facets of the treatment process.Moreover,given the burgeoning interest in mitochondrial delivery,we delved into the feasibility and existing research findings on the transportation of mitochondrial fractions or intact mitochondria through small extracellular vesicles and microvesicles to offer a fresh perspective on ischemic stroke therapy.
基金funding from the Natural Science Foundation of Jiangsu Province(BK20210480)the grant from National Innovation Center of Advanced Dyeing&Finishing Technology(2022GCJJ08).
文摘Zn anode-based electrochromic devices(ZECDs)stand out as a highly promising technology in the upcoming era of multifunctional electronic devices,offering a blend of electrochromic capabilities and energy storage functions within a single transparent platform.However,significant challenges persist in achieving efficient patterning,ensuring long-term stability,and fast color-switching kinetics for these devices.In this study,heterogeneous tungsten oxide nanowires(W_(17)O_(47)/Na_(0.1)WO_(3),WNOs)are formulated into inkjet printing ink to assemble patternable ZECDs.The heterogeneous electrode structure of WNO enables a highly capacitive-controlled mechanism that promotes fast electrochromic/electrochemical behavior.Notably,by utilizing a three-dimensional MXene mesh modified substrate,the inkjet-printed ZECDs exhibit a wide optical modulation range of 69.13%,rapid color-changing kinetics(t_(c)=4.1 s,t_(b)=5.4 s),and highly reversible capacities of 70 mAh cm^(-2)over 1000 cycles.This scalable strategy develops the patterned electrodes with a wide optical modulation range and substantial energy storage properties,offering promising prospects for their application in next-generation smart electronics.
基金supported by the National Natural Science Foundation of China(No.62371080 and 62031006)the National Science Foundation of Chongqing,China(No.CSTB2022NSCQ-MSX0597)the Venture&Innovation Support Program for Chongqing Overseas Returnees,China(No.cx2022063)。
文摘This paper presents a design method to implement an antenna array characterized by ultra-wide beam coverage,low profile,and low Sidelobe Level(SLL)for the application of Unmanned Aerial Vehicle(UAV)air-to-ground communication.The array consists of ten broadside-radiating,ultrawide-beamwidth elements that are cascaded by a central-symmetry series-fed network with tapered currents following Dolph-Chebyshev distribution to provide low SLL.First,an innovative design of end-fire Huygens source antenna that is compatible with metal ground is presented.A low-profile,half-mode Microstrip Patch Antenna(MPA)is utilized to serve as the magnetic dipole and a monopole is utilized to serves as the electric dipole,constructing the compact,end-fire,grounded Huygens source antenna.Then,two opposite-oriented end-fire Huygens source antennas are seamlessly integrated into a single antenna element in the form of monopole-loaded MPA to accomplish the ultrawide,broadside-radiating beam.Particular consideration has been applied into the design of series-fed network as well as antenna element to compensate the adverse coupling effects between elements on the radiation performance.Experiment indicates an ultrawide Half-Power Beamwidth(HPBW)of 161°and a low SLL of-25 dB with a high gain of 12 d Bi under a single-layer configuration.The concurrent ultrawide beamwidth and low SLL make it particularly attractive for applications of UAV air-to-ground communication.
基金supported by the research projects AP23486880 from the Ministry of Higher EducationScience of the Republic of Kazakhstan and 111024CRP2010,20122022FD4135 from Nazarbayev University.
文摘Recycling plastic waste into triboelectric nanogenerators(TENGs)presents a sustainable approach to energy harvesting,self-powered sensing,and environmental remediation.This study investigates the recycling of polyvinyl chloride(PVC)pipe waste polymers into nanofibers(NFs)optimized for TENG applications.We focused on optimizing the morphology of recycled PVC polymer to NFs and enhancing their piezoelectric properties by incorporating ZnO nanoparticles(NPs).The optimized PVC/0.5 wt%ZnO NFs were tested with Nylon-6 NFs,and copper(Cu)electrodes.The Nylon-6 NFs exhibited a power density of 726.3μWcm^(-2)—1.13 times higher than Cu and maintained 90%stability after 172800 cycles,successfully powering various colored LEDs.Additionally,a 3D-designed device was developed to harvest energy from biomechanical movements such as finger tapping,hand tapping,and foot pressing,making it suitable for wearable energy harvesting,automatic switches,and invisible sensors in surveillance systems.This study demonstrates that recycling polymers for TENG devices can effectively address energy,sensor,and environmental challenges.
基金supported in part by National Institute of Health(NIH),USA(Grant Nos.:R01GM126189,R01AI164266,and R35GM148196)the National Science Foundation,USA(Grant Nos.DMS2052983,DMS-1761320,and IIS-1900473)+3 种基金National Aero-nautics and Space Administration(NASA),USA(Grant No.:80NSSC21M0023)Michigan State University(MSU)Foundation,USA,Bristol-Myers Squibb(Grant No.:65109)USA,and Pfizer,USAsupported by the National Natural Science Foundation of China(Grant Nos.:11971367,12271416,and 11972266).
文摘Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.
基金supported in part by the National Research Foundation of Korea(NRF)funded by the Korea government(MSIT)under Grant NRF-2022R1I1A3073740in part by the MSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2024-RS-2024-00436406)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation)+1 种基金in part by the Institute for Information and Communications Technology Promotion(IITP)Grant funded by the Korea Government(MSIP,Development of Cube Satellites Based on Core Technologies in Low Earth Orbit Satellite Communications)under Grant RS-2024-00396992in part by the Korea Research Institute for Defense Technology planning and advancement(KRIT)grant,funded by the Korea government(DAPA(Defense Acquisition Program Administration))(21-106-A00-007,Space-Layer Intelligent Communication Network Laboratory,2022).
文摘In this paper,we investigate a Recofigurable Intelligent Surface(RIS)-assisted Free-Space Optics-Radio Frequency(FSO-RF)mixed dual-hop communication system for Unmanned Aerial Vehicles(UAVs).In the first hop,a source UAV transmits data to a relay UAV using the FSO technique.In the second hop,the relay UAV forwards data to a destination Mobile Station(MS)via an RF channel,with the RIS enhancing coverage and performance.The relay UAV operates in a Decode-and-Forward(DF)mode.As the main contribution,we provide a mathematical performance analysis of the RIS-assisted FSO-RF mixed dual-hop UAV system,evaluating outage probability,Bit-Error Rate(BER),and average capacity.The analysis accounts for factors such as atmospheric attenuation,turbulence,geometric losses,and link interruptions caused by UAV hovering behaviors.To the best of our knowledge,this is the first theoretical investigation of RIS-assisted FSO-RF mixed dual-hop UAV communication systems.Our analytical results show strong agreement with Monte Carlo simulation outcomes.Furthermore,simulation results demonstrate that RIS significantly enhances the performance of UAV-aided mixed RF/FSO systems,although performance saturation is observed due to uncertainties stemming from UAV hovering behavior.
文摘This paper presents an advanced control strategy for DC-DC buck converters utilizing Non-Minimal State Space (NMSS) representation combined with Proportional-Integral-Plus (PIP) control, optimized through Linear Quadratic Regulator (LQR) design. The proposed approach leverages NMSS to eliminate the need for state observers, enhancing robustness against model mismatch and improving overall system performance. The PIP controller extends traditional PI control by incorporating additional dynamic feedback. Experimental results demonstrate that the NMSS-PIP-LQR controlled buck converter achieves excellent dynamic performance. The design procedure is fully documented, and microcontroller implementation issues are discussed.
文摘Air pollution,specifically fine particulate matter(PM2.5),represents a critical environmental and public health concern due to its adverse effects on respiratory and cardiovascular systems.Accurate forecasting of PM2.5 concentrations is essential for mitigating health risks;however,the inherent nonlinearity and dynamic variability of air quality data present significant challenges.This study conducts a systematic evaluation of deep learning algorithms including Convolutional Neural Network(CNN),Long Short-Term Memory(LSTM),and the hybrid CNN-LSTM as well as statistical models,AutoRegressive Integrated Moving Average(ARIMA)and Maximum Likelihood Estimation(MLE)for hourly PM2.5 forecasting.Model performance is quantified using Root Mean Squared Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),and the Coefficient of Determination(R^(2))metrics.The comparative analysis identifies optimal predictive approaches for air quality modeling,emphasizing computational efficiency and accuracy.Additionally,CNN classification performance is evaluated using a confusion matrix,accuracy,precision,and F1-score.The results demonstrate that the Hybrid CNN-LSTM model outperforms standalone models,exhibiting lower error rates and higher R^(2) values,thereby highlighting the efficacy of deep learning-based hybrid architectures in achieving robust and precise PM2.5 forecasting.This study underscores the potential of advanced computational techniques in enhancing air quality prediction systems for environmental and public health applications.
文摘This study investigates the stabilization challenge at the boundaries of a type II thermoelastic network with n-star configuration and terminal masses,which experiences non-uniform bounded external disturbances at its control boundary.This research employs an advanced active disturbance rejection control framework,incorporating an innovative observer with adaptive gain characteristics for precise disturbance estimation,coupled with a robust feedback control mechanism for disturbance compensation.The theoretical analysis establishes rigorous convergence proofs for the proposed time-dependent extended state observer.Furthermore,this investigation utilizes semigroup theory to validate the closed-loop system’s well-posed.Through comprehensive Lyapunov-based analysis,this study confirms the system’s capability to achieve exponential convergence of tracking errors while effectively mitigating disturbance effects.Extensive numerical experiments corroborate the theoretical findings,demonstrating the control scheme’s practical efficacy.
基金supported by the National Natural Science Foundation of China(Grant No.62202210).
文摘The application of generative artificial intelligence(AI)is bringing about notable changes in anime creation.This paper surveys recent advancements and applications of diffusion and language models in anime generation,focusing on their demonstrated potential to enhance production efficiency through automation and personalization.Despite these benefits,it is crucial to acknowledge the substantial initial computational investments required for training and deploying these models.We conduct an in-depth survey of cutting-edge generative AI technologies,encompassing models such as Stable Diffusion and GPT,and appraise pivotal large-scale datasets alongside quantifiable evaluation metrics.Review of the surveyed literature indicates the achievement of considerable maturity in the capacity of AI models to synthesize high-quality,aesthetically compelling anime visual images from textual prompts,alongside discernible progress in the generation of coherent narratives.However,achieving perfect long-form consistency,mitigating artifacts like flickering in video sequences,and enabling fine-grained artistic control remain critical ongoing challenges.Building upon these advancements,research efforts have increasingly pivoted towards the synthesis of higher-dimensional content,such as video and three-dimensional assets,with recent studies demonstrating significant progress in this burgeoning field.Nevertheless,formidable challenges endure amidst these advancements.Foremost among these are the substantial computational exigencies requisite for training and deploying these sophisticated models,particularly pronounced in the realm of high-dimensional generation such as video synthesis.Additional persistent hurdles include maintaining spatial-temporal consistency across complex scenes and mitigating ethical considerations surrounding bias and the preservation of human creative autonomy.This research underscores the transformative potential and inherent complexities of AI-driven synergy within the creative industries.We posit that future research should be dedicated to the synergistic fusion of diffusion and autoregressive models,the integration of multimodal inputs,and the balanced consideration of ethical implications,particularly regarding bias and the preservation of human creative autonomy,thereby establishing a robust foundation for the advancement of anime creation and the broader landscape of AI-driven content generation.
基金supported by the National Natural Science Foundation of China(Grant Nos.12434016 and 12474380)Science and Technology Project of Guangdong Province(Grant No.2020B0101-90001)+1 种基金the National Key Research and Development Program of China(Grant No.2023YFA1406900)the Natural Science Foundation of Guangdong Province(Grant No.2025A1515010714)。
文摘Spin-momentum locking is widely regarded as an inherent property of evanescent waves,where the transverse spin angular momentum is intrinsically tied to the wave's polarization.This principle is well established in systems such as surface plasmon polaritons,surface elastic waves,and other evanescent modes.Here,we theoretically unveil an anomalous breakdown of spin-momentum locking in evanescent electromagnetic waves at a metalgyromagnetic interface.We show that the hybrid polarization of the field induces two successive reversals of transverse spin near the interface—directly violating the conventional locking between spin and momentum.As a result,identical chiral sources placed at different heights above the interface excite evanescent waves propagating in opposite directions,defying standard expectations.This discovery challenges the presumed universality of spin-momentum locking and opens new degrees of freedom for controlling wave propagation in photonic and plasmonic systems.
基金funded by Ajman University,AU-Funded Research Grant 2023-IRG-ENIT-22.
文摘Cyber-Physical System (CPS) devices are increasing exponentially. Lacking confidentiality creates a vulnerable network. Thus, demanding the overall system with the latest and robust solutions for the defence mechanisms with low computation cost, increased integrity, and surveillance. The proposal of a mechanism that utilizes the features of authenticity measures using the Destination Sequence Distance Vector (DSDV) routing protocol which applies to the multi-WSN (Wireless Sensor Network) of IoT devices in CPS which is developed for the Device-to-Device (D2D) authentication developed from the local-chain and public chain respectively combined with the Software Defined Networking (SDN) control and monitoring system using switches and controllers that will route the packets through the network, identify any false nodes, take preventive measures against them and preventing them for any future problems. Next, the system is powered by Blockchain cryptographic features by utilizing the TrustChain features to create a private, secure, and temper-free ledger of the transactions performed inside the network. Results are achieved in the legitimate devices connecting to the network, transferring their packets to their destination under supervision, reporting whenever a false node is causing hurdles, and recording the transactions for temper-proof records. Evaluation results based on 1000+ transactions illustrate that the proposed mechanism not only outshines most aspects of Cyber-Physical systems but also consumes less computation power with a low latency of 0.1 seconds only.
文摘The sinkhole attack is one of the most damaging threats in the Internet of Things(IoT).It deceptively attracts neighboring nodes and initiates malicious activity,often disrupting the network when combined with other attacks.This study proposes a novel approach,named NADSA,to detect and isolate sinkhole attacks.NADSA is based on the RPL protocol and consists of two detection phases.In the first phase,the minimum possible hop count between the sender and receiver is calculated and compared with the sender’s reported hop count.The second phase utilizes the number of DIO messages to identify suspicious nodes and then applies a fuzzification process using RSSI,ETX,and distance measurements to confirm the presence of a malicious node.The proposed method is extensively simulated in highly lossy and sparse network environments with varying numbers of nodes.The results demonstrate that NADSA achieves high efficiency,with PDRs of 68%,70%,and 73%;E2EDs of 81,72,and 60 ms;TPRs of 89%,83%,and 80%;and FPRs of 24%,28%,and 33%.NADSA outperforms existing methods in challenging network conditions,where traditional approaches typically degrade in effectiveness.
文摘Structured illumination,a wide-field imaging approach used in microscopy to enhance image resolution beyond the system's diffraction limits,is a well-studied technique that has gained significant traction over the last two decades.However,when translated to endoscopic systems,severe deformations of illumination patterns occur due to the large depth of field(DOF)and the 3D nature of the targets,introducing significant implementation challenges.Hence,this study explores a speckle-based system that best suits endoscopic practices to enhance image resolution by using random illumination patterns.The study presents a prototypic model of an endoscopic add-on,its design,and fabrication facilitated by using the speckle structured illumination endoscopic(SSIE)system.The imaging results of the SSIE are explained on a colon phantom model at different imaging planes with a wide field of view(FOV)and DOF.The obtained imaging metrics are elucidated and compared with state-of-the-art(SOA)high-resolution endoscopic techniques.Moreover,the potential for a clinical translation of the prototypic SSIE model is also explored in this work.The incorporation of the add-on and its subsequent results on the colon phantom model could potentially pave the way for its successful integration and use in futuristic clinical endoscopic trials.
基金supported by the National Natural Science Foun-dation of China(51975017 and 52405448)the Human Resource Training Project(HRTP-[2022]-53)of Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province(IKKEM)the support by the China Postdoctoral Science Foundation(2024M750149 and GZC20240087).
文摘1.Introduction.In recent decades,the pursuit of miniaturization has been crucial in nanofabrication,fostering innovation,and enabling novel applications in chip manufacturing,nanophotonics,and quantum devices[1,2].Advancements in nanofabrication technology are driven by the demand for higher component density and performance,necessitating precise material processing in atmospheric environments.
文摘Rail defects can pose significant safety risks in railway operations, raising the need for effective detection methods. Acoustic Emission (AE) technology has shown promise for identifying and monitoring these defects, and this study evaluates an advanced on-vehicle AE detection approach using bone-conduct sensors—a solution to improve upon previous AE methods of using on-rail sensor installations, which required extensive, costly on-rail sensor networks with limited effectiveness. In response to these challenges, the study specifically explored bone-conduct sensors mounted directly on the vehicle rather than rails by evaluating AE signals generated by the interaction between rails and the train’s wheels while in motion. In this research, a prototype detection system was developed and tested through initial trials at the Nevada Railroad Museum using a track with pre-damaged welding defects. Further testing was conducted at the Transportation Technology Center Inc. (rebranded as MxV Rail) in Colorado, where the system’s performance was evaluated across various defect types and train speeds. The results indicated that bone-conduct sensors were insufficient for detecting AE signals when mounted on moving vehicles. These findings highlight the limitations of contact-based methods in real-world applications and indicate the need for exploring improved, non-contact approaches.
