Artificial intelligence has the potential to stand as the cornerstone of human society,which could drive our civilization forward and emerge as a pivotal frontier in the ongoing technological revolution and industrial...Artificial intelligence has the potential to stand as the cornerstone of human society,which could drive our civilization forward and emerge as a pivotal frontier in the ongoing technological revolution and industrial transformation.Amidst profound shifts in the global technological landscape,smart materials,smart devices,and smart systems have become the defining pillars of our era,which will catalyze paradigm shifts in engineering science and reshape the trajectory of modern technology.展开更多
目前，全球领先的IP视音频会议系统提供商瑞福特发布了SmartStream系统。该系统是新一代融合点播、直播、互动应用，完全端到端的流媒体平台，其采用领先的自主视频编解码技术，能够在低码流的条件下实现高清晰的流媒体播放效果，是瑞...目前，全球领先的IP视音频会议系统提供商瑞福特发布了SmartStream系统。该系统是新一代融合点播、直播、互动应用，完全端到端的流媒体平台，其采用领先的自主视频编解码技术，能够在低码流的条件下实现高清晰的流媒体播放效果，是瑞福特屡获殊荣的Smart In One系统在流媒体领域的重大突破。展开更多
The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often...The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.展开更多
https://www.sciencedirect.com/journal/energy-and-buildings/vol/350/suppl/CV olume 350,1 January 2026[OA]( 1)Rooftop agrivoltaic powered onsite hydrogenp roduction for insulated gasochromic smart glazing and hydrogen v...https://www.sciencedirect.com/journal/energy-and-buildings/vol/350/suppl/CV olume 350,1 January 2026[OA]( 1)Rooftop agrivoltaic powered onsite hydrogenp roduction for insulated gasochromic smart glazing and hydrogen vehicles:A holistic approach to sustainabler esidential building by Shanza Neda Hussain,Aritra Ghosh,Article 116675 A bstract:The study focused on designing a sustainable buildingi nvolving rooftop agrivoltaics,advanced glazing technologies ando nsite hydrogen production for a residential property in Birmingham,UK where green hydrogen produced by harnessinge lectricity generated by agrivoltaics system on rooftop of the building is employed to change the transparency of vacuum gasochromic glazing and refuel hydrogen-powered fuel cell vehicle using storage hydrogen for a sustainable building approach.展开更多
Unmanned Aerial Vehicles(UAVs)have become integral components in smart city infrastructures,supporting applications such as emergency response,surveillance,and data collection.However,the high mobility and dynamic top...Unmanned Aerial Vehicles(UAVs)have become integral components in smart city infrastructures,supporting applications such as emergency response,surveillance,and data collection.However,the high mobility and dynamic topology of Flying Ad Hoc Networks(FANETs)present significant challenges for maintaining reliable,low-latency communication.Conventional geographic routing protocols often struggle in situations where link quality varies and mobility patterns are unpredictable.To overcome these limitations,this paper proposes an improved routing protocol based on reinforcement learning.This new approach integrates Q-learning with mechanisms that are both link-aware and mobility-aware.The proposed method optimizes the selection of relay nodes by using an adaptive reward function that takes into account energy consumption,delay,and link quality.Additionally,a Kalman filter is integrated to predict UAV mobility,improving the stability of communication links under dynamic network conditions.Simulation experiments were conducted using realistic scenarios,varying the number of UAVs to assess scalability.An analysis was conducted on key performance metrics,including the packet delivery ratio,end-to-end delay,and total energy consumption.The results demonstrate that the proposed approach significantly improves the packet delivery ratio by 12%–15%and reduces delay by up to 25.5%when compared to conventional GEO and QGEO protocols.However,this improvement comes at the cost of higher energy consumption due to additional computations and control overhead.Despite this trade-off,the proposed solution ensures reliable and efficient communication,making it well-suited for large-scale UAV networks operating in complex urban environments.展开更多
Background:To evaluate predictability,stability,efficacy,and safety of transepithelial photorefractive keratectomy(TPRK)using smart pulse technology(SPT)(SmartSurface procedure)of Schwind Amaris with mitomycin C for c...Background:To evaluate predictability,stability,efficacy,and safety of transepithelial photorefractive keratectomy(TPRK)using smart pulse technology(SPT)(SmartSurface procedure)of Schwind Amaris with mitomycin C for correction of post small incision lenticule extraction(SMILE)myopic residual refractive errors.Method:This study is a prospective,non-comparative case series conducted at a private eye centre in Ismailia,Egypt,on eyes with post-SMILE myopic residual refractive errors because of undercorrection or suction loss(suction loss occurred after the posterior lenticular cut and the creation of side-cuts;redocking was attempted,and the treatment was completed in the same session with the same parameters)with myopia or myopic astigmatism.The patients were followed up post-SMILE for six months before the SmartSurface procedure,and then they were followed up for one year after that.TPRK were performed using Amaris excimer laser at 500 kHz.The main outcomes included refractive predictability,stability,efficacy,safety and any reported complications.Results:This study included 68 eyes of 40 patients out of 1920 total eyes(3.5%)with post-SMILE technique myopic residual refractive errors.The average duration between the SMILE surgery and TPRK was 6.7±0.4 months(range 6 to 8 months).The mean refractive spherical equivalent(SE)was within±0.50 D of plano correction in 100%of the eyes at 12 months post-TPRK.Astigmatism of<0.50 D was achieved in 100%of the eyes.The mean of the residual SE error showed statistically significant improvement from preoperative−1.42±0.52 D to 0.23±0.10 D(P<0.0001).Uncorrected distance visual acuity(UDVA)(measured by Snellen’s chart and averaged in logMAR units)was improved significantly to 0.1±0.07(P<0.0001).UDVA was 0.2 logMAR or better in 100%of the eyes,0.1 logMAR or better in 91.2%of the eyes,and 0.0 logMAR in 20.6%of the eyes.Corrected distance visual acuity(CDVA)remained unchanged in 79.4%of eyes.14.7%of eyes gained one line of CDVA(Snellen).5.9%of eyes gained two lines of CDVA(Snellen).Conclusion:Transepithelial photorefractive keratectomy using smart pulse technology with mitomycin C enhancement after SMILE is a safe,predictable,stable,and effective technique.展开更多
Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for...Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for mitigating the energy crisis.A comprehensive review connecting the advancements in engineered radiative cooling systems(ERCSs),encompassing material and structural design as well as thermal and energy-related applications,is currently absent.Herein,this review begins with a concise summary of the essential concepts of ERCSs,followed by an introduction to engineered materials and structures,containing nature-inspired designs,chromatic materials,meta-structural configurations,and multilayered constructions.It subsequently encapsulates the primary applications,including thermal-regulating textiles and energy-saving devices.Next,it highlights the challenges of ERCSs,including maximized thermoregulatory effects,environmental adaptability,scalability and sustainability,and interdisciplinary integration.It seeks to offer direction for forthcoming fundamental research and industrial advancement of radiative cooling systems in real-world applications.展开更多
As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security ...As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security threats to blockchain ecosystems.Although numerous detection techniques have been proposed,existing methods suffer from significant limitations,such as class imbalance and insufficient modeling of transaction-related semantic features.To address these challenges,this paper proposes an oversampling-based detection framework for Ponzi smart contracts.We enhance the Adaptive Synthetic Sampling(ADASYN)algorithm by incorporating sample proximity to decision boundaries and ensuring realistic sample distributions.This enhancement facilitates the generation of high-quality minority class samples and effectively mitigates class imbalance.In addition,we design a Contract Transaction Graph(CTG)construction algorithm to preserve key transactional semantics through feature extraction from contract code.A graph neural network(GNN)is then applied for classification.This study employs a publicly available dataset from the XBlock platform,consisting of 318 verified Ponzi contracts and 6498 benign contracts.Sourced from real Ethereum deployments,the dataset reflects diverse application scenarios and captures the varied characteristics of Ponzi schemes.Experimental results demonstrate that our approach achieves an accuracy of 96%,a recall of 92%,and an F1-score of 94%in detecting Ponzi contracts,outperforming state-of-the-art methods.展开更多
Cement stands as a dominant contributor to global energy consumption and carbon emissions in the construction industry.With the upgrading of infrastructure and the improvement of building standards,traditional cement ...Cement stands as a dominant contributor to global energy consumption and carbon emissions in the construction industry.With the upgrading of infrastructure and the improvement of building standards,traditional cement fails to reconcile ecological responsibility with advanced functional performance.By incorporating tailored fillers into cement matrices,the resulting composites achieve enhanced thermoelectric(TE)conversion capabilities.These materials can harness solar radiation from building envelopes and recover waste heat from indoor thermal gradients,facilitating bidirectional energy conversion.This review offers a comprehensive and timely overview of cementbased thermoelectric materials(CTEMs),integrating material design,device fabrication,and diverse applications into a holistic perspective.It summarizes recent advancements in TE performance enhancement,encompassing fillers optimization and matrices innovation.Additionally,the review consolidates fabrication strategies and performance evaluations of cement-based thermoelectric devices(CTEDs),providing detailed discussions on their roles in monitoring and protection,energy harvesting,and smart building.We also address sustainability,durability,and lifecycle considerations of CTEMs,which are essential for real-world deployment.Finally,we outline future research directions in materials design,device engineering,and scalable manufacturing to foster the practical application of CTEMs in sustainable and intelligent infrastructure.展开更多
The long-standing use of portable toilet cubicles by residents of Shanghai’s narrow,labyrinthine alleys came to an end in September 2025 after the city largely finished building public toilets to make up their lack o...The long-standing use of portable toilet cubicles by residents of Shanghai’s narrow,labyrinthine alleys came to an end in September 2025 after the city largely finished building public toilets to make up their lack of sanitation facilities.The project,targeting 14,082 households,started last year.展开更多
文摘Artificial intelligence has the potential to stand as the cornerstone of human society,which could drive our civilization forward and emerge as a pivotal frontier in the ongoing technological revolution and industrial transformation.Amidst profound shifts in the global technological landscape,smart materials,smart devices,and smart systems have become the defining pillars of our era,which will catalyze paradigm shifts in engineering science and reshape the trajectory of modern technology.
基金The researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025)。
文摘The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.
文摘https://www.sciencedirect.com/journal/energy-and-buildings/vol/350/suppl/CV olume 350,1 January 2026[OA]( 1)Rooftop agrivoltaic powered onsite hydrogenp roduction for insulated gasochromic smart glazing and hydrogen vehicles:A holistic approach to sustainabler esidential building by Shanza Neda Hussain,Aritra Ghosh,Article 116675 A bstract:The study focused on designing a sustainable buildingi nvolving rooftop agrivoltaics,advanced glazing technologies ando nsite hydrogen production for a residential property in Birmingham,UK where green hydrogen produced by harnessinge lectricity generated by agrivoltaics system on rooftop of the building is employed to change the transparency of vacuum gasochromic glazing and refuel hydrogen-powered fuel cell vehicle using storage hydrogen for a sustainable building approach.
基金funded by Hung Yen University of Technology and Education under grand number UTEHY.L.2025.62.
文摘Unmanned Aerial Vehicles(UAVs)have become integral components in smart city infrastructures,supporting applications such as emergency response,surveillance,and data collection.However,the high mobility and dynamic topology of Flying Ad Hoc Networks(FANETs)present significant challenges for maintaining reliable,low-latency communication.Conventional geographic routing protocols often struggle in situations where link quality varies and mobility patterns are unpredictable.To overcome these limitations,this paper proposes an improved routing protocol based on reinforcement learning.This new approach integrates Q-learning with mechanisms that are both link-aware and mobility-aware.The proposed method optimizes the selection of relay nodes by using an adaptive reward function that takes into account energy consumption,delay,and link quality.Additionally,a Kalman filter is integrated to predict UAV mobility,improving the stability of communication links under dynamic network conditions.Simulation experiments were conducted using realistic scenarios,varying the number of UAVs to assess scalability.An analysis was conducted on key performance metrics,including the packet delivery ratio,end-to-end delay,and total energy consumption.The results demonstrate that the proposed approach significantly improves the packet delivery ratio by 12%–15%and reduces delay by up to 25.5%when compared to conventional GEO and QGEO protocols.However,this improvement comes at the cost of higher energy consumption due to additional computations and control overhead.Despite this trade-off,the proposed solution ensures reliable and efficient communication,making it well-suited for large-scale UAV networks operating in complex urban environments.
文摘Background:To evaluate predictability,stability,efficacy,and safety of transepithelial photorefractive keratectomy(TPRK)using smart pulse technology(SPT)(SmartSurface procedure)of Schwind Amaris with mitomycin C for correction of post small incision lenticule extraction(SMILE)myopic residual refractive errors.Method:This study is a prospective,non-comparative case series conducted at a private eye centre in Ismailia,Egypt,on eyes with post-SMILE myopic residual refractive errors because of undercorrection or suction loss(suction loss occurred after the posterior lenticular cut and the creation of side-cuts;redocking was attempted,and the treatment was completed in the same session with the same parameters)with myopia or myopic astigmatism.The patients were followed up post-SMILE for six months before the SmartSurface procedure,and then they were followed up for one year after that.TPRK were performed using Amaris excimer laser at 500 kHz.The main outcomes included refractive predictability,stability,efficacy,safety and any reported complications.Results:This study included 68 eyes of 40 patients out of 1920 total eyes(3.5%)with post-SMILE technique myopic residual refractive errors.The average duration between the SMILE surgery and TPRK was 6.7±0.4 months(range 6 to 8 months).The mean refractive spherical equivalent(SE)was within±0.50 D of plano correction in 100%of the eyes at 12 months post-TPRK.Astigmatism of<0.50 D was achieved in 100%of the eyes.The mean of the residual SE error showed statistically significant improvement from preoperative−1.42±0.52 D to 0.23±0.10 D(P<0.0001).Uncorrected distance visual acuity(UDVA)(measured by Snellen’s chart and averaged in logMAR units)was improved significantly to 0.1±0.07(P<0.0001).UDVA was 0.2 logMAR or better in 100%of the eyes,0.1 logMAR or better in 91.2%of the eyes,and 0.0 logMAR in 20.6%of the eyes.Corrected distance visual acuity(CDVA)remained unchanged in 79.4%of eyes.14.7%of eyes gained one line of CDVA(Snellen).5.9%of eyes gained two lines of CDVA(Snellen).Conclusion:Transepithelial photorefractive keratectomy using smart pulse technology with mitomycin C enhancement after SMILE is a safe,predictable,stable,and effective technique.
基金support from the Contract Research(“Development of Breathable Fabrics with Nano-Electrospun Membrane”,CityU ref.:9231419“Research and application of antibacterial and healing-promoting smart nanofiber dressing for children’s burn wounds”,CityU ref:PJ9240111)+1 种基金the National Natural Science Foundation of China(“Study of Multi-Responsive Shape Memory Polyurethane Nanocomposites Inspired by Natural Fibers”,Grant No.51673162)Startup Grant of CityU(“Laboratory of Wearable Materials for Healthcare”,Grant No.9380116).
文摘Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for mitigating the energy crisis.A comprehensive review connecting the advancements in engineered radiative cooling systems(ERCSs),encompassing material and structural design as well as thermal and energy-related applications,is currently absent.Herein,this review begins with a concise summary of the essential concepts of ERCSs,followed by an introduction to engineered materials and structures,containing nature-inspired designs,chromatic materials,meta-structural configurations,and multilayered constructions.It subsequently encapsulates the primary applications,including thermal-regulating textiles and energy-saving devices.Next,it highlights the challenges of ERCSs,including maximized thermoregulatory effects,environmental adaptability,scalability and sustainability,and interdisciplinary integration.It seeks to offer direction for forthcoming fundamental research and industrial advancement of radiative cooling systems in real-world applications.
基金supported by the Key Project of Joint Fund of the National Natural Science Foundation of China“Research on Key Technologies and Demonstration Applications for Trusted and Secure Data Circulation and Trading”(U24A20241)the National Natural Science Foundation of China“Research on Trusted Theories and Key Technologies of Data Security Trading Based on Blockchain”(62202118)+4 种基金the Major Scientific and Technological Special Project of Guizhou Province([2024]014)Scientific and Technological Research Projects from the Guizhou Education Department(Qian jiao ji[2023]003)the Hundred-Level Innovative Talent Project of the Guizhou Provincial Science and Technology Department(Qiankehe Platform Talent-GCC[2023]018)the Major Project of Guizhou Province“Research and Application of Key Technologies for Trusted Large Models Oriented to Public Big Data”(Qiankehe Major Project[2024]003)the Guizhou Province Computational Power Network Security Protection Science and Technology Innovation Talent Team(Qiankehe Talent CXTD[2025]029).
文摘As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security threats to blockchain ecosystems.Although numerous detection techniques have been proposed,existing methods suffer from significant limitations,such as class imbalance and insufficient modeling of transaction-related semantic features.To address these challenges,this paper proposes an oversampling-based detection framework for Ponzi smart contracts.We enhance the Adaptive Synthetic Sampling(ADASYN)algorithm by incorporating sample proximity to decision boundaries and ensuring realistic sample distributions.This enhancement facilitates the generation of high-quality minority class samples and effectively mitigates class imbalance.In addition,we design a Contract Transaction Graph(CTG)construction algorithm to preserve key transactional semantics through feature extraction from contract code.A graph neural network(GNN)is then applied for classification.This study employs a publicly available dataset from the XBlock platform,consisting of 318 verified Ponzi contracts and 6498 benign contracts.Sourced from real Ethereum deployments,the dataset reflects diverse application scenarios and captures the varied characteristics of Ponzi schemes.Experimental results demonstrate that our approach achieves an accuracy of 96%,a recall of 92%,and an F1-score of 94%in detecting Ponzi contracts,outperforming state-of-the-art methods.
基金supported by the National Natural Science Foundation of China(No.52242305).
文摘Cement stands as a dominant contributor to global energy consumption and carbon emissions in the construction industry.With the upgrading of infrastructure and the improvement of building standards,traditional cement fails to reconcile ecological responsibility with advanced functional performance.By incorporating tailored fillers into cement matrices,the resulting composites achieve enhanced thermoelectric(TE)conversion capabilities.These materials can harness solar radiation from building envelopes and recover waste heat from indoor thermal gradients,facilitating bidirectional energy conversion.This review offers a comprehensive and timely overview of cementbased thermoelectric materials(CTEMs),integrating material design,device fabrication,and diverse applications into a holistic perspective.It summarizes recent advancements in TE performance enhancement,encompassing fillers optimization and matrices innovation.Additionally,the review consolidates fabrication strategies and performance evaluations of cement-based thermoelectric devices(CTEDs),providing detailed discussions on their roles in monitoring and protection,energy harvesting,and smart building.We also address sustainability,durability,and lifecycle considerations of CTEMs,which are essential for real-world deployment.Finally,we outline future research directions in materials design,device engineering,and scalable manufacturing to foster the practical application of CTEMs in sustainable and intelligent infrastructure.
文摘The long-standing use of portable toilet cubicles by residents of Shanghai’s narrow,labyrinthine alleys came to an end in September 2025 after the city largely finished building public toilets to make up their lack of sanitation facilities.The project,targeting 14,082 households,started last year.
