The purpose of this study is to investigate the effectiveness of the“expiration manager”mini program in managing the validity of ward items.The program was used to manage frequently and infrequently used consumables...The purpose of this study is to investigate the effectiveness of the“expiration manager”mini program in managing the validity of ward items.The program was used to manage frequently and infrequently used consumables by setting up an automatic reminder function.The item failure rate and the time required for nurses to conduct counts over 6 months before and after implementation were compared,as well as evaluated system availability using the System Usability scale(SUS).Results showed that after implementing the mini program,both the item failure rate and non-recognition rate significantly decreased(P<0.05),while the inspection pass rate significantly increased(P<0.05),and the monthly inventory time was reduced(P<0.05).The SUS evaluation yielded a total score of 74.38±11.73,with learnability at 80.21±20.27 and availability at 72.92±11.18,all indicating good user acceptance.In conclusion,the“expiration manager”mini program can effectively improve the efficiency of item expiration management,reduce the risk of expiration,and save inspection time,thereby demonstrating high user acceptance and promising potential for wider adoption.展开更多
思维导图工具软件Mindjet Mind Manager作为一种可视化工具,最初在商业领域中得到广泛应用。近年来,国内外学者在图式理论研究基础上逐渐把其发展为一种教学手段。本文在介绍该软件的特性以及教育心理学背景的基础上,以《微波技术与天...思维导图工具软件Mindjet Mind Manager作为一种可视化工具,最初在商业领域中得到广泛应用。近年来,国内外学者在图式理论研究基础上逐渐把其发展为一种教学手段。本文在介绍该软件的特性以及教育心理学背景的基础上,以《微波技术与天线》绪论课程的实例具体说明了其在高等教育教学中有力促进教与学的优势。展开更多
介绍了应用R egion m anager软件绘制等高线的方法:测出所要绘制等高线的区域内各高程控制点的高程值,将处理后的数据输入软件,建立空间数据库,生成数字高程图并创建三角网,根据需要由软件提取出相应等高距的区域等高线.该方法简便、精...介绍了应用R egion m anager软件绘制等高线的方法:测出所要绘制等高线的区域内各高程控制点的高程值,将处理后的数据输入软件,建立空间数据库,生成数字高程图并创建三角网,根据需要由软件提取出相应等高距的区域等高线.该方法简便、精度高、节省工期、节约人力资源,还可根据系统中生成的数字高程图,进行土方量、面积、周长和距离的量算.展开更多
Heavy metal(HM)contamination severely impacts global agricultural production.HMs toxicity effectively damaged the physiological functions such as imbalanced redox homeostasis,altered antioxidant enzyme activity,damage...Heavy metal(HM)contamination severely impacts global agricultural production.HMs toxicity effectively damaged the physiological functions such as imbalanced redox homeostasis,altered antioxidant enzyme activity,damage root system architecture,hindered photosynthetic apparatus,cellular toxicity,restricted mineral accumulation,and changed the metabolite production.Using phytohormones may be a successful strategy for enhancing and stimulating plant tolerance to HMs toxicity without affecting the environment.Melatonin(MT),a novel plant growth regulator,and powerful antioxidant molecule,enhances plant resilience to HMs stress by enhancing seedling growth,protecting the photosynthetic system,increasing nutritional status,balanced redox homeostasis,and restricting HMs accumulation from root to shoot.In addition,MT enhances the activity of antioxidant enzymes and triggers the ascorbate-glutathione(AsA-GSH)cycle,which helps remove excessive ROS.MT improves RuBisCO activity to improve photosynthesis and reduce the breakdown of chlorophyll.To identify future research needs,it is crucial to understand the comprehensive and intricate regulatory mechanisms of exogenous and endogenous MT-mediated reduction of heavy metal toxicity in plants.Melatonin has several functions,and this review sheds light on those functions and the molecular processes by which it alleviates HMs toxicity.More research is needed to fully understand how melatonin affects plant tolerance to heavy metals stress.展开更多
The surge in environmental pollution in recent years driven by numerous pollutants has necessitated the search for efficient removal methods.Phytoremediation is an eco-friendly technique that provides multiple benefit...The surge in environmental pollution in recent years driven by numerous pollutants has necessitated the search for efficient removal methods.Phytoremediation is an eco-friendly technique that provides multiple benefits over conventional methods of removing contaminants.Despite the numerous benefits of this technique,it has certain limitations that can be addressed by incorporating nanoparticles to improve its effectiveness.This review paper aims to explore the impact of heavy metal pollution on plants and human health.It highlights the role and mechanism of nanoparticles in enhancing phytoremediation,their application in the detection of heavy metals,and the strategies for the safe disposal of phytoremediation biomass.Biosynthesized nanoparticles are eco-friendly and non-toxic,with applications in biomedical and environmental fields.Nanoparticles can be used in the form of nano biosensors like smartphone-operated wireless sensors made from Cinnamomum camphora,enabling efficient detection of heavy metal ions.According to the studies,nanoparticles remove 80%–97%of heavy metals by various methods like reduction,precipitation,adsorption,etc.The phytoremediation biomass disposal can be done by heat treatment,phytomining,and microbial treatment with some modifications to further enhance their results.Phytoremediation is an environmentally friendly technique but requires further research and integration with biomass energy production to overcome scalability challenges and ensure safe biomass disposal.展开更多
Shandong Port Group(SPG),which was established in August 2019,regards standardization as the cornerstone of modern enterprise management,and vigorously implements the standardization innovation strategy.Its standardiz...Shandong Port Group(SPG),which was established in August 2019,regards standardization as the cornerstone of modern enterprise management,and vigorously implements the standardization innovation strategy.Its standardization work mainly focuses on the following four aspects.展开更多
Cellulose frameworks have emerged as promising materials for light management due to their exceptional light-scattering capabilities and sustainable nature.Conventional biomass-derived cellulose frameworks face a fund...Cellulose frameworks have emerged as promising materials for light management due to their exceptional light-scattering capabilities and sustainable nature.Conventional biomass-derived cellulose frameworks face a fundamental trade-off between haze and transparency,coupled with impractical thicknesses(≥1 mm).Inspired by squid’s skin-peeling mechanism,this work develops a peroxyformic acid(HCOOOH)-enabled precision peeling strategy to isolate intact 10-μm-thick bamboo green(BG)frameworks—100×thinner than wood-based counterparts while achieving an unprecedented optical performance(88%haze with 80%transparency).This performance surpasses delignified biomass(transparency<40%at 1 mm)and matches engineered cellulose composites,yet requires no energy-intensive nanofibrillation.The preserved native cellulose I crystalline structure(64.76%crystallinity)and wax-coated uniaxial fibril alignment(Hermans factor:0.23)contribute to high mechanical strength(903 MPa modulus)and broadband light scattering.As a light-management layer in polycrystalline silicon solar cells,the BG framework boosts photoelectric conversion efficiency by 0.41%absolute(18.74%→19.15%),outperforming synthetic anti-reflective coatings.The work establishes a scalable,waste-to-wealth route for optical-grade cellulose materials in next-generation optoelectronics.展开更多
As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a no...As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.展开更多
The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.H...The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.However,maintaining consistent forwarding states during these updates is challenging,particularly when rerouting multiple flows simultaneously.Existing approaches pay little attention to multi-flow update,where improper update sequences across data plane nodes may construct deadlock dependencies.Moreover,these methods typically involve excessive control-data plane interactions,incurring significant resource overhead and performance degradation.This paper presents P4LoF,an efficient loop-free update approach that enables the controller to reroute multiple flows through minimal interactions.P4LoF first utilizes a greedy-based algorithm to generate the shortest update dependency chain for the single-flow update.These chains are then dynamically merged into a dependency graph and resolved as a Shortest Common Super-sequence(SCS)problem to produce the update sequence of multi-flow update.To address deadlock dependencies in multi-flow updates,P4LoF builds a deadlock-fix forwarding model that leverages the flexible packet processing capabilities of the programmable data plane.Experimental results show that P4LoF reduces control-data plane interactions by at least 32.6%with modest overhead,while effectively guaranteeing loop-free consistency.展开更多
While desalination is a key solution for global freshwater scarcity,its implementation faces environmental challenges due to concentrated brine byproducts mainly disposed of via coastal discharge systems.Solar interfa...While desalination is a key solution for global freshwater scarcity,its implementation faces environmental challenges due to concentrated brine byproducts mainly disposed of via coastal discharge systems.Solar interfacial evaporation offers sustainable management potential,yet inevitable salt nucleation at evaporation interfaces degrades photothermal conversion and operational stability via light scattering and pathway blockage.Inspired by the mangrove leaf,we propose a photothermal 3D polydopamine and polypyrrole polymerized spacer fabric(PPSF)-based upward hanging model evaporation configuration with a reverse water feeding mechanism.This design enables zero-liquiddischarge(ZLD)desalination through phase-separation crystallization.The interconnected porous architecture and the rough surface of the PPSF enable superior water transport,achieving excellent solar-absorbing efficiency of 97.8%.By adjusting the tilt angle(θ),the evaporator separates the evaporation and salt crystallization zones via controlled capillary-driven brine transport,minimizing heat dissipation from brine discharge.At an optimal tilt angle of 52°,the evaporator reaches an evaporation rate of 2.81 kg m^(−2) h^(−1) with minimal heat loss(0.366 W)under 1-sun illumination while treating a 7 wt%waste brine solution.Furthermore,it sustains an evaporation rate of 2.71 kg m^(−2) h^(−1) over 72 h while ensuring efficient salt recovery.These results highlight a scalable,energy-efficient approach for sustainable ZLD desalination.展开更多
基金The First Affiliated Hospital of Shaoyang University,China(Project No.:23FY1015)。
文摘The purpose of this study is to investigate the effectiveness of the“expiration manager”mini program in managing the validity of ward items.The program was used to manage frequently and infrequently used consumables by setting up an automatic reminder function.The item failure rate and the time required for nurses to conduct counts over 6 months before and after implementation were compared,as well as evaluated system availability using the System Usability scale(SUS).Results showed that after implementing the mini program,both the item failure rate and non-recognition rate significantly decreased(P<0.05),while the inspection pass rate significantly increased(P<0.05),and the monthly inventory time was reduced(P<0.05).The SUS evaluation yielded a total score of 74.38±11.73,with learnability at 80.21±20.27 and availability at 72.92±11.18,all indicating good user acceptance.In conclusion,the“expiration manager”mini program can effectively improve the efficiency of item expiration management,reduce the risk of expiration,and save inspection time,thereby demonstrating high user acceptance and promising potential for wider adoption.
文摘思维导图工具软件Mindjet Mind Manager作为一种可视化工具,最初在商业领域中得到广泛应用。近年来,国内外学者在图式理论研究基础上逐渐把其发展为一种教学手段。本文在介绍该软件的特性以及教育心理学背景的基础上,以《微波技术与天线》绪论课程的实例具体说明了其在高等教育教学中有力促进教与学的优势。
文摘介绍了应用R egion m anager软件绘制等高线的方法:测出所要绘制等高线的区域内各高程控制点的高程值,将处理后的数据输入软件,建立空间数据库,生成数字高程图并创建三角网,根据需要由软件提取出相应等高距的区域等高线.该方法简便、精度高、节省工期、节约人力资源,还可根据系统中生成的数字高程图,进行土方量、面积、周长和距离的量算.
文摘Heavy metal(HM)contamination severely impacts global agricultural production.HMs toxicity effectively damaged the physiological functions such as imbalanced redox homeostasis,altered antioxidant enzyme activity,damage root system architecture,hindered photosynthetic apparatus,cellular toxicity,restricted mineral accumulation,and changed the metabolite production.Using phytohormones may be a successful strategy for enhancing and stimulating plant tolerance to HMs toxicity without affecting the environment.Melatonin(MT),a novel plant growth regulator,and powerful antioxidant molecule,enhances plant resilience to HMs stress by enhancing seedling growth,protecting the photosynthetic system,increasing nutritional status,balanced redox homeostasis,and restricting HMs accumulation from root to shoot.In addition,MT enhances the activity of antioxidant enzymes and triggers the ascorbate-glutathione(AsA-GSH)cycle,which helps remove excessive ROS.MT improves RuBisCO activity to improve photosynthesis and reduce the breakdown of chlorophyll.To identify future research needs,it is crucial to understand the comprehensive and intricate regulatory mechanisms of exogenous and endogenous MT-mediated reduction of heavy metal toxicity in plants.Melatonin has several functions,and this review sheds light on those functions and the molecular processes by which it alleviates HMs toxicity.More research is needed to fully understand how melatonin affects plant tolerance to heavy metals stress.
文摘The surge in environmental pollution in recent years driven by numerous pollutants has necessitated the search for efficient removal methods.Phytoremediation is an eco-friendly technique that provides multiple benefits over conventional methods of removing contaminants.Despite the numerous benefits of this technique,it has certain limitations that can be addressed by incorporating nanoparticles to improve its effectiveness.This review paper aims to explore the impact of heavy metal pollution on plants and human health.It highlights the role and mechanism of nanoparticles in enhancing phytoremediation,their application in the detection of heavy metals,and the strategies for the safe disposal of phytoremediation biomass.Biosynthesized nanoparticles are eco-friendly and non-toxic,with applications in biomedical and environmental fields.Nanoparticles can be used in the form of nano biosensors like smartphone-operated wireless sensors made from Cinnamomum camphora,enabling efficient detection of heavy metal ions.According to the studies,nanoparticles remove 80%–97%of heavy metals by various methods like reduction,precipitation,adsorption,etc.The phytoremediation biomass disposal can be done by heat treatment,phytomining,and microbial treatment with some modifications to further enhance their results.Phytoremediation is an environmentally friendly technique but requires further research and integration with biomass energy production to overcome scalability challenges and ensure safe biomass disposal.
文摘Shandong Port Group(SPG),which was established in August 2019,regards standardization as the cornerstone of modern enterprise management,and vigorously implements the standardization innovation strategy.Its standardization work mainly focuses on the following four aspects.
基金supported by National Natural Science Foundation of China(32494793).
文摘Cellulose frameworks have emerged as promising materials for light management due to their exceptional light-scattering capabilities and sustainable nature.Conventional biomass-derived cellulose frameworks face a fundamental trade-off between haze and transparency,coupled with impractical thicknesses(≥1 mm).Inspired by squid’s skin-peeling mechanism,this work develops a peroxyformic acid(HCOOOH)-enabled precision peeling strategy to isolate intact 10-μm-thick bamboo green(BG)frameworks—100×thinner than wood-based counterparts while achieving an unprecedented optical performance(88%haze with 80%transparency).This performance surpasses delignified biomass(transparency<40%at 1 mm)and matches engineered cellulose composites,yet requires no energy-intensive nanofibrillation.The preserved native cellulose I crystalline structure(64.76%crystallinity)and wax-coated uniaxial fibril alignment(Hermans factor:0.23)contribute to high mechanical strength(903 MPa modulus)and broadband light scattering.As a light-management layer in polycrystalline silicon solar cells,the BG framework boosts photoelectric conversion efficiency by 0.41%absolute(18.74%→19.15%),outperforming synthetic anti-reflective coatings.The work establishes a scalable,waste-to-wealth route for optical-grade cellulose materials in next-generation optoelectronics.
基金funded by the Open Access Initiative of the University of Bremen and the DFG via SuUB BremenThe authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Group Project under grant number(RGP2/367/46)+1 种基金This research is supported and funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R410)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.
基金supported by the National Key Research and Development Program of China under Grant 2022YFB2901501in part by the Science and Technology Innovation leading Talents Subsidy Project of Central Plains under Grant 244200510038.
文摘The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.However,maintaining consistent forwarding states during these updates is challenging,particularly when rerouting multiple flows simultaneously.Existing approaches pay little attention to multi-flow update,where improper update sequences across data plane nodes may construct deadlock dependencies.Moreover,these methods typically involve excessive control-data plane interactions,incurring significant resource overhead and performance degradation.This paper presents P4LoF,an efficient loop-free update approach that enables the controller to reroute multiple flows through minimal interactions.P4LoF first utilizes a greedy-based algorithm to generate the shortest update dependency chain for the single-flow update.These chains are then dynamically merged into a dependency graph and resolved as a Shortest Common Super-sequence(SCS)problem to produce the update sequence of multi-flow update.To address deadlock dependencies in multi-flow updates,P4LoF builds a deadlock-fix forwarding model that leverages the flexible packet processing capabilities of the programmable data plane.Experimental results show that P4LoF reduces control-data plane interactions by at least 32.6%with modest overhead,while effectively guaranteeing loop-free consistency.
基金supported by National Key Research and Development Program of China(2022YFB3804902,2022YFB3804900)the National Natural Science Foundation of China(52203226,52161145406,42376045)the Fundamental Research Funds for the Central Universities(2232024Y-01,2232025D-02).
文摘While desalination is a key solution for global freshwater scarcity,its implementation faces environmental challenges due to concentrated brine byproducts mainly disposed of via coastal discharge systems.Solar interfacial evaporation offers sustainable management potential,yet inevitable salt nucleation at evaporation interfaces degrades photothermal conversion and operational stability via light scattering and pathway blockage.Inspired by the mangrove leaf,we propose a photothermal 3D polydopamine and polypyrrole polymerized spacer fabric(PPSF)-based upward hanging model evaporation configuration with a reverse water feeding mechanism.This design enables zero-liquiddischarge(ZLD)desalination through phase-separation crystallization.The interconnected porous architecture and the rough surface of the PPSF enable superior water transport,achieving excellent solar-absorbing efficiency of 97.8%.By adjusting the tilt angle(θ),the evaporator separates the evaporation and salt crystallization zones via controlled capillary-driven brine transport,minimizing heat dissipation from brine discharge.At an optimal tilt angle of 52°,the evaporator reaches an evaporation rate of 2.81 kg m^(−2) h^(−1) with minimal heat loss(0.366 W)under 1-sun illumination while treating a 7 wt%waste brine solution.Furthermore,it sustains an evaporation rate of 2.71 kg m^(−2) h^(−1) over 72 h while ensuring efficient salt recovery.These results highlight a scalable,energy-efficient approach for sustainable ZLD desalination.
