Due to the small size,active mobility,and intrinsic softness,miniature soft robots hold promising po-tentials in reaching the deep region inside living bodies otherwise inaccessible with compelling agility,adaptabilit...Due to the small size,active mobility,and intrinsic softness,miniature soft robots hold promising po-tentials in reaching the deep region inside living bodies otherwise inaccessible with compelling agility,adaptability and safety.Various materials and actuation strategies have been developed for creating soft robots,among which,ferromagnetic soft materials that self-actuate in response to external magnetic fields have attracted worldwide attention due to their remote controllability and excellent compatibil-ity with biological tissues.This review presents comprehensive and systematic research advancements in the design,fabrication,and applications of ferromagnetic soft materials for miniature robots,providing in-sights into their potential use in biomedical fields and beyond.The programming strategies of ferromag-netic soft materials are summarized and classified,including mold-assisted programming,3D printing-assisted programming,microassembly-assisted programming,and magnetization reprogramming.Each approach possesses unique advantages in manipulating the magnetic responsiveness of ferromagnetic soft materials to achieve outstanding actuation and deformation performances.We then discuss the biomedi-cal applications of ferromagnetic soft material-based soft robots(e.g.,minimally invasive surgery,targeted delivery,and tissue engineering),highlighting their potentials in revolutionizing biomedical technologies.This review also points out the current challenges and provides insights into future research directions,which we hope can serve as a useful reference for the development of next-generation adaptive miniature robots.展开更多
Inspired by bacterial motility mechanisms,Magnetic Helical Miniature Robots(MHMRs)exhibit promising applications in biomedical fields due to their efficient locomotion and compatibility with biological tissues.In this...Inspired by bacterial motility mechanisms,Magnetic Helical Miniature Robots(MHMRs)exhibit promising applications in biomedical fields due to their efficient locomotion and compatibility with biological tissues.In this review,we systematically survey the basics of MHMRs,from propulsion mechanism,magnetization and control methods to biomedical applications,aiming to provide readers with an easily understandable overview and fundamental knowledge on implementing MHMRs.The MHMRs are actuated by rotating magnetic fields,achieving steering and rotation through magnetic torque,and converting rotation into forward motion through the helical structure.Magnetization methods for MHMRs are reviewed into three types:attaching magnets,magnetic coatings,and magnetic powder doping.Additionally,this review discusses the control methods for MHMRs,covering imaging techniques,path tracking control—including classical control algorithms and increasingly popular learning-based methods,and swarm control.Subsequently,a comprehensive survey is conducted on the biomedical applications of MHMRs in the treatment of vascular diseases,drug delivery,cell delivery,and their integration with catheters.We finally provide a perspective about future challenges in MHMR research,including enhancing functional design capabilities,developing swarm-assisted independent control mechanisms,refining in vivo imaging techniques,and ensuring robust biocompatibility for safe medical use.展开更多
Graphene fiber supercapacitors(GFSCs)have garnered significant attention due to their exceptional features,including high power density,rapid charge/discharge rates,prolonged cycling durability,and versatile weaving c...Graphene fiber supercapacitors(GFSCs)have garnered significant attention due to their exceptional features,including high power density,rapid charge/discharge rates,prolonged cycling durability,and versatile weaving capabilities.Nevertheless,inherent challenges in graphene fibers(GFs),particularly the restricted ion-accessible specific surface area(SSA)and sluggish ion transport kinetics,hinder the achievement of optimal capacitance and rate performance.Despite existing reviews on GFSCs,a notable gap exists in thoroughly exploring the kinetics governing the energy storage process in GFSCs.This review aims to address this gap by thoroughly analyzing the energy storage mechanism,fabrication methodologies,property manipulation,and wearable applications of GFSCs.Through theoretical analysis of the energy storage process,specific parameters in advanced GF fabrication methodologies are carefully summarized,which can be used to modulate nano/micro-structures,thereby enhancing energy storage kinetics.In particular,enhanced ion storage is realized by creating more ion-accessible SSA and introducing extra-capacitive components,while accelerated ion transport is achieved by shortening the transport channel length and improving the accessibility of electrolyte ions.Building on the established structure-property relationship,several critical strategies for constructing optimal surface and structure profiles of GF electrodes are summarized.Capitalizing on the exceptional flexibility and wearability of GFSCs,the review further underscores their potential as foundational elements for constructing multifunctional e-textiles using conventional textile technologies.In conclusion,this review provides insights into current challenges and suggests potential research directions for GFSCs.展开更多
IoT has emerged as a game-changing technology that connects numerous gadgets to networks for communication,processing,and real-time monitoring across diverse applications.Due to their heterogeneous nature and constrai...IoT has emerged as a game-changing technology that connects numerous gadgets to networks for communication,processing,and real-time monitoring across diverse applications.Due to their heterogeneous nature and constrained resources,as well as the growing trend of using smart gadgets,there are privacy and security issues that are not adequately managed by conventional securitymeasures.This review offers a thorough analysis of contemporary AI solutions designed to enhance security within IoT ecosystems.The intersection of AI technologies,including ML,and blockchain,with IoT privacy and security is systematically examined,focusing on their efficacy in addressing core security issues.The methodology involves a detailed exploration of existing literature and research on AI-driven privacy-preserving security mechanisms in IoT.The reviewed solutions are categorized based on their ability to tackle specific security challenges.The review highlights key advancements,evaluates their practical applications,and identifies prevailing research gaps and challenges.The findings indicate that AI solutions,particularly those leveraging ML and blockchain,offerpromising enhancements to IoT privacy and security by improving threat detection capabilities and ensuring data integrity.This paper highlights how AI technologies might strengthen IoT privacy and security and offer suggestions for upcoming studies intended to address enduring problems and improve the robustness of IoT networks.展开更多
In today’s digital world,the Internet of Things(IoT)plays an important role in both local and global economies due to its widespread adoption in different applications.This technology has the potential to offer sever...In today’s digital world,the Internet of Things(IoT)plays an important role in both local and global economies due to its widespread adoption in different applications.This technology has the potential to offer several advantages over conventional technologies in the near future.However,the potential growth of this technology also attracts attention from hackers,which introduces new challenges for the research community that range from hardware and software security to user privacy and authentication.Therefore,we focus on a particular security concern that is associated with malware detection.The literature presents many countermeasures,but inconsistent results on identical datasets and algorithms raise concerns about model biases,training quality,and complexity.This highlights the need for an adaptive,real-time learning framework that can effectively mitigate malware threats in IoT applications.To address these challenges,(i)we propose an intelligent framework based on Two-step Deep Reinforcement Learning(TwStDRL)that is capable of learning and adapting in real-time to counter malware threats in IoT applications.This framework uses exploration and exploitation phenomena during both the training and testing phases by storing results in a replay memory.The stored knowledge allows the model to effectively navigate the environment and maximize cumulative rewards.(ii)To demonstrate the superiority of the TwStDRL framework,we implement and evaluate several machine learning algorithms for comparative analysis that include Support Vector Machines(SVM),Multi-Layer Perceptron,Random Forests,and k-means Clustering.The selection of these algorithms is driven by the inconsistent results reported in the literature,which create doubt about their robustness and reliability in real-world IoT deployments.(iii)Finally,we provide a comprehensive evaluation to justify why the TwStDRL framework outperforms them in mitigating security threats.During analysis,we noted that our proposed TwStDRL scheme achieves an average performance of 99.45%across accuracy,precision,recall,and F1-score,which is an absolute improvement of roughly 3%over the existing malware-detection models.展开更多
The forthcoming sixth generation(6G)of mobile communication networks is envisioned to be AInative,supporting intelligent services and pervasive computing at unprecedented scale.Among the key paradigms enabling this vi...The forthcoming sixth generation(6G)of mobile communication networks is envisioned to be AInative,supporting intelligent services and pervasive computing at unprecedented scale.Among the key paradigms enabling this vision,Federated Learning(FL)has gained prominence as a distributed machine learning framework that allows multiple devices to collaboratively train models without sharing raw data,thereby preserving privacy and reducing the need for centralized storage.This capability is particularly attractive for vision-based applications,where image and video data are both sensitive and bandwidth-intensive.However,the integration of FL with 6G networks presents unique challenges,including communication bottlenecks,device heterogeneity,and trade-offs between model accuracy,latency,and energy consumption.In this paper,we developed a simulation-based framework to investigate the performance of FL in representative vision tasks under 6G-like environments.We formalize the system model,incorporating both the federated averaging(FedAvg)training process and a simplified communication costmodel that captures bandwidth constraints,packet loss,and variable latency across edge devices.Using standard image datasets(e.g.,MNIST,CIFAR-10)as benchmarks,we analyze how factors such as the number of participating clients,degree of data heterogeneity,and communication frequency influence convergence speed and model accuracy.Additionally,we evaluate the effectiveness of lightweight communication-efficient strategies,including local update tuning and gradient compression,in mitigating network overhead.The experimental results reveal several key insights:(i)communication limitations can significantly degrade FL convergence in vision tasks if not properly addressed;(ii)judicious tuning of local training epochs and client participation levels enables notable improvements in both efficiency and accuracy;and(iii)communication-efficient FL strategies provide a promising pathway to balance performance with the stringent latency and reliability requirements expected in 6G.These findings highlight the synergistic role of AI and nextgeneration networks in enabling privacy-preserving,real-time vision applications,and they provide concrete design guidelines for researchers and practitioners working at the intersection of FL and 6G.展开更多
Environmental DNA(eDNA)technology has revolutionized biodiversity monitoring with its non-invasive,sensitive,and cost-efficient approach.This paper systematically reviews eDNA advancements,examining its applications i...Environmental DNA(eDNA)technology has revolutionized biodiversity monitoring with its non-invasive,sensitive,and cost-efficient approach.This paper systematically reviews eDNA advancements,examining its applications in aquatic and terrestrial ecosystems and assessing China’s standardization progress.It delineates four developmental phases from single-species detection to high-throughput sequencing,and highlights China’s contribution to the development of technical standards.While significant progress has been made,challenges persist in quantitative accuracy,methodological consistency,and large-scale implementation.Future efforts should prioritize enhanced standardization,improved quantification techniques,broader applications,and international collaboration to drive innovation in eDNA technology.展开更多
Biomass is a resourcewhose organic carbon is formed from atmospheric carbon dioxide.It has numerous characteristics such as low carbon emissions,renewability,and environmental friendliness.The efficient utilization of...Biomass is a resourcewhose organic carbon is formed from atmospheric carbon dioxide.It has numerous characteristics such as low carbon emissions,renewability,and environmental friendliness.The efficient utilization of biomass plays a significant role in promoting the development of clean energy,alleviating environmental pressures,and achieving carbon neutrality goals.Among the numerous processing technologies of biomass,hydrothermal carbonization(HTC)is a promising thermochemical process that can decompose and convert biomass into hydrochar under relatively mild conditions of approximately 180℃–300℃,thereby enabling its efficient resource utilization.In addition,HTC can directly process feedstocks with high moisture content without the need for high-temperature drying,resulting in lower energy consumption.Based on a systematic analysis of the critical articles mainly published in 2011-2025 related to biomass,HTC,and hydrochar applications,in this review,the category of biomass was first classified and the chemical compositions were summarized.Then,the main chemical reaction pathways involved in biomass decomposition and transformation during the HTC process were introduced.Meanwhile,the roles of key process parameters,including reaction temperature,residence time,pH,feedstock type,pressure,mass ratio of biomass to water,and the use of catalysts on HTC,were carefully discussed.Finally,the applications of hydrochar in energy utilization,environmental remediation,soil improvement,adsorbent,microbial fermentation,and phosphorus recovery fields were highlighted.The future directions of the HTC process were also provided,which would respond to climate change by promoting the development of the sustainable carbon materials field.展开更多
Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance ...Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance and scalability,as current trends require the distribution of computation across network nodes/points.In this paper,we survey a large number of mapping and scheduling techniques designed for NoC architectures.This time,we concentrated on 3D systems.We take a systematic literature review approach to analyze existing methods across static,dynamic,hybrid,and machine-learning-based approaches,alongside preliminary AI-based dynamic models in recent works.We classify them into several main aspects covering power-aware mapping,fault tolerance,load-balancing,and adaptive for dynamic workloads.Also,we assess the efficacy of each method against performance parameters,such as latency,throughput,response time,and error rate.Key challenges,including energy efficiency,real-time adaptability,and reinforcement learning integration,are highlighted as well.To the best of our knowledge,this is one of the recent reviews that identifies both traditional and AI-based algorithms for mapping over a modern NoC,and opens research challenges.Finally,we provide directions for future work toward improved adaptability and scalability via lightweight learned models and hierarchical mapping frameworks.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
Conjugated microporous polymers(CMPs)are a unique class of organic porous materials characterized byπ-conjugated structures and permanent micropores,distinguishing them from non-porous polymers and conventionalπ-con...Conjugated microporous polymers(CMPs)are a unique class of organic porous materials characterized byπ-conjugated structures and permanent micropores,distinguishing them from non-porous polymers and conventionalπ-conjugated polymers.CMPs offer extensive versatility in synthetic approaches,enabling the synthesis of cross-linked and mesoporous structures.Advances in chemical processes,structural design,and synthesis methodologies have been developed,resulting in a diverse range of CMPs with unique configurations and properties,contributing to the fast expansion of the field.CMPs are particularly notable for their ability to enable the competitive utilization ofπ-conjugated structures within mesoporous configurations,making them valuable for investigations across various domains.They have shown considerable promise in addressing fuel and environmental challenges,demonstrated by their exceptional performance in applications such as vapor adsorption,heterogeneous catalysis,light emission,light harvesting,and energy generation.This review examines the chemical engineering principles underlying CMPs,including synthesis approaches,systemic research advancements,multifunctional investigations boundaries,potential applications,and progress in synthesis,dimensionality,and morphology studies.Specifically,it offers a comparative analysis of CMPs and linear polymeric materials,aiding in the development of functional polymers.Furthermore,this review explores the primary fundamental limitations of CMPs in fuel-related domains and discusses alternative strategies,including novel synthesis methods incorporating interactions and morphologies,to address these challenges.Ultimately,this assessment aims to provide a valuable and inspiring resource for professionals in the field of fuel management,guiding future research and development efforts.展开更多
Liver transplantation(LT)remains the optimal life-saving intervention for patients with end-stage liver disease.Despite the recent advances in LT several barriers,including organ allocation,donor-recipient matching,an...Liver transplantation(LT)remains the optimal life-saving intervention for patients with end-stage liver disease.Despite the recent advances in LT several barriers,including organ allocation,donor-recipient matching,and patient education,persist.With the growing progress of artificial intelligence,particularly large language models(LLMs)like ChatGPT,new applications have emerged in the field of LT.Current studies demonstrating usage of ChatGPT in LT include various areas of application,from clinical settings to research and education.ChatGPT usage can benefit both healthcare professionals,by decreasing the time spent on non-clinical work,but also LT recipients by providing accurate information.Future potential applications include the expanding usage of ChatGPT and other LLMs in the field of LT pathology and radiology as well as the automated creation of discharge summaries or other related paperwork.Additionally,the next models of ChatGPT might have the potential to provide more accurate patient education material with increased readability.Although ChatGPT usage presents promising applications,there are certain ethical and practical limitations.Key concerns include patient data privacy,information accuracy,misinformation possibility and lack of legal framework.Healthcare providers and policymakers should collaborate for the establishment of a controlled framework for the safe use of ChatGPT.The aim of this minireview is to summarize current literature on ChatGPT in LT,highlighting both opportunities and limitations,while also providing future possible applications.展开更多
Eucommia ulmoides is an important economic forest tree species in China,of which the different tissues and organs are widely used in traditional medicine for their abundant bioactive ingredients.Previous studies alway...Eucommia ulmoides is an important economic forest tree species in China,of which the different tissues and organs are widely used in traditional medicine for their abundant bioactive ingredients.Previous studies always focused on the Eucommia gum,a potential alternative to natural rubber because of its“rubber plastic duality”.In recent years,Eucommia has increasingly attracted more attention and interest for its excellent nutritional and economic value,with the deepening of research and the development of products involving in the application of bioactive ingredients.However,the dietary health effects and future application prospects of the bioactive components of E.ulmoides have not been systematically summarized.Therefore,we firstly reviewed the main bioactive ingredients category,structural characteristics,extraction methods and nutritive value.Furthermore,we also summarized the wide application of bioactive ingredients in food and medicine fields.Finally,this review provides a comprehensive overview of the safety and future development of products derived from E.ulmoides,as well as exploring potential applications for its bioactive constituents,aiming to facilitate further extensive investigation into its utilization.展开更多
This article reviews the research advances in traditional Chinese medicine rhubarb and its compound formulations in the treatment of sepsis,with particular emphasis on elucidating their mechanisms of action and clinic...This article reviews the research advances in traditional Chinese medicine rhubarb and its compound formulations in the treatment of sepsis,with particular emphasis on elucidating their mechanisms of action and clinical application value.Research has demonstrated that rhubarb and its compound formulations exert therapeutic effects via multiple targets and mechanisms,including anti-inflammatory actions,protection of the intestinal barrier,modulation of immune balance,inhibition of oxidative stress,and regulation of associated signaling pathways.Clinically,rhubarb has shown distinct advantages in enhancing gastrointestinal function,mitigating systemic inflammatory responses,and reducing mortality rates among patients with sepsis.These findings provide a foundational reference for the integrated prevention and treatment of sepsis through the combined use of traditional Chinese and Western medicine.展开更多
Biodegradable metals(BMs)have shown significant potential for applications in the field of orthopedic implants.These materials gradually degrade after implantation,eventually disappear without residue,provide necessar...Biodegradable metals(BMs)have shown significant potential for applications in the field of orthopedic implants.These materials gradually degrade after implantation,eventually disappear without residue,provide necessary mechanical support during degradation,and closely integrate with bone tissues.Fe-based BMs are particularly notable for their good mechanical properties and biocompatibility.However,their slow degradation rate is a limitation.The emergence of Mn-incorporated Fe-based alloys(Fe-Mn alloys)offers the possibilities for addressing issues of slow degradation rate and incompatibility of magnetic resonance imaging(MRI)for Fe alloys.This review summarizes the advantages of Fe-Mn alloys as orthopedic implants,and the cutting-edge advances in degradation,mechanical and magnetic properties,and osteogenic performance.The cytotoxicity issue is addressed for the porous structured Fe-Mn alloys caused by the enrichment of manganese ions,and thus the main challenge and the development are involved for the Fe-Mn alloys to achieve a balance among biocompatibility,structure,and degradation rate.Also the perspectives are proposed for Fe-Mn alloys as orthopedic implants.展开更多
Perovskite photovoltaics have attracted extensive research attention as the third-generation photovoltaic technology due to their outstanding photoelectric performance,enabling diverse applications such as flexible we...Perovskite photovoltaics have attracted extensive research attention as the third-generation photovoltaic technology due to their outstanding photoelectric performance,enabling diverse applications such as flexible wearable devices,energy storage devices,fuel conversion devices,smart photovoltaic devices,and space application equipment.However,an important prerequisite for achieving multi-scenario applications lies in ensuring their long-term stability to meet the actual application requirements.Encapsulation plays a crucial role in achieving this stability.For this reason,this review systematically studies the degradation mechanisms of perovskite photovoltaics and comprehensively summarizes encapsulation as a key strategy for enhancing their stability,covering various encapsulation materials and prevalent technologies.More importantly,this paper focuses on the encapsulating technologies in multi-scenario application devices,aiming to deepen the basic understanding of the degradation mechanisms,provide practical guidelines for the development of next-generation encapsulating solutions,and promote the application expansion of encapsulating technologies in broader fields.展开更多
Morocco's oat sector is shifting from forage to food,creating demand for varieties with proven processing performance.We profiled nine Moroccan oats(four parental lines,four interspecific derivatives,and one hull-...Morocco's oat sector is shifting from forage to food,creating demand for varieties with proven processing performance.We profiled nine Moroccan oats(four parental lines,four interspecific derivatives,and one hull-less diploid check)against the key drivers of functionality:β-glucan,hydration metrics(WAI,WSI,swelling power),interfacial metrics(foam capacity/stability,emulsion capacity/stability),and kernel geometry(thousand-kernel weight/width),using SEM to interpret microstructure.Varietal differences were pronounced and actionable.The A.sativa×A.magna derivative Hamdali showed fast wetting(low WAI),strong foaming(highest FS),and high emulsion capacity.These traits make it suitable for oat drinks and large,crack-free flakes.The A.sativa×A.murphyi descendants Al Fawze and Abtah exhibited restrained swelling(lower SP)and moderate WAI/WSI,favoring crisp snacks,biscuits,and pasta;Abtah additionally delivered high emulsion stability suitable for shelf-stable beverages.Amlal and Nezha offered balanced,steerable profiles.Linkingβ-glucan,hydration,and interfacial behavior to kernel traits provides a variety-to-application map for Moroccan oats.We recommend Hamdali/Niema for foamed beverages/flakes;Tissir/Soualem for porridges and thick beverages;Abtah for pasta and stable emulsions;Al Fawze for crisp snacks/biscuits.展开更多
Melt electrowriting(MEW) enables the precise deposition of polymeric fibers at micro-/nanoscale, allowing for the fabrication of 3D biomimetic scaffolds. By incorporating stimuli-responsive polymers and/or functional ...Melt electrowriting(MEW) enables the precise deposition of polymeric fibers at micro-/nanoscale, allowing for the fabrication of 3D biomimetic scaffolds. By incorporating stimuli-responsive polymers and/or functional fillers, MEW-based 4D printing creates scaffolds capable of undergoing controlled, reversible shape transformations in response to external stimuli over time. These dynamic 4D scaffolds can be tailored for minimally invasive delivery, remote actuation, and real-time responsiveness to physiological environments, making them highly relevant for biomedical applications. This review systematically elucidates the principles of MEW-based 4D printing, including material considerations, actuation methods, and structure design strategies, along with shape programming and morphing mechanisms. The versatility of MEW for rational fabrication of biomimetic scaffolds is firstly introduced. Subsequently, the critical elements underpinning MEW-based 4D printing process are overviewed, including an analysis of stimuli-responsive materials compatible with MEW, an evaluation of applicable external stimuli, and a discussion on the advancements in design strategies for 4D scaffolds. Recent progress of MEW 4D scaffolds for applications in tissue engineering, biomedical implants, and drug delivery systems are highlighted. Finally, key challenges and perspectives toward material innovation, fabrication optimization, and actuation control are discussed. This review aims to provide valuable insights for design and creation of multifunctional biomimetic dynamic scaffolds by MEW-based 4D printing.展开更多
The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This rev...The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.展开更多
基金the National Key R&D Program of China(No.2023YFE0208700)National Natural Sci-ence Foundation of China(No.92163109 and 52072095)+7 种基金Shenzhen Science and Technology Program(No.RCJC20231211090000001,GXWD20231129101105001)the National Natural Science Foundation of China(No.52205590)the Natural Science Foundation of Jiangsu Province(No.BK20220834)the Start-up Research Fund of Southeast University(No.RF1028623098)the State Key Laboratory of Robotics and Systems(HIT)(No.SKLRS-2024-KF-11)National Natural Science Foundation of China(No.52202348)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515011491)Shenzhen Science and Technology Program(Nos.GXWD20220818224716001,KJZD20231023100302006).
文摘Due to the small size,active mobility,and intrinsic softness,miniature soft robots hold promising po-tentials in reaching the deep region inside living bodies otherwise inaccessible with compelling agility,adaptability and safety.Various materials and actuation strategies have been developed for creating soft robots,among which,ferromagnetic soft materials that self-actuate in response to external magnetic fields have attracted worldwide attention due to their remote controllability and excellent compatibil-ity with biological tissues.This review presents comprehensive and systematic research advancements in the design,fabrication,and applications of ferromagnetic soft materials for miniature robots,providing in-sights into their potential use in biomedical fields and beyond.The programming strategies of ferromag-netic soft materials are summarized and classified,including mold-assisted programming,3D printing-assisted programming,microassembly-assisted programming,and magnetization reprogramming.Each approach possesses unique advantages in manipulating the magnetic responsiveness of ferromagnetic soft materials to achieve outstanding actuation and deformation performances.We then discuss the biomedi-cal applications of ferromagnetic soft material-based soft robots(e.g.,minimally invasive surgery,targeted delivery,and tissue engineering),highlighting their potentials in revolutionizing biomedical technologies.This review also points out the current challenges and provides insights into future research directions,which we hope can serve as a useful reference for the development of next-generation adaptive miniature robots.
基金the financial support from the Research Institute for Advanced Manufacturing(RIAM)of The Hong Kong Polytechnic University(project Nos.1-CD9F and 1-CDK3)the Research Grants Council(RGC)of Hong Kong(project Nos.25200424 and 15206223)+2 种基金the GuangDong Basic and Applied Basic Research Foundation(project No.2023A1515110709)the Startup fund(project No.1-BE9L)of the Hong Kong Polytechnic Universitysupported by grant from the Research Committee of the Hong Kong Polytechnic University under student account code RN5Y.
文摘Inspired by bacterial motility mechanisms,Magnetic Helical Miniature Robots(MHMRs)exhibit promising applications in biomedical fields due to their efficient locomotion and compatibility with biological tissues.In this review,we systematically survey the basics of MHMRs,from propulsion mechanism,magnetization and control methods to biomedical applications,aiming to provide readers with an easily understandable overview and fundamental knowledge on implementing MHMRs.The MHMRs are actuated by rotating magnetic fields,achieving steering and rotation through magnetic torque,and converting rotation into forward motion through the helical structure.Magnetization methods for MHMRs are reviewed into three types:attaching magnets,magnetic coatings,and magnetic powder doping.Additionally,this review discusses the control methods for MHMRs,covering imaging techniques,path tracking control—including classical control algorithms and increasingly popular learning-based methods,and swarm control.Subsequently,a comprehensive survey is conducted on the biomedical applications of MHMRs in the treatment of vascular diseases,drug delivery,cell delivery,and their integration with catheters.We finally provide a perspective about future challenges in MHMR research,including enhancing functional design capabilities,developing swarm-assisted independent control mechanisms,refining in vivo imaging techniques,and ensuring robust biocompatibility for safe medical use.
基金Shanghai Municipal Commission for Science and Technology,Grant/Award Number:23ZR1402500National Natural Science Foundation of China,Grant/Award Number:51973034+1 种基金National Scholarship CouncilNational Key Research and Development Program of China,Grant/Award Number:2023YFB3809800.
文摘Graphene fiber supercapacitors(GFSCs)have garnered significant attention due to their exceptional features,including high power density,rapid charge/discharge rates,prolonged cycling durability,and versatile weaving capabilities.Nevertheless,inherent challenges in graphene fibers(GFs),particularly the restricted ion-accessible specific surface area(SSA)and sluggish ion transport kinetics,hinder the achievement of optimal capacitance and rate performance.Despite existing reviews on GFSCs,a notable gap exists in thoroughly exploring the kinetics governing the energy storage process in GFSCs.This review aims to address this gap by thoroughly analyzing the energy storage mechanism,fabrication methodologies,property manipulation,and wearable applications of GFSCs.Through theoretical analysis of the energy storage process,specific parameters in advanced GF fabrication methodologies are carefully summarized,which can be used to modulate nano/micro-structures,thereby enhancing energy storage kinetics.In particular,enhanced ion storage is realized by creating more ion-accessible SSA and introducing extra-capacitive components,while accelerated ion transport is achieved by shortening the transport channel length and improving the accessibility of electrolyte ions.Building on the established structure-property relationship,several critical strategies for constructing optimal surface and structure profiles of GF electrodes are summarized.Capitalizing on the exceptional flexibility and wearability of GFSCs,the review further underscores their potential as foundational elements for constructing multifunctional e-textiles using conventional textile technologies.In conclusion,this review provides insights into current challenges and suggests potential research directions for GFSCs.
基金The author Dr.Arshiya Sajid Ansari extends the appreciation to the Deanship of Postgraduate Studies and Scientific Research at Majmaah University for funding this research work through the project number(R-2025-1706).
文摘IoT has emerged as a game-changing technology that connects numerous gadgets to networks for communication,processing,and real-time monitoring across diverse applications.Due to their heterogeneous nature and constrained resources,as well as the growing trend of using smart gadgets,there are privacy and security issues that are not adequately managed by conventional securitymeasures.This review offers a thorough analysis of contemporary AI solutions designed to enhance security within IoT ecosystems.The intersection of AI technologies,including ML,and blockchain,with IoT privacy and security is systematically examined,focusing on their efficacy in addressing core security issues.The methodology involves a detailed exploration of existing literature and research on AI-driven privacy-preserving security mechanisms in IoT.The reviewed solutions are categorized based on their ability to tackle specific security challenges.The review highlights key advancements,evaluates their practical applications,and identifies prevailing research gaps and challenges.The findings indicate that AI solutions,particularly those leveraging ML and blockchain,offerpromising enhancements to IoT privacy and security by improving threat detection capabilities and ensuring data integrity.This paper highlights how AI technologies might strengthen IoT privacy and security and offer suggestions for upcoming studies intended to address enduring problems and improve the robustness of IoT networks.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R104)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia。
文摘In today’s digital world,the Internet of Things(IoT)plays an important role in both local and global economies due to its widespread adoption in different applications.This technology has the potential to offer several advantages over conventional technologies in the near future.However,the potential growth of this technology also attracts attention from hackers,which introduces new challenges for the research community that range from hardware and software security to user privacy and authentication.Therefore,we focus on a particular security concern that is associated with malware detection.The literature presents many countermeasures,but inconsistent results on identical datasets and algorithms raise concerns about model biases,training quality,and complexity.This highlights the need for an adaptive,real-time learning framework that can effectively mitigate malware threats in IoT applications.To address these challenges,(i)we propose an intelligent framework based on Two-step Deep Reinforcement Learning(TwStDRL)that is capable of learning and adapting in real-time to counter malware threats in IoT applications.This framework uses exploration and exploitation phenomena during both the training and testing phases by storing results in a replay memory.The stored knowledge allows the model to effectively navigate the environment and maximize cumulative rewards.(ii)To demonstrate the superiority of the TwStDRL framework,we implement and evaluate several machine learning algorithms for comparative analysis that include Support Vector Machines(SVM),Multi-Layer Perceptron,Random Forests,and k-means Clustering.The selection of these algorithms is driven by the inconsistent results reported in the literature,which create doubt about their robustness and reliability in real-world IoT deployments.(iii)Finally,we provide a comprehensive evaluation to justify why the TwStDRL framework outperforms them in mitigating security threats.During analysis,we noted that our proposed TwStDRL scheme achieves an average performance of 99.45%across accuracy,precision,recall,and F1-score,which is an absolute improvement of roughly 3%over the existing malware-detection models.
文摘The forthcoming sixth generation(6G)of mobile communication networks is envisioned to be AInative,supporting intelligent services and pervasive computing at unprecedented scale.Among the key paradigms enabling this vision,Federated Learning(FL)has gained prominence as a distributed machine learning framework that allows multiple devices to collaboratively train models without sharing raw data,thereby preserving privacy and reducing the need for centralized storage.This capability is particularly attractive for vision-based applications,where image and video data are both sensitive and bandwidth-intensive.However,the integration of FL with 6G networks presents unique challenges,including communication bottlenecks,device heterogeneity,and trade-offs between model accuracy,latency,and energy consumption.In this paper,we developed a simulation-based framework to investigate the performance of FL in representative vision tasks under 6G-like environments.We formalize the system model,incorporating both the federated averaging(FedAvg)training process and a simplified communication costmodel that captures bandwidth constraints,packet loss,and variable latency across edge devices.Using standard image datasets(e.g.,MNIST,CIFAR-10)as benchmarks,we analyze how factors such as the number of participating clients,degree of data heterogeneity,and communication frequency influence convergence speed and model accuracy.Additionally,we evaluate the effectiveness of lightweight communication-efficient strategies,including local update tuning and gradient compression,in mitigating network overhead.The experimental results reveal several key insights:(i)communication limitations can significantly degrade FL convergence in vision tasks if not properly addressed;(ii)judicious tuning of local training epochs and client participation levels enables notable improvements in both efficiency and accuracy;and(iii)communication-efficient FL strategies provide a promising pathway to balance performance with the stringent latency and reliability requirements expected in 6G.These findings highlight the synergistic role of AI and nextgeneration networks in enabling privacy-preserving,real-time vision applications,and they provide concrete design guidelines for researchers and practitioners working at the intersection of FL and 6G.
基金supported by the National Natural Science Foundation of China(Grant No.32160172)the Key Science-Technology Project of Inner Mongolia(2023KYPT0010)+1 种基金the Natural Science Foundation of Inner Mongolia Autonomous Region of China(Grant No.2025QN03006)the 2023 Inner Mongolia Public Institution High-Level Talent Introduction Scientific Research Support Project.
文摘Environmental DNA(eDNA)technology has revolutionized biodiversity monitoring with its non-invasive,sensitive,and cost-efficient approach.This paper systematically reviews eDNA advancements,examining its applications in aquatic and terrestrial ecosystems and assessing China’s standardization progress.It delineates four developmental phases from single-species detection to high-throughput sequencing,and highlights China’s contribution to the development of technical standards.While significant progress has been made,challenges persist in quantitative accuracy,methodological consistency,and large-scale implementation.Future efforts should prioritize enhanced standardization,improved quantification techniques,broader applications,and international collaboration to drive innovation in eDNA technology.
基金supported by National Natural Science Foundation of China(22578155,22478147)the Natural Science Foundation of Huaian City(HAB2024051).
文摘Biomass is a resourcewhose organic carbon is formed from atmospheric carbon dioxide.It has numerous characteristics such as low carbon emissions,renewability,and environmental friendliness.The efficient utilization of biomass plays a significant role in promoting the development of clean energy,alleviating environmental pressures,and achieving carbon neutrality goals.Among the numerous processing technologies of biomass,hydrothermal carbonization(HTC)is a promising thermochemical process that can decompose and convert biomass into hydrochar under relatively mild conditions of approximately 180℃–300℃,thereby enabling its efficient resource utilization.In addition,HTC can directly process feedstocks with high moisture content without the need for high-temperature drying,resulting in lower energy consumption.Based on a systematic analysis of the critical articles mainly published in 2011-2025 related to biomass,HTC,and hydrochar applications,in this review,the category of biomass was first classified and the chemical compositions were summarized.Then,the main chemical reaction pathways involved in biomass decomposition and transformation during the HTC process were introduced.Meanwhile,the roles of key process parameters,including reaction temperature,residence time,pH,feedstock type,pressure,mass ratio of biomass to water,and the use of catalysts on HTC,were carefully discussed.Finally,the applications of hydrochar in energy utilization,environmental remediation,soil improvement,adsorbent,microbial fermentation,and phosphorus recovery fields were highlighted.The future directions of the HTC process were also provided,which would respond to climate change by promoting the development of the sustainable carbon materials field.
文摘Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance and scalability,as current trends require the distribution of computation across network nodes/points.In this paper,we survey a large number of mapping and scheduling techniques designed for NoC architectures.This time,we concentrated on 3D systems.We take a systematic literature review approach to analyze existing methods across static,dynamic,hybrid,and machine-learning-based approaches,alongside preliminary AI-based dynamic models in recent works.We classify them into several main aspects covering power-aware mapping,fault tolerance,load-balancing,and adaptive for dynamic workloads.Also,we assess the efficacy of each method against performance parameters,such as latency,throughput,response time,and error rate.Key challenges,including energy efficiency,real-time adaptability,and reinforcement learning integration,are highlighted as well.To the best of our knowledge,this is one of the recent reviews that identifies both traditional and AI-based algorithms for mapping over a modern NoC,and opens research challenges.Finally,we provide directions for future work toward improved adaptability and scalability via lightweight learned models and hierarchical mapping frameworks.
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 King Khalid University,Abha,Saudi Arabiathe Deanship of Scientific Research at King Khalid University for funding this work through Large Groups Project under grant number(R.G.P.2/335/46)the Guangdong Office of Research Projects at the Provincial University(No.2024KCXTD064)。
文摘Conjugated microporous polymers(CMPs)are a unique class of organic porous materials characterized byπ-conjugated structures and permanent micropores,distinguishing them from non-porous polymers and conventionalπ-conjugated polymers.CMPs offer extensive versatility in synthetic approaches,enabling the synthesis of cross-linked and mesoporous structures.Advances in chemical processes,structural design,and synthesis methodologies have been developed,resulting in a diverse range of CMPs with unique configurations and properties,contributing to the fast expansion of the field.CMPs are particularly notable for their ability to enable the competitive utilization ofπ-conjugated structures within mesoporous configurations,making them valuable for investigations across various domains.They have shown considerable promise in addressing fuel and environmental challenges,demonstrated by their exceptional performance in applications such as vapor adsorption,heterogeneous catalysis,light emission,light harvesting,and energy generation.This review examines the chemical engineering principles underlying CMPs,including synthesis approaches,systemic research advancements,multifunctional investigations boundaries,potential applications,and progress in synthesis,dimensionality,and morphology studies.Specifically,it offers a comparative analysis of CMPs and linear polymeric materials,aiding in the development of functional polymers.Furthermore,this review explores the primary fundamental limitations of CMPs in fuel-related domains and discusses alternative strategies,including novel synthesis methods incorporating interactions and morphologies,to address these challenges.Ultimately,this assessment aims to provide a valuable and inspiring resource for professionals in the field of fuel management,guiding future research and development efforts.
文摘Liver transplantation(LT)remains the optimal life-saving intervention for patients with end-stage liver disease.Despite the recent advances in LT several barriers,including organ allocation,donor-recipient matching,and patient education,persist.With the growing progress of artificial intelligence,particularly large language models(LLMs)like ChatGPT,new applications have emerged in the field of LT.Current studies demonstrating usage of ChatGPT in LT include various areas of application,from clinical settings to research and education.ChatGPT usage can benefit both healthcare professionals,by decreasing the time spent on non-clinical work,but also LT recipients by providing accurate information.Future potential applications include the expanding usage of ChatGPT and other LLMs in the field of LT pathology and radiology as well as the automated creation of discharge summaries or other related paperwork.Additionally,the next models of ChatGPT might have the potential to provide more accurate patient education material with increased readability.Although ChatGPT usage presents promising applications,there are certain ethical and practical limitations.Key concerns include patient data privacy,information accuracy,misinformation possibility and lack of legal framework.Healthcare providers and policymakers should collaborate for the establishment of a controlled framework for the safe use of ChatGPT.The aim of this minireview is to summarize current literature on ChatGPT in LT,highlighting both opportunities and limitations,while also providing future possible applications.
基金financially supported by the National Natural Science Foundation of China(32201586 and 32301760)Key Specialized Research and Development Program in Henan Province(232102110218)+1 种基金Postdoctoral Research Start-Up Fund of Henan Province(HN2022112)Special Fund for Young Talents in Henan Agricultural University(30501318).
文摘Eucommia ulmoides is an important economic forest tree species in China,of which the different tissues and organs are widely used in traditional medicine for their abundant bioactive ingredients.Previous studies always focused on the Eucommia gum,a potential alternative to natural rubber because of its“rubber plastic duality”.In recent years,Eucommia has increasingly attracted more attention and interest for its excellent nutritional and economic value,with the deepening of research and the development of products involving in the application of bioactive ingredients.However,the dietary health effects and future application prospects of the bioactive components of E.ulmoides have not been systematically summarized.Therefore,we firstly reviewed the main bioactive ingredients category,structural characteristics,extraction methods and nutritive value.Furthermore,we also summarized the wide application of bioactive ingredients in food and medicine fields.Finally,this review provides a comprehensive overview of the safety and future development of products derived from E.ulmoides,as well as exploring potential applications for its bioactive constituents,aiming to facilitate further extensive investigation into its utilization.
基金Supported by National Natural Science Foundation of China(82374346)Double Hundred Outstanding Young and Middle-aged Medical and Health Talents of Wuxi City(BJ2023071)Scientific Research Project of Wuxi Municipal Health Commission(Q202358).
文摘This article reviews the research advances in traditional Chinese medicine rhubarb and its compound formulations in the treatment of sepsis,with particular emphasis on elucidating their mechanisms of action and clinical application value.Research has demonstrated that rhubarb and its compound formulations exert therapeutic effects via multiple targets and mechanisms,including anti-inflammatory actions,protection of the intestinal barrier,modulation of immune balance,inhibition of oxidative stress,and regulation of associated signaling pathways.Clinically,rhubarb has shown distinct advantages in enhancing gastrointestinal function,mitigating systemic inflammatory responses,and reducing mortality rates among patients with sepsis.These findings provide a foundational reference for the integrated prevention and treatment of sepsis through the combined use of traditional Chinese and Western medicine.
基金financially supported by the Shandong Province Natural Science Foundation(No.ZR2023ME181)the National Natural Science Foundation of China(No.52305313)the Natural Science Foundation of Hunan Province(Nos.2023JJ40553 and 2023JJ60433)。
文摘Biodegradable metals(BMs)have shown significant potential for applications in the field of orthopedic implants.These materials gradually degrade after implantation,eventually disappear without residue,provide necessary mechanical support during degradation,and closely integrate with bone tissues.Fe-based BMs are particularly notable for their good mechanical properties and biocompatibility.However,their slow degradation rate is a limitation.The emergence of Mn-incorporated Fe-based alloys(Fe-Mn alloys)offers the possibilities for addressing issues of slow degradation rate and incompatibility of magnetic resonance imaging(MRI)for Fe alloys.This review summarizes the advantages of Fe-Mn alloys as orthopedic implants,and the cutting-edge advances in degradation,mechanical and magnetic properties,and osteogenic performance.The cytotoxicity issue is addressed for the porous structured Fe-Mn alloys caused by the enrichment of manganese ions,and thus the main challenge and the development are involved for the Fe-Mn alloys to achieve a balance among biocompatibility,structure,and degradation rate.Also the perspectives are proposed for Fe-Mn alloys as orthopedic implants.
基金supported by the National Key Research and Development Program of China(2024YFE0201800)the National Natural Science Foundation of China(22579136)+6 种基金the Shaanxi Fundamental Science Research Project for Mathematics and Physics(22JSY015,23JSY005)the Shaanxi Province Science and Technology Activities for Overseas Students Selected Funding Project(2023015)the Youth Project in Natural Science and Engineering Technology(2023SYJ15,2023SYJ25)the S&T Program of Energy Shaanxi Laboratory(ESLB202438)the Xi’an Jiaotong University Youth Innovation Team(xtr052025016)the State Key Laboratory for Strength and Vibration of Mechanical Structures(SV2023-KF-18)the China Fundamental Research Funds for the Central Universities。
文摘Perovskite photovoltaics have attracted extensive research attention as the third-generation photovoltaic technology due to their outstanding photoelectric performance,enabling diverse applications such as flexible wearable devices,energy storage devices,fuel conversion devices,smart photovoltaic devices,and space application equipment.However,an important prerequisite for achieving multi-scenario applications lies in ensuring their long-term stability to meet the actual application requirements.Encapsulation plays a crucial role in achieving this stability.For this reason,this review systematically studies the degradation mechanisms of perovskite photovoltaics and comprehensively summarizes encapsulation as a key strategy for enhancing their stability,covering various encapsulation materials and prevalent technologies.More importantly,this paper focuses on the encapsulating technologies in multi-scenario application devices,aiming to deepen the basic understanding of the degradation mechanisms,provide practical guidelines for the development of next-generation encapsulating solutions,and promote the application expansion of encapsulating technologies in broader fields.
文摘Morocco's oat sector is shifting from forage to food,creating demand for varieties with proven processing performance.We profiled nine Moroccan oats(four parental lines,four interspecific derivatives,and one hull-less diploid check)against the key drivers of functionality:β-glucan,hydration metrics(WAI,WSI,swelling power),interfacial metrics(foam capacity/stability,emulsion capacity/stability),and kernel geometry(thousand-kernel weight/width),using SEM to interpret microstructure.Varietal differences were pronounced and actionable.The A.sativa×A.magna derivative Hamdali showed fast wetting(low WAI),strong foaming(highest FS),and high emulsion capacity.These traits make it suitable for oat drinks and large,crack-free flakes.The A.sativa×A.murphyi descendants Al Fawze and Abtah exhibited restrained swelling(lower SP)and moderate WAI/WSI,favoring crisp snacks,biscuits,and pasta;Abtah additionally delivered high emulsion stability suitable for shelf-stable beverages.Amlal and Nezha offered balanced,steerable profiles.Linkingβ-glucan,hydration,and interfacial behavior to kernel traits provides a variety-to-application map for Moroccan oats.We recommend Hamdali/Niema for foamed beverages/flakes;Tissir/Soualem for porridges and thick beverages;Abtah for pasta and stable emulsions;Al Fawze for crisp snacks/biscuits.
基金financially supported by the National Natural Science Foundation of China (Grant No. 1230242212572342)+2 种基金Marie Sklodowska-Curie grant agreement ENSIGN (101086226)Nano Ram (101120146)L4DNANO (101086227)
文摘Melt electrowriting(MEW) enables the precise deposition of polymeric fibers at micro-/nanoscale, allowing for the fabrication of 3D biomimetic scaffolds. By incorporating stimuli-responsive polymers and/or functional fillers, MEW-based 4D printing creates scaffolds capable of undergoing controlled, reversible shape transformations in response to external stimuli over time. These dynamic 4D scaffolds can be tailored for minimally invasive delivery, remote actuation, and real-time responsiveness to physiological environments, making them highly relevant for biomedical applications. This review systematically elucidates the principles of MEW-based 4D printing, including material considerations, actuation methods, and structure design strategies, along with shape programming and morphing mechanisms. The versatility of MEW for rational fabrication of biomimetic scaffolds is firstly introduced. Subsequently, the critical elements underpinning MEW-based 4D printing process are overviewed, including an analysis of stimuli-responsive materials compatible with MEW, an evaluation of applicable external stimuli, and a discussion on the advancements in design strategies for 4D scaffolds. Recent progress of MEW 4D scaffolds for applications in tissue engineering, biomedical implants, and drug delivery systems are highlighted. Finally, key challenges and perspectives toward material innovation, fabrication optimization, and actuation control are discussed. This review aims to provide valuable insights for design and creation of multifunctional biomimetic dynamic scaffolds by MEW-based 4D printing.
文摘The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.
