There is no better way to appreciate the unique character of Chinese modernisation than by spending 10 years fully immersed in the country.I arrived in China from Madagascar in 2016 as a student and have lived and wor...There is no better way to appreciate the unique character of Chinese modernisation than by spending 10 years fully immersed in the country.I arrived in China from Madagascar in 2016 as a student and have lived and worked here ever since.This experience has given me a profound firsthand insight into the country.展开更多
Since the launch of a digitization project for the protection and utilization of ancient texts in the Sakya Monastery of the Xizang Autonomous Region in 2012,significant efforts and achievements have been made in anci...Since the launch of a digitization project for the protection and utilization of ancient texts in the Sakya Monastery of the Xizang Autonomous Region in 2012,significant efforts and achievements have been made in ancient text preservation.展开更多
Pseudosection modeling for the garnet amphibolite samples from the Western Dabie Mountains show they have experienced similar HP metamorphic evolution with that of the adjected eclogites.The common assemblage of
The most of high/ultrahigh-pressure(HP/UHP)terranes of the world are characterized by the occurrence of numerous pods,lenses or layered blocks of eclogite and amphibolites(e.g.O’Brien,1997;Elvevold and Gilotti,2000;Z...The most of high/ultrahigh-pressure(HP/UHP)terranes of the world are characterized by the occurrence of numerous pods,lenses or layered blocks of eclogite and amphibolites(e.g.O’Brien,1997;Elvevold and Gilotti,2000;Zhang et al.,2003;and references there in).Field and petrological features suggest that amphibolites should展开更多
Apples,as respiratory climacteric fruit,undergo postharvest ripening and senescence,impacting commodity value.Cuticular wax protects against environmental stresses.Here,gas chromatography-mass spectrometry(GC-MS)analy...Apples,as respiratory climacteric fruit,undergo postharvest ripening and senescence,impacting commodity value.Cuticular wax protects against environmental stresses.Here,gas chromatography-mass spectrometry(GC-MS)analysis revealed a decline in fatty alcohol levels in apple wax during storage,correlating with fruit quality deterioration.Notably,octacosanol content signifcantly decreased with storage,suggesting that it is a primary cause of wax and fruit quality decline.Octacosanol treatment improved fruit quality and delayed softening by enhancing wax synthesis and antioxidant levels and suppressing cell wall-degrading enzymes.Transcriptome sequencing and real-time quantitative polymerase chain reaction(RT-qPCR)assays indicated increased expression of wax,peroxidase,sucrose,and starch genes and decreased expression of cell wall degradation genes,explaining octacosanol’s benefts.This study provides a theoretical basis for octacosanol application in fruit preservation.展开更多
Dear Editor,This letter addresses the critical challenge of preserving privacy in graph learning without compromising on data utility.Differential privacy(DP)is emerging as an effective method for privacy-preserving g...Dear Editor,This letter addresses the critical challenge of preserving privacy in graph learning without compromising on data utility.Differential privacy(DP)is emerging as an effective method for privacy-preserving graph learning.However,its application often diminishes data utility,especially for nodes with fewer neighbors in graph neural networks(GNNs).展开更多
As the pace of urban life accelerates,plastic wrap has become an everyday necessity.However,traditional petroleum-based plastic wrap is difficult to degrade and prone to releasing harmful plasticizers.Therefore,develo...As the pace of urban life accelerates,plastic wrap has become an everyday necessity.However,traditional petroleum-based plastic wrap is difficult to degrade and prone to releasing harmful plasticizers.Therefore,developing sustainable,biodegradable,and high-performance alternative materials is crucial.Inspired by the cellulose-gum reinforcement mechanism in flaxseed hulls,this study utilized flaxseed hulls as raw material.Through hot water washing,alkali boiling,and bleaching,high-purity insoluble cellulose(FC)was extracted.Subsequently,flaxseed hull cellulose nanofibers(FCN)were prepared via TEMPO oxidation and ultrasonic treatment.Using FC and FCN,an all-natural cellulose-flaxseed gum composite membrane(CM)was constructed,where FCN serves as the framework and flaxseed gum acts as the binder,forming a dense structure.This composite membrane demonstrated effectiveness in nut preservation,significantly delaying nut oxidation and providing a viable pathway for sustainable food packaging.展开更多
This study addresses the risk of privacy leakage during the transmission and sharing of multimodal data in smart grid substations by proposing a three-tier privacy-preserving architecture based on asynchronous federat...This study addresses the risk of privacy leakage during the transmission and sharing of multimodal data in smart grid substations by proposing a three-tier privacy-preserving architecture based on asynchronous federated learning.The framework integrates blockchain technology,the InterPlanetary File System(IPFS)for distributed storage,and a dynamic differential privacy mechanism to achieve collaborative security across the storage,service,and federated coordination layers.It accommodates both multimodal data classification and object detection tasks,enabling the identification and localization of key targets and abnormal behaviors in substation scenarios while ensuring privacy protection.This effectively mitigates the single-point failures and model leakage issues inherent in centralized architectures.A dynamically adjustable differential privacy mechanism is introduced to allocate privacy budgets according to client contribution levels and upload frequencies,achieving a personalized balance between model performance and privacy protection.Multi-dimensional experimental evaluations,including classification accuracy,F1-score,encryption latency,and aggregation latency,verify the security and efficiency of the proposed architecture.The improved CNN model achieves 72.34%accuracy and an F1-score of 0.72 in object detection and classification tasks on infrared surveillance imagery,effectively identifying typical risk events such as not wearing safety helmets and unauthorized intrusion,while maintaining an aggregation latency of only 1.58 s and a query latency of 80.79 ms.Compared with traditional static differential privacy and centralized approaches,the proposed method demonstrates significant advantages in accuracy,latency,and security,providing a new technical paradigm for efficient,secure data sharing,object detection,and privacy preservation in smart grid substations.展开更多
The environment and its preservation are becoming more and more dependent on ecological development in an age of accelerating climate risk,biodiversity loss,and pressures of pollution.This review summarizes the fronti...The environment and its preservation are becoming more and more dependent on ecological development in an age of accelerating climate risk,biodiversity loss,and pressures of pollution.This review summarizes the frontiers of innovation that are capable of enhancing integration of human development and ecological integrity,and how the interaction between technical,ecological,and institutional innovations can produce real-world results.We initially discuss developing ecological innovations that offer new opportunities to urban development,such as low-impact cities,ecological infrastructure,clean energy transitions,and biodiversity-informed siting,and digital decision-support systems enhancing planning and resource efficiency.Then,we evaluate progress in the field of preservation and restoration,with a particular focus on nature-based solutions,a process-based approach to restoration science,connectivity conservation,and a watershed-scale and seascape-scale approach to restore resilience and help recover biodiversity.In these spheres,we discover measurement,monitoring,and verification(MRV),one of the main pillars of scale alongside remote sensing,automated field monitoring,environmental Deoxyribonucleic Acid(DNA),and Artificial Intelligence(AI)-enabled analytics,increasing the range of trackable and manageable indices as well as creating new issues with baselines,uncertainty,and data ethics.Lastly,we compare governance,finance,and equity as key conversion processes that can turn innovations into sustainable dividends with authenticity principles,however,of additionality,permanence,and leakage avoidance,and with rightsbased and redistributive mechanisms and approaches that reinforce legitimacy.We end by providing a portfolio roadmap of prioritization of the interventions that have high co-benefits and the identification of critical research and institutional gaps to provide net-positive ecological results.展开更多
Recognizing frontal faces from non-frontal or profile images is a major problem due to pose changes,self-occlusions,and the complete loss of important structural and textural components,depressing recognition accuracy...Recognizing frontal faces from non-frontal or profile images is a major problem due to pose changes,self-occlusions,and the complete loss of important structural and textural components,depressing recognition accuracy and visual fidelity.This paper introduces a new deep generative framework,Modified Multi-Scale Fused CycleGAN(MMF-CycleGAN),for robust and photo-realistic profile-to-frontal face synthesis.The MMF-CycleGAN framework utilizes pre-processing and then the generator employs a Deep Dilated DenseNet encoder-based hierarchical feature extraction along with a transformer and decoder.The proposed Multi-Scale Fusion PatchGAN discriminator enforces consistency at multiple spatial resolutions,leading to sharper textures and improved global facial geometry.Also,GAN training stability and identity preservation are improved through the Ranger optimizer,which effectively balances adversarial,identity,and cycle-consistency losses.Experiments on three benchmark datasets show that MMFCycleGAN achieves accuracy of 0.9541,0.9455,and 0.9422,F1-scores of 0.9654,0.9641,and 0.9614,and AUC values of 0.9742,0.9714,and 0.9698,respectively,and the extreme-pose accuracy(yaw>60°)reaches 0.92.Despite its enhanced architecture,the framework maintains an efficient inference time of 0.042 s per image,making it suitable for real-time biometric authentication,surveillance,and security applications in unconstrained environments.展开更多
Medical imaging is essential in modern health care,allowing accurate diagnosis and effective treatment planning.These images,however,often demonstrate low contrast,noise,and brightness distortion that reduce their dia...Medical imaging is essential in modern health care,allowing accurate diagnosis and effective treatment planning.These images,however,often demonstrate low contrast,noise,and brightness distortion that reduce their diagnostic reliability.This review presents a structured and comprehensive analysis of advanced histogram equalization(HE)-based techniques for medical image enhancement.Our review methodology encompasses:(1)classical HE approaches and related limitations in medical domains;(2)adaptive schemes like Adaptive Histogram Equalization(AHE)and Contrast Limited Adaptive Histogrma Equalization(CLAHE)and their advance variants;(3)brightnesspreserving schemes like BBHE and MMBEBHE and related algorithms;(4)dynamic and recursive histogram equalization methods incorporating DHE and RMSHE;(5)fuzzy logic-based enhancement methodologies addressing uncertainty and noise in medical images;and(6)hybrid optimization methodologies through the application of metaheuristic algorithms(World Cup Optimization,Particle Swarm Optimization,Genetic Algorithms,along with histogram-based methodologies.)There is also a comparative discussion given based on contrast improvement,image brightness preservation,noise management,and computational efficiency.Such advancements have better capabilities of improving image quality,which is more important for improved diagnosis and image analysis.展开更多
Chinese abbreviations improve communicative efficiency by extracting key components from longer expressions.They are widely used in both daily communication and professional domains.However,existing abbreviation gener...Chinese abbreviations improve communicative efficiency by extracting key components from longer expressions.They are widely used in both daily communication and professional domains.However,existing abbreviation generation methods still face two major challenges.First,sequence-labeling-based approaches often neglect contextual meaning by making binary decisions at the character level,leading to abbreviations that fail to capture semantic completeness.Second,generation-basedmethods rely heavily on a single decoding process,which frequently produces correct abbreviations but ranks them lower due to inadequate semantic evaluation.To address these limitations,we propose a novel two-stage frameworkwithGeneration–Iterative Optimization forAbbreviation(GIOA).In the first stage,we design aChain-of-Thought prompting strategy and incorporate definitional and situational contexts to generate multiple abbreviation candidates.In the second stage,we introduce a Semantic Preservation Dynamic Adjustment mechanism that alternates between character-level importance estimation and semantic restoration to optimize candidate ranking.Experiments on two public benchmark datasets show that our method outperforms existing state-of-the-art approaches,achieving Hit@1 improvements of 15.15%and 13.01%,respectively,while maintaining consistent results in Hit@3.展开更多
Multimodal spatiotemporal data from smart city consumer electronics present critical challenges including cross-modal temporal misalignment,unreliable data quality,limited joint modeling of spatial and temporal depend...Multimodal spatiotemporal data from smart city consumer electronics present critical challenges including cross-modal temporal misalignment,unreliable data quality,limited joint modeling of spatial and temporal dependencies,and weak resilience to adversarial updates.To address these limitations,EdgeST-Fusion is introduced as a cross-modal federated graph transformer framework for context-aware smart city analytics.The architecture integrates cross-modal embedding networks for modality alignment,graph transformer encoders for spatial dependency modeling,temporal self-attention for dynamic pattern learning,and adaptive anomaly detection to ensure data quality and security during aggregation.A privacy-preserving federated learning protocol with differential privacy guarantees enables collaborative model training without centralizing sensitive data.The framework employs data-quality-aware weighted aggregation to enhance robustness against noisy and malicious client updates.Experimental evaluation on the GeoLife,PeMS-Bay,and SmartHome+datasets demonstrates that EdgeST-Fusion achieves 21.8%improvement in prediction accuracy,35.7%reduction in communication overhead,and 29.4%enhancement in security resilience compared to recent baselines.Real-world deployment across three smart city testbeds validates practical viability with 90.0%average accuracy and sub-250 ms inference latency.The proposed framework remains feasible for deployment on heterogeneous and resource-constrained consumer electronics devices whilemaintaining strong privacy guarantees and scalability for large-scale urban environments.展开更多
The Royal Tropical Institute(KIT)in Amsterdam is an independent centre of knowledge and expertise in the areas of international and intercultural cooperation,operating at the interface between theory and practice and ...The Royal Tropical Institute(KIT)in Amsterdam is an independent centre of knowledge and expertise in the areas of international and intercultural cooperation,operating at the interface between theory and practice and between policy and implementation.The Institute contributes to sustainable development,poverty alleviation and cultural preservation and exchange.展开更多
Fault sealing capacity is controlled by present-day geometry and clay content,with current research focusing on enhancing the accuracy of capacity estimates.The mechanisms for evaluating both presentday and paleo-seal...Fault sealing capacity is controlled by present-day geometry and clay content,with current research focusing on enhancing the accuracy of capacity estimates.The mechanisms for evaluating both presentday and paleo-sealing are consistent,where the current sealing capacity representing the final stage in the evolutionary process of fault sealing.To address the limitations of the conventional shale gouge ratio(SGR)in evaluating the dynamic nature of fault sealing,this study proposes a visual model for fault sealing evolution.Fault sealing evolution is jointly controlled by the burial history and clay smear history and exerts a critical influence on hydrocarbon migration and accumulation.Hydrocarbon exploration data confirm that fault sealing during and after hydrocarbon migration critically impacts reservoir preservation.If faults remain unsealed during hydrocarbon migration and accumulation,they serve solely as conduits,with their present-day sealing capacity having limited impact.Effective fault sealing thus depends on the alignment between the evolutionary sealing stages and hydrocarbon activity.Building on this framework,we propose a method to visually and quantitatively characterize the fault sealing evolution alongside hydrocarbon activity.A case study of the Xishanyao Formation in the Houxia Basin highlights that the F4 fault transitioned from being over-open to sealed at the onset of hydrocarbon migration,thereby preserving the trap,while the F8-2 fault underwent a complete sealed–reopen cycle,with the late-stage reopening leading to an absence of hydrocarbon accumulation.This temporal contrast forms the basis for a new time-sensitive methodology for assessing fault-seal integrity in complex structural settings.展开更多
With the rapid expansion of drone applications,accurate detection of objects in aerial imagery has become crucial for intelligent transportation,urban management,and emergency rescue missions.However,existing methods ...With the rapid expansion of drone applications,accurate detection of objects in aerial imagery has become crucial for intelligent transportation,urban management,and emergency rescue missions.However,existing methods face numerous challenges in practical deployment,including scale variation handling,feature degradation,and complex backgrounds.To address these issues,we propose Edge-enhanced and Detail-Capturing You Only Look Once(EHDC-YOLO),a novel framework for object detection in Unmanned Aerial Vehicle(UAV)imagery.Based on the You Only Look Once version 11 nano(YOLOv11n)baseline,EHDC-YOLO systematically introduces several architectural enhancements:(1)a Multi-Scale Edge Enhancement(MSEE)module that leverages multi-scale pooling and edge information to enhance boundary feature extraction;(2)an Enhanced Feature Pyramid Network(EFPN)that integrates P2-level features with Cross Stage Partial(CSP)structures and OmniKernel convolutions for better fine-grained representation;and(3)Dynamic Head(DyHead)with multi-dimensional attention mechanisms for enhanced cross-scale modeling and perspective adaptability.Comprehensive experiments on the Vision meets Drones for Detection(VisDrone-DET)2019 dataset demonstrate that EHDC-YOLO achieves significant improvements,increasing mean Average Precision(mAP)@0.5 from 33.2%to 46.1%(an absolute improvement of 12.9 percentage points)and mAP@0.5:0.95 from 19.5%to 28.0%(an absolute improvement of 8.5 percentage points)compared with the YOLOv11n baseline,while maintaining a reasonable parameter count(2.81 M vs the baseline’s 2.58 M).Further ablation studies confirm the effectiveness of each proposed component,while visualization results highlight EHDC-YOLO’s superior performance in detecting objects and handling occlusions in complex drone scenarios.展开更多
Background:Ex vivo lung perfusion(EVLP)has emerged as a critical technique for lung preservation and evaluation prior to transplantation.While conventional rat EVLP systems utilize closed-loop dual cannulation of pulm...Background:Ex vivo lung perfusion(EVLP)has emerged as a critical technique for lung preservation and evaluation prior to transplantation.While conventional rat EVLP systems utilize closed-loop dual cannulation of pulmonary artery(PA)and vein,the effect of the simplified model using single PA cannulation with passive venous drainage is unknown.Methods:We developed two EVLP models in rats:a semi-closed circuit with PA-only cannulation and left atrial incision for passive venous drainage(SC-EVLP),and a closed circuit employing both arterial and venous cannulation(C-EVLP).Donor lungs were perfused for a defined duration and subsequently orthotopically transplanted.We evaluated pulmonary function parameters,histopathological injury scores,inflammatory cytokine levels,and apoptotic marker expression at the end of perfusion and posttransplantation.Results:Compared to the conventional EVLP,the SC-EVLP group exhibited significantly lower PA pressure and improved dynamic lung compliance throughout perfusion.Although the levels of tumor necrosis factor-αin the perfusate were higher in the SC-EVLP group,other cytokine levels in the perfusate and bronchoalveolar lavage fluid exhibited no significant differences.Pulmonary edema was reduced in the SC-EVLP group,as indicated by a lower lung wet-to-dry ratio.After transplantation,lungs from the SC-EVLP group exhibited lower histological injury scores,reduced apoptosis,and decreased serum cytokine levels,suggesting attenuated inflammation and tissue damage.Conclusions:In a rat model,single PA cannulation with passive venous drainage reduced pulmonary edema during EVLP and reduced lung injury and systemic inflammation after transplantation.展开更多
The multi-objective optimization problems,especially in constrained environments such as power distribution planning,demand robust strategies for discovering effective solutions.This work presents the improved variant...The multi-objective optimization problems,especially in constrained environments such as power distribution planning,demand robust strategies for discovering effective solutions.This work presents the improved variant of the Multi-population Cooperative Constrained Multi-Objective Optimization(MCCMO)Algorithm,termed Adaptive Diversity Preservation(ADP).This enhancement is primarily focused on the improvement of constraint handling strategies,local search integration,hybrid selection approaches,and adaptive parameter control.Theimproved variant was experimented on with the RWMOP50 power distribution systemplanning benchmark.As per the findings,the improved variant outperformed the original MCCMO across the eleven performance metrics,particularly in terms of convergence speed,constraint handling efficiency,and solution diversity.The results also establish that MCCMOADP consistently delivers substantial performance gains over the baseline MCCMO,demonstrating its effectiveness across performancemetrics.The new variant also excels atmaintaining the balanced trade-off between exploration and exploitation throughout the search process,making it especially suitable for complex optimization problems in multiconstrained power systems.These enhancements make MCCMO-ADP a valuable and promising candidate for handling problems such as renewable energy scheduling,logistics planning,and power system optimization.Future work will benchmark the MCCMO-ADP against widely recognized algorithms such as NSGA-Ⅱ,NSGA-Ⅲ,and MOEA/D and will also extend its validation to large-scale real-world optimization domains to further consolidate its generalizability.展开更多
The developing Sixth-Generation(6G)network aims to establish seamless global connectivity for billions of humans,machines,and devices.However,the rich digital service and the explosive heterogeneous connection between...The developing Sixth-Generation(6G)network aims to establish seamless global connectivity for billions of humans,machines,and devices.However,the rich digital service and the explosive heterogeneous connection between various entities in 6G networks can not only induce increasing complications of digital identity management,but also raise material concerns about the security and privacy of the user identity.In this paper,we design a user-centric identity management that returns the sole control to the user self and achieves identity sovereignty toward 6G networks.Specifically,we propose a blockchain-based Identity Management(IDM)architecture for 6G networks,which provides a practical method to secure digital identity management.Subsequently,we develop a fully privacy-preserving identity attribute management scheme by using zero-knowledge proof to protect the privacy-sensitive identity attribute.In particular,the scheme achieves an identity attribute hiding and verification protocol to support users in obtaining and applying their identity attributes without revealing concrete data.Finally,we analyze the security of the proposed architecture and implement a prototype system to evaluate its performance.The results demonstrate that our architecture ensures effective user digital identity management in 6G networks.展开更多
To adapt to gravitational forces during the transition to terrestrial life,animals evolved specialized paw skin to withstand their body weight and allow for locomotion.In a recent Cell article,Di et al.demonstrate SLU...To adapt to gravitational forces during the transition to terrestrial life,animals evolved specialized paw skin to withstand their body weight and allow for locomotion.In a recent Cell article,Di et al.demonstrate SLURP1 as an endoplasmic reticulum(ER)membrane protein that protects palmoplantar keratinocytes from mechanical stress by preserving SERCA2b activity and inhibiting the pPERK-NRF2 signaling under mechanical pressure.展开更多
文摘There is no better way to appreciate the unique character of Chinese modernisation than by spending 10 years fully immersed in the country.I arrived in China from Madagascar in 2016 as a student and have lived and worked here ever since.This experience has given me a profound firsthand insight into the country.
文摘Since the launch of a digitization project for the protection and utilization of ancient texts in the Sakya Monastery of the Xizang Autonomous Region in 2012,significant efforts and achievements have been made in ancient text preservation.
文摘Pseudosection modeling for the garnet amphibolite samples from the Western Dabie Mountains show they have experienced similar HP metamorphic evolution with that of the adjected eclogites.The common assemblage of
文摘The most of high/ultrahigh-pressure(HP/UHP)terranes of the world are characterized by the occurrence of numerous pods,lenses or layered blocks of eclogite and amphibolites(e.g.O’Brien,1997;Elvevold and Gilotti,2000;Zhang et al.,2003;and references there in).Field and petrological features suggest that amphibolites should
基金supported by the grants from the National Key Research and Development Program of China(Nos.2023YFD2301000 and 2022YFD2100102)the National Natural Science Foundation of China(Nos.32122080 and 32302616)+2 种基金the Key Research and Development Program of Shandong Province,China(No.2023CXGC010709)the Natural Science Foundation of Shandong Province,China(No.ZR2023QC032)the National Key Laboratory for Germplasm Innovation and Utilization of Horticultural Crops,China(No.Horti-KF-2023-11).
文摘Apples,as respiratory climacteric fruit,undergo postharvest ripening and senescence,impacting commodity value.Cuticular wax protects against environmental stresses.Here,gas chromatography-mass spectrometry(GC-MS)analysis revealed a decline in fatty alcohol levels in apple wax during storage,correlating with fruit quality deterioration.Notably,octacosanol content signifcantly decreased with storage,suggesting that it is a primary cause of wax and fruit quality decline.Octacosanol treatment improved fruit quality and delayed softening by enhancing wax synthesis and antioxidant levels and suppressing cell wall-degrading enzymes.Transcriptome sequencing and real-time quantitative polymerase chain reaction(RT-qPCR)assays indicated increased expression of wax,peroxidase,sucrose,and starch genes and decreased expression of cell wall degradation genes,explaining octacosanol’s benefts.This study provides a theoretical basis for octacosanol application in fruit preservation.
基金supported by the National Key Research and Development Program of China(2023YFF0612900,2023YFF0612902)the Natural Science Foundation of Beijing,China(4254086)+3 种基金the National Natural Science Foundation of China(62472032)the Open Project Funding of Key Laboratory of Mobile Application Innovation and Governance Technology,Ministry of Industry and Information Technology(2023IFS080601-K)the Beijing Institute of Technology Research Fund Program for Young Scholarsthe Young Elite Scientists Sponsorship Program by CAST(2023QNRC001)。
文摘Dear Editor,This letter addresses the critical challenge of preserving privacy in graph learning without compromising on data utility.Differential privacy(DP)is emerging as an effective method for privacy-preserving graph learning.However,its application often diminishes data utility,especially for nodes with fewer neighbors in graph neural networks(GNNs).
基金supported by the National Key Research and Development Program of China(2023YFD2100403)the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences(CAAS-ASTIP-2021-OCRI)+3 种基金the Earmarked Fund for CARS-14the Innovation Group Project of Hubei Province(2023AFA042)the Key Research Projects of Hubei Province(2020BBA045)Hubei Key Laboratory of Plasma Chemistry and Advanced Materials(2024P09),Wuhan Institute of Technology,Wuhan 430205,China。
文摘As the pace of urban life accelerates,plastic wrap has become an everyday necessity.However,traditional petroleum-based plastic wrap is difficult to degrade and prone to releasing harmful plasticizers.Therefore,developing sustainable,biodegradable,and high-performance alternative materials is crucial.Inspired by the cellulose-gum reinforcement mechanism in flaxseed hulls,this study utilized flaxseed hulls as raw material.Through hot water washing,alkali boiling,and bleaching,high-purity insoluble cellulose(FC)was extracted.Subsequently,flaxseed hull cellulose nanofibers(FCN)were prepared via TEMPO oxidation and ultrasonic treatment.Using FC and FCN,an all-natural cellulose-flaxseed gum composite membrane(CM)was constructed,where FCN serves as the framework and flaxseed gum acts as the binder,forming a dense structure.This composite membrane demonstrated effectiveness in nut preservation,significantly delaying nut oxidation and providing a viable pathway for sustainable food packaging.
基金funded by the National Natural Science Foundation of China,grant number 61605004the Fundamental Research Funds for the Central Universities,grant number FRF-TP-19-016A2Guizhou Power Grid Co.,Ltd.2024 first batch of services(2024-2026 technology R&D services for science and technology projects(in addition to national and SGCC key projects)),grant number 060100KC23100012。
文摘This study addresses the risk of privacy leakage during the transmission and sharing of multimodal data in smart grid substations by proposing a three-tier privacy-preserving architecture based on asynchronous federated learning.The framework integrates blockchain technology,the InterPlanetary File System(IPFS)for distributed storage,and a dynamic differential privacy mechanism to achieve collaborative security across the storage,service,and federated coordination layers.It accommodates both multimodal data classification and object detection tasks,enabling the identification and localization of key targets and abnormal behaviors in substation scenarios while ensuring privacy protection.This effectively mitigates the single-point failures and model leakage issues inherent in centralized architectures.A dynamically adjustable differential privacy mechanism is introduced to allocate privacy budgets according to client contribution levels and upload frequencies,achieving a personalized balance between model performance and privacy protection.Multi-dimensional experimental evaluations,including classification accuracy,F1-score,encryption latency,and aggregation latency,verify the security and efficiency of the proposed architecture.The improved CNN model achieves 72.34%accuracy and an F1-score of 0.72 in object detection and classification tasks on infrared surveillance imagery,effectively identifying typical risk events such as not wearing safety helmets and unauthorized intrusion,while maintaining an aggregation latency of only 1.58 s and a query latency of 80.79 ms.Compared with traditional static differential privacy and centralized approaches,the proposed method demonstrates significant advantages in accuracy,latency,and security,providing a new technical paradigm for efficient,secure data sharing,object detection,and privacy preservation in smart grid substations.
文摘The environment and its preservation are becoming more and more dependent on ecological development in an age of accelerating climate risk,biodiversity loss,and pressures of pollution.This review summarizes the frontiers of innovation that are capable of enhancing integration of human development and ecological integrity,and how the interaction between technical,ecological,and institutional innovations can produce real-world results.We initially discuss developing ecological innovations that offer new opportunities to urban development,such as low-impact cities,ecological infrastructure,clean energy transitions,and biodiversity-informed siting,and digital decision-support systems enhancing planning and resource efficiency.Then,we evaluate progress in the field of preservation and restoration,with a particular focus on nature-based solutions,a process-based approach to restoration science,connectivity conservation,and a watershed-scale and seascape-scale approach to restore resilience and help recover biodiversity.In these spheres,we discover measurement,monitoring,and verification(MRV),one of the main pillars of scale alongside remote sensing,automated field monitoring,environmental Deoxyribonucleic Acid(DNA),and Artificial Intelligence(AI)-enabled analytics,increasing the range of trackable and manageable indices as well as creating new issues with baselines,uncertainty,and data ethics.Lastly,we compare governance,finance,and equity as key conversion processes that can turn innovations into sustainable dividends with authenticity principles,however,of additionality,permanence,and leakage avoidance,and with rightsbased and redistributive mechanisms and approaches that reinforce legitimacy.We end by providing a portfolio roadmap of prioritization of the interventions that have high co-benefits and the identification of critical research and institutional gaps to provide net-positive ecological results.
文摘Recognizing frontal faces from non-frontal or profile images is a major problem due to pose changes,self-occlusions,and the complete loss of important structural and textural components,depressing recognition accuracy and visual fidelity.This paper introduces a new deep generative framework,Modified Multi-Scale Fused CycleGAN(MMF-CycleGAN),for robust and photo-realistic profile-to-frontal face synthesis.The MMF-CycleGAN framework utilizes pre-processing and then the generator employs a Deep Dilated DenseNet encoder-based hierarchical feature extraction along with a transformer and decoder.The proposed Multi-Scale Fusion PatchGAN discriminator enforces consistency at multiple spatial resolutions,leading to sharper textures and improved global facial geometry.Also,GAN training stability and identity preservation are improved through the Ranger optimizer,which effectively balances adversarial,identity,and cycle-consistency losses.Experiments on three benchmark datasets show that MMFCycleGAN achieves accuracy of 0.9541,0.9455,and 0.9422,F1-scores of 0.9654,0.9641,and 0.9614,and AUC values of 0.9742,0.9714,and 0.9698,respectively,and the extreme-pose accuracy(yaw>60°)reaches 0.92.Despite its enhanced architecture,the framework maintains an efficient inference time of 0.042 s per image,making it suitable for real-time biometric authentication,surveillance,and security applications in unconstrained environments.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,under grant No.(IFPDP-261-22).
文摘Medical imaging is essential in modern health care,allowing accurate diagnosis and effective treatment planning.These images,however,often demonstrate low contrast,noise,and brightness distortion that reduce their diagnostic reliability.This review presents a structured and comprehensive analysis of advanced histogram equalization(HE)-based techniques for medical image enhancement.Our review methodology encompasses:(1)classical HE approaches and related limitations in medical domains;(2)adaptive schemes like Adaptive Histogram Equalization(AHE)and Contrast Limited Adaptive Histogrma Equalization(CLAHE)and their advance variants;(3)brightnesspreserving schemes like BBHE and MMBEBHE and related algorithms;(4)dynamic and recursive histogram equalization methods incorporating DHE and RMSHE;(5)fuzzy logic-based enhancement methodologies addressing uncertainty and noise in medical images;and(6)hybrid optimization methodologies through the application of metaheuristic algorithms(World Cup Optimization,Particle Swarm Optimization,Genetic Algorithms,along with histogram-based methodologies.)There is also a comparative discussion given based on contrast improvement,image brightness preservation,noise management,and computational efficiency.Such advancements have better capabilities of improving image quality,which is more important for improved diagnosis and image analysis.
基金supported by the National Key Research and Development Program of China(2020AAA0109300)the Shanghai Collaborative Innovation Center of data intelligence technology(No.0232-A1-8900-24-13).
文摘Chinese abbreviations improve communicative efficiency by extracting key components from longer expressions.They are widely used in both daily communication and professional domains.However,existing abbreviation generation methods still face two major challenges.First,sequence-labeling-based approaches often neglect contextual meaning by making binary decisions at the character level,leading to abbreviations that fail to capture semantic completeness.Second,generation-basedmethods rely heavily on a single decoding process,which frequently produces correct abbreviations but ranks them lower due to inadequate semantic evaluation.To address these limitations,we propose a novel two-stage frameworkwithGeneration–Iterative Optimization forAbbreviation(GIOA).In the first stage,we design aChain-of-Thought prompting strategy and incorporate definitional and situational contexts to generate multiple abbreviation candidates.In the second stage,we introduce a Semantic Preservation Dynamic Adjustment mechanism that alternates between character-level importance estimation and semantic restoration to optimize candidate ranking.Experiments on two public benchmark datasets show that our method outperforms existing state-of-the-art approaches,achieving Hit@1 improvements of 15.15%and 13.01%,respectively,while maintaining consistent results in Hit@3.
基金supported by the University of Tabuk,Saudi Arabia。
文摘Multimodal spatiotemporal data from smart city consumer electronics present critical challenges including cross-modal temporal misalignment,unreliable data quality,limited joint modeling of spatial and temporal dependencies,and weak resilience to adversarial updates.To address these limitations,EdgeST-Fusion is introduced as a cross-modal federated graph transformer framework for context-aware smart city analytics.The architecture integrates cross-modal embedding networks for modality alignment,graph transformer encoders for spatial dependency modeling,temporal self-attention for dynamic pattern learning,and adaptive anomaly detection to ensure data quality and security during aggregation.A privacy-preserving federated learning protocol with differential privacy guarantees enables collaborative model training without centralizing sensitive data.The framework employs data-quality-aware weighted aggregation to enhance robustness against noisy and malicious client updates.Experimental evaluation on the GeoLife,PeMS-Bay,and SmartHome+datasets demonstrates that EdgeST-Fusion achieves 21.8%improvement in prediction accuracy,35.7%reduction in communication overhead,and 29.4%enhancement in security resilience compared to recent baselines.Real-world deployment across three smart city testbeds validates practical viability with 90.0%average accuracy and sub-250 ms inference latency.The proposed framework remains feasible for deployment on heterogeneous and resource-constrained consumer electronics devices whilemaintaining strong privacy guarantees and scalability for large-scale urban environments.
文摘The Royal Tropical Institute(KIT)in Amsterdam is an independent centre of knowledge and expertise in the areas of international and intercultural cooperation,operating at the interface between theory and practice and between policy and implementation.The Institute contributes to sustainable development,poverty alleviation and cultural preservation and exchange.
基金funded by the Project of Xinjiang University of Technology(No.2025XQYM044)PetroChina Coalbed Methane Company Project(No.WK23020DG04)。
文摘Fault sealing capacity is controlled by present-day geometry and clay content,with current research focusing on enhancing the accuracy of capacity estimates.The mechanisms for evaluating both presentday and paleo-sealing are consistent,where the current sealing capacity representing the final stage in the evolutionary process of fault sealing.To address the limitations of the conventional shale gouge ratio(SGR)in evaluating the dynamic nature of fault sealing,this study proposes a visual model for fault sealing evolution.Fault sealing evolution is jointly controlled by the burial history and clay smear history and exerts a critical influence on hydrocarbon migration and accumulation.Hydrocarbon exploration data confirm that fault sealing during and after hydrocarbon migration critically impacts reservoir preservation.If faults remain unsealed during hydrocarbon migration and accumulation,they serve solely as conduits,with their present-day sealing capacity having limited impact.Effective fault sealing thus depends on the alignment between the evolutionary sealing stages and hydrocarbon activity.Building on this framework,we propose a method to visually and quantitatively characterize the fault sealing evolution alongside hydrocarbon activity.A case study of the Xishanyao Formation in the Houxia Basin highlights that the F4 fault transitioned from being over-open to sealed at the onset of hydrocarbon migration,thereby preserving the trap,while the F8-2 fault underwent a complete sealed–reopen cycle,with the late-stage reopening leading to an absence of hydrocarbon accumulation.This temporal contrast forms the basis for a new time-sensitive methodology for assessing fault-seal integrity in complex structural settings.
文摘With the rapid expansion of drone applications,accurate detection of objects in aerial imagery has become crucial for intelligent transportation,urban management,and emergency rescue missions.However,existing methods face numerous challenges in practical deployment,including scale variation handling,feature degradation,and complex backgrounds.To address these issues,we propose Edge-enhanced and Detail-Capturing You Only Look Once(EHDC-YOLO),a novel framework for object detection in Unmanned Aerial Vehicle(UAV)imagery.Based on the You Only Look Once version 11 nano(YOLOv11n)baseline,EHDC-YOLO systematically introduces several architectural enhancements:(1)a Multi-Scale Edge Enhancement(MSEE)module that leverages multi-scale pooling and edge information to enhance boundary feature extraction;(2)an Enhanced Feature Pyramid Network(EFPN)that integrates P2-level features with Cross Stage Partial(CSP)structures and OmniKernel convolutions for better fine-grained representation;and(3)Dynamic Head(DyHead)with multi-dimensional attention mechanisms for enhanced cross-scale modeling and perspective adaptability.Comprehensive experiments on the Vision meets Drones for Detection(VisDrone-DET)2019 dataset demonstrate that EHDC-YOLO achieves significant improvements,increasing mean Average Precision(mAP)@0.5 from 33.2%to 46.1%(an absolute improvement of 12.9 percentage points)and mAP@0.5:0.95 from 19.5%to 28.0%(an absolute improvement of 8.5 percentage points)compared with the YOLOv11n baseline,while maintaining a reasonable parameter count(2.81 M vs the baseline’s 2.58 M).Further ablation studies confirm the effectiveness of each proposed component,while visualization results highlight EHDC-YOLO’s superior performance in detecting objects and handling occlusions in complex drone scenarios.
基金Key Science and Technology Program of Shaanxi Province,Grant/Award Number:2024SF2-GJHX-45National Natural Science Foundation of China,Grant/Award Number:82472191The Natural Science Foundation of Shaanxi Province,Grant/Award Number:2024JC-ZDXM-49。
文摘Background:Ex vivo lung perfusion(EVLP)has emerged as a critical technique for lung preservation and evaluation prior to transplantation.While conventional rat EVLP systems utilize closed-loop dual cannulation of pulmonary artery(PA)and vein,the effect of the simplified model using single PA cannulation with passive venous drainage is unknown.Methods:We developed two EVLP models in rats:a semi-closed circuit with PA-only cannulation and left atrial incision for passive venous drainage(SC-EVLP),and a closed circuit employing both arterial and venous cannulation(C-EVLP).Donor lungs were perfused for a defined duration and subsequently orthotopically transplanted.We evaluated pulmonary function parameters,histopathological injury scores,inflammatory cytokine levels,and apoptotic marker expression at the end of perfusion and posttransplantation.Results:Compared to the conventional EVLP,the SC-EVLP group exhibited significantly lower PA pressure and improved dynamic lung compliance throughout perfusion.Although the levels of tumor necrosis factor-αin the perfusate were higher in the SC-EVLP group,other cytokine levels in the perfusate and bronchoalveolar lavage fluid exhibited no significant differences.Pulmonary edema was reduced in the SC-EVLP group,as indicated by a lower lung wet-to-dry ratio.After transplantation,lungs from the SC-EVLP group exhibited lower histological injury scores,reduced apoptosis,and decreased serum cytokine levels,suggesting attenuated inflammation and tissue damage.Conclusions:In a rat model,single PA cannulation with passive venous drainage reduced pulmonary edema during EVLP and reduced lung injury and systemic inflammation after transplantation.
文摘The multi-objective optimization problems,especially in constrained environments such as power distribution planning,demand robust strategies for discovering effective solutions.This work presents the improved variant of the Multi-population Cooperative Constrained Multi-Objective Optimization(MCCMO)Algorithm,termed Adaptive Diversity Preservation(ADP).This enhancement is primarily focused on the improvement of constraint handling strategies,local search integration,hybrid selection approaches,and adaptive parameter control.Theimproved variant was experimented on with the RWMOP50 power distribution systemplanning benchmark.As per the findings,the improved variant outperformed the original MCCMO across the eleven performance metrics,particularly in terms of convergence speed,constraint handling efficiency,and solution diversity.The results also establish that MCCMOADP consistently delivers substantial performance gains over the baseline MCCMO,demonstrating its effectiveness across performancemetrics.The new variant also excels atmaintaining the balanced trade-off between exploration and exploitation throughout the search process,making it especially suitable for complex optimization problems in multiconstrained power systems.These enhancements make MCCMO-ADP a valuable and promising candidate for handling problems such as renewable energy scheduling,logistics planning,and power system optimization.Future work will benchmark the MCCMO-ADP against widely recognized algorithms such as NSGA-Ⅱ,NSGA-Ⅲ,and MOEA/D and will also extend its validation to large-scale real-world optimization domains to further consolidate its generalizability.
文摘The developing Sixth-Generation(6G)network aims to establish seamless global connectivity for billions of humans,machines,and devices.However,the rich digital service and the explosive heterogeneous connection between various entities in 6G networks can not only induce increasing complications of digital identity management,but also raise material concerns about the security and privacy of the user identity.In this paper,we design a user-centric identity management that returns the sole control to the user self and achieves identity sovereignty toward 6G networks.Specifically,we propose a blockchain-based Identity Management(IDM)architecture for 6G networks,which provides a practical method to secure digital identity management.Subsequently,we develop a fully privacy-preserving identity attribute management scheme by using zero-knowledge proof to protect the privacy-sensitive identity attribute.In particular,the scheme achieves an identity attribute hiding and verification protocol to support users in obtaining and applying their identity attributes without revealing concrete data.Finally,we analyze the security of the proposed architecture and implement a prototype system to evaluate its performance.The results demonstrate that our architecture ensures effective user digital identity management in 6G networks.
基金supported by Applied Basic Research Foundation of Yunnan Province,No.202501AT070205(W.N.).
文摘To adapt to gravitational forces during the transition to terrestrial life,animals evolved specialized paw skin to withstand their body weight and allow for locomotion.In a recent Cell article,Di et al.demonstrate SLURP1 as an endoplasmic reticulum(ER)membrane protein that protects palmoplantar keratinocytes from mechanical stress by preserving SERCA2b activity and inhibiting the pPERK-NRF2 signaling under mechanical pressure.
