Integrated environmental management is important for sustainable development.Under China’s“Three Lines One Permit”(TLOP)policy,three types of management zones—priority protection,critical control,and general contr...Integrated environmental management is important for sustainable development.Under China’s“Three Lines One Permit”(TLOP)policy,three types of management zones—priority protection,critical control,and general control zones—are established based on the ecological red line,the lower-limit line for environmental quality,and the resource use line.Human activities are regulated through a permit system.Integrated and multifactorial protection of soil,plant,hydrological,and atmospheric elements is promoted at the regional level.A follow-up assessment contributes to the improvement of policy implementation and effectiveness.This study demonstrates the achievements of the TLOP policy in Sichuan Province.Results show that(1)276 protection zones have been established under the ecological red line,covering key ecosystems and protected areas to ensure environmental security.Under the lower-limit line,1,626 functional(priority,key,and general control)zones have been designated to regulate air,water,and soil quality,enhancing environmental capacity and pollution control.(2)Through the integration and merging of the three lines,1,128 integrated management zones have been established,including 375,625,and 128 priority protection,critical control,and general control zones,respectively.Each zone has its own list of environmental permits to regulate human activities according to different environmental protection and natural resource development regimes.(3)The design of the follow-up assessment index system was informed by regional primary functions and industrial structure.The index system for provinces and cities is structured around three primary indicators—implementation updating,application,and guarantees—and 15 secondary indicators.The system for critical control zones is structured around environmental access,management,and effectiveness and 14 secondary indicators.A stringent environmental zoning system has been established through the TLOP policy,thereby safeguarding environmental security,promoting harmonious existence between humans and nature,and supporting the vision of Beautiful China.展开更多
Human cardiac organoids have revolutionized the study of cardiac development,disease modeling, drug discovery, and regenerative therapies. This review systematically discusses strategies and progress in the constructi...Human cardiac organoids have revolutionized the study of cardiac development,disease modeling, drug discovery, and regenerative therapies. This review systematically discusses strategies and progress in the construction of cardiac organoids, categorizing them into three main types:cardiac spheroids, self-organizing/assembloid organoids, and organoid-on-a-chip systems. This review uniquely integrates the advances in vascularization, organ-on-chip design, and environmental cardiotoxicity modeling within cardiac organoid platforms, offering a critical synthesis that is absent in the literature. In the context of escalating environmental threats to cardiovascular health, there is an urgent need for physiologically relevant models to accurately identify cardiac toxicants and elucidate their underlying mechanisms of action. This review highlights advances in cardiac organoid applications for disease modeling-including congenital heart defects and acquired cardiovascular diseases-drug development, toxicity screening, and the study of environmentally induced cardiovascular pathogenesis. In addition, it critically examines ongoing challenges and underscores opportunities brought by bioengineering approaches. Finally, we propose future directions for developing standardized cardiac organoid platforms with clinical predictability, aiming to expand the utility of this technology across broader research applications.展开更多
In modern industrial production,foreign object detection in complex environments is crucial to ensure product quality and production safety.Detection systems based on deep-learning image processing algorithms often fa...In modern industrial production,foreign object detection in complex environments is crucial to ensure product quality and production safety.Detection systems based on deep-learning image processing algorithms often face challenges with handling high-resolution images and achieving accurate detection against complex backgrounds.To address these issues,this study employs the PatchCore unsupervised anomaly detection algorithm combined with data augmentation techniques to enhance the system’s generalization capability across varying lighting conditions,viewing angles,and object scales.The proposed method is evaluated in a complex industrial detection scenario involving the bogie of an electric multiple unit(EMU).A dataset consisting of complex backgrounds,diverse lighting conditions,and multiple viewing angles is constructed to validate the performance of the detection system in real industrial environments.Experimental results show that the proposed model achieves an average area under the receiver operating characteristic curve(AUROC)of 0.92 and an average F1 score of 0.85.Combined with data augmentation,the proposed model exhibits improvements in AUROC by 0.06 and F1 score by 0.03,demonstrating enhanced accuracy and robustness for foreign object detection in complex industrial settings.In addition,the effects of key factors on detection performance are systematically analyzed,providing practical guidance for parameter selection in real industrial applications.展开更多
With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comp...With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.展开更多
Prussian blue analogs(PBAs)are considered one of the excellent cathode materials for sodium-ion batteries due to their low cost and high theoretical specific capacity,especially sodium-rich iron-based PBAs(FeHCF)can p...Prussian blue analogs(PBAs)are considered one of the excellent cathode materials for sodium-ion batteries due to their low cost and high theoretical specific capacity,especially sodium-rich iron-based PBAs(FeHCF)can provide higher energy density.FeHCF has a poor charge/discharge platform stability at high voltages(FeC_(6)moiety),which is mainly affected by its coordination environment.In this research,Cu^(+)(six-coordinated),which is close to the ionic radius of Fe^(2+),was used for substitution,the FeC_(6)vacancies of FeHCF were reduced,and the coordination environment was optimized.The low Cu^(+)-substituted FeHCF(Cu^(+)0.625)has an optimal electrochemical performance at 8.5 mA/g with a reversible specific capacity of 142 mA h/g and FeC_(6)moiety contribution of more than 68 mA h/g,which is superior to that of unmodified and other Cu^(2+)-substituted FeHCFs.In situ tests demonstrate the reversible structural stability of the Cu^(+)0.625,supporting the stability of their high-voltage platform capacity.This Cu^(+)substitution strategy further enriches the approach to optimize the coordination environment of sodium-rich FeHCF.展开更多
In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to...In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to dangerous situations.Furthermore,autonomous vehicles may operate abnormally in bad weather due to limitations of their sensors and GPS.Driving simulators,which replicate driving conditions nearly identical to those in the real world,can drastically reduce the time and cost required for market entry validation;consequently,they have become widely used.In this paper,we design a virtual driving test environment capable of collecting and verifying SiLS data under adverse weather conditions using multi-source images.The proposed method generates a virtual testing environment that incorporates various events,including weather,time of day,and moving objects,that cannot be easily verified in real-world autonomous driving tests.By setting up scenario-based virtual environment events,multi-source image analysis and verification using real-world DCUs(Data Concentrator Units)with V2X-Car edge cloud can effectively address risk factors that may arise in real-world situations.We tested and validated the proposed method with scenarios employing V2X communication and multi-source image analysis.展开更多
Oxygen vacancy(Vo)engineering has been recognized as one of the most effective strategies for enhancing the photocatalytic CO_(2) conversion performance of metal oxides,as it can simultaneously facilitate photogenerat...Oxygen vacancy(Vo)engineering has been recognized as one of the most effective strategies for enhancing the photocatalytic CO_(2) conversion performance of metal oxides,as it can simultaneously facilitate photogenerated charge carrier separation efficiency and provide additional surface reaction sites.However,the wide application of Vo engineering in photocatalysis are limited by its poor stability,owing to the easy recovery of these vacancy defects by atmospheric oxygen.Herein,we develop an indium(In)doping strategy to regulate the coordination environment in CeO_(2) with abundant Vo(CeO_(2-x)),thereby enhance its stability during photocatalytic CO_(2) conversion.Confirmed by positron annihilation lifetime spectroscopy(PALS),In dopants combine with Vo by substituting for part of Ce^(4+),forming In^(3+)-Vo complexes that effectively inhibit the formation of unstable va-cancy clusters.Such In^(3+)-Vo complexes can also reduce the energy required for formation of the CO products.Therefore,the optimized In-doped CeO_(2-x) exhibits excellent photocatalytic CO_(2) conversion performance,with a CO yield of 301.6μmol⋅g^(-1) after 5 h of light irradiation,and maintain high activity after four cycles of experiments.Comprehensive experimental and theoretical studies indicate that the introduction of In doping not only significantly improves the stability of Vo in CeO_(2-x),but also reconstruct the reaction kinetics of the CO_(2) conversion by forming In^(3+)-Vo complexes thus facilitating the overall reaction.展开更多
As large,room-scale environments become increasingly common,their spatial complexity increases due to variable,unstructured elements.Consequently,demand for room-scale service robots is surging,yet most technologies r...As large,room-scale environments become increasingly common,their spatial complexity increases due to variable,unstructured elements.Consequently,demand for room-scale service robots is surging,yet most technologies remain corridor-centric,and autonomous navigation in expansive rooms becomes unstable even around static obstacles.Existing approaches face several structural limitations.These include the labor-intensive requirement for large-scale object annotation and continual retraining,as well as the vulnerability of vanishing point or linebased methods when geometric cues are insufficient.In addition,the high cost of LiDAR and 3D perception errors caused by limited wall cues and dense interior clutter further limit their effectiveness.To address these challenges,we propose a zero-shot vision-based algorithm for robust 3D map reconstruction in geometry-deficient room-scale environments.The algorithm operates in three layers:Layer 1 performs dimension-wise boundary detection;Layer 2 estimates vanishing points,refines the precise perspective space,and extracts a floor mask;and Layer 3 conducts 3D spatial mapping and obstacle recognition.The proposed method was experimentally validated across various geometric-deficient room-scale environments,including lobbies,seminar rooms,conference rooms,cafeterias,and museums—demonstrating its ability to reliably reconstruct 3D maps and accurately recognize obstacles.Experimental results show that the proposed algorithm achieved an F1 score of 0.959 in precision perspective space detection and 0.965 in floor mask extraction.For obstacle recognition and classification,it obtained F1 scores of 0.980 in obstacle absent areas,0.913 in solid obstacle environments,and 0.939 in skeleton-type sparse obstacle environments,confirming its high precision and reliability in geometric-deficient room-scale environments.展开更多
The atmospheric corrosion behavior of 510L low alloy steel subjected to acid-cleaned surface(ACS)and eco-pickled surface(EPS)treatments is systematically examined.After 1 year of atmospheric exposure,both ACS-and EPS-...The atmospheric corrosion behavior of 510L low alloy steel subjected to acid-cleaned surface(ACS)and eco-pickled surface(EPS)treatments is systematically examined.After 1 year of atmospheric exposure,both ACS-and EPS-treated samples demonstrate protective ability index values exceeding 2,indicating robust protective properties of the developed rust layers.The corrosion rates of ACS-and EPS-treated samples are similar.During the initial corrosion stage,γ-FeOOH emerges as the dominant corrosion product.With the prolonged atmospheric exposure,γ-FeOOH content progressively decreases through phase transformation into thermodynamically stableα-FeOOH and densely structured Fe_(3)O_(4),which markedly suppresses the corrosion of the steel.Notably,the corrosion rate of the coated EPS sample is obviously lower than that of the coated ACS counterpart,which is ascribed to the distinctive micro-roughness of EPS-treated surfaces that promote mechanical interlocking with protective coatings.展开更多
In the context of the revolution in new technologies,a key question is whether the rapid growth of the digital economy,driven by digital technologies,has improved regional innovation performance.Using inter-provincial...In the context of the revolution in new technologies,a key question is whether the rapid growth of the digital economy,driven by digital technologies,has improved regional innovation performance.Using inter-provincial panel data from China(2012–2022)and adopting a business environment perspective,this study applies a Panel Extended Regression Model(PERM),a Panel Simultaneous Equation Model(PSEM),and a Tobit-IV model to analyze how the development of the digital economy influences regional innovation.The results reveal a pronounced U-shaped relationship between the digital economy and the regional innovation performance at the provincial level in China,with the business environment serving as a significant mediator in this relationship.Moreover,regional innovation performance in China exhibits a“ratchet effect,”with the impact of the digital economy varying markedly across regions.While the eastern and western regions have entered an upward phase,whereby the digital economy boosts innovation,the central region displays a weaker effect.Further analysis indicates that the synergy between the business environment and the digital economy in driving innovation remains suboptimal.These findings were supported by robust checks.This study offers theoretical insights and empirical evidence that support the coordinated development of digital government and the digital factor market,as well as business environment reforms that are in alignment with the innovation demands of the digital era.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
Environment serves as the pivotal medium to produce fermented food,with fluctuations in environmental factors exerting a profound impact on the modulation of fermentation microbial communities.Such shifts are crucial ...Environment serves as the pivotal medium to produce fermented food,with fluctuations in environmental factors exerting a profound impact on the modulation of fermentation microbial communities.Such shifts are crucial for the distinctiveness of fermented food flavor and the variability in quality.Chinese liquor(Baijiu)is one of the typical representatives of spontaneous fermented food.In this review,the multifaceted relationship between regional environmental attributes and the fermentation dynamics of Baijiu was examined,with a spotlight on the strong-flavor,sauce-flavor,and light-flavor varieties.It reveals the influence of regional environmental factors and brewing environmental factors on microbial function and metabolism,which results in the formation of unique flavor characteristics of Baijiu.The 9 main factors affecting the microecology of Baijiu fermentation were further explored,including environmental sensitivity,microbial interactions,biogeographic patterns,and key abiotic factors such as temperature and humidity.Environmental factor management is crucial for controlling microbial community in fermentation.Intelligent detection of the fermentation system is combined with artificial intelligence to realize the digitalization of Baijiu fermentation,with a view to further studying the environmental mechanism or quantitative control relationship of natural fermentation,improving the environmental stability of natural fermentation,and promoting the mechanization and intelligence of fermentation production.展开更多
The surge in environmental pollution in recent years driven by numerous pollutants has necessitated the search for efficient removal methods.Phytoremediation is an eco-friendly technique that provides multiple benefit...The surge in environmental pollution in recent years driven by numerous pollutants has necessitated the search for efficient removal methods.Phytoremediation is an eco-friendly technique that provides multiple benefits over conventional methods of removing contaminants.Despite the numerous benefits of this technique,it has certain limitations that can be addressed by incorporating nanoparticles to improve its effectiveness.This review paper aims to explore the impact of heavy metal pollution on plants and human health.It highlights the role and mechanism of nanoparticles in enhancing phytoremediation,their application in the detection of heavy metals,and the strategies for the safe disposal of phytoremediation biomass.Biosynthesized nanoparticles are eco-friendly and non-toxic,with applications in biomedical and environmental fields.Nanoparticles can be used in the form of nano biosensors like smartphone-operated wireless sensors made from Cinnamomum camphora,enabling efficient detection of heavy metal ions.According to the studies,nanoparticles remove 80%–97%of heavy metals by various methods like reduction,precipitation,adsorption,etc.The phytoremediation biomass disposal can be done by heat treatment,phytomining,and microbial treatment with some modifications to further enhance their results.Phytoremediation is an environmentally friendly technique but requires further research and integration with biomass energy production to overcome scalability challenges and ensure safe biomass disposal.展开更多
The high-temperature interaction of nanostructured Lu_(2)Si_(2)O_(7) environmental barrier coatings(EBCs)with calcium-magnesium-aluminosilicate(CMAS)was investigated at 1400℃ for 1,10,25,and 50 h to evaluate the coat...The high-temperature interaction of nanostructured Lu_(2)Si_(2)O_(7) environmental barrier coatings(EBCs)with calcium-magnesium-aluminosilicate(CMAS)was investigated at 1400℃ for 1,10,25,and 50 h to evaluate the coating’s resistance to CMAS corrosion.The results indicate a phase transformation over time,transitioning from Ca_(2)Lu_(8)(SiO_(4))6O_(2) apatite and Lu_(2)Si_(2)O_(7) to solely Lu_(2)Si_(2)O_(7).The interaction of the Lu_(2)Si_(2)O_(7) coating with the CMAS melts was divided into three stages based on the corrosion reaction behavior.The delamination cracks were distributed throughout the interface between the Si bond layer and Lu_(2)Si_(2)O_(7) layer after corroded at 1400℃ for 50 h,signifying coating failure.In addition,the influence of monosilicates,disilicates,and corrosion duration on the recession layer thickness was analyzed by comparing previous reports on RE_(2)SiO_(5)/RE_(2)Si_(2)O_(7) coatings(RE=Gd,Yb,Lu,Er).Furthermore,the variation in the thermally grown oxide layer thickness in CMAS-corroded Lu_(2)Si_(2)O_(7) coatings was systematically investigated.展开更多
In fire rescue scenarios,traditional manual operations are highly dangerous,as dense smoke,low visibility,extreme heat,and toxic gases not only hinder rescue efficiency but also endanger firefighters’safety.Although ...In fire rescue scenarios,traditional manual operations are highly dangerous,as dense smoke,low visibility,extreme heat,and toxic gases not only hinder rescue efficiency but also endanger firefighters’safety.Although intelligent rescue robots can enter hazardous environments in place of humans,smoke poses major challenges for human detection algorithms.These challenges include the attenuation of visible and infrared signals,complex thermal fields,and interference frombackground objects,all ofwhichmake it difficult to accurately identify trapped individuals.To address this problem,we propose VIF-YOLO,a visible–infrared fusion model for real-time human detection in dense smoke environments.The framework introduces a lightweight multimodal fusion(LMF)module based on learnable low-rank representation blocks to end-to-end integrate visible and infrared images,preserving fine details while enhancing salient features.In addition,an efficient multiscale attention(EMA)mechanism is incorporated into the YOLOv10n backbone to improve feature representation under low-light conditions.Extensive experiments on our newly constructedmultimodal smoke human detection(MSHD)dataset demonstrate thatVIF-YOLOachievesmAP50 of 99.5%,precision of 99.2%,and recall of 99.3%,outperforming YOLOv10n by a clear margin.Furthermore,when deployed on the NVIDIA Jetson Xavier NX,VIF-YOLO attains 40.6 FPS with an average inference latency of 24.6 ms,validating its real-time capability on edge-computing platforms.These results confirm that VIF-YOLO provides accurate,robust,and fast detection across complex backgrounds and diverse smoke conditions,ensuring reliable and rapid localization of individuals in need of rescue.展开更多
Global environmental changes including climate warming,extreme weather events,ambient air pollution,freshwater contamination,and landscape transformation are reshaping the epidemiology of infectious diseases with unpr...Global environmental changes including climate warming,extreme weather events,ambient air pollution,freshwater contamination,and landscape transformation are reshaping the epidemiology of infectious diseases with unprecedented complexity,particularly in the post-COVID-19 era.This review synthesizes evidence from the past decade(2015-2024)to systematically elucidate how key environmental drivers modulate pathogen emergence,transmission dynamics,and clinical outcomes,with a focus on underlying mechanistic pathways.Specifically,we highlight:(1)the temperature-and precipitation-dependent transmission of vector-borne diseases(e.g.,malaria,dengue)via expanded vector habitats and accelerated pathogen incubation;(2)the exacerbation of respiratory infections(including COVID-19)by particulate matter(PM2.5)and nitrogen dioxide(NO2)through impaired mucosal immunity and enhanced inflammatory responses;(3)the persistence of diarrheal diseases in low-and middle-income countries(LMICs)linked to water insecurity and climate-induced infrastructure failure;and(4)zoonotic spillover risks amplified by urbanization and deforestation-driven human-wildlife interface disruption.Integrating the One Health socioecological framework,we further summarize methodological advances from high-resolution genomic surveillance to climate-informed machine learning models that have improved causal inference and predictive accuracy.Our synthesis confirms that environmental factors are not merely contextual but central,modifiable determinants of infectious disease risk,with disproportionate impacts on vulnerable populations.To mitigate future threats,we emphasize the urgency of interdisciplinary collaboration,integrated environmental-health monitoring platforms,and climate-resilient public health policies tailored to post-pandemic challenges.This review provides a timely roadmap for translating environmental epidemiology insights into actionable strategies to strengthen global health resilience.展开更多
Anammox bacteria in constructed wetlands(CWs)play pivotal role in sustainable nitrogen transformation,yet existing studies lack comprehensive analysis of environmental gradients and microbial interactions,both key fac...Anammox bacteria in constructed wetlands(CWs)play pivotal role in sustainable nitrogen transformation,yet existing studies lack comprehensive analysis of environmental gradients and microbial interactions,both key factors in anammox bacteria enrichment.This study investigated the mechanisms driving anammox bacteria enrichment in lab-scale simulated CWs treating high-nitrogen wastewater,focusing on bacterial community re-sponses across wetland layers with various strategies,including continuous up-flow influent,nitrogen loading increase,effluent recirculation,intermittent influent,and anammox bacteria inoculation.Results showed that total relative and absolute abundances of anammox bacteria ranged from 0.77%to 12.50%and from 0.13 to 6.46×10^(7) copies/g,respectively.Dissolved oxygen and pH had significant positive correlations with the absolute abundance of anammox bacteria,while organic matter and nitrate negatively impacted their relative abundance.Permutational multivariate analysis of variance indicated that spatial heterogeneity explained more variation in anammox bacteria abundance(43.44%)compared to operational strategies(8.58%).In terms of microbial interactions,60 dominant species exhibited potential correlations with anammox bacteria,comprising 170 interactions(105 positive and 65 negative),which suggested that anammox bacteria generally foster cooperative relationships with dominant bacteria.Notably,significant interspecies interactions were observed between Candidatus Kuenenia(dominant anammox bacteria in CWs)and species within the genera Chitinivibrio-nia and Anaerolineaceae,suggesting that microbial interactions primarily manifest as indirect facilitative effects rather than direct mutualistic relationships.Given that the Normalized Stochasticity Ratio in CWs were<50%,this study inferred that environmental gradients have greater influence on anammox bacteria than microbial interactions.展开更多
Decarbonising the building sector,particularly residential heating,represents a critical challenge for achieving carbon-neutral energy systems.Efficient solutions must integrate both technological performance and rene...Decarbonising the building sector,particularly residential heating,represents a critical challenge for achieving carbon-neutral energy systems.Efficient solutions must integrate both technological performance and renewable energy sources while considering operational constraints of existing systems.This study investigates a hybrid heating system combining a natural gas boiler(NGB)with an air-to-water heat pump(AWHP),evaluated through a combination of laboratory experiments and dynamic modelling.A prototype developed in the Electrical and Energy Engineering Laboratory enabled the characterization of both heat generators,the collection of experimental data,and the calibration of a MATLAB/Simulink model,including emissions and exhaust analyses.Sensitivity analyses were performed to identify optimal configurations for energy efficiency and system control,accounting for interactions between subsystems.Results highlight that hybridisation significantly improves primary energy efficiency and reduces fuel consumption compared to conventional NGB-only systems.Environmental performance,assessed through CO_(2) and NOx emissions and renewable energy integration,demonstrates the benefits of partial electrification in the residential sector.Economic assessment further quantifies decarbonization costs and fuel savings,illustrating tradeoffs between low-capital,moderate-performance systems and high-efficiency,high-renewable solutions requiring larger investments.The analysis shows that strategic decisions for residential decarbonisation cannot be separated from system-wide considerations,including control strategies,component integration,and economic feasibility.The study underlines the importance of hybrid and renewable-based solutions as pivotal pathways for energy transition in the residential building sector.展开更多
Compared with traditional energy sources,wind power has a lower environmental impact.However,emissions are still generated across the life cycle of wind turbines,from production to recycling.As wind power rapidly deve...Compared with traditional energy sources,wind power has a lower environmental impact.However,emissions are still generated across the life cycle of wind turbines,from production to recycling.As wind power rapidly develops and deployment increases,these impacts are becoming increasingly evident.A comprehensive understanding of these impacts is crucial for sustainable development.Based on the harmonization of previous detailed life cycle assessment(LCA)studies,this study develops a simplified LCA model that estimates the life cycle environmental impacts of wind turbines based on their nominal power.Using this simplified LCA model,we assess the global warming potential(GWP),acidification potential(AP),and cumulative energy demand(CED)of wind power at the regional scale for 2022 and under three future scenarios(high-power wind turbine promotion,reduced wind curtailment,and a comprehensive development scenario).The results indicate that in 2022,the life cycle GWP,AP,and CED of wind power in western China were 10.76 g CO_(2) eq/kWh,0.177 g SO_(2) eq/kWh,and 17.6 kJ/kWh,respectively.Scenario simulations suggest that reducing wind curtailment is the most effective approach for reducing emissions in Inner Mongolia,Gansu,Qinghai,Ningxia,and Xinjiang,producing average decreases of 8.64%in GWP,8.39%in AP,and 9.26%in CED.In contrast,for Guangxi,Chongqing,Sichuan,Guizhou,Yunnan,Xizang,and Shaanxi,the promotion of high-power wind turbines provides greater environmental benefits than reducing curtailment,producing average decreases of 3.45%,3.09%,and 4.29%in GWP,AP,and CED,respectively.These findings help clarify the environmental impact of wind power across its life cycle at the regional scale and provide theoretical references for the direction of future wind power development and the formulation of related policies.展开更多
Background:Exposure to environmental vulnerability poses significant threats to adolescent suicidal ideation,while individual resilience can mitigate these adverse effects with notable gender commonalities and differe...Background:Exposure to environmental vulnerability poses significant threats to adolescent suicidal ideation,while individual resilience can mitigate these adverse effects with notable gender commonalities and differences.However,research examining how these factors co-configure at the individual level remains limited,particularly from a gender-specific perspective.Thus,the present study aims to adopt a person-centered analytic approach to identify gender-specific configurations of environmental vulnerability and individual resilience associated with suicidal ideation among Chinese adolescents.Methods:Data were collected from 2616 Chinese primary and secondary school students(aged 10–17;1223 girls).Participants completed validated scales measuring environmental vulnerability,individual resilience,and suicidal ideation.Latent profile analysis(LPA)was conducted separately by gender.Results:Gender differences were prominent:males exhibited higher resilience and lower suicidal ideation,while females reported higher environmental vulnerability and elevated levels of suicidal ideation.LPA identified three distinct profiles for males:Low Vulnerable–High Protective–Low Risk(LHL),Medium Vulnerable–Low Protective–Low Risk(MLL),and High Vulnerable–Low Protective–High Risk(HLH).Four profiles emerged for females:LHL,MLL,Medium Vulnerable–Low Protective–Medium Risk(MLM),and HLH.Crucially,within the HLH profile,males exhibited particularly deficient humor(η^(2)=0.19)and confidence(η^(2)=0.16),while females formed a distinct subgroup characterized by severe academic and family stressors(η^(2)=0.30–0.36).Conclusion:The study underscores developing gender-specific mental health interventions using a nuanced,person-centered approach that considers both environmental risk and individual resilience factors,which allows for targeted suicide prevention strategies addressing the unique needs of male and female adolescents.展开更多
基金supported by the National Natural Science Foundation of China(grant numbers 42171085)and the National Key R&D Program of China(Grant No.2024YFF1307801,2024YFF1307804).
文摘Integrated environmental management is important for sustainable development.Under China’s“Three Lines One Permit”(TLOP)policy,three types of management zones—priority protection,critical control,and general control zones—are established based on the ecological red line,the lower-limit line for environmental quality,and the resource use line.Human activities are regulated through a permit system.Integrated and multifactorial protection of soil,plant,hydrological,and atmospheric elements is promoted at the regional level.A follow-up assessment contributes to the improvement of policy implementation and effectiveness.This study demonstrates the achievements of the TLOP policy in Sichuan Province.Results show that(1)276 protection zones have been established under the ecological red line,covering key ecosystems and protected areas to ensure environmental security.Under the lower-limit line,1,626 functional(priority,key,and general control)zones have been designated to regulate air,water,and soil quality,enhancing environmental capacity and pollution control.(2)Through the integration and merging of the three lines,1,128 integrated management zones have been established,including 375,625,and 128 priority protection,critical control,and general control zones,respectively.Each zone has its own list of environmental permits to regulate human activities according to different environmental protection and natural resource development regimes.(3)The design of the follow-up assessment index system was informed by regional primary functions and industrial structure.The index system for provinces and cities is structured around three primary indicators—implementation updating,application,and guarantees—and 15 secondary indicators.The system for critical control zones is structured around environmental access,management,and effectiveness and 14 secondary indicators.A stringent environmental zoning system has been established through the TLOP policy,thereby safeguarding environmental security,promoting harmonious existence between humans and nature,and supporting the vision of Beautiful China.
基金supported by the Innovation Promotion Program of NHC and Shanghai Key Labs,SIBPT(grant number PT2025-01)。
文摘Human cardiac organoids have revolutionized the study of cardiac development,disease modeling, drug discovery, and regenerative therapies. This review systematically discusses strategies and progress in the construction of cardiac organoids, categorizing them into three main types:cardiac spheroids, self-organizing/assembloid organoids, and organoid-on-a-chip systems. This review uniquely integrates the advances in vascularization, organ-on-chip design, and environmental cardiotoxicity modeling within cardiac organoid platforms, offering a critical synthesis that is absent in the literature. In the context of escalating environmental threats to cardiovascular health, there is an urgent need for physiologically relevant models to accurately identify cardiac toxicants and elucidate their underlying mechanisms of action. This review highlights advances in cardiac organoid applications for disease modeling-including congenital heart defects and acquired cardiovascular diseases-drug development, toxicity screening, and the study of environmentally induced cardiovascular pathogenesis. In addition, it critically examines ongoing challenges and underscores opportunities brought by bioengineering approaches. Finally, we propose future directions for developing standardized cardiac organoid platforms with clinical predictability, aiming to expand the utility of this technology across broader research applications.
文摘In modern industrial production,foreign object detection in complex environments is crucial to ensure product quality and production safety.Detection systems based on deep-learning image processing algorithms often face challenges with handling high-resolution images and achieving accurate detection against complex backgrounds.To address these issues,this study employs the PatchCore unsupervised anomaly detection algorithm combined with data augmentation techniques to enhance the system’s generalization capability across varying lighting conditions,viewing angles,and object scales.The proposed method is evaluated in a complex industrial detection scenario involving the bogie of an electric multiple unit(EMU).A dataset consisting of complex backgrounds,diverse lighting conditions,and multiple viewing angles is constructed to validate the performance of the detection system in real industrial environments.Experimental results show that the proposed model achieves an average area under the receiver operating characteristic curve(AUROC)of 0.92 and an average F1 score of 0.85.Combined with data augmentation,the proposed model exhibits improvements in AUROC by 0.06 and F1 score by 0.03,demonstrating enhanced accuracy and robustness for foreign object detection in complex industrial settings.In addition,the effects of key factors on detection performance are systematically analyzed,providing practical guidance for parameter selection in real industrial applications.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2023-00235509Development of security monitoring technology based network behavior against encrypted cyber threats in ICT convergence environment).
文摘With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.
基金supported by the Key Talent Project of Gansu Province(2025RCXM017)the National Natural Science Foundation of China(52261040)+2 种基金the Postgraduate Innovation Star Program of Gansu Province(2025CXZX-476)the Major Science and Technology Project of Gansu Province(22ZD6GA008)the Innovation Driven Assistance Engineering Project of Gansu Association for Science and Technology(GXH20250325-5).
文摘Prussian blue analogs(PBAs)are considered one of the excellent cathode materials for sodium-ion batteries due to their low cost and high theoretical specific capacity,especially sodium-rich iron-based PBAs(FeHCF)can provide higher energy density.FeHCF has a poor charge/discharge platform stability at high voltages(FeC_(6)moiety),which is mainly affected by its coordination environment.In this research,Cu^(+)(six-coordinated),which is close to the ionic radius of Fe^(2+),was used for substitution,the FeC_(6)vacancies of FeHCF were reduced,and the coordination environment was optimized.The low Cu^(+)-substituted FeHCF(Cu^(+)0.625)has an optimal electrochemical performance at 8.5 mA/g with a reversible specific capacity of 142 mA h/g and FeC_(6)moiety contribution of more than 68 mA h/g,which is superior to that of unmodified and other Cu^(2+)-substituted FeHCFs.In situ tests demonstrate the reversible structural stability of the Cu^(+)0.625,supporting the stability of their high-voltage platform capacity.This Cu^(+)substitution strategy further enriches the approach to optimize the coordination environment of sodium-rich FeHCF.
基金supported by Institute of Information and Communications Technology Planning and Evaluation(IITP)grant funded by the Korean government(MSIT)(No.2019-0-01842,Artificial Intelligence Graduate School Program(GIST))supported by Korea Planning&Evaluation Institute of Industrial Technology(KEIT)grant funded by the Ministry of Trade,Industry&Energy(MOTIE,Republic of Korea)(RS-2025-25448249+1 种基金Automotive Industry Technology Development(R&D)Program)supported by the Regional Innovation System&Education(RISE)programthrough the(Gwangju RISE Center),funded by the Ministry of Education(MOE)and the Gwangju Metropolitan City,Republic of Korea(2025-RISE-05-001).
文摘In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to dangerous situations.Furthermore,autonomous vehicles may operate abnormally in bad weather due to limitations of their sensors and GPS.Driving simulators,which replicate driving conditions nearly identical to those in the real world,can drastically reduce the time and cost required for market entry validation;consequently,they have become widely used.In this paper,we design a virtual driving test environment capable of collecting and verifying SiLS data under adverse weather conditions using multi-source images.The proposed method generates a virtual testing environment that incorporates various events,including weather,time of day,and moving objects,that cannot be easily verified in real-world autonomous driving tests.By setting up scenario-based virtual environment events,multi-source image analysis and verification using real-world DCUs(Data Concentrator Units)with V2X-Car edge cloud can effectively address risk factors that may arise in real-world situations.We tested and validated the proposed method with scenarios employing V2X communication and multi-source image analysis.
基金supported by the National Natural Science Foundation of China(No.22202152)Tianjin Municipal Science and Technology Bureau(No.24JCQNJC00990)Cangzhou Institute of Tiangong University(No.TGCYY-F-0304).
文摘Oxygen vacancy(Vo)engineering has been recognized as one of the most effective strategies for enhancing the photocatalytic CO_(2) conversion performance of metal oxides,as it can simultaneously facilitate photogenerated charge carrier separation efficiency and provide additional surface reaction sites.However,the wide application of Vo engineering in photocatalysis are limited by its poor stability,owing to the easy recovery of these vacancy defects by atmospheric oxygen.Herein,we develop an indium(In)doping strategy to regulate the coordination environment in CeO_(2) with abundant Vo(CeO_(2-x)),thereby enhance its stability during photocatalytic CO_(2) conversion.Confirmed by positron annihilation lifetime spectroscopy(PALS),In dopants combine with Vo by substituting for part of Ce^(4+),forming In^(3+)-Vo complexes that effectively inhibit the formation of unstable va-cancy clusters.Such In^(3+)-Vo complexes can also reduce the energy required for formation of the CO products.Therefore,the optimized In-doped CeO_(2-x) exhibits excellent photocatalytic CO_(2) conversion performance,with a CO yield of 301.6μmol⋅g^(-1) after 5 h of light irradiation,and maintain high activity after four cycles of experiments.Comprehensive experimental and theoretical studies indicate that the introduction of In doping not only significantly improves the stability of Vo in CeO_(2-x),but also reconstruct the reaction kinetics of the CO_(2) conversion by forming In^(3+)-Vo complexes thus facilitating the overall reaction.
基金supported by Kyonggi University Research Grant 2025.
文摘As large,room-scale environments become increasingly common,their spatial complexity increases due to variable,unstructured elements.Consequently,demand for room-scale service robots is surging,yet most technologies remain corridor-centric,and autonomous navigation in expansive rooms becomes unstable even around static obstacles.Existing approaches face several structural limitations.These include the labor-intensive requirement for large-scale object annotation and continual retraining,as well as the vulnerability of vanishing point or linebased methods when geometric cues are insufficient.In addition,the high cost of LiDAR and 3D perception errors caused by limited wall cues and dense interior clutter further limit their effectiveness.To address these challenges,we propose a zero-shot vision-based algorithm for robust 3D map reconstruction in geometry-deficient room-scale environments.The algorithm operates in three layers:Layer 1 performs dimension-wise boundary detection;Layer 2 estimates vanishing points,refines the precise perspective space,and extracts a floor mask;and Layer 3 conducts 3D spatial mapping and obstacle recognition.The proposed method was experimentally validated across various geometric-deficient room-scale environments,including lobbies,seminar rooms,conference rooms,cafeterias,and museums—demonstrating its ability to reliably reconstruct 3D maps and accurately recognize obstacles.Experimental results show that the proposed algorithm achieved an F1 score of 0.959 in precision perspective space detection and 0.965 in floor mask extraction.For obstacle recognition and classification,it obtained F1 scores of 0.980 in obstacle absent areas,0.913 in solid obstacle environments,and 0.939 in skeleton-type sparse obstacle environments,confirming its high precision and reliability in geometric-deficient room-scale environments.
基金support by National Natural Science Foundation of China(Grant No.52401103)Key Scientific Research Project in Shanxi Province(Grant No.202302050201015)+3 种基金Central Guiding Science and Technology Development of Local Fund(Grant No.YDZJSK20231A046)the Special Fund for Science and Technology Innovation Teams of Shanxi Province(202204051001004)Science and Technology Cooperation and Exchange Special Project of Shanxi Province(202404041101038)Postgraduate Education Innovation Project of Shanxi Province(Grant No.2024SJ304).
文摘The atmospheric corrosion behavior of 510L low alloy steel subjected to acid-cleaned surface(ACS)and eco-pickled surface(EPS)treatments is systematically examined.After 1 year of atmospheric exposure,both ACS-and EPS-treated samples demonstrate protective ability index values exceeding 2,indicating robust protective properties of the developed rust layers.The corrosion rates of ACS-and EPS-treated samples are similar.During the initial corrosion stage,γ-FeOOH emerges as the dominant corrosion product.With the prolonged atmospheric exposure,γ-FeOOH content progressively decreases through phase transformation into thermodynamically stableα-FeOOH and densely structured Fe_(3)O_(4),which markedly suppresses the corrosion of the steel.Notably,the corrosion rate of the coated EPS sample is obviously lower than that of the coated ACS counterpart,which is ascribed to the distinctive micro-roughness of EPS-treated surfaces that promote mechanical interlocking with protective coatings.
基金National Social Science Fund of China(18KXS009)the Sichuan Provincial Soft Science Program(22JDR0261)the Sichuan University“From 0 to 1”Innovation Research Program(2021CXC10)。
文摘In the context of the revolution in new technologies,a key question is whether the rapid growth of the digital economy,driven by digital technologies,has improved regional innovation performance.Using inter-provincial panel data from China(2012–2022)and adopting a business environment perspective,this study applies a Panel Extended Regression Model(PERM),a Panel Simultaneous Equation Model(PSEM),and a Tobit-IV model to analyze how the development of the digital economy influences regional innovation.The results reveal a pronounced U-shaped relationship between the digital economy and the regional innovation performance at the provincial level in China,with the business environment serving as a significant mediator in this relationship.Moreover,regional innovation performance in China exhibits a“ratchet effect,”with the impact of the digital economy varying markedly across regions.While the eastern and western regions have entered an upward phase,whereby the digital economy boosts innovation,the central region displays a weaker effect.Further analysis indicates that the synergy between the business environment and the digital economy in driving innovation remains suboptimal.These findings were supported by robust checks.This study offers theoretical insights and empirical evidence that support the coordinated development of digital government and the digital factor market,as well as business environment reforms that are in alignment with the innovation demands of the digital era.
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financially supported by the National Natural Science Foundation of China(22138004)National Treasure Ecological Research Synergetic Innovation Center.
文摘Environment serves as the pivotal medium to produce fermented food,with fluctuations in environmental factors exerting a profound impact on the modulation of fermentation microbial communities.Such shifts are crucial for the distinctiveness of fermented food flavor and the variability in quality.Chinese liquor(Baijiu)is one of the typical representatives of spontaneous fermented food.In this review,the multifaceted relationship between regional environmental attributes and the fermentation dynamics of Baijiu was examined,with a spotlight on the strong-flavor,sauce-flavor,and light-flavor varieties.It reveals the influence of regional environmental factors and brewing environmental factors on microbial function and metabolism,which results in the formation of unique flavor characteristics of Baijiu.The 9 main factors affecting the microecology of Baijiu fermentation were further explored,including environmental sensitivity,microbial interactions,biogeographic patterns,and key abiotic factors such as temperature and humidity.Environmental factor management is crucial for controlling microbial community in fermentation.Intelligent detection of the fermentation system is combined with artificial intelligence to realize the digitalization of Baijiu fermentation,with a view to further studying the environmental mechanism or quantitative control relationship of natural fermentation,improving the environmental stability of natural fermentation,and promoting the mechanization and intelligence of fermentation production.
文摘The surge in environmental pollution in recent years driven by numerous pollutants has necessitated the search for efficient removal methods.Phytoremediation is an eco-friendly technique that provides multiple benefits over conventional methods of removing contaminants.Despite the numerous benefits of this technique,it has certain limitations that can be addressed by incorporating nanoparticles to improve its effectiveness.This review paper aims to explore the impact of heavy metal pollution on plants and human health.It highlights the role and mechanism of nanoparticles in enhancing phytoremediation,their application in the detection of heavy metals,and the strategies for the safe disposal of phytoremediation biomass.Biosynthesized nanoparticles are eco-friendly and non-toxic,with applications in biomedical and environmental fields.Nanoparticles can be used in the form of nano biosensors like smartphone-operated wireless sensors made from Cinnamomum camphora,enabling efficient detection of heavy metal ions.According to the studies,nanoparticles remove 80%–97%of heavy metals by various methods like reduction,precipitation,adsorption,etc.The phytoremediation biomass disposal can be done by heat treatment,phytomining,and microbial treatment with some modifications to further enhance their results.Phytoremediation is an environmentally friendly technique but requires further research and integration with biomass energy production to overcome scalability challenges and ensure safe biomass disposal.
基金supported by the National Science and Technology Major Project of China(No.2017-VI-0020-0093).
文摘The high-temperature interaction of nanostructured Lu_(2)Si_(2)O_(7) environmental barrier coatings(EBCs)with calcium-magnesium-aluminosilicate(CMAS)was investigated at 1400℃ for 1,10,25,and 50 h to evaluate the coating’s resistance to CMAS corrosion.The results indicate a phase transformation over time,transitioning from Ca_(2)Lu_(8)(SiO_(4))6O_(2) apatite and Lu_(2)Si_(2)O_(7) to solely Lu_(2)Si_(2)O_(7).The interaction of the Lu_(2)Si_(2)O_(7) coating with the CMAS melts was divided into three stages based on the corrosion reaction behavior.The delamination cracks were distributed throughout the interface between the Si bond layer and Lu_(2)Si_(2)O_(7) layer after corroded at 1400℃ for 50 h,signifying coating failure.In addition,the influence of monosilicates,disilicates,and corrosion duration on the recession layer thickness was analyzed by comparing previous reports on RE_(2)SiO_(5)/RE_(2)Si_(2)O_(7) coatings(RE=Gd,Yb,Lu,Er).Furthermore,the variation in the thermally grown oxide layer thickness in CMAS-corroded Lu_(2)Si_(2)O_(7) coatings was systematically investigated.
基金funded by the National Natural Science Foundation of China under Grant 62306128the Leading Innovation Project of Changzhou Science and Technology Bureau underGrant CQ20230072+2 种基金the Basic Science Research Project of Jiangsu Provincial Department of Education under Grant 23KJD520003the Science and Technology Development Plan Project of Jilin Provinceunder Grant 20240101382JCthe National KeyR esearch and Development Program of China under Grant 2023YFF1105102.
文摘In fire rescue scenarios,traditional manual operations are highly dangerous,as dense smoke,low visibility,extreme heat,and toxic gases not only hinder rescue efficiency but also endanger firefighters’safety.Although intelligent rescue robots can enter hazardous environments in place of humans,smoke poses major challenges for human detection algorithms.These challenges include the attenuation of visible and infrared signals,complex thermal fields,and interference frombackground objects,all ofwhichmake it difficult to accurately identify trapped individuals.To address this problem,we propose VIF-YOLO,a visible–infrared fusion model for real-time human detection in dense smoke environments.The framework introduces a lightweight multimodal fusion(LMF)module based on learnable low-rank representation blocks to end-to-end integrate visible and infrared images,preserving fine details while enhancing salient features.In addition,an efficient multiscale attention(EMA)mechanism is incorporated into the YOLOv10n backbone to improve feature representation under low-light conditions.Extensive experiments on our newly constructedmultimodal smoke human detection(MSHD)dataset demonstrate thatVIF-YOLOachievesmAP50 of 99.5%,precision of 99.2%,and recall of 99.3%,outperforming YOLOv10n by a clear margin.Furthermore,when deployed on the NVIDIA Jetson Xavier NX,VIF-YOLO attains 40.6 FPS with an average inference latency of 24.6 ms,validating its real-time capability on edge-computing platforms.These results confirm that VIF-YOLO provides accurate,robust,and fast detection across complex backgrounds and diverse smoke conditions,ensuring reliable and rapid localization of individuals in need of rescue.
基金the Natural Science Basic Research Program of Shaanxi Province,China[2023-JC-QN-0858]the Free Exploration Program of the Second Affiliated Hospital,School of Medicine,Xi’an Jiaotong University[2020YJ(ZYTS)605]the National Natural Science Foundation of China[81900620].
文摘Global environmental changes including climate warming,extreme weather events,ambient air pollution,freshwater contamination,and landscape transformation are reshaping the epidemiology of infectious diseases with unprecedented complexity,particularly in the post-COVID-19 era.This review synthesizes evidence from the past decade(2015-2024)to systematically elucidate how key environmental drivers modulate pathogen emergence,transmission dynamics,and clinical outcomes,with a focus on underlying mechanistic pathways.Specifically,we highlight:(1)the temperature-and precipitation-dependent transmission of vector-borne diseases(e.g.,malaria,dengue)via expanded vector habitats and accelerated pathogen incubation;(2)the exacerbation of respiratory infections(including COVID-19)by particulate matter(PM2.5)and nitrogen dioxide(NO2)through impaired mucosal immunity and enhanced inflammatory responses;(3)the persistence of diarrheal diseases in low-and middle-income countries(LMICs)linked to water insecurity and climate-induced infrastructure failure;and(4)zoonotic spillover risks amplified by urbanization and deforestation-driven human-wildlife interface disruption.Integrating the One Health socioecological framework,we further summarize methodological advances from high-resolution genomic surveillance to climate-informed machine learning models that have improved causal inference and predictive accuracy.Our synthesis confirms that environmental factors are not merely contextual but central,modifiable determinants of infectious disease risk,with disproportionate impacts on vulnerable populations.To mitigate future threats,we emphasize the urgency of interdisciplinary collaboration,integrated environmental-health monitoring platforms,and climate-resilient public health policies tailored to post-pandemic challenges.This review provides a timely roadmap for translating environmental epidemiology insights into actionable strategies to strengthen global health resilience.
基金supported by Natural Science Foundation of Xiamen,China(No.3502Z20227232)the STS Project of Fujian-CAS(No.2023T3018)Bureau of International Cooperation,Chinese Academy of Sciences(No.322GJHZ2022035MI).
文摘Anammox bacteria in constructed wetlands(CWs)play pivotal role in sustainable nitrogen transformation,yet existing studies lack comprehensive analysis of environmental gradients and microbial interactions,both key factors in anammox bacteria enrichment.This study investigated the mechanisms driving anammox bacteria enrichment in lab-scale simulated CWs treating high-nitrogen wastewater,focusing on bacterial community re-sponses across wetland layers with various strategies,including continuous up-flow influent,nitrogen loading increase,effluent recirculation,intermittent influent,and anammox bacteria inoculation.Results showed that total relative and absolute abundances of anammox bacteria ranged from 0.77%to 12.50%and from 0.13 to 6.46×10^(7) copies/g,respectively.Dissolved oxygen and pH had significant positive correlations with the absolute abundance of anammox bacteria,while organic matter and nitrate negatively impacted their relative abundance.Permutational multivariate analysis of variance indicated that spatial heterogeneity explained more variation in anammox bacteria abundance(43.44%)compared to operational strategies(8.58%).In terms of microbial interactions,60 dominant species exhibited potential correlations with anammox bacteria,comprising 170 interactions(105 positive and 65 negative),which suggested that anammox bacteria generally foster cooperative relationships with dominant bacteria.Notably,significant interspecies interactions were observed between Candidatus Kuenenia(dominant anammox bacteria in CWs)and species within the genera Chitinivibrio-nia and Anaerolineaceae,suggesting that microbial interactions primarily manifest as indirect facilitative effects rather than direct mutualistic relationships.Given that the Normalized Stochasticity Ratio in CWs were<50%,this study inferred that environmental gradients have greater influence on anammox bacteria than microbial interactions.
基金supported by European Commission and is a part of the HORIZON2020 project RES Heatfunding from the European Union’s Horizon 2020 program in the field of research and innovation on the basis of grant agreement No.956255.
文摘Decarbonising the building sector,particularly residential heating,represents a critical challenge for achieving carbon-neutral energy systems.Efficient solutions must integrate both technological performance and renewable energy sources while considering operational constraints of existing systems.This study investigates a hybrid heating system combining a natural gas boiler(NGB)with an air-to-water heat pump(AWHP),evaluated through a combination of laboratory experiments and dynamic modelling.A prototype developed in the Electrical and Energy Engineering Laboratory enabled the characterization of both heat generators,the collection of experimental data,and the calibration of a MATLAB/Simulink model,including emissions and exhaust analyses.Sensitivity analyses were performed to identify optimal configurations for energy efficiency and system control,accounting for interactions between subsystems.Results highlight that hybridisation significantly improves primary energy efficiency and reduces fuel consumption compared to conventional NGB-only systems.Environmental performance,assessed through CO_(2) and NOx emissions and renewable energy integration,demonstrates the benefits of partial electrification in the residential sector.Economic assessment further quantifies decarbonization costs and fuel savings,illustrating tradeoffs between low-capital,moderate-performance systems and high-efficiency,high-renewable solutions requiring larger investments.The analysis shows that strategic decisions for residential decarbonisation cannot be separated from system-wide considerations,including control strategies,component integration,and economic feasibility.The study underlines the importance of hybrid and renewable-based solutions as pivotal pathways for energy transition in the residential building sector.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFF1303405).
文摘Compared with traditional energy sources,wind power has a lower environmental impact.However,emissions are still generated across the life cycle of wind turbines,from production to recycling.As wind power rapidly develops and deployment increases,these impacts are becoming increasingly evident.A comprehensive understanding of these impacts is crucial for sustainable development.Based on the harmonization of previous detailed life cycle assessment(LCA)studies,this study develops a simplified LCA model that estimates the life cycle environmental impacts of wind turbines based on their nominal power.Using this simplified LCA model,we assess the global warming potential(GWP),acidification potential(AP),and cumulative energy demand(CED)of wind power at the regional scale for 2022 and under three future scenarios(high-power wind turbine promotion,reduced wind curtailment,and a comprehensive development scenario).The results indicate that in 2022,the life cycle GWP,AP,and CED of wind power in western China were 10.76 g CO_(2) eq/kWh,0.177 g SO_(2) eq/kWh,and 17.6 kJ/kWh,respectively.Scenario simulations suggest that reducing wind curtailment is the most effective approach for reducing emissions in Inner Mongolia,Gansu,Qinghai,Ningxia,and Xinjiang,producing average decreases of 8.64%in GWP,8.39%in AP,and 9.26%in CED.In contrast,for Guangxi,Chongqing,Sichuan,Guizhou,Yunnan,Xizang,and Shaanxi,the promotion of high-power wind turbines provides greater environmental benefits than reducing curtailment,producing average decreases of 3.45%,3.09%,and 4.29%in GWP,AP,and CED,respectively.These findings help clarify the environmental impact of wind power across its life cycle at the regional scale and provide theoretical references for the direction of future wind power development and the formulation of related policies.
基金supported by the Major Planning Project of Philosophy and Social Science of Guangdong Province(GD23ZD17)the Humanities and Social Sciences Program of the Ministry of Education(23YJA190006)+3 种基金the Ministry of Education(MOE)Major Project of Philosophy and Social Sciences Research(2025JZDZ024)the MOE Project of the Key Research Institute of Humanities and Social Sciences in Universities(22JJD190008)a grant from the Research Center for Brain Cognition and Human Development of Guangdong(2024B0303390003)the Psychological Services and Counseling Base for the Happy Guangzhou Project.
文摘Background:Exposure to environmental vulnerability poses significant threats to adolescent suicidal ideation,while individual resilience can mitigate these adverse effects with notable gender commonalities and differences.However,research examining how these factors co-configure at the individual level remains limited,particularly from a gender-specific perspective.Thus,the present study aims to adopt a person-centered analytic approach to identify gender-specific configurations of environmental vulnerability and individual resilience associated with suicidal ideation among Chinese adolescents.Methods:Data were collected from 2616 Chinese primary and secondary school students(aged 10–17;1223 girls).Participants completed validated scales measuring environmental vulnerability,individual resilience,and suicidal ideation.Latent profile analysis(LPA)was conducted separately by gender.Results:Gender differences were prominent:males exhibited higher resilience and lower suicidal ideation,while females reported higher environmental vulnerability and elevated levels of suicidal ideation.LPA identified three distinct profiles for males:Low Vulnerable–High Protective–Low Risk(LHL),Medium Vulnerable–Low Protective–Low Risk(MLL),and High Vulnerable–Low Protective–High Risk(HLH).Four profiles emerged for females:LHL,MLL,Medium Vulnerable–Low Protective–Medium Risk(MLM),and HLH.Crucially,within the HLH profile,males exhibited particularly deficient humor(η^(2)=0.19)and confidence(η^(2)=0.16),while females formed a distinct subgroup characterized by severe academic and family stressors(η^(2)=0.30–0.36).Conclusion:The study underscores developing gender-specific mental health interventions using a nuanced,person-centered approach that considers both environmental risk and individual resilience factors,which allows for targeted suicide prevention strategies addressing the unique needs of male and female adolescents.
