Arid and semi-arid ecosystems are prone to extensive fires due to specific climatic conditions,sparse vegetation cover,and high density of fine fuels.Understanding the flammability characteristics of land covers is es...Arid and semi-arid ecosystems are prone to extensive fires due to specific climatic conditions,sparse vegetation cover,and high density of fine fuels.Understanding the flammability characteristics of land covers is essential for fire management and designing land restoration programs in arid and semi-arid ecosystems.This study provided a new approach to evaluate the flammability of shrublands and woodlands using flammability indices(FIs)including time to ignition(TI),duration of combustion(DC),and flame height(FH)of plant species and their relative frequencies in the Dalfard Basin of southeastern Iran.The results showed that there was a significant difference in FIs between land covers.Shrublands had higher flammability potential compared with woodlands.Plant moisture content had a negative relationship with TI(P<0.010)and no significant relationship with DC and FH(P>0.050).Artemisia spp.,Astragalus gossypinus Fischer,Amygdalus scoparia Spach,and Cymbopogon jwarancusa(Jones)Schult.had the highest FI.Tree species such as Rhazya stricta Decne.,and Pistacia atlantica Desf.showed greater resistance to fire.Using principal component analysis,the relationship between species and FIs was examined,and TI of wet fuel was the most important FI in relation to species.Structural equation model showed that life form(P<0.001)was the most important flammability driver.Precipitation(P<0.010)and legume species(P<0.010)were significantly related to the flammability in arid land.This study emphasizes the importance of managing high-risk species and using resistant species in vegetation restoration and shows that combining species FIs with their abundance is an effective tool for assessing fire risk and fuel management at the plant community scale.展开更多
Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2)...Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.展开更多
To address the challenge of balancing thermal management and thermal runaway mitigation,it is crucial to explore effective methods for enhancing the safety of lithium-ion battery systems.Herein,an innovative hydrated ...To address the challenge of balancing thermal management and thermal runaway mitigation,it is crucial to explore effective methods for enhancing the safety of lithium-ion battery systems.Herein,an innovative hydrated salt composite phase change material(HSCPCM)with dual phase transition temperature zones has been proposed.This HSCPCM,denoted as SDMA10,combines hydrophilic modified expanded graphite,an acrylic emulsion coating,and eutectic hydrated salts to achieve leakage prevention,enhanced thermal stability,cycling stability,and superior phase change behavior.Battery modules incorporating SDMA10 demonstrate significant thermal control capabilities.Specifically,the cylindrical battery modules with SDMA10 can maintain maximum operating temperatures below 55°C at 4 C discharge rate,while prismatic battery modules can keep maximum operating temperatures below 65°C at 2 C discharge rate.In extreme battery overheating conditions simulated using heating plates,SDMA10 effectively suppresses thermal propagation.Even when the central heating plate reaches 300°C,the maximum temperature at the module edge heating plates remains below 85°C.Further,compared to organic composite phase change materials(CPCMs),the battery module with SDMA10 can further reduce the peak thermal runaway temperature by 93°C and delay the thermal runaway trigger time by 689 s,thereby significantly decreasing heat diffusion.Therefore,the designed HSCPCM integrates excellent latent heat storage and thermochemical storage capabilities,providing high thermal energy storage density within the thermal management and thermal runaway threshold temperature range.This research will offer a promising pathway for improving the thermal safety performance of battery packs in electric vehicles and other energy storage systems.展开更多
Sustainable water,energy and food(WEF)supplies are the bedrock upon which human society depends.Solar-driven interfacial evaporation,combined with electricity generation and cultivation,is a promising approach to miti...Sustainable water,energy and food(WEF)supplies are the bedrock upon which human society depends.Solar-driven interfacial evaporation,combined with electricity generation and cultivation,is a promising approach to mitigate the freshwater,energy and food crises.However,the performance of solar-driven systems decreases significantly during operation due to uncontrollable weather.This study proposes an integrated water/electricity cogeneration-cultivation system with superior thermal management.The energy storage evaporator,consisting of energy storage microcapsules/hydrogel composites,is optimally designed for sustainable desalination,achieving an evaporation rate of around 1.91 kg m^(-2)h^(-1).In the dark,heat released from the phase-change layer supported an evaporation rate of around 0.54kg m^(-2)h^(-1).Reverse electrodialysis harnessed the salinity-gradient energy enhanced during desalination,enabling the long-running WEC system to achieve a power output of~0.3 W m^(-2),which was almost three times higher than that of conventional seawater/surface water mixing.Additionally,an integrated crop irrigation platform utilized system drainage for real-time,on-demand wheat cultivation without secondary contaminants,facilitating seamless WEF integration.This work presents a novel approach to all-day solar water production,electricity generation and crop irrigation,offering a solution and blueprint for the sustainable development of WEF.展开更多
Within the domain of Intelligent Group Systems(IGSs),this paper develops a resourceaware multitarget Constant False Alarm Rate(CFAR)detection framework for multisite MIMO radar systems.It underscores the necessity of ...Within the domain of Intelligent Group Systems(IGSs),this paper develops a resourceaware multitarget Constant False Alarm Rate(CFAR)detection framework for multisite MIMO radar systems.It underscores the necessity of managing finite transmit and receive antennas and transmit power systematically to enhance detection performance.To tackle the multidimensional resource optimization challenge,we introduce a Cooperative Transmit-Receive Antenna Selection and Power Allocation(CTRSPA)strategy.It employs a perception-action cycle that incorporates uncertain external support information to optimize worst-case detection performance with multiple targets.First,we derive a closed-form expression that incorporates uncertainty for the noncoherent integration squared-law detection probability using the Neyman-Pearson criterion.Subsequently,a joint optimization model for antenna selection and power allocation in CFAR detection is formulated,incorporating practical radar resource constraints.Mathematically,this represents an NPhard problem involving coupled continuous and Boolean variables.We propose a three-stage method—Reformulation,Node Picker,and Convex Power Allocation—that capitalizes on the independent convexity of the optimization model for each variable,ensuring a near-optimal result.Simulations confirm the approach's effectiveness,efficiency,and timeliness,particularly for large-scale radar networks,and reveal the impact of threat levels,system layout,and detection parameters on resource allocation.展开更多
The United Nations Sustainable Development Goal(SDG) 2 aims to achieve Zero Hunger by 2030.However,global hunger and food insecurity have continued to rise at an alarming rate(UN 2023).Subtropical regions are home to ...The United Nations Sustainable Development Goal(SDG) 2 aims to achieve Zero Hunger by 2030.However,global hunger and food insecurity have continued to rise at an alarming rate(UN 2023).Subtropical regions are home to more than 30% of the world's population,predominantly in developing countries where per capita farmland and food supply are only 40% of those in developed nations(FAO 2018).Meeting the Zero Hunger target amid ongoing population growth in these regions requires a substantial increase in agricultural production while minimizing soil degradation and adverse ecological impacts.This challenge is shared by many countries across South Asia,Africa,and Central and South America.展开更多
High-concentration photovoltaic(HCPV)systems present significant thermal management challenges due to the intense heat fluxes generated under concentrated solar irradiation,especially in arid environments.Effective he...High-concentration photovoltaic(HCPV)systems present significant thermal management challenges due to the intense heat fluxes generated under concentrated solar irradiation,especially in arid environments.Effective heat dissipation is critical to prevent performance degradation and structural failure.This study investigates the thermal performance and design optimization of an enhanced HCPV module,integrating numerical,analytical,and experimental methods.A coupled optical-thermal-electrical model was developed to simulate ray tracing,heat transfer,and temperature-dependent electrical behaviour,with predictions validated under real-world desert conditions.Compared to a baseline commercial module operating at 106℃,the optimized design achieved a peak temperature reduction of 16℃,lowering the cell temperature to 90℃under a concentration ratio of 961×and direct normal irradiance(DNI)of 950 W/m^(2).The total thermal resistance was reduced from 0.25 to 0.15 K/W(a 40%improvement),and the electrical efficiency increased from 37.5%to 38.6%,representing a relative gain of approximately 3.1%.The system consistently maintained a fill factor exceeding 78%,underscoring stable performance under high thermal load.These findings demonstrate that targeted thermal design,informed by integrated modeling,is essential for unlocking the reliability and efficiency of high-flux solar energy systems.展开更多
Neuromodulation for diabetic peripheral neuropathy represents a significant area of interest in the management of chronic pain associated with this condition.Diabetic peripheral neuropathy,a common complication of dia...Neuromodulation for diabetic peripheral neuropathy represents a significant area of interest in the management of chronic pain associated with this condition.Diabetic peripheral neuropathy,a common complication of diabetes,is characterized by nerve damage due to high blood sugar levels that lead to symptoms,such as pain,tingling,and numbness,primarily in the hands and feet.The aim of this systematic review was to evaluate the efficacy of neuromodulatory techniques as potential therapeutic interventions for patients with diabetic peripheral neuropathy,while also examining recent developments in this domain.The investigation encompassed an array of neuromodulation methods,including frequency rhythmic electrical modulated systems,dorsal root ganglion stimulation,and spinal cord stimulation.This systematic review suggests that neuromodulatory techniques may be useful in the treatment of diabetic peripheral neuropathy.Understanding the advantages of these treatments will enable physicians and other healthcare providers to offer additional options for patients with symptoms refractory to standard pharmacologic treatments.Through these efforts,we may improve quality of life and increase functional capacity in patients suffering from complications related to diabetic neuropathy.展开更多
To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the ...To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the effectiveness of flexibility management strategies under different climate conditions and extreme weather events.Using both typical and extreme weather data from cities in five major climate zones of China,this study investigates the energy flexibility potential of an office building under three short-term HVAC management strategies in the context of different climates.The results show that the peak load flexibility and overall energy performance of the three short-term strategies were affected by the surrounding climate conditions.The peak load reduction rate of the pre-cooling and zone temperature reset strategies declined linearly as outdoor temperature increased.Under extreme climate conditions,the daily peak-load time was found to be over two hours earlier than under typical conditions,and the intensive solar radiation found in the extreme conditions can weaken the correlation between peak load reduction and outdoor temperature,risking the ability of a building’s HVAC system to maintain a comfortable indoor environment.展开更多
Both straw incorporation and irrigation practices affect biological nitrogen(N)fixation(BNF),but it is still unclear how straw incorporation impacts BNF under continuous(CFI)or intermittent(IFI)flooding irrigation in ...Both straw incorporation and irrigation practices affect biological nitrogen(N)fixation(BNF),but it is still unclear how straw incorporation impacts BNF under continuous(CFI)or intermittent(IFI)flooding irrigation in a rice cropping system.A15N2-labeling chamber system was placed in a rice field to evaluate BNF with straw incorporation under CFI or IFI for 90 d.The nif H(gene encoding the nitrogenase reductase subunit)DNA and c DNA in soil were amplified using real-time quantitative polymerase chain reaction,and high-throughput sequencing was applied to the nif H gene.The total fixed N in the straw incorporation treatment was 14.3 kg ha^(-1)under CFI,being 116%higher than that under IFI(6.62 kg ha^(-1)).Straw incorporation and CFI showed significant interactive effects on the total fixed N and abundances of nif H DNA and c DNA.The increase in BNF was mainly due to the increase in the abundances of heterotrophic diazotrophs such as Desulfovibrio,Azonexus,and Azotobacter.These results indicated that straw incorporation stimulated BNF under CFI relative to IFI,which might ultimately lead to a rapid enhancement of soil fertility.展开更多
With the anticipated growth in air traffic complexity in the coming years,future civil aviation transportation system(CATS)is transforming into a complex cyber–physical–social system,surpassing all previous experien...With the anticipated growth in air traffic complexity in the coming years,future civil aviation transportation system(CATS)is transforming into a complex cyber–physical–social system,surpassing all previous experiences in the history of civil aviation safety management.Therefore,a new safety concept based on a system-of-systems(SoS)perspective is proposed for the next-generation aviation.This article begins by elucidating the complexity of existing aviation risks and emphasizing the necessity for an updated safety concept.It then presents the challenges of current safety management and potential solutions from the new SoS perspective.To address future risks,the concept of SoS safety is introduced with the inspiration of the human immune system in terms of capability,logic,and architecture,which can serve as a guiding framework and methodology for safety engineering in complex large-scale CATS.This concept indicates the transition from“process and outcome-oriented”to“capability-oriented”intelligent safety management.Our research highlights the development directions and potential technological areas that need to be addressed at different stages of SoS safety.The integration of SoS design and operation through rapid iterations enabled by artificial intelligence(AI)will ultimately achieve endogenous SoS safety.展开更多
All-season thermal management with zero energy consumption and emissions is more crucial to global decarbonization over traditional energy-intensive cooling/heating systems.However,the static single thermal management...All-season thermal management with zero energy consumption and emissions is more crucial to global decarbonization over traditional energy-intensive cooling/heating systems.However,the static single thermal management for cooling or heating fails to self-regulate the temperature in dynamic seasonal temperature condition.Herein,inspired by the dual-temperature regulation function of the fur color changes on the backs and abdomens of penguins,a smart thermal management composite hydrogel(PNA@H-PM Gel)system was subtly created though an"on-demand"dual-layer structure design strategy.The PNA@H-PM Gel system features synchronous solar and thermal radiation modulation as well as tunable phase transition temperatures to meet the variable seasonal thermal requirements and energy-saving demands via self-adaptive radiative cooling and solar heating regulation.Furthermore,this system demonstrates superb modulations of both the solar reflectance(ΔR=0.74)and thermal emissivity(ΔE=0.52)in response to ambient temperature changes,highlighting efficient temperature regulation with average radiative cooling and solar heating effects of 9.6℃in summer and 6.1℃in winter,respectively.Moreover,compared to standard building baselines,the PNA@H-PM Gel presents a more substantial energy-saving cooling/heating potentials for energy-efficient buildings across various regions and climates.This novel solution,inspired by penguins in the real world,will offer a fresh approach for producing intelligent,energy-saving thermal management materials,and serve for temperature regulation under dynamic climate conditions and even throughout all seasons.展开更多
Distributed Federated Learning(DFL)technology enables participants to cooperatively train a shared model while preserving the privacy of their local datasets,making it a desirable solution for decentralized and privac...Distributed Federated Learning(DFL)technology enables participants to cooperatively train a shared model while preserving the privacy of their local datasets,making it a desirable solution for decentralized and privacy-preserving Web3 scenarios.However,DFL faces incentive and security challenges in the decentralized framework.To address these issues,this paper presents a Hierarchical Blockchain-enabled DFL(HBDFL)system,which provides a generic solution framework for the DFL-related applications.The proposed system consists of four major components,including a model contribution-based reward mechanism,a Proof of Elapsed Time and Accuracy(PoETA)consensus algorithm,a Distributed Reputation-based Verification Mechanism(DRTM)and an Accuracy-Dependent Throughput Management(ADTM)mechanism.The model contribution-based rewarding mechanism incentivizes network nodes to train models with their local datasets,while the PoETA consensus algorithm optimizes the tradeoff between the shared model accuracy and system throughput.The DRTM improves the system efficiency in consensus,and the ADTM mechanism guarantees that the throughput performance remains within a predefined range while improving the shared model accuracy.The performance of the proposed HBDFL system is evaluated by numerical simulations,with the results showing that the system improves the accuracy of the shared model while maintaining high throughput and ensuring security.展开更多
The complexity of coupled risks,which refer to the compounded effects of interacting uncertainties across multiple interdependent objectives,is inherent to cities functioning as dynamic,interdependent systems.A disrup...The complexity of coupled risks,which refer to the compounded effects of interacting uncertainties across multiple interdependent objectives,is inherent to cities functioning as dynamic,interdependent systems.A disruption in one domain ripples across various urban systems,often with unforeseen consequences.Central to this complexity are people,whose behaviors,needs,and vulnerabilities shape risk evolution and response effectiveness.Realizing cities as complex systems centered on human needs and behaviors is essential to understanding the complexities of coupled urban risks.This paper adopts a complex systems perspective to examine the intricacies of coupled urban risks,emphasizing the critical role of human decisions and behavior in shaping these dynamics.We focus on two key dimensions:cascading hazards in urban environments and cascading failures across interdependent exposed systems in cities.Existing risk assessment models often fail to capture the complexity of these processes,particularly when factoring in human decision-making.To tackle these challenges,we advocate for a standardized taxonomy of cascading hazards,urban components,and their interactions.At its core is a people-centric perspective,emphasizing the bidirectional interactions between people and the systems that serve them.Building on this foundation,we argue the need for an integrated,people-centric risk assessment framework that evaluates event impacts in relation to the hierarchical needs of people and incorporates their preparedness and response capacities.By leveraging real-time data,advanced simulations,and innovative validation methods,this framework aims to enhance the accuracy of coupled urban risk modeling.To effectively manage coupled urban risks,cities can draw from proven strategies in real complex systems.However,given the escalating uncertainties and complexities associated with climate change,prioritizing people-centric strategies is crucial.This approach will empower cities to build resilience not only against known hazards but also against evolving and unforeseen challenges in an increasingly uncertain world.展开更多
Water scarcity poses a significant challenge globally,with South Africa exemplifying the severe socio-economic and environmental impacts of limited water access.Despite advances in modern water management systems,the ...Water scarcity poses a significant challenge globally,with South Africa exemplifying the severe socio-economic and environmental impacts of limited water access.Despite advances in modern water management systems,the integration of indigenous knowledge(IK)into formal frameworks remains underutilized.This study systematically reviews the role of indigenous water conservation practices in South Africa,analyzing over 50 high-quality sources using the PRISMA methodology.The findings highlight the effectiveness of IK in addressing water scarcity through techniques such as rainwater harvesting,terracing,and wetland management,which are low-cost,environmentally sustainable,and deeply rooted in cultural practices.Indigenous methods also enhance climate resilience by enabling communities to adapt to droughts and floods through practices such as weather prediction and adaptive farming techniques.Furthermore,these practices foster social inclusivity and community empowerment,ensuring equitable water access and intergenerational knowledge transfer.The study underscores the potential of integrating IK with modern water technologies to create holistic solutions that are scalable,sustainable,and aligned with South Africa’s goal of achieving water security by 2030.Policy recommendations emphasize the need for institutional support,data collection,and financial incentives to sustain and mainstream indigenous approaches.By bridging the gap between traditional and contemporary systems,this research provides a roadmap for leveraging diverse knowledge systems to address water scarcity and build resilient communities.展开更多
This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode sche...This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode scheme with chopped op-amps and internal clock generators to eliminate op-amp offset.A low dropout regulator(LDO)and a pre-regula-tor enhance output driving and LS,respectively.Curvature compensation enhances the TC by addressing higher-order nonlinear-ity.These approaches,effective near room temperature,employs trimming at both 20 and 60°C.When combined with fixed cur-vature correction currents,it achieves an ultra-low TC for each chip.Implemented in a CMOS 180 nm process,the BGR occu-pies 0.548 mm²and operates at 2.5 V with 84μA current draw from a 5 V supply.An average TC of 2.69 ppm/℃ with two-point trimming and 0.81 ppm/℃ with multi-point trimming are achieved over the temperature range of-40 to 125℃.It accommo-dates a load current of 1 mA and an LS of 42 ppm/V,making it suitable for precise BMS applications.展开更多
There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficien...There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficient.We simulated the spatiotemporal dynamics of ESs(e.g.,carbon storage,water yield,habitat quality,and soil conservation)and ERs in the upper reach of the Yellow River(URYR)from 2000 to 2100.Additionally,we explored their relationships by combining the InVEST model and a landscape ecological risk model with CMIP6 data.Our main findings showed that regional ERs change in response to land use and environmental dynamics.Specifically,the ER area decreased by 27,673 m^(2)during 2000-2020,but it is projected to increase by 13,273,438,and 68 m^(2)under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios,respectively.We also observed remarkable spatial differences in ESs and ERs between past and future scenarios.For instance,the source area of the URYR exhibited high ESs and low ERs(P<0.001),while the ESs and ERs are declining and increasing,respectively,in the northeastern URYR(P<0.05).Finally,we proposed a spatial optimization framework to improve ESs and reduce ERs,which will support regional sustainable development.展开更多
Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers ...Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers and lacks theoretical guidance.This paper proposes a concise graph representation method based on graph theory for fuel thermal management systems,which can represent all possible connections between subsystems.A generalized optimization algorithm is proposed for fuel thermal management system architecture to minimize the heat sink.This algorithm can autonomously arrange subsystems with heat production differences and efficiently utilize the architecture of the fuel heat sink.At the same time,two evaluation indices are proposed from the perspective of subsystems.These indices intuitively and clearly show that the reason for the high efficiency of heat sink utilization is the balanced and moderate cooling of each subsystem and verify the rationality of the architecture optimization method.A set of simulations are also conducted,which demonstrate that the fuel tank temperature has no effect on the performance of the architecture.This paper provides a reference for the architectural design of aircraft fuel thermal management systems.The metrics used in this paper can also be utilized to evaluate the existing architecture.展开更多
Accurate estimation of evapotranspiration(ET)is crucial for efficient water resource management,particularly in the face of climate change and increasing water scarcity.This study performs a bibliometric analysis of 3...Accurate estimation of evapotranspiration(ET)is crucial for efficient water resource management,particularly in the face of climate change and increasing water scarcity.This study performs a bibliometric analysis of 352 articles and a systematic review of 35 peer-reviewed papers,selected according to PRISMA guidelines,to evaluate the performance of Hybrid Artificial Neural Networks(HANNs)in ET estimation.The findings demonstrate that HANNs,particularly those combining Multilayer Perceptrons(MLPs),Recurrent Neural Networks(RNNs),and Convolutional Neural Networks(CNNs),are highly effective in capturing the complex nonlinear relationships and tem-poral dependencies characteristic of hydrological processes.These hybrid models,often integrated with optimization algorithms and fuzzy logic frameworks,significantly improve the predictive accuracy and generalization capabilities of ET estimation.The growing adoption of advanced evaluation metrics,such as Kling-Gupta Efficiency(KGE)and Taylor Diagrams,highlights the increasing demand for more robust performance assessments beyond traditional methods.Despite the promising results,challenges remain,particularly regarding model interpretability,computational efficiency,and data scarcity.Future research should prioritize the integration of interpretability techniques,such as attention mechanisms,Local Interpretable Model-Agnostic Explanations(LIME),and feature importance analysis,to enhance model transparency and foster stakeholder trust.Additionally,improving HANN models’scalability and computational efficiency is crucial,especially for large-scale,real-world applications.Approaches such as transfer learning,parallel processing,and hyperparameter optimization will be essential in overcoming these challenges.This study underscores the transformative potential of HANN models for precise ET estimation,particularly in water-scarce and climate-vulnerable regions.By integrating CNNs for automatic feature extraction and leveraging hybrid architectures,HANNs offer considerable advantages for optimizing water management,particularly agriculture.Addressing challenges related to interpretability and scalability will be vital to ensuring the widespread deployment and operational success of HANNs in global water resource management.展开更多
Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and ...Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.展开更多
文摘Arid and semi-arid ecosystems are prone to extensive fires due to specific climatic conditions,sparse vegetation cover,and high density of fine fuels.Understanding the flammability characteristics of land covers is essential for fire management and designing land restoration programs in arid and semi-arid ecosystems.This study provided a new approach to evaluate the flammability of shrublands and woodlands using flammability indices(FIs)including time to ignition(TI),duration of combustion(DC),and flame height(FH)of plant species and their relative frequencies in the Dalfard Basin of southeastern Iran.The results showed that there was a significant difference in FIs between land covers.Shrublands had higher flammability potential compared with woodlands.Plant moisture content had a negative relationship with TI(P<0.010)and no significant relationship with DC and FH(P>0.050).Artemisia spp.,Astragalus gossypinus Fischer,Amygdalus scoparia Spach,and Cymbopogon jwarancusa(Jones)Schult.had the highest FI.Tree species such as Rhazya stricta Decne.,and Pistacia atlantica Desf.showed greater resistance to fire.Using principal component analysis,the relationship between species and FIs was examined,and TI of wet fuel was the most important FI in relation to species.Structural equation model showed that life form(P<0.001)was the most important flammability driver.Precipitation(P<0.010)and legume species(P<0.010)were significantly related to the flammability in arid land.This study emphasizes the importance of managing high-risk species and using resistant species in vegetation restoration and shows that combining species FIs with their abundance is an effective tool for assessing fire risk and fuel management at the plant community scale.
基金supported by the National Natural Science Foundation of China(22168008,22378085)the Guangxi Natural Science Foundation(2024GXNSFDA010053)+1 种基金the Technology Development Project of Guangxi Bossco Environmental Protection Technology Co.,Ltd(202100039)Innovation Project of Guangxi Graduate Education(YCBZ2024065).
文摘Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.
基金financially supported by Natural Science Foundation of Guangdong province(2024A1515010228)CATARC Automotive Inspection Center Excellent Engineer Program(2023B0909050007).
文摘To address the challenge of balancing thermal management and thermal runaway mitigation,it is crucial to explore effective methods for enhancing the safety of lithium-ion battery systems.Herein,an innovative hydrated salt composite phase change material(HSCPCM)with dual phase transition temperature zones has been proposed.This HSCPCM,denoted as SDMA10,combines hydrophilic modified expanded graphite,an acrylic emulsion coating,and eutectic hydrated salts to achieve leakage prevention,enhanced thermal stability,cycling stability,and superior phase change behavior.Battery modules incorporating SDMA10 demonstrate significant thermal control capabilities.Specifically,the cylindrical battery modules with SDMA10 can maintain maximum operating temperatures below 55°C at 4 C discharge rate,while prismatic battery modules can keep maximum operating temperatures below 65°C at 2 C discharge rate.In extreme battery overheating conditions simulated using heating plates,SDMA10 effectively suppresses thermal propagation.Even when the central heating plate reaches 300°C,the maximum temperature at the module edge heating plates remains below 85°C.Further,compared to organic composite phase change materials(CPCMs),the battery module with SDMA10 can further reduce the peak thermal runaway temperature by 93°C and delay the thermal runaway trigger time by 689 s,thereby significantly decreasing heat diffusion.Therefore,the designed HSCPCM integrates excellent latent heat storage and thermochemical storage capabilities,providing high thermal energy storage density within the thermal management and thermal runaway threshold temperature range.This research will offer a promising pathway for improving the thermal safety performance of battery packs in electric vehicles and other energy storage systems.
基金supported by the National Natural Science Foundation of China(No.52070057)China Postdoctoral Science Foundation(No.2023M730855)Heilongjiang Postdoctoral Fund(No.LBH-Z22183)for financial support。
文摘Sustainable water,energy and food(WEF)supplies are the bedrock upon which human society depends.Solar-driven interfacial evaporation,combined with electricity generation and cultivation,is a promising approach to mitigate the freshwater,energy and food crises.However,the performance of solar-driven systems decreases significantly during operation due to uncontrollable weather.This study proposes an integrated water/electricity cogeneration-cultivation system with superior thermal management.The energy storage evaporator,consisting of energy storage microcapsules/hydrogel composites,is optimally designed for sustainable desalination,achieving an evaporation rate of around 1.91 kg m^(-2)h^(-1).In the dark,heat released from the phase-change layer supported an evaporation rate of around 0.54kg m^(-2)h^(-1).Reverse electrodialysis harnessed the salinity-gradient energy enhanced during desalination,enabling the long-running WEC system to achieve a power output of~0.3 W m^(-2),which was almost three times higher than that of conventional seawater/surface water mixing.Additionally,an integrated crop irrigation platform utilized system drainage for real-time,on-demand wheat cultivation without secondary contaminants,facilitating seamless WEF integration.This work presents a novel approach to all-day solar water production,electricity generation and crop irrigation,offering a solution and blueprint for the sustainable development of WEF.
基金supported by the National Natural Science Foundation of China(Nos.62071482 and 62471348)the Shaanxi Association of Science and Technology Youth Talent Support Program Project,China(No.20230137)+1 种基金the Innovative Talents Cultivate Program for Technology Innovation Team of Shaanxi Province,China(No.2024RS-CXTD-08)the Youth Innovation Team of Shaanxi Universities,China。
文摘Within the domain of Intelligent Group Systems(IGSs),this paper develops a resourceaware multitarget Constant False Alarm Rate(CFAR)detection framework for multisite MIMO radar systems.It underscores the necessity of managing finite transmit and receive antennas and transmit power systematically to enhance detection performance.To tackle the multidimensional resource optimization challenge,we introduce a Cooperative Transmit-Receive Antenna Selection and Power Allocation(CTRSPA)strategy.It employs a perception-action cycle that incorporates uncertain external support information to optimize worst-case detection performance with multiple targets.First,we derive a closed-form expression that incorporates uncertainty for the noncoherent integration squared-law detection probability using the Neyman-Pearson criterion.Subsequently,a joint optimization model for antenna selection and power allocation in CFAR detection is formulated,incorporating practical radar resource constraints.Mathematically,this represents an NPhard problem involving coupled continuous and Boolean variables.We propose a three-stage method—Reformulation,Node Picker,and Convex Power Allocation—that capitalizes on the independent convexity of the optimization model for each variable,ensuring a near-optimal result.Simulations confirm the approach's effectiveness,efficiency,and timeliness,particularly for large-scale radar networks,and reveal the impact of threat levels,system layout,and detection parameters on resource allocation.
文摘The United Nations Sustainable Development Goal(SDG) 2 aims to achieve Zero Hunger by 2030.However,global hunger and food insecurity have continued to rise at an alarming rate(UN 2023).Subtropical regions are home to more than 30% of the world's population,predominantly in developing countries where per capita farmland and food supply are only 40% of those in developed nations(FAO 2018).Meeting the Zero Hunger target amid ongoing population growth in these regions requires a substantial increase in agricultural production while minimizing soil degradation and adverse ecological impacts.This challenge is shared by many countries across South Asia,Africa,and Central and South America.
基金funded by King Abdullah City for Atomic and Renewable Energy(KACARE),grant number“PC-2020-1”.
文摘High-concentration photovoltaic(HCPV)systems present significant thermal management challenges due to the intense heat fluxes generated under concentrated solar irradiation,especially in arid environments.Effective heat dissipation is critical to prevent performance degradation and structural failure.This study investigates the thermal performance and design optimization of an enhanced HCPV module,integrating numerical,analytical,and experimental methods.A coupled optical-thermal-electrical model was developed to simulate ray tracing,heat transfer,and temperature-dependent electrical behaviour,with predictions validated under real-world desert conditions.Compared to a baseline commercial module operating at 106℃,the optimized design achieved a peak temperature reduction of 16℃,lowering the cell temperature to 90℃under a concentration ratio of 961×and direct normal irradiance(DNI)of 950 W/m^(2).The total thermal resistance was reduced from 0.25 to 0.15 K/W(a 40%improvement),and the electrical efficiency increased from 37.5%to 38.6%,representing a relative gain of approximately 3.1%.The system consistently maintained a fill factor exceeding 78%,underscoring stable performance under high thermal load.These findings demonstrate that targeted thermal design,informed by integrated modeling,is essential for unlocking the reliability and efficiency of high-flux solar energy systems.
文摘Neuromodulation for diabetic peripheral neuropathy represents a significant area of interest in the management of chronic pain associated with this condition.Diabetic peripheral neuropathy,a common complication of diabetes,is characterized by nerve damage due to high blood sugar levels that lead to symptoms,such as pain,tingling,and numbness,primarily in the hands and feet.The aim of this systematic review was to evaluate the efficacy of neuromodulatory techniques as potential therapeutic interventions for patients with diabetic peripheral neuropathy,while also examining recent developments in this domain.The investigation encompassed an array of neuromodulation methods,including frequency rhythmic electrical modulated systems,dorsal root ganglion stimulation,and spinal cord stimulation.This systematic review suggests that neuromodulatory techniques may be useful in the treatment of diabetic peripheral neuropathy.Understanding the advantages of these treatments will enable physicians and other healthcare providers to offer additional options for patients with symptoms refractory to standard pharmacologic treatments.Through these efforts,we may improve quality of life and increase functional capacity in patients suffering from complications related to diabetic neuropathy.
基金National Key R&D Program of China of the 13th Five-Year Plan(No.2018YFD1100704)。
文摘To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the effectiveness of flexibility management strategies under different climate conditions and extreme weather events.Using both typical and extreme weather data from cities in five major climate zones of China,this study investigates the energy flexibility potential of an office building under three short-term HVAC management strategies in the context of different climates.The results show that the peak load flexibility and overall energy performance of the three short-term strategies were affected by the surrounding climate conditions.The peak load reduction rate of the pre-cooling and zone temperature reset strategies declined linearly as outdoor temperature increased.Under extreme climate conditions,the daily peak-load time was found to be over two hours earlier than under typical conditions,and the intensive solar radiation found in the extreme conditions can weaken the correlation between peak load reduction and outdoor temperature,risking the ability of a building’s HVAC system to maintain a comfortable indoor environment.
基金supported by the National Natural Science Foundation of China(Nos.42177333 and 31870500)the National Special Program for Key Basic Research of the Ministry of Science and Technology of China(No.2015FY110700)the Jiangsu Agriculture Science and Technology Innovation Fund,China(No.JASTIFCX(20)2003)。
文摘Both straw incorporation and irrigation practices affect biological nitrogen(N)fixation(BNF),but it is still unclear how straw incorporation impacts BNF under continuous(CFI)or intermittent(IFI)flooding irrigation in a rice cropping system.A15N2-labeling chamber system was placed in a rice field to evaluate BNF with straw incorporation under CFI or IFI for 90 d.The nif H(gene encoding the nitrogenase reductase subunit)DNA and c DNA in soil were amplified using real-time quantitative polymerase chain reaction,and high-throughput sequencing was applied to the nif H gene.The total fixed N in the straw incorporation treatment was 14.3 kg ha^(-1)under CFI,being 116%higher than that under IFI(6.62 kg ha^(-1)).Straw incorporation and CFI showed significant interactive effects on the total fixed N and abundances of nif H DNA and c DNA.The increase in BNF was mainly due to the increase in the abundances of heterotrophic diazotrophs such as Desulfovibrio,Azonexus,and Azotobacter.These results indicated that straw incorporation stimulated BNF under CFI relative to IFI,which might ultimately lead to a rapid enhancement of soil fertility.
基金supported by the National Natural Science Foundation of China(72225012)the National Key Research and Development Program of China(2023YFB4302901)+1 种基金the National Natural Science Foundation of China(72288101,71822101,and 62201577)the Safety Capability Building Fund of the Civil Aviation Administration of China(ASSA2023/19).
文摘With the anticipated growth in air traffic complexity in the coming years,future civil aviation transportation system(CATS)is transforming into a complex cyber–physical–social system,surpassing all previous experiences in the history of civil aviation safety management.Therefore,a new safety concept based on a system-of-systems(SoS)perspective is proposed for the next-generation aviation.This article begins by elucidating the complexity of existing aviation risks and emphasizing the necessity for an updated safety concept.It then presents the challenges of current safety management and potential solutions from the new SoS perspective.To address future risks,the concept of SoS safety is introduced with the inspiration of the human immune system in terms of capability,logic,and architecture,which can serve as a guiding framework and methodology for safety engineering in complex large-scale CATS.This concept indicates the transition from“process and outcome-oriented”to“capability-oriented”intelligent safety management.Our research highlights the development directions and potential technological areas that need to be addressed at different stages of SoS safety.The integration of SoS design and operation through rapid iterations enabled by artificial intelligence(AI)will ultimately achieve endogenous SoS safety.
基金the funding and generous support of the National Natural Science Foundation of China(52103263,52271249)the Key Project of International Science&Technology Cooperation of Shaanxi Province(2023-GHZD-09)+5 种基金the Key Project of Science Foundation of Education Department of Shaanxi Province(22JY011)the Key Project of Scientific Research and Development of Shaanxi Province(2023GXLH-070)the Qinchuangyuan"Scientist+Engineer"Team of Shaanxi Province(2023KXJ-069)the Key Research and Development Program of Shaanxi(2023-YBGY-488)the Sci-tech Innovation Team of Shaanxi Province(2024RS-CXTD-46)the Key Research and Development Program of Shaanxi Province(2020ZDLGY13-11).
文摘All-season thermal management with zero energy consumption and emissions is more crucial to global decarbonization over traditional energy-intensive cooling/heating systems.However,the static single thermal management for cooling or heating fails to self-regulate the temperature in dynamic seasonal temperature condition.Herein,inspired by the dual-temperature regulation function of the fur color changes on the backs and abdomens of penguins,a smart thermal management composite hydrogel(PNA@H-PM Gel)system was subtly created though an"on-demand"dual-layer structure design strategy.The PNA@H-PM Gel system features synchronous solar and thermal radiation modulation as well as tunable phase transition temperatures to meet the variable seasonal thermal requirements and energy-saving demands via self-adaptive radiative cooling and solar heating regulation.Furthermore,this system demonstrates superb modulations of both the solar reflectance(ΔR=0.74)and thermal emissivity(ΔE=0.52)in response to ambient temperature changes,highlighting efficient temperature regulation with average radiative cooling and solar heating effects of 9.6℃in summer and 6.1℃in winter,respectively.Moreover,compared to standard building baselines,the PNA@H-PM Gel presents a more substantial energy-saving cooling/heating potentials for energy-efficient buildings across various regions and climates.This novel solution,inspired by penguins in the real world,will offer a fresh approach for producing intelligent,energy-saving thermal management materials,and serve for temperature regulation under dynamic climate conditions and even throughout all seasons.
文摘Distributed Federated Learning(DFL)technology enables participants to cooperatively train a shared model while preserving the privacy of their local datasets,making it a desirable solution for decentralized and privacy-preserving Web3 scenarios.However,DFL faces incentive and security challenges in the decentralized framework.To address these issues,this paper presents a Hierarchical Blockchain-enabled DFL(HBDFL)system,which provides a generic solution framework for the DFL-related applications.The proposed system consists of four major components,including a model contribution-based reward mechanism,a Proof of Elapsed Time and Accuracy(PoETA)consensus algorithm,a Distributed Reputation-based Verification Mechanism(DRTM)and an Accuracy-Dependent Throughput Management(ADTM)mechanism.The model contribution-based rewarding mechanism incentivizes network nodes to train models with their local datasets,while the PoETA consensus algorithm optimizes the tradeoff between the shared model accuracy and system throughput.The DRTM improves the system efficiency in consensus,and the ADTM mechanism guarantees that the throughput performance remains within a predefined range while improving the shared model accuracy.The performance of the proposed HBDFL system is evaluated by numerical simulations,with the results showing that the system improves the accuracy of the shared model while maintaining high throughput and ensuring security.
基金jointly supported by the National Natural Science Foundation of China(71821001,72371109,72071088,72074089,and 51938004)Strategic Study Project of Chinese Academy of Engineering(2022-JB-02)Project of Interdisciplinary Research Support Program in Huazhong University of Science and Technology(2023-32)。
文摘The complexity of coupled risks,which refer to the compounded effects of interacting uncertainties across multiple interdependent objectives,is inherent to cities functioning as dynamic,interdependent systems.A disruption in one domain ripples across various urban systems,often with unforeseen consequences.Central to this complexity are people,whose behaviors,needs,and vulnerabilities shape risk evolution and response effectiveness.Realizing cities as complex systems centered on human needs and behaviors is essential to understanding the complexities of coupled urban risks.This paper adopts a complex systems perspective to examine the intricacies of coupled urban risks,emphasizing the critical role of human decisions and behavior in shaping these dynamics.We focus on two key dimensions:cascading hazards in urban environments and cascading failures across interdependent exposed systems in cities.Existing risk assessment models often fail to capture the complexity of these processes,particularly when factoring in human decision-making.To tackle these challenges,we advocate for a standardized taxonomy of cascading hazards,urban components,and their interactions.At its core is a people-centric perspective,emphasizing the bidirectional interactions between people and the systems that serve them.Building on this foundation,we argue the need for an integrated,people-centric risk assessment framework that evaluates event impacts in relation to the hierarchical needs of people and incorporates their preparedness and response capacities.By leveraging real-time data,advanced simulations,and innovative validation methods,this framework aims to enhance the accuracy of coupled urban risk modeling.To effectively manage coupled urban risks,cities can draw from proven strategies in real complex systems.However,given the escalating uncertainties and complexities associated with climate change,prioritizing people-centric strategies is crucial.This approach will empower cities to build resilience not only against known hazards but also against evolving and unforeseen challenges in an increasingly uncertain world.
文摘Water scarcity poses a significant challenge globally,with South Africa exemplifying the severe socio-economic and environmental impacts of limited water access.Despite advances in modern water management systems,the integration of indigenous knowledge(IK)into formal frameworks remains underutilized.This study systematically reviews the role of indigenous water conservation practices in South Africa,analyzing over 50 high-quality sources using the PRISMA methodology.The findings highlight the effectiveness of IK in addressing water scarcity through techniques such as rainwater harvesting,terracing,and wetland management,which are low-cost,environmentally sustainable,and deeply rooted in cultural practices.Indigenous methods also enhance climate resilience by enabling communities to adapt to droughts and floods through practices such as weather prediction and adaptive farming techniques.Furthermore,these practices foster social inclusivity and community empowerment,ensuring equitable water access and intergenerational knowledge transfer.The study underscores the potential of integrating IK with modern water technologies to create holistic solutions that are scalable,sustainable,and aligned with South Africa’s goal of achieving water security by 2030.Policy recommendations emphasize the need for institutional support,data collection,and financial incentives to sustain and mainstream indigenous approaches.By bridging the gap between traditional and contemporary systems,this research provides a roadmap for leveraging diverse knowledge systems to address water scarcity and build resilient communities.
基金supported by the National Natural Science Foundation of China(NSFC)under grant No.62204235。
文摘This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode scheme with chopped op-amps and internal clock generators to eliminate op-amp offset.A low dropout regulator(LDO)and a pre-regula-tor enhance output driving and LS,respectively.Curvature compensation enhances the TC by addressing higher-order nonlinear-ity.These approaches,effective near room temperature,employs trimming at both 20 and 60°C.When combined with fixed cur-vature correction currents,it achieves an ultra-low TC for each chip.Implemented in a CMOS 180 nm process,the BGR occu-pies 0.548 mm²and operates at 2.5 V with 84μA current draw from a 5 V supply.An average TC of 2.69 ppm/℃ with two-point trimming and 0.81 ppm/℃ with multi-point trimming are achieved over the temperature range of-40 to 125℃.It accommo-dates a load current of 1 mA and an LS of 42 ppm/V,making it suitable for precise BMS applications.
基金supported by the Ecological Conservation and High-Quality Development of the Yellow River Basin Program,China(2022-YRUC-010102)the Second Tibetan Plateau Scientific Expedition and Research Program,China(20190ZKK0405)the Basic Research Fund Project of Innovation Team of Novel Forage Germplasm and Sustainable Utilization of Grassland Resources,China(BR22-12-07)。
文摘There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficient.We simulated the spatiotemporal dynamics of ESs(e.g.,carbon storage,water yield,habitat quality,and soil conservation)and ERs in the upper reach of the Yellow River(URYR)from 2000 to 2100.Additionally,we explored their relationships by combining the InVEST model and a landscape ecological risk model with CMIP6 data.Our main findings showed that regional ERs change in response to land use and environmental dynamics.Specifically,the ER area decreased by 27,673 m^(2)during 2000-2020,but it is projected to increase by 13,273,438,and 68 m^(2)under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios,respectively.We also observed remarkable spatial differences in ESs and ERs between past and future scenarios.For instance,the source area of the URYR exhibited high ESs and low ERs(P<0.001),while the ESs and ERs are declining and increasing,respectively,in the northeastern URYR(P<0.05).Finally,we proposed a spatial optimization framework to improve ESs and reduce ERs,which will support regional sustainable development.
文摘Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers and lacks theoretical guidance.This paper proposes a concise graph representation method based on graph theory for fuel thermal management systems,which can represent all possible connections between subsystems.A generalized optimization algorithm is proposed for fuel thermal management system architecture to minimize the heat sink.This algorithm can autonomously arrange subsystems with heat production differences and efficiently utilize the architecture of the fuel heat sink.At the same time,two evaluation indices are proposed from the perspective of subsystems.These indices intuitively and clearly show that the reason for the high efficiency of heat sink utilization is the balanced and moderate cooling of each subsystem and verify the rationality of the architecture optimization method.A set of simulations are also conducted,which demonstrate that the fuel tank temperature has no effect on the performance of the architecture.This paper provides a reference for the architectural design of aircraft fuel thermal management systems.The metrics used in this paper can also be utilized to evaluate the existing architecture.
文摘Accurate estimation of evapotranspiration(ET)is crucial for efficient water resource management,particularly in the face of climate change and increasing water scarcity.This study performs a bibliometric analysis of 352 articles and a systematic review of 35 peer-reviewed papers,selected according to PRISMA guidelines,to evaluate the performance of Hybrid Artificial Neural Networks(HANNs)in ET estimation.The findings demonstrate that HANNs,particularly those combining Multilayer Perceptrons(MLPs),Recurrent Neural Networks(RNNs),and Convolutional Neural Networks(CNNs),are highly effective in capturing the complex nonlinear relationships and tem-poral dependencies characteristic of hydrological processes.These hybrid models,often integrated with optimization algorithms and fuzzy logic frameworks,significantly improve the predictive accuracy and generalization capabilities of ET estimation.The growing adoption of advanced evaluation metrics,such as Kling-Gupta Efficiency(KGE)and Taylor Diagrams,highlights the increasing demand for more robust performance assessments beyond traditional methods.Despite the promising results,challenges remain,particularly regarding model interpretability,computational efficiency,and data scarcity.Future research should prioritize the integration of interpretability techniques,such as attention mechanisms,Local Interpretable Model-Agnostic Explanations(LIME),and feature importance analysis,to enhance model transparency and foster stakeholder trust.Additionally,improving HANN models’scalability and computational efficiency is crucial,especially for large-scale,real-world applications.Approaches such as transfer learning,parallel processing,and hyperparameter optimization will be essential in overcoming these challenges.This study underscores the transformative potential of HANN models for precise ET estimation,particularly in water-scarce and climate-vulnerable regions.By integrating CNNs for automatic feature extraction and leveraging hybrid architectures,HANNs offer considerable advantages for optimizing water management,particularly agriculture.Addressing challenges related to interpretability and scalability will be vital to ensuring the widespread deployment and operational success of HANNs in global water resource management.
基金supported by the Deanship of Scientific Research and Graduate Studies at King Khalid University under research grant number(R.G.P.2/93/45).
文摘Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.
