With an increase in population and economic development,water withdrawals are close to or even exceed the amount of water available in many regions of the world.Modelling water withdrawals could help water planners im...With an increase in population and economic development,water withdrawals are close to or even exceed the amount of water available in many regions of the world.Modelling water withdrawals could help water planners improve the efficiency of water use,water resources allocation,and management in order to alleviate water crises.However,minimal information has been obtained on how water withdrawals have changed over space and time,especially on a regional or local scale.This research proposes a data-driven framework to help estimate county-level distribution of water withdrawals.Using this framework,spatial statistical methods are used to estimate water withdrawals for agricultural,industrial,and domestic purposes in the Huaihe River watershed in China for the period 1978–2018.Total water withdrawals were found to have more than doubled,from 292.55×10^(8)m^(3) in 1978 to 642.93×10^(8)m^(3) in 2009,and decreased to 602.63×10^(8)m^(3) in 2018.Agricultural water increased from 208.17×10^(8)m^(3) in 1978 to 435.80×10^(8)m^(3) in 2009 and decreased to 360.84×10^(8)m^(3) in 2018.Industrial and domestic water usage constantly increased throughout the 1978–2018 period.In 1978,industrial and domestic demands were 20.35×10^(8)m^(3) and 60.04×10^(8)m^(3),respectively,and up until 2018,the figures were 105.58×10^(8)m^(3) and 136.20×10^(8)m^(3).From a spatial distribution perspective,Moran’s I statistical results show that the total water withdrawal has significant spatial autocorrelation during 1978–2018.The overall trend was a gradual increase in 1978–2010 with withdrawal beginning to decline in 2010–2018.The results of Getis-Ord G_(i)^(*)statistical calculations showed spatially contiguous clusters of total water withdrawal in the Huaihe River watershed during1978–2010,and the spatial agglomeration weakened from 2010 to 2018.This study provides a data-driven framework for assessing water withdrawals to enable a deeper understanding of competing water use among economic sectors as well as water withdrawal modelled with proper data resource and method.展开更多
A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis ca...A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis can be challenging because production performance is dominated by the complex interaction among a series of geological and engineering factors.In fact,each factor can be viewed as a player who makes cooperative contributions to the production payoff within the constraints of physical laws and models.Inspired by the idea,we propose a hybrid data-driven analysis framework in this study,where the contributions of dominant factors are quantitatively evaluated,the productions are precisely forecasted,and the development optimization suggestions are comprehensively generated.More specifically,game theory and machine learning models are coupled to determine the dominating geological and engineering factors.The Shapley value with definite physical meaning is employed to quantitatively measure the effects of individual factors.A multi-model-fused stacked model is trained for production forecast,which provides the basis for derivative-free optimization algorithms to optimize the development plan.The complete workflow is validated with actual production data collected from the Fuling shale gas field,Sichuan Basin,China.The validation results show that the proposed procedure can draw rigorous conclusions with quantified evidence and thereby provide specific and reliable suggestions for development plan optimization.Comparing with traditional and experience-based approaches,the hybrid data-driven procedure is advanced in terms of both efficiency and accuracy.展开更多
This study integrates multiple sources of data(transaction data,policy text,public opinion data)with visualization techniques(such as heat maps,time-series trend charts,3D building brochures)to construct an analysis f...This study integrates multiple sources of data(transaction data,policy text,public opinion data)with visualization techniques(such as heat maps,time-series trend charts,3D building brochures)to construct an analysis framework for the Chengdu real estate market.By using the Adaptive Neuro-Fuzzy Inference System(ANFIS)prediction model,spatial GIS(Geographic Information System analysis)analysis,and interactive dashboards,this study reveals market differentiation,policy impacts,and changes in demand structure,thereby providing decision support for the government,enterprises,and homebuyers.展开更多
Against the backdrop of the national innovation strategy and the digital transformation of education,the traditional“extensive”training model for innovation and entrepreneurship talents struggles to meet the persona...Against the backdrop of the national innovation strategy and the digital transformation of education,the traditional“extensive”training model for innovation and entrepreneurship talents struggles to meet the personalized development needs of students,making an urgent shift toward precision and intelligence necessary.This study constructs a four-dimensional integrated framework centered on data,“Goal-Data-Intervention-Evaluation”,and proposes a data-driven training model for innovation and entrepreneurship talents in universities.By collecting multi-source data such as learning behaviors,competency assessments,and practical projects,the model conducts in-depth analysis of students’individual characteristics and development potential,enabling precise decision-making in goal setting,teaching intervention,and practical guidance.Based on data analysis,a supportive system for personalized teaching and practical activities is established.Combined with process-oriented and summative evaluations,a closed-loop feedback mechanism is formed to improve training effectiveness.This model provides a theoretical framework and practical path for the scientific,personalized,and intelligent development of innovation and entrepreneurship education in universities.展开更多
This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mi...This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.展开更多
The distillation process is an important chemical process,and the application of data-driven modelling approach has the potential to reduce model complexity compared to mechanistic modelling,thus improving the efficie...The distillation process is an important chemical process,and the application of data-driven modelling approach has the potential to reduce model complexity compared to mechanistic modelling,thus improving the efficiency of process optimization or monitoring studies.However,the distillation process is highly nonlinear and has multiple uncertainty perturbation intervals,which brings challenges to accurate data-driven modelling of distillation processes.This paper proposes a systematic data-driven modelling framework to solve these problems.Firstly,data segment variance was introduced into the K-means algorithm to form K-means data interval(KMDI)clustering in order to cluster the data into perturbed and steady state intervals for steady-state data extraction.Secondly,maximal information coefficient(MIC)was employed to calculate the nonlinear correlation between variables for removing redundant features.Finally,extreme gradient boosting(XGBoost)was integrated as the basic learner into adaptive boosting(AdaBoost)with the error threshold(ET)set to improve weights update strategy to construct the new integrated learning algorithm,XGBoost-AdaBoost-ET.The superiority of the proposed framework is verified by applying this data-driven modelling framework to a real industrial process of propylene distillation.展开更多
In this study,a nickel-based MOF{(NH_(2)(CH_(3))_(2))_(2)[Ni_(3)(O)(L)3(NH(CH_(3))_(2))_(3)]}_(n)(Ni_(3)-MOF),with pore sizes of approximately 1.6 nm×1.6 nm,was synthesized by reacting 4,4′-biphenyldicarboxylic ...In this study,a nickel-based MOF{(NH_(2)(CH_(3))_(2))_(2)[Ni_(3)(O)(L)3(NH(CH_(3))_(2))_(3)]}_(n)(Ni_(3)-MOF),with pore sizes of approximately 1.6 nm×1.6 nm,was synthesized by reacting 4,4′-biphenyldicarboxylic acid(H_(2)L)with Ni(NO_(3))_(2)·6H_(2)O in an N,N-dimethylformamide(DMF)solution.The nanoscale adsorbent Ni_(3)-MOF-N with a particle diameter of approximately 200 nm was prepared using Ni_(3)-MOF.It exhibited a maximum equilibrium tetracycline(TC)adsorption capacity of 358.2 mg·g^(-1)at its isoelectric point(pH=6.50),outperforming most reported MOF-based adsorbents.This exceptional performance is likely attributed to the well-matched pore size of Ni_(3)-MOF-N(1.6 nm×1.6 nm)and the molecular dimensions of TC(0.8 nm×1.2 nm),combined with the presence of partial Ni(Ⅱ)sites on the surface of Ni_(3)-MOF-N.These features collectively facilitate effective TC adsorption through a combination of pore filling,electrostatic attraction,hydrogen bonding,surface complexation,andπ-πinteractions.Recycling experiments demonstrated that Ni_(3)-MOF-N possesses excellent structural stability and consistent adsorption performance.CCDC:2481791,Ni_(3)-MOF.展开更多
A metal-organic framework{[Zn(L)_(0.5)(1,2,4,5-tpb)_(0.5)]·DMF·3H_(2)O}_(n)(1)was synthesized by solvothermal reaction,where H4L=5,5'-(ethane-1,2-diyl)diisophthalic acid,and 1,2,4,5-tpb=1,2,4,5-tetra(pyr...A metal-organic framework{[Zn(L)_(0.5)(1,2,4,5-tpb)_(0.5)]·DMF·3H_(2)O}_(n)(1)was synthesized by solvothermal reaction,where H4L=5,5'-(ethane-1,2-diyl)diisophthalic acid,and 1,2,4,5-tpb=1,2,4,5-tetra(pyridin-4-yl)benzene.The analysis of the single crystal structure indicates that L^(4-)and 1,2,4,5-tpb are connected with Zn(Ⅱ)to form a 2D layered structure,and the layers are linked by 1,2,4,5-tpb to form a 3D structure.1 can be used as a highly selective fluorescent probe for the detection of 2,4-dinitrophenylhydrazine(DNP)and tetracycline(TET),and the detection limits were 0.013 and 0.31μmol·L^(-1),respectively.1 was applied successfully to the determination of TET content in the Yanhe River water sample.CCDC:2466221.展开更多
In this study,a multifunctional aptamer-conjugated magnetic covalent organic framework(COF)-CuO/Au nanozyme(MCOF-CuO/Au@apt)was developed as a“three-in-one”platform for dual-signal colorimetric and fluorescent detec...In this study,a multifunctional aptamer-conjugated magnetic covalent organic framework(COF)-CuO/Au nanozyme(MCOF-CuO/Au@apt)was developed as a“three-in-one”platform for dual-signal colorimetric and fluorescent detection of Vibrio parahaemolyticus.The nanozyme integrated magnetic separation,peroxidase-like catalytic activity,and specific target recognition through an aptamer-based strategy.Upon binding to V.parahaemolyticus,the catalytic oxidation of tetra-aminophenylethylene(TPE-4A)by the nanozyme was selectively inhibited,resulting in distinct colorimetric and fluorescent signals that significantly enhanced the detection accuracy and reliability.The proposed method exhibited high sensitivity,with limits of detection(LOD)of 21 and 7 CFU/mL for the colorimetric and fluorescent assays,respectively.The performance of this method was validated using real seafood samples,including Penaeus vannamei,Mytilus coruscus,and Crassostrea gigas,which showed high recovery rates(101.11%-107.30%)and excellent reproducibility.The system also demonstrated strong specificity and accuracy under various conditions,confirming its robustness and practical applicability.Collectively,this innovative platform presents a promising solution for the rapid,versatile,and sensitive detection of V.parahaemolyticus in seafood,with considerable potential to advance food safety diagnosis and on-site monitoring.展开更多
Under hydrothermal and solvothermal conditions,two novel cobalt-based complexes,{[Co_(2)(CIA)(OH)(1,4-dtb)]·3.2H_(2)O}n(HU23)and{[Co_(2)(CIA)(OH)(1,4-dib)]·3.5H2O·DMF}n(HU24),were successfully construct...Under hydrothermal and solvothermal conditions,two novel cobalt-based complexes,{[Co_(2)(CIA)(OH)(1,4-dtb)]·3.2H_(2)O}n(HU23)and{[Co_(2)(CIA)(OH)(1,4-dib)]·3.5H2O·DMF}n(HU24),were successfully constructed by coordinatively assembling the semi-rigid multidentate ligand 5-(1-carboxyethoxy)isophthalic acid(H₃CIA)with the Nheterocyclic ligands 1,4-di(4H-1,2,4-triazol-4-yl)benzene(1,4-dtb)and 1,4-di(1H-imidazol-1-yl)benzene(1,4-dib),respectively,around Co^(2+)ions.Single-crystal X-ray diffraction analysis revealed that in both complexes HU23 and HU24,the CIA^(3-)anions adopt aκ^(7)-coordination mode,bridging six Co^(2+)ions via their five carboxylate oxygen atoms and one ether oxygen atom.This linkage forms tetranuclear[Co4(μ3-OH)2]^(6+)units.These Co-oxo cluster units were interconnected by CIA^(3-)anions to assemble into 2D kgd-type structures featuring a 3,6-connected topology.The 2D layers were further connected by 1,4-dtb and 1,4-dib,resulting in 3D pillar-layered frameworks for HU23 and HU24.Notably,despite the similar configurations of 1,4-dtb and 1,4-dib,differences in their coordination spatial orientations lead to topological divergence in the 3D frameworks of HU23 and HU24.Topological analysis indicates that the frameworks of HU23 and HU24 can be simplified into a 3,10-connected net(point symbol:(4^(10).6^(3).8^(2))(4^(3))_(2))and a 3,8-connected tfz-d net(point symbol:(4^(3))_(2)((4^(6).6^(18).8^(4)))),respectively.This structural differentiation confirms the precise regulatory role of ligands on the topology of metal-organic frameworks.Moreover,the ultraviolet-visible absorption spectra confirmed that HU23 and HU24 have strong absorption capabilities for ultraviolet and visible light.According to the Kubelka-Munk method,their bandwidths were 2.15 and 2.08 eV,respectively,which are consistent with those of typical semiconductor materials.Variable-temperature magnetic susceptibility measurements(2-300 K)revealed significant antiferromagnetic coupling in both complexes,with their effective magnetic moments decreasing markedly as the temperature lowered.CCDC:2457554,HU23;2457553,HU24.展开更多
To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance dat...To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance data-driven event-triggered fusion control method,which achieves efficient fault diagnosis while suppressing random disturbances and mitigating communication conflicts within the QUAV swarm.First,the impact of random disturbances on the UAV swarm is analyzed,and a model for orientation and attitude control of QUAVs under stochastic perturbations is established,with the disturbance gain threshold determined.Second,a fault diagnosis system based on a high-gain observer is designed,constructing a fault gain criterion by integrating orientation and attitude information from QUAVs.Subsequently,a model-free dynamic linearization-based data modeling(MFDLDM)framework is developed using model-free adaptive control,which efficiently fits the nonlinear control model of the QUAV swarm while reducing temporal constraints on control data.On this basis,this paper constructs a distributed data-driven event-triggered controller based on the staggered communication mechanism,which consists of an equivalent QUAV controller and an event-triggered controller,and is able to reduce the communication conflicts while suppressing the influence of random interference.Finally,by incorporating random disturbances into the controller,comparative experiments and physical validations are conducted on the QUAV platforms,fully demonstrating the strong adaptability and robustness of the proposed distributed event-triggered fault-tolerant control system.展开更多
Wetting deformation in earth-rockfill dams is a critical factor influencingdam safety.Although numerous mathematical models have been developed to describe this phenomenon,most of them rely on empirical formulations a...Wetting deformation in earth-rockfill dams is a critical factor influencingdam safety.Although numerous mathematical models have been developed to describe this phenomenon,most of them rely on empirical formulations and lack prior knowledge of model parameters,which is essential for Bayesian parameter inversion to enhance accuracy and reduce uncertainty.This study introduces a datadriven approach to establishing prior knowledge of earth-rockfill dams.Driving factors are utilized to determine the potential range of model parameters,and settlement changes within this range are calculated.The results are iteratively compared with actual monitoring data until the calculated range encompasses the observed data,thereby providing prior knowledge of the model parameters.The proposed method is applied to the right-bank earth-rockfilldam of Danjiangkou.Employing a Gibbs sample size of 30,000,the proposed method effectively calibrates the prior knowledge of the wetting model parameters,achieving a root mean square error(RMSE)of 5.18 mm for the settlement predictions.By comparison,the use of non-informative priors with sample sizes of 30,000 and 50,000 results in significantly larger RMSE values of 11.97 mm and 16.07 mm,respectively.Furthermore,the computational efficiencyof the proposed method is demonstrated by an inversion computation time of 902 s for 30,000 samples,which is notably shorter than the 1026 s and 1558 s required for noninformative priors with 30,000 and 50,000 samples,respectively.These findingsunderscore the superior performance of the proposed approach in terms of both prediction accuracy and computational efficiency.These results demonstrate that the proposed method not only improves the predictive accuracy but also enhances the computational efficiency,enabling optimal parameter identificationwith reduced computational effort.This approach provides a robust and efficientframework for advancing dam safety assessments.展开更多
Storm-enhanced density(SED)and the tongue of ionization(TOI)are key ionospheric storm-time structures whose rapid evolution and fine-scale variability remain challenging to capture with conventional empirical high-lat...Storm-enhanced density(SED)and the tongue of ionization(TOI)are key ionospheric storm-time structures whose rapid evolution and fine-scale variability remain challenging to capture with conventional empirical high-latitude drivers.In this study,we examine the May 10–11,2024,superstorm using the Thermosphere–Ionosphere–Electrodynamics General Circulation Model(TIEGCM)with observation-constrained high-latitude forcing.Auroral precipitation parameters(energy flux and mean energy)are assimilated from a Defense Meteorological Satellite Program(DMSP)Special Sensor Ultraviolet Spectrographic Imager(SSUSI)using a multi-resolution Gaussian process(Lattice Kriging)approach,whereas high-latitude convection potentials are derived by assimilating Super Dual Auroral Radar Network(SuperDARN)observations with the Thomas and Shepherd(2018)model(TS18).For comparison,an additional simulation is performed using empirical models for both convection and auroral forcing.The results show that during the main phase of the May 10 storm,the data-driven simulation provides a more realistic depiction of the SED source region than does the empirical model run by capturing its rapid intensification more clearly and reproducing its spatial location and structural features with higher fidelity.These improvements lead to a more accurate representation of its poleward extension into the polar cap that develops into the TOI.Above the ionospheric F2 peak over the SED source region,SuperDARN-constrained potentials generate stronger and more localized E×B drifts that dominate plasma uplift and drive its transport into the polar cap,although neutral winds and downward ambipolar diffusion partially offset these effects.Below the F2 peak,neutral winds and photochemical processes play a major role in shaping the spatial extent and intensity of the SED and TOI.These results highlight the role of observation-constrained high-latitude drivers in representing ionosphere–thermosphere responses during extreme storms and suggest their relevance for improving physical interpretation and model performance.展开更多
Silicon possesses a high theoretical capacity,making it a potential contender for lithium-ion battery(LIB)anodes.Nonetheless,its practical usage is challenged by low electrical conductivity and significant volume expa...Silicon possesses a high theoretical capacity,making it a potential contender for lithium-ion battery(LIB)anodes.Nonetheless,its practical usage is challenged by low electrical conductivity and significant volume expansion during cycling.Here,we synthesized a novel silicon/carbon(Si/C)anode doped with ZnO via a template-derived method and high-temperature carbonization.The carbon structure,originated from metal-organic frameworks(MOFs)and ZnO doping,substantially enhanced the electrochemical properties of the composite material.It exhibited an initial capacity of 2100.3 mA h g^(-1)at a current density of 0.2 A g^(-1)and demonstrated excellent capacity retention over successive cycles.Moreover,the composite material displayed superior rate performance at higher current densities of 2 A g^(-1)and 3 A g^(-1).To address the low initial Coulombic efficiency(ICE)of siliconbased materials,we adopted a direct contact prelithiation approach and optimized the lithiation process by controlling the prelithiation time.After 30 min of prelithiation,the ICE reached 97.9%,thereby reducing the initial irreversible capacity loss(ICL)and realizing stable discharge-charge in subsequent cycles.This rational design provides valuable insights for achieving high-performance silicon anode.展开更多
High-sensitive quantitative determination of alpha-fetoprotein(AFP)is of crucial importance for early clinical diagnosis of cancers.Herein,an AuNPs-free electrochemical immunosensor(Ab1-Fc-COF)was prepared from a carb...High-sensitive quantitative determination of alpha-fetoprotein(AFP)is of crucial importance for early clinical diagnosis of cancers.Herein,an AuNPs-free electrochemical immunosensor(Ab1-Fc-COF)was prepared from a carboxylic group enriched COF by post-functionalization with detecting antibody(Ab1)and ferrocene(Fc),and used for electrochemical detection of AFP.Due to the small,homogeneous pore size of the COF,Ab1 with a big size was immobilized on the surface of the COF,while Fc with a small size was covalently modified both on the surface and in the pores of COF.The covalently immobilized Ab1 was quite stable and beneficial to specifically detect AFP biomarkers.Meanwhile,the enriched Fc molecules not only improved the conductivity of the COF,but also effectively transferred and amplified the electrochemical signal.This proposed immunosensor exhibited high sensitivity in detecting AFP with a detection limit of 0.39 pg/mL(S/N of 3:1)and a wide linear response range spanning from 1 pg/mL to 100 ng/mL when plotted against logarithmic concentrations.Furthermore,this immunosensor showed excellent selectivity,stability and reproducibility in the testing of real samples.This study presents an innovative prototype for construction of a precious metal-free,antibody-directly-immobilized,simple and stable electrochemical immunoprobe.展开更多
Autonomous connected vehicles(ACV)involve advanced control strategies to effectively balance safety,efficiency,energy consumption,and passenger comfort.This research introduces a deep reinforcement learning(DRL)-based...Autonomous connected vehicles(ACV)involve advanced control strategies to effectively balance safety,efficiency,energy consumption,and passenger comfort.This research introduces a deep reinforcement learning(DRL)-based car-following(CF)framework employing the Deep Deterministic Policy Gradient(DDPG)algorithm,which integrates a multi-objective reward function that balances the four goals while maintaining safe policy learning.Utilizing real-world driving data from the highD dataset,the proposed model learns adaptive speed control policies suitable for dynamic traffic scenarios.The performance of the DRL-based model is evaluated against a traditional model predictive control-adaptive cruise control(MPC-ACC)controller.Results show that theDRLmodel significantly enhances safety,achieving zero collisions and a higher average time-to-collision(TTC)of 8.45 s,compared to 5.67 s for MPC and 6.12 s for human drivers.For efficiency,the model demonstrates 89.2% headway compliance and maintains speed tracking errors below 1.2 m/s in 90% of cases.In terms of energy optimization,the proposed approach reduces fuel consumption by 5.4% relative to MPC.Additionally,it enhances passenger comfort by lowering jerk values by 65%,achieving 0.12 m/s3 vs.0.34 m/s3 for human drivers.A multi-objective reward function is integrated to ensure stable policy convergence while simultaneously balancing the four key performance metrics.Moreover,the findings underscore the potential of DRL in advancing autonomous vehicle control,offering a robust and sustainable solution for safer,more efficient,and more comfortable transportation systems.展开更多
Accelerating the development of new quality productive forces(NQPF),with innovation at its core,has become essential for firm growth in the new era.Drawing on financial data from China's A-share listed companies s...Accelerating the development of new quality productive forces(NQPF),with innovation at its core,has become essential for firm growth in the new era.Drawing on financial data from China's A-share listed companies spanning the period 2010–2023,this study empirically investigates the impact of entrepreneurial spirit on firm-level NQPF.The results indicate that entrepreneurial spirit significantly promotes firm-level NQPF.Mechanism analysis indicates that entrepreneurial effort—underpinned by technological capital accumulation,effective incentive and constraint mechanisms,and a competitive market environment—plays a mediating role in this relationship.Further heterogeneity analysis reveals that,amid China's economic transition,the positive effects of entrepreneurial spirit are more pronounced in non-state-owned enterprises,high-tech firms,and newly established firms.Accordingly,systematic efforts should be pursued across the technological,organizational,and environmental(TOE)dimensions to optimize the cultivation of entrepreneurial spirit.In particular,greater emphasis should be placed on productive entrepreneurial spirit and the constructive role of entrepreneurial effort,so as to fully leverage their contribution to the advancement of firm-level NQPF.展开更多
Gas sensors are valuable tools for human applications,and extensive research has been conducted in this field.However,practical implementation has yet to be fully realized.In response,efforts have been made to explore...Gas sensors are valuable tools for human applications,and extensive research has been conducted in this field.However,practical implementation has yet to be fully realized.In response,efforts have been made to explore metal-organic frameworks(MOFs),a novel class of porous materials,as potential solutions.MOFs exhibit exceptional porosity and highly tunable chemical compositions and structures,giving rise to a wide range of unique physical and chemical properties.Significant progress has been achieved in developing MOF-based gas sensors,improving sensing performance for various gases.This review aims to provide a comprehensive understanding of MOF-based gas sensors,even for readers unfamiliar with MOFs and gas sensors.It covers the working principles of these sensors,fundamental concepts of MOFs,strategies for tuning MOF properties,fabrication techniques for MOF films,and recent studies on MOF and MOF-derivative gas sensors.Finally,current challenges,overlooked aspects,and future directions for fully exploiting the potential of MOFs in gas sensor development are discussed.展开更多
Lead-halide perovskite solar cells(PSCs)have rapidly achieved certified efficiencies>27%,rivaling silicon photovoltaics.However,their commercialization is hindered by intrinsic material challenges:poor operational ...Lead-halide perovskite solar cells(PSCs)have rapidly achieved certified efficiencies>27%,rivaling silicon photovoltaics.However,their commercialization is hindered by intrinsic material challenges:poor operational stability under moisture,heat,and light;toxic lead leakage from degraded films.Metal-organic frameworks(MOFs),with their unique framework structure,large specific surface area,high heavy metal capturing capacity,and tunable conductivity,offer promising solutions to these issues.Recent studies have integrated MOFs into PSCs architectures to enhance performance and durability.This comprehensive review begins with an in-depth discussion of the structure,optical properties,electrical characteristics,and stability of MOFs,as well as their theoretical compatibility with perovskites.Subsequently,it provides a detailed analysis of how MOFs enhance charge carrier transport,promote perovskite crystallinity,improve device stability,and suppress lead leakage in PSCs.In summary,this review examines the research progress and potential of integrating MOFs with perovskites to address the critical PSCs challenges of efficiency,instability,and toxicity.展开更多
Metal-organic frameworks(MOFs)with high porosity,specific surface area,and unique topologies are highly regarded for their applications in photocatalysis,medical treatment,and environmental pollutant degradation.Howev...Metal-organic frameworks(MOFs)with high porosity,specific surface area,and unique topologies are highly regarded for their applications in photocatalysis,medical treatment,and environmental pollutant degradation.However,due to the limitations of the tumor microenvironment(TME),traditional MOFs have limited efficacy in this environment.This paper designs multi-metal oxide-based heterostructure POMOFs nanoreactors with a nesting doll-like structure.This new structure not only exhibits therapeutic effects in TME but also utilizes ultrasound(US)to enhance the release of reactive oxygen species(ROS)for CDT&SDT co-therapy,becoming an effective sound sensitizer for destroying tumor cells.In summary,our study proposes an idea for constructing multi-metal oxide-based heterostructure MOFs nanoreactors material with a nesting doll-like structure to enhance ROS release and synergistically treat tumor diseases.展开更多
基金Under the auspices of the National Natural Science Foundation of China(No.71203200)the National Social Science Fund Project(No.20&ZD138)+1 种基金the National Science and Technology Platform Construction Project(No.2005DKA32300)the Major Research Projects of the Ministry of Education(No.16JJD770019)。
文摘With an increase in population and economic development,water withdrawals are close to or even exceed the amount of water available in many regions of the world.Modelling water withdrawals could help water planners improve the efficiency of water use,water resources allocation,and management in order to alleviate water crises.However,minimal information has been obtained on how water withdrawals have changed over space and time,especially on a regional or local scale.This research proposes a data-driven framework to help estimate county-level distribution of water withdrawals.Using this framework,spatial statistical methods are used to estimate water withdrawals for agricultural,industrial,and domestic purposes in the Huaihe River watershed in China for the period 1978–2018.Total water withdrawals were found to have more than doubled,from 292.55×10^(8)m^(3) in 1978 to 642.93×10^(8)m^(3) in 2009,and decreased to 602.63×10^(8)m^(3) in 2018.Agricultural water increased from 208.17×10^(8)m^(3) in 1978 to 435.80×10^(8)m^(3) in 2009 and decreased to 360.84×10^(8)m^(3) in 2018.Industrial and domestic water usage constantly increased throughout the 1978–2018 period.In 1978,industrial and domestic demands were 20.35×10^(8)m^(3) and 60.04×10^(8)m^(3),respectively,and up until 2018,the figures were 105.58×10^(8)m^(3) and 136.20×10^(8)m^(3).From a spatial distribution perspective,Moran’s I statistical results show that the total water withdrawal has significant spatial autocorrelation during 1978–2018.The overall trend was a gradual increase in 1978–2010 with withdrawal beginning to decline in 2010–2018.The results of Getis-Ord G_(i)^(*)statistical calculations showed spatially contiguous clusters of total water withdrawal in the Huaihe River watershed during1978–2010,and the spatial agglomeration weakened from 2010 to 2018.This study provides a data-driven framework for assessing water withdrawals to enable a deeper understanding of competing water use among economic sectors as well as water withdrawal modelled with proper data resource and method.
基金This work was supported by the National Natural Science Foundation of China(Grant No.42050104)the Science Foundation of SINOPEC Group(Grant No.P20030).
文摘A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis can be challenging because production performance is dominated by the complex interaction among a series of geological and engineering factors.In fact,each factor can be viewed as a player who makes cooperative contributions to the production payoff within the constraints of physical laws and models.Inspired by the idea,we propose a hybrid data-driven analysis framework in this study,where the contributions of dominant factors are quantitatively evaluated,the productions are precisely forecasted,and the development optimization suggestions are comprehensively generated.More specifically,game theory and machine learning models are coupled to determine the dominating geological and engineering factors.The Shapley value with definite physical meaning is employed to quantitatively measure the effects of individual factors.A multi-model-fused stacked model is trained for production forecast,which provides the basis for derivative-free optimization algorithms to optimize the development plan.The complete workflow is validated with actual production data collected from the Fuling shale gas field,Sichuan Basin,China.The validation results show that the proposed procedure can draw rigorous conclusions with quantified evidence and thereby provide specific and reliable suggestions for development plan optimization.Comparing with traditional and experience-based approaches,the hybrid data-driven procedure is advanced in terms of both efficiency and accuracy.
基金Chengdu City Philosophy and Social Sciences Research Center“artificial intelligence+urban communication”theory and Application Research Center Project“Chengdu real estate vertical market public opinion data visualization research”(Project No.RZCC2025017).
文摘This study integrates multiple sources of data(transaction data,policy text,public opinion data)with visualization techniques(such as heat maps,time-series trend charts,3D building brochures)to construct an analysis framework for the Chengdu real estate market.By using the Adaptive Neuro-Fuzzy Inference System(ANFIS)prediction model,spatial GIS(Geographic Information System analysis)analysis,and interactive dashboards,this study reveals market differentiation,policy impacts,and changes in demand structure,thereby providing decision support for the government,enterprises,and homebuyers.
基金Special Fund for Teacher Development Research Program of University of Shanghai for Science and Technology(Project No.:CFTD2025YB28)。
文摘Against the backdrop of the national innovation strategy and the digital transformation of education,the traditional“extensive”training model for innovation and entrepreneurship talents struggles to meet the personalized development needs of students,making an urgent shift toward precision and intelligence necessary.This study constructs a four-dimensional integrated framework centered on data,“Goal-Data-Intervention-Evaluation”,and proposes a data-driven training model for innovation and entrepreneurship talents in universities.By collecting multi-source data such as learning behaviors,competency assessments,and practical projects,the model conducts in-depth analysis of students’individual characteristics and development potential,enabling precise decision-making in goal setting,teaching intervention,and practical guidance.Based on data analysis,a supportive system for personalized teaching and practical activities is established.Combined with process-oriented and summative evaluations,a closed-loop feedback mechanism is formed to improve training effectiveness.This model provides a theoretical framework and practical path for the scientific,personalized,and intelligent development of innovation and entrepreneurship education in universities.
基金supported by the National Natural Science Foundation of China(No.12372045)the National Key Research and the Development Program of China(Nos.2023YFC2205900,2023YFC2205901)。
文摘This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.
基金supported by the National Key Research and Development Program of China(2023YFB3307801)the National Natural Science Foundation of China(62394343,62373155,62073142)+3 种基金Major Science and Technology Project of Xinjiang(No.2022A01006-4)the Programme of Introducing Talents of Discipline to Universities(the 111 Project)under Grant B17017the Fundamental Research Funds for the Central Universities,Science Foundation of China University of Petroleum,Beijing(No.2462024YJRC011)the Open Research Project of the State Key Laboratory of Industrial Control Technology,China(Grant No.ICT2024B70).
文摘The distillation process is an important chemical process,and the application of data-driven modelling approach has the potential to reduce model complexity compared to mechanistic modelling,thus improving the efficiency of process optimization or monitoring studies.However,the distillation process is highly nonlinear and has multiple uncertainty perturbation intervals,which brings challenges to accurate data-driven modelling of distillation processes.This paper proposes a systematic data-driven modelling framework to solve these problems.Firstly,data segment variance was introduced into the K-means algorithm to form K-means data interval(KMDI)clustering in order to cluster the data into perturbed and steady state intervals for steady-state data extraction.Secondly,maximal information coefficient(MIC)was employed to calculate the nonlinear correlation between variables for removing redundant features.Finally,extreme gradient boosting(XGBoost)was integrated as the basic learner into adaptive boosting(AdaBoost)with the error threshold(ET)set to improve weights update strategy to construct the new integrated learning algorithm,XGBoost-AdaBoost-ET.The superiority of the proposed framework is verified by applying this data-driven modelling framework to a real industrial process of propylene distillation.
文摘In this study,a nickel-based MOF{(NH_(2)(CH_(3))_(2))_(2)[Ni_(3)(O)(L)3(NH(CH_(3))_(2))_(3)]}_(n)(Ni_(3)-MOF),with pore sizes of approximately 1.6 nm×1.6 nm,was synthesized by reacting 4,4′-biphenyldicarboxylic acid(H_(2)L)with Ni(NO_(3))_(2)·6H_(2)O in an N,N-dimethylformamide(DMF)solution.The nanoscale adsorbent Ni_(3)-MOF-N with a particle diameter of approximately 200 nm was prepared using Ni_(3)-MOF.It exhibited a maximum equilibrium tetracycline(TC)adsorption capacity of 358.2 mg·g^(-1)at its isoelectric point(pH=6.50),outperforming most reported MOF-based adsorbents.This exceptional performance is likely attributed to the well-matched pore size of Ni_(3)-MOF-N(1.6 nm×1.6 nm)and the molecular dimensions of TC(0.8 nm×1.2 nm),combined with the presence of partial Ni(Ⅱ)sites on the surface of Ni_(3)-MOF-N.These features collectively facilitate effective TC adsorption through a combination of pore filling,electrostatic attraction,hydrogen bonding,surface complexation,andπ-πinteractions.Recycling experiments demonstrated that Ni_(3)-MOF-N possesses excellent structural stability and consistent adsorption performance.CCDC:2481791,Ni_(3)-MOF.
文摘A metal-organic framework{[Zn(L)_(0.5)(1,2,4,5-tpb)_(0.5)]·DMF·3H_(2)O}_(n)(1)was synthesized by solvothermal reaction,where H4L=5,5'-(ethane-1,2-diyl)diisophthalic acid,and 1,2,4,5-tpb=1,2,4,5-tetra(pyridin-4-yl)benzene.The analysis of the single crystal structure indicates that L^(4-)and 1,2,4,5-tpb are connected with Zn(Ⅱ)to form a 2D layered structure,and the layers are linked by 1,2,4,5-tpb to form a 3D structure.1 can be used as a highly selective fluorescent probe for the detection of 2,4-dinitrophenylhydrazine(DNP)and tetracycline(TET),and the detection limits were 0.013 and 0.31μmol·L^(-1),respectively.1 was applied successfully to the determination of TET content in the Yanhe River water sample.CCDC:2466221.
文摘In this study,a multifunctional aptamer-conjugated magnetic covalent organic framework(COF)-CuO/Au nanozyme(MCOF-CuO/Au@apt)was developed as a“three-in-one”platform for dual-signal colorimetric and fluorescent detection of Vibrio parahaemolyticus.The nanozyme integrated magnetic separation,peroxidase-like catalytic activity,and specific target recognition through an aptamer-based strategy.Upon binding to V.parahaemolyticus,the catalytic oxidation of tetra-aminophenylethylene(TPE-4A)by the nanozyme was selectively inhibited,resulting in distinct colorimetric and fluorescent signals that significantly enhanced the detection accuracy and reliability.The proposed method exhibited high sensitivity,with limits of detection(LOD)of 21 and 7 CFU/mL for the colorimetric and fluorescent assays,respectively.The performance of this method was validated using real seafood samples,including Penaeus vannamei,Mytilus coruscus,and Crassostrea gigas,which showed high recovery rates(101.11%-107.30%)and excellent reproducibility.The system also demonstrated strong specificity and accuracy under various conditions,confirming its robustness and practical applicability.Collectively,this innovative platform presents a promising solution for the rapid,versatile,and sensitive detection of V.parahaemolyticus in seafood,with considerable potential to advance food safety diagnosis and on-site monitoring.
文摘Under hydrothermal and solvothermal conditions,two novel cobalt-based complexes,{[Co_(2)(CIA)(OH)(1,4-dtb)]·3.2H_(2)O}n(HU23)and{[Co_(2)(CIA)(OH)(1,4-dib)]·3.5H2O·DMF}n(HU24),were successfully constructed by coordinatively assembling the semi-rigid multidentate ligand 5-(1-carboxyethoxy)isophthalic acid(H₃CIA)with the Nheterocyclic ligands 1,4-di(4H-1,2,4-triazol-4-yl)benzene(1,4-dtb)and 1,4-di(1H-imidazol-1-yl)benzene(1,4-dib),respectively,around Co^(2+)ions.Single-crystal X-ray diffraction analysis revealed that in both complexes HU23 and HU24,the CIA^(3-)anions adopt aκ^(7)-coordination mode,bridging six Co^(2+)ions via their five carboxylate oxygen atoms and one ether oxygen atom.This linkage forms tetranuclear[Co4(μ3-OH)2]^(6+)units.These Co-oxo cluster units were interconnected by CIA^(3-)anions to assemble into 2D kgd-type structures featuring a 3,6-connected topology.The 2D layers were further connected by 1,4-dtb and 1,4-dib,resulting in 3D pillar-layered frameworks for HU23 and HU24.Notably,despite the similar configurations of 1,4-dtb and 1,4-dib,differences in their coordination spatial orientations lead to topological divergence in the 3D frameworks of HU23 and HU24.Topological analysis indicates that the frameworks of HU23 and HU24 can be simplified into a 3,10-connected net(point symbol:(4^(10).6^(3).8^(2))(4^(3))_(2))and a 3,8-connected tfz-d net(point symbol:(4^(3))_(2)((4^(6).6^(18).8^(4)))),respectively.This structural differentiation confirms the precise regulatory role of ligands on the topology of metal-organic frameworks.Moreover,the ultraviolet-visible absorption spectra confirmed that HU23 and HU24 have strong absorption capabilities for ultraviolet and visible light.According to the Kubelka-Munk method,their bandwidths were 2.15 and 2.08 eV,respectively,which are consistent with those of typical semiconductor materials.Variable-temperature magnetic susceptibility measurements(2-300 K)revealed significant antiferromagnetic coupling in both complexes,with their effective magnetic moments decreasing markedly as the temperature lowered.CCDC:2457554,HU23;2457553,HU24.
基金supported in part by the National Natural Science Foundation of China,Grant/Award Number:62003267the Key Research and Development Program of Shaanxi Province,Grant/Award Number:2023-GHZD-33Open Project of the State Key Laboratory of Intelligent Game,Grant/Award Number:ZBKF-23-05。
文摘To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance data-driven event-triggered fusion control method,which achieves efficient fault diagnosis while suppressing random disturbances and mitigating communication conflicts within the QUAV swarm.First,the impact of random disturbances on the UAV swarm is analyzed,and a model for orientation and attitude control of QUAVs under stochastic perturbations is established,with the disturbance gain threshold determined.Second,a fault diagnosis system based on a high-gain observer is designed,constructing a fault gain criterion by integrating orientation and attitude information from QUAVs.Subsequently,a model-free dynamic linearization-based data modeling(MFDLDM)framework is developed using model-free adaptive control,which efficiently fits the nonlinear control model of the QUAV swarm while reducing temporal constraints on control data.On this basis,this paper constructs a distributed data-driven event-triggered controller based on the staggered communication mechanism,which consists of an equivalent QUAV controller and an event-triggered controller,and is able to reduce the communication conflicts while suppressing the influence of random interference.Finally,by incorporating random disturbances into the controller,comparative experiments and physical validations are conducted on the QUAV platforms,fully demonstrating the strong adaptability and robustness of the proposed distributed event-triggered fault-tolerant control system.
基金supported by the National Key R&D Program of China(Grant No.2023YFC3209504)Natural Science Foundation of Wuhan(Grant No.2024040801020271)the Fundamental Research Funds for Central Public Welfare Research Institutes(Grant No.CKSF2025718/YT).
文摘Wetting deformation in earth-rockfill dams is a critical factor influencingdam safety.Although numerous mathematical models have been developed to describe this phenomenon,most of them rely on empirical formulations and lack prior knowledge of model parameters,which is essential for Bayesian parameter inversion to enhance accuracy and reduce uncertainty.This study introduces a datadriven approach to establishing prior knowledge of earth-rockfill dams.Driving factors are utilized to determine the potential range of model parameters,and settlement changes within this range are calculated.The results are iteratively compared with actual monitoring data until the calculated range encompasses the observed data,thereby providing prior knowledge of the model parameters.The proposed method is applied to the right-bank earth-rockfilldam of Danjiangkou.Employing a Gibbs sample size of 30,000,the proposed method effectively calibrates the prior knowledge of the wetting model parameters,achieving a root mean square error(RMSE)of 5.18 mm for the settlement predictions.By comparison,the use of non-informative priors with sample sizes of 30,000 and 50,000 results in significantly larger RMSE values of 11.97 mm and 16.07 mm,respectively.Furthermore,the computational efficiencyof the proposed method is demonstrated by an inversion computation time of 902 s for 30,000 samples,which is notably shorter than the 1026 s and 1558 s required for noninformative priors with 30,000 and 50,000 samples,respectively.These findingsunderscore the superior performance of the proposed approach in terms of both prediction accuracy and computational efficiency.These results demonstrate that the proposed method not only improves the predictive accuracy but also enhances the computational efficiency,enabling optimal parameter identificationwith reduced computational effort.This approach provides a robust and efficientframework for advancing dam safety assessments.
基金The Shandong Provincial Natural Science Foundation(Grant No.ZR2022JQ18)supported this worksupported by the National Natural Science Foundation of China(NNFSC)Youth Program(Grant No.42304168)+1 种基金supported by the National Key R&D Program of China(Grant No.2022YFF0504400)the NNSFC(Grant Nos.42188101 and 42174210)。
文摘Storm-enhanced density(SED)and the tongue of ionization(TOI)are key ionospheric storm-time structures whose rapid evolution and fine-scale variability remain challenging to capture with conventional empirical high-latitude drivers.In this study,we examine the May 10–11,2024,superstorm using the Thermosphere–Ionosphere–Electrodynamics General Circulation Model(TIEGCM)with observation-constrained high-latitude forcing.Auroral precipitation parameters(energy flux and mean energy)are assimilated from a Defense Meteorological Satellite Program(DMSP)Special Sensor Ultraviolet Spectrographic Imager(SSUSI)using a multi-resolution Gaussian process(Lattice Kriging)approach,whereas high-latitude convection potentials are derived by assimilating Super Dual Auroral Radar Network(SuperDARN)observations with the Thomas and Shepherd(2018)model(TS18).For comparison,an additional simulation is performed using empirical models for both convection and auroral forcing.The results show that during the main phase of the May 10 storm,the data-driven simulation provides a more realistic depiction of the SED source region than does the empirical model run by capturing its rapid intensification more clearly and reproducing its spatial location and structural features with higher fidelity.These improvements lead to a more accurate representation of its poleward extension into the polar cap that develops into the TOI.Above the ionospheric F2 peak over the SED source region,SuperDARN-constrained potentials generate stronger and more localized E×B drifts that dominate plasma uplift and drive its transport into the polar cap,although neutral winds and downward ambipolar diffusion partially offset these effects.Below the F2 peak,neutral winds and photochemical processes play a major role in shaping the spatial extent and intensity of the SED and TOI.These results highlight the role of observation-constrained high-latitude drivers in representing ionosphere–thermosphere responses during extreme storms and suggest their relevance for improving physical interpretation and model performance.
基金supported by the National Key R&D Program of China(No.2022YFA1504100)the Anhui Provincial Major Science and Technology Project(No.202203a05020017)+4 种基金the National Natural Science Foundation of China(Nos.52222210,51925207,U1910210,52161145101,51972067,51902062,and 52002083)the“Transformational Technologies for Clean Energy and Demonstration”Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA21000000)the National Synchrotron Radiation Laboratory(No.KY2060000173)the Joint Fund of the Yulin University and the Dalian National Laboratory for Clean Energy(No.YLU-DNL Fund 2021002)the Fundamental Research Funds for the Central Universities(No.WK2060140026)。
文摘Silicon possesses a high theoretical capacity,making it a potential contender for lithium-ion battery(LIB)anodes.Nonetheless,its practical usage is challenged by low electrical conductivity and significant volume expansion during cycling.Here,we synthesized a novel silicon/carbon(Si/C)anode doped with ZnO via a template-derived method and high-temperature carbonization.The carbon structure,originated from metal-organic frameworks(MOFs)and ZnO doping,substantially enhanced the electrochemical properties of the composite material.It exhibited an initial capacity of 2100.3 mA h g^(-1)at a current density of 0.2 A g^(-1)and demonstrated excellent capacity retention over successive cycles.Moreover,the composite material displayed superior rate performance at higher current densities of 2 A g^(-1)and 3 A g^(-1).To address the low initial Coulombic efficiency(ICE)of siliconbased materials,we adopted a direct contact prelithiation approach and optimized the lithiation process by controlling the prelithiation time.After 30 min of prelithiation,the ICE reached 97.9%,thereby reducing the initial irreversible capacity loss(ICL)and realizing stable discharge-charge in subsequent cycles.This rational design provides valuable insights for achieving high-performance silicon anode.
基金the Natural Science Foundation of ZhejiangProvince(No.LZ24B020005)the National Natural Science Foundation of China(No.22071040)for financial support.
文摘High-sensitive quantitative determination of alpha-fetoprotein(AFP)is of crucial importance for early clinical diagnosis of cancers.Herein,an AuNPs-free electrochemical immunosensor(Ab1-Fc-COF)was prepared from a carboxylic group enriched COF by post-functionalization with detecting antibody(Ab1)and ferrocene(Fc),and used for electrochemical detection of AFP.Due to the small,homogeneous pore size of the COF,Ab1 with a big size was immobilized on the surface of the COF,while Fc with a small size was covalently modified both on the surface and in the pores of COF.The covalently immobilized Ab1 was quite stable and beneficial to specifically detect AFP biomarkers.Meanwhile,the enriched Fc molecules not only improved the conductivity of the COF,but also effectively transferred and amplified the electrochemical signal.This proposed immunosensor exhibited high sensitivity in detecting AFP with a detection limit of 0.39 pg/mL(S/N of 3:1)and a wide linear response range spanning from 1 pg/mL to 100 ng/mL when plotted against logarithmic concentrations.Furthermore,this immunosensor showed excellent selectivity,stability and reproducibility in the testing of real samples.This study presents an innovative prototype for construction of a precious metal-free,antibody-directly-immobilized,simple and stable electrochemical immunoprobe.
基金the Hebei Province Science and Technology Plan Project(19221909D)rincess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R308),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Autonomous connected vehicles(ACV)involve advanced control strategies to effectively balance safety,efficiency,energy consumption,and passenger comfort.This research introduces a deep reinforcement learning(DRL)-based car-following(CF)framework employing the Deep Deterministic Policy Gradient(DDPG)algorithm,which integrates a multi-objective reward function that balances the four goals while maintaining safe policy learning.Utilizing real-world driving data from the highD dataset,the proposed model learns adaptive speed control policies suitable for dynamic traffic scenarios.The performance of the DRL-based model is evaluated against a traditional model predictive control-adaptive cruise control(MPC-ACC)controller.Results show that theDRLmodel significantly enhances safety,achieving zero collisions and a higher average time-to-collision(TTC)of 8.45 s,compared to 5.67 s for MPC and 6.12 s for human drivers.For efficiency,the model demonstrates 89.2% headway compliance and maintains speed tracking errors below 1.2 m/s in 90% of cases.In terms of energy optimization,the proposed approach reduces fuel consumption by 5.4% relative to MPC.Additionally,it enhances passenger comfort by lowering jerk values by 65%,achieving 0.12 m/s3 vs.0.34 m/s3 for human drivers.A multi-objective reward function is integrated to ensure stable policy convergence while simultaneously balancing the four key performance metrics.Moreover,the findings underscore the potential of DRL in advancing autonomous vehicle control,offering a robust and sustainable solution for safer,more efficient,and more comfortable transportation systems.
基金Liaoning Provincial Social Science Fund Key Disciplines Development Project,Research on the New Supply Function of Entrepreneurs Based on Innovation Ecosystems Driven by Data(Grant No.L22ZD061)。
文摘Accelerating the development of new quality productive forces(NQPF),with innovation at its core,has become essential for firm growth in the new era.Drawing on financial data from China's A-share listed companies spanning the period 2010–2023,this study empirically investigates the impact of entrepreneurial spirit on firm-level NQPF.The results indicate that entrepreneurial spirit significantly promotes firm-level NQPF.Mechanism analysis indicates that entrepreneurial effort—underpinned by technological capital accumulation,effective incentive and constraint mechanisms,and a competitive market environment—plays a mediating role in this relationship.Further heterogeneity analysis reveals that,amid China's economic transition,the positive effects of entrepreneurial spirit are more pronounced in non-state-owned enterprises,high-tech firms,and newly established firms.Accordingly,systematic efforts should be pursued across the technological,organizational,and environmental(TOE)dimensions to optimize the cultivation of entrepreneurial spirit.In particular,greater emphasis should be placed on productive entrepreneurial spirit and the constructive role of entrepreneurial effort,so as to fully leverage their contribution to the advancement of firm-level NQPF.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(RS-2024-00333650)supported by basic science research program through the National Research Foundation of Korea funded by the Ministry of Education(NRF-2019R1A6A1A11055660)+1 种基金supported by the Technology Innovation Program(“20013621”,Center for Super Critical Material Industrial Technology)funded By the Ministry of Trade,Industry&Energy(MOTIE,Korea)supported by Strategic Networking&Development Program funded by the Ministry of Science and ICT through the National Research Foundation of Korea(RS-2023-00268523)。
文摘Gas sensors are valuable tools for human applications,and extensive research has been conducted in this field.However,practical implementation has yet to be fully realized.In response,efforts have been made to explore metal-organic frameworks(MOFs),a novel class of porous materials,as potential solutions.MOFs exhibit exceptional porosity and highly tunable chemical compositions and structures,giving rise to a wide range of unique physical and chemical properties.Significant progress has been achieved in developing MOF-based gas sensors,improving sensing performance for various gases.This review aims to provide a comprehensive understanding of MOF-based gas sensors,even for readers unfamiliar with MOFs and gas sensors.It covers the working principles of these sensors,fundamental concepts of MOFs,strategies for tuning MOF properties,fabrication techniques for MOF films,and recent studies on MOF and MOF-derivative gas sensors.Finally,current challenges,overlooked aspects,and future directions for fully exploiting the potential of MOFs in gas sensor development are discussed.
基金financially supported by the National Natural Science foundation of China(grants nos.52272176)。
文摘Lead-halide perovskite solar cells(PSCs)have rapidly achieved certified efficiencies>27%,rivaling silicon photovoltaics.However,their commercialization is hindered by intrinsic material challenges:poor operational stability under moisture,heat,and light;toxic lead leakage from degraded films.Metal-organic frameworks(MOFs),with their unique framework structure,large specific surface area,high heavy metal capturing capacity,and tunable conductivity,offer promising solutions to these issues.Recent studies have integrated MOFs into PSCs architectures to enhance performance and durability.This comprehensive review begins with an in-depth discussion of the structure,optical properties,electrical characteristics,and stability of MOFs,as well as their theoretical compatibility with perovskites.Subsequently,it provides a detailed analysis of how MOFs enhance charge carrier transport,promote perovskite crystallinity,improve device stability,and suppress lead leakage in PSCs.In summary,this review examines the research progress and potential of integrating MOFs with perovskites to address the critical PSCs challenges of efficiency,instability,and toxicity.
基金funded by the National Natural Science Foundation of China(Nos.52372264,32271609and 52473109)+2 种基金The Natural Science Foundation of Heilongjiang Province of China(No.LH2023B002)The Fundamental Research Funds for the Central Universities(No.2572023CT12)Undergraduate Training Programs for Innovations by NEFU(No.202310225565)。
文摘Metal-organic frameworks(MOFs)with high porosity,specific surface area,and unique topologies are highly regarded for their applications in photocatalysis,medical treatment,and environmental pollutant degradation.However,due to the limitations of the tumor microenvironment(TME),traditional MOFs have limited efficacy in this environment.This paper designs multi-metal oxide-based heterostructure POMOFs nanoreactors with a nesting doll-like structure.This new structure not only exhibits therapeutic effects in TME but also utilizes ultrasound(US)to enhance the release of reactive oxygen species(ROS)for CDT&SDT co-therapy,becoming an effective sound sensitizer for destroying tumor cells.In summary,our study proposes an idea for constructing multi-metal oxide-based heterostructure MOFs nanoreactors material with a nesting doll-like structure to enhance ROS release and synergistically treat tumor diseases.
