Traditional source-to-sink analyses cannot effectively characterize deep-time sedimentary processes involving multiple sediment sources and the spatiotemporal evolution of sediment contributions from different sources...Traditional source-to-sink analyses cannot effectively characterize deep-time sedimentary processes involving multiple sediment sources and the spatiotemporal evolution of sediment contributions from different sources.In this study,a dynamic,quantitative source-to-sink analysis approach using stratigraphic forward modeling(SFM)is proposed,and it is applied to the Paleogene Enping Formation in the Baiyun Sag,Pearl River Mouth Basin.The built-in spatiotemporal provenance tagging of the model assigns a unique time-source label to sediments from each provenance,making each source's contribution identifiably“labeled”in the simulated formation,and thus enabling a direct precise tracking and high spatiotemporal resolution quantification of such contributions.Five pseudo-wells(from proximal to distal locations)in the Baiyun Sag were analyzed.The simulation results quantitatively represent the varied proportion of contribution of each source at different locations and in different periods and verify the proposed approach's operability and accuracy of the proposed approach.The simulated 3D deposit distribution shows a high agreement with the measured stratigraphic data,validating the model's reliability.Results reveal significant spatiotemporal changes in the Enping sedimentary system.In the late stage of Enping Formation deposition,a distal source supply from the northern part of the sag became dominant,the depocenter migrated northward to the deepwater area,and large-scale deltaic sand bodies extensively progradating into the sag were formed.The modeled 3D deposit distribution indicates that extensive high-quality reservoir sandstones are likely present across the deepwater area of the Baiyun Sag,which are identified as key exploration targets.Compared to traditional static approaches,the SFM-based dynamic simulation markedly enhances the spatiotemporal resolution of source-to-sink analysis and quantitatively captures the sedimentary system's responses to tectonic activity,base-level fluctuations and other external drivers.The proposed approach provides a novel quantitative framework for investigating complex,deep-time,multi-source systems,and offers an effective tool for reservoir prediction and hydrocarbon exploration planning in underexplored deepwater areas.展开更多
Due to open communication environment,Internet of Vehicles(IoV)are vulnerable to many attacks,including the gray hole attack,which can disrupt the process of transmitting messages.And this results in the degradation o...Due to open communication environment,Internet of Vehicles(IoV)are vulnerable to many attacks,including the gray hole attack,which can disrupt the process of transmitting messages.And this results in the degradation of routing performance.To address this issue,a double deep Q-networks-based stable routing for resisting gray hole attack(DOSR)is proposed in this paper.The aim of the DOSR algorithm is to maximize the message delivery ratio as well as to minimize the transmission delay.For this,the distance ratio,message loss ratio,and connection ratio are taken into consideration when choosing a relay node.Then,to choose the relay node is formulated as an optimization problem,and a double deep Q-networks are utilized to solve the optimization problem.Experimental results show that DOSR outperforms QLTR and TLRP by significant margins:in scenarios with 400 vehicles and 10%malicious nodes,the message delivery ratio(MDR)of DOSR is 8.3%higher than that of QLTR and 5.1%higher than that of TLRP;the average transmission delay(ATD)is reduced by 23.3%compared to QLTR and 17.9%compared to TLRP.Additionally,sensitivity analysis of hyperparameters confirms the convergence and stability of DOSR,demonstrating its robustness in dynamic IoV environments.展开更多
Data privacy leakage has always been a critical concern in cloud-based Internet of Things(IoT)systems.Dynamic Symmetric Searchable Encryption(DSSE)with forward and backward privacy aims to address this issue by enabli...Data privacy leakage has always been a critical concern in cloud-based Internet of Things(IoT)systems.Dynamic Symmetric Searchable Encryption(DSSE)with forward and backward privacy aims to address this issue by enabling updates and retrievals of ciphertext on untrusted cloud server while ensuring data privacy.However,previous research on DSSE mostly focused on single keyword search,which limits its practical application in cloud-based IoT systems.Recently,Patranabis(NDSS 2021)[1]proposed a groundbreaking DSSE scheme for conjunctive keyword search.However,this scheme fails to effectively handle deletion operations in certain circumstances,resulting in inaccurate query results.Additionally,the scheme introduces unnecessary search overhead.To overcome these problems,we present CKSE,an efficient conjunctive keyword DSSE scheme.Our scheme improves the oblivious shared computation protocol used in the scheme of Patranabis,thus enabling a more comprehensive deletion functionality.Furthermore,we introduce a state chain structure to reduce the search overhead.Through security analysis and experimental evaluation,we demonstrate that our CKSE achieves more comprehensive deletion functionality while maintaining comparable search performance and security,compared to the oblivious dynamic cross-tags protocol of Patranabis.The combination of comprehensive functionality,high efficiency,and security makes our CKSE an ideal choice for deployment in cloud-based IoT systems.展开更多
The airborne electromagnetic （AEM） method has a high sampling rate and survey flexibility. However, traditional numerical modeling approaches must use high-resolution physical grids to guarantee modeling accuracy, e...The airborne electromagnetic （AEM） method has a high sampling rate and survey flexibility. However, traditional numerical modeling approaches must use high-resolution physical grids to guarantee modeling accuracy, especially for complex geological structures such as anisotropic earth. This can lead to huge computational costs. To solve this problem, we propose a spectral-element （SE） method for 3D AEM anisotropic modeling, which combines the advantages of spectral and finite-element methods. Thus, the SE method has accuracy as high as that of the spectral method and the ability to model complex geology inherited from the finite-element method. The SE method can improve the modeling accuracy within discrete grids and reduce the dependence of modeling results on the grids. This helps achieve high-accuracy anisotropic AEM modeling. We first introduced a rotating tensor of anisotropic conductivity to Maxwell＇s equations and described the electrical field via SE basis functions based on GLL interpolation polynomials. We used the Galerkin weighted residual method to establish the linear equation system for the SE method, and we took a vertical magnetic dipole as the transmission source for our AEM modeling. We then applied fourth-order SE calculations with coarse physical grids to check the accuracy of our modeling results against a 1D semi-analytical solution for an anisotropic half-space model and verified the high accuracy of the SE. Moreover, we conducted AEM modeling for different anisotropic 3D abnormal bodies using two physical grid scales and three orders of SE to obtain the convergence conditions for different anisotropic abnormal bodies. Finally, we studied the identification of anisotropy for single anisotropic abnormal bodies, anisotropic surrounding rock, and single anisotropic abnormal body embedded in an anisotropic surrounding rock. This approach will play a key role in the inversion and interpretation of AEM data collected in regions with anisotropic geology.展开更多
AVO forward modeling is based on two-phase medium theory and is considered an effective method for describing reservoir rocks and fluids. However, the method depends on the input matrix mineral bulk modulus and the ra...AVO forward modeling is based on two-phase medium theory and is considered an effective method for describing reservoir rocks and fluids. However, the method depends on the input matrix mineral bulk modulus and the rationality of the two-phase medium model. We used the matrix mineral bulk modulus inversion method and multiple constraints to obtain a two-phase medium model with physical meaning. The proposed method guarantees the reliability of the obtained AVO characteristicsin two-phase media. By the comparative analysis of different lithology of the core sample, the advantages and accuracy of the inversion method can be illustrated. Also, the inversion method can be applied in LH area, and the AVO characteristics can be obtained when the porosity, fluid saturation, and other important lithology parameters are changed. In particular, the reflection coefficient amplitude difference between the fast P wave and S wave as a function of porosity at the same incidence angle, and the difference in the incidence angle threshold can be used to decipher porosity.展开更多
In the Chinese lunar calendar,2026 ushers in the Year of the Horse,a creature that has carried humanity across continents and through centuries.More than a marker of time,the horse embodies vitality,courage,and the re...In the Chinese lunar calendar,2026 ushers in the Year of the Horse,a creature that has carried humanity across continents and through centuries.More than a marker of time,the horse embodies vitality,courage,and the relentless spirit to move forward,qualities that resonate not only in China but across the landscapes of many African societies.展开更多
Hepatitis B Virus(HBV)infection and heavy alcohol consumption are the two primary pathogenic causes of liver cirrhosis.In this paper,we proposed a deterministic mathematical model and a logistic equation to investigat...Hepatitis B Virus(HBV)infection and heavy alcohol consumption are the two primary pathogenic causes of liver cirrhosis.In this paper,we proposed a deterministic mathematical model and a logistic equation to investigate the dynamics of liver cirrhosis progression as well as to explain the implications of variations in alcohol consumption on chronic hepatitis B patients,respectively.The intricate interactions between liver cirrhosis,recovery,and treatment dynamics are captured by the model.This study aims to show that alcohol consumption by Hepatitis B-infected individuals accelerates liver cirrhosis progression while treatment of acutely infected individuals reduces it.We proved that a unique solution of the proposed model exists,which is positive and bounded.Using the next-generation matrix approach,two basic reproductive numbers R_(A_(0))and R_(A_(max))are calculated to identify future recurrence.The equilibrium points are calculated,and both equilibria are proved locally and globally asymptotically stable when R_(0)is below and above one,respectively.It is shown that bifurcation exists at R_(0)=1 and a detailed proof for forward bifurcation is given.Furthermore,we performed the sensitivity analysis of the model parameters on R_(0).For the confirmation of analytical work,we performed numerical simulations,and the results indicate that the treatment and the inhibitory effects reduce the risk of developing liver cirrhosis in individuals,while heavy alcohol consumption accelerates markedly the liver cirrhosis progression in patients with chronic hepatitis B.展开更多
Ground penetrating radar(GPR)offers a rapid and non-destructive approach to evaluating asphalt mixtures by capturing variations in their dielectric constant.As a critical electromagnetic parameter,the dielectric const...Ground penetrating radar(GPR)offers a rapid and non-destructive approach to evaluating asphalt mixtures by capturing variations in their dielectric constant.As a critical electromagnetic parameter,the dielectric constant demonstrates significant potential for assessing the material composition and mechanical properties of asphalt mixtures.However,the relationship between the dielectric constant and mechanical properties remains unclear.To investigate the factors affecting the dielectric constant and its correlation with the mechanical properties of asphalt mixtures,a systematic analysis of the influencing parameters was conducted.Fitting equations were established to quantify the relationships between the dielectric constant and mechanical properties.Firstly,the effects of compaction state,testing frequency,and testing temperature on the dielectric constant were evaluated.Subsequently,forward simulations of GPR were executed on asphalt pavements with diverse air voids and detection frequencies.Finally,a fitting analysis was performed to determine the correlation between the dielectric constant and the dynamic modulus,compressive strength,and splitting tensile strength.The results indicated that the dielectric constant increased with the compaction state,decreased with increasing testing frequency until stabilized,and was insignificantly affected by changes in testing temperature.The change of air void in asphalt pavement has significantly affected the amplitude and timing of electromagnetic wave reflection.A linear positive correlation was identified between the dielectric constant and dynamic modulus as well as compressive strength,while a quadratic positive correlation existed with splitting tensile strength.This study provided theoretical and practical foundations for enhancing the reliability and accuracy of non-destructive testing in asphalt pavement.展开更多
The“Forward Together”Dialogue on Building a China-Brunei Community with a Shared Future was held on the morning of February 7 at Universiti Brunei Darussalam(UBD)in Bandar Seri Begawan.Scheduled for the lead-up to t...The“Forward Together”Dialogue on Building a China-Brunei Community with a Shared Future was held on the morning of February 7 at Universiti Brunei Darussalam(UBD)in Bandar Seri Begawan.Scheduled for the lead-up to the 35th anniversary of diplomatic relations between China and Brunei in 2026,the event aimed to deepen strategic mutual trust,build broader consensus on cooperation,and generate both intellectual momentum and practical proposals for advancing a closer China-Brunei community with a shared future.展开更多
Chinese President Xi Jinping has guided China through a year of resilient growth via forward-looking reforms and innovation-driven transformation that is shaping the nation’s economic trajectory for 2026 and beyond.
Plasmas,the most common state of matter in the observable universe,are subject to instabilities of various types:hydrodynamic,magnetohydrodynamic,and electromagnetic.Our limited success in understanding these is due t...Plasmas,the most common state of matter in the observable universe,are subject to instabilities of various types:hydrodynamic,magnetohydrodynamic,and electromagnetic.Our limited success in understanding these is due to the lack of direct experimental information on their origins and evolution.Here,we present direct spatially resolved measurements of the femtosecond evolution of the electromagnetic beam-driven instability that arises from the interaction of forward and return currents in an ultrahigh-intensity laser-produced plasma.We track its evolution from the initial linear stage to the later nonlinear stage by measuring the spatiotemporal evolution of the giant(megagauss)magnetic field created in the interaction process.Our experimental findings and numerical simulations are the first to indicate the observed instability triggered by the emission of electromagnetic radiation,like those known in the context of gravitational interaction,where the emission of gravitational radiation drives specific negative-energy modes in rotating black holes or neutron stars.展开更多
The forward model of optical fiber strain induced by fractures,together with the associated model resolution matrix,is used to demonstrate the interpretability of fracture parameters once the fracture intersects the f...The forward model of optical fiber strain induced by fractures,together with the associated model resolution matrix,is used to demonstrate the interpretability of fracture parameters once the fracture intersects the fiber.A regularized inversion framework for fracture parameters is established to evaluate the influence of measured data quality on the accuracy of iterative regularized inversion.An interpretation approach for both fracture width and height is proposed,and the synthetic forward data with measurement error and field examples are employed to validate the accuracy of the simultaneous inversion of fracture width and height.The results indicate that,after the fracture contacts the fiber,the strain response is strongly sensitive only to the fracture parameters at the intersection location,whereas the interpretability of parameters at other locations remains limited.The iterative regularized inversion method effectively suppresses the impact of measurement error and exhibits high computational efficiency,showing clear advantages for inversion applications.When incorporating the first-order regularization with a Neumann boundary constraint on the tip width,the inverted fracture-width distribution becomes highly sensitive to fracture height;thus,combined with a bisection strategy,simultaneous inversion of fracture width and height can be achieved.Examination using the model resolution matrix,noisy synthetic data,and field data confirms that the iterative regularized inversion model for fracture width and height provides high interpretive accuracy and can be applied to the calculation and analysis of fracture width,fracture height,net pressure and other parameters.展开更多
Pod shattering,while a natural mechanism for seed dispersal,is an undesirable agronomic trait in rapeseed(Brassica napus L.)that complicates mechanical harvesting.It typically causes yield losses of 5%-15%,which can b...Pod shattering,while a natural mechanism for seed dispersal,is an undesirable agronomic trait in rapeseed(Brassica napus L.)that complicates mechanical harvesting.It typically causes yield losses of 5%-15%,which can be further worsened under dry and hot conditions.As most of the modern rapeseed cultivars remain susceptible to shattering,enhancing pod shattering resistance(PSR)is important to safeguard global rapeseed production.Significant progresses have been made in elucidating the molecular and genetic mechanisms of silique dehiscence in the model plant Arabidopsis and pod shattering in rapeseed.This review firstly summarizes the genetic network controlling silique dehiscence in Arabidopsis,which is largely conserved in closely related Brassica species.We then synthesize discoveries from both forward and reverse genetic studies in rapeseed.Finally,the major challenges and future prospects in PSR research and breeding are discussed in depth.展开更多
Sensitivity of observational data is important in the study of Glacial Isostatic Adjustment(GIA).However,depending on whether sensitivity is used for the Inverse Problem or the Forward Problem,the final formulation an...Sensitivity of observational data is important in the study of Glacial Isostatic Adjustment(GIA).However,depending on whether sensitivity is used for the Inverse Problem or the Forward Problem,the final formulation and display of the sensitivity kernel will be different.Unfortunately,in the past,both perspectives give the same name to their quantity computed/displayed,and that has caused some confusion.To distinguish between the two,their perspective should be added to the names.This paper focuses only on the perspective of the Forward Problem where the input parameters are known.The Perturbation method has been successfully used in the computation of the sensitivity kernels of observations on 1D and 3D viscosity variations from the Forward perspective.One aim of this paper is to review and clarify the physics of the Perturbation method and bring out some important aspects of this method that have been misunderstood or neglected.Another aim is to present sensitivity kernels from the Perturbation method using 3D(both radially and laterally heterogeneous)Earth models with realistic ice history.These new results are now suitable for future comparison with those from new methods using the Forward perspective.Finally,the sensitivity computations for realistic ice histories on a 3D Earth is reviewed and used to search for optimal locations of new GIA observations.展开更多
Physics-informed neural networks(PINNs),as a novel artificial intelligence method for solving partial differential equations,are applicable to solve both forward and inverse problems.This study evaluates the performan...Physics-informed neural networks(PINNs),as a novel artificial intelligence method for solving partial differential equations,are applicable to solve both forward and inverse problems.This study evaluates the performance of PINNs in solving the temperature diffusion equation of the seawater across six scenarios,including forward and inverse problems under three different boundary conditions.Results demonstrate that PINNs achieved consistently higher accuracy with the Dirichlet and Neumann boundary conditions compared to the Robin boundary condition for both forward and inverse problems.Inaccurate weighting of terms in the loss function can reduce model accuracy.Additionally,the sensitivity of model performance to the positioning of sampling points varied between different boundary conditions.In particular,the model under the Dirichlet boundary condition exhibited superior robustness to variations in point positions during the solutions of inverse problems.In contrast,for the Neumann and Robin boundary conditions,accuracy declines when points were sampled from identical positions or at the same time.Subsequently,the Argo observations were used to reconstruct the vertical diffusion of seawater temperature in the north-central Pacific for the applicability of PINNs in the real ocean.The PINNs successfully captured the vertical diffusion characteristics of seawater temperature,reflected the seasonal changes of vertical temperature under different topographic conditions,and revealed the influence of topography on the temperature diffusion coefficient.The PINNs were proved effective in solving the temperature diffusion equation of seawater with limited data,providing a promising technique for simulating or predicting ocean phenomena using sparse observations.展开更多
Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This stu...Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller(NFIDC)with a Feedback Radial Basis Function Neural Network(FRBFNN).The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1.The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.A two-stage simulation evaluation was conducted.In the first stage,the controller was tested in a simulated hospital environment under both ideal and non-ideal conditions.In the second,it was benchmarked against four established controllers-Neural Network Model Reference Adaptive(NNMRA),Z-number Fuzzy Logic(Z-FL),Adaptive Dynamic Controller(ADC),and Fuzzy Logic-PID(FL-PID)—using circular and lemniscate trajectories.Across ten runs,the proposed controller achieved the lowest tracking errors under all conditions.Under ideal conditions,it achieved average improvements of 55.24%,75.75%,and 55.20%in integral absolute error(IAE),integral squared error(ISE),and mean absolute error(MAE),respectively,with coefficient of variation(CV)reductions above 55%.Under non-ideal conditions,average improvements exceeded 64%in IAE,77%in ISE,and 66%in MAE,while maintaining CV reductions above 57%.These results confirm that the NFIDC-FRBFNN controller offers superior accuracy,robustness,and consistency for real-time path tracking in healthcare robotics.展开更多
This study examined the spatio-temporal trajectories of the international freight forwarding service(IFFS) in the Yangtze River Delta(YRD) and explored the driving mechanisms of the service. Based on a bipartite netwo...This study examined the spatio-temporal trajectories of the international freight forwarding service(IFFS) in the Yangtze River Delta(YRD) and explored the driving mechanisms of the service. Based on a bipartite network projection from an IFFS firm-city data source, we mapped three IFFS networks in the YRD in 2005, 2010, and 2015. A range of statistical indicators were used to explore changes in the spatial patterns of the three networks. The underlying influence of marketization, globalization, decentralization, and integration was then explored. It was found that the connections between Shanghai and other nodal cities formed the backbones of these networks. The effects of a city's administrative level and provincial administrative borders were generally obvious. We found several specific spatial patterns associated with IFFS. For example, the four non-administrative centers of Ningbo, Suzhou, Lianyungang, and Nantong were the most connected cities and played the role of gateway cities. Furthermore, remarkable regional equalities were found regarding a city's IFFS network provision, with notable examples in the weakly connected areas of northern Jiangsu and southwestern Zhejiang. Finally, an analysis of the driving mechanisms demonstrated that IFFS network changes were highly sensitive to the influences of marketization and globalization, while regional integration played a lesser role in driving changes in IFFS networks.展开更多
The Space-Air-Ground Integrated Network(SAGIN) realizes the integration of space, air,and ground networks, obtaining the global communication coverage.Software-Defined Networking(SDN) architecture in SAGIN has become ...The Space-Air-Ground Integrated Network(SAGIN) realizes the integration of space, air,and ground networks, obtaining the global communication coverage.Software-Defined Networking(SDN) architecture in SAGIN has become a promising solution to guarantee the Quality of Service(QoS).However, the current routing algorithms mainly focus on the QoS of the service, rarely considering the security requirement of flow. To realize the secure transmission of flows in SAGIN, we propose an intelligent flow forwarding scheme with endogenous security based on Mimic Defense(ESMD-Flow). In this scheme, SDN controller will evaluate the reliability of nodes and links, isolate malicious nodes based on the reliability evaluation value, and adapt multipath routing strategy to ensure that flows are always forwarded along the most reliable multiple paths. In addition, in order to meet the security requirement of flows, we introduce the programming data plane to design a multiprotocol forwarding strategy for realizing the multiprotocol dynamic forwarding of flows. ESMD-Flow can reduce the network attack surface and improve the secure transmission capability of flows by implementing multipath routing and multi-protocol hybrid forwarding mechanism. The extensive simulations demonstrate that ESMD-Flow can significantly improve the average path reliability for routing and increase the difficulty of network eavesdropping while improving the network throughput and reducing the average packet delay.展开更多
This work investigates the performance of various forward error correction codes, by which the MIMO-OFDM system is deployed. To ensure fair investigation, the performance of four modulations, namely, binary phase shif...This work investigates the performance of various forward error correction codes, by which the MIMO-OFDM system is deployed. To ensure fair investigation, the performance of four modulations, namely, binary phase shift keying(BPSK), quadrature phase shift keying(QPSK), quadrature amplitude modulation(QAM)-16 and QAM-64 with four error correction codes(convolutional code(CC), Reed-Solomon code(RSC)+CC, low density parity check(LDPC)+CC, Turbo+CC) is studied under three channel models(additive white Guassian noise(AWGN), Rayleigh, Rician) and three different antenna configurations(2×2, 2×4, 4×4). The bit error rate(BER) and the peak signal to noise ratio(PSNR) are taken as the measures of performance. The binary data and the color image data are transmitted and the graphs are plotted for various modulations with different channels and error correction codes. Analysis on the performance measures confirm that the Turbo + CC code in 4×4 configurations exhibits better performance.展开更多
基金Supported by the National Natural Science Foundation of China(92055204)Strategic Priority Research Program of the Chinese Academy of Sciences(Class A)(XDA14010401)China National Offshore Oil Corporation(CNOOC)(CCL2021SKPS0118)。
文摘Traditional source-to-sink analyses cannot effectively characterize deep-time sedimentary processes involving multiple sediment sources and the spatiotemporal evolution of sediment contributions from different sources.In this study,a dynamic,quantitative source-to-sink analysis approach using stratigraphic forward modeling(SFM)is proposed,and it is applied to the Paleogene Enping Formation in the Baiyun Sag,Pearl River Mouth Basin.The built-in spatiotemporal provenance tagging of the model assigns a unique time-source label to sediments from each provenance,making each source's contribution identifiably“labeled”in the simulated formation,and thus enabling a direct precise tracking and high spatiotemporal resolution quantification of such contributions.Five pseudo-wells(from proximal to distal locations)in the Baiyun Sag were analyzed.The simulation results quantitatively represent the varied proportion of contribution of each source at different locations and in different periods and verify the proposed approach's operability and accuracy of the proposed approach.The simulated 3D deposit distribution shows a high agreement with the measured stratigraphic data,validating the model's reliability.Results reveal significant spatiotemporal changes in the Enping sedimentary system.In the late stage of Enping Formation deposition,a distal source supply from the northern part of the sag became dominant,the depocenter migrated northward to the deepwater area,and large-scale deltaic sand bodies extensively progradating into the sag were formed.The modeled 3D deposit distribution indicates that extensive high-quality reservoir sandstones are likely present across the deepwater area of the Baiyun Sag,which are identified as key exploration targets.Compared to traditional static approaches,the SFM-based dynamic simulation markedly enhances the spatiotemporal resolution of source-to-sink analysis and quantitatively captures the sedimentary system's responses to tectonic activity,base-level fluctuations and other external drivers.The proposed approach provides a novel quantitative framework for investigating complex,deep-time,multi-source systems,and offers an effective tool for reservoir prediction and hydrocarbon exploration planning in underexplored deepwater areas.
文摘Due to open communication environment,Internet of Vehicles(IoV)are vulnerable to many attacks,including the gray hole attack,which can disrupt the process of transmitting messages.And this results in the degradation of routing performance.To address this issue,a double deep Q-networks-based stable routing for resisting gray hole attack(DOSR)is proposed in this paper.The aim of the DOSR algorithm is to maximize the message delivery ratio as well as to minimize the transmission delay.For this,the distance ratio,message loss ratio,and connection ratio are taken into consideration when choosing a relay node.Then,to choose the relay node is formulated as an optimization problem,and a double deep Q-networks are utilized to solve the optimization problem.Experimental results show that DOSR outperforms QLTR and TLRP by significant margins:in scenarios with 400 vehicles and 10%malicious nodes,the message delivery ratio(MDR)of DOSR is 8.3%higher than that of QLTR and 5.1%higher than that of TLRP;the average transmission delay(ATD)is reduced by 23.3%compared to QLTR and 17.9%compared to TLRP.Additionally,sensitivity analysis of hyperparameters confirms the convergence and stability of DOSR,demonstrating its robustness in dynamic IoV environments.
基金supported in part by the Major Science and Technology Projects in Yunnan Province(202202AD080013)King Khalid University for funding this work through Large Group Project under grant number RGP.2/373/45.
文摘Data privacy leakage has always been a critical concern in cloud-based Internet of Things(IoT)systems.Dynamic Symmetric Searchable Encryption(DSSE)with forward and backward privacy aims to address this issue by enabling updates and retrievals of ciphertext on untrusted cloud server while ensuring data privacy.However,previous research on DSSE mostly focused on single keyword search,which limits its practical application in cloud-based IoT systems.Recently,Patranabis(NDSS 2021)[1]proposed a groundbreaking DSSE scheme for conjunctive keyword search.However,this scheme fails to effectively handle deletion operations in certain circumstances,resulting in inaccurate query results.Additionally,the scheme introduces unnecessary search overhead.To overcome these problems,we present CKSE,an efficient conjunctive keyword DSSE scheme.Our scheme improves the oblivious shared computation protocol used in the scheme of Patranabis,thus enabling a more comprehensive deletion functionality.Furthermore,we introduce a state chain structure to reduce the search overhead.Through security analysis and experimental evaluation,we demonstrate that our CKSE achieves more comprehensive deletion functionality while maintaining comparable search performance and security,compared to the oblivious dynamic cross-tags protocol of Patranabis.The combination of comprehensive functionality,high efficiency,and security makes our CKSE an ideal choice for deployment in cloud-based IoT systems.
基金financially supported by the Key Program of National Natural Science Foundation of China(No.41530320)China Natural Science Foundation for Young Scientists(No.41404093)+1 种基金Key National Research Project of China(Nos2016YFC0303100 and 2017YFC0601900)China Natural Science Foundation(No.41774125)
文摘The airborne electromagnetic （AEM） method has a high sampling rate and survey flexibility. However, traditional numerical modeling approaches must use high-resolution physical grids to guarantee modeling accuracy, especially for complex geological structures such as anisotropic earth. This can lead to huge computational costs. To solve this problem, we propose a spectral-element （SE） method for 3D AEM anisotropic modeling, which combines the advantages of spectral and finite-element methods. Thus, the SE method has accuracy as high as that of the spectral method and the ability to model complex geology inherited from the finite-element method. The SE method can improve the modeling accuracy within discrete grids and reduce the dependence of modeling results on the grids. This helps achieve high-accuracy anisotropic AEM modeling. We first introduced a rotating tensor of anisotropic conductivity to Maxwell＇s equations and described the electrical field via SE basis functions based on GLL interpolation polynomials. We used the Galerkin weighted residual method to establish the linear equation system for the SE method, and we took a vertical magnetic dipole as the transmission source for our AEM modeling. We then applied fourth-order SE calculations with coarse physical grids to check the accuracy of our modeling results against a 1D semi-analytical solution for an anisotropic half-space model and verified the high accuracy of the SE. Moreover, we conducted AEM modeling for different anisotropic 3D abnormal bodies using two physical grid scales and three orders of SE to obtain the convergence conditions for different anisotropic abnormal bodies. Finally, we studied the identification of anisotropy for single anisotropic abnormal bodies, anisotropic surrounding rock, and single anisotropic abnormal body embedded in an anisotropic surrounding rock. This approach will play a key role in the inversion and interpretation of AEM data collected in regions with anisotropic geology.
基金supported by the National Natural Science Foundation of China(Grant Nos.41404101,41174114,41274130,and 41404102)
文摘AVO forward modeling is based on two-phase medium theory and is considered an effective method for describing reservoir rocks and fluids. However, the method depends on the input matrix mineral bulk modulus and the rationality of the two-phase medium model. We used the matrix mineral bulk modulus inversion method and multiple constraints to obtain a two-phase medium model with physical meaning. The proposed method guarantees the reliability of the obtained AVO characteristicsin two-phase media. By the comparative analysis of different lithology of the core sample, the advantages and accuracy of the inversion method can be illustrated. Also, the inversion method can be applied in LH area, and the AVO characteristics can be obtained when the porosity, fluid saturation, and other important lithology parameters are changed. In particular, the reflection coefficient amplitude difference between the fast P wave and S wave as a function of porosity at the same incidence angle, and the difference in the incidence angle threshold can be used to decipher porosity.
文摘In the Chinese lunar calendar,2026 ushers in the Year of the Horse,a creature that has carried humanity across continents and through centuries.More than a marker of time,the horse embodies vitality,courage,and the relentless spirit to move forward,qualities that resonate not only in China but across the landscapes of many African societies.
文摘Hepatitis B Virus(HBV)infection and heavy alcohol consumption are the two primary pathogenic causes of liver cirrhosis.In this paper,we proposed a deterministic mathematical model and a logistic equation to investigate the dynamics of liver cirrhosis progression as well as to explain the implications of variations in alcohol consumption on chronic hepatitis B patients,respectively.The intricate interactions between liver cirrhosis,recovery,and treatment dynamics are captured by the model.This study aims to show that alcohol consumption by Hepatitis B-infected individuals accelerates liver cirrhosis progression while treatment of acutely infected individuals reduces it.We proved that a unique solution of the proposed model exists,which is positive and bounded.Using the next-generation matrix approach,two basic reproductive numbers R_(A_(0))and R_(A_(max))are calculated to identify future recurrence.The equilibrium points are calculated,and both equilibria are proved locally and globally asymptotically stable when R_(0)is below and above one,respectively.It is shown that bifurcation exists at R_(0)=1 and a detailed proof for forward bifurcation is given.Furthermore,we performed the sensitivity analysis of the model parameters on R_(0).For the confirmation of analytical work,we performed numerical simulations,and the results indicate that the treatment and the inhibitory effects reduce the risk of developing liver cirrhosis in individuals,while heavy alcohol consumption accelerates markedly the liver cirrhosis progression in patients with chronic hepatitis B.
基金supported by the Major Program of Xiangjiang Laboratory(No.22XJ01009)National Natural Science Foundation of China(Grant Nos.52227815,52078065,and 52178414)the Postgraduate Scientific Research Innovation Project of Hunan Province(Nos.CX20230852 and CX20230848).
文摘Ground penetrating radar(GPR)offers a rapid and non-destructive approach to evaluating asphalt mixtures by capturing variations in their dielectric constant.As a critical electromagnetic parameter,the dielectric constant demonstrates significant potential for assessing the material composition and mechanical properties of asphalt mixtures.However,the relationship between the dielectric constant and mechanical properties remains unclear.To investigate the factors affecting the dielectric constant and its correlation with the mechanical properties of asphalt mixtures,a systematic analysis of the influencing parameters was conducted.Fitting equations were established to quantify the relationships between the dielectric constant and mechanical properties.Firstly,the effects of compaction state,testing frequency,and testing temperature on the dielectric constant were evaluated.Subsequently,forward simulations of GPR were executed on asphalt pavements with diverse air voids and detection frequencies.Finally,a fitting analysis was performed to determine the correlation between the dielectric constant and the dynamic modulus,compressive strength,and splitting tensile strength.The results indicated that the dielectric constant increased with the compaction state,decreased with increasing testing frequency until stabilized,and was insignificantly affected by changes in testing temperature.The change of air void in asphalt pavement has significantly affected the amplitude and timing of electromagnetic wave reflection.A linear positive correlation was identified between the dielectric constant and dynamic modulus as well as compressive strength,while a quadratic positive correlation existed with splitting tensile strength.This study provided theoretical and practical foundations for enhancing the reliability and accuracy of non-destructive testing in asphalt pavement.
文摘The“Forward Together”Dialogue on Building a China-Brunei Community with a Shared Future was held on the morning of February 7 at Universiti Brunei Darussalam(UBD)in Bandar Seri Begawan.Scheduled for the lead-up to the 35th anniversary of diplomatic relations between China and Brunei in 2026,the event aimed to deepen strategic mutual trust,build broader consensus on cooperation,and generate both intellectual momentum and practical proposals for advancing a closer China-Brunei community with a shared future.
文摘Chinese President Xi Jinping has guided China through a year of resilient growth via forward-looking reforms and innovation-driven transformation that is shaping the nation’s economic trajectory for 2026 and beyond.
基金Department of Atomic Energy(DAE)for long-term support of this research,at present from the grant“Physics and Astronomy(Project Identification No.RTI4002)Department of Atomic Energy,Tata Institute of Fundamental Research”and partially from Grant No.JBR/2020/00039 of the Anusandhan National Research Foundation(ANRF),both agencies of the Government of Indiasupport from the ANRF through the J.C.Bose Fellowship Grant No.JCB/2017/000055 and Core Research Grant(CRG)Proposal Nos.ANRF/JBG/2025/000237/PS and CRG/2022/002782+1 种基金partial support from the Infosys-TIFR Leading Edge Research Grant(Cycle 2)the OSIRIS Consortium,consisting of UCLA and IST(Lisbon,Portugal),for providing access to the OSIRIS framework,which is work supported by Grant No.NSF ACI-1339893.
文摘Plasmas,the most common state of matter in the observable universe,are subject to instabilities of various types:hydrodynamic,magnetohydrodynamic,and electromagnetic.Our limited success in understanding these is due to the lack of direct experimental information on their origins and evolution.Here,we present direct spatially resolved measurements of the femtosecond evolution of the electromagnetic beam-driven instability that arises from the interaction of forward and return currents in an ultrahigh-intensity laser-produced plasma.We track its evolution from the initial linear stage to the later nonlinear stage by measuring the spatiotemporal evolution of the giant(megagauss)magnetic field created in the interaction process.Our experimental findings and numerical simulations are the first to indicate the observed instability triggered by the emission of electromagnetic radiation,like those known in the context of gravitational interaction,where the emission of gravitational radiation drives specific negative-energy modes in rotating black holes or neutron stars.
基金Supported by the Ministry of Education U40 Program(ZYGXONJSKYCXNLZCXM-E19)National Natural Science Foundation of China(52574078)。
文摘The forward model of optical fiber strain induced by fractures,together with the associated model resolution matrix,is used to demonstrate the interpretability of fracture parameters once the fracture intersects the fiber.A regularized inversion framework for fracture parameters is established to evaluate the influence of measured data quality on the accuracy of iterative regularized inversion.An interpretation approach for both fracture width and height is proposed,and the synthetic forward data with measurement error and field examples are employed to validate the accuracy of the simultaneous inversion of fracture width and height.The results indicate that,after the fracture contacts the fiber,the strain response is strongly sensitive only to the fracture parameters at the intersection location,whereas the interpretability of parameters at other locations remains limited.The iterative regularized inversion method effectively suppresses the impact of measurement error and exhibits high computational efficiency,showing clear advantages for inversion applications.When incorporating the first-order regularization with a Neumann boundary constraint on the tip width,the inverted fracture-width distribution becomes highly sensitive to fracture height;thus,combined with a bisection strategy,simultaneous inversion of fracture width and height can be achieved.Examination using the model resolution matrix,noisy synthetic data,and field data confirms that the iterative regularized inversion model for fracture width and height provides high interpretive accuracy and can be applied to the calculation and analysis of fracture width,fracture height,net pressure and other parameters.
基金supported by Biological Breeding-National Science and Technology Major Project(2022ZD04008)the Jiujiang Municipal Key Research and Development Program(2025_001556)Lushan City Scientific and Technological Innovation Talents and Teams Program and Earmarked Fund for China Agricultural Research System(CARS-12)。
文摘Pod shattering,while a natural mechanism for seed dispersal,is an undesirable agronomic trait in rapeseed(Brassica napus L.)that complicates mechanical harvesting.It typically causes yield losses of 5%-15%,which can be further worsened under dry and hot conditions.As most of the modern rapeseed cultivars remain susceptible to shattering,enhancing pod shattering resistance(PSR)is important to safeguard global rapeseed production.Significant progresses have been made in elucidating the molecular and genetic mechanisms of silique dehiscence in the model plant Arabidopsis and pod shattering in rapeseed.This review firstly summarizes the genetic network controlling silique dehiscence in Arabidopsis,which is largely conserved in closely related Brassica species.We then synthesize discoveries from both forward and reverse genetic studies in rapeseed.Finally,the major challenges and future prospects in PSR research and breeding are discussed in depth.
文摘Sensitivity of observational data is important in the study of Glacial Isostatic Adjustment(GIA).However,depending on whether sensitivity is used for the Inverse Problem or the Forward Problem,the final formulation and display of the sensitivity kernel will be different.Unfortunately,in the past,both perspectives give the same name to their quantity computed/displayed,and that has caused some confusion.To distinguish between the two,their perspective should be added to the names.This paper focuses only on the perspective of the Forward Problem where the input parameters are known.The Perturbation method has been successfully used in the computation of the sensitivity kernels of observations on 1D and 3D viscosity variations from the Forward perspective.One aim of this paper is to review and clarify the physics of the Perturbation method and bring out some important aspects of this method that have been misunderstood or neglected.Another aim is to present sensitivity kernels from the Perturbation method using 3D(both radially and laterally heterogeneous)Earth models with realistic ice history.These new results are now suitable for future comparison with those from new methods using the Forward perspective.Finally,the sensitivity computations for realistic ice histories on a 3D Earth is reviewed and used to search for optimal locations of new GIA observations.
基金Supported by the National Key Research and Development Program of China(No.2023YFC3008200)the Independent Research Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(No.SML2022SP505)。
文摘Physics-informed neural networks(PINNs),as a novel artificial intelligence method for solving partial differential equations,are applicable to solve both forward and inverse problems.This study evaluates the performance of PINNs in solving the temperature diffusion equation of the seawater across six scenarios,including forward and inverse problems under three different boundary conditions.Results demonstrate that PINNs achieved consistently higher accuracy with the Dirichlet and Neumann boundary conditions compared to the Robin boundary condition for both forward and inverse problems.Inaccurate weighting of terms in the loss function can reduce model accuracy.Additionally,the sensitivity of model performance to the positioning of sampling points varied between different boundary conditions.In particular,the model under the Dirichlet boundary condition exhibited superior robustness to variations in point positions during the solutions of inverse problems.In contrast,for the Neumann and Robin boundary conditions,accuracy declines when points were sampled from identical positions or at the same time.Subsequently,the Argo observations were used to reconstruct the vertical diffusion of seawater temperature in the north-central Pacific for the applicability of PINNs in the real ocean.The PINNs successfully captured the vertical diffusion characteristics of seawater temperature,reflected the seasonal changes of vertical temperature under different topographic conditions,and revealed the influence of topography on the temperature diffusion coefficient.The PINNs were proved effective in solving the temperature diffusion equation of seawater with limited data,providing a promising technique for simulating or predicting ocean phenomena using sparse observations.
基金supported by the Malaysia Ministry of Higher Education under Fundamental Research Grant Scheme with Project Code:FRGS/1/2024/TK07/USM/02/3.
文摘Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller(NFIDC)with a Feedback Radial Basis Function Neural Network(FRBFNN).The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1.The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.A two-stage simulation evaluation was conducted.In the first stage,the controller was tested in a simulated hospital environment under both ideal and non-ideal conditions.In the second,it was benchmarked against four established controllers-Neural Network Model Reference Adaptive(NNMRA),Z-number Fuzzy Logic(Z-FL),Adaptive Dynamic Controller(ADC),and Fuzzy Logic-PID(FL-PID)—using circular and lemniscate trajectories.Across ten runs,the proposed controller achieved the lowest tracking errors under all conditions.Under ideal conditions,it achieved average improvements of 55.24%,75.75%,and 55.20%in integral absolute error(IAE),integral squared error(ISE),and mean absolute error(MAE),respectively,with coefficient of variation(CV)reductions above 55%.Under non-ideal conditions,average improvements exceeded 64%in IAE,77%in ISE,and 66%in MAE,while maintaining CV reductions above 57%.These results confirm that the NFIDC-FRBFNN controller offers superior accuracy,robustness,and consistency for real-time path tracking in healthcare robotics.
基金National Natural Science Foundation of China(No.41671132,41771139)Natural Science Foundation of Jiangsu Province(No.BK20171516)
文摘This study examined the spatio-temporal trajectories of the international freight forwarding service(IFFS) in the Yangtze River Delta(YRD) and explored the driving mechanisms of the service. Based on a bipartite network projection from an IFFS firm-city data source, we mapped three IFFS networks in the YRD in 2005, 2010, and 2015. A range of statistical indicators were used to explore changes in the spatial patterns of the three networks. The underlying influence of marketization, globalization, decentralization, and integration was then explored. It was found that the connections between Shanghai and other nodal cities formed the backbones of these networks. The effects of a city's administrative level and provincial administrative borders were generally obvious. We found several specific spatial patterns associated with IFFS. For example, the four non-administrative centers of Ningbo, Suzhou, Lianyungang, and Nantong were the most connected cities and played the role of gateway cities. Furthermore, remarkable regional equalities were found regarding a city's IFFS network provision, with notable examples in the weakly connected areas of northern Jiangsu and southwestern Zhejiang. Finally, an analysis of the driving mechanisms demonstrated that IFFS network changes were highly sensitive to the influences of marketization and globalization, while regional integration played a lesser role in driving changes in IFFS networks.
基金supported by the National Key Research and Development Program of China under Grant 2020YFB1804803the National Natural Science Foundation of China under Grant 61872382the Research and Development Program in Key Areas of Guangdong Province under Grant No.2018B010113001。
文摘The Space-Air-Ground Integrated Network(SAGIN) realizes the integration of space, air,and ground networks, obtaining the global communication coverage.Software-Defined Networking(SDN) architecture in SAGIN has become a promising solution to guarantee the Quality of Service(QoS).However, the current routing algorithms mainly focus on the QoS of the service, rarely considering the security requirement of flow. To realize the secure transmission of flows in SAGIN, we propose an intelligent flow forwarding scheme with endogenous security based on Mimic Defense(ESMD-Flow). In this scheme, SDN controller will evaluate the reliability of nodes and links, isolate malicious nodes based on the reliability evaluation value, and adapt multipath routing strategy to ensure that flows are always forwarded along the most reliable multiple paths. In addition, in order to meet the security requirement of flows, we introduce the programming data plane to design a multiprotocol forwarding strategy for realizing the multiprotocol dynamic forwarding of flows. ESMD-Flow can reduce the network attack surface and improve the secure transmission capability of flows by implementing multipath routing and multi-protocol hybrid forwarding mechanism. The extensive simulations demonstrate that ESMD-Flow can significantly improve the average path reliability for routing and increase the difficulty of network eavesdropping while improving the network throughput and reducing the average packet delay.
文摘This work investigates the performance of various forward error correction codes, by which the MIMO-OFDM system is deployed. To ensure fair investigation, the performance of four modulations, namely, binary phase shift keying(BPSK), quadrature phase shift keying(QPSK), quadrature amplitude modulation(QAM)-16 and QAM-64 with four error correction codes(convolutional code(CC), Reed-Solomon code(RSC)+CC, low density parity check(LDPC)+CC, Turbo+CC) is studied under three channel models(additive white Guassian noise(AWGN), Rayleigh, Rician) and three different antenna configurations(2×2, 2×4, 4×4). The bit error rate(BER) and the peak signal to noise ratio(PSNR) are taken as the measures of performance. The binary data and the color image data are transmitted and the graphs are plotted for various modulations with different channels and error correction codes. Analysis on the performance measures confirm that the Turbo + CC code in 4×4 configurations exhibits better performance.
