We propose a novel workflow for fast forward modeling of well logs in axially symmetric 2D models of the nearwellbore environment.The approach integrates the finite element method with deep residual neural networks to...We propose a novel workflow for fast forward modeling of well logs in axially symmetric 2D models of the nearwellbore environment.The approach integrates the finite element method with deep residual neural networks to achieve exceptional computational efficiency and accuracy.The workflow is demonstrated through the modeling of wireline electromagnetic propagation resistivity logs,where the measured responses exhibit a highly nonlinear relationship with formation properties.The motivation for this research is the need for advanced modeling al-gorithms that are fast enough for use in modern quantitative interpretation tools,where thousands of simulations may be required in iterative inversion processes.The proposed algorithm achieves a remarkable enhancement in performance,being up to 3000 times faster than the finite element method alone when utilizing a GPU.While still ensuring high accuracy,this makes it well-suited for practical applications when reliable payzone assessment is needed in complex environmental scenarios.Furthermore,the algorithm’s efficiency positions it as a promising tool for stochastic Bayesian inversion,facilitating reliable uncertainty quantification in subsurface property estimation.展开更多
Multifocal metalenses are of great concern in optical communications,optical imaging and micro-optics systems,but their design is extremely challenging.In recent years,deep learning methods have provided novel solutio...Multifocal metalenses are of great concern in optical communications,optical imaging and micro-optics systems,but their design is extremely challenging.In recent years,deep learning methods have provided novel solutions to the design of optical planar devices.Here,an approach is proposed to explore the use of generative adversarial networks(GANs)to realize the design of metalenses with different focusing positions at dual wavelengths.This approach includes a forward network and an inverse network,where the former predicts the optical response of meta-atoms and the latter generates structures that meet specific requirements.Compared to the traditional search method,the inverse network demonstrates higher precision and efficiency in designing a dual-wavelength bifocal metalens.The results will provide insights and methodologies for the design of tunable wavelength metalenses,while also highlighting the potential of deep learning in optical device design.展开更多
Insertional mutation,phenotypic evaluation,and mutated gene cloning are widely used to clone genes from scratch.Exogenous genes can be integrated into the genome during non-homologous end joining(NHEJ)of the double-st...Insertional mutation,phenotypic evaluation,and mutated gene cloning are widely used to clone genes from scratch.Exogenous genes can be integrated into the genome during non-homologous end joining(NHEJ)of the double-strand breaks of DNA,causing insertional mutation.The random insertional mutant library constructed using this method has become a method of forward genetics for gene cloning.However,the establishment of a random insertional mutant library requires a high transformation efficiency of exogenous genes.Many microalgal species show a low transformation efficiency,making constructing random insertional mutant libraries difficult.In this study,we established a highly efficient transformation method for constructing a random insertional mutant library of Nannochloropsis oceanica,and tentatively tried to isolate its genes to prove the feasibility of the method.A gene that may control the growth rate and cell size was identified.This method will facilitate the genetic studies of N.oceanica,which should also be a reference for other microalgal species.展开更多
Named Data Networking(NDN)has emerged as a promising communication paradigm,emphasizing content-centric access rather than location-based access.This model offers several advantages for Internet of Healthcare Things(I...Named Data Networking(NDN)has emerged as a promising communication paradigm,emphasizing content-centric access rather than location-based access.This model offers several advantages for Internet of Healthcare Things(IoHT)environments,including efficient content distribution,built-in security,and natural support for mobility and scalability.However,existing NDN-based IoHT systems face inefficiencies in their forwarding strategy,where identical Interest packets are forwarded across multiple nodes,causing broadcast storms,increased collisions,higher energy consumption,and delays.These issues negatively impact healthcare system performance,particularly for individuals with disabilities and chronic diseases requiring continuous monitoring.To address these challenges,we propose a Smart and Energy-Aware Forwarding(SEF)strategy based on reinforcement learning for NDN-based IoHT.The SEF strategy leverages the geographical distance and energy levels of neighboring nodes,enabling devices to make more informed forwarding decisions and optimize next-hop selection.This approach reduces broadcast storms,optimizes overall energy consumption,and extends network lifetime.The system model,which targets smart hospitals and monitoring systems for individuals with disabilities,was examined in relation to the proposed strategy.The SEF strategy was then implemented in the NS-3 simulation environment to assess its performance in healthcare scenarios.Results demonstrated that SEF significantly enhanced NDN-based IoHT performance.Specifically,it reduced energy consumption by up to 27.11%,82.23%,and 84.44%,decreased retrieval time by 20.23%,48.12%,and 51.65%,and achieved satisfaction rates that were approximately 0.69 higher than those of other strategies,even in more densely populated areas.This forwarding strategy is anticipated to substantially improve the quality and efficiency of NDN-based IoHT systems.展开更多
Unmanned aerial vehicle transient electromagnetic(UAV-TEM)is a novel airborne exploration method that offers advantages such as low cost,simple operation,high exploration efficiency and suitability for near-surface ex...Unmanned aerial vehicle transient electromagnetic(UAV-TEM)is a novel airborne exploration method that offers advantages such as low cost,simple operation,high exploration efficiency and suitability for near-surface exploration in complex terrain areas.To improve the accuracy of data interpretation in this method,the authors conducted a systematic three-dimensional(3D)forward modeling and inversion of the UAV-TEM.This study utilized the finite element method based on unstructured tetrahedral elements and employed the second-order backward Euler method for time discretization.This allowed for accurate 3D modeling and accounted for the effects of complex terrain.Based on these,the influence characteristics of flight altitudes and the sizes,burial depths,and resistivities of anomalies are compared and analyzed to explore the UAV-TEM systems’exploration capability.Lastly,four typical geoelectrical models of landslides are designed,and the inversion method based on the Gauss-Newton optimization method is used to image the landslide models and analyze the imaging effect of the UAV-TEM method on landslide geohazards.Numerical results showed that UAV-TEM could have better exploration resolution and fine imaging of nearsurface structures,providing important technical support for monitoring,early warning,and preventing landslides and other geological hazards.展开更多
The superparamagnetic effect arises from the superparamagnetism exhibited by a multitude of nano-sized magnetic mineral particles under an external electric field.This phenomenon manifests in transient electromagnetic...The superparamagnetic effect arises from the superparamagnetism exhibited by a multitude of nano-sized magnetic mineral particles under an external electric field.This phenomenon manifests in transient electromagnetic data primarily as a deceleration in the attenuation rate of late-stage signals,a characteristic difficult to discern directly from airborne transient electromagnetic signals,consequently leading to significant misinterpretations of subterranean electrical structures.This study embarks on 3D forward modeling of airborne electromagnetic responses in the frequency domain,accounting for the superparamagnetic effect,utilizing an unstructured finite element method.Superparamagnetic responses in the time domain were obtained through frequency-time conversion.This investigation explores the influence of various parameters-such as magnetic susceptibility,time constants,and flight altitude-on the superparamagnetic effect by examining the response characteristics of typical targets.Findings indicate that in its late stages,the superparamagnetic effect can induce a relative anomaly of up to 300%.There is a positive correlation between magnetic susceptibility and the strength of the superparamagnetic effect.The influence of the time constant's upper and lower limits on the superparamagnetic effect is minimal;however,the range between these limits significantly affects the effect,showing a negative correlation with its intensity.Higher flight altitudes weaken the superparamagnetic signal.The impact is most pronounced when superparamagnetic minerals are shallowly buried,effectively shielding the underlying geology with the characteristics of a good conductivity anomaly,but this effect diminishes with greater depth.The insights from this study provide a theoretical framework for a deeper understanding of the superparamagnetic effect in transient electromagnetic signals and for more accurate interpretations of subterranean geological and electrical structures.展开更多
As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal vari...As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal variations in the lithosphere.Traditional approaches either do not consider the non-axial dipolar terms of the inducing field and its radial variation or do so by means of complicated formulae.Moreover,existing methods treat the magnetic lithosphere either as an infinitesimally thin layer or as a radially uniform spherical shell of constant thickness.Here,we present alternative forward formulae that account for an arbitrarily high maximum degree of the inducing field and for a magnetic lithosphere of variable thickness.Our simulations based on these formulae suggest that the satellite magnetic anomaly field is sensitive to the non-axial dipolar terms of the inducing field but not to its radial variation.Therefore,in forward and inverse calculations of satellite magnetic anomaly data,the non-axial dipolar terms of the inducing field should not be ignored.Furthermore,our results show that the satellite magnetic anomaly field is sensitive to variability in the lateral thickness of the magnetized shell.In particular,we show that for a given vertically integrated susceptibility distribution,underestimating the thickness of the magnetic layer overestimates the induced magnetic field.This discovery bridges the greatest part of the alleged gap between the susceptibility values measured from rock samples and the susceptibility values required to match the observed magnetic field signal.We expect the formulae and conclusions of this study to be a valuable tool for the quantitative interpretation of the Earth's global lithospheric magnetic field,through an inverse or forward modelling approach.展开更多
To investigate the forward kinematics problem of parallel mechanisms with complex limbs and to expand the applicability of the powerful tool of Conformal Geometric Algebra(CGA),a CGA-based modeling and solution method...To investigate the forward kinematics problem of parallel mechanisms with complex limbs and to expand the applicability of the powerful tool of Conformal Geometric Algebra(CGA),a CGA-based modeling and solution method for a class of parallel platforms with 3-RE structure after locking the actuated joints is proposed in this paper.Given that the angle between specific joint axes of limbs remains constant,a set of geometric constraints for the forward kinematics of parallel mechanisms(PM)are determined.After translating unit direction vectors of these joint axes to the common starting point,the geometric constraints of the angle between the vectors are transformed into the distances between the endpoints of the vectors,making them easier to handle.Under the framework of CGA,the positions of key points that determine the position and orientation of the moving platform can be intuitively determined by the intersection,division,and duality of basic geometric entities.By employing the tangent half-angle substitution,the forward kinematic analysis of the parallel mechanisms leads to a high-order univariate polynomial equation without the need for any complex algebraic elimination operations.After solving this equation and back substitution,the position and pose of the MP can be obtained indirectly.A numerical case is utilized to confirm the effectiveness of the proposed method.展开更多
The Earth's magnetic field,which has been extensively observed from ground to satellite altitudes over several decades,originates from multiple sources,such as the core dynamo,the conductive mantle,the magnetized ...The Earth's magnetic field,which has been extensively observed from ground to satellite altitudes over several decades,originates from multiple sources,such as the core dynamo,the conductive mantle,the magnetized lithosphere,and the space current systems.Modeling of the lithospheric contribution plays an important role in the geophysical studies and industrial applications.In this paper,we propose a new method for global and regional modeling of the lithospheric magnetic field based on the cubed-sphere.An equivalent dipole source method on a quasi-uniform cubed-sphere grid is employed in the forward modeling.The dipole directions are fixed according to a priori magnetization and the relative intensities are estimated by an inversion procedure of least-squares fitting with minimum model regularization.Several numerical tests are performed to validate the accuracy and efficiency of both forward modeling and inversion procedure.The proposed method is applied to the global and regional modeling based on the latest magnetic data from Swarm Alpha satellite and MSS-1 mission.The model results indicate that the proposed method works quite well for realistic satellite data and MSS-1 data is consistent with the Swarm data in terms of lithospheric field modeling.展开更多
This study presents a novel analytical algorithm for solving the forward position problem of a triangular platform Stewart-type parallel robot(STPR).By introducing a virtual chain and leveraging tetrahedral geometric ...This study presents a novel analytical algorithm for solving the forward position problem of a triangular platform Stewart-type parallel robot(STPR).By introducing a virtual chain and leveraging tetrahedral geometric principles,the proposed method derives analytical solutions for the position and orientation of the moving platform.The algorithm systematically addresses the nonlinearity inherent in the kinematic equations of parallel mechanisms,providing explicit expressions for the coordinates of key moving attachment points.Furthermore,the methodology is extended to general triangular platform STPRs with non-coplanar fixed attachments.Numerical validation through virtual experiments confirms the accuracy of the solutions,demonstrating that the mechanism admits eight distinct configurations for a given set of limb lengths.The results align with established kinematic principles and offer a computationally efficient alternative to iterative analytical approaches,contributing to the advancement of precision control in parallel robotic systems.展开更多
Seawater electrolysis for hydrogen production faces inherent challenges, including side reactions, corrosion, and scaling, stemming from the intricate composition of seawater. In response, researchers have turned to c...Seawater electrolysis for hydrogen production faces inherent challenges, including side reactions, corrosion, and scaling, stemming from the intricate composition of seawater. In response, researchers have turned to continuous water splitting using forward osmosis(FO)-driven seawater desalination. However, the necessity of a neutral electrolyte hampers this strategy due to the limited current density and scarcity of precious metals. Herein, this study applies alkali-durable FO membranes to enable self-sustaining seawater splitting, which can selectively withdraw water molecules, from seawater, via concentration gradient. The membranes demonstrates outstanding perm-selectivity of water/ions(~5830 mol mol^(-1)) during month-long alkaline resistance tests, preventing electrolyte leaching(>97% OHàretention) while maintaining ~95%water balance(V_(FO)= V_(electrolysis)) via preserved concentration gradient for consistent forward-osmosis influx of water molecules. With the consistent electrolyte environment protected by the polyamide FO membranes, the Ni Fe-Ar-P catalyst exhibits promising performance: a sustain current density of 360 m A cmà2maintained at the cell voltage of 2.10 V and 2.15 V for 360 h in the offshore seawater, preventing Cl/Br corrosion(98% rejection) and Mg/Ca passivation(99.6% rejection). This research marks a significant advancement towards efficient and durable seawater-based hydrogen production.展开更多
On the morning of May 31st,the parallel forum"Ecological Actions to Carry Forward the Shared Values of Mankind,"as part of the 4th Dialogue on Exchanges and Mutual Learning among Civilisations,was held in Du...On the morning of May 31st,the parallel forum"Ecological Actions to Carry Forward the Shared Values of Mankind,"as part of the 4th Dialogue on Exchanges and Mutual Learning among Civilisations,was held in Dunhuang.More than 50 experts and scholars from different countries,including China,Kenya and Japan,engaged in indepth discussions on the theme.展开更多
A temperature and acoustic impedance simultaneous sensor based on forward stimulated Brillouin scattering(FSBS)in highly nonlinear fiber(HNLF)with high sensitivity and high accuracy is proposed and demonstrated in thi...A temperature and acoustic impedance simultaneous sensor based on forward stimulated Brillouin scattering(FSBS)in highly nonlinear fiber(HNLF)with high sensitivity and high accuracy is proposed and demonstrated in this paper.High-order acoustic modes(HOAMs)are used to achieve individual or simultaneous measurement of the two parameters.Transverse acoustic waves(TAWs)involved in the FSBS process can efficiently sense the mechanical or environmental changes outside the fiber cladding,which will be reflected in a linear shift of the acoustic resonance frequency.By analyzing the frequencies of specific scattering peaks,the temperature and acoustic impedance outside the fiber cladding can be obtained simultaneously.The highest measured temperature and acoustic impedance sensitivities are 184.93 k Hz/℃and444.56 k Hz/MRayl,and the measurement accuracies are 0.09℃and 0.009 MRayl,respectively,which are both at desirable levels.We believe this work can provide potential application solutions for sensing fields involving temperature or acoustic impedance measurements.展开更多
Objective To study the key technologies in the field of ginsenosides and to offer a guide for the future development ginsenosides through the main path identification method based on genetic knowledge persistence algo...Objective To study the key technologies in the field of ginsenosides and to offer a guide for the future development ginsenosides through the main path identification method based on genetic knowledge persistence algorithm(GKPA).Methods The global ginsenoside invention authorized patents were used as the data source to construct a ginsenoside patent self-citation network,and to identify high knowledge persistent patents(HKPP)of ginsenoside technology based on the GKPA,and extract its high knowledge persistence main path(HKPMP).Finally,the genetic forward and backward path(GFBP)was used to search the nodes on the main path,and draw the genetic forward and backward main path(GFBMP)of ginsenoside technology.Results and Conclusion The algorithm was applied to the field of ginsenosides.The research results show the milestone patents in ginsenosides technology and the main evolution process of three key technologies,which points out the future direction for the technological development of ginsenosides.The results obtained by this algorithm are more interpretable,comprehensive and scientific.展开更多
A novel behavioral model using three-layer time-delay feed-forward neural networks （TDFFNN）is adopted to model radio frequency （RF）power amplifiers exhibiting memory nonlinearities. In order to extract the paramet...A novel behavioral model using three-layer time-delay feed-forward neural networks （TDFFNN）is adopted to model radio frequency （RF）power amplifiers exhibiting memory nonlinearities. In order to extract the parameters, the back- propagation algorithm is applied to train the proposed neural networks. The proposed model is verified by the typical odd- order-only memory polynomial model in simulation, and the performance is compared with different numbers of taped delay lines（TDLs） and perceptrons of the hidden layer. For validating the TDFFNN model by experiments, a digital test bench is set up to collect input and output data of power amplifiers at a 60 × 10^6 sample/s sampling rate. The 3.75 MHz 16-QAM signal generated in the vector signal generator（VSG） is chosen as the input signal, when measuring the dynamic AM/AM and AM/PM characteristics of power amplifiers. By comparisons and analyses, the presented model provides a good performance in convergence, accuracy and efficiency, which is approved by simulation results and experimental results in the time domain and frequency domain.展开更多
We discuss the feasibility of using controlled-source electromagnetic （CSEM） in the frequency domain for prospecting marine gas hydrates. Based on the Ocean Drilling Program （ODP） Leg 164 log data, we have establi...We discuss the feasibility of using controlled-source electromagnetic （CSEM） in the frequency domain for prospecting marine gas hydrates. Based on the Ocean Drilling Program （ODP） Leg 164 log data, we have established several 1-D resistivity models which have different gas hydrate concentrations. Meanwhile, we analyzed the electromagnetic response of marine gas hydrates in the frequency domain based on these models. We also studied the relationship between electrical field magnitude or phase and parameters such as receiver-transmitter distance and frequency. Our numerical modeling results provide us with a quantitative reference for exploration and resource evaluation of marine gas hydrates.展开更多
The workload of the 3D magnetotelluric forward modeling algorithm is so large that the traditional serial algorithm costs an extremely large compute time. However, the 3D forward modeling algorithm can process the dat...The workload of the 3D magnetotelluric forward modeling algorithm is so large that the traditional serial algorithm costs an extremely large compute time. However, the 3D forward modeling algorithm can process the data in the frequency domain, which is very suitable for parallel computation. With the advantage of MPI and based on an analysis of the flow of the 3D magnetotelluric serial forward algorithm, we suggest the idea of parallel computation and apply it. Three theoretical models are tested and the execution efficiency is compared in different situations. The results indicate that the parallel 3D forward modeling computation is correct and the efficiency is greatly improved. This method is suitable for large size geophysical computations.展开更多
In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of faul...In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global sin-gle-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems.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
基金financially supported by the Russian federal research project No.FWZZ-2022-0026“Innovative aspects of electro-dynamics in problems of exploration and oilfield geophysics”.
文摘We propose a novel workflow for fast forward modeling of well logs in axially symmetric 2D models of the nearwellbore environment.The approach integrates the finite element method with deep residual neural networks to achieve exceptional computational efficiency and accuracy.The workflow is demonstrated through the modeling of wireline electromagnetic propagation resistivity logs,where the measured responses exhibit a highly nonlinear relationship with formation properties.The motivation for this research is the need for advanced modeling al-gorithms that are fast enough for use in modern quantitative interpretation tools,where thousands of simulations may be required in iterative inversion processes.The proposed algorithm achieves a remarkable enhancement in performance,being up to 3000 times faster than the finite element method alone when utilizing a GPU.While still ensuring high accuracy,this makes it well-suited for practical applications when reliable payzone assessment is needed in complex environmental scenarios.Furthermore,the algorithm’s efficiency positions it as a promising tool for stochastic Bayesian inversion,facilitating reliable uncertainty quantification in subsurface property estimation.
基金National Natural Science Foundation of China(No.61975029)。
文摘Multifocal metalenses are of great concern in optical communications,optical imaging and micro-optics systems,but their design is extremely challenging.In recent years,deep learning methods have provided novel solutions to the design of optical planar devices.Here,an approach is proposed to explore the use of generative adversarial networks(GANs)to realize the design of metalenses with different focusing positions at dual wavelengths.This approach includes a forward network and an inverse network,where the former predicts the optical response of meta-atoms and the latter generates structures that meet specific requirements.Compared to the traditional search method,the inverse network demonstrates higher precision and efficiency in designing a dual-wavelength bifocal metalens.The results will provide insights and methodologies for the design of tunable wavelength metalenses,while also highlighting the potential of deep learning in optical device design.
基金the National Key R&D Program of China(Nos.2018YFD0901506,2018YFD0900305)the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(No.2018 SDKJ0406-3)。
文摘Insertional mutation,phenotypic evaluation,and mutated gene cloning are widely used to clone genes from scratch.Exogenous genes can be integrated into the genome during non-homologous end joining(NHEJ)of the double-strand breaks of DNA,causing insertional mutation.The random insertional mutant library constructed using this method has become a method of forward genetics for gene cloning.However,the establishment of a random insertional mutant library requires a high transformation efficiency of exogenous genes.Many microalgal species show a low transformation efficiency,making constructing random insertional mutant libraries difficult.In this study,we established a highly efficient transformation method for constructing a random insertional mutant library of Nannochloropsis oceanica,and tentatively tried to isolate its genes to prove the feasibility of the method.A gene that may control the growth rate and cell size was identified.This method will facilitate the genetic studies of N.oceanica,which should also be a reference for other microalgal species.
基金funded by the King Salman Center for Disability Research through Research Group No.KSRG-2023-335.
文摘Named Data Networking(NDN)has emerged as a promising communication paradigm,emphasizing content-centric access rather than location-based access.This model offers several advantages for Internet of Healthcare Things(IoHT)environments,including efficient content distribution,built-in security,and natural support for mobility and scalability.However,existing NDN-based IoHT systems face inefficiencies in their forwarding strategy,where identical Interest packets are forwarded across multiple nodes,causing broadcast storms,increased collisions,higher energy consumption,and delays.These issues negatively impact healthcare system performance,particularly for individuals with disabilities and chronic diseases requiring continuous monitoring.To address these challenges,we propose a Smart and Energy-Aware Forwarding(SEF)strategy based on reinforcement learning for NDN-based IoHT.The SEF strategy leverages the geographical distance and energy levels of neighboring nodes,enabling devices to make more informed forwarding decisions and optimize next-hop selection.This approach reduces broadcast storms,optimizes overall energy consumption,and extends network lifetime.The system model,which targets smart hospitals and monitoring systems for individuals with disabilities,was examined in relation to the proposed strategy.The SEF strategy was then implemented in the NS-3 simulation environment to assess its performance in healthcare scenarios.Results demonstrated that SEF significantly enhanced NDN-based IoHT performance.Specifically,it reduced energy consumption by up to 27.11%,82.23%,and 84.44%,decreased retrieval time by 20.23%,48.12%,and 51.65%,and achieved satisfaction rates that were approximately 0.69 higher than those of other strategies,even in more densely populated areas.This forwarding strategy is anticipated to substantially improve the quality and efficiency of NDN-based IoHT systems.
基金Supported by Key Research and Development Project of Guangxi Pr ovince(No.AB21196028).
文摘Unmanned aerial vehicle transient electromagnetic(UAV-TEM)is a novel airborne exploration method that offers advantages such as low cost,simple operation,high exploration efficiency and suitability for near-surface exploration in complex terrain areas.To improve the accuracy of data interpretation in this method,the authors conducted a systematic three-dimensional(3D)forward modeling and inversion of the UAV-TEM.This study utilized the finite element method based on unstructured tetrahedral elements and employed the second-order backward Euler method for time discretization.This allowed for accurate 3D modeling and accounted for the effects of complex terrain.Based on these,the influence characteristics of flight altitudes and the sizes,burial depths,and resistivities of anomalies are compared and analyzed to explore the UAV-TEM systems’exploration capability.Lastly,four typical geoelectrical models of landslides are designed,and the inversion method based on the Gauss-Newton optimization method is used to image the landslide models and analyze the imaging effect of the UAV-TEM method on landslide geohazards.Numerical results showed that UAV-TEM could have better exploration resolution and fine imaging of nearsurface structures,providing important technical support for monitoring,early warning,and preventing landslides and other geological hazards.
文摘The superparamagnetic effect arises from the superparamagnetism exhibited by a multitude of nano-sized magnetic mineral particles under an external electric field.This phenomenon manifests in transient electromagnetic data primarily as a deceleration in the attenuation rate of late-stage signals,a characteristic difficult to discern directly from airborne transient electromagnetic signals,consequently leading to significant misinterpretations of subterranean electrical structures.This study embarks on 3D forward modeling of airborne electromagnetic responses in the frequency domain,accounting for the superparamagnetic effect,utilizing an unstructured finite element method.Superparamagnetic responses in the time domain were obtained through frequency-time conversion.This investigation explores the influence of various parameters-such as magnetic susceptibility,time constants,and flight altitude-on the superparamagnetic effect by examining the response characteristics of typical targets.Findings indicate that in its late stages,the superparamagnetic effect can induce a relative anomaly of up to 300%.There is a positive correlation between magnetic susceptibility and the strength of the superparamagnetic effect.The influence of the time constant's upper and lower limits on the superparamagnetic effect is minimal;however,the range between these limits significantly affects the effect,showing a negative correlation with its intensity.Higher flight altitudes weaken the superparamagnetic signal.The impact is most pronounced when superparamagnetic minerals are shallowly buried,effectively shielding the underlying geology with the characteristics of a good conductivity anomaly,but this effect diminishes with greater depth.The insights from this study provide a theoretical framework for a deeper understanding of the superparamagnetic effect in transient electromagnetic signals and for more accurate interpretations of subterranean geological and electrical structures.
基金supported by the National Natural Science Foundation of China(Grant Nos.42250103 and 42174090)the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(Grant No.GLAB2023ZR02)the Ministry of Science and Technology(MOST)Special Fund from the State Key Laboratory of Geological Processes and Mineral Resources(Grant No.MSFGPMR2022-4)。
文摘As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal variations in the lithosphere.Traditional approaches either do not consider the non-axial dipolar terms of the inducing field and its radial variation or do so by means of complicated formulae.Moreover,existing methods treat the magnetic lithosphere either as an infinitesimally thin layer or as a radially uniform spherical shell of constant thickness.Here,we present alternative forward formulae that account for an arbitrarily high maximum degree of the inducing field and for a magnetic lithosphere of variable thickness.Our simulations based on these formulae suggest that the satellite magnetic anomaly field is sensitive to the non-axial dipolar terms of the inducing field but not to its radial variation.Therefore,in forward and inverse calculations of satellite magnetic anomaly data,the non-axial dipolar terms of the inducing field should not be ignored.Furthermore,our results show that the satellite magnetic anomaly field is sensitive to variability in the lateral thickness of the magnetized shell.In particular,we show that for a given vertically integrated susceptibility distribution,underestimating the thickness of the magnetic layer overestimates the induced magnetic field.This discovery bridges the greatest part of the alleged gap between the susceptibility values measured from rock samples and the susceptibility values required to match the observed magnetic field signal.We expect the formulae and conclusions of this study to be a valuable tool for the quantitative interpretation of the Earth's global lithospheric magnetic field,through an inverse or forward modelling approach.
基金Supported by National Natural Science Foundation of China (Grant No. 52175019)Beijing Municipal Natural Science Foundation of China (Grant No. L222038)+3 种基金Beijing Nova Programme Interdisciplinary Cooperation Project of China (Grant No. 20240484699)Joint Funds of Industry-University-Research of Shanghai Academy of Spaceflight Technology of China (Grant No. SAST2022-017)Beijing Municipal Key Laboratory of Space-ground Interconnection and Convergence of ChinaKey Laboratory of IoT Monitoring and Early Warning,Ministry of Emergency Management of China
文摘To investigate the forward kinematics problem of parallel mechanisms with complex limbs and to expand the applicability of the powerful tool of Conformal Geometric Algebra(CGA),a CGA-based modeling and solution method for a class of parallel platforms with 3-RE structure after locking the actuated joints is proposed in this paper.Given that the angle between specific joint axes of limbs remains constant,a set of geometric constraints for the forward kinematics of parallel mechanisms(PM)are determined.After translating unit direction vectors of these joint axes to the common starting point,the geometric constraints of the angle between the vectors are transformed into the distances between the endpoints of the vectors,making them easier to handle.Under the framework of CGA,the positions of key points that determine the position and orientation of the moving platform can be intuitively determined by the intersection,division,and duality of basic geometric entities.By employing the tangent half-angle substitution,the forward kinematic analysis of the parallel mechanisms leads to a high-order univariate polynomial equation without the need for any complex algebraic elimination operations.After solving this equation and back substitution,the position and pose of the MP can be obtained indirectly.A numerical case is utilized to confirm the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(42250101,42250102,42250103,12250013)the Macao Foundation。
文摘The Earth's magnetic field,which has been extensively observed from ground to satellite altitudes over several decades,originates from multiple sources,such as the core dynamo,the conductive mantle,the magnetized lithosphere,and the space current systems.Modeling of the lithospheric contribution plays an important role in the geophysical studies and industrial applications.In this paper,we propose a new method for global and regional modeling of the lithospheric magnetic field based on the cubed-sphere.An equivalent dipole source method on a quasi-uniform cubed-sphere grid is employed in the forward modeling.The dipole directions are fixed according to a priori magnetization and the relative intensities are estimated by an inversion procedure of least-squares fitting with minimum model regularization.Several numerical tests are performed to validate the accuracy and efficiency of both forward modeling and inversion procedure.The proposed method is applied to the global and regional modeling based on the latest magnetic data from Swarm Alpha satellite and MSS-1 mission.The model results indicate that the proposed method works quite well for realistic satellite data and MSS-1 data is consistent with the Swarm data in terms of lithospheric field modeling.
基金supported by the Opening Project of State Key Laboratory of Mechanical Transmission for Advanced Equipment(No.SKLMT-MSKFKT202330)the National Natural Science Foundation of China(No.52575022)the Jiangsu Province Postgraduate Research&Practice Innovation Program(No.KYCX25_1403)。
文摘This study presents a novel analytical algorithm for solving the forward position problem of a triangular platform Stewart-type parallel robot(STPR).By introducing a virtual chain and leveraging tetrahedral geometric principles,the proposed method derives analytical solutions for the position and orientation of the moving platform.The algorithm systematically addresses the nonlinearity inherent in the kinematic equations of parallel mechanisms,providing explicit expressions for the coordinates of key moving attachment points.Furthermore,the methodology is extended to general triangular platform STPRs with non-coplanar fixed attachments.Numerical validation through virtual experiments confirms the accuracy of the solutions,demonstrating that the mechanism admits eight distinct configurations for a given set of limb lengths.The results align with established kinematic principles and offer a computationally efficient alternative to iterative analytical approaches,contributing to the advancement of precision control in parallel robotic systems.
基金funding provided by the National Key R&D Program of China (Grant No. 2021YFB3801301)National Natural Science Foundation of China (Grant Nos. 22075076, 22208097 and 22378119)Shanghai Pilot Program for Basic Research (22TQ1400100-4)。
文摘Seawater electrolysis for hydrogen production faces inherent challenges, including side reactions, corrosion, and scaling, stemming from the intricate composition of seawater. In response, researchers have turned to continuous water splitting using forward osmosis(FO)-driven seawater desalination. However, the necessity of a neutral electrolyte hampers this strategy due to the limited current density and scarcity of precious metals. Herein, this study applies alkali-durable FO membranes to enable self-sustaining seawater splitting, which can selectively withdraw water molecules, from seawater, via concentration gradient. The membranes demonstrates outstanding perm-selectivity of water/ions(~5830 mol mol^(-1)) during month-long alkaline resistance tests, preventing electrolyte leaching(>97% OHàretention) while maintaining ~95%water balance(V_(FO)= V_(electrolysis)) via preserved concentration gradient for consistent forward-osmosis influx of water molecules. With the consistent electrolyte environment protected by the polyamide FO membranes, the Ni Fe-Ar-P catalyst exhibits promising performance: a sustain current density of 360 m A cmà2maintained at the cell voltage of 2.10 V and 2.15 V for 360 h in the offshore seawater, preventing Cl/Br corrosion(98% rejection) and Mg/Ca passivation(99.6% rejection). This research marks a significant advancement towards efficient and durable seawater-based hydrogen production.
文摘On the morning of May 31st,the parallel forum"Ecological Actions to Carry Forward the Shared Values of Mankind,"as part of the 4th Dialogue on Exchanges and Mutual Learning among Civilisations,was held in Dunhuang.More than 50 experts and scholars from different countries,including China,Kenya and Japan,engaged in indepth discussions on the theme.
文摘A temperature and acoustic impedance simultaneous sensor based on forward stimulated Brillouin scattering(FSBS)in highly nonlinear fiber(HNLF)with high sensitivity and high accuracy is proposed and demonstrated in this paper.High-order acoustic modes(HOAMs)are used to achieve individual or simultaneous measurement of the two parameters.Transverse acoustic waves(TAWs)involved in the FSBS process can efficiently sense the mechanical or environmental changes outside the fiber cladding,which will be reflected in a linear shift of the acoustic resonance frequency.By analyzing the frequencies of specific scattering peaks,the temperature and acoustic impedance outside the fiber cladding can be obtained simultaneously.The highest measured temperature and acoustic impedance sensitivities are 184.93 k Hz/℃and444.56 k Hz/MRayl,and the measurement accuracies are 0.09℃and 0.009 MRayl,respectively,which are both at desirable levels.We believe this work can provide potential application solutions for sensing fields involving temperature or acoustic impedance measurements.
文摘Objective To study the key technologies in the field of ginsenosides and to offer a guide for the future development ginsenosides through the main path identification method based on genetic knowledge persistence algorithm(GKPA).Methods The global ginsenoside invention authorized patents were used as the data source to construct a ginsenoside patent self-citation network,and to identify high knowledge persistent patents(HKPP)of ginsenoside technology based on the GKPA,and extract its high knowledge persistence main path(HKPMP).Finally,the genetic forward and backward path(GFBP)was used to search the nodes on the main path,and draw the genetic forward and backward main path(GFBMP)of ginsenoside technology.Results and Conclusion The algorithm was applied to the field of ginsenosides.The research results show the milestone patents in ginsenosides technology and the main evolution process of three key technologies,which points out the future direction for the technological development of ginsenosides.The results obtained by this algorithm are more interpretable,comprehensive and scientific.
基金The National Natural Science Foundation of China(No.60621002)the National High Technology Research and Development Pro-gram of China(863 Program)(No.2007AA01Z2B4).
文摘A novel behavioral model using three-layer time-delay feed-forward neural networks （TDFFNN）is adopted to model radio frequency （RF）power amplifiers exhibiting memory nonlinearities. In order to extract the parameters, the back- propagation algorithm is applied to train the proposed neural networks. The proposed model is verified by the typical odd- order-only memory polynomial model in simulation, and the performance is compared with different numbers of taped delay lines（TDLs） and perceptrons of the hidden layer. For validating the TDFFNN model by experiments, a digital test bench is set up to collect input and output data of power amplifiers at a 60 × 10^6 sample/s sampling rate. The 3.75 MHz 16-QAM signal generated in the vector signal generator（VSG） is chosen as the input signal, when measuring the dynamic AM/AM and AM/PM characteristics of power amplifiers. By comparisons and analyses, the presented model provides a good performance in convergence, accuracy and efficiency, which is approved by simulation results and experimental results in the time domain and frequency domain.
基金supported by the Program for New Century Excellent Talents in University(No.NCET-04-0370)
文摘We discuss the feasibility of using controlled-source electromagnetic （CSEM） in the frequency domain for prospecting marine gas hydrates. Based on the Ocean Drilling Program （ODP） Leg 164 log data, we have established several 1-D resistivity models which have different gas hydrate concentrations. Meanwhile, we analyzed the electromagnetic response of marine gas hydrates in the frequency domain based on these models. We also studied the relationship between electrical field magnitude or phase and parameters such as receiver-transmitter distance and frequency. Our numerical modeling results provide us with a quantitative reference for exploration and resource evaluation of marine gas hydrates.
基金This research is sponsored by the National Natural Science Foundation of China （No. 40374024）.
文摘The workload of the 3D magnetotelluric forward modeling algorithm is so large that the traditional serial algorithm costs an extremely large compute time. However, the 3D forward modeling algorithm can process the data in the frequency domain, which is very suitable for parallel computation. With the advantage of MPI and based on an analysis of the flow of the 3D magnetotelluric serial forward algorithm, we suggest the idea of parallel computation and apply it. Three theoretical models are tested and the execution efficiency is compared in different situations. The results indicate that the parallel 3D forward modeling computation is correct and the efficiency is greatly improved. This method is suitable for large size geophysical computations.
基金the National Natural Science Foundation of China (No. 50677062)the New Century Excellent Talents in Uni-versity of China (No. NCET-07-0745)the Natural Science Foundation of Zhejiang Province, China (No. R107062)
文摘In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global sin-gle-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems.
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.
