This study examines whether and how cues focusing enhances Chinese-speaking English learners’engagement in comparison,thereby facilitating their acquisition of English articles within xu-based comparative continuatio...This study examines whether and how cues focusing enhances Chinese-speaking English learners’engagement in comparison,thereby facilitating their acquisition of English articles within xu-based comparative continuation writing tasks.Fifty English majors from a Chinese university were randomly assigned to three groups and each group was required to complete a comparative continuation task with one of three conditions:paired cues(cues presented in pairs),randomized cues(cues presented in random order),or implicit cues(no explicit cues provided).All participants undertook pretests,posttests,and delayed tests on English article knowledge,and ten of them volunteered to take follow-up interviews.The results indicate that:1)paired cues were more effective than randomized or implicit cues in promoting the acquisition of English articles;and 2)learners in the paired cues condition produced more target-like article usage in their continuation writings compared to those in the other two conditions.The effectiveness of paired cues is attributed to an enhanced contrast effect,which prompts learners to identify similarities and differences between cues within each pair,relates cue explanations and examples with actual article usage in the reading text,and reflects upon and compares their own article productions against those in the provided reading text.The study concludes that the process of learning through continuation is fundamentally supported by learners’capacity for comparison,reinforcing its role as a core element of xu-competence.展开更多
This interview examines the theoretical foundations,pedagogical applications,developmental trajectory,and future directions of the xu-argument.Professor Wang Chuming offers a comprehensive account of the xu-argument,c...This interview examines the theoretical foundations,pedagogical applications,developmental trajectory,and future directions of the xu-argument.Professor Wang Chuming offers a comprehensive account of the xu-argument,clarifying its theoretical framework,the learning mechanisms underlying xu,and its interface with international theories of second language acquisition(SLA).From the perspective of the xu-argument,he proposes novel interpretations of core issues in SLA.Drawing on the development of the xu-argument,Wang further discusses the essence,directions,and methodology of innovation in SLA theory.He emphasizes that theoretical advances must capture and illuminate underlying natural laws,arguing that innovative approaches are typically rooted in deep reflection on common sense.He also calls for theoretical innovation in SLA in the Chinese context,advocating a robust research paradigm that shifts from local observation to global theoretical generalization,thereby promoting bottom-up theoretical development.In closing,he highlights the promising prospects for SLA theory in the era of artificial intelligence.展开更多
Nuclear magnetic resonance(NMR)spectroscopy is a powerful tool for analyzing molecular structure and composition.However,traditional NMR experiments suffer from long acquisition times,especially in multidimensional NM...Nuclear magnetic resonance(NMR)spectroscopy is a powerful tool for analyzing molecular structure and composition.However,traditional NMR experiments suffer from long acquisition times,especially in multidimensional NMR spectroscopy.This problem,to some extent,limits broader applications of NMR techniques.Various methods have been proposed to accelerate sampling,including non-uniform sampling(NUS),multi-FID acquisition(MFA),Hadamard encoding,Fourier encoding,spatial encoding Ultrafast 2D NMR(UF2DNMR),and so on.The review focuses on rapid sampling methods developed in contemporary China,introducing their fundamental principles and applications while discussing their respective advantages and disadvantages.展开更多
In this work we describe a multi-parameter data acquisition system(DAQ)which has been developed for the Shanghai EBIT.This system is operated at the collision research platform which includes a recoil-ion momentum spe...In this work we describe a multi-parameter data acquisition system(DAQ)which has been developed for the Shanghai EBIT.This system is operated at the collision research platform which includes a recoil-ion momentum spectrometer(RIMS).We have employed DAQ based on the VME system,which is a very fast developing system within the RIMS community,and with which we can reach data transfer rates of up to 160 Mb·s- 1.The software developed for DAQ based on UnisDX-XP is also described.展开更多
Phosphorus(P)is an essential nutrient for crop growth,making it important for maintaining food security as the global population continues to increase.Plants acquire P primarily via the uptake of inorganic phosphate(P...Phosphorus(P)is an essential nutrient for crop growth,making it important for maintaining food security as the global population continues to increase.Plants acquire P primarily via the uptake of inorganic phosphate(Pi)in soil through their roots.Pi,which is usually sequestered in soils,is not easily absorbed by plants and represses plant growth.Plants have developed a series of mechanisms to cope with P deficiency.Moreover,P fertilizer applications are critical for maximizing crop yield.Maize is a major cereal crop cultivated worldwide.Increasing its P-use efficiency is important for optimizing maize production.Over the past two decades,considerable progresses have been achieved in studies aimed at adapting maize varieties to changes in environmental P supply.Here,we present an overview of the morphological,physiological,and molecular mechanisms involved in P acquisition,translocation,and redistribution in maize and combine the advances in Arabidopsis and rice,to better elucidate the progress of P nutrition.Additionally,we summarize the correlation between P and abiotic stress responses.Clarifying the mechanisms relevant to improving P absorption and use in maize can guide future research on sustainable agriculture.展开更多
Based on waveform fitting,full waveform inversion(FWI)is an important inversion method with the ability to reconstruct multi-parameter models in high precision.However,the strong nonlinear equation used in FWI present...Based on waveform fitting,full waveform inversion(FWI)is an important inversion method with the ability to reconstruct multi-parameter models in high precision.However,the strong nonlinear equation used in FWI presents the following challenges,such as low convergence efficiency,high dependence on the initial model,and the energy imbalance in deep region of the inverted model.To solve these inherent problems,we develop a timedomain elastic FWI method based on gradient preconditioning with the following details:(1)the limited memory Broyden Fletcher Goldfarb Shanno method with faster convergence is adopted to im-prove the inversion stability;(2)a multi-scaled inversion strategy is used to alleviate the nonlinear inversion instead of falling into the local minimum;(3)in addition,the pseudo-Hessian preconditioned illumination operator is involved for preconditioning the parameter gradients to improve the illumination equilibrium degree of deep structures.Based on the programming implementation of the new method,a deep depression model with five diffractors is used for testing.Compared with the conventional elastic FWI method,the technique proposed by this study has better effectiveness and accuracy on the inversion effect and con-vergence,respectively.展开更多
With the continued expansion of oil and gas exploration,both in the eastern and western regions,the quality of seismic acquisition has become a key factor in oil and gas exploration in complex areas.However,convention...With the continued expansion of oil and gas exploration,both in the eastern and western regions,the quality of seismic acquisition has become a key factor in oil and gas exploration in complex areas.However,conventional seismic acquisition methods cannot efficiently avoid challenging acquisition locations and produce high-quality seismic data.In this regard,based on the curvelet transform,this paper proposes an irregular seismic acquisition method,which utilizes the high-precision characteristics of the curvelet transform and simulated annealing algorithm to establish a method for the evaluation of the coherence of irregular sampling matrices and design of observation systems.The method was verified using forward simulation and actual acquisition data.The results suggest the superior quality of seismic data gathered in complicated areas through this method over those acquired using traditional methods,which can provide technical guidance for the design of observation systems in complex areas.展开更多
In this article,the multi-parameters Mittag-Leffler function is studied in detail.As a consequence,a series of novel results such as the integral representation,series representation and Mellin transform to the above ...In this article,the multi-parameters Mittag-Leffler function is studied in detail.As a consequence,a series of novel results such as the integral representation,series representation and Mellin transform to the above function,are obtained.Especially,we associate the multi-parameters Mittag-Leffler function with two special functions which are the generalized Wright hypergeometric and the Fox’s-H functions.Meanwhile,some interesting integral operators and derivative operators of this function,are also discussed.展开更多
Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in...Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in time-independent Hamiltonians.Here,our work makes an effort to explore multi-parameter estimation with time-dependent Hamiltonians.In particular,we focus on the discrimination of two close frequencies of a magnetic field by using a single qubit.We optimize the quantum controls by employing both traditional optimization methods and reinforcement learning to improve the precision for estimating the frequencies of the two magnetic fields.In addition to the estimation precision,we also evaluate the robustness of the optimization schemes against the shift of the control parameters.The results demonstrate that the hybrid reinforcement learning approach achieves the highest estimation precision,and exhibits superior robustness.Moreover,a fundamental challenge in multi-parameter quantum estimation stems from the incompatibility of the optimal control strategies for different parameters.We demonstrate that the hybrid control strategies derived through numerical optimization remain effective in enhancing the precision of multi-parameter estimation in spite of the incompatibilities,thereby mitigating incompatibilities between control strategies on the estimation precision.Finally,we investigate the trade-offs in estimation precision among different parameters for different scenarios,revealing the inherent challenges in balancing the optimization of multiple parameters simultaneously and providing insights into the fundamental distinction between quantum single-parameter estimation and multi-parameter estimation.展开更多
Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).C...Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).Conventional battery monitoring technologies struggle to track multiple physicochemical parameters in real time,hindering early hazard detection.Embedded optical fiber sensors have gained prominence as a transformative solution for next-generation smart battery sensing,owing to their micrometer size,multiplexing capability,and electromagnetic immunity.However,comprehensive reviews focusing on their advancements in operando multi-parameter monitoring remain scarce,despite their critical importance for ensuring battery safety.To address this gap,this review first introduces a classification and the fundamental principles of advanced battery-oriented optical fiber sensors.Subsequently,it summarizes recent developments in single-parameter battery monitoring using optical fiber sensors.Building on this foundation,this review presents the first comprehensive analysis of multifunctional optical fiber sensing platforms capable of simultaneously tracking temperature,strain,pressure,refractive index,and monitoring battery aging.Targeted strategies are proposed to facilitate the practical development of this technology,including optimization of sensor integration techniques,minimizing sensor invasiveness,resolving the cross-sensitivity of fiber Bragg grating(FBG)through structural innovation,enhancing techno-economics,and combining with artificial intelligence(AI).By aligning academic research with industry requirements,this review provides a methodological roadmap for developing robust optical sensing systems to ensure battery safety in decarbonization-driven applications.展开更多
Deblending is a data processing procedure used to separate the source interferences of blended seismic data,which are obtained by simultaneous sources with random time delays to reduce the cost of seismic acquisition....Deblending is a data processing procedure used to separate the source interferences of blended seismic data,which are obtained by simultaneous sources with random time delays to reduce the cost of seismic acquisition.There are three types of deblending algorithms,i.e.,filtering-type noise suppression algorithm,inversion-based algorithm and deep-learning based algorithm.We review the merits of these techniques,and propose to use a sparse inversion method for seismic data deblending.Filtering-based deblending approach is applicable to blended data with a low blending fold and simple geometry.Otherwise,it can suffer from signal distortion and noise leakage.At present,the deep learning based deblending methods are still under development and field data applications are limited due to the lack of high-quality training labels.In contrast,the inversion-based deblending approaches have gained industrial acceptance.Our used inversion approach transforms the pseudo-deblended data into the frequency-wavenumber-wavenumher(FKK)domain,and a sparse constraint is imposed for the coherent signal estimation.The estimated signal is used to predict the interference noise for subtraction from the original pseudo-deblended data.Via minimizing the data misfit,the signal can be iteratively updated with a shrinking threshold until the signal and interference are fully separated.The used FKK sparse inversion algorithm is very accurate and efficient compared with other sparse inversion methods,and it is widely applied in field cases.Synthetic example shows that the deblending error is less than 1%in average amplitudes and less than-40 dB in amplitude spectra.We present three field data examples of land,marine OBN(Ocean Bottom Nodes)and streamer acquisitions to demonstrate its successful applications in separating the source interferences efficiently and accurately.展开更多
The paper aims to examine the application of multimedia technology in expanding vocabulary in second language acquisition.Incorporating innovative technology such as mobile applications,gaming applications,websites,an...The paper aims to examine the application of multimedia technology in expanding vocabulary in second language acquisition.Incorporating innovative technology such as mobile applications,gaming applications,websites,and other related online tools has increased learners’vocabulary mastery,engagement,and motivation levels.Interactional processes like media-embedded objects,teach-learning capacity algorithms,and feedback help learners receive the course in a personalized way that considers individual learning patterns or abilities.However,there are the following challenges:accessibility issues,total reliance on technology,and issues related to privacy.The following challenges affecting learning that arise from using gadgets:the digital divide,limited device access,and environmental issues that may distract a learner in a technology-enabled environment.Moreover,the security issue for data and the ethical question of users’information remain important too.Hence,the paper provides arguments that although these technologies contribute significantly to vocabulary acquisition,the challenge that emerges should be addressed by integrating technology in teaching and learning alongside conventional methods for vocabulary acquisition,which is a practical language acquisition tool that should not be monopolized.展开更多
This article focuses on financial management issues in mergers and acquisitions(M&A).It provides an indepth analysis of the financial risks and management challenges faced by contemporary businesses during various...This article focuses on financial management issues in mergers and acquisitions(M&A).It provides an indepth analysis of the financial risks and management challenges faced by contemporary businesses during various stages of M&A,such as pre-merger valuation pricing difficulties,unreasonable financing structures,risks in payment method selection,obstacles to financial integration,and lack of risk management.Targeted management strategies are proposed to address these issues.This paper suggests strengthening due diligence and valuation management,optimizing financing structures,rationally selecting payment methods,deepening financial integration,and improving tax planning.These strategies aim to enhance the level of financial management in M&A,promote economic synergies and management effects,help companies quickly achieve M&A goals,and drive sustainable business development.展开更多
Under sensorless control, the position estimation error in interior permanent magnet(PM) synchronous machines will lead to parameter identification errors and a rank-deficiency issue. This paper proposes a parameter i...Under sensorless control, the position estimation error in interior permanent magnet(PM) synchronous machines will lead to parameter identification errors and a rank-deficiency issue. This paper proposes a parameter identification model that is independent of position error by combining the dq-axis voltage equations. Then, a novel dual signal alternate injection method is proposed to address the rank-deficiency issue, i.e., during one injection period, a zero, positive, and negative d-axis current injection together with a rotor position offset injection, to simultaneously identify the multi-parameters, including stator resistance, dq-axis inductances, and PM flux linkage. The proposed method is verified by experiments at different dq-axis current conditions.展开更多
In the anticorrosive coating line of a welded tube plant, the current status and existing problems of the medium-frequency induction heating equipment were discussed.Partial renovations of the power control cabinet ha...In the anticorrosive coating line of a welded tube plant, the current status and existing problems of the medium-frequency induction heating equipment were discussed.Partial renovations of the power control cabinet have been conducted.Parameters such as the DC current, DC voltage, intermediate frequency power, heating temperature, and the positioning signal at the pipe end were collected.A data acquisition and processing system, which can process data according to user needs and provide convenient data processing functions, has been developed using LabVIEW software.This system has been successfully applied in the coating line for the automatic control of high-power induction heating equipment, production management, and digital steel tube and/or digital delivery.展开更多
The paper is an introduction to the front-end pulse acquisition and the back-end pulse biomimetic reproduction system.This system is capable of faithfully replicating the complete pulse waveform collected at the front...The paper is an introduction to the front-end pulse acquisition and the back-end pulse biomimetic reproduction system.This system is capable of faithfully replicating the complete pulse waveform collected at the front end.Traditional Chinese Medicine(TCM)practitioners analyze and diagnose the pulse patterns at the replication end.Meanwhile,the obtained pulse waveforms are analyzed and learnt by a neural network based on key diagnostic points in TCM pulse taking,which enables the determination of the corresponding relationships between different pulse waveforms and various pulse patterns in TCM pulse taking.With the support of clinical samples,an auxiliary diagnostic system for TCM pulse patterns ensures the accuracy of pulse pattern replication.展开更多
Objective To explore the impact of mergers and acquisitions(M&A)on the innovation performance of the companies from both a patent perspective and a financial perspective by taking the case of M&A Company J as ...Objective To explore the impact of mergers and acquisitions(M&A)on the innovation performance of the companies from both a patent perspective and a financial perspective by taking the case of M&A Company J as an example.Methods The literature research method,patent data analysis method,and financial data analysis method were used.Results:The M&A has a positive impact on the innovation performance of Company J,and the results from the patent perspective and the financial perspective are consistent.Results and Conclusion The literature research method,patent data analysis method,and financial data analysis method were used.The M&A has a positive impact on the innovation performance of Company J,and the results from the patent perspective and the financial perspective are consistent.展开更多
Dengue virus(DENV)remains a pervasive global health threat,further complicated by the occurrence of neutropenia-a distinct clinical feature indicative of an altered host immune response,closely correlated with progres...Dengue virus(DENV)remains a pervasive global health threat,further complicated by the occurrence of neutropenia-a distinct clinical feature indicative of an altered host immune response,closely correlated with progressive disease deterioration and increased severity.Nevertheless,the molecular mechanisms underlying dengue-associated neutropenia remain inadequately elucidated.In this study,the comprehensive plasma proteomic profiling of dengue fever(DF)patients,DF patients with neutropenia(DFN),and healthy controls(HC)was systematically analyzed using a deep dataindependent acquisition(DIA)workflow combined with LC-MS/MS analysis,to elucidate key cellular pathways and identify promising biomarkers.DFN patients exhibited significant dual hematological alterations,with notable changes in both platelet and neutrophil counts,reflecting a complex disturbance in hematological homeostasis during dengue progression.DIA analysis quantified 2475 proteins,revealing widespread proteomic alterations among the DF,DFN,and HC subjects.Differential analysis highlighted significant fluctuations in proteins related to cytoskeletal organization,metabolic regulation,and intracellular signaling.Enrichment analyses implicated pathways such as focal adhesion,platelet activation,and PI3K-Akt signaling.Machine learning methods further identified a panel of four biomarkers-CNST,DSTN,DUSP3,and PDIA5-with high predictive accuracy for dengue diagnosis and subgroup differentiation.In conclusion,this study advances our understanding of dengue’s plasma proteomic landscape and underscores the synergistic potential of DIA-based proteomics and machine learning in unveiling host-response mechanisms,thereby informing early diagnosis and targeted therapeutic strategies.展开更多
Against the backdrop of increasingly prominent global environmental issues,heavily polluting enterprises(HPPs)urgently need to find a path to green transformation that achieves sustainable development and overcomes ef...Against the backdrop of increasingly prominent global environmental issues,heavily polluting enterprises(HPPs)urgently need to find a path to green transformation that achieves sustainable development and overcomes efficiency challenges.Based on data on mergers and acquisitions of HPPs from 2010 to 2023,this article explores the direct impact and mechanisms of green mergers and acquisitions(GMAs)on enterprises green transformation.Research findings are as follows:(1)GMAs significantly promote the green transformation of HPPs,a conclusion that is robust across various tests.(2)Internal control and green innovation quality serve as partial and chain mediators,respectively,in the relationship between GMAs and the green transformation of HPPs.(3)Media pressure negatively affects the impact of GMAs on internal control.(4)The heterogeneity analysis shows that the GMAs of enterprises in the eastern region,non-state-owned enterprises,large enterprises,and enterprises in the electricity,heat,gas,and water production and supply industries have a more obvious impact on green transformation.These findings elucidate the mechanisms through which GMAs drive the green transformation of HPPs and offer empirical insights into supporting the sustainable development of such enterprises in China.展开更多
文摘This study examines whether and how cues focusing enhances Chinese-speaking English learners’engagement in comparison,thereby facilitating their acquisition of English articles within xu-based comparative continuation writing tasks.Fifty English majors from a Chinese university were randomly assigned to three groups and each group was required to complete a comparative continuation task with one of three conditions:paired cues(cues presented in pairs),randomized cues(cues presented in random order),or implicit cues(no explicit cues provided).All participants undertook pretests,posttests,and delayed tests on English article knowledge,and ten of them volunteered to take follow-up interviews.The results indicate that:1)paired cues were more effective than randomized or implicit cues in promoting the acquisition of English articles;and 2)learners in the paired cues condition produced more target-like article usage in their continuation writings compared to those in the other two conditions.The effectiveness of paired cues is attributed to an enhanced contrast effect,which prompts learners to identify similarities and differences between cues within each pair,relates cue explanations and examples with actual article usage in the reading text,and reflects upon and compares their own article productions against those in the provided reading text.The study concludes that the process of learning through continuation is fundamentally supported by learners’capacity for comparison,reinforcing its role as a core element of xu-competence.
文摘This interview examines the theoretical foundations,pedagogical applications,developmental trajectory,and future directions of the xu-argument.Professor Wang Chuming offers a comprehensive account of the xu-argument,clarifying its theoretical framework,the learning mechanisms underlying xu,and its interface with international theories of second language acquisition(SLA).From the perspective of the xu-argument,he proposes novel interpretations of core issues in SLA.Drawing on the development of the xu-argument,Wang further discusses the essence,directions,and methodology of innovation in SLA theory.He emphasizes that theoretical advances must capture and illuminate underlying natural laws,arguing that innovative approaches are typically rooted in deep reflection on common sense.He also calls for theoretical innovation in SLA in the Chinese context,advocating a robust research paradigm that shifts from local observation to global theoretical generalization,thereby promoting bottom-up theoretical development.In closing,he highlights the promising prospects for SLA theory in the era of artificial intelligence.
基金financially supported by the National Natural Science Foundation of China(grant numbers 22174118,12411530077,and 22374124).
文摘Nuclear magnetic resonance(NMR)spectroscopy is a powerful tool for analyzing molecular structure and composition.However,traditional NMR experiments suffer from long acquisition times,especially in multidimensional NMR spectroscopy.This problem,to some extent,limits broader applications of NMR techniques.Various methods have been proposed to accelerate sampling,including non-uniform sampling(NUS),multi-FID acquisition(MFA),Hadamard encoding,Fourier encoding,spatial encoding Ultrafast 2D NMR(UF2DNMR),and so on.The review focuses on rapid sampling methods developed in contemporary China,introducing their fundamental principles and applications while discussing their respective advantages and disadvantages.
基金Supported by Shanghai Leading Academic Discipline Project(Project Number:B107)the Project-sponsored by SRF for ROCS,SEM
文摘In this work we describe a multi-parameter data acquisition system(DAQ)which has been developed for the Shanghai EBIT.This system is operated at the collision research platform which includes a recoil-ion momentum spectrometer(RIMS).We have employed DAQ based on the VME system,which is a very fast developing system within the RIMS community,and with which we can reach data transfer rates of up to 160 Mb·s- 1.The software developed for DAQ based on UnisDX-XP is also described.
基金supported by grants from the National Key Research and Development Program of China(2021YFF1000500)the National Natural Science Foundation of China(32370272,31970273,and 31921001).
文摘Phosphorus(P)is an essential nutrient for crop growth,making it important for maintaining food security as the global population continues to increase.Plants acquire P primarily via the uptake of inorganic phosphate(Pi)in soil through their roots.Pi,which is usually sequestered in soils,is not easily absorbed by plants and represses plant growth.Plants have developed a series of mechanisms to cope with P deficiency.Moreover,P fertilizer applications are critical for maximizing crop yield.Maize is a major cereal crop cultivated worldwide.Increasing its P-use efficiency is important for optimizing maize production.Over the past two decades,considerable progresses have been achieved in studies aimed at adapting maize varieties to changes in environmental P supply.Here,we present an overview of the morphological,physiological,and molecular mechanisms involved in P acquisition,translocation,and redistribution in maize and combine the advances in Arabidopsis and rice,to better elucidate the progress of P nutrition.Additionally,we summarize the correlation between P and abiotic stress responses.Clarifying the mechanisms relevant to improving P absorption and use in maize can guide future research on sustainable agriculture.
基金supported by the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(Grant No.2021QNLM020001)the National Key R&D Program of China(Grant No.2019YFC0605503C)+2 种基金the Major Scientific and Technological Projects of China National Petroleum Corporation(CNPC)(Grant No.ZD2019-183-003)the National Outstanding Youth Science Foundation(Grant No.41922028)the National Innovation Group Project(Grant No.41821002).
文摘Based on waveform fitting,full waveform inversion(FWI)is an important inversion method with the ability to reconstruct multi-parameter models in high precision.However,the strong nonlinear equation used in FWI presents the following challenges,such as low convergence efficiency,high dependence on the initial model,and the energy imbalance in deep region of the inverted model.To solve these inherent problems,we develop a timedomain elastic FWI method based on gradient preconditioning with the following details:(1)the limited memory Broyden Fletcher Goldfarb Shanno method with faster convergence is adopted to im-prove the inversion stability;(2)a multi-scaled inversion strategy is used to alleviate the nonlinear inversion instead of falling into the local minimum;(3)in addition,the pseudo-Hessian preconditioned illumination operator is involved for preconditioning the parameter gradients to improve the illumination equilibrium degree of deep structures.Based on the programming implementation of the new method,a deep depression model with five diffractors is used for testing.Compared with the conventional elastic FWI method,the technique proposed by this study has better effectiveness and accuracy on the inversion effect and con-vergence,respectively.
基金innovation consortium project of China Petroleum and Southwest Petroleum University(No.2020CX010201)Sichuan Science and Technology Program(No.2024NSFSC0081)。
文摘With the continued expansion of oil and gas exploration,both in the eastern and western regions,the quality of seismic acquisition has become a key factor in oil and gas exploration in complex areas.However,conventional seismic acquisition methods cannot efficiently avoid challenging acquisition locations and produce high-quality seismic data.In this regard,based on the curvelet transform,this paper proposes an irregular seismic acquisition method,which utilizes the high-precision characteristics of the curvelet transform and simulated annealing algorithm to establish a method for the evaluation of the coherence of irregular sampling matrices and design of observation systems.The method was verified using forward simulation and actual acquisition data.The results suggest the superior quality of seismic data gathered in complicated areas through this method over those acquired using traditional methods,which can provide technical guidance for the design of observation systems in complex areas.
基金Supported by The National Undergraduate Innovation Training Program(Grant No.202310290069Z).
文摘In this article,the multi-parameters Mittag-Leffler function is studied in detail.As a consequence,a series of novel results such as the integral representation,series representation and Mellin transform to the above function,are obtained.Especially,we associate the multi-parameters Mittag-Leffler function with two special functions which are the generalized Wright hypergeometric and the Fox’s-H functions.Meanwhile,some interesting integral operators and derivative operators of this function,are also discussed.
基金supported by the National Natural Science Foundation of China(Grant No.12075323)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0300702).
文摘Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in time-independent Hamiltonians.Here,our work makes an effort to explore multi-parameter estimation with time-dependent Hamiltonians.In particular,we focus on the discrimination of two close frequencies of a magnetic field by using a single qubit.We optimize the quantum controls by employing both traditional optimization methods and reinforcement learning to improve the precision for estimating the frequencies of the two magnetic fields.In addition to the estimation precision,we also evaluate the robustness of the optimization schemes against the shift of the control parameters.The results demonstrate that the hybrid reinforcement learning approach achieves the highest estimation precision,and exhibits superior robustness.Moreover,a fundamental challenge in multi-parameter quantum estimation stems from the incompatibility of the optimal control strategies for different parameters.We demonstrate that the hybrid control strategies derived through numerical optimization remain effective in enhancing the precision of multi-parameter estimation in spite of the incompatibilities,thereby mitigating incompatibilities between control strategies on the estimation precision.Finally,we investigate the trade-offs in estimation precision among different parameters for different scenarios,revealing the inherent challenges in balancing the optimization of multiple parameters simultaneously and providing insights into the fundamental distinction between quantum single-parameter estimation and multi-parameter estimation.
基金the financial supports of the National Natural Science Foundation of China(No.52372200)a project supported by the State Key Laboratory of Mechanics and Control for Aerospace Structures(No.MCAS-S-0324G01)。
文摘Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).Conventional battery monitoring technologies struggle to track multiple physicochemical parameters in real time,hindering early hazard detection.Embedded optical fiber sensors have gained prominence as a transformative solution for next-generation smart battery sensing,owing to their micrometer size,multiplexing capability,and electromagnetic immunity.However,comprehensive reviews focusing on their advancements in operando multi-parameter monitoring remain scarce,despite their critical importance for ensuring battery safety.To address this gap,this review first introduces a classification and the fundamental principles of advanced battery-oriented optical fiber sensors.Subsequently,it summarizes recent developments in single-parameter battery monitoring using optical fiber sensors.Building on this foundation,this review presents the first comprehensive analysis of multifunctional optical fiber sensing platforms capable of simultaneously tracking temperature,strain,pressure,refractive index,and monitoring battery aging.Targeted strategies are proposed to facilitate the practical development of this technology,including optimization of sensor integration techniques,minimizing sensor invasiveness,resolving the cross-sensitivity of fiber Bragg grating(FBG)through structural innovation,enhancing techno-economics,and combining with artificial intelligence(AI).By aligning academic research with industry requirements,this review provides a methodological roadmap for developing robust optical sensing systems to ensure battery safety in decarbonization-driven applications.
基金supported by National Science and Technology Major Project(Grant No.2017ZX05018-001)。
文摘Deblending is a data processing procedure used to separate the source interferences of blended seismic data,which are obtained by simultaneous sources with random time delays to reduce the cost of seismic acquisition.There are three types of deblending algorithms,i.e.,filtering-type noise suppression algorithm,inversion-based algorithm and deep-learning based algorithm.We review the merits of these techniques,and propose to use a sparse inversion method for seismic data deblending.Filtering-based deblending approach is applicable to blended data with a low blending fold and simple geometry.Otherwise,it can suffer from signal distortion and noise leakage.At present,the deep learning based deblending methods are still under development and field data applications are limited due to the lack of high-quality training labels.In contrast,the inversion-based deblending approaches have gained industrial acceptance.Our used inversion approach transforms the pseudo-deblended data into the frequency-wavenumber-wavenumher(FKK)domain,and a sparse constraint is imposed for the coherent signal estimation.The estimated signal is used to predict the interference noise for subtraction from the original pseudo-deblended data.Via minimizing the data misfit,the signal can be iteratively updated with a shrinking threshold until the signal and interference are fully separated.The used FKK sparse inversion algorithm is very accurate and efficient compared with other sparse inversion methods,and it is widely applied in field cases.Synthetic example shows that the deblending error is less than 1%in average amplitudes and less than-40 dB in amplitude spectra.We present three field data examples of land,marine OBN(Ocean Bottom Nodes)and streamer acquisitions to demonstrate its successful applications in separating the source interferences efficiently and accurately.
基金Interim Achievements of the“Yingying Technology Empowerment–Application-Oriented Talent Enhancement Project at Changchun College of Electronic Technology”under the Fourth Phase of the 2024 Ministry of Education’s Employment-Education Collaboration Project(Project Number:2024121188944Project Leader:Chunhua Ren)+3 种基金Interim Achievements of the“Directional Cultivation Project for Composite Talents at Changchun College of Electronic Technology”under the Fourth Phase of the 2024 Ministry of Education’s Supply-Demand Matching and Employment-Education Cultivation Program(Project Number:2024121107571Project Leader:Chunhua Ren)Interim Achievements of the“Research on the Cultivation Path of Craftsmanship Spirit among University Teachers in the Context of Industry-University Collaboration”under the 2025 Ministry of Education’s Industry-University Cooperative Education Project(Project Number:2505164755Project Leader:Chunhua Ren)。
文摘The paper aims to examine the application of multimedia technology in expanding vocabulary in second language acquisition.Incorporating innovative technology such as mobile applications,gaming applications,websites,and other related online tools has increased learners’vocabulary mastery,engagement,and motivation levels.Interactional processes like media-embedded objects,teach-learning capacity algorithms,and feedback help learners receive the course in a personalized way that considers individual learning patterns or abilities.However,there are the following challenges:accessibility issues,total reliance on technology,and issues related to privacy.The following challenges affecting learning that arise from using gadgets:the digital divide,limited device access,and environmental issues that may distract a learner in a technology-enabled environment.Moreover,the security issue for data and the ethical question of users’information remain important too.Hence,the paper provides arguments that although these technologies contribute significantly to vocabulary acquisition,the challenge that emerges should be addressed by integrating technology in teaching and learning alongside conventional methods for vocabulary acquisition,which is a practical language acquisition tool that should not be monopolized.
文摘This article focuses on financial management issues in mergers and acquisitions(M&A).It provides an indepth analysis of the financial risks and management challenges faced by contemporary businesses during various stages of M&A,such as pre-merger valuation pricing difficulties,unreasonable financing structures,risks in payment method selection,obstacles to financial integration,and lack of risk management.Targeted management strategies are proposed to address these issues.This paper suggests strengthening due diligence and valuation management,optimizing financing structures,rationally selecting payment methods,deepening financial integration,and improving tax planning.These strategies aim to enhance the level of financial management in M&A,promote economic synergies and management effects,help companies quickly achieve M&A goals,and drive sustainable business development.
文摘Under sensorless control, the position estimation error in interior permanent magnet(PM) synchronous machines will lead to parameter identification errors and a rank-deficiency issue. This paper proposes a parameter identification model that is independent of position error by combining the dq-axis voltage equations. Then, a novel dual signal alternate injection method is proposed to address the rank-deficiency issue, i.e., during one injection period, a zero, positive, and negative d-axis current injection together with a rotor position offset injection, to simultaneously identify the multi-parameters, including stator resistance, dq-axis inductances, and PM flux linkage. The proposed method is verified by experiments at different dq-axis current conditions.
文摘In the anticorrosive coating line of a welded tube plant, the current status and existing problems of the medium-frequency induction heating equipment were discussed.Partial renovations of the power control cabinet have been conducted.Parameters such as the DC current, DC voltage, intermediate frequency power, heating temperature, and the positioning signal at the pipe end were collected.A data acquisition and processing system, which can process data according to user needs and provide convenient data processing functions, has been developed using LabVIEW software.This system has been successfully applied in the coating line for the automatic control of high-power induction heating equipment, production management, and digital steel tube and/or digital delivery.
基金Key R&D Plan of Liaoning Province(No.202000357-JH13/103):Construction of Liaoning Traditional Chinese Medicine Industry Technology Innovation Research InstituteNational Key Research and Development Plan Special Project(No.2019JH2/10300040)。
文摘The paper is an introduction to the front-end pulse acquisition and the back-end pulse biomimetic reproduction system.This system is capable of faithfully replicating the complete pulse waveform collected at the front end.Traditional Chinese Medicine(TCM)practitioners analyze and diagnose the pulse patterns at the replication end.Meanwhile,the obtained pulse waveforms are analyzed and learnt by a neural network based on key diagnostic points in TCM pulse taking,which enables the determination of the corresponding relationships between different pulse waveforms and various pulse patterns in TCM pulse taking.With the support of clinical samples,an auxiliary diagnostic system for TCM pulse patterns ensures the accuracy of pulse pattern replication.
文摘Objective To explore the impact of mergers and acquisitions(M&A)on the innovation performance of the companies from both a patent perspective and a financial perspective by taking the case of M&A Company J as an example.Methods The literature research method,patent data analysis method,and financial data analysis method were used.Results:The M&A has a positive impact on the innovation performance of Company J,and the results from the patent perspective and the financial perspective are consistent.Results and Conclusion The literature research method,patent data analysis method,and financial data analysis method were used.The M&A has a positive impact on the innovation performance of Company J,and the results from the patent perspective and the financial perspective are consistent.
基金supported by National Key R&D Program of China(2023YFA0915600)Guangdong Basic and Applied Basic Research Foundation(2025B1515020010)+3 种基金Shenzhen Clinical Research Center for Emerging Infectious Diseases(LCYSSQ20220823091203007)Sanming Project of Medicine in Shenzhen(SZSM202311033)Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties(No.SZGSP011)Shenzhen High-level Hospital Construction Fund(XKJSCRGRK-006).
文摘Dengue virus(DENV)remains a pervasive global health threat,further complicated by the occurrence of neutropenia-a distinct clinical feature indicative of an altered host immune response,closely correlated with progressive disease deterioration and increased severity.Nevertheless,the molecular mechanisms underlying dengue-associated neutropenia remain inadequately elucidated.In this study,the comprehensive plasma proteomic profiling of dengue fever(DF)patients,DF patients with neutropenia(DFN),and healthy controls(HC)was systematically analyzed using a deep dataindependent acquisition(DIA)workflow combined with LC-MS/MS analysis,to elucidate key cellular pathways and identify promising biomarkers.DFN patients exhibited significant dual hematological alterations,with notable changes in both platelet and neutrophil counts,reflecting a complex disturbance in hematological homeostasis during dengue progression.DIA analysis quantified 2475 proteins,revealing widespread proteomic alterations among the DF,DFN,and HC subjects.Differential analysis highlighted significant fluctuations in proteins related to cytoskeletal organization,metabolic regulation,and intracellular signaling.Enrichment analyses implicated pathways such as focal adhesion,platelet activation,and PI3K-Akt signaling.Machine learning methods further identified a panel of four biomarkers-CNST,DSTN,DUSP3,and PDIA5-with high predictive accuracy for dengue diagnosis and subgroup differentiation.In conclusion,this study advances our understanding of dengue’s plasma proteomic landscape and underscores the synergistic potential of DIA-based proteomics and machine learning in unveiling host-response mechanisms,thereby informing early diagnosis and targeted therapeutic strategies.
基金supported by the National Natural Science Foundation of China“Reconstruction of Competitive Advantage of China's High-tech Industry from the Perspective of Dual Value Chain”(Grant No.71972063)Natural Science Foundation of Heilongjiang Province“Innovation Decision-making and Performance of Green Factories in Heilongjiang Province under the Dual Carbon Target:an Incentive Environmental Regulation Perspective”(Grant No.JJ2022LH0765)Key R&D Program(Soft Science Project)of Shandong Province,China“Research on the Development Status and Countermeasures of High-tech Enterprises in Shandong Province”(Grant No.2023RZB03024).
文摘Against the backdrop of increasingly prominent global environmental issues,heavily polluting enterprises(HPPs)urgently need to find a path to green transformation that achieves sustainable development and overcomes efficiency challenges.Based on data on mergers and acquisitions of HPPs from 2010 to 2023,this article explores the direct impact and mechanisms of green mergers and acquisitions(GMAs)on enterprises green transformation.Research findings are as follows:(1)GMAs significantly promote the green transformation of HPPs,a conclusion that is robust across various tests.(2)Internal control and green innovation quality serve as partial and chain mediators,respectively,in the relationship between GMAs and the green transformation of HPPs.(3)Media pressure negatively affects the impact of GMAs on internal control.(4)The heterogeneity analysis shows that the GMAs of enterprises in the eastern region,non-state-owned enterprises,large enterprises,and enterprises in the electricity,heat,gas,and water production and supply industries have a more obvious impact on green transformation.These findings elucidate the mechanisms through which GMAs drive the green transformation of HPPs and offer empirical insights into supporting the sustainable development of such enterprises in China.
