In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergen...In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.展开更多
The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the...The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.展开更多
This study looks at how the Belt and Road Initiative(BRI)has affected the economic convergence of the Central Asian Turkic Republics,China,Pakistan,and their major diplomatic partners in the Silk Road region.Using bet...This study looks at how the Belt and Road Initiative(BRI)has affected the economic convergence of the Central Asian Turkic Republics,China,Pakistan,and their major diplomatic partners in the Silk Road region.Using beta and sigma convergence models over a predetermined time frame,the research evaluates economic alignment trends statistically and looks into how trade openness,FDI,and human capital affect the convergence process.The research attempts to discover larger causes of convergence,such as institutional quality and geopolitical closeness,by combining econometric analysis with regional economic dynamics.The purpose of the results is to provide policy suggestions that will improve equitable and sustainable economic convergence inside the Silk Road circle,promoting international cooperation and growth.展开更多
The harmonic balance method(HBM)has been widely applied to get the periodic solution of nonlinear systems,however,its convergence rate as well as computation efficiency is dramatically degraded when the system is high...The harmonic balance method(HBM)has been widely applied to get the periodic solution of nonlinear systems,however,its convergence rate as well as computation efficiency is dramatically degraded when the system is highly non-smooth,e.g.,discontinuous.In order to accelerate the convergence,an enriched HBM is developed in this paper where the non-smooth Bernoulli bases are additionally introduced to enrich the conventional Fourier bases.The basic idea behind is that the convergence rate of the HB solution,as a truncated Fourier series,can be improved if the smoothness of the solution becomes finer.Along this line,using non-smooth Bernoulli bases can compensate the highly non-smooth part of the solution and then,the smoothness of the residual part for Fourier approximation is improved so as to achieve accelerated convergence.Numerical examples are conducted on systems with non-smooth restoring and/or external forces.The results confirm that the proposed enriched HBM indeed increases the convergence rate and the increase becomes more significant if more non-smooth bases are used.展开更多
In this paper,the convergence of the split-step theta method for stochastic differential equations is analyzed using stochastic C-stability and stochastic B-consistency.The fact that the numerical scheme,which is both...In this paper,the convergence of the split-step theta method for stochastic differential equations is analyzed using stochastic C-stability and stochastic B-consistency.The fact that the numerical scheme,which is both stochastically C-stable and stochastically B-consistent,is convergent has been proved in a previous paper.In order to analyze the convergence of the split-step theta method(θ∈[1/2,1]),the stochastic C-stability and stochastic B-consistency under the condition of global monotonicity have been researched,and the rate of convergence 1/2 has been explored in this paper.It can be seen that the convergence does not require the drift function should satisfy the linear growth condition whenθ=1/2 Furthermore,the rate of the convergence of the split-step scheme for stochastic differential equations with additive noise has been researched and found to be 1.Finally,an example is given to illustrate the convergence with the theoretical results.展开更多
This study investigates the convergence hypothesis and stochastic dynamics of agricultural land use and ecological balance across 13 major agricultural countries from 1992 to 2022.The study's concentrated samples ...This study investigates the convergence hypothesis and stochastic dynamics of agricultural land use and ecological balance across 13 major agricultural countries from 1992 to 2022.The study's concentrated samples are Russia,the United States,the Netherlands,Brazil,Germany,China,France,Spain,Italy,Canada,Belgium,Indonesia,and India.The research uncovers notable variations in ecological balance by utilizing a comprehensive set of advanced panel unit root tests(Panel CIPS,CADF,Panel-LM,Panel-KPSS,and Bahmani-Oskooee et al.’s Panel KPSS Unit Root Test).The findings highlight significant improvements in Canada,contrasting with declines in the Netherlands,France,Germany,and the United States.The results indicate convergence in ecological balance among these countries,suggesting that agricultural practices are progressively aligning with sustainability objectives.The considered countries can determine and enact joint and collective policy actions addressing cropland sustainability.However,the univariate outcome also shows that the cropland ecological balance of Germany,China,France,Indonesia,and India does contain a unit root and stationary which means the presence of the constant-mean.The univariate actions from the mentioned governments will not promote persistent impact.Therefore,joint actions determined by the countries considered are recommended for the mentioned countries.However,the rest of the countries also enact local policies.The insights gained are critical for informing global sustainability strategies and aiding policymakers in developing effective measures to enhance agricultural practices and mitigate environmental impacts.This research provides a data-driven foundation for optimizing agricultural sustainability and supports international efforts to achieve long-term ecological stability.展开更多
Designing novel van der Waals layered materials with low thermal conductivity and large power factor is important for the development of layered thermoelectric materials.Therefore,the novel van der Waals intercalated ...Designing novel van der Waals layered materials with low thermal conductivity and large power factor is important for the development of layered thermoelectric materials.Therefore,the novel van der Waals intercalated compound La_(2)Bi_(4)Cu_(2)O_(6)Se_(4),which is constructed by alternately stacking LaCuSeO and Bi_(2)O_(2)Se units along the c-axis in a 1:2 ratio,has designed for thermoelectric materials.The unique intercalated strategy leads to the four-band convergence at the valence band maximum,and the combination of multiple heavy band and light band,which significantly enhances the p-type doping power factor.The lattice thermal conductivities in La_(2)Bi_(4)Cu_(2)O_(6)Se_(4)and LaCuSeO compounds are accurately calculated by considering the coherence contributions of the anharmonic phonon reformulations and the off-diagonal term of the heat flux operator.The weak bond property of the Cu d-Se p bonding causes phonon softening,reducing the lattice thermal conductivity.The intercalated Bi atom has stereochemically active lone-pair electrons,which causes acoustic-optical coupling and produces strong fourth acoustic-optical phonon scattering,suppressing low-frequency phonon transport.The carrier relaxation time is rationalized by considering multiple carrier scattering mechanisms.The p-type doping La_(2)Bi_(4)Cu_(2)O_(6)Se_(4)achieves an average ZT of 2.3 at 700 K,and an optimal ZT of 2.7 along the in-plane direction.Our current work not only reveals the origin of the strong phonon scattering and large power factor of La_(2)Bi_(4)Cu_(2)O_(6)Se_(4)compound,but also provides theoretical guidance for the design of La-based layered oxides for thermoelectric applications.展开更多
Hypertrophic cardiomyopathy(HCM)is a primary myocardial disease characterized by myocardial hypertrophy,excluding other cardiovascular or systemic/metabolic causes of ventricular wall thickening.Apical hypertrophic ca...Hypertrophic cardiomyopathy(HCM)is a primary myocardial disease characterized by myocardial hypertrophy,excluding other cardiovascular or systemic/metabolic causes of ventricular wall thickening.Apical hypertrophic cardiomyopathy(ApHCM)represents a special form of ventricular hypertrophy predominantly affecting the left ventricular apex below the papillary muscles,typically without significant left ventricular outflow tract obstruction.[1,2]ApHCM often coexists with mild coronary artery abnormalities,[3]and reports of acute myocardial infarction with coronary artery stenosis in ApHCM or HCM patients are uncommon.展开更多
Island-arc magmatism is a crucial process in the Earth’s crustal growth.However,how the island-arc magma production rate(MPR)changes and the key influencing factors remains unclear.This study employs numerical models...Island-arc magmatism is a crucial process in the Earth’s crustal growth.However,how the island-arc magma production rate(MPR)changes and the key influencing factors remains unclear.This study employs numerical models to simulate island-arc growth,incorporating slab dehydration,mantle hydration and melting,and melt extraction.In addition,the impacts of convergence rate and slab dip angle on island-arc magma production were studied.Results suggest that,(1)MPR increases with higher convergence rates;high convergence rates enhance slab water transport efficiency and mantle wedge convection,thereby promoting water fraction and temperature in potential molten regions;(2)MPR initially rises and then falls as the slab dip angle varies from 30°to 45°,and to 60°.This variation is closely tied to water content in the wedge rather than mantle temperature.However,a higher slab dip promotes dehydration towards the potential-melting mantle wedge,which causes water to ascend to shallow areas and reduces the area of the potential molten region.Ultimately,a dip angle of 45°is optimal for retaining the most suitable water fraction and mantle wedge area,thereby maintaining the largest MPR;(3)convergence rate variation has a much larger influence on magma production rate than dip angle variation.When the convergence rate varies from 2 to 10 cm/a,the largest time-averaged MPR is 64.0 times the smallest one,whereas when the slab dip varies from 30°to 60°,the largest time-averaged MPR is only 3.5 times the smallest one.These findings align with numerous instances observed in modern-day subduction zones.展开更多
Assume that{a_(i),−∞<i<∞}is an absolutely summable sequence of real numbers.We establish the complete q-order moment convergence for the partial sums of moving average processes{X_(n)=Σ_(i=−∞)^(∞)a_(i)Y_(i+...Assume that{a_(i),−∞<i<∞}is an absolutely summable sequence of real numbers.We establish the complete q-order moment convergence for the partial sums of moving average processes{X_(n)=Σ_(i=−∞)^(∞)a_(i)Y_(i+n),n≥1}under some proper conditions,where{Yi,-∞<i<∞}is a doubly infinite sequence of negatively dependent random variables under sub-linear expectations.These results extend and complement the relevant results in probability space.展开更多
The rapid development of Internet technology has made“Internet+”a hallmark of the current era.The transformation and development of traditional media into all-media have provided a guiding direction for the developm...The rapid development of Internet technology has made“Internet+”a hallmark of the current era.The transformation and development of traditional media into all-media have provided a guiding direction for the development of campus media.The traditional form of campus media,which mainly consists of campus newspapers and campus radio,can no longer meet the application demands of modern higher education for media.In line with the current media convergence environment,campus media need to actively innovate to achieve their own development and progress in keeping with the times.This article explores the innovation path of campus media in the context of media convergence,analyzing the promotion of campus media innovation by the development of new media,the diversification of campus media innovation,and the effective ways of campus media innovation,in order to promote the realization of the innovation and development goals of campus media in the context of media convergence.展开更多
Convergent journalism constitutes a systematic investigation into emergent journalistic forms,conceptual frameworks,and practices emerging within media convergence context,characterized by its inherent attributes of c...Convergent journalism constitutes a systematic investigation into emergent journalistic forms,conceptual frameworks,and practices emerging within media convergence context,characterized by its inherent attributes of convergence,datacentricity,and interactivity.Grounded in the theoretical discourse of digital narratology,this monograph crystallizes its analytical focus on the triadic conceptual constellation of"convergence""mediaticity"and"narrativity",By positioning""convergence"as the central problematique,it systematically constructs an epistemological framework for convergent journalistic narrative through three dimensions:narrative theory,narrative language,and narrative praxis,thereby elucidates the ontological foundations and operational logics intrinsic to contemporary journalism studies.展开更多
This paper,grounded in the theory of business model innovation,examines the Chinese People’s Health Press(人民卫生出版社)as a case study to explore strategies for innovating business models within the context of prof...This paper,grounded in the theory of business model innovation,examines the Chinese People’s Health Press(人民卫生出版社)as a case study to explore strategies for innovating business models within the context of professional publishing convergence development.The research posits that effective business model innovation in this domain necessitates a comprehensive reform of its constituent elements.It advocates for a systematic approach to reconstructing value propositions,enhancing value creation and delivery processes,and optimizing value capture mechanisms to achieve desired outcomes.展开更多
In this study,we present a deterministic convergence analysis of Gated Recurrent Unit(GRU)networks enhanced by a smoothing L_(1)regularization technique.While GRU architectures effectively mitigate gradient vanishing/...In this study,we present a deterministic convergence analysis of Gated Recurrent Unit(GRU)networks enhanced by a smoothing L_(1)regularization technique.While GRU architectures effectively mitigate gradient vanishing/exploding issues in sequential modeling,they remain prone to overfitting,particularly under noisy or limited training data.Traditional L_(1)regularization,despite enforcing sparsity and accelerating optimization,introduces non-differentiable points in the error function,leading to oscillations during training.To address this,we propose a novel smoothing L_(1)regularization framework that replaces the non-differentiable absolute function with a quadratic approximation,ensuring gradient continuity and stabilizing the optimization landscape.Theoretically,we rigorously establish threekey properties of the resulting smoothing L_(1)-regularizedGRU(SL_(1)-GRU)model:(1)monotonic decrease of the error function across iterations,(2)weak convergence characterized by vanishing gradients as iterations approach infinity,and(3)strong convergence of network weights to fixed points under finite conditions.Comprehensive experiments on benchmark datasets-spanning function approximation,classification(KDD Cup 1999 Data,MNIST),and regression tasks(Boston Housing,Energy Efficiency)-demonstrate SL_(1)-GRUs superiority over baseline models(RNN,LSTM,GRU,L_(1)-GRU,L2-GRU).Empirical results reveal that SL_(1)-GRU achieves 1.0%-2.4%higher test accuracy in classification,7.8%-15.4%lower mean squared error in regression compared to unregularized GRU,while reducing training time by 8.7%-20.1%.These outcomes validate the method’s efficacy in balancing computational efficiency and generalization capability,and they strongly corroborate the theoretical calculations.The proposed framework not only resolves the non-differentiability challenge of L_(1)regularization but also provides a theoretical foundation for convergence guarantees in recurrent neural network training.展开更多
The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward...The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward-looking information of key wind farms in a cluster under different weather conditions is an effective method to improve the accuracy of ultrashort-term cluster power forecasting.To this end,this paper proposes a refined modeling method for ultrashort-term wind power cluster forecasting based on a convergent cross-mapping algorithm.From the perspective of causality,key meteorological forecasting factors under different cluster power fluctuation processes were screened,and refined training modeling was performed for different fluctuation processes.First,a wind process description index system and classification model at the wind power cluster level are established to realize the classification of typical fluctuation processes.A meteorological-cluster power causal relationship evaluation model based on the convergent cross-mapping algorithm is pro-posed to screen meteorological forecasting factors under multiple types of typical fluctuation processes.Finally,a refined modeling meth-od for a variety of different typical fluctuation processes is proposed,and the strong causal meteorological forecasting factors of each scenario are used as inputs to realize high-precision modeling and forecasting of ultra-short-term wind cluster power.An example anal-ysis shows that the short-term wind power cluster power forecasting accuracy of the proposed method can reach 88.55%,which is 1.57-7.32%higher than that of traditional methods.展开更多
The mesoscale eddy(ME)has a significant influence on the convergence effect in deep-sea acoustic propagation.This paper use statistical approaches to express quantitative relationships between the ME conditions and co...The mesoscale eddy(ME)has a significant influence on the convergence effect in deep-sea acoustic propagation.This paper use statistical approaches to express quantitative relationships between the ME conditions and convergence zone(CZ)characteristics.Based on the Gaussian vortex model,we construct various sound propagation scenarios under different eddy conditions,and carry out sound propagation experiments to obtain simulation samples.With a large number of samples,we first adopt the unified regression to set up analytic relationships between eddy conditions and CZ parameters.The sensitivity of eddy indicators to the CZ is quantitatively analyzed.Then,we adopt the machine learning(ML)algorithms to establish prediction models of CZ parameters by exploring the nonlinear relationships between multiple ME indicators and CZ parameters.Through the research,we can express the influence of ME on the CZ quantitatively,and achieve the rapid prediction of CZ parameters in ocean eddies.The prediction accuracy(R)of the CZ distance(mean R:0.9815)is obviously better than that of the CZ width(mean R:0.8728).Among the three ML algorithms,Gradient Boosting Decision Tree has the best prediction ability(root mean square error(RMSE):0.136),followed by Random Forest(RMSE:0.441)and Extreme Learning Machine(RMSE:0.518).展开更多
In this paper,we investigate the complete convergence and complete moment conver-gence for weighted sums of arrays of rowwise asymptotically negatively associated(ANA)random variables,without assuming identical distri...In this paper,we investigate the complete convergence and complete moment conver-gence for weighted sums of arrays of rowwise asymptotically negatively associated(ANA)random variables,without assuming identical distribution.The obtained results not only extend those of An and Yuan[1]and Shen et al.[2]to the case of ANA random variables,but also partially improve them.展开更多
This paper aims to interpret the connotation of high-quality development of tourism economy(HQTE)from the perspective of the new development concepts of innovation,coordination,green,openness and sharing,and then to e...This paper aims to interpret the connotation of high-quality development of tourism economy(HQTE)from the perspective of the new development concepts of innovation,coordination,green,openness and sharing,and then to evaluate the spatial differenti-ation of China’s HQTE based on provincial panel data from 2009 to 2018.Specifically,we employ the spatial convergence model to ex-plore the absolute and conditionalβconvergence trends of HQTE in the whole country and the eastern,central and western regions of China.Our empirical results reveal that:1)within the decade,from 2009 to 2018,regions of China with the highest HQTE index is its eastern region followed by the central region and then the western region,but the fastest growing one is the western region of China fol-lowed by the central region and then the eastern region.2)Whether or not the spatial effect is included,there are absolute and condition-alβconvergence in HQTE in the whole country and aforementioned three regions.3)The degree of government attention as well as the level of economic development and location accessibility are the positive driving factors for the convergence of HQTE in the whole country and the three regions.The degree of marketization and human capital have not passed the significance test either in the whole country or in the three regions.The above conclusions could deepen the understanding of the regional imbalance and spatial conver-gence characteristics of HQTE,clarify the primary development objects,and accomplish the goal of China’s HQTE.展开更多
The active sensor often uses the convergence zone mode to detect a distant target in the deep ocean.However,convergence zones are regions with limited widths that only appear at some discrete distances.Thus,widening t...The active sensor often uses the convergence zone mode to detect a distant target in the deep ocean.However,convergence zones are regions with limited widths that only appear at some discrete distances.Thus,widening the width by adjusting the transmitting array depth facilitates target observation and detection.Traversal search is an effective method for determining the optimal depth,but the heavy computation burden resulting from the calculation of the transmission losses at all source depths impedes its application.To solve the problem,a fast method based on ray cluster theory is proposed.Due to the coherent sound field structure in the deep ocean,several ray clusters with different departure angles radiate from the source,where ray clusters with small departure angles reverse in the water and form a convergence zone.When the source is set to a depth that only the first ray cluster inverts in water,the maximum width of the convergence zone is obtained.Based on this,an optimal transmitting array depth selection method utilizing the reversion condition of the first ray cluster is formulated.Simulation results show that the active sensor can achieve a large convergence zone width with real-time performance using the proposed method.展开更多
A cautious projection BFGS method is proposed for solving nonconvex unconstrained optimization problems.The global convergence of this method as well as a stronger general convergence result can be proven without a gr...A cautious projection BFGS method is proposed for solving nonconvex unconstrained optimization problems.The global convergence of this method as well as a stronger general convergence result can be proven without a gradient Lipschitz continuity assumption,which is more in line with the actual problems than the existing modified BFGS methods and the traditional BFGS method.Under some additional conditions,the method presented has a superlinear convergence rate,which can be regarded as an extension and supplement of BFGS-type methods with the projection technique.Finally,the effectiveness and application prospects of the proposed method are verified by numerical experiments.展开更多
基金supported by the National Social Science Fundation(Grant No.21BTJ040)the Project of Outstanding Young People in University of Anhui Province(Grant Nos.2023AH020037,SLXY2024A001).
文摘In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.
基金supported by Doctoral Scientific Research Starting Foundation of Jingdezhen Ceramic University(Grant No.102/01003002031)Re-accompanying Funding Project of Academic Achievements of Jingdezhen Ceramic University(Grant Nos.215/20506277,215/20506341)。
文摘The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.
文摘This study looks at how the Belt and Road Initiative(BRI)has affected the economic convergence of the Central Asian Turkic Republics,China,Pakistan,and their major diplomatic partners in the Silk Road region.Using beta and sigma convergence models over a predetermined time frame,the research evaluates economic alignment trends statistically and looks into how trade openness,FDI,and human capital affect the convergence process.The research attempts to discover larger causes of convergence,such as institutional quality and geopolitical closeness,by combining econometric analysis with regional economic dynamics.The purpose of the results is to provide policy suggestions that will improve equitable and sustainable economic convergence inside the Silk Road circle,promoting international cooperation and growth.
基金supported by the National Natural Science Foundation of China (Grant No. 12372028)the National Key Research and Development Program of China (Grant No. 2020YFC2201101)the Guangdong Basic and Applied Basic Research Foundation (Grant No.2022A1515011809)。
文摘The harmonic balance method(HBM)has been widely applied to get the periodic solution of nonlinear systems,however,its convergence rate as well as computation efficiency is dramatically degraded when the system is highly non-smooth,e.g.,discontinuous.In order to accelerate the convergence,an enriched HBM is developed in this paper where the non-smooth Bernoulli bases are additionally introduced to enrich the conventional Fourier bases.The basic idea behind is that the convergence rate of the HB solution,as a truncated Fourier series,can be improved if the smoothness of the solution becomes finer.Along this line,using non-smooth Bernoulli bases can compensate the highly non-smooth part of the solution and then,the smoothness of the residual part for Fourier approximation is improved so as to achieve accelerated convergence.Numerical examples are conducted on systems with non-smooth restoring and/or external forces.The results confirm that the proposed enriched HBM indeed increases the convergence rate and the increase becomes more significant if more non-smooth bases are used.
基金Supported by the National Natural Science Foundation of China (Grant No. 12301521)the Natural Science Foundation of Shanxi Province (Grant No. 20210302124081)。
文摘In this paper,the convergence of the split-step theta method for stochastic differential equations is analyzed using stochastic C-stability and stochastic B-consistency.The fact that the numerical scheme,which is both stochastically C-stable and stochastically B-consistent,is convergent has been proved in a previous paper.In order to analyze the convergence of the split-step theta method(θ∈[1/2,1]),the stochastic C-stability and stochastic B-consistency under the condition of global monotonicity have been researched,and the rate of convergence 1/2 has been explored in this paper.It can be seen that the convergence does not require the drift function should satisfy the linear growth condition whenθ=1/2 Furthermore,the rate of the convergence of the split-step scheme for stochastic differential equations with additive noise has been researched and found to be 1.Finally,an example is given to illustrate the convergence with the theoretical results.
文摘This study investigates the convergence hypothesis and stochastic dynamics of agricultural land use and ecological balance across 13 major agricultural countries from 1992 to 2022.The study's concentrated samples are Russia,the United States,the Netherlands,Brazil,Germany,China,France,Spain,Italy,Canada,Belgium,Indonesia,and India.The research uncovers notable variations in ecological balance by utilizing a comprehensive set of advanced panel unit root tests(Panel CIPS,CADF,Panel-LM,Panel-KPSS,and Bahmani-Oskooee et al.’s Panel KPSS Unit Root Test).The findings highlight significant improvements in Canada,contrasting with declines in the Netherlands,France,Germany,and the United States.The results indicate convergence in ecological balance among these countries,suggesting that agricultural practices are progressively aligning with sustainability objectives.The considered countries can determine and enact joint and collective policy actions addressing cropland sustainability.However,the univariate outcome also shows that the cropland ecological balance of Germany,China,France,Indonesia,and India does contain a unit root and stationary which means the presence of the constant-mean.The univariate actions from the mentioned governments will not promote persistent impact.Therefore,joint actions determined by the countries considered are recommended for the mentioned countries.However,the rest of the countries also enact local policies.The insights gained are critical for informing global sustainability strategies and aiding policymakers in developing effective measures to enhance agricultural practices and mitigate environmental impacts.This research provides a data-driven foundation for optimizing agricultural sustainability and supports international efforts to achieve long-term ecological stability.
基金Financial supports from the National Natural Science Foundation of China(Grant No.21503039)Department of Science and Technology of Liaoning Province(Grant No.2019MS164)+1 种基金Department of Education of Liaoning Province(Grant No.LJ2020JCL034)Discipline Innovation Team of Liaoning Technical University(Grant No.LNTU20TD-16)are greatly acknowledged。
文摘Designing novel van der Waals layered materials with low thermal conductivity and large power factor is important for the development of layered thermoelectric materials.Therefore,the novel van der Waals intercalated compound La_(2)Bi_(4)Cu_(2)O_(6)Se_(4),which is constructed by alternately stacking LaCuSeO and Bi_(2)O_(2)Se units along the c-axis in a 1:2 ratio,has designed for thermoelectric materials.The unique intercalated strategy leads to the four-band convergence at the valence band maximum,and the combination of multiple heavy band and light band,which significantly enhances the p-type doping power factor.The lattice thermal conductivities in La_(2)Bi_(4)Cu_(2)O_(6)Se_(4)and LaCuSeO compounds are accurately calculated by considering the coherence contributions of the anharmonic phonon reformulations and the off-diagonal term of the heat flux operator.The weak bond property of the Cu d-Se p bonding causes phonon softening,reducing the lattice thermal conductivity.The intercalated Bi atom has stereochemically active lone-pair electrons,which causes acoustic-optical coupling and produces strong fourth acoustic-optical phonon scattering,suppressing low-frequency phonon transport.The carrier relaxation time is rationalized by considering multiple carrier scattering mechanisms.The p-type doping La_(2)Bi_(4)Cu_(2)O_(6)Se_(4)achieves an average ZT of 2.3 at 700 K,and an optimal ZT of 2.7 along the in-plane direction.Our current work not only reveals the origin of the strong phonon scattering and large power factor of La_(2)Bi_(4)Cu_(2)O_(6)Se_(4)compound,but also provides theoretical guidance for the design of La-based layered oxides for thermoelectric applications.
文摘Hypertrophic cardiomyopathy(HCM)is a primary myocardial disease characterized by myocardial hypertrophy,excluding other cardiovascular or systemic/metabolic causes of ventricular wall thickening.Apical hypertrophic cardiomyopathy(ApHCM)represents a special form of ventricular hypertrophy predominantly affecting the left ventricular apex below the papillary muscles,typically without significant left ventricular outflow tract obstruction.[1,2]ApHCM often coexists with mild coronary artery abnormalities,[3]and reports of acute myocardial infarction with coronary artery stenosis in ApHCM or HCM patients are uncommon.
基金Supported by the National Natural Science Foundation of China(Nos.42176068,42476063,92058213,42376081,42121005)。
文摘Island-arc magmatism is a crucial process in the Earth’s crustal growth.However,how the island-arc magma production rate(MPR)changes and the key influencing factors remains unclear.This study employs numerical models to simulate island-arc growth,incorporating slab dehydration,mantle hydration and melting,and melt extraction.In addition,the impacts of convergence rate and slab dip angle on island-arc magma production were studied.Results suggest that,(1)MPR increases with higher convergence rates;high convergence rates enhance slab water transport efficiency and mantle wedge convection,thereby promoting water fraction and temperature in potential molten regions;(2)MPR initially rises and then falls as the slab dip angle varies from 30°to 45°,and to 60°.This variation is closely tied to water content in the wedge rather than mantle temperature.However,a higher slab dip promotes dehydration towards the potential-melting mantle wedge,which causes water to ascend to shallow areas and reduces the area of the potential molten region.Ultimately,a dip angle of 45°is optimal for retaining the most suitable water fraction and mantle wedge area,thereby maintaining the largest MPR;(3)convergence rate variation has a much larger influence on magma production rate than dip angle variation.When the convergence rate varies from 2 to 10 cm/a,the largest time-averaged MPR is 64.0 times the smallest one,whereas when the slab dip varies from 30°to 60°,the largest time-averaged MPR is only 3.5 times the smallest one.These findings align with numerous instances observed in modern-day subduction zones.
基金Supported by the Academic Achievement Re-cultivation Projects of Jingdezhen Ceramic University(Grant Nos.215/20506341215/20506277)the Doctoral Scientific Research Starting Foundation of Jingdezhen Ceramic University(Grant No.102/01003002031)。
文摘Assume that{a_(i),−∞<i<∞}is an absolutely summable sequence of real numbers.We establish the complete q-order moment convergence for the partial sums of moving average processes{X_(n)=Σ_(i=−∞)^(∞)a_(i)Y_(i+n),n≥1}under some proper conditions,where{Yi,-∞<i<∞}is a doubly infinite sequence of negatively dependent random variables under sub-linear expectations.These results extend and complement the relevant results in probability space.
文摘The rapid development of Internet technology has made“Internet+”a hallmark of the current era.The transformation and development of traditional media into all-media have provided a guiding direction for the development of campus media.The traditional form of campus media,which mainly consists of campus newspapers and campus radio,can no longer meet the application demands of modern higher education for media.In line with the current media convergence environment,campus media need to actively innovate to achieve their own development and progress in keeping with the times.This article explores the innovation path of campus media in the context of media convergence,analyzing the promotion of campus media innovation by the development of new media,the diversification of campus media innovation,and the effective ways of campus media innovation,in order to promote the realization of the innovation and development goals of campus media in the context of media convergence.
文摘Convergent journalism constitutes a systematic investigation into emergent journalistic forms,conceptual frameworks,and practices emerging within media convergence context,characterized by its inherent attributes of convergence,datacentricity,and interactivity.Grounded in the theoretical discourse of digital narratology,this monograph crystallizes its analytical focus on the triadic conceptual constellation of"convergence""mediaticity"and"narrativity",By positioning""convergence"as the central problematique,it systematically constructs an epistemological framework for convergent journalistic narrative through three dimensions:narrative theory,narrative language,and narrative praxis,thereby elucidates the ontological foundations and operational logics intrinsic to contemporary journalism studies.
文摘This paper,grounded in the theory of business model innovation,examines the Chinese People’s Health Press(人民卫生出版社)as a case study to explore strategies for innovating business models within the context of professional publishing convergence development.The research posits that effective business model innovation in this domain necessitates a comprehensive reform of its constituent elements.It advocates for a systematic approach to reconstructing value propositions,enhancing value creation and delivery processes,and optimizing value capture mechanisms to achieve desired outcomes.
基金supported by the National Science Fund for Distinguished Young Scholarship(No.62025602)National Natural Science Foundation of China(Nos.U22B2036,11931015)+2 种基金the Fok Ying-Tong Education Foundation China(No.171105)the Fundamental Research Funds for the Central Universities(No.G2024WD0151)in part by the Tencent Foundation and XPLORER PRIZE.
文摘In this study,we present a deterministic convergence analysis of Gated Recurrent Unit(GRU)networks enhanced by a smoothing L_(1)regularization technique.While GRU architectures effectively mitigate gradient vanishing/exploding issues in sequential modeling,they remain prone to overfitting,particularly under noisy or limited training data.Traditional L_(1)regularization,despite enforcing sparsity and accelerating optimization,introduces non-differentiable points in the error function,leading to oscillations during training.To address this,we propose a novel smoothing L_(1)regularization framework that replaces the non-differentiable absolute function with a quadratic approximation,ensuring gradient continuity and stabilizing the optimization landscape.Theoretically,we rigorously establish threekey properties of the resulting smoothing L_(1)-regularizedGRU(SL_(1)-GRU)model:(1)monotonic decrease of the error function across iterations,(2)weak convergence characterized by vanishing gradients as iterations approach infinity,and(3)strong convergence of network weights to fixed points under finite conditions.Comprehensive experiments on benchmark datasets-spanning function approximation,classification(KDD Cup 1999 Data,MNIST),and regression tasks(Boston Housing,Energy Efficiency)-demonstrate SL_(1)-GRUs superiority over baseline models(RNN,LSTM,GRU,L_(1)-GRU,L2-GRU).Empirical results reveal that SL_(1)-GRU achieves 1.0%-2.4%higher test accuracy in classification,7.8%-15.4%lower mean squared error in regression compared to unregularized GRU,while reducing training time by 8.7%-20.1%.These outcomes validate the method’s efficacy in balancing computational efficiency and generalization capability,and they strongly corroborate the theoretical calculations.The proposed framework not only resolves the non-differentiability challenge of L_(1)regularization but also provides a theoretical foundation for convergence guarantees in recurrent neural network training.
基金funded by the State Grid Science and Technology Project“Research on Key Technologies for Prediction and Early Warning of Large-Scale Offshore Wind Power Ramp Events Based on Meteorological Data Enhancement”(4000-202318098A-1-1-ZN).
文摘The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward-looking information of key wind farms in a cluster under different weather conditions is an effective method to improve the accuracy of ultrashort-term cluster power forecasting.To this end,this paper proposes a refined modeling method for ultrashort-term wind power cluster forecasting based on a convergent cross-mapping algorithm.From the perspective of causality,key meteorological forecasting factors under different cluster power fluctuation processes were screened,and refined training modeling was performed for different fluctuation processes.First,a wind process description index system and classification model at the wind power cluster level are established to realize the classification of typical fluctuation processes.A meteorological-cluster power causal relationship evaluation model based on the convergent cross-mapping algorithm is pro-posed to screen meteorological forecasting factors under multiple types of typical fluctuation processes.Finally,a refined modeling meth-od for a variety of different typical fluctuation processes is proposed,and the strong causal meteorological forecasting factors of each scenario are used as inputs to realize high-precision modeling and forecasting of ultra-short-term wind cluster power.An example anal-ysis shows that the short-term wind power cluster power forecasting accuracy of the proposed method can reach 88.55%,which is 1.57-7.32%higher than that of traditional methods.
基金The National Natural Science Foundation of China under contract Nos 41875061 and 41775165.
文摘The mesoscale eddy(ME)has a significant influence on the convergence effect in deep-sea acoustic propagation.This paper use statistical approaches to express quantitative relationships between the ME conditions and convergence zone(CZ)characteristics.Based on the Gaussian vortex model,we construct various sound propagation scenarios under different eddy conditions,and carry out sound propagation experiments to obtain simulation samples.With a large number of samples,we first adopt the unified regression to set up analytic relationships between eddy conditions and CZ parameters.The sensitivity of eddy indicators to the CZ is quantitatively analyzed.Then,we adopt the machine learning(ML)algorithms to establish prediction models of CZ parameters by exploring the nonlinear relationships between multiple ME indicators and CZ parameters.Through the research,we can express the influence of ME on the CZ quantitatively,and achieve the rapid prediction of CZ parameters in ocean eddies.The prediction accuracy(R)of the CZ distance(mean R:0.9815)is obviously better than that of the CZ width(mean R:0.8728).Among the three ML algorithms,Gradient Boosting Decision Tree has the best prediction ability(root mean square error(RMSE):0.136),followed by Random Forest(RMSE:0.441)and Extreme Learning Machine(RMSE:0.518).
基金National Natural Science Foundation of China (Grant Nos.12061028, 71871046)Support Program of the Guangxi China Science Foundation (Grant No.2018GXNSFAA281011)。
文摘In this paper,we investigate the complete convergence and complete moment conver-gence for weighted sums of arrays of rowwise asymptotically negatively associated(ANA)random variables,without assuming identical distribution.The obtained results not only extend those of An and Yuan[1]and Shen et al.[2]to the case of ANA random variables,but also partially improve them.
基金Under the auspices of the National Natural Science Foundation of China(No.42001156)。
文摘This paper aims to interpret the connotation of high-quality development of tourism economy(HQTE)from the perspective of the new development concepts of innovation,coordination,green,openness and sharing,and then to evaluate the spatial differenti-ation of China’s HQTE based on provincial panel data from 2009 to 2018.Specifically,we employ the spatial convergence model to ex-plore the absolute and conditionalβconvergence trends of HQTE in the whole country and the eastern,central and western regions of China.Our empirical results reveal that:1)within the decade,from 2009 to 2018,regions of China with the highest HQTE index is its eastern region followed by the central region and then the western region,but the fastest growing one is the western region of China fol-lowed by the central region and then the eastern region.2)Whether or not the spatial effect is included,there are absolute and condition-alβconvergence in HQTE in the whole country and aforementioned three regions.3)The degree of government attention as well as the level of economic development and location accessibility are the positive driving factors for the convergence of HQTE in the whole country and the three regions.The degree of marketization and human capital have not passed the significance test either in the whole country or in the three regions.The above conclusions could deepen the understanding of the regional imbalance and spatial conver-gence characteristics of HQTE,clarify the primary development objects,and accomplish the goal of China’s HQTE.
基金supported by the National Key R&D Program of China(No.2021YFF0501200)the National Natural Science Foundation of China(No.11774374)。
文摘The active sensor often uses the convergence zone mode to detect a distant target in the deep ocean.However,convergence zones are regions with limited widths that only appear at some discrete distances.Thus,widening the width by adjusting the transmitting array depth facilitates target observation and detection.Traversal search is an effective method for determining the optimal depth,but the heavy computation burden resulting from the calculation of the transmission losses at all source depths impedes its application.To solve the problem,a fast method based on ray cluster theory is proposed.Due to the coherent sound field structure in the deep ocean,several ray clusters with different departure angles radiate from the source,where ray clusters with small departure angles reverse in the water and form a convergence zone.When the source is set to a depth that only the first ray cluster inverts in water,the maximum width of the convergence zone is obtained.Based on this,an optimal transmitting array depth selection method utilizing the reversion condition of the first ray cluster is formulated.Simulation results show that the active sensor can achieve a large convergence zone width with real-time performance using the proposed method.
基金supported by the Guangxi Science and Technology base and Talent Project(AD22080047)the National Natural Science Foundation of Guangxi Province(2023GXNFSBA 026063)+1 种基金the Innovation Funds of Chinese University(2021BCF03001)the special foundation for Guangxi Ba Gui Scholars.
文摘A cautious projection BFGS method is proposed for solving nonconvex unconstrained optimization problems.The global convergence of this method as well as a stronger general convergence result can be proven without a gradient Lipschitz continuity assumption,which is more in line with the actual problems than the existing modified BFGS methods and the traditional BFGS method.Under some additional conditions,the method presented has a superlinear convergence rate,which can be regarded as an extension and supplement of BFGS-type methods with the projection technique.Finally,the effectiveness and application prospects of the proposed method are verified by numerical experiments.
