Phase transitions,as one of the most intriguing phenomena in nature,are divided into first-order phase transitions(FOPTs)and continuous ones in current classification.While the latter shows striking phenomena of scali...Phase transitions,as one of the most intriguing phenomena in nature,are divided into first-order phase transitions(FOPTs)and continuous ones in current classification.While the latter shows striking phenomena of scaling and universality,the former has recently also been demonstrated to exhibit scaling and universal behavior within a mesoscopic,coarse-grained Landau-Ginzburg theory.Here we apply this theory to a microscopic model-the paradigmatic Ising model,which undergoes FOPTs between two ordered phases below its critical temperature-and unambiguously demonstrate universal scaling behavior in such FOPTs.These results open the door for extending the theory to other microscopic FOPT systems and experimentally testing them to systematically uncover their scaling and universal behavior.展开更多
The use of peat for the removal of nickel from aqueous solutions has been investigated at various pH values by means of static conditions. The present research shows that the ability of Ni to bind to peat increases as...The use of peat for the removal of nickel from aqueous solutions has been investigated at various pH values by means of static conditions. The present research shows that the ability of Ni to bind to peat increases as the pH value increases. The solutions reach adsorption equilibrium rapidly. A reasonable kinetic model, first-order in nickel concentration, has been developed and fitted to the adsorption of nickel （Ⅱ） onto peat. The first-order model provides a good correlation to the experimental data. The characteristic parameters of the Langmuir isotherm were determined at various temperatures. The relationship between kinetics and equilibrium isotherms was established through the forward- and backward-rate-constants, k~ and k2, and the equilibrium constant, K.展开更多
In this article, we use the spin coherent state transformation and the ground state variational method to theoretically calculate the ground function. In order to consider the influence of the atom-atom interaction on...In this article, we use the spin coherent state transformation and the ground state variational method to theoretically calculate the ground function. In order to consider the influence of the atom-atom interaction on the extended Dicke model's ground state properties, the mean photon number, the scaled atomic population and the average ground energy are displayed. Using the self-consistent field theory to solve the atom-atom interaction, we discover the system undergoes a first-order quantum phase transition from the normal phase to the superradiant phase, but a famous Dicke-type second-order quantum phase transition without the atom-atom interaction. Meanwhile, the atom-atom interaction makes the phase transition point shift to the lower atom-photon collective coupling strength.展开更多
This study was performed in two phases of work.In the first stage,four conventional first-order flotation kinetics models were fitted to the measured recoveries data and the best model were selected.In the second stag...This study was performed in two phases of work.In the first stage,four conventional first-order flotation kinetics models were fitted to the measured recoveries data and the best model were selected.In the second stage,influence of pH,solid concentration,water chemistry and the amount of collector dosage were investigated on kinetics parameters including flotation rate constant and ultimate recovery.The results indicated that that perfectly mixed reactor model and Kelsall model gave the best and the weakest fit to the experimental data,respectively.It was observed that flotation rate constant and ultimate recovery were strongly affected by chemical factors investigated especially water quality.The flotation rate constant decreased with increasing the solids content,while ultimate recovery increased to certain value and thereafter reduced.It was also found that the most values of flotation rate constant and ultimate recovery obtained in dosage of collector are 30 and 40 g/t,respectively.展开更多
In this paper, we not only construct the confidence region for parameters in a mixed integer-valued autoregressive process using the empirical likelihood method, but also establish the empirical log-likelihood ratio s...In this paper, we not only construct the confidence region for parameters in a mixed integer-valued autoregressive process using the empirical likelihood method, but also establish the empirical log-likelihood ratio statistic and obtain its limiting distribution. And then, via simulation studies we give coverage probabilities for the parameters of interest. The results show that the empirical likelihood method performs very well.展开更多
Long-term responses of floating structures pose a great concern in their design phase. Existing approaches for addressing long-term extreme responses are extremely cumbersome for adoption. This work aims to develop an...Long-term responses of floating structures pose a great concern in their design phase. Existing approaches for addressing long-term extreme responses are extremely cumbersome for adoption. This work aims to develop an approach for the long-term extreme-response analysis of floating structures. A modified gradient-based retrieval algorithm in conjunction with the inverse first-order reliability method(IFORM) is proposed to enable the use of convolution models in long-term extreme analysis of structures with an analytical formula of response amplitude operator(RAO). The proposed algorithm ensures convergence stability and iteration accuracy and exhibits a higher computational efficiency than the traditional backtracking method. However, when the RAO of general offshore structures cannot be analytically expressed, the convolutional integration method fails to function properly. A numerical discretization approach is further proposed for offshore structures in the case when the analytical expression of the RAO is not feasible. Through iterative discretization of environmental contours(ECs) and RAOs, a detailed procedure is proposed to calculate the long-term response extremes of offshore structures. The validity and accuracy of the proposed approach are tested using a floating offshore wind turbine as a numerical example. The long-term extreme heave responses of various return periods are calculated via the IFORM in conjunction with a numerical discretization approach. The environmental data corresponding to N-year structural responses are located inside the ECs, which indicates that the selection of design points directly along the ECs yields conservative design results.展开更多
In this paper,we present a novel first-order digitalΣΔconverter tailored for digital-to-analog applications,focusing on achieving both high yield and reduced silicon estate.Our approach incorporates a substantial le...In this paper,we present a novel first-order digitalΣΔconverter tailored for digital-to-analog applications,focusing on achieving both high yield and reduced silicon estate.Our approach incorporates a substantial level of dithering noise into the input signal,strategically aimed at mitigating the spurious frequencies commonly encountered in such converters.Validation of our design is performed through simulations using a high-level simulator specialized in mixed-signal circuit analysis.The results underscore the enhanced performance of our circuit,especially in reducing spurious frequencies,highlighting its efficiency and effectiveness.The final circuit exhibits an effective number of bits of 13.展开更多
Methane generation in landfills and its inadequate management represent the major avoidable source of anthropogenic methane today. This paper models methane production and the potential resources expected (electrical ...Methane generation in landfills and its inadequate management represent the major avoidable source of anthropogenic methane today. This paper models methane production and the potential resources expected (electrical energy production and potential carbon credits from avoided CH4 emissions) from its proper management in a municipal solid waste landfill located in Ouagadougou, Burkina Faso. The modeling was carried out using two first-order decay (FOD) models (LandGEM V3.02 and SWANA) using parameters evaluated on the basis of the characteristics of the waste admitted to the landfill and weather data for the site. At the same time, production data have been collected since 2016 in order to compare them with the model results. The results obtained from these models were compared to experimental one. For the simulation of methane production, the SWANA model showed better consistency with experimental data, with a coefficient of determination (R²) of 0.59 compared with the LandGEM model, which obtained a coefficient of 0.006. Thus, despite the low correlation values linked to the poor consistency of experimental data, the SWANA model models methane production much better than the LandGEM model. Thus, despite the low correlation values linked to the poor consistency of the experimental data, the SWANA model models methane production much better than the LandGEM V3.02 model. It was noted that the poor consistency of the experimental data justifies these low coefficients, and that they can be improved in the future thanks to ongoing in situ measurements. According to the SWANA model prediction, in 27 years of operation a biogas plant with 33% electrical efficiency using biogas from the Polesgo landfill would avoid 1,340 GgCO2e. Also, the evaluation of revenues due to electricity and carbon credit gave a total revenue derived from methane production of US$27.38 million at a cost of US$10.5/tonne CO2e.展开更多
In this paper, we propose a log-normal linear model whose errors are first-order correlated, and suggest a two-stage method for the efficient estimation of the conditional mean of the response variable at the original...In this paper, we propose a log-normal linear model whose errors are first-order correlated, and suggest a two-stage method for the efficient estimation of the conditional mean of the response variable at the original scale. We obtain two estimators which minimize the asymptotic mean squared error （MM） and the asymptotic bias （MB）, respectively. Both the estimators are very easy to implement, and simulation studies show that they are perform better.展开更多
The pyrolysis behavior of two kinds of typical biomass (pine wood and cotton stalk) was studied in nitrogen atmosphere at various heating rates by thermogravimetric analysis (TGA). The pyrolysis process can be divided...The pyrolysis behavior of two kinds of typical biomass (pine wood and cotton stalk) was studied in nitrogen atmosphere at various heating rates by thermogravimetric analysis (TGA). The pyrolysis process can be divided into three stages: evolution of moisture (<200 ℃), devolatilization (200～400℃) and carbonization (>400 ℃). The comparison of DTG curves of two biomass materials show that the higher the hemicellulose content of biomass, the more evident the shoulder peak of DTG curve. The weight loss process of two materials was simulated by the kinetic model assuming cellulose, hemicellulose and lignin pyrolyzing independently and in parallel, obeying first-order reactions. The pyrolysis kinetic parameters corresponding to the three components were estimated by the nonlinear least square algorithm. The results show that their fitting curves are in good agreement with the experimental data. Their activation energy values for pine wood and cotton stalk are in the range of 188～215, 90～102, 29～49 and 187～214, 95～101, 30～38 kJ/mol, respectively. The corresponding pre-exponential factors are in the range of 1.8×1015～2.0×1016 , 1.6×107～7.1×108 , 9.3×101～1.5×103 and 1.2×1015～6.7×1017 , 1.2×108～1.4×109 , 1.4×102～4.6×102 min-1 , respectively. In addition, the activation energy of cellulose and lignin increased and their contributions to volatile tended to fall, whereas the activation energy of hemicellulose decreased and its contribution to volatile tended to rise with increasing of heating rate.展开更多
We study the quantum phase transition and entanglement in the Jaynes-Cummings model with squeezed light,utilize a special transformation method to obtain the analytical ground state of the model within the near-resona...We study the quantum phase transition and entanglement in the Jaynes-Cummings model with squeezed light,utilize a special transformation method to obtain the analytical ground state of the model within the near-resonance regime,and numerically verify the validity of the analytical ground state.It is found that the ground state exhibits a first-order quantum phase transition at the critical point linearly induced by squeezed light,and the ground state entanglement reaches its maximum when the qubit-field coupling strength is large enough at the critical point.展开更多
In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.展开更多
In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is empl...Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.展开更多
Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(...Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].展开更多
Possessing advantages such as high computing efficiency and ease of programming,the Symplectic Euler algorithm can be applied to construct a groundpenetrating radar(GPR)wave propagation numerical model for complex geo...Possessing advantages such as high computing efficiency and ease of programming,the Symplectic Euler algorithm can be applied to construct a groundpenetrating radar(GPR)wave propagation numerical model for complex geoelectric structures.However,the Symplectic Euler algorithm is still a difference algorithm,and for a complicated boundary,ladder grids are needed to perform an approximation process,which results in a certain amount of error.Further,grids that are too dense will seriously decrease computing efficiency.This paper proposes a conformal Symplectic Euler algorithm based on the conformal grid technique,amends the electric/magnetic fieldupdating equations of the Symplectic Euler algorithm by introducing the effective dielectric constant and effective permeability coefficient,and reduces the computing error caused by the ladder approximation of rectangular grids.Moreover,three surface boundary models(the underground circular void model,the undulating stratum model,and actual measurement model)are introduced.By comparing reflection waveforms simulated by the traditional Symplectic Euler algorithm,the conformal Symplectic Euler algorithm and the conformal finite difference time domain(CFDTD),the conformal Symplectic Euler algorithm achieves almost the same level of accuracy as the CFDTD method,but the conformal Symplectic Euler algorithm improves the computational efficiency compared with the CFDTD method dramatically.When the dielectric constants of the two materials vary greatly,the conformal Symplectic Euler algorithm can reduce the pseudo-waves almost by 80% compared with the traditional Symplectic Euler algorithm on average.展开更多
Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying ...Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.展开更多
This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to use...This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to user behavior and platform-driven moderation on social media.The proposed methodological framework(1)utilizes large language models for social media post analysis and categorization,(2)employs k-means clustering for content characterization,and(3)incorporates the TODIM(Tomada de Decisão Interativa Multicritério)method to determine moderation strategies based on expert judgments.In general,the fully integrated framework leverages the strengths of these intelligent systems in a more systematic evaluation of large-scale decision problems.When applied in social media moderation,this approach promotes nuanced and context-sensitive self-moderation by taking into account factors such as cultural background and geographic location.The application of this framework is demonstrated within Facebook groups.Eight distinct content clusters encompassing safety,harassment,diversity,and misinformation are identified.Analysis revealed a preference for content removal across all clusters,suggesting a cautious approach towards potentially harmful content.However,the framework also highlights the use of other moderation actions,like account suspension,depending on the content category.These findings contribute to the growing body of research on self-moderation and offer valuable insights for creating safer and more inclusive online spaces within smaller communities.展开更多
Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy...Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy plates.First,finite element simulations of casting processes were carried out with various parameters to build a dataset.Subsequently,different machine learning algorithms were employed to achieve high precision in predicting temperature fields,mushy zone locations,mushy zone inclination angle,and billet grain size.Finally,the process parameters were quickly optimized using a strategy consisting of random generation,prediction,and screening,allowing the mushy zone to be controlled to the desired target.The optimized parameters are 1234℃for heating mold temperature,47 mm/min for casting speed,and 10 L/min for cooling water flow rate.The optimized mushy zone is located in the middle of the second heat insulation section and has an inclination angle of roughly 7°.展开更多
Vegetation plays an important role in the environmental transport behavior of organic pollutants,however,the different roles of crops and natural vegetation have been ignored in most previous studies.In this study,we ...Vegetation plays an important role in the environmental transport behavior of organic pollutants,however,the different roles of crops and natural vegetation have been ignored in most previous studies.In this study,we developed the BETR-Urban-Rural-Veg model to quantitatively evaluate the influences of both natural vegetation and crops on the multimedia transport processes of Phenanthrene(PHE)and Benzo(a)pyrene(BaP)in mainland of China.The geographic distribution of polycyclic aromatic hydrocarbon(PAH)emissions and concentrations were consistent,displaying higher levels in northern China while lower levels in southern China.Under seasonal simulations,for both natural vegetation and crops,PAH concentrations in winter and spring were 1.5 to 27-fold higher than in summer and autumn,especially for PHE.Owing to the higher leaf area index(LAI)of natural vegetation and harvesting of crops,the filter and sequestration effect of natural vegetation was stronger than crops,while the seasonal changes of PAH concentrations in crops were more significant than natural vegetation.Temperature,precipitation rates and LAI might have important influences on seasonal concentrations and overall persistence of PAHs.PHE was more sensitive to the impacts of seasonal environmental parameters.Under different landscape scenarios,average annual PAH concentrations in natural vegetation were always a little higher than those in crops,and the overall persistence of BaP was greatly affected increasing by 15.15%-16.47%.This improved model provides a useful tool for environmental management.The results of this study are expected to support land use plans and decision-making in China's mainland.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.12175316).
文摘Phase transitions,as one of the most intriguing phenomena in nature,are divided into first-order phase transitions(FOPTs)and continuous ones in current classification.While the latter shows striking phenomena of scaling and universality,the former has recently also been demonstrated to exhibit scaling and universal behavior within a mesoscopic,coarse-grained Landau-Ginzburg theory.Here we apply this theory to a microscopic model-the paradigmatic Ising model,which undergoes FOPTs between two ordered phases below its critical temperature-and unambiguously demonstrate universal scaling behavior in such FOPTs.These results open the door for extending the theory to other microscopic FOPT systems and experimentally testing them to systematically uncover their scaling and universal behavior.
基金Projects [2006]331 supported by the Scientific Research Foundation for the Returned Overseas Chinese Scholars070712 by the Key Laboratory ofNuclear Resources and Environment,Ministry of Education of China
文摘The use of peat for the removal of nickel from aqueous solutions has been investigated at various pH values by means of static conditions. The present research shows that the ability of Ni to bind to peat increases as the pH value increases. The solutions reach adsorption equilibrium rapidly. A reasonable kinetic model, first-order in nickel concentration, has been developed and fitted to the adsorption of nickel （Ⅱ） onto peat. The first-order model provides a good correlation to the experimental data. The characteristic parameters of the Langmuir isotherm were determined at various temperatures. The relationship between kinetics and equilibrium isotherms was established through the forward- and backward-rate-constants, k~ and k2, and the equilibrium constant, K.
基金Supported by the National Natural Science Foundation of China under Grant Nos.11275118,11404198,91430109,61505100,51502189the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi Province(STIP)under Grant No.2014102+2 种基金the Launch of the Scientific Research of Shanxi University under Grant No.011151801004the National Fundamental Fund of Personnel Training under Grant No.J1103210The Natural Science Foundation of Shanxi Province under Grant No.2015011008
文摘In this article, we use the spin coherent state transformation and the ground state variational method to theoretically calculate the ground function. In order to consider the influence of the atom-atom interaction on the extended Dicke model's ground state properties, the mean photon number, the scaled atomic population and the average ground energy are displayed. Using the self-consistent field theory to solve the atom-atom interaction, we discover the system undergoes a first-order quantum phase transition from the normal phase to the superradiant phase, but a famous Dicke-type second-order quantum phase transition without the atom-atom interaction. Meanwhile, the atom-atom interaction makes the phase transition point shift to the lower atom-photon collective coupling strength.
文摘This study was performed in two phases of work.In the first stage,four conventional first-order flotation kinetics models were fitted to the measured recoveries data and the best model were selected.In the second stage,influence of pH,solid concentration,water chemistry and the amount of collector dosage were investigated on kinetics parameters including flotation rate constant and ultimate recovery.The results indicated that that perfectly mixed reactor model and Kelsall model gave the best and the weakest fit to the experimental data,respectively.It was observed that flotation rate constant and ultimate recovery were strongly affected by chemical factors investigated especially water quality.The flotation rate constant decreased with increasing the solids content,while ultimate recovery increased to certain value and thereafter reduced.It was also found that the most values of flotation rate constant and ultimate recovery obtained in dosage of collector are 30 and 40 g/t,respectively.
基金Supported by National Natural Science Foundation of China(11731015,11571051,J1310022,11501241)Natural Science Foundation of Jilin Province(20150520053JH,20170101057JC,20180101216JC)+2 种基金Program for Changbaishan Scholars of Jilin Province(2015010)Science and Technology Program of Jilin Educational Department during the "13th Five-Year" Plan Period(2016-399)Science and Technology Research Program of Education Department in Jilin Province for the 13th Five-Year Plan(2016213)
文摘In this paper, we not only construct the confidence region for parameters in a mixed integer-valued autoregressive process using the empirical likelihood method, but also establish the empirical log-likelihood ratio statistic and obtain its limiting distribution. And then, via simulation studies we give coverage probabilities for the parameters of interest. The results show that the empirical likelihood method performs very well.
基金Supported by the National Natural Science Foundation of China (Grant Nos.52088102 and 51879287)National Key Research and Development Program of China (Grant No.2022YFB2602301)。
文摘Long-term responses of floating structures pose a great concern in their design phase. Existing approaches for addressing long-term extreme responses are extremely cumbersome for adoption. This work aims to develop an approach for the long-term extreme-response analysis of floating structures. A modified gradient-based retrieval algorithm in conjunction with the inverse first-order reliability method(IFORM) is proposed to enable the use of convolution models in long-term extreme analysis of structures with an analytical formula of response amplitude operator(RAO). The proposed algorithm ensures convergence stability and iteration accuracy and exhibits a higher computational efficiency than the traditional backtracking method. However, when the RAO of general offshore structures cannot be analytically expressed, the convolutional integration method fails to function properly. A numerical discretization approach is further proposed for offshore structures in the case when the analytical expression of the RAO is not feasible. Through iterative discretization of environmental contours(ECs) and RAOs, a detailed procedure is proposed to calculate the long-term response extremes of offshore structures. The validity and accuracy of the proposed approach are tested using a floating offshore wind turbine as a numerical example. The long-term extreme heave responses of various return periods are calculated via the IFORM in conjunction with a numerical discretization approach. The environmental data corresponding to N-year structural responses are located inside the ECs, which indicates that the selection of design points directly along the ECs yields conservative design results.
文摘In this paper,we present a novel first-order digitalΣΔconverter tailored for digital-to-analog applications,focusing on achieving both high yield and reduced silicon estate.Our approach incorporates a substantial level of dithering noise into the input signal,strategically aimed at mitigating the spurious frequencies commonly encountered in such converters.Validation of our design is performed through simulations using a high-level simulator specialized in mixed-signal circuit analysis.The results underscore the enhanced performance of our circuit,especially in reducing spurious frequencies,highlighting its efficiency and effectiveness.The final circuit exhibits an effective number of bits of 13.
文摘Methane generation in landfills and its inadequate management represent the major avoidable source of anthropogenic methane today. This paper models methane production and the potential resources expected (electrical energy production and potential carbon credits from avoided CH4 emissions) from its proper management in a municipal solid waste landfill located in Ouagadougou, Burkina Faso. The modeling was carried out using two first-order decay (FOD) models (LandGEM V3.02 and SWANA) using parameters evaluated on the basis of the characteristics of the waste admitted to the landfill and weather data for the site. At the same time, production data have been collected since 2016 in order to compare them with the model results. The results obtained from these models were compared to experimental one. For the simulation of methane production, the SWANA model showed better consistency with experimental data, with a coefficient of determination (R²) of 0.59 compared with the LandGEM model, which obtained a coefficient of 0.006. Thus, despite the low correlation values linked to the poor consistency of experimental data, the SWANA model models methane production much better than the LandGEM model. Thus, despite the low correlation values linked to the poor consistency of the experimental data, the SWANA model models methane production much better than the LandGEM V3.02 model. It was noted that the poor consistency of the experimental data justifies these low coefficients, and that they can be improved in the future thanks to ongoing in situ measurements. According to the SWANA model prediction, in 27 years of operation a biogas plant with 33% electrical efficiency using biogas from the Polesgo landfill would avoid 1,340 GgCO2e. Also, the evaluation of revenues due to electricity and carbon credit gave a total revenue derived from methane production of US$27.38 million at a cost of US$10.5/tonne CO2e.
基金The NSF(11271155) of ChinaResearch Fund(20070183023) for the Doctoral Program of Higher Education
文摘In this paper, we propose a log-normal linear model whose errors are first-order correlated, and suggest a two-stage method for the efficient estimation of the conditional mean of the response variable at the original scale. We obtain two estimators which minimize the asymptotic mean squared error （MM） and the asymptotic bias （MB）, respectively. Both the estimators are very easy to implement, and simulation studies show that they are perform better.
基金Supported by National Natural Science Foundation of China(No.20676002)
文摘The pyrolysis behavior of two kinds of typical biomass (pine wood and cotton stalk) was studied in nitrogen atmosphere at various heating rates by thermogravimetric analysis (TGA). The pyrolysis process can be divided into three stages: evolution of moisture (<200 ℃), devolatilization (200～400℃) and carbonization (>400 ℃). The comparison of DTG curves of two biomass materials show that the higher the hemicellulose content of biomass, the more evident the shoulder peak of DTG curve. The weight loss process of two materials was simulated by the kinetic model assuming cellulose, hemicellulose and lignin pyrolyzing independently and in parallel, obeying first-order reactions. The pyrolysis kinetic parameters corresponding to the three components were estimated by the nonlinear least square algorithm. The results show that their fitting curves are in good agreement with the experimental data. Their activation energy values for pine wood and cotton stalk are in the range of 188～215, 90～102, 29～49 and 187～214, 95～101, 30～38 kJ/mol, respectively. The corresponding pre-exponential factors are in the range of 1.8×1015～2.0×1016 , 1.6×107～7.1×108 , 9.3×101～1.5×103 and 1.2×1015～6.7×1017 , 1.2×108～1.4×109 , 1.4×102～4.6×102 min-1 , respectively. In addition, the activation energy of cellulose and lignin increased and their contributions to volatile tended to fall, whereas the activation energy of hemicellulose decreased and its contribution to volatile tended to rise with increasing of heating rate.
基金Project supported by the Natural Science Foundation of Fujian Province,China(Grant No.2021J01574).
文摘We study the quantum phase transition and entanglement in the Jaynes-Cummings model with squeezed light,utilize a special transformation method to obtain the analytical ground state of the model within the near-resonance regime,and numerically verify the validity of the analytical ground state.It is found that the ground state exhibits a first-order quantum phase transition at the critical point linearly induced by squeezed light,and the ground state entanglement reaches its maximum when the qubit-field coupling strength is large enough at the critical point.
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
文摘Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.
文摘Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].
基金funded by the National Key Research and Development Program of China(No.2017YFC1501204)the National Natural Science Foundation of China(Nos.51678536,41404096)+2 种基金the Scientific and Technological Research Program of Henan Province(No.171100310100)Program for Innovative Research Team(in Science and Technology)in University of Henan Province(19HASTIT043)the Outstanding Young Talent Research Fund of Zhengzhou University(1621323001).
文摘Possessing advantages such as high computing efficiency and ease of programming,the Symplectic Euler algorithm can be applied to construct a groundpenetrating radar(GPR)wave propagation numerical model for complex geoelectric structures.However,the Symplectic Euler algorithm is still a difference algorithm,and for a complicated boundary,ladder grids are needed to perform an approximation process,which results in a certain amount of error.Further,grids that are too dense will seriously decrease computing efficiency.This paper proposes a conformal Symplectic Euler algorithm based on the conformal grid technique,amends the electric/magnetic fieldupdating equations of the Symplectic Euler algorithm by introducing the effective dielectric constant and effective permeability coefficient,and reduces the computing error caused by the ladder approximation of rectangular grids.Moreover,three surface boundary models(the underground circular void model,the undulating stratum model,and actual measurement model)are introduced.By comparing reflection waveforms simulated by the traditional Symplectic Euler algorithm,the conformal Symplectic Euler algorithm and the conformal finite difference time domain(CFDTD),the conformal Symplectic Euler algorithm achieves almost the same level of accuracy as the CFDTD method,but the conformal Symplectic Euler algorithm improves the computational efficiency compared with the CFDTD method dramatically.When the dielectric constants of the two materials vary greatly,the conformal Symplectic Euler algorithm can reduce the pseudo-waves almost by 80% compared with the traditional Symplectic Euler algorithm on average.
文摘Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.
基金funded by the Office of the Vice-President for Research and Development of Cebu Technological University.
文摘This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to user behavior and platform-driven moderation on social media.The proposed methodological framework(1)utilizes large language models for social media post analysis and categorization,(2)employs k-means clustering for content characterization,and(3)incorporates the TODIM(Tomada de Decisão Interativa Multicritério)method to determine moderation strategies based on expert judgments.In general,the fully integrated framework leverages the strengths of these intelligent systems in a more systematic evaluation of large-scale decision problems.When applied in social media moderation,this approach promotes nuanced and context-sensitive self-moderation by taking into account factors such as cultural background and geographic location.The application of this framework is demonstrated within Facebook groups.Eight distinct content clusters encompassing safety,harassment,diversity,and misinformation are identified.Analysis revealed a preference for content removal across all clusters,suggesting a cautious approach towards potentially harmful content.However,the framework also highlights the use of other moderation actions,like account suspension,depending on the content category.These findings contribute to the growing body of research on self-moderation and offer valuable insights for creating safer and more inclusive online spaces within smaller communities.
基金financially supported by the National Key Research and Development Program of China (No. 2023YFB3812601)the National Natural Science Foundation of China (No. 51925401)the Young Elite Scientists Sponsorship Program by CAST, China (No. 2022QNRC001)。
文摘Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy plates.First,finite element simulations of casting processes were carried out with various parameters to build a dataset.Subsequently,different machine learning algorithms were employed to achieve high precision in predicting temperature fields,mushy zone locations,mushy zone inclination angle,and billet grain size.Finally,the process parameters were quickly optimized using a strategy consisting of random generation,prediction,and screening,allowing the mushy zone to be controlled to the desired target.The optimized parameters are 1234℃for heating mold temperature,47 mm/min for casting speed,and 10 L/min for cooling water flow rate.The optimized mushy zone is located in the middle of the second heat insulation section and has an inclination angle of roughly 7°.
基金supported by the National Natural Science Foundation of China(Nos.42107420,U23A20157,and U1910207)Shanxi Province Science Foundation for Young Scholars(No.20210302124363).
文摘Vegetation plays an important role in the environmental transport behavior of organic pollutants,however,the different roles of crops and natural vegetation have been ignored in most previous studies.In this study,we developed the BETR-Urban-Rural-Veg model to quantitatively evaluate the influences of both natural vegetation and crops on the multimedia transport processes of Phenanthrene(PHE)and Benzo(a)pyrene(BaP)in mainland of China.The geographic distribution of polycyclic aromatic hydrocarbon(PAH)emissions and concentrations were consistent,displaying higher levels in northern China while lower levels in southern China.Under seasonal simulations,for both natural vegetation and crops,PAH concentrations in winter and spring were 1.5 to 27-fold higher than in summer and autumn,especially for PHE.Owing to the higher leaf area index(LAI)of natural vegetation and harvesting of crops,the filter and sequestration effect of natural vegetation was stronger than crops,while the seasonal changes of PAH concentrations in crops were more significant than natural vegetation.Temperature,precipitation rates and LAI might have important influences on seasonal concentrations and overall persistence of PAHs.PHE was more sensitive to the impacts of seasonal environmental parameters.Under different landscape scenarios,average annual PAH concentrations in natural vegetation were always a little higher than those in crops,and the overall persistence of BaP was greatly affected increasing by 15.15%-16.47%.This improved model provides a useful tool for environmental management.The results of this study are expected to support land use plans and decision-making in China's mainland.
