Natural soil generally exhibits significant transverse isotropy(TI)due to weathering and sedimentation,meaning that horizontal moduli differ from their vertical counterpart.The TI mechanical model is more appropriate ...Natural soil generally exhibits significant transverse isotropy(TI)due to weathering and sedimentation,meaning that horizontal moduli differ from their vertical counterpart.The TI mechanical model is more appropriate for actual situations.Although soil exhibits material nonlinearity under earthquake excitation,existing research on the TI medium is limited to soil linearity and neglects the nonlinear response of TI sites.A 2D equivalent linear model for a layered TI half-space subjected to seismic waves is derived in the transformed wave number domain using the exact dynamic stiffness matrix of the TI medium.This study introduces a method for determining the effective shear strain of TI sites under oblique wave incidence,and further describes a systematic study on the effects of TI parameters and soil nonlinearity on site responses.Numerical results indicate that seismic responses of the TI medium significantly differ from those of isotropic sites and that the responses are highly dependent on TI parameters,particularly in nonlinear cases,while also being sensitive to incident angle and excitation intensity.Moreover,the differences in peak acceleration and waveform for various TI materials may also be amplified due to the strong nonlinearity.The study provides valuable insights for improving the accuracy of seismic response analysis in engineering applications.展开更多
The Madden-Julian Oscillation(MJO)is a key atmospheric component connecting global weather and climate.It func-tions as a primary source for subseasonal forecasts.Previous studies have highlighted the vital impact of ...The Madden-Julian Oscillation(MJO)is a key atmospheric component connecting global weather and climate.It func-tions as a primary source for subseasonal forecasts.Previous studies have highlighted the vital impact of oceanic processes on MJO propagation.However,few existing MJO prediction approaches adequately consider these factors.This study determines the critical region for the oceanic processes affecting MJO propagation by utilizing 22-year Climate Forecast System Reanalysis data.By intro-ducing surface and subsurface oceanic temperature within this critical region into a lagged multiple linear regression model,the MJO forecasting skill is considerably optimized.This optimization leads to a 12 h enhancement in the forecasting skill of the first principal component and efficiently decreases prediction errors for the total predictions.Further analysis suggests that,during the years in which MJO events propagate across the Maritime Continent over a more southerly path,the optimized statistical forecasting model obtains better improvements in MJO prediction.展开更多
While much of international marketing research involves two or more levels, limited work in the international marketing literature uses hierarchical linear modeling to examine different level effects. This study condu...While much of international marketing research involves two or more levels, limited work in the international marketing literature uses hierarchical linear modeling to examine different level effects. This study conducts a thorough literature review on hierarchical linear modeling （HLM） in 28 international marketing papers that employed HLM from 2005-2014 and evaluates the use of HLM in these papers on the objects, operating levels, and other issues. We call for more applications of HLM in international marketing research, particularly for research on emerging markets with significant sub-national and institutional variations. The paper provides an illustrative empirical study that employs HLM to test the moderating role of industry-level government subsidies in the relationship between firm innovation and exporter performance in China.展开更多
Stable water isotopes are natural tracers quantifying the contribution of moisture recycling to local precipitation,i.e.,the moisture recycling ratio,but various isotope-based models usually lead to different results,...Stable water isotopes are natural tracers quantifying the contribution of moisture recycling to local precipitation,i.e.,the moisture recycling ratio,but various isotope-based models usually lead to different results,which affects the accuracy of local moisture recycling.In this study,a total of 18 stations from four typical areas in China were selected to compare the performance of isotope-based linear and Bayesian mixing models and to determine local moisture recycling ratio.Among the three vapor sources including advection,transpiration,and surface evaporation,the advection vapor usually played a dominant role,and the contribution of surface evaporation was less than that of transpiration.When the abnormal values were ignored,the arithmetic averages of differences between isotope-based linear and the Bayesian mixing models were 0.9%for transpiration,0.2%for surface evaporation,and–1.1%for advection,respectively,and the medians were 0.5%,0.2%,and–0.8%,respectively.The importance of transpiration was slightly less for most cases when the Bayesian mixing model was applied,and the contribution of advection was relatively larger.The Bayesian mixing model was found to perform better in determining an efficient solution since linear model sometimes resulted in negative contribution ratios.Sensitivity test with two isotope scenarios indicated that the Bayesian model had a relatively low sensitivity to the changes in isotope input,and it was important to accurately estimate the isotopes in precipitation vapor.Generally,the Bayesian mixing model should be recommended instead of a linear model.The findings are useful for understanding the performance of isotope-based linear and Bayesian mixing models under various climate backgrounds.展开更多
As maritime activities increase globally,there is a greater dependency on technology in monitoring,control,and surveillance of vessel activity.One of the most prominent systems for monitoring vessel activity is the Au...As maritime activities increase globally,there is a greater dependency on technology in monitoring,control,and surveillance of vessel activity.One of the most prominent systems for monitoring vessel activity is the Automatic Identification System(AIS).An increase in both vessels fitted with AIS transponders and satellite and terrestrial AIS receivers has resulted in a significant increase in AIS messages received globally.This resultant rich spatial and temporal data source related to vessel activity provides analysts with the ability to perform enhanced vessel movement analytics,of which a pertinent example is the improvement of vessel location predictions.In this paper,we propose a novel strategy for predicting future locations of vessels making use of historic AIS data.The proposed method uses a Linear Regression Model(LRM)and utilizes historic AIS movement data in the form of a-priori generated spatial maps of the course over ground(LRMAC).The LRMAC is an accurate low complexity first-order method that is easy to implement operationally and shows promising results in areas where there is a consistency in the directionality of historic vessel movement.In areas where the historic directionality of vessel movement is diverse,such as areas close to harbors and ports,the LRMAC defaults to the LRM.The proposed LRMAC method is compared to the Single-Point Neighbor Search(SPNS),which is also a first-order method and has a similar level of computational complexity,and for the use case of predicting tanker and cargo vessel trajectories up to 8 hours into the future,the LRMAC showed improved results both in terms of prediction accuracy and execution time.展开更多
Adaptive fractional polynomial modeling of general correlated outcomes is formulated to address nonlinearity in means, variances/dispersions, and correlations. Means and variances/dispersions are modeled using general...Adaptive fractional polynomial modeling of general correlated outcomes is formulated to address nonlinearity in means, variances/dispersions, and correlations. Means and variances/dispersions are modeled using generalized linear models in fixed effects/coefficients. Correlations are modeled using random effects/coefficients. Nonlinearity is addressed using power transforms of primary (untransformed) predictors. Parameter estimation is based on extended linear mixed modeling generalizing both generalized estimating equations and linear mixed modeling. Models are evaluated using likelihood cross-validation (LCV) scores and are generated adaptively using a heuristic search controlled by LCV scores. Cases covered include linear, Poisson, logistic, exponential, and discrete regression of correlated continuous, count/rate, dichotomous, positive continuous, and discrete numeric outcomes treated as normally, Poisson, Bernoulli, exponentially, and discrete numerically distributed, respectively. Example analyses are also generated for these five cases to compare adaptive random effects/coefficients modeling of correlated outcomes to previously developed adaptive modeling based on directly specified covariance structures. Adaptive random effects/coefficients modeling substantially outperforms direct covariance modeling in the linear, exponential, and discrete regression example analyses. It generates equivalent results in the logistic regression example analyses and it is substantially outperformed in the Poisson regression case. Random effects/coefficients modeling of correlated outcomes can provide substantial improvements in model selection compared to directly specified covariance modeling. However, directly specified covariance modeling can generate competitive or substantially better results in some cases while usually requiring less computation time.展开更多
The purpose of this research is to explore the factors influencing the self-improvement process of museums in China and to conduct empirical analyses based on multiple linear regression models.As core institutions for...The purpose of this research is to explore the factors influencing the self-improvement process of museums in China and to conduct empirical analyses based on multiple linear regression models.As core institutions for inheriting and displaying cultural heritage and enhancing public cultural literacy,museums’self-improvement is of great significance in promoting cultural development,optimizing the supply of public cultural services,and enhancing social influence.This paper constructs a multiple linear regression model for the influencing factors of museum self-improvement by integrating several key variables,including emerging cultural and museum business(EF),institutional reform(SR),research and innovation level(RIL),management level(ML),and the museum cultural and creative industry(MCCI).The study employs scientific methods such as literature review,data collection,and data analysis to thoroughly explore the internal logic of museum operations and development.Through multiple linear regression analyses,it quantifies the specific influence and relative importance of each factor on the level of museum self-improvement.The results indicate that the management level(ML)is the dominant factor among the variables studied,exerting the most significant influence on museum self-improvement.Based on these empirical findings,this paper provides an in-depth analysis of the specific factors affecting museum self-improvement in China,offering solid theoretical support and practical guidance for the sustainable development of museums.展开更多
Pyrrolizidine alkaloids(PAs)and their N-oxides(PANOs)are phytotoxins produced by various plant species and have been emerged as environmental pollutants.The sorption/desorption behaviors of PAs/PANOs in soil are cruci...Pyrrolizidine alkaloids(PAs)and their N-oxides(PANOs)are phytotoxins produced by various plant species and have been emerged as environmental pollutants.The sorption/desorption behaviors of PAs/PANOs in soil are crucial due to the horizontal transfer of these natural products from PA-producing plants to soil and subsequently absorbed by plant roots.This study firstly investigated the sorption/desorption behaviors of PAs/PANOs in tea plantation soils with distinct characteristics.Sorption amounts for seneciphylline(Sp)and seneciphylline-N-oxide(SpNO)in three acidic soils ranged from 2.9 to 5.9μg/g and 1.7 to 2.8μg/g,respectively.Desorption percentages for Sp and SpNO were from 22.2%to 30.5%and 36.1%to 43.9%.In the mixed PAs/PANOs systems,stronger sorption of PAs over PANOs was occurred in tested soils.Additionally,the Freundlich models more precisely described the sorption/desorption isotherms.Cation exchange capacity,sand content and total nitrogen were identified as major influencing factors by linear regression models.Overall,the soils exhibiting higher sorption capacities for compounds with greater hydrophobicity.PANOs were more likely to migrate within soils and be absorbed by tea plants.It contributes to the understanding of environmental fate of PAs/PANOs in tea plantations and provides basic data and clues for the development of PAs/PANOs reduction technology.展开更多
Necessary and sufficient conditions for equalities between a 2 y′(I-P Xx)y and minimum norm quadratic unbiased estimator of variance under the general linear model, where a 2 is a known positive number, are...Necessary and sufficient conditions for equalities between a 2 y′(I-P Xx)y and minimum norm quadratic unbiased estimator of variance under the general linear model, where a 2 is a known positive number, are derived. Further, when the Gauss? Markov estimators and the ordinary least squares estimator are identical, a relative simply equivalent condition is obtained. At last, this condition is applied to an interesting example.展开更多
The genus Beta encompasses economically important root crops such as sugar and table beet.A Beta diversity set including the wild relative B.vulgaris ssp.maritima was grown in the field,and a large phenotypic diversit...The genus Beta encompasses economically important root crops such as sugar and table beet.A Beta diversity set including the wild relative B.vulgaris ssp.maritima was grown in the field,and a large phenotypic diversity was observed.The genomes of 290 accessions were sequenced,and more than 10 million high-quality SNPs were employed to study genetic diversity.A genome-wide association study was performed,and marker-trait associations were found for nine phenotypic traits.The candidate gene within the M locus controlling monogermity on chromosome 4 was previously unknown.The most significant association for monogermity was identified at the end of chromosome 4.Within this region,a non-synonymous mutation within the zinc-finger domain of the WIP2 gene co-segregated with monogermity.This gene plays a regulatory role in AGL8/FUL in Arabidopsis.Intriguingly,commercial hybrids are in a heterozygous state at this position.Thus,the long-sought gene for monogermity was identified in this study.Red and yellow pigmentation due to betalain accumulation in shoots and roots is an important characteristic of table and leaf beets.The strongest associations were found upstream or downstream of two genes encoding Cytochrome P450 and anthocyanin MYB-like transcription factor proteins involved in betalain biosynthesis.Significant associations for Cercospora leaf spot resistance were identified on chromosomes 1,2,7,and 9.The associated regions harbor genes encoding proteins with leucinerich repeats and nucleotide binding sites whose homologs are major constituents of plant-pathogen defense.展开更多
Since its inception,the epsilon distribution has piqued the interest of statisticians.It has been successfully used to solve a variety of statistical problems.In this article,we propose to use the quadratic rank trans...Since its inception,the epsilon distribution has piqued the interest of statisticians.It has been successfully used to solve a variety of statistical problems.In this article,we propose to use the quadratic rank transmutation map mechanism to extend this distribution.This mechanism is not new;it was already used to improve the modeling capabilities of a number of existing distributions.For the original epsilon distribution,we expect the same benefits.As a result,we implement the transmuted epsilon distribution as a flexible three-parameter distribution with a bounded domain.We demonstrate its key features,focusing on the properties of its distributional mechanism and conducting quantile and moment analyses.Applications of the model are presented using two data sets.We also perform a regression analysis based on this distribution.展开更多
The multiscale variability in summer extreme persistent precipitation(SEPP)in China from 1961 to 2020 was investigated via three extreme precipitation indices:consecutive wet days,total precipitation amount,and daily ...The multiscale variability in summer extreme persistent precipitation(SEPP)in China from 1961 to 2020 was investigated via three extreme precipitation indices:consecutive wet days,total precipitation amount,and daily precipitation intensity.The relationships between precursory and concurrent global oceanic modes and SEPP were identified via a generalized linear model(GLM).The influence of oceanic modes on SEPP was finally investigated via numerical simulations.The results revealed that the climatological SEPP(≥14 days)mainly appears across the Tibetan Plateau,Yunnan–Guizhou Plateau,and South China coast.The first EOF mode for all three indices showed strong signals over the Yangtze River.Further analysis via the GLM suggested that the positive phases of the tropical North Atlantic(TNA)in autumn,ENSO in winter,the Indian Ocean Basin(IOB)in spring,and the western North Pacific(WNP)in summer emerged as the most effective precursory factors of SEPP,which could serve as preceding signals for future predictions,contributing 30.2%,36.4%,38.0%,and 55.6%,respectively,to the GLM.Sensitivity experiments revealed that SST forcing in all four seasons contributes to SEPP over China,whereas the winter and summer SST warming over the Pacific and Indian Ocean(IO)contributes the most.Diagnosis of the hydrological cycle suggested that water vapor advection predominantly originates from the western Pacific and IO in summer,driven by the strengthened subtropical high and Asian summer monsoon(ASM).The enhanced vertical water vapor transport is attributed to stronger upward motion across all four seasons.These findings are helpful for better understanding SEPP variabilities and their prediction under SST warming.展开更多
Maintaining optimal quality of life(QoL)is a pivotal for“successful aging”.Understanding how the QoL of the elderly develops and what role psychological factors play in its development will help improve QoL from a p...Maintaining optimal quality of life(QoL)is a pivotal for“successful aging”.Understanding how the QoL of the elderly develops and what role psychological factors play in its development will help improve QoL from a psychological perspective.Embedded within the lifespan theory of control,this longitudinal study aimed to(1)map the temporal trajectory of QoL among Chinese older adults,(2)examine differential effects of tripartite negative emotions(stress,anxiety,depression),and(3)test themoderating role of control strategies(goal engagement,goal disengagement,self-protection)in emotion-QoL dynamics.A prospective cohort of 345 community-dwelling older adults(Mage=83.84±8.49 years;55.1%female)completed validated measures-SF-36 for QoL,DASS-21 for negative emotions,and an adapted Control Strategies Questionnaire(CAS)-at three waves spanning 12 months.Hierarchical linear modeling(HLM)with time-nested structure analyzed intraindividual changes and interindividual differences.QoL exhibited a significant linear decline over time(β=−4.75,p<0.001).Stress(β=−14.12,p<0.001)and anxiety(β=−11.24,p<0.001)robustly predicted QoL decline,whereas depression showed no significant effect.Control strategies had divergent associations:goal engagement(β=3.51,p<0.001)and self-protection(β=2.38,p=0.015)predicted higher baseline QoL,while goal disengagement accelerated decline(β=−7.00,p<0.001;interaction with time:β=−2.46,p<0.001).Contrary to hypotheses,control strategies did not moderate emotion-QoL associations(ΔR2=0.02,p=0.21).The results showed that stress and anxiety played an important role in the QoL of the elderly.At the same time,goal engagement and self-protection were beneficial to the QoL of the elderly,while goal disengagement was not conducive to QoL and its development among the elderly.Meanwhile,the negative effect of anxiety and stress on the QoL of the elderly was not affected by the control strategies.展开更多
Doline susceptibility mapping(DSM)in karst aquifer is important in terms of estimating the vulnerability of the aquifer to pollutants,estimating the infiltration rate,and infrastructures exposed to the development of ...Doline susceptibility mapping(DSM)in karst aquifer is important in terms of estimating the vulnerability of the aquifer to pollutants,estimating the infiltration rate,and infrastructures exposed to the development of dolines.In this research,doline susceptibility map was prepared in Saldaran mountain by generalized linear model(GLM)using 14 affecting parameters extracted from satellite images,digital elevation model,and geology map.Only 8 parameters have been inputted to the model which had correlation with dolines.In this regards,306 dolines were identified by the photogrammetric Unmanned Aerial Vehicles(UAV)method in 600 hectares of Salderan lands and then,these data were divided into the training(70%)and testing(30%)data for modelling.The results of DSM modeling showed that classified probability of doline occurrences in the Saldaran mountain were as follow:16.5%of the area high to very high,72%in the class of low to very low,and 5%in the moderate class.Also,locally,in Saldaran mountain,the Pirghar aquifer has the highest potential for the doline development,followed by Bagh Rostam and Sarab aquifers.Also,the precipitation,digital elevation model,Topographic Position Index,drainage density,slope,TRASP(transformed the circular aspect to a radiation index),Snow-Covered Days and vegetation cover index are of highest importance in the DSM modeling,respectively.Accurate evaluation of the model using the Receiver Operating Characteristics(ROC)curve represents a very good accuracy(AUC=0.953)of the DSM model.展开更多
High-dimensional heterogeneous data have acquired increasing attention and discussion in the past decade.In the context of heterogeneity,semiparametric regression emerges as a popular method to model this type of data...High-dimensional heterogeneous data have acquired increasing attention and discussion in the past decade.In the context of heterogeneity,semiparametric regression emerges as a popular method to model this type of data in statistics.In this paper,we leverage the benefits of expectile regression for computational efficiency and analytical robustness in heterogeneity,and propose a regularized partially linear additive expectile regression model with a nonconvex penalty,such as SCAD or MCP,for high-dimensional heterogeneous data.We focus on a more realistic scenario where the regression error exhibits a heavy-tailed distribution with only finite moments.This scenario challenges the classical sub-gaussian distribution assumption and is more prevalent in practical applications.Under certain regular conditions,we demonstrate that with probability tending to one,the oracle estimator is one of the local minima of the induced optimization problem.Our theoretical analysis suggests that the dimensionality of linear covariates that our estimation procedure can handle is fundamentally limited by the moment condition of the regression error.Computationally,given the nonconvex and nonsmooth nature of the induced optimization problem,we have developed a two-step algorithm.Finally,our method’s effectiveness is demonstrated through its high estimation accuracy and effective model selection,as evidenced by Monte Carlo simulation studies and a real-data application.Furthermore,by taking various expectile weights,our method effectively detects heterogeneity and explores the complete conditional distribution of the response variable,underscoring its utility in analyzing high-dimensional heterogeneous data.展开更多
Over the past decades,the expansion of natu-ral secondary forests has played a crucial role in offsetting the loss of primary forests and combating climate change.Despite this,there is a gap in our understanding of ho...Over the past decades,the expansion of natu-ral secondary forests has played a crucial role in offsetting the loss of primary forests and combating climate change.Despite this,there is a gap in our understanding of how tree species’growth and mortality patterns vary with eleva-tion in these secondary forests.In this study,we analyzed data from two censuses(spanning a five-year interval)conducted in both evergreen broadleaved forests(EBF)and temperate coniferous forests(TCF),which have been recovering for half a century,across elevation gradients in a subtropical mountain region,Mount Wuyi,China.The results indicated that the relative growth rate(RGR)of EBF(0.028±0.001 cm·cm^(-1)·a^(-1))and the mortality rate(MR)(20.03%±1.70%)were 27.3%and 16.4%higher,respec-tively,than those of TCF.Interestingly,the trade-off between RGR and MR in EBF weakened as elevation increased,a trend not observed in TCF.Conversely,TCF consistently showed a stronger trade-off between RGR and MR compared to EBF.Generalized linear mixed models revealed that ele-vation influences RGR both directly and indirectly through its interactions with slope,crown competition index(CCI),and tree canopy height(CH).However,tree mortality did not show a significant correlation with elevation.Additionally,DBH significantly influenced both tree growth and mortal-ity,whereas and CH and CCI had opposite effects on tree growth between EBF and TCF.Our study underscores the importance of elevation in shaping the population dynamics and the biomass carbon sink balance of mountain forests.These insights enhance our understanding of tree species’life strategies,enabling more accurate predictions of forest dynamics and their response to environmental changes.展开更多
Under the background of this era,green finance and the upgrading and optimization of industrial structure have become a hot research topic.The article focuses on Jiangsu Province,carefully explores the impact of green...Under the background of this era,green finance and the upgrading and optimization of industrial structure have become a hot research topic.The article focuses on Jiangsu Province,carefully explores the impact of green financial development on the upgrading and optimization of industrial structure and the real effect,collates and summarizes the theories of green finance and industrial structure at home and abroad,and carefully analyzes the development of green finance in Jiangsu Province,such as the gradual expansion of green credit scale,the characteristics of industrial structure,the change of the proportion of three industries,the development situation of emerging industries and so on.By means of econometrics,an empirical model covering Green Financial Development Indicators and industrial structure optimization indicators is established to do multiple linear regression analysis and stability test.The empirical results show that the development of green finance in Jiangsu plays an obvious positive role in the optimization and upgrading of industrial structure.Green finance is environmental protection,new energy and other green industries are given important financial support,which drives their scale expansion and technological innovation,and makes the industrial structure develop towards a higher level and a more reasonable direction.From this point of view,corresponding proposals are put forward to improve the policy incentive system,add green financial products,and strengthen the construction of green financial market.The purpose is to give better play to the advantages of green finance,accelerate the optimization and upgrading of industrial structure in Jiangsu,and provide theoretical basis and practical guidance for achieving green economic transformation and sustainable development.展开更多
By analyzing the observed phenomena and the data collected in the study, a multi-compartment linear circulation model for targeting drug delivery system was developed and the function formulas of the drug concentratio...By analyzing the observed phenomena and the data collected in the study, a multi-compartment linear circulation model for targeting drug delivery system was developed and the function formulas of the drug concentration-time in blood and target organ by computing were figured out. The drug concentration-time curve for target organ can be plotted with reference to the data of drug concentration in blood according to the model. The pharmacokinetic parameters of the drug in target organ could also be obtained. The practicability of the model was further checked by the curves of drug concentration-time in blood and target organ(liver) of liver-targeting nanoparticles in animal tests. Based on the liver drug concentration-time curves calculated by the function formula of the drug in target organ, the pharmacokinetic behavior of the drug in target organ(liver) was analyzed by statistical moment, and its pharmacokinetic parameters in liver were obtained. It is suggested that the (relative targeting index( can be used for quantitative evaluation of the targeting drug delivery systems.展开更多
Firstly,based on the data of air quality and the meteorological data in Baoding City from 2017 to 2021,the correlations of meteorological elements and pollutants with O_(3)concentration were explored to determine the ...Firstly,based on the data of air quality and the meteorological data in Baoding City from 2017 to 2021,the correlations of meteorological elements and pollutants with O_(3)concentration were explored to determine the forecast factors of forecast models.Secondly,the O_(3)-8h concentration in Baoding City in 2021 was predicted based on the constructed models of multiple linear regression(MLR),backward propagation neural network(BPNN),and auto regressive integrated moving average(ARIMA),and the predicted values were compared with the observed values to test their prediction effects.The results show that overall,the MLR,BPNN and ARIMA models were able to forecast the changing trend of O_(3)-8h concentration in Baoding in 2021,but the BPNN model gave better forecast results than the ARIMA and MLR models,especially for the prediction of the high values of O_(3)-8h concentration,and the correlation coefficients between the predicted values and the observed values were all higher than 0.9 during June-September.The mean error(ME),mean absolute error(MAE),and root mean square error(RMSE)of the predicted values and the observed values of daily O_(3)-8h concentration based on the BPNN model were 0.45,19.11 and 24.41μg/m 3,respectively,which were significantly better than those of the MLR and ARIMA models.The prediction effects of the MLR,BPNN and ARIMA models were the best at the pollution level,followed by the excellent level,and it was the worst at the good level.In comparison,the prediction effect of BPNN model was better than that of the MLR and ARIMA models as a whole,especially for the pollution and excellent levels.The TS scores of the BPNN model were all above 66%,and the PC values were above 86%.The BPNN model can forecast the changing trend of O_(3)concentration more accurately,and has a good practical application value,but at the same time,the predicted high values of O_(3)concentration should be appropriately increased according to error characteristics of the model.展开更多
The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a nove...The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.展开更多
基金National Natural Science Foundation of China under Grant No.U2139208。
文摘Natural soil generally exhibits significant transverse isotropy(TI)due to weathering and sedimentation,meaning that horizontal moduli differ from their vertical counterpart.The TI mechanical model is more appropriate for actual situations.Although soil exhibits material nonlinearity under earthquake excitation,existing research on the TI medium is limited to soil linearity and neglects the nonlinear response of TI sites.A 2D equivalent linear model for a layered TI half-space subjected to seismic waves is derived in the transformed wave number domain using the exact dynamic stiffness matrix of the TI medium.This study introduces a method for determining the effective shear strain of TI sites under oblique wave incidence,and further describes a systematic study on the effects of TI parameters and soil nonlinearity on site responses.Numerical results indicate that seismic responses of the TI medium significantly differ from those of isotropic sites and that the responses are highly dependent on TI parameters,particularly in nonlinear cases,while also being sensitive to incident angle and excitation intensity.Moreover,the differences in peak acceleration and waveform for various TI materials may also be amplified due to the strong nonlinearity.The study provides valuable insights for improving the accuracy of seismic response analysis in engineering applications.
基金supported by the National Key Program for Developing Basic Science(Nos.2022YFF0801702 and 2022YFE0106600)the National Natural Science Foundation of China(Nos.42175060 and 42175021)the Jiangsu Province Science Foundation(No.BK20250200302).
文摘The Madden-Julian Oscillation(MJO)is a key atmospheric component connecting global weather and climate.It func-tions as a primary source for subseasonal forecasts.Previous studies have highlighted the vital impact of oceanic processes on MJO propagation.However,few existing MJO prediction approaches adequately consider these factors.This study determines the critical region for the oceanic processes affecting MJO propagation by utilizing 22-year Climate Forecast System Reanalysis data.By intro-ducing surface and subsurface oceanic temperature within this critical region into a lagged multiple linear regression model,the MJO forecasting skill is considerably optimized.This optimization leads to a 12 h enhancement in the forecasting skill of the first principal component and efficiently decreases prediction errors for the total predictions.Further analysis suggests that,during the years in which MJO events propagate across the Maritime Continent over a more southerly path,the optimized statistical forecasting model obtains better improvements in MJO prediction.
基金The anthors are grateful for the financial support of the Research Funding for the Doctoral Programs of Higher Education, Ministry of Education, China （20120004120005）, the Beijing Youth Talent Project, and National Natural Science Foundation of China （71202149）.
文摘While much of international marketing research involves two or more levels, limited work in the international marketing literature uses hierarchical linear modeling to examine different level effects. This study conducts a thorough literature review on hierarchical linear modeling （HLM） in 28 international marketing papers that employed HLM from 2005-2014 and evaluates the use of HLM in these papers on the objects, operating levels, and other issues. We call for more applications of HLM in international marketing research, particularly for research on emerging markets with significant sub-national and institutional variations. The paper provides an illustrative empirical study that employs HLM to test the moderating role of industry-level government subsidies in the relationship between firm innovation and exporter performance in China.
基金This study was supported by the National Natural Science Foundation of China(42261008,41971034)the Natural Science Foundation of Gansu Province,China(22JR5RA074).
文摘Stable water isotopes are natural tracers quantifying the contribution of moisture recycling to local precipitation,i.e.,the moisture recycling ratio,but various isotope-based models usually lead to different results,which affects the accuracy of local moisture recycling.In this study,a total of 18 stations from four typical areas in China were selected to compare the performance of isotope-based linear and Bayesian mixing models and to determine local moisture recycling ratio.Among the three vapor sources including advection,transpiration,and surface evaporation,the advection vapor usually played a dominant role,and the contribution of surface evaporation was less than that of transpiration.When the abnormal values were ignored,the arithmetic averages of differences between isotope-based linear and the Bayesian mixing models were 0.9%for transpiration,0.2%for surface evaporation,and–1.1%for advection,respectively,and the medians were 0.5%,0.2%,and–0.8%,respectively.The importance of transpiration was slightly less for most cases when the Bayesian mixing model was applied,and the contribution of advection was relatively larger.The Bayesian mixing model was found to perform better in determining an efficient solution since linear model sometimes resulted in negative contribution ratios.Sensitivity test with two isotope scenarios indicated that the Bayesian model had a relatively low sensitivity to the changes in isotope input,and it was important to accurately estimate the isotopes in precipitation vapor.Generally,the Bayesian mixing model should be recommended instead of a linear model.The findings are useful for understanding the performance of isotope-based linear and Bayesian mixing models under various climate backgrounds.
文摘As maritime activities increase globally,there is a greater dependency on technology in monitoring,control,and surveillance of vessel activity.One of the most prominent systems for monitoring vessel activity is the Automatic Identification System(AIS).An increase in both vessels fitted with AIS transponders and satellite and terrestrial AIS receivers has resulted in a significant increase in AIS messages received globally.This resultant rich spatial and temporal data source related to vessel activity provides analysts with the ability to perform enhanced vessel movement analytics,of which a pertinent example is the improvement of vessel location predictions.In this paper,we propose a novel strategy for predicting future locations of vessels making use of historic AIS data.The proposed method uses a Linear Regression Model(LRM)and utilizes historic AIS movement data in the form of a-priori generated spatial maps of the course over ground(LRMAC).The LRMAC is an accurate low complexity first-order method that is easy to implement operationally and shows promising results in areas where there is a consistency in the directionality of historic vessel movement.In areas where the historic directionality of vessel movement is diverse,such as areas close to harbors and ports,the LRMAC defaults to the LRM.The proposed LRMAC method is compared to the Single-Point Neighbor Search(SPNS),which is also a first-order method and has a similar level of computational complexity,and for the use case of predicting tanker and cargo vessel trajectories up to 8 hours into the future,the LRMAC showed improved results both in terms of prediction accuracy and execution time.
文摘Adaptive fractional polynomial modeling of general correlated outcomes is formulated to address nonlinearity in means, variances/dispersions, and correlations. Means and variances/dispersions are modeled using generalized linear models in fixed effects/coefficients. Correlations are modeled using random effects/coefficients. Nonlinearity is addressed using power transforms of primary (untransformed) predictors. Parameter estimation is based on extended linear mixed modeling generalizing both generalized estimating equations and linear mixed modeling. Models are evaluated using likelihood cross-validation (LCV) scores and are generated adaptively using a heuristic search controlled by LCV scores. Cases covered include linear, Poisson, logistic, exponential, and discrete regression of correlated continuous, count/rate, dichotomous, positive continuous, and discrete numeric outcomes treated as normally, Poisson, Bernoulli, exponentially, and discrete numerically distributed, respectively. Example analyses are also generated for these five cases to compare adaptive random effects/coefficients modeling of correlated outcomes to previously developed adaptive modeling based on directly specified covariance structures. Adaptive random effects/coefficients modeling substantially outperforms direct covariance modeling in the linear, exponential, and discrete regression example analyses. It generates equivalent results in the logistic regression example analyses and it is substantially outperformed in the Poisson regression case. Random effects/coefficients modeling of correlated outcomes can provide substantial improvements in model selection compared to directly specified covariance modeling. However, directly specified covariance modeling can generate competitive or substantially better results in some cases while usually requiring less computation time.
基金2024 Guangdong Philosophy and Social Science Planning Discipline Co-construction Project“Study on the Measurement of Economic Benefits and Path of High-Quality Development of Museums in Guangdong Province”(Project No.GD24XYS045)Key Project of the Social Sciences Division of Shenzhen Polytechnic University“Research on Strategies for Enhancing the Effectiveness of Non-State-Owned Museums in Shenzhen”(Project No.20240105)+1 种基金Shenzhen Polytechnic University’s Platform Construction Project“SZPU-Fangzhi Technology AI New Media R&D Centre”(Project No:602331019PQ)Open-ended Project of the Global Urban Civilization Model Research Institute of Southern University of Science and Technology in 2024,“Research on the Efficiency Enhancement Strategy of Non State owned Museums in Shenzhen from the Perspective of Urban Civilization Construction”(Project No.IGUC24C011)。
文摘The purpose of this research is to explore the factors influencing the self-improvement process of museums in China and to conduct empirical analyses based on multiple linear regression models.As core institutions for inheriting and displaying cultural heritage and enhancing public cultural literacy,museums’self-improvement is of great significance in promoting cultural development,optimizing the supply of public cultural services,and enhancing social influence.This paper constructs a multiple linear regression model for the influencing factors of museum self-improvement by integrating several key variables,including emerging cultural and museum business(EF),institutional reform(SR),research and innovation level(RIL),management level(ML),and the museum cultural and creative industry(MCCI).The study employs scientific methods such as literature review,data collection,and data analysis to thoroughly explore the internal logic of museum operations and development.Through multiple linear regression analyses,it quantifies the specific influence and relative importance of each factor on the level of museum self-improvement.The results indicate that the management level(ML)is the dominant factor among the variables studied,exerting the most significant influence on museum self-improvement.Based on these empirical findings,this paper provides an in-depth analysis of the specific factors affecting museum self-improvement in China,offering solid theoretical support and practical guidance for the sustainable development of museums.
基金supported by the earmarked fund for the Modern Agro-Industry Technology Research System (No.CARS-19)the Innovative Research Team in Chinese Academy of Agricultural Sciences (No.CAAS ASTIP-2014-TRICAAS).
文摘Pyrrolizidine alkaloids(PAs)and their N-oxides(PANOs)are phytotoxins produced by various plant species and have been emerged as environmental pollutants.The sorption/desorption behaviors of PAs/PANOs in soil are crucial due to the horizontal transfer of these natural products from PA-producing plants to soil and subsequently absorbed by plant roots.This study firstly investigated the sorption/desorption behaviors of PAs/PANOs in tea plantation soils with distinct characteristics.Sorption amounts for seneciphylline(Sp)and seneciphylline-N-oxide(SpNO)in three acidic soils ranged from 2.9 to 5.9μg/g and 1.7 to 2.8μg/g,respectively.Desorption percentages for Sp and SpNO were from 22.2%to 30.5%and 36.1%to 43.9%.In the mixed PAs/PANOs systems,stronger sorption of PAs over PANOs was occurred in tested soils.Additionally,the Freundlich models more precisely described the sorption/desorption isotherms.Cation exchange capacity,sand content and total nitrogen were identified as major influencing factors by linear regression models.Overall,the soils exhibiting higher sorption capacities for compounds with greater hydrophobicity.PANOs were more likely to migrate within soils and be absorbed by tea plants.It contributes to the understanding of environmental fate of PAs/PANOs in tea plantations and provides basic data and clues for the development of PAs/PANOs reduction technology.
文摘Necessary and sufficient conditions for equalities between a 2 y′(I-P Xx)y and minimum norm quadratic unbiased estimator of variance under the general linear model, where a 2 is a known positive number, are derived. Further, when the Gauss? Markov estimators and the ordinary least squares estimator are identical, a relative simply equivalent condition is obtained. At last, this condition is applied to an interesting example.
基金the financial support from the German Research Foundation(Deutsche Forschungsgemeinschaft,DFG)—Project Number 400993799(Project 2 within the Research Training Group 2501 Translational Evolutionary Research,https://gepris.dfg.de/gepris/projekt/400993799)supported by the BMBF-funded de.NBI Cloud,part of the German Network for Bioinformatics(de.NBI)。
文摘The genus Beta encompasses economically important root crops such as sugar and table beet.A Beta diversity set including the wild relative B.vulgaris ssp.maritima was grown in the field,and a large phenotypic diversity was observed.The genomes of 290 accessions were sequenced,and more than 10 million high-quality SNPs were employed to study genetic diversity.A genome-wide association study was performed,and marker-trait associations were found for nine phenotypic traits.The candidate gene within the M locus controlling monogermity on chromosome 4 was previously unknown.The most significant association for monogermity was identified at the end of chromosome 4.Within this region,a non-synonymous mutation within the zinc-finger domain of the WIP2 gene co-segregated with monogermity.This gene plays a regulatory role in AGL8/FUL in Arabidopsis.Intriguingly,commercial hybrids are in a heterozygous state at this position.Thus,the long-sought gene for monogermity was identified in this study.Red and yellow pigmentation due to betalain accumulation in shoots and roots is an important characteristic of table and leaf beets.The strongest associations were found upstream or downstream of two genes encoding Cytochrome P450 and anthocyanin MYB-like transcription factor proteins involved in betalain biosynthesis.Significant associations for Cercospora leaf spot resistance were identified on chromosomes 1,2,7,and 9.The associated regions harbor genes encoding proteins with leucinerich repeats and nucleotide binding sites whose homologs are major constituents of plant-pathogen defense.
文摘Since its inception,the epsilon distribution has piqued the interest of statisticians.It has been successfully used to solve a variety of statistical problems.In this article,we propose to use the quadratic rank transmutation map mechanism to extend this distribution.This mechanism is not new;it was already used to improve the modeling capabilities of a number of existing distributions.For the original epsilon distribution,we expect the same benefits.As a result,we implement the transmuted epsilon distribution as a flexible three-parameter distribution with a bounded domain.We demonstrate its key features,focusing on the properties of its distributional mechanism and conducting quantile and moment analyses.Applications of the model are presented using two data sets.We also perform a regression analysis based on this distribution.
基金jointly funded by the National Natural Science Foundation of China(Grant Nos.42122035,42288101,42130605,72293604,42475179,and 42475020)the support of the Guangdong Provincial Observation and Research Station for Tropical Ocean Environment in Western Coastal Waters(GSTOEW)+2 种基金Key Laboratory of Space Ocean Remote Sensing and ApplicationCMAGDOU Joint Laboratory for Marine MeteorologyKey Laboratory of Climate Resources and Environment in Continental Shelf Sea and Deep Ocean(LCRE)。
文摘The multiscale variability in summer extreme persistent precipitation(SEPP)in China from 1961 to 2020 was investigated via three extreme precipitation indices:consecutive wet days,total precipitation amount,and daily precipitation intensity.The relationships between precursory and concurrent global oceanic modes and SEPP were identified via a generalized linear model(GLM).The influence of oceanic modes on SEPP was finally investigated via numerical simulations.The results revealed that the climatological SEPP(≥14 days)mainly appears across the Tibetan Plateau,Yunnan–Guizhou Plateau,and South China coast.The first EOF mode for all three indices showed strong signals over the Yangtze River.Further analysis via the GLM suggested that the positive phases of the tropical North Atlantic(TNA)in autumn,ENSO in winter,the Indian Ocean Basin(IOB)in spring,and the western North Pacific(WNP)in summer emerged as the most effective precursory factors of SEPP,which could serve as preceding signals for future predictions,contributing 30.2%,36.4%,38.0%,and 55.6%,respectively,to the GLM.Sensitivity experiments revealed that SST forcing in all four seasons contributes to SEPP over China,whereas the winter and summer SST warming over the Pacific and Indian Ocean(IO)contributes the most.Diagnosis of the hydrological cycle suggested that water vapor advection predominantly originates from the western Pacific and IO in summer,driven by the strengthened subtropical high and Asian summer monsoon(ASM).The enhanced vertical water vapor transport is attributed to stronger upward motion across all four seasons.These findings are helpful for better understanding SEPP variabilities and their prediction under SST warming.
文摘Maintaining optimal quality of life(QoL)is a pivotal for“successful aging”.Understanding how the QoL of the elderly develops and what role psychological factors play in its development will help improve QoL from a psychological perspective.Embedded within the lifespan theory of control,this longitudinal study aimed to(1)map the temporal trajectory of QoL among Chinese older adults,(2)examine differential effects of tripartite negative emotions(stress,anxiety,depression),and(3)test themoderating role of control strategies(goal engagement,goal disengagement,self-protection)in emotion-QoL dynamics.A prospective cohort of 345 community-dwelling older adults(Mage=83.84±8.49 years;55.1%female)completed validated measures-SF-36 for QoL,DASS-21 for negative emotions,and an adapted Control Strategies Questionnaire(CAS)-at three waves spanning 12 months.Hierarchical linear modeling(HLM)with time-nested structure analyzed intraindividual changes and interindividual differences.QoL exhibited a significant linear decline over time(β=−4.75,p<0.001).Stress(β=−14.12,p<0.001)and anxiety(β=−11.24,p<0.001)robustly predicted QoL decline,whereas depression showed no significant effect.Control strategies had divergent associations:goal engagement(β=3.51,p<0.001)and self-protection(β=2.38,p=0.015)predicted higher baseline QoL,while goal disengagement accelerated decline(β=−7.00,p<0.001;interaction with time:β=−2.46,p<0.001).Contrary to hypotheses,control strategies did not moderate emotion-QoL associations(ΔR2=0.02,p=0.21).The results showed that stress and anxiety played an important role in the QoL of the elderly.At the same time,goal engagement and self-protection were beneficial to the QoL of the elderly,while goal disengagement was not conducive to QoL and its development among the elderly.Meanwhile,the negative effect of anxiety and stress on the QoL of the elderly was not affected by the control strategies.
文摘Doline susceptibility mapping(DSM)in karst aquifer is important in terms of estimating the vulnerability of the aquifer to pollutants,estimating the infiltration rate,and infrastructures exposed to the development of dolines.In this research,doline susceptibility map was prepared in Saldaran mountain by generalized linear model(GLM)using 14 affecting parameters extracted from satellite images,digital elevation model,and geology map.Only 8 parameters have been inputted to the model which had correlation with dolines.In this regards,306 dolines were identified by the photogrammetric Unmanned Aerial Vehicles(UAV)method in 600 hectares of Salderan lands and then,these data were divided into the training(70%)and testing(30%)data for modelling.The results of DSM modeling showed that classified probability of doline occurrences in the Saldaran mountain were as follow:16.5%of the area high to very high,72%in the class of low to very low,and 5%in the moderate class.Also,locally,in Saldaran mountain,the Pirghar aquifer has the highest potential for the doline development,followed by Bagh Rostam and Sarab aquifers.Also,the precipitation,digital elevation model,Topographic Position Index,drainage density,slope,TRASP(transformed the circular aspect to a radiation index),Snow-Covered Days and vegetation cover index are of highest importance in the DSM modeling,respectively.Accurate evaluation of the model using the Receiver Operating Characteristics(ROC)curve represents a very good accuracy(AUC=0.953)of the DSM model.
基金Supported by the Hangzhou Joint Fund of the Zhejiang Provincial Natural Science Foundation of Chi-na(LHZY24A010002)the MOE Project of Humanities and Social Sciences(21YJCZH235).
文摘High-dimensional heterogeneous data have acquired increasing attention and discussion in the past decade.In the context of heterogeneity,semiparametric regression emerges as a popular method to model this type of data in statistics.In this paper,we leverage the benefits of expectile regression for computational efficiency and analytical robustness in heterogeneity,and propose a regularized partially linear additive expectile regression model with a nonconvex penalty,such as SCAD or MCP,for high-dimensional heterogeneous data.We focus on a more realistic scenario where the regression error exhibits a heavy-tailed distribution with only finite moments.This scenario challenges the classical sub-gaussian distribution assumption and is more prevalent in practical applications.Under certain regular conditions,we demonstrate that with probability tending to one,the oracle estimator is one of the local minima of the induced optimization problem.Our theoretical analysis suggests that the dimensionality of linear covariates that our estimation procedure can handle is fundamentally limited by the moment condition of the regression error.Computationally,given the nonconvex and nonsmooth nature of the induced optimization problem,we have developed a two-step algorithm.Finally,our method’s effectiveness is demonstrated through its high estimation accuracy and effective model selection,as evidenced by Monte Carlo simulation studies and a real-data application.Furthermore,by taking various expectile weights,our method effectively detects heterogeneity and explores the complete conditional distribution of the response variable,underscoring its utility in analyzing high-dimensional heterogeneous data.
基金funded by the National Natural Science Foundation of China(Grant No.32271872).
文摘Over the past decades,the expansion of natu-ral secondary forests has played a crucial role in offsetting the loss of primary forests and combating climate change.Despite this,there is a gap in our understanding of how tree species’growth and mortality patterns vary with eleva-tion in these secondary forests.In this study,we analyzed data from two censuses(spanning a five-year interval)conducted in both evergreen broadleaved forests(EBF)and temperate coniferous forests(TCF),which have been recovering for half a century,across elevation gradients in a subtropical mountain region,Mount Wuyi,China.The results indicated that the relative growth rate(RGR)of EBF(0.028±0.001 cm·cm^(-1)·a^(-1))and the mortality rate(MR)(20.03%±1.70%)were 27.3%and 16.4%higher,respec-tively,than those of TCF.Interestingly,the trade-off between RGR and MR in EBF weakened as elevation increased,a trend not observed in TCF.Conversely,TCF consistently showed a stronger trade-off between RGR and MR compared to EBF.Generalized linear mixed models revealed that ele-vation influences RGR both directly and indirectly through its interactions with slope,crown competition index(CCI),and tree canopy height(CH).However,tree mortality did not show a significant correlation with elevation.Additionally,DBH significantly influenced both tree growth and mortal-ity,whereas and CH and CCI had opposite effects on tree growth between EBF and TCF.Our study underscores the importance of elevation in shaping the population dynamics and the biomass carbon sink balance of mountain forests.These insights enhance our understanding of tree species’life strategies,enabling more accurate predictions of forest dynamics and their response to environmental changes.
基金The Impact of Digital Economy on Green Development Efficiency.2025 Nanjing University of Science and Technology Zijin College Campus Level Scientific Research Project(Project No.:2025ZXSK0401011)。
文摘Under the background of this era,green finance and the upgrading and optimization of industrial structure have become a hot research topic.The article focuses on Jiangsu Province,carefully explores the impact of green financial development on the upgrading and optimization of industrial structure and the real effect,collates and summarizes the theories of green finance and industrial structure at home and abroad,and carefully analyzes the development of green finance in Jiangsu Province,such as the gradual expansion of green credit scale,the characteristics of industrial structure,the change of the proportion of three industries,the development situation of emerging industries and so on.By means of econometrics,an empirical model covering Green Financial Development Indicators and industrial structure optimization indicators is established to do multiple linear regression analysis and stability test.The empirical results show that the development of green finance in Jiangsu plays an obvious positive role in the optimization and upgrading of industrial structure.Green finance is environmental protection,new energy and other green industries are given important financial support,which drives their scale expansion and technological innovation,and makes the industrial structure develop towards a higher level and a more reasonable direction.From this point of view,corresponding proposals are put forward to improve the policy incentive system,add green financial products,and strengthen the construction of green financial market.The purpose is to give better play to the advantages of green finance,accelerate the optimization and upgrading of industrial structure in Jiangsu,and provide theoretical basis and practical guidance for achieving green economic transformation and sustainable development.
文摘By analyzing the observed phenomena and the data collected in the study, a multi-compartment linear circulation model for targeting drug delivery system was developed and the function formulas of the drug concentration-time in blood and target organ by computing were figured out. The drug concentration-time curve for target organ can be plotted with reference to the data of drug concentration in blood according to the model. The pharmacokinetic parameters of the drug in target organ could also be obtained. The practicability of the model was further checked by the curves of drug concentration-time in blood and target organ(liver) of liver-targeting nanoparticles in animal tests. Based on the liver drug concentration-time curves calculated by the function formula of the drug in target organ, the pharmacokinetic behavior of the drug in target organ(liver) was analyzed by statistical moment, and its pharmacokinetic parameters in liver were obtained. It is suggested that the (relative targeting index( can be used for quantitative evaluation of the targeting drug delivery systems.
基金the Project of the Key Open Laboratory of Atmospheric Detection,China Meteorological Administration(2023KLAS02M)the Second Batch of Science and Technology Project of China Meteorological Administration("Jiebangguashuai"):the Research and Development of Short-term and Near-term Warning Products for Severe Convective Weather in Beijing-Tianjin-Hebei Region(CMAJBGS202307).
文摘Firstly,based on the data of air quality and the meteorological data in Baoding City from 2017 to 2021,the correlations of meteorological elements and pollutants with O_(3)concentration were explored to determine the forecast factors of forecast models.Secondly,the O_(3)-8h concentration in Baoding City in 2021 was predicted based on the constructed models of multiple linear regression(MLR),backward propagation neural network(BPNN),and auto regressive integrated moving average(ARIMA),and the predicted values were compared with the observed values to test their prediction effects.The results show that overall,the MLR,BPNN and ARIMA models were able to forecast the changing trend of O_(3)-8h concentration in Baoding in 2021,but the BPNN model gave better forecast results than the ARIMA and MLR models,especially for the prediction of the high values of O_(3)-8h concentration,and the correlation coefficients between the predicted values and the observed values were all higher than 0.9 during June-September.The mean error(ME),mean absolute error(MAE),and root mean square error(RMSE)of the predicted values and the observed values of daily O_(3)-8h concentration based on the BPNN model were 0.45,19.11 and 24.41μg/m 3,respectively,which were significantly better than those of the MLR and ARIMA models.The prediction effects of the MLR,BPNN and ARIMA models were the best at the pollution level,followed by the excellent level,and it was the worst at the good level.In comparison,the prediction effect of BPNN model was better than that of the MLR and ARIMA models as a whole,especially for the pollution and excellent levels.The TS scores of the BPNN model were all above 66%,and the PC values were above 86%.The BPNN model can forecast the changing trend of O_(3)concentration more accurately,and has a good practical application value,but at the same time,the predicted high values of O_(3)concentration should be appropriately increased according to error characteristics of the model.
基金Fundamental Research Funds for the Central Universities(2024JBZX038)National Natural Science F oundation of China(62076023)。
文摘The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.
