Methodology for local correction of the heights of global geoid models to improve the accuracy of GNSS leveling

At present,one of the methods used to determine the height of points on the Earth’s surface is Global Navigation Satellite System(GNSS)leveling.It is possible to determine the orthometric or normal height by this method only if there is a geoid or quasi-geoid height model available.This paper proposes the methodology for local correction of the heights of high-order global geoid models such as EGM08,EIGEN-6C4,GECO,and XGM2019e_2159.This methodology was tested in different areas of the research field,covering various relief forms.The dependence of the change in corrected height accuracy on the input data was analyzed,and the correction was also conducted for model heights in three tidal systems:"tide free","mean tide",and"zero tide".The results show that the heights of EIGEN-6C4 model can be corrected with an accuracy of up to 1 cm for flat and foothill terrains with the dimensionality of 1°×1°,2°×2°,and 3°×3°.The EGM08 model presents an almost identical result.The EIGEN-6C4 model is best suited for mountainous relief and provides an accuracy of 1.5 cm on the 1°×1°area.The height correction accuracy of GECO and XGM2019e_2159 models is slightly poor,which has fuzziness in terms of numerical fluctuation.

A hybrid CNN-LSTM model for diagnosing rice nutrient levels at the rice panicle initiation stage

Nitrogen(N)and potassium(K)are two key mineral nutrient elements involved in rice growth.Accurate diagnosis of N and K status is very important for the rational application of fertilizers at a specific rice growth stage.Therefore,we propose a hybrid model for diagnosing rice nutrient levels at the early panicle initiation stage(EPIS),which combines a convolutional neural network(CNN)with an attention mechanism and a long short-term memory network(LSTM).The model was validated on a large set of sequential images collected by an unmanned aerial vehicle(UAV)from rice canopies at different growth stages during a two-year experiment.Compared with VGG16,AlexNet,GoogleNet,DenseNet,and inceptionV3,ResNet101 combined with LSTM obtained the highest average accuracy of 83.81%on the dataset of Huanghuazhan(HHZ,an indica cultivar).When tested on the datasets of HHZ and Xiushui 134(XS134,a japonica rice variety)in 2021,the ResNet101-LSTM model enhanced with the squeeze-and-excitation(SE)block achieved the highest accuracies of 85.38 and 88.38%,respectively.Through the cross-dataset method,the average accuracies on the HHZ and XS134 datasets tested in 2022 were 81.25 and 82.50%,respectively,showing a good generalization.Our proposed model works with the dynamic information of different rice growth stages and can efficiently diagnose different rice nutrient status levels at EPIS,which are helpful for making practical decisions regarding rational fertilization treatments at the panicle initiation stage.

Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

Purpose-In order to solve the problem of inaccurate calculation of index weights,subjectivity and uncertainty of index assessment in the risk assessment process,this study aims to propose a scientific and reasonable centralized traffic control(CTC)system risk assessment method.Design/methodologylapproach-First,system-theoretic process analysis(STPA)is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis.Then,to enhance the accuracy of weight calculation,the fuzzy analytical hierarchy process(FAHP),fuzzy decision-making trial and evaluation laboratory(FDEMATEL)and entropy weight method are employed to calculate the subjective weight,relative weight and objective weight of each index.These three types of weights are combined using game theory to obtain the combined weight for each index.To reduce subjectivity and uncertainty in the assessment process,the backward cloud generator method is utilized to obtain the numerical character(NC)of the cloud model for each index.The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system.This cloud model is used to obtain the CTC system's comprehensive risk assessment.The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud.Finally,this process yields the risk assessment results for the CTC system.Findings-The cloud model can handle the subjectivity and fuzziness in the risk assessment process well.The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/value-This study provides a cloud model-based method for risk assessment of CTC systems,which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment,achieving effective risk assessment of CTC systems.It can provide a reference and theoretical basis for risk management of the CTC system.

Noncooperative Model Predictive Game With Markov Jump Graph

In this paper,the distributed stochastic model predictive control(MPC)is proposed for the noncooperative game problem of the discrete-time multi-player systems(MPSs)with the undirected Markov jump graph.To reflect the reality,the state and input constraints have been considered along with the external disturbances.An iterative algorithm is designed such that model predictive noncooperative game could converge to the socalledε-Nash equilibrium in a distributed manner.Sufficient conditions are established to guarantee the convergence of the proposed algorithm.In addition,a set of easy-to-check conditions are provided to ensure the mean-square uniform bounded stability of the underlying MPSs.Finally,a numerical example on a group of spacecrafts is studied to verify the effectiveness of the proposed method.

An integrated MINLP model for multi-party coordination in downstream oil supply chain

Cooperation among enterprises can bring overall and individual performance improvement,and a smooth coordination method is indispensable.However,due to the lack of customized coordination methods,cooperation in the downstream oil supply chain cannot be carried out smoothly.This paper intends to propose a multi-party coordination method to promote cooperation between oil shippers and pipeline operator by optimizing oil transportation,oil substitution and pipeline pricing schemes.An integrated game-theoretic modeling and analysis approach is developed to characterize the operation behaviors of all stakeholders in the downstream oil supply chain.The proposed mixed integer nonlinear programming model constrains supply and demand capacity,transportation routes,oil substitution rules and pipeline freight levels.Logarithm transformation and price discretization are introduced for model linear approximation.Simulation experiments are carried out in the oil distribution system in South China.The results show that compared to the business-as-usual scheme,the new scheme saves transportation cost by 3.48%,increases pipeline turnover by 5.7%,and reduces energy consumption and emissions by 7.66%and 6.77%.It is proved that the proposed method improves the revenue of the whole system,achieves fair revenue distribution,and also improves the energy and environmental benefits of the oil supply chain.

Regional Climate Damage Quantification and Its Impacts on Future Emission Pathways Using the RICE Model

This study quantified the regional damages resulting from temperature and sea level changes using the Regional Integrated of Climate and Economy(RICE)model,as well as the effects of enabling and disabling the climate impact module on future emission pathways.Results highlight varied damages depending on regional economic development and locations.Specifically,China and Africa could suffer the most serious comprehensive damages caused by temperature change and sea level rise,followed by India,other developing Asian countries(OthAsia),and other high-income countries(OHI).The comprehensive damage fractions for China and Africa are projected to be 15.1%and 12.5%of gross domestic product(GDP)in 2195,with corresponding cumulative damages of 124.0 trillion and 87.3 trillion United States dollars(USD)from 2005 to 2195,respectively.Meanwhile,the comprehensive damage fractions in Japan,Eurasia,and Russia are smaller and projected to be lower than 5.6%of GDP in 2195,with cumulative damages of 6.8 trillion,4.2 trillion,and 3.3 trillion USD,respectively.Additionally,coastal regions like Africa,the European Union(EU),and OHI show comparable damages for sea level rise and temperature change.In China,however,sea level-induced damages are projected to exceed those from temperature changes.Moreover,this study indicates that switching the damage modules on or off affects the regional and global emission trajectories,but the magnitude is relatively small.By 2195,global emissions under the experiments with all of the damage modules switched off,only the sea level damage module switched on,and only the temperature damage module switched on,were 3.5%,2.3%and 1.2%higher than those with all of the damage modules switched on,respectively.

Research on the Digital Economy's Impact on China's Economic Growth:Based on the Variations in Urbanization Levels Across China's Eastern,Central,and Western Regions and Sectoral Heterogeneity

This paper uses inter-provincial panel data from 2011 to 2017,a linear regression model,and a threshold model to conduct empirical analyses of the impact of the digital economy on China's overall economic growth and the three main sectors of industry.The paper then investigates the impact and effects the digital economy has had on the economic growth of the three main sectors of industry in China's eastern,central,and western regions.Finally,the paper investigates the most significant differences among the various regions and the threshold effects of urbanization levels on the relationship between the digital economy and economic growth.The findings indicate a significantly positive correlation between the digital economy and regional economic growth.Moreover,geographical factors notably influence this correlation.The digital economy exerts a positive effect on all sectors of industry.It may not substantially impact industrial development in regions with highly developed infrastructure.Regarding the other regions,the digital economy exhibits varying degrees of impact due to the differences in the specific indicators.The conclusion drawn by the threshold model is that the magnitude of the threshold effect correlates with geographic factors.No threshold effect was observed in the eastern region,while the threshold effect occurred in the central region when the urbanization levels for the provinces were below 0.6645.Similarly,the threshold effect was noted in the western region when the urbanization level was below 0.3931.Considering all of this,the study also offers policy recommendations that will help balance the regional development of digital economies,accelerate the digital transformation of traditional industries,enhance digital infrastructure construction,refine the formulation and implementation of data policy,and establish relevant incentive mechanisms.

Can a global mean sea-level rise reduce the Last Interglacial model-data mismatch in East Asia?

末次间冰期有着丰富的重建和模拟资料,为研究未来温暖气候提供了一个理想的参考.然而,关于末次间冰期的东亚气候,模拟与重建的结果间长期存在着不匹配的情况,模拟结果普遍较重建结果更为冷干。本研究利用挪威地球系统模式(NorESM1-F),探讨了在末次间冰期模拟试验中纳入全球平均海平面上升能否减少模式-数据的不匹配.该试验结果表明,海平面上升情况下东亚地区会产生一定的增温增湿效应,但不足以消除模式-数据不匹配.基于这些结果,作者探讨了其它可能造成不匹配的因素以供进一步研究.

Performance of CMIP6 models in simulating the dynamic sea level:Mean and interannual variance

本研究采用卫星测高数据与第六次国际耦合模式比较计划(CMIP6)海平面动力进行对比,重点针对40S-40N地区的动力海平面(DSL),评估了模式对其平均态与年际变率的综合模拟能力,结果表明,对于DSL平均态的模拟,模式与观测结果非常吻合,模式之间的差异较小.其中,副热带北大西洋是模拟偏差和模式间差异较为显著的区域,对于DSL年际变率的模拟,模式之间保持较高的一致性,但是,模式与观测结果存在明显差异,模式普遍低估了DSL的年际方差;其中,误差大值区域出现在副热带西边界流附近,模式分辨率会影响CMIP6对中小尺度海洋过程的重现能力,这可能是导致CMIP6历史模拟出现误差的原因之一.

Parental Psychological Control and Internet Gaming Disorder Tendency:A Moderated Mediation Model of Core Self-Evaluation and Intentional Self-Regulation

Internet gaming disorder(IGD)among junior high school students is an increasingly prominent mental health concern.It is important to look for influences behind internet gaming disorder tendency(IGDT)in the junior high school student population.The present study aimed to reveal the explanatory mechanisms underlying the association between parental psychological control(PPC)and internet gaming disorder tendency among junior high school students by testing the mediating role of core self-evaluation(CSE)and the moderating role of intentional self-regulation(ISR).Participants in present study were 735 Chinese junior high school students who completed offline self-report questionnaires on parental psychological control,core self-evaluation,intentional self-regulation,and Internet gaming disorder tendency.Analyses were conducted via mediation and moderated mediation.The results showed that:(1)Parental psychological control was positively related to junior high school students’Internet gaming disorder tendency.Core self-evaluation,and intentional self-regulation were negatively related to junior high school students’Internet gaming disorder tendency,respectively.(2)Core self-evaluation partially mediated the relationship between parental psychological control and junior high school students’Internet gaming disorder tendency.(3)Intentional self-regulation moderated the association between parental psychological control and Internet gaming disorder tendency,as well as the relationships between parental psychological control and core self-evaluation and core self-evaluation and Internet gaming disorder tendency in the mediated model.Based on these findings,we believe that there is a need to weaken parental psychological control,strengthen junior high school students’core self-evaluation and intentional self-regulation,and to recognize the important role of parents as well as their children’s personal positive traits in the healthy development of junior high school students.

Change in self-image pressure level before and after autologous fat breast augmentation and its effect on social adaptability

BACKGROUND There is an increasingly strong demand for appearance and physical beauty in social life,marriage,and other aspects with the development of society and the improvement of material living standards.An increasing number of people have improved their appearance and physical shape through aesthetic plastic surgery.The female breast plays a significant role in physical beauty,and droopy or atrophied breasts can frequently lead to psychological inferiority and lack of confidence in women.This,in turn,can affect their mental health and quality of life.AIM To analyze preoperative and postoperative self-image pressure-level changes of autologous fat breast augmentation patients and their impact on social adaptability.METHODS We selected 160 patients who underwent autologous fat breast augmentation at the First Affiliated Hospital of Xinxiang Medical University from January 2020 to December 2022 using random sampling method.The general information,selfimage pressure level,and social adaptability of the patients were investigated using a basic information survey,body image self-assessment scale,and social adaptability scale.The self-image pressure-level changes and their effects on the social adaptability of patients before and after autologous fat breast augmentation were analyzed.RESULTS We collected 142 valid questionnaires.The single-factor analysis results showed no statistically significant difference in the self-image pressure level and social adaptability score of patients with different ages,marital status,and monthly income.However,there were significant differences in social adaptability among patients with different education levels and employment statuses.The correlation analysis results revealed a significant correlation between the self-image pressure level and social adaptability score before and after surgery.Multiple factors analysis results showed that the degree of concern caused by appearance in selfimage pressure,the degree of possible behavioral intervention,the related distress caused by body image,and the influence of body image on social life influenced the social adaptability of autologous fat breast augmentation patients.CONCLUSION The self-image pressure on autologous fat breast augmentation patients is inversely proportional to their social adaptability.

Spatio-temporal variation of depth to groundwater level and its driving factors in arid and semi-arid regions of India

Climate change and increasing anthropogenic activities,such as over-exploitation of groundwater,are exerting unavoidable stress on groundwater resources.This study investigated the spatio-temporal variation of depth to groundwater level(DGWL)and the impacts of climatic(precipitation,maximum temperature,and minimum temperature)and anthropogenic(gross district product(GDP),population,and net irrigated area(NIA))variables on DGWL during 1994-2020.The study considered DGWL in 113 observation wells and piezometers located in arid western plains(Barmer and Jodhpur districts)and semi-arid eastern plains(Jaipur,Ajmer,Dausa,and Tonk districts)of Rajasthan State,India.Statistical methods were employed to examine the annual and seasonal patterns of DGWL,and the generalized additive model(GAM)was used to determine the impacts of climatic and anthropogenic variables on DGWL.During 1994-2020,except for Barmer District,where the mean annual DGWL was almost constant(around 26.50 m),all other districts exhibited increase in DGWL,with Ajmer District experiencing the most increase.The results also revealed that 36 observation wells and piezometers showed a statistically significant annual increasing trend in DGWL and 34 observation wells and piezometers exhibited a statistically significant decreasing trend in DGWL.Similarly,32 observation wells and piezometers showed an statistically significant increasing trend and 37 observation wells and piezometers showed a statistically significant decreasing trend in winter;33 observation wells and piezometers indicated a statistically significant increasing trend and 34 had a statistically significant decreasing trend in post-monsoon;35 observation wells and piezometers exhibited a statistically significant increasing trend and 32 observation wells and piezometers showed a statistically significant decreasing trend in pre-monsoon;and 36 observation wells and piezometers reflected a statistically significant increasing trend and 30 observation wells and piezometers reflected a statistically significant decreasing trend in monsoon.Interestingly,most of the observation wells and piezometers with increasing trends of DGWL were located in Dausa and Jaipur districts.Furthermore,the GAM analysis revealed that climatic variables,such as precipitation,significantly affected DGWL in Barmer District,and DGWL in all other districts was influenced by anthropogenic variables,including GDP,NIA,and population.As a result,stringent regulations should be implemented to curb excessive groundwater extraction,manage agricultural water demand,initiate proactive aquifer recharge programs,and strengthen sustainable management in these water-scarce regions.

Sea level rise projection in the South China Sea from CMIP5 models

Future potential sea level change in the South China Sea （SCS） is estimated by using 24 CMIP5 models under different representative concentration pathway （RCP） scenarios. By the end of the 21st century （2081–2100 relative to 1986–2005）, the multimodel ensemble mean dynamic sea level （DSL） is projected to rise 0.9, 1.6, and 1.1 cm under RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, resulting in a total sea level rise （SLR） of 40.9, 48.6, and 64.1 cm in the SCS. It indicates that the SCS will experience a substantial SLR over the 21st century, and the rise is only marginal larger than the global mean SLR. During the same period, the steric sea level （SSL） rise is estimated to be 6.7, 10.0, and 15.3 cm under the three scenarios, respectively, which accounts only for 16%, 21% and 24% of the total SLR in this region. The changes of the SSL in the SCS are almost out of phase with those of the DSL for the three scenarios. The central deep basin has a slightly weak DSL rise, but a strong SSL rise during the 21st century, compared with the north and southwest shelves.

Greenland Ice Sheet Contribution to Future Global Sea Level Rise based on CMIP5 Models

Sea level rise （SLR） is one of the major socioeconomic risks associated with global warming. Mass losses from the Greenland ice sheet （GrIS） will be partially responsible for future SLR, although there are large uncertainties in modeled climate and ice sheet behavior. We used the ice sheet model SICOPOLIS （Simulation COde for POLythermal Ice Sheets） driven by climate projections from 20 models in the fifth phase of the Coupled Model Intercomparison Project （CMIP5） to estimate the GrlS contribution to global SLR. Based on the outputs of the 20 models, it is estimated that the GrIS will contribute 0-16 （0-27） cm to global SLR by 2100 under the Representative Concentration Pathways （RCP） 4.5 （RCP 8.5） scenarios. The projected SLR increases further to 7-22 （7-33） cm with 2~basal sliding included. In response to the results of the multimodel ensemble mean, the ice sheet model projects a global SLR of 3 cm and 7 cm （10 cm and 13 cm with 2~basal sliding） under the RCP 4.5 and RCP 8.5 scenarios, respectively. In addition, our results suggest that the uncertainty in future sea level projection caused by the large spread in climate projections could be reduced with model-evaluation and the selective use of model outputs.

Modelling of a Human Driver’s Interaction with Vehicle Automated Steering Using Cooperative Game Theory

The introduction of automated driving systems raised questions about how the human driver interacts with the automated system. Non-cooperative game theory is increasingly used for modelling and understanding such interaction, while its counterpart, cooperative game theory is rarely discussed for similar applications despite it may be potentially more suitable. This paper describes the modelling of a human driver’s steering interaction with an automated steering system using cooperative game theory. The distributed Model Predictive Control approach is adopted to derive the driver’s and the automated steering system’s strategies in a Pareto equilibrium sense, namely their cooperative Pareto steering strategies. Two separate numerical studies are carried out to study the influence of strategy parameters, and the influence of strategy types on the driver’s and the automated system’s steering performance. It is found that when a driver interacts with an automated steering system using a cooperative Pareto steering strategy, the driver can improve his/her performance in following a target path through increasing his/her effort in pursuing his/her own interest under the driver-automation cooperative control goal. It is also found that a driver’s adoption of cooperative Pareto steering strategy leads to a reinforcement in the driver’s steering angle control, compared to the driver’s adoption of non-cooperative Nash strategy. This in turn enables the vehicle to return from a lane-change maneuver to straight-line driving swifter.

New partial cooperation model for bilevel programming problems

Partial cooperation models are studied for many years to solve the bilevel programming problems where the follower’s optimal reaction is not unique. However, in these existed models, the follower’s cooperation level does not depend on the leader’s decision. A new model is proposed to solve this deficiency. It is proved the feasibility of the new model when the reaction set of the lower level is lower semicontinuous. And the numerical results show that the new model has optimal solutions when the reaction set of the lower level is discrete, lower semi-continuous and non-lower semi-continuous.

High level architecture evolved modular federation object model

To improve the agility, dynamics, composability, reusability, and development efficiency restricted by monolithic federation object model （FOM）, a modular FOM is proposed by high level architecture （HLA） evolved product development group. This paper reviews the state-of-the-art of HLA evolved modular FOM. In particular, related concepts, the overall impact on HLA standards, extension principles, and merging processes are discussed. Also permitted and restricted combinations, and merging rules are provided, and the influence on HLA interface specification is given. The comparison between modular FOM and base object model （BOM） is performed to illustrate the importance of their combination. The applications of modular FOM are summarized. Finally, the significance to facilitate compoable simulation both in academia and practice is presented and future directions are pointed out.

Model test of the influence of cyclic water level fluctuations on a landslide

Many landslides in reservoir areas continuously deform under cyclic water level fluctuations due to reservoir operations. In this paper,a landslide model, developed for a typical colluvial landslide in the Three Gorges Reservoir area, is used to study the effect of cyclic water level fluctuations on the landslide. Five cyclic water level fluctuations were implemented in the test, and the fluctuation rate in the last two fluctuations doubled over the first three fluctuations. The pore water pressure and lateral landslide profiles were obtained during the test. A measurement of the landslide soil loss was proposed to quantitatively evaluate the influence of water level fluctuations. The test results show that the first water level rising is most negative to the landslide among the five cycles. The fourth drawdown with a higher drawdown rate caused further large landslide deformation. An increase of the water level drawdown rate is much more unfavorable to the landslide than an increase of the water level rising rate. In addition, the landslide was found to have an adaptive ability to resist subsequent water level fluctuations after undergoing large deformation during a water level fluctuation. The landslide deformation and observations in the field were found to support the test results well.

Incorporation of GIS Based Program into Hydraulic Model for Water Level Modeling on River Basin

Water resources management usually requires that hydraulic, ecological, and hydrological models be linked. The Hy- drologic Engineering Center River Analysis System (HEC-RAS) hydraulic model and the Hydrologic Engineering Center Geospatial River Analysis System (HEC-GEORAS), imitates flow and water profiles in the Neka river basin’s downstream flood plain. Hydrograph phases studied during the flood seasons of 1986-1999 and from 2002-2004 were used to calibrate and verify the hydraulic model respectively. Simulations of peak flood stages and hydrographs’ evaluations are congruent with studies and observations, with the former showing mean square errors between 4.8 - 10 cm. HECRAS calculations and forecast flood water levels. Nash-Sutcliffe effectiveness (CR3) is more than 0.92 along with elevated levels of water which were created with some effectiveness (CR5) of 0.94 for the validation period. The coupled two models show good performance in the water level modeling.

Chaos game representation walk model for the protein sequences

A new chaos game representation of protein sequences based on the detailed hydrophobic-hydrophilic （HP） model has been proposed by Yu et al （Physica A 337（2004） 171）. A CGR-walk model is proposed based on the new CGR coordinates for the protein sequences from complete genomes in the present paper. The new CCR coordinates based on the detailed HP model are converted into a time series, and a long-memory ARFIMA（p, d, q） model is introduced into the protein sequence analysis. This model is applied to simulating real CCR-walk sequence data of twelve protein sequences. Remarkably long-range correlations are uncovered in the data and the results obtained from these models are reasonably consistent with those available from the ARFIMA（p, d, q） model.