Landslide susceptibility prediction using slope unit-based machine learning models considering the heterogeneity of conditioning factors

To perform landslide susceptibility prediction(LSP),it is important to select appropriate mapping unit and landslide-related conditioning factors.The efficient and automatic multi-scale segmentation(MSS)method proposed by the authors promotes the application of slope units.However,LSP modeling based on these slope units has not been performed.Moreover,the heterogeneity of conditioning factors in slope units is neglected,leading to incomplete input variables of LSP modeling.In this study,the slope units extracted by the MSS method are used to construct LSP modeling,and the heterogeneity of conditioning factors is represented by the internal variations of conditioning factors within slope unit using the descriptive statistics features of mean,standard deviation and range.Thus,slope units-based machine learning models considering internal variations of conditioning factors(variant slope-machine learning)are proposed.The Chongyi County is selected as the case study and is divided into 53,055 slope units.Fifteen original slope unit-based conditioning factors are expanded to 38 slope unit-based conditioning factors through considering their internal variations.Random forest(RF)and multi-layer perceptron(MLP)machine learning models are used to construct variant Slope-RF and Slope-MLP models.Meanwhile,the Slope-RF and Slope-MLP models without considering the internal variations of conditioning factors,and conventional grid units-based machine learning(Grid-RF and MLP)models are built for comparisons through the LSP performance assessments.Results show that the variant Slopemachine learning models have higher LSP performances than Slope-machine learning models;LSP results of variant Slope-machine learning models have stronger directivity and practical application than Grid-machine learning models.It is concluded that slope units extracted by MSS method can be appropriate for LSP modeling,and the heterogeneity of conditioning factors within slope units can more comprehensively reflect the relationships between conditioning factors and landslides.The research results have important reference significance for land use and landslide prevention.

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.

MATHEMATICAL MODELING AND BIFURCATION ANALYSIS FOR A BIOLOGICAL MECHANISM OF CANCER DRUG RESISTANCE

Drug resistance is one of the most intractable issues in targeted therapy for cancer diseases.It has also been demonstrated to be related to cancer heterogeneity,which promotes the emergence of treatment-refractory cancer cell populations.Focusing on how cancer cells develop resistance during the encounter with targeted drugs and the immune system,we propose a mathematical model for studying the dynamics of drug resistance in a conjoint heterogeneous tumor-immune setting.We analyze the local geometric properties of the equilibria of the model.Numerical simulations show that the selectively targeted removal of sensitive cancer cells may cause the initially heterogeneous population to become a more resistant population.Moreover,the decline of immune recruitment is a stronger determinant of cancer escape from immune surveillance or targeted therapy than the decay in immune predation strength.Sensitivity analysis of model parameters provides insight into the roles of the immune system combined with targeted therapy in determining treatment outcomes.

Neurophysiological, histological, and behavioral characterization of animal models of distraction spinal cord injury: a systematic review

Distraction spinal cord injury is caused by some degree of distraction or longitudinal tension on the spinal cord and commonly occurs in patients who undergo corrective operation for severe spinal deformity.With the increased degree and duration of distraction,spinal cord injuries become more serious in terms of their neurophysiology,histology,and behavior.Very few studies have been published on the specific characteristics of distraction spinal cord injury.In this study,we systematically review 22 related studies involving animal models of distraction spinal cord injury,focusing particularly on the neurophysiological,histological,and behavioral characteristics of this disease.In addition,we summarize the mechanisms underlying primary and secondary injuries caused by distraction spinal cord injury and clarify the effects of different degrees and durations of distraction on the primary injuries associated with spinal cord injury.We provide new concepts for the establishment of a model of distraction spinal cord injury and related basic research,and provide reference guidelines for the clinical diagnosis and treatment of this disease.

Spatio-temporal Heterogeneity in the Performance of Rural Revitalization in Chifeng City of China:Based on a Range-wide EBM-GML Model

To solve the problems of rural revitalization performance research,a quantitative model of non-oriented range-wide EBM(Epsilon-Based Measure)-GML(Global-Malmquist)based on VRS(Variable Returns to Scale)conditions including non-desired outputs is constructed.A comprehensive spatio-temporal heterogeneity research index system of rural revitalization performance is also constructed.Taking the typical rural in Chifeng City as an example,the panel data from 2016-2020 are selected for empirical analysis,the conclusions and countermeasures are suggested as follows:1)In general,the rural revitalization performance of Chifeng City increases significantly during the five-year period,with significant spatio-temporal heterogeneity.The overall analysis shows that the overall performance value of rural revitalization in Chifeng City is 0.683 from 2016 to 2020.The highest performance value is 1 and the lowest performance value is 0.389.The performance growth rate increases year by year,with an average annual growth rate of 4.46%.2)From 2016 to 2020,the GML index of rural revitalization performance in Chifeng City is 1.174,showing an increasing trend.Based on the range of change of GML index,Chifeng City can be classified into three types:Continuous improvement,fluctuating improvement and fluctuating decline.3)Niujiayingzi,Guandongche,Zhaidamu,and Qiangangtai rural have the highest degree of technological progress.

Time Predictable Modeling Method for GPU Architecture with SIMT and Cache Miss Awareness

Graphics Processing Units(GPUs)are used to accelerate computing-intensive tasks,such as neural networks,data analysis,high-performance computing,etc.In the past decade or so,researchers have done a lot of work on GPU architecture and proposed a variety of theories and methods to study the microarchitectural characteristics of various GPUs.In this study,the GPU serves as a co-processor and works together with the CPU in an embedded real-time system to handle computationally intensive tasks.It models the architecture of the GPU and further considers it based on some excellent work.The SIMT mechanism and Cache-miss situation provide a more detailed analysis of the GPU architecture.In order to verify the GPU architecture model proposed in this article,10 GPU kernel_task and an Nvidia GPU device were used to perform experiments.The experimental results showed that the minimum error between the kernel task execution time predicted by the GPU architecture model proposed in this article and the actual measured kernel task execution time was 3.80%,and the maximum error was 8.30%.

The Time-Consistent Optimal Reinsurance Strategy of Insurance Group under the CEV Model

The article introduces proportional reinsurance contracts under the mean-variance criterion,studying the time-consistence investment portfolio problem considering the interests of both insurance companies and reinsurance companies.The insurance claims process follows a jump-diffusion model,assuming that the risk asset prices of insurance companies and reinsurance companies follow CEV models different from each other.In the framework of game theory,the time-consistent equilibrium reinsurance strategy is obtained by solving the extended HJB equation analytically.Finally,numerical examples are used to illustrate the impact of model parameters on equilibrium strategies and provide economic explanations.The results indicate that the decision weights of insurance companies and reinsurance companies do have a significant impact on both the reinsurance ratio and the equilibrium reinsurance strategy.

Seismic attenuation relationship with homogeneous and heterogeneous prediction-error variance models

Peak ground acceleration(PGA) estimation is an important task in earthquake engineering practice.One of the most well-known models is the Boore-Joyner-Fumal formula,which estimates the PGA using the moment magnitude,the site-to-fault distance and the site foundation properties.In the present study,the complexity for this formula and the homogeneity assumption for the prediction-error variance are investigated and an effi ciency-robustness balanced formula is proposed.For this purpose,a reduced-order Monte Carlo simulation algorithm for Bayesian model class selection is presented to obtain the most suitable predictive formula and prediction-error model for the seismic attenuation relationship.In this approach,each model class(a predictive formula with a prediction-error model) is evaluated according to its plausibility given the data.The one with the highest plausibility is robust since it possesses the optimal balance between the data fi tting capability and the sensitivity to noise.A database of strong ground motion records in the Tangshan region of China is obtained from the China Earthquake Data Center for the analysis.The optimal predictive formula is proposed based on this database.It is shown that the proposed formula with heterogeneous prediction-error variance is much simpler than the attenuation model suggested by Boore,Joyner and Fumal(1993).

A Numerical Study on Effects of Land-Surface Heterogeneity from' Combined Approach' on Atmospheric ProcessPart II: Coupling-Model Simulations

Two land surface schemes, one the standard Biosphere / Atmosphere Transfer Scheme Version ie (BOZ) and the other B1Z based on B0Z and heterogeneously-treated by' combined approach' , were co 'pled to the meso-scale model MM4, respectively. Through the calculations of equations from the companion paper, parameters representing land surface heterogeneity and suitable for the coupling models were found out. Three cases were simulated for heavy rainfalls during 36 hours, and the sensitivity of short-term weather modeling to the land surface heterogeneity was tested. Through the analysis of the simulations of the three heavy rainfalls, it was demonstrated that BIZ, compared with BOZ, could more realistically reflect the features of the land surface heterogeneity, therefore could more realistically reproduce the circulation and precipitation amount in the heavy rainfall processes of the three cases. This shows that even short-term weather is sensitive to the land surface heterogeneity, which is more obvious with time passing, and whose influence is more pronounced in the lower layer and gradually extends to the middle and upper layer. Through the analysis of these simulations with BlZ, it is suggested that the bulk effect of smaller-scale fluxes (i.e., the momentum, water vapor and sensible heat fluxes) near the s ig nificantly-heterogeneous land surface is to change the larger-scale (i.e., meso-scale) circulation, and then to influence the development of the low-level jets and precipitation. And also, the complexity of the land-atmosphere interaction was shown in these simulations.

Influence of heterogeneity on rock strength and stiffness using discrete element method and parallel bond model

The particulate discrete element method(DEM) can be employed to capture the response of rock,provided that appropriate bonding models are used to cement the particles to each other.Simulations of laboratory tests are important to establish the extent to which those models can capture realistic rock behaviors.Hitherto the focus in such comparison studies has either been on homogeneous specimens or use of two-dimensional(2D) models.In situ rock formations are often heterogeneous,thus exploring the ability of this type of models to capture heterogeneous material behavior is important to facilitate their use in design analysis.In situ stress states are basically three-dimensional(3D),and therefore it is important to develop 3D models for this purpose.This paper revisits an earlier experimental study on heterogeneous specimens,of which the relative proportions of weaker material(siltstone) and stronger,harder material(sandstone) were varied in a controlled manner.Using a 3D DEM model with the parallel bond model,virtual heterogeneous specimens were created.The overall responses in terms of variations in strength and stiffness with different percentages of weaker material(siltstone) were shown to agree with the experimental observations.There was also a good qualitative agreement in the failure patterns observed in the experiments and the simulations,suggesting that the DEM data enabled analysis of the initiation of localizations and micro fractures in the specimens.

EMPIRICAL BAYES TEST PROBLEMS OF VARIANCE COMPONENTS IN RANDOM EFFECTS MODEL

Bayes decision rule of variance components for one-way random effects model is derived and empirical Bayes (EB) decision rules are constructed by kernel estimation method. Under suitable conditions, it is shown that the proposed EB decision rules are asymptotically optimal with convergence rates near O(n-1/2). Finally, an example concerning the main result is given.

A discrete-event model to simulate the effect of truck bunching due to payload variance on cycle time, hauled mine materials and fuel consumption

Data collected from truck payload management systems at various surface mines shows that the payload variance is significant and must be considered in analysing the mine productivity,energy consumption,greenhouse gas emissions and associated cost.Payload variance causes significant differences in gross vehicle weights.Heavily loaded trucks travel slower up ramps than lightly loaded trucks.Faster trucks are slowed by the presence of slower trucks,resulting in‘bunching’,production losses and increasing fuel consumptions.This paper simulates the truck bunching phenomena in large surface mines to improve truck and shovel systems’efficiency and minimise fuel consumption.The study concentrated on completing a practical simulation model based on a discrete event method which is most commonly used in this field of research in other industries.The simulation model has been validated by a dataset collected from a large surface mine in Arizona state,USA.The results have shown that there is a good agreement between the actual and estimated values of investigated parameters.

Influence of formation heterogeneity on foam flooding performance using 2D and 3D models:an experimental study

The formation heterogeneity is considered as one of the major factors limiting the application of foam flooding.In this paper,influences of formation properties,such as permeability,permeability distribution,interlayer,sedimentary rhythm and 3D heterogeneity,on the mobility control capability and oil displacement efficiency of foam flooding,were systematically investigated using 2D homogeneous and 2D/3D heterogeneous models under 120°C and salinity of 20×10~4 mg/L.The flow resistance of foam was promoted as the permeability increased,which thus resulted in a considerable oil recovery behavior.In the scenario of the vertical heterogeneous formations,it was observed that the permeability of the high-permeable layer was crucial to foam mobility control,and the positive rhythm appeared favorable to improve the foam flooding performance.The additional oil recovery increased to about 40%.The interlayer was favorable for the increases in mobility reduction factor and oil recovery of foam flooding when the low permeability ratio was involved.For the 3D heterogeneous formations,foam could efficiently adjust the areal and vertical heterogeneity through mobility control and gravity segregation,and thus enhancing the oil recovery to 11%–14%.The results derived from this work may provide some insight for the field test designs of foam flooding.

Regional Economic Efficiency and Its Influencing Factors of Beijing-Tianjin-Hebei Metropolitans in China Based on a Heterogeneity Stochastic Frontier Model

Using a heterogeneity stochastic frontier model(HSFM),we empirically investigated the economic efficiency of Beijing-Tianjin-Hebei from 2003 to 2016 and its influencing factors.The key findings of the paper lie in:1)in Beijing-Tianjin-Hebei,the overall economic and technological efficiency tended to increase in a wavelike manner,economic growth slowed down,and there was an obvious imbalance in economic efficiency between the different districts,counties and cities;2)the heterogeneity stochastic frontier production functions(SFPFs)of Beijing,Tianjin and Hebei were different from each other,and investment was still an important impetus of economic growth in Beijing-Tianjin-Hebei;3)economic efficiency was positively correlated with economic agglomeration,human capital,industrial structure,infrastructure,the informatization level,and institutional factors,but negatively correlated with the government role and economic opening.The following policy suggestions are offered:1)to improve regional economic efficiency and reduce the economic gap in Beijing-Tianjin-Hebei,governments must reduce their intervention in economic activities,stimulate the potentials of labor and capital,optimize the structure of human resources,and foster new demographic incentives;2)governments must guide economic factors that are reasonable throughout Beijing-Tianjin-Hebei and strengthen infrastructure construction in underdeveloped regions,thus attaining sustainable economic development;3)governments must plan overall economic growth factors of Beijing-Tianjin-Hebei and promote reasonable economic factors(e.g.,labor,resources,and innovations)across different regions,thus attaining complementary advantages between Beijing,Tianjin,and Hebei.

Nonlinear total least-squares variance component estimation for GM(1,1)model

The solution of the grey model(GM(1,1)model)generally involves equal-precision observations,and the(co)variance matrix is established from the prior information.However,the data are generally available with unequal-precision measurements in reality.To deal with the errors of all observations for GM(1,1)model with errors-in-variables(EIV)structure,we exploit the total least-squares(TLS)algorithm to estimate the parameters of GM(1,1)model in this paper.Ignoring that the effect of the improper prior stochastic model and the homologous observations may degrade the accuracy of parameter estimation,we further present a nonlinear total least-squares variance component estimation approach for GM(1,1)model,which resorts to the minimum norm quadratic unbiased estimation(MINQUE).The practical and simulative experiments indicate that the presented approach has significant merits in improving the predictive accuracy in comparison with control methods.

Quantifying the impact of mineralogical heterogeneity on reactive transport modeling of CO_(2)+O_(2) in-situ leaching of uranium

CO_(2)+O_(2) in-situ leaching(ISL)of sandstonetype uranium ore represents the third generation of solution mining in China.In this study,reactive transport modeling of the interaction between hydrodynamic and geochemical reactions is performed to enable better prediction and regulation of the CO_(2)+O_(2) in-situ leaching process of uranium.Geochemical reactions between mining solutions and rock,and the kinetic uranium dissolution controlled by O_(2)(aq)and bicarbonate(HCO_(3)-)are considered in the CO_(2)+O_(2) ISL reactive transport model of a typical sandstone-hosted uranium ore deposit in northern China.The reactive leaching of uranium is most sensitive to the spatial distribution of the mineralogical properties of the uranium deposit.Stochastic geostatistical models are used to represent the uncertainty on the spatial distribution of mineral grades.A Monte Carlo analysis was also performed to simulate the uranium production variability over an entire set of geostatistical realizations.The ISL stochastic simulation performed with the selected geostatistical realizations approximates the uranium production variability well.The simulation results of the ISL reactive transport model show that the extent of the uranium plume is highly dependent on mineralogical heterogeneity.The uncertainty analysis suggests the effect of uranium grade heterogeneity was found to be important to improve the accurate capture of the uncertainty.This study provides guidance for the accurate simulation and dynamic regulation of the CO_(2)+O_(2) leaching process of uranium at the scale of large mining areas.

A Mean-variance Problem in the Constant Elasticity of Variance(CEV) Model

In this paper, we focus on a constant elasticity of variance （CEV） modeland want to find its optimal strategies for a mean-variance problem under two constrainedcontrols： reinsurance/new business and investment （no-shorting）. First, aLagrange multiplier is introduced to simplify the mean-variance problem and thecorresponding Hamilton-Jacobi-Bellman （HJB） equation is established. Via a powertransformation technique and variable change method, the optimal strategies withthe Lagrange multiplier are obtained. Final, based on the Lagrange duality theorem,the optimal strategies and optimal value for the original problem （i.e., the efficientstrategies and efficient frontier） are derived explicitly.

COMPLETE CONVERGENCE OF ERROR VARIANCE ESITIMATES UNDER Ф－MIXING ERROR IN LINEAR MODELS

In this paper,we consider the estimates d of error variance d2=Var(ei) in the linear models Yi=x' iβ+ei(i= 1, 2, ... ). We study the complete convergence of dm2-o2 when the error {ei }is a sequence of identically distributed p-mixing variables. And we also obtain the better convergence rates when {ei} is not identically distribution

Heteroscedasticity check in nonlinear semiparametric models based on nonparametric variance function

The assumption of homoscedasticity has received much attention in classical analysis of regression. Heteroscedasticity tests have been well studied in parametric and nonparametric regressions. The aim of this paper is to present a test of heteroscedasticity for nonlinear semiparametric regression models with nonparametric variance function. The validity of the proposed test is illustrated by two simulated examples and a real data example.

Variance Estimation for High-Dimensional Varying Index Coefficient Models

This paper studies the re-adjusted cross-validation method and a semiparametric regression model called the varying index coefficient model. We use the profile spline modal estimator method to estimate the coefficients of the parameter part of the Varying Index Coefficient Model (VICM), while the unknown function part uses the B-spline to expand. Moreover, we combine the above two estimation methods under the assumption of high-dimensional data. The results of data simulation and empirical analysis show that for the varying index coefficient model, the re-adjusted cross-validation method is better in terms of accuracy and stability than traditional methods based on ordinary least squares.