Sudden and unforeseen seismic failures of coal mine overburden(OB)dump slopes interrupt mining operations,cause loss of lives and delay the production of coal.Consideration of the spatial heterogeneity of OB dump mate...Sudden and unforeseen seismic failures of coal mine overburden(OB)dump slopes interrupt mining operations,cause loss of lives and delay the production of coal.Consideration of the spatial heterogeneity of OB dump materials is imperative for an adequate evaluation of the seismic stability of OB dump slopes.In this study,pseudo-static seismic stability analyses are carried out for an OB dump slope by considering the material parameters obtained from an insitu field investigation.Spatial heterogeneity is simulated through use of the random finite element method(RFEM)and the random limit equilibrium method(RLEM)and a comparative study is presented.Combinations of horizontal and vertical spatial correlation lengths were considered for simulating isotropic and anisotropic random fields within the OB dump slope.Seismic performances of the slope have been reported through the probability of failure and reliability index.It was observed that the RLEM approach overestimates failure probability(P_(f))by considering seismic stability with spatial heterogeneity.The P_(f)was observed to increase with an increase in the coefficient of variation of friction angle of the dump materials.Further,it was inferred that the RLEM approach may not be adequately applicable for assessing the seismic stability of an OB dump slope for a horizontal seismic coefficient that is more than or equal to 0.1.展开更多
This paper takes global manufacturing listed companies from 2010 to 2022 as samples and uses the difference-in-differences(DID)method to empirically examine the impact of the internationalization of ESG standards on t...This paper takes global manufacturing listed companies from 2010 to 2022 as samples and uses the difference-in-differences(DID)method to empirically examine the impact of the internationalization of ESG standards on the trade competitiveness of multinational enterprises and their mechanisms.The research finds that the internationalization of ESG standards significantly enhances the trade competitiveness of multinational manufacturing enterprises,and this effect is dynamic and sustainable.The mechanism analysis indicates that the internationalization of ESG standards exerts its influence through three pathways:reducing enterprise financing costs,promoting technological innovation,and enhancing brand reputation.The heterogeneity analysis shows that this effect is more significant in enterprises from developed countries,high-pollution industries,and larger enterprises.This paper provides micro-level evidence for understanding the economic consequences of the internationalization of ESG standards and offers policy implications for multinational enterprises to cope with the global ESG rule changes and enhance their trade competitiveness.展开更多
The mathematical method of ZTD(zenith tropospheric delay)spatial prediction is important for precise ZTD derivation and real-time precise point positioning(PPP)augmentation.This paper analyses the performance of the p...The mathematical method of ZTD(zenith tropospheric delay)spatial prediction is important for precise ZTD derivation and real-time precise point positioning(PPP)augmentation.This paper analyses the performance of the popular optimal function coefficient(OFC),sphere cap harmonic analysis(SCHA),kriging and inverse distance weighting(IDW)interpolation in ZTD spatial prediction and Beidou satellite navigation system(BDS)-PPP augmentation over China.For ZTD spatial prediction,the average time consumption of the OFC,kriging,and IDW methods is less than 0.1 s,which is significantly better than that of the SCHA method(63.157 s).The overall ZTD precision of the OFC is 3.44 cm,which outperforms those of the SCHA(9.65 cm),Kriging(10.6 cm),and IDW(11.8 cm)methods.We confirmed that the low performance of kriging and IDW is caused by their weakness in modelling ZTD variation in the vertical direction.To mitigate such deficiencies,an elevation normalization factor(ENF)is introduced into the kriging and IDW models(kriging-ENF and IDW-ENF).The overall ZTD spatial prediction accuracies of IDW-ENF and kriging-ENF are 2.80 cm and 2.01 cm,respectively,which are both superior to those of the OFC and the widely used empirical model GPT3(4.92 cm).For BDS-PPP enhancement,the ZTD provided by the kriging-ENF,IDW-ENF and OFC as prior constraints can effectively reduce the convergence time.Compared with unconstrained BDS-PPP,our proposed kriging-ENF outperforms IDW-ENF and OFC by reducing the horizontal and vertical convergence times by approximately 13.2%and 5.8%in Ningxia and 30.4%and 7.84%in Guangdong,respectively.These results indicate that kriging-ENF is a promising method for ZTD spatial prediction and BDS-PPP enhancement over China.展开更多
The precision and reliability of first-arrival picking are crucial for determining the accuracy of geological structure inversion using active source ocean bottom seismometer(OBS)refraction data.Traditional methods fo...The precision and reliability of first-arrival picking are crucial for determining the accuracy of geological structure inversion using active source ocean bottom seismometer(OBS)refraction data.Traditional methods for first-arrival picking based on sample points are characterized by theoretical errors,especially in low-sampling-frequency OBS data because the travel time of seismic waves is not an integer multiple of the sampling interval.In this paper,a first-arrival picking method that utilizes the spatial waveform variation characteristics of active source OBS data is presented.First,the distribution law of theoretical error is examined;adjacent traces exhibit variation characteristics in their waveforms.Second,a label cross-correlation superposition method for extracting highfrequency signals is presented to enhance the first-arrival picking precision.Results from synthetic and field data verify that the proposed approach is robust,successfully overcomes the limitations of low sampling frequency,and achieves precise outcomes that are comparable with those of high-sampling-frequency data.展开更多
Although the classical spectral representation method(SRM)has been widely used in the generation of spatially varying ground motions,there are still challenges in efficient simulation of the non-stationary stochastic ...Although the classical spectral representation method(SRM)has been widely used in the generation of spatially varying ground motions,there are still challenges in efficient simulation of the non-stationary stochastic vector process in practice.The first problem is the inherent limitation and inflexibility of the deterministic time/frequency modulation function.Another difficulty is the estimation of evolutionary power spectral density(EPSD)with quite a few samples.To tackle these problems,the wavelet packet transform(WPT)algorithm is utilized to build a time-varying spectrum of seed recording which describes the energy distribution in the time-frequency domain.The time-varying spectrum is proven to preserve the time and frequency marginal property as theoretical EPSD will do for the stationary process.For the simulation of spatially varying ground motions,the auto-EPSD for all locations is directly estimated using the time-varying spectrum of seed recording rather than matching predefined EPSD models.Then the constructed spectral matrix is incorporated in SRM to simulate spatially varying non-stationary ground motions using efficient Cholesky decomposition techniques.In addition to a good match with the target coherency model,two numerical examples indicate that the generated time histories retain the physical properties of the prescribed seed recording,including waveform,temporal/spectral non-stationarity,normalized energy buildup,and significant duration.展开更多
It is of crucial importance to investigate the spatial structures of ancient landslides in the eastern Tibetan Plateau’s alpine canyons as they could provide valuable insights into the evolutionary history of the lan...It is of crucial importance to investigate the spatial structures of ancient landslides in the eastern Tibetan Plateau’s alpine canyons as they could provide valuable insights into the evolutionary history of the landslides and indicate the potential for future reactivation.This study examines the Deda ancient landslide,situated in the Chalong-ranbu fault zone,where creep deformation suggests a complex underground structure.By integrating remote sensing,field surveys,Audio-frequency Magnetotellurics(AMT),and Microtremor Survey Method(MSM)techniques,along with engineering geological drilling for validation,to uncover the landslide’s spatial feature s.The research indicates that a fault is developed in the upper part of the Deda ancient landslide,and the gully divides it into Deda landslide accumulation zoneⅠand Deda landslide accumulation zoneⅡin space.The distinctive geological characteristics detectable by MSM in the shallow subsurface and by AMT in deeper layers.The findings include the identification of two sliding zones in the Deda I landslide,the shallow sliding zone(DD-I-S1)depth is approximately 20 m,and the deep sliding zone(DD-I-S2)depth is 36.2-49.9 m.The sliding zone(DD-Ⅱ-S1)depth of the DedaⅡlandslide is 37.6-43.1 m.A novel MSM-based method for sliding zone identification is proposed,achieving less than 5%discrepancy in depth determination when compared with drilling data.These results provide a valuable reference for the spatial structural analysis of large-deepseated landslides in geologically complex regions like the eastern Tibetan Plateau.展开更多
Estimating fracture size is a fundamental aspect of rock engineering.However,determining the most probable diameter(MPD)from a fracture's surface trace remains challenging in the scientific community.The prevailin...Estimating fracture size is a fundamental aspect of rock engineering.However,determining the most probable diameter(MPD)from a fracture's surface trace remains challenging in the scientific community.The prevailing methodologies typically infer statistical distributions of fracture sizes rather than specific values.This research presents a novel approach to inferring the MPD and the true spatial distribution pattern of each fracture.The challenge lies in linking the inference process with the trace length of each fracture and the statistical characteristics of the entire outcrop.Additionally,it is necessary to address the non-unique inverse problem.The methodology comprises several key steps.Firstly,the issue of censoring bias is addressed by considering the lengths of the traces contained.Secondly,the orientation bias is corrected using the vector method,and the true mean trace length and standard deviation are estimated and derived.Thirdly,assuming a lognormal distribution for fracture sizes,the mean and standard deviation of diameters are derived through a high-order moment relationship between trace lengths and diameters,validated by Crofton's theorem.Finally,the MPDs of all trace samples are determined by relating MPDs to trace lengths and the standard deviation of diameters using stereology techniques.Furthermore,the true fracture spatial patterns are inverted based on spatial geometric relationships.The proposed methodology is validated through rigorous Monte Carlo simulation and applied in a practical engineering case study,demonstrating its potential for use in rock engineering applications.展开更多
Current research on rail vehicle system vibrations primarily relies on numerical methods,with vibration transfer functions commonly derived through data fitting.However,the physical mechanisms underlying these vibrati...Current research on rail vehicle system vibrations primarily relies on numerical methods,with vibration transfer functions commonly derived through data fitting.However,the physical mechanisms underlying these vibrations are not well understood.To clarify the vibration transfer function and its characteristics,four basic input vectors are defined,and an analytical method is proposed.The vibration transfer functions of the vehicle system are solved,and their spatial coherence is analyzed.The results show that there are two spatial scales and four coherent modes in the vehicle system.The track irregularity wavelengths are combined with two spatial scales to alter the proportions of basic input vectors and then show the characteristics of spatial coherence.Four coherent modes are involved in wheel-rail force and primary suspension force;two coherent modes are involved in bogie vertical motion;and their dominant modes vary with the input frequency.On the other hand,the coherent modes involved in the bogie pitching motion and vehicle body motion are single and fixed over the whole range of frequency.This study presents an analytical method for the rapid solution of dynamic responses in vehicle systems and systematically analyzes the coherence behavior of vibration transfer functions with respect to tracking irregularity wavelengths.展开更多
Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes,resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patte...Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes,resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patterns.This complexity poses significant challenges for slope stability analysis,requiring the development of specialized techniques to address these issues.This research presents a numerical methodology that incorporates spatial variability,nonlinear material characterization,and probabilistic analysis using a Monte Carlo framework to address this issue.The heterogeneous structure is represented by randomly assigning different lithotypes across the slope,while maintaining predefined global proportions.This contrasts with the more common approach of applying probabilistic variability to mechanical parameters within a homogeneous slope model.The material behavior is defined using complex nonlinear failure criteria,such as the Hoek-Brown model and a parabolic model with collapse,both implemented through linearization techniques.The Discontinuity Layout Optimization(DLO)method,a novel numerical approach based on limit analysis,is employed to efficiently incorporate these advances and compute the factor of safety of the slope.Within this framework,the Monte Carlo procedure is used to assess slope stability by conducting a large number of simulations,each with a different lithotype distribution.Based on the results,a hybrid method is proposed that combines probabilistic modeling with deterministic design principles for the slope stability assessment.As a case study,the methodology is applied to a 20-m-high vertical slope composed of three lithotypes(altered scoria,welded scoria,and basalt)randomly distributed in proportions of 15%,60%,and 25%,respectively.The results show convergence of mean values after approximately 400 simulations and highlight the significant influence of spatial heterogeneity,with variations of the factor of safety between 5 and 12 in 85%of cases.They also reveal non-circular and mid-slope failure wedges not captured by traditional stability methods.Finally,an equivalent normal probability distribution is proposed as a reliable approximation of the factor of safety for use in risk analysis and engineering decision-making.展开更多
A DFN-DEC(discrete fracture network-distinct element code)method based on the MATLAB platform is developed to generate heterogeneous DFN.Subsequently,the effects of the spatial variability(the meanμand the standard d...A DFN-DEC(discrete fracture network-distinct element code)method based on the MATLAB platform is developed to generate heterogeneous DFN.Subsequently,the effects of the spatial variability(the meanμand the standard deviationσ)of the geometric properties(i.e.,the fracture dip D,the trace length T and the spacing S)of both the gently-dipping(denoted with 1)and the steeply-dipping(denoted with 2)fractures on the stability of granite slope are investigated.Results indicate that the proposed DFN-DEC method is robust,generating fracture networks that resemble reality.In addition,the spatial variability of fracture geometry,influencing the structure of granite slope,plays a significant role in slope stability.The mean stability of the slope decreases with the increase ofμ_(D_(1))(the mean of gently-dipping fracture dip),σ_(D_(2))(the mean of steeply-dipping fracture dip),μ_(T_(1))(the mean of gently-dipping fracture trace length),μ_(T_(2))(the mean of steeply-dipping fracture trace length),σ_(T_(1))(the standard deviation of gently-dipping fracture trace length),σ_(T_(2))(the standard deviation of steeply-dipping fracture trace length),and the decrease ofσ_(D_(1))(the standard deviation of gently-dipping fracture dip),μ_(D_(2))(the standard deviation of steeply-dipping fracture dip),μ_(S_(1))(the mean of gently-dipping fracture spacing)andμ_(S_(2))(the mean of steeply-dipping fracture spacing).Among them,μ_(T_(1)),μ_(D_(1))andμ_(S_(1))have the major impact.When the fracture spacing is large,the variability in the fracture geometry becomes less relevant to slope stability.When within some ranges of the fracture spacing,the spatial varying of dips can increase the slope stability by forming an interlaced structure.The results also show that the effects of the variability of trace length on slope stability depend on the variability of dip.These findings highlight the importance of spatial variability in the geometry of fractures to rock slope stability analysis.展开更多
Near-surface geological defects pose a serious threat to human life and infrastructure.Hence,the exploration of geological hazards is essential.Currently,there are various geological hazard exploration methods;however...Near-surface geological defects pose a serious threat to human life and infrastructure.Hence,the exploration of geological hazards is essential.Currently,there are various geological hazard exploration methods;however,those require improvements in terms of economic feasibility,convenience,and lateral resolution.To address this,this study examined an extraction method to determine spatial autocorrelation velocity dispersion curves for application in near-surface exploration.展开更多
With a three-dimensional semiclassical ensemble method, we theoretically investigated the nonsequential double ionization of Ar driven by the spatially inhomogeneous few-cycle negatively chirped laser pulses. Our resu...With a three-dimensional semiclassical ensemble method, we theoretically investigated the nonsequential double ionization of Ar driven by the spatially inhomogeneous few-cycle negatively chirped laser pulses. Our results show that the recollision time window can be precisely controlled within an isolated time interval of several hundred attoseconds, which is useful for understanding the subcycle correlated electron dynamics. More interestingly, the correlated electron momentum distribution (CEMD) exhibits a strong dependence on laser intensity. That is, at lower laser intensity, CEMD is located in the first quadrant. As the laser intensity increases,CEMD shifts almost completely to the second and fourth quadrants, and then gradually to the third quadrant.The underlying physics governing the CEMD's dependence on laser intensity is explained.展开更多
Since the introduction of the concept, studies on valuation of ecosystem services have been overwhelming, in cognizance of its great significance. In this article, the authors took Northeast China as the study area an...Since the introduction of the concept, studies on valuation of ecosystem services have been overwhelming, in cognizance of its great significance. In this article, the authors took Northeast China as the study area and applied the published coefficients for the world by Costanza to calculate the ecosystem services values through a spatial convolution method. The convolution analysis was done with a square processor with 5×5 neighborhood cells. The results showed that the ecosystem services value for the study area in the year 2003 was US$44 990 million which is US$89 million less than the value without operation, and the main contributions for that decrease were from water bodies, wetlands and estuaries. It is expected that this article can attract more interest to explore this field adopting geographic methods.展开更多
The rolls in contemporary four-high mills cannot be maintained parallel during the rolling process. There- fore, four-high rolling mill vibrations take place in six degree of freedom （DOF） leading to spatial behavio...The rolls in contemporary four-high mills cannot be maintained parallel during the rolling process. There- fore, four-high rolling mill vibrations take place in six degree of freedom （DOF） leading to spatial behaviors invol- ving vertical, horizontal, axial, torsional, cross and swinging vibration modes resulting in complex relative motions between the rolls. Two numerical methods, modified Riccati-transfer matrix method （Riccati-TMM） and finite ele- ment method （FEM）, are presented to analyze a spatial vibration characteristic of two four-high rolling mills with different stability. The natural frequency and mode shape of four-high rolling mills are obtained, and the clearance has a great effect on natural frequency and mode shape. In addition, field testing experiment is also conducted to measure natural frequency by power spectrum analysis of rolling mill vibration. Experimental results basically agree with those calculated by Riccati-TMM and FEM, which means that the Riccati-TMM and the FEM can be used for analysis of spatial vibration of four-high rolling mill. Meanwhile, the spatial vibration shows more compound vibra- tion behaviors and the negative effect of horizontal, vertical, cross and swinging vibration modes are effectively con- trolled after redesign of rolling mill. These advantages have a great significance for the rolling mill to be operated with a much higher rolling speed and improved yield of products.展开更多
With the rapid increase of the number and influence of floating population in China,it is urgently needed to understand the regional types of China＇s floating population and their spatial characteristics. After revie...With the rapid increase of the number and influence of floating population in China,it is urgently needed to understand the regional types of China＇s floating population and their spatial characteristics. After reviewing the current methods for identifying regional types of floating population,this paper puts forward a new composite-index identification method and its modification version which is consisted of two indexes of the net migration rate and gross migration rate. Then,the traditional single-index and the new composite-index identification methods are empirically tested to explore their spatial patterns and characteristics by using China＇s 2000 census data at county level. The results show：（1） The composite-index identification method is much better than traditional single-index method because it can measure the migration direction and scale of floating simultaneously,and in particular it can identify the unique regional types of floating population with large scale of immigration and emigration. （2） The modified composite-index identification method,by using the share of a region＇s certain type of floating population to the total in China as weights,can effectively correct the over-or under-estimated errors due to the rather large or small total population of a region. （3） The spatial patterns of different regional types of China＇s floating population are closely related to the regional differentiation of their natural environment,population density and socio-economic development level. The three active regional types of floating population are mainly located in the eastern part of China with lower elevation,more than 800 mm precipitation,rather higher population densities and economic development levels.展开更多
Spatial interpolation is a common tool used in the study of fishery ecology, especially for the construction of ecosystem models. To develop an appropriate interpolation method of determining fishery resources density...Spatial interpolation is a common tool used in the study of fishery ecology, especially for the construction of ecosystem models. To develop an appropriate interpolation method of determining fishery resources density in the Yellow Sea, we tested four frequently used methods, including inverse distance weighted interpolation(IDW), global polynomial interpolation(GPI), local polynomial interpolation(LPI) and ordinary kriging(OK).A cross-validation diagnostic was used to analyze the efficacy of interpolation, and a visual examination was conducted to evaluate the spatial performance of the different methods. The results showed that the original data were not normally distributed. A log transformation was then used to make the data fit a normal distribution. During four survey periods, an exponential model was shown to be the best semivariogram model in August and October 2014, while data from January and May 2015 exhibited the pure nugget effect.Using a paired-samples t test, no significant differences(P>0.05) between predicted and observed data were found in all four of the interpolation methods during the four survey periods. Results of the cross-validation diagnostic demonstrated that OK performed the best in August 2014, while IDW performed better during the other three survey periods. The GPI and LPI methods had relatively poor interpolation results compared to IDW and OK. With respect to the spatial distribution, OK was balanced and was not as disconnected as IDW nor as overly smooth as GPI and LPI, although OK still produced a few 'bull's-eye' patterns in some areas.However, the degree of autocorrelation sometimes limits the application of OK. Thus, OK is highly recommended if data are spatially autocorrelated. With respect to feasibility and accuracy, we recommend IDW to be used as a routine interpolation method. IDW is more accurate than GPI and LPI and has a combination of desirable properties, such as easy accessibility and rapid processing.展开更多
Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product speeifieation（GPS） requires the measurement uncertainty characterizing the reliability of the resul...Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product speeifieation（GPS） requires the measurement uncertainty characterizing the reliability of the results should be given together when the measurement result is given. Nowadays most researches on straightness focus on error calculation and only several research projects evaluate the measurement uncertainty based on ＂The Guide to the Expression of Uncertainty in Measurement（GUM）＂. In order to compute spatial straightness error（SSE） accurately and rapidly and overcome the limitations of GUM, a quasi particle swarm optimization（QPSO） is proposed to solve the minimum zone SSE and Monte Carlo Method（MCM） is developed to estimate the measurement uncertainty. The mathematical model of minimum zone SSE is formulated. In QPSO quasi-random sequences are applied to the generation of the initial position and velocity of particles and their velocities are modified by the constriction factor approach. The flow of measurement uncertainty evaluation based on MCM is proposed, where the heart is repeatedly sampling from the probability density function（PDF） for every input quantity and evaluating the model in each case. The minimum zone SSE of a shaft measured on a Coordinate Measuring Machine（CMM） is calculated by QPSO and the measurement uncertainty is evaluated by MCM on the basis of analyzing the uncertainty contributors. The results show that the uncertainty directly influences the product judgment result. Therefore it is scientific and reasonable to consider the influence of the uncertainty in judging whether the parts are accepted or rejected, especially for those located in the uncertainty zone. The proposed method is especially suitable when the PDF of the measurand cannot adequately be approximated by a Gaussian distribution or a scaled and shifted t-distribution and the measurement model is non-linear.展开更多
Geological disasters not only cause economic losses and ecological destruction, but also seriously threaten human survival. Selecting an appropriate method to evaluate susceptibility to geological disasters is an impo...Geological disasters not only cause economic losses and ecological destruction, but also seriously threaten human survival. Selecting an appropriate method to evaluate susceptibility to geological disasters is an important part of geological disaster research. The aims of this study are to explore the accuracy and reliability of multi-regression methods for geological disaster susceptibility evaluation, including Logistic Regression(LR), Spatial Autoregression(SAR), Geographical Weighted Regression(GWR), and Support Vector Regression(SVR), all of which have been widely discussed in the literature. In this study, we selected Yunnan Province of China as the research site and collected data on typical geological disaster events and the associated hazards that occurred within the study area to construct a corresponding index system for geological disaster assessment. Four methods were used to model and evaluate geological disaster susceptibility. The predictive capabilities of the methods were verified using the receiver operating characteristic(ROC) curve and the success rate curve. Lastly, spatial accuracy validation was introduced to improve the results of the evaluation, which was demonstrated by the spatial receiver operating characteristic(SROC) curve and the spatial success rate(SSR) curve. The results suggest that: 1) these methods are all valid with respect to the SROC and SSR curves, and the spatial accuracy validation method improved their modelling results and accuracy, such that the area under the curve(AUC) values of the ROC curves increased by about 3%–13% and the AUC of the success rate curve values increased by 15%–20%; 2) the evaluation accuracies of LR, SAR, GWR, and SVR were 0.8325, 0.8393, 0.8370 and 0.8539, which proved the four statistical regression methods all have good evaluation capability for geological disaster susceptibility evaluation and the evaluation results of SVR are more reasonable than others; 3) according to the evaluation results of SVR, the central-southern Yunnan Province are the highest sus-ceptibility areas and the lowest susceptibility is mainly located in the central and northern parts of the study area.展开更多
Spatial interpolation methods are frequently used to estimate values of meteorological data in locations where they are not measured. However, very little research has been investigated the relative performance of dif...Spatial interpolation methods are frequently used to estimate values of meteorological data in locations where they are not measured. However, very little research has been investigated the relative performance of different interpolation methods in meteorological data of Xinjiang Uygur Autonomous Region (Xinjiang). Actually, it has importantly practical significance to as far as possibly improve the accuracy of interpolation results for meteorological data, especially in mountainous Xinjiang. There- fore, this paper focuses on the performance of different spatial interpolation methods for monthly temperature data in Xinjiang. The daily observed data of temperature are collected from 38 meteorological stations for the period 1960- 2004. Inverse distance weighting (IDW), ordinary kriging (OK), temperature lapse rate method (TLR) and multiple linear regressions (MLR) are selected as interpolated methods. Two rasterized methods, multiple regression plus space residual error and directly interpolated observed temperature (DIOT) data, are used to analyze and compare the performance of these interpolation methods respectively. Moreover, cross-validation is used to evaluate the performance of different spatial interpolation methods. The results are as follows: 1) The method of DIOT is unsuitable for the study area in this paper. 2) It is important to process the observed data by local regression model before the spatial interpolation. 3) The MLR-IDW is the optimum spatial interpolation method for the monthly mean temperature based on cross-validation. For the authors, the reliability of results and the influence of measurement accuracy, density, distribution and spatial variability on the accuracy of the interpolation methods will be tested and analyzed in the future.展开更多
A large database is desired for machine learning(ML) technology to make accurate predictions of materials physicochemical properties based on their molecular structure.When a large database is not available,the develo...A large database is desired for machine learning(ML) technology to make accurate predictions of materials physicochemical properties based on their molecular structure.When a large database is not available,the development of proper featurization method based on physicochemical nature of target proprieties can improve the predictive power of ML models with a smaller database.In this work,we show that two new featurization methods,volume occupation spatial matrix and heat contribution spatial matrix,can improve the accuracy in predicting energetic materials' crystal density(ρ_(crystal)) and solid phase enthalpy of formation(H_(f,solid)) using a database containing 451 energetic molecules.Their mean absolute errors are reduced from 0.048 g/cm~3 and 24.67 kcal/mol to 0.035 g/cm~3 and 9.66 kcal/mol,respectively.By leave-one-out-cross-validation,the newly developed ML models can be used to determine the performance of most kinds of energetic materials except cubanes.Our ML models are applied to predict ρ_(crystal) and H_(f,solid) of CHON-based molecules of the 150 million sized PubChem database,and screened out 56 candidates with competitive detonation performance and reasonable chemical structures.With further improvement in future,spatial matrices have the potential of becoming multifunctional ML simulation tools that could provide even better predictions in wider fields of materials science.展开更多
基金the financial support provided by MHRD,Govt.of IndiaCoal India Limited for providing financial assistance for the research(Project No.CIL/R&D/01/73/2021)the partial financial support provided by the Ministry of Education,Government of India,under SPARC project(Project No.P1207)。
文摘Sudden and unforeseen seismic failures of coal mine overburden(OB)dump slopes interrupt mining operations,cause loss of lives and delay the production of coal.Consideration of the spatial heterogeneity of OB dump materials is imperative for an adequate evaluation of the seismic stability of OB dump slopes.In this study,pseudo-static seismic stability analyses are carried out for an OB dump slope by considering the material parameters obtained from an insitu field investigation.Spatial heterogeneity is simulated through use of the random finite element method(RFEM)and the random limit equilibrium method(RLEM)and a comparative study is presented.Combinations of horizontal and vertical spatial correlation lengths were considered for simulating isotropic and anisotropic random fields within the OB dump slope.Seismic performances of the slope have been reported through the probability of failure and reliability index.It was observed that the RLEM approach overestimates failure probability(P_(f))by considering seismic stability with spatial heterogeneity.The P_(f)was observed to increase with an increase in the coefficient of variation of friction angle of the dump materials.Further,it was inferred that the RLEM approach may not be adequately applicable for assessing the seismic stability of an OB dump slope for a horizontal seismic coefficient that is more than or equal to 0.1.
文摘This paper takes global manufacturing listed companies from 2010 to 2022 as samples and uses the difference-in-differences(DID)method to empirically examine the impact of the internationalization of ESG standards on the trade competitiveness of multinational enterprises and their mechanisms.The research finds that the internationalization of ESG standards significantly enhances the trade competitiveness of multinational manufacturing enterprises,and this effect is dynamic and sustainable.The mechanism analysis indicates that the internationalization of ESG standards exerts its influence through three pathways:reducing enterprise financing costs,promoting technological innovation,and enhancing brand reputation.The heterogeneity analysis shows that this effect is more significant in enterprises from developed countries,high-pollution industries,and larger enterprises.This paper provides micro-level evidence for understanding the economic consequences of the internationalization of ESG standards and offers policy implications for multinational enterprises to cope with the global ESG rule changes and enhance their trade competitiveness.
基金co-supported by the National Nature Science Foundation of China(No.12303071)the Shanghai Science and Technology Plan Project,China(No.23YF1455500)+1 种基金the China Postdoctoral Science Foundation(No.2023M743653)Ministry of Industry and Information Technology of China through the High Precision Timing Service Project(No.TC220A04A-80)。
文摘The mathematical method of ZTD(zenith tropospheric delay)spatial prediction is important for precise ZTD derivation and real-time precise point positioning(PPP)augmentation.This paper analyses the performance of the popular optimal function coefficient(OFC),sphere cap harmonic analysis(SCHA),kriging and inverse distance weighting(IDW)interpolation in ZTD spatial prediction and Beidou satellite navigation system(BDS)-PPP augmentation over China.For ZTD spatial prediction,the average time consumption of the OFC,kriging,and IDW methods is less than 0.1 s,which is significantly better than that of the SCHA method(63.157 s).The overall ZTD precision of the OFC is 3.44 cm,which outperforms those of the SCHA(9.65 cm),Kriging(10.6 cm),and IDW(11.8 cm)methods.We confirmed that the low performance of kriging and IDW is caused by their weakness in modelling ZTD variation in the vertical direction.To mitigate such deficiencies,an elevation normalization factor(ENF)is introduced into the kriging and IDW models(kriging-ENF and IDW-ENF).The overall ZTD spatial prediction accuracies of IDW-ENF and kriging-ENF are 2.80 cm and 2.01 cm,respectively,which are both superior to those of the OFC and the widely used empirical model GPT3(4.92 cm).For BDS-PPP enhancement,the ZTD provided by the kriging-ENF,IDW-ENF and OFC as prior constraints can effectively reduce the convergence time.Compared with unconstrained BDS-PPP,our proposed kriging-ENF outperforms IDW-ENF and OFC by reducing the horizontal and vertical convergence times by approximately 13.2%and 5.8%in Ningxia and 30.4%and 7.84%in Guangdong,respectively.These results indicate that kriging-ENF is a promising method for ZTD spatial prediction and BDS-PPP enhancement over China.
基金supported by the Major Research Plan on West-Pacific Earth System Multispheric Interactions (Nos.91858215,91958206)the National Natural Science Foundation of China (NSFC)Shiptime Sharing Project (No.41949581)the Key Research and Development Program of Shandong Province (No.2019GHY112019)。
文摘The precision and reliability of first-arrival picking are crucial for determining the accuracy of geological structure inversion using active source ocean bottom seismometer(OBS)refraction data.Traditional methods for first-arrival picking based on sample points are characterized by theoretical errors,especially in low-sampling-frequency OBS data because the travel time of seismic waves is not an integer multiple of the sampling interval.In this paper,a first-arrival picking method that utilizes the spatial waveform variation characteristics of active source OBS data is presented.First,the distribution law of theoretical error is examined;adjacent traces exhibit variation characteristics in their waveforms.Second,a label cross-correlation superposition method for extracting highfrequency signals is presented to enhance the first-arrival picking precision.Results from synthetic and field data verify that the proposed approach is robust,successfully overcomes the limitations of low sampling frequency,and achieves precise outcomes that are comparable with those of high-sampling-frequency data.
基金National Key Research and Development Program of China under Grant No.2023YFE0102900National Natural Science Foundation of China under Grant Nos.52378506 and 52208164。
文摘Although the classical spectral representation method(SRM)has been widely used in the generation of spatially varying ground motions,there are still challenges in efficient simulation of the non-stationary stochastic vector process in practice.The first problem is the inherent limitation and inflexibility of the deterministic time/frequency modulation function.Another difficulty is the estimation of evolutionary power spectral density(EPSD)with quite a few samples.To tackle these problems,the wavelet packet transform(WPT)algorithm is utilized to build a time-varying spectrum of seed recording which describes the energy distribution in the time-frequency domain.The time-varying spectrum is proven to preserve the time and frequency marginal property as theoretical EPSD will do for the stationary process.For the simulation of spatially varying ground motions,the auto-EPSD for all locations is directly estimated using the time-varying spectrum of seed recording rather than matching predefined EPSD models.Then the constructed spectral matrix is incorporated in SRM to simulate spatially varying non-stationary ground motions using efficient Cholesky decomposition techniques.In addition to a good match with the target coherency model,two numerical examples indicate that the generated time histories retain the physical properties of the prescribed seed recording,including waveform,temporal/spectral non-stationarity,normalized energy buildup,and significant duration.
基金supported by the National Natural Science Foundation of China(42372339)the China Geological Survey Project(DD20221816,DD20190319)。
文摘It is of crucial importance to investigate the spatial structures of ancient landslides in the eastern Tibetan Plateau’s alpine canyons as they could provide valuable insights into the evolutionary history of the landslides and indicate the potential for future reactivation.This study examines the Deda ancient landslide,situated in the Chalong-ranbu fault zone,where creep deformation suggests a complex underground structure.By integrating remote sensing,field surveys,Audio-frequency Magnetotellurics(AMT),and Microtremor Survey Method(MSM)techniques,along with engineering geological drilling for validation,to uncover the landslide’s spatial feature s.The research indicates that a fault is developed in the upper part of the Deda ancient landslide,and the gully divides it into Deda landslide accumulation zoneⅠand Deda landslide accumulation zoneⅡin space.The distinctive geological characteristics detectable by MSM in the shallow subsurface and by AMT in deeper layers.The findings include the identification of two sliding zones in the Deda I landslide,the shallow sliding zone(DD-I-S1)depth is approximately 20 m,and the deep sliding zone(DD-I-S2)depth is 36.2-49.9 m.The sliding zone(DD-Ⅱ-S1)depth of the DedaⅡlandslide is 37.6-43.1 m.A novel MSM-based method for sliding zone identification is proposed,achieving less than 5%discrepancy in depth determination when compared with drilling data.These results provide a valuable reference for the spatial structural analysis of large-deepseated landslides in geologically complex regions like the eastern Tibetan Plateau.
基金supported by the National Natural Science Foundation of China(Grant Nos.41941017 and U1702241).
文摘Estimating fracture size is a fundamental aspect of rock engineering.However,determining the most probable diameter(MPD)from a fracture's surface trace remains challenging in the scientific community.The prevailing methodologies typically infer statistical distributions of fracture sizes rather than specific values.This research presents a novel approach to inferring the MPD and the true spatial distribution pattern of each fracture.The challenge lies in linking the inference process with the trace length of each fracture and the statistical characteristics of the entire outcrop.Additionally,it is necessary to address the non-unique inverse problem.The methodology comprises several key steps.Firstly,the issue of censoring bias is addressed by considering the lengths of the traces contained.Secondly,the orientation bias is corrected using the vector method,and the true mean trace length and standard deviation are estimated and derived.Thirdly,assuming a lognormal distribution for fracture sizes,the mean and standard deviation of diameters are derived through a high-order moment relationship between trace lengths and diameters,validated by Crofton's theorem.Finally,the MPDs of all trace samples are determined by relating MPDs to trace lengths and the standard deviation of diameters using stereology techniques.Furthermore,the true fracture spatial patterns are inverted based on spatial geometric relationships.The proposed methodology is validated through rigorous Monte Carlo simulation and applied in a practical engineering case study,demonstrating its potential for use in rock engineering applications.
基金Supported by Fundamental Research Funds for the Central Universities(Grant No.2024QYBS031)Fundamental Research Funds for the Central Universities(Grant No.2022JBQY007)。
文摘Current research on rail vehicle system vibrations primarily relies on numerical methods,with vibration transfer functions commonly derived through data fitting.However,the physical mechanisms underlying these vibrations are not well understood.To clarify the vibration transfer function and its characteristics,four basic input vectors are defined,and an analytical method is proposed.The vibration transfer functions of the vehicle system are solved,and their spatial coherence is analyzed.The results show that there are two spatial scales and four coherent modes in the vehicle system.The track irregularity wavelengths are combined with two spatial scales to alter the proportions of basic input vectors and then show the characteristics of spatial coherence.Four coherent modes are involved in wheel-rail force and primary suspension force;two coherent modes are involved in bogie vertical motion;and their dominant modes vary with the input frequency.On the other hand,the coherent modes involved in the bogie pitching motion and vehicle body motion are single and fixed over the whole range of frequency.This study presents an analytical method for the rapid solution of dynamic responses in vehicle systems and systematically analyzes the coherence behavior of vibration transfer functions with respect to tracking irregularity wavelengths.
基金the project PID2022-139202OB-I00Neural Networks and Optimization Techniques for the Design and Safe Maintenance of Transportation Infrastructures:Volcanic Rock Geotechnics and Slope Stability(IA-Pyroslope),funded by the Spanish State Research Agency of the Ministry of Science,Innovation and Universities of Spain and the European Regional Development Fund,MCIN/AEI/10.13039/501100011033/FEDER,EU。
文摘Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes,resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patterns.This complexity poses significant challenges for slope stability analysis,requiring the development of specialized techniques to address these issues.This research presents a numerical methodology that incorporates spatial variability,nonlinear material characterization,and probabilistic analysis using a Monte Carlo framework to address this issue.The heterogeneous structure is represented by randomly assigning different lithotypes across the slope,while maintaining predefined global proportions.This contrasts with the more common approach of applying probabilistic variability to mechanical parameters within a homogeneous slope model.The material behavior is defined using complex nonlinear failure criteria,such as the Hoek-Brown model and a parabolic model with collapse,both implemented through linearization techniques.The Discontinuity Layout Optimization(DLO)method,a novel numerical approach based on limit analysis,is employed to efficiently incorporate these advances and compute the factor of safety of the slope.Within this framework,the Monte Carlo procedure is used to assess slope stability by conducting a large number of simulations,each with a different lithotype distribution.Based on the results,a hybrid method is proposed that combines probabilistic modeling with deterministic design principles for the slope stability assessment.As a case study,the methodology is applied to a 20-m-high vertical slope composed of three lithotypes(altered scoria,welded scoria,and basalt)randomly distributed in proportions of 15%,60%,and 25%,respectively.The results show convergence of mean values after approximately 400 simulations and highlight the significant influence of spatial heterogeneity,with variations of the factor of safety between 5 and 12 in 85%of cases.They also reveal non-circular and mid-slope failure wedges not captured by traditional stability methods.Finally,an equivalent normal probability distribution is proposed as a reliable approximation of the factor of safety for use in risk analysis and engineering decision-making.
基金supported by the National Natural Science Foundation of China(Nos.41807264,41972289)the Engineering Research Center of Rock-Soil Drilling&Excavation and Protection,Ministry of Education(No.202102)+3 种基金the Key Laboratory of Geological Hazards on Three Gorges Reservoir Area(China Three Gorges University),Ministry of Education(No.2020KDZ01)the Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)(Nos.CUG170686,CUGQY1932)the China Scholarship Council(No.201406410032)the Science and Technology Research Project of Education Department of Hubei Province(Nos.B2019452,B2024509)。
文摘A DFN-DEC(discrete fracture network-distinct element code)method based on the MATLAB platform is developed to generate heterogeneous DFN.Subsequently,the effects of the spatial variability(the meanμand the standard deviationσ)of the geometric properties(i.e.,the fracture dip D,the trace length T and the spacing S)of both the gently-dipping(denoted with 1)and the steeply-dipping(denoted with 2)fractures on the stability of granite slope are investigated.Results indicate that the proposed DFN-DEC method is robust,generating fracture networks that resemble reality.In addition,the spatial variability of fracture geometry,influencing the structure of granite slope,plays a significant role in slope stability.The mean stability of the slope decreases with the increase ofμ_(D_(1))(the mean of gently-dipping fracture dip),σ_(D_(2))(the mean of steeply-dipping fracture dip),μ_(T_(1))(the mean of gently-dipping fracture trace length),μ_(T_(2))(the mean of steeply-dipping fracture trace length),σ_(T_(1))(the standard deviation of gently-dipping fracture trace length),σ_(T_(2))(the standard deviation of steeply-dipping fracture trace length),and the decrease ofσ_(D_(1))(the standard deviation of gently-dipping fracture dip),μ_(D_(2))(the standard deviation of steeply-dipping fracture dip),μ_(S_(1))(the mean of gently-dipping fracture spacing)andμ_(S_(2))(the mean of steeply-dipping fracture spacing).Among them,μ_(T_(1)),μ_(D_(1))andμ_(S_(1))have the major impact.When the fracture spacing is large,the variability in the fracture geometry becomes less relevant to slope stability.When within some ranges of the fracture spacing,the spatial varying of dips can increase the slope stability by forming an interlaced structure.The results also show that the effects of the variability of trace length on slope stability depend on the variability of dip.These findings highlight the importance of spatial variability in the geometry of fractures to rock slope stability analysis.
基金supported by the Henan Province science and technology research project(Grant No.242102321031)National Natural Science Foundation of China(grant numbers 42207200).
文摘Near-surface geological defects pose a serious threat to human life and infrastructure.Hence,the exploration of geological hazards is essential.Currently,there are various geological hazard exploration methods;however,those require improvements in terms of economic feasibility,convenience,and lateral resolution.To address this,this study examined an extraction method to determine spatial autocorrelation velocity dispersion curves for application in near-surface exploration.
基金supported by the National Natural Science Foundation of China (Grant No. 12074329)Nanhu Scholars Program for Young Scholars of Xinyang Normal University。
文摘With a three-dimensional semiclassical ensemble method, we theoretically investigated the nonsequential double ionization of Ar driven by the spatially inhomogeneous few-cycle negatively chirped laser pulses. Our results show that the recollision time window can be precisely controlled within an isolated time interval of several hundred attoseconds, which is useful for understanding the subcycle correlated electron dynamics. More interestingly, the correlated electron momentum distribution (CEMD) exhibits a strong dependence on laser intensity. That is, at lower laser intensity, CEMD is located in the first quadrant. As the laser intensity increases,CEMD shifts almost completely to the second and fourth quadrants, and then gradually to the third quadrant.The underlying physics governing the CEMD's dependence on laser intensity is explained.
基金funded by the Major Program of National Natural Science Foundation of China (40930101)National Technology Introduction Program of China (948 Program,2009-Z31)the Key Project of the Commonweal Foundation of China's National Academy (2010-02)~~
文摘Since the introduction of the concept, studies on valuation of ecosystem services have been overwhelming, in cognizance of its great significance. In this article, the authors took Northeast China as the study area and applied the published coefficients for the world by Costanza to calculate the ecosystem services values through a spatial convolution method. The convolution analysis was done with a square processor with 5×5 neighborhood cells. The results showed that the ecosystem services value for the study area in the year 2003 was US$44 990 million which is US$89 million less than the value without operation, and the main contributions for that decrease were from water bodies, wetlands and estuaries. It is expected that this article can attract more interest to explore this field adopting geographic methods.
基金Item Sponsored by Doctoral Fund of Ministry of Education of China(20111333110001)
文摘The rolls in contemporary four-high mills cannot be maintained parallel during the rolling process. There- fore, four-high rolling mill vibrations take place in six degree of freedom （DOF） leading to spatial behaviors invol- ving vertical, horizontal, axial, torsional, cross and swinging vibration modes resulting in complex relative motions between the rolls. Two numerical methods, modified Riccati-transfer matrix method （Riccati-TMM） and finite ele- ment method （FEM）, are presented to analyze a spatial vibration characteristic of two four-high rolling mills with different stability. The natural frequency and mode shape of four-high rolling mills are obtained, and the clearance has a great effect on natural frequency and mode shape. In addition, field testing experiment is also conducted to measure natural frequency by power spectrum analysis of rolling mill vibration. Experimental results basically agree with those calculated by Riccati-TMM and FEM, which means that the Riccati-TMM and the FEM can be used for analysis of spatial vibration of four-high rolling mill. Meanwhile, the spatial vibration shows more compound vibra- tion behaviors and the negative effect of horizontal, vertical, cross and swinging vibration modes are effectively con- trolled after redesign of rolling mill. These advantages have a great significance for the rolling mill to be operated with a much higher rolling speed and improved yield of products.
基金Foundation： Knowledge Innovation Program of the Chinese Academy of Sciences, No.KZCX2-YW-322, National Natural Science Foundation of China, No.40971102 The National Science and Technology Support Plan, No.2006BAJ11B02-04
文摘With the rapid increase of the number and influence of floating population in China,it is urgently needed to understand the regional types of China＇s floating population and their spatial characteristics. After reviewing the current methods for identifying regional types of floating population,this paper puts forward a new composite-index identification method and its modification version which is consisted of two indexes of the net migration rate and gross migration rate. Then,the traditional single-index and the new composite-index identification methods are empirically tested to explore their spatial patterns and characteristics by using China＇s 2000 census data at county level. The results show：（1） The composite-index identification method is much better than traditional single-index method because it can measure the migration direction and scale of floating simultaneously,and in particular it can identify the unique regional types of floating population with large scale of immigration and emigration. （2） The modified composite-index identification method,by using the share of a region＇s certain type of floating population to the total in China as weights,can effectively correct the over-or under-estimated errors due to the rather large or small total population of a region. （3） The spatial patterns of different regional types of China＇s floating population are closely related to the regional differentiation of their natural environment,population density and socio-economic development level. The three active regional types of floating population are mainly located in the eastern part of China with lower elevation,more than 800 mm precipitation,rather higher population densities and economic development levels.
基金The National Basic Research Program of China under contract No.2015CB453303the National Natural Science Foundation of China under contract No.U1405234+1 种基金the Aoshan Science&Technology Innovation Program under contract No.2015ASKJ02-05the Special Fund of the Taishan Scholar Project
文摘Spatial interpolation is a common tool used in the study of fishery ecology, especially for the construction of ecosystem models. To develop an appropriate interpolation method of determining fishery resources density in the Yellow Sea, we tested four frequently used methods, including inverse distance weighted interpolation(IDW), global polynomial interpolation(GPI), local polynomial interpolation(LPI) and ordinary kriging(OK).A cross-validation diagnostic was used to analyze the efficacy of interpolation, and a visual examination was conducted to evaluate the spatial performance of the different methods. The results showed that the original data were not normally distributed. A log transformation was then used to make the data fit a normal distribution. During four survey periods, an exponential model was shown to be the best semivariogram model in August and October 2014, while data from January and May 2015 exhibited the pure nugget effect.Using a paired-samples t test, no significant differences(P>0.05) between predicted and observed data were found in all four of the interpolation methods during the four survey periods. Results of the cross-validation diagnostic demonstrated that OK performed the best in August 2014, while IDW performed better during the other three survey periods. The GPI and LPI methods had relatively poor interpolation results compared to IDW and OK. With respect to the spatial distribution, OK was balanced and was not as disconnected as IDW nor as overly smooth as GPI and LPI, although OK still produced a few 'bull's-eye' patterns in some areas.However, the degree of autocorrelation sometimes limits the application of OK. Thus, OK is highly recommended if data are spatially autocorrelated. With respect to feasibility and accuracy, we recommend IDW to be used as a routine interpolation method. IDW is more accurate than GPI and LPI and has a combination of desirable properties, such as easy accessibility and rapid processing.
基金supported by National Natural Science Foundation of China (Grant No. 51075198)Jiangsu Provincial Natural Science Foundation of China (Grant No. BK2010479)+2 种基金Innovation Research of Nanjing Institute of Technology, China (Grant No. CKJ20100008)Jiangsu Provincial Foundation of 333 Talents Engineering of ChinaJiangsu Provincial Foundation of Six Talented Peak of China
文摘Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product speeifieation（GPS） requires the measurement uncertainty characterizing the reliability of the results should be given together when the measurement result is given. Nowadays most researches on straightness focus on error calculation and only several research projects evaluate the measurement uncertainty based on ＂The Guide to the Expression of Uncertainty in Measurement（GUM）＂. In order to compute spatial straightness error（SSE） accurately and rapidly and overcome the limitations of GUM, a quasi particle swarm optimization（QPSO） is proposed to solve the minimum zone SSE and Monte Carlo Method（MCM） is developed to estimate the measurement uncertainty. The mathematical model of minimum zone SSE is formulated. In QPSO quasi-random sequences are applied to the generation of the initial position and velocity of particles and their velocities are modified by the constriction factor approach. The flow of measurement uncertainty evaluation based on MCM is proposed, where the heart is repeatedly sampling from the probability density function（PDF） for every input quantity and evaluating the model in each case. The minimum zone SSE of a shaft measured on a Coordinate Measuring Machine（CMM） is calculated by QPSO and the measurement uncertainty is evaluated by MCM on the basis of analyzing the uncertainty contributors. The results show that the uncertainty directly influences the product judgment result. Therefore it is scientific and reasonable to consider the influence of the uncertainty in judging whether the parts are accepted or rejected, especially for those located in the uncertainty zone. The proposed method is especially suitable when the PDF of the measurand cannot adequately be approximated by a Gaussian distribution or a scaled and shifted t-distribution and the measurement model is non-linear.
基金National Natural Science Foundation of China,No.41571077,No.41171318The Fundamental Research Funds for the Central Universities
文摘Geological disasters not only cause economic losses and ecological destruction, but also seriously threaten human survival. Selecting an appropriate method to evaluate susceptibility to geological disasters is an important part of geological disaster research. The aims of this study are to explore the accuracy and reliability of multi-regression methods for geological disaster susceptibility evaluation, including Logistic Regression(LR), Spatial Autoregression(SAR), Geographical Weighted Regression(GWR), and Support Vector Regression(SVR), all of which have been widely discussed in the literature. In this study, we selected Yunnan Province of China as the research site and collected data on typical geological disaster events and the associated hazards that occurred within the study area to construct a corresponding index system for geological disaster assessment. Four methods were used to model and evaluate geological disaster susceptibility. The predictive capabilities of the methods were verified using the receiver operating characteristic(ROC) curve and the success rate curve. Lastly, spatial accuracy validation was introduced to improve the results of the evaluation, which was demonstrated by the spatial receiver operating characteristic(SROC) curve and the spatial success rate(SSR) curve. The results suggest that: 1) these methods are all valid with respect to the SROC and SSR curves, and the spatial accuracy validation method improved their modelling results and accuracy, such that the area under the curve(AUC) values of the ROC curves increased by about 3%–13% and the AUC of the success rate curve values increased by 15%–20%; 2) the evaluation accuracies of LR, SAR, GWR, and SVR were 0.8325, 0.8393, 0.8370 and 0.8539, which proved the four statistical regression methods all have good evaluation capability for geological disaster susceptibility evaluation and the evaluation results of SVR are more reasonable than others; 3) according to the evaluation results of SVR, the central-southern Yunnan Province are the highest sus-ceptibility areas and the lowest susceptibility is mainly located in the central and northern parts of the study area.
文摘Spatial interpolation methods are frequently used to estimate values of meteorological data in locations where they are not measured. However, very little research has been investigated the relative performance of different interpolation methods in meteorological data of Xinjiang Uygur Autonomous Region (Xinjiang). Actually, it has importantly practical significance to as far as possibly improve the accuracy of interpolation results for meteorological data, especially in mountainous Xinjiang. There- fore, this paper focuses on the performance of different spatial interpolation methods for monthly temperature data in Xinjiang. The daily observed data of temperature are collected from 38 meteorological stations for the period 1960- 2004. Inverse distance weighting (IDW), ordinary kriging (OK), temperature lapse rate method (TLR) and multiple linear regressions (MLR) are selected as interpolated methods. Two rasterized methods, multiple regression plus space residual error and directly interpolated observed temperature (DIOT) data, are used to analyze and compare the performance of these interpolation methods respectively. Moreover, cross-validation is used to evaluate the performance of different spatial interpolation methods. The results are as follows: 1) The method of DIOT is unsuitable for the study area in this paper. 2) It is important to process the observed data by local regression model before the spatial interpolation. 3) The MLR-IDW is the optimum spatial interpolation method for the monthly mean temperature based on cross-validation. For the authors, the reliability of results and the influence of measurement accuracy, density, distribution and spatial variability on the accuracy of the interpolation methods will be tested and analyzed in the future.
基金support from the Ministry of Education(MOE) Singapore Tier 1 (RG8/20)。
文摘A large database is desired for machine learning(ML) technology to make accurate predictions of materials physicochemical properties based on their molecular structure.When a large database is not available,the development of proper featurization method based on physicochemical nature of target proprieties can improve the predictive power of ML models with a smaller database.In this work,we show that two new featurization methods,volume occupation spatial matrix and heat contribution spatial matrix,can improve the accuracy in predicting energetic materials' crystal density(ρ_(crystal)) and solid phase enthalpy of formation(H_(f,solid)) using a database containing 451 energetic molecules.Their mean absolute errors are reduced from 0.048 g/cm~3 and 24.67 kcal/mol to 0.035 g/cm~3 and 9.66 kcal/mol,respectively.By leave-one-out-cross-validation,the newly developed ML models can be used to determine the performance of most kinds of energetic materials except cubanes.Our ML models are applied to predict ρ_(crystal) and H_(f,solid) of CHON-based molecules of the 150 million sized PubChem database,and screened out 56 candidates with competitive detonation performance and reasonable chemical structures.With further improvement in future,spatial matrices have the potential of becoming multifunctional ML simulation tools that could provide even better predictions in wider fields of materials science.
