书讯

《藏语语音史研究》作者江荻。该书是国内第一本关于藏语语音历史演变的专著,全书共分6章,分别阐述了藏语语音史研究的方法、藏族历史地理分布及政体变迁、藏语方言音系、藏语韵母及元音的发展、藏语声母及辅音的发展、藏语声调的产生与发展,并初步阐释了藏语语音史上一些特别的音类变化现象。该书还将境外的藏语西部方言(克什米尔——拉达克、桑噶尔、巴尔提、普里克)和南部方言(不丹的宗卡语)统筹考虑,突破了长期以来国内学者将藏语仅划分为三大方言(卫藏、康巴、安多)的局限,可以更全而地了解藏语的各类演化现象。大32开,220千字,书号ISBN7-105-05255-4,定价18.00元。已由民族出版社出版发行。

Grout diffusion characteristics during chemical grouting in a deep water-bearing sand layer

This paper is devoted to application of ordinary kriging method in Choghart north anomaly iron ore deposit in Yazd province, Iran. In order to estimate the deposit, 2329 input data gained from 26 boreholes were used. Fe grade was selected as the major regional variable on which the present research has focused. All of the available data were changed to 12.5 m composites so that statistical regularization could be reached. Studies indicated that iron grade input data had single-population characteristics. To carry out ordinary kriging, a spherical model was fitted over empirical variogram. Then the model was verified through cross validation method and proved to be valid with a coherence coefficient of 0.773 between the estimated and real data. Plotting the empirical variogram in different directions showed no geometric anisotropy for the deposit. To estimate the Iron grade, ordinary kriging method was used according to which, all of the exploitable blocks with dimensions 20 m x 20 m x 12.5 m were block esti- mated within the estimation space. Finally tonnage-grade curve has been drawn and reserve classified into measured, indicated and inferred.

Fair Preorder for Partial Fair Kripke Structures

This paper discussed how to handle the fairness conditions in partial Kripke structures. The partial Kripke structures were used for partial state spaces model checking, which is a new technique to solve problems of state explosion. This paper extended the partial Kripke structure with fairness conditions by defining a partial fair Kripke structure, and a 3 valued fair CTL(Computation Tree Logic) semantics correspondingly. It defines a fair preorder between partial Kripke structures that preserves fairness and is akin to fair bisimulation. In addition, a pertinent theorem is also given, which indicates the relationship between the partial state spaces and the more complete one by illustrating the characterizations of states in the partial fair structure in terms of CTL formulae.

Determination of Ash Contents in Coal by Means of Ordinary Kriging Method

The ash contents in coal particles were examined in the paper dependably on particle size and its density. So, the two-dimensional regressive function Z = Z（P, D） was the searched object, where Z is random variable describing ash contents, P---density and D---particle diameter. This dependence was determined based on experimental data concerning the coal of type 31. For this coal, the method of ordinary kriging was applied to calculate the values of random variable Z. This method required the proper selection of so-called variogram function, in which four forms were considered in this paper in purpose to select the best solution. The given results were then evaluated by the mean standard error value and compared with empirical data.

Path prediction of flexible needles based on Fokker-Planck equation and disjunctive Kriging model

Path prediction of flexible needles based on the Fokker-Planck equation and disjunctive Kriging model is proposed to improve accuracy and consider the nonlinearity and anisotropy of soft tissues.The stochastic differential equation is developed into the Fokker-Planck equation with Gaussian noise,and the position and orientation probability density function of flexible needles are then optimized by the stochastic differential equation.The probability density function obtains the mean and covariance of flexible needle movement and helps plan puncture paths by combining with the probabilistic path algorithm.The weight coefficients of the ordinary Kriging are extended to nonlinear functions to optimize the planned puncture path,and the Hermite expansion is used to calculate nonlinear parameter values of the disjunctive Kriging optimization model.Finally,simulation experiments are performed.Detailed comparison results under different path planning maps show that the kinematics model can plan optimal puncture paths under clinical requirements with an error far less than 2 mm.It can effectively optimize the path prediction model and help improve the target rate of soft tissue puncture with flexible needles through data analysis and processing of the mean value and covariance parameters derived by the probability density and disjunctive Kriging algorithms.

Distribution of Extracellular Polymeric Substances in Pilot-Scale Membrane Bioreactor

The spatial distribution of extracellular polymeric substances （EPS） in a pilot-scale membrane bioreactor （MBR） was studied. The sampling points on top of and inside the membrane module were measured and analyzed by the experimental variant function. The content of EPS was spatially interpolated by ordinary Kriging method, and il- lustrated with SURFER software. A case study was carried out in an MBR with membrane aperture of 0.4 ~tm and handling capacity of 120 ma/d in Jizhuangzi sewage treatment plant, Tianjin. From the visualization of EPS distribu- tion, it is seen that on the horizontal plane, the content of EPS was the lowest at the center; and on the vertical plane, the content of EPS decreased with the increase of depth. The shearing force caused by aeration of perforated pipe and the influent mode are the main influencing factors for this distribution.

Comparison of Interpolation Methods for the Study of Forest Variables Using a Geographic Information System

Interpolation methods in ArcGIS_ESRI Geostatistical Analyst tool allow obtaining unknown values at unsampled points from observed data and generating continuous surfaces. In this paper, forest data variables as tree height and diameter measured in two plots in Central Mountains in Spain. These data were georeferenced to obtain maps that can visualize the spatial variability of these forest variables. In order to evaluate the best interpolation method that could adequately explain the spatial variability of those variables, two interpolation methods were studied： inverse results was made by means of statistical methods to analyze distance weighted （IDW） and Ordinary Kriging （OK）. A comparison of residuals. Results with the kriging method were slightly better.

艺术史的意义

自从思辨哲学被挤到艺术的领地和现代意义上的自然科学扩张到艺术的领地以来,“美学”又独门立户之后,世界艺术史已被重新编写了许多次;其结果是:在相当程度上,艺术史成了思辨哲学的形象说明,自然科学的判断物和“美学”的实验田。另一方面,由于政治与经济在人类社会活动中起显而易见的主导作用,使得有些艺术史家竞简单地把一部艺术史写成是政治与经济史的附庸。

Spatial Patterns of Soil Organic Matter,Nitrogen,Phosphorus and Potassium in a Subtropical Forest and Its Implication for Forest Management

Total nitrogen(TN),total phosphorus(TP),total potassium(TK),and soil organic matter(OM)can significantly affect forest growth.However,these soil properties are spatially heterogeneously distributed,complicating the prescription of forest management strategies.Thus,it is imperative to obtain an in-depth understanding of the spatial distribution of soil properties.In this study,soils were sampled at 181 locations in the Tropical Forest Research Center in the southwestern Guangxi Zhuang Autonomous Region in southern China.We investigated the spatial variability of soil OM,TN,TP,and TK using geostatistical analysis.The nugget to sill ratio indicated a strong spatial dependence of soil TN and a moderate spatial dependence of soil OM,TP,and TK,suggesting that TN was primarily controlled by intrinsic factors(e.g.,soil texture,parent material,vegetation type,and topography),whereas soil OM,TP,and TK were controlled by intrinsic and extrinsic factors(e.g.,cultivation practices,fertilization,and planting systems).Based on the spatial variability determined by the geostatistical analysis,we performed ordinary kriging to create thematic maps of soil TN,TP,TK,and OM.Model validation indicated that the thematic maps were reliable to inform forest management.

Application of Ordinary Kriging in Mapping Soil Organic Carbon in Zambia

The quantification of the pattern and spatial distribution of soil organic carbon （SOC） is fundamental to understand many ecosystem processes. This study aimed to apply ordinary kriging （OK） to model the spatial distribution of SOC in a selected part of Zambia. A total of 100 soil samples were collected from the study area and analyzed for SOC by determining soil oxidizable carbon using the Walkley-Black method. An automated fitting procedure was followed when modeling the spatial structure of the SOC data with the exponential semivariogram. The results indicated that the short range spatial dependence of SOC was strong with a nugget close to zero. The spatial autocorrelation was high to medium with a nugget to sill ratio of 0.25. The root mean square error of the predictions was 0.64, which represented 58.18% of the mean observed data for SOC. It can be concluded that the generated map could serve as a proxy for SOC in the region where evidence of spatial structure and quantitative estimates of uncertainty are reported. Therefore, the maps produced can be used as guides for various uses including optimization of soil sarapling.

Source Apportionment of Heavy Metals in Soils Using Multivariate Statistics and Geostatistics

The main objectives of this study were to introduce an integrated method for effectively identifying soil heavy metal pollution sources and apportioning their contributions, and apply it to a case study. The method combines the principal component analysis/absolute principal component scores (PCA/APCS) receptor model and geostatistics. The case study was conducted in an area of 31 km2 in the urban-rural transition zone of Wuhan, a metropolis of central China. 124 topsoil samples were collected for measuring the concentrations of eight heavy metal elements (Mn, Cu, Zn, Pb, Cd, Cr, Ni and Co). PCA results revealed that three major factors were responsible for soil heavy metal pollution, which were initially identified as "steel production", "agronomic input" and "coal consumption". The APCS technique, combined with multiple linear regression analysis, was then applied for source apportionment. Steel production appeared to be the main source for Ni, Co, Cd, Zn and Mn, agronomic input for Cu, and coal consumption for Pb and Cr. Geostatistical interpolation using ordinary kriging was finally used to map the spatial distributions of the contributions of pollution sources and further confirm the result interpretations. The introduced method appears to be an effective tool in soil pollution source apportionment and identification, and might provide valuable reference information for pollution control and environmental management.

Spatial Estimation of Saturated Hydraulic Conductivity from Terrain Attributes Using Regression,Kriging,and Artificial Neural Networks

Several methods,including stepwise regression,ordinary kriging,cokriging,kriging with external drift,kriging with varying local means,regression-kriging,ordinary artificial neural networks,and kriging combined with artificial neural networks,were compared to predict spatial variation of saturated hydraulic conductivity from environmental covariates.All methods except ordinary kriging allow for inclusion of secondary variables.The secondary spatial information used was terrain attributes including elevation,slope gradient,slope aspect,profile curvature and contour curvature.A multiple jackknifing procedure was used as a validation method.Root mean square error (RMSE) and mean absolute error (MAE) were used as the validation indices,with the mean RMSE and mean MAE used to judge the prediction quality.Prediction performance by ordinary kriging was poor,indicating that prediction of saturated hydraulic conductivity can be improved by incorporating ancillary data such as terrain variables.Kriging combined with artificial neural networks performed best.These prediction models made better use of ancillary information in predicting saturated hydraulic conductivity compared with the competing models.The combination of geostatistical predictors with neural computing techniques offers more capability for incorporating ancillary information in predictive soil mapping.There is great potential for further research and development of hybrid methods for digital soil mapping.

Non-Algorithmically Integrating Land Use Type with Spatial Interpolation of Surface Soil Nutrients in an Urbanizing Watershed

Integrating land use type and other geographic information within spatial interpolation has been proposed as a solution to improve the performance and accuracy of soil nutrient mapping at the regional scale. This study developed a non-algorithm approach, i.e., applying inverse distance weighting （IDW） and ordinary kriging （OK）, to individual land use types rather than to the whole watershed, to determine if this improved the performance in mapping soil total C （TC）, total N （TN）, and total P （TP） in a 200-km2 urbanizing watershed in Southeast China. Four land use types were identified by visual interpretation as forest land, agricultural land, green land, and urban land. One hundred and fifty soil samples （0-10 cm） were taken according to land use type and patch size. Results showed that the non-algorithm approach, interpolation based on individual land use types, substantially improved the performance of IDW and OK for mapping TC, TN, and TP in the watershed. Root mean square errors were reduced by 3.9% for TC, 10.770 for TN, and 25.9% for TP by the application of IDW, while the improvements by OK were slightly lower as 0.9% for TC, 7.7% for TN, and 18.1% for TP. Interpolations based on individual land use types visually improved depiction of spatial patterns for TC, TN, and TP in the watershed relative to interpolations by the whole watershed. Substantial improvements might be expected with denser sampling points. We suggest that this non-algorithm approach might provide an alternative to algorithm-based approaches to depict watershed-scale nutrient patterns.

Using Digital Elevation Model to Improve Soil pH Prediction in an Alpine Doline

Among spatial interpolation techniques,geostatistics is generally preferred because it takes into account the spatial correlation between neighbouring observations in order to predict attribute values at unsampled locations.A doline of approximately 15 000 m 2 at 1 900 m above sea level (North Italy) was selected as the study area to estimate a digital elevation model (DEM) using geostatistics,to provide a realistic distribution of the errors and to demonstrate whether using widely available secondary data provided more accurate estimates of soil pH than those obtained by univariate kriging.Elevation was measured at 467 randomly distributed points that were converted into a regular DEM using ordinary kriging.Further,110 pits were located using spatial simulated annealing (SSA) method.The interpolation techniques were multi-linear regression analysis (MLR),ordinary kriging (OK),regression kriging (RK),kriging with external drift (KED) and multi-collocated ordinary cokriging (CKmc).A cross-validation test was used to assess the prediction performances of the different algorithms and then evaluate which methods performed best.RK and KED yielded better results than the more complex CKmc and OK.The choice of the most appropriate interpolation method accounting for redundant auxiliary information was strongly conditioned by site specific situations.

Spatio-Temporal Variability of Soil Salinity in Alluvial Plain of the Lower Reaches of the Yellow River——A Case Study

Soil salinity and hydrologic datasets were assembled to analyze the spatio-temporal variability of salinization in Fengqiu County, Henan Province, China, in the alluvial plain of the lower reaches of the Yellow River. The saline soil and groundwater depth data of the county in 1981 were obtained to serve as a historical reference. Electrical conductivity （EC） of 293 surface soil samples taken from 2 kin x 2 km grids in 2007 and 4{） soil profiles acquired in 2（108 was analyzed and used for comparative mapping. Ordinary kriging was applied to predict EC at unobserved locations to derive the horizontal and vertical distribution patterns and variation of soil salinity. Groundwater table data from 22 observation wells in 2008 were collected and used as input for regression kriging to predict the maximum groundwater depth of the county in 2008. Changes in the groundwater level of Fengqiu County in 27 years from 1981 to 2008 was calculated. Two quantitative criteria, the mean error or bias （ME） and the mean squared error （MSE）, were computed to assess the estimation accuracy of the kriging predictions. The results demonstrated that the soil salinity in the upper soil layers decreased dramatically and the taxonomically defined saline soils were present only in a few micro-landscapes after 27 years. Presently, the soils with relatively elevated salt content were mainly distributed in depressions along the Yellow River bed. The reduction in surface soil salinity corresponded to the locations with deepened maximum groundwater depth. It could be concluded that groundwater table recession allowed water to move deeper into the soil profile, transporting salts with it, and thus played an important role in reducing soil salinity in this region. Accumulation of salts in the soil profiles at various depths below the surface indicated that secondary soil salinization would occur when the groundwater was not controlled at a safe depth.