Profile-Based Linguistic Uniformity as a Generic Method for Comparing Language Varieties

In this text we present``profile-based linguistic uniformity', a methoddesigned to compare language varieties on thebasis of a wide range of potentiallyheterogeneous linguistic variables. In manyrespects a parallel can be drawn with currentmethods in dialectometry (for an overview, see,Nerbonne and Heeringa, 2001; Heeringa, Nerbonneand Kleiweg, 2002): in both casesdissimilarities between varieties on the basisof individual variables are summarized inglobal dissimilarities, and a series oflanguage varieties are subsequently clusteredor charted using multivariate techniques suchas cluster analysis or multidimensionalscaling. This global similarity between themethods makes it possible to compare them andto investigate the implications of notabledifferences. In this text we specifically focuson, and defend one characteristic of ourmethodology, its profile-based nature.     

Hybrid Approach for Addressing Uncertainty in Risk Assessments

Parameter uncertainty is a major aspect of the model-based estimation of the risk of human exposure to pollutants. The Monte Carlo method, which applies probability theory to address model parameter uncertainty, relies on a statistical representation of available information. In recent years, other uncertainty theories have been proposed as alternative approaches to address model parameter uncertainty in situations where available information is insufficient to identify statistically representative probability distributions, due in particular to data scarcity. The simplest such theory is possibility theory, which uses so-called fuzzy numbers to represent model parameter uncertainty. In practice, it may occur that certain model parameters can be reasonably represented by probability distributions, because there are sufficient data available to substantiate such distributions by statistical analysis, while others are better represented by fuzzy numbers (due to data scarcity). The question then arises as to how these two modes of representation of model parameter uncertainty can be combined for the purpose of estimating the risk of exposure. This paper proposes an approach (termed a hybrid approach) which combines Monte Carlo random sampling of probability distribution functions with fuzzy calculus. The approach is applied to a real case of estimation of human exposure, via vegetable consumption, to cadmium present in the surficial soils of an industrial site located in the north of France. The application illustrates the potential of the proposed approach, which allows the uncertainty affecting model parameters to be represented in a way that is consistent with the information at hand. Also, because the hybrid approach takes advantage of the “rich” information provided by probability distributions, while retaining the conservative character of fuzzy calculus, it is believed to hold value in terms of a “reasonable” application of the precautionary principle.     

Mixed formulation of nonlinear beam on foundation elements

This paper presents an inelastic element for the analysis of beams on foundations. The element is derived from a two-field mixed formulation with independent approximation of forces and displacements. The state determination algorithm for the implementation of the element in a general purpose nonlinear finite element analysis program is presented and its stability characteristics are discussed. Numerical studies are performed to compare the model with the classical displacement formulation. The studies confirm the superiority of the proposed model in describing the inelastic behavior of beams on foundations.     

Probabilistic Strength Estimates and Reliability of Damaged Parallel Wire Cables

Cable reliability analysis involves the combined evaluation of cable capacity and cable load in a probabilistic manner. Assessment of cable capacity is only possible through visual inspections of the wires, field sampling, laboratory analysis of the degraded wire populations, and analytical techniques. In addition to a brief presentation of cable mechanics and deterministic models that approximate cable strength, this paper discusses inspection methodologies and statistical methods of estimation of the sizes of the degraded wire populations, and wire properties, leading to cable capacities. These capacities are described by probability distributions. The paper also discusses fundamentals of reliability analysis as they apply to bridge cables. Load criteria of present standard specifications (such as AASHTO or other international codes) are not applicable to long-span suspension bridges. The paper discusses criteria of bridge loading and reliability indices for bridge cables. More work is needed in the evaluation of loading for long-span bridges.     

民族特色词语的英汉互译

语言在其发展演变过程中,逐步具有了鲜明的民族文化色彩。阐述了民族特色词语的可译性,并提出了具体的翻译方法。     

金属包覆平板波导模式特性的有限元法分析

采用有限元法（FEM）分析了具有复数折射率的金属包覆介质波导的模折射率与模场分布情况。计算了具有损耗层的6层介质平板波导模折射率，并与解析解比较，二者有较好的一致性；分析了金属包覆3层平板波导中TM模折射率与波导芯厚度的变化关系，计算了金属包覆5层平板波导中TM模折秧经与金属层厚度的变化关系，并结合对模场分布的分析对模式进行了定性判断，给出了其模式演变过程。     

Effect of Organic Additives on Electrochemical Surface Precipitation and Polymorphism of CaCO3

The inhibition effect of three organic additives on the precipitation and polymorphism of CaCO₃ deposited on gold surfaces was investigated using electrochemical and microscopic techniques. Additives, two polyacrylic acid (PAA) polymers with different molecular weights (Mw 2100, Mw 30,000), and 1,2,4,5‐benzenetetracarboxylic acid (BTCA), were either added to the solution before or during deposition. In the presence of 100 ppm of one of the three additives in solution, almost no scale was observed on the surface for at least 24 hours. In the presence of lower concentrations of PAA Mw 2100, only distorted calcite crystals were obtained while with PAA Mw 30,000 the polymorph was spherical vaterite. A mixture of calcite and vaterite was observed with the BTCA additive. Addition of the polymers inhibits further nucleation and growth even if added after partial deposition of CaCO₃ while BTCA has no effect once nucleation has started. The results indicate that the inhibit ion effect of the PAA polymers is due to adsorption on the electrode surface while the effect of BTCA is related to chelation of calcium ions in solution.     

尖晶石型软磁铁氧体纳米材料的制备研究进展

介绍了软磁铁氧体纳米材料的特性,综述了近年来具有尖晶石结构的软磁铁氧体纳米材料的制备方法。其中包括:化学共沉淀法,水热法,溶胶-凝胶法,喷雾热解法,微乳液法,相转化法,超临界法,冲击波合成法,微波场下湿法合成,爆炸法,高能球磨法,自蔓延高温合成法等。详细介绍了各种制备方法的特点,研究进展及其发展趋势。     

The Challenge of the Market

Identifying markets for new or improved products for minor crops threatened with extinction is one critical component of any strategy intended to enhance prospects for sustainable production and use. Typically, however, activities linked to the sustainability of these commodities avoid addressing questions associated with assessing their commercial potential. After a brief review of this avoidance syndrome, this article presents a sample of practical, low-cost procedures to help evaluate the market prospects and procedures for crops like quinoa, while citing references to other methodological materials covering similar topics.     

A semiparametric model for compositional data analysis in presence of covariates on the simplex

Compositional data occur as natural realizations of multivariate observations comprising element proportions of some whole quantity. Such observations predominate in disciplines like geology, biology, ecology, economics and chemistry. Due to unit sum constraint on compositional data, specialized statistical methods are required for analyzing these data. Dirichlet distributions were originally used to study compositional data even though this family of distribution is not appropriate (see Aitchison, 1986) because of their extreme independence properties. Aitchison (1982) endeavored to provide a viable alternative to existing methods by employing Logistic Normal distribution to analyze such constrained data. However this family does not include the Dirichlet class and is therefore unable to address the issue of extreme independence. In this paper generalized Liouville family is investigated to model compositional data which includes covariates. This class permits distributions that admit negative or mixed correlation and also contains non-Dirichlet distributions with non-positive correlation and overcomes deficits in the Dirichlet class. Semiparametric Bayesian methods are proposed to estimate the probability density. Predictive distributions are used to assess performance of the model. The methods are illustrated on a real data set.