现金流量表准则的国际比较

《企业会计准则——现金流量表》的颁布与实施 ,是我国会计顺应世界会计发展潮流的又一重大举措。本文试就该准则与美国、英国及国际会计准则委员会等西方会计规范进行比较 ,借以透视我国的现金流量表准则     

应用马尔科夫状态图法进行可靠性评估

应用马尔科夫状态图法,对一个实际的硬件式可修容错计算机系统进行了可靠性评估。并针对两种容错方式分别得出各自的评估数据,通过实际的数据分析了其优缺点及最佳适用范围。     

On the adjacent vertex-distinguishing total chromatic numbers of the graphs with Δ (G) = 3

Let be a simple graph and T(G) be the set of vertices and edges of G. Let C be a k-color set. A (proper) total k-coloring f of G is a function such that no adjacent or incident elements of T(G) receive the same color. For any , denote . The total k-coloring f of G is called the adjacent vertex-distinguishing if for any edge . And the smallest number of colors is called the adjacent vertex-distinguishing total chromatic number of G. In this paper, we prove that for all connected graphs with maximum degree three. This is a step towards a conjecture on the adjacent vertex-distinguishing total coloring. MSC: 05C15     

Physiological Daily Inhalation Rates for Health Risk Assessment in Overweight/Obese Children,Adults, and Elderly

Physiological daily inhalation rates reported in our previous study for normal‐weight subjects 2.6–96 years old were compared to inhalation data determined in free‐living overweight/obese individuals (n = 661) aged 5–96 years. Inhalation rates were also calculated in normal‐weight (n = 408), overweight (n = 225), and obese classes 1, 2, and 3 adults (n = 134) aged 20–96 years. These inhalation values were based on published indirect calorimetry measurements (n = 1,069) and disappearance rates of oral doses of water isotopes (i.e., ²H₂O and H₂¹⁸O) monitored by gas isotope ratio mass spectrometry usually in urine samples for an aggregate period of over 16,000 days. Ventilatory equivalents for overweight/obese subjects at rest and during their aggregate daytime activities (28.99 ± 6.03 L to 34.82 ± 8.22 L of air inhaled/L of oxygen consumed; mean ±  SD) were determined and used for calculations of inhalation rates. The interindividual variability factor calculated as the ratio of the highest 99th percentile to the lowest 1st percentile of daily inhalation rates is higher for absolute data expressed in m³/day (26.7) compared to those of data in m³/kg‐day (12.2) and m³/m²‐day (5.9). Higher absolute rates generally found in overweight/obese individuals compared to their normal‐weight counterparts suggest higher intakes of air pollutants (in μg/day) for the former compared to the latter during identical exposure concentrations and conditions. Highest absolute mean (24.57 m³/day) and 99th percentile (55.55 m³/day) values were found in obese class 2 adults. They inhale on average 8.21 m³ more air per day than normal‐weight adults.     

Who speaks up to whom? A relational approach to employee voice

We adopt a relational approach to examine the effects of social relations and formal structure on who speaks up to whom about problems at work. Data were collected in a two-wave employee survey in three Dutch preschools. Using exponential random graph modeling, we found significant positive effects of formal structure (recipient's hierarchical level; team co-membership) and good relations between speaker and recipient on the likelihood of voice in a dyad. Speaker's hierarchical level had positive effects, significant in Wave 1. Speaker's degree centrality significantly reduced the likelihood of voice, whereas recipient's degree centrality had no effect.     

The local and global structure of knowledge production in an emergent research field: An exponential random graph analysis

Previous research has characterized knowledge networks by diffuse connectivity and/or clusters and the absence of centrality. In contrast, exponential random graph models used in this article demonstrate that the uncertainty and centralized influence typical of an emerging area of research leads to the creation of a densely interconnecting core that acts to cohere the network. Moreover, eclecticism and innovativeness, also characteristic of a developing area, lead to a diffusely connected structure. The data, comprising 2200 authors and 76 papers have been manually coded from articles on the feminization of the labor force in Asia.     

Curved Exponential Family Models for Social Networks

Curved exponential family models are a useful generalization of exponential random graph models (ERGMs). In particular, models involving the alternating k-star, alternating k-triangle, and alternating k-twopath statistics of Snijders et al (2006) may be viewed as curved exponential family models. This article unifies recent material in the literature regarding curved exponential family models for networks in general and models involving these alternating statistics in particular. It also discusses the intuition behind rewriting the three alternating statistics in terms of the degree distribution and the recently introduced shared partner distributions. This intuition suggests a redefinition of the alternating k-star statistic. Finally, this article demonstrates the use of the statnet package in R for fitting models of this sort, comparing new results on an oft-studied network dataset with results found in the literature.     

Advances in Exponential Random Graph (p*) Models Applied to a Large Social Network

Recent advances in statistical network analysis based on the family of exponential random graph (ERG) models have greatly improved our ability to conduct inference on dependence in large social networks (Snijders 2002, Pattison and Robins 2002, Handcock 2002, Handcock 2003, Snijders et al. 2006, Hunter et al. 2005, Goodreau et al. 2005, previous papers this issue). This paper applies advances in both model parameterizations and computational algorithms to an examination of the structure observed in an adolescent friendship network of 1,681 actors from the National Longitudinal Study of Adolescent Health (AddHealth). ERG models of social network structure are fit using the R package statnet, and their adequacy assessed through comparison of model predictions with the observed data for higher-order network statistics.For this friendship network, the commonly used model of Markov dependence leads to the problems of degeneracy discussed by Handcock (2002, 2003). On the other hand, model parameterizations introduced by Snijders et al (2006) and Hunter and Handcock (2006) avoid degeneracy and provide reasonable fit to the data. Degree-only models did a poor job of capturing observed network structure; those that did best included terms both for heterogeneous mixing on exogenous attributes (grade and self-reported race) as well as endogenous clustering. Networks simulated from this model were largely consistent with the observed network on multiple higher-order network statistics, including the number of triangles, the size of the largest component, the overall reachability, the distribution of geodesic distances, the degree distribution, and the shared partner distribution. The ability to fit such models to large datasets and to make inference about the underling processes generating the network represents a major advance in the field of statistical network analysis.     

Decomposing Bayesian networks: triangulation of the moral graph with genetic algorithms

In this paper we consider the optimal decomposition of Bayesian networks. More concretely, we examine empirically the applicability of genetic algorithms to the problem of the triangulation of moral graphs. This problem constitutes the only difficult step in the evidence propagation algorithm of Lauritzen and Spiegelhalter (1988) and is known to be NP-hard (Wen, 1991). We carry out experiments with distinct crossover and mutation operators and with different population sizes, mutation rates and selection biasses. The results are analysed statistically. They turn out to improve the results obtained with most other known triangulation methods (Kjærulff, 1990) and are comparable to results obtained with simulated annealing (Kjærulff, 1990; Kjærulff, 1992).     

Using Graph Models to Analyze the Vulnerability of Electric Power Networks

In this article, we model electric power delivery networks as graphs, and conduct studies of two power transmission grids, i.e., the Nordic and the western states (U.S.) transmission grid. We calculate values of topological (structural) characteristics of the networks and compare their error and attack tolerance (structural vulnerability), i.e., their performance when vertices are removed, with two frequently used theoretical reference networks (the Erdös‐Rényi random graph and the Barabási‐Albert scale‐free network). Further, we perform a structural vulnerability analysis of a fictitious electric power network with simple structure. In this analysis, different strategies to decrease the vulnerability of the system are evaluated. Finally, we present a discussion on the practical applicability of graph modeling.