Using In Vitro High‐Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high‐throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline‐based meta‐regression can be used to integrate data across multiple assay replicates to generate a concentration–response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk‐specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta‐regression, may allow risk assessors to identify points of departure and risk‐specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods.     

Interactive profit-planning systems and market turbulence: A dynamic capabilities perspective

This article describes, theorizes and empirically investigates the concept of interactive profit-planning systems (PPS) through the lens of the dynamic capabilities logic. With this conceptualization: interactive PPS capabilities comprise budgeting, forecasting and results-reporting routines, in which top and middle managers interact to create knowledge for sensing, seizing, and business model reconfiguring (to manage strategic business change). Survey data from 331 Australian firms is analyzed employing partial least squares structural equation modeling. The data provides support for two hypotheses: (1) greater market turbulence strengthens the positive effect of interactive PPS capabilities on business unit performance; and (2) greater market turbulence strengthens the positive effect of flexibility values (of organizational culture) on interactive PPS capabilities. Our findings show that interactive PPS capabilities function according to the salient tenets of the dynamic capabilities logic, and clarify the beneficial roles of formal cybernetic control systems and the intertwined involvement of top and middle managers in using dynamic capabilities.     

Values and Their Change During the Business Education – A Gender Perspective

Modern management and organization theory have been criticized for being based on masculine values and concepts. The theory and associated values influence not only managerial behavior in practice, but also business education's value system. In this study, we analyze the change in values during business education from a gender perspective. By values we mean feminine and masculine values. Our empirical study is based on the literature of cultural values and gender socialization theories. We surveyed 324 students. The result of our study lends support to earlier research: men are more masculine and women more feminine in their values. The change towards masculinity during business education is not supported statistically in this study. However, there may be a weak tendency towards masculinity, especially among female students. In addition, we propose that it is possible that business students have a tendency to try to fulfil masculine needs in their occupational choice. Further research is needed to investigate the empirical findings of our study. This revised version was published online in July 2006 with corrections to the Cover Date.     

An Empirical Test of Competing Theories of Hazard-Related Trust: The Case of GM Food

Few scholars doubt the importance of trust in explaining variation in public perception of technological risk. Relatively little, however, is known about the particular types of judgments that people use in granting or withholding trust. This article presents findings from an empirical study that explores several dimensions of trust relevant for citizens' judgments of scientists involved in the development of GM food. The relationship between particular dimensions of trust and perceptions of GM food risk is also explored, using structural equation modeling. Results suggest that trust judgments based on the perception of shared values are most important in relation to GM food risk, but that judgments about scientists' technical competence are also important.     

Underlying Values and Consequences in Financial Services

The freeing of financial markets has brought with it increasing sophistication in regulatory regimes. Over time, a succession of frauds and financial scandals has emphasised some limitations of these complex regulatory schemes. This paper seeks to address the reasons for the events that have caused concern, and suggests that they are to be found principally in three categories: (1) the underlying values that drive financial services; (2) the assumptions and values of regulatory regimes, and (3) the increased opportunities to break or evade the rules. Some possible ways forward are sketched. This revised version was published online in July 2006 with corrections to the Cover Date.     

基于MA S 的群决策支持系统研究

群决策支持系统(GDSS) 与传统的决策支持系统(DSS) 在体系结构和工作方式上有着较 大的差异. 在网络环境中, 组织的决策需要一种开放的GDSS 体系结构和协作的工作方式. 本 文提出一种基于MA S 的GDSS 体系结构, 以及在这种体系结构下的协同决策的模型. 在此基 础上开发了一个GDSS 的原型系统, 并对今后的研究方向进行了展望.     

Identification of Standard Auction Models

This paper presents new identification results for models of first–price, second–price, ascending (English), and descending (Dutch) auctions. We consider a general specification of the latent demand and information structure, nesting both private values and common values models, and allowing correlated types as well as ex ante asymmetry. We address identification of a series of nested models and derive testable restrictions enabling discrimination between models on the basis of observed data. The simplest model—symmetric independent private values—is nonparametrically identified even if only the transaction price from each auction is observed. For richer models, identification and testable restrictions may be obtained when additional information of one or more of the following types is available: (i) the identity of the winning bidder or other bidders; (ii) one or more bids in addition to the transaction price; (iii) exogenous variation in the number of bidders; (iv) bidder–specific covariates. While many private values (PV) models are nonparametrically identified and testable with commonly available data, identification of common values (CV) models requires stringent assumptions. Nonetheless, the PV model can be tested against the CV alternative, even when neither model is identified.     

General results for the Kumaraswamy-G distribution

For any continuous baseline G distribution [G.M. Cordeiro and M. de Castro, A new family of generalized distributions, J. Statist. Comput. Simul. 81 (2011), pp. 883–898], proposed a new generalized distribution (denoted here with the prefix ‘Kw-G’ (Kumaraswamy-G)) with two extra positive parameters. They studied some of its mathematical properties and presented special sub-models. We derive a simple representation for the Kw-G density function as a linear combination of exponentiated-G distributions. Some new distributions are proposed as sub-models of this family, for example, the Kw-Chen [Z.A. Chen, A new two-parameter lifetime distribution with bathtub shape or increasing failure rate function, Statist. Probab. Lett. 49 (2000), pp. 155–161], Kw-XTG [M. Xie, Y. Tang, and T.N. Goh, A modified Weibull extension with bathtub failure rate function, Reliab. Eng. System Safety 76 (2002), pp. 279–285] and Kw-Flexible Weibull [M. Bebbington, C.D. Lai, and R. Zitikis, A flexible Weibull extension, Reliab. Eng. System Safety 92 (2007), pp. 719–726]. New properties of the Kw-G distribution are derived which include asymptotes, shapes, moments, moment generating function, mean deviations, Bonferroni and Lorenz curves, reliability, Rényi entropy and Shannon entropy. New properties of the order statistics are investigated. We discuss the estimation of the parameters by maximum likelihood. We provide two applications to real data sets and discuss a bivariate extension of the Kw-G distribution.     

Model-based clustering of multivariate skew data with circular components and missing values

Motivated by classification issues that arise in marine studies, we propose a latent-class mixture model for the unsupervised classification of incomplete quadrivariate data with two linear and two circular components. The model integrates bivariate circular densities and bivariate skew normal densities to capture the association between toroidal clusters of bivariate circular observations and planar clusters of bivariate linear observations. Maximum-likelihood estimation of the model is facilitated by an expectation maximization (EM) algorithm that treats unknown class membership and missing values as different sources of incomplete information. The model is exploited on hourly observations of wind speed and direction and wave height and direction to identify a number of sea regimes, which represent specific distributional shapes that the data take under environmental latent conditions.