Sample selection in radiocarbon dating

Archaeologists working on the island of O'ahu, Hawai'i, use radiocarbon dating of samples of organic matter found trapped in fish-pond sediments to help them to learn about the chronology of the construction and use of the aquicultural systems created by the Polynesians. At one particular site, Loko Kuwili, 25 organic samples were obtained and funds were available to date an initial nine. However, on calibration to the calendar scale, the radiocarbon determinations provided date estimates that had very large variances. As a result, major issues of chronology remained unresolved and the archaeologists were faced with the prospect of another expensive programme of radiocarbon dating. This paper presents results of research that tackles the problems associated with selecting samples from those which are still available. Building on considerable recent research that utilizes Markov chain Monte Carlo methods to aid archaeologists in their radiocarbon calibration and interpretation, we adopt the standard Bayesian framework of risk functions, which allows us to assess the optimal samples to be sent for dating. Although rather computer intensive, our algorithms are simple to implement within the Bayesian radiocarbon framework that is already in place and produce results that are capable of direct interpretation by the archaeologists. By dating just three more samples from Loko Kuwili the expected variance on the date of greatest interest could be substantially reduced.     

Circuit optimization via sequential computer experiments: design of an output buffer

In electrical engineering, circuit designs are now often optimized via circuit simulation computer models. Typically, many response variables characterize the circuit's performance. Each response is a function of many input variables, including factors that can be set in the engineering design and noise factors representing manufacturing conditions. We describe a modelling approach which is appropriate for the simulator's deterministic input–output relationships. Non-linearities and interactions are identified without explicit assumptions about the functional form. These models lead to predictors to guide the reduction of the ranges of the designable factors in a sequence of experiments. Ultimately, the predictors are used to optimize the engineering design. We also show how a visualization of the fitted relationships facilitates an understanding of the engineering trade-offs between responses. The example used to demonstrate these methods, the design of a buffer circuit, has multiple targets for the responses, representing different trade-offs between the key performance measures.     

Is Stakeholder Corporate Governance Appropriate in Russia?

Journal of Management and Governance - Alternative forms of disciplining the actionsof senior enterprise managers can becharacterized as shareholder or stakeholdergovernance. This paper analyzes...     

Individual and situational correlates of motivation for skills upgrading: an empirical study

The present research examines the tenability of a number of factors thought to precede an individual's motivation for skills upgrading. Because motivation for skills upgrading is instrumental to training success and is highly malleable, knowing the factors that precede motivation for skills upgrading would help managers and policy makers a great deal in formulating strategies to raise the competitiveness of the workforce. We derive several testable hypotheses from the existing literature and empirically verify the selected antecedents of motivation for skills upgrading. Results based on responses from 413 employees suggest that an individual's attitude towards skills upgrading, self-efficacy, usefulness of skills upgrading, health condition and long-term orientation are positively related to motivation for skills upgrading. Implications for policy makers, managers and researchers are discussed.     

环状区域的车辆路径方案生成系统及优化模型

针对顾客满足环状区域分布的车辆路径问题(VRP),以大幅度地缩减问题求解的状态空间为突破口,引入人工智能和运筹学理论,提出求解这类特殊车辆路径问题的两阶段方法.第1阶段考虑行车时间和车载容量,提出带有控制策略的深度优先搜索算法自动生成备选的车辆路径方案集合.第2阶段将此备选方案集合归结为整数规划模型.采用VB6.0编程语言构建了车辆路径方案生成系统,并实现该系统与运筹学求解软件lindo的集成.通过案例验证了上述方法及自动求解系统的有效性.该项研究为解决环状配送区域的车辆路径问题这一难题提供了新方法.     

Observational Stance as a Predictor of Subjective and Genital Sexual Arousal in Men and Women

Observational stance refers to the perspective a person takes while viewing a sexual stimulus, either as a passive observer (observer stance) or an active participant (participant stance). The objective of the current study was to examine the relationship between observational stance and sexual arousal (subjective and genital) across a range of sexual stimuli that do or do not correspond with a participant's sexual attraction (preferred or nonpreferred stimuli, respectively). Regression analyses revealed that, for men (n = 44), participant stance significantly predicted subjective and genital arousal. Women's (n = 47) observer and participant stance predicted subjective arousal but not genital arousal. Analysis of variance showed that participant stance was greatest under preferred sexual stimuli conditions for all groups of participants, while observer stance scores revealed a less consistent pattern of response. This was particularly true for opposite-sex-attracted women, whose ratings of observer stance were lowest for preferred stimuli. Observational stance does not appear to account for gender differences in specificity of sexual arousal; for men, however, participant stance uniquely predicted genital response after controlling for sexual attractions. Similarities in the relationships between men's and women's observational stance and sexual responses challenge previous claims of gender differences in how men and women view erotica.     

Resampling-based Classification Using Depth for Functional Curves

The depths, which have been used to detect outliers or to extract a representative subset, can be applied to classification. We propose a resampling-based classification method based on the fact that resampling techniques yield a consistent estimator of the distribution of a statistic. The performance of this method was evaluated with eight contaminated models in terms of Correct Classification Rates (CCRs), and the results were compared with other known methods. The proposed method consistently showed higher average CCRs and 4% higher CCR at the maximum compared to other methods. In addition, this method was applied to Berkeley data. The average CCRs were between 0.79 and 0.85.