A Relational Model of Workplace Victimization: Social Roles and Patterns of Victimization in Dyadic Relationships.

This article proposes a model of the ways in which dyadic interactions between employees who occupy 1 of 4 archetypal social roles in organizations can lead to either episodic or institutionalized patterns of victimization. The model shows how the occurrence of victimization involving these 4 role types is influenced by organizational variables such as power differences, culture, and access to social capital. The model integrates behavioral and social structural antecedents of victimization to develop a relational perspective on the dynamics of harmful behavior in the workplace. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Dyadic perfectionism as a predictor of relationship continuity and distress among college students.

This study examined the nature and impact of dyadic perfectionism over a 3-month interval within a sample of 116 college students who were currently involved in an intimate heterosexual relationship. Dyadic perfectionism scores were stable and correlated as expected with scores on concurrent measures of adult attachment orientations and relationship satisfaction. Logistic regression analyses revealed that, controlling for initial commitment status and adult attachment orientations, Time 1 dyadic perfectionism scores significantly and uniquely predicted relationship continuity 3 months later. Lastly, controlling for social desirability, relationship commitment status, and Time 1 adult attachment orientation scores, Time 1 dyadic perfectionism scores also uniquely predicted Time 2 relationship distress. Findings provide additional evidence that dyadic perfectionism is a risk factor for relationship dysfunction. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Two- or three-stage least squares?

Two elements enter the choice between 2 and 3SLS for full-system estimation: statistical efficiency and computational cost. 2SLS always has the computational edge, but 3SLS can be more efficient, a relative advantage that increases with the strength of the interrelations among the error terms. A measure of these interrelations is thus helpful in making the choice, and, when there are only two equations, this has suggested using a high pairwise error correlation as an indicator of when to use 3SLS. In larger systems of equations, however, these pairwise correlations can remain small even though more general interrelations give 3SLS the relative advantage. More general indicators are therefore needed, and this paper suggests three such and demonstrates their efficacy.Professor of Economics, Boston College, and Principal Research Associate, Center for Computational Research in Economics and Management Science, MIT. All computation was done on the TROLL system at MIT. My thanks go to Josh Charap for his able research assistance. This research was sponsored in part by the National Science Foundation under grant #IST-8420614.     

Does the alliance cause good outcome? Recommendations for future research on the alliance.

Research has consistently documented that the quality of the therapeutic alliance is related to the outcome of diverse psychotherapies. Insufficient attention, however, has been directed at identifying the nature and magnitude of the causal relationship between the alliance and outcome. In this commentary, we discuss the major threats to causal interpretation of alliance-outcome correlations and provide suggestions for future research that would help clarify the extent to which the alliance causes positive outcomes. Assuming the alliance is a causal factor in relation to outcome, we provide recommendations for research on the alliance that would attempt to improve patient care by enhancing the alliance. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Convective cooling of supercritical carbon dioxide inside tubes: heat transfer analysis through neural networks

In a previous work, convective heating of carbon dioxide was studied with neural networks (NN), obtaining a totally heuristical heat transfer equation from the direct regression of experimental data. In the present work, the analysis focuses on the cooling process, which has a technical relevance in various applications, as for example in transcritical refrigeration cycles. Heat transfer around the critical zone presents a marked enhancement, that follows the peaks in thermophysical properties like thermal conductivity and heat capacity. Similarly, other properties like density and enthalpy, present a strong variation in narrow temperature intervals around the critical point.This constitutes then a highly non-linear phenomenon, for which it is advisable to use a very flexible function approximator like the NNs. NN models were applied both in terms of dimensionless numbers and of physical quantities, obtaining the two corresponding NN architectures. The choice of the optimal number of neurons in the NN hidden layer is discussed. The NN models are then compared with a recent correlation from literature, for which the validation results present an AAD of 27% and a bias of −26% with an evident prediction shifting. On the other hand the NN models in terms of dimensionless numbers and of physical quantities have AAD and bias of 14% and −4%, and of 7% and −2%, respectively, showing a largely better performance.     

用人工神经网络方法预测鼓泡塔气含率

A new correlation for the prediction of gas hod up in bubble columns was proposed based on an extensive experimental database set up from the literature published over last 30 years .The updated estimation method relying on artificial neural network,dimensional analysis and phenomenological approaches was used and the model prediction agreed with the experimental data with average relative error less than 10%.     

A unified model for the structure of polymers in semidilute solution

A model is developed to analyse the concentration dependence of the range ξ_? of the monomer pair correlation function. In semidilute solution, three concentration regimes are found for semiflexible molecules and the crossover points between the various regimes are predicted in terms of the characteristic ratio of the chains in dilute solution and in terms of the Flory interaction parameter χ. A simple physical interpretation is given which explains the concentration dependence of ξ_? based on binary contacts initially and then ternary contacts at higher concentration. Temperature-concentration diagrams are developed for several common polymer-solvent systems.     

Graph regularized multiset canonical correlations with applications to joint feature extraction

Multiset canonical correlation analysis (MCCA) is a powerful technique for analyzing linear correlations among multiple representation data. However, it usually fails to discover the intrinsic geometrical and discriminating structure of multiple data spaces in real-world applications. In this paper, we thus propose a novel algorithm, called graph regularized multiset canonical correlations (GrMCCs), which explicitly considers both discriminative and intrinsic geometrical structure in multiple representation data. GrMCC not only maximizes between-set cumulative correlations, but also minimizes local intraclass scatter and simultaneously maximizes local interclass separability by using the nearest neighbor graphs on within-set data. Thus, it can leverage the power of both MCCA and discriminative graph Laplacian regularization. Extensive experimental results on the AR, CMU PIE, Yale-B, AT&T, and ETH-80 datasets show that GrMCC has more discriminating power and can provide encouraging recognition results in contrast with the state-of-the-art algorithms.     

海拔高度对变频器散热影响的研究

根据高海拔地区空气的流动特点,引入海拔高度参数。结合不同海拔高度空气特性对散热器温度的影响,对文献[11]提出的板翅式散热器对流换热系数关联式做了修正。根据修正后的关联式计算了散热器出风口空气平均温度和散热器平均压降。修正后的理论计算结果与仿真结果的相对误差小于5％,表明该修正合理。文中的结果可为高海拔地区变频器等电气产品的热设计和可靠性评估提供计算方法和参考数据。