The environmental value of buildings: a proposal for performance assessment with reference to the case of the tall office building

Buildings consume approximately 33% of the world's energy, equivalent to 21% of global CO₂ emissions (IEA 2009, World energy outlook 2009, http://www.iea.org/weo/electricity.asp). Given the current scenario of energy consumption in buildings, the objective of this paper is to present some of the key issues related to assessment of the environmental performance of buildings, supported by the proposal of strategic indicators (with reference to the tall office building), followed by a critical review of the value of environmental design. Fieldwork has shown that a group of European case-studies show signs of change beginning to emerge considering value ahead of first cost, challenging the conventional commercial model. Energy savings and environmental quality in the operation of buildings bring marketability benefits to tenants, whilst future-proofing investments are of benefit to investors. In addition, buildings need to go beyond governmental targets to be able to remain competitive, adding value to environmentally considerate design.     

Utilization of administrative files in health research

Many authors have suggested that administrative health data files could provide the solution to the well-known research problem of obtaining data about volunteer subjects. However, many authors have failed to achieve satisfactory results because the use of these data files leads to special difficulties. Thus, unless the proper methodology is applied, use of health data files does not produce valuable results. In this paper we propose a conceptual framework which can be used to examine the suitability of health data files. More specifically, five aspects are discussed: (1) research team knowledge and skills; (2) identification and documentation of an accessible file; (3) file adequacy to answer the research question; (4) data quality; and (5) data processing. This conceptual framework should help health policy planners and researchers to better identify the problems they will meet and to find adequate solutions to these problems before embarking on the venture of using public data files.     

Investing in children’s education: are Muslim immigrants different?

Using a unique data set on immigrants living in France in 2003, we investigate whether Muslims invest differently in their children’s education compared to non-Muslims. In particular, we want to assess whether educational inequalities between the children of Muslim and non-Muslim immigrants stem from differences between or within families. After controlling for a broad set of individual and household characteristics, we find no difference in education between children of different religions. However, we do find more within-family inequality in children’s educational achievements among Muslims relative to non-Muslims. The within-family variance is 15 % higher among Muslims relative to Catholics and 45 % higher relative to immigrants with other religions, but the intra-family inequality remains difficult to explain. Overall, our results suggest that Muslim parents tend to redistribute their resources more unequally among their children.     

Financial data modeling by Poisson mixture regression

In many financial applications, Poisson mixture regression models are commonly used to analyze heterogeneous count data. When fitting these models, the observed counts are supposed to come from two or more subpopulations and parameter estimation is typically performed by means of maximum likelihood via the Expectation–Maximization algorithm. In this study, we discuss briefly the procedure for fitting Poisson mixture regression models by means of maximum likelihood, the model selection and goodness-of-fit tests. These models are applied to a real data set for credit-scoring purposes. We aim to reveal the impact of demographic and financial variables in creating different groups of clients and to predict the group to which each client belongs, as well as his expected number of defaulted payments. The model's conclusions are very interesting, revealing that the population consists of three groups, contrasting with the traditional good versus bad categorization approach of the credit-scoring systems.     

Bridging between academia and the workplace: lessons learned about translational research on work-family balance

ABSTRACT

Balancing work and family is a continuous and growing challenge, requiring carefully chosen coping strategies. In spite of the growing amount of research on work-family balance, successful, long term solutions are still not readily available to most workers who are trying to cope with the tensions involved in fulfilling both work and family roles. One possible explanation for this lack of translation of research findings in applied settings may lie in how we do work-family research. The present research note presents translational research as a solution to bridge academia and the workplace. More specifically, it shares our experience of a participatory approach to translational research that was adopted in an interdisciplinary research project on work-family balancing strategies. The main objective of this research note is to provide an example of how translational research was carried out in this kind of community-initiated study, and how this approach can facilitate short-term, concrete applications of the knowledge gained from and with the research partners.     

Optimal SIR algorithm vs. fully adapted auxiliary particle filter: a non asymptotic analysis

Particle filters (PF) and auxiliary particle filters (APF) are widely used sequential Monte Carlo (SMC) techniques. In this paper we comparatively analyse, from a non asymptotic point of view, the Sampling Importance Resampling (SIR) PF with optimal conditional importance distribution (CID) and the fully adapted APF (FA). We compute the (finite samples) conditional second order moments of Monte Carlo (MC) estimators of a moment of interest of the filtering pdf, and analyse under which circumstances the FA-based estimator outperforms (or not) the optimal Sequential Importance Sampling (SIS)-based one. Our analysis is local, in the sense that we compare the estimators produced by one time step of the different SMC algorithms, starting from a common set of weighted points. This analysis enables us to propose a hybrid SIS/FA algorithm which automatically switches at each time step from one loop to the other. We finally validate our results via computer simulations.     

Psychological Distress in Older Portuguese Gay and Bisexual Men: The Mediating Role of LGBT Community Connectedness

Abstract

Objectives: Examining Psychological Distress (PD) among older Portuguese gay and bisexual men (GBM), and the mediator role of LGBT community connectedness (LGBTCC) of minority stress variables on PD. Methods: We performed a mediation analysis with LGBTCC as mediator between minority stress variables and PD with a sample of 110 elderly GBM. Results: We found moderate PD levels; LGBTCC was a significant mediator between concealment of sexual orientation and PD, but not between internalized stigma and expectations of rejection and PD. Conclusions: More attention is needed to Older Portuguese GBM’s mental health. LGBTCC is an important ameliorating factor for older GBM.     

Unknown Knowns and Known Unknowns: Framing the Role of Organizational Learning in Corporate Social Responsibility Development

Corporate social responsibility (CSR) is now widely seen as an increasingly significant concern for firms because of moral, relational and instrumental motives. Nevertheless, practical aspects and challenges associated with CSR development in firms remains only partially understood. In this setting, the organizational learning (OL) discipline is recurrently put forward as key in the pursuit and successful development of CSR, but the existing literature remains disjointed. This study critically reviews the existing literature to conceptualize how research to date has approached CSR development in terms of OL, and to provide a two‐dimensional structuring framework of the role of OL in CSR development that emphasizes key OL‐related aspects supporting CSR development and goes beyond an organization‐centric viewpoint to consider not only learning within the organization, but also from others, and with others. In particular, the authors identify key learning processes and sub‐processes and critical areas that remain understudied. Overall, the authors propose a macro view of the work done to date at the intersection of OL and CSR, and in doing so help make the ‘OL for CSR development’ scholarship more recognizable as a sub‐discipline.     

基于信息化的企业知识管理

本文在企业信息化的背景下,阐述了企业知识管理的概念和特征,并在此基础上提出了知识管理的一个流程模型。该模型对于企业在信息化的基础上有效实施知识管理有重要借鉴作用。同时,以农机企业为例,在信息化基础之上,将农机企业知识管理理论分析与实施运用相结合,简要介绍了农机企业知识管理的解决方案与具体构建方法。