Changes in preschool children’s social engagement positively predict changes in social competence: A three‐year longitudinal study of portuguese children

To test the hypothesis that social engagement is a foundational aspect of other peer social competence indicators during early childhood, 160 Portuguese preschool children (“3‐year‐olds”) were observed at least in two different school years, using a battery of validated social competence assessments based on direct observations and child interviews. Multilevel growth models tested whether social engagement predicted initial values and linear changes in the other social competence indicators. Results were consistent with the hypothesis, insofar as both initial values and changes in social engagement significantly predicted initial values and changes in other social competence indicators. Additionally, the number of children's reciprocated friendships was also predicted by social engagement. These results are discussed from the perspectives of conceptual frameworks that consider individual differences in social competence during early childhood as a consequence of attachment histories and/or emotional competence.     

Leadership’s Role in Process Safety: An Understanding of Behavioral Science Among Managers and Executives Is Needed

ABSTRACT

A recent prevalence of high visibility catastrophic events has garnered increased attention to process safety issues. While the use of Behavior-Based Safety interventions demonstrate a reduction in workplace injuries by targeting employee behavior, we believe that process safety requires a greater focus on the behavior of leaders (e.g., creating and executing strategy). One effective method to begin targeting leader behavior for the improvement of process safety is to teach leaders about the principles of behavior, including ways by which the science may be applied within their own organizational models.     

Modeling the demand reduction input-output (I-O) inoperability due to terrorism of interconnected infrastructures.

Interdependency analysis in the context of this article is a process of assessing and managing risks inherent in a system of interconnected entities (e.g., infrastructures or industry sectors). Invoking the principles of input-output (I-O) and decomposition analysis, the article offers a framework for describing how terrorism-induced perturbations can propagate due to interconnectedness. Data published by the Bureau of Economic Analysis Division of the U.S. Department of Commerce is utilized to present applications to serve as test beds for the proposed framework. Specifically, a case study estimating the economic impact of airline demand perturbations to national-level U.S. sectors is made possible using I-O matrices. A ranking of the affected sectors according to their vulnerability to perturbations originating from a primary sector (e.g., air transportation) can serve as important input to risk management. For example, limited resources can be prioritized for the "top-n" sectors that are perceived to suffer the greatest economic losses due to terrorism. In addition, regional decomposition via location quotients enables the analysis of local-level terrorism events. The Regional I-O Multiplier System II (RIMS II) Division of the U.S. Department of Commerce is the agency responsible for releasing the regional multipliers for various geographical resolutions (economic areas, states, and counties). A regional-level case study demonstrates a process of estimating the economic impact of transportation-related scenarios on industry sectors within Economic Area 010 (the New York metropolitan region and vicinities).     

Risk Modeling, Assessment, and Management of Lahar Flow Threat

The 1991 eruption of Mount Pinatubo in the Philippines is considered one of the most violent and destructive volcanic activities in the 20th century. Lahar is the Indonesian term for volcanic ash, and lahar flows resulting from the massive amount of volcanic materials deposited on the mountain's slope posed continued post-eruption threats to the surrounding areas, destroying lives, homes, agricultural products, and infrastructures. Risks of lahar flows were identified immediately after the eruption, with scientific data provided by the Philippine Institute of Volcanology, the U.S. Geological Survey, and other research institutions. However, competing political, economic, and social agendas subordinated the importance of scientific information to policy making. Using systemic risk analysis and management, this article addresses the issues of multiple objectives and the effective integration of scientific techniques into the decision-making process. It provides a modeling framework for identifying, prioritizing, and evaluating policies for managing risk. The major considerations are: (1) applying a holistic approach to risk analysis through hierarchical holographic modeling, (2) applying statistical methods to gain insight into the problem of uncertainty in risk assessment, (3) using multiobjective trade-off analysis to address the issue of multiple decisionmakers and stakeholders in the decision-making process, (4) using the conditional expected value of extreme events to complement and supplement the expected value in quantifying risk, and (5) assessing the impacts of multistage decisions. Numerical examples based on ex post data are formulated to illustrate applications to various problems. The resulting framework from this study can serve as a general baseline model for assessing and managing risks of natural disasters, which the Philippines' lead agency-the National Disaster Coordinating Council (NDCC)-and other related organizations can use for their decision-making processes.     

A Bayesian analysis for the Block and Basu bivariate exponential distribution in the presence of covariates and censored data

In this paper, we introduce a Bayesian Analysis for the Block and Basu bivariate exponential distribution using Markov Chain Monte Carlo (MCMC) methods and considering lifetimes in presence of covariates and censored data. Posterior summaries of interest are obtained using the popular WinBUGS software. Numerical illustrations are introduced considering a medical data set related to the recurrence times of infection for kidney patients and a medical data set related to bone marrow transplantation for leukemia.     

人造卫星捕捉污染物的全球迁移(上)

在20世纪中期,高耸的烟囱是解决工业废气排放的常见方法.把废气泵到足够高的空中,便想当然地认为污染问题也随之解决了.然而,随后的许多研究却强有力地显示高大烟囱不足以减轻污染的影响,那些高耸的大烟囱排放的污染物最终还是会回到地面,当然可能是到达几十里或数千里以外的其它地方.     

展望一种可持续的后现代生态文明

遏制贪婪和其它欲望是个体幸福的关键,同时也是一笔共同财富。西方资本主义一直以贪婪和欲望作为经济发展的动力,这是直接导致过度消费、债务和不可持续性的根源。中国在这件事情上会更加聪明,去努力建设一个可持续的后现代生态文明,拥抱自由和有创造力的自由市场体系,同时拒绝西方破坏性的贪婪和欲望。     

Effects of Alternative Policies on Income Redistribution: Evidence from Brazil

Despite recent successes, Brazilian income (cash) transfer policies remain controversial, and alternative approaches to income redistribution are being actively considered. This article contributes to this debate, analysing the effects of several alternative policies for income redistribution in the Brazilian economy using a computable general equilibrium model. Simulations were conducted consistent with the following policies: direct transfer of income, reduction of taxes, and incentives to agricultural exports. The results suggest that transfer of income is the most effective in promoting redistribution of income, with a positive impact on the level of welfare of the poorest households.     

Pandemic Recovery Analysis Using the Dynamic Inoperability Input-Output Model

Economists have long conceptualized and modeled the inherent interdependent relationships among different sectors of the economy. This concept paved the way for input-output modeling, a methodology that accounts for sector interdependencies governing the magnitude and extent of ripple effects due to changes in the economic structure of a region or nation. Recent extensions to input-output modeling have enhanced the model's capabilities to account for the impact of an economic perturbation; two such examples are the inoperability input-output model^{( 1 , 2 )} and the dynamic inoperability input-output model (DIIM).^{( 3 )} These models introduced sector inoperability, or the inability to satisfy as-planned production levels, into input-output modeling. While these models provide insights for understanding the impacts of inoperability, there are several aspects of the current formulation that do not account for complexities associated with certain disasters, such as a pandemic. This article proposes further enhancements to the DIIM to account for economic productivity losses resulting primarily from workforce disruptions. A pandemic is a unique disaster because the majority of its direct impacts are workforce related. The article develops a modeling framework to account for workforce inoperability and recovery factors. The proposed workforce-explicit enhancements to the DIIM are demonstrated in a case study to simulate a pandemic scenario in the Commonwealth of Virginia.     

The industrial athlete?

Many similarities can be drawn between the athletic and industrial population. It is time for a shift in the approach toward injured workers utilizing a sports medicine perspective. We must think of workers as industrial athletes and recognize that the sports medicine model can be appropriately adapted to the injured worker. This model includes prevention, early intervention/identification, training and conditioning, and progressive treatment. Sports medicine rehabilitation concepts include treating the entire kinetic chain that is associated with a specific injury and the SAID principle (Specific Adaptations to Imposed Demands).