Generating a smallest binary tree by proper selection of the longest edges to bisect in a unit simplex refinement

In several areas like global optimization using branch-and-bound methods for mixture design, the unit n-simplex is refined by longest edge bisection (LEB). This process provides a binary search tree. For \(n>2\), simplices appearing during the refinement process can have more than one longest edge (LE). The size of the resulting binary tree depends on the specific sequence of bisected longest edges. The questions are how to calculate the size of one of the smallest binary trees generated by LEB and how to find the corresponding sequence of LEs to bisect, which can be represented by a set of LE indices. Algorithms answering these questions are presented here. We focus on sets of LE indices that are repeated at a level of the binary tree. A set of LEs was presented in Aparicio et al. (Informatica 26(1):17–32, 2015), for \(n=3\). An additional question is whether this set is the best one under the so-called \(m_k\)-valid condition.     

Changing Trends of Mothers’ Active and Passive Childcare Times

This paper explores how mothers’ allocation of types of time with children and the determinants of this allocation have changed during 1981–1997 in the United States, using Time Use Longitudinal Panel Study and Family Interaction, Social Capital and Trends in Time Use. Data reveal that active time with children has increased for the case of educated working mothers with young children. Estimations also provide evidence that although different uses of time are substitutes; active time is less sensitive than passive. Moreover, the relationship between active and passive time with children has changed over time.     

Climate change and population migration in Brazil’s Northeast: scenarios for 2025–2050

This research contributes to an understanding of the relationship between climate change, economic impacts and migration. We model the long-term relationship (up to 45 years of projection) between demographic dynamics—particularly migration—driven by changes in the performance of the economy due to climate changes in the Northeast region of Brazil. The region is of particular relevance to the study of climate change impacts given its large human population (28% of Brazil’s population) and high levels of impoverishment, having an extensive semi-dry area which will be severely impacted by growing temperatures. Ultimately, the integrated model generates state- and municipal-level migration scenarios based on climate change impacts on the primary economic sectors and their articulations with other sectors. Results suggest that the predicted climate changes will impact severely the agriculture sector in the region, acting as a potential migration push factor to other regions in the country. Finally, we discuss how the increased vulnerability of some groups, particularly migrants, can be factored into Brazilian public policy and planning.     

An Analysis of Student Satisfaction: Full-Time vs. Part-Time Students

This paper examines how full-time or part-time status affects students’ level of satisfaction with their degree programs. For our analysis, we obtained data from a survey of graduate students. The survey was conducted at a public university in Spain from 2001 to 2004. The decision to undertake paid employment while studying emerges as one of the key determinants of student satisfaction. In particular, our findings indicate that students who hold a part-time job while studying are more likely to express less satisfaction with their college experience.     

Household Saving Behavior and the Influence of Family-Owned Business

This study focused on the lifecycle income objective of business-owning (farm and nonfarm) households. We hypothesized that the complex relationship between household and business management decisions had the potential to challenge predictions from standard household savings theory. Specifically, we tested for differences in saving behavior of these entrepreneurial households relative to the average US household. A limited dependent variable model was performed, keying in on the saving behavior and ability of household respondents in the Survey of Consumer Finances for 2007. The estimation results indicated that, along with standard demographic influences of savings models, households owning a farm or nonfarm business had a significantly higher likelihood of maintaining private saving in a given year. Our results highlight the necessity for future research on household saving behavior to account for the differing objectives and choice sets faced by households that own businesses when conducting analyses of household saving.     

The influence of FDA advisory information and black box warnings on individual use of prescription antidepressants

We examine how use of antidepressant medications is influenced by Food and Drug Administration (FDA) warnings about the increased risk of suicidality associated with pediatric antidepressant use. With individual-level data on antidepressant use from the Medical Expenditure Panel Survey, we consider whether consumer responses to FDA warnings differ among targeted (children) and non-targeted (adult) age-groups. Because the warning labels specifically mentioned new users, we examine separately the effects of the warnings on initiations of antidepressant therapy and on continued use of antidepressants. We find evidence consistent with reduced initiation of antidepressant use among the intended population of children, and that usage among children with more highly educated parents responded earlier to FDA information. However, we also find spillover effects of reduced initiation among the non-targeted population of adults. Overall, our results indicate that the FDA warning may have led consumers to perceive risks beyond those specifically mentioned.     

AD HOC MODEL BUILDING USING TIME-VARYING PARAMETER MODELS*

Decision support for managers and policy makers, such as required in planning and evaluation efforts, often requires ad hoc behavioral modeling to account for context-specific phenomena and to handle data limitations. This paper introduces a systematic approach useful for meeting these requirements in which time-varying parameter estimation plays an important role. A case study evaluating the impacts of public policy actions on residential natural gas conservation illustrates the approach.     

Applications and Implementation DECISION SUPPORT SYSTEMS: AN EMPIRICAL ASSESSMENT FOR DECISION MAKING

A laboratory experiment examined the effects of applying decision support system (DSS) technology to decision making in ill-structured problem environments under varying information conditions. Marketing executives participated in the experiment which investigated the effects of DSS availability, DSS training, and data availability on dependent variables that included: (1) the number of alternatives considered by a subject during decision making, (2) the period of time spent by a subject to complete the decision-making process, (3) the subject's perceived confidence in the decisions he or she had made, (4) the amount of data considered by a subject's during decision making, (5) the individual subject's decision processing, and (6) the subject's performance overall. Our results indicate that all three factors significantly affect the number of alternatives considered by subjects during the decision-making process. We therefore suggest that DSS training be coordinated with decision training in order to realize the potential of DSSs as described in the DSS literature.