A spanning heuristic for the unordered and ordered matching identification problem

The matching identification problem (MIP) is a combinatoric search problem related to the fields of learning from examples, boolean functions, and knowledge acquisition. The MIP involves identifying a single “goal” item from a large set of items. Because there is commonly a cost associated with evaluating each guess, the goal item should be identified in as few guesses as possible. As in most search problems, the items have a similar structure, which allows an evaluation of each guessed item. In other words, each guessed item elicits partial information about the goal item, i.e. how similar the guess is to the goal. With this information the goal is more quickly identified.The unordered MIP has been studied by Mehrez and Steinberg (ORSA J. Comput. 7 (1995) 211) in which they proposed two different types of algorithms. The purpose of the present paper is to suggest an improved Spanning Heuristic algorithm. Its improvement increases as the problem size increases. Further results and comparisons are derived for the unordered and ordered cases.This research shows that when the search space is very large, it is better to inquire from items that are known not to be the goal (they have been ruled out by previous guesses), for the purpose of acquiring more information about the goal. As the search space is narrowed, it is better to guess items that have not been ruled out.     

Using a capabilities approach to understand poverty and social exclusion of psychiatric survivors

The purpose of this project is to better understand poverty and social exclusion of psychiatric survivors using a capabilities approach to social justice as part of a larger mixed-methods longitudinal study (N=380) in Ontario, Canada. Using thematic coding, four themes emerged: poverty, ‘You just try to survive’; stigma, ‘People treat you like trash’; belonging, ‘You feel like you don’t belong’; and shared concern and advocacy, ‘Everyone deserves housing’. This analysis provides a deeper understanding of poverty and other social determinants of experiences of psychiatric survivors, including the synergism of poverty and social exclusion.     

Testofen,a specialised Trigonella foenum-graecum seed extract reduces age-related symptoms of androgen decrease,increases testosterone levels and improves sexual function in healthy aging males in a double-blind randomised clinical study

This study examined the effect of Testofen, a specialised Trigonella foenum-graecum seed extract on the symptoms of possible androgen deficiency, sexual function and serum androgen concentrations in healthy aging males. This was a double-blind, randomised, placebo-controlled trial involving 120 healthy men aged between 43 and 70 years of age. The active treatment was standardised Trigonella foenum-graecum seed extract at a dose of 600?mg/day for 12 weeks. The primary outcome measure was the change in the Aging Male Symptom questionnaire (AMS), a measure of possible androgen deficiency symptoms; secondary outcome measures were sexual function and serum testosterone. There was a significant decrease in AMS score over time and between the active and placebo groups. Sexual function improved, including number of morning erections and frequency of sexual activity. Both total serum testosterone and free testosterone increased compared to placebo after 12 weeks of active treatment. Trigonella foenum-graecum seed extract is a safe and effective treatment for reducing symptoms of possible androgen deficiency, improves sexual function and increases serum testosterone in healthy middle-aged and older men.     

Building Virtual Age-Friendly Communities in Minecraft

A key theme of Age-Friendly Honolulu’s initiative is intergenerational exchange. The initiative believes that youth need to be aware of aging issues, demographic change, and think critically about the potential impact on their lives. The goal of the Age-Friendly Honolulu Youth Engagement Initiative is to teach youth about the role of the built environment and community features in promoting active aging and engagement among older adults. This article describes a new program in the field that teaches youth and older adults to assess the built environment and then use design thinking and Minecraft (a popular video game in which players use 3-D blocks to create virtual lands) to develop and envision ideas to improve the livability of their neighborhood.     

A characterization of linearizable instances of the quadratic minimum spanning tree problem

We investigate special cases of the quadratic minimum spanning tree problem (QMSTP) on a graph \(G=(V,E)\) that can be solved as a linear minimum spanning tree problem. We give a characterization of such problems when G is a complete graph, which is the standard case in the QMSTP literature. We extend our characterization to a larger class of graphs that include complete bipartite graphs and cactuses, among others. Our characterization can be verified in \(O(|E|^2)\) time. In the case of complete graphs and when the cost matrix is given in factored form, we show that our characterization can be verified in O(|E|) time. Related open problems are also indicated.     

Open Order Rescheduling in Job Shops with Demand Uncertainty: A Simulation Study

This paper addresses the problem of open order rescheduling in a job shop. Results are reported of experiments conducted in a simulation model of an 8-machine job shop. Four different order updating policies are examined. The due-date process is modeled to include several realistic features about the pattern of due-date variability. These features are parameterized and tested at several levels. Tardiness results indicate that open order rescheduling is beneficial only when allowances are loosely set. The results indicate that inventory performance is improved by order rescheduling, particularly in cases when due dates are revised to earlier times than originally forecast.     

Global Robustness with Respect to the Loss Function and the Prior

We propose a class [I,S] of loss functions for modeling the imprecise preferences of the decision maker in Bayesian Decision Theory. This class is built upon two extreme loss functions I and S which reflect the limited information about the loss function. We give an approximation of the set of Bayes actions for every loss function in [I,S] and every prior in a mixture class; if the decision space is a subset of , we obtain the exact set.