American Indian/Alaska Native Elders: A Growing Demographic that Is Changing How We View Aging

Today, AIAN Elders are more actively engaged in their families and communities, encouraging the development of intergenerational programs, language and cultural revitalization, being stewards in research conducted in their communities, as well passing on their knowledge and experiences on how to live as healthy Native people. Elders have traditionally been quiet and observant of their environment, but the current and future cohorts of Elders are advocates, leaders, and culture bearers for their families and communities and they are now in positions of leadership. Western society acknowledges the value of traditional knowledge and AIAN Elders are viewed as exemplars of healthy aging and their lessons and experiences can be attributed to our own lives. This commentary highlights the paradigm shift in how society views older adults, specifically AIAN Elders and their role in health and wellbeing.     

Sequential Monte Carlo for rare event estimation

This paper discusses a novel strategy for simulating rare events and an associated Monte Carlo estimation of tail probabilities. Our method uses a system of interacting particles and exploits a Feynman-Kac representation of that system to analyze their fluctuations. Our precise analysis of the variance of a standard multilevel splitting algorithm reveals an opportunity for improvement. This leads to a novel method that relies on adaptive levels and produces, in the limit of an idealized version of the algorithm, estimates with optimal variance. The motivation for this theoretical work comes from problems occurring in watermarking and fingerprinting of digital contents, which represents a new field of applications of rare event simulation techniques. Some numerical results show performance close to the idealized version of our technique for these practical applications.     

Can Carbon Nanomaterials Improve CZTS Photovoltaic Devices? Evaluation of Performance and Impacts Using Integrated Life‐Cycle Assessment and Decision Analysis

In emergent photovoltaics, nanoscale materials hold promise for optimizing device characteristics; however, the related impacts remain uncertain, resulting in challenges to decisions on strategic investment in technology innovation. We integrate multi‐criteria decision analysis (MCDA) and life‐cycle assessment (LCA) results (LCA‐MCDA) as a method of incorporating values of a hypothetical federal acquisition manager into the assessment of risks and benefits of emerging photovoltaic materials. Specifically, we compare adoption of copper zinc tin sulfide (CZTS) devices with molybdenum back contacts to alternative devices employing graphite or graphene instead of molybdenum. LCA impact results are interpreted alongside benefits of substitution including cost reductions and performance improvements through application of multi‐attribute utility theory. To assess the role of uncertainty we apply Monte Carlo simulation and sensitivity analysis. We find that graphene or graphite back contacts outperform molybdenum under most scenarios and assumptions. The use of decision analysis clarifies potential advantages of adopting graphite as a back contact while emphasizing the importance of mitigating conventional impacts of graphene production processes if graphene is used in emerging CZTS devices. Our research further demonstrates that a combination of LCA and MCDA increases the usability of LCA in assessing product sustainability. In particular, this approach identifies the most influential assumptions and data gaps in the analysis and the areas in which either engineering controls or further data collection may be necessary.     

Vacant land conversion to community gardens: influences on generalist arthropod predators and biocontrol services in urban greenspaces

Due to economic decline and the recent rise in home foreclosure, many U.S. cities are faced with managing large acreages of vacant land. Interest in local food production on this land has the potential to dramatically reshape the composition of greenspace found within urban landscapes. This study examined how the conversion of vacant land to urban gardens and farms influenced arthropod generalist predator populations and their ability to support biocontrol services. We found that the abundance of Coccinellidae and Syrphidae, and the activity density of Carabidae, Formicidae, and Lycosidae were equivalent among vacant lot and urban garden sites. Dolichopodidae abundance and the activity density of Linyphiidae and Opiliones were reduced in urban gardens whereas Anthocoridae abundance and the activity density of Staphylinidae were greater within urban gardens relative to vacant lots. The biocontrol service supplied by generalist predators was measured using sentinel eggs (Helicoverpa zea (Noctuiidae)) and pupae (Sarcophaga bullata (Sarcophagidae) and Musca domestica (Muscidae)). We found no difference in the biocontrol of H. zea eggs or M. domestica pupae among the focal greenspaces. We found no difference in the removal of S. bullata pupae by predators in June 2010, whereas in August 2010 a greater proportion of pupae were removed in urban garden sites relative to vacant lots. Based on these findings, we discuss the potential of the urban landscape to support generalist predators and sustainable urban gardening and farming.     

Efficient Monte Carlo simulation via the generalized splitting method

We describe a new Monte Carlo algorithm for the consistent and unbiased estimation of multidimensional integrals and the efficient sampling from multidimensional densities. The algorithm is inspired by the classical splitting method and can be applied to general static simulation models. We provide examples from rare-event probability estimation, counting, and sampling, demonstrating that the proposed method can outperform existing Markov chain sampling methods in terms of convergence speed and accuracy.     

Does race matter? Assessing consumer discrimination in the secondary basketball card market

Sociologists continue to observe the ways race permeates America's social institutions, the institution of sport being no exception. Although researchers have explored customer racial discrimination via examinations of the secondary sports card market, only three studies have explored the phenomenon in the context of basketball, a sporting context with a higher proportion of non-White players than the baseball and football leagues that have been the primary focus to date. We explore the unique way race matters on the hardwood by employing a methodological approach that previously has been used to study card collecting in other contexts. Data were obtained for 215 retired players and their rookie cards. Controlling for other factors, to include career performance, position, and card scarcity, the results reveal no direct effect of race on card values, but there is an interaction effect between race and Hall of Fame status that impacts card prices. The potential source and implications of this interaction are discussed as well as suggestions for future research.     

Improved cross-entropy method for estimation

The cross-entropy (CE) method is an adaptive importance sampling procedure that has been successfully applied to a diverse range of complicated simulation problems. However, recent research has shown that in some high-dimensional settings, the likelihood ratio degeneracy problem becomes severe and the importance sampling estimator obtained from the CE algorithm becomes unreliable. We consider a variation of the CE method whose performance does not deteriorate as the dimension of the problem increases. We then illustrate the algorithm via a high-dimensional estimation problem in risk management.     

Estimation for a first-order bifurcating autoregressive process with heavy-tail innovations

Asymptotics of an alternative extreme-value estimator for the autocorrelation parameter in a first-order bifurcating autoregressive (BAR) process with non-gaussian innovations are derived. This contrasts with traditional estimators whose asymptotic behavior depends on the central part of the innovation distribution. Within any BAR model, the main concern is addressing the complex dependency between generations. The inability of traditional methods to handle this dependency motivated an alternative procedure. With the combination of an extreme-value approach and a clever blocking argument, the dependency issue within the BAR process was resolved, which in turn allowed us to derive the limiting distribution for the proposed estimator through the use of regular variation and non-stationary point processes. Finally, the implications of our extreme-value approach are discussed with an extensive simulation study that not only assesses the reliability of our proposed estimate but also presents the findings for a new estimator of an unknown location parameter θ and its implications.     

Bioaccessibility and Risk of Exposure to Metals and SVOCs in Artificial Turf Field Fill Materials and Fibers

To reduce maintenance costs, municipalities and schools are starting to replace natural grass fields with a new generation synthetic turf. Unlike Astro‐Turf, which was first introduced in the 1960s, synthetic field turf provides more cushioning to athletes. Part of this cushioning comes from materials like crumb rubber infill, which is manufactured from recycled tires and may contain a variety of chemicals. The goal of this study was to evaluate potential exposures from playing on artificial turf fields and associated risks to trace metals, semi‐volatile organic compounds (SVOCs), and polycyclic aromatic hydrocarbons (PAHs) by examining typical artificial turf fibers (n = 8), different types of infill (n = 8), and samples from actual fields (n = 7). Three artificial biofluids were prepared, which included: lung, sweat, and digestive fluids. Artificial biofluids were hypothesized to yield a more representative estimation of dose than the levels obtained from total extraction methods. PAHs were routinely below the limit of detection across all three biofluids, precluding completion of a meaningful risk assessment. No SVOCs were identified at quantifiable levels in any extracts based on a match of their mass spectrum to compounds that are regulated in soil. The metals were measurable but at concentrations for which human health risk was estimated to be low. The study demonstrated that for the products and fields we tested, exposure to infill and artificial turf was generally considered de minimus, with the possible exception of lead for some fields and materials.     

Misestimating Betting Behavior: The Role of Negative Asymmetries in Emotional Self Prediction

This paper addresses the role of negative asymmetries in emotional self-prediction by looking at the extent to which individuals misestimate their own betting behavior in sequential gambles. In a series of three experimental studies, we demonstrate that losses lead to higher than planned bets whereas bets are on average carried over after gains. Such asymmetric deviations from the plan emerge (1) when monetary and non-monetary incentives are used, and (2) when participants face fair and unfair gambles. The asymmetry is based on people’s inability to predict how much the negative emotions generated by a bad experience (e.g. the loss) will influence them to put more effort (e.g. bet more) than planned in an attempt to re-establish a homeostatic state in the prospect of a good experience (e.g. winning).