ASU Scholarship Showcase

Background: GoGirlGo! (GGG) is designed to increase girls’ physical activity (PA) using a health behavior and PA-based curriculum and is widely available for free to afterschool programs across the nation. However, GGG has not been formally evaluated. The purpose of this pilot study was to evaluate the effectiveness of the GGG curricula to improve PA, and self-efficacy for and enjoyment of PA in elementary aged girls (i.e., 5-13 years).

Methods: Nine afterschool programs were recruited to participate in the pilot (within subjects repeated measures design). GGG is a 12-week program, with a once a week, one-hour lesson with 30 minutes of education and 30 minutes of PA). Data collection occurred at baseline, mid (twice), post, and at follow-up (3-months after the intervention ended). PA was assessed via accelerometry at each time point. Self-efficacy for and enjoyment of PA was measured using the Self-Efficacy Scale and the Short-PA enjoyment scale and was assessed at baseline, post, and follow-up. Fidelity was assessed at midpoint.

Results: Across all age groups there was a statistically significant increase in PA. Overall, on days GGG was offered girls accumulated an average of 11 minutes of moderate-to-vigorous PA compared to 8 minutes during non-GGG days. There was a statistically significant difference in girls’ self-efficacy for PA reported between baseline and post, which was maintained at follow-up. An improvement in enjoyment of PA for girls was found between baseline and follow-up. According to fidelity assessment, 89% of the activities within the curriculum were completed each lesson. Girls appeared to respond well to the curriculum but girls 5-7 years had difficulties paying attention and understanding discussion questions.

Conclusions: Even though there were statistically significant differences in self-efficacy for PA and enjoyment of PA, minimal increases in girls’ PA were observed. GGG curricula improvements are warranted. Future GGG programming should explore offering GGG every day, modifying activities so that they are moderate-to-vigorous in intensity, and providing additional trainings that allow staff to better implement PA and improve behavior management techniques. With modifications, GGG could provide a promising no-cost curriculum that afterschool programs may implement to help girls achieve recommendations for PA.

Theory suggests that human behavior has implications for disease spread. We examine the hypothesis that individuals engage in voluntary defensive behavior during an epidemic. We estimate the number of passengers missing previously purchased flights as a function of concern for swine flu or A/H1N1 influenza using 1.7 million detailed flight records, Google Trends, and the World Health Organization's FluNet data. We estimate that concern over “swine flu,” as measured by Google Trends, accounted for 0.34% of missed flights during the epidemic. The Google Trends data correlates strongly with media attention, but poorly (at times negatively) with reported cases in FluNet. Passengers show no response to reported cases. Passengers skipping their purchased trips forwent at least $50 M in travel related benefits. Responding to actual cases would have cut this estimate in half. Thus, people appear to respond to an epidemic by voluntarily engaging in self-protection behavior, but this behavior may not be responsive to objective measures of risk. Clearer risk communication could substantially reduce epidemic costs. People undertaking costly risk reduction behavior, for example, forgoing nonrefundable flights, suggests they may also make less costly behavior adjustments to avoid infection. Accounting for defensive behaviors may be important for forecasting epidemics, but linking behavior with epidemics likely requires consideration of risk communication.

With the advent of high-dimensional stored big data and streaming data, suddenly machine learning on a very large scale has become a critical need. Such machine learning should be extremely fast, should scale up easily with volume and dimension, should be able to learn from streaming data, should automatically perform dimension reduction for high-dimensional data, and should be deployable on hardware. Neural networks are well positioned to address these challenges of large scale machine learning. In this paper, we present a method that can effectively handle large scale, high-dimensional data. It is an online method that can be used for both streaming and large volumes of stored big data. It primarily uses Kohonen nets, although only a few selected neurons (nodes) from multiple Kohonen nets are actually retained in the end; we discard all Kohonen nets after training. We use Kohonen nets both for dimensionality reduction through feature selection and for building an ensemble of classifiers using single Kohonen neurons. The method is meant to exploit massive parallelism and should be easily deployable on hardware that implements Kohonen nets. Some initial computational results are presented.

A significant challenge of our time is conserving biological diversity while maintaining economic development and cultural values. The United Nations Educational, Scientific and Cultural Organization has established biosphere reserves within its Man and the Biosphere program as a model means for accomplishing this very challenge. The East Carpathians Biosphere Reserve (ECBR), spreading across Poland, Slovakia, and Ukraine, represents a large social-ecological system (SES) that has been protected under the biosphere reserve designation since 1998. We have explored its successes and failures in improving human livelihoods while safeguarding its ecosystems. The SES framework, which includes governance system, actors, resources, and external influences, was used as a frame of analysis. The outcomes of this protected area have been mixed; its creation led to national and international collaboration, yet some actor groups remain excluded. Implementation of protocols arising from the Carpathian Convention has been slow, while deforestation, hunting, erosion, temperature extremes, and changes in species behavior remain significant threats but have also been factors in ecological adaptation. The loss of cultural links and traditional knowledge has also been significant. Nevertheless, this remains a highly biodiverse area. Political barriers and institutional blockages will have to be removed to ensure this reserve fulfills its role as a model region for international collaboration and capacity building. These insights drawn from the ECBR demonstrate that biosphere reserves are indeed learning sites for sustainable development and that this case is exemplary in illustrating the challenges, but more importantly, the opportunities that arise when ensuring parallel care and respect for people and ecosystems through the model of transboundary protected areas around the world.

Based on considerable neurophysiological evidence, Roy (2012) proposed the theory that localist representation is widely used in the brain, starting from the lowest levels of processing. Grandmother cells are a special case of localist representation. In this article, I present the theory that grandmother cells are also widely used in the brain. To support the proposed theory, I present neurophysiological evidence and an analysis of the concept of grandmother cells. Konorski (1967) first predicted the existence of grandmother cells (he called them “gnostic” neurons) - single neurons that respond to complex stimuli such as faces, hands, expressions, objects, and so on. The term “grandmother cell” was introduced by Jerry Lettvin in 1969 (Barlow, 1995).

Background: In the USA, stillbirth (in utero fetal death ≥20 weeks gestation) is a major public health issue. Women who experience stillbirth, compared to women with live birth, have a nearly sevenfold increased risk of a positive screen for post-traumatic stress disorder (PTSD) and a fourfold increased risk of depressive symptoms. Because the majority of women who have experienced the death of their baby become pregnant within 12–18 months and the lack of intervention studies conducted within this population, novel approaches targeting physical and mental health, specific to the needs of this population, are critical. Evidence suggests that yoga is efficacious, safe, acceptable, and cost-effective for improving mental health in a variety of populations, including pregnant and postpartum women. To date, there are no known studies examining online-streaming yoga as a strategy to help mothers cope with PTSD symptoms after stillbirth.

Methods: The present study is a two-phase randomized controlled trial. Phase 1 will involve (1) an iterative design process to develop the online yoga prescription for phase 2 and (2) qualitative interviews to identify cultural barriers to recruitment in non-Caucasian women (i.e., predominately Hispanic and/or African American) who have experienced stillbirth (N = 5). Phase 2 is a three-group randomized feasibility trial with assessments at baseline, and at 12 and 20 weeks post-intervention. Ninety women who have experienced a stillbirth within 6 weeks to 24 months will be randomized into one of the following three arms for 12 weeks: (1) intervention low dose (LD) = 60 min/week online-streaming yoga (n = 30), (2) intervention moderate dose (MD) = 150 min/week online-streaming yoga (n = 30), or (3) stretch and tone control (STC) group = 60 min/week of stretching/toning exercises (n = 30).

Discussion: This study will explore the feasibility and acceptability of a 12-week, home-based, online-streamed yoga intervention, with varying doses among mothers after a stillbirth. If feasible, the findings from this study will inform a full-scale trial to determine the effectiveness of home-based online-streamed yoga to improve PTSD. Long-term, health care providers could use online yoga as a non-pharmaceutical, inexpensive resource for stillbirth aftercare.

Protected areas are a cornerstone of biodiversity conservation, and increasingly, conservation science is integrating ecological and social considerations in park management. Indeed, both social and ecological factors need to be considered to understand processes that lead to changes in environmental conditions. Here, we use a social-ecological systems lens to examine changes in governance through time in an extensive regional protected area network, the Great Barrier Reef Marine Park. We studied the peer-reviewed and nonpeer-reviewed literature to develop an understanding of governance of the Great Barrier Reef Marine Park and its management changes through time. In particular, we examined how interacting and changing property rights, as designated by the evolving marine protected area network and other institutional changes (e.g., fisheries management), defined multiple goods and ecosystem services and altered who could benefit from them.

The rezoning of the Great Barrier Reef Marine Park in 2004 substantially altered the types and distribution of property rights and associated benefits from ecosystem goods and services. Initially, common-pool resources were enjoyed as common and private benefits at the expense of public goods (overexploited fisheries and reduced biodiversity and ecosystem health). The rezoning redefined the available goods and benefits and who could benefit, prioritizing public goods and benefits (i.e., biodiversity conservation), and inducing private costs (through reduced fishing). We also found that the original conceptualization of the step-wise progression of property rights from user to owner oversimplifies property rights based on its division into operational and collective-choice rule-making levels. Instead, we suggest that a diversity of available management tools implemented simultaneously can result in interactions that are seldom fully captured by the original conceptualization of the bundling of property rights. Understanding the complexities associated with overlapping property rights and multiple goods and ecosystem services, particularly within large-scale systems, can help elucidate the source and nature of some of the governance challenges that large protected areas are facing.

This study is an attempt to use group information collected on climate change from farmers in eastern Uttar Pradesh, India to address a key question related to climate change policy: How to encourage farmers to adapt to climate change? First, we investigate farmers’ perception of and adaptation to climate change using content analysis and group information. The findings are then compared with climatic and agriculture information collected through secondary sources. Results suggest that though farmers are aware of long-term changes in climatic factors (temperature and rainfall, for example), they are unable to identify these changes as climate change. Farmers are also aware of risks generated by climate variability and extreme climatic events. However, farmers are not taking concrete steps in dealing with perceived climatic changes, although we find out that farmers are changing their agricultural and farming practices. These included changing sowing and harvesting timing, cultivation of crops of short duration varieties, inter-cropping, changing cropping pattern, investment in irrigation, and agroforestry. Note that these changes may be considered as passive response or adaptation strategies to climate change. Perhaps farmers are implicitly taking initiatives to adapt climate change. Finally, the paper suggests some policy interventions to scale up adaptation to climate change in Indian agriculture.

There is an increasing demand in higher education institutions for training in complex environmental problems. Such training requires a careful mix of conventional methods and innovative solutions, a task not always easy to accomplish. In this paper we review literature on this theme, highlight relevant advances in the pedagogical literature, and report on some examples resulting from our recent efforts to teach complex environmental issues. The examples range from full credit courses in sustainable development and research methods to project-based and in-class activity units. A consensus from the literature is that lectures are not sufficient to fully engage students in these issues. A conclusion from the review of examples is that problem-based and project-based, e.g., through case studies, experiential learning opportunities, or real-world applications, learning offers much promise. This could greatly be facilitated by online hubs through which teachers, students, and other members of the practitioner and academic community share experiences in teaching and research, the way that we have done here.

Adaptive comanagement endeavors to increase knowledge and responsiveness in the face of uncertainty and complexity. However, when collaboration between agency and nonagency stakeholders is mandated, rigid institutions may hinder participation and ecological outcomes. In this case study we analyzed qualitative data to understand how participants perceive strengths and challenges within an emerging adaptive comanagement in the Agua Fria Watershed in Arizona, USA that utilizes insight and personnel from a long-enduring comanagement project, Las Cienegas. Our work demonstrates that general lessons and approaches from one project may be transferable, but particular institutions, management structures, or projects must be place-specific. As public agencies establish and expand governance networks throughout the western United States, our case study has shed light on how to maintain a shared vision and momentum within an inherently murky and shared decision-making environment.