The title “Regents’ Professor” is the highest faculty honor awarded at Arizona State University. It is conferred on ASU faculty who have made pioneering contributions in their areas of expertise, who have achieved a sustained level of distinction, and who enjoy national and international recognition for these accomplishments. This collection contains primarily open access works by ASU Regents' Professors.

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Description
Background
Weight gain during the childbearing years and failure to lose pregnancy weight after birth contribute to the development of obesity in postpartum Latinas.
Methods
Madres para la Salud [Mothers for Health] was a 12-month, randomized controlled trial exploring a social support intervention with moderate-intensity physical activity (PA) seeking to effect changes in

Background
Weight gain during the childbearing years and failure to lose pregnancy weight after birth contribute to the development of obesity in postpartum Latinas.
Methods
Madres para la Salud [Mothers for Health] was a 12-month, randomized controlled trial exploring a social support intervention with moderate-intensity physical activity (PA) seeking to effect changes in body fat, fat tissue inflammation, and depression symptoms in sedentary postpartum Latinas. This report describes the efficacy of the Madres intervention.
Results
The results show that while social support increased during the active intervention delivery, it declined to pre-intervention levels by the end of the intervention. There were significant achievements in aerobic and total steps across the 12 months of the intervention, and declines in body adiposity assessed with bioelectric impedance.
Conclusions
Social support from family and friends mediated increases in aerobic PA resulting in decrease in percent body fat.
Created2014-09-19
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Description
This article reviews the range of delivery platforms that have been developed for the PySAL open source Python library for spatial analysis. This includes traditional desktop software (with a graphical user interface, command line or embedded in a computational notebook), open spatial analytics middleware, and web, cloud and distributed open

This article reviews the range of delivery platforms that have been developed for the PySAL open source Python library for spatial analysis. This includes traditional desktop software (with a graphical user interface, command line or embedded in a computational notebook), open spatial analytics middleware, and web, cloud and distributed open geospatial analytics for decision support. A common thread throughout the discussion is the emphasis on openness, interoperability, and provenance management in a scientific workflow. The code base of the PySAL library provides the common computing framework underlying all delivery mechanisms.
ContributorsRey, Sergio (Author) / Anselin, Luc (Author) / Li, Xun (Author) / Pahle, Robert (Author) / Laura, Jason (Author) / Li, Wenwen (Author) / Koschinsky, Julia (Author) / College of Liberal Arts and Sciences (Contributor) / School of Geographical Sciences and Urban Planning (Contributor) / Computational Spatial Science (Contributor)
Created2015-06-01
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Description
Estimating and projecting population trends using population viability analysis (PVA) are central to identifying species at risk of extinction and for informing conservation management strategies. Models for PVA generally fall within two categories, scalar (count-based) or matrix (demographic). Model structure, process error, measurement error, and time series length all have

Estimating and projecting population trends using population viability analysis (PVA) are central to identifying species at risk of extinction and for informing conservation management strategies. Models for PVA generally fall within two categories, scalar (count-based) or matrix (demographic). Model structure, process error, measurement error, and time series length all have known impacts in population risk assessments, but their combined impact has not been thoroughly investigated. We tested the ability of scalar and matrix PVA models to predict percent decline over a ten-year interval, selected to coincide with the IUCN Red List criterion A. 3, using data simulated for a hypothetical, short-lived organism with a simple life-history and for a threatened snail, Tasmaphena lamproides. PVA performance was assessed across different time series lengths, population growth rates, and levels of process and measurement error. We found that the magnitude of effects of measurement error, process error, and time series length, and interactions between these, depended on context. We found that high process and measurement error reduced the reliability of both models in predicted percent decline. Both sources of error contributed strongly to biased predictions, with process error tending to contribute to the spread of predictions more than measurement error. Increasing time series length improved precision and reduced bias of predicted population trends, but gains substantially diminished for time series lengths greater than 10-15 years. The simple parameterization scheme we employed contributed strongly to bias in matrix model predictions when both process and measurement error were high, causing scalar models to exhibit similar or greater precision and lower bias than matrix models. Our study provides evidence that, for short-lived species with structured but simple life histories, short time series and simple models can be sufficient for reasonably reliable conservation decision-making, and may be preferable for population projections when unbiased estimates of vital rates cannot be obtained.
Created2015-07-15
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Description

Aim
To establish a chronology for late Quaternary avian extinction, extirpation and persistence in the Bahamas, thereby testing the relative roles of climate change and human impact as causes of extinction.
Location
Great Abaco Island (Abaco), Bahamas, West Indies.
Methods
We analysed the resident bird community as sampled by Pleistocene (> 11.7 ka) and Holocene

Aim
To establish a chronology for late Quaternary avian extinction, extirpation and persistence in the Bahamas, thereby testing the relative roles of climate change and human impact as causes of extinction.
Location
Great Abaco Island (Abaco), Bahamas, West Indies.
Methods
We analysed the resident bird community as sampled by Pleistocene (> 11.7 ka) and Holocene (< 11.7 ka) fossils. Each species was classified as extinct (lost globally), extirpated (gone from Abaco but persists elsewhere), or extant (still resident on Abaco). We compared patterns of extinction, extirpation and persistence to independent estimates of climate and sea level for glacial (late Pleistocene) and interglacial (Holocene) times.
Results
Of 45 bird species identified in Pleistocene fossils, 25 (56%) no longer occur on Abaco (21 extirpated, 4 extinct). Of 37 species recorded in Holocene deposits, 15 (14 extirpated, 1 extinct; total 41%) no longer exist on Abaco. Of the 30 extant species, 12 were recovered as both Pleistocene and Holocene fossils, as were 9 of the 30 extirpated or extinct species. Most of the extinct or extirpated species that were only recorded from Pleistocene contexts are characteristic of open habitats (pine woodlands or grasslands); several of the extirpated species are currently found only where winters are cooler than in the modern or Pleistocene Bahamas. In contrast, most of the extinct or extirpated species recorded from Holocene contexts are habitat generalists.
Main conclusions
The fossil evidence suggests two main times of late Quaternary avian extirpation and extinction in the Bahamas. The first was during the Pleistocene–Holocene transition (PHT; 15–9 ka) and was fuelled by climate change and associated changes in sea level and island area. The second took place during the late Holocene (< 4 ka, perhaps primarily < 1 ka) and can be attributed to human impact. Although some species lost during the PHT are currently found where climates are cooler and drier than in the Bahamas today, a taxonomically and ecologically diverse set of species persisted through that major climate change but did not survive the past millennium of human presence.

Created2015-03-01
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Description
We have fabricated a high mobility device, composed of a monolayer graphene flake sandwiched between two sheets of hexagonal boron nitride. Conductance fluctuations as functions of a back gate voltage and magnetic field were obtained to check for ergodicity. Non-linear dynamics concepts were used to study the nature of these

We have fabricated a high mobility device, composed of a monolayer graphene flake sandwiched between two sheets of hexagonal boron nitride. Conductance fluctuations as functions of a back gate voltage and magnetic field were obtained to check for ergodicity. Non-linear dynamics concepts were used to study the nature of these fluctuations. The distribution of eigenvalues was estimated from the conductance fluctuations with Gaussian kernels and it indicates that the carrier motion is chaotic at low temperatures. We argue that a two-phase dynamical fluid model best describes the transport in this system and can be used to explain the violation of the so-called ergodic hypothesis found in graphene.
Contributorsda Cunha, C. R. (Author) / Mineharu, M. (Author) / Matsunaga, M. (Author) / Matsumoto, N. (Author) / Chuang, C. (Author) / Ochiai, Y. (Author) / Kim, G.-H. (Author) / Watanabe, K. (Author) / Taniguchi, T. (Author) / Ferry, David (Author) / Aoki, N. (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School of Electrical, Computer and Energy Engineering (Contributor)
Created2016-09-09
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Description
Background
Obese Latino adolescents are disproportionately impacted by insulin resistance and type 2 diabetes. Prediabetes is an intermediate stage in the pathogenesis of type 2 diabetes and represents a critical opportunity for intervention. However, to date, no diabetes prevention studies have been conducted in obese Latino youth with prediabetes, a highly

Background
Obese Latino adolescents are disproportionately impacted by insulin resistance and type 2 diabetes. Prediabetes is an intermediate stage in the pathogenesis of type 2 diabetes and represents a critical opportunity for intervention. However, to date, no diabetes prevention studies have been conducted in obese Latino youth with prediabetes, a highly vulnerable and underserved group. Therefore, we propose a randomized-controlled trial to test the short-term (6-month) and long-term (12-month) efficacy of a culturally-grounded, lifestyle intervention, as compared to usual care, for improving glucose tolerance and reducing diabetes risk in 120 obese Latino adolescents with prediabetes.
Methods
Participants will be randomized to a lifestyle intervention or usual care group. Participants in the intervention group will attend weekly nutrition and wellness sessions and physical activity sessions twice a week for six months, followed by three months of booster sessions. The overall approach of the intervention is framed within a multilevel Ecodevelopmental model that leverages community, family, peer, and individual factors during the critical transition period of adolescence. The intervention is also guided by Social Cognitive Theory and employs key behavioral modification strategies to enhance self-efficacy and foster social support for making and sustaining healthy behavior changes. We will test intervention effects on quality of life, explore the potential mediating effects of changes in body composition, total, regional, and organ fat on improving glucose tolerance and increasing insulin sensitivity, and estimate the initial incremental cost effectiveness of the intervention as compared with usual care for improving glucose tolerance.
Discussion
The proposed trial builds upon extant collaborations of a transdisciplinary team of investigators working in concert with local community agencies to address critical gaps in how diabetes prevention interventions for obese Latino youth are developed, implemented and evaluated. This innovative approach is an essential step in the development of scalable, cost-effective, solution oriented programs to prevent type 2 diabetes in this and other populations of high-risk youth.
Created2017-03-16
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Description
Evolving Earth observation and change detection techniques enable the automatic identification of Land Use and Land Cover Change (LULCC) over a large extent from massive amounts of remote sensing data. It at the same time poses a major challenge in effective organization, representation and modeling of such information. This study

Evolving Earth observation and change detection techniques enable the automatic identification of Land Use and Land Cover Change (LULCC) over a large extent from massive amounts of remote sensing data. It at the same time poses a major challenge in effective organization, representation and modeling of such information. This study proposes and implements an integrated computational framework to support the modeling, semantic and spatial reasoning of change information with regard to space, time and topology. We first proposed a conceptual model to formally represent the spatiotemporal variation of change data, which is essential knowledge to support various environmental and social studies, such as deforestation and urbanization studies. Then, a spatial ontology was created to encode these semantic spatiotemporal data in a machine-understandable format. Based on the knowledge defined in the ontology and related reasoning rules, a semantic platform was developed to support the semantic query and change trajectory reasoning of areas with LULCC. This semantic platform is innovative, as it integrates semantic and spatial reasoning into a coherent computational and operational software framework to support automated semantic analysis of time series data that can go beyond LULC datasets. In addition, this system scales well as the amount of data increases, validated by a number of experimental results. This work contributes significantly to both the geospatial Semantic Web and GIScience communities in terms of the establishment of the (web-based) semantic platform for collaborative question answering and decision-making.
Created2016-10-25
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Description
Urban economic modeling and effective spatial planning are critical tools towards achieving urban sustainability. However, in practice, many technical obstacles, such as information islands, poor documentation of data and lack of software platforms to facilitate virtual collaboration, are challenging the effectiveness of decision-making processes. In this paper, we report on

Urban economic modeling and effective spatial planning are critical tools towards achieving urban sustainability. However, in practice, many technical obstacles, such as information islands, poor documentation of data and lack of software platforms to facilitate virtual collaboration, are challenging the effectiveness of decision-making processes. In this paper, we report on our efforts to design and develop a geospatial cyberinfrastructure (GCI) for urban economic analysis and simulation. This GCI provides an operational graphic user interface, built upon a service-oriented architecture to allow (1) widespread sharing and seamless integration of distributed geospatial data; (2) an effective way to address the uncertainty and positional errors encountered in fusing data from diverse sources; (3) the decomposition of complex planning questions into atomic spatial analysis tasks and the generation of a web service chain to tackle such complex problems; and (4) capturing and representing provenance of geospatial data to trace its flow in the modeling task. The Greater Los Angeles Region serves as the test bed. We expect this work to contribute to effective spatial policy analysis and decision-making through the adoption of advanced GCI and to broaden the application coverage of GCI to include urban economic simulations.
Created2013-05-21
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Description
Despite their low cost and high nutrient density, the contribution of eggs to nutrient intake and dietary quality among Mexican-American postpartum women has not been evaluated. Nutrient intake and dietary quality, as assessed by the Healthy Eating Index 2010 (HEI-2010), were measured in habitually sedentary overweight/obese (body mass index (BMI)

Despite their low cost and high nutrient density, the contribution of eggs to nutrient intake and dietary quality among Mexican-American postpartum women has not been evaluated. Nutrient intake and dietary quality, as assessed by the Healthy Eating Index 2010 (HEI-2010), were measured in habitually sedentary overweight/obese (body mass index (BMI) = 29.7 ± 3.5 kg/m[superscript 2]) Mexican-American postpartum women (28 ± 6 years) and compared between egg consumers (n = 82; any egg intake reported in at least one of three 24-h dietary recalls) and non-consumers (n = 57). Egg consumers had greater intake of energy (+808 kJ (193 kcal) or 14%; p = 0.033), protein (+9 g or 17%; p = 0.031), total fat (+9 g or 19%; p = 0.039), monounsaturated fat (+4 g or 24%; p = 0.020), and several micronutrients than non-consumers. Regarding HEI-2010 scores, egg consumers had a greater total protein foods score than non-consumers (4.7 ± 0.7 vs. 4.3 ± 1.0; p = 0.004), and trends for greater total fruit (2.4 ± 1.8 vs. 1.9 ± 1.7; p = 0.070) and the total composite HEI-2010 score (56.4 ± 12.6 vs. 52.3 ± 14.4; p = 0.082). Findings suggest that egg intake could contribute to greater nutrient intake and improved dietary quality among postpartum Mexican-American women. Because of greater energy intake among egg consumers, recommendations for overweight/obese individuals should include avoiding excessive energy intake and incorporating eggs to a nutrient-dense, fiber-rich dietary pattern.
Created2015-10-02
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Description
A species’ response to climate change depends on the interaction of biotic and abiotic factors that define future habitat suitability and species’ ability to migrate or adapt. The interactive effects of processes such as fire, dispersal, and predation have not been thoroughly addressed in the climate change literature. Our objective

A species’ response to climate change depends on the interaction of biotic and abiotic factors that define future habitat suitability and species’ ability to migrate or adapt. The interactive effects of processes such as fire, dispersal, and predation have not been thoroughly addressed in the climate change literature. Our objective was to examine how life history traits, short-term global change perturbations, and long-term climate change interact to affect the likely persistence of an oak species - Quercus engelmannii (Engelmann oak). Specifically, we combined dynamic species distribution models, which predict suitable habitat, with stochastic, stage-based metapopulation models, which project population trajectories, to evaluate the effects of three global change factors – climate change, land use change, and altered fire frequency – emphasizing the roles of dispersal and seed predation. Our model predicted dramatic reduction in Q. engelmannii abundance, especially under drier climates and increased fire frequency. When masting lowers seed predation rates, decreased masting frequency leads to large abundance decreases. Current rates of dispersal are not likely to prevent these effects, although increased dispersal could mitigate population declines. The results suggest that habitat suitability predictions by themselves may under-estimate the impact of climate change for other species and locations.
ContributorsConlisk, Erin (Author) / Lawson, Dawn (Author) / Syphard, Alexandra D. (Author) / Franklin, Janet (Author) / Flint, Lorraine (Author) / Flint, Alan (Author) / Regan, Helen M. (Author) / College of Liberal Arts and Sciences (Contributor) / School of Geographical Sciences and Urban Planning (Contributor)
Created2012-05-18