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- Creators: Ira A. Fulton Schools of Engineering
- Member of: ASU Regents' Professors Open Access Works
Description
Background
Increasing empirical evidence supports associations between neighborhood environments and physical activity. However, since most studies were conducted in a single country, particularly western countries, the generalizability of associations in an international setting is not well understood. The current study examined whether associations between perceived attributes of neighborhood environments and physical activity differed by country.
Methods
Population representative samples from 11 countries on five continents were surveyed using comparable methodologies and measurement instruments. Neighborhood environment × country interactions were tested in logistic regression models with meeting physical activity recommendations as the outcome, adjusted for demographic characteristics. Country-specific associations were reported.
Results
Significant neighborhood environment attribute × country interactions implied some differences across countries in the association of each neighborhood attribute with meeting physical activity recommendations. Across the 11 countries, land-use mix and sidewalks had the most consistent associations with physical activity. Access to public transit, bicycle facilities, and low-cost recreation facilities had some associations with physical activity, but with less consistency across countries. There was little evidence supporting the associations of residential density and crime-related safety with physical activity in most countries.
Conclusion
There is evidence of generalizability for the associations of land use mix, and presence of sidewalks with physical activity. Associations of other neighborhood characteristics with physical activity tended to differ by country. Future studies should include objective measures of neighborhood environments, compare psychometric properties of reports across countries, and use better specified models to further understand the similarities and differences in associations across countries.
Increasing empirical evidence supports associations between neighborhood environments and physical activity. However, since most studies were conducted in a single country, particularly western countries, the generalizability of associations in an international setting is not well understood. The current study examined whether associations between perceived attributes of neighborhood environments and physical activity differed by country.
Methods
Population representative samples from 11 countries on five continents were surveyed using comparable methodologies and measurement instruments. Neighborhood environment × country interactions were tested in logistic regression models with meeting physical activity recommendations as the outcome, adjusted for demographic characteristics. Country-specific associations were reported.
Results
Significant neighborhood environment attribute × country interactions implied some differences across countries in the association of each neighborhood attribute with meeting physical activity recommendations. Across the 11 countries, land-use mix and sidewalks had the most consistent associations with physical activity. Access to public transit, bicycle facilities, and low-cost recreation facilities had some associations with physical activity, but with less consistency across countries. There was little evidence supporting the associations of residential density and crime-related safety with physical activity in most countries.
Conclusion
There is evidence of generalizability for the associations of land use mix, and presence of sidewalks with physical activity. Associations of other neighborhood characteristics with physical activity tended to differ by country. Future studies should include objective measures of neighborhood environments, compare psychometric properties of reports across countries, and use better specified models to further understand the similarities and differences in associations across countries.
ContributorsDing, Ding (Author) / Adams, Marc (Author) / Sallis, James F. (Author) / Norman, Gregory J. (Author) / Hovell, Melbourn F. (Author) / Chambers, Christina D. (Author) / Hofstetter, C. Richard (Author) / Bowles, Heather R. (Author) / Hagstromer, Maria (Author) / Craig, Cora L. (Author) / Fernando Gomez, Luis (Author) / De Bourdeaudhuij, Ilse (Author) / Macfarlane, Duncan J. (Author) / Ainsworth, Barbara (Author) / Bergman, Patrick (Author) / Bull, Fiona C. (Author) / Carr, Harriette (Author) / Klasson-Heggebo, Lena (Author) / Inoue, Shigeru (Author) / Murase, Norio (Author) / Matsudo, Sandra (Author) / Matsudo, Victor (Author) / McLean, Grant (Author) / Sjostrom, Michael (Author) / Tomten, Heidi (Author) / Lefevre, Johan (Author) / Volbekiene, Vida (Author) / Bauman, Adrian E. (Author) / College of Health Solutions (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2013-05-14
Description
Background
Neighborhood environment studies of physical activity (PA) have been mainly single-country focused. The International Prevalence Study (IPS) presented a rare opportunity to examine neighborhood features across countries. The purpose of this analysis was to: 1) detect international neighborhood typologies based on participants’ response patterns to an environment survey and 2) to estimate associations between neighborhood environment patterns and PA.
Methods
A Latent Class Analysis (LCA) was conducted on pooled IPS adults (N=11,541) aged 18 to 64 years old (mean=37.5 ±12.8 yrs; 55.6% women) from 11 countries including Belgium, Brazil, Canada, Colombia, Hong Kong, Japan, Lithuania, New Zealand, Norway, Sweden, and the U.S. This subset used the Physical Activity Neighborhood Environment Survey (PANES) that briefly assessed 7 attributes within 10–15 minutes walk of participants’ residences, including residential density, access to shops/services, recreational facilities, public transit facilities, presence of sidewalks and bike paths, and personal safety. LCA derived meaningful subgroups from participants’ response patterns to PANES items, and participants were assigned to neighborhood types. The validated short-form International Physical Activity Questionnaire (IPAQ) measured likelihood of meeting the 150 minutes/week PA guideline. To validate derived classes, meeting the guideline either by walking or total PA was regressed on neighborhood types using a weighted generalized linear regression model, adjusting for gender, age and country.
Results
A 5-subgroup solution fitted the dataset and was interpretable. Neighborhood types were labeled, “Overall Activity Supportive (52% of sample)”, “High Walkable and Unsafe with Few Recreation Facilities (16%)”, “Safe with Active Transport Facilities (12%)”, “Transit and Shops Dense with Few Amenities (15%)”, and “Safe but Activity Unsupportive (5%)”. Country representation differed by type (e.g., U.S. disproportionally represented “Safe but Activity Unsupportive”). Compared to the Safe but Activity Unsupportive, two types showed greater odds of meeting PA guideline for walking outcome (High Walkable and Unsafe with Few Recreation Facilities, OR= 2.26 (95% CI 1.18-4.31); Overall Activity Supportive, OR= 1.90 (95% CI 1.13-3.21). Significant but smaller odds ratios were also found for total PA.
Conclusions
Meaningful neighborhood patterns generalized across countries and explained practical differences in PA. These observational results support WHO/UN recommendations for programs and policies targeted to improve features of the neighborhood environment for PA.
Neighborhood environment studies of physical activity (PA) have been mainly single-country focused. The International Prevalence Study (IPS) presented a rare opportunity to examine neighborhood features across countries. The purpose of this analysis was to: 1) detect international neighborhood typologies based on participants’ response patterns to an environment survey and 2) to estimate associations between neighborhood environment patterns and PA.
Methods
A Latent Class Analysis (LCA) was conducted on pooled IPS adults (N=11,541) aged 18 to 64 years old (mean=37.5 ±12.8 yrs; 55.6% women) from 11 countries including Belgium, Brazil, Canada, Colombia, Hong Kong, Japan, Lithuania, New Zealand, Norway, Sweden, and the U.S. This subset used the Physical Activity Neighborhood Environment Survey (PANES) that briefly assessed 7 attributes within 10–15 minutes walk of participants’ residences, including residential density, access to shops/services, recreational facilities, public transit facilities, presence of sidewalks and bike paths, and personal safety. LCA derived meaningful subgroups from participants’ response patterns to PANES items, and participants were assigned to neighborhood types. The validated short-form International Physical Activity Questionnaire (IPAQ) measured likelihood of meeting the 150 minutes/week PA guideline. To validate derived classes, meeting the guideline either by walking or total PA was regressed on neighborhood types using a weighted generalized linear regression model, adjusting for gender, age and country.
Results
A 5-subgroup solution fitted the dataset and was interpretable. Neighborhood types were labeled, “Overall Activity Supportive (52% of sample)”, “High Walkable and Unsafe with Few Recreation Facilities (16%)”, “Safe with Active Transport Facilities (12%)”, “Transit and Shops Dense with Few Amenities (15%)”, and “Safe but Activity Unsupportive (5%)”. Country representation differed by type (e.g., U.S. disproportionally represented “Safe but Activity Unsupportive”). Compared to the Safe but Activity Unsupportive, two types showed greater odds of meeting PA guideline for walking outcome (High Walkable and Unsafe with Few Recreation Facilities, OR= 2.26 (95% CI 1.18-4.31); Overall Activity Supportive, OR= 1.90 (95% CI 1.13-3.21). Significant but smaller odds ratios were also found for total PA.
Conclusions
Meaningful neighborhood patterns generalized across countries and explained practical differences in PA. These observational results support WHO/UN recommendations for programs and policies targeted to improve features of the neighborhood environment for PA.
ContributorsAdams, Marc (Author) / Ding, Ding (Author) / Sallis, James F. (Author) / Bowles, Heather R. (Author) / Ainsworth, Barbara (Author) / Bergman, Patrick (Author) / Bull, Fiona C. (Author) / Carr, Harriette (Author) / Craig, Cora L. (Author) / De Bourdeaudhuij, Ilse (Author) / Fernando Gomez, Luis (Author) / Hagstromer, Maria (Author) / Klasson-Heggebo, Lena (Author) / Inoue, Shigeru (Author) / Lefevre, Johan (Author) / Macfarlane, Duncan J. (Author) / Matsudo, Sandra (Author) / Matsudo, Victor (Author) / McLean, Grant (Author) / Murase, Norio (Author) / Sjostrom, Michael (Author) / Tomten, Heidi (Author) / Volbekiene, Vida (Author) / Bauman, Adrian (Author) / College of Health Solutions (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2013-03-07
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval
Description
Background
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
ContributorsYuan, Lei (Author) / Woodard, Alexander (Author) / Ji, Shuiwang (Author) / Jiang, Yuan (Author) / Zhou, Zhi-Hua (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / Ira A. Fulton School of Engineering (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2012-05-23
Description
Background
Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.
Results
We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach.
Conclusion
In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation.
Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.
Results
We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach.
Conclusion
In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation.
ContributorsSun, Qian (Author) / Muckatira, Sherin (Author) / Yuan, Lei (Author) / Ji, Shuiwang (Author) / Newfeld, Stuart (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2013-12-03
Description
Background:
Drosophila gene expression pattern images document the spatiotemporal dynamics of gene expression during embryogenesis. A comparative analysis of these images could provide a fundamentally important way for studying the regulatory networks governing development. To facilitate pattern comparison and searching, groups of images in the Berkeley Drosophila Genome Project (BDGP) high-throughput study were annotated with a variable number of anatomical terms manually using a controlled vocabulary. Considering that the number of available images is rapidly increasing, it is imperative to design computational methods to automate this task.
Results:
We present a computational method to annotate gene expression pattern images automatically. The proposed method uses the bag-of-words scheme to utilize the existing information on pattern annotation and annotates images using a model that exploits correlations among terms. The proposed method can annotate images individually or in groups (e.g., according to the developmental stage). In addition, the proposed method can integrate information from different two-dimensional views of embryos. Results on embryonic patterns from BDGP data demonstrate that our method significantly outperforms other methods.
Conclusion:
The proposed bag-of-words scheme is effective in representing a set of annotations assigned to a group of images, and the model employed to annotate images successfully captures the correlations among different controlled vocabulary terms. The integration of existing annotation information from multiple embryonic views improves annotation performance.
ContributorsJi, Shuiwang (Author) / Li, Ying-Xin (Author) / Zhou, Zhi-Hua (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Ira A. Fulton School of Engineering (Contributor) / School of Electrical, Computer and Energy Engineering (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2009-04-21
Description
The impact of finite dielectric-covered ground-plane edge diffractions on the amplitude patterns of circular apertures is investigated. The model is based on the Geometrical Optics (GO) and the Uniform Theory of Diffraction (UTD) for an impedance wedge. The circular aperture antenna is mounted on square and circular finite ground planes that are coated with a thin lossy dielectric layer. The predictions based on the GO/UTD model are validated by comparisons to experimental results and simulated data.
ContributorsAboserwal, Nafati (Author) / Balanis, Constantine (Author) / Birtcher, Craig (Author) / Ira A. Fulton School of Engineering (Contributor) / School of Electrical, Computer and Energy Engineering (Contributor)
Created2014-11-30
Description
This paper presents a multiscale modeling approach to simulating the self-sensing behavior of a load sensitive smart polymer material. A statistical spring-bead based network model is developed to bridge the molecular dynamics simulations at the nanoscale and the finite element model at the macroscale. Parametric studies are conducted on the developed network model to investigate the effects of the thermoset crosslinking degree on the mechanical response of the self-sensing material. A comparison between experimental and simulation results shows that the multiscale framework is able to capture the global mechanical response with adequate accuracy and the network model is also capable of simulating the self-sensing phenomenon of the smart polymer. Finally, the molecular dynamics simulation and network model based simulation are implemented to evaluate damage initiation in the self-sensing material under monotonic loading.
ContributorsZhang, Jinjun (Author) / Koo, Bonsung (Author) / Liu, Yingtao (Author) / Zou, Jin (Author) / Chattopadhyay, Aditi (Author) / Dai, Lenore (Author) / Ira A. Fulton School of Engineering (Contributor) / School for the Engineering of Matter, Transport and Energy (Contributor)
Created2015-08-01
Description
Sustainable production of microalgae for biofuel requires efficient phosphorus (P) utilization, which is a limited resource and vital for global food security. This research tracks the fate of P through biofuel production and investigates P recovery from the biomass using the cyanobacterium Synechocystis sp. PCC 6803. Our results show that Synechocystis contained 1.4% P dry weight. After crude lipids were extracted (e.g., for biofuel processing), 92% of the intracellular P remained in the residual biomass, indicating phospholipids comprised only a small percentage of cellular P. We estimate a majority of the P is primarily associated with nucleic acids. Advanced oxidation using hydrogen peroxide and microwave heating released 92% of the cellular P into orthophosphate. We then recovered the orthophosphate from the digestion matrix using two different types of anion exchange resins. One resin impregnated with iron nanoparticles adsorbed 98% of the influent P through 20 bed volumes, but only released 23% during regeneration. A strong-base anion exchange resin adsorbed 87% of the influent P through 20 bed volumes and released 50% of it upon regeneration. This recovered P subsequently supported growth of Synechocystis. This proof-of-concept recovery process reduced P demand of biofuel microalgae by 54%.
ContributorsGifford, McKay (Author) / Liu, Jianyong (Author) / Rittmann, Bruce (Author) / Vannela, Raveender (Author) / Westerhoff, Paul (Author) / Ira A. Fulton School of Engineering (Contributor) / School of Sustainable Engineering and the Built Environment (Contributor) / Biodesign Institute (Contributor) / Swette Center for Environmental Biotechnology (Contributor)
Created2015-03-01
Description
Wall-bounded turbulence manifests itself in a broad range of applications, not least of which in hydraulic systems. Here we briefly review the significant advances over the past few decades in the fundamental study of wall turbulence over smooth and rough surfaces, with an emphasis on coherent structures and their role at high Reynolds numbers. We attempt to relate these findings to parallel efforts in the hydraulic engineering community and discuss the implications of coherent structures in important hydraulic phenomena.
ContributorsAdrian, Ronald (Author) / Marusic, Ivan (Author) / Ira A. Fulton School of Engineering (Contributor) / School for the Engineering of Matter, Transport and Energy (Contributor)
Created2012-09-10
Description
Vortex organization in the outer layer of a turbulent boundary layer overlying sparse, hemispherical roughness elements is explored with two-component particle-image velocimetry (PIV) in multiple streamwise-wall-normal measurement planes downstream and between elements. The presence of sparse roughness elements causes a shortening of the streamwise length scale in the near-wall region. These measurements confirm that vortex packets exist in the outer layer of flow over rough walls, but that their organization is altered, and this is interpreted as the underlying cause of the length-scale reduction. In particular, the elements shed vortices which appear to align in the near-wall region, but are distinct from the packets. Further, it is observed that ejection events triggered in the element wakes are more intense compared to the ejection events in smooth wall. We speculate that this may initiate a self-sustaining mechanism leading to the formation of hairpin packets as a much more effective instability compared to those typical of smooth-wall turbulence.
ContributorsGuala, Michael (Author) / Tomkins, Christopher D. (Author) / Christensen, Kenneth T. (Author) / Adrian, Ronald (Author) / Ira A. Fulton School of Engineering (Contributor) / School for the Engineering of Matter, Transport and Energy (Contributor)
Created2012-09-09