Matching Items (13,583)
Filtering by
- Creators: ASU Library. Music Library
- Creators: College of Liberal Arts and Sciences
Description
This study examines the creation of a sustainability toolkit that can be implemented in many communities, beginning with Johnson City, Tennessee. This project began in 2019 and will continue to grow indefinitely. For this project, a toolkit that will allow the public to have access to the tools and information they need in order to make their homes more energy-efficient will be created. It will be stocked in the local library in Johnson City Tennessee for free use to the public, as long as they have a library card, they can check out the toolkits. The toolkits will be used by the public, then returned to the library so that they can be restocked and checked out again. This study looks at the market, business and organizational research and the infrastructure of the project. Methods of research included looking at how the need for a change came about, who will benefit, existing similar programs and how they will be used in conjunction with this project, current organizational structures attached to the project, current team infrastructure and what resources are needed to fill the voids. Findings include what financial resources will be required and how they will be acquired, as well as resources that are currently available for this project and what is still needed in order for this project to be successful. As a result of this project, at least two libraries in the Johnson City area will be stocked with several energy toolkits for free and a partnership for future project expansion will have been established. This study looks at the process and what was learned during the implementation of the project.
ContributorsMassick, Emma (Writer of accompanying material)
Created2020-05-18
ContributorsChandler, N. Kayla (Author) / Neisewander, Janet (Thesis director) / Sanabria, Federico (Committee member) / Olive, M. Foster (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2013-05
Description
RESEARCH QUESTION: Does Online "Working Out Work" as a Treatment and Prevention for Depression in Older Adults? An Analysis of a Prescribed and Monitored Exercise Program Administered via the Internet for Senior Adults with Depression.
OBJECTIVE: The purpose of this study is to investigate and access the effectiveness of an online prescribed and monitored exercise program for the treatment of depression in Older Adults. The Dependent Variable for the study is Depression. The Independent Variable for the study is the Effects of Exercise administered via the Internet and the population is geriatric adults defined as senior adults aged 50 and older. Depression is defined by Princeton University Scholars (Wordnet, 2006) as a mental state characterized by a pessimistic sense of inadequacy and a despondent lack of activity.
METHODS: The presence and severity of depression will be assessed by using The Merck Manual of Geriatrics (GDS-15) Geriatric Depression Scale. Assessments will be performed at baseline, before and after the treatment is concluded. The subjects will complete the Physical Activity Readiness Questionnaire (PAR-Q) prior to participating in an exercise program three times per week.
LIMITATIONS OF RESEARCH: The limitations of this study are: 1) There is a small sample size limited to Senior Adults aged 50 - 80, and 2) there is no control group with structured activity or placebo, therefore researcher is unable to evaluate if the marked improvement was due to a non-specific therapeutic effect associated with taking part in a social activity (group online exercise program). Further research could compare and analyze the positive effects of a muscular strength training exercise program verses a cardiovascular training exercise program.
ContributorsCaballero-Garcia, Robelyn (Author) / Waldron, Kathleen (Thesis advisor) / College of Liberal Arts and Sciences (Contributor)
Created2011-05-02
Description
Background
The transmission dynamics of Tuberculosis (TB) involve complex epidemiological and socio-economical interactions between individuals living in highly distinct regional conditions. The level of exogenous reinfection and first time infection rates within high-incidence settings may influence the impact of control programs on TB prevalence. The impact that effective population size and the distribution of individuals’ residence times in different patches have on TB transmission and control are studied using selected scenarios where risk is defined by the estimated or perceive first time infection and/or exogenous re-infection rates.
Methods
This study aims at enhancing the understanding of TB dynamics, within simplified, two patch, risk-defined environments, in the presence of short term mobility and variations in reinfection and infection rates via a mathematical model. The modeling framework captures the role of individuals’ ‘daily’ dynamics within and between places of residency, work or business via the average proportion of time spent in residence and as visitors to TB-risk environments (patches). As a result, the effective population size of Patch i (home of i-residents) at time t must account for visitors and residents of Patch i, at time t.
Results
The study identifies critical social behaviors mechanisms that can facilitate or eliminate TB infection in vulnerable populations. The results suggest that short-term mobility between heterogeneous patches contributes to significant overall increases in TB prevalence when risk is considered only in terms of direct new infection transmission, compared to the effect of exogenous reinfection. Although, the role of exogenous reinfection increases the risk that come from large movement of individuals, due to catastrophes or conflict, to TB-free areas.
Conclusions
The study highlights that allowing infected individuals to move from high to low TB prevalence areas (for example via the sharing of treatment and isolation facilities) may lead to a reduction in the total TB prevalence in the overall population. The higher the population size heterogeneity between distinct risk patches, the larger the benefit (low overall prevalence) under the same “traveling” patterns. Policies need to account for population specific factors (such as risks that are inherent with high levels of migration, local and regional mobility patterns, and first time infection rates) in order to be long lasting, effective and results in low number of drug resistant cases.
The transmission dynamics of Tuberculosis (TB) involve complex epidemiological and socio-economical interactions between individuals living in highly distinct regional conditions. The level of exogenous reinfection and first time infection rates within high-incidence settings may influence the impact of control programs on TB prevalence. The impact that effective population size and the distribution of individuals’ residence times in different patches have on TB transmission and control are studied using selected scenarios where risk is defined by the estimated or perceive first time infection and/or exogenous re-infection rates.
Methods
This study aims at enhancing the understanding of TB dynamics, within simplified, two patch, risk-defined environments, in the presence of short term mobility and variations in reinfection and infection rates via a mathematical model. The modeling framework captures the role of individuals’ ‘daily’ dynamics within and between places of residency, work or business via the average proportion of time spent in residence and as visitors to TB-risk environments (patches). As a result, the effective population size of Patch i (home of i-residents) at time t must account for visitors and residents of Patch i, at time t.
Results
The study identifies critical social behaviors mechanisms that can facilitate or eliminate TB infection in vulnerable populations. The results suggest that short-term mobility between heterogeneous patches contributes to significant overall increases in TB prevalence when risk is considered only in terms of direct new infection transmission, compared to the effect of exogenous reinfection. Although, the role of exogenous reinfection increases the risk that come from large movement of individuals, due to catastrophes or conflict, to TB-free areas.
Conclusions
The study highlights that allowing infected individuals to move from high to low TB prevalence areas (for example via the sharing of treatment and isolation facilities) may lead to a reduction in the total TB prevalence in the overall population. The higher the population size heterogeneity between distinct risk patches, the larger the benefit (low overall prevalence) under the same “traveling” patterns. Policies need to account for population specific factors (such as risks that are inherent with high levels of migration, local and regional mobility patterns, and first time infection rates) in order to be long lasting, effective and results in low number of drug resistant cases.
ContributorsMoreno Martinez, Victor (Author) / Espinoza Cortes, Baltazar (Author) / Barley, Kamal (Author) / Paredes Gutierrez, Marlio (Author) / Bichara, Derdei (Author) / Mubayi, Anuj (Author) / Castillo-Chavez, Carlos (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2017-01-11
Description
Background
The maintenance of chromosomal integrity is an essential task of every living organism and cellular repair mechanisms exist to guard against insults to DNA. Given the importance of this process, it is expected that DNA repair proteins would be evolutionarily conserved, exhibiting very minimal sequence change over time. However, BRCA1, an essential gene involved in DNA repair, has been reported to be evolving rapidly despite the fact that many protein-altering mutations within this gene convey a significantly elevated risk for breast and ovarian cancers.
Results
To obtain a deeper understanding of the evolutionary trajectory of BRCA1, we analyzed complete BRCA1 gene sequences from 23 primate species. We show that specific amino acid sites have experienced repeated selection for amino acid replacement over primate evolution. This selection has been focused specifically on humans and our closest living relatives, chimpanzees (Pan troglodytes) and bonobos (Pan paniscus). After examining BRCA1 polymorphisms in 7 bonobo, 44 chimpanzee, and 44 rhesus macaque (Macaca mulatta) individuals, we find considerable variation within each of these species and evidence for recent selection in chimpanzee populations. Finally, we also sequenced and analyzed BRCA2 from 24 primate species and find that this gene has also evolved under positive selection.
Conclusions
While mutations leading to truncated forms of BRCA1 are clearly linked to cancer phenotypes in humans, there is also an underlying selective pressure in favor of amino acid-altering substitutions in this gene. A hypothesis where viruses are the drivers of this natural selection is discussed.
The maintenance of chromosomal integrity is an essential task of every living organism and cellular repair mechanisms exist to guard against insults to DNA. Given the importance of this process, it is expected that DNA repair proteins would be evolutionarily conserved, exhibiting very minimal sequence change over time. However, BRCA1, an essential gene involved in DNA repair, has been reported to be evolving rapidly despite the fact that many protein-altering mutations within this gene convey a significantly elevated risk for breast and ovarian cancers.
Results
To obtain a deeper understanding of the evolutionary trajectory of BRCA1, we analyzed complete BRCA1 gene sequences from 23 primate species. We show that specific amino acid sites have experienced repeated selection for amino acid replacement over primate evolution. This selection has been focused specifically on humans and our closest living relatives, chimpanzees (Pan troglodytes) and bonobos (Pan paniscus). After examining BRCA1 polymorphisms in 7 bonobo, 44 chimpanzee, and 44 rhesus macaque (Macaca mulatta) individuals, we find considerable variation within each of these species and evidence for recent selection in chimpanzee populations. Finally, we also sequenced and analyzed BRCA2 from 24 primate species and find that this gene has also evolved under positive selection.
Conclusions
While mutations leading to truncated forms of BRCA1 are clearly linked to cancer phenotypes in humans, there is also an underlying selective pressure in favor of amino acid-altering substitutions in this gene. A hypothesis where viruses are the drivers of this natural selection is discussed.
ContributorsLou, Dianne I. (Author) / McBee, Ross M. (Author) / Le, Uyen Q. (Author) / Stone, Anne (Author) / Wilkerson, Gregory K. (Author) / Demogines, Ann M. (Author) / Sawyer, Sara L. (Author) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / School of Life Sciences (Contributor)
Created2014-07-11
Description
Background
Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide promising ways for addressing key scientific questions.
Results
We develop a set of computational methods and open source tools for identifying co-expressed embryonic domains and the associated genes simultaneously. To map the expression patterns of many genes into the same coordinate space and account for the embryonic shape variations, we develop a mesh generation method to deform a meshed generic ellipse to each individual embryo. We then develop a co-clustering formulation to cluster the genes and the mesh elements, thereby identifying co-expressed embryonic domains and the associated genes simultaneously. Experimental results indicate that the gene and mesh co-clusters can be correlated to key developmental events during the stages of embryogenesis we study. The open source software tool has been made available at http://compbio.cs.odu.edu/fly/.
Conclusions
Our mesh generation and machine learning methods and tools improve upon the flexibility, ease-of-use and accuracy of existing methods.
Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide promising ways for addressing key scientific questions.
Results
We develop a set of computational methods and open source tools for identifying co-expressed embryonic domains and the associated genes simultaneously. To map the expression patterns of many genes into the same coordinate space and account for the embryonic shape variations, we develop a mesh generation method to deform a meshed generic ellipse to each individual embryo. We then develop a co-clustering formulation to cluster the genes and the mesh elements, thereby identifying co-expressed embryonic domains and the associated genes simultaneously. Experimental results indicate that the gene and mesh co-clusters can be correlated to key developmental events during the stages of embryogenesis we study. The open source software tool has been made available at http://compbio.cs.odu.edu/fly/.
Conclusions
Our mesh generation and machine learning methods and tools improve upon the flexibility, ease-of-use and accuracy of existing methods.
ContributorsZhang, Wenlu (Author) / Feng, Daming (Author) / Li, Rongjian (Author) / Chernikov, Andrey (Author) / Chrisochoides, Nikos (Author) / Osgood, Christopher (Author) / Konikoff, Charlotte (Author) / Newfeld, Stuart (Author) / Kumar, Sudhir (Author) / Ji, Shuiwang (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2013-12-28
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
Diacylglycerol kinase catalyses the ATP-dependent conversion of diacylglycerol to phosphatidic acid in the plasma membrane of Escherichia coli. The small size of this integral membrane trimer, which has 121 residues per subunit, means that available protein must be used economically to craft three catalytic and substrate-binding sites centred about the membrane/cytosol interface. How nature has accomplished this extraordinary feat is revealed here in a crystal structure of the kinase captured as a ternary complex with bound lipid substrate and an ATP analogue. Residues, identified as essential for activity by mutagenesis, decorate the active site and are rationalized by the ternary structure. The γ-phosphate of the ATP analogue is positioned for direct transfer to the primary hydroxyl of the lipid whose acyl chain is in the membrane. A catalytic mechanism for this unique enzyme is proposed. The active site architecture shows clear evidence of having arisen by convergent evolution.
ContributorsLi, Dianfan (Author) / Stansfeld, Phillip J. (Author) / Sansom, Mark S. P. (Author) / Keogh, Aaron (Author) / Vogeley, Lutz (Author) / Howe, Nicole (Author) / Lyons, Joseph A. (Author) / Aragao, David (Author) / Fromme, Petra (Author) / Fromme, Raimund (Author) / Basu, Shibom (Author) / Grotjohann, Ingo (Author) / Kupitz, Christopher (Author) / Rendek, Kimberley (Author) / Weierstall, Uwe (Author) / Zatsepin, Nadia (Author) / Cherezov, Vadim (Author) / Liu, Wei (Author) / Bandaru, Sateesh (Author) / English, Niall J. (Author) / Gati, Cornelius (Author) / Barty, Anton (Author) / Yefanov, Oleksandr (Author) / Chapman, Henry N. (Author) / Diederichs, Kay (Author) / Messerschmidt, Marc (Author) / Boutet, Sebastien (Author) / Williams, Garth J. (Author) / Seibert, M. Marvin (Author) / Caffrey, Martin (Author) / College of Liberal Arts and Sciences (Contributor) / School of Molecular Sciences (Contributor) / Biodesign Institute (Contributor) / Applied Structural Discovery (Contributor) / Department of Physics (Contributor)
Created2015-12-17
Description
Large quantities of sodic and alkaline bauxite residue are produced globally as a by-product from alumina refineries. Ecological stoichiometry of key elements [nitrogen (N) and phosphorus (P)] plays a critical role in establishing vegetation cover in bauxite residue sand (BRS). Here we examined how changes in soil chemical properties over time in rehabilitated sodic and alkaline BRS affected leaf N to P stoichiometry of native species used for rehabilitation. Both Ca and soil pH influenced the shifts in leaf N:P ratios of the study species as supported by consistently significant positive relationships (P < 0.001) between these soil indices and leaf N:P ratios. Shifts from N to P limitation were evident for N-fixing species, while N limitation was consistently experienced by non-N-fixing plant species. In older rehabilitated BRS embankments, soil and plant indices (Ca, Na, pH, EC, ESP and leaf N:P ratios) tended to align with those of the natural ecosystem, suggesting improved rehabilitation performance. These findings highlight that leaf N:P stoichiometry can effectively provide a meaningful assessment on understanding nutrient limitation and productivity of native species used for vegetating highly sodic and alkaline BRS, and is a crucial indicator for assessing ecological rehabilitation performance.
ContributorsGoloran, Johnvie B. (Author) / Chen, Chengrong (Author) / Phillips, Ian R. (Author) / Elser, James (Author) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2015-10-07