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- Creators: Arizona State University
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ABSTRACT The elephant tree, Bursera microphylla, is at the northern limit of its range in central Arizona. This species is sensitive to frost damage thus limiting its occurrence in more northern areas of the southwest. Marginal populations of B. microphylla are found in mountain ranges of Central Arizona and are known to occur in the rugged mountain range system of the South Mountain Municipal Park (SMMP). Little is known of the distribution of this species within the park and details relevant to the health of both individual plants and the population such as diameter and number of trunks, height, and presence of damage have not been examined. This study was designed, in part, to test the hypothesis that favorable microhabitats at SMMP are created by particular combinations of abiotic features including aspect, slope, elevation and solar radiation. Data on abiotic factors, as well as specific individual plant locations and characteristics were obtained for 100 individuals. Temperature data was collected in vertical transects at different altitudinal levels. Some of these data were used in spatial analyses to generate a habitat suitability model using GIS software. Furthermore, collected data was analyzed using Matlab© software to identify potential trends in the variation of morphological traits. In addition, for comparative purposes similar information at one hundred computer-generated randomly chosen points throughout SMMP was obtained. The GIS spatial analyses indicated that aspect, slope, elevation, and relative solar radiance are strongly associated as major climatic components of the microhabitat of B. microphylla. Temperature data demonstrated that there are significant differences in ambient temperature among different altitudinal gradients with middle elevations being more favorable. Furthermore, analyses performed using Matlab© to explore trends of elevation as a factor indicated that multiple trunk plants are more commonly found at higher elevations than single trunk plants, there is a positive correlation of trunk diameter with elevation, and that canopy volume has a negative correlation with respect to elevation. It was concluded that microhabitats where B. microphylla occurs at the northern limit of its range require a particular combination of abiotic features that can be easily altered by climatic changes.
ContributorsCordova, Cesar, M.S (Author) / Steele, Kelly P. (Thesis advisor) / Tridane, Abdessaman (Committee member) / Miller, William (Committee member) / Brady, Ward (Committee member) / Arizona State University (Publisher)
Created2011
Description
Coal bed natural gas (CBNG) production has become a significant contribution to the nation's energy supply. Large volumes of water are generated as a byproduct of CBNG extraction, of which this "product water" is relatively high in sodium. High sodicity reduces water quality and limits environmentally compliant disposal options for producers. Crop irrigation with CBNG product water complies with state and federal laws and is a disposal method that also provides a beneficial use to private landowners. However, this disposal method typically requires gypsum and sulfur soil amendments due to the high levels of sodium in the water, which can reduce soil infiltration and hydraulic conductivity. In this study, I tested a new product called Salt Extractor that was marketed to CBNG producers to ameliorate the negative effects of high sodicity. The experiment was conducted in the Powder River Basin of Wyoming. I used a random block design to compare the soil and vegetation properties of plots following application with CBNG product water and treatments of either Salt Extractor, gypsum and sulfur (conventional), or no treatment (control). Data was analyzed by comparing the amount of change between treatments after watering. Results demonstrated the known ability of gypsum and sulfur to lower the relative sodicity of the soil. Plots treated with Salt Extractor, however, did not improve relative levels of sodicity and exhibited no favorable benefits to vegetation.
ContributorsAdams, Shelly (Author) / Hall, Sharon (Thesis advisor) / Chew, Matt (Committee member) / Stromberg, Juliet (Committee member) / Arizona State University (Publisher)
Created2011
Description
Cognitive function is multidimensional and complex, and research indicates that it is impacted by age, lifetime experience, and ovarian hormone milieu. One particular domain of cognitive function that is susceptible to age-related decrements is spatial memory. Cognitive practice can affect spatial memory when aged in both males and females, and in females alone ovarian hormones have been found to alter spatial memory via modulating brain microstructure and function in many of the same brain areas affected by aging. The research in this dissertation has implications that promote an understanding of the effects of cognitive practice on aging memory, why males and females respond differently to cognitive practice, and the parameters and mechanisms underlying estrogen's effects on memory. This body of work suggests that cognitive practice can enhance memory when aged and that estrogen is a probable candidate facilitating the observed differences in the effects of cognitive practice depending on sex. This enhancement in cognitive practice effects via estrogen is supported by data demonstrating that estrogen enhances spatial memory and hippocampal synaptic plasticity. The estrogen-facilitated memory enhancements and alterations in hippocampal synaptic plasticity are at least partially facilitated via enhancements in cholinergic signaling from the basal forebrain. Finally, age, dose, and type of estrogen utilized are important factors to consider when evaluating estrogen's effects on memory and its underlying mechanisms, since age alters the responsiveness to estrogen treatment and the dose of estrogen needed, and small alterations in the molecular structure of estrogen can have a profound impact on estrogen's efficacy on memory. Collectively, this dissertation elucidates many parameters that dictate the outcome, and even the direction, of the effects that cognitive practice and estrogens have on cognition during aging. Indeed, many parameters including the ones described here are important considerations when designing future putative behavioral interventions, behavioral therapies, and hormone therapies. Ideally, the parameters described here will be used to help design the next generation of interventions, therapies, and nootropic agents that will allow individuals to maintain their cognitive capacity when aged, above and beyond what is currently possible, thus enacting lasting improvement in women's health and public health in general.
ContributorsTalboom, Joshua S (Author) / Bimonte-Nelson, Heather A. (Thesis advisor) / Conrad, Cheryl D. (Committee member) / Neisewander, Janet L (Committee member) / West, Stephen G. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Rhodoferax antarcticus strain ANT.BR, a purple nonsulfur bacterium isolated from a microbial mat in Ross Island, Antarctica, is the first described anoxygenic phototrophic bacterium that is adapted to cold habitats and is the first beta-proteobacterium to undergo complete genome sequencing. R. antarcticus has unique absorption spectra and there are no obvious intracytoplasmic membranes in cells grown phototrophically, even under low light intensity. Analysis of the finished genome sequence reveals a single chromosome (3,809,266 bp) and a large plasmid (198,615 bp) that together harbor 4,262 putative genes. The genome contains two types of Rubiscos, Form IAq and Form II, which are known to exhibit quite different kinetic properties in other bacteria. The presence of multiple Rubisco forms could give R. antarcticus high metabolic flexibility in diverse environments. Annotation of the complete genome sequence along with previous experimental results predict the presence of structural genes for three types of light-harvesting (LH) complexes, LH I (B875), LH II (B800/850), and LH III (B800/820). There is evidence that expression of genes for the LH II complex might be inhibited when R. antarcticus is under low temperature and/or low light intensity. These interesting condition-dependent light-harvesting apparatuses and the control of their expression are very valuable for the further understanding of photosynthesis in cold environments. Finally, R. antarcticus exhibits a highly motile lifestyle. The genome content and organization of all putative polar flagella genes are characterized and discussed.
ContributorsZhao, Tingting, M.S (Author) / Touchman, Jeffrey (Thesis advisor) / Rosenberg, Michael (Committee member) / Redding, Kevin (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created2011
Description
Multi-label learning, which deals with data associated with multiple labels simultaneously, is ubiquitous in real-world applications. To overcome the curse of dimensionality in multi-label learning, in this thesis I study multi-label dimensionality reduction, which extracts a small number of features by removing the irrelevant, redundant, and noisy information while considering the correlation among different labels in multi-label learning. Specifically, I propose Hypergraph Spectral Learning (HSL) to perform dimensionality reduction for multi-label data by exploiting correlations among different labels using a hypergraph. The regularization effect on the classical dimensionality reduction algorithm known as Canonical Correlation Analysis (CCA) is elucidated in this thesis. The relationship between CCA and Orthonormalized Partial Least Squares (OPLS) is also investigated. To perform dimensionality reduction efficiently for large-scale problems, two efficient implementations are proposed for a class of dimensionality reduction algorithms, including canonical correlation analysis, orthonormalized partial least squares, linear discriminant analysis, and hypergraph spectral learning. The first approach is a direct least squares approach which allows the use of different regularization penalties, but is applicable under a certain assumption; the second one is a two-stage approach which can be applied in the regularization setting without any assumption. Furthermore, an online implementation for the same class of dimensionality reduction algorithms is proposed when the data comes sequentially. A Matlab toolbox for multi-label dimensionality reduction has been developed and released. The proposed algorithms have been applied successfully in the Drosophila gene expression pattern image annotation. The experimental results on some benchmark data sets in multi-label learning also demonstrate the effectiveness and efficiency of the proposed algorithms.
ContributorsSun, Liang (Author) / Ye, Jieping (Thesis advisor) / Li, Baoxin (Committee member) / Liu, Huan (Committee member) / Mittelmann, Hans D. (Committee member) / Arizona State University (Publisher)
Created2011
Description
One hypothesis for the small size of insects relative to vertebrates, and the existence of giant fossil insects, is that atmospheric oxygen levels have constrained body sizes because oxygen delivery would be unable to match the needs of metabolically active tissues in larger insects. This study tested whether oxygen delivery becomes more challenging for larger insects by measuring the oxygen-sensitivity of flight metabolic rates and behavior during hovering for 11 different species of dragonflies that range in mass by an order of magnitude. Animals were flown in 7 different oxygen concentrations ranging from 30% to 2.5% to assess the sensitivity of their behavior and flight metabolic rates to oxygen. I also assessed the oxygen-sensitivity of flight in low-density air (nitrogen replaced with helium), to increase the metabolic demands of hovering flight. Lowered atmosphere densities did induce higher metabolic rates. Flight behaviors but not flight metabolic rates were highly oxygen-sensitive. A significant interaction between oxygen and mass was found for total flight time, with larger dragonflies varying flight time more in response to atmospheric oxygen. This study provides some support for the hypothesis that larger insects are more challenged in oxygen delivery, as predicted by the oxygen limitation hypothesis for insect gigantism in the Paleozoic.
ContributorsHenry, Joanna Randyl (Author) / Harrison, Jon F. (Thesis advisor) / Kaiser, Alexander (Committee member) / Rutowski, Ronald L (Committee member) / Arizona State University (Publisher)
Created2011
Description
Real-world environments are characterized by non-stationary and continuously evolving data. Learning a classification model on this data would require a framework that is able to adapt itself to newer circumstances. Under such circumstances, transfer learning has come to be a dependable methodology for improving classification performance with reduced training costs and without the need for explicit relearning from scratch. In this thesis, a novel instance transfer technique that adapts a "Cost-sensitive" variation of AdaBoost is presented. The method capitalizes on the theoretical and functional properties of AdaBoost to selectively reuse outdated training instances obtained from a "source" domain to effectively classify unseen instances occurring in a different, but related "target" domain. The algorithm is evaluated on real-world classification problems namely accelerometer based 3D gesture recognition, smart home activity recognition and text categorization. The performance on these datasets is analyzed and evaluated against popular boosting-based instance transfer techniques. In addition, supporting empirical studies, that investigate some of the less explored bottlenecks of boosting based instance transfer methods, are presented, to understand the suitability and effectiveness of this form of knowledge transfer.
ContributorsVenkatesan, Ashok (Author) / Panchanathan, Sethuraman (Thesis advisor) / Li, Baoxin (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2011
Description
Sparse learning is a technique in machine learning for feature selection and dimensionality reduction, to find a sparse set of the most relevant features. In any machine learning problem, there is a considerable amount of irrelevant information, and separating relevant information from the irrelevant information has been a topic of focus. In supervised learning like regression, the data consists of many features and only a subset of the features may be responsible for the result. Also, the features might require special structural requirements, which introduces additional complexity for feature selection. The sparse learning package, provides a set of algorithms for learning a sparse set of the most relevant features for both regression and classification problems. Structural dependencies among features which introduce additional requirements are also provided as part of the package. The features may be grouped together, and there may exist hierarchies and over- lapping groups among these, and there may be requirements for selecting the most relevant groups among them. In spite of getting sparse solutions, the solutions are not guaranteed to be robust. For the selection to be robust, there are certain techniques which provide theoretical justification of why certain features are selected. The stability selection, is a method for feature selection which allows the use of existing sparse learning methods to select the stable set of features for a given training sample. This is done by assigning probabilities for the features: by sub-sampling the training data and using a specific sparse learning technique to learn the relevant features, and repeating this a large number of times, and counting the probability as the number of times a feature is selected. Cross-validation which is used to determine the best parameter value over a range of values, further allows to select the best parameter value. This is done by selecting the parameter value which gives the maximum accuracy score. With such a combination of algorithms, with good convergence guarantees, stable feature selection properties and the inclusion of various structural dependencies among features, the sparse learning package will be a powerful tool for machine learning research. Modular structure, C implementation, ATLAS integration for fast linear algebraic subroutines, make it one of the best tool for a large sparse setting. The varied collection of algorithms, support for group sparsity, batch algorithms, are a few of the notable functionality of the SLEP package, and these features can be used in a variety of fields to infer relevant elements. The Alzheimer Disease(AD) is a neurodegenerative disease, which gradually leads to dementia. The SLEP package is used for feature selection for getting the most relevant biomarkers from the available AD dataset, and the results show that, indeed, only a subset of the features are required to gain valuable insights.
ContributorsThulasiram, Ramesh (Author) / Ye, Jieping (Thesis advisor) / Xue, Guoliang (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011
Description
The repression of reproductive competition and the enforcement of altruism are key components to the success of animal societies. Eusocial insects are defined by having a reproductive division of labor, in which reproduction is relegated to one or few individuals while the rest of the group members maintain the colony and help raise offspring. However, workers have retained the ability to reproduce in most insect societies. In the social Hymenoptera, due to haplodiploidy, workers can lay unfertilized male destined eggs without mating. Potential conflict between workers and queens can arise over male production, and policing behaviors performed by nestmate workers and queens are a means of repressing worker reproduction. This work describes the means and results of the regulation of worker reproduction in the ant species Aphaenogaster cockerelli. Through manipulative laboratory studies on mature colonies, the lack of egg policing and the presence of physical policing by both workers and queens of this species are described. Through chemical analysis and artificial chemical treatments, the role of cuticular hydrocarbons as indicators of fertility status and the informational basis of policing in this species is demonstrated. An additional queen-specific chemical signal in the Dufour's gland is discovered to be used to direct nestmate aggression towards reproductive competitors. Finally, the level of actual worker-derived males in field colonies is measured. Together, these studies demonstrate the effectiveness of policing behaviors on the suppression of worker reproduction in a social insect species, and provide an example of how punishment and the threat of punishment is a powerful force in maintaining cooperative societies.
ContributorsSmith, Adrian A. (Author) / Liebig, Juergen (Thesis advisor) / Hoelldobler, Bert (Thesis advisor) / Gadau, Juergen (Committee member) / Johnson, Robert A. (Committee member) / Pratt, Stephen (Committee member) / Arizona State University (Publisher)
Created2011
Description
The advent of advanced reproductive technologies has sparked a number of ethical concerns regarding the practices of reproductive tourism and commercial gestational surrogacy. In the past few decades, reproductive tourism has become a global industry in which individuals or couples travel, usually across borders, to gain access to reproductive services. This marketable field has expanded commercial gestational surrogacy--defined by a contractual relationship between an intending couple and gestational surrogate in which the surrogate has no genetic tie to fetus--to take on transnational complexities. India has experienced extreme growth due to a preferable combination of western educated doctors and extremely low medical costs. However, a slew of ethical issues have been brought to the forefront: the big ones manifesting as concern for reduction of a woman's worth to her reproductive capabilities along with concern for exploitation of third world women. This project will be based exclusively on literature review and serves primarily as a call for cultural competency and understanding the circumstances that gestational surrogates are faced with before implementing policy regulating commercial gestational surrogacy. The paper argues that issues of exploitation and commodification hinge on constructions of motherhood. It is critical to define and understand definitions of motherhood and how these definitions affect a woman's approach to reproduction within the cultural context of a gestational surrogate. This paper follows the case study of the Akanksha Infertility Clinic in northern India, a surrogacy clinic housing around 50 Indian surrogates. The findings of the project invokes the critical significance of narrative ethics, which help Indian surrogates construct the practice of surrogacy so that it fits into cultural comprehensions of Indian motherhood--in which motherhood is selfless, significant, and shared.
ContributorsMoorthy, Anjali (Author) / Robert, Jason S (Thesis advisor) / Hurlbut, Benjamin (Committee member) / Ellison, Karin (Committee member) / Arizona State University (Publisher)
Created2011