Matching Items (127)
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In this thesis I introduce a new direction to computing using nonlinear chaotic dynamics. The main idea is rich dynamics of a chaotic system enables us to (1) build better computers that have a flexible instruction set, and (2) carry out computation that conventional computers are not good at it.

In this thesis I introduce a new direction to computing using nonlinear chaotic dynamics. The main idea is rich dynamics of a chaotic system enables us to (1) build better computers that have a flexible instruction set, and (2) carry out computation that conventional computers are not good at it. Here I start from the theory, explaining how one can build a computing logic block using a chaotic system, and then I introduce a new theoretical analysis for chaos computing. Specifically, I demonstrate how unstable periodic orbits and a model based on them explains and predicts how and how well a chaotic system can do computation. Furthermore, since unstable periodic orbits and their stability measures in terms of eigenvalues are extractable from experimental times series, I develop a time series technique for modeling and predicting chaos computing from a given time series of a chaotic system. After building a theoretical framework for chaos computing I proceed to architecture of these chaos-computing blocks to build a sophisticated computing system out of them. I describe how one can arrange and organize these chaos-based blocks to build a computer. I propose a brand new computer architecture using chaos computing, which shifts the limits of conventional computers by introducing flexible instruction set. Our new chaos based computer has a flexible instruction set, meaning that the user can load its desired instruction set to the computer to reconfigure the computer to be an implementation for the desired instruction set. Apart from direct application of chaos theory in generic computation, the application of chaos theory to speech processing is explained and a novel application for chaos theory in speech coding and synthesizing is introduced. More specifically it is demonstrated how a chaotic system can model the natural turbulent flow of the air in the human speech production system and how chaotic orbits can be used to excite a vocal tract model. Also as another approach to build computing system based on nonlinear system, the idea of Logical Stochastic Resonance is studied and adapted to an autoregulatory gene network in the bacteriophage λ.
ContributorsKia, Behnam (Author) / Ditto, William (Thesis advisor) / Huang, Liang (Committee member) / Lai, Ying-Cheng (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2011
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This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems

This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Droughts are a common phenomenon of the arid South-west USA climate. Despite water limitations, the region has been substantially transformed by agriculture and urbanization. The water requirements to support these human activities along with the projected increase in droughts intensity and frequency challenge long term sustainability and water security, thus

Droughts are a common phenomenon of the arid South-west USA climate. Despite water limitations, the region has been substantially transformed by agriculture and urbanization. The water requirements to support these human activities along with the projected increase in droughts intensity and frequency challenge long term sustainability and water security, thus the need to spatially and temporally characterize land use/land cover response to drought and quantify water consumption is crucial. This dissertation evaluates changes in `undisturbed' desert vegetation in response to water availability to characterize climate-driven variability. A new model coupling phenology and spectral unmixing was applied to Landsat time series (1987-2010) in order to derive fractional cover (FC) maps of annuals, perennials, and evergreen vegetation. Results show that annuals FC is controlled by short term water availability and antecedent soil moisture. Perennials FC follow wet-dry multi-year regime shifts, while evergreen is completely decoupled from short term changes in water availability. Trend analysis suggests that different processes operate at the local scale. Regionally, evergreen cover increased while perennials and annuals cover decreased. Subsequently, urban land cover was compared with its surrounding desert. A distinct signal of rain use efficiency and aridity index was documented from remote sensing and a soil-water-balance model. It was estimated that a total of 295 mm of water input is needed to sustain current greenness. Finally, an energy balance model was developed to spatio-temporally estimate evapotranspiration (ET) as a proxy for water consumption, and evaluate land use/land cover types in response to drought. Agricultural fields show an average ET of 9.3 mm/day with no significant difference between drought and wet conditions, implying similar level of water usage regardless of climatic conditions. Xeric neighborhoods show significant variability between dry and wet conditions, while mesic neighborhoods retain high ET of 400-500 mm during drought due to irrigation. Considering the potentially limited water availability, land use/land cover changes due to population increases, and the threat of a warming and drying climate, maintaining large water-consuming, irrigated landscapes challenges sustainable practices of water conservation and the need to provide amenities of this desert area for enhancing quality of life.
ContributorsKaplan, Shai (Author) / Myint, Soe Win (Thesis advisor) / Brazel, Anthony J. (Committee member) / Georgescu, Matei (Committee member) / Arizona State University (Publisher)
Created2014
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Description
While exercising mammalian muscle increasingly relies on carbohydrates for fuel as aerobic exercise intensity rises above the moderate range, flying birds are extraordinary endurance athletes and fuel flight, a moderate-high intensity exercise, almost exclusively with lipid. In addition, Aves have long lifespans compared to weight-matched mammals. As skeletal muscle mitochondria

While exercising mammalian muscle increasingly relies on carbohydrates for fuel as aerobic exercise intensity rises above the moderate range, flying birds are extraordinary endurance athletes and fuel flight, a moderate-high intensity exercise, almost exclusively with lipid. In addition, Aves have long lifespans compared to weight-matched mammals. As skeletal muscle mitochondria account for the majority of oxygen consumption during aerobic exercise, the primary goal was to investigate differences in isolated muscle mitochondria between these species and to examine to what extent factors intrinsic to mitochondria may account for the behavior observed in the intact tissue and whole organism. First, maximal enzyme activities were assessed in sparrow and rat mitochondria. Citrate synthase and aspartate aminotransferase activity were higher in sparrow compared to rat mitochondria, while glutamate dehydrogenase activity was lower. Sparrow mitochondrial NAD-linked isocitrate dehydrogenase activity was dependent on phosphate, unlike the mammalian enzyme. Next, the rate of oxygen consumption (JO), electron transport chain (ETC) activity, and reactive oxygen species (ROS) production were assessed in intact mitochondria. Maximal rates of fat oxidation were lower than for carbohydrate in rat but not sparrow mitochondria. ETC activity was higher in sparrows, but no differences were found in ROS production between species. Finally, fuel selection and control of respiration at three rates between rest and maximum were assessed. Mitochondrial fuel oxidation and selection mirrored that of the whole body; in rat mitochondria the reliance on carbohydrate increased as the rate of oxygen consumption increased, whereas fat dominated under all conditions in the sparrow. These data indicate fuel selection, at least in part, can be modulated at the level of the mitochondrial matrix when multiple substrates are present at saturating levels. As an increase in matrix oxidation-reduction potential has been linked to a suppression of fat oxidation and high ROS production, the high ETC activity relative to dehydrogenase activity in avian compared to mammalian mitochondria may result in lower matrix oxidation-reduction potential, allowing fatty acid oxidation to proceed while also resulting in low ROS production in vivo.
ContributorsKuzmiak, Sarah (Author) / Willis, Wayne T (Thesis advisor) / Mandarino, Lawrence (Committee member) / Sweazea, Karen (Committee member) / Harrison, Jon (Committee member) / Gadau, Juergen (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Complex dynamical systems consisting interacting dynamical units are ubiquitous in nature and society. Predicting and reconstructing nonlinear dynamics of units and the complex interacting networks among them serves the base for the understanding of a variety of collective dynamical phenomena. I present a general method to address the two outstanding

Complex dynamical systems consisting interacting dynamical units are ubiquitous in nature and society. Predicting and reconstructing nonlinear dynamics of units and the complex interacting networks among them serves the base for the understanding of a variety of collective dynamical phenomena. I present a general method to address the two outstanding problems as a whole based solely on time-series measurements. The method is implemented by incorporating compressive sensing approach that enables an accurate reconstruction of complex dynamical systems in terms of both nodal equations that determines the self-dynamics of units and detailed coupling patterns among units. The representative advantages of the approach are (i) the sparse data requirement which allows for a successful reconstruction from limited measurements, and (ii) general applicability to identical and nonidentical nodal dynamics, and to networks with arbitrary interacting structure, strength and sizes. Another two challenging problem of significant interest in nonlinear dynamics: (i) predicting catastrophes in nonlinear dynamical systems in advance of their occurrences and (ii) predicting the future state for time-varying nonlinear dynamical systems, can be formulated and solved in the framework of compressive sensing using only limited measurements. Once the network structure can be inferred, the dynamics behavior on them can be investigated, for example optimize information spreading dynamics, suppress cascading dynamics and traffic congestion, enhance synchronization, game dynamics, etc. The results can yield insights to control strategies design in the real-world social and natural systems. Since 2004, there has been a tremendous amount of interest in graphene. The most amazing feature of graphene is that there exists linear energy-momentum relationship when energy is low. The quasi-particles inside the system can be treated as chiral, massless Dirac fermions obeying relativistic quantum mechanics. Therefore, the graphene provides one perfect test bed to investigate relativistic quantum phenomena, such as relativistic quantum chaotic scattering and abnormal electron paths induced by klein tunneling. This phenomenon has profound implications to the development of graphene based devices that require stable electronic properties.
ContributorsYang, Rui (Author) / Lai, Ying-Cheng (Thesis advisor) / Duman, Tolga M. (Committee member) / Akis, Richard (Committee member) / Huang, Liang (Committee member) / Arizona State University (Publisher)
Created2012
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Description
What can classical chaos do to quantum systems is a fundamental issue highly relevant to a number of branches in physics. The field of quantum chaos has been active for three decades, where the focus was on non-relativistic quantumsystems described by the Schr¨odinger equation. By developing an efficient method to

What can classical chaos do to quantum systems is a fundamental issue highly relevant to a number of branches in physics. The field of quantum chaos has been active for three decades, where the focus was on non-relativistic quantumsystems described by the Schr¨odinger equation. By developing an efficient method to solve the Dirac equation in the setting where relativistic particles can tunnel between two symmetric cavities through a potential barrier, chaotic cavities are found to suppress the spread in the tunneling rate. Tunneling rate for any given energy assumes a wide range that increases with the energy for integrable classical dynamics. However, for chaotic underlying dynamics, the spread is greatly reduced. A remarkable feature, which is a consequence of Klein tunneling, arise only in relativistc quantum systems that substantial tunneling exists even for particle energy approaching zero. Similar results are found in graphene tunneling devices, implying high relevance of relativistic quantum chaos to the development of such devices. Wave propagation through random media occurs in many physical systems, where interesting phenomena such as branched, fracal-like wave patterns can arise. The generic origin of these wave structures is currently a matter of active debate. It is of fundamental interest to develop a minimal, paradigmaticmodel that can generate robust branched wave structures. In so doing, a general observation in all situations where branched structures emerge is non-Gaussian statistics of wave intensity with an algebraic tail in the probability density function. Thus, a universal algebraic wave-intensity distribution becomes the criterion for the validity of any minimal model of branched wave patterns. Coexistence of competing species in spatially extended ecosystems is key to biodiversity in nature. Understanding the dynamical mechanisms of coexistence is a fundamental problem of continuous interest not only in evolutionary biology but also in nonlinear science. A continuous model is proposed for cyclically competing species and the effect of the interplay between the interaction range and mobility on coexistence is investigated. A transition from coexistence to extinction is uncovered with a non-monotonic behavior in the coexistence probability and switches between spiral and plane-wave patterns arise. Strong mobility can either promote or hamper coexistence, while absent in lattice-based models, can be explained in terms of nonlinear partial differential equations.
ContributorsNi, Xuan (Author) / Lai, Ying-Cheng (Thesis advisor) / Huang, Liang (Committee member) / Yu, Hongbin (Committee member) / Akis, Richard (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Urban areas produce an urban heat island (UHI), which is manifest as warmer temperatures compared to the surrounding and less developed areas. While it is understood that UHI's are warmer than their surrounding areas, attributing the amount of heat added by the urban area is not easily determined. Current generation

Urban areas produce an urban heat island (UHI), which is manifest as warmer temperatures compared to the surrounding and less developed areas. While it is understood that UHI's are warmer than their surrounding areas, attributing the amount of heat added by the urban area is not easily determined. Current generation modeling systems require diurnal anthropogenic heating profiles. Development of diurnal cycle profiles of anthropogenic heating will help the modeling community as there is currently no database for anthropogenic heating profiles for cities across the United States. With more accurate anthropogenic heating profiles, climate models will be better able to show how humans directly impact the urban climate. This research attempts to create anthropogenic heating profiles for 61 cities in the United States. The method used climate, electricity, natural gas, and transportation data to develop anthropogenic heating profiles for each state. To develop anthropogenic heating profiles, profiles are developed for buildings, transportation, and human metabolism using the most recently available data. Since utilities are reluctant to release data, the building energy profile is developed using statewide electricity by creating a linear regression between the climate and electricity usage. A similar method is used to determine the contribution of natural gas consumption. These profiles are developed for each month of the year, so annual changes in anthropogenic heating can be seen. These profiles can then be put into climate models to enable more accurate urban climate modeling.
ContributorsMilne, Jeffrey (Author) / Georgescu, Matei (Thesis director) / Sailor, David (Committee member) / Brazel, Anthony (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Geographical Sciences and Urban Planning (Contributor)
Created2014-05
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Modeling results incorporating several distinct urban expansion futures for the United States in 2100 show that, in the absence of any adaptive urban design, megapolitan expansion, alone and separate from greenhouse gas-induced forcing, can be expected to raise near-surface temperatures 1–2 °C not just at the scale of individual cities

Modeling results incorporating several distinct urban expansion futures for the United States in 2100 show that, in the absence of any adaptive urban design, megapolitan expansion, alone and separate from greenhouse gas-induced forcing, can be expected to raise near-surface temperatures 1–2 °C not just at the scale of individual cities but over large regional swaths of the country. This warming is a significant fraction of the 21st century greenhouse gas-induced climate change simulated by global climate models. Using a suite of regional climate simulations, we assessed the efficacy of commonly proposed urban adaptation strategies, such as green, cool roof, and hybrid approaches, to ameliorate the warming. Our results quantify how judicious choices in urban planning and design cannot only counteract the climatological impacts of the urban expansion itself but also, can, in fact, even offset a significant percentage of future greenhouse warming over large scales. Our results also reveal tradeoffs among different adaptation options for some regions, showing the need for geographically appropriate strategies rather than one size fits all solutions.

ContributorsGeorgescu, Matei (Author) / Morefield, Philip E. (Author) / Bierwagen, Britta G. (Author) / Weaver, Christopher P. (Author)
Created2014-02-25
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Because of a projected surge of several billion urban inhabitants by mid-century, a rising urgency exists to advance local and strategically deployed measures intended to ameliorate negative consequences on urban climate (e.g., heat stress, poor air quality, energy/water availability). Here we highlight the importance of incorporating scale-dependent built environment induced

Because of a projected surge of several billion urban inhabitants by mid-century, a rising urgency exists to advance local and strategically deployed measures intended to ameliorate negative consequences on urban climate (e.g., heat stress, poor air quality, energy/water availability). Here we highlight the importance of incorporating scale-dependent built environment induced solutions within the broader umbrella of urban sustainability outcomes, thereby accounting for fundamental physical principles. Contemporary and future design of settlements demands cooperative participation between planners, architects, and relevant stakeholders, with the urban and global climate community, which recognizes the complexity of the physical systems involved and is ideally fit to quantitatively examine the viability of proposed solutions. Such participatory efforts can aid the development of locally sensible approaches by integrating across the socioeconomic and climatic continuum, therefore providing opportunities facilitating comprehensive solutions that maximize benefits and limit unintended consequences.

ContributorsGeorgescu, Matei (Author) / Chow, Winston, 1951- (Author) / Brazel, Anthony J. (Author) / Trapido-Lurie, B (Author) / Roth, M (Author) / Benson-Lira, V (Author)
Created2015-06-09
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Conversion of natural to urban land forms imparts influence on local and regional hydroclimate via modification of the surface energy and water balance, and consideration of such effects due to rapidly expanding megapolitan areas is necessary in light of the growing global share of urban inhabitants. Based on a suite

Conversion of natural to urban land forms imparts influence on local and regional hydroclimate via modification of the surface energy and water balance, and consideration of such effects due to rapidly expanding megapolitan areas is necessary in light of the growing global share of urban inhabitants. Based on a suite of ensemble-based, multi-year simulations using the Weather Research and Forecasting (WRF) model, we quantify seasonally varying hydroclimatic impacts of the most rapidly expanding megapolitan area in the US: Arizona's Sun Corridor, centered upon the Greater Phoenix metropolitan area. Using a scenario-based urban expansion approach that accounts for the full range of Sun Corridor growth uncertainty through 2050, we show that built environment induced warming for the maximum development scenario is greatest during the summer season (regionally averaged warming over AZ exceeds 1 °C).

Warming remains significant during the spring and fall seasons (regionally averaged warming over AZ approaches 0.9 °C during both seasons), and is least during the winter season (regionally averaged warming over AZ of 0.5 °C). Impacts from a minimum expansion scenario are reduced, with regionally averaged warming ranging between 0.1 and 0.3 °C for all seasons except winter, when no warming impacts are diagnosed. Integration of highly reflective cool roofs within the built environment, increasingly recognized as a cost-effective option intended to offset the warming influence of urban complexes, reduces urban-induced warming considerably. However, impacts on the hydrologic cycle are aggravated via enhanced evapotranspiration reduction, leading to a 4% total accumulated precipitation decrease relative to the non-adaptive maximum expansion scenario. Our results highlight potentially unintended consequences of this adaptation approach within rapidly expanding megapolitan areas, and emphasize the need for undeniably sustainable development paths that account for hydrologic impacts in addition to continued focus on mean temperature effects.

ContributorsGeorgescu, Matei (Author) / Mahalov, A. (Author) / Moustaoui, M. (Author)
Created2012-09-07