Matching Items (187)
Description
The elaborate signals of animals are often costly to produce and maintain, thus communicating reliable information about the quality of an individual to potential mates or competitors. The properties of the sensory systems that receive signals can drive the evolution of these signals and shape their form and function. However, relatively little is known about the ecological and physiological constraints that may influence the development and maintenance of sensory systems. In the house finch (Carpodacus mexicanus) and many other bird species, carotenoid pigments are used to create colorful sexually selected displays, and their expression is limited by health and dietary access to carotenoids. Carotenoids also accumulate in the avian retina, protecting it from photodamage and tuning color vision. Analogous to plumage carotenoid accumulation, I hypothesized that avian vision is subject to environmental and physiological constraints imposed by the acquisition and allocation of carotenoids. To test this hypothesis, I carried out a series of field and captive studies of the house finch to assess natural variation in and correlates of retinal carotenoid accumulation and to experimentally investigate the effects of dietary carotenoid availability, immune activation, and light exposure on retinal carotenoid accumulation. Moreover, through dietary manipulations of retinal carotenoid accumulation, I tested the impacts of carotenoid accumulation on visually mediated foraging and mate choice behaviors. My results indicate that avian retinal carotenoid accumulation is variable and significantly influenced by dietary carotenoid availability and immune system activity. Behavioral studies suggest that retinal carotenoid accumulation influences visual foraging performance and mediates a trade-off between color discrimination and photoreceptor sensitivity under dim-light conditions. Retinal accumulation did not influence female choice for male carotenoid-based coloration, indicating that a direct link between retinal accumulation and sexual selection for coloration is unlikely. However, retinal carotenoid accumulation in males was positively correlated with their plumage coloration. Thus, carotenoid-mediated visual health and performance or may be part of the information encoded in sexually selected coloration.
ContributorsToomey, Matthew (Author) / McGraw, Kevin J. (Thesis advisor) / Deviche, Pierre (Committee member) / Smith, Brian (Committee member) / Rutowski, Ronald (Committee member) / Verrelli, Brian (Committee member) / Arizona State University (Publisher)
Created2011
Description
A novel concept for integration of flame-assisted fuel cells (FFC) with a gas turbine is analyzed in this paper. Six different fuels (CH4, C3H8, JP-4, JP-5, JP-10(L), and H2) are investigated for the analytical model of the FFC integrated gas turbine hybrid system. As equivalence ratio increases, the efficiency of the hybrid system increases initially then decreases because the decreasing flow rate of air begins to outweigh the increasing hydrogen concentration. This occurs at an equivalence ratio of 2 for CH4. The thermodynamic cycle is analyzed using a temperature entropy diagram and a pressure volume diagram. These thermodynamic diagrams show as equivalence ratio increases, the power generated by the turbine in the hybrid setup decreases. Thermodynamic analysis was performed to verify that energy is conserved and the total chemical energy going into the system was equal to the heat rejected by the system plus the power generated by the system. Of the six fuels, the hybrid system performs best with H2 as the fuel. The electrical efficiency with H2 is predicted to be 27%, CH4 is 24%, C3H8 is 22%, JP-4 is 21%, JP-5 is 20%, and JP-10(L) is 20%. When H2 fuel is used, the overall integrated system is predicted to be 24.5% more efficient than the standard gas turbine system. The integrated system is predicted to be 23.0% more efficient with CH4, 21.9% more efficient with C3H8, 22.7% more efficient with JP-4, 21.3% more efficient with JP-5, and 20.8% more efficient with JP-10(L). The sensitivity of the model is investigated using various fuel utilizations. When CH4 fuel is used, the integrated system is predicted to be 22.7% more efficient with a fuel utilization efficiency of 90% compared to that of 30%.
ContributorsRupiper, Lauren Nicole (Author) / Milcarek, Ryan (Thesis director) / Wang, Liping (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / School for Engineering of Matter,Transport & Enrgy (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Patients with Alzheimer's disease (AD) exhibit a significantly higher incidence of unprovoked seizures compared to age-matched non-AD controls, and animal models of AD (i.e., transgenic human amyloid precursor protein, hAPP mice) display neural hyper-excitation and epileptic seizures. Hyperexcitation is particularly important because it contributes to the high incidence of epilepsy in AD patients as well as AD-related synaptic deficits and neurodegeneration. Given that there is significant amyloid-β (Aβ) accumulation and deposition in AD brain, Aβ exposure ultimately may be responsible for neural hyper-excitation in both AD patients and animal models. Emerging evidence indicates that α7 nicotinic acetylcholine receptors (α7-nAChR) are involved in AD pathology, because synaptic impairment and learning and memory deficits in a hAPPα7-/- mouse model are decreased by nAChR α7 subunit gene deletion. Given that Aβ potently modulates α7-nAChR function, that α7-nAChR expression is significantly enhanced in both AD patients and animal models, and that α7-nAChR play an important role in regulating neuronal excitability, it is reasonable that α7-nAChRs may contribute to Aβ-induced neural hyperexcitation. We hypothesize that increased α7-nAChR expression and function as a consequence of Aβ exposure is important in Aβ-induced neural hyperexcitation. In this project, we found that exposure of Aβ aggregates at a nanomolar range induces neuronal hyperexcitation and toxicity via an upregulation of α7-nAChR in cultured hippocampus pyramidal neurons. Aβ up-regulates α7-nAChRs function and expression through a post translational mechanism. α7-nAChR up-regulation occurs prior to Aβ-induced neuronal hyperexcitation and toxicity. Moreover, inhibition of α7-nAChR or deletion of α7-nAChR prevented Aβ induced neuronal hyperexcitation and toxicity, which suggests that α7-nAChRs are required for Aβ induced neuronal hyperexcitation and toxicity. These results reveal a profound role for α7-nAChR in mediating Aβ-induced neuronal hyperexcitation and toxicity and predict that Aβ-induced up-regulation of α7-nAChR could be an early and critical event in AD etiopathogenesis. Drugs targeting α7-nAChR or seizure activity could be viable therapies for AD treatment.
ContributorsLiu, Qiang (Author) / Wu, Jie (Thesis advisor) / Lukas, Ronald J (Committee member) / Chang, Yongchang (Committee member) / Sierks, Michael (Committee member) / Smith, Brian (Committee member) / Vu, Eric (Committee member) / Arizona State University (Publisher)
Created2011
Description
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
Description
Production from a high pressure gas well at a high production-rate encounters the risk of operating near the choking condition for a compressible flow in porous media. The unbounded gas pressure gradient near the point of choking, which is located near the wellbore, generates an effective tensile stress on the porous rock frame. This tensile stress almost always exceeds the tensile strength of the rock and it causes a tensile failure of the rock, leading to wellbore instability. In a porous rock, not all pores are choked at the same flow rate, and when just one pore is choked, the flow through the entire porous medium should be considered choked as the gas pressure gradient at the point of choking becomes singular. This thesis investigates the choking condition for compressible gas flow in a single microscopic pore. Quasi-one-dimensional analysis and axisymmetric numerical simulations of compressible gas flow in a pore scale varicose tube with a number of bumps are carried out, and the local Mach number and pressure along the tube are computed for the flow near choking condition. The effects of tube length, inlet-to-outlet pressure ratio, the number of bumps and the amplitude of the bumps on the choking condition are obtained. These critical values provide guidance for avoiding the choking condition in practice.
ContributorsYuan, Jing (Author) / Chen, Kangping (Thesis advisor) / Wang, Liping (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2013
Description
Specific dendritic morphologies are a hallmark of neuronal identity, circuit assembly, and behaviorally relevant function. Despite the importance of dendrites in brain health and disease, the functional consequences of dendritic shape remain largely unknown. This dissertation addresses two fundamental and interrelated aspects of dendrite neurobiology. First, by utilizing the genetic power of Drosophila melanogaster, these studies assess the developmental mechanisms underlying single neuron morphology, and subsequently investigate the functional and behavioral consequences resulting from developmental irregularity. Significant insights into the molecular mechanisms that contribute to dendrite development come from studies of Down syndrome cell adhesion molecule (Dscam). While these findings have been garnered primarily from sensory neurons whose arbors innervate a two-dimensional plane, it is likely that the principles apply in three-dimensional central neurons that provide the structural substrate for synaptic input and neural circuit formation. As such, this dissertation supports the hypothesis that neuron type impacts the realization of Dscam function. In fact, in Drosophila motoneurons, Dscam serves a previously unknown cell-autonomous function in dendrite growth. Dscam manipulations produced a range of dendritic phenotypes with alteration in branch number and length. Subsequent experiments exploited the dendritic alterations produced by Dscam manipulations in order to correlate dendritic structure with the suggested function of these neurons. These data indicate that basic motoneuron function and behavior are maintained even in the absence of all adult dendrites within the same neuron. By contrast, dendrites are required for adjusting motoneuron responses to specific challenging behavioral requirements. Here, I establish a direct link between dendritic structure and neuronal function at the level of the single cell, thus defining the structural substrates necessary for conferring various aspects of functional motor output. Taken together, information gathered from these studies can inform the quest in deciphering how complex cell morphologies and networks form and are precisely linked to their function.
ContributorsHutchinson, Katie Marie (Author) / Duch, Carsten (Thesis advisor) / Neisewander, Janet (Thesis advisor) / Newfeld, Stuart (Committee member) / Smith, Brian (Committee member) / Orchinik, Miles (Committee member) / Arizona State University (Publisher)
Created2013
Description
Olfaction is an important sensory modality for behavior since odors inform animals of the presence of food, potential mates, and predators. The fruit fly, Drosophila melanogaster, is a favorable model organism for the investigation of the biophysical mechanisms that contribute to olfaction because its olfactory system is anatomically similar to but simpler than that of vertebrates. In the Drosophila olfactory system, sensory transduction takes place in olfactory receptor neurons housed in the antennae and maxillary palps on the front of the head. The first stage of olfactory processing resides in the antennal lobe, where the structural unit is the glomerulus. There are at least three classes of neurons in the antennal lobe - excitatory projection neurons, excitatory local neurons, and inhibitory local neurons. The arborizations of the local neurons are confined to the antennal lobe, and output from the antennal lobe is carried by projection neurons to higher regions of the brain. Different views exist of how circuits of the Drosophila antennal lobe translate input from the olfactory receptor neurons into projection neuron output. We construct a conductance based neuronal network model of the Drosophila antennal lobe with the aim of understanding possible mechanisms within the antennal lobe that account for the variety of projection neuron activity observed in experimental data. We explore possible outputs obtained from olfactory receptor neuron input that mimic experimental recordings under different connectivity paradigms. First, we develop realistic minimal cell models for the excitatory local neurons, inhibitory local neurons, and projections neurons based on experimental data for Drosophila channel kinetics, and explore the firing characteristics and mathematical structure of these models. We then investigate possible interglomerular and intraglomerular connectivity patterns in the Drosophila antennal lobe, where olfactory receptor neuron input to the antennal lobe is modeled with Poisson spike trains, and synaptic connections within the antennal lobe are mediated by chemical synapses and gap junctions as described in the Drosophila antennal lobe literature. Our simulation results show that inhibitory local neurons spread inhibition among all glomeruli, where projection neuron responses are decreased relatively uniformly for connections of synaptic strengths that are homogeneous. Also, in the case of homogeneous excitatory synaptic connections, the excitatory local neuron network facilitates odor detection in the presence of weak stimuli. Excitatory local neurons can spread excitation from projection neurons that receive more input from olfactory receptor neurons to projection neurons that receive less input from olfactory receptor neurons. For the parameter values for the network models associated with these results, eLNs decrease the ability of the network to discriminate among single odors.
ContributorsLuli, Dori (Author) / Crook, Sharon (Thesis advisor) / Baer, Steven (Committee member) / Castillo-Chavez, Carlos (Committee member) / Smith, Brian (Committee member) / Arizona State University (Publisher)
Created2013
Description
Tesla turbo-machinery offers a robust, easily manufactured, extremely versatile prime mover with inherent capabilities making it perhaps the best, if not the only, solution for certain niche applications. The goal of this thesis is not to optimize the performance of the Tesla turbine, but to compare its performance with various working fluids. Theoretical and experimental analyses of a turbine-generator assembly utilizing compressed air, saturated steam and water as the working fluids were performed and are presented in this work. A brief background and explanation of the technology is provided along with potential applications. A theoretical thermodynamic analysis is outlined, resulting in turbine and rotor efficiencies, power outputs and Reynolds numbers calculated for the turbine for various combinations of working fluids and inlet nozzles. The results indicate the turbine is capable of achieving a turbine efficiency of 31.17 ± 3.61% and an estimated rotor efficiency 95 ± 9.32%. These efficiencies are promising considering the numerous losses still present in the current design. Calculation of the Reynolds number provided some capability to determine the flow behavior and how that behavior impacts the performance and efficiency of the Tesla turbine. It was determined that turbulence in the flow is essential to achieving high power outputs and high efficiency. Although the efficiency, after peaking, begins to slightly taper off as the flow becomes increasingly turbulent, the power output maintains a steady linear increase.
ContributorsPeshlakai, Aaron (Author) / Phelan, Patrick (Thesis advisor) / Trimble, Steve (Committee member) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2012
Description
Of all the signals and cues that orchestrate the activities of a social insect colony, the reproductives' fertility pheromones are perhaps the most fundamental. These pheromones regulate reproductive division of labor, a defining characteristic of eusociality. Despite their critical role, reproductive fertility pheromones are not evenly expressed across the development of a social insect colony and may even be absent in the earliest colony stages. In the ant Camponotus floridanus, queens of incipient colonies do not produce the cuticular hydrocarbons that serve as fertility and egg-marking signals in this species. My dissertation investigates the consequences of the dramatic change in the quantity of these pheromones that occurs as the colony grows. C. floridanus workers from large, established colonies use egg surface hydrocarbons to discriminate among eggs. Eggs with surface hydrocarbons typical of eggs laid by established queens are nurtured, whereas eggs lacking these signals (i.e., eggs laid by workers and incipient queens) are destroyed. I characterized how workers from incipient colonies responded to eggs lacking queen fertility hydrocarbons. I found that established-queen-laid eggs, incipient-queen-laid eggs, and worker-laid eggs were not destroyed by workers at this colony stage. Destruction of worker-laid eggs is a form of policing, and theoretical models predict that policing should be strongest in incipient colonies. Since there was no evidence of policing by egg-eating in incipient C. floridanus colonies, I searched for evidence of another policing mechanism at this colony stage. Finding none, I discuss reasons why policing behavior may not be expressed in incipient colonies. I then considered the mechanism that accounts for the change in workers' response to eggs. By manipulating ants' egg experience and testing their egg-policing decisions, I found that ants use a combination of learned and innate criteria to discriminate between targets of care and destruction. Finally, I investigated how the increasing strength of queen-fertility hydrocarbons affects nestmate recognition, which also relies on cuticular hydrocarbons. I found that queens with strong fertility hydrocarbons can be transferred between established colonies without aggression, but they cannot be introduced into incipient colonies. Queens from incipient colonies cannot be transferred into incipient or established colonies.
ContributorsMoore, Dani (Author) / Liebig, Juergen (Thesis advisor) / Gadau, Juergen (Committee member) / Pratt, Stephen (Committee member) / Smith, Brian (Committee member) / Rutowski, Ronald (Committee member) / Arizona State University (Publisher)
Created2012
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 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