Matching Items (175)
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
The use of synthetic cathinones or "bath salts" has risen dramatically in recent years with one of the most popular being Methylendioxypyrovalerone (MDPV). Following the temporary legislative ban on the sale and distribution of this compound , a multitude of other cathinone derivatives have been synthesized. The current study seeks to compare the abuse potential of MDPV with one of the emergent synthetic cathinones 4-methylethcathinone (4-MEC), based on their respective ability to lower current thresholds in an intracranial self-stimulation (ICSS) paradigm. Following acute administration (0.1, 0.5, 1 and 2 mg/kg i.p.) MDPV was found to significantly lower ICSS thresholds at all doses tested (F4,35=11.549, p<0.001). However, following acute administration (0.3,1,3,10,30 mg/kg i.p) 4-MEC produced no significant ICSS threshold depression (F5,135= 0.622, p = 0.684). Together these findings suggest that while MDPV may possess significant abuse potential, other synthetic cathinones such as 4-MEC may have a drastically reduced potential for abuse.
ContributorsWegner, Scott Andrew (Author) / Olive, M. Foster (Thesis director) / Presson, Clark (Committee member) / Sanabria, Federico (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Department of Psychology (Contributor)
Created2013-05
Description
Chronic restraint stress impairs hippocampal-mediated spatial learning and memory, which improves following a post-stress recovery period. Here, we investigated whether brain derived neurotrophic factor (BDNF), a protein important for hippocampal function, would alter the recovery from chronic stress-induced spatial memory deficits. Adult male Sprague-Dawley rats were infused into the hippocampus with adeno- associated viral vectors containing the coding sequence for short interfering (si)RNA directed against BDNF or a scrambled sequence (Scr), with both containing the coding information for green fluorescent protein to aid in anatomical localization. Rats were then chronically restrained (wire mesh, 6h/d/21d) and assessed for spatial learning and memory using a radial arm water maze (RAWM) either immediately after stressor cessation (Str-Imm) or following a 21-day post-stress recovery period (Str-Rec). All groups learned the RAWM task similarly, but differed on the memory retention trial. Rats in the Str-Imm group, regardless of viral vector contents, committed more errors in the spatial reference memory domain than did non-stressed controls. Importantly, the typical improvement in spatial memory following recovery from chronic stress was blocked with the siRNA against BDNF, as Str-Rec-siRNA performed worse on the RAWM compared to the non-stressed controls or Str-Rec-Scr. These effects were specific for the reference memory domain as repeated entry errors that reflect spatial working memory were unaffected by stress condition or viral vector contents. These results demonstrate that hippocampal BDNF is necessary for the recovery from stress-induced hippocampal dependent spatial memory deficits in the reference memory domain.
ContributorsOrtiz, J. Bryce (Author) / Conrad, Cheryl D. (Thesis advisor) / Olive, M. Foster (Committee member) / Taylor, Sara (Committee member) / Bimonte-Nelson, Heather A. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Functional magnetic resonance imaging (fMRI) has been widely used to measure the retinotopic organization of early visual cortex in the human brain. Previous studies have identified multiple visual field maps (VFMs) based on statistical analysis of fMRI signals, but the resulting geometry has not been fully characterized with mathematical models. This thesis explores using concepts from computational conformal geometry to create a custom software framework for examining and generating quantitative mathematical models for characterizing the geometry of early visual areas in the human brain. The software framework includes a graphical user interface built on top of a selected core conformal flattening algorithm and various software tools compiled specifically for processing and examining retinotopic data. Three conformal flattening algorithms were implemented and evaluated for speed and how well they preserve the conformal metric. All three algorithms performed well in preserving the conformal metric but the speed and stability of the algorithms varied. The software framework performed correctly on actual retinotopic data collected using the standard travelling-wave experiment. Preliminary analysis of the Beltrami coefficient for the early data set shows that selected regions of V1 that contain reasonably smooth eccentricity and polar angle gradients do show significant local conformality, warranting further investigation of this approach for analysis of early and higher visual cortex.
ContributorsTa, Duyan (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Wonka, Peter (Committee member) / Arizona State University (Publisher)
Created2013
Description
The brain is a fundamental target of the stress response that promotes adaptation and survival but the repeated activation of the stress response has the potential alter cognition, emotion, and motivation, key functions of the limbic system. Three structures of the limbic system in particular, the hippocampus, medial prefrontal cortex (mPFC), and amygdala, are of special interest due to documented structural changes and their implication in post-traumatic stress disorder (PTSD). One of many notable chronic stress-induced changes include dendritic arbor restructuring, which reflect plasticity patterns in parallel with the direction of alterations observed in functional imaging studies in PTSD patients. For instance, chronic stress produces dendritic retraction in the hippocampus and mPFC, but dendritic hypertrophy in the amygdala, consistent with functional imaging in patients with PTSD. Some have hypothesized that these limbic region's modifications contribute to one's susceptibility to develop PTSD following a traumatic event. Consequently, we used a familiar chronic stress procedure in a rat model to create a vulnerable brain that might develop traits consistent with PTSD when presented with a challenge. In adult male rats, chronic stress by wire mesh restraint (6h/d/21d) was followed by a variety of behavioral tasks including radial arm water maze (RAWM), fear conditioning and extinction, and fear memory reconsolidation to determine chronic stress effects on behaviors mediated by these limbic structures. In chapter 2, we corroborated past findings that chronic stress caused hippocampal CA3 dendritic retraction. Importantly, we present new findings that CA3 dendritic retraction corresponded with poor spatial memory in the RAWM and that these outcomes reversed after a recovery period. In chapter 3, we also showed that chronic stress impaired mPFC-mediated extinction memory, findings that others have reported. Using carefully assessed behavior, we present new findings that chronic stress impacted nonassociative fear by enhancing contextual fear during extinction that generalized to a new context. Moreover, the generalization behavior corresponded with enhanced functional activation in the hippocampus and amygdala during fear extinction memory retrieval. In chapter 5, we showed for the first time that chronic stress enhanced amygdala functional activation during fear memory retrieval, i.e., reactivation. Moreover, these enhanced fear memories were resistant to protein synthesis interference to disrupt a previously formed memory, called reconsolidation in a novel attempt to weaken chronic stress enhanced traumatic memory. Collectively, these studies demonstrated the plastic and dynamic effects of chronic stress on limbic neurocircuitry implicated in PTSD. We showed that chronic stress created a structural and functional imbalance across the hippocampus, mPFC, and amygdala, which lead to a PTSD-like phenotype with persistent and exaggerated fear following fear conditioning. These behavioral disruptions in conjunction with morphological and functional imaging data reflect a chronic stress-induced imbalance between hippocampal and mPFC regulation in favor of amygdala function overdrive, and supports a novel approach for traumatic memory processing in PTSD.
ContributorsHoffman, Ann (Author) / Conrad, Cheryl D. (Thesis advisor) / Olive, M. Foster (Committee member) / Hammer, Jr., Ronald P. (Committee member) / Sanabria, Federico (Committee member) / Arizona State University (Publisher)
Created2013
Description
In blindness research, the corpus callosum (CC) is the most frequently studied sub-cortical structure, due to its important involvement in visual processing. While most callosal analyses from brain structural magnetic resonance images (MRI) are limited to the 2D mid-sagittal slice, we propose a novel framework to capture a complete set of 3D morphological differences in the corpus callosum between two groups of subjects. The CCs are segmented from whole brain T1-weighted MRI and modeled as 3D tetrahedral meshes. The callosal surface is divided into superior and inferior patches on which we compute a volumetric harmonic field by solving the Laplace's equation with Dirichlet boundary conditions. We adopt a refined tetrahedral mesh to compute the Laplacian operator, so our computation can achieve sub-voxel accuracy. Thickness is estimated by tracing the streamlines in the harmonic field. We combine areal changes found using surface tensor-based morphometry and thickness information into a vector at each vertex to be used as a metric for the statistical analysis. Group differences are assessed on this combined measure through Hotelling's T2 test. The method is applied to statistically compare three groups consisting of: congenitally blind (CB), late blind (LB; onset > 8 years old) and sighted (SC) subjects. Our results reveal significant differences in several regions of the CC between both blind groups and the sighted groups; and to a lesser extent between the LB and CB groups. These results demonstrate the crucial role of visual deprivation during the developmental period in reshaping the structural architecture of the CC.
ContributorsXu, Liang (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups or graphs. In this thesis, I first propose to solve a sparse learning model with a general group structure, where the predefined groups may overlap with each other. Then, I present three real world applications which can benefit from the group structured sparse learning technique. In the first application, I study the Alzheimer's Disease diagnosis problem using multi-modality neuroimaging data. In this dataset, not every subject has all data sources available, exhibiting an unique and challenging block-wise missing pattern. In the second application, I study the automatic annotation and retrieval of fruit-fly gene expression pattern images. Combined with the spatial information, sparse learning techniques can be used to construct effective representation of the expression images. In the third application, I present a new computational approach to annotate developmental stage for Drosophila embryos in the gene expression images. In addition, it provides a stage score that enables one to more finely annotate each embryo so that they are divided into early and late periods of development within standard stage demarcations. Stage scores help us to illuminate global gene activities and changes much better, and more refined stage annotations improve our ability to better interpret results when expression pattern matches are discovered between genes.
ContributorsYuan, Lei (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Xue, Guoliang (Committee member) / Kumar, Sudhir (Committee member) / Arizona State University (Publisher)
Created2013
Description
Woody plant encroachment is a worldwide phenomenon linked to water availability in semiarid systems. Nevertheless, the implications of woody plant encroachment on the hydrologic cycle are poorly understood, especially at the catchment scale. This study takes place in a pair of small semiarid rangeland undergoing the encroachment of Prosopis velutina Woot., or velvet mesquite tree. The similarly-sized basins are in close proximity, leading to equivalent meteorological and soil conditions. One basin was treated for mesquite in 1974, while the other represents the encroachment process. A sensor network was installed to measure ecohydrological states and fluxes, including precipitation, runoff, soil moisture and evapotranspiration. Observations from June 1, 2011 through September 30, 2012 are presented to describe the seasonality and spatial variability of ecohydrological conditions during the North American Monsoon (NAM). Runoff observations are linked to historical changes in runoff production in each watershed. Observations indicate that the mesquite-treated basin generates more runoff pulses and greater runoff volume for small rainfall events, while the mesquite-encroached basin generates more runoff volume for large rainfall events. A distributed hydrologic model is applied to both basins to investigate the runoff threshold processes experienced during the NAM. Vegetation in the two basins is classified into grass, mesquite, or bare soil using high-resolution imagery. Model predictions are used to investigate the vegetation controls on soil moisture, evapotranspiration, and runoff generation. The distributed model shows that grass and mesquite sites retain the highest levels of soil moisture. The model also captures the runoff generation differences between the two watersheds that have been observed over the past decade. Generally, grass sites in the mesquite-treated basin have less plant interception and evapotranspiration, leading to higher soil moisture that supports greater runoff for small rainfall events. For large rainfall events, the mesquite-encroached basin produces greater runoff due to its higher fraction of bare soil. The results of this study show that a distributed hydrologic model can be used to explain runoff threshold processes linked to woody plant encroachment at the catchment-scale and provides useful interpretations for rangeland management in semiarid areas.
ContributorsPierini, Nicole A (Author) / Vivoni, Enrique R (Thesis advisor) / Wang, Zhi-Hua (Committee member) / Mays, Larry W. (Committee member) / Arizona State University (Publisher)
Created2013
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
Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint.
ContributorsMao, Jingxian (Author) / Maciejewski, Ross (Thesis advisor) / Farin, Gerald (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012