Matching Items (983)
Description
Stream flow permanence plays a critical role in determining floristic composition, abundance, and diversity in the Sonoran Desert, but questions remain about the effects of stream flow permanence on butterfly composition, abundance, and diversity. Understanding the effects of flow permanence on butterflies and relevant subsets of butterflies (such as butterflies whose host plants are present) and comparing them to these same effects on plants and relevant subsets of plants (such as butterfly nectar plants and larval host plants) provided insight into pollinator and riparian conservation and restoration.
I surveyed four Sonoran desert stream sites, and found significant relationships between flow permanence and plant and butterfly species richness and abundance, as well as strong relationships between plant and butterfly abundance and between plant and butterfly species richness. Most notably, my results pointed to hosted butterflies as a break-out category of butterflies which may more clearly delineate ecological relationships between butterfly and plant abundance and diversity along Sonoran Desert streams; this can inform conservation decisions. Managing for hosted (resident) butterflies will necessarily entail managing for the presence of surface water, nectar forage, varying levels of canopy cover, and plant, nectar plant, and host plant diversity since the relationships between hosted butterfly species richness and/or abundance and all of these variables were significant, both statistically and ecologically.
I surveyed four Sonoran desert stream sites, and found significant relationships between flow permanence and plant and butterfly species richness and abundance, as well as strong relationships between plant and butterfly abundance and between plant and butterfly species richness. Most notably, my results pointed to hosted butterflies as a break-out category of butterflies which may more clearly delineate ecological relationships between butterfly and plant abundance and diversity along Sonoran Desert streams; this can inform conservation decisions. Managing for hosted (resident) butterflies will necessarily entail managing for the presence of surface water, nectar forage, varying levels of canopy cover, and plant, nectar plant, and host plant diversity since the relationships between hosted butterfly species richness and/or abundance and all of these variables were significant, both statistically and ecologically.
ContributorsButler, Lane (Author) / Stromberg, Juliet C. (Thesis advisor) / Makings, Elizabeth (Committee member) / Pearson, David L (Committee member) / Boggess, May (Committee member) / Buchmann, Stephen (Committee member) / Arizona State University (Publisher)
Created2015
Description
Small-scale fisheries are globally ubiquitous, employing more than 99% of the world’s fishers and providing over half of the world’s seafood. However, small-scale fisheries face many management challenges including declining catches, inadequate resources and infrastructure, and overcapacity. Baja California Sur, Mexico (BCS) is a region with diverse small-scale fisheries; these fisheries are intense, poorly regulated, and overlap with foraging hot spots of endangered sea turtles. In partnership with researchers, fishers, managers, and practitioners from Mexico and the United States, I documented bycatch rates of loggerhead turtles at BCS that represent the highest known megafauna bycatch rates worldwide. Concurrently, I conducted a literature review that determined gear modifications were generally more successful than other commonly used fisheries management strategies for mitigating bycatch of vulnerable megafauna including seabirds, marine mammals, and sea turtles. I then applied these results by partnering with researchers, local fishers, and Mexico’s federal fisheries science agency to develop and test two gear modifications (i.e. buoyless and illuminated nets) in operating net fisheries at BCS as potential solutions to reduce bycatch of endangered sea turtles, improve fisheries sustainability, and maintain fisher livelihoods. I found that buoyless nets significantly reduced mean turtle bycatch rates by 68% while maintaining target catch rates and composition. By contrast, illuminated nets did not significantly reduce turtle bycatch rates across day-night periods, although they reduced mean turtle bycatch rates by 50% at night. Illuminated nets, however, significantly reduced mean rates of total bycatch biomass by 34% across day-night periods while maintaining target fish catch and market value. I conclude with a policy analysis of the unilateral identification of Mexico by the U.S. State Department under section 610 of the Magnusson-Stevens Fishery Conservation and Management Act for failure to manage bycatch of loggerhead turtles at BCS. Taken together, the gear modifications developed and tested here represent promising bycatch mitigation solutions with strong potential for commercial adoption, but fleet-wide conversion to more selective and turtle-friendly gear (e.g. hook and line and/or traps) at BCS, coupled with coordinated international conservation action, is ultimately needed to eliminate sea turtle bycatch and further improve fisheries sustainability.
ContributorsSenko, Jesse (Author) / Smith, Andrew (Thesis advisor) / Boggess, May (Committee member) / Chhetri, Nalini (Committee member) / Jenkins, Lekelia (Committee member) / Minteer, Ben (Committee member) / Arizona State University (Publisher)
Created2015
Model Based Automatic and Robust Spike Sorting for Large Volumes of Multi-channel Extracellular Data
Description
Spike sorting is a critical step for single-unit-based analysis of neural activities extracellularly and simultaneously recorded using multi-channel electrodes. When dealing with recordings from very large numbers of neurons, existing methods, which are mostly semiautomatic in nature, become inadequate.
This dissertation aims at automating the spike sorting process. A high performance, automatic and computationally efficient spike detection and clustering system, namely, the M-Sorter2 is presented. The M-Sorter2 employs the modified multiscale correlation of wavelet coefficients (MCWC) for neural spike detection. At the center of the proposed M-Sorter2 are two automatic spike clustering methods. They share a common hierarchical agglomerative modeling (HAM) model search procedure to strategically form a sequence of mixture models, and a new model selection criterion called difference of model evidence (DoME) to automatically determine the number of clusters. The M-Sorter2 employs two methods differing by how they perform clustering to infer model parameters: one uses robust variational Bayes (RVB) and the other uses robust Expectation-Maximization (REM) for Student’s 𝑡-mixture modeling. The M-Sorter2 is thus a significantly improved approach to sorting as an automatic procedure.
M-Sorter2 was evaluated and benchmarked with popular algorithms using simulated, artificial and real data with truth that are openly available to researchers. Simulated datasets with known statistical distributions were first used to illustrate how the clustering algorithms, namely REMHAM and RVBHAM, provide robust clustering results under commonly experienced performance degrading conditions, such as random initialization of parameters, high dimensionality of data, low signal-to-noise ratio (SNR), ambiguous clusters, and asymmetry in cluster sizes. For the artificial dataset from single-channel recordings, the proposed sorter outperformed Wave_Clus, Plexon’s Offline Sorter and Klusta in most of the comparison cases. For the real dataset from multi-channel electrodes, tetrodes and polytrodes, the proposed sorter outperformed all comparison algorithms in terms of false positive and false negative rates. The software package presented in this dissertation is available for open access.
This dissertation aims at automating the spike sorting process. A high performance, automatic and computationally efficient spike detection and clustering system, namely, the M-Sorter2 is presented. The M-Sorter2 employs the modified multiscale correlation of wavelet coefficients (MCWC) for neural spike detection. At the center of the proposed M-Sorter2 are two automatic spike clustering methods. They share a common hierarchical agglomerative modeling (HAM) model search procedure to strategically form a sequence of mixture models, and a new model selection criterion called difference of model evidence (DoME) to automatically determine the number of clusters. The M-Sorter2 employs two methods differing by how they perform clustering to infer model parameters: one uses robust variational Bayes (RVB) and the other uses robust Expectation-Maximization (REM) for Student’s 𝑡-mixture modeling. The M-Sorter2 is thus a significantly improved approach to sorting as an automatic procedure.
M-Sorter2 was evaluated and benchmarked with popular algorithms using simulated, artificial and real data with truth that are openly available to researchers. Simulated datasets with known statistical distributions were first used to illustrate how the clustering algorithms, namely REMHAM and RVBHAM, provide robust clustering results under commonly experienced performance degrading conditions, such as random initialization of parameters, high dimensionality of data, low signal-to-noise ratio (SNR), ambiguous clusters, and asymmetry in cluster sizes. For the artificial dataset from single-channel recordings, the proposed sorter outperformed Wave_Clus, Plexon’s Offline Sorter and Klusta in most of the comparison cases. For the real dataset from multi-channel electrodes, tetrodes and polytrodes, the proposed sorter outperformed all comparison algorithms in terms of false positive and false negative rates. The software package presented in this dissertation is available for open access.
ContributorsMa, Weichao (Author) / Si, Jennie (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / He, Jingrui (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2019
Description
A Guide to Financial Mathematics is a comprehensive and easy-to-use study guide for students studying for the one of the first actuarial exams, Exam FM. While there are many resources available to students to study for these exams, this study is free to the students and offers an approach to the material similar to that of which is presented in class at ASU. The guide is available to students and professors in the new Actuarial Science degree program offered by ASU. There are twelve chapters, including financial calculator tips, detailed notes, examples, and practice exercises. Included at the end of the guide is a list of referenced material.
ContributorsDougher, Caroline Marie (Author) / Milovanovic, Jelena (Thesis director) / Boggess, May (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
Standardized testing plays a pivotal role in education. The results of standardized testing are used as performance metrics for students, teachers, and schools. The goal in education is to use performance metrics that are as accurate as possible. There are numerous measurement methods, but a popular choice is Student Growth Percentiles. This study will provide an analysis of Student Growth Percentiles in the Chandler Unified School District, located in Arizona. This study will use the Chandler Unified School District data to calculate standard error measurements and create Student Growth Percentile confidence intervals.
ContributorsSmith, Jacob (Author) / Boggess, May (Committee member) / Kashiwagi, Dean (Committee member) / Matthew, Strom (Committee member) / Barrett, The Honors College (Contributor)
Created2014-12
Description
In this paper, it is determined that learning retention decreases with age and there is a linear rate of decrease. In this study, four male Long-Evans Rats were used. The rats were each trained in 4 different tasks throughout their lifetime, using a food reward as motivation to work. Rats were said to have learned a task at the age when they received the highest accuracy during a task. A regression of learning retention was created for the set of studied rats: Learning Retention = 112.9 \u2014 0.085919 x (Age at End of Task), indicating that learning retention decreases at a linear rate, although rats have different rates of decrease of learning retention. The presence of behavioral training was determined not to have a positive impact on this rate. In behavioral studies, there were statistically significant differences between timid/outgoing and large ball ability between W12 and Z12. Rat W12 had overall better learning retention and also was more compliant, did not resist being picked up and traveled more frequently at high speeds (in the large ball) than Z12. Further potential studies include implanting an electrode into the frontal cortex in order to compare neuro feedback with learning retention, and using human subjects to find the rate of decrease in learning retention. The implication of this study, if also true for human subjects, is that older persons may need enhanced training or additional refresher training in order to retain information that is learned at a later age.
ContributorsSpinrad, Amelia (Author) / Si, Jennie (Thesis director) / Thompson, Patrick (Committee member) / Ma, Weichao (Committee member) / Barrett, The Honors College (Contributor)
Created2014-05
Description
With the new independence of adulthood, college students are a group susceptible to adopting unsupported, if not harmful, health practices. A survey of Arizona State University undergraduate students (N=200) was conducted to evaluate supplement use, trust in information sources, and beliefs about supplement regulation. Of those who reported using supplements, college students most frequently received information from friends and family. STEM majors in fields unrelated to health who were taking a supplement were found to be less likely to receive information about the supplement from a medical practitioner than those in health fields or those in non-STEM majors (-26.9%, p=0.018). STEM majors in health-related fields were 15.0% more likely to treat colds and/or cold symptoms with research-supported methods identified from reliable sources, while non-health STEM and non-STEM majors were more likely to take unsupported cold treatments (p=0.010). Surveyed students, regardless of major, also stated they would trust a medical practitioner for supplement advice above other sources (88.0%), and the majority expressed a belief that dietary supplements are approved/regulated by the government (59.8%).
ContributorsPerez, Jacob Tanner (Author) / Hendrickson, Kirstin (Thesis director) / Lefler, Scott (Committee member) / College of Liberal Arts and Sciences (Contributor) / School of Molecular Sciences (Contributor) / Department of Physics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This paper investigates whether measures of investor sentiment can be used to predict future total returns of the S&P 500 index. Rolling regressions and other statistical techniques are used to determine which indicators contain the most predictive information and which time horizons' returns are "easiest" to predict in a three year data set. The five "most predictive" indicators are used to predict 180 calendar day future returns of the market and simulated investment of hypothetical accounts is conducted in an independent six year data set based on the rolling regression future return predictions. Some indicators, most notably the VIX index, appear to contain predictive information which led to out-performance of the accounts that invested based on the rolling regression model's predictions.
ContributorsDundas, Matthew William (Author) / Boggess, May (Thesis director) / Budolfson, Arthur (Committee member) / Hedegaard, Esben (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor)
Created2013-12
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
I propose that norms regulate behaviors that negatively impact an individual's survival and reproduction. But because monitoring and enforcing of norms can be costly, individuals should be selective about which norms they police and under what circumstances they should do so. Two studies tested this idea by experimentally activating fitness-relevant motives and having participants answer questions about the policing of norms. The first study examined a norm prescribing respect for status and another proscribing sexual coercion. Results from Study 1 failed to support the hypotheses; activating a status-seeking motive did not have the predicted effects on policing of the respect-status norm nor did activating a mating motive have the predicted effects on policing of the respect-status norm or anti-coercion norm. Study 2 examined two new norms, one prescribing that people stay home when sick and the other proscribing people from having sex with another person's partners. Study 2 also manipulated whether self or others were the target of the policing. Study 2 failed to provide support; a disease avoidance motive failed to have effects on policing of the stay home when sick norm. Individuals in a relationship under a mating motive wanted less policing of others for violation of the mate poaching norm than those in a baseline condition, opposite of the predicted effects.
ContributorsSmith, M. Kristopher (Author) / Neuberg, L. Steven (Thesis director) / Presson, Clark (Committee member) / Hruschka, J. Daniel (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2013-05