Matching Items (69)
Filtering by

Clear all filters

148207-Thumbnail Image.png
Description

Optimal foraging theory provides a suite of tools that model the best way that an animal will <br/>structure its searching and processing decisions in uncertain environments. It has been <br/>successful characterizing real patterns of animal decision making, thereby providing insights<br/>into why animals behave the way they do. However, it does

Optimal foraging theory provides a suite of tools that model the best way that an animal will <br/>structure its searching and processing decisions in uncertain environments. It has been <br/>successful characterizing real patterns of animal decision making, thereby providing insights<br/>into why animals behave the way they do. However, it does not speak to how animals make<br/>decisions that tend to be adaptive. Using simulation studies, prior work has shown empirically<br/>that a simple decision-making heuristic tends to produce prey-choice behaviors that, on <br/>average, match the predicted behaviors of optimal foraging theory. That heuristic chooses<br/>to spend time processing an encountered prey item if that prey item's marginal rate of<br/>caloric gain (in calories per unit of processing time) is greater than the forager's<br/>current long-term rate of accumulated caloric gain (in calories per unit of total searching<br/>and processing time). Although this heuristic may seem intuitive, a rigorous mathematical<br/>argument for why it tends to produce the theorized optimal foraging theory behavior has<br/>not been developed. In this thesis, an analytical argument is given for why this<br/>simple decision-making heuristic is expected to realize the optimal performance<br/>predicted by optimal foraging theory. This theoretical guarantee not only provides support<br/>for why such a heuristic might be favored by natural selection, but it also provides<br/>support for why such a heuristic might a reliable tool for decision-making in autonomous<br/>engineered agents moving through theatres of uncertain rewards. Ultimately, this simple<br/>decision-making heuristic may provide a recipe for reinforcement learning in small robots<br/>with little computational capabilities.

ContributorsCothren, Liliaokeawawa Kiyoko (Author) / Pavlic, Theodore (Thesis director) / Brewer, Naala (Committee member) / School of Mathematical and Statistical Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
148454-Thumbnail Image.png
Description

This thesis is a supplement textbook designed with ASU’s MAT 370, or more generally, a course in introductory real analysis (IRA). With research in the realms of mathematics textbook creation and IRA pedagogy, this supplement aims to provide students or interested readers an additional presentation of the materials. Topics discussed

This thesis is a supplement textbook designed with ASU’s MAT 370, or more generally, a course in introductory real analysis (IRA). With research in the realms of mathematics textbook creation and IRA pedagogy, this supplement aims to provide students or interested readers an additional presentation of the materials. Topics discussed include the real number system, some topology of the real line, sequences of real numbers, continuity, differentiation, integration, and the Fundamental Theorem of Calculus. Special emphasis was placed on worked examples of proven results and exercises with hints at the end of every chapter. In this respect, this supplement aims to be both versatile and self-contained for the different mathematics skill levels of readers.

ContributorsCarpenter, Jackson Robinett (Author) / Jones, Don (Thesis director) / Quigg, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
136542-Thumbnail Image.png
Description
Introduction: Human papillomavirus (HPV) infection is seen in up to 90% of cases of cervical cancer, the third leading cancer cause of death in women. Current HPV screening focuses on only two HPV types and covers roughly 75% of HPV-associated cervical cancers. A protein based assay to test for antibody

Introduction: Human papillomavirus (HPV) infection is seen in up to 90% of cases of cervical cancer, the third leading cancer cause of death in women. Current HPV screening focuses on only two HPV types and covers roughly 75% of HPV-associated cervical cancers. A protein based assay to test for antibody biomarkers against 98 HPV antigens from both high and low risk types could provide an inexpensive and reliable method to screen for patients at risk of developing invasive cervical cancer. Methods: 98 codon optimized, commercially produced HPV genes were cloned into the pANT7_cGST vector, amplified in a bacterial host, and purified for mammalian expression using in vitro transcription/translation (IVTT) in a luminescence-based RAPID ELISA (RELISA) assay. Monoclonal antibodies were used to determine immune cross-reactivity between phylogenetically similar antigens. Lastly, several protein characteristics were examined to determine if they correlated with protein expression. Results: All genes were successfully moved into the destination vector and 86 of the 98 genes (88%) expressed protein at an adequate level. A difference was noted in expression by gene across HPV types but no correlation was found between protein size, pI, or aliphatic index and expression. Discussion: Further testing is needed to express the remaining 12 HPV genes. Once all genes have been successfully expressed and purified at high concentrations, DNA will be printed on microscope slides to create a protein microarray. This microarray will be used to screen HPV-positive patient sera for antibody biomarkers that may be indicative of cervical cancer and precancerous cervical neoplasias.
ContributorsMeshay, Ian Matthew (Author) / Anderson, Karen (Thesis director) / Magee, Mitch (Committee member) / Katchman, Benjamin (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2015-05
136077-Thumbnail Image.png
Description
Background: Coccidioidomycosis (Valley Fever) is a respiratory disease that is caused by the soil-dwelling fungi Coccidioides immitis and Coccidioides posadasii. Because fungal glycosylation patterns are distinct from mammalian glycosylation patterns, we hypothesized that certain lectins (carbohydrate-binding proteins) might have differential binding properties to coccidioidal glycoproteins, and therefore serve as a

Background: Coccidioidomycosis (Valley Fever) is a respiratory disease that is caused by the soil-dwelling fungi Coccidioides immitis and Coccidioides posadasii. Because fungal glycosylation patterns are distinct from mammalian glycosylation patterns, we hypothesized that certain lectins (carbohydrate-binding proteins) might have differential binding properties to coccidioidal glycoproteins, and therefore serve as a tool for the purification and characterization of these glycoproteins from patient specimens. Materials and Methods: To identify potential Coccidioides-binding lectins, lectin-based immunohistochemistry was performed using a panel of 21 lectins on lung tissue from human patients infected with Coccidioides. Enzyme-Linked Immunosorbent Assays (ELISAs) were used to confirm and test candidate Coccidioides-binding lectins for their ability to bind to proteins from antigen preparations of laboratory-grown Coccidioides. Inhibition IHC and ELISAs were used to confirm binding properties of these lectins. SDS-PAGE and mass spectrometry were performed on eluates from coccidioidal antigen preparations run through lectin-affinity chromatography columns to characterize and identify lectin-binding coccidioidal glycoproteins. Results: Two GlcNAc-binding lectins, GSLII and sWGA, bound specifically to spherules and endospores in infected human lung tissue, and not to adjacent lung tissue. The binding of these lectins to both Coccidioides proteins in lung tissue and to coccidioidal antigen preparations was confirmed to have lectin-like characteristics. SDS-PAGE analysis of eluates from lectin-affinity chromatography demonstrated that GSLII and sWGA bind to coccidioidal glycoproteins. Mass spectrometric identification of the top ten lectin affinity-purified glycoproteins demonstrated that GSLII and sWGA share affinity to a common set of coccidioidal glycoproteins. Conclusion: This is the first report of lectins that bind specifically to Coccidioides spherules and endospores in infected humans. These lectins may have the potential to serve as tools for a better method of detection and diagnosis of Valley Fever.
ContributorsChowdhury, Yasmynn (Author) / Lake, Douglas (Thesis director) / Grys, Thomas (Committee member) / Magee, Mitchell (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2015-05
136340-Thumbnail Image.png
Description
This paper focuses on the Szemerédi regularity lemma, a result in the field of extremal graph theory. The lemma says that every graph can be partitioned into bounded equal parts such that most edges of the graph span these partitions, and these edges are distributed in a fairly uniform way.

This paper focuses on the Szemerédi regularity lemma, a result in the field of extremal graph theory. The lemma says that every graph can be partitioned into bounded equal parts such that most edges of the graph span these partitions, and these edges are distributed in a fairly uniform way. Definitions and notation will be established, leading to explorations of three proofs of the regularity lemma. These are a version of the original proof, a Pythagoras proof utilizing elemental geometry, and a proof utilizing concepts of spectral graph theory. This paper is intended to supplement the proofs with background information about the concepts utilized. Furthermore, it is the hope that this paper will serve as another resource for students and others to begin study of the regularity lemma.
ContributorsByrne, Michael John (Author) / Czygrinow, Andrzej (Thesis director) / Kierstead, Hal (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
Description
Efforts to quantify the diversity of the T cell repertoire have generally been unsuccessful because not all factors accounting for diversity have been considered. In order to get an accurate representation of the T cell repertoire, one must incorporate analysis of germline gene diversity, diversity from somatic recombination, joining diversity

Efforts to quantify the diversity of the T cell repertoire have generally been unsuccessful because not all factors accounting for diversity have been considered. In order to get an accurate representation of the T cell repertoire, one must incorporate analysis of germline gene diversity, diversity from somatic recombination, joining diversity from N- and P- nucleotides, and TCR chain pairing diversity. Because of advances in high-throughput sequencing techniques, estimates have been able to account for diversity from TCR genes. However the ability to account for chain pairing diversity has been more difficult. In order to do so, single cell sorting techniques must be employed. These techniques, though effective, are time consuming and expensive. For this reason, no large-scale analyses have been done on the immune repertoires using these techniques. In this study, we propose a novel method for linking the two TCR chain sequences from an individual cell. DNA origami nanostructure technology is employed to capture and bind the TCRγ and TCRδ chain mRNA inside individual cells using probe strands complementary to the C-region of those sequences. We then use a dual-primer RT and ligation molecular strategy to link the two sequences together. The result is a single amplicon containing the CDR3 region of the TCRγ and TCRδ. This amplicon can then be easily PCR amplified using sequence specific primers, and sequenced. DNA origami nanostructures offer a rapid, cost-effective method alternative to conventional single cell sorting techniques, as both TCR mRNA can be captured on one origami molecule inside a single cell. At present, this study outlines a proof-of-principle analysis of the method to determine its functionality. Using known TCRγ and TCRδ sequences, the DNA origami and RT/PCR method was tested and resulting sequence data proved the effectiveness of the method. The original TCRγ and TCRδ sequences were linked together as a single amplicon containing both CDR3 regions of the genes. Thus, this method can be employed in further research to elucidate the γδ T cell repertoire. This technology is also easily adapted to any gene target or cell type and therefore presents a large opportunity to be used in other immune repertoire analysis and other immunological studies (such as the rapid identification and subsequent production of antibodies).
ContributorsPoindexter, Morgan Elizabeth (Author) / Blattman, Joseph (Thesis director) / Yan, Hao (Committee member) / Schoettle, Louis (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2015-05
136520-Thumbnail Image.png
Description
Deconvolution of noisy data is an ill-posed problem, and requires some form of regularization to stabilize its solution. Tikhonov regularization is the most common method used, but it depends on the choice of a regularization parameter λ which must generally be estimated using one of several common methods. These methods

Deconvolution of noisy data is an ill-posed problem, and requires some form of regularization to stabilize its solution. Tikhonov regularization is the most common method used, but it depends on the choice of a regularization parameter λ which must generally be estimated using one of several common methods. These methods can be computationally intensive, so I consider their behavior when only a portion of the sampled data is used. I show that the results of these methods converge as the sampling resolution increases, and use this to suggest a method of downsampling to estimate λ. I then present numerical results showing that this method can be feasible, and propose future avenues of inquiry.
ContributorsHansen, Jakob Kristian (Author) / Renaut, Rosemary (Thesis director) / Cochran, Douglas (Committee member) / Barrett, The Honors College (Contributor) / School of Music (Contributor) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
135873-Thumbnail Image.png
Description
Cancer remains one of the leading killers throughout the world. Death and disability due to lung cancer in particular accounts for one of the largest global economic burdens a disease presents. The burden on third-world countries is especially large due to the unusually large financial stress that comes from

Cancer remains one of the leading killers throughout the world. Death and disability due to lung cancer in particular accounts for one of the largest global economic burdens a disease presents. The burden on third-world countries is especially large due to the unusually large financial stress that comes from late tumor detection and expensive treatment options. Early detection using inexpensive techniques may relieve much of the burden throughout the world, not just in more developed countries. I examined the immune responses of lung cancer patients using immunosignatures – patterns of reactivity between host serum antibodies and random peptides. Immunosignatures reveal disease-specific patterns that are very reproducible. Immunosignaturing is a chip-based method that has the ability to display the antibody diversity from individual sera sample with low cost. Immunosignaturing is a medical diagnostic test that has many applications in current medical research and in diagnosis. From a previous clinical study, patients diagnosed for lung cancer were tested for their immunosignature vs. healthy non-cancer volunteers. The pattern of reactivity against the random peptides (the ‘immunosignature’) revealed common signals in cancer patients, absent from healthy controls. My study involved the search for common amino acid motifs in the cancer-specific peptides. My search through the hundreds of ‘hits’ revealed certain motifs that were repeated more times than expected by random chance. The amino acids that were the most conserved in each set include tryptophan, aspartic acid, glutamic acid, proline, alanine, serine, and lysine. The most overall conserved amino acid observed between each set was D - aspartic acid. The motifs were short (no more than 5-6 amino acids in a row), but the total number of motifs I identified was large enough to assure significance. I utilized Excel to organize the large peptide sequence libraries, then CLUSTALW to cluster similar-sequence peptides, then GLAM2 to find common themes in groups of peptides. In so doing, I found sequences that were also present in translated cancer expression libraries (RNA) that matched my motifs, suggesting that immunosignatures can find cancer-specific antigens that can be both diagnostic and potentially therapeutic.
ContributorsShiehzadegan, Shima (Author) / Johnston, Stephen (Thesis director) / Stafford, Phillip (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
135651-Thumbnail Image.png
Description
Honey bees (Apis mellifera) are responsible for pollinating nearly 80\% of all pollinated plants, meaning humans depend on honey bees to pollinate many staple crops. The success or failure of a colony is vital to global food production. There are various complex factors that can contribute to a colony's failure,

Honey bees (Apis mellifera) are responsible for pollinating nearly 80\% of all pollinated plants, meaning humans depend on honey bees to pollinate many staple crops. The success or failure of a colony is vital to global food production. There are various complex factors that can contribute to a colony's failure, including pesticides. Neonicotoids are a popular pesticide that have been used in recent times. In this study we concern ourselves with pesticides and its impact on honey bee colonies. Previous investigations that we draw significant inspiration from include Khoury et Al's \emph{A Quantitative Model of Honey Bee Colony Population Dynamics}, Henry et Al's \emph{A Common Pesticide Decreases Foraging Success and Survival in Honey Bees}, and Brown's \emph{ Mathematical Models of Honey Bee Populations: Rapid Population Decline}. In this project we extend a mathematical model to investigate the impact of pesticides on a honey bee colony, with birth rates and death rates being dependent on pesticides, and we see how these death rates influence the growth of a colony. Our studies have found an equilibrium point that depends on pesticides. Trace amounts of pesticide are detrimental as they not only affect death rates, but birth rates as well.
ContributorsSalinas, Armando (Author) / Vaz, Paul (Thesis director) / Jones, Donald (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
135739-Thumbnail Image.png
Description
Many programmable matter systems have been proposed and realized recently, each often tailored toward a particular task or physical setting. In our work on self-organizing particle systems, we abstract away from specific settings and instead describe programmable matter as a collection of simple computational elements (to be referred to as

Many programmable matter systems have been proposed and realized recently, each often tailored toward a particular task or physical setting. In our work on self-organizing particle systems, we abstract away from specific settings and instead describe programmable matter as a collection of simple computational elements (to be referred to as particles) with limited computational power that each perform fully distributed, local, asynchronous algorithms to solve system-wide problems of movement, configuration, and coordination. In this thesis, we focus on the compression problem, in which the particle system gathers as tightly together as possible, as in a sphere or its equivalent in the presence of some underlying geometry. While there are many ways to formalize what it means for a particle system to be compressed, we address three different notions of compression: (1) local compression, in which each individual particle utilizes local rules to create an overall convex structure containing no holes, (2) hole elimination, in which the particle system seeks to detect and eliminate any holes it contains, and (3) alpha-compression, in which the particle system seeks to shrink its perimeter to be within a constant factor of the minimum possible value. We analyze the behavior of each of these algorithms, examining correctness and convergence where appropriate. In the case of the Markov Chain Algorithm for Compression, we provide improvements to the original bounds for the bias parameter lambda which influences the system to either compress or expand. Lastly, we briefly discuss contributions to the problem of leader election--in which a particle system elects a single leader--since it acts as an important prerequisite for compression algorithms that use a predetermined seed particle.
ContributorsDaymude, Joshua Jungwoo (Author) / Richa, Andrea (Thesis director) / Kierstead, Henry (Committee member) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05