Matching Items (22)
Description
This work presents two complementary studies that propose heuristic methods to capture characteristics of data using the ensemble learning method of random forest. The first study is motivated by the problem in education of determining teacher effectiveness in student achievement. Value-added models (VAMs), constructed as linear mixed models, use students’ test scores as outcome variables and teachers’ contributions as random effects to ascribe changes in student performance to the teachers who have taught them. The VAMs teacher score is the empirical best linear unbiased predictor (EBLUP). This approach is limited by the adequacy of the assumed model specification with respect to the unknown underlying model. In that regard, this study proposes alternative ways to rank teacher effects that are not dependent on a given model by introducing two variable importance measures (VIMs), the node-proportion and the covariate-proportion. These VIMs are novel because they take into account the final configuration of the terminal nodes in the constitutive trees in a random forest. In a simulation study, under a variety of conditions, true rankings of teacher effects are compared with estimated rankings obtained using three sources: the newly proposed VIMs, existing VIMs, and EBLUPs from the assumed linear model specification. The newly proposed VIMs outperform all others in various scenarios where the model was misspecified. The second study develops two novel interaction measures. These measures could be used within but are not restricted to the VAM framework. The distribution-based measure is constructed to identify interactions in a general setting where a model specification is not assumed in advance. In turn, the mean-based measure is built to estimate interactions when the model specification is assumed to be linear. Both measures are unique in their construction; they take into account not only the outcome values, but also the internal structure of the trees in a random forest. In a separate simulation study, under a variety of conditions, the proposed measures are found to identify and estimate second-order interactions.
ContributorsValdivia, Arturo (Author) / Eubank, Randall (Thesis advisor) / Young, Dennis (Committee member) / Reiser, Mark R. (Committee member) / Kao, Ming-Hung (Committee member) / Broatch, Jennifer (Committee member) / Arizona State University (Publisher)
Created2013
Description
The purpose of this study was to compare perceptions of success and failure, attributions of success and failure, predictions of future success, and reports of out-of-class engagement in composition among middle school band students composing in open task conditions (n = 32) and closed task conditions (n = 31). Two intact band classes at the same middle school were randomly assigned to treatment groups. Both treatment groups composed music once a week for eight weeks during their regular band time. In Treatment A (n = 32), the open task group, students were told to compose music however they wished. In Treatment B (n = 31), the closed task group, students were given specific, structured composition assignments to complete each week. At the end of each session, students were asked to complete a Composing Diary in which they reported what they did each week. Their responses were coded for evidence of perceptions of success and failure as well as out-of-class engagement in composing. At the end of eight weeks, students were given three additional measures: the Music Attributions Survey to measure attributions of success and failure on 11 different subscales; the Future Success survey to measure students' predictions of future success; and the Out-of-Class Engagement Letter to measure students' engagement with composition outside of the classroom. Results indicated that students in the open task group and students in the closed task group behaved similarly. There were no significant differences between treatment groups in terms of perceptions of success or failure as composers, predictions of future success composing music, and reports of out-of-class engagement in composition. Students who felt they failed at composing made similar attributions for their failure in both treatment groups. Students who felt they succeeded also made similar attributions for their success in both treatment groups, with one exception. Successful students in the closed task group rated Peer Influence significantly higher than the successful students in the open task group. The findings of this study suggest that understanding individual student's attributions and offering a variety of composing tasks as part of music curricula may help educators meet students' needs.
ContributorsSchwartz, Emily, 1985- (Author) / Stauffer, Sandra L (Thesis advisor) / Tobias, Evan (Committee member) / Schmidt, Margaret (Committee member) / Broatch, Jennifer (Committee member) / Sullivan, Jill (Committee member) / Arizona State University (Publisher)
Created2014
Description
Correlation is common in many types of data, including those collected through longitudinal studies or in a hierarchical structure. In the case of clustering, or repeated measurements, there is inherent correlation between observations within the same group, or between observations obtained on the same subject. Longitudinal studies also introduce association between the covariates and the outcomes across time. When multiple outcomes are of interest, association may exist between the various models. These correlations can lead to issues in model fitting and inference if not properly accounted for. This dissertation presents three papers discussing appropriate methods to properly consider different types of association. The first paper introduces an ANOVA based measure of intraclass correlation for three level hierarchical data with binary outcomes, and corresponding properties. This measure is useful for evaluating when the correlation due to clustering warrants a more complex model. This measure is used to investigate AIDS knowledge in a clustered study conducted in Bangladesh. The second paper develops the Partitioned generalized method of moments (Partitioned GMM) model for longitudinal studies. This model utilizes valid moment conditions to separately estimate the varying effects of each time-dependent covariate on the outcome over time using multiple coefficients. The model is fit to data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to investigate risk factors of childhood obesity. In the third paper, the Partitioned GMM model is extended to jointly estimate regression models for multiple outcomes of interest. Thus, this approach takes into account both the correlation between the multivariate outcomes, as well as the correlation due to time-dependency in longitudinal studies. The model utilizes an expanded weight matrix and objective function composed of valid moment conditions to simultaneously estimate optimal regression coefficients. This approach is applied to Add Health data to simultaneously study drivers of outcomes including smoking, social alcohol usage, and obesity in children.
ContributorsIrimata, Kyle (Author) / Wilson, Jeffrey R (Thesis advisor) / Broatch, Jennifer (Committee member) / Kamarianakis, Ioannis (Committee member) / Kao, Ming-Hung (Committee member) / Reiser, Mark R. (Committee member) / Arizona State University (Publisher)
Created2018
Description
Vitamin D, a bioactive lipid and essential nutrient, is obtained by humans through either endogenous synthesis in response to UV light exposure or via nutritional intake. Once activated to its hormonal form, vitamin D binds to and activates the nuclear vitamin D receptor (VDR). Activation of VDR is known to modulate gene transcription in vitamin D target tissues such as kidney, colon, and bone; however, less is known about the ability of VDR to respond to "nutritional modulators". One such potential VDR modulator is resveratrol, a plant-derived polyphenol and potent antioxidant nutrient that also functions as a chemopreventative. Resveratrol is known to activate sirtuin-1, a deacetylase enzyme with potential anti-aging properties. This study explores the potential for resveratrol, an anticancer nutraceutical, to upregulate VDR activity through its effector protein, sirtuin-1. Furthermore, due to its putative interactions with several intracellular signaling pathways, klotho has been proposed as an anti-aging protein and tumor suppressor gene, while the Wnt/β-catenin signaling pathway drives enhanced cellular proliferation leading to numerous types of cancers, especially colorectal neoplasia. Thus, the ability of klotho to cooperate with vitamin D to inhibit oncogenic β-catenin signaling was also analyzed. The experiments and resultant data presented in this thesis explore the potential role of VDR as a physiologically relevant nutritional sensor in human cells. This novel study reveals the importance of nutrient modulation of the VDR system by vitamin D and resveratrol and how this might represent a molecular mechanism that is responsible for the putative anti-cancer actions of vitamin D. Furthermore, this study enhances our understanding of how vitamin D/VDR and resveratrol interact with klotho and how this interaction affects β-catenin signaling to mitigate oncogenic growth and differentiation. This works demonstrates that the vitamin D hormone serves as a likely chemopreventive agent for various types of cancers through control of anti-oxidation and cellular proliferation pathways via its nuclear receptor. Our results also indicate the potential for resveratrol, an anticancer nutraceutical, to upregulate VDR activity through SIRT1. Furthermore, the novel data presented in this work illustrate that klotho, an anti-aging protein, cooperates with vitamin D to synergistically inhibit oncogenic β-catenin signaling. Ultimately, this study enhances our understating of the molecular pathways that underpin nutritional chemoprevention, and how modulation of these pathways via dietary intervention may lead to advances in public health strategies to eventually curb carcinogenesis.
ContributorsKhan, Zainab (Author) / Jurutka, Peter (Thesis director) / Hackney Price, Jennifer (Committee member) / School of Mathematical and Natural Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Rainbowfish, Melanotaenia splendida, are a common freshwater species in tropical regions of the world. They are members of the Atheriniformes (Atherinomorpha), the silverside fishes, which are known for some unusual feeding behaviors. Their close relatives, the Cypriniformes, such as mollies, guppies, and mosquitofish, are well studied and exhibit innovative morphologies associated with feeding. The third member of the Atherinomorphs, the Beloniformes, contains the recognizably odd needlefish, halfbeaks, and flying fishes. As a group, it is fair to say that the Atherinomorpha contain some pretty unusual fishes. The purpose of this project was to gain a further understanding of the unique feeding kinematics of Atheriniform fishes using the rainbowfish as an exemplar species. Feeding kinematics were quantified using high speed video recording unrestrained feeding events. Three feeding events from five individuals were analyzed frame by frame, from the time of the mouth opening to mouth closing. The X,Y coordinates of seven specific points were used to calculate the following kinematic variables: cranial elevation, gape distance, premaxillary protrusion, and hyoid depression. The contribution of cranial elevation to the strike was inconsistent. At times the fish raised the head as they expanded the mouth for prey capture, and at other times they did not. Cranial elevation is theoretically important for expanding the head during suction prey capture. Hyoid depression was more consistent, and clearly contributed to expansion of the head elements. Premaxillary protrusion contributed strongly to the event, and the jaws are closed with the premaxilla still protruded, facilitating a ‘nipping’ style jaw closure. A nipping style of prey capture is much like the Cyprinodontiforms, however, in rainbowfish, the event was quicker, and appeared to rely heavily on suction. We used both cleared and stained specimens and CT scans to investigate the underlying morphology of rainbowfish. These images revealed nearly microscopic teeth on the exterior of the jaws, and other features associated with feeding on highly elusive prey (i.e. prey that are mobile and likely to be able to escape predation). Further examination revealed a surprisingly well developed set of pharyngeal jaws, secondary to the oral jaws. The structure of the pharyngeal jaws suggested that most of the prey processing occurred within the pharynx.
ContributorsLerma, Sarahi (Author) / Ferry, Lara A. (Thesis director) / Hackney Price, Jennifer (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Natural Sciences (Contributor) / School of Social and Behavioral Sciences (Contributor)
Created2015-05
Description
With the advent of sophisticated computer technology, we increasingly see the use of computational techniques in the study of problems from a variety of disciplines, including the humanities. In a field such as poetry, where classic works are subject to frequent re-analysis over the course of years, decades, or even centuries, there is a certain demand for fresh approaches to familiar tasks, and such breaks from convention may even be necessary for the advancement of the field. Existing quantitative studies of poetry have employed computational techniques in their analyses, however, there remains work to be done with regards to the deployment of deep neural networks on large corpora of poetry to classify portions of the works contained therein based on certain features. While applications of neural networks to social media sites, consumer reviews, and other web-originated data are common within computational linguistics and natural language processing, comparatively little work has been done on the computational analysis of poetry using the same techniques. In this work, I begin to lay out the first steps for the study of poetry using neural networks. Using a convolutional neural network to classify author birth date, I was able to not only extract a non-trivial signal from the data, but also identify the presence of clustering within by-author model accuracy. While definitive conclusions about the cause of this clustering were not reached, investigation of this clustering reveals immense heterogeneity in the traits of accurately classified authors. Further study may unpack this clustering and reveal key insights about how temporal information is encoded in poetry. The study of poetry using neural networks remains very open but exhibits potential to be an interesting and deep area of work.
ContributorsGoodloe, Oscar Laurence (Author) / Nishimura, Joel (Thesis director) / Broatch, Jennifer (Committee member) / School of Mathematical and Natural Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
As threats to Earth's biodiversity continue to evolve, an effective methodology to predict such threats is crucial to ensure the survival of living species. Organizations like the International Union for Conservation of Nature (IUCN) monitor the Earth's environmental networks to preserve the sanctity of terrestrial and marine life. The IUCN Red List of Threatened Species informs the conservation activities of governments as a world standard of species' risks of extinction. However, the IUCN's current methodology is, in some ways, inefficient given the immense volume of Earth's species and the laboriousness of its species' risk classification process. IUCN assessors can take years to classify a species' extinction risk, even as that species continues to decline. Therefore, to supplement the IUCN's classification process and thus bolster conservationist efforts for threatened species, a Random Forest model was constructed, trained on a group of fish species previously classified by the IUCN Red List. This Random Forest model both validates the IUCN Red List's classification method and offers a highly efficient, supplemental classification method for species' extinction risk. In addition, this Random Forest model is applicable to species with deficient data, which the IUCN Red List is otherwise unable to classify, thus engendering conservationist efforts for previously obscure species. Although this Random Forest model is built specifically for the trained fish species (Sparidae), the methodology can and should be extended to additional species.
ContributorsWoodyard, Megan (Author) / Broatch, Jennifer (Thesis director) / Polidoro, Beth (Committee member) / Mancenido, Michelle (Committee member) / School of Humanities, Arts, and Cultural Studies (Contributor) / School of Mathematical and Natural Sciences (Contributor) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Bexarotene (Bex) is a FDA-approved drug used to treat cutaneous T-cell lymphoma (CTCL). It binds with high affinity to the retinoid-X-receptor (RXR), a nuclear receptor implicated in numerous biological pathways. Bex may have the potential to attenuate estrogenic activity by acting as an estrogen receptor alpha (ERα) signaling antagonist, and can therefore be used to treat ERα-positive cancers, such as breast cancer. Using dual luciferase reporter assays, real-time qRT-PCR, and metabolic proliferation assays, the anti-estrogenic properties of Bex were ascertained. However, since Bex produces numerous contraindications, select novel RXR drug analogs were also evaluated. Results revealed that, in luciferase assays, Bex could significantly (P < 0.01) inhibit the transcriptional activity of ERα, so much so that it rivaled ER pan-antagonist ZK164015 in potency. Bex was also able to suppress the proliferation of two breast cancer cell models, MCF-7 and T-47D, and downregulate the expression of an estrogen receptor target gene (A-myb), which is responsible for cell proliferation. In addition, novel analogs A30, A33, A35, and A38 were evaluated as being more potent at inhibiting ERE-mediated transcription than Bex at lower concentrations. Analogs A34 and A35 were able to suppress MCF-7 cell proliferation to a degree comparable to that of Bex. Inhibition of T-47D cell proliferation, by contrast, was best achieved by analogs A34 and A36. For those with ERα – positive breast cancer who are refractory to current chemotherapeutics used to treat breast cancer, Bex and its analogs may prove to be useful alternative options.
ContributorsBains, Supreet (Author) / Jurutka, Peter (Thesis director) / Hackney Price, Jennifer (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Colchicine is a chemical known for inhibiting mitosis during eukaryotic cellular reproduction by halting the tubulin formation necessary for the division of the chromosomes. The meristem is the primary source of mitosis in developing flowering plants, and it was the focus of our research to determine if the hindrance of mitosis would interfere with the production of capsaicinoids within pungent pepper plants. Moruga Scorpion peppers have one of the world's highest concentration of capsaicinoids with Scoville Heat Units (SHU) averaging 1.2 million SHU (Bannister, 2012). The highest concentration of these capsaicinoids are within the placental and endocarp regions of the fruit, which are the primary location for capsaicinoid biosynthesis (Aza-Gonzalez & Nunez-Palenius, 2010). Hindering mitosis from the earliest stage of development could lead to phenotypic abnormalities within those placental and endocarp regions, quite possibly through the mechanism of the induced polyploidy. In many cases, this polymerization interference is beneficial in cultivating plants with characterized polyploidy due to its desired increased size of fruits and leaves. Due to the lethal nature of colchicine, there is threshold of effectiveness where it may induce polyploidy or it may result in fatality. This first stage of this research sought to determine which lethal dose was required to elicit a polyploid response or lead to seed unviability. The second stage was analyzing capsaicin concentration within the fruit of the mature dosed plants to determine whether there was an effect on the capsaicinoids, and whether polyploidy played a role in those effects. The final inspection of this research was in germinating the seeds from the hottest F1 pepper that had developed the fruit the slowest of all the doses, and determining whether there were any effects on the germination or seedling development.
ContributorsKeppler, Lydia Jacqueline (Author) / Cahill, Thomas (Thesis director) / Sweat, Ken G. (Committee member) / Hackney Price, Jennifer (Committee member) / School of Mathematical and Natural Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
The significance of hormonal vitamin D in the numerous facets of health stresses the importance of elucidating the molecular mechanism(s) associated with 1,25D-VDR signaling modulators (e.g., resveratrol and sirtuin-1). Resveratrol (Res), a natural antioxidant, is a potent activator of NAD-dependent deacetylase sirtuin-1 (SIRT-1), an enzyme associated with longevity in animal models. This present study employed mammalian 2-hybrid (M2H) and vitamin D responsive element (VDRE)-based transcriptional assays to investigate the potential effects of Res and SIRT-1 on VDR signal transduction. Results from VDRE-based assays indicate that Res and SIRT-1 potentiate 1,25D-VDR activity via cell-and-promoter-specific pathways. In addition, 1,25D displacement experiments revealed an increase in VDR-bound radiolabeled 1,25D in the presence of Res, suggesting that Res may potentiate VDR transactivation by stimulating 1,25D binding. M2H assays in HEK293 cells were then utilized to assess levels of interaction between VDR and VDR comodulators, including RXR, SRC-1, and DRIP-205. Both Res and SIRT-1 increased the ability of VDR to associate with RXR; however, SRC-1 and DRIP-205 interactions were not enhanced. The activity of a novel, non-acetylatable VDR mutant, K413R, was probed revealing that K413R possesses amplified transactivation capacity over wild-type VDR. A SIRT-1 inhibitor, EX-527, was used to suppress endogenous SIRT-1, resulting in significantly decreased VDR transactivation. Finally, qPCR results in HEK293 cells revealed that the 1,25D-mediated induction of CYP24A1, an endogenous VDR target gene, was enhanced (85%) by SIRT-1 while Res increased CYP24A1 expression by 294%. The combination of 1,25D, SIRT-1, and Res amplified CYP24A1 expression by 326% over 1,25D, although this effect did not reach statistical significance when compared to the Res only treated group. We conclude that acetylation of VDR comprises a negative feedback loop that attenuates 1,25D-VDR signaling. This loop is suppressed by resveratrol/SIRT-1-catalyzed deacetylation of VDR, restoring VDR activity. The two compounds, 1,25-dihydroxyvitamin D (1,25D, vitamin D) and 5-hydroxytryptamine (5-HT, serotonin), have been proposed to play a significant role in abnormal social behavior associated with psychological conditions including autism spectrum disorders (ASDs) and depression; however, the mechanism underlying these associations has yet to be elucidated. Deficiencies in 1,25D or 5-HT have been linked to the increased incidence of ASDs. Thus, examining the modulation of genes involved in 5-HT biosynthesis, reuptake, and degradation is fundamental in linking low 1,25D levels to the increased incidence of psychiatric disorders. We propose that 1,25D regulates tryptophan hydroxylase-2 (TPH2), the initial and rate-limiting enzyme in the biosynthetic pathway of 5-HT. In order to evaluate the regulation of TPH2 in neuronal cells, three formulations of media were examined to optimize the cell culture conditions necessary for growth and morphology of embryonic rat medullary raphe (B14) serotonergic neurons. Next, quantitative real time-PCR (qPCR) was utilized to examine TPH2 expression in cultured human glioblastoma (U-87) cells and rat serotonergic neurons (B-14). Human TPH2 mRNA in U-87 cells was induced dose-dependently resulting in a 2.4-fold increase at 10 nM 1,25D. Strikingly, TPH2 mRNA in B-14 cells was observed to be 26- to 86-fold upregulated at 10 nM 1,25D; however, 1 nM and 100 nM 1,25D elicited significantly smaller inductions (8-fold and 1.2-fold, respectively).
ContributorsSabir, Marya Sabah (Author) / Jurutka, Peter (Thesis director) / Hackney Price, Jennifer (Committee member) / Sandrin, Todd R. (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12