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Description
This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data mining, machine learning, and geovisualization techniques. Three different types of spatiotemporal activity data were collected through different data collection approaches: (1) crowd sourced geo-tagged digital photos, representing people's travel activity, were retrieved from the website Panoramio.com through information retrieval techniques; (2) the same techniques were used to crawl crowd sourced GPS trajectory data and related metadata of their daily activities from the website OpenStreetMap.org; and finally (3) preschool children's daily activities and interactions tagged with time and geographical location were collected with a novel TabletPC-based behavioral coding system. The proposed methodology is applied to these data to (1) automatically recommend optimal multi-day and multi-stay travel itineraries for travelers based on discovered attractions from geo-tagged photos, (2) automatically detect movement types of unknown moving objects from GPS trajectories, and (3) explore dynamic social and socio-spatial patterns of preschool children's behavior from both geographic and social perspectives.
ContributorsLi, Xun (Author) / Anselin, Luc (Thesis advisor) / Koschinsky, Julia (Committee member) / Maciejewski, Ross (Committee member) / Rey, Sergio (Committee member) / Griffin, William (Committee member) / Arizona State University (Publisher)
Created2012
Description
In the mid-1970s, social scientists began observing marital dyad conversations in laboratory settings with the hope of determining which observable features best discriminate couples who report being either satisfied or unsatisfied with their relationship. These studies continued until about a decade ago when, in addition to increasing laboratory costs slowing the pace of new data collection, researchers realized that distressed couples were easier to quantitatively describe than nondistressed couples. Specifically, distressed couples exhibit rigid patterns of negativity whereas couples who report being maritally satisfied show minimal rigidity in the opposite direction \u2014 positivity. This was, and is, a theoretical dilemma: how can clinicians understand and eventually modify distressed relationships when the behavior of satisfied couples are less patterned, less predictable and more diverse? A recent study by Griffin and Li (2015), using contemporary machine learning techniques, reanalyzed existing marital interaction data and found that, contrary to expectation and existing theory, nondistressed couples should be further subdivided into two groups \u2014 those who are predictably positive or neutral and those who interact using diverse and varying levels of positive and negative behaviors. The latter group is the focus of this thesis. Using these recent findings as discussion points, I review how the unexpected behaviors in this novel group can maintain and possibly perpetuate marital satisfaction.
ContributorsAbdul-Quadir, Hasana (Author) / Griffin, William A. (Thesis director) / Li, Xun (Committee member) / Barrett, The Honors College (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor) / School of International Letters and Cultures (Contributor) / Hugh Downs School of Human Communication (Contributor)
Created2015-05
Description
In the digital humanities, there is a constant need to turn images and PDF files into plain text to apply analyses such as topic modelling, named entity recognition, and other techniques. However, although there exist different solutions to extract text embedded in PDF files or run OCR on images, they typically require additional training (for example, scholars have to learn how to use the command line) or are difficult to automate without programming skills. The Giles Ecosystem is a distributed system based on Apache Kafka that allows users to upload documents for text and image extraction. The system components are implemented using Java and the Spring Framework and are available under an Open Source license on GitHub (https://github.com/diging/).
ContributorsLessios-Damerow, Julia (Contributor) / Peirson, Erick (Contributor) / Laubichler, Manfred (Contributor) / ASU-SFI Center for Biosocial Complex Systems (Contributor)
Created2017-09-28
Description
This article reviews the range of delivery platforms that have been developed for the PySAL open source Python library for spatial analysis. This includes traditional desktop software (with a graphical user interface, command line or embedded in a computational notebook), open spatial analytics middleware, and web, cloud and distributed open geospatial analytics for decision support. A common thread throughout the discussion is the emphasis on openness, interoperability, and provenance management in a scientific workflow. The code base of the PySAL library provides the common computing framework underlying all delivery mechanisms.
ContributorsRey, Sergio (Author) / Anselin, Luc (Author) / Li, Xun (Author) / Pahle, Robert (Author) / Laura, Jason (Author) / Li, Wenwen (Author) / Koschinsky, Julia (Author) / College of Liberal Arts and Sciences (Contributor) / School of Geographical Sciences and Urban Planning (Contributor) / Computational Spatial Science (Contributor)
Created2015-06-01
Description
Honey bee workers display remarkable flexibility in the aging process. This plasticity is closely tied to behavioral maturation. Workers who initiate foraging behavior at earlier ages have shorter lifespans, and much of the variation in total lifespan can be explained by differences in pre-foraging lifespan. Vitellogenin (Vg), a yolk precursor protein, influences worker lifespan both as a regulator of behavioral maturation and through anti-oxidant and immune functions. Experimental reduction of Vg mRNA, and thus Vg protein levels, in wild-type bees results in precocious foraging behavior, decreased lifespan, and increased susceptibility to oxidative damage. We sought to separate the effects of Vg on lifespan due to behavioral maturation from those due to immune and antioxidant function using two selected strains of honey bees that differ in their phenotypic responsiveness to Vg gene knockdown. Surprisingly, we found that lifespans lengthen in the strain described as behaviorally and hormonally insensitive to Vg reduction. We then performed targeted gene expression analyses on genes hypothesized to mediate aging and lifespan: the insulin-like peptides (Ilp1 and 2) and manganese superoxide dismutase (mnSOD). The two honey bee Ilps are the most upstream components in the insulin-signaling pathway, which influences lifespan in Drosophila melanogaster and other organisms, while manganese superoxide dismutase encodes an enzyme with antioxidant functions in animals. We found expression differences in the llps in fat body related to behavior (llp1 and 2) and genetic background (Ilp2), but did not find strain by treatment effects. Expression of mnSOD was also affected by behavior and genetic background. Additionally, we observed a differential response to Vg knockdown in fat body expression of mnSOD, suggesting that antioxidant pathways may partially explain the strain-specific lifespan responses to Vg knockdown.
ContributorsIhle, Kate (Author) / Fondrk, M. Kim (Author) / Page, Robert (Author) / Amdam, Gro (Author) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2015-01-01
Description
Because collective cognition emerges from local signaling among group members, deciphering communication systems is crucial to understanding the underlying mechanisms. Alarm signals are widespread in the social insects and can elicit a variety of behavioral responses to danger, but the functional plasticity of these signals has not been well studied. Here we report an alarm pheromone in the ant Temnothorax rugatulus that elicits two different behaviors depending on context. When an ant was tethered inside an unfamiliar nest site and unable to move freely, she released a pheromone from her mandibular gland that signaled other ants to reject this nest as a potential new home, presumably to avoid potential danger. When the same pheromone was presented near the ants' home nest, they were instead attracted to it, presumably to respond to a threat to the colony. We used coupled gas chromatography/mass spectrometry to identify candidate compounds from the mandibular gland and tested each one in a nest choice bioassay. We found that 2,5-dimethylpyrazine was sufficient to induce rejection of a marked new nest and also to attract ants when released at the home nest. This is the first detailed investigation of chemical communication in the leptothoracine ants. We discuss the possibility that this pheromone's deterrent function can improve an emigrating colony's nest site selection performance.
ContributorsSasaki, Takao (Author) / Hoelldobler, Bert (Author) / Millar, Jocelyn G. (Author) / Pratt, Stephen (Author) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / ASU-SFI Center for Biosocial Complex Systems (Contributor) / Center for Social Dynamics and Complexity (Contributor)
Created2014-09-01
Description
Background
The reproductive ground plan hypothesis of social evolution suggests that reproductive controls of a solitary ancestor have been co-opted during social evolution, facilitating the division of labor among social insect workers. Despite substantial empirical support, the generality of this hypothesis is not universally accepted. Thus, we investigated the prediction of particular genes with pleiotropic effects on ovarian traits and social behavior in worker honey bees as a stringent test of the reproductive ground plan hypothesis. We complemented these tests with a comprehensive genome scan for additional quantitative trait loci (QTL) to gain a better understanding of the genetic architecture of the ovary size of honey bee workers, a morphological trait that is significant for understanding social insect caste evolution and general insect biology.
Results
Back-crossing hybrid European x Africanized honey bee queens to the Africanized parent colony generated two study populations with extraordinarily large worker ovaries. Despite the transgressive ovary phenotypes, several previously mapped QTL for social foraging behavior demonstrated ovary size effects, confirming the prediction of pleiotropic genetic effects on reproductive traits and social behavior. One major QTL for ovary size was detected in each backcross, along with several smaller effects and two QTL for ovary asymmetry. One of the main ovary size QTL coincided with a major QTL for ovary activation, explaining 3/4 of the phenotypic variance, although no simple positive correlation between ovary size and activation was observed.
Conclusions
Our results provide strong support for the reproductive ground plan hypothesis of evolution in study populations that are independent of the genetic stocks that originally led to the formulation of this hypothesis. As predicted, worker ovary size is genetically linked to multiple correlated traits of the complex division of labor in worker honey bees, known as the pollen hoarding syndrome. The genetic architecture of worker ovary size presumably consists of a combination of trait-specific loci and general regulators that affect the whole behavioral syndrome and may even play a role in caste determination. Several promising candidate genes in the QTL intervals await further study to clarify their potential role in social insect evolution and the regulation of insect fertility in general.
The reproductive ground plan hypothesis of social evolution suggests that reproductive controls of a solitary ancestor have been co-opted during social evolution, facilitating the division of labor among social insect workers. Despite substantial empirical support, the generality of this hypothesis is not universally accepted. Thus, we investigated the prediction of particular genes with pleiotropic effects on ovarian traits and social behavior in worker honey bees as a stringent test of the reproductive ground plan hypothesis. We complemented these tests with a comprehensive genome scan for additional quantitative trait loci (QTL) to gain a better understanding of the genetic architecture of the ovary size of honey bee workers, a morphological trait that is significant for understanding social insect caste evolution and general insect biology.
Results
Back-crossing hybrid European x Africanized honey bee queens to the Africanized parent colony generated two study populations with extraordinarily large worker ovaries. Despite the transgressive ovary phenotypes, several previously mapped QTL for social foraging behavior demonstrated ovary size effects, confirming the prediction of pleiotropic genetic effects on reproductive traits and social behavior. One major QTL for ovary size was detected in each backcross, along with several smaller effects and two QTL for ovary asymmetry. One of the main ovary size QTL coincided with a major QTL for ovary activation, explaining 3/4 of the phenotypic variance, although no simple positive correlation between ovary size and activation was observed.
Conclusions
Our results provide strong support for the reproductive ground plan hypothesis of evolution in study populations that are independent of the genetic stocks that originally led to the formulation of this hypothesis. As predicted, worker ovary size is genetically linked to multiple correlated traits of the complex division of labor in worker honey bees, known as the pollen hoarding syndrome. The genetic architecture of worker ovary size presumably consists of a combination of trait-specific loci and general regulators that affect the whole behavioral syndrome and may even play a role in caste determination. Several promising candidate genes in the QTL intervals await further study to clarify their potential role in social insect evolution and the regulation of insect fertility in general.
ContributorsGraham, Allie M. (Author) / Munday, Michael D. (Author) / Kaftanoglu, Osman (Author) / Page, Robert (Author) / Amdam, Gro (Author) / Rueppell, Olav (Author) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2011-04-13
Description
Honeybees (Apis mellifera) are pollinators that face multiple challenges during foraging such as fungicides applied to floral sources. Fungicides are chemicals used to inhibit key fungal mechanisms like metabolism, but their effects remain relatively unknown in bees. In addition, studying the maturing bee can help us identify demographics that are more vulnerable to toxic materials like fungicides. The purpose of this study is test whether maturation and the fungicide Pristine influence the permeability of the blood-brain barrier. Specifically, we use a transportable dye to test how blood brain barrier transporter function responds to toxic insult and how it changes with age. Oral ingestion of Pristine by female workers did not have an effect on blood brain barrier permeability which suggests Pristine may have no or longer term consequences in the bee. However, blood brain barrier permeability changed with the bee's age which could be explained by the regulation of blood brain barrier transporters during natural transitions in hive task or the presence of hemolymph protein filtration
ContributorsPatel, Aamir S. (Author) / Amdam, Gro (Thesis director) / Harrison, Jon (Committee member) / Ozturk, Cahit (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Dire wolves have recently risen to fame as a result of the popular television program Game of Thrones, and thus many viewers know dire wolves as the sigil and loyal companions of the Stark house. Far fewer recognize dire wolves by their scientific name, Canis dirus, or understand the population history of this ‘fearsome wolf’ species that roamed the Americas until the megafaunal mass extinction event of the Late Pleistocene. Although numerous studies have examined the species using morphological and geographical methods, thus far their results have been either inconclusive or contradictory. Remaining questions include the relationships dire wolves share with other members of the Canis genus and the internal structure of their populations. Advancements in ancient DNA recovery methods may make it possible to study dire wolf specimens at the molecular level for the first time and may therefore prove useful in clarifying the answers to these questions. Eighteen dire wolf specimens were collected from across the United States and subjected to ancient DNA extraction, library preparation, amplification and purification, bait preparation and capture, and next-generation sequencing. There was an average of 76.9 unique reads and 5.73% coverage when mapped to the Canis familiaris reference genome in ultraconserved regions of the mitochondrial genome. The results indicate that endogenous ancient DNA was not successfully recovered and perhaps ancient DNA recovery methods have not advanced to the point of retrieving informative amounts of DNA from particularly old, thermally degraded specimens. Nevertheless, the ever-changing nature of ancient DNA research makes it vital to continually test the limitations of the field and suggests that ancient DNA recovery methods will prove useful in illuminating dire wolf population history at some point in the future.
ContributorsSkerry, Katherine Marie (Author) / Stone, Anne (Thesis director) / Amdam, Gro (Committee member) / Larson, Greger (Committee member) / School of Human Evolution and Social Change (Contributor) / School of Nutrition and Health Promotion (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Vitellogenin (vg) is a precursor protein of egg yolk in honeybees, but it is also known to have immunological functions. The purpose of this experiment was to determine the effect of vg on the viral load of deformed wing virus (DWV) in worker honey bees (Apis mellifera). I hypothesized that a reduction in vg expression would lead to an increase in the viral load. I collected 180 worker bees and split them into four groups: half the bees were subjected to a vg gene knockdown by injections of double stranded vg RNA, and the rest were injected with green fluorescent protein (gfp) double stranded RNA. Half of each group was thereafter injected with DWV, and half given a sham injection. The rate of mortality in all four groups was higher than expected, leaving only 17 bees total. I dissected these bees' fat bodies and extracted their RNA to test for vg and DWV. PCR results showed that, out of the small group of remaining bees, the levels of vg were not statistically different. Furthermore, both groups of virus-injected bees showed similar viral loads. Because of the high mortality rate bees and the lack of differing levels of vg transcript between experimental and control groups, I could not draw conclusions from these results. The high mortality could be caused by several factors: temperature-induced stress, repeated stress from the two injections, and stress from viral infection. In addition, it is possible that the vg dsRNA batch I used was faulty. This thesis exemplifies that information cannot safely be extracted when loss of sampling units result in a small datasets that do not represent the original sampling population.
ContributorsCrable, Emma Lewis (Author) / Amdam, Gro (Thesis director) / Wang, Ying (Committee member) / Dahan, Romain (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12