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Title: Measurement of Capture Excitation Functions with Neutron-Rich Nuclei
Creator: Watwood, Nathan
Date: 2021
Collection: Electronic Theses & Dissertations
Description: The study of heavy and superheavy elements is important for understanding nuclear structure at the limit of stability where macroscopic and microscopic effects are delicately balanced. It is a benchmark domain for a rich variety of calculations including time-dependent Hartree-Fock (TDHF) and density functional theory (DFT). One difficulty in studying these nuclei is the low formation probability. There is limited reliability in models to predict the outcome of superheavy particle formation...
Show moreThe study of heavy and superheavy elements is important for understanding nuclear structure at the limit of stability where macroscopic and microscopic effects are delicately balanced. It is a benchmark domain for a rich variety of calculations including time-dependent Hartree-Fock (TDHF) and density functional theory (DFT). One difficulty in studying these nuclei is the low formation probability. There is limited reliability in models to predict the outcome of superheavy particle formation due to the significantly large number of degrees of freedom. The fusion-fission process is a key reaction to access heavy element formation. Experiments were performed at the National Superconducting Cyclotron Laboratory (NSCL) at Michigan State University and at the Heavy Ion Accelerator Facility at Australian National University to measure fusion-fission excitation functions of two different combinations of Ca+Sm and K+Pb with varying neutron-richness. The excitation functions were measured at center-of-mass energies ranging from 1.1$\%$ to 0.9$\%$ above and below the predicted barrier heights. Measured cross sections were found to be comparable above the barrier regardless of neutron-richness. At and below the barrier, cross sections were enhanced for systems with positive Q-value neutron transfer channels. Furthermore the experiment performed at the NSCL was the first measurement of fusion-fission cross sections using the Active-Target Time Projection Chamber. This experiment demonstrated the successful reconstruction and identification of fission tracks and established the viability of performing similar experiments in the future.
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Title: Anarchist Mathematics Education : Ethic, Motivation, and Praxis
Creator: Bowers, David
Date: 2021
Collection: Electronic Theses & Dissertations
Description: Anarchists and (mathematics) education researchers generally share convergent interests regarding social (in)equality—that is to say, both groups share a concern over noticing inequality and making efforts to pursue social justice. In this dissertation, I employ three tenets of anarchism (cooperation; mutual aid; freedom from unjustified, coercive hierarchy) to formulate and live out the beginnings of a mathematics education research approach rooted anarchism, in pursuit of the larger goal of...
Show moreAnarchists and (mathematics) education researchers generally share convergent interests regarding social (in)equality—that is to say, both groups share a concern over noticing inequality and making efforts to pursue social justice. In this dissertation, I employ three tenets of anarchism (cooperation; mutual aid; freedom from unjustified, coercive hierarchy) to formulate and live out the beginnings of a mathematics education research approach rooted anarchism, in pursuit of the larger goal of developing cohesion between my anarchist worldview and the possible/probable products of a career in research. In so doing, I aim to simultaneously: (1) Respond productively to critiques of mathematics education as atheoretical, (2) articulate one possible cohesion between anarchist worldview and research methods, (3) unsettle some of the taken-for-granted assumptions of the mathematics education research community, and (4) invite others into more radical forms of anti-oppressive research and praxis.
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Title: Searches for Beyond the Standard Model Phenomena with the HAWC Detector
Creator: Lundeen II, Joseph Andrew
Date: 2021
Collection: Electronic Theses & Dissertations
Description: The universe is known to be dominated by a class of matter known as dark matter. No known particles possess the necessary characteristics to make up this dark sector. Possible extensions to the Standard Model produce promising candidates, in particular Weakly Interacting Massing Particles (WIMPs). Under this hypothesis, it may be possible to probe dark matter with high-energy gamma-rays. The High Altitude Water Cherenkov (HAWC) detector is a contemporary experiment sensitive to multi-TeV...
Show moreThe universe is known to be dominated by a class of matter known as dark matter. No known particles possess the necessary characteristics to make up this dark sector. Possible extensions to the Standard Model produce promising candidates, in particular Weakly Interacting Massing Particles (WIMPs). Under this hypothesis, it may be possible to probe dark matter with high-energy gamma-rays. The High Altitude Water Cherenkov (HAWC) detector is a contemporary experiment sensitive to multi-TeV cosmic gamma rays and able to observe approximately two thirds of the sky in any given day. With these properties, HAWC is able to search for high-mass classes of WIMPs from the dark matter halo surrounding the Milky Way galaxy and set strong constraints on dark matter annihilation and decay into gamma rays.
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Title: CROSS-RACE FRIENDSHIPS AND ADJUSTMENT : LONGITUDINAL STUDIES OF ASIAN AMERICAN ADOLESCENTS
Creator: Liu, Shizhu
Date: 2021
Collection: Electronic Theses & Dissertations
Description: Asian American adolescents’ cross-race friendships are poorly understood. Using data from the National Longitudinal Study for Adolescent to Adult Health, two longitudinal studies (Ns = 915 and 1,154) investigated the associations between cross-race friendships and psychosocial and academic adjustment among Asian American adolescents. Study 1 examined the influence of cross-race friendships (derived from quantity and quality measures) on trajectories of perception of peer prejudice at school....
Show moreAsian American adolescents’ cross-race friendships are poorly understood. Using data from the National Longitudinal Study for Adolescent to Adult Health, two longitudinal studies (Ns = 915 and 1,154) investigated the associations between cross-race friendships and psychosocial and academic adjustment among Asian American adolescents. Study 1 examined the influence of cross-race friendships (derived from quantity and quality measures) on trajectories of perception of peer prejudice at school. Results showed that cross-race friendships were associated with weaker perception of peer prejudice. Cross-race friendships measured as quantity had an immediate but short effect, while cross-race friendships measured as quality exerted a delayed but long-term influence over how Asian American adolescents perceive peer prejudice at school. Similar findings were observed for friendships with other non-White groups (but not with the White group and not for cross-ethnic friendships). Study 2 explored the directionality in associations between cross-race best friendships (i.e., the proportion of cross-race friends in one’s best female and male friend network) and psychological well-being and academic adjustment (school attachment and GPA). Results identified an overall linear decline in cross-race best friendships with age among Asian American adolescents. Cross-race best friendships positively influenced later self-esteem, but not the other way around. Higher levels of school attachment predicted greater decrease in cross-race best friendships, and declines in cross-race best friendships were accompanied by decreases in GPA for Asian American adolescents.
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Title: Dogs as a model of human retinal disease : extensions of the full-field electroretinogram to characterize normal and altered retinal function and applications to translatable gene augmentation therapy
Creator: Pasmanter, Nathaniel
Date: 2021
Collection: Electronic Theses & Dissertations
Description: Dogs are an important model of human retinal disease and are frequently used to develop and test translational therapies. Accurate characterization and quantification of the full-field electroretinogram (ERG) is essential in assessing potential treatments, yet many methods used to study the human ERG are rarely used in canine studies. This study aims to assess the utility of several mathematical models of the a- and b-waves and expanded protocols - such as chromatic, increasing background...
Show moreDogs are an important model of human retinal disease and are frequently used to develop and test translational therapies. Accurate characterization and quantification of the full-field electroretinogram (ERG) is essential in assessing potential treatments, yet many methods used to study the human ERG are rarely used in canine studies. This study aims to assess the utility of several mathematical models of the a- and b-waves and expanded protocols - such as chromatic, increasing background luminance, extended flickers, and long-duration flashes - in characterizing and analyzing the canine ERG. This study establishes baseline parameters for normal canine retinal function and quantifies the altered function in several dog models of human retinal disease. The results of this study demonstrate that mathematical models of the ERG waveforms provide excellent fits in normal dogs, and that expanded protocols better characterize rod and cone contributions to the canine ERG. These methods additionally enable direct comparison of quantified parameters between normal dogs and dog models of human disease as well as longitudinal assessment of disease progression and response to treatment with gene augmentation therapy. The results indicate that incorporating these methods adds valuable information of retinal function. Further research is needed to assess the reliability of these methods across breeds and different recording conditions.
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Title: A Neural Networks Based Method With Genetic Data Analysis of Complex Diseases
Creator: Lin, Jinghang
Date: 2021
Collection: Electronic Theses & Dissertations
Description: The genetic etiologies of common diseases are highly complex and heterogeneous. Classic statistical methods, such as linear regression, have successfully identified numerous genetic variants associated with complex diseases. Nonetheless, for most complex diseases, the identified variants only account for a small proportion of heritability. Challenges remain to discover additional variants contributing to complex diseases. In this dissertation, we developed an expectile neural network (ENN)...
Show moreThe genetic etiologies of common diseases are highly complex and heterogeneous. Classic statistical methods, such as linear regression, have successfully identified numerous genetic variants associated with complex diseases. Nonetheless, for most complex diseases, the identified variants only account for a small proportion of heritability. Challenges remain to discover additional variants contributing to complex diseases. In this dissertation, we developed an expectile neural network (ENN) method and applied the method to genetic data analysis. ENN provides a comprehensive view of relationships between genetic variants and disease phenotypes and can be used to discover genetic variants predisposing to sub-populations (e.g., high-risk groups). We integrate the idea of neural networks into ENN, making it capable of capturing non-linear and non-additive genetic effects (e.g., gene-gene interactions). Through simulations, we showed that the proposed method outperformed an existing expectile regression when there exist complex relationships between genetic variants and disease phenotypes. We also applied the proposed method to the genetic data from the Study of Addiction: Genetics and Environment(SAGE), investigating the relationships of candidate genes with smoking quantity. Neural networks have been widely used in applications. However, few studies have been focused on the statistical properties of neural networks. We further investigate the Asymptotic properties of ENN (e.g., consistency). Simulations have been conducted to test the validity of the theory.
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Title: The well-being of adults who volunteer with children at risk of child maltreatment
Creator: Bishop, Joshua Daniel
Date: 2019
Collection: Electronic Theses & Dissertations
Description: The lack of sufficient foster care homes, their inconsistent quality, and their risk of increasing negative outcomes for children highlight the need for more people to be involved in roles that support children at risk of maltreatment and foster care. While volunteer opportunities exist for supporting children after foster care placements, few opportunities exist to care for children who are at risk of maltreatment and foster care. Innovative approaches are being developed to provide such...
Show moreThe lack of sufficient foster care homes, their inconsistent quality, and their risk of increasing negative outcomes for children highlight the need for more people to be involved in roles that support children at risk of maltreatment and foster care. While volunteer opportunities exist for supporting children after foster care placements, few opportunities exist to care for children who are at risk of maltreatment and foster care. Innovative approaches are being developed to provide such opportunities. These approaches may find support from an emerging literature that has found a positive relationship between volunteerism and well-being. However, no studies have investigated the well-being of those who volunteer with children at risk of maltreatment and/or child welfare involvement. This dissertation, which is an exploratory, cross-sectional, quantitative study, will address this gap with a sample of volunteers (N = 302) from Safe Families for Children (SFFC), a faith-based organization that works to keep children safe during family crises, prevent child maltreatment, and reduce the number of children entering the child welfare system. The aim of the dissertation is to investigate whether volunteering and/or motivation are associated with seven dimensions of well-being: Happiness, Physical Health, Life Satisfaction, Self-Mastery, Self-Esteem, Anxiety, and Depression.Results demonstrate limited evidence of significant relationships between volunteering and well-being dimensions. There is also limited evidence of significant relationships between motivation and well-being. However, an important finding of this study is that despite the high time and emotional demands of doing this type of volunteer work, there is no apparent decrease or drop-off in the well-being of the volunteers. Rather, they are happy and physically healthy. They report very low levels of anxiety and depression, and they demonstrate a high degree of Self-Esteem, Self-Mastery, and Life Satisfaction. While some may believe that working with children at risk of maltreatment is stressful and may result in a decrease in well-being (Tyebjee, 2003), the results of this study suggest that it is not the case for Host Families from Safe Families for Children.The Confirmatory Factor Analysis used in this study is a unique contribution to the literature. It robustly demonstrates very reliable methods for operationalizing and measuring seven well-being dimensions as well as four dimensions of motivation. The analyses and results in this study go beyond typically used measurements of reliability and offer strong evidence for reliably measuring well-being in future studies.The most important limitation in this study is the lack of control or comparison group that would allow for investigating the difference in well-being among SFFC volunteers and those who are not SFFC volunteers.This study offers reliable options for future studies to operationalize well-being and motivation in a way that encourages accurate comparison between studies. Future studies should consider whether using measurement scales that can detect small changes in well-being among populations that may have a high level of well-being are important. Implications for practice include recommendations for volunteer managers to focus on volunteer efficiency, the importance of social support, and motivation.
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Title: The CA19-9 antigen and sTRA glycans define independent pancreatic ductal adenocarcinoma subpopulations improving diagnostic accuracy and approach to prognostic classification
Creator: Barnett, Daniel Mark
Date: 2020
Collection: Electronic Theses & Dissertations
Description: Pancreatic cancer is the third deadliest cancer annually in the United States. Although the vast majority of pancreatic cancer belongs to a single type called pancreatic ductal adenocarcinoma (PDAC), tremendous heterogeneity exists within and between PDACs in their biology and clinical behavior, making it difficult to optimize treatment strategies and therapeutics research. The possibility exists that the heterogeneity results from the fact that PDACs actually encompass several distinct...
Show morePancreatic cancer is the third deadliest cancer annually in the United States. Although the vast majority of pancreatic cancer belongs to a single type called pancreatic ductal adenocarcinoma (PDAC), tremendous heterogeneity exists within and between PDACs in their biology and clinical behavior, making it difficult to optimize treatment strategies and therapeutics research. The possibility exists that the heterogeneity results from the fact that PDACs actually encompass several distinct subtypes. Recent research has uncovered much evidence for such subtypes, but so far, the research has not produced clear definitions of the subtypes or associated biomarkers that define them. PDACs express a unique set of glycans derived largely from their origins as duct cells with a protective glycocalyx, including the CA19-9 antigen sialyl-Lewis A (sLeA), which serves as the only approved biomarker of pancreatic cancer, and its near relative sTRA. I hypothesized that the neoplastic cells of pancreatic ductal adenocarcinoma can be separated into subpopulations by their specific glycan expression of sTRA and CA19-9 and that these subpopulations have different functional characteristics and risk for disease dissemination. To test this hypothesis, I used several methods involving both primary specimens and model systems. First, I used multimarker immunofluorescence to detect sTRA and CA19-9 and compare their cellular locations, morphologies, and protein co-expression in tumor and matched adjacent uninvolved tissue, lymph nodes, and metastases. Immunofluorescence was detected by automated microscopy and quantified by novel automated software developed specifically for this project. Clear differences were observed between cancer cells that expressed only CA19-9 and those that expressed only sTRA, as well as a third cell subpopulation represented by dual expression. Dual expression represented a well differentiated epithelial population of cells in well-formed glandular tissue; CA19-9-only expression represented poor to moderately differentiated cell subpopulations of epithelial and flat (mesenchymal) characteristics; and sTRA-only expression represented poor to moderately differentiated cell subpopulations present in "foamy cytoplasm" and flat (mesenchymal) cell features. The co-expression of MUC5AC and beta-catenin was different between the subsets, indicating differences in differentiation. The differences were preserved in cell-line and patient-derived mouse xenografts. I next tested for differences in metastatic propensity. Xenograft tumors expressing sTRA were more strongly correlated with metastasis than those expressing CA19-9, and primary tumors showed differential correlations with lymph-node or liver metastasis depending on glycan expression. Finally, we tested whether blood plasma levels of these glycans correlate with tissue expression and whether elevations occur in distinct subpopulations of patients. The secretion of glycans into cell-culture media, mouse sera, or plasma from human patients generally correlated with glycan expression in the cancer cells, indicating the value of the glycans as serological biomarkers to indicate the tumor type. Certain tissues expressing only CA19-9 did not secrete to blood plasma, particularly in hyperglandular and very high stromal tissue, suggesting a new cause of false negative CA19-9 patients in PDAC detection. CA19-9 and sTRA were elevated in separate subgroups of patients, each with low false-positive rates. As a result, CA19-9 and sTRA together gave better accuracy of PDAC diagnosis than CA19-9 alone (97% specificity, 65% sensitivity vs. 96% and 46%). In summary, these studies support the concept that distinct subtypes of PDAC can be identified by the expression of sTRA or CA19-9. Additionally, sTRA co-expression with CA19-9 also identified a third subpopulation of PDAC with different morphology, likely aggressiveness, and secretion characteristics. Clinical translation is potentially enabled by the detection of these biomarkers in blood plasma, which provides a new approach to improve diagnosis, prognosis and treatment development.
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Title: Bimanual interference and neuromotor control in healthy individuals and those with cervical dystonia
Creator: Desrochers, Phillip C.
Date: 2019
Collection: Electronic Theses & Dissertations
Description: The purpose of this dissertation was to investigate interference during bimanual movements in healthy individuals, and those with impaired movement. During complex bimanual movements, interference can occur, where one hand influences the action of the contralateral hand. Interference likely results from conflicting sensorimotor information shared between brain regions controlling hand movements via neural crosstalk. However, how visual and dynamic feedback processes interact with each other...
Show moreThe purpose of this dissertation was to investigate interference during bimanual movements in healthy individuals, and those with impaired movement. During complex bimanual movements, interference can occur, where one hand influences the action of the contralateral hand. Interference likely results from conflicting sensorimotor information shared between brain regions controlling hand movements via neural crosstalk. However, how visual and dynamic feedback processes interact with each other during bimanual reaching movements is not well understood. This dissertation reports two studies that address mechanisms underlying interference in healthy individuals, and one in individuals with dystonia. In the first study, groups experienced either a visuomotor perturbation, dynamic perturbation, combined visuomotor and dynamic perturbation, or no perturbation in their right hand during bimanual reaches. The left hand was examined for interference. The results indicated that the visuomotor and combined perturbations showed greater interference than the dynamic perturbation, but that the combined and visuomotor perturbations were equivalent with one another. This suggests that dynamic and visuomotor sensorimotor processes do not interact between hemisphere-hand systems, and that primarily visuomotor processes result in interference between the hands.The results of Experiment 1 could be explained by visuomotor and dynamic perturbations being coordinated in reference frames that were differentially shared between hemisphere-hand systems. Reference frames are a theoretical construct which explain how the motor system coordinates movements relative to the environment and/or itself. Research suggests that unimanual responses to dynamic perturbations are coordinated in unilateral intrinsic joint-centered reference frames, while visuomotor perturbations are coordinated in bilateral extrinsic reference frames. Little is known about the role of reference frames in interference during bimanual movements. As such, interference may only occur when movements of each hand share a reference frame. In Experiment 2, two groups made bimanual reaching movements while their right hand experienced a dynamic perturbation. In one group, separate cursors represented each hand. In the other group, both hands shared control of a single cursor. Shared control was hypothesized to compel the system to coordinate both hands with a shared representation. The results indicated that the shared-cursor group demonstrated more interference than the dual-cursors group, suggesting that a shared reference frame may induce greater interference.Finally, motor coordination is often disrupted in individuals with movement disorders, such as cervical dystonia (CD). Additionally, patients with CD can show "mirror movements", in which voluntary actions of one effector cause involuntary actions in another effector, suggesting the presence of abnormal sensorimotor integration and neural inhibition. However, how the coordination of bimanual actions and interference are different in cervical dystonia has been unexplored. In Experiment 3, patients with CD and healthy controls performed a bimanual interference task before and after treatment with botulinum toxin. Brain activity was simultaneously recorded with EEG. Results indicated that overall, movements were coordinated similarly between patients and controls. However, greater event-related desynchronization was found in patients, particularly in the post-treatment session. This suggests that bimanual coordination necessitates greater neural resources for successful coordination in CD patients. Together, these studies advance the understanding of how bimanual coordination and interference occurs in healthy individuals, and those with cervical dystonia.
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Title: Gameplay livestreaming : human agents of gamespace and their parasocial relationships
Creator: Leith, Alex P.
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "Gameplay livestreaming is an increasingly popular form of media with tens of thousands of people choosing to do it as either a hobby or career. Once each of these individuals creates a Twitch account and starts broadcasting themselves, they become a media figure. This dissertation examined the chats from thousands of partnered Twitch channels. The two key areas of examination are parasocial relationships and gameplay engagement. Parasocial relationshxips state that media users can begin to...
Show more"Gameplay livestreaming is an increasingly popular form of media with tens of thousands of people choosing to do it as either a hobby or career. Once each of these individuals creates a Twitch account and starts broadcasting themselves, they become a media figure. This dissertation examined the chats from thousands of partnered Twitch channels. The two key areas of examination are parasocial relationships and gameplay engagement. Parasocial relationshxips state that media users can begin to develop perceived relationships with media figures as they consume content containing that figure. A series of Python bots gathered chat and stream data over a month from 30 Twitch categories (e.g., Hearthstone, League of Legends, Art, and Just Chatting). The bots logged a total of 321,189,309 messages from 6,564,307 senders and 117,943 channels. After cleaning the data for partnership status, stream language, and message count, coding divided the remaining 3,224,942 messages from 1,298,148 senders and 3,127 channels into their appropriate groups (i.e., messages target and stream content). The research hypotheses subdivided the dataset several times. All hypotheses had the messages separated between streamer-specific messages and other-specific messages. Streamer-specific messages are messages which include the at symbol ( ) and the channel name, thus signaling message intentionality to the streamer. Hypotheses two further divided the messages between gameplay and non-gameplay streams, and hypothesis three divided the messages from gameplay streams into entertainment and expertise streams. The hypotheses persistently found that the message target was a reliable predictor of verbal immediacy, the metric used to identify parasocial relationships. Stream content either proved to be a counter-intuitive predictor or no predictor of verbal immediacy. Grounded theory methods addressed the research questions and produced two common distinctions for gameplay involvement. Viewers can engage with gameplay by asking questions but can also elevate themselves to human agents of gamespace through providing information or suggestions."--Pages ii-iii.
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Title: Signal processing and machine learning approaches to enabling advanced sensing and networking capabilities in everyday infrastructure and electronics
Creator: Ali, Kamran (Scientist)
Date: 2020
Collection: Electronic Theses & Dissertations
Description: Mainstream commercial off-the-shelf (COTS) electronic devices of daily use are usually designed and manufactured to serve a very specific purpose. For example, the WiFi routers and network interface cards (NICs) are designed for high speed wireless communication, RFID readers and tags are designed to identify and track items in supply chain, and smartphone vibrator motors are designed to provide haptic feedback (e.g. notifications in silent mode) to the users. This dissertation focuses on...
Show moreMainstream commercial off-the-shelf (COTS) electronic devices of daily use are usually designed and manufactured to serve a very specific purpose. For example, the WiFi routers and network interface cards (NICs) are designed for high speed wireless communication, RFID readers and tags are designed to identify and track items in supply chain, and smartphone vibrator motors are designed to provide haptic feedback (e.g. notifications in silent mode) to the users. This dissertation focuses on revisiting the physical-layer of various such everyday COTS electronic devices, either to leverage the signals obtained from their physical layers to develop novel sensing applications, or to modify/improve their PHY/MAC layer protocols to enable even more useful deployment scenarios and networking applications - while keeping their original purpose intact - by introducing mere software/firmware level changes and completely avoiding any hardware level changes. Adding such new usefulness and functionalities to existing everyday infrastructure and electronics has advantages both in terms of cost and convenience of use/deployment, as those devices (and their protocols) are already mainstream, easily available, and often already purchased and in use/deployed to serve their mainstream purpose of use.In our works on WiFi signals based sensing, we propose signal processing and machine learning approaches to enable fine-grained gesture recognition and sleep monitoring using COTS WiFi devices. In our work on gesture recognition, we show for the first time thatWiFi signals can be used to recognize small gestures with high accuracy. In our work on sleep monitoring, we propose for the first time aWiFi CSI based sleep quality monitoring scheme which can robustly track breathing and body/limb activity related vital signs during sleep throughout a night in an individual and environment independent manner.In our work on RFID signals based sensing, we propose signal processing and machine learning approaches to effectively image customer activity in front of display items in places such as retail stores using commercial off-the-shelf (COTS) monostatic RFID devices (i.e. which use a single antenna at a time for both transmitting and receiving RFID signals to and from the tags). The key novelty of this work is on achieving multi-person activity tracking in front of display items by constructing coarse grained images via robust, analytical model-driven deep learning based, RFID imaging. We implemented our scheme using a COTS RFID reader and tags.In our work on smartphone's vibration based sensing, we propose a robust and practical vibration based sensing scheme that works with smartphones with different hardware, can extract fine-grained vibration signatures of different surfaces, and is robust to environmental noise and hardware based irregularities. A useful application of this sensing is symbolic localization/tagging, e.g. figuring out whether a user's device is in their hand, pocket, or at their bedroom table, etc. Such symbolic tagging of locations can provide us with indirect information about user activities and intentions without any dedicated infrastructure, based on which we can enable useful services such as context aware notifications/alarms. To make our scheme easily scalable and compatible with COTS smartphones, we design our signal processing and machine learning pipeline such that it relies only on builtin vibration motors and microphone for sensing, and it is robust to hardware irregularities and background environmental noises. We tested our scheme on two different Android smartphones.In our work on powerline communications (PLCs), we propose a distributed spectrum sharing scheme for enterprise level PLC mesh networks. This work is a major step towards using existing COTS PLC devices to connect different types of Internet of Things (IoT) devices for sensing and control related applications in large campuses such as enterprises. Our work is based on identification of a key weakness of the existing HomePlug AV (HPAV) PLC protocol that it does not support spectrum sharing, i.e., currently each link operates over the whole available spectrum, and therefore, only one link can operate at a time. Our proposed spectrum sharing scheme significantly boosts both aggregated and per-link throughputs, by allowing multiple links to communicate concurrently, while requiring a few modifications to the existing HPAV protocol.
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Title: The owner's role in contractor safety management : a pattern language
Creator: Hansmann, Zachary David
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "Construction is a dangerous industry that historically accounts for a disproportionate number of injuries and illnesses. Despite improvements in the last few decades, this trend of injuries compared to other industries persists year over year. The owner has been shown to be a pivotal member of construction projects with the ability to improve contractor safety performance. It has also been shown that owners ultimately reap the benefits of these improvements in safety performance, yet buyers...
Show more"Construction is a dangerous industry that historically accounts for a disproportionate number of injuries and illnesses. Despite improvements in the last few decades, this trend of injuries compared to other industries persists year over year. The owner has been shown to be a pivotal member of construction projects with the ability to improve contractor safety performance. It has also been shown that owners ultimately reap the benefits of these improvements in safety performance, yet buyers of construction are still inconsistent in their focus on the importance of construction safety.Previous research studied owners whose contractors exhibited exemplary contractor safety performance to establish recommended practices. These studies have not considered the reality owners must operate in, including what bad practices owners may unintentionally participate in that lead to an increase in problems and ultimately liability for the owner.This research investigated how an owner should interact with independent contractors when it comes to safety management. To do this, pattern language and grounded theory methods were combined to examine the practices of owners, the preferences of safety professionals, and the existing academic recommendations to both determine the state of the industry and to identify the aspirational practices owners may seek to employ.This study found that owner practices do not align with the practices identified in the literature, and that both owners and academics need to expand their perspective to maximize any potential improvement. Thirty-six positive practices were identified across four major categories, including communication, site safety planning, contractual control, and owner involvement. Further, eleven potentially negative practices were also identified that often led to owners unknowingly and needlessly taking responsibility and, by extension, shouldering liability for their contractors. Finally, the forces that an owner must consider when balancing competing priorities were identified to help understand the often conflicting priorities that shape owner behavior.Ultimately, the owner's role in construction safety is driven by their project risk, risk tolerance, capability, resources, and other characteristics specific to that owner, at that time, and in that space. Each situation remains a fact-intensive occurrence that deserves careful consideration and action. The work practices, identified in this research as patterns, allow owners to understand the recommended practices of the industry and allow each to make a careful assessment of their best course of action. Owners who understand the implication of their actions, as well as the impact of each related practice, will make decisions that more appropriately fit their needs.Future work on this topic should take the practices laid out in this research and begin to assess the impact of each practice on the balance of the remaining practices of the pattern language. With this information, owners could identify their best course of action in a quantitative way. Likewise, research in this area must reevaluate prior findings in the light of the current environment in which these owners work. Some practices and solutions suggested in existing work are untenable in many owner situations. This is evident from the significant difference in the practices recommended by academia and the current practices of owners."--Pages ii-iii.
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Title: Exploring the molecular evolution of proteins with deep mutational scanning
Creator: Faber, Matthew Steven
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "In this thesis, deep mutational scanning is expanded and applied to better understand the molecular evolution of proteins. Protein evolution is a complex process where subtle changes in molecular architecture can have massive impacts on biophysical properties, altering how well-adapted a protein is to a specific task or environment. Deep mutational scanning provides a finer level of understanding of molecular evolution by assessing the effect of every possible single-mutation on a protein's...
Show more"In this thesis, deep mutational scanning is expanded and applied to better understand the molecular evolution of proteins. Protein evolution is a complex process where subtle changes in molecular architecture can have massive impacts on biophysical properties, altering how well-adapted a protein is to a specific task or environment. Deep mutational scanning provides a finer level of understanding of molecular evolution by assessing the effect of every possible single-mutation on a protein's function. The technique combines site saturation mutant libraries, high throughput selections, and deep sequencing to tabulate the changes in mutant frequencies. From these changes the impacts of the mutations on protein function are characterized. This technology allows for efficient exploration of the local evolutionary landscape of a protein, making it a powerful tool for understanding evolution. Here, I use deep mutational scanning to study how the initial likelihood of obtaining the native folded state of an enzyme in vivo constrains its evolution. We designed two unique single-point mutants of AmiE, an aliphatic amidase from Pseudomonas aeruginosa. These mutant enzymes are significantly less likely to reach the native folded state in vivo than the unmutated precursor and have catalytic efficiencies that are statistically indistinguishable from the initial unmutated enzyme. I tested the impacts of nearly all single-point mutations for the two impaired enzymes using high-throughput growth selections and compared them to the precursor enzyme. These comparisons provided insights into how evolutionary outcomes are changed following decreases in the likelihood of native folding, and on how the impacts of single mutations combine to influence function. The other primary goal of this thesis is the development of a new method that expands the utility of deep mutational scanning studies. This method assembles comprehensive single-site saturation, and large multi-point, mutant genome libraries of the bacteriophage phi-X174. To assemble the mutant genome libraries we combine nicking scanning mutagenesis and Golden Gate cloning. With these viral genome libraries, deep mutational scanning experiments can be performed in situ. These libraries are a valuable tool for studying the molecular determinants of viral host switching, the combination of inter- and intra-subunit mutations, and other aspects of the molecular evolution of viruses."--Pages ii-iii.
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Title: Characterization of resistance gene diversity and structural variation in Beta vulgaris
Creator: Funk, Andrew Joseph
Date: 2020
Collection: Electronic Theses & Dissertations
Description: Plants are under threat from bacteria, viruses, fungi, and nematodes in their environment. Plants deploy a sophisticated network of defense responses to avoid and defeat these pathogens, and in response pathogens counteract plant defenses through their own suite of biochemical weapons and signaling molecules. These battles are pervasive in both natural settings and agriculture. The goal of this dissertation research is to provide insight into genetic variation present in diverse populations...
Show morePlants are under threat from bacteria, viruses, fungi, and nematodes in their environment. Plants deploy a sophisticated network of defense responses to avoid and defeat these pathogens, and in response pathogens counteract plant defenses through their own suite of biochemical weapons and signaling molecules. These battles are pervasive in both natural settings and agriculture. The goal of this dissertation research is to provide insight into genetic variation present in diverse populations of Beta vulgaris and identify patterns of disease resistance (R) gene variation.Nucleotide-binding (NB-ARC), leucine-rich-repeat genes (NLRs) account for 60.8% of R genes molecularly characterized from plants. NLRs exist as large gene families prone to tandem duplication and transposition, with high sequence diversity among crops and their wild relatives. I used the conserved NB-ARC domain to build a B.vulgaris-specific hidden Markov model (HMM). The HMM identified 231 tentative NB-ARC loci in a highly contiguous genome assembly of sugar beet, revealing diverged and truncated NB-ARC signatures as well as full-length sequences. The putative NB-ARC-associated proteins contained NLR resistance gene domains, including Toll/interleukin-1 receptor (TIR), coiled-coil (CC), and leucine-rich repeat (LRR), as well as other integrated domains. HMM-based domain detection was extended to 23 populations encompassing four crop types of B. vulgaris. Whole-genome sequences were generated by pooling 25 individuals per population, then sequencing each population in a single bulk reaction using 2x150 bp chemistry. These reads were assembled de novo to efficiently capture population-wide genetic variation. The nucleic-acid-based NB-ARC HMM was used to scan de novo contigs and infer genetic variation within and between populations, which identified an average of 139.5 NB-ARC domains per population. The pooled population sequencing strategy was expanded to 71 populations total. Short reads were used in a targeted reassembly pipeline to detect structural variation in each of the 71 populations. This method identified 4,995,443 indels with lengths under 1 kb. These indels were analyzed for chromosome position, length in bp, and frequency across populations, and revealed non-random patterns of indel variation. Half of the indels were detected in five or more populations, suggesting that indel assembly from pooled population sequences is reproducible. Furthermore, indels were sufficient to differentiate populations by crop type, supporting the conclusion that the data modeled genetic differences originating in historical crop development. Divergence in the population-wide distribution of seven- and eight-bp indels led to identification of an enriched sequence motif, suggesting possible biological function of the sequence such as a TE target site duplication or transcription factor binding site.This work presents the first detailed view of NLR family composition in a member of the Caryophyllales and demonstrates an additional nucleic-acid-based method for resistance gene prediction in non-model plant species. Pooled population sequencing was used to access novel variation in breeding populations of B. vulgaris and identify structural variants that reflected underlying genotypic relationships. Future work will build on resistance gene modeling, pooled population sequencing, and detection of genetic variation to aid breeding for disease resistance.
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Title: Searching for kinetic control of excited-state evolution in Fe(II) polypyridyl chromophores
Creator: Adelman, Sara Linnae
Date: 2020
Collection: Electronic Theses & Dissertations
Description: Iron(II) polypyridyl chromophores represent an earth-abundant alternative to ruthenium-based complexes in photo-induced electron transfer applications, yet the sub-150 fs metal-to-ligand charge transfer (MLCT) excited-state lifetime endemic to low-spin Fe(II) polypyridyls has hampered their widespread use. One promising avenue towards achieving a longer-lived MLCT excited-state lifetime is through the exertion of kinetic control, made possible through the identification and subsequent...
Show moreIron(II) polypyridyl chromophores represent an earth-abundant alternative to ruthenium-based complexes in photo-induced electron transfer applications, yet the sub-150 fs metal-to-ligand charge transfer (MLCT) excited-state lifetime endemic to low-spin Fe(II) polypyridyls has hampered their widespread use. One promising avenue towards achieving a longer-lived MLCT excited-state lifetime is through the exertion of kinetic control, made possible through the identification and subsequent disruption of the nuclear coordinate of excited-state deactivation. With this aim, a series of structurally similar iron(II) polypyridyl complexes spanning from low-spin to high-spin, including a spin crossover complex, were synthesized, which allowed for the determination of reorganization energy from the lowest-energy excited state (5T2) to the ground state (1A1) through a combination of variable temperature transient absorption and magnetic susceptibility measurements. In addition to experimentally determining the reorganization energy and electronic coupling constant associated with this conversion, we will deduce the kinetically competent degree of freedom associated with this transition through a convergence of analyses from semi-classical to fully quantum mechanical non-radiative decay theories. A ruthenium(II)-based analog of the spin crossover complex provided insight into the geometric distortions coupled to the deactivation of the MLCT excited states. Coupled together, these results offered new guidelines for ligand design, inspiring the synthesis of new iron(II) complexes with unique photophysical dynamics and establishing new roadmaps towards controlling excited-state dynamics in this class of compounds.
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Title: Measurement of the charged current muon neutrino differential cross section on scintillator with zero pions in the final state with the T2K on/off-axis near detectors
Creator: Cudd, Andrew Bruce
Date: 2020
Collection: Electronic Theses & Dissertations
Description: The Tokai to Kamioka (T2K) is a long-baseline neutrino oscillation experiment in Japan producing precise measurements of neutrino oscillations and neutrino interactions with nuclear targets. T2K utilizes a muon (anti-)neutrino beam produced at the J-PARC proton accelerator facility which is measured at a suite of near detectors, ND280 and INGRID, and the far detector, Super-Kamiokande. One of the dominant systematic uncertainties for the oscillation analysis is from the uncertainty in...
Show moreThe Tokai to Kamioka (T2K) is a long-baseline neutrino oscillation experiment in Japan producing precise measurements of neutrino oscillations and neutrino interactions with nuclear targets. T2K utilizes a muon (anti-)neutrino beam produced at the J-PARC proton accelerator facility which is measured at a suite of near detectors, ND280 and INGRID, and the far detector, Super-Kamiokande. One of the dominant systematic uncertainties for the oscillation analysis is from the uncertainty in neutrino interaction modeling with complex nuclei, which will eventually become the limiting uncertainty for the next generation of neutrino oscillation experiments. Therefore measurements of neutrino cross sections on nuclear targets is essential for understanding how to model these complicated nuclear interactions. This thesis presents a novel neutrino cross section measurement utilizing both of the T2K near detectors, ND280 and INGRID, in a joint statistical fit. Because the T2K near detectors are exposed to neutrinos from the same beamline, the uncertainties in the neutrino flux prediction will be correlated. This fact combined with the different neutrino energy spectra seen at each detector will allow for some separation of flux and cross section effects, and presents an opportunity to study the neutrino cross section as a function of energy using the same neutrino beam. This analysis is the first cross section measurement on T2K to use samples from multiple detectors in the same beamline. This thesis presents a description of the statistical analysis framework, the event selection, the treatment of systematic uncertainties, and the extracted muon neutrino CC0pi double differential cross section in bins of muon kinematics for ND280 and INGRID, including the correlations between the detectors.
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Title: Effect of shear layer unsteadiness on the aerodynamics of a pitching airfoil
Creator: Safaripour-Tabalvandani, Alireza
Date: 2020
Collection: Electronic Theses & Dissertations
Description: It is common practice to utilize a uniform approach flow in most of the problems in aerodynamics. However, in numerous circumstances the complex approach flows found in nature can be significantly non-uniform and even include spatially non-uniform temporal fluctuations. Motivated by these non-uniform unsteady flows, this experimental study investigates the effects of non-uniform approach flow unsteadiness on the aerodynamic performance of an airfoil.To isolate the effects of unsteadiness from...
Show moreIt is common practice to utilize a uniform approach flow in most of the problems in aerodynamics. However, in numerous circumstances the complex approach flows found in nature can be significantly non-uniform and even include spatially non-uniform temporal fluctuations. Motivated by these non-uniform unsteady flows, this experimental study investigates the effects of non-uniform approach flow unsteadiness on the aerodynamic performance of an airfoil.To isolate the effects of unsteadiness from those of the mean non-uniform approach flow, two non-uniform (shear) flows with a matching mean velocity profile are generated in a water tunnel facility. One of these profiles is made through a canonical two-stream shear layer, which is known to contain vortical structures and exhibit non-uniform velocity fluctuations. A matching shear velocity profile with uniform low level fluctuations is generated utilizing a modified shaped honeycomb shear generation method based on the original model proposed by Kotansky (1966). These shear flows demonstrate the same mean behavior and only differ in their fluctuation profiles.Behavior and development of both shear flows are examined through measurements of their streamwise velocity profile at multiple downstream locations utilizing single component molecular tagging velocimetry. The steady and unsteady shear flows are found to produce the same mean velocity profile with different classes of velocity fluctuations. The steady shear flow demonstrates a uniform low level of fluctuating velocity profile while the unsteady shear layer velocity fluctuations mimic the signature fluctuating velocity profile of plane mixing layers, with a high level of fluctuations in the center and a gradual decrease in fluctuations moving away from the shear layer center line.A NACA0012 airfoil is positioned at the center of each shear flow and the average aerodynamic forces on the stationary airfoil are directly measured across a wide range of angles of attack. The resulting lift and drag coefficient curves are compared for each of these shear flows as well as the reference uniform flow. The unsteady shear layer is found to generate a positive lift at zero angle of attack, in contrast to the negative lift observed under the same condition in the steady shear flow. Furthermore, in the presence of the unsteady shear flow, the linear region of the lift curve around zero angle of attack shows a larger slope and extends over a wider range of angles of attack compared to those of the steady shear and uniform flow lift curves. The unsteady shear flow results in a smaller magnitude of drag at small angles of attack compared to the other two flow conditions.Force measurements are also performed with the airfoil set to sinusoidally pitch around its quarter chord over a range of oscillation frequencies at the center of both shear flows and the reference uniform flow. The mean lift results show that at small oscillation frequencies the steady and unsteady shear flows produce opposite sign lift forces (negative lift in steady shear flow), but both result in positive lift coefficients of similar magnitudes at higher frequencies. The presence of shear and its unsteadiness seems to only weakly affect the mean and fluctuations of the streamwise force, with almost no effect observed on lift fluctuations.A closer look at the flow around the surface of the stationary airfoil reveals interesting differences between the behavior of the airfoil boundary layer in the presence of steady versus unsteady shear flow. Single component molecular tagging velocimetry is used to measure the streamwise velocity of the flow near the surface of the airfoil at multiple angles of attack in each shear flow. While the steady shear layer results confirm the presence of laminar separation on the suction side of the airfoil at the angles of attack investigated here, no sign of laminar separation or a reverse flow region is found when the airfoil is placed in the unsteady shear layer.The wake flow behind the pitching airfoil is also visualized through molecular tagging flow visualization to qualitatively examine how these shear flows affect the wake flow behavior. It is observed that both steady and unsteady shear flows result in the wake flow deflecting towards the high speed side of the flow at high oscillation frequencies, with more cycle-to-cycle variation and perturbations observed in the presence of unsteady shear flow.
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Title: Development and validation of risk stratification models in a cohort of community-living homebound older adults, comparison of three methods : logistic regression, random forest, and Cox proportional hazard regression
Creator: Nasiriahmadabadi, Mojdeh
Date: 2019
Collection: Electronic Theses & Dissertations
Description: Risk stratification (RS) models make predictions of an outcome based on the observed information from predictor variables. Classification of a population into different groups based on their risk of an outcome provides the opportunity for delivering targeted services to each group based on their needs and priorities. Different RS tools have been developed for older adults, but there is a limited number of RS studies developed for use in community-living older adults. This dissertation aims to...
Show moreRisk stratification (RS) models make predictions of an outcome based on the observed information from predictor variables. Classification of a population into different groups based on their risk of an outcome provides the opportunity for delivering targeted services to each group based on their needs and priorities. Different RS tools have been developed for older adults, but there is a limited number of RS studies developed for use in community-living older adults. This dissertation aims to develop and validate risk stratification models in a cohort of community-living homebound older adults. The study population consisted of older homebound adults who received home-based medical services from the Visiting Physician Association (VPA), which is a part of the United States Medical Management (USMM) Corporation. USMM provides a range of services, including home-based primary care and medical visits, senior home care, palliative care, and hospice services. The cohort had several features indicative of high risk: the average age was 82 years, 50% had 2265 5 comorbidities, and 45% had a severe disability (defined by a Karnofsky Performance Score KPS 226440). The population had very high rates of mortality and hospice admission (1-year rates were 32% and 10%, respectively). Given the unique and high-risk nature of this population, a RS approach was developed to help to provide USMM patients with appropriate services aligned with their priorities, as guided by a recent conceptual framework for the care of older adults with multiple comorbidities (Table 1.2). We developed and validated prediction models for two outcomes (death and hospice admission) by using three alternate statistical approaches: logistic regression (LR), random forest (RF), and Cox regression. The performance of these models was compared using the discrimination ability measured by area under the receiver operating curve (AUC). When developing the LR model we applied different variable selection methods (stepwise, backward, forward, adaptive lasso, elastic net, and manual). We developed a prediction model using a RF algorithm and used Cox regression to model time-to-event for each outcome separately (using the same variable selection methods as used in Logistic regression). All three models were developed in a derivation dataset (consisting of a random 50% of the cohort) and validated by applying to the validation dataset. Because of the large amount of missing data among predictor variables we applied multiple imputation (MI) procedures and compared the performance of LR and RF models in the original data and imputed data. For the prediction of mortality, all of the variable selection methods used in the LR model showed similar predictive performance (AUC 0.762- 0.769). Random forest had the best discrimination ability (AUC=0.83), whereas the LR and Cox models had comparable AUCs (0.76 and 0.74 respectively). We determined that the higher AUC of the RF model was mainly due to its ability to include subjects with missing data because when the subjects with missing data were excluded from the RF cohort, the UAC of the model was similar to the LR model. Also when the RF model was applied to imputed data it has similar predictive performance as the LR model which indicated the basic assumption of multiple imputation (i.e., missing at random) was not met in this data. For hospice admission, all three models had a similar discriminative ability (AUC for RF, LR, and Cox, were 0.70, 0.73, and 0.72, respectively). The variables age, race, KPS, serum albumin, surprise question (SQ), and hyperlipidemia were consistently selected as the important predictors of both outcomes in all three approaches. WE concluded that the RF approach can significantly improve the predictive performance of the RS model but this advantage comes from its ability for the inclusion of observation with missing data. When data are missing not at random use of MI had a limited effect on improving the prediction of models because the basic assumption in MI procedure is missing at random. The quality of data from large electronic health record datasets remains a limitation of developing RS models.
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Title: Assessing species distributions and the effects of habitat fragmentation : the case of the giant panda
Creator: Connor, Thomas
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "Environmental degradation has become a ubiquitous feature in the modern world. This degradation is resulting in widespread loss and fragmentation of wildlife habitat, leading to increased extinction risks and population declines. In order to stem these threats, it is imperative to accurately predict species' habitats, how to optimize the restoration and protection of these habitats, and better understand how their ecology interacts with habitat requirements. I used both simulated and...
Show more"Environmental degradation has become a ubiquitous feature in the modern world. This degradation is resulting in widespread loss and fragmentation of wildlife habitat, leading to increased extinction risks and population declines. In order to stem these threats, it is imperative to accurately predict species' habitats, how to optimize the restoration and protection of these habitats, and better understand how their ecology interacts with habitat requirements. I used both simulated and empirical study systems to investigate these topics and focused heavily on giant panda (Ailuropoda melanoleuca) populations across Wolong Nature Reserve and Southwest China.Given the uncertainty and debate surrounding the relative effects of habitat amount and habitat fragmentation on ecological responses (Chapter 1), I set out to accurately define habitat before further investigating these effects. I found that the grain size of environmental predictor variables had important effects on modeling the distributions of virtual species simulated on real landscapes, and that modeling with grain sizes farther away from the "true" grain size used to simulate the species resulted in lower predictive accuracy and incorrect ecological inferences about the importance of environmental variables to habitat (Chapter 2). I then went a step further and investigated interactive spatial scale effects on species distribution modeling by varying the total extent of the study areas and grain size of the environmental variables used to predict panda habitat and distributions across Southwest China (Chapter 3). I found that increasing total extent offset the negative effects of increasing grain size on model accuracy and that total extent can be optimized as both larger (at smaller spatial scales) and smaller (at the geographic range scale) than the study area of interest. I then further improved the accuracy of our species habitat and distribution modeling by leveraging empirical movement distributions derived from GPS-collar data to transform the environmental predictor variables, and used the resulting habitat map to investigate the effects of habitat amount and fragmentation on functional connectivity in the panda population in Wolong (Chapter 4). I found that the standard deviation of the core area index, a measure of habitat configuration, was the best predictor of functional connectivity. Habitat amount was the second-best predictor and we found that in our study system it could optimized to cover about 80% of a local landscape to maximize functional connectivity. Habitat fragmentation also showed a nonlinear and threshold-dependent relationship with functional connectivity-important findings to consider in the spatial planning of protected areas. Finally, I used the noninvasive genetics data to "capture" and "recapture" unique individuals across a core habitat area in Wolong and conduct the first social network analysis of pandas (Chapter 5). I found strong evidence of two to three social clusters in the population, defined as groups of pandas that associated with each other at a significantly higher rate than individuals outside the cluster. These clusters may represent cryptic family structuring, as genetic relatedness was a significant positive predictor of associations between individuals. My detailed approaches to investigating the habitat and ecology of giant pandas used throughout this manuscript resulted in unique insights into this threatened habitat specialist species, and we recommend they be applied widely to other species. Optimizing the way in which we predict and conserve habitat in each landscape and system, as opposed to relying on expert opinion or competing theories, will be increasingly important as environmental degradation continues in the Anthropocene."--Pages ii-iii.
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Title: Transmission timing modulation for information coding in energy-constrained wireless networks
Creator: Feng, Dezhi
Date: 2020
Collection: Electronic Theses & Dissertations
Description: The objective of this thesis is to develop a framework of transmission timing-based modulation framework for improving energy efficiency, security, and information transfer capacity in embedded wireless networks with very thin energy budgets. The key idea is to modulate both intra-PDU (Protocol Data Unit) and inter-PDU timing for addressing energy, security, and information transfer capacity in wireless embedded networks. As for energy efficiency, we developed a novel pulse position-coded PDU...
Show moreThe objective of this thesis is to develop a framework of transmission timing-based modulation framework for improving energy efficiency, security, and information transfer capacity in embedded wireless networks with very thin energy budgets. The key idea is to modulate both intra-PDU (Protocol Data Unit) and inter-PDU timing for addressing energy, security, and information transfer capacity in wireless embedded networks. As for energy efficiency, we developed a novel pulse position-coded PDU (PPCP) paradigm. The core idea is to encode a protocol data unit (PDU) in terms of the silence duration between two sets of delimiter pulses, whose positions are modulated based on the value of the PDU. This PPCP architecture achieves significant energy savings by using a lesser amount of bit/pulse transmissions, and by eliminating long multi-bit preambles and headers, which are normally used in traditional packets. The proposed multi-access pulse-based PDU scheme enables medium sharing among many sensor nodes without requiring per-PDU frame synchronization. As for security, we developed the concept of a novel chaotic pulse position coded protocol data unit (CPPCP) for secure embedded networking. The core idea of CPPCP is to encode a protocol data unit (PDU) with a wideband pulse train with chaotically-varied inter-pulse intervals. The architecture ensures communication security by introducing randomness between data symbols, noise-like frequency spectrum, and significant energy savings by using a smaller number of pulse transmissions compared to existing secure coding schemes such as Bluetooth Low Energy (BLE). Compared with the traditional key-based cryptographic techniques, CPPCP suppresses decipherable information by eliminating symbol periodicity. The mechanism can also be piggy-backed on traditional cryptography solutions to achieve higher levels of security. Finally, for enhancing the information transfer capacity, we developed a data packet position modulation (DPPM) paradigm. Packet transmissions in low duty cycle networks are often scheduled as TDMA slots, whose periodicity is determined based on application sampling requirements and the energy in-flow, often in the form of energy harvesting. The key idea of DPPM is to modulate the inter-packet spacing for coding additional information without incurring additional transmission energy expenditures. We first developed a have a DPPM based networking solution for single-hop transmit-only networks in which a number of low-energy nodes transmit data to an aggregator. The architecture is developed for a two-node point-to-point link, followed by a multipoint-to-point multi-access network. Detailed analytical and simulation models are developed to demonstrate the performance of a symmetric and an asymmetric version of DPPM.
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