Dynamics of the Disk-Pendulum Coupled System With Vertical Excitation

This paper investigates the static and dynamic characteristics of the semi-elliptical rocking disk on which a pendulum pinned. This coupled system’s response is also analyzed analytically and numerically when a vertical harmonic excitation is applied to the bottom of the rocking disk. Lagrange’s Equation is used to derive the motion equations of the disk-pendulum coupled system. The second derivative test for the system’s potential energy shows how the location of the pendulum’s pivotal point affects the number and stability of equilibria, and the change of location presents different bifurcation diagrams for different geometries of the rocking disk. For both vertically excited and unforced cases, the coupled system shows chaos easily, but the proper chosen parameters can still help the system reach and keep the steady state. For the steady state of the vertically excited rocking disk without a pendulum, the variation of the excitation’s amplitude and frequency result in the hysteresis for the amplitude of the response. When a pendulum is pinned on the rocking disk, three major categories of steady states are presently in the numerical way.

Theory and Practice in Sustainability Science: Influence of Urban Form on the Urban Heat Island and Implications for Urban Systems

As the world population continues to grow past seven billion people and global challenges continue to persist including resource availability, biodiversity loss, climate change and human well-being, a new science is required that can address the integrated nature of these challenges and the multiple scales on which they are manifest. Sustainability science has emerged to fill this role. In the fifteen years since it was first called for in the pages of Science, it has rapidly matured, however its place in the history of science and the way it is practiced today must be continually evaluated. In Part I, two chapters address this theoretical and practical grounding. Part II transitions to the applied practice of sustainability science in addressing the urban heat island (UHI) challenge wherein the climate of urban areas are warmer than their surrounding rural environs. The UHI has become increasingly important within the study of earth sciences given the increased focus on climate change and as the balance of humans now live in urban areas.

In Chapter 2 a novel contribution to the historical context of sustainability is argued. Sustainability as a concept characterizing the relationship between humans and nature emerged in the mid to late 20th century as a response to findings used to also characterize the Anthropocene. Emerging from the human-nature relationships that came before it, evidence is provided that suggests Sustainability was enabled by technology and a reorientation of world-view and is unique in its global boundary, systematic approach and ambition for both well being and the continued availability of resources and Earth system function. Sustainability is further an ambition that has wide appeal, making it one of the first normative concepts of the Anthropocene.

Despite its widespread emergence and adoption, sustainability science continues to suffer from definitional ambiguity within the academe. In Chapter 3, a review of efforts to provide direction and structure to the science reveals a continuum of approaches anchored at either end by differing visions of how the science interfaces with practice (solutions). At one end, basic science of societally defined problems informs decisions about possible solutions and their application. At the other end, applied research directly affects the options available to decision makers. While clear from the literature, survey data further suggests that the dichotomy does not appear to be as apparent in the minds of practitioners.

In Chapter 4, the UHI is first addressed at the synoptic, mesoscale. Urban climate is the most immediate manifestation of the warming global climate for the majority of people on earth. Nearly half of those people live in small to medium sized cities, an understudied scale in urban climate research. Widespread characterization would be useful to decision makers in planning and design. Using a multi-method approach, the mesoscale UHI in the study region is characterized and the secular trend over the last sixty years evaluated. Under isolated ideal conditions the findings indicate a UHI of 5.3 ± 0.97 °C to be present in the study area, the magnitude of which is growing over time.

Although urban heat islands (UHI) are well studied, there remain no panaceas for local scale mitigation and adaptation methods, therefore continued attention to characterization of the phenomenon in urban centers of different scales around the globe is required. In Chapter 5, a local scale analysis of the canopy layer and surface UHI in a medium sized city in North Carolina, USA is conducted using multiple methods including stationary urban sensors, mobile transects and remote sensing. Focusing on the ideal conditions for UHI development during an anticyclonic summer heat event, the study observes a range of UHI intensity depending on the method of observation: 8.7 °C from the stationary urban sensors; 6.9 °C from mobile transects; and, 2.2 °C from remote sensing. Additional attention is paid to the diurnal dynamics of the UHI and its correlation with vegetation indices, dewpoint and albedo. Evapotranspiration is shown to drive dynamics in the study region.

Finally, recognizing that a bridge must be established between the physical science community studying the Urban Heat Island (UHI) effect, and the planning community and decision makers implementing urban form and development policies, Chapter 6 evaluates multiple urban form characterization methods. Methods evaluated include local climate zones (LCZ), national land cover database (NCLD) classes and urban cluster analysis (UCA) to determine their utility in describing the distribution of the UHI based on three standard observation types 1) fixed urban temperature sensors, 2) mobile transects and, 3) remote sensing. Bivariate, regression and ANOVA tests are used to conduct the analyses. Findings indicate that the NLCD classes are best correlated to the UHI intensity and distribution in the study area. Further, while the UCA method is not useful directly, the variables included in the method are predictive based on regression analysis so the potential for better model design exists. Land cover variables including albedo, impervious surface fraction and pervious surface fraction are found to dominate the distribution of the UHI in the study area regardless of observation method.

Chapter 7 provides a summary of findings, and offers a brief analysis of their implications for both the scientific discourse generally, and the study area specifically. In general, the work undertaken does not achieve the full ambition of sustainability science, additional work is required to translate findings to practice and more fully evaluate adoption. The implications for planning and development in the local region are addressed in the context of a major light-rail infrastructure project including several systems level considerations like human health and development. Finally, several avenues for future work are outlined. Within the theoretical development of sustainability science, these pathways include more robust evaluations of the theoretical and actual practice. Within the UHI context, these include development of an integrated urban form characterization model, application of study methodology in other geographic areas and at different scales, and use of novel experimental methods including distributed sensor networks and citizen science.

Robust Uncertainty Quantification and Scalable Computation for Computer Models with Massive Output

Uncertainty quantification (UQ) is both an old and new concept. The current novelty lies in the interactions and synthesis of mathematical models, computer experiments, statistics, field/real experiments, and probability theory, with a particular emphasize on the large-scale simulations by computer models. The challenges not only come from the complication of scientific questions, but also from the size of the information. It is the focus in this thesis to provide statistical models that are scalable to massive data produced in computer experiments and real experiments, through fast and robust statistical inference.

Chapter 2 provides a practical approach for simultaneously emulating/approximating massive number of functions, with the application on hazard quantification of Soufri\`{e}re Hills volcano in Montserrate island. Chapter 3 discusses another problem with massive data, in which the number of observations of a function is large. An exact algorithm that is linear in time is developed for the problem of interpolation of Methylation levels. Chapter 4 and Chapter 5 are both about the robust inference of the models. Chapter 4 provides a new criteria robustness parameter estimation criteria and several ways of inference have been shown to satisfy such criteria. Chapter 5 develops a new prior that satisfies some more criteria and is thus proposed to use in practice.

HPA Axis Activation by Ethanol Dependence in Adult and Adolescent Rats

Alcoholism is a disorder marked by cycles of heavy drinking and chronic relapse, and adolescents are an age cohort particularly susceptible to consuming large amounts of alcohol, placing them at high risk for developing an alcohol use disorder. Adolescent humans and rats voluntarily consume more alcohol than their adult counterparts, suggesting that younger consumers of alcohol may be less sensitive to its aversive effects, which are regulated by the function of the hypothalamic-pituitary-adrenal (HPA) stress axis. While HPA axis dysfunction resulting from ethanol exposure has been extensively studied in adult animals, what happens in the adolescent brain remains largely unclear. In this study, chronic injections of ethanol was used to model alcohol dependence in adult and adolescent rats, and post-withdrawal anxiety behaviors were measured using light-dark box testing. Furthermore, corticosterone (CORT) release during treatment and after withdrawal was measured by collecting fecal and plasma samples from adults and adolescents. It was found that adults, but not adolescents, exhibit significant anxiety-like behavior following chronic ethanol withdrawal. Additionally, while the process of chronic ethanol treatment elicits an increase in day-by-day CORT release in both adults and adolescents, significantly sustained levels of CORT were not observed during withdrawal for either age group. Moreover, it was found that adults experience a longer-lasting CORT increase during chronic treatment, suggesting a larger and more robust period of dysfunction in the HPA axis for older consumers of alcohol. These results highlight CORT and glucocorticoids in general as a potential therapeutic target for treatment for alcoholism, especially that which has an onset during adolescence.

Ghrelin suppresses glucose-stimulated insulin secretion and deteriorates glucose tolerance in healthy humans.

OBJECTIVE: The orexigenic gut hormone ghrelin and its receptor are present in pancreatic islets. Although ghrelin reduces insulin secretion in rodents, its effect on insulin secretion in humans has not been established. The goal of this study was to test the hypothesis that circulating ghrelin suppresses glucose-stimulated insulin secretion in healthy subjects. RESEARCH DESIGN AND METHODS: Ghrelin (0.3, 0.9 and 1.5 nmol/kg/h) or saline was infused for more than 65 min in 12 healthy patients (8 male/4 female) on 4 separate occasions in a counterbalanced fashion. An intravenous glucose tolerance test was performed during steady state plasma ghrelin levels. The acute insulin response to intravenous glucose (AIRg) was calculated from plasma insulin concentrations between 2 and 10 min after the glucose bolus. Intravenous glucose tolerance was measured as the glucose disappearance constant (Kg) from 10 to 30 min. RESULTS: The three ghrelin infusions raised plasma total ghrelin concentrations to 4-, 15-, and 23-fold above the fasting level, respectively. Ghrelin infusion did not alter fasting plasma insulin or glucose, but compared with saline, the 0.3, 0.9, and 1.5 nmol/kg/h doses decreased AIRg (2,152 +/- 448 vs. 1,478 +/- 2,889, 1,419 +/- 275, and 1,120 +/- 174 pmol/l) and Kg (0.3 and 1.5 nmol/kg/h doses only) significantly (P < 0.05 for all). Ghrelin infusion raised plasma growth hormone and serum cortisol concentrations significantly (P < 0.001 for both), but had no effect on glucagon, epinephrine, or norepinephrine levels (P = 0.44, 0.74, and 0.48, respectively). CONCLUSIONS: This is a robust proof-of-concept study showing that exogenous ghrelin reduces glucose-stimulated insulin secretion and glucose disappearance in healthy humans. Our findings raise the possibility that endogenous ghrelin has a role in physiologic insulin secretion, and that ghrelin antagonists could improve beta-cell function.

Sensor Planning for Bayesian Nonparametric Target Modeling

Bayesian nonparametric models, such as the Gaussian process and the Dirichlet process, have been extensively applied for target kinematics modeling in various applications including environmental monitoring, traffic planning, endangered species tracking, dynamic scene analysis, autonomous robot navigation, and human motion modeling. As shown by these successful applications, Bayesian nonparametric models are able to adjust their complexities adaptively from data as necessary, and are resistant to overfitting or underfitting. However, most existing works assume that the sensor measurements used to learn the Bayesian nonparametric target kinematics models are obtained a priori or that the target kinematics can be measured by the sensor at any given time throughout the task. Little work has been done for controlling the sensor with bounded field of view to obtain measurements of mobile targets that are most informative for reducing the uncertainty of the Bayesian nonparametric models. To present the systematic sensor planning approach to leaning Bayesian nonparametric models, the Gaussian process target kinematics model is introduced at first, which is capable of describing time-invariant spatial phenomena, such as ocean currents, temperature distributions and wind velocity fields. The Dirichlet process-Gaussian process target kinematics model is subsequently discussed for modeling mixture of mobile targets, such as pedestrian motion patterns.

Novel information theoretic functions are developed for these introduced Bayesian nonparametric target kinematics models to represent the expected utility of measurements as a function of sensor control inputs and random environmental variables. A Gaussian process expected Kullback Leibler divergence is developed as the expectation of the KL divergence between the current (prior) and posterior Gaussian process target kinematics models with respect to the future measurements. Then, this approach is extended to develop a new information value function that can be used to estimate target kinematics described by a Dirichlet process-Gaussian process mixture model. A theorem is proposed that shows the novel information theoretic functions are bounded. Based on this theorem, efficient estimators of the new information theoretic functions are designed, which are proved to be unbiased with the variance of the resultant approximation error decreasing linearly as the number of samples increases. Computational complexities for optimizing the novel information theoretic functions under sensor dynamics constraints are studied, and are proved to be NP-hard. A cumulative lower bound is then proposed to reduce the computational complexity to polynomial time.

Three sensor planning algorithms are developed according to the assumptions on the target kinematics and the sensor dynamics. For problems where the control space of the sensor is discrete, a greedy algorithm is proposed. The efficiency of the greedy algorithm is demonstrated by a numerical experiment with data of ocean currents obtained by moored buoys. A sweep line algorithm is developed for applications where the sensor control space is continuous and unconstrained. Synthetic simulations as well as physical experiments with ground robots and a surveillance camera are conducted to evaluate the performance of the sweep line algorithm. Moreover, a lexicographic algorithm is designed based on the cumulative lower bound of the novel information theoretic functions, for the scenario where the sensor dynamics are constrained. Numerical experiments with real data collected from indoor pedestrians by a commercial pan-tilt camera are performed to examine the lexicographic algorithm. Results from both the numerical simulations and the physical experiments show that the three sensor planning algorithms proposed in this dissertation based on the novel information theoretic functions are superior at learning the target kinematics with

little or no prior knowledge

Makarios Now: Plundering Athens and Hippo

A Christian doctrine of happiness differs greatly from contemporary and pseudo-Christian conceptions of happiness, which are measured subjectively and by the accumulation of external goods. In order to develop a fresh account with objective standards, I critique, integrate and revise Aristotle and Augustine’s accounts of happiness. Additionally, I rely heavily on scriptures to present a telos of godlikeness that in turn informs a robust account of makarios. Throughout the thesis, the argument is made that happiness (eudaimonia) and blessedness (makarios) are equivalents. Despite the skepticism of liberal theologians, Christian happiness (makarios) is promised in the New Testament and achievable in this life. Fundamentally, makarios is relational, active, constant, and dependent.

Synergy between Piezo1 and Piezo2 channels confers high-strain mechanosensitivity to articular cartilage.

Diarthrodial joints are essential for load bearing and locomotion. Physiologically, articular cartilage sustains millions of cycles of mechanical loading. Chondrocytes, the cells in cartilage, regulate their metabolic activities in response to mechanical loading. Pathological mechanical stress can lead to maladaptive cellular responses and subsequent cartilage degeneration. We sought to deconstruct chondrocyte mechanotransduction by identifying mechanosensitive ion channels functioning at injurious levels of strain. We detected robust expression of the recently identified mechanosensitive channels, PIEZO1 and PIEZO2. Combined directed expression of Piezo1 and -2 sustained potentiated mechanically induced Ca(2+) signals and electrical currents compared with single-Piezo expression. In primary articular chondrocytes, mechanically evoked Ca(2+) transients produced by atomic force microscopy were inhibited by GsMTx4, a PIEZO-blocking peptide, and by Piezo1- or Piezo2-specific siRNA. We complemented the cellular approach with an explant-cartilage injury model. GsMTx4 reduced chondrocyte death after mechanical injury, suggesting a possible therapy for reducing cartilage injury and posttraumatic osteoarthritis by attenuating Piezo-mediated cartilage mechanotransduction of injurious strains.