Does Public Health Policy Matter?: Explaining Variation in COVID-19 Outcomes Across the 50 States

The Covid-19 pandemic has prompted debate about what factors cause wide variations in mortality and infection rates across the United States and raised questions about what can be done to limit the spread of future outbreaks. In the comparative international politics literature, there are four explanations that determine how well a country can contain outbreaks: leadership, state capacity, demographics, and state culture. Currently, there are no studies that show a comprehensive evaluation of what has caused variations in mortality rate among the fifty states. This study aims to examine state variation among the 50 states in the U.S. and its influence on Covid-19 infection and mortality rate. The study will utilize a mixed-method approach to determine which factors have the most impact on mortality and infection rate. Using a multivariate and case study analysis, I aim to show how the four explanations predicted the pandemic case and death rates. In the findings of this study, I found that several factors, including Republican party control, urbanization, and race, predicted a state’s Covid-19 outcomes. The purpose of this study is to urge states to repair weaknesses in pandemic response plans, address structural discrimination within the healthcare system, and facilitate national cooperation that will better equip states with the ability to contain an outbreak

OPTICAL CHARACTERIZATION OF INHOMOGENEITIES IN BLUE-EMITTING INGAN/GAN MQWS

The growth of blue-emitting InGaN/GaN MQWs, the system setup of a low temperature PL/EL/IV system for temperature dependent PL/EL/IV spectroscopy, and the system setup of a CLSM with nanometer-scale spectrum measurement and TRPL measurement abilities are described. A range of temperature-dependent PL experimental work, CLSM imaging experimental work and TRPL experimental work on blue-emitting InGaN/GaN MQWs are presented. In temperature-dependent PL measurements, the decreasing of spectrum- integrated PL intensity with increasing temperature is explained with a two-nonradiative- channel model, in which the two nonradiative channels correspond to the thermal activation of carriers out of the strongly localized states and the weakly localized states, respectively. The ‘S-shaped’ red-blue-red shift of PL peak energy and the ‘inverse S- shaped’ change of PL FWHM when temperature increases from 10 K to 300 K are explained with carrier localization and carrier dynamics. CLSM imaging and nanometer-scale PL spectral measurements show that the PL intensity fluctuates in micrometer scale, and that the bandgap energy in bright region is tens of meV smaller than that in dark region. The small-bandgap-energy regions are localization centers which limit the diffusion of the carriers and prevent carriers from diffusing to the NRRCs. Nanometer-scale TRPL measurements are conducted on blue-emitting InGaN/GaN MQWs for the first time, as far as the author knows. The measurements show that both bright region and dark region are characterized by two lifetimes: fast decay lifetime t1 is smaller than 3 ns and slow decay lifetime t2 is longer than 10 ns. The fast decay with shorter lifetime t1 corresponds to the carrier localization in weakly localized states, where the radiative recombination is more quenched by NRRCs and also competes with carrier transfer intro strongly localized states. And the slow decay with longer lifetime t2 corresponds carrier localization in strongly localized states. The fact that both fast decay and slow decay exist in both bright region and dark region indicates that both bright region and dark region has small bandgap energy fluctuation in themselves. Measurements show that the slow decay lifetime t2 in bright region is longer than that in dark region, indicating a higher probability of nonradiative recombination in dark region or carrier transporting from dark region to bright region. Measurements show that larger bandgap energy difference between small- bandgap-energy regions and large-bandgap-energy regions provides stronger carrier localization effect, via the presence of higher CLSM image average intensity, larger PL intensity ratio and longer smaller-bandgap-energy slow decay lifetime t2 when larger bandgap energy difference occurs. The effect of MOCVD growth parameters on MQW bandgap energy fluctuations and average intensity was analyzed. It was found out that by increasing growth pressure, decreasing growth rate, increasing growth temperature, increasing effective V/III ratio, and increasing gas speed, the bandgap energy difference between bright region and dark region increases, leading to higher average PL intensity

Coordinating decentralized learning and conflict resolution across agent boundaries

It is crucial for embedded systems to adapt to the dynamics of open environments. This adaptation process becomes especially challenging in the context of multiagent systems because of scalability, partial information accessibility and complex interaction of agents. It is a challenge for agents to learn good policies, when they need to plan and coordinate in uncertain, dynamic environments, especially when they have large state spaces. It is also critical for agents operating in a multiagent system (MAS) to resolve conflicts among the learned policies of different agents, since such conflicts may have detrimental influence on the overall performance. The focus of this research is to use a reinforcement learning based local optimization algorithm within each agent to learn multiagent policies in a decentralized fashion. These policies will allow each agent to adapt to changes in environmental conditions while reorganizing the underlying multiagent network when needed. The research takes an adaptive approach to resolving conflicts that can arise between locally optimal agent policies. First an algorithm that uses heuristic rules to locally resolve simple conflicts is presented. When the environment is more dynamic and uncertain, a mediator-based mechanism to resolve more complicated conflicts and selectively expand the agents' state space during the learning process is harnessed. For scenarios where mediator-based mechanisms with partially global views are ineffective, a more rigorous approach for global conflict resolution that synthesizes multiagent reinforcement learning (MARL) and distributed constraint optimization (DCOP) is developed. These mechanisms are evaluated in the context of a multiagent tornado tracking application called NetRads. Empirical results show that these mechanisms significantly improve the performance of the tornado tracking network for a variety of weather scenarios. The major contributions of this work are: a state of the art decentralized learning approach that supports agent interactions and reorganizes the underlying network when needed; the use of abstract classes of scenarios/states/actions that efficiently manages the exploration of the search space; novel conflict resolution algorithms of increasing complexity that use heuristic rules, sophisticated automated negotiation mechanisms and distributed constraint optimization methods respectively; and finally, a rigorous study of the interplay between two popular theories used to solve multiagent problems, namely decentralized Markov decision processes and distributed constraint optimization

Three essays in real option models of real estate development

Real estate developments make great applications for real option theory. However, current real option models for real estate development do not pick up the important features of real estate development such as the land-use right as an on-going lease agreement or the entitlement processes in every development project. We build and solve mathematically parsimoneous yet plausible stochastic-control models to capture these features and the models yield rich implications. We then test these implications empirically using manually-collected data. In chapter one, we model the real estate development process as a compound real option in a parsimonious continuous-time feedback control framework. The acquisition of a land-use right is the first option, and the decision to begin construction is the second option. We model the cost of maintaining the land-use right as a running cost during the waiting period before construction. This feature allows the running cost to be stochastic and interacts with both the decision to obtain the right and the decision to start construction. We obtain a closed-form solution for the value of the compound option and demonstrate rich implications using numerical examples. A higher running cost squeezes the two decisions together while a lower running cost encourages the acquisition of the land-use right and delays construction simultaneously. In chapter two, we recognize that entitlement process is highly risky and out of control of the investors in reality. Moreover, the real estate market in the U.S. has shown a trend towards more stringent entitlement regulation. Therefore, we model entitlement process as a separate stage in development process in which the investor has little control. In particular, we model the entitlement stage as a European style real option with a stochastic entitlement cost. We solve the model analytically. Our main result implies that, to the contrary of tradition real option theory, higher entitlement risk urges the investors to start entitlement process earlier in order to counter the lack of control. In chapter three, we test the empirical implications of entitlement in the previous chapter using hand-collected Charlotte local data of rezoning petitions. In particular, we collect waiting time, number of revisions, size of lot, decision outcome as well as other characteristics for rezoning petition from 2001 to 2012, published on Charlotte-Mecklenburg City Planning website. The results of negative binomial regressions confirm our earlier theoretical prediction that the investors start earlier when facing more difficult and riskier entitlement process. Moreover, house price is overall negatively correlated with the entitlement riskiness, which aggravates the hastening effect of entitlement risk. In conclusion, our real option models of land-use right and entitlement in real estate development prove to be mathematically novel, economically insightful, and show potential for wide applications

Spintronic Terahertz Emitters: Status and Prospects from a Materials Perspective

Spintronic terahertz (THz) emitters, consisting of ferromagnetic (FM)/non-magnetic (NM) thin films, have demonstrated remarkable potential for use in THz time-domain spectroscopy and its exploitation in scientific and industrial applications. Since the discovery that novel FM/NM heterostructures can be utilized as sources of THz radiation, researchers have endeavored to find the optimum combination of materials to produce idealized spintronic emitters capable of generating pulses of THz radiation over a large spectral bandwidth. In the last decade, researchers have investigated the influence of a wide range of material properties, including the choice of materials and thicknesses of the layers, the quality of the FM/NM interface, and the stack geometry upon the emission of THz radiation. It has been found that particular combinations of these properties have greatly improved the amplitude and bandwidth of the emitted THz pulse. Significantly, studying the material properties of spintronic THz emitters has increased the understanding of the spin-to-charge current conversion processes involved in the generation of THz radiation. Ultimately, this has facilitated the development of spintronic heterostructures that can emit THz radiation without the application of an external magnetic field. In this review, we present a comprehensive overview of the experimental and theoretical findings that have led to the development of spintronic THz emitters, which hold promise for use in a wide range of THz applications. We summarize the current understanding of the mechanisms that contribute to the emission of THz radiation from the spintronic heterostructures and explore how the material properties contribute to the emission process

Interactions between amiodarone and the hERG potassium channel pore determined with mutagenesis and in silico docking

AbstractThe antiarrhythmic drug amiodarone delays cardiac repolarisation through inhibition of hERG-encoded potassium channels responsible for the rapid delayed rectifier potassium current (IKr). This study aimed to elucidate molecular determinants of amiodarone binding to the hERG channel. Whole-cell patch-clamp recordings were made at 37°C of ionic current (IhERG) carried by wild-type (WT) or mutant hERG channels expressed in HEK293 cells. Alanine mutagenesis and ligand docking were used to investigate the roles of pore cavity amino-acid residues in amiodarone binding. Amiodarone inhibited WT outward IhERG tails with a half-maximal inhibitory concentration (IC50) of ∼45nM, whilst inward IhERG tails in a high K+ external solution ([K+]e) of 94mM were blocked with an IC50 of 117.8nM. Amiodarone’s inhibitory action was contingent upon channel gating. Alanine-mutagenesis identified multiple residues directly or indirectly involved in amiodarone binding. The IC50 for the S6 aromatic Y652A mutation was increased to ∼20-fold that of WT IhERG, similar to the pore helical mutant S624A (∼22-fold WT control). The IC50 for F656A mutant IhERG was ∼17-fold its corresponding WT control. Computational docking using a MthK-based hERG model differentiated residues likely to interact directly with drug and those whose Ala mutation may affect drug block allosterically. The requirements for amiodarone block of aromatic residues F656 and Y652 within the hERG pore cavity are smaller than for other high affinity IhERG inhibitors, with relative importance to amiodarone binding of the residues investigated being S624A∼Y652A>F656A>V659A>G648A>T623A

Dislocation interaction with C in alpha-Fe: a comparison between atomic simulations and elasticity theory

The interaction of C atoms with a screw and an edge dislocation is modelled at an atomic scale using an empirical Fe-C interatomic potential based on the Embedded Atom Method (EAM) and molecular statics simulations. Results of atomic simulations are compared with predictions of elasticity theory. It is shown that a quantitative agreement can be obtained between both modelling techniques as long as anisotropic elastic calculations are performed and both the dilatation and the tetragonal distortion induced by the C interstitial are considered. Using isotropic elasticity allows to predict the main trends of the interaction and considering only the interstitial dilatation will lead to a wrong interaction

Multi-Object Tracking by Iteratively Associating Detections with Uniform Appearance for Trawl-Based Fishing Bycatch Monitoring

The aim of in-trawl catch monitoring for use in fishing operations is to detect, track and classify fish targets in real-time from video footage. Information gathered could be used to release unwanted bycatch in real-time. However, traditional multi-object tracking (MOT) methods have limitations, as they are developed for tracking vehicles or pedestrians with linear motions and diverse appearances, which are different from the scenarios such as livestock monitoring. Therefore, we propose a novel MOT method, built upon an existing observation-centric tracking algorithm, by adopting a new iterative association step to significantly boost the performance of tracking targets with a uniform appearance. The iterative association module is designed as an extendable component that can be merged into most existing tracking methods. Our method offers improved performance in tracking targets with uniform appearance and outperforms state-of-the-art techniques on our underwater fish datasets as well as the MOT17 dataset, without increasing latency nor sacrificing accuracy as measured by HOTA, MOTA, and IDF1 performance metrics

Molecular Russian dolls

The host-guest recognition between two macrocycles to form hierarchical non-intertwined ring-in-ring assemblies remains an interesting and challenging target in noncovalent synthesis. Herein, we report the design and characterization of a box-in-box assembly on the basis of host-guest radical-pairing interactions between two rigid diradical dicationic cyclophanes. One striking feature of the box-in-box complex is its ability to host various 1,4-disubstituted benzene derivatives inside as a third component in the cavity of the smaller of the two diradical dicationic cyclophanes to produce hierarchical Russian doll like assemblies. These results highlight the utility of matching the dimensions of two different cyclophanes as an efficient approach for developing new hybrid supramolecular assemblies with radical-paired ring-in-ring complexes and smaller neutral guest molecules