Optimal Investment With Default Risk

In this paper, we investigate how investors who face both equity risk and credit risk would optimally allocate their financial wealth in a dynamic continuous-time setup. We model credit risk through the defaultable zero-coupon bond and solve the dynamics of its price after pricing it. Using stochastic control methods, we obtain a closed-form solution to this investment problem and characterize its variation with respect to different factors in the economy. We find that non-zero recovery rate of the credit-risky bond affects investors' decision in a fundamental way. Because of this, investors try to time the market conditions in their decision making process. It also induces hedging term in this setup of otherwise deterministic investment opportunity set. Through numerical examples, we show that the inclusion of credit market is shown to be able to enhance investors' welfare.Default Risk; Corporate Bond; Asset Allocation; Welfare Analysis

Thermoelectric Behavior of Quantum Dots Engineered Bulk Half-Heusler Nanocomposites.

Over the past 20 years, thermoelectric materials have received more and more attention due to dwindling natural resources and inefficient energy conversion systems. In this thesis, focus was placed on the development of half-Heusler based nanocomposite materials for application in thermoelectric technology. Half-Heusler alloys were chosen as our research focus due to its environmentally friendly nature, cheap elemental constituents, and their robust mechanical stability relative to other thermoelectric materials. Half-Heuslers with 18 valence electrons are narrow band gap semiconductors with large Seebeck coefficients. Detrimentally, however, the thermal conductivity can reach ~ 10 Wm-1K-1. In order to improve the thermoelectric properties of half-Heusler, two main strategies were applied. The first strategy is to increase mass fluctuation or point defects in the sample during solid-state reaction. The second strategy is to add a doping element to tune the carrier density or other phases to form additional phonon scattering centers. This work focuses on the effects of (1) the full-Heusler (FH) second phase, (2) heavy doping via Sb substitution at Sn sites, and (3) band gap engineering through Ge substitution at Sn sites on the electronic and thermal properties of half-Heusler (HH) matrices with composition Ti0.1Zr0.9NiSn. Additionally, (4) the concept of energy filtering at HH/FH interfaces on Zr0.25Hf0.75Ni1+xSn1-ySby composites with varying doping levels is investigated. And lastly, (5) we explore the effect of varying chemical composition of the FH inclusions on the electronic and thermal properties of HH phases. This is achieved by the reaction of elemental Co with polycrystalline powder with composition Zr0.25Hf0.75NiSn.PhDMaterials Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113524/1/yuanfeng_1.pd

Analysis of malicious input issues on intelligent systems

Intelligent systems can facilitate decision making and have been widely applied to various domains. The output of intelligent systems relies on the users\u27 input. However, with the development of Web-Based Interface, users can easily provide dishonest input. Therefore, the accuracy of the generated decision will be affected. This dissertation presents three essays to discuss the defense solutions for malicious input into three types of intelligent systems: expert systems, recommender systems, and rating systems. Different methods are proposed in each domain based on the nature of each problem. The first essay addresses the input distortion issue in expert systems. It develops four methods to distinguish liars from truth-tellers, and redesign the expert systems to control the impact of input distortion by liars. Experimental results show that the proposed methods could lead to the better accuracy or the lower misclassification cost. The second essay addresses the shilling attack issue in recommender systems. It proposes an integrated Value-based Neighbor Selection (VNS) approach, which aims to select proper neighbors for recommendation systems that maximize the e-retailer\u27s profit while protecting the system from shilling attacks. Simulations are conducted to demonstrate the effectiveness of the proposed method. The third essay addresses the rating fraud issue in rating systems. It designs a two-phase procedure for rating fraud detection based on the temporal analysis on the rating series. Experiments based on the real-world data are utilized to evaluate the effectiveness of the proposed method

Efficient Precise Dynamic Data Race Detection For Cpu And Gpu

Data races are notorious bugs. They introduce non-determinism in programs behavior, complicate programs semantics, making it challenging to debug parallel programs. To make parallel programming easier, efficient data race detection has been a research topic in the last decades. However, existing data race detectors either sacrifice precision or incur high overhead, limiting their application to real-world applications and scenarios. This dissertation proposes approaches to improve the performance of dynamic data race detection without undermining precision, by identifying and removing metadata redundancy dynamically. This dissertation also explores ways to make it practical to detect data races dynamically for GPU programs, which has a disparate programming and execution model from CPU workloads. Further, this dissertation shows how the structured synchronization model in GPU programs can simplify the algorithm design of data race detection for GPU, and how the unique patterns in GPU workloads enable an efficient implementation of the algorithm, yielding a high-performance dynamic data race detector for GPU programs

Biomimetic approaches toward the control of bacterial infections

Bacterial infection form a growing health problem worldwide, requiring novel strategies to prevent and treat bacterial infections. This thesis aims to learn from the natural defense systems of the human body to fight bacterial infection. Firstly, inspired by the natural versatility of cell membranes, macrophage-membrane coated, antimicrobial nanoparticles were developed to kill bacteria, that were seeking shelter inside the same macrophages that were supposed to kill them. This class of infections is troublesome as it often causes re-occurrence of infection after traditional antibiotic treatment, since antibiotics may have difficulty entering infected macrophages. Macrophage-membrane coated, antimicrobial nanoparticles however, easily entered infected macrophages and killed infecting bacteria more effectively than a clinically-used antibiotic. Secondly, inspired by the secondary G-quadruplex structure of DNA, a hydrogel based novel biomimetic cascade reaction container material was designed producing reactive oxygen species (ROS) from endogenous glucose to control bacterial infections. Animal evaluation was successful and demonstrated reduced glucose levels around an infected wound making it extremely suitable for use in diabetic patients as an antimicrobial wound dressing. Importantly, this strategy was non-antibiotic based and induction of ROS resistance is unlikely. Nature has more to teach us than the two examples developed further in this thesis and lessons from nature are worth to consider more extensive in developing novel strategies for bacterial infection control

The relationship between the ownership of elder care homes and quality of care in urban China

Traditional familial care has been challenged due to the reduction of family size and increased mobility of the Chinese population. Institutional elder care is increasingly becoming an alternative to familial care. This study explores the relationship between ownership of elder care home and care quality, using data collected in 2010 from 157 homes in Tianjin. Two hypotheses were proposed for the study: 1) There is a difference between government and non government-owned facilities in facility characteristics; 2) Government-owned facilities have better care quality outcomes. The t-test results showed that government-owned elder care homes had advantages in economic resources, staffing and the availability of services. Government-owned facilities reported lower mortality rate compared to non government-owned facilities. Multi-variant regression analysis showed that economic resources—whether funding from the government or high payments from care-recipients in private facilities--are important factors predicting higher levels of care quality. These results indicate that the Chinese government continues to play an important role in institutional long term care; in the meantime, private market is increasing its prominence in the long term care market

Higher-order Topology of Axion Insulator EuIn2_2As2_2

Based on first-principles calculations and symmetry analysis, we propose that EuIn$_2$As$_2$ is a long awaited axion insulator with antiferromagnetic (AFM) long range order. Characterized by the parity-based invariant $\mathbb Z_4=2$, the topological magneto-electric effect is quantized with $\theta=\pi$ in the bulk, with a band gap as large as 0.1 eV. When the staggered magnetic moment of the AFM phase is along $a/b$ axis, it's also a TCI phase. Gapless surface states emerge on (100), (010) and (001) surfaces, protected by mirror symmetries (nonzero mirror Chern numbers). When the magnetic moment is along $c$ axis, the (100) and (001) surfaces are gapped. As a consequence of a high-order topological insulator with $\mathbb Z_4=2$, the one-dimensional (1D) chiral state can exist on the hinge between those gapped surfaces. We have calculated both the topological surface states and hinge state in different phases of the system, respectively, which can be detected by ARPES or STM experiments

Rating Fraud Detection---Towards Designing a Trustworthy Reputation Systems

Reputation systems could help consumers avoid transaction risk by providing historical consumers’ feedback. But, traditional reputation systems are vulnerable to the rating manipulation. It will undermine the trustworthiness of the reputation systems and users’ satisfaction will be lost. To address the issue, this study uses the real-world rating data from two travel website: Tripadvisor.com and Expedia.com and one e-commerce website Amazon.com to empirically exploit the features of fraudulent raters. Based on those features, it proposes the new method for fraudulent rater detection. First, it examines the received rating series of each entity and filter out the entity which is under attack (termed as target entity). Second, the clustering based method is applied to discriminate fraudulent raters. Experimental studies have shown that the proposed method is effective in detecting the fraudulent raters accurately while keeping the majority of the normal users in the systems in various attack environment settings