Comparison of single-phase matrix converter and H-bridge converter for radio frequency induction heating

This paper compares the newly developed single-phase matrix converter and the more conventional H- bridge converter for radio frequency induction heating. Both the converters exhibit unity power factor, very low total harmonic distortion at the utility supply interface, good controllability under soft switching condition for a wide range of power, and high efficiencies, whilst still having simple structures. A novel switching control pattern has been proposed for the matrix converter in order to maintain the comparable performance to the H-bridge converter. Simulation and experimental results for both converters are presented. Comparisons between two converters have confirmed the excellent performance of the proposed matrix converter

Deciphering Taxa-function Relationships in Population-level Studies of Human Gut Microbiomes

The human gut microbiome is a complex and dynamic ecosystem, featuring a multitude of microbes all interacting with their hosts in an elaborate manner. Even though this exchange is often mediated through microbial metabolic and functional outputs, such as the production of certain metabolites, environmental exposures, and host lifestyle are highly influential in shaping the presence of microbial species irrespective of their individual roles. As such, a comprehensive understanding of the microbiome requires researchers to examine the relationship between taxonomic abundance and function simultaneously. Assessing microbial contributions to important ecosystem services can enable identification of robust functions supported by a variety of species, or to identify important keystone taxa that are associated with a disease-causing biochemical pathway. The primary objective of this thesis is to assess different approaches for investigating the taxa-function relationship and evaluate its value in providing unique biological insights. First, we leveraged densely collected multi-omics data from the New Hampshire Birth Cohort Study to identify genus-metabolite pairs that are core to infant gut microbiomes. Second, we developed a novel statistical method that enables integrating taxa-function relationships in epidemiological studies. Third, we assessed microbial phenotypic traits as a potential source for defining interpretable and human-centric microbiome function

Single phase matrix converter for radio frequency induction heating

Conventional converters for radio frequency induction heating usually follow an AC-DC-AC structure, which can exhibit non-unity power factor and introduce large harmonic currents into the utility supply. The need for a direct converter for radio frequency induction heating, featuring unity power factor, and sinusoidal input current, has motivated the development of a single phase matrix converter as an induction heater. A novel commutation strategy is therefore required to ensure smooth operation of the converter whilst creating a high frequency output under soft switching conditions. The operating principle and features of the proposed converter are described here, and experimentally verifie

An open--quantum--system formulation of particle decay

We consider an open quantum system which contains unstable states. The time evolution of the system can be described by an effective non-hermitian Hamiltonian H_{eff}, in accord with the Wigner--Weisskopf approximation, and an additional term of the Lindblad form, the socalled dissipator. We show that, after enlarging the original Hilbert space by states which represent the decay products of the unstable states, the non-hermitian part of H_{eff} --the ``particle decay''-- can be incorporated into the dissipator of the enlarged space via a specific Lindblad operator. Thus the new formulation of the time evolution on the enlarged space has a hermitian Hamiltonian and is probability conserving. The equivalence of the new formulation with the original one demonstrates that the time evolution which is governed by a non-hermitian Hamiltonian and a dissipator of the Lindblad form is nevertheless completely positive, just as systems with hermitian Hamiltonians.Comment: 8 page

Performance of first and second-order sliding mode observers for nonlinear systems

This paper presents a brief study on the design and performance comparison of conventional first-order and super-twisting second-order sliding mode observers for some nonlinear control systems. Estimation accuracy, fast response, chattering effect, peaking phenomenon and robustness are considered for nonlinear ystems under observer-based output feedback control and state feedback control

Learning and Predicting Dynamic Behavior with Graphical Multiagent Models

Factored models of multiagent systems address the complexity of joint behavior by exploiting locality in agent interactions. History-dependent graphical multiagent models (hGMMs) further capture dynamics by conditioning behavior on history. The challenges of modeling real human behavior motivated us to extend the hGMM representation by distinguishing two types of agent interactions. This distinction opens the opportunity for learning dependence networks that are different from given graphical structures representing observed agent interactions. We propose a greedy algorithm for learning hGMMs from time-series data, inducing both graphical structure and parameters. Our empirical study employs human-subject experiment data for a dynamic consensus scenario, where agents on a network attempt to reach a unanimous vote. We show that the learned hGMMs directly expressing joint behavior outperform alternatives in predicting dynamic human voting behavior, and end-game vote results. Analysis of learned graphical structures reveals patterns of action dependence not directly reflected in the original experiment networks

Cultural evolution in Vietnam’s early 20th century: a Bayesian networks analysis of Franco-Chinese house designs

The study of cultural evolution has taken on an increasingly interdisciplinary and diverse approach in explicating phenomena of cultural transmission and adoptions. Inspired by this computational movement, this study uses Bayesian networks analysis, combining both the frequentist and the Hamiltonian Markov chain Monte Carlo (MCMC) approach, to investigate the highly representative elements in the cultural evolution of a Vietnamese city’s architecture in the early 20th century. With a focus on the façade design of 68 old houses in Hanoi’s Old Quarter (based on 78 data lines extracted from 248 photos), the study argues that it is plausible to look at the aesthetics, architecture, and designs of the house façade to find traces of cultural evolution in Vietnam, which went through more than six decades of French colonization and centuries of sociocultural influence from China. The in-depth technical analysis, though refuting the presumed model on the probabilistic dependency among the variables, yields several results, the most notable of which is the strong influence of Buddhism over the decorations of the house façade. Particularly, in the top 5 networks with the best Bayesian Information Criterion (BIC) scores and p\u3c0.05, the variable for decorations (DC) always has a direct probabilistic dependency on the variable B for Buddhism. The paper then checks the robustness of these models using Hamiltonian MCMC method and find the posterior distributions of the models’ coefficients all satisfy the technical requirement. Finally, this study suggests integrating Bayesian statistics in the social sciences in general and for the study of cultural evolution and architectural transformation in particular