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We propose a novel set of Poisson Cluster Process models to detect Ultra-Diffuse Galaxies (UDGs), a recently-discovered class of galaxies that are challenging to detect and are of substantial interests in modern astrophysics. We construct an improved spatial birth-death-move MCMC algorithm to make inferences about the locations of these otherwise un-observable galaxies. Our novel models significantly out-perform existing approaches based on the Log-Gaussian Cox Process; the novel marked point process we propose can also improve the detection performance for UDGs in noisy environments. We find evidence of a potential new "dark galaxy" that was not detected using previous methods., Comment: 21 pages, 6 figures, 1 table; submitted to AoAS, comments are welcome

A unified power quality controller based on a magnetic flux control tunable reactor is proposed. The magnetic flux control tunable reactor is composed of a voltage source inverter (VSI) and a transformer with an air gap. The power quality controller is divided into two parts: the harmonic open circuit part is connected in series in the system, and the harmonic short circuit part is connected in parallel in the system. Among them, the series part detects the fundamental wave component of the primary side current of the transformer, generates a reference signal, and controls the VSI to generate a fundamental wave controllable current, after the filter is applied to the secondary side of the transformer, the primary side of the transformer will show variable impedance and open circuit to the fundamental wave and harmonic current respectively; The parallel part detects the fundamental wave component of the primary side current, generates a reference signal, and controls the VSI to generate a fundamental controllable voltage, After the filter is applied to the secondary side of the transformer, the primary side of the transformer presents controllable impedance and short circuit to the fundamental wave and harmonic current respectively.By building a MATLAB simulation model, the effectiveness of the proposed unified power quality controller is verified.

In this thesis, Gibbs point process (GPP) models are constructed to study the spatial distribution of objects in the star formation complexes of the M33 galaxy. The GPP models circumvent the limitations of the two-point correlation function employed in the current astronomy literature by naturally accounting for the inhomogeneous distribution of these objects. The spatial distribution of these objects serves as a sensitive probe in understanding the star formation process, which is crucial in understanding the formation of galaxies and the Universe. The objects under study include the CO filament structure, giant molecular clouds (GMCs) and young stellar cluster candidates (YSCCs). A hierarchical model is adopted to account for the natural formation hierarchy among these objects. The effect of the properties of GMCs on their spatial correlation with YSCCs is also investigated. A Bayesian paradigm is employed for model inference. Potential physical implications are obtained and addressed through model criticism.

Targeting glycolysis has been considered therapeutically intractable owing to its essential housekeeping role. However, the context-dependent requirement for individual glycolytic steps has not been fully explored. We show that CRISPR-mediated targeting of glycolysis in T cells in mice results in global loss of Th17 cells, whereas deficiency of the glycolytic enzyme glucose phosphate isomerase (Gpi1) selectively eliminates inflammatory encephalitogenic and colitogenic Th17 cells, without substantially affecting homeostatic microbiota-specific Th17 cells. In homeostatic Th17 cells, partial blockade of glycolysis upon Gpi1 inactivation was compensated by pentose phosphate pathway flux and increased mitochondrial respiration. In contrast, inflammatory Th17 cells experience a hypoxic microenvironment known to limit mitochondrial respiration, which is incompatible with loss of Gpi1 . Our study suggests that inhibiting glycolysis by targeting Gpi1 could be an effective therapeutic strategy with minimum toxicity for Th17-mediated autoimmune diseases, and, more generally, that metabolic redundancies can be exploited for selective targeting of disease processes.

A novel active power filter based on linear transformer harmonic current compensation is proposed for high voltage power distribution systems application. In the active power filter, the primary of the transformer is in parallel with the harmonic-producing loads, the secondary of the transformer is connected with PWM voltage source inverters that produce harmonic compensation current. The harmonic current of the primary is detected and tracked by the inverters with a fixed compensation coefficient. When satisfied the harmonic current compensation condition, the linear transformer can really exhibit nearly zero impedance to harmonic current and excitation impedance to fundamental current, thus lead harmonic current flow into the linear transformer circuit. The principle of operation of the proposed active power filter is discussed in detail. Simulated waveforms and experimental results obtained from a prototype are presented to verify the effectiveness of the active power filter