Design and implementation of two non-isolated high gain DC-DC converters

In most solar energy systems, the output voltage of a photovoltaic panel is usually between 20 to 40 Vdc. In order to interface the panels to a 400 Vdc bus, a high voltage gain dc-dc converter is required. This thesis starts with analyzing and simulating several topologies that have been already introduced for this application. The voltage gain and efficiency are investigated analytically. A hardware prototype of one of the existing topologies, the interleaved boost converter with voltage multiplier cell, has been developed. Finally, a new topology with a higher voltage transfer ratio is proposed and its experimental results are compared with former topologies. Simulations are used to verify the design and predict the performance of each topology --Abstract, page iii

"Seed Science and Engineering" Exploration on the Construction of Curriculum Ideological and Political System

The specialty of "seed science and Engineering" has trained a large number of scarce seed talents for China. This paper summarizes the experience, existing problems and future improvement direction of the ideological and political system construction of the curriculum of "seed science and Engineering" in our university, in order to improve the ideological and political system construction of colleges and universities

Circular External Difference Families: Construction and Non-Existence

The circular external difference family and its strong version, which themselves are of independent combinatorial interest, were proposed as variants of the difference family to construct new unconditionally secure non-malleable threshold schemes. In this paper, we present new results regarding the construction and non-existence of (strong) circular external difference families, thereby solving several open problems on this topic

City in the park,” Greenway Network Concept of High-Density Cities: Adaptation of Singapore Park Connector Network in Chinese Cities

This paper uses the “Park Connector Network” (PCN) as a model, to analyze Singapore’s experience and to cope with the dramatic increase in population and urbanization, and then to apply this experience to Chinese high-density cities. The research goal is to provide guidance for the adaptation of “City in the Park” in China and the construction of high-density urban green space systems. The concept of “City in the Park” that was born in 2018 in China can be related directly to the “Park Connector Network” model

On the Performances of Estimating Stellar Atmospheric Parameters from CSST Broad-band Photometry

Deriving atmospheric parameters of a large sample of stars is of vital importance to understand the formation and evolution of the Milky Way. Photometric surveys, especially those with near-ultraviolet filters, can offer accurate measurements of stellar parameters, with the precision comparable to that from low/medium resolution spectroscopy. In this study, we explore the capability of measuring stellar atmospheric parameters from CSST broad-band photometry (particularly the near-ultraviolet bands), based on synthetic colors derived from model spectra. We find that colors from the optical and near-ultraviolet filter systems adopted by CSST show significant sensitivities to the stellar atmospheric parameters, especially the metallicity. According to our mock data tests, the precision of the photometric metallicity is quite high, with typical values of 0.17 dex and 0.20 dex for dwarf and giant stars, respectively. The precision of the effective temperature estimated from broad-band colors are within 50 K.Comment: 16 pages, 18 figures, accepted by Research in Astronomy and Astrophysic

The Circular Velocity Curve of the Milky Way from 5 to 25 kpc using luminous red giant branch star

We present a sample of 254,882 luminous red giant branch (LRGB) stars selected from the APOGEE and LAMOST surveys. By combining photometric and astrometric information from the 2MASS and Gaia surveys, the precise distances of the sample stars are determined by a supervised machine learning algorithm: the gradient boosted decision trees. To test the accuracy of the derived distances, member stars of globular clusters (GCs) and open clusters (OCs) are used. The tests by cluster member stars show a precision of about 10 per cent with negligible zero-point offsets, for the derived distances of our sample stars. The final sample covers a large volume of the Galactic disk(s) and halo of $0<R<30$ kpc and $|Z|\leqslant15$ kpc. The rotation curve (RC) of the Milky Way across radius of $5\lesssim R\lesssim25$ kpc have been accurately measured with $\sim$ 54,000 stars of the thin disk population selected from the LRGB sample. The derived RC shows a weak decline along $R$ with a gradient of $-1.83\pm0.02$ $({\rm stat.}) \pm 0.07$ $({\rm sys.})$ km s$^{-1}$ kpc$^{-1}$, in excellent agreement with the results measured by previous studies. The circular velocity at the solar position, yielded by our RC, is $234.04\pm0.08$ $({\rm stat.}) \pm 1.36$ $({\rm sys.})$ km s$^{-1}$, again in great consistent with other independent determinations. From the newly constructed RC, as well as constraints from other data, we have constructed a mass model for our Galaxy, yielding a mass of the dark matter halo of $M_{\rm{200}}$ = ($8.05\pm1.15$)$\times$10$^{11} \rm{M_\odot}$ with a corresponding radius of $R_{\rm{200}}$ = $192.37\pm9.24$ kpc and a local dark matter density of $0.39\pm0.03$ GeV cm$^{-3}$.Comment: 16 pages, 13 figures and 5 tables, accepted by Ap

ExpCLIP: Bridging Text and Facial Expressions via Semantic Alignment

The objective of stylized speech-driven facial animation is to create animations that encapsulate specific emotional expressions. Existing methods often depend on pre-established emotional labels or facial expression templates, which may limit the necessary flexibility for accurately conveying user intent. In this research, we introduce a technique that enables the control of arbitrary styles by leveraging natural language as emotion prompts. This technique presents benefits in terms of both flexibility and user-friendliness. To realize this objective, we initially construct a Text-Expression Alignment Dataset (TEAD), wherein each facial expression is paired with several prompt-like descriptions.We propose an innovative automatic annotation method, supported by Large Language Models (LLMs), to expedite the dataset construction, thereby eliminating the substantial expense of manual annotation. Following this, we utilize TEAD to train a CLIP-based model, termed ExpCLIP, which encodes text and facial expressions into semantically aligned style embeddings. The embeddings are subsequently integrated into the facial animation generator to yield expressive and controllable facial animations. Given the limited diversity of facial emotions in existing speech-driven facial animation training data, we further introduce an effective Expression Prompt Augmentation (EPA) mechanism to enable the animation generator to support unprecedented richness in style control. Comprehensive experiments illustrate that our method accomplishes expressive facial animation generation and offers enhanced flexibility in effectively conveying the desired style