A Selective Study on Art Songs Composed by Chinese Contemporary Composer Liu Cong

In this article, a nationally renowned Chinese contemporary composer Liu Cong and his representative art songs were introduced. Focuses on Cong Liu’s music style, this analyzes his favorite compositional subjects, his salient tonal languages, and many of his compositional inspirations. Selective art songs composed by Cong Liu were also carefully demonstrated

Three Essays on Stock Market Volatility

Volatility is inherently unobservable, and thus the selection of models and their definition is crucial in financial research. This dissertation attempts to check the role of investor sentiment and forecast Value-at-Risk (VaR) of the stock market using both parametric and nonparametric approaches. In the first essay, based on daily return data of three stock indices and four individual stocks from January 1988 to December 2006, the role of day-of-the-week, as well as investor sentiment, is examined using two approaches: linear regression to test investor sentiment effect on stock returns and Logit regression to test the investor sentiment effect on market direction. The results indicate that there is a significant positive role of investor sentiment in the market. However, the outcome also shows that the role of the day-of-the-week effect varies among stocks Based on the results presented in the first essay, in the second paper investor sentiment effect was included in both mean and conditional variance equations of GARCH models. By comparing augmented GARCH models considering investor sentiment effect with traditional GARCH models, the result demonstrated that aug-mented GARCH models are signifiantly better than traditional GARCH models where AIC, BIC, log-likelihood, and out-of-sample VaR forecasting were employed. The research indicates that a significant role of investor sentiment in forecasting conditional mean and conditional volatility and the accuracy of GARCH models is improved by accounting for investor sentiment effect. Compared with the first and second essays employing a parametric method to analyze the stock market, the third paper adopts a nonparametric approach to estimate the conditional probability distribution of asset returns. It is evident that the exact conditional mean and conditional variance is inherently unobservable for time series. In practice, conditional variance is often achieved from different parametric models, such as GARCH, EGARCH, IGARCH, etc., by assuming di®erent distributions such as normal, student\u27s t, or skewed t. Therefore, the accuracy of forecasting strongly depends on the distribution assumption. The nonparametric method avoids the need for a distribution assumption by using a neural network to estimate the potentially nonlinear relationship between VaR and returns. Our results show that the neural network approach outperforms traditional GARCH models. (96 pages

The Non-Verismo Tendency of the Verismo Opera La Bohème: A Comparative Study of Murger’s Novel and Puccini’s Opera

Through a comparative study of Puccini’s opera, La Bohème, and the literary script, Murger’s novel, Scènes de la vie de Bohème, this paper analyzes the selecting, adding and re-shaping of the original plot when Puccini adapted the opera script in collaboration with the playwrights, the artistic transformation of the characters and their destinies and the great changes in storytelling techniques and the tone so as to explore Puccini’s unique opera aesthetic philosophy under the influence of verismo and sum up the “non-verismo” tendencies of his works in the form of verismo

A Corpus-based Study on the Features and Translation Skills of Conjunctions in the English Translation of Chinese Family Law

As the number of foreign friends coming to live and work in China had demonstrated an apparent upward trend, the research sets out to conduct a corpus-based analysis on conjunctions in the English translation of the Chinese Family Law through quantitative and qualitative approaches. Based on the data analysis, it could be concluded that the translation text tends to use additive and hypothetical conjunctions, but adversative conjunctions appear less frequent; the translation text presents a low diversity in additive, hypothetical and adversative conjunctions; in the translation text, additive, hypothetical, and clarifying conjunctions exhibit explicitness, while temporal, adversative, causal and continuative conjunctions represent implicitness. Then four translation skills are proposed based on the data, including “amplification” “interpretation” “ellipsis” and “sentence reorganization”

The Formation and Mechanism of Soft Power

As we know soft power has got more and more attention in this world, yet how is it formed and functioning? This article attempts to illustrate the formation and mechanism of soft power, through the research upon a wide range of various subjects and fields, such as physics, law of principle, humanism, culture, philosophy, the methodology of natural science and social science, the Oriental wisdom and western technology, finally pointing to human nature and the heart

Application of fine injection production technology in water drive reservoir

As the basic condition for ensuring the stability of oil extraction in the development process of oil extraction in our country, some areas have entered the stage of high water cut development. It is very difficult to develop water drive reservoirs in the high water cut development stage, especially under the background of low oil price industry. How to ensure the orderly promotion of the beneficial development of water drive reservoirs and optimize the comprehensive quality of development has become the core of the development process of the industry and enterprises. The core of this is how to use fine injection and production technology. Therefore, the oil production plant needs to integrate different types of water drive reservoir requirements, take it as the core orientation, start based on the water quality source, place the target on good water injection and effective water injection, optimize and innovate fine injection and production technology in an all-round way, so as to achieve the high efficiency of the entire regulation process, improve the quality of water drive, and achieve the development goal of water drive reservoir benefits. Based on this, this paper analyzes this problem, and puts forward some suggestions on the application of technology for reference

Wakening Past Concepts without Past Data: Class-Incremental Learning from Online Placebos

Not forgetting old class knowledge is a key challenge for class-incremental learning (CIL) when the model continuously adapts to new classes. A common technique to address this is knowledge distillation (KD), which penalizes prediction inconsistencies between old and new models. Such prediction is made with almost new class data, as old class data is extremely scarce due to the strict memory limitation in CIL. In this paper, we take a deep dive into KD losses and find that "using new class data for KD" not only hinders the model adaption (for learning new classes) but also results in low efficiency for preserving old class knowledge. We address this by "using the placebos of old classes for KD", where the placebos are chosen from a free image stream, such as Google Images, in an automatical and economical fashion. To this end, we train an online placebo selection policy to quickly evaluate the quality of streaming images (good or bad placebos) and use only good ones for one-time feed-forward computation of KD. We formulate the policy training process as an online Markov Decision Process (MDP), and introduce an online learning algorithm to solve this MDP problem without causing much computation costs. In experiments, we show that our method 1) is surprisingly effective even when there is no class overlap between placebos and original old class data, 2) does not require any additional supervision or memory budget, and 3) significantly outperforms a number of top-performing CIL methods, in particular when using lower memory budgets for old class exemplars, e.g., five exemplars per class.Comment: Accepted to WACV 2024. Code: https://github.com/yaoyao-liu/online-placebo

InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale

InSite is a computational method that integrates high-throughput protein and sequence data to infer the specific binding regions of interacting protein pairs

Effect of ultrasound on physicochemical properties of emulsion stabilized by fish myofibrillar protein and xanthan gum

peer-reviewedTo investigate the effects ultrasound (20 kHz, 150–600 W) on physicochemical properties of emulsion stabilized by myofibrillar protein (MP) and xanthan gum (XG), the emulsions were characterized by Fourier transform infrared (FT-IR) spectroscopy, ζ-potential, particle size, rheology, surface tension, and confocal laser scanning microscopy (CLSM). FT-IR spectra confirmed the complexation of MP and XG, and ultrasound did not change the functional groups in the complexes. The emulsion treated at 300 W showed the best stability, with the lowest particle size, the lowest surface tension (26.7 mNm−1) and the largest ζ-potential absolute value (25.4 mV), that were confirmed in the CLSM photos. Ultrasound reduced the apparent viscosity of the MP-XG emulsions, and the changes of particle size were manifested in flow properties. Generally, ultrasound was successfully applied to improve the physical stability of MP-XG emulsion, which could be used as a novel delivery system for functional material