Acoustic Analysis of the Tones in the Shantou Dialect

This paper mainly analyzes the different tones in the Shantou dialect. The Shantou dialect is known as one of the branches of the Chaoshan dialect which is a sub-group of the southern Min. Compared to other sub-group southern Min dialects, one of the distinguishing tonal characteristics of the Shantou dialect is that it has eight tones while the others have seven. Common views have explained that the eight tones in the Shantou dialect are the result of the four Middle Chinese tones further splitting into the upper register and the lower register. Thus, the Shantou dialect has its unique position in the study of the tonal development of Chinese. In order to better understand this unique tonal phenomenon, with references to the four Middle Chinese tonal categories, the tonal system in the Shantou dialect is acoustically examined. With an acoustic tonal experiment, this study aims to discuss three questions. First, what are the Shantou dialect’s tonal values? Second, what is the relation between its tones and the four Middle Chinese tones? Third, what is the tonal value difference between auditory perception and objective analysis? Based on the measurement of fundamental frequency of speeches from the selected native Shantou dialect speakers by Praat, objectively analyzed tonal values are provided. In comparison with an auditory perception of tonal value in previous studies, differences between the current study and previous research will be discussed. Moreover, I point out that the tonal system in the Shantou dialect is not spoken with as much symmetrical alignment as compared to the four Middle Chinese tones divided into the upper register and the lower register. This paper contains five main parts. The first chapter gives a detailed introduction of the Shantou dialect. Second, the methodology that is used in this study is illustrated. Specifically, it includes how the data was collected and processed using a software program called Praat. Next, the third chapter gives an analysis on each tone’s value, including illustration on its fundamental frequency and tonal contour. Fourth, previous studies and current study on the tonal system in the Shantou dialect are further discussed. Last, a brief conclusion is listed

Intraday volatility analysis of CSI 300 index futures: a dependent functional data method

This study introduces a new volatility model based on dependent functional data to investigate the intraday volatility characteristics of CSI 300 in the context of high-frequency data. The volatility curve is fitted and reconstructed using three methods: functional principal component analysis, Newey-West kernel, and truncationfree Bartlett kernel. We adopt a functional time series approach for short-term dynamic forecasting. The empirical results show that the proposed dependent functional volatility estimation model based on the long-term covariance of the truncated Bartlett kernel can accurately capture the intraday volatility trajectory and outperforms other models in terms of forecast accuracy and profitability. This study improves the volatility-related research methodology, which is conducive to discovering the price formation mechanism of the stock index futures market and improving risk management capabilities

Factors Affecting Users\u27 Dynamic Message Deleting Intention on Social Networks: An Empirical Study Based on Impression Management Theory

Social dynamics is a social networking service that allows users to input updates including letters, pictures, videos and share them with their social friends. Previous research mainly focus on the application of dynamic messages in the fields of communication science and economics. Based on impression management theory, this paper studies the influencing factors of users\u27 dynamic message deleting intention on social networks. The results show that impression management performance and social network fatigue significantly affect user\u27s intention to delete the dynamic messages. While message sender factors, such as self-monitoring, interpersonal interaction and image promotion; social platform factors such as information overload and social overload, indirectly influence the deleting intention through intermediary variables. This paper makes up for the lack of relevant empirical research, making users more social flexibility and effectiveness, thereby enhancing social validity, and have some practical implications for social networking services platforms

Biomarkers for Vincristine-induced Neuropathy

Vincristine is a vinca alkaloid, a commonly used chemotherapy drug for treating leukemia, lymphoma, multiple myeloma and some pediatric cancers. Its major dose-limiting side effect is peripheral neuropathy. The current dosing of “standard-dose-for-all” ignores the genetic and phenotypic variations among different patients, and causes severe neuropathy in some patients while ineffectively treats the others. In the present study, we aim to discover novel biomarkers involved in vincristine-induced neuropathy and identify patients with varied metabolic characteristics. Thus treatment can be tailored accordingly to improve outcomes of vincristine treatment. Pre-dose and post-dose serum samples were collected from two groups of patients (low and high toxicity groups) at the beginning of treatment and at the end of treatments. Liquid chromatography–mass spectrometry (LC-MS) was used to identify and quantify metabolites in the samples. Metabolomics data analysis tools were utilized to analyze the raw spectrum obtained from LC-MS. From statistical analysis and modeling, we identified 27 compounds that showed a difference in intensity between low toxicity and high toxicity patients at the beginning of the treatment. Further verification against database and validation are needed to confirm the biomarkers to be able to be useful in clinics. . Successful validation of the biomarkers will enable the clinicians to treat the patients according to their characteristics which will ultimately improve the survival and quality-of-life of cancer patients

The ProfessionAl Go annotation datasEt (PAGE)

The game of Go has been highly under-researched due to the lack of game records and analysis tools. In recent years, the increasing number of professional competitions and the advent of AlphaZero-based algorithms provide an excellent opportunity for analyzing human Go games on a large scale. In this paper, we present the ProfessionAl Go annotation datasEt (PAGE), containing 98,525 games played by 2,007 professional players and spans over 70 years. The dataset includes rich AI analysis results for each move. Moreover, PAGE provides detailed metadata for every player and game after manual cleaning and labeling. Beyond the preliminary analysis of the dataset, we provide sample tasks that benefit from our dataset to demonstrate the potential application of PAGE in multiple research directions. To the best of our knowledge, PAGE is the first dataset with extensive annotation in the game of Go. This work is an extended version of [1] where we perform a more detailed description, analysis, and application.Comment: Journal version of arXiv:2205.00254, under revie

The Value Trade-off in Higher Education Service: a Qualitative Intercultural Approach to Students

Purpose: Higher Education Institutions (HEIs) have become a highly competitive market, where consumers (i.e. students) are highly involved in their choices, and managers need to focus on competitive edges. This paper aims to understand the factors that influence international Master students' choice behaviour and fulfil student expectations of customer value in HEIs. Design/methodology: With qualitative information (five focus groups) collected from international students (of 12 different nationalities) of several universities in Spain, UK and China, the paper investigates the formation of customer value as a trade-off between benefits and costs. This qualitative approach aims first at assessing this particular service through the concept of value through verifying both the positive and negative dimensions of educational service, and second, to comment on the intercultural aspects of this dual approach to higher education consumption. Findings: The results show different levels of benefits: the functional value generally comes from infrastructures and good teachers that offer abundant practical experiences. The benefits from quality education also derived from teamwork with the colleagues who possess equal academic strength. Social benefits come from experiences outside the academic environment, -855- Intangible Capital - http://dx.doi.org/10.3926/ic.706 working with people from different cultural backgrounds who have different perspectives. Emotional rewards come from University reputation and relationships with instructors. Costs of time and effort are differently seen across programs and vary widely upon nationalities and cultural backgrounds. Practical implications: Since the competitive environments of HEIS are fast becoming more and more complex changing rapidly and dynamically, attention must be paid to International students spreading positive or negative word-of-mouth out of their experience. Different values of customers in different countries suggest that the strategy used by the corporation in a certain country, may not be apply to another. Social implications: The results of the study allow the industry to see the future prospects of the meat sector and make the necessary changes. The results lead to improved transparency and responsible behaviour. Originality/value: Within the wide trend of research on students' choice, this work has focused on International Master Students, a public with relatively limited number of studies. The contribution lays on a value-based approach as a trade-off focusing, as a step forward from the traditional sociodemographic approaches, on behavioural variables (functional, social and emotional values) and considering not just price but also non-monetary costs

Assessing the potential of LLM-assisted annotation for corpus-based pragmatics and discourse analysis:The case of apologies

Certain forms of linguistic annotation, like part of speech and semantic tagging, can be automated with high accuracy. However, manual annotation is still necessary for complex pragmatic and discursive features that lack a direct mapping to lexical forms. This manual process is time-consuming and error-prone, limiting the scalability of function-to-form approaches in corpus linguistics. To address this, our study explores the possibility of using large language models (LLMs) to automate pragma-discursive corpus annotation. We compare GPT-3.5 (the model behind the free-to-use version of ChatGPT), GPT-4 (the model underpinning the precise mode of Bing chatbot), and a human coder in annotating apology components in English based on the local grammar framework. We find that GPT-4 outperformed GPT-3.5, with accuracy approaching that of a human coder. These results suggest that LLMs can be successfully deployed to aid pragma-discursive corpus annotation, making the process more efficient, scalable and accessible

The Study of Low-Light Sights Reliability Test System in High and Low Temperature Environment

In a certain period of time Products and system complete the required function under the condition of rules, the ability is called the reliability. Reliability is an important factor to reflect the quality of products, is the focus of the weapons and equipment quality. There is no guarantee reliability, even the most advanced equipment can not also play a role. In this paper, the design of test system is mainly used for small arms LOW-LIGHT SIGHTS sight reliability test. The shimmer sight reliability tests provide light stress, electrical stress, thermal stress and other stress environment. Detection shimmer sight working conditions, on failure of the automatic screening and recording

Assessing the potential of LLM-assisted annotation for corpus-based pragmatics and discourse analysis:The case of apologies

Certain forms of linguistic annotation, like part of speech and semantic tagging, can be automated with high accuracy. However, manual annotation is still necessary for complex pragmatic and discursive features that lack a direct mapping to lexical forms. This manual process is time-consuming and error-prone, limiting the scalability of function-to-form approaches in corpus linguistics. To address this, our study explores the possibility of using large language models (LLMs) to automate pragma-discursive corpus annotation. We compare GPT-3.5 (the model behind the free-to-use version of ChatGPT), GPT-4 (the model underpinning the precise mode of Bing chatbot), and a human coder in annotating apology components in English based on the local grammar framework. We find that GPT-4 outperformed GPT-3.5, with accuracy approaching that of a human coder. These results suggest that LLMs can be successfully deployed to aid pragma-discursive corpus annotation, making the process more efficient, scalable and accessible