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This paper sets out to solve a common and crucial fundamental theoretical problem of gray incidence cluster analysis: to [X]={X|ρ(X,Y)≥1−ε0} constitute an approximate classification, it must first be proven that [X]={X|ρ(X,Y)=1} constitutes a rigorous classification.

This paper does not study the concrete expressions of various incidence degrees but rather the perfect correlation essence of such incidence degrees, that is, sufficient and necessary conditions.

For any order difference incidence degree, the similarity incidence degree, the direct proportion incidence degree, the parallel incidence degree and the nearness incidence degree, it is proven that the perfect correlation relation is an equivalence relation. The set composed of all sequences Y that are equivalent to sequences X is studied, that is, the equivalence class of X. The structure and mutual relations of these equivalence classes are discussed, and the topological homeomorphism concept of incidence degree is introduced. The conclusion is obtained that the equivalence classes of the two incidence degrees must be the same when the topological homeomorphism is obtained.

In this paper, only the perfect correlation relation of any order difference incidence degree, the similarity incidence degree, the direct proportion incidence degree, the parallel incidence degree and the nearness incidence degree are studied as equivalent relations.

Not only are the research results of several incidence degrees involved in this paper original but also many other effective incidence degrees have not done this basic research, so this paper opens up a research direction with theoretical significance.

The purpose of this study is investigate the transient aerodynamic characteristics of high-speed vehicle with body roll motion under crosswind condition to improve aerodynamic stability.

An overset mesh was used to simulate the rolling motion of the vehicle body. A wind tunnel experiment was conducted to validate the numerical method.

The results revealed that the vehicle’s aerodynamic characteristics changed periodically with the body’s periodic motion. In the absence of crosswind, the pressure distribution on the left and right sides of the vehicle body was symmetrical, and the speed streamline flowed to the rear of the vehicle in an orderly manner. The maximum aerodynamic lift observed in the transient simulation was −0.089, which is approximately 0.70 times that of the quasi-static simulation experiment. In addition, the maximum aerodynamic side force observed in the transient simulation was 0.654, which is approximately 1.25 times that of the quasi-static simulation experiment.

The aerodynamic load varies periodically with the vehicle body’s cyclic motion. However, the extreme values of the aerodynamic load do not occur when the vehicle body is at its highest or lowest position. This phenomenon is primarily attributed to the mutual interference of airflow viscosity and the hysteresis effect in the flow field, leading to the formation of a substantial vortex near the wheel. Consequently, the aerodynamic coefficient at each horizontal position becomes inconsistent during the periodic rolling of the vehicle body.

Mental health is not simply the absence of psychological problems any more than physical health is the absence of disease. This chapter explores various aspects of optimal mental health and wellbeing among college students. It examines the question of what is required for college students to both feel their best and function at or near their highest levels. It also discusses the characteristics of peak mental health, including its transient nature. Predictive factors such as exercise, diet, sleep and social connection will be explored. Regarding the features of optimal wellbeing, the following variables are described: integrity, values, mindfulness, self-compassion, flow and resilience. These variables are considered in an integrated fashion as components, as well as byproducts, of wellness. Hettler’s multidimensional model of wellness is presented at the outset of the chapter, followed by Keyes’ theory of flourishing.

The purpose of this paper is to use the corresponding magnetic sensor and detection method to detect and image the defects of small diameter pipelines. Urban gas pipeline is an energy transportation tool for urban industrial production and social life, which is closely related to urban safety. Preventing the occurrence of urban gas pipeline transportation accidents and carrying out pipeline defect detection are of great significance for the urban economic and social stability. To perform pipeline defect detection, the magnetic flux leakage internal detection method is generally used in the detection of large-diameter long-distance oil and gas pipelines. However, in terms of the internal detection of small-diameter pipelines, due to the heavy weight, large structure of the detection device and small pipe diameter, the detection is more difficult.

In order to solve the above matters, self-made three-dimensional magnetic sensor and three-dimensional magnetic flux leakage imaging direct method are proposed for studying the defect identification. Firstly, for adapting to the diameter range of small-diameter pipelines, and containing the complete information of the defect, a self-made three-dimensional magnetic sensor is made in this paper to improve the accuracy of magnetic flux leakage detection. And on the basis of it, a small diameter pipeline defect detection system is built. Secondly, as detection signal may be affected by background magnetic field interference and the jitter interference, the complete ensemble empirical mode decomposition with adaptive noise method is utilized to screen the detected signal. As a result, the useful signal is reconstructed and the interference signal is removed. Finally, the defect contour inversion imaging of detection is realized based on the direct method of three-dimensional magnetic flux leakage imaging, which includes three-dimensional magnetic flux leakage detection data and data segmentation recognition.

The three-dimensional magnetic flux leakage imaging experimental results shown that, compared to the actual defects, the typical defects, irregular defects and crack groove defects can be analyzed by the magnetic flux leakage defect contour imaging method in qualitative and quantitative way respectively, which provides a new idea for the research of defect recognition.

A three-dimensional magnetic sensor is made to adapt the diameter range of small diameter pipeline, and based on it, a small-diameter pipeline defect detection system is built to collect and display the magnetic flux leakage signal.

The purpose of this study is to investigate the effects of different bullet screen types (functional vs social) on the continuous watching intention of consumers, as well as the influence mechanism. In addition, this study analyses the moderating role of consumer motivational orientation on the above effects.

First, objective data were obtained through the crawler to test the proposed hypotheses. An objective data analysis (417 group sample) was conducted to analyse the relationship between the percentage of social bullet screens and consumers sustained growth ratio to indirectly test the primary effect. Second, a questionnaire survey was conducted to test (176 questionnaires) the mediating role of perceived social crowding. Finally, a simulated online contextual experiment (340 participants) is conducted to explore the moderating role of consumer motivational orientation.

First, functional bullet screens produce higher continuous watching intention and lower perceived social crowding than social bullet screens. Second, perceived social crowding mediates the relationship between bullet screen type and continuous watching intention. Third, consumers' motivational orientation type (task-motivated vs recreation-motivated) moderates the relationship among bullet screen type, perceived social crowding and continuous watching intention.

The results of this study shed light on the differential impact of different types of bullet screens (functional and social) on consumers' continuous watching intentions, which makes up for the lack of research on the content of bullet screens in the field of livestreaming. Meanwhile, compared with the previous positive psychological research perspective, this study explores the intermediate mechanism of bullet screen type on consumers' continuous watching intention through a negative psychological perspective, which helps e-commerce companies and streamers better understand the differential impact of different bullet screens. Finally, this study explores the joint influence effect of bullet screen and consumer motivation type, which fills the theoretical research gap of consumer motivation orientation type in the category of live-streaming.

This study identified how investor sentiment on Twitter is associated with Brazilian stock market return and trading volume.

The study analyzes 314,864 tweets between January 1, 2017, to December 31, 2018, collected with the Tweepy library. The companies’ financial data were obtained from Refinitiv Eikon. Using the netnographic method, a Twitter Investor Sentiment Index (ISI) was constructed based on terms associated with the stocks. This Twitter sentiment was attributed through machine learning using the Google Cloud Natural Language API. The associations between Twitter sentiment and market performance were performed using quantile regressions and vector auto-regression (VAR) models, because the variables of interest are heterogeneous and non-normal, even as relationships can be dynamic.

In the contemporary period, the ISI is positively correlated with stock market returns, but negatively correlated with trading volume. The autoregressive analysis did not confirm the expectation of a dynamic relationship between sentiment and market variables. The quantile analysis showed that the ISI explains the stock market return, however, only at times of lower returns. It is possible to state that this effect is due to the informational content of the tweets (sentiment), and not to the volume of tweets.

The study presents unprecedented evidence for the Brazilian market that investor sentiment can be identified on Twitter, and that this sentiment can be useful for the formation of an investment strategy, especially in times of lower returns. These findings are original and relevant to market agents, such as investors, managers and regulators, as they can be used to obtain abnormal returns.

Users' knowledge contribution behaviors are critical for online Q&A communities to thrive. Well-organized question threads in online Q&A communities enable users to clearly read existing answers and their evaluations before contributing. Based on the social comparison and peer influence literature, the authors examine peer influence on the informativeness of knowledge contributions in competitive settings. The authors also consider three levels of moderating factors concerning individuals' perception of competitiveness: question level, thread level and contributor level.

The authors collected data from one of the largest online Q&A communities in China. The hypotheses were validated using hierarchical linear models with cross-classified random effects. The generalized propensity score weighting method was employed for the robustness check.

The authors demonstrate the peer influence due to social comparison concerns among knowledge contribution behaviors in the same question thread. If more prior knowledge contributors choose to contribute long answers in the question thread, the subsequent contributions are more informative. This peer influence is stronger for factual questions and questions with higher popularity of answering but weaker in recommendation-type and well-answered questions and for contributors with higher social status.

This research provides a new cue of peer influence on online UGC contributions in competitive settings initiated by social comparison concerns. Additionally, the authors identify three levels of moderating factors (question level, thread level and contributor level) that are specific to online Q&A settings and are related to a contributor's perception of competitiveness, which affect the direct effect of peer influence on knowledge contributions. Rather than focus on motivation and quality evaluation, the authors concentrate on the specific content of online knowledge contributions. Peer influence here is not based on an actual acquaintance or a following relationship but on answering the same question. The authors also illustrate the competitive peer influence in subjective and personalized behaviors in online UGC communities.

This study identifies a methodology to explore the issues of enterprise innovation ecosystem health (EIEH).

First, this study constructs the indicator system of EIEH based on the research objective; second, the dynamic vertical projection method (DVPM) and entropy weight method are proposed to analyze the status and influencing factors of EIEH; finally, the future development of EIEH is analyzed using GM (1,1).

In terms of methodology, the DVPM can effectively analyze EIEH, which can not only analyze the development status and potential of EIEH every year but also analyze the comprehensive state of EIEH for many years. In terms of practice, the value and grade of EIEH in China have been gradually increasing from 2016 to 2020, but the overall development is unbalanced, and five key factors affecting EIEH have been identified. The EIEH in China is predicted to steadily grow from 2021 to 2025.

The analytical method employed in this study can effectively analyze EIEH, which provides a new analytical perspective for the evaluation of EIEH and enriches the research content of the enterprise innovation ecosystem (EIE). By analyzing the results, we can gain a comprehensive understanding of the state of different EIEs, enabling each EIE to design tailored remedial measures to enhance EIEH and achieve sustainable development.

This study provides a comprehensive overview of the research landscape of Kansei engineering (KE) within the domain of emotional clothing design. It explores the pivotal technologies, challenges and potential future directions of KE, offering application methodologies and theoretical underpinnings to support emotional clothing design.

This study briefly introduces KE, outlining its overarching research methodologies and processes. This framework lays the groundwork for advancing research in clothing Kansei. Subsequently, by reviewing literature from both domestic and international sources, this research initially explores the application of KE in the design and evaluation of clothing products as well as the development of intelligent clothing design systems from the vantage point of designers. Second, it investigates the role of KE in the customization of online clothing recommendation systems and the optimization of retail environments, as perceived by consumers. Finally, with the research methodologies of KE as a focal point, this paper discusses the principal challenges and opportunities currently confronting the field of clothing Kansei research.

At present, studies in the domain of clothing KE have achieved partial progress, but there are still some challenges to be solved in the concept, technical methods and area of application. In the future, multimodal and multisensory user Kansei acquisition, multidimensional product deconstruction, artificial intelligence (AI) enabling KE research and clothing sales environment Kansei design will become new development trends.

This study provides significant directions and concepts in the technology, methods and application types of KE, which is helpful to better apply KE to emotional clothing design.

This paper aims to investigate the effects on coatings performance in the epoxy silicone resin system owing to the existence of the different chain length of open-chain epoxy monomer. In this paper, [4-Methylphenyl-(4–(2-methylpropyl) phenyl)]iodonium as photoinitiator was added into epoxy silicone resin by ultraviolet (UV)-cured polymerization to investigate the effects on coatings performance owing to the existence of the different chain length of open-chain epoxy monomer.

A simple hydrosilylation reaction was used to synthesize epoxy-based silicone prepolymers by using hydrogen-terminated polydimethylsiloxane, 1,2-epoxy-5-hexene, 1,2-epoxy-7-octene and 1,2-epoxy-9-decene as precursors.

The results revealed that the glass transition temperatures (Tg) and hydrophobicity increased with the chain length of open-chain epoxy monomer in the UV curable epoxy-based silicone coatings, and these films had excellent heat resistance, hydrophobicity, antigraffiti and ink removal properties.

The cationic photocuring systems are not susceptible to the effect of oxygen inhibition. However, the limitation of cationic light curing process is that it requires a long curing time.

The coatings prepared via the UV curing approach can provide superior antismudge effects, and thus they are promising candidates for use in various industries, especially in fields such as antismudge coatings and antigraffiti coatings.