本书分为三篇,介绍了物象美学的背景;物象美学的理论构成;物象美学的展开与实践等。.

本书收录了国内外公开发表的论文刘熙载美学思想研究22篇,其中有:《刘熙载略论》、《关于刘熙载文艺思想的探索》、《刘熙载美学思想与道家影响》等。.

In recent years, the green aviation technology draws more attention, and more hybrid power units have been applied to the aerial vehicles. To achieve the high performance and long lifetime of components during varied working conditions, the effective regulation of the energy management is necessary for the vehicles with hybrid power unit. In this paper, power prediction-based model predictive control for energy management strategy is proposed for the vehicle equipped with HPU based on turboshaft engine in order to maintain proper (...) battery’s state of charge and decrease turboshaft engine’s exhaust gas temperature. First, a modeling approach based on data-driven method is adopted to obtain the mathematical model of turboshaft engine considering time delay and inertial of states. An integrated power predictor consisting of the classification of input status and the subpredictors are developed based on the deep learning method to improve the accuracy of the prediction model of the model predictive control. Subsequently, an EMS based on MPC using the proposed power predictor is introduced to regulate the SOC of battery and the EGT of turboshaft engine. The comparison with experimental results shows the high accuracy of mathematical model of turboshaft engine. The simulation results show the effectiveness of the proposed EMS for the vehicle, and the effects of different weight coefficients of objective function on the proposed EMS are discussed. (shrink)

The power trading system has the characteristics of nonlinearity, dynamics, and complexity. Part of the business data in the trading system needs to be exposed to numerous external business systems. The traditional centralized power trading model has some problems, such as low data security and trust crisis of regulators. Blockchain technology provides prominent ideas for solving these problems. Firstly, the improved AdaBoost algorithm is used to predict the supply and demand gap of power trading nodes. Secondly, based on the fact (...) that the information on the blockchain is only open to the power supply side, a two-stage game model of asymmetric information between the power supply side and the power user is constructed to capture the price competition behavior between them in order to find the Nash equilibrium price in two stages. Finally, the US PJM market electricity market data are used to carry out an example analysis to verify the effectiveness of the algorithm and model. (shrink)

Children with autism spectrum disorder show marked difficulties in reading comprehension, a complex cognitive skill fundamental to successful daily functioning that is associated with core executive functions. However, the neurophysiological mechanisms underlying reading comprehension deficits in these children remain elusive. Twenty-one right-handed males with high-functioning ASD and 23 age-, IQ-, educational level-, sex- and handedness-matched typically developing individuals underwent a reading comprehension test and the semantic verbal fluency test that tapped core executive functions underlying reading comprehension during concurrent prefrontal functional (...) near-infrared spectroscopy measurement. Participants’ information processing efficiency was also assessed. High-functioning ASD children exhibited general reading comprehension [main effect of group: F = 7.58, p = 0.009], selective verbal fluency deficits [Group × category interaction: F = 4.90, p = 0.032] and slower processing speed. Regarding the hemodynamics of the prefrontal cortex, although ASD individuals showed comparable patterns of PFC brain activation to their healthy counterparts, lower PFC intrahemispheric [main effect of group: F = 11.36, p = 0.002] and interhemispheric [main effect of group: F = 7.79, p = 0.008] functional connectivity were evident during the semantic verbal fluency test. At the whole-group level, poorer reading comprehension performance was associated with poorer performance in the semantic verbal fluency test. Moreover, poorer semantic verbal fluency test performance was associated with slower information processing speed, which is associated with reduced left medial PFC functional connectivity. Abnormal intrahemispheric and interhemispheric prefrontal hypoconnectivity is associated with deficits in executive processes essential for reading comprehension in ASD. Our study has provided important implications for the neuropsychological and neurophysiological mechanisms underlying reading comprehension deficits in ASD. (shrink)

IntroductionDuring the COVID-19 outbreak, many citizens were asked to stay at home in self-quarantine, which can pose a significant challenge with respect to remaining physically active and maintaining mental health. This study aimed to evaluate the prevalence of inadequate physical activity, anxiety, and depression and to explore the relationship of physical activity with anxiety and depression symptoms among Chinese college students during quarantine.MethodUsing a web-based cross-sectional survey, we collected data from 1,396 Chinese college students. Anxiety and depression were assessed with (...) the Self-Rating Anxiety Scale and the Self-Rating Depression Scale, respectively. The data on physical activity were collected by types of physical activity and the International Physical Activity Questionnaire.ResultsDuring the COVID-19 outbreak, about 52.3% of Chinese college students had inadequate physical activity. The rates of anxiety and depression symptoms were 31.0 and 41.8%, respectively. A high level of physical activity was significantly closely associated with low anxiety, while a moderate, or high level of physical activity was significantly closely associated with reduced depression after adjusting confounding demographic factors. Moreover, specific types of physical activity, such as stretching and resistance training, were negatively correlated with both anxiety and depression; doing household chores was negatively correlated with depression.ConclusionOur findings highlight specific levels and types of home-based physical activities that need to be taken into consideration to protect the mental health of college students during the COVID-19 epidemic. (shrink)

This paper focuses on the problem of target tracking using k fittest robots in a group of n mobile robots with n>k. We present centralized and distributed coordination models with all-to-all and limited communications, respectively. For the case of all-to-all communication between robots, theoretical analysis is presented to prove the exponential stability of the whole system. In real applications of robotic networks, a robot may only be allowed to exchange information with a limited number of neighbors. In such a limited (...) communication case where centralized quantity is not available, a consensus filter is used to estimate the centralized quantities in a distributed way, and a distributed competitive target tracking is thus achieved. The stability of the distributed control is also proved in theory. Finally, illustrative examples are provided and analyzed to substantiate the efficacy of the proposed models for tracking moving target in a competition manner with all-to-all communications and limited communications. (shrink)

Emotional stability is of great importance for undergraduates and has significant predictive power for mental health. Emotions are associated with individuals’ daily lives and routines. Undergraduates commonly post their opinions and feelings on social networks, providing a huge amount of data for studying their emotional states and rhythms. Based on the construction of the emotion dictionary of undergraduates’ Tencent tweets —a social network for users to share their life situations and express emotions and feelings to friends—we used big data text (...) analysis technology to analyze the emotion words in 45,996 Tencent tweets published by 894 undergraduates. Then, we used hierarchical linear modeling to further analyze the daily rhythms of undergraduate students’ emotions and how demographic variables are associated with the daily rhythmic changes. The results were as follows: Undergraduates tweeted about more positive emotions than negative emotions ; The emotions in undergraduates’ tweets changed considerably from 1 a.m. to 6 a.m., but were fairly stable during the day; There was a rising trend in the frequency of using emotion words in Tencent tweets during the day as each hour progressed, and there was a higher increase in positive emotion than negative emotion; and The word frequencies and daily rhythms of emotions varied depending on demographic variables. Gender was correlated with the frequencies of gratitude and the daily rhythms of anger. As the grade increased, the frequency of emotion words in most subcategories in TTs decreased and the fluctuation in daily rhythms became smaller. There was no significant difference in the frequency and daily rhythm of emotion words used in TTs based on having had a left-behind experience. The results of the present study provided emotion expression in social networks in Chinese collectivist culture. This study added new evidence to support the notion that positive and negative emotions are independent dimensions. (shrink)

This study explores the challenge of cyber security threats that e-commerce technology and business are facing. Technology applications for e-commerce are attracting attention from both academia and industry. It has made what was not possible before for the business community and consumers. But it did not come all alone but has brought some challenges, and cyber security challenge is one of them. Cyber security concerns have many forms, but this study focuses on social engineering, denial of services, malware, and attacks (...) on personal data. Firms worldwide spend a lot on addressing cybersecurity issues, which grow each year. However, it seems complicated to overcome the challenge because the attackers continuously search for new vulnerabilities in humans, organizations, and technology. This paper is based on the conceptual analysis of social engineering, denial of services, malware, and attacks on personal data. We argue that implementing modern technology for e-commerce and cybersecurity issues is a never-ending game of cat and mouse. To reduce risks, reliable technology is needed, training of employees and consumer is necessary for using the technology, and a strong policy and regulation is needed at the firm and governmental level. (shrink)

To demonstrate how green innovation effectively occurs, this study examines the effects of green intellectual capital on GI from the perspective of green supply chain integration. Based on a natural-resource-based view and knowledge-based view, the authors constructed an intermediary model of GIC-GSCI-GI, and analyzed the effects of green absorptive ability and relationship learning ability as moderators. An empirical survey of 328 Chinese manufacturing companies was conducted. Our results indicate that three dimensions of GIC positively impact GI. The mediating effects of (...) internal and external GSCI exist in the relationship between GIC and GI. The moderating effects of GAA and RLA in these effects were also verified. Our study provides further empirical evidence for the relationship between GIC and GI, highlights the effects of companies’ internal and external abilities on GI, and suggests new ways and implementation contexts for GI. (shrink)

In the present study, we tested the effectiveness of color coding on the programming learning of students who were learning from video lectures. Effectiveness was measured using multimodal physiological measures, combining eye tracking and electroencephalography. Using a between-subjects design, 42 university students were randomly assigned to two video lecture conditions. The participants’ eye tracking and EEG signals were recorded while watching the assigned video, and their learning performance was subsequently assessed. The results showed that the color-coded design was more beneficial (...) than the grayscale design, as indicated by smaller pupil diameter, shorter fixation duration, higher EEG theta and alpha band power, lower EEG cognitive load, and better learning performance. The present findings have practical implications for designing slide-based programming learning video lectures; slides should highlight the format of the program code using color coding. (shrink)

This study uses the Planned Risk Information Seeking Model (PRISM) to estimate the public's information seeking and avoidance intentions during the COVID-19 outbreak based on an online sample of 1031 Chinese adults and provides support for the applicability of PRISM framework in the situation of a novel high-level risk. The results indicate that information seeking is primarily directed by informational subjective norms (ISN) and perceived seeking control (PSC), while the main predictors of information avoidance include ISN and attitude toward seeking. (...) Because ISN are the strongest predictor of both information seeking and avoidance, the way the public copes with COVID-19 information may be strongly affected by individuals' social environment. Furthermore, a significant relationship between risk perception and affective risk response is identified. Our results also indicate that people who perceive greater knowledge of COVID-19 are more likely to report greater knowledge insufficiency, which results in less information avoidance. (shrink)

In online communities, such as Twitter, Facebook, or Reddit, millions of pieces of contents are generated by users every day, and these user-generated contents show a great variety of topics discussed that make the online community vivid and attractive. However, the reasons why UGCs show great variety and how a firm can influence this variety was unknown, which had been an obstacle to understanding and managing UGCs’ variety. This study fills these two gaps based on variety-seeking theory and topic modeling, (...) which is a technique in machine learning. We extract, quantitatively, the topic of the UGCs using topic modeling and divide UGCs into two types: single topic and multiple topics. The user’s tendency to choose the type of UGC is used to measure variety-seeking behavior. We found that users have an intrinsic preference for variety when producing UGCs; the more single topic UGCs were produced in the past, the higher the probability of producing multiple topics UGC and the lower the probability of producing single topic UGC would be in the next, and vice versa. Furthermore, we discussed the effect of language/linguistic style matching between firm feedbacks and UGCs on users’ variety-seeking tendencies in UGCs’ production. This study makes three contributions: broadening variety-seeking theory to new behavior, that is content production behavior, and the results demonstrated that people would show a variety-seeking behavior in producing UGCs. a new feasible method to measure the variety of UGCs by using topic modeling to extract the topics of UGCs and then measure the variety-seeking behavior in producing UGCs by analyzing the choice between single topic and multiple topics. guidance for the firm to alter LSM of feedbacks to influence the variety of UGCs. (shrink)

Chengbing WangShanxi University, Taiyuan, ChinaMichael A. PetersBeijing Normal University, Beijing, ChinaContemporary Chinese Marxism is not only an important theory in the humanities and social sc...

Business Ethics: A European Review, EarlyView.

From the end of 1973 to early 1974, silk books from the Han dynasty were unearthed from tomb no. 3 at Mawangdui in Changsha, Hunan. After reorganizing and piecing them together, there were a total of twenty-eight kinds of silk books, of which four are copies of ancient books that are no longer in existence.1 They are: Jing fa, Shi liu jing, Cheng, and Dao yun, with a total of more than eleven thousand characters. These books were written before the (...) book Lao Zi. To simplify the titles, we have temporarily named these four books Huangdi shu.2 Six works of notes and interpretation have been published up until now, collating and piecing the silk book Huangdi shu. There was warm discussion in academic circles as to the name and nature of this book, when and who copied and wrote it out, the content and ideology, and which school it belongs to. Research on these questions began in the 1980s. This article focuses on a brief review of local research. I will make a special introduction about the research abroad. (shrink)

Immersive 360-degree video has become a new learning resource because of its immersive sensory experience. This study examined the effects of textual and visual cues on learning and attention in immersive 360-degree video by using eye-tracking equipment integrated in a virtual reality head-mounted display. Participants were randomly assigned to one of four conditions: no cues, textual cues in the initial field of view, textual cues outside the initial FOV, and textual cues outside the initial FOV + visual cues. The results (...) showed that the cues helped learners achieve better learning outcomes and spend more time focusing on the areas with cues. In addition, the study found a serious imbalance in the distribution of learners’ attention in each region of the video. The attention directed to textual cues in the initial FOV is much higher than the attention directed to textual cues outside the initial FOV. Adding visual cues can effectively direct attention to textual cues outside the initial FOV and alleviate the imbalance of attention distribution. Consequently, adding cues to immersive 360-degree video can be an appropriate approach to promote learning and guide attention in immersive 360-degree video learning environments. This study provided new insights into the design and development of immersive 360-degree video instructional resources. (shrink)

The interpretability of AI is just as important as its performance. In the LegalAI field, there have been efforts to enhance the interpretability of models, but a trade-off between interpretability and prediction accuracy remains inevitable. In this paper, we introduce a novel framework called LK-IB for compulsory measure prediction (CMP), one of the critical tasks in LegalAI. LK-IB leverages Legal Knowledge and combines an Interpretable model and a Black-box model to balance interpretability and prediction performance. Specifically, LK-IB involves three steps: (...) (1) inputting cases into the first module, where first-order logic (FOL) rules are used to make predictions and output them directly if possible; (2) sending cases to the second module if FOL rules are not applicable, where a case distributor categorizes them as either “simple” or “complex“; and (3) sending simple cases to an interpretable model with strong interpretability and complex cases to a black-box model with outstanding performance. Experimental results demonstrate that the LK-IB framework provides more interpretable and accurate predictions than other state-of-the-art models. Given that the majority of cases in LegalAI are simple, the idea of model combination has significant potential for practical applications. (shrink)