The notion of “agent bookkeeping” was proposed when the “Accounting Law of the People’s Republic of China” was updated in 1993. Since their business is specialized in serving small and micro-enterprises, this has created the industry characteristic of generally small in the size of company and low in the salary of employees in Chinese agent bookkeeping companies. Such characteristic results in a series of problems including negative work attitude of employees in the development process, which seriously limit the development of (...) Chinese agent bookkeeping companies. However, issues occurred in the development of agent bookkeeping, such as negative employee attitudes, which severely hampered the growth of Chinese agent bookkeeping companies. Therefore, a model of three dimensions of work attitude has been set up in this paper to demonstrate the working attitude of the staff of the agent bookkeeping companies in China’s Guangdong-Hong Kong-Macao Greater Bay Area, including emotional dimension, behavioral dimension, and cognitive dimension which consists of eight factors: work environment, career satisfaction, interpersonal relationship, role engagement, work vitality, responsibility attitude, emotional identity, and retention attitude. The result indicates that female employees outnumber male ones in agent bookkeeping companies, most employees have a low sense of belonging to the company, limited career development affects employees’ enthusiasm for work, work attitudes are influenced by mediocre work performance among employees with a graduate degree or higher. (shrink)

Post-stroke depression is a serious complication of stroke that significantly restricts rehabilitation. The use of immersive virtual reality for stroke survivors is promising. Herein, we investigated the effects of a novel immersive virtual reality training system on PSD and explored induced effective connectivity alterations in emotional networks using multivariate Granger causality analysis. Forty-four patients with PSD were equally allocated into an immersive-virtual reality group and a control group. In addition to their usual rehabilitation treatments, the participants in the immersive-virtual reality (...) group participated in an immersive-virtual reality rehabilitation program, while the patients in the control group received 2D virtual reality rehabilitation training. The Hamilton Depression Rating Scale, modified Barthel Index, and resting-state functional magnetic resonance imaging data were collected before and after a 4-week intervention. rsfMRI data were analyzed using multivariate GCA. We found that the immersive virtual reality training was more effective in improving depression in patients with PSD but had no statistically significant improvement in MBI scores compared to the control group. The GCA showed that the following causal connectivities were strengthened after immersive virtual reality training: from the amygdala, insula, middle temporal gyrus, and caudate nucleus to the dorsolateral prefrontal cortex; from the insula to the medial prefrontal cortex; and from the thalamus to the posterior superior temporal sulcus. These causal connectivities were weakened after treatment in the control group. Our results indicated the neurotherapeutic use of immersive virtual reality rehabilitation as an effective non-pharmacological intervention for PSD; the alteration of causal connectivity in emotional networks might constitute the neural mechanisms underlying immersive-virtual reality rehabilitation in PSD. (shrink)

An integrated hog futures price forecasting model based on whale optimization algorithm, LightGBM, and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise is proposed to overcome the limitations of a single machine learning model with low prediction accuracy and insufficient model stability. The simulation process begins with a grey correlation analysis of the hog futures price index system in order to identify influencing factors; after that, the WOA-LightGBM model is developed, and the WOA algorithm is used to optimize the LightGBM (...) model parameters; and, finally, the residual sequence is decomposed and corrected by using the CEEMDAN method to build a combined WOA-LightGBM-CEEMDAN model. Furthermore, it is used for comparison experiments to check the validity of the model by using data from CSI 300 stock index futures. Based on all experimental results, the proposed combined model shows the highest prediction accuracy, surpassing the comparative model. The model proposed in this study is accurate enough to meet the forecasting accuracy requirements and provides an effective method for forecasting future prices. (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...

This study employs quantitative and qualitative methodologies mainly to examine how UNFCCC Executive Secretaries use concessive but-constructions and linguistic polyphony to implicitly argue points of view and convey stance in speeches on climate change. Our findings indicate that, in order to achieve its goals for global climate governance while adhering to humanitarian and diplomatic principles, UNFCCC speeches delivered to the Parties to the Convention and the Stakeholders emphasize the urgent need for concerted action on climate change while implicitly expressing discontent (...) and mild criticism of various Parties and Stakeholders for failing to do their fair share in support of such action. This style of discourse aims to promote group unity, solidarity, and transparency while minimizing the possibility of offending any Parties or Stakeholders. Nevertheless, given the urgency of addressing climate change challenges, we advise that UNFCCC speakers utilize more explicit linguistic methods that exert more direct pressure on specific Parties or Stakeholders who fail to assume their share of responsibility. In addition, we suggest that the UNFCCC focus on enabling the implementation of practical actions to limit the effects of global warming, while continuing to urge affluent countries to provide developing countries with much-needed financial and technological help. (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)

Although previous studies have recognized the important role of patients' trust in promoting their intention to use health information technologies, most of those studies were under the “risk-benefit” theoretical framework. To deepen the understanding of patients' online consultation decisions, this paper develops a dual-path model investigating how patients develop trust beliefs toward online physicians from the perspective of communication. Drawing on media naturalness theory, we propose that HIT media naturalness will improve patients' perception of communication effort from online physicians and (...) decrease communication ambiguity between patients and online physicians. This improved communication will further strengthen patients' trust in online physicians and promote their intention to use HIT. Based on a two-wave time-lagged survey from 361 participants, the empirical results demonstrated that the relationship between HIT media naturalness and patients' intention to use HIT is individually and serially mediated by two chains, including perceived communication effort and patients' trust and perceived communication ambiguity and patients' trust. We thus contribute to the related literature and provide practical implications. (shrink)

The innovation of the deep learning modeling scheme plays an important role in promoting the research of complex problems handled with artificial intelligence in smart cities and the development of the next generation of information technology. With the widespread use of smart interactive devices and systems, the exponential growth of data volume and the complex modeling requirements increase the difficulty of deep learning modeling, and the classical centralized deep learning modeling scheme has encountered bottlenecks in the improvement of model performance (...) and the diversification of smart application scenarios. The parallel processing system in deep learning links the virtual information space with the physical world, although the distributed deep learning research has become a crucial concern with its unique advantages in training efficiency, and improving the availability of trained models and preventing privacy disclosure are still the main challenges faced by related research. To address these above issues in distributed deep learning, this research developed a clonal selective optimization system based on the federated learning framework for the model training process involving large-scale data. This system adopts the heuristic clonal selective strategy in local model optimization and optimizes the effect of federated training. First of all, this process enhances the adaptability and robustness of the federated learning scheme and improves the modeling performance and training efficiency. Furthermore, this research attempts to improve the privacy security defense capability of the federated learning scheme for big data through differential privacy preprocessing. The simulation results show that the proposed clonal selection optimization system based on federated learning has significant optimization ability on model basic performance, stability, and privacy. (shrink)

苏珊·朗格是西方美学史上迄今为止惟一的一位声名显赫的女性美学家。本书勾勒了朗格的生平,揭示了朗格哲学美学思想演化的内在脉络,阐述了她的符号论思想、生命形式、逻辑类似、艺术幻象等理论。.

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 article compares the use of Romantic metaphor with the Chinese literary device xiang 象 (which I translate as “thing-metaphor”) in regard to how they embody different metaphysical relations between humans and things. Whereas Romantic metaphor transports a physical thing to the immaterial realm of imagination, xiang is a literary device in which the material qualities of the thing, while creatively interpreted to generate human meaning, retain ontologically a strong physical presence. Xiang therefore epitomizes a theory of (...) creation that challenges the Western dualistic paradigm: that the poet creates not virtual copies of the thing, but meanings of the thing, and therefore our relationships with things. The article concludes with Heidegger’s discourses on metaphor to suggest that my discussion of thing-metaphor has universal applicability. (shrink)

本書為作者所著《純粹力動現象學》的續篇，主要是補充正篇所未及充分闡發的義理，特別是純粹力動作為終極原理的宇宙論方面的開拓問題。宇宙論是處理現象界的事物的生成與變化的哲學。 人生在這個現象世界中，一舉一動莫不與周圍環境的事物發生關係；人一出生，便是以雙足踏著大地生活的。要生活得好，能運用周圍的資源，提高生活的質素，便得對它們有既廣且深的理解，故宇宙論是不能忽視的。在這個問 題上，作者透過純粹力動的凝聚、蘊聚、詐現等宇宙論概念來說，發前人所未發。 另外，本書又有兩篇具分量的有關京都學派哲學的文字。筆者的純粹力動現象學的建構，頗受到京都學派的啟發。但後者以絕對無來說宇宙與人生的終極原理，動感顯然淡薄，甚至流於薄弱。該兩篇文字主要處理這個問題，透過 對純粹力動與絕對無這兩個關鍵性觀念的廣泛的、深入的比較，展示出純粹力動作為終極原理、真理較絕對無更為殊勝之處，更具足動感，並提出絕對無的力動轉向觀點。 這是對京都學派的多面的理解與嚴刻的批判，在國際哲學研究界中亦為首次，因而具有特殊的意義。附錄中有三篇英語作品，是提供予不看中文的學者、朋友參考的，俾能略知純粹力動現象學的扼要內容。.

本书以多元的视角讨论前沿文艺作品,从关注,对话,名家,锐评,艺海等多个板块共18篇文章展开对当代艺术的讨论,收录了浙江戏剧一度创作中存在的问题,深刻的真实,传统戏曲与现代多媒体技术等文章.

di 1 juan. Qian shen shou--shen shou shi dai -- di 2 juan. She ji shou shi dai -- di 3 juan. Zhu zi shi dai.