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The purpose of this paper is to demonstrate that the numerical method is not everything for nonlinear equations. Some properties cannot be revealed numerically; an example is used to elucidate the fact.

A variational principle is established for the generalized KdV – Burgers equation by the semi-inverse method, and the equation is solved analytically by the exp-function method, and some exact solutions are obtained, including blowup solutions and discontinuous solutions. The solution morphologies are studied by illustrations using different scales.

Solitary solution is the basic property of nonlinear wave equations. This paper finds some new properties of the KdV–Burgers equation, which have not been reported in open literature and cannot be effectively elucidated by numerical methods. When the solitary solution or the blowup solution is observed on a much small scale, their discontinuous property is first found.

The variational principle can explain the blowup and discontinuous properties of a nonlinear wave equation, and the exp-function method is a good candidate to reveal the solution properties.

Enterprise application integration (EAI) aims to integrate various enterprise applications, such as legacy systems, enterprise resource planning systems, and best‐of‐breed business applications, to aid in promoting organizational goals. EAI is a relatively new area of concern for researchers and practitioners and research on its adoption by organizations remain to be examined.

This paper extends prior research by providing a systematic examination of both generic and specific dimensions of facilitators and inhibitors for the adoption of EAI technology. A rigorous validation of these factors was established. A case study was conducted to refine the developed instrument.

The results indicate that EAI adoption is facilitated by generic as well as specific factors to this technology.

Several limitations of the study need to be mentioned at this stage. First, the research design of this study has incorporated only one site to examine and enrich the list of facilitators and inhibitors of EAI adoption. It is not known whether these results would apply to other organizations, other technologies and whether the project size has some influence on the results. More empirical work is needed to increment the developed instrument. The results of this study have three specific implications for future research. First, this study can be replicated to examine the effect of these facilitators on EAI project performance. Second, more research can be conducted to validate dimensions identified in this study. A survey may strengthen the validation process of the developed instrument and the structure of the dimensions and constructs used. Finally, the results of this study and the developed instrument can be applied on other technologies such as web services, etc.

The paper extends King and Teo's list to include EAI‐specific factors. Second, it validates the instrument through the card sorting procedure and a case study. The identified dimensions can be used in future research on EAI adoption. The results have also important managerial implications. Managers who are planning to adopt EAI technology can use the developed instrument to assess systematically the facilitators and inhibitors of this technology in their organizational context.

This study extends and accumulates on Teo's framework for inhibitors and facilitators of IT adoption in the EAI context.

The purpose of this offered research is to articulate a multifaceted kind of highly unstable initial perturbation and further analyze the performance of the plasma particles for time-fractional order evaluation.

For this purpose, the authors designed specific geometry and further interpreted it into the mathematical model using the concepts of the Vlasov Maxwell system. The suggested algorithm is based on the finite-difference and spectral estimation philosophy. The management of time and memory in generic code for computational purposes is also discussed.

The main purpose is to analyze the fractional behavior of plasma particles and also the capability of the suggested numerical algorithm. Due to initial perturbations, there are a lot of sudden variations that occurred in the formulated system. Graphical behavior shows that SR parameter produces devastation as compared to others. The variation of fractional parameter between the defend domain demonstrates the hidden pictures of plasma particles. The design scheme is efficient, convergent and has the capability to cover the better physics of the problem.

Plasma material is commonly used in different areas of science. Therefore, in this paper, the authors increase the capability of the mathematical plasma model with specific geometry, and further suitable numerical algorithm is suggested with detailed physical analysis of the outcomes. The authors gave a new direction to study the performance of plasma particles under the influence of LASER light.

In the recent era, science has produced a lot of advancements to study and analyze the physical natural process, which exist everywhere in the real word. On behalf of this current developments, it is now insufficient to study the first-order time evaluation of the plasma particles. One needs to be more precise and should move toward the bottomless state of it, that is, macroscopic and microscopic time-evaluation scales, and it is not wrong to say that there exits a huge gap, to study the time evaluation in this discussed manner. The presented study is entirely an advanced and efficient way to investigate the problem into the new directions. The capability of the proposed algorithm and model with fractional concepts can fascinate the reader to extend to the other dimensions.

As information technology advances, the prevalence of AI chatbot products is on the rise. Despite optimistic market projections, consumer skepticism towards these agents persists. This paper aims to expand the scope of the technology acceptance model by integrating the aspect of appearance. It examines the influence of different attributes of AI chatbot, such as usefulness, ease of use and appearance, individually and in combination, on consumers' intentions to share and purchase.

Using an exploratory study of Web Texts, a 2 (usefulness: high vs low) × 2 (ease of use: high vs low) mixed design and a 2 (usefulness: high vs low) × 2 (ease of use: high vs low) × 2 (anthropomorphism appearance: humanoid vs cartoon) for between-subjects designs and the price level (high vs low) for within-subjects designs. The hypotheses were tested by Octoparse and SPSS 22.0.

The research highlights the significant role of usefulness, ease of use and anthropomorphic appearance in shaping consumer attitudes towards AI chatbots, thus influencing their intentions to share information and make purchases. Grouped regression analysis reveals that lower prices exert a more pronounced positive influence on consumers' inclinations to both share and purchase, compared to higher prices. Moreover, novelty-seeking behavior moderates the effect of perceived usefulness or ease of use on attitude. Specifically, heightened novelty-seeking tendencies mitigate the impact of low perceived usefulness or ease of use, leading to sustained positive attitudes towards AI chatbots among consumers.

This study innovatively incorporates product appearance into the Technology Acceptance Model (TAM), considering both the functional attributes and appearance of AI chatbot and their impact on consumers. It offers valuable insights for marketing strategies, extends the scope of TAM application and holds significant practical implications for enhancing enterprise product planning.

随着信息技术的进步, AI聊天机器人产品的普及正在增长。尽管市场对这些代理人持乐观态度, 但消费者对这些代理人的怀疑仍然存在。本文旨在通过整合外观方面来扩展技术接受模型的范围。它考察了AI聊天机器人的不同属性（如有用性、易用性和外观）对消费者分享和购买意图的影响, 单独以及组合。

使用Web文本的探索性研究, 一个2（有用性：高vs低）× 2（易用性：高vs低）的混合设计和一个2（有用性：高vs低）× 2（易用性：高vs低）× 2（人格化外观：类人形vs卡通）用于受试者间设计和价格水平（高vs低）用于受试者内设计。通过 Octoparse 和 SPSS 22.0 测试假设。

研究突出了有用性、易用性和拟人化外观在塑造消费者对AI聊天机器人态度方面的重要作用, 从而影响了他们分享信息和购买的意图。分组回归分析显示, 相对于高价格, 低价格对消费者分享和购买的倾向产生了更为显著的正面影响。此外, 新奇寻求行为调节了感知有用性或易用性对态度的影响。具体来说, 增强的新奇寻求倾向减轻了对低感知有用性或易用性的影响, 导致消费者对AI 聊天机器人持续保持积极态度。

本研究将产品外观创新地纳入技术接受模型（TAM）中, 考虑了AI 聊天机器人的功能属性和外观以及它们对消费者的影响。它为营销策略提供了有价值的见解, 拓展了TAM的应用范围, 并对增强企业产品规划产生了重要的实际影响。

This paper aims to build a legal intelligent auxiliary discretionary system for predicting the penalty and damage compensation values. After extensively considering current the characteristics of the current Chinese legal system, a practical legal intelligent auxiliary discretionary system based on genetic algorithm-backpropagation (GA-BP) neural network (NN) is proposed herein.

An experiment is designed to analyze cases involving mental anguish compensation in medical disputes, and a Chinese legal intelligent auxiliary discretionary adviser system is built based on a GA-BP NN. Because BP neural networks perform well for nonlinear problems and GAs can improve their ability to find optimal values, and accelerate their convergence, a combined GA–BP algorithm is used. In addition, an ontology is used to reduce the semantic ambiguities and extract the implied semantic information.

We confirm that a case-based legal intelligent auxiliary discretionary adviser system based on a GA-BP NN and ontology techniques has good performance in prediction. By predicting the mental anguish compensation values, the legal intelligent auxiliary discretionary adviser system can help judges to handle cases more quickly and ordinary people to discover the suggested compensation or penalty. In contrast to BP NN or SVM, the result seems more close to the actual compensation rate.

Recently, smart court has been developed in China; the purpose of which is to build the legal advice system for improving judicial justice and reducing differences in sentencing. A practical legal advice system is an urgent requirement for the judiciary.

This paper presents a study of a case-based legal intelligent auxiliary discretionary adviser system based on a GA-BP NN and ontology techniques. The findings offer advice to optimize legal intelligent auxiliary discretionary adviser systems for mental anguish compensation in medical disputes.

A low-level controller is critical to the overall performance of multirotor unmanned aerial vehicles. The purpose of this paper is to propose a nonlinear low-level angular velocity controller for multirotor unmanned aerial vehicles in various operating conditions (e.g. different speed and different mode).

To tackle the above challenge, the authors have designed a nonlinear low-level controller taking the actuator dynamics into account. The authors first build the actuator subsystem by combining the actuator dynamics with the angular velocity dynamics model. Then, a recursive low-level controller is developed by designing a high-gain observer to estimate unmeasurable states. Furthermore, a detailed stability analysis is given with the Lyapunov theory.

Simulation tests and real-world flying experiments are provided to validate the proposed approach. In particular, we illustrate the performance of the proposed controller using violent random command test, attitude mode flight and high-speed flight of up to 18.7 m/s in real world. Compared with the classical method used in PX4 autopilot and the estimation-based incremental nonlinear dynamic inversion method, experimental results show that the proposed method can further reduce the control error.

Low-level control of multirotor UAVs is challenging due to the complex dynamic characteristics of UAVs and the diversity of tasks. Although some progress has been made, the performance of existing methods will deteriorate as operating conditions change due to the disregard for the electromechanical characteristics of the actuator.

To solve the low-level angular velocity control problem in various operating conditions of multirotor UAVs, this paper proposes a nonlinear low-level angular velocity controller which takes the actuator dynamics into account.

This study aims to explore how a buyer's perceived buyer-seller (B-S) guanxi facets (i.e. ganqing, renqing and mianzi) and guanxi positions (i.e. zi-ji-ren, shou-ren and sheng-ren) affect the seller's influence effectiveness (SIE) and purchase intention (PI) in social commerce.

This study conducted an online survey in three cities of Taiwan and collected a total of 364 data. The structural equation modeling and cluster analysis were used to test research hypotheses.

The results indicate that (1) each guanxi facet exerts a different and positive impact on SIE, but only one guanxi facet – renqing – helps improve PI, (2) guanxi facets can be used to predict the buyer's perceived guanxi position toward the seller, (3) the effect of guanxi facets on SIE and PI varies across B-S guanxi positions and (4) the SIE positively mediates effects of guanxi facets on the PI.

This study demonstrates the individual effect of each guanxi facet on SIE and PI and affirms the implicit guanxi position features guanxi facets and determines the buyer's perceived SIE and PI as well. To the best of our knowledge, these findings are rarely proposed in previous research and are beneficial for understanding the guanxi mechanism in social commerce.

To examine the nature of Chinese business negotiating style in Sino‐Western business negotiations in business‐to‐business markets involving large industrial projects from a social cultural point of view.

A conceptual approach developed from personal interviews.

This study reveals that the Chinese negotiator does not possess an absolute negotiating style but rather embraces a mixture of different roles together: “Maoist bureaucrat in learning”, “Confucian gentleman”, and “Sun Tzu‐like strategist”. The Chinese negotiating strategy is essentially a combination of cooperation and competition (termed as the “coop‐comp” negotiation strategy in this study). Trust is the ultimate indicator of Chinese negotiating propensities and role choices.

The focus of this study is on Chinese negotiating style shown in large B2B negotiations with Chinese SOEs.

Differing from most other studies on Chinese negotiating style which tend to depict the Chinese negotiator as either sincere or deceptive, this study points out that there exists an intrinsic paradox in Chinese negotiating style which reflects the Yin Yang thinking. The Chinese negotiator has a cultural capacity to negotiate both sincerely and deceptively and he/she changes coping strategies according to situation and context, all depending on the level of trust between negotiating partners.

To predict the price of battery-grade lithium carbonate accurately and provide proper guidance to investors, a method called MFTBGAM is proposed in this study. This method integrates textual and numerical information using TCN-BiGRU–Attention.

The Word2Vec model is initially employed to process the gathered textual data concerning battery-grade lithium carbonate. Subsequently, a dual-channel text-numerical extraction model, integrating TCN and BiGRU, is constructed to extract textual and numerical features separately. Following this, the attention mechanism is applied to extract fusion features from the textual and numerical data. Finally, the market price prediction results for battery-grade lithium carbonate are calculated and outputted using the fully connected layer.

Experiments in this study are carried out using datasets consisting of news and investor commentary. The findings reveal that the MFTBGAM model exhibits superior performance compared to alternative models, showing its efficacy in precisely forecasting the future market price of battery-grade lithium carbonate.

The dataset analyzed in this study spans from 2020 to 2023, and thus, the forecast results are specifically relevant to this timeframe. Altering the sample data would necessitate repetition of the experimental process, resulting in different outcomes. Furthermore, recognizing that raw data might include noise and irrelevant information, future endeavors will explore efficient data preprocessing techniques to mitigate such issues, thereby enhancing the model’s predictive capabilities in long-term forecasting tasks.

The price prediction model serves as a valuable tool for investors in the battery-grade lithium carbonate industry, facilitating informed investment decisions. By using the results of price prediction, investors can discern opportune moments for investment. Moreover, this study utilizes two distinct types of text information – news and investor comments – as independent sources of textual data input. This approach provides investors with a more precise and comprehensive understanding of market dynamics.

We propose a novel price prediction method based on TCN-BiGRU Attention for “text-numerical” information fusion. We separately use two types of textual information, news and investor comments, for prediction to enhance the model's effectiveness and generalization ability. Additionally, we utilize news datasets including both titles and content to improve the accuracy of battery-grade lithium carbonate market price predictions.

Online influencers are increasingly used by brands around the globe to establish brand communication. This study aims to investigate the characteristics of social media content in terms of presentation style and brand communication among online influencers in China. The authors identified how characteristics of social media posts influence young consumers’ engagement with the posts.

The authors analyzed 1,779 posts from the Sina Weibo accounts of ten top-ranked online influencers by combining traditional content analysis with Web data crawling of audience engagement with social media posts.

Online influencers in China more frequently used photos than videos to communicate with their social media audience. Altogether 8% and 6% of posts carried information about promotion and event, respectively. Posts with promotional incentives as well as event information were more likely to engage audiences. Altogether 22% of the sampled social media posts mentioned brands. Posts with brand information, however, were less likely to engage audiences. Furthermore, having long text is more effective than photos/images in generating likes from social media audiences.

Combining content analysis of social media posts and engagement analytics obtained via Web data crawling, this study is, to the best of the authors’ knowledge, one of the first empirical studies to analyze influencer marketing and young consumers’ reactions to social media in China.