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This purpose of this paper is to present a new approach of solving quantum control problem.

State‐transition‐matrix (STM) is used to solute quantum control problem.

The paper obtains the matrix representation for wave function, normalization, and some other quantum operators, and then gives the possible methods to establish the STM model and solve it.

Based on this, many tools of the widely used control theory can be adopted to denote or analyze the quantum system.

Deadlock is a rather undesirable phenomenon and must be well solved in flexible manufacturing systems (FMS). This paper aims to propose a general iterative deadlock control method for a class of generalized Petri nets (GPN), namely, G-systems, which can model an FMS with assembly and disassembly operations of multiple resource acquisition. When given an uncontrolled G-system prone to deadlocks, the work focuses on the synthesis of a near-optimal, non-blocking supervisor based on reachability graph (RG) analysis.

The concept of a global idle place (GIP) for an original uncontrolled G-system is presented. To simplify the RG computation of an uncontrolled G-system, a GIP is added temporarily to the net model during monitor computation steps. Starting with one token and then by gradually increasing the number of tokens in the GIP at each iteration step, the related net system is obtained. The minimal-covered-set of all bad markings of the related net system suffering from deadlock can be identified and then removed by additional monitors through an established place-invariant control method. Consequently, all related systems are live, and the GIP is finally removed when the non-blockingness of the controlled system is achieved. Meanwhile, the redundancy of monitors is also checked.

A typical G-system example is provided to demonstrate the applicability and effectiveness of the proposed method. Experiments show that the proposed method is easy to use and provides very high behavioral permissiveness for G-system. Generally, it can achieve an optimal or a near-optimal solution of the non-blocking supervisor.

In this work, the concept of GIP for G-systems is presented for synthesis non-blocking supervisors based on RG analysis. By using GIP, an effective deadlock control method is proposed. Generally, the proposed method can achieve an optimal or a near-optimal, non-blocking supervisor for an uncontrolled G-system prone to deadlocks.

Social media, especially microblog, has become one of the most popular platforms for public opinion dissemination. However, so far few studies have been conducted to explore information dissemination under the mobile environment. This paper aims to introduce the approach to analyze the public opinion information dissemination in mobile social networks.

This paper chooses “network attack” as the research topic and extracts 23,567 relevant messages from Sina Microblogs to study the structure of nodes for public opinion dissemination and the characteristics of propagation paths on mobile internet. Public opinion dissemination is compared on both mobile and non-mobile terminals.

The results reveal the characteristics of public opinion dissemination in mobile environment and identify three patterns of information propagation path. This study concludes that public opinion on mobile internet propagates more widely and efficiently and generates more impact than that on the non-mobile internet.

The methods used in this study can be useful for the government and other organizations to analyze and identify problems in online information dissemination.

This paper explores the mechanism of public opinion dissemination on mobile internet in China and further investigates how to improve public opinion management through a case study related to “network attack.”

COVID-19, a causative agent of the potentially fatal disease, has raised great global public health concern. Information spreading on the COVID-19 outbreak can strongly influence people behaviour in social media. This paper aims to question of information spreading on COVID-19 outbreak are addressed with a massive data analysis on Twitter from a multidimensional perspective.

The evolutionary trend of user interaction and the network structure is analysed by social network analysis. A differential assessment on the topics evolving is provided by the method of text clustering. Visualization is further used to show different characteristics of user interaction networks and public opinion in different periods.

Information spreading in social media emerges from different characteristics during various periods. User interaction demonstrates multidimensional cross relations. The results interpret how people express their thoughts and detect topics people are most discussing in social media.

This study is mainly limited by the size of the data sets and the unicity of the social media. It is challenging to expand the data sets and choose multiple social media to cross-validate the findings of this study.

This paper aims to find the evolutionary trend of information spreading on the COVID-19 outbreak in social media, including user interaction and topical issues. The findings are of great importance to help government and related regulatory units to manage the dissemination of information on emergencies, in terms of early detection and prevention.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

The purpose of this paper is to introduce an augmented high-order capital asset pricing model (AH-CAPM) as a new risk-based model to price stocks.

The AH-CAPM is defined as a linear model with high-order marginal moments and co-moments from the joint distributions of the sorted stock portfolio returns and the market return.

The performance of the AH-CAPM is tested in the Chinese and US stock markets. Empirical results show that the high-order marginal moments and co-moments from the joint distributions in AH-CAPM contain the risk and return information implied by the Fama–French factors, indicating it as a better risk measurement. Moreover, the AH-CAPM performs better than the Fama–French three-factor model and the Carhart four-factor model in both the Chinese and US stock markets.

Overall, this study introduces a new asset pricing model with better measurements to incorporate risk information in the stock market.

This paper aims to show a series of hydrogels with adjustable mechanical properties, which can be cured quickly with visible light. The hydrogel is prepared conveniently with hydroxyethyl acrylate, cross-linker, gelatin and photoinitiator, and can be printed into certain 3D patterns with the direct ink write (DIW) 3D printer designed and developed by the research group.

In this paper, the authors designed a composite sensitization initiation system that is suitable for hydrogels. The concentration of photoinitiator, gelatin and cross-linker was studied to optimize the curing efficiency and adjust the mechanical properties. A DIW 3D printer was designed for the printing of hydrogel. Pre-gel solution was loaded into printer for printing into established models. The models were made and sliced with software.

The hydrogels can be cured efficiently with 405-nm visible light. While adding various content of gelatin and cross-linker, the mechanical properties of hydrogels show from soft and fragile (elastic modulus of 121.18 kPa and work of tension of 218.11 kJ·m⁻³) to rigid and tough (elastic modulus of 505.15 kPa and work of tension of 969.00 kJ·m⁻³). The hydrogels have high capacity of water absorption. With the DIW 3D printer, pre-gel hydrogel solution can be printed into objects with certain dimension.

In this work, a composite sensitization initiation system was designed, and fast curing hydrogels with adjustable mechanical properties had been prepared conveniently, which has high equilibrium water content and 3D printability with the DIW 3D printer.

This paper aims to reveal the factors patients consider when choosing a doctor for consultation on an online medical consultation (OMC) platform and how these factors influence doctors' consultation volumes.

In Study 1, influencing factors reflected as service features were identified by applying a feature extraction method to physician reviews, and the importance of each feature was determined based on word frequencies and the PageRank algorithm. Sentiment analysis was used to analyze patient satisfaction with each service feature. In Study 2, regression models were used to analyze the relationships between the service features obtained from Study 1 and the doctor's consultation volume.

The study identified 14 service features of patients' concerns and found that patients mostly care about features such as trust, phraseology, overall service experience, word of mouth and personality traits, all of which describe a doctor's soft skills. These service features affect patients' trust in doctors, which, in turn, affects doctors' consultation volumes.

This research is important as it informs doctors about the features they should improve, to increase their consultation volume on OMC platforms. Furthermore, it not only enriches current trust-related research in the field of OMC, which has a certain reference significance for subsequent research on establishing trust in online doctor–patient relationships, but it also provides a reference for research concerning the antecedents of trust in general.

The purpose of this paper is to examine the production of smart tourism knowledge, thereby revealing the development of the concept through collaborative networks.

A bibliometric analysis, which enables visual mapping and observation of the domain, was conducted using journal articles retrieved during the period of 2000 to 2018.

The understanding of smart tourism is shaped and enhanced through collaborative network of researchers. As the domain develops, its reach expands across different networks as well as core themes.

Data for the study was generated from English-written journal articles that were produced from a database search of specific keywords associated with smart tourism.

Findings can prove useful to academic researchers and industry practitioners to aid their understanding of smart tourism research development, identify the underlying context and aid in coherent development of the concept.

The paper is one of the first articles to provide a greater understanding of smart tourism as a research topic by examining its evolution in an academic context through bibliometric analysis.

本论文对智慧旅游相关知识进行审阅, 并通过协作网络对其概念发展进行梳理。

本论文采用Gephi文献计量分析方法, 对其相关领域的发展进行视觉化处理, 构建出发展图。研究样本为2000年至2018年发表的期刊文章, 通过在线搜索数据库获得。

通过研究者之间的协作网络, 本论文研究结果对智慧旅游的认识清晰形成并且更加深刻。自智慧旅游领域发展以来, 其发展扩展到不同网络以及多个核心主题。

研究样本只局限于数据库中的英文期刊文章, 以及采用有限的智慧旅游的关键词搜索。

研究结果对学术学者和业界人士有着深刻效用, 以帮助他们对智慧旅游研究发展构筑清晰理解, 找到其研究背景以及概念发展的核心过程。