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Land policy plays an important role in urban development planning. The value of land use depends on the nature and scale of urban land use. Based on this, in the study and analysis, the adaptation between regional land finance and urban planning and construction was discussed. First of all, the current incoordination between the land policy and the urban planning and construction in the development of urbanization was elaborated, and the status quo of the research was analyzed; then, the coordination of the layout of the urban planning space under the land finance was analyzed; taking a small-town project as an example, the actual planning of towns was concretely analyzed, and the waterfront landscape was planned and designed, the functional utilization of the land was promoted. Regression analysis of adaptation confirmed the success of urban planning and construction.

People’s economic behaviors are often embedded in their social networks. Based on social embeddedness theory, this study investigates how customers’ social network embeddedness (structural and relational embeddedness) affects their online referral intentions through four studies.

This study adopted a vignette experimental design and used both offline and online channels to collect data. The respondents were undergraduate students and consumers, covering different age groups and occupation types. We used the ANOVA and bootstrap methods of SPSS to conduct data processing and hypothesis testing.

We found that when fewer (vs more) people in a customer’s social network participated in reward referral programs (RRPs), the customer’s online referral intention was also lower because of higher perceived social costs and lower perceived control. However, when the tie strength, reciprocity and normative influence between customers and people who have participated in RRPs were high, customers’ online referral intention also increased, ignoring the influence of participants’ network size. In these relationships, perceived social costs and perceived control played important mediating roles.

The results provide practical implications for enterprises to develop efficient RRPs in the context of the increasing popularity of the mobile Internet and intelligent terminals.

This study offers insights into the influence mechanism of social network embeddedness on referral likelihood, contributing to the field of RRPs and social embeddedness theory.

The rapid development of generative artificial intelligence has witnessed its widespread integration across various industries, contributing to enhanced productivity. However, a comprehensive exploration of the underlying factors influencing the behavior of graphic designers in employing such tools remains incomplete. This research aims to amalgamate the IDT theory with the UTAUT2 model to construct a structural model, delving into the factors affecting graphic designers’ behavior in using GenAI tools.

A survey was conducted with 394 respondents, and the results were analyzed using PLS-SEM.

The findings reveal that most factors proposed in both the UTAUT2 and IDT theories exert positive influences. Notably, the study highlights that AI anxiety significantly influences designers’ usage behavior.

This research provides a theoretical foundation and practical guidance for both graphic designers and AI developers.

The problem of port and starboard ambiguity will exist when only utilize the vector or scalar parameters. Meanwhile, the amplitude-phase error between the vector and scalar can also cause this problem. In this paper, a compound MEMS vector hydrophone which contains cilia vector microstructure and piezoelectric ceramic tube has been presented to solve the problem. Compared with traditional MEMS vector hydrophone, the compound MEMS vector hydrophone can realize the measurement of sound pressure and vibration velocity simultaneously.

A compound MEMS vector hydrophone has been presented. The unipolar directivity of the combined signal which combine the acoustic pressure and vibration velocity is used to achieve the direction of arrival (DOA). This paper introduced the working principle and the target detection mechanism of the compound vector hydrophone. The amplitude and phase error are analyzed and corrected in the standing wave tube. After that, the authors use beam-forming algorithm to estimate the DOA.

The experimental results in the standing wave tube and the external field verified the vector hydrophone's directional accuracy up to 1 and 5 degrees, respectively.

The research of compound vector hydrophone plays an important role in marine acoustic exploration and engineering applications.

This research provides a basis for MEMS hydrophone directivity theory. The compound vector hydrophone has been applied in the underwater location, with a huge market potential in underwater detection systems.

Using science mapping analysis approach and co-word analysis, the present study explores and visualizes research fields and thematic evolution of the coronavirus. Based on this method, one can get a picture of the real content of the themes in the mentioned thematic area and identify the main minor and emerging themes.

This study was conducted based on co-word science mapping analysis under a longitudinal study (from 1988 to 2020). The collection of documents in this study was further divided into three subperiods: 1988–1998, 1999–2009 and 2010–2020. In order to perform science mapping analysis based on co-word bibliographic networks, SciMAT was utilized as a bibliometric tool. Moreover, WoS, PubMed and Scopus bibliographic databases were used to download all records.

In this study, strategic diagrams were demonstrated for the coronavirus research for a chronological period to assess the most relevant themes. Each diagram depended on the sum of documents linked to each research topic. In the first period (1988–1998), the most centralizations were on virology and evaluation of coronavirus structure and its structural and nonstructural proteins. In the second period (1999–2009), with due attention to high population density in eastern Asia and the increasing number of people affected with the new generation of coronavirus (named severe acute respiratory syndrome virus or SARS virus), publications have been concentrated on “antiviral activity.” In the third period (2010–2020), there was a tendency to investigate clinical syndromes, and most of the publications and citations were about hot topics like “severe acute respiratory syndrome,” “coronavirus” and “respiratory tract disease.” Scientometric analysis of the field of coronavirus can be regarded as a roadmap for future research and policymaking in this important area.

The originality of this research can be considered in two ways. First, the strategic diagrams of coronavirus are drawn in four thematic areas including motor cluster, basic and transversal cluster, highly developed cluster and emerging and declining cluster. Second, COVID-19 is mentioned as a hot topic of research.

When the mobile manipulator is traveling on an unconstructed terrain, the external disturbance is generated. The load on the end of the mobile manipulator will be affected strictly by the disturbance. The purpose of this paper is to reject the disturbance and keep the end effector in a stable pose all the time, a control method is proposed for the onboard manipulator.

In this paper, the kinematics and dynamics models of the end pose stability control system for the tracked robot are built. Through the guidance of this model information, the control framework based on active disturbance rejection control (ADRC) is designed, which keeps the attitude of the end of the manipulator stable in the pitch, roll and yaw direction. Meanwhile, the control algorithm is operated with cloud computing because the research object, the rescue robot, aims to be lightweight and execute work with remote manipulation.

The challenging simulation experiments demonstrate that the methodology can achieve valid stability control performance in the challenging terrain road in terms of robustness and real-time.

This research facilitates the stable posture control of the end-effector of the mobile manipulator and maintains it in a suitable stable operating environment. The entire system can normally work even in dynamic disturbance scenarios and uncertain nonlinear modeling. Furthermore, an example is given to guide the parameter tuning of ADRC by using model information and estimate the unknown internal modeling uncertainty, which is difficult to be modeled or identified.

The cardiomegaly can be determined by the cardiothoracic ratio (CTR) which can be measured in a chest x-ray image. It is calculated based on a relationship between a size of heart and a transverse dimension of chest. The cardiomegaly is identified when the ratio is larger than a cut-off threshold. This paper aims to propose a solution to calculate the ratio for classifying the cardiomegaly in chest x-ray images.

The proposed method begins with constructing lung and heart segmentation models based on U-Net architecture using the publicly available datasets with the groundtruth of heart and lung masks. The ratio is then calculated using the sizes of segmented lung and heart areas. In addition, Progressive Growing of GANs (PGAN) is adopted here for constructing the new dataset containing chest x-ray images of three classes including male normal, female normal and cardiomegaly classes. This dataset is then used for evaluating the proposed solution. Also, the proposed solution is used to evaluate the quality of chest x-ray images generated from PGAN.

In the experiments, the trained models are applied to segment regions of heart and lung in chest x-ray images on the self-collected dataset. The calculated CTR values are compared with the values that are manually measured by human experts. The average error is 3.08%. Then, the models are also applied to segment regions of heart and lung for the CTR calculation, on the dataset computed by PGAN. Then, the cardiomegaly is determined using various attempts of different cut-off threshold values. With the standard cut-off at 0.50, the proposed method achieves 94.61% accuracy, 88.31% sensitivity and 94.20% specificity.

The proposed solution is demonstrated to be robust across unseen datasets for the segmentation, CTR calculation and cardiomegaly classification, including the dataset generated from PGAN. The cut-off value can be adjusted to be lower than 0.50 for increasing the sensitivity. For example, the sensitivity of 97.04% can be achieved at the cut-off of 0.45. However, the specificity is decreased from 94.20% to 79.78%.

Science and technology policy plays an important role in promoting the development of economic and social development in China. At present, the research on science and technology policy is mainly focused on the basic theories and some quantitative research. The analyses for contents of massive science and technology policies are relatively less. This paper makes use of semantic technologies to extract and analyze the relatively important information from massive science and technology policies. The purpose of this paper is to facilitate users to quickly and effectively obtain valuable information from the massive science and technology policies. The key methods and study results are presented in the paper. The study results can provide references for further study and application in China.

The paper presented the analysis model and method for science and technology policy in China. The terms and sentences are the important information in the science and technology policy. The study adopted the technology of natural language processing to analyze the linguistics characteristics of terms and combined with statistical analyses to extract the terms from Chinese science and technology policy. Then, the authors designed an algorithm, calculated and analyzed the important sentences in Chinese science and technology policies. The experiments were run on the Java test platform.

This paper put forward the analysis model and method for science and technology policy in China. The study obtained the following conclusions: term extraction of science and technology policy: the paper analyzed characteristic of terms in Chinese science and technology policy and designed a method of extracting a term that was suitable for the science and technology policy. The calculation of important sentences for science and technology policy: the paper designed an algorithm and calculated the importance of the sentences to obtain valuable information from the massive science and technology policies.

In our methods, there are some defects to be improved or solved in the future. For example, the precision of algorithm needs to be improved. The significance of this paper is to propose and use the analysis model to process Chinese science and technology policy; we can provide an auxiliary tool to help policy beneficiaries. Enterprises and individuals can be more effective to extraction and mining information from massive science and technology policy and find the target policy.

To verify the effectiveness of the method, the paper selected the real policies about the new energy vehicles as experimental data; at the same time, the paper added uncorrelated policies. It used the proposed analysis model of science and technology policy to calculate and find out the relatively important sentences. The results of study showed that the proposed method can obtain better performance. It verified the validity of this method. The model and method have been applied to actual retrieval system.

The proposed model and method in the paper have been applied to actual retrieval system for users.

The paper proposed the new analysis model and method to analyze science and technology policies in China. The presented model and method are a new attempt. According to the experimental results, this exploration and study are valuable. In addition, the idea and method will give a good start for improving information services of massive science and technology policies in China.

The purpose of this study is to examine the relationships between face concerns, articulated (upward) dissent and organizational assimilation. In this study, articulated dissent was conceptualized as a type of dissent.

A questionnaire was distributed to 370 working adults in the USA via Qualtrics. The questionnaire measured five face concerns, namely, self, other and mutual-face, articulated dissent and organizational assimilation. Before hypothesis testing, each measure was subjected to a confirmatory factor analysis to ensure that the hypothesized factor structure held. Pearson correlation and ordinary least squares estimation were used to test the hypotheses.

Conceptualizing dissent as a type of conflict, the findings of the current study are as follows: self-face and assimilation are positively correlated, other-face and assimilation are positively correlated, mutual-face and assimilation are positively correlated, assimilation and articulated dissent are positively correlated and organizational assimilation mediated the relationship between mutual-face and articulated dissent.

Theoretically, the self-presentation process (face) is more critical as a person becomes part of an organization; it is through assimilating into an organization that members become familiar with the norms of an organization and more comfortable dissenting to their superiors (articulated dissent); and the more the authors integrate with the work colleagues the more the authors engage in mutual face-saving.

The results of this study demonstrate that self-presentation is critical as a person becomes part of an organization, particularly when it comes to managing conflict.

This is the first study to link facework with organizational dissent. The results add to the understanding of how face affects whether we choose to express this kind of conflict behavior.

This paper studies the lateral stability regulation of intelligent electric vehicle (EV) based on model predictive control (MPC) algorithm.

Firstly, the bicycle model is adopted in the system modelling process. To improve the accuracy, the lateral stiffness of front and rear tire is estimated using the real-time yaw rate acceleration and lateral acceleration of the vehicle based on the vehicle dynamics. Then the constraint of input and output in the model predictive controller is designed. Soft constraints on the lateral speed of the vehicle are designed to guarantee the solved persistent feasibility and enforce the vehicle’s sideslip angle within a safety range.

The simulation results show that the proposed lateral stability controller based on the MPC algorithm can improve the handling and stability performance of the vehicle under complex working conditions.

The MPC schema and the objective function are established. The integrated active front steering/direct yaw moments control strategy is simultaneously adopted in the model. The vehicle’s sideslip angle is chosen as the constraint and is controlled in stable range. The online estimation of tire stiffness is performed. The vehicle’s lateral acceleration and the yaw rate acceleration are modelled into the two-degree-of-freedom equation to solve the tire cornering stiffness in real time. This can ensure the accuracy of model.