The experience of emotion has a powerful influence on daily-life decision making. Following Plato’s description of emotion and reason as two horses pulling us in opposite directions, modern dual-system models of decision making endorse the antagonism between reason and emotion. Decision making is perceived as the competition between an emotion system that is automatic but prone to error and a reason system that is slow but rational. The reason system (in “the head”) reins in our impulses (from “the heart) and (...) overrides our snap judgments. However, from Darwin’s evolutionary perspective, emotion is adaptive, guiding us to make sound decisions in uncertainty. In this review, we provide a new model, called “The interactive influence model of emotion & cognition”, to elaborate the relationship of emotion and reason in decision making. Specifically, in our model, we identify factors that determine when emotions override reason and delineate the type of contexts in which emotions help or hurt decision making. We then illustrate how cognition modulates emotion and how they cooperate to affect decision making. (shrink)

Hierarchies occur widely in evolving self‐organizing ecological, biological, technological, and social networks, but detecting and comparing hierarchies is difficult. Here we present a metric and technique to quantitatively assess the extent to which self‐organizing directed networks exhibit a flow hierarchy. Flow hierarchy is a commonly observed but theoretically overlooked form of hierarchy in networks. We show that the ecological, neurobiological, economic, and information processing networks are generally more hierarchical than their comparable random networks. We further discovered that hierarchy degree has (...) increased over the course of the evolution of Linux kernels. Taken together, our results suggest that hierarchy is a central organizing feature of real‐world evolving networks, and the measurement of hierarchy opens the way to understand the structural regimes and evolutionary patterns of self‐organizing networks. Our measurement technique makes it possible to objectively compare hierarchies of different networks and of different evolutionary stages of a single network, and compare evolving patterns of different networks. It can be applied to various complex systems, which can be represented as directed networks. (shrink)

With people’s concerns about the environment growing, the demand for organic food has increased. However, few studies have focused on organic dining intention. Therefore, this study examined generativity, which is defined as the direction and care for the growth of future generations through self-expanding forms, and its influence on attitude toward organic food, environment concern and dining intention. The moderating effect of age was also examined. A total of 418 responses were collected through a face-to-face survey from Shanghai respondents. PLS-SEM (...) was utilized to verify the model and test the relationships among the constructs. The results show that generativity directly influences environmental concerns, attitudes toward organic food and dining intentions. Furthermore, environmental concerns and attitudes toward organic food are mediating variables for generativity to affect dining intentions. The older the age group, the more likely it is for generativity to have a positive influence on attitude toward organic food and environmental concerns. Theoretical and practical implications are also discussed in this study. (shrink)

The unprecedented public panic caused by COVID-19 will affect the recovery of tourism, especially the theme parks, which are generally crowded due to high visitor volume. The purpose of this study is to discuss the effect of the COVID-19 on the theme park industry. This study aims to predict recommendation intentions of theme park visitors by exploring the complicated mechanism derived from the fear of COVID-19. This study uses a quantitative research method, and SPSS 20.0 and AMOS 22.0 were used (...) for data analysis. An online survey was conducted with 420 Chinese respondents who visited Shanghai Disneyland after its reopening. The study explored the relationship between Fear of COVID-19, perceived risk, participation, service experience, and revisit intention. Results indicated the perceived risk of theme park visitors will not directly ruin their recommendation intention. Visitors’ fear of COVID-19 enhanced their perceived risk, reduced their desire for active participation and impaired their service experience, which consequently affected their recommendation intention. We provide theoretical and managerial implications. (shrink)

A novel data-driven model-free adaptive control approach is first proposed by combining the advantages of model-free adaptive control and data-driven optimal iterative learning control, and then its stability and convergence analysis is given to prove algorithm stability and asymptotical convergence of tracking error. Besides, the parameters of presented approach are adaptively adjusted with fuzzy logic to determine the occupied proportions of MFAC and DDOILC according to their different control performances in different control stages. Lastly, the proposed fuzzy DDMFAC approach is (...) applied to the control of particle quality in drug development phase of spray fluidized-bed granulation process, and its control effect is compared with MFAC and DDOILC and their fuzzy forms, in which the parameters of MFAC and DDOILC are adaptively adjusted with fuzzy logic. The effectiveness of the presented FDDMFAC approach is verified by a series of simulations. (shrink)

ObjectiveThis study aimed to develop a diagnostic model of multi-kinematic parameters for patients with amnestic mild cognitive impairment (aMCI).MethodIn this cross-sectional study, 94 older adults were included (33 cognitively normal, CN; and 61 aMCI). We conducted neuropsychological battery tests, such as global cognition and cognitive domains, and collected gait parameters by an inertial-sensor gait analysis system. Multivariable regression models were used to identify the potential diagnostic variables for aMCI. Receiver operating characteristic (ROC) curves were applied to assess the diagnostic accuracy (...) of kinematic parameters in discriminating aMCI from healthy subjects.ResultsMultivariable regression showed that multi-kinematic parameters were the potential diagnostic variables for aMCI. The multi-kinematic parameter model, developed using Timed Up and Go (TUG) time, stride length, toe-off/heel stride angles, one-leg standing (OLS) time, and braking force, showed areas under ROC (AUC), 0.96 [95% confidence interval (CI), 0.905–0.857]; sensitivity, 0.90; and specificity, 0.91. In contrast, a single kinematic parameter’s sensitivity was 0.26–0.95 and specificity was 0.21–0.90. Notably, the separating capacity of multi-kinematic parameters was highly similar to Montreal Cognitive Assessment (MoCA; AUC: 0.96 vs. 0.95). Compared to cognitive domain tests, the separating ability was comparable to Auditory Verbal Learning Test (AVLT) and Boston Naming Test (BNT; AUC: 0.96 vs. 0.97; AUC: 0.96 vs. 0.94).ConclusionWe developed one diagnostic model of multi-kinematic parameters for patients with aMCI in Foshan. (shrink)

Customers have obvious occupational gender stereotypes for service employees. In recent years, intelligent service robots have been widely used in the hospitality industry and have also been given gender characteristics to attract customers to use them. However, whether and when the usage of gendered service robots is effective remains to be explored. This research focuses on customers' occupational gender stereotypes and the gender of service robots, examining the influences of their consistency on customers' willingness to use service robots through three (...) scenario studies. The findings suggest that: The consistency between occupational gender stereotypes and service robot gender positively affects customers' willingness to use service robots. Performance expectancy and trust are two psychological mechanisms underlying the above effect. In the context of service failures, the consistency backfires and brings negative effects on willingness to use. This research extends the literature on customers' acceptance of anthropomorphized robots from the perspective of gender stereotypes and identifies the mechanisms behind the stereotype consistency effect. For practical implications, hotels should design and deploy gendered robots consistent with corresponding occupational gender stereotypes. (shrink)

本书是一部研究北宋草根思想家,文学家和教育家李觏的文史专著.全书对北宋名儒李觏的生平,交往,著述,事迹,文学,创作及其影响进行了较为全面而细致的研究和探析.

A diferencia de los productos estandarizados del té, la difusión del té chino nunca ha sido una simple cuestión de transporte y logística, y está estrechamente relacionado con la substancia, rutas de propagación, difusión localizada, cambios de épocas, etc. Todos estos elementos mezclados hacen que el té mantenga un equilibrio espontáneo entre propiedad mercantil y etiqueta cultural. Este trabajo investiga principalmente sobre la difusión vertical (cambios a lo largo de la historia de China) y horizontal del té chino. Y en (...) la difusión horizontal toma como ejemplo la ceremonia del té japonesa en comparación con la china para aclarar las cuestiones relacionadas. (shrink)

本書輯錄駱建人先生以論學為主的文章，無論在內容或文體方面，都比較多樣化，其中不但有單純的學術討論，也有對知識份子的期許與匡時濟世的箴言。先生一生奉獻教育，關懷社會，篤志於學，著述不輟，內心秉持傳統儒者 入世的情懷，也嚮往陶淵明自然率真的心靈境界。全書不但體現了先生為學的廣博與深入，也令人感受到一位傳統知識份子的勁直的節操與捨我其誰的使命感。.

Artificial intelligence is a cutting-edge technology that has been widely applied in tourism operations. To enhance tourists' experience, many tourism suppliers introduced AI devices to interact with tourists. Previous studies classified AI devices as task- and social- oriented based on their functions; however, current models that explain customers' intention to use AI devices did not reflect the discrepancy between the two different types. Therefore, this paper attempts to fill this gap by proposing a theoretical model for the use of task-oriented (...) AI devices. Based on the multi-stage appraisal framework and the Structural Equation Modeling analysis, this paper presents the following findings: utilitarian motivation, interaction convenience, and task-technology fit are the factors appraised in the first stage; perceived competence and flow experience are the factors appraised in the second stage; utilitarian motivation, interaction convenience, and task-technology fit are positively associated with perceived competence. Perceived competence positively influences flow experience, which further affects customers' switching intention from task-oriented AI devices to human service; the serial mediating effect of perceived competence and flow experience between the stimulus mentioned in the first appraisal stage and the switching intention is confirmed. This study reveals the underlying psychological mechanism when customers use task-oriented AI devices, and it provides a theoretical framework for task-oriented AI device adoption. (shrink)