Xiao Wang

Chinese international students who studied in the United States received “double stigmatization” from American and Chinese authorities because of the “political othering” tactic during COVID-19. The research used a phenomenological approach to examine why and how specifically the transnational identity of Chinese international students in the United States shifted during the double stigmatization. The researcher conducted a total of three rounds of interviews with 15 Chinese international students who studied in the United States and returned to China between 2018 and 2020, which culminated in 45 interviews through a longitudinal study to probe the transnational identities of this population before and during the double stigmatization; the study also examined how the mindsponge mechanism worked during the identity shifts and the interplay among stigmatization, transnational identity shifts, and the mindsponge mechanism. The study concluded that before COVID-19, Chinese international students had been stigmatized in both China and the United States.

With the development of deep neural networks, automatic music composition has made great progress. Although emotional music can evoke listeners' different auditory perceptions, only few research studies have focused on generating emotional music. This paper presents EmotionBox -a music-element-driven emotional music generator based on music psychology that is capable of composing music given a specific emotion, while this model does not require a music dataset labeled with emotions as previous methods. In this work, pitch histogram and note density are extracted as features that represent mode and tempo, respectively, to control music emotions. The specific emotions are mapped from these features through Russell's psychology model. The subjective listening tests show that the Emotionbox has a competitive performance in generating different emotional music and significantly better performance in generating music with low arousal emotions, especially peaceful emotion, compared with the emotion-label-based method.

Responding to serious environmental problems, requires urgent and fundamental shifts in our day-to-day lifestyles. This paper employs a qualitative, cross-cultural approach to explore people’s subjective self-reflections on their experiences of pro-environmental behavioral spillover in three countries; Brazil, China, and Denmark. Behavioral spillover is an appealing yet elusive phenomenon, but offers a potential way of encouraging wider, voluntary lifestyle shifts beyond the scope of single behavior change interventions. Behavioral spillover theory proposes that engaging in one pro-environmental action can catalyze the performance of others. To date, evidence for the phenomenon has been mixed, and the causal processes governing relationships between behaviors appear complex, inconsistent and only partly understood. This paper addresses a gap in the literature by investigating accounts of behavioral spillover in three diverse cultural settings using qualitative semi-structured interviews. The analysis shows that while around half of participants overall who were questioned recalled spillover effects, the other half had not consciously experienced spillover. There were few significant differences across cultures, though some forms of spillover effects were reported more in some cultures than others. More environmentally-engaged participants across all three countries were significantly more likely to experience spillover than those who were less engaged. Accounts of within-domain spillovers were most commonly reported, mainly comprising waste, resource conservation and consumption-related actions. Accounts of between-domain spillover were very rare. Recollection of contextual and interpersonal spillover effects also emerged from the interviews. Our findings suggest that more conscious behavioral spillover pathways may be limited to those with pre-existing environmental values. Behavioral spillover may comprise multiple pathways incorporating conscious and unconscious processes. We conclude that targeting behavioral catalysts that generate more socially diffuse spillover effects could offer more potential than conventional spillover involving a single individual.

Most research in environmental psychology is conducted in individualistic countries and focuses on factors pertaining to individuals. It is yet unclear whether these findings also apply to more collectivistic countries, in which group factors might play a prominent role. In the current paper, we test the individual-focused value–identity–behaviour pathway, in which personal biospheric values relate to pro-environmental actions via environmental self-identity, in an individualistic and a collectivistic country. Furthermore, we test in both countries whether a new group-focused pathway also exists, in which group values relate to pro-environmental behaviour via environmental group identity, particularly in collectivistic countries. Questionnaire studies were conducted among Dutch and Chinese students. Our results indicated that personal biospheric values, mostly via environmental self-identity, predict pro-environmental behaviour in both countries. We also found initial support for our newly proposed value–identity–behaviour pathway at the group level, particularly in China. Yet, in both countries, the association between group-level variables and pro-environmental behaviour was weaker than for personal-level variables, and partly overlapped with personal-level variables. Our findings show the relevance of personal- and group-level factors in understanding pro-environmental behaviour in both individualistic and collectivistic countries, which has strong theoretical and practical implications, particularly for developing international strategies to promote pro-environmental actions across the world.

Cognitive diversity is an important concept stemming from western management research in the 1990s. With the rapid development of science and technology, there is a growing interest in the composition of an academic research team, such as team diversity. However, there is no tool available for measuring team cognitive diversity for academic research teams. Based on Van der Vegt’s theoretical model of TCD, an Academic Research Team Cognitive Diversity Scale is developed and validated for an academic research team in our research with two studies. In Study One, in-depth interviews and panel discussions were conducted to generate a preliminary questionnaire. In Study Two, the questionnaire was administered among academic research teams. Exploratory factor analysis revealed four factors regarding cognitive diversity: the way of thinking, knowledge and skills, the view of the world, and beliefs about what is right and wrong. The factor structure was further validated by confirmatory factor analysis. Moreover, correlation and regression analyses showed that academic research TCD was positively related to team creativity and performance. To sum up, our newly developed 15-item ATCDS is sufficiently reliable and valid to be used for understanding cognitive diversity among academic research teams.

Tradition wireless sensor networks transmit data by single or multiple hops. However, some sensor nodes close to a static base station forward data more frequently than others, which results in the problem of energy holes and makes networks fragile. One promising solution is to use a mobile node as a mobile sink, which is especially useful in energy-constrained networks. In these applications, the tour planning of MS is a key to guarantee the network performance. In this paper, a novel strategy is proposed to reduce the latency of mobile data gathering in a WSN while the routing strategies and tour planning of MS are jointly optimized. First, the issue of network coverage is discussed before the appropriate number of clusters being calculated. A dynamic clustering scheme is then developed where a virtual cluster center is defined as the MS sojourn for data collection. Afterwards, a tour planning of MS based on prediction is proposed subject to minimizing the traveling distance to collect data. The proposed method is simulated in a MATLAB platform to show the overall performance of the developed system. Furthermore, the physical tests on a test rig are also carried out where a small WSN based on an unmanned aerial vehicle is developed in our laboratory. The test results validate the feasibility and effectiveness of the method proposed.

We present a population density and moment-based description of the stochastic dynamics of domain $${\text{Ca}}^{2+}$$ -mediated inactivation of L-type $${\text{Ca}}^{2+}$$ channels. Our approach accounts for the effect of heterogeneity of local $${\text{Ca}}^{2+}$$ signals on whole cell $${\text{Ca}}^{2+}$$ currents; however, in contrast with prior work, e.g., Sherman et al. :985–995, 1990), we do not assume that $${\text{Ca}}^{2+}$$ domain formation and collapse are fast compared to channel gating. We demonstrate the population density and moment-based modeling approaches using a 12-state Markov chain model of an L-type $${\text{Ca}}^{2+}$$ channel introduced by Greenstein and Winslow :2918–2945, 2002). Simulated whole cell voltage clamp responses yield an inactivation function for the whole cell $${\text{Ca}}^{2+}$$ current that agrees with the traditional approach when domain dynamics are fast. We analyze the voltage-dependence of $${\text{Ca}}^{2+}$$ inactivation that may occur via slow heterogeneous domain [ $${\text{Ca}}^{2+}$$ ]. Next, we find that when channel permeability is held constant, $${\text{Ca}}^{2+}$$ -mediated inactivation of L-type channels increases as the domain time constant increases, because a slow domain collapse rate leads to increased mean domain [ $${\text{Ca}}^{2+}$$ ] near open channels; conversely, when the maximum domain [ $${\text{Ca}}^{2+}$$ ] is held constant, inactivation decreases as the domain time constant increases. Comparison of simulation results using population densities and moment equations confirms the computational efficiency of the moment-based approach, and enables the validation of two distinct methods of truncating and closing the open system of moment equations. In general, a slow domain time constant requires higher order moment truncation for agreement between moment-based and population density simulations.

Managerial myopia occurs when executives value short-term benefits to the extent that firm long-run development will be obstructed. Recent studies have shown that the locality effect plays an important role in managerial myopia—local United States chief executive officers who work near their home states are less likely to behave myopically because of more effective monitoring and greater reputation concern. In an emerging market, government policies play a more important role in the strategic planning enterprises. A local CEO may have better understanding of local government’s policies thus makes less short-term decisions. This article adds to this literature by testing whether local-province CEOs in China, i.e., the CEO’s native place or birthplace is in the same province as her company’s headquarters, are also far-sighted. Using data on 470 publicly listed non-state-owned Chinese firms from 2014 to 2018, supportive evidence has been found that non-local-province CEOs in China tend to cut R&D expenses for beating analyst forecasts, reversing earnings decline, or pursuing higher returns. This article also confirms social capital as one mechanism of Chinese local-province CEOs behaving less myopically. This investigation also adds to the literature by revealing a new mechanism that CEO locality in China has a positive and direct bearing on how governments support corporate innovation.

In this paper, the issue of optimally modifying the structure of a directed network to guarantee its structural controllability is investigated. Given a directed network, in order to obtain a structurally controllable system, a framework for finding the minimum number of directed edges that need to be added to the network is proposed. After we get these edge-addition configurations, we further calculate the network cost of each optimization scheme and choose the one with the minimum cost. Our main contribution is twofold: first, we provide an algorithm able to find all optimal network modifications in polynomial time; second, we provide a way to calculate the cost of optimizing the network based on the node betweenness. Numerical simulations are given to illustrate the theoretical results.