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This study is among the first to provide empirical evidence on maximizing the benefits of AI capabilities to generate sustained SCP. The study could be further extended using a longitudinal investigation to explore more facets of the phenomenon.Multiplex networks have drawn much attention since they have been observed in many systems, e.g., brain, transport, and social relationships. In this paper, the nonlinear dynamics of a multiplex network with three neural groups and delayed interactions is studied. The stability and bifurcation of the network equilibrium are discussed, and interesting neural activities of the network are explored. Based on the neuron circuit, transfer function circuit, and time delay circuit, a circuit platform of the network is constructed. It is shown that delayed couplings play crucial roles in the network dynamics, e.g., the enhancement and suppression of the stability, the patterns of the synchronization between networks, and the generation of complicated attractors and multi-stability coexistence.Although self-control tends to increase through late adolescence, there are individual differences in patterns of growth. Latent growth modeling was used to investigate change in self-control across students' first year of college (N = 569, Mage = 18.03; 70.3% female; 89.6% White), and whether attachment to parents predicted this change when controlling for personality and demographic variables. Self-control decreased linearly across five assessments, with significant heterogeneity in intercepts and slopes. Personality was associated with initial self-control, and greater avoidant attachment to mothers and openness to experience predicted greater declines. Overall, self-control changes across late adolescence, and attachment and personality explain individual differences in that change, indicating potential intervention targets during emerging adulthood.During the lockdown due to SARS-CoV-2 (coronavirus lockdown), there has been a tremendous increase in the number of students taking online courses. Few studies, however, have examined the individual dispositions that influence self-regulated online learning during the coronavirus lockdown. To address this gap, the present study explored the ineffectiveness of online learning and examined how it can be predicted by self-regulated online learning and participants' procrastination disposition. Data of 433 participants were collected and subjected to confirmatory factor analysis with structural equation modeling. The results indicated that procrastination is negatively related to 6 sub-constructs of self-regulated online learning task strategy, mood adjustment, self-evaluation, environmental structure, time management, and help-seeking. These sub-constructs were negatively related to the learners' perceived ineffectiveness of online learning. However, the relationship between perceived learning ineffectiveness and environmental structure or help-seeking was weaker than that with task strategy or mood adjustment, indicating that the latter two subtypes of self-regulated online learning should be considered before students engage in online learning.Given that individual differences influence virus-mitigating behaviors and the COVID-19 pandemic posed new moral dilemmas for individuals to resolve, across three studies (N = 704), we assessed how masculine honor beliefs (MHB), beliefs in pure good (BPG), evil (BPE), and the dark triad (DT) influence COVID-19 moral decision-making. Specifically, we analyzed moral decision-making at the microlevel (i.e., individual- and familial-level; Study 1), in decisions with (hypothetical) life-or-death consequences (Study 2), and at the macrolevel (i.e., nationwide virus-mitigation efforts; Study 3). In all studies, participants completed the four individual difference scales and rated their pandemic attitudes on Likert-type agreement scales, and resolved various moral dilemmas in Studies 2 and 3. Consistent with our hypotheses, individuals reported more virus-mitigation efforts in order to protect their families than themselves. In terms of hypothetical life-or-death and nationwide decisions, MHB, BPE, and the DT predicted more confidence and social motivations, whereas BPG predicted more distress. This research has implications for moral decision-making at varying degrees of severity during the COVID-19 pandemic.In the United States, while the number of COVID-19 cases continue to increase, the practice of social distancing and mask-wearing have been controversial and even politicized. The present study examined the role of psychological traits in social distancing compliance and mask-wearing behavior and attitude. A sample of 233 U.S. adult residents were recruited from Amazon Mechanical Turk. Participants completed scales of social distancing compliance, mask-wearing behavior and attitude, need for cognition, self-control, risk attitude, and political ideology. Epidemiological information (seven-day positive rate and the number of cases per 100,000) was obtained based on the state participants resided in. As a result, epidemiological information did not correlate with social distancing compliance mask-wearing. Political ideology, on the other hand, was a significant factor, with a more liberal tendency being associated with greater engagement in social distancing compliance and mask-wearing behavior an attitude. Importantly, those who were more risk averse, or had a higher level of self-control or need for cognition practiced more social distancing and mask-wearing, after controlling for demographics, epidemiological information, and political ideology. Furthermore, for mask-wearing behavior, political ideology interacted with both need for cognition and self-control. Collectively, the study revealed the psychological roots of individual differences in social distancing and mask-wearing compliance.It has been more than 10 months since the first COVID-19 case was reported in Wuhan, China, still menacing the world with a possible second wave. This study aimed to analyze how meteorological variables can affect the spread of local COVID-19 transmission in Bangladesh. Nine spatial units were considered from a meteorological standpoint to characterize COVID-19 transmission in Bangladesh. The daily COVID-19 incidence and meteorological variable (e.g., mean temperature, relative humidity, precipitation, and wind speed) data from April 5 to September 20, 2020, were collected. The Spearman rank correlation, heat maps, and multivariate quasi-Poisson regression were employed to understand their association. Retinoic acid STAT inhibitor The effect of meteorological variables on COVID-19 transmission was modeled using a lag period of 10 days. Results showed that mean temperature, relative humidity, and wind speed are substantially associated with an increased risk of COVID-19. On the other hand, daily precipitation is significantly associated with a decreased risk of COVID-19 incidence.