Y Jiang

The purpose of this study was to evaluate, revise, and extend the Informed Consent Ontology (ICO) for expressing clinical permissions, including reuse of residual clinical biospecimens and health data. This study followed a formative evaluation design and used a bottom-up modeling approach. Data were collected from the literature on US federal regulations and a study of clinical consent forms. Eleven federal regulations and fifteen permission-sentences from clinical consent forms were iteratively modeled to identify entities and their relationships, followed by community reflection and negotiation based on a series of predetermined evaluation questions. ICO included fifty-two classes and twelve object properties necessary when modeling, demonstrating appropriateness of extending ICO for the clinical domain. Twenty-six additional classes were imported into ICO from other ontologies, and twelve new classes were recommended for development. This work addresses a critical gap in formally representing permissions clinical permissions, including reuse of residual clinical biospecimens and health data. It makes missing content available to the OBO Foundry, enabling use alongside other widely-adopted biomedical ontologies. ICO serves as a machine-interpretable and interoperable tool for responsible reuse of residual clinical biospecimens and health data at scale.

Actions are usually generalized among social group members. Importantly, the efficiency of an action with respect to achieving an external target determines action understanding, and it may have different degrees of social relevance to social groups. Thus, this study explored the role of action efficiency in action generalization. We used computer animations to simulate actions in social groups initiated by visual action cues or category labels, and we measured differences in response times between identifying actions that were and were not consistent with group members, without explicit requirements regarding generalization. It was found that in both visually introduced and explicitly labeled social groups, when the group members acted inefficiently toward the external object, perceivers identified group‐consistent actions faster than group‐inconsistent actions, indicating that the exemplars' common inefficient actions are generalized to the unknown ingroup member, accordingly facilitating the identification of expected consistent inefficient action (Experiment 1). As this effect was not present when removing social group cues, it was determined to be specific to social groups (Experiment 2). Importantly, such generalization was not observed when the identical action was deemed efficient toward the external object (Experiment 3) and was specific to the demonstration of the action being completed by multiple group members rather than being repeated twice by one group member, supporting the group‐based inference and ruling out the possibility of the increased memorability of inefficient actions leading to more generalization relative to efficient actions (Experiment 4). Therefore, the efficiency of an action bounds the generalization of the action across social group members through a process that is spontaneous and implicit. This constrained action generalization may be due to inefficient actions being represented as culture‐specific conventional forms.

The outbreak of COVID-19 has greatly affected university students’ studies and life. This study aimed to examine the possible mediating role of psychological capital and the moderating role of academic burnout in the relationship between problematic social media usage and anxiety among university students during COVID-19. A total of 3,123 undergraduates from universities in Shanghai participated in an online survey from March to April 2020. The results showed that problematic social media usage among university students predicted their levels of anxiety. Mediation analysis indicated that psychological capital mediated the relationship between problematic social media usage and anxiety. Furthermore, for university students whose academic performance had been affected by the COVID-19 pandemic, the effects of both problematic social media usage and the psychological capital on anxiety were moderated by academic burnout. For university students whose academic performance was not affected by the COVID-19 pandemic, academic burnout moderated the effects of psychological capital but not the effects of problematic social media usage on anxiety. The results highlighted the underlying mechanisms in the relationship between problematic social media usage and anxiety. These findings provide practical insights into the development and implementation of psychological interventions when facing a pandemic.

Teacher behaviors are one of the most significant factors influencing student learning. Students from different cultures may have different interpretations of their teachers’ behaviors. This study compared the associations between teacher strictness, teacher feedback, and students’ motivational beliefs using data from six Western countries (the United States, the United Kingdom, Finland, Norway, Australia, and New Zealand) and six East Asian regions (Japan, Korea, mainland China, Hong Kong, Macau, and Taiwan) in the Program for International Student Assessment (PISA) 2015. A total of 89,869 15-year-old students were included in data analysis. The findings indicate that (i) teacher strictness was negatively associated with Western students’ motivation, but positively related to that of East Asian students; (ii) teacher feedback had significant positive associations with the motivational beliefs of both Western and East Asian students; and (iii) there was a positive relationship between teacher strictness and teacher feedback in East Asian context. These results highlight the need to consider cultural factors when interpreting students’ reactions to teacher behaviors.

Upholding sustainability in the use of energies for the increasing global industrial activity has been one of the priority agendas of the global leaders of the West and East. The projection of different GHGs has thus been the important policy agenda of the economies to justify the positions of their own as well as of others. Methane is one of the important components of GHGs, and its main sources of generation are the agriculture and livestock activities. Global diplomacy regarding the curtailment of the GHGs has set the target of reducing the levels of GHGs time to time, but the ground reality regarding the reduction is far away from the targets. Sometimes, the targets are fixed without the application of scientific methods. The aim of the present study is to examine sustainability of energy systems through the forecasting of the methane emission and agricultural output of the world’s different income groups up to 2030 using the data for the period 1981–2012. The work is novel in two senses: the existing studies did not use both the Box–Jenkins and artificial neural network methods, and the present study covers all the major economic groups in the world which is unlike to any existing studies. Two methods are used for forecasting of the two. One is the Box–Jenkins method, where linear nature of the two variables is considered and the other is artificial neural network methods where nonlinear nature of the variables is also considered. The results show that, except the OECD group, all the remaining groups display increasing trends of methane emission, but unquestionably, all the groups display increasing trends of agricultural output, where middle- and upper middle-income groups hold the upper berths. The forecasted emission is justified to be sustainable in major groups under both methods of estimations since overall growth of agricultural output is greater than that of methane emission.