J Li

This study investigated cross-cultural differences in individual pride and collective pride between Chinese and Americans using data from text corpora. We found higher absolute frequencies of pride items in the American corpus than in the Chinese corpus. Cross-cultural differences were found for relative frequencies of different types of pride, and some of them depended on the genre of the text corpora. For both blogs and news genres, Americans showed higher frequencies of individual pride items and lower frequencies of relational pride items than did their Chinese counterparts. Cross-cultural differences in national pride, however, depended on the genre: Chinese news genre included more national pride items than its American counterpart, but the opposite was true for the blog genre. We discuss the implications of these results in relation to the existing literature on cultural differences in individual pride and collective pride.

BackgroundPsychological resilience may reduce the impact of psychological distress to some extent. We aimed to investigate the mental health status of the public during the outbreak of coronavirus disease 2019 and explore the level and related factors of anxiety and depression.MethodsFrom February 8 to March 9, 2020, 3,180 public completed the Zung’s Self-Rating Anxiety Scale for anxiety, Zung’s Self-Rating Depression Scale for depression, the Connor–Davidson resilience scale for psychological resilience, and the Simplified Coping Style Questionnaire for the attitudes and coping styles.ResultsThe number of people with depressive symptoms was 1,303. The number of people with anxiety symptoms was 1,184. The depressed group and anxiety group had less education, more unmarried and younger age, as well as had significant different in SDS total score, SAS total score, CD-RISC total score, and SCSQ score. The binary logistic regression showed that female, strength, and the subscales of active coping style in SCSQ remained protective factors and passive coping style and higher SAS score were risk factors for depression. Optimism in CD-RISC was a protective factor, and passive coping styles and higher SDS score were risk factors for anxiety.LimitationsThis study adopted a cross-sectional design and used self-report questionnaires.ConclusionThe mental health of the public, especially females, the younger and less educational populations, and unmarried individuals, should be given more attention. Individuals with high level of mental resilience and active coping styles would have lower levels of anxiety and depression during the outbreak of COVID-19.

The European Union Commission’s whitepaper on Artificial Intelligence proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: the lack of a coherent EU vision to drive future decision-making processes at state and local levels and the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. Moreover, the Commission aims at changing the AI development culture proposing a human-centred and safety-first perspective that is not supported by methodological advancements, thus taking the risks of unforeseen social and societal impacts of AI. We discuss potential societal, technical, and methodological gaps that should be filled to avoid the risks of developing AI systems at the expense of society. Our analysis results in the recommendation that the EU regulators and policymakers consider how to complement the EC programme with rules and compensatory mechanisms to avoid market fragmentation due to local and global ambitions. Moreover, regulators should go beyond the human-centred approach establishing a research agenda seeking answers to the technical and methodological open questions regarding the development and assessment of human-AI co-action aiming for a sustainable AI diffusion in the society.

The sampling-based motion planner is the mainstream method to solve the motion planning problem in high-dimensional space. In the process of exploring robot configuration space, this type of algorithm needs to perform collision query on a large number of samples, which greatly limits their planning efficiency. Therefore, this paper uses machine learning methods to establish a probabilistic model of the obstacle region in configuration space by learning a large number of labeled samples. Based on this, the high-dimensional samples’ rapid collision query is realized. The influence of number of Gaussian components on the fitting accuracy is analyzed in detail, and a self-adaptive model training method based on Greedy expectation-maximization algorithm is proposed. At the same time, this method has the capability of online updating and can eliminate model fitting errors due to environmental changes. Finally, the model is combined with a variety of sampling-based motion planners and is validated in multiple sets of simulations and real world experiments. The results show that, compared with traditional methods, the proposed method has significantly improved the planning efficiency.

BackgroundThe Basal ganglia (BG) played a crucial role in the brain-level mechanisms of chronic pain disorders. However, the functional changes of BG in chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) are still poorly understood. This study investigated the BG subregions’ resting-state functional connectivity (rs-FC) in CP/CPPS patients compared with healthy controls.MethodsTwenty eight patients with CP/CPPS and 28 age- and education-matched healthy males underwent clinical measurements and 3T brain MR imaging, including T1-weighted structural images and resting-state functional imaging. The data were analyzed by the seeded-based rs-FC analysis. Then, a machine learning method was applied to assess the feasibility of detecting CP/CPPS patients through the changed rs-FC.ResultsCompared with healthy males, patients presented decreased rs-FC between the BG subregions and right middle cingulate cortex, and correlated with pain (r = 0.51, p-uncorrected = 0.005) and urinary symptoms (r = –0.4, p-uncorrected = 0.034). The left superior temporal gyrus and right supramarginal gyrus showed decreased rs-FC with the BG subregions as well. The area under the receiver operating characteristic curve of 0.943 (accuracy = 80%, F1-score = 80.6%) was achieved for the classification of CP/CPPS patients and healthy males with support vector machine (SVM) based on the changed rs-FC.ConclusionThese findings provide evidence of altered BG subregions’ rs-FC in CP/CPPS, which may contribute to our understanding of the BG’s role in CP/CPPS.

Pursuing world-class universities, China has emerged in recent decades as an increasingly popular destination for internationally mobile academics. The goal of this study was to identify current education policy dispositions toward foreign faculty at the national and institutional levels in China. Findings indicate that within China’s higher education policy discourse, foreign faculty are identified as an advantage, and a source of conflict, ultimately having an ambiguous role as they attempt to manage their complicated status in Chinese higher education institutions. Foreign faculty are typically regarded as an international asset, accelerating global competitiveness and international rankings to enhance the acceleration of China’s higher education system. They are also considered controversial in relation to Chinese culture, values, and traditions. However, the most prevalent policy disposition explored in this study was that of vagueness and marginality, indicating underlying ambiguity toward foreign faculty. The study concludes with implications for future scholars and policymakers to consider.

Evidence accumulation has been the core component in recent development of perceptual and value-based decision-making theories. Most studies have focused on the evaluation of evidence between alternative options. What remains largely unknown is the process that prepares evidence: how may the decision-maker sample different sources of information sequentially, if they can only sample one source at a time? Here we propose a normative framework in prescribing how different sources of information should be sampled proactively to facilitate the decision process: beliefs for different noisy sources are updated in a Bayesian manner and participants can proactively allocate resource for sampling (i.e. saccades) among different sources to maximize the information gain in such process. We show that our framework can account for human participants’ actual choice and saccade behaviors in a two-alternative value-based decision-making task. Moreover, our framework makes novel predictions about the empirical eye movement patterns.

BackgroundExercise is increasingly recognized as a key component of Parkinson’s disease treatment strategies, but the underlying mechanism of how exercise affects PD is not yet fully understood.ObjectiveThe activation likelihood estimation method is used to study the mechanism of exercise affecting PD, providing a theoretical basis for studying exercise and PD, and promoting the health of patients with PD.MethodsRelevant keywords were searched on the PubMed, Cochrane Library, and Web of Science databases. Seven articles were finally included according to the screening criteria, with a total sample size of 97 individuals. Using the GingerALE 3.0.2 software, an ALE meta-analysis was performed using seven studies that met the requirements, and the probability of the cross-experiment activation of each voxel was calculated.ResultsThe meta-analysis produced seven clusters, and major activations were found in the cerebellum, occipital lobe, parietal lobe, and frontal lobe brain regions.ConclusionExercise for PD mainly results in the enhanced activation of the cerebellum, occipital lobe, parietal lobe, and frontal lobe. Exercise for PD does not cause a change in the activation of a single brain area, and the observed improvement may result from coordinated changes in multiple brain areas.

The biology major has developed rapidly in recent years. Biology is a science that penetrates every aspect of human life and is one of the core majors in most agricultural colleges and universities. However, many teachers lack practical experience in the subject. To overcome this problem, in recent years, we have been trying to introduce new reforms into our teaching. This article provides some insight into the way that biology majors have been reformed, which will help educators in agricultural colleges and universities. At present, teachers implement the “Industrial Innovation and Entrepreneurship Talent Cultivation” model, but it is not clear whether this helps biology majors to master the course and improve their practical skills. In this study, the IIETC model is outlined, and the academic achievement and satisfaction of students taught under the IIETC model are assessed. A T-test is used to examine potential differences between IIETC and traditional teaching models. In-depth interviews and questionnaires were given to two groups of students who followed different teaching models as part of an exploratory study. The aim was to explore how effective IIETC is at helping biology majors master the course and improve students’ wellbeing. Our results show that compared with traditional teaching methods, the IIETC model has a significant positive impact on the academic performance and happiness of biology students. Students trained under the IIETC model were more active and scored more highly in their final exams. They were more likely to feel that they had achieved success and happiness through the course. The outcomes of this research reveal a novel teaching reform that improved students’ enthusiasm for innovation and entrepreneurship during the ongoing COVID-19 pandemic. The effects are very encouraging and deserve further exploration and expansion in future work.

This study examines the key historical stages of the sustainable rural education policy development, including the stage of Rural Education Restoration and Adjustment Period (1979–1985); the stage of Comprehensive Reform Period of Rural Education (1985–2003); the stage of Rural Education Coordinated Development Period (2003–2018); and the stage of Rural Education Revitalization and Development Period (2018 to present). Along with the analysis, the policy characteristics of sustainable development of rural education policy in China concentrates on adhering to the unified leadership of the Party as the fundamental, adhering to the principle of comprehensive reform, adhering to the goal of serving rural development; adhere to promoting equity in education as the main task; and adhering to the construction of teachers as the key. In addition, policy problems on the sustainable development of rural education in China are also highlighted in this study. The conclusion and remarks are finally offered in the last.

Transportation cyber-physical systems are constrained by spatiality and real-time because of their high level of heterogeneity. Therefore, applications like traffic control generally manage moving objects in a single-machine multithreaded manner, whereas suffering from frequent locking operations. To address this problem and improve the throughput of moving object databases, we propose a GPU-accelerated indexing method, based on a grid data structure, combined with quad-trees. We count object movements and decide whether a particular node should be split or be merged on the GPU. In this case, bottlenecked nodes can be translated to quad-tree without interfering with the CPU. Hence, waiting time of other threads caused by locking operations raised by object data updating can be reduced. The method is simple while more adaptive to scenarios where the distribution of moving objects is skewed. It also avoids shortcomings of existing methods with performance bottleneck on the hot area or spending plenty of calculation resources on structure balancing. Experiments suggest that our method shows higher throughput and lower response time than the existing indexing methods. The advantage is even more significant under the skewed distribution of moving objects.