This article conducts a mixed-method content analysis of Chinese and American news media coverage of Google DeepMind’s Go playing computer program, AlphaGo. Drawing on humanistic approaches to artificial intelligence, combined with an empirically rigorous content analysis, it examines the differences and overlap in coverage by the Chinese and American press in their accounts of AlphaGo, and its historic match with Korea’s Lee Sedol in March, 2016. The event was not only followed intensely in China, but also made the front page (...) of The New York Times. This article finds that the Chinese press was more likely than the American press to frame AlphaGo as non-threatening, which the authors attribute to cultural differences and the two countries' different understandings of Go. In addition to quantitatively identifying similarities and differences in the framing of AlphaGo, this paper also investigates the underlying and evolving contestations over what constitutes the “human” and the “machine.” It concludes by discussing the implications of the study’s findings as well as outlining avenues for further research. (shrink)

Cross-sector relationship building is an important strategy in corporate social responsibility initiatives, and communicating cross-sector relationships on social media can help raise the visibility of collaborative relationships. A noticeable gap in the literature is how social media enables and constrains the formation patterns of cross-sector connections. To understand how businesses communicate their relationships with government agencies and nonprofits about social issues on social media, we propose a theoretical framework that centers public attention as a critical resource and considers different sectors' (...) interests in the COVID-19 issue. We tested this framework with a nationally representative sample of 1,980 organizations on Twitter. The analysis reveals that the increase in public attention to the COVID-19 issue was accompanied by a greater likelihood of cross-sector ties. Specifically, firms severely affected by COVID-19 were more likely to build ties with government agencies, and the increase in public attention also drove firms to build more ties with nonprofits, especially advocacy nonprofits. Our findings suggest managers of social media communication should observe the volatile public attention and design communicative strategies accordingly. (shrink)

Eye-tracking technology has become a powerful tool for biomedical-related applications due to its simplicity of operation and low requirements on patient language skills. This study aims to use the machine-learning models and deep-learning networks to identify key features of eye movements in Alzheimer's Disease (AD) under specific visual tasks, thereby facilitating computer-aided diagnosis of AD. Firstly, a three-dimensional (3D) visuospatial memory task is designed to provide participants with visual stimuli while their eye-movement data are recorded and used to build an (...) eye-tracking dataset. Then, we propose a novel deep-learning-based model for identifying patients with Alzheimer's Disease (PwAD) and healthy controls (HCs) based on the collected eye-movement data. The proposed model utilizes a nested autoencoder network to extract the eye-movement features from the generated fixation heatmaps and a weight adaptive network layer for the feature fusion, which can preserve as much useful information as possible for the final binary classification. To fully verify the performance of the proposed model, we also design two types of models based on traditional machine-learning and typical deep-learning for comparison. Furthermore, we have also done ablation experiments to verify the effectiveness of each module of the proposed network. Finally, these models are evaluated by four-fold cross-validation on the built eye-tracking dataset. The proposed model shows 85% average accuracy in AD recognition, outperforming machine-learning methods and other typical deep-learning networks. (shrink)

Objective: To investigate the prevalence of and risk factors associated with mental health symptoms in psychiatric outpatients and their family members in China during the COVID-19 pandemic.Methods: This cross-sectional, survey-based, region-stratified study collected demographic data and mental health measurements for depression, anxiety and acute stress from 269 psychiatric patients and 231 family members in the Second Xiangya Hospital in China from April 27, 2020 to May 8, 2020. Binary logistic regression analysis was performed to identify risk factors associated with mental (...) health outcomes.Result: The results of this survey revealed that symptoms of depression, anxiety, and acute stress were highly prevalent symptoms in the psychiatric patient group. Respondents who were female, unmarried or highly educated were significantly more likely to have the above symptoms. In the family member group, more than half of them felt that the burden of nursing had increased during the epidemic. Subjects with a high degree of burden of care were significantly more likely to exhibit the above mental health symptoms, while females were significantly more likely to have acute stress.Conclusions: The results of this survey revealed a high prevalence of mental health disorder symptoms among psychiatric patients and an increased burden of nursing among their family members after the COVID-19 outbreak in China. Understanding the risk factors in those particular groups of people help improve the public health service system for mental health problems during public health events. For further study, exploration of the needs of mental health services and dynamic change tracking will be needed. (shrink)

This article depicts the dynamic demonstrations of religions in late imperial and republican Jining. It argues with evidences that the open, tolerant and advanced urban circumstances and atmosphere nurtured the diversity and prosperity of formal religions in Jining in much of the Ming and Qing periods. It also argues that the same air and ethos enabled Jining to less difficultly adapt to the West-led modern epoch, with a notable result of welcoming Christianity, quite exceptional in hinterland China.

王阳明(1472~1528),我国明代最重要的哲学家、政治家和教育家。本书以王阳明的生平经历为经,以其思想理论为纬,介绍了他一生各个时期的活动和政治、军事、教育等思想及其心路历程,肯定了他在思想史上的 作用。.

The complexity of language is usually reflected in the complexity of sentences. At present, the research of sentence complexity mainly focuses on the analysis of syntactic complexity. In this paper, from the perspective of Leech's theory of sentence semantic structure, the predication structure is taken as the semantic unit to explore the sentence semantic complexity. The predication structures are extracted based on the result of sentence-based syntactic analysis, and then the linear expression sequence of a sentence is converted into a (...) semantic hierarchy based on predicate semantic frameworks; the universality of predicate semantic frameworks is obtained by using the spectral clustering algorithm; and the sentence semantic complexity depends on the universality of predicate semantic frameworks at various layers. The experimental results show that the measurement method of sentence sematic complexity based on predicate semantic frameworks is more effective by comparing with the method that only considers the semantic categories of words in the sentence. (shrink)