X. Wang

In the automatic detection of epileptic seizures, the monitoring of critically ill patients with time varying EEG signals is an essential procedure in intensive care units. There is an increasing interest in using EEG analysis to detect seizure, and in this study we aim to get a better understanding of how to visualize the information in the EEG time-frequency feature, and design and train a novel random forest algorithm for EEG decoding, especially for multiple-levels of illness. Here, we propose an automatic detection framework for epileptic seizure based on multiple time-frequency analysis approaches; it involves a novel random forest model combined with grid search optimization. The short-time Fourier transformation visualizes seizure features after normalization. The dimensionality of features is reduced through principal component analysis before feeding them into the classification model. The training parameters are optimized using grid search optimization to improve detection performance and diagnostic accuracy by in the recognition of three different levels epileptic of conditions (healthy subjects, seizure-free intervals, seizure activity). Our proposed model was used to classify 500 samples of raw EEG data, and multiple cross-validations were adopted to boost the modeling accuracy. Experimental results were evaluated by an accuracy, a confusion matrix, a receiver operating characteristic curve and an area under the curve. The evaluations indicated that our model achieved the more effective classification than some previous typical methods. Such a scheme for computer-assisted clinical diagnosis of seizures has a potential guiding significance, which not only relieves the suffering of patient with epilepsy to improve quality of life, but also helps neurologists reduce their workload.

Judges tend to discount the opinions of others even though advice is often helpful in improving their accuracy. The present research proposes that this phenomenon of advice discounting results from the judges’ confidence in their initial decision and little trust in advice. Furthermore, the degree of advice discounting may be predicted by the combined roles of confidence and trust. Three studies provide evidence for these hypotheses. Participants were very confident in their initial estimation and had little trust in the advice (study 1). The degree of advice discounting decreased when participants felt less confidence in performing difficult tasks compared with easy tasks (study 2) or when participants placed more trust in advice because the advice was from an expert rather than from a novice (study 3). In addition, confidence and trust predicted the degree of advice discounting across three studies. These findings shed new light on the mechanism underlying advice discounting and advice taking by indicating the combined roles of confidence and trust.

This study examined the extent to which the impact of green transformational leadership on employee green behavior through follower perceptions of value congruence. Path analyzing on data from 193 subordinate-leader dyads showed that followers’ value congruence with their leader mediated the effects of green transformational leadership on employee green behavior. Results also supported that green identity moderated the indirect effect of green transformational leadership on employee green behavior through value congruence, such that the indirect effect was more positive when green identity was high than when it was low. These findings provided valuable contribution to green transformational leadership, value congruence and employee green behavior by exploring the relationship between them. Practical implications and directions for future research are also discussed.

Unlike other creatures, humans developed the ability to cooperate with genetically unrelated strangers and a tendency to comply with social norms. However, humans deviate from social norms in various situations. This study used the modified ultimatum game to explore why humans deviate from social norms and how their prosocial behavior can be promoted. In Study 1, participants were asked to imagine working with an anonymous counterpart to complete a task and obtain a certain amount of money (e.g., ¥10). The computer divided the money randomly in favor of the participant (e.g., 9:1 or 8:2). Participants should decide whether to accept or reject such a self-benefiting division. In the non-risk condition, an absolutely fair redivision of money would take place if participants reject self-benefiting division (e.g. 5:5 or 6:4). By contrast, in the risk condition, other-benefiting redivision of money (e.g., 1:9 or 2:8) would take place if participants rejected the self-benefiting division. Results involving 40 college students showed the main effect of condition. The frequency of accepting self-benefiting division in the risk condition was higher than that in the non-risk condition. As such, compliance with social norms is based on the preservation of material resources. In Study 2, we used economic or moral rewards to compensate for economic loss following compliance with the norm. Results involving 28 college students revealed a significant effect of compensation. The rewards, including moral praise, effectively decreased selfish choices. These findings extend previous studies on social norm compliance by emphasizing the importance of internal, fairness-based balance between material and moral needs, as well as the role of moral praise in promoting prosocial behavior.

While robots were traditionally built to achieve economic efficiency and financial profits, their roles are likely to change in the future with the aim to provide social support and companionship. In this research, we examined whether the robot’s proposed function (social vs. economic) impacts judgments of mind and moral treatment. Studies 1a and 1b demonstrated that robots with social function were perceived to possess greater ability for emotional experience, but not cognition, compared to those with economic function and whose function was not mentioned explicitly. Study 2 replicated this finding and further showed that low economic value reduced ascriptions of cognitive capacity, whereas high social value resulted in increased emotion perception. In Study 3, robots with high social value were more likely to be afforded protection from harm, and such effect was related to levels of ascribed emotional experience. Together, the findings demonstrate a dissociation between function type (social vs. economic) and ascribed mind (emotion vs. cognition). In addition, the two types of functions exert asymmetric influences on the moral treatment of robots. Theoretical and practical implications for the field of social psychology and human-computer interaction are discussed.

D. Davidson argues that the existence of alternative conceptual schemes presupposes the Kantian scheme-content dualism, which requires a scheme-neutral empirical content and a fixed, sharp schemecontent distinction. The dismantlement of such a Kantian scheme-content dualism, which Davidson calls “the third dogma of empiricism”, would render the notion of alternative conceptual schemes groundless. To counter Davidson’s attack on the notion of alternative conceptual schemes, I argue that alternative conceptual schemes neither entail nor presuppose the Kantian scheme-content dualism. On the contrary, it is exactly the abandonment of the concept-neutral content and the denial of a fixed, absolute scheme-content distinction that turns the Kantian conceptualabsolutism upside down and thus makes alternative conceptual schemes possible. Proposing common-sense experience as the empirical content of alternative schemes, I construct and defend a non-Kantian scheme-content dualism based on a non-fixed, relative scheme-content distinction. The proposed non-Kantian scheme-content dualism is not only “innocent” enough to be immune from Davidson’s charge of the third dogma of empiricism, but also “solid” enough to be able to sustain alternative conceptual schemes. I conclude that in terms of our conceptual schemes, we are connected to the world as closely as possible; only through conceptual schemes can we be connected to the world.

A survey study was conducted to look into the effect of Confucian ethics and the psychological foundations of morality on business managers' perspectives on corporate social responsibility (CSR). Using responses from 393 Chinese managers, we first conducted confirmatory factor analysis to assess the reliability and validity of the measurement model and then employed hierarchical regression to explore the relationships among Confucian ethics, moral foundations, and managers' shareholder value perspectives. The results indicate that both Confucian ethics and managers' moral foundations had significant influence on shareholder value perspectives. In fact, moral foundations and Confucian ethics interacted and jointly affected managers' positions on the shareholder value model of corporate responsibility. This study demonstrates the importance of psychological foundations of morality to managers' CSR orientations and substantiates the persistent impact of Confucian ethics/cultural traditions on today' business practices.

The members of the International Network for the Analysis of Intergenerational Relations proudly present the most recent issue of the jointly produced compendium "Generations, Intergenerational Relations and Generational Policy". This new version includes 17 languages: English, French, German, Italian, Spanish, Polish, Portuguese, Swedish, Hungarian, Turkish, Romanian, Lithuanian, Slovenian, Bosnian, Ukrainian, Russian and Chinese. The layout of the compendium is designed for using it to translate the specific concepts and terminology of research on generations and intergenerational relations from one language into another. **** K. Lüscher, A. Klimczuk, Generations, intergenerational relationships, generational policy: A multilingual compendium, 17 languages, Universität Konstanz, Konstanz 2017, 428pp.