The Immune System as a Sensory System: Implications for Psychology

The brain and immune system form a bidirectional communication network in which the immune system operates as a sense organ to provide the brain with information about infection and injury, thereby allowing the brain to coordinate a defense. Activated immune cells release proteins called cytokines, which signal the brain by both blood and neural routes. Information that reaches the brain across this sensory channel produces large changes in neural activity, behavior, mood, and cognitive functioning. Appreciation of the functioning of this network may illuminate poorly understood aspects of stress, depression, and intraindividual variability in behavior, mood, and cognition.     

Stochastic pairwise comparative judgements and direct ratings of alternatives in the REMBRANDT system

The REMBRANDT system for multicriteria decision analysis consists of both the multiplicative variant of the AHP (which employs a method of pairwise comparative judgements by a decision maker to arrive at final impact scores for the alternatives under consideration) and SMART, the simple multiattribute rating technique (which utilizes direct rating of alternatives to achieve final impact scores). This paper examines the effect of imprecision or uncertainty in the decision maker's pairwise judgements or ratings of alternatives by expressing each pairwise judgement or rating as a probability distribution, and the structure of REMBRANDT's component models is exploited to derive interval judgements or interval ratings of the alternatives’ final impact scores. These interval judgements or interval ratings can be used to determine the probability of rank reversal amongst alternatives, i.e. to assess the stability of the final impact score vector. © 1998 John Wiley & Sons, Ltd.     

高质量中国特色社会心理服务体系建设要贯彻好“六个必须坚持”

建设高质量中国特色社会心理服务体系,既是助力实现“健康中国”的重要路径,也是推进新时代创新社会治理与治理能力现代化的重要举措与手段。党的二十大报告提出的“六个必须坚持”既为建设高质量中国特色社会心理服务体系工作指明了方向,又从方法论的高度深刻阐述了推进理论创新的科学方法和正确路径。本文论述了如何通过贯彻落实“六个必须坚持”开展高质量中国特色社会心理服务体系建设。     

Playing the Woman Card: Ambivalent Sexism in the 2016 U.S. Presidential Race

Late in the 2016 U.S. Presidential primary, Donald Trump attacked Hillary Clinton for playing the “woman’s card.” Theories of system justification suggest that attitudes about gender, particularly endorsement of hostile and benevolent sexism, likely shaped reactions to this campaign attack. Using a set of two studies, we find that hostile sexists exposed to the attack showed increased support for Trump and decreased support for Clinton. Benevolent sexists, however, reacted to Trump’s statements with increased support for Clinton, consistent with benevolent sexism’s focus on protecting women (Study 1). We further found that the woman card attack produced distinct emotional reactions among those with low and high levels of hostile and benevolent sexism. The attack also increased political participation among hostile sexists (Study 2). Our results offer new insights into the role of sexism in the 2016 presidential contest and further the discipline’s understanding of the gendered dimension of negative campaigning.     

Overt congruent facial reaction to dynamic emotional expressions in 9–10-month-old infants

The current study aimed to extend the understanding of the early development of spontaneous facial reactions toward observed facial expressions. Forty-six 9- to 10-month-old infants observed video clips of dynamic human facial expressions that were artificially created with morphing technology. The infants’ facial responses were recorded, and the movements of the facial action unit 12 (e.g., lip-corner raising, associated with happiness) and facial action unit 4 (e.g., brow-lowering, associated with anger) were visually evaluated by multiple naïve raters. Results showed that (1) infants make congruent, observable facial responses to facial expressions, and (2) these specific facial responses are enhanced during repeated observation of the same emotional expressions. These results suggest the presence of observable congruent facial responses in the first year of life, and that they appear to be influenced by contextual information, such as the repetition of presentation of the target emotional expressions.     

人类镜像系统参与音乐情绪的自动加工：来自EEG的证据

大脑中线电极诱发的μ抑制波(包括α和β频段)是人类镜像系统活动的电生理指标。尽管音乐情绪表现被认为是通过模仿个体的心理状态来实现的, 但是尚未有研究探讨人类镜像系统与音乐情绪加工的关系。本研究通过EEG技术, 采用跨通道情绪启动范式, 探究人类镜像系统是否参与和弦情绪的自动加工。愉悦或不愉悦的和弦启动情绪一致与不一致的目标面孔。行为结果显示, 被试对情绪一致面孔的反应显著快于情绪不一致面孔的反应。EEG结果显示, 在听觉刺激出现后的500~650 ms之间, 与情绪一致条件相比, 情绪不一致条件诱发了β频段的去同步化。在听觉刺激出现后的300~450 ms, 无论是情绪一致, 还是不一致条件, 都诱发了α频段的去同步化。源分析结果显示, μ抑制波主要出现在人类镜像系统的相关脑区。这些结果表明, 音乐情绪的自动加工与人类镜像系统的活动密切相关。     

Design and implementation of domain-specific cognitive system based on question similarity algorithm

The cognitive system is an artificial intelligence product that integrates natural language processing techniques. The biggest d on logical reasoning, which can help users improve exploration and accelerate discovery. On the basis of natural language processing and logical reasoning, the paper adopts similarity algorithm bas difference between big data analysis systems and cognitive systems is that cognitive systems can directly deal with the problems raised by natural language forms and provide predictions baseded on question sentences, designs a cognitive system for specific domains, and finally realizes it on the NAO robot platform.     

Bioinspired decision-making for a socially interactive robot

Nowadays, robots and humans coexist in real settings where robots need to interact autonomously making their own decisions. Many applications require that robots adapt their behavior to different users and remember each user’s preferences to engage them in the interaction. To this end, we propose a decision making system for social robots that drives their actions taking into account the user and the robot’s state. This system is based on bio-inspired concepts, such as motivations, drives and wellbeing, that facilitate the rise of natural behaviors to ease the acceptance of the robot by the users. The system has been designed to promote the human-robot interaction by using drives and motivations related with social aspects, such as the users’ satisfaction or the need of social interaction. Furthermore, the changes of state produced by the users’ exogenous actions have been modeled as transitional states that are considered when the next robot’s action has to be selected. Our system has been evaluated considering two different user profiles. In the proposed system, user’s preferences are considered and alter the homeostatic process that controls the decision making system. As a result, using reinforcement learning algorithms and considering the robot’s wellbeing as the reward function, the social robot Mini has learned from scratch two different policies of action, one for each user, that fit the users’ preferences. The robot learned behaviors that maximize its wellbeing as well as keep the users engaged in the interactions.     

Examining multiple feature evaluation and classification methods for improving the diagnosis of Parkinson’s disease

An accurate diagnosis of Parkinson’s disease by specialists involves many neurological, psychological and physical examinations. The specialists investigate a number of symptoms and signs when examining the nervous system conditions of a person. The diagnosis involves reviewing the medical history and genetic factor of the person. The recent diagnosis methodology to Parkinson’s disease relies on voice disorders analysis. This methodology entails extracting feature sets of a recorded person’s voice then utilizing a machine learning technique to identify the healthy and Parkinson’s cases from the voice. This paper attempts to improve the diagnoses of Parkinson’s disease by testing multiple feature evaluation and classification machine learning methods based on the voice disorders analysis. The aim of this paper is to find the optimal solution to the problem by (i) proposing a new Multiple Feature Evaluation Approach (MFEA) of a multi-agent system (ii) implementing five independent classification schemas which are Decision Tree, Naïve Bayes, Neural Network, Random Forests, and Support Vector Machine on the Parkinson’s diagnosis before and after applying the MFEA, and (iii) evaluating the diagnosis accuracy of the results. The methodology of the tests encompasses 10-fold cross-validation to evaluate the learning of methods and track variation in their performance. The test results show that the MFEA of the multi-agent system finds the best set of features and improves the performance of the classifiers. The average rate of improvement in the diagnostic accuracy of the classifiers are Decision Tree 10.51%, Naïve Bayes 15.22%, Neural Network 9.19%, Random Forests 12.75%, and Support Vector Machine 9.13%. These results show that the MFEA makes a significant improvement to the classifiers’ diagnosis results.     

Measuring driving workload of heavy vehicles at roundabouts

Correctly designed roundabouts proved to have positive safety and functional performances. However, they are also affected by peculiar disadvantages. In particular, they are difficult to manoeuvre, especially for heavy vehicle drivers. Despite these concerns, there are currently no driving workload metrics devoted to roundabouts.A novel methodological approach is proposed for trying to quantify workload impinging on heavy vehicle drivers when manoeuvring through complex at-grade intersections. Proper acquisition of input data constitutes the starting point for future research about ascertainment of workload for these particular road scenarios. The described procedure enables recording steering wheel angles performed by a driver when manoeuvring an articulated lorry through a complex at-grade intersection. A field trial was carried out for verifying the practical feasibility of proposed method in capturing driver’s steering behaviour. Dynamic data acquired via global navigation satellite system instrumentation were related to actual driver’s steering wheel behaviour captured by camera frames. As a complement to the experiment, selected steering behaviour metrics were calculated. Steering Entropy attributed a high difficulty level to the manoeuvres performed through the roundabout, whereas High Frequency Component and Steering Reversal Rate showed intensity and occurrences of driver’s corrections needed for controlling position of the semitrailer at the ring. It appears that even a single roundabout may represent an arduous task for drivers. The study concludes with recommendations for further research about workload imposed by roundabouts to heavy vehicle drivers, with special attention to successions of closely spaced roundabouts.