Wang Shuo

Given the cultural significance of the Silver Age religious renaissance in the history of Russian thought, it is important to examine how contemporary Russian philosophers, amidst increasing academic specialization, approach and categorize indigenous religious philosophy from this period. This article investigates contemporary Russian philosophical research and its evaluations of Sergei Nikolayevich Bulgakov, a key Silver Age figure. This study finds that, following the surge in research during the 1990s, Russian scholars have maintained consistent interest in Bulgakov. However, within the discipline of philosophy these researchers may still be facing some structural problems. Bulgakov’s philosophical and theological ideas are intrinsically linked, which makes it difficult to pinpoint his disciplinary orientation. Researchers have been obliged to adjust their approaches to overcome misunderstandings. Not only philosophy of language but also philosophy of science and technology have been influenced by this new interest in Bulgakov. The overall trend in the examination of Bulgakov’s intellectual legacy has been toward careful and balanced deliberation and analysis.

A hierarchical and compositional representation is an essential requirement for an image model effectively to represent many instances with huge complexity arising from varying geometric configurations and appearance types. In this chapter, we introduce a model, hierarchical tiling by And-Or Tree, which capitalizes on hierarchical region decomposition and region tiling to generate an exponential number of configurations with a small dictionary. We also describe an iterative learning algorithm automatically to learn the parts and their structures in a weakly supervised fashion. The proposed model and approach has been applied to two important image domains: natural scene categories and human figures. We present various experimental results to demonstrate advantages of our model in both cases.

Different styles of social interaction are one of the core characteristics of autism spectrum disorder. Social differences among individuals with ASD often include difficulty in discerning the emotions of neurotypical people based on their facial expressions. This review first covers the rich body of literature studying differences in facial emotion recognition in those with ASD, including behavioral studies and neurological findings. In particular, we highlight subtle emotion recognition and various factors related to inconsistent findings in behavioral studies of FER in ASD. Then, we discuss the dual problem of FER – namely facial emotion expression or the production of facial expressions of emotion. Despite being less studied, social interaction involves both the ability to recognize emotions and to produce appropriate facial expressions. How others perceive facial expressions of emotion in those with ASD has remained an under-researched area. Finally, we propose a method for teaching FER [FER teaching hierarchy ] based on recent research investigating FER in ASD, considering the use of posed vs. genuine emotions and static vs. dynamic stimuli. We also propose two possible teaching approaches: a standard method of teaching progressively from simple drawings and cartoon characters to more complex audio-visual video clips of genuine human expressions of emotion with context clues or teaching in a field of images that includes posed and genuine emotions to improve generalizability before progressing to more complex audio-visual stimuli. Lastly, we advocate for autism interventionists to use FER stimuli developed primarily for research purposes to facilitate the incorporation of well-controlled stimuli to teach FER and bridge the gap between intervention and research in this area.

This policy-capturing study, conducted in China, investigated the cognitive basis of managerial decisions to make a corporate charitable donation, a global issue in the context of corporate social responsibility research and practice. Participants responded to a series of scenarios manipulating pressure from the five stakeholders most commonly addressed by CSR research. The independent variables examined included organizational factors and the participants’ personal values. Results indicate a large positive effect of shareholder and governmental pressure on the decision with lesser positive effects from customers and competitors. Surprisingly, employee pressure had a negative effect on the decision to make a charitable donation. Further, personal values and perceived CEO attitudes toward charity were significantly related to the decisions participants made. In line with our theorizing, the findings indicate that a combination of personal, organizational, and institutional factors was salient in the minds of decision makers

Facial expressions of emotion play an important role in human social interactions. However, posed expressions of emotion are not always the same as genuine feelings. Recent research has found that facial expressions are increasingly used as a tool for understanding social interactions instead of personal emotions. Therefore, the credibility assessment of facial expressions, namely, the discrimination of genuine (spontaneous) expressions from posed (deliberate/volitional/deceptive) ones, is a crucial yet challenging task in facial expression understanding. With recent advances in computer vision and machine learning techniques, rapid progress has been made in recent years for automatic detection of genuine and posed facial expressions. This paper presents a general review of the relevant research, including several spontaneous vs. posed (SVP) facial expression databases and various computer vision based detection methods. In addition, a variety of factors that will influence the performance of SVP detection methods are discussed along with open issues and technical challenges in this nascent field.