Previous behavioral studies have identified the significant role of subliminal cues in creative problem solving. However, neural mechanisms of such unconscious processing remain poorly understood. Here we utilized an event-related potential approach and sandwich mask technique to investigate cerebral activities underlying the unconscious processing of cues in creative problem solving. College students were instructed to solve divergent problems under three different conditions . Our data showed that creative problem solving can benefit from unconscious cues, although not as much as from (...) conscious cues. More importantly, we found that there are crucial ERP components associated with unconscious processing of cues in solving divergent problems. Similar to the processing of conscious cues, processing unconscious cues in problem solving involves the semantic activation of unconscious cues in the right inferior parietal lobule , new association formation in the right parahippocampal gyrus , and mental representation transformation in the right superior temporal gyrus . The present results suggest that creative problem solving can be modulated by unconscious processing of enlightening information that is weakly diffused in the semantic network beyond our conscious awareness. (shrink)

In the big data era, sequencing technology has produced a large number of biological sequencing data. Different views of the cancer genome data provide sufficient complementary information to explore genetic activity. The identification of differentially expressed genes from multiview cancer gene data is of great importance in cancer diagnosis and treatment. In this paper, we propose a novel method for identifying differentially expressed genes based on tensor robust principal component analysis, which extends the matrix method to the processing of multiway (...) data. To identify differentially expressed genes, the plan is carried out as follows. First, multiview data containing cancer gene expression data from different sources are prepared. Second, the original tensor is decomposed into a sum of a low-rank tensor and a sparse tensor using TRPCA. Third, the differentially expressed genes are considered to be sparse perturbed signals and then identified based on the sparse tensor. Fourth, the differentially expressed genes are evaluated using Gene Ontology and Gene Cards tools. The validity of the TRPCA method was tested using two sets of multiview data. The experimental results showed that our method is superior to the representative methods in efficiency and accuracy aspects. (shrink)

Public information is a social resource that connects all aspects of social life, regulates social activities and public behaviors, and plays a very important role in influencing public trust. Based on the perspective of communication, we divide the government into two ways to release public information, that is, mass communication and personalized recommendation. Moreover, the public can choose to acquire or not acquire a strategy. Then, this study conducts an evolutionary game between the government and the public to analyze the (...) influence of public information on the public in China. Our objective is to find how the evolutionary path changes between the two players when strategies are changing. Then, a simulation analysis is presented in six scenarios to illustrate the results. The results show that the two players can converge to different stable statuses under different situations. (shrink)

The purpose of the study was to solve the problem of the mismatching between the supply and demand of the talents that universities provide for society, whose major is communication design. The correlations between social post demand and university cultivation, as well as between social post demand and the demand indexes of enterprises for posts, are explored under the guidance of University-Industrial Research Collaboration. The backpropagation neural network is used, and the advantages of the Seasonal Autoregressive Integrated Moving Average model (...) model are combined to design the SARIMA-BPNN model after the relevant parameters are adjusted. Through the experimental analysis, it is found that the error of the root mean square of the designed SARIMA-BP model in post prediction is 7.523 and that of the BPNN model is 16.122. The effect of the prediction model that was designed based on deep learning is smaller than that of the previous model based on the neural network, and it can predict future posts more accurately for colleges and universities. Guided by the “University-Industrial Research Collaboration,” students will have more practice in the teaching process in response to social needs. “University-Industrial Research Collaboration” guides the teaching direction for communication design majors and can help to cultivate communication design talents who are competent for the post provided. (shrink)