The Research on Consumer Behavior of Online Games and Its Influencing Factors

The purpose of this paper is to explore consumer behavior of online game and its influencing factors by the methods of literature review and questionnaire analysis. The results show that the monthly consumption of online games by respondents exceeds RMB150, and its daily game time is about 3 hours. And the cognitions on the advantages, disadvantages, quality advantages, and quality disadvantages of online game and individual variables of player are all significant influencing factors on consumer behavior of online game. This paper suggests that the government should actively help domestic online games to develop their derivatives and export, and companies should make the differentiated marketing strategies for the consumer groups which divided by their different individual variables

Accurate inverse design of Fabry–Perot-cavity-based color filters far beyond sRGB via a bidirectional artificial neural network

Structural color based on Fabry–Perot (F-P) cavity enables a wide color gamut with high resolution at submicroscopic scale by varying its geometrical parameters. The ability to design such parameters that can accurately display the desired color is therefore crucial to the manufacturing of F-P cavities for practical applications. This work reports the first inverse design of F-P cavity structure using deep learning through a bidirectional artificial neural network. It enables the production of a significantly wider coverage of color space that is over 215% of sRGB with extremely high accuracy, represented by an average Δ퐸2000 value below 1.2. The superior performance of this structural color-based neural network is directly ascribed to the definition of loss function in the uniform CIE 1976-Lab color space. Over 100,000 times improvement in the design efficiency has been demonstrated by comparing the neural network to the metaheuristic optimization technique using an evolutionary algorithm when designing the famous painting of “Haystacks, end of Summer” by Claude Monet. Our results demonstrate that, with the correct selection of loss function, deep learning can be very powerful to achieve extremely accurate design of nanostructured color filters with very high efficiency

Dataset for Accurate Inverse Design of Fabry–Pérot-Cavity-Based Color Filters far beyond sRGB via a Bidirectional Artificial Neural Network

Data to support article &quot;Accurate inverse design of Fabry&ndash;Perot-cavity-based color filters far beyond sRGB via a bidirectional artificial neural network&quot;. Peng Dai, Yasi Wang, Yueqiang Hu, C. H. de Groot, Otto Muskens, Huigao Duan, and Ruomeng Huang. PHOTONICS Research. 10.1364/PRJ.415141</span

Habitat Quality Assessment and Ecological Risks Prediction: An Analysis in the Beijing-Hangzhou Grand Canal (Suzhou Section)

With the fast pace of global urbanization, anthropogenic disturbances not only lead to frequent disasters, but also cause direct and indirect ecological and economic losses. To reduce the adverse effects of anthropogenic disturbances as part of sustainable ecosystem management, assessments of habitat quality and ecological risk are necessary. The objectives of this study are to analyze environmental conditions of the Beijing-Hangzhou Grand Canal (Suzhou section) for evaluating habitat quality and habitat degradation, and to conduct ecological-risk early warning assessment in this section. The Grand Canal is the longest and first canal in the world to be artificially excavated from natural rivers and lakes. By evaluating habitat quality using the InVEST suite of open-source software models for mapping and valuing the ecosystem, it was found that the natural lands with high habitat quality such as wetlands, forests and lakes along the Suzhou section of the Grand Canal have gradually decreased, while construction lands such as roads and buildings have gradually increased; there is a clear trend of decreasing areas with high habitat quality and increasing areas with low habitat quality, which is likely the result of urbanization. It was also found that the region has a high habitat degradation index, meaning that areas located at the junction of different land types are vulnerable to the surrounding environment due to narrow buffer zones that allow areas with high habitat quality to be easily affected by areas with low habitat quality. In terms of ecological risks, it was found that the natural land area with high habitat quality in the downstream locations was declining, thereby increasing the risks of pollution and flooding events while reducing the ecosystem’s resilience. The valuation model used in this study can be used as an effective decision-support tool to prioritize important ecological areas for conservation in the Grand Canal, and can also be adapted for use in the ecosystem management of other regions

Vitamin D receptor (VDR) on the cell membrane of mouse macrophages participates in the formation of lipopolysaccharide tolerance: mVDR is related to the effect of artesunate to reverse LPS tolerance

Abstract It is unclear whether membrane vitamin D receptor (mVDR) exists on the macrophage membrane or whether mVDR is associated with lipopolysaccharide (LPS) tolerance. Herein, we report that interfering with caveolae and caveolae-dependent lipid rafts inhibited the formation of LPS tolerance. VDR was detected as co-localized with membrane molecular markers. VDR was detected on the cell membrane and its level was higher in LPS-tolerant cells than that in only LPS treatment cells. Anti-VDR antibodies could abolish the effect of artesunate (AS) to reverse LPS tolerance, and the wild-type peptides (H397 and H305) of VDR, but not the mutant peptide (H397D and H305A), led to the loss of AS’s effect. AS decreased the mVDR level in LPS-tolerant cells. In vivo, AS significantly reduced VDR level in the lung tissue of LPS-tolerant mice. In summary, mVDR exists on the cell membrane of macrophages and is closely associated with the formation of LPS tolerance and the effects of AS. Video Abstrac

Habitat Quality Assessment and Ecological Risks Prediction: An Analysis in the Beijing-Hangzhou Grand Canal (Suzhou Section)

With the fast pace of global urbanization, anthropogenic disturbances not only lead to frequent disasters, but also cause direct and indirect ecological and economic losses. To reduce the adverse effects of anthropogenic disturbances as part of sustainable ecosystem management, assessments of habitat quality and ecological risk are necessary. The objectives of this study are to analyze environmental conditions of the Beijing-Hangzhou Grand Canal (Suzhou section) for evaluating habitat quality and habitat degradation, and to conduct ecological-risk early warning assessment in this section. The Grand Canal is the longest and first canal in the world to be artificially excavated from natural rivers and lakes. By evaluating habitat quality using the InVEST suite of open-source software models for mapping and valuing the ecosystem, it was found that the natural lands with high habitat quality such as wetlands, forests and lakes along the Suzhou section of the Grand Canal have gradually decreased, while construction lands such as roads and buildings have gradually increased; there is a clear trend of decreasing areas with high habitat quality and increasing areas with low habitat quality, which is likely the result of urbanization. It was also found that the region has a high habitat degradation index, meaning that areas located at the junction of different land types are vulnerable to the surrounding environment due to narrow buffer zones that allow areas with high habitat quality to be easily affected by areas with low habitat quality. In terms of ecological risks, it was found that the natural land area with high habitat quality in the downstream locations was declining, thereby increasing the risks of pollution and flooding events while reducing the ecosystem’s resilience. The valuation model used in this study can be used as an effective decision-support tool to prioritize important ecological areas for conservation in the Grand Canal, and can also be adapted for use in the ecosystem management of other regions