摘要：
Enhancing the stability and durability of superhydrophobic wood remains a significant challenge for its long-term application in various fields. This study presents a novel approach to developing durable superhydrophobic wood by regulating wood structure. The analyses of the mechanism revealed that Si-Ti@PDMS prepolymer infiltrated wood’s pores and cell walls, forming a highly cross-linked micro-nanoscale superhydrophobic coating extending from the exterior to the interior. The resulting superhydrophobic wood exhibited excellent hydrophobic characteristics on both its surface and various cutting surfaces. Furthermore, the water contact angles (WCA) measured on the various cut surfaces of the wood consistently exceeded 150°, thereby confirming its superhydrophobicity. Additionally, the water contact angles (WCA) at wood depth surfaces remained above 130°. This observation indicates that the non-wettability characteristic of the superhydrophobic wood extends from the surface to the interior. Consequently, even in the event of surface structural damage, the wood retains its robust hydrophobic performance. This study provides a theoretical foundation for regulating durable superhydrophobic wood, and it was beneficial to the efficient use of superhydrophobic wood in construction and furniture fields.
Enhancing the stability and durability of superhydrophobic wood remains a significant challenge for its long-term application in various fields. This study presents a novel approach to developing durable superhydrophobic wood by regulating wood structure. The analyses of the mechanism revealed that Si-Ti@PDMS prepolymer infiltrated wood’s pores and cell walls, forming a highly cross-linked micro-nanoscale superhydrophobic coating extending from the exterior to the interior. The resulting superhydrophobic wood exhibited excellent hydrophobic characteristics on both its surface and various cutting surfaces. Furthermore, the water contact angles (WCA) measured on the various cut surfaces of the wood consistently exceeded 150°, thereby confirming its superhydrophobicity. Additionally, the water contact angles (WCA) at wood depth surfaces remained above 130°. This observation indicates that the non-wettability characteristic of the superhydrophobic wood extends from the surface to the interior. Consequently, even in the event of surface structural damage, the wood retains its robust hydrophobic performance. This study provides a theoretical foundation for regulating durable superhydrophobic wood, and it was beneficial to the efficient use of superhydrophobic wood in construction and furniture fields.
摘要：
In order to enhance the satisfaction of pop music personalised recommendation and improve the accuracy and efficiency of pop music personalised recommendation, a pop music personalised recommendation method based on machine learning is proposed. Firstly, the relevant theories of machine learning and short-term and long-term memory artificial neural networks are studied, and then the popular music word vector is extracted by using softmax function, and the collaborative filtering algorithm with weighting factor is introduced to calculate the similarity of popular music word vector. Finally, based on the LSTM network, a pop music personalised recommendation model is constructed to realise pop music personalised recommendation. Experiments show that the method proposed in this paper has a personalised recommendation satisfaction index of 97.8% for pop music, the recommendation time is only 19.4s, and the average value of MAPE and RMSE are only 0.037 and 0.039 respectively. The recommendation accuracy, satisfaction and efficiency are high, and the design purpose can be achieved.
期刊：
FRONTIERS IN PSYCHOLOGY,2022年13:880179 ISSN：1664-1078
通讯作者：
Yang, P.
作者机构：
[Yang, Yong] Hunan City Univ, Coll Art, Yiyang, Peoples R China.;[Yang, Pingzhan] Hunan Normal Univ, Sch Educ Sci, Changsha, Peoples R China.
通讯机构：
[Yang, P.] S;School of Educational Science, China
关键词：
Normalization of COVID-19 pandemic;Academic stress;Psychological Capital;anxi ety;college students
摘要：
<jats:p>Based on the background of the continuous development of COVID-19 pandemic, the effect of academic stress on anxiety of college students, as well as the mediating and moderating role of psychological capital are discussed, so as to provide intervention measures for reducing the academic stress and anxiety level of college students during the pandemic. The study used the Academic Stress Scale, the Psychological Capital Scale and the Anxiety Scale to conduct a questionnaire survey on 280 college students in five colleges and universities in Northern Hunan, and obtained 229 valid questionnaires. The data analysis results show that there are differences in academic stress between different genders, and differences in the variable of psychological capital among college students of different grades; Whether he is a student leader and whether he has won a scholarship, the difference of this factor in the three variables of academic stress, psychological capital and anxiety.is not statistically significant. The results of this study showed that psychological capital significantly negatively predicted anxiety (β = −0.602, t = −9.702, <jats:italic>p</jats:italic> &lt; 0.001), academic stress significantly positively predicted anxiety (β = 0.247, t = 5.462, p &lt; 0.001), psychological capital played a partial mediating role between academic stress and anxiety, and psychological capital also had a certain moderating role between academic stress and anxiety (β = −0.15, t = −4.51, <jats:italic>p</jats:italic> &lt; 0.001). The conclusion of the study is that in the context of the continuous development of COVID-19 pandemic, positive psychological capital can effectively reduce the anxiety caused by academic stress. This result suggests that the positive psychological capital state of college students should be improved, which can effectively relieve pressure and reduce anxiety.</jats:p>
期刊：
International Journal of Arts and Technology,2022年14(1):40-55 ISSN：1754-8853
通讯作者：
Yang, Ting(tingyang5@mls.sinanet.com)
作者机构：
[Hua Jiang] College of Art, Hunan City University, Yiyang;413000, China;[Ting Yang] Art Design Institute Porcelain College, Hunan Vocational College of Science and Technology, Changsha;410004, China;[Hua Jiang] 413000, China
通讯机构：
[Yang, T.] A;Art Design Institute Porcelain College, China
关键词：
CNN;convolution neural network;deep hash coding;feature extraction;paintings;style features
