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293 results on '"Song, Xiaowen"'

67. An adaptive activation energy method for predicting resin curing behavior and thermal overshoot in thick CFRP plates.

Author

Chen, Qisen, Ye, Yaoyao, Li, Hao, Zhang, Fan, Xu, Qiang, Song, Xiaowen, and Ke, Yinglin

Subjects
LAMINATED materials, ACTIVATION energy, CURING, COMPOSITE plates, POLYMERIC composites
Abstract

This study concerns the importance of curing kinetic models for the prediction accuracy of the thermal overshoot in the curing process of thick polymeric composite plates. An adaptive activation energy (AAE) method was proposed to determine an accurate curing kinetic model with adaptive activation energy (CK‐AAE). Then the temperature field model of the autoclave curing process was established based on the CK‐AAE equations for predicting the curing thermal overshoot of thick polymer‐matrix composite plates. The prediction accuracy of the curing degree using the CK‐AAE model was improved greatly compared with the common curing kinetic models. And the predicted curing thermal overshoot of thick polymeric composite plates yielded good agreement with the measured results from the autoclave curing experiments. Moreover, it was observed that the curing thermal overshoot was more susceptible to the laminate thickness and less affected by the stacking sequence. [ABSTRACT FROM AUTHOR]

Published
2023
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68. 3D printing of liquid crystal elastomers-based actuator for an inchworm-inspired crawling soft robot

Author

Song, Xiaowen, Zhang, Weitian, Liu, Haoran, Zhao, Limeng, Chen, Qi, and Tian, Hongmiao

Subjects
Artificial Intelligence, Computer Science Applications
Abstract

Liquid crystal elastomers (LCEs) have shown great potential as soft actuating materials in soft robots, with large actuation strain and fast response speed. However, to achieve the unique features of actuation, the liquid crystal mesogens should be well aligned and permanently fixed by polymer networks, limiting their practical applications. The recent progress in the 3D printing technologies of LCEs overcame the shortcomings in conventional processing techniques. In this study, the relationship between the 3D printing parameters and the actuation performance of LCEs is studied in detail. Furthermore, a type of inchworm-inspired crawling soft robot based on a liquid crystal elastomeric actuator is demonstrated, coupled with tilted fish-scale-like microstructures with anisotropic friction as the foot for moving forwards. In addition, the anisotropic friction of inclined scales with different angles is measured to demonstrate the performance of anisotropic friction. Lastly, the kinematic performance of the inchworm-inspired robot is tested on different surfaces.

Published
2022

80. MiR‐3017b contributes to metamorphosis by targeting sarco/endoplasmic reticulum Ca2+ATPase in Tribolium castaneum.

Author

Tang, Jing, Zhai, Mengfan, Yu, Runnan, Song, Xiaowen, Feng, Fan, Gao, Han, and Li, Bin

Subjects
RED flour beetle, ENDOPLASMIC reticulum, INSECT metamorphosis, RNA regulation, NUCLEOTIDE sequencing, METAMORPHOSIS
Abstract

In recent years, increasing numbers of microRNAs (miRNAs) have been reported to regulate insect metamorphosis. One thousand, one hundred fifty‐four miRNAs have been previously identified from Tribolium castaneum by high‐throughput sequencing; however, little is known about which miRNAs can participate in metamorphosis, leaving the role of miRNAs in regulating the underlying mechanism elusive. Here, we report the participation of miR‐3017b in the metamorphosis of T. castaneum. Temporal profiles revealed that miR‐3017b was highly expressed at the late larval stage, but significantly decreased at the early pupal stage. Overexpression of miR‐3017b caused larval to pupal to adult metamorphosis arrested. Dual‐luciferase reporter assay and miRNA–mRNA interaction assay illustrated that miR‐3017b interacts with the coding sequence of sarco/endoplasmic reticulum Ca2+ ATPase (SERCA) and suppresses its expression. Knockdown of SERCA caused metamorphosis arrested, similar to that observed in miR‐3017b overexpression beetles. Further functional mechanism analyses revealed that 20‐hydroxyecdysone application downregulates miR‐3017b and up‐regulates SERCA expression. The expression level of downstream genes in the 20E pathway was disrupted after overexpressing miR‐3017 and the knockdown of SERCA. These results provided evidence miR‐3017b‐SERCA contributes to metamorphosis by regulating the 20E pathway in T. castaneum. It could advance our understanding of the coordination of 20E and miRNA regulation in insect metamorphosis. [ABSTRACT FROM AUTHOR]

Published
2022
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97. A Method to Inspect the Implementation of Electricity Price Based on Deep Learning Variational Autoencoder

Author

Zhang Ye, Ye Ning, Gao Xiying, Hui Qian, Zhang Wenshu, Wang Haomiao, Guan Yan, Li Dan, Song Xiaowen, Cai Yingkai, and Jinchun Song

Subjects
Measure (data warehouse), Electricity price, business.industry, Computer science, 020209 energy, Deep learning, Probabilistic logic, 02 engineering and technology, computer.software_genre, Autoencoder, Power (physics), Feature (computer vision), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Anomaly detection, Data mining, Artificial intelligence, business, computer
Abstract

In this paper, we propose a method for performing electricity price execution inspection by using a variational autoencoder technology in deep learning. The variational auto encoder based anomaly detection algorithm(VABAD) can be used both as a discriminant model and as a feature of the generation model, which effectively solves the calculation problem of multiple heterogeneous parameters of current electricity price inspection implementation. The reconstruction probability is a probabilistic measure that takes into account the variability of the distribution of variables. It is used by autoencoder based anomaly detection methods. Experimental results show that the proposed method has been validated and compared to the existing approaches. The databases used in this paper come from Power Marketing System that occurred in Liaoning, China in 2015.

Published
2018

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