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Hao Fang,Chaofeng Li,Jiajia Zhao,Chen Zhao 한국생물공학회 2021 Biotechnology and Bioprocess Engineering Vol.26 No.4
Cellulase has the biggest contribution to the high production costs of lignocellulose bioconversion and the substantial decrease of its production cost is the key to the commercialization of lignocellulosic biorefineries. Trichoderma reesei has the most robust cellulase among the candidates, which therefore is widely used for cellulase production in industry. This is not because of the size of its cellulase gene pool but its prodigious cargo of cellulase productivity. Still, T. reesei cellulase falls far short of perfection in real-world applications, especially for the composition. This review summarized the biotechnological advances in engineering T. reesei for enhanced cellulase production. Meanwhile, we proposed innovative ideas of systematically optimizing cellulase composition at the transcriptional level and improving cellulase production at the regulation level. Efficient genome editing is essential to achieving that target. Thus, the developments of the tools of multiple gene manipulations were discussed in detail here. This review provides ideas and/or inspirations to the future researches on T. reesei cellulase.
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False Information Diffusion in Public Crisis on Interpersonal Network and Intervention Strategies
Zhu Xiaoxia,Hao Jiajia,Hu Haiju 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.10
With the development of economy, the public crisis has been increasing frequently and false information took shape because of the public’s assentation and lack of recognition. The diffusion of false information has intensified the public panic and anxiety. Beside, it may cause secondary damage easily. Therefore, the management department of false information in public crisis information should control the diffusion of the false information quickly in order to reduce the loss. By the diffusion of the network of false information in public crisis based on the scale-free network (BA), this paper defines the nature of each social individual from the perspective of multi-agent. On the basis of these properties, this paper defines the individual opinion interaction rules when communicating. The research concludes that active individuals of information diffusion on interpersonal network are not the people with a great amount of friends, but the ones who have few friends. Nevertheless, the management department of false information in public crisis should maintain a circuitous neutral attitude rather than the “all-or nothing” coercive measures when intervene the diffusion process of the false information diffusion. Besides, the influencing social individuals are the “opinion leaders” who have a wide range of interpersonal communication.
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Damage localization and quantification of a truss bridge using PCA and convolutional neural network
Xinqun Zhu,Jiajia Hao,Yang Yu,Chunwei Zhang,Jianchun Li 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.30 No.6
Deep learning algorithms for Structural Health Monitoring (SHM) have been extracting the interest of researchers and engineers. These algorithms commonly used loss functions and evaluation indices like the mean square error (MSE) which were not originally designed for SHM problems. An updated loss function which was specifically constructed for deep-learningbased structural damage detection problems has been proposed in this study. By tuning the coefficients of the loss function, the weights for damage localization and quantification can be adapted to the real situation and the deep learning network can avoid unnecessary iterations on damage localization and focus on the damage severity identification. To prove efficiency of the proposed method, structural damage detection using convolutional neural networks (CNNs) was conducted on a truss bridge model. Results showed that the validation curve with the updated loss function converged faster than the traditional MSE. Data augmentation was conducted to improve the anti-noise ability of the proposed method. For reducing the training time, the normalized modal strain energy change (NMSEC) was extracted, and the principal component analysis (PCA) was adopted for dimension reduction. The results showed that the training time was reduced by 90% and the damage identification accuracy could also have a slight increase. Furthermore, the effect of different modes and elements on the training dataset was also analyzed. The proposed method could greatly improve the performance for structural damage detection on both the training time and detection accuracy.
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Jia Yang,Jiajia Hao,Chen Tang,Yaxin Guo,Mingxin Guo,Zhipeng Li,Shuzheng Liu,Hui Yu,Gang Qin,Qiang Chen 한국공업화학회 2022 Journal of Industrial and Engineering Chemistry Vol.116 No.-
Although many hydrogels have been applied to wearable sensors, it is still challenging to simultaneouslyrealize hydrogels with optical transparency, superior mechanical properties, excellent sensing performance,and anti-freezing by using inexpensive raw materials and an easy preparation process. Herein,using ethylene glycol/H2O (EG/ H2O) as a solvent, poly(vinyl alcohol)/EG organohydrogel (PVA/EGOHG) was prepared by a simple heating and frozen-thawing method. Owing to the multifunctionalityof EG (i.e., physical cross-linker, anti-freezer and co-solvent), PVA/EG OHG demonstrated excellent integratedproperties, including high strength, high toughness, and anti-freezing performances. Besides, PVA/EG OHG also showed low friction, self-cleaning, and frost resistance properties. After the introduction ofLiCl, ionically conductive PVA/EG @LiCl organohydrogel was served as a self-cleaning strain sensor, whichcould be long-term stable to detect the motions of human under room and low temperatures. The studyprovides to further understanding of the organohydrogel, which will help us design next-generationhigh-performance organohydrogels.
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