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6. Flexible Resistive Gas Sensor Based on Molybdenum Disulfide-Modified Polypyrrole for Trace NO 2 Detection.

Author

Zhao, Kuo, Shi, Yunbo, Cui, Mingrui, Tang, Bolun, Zheng, Canda, Chen, Qinglong, and Hu, Yuhan

Subjects
*GAS detectors, *POLYIMIDES, *POLYPYRROLE, *P-N heterojunctions, *CONDUCTING polymers, *MOLYBDENUM
Abstract

High sensitivity and selectivity and short response and recovery times are important for practical conductive polymer gas sensors. However, poor stability, poor selectivity, and long response times significantly limit the applicability of single-phase conducting polymers, such as polypyrrole (PPy). In this study, PPy/MoS2 composite films were prepared via chemical polymerization and mechanical blending, and flexible thin-film resistive NO2 sensors consisting of copper heating, fluorene polyester insulating, and PPy/MoS2 sensing layers with a silver fork finger electrode were fabricated on a flexible polyimide substrate using a flexible electronic printer. The PPy/MoS2 composite films were characterized using X-ray diffraction, Fourier-transform infrared spectroscopy, and field-emission scanning electron microscopy. A home-built gas sensing test platform was built to determine the resistance changes in the composite thin-film sensor with temperature and gas concentration. The PPy/MoS2 sensor exhibited better sensitivity, selectivity, and stability than a pure PPy sensor. Its response to 50 ppm NO2 was 38% at 150 °C, i.e., 26% higher than that of the pure PPy sensor, and its selectivity and stability were also higher. The greater sensitivity was attributed to p–n heterojunction formation after MoS2 doping and more gas adsorption sites. Thus, PPy/MoS2 composite film sensors have good application prospects. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Social Network Forensics Analysis Model Based on Network Representation Learning.

Author

Zhao, Kuo, Zhang, Huajian, Li, Jiaxin, Pan, Qifu, Lai, Li, Nie, Yike, and Zhang, Zhongfei

Subjects
*SOCIAL network analysis, *HIERARCHICAL clustering (Cluster analysis), *INTERPERSONAL communication, *RANDOM walks, *VECTOR spaces, *HUFFMAN codes, *CONCEPT mapping
Abstract

The rapid evolution of computer technology and social networks has led to massive data generation through interpersonal communications, necessitating improved methods for information mining and relational analysis in areas such as criminal activity. This paper introduces a Social Network Forensic Analysis model that employs network representation learning to identify and analyze key figures within criminal networks, including leadership structures. The model incorporates traditional web forensics and community algorithms, utilizing concepts such as centrality and similarity measures and integrating the Deepwalk, Line, and Node2vec algorithms to map criminal networks into vector spaces. This maintains node features and structural information that are crucial for the relational analysis. The model refines node relationships through modified random walk sampling, using BFS and DFS, and employs a Continuous Bag-of-Words with Hierarchical Softmax for node vectorization, optimizing the value distribution via the Huffman tree. Hierarchical clustering and distance measures (cosine and Euclidean) were used to identify the key nodes and establish a hierarchy of influence. The findings demonstrate the effectiveness of the model in accurately vectorizing nodes, enhancing inter-node relationship precision, and optimizing clustering, thereby advancing the tools for combating complex criminal networks. [ABSTRACT FROM AUTHOR]

Published
2024
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35. Additional file 1 of EZH2 regulates pancreatic cancer cells through E2F1, GLI1, CDK3, and Mcm4

Author

Li, Hongfeng, Wang, Hailong, Cui, Yunlong, Jiang, Wenhua, Zhan, Hongjie, Feng, Lixia, Gao, Mingyou, Zhao, Kuo, Zhang, Limeng, Xie, Xiaojing, Zhao, Ning, Li, Ying, and Liu, Pengfei

Abstract

Additional file 1: Supplementary Table 1. EZH2 shRNA sequences. Supplementary Table 2. RT-qPCR primer sequences. Supplementary Table 3. The list of EZH2 overexpression and knockdown stably transfected cell line. Supplementary Table 4. The list of Top 30 DEGs. Supplementary Figure 1. Western blot detected the expression level of EZH2 protein in the establishment of EZH2 overexpression and knockdown cell models. A, C and E showed the BXPC-3 cells, B, D and F showed the HPDE6-C7 cells. The internal reference target was β-actin gene. *,**,*** represented significant differences between the different of EZH2 stable transfected cells models, P < 0.05, P < 0.01, and P < 0.001, respectively. Supplementary Figure 2. Effect of EZH2 on cell proliferation detected by colony formation experiment. A and C showed the BXPC-3 cells, B and D showed the HPDE6-C7 cells. Supplementary Figure 3. Gating strategy for living/dead cells exclusion by staining 7AAD. Supplementary Figure 4. Ki-67 antibody experiments tested the effect of EZH2 on cell proliferation. A and C showed the BXPC-3 cells, B and D showed the HPDE6-C7 cells. *,**,*** represented significant differences between the different of EZH2 stable transfected cells models, P < 0.05, P < 0.01, and P < 0.001, respectively. Supplementary Figure 5. The influence of EZH2 on cell migration in HPDE6-C7 cell lines was detected by scratch test. *,**,*** represented significant differences between the different of EZH2 stable transfected cells models, P < 0.05, P < 0.01, and P < 0.001, respectively. Supplementary Figure 6. Scratch test detected the cell migration of EZH2 overexpression and knockdown BXPC-3 cell models. *,**,*** represented significant differences between the different of EZH2 stable transfected cells models, P < 0.05, P < 0.01, and P < 0.001, respectively.

Published
2023
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39. Self-adjusting inverse design method for nanophotonic devices

Author

Liu, Haida, primary, Wang, Qianqian, additional, Xiang, Zhengxin, additional, Teng, Geer, additional, Zhao, Yu, additional, Liu, Ziyang, additional, Wei, Kai, additional, Dai, Fengtong, additional, Lv, Linji, additional, Zhao, Kuo, additional, and Yang, Chenyi, additional

Published
2022
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