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276 results on '"Wei, Wentao"'

1. From Unimodal to Multimodal: improving sEMG-Based Pattern Recognition via deep generative models

Author

Wei, Wentao and Ren, Linyan

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Objective: Multimodal hand gesture recognition (HGR) systems can achieve higher recognition accuracy compared to unimodal HGR systems. However, acquiring multimodal gesture recognition data typically requires users to wear additional sensors, thereby increasing hardware costs. Methods: This paper proposes a novel generative approach to improve Surface Electromyography (sEMG)-based HGR accuracy via virtual Inertial Measurement Unit (IMU) signals. Specifically, we trained a deep generative model based on the intrinsic correlation between forearm sEMG signals and forearm IMU signals to generate virtual forearm IMU signals from the input forearm sEMG signals at first. Subsequently, the sEMG signals and virtual IMU signals were fed into a multimodal Convolutional Neural Network (CNN) model for gesture recognition. Results: We conducted evaluations on six databases, including five publicly available databases and our collected database comprising 28 subjects performing 38 gestures, containing both sEMG and IMU data. The results show that our proposed approach significantly outperforms the sEMG-based unimodal HGR approach (with increases of 2.15%-13.10%). Moreover, it achieves accuracy levels closely matching those of multimodal HGR when using virtual Acceleration (ACC) signals. Conclusion: It demonstrates that incorporating virtual IMU signals, generated by deep generative models, can significantly improve the accuracy of sEMG-based HGR. Significance: The proposed approach represents a successful attempt to bridge the gap between unimodal HGR and multimodal HGR without additional sensor hardware, which can help to promote further development of natural and cost-effective myoelectric interfaces in the biomedical engineering field.

Published
2023

2. Attention Paper: How Generative AI Reshapes Digital Shadow Industry?

Author

Wang, Qichao, Ma, Huan, Wei, Wentao, Li, Hangyu, Chen, Liang, Zhao, Peilin, Zhao, Binwen, Hu, Bo, Zhang, Shu, Zheng, Zibin, and Wu, Bingzhe

Subjects
Computer Science - Computers and Society, Computer Science - Artificial Intelligence
Abstract

The rapid development of digital economy has led to the emergence of various black and shadow internet industries, which pose potential risks that can be identified and managed through digital risk management (DRM) that uses different techniques such as machine learning and deep learning. The evolution of DRM architecture has been driven by changes in data forms. However, the development of AI-generated content (AIGC) technology, such as ChatGPT and Stable Diffusion, has given black and shadow industries powerful tools to personalize data and generate realistic images and conversations for fraudulent activities. This poses a challenge for DRM systems to control risks from the source of data generation and to respond quickly to the fast-changing risk environment. This paper aims to provide a technical analysis of the challenges and opportunities of AIGC from upstream, midstream, and downstream paths of black/shadow industries and suggest future directions for improving existing risk control systems. The paper will explore the new black and shadow techniques triggered by generative AI technology and provide insights for building the next-generation DRM system.

Published
2023

3. OlaGPT: Empowering LLMs With Human-like Problem-Solving Abilities

Author

Xie, Yuanzhen, Xie, Tao, Lin, Mingxiong, Wei, WenTao, Li, Chenglin, Kong, Beibei, Chen, Lei, Zhuo, Chengxiang, Hu, Bo, and Li, Zang

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

In most current research, large language models (LLMs) are able to perform reasoning tasks by generating chains of thought through the guidance of specific prompts. However, there still exists a significant discrepancy between their capability in solving complex reasoning problems and that of humans. At present, most approaches focus on chains of thought (COT) and tool use, without considering the adoption and application of human cognitive frameworks. It is well-known that when confronting complex reasoning challenges, humans typically employ various cognitive abilities, and necessitate interaction with all aspects of tools, knowledge, and the external environment information to accomplish intricate tasks. This paper introduces a novel intelligent framework, referred to as OlaGPT. OlaGPT carefully studied a cognitive architecture framework, and propose to simulate certain aspects of human cognition. The framework involves approximating different cognitive modules, including attention, memory, reasoning, learning, and corresponding scheduling and decision-making mechanisms. Inspired by the active learning mechanism of human beings, it proposes a learning unit to record previous mistakes and expert opinions, and dynamically refer to them to strengthen their ability to solve similar problems. The paper also outlines common effective reasoning frameworks for human problem-solving and designs Chain-of-Thought (COT) templates accordingly. A comprehensive decision-making mechanism is also proposed to maximize model accuracy. The efficacy of OlaGPT has been stringently evaluated on multiple reasoning datasets, and the experimental outcomes reveal that OlaGPT surpasses state-of-the-art benchmarks, demonstrating its superior performance. Our implementation of OlaGPT is available on GitHub: \url{https://github.com/oladata-team/OlaGPT}.

Published
2023

15. Predictive Maintenance System for Production Line Equipment Based on Digital Twin and Augmented Reality

Author

Wei, Wentao, Liu, Lilan, Yang, Muchen, Li, Jiaying, Wu, Fang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Wang, Yi, editor, Martinsen, Kristian, editor, Yu, Tao, editor, and Wang, Kesheng, editor

Published
2022
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16. Research on Digital Twin System of Intelligent Workshop and Application of Historical Data

Author

Yang, Muchen, Liu, Lilan, Gao, Zenggui, Wei, Wentao, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Wang, Yi, editor, Martinsen, Kristian, editor, Yu, Tao, editor, and Wang, Kesheng, editor

Published
2022
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17. Visualized Interaction Method of Mechanical Arm Based on Augmented Reality

Author

Zhou, Shuaichang, Liu, Lilan, Cao, Heng, Chang, Yuxing, Li, Jiaying, Wei, Wentao, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Wang, Yi, editor, Martinsen, Kristian, editor, Yu, Tao, editor, and Wang, Kesheng, editor

Published
2022
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18. Real-Time Data-Driven Digital Twin Workshop Web Interactive Application

Author

Cao, Heng, Liu, Lilan, Zhou, Shuaichang, Li, Jiaying, Chang, Yuxing, Wei, Wentao, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Wang, Yi, editor, Martinsen, Kristian, editor, Yu, Tao, editor, and Wang, Kesheng, editor

Published
2022
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19. Discovery of Potent, Selective, and Orally Available IRE1α Inhibitors Demonstrating Comparable PD Modulation to IRE1 Knockdown in a Multiple Myeloma Model

Author

Braun, Marie-Gabrielle, primary, Ashkenazi, Avi, additional, Beveridge, Ramsay E., additional, Castanedo, Georgette, additional, Wallweber, Heidi Ackerly, additional, Beresini, Maureen H., additional, Clark, Kevin R., additional, De Bruyn, Tom, additional, Fu, Liqiang, additional, Gibbons, Paul, additional, Jiang, Fan, additional, Kaufman, Susan, additional, Kan, David, additional, Kiefer, James R., additional, Leclerc, Jean-Philippe, additional, Lemire, Alexandre, additional, Ly, Cuong, additional, Segal, Ehud, additional, Sims, Jessica, additional, Wang, Weiru, additional, Wei, Wentao, additional, Zhao, Liang, additional, Schwarz, Jacob B., additional, and Rudolph, Joachim, additional

Published
2024
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22. Quantitative Determination of Plant Hormone Abscisic Acid Using Surface Enhanced Raman Spectroscopy

Author

ZHANG Yanyan, LI Can, SU Rui, LI Linze, WEI Wentao, LI Baolei, and HU Jiandong

Subjects
abscisic acid, aptamer recognition, surface-enhanced raman spectroscopy, gold nanoparticles, biosensor, Agriculture (General), S1-972, Technology (General), T1-995
Abstract

Plant hormone Abscisic Acid (ABA) plays an important role in regulating plant growth. However, the content of ABA in plant tissues is very low, and rapid and sensitive detection methods are urgently needed. In this study, a rapid and quantitative ABA detection method was established based on aptamer recognition and surface-enhanced Raman spectroscop (SERS). The gold nanoparticles modified by ABA aptamer had the characteristics of SERS signal enhancement and selective recognition, realizing the rapid and sensitive detection of trace ABA in complex plant sample matrix. When ABA molecules appeared in detect system, the aptamer would specifically bind with ABA molecules, and the aptamer folded into G-tetrad structure at same time, which wrapped ABA molecules in the tetrad structure, shortened the distance between ABA molecules and gold nanoparticles, and the enhanced and stable ABA molecules SERS signal were obtained. Under the condition of optimized aptamer concentration at 0.12 µmol/L, different concentrations of ABA solutions in the detection system were detected. Within the concentration range of 0.1－100 µmol/L, the SERS intensity of ABA presented a good linear relationship with the concentration. The detection limit of this method was 0.1 µmol/L and the linear correlation coefficient R2 was 0.9855. The repeatability test of 20 points randomly on SERS substrate showed that the relative standard deviation (RSD) was 6.71%, indicating the stability of SERS substrate was well. Furthermore, the substrate of gold nanoparticles modified by the ABA aptamer terminal with sulfhydryl group (SH-Apt) could be stored in the refrigerator for more than half a year, indicating that the substrate has good stability. Once the preparation of the synthesized SH-Apt modified gold nanoparticles was completed. It could be used on demand without the need to prepare SERS substrate for every detection. In this sense, the constructed aptamer SERS biosensor could realize the rapid and quantitative detection of ABA. The method was used for the determination of ABA in wheat leaves, and the result was in good agreement with the Enzyme Linked Immunosorbent Assay (ELISA) (The max relative error was 9.13%). This biosensor is an exploratory study on the detection of plant hormones by SERS, and the results of the study will have important reference value for the subsequent quantitative and on-site detection of ABA, as well as the detection of other plant hormones.

Published
2022
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25. Mechanical properties and oxidation corrosion resistance of phosphate ceramic coating enhanced by SiO2‐BNNSs material.

Author

Wei, Wentao, Wang, Quanlong, Wu, Meiping, Ma, Chenglong, Miao, Xiaojin, Wang, Yiyao, Wang, Jianyu, Zhou, Wen, and Wang, Chenyu

Subjects
*CERAMIC coating, *PHOSPHATE coating, *SURFACE energy, *CONTACT angle, *PROTECTIVE coatings, *HYBRID materials, *CORROSION resistance
Abstract

A method of preparing SiO2‐BNNSs hybrid material by surface modification of boron nitride nanosheets (BNNSs) with SiO2 was proposed to improve the dispersion of BNNSs in the coatings. Then, phosphate ceramic coatings with BNNSs and SiO2‐BNNSs were prepared on stainless steel (304) by spraying. Characterization of BNNSs and SiO2‐BNNSs by X‐ray diffraction, Fourier transform‐infrared, Raman, and scanning electron microscopy proved the success of hybridization. The surface morphology and mechanical properties were conducted to characterize the protective performance of the coating. Simultaneously, the phase composition and electrochemical properties of the coatings after high‐temperature oxidation were studied. The results showed that ceramic coatings had low surface energy with a contact angle of 102.41° when.4 wt.% SiO2‐BNNSs was added. Compared with BNNSs coating, the mechanical properties of SiO2‐BNNSs coating were significantly enhanced, the hardness of.4 wt.%SiO2‐BNNSs coating was as high as 170 HV, and the interface bonding strength was 12.24 MPa. For the oxidation corrosion resistance,.4 wt.% SiO2‐BNNSs coating under oxidation at 400°C for 50 h had the minimum corrosion current density and maximum impedance, which were.864 μA/cm2 and 177 kΩ/cm2, respectively, this indicated that SiO2‐BNNSs coating could still maintain excellent oxidation corrosion resistance under high‐temperature conditions for a long time. [ABSTRACT FROM AUTHOR]

Published
2024
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29. A New Open Channel Flow Correction Method Based on Different Boundary Combinations in Hydraulic Modeling.

Author

Chen, Mingrui, Wei, Wentao, Zhang, Zhao, Xue, Linan, Kong, Lingzhong, Li, Haichen, Liu, Yuxin, and Liu, Hairuo

Subjects
CHANNEL flow, HYDRAULIC models, WATER transfer, PROBLEM solving
Abstract

In open-channel water transfer projects, hydrodynamic modeling has been one of the tools commonly used by the scheduling staff to perceive the changes in the water condition of the channel. The reliability of the flow monitoring data has not been guaranteed due to restrictions in the flow monitoring method. Flow monitoring errors directly reduce the accuracy of hydrodynamic modeling calculations, making it impossible to accurately grasp the real-time changes in the internal water conditions of the channel. In this paper, by utilizing the characteristics of the hydrodynamic model itself, which can be solved discretely with multiple boundary conditions, the method of correcting the boundary anomaly data is proposed by changing the combination of hydrodynamic boundaries. This solves the problem of the inaccuracy of hydrodynamic model calculations due to errors in the monitoring data and improves the accuracy of the hydrodynamic model calculations. In the actual operation process, it is found that the method proposed in this paper solves the problem of hydrodynamic model misalignment caused by flow observation errors by correcting the flow during the flow adjustment period, which greatly improves the calculation accuracy of the hydrodynamic model. Secondly, for a stable flow period, the method proposed in this paper can quickly capture and correct the local monitoring of abnormal data and improve the overall hydrodynamic simulation accuracy. [ABSTRACT FROM AUTHOR]

Published
2024
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34. Data from AG-221, a First-in-Class Therapy Targeting Acute Myeloid Leukemia Harboring Oncogenic IDH2 Mutations

Author

Yen, Katharine, primary, Travins, Jeremy, primary, Wang, Fang, primary, David, Muriel D., primary, Artin, Erin, primary, Straley, Kimberly, primary, Padyana, Anil, primary, Gross, Stefan, primary, DeLaBarre, Byron, primary, Tobin, Erica, primary, Chen, Yue, primary, Nagaraja, Raj, primary, Choe, Sung, primary, Jin, Lei, primary, Konteatis, Zenon, primary, Cianchetta, Giovanni, primary, Saunders, Jeffrey O., primary, Salituro, Francesco G., primary, Quivoron, Cyril, primary, Opolon, Paule, primary, Bawa, Olivia, primary, Saada, Véronique, primary, Paci, Angelo, primary, Broutin, Sophie, primary, Bernard, Olivier A., primary, de Botton, Stéphane, primary, Marteyn, Benoît S., primary, Pilichowska, Monika, primary, Xu, YingXia, primary, Fang, Cheng, primary, Jiang, Fan, primary, Wei, Wentao, primary, Jin, Shengfang, primary, Silverman, Lee, primary, Liu, Wei, primary, Yang, Hua, primary, Dang, Lenny, primary, Dorsch, Marion, primary, Penard-Lacronique, Virginie, primary, Biller, Scott A., primary, and Su, Shin-San Michael, primary

Published
2023
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35. Supplementary Tables 1 - 8 from AG-221, a First-in-Class Therapy Targeting Acute Myeloid Leukemia Harboring Oncogenic IDH2 Mutations

Author

Yen, Katharine, primary, Travins, Jeremy, primary, Wang, Fang, primary, David, Muriel D., primary, Artin, Erin, primary, Straley, Kimberly, primary, Padyana, Anil, primary, Gross, Stefan, primary, DeLaBarre, Byron, primary, Tobin, Erica, primary, Chen, Yue, primary, Nagaraja, Raj, primary, Choe, Sung, primary, Jin, Lei, primary, Konteatis, Zenon, primary, Cianchetta, Giovanni, primary, Saunders, Jeffrey O., primary, Salituro, Francesco G., primary, Quivoron, Cyril, primary, Opolon, Paule, primary, Bawa, Olivia, primary, Saada, Véronique, primary, Paci, Angelo, primary, Broutin, Sophie, primary, Bernard, Olivier A., primary, de Botton, Stéphane, primary, Marteyn, Benoît S., primary, Pilichowska, Monika, primary, Xu, YingXia, primary, Fang, Cheng, primary, Jiang, Fan, primary, Wei, Wentao, primary, Jin, Shengfang, primary, Silverman, Lee, primary, Liu, Wei, primary, Yang, Hua, primary, Dang, Lenny, primary, Dorsch, Marion, primary, Penard-Lacronique, Virginie, primary, Biller, Scott A., primary, and Su, Shin-San Michael, primary

Published
2023
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36. Supplementary Methods from AG-221, a First-in-Class Therapy Targeting Acute Myeloid Leukemia Harboring Oncogenic IDH2 Mutations

Author

Yen, Katharine, primary, Travins, Jeremy, primary, Wang, Fang, primary, David, Muriel D., primary, Artin, Erin, primary, Straley, Kimberly, primary, Padyana, Anil, primary, Gross, Stefan, primary, DeLaBarre, Byron, primary, Tobin, Erica, primary, Chen, Yue, primary, Nagaraja, Raj, primary, Choe, Sung, primary, Jin, Lei, primary, Konteatis, Zenon, primary, Cianchetta, Giovanni, primary, Saunders, Jeffrey O., primary, Salituro, Francesco G., primary, Quivoron, Cyril, primary, Opolon, Paule, primary, Bawa, Olivia, primary, Saada, Véronique, primary, Paci, Angelo, primary, Broutin, Sophie, primary, Bernard, Olivier A., primary, de Botton, Stéphane, primary, Marteyn, Benoît S., primary, Pilichowska, Monika, primary, Xu, YingXia, primary, Fang, Cheng, primary, Jiang, Fan, primary, Wei, Wentao, primary, Jin, Shengfang, primary, Silverman, Lee, primary, Liu, Wei, primary, Yang, Hua, primary, Dang, Lenny, primary, Dorsch, Marion, primary, Penard-Lacronique, Virginie, primary, Biller, Scott A., primary, and Su, Shin-San Michael, primary

Published
2023
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37. Supplementary Figures 1 - 11 from AG-221, a First-in-Class Therapy Targeting Acute Myeloid Leukemia Harboring Oncogenic IDH2 Mutations

Author

Yen, Katharine, primary, Travins, Jeremy, primary, Wang, Fang, primary, David, Muriel D., primary, Artin, Erin, primary, Straley, Kimberly, primary, Padyana, Anil, primary, Gross, Stefan, primary, DeLaBarre, Byron, primary, Tobin, Erica, primary, Chen, Yue, primary, Nagaraja, Raj, primary, Choe, Sung, primary, Jin, Lei, primary, Konteatis, Zenon, primary, Cianchetta, Giovanni, primary, Saunders, Jeffrey O., primary, Salituro, Francesco G., primary, Quivoron, Cyril, primary, Opolon, Paule, primary, Bawa, Olivia, primary, Saada, Véronique, primary, Paci, Angelo, primary, Broutin, Sophie, primary, Bernard, Olivier A., primary, de Botton, Stéphane, primary, Marteyn, Benoît S., primary, Pilichowska, Monika, primary, Xu, YingXia, primary, Fang, Cheng, primary, Jiang, Fan, primary, Wei, Wentao, primary, Jin, Shengfang, primary, Silverman, Lee, primary, Liu, Wei, primary, Yang, Hua, primary, Dang, Lenny, primary, Dorsch, Marion, primary, Penard-Lacronique, Virginie, primary, Biller, Scott A., primary, and Su, Shin-San Michael, primary

Published
2023
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44. Transcriptome Profiling of Stem-Differentiating Xylem in Response to Abiotic Stresses Based on Hybrid Sequencing in Cunninghamia lanceolata

Author

Wei, Wentao, primary, Wang, Huiyuan, additional, Liu, Xuqing, additional, Kou, Wenjing, additional, Liu, Ziqi, additional, Wang, Huihui, additional, Yang, Yongkang, additional, Zhao, Liangzhen, additional, Zhang, Hangxiao, additional, Liu, Bo, additional, Ma, Xiangqing, additional, and Gu, Lianfeng, additional

Published
2022
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45. Multi-omics of Circular RNAs and Their Responses to Hormones in Moso Bamboo (Phyllostachys edulis)

Author

Wang, Yongsheng, primary, Wang, Huihui, additional, Wang, Huiyuan, additional, Zhou, Ruifan, additional, Wu, Ji, additional, Zhang, Zekun, additional, Jin, Yandong, additional, Li, Tao, additional, Kohnen, Markus V., additional, Liu, Xuqing, additional, Wei, Wentao, additional, Chen, Kai, additional, Gao, Yubang, additional, Ding, Jiazhi, additional, Zhang, Hangxiao, additional, Liu, Bo, additional, Lin, Chentao, additional, and Gu, Lianfeng, additional

Published
2022
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47. Clinical features of multifocal papillary thyroid carcinoma and risk factors of cervical metastatic lymph nodes

Author

NI, Yaqiong, WANG, Tao, WANG, Xingyue, TIAN, Youxin, WEI, Wentao, and LIU, Qinjiang

Subjects
Male, Thyrotropin, General Medicine, Hashimoto Disease, Middle Aged, Thyroglobulin, Carcinoma, Papillary, Risk Factors, Thyroid Cancer, Papillary, Lymphatic Metastasis, Hypertension, Humans, Female, Lymph Nodes, Thyroid Neoplasms, Research Article, Retrospective Studies
Abstract

OBJECTIVE: To analyze the clinical features of multifocal papillary thyroid carcinoma (PTC) and the risk factors of cervical metastatic lymph nodes. METHODS: A total of 1524 patients with papillary thyroid carcinoma admitted in Gansu Provincial Cancer Hospital from January 2020 to August 2021 were enrolled, including 492 cases of multifocal PTC and 1032 cases of unifocal PTC. The clinicopathologic features of multifocal PTC and unifocal PTC were analyzed by comparing their differences in gender, ethnicity, age, body mass index, accompanying diabetes mellitus, accompanying hypertension, preoperative thyroid stimulating hormone and thyroglobulin levels, location of lesions, maximum diameter of lesions, sum of lesion diameters, central metastatic lymph nodes, lateral cervical metastatic lymph nodes, presence of Hashimoto’s thyroiditis, and thyroid capsule invasion. Patients were also assessed according to the presence or absence of central metastatic lymph nodes and lateral cervical metastatic lymph nodes to understand clinicopathological parameter differences, and multivariate logistic regression analysis was used to explore the risk factors. RESULTS: Compared with unifocal PTC group, multifocal PTC group had significantly higher proportion of patients aged over 55 years, accompanying hypertension, central metastatic lymph nodes or cervical metastatic lymph nodes, Hashimoto’s thyroiditis and capsule invasion (all P

Published
2022

50. EPMDroid

Author

Wei, Wentao, Wang, Jie, Yan, Zheng, Ding, Wenxiu, Xidian University, Department of Communications and Networking, Aalto-yliopisto, and Aalto University

Subjects
Malware detection, Intel SGX, Data fusion, Probabilistic data structures, Privacy preservation
Abstract

Funding Information: This work is supported in part by the National Natural Science Foundation of China under Grant 62072351 ; in part by the Academy of Finland under Grant 308087 , Grant 335262 and Grant 345072 ; in part by the open research project of ZheJiang Lab, China under Grant 2021PD0AB01 ; in part by the Shaanxi Innovation Team Project, China under Grant 2018TD-007 ; and in part by the 111 Project, China under Grant B16037 , as well as Huawei Technologies Group Co., Ltd, China . Funding Information: This work is supported in part by the National Natural Science Foundation of China under Grant 62072351; in part by the Academy of Finland under Grant 308087, Grant 335262 and Grant 345072; in part by the open research project of ZheJiang Lab, China under Grant 2021PD0AB01; in part by the Shaanxi Innovation Team Project, China under Grant 2018TD-007; and in part by the 111 Project, China under Grant B16037, as well as Huawei Technologies Group Co. Ltd, China. Publisher Copyright: © 2021 Android has stood at a predominant position in mobile operating systems for many years. However, its popularity and openness make it a desirable target of malicious attackers. There is an increasing need for mobile malware detection. Existing analysis methods fall into two categories, i.e., static analysis and dynamic analysis. The dynamic analysis is more effective and timely than the static one, but it incurs a high computational overhead, thus cannot be deployed in resource-constrained mobile devices. Existing studies solve this issue by outsourcing malware detection to the cloud. However, the privacy of mobile app runtime data uploaded to the cloud is not well preserved during both detection model training and malware detection. Numerous efforts have been made to preserve privacy with cryptography, which suffers from high computational overhead and low flexibility. To address these issues, in this paper, we propose an Intel SGX-empowered mobile malware detection scheme called EPMDroid. We also design a probabilistic data structure based on cuckoo filters, named CuckooTable, to effectively fuse features for detection and achieve high space efficiency. We conduct both theoretical analysis and real-world data based tests on EPMDroid performance. Experimental results show that EPMDroid can speed up malware detection by up to 43.8 times and save memory space by up to 3.7 times with the same accuracy, as compared to a baseline method.

Published
2022

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