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145 results on '"Liao, Binbin"'

9. Cross-layer Path Selection in Multi-path Transport Protocol for Mobile Devices

Author

Liao, Binbin, Zhang, Guangxing, Wu, Qinghua, Li, Zhenyu, and Xie, Gaogang

Subjects
Computer Science - Networking and Internet Architecture
Abstract

MPTCP is a new transport protocol that enables mobile devices to use multiple physical paths simultaneously through several network interfaces, such as WiFi and Cellular. However, wireless path capacities change frequently in the mobile environments, causing challenges for path selection. For example, WiFi associated paths often become poor as devices walk away, since WiFi has intermittent connectivity caused by the short signal coverage and stochastic interference. MPTCP's native decision based on hysteretic TCP-layer estimation will miss the real switching point of wireless quality, which may cumulate packets on the broken path and causes serious packets reinjection. Through analyzing a unique dataset in the wild, we quantitatively study the impact of MAC-layer factors on the aggregated performance of MPTCP. We then propose a decision tree approach for cross-layer path selection that decides which path to carry the incoming packets dynamically according to the prior learned schemes. A prototype of the path selection system named SmartPS, which proactively probes the wireless environments, is realized and deployed in Linux and Android. Evaluation results demonstrate that our SmartPS can efficiently utilize the faster path, with goodput improvements of up to 29%., Comment: ICNP under review

Published
2020

18. Energy Price Distortions and Urban Carbon Emission Efficiency: Evidence from China's Energy-Intensive Sectors.

Author

Wang, Xiaozhen, Liao, Binbin, Cheng, Li, Li, Jingyi, Yang, Xuanyadong, and Wang, Xiaolei

Abstract

With a primary focus of achieving carbon neutrality, the energy-intensive industrial sectors (EIIs) contribute to more than half of China's carbon dioxide (CO2) emissions. During the process of China's rapid economic development, distorted energy prices gradually became the main obstacle to energy conservation and emission reductions in the EIIs. Therefore, this study focused on determining the mechanisms affecting the energy price distortions of carbon emission efficiency (CEE) in China's EIIs. Based on a stochastic frontier analysis, the changing trend of CEE in China's EIIs was evaluated. The channels impacting the energy price distortions of CEE were further analyzed by a mediating effect and moderated mediating effect model. The main contributions and findings include the following: energy price distortions have a significant negative impact on CEE by suppressing technological innovations and hindering the restructuring of energy consumption; governmental environmental regulatory policies mitigate their suppressing effect on technological innovations and reduce the preventing effect by improving the energy consumption structure. The results suggest that market-based price reforms and moderate environmental regulation by the government could help to improve CEE in China's EIIs. These findings are of great significance for promoting the sustainable development of the energy-intensive industrial sectors and achieving carbon neutrality. [ABSTRACT FROM AUTHOR]

Published
2024
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32. Advances in Punica granatumpolysaccharides: Isolation, structural-activity relationships, bioactivities, and potential applications

Author

Yang, Qiuli, Cheng, Lei, Liao, Binbin, Wang, Jiale, Lin, Yuan, Liu, Yinglin, and Zhou, Ping

Abstract

Punica granatum(Pomegranate) is a well-known plant resource with a rich history of medicinal and culinary uses since ancient times. The unique bioactivity of P. granatumpolysaccharides (PGPs) has attracted increasing attention in research. However, the advancement of PGPs-based functional foods and medicines has been hindered by a lack of comprehensive understanding regarding the structure–activity relationship (SAR), structural modification, applications, and safety of PGPs. This review aims to summarize the current knowledge on extraction and purification methods, structural features, biological activities, SAR, applications, and safety considerations of PGPs. Studies have demonstrated that PGPs exhibit a wide range of bioactivities, including antioxidant, antitumor, immunomodulatory, anti-inflammatory, and hypolipidemic effects. SAR studies have indicated that PGPs with moderate molecular weight (10–422.55 kDa) exhibit excellent immunostimulatory activity, while selenium modification of PGPs enhances their antioxidant activities. Additionally, PGPs containing β-(1 → 3)-bonds are crucial for their antitumor effects. Furthermore, PGPs display remarkable rheological properties, bioavailability, and biodegradability, with no observed toxic effects, making them promising candidates for applications in the food, medicine, nanomaterials, and cosmetic industries. In conclusion, this article provides both theoretical insights and practical guidance for the development of PGPs as innovative functional foods.

Published
2024
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33. The Deficiency of Acetylcholinesterase Gene Function in Aleuroglyphus Ovatus Troupeau (Acarina: Acaridae) Increases its Susceptibility to Phoxim and Natural Pyrethrins

Author

Xiong, Wenhui, primary, Liao, Binbin, additional, Yang, Yuanfa, additional, Zhong, Shanglin, additional, Zhang, Jinnan, additional, Sun, Wenxuan, additional, Zou, Yang, additional, Ai, Hui, additional, Xin, Tianrong, additional, bin, xia, additional, and Zou, Zhiwen, additional

Published
2024
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42. Efficient Bayesian inversion of planetary structures based on normal mode analysis using generative neural networks

Author

Liao, Binbin and Sun, Heping

Abstract

Bayesian inversion based on normal modes analysis is an essential approach to understanding the internal structure of the Earth and other planets. While the traditional Markov Chain Monte Carlo (MCMC) method provides a feasible approach to obtain the posterior probability density distributions of model parameters, it demands a considerable amount of forward calculation and is slow in terms of computational efficiency. In order to overcome the limitations of the MCMC method, a new approach to Bayesian inversion using generative neural networks has been proposed in this study, which can deliver outcomes equivalent in accuracy to those of the MCMC method with less sample learning. The study proposed three types of Bayesian inversion neural network models based on popular generative neural networks, including GAN, flow model, and energy model, and evaluated their accuracy and discreteness of inversion results. By using the generative neural network method based on actual lunar normal mode observation data, this study has provided posterior probability density distribution of one-dimensional density and velocity structure parameters of the Moon, along with the optimal parameter values.The results demonstrate the potential of using generative neural networks in Bayesian inversion and provide a new direction for future research in this field., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Published
2023

44. A novel application of deep learning in extracting Earth's free oscillation

Author

Zeng, Shiyu, Guo, Rumeng, Liao, Binbin, Dai, Kun, Zhang, Yijun, Cui, Xiaoming, Zhou, Jiangcun, Xu, Jianqiao, Chen, Xiaodong, Hou, Mingqiang, and Sun, Heping

Abstract

The normal modes (i.e. Earth's free oscillations) are long-period low-frequency seismic signals, which are excited by a variety of factors, such as earthquakes, volcanic eruption, landslide, avalanche and so on, are an essential vehicle for global seismic tomography to elucidate large-scale heterogeneities within the deep Earth. Accurate extraction of signals on normal mode spectrum is a prerequisite for the imaging inversion, providing the differences between the observed and synthetic normal mode spectrum. However, the normal mode spectrum has great complexity due to many structural factors within the Earth, so unacceptable false and dismissed selections of the signals always occur, which hinder the development of exploration of the deep Earth’s deep interior based on normal mode data. To address these problems, we build a deep-learning based neural network, named ModeNet, which is capable of precisely and efficient selecting the frequency windows to cover the target normal modal signals on a noisy spectrum, which could outperform the conventional spectrum-FLEXWIN method without relying on comparisons with synthetics. We also define our own method to evaluate the performance of ModeNet on the testing set and obtain a precision as high as ~0.98. Moreover, ModeNet achieves good generalization in processing seismograms of different events with different noise levels, components, and time window data, as well as superconductivity-gravimeter observations. Therefore, ModeNet could be implemented as a valuable tool for the future deep Earth inversion., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Published
2023

47. First-Principles Study of Atomic Diffusion by Vacancy Defect of the L1 2 -Al 3 M (M = Sc, Zr, Er, Y) Phase.

Author

Liu, Shuai, Liao, Binbin, Nie, Baohua, Fan, Touwen, Chen, Dongchu, Zhang, Jianglong, and Song, Yu

Subjects
*POINT defects, *ACTIVATION energy, *ATOMS
Abstract

Atomic diffusion by the vacancy defect of L12-Al3M (M = Sc, Zr, Er, Y) was investigated based on a first-principles calculation. The point defect formation energies were firstly evaluated. Then, the migration energy for different diffusion paths was obtained by the climbing-image nudged elastic band (CI-NEB) method. The results showed that Al atomic and M atomic diffusions through nearest-neighbor jump (NNJ) mediated by Al vacancy (VAl) were, respectively, the preferred diffusion paths in Al3M phases under both Al-rich and M-rich conditions. The other mechanisms, such as six-jump cycle (6JC) and next-nearest-neighbor jump (NNNJ), were energetically inhibited. The order of activation barriers for NNJ(Al-VAl) was Al3Zr < Al3Y < Al3Er < Al3Sc. The Al3Sc phase had high stability with a high self-diffusion activation barrier, while the Al3Zr and Al3Y phases were relatively unstable with a low self-diffusion activation energy. Moreover, the atomic-diffusion behavior between the core and shell layers of L12-Al3M was also further investigated. Zr atoms were prone to diffusion into the Al3Y core layer, resulting in no stable core-shelled Al3(Y,Zr), which well agreed with experimental observation. [ABSTRACT FROM AUTHOR]

Published
2023
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