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468 results on '"Ma, Ju"'

9. Studies of Extragalactic Background Light with TeV BL Lac Objects

Author

Qin, Longhua, Wang, Jiancheng, Gao, Quangui, Na, Weiwei, Li, Huaizhen, Ma, Ju, and Yang, Jianping

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Very high energy (VHE; $E \geq$ 100GeV) $\gamma-$ray from cosmological distances are attenuated by the extragalactic background light (EBL) in the IR to UV band. By contrasting measured versus intrinsic emission, the EBL photon density can be derived. However, neither the intrinsic spectra nor the EBL is separately known~-~except their combined effect. Here we first present a flexible model-dependent optical depth method to study EBL by fitting the emission spectra of TeV BL Lacs objects via a one-zone leptonic synchrotron self-Compton model (SSC). We have little information about electron energy distributions (EEDs) in the jet, which is critically important to build spectral energy distributions (SEDs) in SSC scenario. Based on the current particle acceleration models, we use two types of EEDs, i,e., a power-law log-parabola (PLLP) EED and a broken power-law (BPL) EED to fit the observed spectra. We obtain that the upper limits of EBL density are around about 30 n W m$^{-2}$ sr$^{-1}$, which are similar to the published measurement. Furthermore, we propose an unprecedented method to test radiation mechanisms involved in TeV objects by simply comparing the reduced EBL density with the limit obtained by galaxy counts, and demonstrate that for some BL Lacs, at least, the one-zone SSC model should be reconsidered., Comment: Accepted by MNRAS

Published
2020
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15. Spatial–Temporal Transformer Networks for Traffic Flow Forecasting Using a Pre-Trained Language Model.

Author

Ma, Ju, Zhao, Juan, and Hou, Yao

Subjects
*GRAPH neural networks, *LANGUAGE models, *TRANSFORMER models, *TRAFFIC flow, *ARCHITECTURAL design
Abstract

Most current methods use spatial–temporal graph neural networks (STGNNs) to analyze complex spatial–temporal information from traffic data collected from hundreds of sensors. STGNNs combine graph neural networks (GNNs) and sequence models to create hybrid structures that allow for the two networks to collaborate. However, this collaboration has made the model increasingly complex. This study proposes a framework that relies solely on original Transformer architecture and carefully designs embeddings to efficiently extract spatial–temporal dependencies in traffic flow. Additionally, we used pre-trained language models to enhance forecasting performance. We compared our new framework with current state-of-the-art STGNNs and Transformer-based models using four real-world traffic datasets: PEMS04, PEMS08, METR-LA, and PEMS-BAY. The experimental results demonstrate that our framework outperforms the other models in most metrics. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Cascade analysis of awareness, willingness, uptake and adherence with regard to PrEP among young men who have sex with men (YMSM) in China: A comparison between students and non‐students

Author

Liu, Yuanyuan, primary, Cheng, Zhaoyu, additional, Xian, Yidan, additional, Liu, Xuan, additional, Wei, Siyue, additional, Ma, Ju, additional, Chen, Jiageng, additional, Chen, Zhongdan, additional, Liu, Fengli, additional, Yang, Jie, additional, Yu, Maohe, additional, Li, Changping, additional, and Cui, Zhuang, additional

Published
2024
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19. An Interactive System for Knowledge Graph Search

Author

Baivab, Sinha, Wang, Xin, Jiang, Wei, Ma, Ju, Zhan, Huayi, Zhong, Xueyan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Nah, Yunmook, editor, Cui, Bin, editor, Lee, Sang-Won, editor, Yu, Jeffrey Xu, editor, Moon, Yang-Sae, editor, and Whang, Steven Euijong, editor

Published
2020
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35. D-Optimal Design and Development of a Koumine-Loaded Microemulsion for Rheumatoid Arthritis Treatment: In vivo and in vitro Evaluation

Author

Hu,Qing, Fu,Xiao-Ling, Dong,Yi-Yan, Ma,Ju, Hua,Jian, Li,Jia-Ting, Liu,Kai-Xin, Yang,Jian, and Yu,Chang-Xi

Subjects
International Journal of Nanomedicine
Abstract

Qing Hu,1,2,* Xiao-Ling Fu,1,* Yi-Yan Dong,1,2 Ju Ma,1 Jian Hua,1 Jia-Ting Li,1 Kai-Xin Liu,1 Jian Yang,1,2 Chang-Xi Yu1,2 1School of Pharmacy, Fujian Medical University, Fuzhou, People’s Republic of China; 2Fujian Key Laboratory of Drug Target Discovery and Structural and Functional Research, School of Pharmacy, Fujian Medical University, Fuzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Chang-Xi Yu; Jian Yang, School of Pharmacy, Fujian Medical University, No. 1 Xuefu North Road, Fuzhou, 350122, People’s Republic of China, Tel +86-0591-22862016, Email changxiyu@mail.fjmu.edu.cn; fjmukent@mail.fjmu.edu.cnIntroduction: Koumine (KME) is the most abundant active ingredient separated from Gelsemium elegans Benth and exhibits a significant therapeutic effect on rheumatoid arthritis (RA). It is a lipophilic compound with poor aqueous solubility, and there is an urgent need to develop novel dosage forms of KME and promote its clinical application for the treatment of RA. The aim of this study was to design and develop KME-loaded microemulsions (KME-MEs) for the effective management of RA.Methods: The composition of the microemulsion was selected by carrying out a solubility study and generating pseudoternary phase diagrams, and further optimized by D-Optimal design. The optimized KME-MEs was evaluated for particle size, viscosity, drug release, storage stability, cytotoxicity, cellular uptake, Caco-2 cell transport and everted gut sac investigations. In vivo fluorescence imaging and the therapeutic effects of KME and KME-MEs on collagen-induced arthritis (CIA) rats were also evaluated.Results: The optimized microemulsion contained 8% oil, 32% Smix (surfactant/cosurfactant) and 60% water and was used for in vivo and in vitro studies. The optimal KME-MEs exhibited a small globule size of 18.5 ± 0.14 nm and good stability over 3 months, and the release kinetics followed a first-order model. These KME-MEs had no toxic effect on Caco-2 cells but were efficiently internalized into the cytoplasm. Compared to KME, the KME-MEs displayed significantly increased permeability and absorption in Caco-2 cell monolayer assay and ex vivo everted gut sac experiment. As expected, the KME-MEs attenuated the progression of RA in CIA rats and were more effective than free KME with a reduced frequency of administration.Conclusion: The KME-MEs improved the solubility and therapeutic efficacy of KME by employing formulation technology. These results provide a promising vehicle for the oral delivery of KME to treat RA and have attractive potential for clinical translation.Graphical Abstract: Keywords: rheumatoid arthritis, koumine, microemulsion, permeability, oral administration

Published
2023

39. Ischemic accumulation of succinate induces Cdc42 succinylation and inhibits neural stem cell proliferation after cerebral ischemia/reperfusion

Author

Qi, Su-Hua, primary, Huang, Lin-Yan, additional, Ma, Ju-Yun, additional, Song, Jin-Xiu, additional, Xu, Jing-Jing, additional, Hong, Rui, additional, Fan, Hai-Di, additional, Cai, Heng, additional, Wang, Wan, additional, Wang, Yan-Ling, additional, Hu, Zhao-Li, additional, and Shen, Jian-Gang, additional

Published
2023
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