Author: "Guo, X." - Searchworks@Jio Institute Digital Library Search Results

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36,888 results on '"Guo, X."'

1. Detection of two TeV gamma-ray outbursts from NGC 1275 by LHAASO

Author: Cao, Zhen, Aharonian, F., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo., X.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: The Water Cherenkov Detector Array (WCDA) is one of the components of Large High Altitude Air Shower Observatory (LHAASO) and can monitor any sources over two-thirds of the sky for up to 7 hours per day with >98\% duty cycle. In this work, we report the detection of two outbursts of the Fanaroff-Riley I radio galaxy NGC 1275 that were detected by LHAASO-WCDA between November 2022 and January 2023 with statistical significance of 5.2~$\sigma$ and 8.3~$\sigma$. The observed spectral energy distribution in the range from 500 GeV to 3 TeV is fitted by a power-law with a best-fit spectral index of $\alpha=-3.37\pm0.52$ and $-3.35\pm0.29$, respectively. The outburst flux above 0.5~TeV was ($4.55\pm 4.21)\times~10^{-11}~\rm cm^{-2}~s^{-1}$ and ($3.45\pm 1.78)\times~10^{-11}~\rm cm^{-2}~s^{-1}$, corresponding to 60\%, 45\% of Crab Nebula flux. Variation analysis reveals the variability time-scale of days at the TeV energy band. A simple test by one-zone synchrotron self-Compton model reproduces the data in the gamma-ray band well., Comment: 11 pages, 8 figures, 3 tables
Published: 2024

2. LHAASO detection of very-high-energy gamma-ray emission surrounding PSR J0248+6021

Author: Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, J. H., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., Zou, Y. C., and Zuo, X.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We report the detection of an extended very-high-energy (VHE) gamma-ray source coincident with the locations of middle-aged (62.4~\rm kyr) pulsar PSR J0248+6021, by using the LHAASO-WCDA data of live 796 days and LHAASO-KM2A data of live 1216 days. A significant excess of \gray induced showers is observed both by WCDA in energy bands of 1-25~\rm TeV and KM2A in energy bands of $>$ 25~\rm TeV with 7.3 $\sigma$ and 13.5 $\sigma$, respectively. The best-fit position derived through WCDA data is R.A. = 42.06$^\circ \pm$ 0.12$^\circ$ and Dec. = 60.24$^\circ \pm $ 0.13$^\circ$ with an extension of 0.69$^\circ\pm$0.15$^\circ$ and that of the KM2A data is R.A.= 42.29$^\circ \pm $ 0.13$^\circ$ and Dec. = 60.38$^\circ \pm$ 0.07$^\circ$ with an extension of 0.37$^\circ\pm$0.07$^\circ$. No clear extended multiwavelength counterpart of this LHAASO source has been found from the radio band to the GeV band. The most plausible explanation of the VHE \gray emission is the inverse Compton process of highly relativistic electrons and positrons injected by the pulsar. These electrons/positrons are hypothesized to be either confined within the pulsar wind nebula or to have already escaped into the interstellar medium, forming a pulsar halo., Comment: 12 pages, 10 figures, Accepted by Sci. China-Phys. Mech. Astron
Published: 2024

3. BERT and LLMs-Based avGFP Brightness Prediction and Mutation Design

Author: Guo, X. and Che, W.
Subjects: Quantitative Biology - Other Quantitative Biology
Abstract: This study aims to utilize Transformer models and large language models (such as GPT and Claude) to predict the brightness of Aequorea victoria green fluorescent protein (avGFP) and design mutants with higher brightness. Considering the time and cost associated with traditional experimental screening methods, this study employs machine learning techniques to enhance research efficiency. We first read and preprocess a proprietary dataset containing approximately 140,000 protein sequences, including about 30,000 avGFP sequences. Subsequently, we constructed and trained a Transformer-based prediction model to screen and design new avGFP mutants that are expected to exhibit higher brightness. Our methodology consists of two primary stages: first, the construction of a scoring model using BERT, and second, the screening and generation of mutants using mutation site statistics and large language models. Through the analysis of predictive results, we designed and screened 10 new high-brightness avGFP sequences. This study not only demonstrates the potential of deep learning in protein design but also provides new perspectives and methodologies for future research by integrating prior knowledge from large language models.
Published: 2024

4. Constraints on Ultra Heavy Dark Matter Properties from Dwarf Spheroidal Galaxies with LHAASO Observations

Author: Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Saiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Phenomenology
Abstract: In this work we try to search for signals generated by ultra-heavy dark matter at the Large High Altitude Air Shower Observatory (LHAASO) data. We look for possible gamma-ray by dark matter annihilation or decay from 16 dwarf spheroidal galaxies in the field of view of LHAASO. Dwarf spheroidal galaxies are among the most promising targets for indirect detection of dark matter which have low fluxes of astrophysical $\gamma$-ray background while large amount of dark matter. By analyzing more than 700 days observational data at LHAASO, no significant dark matter signal from 1 TeV to 1 EeV is detected. Accordingly we derive the most stringent constraints on the ultra-heavy dark matter annihilation cross-section up to EeV. The constraints on the lifetime of dark matter in decay mode are also derived., Comment: 17 pages, 12 figures, accepted by PRL
Published: 2024

5. Measurement of Electron Antineutrino Oscillation Amplitude and Frequency via Neutron Capture on Hydrogen at Daya Bay

Author: Daya Bay collaboration, An, F. P., Bai, W. D., Balantekin, A. B., Bishai, M., Blyth, S., Cao, G. F., Cao, J., Chang, J. F., Chang, Y., Chen, H. S., Chen, H. Y., Chen, S. M., Chen, Y., Chen, Y. X., Chen, Z. Y., Cheng, J., Cheng, Y. -C., Cheng, Z. K., Cherwinka, J. J., Chu, M. C., Cummings, J. P., Dalager, O., Deng, F. S., Ding, X. Y., Ding, Y. Y., Diwan, M. V., Dohnal, T., Dolzhikov, D., Dove, J., Duyang, H. Y., Dwyer, D. A., Gallo, J. P., Gonchar, M., Gong, G. H., Gong, H., Gu, W. Q., Guo, J. Y., Guo, L., Guo, X. H., Guo, Y. H., Guo, Z., Hackenburg, R. W., Han, Y., Hans, S., He, M., Heeger, K. M., Heng, Y. K., Hor, Y. K., Hsiung, Y. B., Hu, B. Z., Hu, J. R., Hu, T., Hu, Z. J., Huang, H. X., Huang, J. H., Huang, X. T., Huang, Y. B., Huber, P., Jaffe, D. E., Jen, K. L., Ji, X. L., Ji, X. P., Johnson, R. A., Jones, D., Kang, L., Kettell, S. H., Kohn, S., Kramer, M., Langford, T. J., Lee, J., Lee, J. H. C., Lei, R. T., Leitner, R., Leung, J. K. C., Li, F., Li, H. L., Li, J. J., Li, Q. J., Li, R. H., Li, S., Li, S. C., Li, W. D., Li, X. N., Li, X. Q., Li, Y. F., Li, Z. B., Liang, H., Lin, C. J., Lin, G. L., Lin, S., Ling, J. J., Link, J. M., Littenberg, L., Littlejohn, B. R., Liu, J. C., Liu, J. L., Liu, J. X., Lu, C., Lu, H. Q., Luk, K. B., Ma, B. Z., Ma, X. B., Ma, X. Y., Ma, Y. Q., Mandujano, R. C., Marshall, C., McDonald, K. T., McKeown, R. D., Meng, Y., Napolitano, J., Naumov, D., Naumova, E., Nguyen, T. M. T., Ochoa-Ricoux, J. P., Olshevskiy, A., Park, J., Patton, S., Peng, J. C., Pun, C. S. J., Qi, F. Z., Qi, M., Qian, X., Raper, N., Ren, J., Reveco, C. Morales, Rosero, R., Roskovec, B., Ruan, X. C., Russell, B., Steiner, H., Sun, J. L., Tmej, T., Treskov, K., Tse, W. -H., Tull, C. E., Tung, Y. C., Viren, B., Vorobel, V., Wang, C. H., Wang, J., Wang, M., Wang, N. Y., Wang, R. G., Wang, W., Wang, X., Wang, Y. F., Wang, Z., Wang, Z. M., Wei, H. Y., Wei, L. H., Wei, W., Wen, L. J., Whisnant, K., White, C. G., Wong, H. L. H., Worcester, E., Wu, D. R., Wu, Q., Wu, W. J., Xia, D. M., Xie, Z. Q., Xing, Z. Z., Xu, H. K., Xu, J. L., Xu, T., Xue, T., Yang, C. G., Yang, L., Yang, Y. Z., Yao, H. F., Ye, M., Yeh, M., Young, B. L., Yu, H. Z., Yu, Z. Y., Yue, B. B., Zavadskyi, V., Zeng, S., Zeng, Y., Zhan, L., Zhang, C., Zhang, F. Y., Zhang, H. H., Zhang, J. L., Zhang, J. W., Zhang, Q. M., Zhang, S. Q., Zhang, X. T., Zhang, Y. M., Zhang, Y. X., Zhang, Y. Y., Zhang, Z. J., Zhang, Z. P., Zhang, Z. Y., Zhao, J., Zhao, R. Z., Zhou, L., Zhuang, H. L., and Zou, J. H.
Subjects: High Energy Physics - Experiment
Abstract: This Letter reports the first measurement of the oscillation amplitude and frequency of reactor antineutrinos at Daya Bay via neutron capture on hydrogen using 1958 days of data. With over 3.6 million signal candidates, an optimized candidate selection, improved treatment of backgrounds and efficiencies, refined energy calibration, and an energy response model for the capture-on-hydrogen sensitive region, the relative $\overline{\nu}_{e}$ rates and energy spectra variation among the near and far detectors gives $\mathrm{sin}^22\theta_{13} = 0.0759_{-0.0049}^{+0.0050}$ and $\Delta m^2_{32} = (2.72^{+0.14}_{-0.15})\times10^{-3}$ eV$^2$ assuming the normal neutrino mass ordering, and $\Delta m^2_{32} = (-2.83^{+0.15}_{-0.14})\times10^{-3}$ eV$^2$ for the inverted neutrino mass ordering. This estimate of $\sin^2 2\theta_{13}$ is consistent with and essentially independent from the one obtained using the capture-on-gadolinium sample at Daya Bay. The combination of these two results yields $\mathrm{sin}^22\theta_{13}= 0.0833\pm0.0022$, which represents an 8% relative improvement in precision regarding the Daya Bay full 3158-day capture-on-gadolinium result.
Published: 2024
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6. Modeling of Back-Propagation Neural Network Based State-of-Charge Estimation for Lithium-Ion Batteries with Consideration of Capacity Attenuation

Author: ZHANG, S., GUO, X., and ZHANG, X.
Subjects: attenuation measurement, backpropagation, battery management systems, lithium batteries, neural networks, Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Computer engineering. Computer hardware, TK7885-7895
Abstract: The state of charge of lithium-ion batteries reflects the power available in the battery. Precise SOC estimation is a challenging task for battery management system. In this paper, a novel hybrid method by fusion of back-propagation (BP) neural network and improved ampere-hour counting method is proposed for SOC estimation of lithium-ion battery, which considers the impact of battery capacity attenuation on SOC estimation during the process of charging and discharging. The predictive accuracy and effectiveness of model are validated by NASA lithium-ion battery dataset. Moreover, the adaptability and feasibility of this method are further demonstrated using dataset of accelerated life experiment. The validation results indicate that the proposed method can provide accurate SOC estimation in different capacity attenuation stage.
Published: 2019
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7. Data quality control system and long-term performance monitor of the LHAASO-KM2A

Author: Cao, Zhen, Aharonian, F., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Bian, W., Bukevich, A. V., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, H. X., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, J. H., Fang, K., Feng, C. F., Feng, H., Feng, L., Feng, S. H., Feng, X. T., Feng, Y., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., Hasan, M., He, H. H., He, H. N., He, J. Y., He, Y., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Karpikov, I., Kuleshov, D., Kurinov, K., Li, B. B., Li, C. M., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, Jian, Li, Jie, Li, K., Li, S. D., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, D. B., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Luo, Q., Luo, Y., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, L. J., Pattarakijwanich, P., Pei, Z. Y., Qi, J. C., Qi, M. Y., Qiao, B. Q., Qin, J. J., Raza, A., Ruffolo, D., Sáiz, A., Saeed, M., Semikoz, D., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, D. X., Sun, Q. N., Sun, X. N., Sun, Z. B., Takata, J., Tam, P. H. T., Tang, Q. W., Tang, R., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, Kai, Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, Q. W., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, Y. L., Xing, Y., Xiong, D. R., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, C. Y., Yang, F., Yang, F. F., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, W. X., Yao, Y. H., Yao, Z. G., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zhao, X. H., Zheng, F., Zhong, W. J., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, B. Y., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., Zou, Y. C., and Zuo, X.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract: The KM2A is the largest sub-array of the Large High Altitude Air Shower Observatory (LHAASO). It consists of 5216 electromagnetic particle detectors (EDs) and 1188 muon detectors (MDs). The data recorded by the EDs and MDs are used to reconstruct primary information of cosmic ray and gamma-ray showers. This information is used for physical analysis in gamma-ray astronomy and cosmic ray physics. To ensure the reliability of the LHAASO-KM2A data, a three-level quality control system has been established. It is used to monitor the status of detector units, stability of reconstructed parameters and the performance of the array based on observations of the Crab Nebula and Moon shadow. This paper will introduce the control system and its application on the LHAASO-KM2A data collected from August 2021 to July 2023. During this period, the pointing and angular resolution of the array were stable. From the observations of the Moon shadow and Crab Nebula, the results achieved using the two methods are consistent with each other. According to the observation of the Crab Nebula at energies from 25 TeV to 100 TeV, the time averaged pointing errors are estimated to be $-0.003^{\circ} \pm 0.005^{\circ}$ and $0.001^{\circ} \pm 0.006^{\circ}$ in the R.A. and Dec directions, respectively., Comment: 15 pages, 9 figures
Published: 2024

8. Discovery of Very-high-energy Gamma-ray Emissions from the Low Luminosity AGN NGC 4278 by LHAASO

Author: Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, J. H., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., Zou, Y. C., and Zuo, X.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: The first source catalog of Large High Altitude Air Shower Observatory reported the detection of a very-high-energy gamma ray source, 1LHAASO J1219+2915. In this paper a further detailed study of the spectral and temporal behavior of this point-like source have been carried. The best-fit position of the TeV source ($\rm{RA}=185.05^{\circ}\pm0.04^{\circ}$, $\rm{Dec}=29.25^{\circ}\pm0.03^{\circ}$) is compatible with NGC 4278 within $\sim0.03$ degree. Variation analysis shows an indication of the variability at a few months level in the TeV band, which is consistent with low frequency observations. Based on these observations, we report the detection of TeV $\gamma$-ray emissions from this low-luminosity AGN NGC 4278. The observations by LHAASO-WCDA during active period has a significance level of 8.8\,$\sigma$ with best-fit photon spectral index $\varGamma=2.56\pm0.14$ and a flux $f_{1-10\,\rm{TeV}}=(7.0\pm1.1_{\rm{sta}}\pm0.35_{\rm{syst}})\times10^{-13}\,\rm{photons\,cm^{-2}\,s^{-1}}$, or approximately $5\%$ of the Crab Nebula. The discovery of VHE from NGC 4278 indicates that the compact, weak radio jet can efficiently accelerate particles and emit TeV photons., Comment: 11 pages, 5 figures
Published: 2024

9. Search for solar axions by Primakoff effect with the full dataset of the CDEX-1B Experiment

Author: Yang, L. T., Liu, S. K., Yue, Q., Kang, K. J., Li, Y. J., An, H. P., C., Greeshma, Chang, J. P., Chen, Y. H., Cheng, J. P., Dai, W. H., Deng, Z., Fang, C. H., Geng, X. P., Gong, H., Guo, Q. J., Guo, T., Guo, X. Y., He, L., He, J. R., Hu, J. W., Huang, H. X., Huang, T. C., Jiang, L., Karmakar, S., Li, H. B., Li, H. Y., Li, J. M., Li, J., Li, M. C., Li, Q. Y., Li, R. M. J., Li, X. Q., Li, Y. L., Liang, Y. F., Liao, B., Lin, F. K., Lin, S. T., Liu, J. X., Liu, Y. D., Liu, Y., Liu, Y. Y., Ma, H., Mao, Y. C., Nie, Q. Y., Pan, H., Qi, N. C., Ren, J., Ruan, X. C., Shen, M. B., Singh, M. K., Sun, T. X., Sun, W. L., Tang, C. J., Tian, Y., Wang, G. F., Wang, J. Z., Wang, L., Wang, Q., Wang, Y. F., Wang, Y. X., Wong, H. T., Wu, Y. C., Xing, H. Y., Xiong, K. Z., Xu, R., Xu, Y., Xue, T., Yan, Y. L., Yi, N., Yu, C. X., Yu, H. J., Zeng, M., Zeng, Z., Zhang, B. T., Zhang, F. S., Zhang, L., Zhang, P., Zhang, Z. H., Zhang, Z. Y., Zhao, J. Z., Zhao, K. K., Zhao, M. G., Zhou, J. F., Zhou, Z. Y., and Zhu, J. J.
Subjects: High Energy Physics - Experiment, High Energy Physics - Phenomenology, Physics - Instrumentation and Detectors
Abstract: We present the first limit on $g_{A\gamma}$ coupling constant using the Bragg-Primakoff conversion based on an exposure of 1107.5 kg days of data from the CDEX-1B experiment at the China Jinping Underground Laboratory. The data are consistent with the null signal hypothesis, and no excess signals are observed. Limits of the coupling $g_{A\gamma}<2.08\times10^{-9}$ GeV$^{-1}$ (95\% C.L.) are derived for axions with mass up to 100 eV/$c^2$. Within the hadronic model of KSVZ, our results exclude axion mass $>5.3~\rm{eV}/c^2$ at 95\% C.L., Comment: 7 pages, 5 figures
Published: 2024

10. First Search for Light Fermionic Dark Matter Absorption on Electrons Using Germanium Detector in CDEX-10 Experiment

Author: Liu, J. X., Yang, L. T., Yue, Q., Kang, K. J., Li, Y. J., An, H. P., C., Greeshma, Chang, J. P., Chen, Y. H., Cheng, J. P., Dai, W. H., Deng, Z., Fang, C. H., Geng, X. P., Gong, H., Guo, Q. J., Guo, T., Guo, X. Y., He, L., He, J. R., Hu, J. W., Huang, H. X., Huang, T. C., Jiang, L., Karmakar, S., Li, H. B., Li, H. Y., Li, J. M., Li, J., Li, M. C., Li, Q. Y., Li, R. M. J., Li, X. Q., Li, Y. L., Liang, Y. F., Liao, B., Lin, F. K., Lin, S. T., Liu, S. K., Liu, Y. D., Liu, Y., Liu, Y. Y., Ma, H., Mao, Y. C., Nie, Q. Y., Pan, H., Qi, N. C., Ren, J., Ruan, X. C., Shen, M. B., Singh, M. K., Sun, T. X., Sun, W. L., Tang, C. J., Tian, Y., Wang, G. F., Wang, J. Z., Wang, L., Wang, Q., Wang, Y. F., Wang, Y. X., Wong, H. T., Wu, Y. C., Xing, H. Y., Xiong, K. Z., Xu, R., Xu, Y., Xue, T., Yan, Y. L., Yi, N., Yu, C. X., Yu, H. J., Zeng, M., Zeng, Z., Zhang, B. T., Zhang, F. S., Zhang, L., Zhang, P., Zhang, Z. H., Zhang, Z. Y., Zhao, J. Z., Zhao, K. K., Zhao, M. G., Zhou, J. F., Zhou, Z. Y., and Zhu, J. J.
Subjects: High Energy Physics - Experiment, High Energy Physics - Phenomenology, Physics - Instrumentation and Detectors
Abstract: We present the first results of the search for sub-MeV fermionic dark matter absorbed by electron targets of Germanium using the 205.4~kg$\cdot$day data collected by the CDEX-10 experiment, with the analysis threshold of 160~eVee. No significant dark matter (DM) signals over the background are observed. Results are presented as limits on the cross section of DM--electron interaction. We present new constraints of cross section in the DM range of 0.1--10 keV/$c^2$ for vector and axial-vector interaction. The upper limit on the cross section is set to be $\rm 5.5\times10^{-46}~cm^2$ for vector interaction, and $\rm 1.8\times10^{-46}~cm^2$ for axial-vector interaction at DM mass of 5 keV/$c^2$., Comment: 6 pages, 4 figures
Published: 2024

11. LHAASO-KM2A detector simulation using Geant4

Author: Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, J. H., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract: KM2A is one of the main sub-arrays of LHAASO, working on gamma ray astronomy and cosmic ray physics at energies above 10 TeV. Detector simulation is the important foundation for estimating detector performance and data analysis. It is a big challenge to simulate the KM2A detector in the framework of Geant4 due to the need to track numerous photons from a large number of detector units (>6000) with large altitude difference (30 m) and huge coverage (1.3 km^2). In this paper, the design of the KM2A simulation code G4KM2A based on Geant4 is introduced. The process of G4KM2A is optimized mainly in memory consumption to avoid memory overffow. Some simpliffcations are used to signiffcantly speed up the execution of G4KM2A. The running time is reduced by at least 30 times compared to full detector simulation. The particle distributions and the core/angle resolution comparison between simulation and experimental data of the full KM2A array are also presented, which show good agreement.
Published: 2024
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12. Search for a sub-eV sterile neutrino using Daya Bay's full dataset

Author: An, F. P., Bai, W. D., Balantekin, A. B., Bishai, M., Blyth, S., Cao, G. F., Cao, J., Chang, J. F., Chang, Y., Chen, H. S., Chen, H. Y., Chen, S. M., Chen, Y., Chen, Y. X., Chen, Z. Y., Cheng, J., Cheng, Y. C., Cheng, Z. K., Cherwinka, J. J., Chu, M. C., Cummings, J. P., Dalager, O., Deng, F. S., Ding, X. Y., Ding, Y. Y., Diwan, M. V., Dohnal, T., Dolzhikov, D., Dove, J., Dugas, K. V., Duyang, H. Y., Dwyer, D. A., Gallo, J. P., Gonchar, M., Gong, G. H., Gong, H., Gu, W. Q., Guo, J. Y., Guo, L., Guo, X. H., Guo, Y. H., Guo, Z., Hackenburg, R. W., Han, Y., Hans, S., He, M., Heeger, K. M., Heng, Y. K., Hor, Y. K., Hsiung, Y. B., Hu, B. Z., Hu, J. R., Hu, T., Hu, Z. J., Huang, H. X., Huang, J. H., Huang, X. T., Huang, Y. B., Huber, P., Jaffe, D. E., Jen, K. L., Ji, X. L., Ji, X. P., Johnson, R. A., Jones, D., Kang, L., Kettell, S. H., Kohn, S., Kramer, M., Langford, T. J., Lee, J., Lee, J. H. C., Lei, R. T., Leitner, R., Leung, J. K. C., Li, F., Li, H. L., Li, J. J., Li, Q. J., Li, R. H., Li, S., Li, S. C., Li, W. D., Li, X. N., Li, X. Q., Li, Y. F., Li, Z. B., Liang, H., Lin, C. J., Lin, G. L., Lin, S., Ling, J. J., Link, J. M., Littenberg, L., Littlejohn, B. R., Liu, J. C., Liu, J. L., Liu, J. X., Lu, C., Lu, H. Q., Luk, K. B., Ma, B. Z., Ma, X. B., Ma, X. Y., Ma, Y. Q., Mandujano, R. C., Marshall, C., McDonald, K. T., McKeown, R. D., Meng, Y., Napolitano, J., Naumov, D., Naumova, E., Nguyen, T. M. T., Ochoa-Ricoux, J. P., Olshevskiy, A., Park, J., Patton, S., Peng, J. C., Pun, C. S. J., Qi, F. Z., Qi, M., Qian, X., Raper, N., Ren, J., Reveco, C. Morales, Rosero, R., Roskovec, B., Ruan, X. C., Russell, B., Steiner, H., Sun, J. L., Tmej, T., Tse, W. -H., Tull, C. E., Tung, Y. C., Viren, B., Vorobel, V., Wang, C. H., Wang, J., Wang, M., Wang, N. Y., Wang, R. G., Wang, W., Wang, X., Wang, Y. F., Wang, Z., Wang, Z. M., Wei, H. Y., Wei, L. H., Wei, W., Wen, L. J., Whisnant, K., White, C. G., Wong, H. L. H., Worcester, E., Wu, D. R., Wu, Q., Wu, W. J., Xia, D. M., Xie, Z. Q., Xing, Z. Z., Xu, H. K., Xu, J. L., Xu, T., Xue, T., Yang, C. G., Yang, L., Yang, Y. Z., Yao, H. F., Ye, M., Yeh, M., Young, B. L., Yu, H. Z., Yu, Z. Y., Yue, B. B., Zavadskyi, V., Zeng, S., Zeng, Y., Zhan, L., Zhang, C., Zhang, F. Y., Zhang, H. H., Zhang, J. L., Zhang, J. W., Zhang, Q. M., Zhang, S. Q., Zhang, X. T., Zhang, Y. M., Zhang, Y. X., Zhang, Y. Y., Zhang, Z. J., Zhang, Z. P., Zhang, Z. Y., Zhao, J., Zhao, R. Z., Zhou, L., Zhuang, H. L., and Zou, J. H.
Subjects: High Energy Physics - Experiment
Abstract: This Letter presents results of a search for the mixing of a sub-eV sterile neutrino with three active neutrinos based on the full data sample of the Daya Bay Reactor Neutrino Experiment, collected during 3158 days of detector operation, which contains $5.55 \times 10^{6}$ reactor \anue candidates identified as inverse beta-decay interactions followed by neutron-capture on gadolinium. The analysis benefits from a doubling of the statistics of our previous result and from improvements of several important systematic uncertainties. No significant oscillation due to mixing of a sub-eV sterile neutrino with active neutrinos was found. Exclusion limits are set by both Feldman-Cousins and CLs methods. Light sterile neutrino mixing with $\sin^2 2\theta_{14} \gtrsim 0.01$ can be excluded at 95\% confidence level in the region of $0.01$ eV$^2 \lesssim |\Delta m^{2}_{41}| \lesssim 0.1 $ eV$^2$. This result represents the world-leading constraints in the region of $2 \times 10^{-4}$ eV$^2 \lesssim |\Delta m^{2}_{41}| \lesssim 0.2 $ eV$^2$., Comment: 7 pages, 4 figures, 1 table
Published: 2024

13. Constraints on the Blazar-Boosted Dark Matter from the CDEX-10 Experiment

Author: Xu, R., Yang, L. T., Yue, Q., Kang, K. J., Li, Y. J., An, H. P., C., Greeshma, Chang, J. P., Chen, Y. H., Cheng, J. P., Dai, W. H., Deng, Z., Fang, C. H., Geng, X. P., Gong, H., Guo, Q. J., Guo, T., Guo, X. Y., He, L., He, S. M., Hu, J. W., Huang, H. X., Huang, T. C., Jiang, L., Karmakar, S., Li, H. B., Li, H. Y., Li, J. M., Li, J., Li, Q. Y., Li, R. M. J., Li, X. Q., Li, Y. L., Liang, Y. F., Liao, B., Lin, F. K., Lin, S. T., Liu, J. X., Liu, S. K., Liu, Y. D., Liu, Y., Liu, Y. Y., Ma, H., Mao, Y. C., Nie, Q. Y., Ning, J. H., Pan, H., Qi, N. C., Ren, J., Ruan, X. C., Singh, M. K., Sun, T. X., Tang, C. J., Tian, Y., Wang, G. F., Wang, J. Z., Wang, L., Wang, Q., Wang, Y. F., Wang, Y. X., Wong, H. T., Wu, S. Y., Wu, Y. C., Xing, H. Y., Xu, Y., Xue, T., Yan, Y. L., Yi, N., Yu, C. X., Yu, H. J., Yue, J. F., Zeng, M., Zeng, Z., Zhang, B. T., Zhang, F. S., Zhang, L., Zhang, Z. H., Zhang, Z. Y., Zhao, J. Z., Zhao, K. K., Zhao, M. G., Zhou, J. F., Zhou, Z. Y., and Zhu, J. J.
Subjects: High Energy Physics - Experiment, High Energy Physics - Phenomenology, Physics - Instrumentation and Detectors
Abstract: We report new constraints on light dark matter (DM) boosted by blazars using the 205.4 kg day data from the CDEX-10 experiment located at the China Jinping Underground Laboratory. Two representative blazars, TXS 0506+56 and BL Lacertae are studied. The results derived from TXS 0506+56 exclude DM-nucleon elastic scattering cross sections from $4.6\times 10^{-33}\ \rm cm^2$ to $1\times10^{-26}\ \rm cm^2$ for DM masses between 10 keV and 1 GeV, and the results derived from BL Lacertae exclude DM-nucleon elastic scattering cross sections from $2.4\times 10^{-34}\ \rm cm^2$ to $1\times10^{-26}\ \rm cm^2$ for the same range of DM masses. The constraints correspond to the best sensitivities among solid-state detector experiments in the sub-MeV mass range., Comment: 7 pages, 4 figures
Published: 2024

14. Probing Dark Matter Particles from Evaporating Primordial Black Holes via Electron Scattering in the CDEX-10 Experiment

Author: Zhang, Z. H., Yang, L. T., Yue, Q., Kang, K. J., Li, Y. J., An, H. P., C., Greeshma, Chang, J. P., Chen, Y. H., Cheng, J. P., Dai, W. H., Deng, Z., Fang, C. H., Geng, X. P., Gong, H., Guo, Q. J., Guo, T., Guo, X. Y., He, L., He, S. M., Hu, J. W., Huang, H. X., Huang, T. C., Jiang, L., Karmakar, S., Li, H. B., Li, H. Y., Li, J. M., Li, J., Li, Q. Y., Li, R. M. J., Li, X. Q., Li, Y. L., Liang, Y. F., Liao, B., Lin, F. K., Lin, S. T., Liu, J. X., Liu, S. K., Liu, Y. D., Liu, Y., Liu, Y. Y., Ma, H., Mao, Y. C., Nie, Q. Y., Ning, J. H., Pan, H., Qi, N. C., Ren, J., Ruan, X. C., Singh, M. K., Sun, T. X., Tang, C. J., Tian, Y., Wang, G. F., Wang, J. Z., Wang, L., Wang, Q., Wang, Y. F., Wang, Y. X., Wong, H. T., Wu, S. Y., Wu, Y. C., Xing, H. Y., Xu, R., Xu, Y., Xue, T., Yan, Y. L., Yi, N., Yu, C. X., Yu, H. J., Yue, J. F., Zeng, M., Zeng, Z., Zhang, B. T., Zhang, F. S., Zhang, L., Zhang, Z. Y., Zhao, J. Z., Zhao, K. K., Zhao, M. G., Zhou, J. F., Zhou, Z. Y., and Zhu, J. J.
Subjects: High Energy Physics - Experiment, High Energy Physics - Phenomenology, Physics - Instrumentation and Detectors
Abstract: Dark matter (DM) is a major constituent of the Universe. However, no definite evidence of DM particles (denoted as ``$\chi$") has been found in DM direct detection (DD) experiments to date. There is a novel concept of detecting $\chi$ from evaporating primordial black holes (PBHs). We search for $\chi$ emitted from PBHs by investigating their interaction with target electrons. The examined PBH masses range from 1$\times$10$^{15}$ to 7$\times$10$^{16}$ g under the current limits of PBH abundance $f_{PBH}$. Using 205.4 kg$\cdot$day data obtained from the CDEX-10 experiment conducted in the China Jinping Underground Laboratory, we exclude the $\chi$--electron ($\chi$--$e$) elastic-scattering cross section $\sigma_{\chi e} \sim 5\times10^{-29}$ cm$^2$ for $\chi$ with a mass $m_{\chi}\lesssim$ 0.1 keV from our results. With the higher radiation background but lower energy threshold (160 eV), CDEX-10 fill a part of the gap in the previous work. If ($m_{\chi}$, $\sigma_{\chi e}$) can be determined in the future, DD experiments are expected to impose strong constraints on $f_{PBH}$ for large $M_{PBH}$s., Comment: 9 pages, 6 figures, 3 tables. Version updated to match SCPMA version
Published: 2024
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15. Measurements of All-Particle Energy Spectrum and Mean Logarithmic Mass of Cosmic Rays from 0.3 to 30 PeV with LHAASO-KM2A

Author: The LHAASO Collaboration, Cao, Zhen, Aharonian, F., An, Q., Axikegu, A., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We present the measurements of all-particle energy spectrum and mean logarithmic mass of cosmic rays in the energy range of 0.3-30 PeV using data collected from LHAASO-KM2A between September 2021 and December 2022, which is based on a nearly composition-independent energy reconstruction method, achieving unprecedented accuracy. Our analysis reveals the position of the knee at $3.67 \pm 0.05 \pm 0.15$ PeV. Below the knee, the spectral index is found to be -$2.7413 \pm 0.0004 \pm 0.0050$, while above the knee, it is -$3.128 \pm 0.005 \pm 0.027$, with the sharpness of the transition measured with a statistical error of 2%. The mean logarithmic mass of cosmic rays is almost heavier than helium in the whole measured energy range. It decreases from 1.7 at 0.3 PeV to 1.3 at 3 PeV, representing a 24% decline following a power law with an index of -$0.1200 \pm 0.0003 \pm 0.0341$. This is equivalent to an increase in abundance of light components. Above the knee, the mean logarithmic mass exhibits a power law trend towards heavier components, which is reversal to the behavior observed in the all-particle energy spectrum. Additionally, the knee position and the change in power-law index are approximately the same. These findings suggest that the knee observed in the all-particle spectrum corresponds to the knee of the light component, rather than the medium-heavy components., Comment: 8 pages, 3 figures
Published: 2024
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16. Spatio-temporal characteristics and scenario prediction of carbon emissions from land use in Jiangxi Province, China

Author: Duo, L., Zhong, Y., Wang, J., Chen, Y., and Guo, X.
Published: 2024
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17. Independent and Joint Associations of Socioeconomic Status and Lifestyle behaviors with Cognitive Impairment among Elderly Chinese Population

Author: Feng, Y., Jia, S., Zhao, W., Wu, X., Zuo, Y., Wang, S., Zhao, L., Ma, M., Guo, X., Tarimo, C. S., Miao, Y., and Wu, Jian
Published: 2024
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18. First measurement of the yield of $^8$He isotopes produced in liquid scintillator by cosmic-ray muons at Daya Bay

Author: Daya Bay Collaboration, An, F. P., Bai, W. D., Balantekin, A. B., Bishai, M., Blyth, S., Cao, G. F., Cao, J., Chang, J. F., Chang, Y., Chen, H. S., Chen, H. Y., Chen, S. M., Chen, Y., Chen, Y. X., Chen, Z. Y., Cheng, J., Cheng, Y. C., Cheng, Z. K., Cherwinka, J. J., Chu, M. C., Cummings, J. P., Dalager, O., Deng, F. S., Ding, X. Y., Ding, Y. Y., Diwan, M. V., Dohnal, T., Dolzhikov, D., Dove, J., Dugas, K. V., Duyang, H. Y., Dwyer, D. A., Gallo, J. P., Gonchar, M., Gong, G. H., Gong, H., Gu, W. Q., Guo, J. Y., Guo, L., Guo, X. H., Guo, Y. H., Guo, Z., Hackenburg, R. W., Han, Y., Hans, S., He, M., Heeger, K. M., Heng, Y. K., Hor, Y. K., Hsiung, Y. B., Hu, B. Z., Hu, J. R., Hu, T., Hu, Z. J., Huang, H. X., Huang, J. H., Huang, X. T., Huang, Y. B., Huber, P., Jaffe, D. E., Jen, K. L., Ji, X. L., Ji, X. P., Johnson, R. A., Jones, D., Kang, L., Kettell, S. H., Kohn, S., Kramer, M., Langford, T. J., Lee, J., Lee, J. H. C., Lei, R. T., Leitner, R., Leung, J. K. C., Li, F., Li, H. L., Li, J. J., Li, Q. J., Li, R. H., Li, S., Li, S. C., Li, W. D., Li, X. N., Li, X. Q., Li, Y. F., Li, Z. B., Liang, H., Lin, C. J., Lin, G. L., Lin, S., Ling, J. J., Link, J. M., Littenberg, L., Littlejohn, B. R., Liu, J. C., Liu, J. L., Liu, J. X., Lu, C., Lu, H. Q., Luk, K. B., Ma, B. Z., Ma, X. B., Ma, X. Y., Ma, Y. Q., Mandujano, R. C., Marshall, C., McDonald, K. T., McKeown, R. D., Meng, Y., Napolitano, J., Naumov, D., Naumova, E., Nguyen, T. M. T., Ochoa-Ricoux, J. P., Olshevskiy, A., Park, J., Patton, S., Peng, J. C., Pun, C. S. J., Qi, F. Z., Qi, M., Qian, X., Raper, N., Ren, J., Reveco, C. Morales, Rosero, R., Roskovec, B., Ruan, X. C., Russell, B., Steiner, H., Sun, J. L., Tmej, T., Tse, W. -H., Tull, C. E., Tung, Y. C., Viren, B., Vorobel, V., Wang, C. H., Wang, J., Wang, M., Wang, N. Y., Wang, R. G., Wang, W., Wang, X., Wang, Y. F., Wang, Z., Wang, Z. M., Wei, H. Y., Wei, L. H., Wei, W., Wen, L. J., Whisnant, K., White, C. G., Wong, H. L. H., Worcester, E., Wu, D. R., Wu, Q., Wu, W. J., Xia, D. M., Xie, Z. Q., Xing, Z. Z., Xu, H. K., Xu, J. L., Xu, T., Xue, T., Yang, C. G., Yang, L., Yang, Y. Z., Yao, H. F., Ye, M., Yeh, M., Young, B. L., Yu, H. Z., Yu, Z. Y., Yue, B. B., Zavadskyi, V., Zeng, S., Zeng, Y., Zhan, L., Zhang, C., Zhang, F. Y., Zhang, H. H., Zhang, J. L., Zhang, J. W., Zhang, Q. M., Zhang, S. Q., Zhang, X. T., Zhang, Y. M., Zhang, Y. X., Zhang, Y. Y., Zhang, Z. J., Zhang, Z. P., Zhang, Z. Y., Zhao, J., Zhao, R. Z., Zhou, L., Zhuang, H. L., and Zou, J. H.
Subjects: Nuclear Experiment, High Energy Physics - Experiment
Abstract: Daya Bay presents the first measurement of cosmogenic $^8$He isotope production in liquid scintillator, using an innovative method for identifying cascade decays of $^8$He and its child isotope, $^8$Li. We also measure the production yield of $^9$Li isotopes using well-established methodology. The results, in units of 10$^{-8}\mu^{-1}$g$^{-1}$cm$^{2}$, are 0.307$\pm$0.042, 0.341$\pm$0.040, and 0.546$\pm$0.076 for $^8$He, and 6.73$\pm$0.73, 6.75$\pm$0.70, and 13.74$\pm$0.82 for $^9$Li at average muon energies of 63.9~GeV, 64.7~GeV, and 143.0~GeV, respectively. The measured production rate of $^8$He isotopes is more than an order of magnitude lower than any other measurement of cosmogenic isotope production. It replaces the results of previous attempts to determine the ratio of $^8$He to $^9$Li production that yielded a wide range of limits from 0 to 30\%. The results provide future liquid-scintillator-based experiments with improved ability to predict cosmogenic backgrounds.
Published: 2024

19. Charged-current non-standard neutrino interactions at Daya Bay

Author: Daya Bay collaboration, An, F. P., Bai, W. D., Balantekin, A. B., Bishai, M., Blyth, S., Cao, G. F., Cao, J., Chang, J. F., Chang, Y., Chen, H. S., Chen, H. Y., Chen, S. M., Chen, Y., Chen, Y. X., Chen, Z. Y., Cheng, J., Cheng, Y. C., Cheng, Z. K., Cherwinka, J. J., Chu, M. C., Cummings, J. P., Dalager, O., Deng, F. S., Ding, X. Y., Ding, Y. Y., Diwan, M. V., Dohnal, T., Dolzhikov, D., Dove, J., Dugas, K. V., Duyang, H. Y., Dwyer, D. A., Gallo, J. P., Gonchar, M., Gong, G. H., Gong, H., Gu, W. Q., Guo, J. Y., Guo, L., Guo, X. H., Guo, Y. H., Guo, Z., Hackenburg, R. W., Han, Y., Hans, S., He, M., Heeger, K. M., Heng, Y. K., Hor, Y. K., Hsiung, Y. B., Hu, B. Z., Hu, J. R., Hu, T., Hu, Z. J., Huang, H. X., Huang, J. H., Huang, X. T., Huang, Y. B., Huber, P., Jaffe, D. E., Jen, K. L., Ji, X. L., Ji, X. P., Johnson, R. A., Jones, D., Kang, L., Kettell, S. H., Kohn, S., Kramer, M., Langford, T. J., Lee, J., Lee, J. H. C., Lei, R. T., Leitner, R., Leung, J. K. C., Li, F., Li, H. L., Li, J. J., Li, Q. J., Li, R. H., Li, S., Li, S. C., Li, W. D., Li, X. N., Li, X. Q., Li, Y. F., Li, Z. B., Liang, H., Lin, C. J., Lin, G. L., Lin, S., Ling, J. J., Link, J. M., Littenberg, L., Littlejohn, B. R., Liu, J. C., Liu, J. L., Liu, J. X., Lu, C., Lu, H. Q., Luk, K. B., Ma, B. Z., Ma, X. B., Ma, X. Y., Ma, Y. Q., Mandujano, R. C., Marshall, C., McDonald, K. T., McKeown, R. D., Meng, Y., Napolitano, J., Naumov, D., Naumova, E., Nguyen, T. M. T., Ochoa-Ricoux, J. P., Olshevskiy, A., Park, J., Patton, S., Peng, J. C., Pun, C. S. J., Qi, F. Z., Qi, M., Qian, X., Raper, N., Ren, J., Reveco, C. Morales, Rosero, R., Roskovec, B., Ruan, X. C., Russell, B., Steiner, H., Sun, J. L., Tmej, T., Tse, W. -H., Tull, C. E., Tung, Y. C., Viren, B., Vorobel, V., Wang, C. H., Wang, J., Wang, M., Wang, N. Y., Wang, R. G., Wang, W., Wang, X., Wang, Y. F., Wang, Z., Wang, Z. M., Wei, H. Y., Wei, L. H., Wei, W., Wen, L. J., Whisnant, K., White, C. G., Wong, H. L. H., Worcester, E., Wu, D. R., Wu, Q., Wu, W. J., Xia, D. M., Xie, Z. Q., Xing, Z. Z., Xu, H. K., Xu, J. L., Xu, T., Xue, T., Yang, C. G., Yang, L., Yang, Y. Z., Yao, H. F., Ye, M., Yeh, M., Young, B. L., Yu, H. Z., Yu, Z. Y., Yue, B. B., Zavadskyi, V., Zeng, S., Zeng, Y., Zhan, L., Zhang, C., Zhang, F. Y., Zhang, H. H., Zhang, J. L., Zhang, J. W., Zhang, Q. M., Zhang, S. Q., Zhang, X. T., Zhang, Y. M., Zhang, Y. X., Zhang, Y. Y., Zhang, Z. J., Zhang, Z. P., Zhang, Z. Y., Zhao, J., Zhao, R. Z., Zhou, L., Zhuang, H. L., and Zou, J. H.
Subjects: High Energy Physics - Phenomenology, High Energy Physics - Experiment
Abstract: The full data set of the Daya Bay reactor neutrino experiment is used to probe the effect of the charged current non-standard interactions (CC-NSI) on neutrino oscillation experiments. Two different approaches are applied and constraints on the corresponding CC-NSI parameters are obtained with the neutrino flux taken from the Huber-Mueller model with a $5\%$ uncertainty. For the quantum mechanics-based approach (QM-NSI), the constraints on the CC-NSI parameters $\epsilon_{e\alpha}$ and $\epsilon_{e\alpha}^{s}$ are extracted with and without the assumption that the effects of the new physics are the same in the production and detection processes, respectively. The approach based on the weak effective field theory (WEFT-NSI) deals with four types of CC-NSI represented by the parameters $[\varepsilon_{X}]_{e\alpha}$. For both approaches, the results for the CC-NSI parameters are shown for cases with various fixed values of the CC-NSI and the Dirac CP-violating phases, and when they are allowed to vary freely. We find that constraints on the QM-NSI parameters $\epsilon_{e\alpha}$ and $\epsilon_{e\alpha}^{s}$ from the Daya Bay experiment alone can reach the order $\mathcal{O}(0.01)$ for the former and $\mathcal{O}(0.1)$ for the latter, while for WEFT-NSI parameters $[\varepsilon_{X}]_{e\alpha}$, we obtain $\mathcal{O}(0.1)$ for both cases., Comment: 25 pages, 16 figures, 6 tables; 36 pages, format changed, references added
Published: 2024

20. Dexamethasone relieves the inflammatory response caused by inguinal hernia meshes through miR-155

Author: Li, Y., Lv, Y., Li, J., Ling, P., Guo, X., Zhang, L., Ni, J., and Long, Y.
Published: 2024
Full Text: View/download PDF

21. Does or did the supernova remnant Cassiopeia A operate as a PeVatron?

Author: Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo., X.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: For decades, supernova remnants (SNRs) have been considered the prime sources of Galactic Cosmic rays (CRs). But whether SNRs can accelerate CR protons to PeV energies and thus dominate CR flux up to the knee is currently under intensive theoretical and phenomenological debate. The direct test of the ability of SNRs to operate as CR PeVatrons can be provided by ultrahigh-energy (UHE; $E_\gamma \geq 100$~TeV) $\gamma$-rays. In this context, the historical SNR Cassiopeia A (Cas A) is considered one of the most promising target for UHE observations. This paper presents the observation of Cas A and its vicinity by the LHAASO KM2A detector. The exceptional sensitivity of LHAASO KM2A in the UHE band, combined with the young age of Cas A, enabled us to derive stringent model-independent limits on the energy budget of UHE protons and nuclei accelerated by Cas A at any epoch after the explosion. The results challenge the prevailing paradigm that Cas A-type SNRs are major suppliers of PeV CRs in the Milky Way., Comment: 11 pages, 3 figures, Accepted by the APJL
Published: 2023

22. Very high energy gamma-ray emission beyond 10 TeV from GRB 221009A

Author: Cao, Zhen, Aharonian, F., An, Q., Axikegu, A., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: The highest energy gamma-rays from gamma-ray bursts (GRBs) have important implications for their radiation mechanism. Here we report for the first time the detection of gamma-rays up to 13 TeV from the brightest GRB 221009A by the Large High Altitude Air-shower Observatory (LHAASO). The LHAASO-KM2A detector registered more than 140 gamma-rays with energies above 3 TeV during 230$-$900s after the trigger. The intrinsic energy spectrum of gamma-rays can be described by a power-law after correcting for extragalactic background light (EBL) absorption. Such a hard spectrum challenges the synchrotron self-Compton (SSC) scenario of relativistic electrons for the afterglow emission above several TeV. Observations of gamma-rays up to 13 TeV from a source with a measured redshift of z=0.151 hints more transparency in intergalactic space than previously expected. Alternatively, one may invoke new physics such as Lorentz Invariance Violation (LIV) or an axion origin of very high energy (VHE) signals., Comment: 49pages, 11figures
Published: 2023
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23. Experimental Limits on Solar Reflected Dark Matter with a New Approach on Accelerated-Dark-Matter-Electron Analysis in Semiconductors

Author: Zhang, Z. Y., Yang, L. T., Yue, Q., Kang, K. J., Li, Y. J., An, H. P., C., Greeshma, Chang, J. P., Chen, Y. H., Cheng, J. P., Dai, W. H., Deng, Z., Fang, C. H., Geng, X. P., Gong, H., Guo, Q. J., Guo, T., Guo, X. Y., He, L., He, S. M., Hu, J. W., Huang, H. X., Huang, T. C., Jiang, L., Karmakar, S., Li, H. B., Li, H. Y., Li, J. M., Li, J., Li, Q. Y., Li, R. M. J., Li, X. Q., Li, Y. L., Liang, Y. F., Liao, B., Lin, F. K., Lin, S. T., Liu, J. X., Liu, S. K., Liu, Y. D., Liu, Y., Liu, Y. Y., Ma, H., Mao, Y. C., Nie, Q. Y., Ning, J. H., Pan, H., Qi, N. C., Ren, J., Ruan, X. C., Singh, M. K., Sun, T. X., Tang, C. J., Tian, Y., Wang, G. F., Wang, J. Z., Wang, L., Wang, Q., Wang, Y. F., Wang, Y. X., Wong, H. T., Wu, S. Y., Wu, Y. C., Xing, H. Y., Xu, R., Xu, Y., Xue, T., Yan, Y. L., Yi, N., Yu, C. X., Yu, H. J., Yue, J. F., Zeng, M., Zeng, Z., Zhang, B. T., Zhang, F. S., Zhang, L., Zhang, Z. H., Zhao, J. Z., Zhao, K. K., Zhao, M. G., Zhou, J. F., Zhou, Z. Y., and Zhu, J. J.
Subjects: High Energy Physics - Experiment, High Energy Physics - Phenomenology, Physics - Instrumentation and Detectors
Abstract: Recently a dark matter-electron (DM-electron) paradigm has drawn much attention. Models beyond the standard halo model describing DM accelerated by high energy celestial bodies are under intense examination as well. In this Letter, a velocity components analysis (VCA) method dedicated to swift analysis of accelerated DM-electron interactions via semiconductor detectors is proposed and the first HPGe detector-based accelerated DM-electron analysis is realized. Utilizing the method, the first germanium based constraint on sub-GeV solar reflected DM-electron interaction is presented with the 205.4 kg$\cdot$day dataset from the CDEX-10 experiment. In the heavy mediator scenario, our result excels in the mass range of 5$-$15 keV/$c^2$, achieving a 3 orders of magnitude improvement comparing with previous semiconductor experiments. In the light mediator scenario, the strongest laboratory constraint for DM lighter than 0.1 MeV/$c^2$ is presented. The result proves the feasibility and demonstrates the vast potential of the VCA technique in future accelerated DM-electron analyses with semiconductor detectors., Comment: 7 pages, 4 figures. Version updated to match PRL version
Published: 2023
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24. Mapper of the IGM spin temperature: instrument overview

Author: Monsalve, R. A., Altamirano, C., Bidula, V., Bustos, R., Bye, C. H., Chiang, H. C., Diaz, M., Fernandez, B., Guo, X., Hendricksen, I., Hornecker, E., Lucero, F., Mani, H., McGee, F., Mena, F. P., Pessoa, M., Prabhakar, G., Restrepo, O., Sievers, J. L., and Thyagarajan, N.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The observation of the global 21 cm signal produced by neutral hydrogen gas in the intergalactic medium (IGM) during the Dark Ages, Cosmic Dawn, and Epoch of Reionization requires measurements with extremely well-calibrated wideband radiometers. We describe the design and characterization of the Mapper of the IGM Spin Temperature (MIST), which is a new ground-based, single-antenna, global 21 cm experiment. The design of MIST was guided by the objectives of avoiding systematics from an antenna ground plane and cables around the antenna, as well as maximizing the instrument's on-sky efficiency and portability for operations at remote sites. We have built two MIST instruments, which observe in the range 25-105 MHz. For the 21 cm signal, this frequency range approximately corresponds to redshifts 55.5 > z > 12.5, encompassing the Dark Ages and Cosmic Dawn. The MIST antenna is a horizontal blade dipole of 2.42 m in length, 60 cm in width, and 52 cm in height above the ground. This antenna operates without a metal ground plane. The instruments run on 12 V batteries and have a maximum power consumption of 17 W. The batteries and electronics are contained in a single receiver box located under the antenna. We present the characterization of the instruments using electromagnetic simulations and lab measurements. We also show sample sky measurements from recent observations at remote sites in California, Nevada, and the Canadian High Arctic. These measurements indicate that the instruments perform as expected. Detailed analyses of the sky measurements are left for future work., Comment: Matches version published in MNRAS
Published: 2023
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25. Projected WIMP sensitivity of the CDEX-50 dark matter experiment

Author: Geng, X. P., Yang, L. T., Yue, Q., Kang, K. J., Li, Y. J., An, H. P., C., Greeshma, Chang, J. P., Chen, Y. H., Cheng, J. P., Dai, W. H., Deng, Z., Fang, C. H., Gong, H., Guo, Q. J., Guo, T., Guo, X. Y., He, L., He, S. M., Hu, J. W., Huang, H. X., Huang, T. C., Jiang, L., Karmakar, S., Li, H. B., Li, H. Y., Li, J. M., Li, J., Li, Q. Y., Li, R. M. J., Li, X. Q., Li, Y. L., Liang, Y. F., Liao, B., Lin, F. K., Lin, S. T., Liu, J. X., Liu, S. K., Liu, Y. D., Liu, Y., Liu, Y. Y., Ma, H., Mao, Y. C., Nie, Q. Y., Ning, J. H., Pan, H., Qi, N. C., Ren, J., Ruan, X. C., Singh, M. K., Sun, T. X., Tang, C. J., Tian, Y., Wang, G. F., Wang, J. Z., Wang, L., Wang, Q., Wang, Y. F., Wang, Y. X., Wong, H. T., Wu, S. Y., Wu, Y. C., Xing, H. Y., Xu, R., Xu, Y., Xue, T., Yan, Y. L., Yi, N., Yu, C. X., Yu, H. J., Yue, J. F., Zeng, M., Zeng, Z., Zhang, B. T., Zhang, F. S., Zhang, L., Zhang, Z. H., Zhang, Z. Y., Zhao, J. Z., Zhao, K. K., Zhao, M. G., Zhou, J. F., Zhou, Z. Y., and Zhu, J. J.
Subjects: High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract: CDEX-50 is a next-generation project of the China Dark Matter Experiment (CDEX) that aims to search for dark matter using a 50-kg germanium detector array. This paper comprises a thorough summary of the CDEX-50 dark matter experiment, including an investigation of potential background sources and the development of a background model. Based on the baseline model, the projected sensitivity of weakly interacting massive particle (WIMP) is also presented. The expected background level within the energy region of interest, set to 2--2.5 keVee, is $\sim$0.01 counts keVee$^{-1}$ kg$^{-1}$ day$^{-1}$. At 90\% confidence level, the expected sensitivity to spin-independent WIMP-nucleon couplings is estimated to reach a cross-section of 5.1 $\times$ 10$^{-45}$ cm$^{2}$ for a WIMP mass of 5 GeV/c$^{2}$ with an exposure objective of 150 kg$\cdot$year and an analysis threshold of 160 eVee. This science goal will correspond to the most sensitive results for WIMPs with a mass of 2.2--8 GeV/c$^{2}$., Comment: 12 pages, 11 figures. Version updated to match JCAP version
Published: 2023
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26. Grand Challenges at the Interface of Engineering and Medicine.

Author: Subramaniam, Shankar, Akay, Metin, Anastasio, Mark, Bailey, Vasudev, Boas, David, Bonato, Paolo, Chilkoti, Ashutosh, Cochran, Jennifer, Colvin, Vicki, Desai, Tejal, Duncan, James, Epstein, Frederick, Fraley, Stephanie, Giachelli, Cecilia, Grande-Allen, K, Green, Jordan, Guo, X, Hilton, Isaac, Humphrey, Jay, Johnson, Chris, Karniadakis, George, King, Michael, Kirsch, Robert, Kumar, Sanjay, Laurencin, Cato, Li, Song, Lieber, Richard, Lovell, Nigel, Mali, Prashant, Margulies, Susan, Meaney, David, Ogle, Brenda, Palsson, Bernhard, A Peppas, Nicholas, Perreault, Eric, Rabbitt, Rick, Setton, Lori, Shea, Lonnie, Shroff, Sanjeev, Shung, Kirk, Tolias, Andreas, van der Meulen, Marjolein, Varghese, Shyni, Vunjak-Novakovic, Gordana, White, John, Winslow, Raimond, Zhang, Jianyi, Zhang, Kun, Zukoski, Charles, and Miller, Michael
Subjects: Genome-engineering, artificial intelligence, biomanufacturing, biomaterials, bioreactors, bone, brain, brain-computer interfaces, cell therapy, digital twins, disease resistance, drug testing, gene therapy, heart, human function augmentation, immuno-engineering, lung, machine learning, models of disease, neuroimaging, neuromodulation, organ regeneration, organs-on-chip, patient on a chip, precision medicine, stem cells, synthetic biology, tissue engineering
Abstract: Over the past two decades Biomedical Engineering has emerged as a major discipline that bridges societal needs of human health care with the development of novel technologies. Every medical institution is now equipped at varying degrees of sophistication with the ability to monitor human health in both non-invasive and invasive modes. The multiple scales at which human physiology can be interrogated provide a profound perspective on health and disease. We are at the nexus of creating avatars (herein defined as an extension of digital twins) of human patho/physiology to serve as paradigms for interrogation and potential intervention. Motivated by the emergence of these new capabilities, the IEEE Engineering in Medicine and Biology Society, the Departments of Biomedical Engineering at Johns Hopkins University and Bioengineering at University of California at San Diego sponsored an interdisciplinary workshop to define the grand challenges that face biomedical engineering and the mechanisms to address these challenges. The Workshop identified five grand challenges with cross-cutting themes and provided a roadmap for new technologies, identified new training needs, and defined the types of interdisciplinary teams needed for addressing these challenges. The themes presented in this paper include: 1) accumedicine through creation of avatars of cells, tissues, organs and whole human; 2) development of smart and responsive devices for human function augmentation; 3) exocortical technologies to understand brain function and treat neuropathologies; 4) the development of approaches to harness the human immune system for health and wellness; and 5) new strategies to engineer genomes and cells.
Published: 2024

27. Circulating Protectin D1 and Neutrophils Extracellular Traps in the Diagnosis and Progression of Acute Pancreatitis

Author: Wu Z, Lu W, Zhang X, Xia Q, Zuo H, Guo X, Liu Y, Zhang F, and Zhang L
Subjects: pd1, acute pancreatitis, cith3, mpo-dna, infected pancreatic necrosis, organ failure, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Zhiyang Wu,1,&ast; Wenjun Lu,2,&ast; Xin Zhang,1 Qiaoying Xia,2 Han Zuo,2 Xi Guo,1 Yu Liu,1 Fan Zhang,3 Xin Zhang,4 Luyao Zhang2 1Department of Critical Care Medicine, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, Shandong, People’s Republic of China; 2Department of Pathology and Pathophysiology, School of Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China; 3Department of Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Qingdao, Shandong, People’s Republic of China; 4Department of General Surgery, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, Shandong, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Luyao Zhang, Department of Pathology and Pathophysiology, School of Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China, Email zhangluyao@njucm.edu.cn Xin Zhang, Department of General Surgery, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, Shandong, People’s Republic of China, Email 514557061@qq.comPurpose: Protectin D1 (PD1), a biologically active molecule derived from docosahexaenoic acid (DHA), plays a major role in the body’s endogenous lipid-mediated inflammatory response. The study aims to explore the relationship between PD1, inflammatory response and the severity of acute pancreatitis (AP).Patients and Methods: Sixty consecutive AP patients within 72h of disease onset were enrolled as the study group, a further thirty healthy people were enrolled as the control group. General demographics collected at the time of enrollment. Serum PD1, Citrullinated Histone 3 (CitH3), myeloperoxidase-Deoxyribonucleic acid (MPO-DNA), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) level were measured in AP patients on enrollment day 0, day 1, day 3 and day 7. Meanwhile, the Acute Physiology and Chronic Health evaluation II (APACHE II) scores, Sequential Organ Failure Assessment (SOFA) scores were also evaluated on day 0, day 1, day 3 and day 7.Results: AP was severe in 29 patients (48.3%), moderately severe acute pancreatitis (MSAP) was found in 9 patients (15%), and mild acute pancreatitis (MAP) was found in 22 patients (36.7%). The level of PD1, CitH3 and MPO-DNA were statistically significantly higher in AP patients than in the healthy population. Serum PD1, CitH3 and MPO-DNA concentration increased with AP severity. In AP patients, PD1 has a strong linear association with TNF-α, CitH3 and MPO-DNA. The AUC for SAP predicted by PD1 was 0.938. The calculated cut-off point for prognosis SAP is 7.94 pg/mL. The AUC for infected pancreatic necrosis (IPN) predicted by PD1 was 0.836 and the cut-off point was 8.65 pg/mL. The AUC for organ failure (OF) predicted by PD1 was 0.719 and the cut-off point was 7.94 pg/mL.Conclusion: PD1 is associated with both the presence of AP and the severity of pancreatitis.Keywords: PD1, acute pancreatitis, CitH3, MPO-DNA, infected pancreatic necrosis, organ failure
Published: 2024

28. Protopine Exerts Neuroprotective Effects on Neonatal Hypoxic-Ischemic Brain Damage in Rats via Activation of the AMPK/PGC1α Pathway

Author: Lu L, Pang M, Chen T, Hu Y, Chen L, Tao X, Chen S, Zhu J, Fang M, Guo X, and Lin Z
Subjects: neonatal hypoxic-ischemic brain damage, protopine, reactive oxygen species, apoptosis, mitochondrial biogenesis, Therapeutics. Pharmacology, RM1-950
Abstract: Liying Lu,1,2 Mengdan Pang,1,2 Tingting Chen,1,2 Yingying Hu,1,2 Likai Chen,3 Xiaoyue Tao,1,2 Shangqin Chen,1,2 Jianghu Zhu,1,2 Mingchu Fang,1,2 XiaoLing Guo,1,4 Zhenlang Lin1,2,4 1Department of Pediatrics, The Second School of Medicine, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People’s Republic of China; 2Key Laboratory of Perinatal Medicine of Wenzhou, the Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People’s Republic of China; 3Elson S. Floyd College of Medicine at Washington State University, Spokane, WA, USA; 4Basic Medical Research Center, the Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People’s Republic of ChinaCorrespondence: XiaoLing Guo; Zhenlang Lin, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, 109 Xueyuan West Road, Wenzhou, Zhejiang, 325027, People’s Republic of China, Tel +00-86-138-0668-9800, Fax +86-0577-88002198, Email guoxling@hotmail.com; linzhenlang@hotmail.comIntroduction: Neonatal hypoxic-ischemic encephalopathy (HIE), caused by perinatal asphyxia, is characterized by high morbidity and mortality, but there are still no effective therapeutic drugs. Mitochondrial biogenesis and apoptosis play key roles in the pathogenesis of HIE. Protopine (Pro), an isoquinoline alkaloid, has anti-apoptotic and neuro-protective effects. However, the protective roles of Pro on neonatal hypoxic-ischemic brain injury remain unclear.Methods: In this study, we established a CoCl2-induced PC12 cell model in vitro and a neonatal rat hypoxic-ischemic (HI) brain damage model in vivo to explore the neuro-protective effects of Pro and try to elucidate the potential mechanisms.Results: Our results showed that Pro significantly reduced cerebral infarct volume, alleviated brain edema, inhibited glia activation, improved mitochondrial biogenesis, relieved neuron cell loss, decreased cell apoptosis and reactive oxygen species (ROS) after HI damage. In addition, Pro intervention upregulated the levels of p-AMPK/AMPK and PGC1α as well as the downstream mitochondrial biogenesis related factors, such as nuclear respiratory factor 1 (NRF1) and mitochondrial transcription factor A (TFAM), but the AMPK inhibitor compound c (CC) could significantly reverse these effects of Pro.Discussion: Pro may exert neuroprotective effects on neonatal hypoxic-ischemic brain damage via activation of the AMPK/PGC1α pathway, suggesting that Pro may be a promising therapeutic candidate for HIE, and our study firstly demonstrate the neuro-protective roles of Pro in HIE models.Keywords: neonatal hypoxic-ischemic brain damage, protopine, reactive oxygen species, apoptosis, mitochondrial biogenesis
Published: 2024

29. Risk Factors Analysis and Prediction Model Establishment for Carbapenem-Resistant Enterobacteriaceae Colonization: A Retrospective Cohort Study

Author: Guo X, Wu D, Chen X, Lin J, Chen J, Wang L, Shi S, Yang H, Liu Z, and Hong D
Subjects: carbapenem-resistant enterobacteriaceae, intensive care unit, colonization, risk factors, risk prediction model, Infectious and parasitic diseases, RC109-216
Abstract: Xiaolan Guo,1 Dansen Wu,1 Xiaoping Chen,2 Jing Lin,1 Jialong Chen,1 Liming Wang,1 Songjing Shi,1 Huobao Yang,1 Ziyi Liu,3 Donghuang Hong1,4 1Department of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, People’s Republic of China; 2Computer Science and Mathematics, Fujian University of Technology, Fuzhou, Fujian, People’s Republic of China; 3Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 4Fujian Provincial Key Laboratory of Critical Care Medicine, Fuzhou, Fujian, People’s Republic of ChinaCorrespondence: Ziyi Liu, Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, No. 160, Pujian Road, Pudong District, Shanghai, 200127, People’s Republic of China, Email liu-ziyi@sjtu.edu.cn Donghuang Hong, Department of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, No. 134, Dongjie Street, Gulou District, Fuzhou, Fujian, 350001, People’s Republic of China, Email hongdh2003@fjmu.edu.cnPurpose: The objective of this study was to identify the risk factors associated with Carbapenem-resistant Enterobacteriaceae (CRE) colonization in intensive care unit (ICU) patients and to develop a predictive risk model for CRE colonization.Patients and Methods: In this study, 121 ICU patients from Fujian Provincial Hospital were enrolled between January 2021 and July 2022. Based on bacterial culture results from rectal and throat swabs, patients were categorized into two groups: CRE-colonized (n = 18) and non-CRE-colonized (n = 103). To address class imbalance, Synthetic Minority Over-sampling Technique (SMOTE) was applied. Statistical analyses including T-tests, Chi-square tests, and Mann–Whitney U-tests were employed to compare differences between the groups. Feature selection was performed using Lasso regression and Random Forest algorithms. A Logistic regression model was then developed to predict CRE colonization risk, and the results were presented in a nomogram.Results: After applying SMOTE, the dataset included 198 CRE-colonized patients and 180 non-CRE-colonized patients, ensuring balanced groups. The two groups were comparable in most clinical characteristics except for diabetes, previous emergency department admission, and abdominal infection. Eight independent risk factors for CRE colonization were identified through Random Forest, Lasso regression, and Logistic regression, including Acute Physiology and Chronic Health Evaluation (APACHE) II score > 16, length of hospital stay > 31 days, female gender, previous carbapenem antibiotic exposure, skin infection, multi-site infection, immunosuppressant exposure, and tracheal intubation. The risk prediction model for CRE colonization demonstrated high accuracy (87.83%), recall rate (89.9%), precision (85.6%), and an AUC value of 0.877. Patients were categorized into low-risk (0– 90 points), medium-risk (91– 160 points), and high-risk (161– 381 points) groups, with corresponding CRE colonization rates of 1.82%, 7.14%, and 58.33%, respectively.Conclusion: This study identified independent risk factors for CRE colonization and developed a predictive model for assessing the risk of CRE colonization.Keywords: carbapenem-resistant Enterobacteriaceae, intensive care unit, colonization, risk factors, risk prediction model
Published: 2024

30. Multiomics Analysis Reveals Significant Disparities in the Oral Microbiota and Metabolites Between Pregnant Women with and without Periodontitis

Author: Zhao M, Yang C, Zhu L, Guo X, Ma H, Luo Y, Wang Q, and Chen J
Subjects: pregnancy-induced periodontitis, oral microbiota composition, predicted functional modules, microbial metabolites profiling, biomarkers identification., Infectious and parasitic diseases, RC109-216
Abstract: Min Zhao,1 Changyi Yang,1 Linhong Zhu,1 Xiaoqian Guo,1 Haiyan Ma,2 Yuanhao Luo,3 Qi Wang,4 Juanjuan Chen4 1Department of Periodontology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, 750004, People’s Republic of China; 2School of Stomatology, Ningxia Medical University, Yinchuan, Ningxia, 750004, People’s Republic of China; 3The Second Clinical Medical School, Lanzhou University, Lanzhou, Gansu, 730030, People’s Republic of China; 4Cuiying Biomedical Research Center, Lanzhou University Second Hospital, Lanzhou, Gansu, 730030, People’s Republic of ChinaCorrespondence: Juanjuan Chen; Qi Wang, Email ery_juanjuanchen@lzu.edu.cn; ery_wangqery@lzu.edu.cnIntroduction: Our study investigated the disparities and correlations between oral microbiota and metabolites in pregnant patients with and without periodontitis.Methods: Subgingival plaque samples from all subjects were collected for shotgun metagenomic sequencing and broad-target metabolomics analysis.Results: Forty pathogens, including Porphyromonas gingivalis, Fusobacterium nucleatum, Eubacterium saphenum, Gemella morbillorum, Tannerella forsythia, Streptococcus anginosus group, Selenomonas sputigena etc, were significantly enriched in pregnant patients with periodontitis (PPP). Conversely, symbiotic species such as Morococcus cerebrosus, Streptococcus vestibularis, S. salivarius, S. mitis, and S. pneumoniae were significantly more abundant in healthy controls (HCs). A total of 87 predicted functional modules (PFMs) exhibited significant differences between the two groups; eight PFMs showed high enrichment in PPP with involvement of PPP-enriched species within these pathways. The remaining 79 PFMs encompassing ribonucleotide biosynthesis, carbohydrate, and amino acid metabolism were highly abundant in HCs. For oral microbial metabolome, a total of 105 metabolites related to 150 KEGG pathways displayed significant differences between the two groups. Pathways such as pyruvate metabolism, folate biosynthesis, vascular smooth muscle contraction, and AMPK/mTOR signaling pathway along with their associated metabolites were found to be enriched in PPP, while carbohydrate metabolism predominated among HCs. Spearman’s rank correlation analysis revealed significant positive associations between species enriched in PPP and metabolites enriched in PPP, but significant negative associations between species enriched in PPP and metabolites enriched in HCs.Discussion: Our findings provide potential biomarkers for distinguishing periodontitis during pregnancy while offering valuable insights into mechanisms exploration and clinical intervention.Keywords: Pregnancy-induced periodontitis, oral microbiota composition, predicted functional modules, microbial metabolites profiling, biomarkers identification
Published: 2024

31. Clinical Features and Electroencephalogram Analysis of Brain Network Functional Connectivity in Anti-Leucine-Rich Glioma-Inactivated 1 Antibody Encephalitis

Author: Guo X, Shi H, Sun Y, Xing Y, Shen Z, Zheng M, Zhang Y, Jia Y, Li Y, Bao J, and Tian S
Subjects: anti-lgi1 antibody encephalitis, epilepsy, electroencephalogram, brain network functional connectivity, immunotherapy, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Xiaosu Guo,1– 4,&ast; Huimin Shi,1,2,&ast; Yuteng Sun,1 Yuan Xing,1– 3 Xin Guo,1– 3 Zhiyuan Shen,1– 3 Mengyi Zheng,1 Yaxin Zhang,1 Yicun Jia,1 Ye Li,1 Junqiang Bao,1,2 Shujuan Tian1– 3 1Department of Neurology, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, People’s Republic of China; 2Department of Neurology, Hebei Hospital, Xuanwu Hospital, Capital Medical University, Shijiazhuang, Hebei, People’s Republic of China; 3Neuromedical Technology Innovation Center of Hebei Province, Shijiazhuang, Hebei, People’s Republic of China; 4Brain Aging and Cognitive Neuroscience Laboratory of Hebei Province, Shijiazhuang, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Shujuan Tian; Junqiang Bao, Department of Neurology, The First hospital of Hebei Medical University, Shijiazhuang, Hebei, 050030, People’s Republic of China, Tel +86-0311-87156309, Email 57203005@hebmu.edu.cn; 57903004@hebmu.edu.cnPurpose: To summarize the clinical manifestations, laboratory findings, and magnetic resonance imaging (MRI) characteristics of anti-leucine-rich glioma-inactivated 1 (LGI1) antibody encephalitis (anti-LGI1 antibody encephalitis) and explore the electroencephalogram (EEG) features.Patients and Methods: We retrospectively analyzed the medical history of 16 patients diagnosed with anti-LGI1 antibody encephalitis at the First Hospital of Hebei Medical University from 2021 to 2023. EEGs of patients with anti-LGI1 antibody encephalitis and healthy individuals were analyzed. Based on Video-EEG signal analysis of EEG δ, θ, α, β frequency bands, weighted phase lag index values were calculated to form brain network matrices, studying differences in coherence between brain regions of patients with anti-LGI1 antibody encephalitis and healthy individuals.Results: Patients with anti-LGI1 antibody encephalitis often presented with subacute onset seizures and cognitive decline. Routine test of cerebrospinal fluid was mostly normal. Serum testing revealed hyponatremia in 62.50% of patients, along with positive serum antinuclear antibodies, decreased vitamin B12, and abnormal cytokines such as interleukin-6. Head MRI revealed abnormal lesions related to the disease in seven cases (43.75%), mainly located in the unilateral or bilateral frontal and temporal lobes of the hippocampus. The EEG mainly showed generalized and focal slow waves, sometimes with focal discharges. Brain network functional connectivity analysis found a significant weakening of functional connections in the frontal-temporal lobe in the δ and β frequency bands. Intravenous pulse corticosteroids and intravenous immunoglobulin are first-line immunotherapies for anti-LGI1 antibody-related encephalitis. The disease recovery and cognitive decline improved in most patients.Conclusion: Anti-LGI1 antibody encephalitis is characterized by seizures and cognitive dysfunction. Serum may show abnormalities in immune indicators such as cytokines. Head MRI mainly reveals abnormal signals in the frontal-temporal lobes and the hippocampus. EEG brain network connectivity analysis reveals characteristic weakening of functional connections in the frontal-temporal lobe in the δ and β frequency bands.Keywords: anti-LGI1 antibody encephalitis, epilepsy, electroencephalogram, brain network functional connectivity, immunotherapy
Published: 2024

32. Clinical Outcomes of Exercise Rehabilitation for Degenerative Tibial Meniscal Tears: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Author: Mao S, Xiao K, Xu H, Wang Y, and Guo X
Subjects: degenerative meniscus injury, exercise rehabilitation, non-pharmacological treatment, pain, Medicine (General), R5-920
Abstract: Sujie Mao,1 Kaiwen Xiao,2 Hong Xu,3 YanAn Wang,4 Xiujin Guo2 1Graduate Department, Harbin Sport University, Harbin, Heilongjiang, People’s Republic of China; 2School of Sports Industry and Leisure, Nanjing Sport Institute, Nanjing, Jiangsu, People’s Republic of China; 3College of Sports and Health, Sangmyung University, Seoul, South Korea; 4Academic Affairs Office, Jiangsu Police College, Nanjing, Jiangsu, People’s Republic of ChinaCorrespondence: Xiujin Guo, Nanjing Sport Institute, No. 8, Linggu Temple, XuanWu District, Nanjing, Jiangsu, People’s Republic of China, Email ntxiujin@163.comObjective: This study aims to comprehensively evaluate the effectiveness of exercise rehabilitation therapy for patients with Degenerative Meniscal Lesions of the Tibia (DMLT), providing more effective and safer treatment options for DMLT patients and offering more reliable evidence-based medical recommendations.Methods: Adhering to the PRISMA guidelines, this research conducted a literature search through databases such as PubMed, Web of Science, EMBASE, EBSCOhost, and Cochrane, with the search cut-off date being January 2024. Following the PICOS principles, a comprehensive search was conducted. Two researchers independently screened the literature and extracted data. Using R software, effect size analyses were conducted on indicators such as pain, knee joint function, lower limb muscle strength, and physical function in DMLT patients, with the significance level set at P< 0.05, aiming to comprehensively assess the impact of exercise therapy on the rehabilitation outcomes for DMLT patients.Results: The study included 12 randomized controlled trials, encompassing 1336 DMLT patients. Based on the quality assessment using the modified Jadad scale, the overall quality of the included studies was determined to be moderate.The meta-analysis showed that exercise therapy significantly reduced pain (WMD=− 5.50, P< 0.05), improved lower limb muscle strength (SMD=0.05, P< 0.05), and enhanced physical function (SMD=0.65, P< 0.05). Subgroup analyses revealed that, compared to surgery alone, exercise therapy combined with surgery had a significant effect on improving muscle strength and physical function. Functional training and home-based exercises showed more pronounced effects on specific indicators. The study results indicate that exercise therapy alone has limited effectiveness in improving knee joint function, and combining exercise with surgery does not show a significant advantage (P > 0.05). Additionally, subgroup analysis revealed no significant impact of intervention duration, exercise type, or patient age on functional improvement.Conclusion: Exercise therapy has shown potential in alleviating pain, enhancing lower limb muscle strength, and improving mobility in patients with degenerative meniscal lesions of the tibia (DMLT). Functional training and varied rehabilitation exercises may provide effective pathways for long-term recovery in these patients.Registration: This study has been registered in a prospective registry platform with the registration number: CRD42024518643.Keywords: degenerative meniscus injury, exercise rehabilitation, non-pharmacological treatment, pain
Published: 2024

33. Dynamic Insights: Unraveling Public Demand Evolution in Health Emergencies Through Integrated Language Models and Spatial-Temporal Analysis

Author: Zhang Y, Fu L, Guo X, and Li M
Subjects: public demands, spatial-temporal evolution, dynamic topic mining, health emergency management, public health emergencies, Public aspects of medicine, RA1-1270
Abstract: Yuan Zhang,1 Lin Fu,2 Xingyu Guo,1 Mengkun Li1 1School of Management, Capital Normal University, Beijing, People’s Republic of China; 2School of Management, China Women’s University, Beijing, People’s Republic of ChinaCorrespondence: Yuan Zhang; Mengkun Li, Email zhangyuan@cnu.edu.cn; limengkun@cnu.edu.cnBackground and Purpose: In public health emergencies, rapid perception and analysis of public demands are essential prerequisites for effective crisis communication. Public demands serve as the most instinctive response to the current state of a public health crisis. Therefore, the government must promptly grasp and leverage public demands information to enhance the effectiveness and efficiency of health emergency management, that is planned to better deal with the outbreak and meet the medical demands of the public.Methods: This study employs dynamic topic mining and knowledge graph construction to analyze public demands, presenting a spatial-temporal evolution analysis method for emergencies based on EBU models. EBU models are three large language models, including ERNIE, BERTopic, and UIE.Results: The data analysis of Shanghai’s city closure and control during the COVID-19 epidemic has verified that this method can simplify the labeling and training process, and can use massive social media data to quickly, comprehensively, and accurately analyze public demands from both time and space dimensions. From the visual analysis, geographic information on public demands can be quickly obtained and areas with serious problems can be located. The classification of geographical information can help guide the formulation and implementation of government policies at different levels, and provide a basis for health emergency material dispatch.Conclusion: This study extends the scope and depth of research on health emergency management, enriching subject categories and research methods in the context of public health emergencies. The use of social media data underscores its potential as a valuable tool for analyzing public demands. The method can provide rapid decision supports for decision-making for public services such as government departments, centers for disease control, medical emergency centers and transport authorities.Keywords: public demands, spatial-temporal evolution, dynamic topic mining, health emergency management, public health emergencies
Published: 2024

34. KRAS Gene Mutation Associated with Grade of Tumor Budding and Peripheral Immunoinflammatory Indices in Patients with Colorectal Cancer

Author: Liang L, Guo X, Ye W, and Liu Y
Subjects: colorectal cancer, kras, systemic immune inflammation index, tumor budding, Medicine (General), R5-920
Abstract: Liu Liang,1 Xuemin Guo,1 Wei Ye,1 Yuxiang Liu2 1Department of Laboratory Medicine, Meizhou People’s Hospital, Meizhou, People’s Republic of China; 2Department of Medical Oncology, Meizhou People’s Hospital, Meizhou, People’s Republic of ChinaCorrespondence: Liu Liang, Department of Laboratory Medicine, Meizhou People’s Hospital, Meizhou, People’s Republic of China, Email 19926117315@163.comBackground: The efficacy of targeted therapy for colorectal cancer (CRC) is affected by hub genes of epidermal growth factor receptor (EGFR) signaling pathways, such as KRAS. Immune cell infiltration may lead to gene mutation, but the relationship between KRAS status and peripheral immune-inflammatory indices has not been clarified in CRC.Methods: Clinical records of CRC patients were collected. The relationship between KRAS status and clinicopathological characteristics, peripheral immune-inflammatory indices (pan-immune inflammation value (PIV) (monocyte×neutrophil×platelet/lymphocyte), systemic immune inflammation index (SII) (platelet×neutrophil/lymphocyte), and system inflammation response index (SIRI) (monocyte×neutrophil/lymphocyte)) were analyzed.Results: 1033 CRC patients were collected, there were 514 (49.8%) patients with KRAS wild-type and 519 (50.2%) with KRAS mutation. Patients with KRAS mutation had higher proportions of female, III-IV stage, and lymph node metastasis and lower proportion of low grade of tumor budding (the presence of single tumor cells or small clusters of up to 5 cells in mesenchyma at the front of tumor invasion) than those with KRAS wild-type. The PIV, SII, and SIRI levels in KRAS mutation patients were significantly higher than those in KRAS wild-type patients. The proportion of aged ≥ 65 years old, dMMR, distant metastasis, and KRAS mutation were high in patients with high PIV, SII, and SIRI levels. Logistic regression analysis showed that non-low grade of tumor budding (odds ratio (OR): 1.970, 95% confidence interval (CI): 1.287– 3.016, p=0.002), and high SII level (≥ 807.81 vs < 807.81, OR: 1.915, 95% CI: 1.120– 3.272, p=0.018) were independently associated with KRAS mutation.Conclusion: Non-low grade of tumor budding, and high SII level were independently associated with KRAS mutation in CRC. It provides additional references for diagnosis and treatment options for patients with CRC.Keywords: colorectal cancer, KRAS, systemic immune inflammation index, tumor budding
Published: 2024

35. Effects of Sleep Quality, Acute Sleep Deprivation, and Napping on Facial Emotion Recognition Accuracy and Speed

Author: Huang Y, Li Y, Su T, Wang H, Xu S, Xu J, Zheng S, Du J, Wang Y, Zhang R, Meng Y, Guo X, Xiao L, and Tang Y
Subjects: facial emotion recognition, sleep quality, facial features, facial emotion, sleep deprivation, sleep loss, Psychiatry, RC435-571, Neurophysiology and neuropsychology, QP351-495
Abstract: Yujia Huang,1,2,&ast; Yinan Li,2,&ast; Tong Su,3 Hao Wang,2 Shuyu Xu,2 Jingzhou Xu,2 Siqi Zheng,4 Jing Du,2 Yajing Wang,2 Ruike Zhang,2 Yao Meng,2 Xin Guo,2 Lei Xiao,2 Yunxiang Tang3 1Psychology Department, The Second Naval Hospital of Southern Theater Command, Sanya, People’s Republic of China; 2Department of Medical Psychology, Faculty of Psychology, Naval Medical University, Shanghai, People’s Republic of China; 3Faculty of Psychology, Naval Medical University, Shanghai, People’s Republic of China; 4Department of Psychology, TongJi University, Shanghai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Lei Xiao; Yunxiang Tang, Email xiaolei0237@163.com; tangyun7633@sina.comObjective: To investigate the effects of sleep quality, sleep deprivation, and napping on facial emotion recognition (FER) accuracy and speed.Methods: This research included a cross-sectional study (102 qualified participants) and a randomized controlled study (26 in the napping group and 24 in the control group). The stimuli for the FER task were obtained from the Chinese Facial Affective Picture System (CFAPS). Four facial expressions (fearful, disgusted, sad, and angry) were used. The Pittsburgh Sleep Quality Index (PSQI), Self-Rating Anxiety Scale, and Self-Rating Depression Scale were used to measure participants’ sleep quality and psychological conditions. In Study 1, FER ability was compared between good and poor sleepers. In Study 2, all participants were sleep-deprived for one night, and completed the FER task before and after sleep deprivation. After different interventions (ie, napping for one hour, or walking around for ten minutes), the participants completed the third FER task.Results: Study 1: Poor sleepers were able to recognize sad expressions more accurately compared with good sleepers. Study 2: 30-h sleep deprivation had no significant effect on the accuracy (ACC). Napping after sleep deprivation improved the FER ACC of upper-face expressions and marginally significantly improved the FER ACC of disgusted expressions.Conclusion: Better sleep quality was linked to lower FER accuracy, particularly in recognizing sad expressions, while no significant differences in recognition speed were observed. Additionally, 30 hours of sleep deprivation did not affect FER accuracy, but napping after sleep deprivation improved accuracy for upper-face and marginally for disgusted expressions.Keywords: facial emotion recognition, sleep quality, facial features, facial emotion, sleep deprivation, sleep loss
Published: 2024

36. The Impact of Bispectral Index Monitoring on Outcomes in Spinal Cord Stimulation for Chronic Disorders of Consciousness

Author: Chen X, Qin X, Zhuang Y, Li Z, Liang Z, Zhang H, Yao L, Li X, He J, and Guo X
Subjects: chronic disturbance of consciousness, vegetative state/ unresponsive wakefulness syndrome, spinal cord stimulation, general anesthesia, bispectral index, improved coma recovery scale, Therapeutics. Pharmacology, RM1-950
Abstract: Xuanling Chen,1,&ast; Xuewei Qin,1,&ast; Yutong Zhuang,2 Zhengqian Li,3 Zhenhu Liang,4 Hua Zhang,5 Lan Yao,1 Xiaoli Li,6 Jianghong He,7 Xiangyang Guo3 1Department of Anesthesiology, Peking University International Hospital, Beijing, People’s Republic of China; 2Department of Neurosurgery, The Second School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, People’s Republic of China; 3Department of Anesthesiology, Peking University Third Hospital, Beijing, People’s Republic of China; 4Institute of Electrical Engineering, Yanshan University, Qinhuangdao, People’s Republic of China; 5Clinical Epidemiology Research Center, Peking University Third Hospital, Beijing, People’s Republic of China; 6The State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, People’s Republic of China; 7Department of Neurosurgery, Tiantan Hospital, Capital Medical University, Beijing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xiangyang Guo, Peking University, Third Hospital, 49 huayuan North Road, Haidian District, Beijing, 100191, People’s Republic of China, Email puthmzk@hsc.pku.edu.cn Jianghong He, Beijing Tiantan Hospital, 119 South Fourth Ring Road West, Fengtai District, Beijing, 100069, People’s Republic of China, Email hejianghong@sina.cnObjective: To observe whether maintaining the appropriate depth of anesthesia with Bispectral Index (BIS) can improve the prognosis of Spinal Cord stimulation (SCS) implantation in patients with chronic Disorders of consciousness (DoC).Methods: 103 patients with DoC undergoing SCS implantation were reviewed, and 83 patients with DoC were included according to the standard of inclusion and exclusion Criteria. Patients were divided into a BIS group (n =45) and a non-BIS group (n =38) according to whether BIS monitoring was used during the operation. The depth of anesthesia in the BIS group was maintained between 40– 60. The anesthesiologist adjusted the depth of anesthesia in the non-BIS group according to clinical experience. Relevant information such as disease course, cause, anesthesia time, and operation time were collected. Preoperative CRS-R(preoperative) score, postoperative CRS-R(24h), and postoperative CRS-R(3m) changes were collected.Results: The CRS-R(3m) score in the BIS group was higher than that in the non-BIS group (preoperative), and the difference was statistically significant (P < 0.05). In CRS-R (24h), the BIS group was higher than the non-BIS group, and the difference was statistically significant (X2=8.787, P =0.004). The improvement of consciousness was included in the multivariate Logistic regression analysis model, and it was found that the thalamus was an independent factor affecting the improvement of consciousness (P < 0.05). During follow-up, 1 patient in the BIS group had a decrease in consciousness from MCS− to VS/ UWS and 2 patients in the non-BIS group died during follow-up.Conclusion: Patients can be benefit in hearing in CRS-R (24h). We recommend the use of BIS to monitor the depth of anesthesia in patients with DoC to improve patient outcomes.Keywords: chronic disturbance of consciousness, vegetative state/unresponsive wakefulness syndrome, spinal cord stimulation, general anesthesia, bispectral index, improved coma recovery scale
Published: 2024

37. Associations of Intermittent Hypoxia Burden with Gut Microbiota Dysbiosis in Adult Patients with Obstructive Sleep Apnea

Author: Guo W, Sun L, Yue H, Guo X, Chen L, Zhang J, Chen Z, Wang Y, Wang J, and Lei W
Subjects: obstructive sleep apnea, gut microbiota, 16s rrna, intermittent hypoxia, Psychiatry, RC435-571, Neurophysiology and neuropsychology, QP351-495
Abstract: Wenbin Guo,1,&ast; Lin Sun,1,&ast; Huijun Yue,1,&ast; Xueqin Guo,1 Lin Chen,1 Jinhong Zhang,1 Zhuqi Chen,1 Yiming Wang,1 Jiao Wang,2 Wenbin Lei1 1Otorhinolaryngology Hospital, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, 510080, People’s Republic of China; 2School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jiao Wang, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, Guangdong, People’s Republic of China, Email wangj836@mail.sysu.edu.cn Wenbin Lei, Otorhinolaryngology Hospital, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, Guangdong, People’s Republic of China, Email leiwb@mail.sysu.edu.cnPurpose: Clinical studies focusing on the association between the gut microbiota and obstructive sleep apnea (OSA) are limited. This study aimed to explore the relationship between intermittent hypoxia and the composition of gut microbiota in adults by analyzing the differences in the characteristics and functional distribution of gut microbiota between patients with different severities of OSA and healthy individuals.Patients and Methods: A cohort of 113 individuals from the First Affiliated Hospital of Sun Yat-sen University underwent overnight polysomnography from July 2019 to August 2021. The individuals included 16 healthy controls and 97 patients with OSA, categorized by the apnea-hypopnea index into mild, moderate, and severe groups. Fecal samples were analyzed using high-throughput sequencing of the 16S rRNA V3–V4 region to assess gut microbiota composition and function. Correlation analysis was used to evaluate the association between clinical indicators and microbiota markers.Results: In patients with OSA, the gut microbiota diversity and the abundance of specific microbes that produce short-chain fatty acids decreased (P< 0.05). The phyla Verrucomicrobia and Candidatus Saccharibacteria, genera Gemmiger and Faecalibacterium, and the species Gemmiger formicilis exhibited decreasing abundance with increasing OSA severity. Correlation analysis revealed a robust association between the proportion of total sleep time, characterized by nighttime blood oxygen saturation below 90%, and the alterations in the gut microbiota, demonstrating that elevated levels of desaturation are correlated with pronounced microbiota dysbiosis (P< 0.05).Conclusion: Compared to the control group, the intermittent hypoxia exhibited by patients with OSA may be related to alterations in the composition and structure of the gut microbiota. Our results demonstrate the importance of monitoring hypoxia indicators in future clinical practice.Keywords: obstructive sleep apnea, gut microbiota, 16S rRNA, intermittent hypoxia
Published: 2024

38. An Experimental Animal Study: Electroacupuncture Facilitates Antiviral Immunity Against Hepatitis B Virus Through the IFN-γ/JAK/STAT Axis

Author: Yang Y, Ge F, Luo C, Liao C, Deng J, Chen Y, Guo X, Bai Z, Xiao X, and Tang C
Subjects: hepatitis b virus, electroacupuncture, antiviral activity, immune modulation，ifn-γ, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Yan Yang,1,&ast; Feilin Ge,2,&ast; Chen Luo,1 Cai Liao,1 Junyuan Deng,1 Yunhao Yang,1 Yang Chen,1 Xiao Guo,1 Zhaofang Bai,3 Xiaohe Xiao,3 Chenglin Tang1 1College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, 400010, People’s Republic of China; 2Department of Chinese Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, People’s Republic of China; 3Senior Department of Hepatology, the Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xiaohe Xiao, Senior Department of Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China, Email pharmacy302xxh@126.com Chenglin Tang, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, People’s Republic of China, Email tangchenglin@cqmu.edu.cnBackground: Chronic hepatitis B (CHB) remains a global health challenge, necessitating innovative therapeutic strategies. Enhancing the body’s immune response against the hepatitis B virus (HBV) emerges as a fundamental strategy for achieving a functional cure. While acupuncture has shown potential in immune modulation, its specific anti-HBV effects are not well understood. This study evaluates the potential of electroacupuncture (EA) in HBV infection and explores its underlying immunological mechanisms using a mouse model.Methods: HBV-infected mice were established using the high-pressure hydrodynamic method and divided into four groups: normal saline (NS), EA, sham EA (SE), and tenofovir disoproxil fumarate (TF), with n = 6 per group. During treatment, blood was collected every Sunday via the orbital sinus to monitor HBV DNA, HBsAg, and HBeAg levels. Transcriptomics and metabolomics analyses were employed to unearth clues regarding EA’s anti-HBV mechanism. Validation of these mechanisms included splenic T-cell flow analysis, Western blotting, RT-qPCR, immunofluorescence, and ELISA.Results: Serum HBV DNA levels decreased by 1.10, 0.19, and 1.98 log10 IU/mL in the EA, SE, and TF-treated mice, respectively, compared to the NS. Concurrently, the hepatic HBV DNA levels decreased by 1.09, 0.24, and 2.03 log10 IU/mL. EA also demonstrated superior inhibition of HBV antigens, with serum HBeAg levels decreasing by 43.86%, 8.74%, and 8.03%, and serum HBsAg levels decreasing by 28.01%, 0.26%, and 9.39% in the EA, SE, and TF groups, respectively. Further analysis through transcriptomics and metabolomics revealed that EA’s anti-HBV effects primarily hinge on immune modulation, particularly the IFN-γ/JAK/STAT pathway and taurine metabolism. EA also increased the ratio of splenic CD8+ CD69+ and CD8+ IFN-γ+ T-cells while upregulating key proteins in the JAK/STAT pathway and cytokines associated with antiviral immunity.Conclusion: EA manifests inhibitory effects on HBV, particularly in antigen suppression, with its mode of action intricately linked to the regulation of IFN-γ/JAK/STAT.Keywords: hepatitis B virus, electroacupuncture, antiviral activity, immune modulation, IFN-&#x03B3
Published: 2024

39. Acute Aerobic Exercise Intensity on Working Memory and Vigilance After Nap Deprivation: Effects of Low-Intensity Deserve Attention

Author: Guo X, Xu Y, Meng Y, Lian H, He J, Zhang R, Xu J, Wang H, Xu S, Cai W, Xiao L, Su T, and Tang Y
Subjects: exercise intensity, executive function, habitual nappers, nap deprivation, working memory., Psychiatry, RC435-571, Neurophysiology and neuropsychology, QP351-495
Abstract: Xin Guo,1,&ast; Ying Xu,1,&ast; Yao Meng,1,2,&ast; Hao Lian,1,&ast; Jingwen He,1 Ruike Zhang,1 Jingzhou Xu,1 Hao Wang,1 Shuyu Xu,1 Wenpeng Cai,1 Lei Xiao,1 Tong Su,3 Yunxiang Tang3 1Department of Medical Psychology, Faculty of Psychology, Naval Medical University, Shanghai, People’s Republic of China; 2Department of Diving and Hyperbaric Medical Research, Naval Special Medical Center, Naval Medical University, Shanghai, People’s Republic of China; 3Faculty of Psychology, Naval Medical University, Shanghai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yunxiang Tang, Email tangyun7633@sina.comBackground: Napping deprivation in habitual nappers leads to cognitive impairment. The ameliorative effect of acute aerobic exercise has been demonstrated for this post-cognitive impairment. However, it is still unclear which intensity of aerobic exercise is the most effective and how long this improvement can be sustained.Methods: Fifty-eight healthy adults with a chronic napping habit were randomly assigned to four intervention groups after undergoing nap deprivation: a sedentary control group, a low-intensity exercise group (50– 59% maximum heart rate, HRmax), a moderate-intensity exercise group (60– 69% HRmax), and a high-intensity exercise group (70– 79% HRmax). Working memory (N-back task), vigilance (Psychomotor Vigilance Task, PVT), and response inhibitory capacity (Go/NoGo task) were measured.Results: Regression analyses showed a quadratic trend between exercise intensity and working memory reaction time and accuracy (F =3.297– 5.769, p < 0.05, R2 =10.7– 18.9%). The effects of exercise were optimal at low-intensity. There was a significant quadratic trend between exercise intensity and PVT lapse (F =4.314, p =0.042, R² =7.2%). The effect of exercise increased with higher intensity. Prolonged observation found that the effect of low-intensity exercise on working memory was maintained for 2 hours.Conclusion: The effect of low-intensity exercise might be underestimated. Low-intensity exercise significantly improved working memory performance, and the effects could be maintained throughout the afternoon. In contrast, the effects of high-intensity exercise were unlikely to be maintained and might even have negative effects. Future researchers can broaden the categories of participants to enhance the external validity and collect diverse physiological indicators to explore related physiological mechanisms.Keywords: exercise intensity, executive function, habitual nappers, nap deprivation, working memory
Published: 2024

40. Network Analysis of Pain Catastrophizing, Self-Efficacy, and Kinesiophobia Among Patients After Total Knee Arthroplasty: A Cross-Sectional Study

Author: Zhou Y, Gao W, Cao Z, Gao S, Guo X, Liu M, and Cao C
Subjects: pain catastrophizing, self-efficacy, kinesiophobia, total knee arthroplasty, network analysis, Medicine (General), R5-920
Abstract: Yi Zhou,1 Weina Gao,2 Zhijiao Cao,3 Shumin Gao,2 Xutong Guo,2 Meng Liu,2 Congjie Cao4 1School of Nursing, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China; 2Department of Orthopedics, Baoding No.1 Central Hospital, Baoding, Hebei, People’s Republic of China; 3Department of Nursing, Baoding No.1 Central Hospital, Baoding, Hebei, People’s Republic of China; 4Nursing Department, Langfang Health Vocational College, Langfang, Hebei, People’s Republic of ChinaCorrespondence: Weina Gao, Department of Orthopedics, Baoding No.1 Central Hospital, No. 320, Changcheng North Street, Lianchi District, Baoding, Hebei, 071000, People’s Republic of China, Tel +86 0312-5975023, Email gaoweina984926@163.comBackground: Kinesiophobia is common in patients after total knee arthroplasty and is an important risk factor for post-operative recovery outcomes. Little is known about the complex intercorrelations between different components of pain catastrophizing, self-efficacy, and kinesiophobia. This study aimed to identify the central components of kinesiophobia and to explore the interconnectedness between components of pain catastrophizing, self-efficacy, and kinesiophobia.Methods: A total of 216 patients after total knee arthroplasty were recruited in this study. Pain Catastrophizing Scale, Self-efficacy of Rehabilitation Outcome Scale and Tampa Scale for Kinesiophobia were used to assess pain catastrophizing, self-efficacy and kinesiophobia. R software was used to visualize the networks and analyze the centrality of the networks. The index “strength” and “bridge expected influence” were employed to identify the central components and the bridge components of the networks.Results: In the item network of kinesiophobia, three items (“Simply being careful that I do not make any unnecessary movements is the safest thing I can do to prevent my pain from worsening”, “My accident has put my body at risk for the rest of my life”, and “My body is telling me I have something dangerously wrong”) had the highest strength centrality. In the pain catastrophizing/self-efficacy–kinesiophobia network, rumination had the highest positive bridge expected influence, while coping self-efficacy had the highest negative value.Conclusion: The three central components of kinesiophobia identified in this study, as well as two bridge variables (rumination and coping self-efficacy), could be promising and effective targets for prevention and intervention of kinesiophobia.Keywords: pain catastrophizing, self-efficacy, kinesiophobia, total knee arthroplasty, network analysis
Published: 2024

41. Extreme events generated in microcavity lasers and their predictions by reservoir computing

Author: Wang, T., Zhou, H. X., Fang, Q., Han, Y. N., Guo, X. X., Zhang, Y. H., Qian, C., Chen, H. S., Barland, S., Xiang, S. Y., and Lippi, G. L.
Subjects: Physics - Optics
Abstract: Extreme events generated by complex systems have been intensively studied in many fields due to their great impact on scientific research and our daily lives. However, their prediction is still a challenge in spite of the tremendous progress that model-free machine learning has brought to the field. We experimentally generate, and theoretically model, extreme events in a current-modulated, single-mode microcavity laser operating on orthogonal polarizations, where their strongly differing thresholds -- due to cavity birefringence -- give rise to giant light pulses initiated by spontaneous emission. Applying reservoir-computing techniques, we identify in advance the emergence of an extreme event from a time series, in spite of coarse sampling and limited sample length. Performance is optimized through new hybrid configurations that we introduce in this paper. Advance warning times can reach 5ns, i.e. approximately ten times the rise time of the individual extreme event.
Published: 2023

42. Deformations at Earth's dayside magnetopause during quasi-radial IMF conditions: Global kinetic simulations and soft X-ray imaging

Author: Yang, Zhongwei, Jarvinen, R., Guo, X. C., Sun, T. R., Koutroumpa, D., Parks, G. K., Huang, C., Tang, B. B., Lu, Q. M., and Wang, C.
Subjects: Physics - Space Physics
Abstract: The Solar wind Magnetosphere Ionosphere Link Explorer (SMILE) is an ESA-CAS joint mission. Primary goals are investigating the dynamic response of the Earth's magnetosphere to the solar wind (SW) impact via simultaneous in situ magnetosheath (MS) plasma and magnetic field measurements, X-Ray images of the magnetosheath and magnetic cusps, and UV images of global auroral distributions. Magnetopause (MP) deformations associated with MS high speed jets (HSJs) under a quasi-parallel interplanetary magnetic field condition are studied using a three-dimensional (3-D) global hybrid simulation. Soft X-ray intensity calculated based on both physical quantities of solar wind proton and oxygen ions is compared. We obtain key findings concerning deformations at the MP: (1) MP deformations are highly coherent with the MS HSJs generated at the quasiparallel region of the bow shock, (2) X-ray intensities estimated using solar wind H+ and self-consistent O7+ ions are consistent with each other, (3) Visual spacecraft are employed to check the discrimination ability for capturing MP deformations on Lunar and polar orbits, respectively. The SMILE spacecraft on the polar orbit could be expected to provide opportunities for capturing the global geometry of the magnetopause in the equatorial plane. A striking point is that SMILE has the potential to capture small-scale MP deformations and MS transients, such as HSJs, at medium altitudes on its orbit.
Published: 2023

43. Rescuing SERCA2 pump deficiency improves bone mechano-responsiveness in type 2 diabetes by shaping osteocyte calcium dynamics

Author: Shao, Xi, Tian, Yulan, Liu, Juan, Yan, Zedong, Ding, Yuanjun, Hao, Xiaoxia, Wang, Dan, Shen, Liangliang, Luo, Erping, Guo, X. Edward, Luo, Peng, Luo, Wenjing, Cai, Jing, and Jing, Da
Published: 2024
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44. Biosynthesis and Characterization of Monodisperse Gold Nanoparticles using Mulberry Leaf Extract at Room Temperature

Author: Dong, C., Fu, R., Yu, S., Guo, X., and Chen, W.
Published: 2024
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45. Vibration Attenuation of FG–GR-Laminated Composite Cantilever Rectangular Plate Integrated with Piezoelectric Actuator and Sensor

Author: Jiang, Y., Zhang, Y. F., Zhang, W., and Guo, X. T.
Published: 2024
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46. The First LHAASO Catalog of Gamma-Ray Sources

Author: Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo., X.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Phenomenology
Abstract: We present the first catalog of very-high energy and ultra-high energy gamma-ray sources detected by the Large High Altitude Air Shower Observatory (LHAASO). The catalog was compiled using 508 days of data collected by the Water Cherenkov Detector Array (WCDA) from March 2021 to September 2022 and 933 days of data recorded by the Kilometer Squared Array (KM2A) from January 2020 to September 2022. This catalog represents the main result from the most sensitive large coverage gamma-ray survey of the sky above 1 TeV, covering declination from $-$20$^{\circ}$ to 80$^{\circ}$. In total, the catalog contains 90 sources with an extended size smaller than $2^\circ$ and a significance of detection at $> 5\sigma$. Based on our source association criteria, 32 new TeV sources are proposed in this study. Among the 90 sources, 43 sources are detected with ultra-high energy ($E > 100$ TeV) emission at $> 4\sigma$ significance level. We provide the position, extension, and spectral characteristics of all the sources in this catalog., Comment: 40 pages, 13 figures, 4 tables
Published: 2023
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47. Measurement of ultra-high-energy diffuse gamma-ray emission of the Galactic plane from 10 TeV to 1 PeV with LHAASO-KM2A

Author: Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Saiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: The diffuse Galactic $\gamma$-ray emission, mainly produced via interactions between cosmic rays and the interstellar medium and/or radiation field, is a very important probe of the distribution, propagation, and interaction of cosmic rays in the Milky Way. In this work we report the measurements of diffuse $\gamma$-rays from the Galactic plane between 10 TeV and 1 PeV energies, with the square kilometer array of the Large High Altitude Air Shower Observatory (LHAASO). Diffuse emissions from the inner ($15^{\circ}10$~TeV). The energy spectrum in the inner Galaxy regions can be described by a power-law function with an index of $-2.99\pm0.04$, which is different from the curved spectrum as expected from hadronic interactions between locally measured cosmic rays and the line-of-sight integrated gas content. Furthermore, the measured flux is higher by a factor of $\sim3$ than the prediction. A similar spectrum with an index of $-2.99\pm0.07$ is found in the outer Galaxy region, and the absolute flux for $10\lesssim E\lesssim60$ TeV is again higher than the prediction for hadronic cosmic ray interactions. The latitude distributions of the diffuse emission are consistent with the gas distribution, while the longitude distributions show clear deviation from the gas distribution. The LHAASO measurements imply that either additional emission sources exist or cosmic ray intensities have spatial variations., Comment: 12 pages, 8 figures, 5 tables; accepted for publication in Physical Review Letters; source mask file provided as ancillary file
Published: 2023
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48. Reservoir computing and task performing through using high-$\beta$ lasers with delayed optical feedback

Author: Wang, T., Jiang, C., Fang, Q., Guo, X., Zhang, Y., Jin, C., and Xiang, S.
Subjects: Physics - Optics, Computer Science - Emerging Technologies
Abstract: Nonlinear photonic sources including semiconductor lasers have recently been utilized as ideal computation elements for information processing. They supply energy-efficient way and rich dynamics for classification and recognition tasks. In this work, we propose and numerically study the dynamics of complex photonic systems including high-$\beta$ laser element with delayed feedback and functional current modulation, and employ nonlinear laser dynamics of near-threshold region for the application in time-delayed reservoir computing. The results indicate a perfect (100$\%$) recognition accuracy for the pattern recognition task, and an accuracy of about 98$\%$ for the Mackey-Glass chaotic sequences prediction. Therefore, the system shows an improvement of performance with low-power consumption, in particular, the error rate is an order of magnitude smaller in comparison with previous works. Furthermore, by changing the DC pump, we are able to modify the amount of spontaneous emission photons of the system, this then allow us to explore how the laser noise impact the performance of the reservoir computing system. Through manipulating these variables, we show a deeper understanding on the proposed system, which is helpful for the practical applications of reservoir computing.
Published: 2023

49. Searching for $^{76}$Ge neutrinoless double beta decay with the CDEX-1B experiment

Author: Zhang, B. T., Wang, J. Z., Yang, L. T., Yue, Q., Kang, K. J., Li, Y. J., An, H. P., C., Greeshma, Chang, J. P., Chen, Y. H., Cheng, J. P., Dai, W. H., Deng, Z., Fang, C. H., Geng, X. P., Gong, H., Guo, Q. J., Guo, X. Y., He, L., He, S. M., Hu, J. W., Huang, H. X., Huang, T. C., Jia, H. T., Jiang, X., Karmakar, S., Li, H. B., Li, J. M., Li, J., Li, Q. Y., Li, R. M. J., Li, X. Q., Li, Y. L., Liang, Y. F., Liao, B., Lin, F. K., Lin, S. T., Liu, J. X., Liu, S. K., Liu, Y. D., Liu, Y., Liu, Y. Y., Liu, Z. Z., Ma, H., Mao, Y. C., Nie, Q. Y., Ning, J. H., Pan, H., Qi, N. C., Ren, J., Ruan, X. C., She, Z., Singh, M. K., Sun, T. X., Tang, C. J., Tang, W. Y., Tian, Y., Wang, G. F., Wang, L., Wang, Q., Wang, Y. F., Wang, Y. X., Wong, H. T., Wu, S. Y., Wu, Y. C., Xing, H. Y., Xu, R., Xu, Y., Xue, T., Yan, Y. L., Yi, N., Yu, C. X., Yu, H. J., Yue, J. F., Zeng, M., Zeng, Z., Zhang, F. S., Zhang, L., Zhang, Z. H., Zhang, Z. Y., Zhao, K. K., Zhao, M. G., Zhou, J. F., Zhou, Z. Y., and Zhu, J. J.
Subjects: Nuclear Experiment, High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract: We operated a p-type point contact high purity germanium (PPCGe) detector (CDEX-1B, 1.008 kg) in the China Jinping Underground Laboratory (CJPL) for 500.3 days to search for neutrinoless double beta ($0\nu\beta\beta$) decay of $^{76}$Ge. A total of 504.3 kg$\cdot$day effective exposure data was accumulated. The anti-coincidence and the multi/single-site event (MSE/SSE) discrimination methods were used to suppress the background in the energy region of interest (ROI, 1989$-$2089 keV for this work) with a factor of 23. A background level of 0.33 counts/(keV$\cdot$kg$\cdot$yr) was realized. The lower limit on the half life of $^{76}$Ge $0\nu\beta\beta$ decay was constrained as $T_{1/2}^{0\nu}\ > \ {1.0}\times 10^{23}\ \rm yr\ (90\% \ C.L.)$, corresponding to the upper limits on the effective Majorana neutrino mass: $\langle m_{\beta\beta}\rangle < $3.2$-$7.5$\ \mathrm{eV}$., Comment: 11 pages, 12 figures, 2 tables. Version updated to match CPC version
Published: 2023
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50. Effectiveness of Compound Dilong Capsules in Patients with Asymptomatic Cerebral Carotid Artery Stenosis: A Retrospective Case-Control Study

Author: Qin X, Guo X, Liu Y, Wang Z, Wang X, Wan Q, Gao M, and Song J
Subjects: asymptomatic cerebral carotid artery stenosis, case-control study, secondary prevention, compound dilong capsules, Medicine (General), R5-920
Abstract: Xinzuo Qin,1,&ast; Xu Guo,2,&ast; Yijiang Liu,1,3,&ast; Zijian Wang,1 Xinyu Wang,1 Qi Wan,4 Mingjie Gao,5 Juexian Song1 1Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, People’s Republic of China; 2Department of Pharmacy, Xuanwu Hospital of Capital Medical University, Beijing, People’s Republic of China; 3School of Traditional Chinese Medicine, Capital Medical University, Beijing, People’s Republic of China; 4No. 904 Hospital of Joint Logistics Unit, Jiangsu, Wuxi, People’s Republic of China; 5Department of Ultrasonography, Beijing Luhe Hospital, Capital Medical University, Beijing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Mingjie Gao; Juexian Song, Email mingjie.gao@xwh.ccmu.edu.cn; songjuexian@vip.163.comPurpose: Asymptomatic cerebral carotid artery stenosis (ACCAS) benefits from secondary prevention via statins and antiplatelets; nonetheless, the impact of medication alone is often limited. Evidence has suggested enhanced therapeutic outcomes when Chinese patent medicine—specifically, compound dilong capsules (CDC)—is integrated with conventional secondary prevention measures.Patients and Methods: We retrospectively analyzed 319 ACCAS patients from January 2018 to December 2022 at Xuanwu Hospital, Capital Medical University. Depending on the clinical outcomes—improvement or stabilization versus progression—patients were classified into effective or ineffective treatment groups. Patient medical records and questionnaire responses were the primary data sources. The study accounted for demographic variables, clinical history, and medication details, with the primary focus on CDC use and its duration. Treatment outcomes were gauged alongside Transcranial color-coded sonography and Carotid Doppler ultrasonography findings. We employed both univariate and multivariate statistical methods to assess the data.Results: CDC administration (aOR=2.51, 95% CI 1.39– 4.54, P=0.002) and extended usage beyond six months (aOR=3.54, 95% CI 1.71– 7.32, P=0.001) demonstrate a statistically significant correlation with treatment efficacy. Gender (aOR=2.54, 95% CI 1.30– 5.00, P=0.007), hypertension management (aOR=0.56, 95% CI 0.33– 0.95, P=0.031), and antiplatelet therapy with aspirin (aOR=9.53, 95% CI 1.15– 78.89, P=0.037) or clopidogrel (aOR=9.97, 95% CI 1.10– 90.12, P=0.041) also influenced the therapeutic outcome significantly.Conclusion: Incorporating CDC as part of a secondary prevention strategy for over six months can beneficially modulate and limit the progression of vascular stenosis in ACCAS. These findings underscore the value of combining traditional Chinese medicine with modern pharmacological interventions in ACCAS management.Keywords: asymptomatic cerebral carotid artery stenosis, case-control study, secondary prevention, compound dilong capsules
Published: 2024

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