Author: "Gao,W" - Searchworks@Jio Institute Digital Library Search Results

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15,175 results on '"Gao,W"'

1. 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

2. 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

3. 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

4. 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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5. 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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6. I-mode Plasma Confinement Improvement by Real-time Lithium Injection and its Classification on EAST Tokamak

Author: Zhong, X. M., Zou, X. L., Liu, A. D., Song, Y. T., Zhuang, G., Liu, H. Q., Xu, L. Q., Li, E. Z., Zhang, B., Zuo, G. Z., Wang, Z., Zhou, C., Zhang, J., Shi, W. X., Gao, L. T., Wang, S. F., Gao, W., Jia, T. Q., Zang, Q., Zhao, H. L., Wang, M., Xu, H. D., Wang, X. J., Gao, X., Lin, X. D., Li, J. G., Group, EAST I-mode Working, and Team, EAST
Subjects: Physics - Plasma Physics
Abstract: I-mode is a promising regime for future fusion reactors due to the high energy confinement and the moderate particle confinement. However, the effect of lithium, which has been widely applied for particle recycling and impurity control, on I-mode plasma is still unclear. Recently, experiments of real-time lithium powder injection on I-mode plasma have been carried out in EAST Tokamak. It was found that the confinement performance of the I-mode can be improved by the lithium powder injection, which can strongly reduce electron turbulence (ET) and then trigger ion turbulence (IT). Four different regimes of I-mode have been identified in EAST. The Type I I-mode plasma is characterized by the weakly coherent mode (WCM) and the geodesic-acoustic mode (GAM). The Type II I-mode is featured as the WCM and the edge temperature ring oscillation (ETRO). The Type III I-mode corresponds to the plasma with the co-existence of ETRO, GAM, and WCM. The Type IV I-mode denotes the plasma with only WCM but without ETRO and GAM. It has been observed that WCM and ETRO are increased with lithium powder injection due to the reduction of ion and electron turbulence, and the enhancement of the pedestal electron temperature gradient. EAST experiments demonstrate that lithium powder injection is an effective tool for real-time control and confinement improvement of I-mode plasma.
Published: 2024

7. Effect of Shear Flow on the Double Tearing Mode Induced by Resonant Magnetic Perturbation

Author: Wang, L., Wang, Y., Xu, H., Sun, W., Liu, Ch., Xia, K., Gao, W., and Wang, L.
Published: 2024
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8. The non-uniformity study under geo-magnetic field of 20-inch MCP-PMT for LHAASO

Author: Liu, C. C., Gao, B., Lu, S. X., Chen, M. J., You, X. H., Li, K., Liu, Lin, and Gao, W. K.
Published: 2024
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9. 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

10. 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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11. 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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12. 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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13. Roles of Microenvironment on Mesenchymal Stem Cells Therapy for Osteoarthritis

Author: Zhang H, Jin C, Hua J, Chen Z, Gao W, Xu W, Zhou L, and Shan L
Subjects: microenvironment, mesenchymal stem cells, osteoarthritis, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Haiyan Zhang,1,&ast; Chaoying Jin,2,&ast; Jiaqing Hua,3,&ast; Zuxiang Chen,4 Wenxin Gao,4 Wenting Xu,4 Li Zhou,4 Letian Shan1 1The Second Affiliated Hospital, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China; 2School of Medicine, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China; 3College of Pharmaceutical Science, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China; 4The First Affiliated Hospital, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Letian Shan; Li Zhou, Email letian.shan@zcmu.edu.cn; zhouli@zcmu.edu.cnAbstract: Osteoarthritis (OA) induced microenvironmental alterations are a common and unavoidable phenomenon that greatly exacerbate the pathologic process of OA. Imbalances in the synthesis and degradation of cartilage extracellular matrix (ECM) have been reported to be associated with an adverse microenvironment. Stem cell therapy is a promising treatment for OA, and mesenchymal stem cells (MSCs) are the main cell sources for this therapy. With multispectral differentiation and immunomodulation, MSCs can effectively regulate the microenvironment of articular cartilage, ameliorate inflammation, promote regeneration of damaged cartilage, and ultimately alleviate OA symptoms. However, the efficacy of MSCs in the treatment of OA is greatly influenced by articular cavity microenvironments. This article reviews the five microenvironments of OA articular cavity, including inflammatory microenvironment, senescence microenvironment, hypoxic microenvironment, high glucose microenvironment and high lipid environment, focus on the positive and negative effects of OA microenvironments on the fate of MSCs. In this regard, we emphasize the mechanisms of the current use of MSCs in OA treatment, as well as its limitations and challenges.Keywords: microenvironment, mesenchymal stem cells, osteoarthritis
Published: 2024

14. Validation of the Three-Factor Reflective Functioning Questionnaire for Youth in a Chinese Adolescent Sample

Author: Chen W, Li Y, Jahrami H, Wang W, Zheng W, Huang Y, Bragazzi NL, and Gao W
Subjects: mentalizing, adolescence, psychometric validation, borderline personality disorder, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429
Abstract: Wen Chen,1,2 Yun Li,2 Haitham Jahrami,3,4 Weiyan Wang,5 Wei Zheng,2 Yuxia Huang,1 Nicola Luigi Bragazzi,6,7 Weijia Gao1 1Department of Child Psychology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children’s Regional Medical Center, Hangzhou, People’s Republic of China; 2Department of Psychiatry, Xiamen Xianyue Hospital, Xiamen, People’s Republic of China; 3College of Medicine and Medical Sciences, Arabian Gulf University, Manama, Bahrain; 4Ministry of Health, Manama, Bahrain; 5Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China; 6Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, Canada; 7Human Nutrition Unit (HNU), Department of Food and Drugs, Medical School, University of Parma, Parma, ItalyCorrespondence: Weijia Gao, Department of Child Psychology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children’s Regional Medical Center, Hangzhou, Zhejiang Province, People’s Republic of China, Email 6314017@zju.edu.cn Nicola Luigi Bragazzi Human Nutrition Unit (HNU), Department of Food and Drugs, Medical School, University of Parma, Parma, Italy, Email robertobragazzi@gmail.comPurpose: This study focused on the validation of the Three-Factor Reflective Functioning Questionnaire for Youth(RFQY) within a sample of Chinese adolescents.Patients and Methods: All the items of the RFQY were translated into Chinese language through the process of translation and back translation. A total of 532 adolescents aged between 12– 20 years completed the Chinese version of RFQY, McLean Screening Instrument for Borderline Personality Disorder (MSI-BPD), Basic Empathy Scale (BES), and the 20-item Toronto Alexithymia Scale (TAS-20).Results: Twenty items meeting psychometric standards were retained in the Chinese version of the RFQY. The indices for confirmatory factor analysis, including χ 2/df (2.354), SRMR (0.053), GFI (0.930), CFI (0.921), TLI (0.910), and RMSEA (0.050), all conformed to the requirements of psychometrics. The Cronbach’s alpha coefficients for the three factors, “uncertainty/confusion”, “interest/curiosity”, and “excessive certainty”, were 0.820, 0.673, and 0.839, respectively, with test-retest reliability scores of 0.751, 0.643, and 0.764. A significant positive correlation was found between uncertainty/confusion and symptoms of borderline personality disorder (BPD), particularly in adolescents with high BPD traits. Excessive certainty was positively correlated with unstable interpersonal relationships, while the interest/curiosity factor shows no significant correlation with BPD symptoms. The uncertainty/confusion factor demonstrates a complex relationship with empathy, correlating positively with affective empathy but negatively with cognitive empathy. The uncertainty/confusion factor shows a significant positive correlation with alexithymia, while the factor of excessive certainty demonstrates the opposite effect. Additionally, a significant negative correlation exists between the interest/curiosity factor and the externally oriented thinking.Conclusion: This study validates the Chinese version of the Reflective Functioning Questionnaire for Youth (RFQY), demonstrating its reliability and validity in assessing reflective functioning among Chinese adolescents. This enhances the understanding of reflective functioning and its role in adolescent mental health.Keywords: mentalizing, adolescence, psychometric validation, borderline personality disorder
Published: 2024

15. 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

16. Stability and inter-family associations of hair endocannabinoid and N-acylethanolamines across the perinatal period in mothers, fathers, and children

Author: Bergunde, L., Steudte-Schmiedgen, S., Karl, M., Jaramillo, I., Gao, W., von Soest, T., and Garthus-Niegel, S.
Published: 2024
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17. Age effect on the shared etiology of glycemic traits and serum lipids: evidence from a Chinese twin study

Author: Wang, Y., Hong, X., Cao, W., Lv, J., Yu, C., Huang, T., Sun, D., Liao, C., Pang, Y., Pang, Z., Yu, M., Wang, H., Wu, X., Liu, Y., Gao, W., and Li, L.
Published: 2024
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18. Polydopamine-Based Targeted Nanosystem for Chemo/Photothermal Therapy of Retinoblastoma in a Mouse Orthotopic Model

Author: Jin B, Lu K, Gao W, Liu Y, Wang M, Zhang X, Chen H, Zheng L, and Zou M
Subjects: retinoblastoma, orthotopic model, nanoparticle, synergistic therapy, Medicine (General), R5-920
Abstract: Bo Jin,1 Kexin Lu,2 Wenna Gao,1 Yixian Liu,3 Mengfei Wang,2 Xiaojun Zhang,3 Huiping Chen,3 Liyun Zheng,3 Min Zou3 1Department of Ophthalmology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Hennan, 450052, People’s Republic of China; 2BGI College, Zhengzhou University, Zhengzhou, 450052, People’s Republic of China; 3Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450052, People’s Republic of ChinaCorrespondence: Min Zou; Liyun Zheng, Email Minzou1980@126.com; zhengliyun@zzu.edu.cnBackground: At present, the few photothermal/chemotherapy studies about retinoblastoma that have been reported are mainly restricted to ectopic models involving subcutaneous implantation. However, eyeball is unique physiological structure, the blood-retina barrier (BRB) hinders the absorption of drug molecules through the systemic route. Moreover, the abundant blood circulation in the fundus accelerates drug metabolism. To uphold the required drug concentration, patients must undergo frequent chemotherapy sessions.Purpose: To address these challenges above, we need to develop a secure and effective drug delivery system (FA-PEG-PDA-DOX) for the fundus.Methods: We offered superior therapeutic efficacy with minimal or no side effects and successfully established orthotopic mouse models. We evaluated cellular uptake performance and targeting efficiency of FA-PEG-PDA-DOX nanosystem and assessed its synergistic antitumor effects in vitro and vivo. Biodistribution assessments were performed to determine the retention time and targeting efficiency of the NPs in vivo. Additionally, safety assessments were conducted.Results: Cell endocytosis rates of the FA-PEG-PDA-DOX+Laser group became 5.23 times that of the DOX group and 2.28 times that of FA-PEG-PDA-DOX group without irradiation. The fluorescence signal of FA-PEG-PDA-DOX persisted for more than 120 hours at the tumor site. The number of tumor cells (17.2%) in the proliferative cycle decreased by 61.6% in the photothermal-chemotherapy group, in contrast to that of the saline control group (78.8%). FA-PEG-PDA-DOX nanoparticles(NPs) exhibited favorable biosafety and high biocompatibility.Conclusion: The dual functional targeted nanosystem, with the effects of DOX and mild-temperature elevation by irradiation, resulted in precise chemo/photothermal therapy in nude mice model.Keywords: retinoblastoma, orthotopic model, nanoparticle, synergistic therapy
Published: 2024

19. Research Progress on the Role of Epigenetic Methylation Modification in Hepatocellular Carcinoma

Author: Wang J, Gao W, Yu H, Xu Y, Bai C, Cong Q, and Zhu Y
Subjects: methylation modifying proteins, biomarkers, methyltransferases, hcc tumorigenesis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Jing Wang,1 Wenyue Gao,1 Hongbo Yu,1 Yuting Xu,1 Changchuan Bai,2 Qingwei Cong,1 Ying Zhu1 1Infectious Department, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, 116000, People’s Republic of China; 2Internal Department of Chinese Medicine, Dalian Hospital of Traditional Chinese Medicine, Dalian, Liaoning, 116013, People’s Republic of ChinaCorrespondence: Ying Zhu, Email zhuyingsh52@126.comAbstract: Hepatocellular carcinoma (HCC) stands as the prevailing form of primary liver cancer, characterized by a poor prognosis and high mortality rate. A pivotal factor in HCC tumorigenesis is epigenetics, specifically the regulation of gene expression through methylation. This process relies significantly on the action of proteins that modify methylation, including methyltransferases, their associated binding proteins, and demethylases. These proteins are crucial regulators, orchestrating the methylation process by regulating enzymes and their corresponding binding proteins. This orchestration facilitates the reading, binding, detection, and catalysis of gene methylation sites. Methylation ences the development, prolisignificantly influferation, invasion, and prognosis of HCC. Furthermore, methylation modification and its regulatory mechanisms activate distinct biological characteristics in HCC cancer stem cells, such as inducing cancer-like differentiation of stem cells. They also influence the tumor microenvironment (TME) in HCC, modulate immune responses, affect chemotherapy resistance in HCC patients, and contribute to HCC progression through signaling pathway feedback. Given the essential role of methylation in genetic information, it holds promise as a potential tool for the early detection of HCC and as a target to improve drug resistance and promote apoptosis in HCC cells.Keywords: methylation modifying proteins, biomarkers, methyltransferases, HCC tumorigenesis
Published: 2024

20. Flux Variations of Cosmic Ray Air Showers Detected by LHAASO-KM2A During a Thunderstorm on 10 June 2021

Author: LHAASO Collaboration, Aharonian, F., An, Q., Axikegu, Bai, L. X., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Zhe, Cao, Zhen, Chang, J., Chang, J. F., Chen, E. S., Chen, Liang, Chen, Long, Chen, M. J., Chen, M. L., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, X. J., Chen, Y., Cheng, H. L., Cheng, N., Cheng, Y. D., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Duan, K. K., Fan, J. H., Fan, Y. Z., Fan, Z. X., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Gong, G. H., Gou, Q. B., Gu, M. H., Gu, F. L., Guo, J. G., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, S. L., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S., Hu, S. C., Hu, X. J., Huang, D. H., Huang, W. H., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Li, B. B., Li, Cheng, Li, Cong, 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. S., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Long, W. J., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Masood, A., Min, Z., Mitthumsiri, W., Nan, Y. C., 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., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shi, J. Y., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Z. B., Tian, W. W., Wang, B. D., Wang, C., Wang, H., Wang, H. G., Wang, J. C., Wang, J. S., Wang, L. P., Wang, L. Y., Wang, R., Wang, R. N., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Y. P., 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., W, 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. X., Xue, L., Yan, D. H., Yan, J. Z., Yang, C. W., 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., Zeng, Z. K., Zha, M., Zhai, X. X., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, Lu, 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, Y. L., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, Y., Zhou, B., Zhou, H., Zhou, J. N., 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 - Experiment
Abstract: The Large High Altitude Air Shower Observatory (LHAASO) has three sub-arrays, KM2A, WCDA and WFCTA. The flux variations of cosmic ray air showers were studied by analyzing the KM2A data during the thunderstorm on 10 June 2021. The number of shower events that meet the trigger conditions increases significantly in atmospheric electric fields, with maximum fractional increase of 20%. The variations of trigger rates (increases or decreases) are found to be strongly dependent on the primary zenith angle. The flux of secondary particles increases significantly, following a similar trend with that of the shower events. To better understand the observed behavior, Monte Carlo simulations are performed with CORSIKA and G4KM2A (a code based on GEANT4). We find that the experimental data (in saturated negative fields) are in good agreement with simulations, assuming the presence of a uniform upward electric field of 700 V/cm with a thickness of 1500 m in the atmosphere above the observation level. Due to the acceleration/deceleration and deflection by the atmospheric electric field, the number of secondary particles with energy above the detector threshold is modified, resulting in the changes in shower detection rate., Comment: 18 pages, 11 figures
Published: 2022
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21. Low-depth Raw Reads of Nanopore Sequencing Enables Rapid and Accurate Bacterial Identification

Author: Gao, W., Li, H., Hong, W., Liu, S., Li, J., Wu, Y., Liu, Y., Fan, X., Wang, H., Wang, M., Yang, B., and Wang, T.
Published: 2023
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22. IFN-γ, SCF, MIP1b and IL-16 Were Associated with Risk of Diabetic Nephropathy: A Mendelian Randomization Study

Author: An L, Ren X, Pan Y, Gao W, Ren L, Wang J, and Wang Y
Subjects: causal association, diabetic nephropathy, inflammatory factors, mendelian randomization, Specialties of internal medicine, RC581-951
Abstract: Li An,1,2,&ast; Xiaomei Ren,1,&ast; Ye Pan,2 Wei Gao,1 Liqun Ren,1 Jing Wang,3 Yao Wang2 1Department of Geriatrics, ZhongDa Hospital, Southeast University School of Medicine, Nanjing, 210009, People’s Republic of China; 2Department of Endocrine, ZhongDa Hospital, Southeast University School of Medicine, Nanjing, 210009, People’s Republic of China; 3Yizheng Hospital of Nanjing Drum Tower Hospital Group, Yizheng, 211400, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jing Wang; Yao Wang, Tel/Fax +86-25- 83272111, Email wang_yao100@163.com; yz3466599@hotmail.comBackground: The impact of inflammatory factors on the risk of diabetic nephropathy (DN) is inconsistent. Two-sample Mendelian randomization (MR) analyses were used to detect the causal role of inflammatory factors in DN risk.Methods: Inflammatory factor GWAS summary data were collected from a meta-analysis including 8,293 Finnish participants, and DN information was extracted from a GWAS of 213,746 individuals from FinnGen. The MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) outlier test was used for the removal of horizontal pleiotropic outliers. Multivariable MR analysis was also used to adjust for pleiotropy.Results: IFN-γ [ORIVW: 1.33; 95% CI: 1.09– 1.63; p=0.005] and SCF [ORIVW: 1.25, 1.02– 1.52; p = 0.027] were associated with an increased risk of DN. MIP1b [ORIVW: 0.92; 95% CI: 0.85– 0.98; p = 0.022] and IL-16 [ORIVW: 0.89, 0.81– 0.99; p = 0.043] showed negative associations with the risk of DN. We validated our MR results with MR-PRESSO analyses. Significant horizontal pleiotropy was not found. Moreover, in the multivariable MR analysis, the associations between cytokines and DN risk remained.Conclusion: Our MR results based on genetic data contribute to a better understanding of the pathogenesis of DN and provide evidence for a causal effect of inflammatory factors on DN. These findings support targeting specific inflammatory factors to alleviate DN risk.Keywords: causal association, diabetic nephropathy, inflammatory factors, Mendelian randomization
Published: 2024

23. Evidence for particle acceleration approaching PeV energies in the W51 complex

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., Zuo, X., and Celli, S.
Published: 2024
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24. Role of oedema and shrinkage patterns for prediction of response to neoadjuvant chemotherapy and survival outcomes in luminal breast cancer

Author: Sun, S., Zhou, J., Bai, Y., Gao, W., Lin, L., Jiang, T., You, C., and Gu, Y.
Published: 2024
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25. Data quality control system and long-term performance monitor of 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.
Published: 2025
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26. A Targeted Multi-Crystalline Manganese Oxide as a Tumor-Selective Nano-Sized MRI Contrast Agent for Early and Accurate Diagnosis of Tumors

Author: Yang G, Xia J, Dai X, Zhao H, Gao W, Ding W, Tao X, and Zhu L
Subjects: multi-crystalline manganese oxide, mri contrast agent, tumor targeting, tumor selectivity, accurate diagnosis, Medicine (General), R5-920
Abstract: Gongxin Yang,1,&ast; Jikai Xia,2,&ast; Xiaoqing Dai,1,&ast; Hongbo Zhao,1 Weiqing Gao,1 Weilong Ding,1 Xiaofeng Tao,1 Ling Zhu1 1Department of Radiology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200001, People’s Republic of China; 2Department of Radiology, Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong, 264100, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xiaofeng Tao; Ling Zhu, Department of Radiology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200001, People’s Republic of China, Email cjr.taoxiaofeng@vip.163.com; zhuling011@126.comIntroduction: Magnetic resonance imaging (MRI) is an important tool for the accurate diagnosis of malignant tumors in clinical settings. However, the lack of tumor-specific MRI contrast agents limits diagnostic accuracy.Methods: Herein, we developed αv integrin receptor-targeting multi-crystalline manganese oxide (MCMO) as a novel MRI contrast agent for accurate diagnosis of tumors by coupling iRGD cyclopeptide PEGylation polymer onto the surface of MCMO (iRGD-pMCMO).Results: The MCMO consisted of numerous small crystals and exhibited an oval structure of 200 nm in size. The iRGD-pMCMO actively recognizes tumor cells and effectively accumulates at the tumor site, consequently releasing abundant Mn2+ ions in a weakly acidic and high-GSH-expressing tumor microenvironment. Subsequently, Mn2+ ions interact with cellular GSH to form Mn-GSH chelates, enabling efficient T1-weighted MR contrast imaging. In vivo experiments indicated that iRGD-pMCMO significantly improved T1-weighted images, achieving an accurate diagnosis of subcutaneous and orthotopic tumors. The results verified that the T1 contrast effect of iRGD-pMCMO was closely associated with the expression of GSH in tumor cells.Conclusion: Altogether, the novel tumor-targeting, highly sensitive MRI contrast agent developed in this study can improve the accuracy of MRI for tumor diagnosis. Keywords: multi-crystalline manganese oxide, MRI contrast agent, tumor targeting, tumor selectivity, accurate diagnosis
Published: 2024

27. Association between Frailty Assessed Using Two Electronic Medical Record-Based Frailty Assessment Tools and Long-Term Adverse Prognosis in Older Critically Ill Survivors

Author: Hao, B., Xu, W., Gao, W., Huang, T., Lyu, L., Lyu, D., Xiao, H., Li, H., Qin, J., Sheng, Li, and Liu, Hongbin
Published: 2023
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28. Association of Frailty with Adverse Outcomes in Patients with Critical Acute Myocardial Infarction: A Retrospective Cohort Study

Author: Bai W, Huang T, Li X, Gao W, Qin J, Bian Y, Xu W, Xu J, and Qin L
Subjects: frailty, modified frailty index, acute myocardial infarction, critically ill patients, prognosis., Geriatrics, RC952-954.6
Abstract: Weimin Bai,1,&ast; Taoke Huang,2,&ast; Xinying Li,3,&ast; Weiyang Gao,2 Ji Qin,2 Yongxin Bian,4 Weihao Xu,5 Juan Xu,6 Lijie Qin1 1Department of Emergency, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, People’s Hospital of Henan University, Zhengzhou, 463599, People’s Republic of China; 2Medical School of Chinese PLA, Beijing, 100853, People’s Republic of China; 3Faculty of Postgraduate Education, Shandong Sport University, Jinan, 250102, People’s Republic of China; 4The First School of Clinical Medicine, Binzhou Medical University, Yantai, 264003, People’s Republic of China; 5Haikou Cadre’s Sanitarium of Hainan Military Region, Haikou, 570203, People’s Republic of China; 6Department of General Surgery, Affiliated Xiaoshan Hospital, Hangzhou Normal University, Hangzhou, 311202, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Juan Xu; Lijie Qin, Email sophia2932@163.com; qinlijie1819@163.comBackground: Frailty is a risk factor for acute myocardial infarction (AMI). This study examined the association between the modified frailty index (MFI) and adverse outcomes in patients with critical AMI.Methods: Data were obtained from the Medical Information Mart for Intensive Care IV database. Logistic and Cox regression models and a competing risk model were applied.Results: Of 5003 patients, 1496 were non-frail and 3507 were frail. Frailty was significantly associated with in-hospital mortality (per point, OR 1.13, 95% CI: 1.05– 1.21; frail vs non-frail, OR 1.31, 95% CI: 1.04– 1.65) and 1-year mortality (per point, HR 1.15, 95% CI: 1.11– 1.20; frail vs non-frail, HR 1.37, 95% CI: 1.20– 1.58). Frailty was significantly associated with post-discharge care needs (per point, OR 1.23, 95% CI: 1.14– 1.33; frail vs non-frail, OR 1.47, 95% CI: 1.22– 1.78). In the competing risk models, frailty was significantly associated with a lower probability of being discharged from the ICU (per point, HR 0.87, 95% CI: 0.85– 0.90; frail vs non-frail, HR 0.73, 95% CI: 0.68– 0.79) and hospital (per point, HR 0.82, 95% CI: 0.80– 0.85; frail vs non-frail, HR 0.62, 95% CI: 0.57– 0.68). Subgroup analyses showed the association of frailty with in-hospital and 1-year mortality was stronger in patients with a SOFA score ≤ 2 than in those with a SOFA score > 2 (both p< 0.05 for interaction).Conclusion: Frailty assessed by the MFI was an independent predictor of adverse outcomes in patients with critical AMI and may be helpful for prognostic risk stratification.Keywords: frailty, modified frailty index, acute myocardial infarction, critically ill patients, prognosis
Published: 2023

29. Pain Catastrophizing, Kinesiophobia and Exercise Adherence in Patients After Total Knee Arthroplasty: The Mediating Role of Exercise Self-Efficacy

Author: Zhou Y, Gao W, Gao S, Guo X, Liu M, and Cao C
Subjects: pain catastrophizing, kinesiophobia, self-efficacy, exercise, adherence, total knee arthroplasty, Medicine (General), R5-920
Abstract: Yi Zhou,1 Weina Gao,2 Shumin Gao,2 Xutong Guo,2 Meng Liu,2 Congjie Cao1 1School of Nursing, Langfang Health Vocational College, Langfang, Hebei, People’s Republic of China; 2Department of Orthopedics, Baoding No.1 Central Hospital, Baoding, 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/Fax +86 312-5975023, Email gaoweina984926@163.comPurpose: To examine whether exercise self-efficacy mediates the contributions of pain catastrophizing and kinesiophobia to exercise adherence in patients after total knee arthroplasty.Patients and Methods: A cross-sectional study design was conducted. A total 211 post-total knee arthroplasty patients were recruited from three orthopedics units of a tertiary hospital in China. Participants were invited to complete questionnaires on pain catastrophizing, kinesiophobia, exercise self-efficacy, and exercise adherence. Mplus 8.3 software was used to construct mediation models.Results: Pain catastrophizing and kinesiophobia were negatively correlated with exercise adherence (r = − 0.509, r = − 0.605, p < 0.001 respectively), while exercise self-efficacy were positively associated with exercise adherence (r = 0.799, p < 0.001). The results found exercise self-efficacy mediated the correlations of pain catastrophizing and kinesiophobia with exercise adherence after adjusting for demographic and clinical covariates. Pain catastrophizing indirectly affected patients’ exercise adherence through its effect on exercise efficacy (indirect effect: − 0.412), while Kinesiophobia is directly associated with exercise adherence and also indirectly through exercise self-efficacy (direct effect: − 0.184, indirect effect: − 0.415).Conclusion: Patients after total knee arthroplasty who have high levels of psychological distress (pain catastrophizing and kinesiophobia) are vulnerable to be non-adherent to exercise behaviors. Exercise self-efficacy explains the effects of pain catastrophizing and kinesiophobia on exercise adherence and may be a key target for measures to improve exercise behaviors in patients after total knee arthroplasty.Keywords: pain catastrophizing, kinesiophobia, self-efficacy, exercise, adherence, total knee arthroplasty
Published: 2023

30. Peta-electron volt gamma-ray emission from the Crab Nebula

Author: The LHAASO Collaboration, Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, L. X., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, H., Cai, J. T., Cao, Zhe, Chang, J., Chang, J. F., Chen, B. M., Chen, E. S., Chen, J., Chen, Liang, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, X. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, S. W., Cui, X. H., Cui, Y. D., Piazzoli, B. D'Ettorre, Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. J., Duan, K. K., Fan, J. H., Fan, Y. Z., Fan, Z. X., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, Y. L., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Ge, M. M., Geng, L. S., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, J. G., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. C., He, S. L., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, C., Hou, X., Hu, H. B., Hu, S., Hu, S. C., Hu, X. J., Huang, D. H., Huang, Q. L., Huang, W. H., Huang, X. T., Huang, X. Y., Huang, Z. C., Ji, F., Ji, X. L., Jia, H. Y., Jiang, K., Jiang, Z. J., Jin, C., Ke, T., Kuleshov, D., Levochkin, K., Li, B. B., Li, Cheng, Li, Cong, Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, Jie, Li, Jian, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y., 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. S., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Liu, Z. X., Long, W. J., Lu, R., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Masood, A., Min, Z., Mitthumsiri, W., Montaruli, T., Nan, Y. C., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Rulev, V., Sáiz, A., Shao, L., Shchegolev, O., Sheng, X. D., Shi, J. Y., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Z. B., Tian, W. W., Wang, B. D., Wang, C., Wang, H., Wang, H. G., Wang, J. C., Wang, J. S., Wang, L. P., Wang, L. Y., Wang, R. N., Wang, Wei, Wang, X. G., Wang, X. J., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Y. P., 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, W. X., Wu, X. F., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xiao, H. B., Xin, G. G., Xin, Y. L., Xing, Y., Xu, D. L., Xu, R. X., Xue, L., Yan, D. H., Yan, J. Z., Yang, C. W., Yang, F. F., 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., Zeng, H. D., Zeng, T. X., Zeng, W., Zeng, Z. K., Zha, M., Zhai, X. X., Zhang, B. B., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, J. W., Zhang, L. X., Zhang, Li, Zhang, Lu, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Y. L., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, Y., Zhou, B., Zhou, H., Zhou, J. N., 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 Crab pulsar and the surrounding nebula powered by the pulsar's rotational energy through the formation and termination of a relativistic electron-positron wind is a bright source of gamma-rays carrying crucial information about this complex conglomerate. We report the detection of $\gamma$-rays with a spectrum showing gradual steepening over three energy decades, from $5\times 10^{-4}$ to $1.1$ petaelectronvolt (PeV). The ultra-high-energy photons exhibit the presence of a PeV electron accelerator (a pevatron) with an acceleration rate exceeding 15% of the absolute theoretical limit. Assuming that unpulsed $\gamma$-rays are produced at the termination of the pulsar's wind, we constrain the pevatron's size, between $0.025$ and $0.1$ pc, and the magnetic field $\approx 110 \mu$G. The production rate of PeV electrons, $2.5 \times 10^{36}$ erg $\rm s^{-1}$, constitutes 0.5% of the pulsar's spin-down luminosity, although we do not exclude a non-negligible contribution of PeV protons to the production of the highest energy $\gamma$-rays., Comment: 43 pages, 13 figures, 2 tables; Published in Science
Published: 2021
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31. In-plane quasi-single-domain BaTiO$_3$ via interfacial symmetry engineering

Author: Lee, J. W., Eom, K., Paudel, T. R., Wang, B., Lu, H., Huyan, H., Lindemann, S., Ryu, S., Lee, H., Kim, T. H., Yuan, Y., Zorn, J. A., Lei, S., Gao, W., Tybell, T., Gopalan, V., Pan, X., Gruverman, A., Chen, L. Q., Tsymbal, E. Y., and Eom, C. B.
Subjects: Condensed Matter - Materials Science
Abstract: The control of the in-plane domain evolution in ferroelectric thin films is not only critical to understanding ferroelectric phenomena but also to enabling functional device fabrication. However, in-plane polarized ferroelectric thin films typically exhibit complicated multi-domain states, not desirable for optoelectronic device performance. Here we report a strategy combining interfacial symmetry engineering and anisotropic strain to design single-domain, in-plane polarized ferroelectric BaTiO$_3$ thin films. Theoretical calculations predict the key role of the BaTiO$_3$ / PrScO$_3$ (110)$_O$ substrate interfacial environment, where anisotropic strain, monoclinic distortions, and interfacial electrostatic potential stabilize a single-variant spontaneous polarization. A combination of scanning transmission electron microscopy, piezoresponse force microscopy, ferroelectric hysteresis loop measurements, and second harmonic generation measurements directly reveals the stabilization of the in-plane quasi-single-domain polarization state. This work offers design principles for engineering in-plane domains of ferroelectric oxide thin films, which is a prerequisite for high performance optoelectronic devices.
Published: 2021
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32. KIF20A is a Prognostic Marker for Female Patients with Estrogen Receptor-Positive Breast Cancer and Receiving Tamoxifen as Adjuvant Endocrine Therapy

Author: Huang X, Li S, Gao W, Shi J, Cheng M, Mi Y, Liu Y, Sang M, Li Z, and Geng C
Subjects: kif20a, breast carcinoma, biomarker, tamoxifen, survival, prognosis, Medicine (General), R5-920
Abstract: Xuchen Huang,1,2 Sainan Li,1,2 Wei Gao,1,2 Jiajie Shi,1,2 Meng Cheng,1,2 Yunzhe Mi,1,2 Yueping Liu,3 Meixiang Sang,4 Ziyi Li,4 Cuizhi Geng1,2 1Department of Breast Center, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, People’s Republic of China; 2Key Laboratory in Hebei Province for Molecular Medicine of Breast Cancer, Shijiazhuang, Hebei, People’s Republic of China; 3Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, People’s Republic of China; 4Research Center and Tumor Research Institute, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, People’s Republic of ChinaCorrespondence: Cuizhi Geng, Department of Breast Center, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050000, People’s Republic of China, Tel/Fax +86-311-66696313, Email gengcuizhisci@163.comPurpose: Our aim was to verify whether KIF20A has the potential to serve as a prognostic marker for female patients with estrogen receptor (ER)-positive breast cancer (BC) and treated with tamoxifen (TAM).Patients and Methods: Online tools were used to investigate the potential correlation between KIF20A gene expression and survival of patients with ER-positive BC and TAM treatment. Furthermore, immunohistochemistry (IHC) was conducted to assess the expression levels of KIF20A in patients included from our center. The prognostic value of KIF20A for disease-free survival (DFS) and overall survival (OS) was further evaluated using Cox regression analysis.Results: According to the results obtained from online tools, it was found that patients with low KIF20A expression exhibited significantly better survival outcomes in terms of relapse-free survival (RFS), distant metastasis-free survival (DMFS), and OS compared to those with high KIF20A expression (P < 0.001, P < 0.001, and P = 0.008, respectively). Additionally, significantly lower gene expression of KIF20A was found in patients who responded to TAM than in those who did not respond to TAM (P < 0.001). We further included 203 patients with adjuvant TAM therapy, and IHC for KIF20A was performed on sections from paraffin-embedded blocks. Patients with low KIF20A expression had significantly better DFS and OS (P = 0.001 and 0.002, respectively, log rank test), and the expression of KIF20A was identified as an independent factor for predicting both DFS and OS (P = 0.001 and 0.008, respectively).Conclusion: KIF20A expression is an independent prognostic factor for survival in patients with ER-positive BC who received adjuvant TAM therapy. In clinical practice, IHC evaluation of KIF20A expression in surgical samples before administering tamoxifen may assist in predicting the treatment outcomes of these patients.Keywords: KIF20A, breast carcinoma, biomarker, tamoxifen, survival, prognosis
Published: 2023

33. High Prevalence and Burden of Physical and Psychological Symptoms in a Chronic Obstructive Pulmonary Disease Population in Primary Care Settings in South Africa

Author: Nkhoma KB, Farrant L, Mzimkulu O, Hunter J, Higginson I, Gao W, Maddocks M, Gwyther L, and Harding R
Subjects: chronic lung disease, chronic obstructive pulmonary disease, symptom burden, symptom distress, symptom prevalence, Diseases of the respiratory system, RC705-779
Abstract: Kennedy B Nkhoma,1 Lindsay Farrant,2 Olona Mzimkulu,2 Joy Hunter,2 Irene Higginson,1 Wei Gao,2 Matthew Maddocks,1 Liz Gwyther,2 Richard Harding1 1Cicely Saunders Institute of Palliative Care Policy and Rehabilitation, King’s College London, London, UK; 2Division of Interdisciplinary Palliative Care & Medicine, Department of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaCorrespondence: Kennedy B Nkhoma, Email kennedy.nkhoma@kcl.ac.ukBackground: Many deaths globally are attributable to non-communicable disease, and four-fifths of these deaths are in low- and middle-income countries. Globally, COPD is currently the third leading cause of mortality.Research Question: 1) To determine the prevalence and burden of symptoms and concerns, and 2) determine predicting factors of symptom burden among patients with COPD.Methods: A cross-sectional survey was conducted at eight primary care sites in Western Cape. We collected socio-demographic data (age, gender, smoking status, number of missed doses of prescribed medication in the last seven days) and clinical data (PEF and KPS). The Memorial Symptom Assessment Scale (MSAS), the Medical Outcomes Study, Social Support Survey (MOS-SSS), the London Chest Activity of Daily Living Scale (LCADLS) and the COPD Assessment Test (CAT) (impairment on person’s life) were administered to patients. We conducted ordered logistic regression analysis to assess factors associated with the burden of symptoms. MSAS subscales: 1) Global symptom distress index, 2) physical symptom distress and 3) psychological symptom distress were dependent outcomes. We constructed three ordinal logistic regression models for each of the three subscales. Covariates were MOS-SSS, LCADLS, CAT, demographic and clinical variables.Results: We recruited n=387 patients, mean age 59.5 years, 53.0% female. In multivariate analysis, each of the three models (ie, global, psychological and physical symptom distress) was positively associated with impairment on person’s life p< 0.001, difficulty to perform activities of daily living p< 0.001, and low social support p< 0.001. Old age was associated with lower global symptom distress (p=0.004), psychological and (0.014) physical distress (0.005). Missing 1 or more doses of medication was associated with higher levels of global (0.004) and physical (0.005) symptom distress.Interpretation: The high prevalence and burden of physical and psychological symptoms provides strong evidence of the need for integrating person-centred assessment and management of symptoms in primary care settings.Keywords: chronic lung disease, chronic obstructive pulmonary disease, symptom burden, symptom distress, symptom prevalence
Published: 2023

34. Feasibility of Data Transmission under Attack: From Isolated Toughness Variant Perspective

Author: Gao, W., Başkonuş, H. M., and Cattani, C.
Published: 2023
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35. Method to measure muon content of extensive air showers with LHAASO KM2A-WCDA synergy

Author: Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, L.X., 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, 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, H.L., Cheng, N., Cheng, Y.D., 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., Gao, B., Gao, C.D., Gao, L.Q., Gao, Q., Gao, W., Gao, W.K., Ge, M.M., Geng, L.S., 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.S., Liu, J.Y., Liu, M.Y., Liu, R.Y., Liu, S.M., Liu, W., Liu, Y., Liu, Y.N., Long, W.J., Lu, R., Luo, Q., Lv, H.K., Ma, B.Q., Ma, L.L., Ma, X.H., Mao, J.R., Min, Z., Mitthumsiri, W., Nan, Y.C., 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., Shao, C.Y., Shao, L., Shchegolev, O., Sheng, X.D., Song, H.C., Stenkin, Yu.V., Stepanov, V., Su, Y., Sun, Q.N., Sun, X.N., Sun, Z.B., Tam, P.H.T., Tang, Z.B., Tian, W.W., Wang, C., Wang, C.B., Wang, G.W., Wang, H.G., Wang, H.H., Wang, J.C., Wang, J.S., 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., 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., Zeng, Z.K., 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, Y., Zhou, B., Zhou, H., Zhou, J.N., Zhou, P., Zhou, R., Zhou, X.X., Zhu, C.G., Zhu, F.R., Zhu, H., Zhu, K.J., and Zuo, X.
Published: 2024
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36. Calibration of the Air Shower Energy Scale of the Water and Air Cherenkov Techniques in the LHAASO experiment

Author: Aharonian, F., An, Q., Axikegu, Bai, L. X., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, H., Cai, J. T., Cao, Z. Cao Z., Chang, J., Chang, J. F., Chang, X. C., Chen, B. M., Chen, J., Chen, L., Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, X. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Piazzoli, B. DEttorre, Dong, X. J., Fan, J. H., Fan, Y. Z., Fan, Z. X., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, Y. L., Gao, B., Gao, C. D., Gao, Q., Gao, W., Ge, M. M., Geng, L. S., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, J. G., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. C., He, S. L., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, C., Hou, X., Hu, H. B., Hu, S., Hu, S. C., Hu, X. J., Huang, D. H., Huang, Q. L., Huang, W. H., Huang, X. T., Huang, Z. C., Ji, F., Ji, X. L., Jia, H. Y., Jiang, K., Jiang, Z. J., Jin, C., Kuleshov, D., Levochkin, K., Li, B. B., Li, C., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, K., Li, W. L., Li, X., Li, X. R., Li, Y., Li, Y. Z., Li, Z., 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. S., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y. N., Liu, Z. X., Long, W. J., Lu, R., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Masood, A., Mitthumsiri, W., Montaruli, T., Nan, Y. C., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Ruffolo, D., Rulev, V., Saiz, A., Shao, L., Shchegolev, O., Sheng, X. D., Shi, J. R., Song, H. C., Stenkin, Yu. V., Stepanov, V., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Z. B., Tian, W. W., Wang, B. D., Wang, C., Wang, H., Wang, H. G., Wang, J. C., Wang, J. S., Wang, L. P., Wang, L. Y., Wang, R. N., Wang, W., Wang, X. G., Wang, X. J., Wang, X. Y., Wang, Y. D., Wang, Y. J., Wang, Y. P., Wang, Z., Wang, Z. H., Wang, Z. X., Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X., Wu, X. F., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, G., Xiao, H. B., Xin, G. G., Xin, Y. L., Xing, Y., Xu, D. L., Xu, R. X., Xue, L., Yan, D. H., Yang, C. W., Yang, F. F., 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., Zeng, H. D., Zeng, T. X., Zeng, W., Zeng, Z. K., Zha, M., Zhai, X. X., Zhang, B. B., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, J. W., Zhang, L., Zhang, L. X., Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y., Zhang, Y. F., Zhang, Y. L., Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, Y., Zhou, B., Zhou, H., Zhou, J. N., 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: The Wide Field-of-View Cherenkov Telescope Array (WFCTA) and the Water Cherenkov Detector Arrays (WCDA) of LHAASO are designed to work in combination for measuring the energy spectra of various cosmic ray species over a very wide energy range from a few TeV to 10 PeV. The energy calibration of WCDA can be achieved with a proven technique of measuring the westward shift of the Moon shadow of galactic cosmic rays due to the geomagnetic field. This deflection angle $\Delta$ is inversely proportional to the energy of the cosmic rays. The precise measurements of the shifts by WCDA allows us to calibrate its energy scale for energies as high as 35 TeV. The energy scale measured by WCDA can be used to cross calibrate the energy reconstructed by WFCTA, which spans the whole energy range up to 10 PeV. In this work, we will demonstrate the feasibility of the method using the data collected from April 2019 to January 2020 by the WFCTA array and WCDA-1 detector, the first of the three water Cherenkov ponds, already commissioned at LHAASO site.
Published: 2021
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37. Reconstruction of Cherenkov image by multiple telescopes of LHAASO-WFCTA

Author: Aharonian, F., An, Q., Axikegu, Bai, L. X., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Zhe, Cao, Zhen, Chang, J., Chang, J. F., Chen, E. S., Chen, Liang, Chen, Liang, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, H. L., Cheng, N., Cheng, Y. D., Cui, S. W., Cui, X. H., Cui, Y. D., D’Ettorre Piazzoli, B., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Duan, K. K., Fan, J. H., Fan, Y. Z., Fan, Z. X., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, J. G., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, S. L., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S., Hu, S. C., Hu, X. J., Huang, D. H., Huang, W. H., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Levochkin, K., Li, B. B., Li, Cheng, Li, Cong, 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, 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. S., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Long, W. J., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Masood, A., Min, Z., Mitthumsiri, W., Nan, Y. C., 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., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shi, J. Y., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Z. B., Tian, W. W., Wang, B. D., Wang, C., Wang, H., Wang, H. G., Wang, J. C., Wang, J. S., Wang, L. P., Wang, L. Y., Wang, R., Wang, R. N., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Y. P., 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. X., Xue, L., Yan, D. H., Yan, J. Z., Yang, C. W., 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., Zeng, Z. K., Zha, M., Zhai, X. X., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, Lu, 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, Y. L., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, Y., Zhou, B., Zhou, H., Zhou, J. N., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.
Published: 2022
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38. Construction and On-site Performance of the LHAASO WFCTA Camera

Author: Aharonian, F., An, Q., Axikegu, Bai, L. X., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, H., Cai, J. T., Cao, Z., Chang, J., Chang, J. F., Chang, X. C., Chen, B. M., Chen, J., Chen, L., Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, X. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Piazzoli, B. D'Ettorre, Dong, X. J., Fan, J. H., Fan, Y. Z., Fan, Z. X., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, Y. L., Gao, B., Gao, C. D., Gao, Q., Gao, W., Ge, M. M., Geng, L. S., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, J. G., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. C., He, S. L., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, C., Hou, X., Hu, H. B., Hu, S., Hu, S. C., Hu, X. J., Huang, D. H., Huang, Q. L., Huang, W. H., Huang, X. T., Huang, Z. C., Ji, F., Ji, X. L., Jia, H. Y., Jiang, K., Jiang, Z. J., Jin, C., Kuleshov, D., Levochkin, K., Li, B. B., Li, C., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, K., Li, W. L., Li, X., Li, X. R., Li, Y., Li, Y. Z., Li, Z., 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. S., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y. N., Liu, Z. X., Long, W. J., Lu, R., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Masood, A., Mitthumsiri, W., Montaruli, T., Nan, Y. C., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Ruffolo, D., Rulev, V., Sáiz, A., Shao, L., Shchegolev, O., Sheng, X. D., Shi, J. R., Song, H. C., Stenkin, Yu. V., Stepanov, V., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Z. B., Tian, W. W., Wang, B. D., Wang, C., Wang, H., Wang, H. G., Wang, J. C., Wang, J. S., Wang, L. P., Wang, L. Y., Wang, R. N., Wang, W., Wang, X. G., Wang, X. J., Wang, X. Y., Wang, Y. D., Wang, Y. J., Wang, Y. P., Wang, Z., Wang, Z. H., Wang, Z. X., Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, W. X., Wu, X. F., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, G., Xiao, H. B., Xin, G. G., Xin, Y. L., Xing, Y., Xu, D. L., Xu, R. X., Xue, L., Yan, D. H., Yang, C. W., Yang, F. F., 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., Zeng, H. D., Zeng, T. X., Zeng, W., Zeng, Z. K., Zha, M., Zhai, X. X., Zhang, B. B., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, J. W., Zhang, L., Zhang, L. X., Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y., Zhang, Y. F., Zhang, Y. L., Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, Y., Zhou, B., Zhou, H., Zhou, J. N., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.
Subjects: Physics - Instrumentation and Detectors, Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment
Abstract: The focal plane camera is the core component of the Wide Field-of-view Cherenkov/fluorescence Telescope Array (WFCTA) of the Large High-Altitude Air Shower Observatory (LHAASO). Because of the capability of working under moonlight without aging, silicon photomultipliers (SiPM) have been proven to be not only an alternative but also an improvement to conventional photomultiplier tubes (PMT) in this application. Eighteen SiPM-based cameras with square light funnels have been built for WFCTA. The telescopes have collected more than 100 million cosmic ray events and preliminary results indicate that these cameras are capable of working under moonlight. The characteristics of the light funnels and SiPMs pose challenges (e.g. dynamic range, dark count rate, assembly techniques). In this paper, we present the design features, manufacturing techniques and performances of these cameras. Finally, the test facilities, the test methods and results of SiPMs in the cameras are reported here., Comment: 45 pages, 21 figures, article
Published: 2020
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39. Non-probabilistic Informed Structural Health Assessment with Virtual Modelling Technique

Author: Wang, Q., Feng, Y., Wu, D., Gao, W., di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Duan, Wenhui, editor, Zhang, Lihai, editor, and Shah, Surendra P., editor
Published: 2023
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40. Insights into the Size Effect of the Dynamic Characteristics of the Perovskite Solar Cell

Author: Li, Q., Wu, D., Gao, W., di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Duan, Wenhui, editor, Zhang, Lihai, editor, and Shah, Surendra P., editor
Published: 2023
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41. Machine Learning-Aided Nonlinear Dynamic Analysis of Engineering Structures

Author: Feng, Y., Wang, Q., Wu, D., Gao, W., di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Duan, Wenhui, editor, Zhang, Lihai, editor, and Shah, Surendra P., editor
Published: 2023
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42. An Experimental Characterization of LARMbot Torso V1

Author: Gao, W., Ceccarelli, M., Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, Doroftei, Ioan, editor, Nitulescu, Mircea, editor, Pisla, Doina, editor, and Lovasz, Erwin-Christian, editor
Published: 2023
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43. Experimental study of subcooled flow boiling in microchannel heat sinks integrated with different embedded pin fin arrays microstructures

Author: Gao, W., Qu, Z.G., Zhang, J.F., and Jiao, Binbin
Published: 2025
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44. Investigation of the Effect of Aspect Ratio of Graphene Nanoplatelets on the Microstructure of Copper Matrix Composites

Author: Zhang, D., Ding, M., Xu, Y., Li, H., and Gao, W.
Published: 2023
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45. High Contrast Detection of Carotid Neothrombus with Strong Near-Infrared Absorption Selenium Nanosphere Enhanced Photoacoustic Imaging

Author: He F, Hou W, Lan Y, Gao W, Zhou M, Li J, Liu S, Yang B, and Zhang J
Subjects: photoacoustic contrast agent, molecular imaging, se@ppy nanocomposites, carotid artery thrombus, Medicine (General), R5-920
Abstract: Fengbing He,1,&ast; Wenzhong Hou,1,&ast; Yintao Lan,1,2 Weijian Gao,1 Mengyu Zhou,1 Jinghang Li,1 Shutong Liu,1 Bin Yang,1 Jian Zhang1 1Qingyuan People’s Hospital, The Sixth Affiliated Hospital of Guangzhou Medical University, School of Biomedical Engineering, Guangzhou Medical University, Guangdong, People’s Republic of China; 2Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangdong, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jian Zhang, Email jianzhang@gzhmu.edu.cnBackground: Carotid artery thrombosis is the leading cause of stroke. Since there are no apparent symptoms in the early stages of carotid atherosclerosis onset, it causes a more significant clinical diagnosis. Photoacoustic (PA) imaging provides high contrast and good depth information, which has been used for the early detection and diagnosis of many diseases.Methods: We investigated thrombus formation by using 20% ferric chloride (FeCl3) in the carotid arteries of KM mice for the thrombosis model. The near-infrared selenium/polypyrrole (Se@PPy) nanomaterials are easy to synthesize and have excellent optical absorption in vivo, which can be used as PA contrast agents to obtain thrombosis information.Results: In vitro experiments showed that Se@PPy nanocomposites have fulfilling PA ability in the 700 nm to 900 nm wavelength range. In the carotid atherosclerosis model, maximum PA signal enhancement up to 3.44, 4.04, and 5.07 times was observed by injection of Se@PPy nanomaterials, which helped to diagnose the severity of carotid atherosclerosis.Conclusion: The superior PA signal of Se@PPy nanomaterials can identify the extent of atherosclerotic carotid lesions, demonstrating the feasibility of PA imaging technology in diagnosing carotid thrombosis lesion formation. This study demonstrates nanocomposites and PA techniques for imaging and diagnosing carotid thrombosis in vivo.Keywords: photoacoustic contrast agent, molecular imaging, Se@PPy nanocomposites, carotid artery thrombus
Published: 2023

46. Emerging Anesthetic Nanomedicines: Current State and Challenges

Author: Zhang S, Wang Y, Huang C, Ding Q, Xia J, Wu D, and Gao W
Subjects: anesthesia, nanocarriers, blood-brain barrier, drugs, Medicine (General), R5-920
Abstract: Shuo Zhang,1,&ast; Yishu Wang,1,&ast; Shuai Zhang,1 Chengqi Huang,1 Qiyang Ding,2 Ji Xia,2 Daocheng Wu,1 Wei Gao2 1The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, 710049, People’s Republic of China; 2Department of Anesthesiology & Center for Brain Science & Center for Translational Medicine, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, 710049, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Daocheng Wu, The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, 710049, People’s Republic of China, Tel/Fax +86-29-82663941, Email wudaocheng@mail.xjtu.edu.cn Wei Gao, Department of Anesthesiology & Center for Brain Science & Center for Translational Medicine, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, 710049, People’s Republic of China, Tel +86 15209225834, Email gaowei2906@xjtufh.edu.cnAbstract: Anesthetics, which include both local and general varieties, are a unique class of drugs widely utilized in clinical surgery to alleviate pain and promote relaxation in patients. Although numerous anesthetics and their traditional formulations are available in the market, only a select few exhibit excellent anesthetic properties that meet clinical requirements. The main challenges are the potential toxic and adverse effects of anesthetics, as well as the presence of the blood-brain barrier (BBB), which makes it difficult for most general anesthetics to effectively penetrate to the brain. Loading anesthetics onto nanocarriers as anesthetic nanomedicines might address these challenges and improve anesthesia effectiveness, reduce toxic and adverse effects, while significantly enhance the efficiency of general anesthetics passing through the BBB. Consequently, anesthetic nanomedicines play a crucial role in the field of anesthesia. Despite their significance, research on anesthetic nanomedicines is still in its infancy, especially when compared to other types of nanomedicines in terms of depth and breadth. Although local anesthetic nanomedicines have received considerable attention and essentially meet clinical needs, there are few reported instances of nanomedicines for general anesthetics. Given the extensive usage of anesthetics and the many of them need for improved performance, emerging anesthetic nanomedicines face both unparalleled opportunities and considerable challenges in terms of theory and technology. Thus, a comprehensive summary with systematic analyses of anesthetic nanomedicines is urgently required. This review provides a comprehensive summary of the classification, properties, and research status of anesthetic nanomedicines, along with an exploration of their opportunities and challenges. In addition, future research directions and development prospects are discussed. It is hoped that researchers from diverse disciplines will collaborate to study anesthetic nanomedicines and develop them as a valuable anesthetic dosage form for clinical surgery.Keywords: anesthesia, nanocarriers, blood-brain barrier, drugs
Published: 2023

47. Partial Response to Crizotinib in a Lung Adenocarcinoma Patient with a Novel FBXO11 (Intergenic)-ALK (Exon 20-29) Fusion

Author: He J, Yao Y, Quan F, Lu Z, Wang J, and Gao W
Subjects: intergenic fusion, lung adenocarcinoma, alk, slx4, chromothripsis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Jing He,1,&ast; Youyuan Yao,1,&ast; Fei Quan,2 Zhongyu Lu,2 Jian Wang,1 Wen Gao1 1Medical Oncology Department, Jiangsu Province Hospital, Nanjing, Jiangsu, 210029, People’s Republic of China; 2The Medical Department, Jiangsu Simcere Diagnostics Co., Ltd, Nanjing, Jiangsu, 210021, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Wen Gao; Jian Wang, Medical Oncology Department, Jiangsu Province Hospital, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, People’s Republic of China, Tel +86 025 68305755, Fax +86 025 68305758, Email drgaowen@yeah.net; WJ20210205@126.comAbstract: Intergenic-gene fusion detected by DNA-seq is particularly confusing for drug selection since the function of the intergenic region located upstream is unknown. We reported a case of a 49-year-old male with advanced lung adenocarcinoma, who was detected FBXO11 (intergenic)-ALK (exon 20-29) by DNA-seq, and FISH analysis revealed a positive result. The patient was treated with crizotinib and achieved a PR. The canonical EML4 (exon 1-13)-ALK (exon 20-29) fusion verified by RNA-seq suggested a complex EML4 (exon 1-13)-FBXO11 (intergenic)-ALK (exon 20-29) tripartite rearrangement at the DNA level. Our case emphasized the necessity of RNA-seq for verifying intergenic-gene fusion. Simultaneously, the pathogenic germline SLX4 variant and extensive CNVs of DNA segment were detected by DNA-seq deserves our attention.Keywords: intergenic fusion, lung adenocarcinoma, ALK, SLX4, chromothripsis
Published: 2023

48. Comparison of High Flow Nasal Therapy with Non-Invasive Ventilation and Conventional Oxygen Therapy for Acute Hypercapnic Respiratory Failure: A Meta-Analysis of Randomized Controlled Trials

Author: Xu C, Yang F, Wang Q, and Gao W
Subjects: high-flow nasal cannula, non-invasive ventilation, conventional oxygen treatment, hypercapnic respiratory failure, Diseases of the respiratory system, RC705-779
Abstract: Cuiping Xu, Feng Yang, Qimin Wang, Wei Gao Department of Respiratory and Critical Care Medicine, China Rehabilitation Research Center, Rehabilitation School of Capital Medical University, Beijing, People’s Republic of ChinaCorrespondence: Wei Gao, Tel +86 10-87569070, Fax +86 10-67573428, Email rhhuxi@163.comPurpose: We aimed to evaluate whether high flow nasal cannula (HFNC) is an effective and safe method for adult patients with acute hypercapnic respiratory failure (AHRF).Methods: We searched the Cochrane Library, Embase, and PubMed databases from inception to August 2022 to obtain randomized controlled trials (RCTs) that compared HFNC with conventional oxygen treatment (COT) or non-invasive ventilation (NIV) in patients with AHRF, and then performed a meta-analysis.Results: A total of ten parallel RCTs with 1265 individuals were identified. Of them, two studies compared HFNC with COT and eight studies compared HFNC with NIV. In terms of intubation rate, mortality, and arterial blood gas (ABG) improvement, HFNC showed comparable effects to NIV and COT. However, HFNC was more comfortable (mean difference [MD] − 1.87, 95% confidence interval [CI] =− 2.59, − 1.15, P < 0.00001, I2 =0%) and resulted in fewer adverse events (odds ratio [OR] 0.12, 95% CI=0.06, 0.28, P< 0.00001, I2 = 0%), compared with NIV. In comparison to NIV, HFNC could significantly lower heart rate (HR) (MD − 4.66, 95% CI=− 6.82, − 2.50, P < 0.0001, I2 =0%), respiratory rate (RR) (MD − 1.17, 95% CI=− 2.03, − 0.31, P =0.008, I2 =0%), and hospital stay length (MD − 0.80, 95% CI=− 1.44, − 0.16, P =0.01, I2 =0%). NIV showed a decreased frequency in the treatment crossover rate, compared with HFNC in patients with pH< 7.30 (OR 5.78, 95% CI=1.50, 22.31, P = 0.01, I2: not applicable). Contrary to COT, HFNC could considerably reduce the need for NIV (OR 0.57, 95% CI=0.35, 0.91, P=0.02, I2=0%).Conclusion: HFNC was effective and safe in patients with AHRF. However, in patients with pH < 7.30, HFNC may result in a higher incidence of treatment crossover, compared with NIV. Compared to COT, HFNC may decrease the need for NIV in patients with compensated hypercapnia.Keywords: high-flow nasal cannula, non-invasive ventilation, conventional oxygen treatment, hypercapnic respiratory failure
Published: 2023

49. The observation of the Crab Nebula with LHAASO-KM2A for the performance study

Author: Aharonian, F., An, Q., Axikegu, Bai, L. X., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, H., Cai, J. T., Cao, Z., Chang, J., Chang, J. F., Chang, X. C., Chen, B. M., Chen, J., Chen, L., Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, X. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Piazzoli, B. D'Ettorre, Dong, X. J., Fan, J. H., Fan, Y. Z., Fan, Z. X., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, Y. L., Gao, B., Gao, C. D., Gao, Q., Gao, W., Ge, M. M., Geng, L. S., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, J. G., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. C., He, S. L., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, C., Hou, X., Hu, H. B., Hu, S., Hu, S. C., Hu, X. J., Huang, D. H., Huang, Q. L., Huang, W. H., Huang, X. T., Huang, Z. C., Ji, F., Ji, X. L., Jia, H. Y., Jiang, K., Jiang, Z. J., Jin, C., Kuleshov, D., Levochkin, K., Li, B. B., Li, C., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, K., Li, W. L., Li, X., Li, X. R., Li, Y., Li, Y. Z., Li, Z., 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. S., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y. N., Liu, Z. X., Long, W. J., Lu, R., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Masood, A., Mitthumsiri, W., Montaruli, T., Nan, Y. C., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Ruffolo, D., Rulev, V., Sáiz, A., Shao, L., Shchegolev, O., Sheng, X. D., Shi, J. R., Song, H. C., Stenkin, Yu. V., Stepanov, V., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Z. B., Tian, W. W., Wang, B. D., Wang, C., Wang, H., Wang, H. G., Wang, J. C., Wang, J. S., Wang, L. P., Wang, L. Y., Wang, R. N., Wang, W., Wang, X. G., Wang, X. J., Wang, X. Y., Wang, Y. D., Wang, Y. J., Wang, Y. P., Wang, Z., Wang, Z. H., Wang, Z. X., Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, W. X., Wu, X. F., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, G., Xiao, H. B., Xin, G. G., Xin, Y. L., Xing, Y., Xu, D. L., Xu, R. X., Xue, L., Yan, D. H., Yang, C. W., Yang, F. F., 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., Zeng, H. D., Zeng, T. X., Zeng, W., Zeng, Z. K., Zha, M., Zhai, X. X., Zhang, B. B., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, J. W., Zhang, L., Zhang, L. X., Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y., Zhang, Y. F., Zhang, Y. L., Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, Y., Zhou, B., Zhou, H., Zhou, J. N., 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, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: As a sub-array of the Large High Altitude Air Shower Observatory (LHAASO), KM2A is mainly designed to cover a large fraction of the northern sky to hunt for gamma-ray sources at energies above 10 TeV. Even though the detector construction is still underway, a half of the KM2A array has been operating stably since the end of 2019. In this paper, we present the pipeline of KM2A data analysis and the first observation on the Crab Nebula, a standard candle in very high energy gamma-ray astronomy. We detect gamma-ray signals from the Crab Nebula in both energy ranges of 10$-$100 TeV and $>$100 TeV with high significance, by analyzing the KM2A data of 136 live days between December 2019 and May 2020. With the observations, we test the detector performance including angular resolution, pointing accuracy and cosmic ray background rejection power. The energy spectrum of the Crab Nebula in the energy range 10-250 TeV fits well with a single power-law function dN/dE =(1.13$\pm$0.05$_{stat}$$\pm$0.08$_{sys}$)$\times$10$^{-14}$$\cdot$(E/20TeV)$^{-3.09\pm0.06_{stat}\pm0.02_{sys}}$ cm$^{-2}$ s$^{-1}$ TeV$^{-1}$. It is consistent with previous measurements by other experiments. This opens a new window of gamma-ray astronomy above 0.1 PeV through which ultrahigh-energy gamma-ray new phenomena, such as cosmic PeVatrons, might be discovered., Comment: 13 pages, 15 figures,submitted to CPC
Published: 2020
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50. Observation of Photoinduced Terahertz Gain in GaAs Quantum Wells: Evidence for Radiative Two-Exciton-to-Biexciton Scattering

Author: Li, X., Yoshioka, K., Zhang, Q., Peraca, N. Marquez, Katsutani, F., Gao, W., Noe II, G. T., Watson, J. D., Manfra, M. J., Katayama, I., Takeda, J., and Kono, J.
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science, Condensed Matter - Quantum Gases
Abstract: We have observed photoinduced negative optical conductivity, or gain, in the terahertz frequency range in a GaAs multiple-quantum-well structure in a strong perpendicular magnetic field at low temperatures. The gain is narrow-band: it appears as a sharp peak (linewidth $<$0.45 meV) whose frequency shifts with applied magnetic field. The gain has a circular-polarization selection rule: a strong line is observed for hole-cyclotron-resonance-active polarization. Furthermore, the gain appears only when the exciton $1s$ state is populated, which rules out intraexcitonic transitions to be its origin. Based on these observations, we propose a possible process in which the stimulated emission of a terahertz photon occurs while two free excitons scatter into one biexciton in an energy and angular-momentum conserving manner., Comment: 5 pages, 4 figures
Published: 2020
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