Data quality control system and long-term performance monitor of the LHAASO-KM2A

Autor: 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.

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 pri

Externí odkaz: http://arxiv.org/abs/2405.11826

Engineering Probiotics for Diabetes Management: Advances, Challenges, and Future Directions in Translational Microbiology

Autor: Zhang S, Ma J, Ma Y, Yi J, Wang B, Wang H, Yang Q, Zhang K, Yan X, Sun D, You J

Publikováno v: International Journal of Nanomedicine, Vol Volume 19, Pp 10917-10940 (2024)

Shenghao Zhang,1,* Jiahui Ma,1,* Yilei Ma,1,* Jia Yi,1 Beier Wang,2 Hanbing Wang,3 Qinsi Yang,4 Kun Zhang,5 Xiaoqing Yan,6 Da Sun,1,7 Jinfeng You8 1Institute of Life Sciences & Biomedical Collaborative Innovation Center of Zhejiang Provin

Externí odkaz: https://doaj.org/article/be4e8448f8314100af57702f8252df4d

A Novel Scale System Based on the Frailty Index and Laboratory Indicators for the Short-Term Prognosis of Patients with Acute Myocardial Infarction: A Retrospective Cohort Study

Autor: Cao T, Liu F, Yao Y, Sun D, Wang R, Cao J, Meng J, Zhang L, Li W

Publikováno v: Clinical Interventions in Aging, Vol Volume 19, Pp 1597-1606 (2024)

Tianqing Cao,1,* Fei Liu,2,* Yan Yao,2 Danghong Sun,2 Rong Wang,3 Junxia Cao,3 Jie Meng,2 Ling Zhang,4 Weiming Li1 1Shanghai Tenth People’s Hospital, Clinical Medical College of Nanjing Medical University, Nanjing, People’s Republic of Ch

Externí odkaz: https://doaj.org/article/6fc0885247af4e7e86b7ced4b62a2c89

Reduced Graphene Oxide Fibers Combined with Electrical Stimulation Promote Peripheral Nerve Regeneration

Autor: Zhao Y, Liu Y, Lu C, Sun D, Kang S, Wang X, Lu L

Publikováno v: International Journal of Nanomedicine, Vol Volume 19, Pp 2341-2357 (2024)

Yuanyuan Zhao,1 Yang Liu,1 Cheng Lu,1 Daokuan Sun,2 Shiqi Kang,1 Xin Wang,2,* Laijin Lu1,* 1Department of Hand and Podiatric Surgery, Orthopedics Center, The First Hospital of Jilin University, Changchun, Jilin, People’s Republic of China;

Externí odkaz: https://doaj.org/article/3f7773fe573e465680778d8de1ae6d50

The Angell Plot from the Potential Energy Landscape Perspective

Autor: Zhang, D. M., Sun, D. Y., Gong, X. G.

Within the scenario of the potential energy landscape (PEL), a thermodynamic model has been developed to uncover the physics behind the Angell plot. In our model, by separating the barrier distribution in PELs into a Gaussian-like and a power-law for

Externí odkaz: http://arxiv.org/abs/2203.11428