Author: "X Lu" - Searchworks@Jio Institute Digital Library Search Results

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24,933 results on '"X Lu"'

1. P05.01 Sensitizing immunotherapy refractory prostate cancer with optimized ketogenic diet regimen and epigenetic reprogramming

Author: S Murphy, J Li, X Lu, D Gan, and S Rahmy
Subjects: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Published: 2024
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2. Association Analysis Between ESR Gene and Egg Production Performance of Laying Quails

Author: J Bai, HD Fan, and X Lu
Subjects: Association analysis, egg quail, ESR gene, egg production performance, PCR-RFLP, Animal culture, SF1-1100, Veterinary medicine, SF600-1100, Zoology, QL1-991
Abstract: ABSTRACT In order to explore the effect of estrogen receptor (ESR) gene polymorphism on the egg production performance of quails, the polymorphisms of exon 1, exon 4 and exon 8 of the ESR gene in three Laying Quail Populations of Chinese Yellow quail, Korean quail and Beijing white quail were detected by PCR-RFLP, and their association with the egg production performance of quails was analyzed. The results showed that three genotypes were detected in exon 1, exon 4 and exon 8 of the ESR gene in three quail populations, namely TT, CC and CT genotypes. Among them, the frequency of CC genotype in exon 1 of the ESR gene was the highest in Chinese Yellow quail, Beijing white quail and Korean quail (0.515, 0.600 and 0.723); Exon 4 of the ESR gene had the highest frequency of TT genotype (0.409, 0.617) in Chinese yellow and Korean quails, while CC genotype was the highest in Beijing white quails (0.667).The frequency of TT genotype in exon 8 of the ESR gene was the highest in Beijing white quail and Korean quail (0.708, 0.500), while the frequency of CT gene was the highest in Chinese yellow quail (0.521). The results of association analysis showed that there was no correlation between exon 1 of the ESR gene and quail egg production performance (p>0.05). Exon 4 of the ESR gene was significantly correlated with laying traits such as feed-egg ratio, egg laying number, laying rate and starting weight of quails (p
Published: 2023
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3. Search for the radiative decay D s + → γρ 770 + $$ {D}_s^{+}\to \gamma \rho {(770)}^{+} $$

Author: The BESIII collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, O. Afedulidis, X. C. Ai, R. Aliberti, A. Amoroso, Q. An, Y. Bai, O. Bakina, I. Balossino, Y. Ban, H.-R. Bao, V. Batozskaya, K. Begzsuren, N. Berger, M. Berlowski, M. Bertani, D. Bettoni, F. Bianchi, E. Bianco, A. Bortone, I. Boyko, R. A. Briere, A. Brueggemann, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, X. Y. Chai, J. F. Chang, G. R. Che, Y. Z. Che, G. Chelkov, C. Chen, C. H. Chen, Chao Chen, G. Chen, H. S. Chen, H. Y. Chen, M. L. Chen, S. J. Chen, S. L. Chen, S. M. Chen, T. Chen, X. R. Chen, X. T. Chen, Y. B. Chen, Y. Q. Chen, Z. J. Chen, Z. Y. Chen, S. K. Choi, G. Cibinetto, F. Cossio, J. J. Cui, H. L. Dai, J. P. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, C. Q. Deng, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, B. Ding, X. X. Ding, Y. Ding, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, M. C. Du, S. X. Du, Y. Y. Duan, Z. H. Duan, P. Egorov, Y. H. Fan, J. Fang, S. S. Fang, W. X. Fang, Y. Fang, Y. Q. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, Y. T. Feng, M. Fritsch, C. D. Fu, J. L. Fu, Y. W. Fu, H. Gao, X. B. Gao, Y. N. Gao, Yang Gao, S. Garbolino, I. Garzia, L. Ge, P. T. Ge, Z. W. Ge, C. Geng, E. M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, S. Gramigna, M. Greco, M. H. Gu, Y. T. Gu, C. Y. Guan, A. Q. Guo, L. B. Guo, M. J. Guo, R. P. Guo, Y. P. Guo, A. Guskov, J. Gutierrez, K. L. Han, T. T. Han, F. Hanisch, X. Q. Hao, F. A. Harris, K. K. He, K. L. He, F. H. Heinsius, C. H. Heinz, Y. K. Heng, C. Herold, T. Holtmann, P. C. Hong, G. Y. Hou, X. T. Hou, Y. R. Hou, Z. L. Hou, B. Y. Hu, H. M. Hu, J. F. Hu, S. L. Hu, T. Hu, Y. Hu, G. S. Huang, K. X. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Y. S. Huang, T. Hussain, F. Hölzken, N. Hüsken, N. in der Wiesche, J. Jackson, S. Janchiv, J. H. Jeong, Q. Ji, Q. P. Ji, W. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, X. Q. Jia, Z. K. Jia, D. Jiang, H. B. Jiang, P. C. Jiang, S. S. Jiang, T. J. Jiang, X. S. Jiang, Y. Jiang, J. B. Jiao, J. K. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, X. M. Jing, T. Johansson, S. Kabana, N. Kalantar-Nayestanaki, X. L. Kang, X. S. Kang, M. Kavatsyuk, B. C. Ke, V. Khachatryan, A. Khoukaz, R. Kiuchi, O. B. Kolcu, B. Kopf, M. Kuessner, X. Kui, N. Kumar, A. Kupsc, W. Kühn, J. J. Lane, L. Lavezzi, T. T. Lei, Z. H. Lei, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. B. Li, H. J. Li, H. N. Li, Hui Li, J. R. Li, J. S. Li, K. Li, K. L. Li, L. J. Li, L. K. Li, Lei Li, M. H. Li, P. R. Li, Q. M. Li, Q. X. Li, R. Li, S. X. Li, T. Li, W. D. Li, W. G. Li, X. Li, X. H. Li, X. L. Li, X. Y. Li, X. Z. Li, Y. G. Li, Z. J. Li, Z. Y. Li, C. Liang, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, Y. P. Liao, J. Libby, A. Limphirat, C. C. Lin, D. X. Lin, T. Lin, B. J. Liu, B. X. Liu, C. Liu, C. X. Liu, F. Liu, F. H. Liu, Feng Liu, G. M. Liu, H. Liu, H. B. Liu, H. H. Liu, H. M. Liu, Huihui Liu, J. B. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, L. C. Liu, Lu Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, T. Liu, W. K. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. D. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, Z. H. Lu, C. L. Luo, J. R. Luo, M. X. Luo, T. Luo, X. L. Luo, X. R. Lyu, Y. F. Lyu, F. C. Ma, H. Ma, H. L. Ma, J. L. Ma, L. L. Ma, L. R. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, T. Ma, X. T. Ma, X. Y. Ma, Y. M. Ma, F. E. Maas, I. MacKay, M. Maggiora, S. Malde, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, H. Miao, T. J. Min, R. E. Mitchell, X. H. Mo, B. Moses, N. Yu. Muchnoi, J. Muskalla, Y. Nefedov, F. Nerling, L. S. Nie, I. B. Nikolaev, Z. Ning, S. Nisar, Q. L. Niu, W. D. Niu, Y. Niu, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, Y. P. Pei, M. Pelizaeus, H. P. Peng, Y. Y. Peng, K. Peters, J. L. Ping, R. G. Ping, S. Plura, V. Prasad, F. Z. Qi, H. Qi, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, C. F. Qiao, X. K. Qiao, J. J. Qin, L. Q. Qin, L. Y. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, Z. H. Qu, C. F. Redmer, K. J. Ren, A. Rivetti, M. Rolo, G. Rong, Ch. Rosner, M. Q. Ruan, S. N. Ruan, N. Salone, A. Sarantsev, Y. Schelhaas, K. Schoenning, M. Scodeggio, K. Y. Shan, W. Shan, X. Y. Shan, Z. J. Shang, J. F. Shangguan, L. G. Shao, M. Shao, C. P. Shen, H. F. Shen, W. H. Shen, X. Y. Shen, B. A. Shi, H. Shi, H. C. Shi, J. L. Shi, J. Y. Shi, Q. Q. Shi, S. Y. Shi, X. Shi, J. J. Song, T. Z. Song, W. M. Song, Y. J. Song, Y. X. Song, S. Sosio, S. Spataro, F. Stieler, S. S Su, Y. J. Su, G. B. Sun, G. X. Sun, H. Sun, H. K. Sun, J. F. Sun, K. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, Y. Sun, Y. J. Sun, Y. Z. Sun, Z. Q. Sun, Z. T. Sun, C. J. Tang, G. Y. Tang, J. Tang, M. Tang, Y. A. Tang, L. Y. Tao, Q. T. Tao, M. Tat, J. X. Teng, V. Thoren, W. H. Tian, Y. Tian, Z. F. Tian, I. Uman, Y. Wan, S. J. Wang, B. Wang, B. L. Wang, Bo Wang, D. Y. Wang, F. Wang, H. J. Wang, J. J. Wang, J. P. Wang, K. Wang, L. L. Wang, M. Wang, N. Y. Wang, S. Wang, T. Wang, T. J. Wang, W. Wang, W. P. Wang, X. Wang, X. F. Wang, X. J. Wang, X. L. Wang, X. N. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. L. Wang, Y. N. Wang, Y. Q. Wang, Yaqian Wang, Yi Wang, Z. Wang, Z. L. Wang, Z. Y. Wang, Ziyi Wang, D. H. Wei, F. Weidner, S. P. Wen, Y. R. Wen, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, C. Wu, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, X. H. Wu, Y. Wu, Y. H. Wu, Y. J. Wu, Z. Wu, L. Xia, X. M. Xian, B. H. Xiang, T. Xiang, D. Xiao, G. Y. Xiao, S. Y. Xiao, Y. L. Xiao, Z. J. Xiao, C. Xie, X. H. Xie, Y. Xie, Y. G. Xie, Y. H. Xie, Z. P. Xie, T. Y. Xing, C. F. Xu, C. J. Xu, G. F. Xu, H. Y. Xu, M. Xu, Q. J. Xu, Q. N. Xu, W. Xu, W. L. Xu, X. P. Xu, Y. Xu, Y. C. Xu, Z. S. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, X. Q. Yan, H. J. Yang, H. L. Yang, H. X. Yang, J. H. Yang, T. Yang, Y. Yang, Y. F. Yang, Y. X. Yang, Z. W. Yang, Z. P. Yao, M. Ye, M. H. Ye, J. H. Yin, Junhao Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, M. C. Yu, T. Yu, X. D. Yu, Y. C. Yu, C. Z. Yuan, J. Yuan, L. Yuan, S. C. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. A. Zafar, F. R. Zeng, S. H. Zeng, X. Zeng, Y. Zeng, Y. J. Zeng, X. Y. Zhai, Y. C. Zhai, Y. H. Zhan, A. Q. Zhang, B. L. Zhang, B. X. Zhang, D. H. Zhang, G. Y. Zhang, H. Zhang, H. C. Zhang, H. H. Zhang, H. Q. Zhang, H. R. Zhang, H. Y. Zhang, J. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. S. Zhang, J. W. Zhang, J. X. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, L. M. Zhang, Lei Zhang, N Zhang, P. Zhang, Q. Y. Zhang, R. Y. Zhang, S. H. Zhang, Shulei Zhang, X. M. Zhang, X. Y Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Y. M. Zhang, Yan Zhang, Z. D. Zhang, Z. H. Zhang, Z. L. Zhang, Z. Y. Zhang, Z. Z. Zhang, G. Zhao, J. Y. Zhao, J. Z. Zhao, L. Zhao, Lei Zhao, M. G. Zhao, N. Zhao, R. P. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, B. M. Zheng, J. P. Zheng, W. J. Zheng, Y. H. Zheng, B. Zhong, X. Zhong, H. Zhou, J. Y. Zhou, L. P. Zhou, S. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, Y. Z. Zhou, Z. C. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, K. S. Zhu, L. Zhu, L. X. Zhu, S. H. Zhu, T. J. Zhu, W. D. Zhu, Y. C. Zhu, Z. A. Zhu, J. H. Zou, and J. Zu
Subjects: Branching fraction, Charm Physics, e +-e − Experiments, Rare Decay, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract Using 7.33 fb −1 of e + e − collision data samples collected with the BESIII detector at center-of-mass energies between 4.128 and 4.226 GeV, we search for the radiative decay D s + → γρ 770 + $$ {D}_s^{+}\to \gamma \rho {(770)}^{+} $$ for the first time. A hint of D s + → γρ 770 + $$ {D}_s^{+}\to \gamma \rho {(770)}^{+} $$ is observed with a statistical significance of 2.5σ. The branching fraction of D s + → γρ 770 + $$ {D}_s^{+}\to \gamma \rho {(770)}^{+} $$ is measured to be (2.2 ± 0.9stat. ± 0.2syst. ) × 10 −4, corresponding to an upper limit of 6.1 × 10 −4 at the 90% confidence level.
Published: 2024
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4. Improved measurement of the branching fraction of h c → γη′/η and search for h c → γπ 0

Author: The BESIII collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, O. Afedulidis, X. C. Ai, R. Aliberti, A. Amoroso, Q. An, Y. Bai, O. Bakina, I. Balossino, Y. Ban, H. -R. Bao, V. Batozskaya, K. Begzsuren, N. Berger, M. Berlowski, M. Bertani, D. Bettoni, F. Bianchi, E. Bianco, A. Bortone, I. Boyko, R. A. Briere, A. Brueggemann, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, G. R. Che, Y. Z. Che, G. Chelkov, C. Chen, C. H. Chen, Chao Chen, G. Chen, H. S. Chen, H. Y. Chen, M. L. Chen, S. J. Chen, S. L. Chen, S. M. Chen, T. Chen, X. R. Chen, X. T. Chen, Y. B. Chen, Y. Q. Chen, Z. J. Chen, Z. Y. Chen, S. K. Choi, G. Cibinetto, F. Cossio, J. J. Cui, H. L. Dai, J. P. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, C. Q. Deng, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, B. Ding, X. X. Ding, Y. Ding, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, M. C. Du, S. X. Du, Y. Y. Duan, Z. H. Duan, P. Egorov, Y. H. Fan, J. Fang, S. S. Fang, W. X. Fang, Y. Fang, Y. Q. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, Y. T. Feng, M. Fritsch, C. D. Fu, J. L. Fu, Y. W. Fu, H. Gao, X. B. Gao, Y. N. Gao, Yang Gao, S. Garbolino, I. Garzia, L. Ge, P. T. Ge, Z. W. Ge, C. Geng, E. M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, S. Gramigna, M. Greco, M. H. Gu, Y. T. Gu, C. Y. Guan, A. Q. Guo, L. B. Guo, M. J. Guo, R. P. Guo, Y. P. Guo, A. Guskov, J. Gutierrez, K. L. Han, T. T. Han, F. Hanisch, X. Q. Hao, F. A. Harris, K. K. He, K. L. He, F. H. Heinsius, C. H. Heinz, Y. K. Heng, C. Herold, T. Holtmann, P. C. Hong, G. Y. Hou, X. T. Hou, Y. R. Hou, Z. L. Hou, B. Y. Hu, H. M. Hu, J. F. Hu, S. L. Hu, T. Hu, Y. Hu, G. S. Huang, K. X. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Y. S. Huang, T. Hussain, F. Hölzken, N. Hüsken, N. in der Wiesche, J. Jackson, S. Janchiv, J. H. Jeong, Q. Ji, Q. P. Ji, W. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, X. Q. Jia, Z. K. Jia, D. Jiang, H. B. Jiang, P. C. Jiang, S. S. Jiang, T. J. Jiang, X. S. Jiang, Y. Jiang, J. B. Jiao, J. K. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, X. M. Jing, T. Johansson, S. Kabana, N. Kalantar-Nayestanaki, X. L. Kang, X. S. Kang, M. Kavatsyuk, B. C. Ke, V. Khachatryan, A. Khoukaz, R. Kiuchi, O. B. Kolcu, B. Kopf, M. Kuessner, X. Kui, N. Kumar, A. Kupsc, W. Kühn, J. J. Lane, L. Lavezzi, T. T. Lei, Z. H. Lei, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. B. Li, H. J. Li, H. N. Li, Hui Li, J. R. Li, J. S. Li, K. Li, K. L. Li, L. J. Li, L. K. Li, Lei Li, M. H. Li, P. R. Li, Q. M. Li, Q. X. Li, R. Li, S. X. Li, T. Li, W. D. Li, W. G. Li, X. Li, X. H. Li, X. L. Li, X. Y. Li, X. Z. Li, Y. G. Li, Z. J. Li, Z. Y. Li, C. Liang, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, Y. P. Liao, J. Libby, A. Limphirat, C. C. Lin, D. X. Lin, T. Lin, B. J. Liu, B. X. Liu, C. Liu, C. X. Liu, F. Liu, F. H. Liu, Feng Liu, G. M. Liu, H. Liu, H. B. Liu, H. H. Liu, H. M. Liu, Huihui Liu, J. B. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, L. C. Liu, Lu Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, T. Liu, W. K. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. D. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, Z. H. Lu, C. L. Luo, J. R. Luo, M. X. Luo, T. Luo, X. L. Luo, X. R. Lyu, Y. F. Lyu, F. C. Ma, H. Ma, H. L. Ma, J. L. Ma, L. L. Ma, L. R. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, T. Ma, X. T. Ma, X. Y. Ma, Y. M. Ma, F. E. Maas, M. Maggiora, S. Malde, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, H. Miao, T. J. Min, R. E. Mitchell, X. H. Mo, B. Moses, N. Yu. Muchnoi, J. Muskalla, Y. Nefedov, F. Nerling, L. S. Nie, I. B. Nikolaev, Z. Ning, S. Nisar, Q. L. Niu, W. D. Niu, Y. Niu, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, Y. P. Pei, M. Pelizaeus, H. P. Peng, Y. Y. Peng, K. Peters, J. L. Ping, R. G. Ping, S. Plura, V. Prasad, F. Z. Qi, H. Qi, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, C. F. Qiao, X. K. Qiao, J. J. Qin, L. Q. Qin, L. Y. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, Z. H. Qu, C. F. Redmer, K. J. Ren, A. Rivetti, M. Rolo, G. Rong, Ch. Rosner, M. Q. Ruan, S. N. Ruan, N. Salone, A. Sarantsev, Y. Schelhaas, K. Schoenning, M. Scodeggio, K. Y. Shan, W. Shan, X. Y. Shan, Z. J. Shang, J. F. Shangguan, L. G. Shao, M. Shao, C. P. Shen, H. F. Shen, W. H. Shen, X. Y. Shen, B. A. Shi, H. Shi, H. C. Shi, J. L. Shi, J. Y. Shi, Q. Q. Shi, S. Y. Shi, X. Shi, J. J. Song, T. Z. Song, W. M. Song, Y. J. Song, Y. X. Song, S. Sosio, S. Spataro, F. Stieler, S. S Su, Y. J. Su, G. B. Sun, G. X. Sun, H. Sun, H. K. Sun, J. F. Sun, K. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, Y. Sun, Y. J. Sun, Y. Z. Sun, Z. Q. Sun, Z. T. Sun, C. J. Tang, G. Y. Tang, J. Tang, M. Tang, Y. A. Tang, L. Y. Tao, Q. T. Tao, M. Tat, J. X. Teng, V. Thoren, W. H. Tian, Y. Tian, Z. F. Tian, I. Uman, Y. Wan, S. J. Wang, B. Wang, B. L. Wang, Bo Wang, D. Y. Wang, F. Wang, H. J. Wang, J. J. Wang, J. P. Wang, K. Wang, L. L. Wang, M. Wang, N. Y. Wang, S. Wang, T. Wang, T. J. Wang, W. Wang, W. P. Wang, X. Wang, X. F. Wang, X. J. Wang, X. L. Wang, X. N. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. H. Wang, Y. L. Wang, Y. N. Wang, Y. Q. Wang, Yaqian Wang, Yi Wang, Z. Wang, Z. L. Wang, Z. Y. Wang, Ziyi Wang, D. H. Wei, F. Weidner, S. P. Wen, Y. R. Wen, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, C. Wu, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, X. H. Wu, Y. Wu, Y. H. Wu, Y. J. Wu, Z. Wu, L. Xia, X. M. Xian, B. H. Xiang, T. Xiang, D. Xiao, G. Y. Xiao, S. Y. Xiao, Y. L. Xiao, Z. J. Xiao, C. Xie, X. H. Xie, Y. Xie, Y. G. Xie, Y. H. Xie, Z. P. Xie, T. Y. Xing, C. F. Xu, C. J. Xu, G. F. Xu, H. Y. Xu, M. Xu, Q. J. Xu, Q. N. Xu, W. Xu, W. L. Xu, X. P. Xu, Y. Xu, Y. C. Xu, Z. S. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, X. Q. Yan, H. J. Yang, H. L. Yang, H. X. Yang, J. H. Yang, T. Yang, Y. Yang, Y. F. Yang, Y. X. Yang, Z. W. Yang, Z. P. Yao, M. Ye, M. H. Ye, J. H. Yin, Junhao Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, M. C. Yu, T. Yu, X. D. Yu, Y. C. Yu, C. Z. Yuan, J. Yuan, L. Yuan, S. C. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. A. Zafar, F. R. Zeng, S. H. Zeng, X. Zeng, Y. Zeng, Y. J. Zeng, X. Y. Zhai, Y. C. Zhai, Y. H. Zhan, A. Q. Zhang, B. L. Zhang, B. X. Zhang, D. H. Zhang, G. Y. Zhang, H. Zhang, H. C. Zhang, H. H. Zhang, H. Q. Zhang, H. R. Zhang, H. Y. Zhang, J. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. S. Zhang, J. W. Zhang, J. X. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, L. M. Zhang, Lei Zhang, P. Zhang, Q. Y. Zhang, R. Y. Zhang, S. H. Zhang, Shulei Zhang, X. D. Zhang, X. M. Zhang, X. Y Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Y. M. Zhang, Yan Zhang, Z. D. Zhang, Z. H. Zhang, Z. L. Zhang, Z. Y. Zhang, Z. Z. Zhang, G. Zhao, J. Y. Zhao, J. Z. Zhao, L. Zhao, Lei Zhao, M. G. Zhao, N. Zhao, R. P. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, B. M. Zheng, J. P. Zheng, W. J. Zheng, Y. H. Zheng, B. Zhong, X. Zhong, H. Zhou, J. Y. Zhou, L. P. Zhou, S. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, Y. Z. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, K. S. Zhu, L. Zhu, L. X. Zhu, S. H. Zhu, T. J. Zhu, W. D. Zhu, Y. C. Zhu, Z. A. Zhu, J. H. Zou, and J. Zu
Subjects: Branching fraction, e +-e − Experiments, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract The processes h c → γP (P = η′, η, π 0) are studied with a sample of (27.12 ± 0.14) × 108 ψ(3686) events collected by the BESIII detector at the BEPCII collider. The decay h c → γη is observed for the first time with the significance of 9.0 σ, and the branching fraction is determined to be (3.77 ± 0.55 ± 0.13 ± 0.26) × 10 −4, while B $$ \mathcal{B} $$ (h c → γη′) is measured to be (1.40 ± 0.11 ± 0.04 ± 0.10) × 10 −3, where the first uncertainties are statistical, the second systematic, and the third from the branching fraction of ψ(3686) → π 0 h c . The combination of these results allows for a precise determination of R h c = B h c → γη B h c → γ η ′ , $$ {R}_{h_c}=\frac{\mathcal{B}\left({h}_c\to {\pi}^0\gamma \eta \right)}{\mathcal{B}\left({h}_c\to {\pi}^0\gamma {\eta}^{\prime}\right)}, $$ which is calculated to be (27.0 ± 4.4 ± 1.0)%. The results are valuable for gaining a deeper understanding of η − η′ mixing, and its manifestation within quantum chromodynamics. No significant signal is found for the decay h c → γπ 0, and an upper limit is placed on its branching fraction of B $$ \mathcal{B} $$ (h c → γπ 0) < 5.0 × 10 −5, at the 90% confidence level.
Published: 2024
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5. Potential influence of climate-induced vegetation shifts on future land use and associated land carbon fluxes in Northern Eurasia

Author: D W Kicklighter, Y Cai, Q Zhuang, E I Parfenova, S Paltsev, A P Sokolov, J M Melillo, J M Reilly, N M Tchebakova, and X Lu
Subjects: climate-change effects, climate policy, economic feedbacks, land-cover change, land-use change, carbon sequestration, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350, Science, Physics, QC1-999
Abstract: Climate change will alter ecosystem metabolism and may lead to a redistribution of vegetation and changes in fire regimes in Northern Eurasia over the 21st century. Land management decisions will interact with these climate-driven changes to reshape the region’s landscape. Here we present an assessment of the potential consequences of climate change on land use and associated land carbon sink activity for Northern Eurasia in the context of climate-induced vegetation shifts. Under a ‘business-as-usual’ scenario, climate-induced vegetation shifts allow expansion of areas devoted to food crop production (15%) and pastures (39%) over the 21st century. Under a climate stabilization scenario, climate-induced vegetation shifts permit expansion of areas devoted to cellulosic biofuel production (25%) and pastures (21%), but reduce the expansion of areas devoted to food crop production by 10%. In both climate scenarios, vegetation shifts further reduce the areas devoted to timber production by 6–8% over this same time period. Fire associated with climate-induced vegetation shifts causes the region to become more of a carbon source than if no vegetation shifts occur. Consideration of the interactions between climate-induced vegetation shifts and human activities through a modeling framework has provided clues to how humans may be able to adapt to a changing world and identified the trade-offs, including unintended consequences, associated with proposed climate/energy policies.
Published: 2014
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6. DL Based Forest Height Reconstruction Using Single-Pol Tomosar Images.

Author: Wenyu Yang, Hossein Aghababaei, Giampaolo Ferraioli, X. Lu, Vito Pascazio, Sergio Vitale, and Gilda Schirinzi
Published: 2023
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7. Influence of pass spacing on the spinning process of nickel-based alloy conical casing

Author: L. Ding, X. S. Gao, X. X. Lu, B. S. Sun, and X. D. Shu
Subjects: nickel-based alloys, wheel track, FEM, stress-strain, pass spacing, Mining engineering. Metallurgy, TN1-997
Abstract: High temperature nickel-based alloys are prone to forming defects due to serious work hardening, and the pass spacing is an important parameter in multi-pass drawing and spinning. Using GH4169 superalloy as the material, a Finite Element Model (FEM) was established based on the Simufact platform, and the influence of the pass spacing on the spinning process was explored by using the concave curve and circular arc trajectory. The results show that the stress-strain increases with the increase of the pass spacing. Obtain the optimal pass spacing under specific conditions: blank wall thickness t = 2,5 mm, blank diameter d = 250 mm, feed ratio f = 1,2 mm/rad, mandrel speed n = 300 r/min, pass spacing p = 14 mm.
Published: 2023

8. ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition.

Author: Aashaka Desai, Lauren Berger, Fyodor Minakov, Nessa Milano, Chinmay Singh, Kriston Pumphrey, Richard E. Ladner, Hal Daumé III, Alex X. Lu, Naomi Caselli, and Danielle Bragg
Published: 2023

9. Amplitude analysis and branching fraction measurement of the decay D s + $$ {\textrm{D}}_{\textrm{s}}^{+} $$ → K+ π + π − π 0

Author: The BESIII collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, V. Batozskaya, D. Becker, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, A. Brueggemann, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, C. Chen, Chao Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, S. M. Chen, T. Chen, X. R. Chen, X. T. Chen, Y. B. Chen, Z. J. Chen, W. S. Cheng, X. Chu, G. Cibinetto, F. Cossio, J. J. Cui, H. L. Dai, J. P. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, P. Egorov, Y. L. Fan, J. Fang, S. S. Fang, W. X. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, K. Fischer, M. Fritsch, C. Fritzsch, C. D. Fu, H. Gao, Y. N. Gao, Yang Gao, S. Garbolino, I. Garzia, P. T. Ge, Z. W. Ge, C. Geng, E. M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, W. Y. Han, X. Q. Hao, F. A. Harris, K. K. He, K. L. He, F. H. Heinsius, C. H. Heinz, Y. K. Heng, C. Herold, M. Himmelreich, G. Y. Hou, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, K. X. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, T. Hussain, N. Hüsken, W. Imoehl, M. Irshad, J. Jackson, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, Z. K. Jia, H. B. Jiang, S. S. Jiang, X. S. Jiang, Y. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, H. N. Li, J. Q. Li, J. S. Li, J. W. Li, Ke Li, L. J Li, L. K. Li, Lei Li, M. H. Li, P. R. Li, S. X. Li, S. Y. Li, T. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Xiaoyu Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, A. Limphirat, D. X. Lin, T. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, G. M. Liu, H. Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. L. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, Lu Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, T. Liu, W. K. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, Z. H. Lu, C. L. Luo, M. X. Luo, T. Luo, X. L. Luo, X. R. Lyu, Y. F. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. Y. Ma, Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, H. Miao, T. J. Min, R. E. Mitchell, X. H. Mo, N. Yu. Muchnoi, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, Y. Niu, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, M. Pelizaeus, H. P. Peng, K. Peters, J. L. Ping, R. G. Ping, S. Plura, S. Pogodin, V. Prasad, F. Z. Qi, H. Qi, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, J. J. Qin, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, C. F. Redmer, K. J. Ren, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, S. N. Ruan, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, K. Y. Shan, W. Shan, X. Y. Shan, J. F. Shangguan, L. G. Shao, M. Shao, C. P. Shen, H. F. Shen, X. Y. Shen, B. A. Shi, H. C. Shi, J. Y. Shi, Q. Q. Shi, R. S. Shi, X. Shi, X. D. Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, F. Stieler, K. X. Su, P. P. Su, Y. J. Su, G. X. Sun, H. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, X. Sun, Y. J. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, L. Y Tao, Q. T. Tao, J. X. Teng, V. Thoren, W. H. Tian, Y. Tian, I. Uman, B. Wang, B. L. Wang, C. W. Wang, D. Y. Wang, F. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, Meng Wang, S. Wang, T. Wang, T. J. Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. H. Wang, Y. Q. Wang, Yaqian Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, D. H. Wei, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, X. H. Wu, Y. Wu, Y. J Wu, Z. Wu, L. Xia, T. Xiang, D. Xiao, G. Y. Xiao, H. Xiao, S. Y. Xiao, Y. L. Xiao, Z. J. Xiao, C. Xie, X. H. Xie, Y. Xie, Y. G. Xie, Y. H. Xie, Z. P. Xie, T. Y. Xing, C. F. Xu, C. J. Xu, G. F. Xu, H. Y. Xu, Q. J. Xu, X. P. Xu, Y. C. Xu, Z. P. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, H. J. Yang, H. L. Yang, H. X. Yang, L. Yang, S. L. Yang, Tao Yang, Y. F. Yang, Y. X. Yang, Yifan Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, T. Yu, C. Z. Yuan, L. Yuan, S. C. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. A. Zafar, F. R. Zeng, X. Zeng, Y. Zeng, Y. H. Zhan, A. Q. Zhang, B. L. Zhang, B. X. Zhang, D. H. Zhang, G. Y. Zhang, H. Zhang, H. H. Zhang, H. Y. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. X. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. M. Zhang, L. Q. Zhang, Lei Zhang, P. Zhang, Q. Y. Zhang, Shuihan Zhang, Shulei Zhang, X. D. Zhang, X. M. Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Yan Zhang, Yao Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, X. Zhong, H. Zhou, L. P. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, Y. Z. Zhou, J. Zhu, K. Zhu, K. J. Zhu, L. X. Zhu, S. H. Zhu, S. Q. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, and J. H. Zou
Subjects: Charm Physics, e +-e − Experiments, Particle and Resonance Production, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract The singly Cabibbo-suppressed decay D s + $$ {D}_s^{+} $$ → K + π + π − π 0 is observed by using a data set corresponding to an integrated luminosity of 6.32 fb −1 recorded by the BESIII detector at the centre-of-mass energies between 4.178 and 4.226 GeV. The first amplitude analysis of D s + $$ {D}_s^{+} $$ → K + π + π − π 0 reveals the sub-structures in this decay and determines the fractions and relative phases of different intermediate processes. The dominant intermediate process is D s + $$ {D}_s^{+} $$ → K *0 ρ +, with a fit fraction of (40.5 ± 2.8stat. ± 1.5syst. )%. With the detection efficiency based on our amplitude analysis, the absolute branching fraction for D s + $$ {D}_s^{+} $$ → K + π + π − π 0 is measured to be (9.75 ± 0.54stat. ± 0.17syst. ) × 10 −3.
Published: 2022
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10. Satellite quantification of oil and natural gas methane emissions in the US and Canada including contributions from individual basins

Author: L. Shen, R. Gautam, M. Omara, D. Zavala-Araiza, J. D. Maasakkers, T. R. Scarpelli, A. Lorente, D. Lyon, J. Sheng, D. J. Varon, H. Nesser, Z. Qu, X. Lu, M. P. Sulprizio, S. P. Hamburg, and D. J. Jacob
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: We use satellite methane observations from the Tropospheric Monitoring Instrument (TROPOMI), for May 2018 to February 2020, to quantify methane emissions from individual oil and natural gas (O/G) basins in the US and Canada using a high-resolution (∼25 km) atmospheric inverse analysis. Our satellite-derived emission estimates show good consistency with in situ field measurements (R=0.96) in 14 O/G basins distributed across the US and Canada. Aggregating our results to the national scale, we obtain O/G-related methane emission estimates of 12.6±2.1 Tg a−1 for the US and 2.2±0.6 Tg a−1 for Canada, 80 % and 40 %, respectively, higher than the national inventories reported to the United Nations. About 70 % of the discrepancy in the US Environmental Protection Agency (EPA) inventory can be attributed to five O/G basins, the Permian, Haynesville, Anadarko, Eagle Ford, and Barnett basins, which in total account for 40 % of US emissions. We show more generally that our TROPOMI inversion framework can quantify methane emissions exceeding 0.2–0.5 Tg a−1 from individual O/G basins, thus providing an effective tool for monitoring methane emissions from large O/G basins globally.
Published: 2022
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11. Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations

Author: Z. Chen, D. J. Jacob, H. Nesser, M. P. Sulprizio, A. Lorente, D. J. Varon, X. Lu, L. Shen, Z. Qu, E. Penn, and X. Yu
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: We quantify methane emissions in China and the contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. The inversion uses as a prior estimate the latest 2014 national sector-resolved anthropogenic emission inventory reported by the Chinese government to the United Nations Framework Convention on Climate Change (UNFCCC) and thus serves as a direct evaluation of that inventory. Emissions are optimized with a Gaussian mixture model (GMM) at up to 0.25∘×0.3125∘ resolution. The optimization is done analytically assuming log-normally distributed errors on prior emissions. Errors and information content on the optimized estimates are obtained directly from the analytical solution and also through a 36-member inversion ensemble. Our best estimate for total anthropogenic emissions in China is 65.0 (57.7–68.4) Tg a−1, where parentheses indicate the uncertainty range determined by the inversion ensemble. Contributions from individual sectors include 16.6 (15.6–17.6) Tg a−1 for coal, 2.3 (1.8–2.5) for oil, 0.29 (0.23–0.32) for gas, 17.8 (15.1–21.0) for livestock, 9.3 (8.2–9.9) for waste, 11.9 (10.7–12.7) for rice paddies, and 6.7 (5.8–7.1) for other sources. Our estimate is 21% higher than the Chinese inventory reported to the UNFCCC (53.6 Tg a−1), reflecting upward corrections to emissions from oil (+147 %), gas (+61 %), livestock (+37 %), waste (+41 %), and rice paddies (+34 %), but downward correction for coal (−15 %). It is also higher than previous inverse studies (43–62 Tg a−1) that used the much sparser GOSAT satellite observations and were conducted at coarser resolution. We are in particular better able to separate coal and rice emissions. Our higher livestock emissions are attributed largely to northern China where GOSAT has little sensitivity. Our higher waste emissions reflect at least in part a rapid growth in wastewater treatment in China. Underestimate of oil emissions in the UNFCCC report appears to reflect unaccounted-for super-emitting facilities. Gas emissions in China are mostly from distribution, in part because of low emission factors from production and in part because 42 % of the gas is imported. Our estimate of emissions per unit of domestic gas production indicates a low life-cycle loss rate of 1.7 % (1.3 %–1.9 %), which would imply net climate benefits from the current “coal-to-gas” energy transition in China. However, this small loss rate is somewhat misleading considering China's high gas imports, including from Turkmenistan where emission per unit of gas production is very high.
Published: 2022
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12. Amplitude analysis and branching fraction measurement of the decay D s + $$ {D}_s^{+} $$ → K + π + π −

Author: The BESIII collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, V. Batozskaya, D. Becker, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, A. Brueggemann, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, C. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, T. Chen, X. R. Chen, X. T. Chen, Y. B. Chen, Z. J. Chen, W. S. Cheng, G. Cibinetto, F. Cossio, J. J. Cui, H. L. Dai, J. P. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, P. Egorov, Y. L. Fan, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, K Fischer, M. Fritsch, C. Fritzsch, C. D. Fu, H. Gao, Y. N. Gao, Yang Gao, S. Garbolino, I. Garzia, P. T. Ge, Z. W. Ge, C. Geng, E. M. Gersabeck, A Gilman, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, W. Y. Han, X. Q. Hao, F. A. Harris, K. K. He, K. L. He, F. H. Heinsius, C. H. Heinz, Y. K. Heng, C. Herold, T. Holtmann, G. Y. Hou, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, K. X. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, N Hüsken, W. Imoehl, M. Irshad, J. Jackson, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, Z. K. Jia, H. B. Jiang, S. S. Jiang, X. S. Jiang, Y. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, H. N. Li, J. Q. Li, J. S. Li, J. W. Li, Ke Li, L. J Li, L. K. Li, Lei Li, M. H. Li, P. R. Li, S. X. Li, S. Y. Li, T. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Xiaoyu Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, A. Limphirat, C. X. Lin, D. X. Lin, T. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, G. M. Liu, H. Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. L. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, T. Liu, W. K. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, Z. H. Lu, C. L. Luo, M. X. Luo, T. Luo, X. L. Luo, X. R. Lyu, Y. F. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. Y. Ma, Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, H. Miao, T. J. Min, R. E. Mitchell, X. H. Mo, N. Yu. Muchnoi, H. Muramatsu, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, Y. Niu, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, M. Pelizaeus, H. P. Peng, J. Pettersson, J. L. Ping, R. G. Ping, S. Plura, S. Pogodin, R. Poling, V. Prasad, H. Qi, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, J. J. Qin, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, C. F. Redmer, K. J. Ren, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, S. N. Ruan, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, K. Y. Shan, W. Shan, X. Y. Shan, J. F. Shangguan, L. G. Shao, M. Shao, C. P. Shen, H. F. Shen, X. Y. Shen, B.-A. Shi, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, F. Stieler, K. X. Su, P. P. Su, Y.-J. Su, G. X. Sun, H. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, X Sun, Y. J. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, L. Y Tao, Q. T. Tao, J. X. Teng, V. Thoren, W. H. Tian, Y. Tian, I. Uman, B. Wang, B. L. Wang, C. W. Wang, D. Y. Wang, F. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, S. Wang, T. Wang, T. J. Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. D. Wang, Y. F. Wang, Y. H. Wang, Y. Q. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, D. H. Wei, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, X. H. Wu, Y. Wu, Z. Wu, L. Xia, T. Xiang, D. Xiao, G. Y. Xiao, H. Xiao, S. Y. Xiao, Y. L. Xiao, Z. J. Xiao, C. Xie, X. H. Xie, Y. Xie, Y. G. Xie, Y. H. Xie, Z. P. Xie, T. Y. Xing, C. F. Xu, C. J. Xu, G. F. Xu, H. Y. Xu, Q. J. Xu, S. Y. Xu, X. P. Xu, Y. C. Xu, Z. P. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, H. J. Yang, H. L. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. X. Yang, Yifan Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, T. Yu, C. Z. Yuan, L. Yuan, S. C. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. A. Zafar, F. R. Zeng, X. Zeng, Y. Zeng, Y. H. Zhan, A. Q. Zhang, B. L. Zhang, B. X. Zhang, G. Y. Zhang, H. Zhang, H. H. Zhang, H. Y. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. X. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. M. Zhang, L. Q. Zhang, Lei Zhang, P. Zhang, Q. Y. Zhang, Shulei Zhang, X. D. Zhang, X. M. Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Yan Zhang, Yao Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, X. Zhong, H. Zhou, L. P. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, Y. Z. Zhou, J. Zhu, K. Zhu, K. J. Zhu, L. X. Zhu, S. H. Zhu, S. Q. Zhu, T. J. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, and J. H. Zou
Subjects: Branching fraction, Charm Physics, e +-e − Experiments, Particle and Resonance Production, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract Using 6.32 fb −1 of e + e − collision data collected at the center-of-mass energies between 4.178 and 4.226 GeV with the BESIII detector, we perform an amplitude analysis of the decay D s + $$ {D}_s^{+} $$ → K + π + π − and determine the amplitudes of the various intermediate states. The absolute branching fraction of D s + $$ {D}_s^{+} $$ → K + π + π − is measured to be (6.11 ± 0.18stat. ± 0.11syst. ) × 10 −3. The branching fractions of the dominant intermediate processes D s + $$ {D}_s^{+} $$ → K + ρ 0 , ρ 0 → π + π − and D s + $$ {D}_s^{+} $$ → K *(892)0 π + , K *(892)0 → K + π − are determined to be (1.96 ± 0.19stat. ± 0.23syst. ) × 10 −3 and (1.85 ± 0.12stat. ± 0.13syst. ) × 10 −3, respectively. The intermediate resonances f 0(500), f 0(980), and f 0(1370) are observed for the first time in this channel.
Published: 2022
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13. Measurement of e+e − → K+K − π 0 cross section and observation of a resonant structure

Author: The BESIII collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, V. Batozskaya, D. Becker, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, C. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, T. Chen, X. R. Chen, X. T. Chen, Y. B. Chen, Z. J. Chen, W. S. Cheng, G. Cibinetto, F. Cossio, J. J. Cui, X. F. Cui, H. L. Dai, J. P. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, P. Egorov, Y. L. Fan, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, M. Fritsch, C. D. Fu, Y. Gao, I. Garzia, P. T. Ge, C. Geng, E. M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, M. H. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, W. Y. Han, X. Q. Hao, F. A. Harris, K. K. He, K. L. He, F. H. Heinsius, C. H. Heinz, Y. K. Heng, C. Herold, M. Himmelreich, T. Holtmann, G. Y. Hou, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, N. Hüsken, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, H. B. Jiang, S. S. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, H. N. Li, J. L. Li, J. Q. Li, J. S. Li, Ke Li, L. J Li, L. K. Li, Lei Li, M. H. Li, P. R. Li, S. Y. Li, T. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Xiaoyu Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, A. Limphirat, C. X. Lin, D. X. Lin, T. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, G. M. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. L. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, T. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, Z. H. Lu, C. L. Luo, M. X. Luo, T. Luo, X. L. Luo, X. R. Lyu, Y. F. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. X. Ma, X. Y. Ma, Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, H. Miao, T. J. Min, R. E. Mitchell, X. H. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, S. Plura, S. Pogodin, R. Poling, V. Prasad, H. Qi, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, J. J. Qin, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, K. J. Ren, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, W. Shan, X. Y. Shan, J. F. Shangguan, L. G. Shao, M. Shao, C. P. Shen, H. F. Shen, X. Y. Shen, B.-A. Shi, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, F. Stieler, K. X. Su, P. P. Su, Y.-J. Su, G. X. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, X. Sun, Y. J. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, L. Y Tao, Q. T. Tao, J. X. Teng, V. Thoren, W. H. Tian, Y. T. Tian, I. Uman, B. Wang, D. Y. Wang, F. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, S. Wang, T. J. Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Y. Y. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, X. H. Wu, Z. Wu, L. Xia, T. Xiang, H. Xiao, S. Y. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, C. F. Xu, C. J. Xu, G. F. Xu, Q. J. Xu, W. Xu, X. P. Xu, Y. C. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, H. J. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, L. Yuan, S. C. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. A. Zafar, X. Zeng, Y. Zeng, A. Q. Zhang, B. L. Zhang, B. X. Zhang, G. Y. Zhang, H. Zhang, H. H. Zhang, H. Y. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. M. Zhang, L. Q. Zhang, Lei Zhang, P. Zhang, Shulei Zhang, X. D. Zhang, X. M. Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Yan Zhang, Yao Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, T. J. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, and J. H. Zou
Subjects: e +-e − Experiments, Particle and Resonance Production, Spectroscopy, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract Based on e + e − collision data collected by the BESIII detector at the BEPCII collider at center-of-mass energies from 2.000 to 3.080 GeV, a partial-wave analysis is performed for the process e + e − → K + K − π 0. The Born cross section of the process e + e − → K + K − π 0 and its subprocesses e + e − → ϕπ 0, K *+(892)K − and K 2 ∗ + $$ {K}_2^{\ast +} $$ (1430)K − are measured. The results for e + e − → K + K − π 0 and ϕπ 0 are consistent with the BaBar measurements and with improved precision. By analyzing the cross sections of the subprocesses e + e − → K *+(892)K − and K 2 ∗ + $$ {K}_2^{\ast +} $$ (1430)K − , a structure with mass M R = (2190 ± 19 ± 37) MeV/c 2 and width Γ R = (191 ± 28 ± 60) MeV is observed with a combined statistical significance of 7.1σ. The measured resonance parameters suggest it can be identified as the ϕ(2170), thus the results provide valuable input to understand the internal nature of this state.
Published: 2022
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14. Cross section measurements of the processes e + e − → ωπ 0 and ωη at center-of-mass energies between 3.773 and 4.701 GeV

Author: The BESIII collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, V. Batozskaya, D. Becker, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, C. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, T. Chen, X. R. Chen, X. T. Chen, Y. B. Chen, Z. J. Chen, W. S. Cheng, G. Cibinetto, F. Cossio, J. J. Cui, X. F. Cui, H. L. Dai, J. P. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, P. Egorov, Y. L. Fan, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, M. Fritsch, C. D. Fu, Y. N. Gao, Yang Gao, I. Garzia, P. T. Ge, C. Geng, E. M. Gersabeck, A Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, M. H. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, W. Y. Han, X. Q. Hao, F. A. Harris, K. K. He, K. L. He, F. H. Heinsius, C. H. Heinz, Y. K. Heng, C. Herold, M. Himmelreich, T. Holtmann, G. Y. Hou, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, N Hüsken, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, H. B. Jiang, S. S. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, H. N. Li, J. L. Li, J. Q. Li, J. S. Li, Ke Li, L. J Li, L. K. Li, Lei Li, M. H. Li, P. R. Li, S. X. Li, S. Y. Li, T. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Xiaoyu Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, A. Limphirat, C. X. Lin, D. X. Lin, T. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, G. M. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. L. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, T. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, Z. H. Lu, C. L. Luo, M. X. Luo, T. Luo, X. L. Luo, X. R. Lyu, Y. F. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. X. Ma, X. Y. Ma, Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, H. Miao, T. J. Min, R. E. Mitchell, X. H. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, S. Plura, S. Pogodin, R. Poling, V. Prasad, H. Qi, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, J. J. Qin, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, K. J. Ren, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, K. Y. Shan, W. Shan, X. Y. Shan, J. F. Shangguan, L. G. Shao, M. Shao, C. P. Shen, H. F. Shen, X. Y. Shen, B.-A. Shi, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, F. Stieler, K. X. Su, P. P. Su, Y.-J. Su, G. X. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, X Sun, Y. J. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, L. Y Tao, Q. T. Tao, J. X. Teng, V. Thoren, W. H. Tian, Y. T. Tian, I. Uman, B. Wang, D. Y. Wang, F. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, S. Wang, T. J. Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Y. Y. Wang, Ying Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, X. H. Wu, Z. Wu, L. Xia, T. Xiang, H. Xiao, S. Y. Xiao, Y. L. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, C. F. Xu, C. J. Xu, G. F. Xu, Q. J. Xu, S. Y. Xu, W. Xu, X. P. Xu, Y. C. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, H. J. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, L. Yuan, S. C. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. A. Zafar, X. Zeng, Y. Zeng, A. Q. Zhang, B. L. Zhang, B. X. Zhang, G. Y. Zhang, H. Zhang, H. H. Zhang, H. Y. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. M. Zhang, L. Q. Zhang, Lei Zhang, P. Zhang, Shulei Zhang, X. D. Zhang, X. M. Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Yan Zhang, Yao Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, Y. Z. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, T. J. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, and J. H. Zou
Subjects: e +-e − Experiments, Exotics, Particle and Resonance Production, Quarkonium, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract The Born cross sections of the processes e + e − → ωπ 0 and e + e − → ωη are measured at center-of-mass energies between 3.773 and 4.701 GeV using a total integrated luminosity of 22.7 fb −1 collected with the BESIII detector operating at the BEPCII collider. A simple s −n dependence for the continuum process can describe the measured Born cross sections. No significant contributions from the ψ(4160), Y(4230), Y(4360), ψ(4415), Y(4660) resonances are found, which indicates relative small branching fractions for these resonances into the ωπ 0 and ωη final states.
Published: 2022
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15. Amplitude analysis and branching fraction measurement of D s + $$ {D}_s^{+} $$ → K − K + π + π + π −

Author: The BESIII collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, Z. J Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, Y. L. Fan, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, M. Fritsch, C. D. Fu, Y. Gao, Y. G. Gao, I. Garzia, P. T. Ge, C. Geng, E. M. Gersabeck, A Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, W. Y. Han, X. Q. Hao, F. A. Harris, K. L. He, F. H. Heinsius, C. H. Heinz, T. Held, Y. K. Heng, C. Herold, M. Himmelreich, T. Holtmann, G. Y. Hou, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, N Hüsken, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, H. B. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, J. S. Li, Ke Li, L. K. Li, Lei Li, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Xiaoyu Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, C. X. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. L. Liu, J. Y. Liu, K. Liu, K. Y. Liu, L. Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, Shuai Liu, T. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. X. Ma, X. Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, R. Poling, V. Prasad, H. Qi, H. R. Qi, K. H. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, D. C. Shan, W. Shan, X. Y. Shan, J. F. Shangguan, M. Shao, C. P. Shen, H. F. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, K. X. Su, P. P. Su, F. F. Sui, G. X. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, X Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, J. X. Teng, V. Thoren, W. H. Tian, Y. T. Tian, I. Uman, B. Wang, C. W. Wang, D. Y. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Y. Y. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, G. F. Xu, Q. J. Xu, W. Xu, X. P. Xu, Y. C. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, L. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. A. Zafar, X. Zeng, Y. Zeng, A. Q. Zhang, B. X. Zhang, Guangyi Zhang, H. Zhang, H. H. Zhang, H. Y. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. M. Zhang, L. Q. Zhang, Lei Zhang, S. Zhang, S. F. Zhang, Shulei Zhang, X. D. Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Yan Zhang, Yao Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, T. J. Zhu, W. J. Zhu, X. Y. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, and J. H. Zou
Subjects: Branching fraction, Charm Physics, e +-e − Experiments, Particle and Resonance Production, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract Using e + e − annihilation data corresponding to a total integrated luminosity of 6.32 fb −1 collected at the center-of-mass energies between 4.178 and 4.226 GeV with the BESIII detector, we perform an amplitude analysis of the decay D s + $$ {D}_s^{+} $$ → K − K + π + π + π − and determine the relative fractions and phases of different intermediate processes. Absolute branching fraction of D s + $$ {D}_s^{+} $$ → K − K + π + π + π − decay is measured to be (6.60 ± 0.47stat. ± 0.38syst. ) × 10 −3. The dominant intermediate process is D s + $$ {D}_s^{+} $$ → a 1(1260)+ ϕ, ϕ → K − K + , a 1(1260)+ → ρπ + , ρ → π + π − , with a branching fraction of (5.15 ± 0.41stat. ± 0.32syst. ) × 10 −3.
Published: 2022
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16. APPLICATION OF A SHELLNET BASED APPROACH TO SEMANTIC SEGMENTATION IN URBAN POINT CLOUD

Author: D. Chen, X. Ma, X. Lu, and J. Xiao
Subjects: Technology, Engineering (General). Civil engineering (General), TA1-2040, Applied optics. Photonics, TA1501-1820
Abstract: In recent years, the popularity of airborne, vehicle-borne, and terrestrial 3D laser scanners has driven the rapid development of 3D point cloud processing methods. The 3D laser scanning technology has the characteristics of non-contact, high density, high accuracy, and digitalization, which can achieve comprehensive and fast 3D scanning of urban point clouds. To address the current situation that it is difficult to accurately segment urban point clouds in complex scenes from 3D laser scanned point clouds, a technical process for accurate and fast semantic segmentation of urban point clouds is proposed. In this study, the point clouds are first denoised, then the samples are annotated and sample sets are created based on the point cloud features of the category targets using CloudCompare software, followed by an end-to-end trainable optimization network-ShellNet, to train the urban point cloud samples, and finally, the models are evaluated on a test set. The method achieved IoU metrics of 89.83% and 73.74% for semantic segmentation of buildings and rods-like objects respectively. From the visualization results of the test set, the algorithm is feasible and robust, providing a new idea and method for semantic segmentation of large-scale urban scenes.
Published: 2022
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17. Search for new hadronic decays of h c and observation of h c → p p ¯ η $$ p\overline{p}\eta $$

Author: The BESIII collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, Z. J. Chen, W. S. Cheng, G. Cibinetto, F. Cossio, J. J. Cui, X. F. Cui, H. L. Dai, J. P. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, P. Egorov, Y. L. Fan, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, M. Fritsch, C. D. Fu, Y. Gao, I. Garzia, P. T. Ge, C. Geng, E. M. Gersabeck, A Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, W. Y. Han, X. Q. Hao, F. A. Harris, K. K. He, K. L. He, F. H. Heinsius, C. H. Heinz, Y. K. Heng, C. Herold, M. Himmelreich, T. Holtmann, G. Y. Hou, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, N Hüsken, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, H. B. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, H. N. Li, J. L. Li, J. Q. Li, J. S. Li, Ke Li, L. K. Li, Lei Li, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Xiaoyu Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, A. Limphirat, C. X. Lin, D. X. Lin, T. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, G. M. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. L. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, T. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. X. Ma, X. Y. Ma, Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, S. Plura, S. Pogodin, R. Poling, V. Prasad, H. Qi, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, J. J. Qin, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, W. Shan, X. Y. Shan, J. F. Shangguan, M. Shao, C. P. Shen, H. F. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, F. Stieler, K. X. Su, P. P. Su, G. X. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, X Sun, Y. J. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, Q. T. Tao, J. X. Teng, V. Thoren, W. H. Tian, Y. T. Tian, I. Uman, B. Wang, C. W. Wang, D. Y. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, S. Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Y. Y. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, X. H. Wu, Z. Wu, L. Xia, T. Xiang, H. Xiao, S. Y. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, C. J. Xu, G. F. Xu, Q. J. Xu, W. Xu, X. P. Xu, Y. C. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, H. J. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, L. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. A. Zafar, X. Zeng Zeng, Y. Zeng, A. Q. Zhang, B. X. Zhang, G. Y. Zhang, H. Zhang, H. H. Zhang, H. Y. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. M. Zhang, L. Q. Zhang, Lei Zhang, S. Zhang, S. F. Zhang, Shulei Zhang, X. D. Zhang, X. M. Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Yan Zhang, Yao Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, L. Zhu, S. H. Zhu, T. J. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, and J. H. Zou
Subjects: Branching fraction, e +-e − Experiments, Particle and Resonance Production, Quarkonium, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract A search for the hadronic decays of the h c meson to the final states p p ¯ $$ p\overline{p} $$ π + π − π 0, p p ¯ η $$ p\overline{p}\eta $$ , and p p ¯ $$ p\overline{p} $$ π 0 via the process ψ(3686) → π 0 h c is performed using (4.48 ± 0.03) × 108 ψ(3686) events collected with the BESIII detector. The decay channel h c → p p ¯ η $$ p\overline{p}\eta $$ is observed for the first time with a significance greater than 5σ and a branching fraction of (6.41 ± 1.74 ± 0.53 ± 1.00) × 10 −4, where the uncertainties are statistical, systematic, and that from the branching fraction of ψ(3686) → π 0 h c . Strong evidence for the decay h c → p p ¯ $$ p\overline{p} $$ π + π − π 0 is found with a significance of 4.9σ and a branching fraction of (3.84 ± 0.83 ± 0.69 ± 0.58) × 10 −3. The significances include systematic uncertainties. No clear signal of the decay h c → p p ¯ $$ p\overline{p} $$ π 0 is found, and an upper limit of 6.59 × 10 −4 on its branching fraction is set at the 90% confidence level.
Published: 2022
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18. Amplitude analysis and branching-fraction measurement of D s + $$ {\mathrm{D}}_{\mathrm{s}}^{+} $$ → π + π 0 η′

Author: The BESIII collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. B. Ferroli, I. Balossino, Y. Ban, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, Z. J. Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, Y. L. Fan, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, M. Fritsch, C. D. Fu, Y. Gao, Y. G. Gao, I. Garzia, P. T. Ge, C. Geng, E. M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y. Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, W. Y. Han, X. Q. Hao, F. A. Harris, K. L. He, F. H. Heinsius, C. H. Heinz, T. Held, Y. K. Heng, C. Herold, M. Himmelreich, T. Holtmann, G. Y. Hou, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, N. Hüsken, W. I. Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, H. B. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, J. S. Li, K. Li, L. K. Li, L. Li, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, X. Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, C. X. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, F. Liu, H. B. Liu, H. M. Liu, H. Liu, J. B. Liu, J. L. Liu, J. Y. Liu, K. Liu, K. Y. Liu, L. Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, S. Liu, T. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. X. Ma, X. Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Y. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, R. Poling, V. Prasad, H. Qi, H. R. Qi, K. H. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, C. Rosner, M. Rump, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, D. C. Shan, W. Shan, X. Y. Shan, J. F. Shangguan, M. Shao, C. P. Shen, H. F. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D. Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, K. X. Su, P. P. Su, F. F. Sui, G. X. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, X. Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, J. X. Teng, V. Thoren, W. H. Tian, Y. T. Tian, I. Uman, B. Wang, C. W. Wang, D. Y. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Y. Y. Wang, Z. Wang, Z. Y. Wang, D. H. Wei, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, G. F. Xu, Q. J. Xu, W. Xu, X. P. Xu, Y. C. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, X. Yan, H. J. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. X. Yang, Y. Yang, Z. Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, L. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. A. Zafar, X. Z. Zeng, Y. Zeng, A. Q. Zhang, B. X. Zhang, G. Zhang, H. Zhang, H. H. Zhang, H. Y. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, J. Zhang, L. M. Zhang, L. Q. Zhang, L. Zhang, S. Zhang, S. F. Zhang, X. D. Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, L. Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, T. J. Zhu, W. J. Zhu, X. Y. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, and J. H. Zou
Subjects: Branching fraction, Charm Physics, e +-e − Experiments, Particle and Resonance Production, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract Using data collected with the BESIII detector in e + e − collisions at center-of-mass energies between 4.178 and 4.226 GeV and corresponding to 6.32 fb −1 of integrated luminosity, we report the amplitude analysis and branching-fraction measurement of the D s + $$ {D}_s^{+} $$ → π + π 0 η′ decay. We find that the dominant intermediate process is D s + $$ {D}_s^{+} $$ → ρ + η′ and the significances of other resonant and nonresonant processes are all less than 3σ. The upper limits on the branching fractions of S-wave and P-wave nonresonant components are set to 0.10% and 0.74% at the 90% confidence level, respectively. In addition, the branching fraction of the D s + $$ {D}_s^{+} $$ → π + π 0 η′ decay is measured to be (6.15 ± 0.25(stat.) ± 0.18(syst.))%, which receives significant contribution only from D s + $$ {D}_s^{+} $$ → ρ + η′ according to the amplitude analysis.
Published: 2022
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19. Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis.

Author: Karren D. Yang, Samuel Goldman, Wengong Jin, Alex X. Lu, Regina Barzilay, Tommi S. Jaakkola, and Caroline Uhler
Published: 2021
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20. The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers.

Author: Alex X. Lu, Amy X. Lu, Wiebke Schormann, Marzyeh Ghassemi, David W. Andrews, and Alan M. Moses
Published: 2019

21. Hurtful words: quantifying biases in clinical contextual word embeddings.

Author: Haoran Zhang 0003, Amy X. Lu, Mohamed Abdalla, Matthew B. A. McDermott, and Marzyeh Ghassemi
Published: 2020
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22. Development of an automatic linear calibration method for high-resolution single-particle mass spectrometry: improved chemical species identification for atmospheric aerosols

Author: S. Zhu, L. Li, S. Wang, M. Li, Y. Liu, X. Lu, H. Chen, L. Wang, J. Chen, Z. Zhou, X. Yang, and X. Wang
Subjects: Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract: The mass resolution of laser desorption ionization (LDI) single-particle aerosol mass spectrometry (SPAMS) is usually low (∼500), which has been greatly improved by the recent development of the delayed ion extraction technique. However, due to large fluctuations among LDI processes during each laser shot, accurate calibration of the mass-to-charge ratio for high-resolution SPAMS (HR-SPAMS) spectra is challenging. Here we developed an automatic linear calibration method to improve the accuracy of mass-to-charge (m∕z) measurement for single atmospheric aerosol particles. Laboratory-generated sea spray aerosol and atmospheric ambient aerosol were tested. After the calibration, the fluctuation ranges of the reference ions' (e.g., Pb+ and SO4+) m∕z reaches ±0.018 for sea spray aerosol and ±0.024 for ambient aerosol in average mass spectra. With such m∕z accuracy, the HR-SPAMS spectra of sea spray aerosol can easily identify elemental compositions of organic peaks, such as Cx, CxHy and CxHyOz. While the chemical compositions of ambient aerosols are more complicated, CxHy, CxHyOz and CNO peaks can also be identified based on their accurate mass. With the improved resolution, the time series of peaks with small m∕z differences can be separated and measured. In addition, it is also found that applying high-resolution data with enhanced mass calibration can significantly affect particle classification (identification) using the ART-2a algorithm, which classify particles based on similarities among single-particle mass spectra.
Published: 2020
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23. WRF-GC (v1.0): online coupling of WRF (v3.9.1.1) and GEOS-Chem (v12.2.1) for regional atmospheric chemistry modeling – Part 1: Description of the one-way model

Author: H. Lin, X. Feng, T.-M. Fu, H. Tian, Y. Ma, L. Zhang, D. J. Jacob, R. M. Yantosca, M. P. Sulprizio, E. W. Lundgren, J. Zhuang, Q. Zhang, X. Lu, L. Shen, J. Guo, S. D. Eastham, and C. A. Keller
Subjects: Geology, QE1-996.5
Abstract: We developed the WRF-GC model, an online coupling of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the GEOS-Chem atmospheric chemistry model, for regional atmospheric chemistry and air quality modeling. WRF and GEOS-Chem are both open-source community models. WRF-GC offers regional modellers access to the latest GEOS-Chem chemical module, which is state of the science, well documented, traceable, benchmarked, actively developed by a large international user base, and centrally managed by a dedicated support team. At the same time, WRF-GC enables GEOS-Chem users to perform high-resolution forecasts and hindcasts for any region and time of interest. WRF-GC uses unmodified copies of WRF and GEOS-Chem from their respective sources; the coupling structure allows future versions of either one of the two parent models to be integrated into WRF-GC with relative ease. Within WRF-GC, the physical and chemical state variables are managed in distributed memory and translated between WRF and GEOS-Chem by the WRF-GC coupler at runtime. We used the WRF-GC model to simulate surface PM2.5 concentrations over China during 22 to 27 January 2015 and compared the results to surface observations and the outcomes from a GEOS-Chem Classic nested-China simulation. Both models were able to reproduce the observed spatiotemporal variations of regional PM2.5, but the WRF-GC model (r=0.68, bias =29 %) reproduced the observed daily PM2.5 concentrations over eastern China better than the GEOS-Chem Classic model did (r=0.72, bias =55 %). This was because the WRF-GC simulation, nudged with surface and upper-level meteorological observations, was able to better represent the pollution meteorology during the study period. The WRF-GC model is parallelized across computational cores and scales well on massively parallel architectures. In our tests where the two models were similarly configured, the WRF-GC simulation was 3 times more efficient than the GEOS-Chem Classic nested-grid simulation due to the efficient transport algorithm and the Message Passing Interface (MPI)-based parallelization provided by the WRF software framework. WRF-GC v1.0 supports one-way coupling only, using WRF-simulated meteorological fields to drive GEOS-Chem with no chemical feedbacks. The development of two-way coupling capabilities, i.e., the ability to simulate radiative and microphysical feedbacks of chemistry to meteorology, is under way. The WRF-GC model is open source and freely available from http://wrf.geos-chem.org (last access: 10 July 2020).
Published: 2020
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24. Reviewing global estimates of surface reactive nitrogen concentration and deposition using satellite retrievals

Author: L. Liu, X. Zhang, W. Xu, X. Liu, X. Lu, J. Wei, Y. Li, Y. Yang, Z. Wang, and A. Y. H. Wong
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: Since the industrial revolution, human activities have dramatically changed the nitrogen (N) cycle in natural systems. Anthropogenic emissions of reactive nitrogen (Nr) can return to the earth's surface through atmospheric Nr deposition. Increased Nr deposition may improve ecosystem productivity. However, excessive Nr deposition can cause a series of negative effects on ecosystem health, biodiversity, soil, and water. Thus, accurate estimations of Nr deposition are necessary for evaluating its environmental impacts. The United States, Canada and Europe have successively launched a number of satellites with sensors that allow retrieval of atmospheric NO2 and NH3 column density and therefore estimation of surface Nr concentration and deposition at an unprecedented spatiotemporal scale. Atmosphere NH3 column can be retrieved from atmospheric infra-red emission, while atmospheric NO2 column can be retrieved from reflected solar radiation. In recent years, scientists attempted to estimate surface Nr concentration and deposition using satellite retrieval of atmospheric NO2 and NH3 columns. In this study, we give a thorough review of recent advances of estimating surface Nr concentration and deposition using the satellite retrievals of NO2 and NH3, present a framework of using satellite data to estimate surface Nr concentration and deposition based on recent works, and summarize the existing challenges for estimating surface Nr concentration and deposition using the satellite-based methods. We believe that exploiting satellite data to estimate Nr deposition has a broad and promising prospect.
Published: 2020
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25. S177: EVALUATING SERUM FREE LIGHT CHAIN RATIO AS A BIOMARKER FOR MULTIPLE MYELOMA

Author: T. Akhlaghi, K. Maclachlan, N. Korde, S. Mailankody, A. Lesokhin, H. Hassoun, S. X. Lu, D. Patel, U. Shah, C. Tan, A. Derkach, O. Lahoud, H. J. Landau, G. L. Shah, M. Scordo, D. J. Chung, S. A. Giralt, S. Z. Usmani, O. Landgren, and M. Hultcrantz
Subjects: Diseases of the blood and blood-forming organs, RC633-647.5
Published: 2022
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26. S229: CHARACTERISATION OF TUMOR MICROENVIROMENT REMODELLING IN THE PROGRESSION OF AITL WITH SINGLE-CELL RNA SEQUENCING AND IMAGING MASS CYTOMETRY

Author: H. Jin, X. Lu, L. Fan, L. Cao, W. Zhang, J. Li, and Z. Wu
Subjects: Diseases of the blood and blood-forming organs, RC633-647.5
Published: 2022
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27. P886: AFRICAN AMERICAN PATIENTS WITH SMOLDERING MULTIPLE MYELOMA MAY HAVE A LOWER RISK OF PROGRESSION COMPARED TO WHITE PATIENTS

Author: T. Akhlaghi, K. Maclachlan, N. Korde, S. Mailankody, A. Lesokhin, H. Hassoun, S. X. Lu, D. Patel, U. Shah, C. Tan, A. Derkach, O. Lahoud, H. J. Landau, G. L. Shah, M. Scordo, D. J. Chung, S. A. Giralt, S. Z. Usmani, O. Landgren, and M. Hultcrantz
Subjects: Diseases of the blood and blood-forming organs, RC633-647.5
Published: 2022
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28. Comparative effectiveness and safety of antibiotic prophylaxis during induction chemotherapy in children with acute leukaemia: a systematic review and meta-analysis

Author: M. Yang, X. Lu, L. Xin, J. Luo, S. Diao, Z. Jia, G. Cheng, L. Zeng, and L. Zhang
Subjects: Microbiology (medical), Infectious Diseases, General Medicine
Published: 2023
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29. Exploring 2016–2017 surface ozone pollution over China: source contributions and meteorological influences

Author: X. Lu, L. Zhang, Y. Chen, M. Zhou, B. Zheng, K. Li, Y. Liu, J. Lin, T.-M. Fu, and Q. Zhang
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: Severe surface ozone pollution over major Chinese cities has become an emerging air quality concern, raising a new challenge for emission control measures in China. In this study, we explore the source contributions to surface daily maximum 8 h average (MDA8) ozone over China in 2016 and 2017, the 2 years with the highest surface ozone averaged over Chinese cities in record. We estimate the contributions of anthropogenic, background, and individual natural sources to surface ozone over China using the GEOS-Chem chemical transport model at 0.25∘×0.3125∘ horizontal resolution with the most up-to-date Chinese anthropogenic emission inventory. Model results are evaluated with concurrent surface ozone measurements at 169 cities over China and show generally good agreement. We find that background ozone (defined as ozone that would be present in the absence of all Chinese anthropogenic emissions) accounts for 90 % (49.4 ppbv) of the national March–April mean surface MDA8 ozone over China and 80 % (44.5 ppbv) for May–August. It includes large contributions from natural sources (80 % in March–April and 72 % in May–August). Among them, biogenic volatile organic compound (BVOC) emissions enhance MDA8 ozone by more than 15 ppbv in eastern China during July–August, while lightning NOx emissions and ozone transport from the stratosphere both lead to ozone enhancements of over 20 ppbv in western China during March–April. Over major Chinese city clusters, domestic anthropogenic sources account for about 30 % of the May–August mean surface MDA8 ozone and reach 39–73 ppbv (38 %–69 %) for days with simulated MDA8 ozone > 100 ppbv in the North China Plain, Fenwei Plain, Yangtze River Delta, and Pearl River Delta city clusters. These high ozone episodes are usually associated with high temperatures, which induce large BVOC emissions and enhance ozone chemical production. Our results indicate that there would be no days with MDA8 ozone > 80 ppbv in these major Chinese cities in the absence of domestic anthropogenic emissions. We find that the 2017 ozone increases relative to 2016 are largely due to higher background ozone driven by hotter and drier weather conditions, while changes in domestic anthropogenic emissions alone would have led to ozone decreases in 2017. Meteorological conditions in 2017 favor natural source contributions (particularly soil NOx and BVOC ozone enhancements) and ozone chemical production, increase the thermal decomposition of peroxyacetyl nitrate (PAN), and further decrease ozone dry deposition velocity. More stringent emission control measures are thus required to offset the adverse effects of unfavorable meteorology, such as high temperature, on surface ozone air quality.
Published: 2019
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30. A new method for molecular sex identification in the emu (Dromaius novaehollandiae)

Author: X. X. Jia, J. X. Lu, X. J. Tang, Y. F. Fan, and Y. S. Gao
Subjects: Animal Science and Zoology, General Medicine, Food Science
Published: 2023
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31. Plasma poration: Transdermal electric fields, conduction currents, and reactive species transport

Author: E. Wu, L. Nie, D. Liu, X. Lu, and Kostya (Ken) Ostrikov
Subjects: Physiology (medical), Biochemistry
Published: 2023
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32. Identification of ovarian endometriotic cysts in cystic lesions of the ovary by amide proton transfer-weighted imaging and R2∗ mapping

Author: Y, Li, X, Lu, L, Chen, Q, Zhang, N, Wang, J, Wang, L, Lin, G, Hu, Y, Zhang, and A, Liu
Subjects: Radiology, Nuclear Medicine and imaging, General Medicine
Abstract: To investigate the value of amide proton transfer weighted (APTw) imaging and R2∗ mapping of cystic fluid in differentiating ovarian endometriotic cysts (OE) from other ovarian cystic (OOC) lesions.A total of 42 patients who underwent 3 T pelvic magnetic resonance imaging (MRI) were enrolled. Nineteen lesions were OE and 27 lesions were OOC. The APTw imaging and R2∗ values of the cystic fluid were measured and compared between the two groups using the independent sample t-test or Mann-Whitney U-test. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy of different parameters. The area under ROC curves (AUCs) was compared using the Delong test. Spearman's correlation analysis was used to assess the correlation between APTw imaging and R2∗ values.APTw imaging values of OE were lower, while R2∗ values were higher in OE than those in OOC (p=0.001 and 0.001). The AUCs of APTw imaging and R2∗ values to identify OE from OOC were 0.910 and 0.975. The AUC increased to 0.990 when combining APTw imaging and R2∗ values, yet without a significant difference to the APTw imaging or R2∗ value alone (p=0.229 and 0.082, respectively). APTw imaging values were negatively correlated with R2∗ values (r=-0.522, p0.001).Both APTw imaging and R2∗ values of OE are significantly different from other ovarian cystic lesions. APTw imaging combined with R2∗ values show excellent diagnostic efficacy to differentiate between OE and OOC.
Published: 2023
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33. Propagation Characteristic for Indoor E-Band Wideband Channels.

Author: Chang Cao, Xiongfei Zou, Hua Yan, David Steer, Stan X. Lu, Jia He 0002, and Guangjian Wang
Published: 2016
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34. Past, present, and the future of the research and commercialization of CVD diamond in China

Author: F. X. Lu
Subjects: General Medicine
Published: 2022
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35. Malnutrition Increases the Risk of Left Ventricular Remodeling

Author: Q, Li, X, Lu, W, Chen, H, Huang, S, Chen, S, Shi, G, Liang, Z, Huang, J, Deng, W, Guo, S, Su, N, Tan, J, Chen, J, Liu, Y, Liu, and N, Xie
Subjects: Male, Heart Failure, Nutrition and Dietetics, Ventricular Remodeling, Malnutrition, Nutritional Status, Medicine (miscellaneous), Prognosis, Nutrition Assessment, Humans, Female, Geriatrics and Gerontology, Aged, Retrospective Studies
Abstract: Malnutrition is associated with increased incidence of heart failure (HF). Left ventricular (LV) remodeling is one of the most important processes in the occurrence and evolution of HF. However, the association between nutritional status and LV remodeling is not well known. The study aimed to investigate the association between malnutrition and LV remodeling.The study was a retrospective observation study.We included patients from the registry of Cardiorenal Improvement study from January 2007 to December 2018 at Guangdong Provincial People's Hospital.The primary endpoint was LV remodeling, defined as an absolute decrease in LV ejection fraction ≥10% after discharge compared with baseline. Nutritional status was assessed by the Controlling Nutritional Status (CONUT) score. Eligible patients were divided into absent-mild malnutrition group (CONUT score ≤4) and moderate-severe malnutrition group (CONUT score4). Univariable and multivariable logistic regression was performed to verify the association between malnutrition and left ventricular remodeling.A total of 7,217 patients (mean age 61.3±10.5 years, 71.7% male) were included in the final analysis, among which 712 (9.9%) had LV remodeling. The incidence of LV remodeling in moderate-severe malnutrition group was significantly higher than that in absent-mild malnutrition group (12.9% vs. 9.5%, p=0.002). In multivariable logistic regression, moderate-severe malnutrition group was significantly associated with 1.69-fold increased risk of LV remodeling after adjusting confounders (OR: 1.69, CI: 1.32-2.16). Similar results were observed in subgroup stratified by age, gender, and coronary artery disease.Nearly one eighth of patients were classified as moderate-severe malnutrition, 12% of whom had LV remodeling. Moderate-severe malnutrition was associated with 69% increased risk of LV remodeling. Further studies are needed to prospectively evaluate the nutrition-oriented managements on outcomes in LV remodeling.
Published: 2022
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36. Isolation of Lactic Acid Bacteria from Yogurt and the Effect on the Intestinal Microflora in Mice

Author: W. J. Ma, M. N. Zhao, Z. X. Lu, F. X. Lv, P. Zhang, and X. M. Bie
Subjects: General Agricultural and Biological Sciences, General Biochemistry, Genetics and Molecular Biology
Published: 2022
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37. Aldosterone, Renin, and Aldosterone-to-Renin Ratio Variability in Screening for Primary Aldosteronism

Author: Elisabeth Ng, Stella May Gwini, Renata Libianto, Kay Weng Choy, Zhong X Lu, Jimmy Shen, James C G Doery, Peter J Fuller, and Jun Yang
Subjects: Endocrinology, Endocrinology, Diabetes and Metabolism, Biochemistry (medical), Clinical Biochemistry, Biochemistry
Abstract: Context The plasma aldosterone concentration (PAC), renin, and aldosterone-to-renin ratio (ARR) are used to screen for primary aldosteronism (PA). Substantial intra-individual variability of PAC and ARR using plasma renin activity in the context of usual antihypertensive therapy has been described, but there is no data on ARR variability calculated using direct renin concentration (DRC). Objective To describe the intra-individual variability of PAC, DRC, and ARR in the absence of interfering medications in patients with and without PA. Design Retrospective cohort study. Patients Hypertensive patients referred for investigation of PA, with at least 2 ARR measurements while off interfering medications. Setting Endocrine hypertension service of a tertiary center, from May 2017 to July 2021. Main outcome measures PAC, DRC, and ARR variability was calculated as coefficient of variation (CV) and percent difference (PD). Results Analysis of 223 patients (55% female, median age 52 years), including 162 with confirmed PA, demonstrated high variability with a sample CV of 22-25% in the PAC and sample CV of 41% to 42% in the DRC and ARR in both the PA and non-PA groups. The degree of variability was substantially higher than the assays’ analytical CV. Sixty-two patients (38%) with PA had at least one ARR below 70 pmol/L:mU/L (2.4 ng/dL:mU/L), a cut-off for first-line screening of PA. Conclusions Significant intra-individual variability in PAC, DRC, and hence ARR occurs in a large proportion of patients being investigated for PA. These findings support the need for at least 2 ARR before PA is excluded or further investigated.
Published: 2022
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38. Sustained Minimal Residual Disease Negativity in Multiple Myeloma is Associated with Stool Butyrate and Healthier Plant-Based Diets

Author: Urvi A. Shah, Kylee H. Maclachlan, Andriy Derkach, Meghan Salcedo, Kelly Barnett, Julia Caple, Jenna Blaslov, Linh Tran, Amanda Ciardiello, Miranda Burge, Tala Shekarkhand, Peter Adintori, Justin Cross, Matthew J. Pianko, Kinga Hosszu, Devin McAvoy, Sham Mailankody, Neha Korde, Malin Hultcrantz, Hani Hassoun, Carlyn R. Tan, Sydney X. Lu, Dhwani Patel, Benjamin Diamond, Gunjan Shah, Michael Scordo, Oscar Lahoud, David J. Chung, Heather Landau, Saad Z. Usmani, Sergio Giralt, Ying Taur, C. Ola Landgren, Gladys Block, Torin Block, Jonathan U. Peled, Marcel R.M. van den Brink, and Alexander M. Lesokhin
Subjects: Healthy, Cancer Research, Neoplasm, Residual, Diet, Vegetarian, Oncology and Carcinogenesis, Hematology, Oral and gastrointestinal, Article, Diet, Butyrates, Rare Diseases, Good Health and Well Being, Vegetarian, Oncology, Clinical Research, Residual, Complementary and Integrative Health, Neoplasm, Humans, Oncology & Carcinogenesis, Diet, Healthy, Multiple Myeloma, Nutrition, Cancer
Abstract: Purpose: Sustained minimal residual disease (MRD) negativity is associated with long-term survival in multiple myeloma. The gut microbiome is affected by diet, and in turn can modulate host immunity, for example through production of short-chain fatty acids including butyrate. We hypothesized that dietary factors affect the microbiome (abundance of butyrate-producing bacteria or stool butyrate concentration) and may be associated with multiple myeloma outcomes. Experimental Design: We examined the relationship of dietary factors (via a food frequency questionnaire), stool metabolites (via gas chromatography–mass spectrometry), and the stool microbiome (via 16S sequencing - α-diversity and relative abundance of butyrate-producing bacteria) with sustained MRD negativity (via flow cytometry at two timepoints 1 year apart) in myeloma patients on lenalidomide maintenance. The Healthy Eating Index 2015 score and flavonoid nutrient values were calculated from the food frequency questionnaire. The Wilcoxon rank sum test was used to evaluate associations with two-sided P < 0.05 considered significant. Results: At 3 months, higher stool butyrate concentration (P = 0.037), butyrate producers (P = 0.025), and α-diversity (P = 0.0035) were associated with sustained MRD negativity. Healthier dietary proteins, (from seafood and plants), correlated with butyrate at 3 months (P = 0.009) and sustained MRD negativity (P = 0.05). Consumption of dietary flavonoids, plant nutrients with antioxidant effects, correlated with stool butyrate concentration (anthocyanidins P = 0.01, flavones P = 0.01, and flavanols P = 0.02). Conclusions: This is the first study to demonstrate an association between a plant-based dietary pattern, stool butyrate production, and sustained MRD negativity in multiple myeloma, providing rationale to evaluate a prospective dietary intervention.
Published: 2022
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39. Relationship Between Urinary Phosphate and All-Cause and Cardiovascular Mortality in a National Population-Based Longitudinal Cohort Study

Author: Nigel D. Toussaint, Matthew J. Damasiewicz, Stephen G. Holt, Zhong X. Lu, Dianna J. Magliano, Robert C. Atkins, Steven J. Chadban, Jonathan E. Shaw, and Kevan R. Polkinghorne
Subjects: Male, Nutrition and Dietetics, Australia, Medicine (miscellaneous), Middle Aged, Phosphates, Cohort Studies, Cardiovascular Diseases, Risk Factors, Nephrology, Humans, Female, Longitudinal Studies, Renal Insufficiency, Chronic, Proportional Hazards Models
Abstract: High dietary phosphate intake may lead to adverse outcomes including cardiovascular disease (CVD). Urinary phosphate excretion, a marker of intestinal phosphate absorption, may be a more reliable marker of phosphate homeostasis in steady state than serum phosphate. Studies report good agreement between urine phosphate-to-creatinine ratio (uPiCr) and 24-hour urinary phosphate; however, whether uPiCr is associated with increased risk of CVD or mortality remains uncertain. This study aimed to assess the relationship between uPiCr and all-cause and CVD mortality.This is an observational longitudinal cohort study using data from the population-based national Australian Diabetes, Obesity and Lifestyle study (n = 10,014 participants). Non-linear association between uPiCr and all-cause and CVD mortality was assessed using fractional polynomial transformations. Cox proportional hazards regression models were used to estimate adjusted hazard ratios for all-cause and CVD mortality.Median age [interquartile range] was 50 [41-62] years, and 46% were male. Median uPiCr was 1.38 [1.02-1.79] mmol/mmol. Median follow-up time was 16.9 years with 1,735 deaths. uPiCr was associated with all-cause and CVD mortality in univariate models and when adjusted for age and gender. However, associations were not significant in multivariate models. Sensitivity analyses excluding participants with chronic kidney disease (CKD) revealed a significant J-shaped association between uPiCr and all-cause mortality. Urine phosphate alone showed an association with increased all-cause mortality in a similar J-shape relationship.Although no association between uPiCr and all-cause and CVD mortality was observed in multivariate analyses in the whole cohort, a significant relationship between uPiCr and mortality in those without CKD suggests that uPiCr may have predictive validity for future adverse outcomes in people with no CKD.
Published: 2022
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40. A ROBUST METHOD FOR STEREO VISUAL ODOMETRY BASED ON MULTIPLE EUCLIDEAN DISTANCE CONSTRAINT AND RANSAC ALGORITHM

Author: Q. Zhou, X. Tong, S. Liu, X. Lu, P. Chen, Y. Jin, and H. Xie
Subjects: Technology, Engineering (General). Civil engineering (General), TA1-2040, Applied optics. Photonics, TA1501-1820
Abstract: Visual Odometry (VO) is a critical component for planetary robot navigation and safety. It estimates the ego-motion using stereo images frame by frame. Feature points extraction and matching is one of the key steps for robotic motion estimation which largely influences the precision and robustness. In this work, we choose the Oriented FAST and Rotated BRIEF (ORB) features by considering both accuracy and speed issues. For more robustness in challenging environment e.g., rough terrain or planetary surface, this paper presents a robust outliers elimination method based on Euclidean Distance Constraint (EDC) and Random Sample Consensus (RANSAC) algorithm. In the matching process, a set of ORB feature points are extracted from the current left and right synchronous images and the Brute Force (BF) matcher is used to find the correspondences between the two images for the Space Intersection. Then the EDC and RANSAC algorithms are carried out to eliminate mismatches whose distances are beyond a predefined threshold. Similarly, when the left image of the next time matches the feature points with the current left images, the EDC and RANSAC are iteratively performed. After the above mentioned, there are exceptional remaining mismatched points in some cases, for which the third time RANSAC is applied to eliminate the effects of those outliers in the estimation of the ego-motion parameters (Interior Orientation and Exterior Orientation). The proposed approach has been tested on a real-world vehicle dataset and the result benefits from its high robustness.
Published: 2017
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41. Inhibition of O-GlcNAcase leads to elevation of O-GlcNAc tau and reduction of tauopathy and cerebrospinal fluid tau in rTg4510 mice

Author: Nicholas B. Hastings, Xiaohai Wang, Lixin Song, Brent D. Butts, Diane Grotz, Richard Hargreaves, J. Fred Hess, Kwok-Lam Karen Hong, Cathy Ruey-Ruey Huang, Lynn Hyde, Maureen Laverty, Julie Lee, Diane Levitan, Sherry X. Lu, Maureen Maguire, Veeravan Mahadomrongkul, Ernest J. McEachern, Xuesong Ouyang, Thomas W. Rosahl, Harold Selnick, Michaela Stanton, Giuseppe Terracina, David J. Vocadlo, Ganfeng Wang, Joseph L. Duffy, Eric M. Parker, and Lili Zhang
Subjects: Tau, OGA, O-GlcNAc, Alzheimer’s disease, Tauopathy, Neurodegeneration, Neurology. Diseases of the nervous system, RC346-429, Geriatrics, RC952-954.6
Abstract: Abstract Background Hyperphosphorylation of microtubule-associated protein tau is a distinct feature of neurofibrillary tangles (NFTs) that are the hallmark of neurodegenerative tauopathies. O-GlcNAcylation is a lesser known post-translational modification of tau that involves the addition of N-acetylglucosamine onto serine and threonine residues. Inhibition of O-GlcNAcase (OGA), the enzyme responsible for the removal of O-GlcNAc modification, has been shown to reduce tau pathology in several transgenic models. Clarifying the underlying mechanism by which OGA inhibition leads to the reduction of pathological tau and identifying translatable measures to guide human dosing and efficacy determination would significantly facilitate the clinical development of OGA inhibitors for the treatment of tauopathies. Methods Genetic and pharmacological approaches are used to evaluate the pharmacodynamic response of OGA inhibition. A panel of quantitative biochemical assays is established to assess the effect of OGA inhibition on pathological tau reduction. A “click” chemistry labeling method is developed for the detection of O-GlcNAcylated tau. Results Substantial (>80%) OGA inhibition is required to observe a measurable increase in O-GlcNAcylated proteins in the brain. Sustained and substantial OGA inhibition via chronic treatment with Thiamet G leads to a significant reduction of aggregated tau and several phosphorylated tau species in the insoluble fraction of rTg4510 mouse brain and total tau in cerebrospinal fluid (CSF). O-GlcNAcylated tau is elevated by Thiamet G treatment and is found primarily in the soluble 55 kD tau species, but not in the insoluble 64 kD tau species thought as the pathological entity. Conclusion The present study demonstrates that chronic inhibition of OGA reduces pathological tau in the brain and total tau in the CSF of rTg4510 mice, most likely by directly increasing O-GlcNAcylation of tau and thereby maintaining tau in the soluble, non-toxic form by reducing tau aggregation and the accompanying panoply of deleterious post-translational modifications. These results clarify some conflicting observations regarding the effects and mechanism of OGA inhibition on tau pathology, provide pharmacodynamic tools to guide human dosing and identify CSF total tau as a potential translational biomarker. Therefore, this study provides additional support to develop OGA inhibitors as a treatment for Alzheimer’s disease and other neurodegenerative tauopathies.
Published: 2017
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42. Genetic landscape of indolent and aggressive Kaposi sarcomas

Author: G.G. Malouf, X. Lu, R. Mouawad, J.‐P. Spano, P. Grange, F. Yan, S. Aractingi, X. Su, and N. Dupin
Subjects: Acquired Immunodeficiency Syndrome, Skin Neoplasms, Infectious Diseases, Herpesvirus 8, Human, Mutation, Humans, Dermatology, Sarcoma, Kaposi
Abstract: Kaposi sarcoma (KS) is a rare skin tumour caused by herpesvirus 8 infection and characterized by either indolence or an aggressive course necessitating systemic therapies. The genetic basis of this difference remains unknown.To explore the tumour mutational burden in indolent and aggressive KS.We performed whole-exome sequencing on a cohort of 21 KS patients. We compared genetic landscape including tumor mutational burden between the two forms of indolent and agressive KS.Aggressive KS tumours had a significantly higher TMB and a larger cumulative number of deleterious mutations than indolent KS tumours. In addition, all aggressive tumours had at least three deleterious mutations, whereas most indolent tumours harboured only one or no predicted deleterious mutations. Deleterious mutations listed in the Cancer Gene Census were detected exclusively in patients with aggressive disease. An analysis of somatic copy-number alterations (SCNA) revealed a tendency towards higher number of alterations in aggressive KS.These data suggest that SCNA alterations and an increase in mutational burden promote aggressive KS and that it might be more appropriate to consider indolent KS as an opportunistic skin disease rather than a cancer.
Published: 2022
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43. A prognostic nomogram based on log odds of positive lymph nodes to predict the overall survival in biliary neuroendocrine neoplasms (NENs) patients after surgery

Author: S. Jiang, F. Yang, L. Zhang, X. Sang, X. Lu, Y. Zheng, and Y. Xu
Subjects: Endocrinology, Endocrinology, Diabetes and Metabolism
Published: 2022
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44. Characterising Mechanical Properties of Flowing Microcapsules Using a Deep Convolutional Neural Network

Author: T. Lin, Z. Wang, R. X. Lu, W. Wang, and Y. Sui
Subjects: Computer science, Applied Mathematics, Mechanical Engineering, Biological system, Convolutional neural network
Published: 2022
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45. Intravoxel incoherent motion diffusion-weighted imaging as a quantitative tool for evaluating disease activity in patients with axial spondyloarthritis

Author: C, Guo, K, Zheng, Z, Xie, X, Lu, S, Wu, Q, Ye, Y, He, Q, Zhou, E, Sun, and Y Zhao
Subjects: Motion, Diffusion Magnetic Resonance Imaging, Spondylarthritis, Humans, Sacroiliac Joint, Spondylitis, Ankylosing, Radiology, Nuclear Medicine and imaging, Prospective Studies, General Medicine, Axial Spondyloarthritis
Abstract: To determine the correlations between four quantitative magnetic resonance imaging (MRI) parameters derived from intravoxel incoherent motion diffusion-weighted images (IVIM DWI) and the semi-quantitative Spondyloarthritis Research Consortium of Canada (SPARCC) score of the sacroiliac joint (SIJ) and five clinical activity indices in patients with axial spondyloarthritis (axSpA).A total of 75 patients with axSpA and complete clinical activity indices and SIJ MRI were enrolled to this prospective study. Univariable and multivariable linear regression analyses were performed to evaluate correlations between MRI parameters and clinical activity indices after controlling for confounders. All data were further analysed using Pearson's correlation coefficients (r).Only pure diffusion coefficient (D) and incoherent perfusion related microcirculation (D∗) were found to be independently positively correlated with several clinical activity indices (all p0.05). Positive correlations were observed between D and the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), the Bath Ankylosing Spondylitis Functional Index (BASFI), Patient Global Assessment (PGA), extent of influence of pain, with r of 0.605, 0.402, 0.319, and 0.485 (all p0.0125). D∗ correlated positively with BASDAI, BASFI, and PGA (r=0.436, 0.356, 0.301, respectively; all p0.0125).D and D∗ derived from IVIM DWI could be associated with some disease activity indices in patients with axSpA; apparent diffusion coefficient (ADC) and SPARCC scores were not correlated with these indices. IVIM DWI may be a useful tool for the quantitative assessment of disease activity in patients with axSpA.
Published: 2022
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46. Observation of <math><mrow><mi>ψ</mi><mo>(</mo><mn>3770</mn><mo>)</mo><mo>→</mo><mi>η</mi><mi>J</mi><mo>/</mo><mi>ψ</mi></mrow></math>

Author: Ablikim, M., Achasov, M. N., Adlarson, P., Ahmed, S., Albrecht, M., Aliberti, R., Amoroso, A., M. R., An, An, Q., Bai, X. H., Bai, Y., Bakina, O., Baldini Ferroli, R., Balossino, I., Ban, Y., Batozskaya, V., Becker, D., Begzsuren, K., Berger, N., Bertani, M., Bettoni, D., Bianchi, F., Bloms, J., Bortone, A., Boyko, I., Briere, R. A., Brueggemann, A., Cai, H., Cai, X., Calcaterra, A., Cao, G. F., Cao, N., Cetin, S. A., Chang, J. F., Chang, W. L., Chelkov, G., Chen, C., Chen, G., Chen, H. S., Chen, M. L., Chen, S. J., Chen, T., Chen, X. R., Chen, X. T., Chen, Y. B., Chen, Z. J., Cheng, W. S., Cibinetto, G., Cossio, F., Cui, J. J., Dai, H. L., Dai, J. P., Dbeyssi, A., de Boer, R. E., Dedovich, D., Deng, Z. Y., Denig, A., Denysenko, I., Destefanis, M., De Mori, F., Ding, Y., Dong, J., Dong, L. Y., Dong, M. Y., Dong, X., S. X., Du, Egorov, P., Fan, Y. L., Fang, J., Fang, S. S., Fang, Y., Farinelli, R., Fava, L., Feldbauer, F., Felici, G., Feng, C. Q., Feng, J. H., Fischer, K., Fritsch, M., C. D., Fu, Gao, H., Gao, Y. N., Gao, Yang, Garzia, I., P. T., Ge, Z. W., Ge, Geng, C., Gersabeck, E. M., Gilman, A., Goetzen, K., Gong, L., Gong, W. X., Gradl, W., Greco, M., L. M., Gu, M. H., Gu, Y. T., Gu, Guan, C. Y., Guo, A. Q., Guo, L. B., Guo, R. P., Guo, Y. P., Guskov, A., Han, T. T., Han, W. Y., Hao, X. Q., Harris, F. A., K. K., He, K. L., He, Heinsius, F. H., Heinz, C. H., Heng, Y. K., Herold, C., Himmelreich, M., Holtmann, T., Hou, G. Y., Hou, Y. R., Hou, Z. L., H. M., Hu, J. F., Hu, Hu, T., Hu, Y., Huang, G. S., Huang, K. X., Huang, L. Q., Huang, X. T., Huang, Y. P., Huang, Z., Hussain, T., Hüsken, N., Imoehl, W., Irshad, M., Jackson, J., Jaeger, S., Janchiv, S., Ji, Q., Q. P., Ji, X. B., Ji, X. L., Ji, Y. Y., Ji, Jiang, H. B., Jiang, S. S., Jiang, X. S., Jiang, Y., Jiao, J. B., Jiao, Z., Jin, S., Jin, Y., Jing, M. Q., Johansson, T., Kalantar-Nayestanaki, N., Kang, X. S., Kappert, R., Kavatsyuk, M., B. C., Ke, Keshk, I. K., Khoukaz, A., Kiese, P., Kiuchi, R., Kliemt, R., Koch, L., Kolcu, O. B., Kopf, B., Kuemmel, M., Kuessner, M., Kupsc, A., Kühn, W., Lane, J. J., Lange, J. S., Larin, P., Lavania, A., Lavezzi, L., Lei, Z. H., Leithoff, H., Lellmann, M., Lenz, T., Li, C., C. H., Li, Cheng, Li, D. M., Li, Li, F., Li, G., Li, H., H. B., Li, H. J., Li, H. N., Li, J. Q., Li, J. S., Li, J. W., Li, Ke, Li, L. J., Li, L. K., Li, Lei, Li, M. H., Li, P. R., Li, S. X., Li, S. Y., Li, Li, T., W. D., Li, W. G., Li, X. H., Li, X. L., Li, Xiaoyu, Li, Z. Y., Li, Liang, H., Liang, Y. F., Liang, Y. T., Liao, G. R., Liao, L. Z., Libby, J., Limphirat, A., Lin, C. X., Lin, D. X., Lin, T., Liu, B. J., Liu, C. X., Liu, D., Liu, F. H., Liu, Fang, Liu, Feng, Liu, G. M., Liu, H. B., Liu, H. M., Liu, Huanhuan, Liu, Huihui, Liu, J. B., Liu, J. L., Liu, J. Y., Liu, K., Liu, K. Y., Liu, Ke, Liu, L., Liu, Lu, Liu, M. H., Liu, P. L., Liu, Q., Liu, S. B., Liu, T., Liu, W. K., Liu, W. M., Liu, X., Liu, Y., Liu, Y. B., Liu, Z. A., Liu, Z. Q., Lou, X. C., F. X., Lu, H. J., Lu, J. G., Lu, X. L., Lu, Lu, Y., Y. P., Lu, Z. H., Lu, Luo, C. L., Luo, M. X., Luo, T., Luo, X. L., Lyu, X. R., Lyu, Y. F., F. C., Ma, H. L., Ma, L. L., Ma, M. M., Ma, Q. M., Ma, R. Q., Ma, R. T., Ma, X. Y., Ma, Ma, Y., Maas, F. E., Maggiora, M., Maldaner, S., Malde, S., Malik, Q. A., Mangoni, A., Mao, Y. J., Mao, Z. P., Marcello, S., Meng, Z. X., Messchendorp, J. G., Mezzadri, G., Miao, H., Min, T. J., Mitchell, R. E., X. H., Mo, Muchnoi, N. Yu., Muramatsu, H., Nakhoul, S., Nefedov, Y., Nerling, F., Nikolaev, I. B., Ning, Z., Nisar, S., Niu, Y., Olsen, S. L., Ouyang, Q., Pacetti, S., Pan, X., Pan, Y., Pathak, A., Pelizaeus, M., Peng, H. P., Peters, K., Ping, J. L., Ping, R. G., Plura, S., Pogodin, S., Poling, R., Prasad, V., Qi, H., H. R., Qi, Qi, M., T. Y., Qi, Qian, S., Qian, W. B., Qian, Z., Qiao, C. F., Qin, J. J., Qin, L. Q., Qin, X. P., Qin, X. S., Qin, Z. H., Qiu, J. F., S. Q., Qu, Rashid, K. H., Ravindran, K., Redmer, C. 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Abstract: Using a data sample collected with the BESIII detector operating at the BEPCII storage ring, the Born cross section of the process e+e−→ηJ/ψ at a center-of-mass energy s=3.773 GeV is measured to be (8.88±0.87±0.42) pb. We fit the cross section line shape before correcting for the initial state radiation from s=3.773 to 4.600 GeV to obtain the branching fraction B(ψ(3770)→ηJ/ψ). We obtain B(ψ(3770)→ηJ/ψ)=(11.3±5.9±1.1)×10−4 when the ψ(3770) decay amplitude is added coherently to the other contributions, and (8.7±1.0±0.8)×10−4 when it is added incoherently. Here the quoted uncertainties are statistical and systematic, respectively. In both cases, the statistical significance of ψ(3770) resonance is above 7σ. This is the first time the decay ψ(3770)→ηJ/ψ is observed with a statistical significance greater than 5σ.
Published: 2023

47. Anomalous lattice thermal conductivity driven by all-scale electron-phonon scattering in bulk semiconductors

Author: Z. Z. Zhou, Y. C. Yan, X. L. Yang, Y. Xia, G. Y. Wang, X. Lu, and X. Y. Zhou
Published: 2023
Full Text: View/download PDF

48. Distinct Proteomic Signatures Are Associated With Right Ventricular Vulnerability and Outcomes in Pulmonary Arterial Hypertension

Author: H. Pi, X. Lu, L.J. Oppegard, S.G. Rayner, A. Shojaie, S.A. Gharib, and P.J. Leary
Published: 2023
Full Text: View/download PDF

49. Coronavirus Disease Vaccination In Patients With Pulmonary Hypertension: A National Prospective Cohort Study

Author: X.-H. Wu, J.-Y. Li, J.-L. Ma, Q.-Q. Liu, L. Wang, Y.-J. Zhu, Y. Cui, J.-X. Lu, A.-Y. Wang, C.-J. Wen, L.-H. Qiu, Y.-J. Yang, D. Lu, X.-Q. Xu, X.-J. Zhu, C.-Y. Cheng, D.-L. Wang, and Z.-C. Jing
Published: 2023
Full Text: View/download PDF

50. Damaged Mitochondria Contribute to Hyperoxia-induced Impaired Angiogenesis and Lung Injury in Neonatal Mice

Author: H. Yao, Z. Feng, J. Gong, X. Lu, K. Hegarty, and P.A. Dennery
Published: 2023
Full Text: View/download PDF

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