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1. Yu Shuxi's Biography and Transmission of Pingdiao Sanxianshu Chinese Folk Singing in the Context of Literacy

Author

Ke Liu and Sarawut Choatchamrat

Abstract

This study investigates the role of Yu Shuxi in the transmission and preservation of Pingdiao Sanxianshu, an intangible cultural heritage, within the context of literacy and education. By analyzing the cultural significance and pedagogical practices of Yu Shuxi's artistry, the research explores the impact of traditional folk arts on literacy development and cultural identity formation. Utilizing qualitative methods, including interviews with key informants and field observations in Baofeng County, Henan Province, the study captures the intricate relationship between individual biographies and broader educational practices. Data analysis reveals how Yu Shuxi's life story and teachings in Pingdiao Sanxianshu contribute to cultural preservation and literacy skills among learners, emphasizing the need for integration of traditional arts in modern education. The results indicate the potential of such arts to enhance critical thinking, linguistic abilities, and cultural literacy. Consequently, the research suggests collaborative measures across educational institutions, governmental policies, and community efforts to ensure the viability and relevance of traditional folk arts like Pingdiao Sanxianshu in contemporary society, maintaining their legacy for future generations.

Published
2024

3. 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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4. Adsorption and sensing characteristics of insulating gas C4F7N on 3d late transition metal‐phthalocyanine: Theoretical and experimental study

Author

Dachang Chen, Ziang Zheng, Cong Zhang, Yi Luo, Song Xiao, Qing Miao, Ke Liu, and Beibei Xiao

Subjects
Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Electricity, QC501-721
Abstract

Abstract Heptafluoroisobutyronitrile (C4F7N) is being considered as a promising alternative to the greenhouse gas SF6 in the electrical industry. However, its biotoxicity necessitates the development of gas sensing technology to detect leaked C4F7N. A combination of density functional theory and experiments was employed to evaluate the adsorption and sensing performance of different metal‐phthalocyanines as potential sensing materials for C4F7N detection. The study included exploring adsorption configurations with adsorption energies, electron transfer, and adsorption distance, as well as comparisons of electronic properties, electron distribution, and density of states (DOS) among the MPcs. Furthermore, gas sensing experiments were conducted using different MPcs to detect 25–100 ppm C4F7N. The results revealed that Mn‐Pc, Fe‐Pc, Co‐Pc, and Zn‐Pc exhibited considerable chemical interactions, while Ni‐Pc and Cu‐Pc showed weaker adsorption strength. These findings were further elucidated based on the electron density and DOS of atomic orbitals. Moreover, gas sensing experiments indicated that Co‐Pc demonstrated a higher response compared to Fe‐Pc at the same concentration of C4F7N. Overall, the theoretical and experimental insights offer valuable guidance for C4F7N detection and provide a systematic approach to screen and explore organometallic polymer‐based gas sensors applicable in various fields.

Published
2024
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5. Artemisitene shows superiority over artemisinin in preventing Schistosoma japonica-induced liver disease

Author

Meng-Ke Liu, Xu-Yang Chen, Juan-Juan Tang, Zhi-Peng Liu, Gui-Ying Lin, Jun-Ling Cai, Zuo-Ming Chen, Yu-Yun Yan, Xiao-Fang Ji, Zhong-Jin Yang, and Zi Li

Subjects
Artemisinin, Artemisitene, Schistosoma japonica, Liver fibrosis, Tegument, Host immunity, Infectious and parasitic diseases, RC109-216
Abstract

Abstract Background Artemisinin (ART) analogs, such as dihydroartemisinin, arteether, artemether, and artesunate, all featuring an endoperoxide bridge, have demonstrated efficacy against schistosomiasis. Artemisitene (ATT), which contains an additional α, β-unsaturated carbonyl structure, has shown enhanced biological activities. This study aims to evaluate the anti-schistosomaiasis japonica activity of ATT and compare it with ART. Methods We assessed liver inflammation and fibrosis in mice using hematoxylin and eosin staining and Sirius red staining, respectively. RNA sequencing analyzed transcriptomics in female and male Schistosoma japonicum (S. japonicum) adult worms and mice livers, with cytokine profiling and flow cytometry to study immune responses under ART or ATT treatment. Results ATT exhibits a marked reduction in female S. japonicum adult worms and egg numbers, damaging the adult worms’ surface. It also influences the transcription of genes related to cellular anatomical structures. Notably, ATT treatment resulted in significant reductions in liver granuloma size and collagen area, alongside lowering serum levels of glutamic pyruvic and glutamic oxaloacetic transaminase more effectively than ART. Both ART and ATT markedly decreased neutrophil frequency in the liver and elevated eosinophil counts. However, only ATT treatment significantly reduced the M1/M2 and Th1/Th2 indices, indicating a pronounced shift in immune response profiles. ATT-affected host immunity correlated with the extent of liver fibrosis and the count of single males more strongly than ART. Conclusion ATT, as a novel preventive strategy for schistosomiasis japonica in mice, significantly outperforms ART. Graphical Abstract

Published
2024
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6. Dissecting the vital role of dietary changes in food security assessment under climate change

Author

Jin Zhao, Zhentao Zhang, Chuang Zhao, Zhijuan Liu, Erjing Guo, Tianyi Zhang, Ji Chen, Jørgen Eivind Olesen, Ke Liu, Matthew Tom Harrison, Yumei Zhang, Xiaolong Feng, Ting Meng, Qing Ye, Shenggen Fan, and Xiaoguang Yang

Subjects
Geology, QE1-996.5, Environmental sciences, GE1-350
Abstract

Abstract National and global food security depend on both supply and demand, yet the vast majority of studies on the impact of climate change on food security have focused somewhat myopically on the supply side. Here, we assess planetary implications of the changing climate for food supply, concurrently considering implications of shifts in dietary preferences on food security. From 1990 to 2018, climate change detrimentally impacted on the food production of 92% of nations assessed. During this time, demand decreased at a greater rate than food supply in 28% of countries; food security for 35% of the global population was unperturbed by climate change. On the other hand, 2% of the global population did not benefit from positive impacts of climate change on food production, due to dietary changes faster increasing food demand. If consumers shift dietary preferences en masse towards healthier diets, detrimental impacts of the climate crisis on food security may be abated, although en mass and/or abrupt transitions in dietary preferences are unlikely.

Published
2024
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7. Association of serum 25-hydroxyvitamin D concentrations with all-cause and cause-specific mortality among individuals with gout and hyperuricemia

Author

Ke Liu, Xuanni Lu, Anqi Wang, Weiwei Chen, Ying Chen, Jiayu Li, Xiaohui Sun, Lin Huang, Zhixing He, Chengping Wen, Yingying Mao, and Ding Ye

Subjects
25-hydroxyvitamin D, Gout, Hyperuricemia, Mortality, Cardiovascular disease, Cancer, Nutrition. Foods and food supply, TX341-641, Nutritional diseases. Deficiency diseases, RC620-627
Abstract

Abstract Background We aimed to probe the association of serum 25-hydroxyvitamin D [25(OH)D] concentrations with all-cause and cause-specific mortality among patients with gout and hyperuricemia (HUA). Methods The study included 1169 gout patients and 7029 HUA patients from the National Health and Nutrition Examination Survey (NHANES) 2007–2018 and 2001–2018, respectively. The association between serum 25(OH)D and mortality was evaluated by Cox proportional hazard and restricted cubic spline models. Results Among participants with gout and HUA, the weighted mean concentrations of serum 25(OH)D were 71.49 ± 30.09 nmol/L and 64.81 ± 26.92 nmol/L, respectively. Vitamin D deficiency occurred in 29.68% of gout patients and 37.83% of HUA patients. During 6783 person-years of follow-up among gout patients, 248 all-cause deaths occurred, among which 76 died from cardiovascular disease (CVD) and 49 died from cancer. 1375 HUA patients were recorded for all-cause mortality during 59,859 person-years of follow-up, including 427 CVD deaths and 232 cancer deaths. After multifactorial adjustment, per one-unit increment in natural log-transformed 25(OH)D was associated with lower risk of 55% all-cause mortality and 61% CVD mortality among gout patients, and a 45% reduced risk of cancer mortality among HUA patients. Restricted cubic splines showed a U-shaped relationship with all-cause and CVD mortality among HUA patients, with inflection points of 72.7 nmol/L and 38.0 nmol/L, respectively. The results were robust in subgroup and sensitivity analyses. Conclusions Serum 25(OH)D was negatively linearly correlated with mortality among gout patients, whereas U-shaped correlated with mortality in HUA patients. These results indicate that adequate vitamin D status could prevent premature death.

Published
2024
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8. Measurement of the cross sections of e + e − → K − Ξ ¯ + Λ / Σ 0 $$ {e}^{+}{e}^{-}\to {K}^{-}{\overline{\Xi}}^{+}\Lambda /{\Sigma}^0 $$ at center-of-mass energies between 3.510 and 4.914 GeV

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, 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, P. Larin, 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, 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, L. Z. 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, M. M. Ma, Q. M. Ma, R. Q. Ma, T. Ma, X. T. Ma, X. Y. Ma, 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, P. Patteri, 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. 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, 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, 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. C. Xu, Z. P. 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, T. Yang, Y. Yang, Y. F. Yang, Y. X. Yang, Z. W. Yang, Z. P. Yao, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. 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, 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, J. Zhu, K. Zhu, K. J. Zhu, K. S. Zhu, L. Zhu, L. X. Zhu, S. H. Zhu, S. Q. Zhu, T. J. Zhu, W. D. Zhu, Y. C. Zhu, Z. A. Zhu, J. H. Zou, and J. Zu

Subjects
e +-e − Experiments, QCD, Particle and Resonance Production, Branching fraction, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract Using e + e − collision data collected with the BESIII detector at the BEPCII collider at center-of-mass energies between 3.510 and 4.914 GeV, corresponding to an integrated luminosity of 25 fb −1, we measure the Born cross sections for the process e + e − → K − Ξ ¯ + Λ / Σ 0 $$ {e}^{+}{e}^{-}\to {K}^{-}{\overline{\Xi}}^{+}\Lambda /{\Sigma}^0 $$ at thirty-five energy points with a partial-reconstruction strategy. By fitting the dressed cross sections of e + e − → K − Ξ ¯ + Λ / Σ 0 $$ {e}^{+}{e}^{-}\to {K}^{-}{\overline{\Xi}}^{+}\Lambda /{\Sigma}^0 $$ , evidence for ψ 4160 → K − Ξ ¯ + Λ $$ \psi (4160)\to {K}^{-}{\overline{\Xi}}^{+}\Lambda $$ is found for the first time with a significance of 4.4σ, including systematic uncertainties. No evidence for other possible resonances is found. In addition, the products of electronic partial width and branching fraction for all assumed resonances decaying into K − Ξ ¯ + Λ / Σ 0 $$ {K}^{-}{\overline{\Xi}}^{+}\Lambda /{\Sigma}^0 $$ are determined.

Published
2024
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9. Study of η′ → π + π − l + l − decays at BESIII

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, W. L. Chang, G. R. Che, G. Chelkov, C. Chen, C. H. Chen, Chao Chen, G. Chen, H. S. 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, X. Chu, 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, 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, K. Fischer, M. Fritsch, C. D. Fu, J. L. Fu, Y. W. 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, S. Gramigna, M. Greco, M. H. Gu, Y. T. Gu, C. Y. Guan, Z. L. 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, 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, T. Hu, Y. Hu, G. S. Huang, K. X. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, T. Hussain, F. Hölzken, N Hüsken, N. in der Wiesche, M. Irshad, 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, A. Kupsc, W. Kühn, J. J. Lane, P. Larin, L. Lavezzi, T. T. Lei, 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, Hui Li, J. R. Li, J. S. Li, Ke 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, Xiaoyu Li, Y. G. Li, Z. J. Li, Z. X. Li, C. Liang, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, Y. P. Liao, J. Libby, A. Limphirat, D. X. Lin, T. Lin, B. J. Liu, B. X. Liu, C. Liu, C. X. 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. 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, 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, M. M. Ma, Q. M. Ma, R. Q. Ma, X. T. Ma, X. Y. Ma, Y. Ma, Y. M. Ma, F. E. Maas, M. Maggiora, S. Malde, 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, B. Moses, N. Yu. Muchnoi, J. Muskalla, Y. Nefedov, F. Nerling, 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, P. Patteri, 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, J. J. Qin, L. Q. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, Z. H. Qu, C. F. Redmer, K. J. Ren, A. Rivetti, M. Rolo, G. Rong, Ch. Rosner, S. N. Ruan, N. Salone, A. Sarantsev, Y. Schelhaas, 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, W. H. Shen, X. Y. Shen, B. A. Shi, H. C. Shi, J. L. Shi, J. Y. Shi, Q. Q. Shi, R. S. Shi, S. Y. Shi, X. Shi, J. J. Song, T. Z. Song, W. M. Song, Y. J. Song, S. Sosio, S. Spataro, F. Stieler, 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, 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. P. Wang, K. Wang, L. L. Wang, M. Wang, Meng 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. Wei, 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, Q. J. Xu, Q. N. Xu, W. Xu, W. L. Xu, X. P. Xu, Y. C. Xu, Z. P. 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, Tao Yang, Y. Yang, Y. F. Yang, Y. X. Yang, Yifan Yang, Z. W. Yang, Z. P. Yao, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, X. D. 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. Y. Zhang, J. Zhang, J. J. Zhang, J. L. Zhang, J. Q. 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, Shuihan Zhang, Shulei Zhang, X. D. Zhang, X. M. Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Y. M. Zhang, Yan Zhang, Yao Zhang, Z. D. Zhang, Z. H. Zhang, Z. L. Zhang, Z. Y. Zhang, G. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, R. P. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, W. J. Zheng, Y. H. Zheng, B. Zhong, X. Zhong, H. Zhou, J. Y. 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. Zhu, L. X. Zhu, S. H. Zhu, S. Q. Zhu, T. J. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, J. H. Zou, and J. Zu

Subjects
e +-e − Experiments, QCD, CP Violation, Dark Matter, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract With a sample of (10087 ± 44) × 106 J/ψ events accumulated with the BESIII detector, we analyze the decays η′ → π + π − l + l − (l = e, μ) via the process J/ψ → γη′. The branching fractions are measured to be B $$ \mathcal{B} $$ (η′ → π + π − e + e − ) = (2.45 ± 0.02(stat.) ± 0.08(syst.)) × 10 −3 and B $$ \mathcal{B} $$ (η′ → π + π − μ + μ − ) = (2.16 ± 0.12(stat.) ± 0.06(syst.)) × 10 −5, and the ratio is B η ′ → π + π − e + e − B η ′ → π + π − μ + μ − = 113.4 ± 0.9 stat . ± 3.7 syst . $$ \frac{\mathcal{B}\left({\eta}^{\prime}\to {\pi}^{+}{\pi}^{-}{e}^{+}{e}^{-}\right)}{\mathcal{B}\left({\eta}^{\prime}\to {\pi}^{+}{\pi}^{-}{\mu}^{+}{\mu}^{-}\right)}=113.4\pm 0.9\left(\textrm{stat}.\right)\pm 3.7\left(\textrm{syst}.\right) $$ . In addition, by combining the η′ → π + π − e + e − and η′ → π + π − μ + μ − decays, the slope parameter of the electromagnetic transition form factor is measured to be b η′ = 1.30 ± 0.19 (GeV/c 2) −2, which is consistent with previous measurements from BESIII and theoretical predictions from the VMD model. The asymmetry in the angle between the π + π − and l + l − decay planes, which has the potential to reveal the CP-violation originating from an unconventional electric dipole transition, is also investigated. The asymmetry parameters are determined to be A CP η ′ → π + π − e + e − = − 0.21 ± 0.73 stat . ± 0.01 syst . % $$ {\mathcal{A}}_{CP}\left({\eta}^{\prime}\to {\pi}^{+}{\pi}^{-}{e}^{+}{e}^{-}\right)=\left(-0.21\pm 0.73\left(\textrm{stat}.\right)\pm 0.01\left(\textrm{syst}.\right)\right)\% $$ and A CP η ′ → π + π − μ + μ − = 0.62 ± 4.71 stat . ± 0.08 syst . % $$ {\mathcal{A}}_{CP}\left({\eta}^{\prime}\to {\pi}^{+}{\pi}^{-}{\mu}^{+}{\mu}^{-}\right)=\left(0.62\pm 4.71\left(\textrm{stat}.\right)\pm 0.08\left(\textrm{syst}.\right)\right)\% $$ , implying that no evidence of CP-violation is observed at the present statistics. Finally, an axion-like particle is searched for via the decay η′ → π + π − a, a → e + e − , and upper limits of the branching fractions are presented for the mass assumptions of the axion-like particle in the range of 0 − 500 MeV/c 2.

Published
2024
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10. Qualification rate and associated factors regarding COVID-19 clinical skills training based on scenario simulation teaching to medical staffs in China: a hospital-based cross-sectional study

Author

Manyuan Cai, Yanping Chen, Fangting Luo, Yanqun Zheng, Ying Liu, Bing Xiao, Xiaoyan Wang, Lulu Sun, Yi Lin, Xianhu Zeng, Shuni Tan, Ke Liu, Yuanbo Gu, Jinghua Wang, Xianjia Ning, Jing Yuan, Min Wen, and Jing Cao

Subjects
Clinical skills training, Infectious diseases, Scenario Simulation, Education, Gender, Professional background, Special aspects of education, LC8-6691, Medicine
Abstract

Abstract Background The coronavirus disease (COVID-19) pandemic has accentuated the need for effective clinical skills training in infectious diseases. This study aimed to explore the influencing factors of infectious disease clinical skills training based on scenario simulation teaching for medical staff in China. Methods This hospital-based, cross-sectional study was conducted at the Third People’s Hospital of Shenzhen between March and December 2022. Scenario simulation teaching was applied, and factors such as gender, educational level, professional background, and previous experience were examined to determine their impact on qualification outcomes. Results The study included participants primarily between the ages of 20–40 years, with a higher proportion of women holding university degrees. Nurses and physicians were more likely to qualify, indicating the significance of professional backgrounds. Women showed a higher likelihood of qualifying than men and higher educational attainment correlated with better qualification rates. Prior experience with protective clothing in isolation wards was a significant determinant of successful qualification. Multivariate analysis underscored the influence of sex, education, and previous experience on training effectiveness. Conclusion Scenario simulation is an effective strategy for training clinical skills in treating infectious diseases. This study highlights the importance of considering sex, education, professional background, and prior experience when designing training programs to enhance the efficacy and relevance of infectious disease training.

Published
2024
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11. Measurement of e + e − → ωη′ cross sections at s $$ \sqrt{s} $$ = 2.000 to 3.080 GeV

Author

The BESIII collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, X. C. Ai, R. Aliberti, A. Amoroso, M. R. An, Q. An, Y. Bai, O. Bakina, I. Balossino, Y. Ban, 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, T. T. Chang, W. L. Chang, G. R. Che, 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, Y. Q. Chen, Z. J. Chen, W. S. Cheng, S. K. Choi, X. Chu, G. Cibinetto, S. C. Coen, 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, B. Ding, X. X. Ding, Y. Ding, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, M. C. Du, S. X. Du, Z. H. Duan, P. Egorov, Y. H. Y. Fan, 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, J. L. Fu, Y. W. 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, S. Gramigna, M. Greco, M. H. Gu, C. Y Guan, Z. L. Guan, A. Q. Guo, L. B. Guo, M. J. 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. 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, 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, J. Jackson, S. Jaeger, S. Janchiv, J. H. Jeong, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, X. Q. Jia, Z. K. Jia, H. J. Jiang, P. C. Jiang, S. S. Jiang, T. J. Jiang, X. S. Jiang, Y. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, T. Johansson, X. Kui, S. Kabana, N. Kalantar-Nayestanaki, X. L. Kang, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, A. Khoukaz, R. Kiuchi, R. Kliemt, O. B. Kolcu, B. Kopf, M. Kuessner, A. Kupsc, W. Kühn, J. J. Lane, P. Larin, A. Lavania, L. Lavezzi, T. T. Lei, 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, Hui Li, J. R. Li, J. S. Li, J. W. Li, K. L. Li, Ke Li, L. J Li, L. K. Li, Lei Li, M. H. Li, P. R. Li, Q. X. Li, S. X. Li, T. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Xiaoyu Li, Y. G. Li, Z. J. Li, C. Liang, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, Y. P. Liao, J. Libby, A. Limphirat, D. X. Lin, T. Lin, B. J. Liu, B. X. Liu, C. Liu, C. X. Liu, F. H. Liu, Fang Liu, Feng Liu, G. M. Liu, H. 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, 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. 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, J. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. Y. Ma, Y. Ma, Y. M. Ma, F. E. Maas, M. Maggiora, 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, J. Muskalla, 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, P. Patteri, Y. P. Pei, 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, C. F. Qiao, J. J. Qin, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, C. F. Redmer, K. J. Ren, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, S. N. Ruan, N. Salone, A. Sarantsev, Y. Schelhaas, 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, W. H. Shen, X. Y. Shen, B. A. Shi, H. C. Shi, J. L. Shi, J. Y. Shi, Q. Q. Shi, R. S. Shi, X. Shi, J. J. Song, T. Z. Song, W. M. Song, Y. J. Song, Y. X. Song, S. Sosio, S. Spataro, F. Stieler, 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. T. Sun, Y. X. Tan, C. J. Tang, G. Y. Tang, J. 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, S. J. Wang, B. Wang, B. L. Wang, Bo Wang, C. W. Wang, D. Y. Wang, F. Wang, H. J. Wang, H. P. Wang, J. P. Wang, K. Wang, L. L. Wang, M. Wang, Meng Wang, S. Wang, T. Wang, T. J. Wang, W. Wang, W. P. Wang, X. Wang, X. F. Wang, X. J. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. H. Wang, Y. N. Wang, Y. Q. Wang, Yaqian Wang, Yi Wang, Z. Wang, Z. L. Wang, Z. Y. Wang, Ziyi Wang, D. Wei, D. H. Wei, F. Weidner, S. P. Wen, C. W. Wenzel, 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. J. Wu, Z. Wu, L. Xia, X. M. Xian, 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, Q. J. Xu, Q. N. Xu, W. Xu, W. L. Xu, X. P. Xu, Y. C. Xu, Z. P. 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, Tao Yang, Y. Yang, Y. F. Yang, Y. X. Yang, Yifan Yang, Z. W. Yang, Z. P. Yao, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, X. D. 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. 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. H. Zhang, H. Q. Zhang, H. Y. Zhang, J. 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, Xuyan Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Yan Zhang, Yao Zhang, Z. H. Zhang, Z. L. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, W. J. Zheng, Y. H. Zheng, B. 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. Zhu, L. X. Zhu, S. H. Zhu, S. Q. Zhu, T. J. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, J. H. Zou, and J. Zu

Subjects
e +-e − Experiments, Particle and Resonance Production, Spectroscopy, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract We measured the Born cross sections for the process e + e − → ωη′ at 22 center-of-mass energies from 2.000 to 3.080 GeV with the BESIII detector at the BEPCII collider. We observed a resonant structure with a statistical significance of 9.6σ. A Breit-Wigner fit determines its mass to be M R = (2153 ± 30 ± 31) MeV/c 2 and its width to be Γ R = (167 ± 77 ± 7) MeV, where the first uncertainties are statistical and the second are systematic.

Published
2024
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12. Numerical study on the stimulation effect of boundary sealing and hot water injection in marine challenging gas hydrate extraction

Author

Shuaishuai Nie, Ke Liu, Kangtai Xu, Xiuping Zhong, Shixing Tang, Jian Song, Hongjing Zhang, Jiangfei Li, and Yafei Wang

Subjects
Gas hydrate, Open boundary, Reservoir stimulation, Methane leakage, Water control, Medicine, Science
Abstract

Abstract This study proposed a novel development mode combining boundary sealing and hot water injection to address the challenges of gas leakage, limited reservoir sensible heat, boundary water intrusion, and low productivity faced by challenging hydrate extraction, and the stimulation effect was numerically investigated with Shenhu hydrates as the geological background. The results showed that lower boundary permeability facilitated pressure propagation and achieved volumetric dissociation of hydrates, whereas insufficient formation energy resulted in substantial gas retention. Hot water injection was effective for stimulation, but open boundaries could not maintain the high injection pressure, leading to massive hot water losses and gas escapes. However, their combination achieved a synergistic stimulation like “1 + 1 > 2” because a piston water drive similar to secondary recovery in oil and gas development was formed. Relative to three-spot well patterns, the five-spot shortened the extraction cycle by 680 days and enhanced the gas-to-water ratio by 17%. Increasing injection pressure enhanced water yield more significantly while the improvement of gas yield was more significant by increasing hot water temperature. Overall, high-pressure and high-temperature injection was suggested for gas enhancement and water control. These findings provide important guidance for advancing the commercial development of challenging hydrates.

Published
2024
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17. Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference

Author

Huang, Haiyang, Ardalani, Newsha, Sun, Anna, Ke, Liu, Lee, Hsien-Hsin S., Sridhar, Anjali, Bhosale, Shruti, Wu, Carole-Jean, and Lee, Benjamin

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Hardware Architecture, Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Mixture-of-Experts (MoE) models have gained popularity in achieving state-of-the-art performance in a wide range of tasks in computer vision and natural language processing. They effectively expand the model capacity while incurring a minimal increase in computation cost during training. However, deploying such models for inference is difficult due to their large size and complex communication pattern. In this work, we provide a characterization of two MoE workloads, namely Language Modeling (LM) and Machine Translation (MT) and identify their sources of inefficiencies at deployment. We propose three optimization techniques to mitigate sources of inefficiencies, namely (1) Dynamic gating, (2) Expert Buffering, and (3) Expert load balancing. We show that dynamic gating improves maximum throughput by 6.21-11.23$\times$ for LM, 5.75-10.98$\times$ for MT Encoder and 2.58-5.71$\times$ for MT Decoder. It also reduces memory usage by up to 1.36$\times$ for LM and up to 1.1$\times$ for MT. We further propose Expert Buffering, a new caching mechanism that only keeps hot, active experts in GPU memory while buffering the rest in CPU memory. This reduces static memory allocation by up to 1.47$\times$. We finally propose a load balancing methodology that provides additional scalability to the workload.

Published
2023

18. Effects of deformation temperatures on microstructures, aging behaviors and mechanical properties of Mg-Gd-Er-Zr alloys fabricated by hard-plate rolling

Author

Ke Liu, Dalong Hu, Feng Lou, Zijian Yu, Shubo Li, Xian Du, and Wenbo Du

Subjects
Mg-Gd-Er-Zr sheets, Age hardening response, Precipitates, Mechanical properties, Mining engineering. Metallurgy, TN1-997
Abstract

In this investigation, a high-strength Mg-12Gd-1.0Er-0.5Zr (wt.%) alloy sheet was produced by hot extrusion (HE) and subsequent hard-plate rolling (HPR) at different temperatures. The results indicate that the microstructures of these final-rolled sheets are inhomogeneous, mainly including coarse deformed grains and dynamic recrystallized (DRXed) grains, and the volume fraction of these coarse deformed grains increases as the rolling temperature increases. Thus, more DRXed grains can be found in R-385 °C sheet, resulting in a smaller average grain size and weaker basal texture, while the biggest grains and the highest strong basal texture are present in R-450 °C sheet. Amounts of dynamic precipitation of β phases which are mainly determined by the rolling temperature are present in these sheets, and its precipitation can consume the content of Gd solutes in the matrix. As a result, the lowest number density of β phase in R-450 °C sheet is beneficial to modify the age hardening response. Thus, the R-450 °C sheet displays the best age hardening response because of a severe traditional precipitation of β' (more) and βΗ /βΜ (less) precipitates, resulting in a sharp improvement in strength, i.e. ultimate tensile strength (UTS) of ∼ 518 ± 17 MPa and yield strength (YS) of ∼ 438±18 MPa. However, the elongation (EL) of this sheet reduces greatly, and its value is ∼ 2.7 ± 0.3%. By contrasting, the EL of the peak-aging R-385 °C sheet keeps better, changing from ∼ 4.9 ± 1.2% to ∼ 4.8 ± 1.4% due to a novel dislocation-induced chain-like precipitate which is helpful to keep good balance between strength and ductility.

Published
2024
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19. Germination responses of Lens Culiunaris L. seeds to osmotic potentials at cardinal temperatures using hydrothermal time model

Author

Ibrar Ullah, Sami Ullah, Fazal Amin, Jehad S. Al-Hawadi, Mohammad K. Okla, Ibrahim A. Alaraidh, Hamada AbdElgawad, Ke Liu, Matthew Tom Harrison, Shah Saud, Shah Hassan, Taufiq Nawaz, Mo Zhu, Haitao Liu, and Shah Fahad

Subjects
Lentil, Hydrothermal time model, Germination, Osmotic potential, Temperature, Botany, QK1-989
Abstract

Abstract Background Lentil is a significant legume that are consumed as a staple food and have a significant economic impact around the world. The purpose of the present research on lentil was to assess the hydrothermal time model’s capacity to explain the dynamics of Lens culinaris L. var. Markaz-09 seed germination, as well as to ascertain the germination responses at various sub-optimal temperatures (T) and water potentials (Ψ). In order to study lentil seed germination (SG) behavior at variable water potentials (Ψs) and temperatures (Ts). A lab experiment employing the hydrothermal time model was created. Seeds were germinated at six distinct temperatures: 15 0С, 20 0С, 25 0С, 30 0С, 35 0С, and 40 0С, with five Ψs of 0, -0.3, -0.6, -0.9, and − 1.2 MPa in a PEG-6000 (Polyethylene glycol 6000) solution. Results The results indicated that the agronomic parameters like Germination index (GI), Germination energy (GE), Timson germination index (TGI), were maximum in 25 0C at (-0.9 MPa) and lowest at 40 0C in 0 MPa. On other hand, mean germination time (MGT) value was highest at 15 0C in -1.2 MPa and minimum at 40 0C in (-0.6 MPa) while Mean germination rate (MGR) was maximum at 40 0C in (0 MPa) and minimum at 15 0C in (-0.6 MPa). Conclusions The HTT model eventually defined the germination response of Lens culinaris L. var. Markaz-09 (Lentil) for all Ts and Ψs, allowing it to be employed as a predictive tool in Lens culinaris L. var. Markaz-09 (Lentil) seed germination simulation models.

Published
2024
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20. Measurement of absolute branching fractions of D s + $$ {\textrm{D}}_{\textrm{s}}^{+} $$ hadronic decays

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, 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, 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, Z. L. 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, 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, 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, P. Larin, 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, Ke 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. Z. Li, Xiaoyu Li, Y. G. Li, Z. J. Li, Z. X. Li, C. Liang, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. 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. 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. 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, 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, M. M. Ma, Q. M. Ma, R. Q. Ma, X. T. Ma, X. Y. Ma, 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, P. Patteri, 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. 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, 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, 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, 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, Meng 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. C. Xu, Z. P. 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, Tao Yang, Y. Yang, Y. F. Yang, Y. X. Yang, Yifan Yang, Z. W. Yang, Z. P. Yao, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, X. D. Yu, Y. C. Yu, C. Z. Yuan, J. Yuan, L. Yuan, S. C. Yuan, Y. Yuan, Y. J. 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, Shuihan Zhang, Shulei Zhang, X. D. Zhang, X. M. Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Y. M. Zhang, Yan Zhang, Yao Zhang, Z. D. Zhang, Z. H. Zhang, Z. L. Zhang, Z. Y. Zhang, Z. Z. Zhang, G. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling 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, J. Zhu, K. Zhu, K. J. Zhu, K. S. Zhu, L. Zhu, L. X. Zhu, S. H. Zhu, S. Q. Zhu, T. J. Zhu, W. D. Zhu, Y. C. Zhu, Z. A. Zhu, J. H. Zou, and J. Zu

Subjects
Branching fraction, Charm Physics, CP Violation, e +-e − Experiments, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract Using e + e − collision data collected at the BESIII detector at center-of-mass energies between 4.128 and 4.226 GeV, corresponding to an integrated luminosity of 7.33 fb −1, we determine the absolute branching fractions of fifteen hadronic D s + $$ {D}_s^{+} $$ decays with a double-tag technique. In particular, we make precise measurements of the branching fractions B D s + → K + K − π + = 5.49 ± 0.04 ± 0.07 % $$ \mathcal{B}\left({D}_s^{+}\to {K}^{+}{K}^{-}{\pi}^{+}\right)=\left(5.49\pm 0.04\pm 0.07\right)\% $$ , B D s + → K S 0 K + = 1.50 ± 0.01 ± 0.01 % $$ \mathcal{B}\left({D}_s^{+}\to {K}_S^0{K}^{+}\right)=\left(1.50\pm 0.01\pm 0.01\right)\% $$ and B D s + → K + K − π + π 0 = 5.50 ± 0.05 ± 0.11 % $$ \mathcal{B}\left({D}_s^{+}\to {K}^{+}{K}^{-}{\pi}^{+}{\pi}^0\right)=\left(5.50\pm 0.05\pm 0.11\right)\% $$ , where the first uncertainties are statistical and the second ones are systematic. The CP asymmetries in these decays are also measured and all are found to be compatible with zero.

Published
2024
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21. Salicylic acid and Tocopherol improve wheat (Triticum aestivum L.) Physio-biochemical and agronomic features grown in deep sowing stress: a way forward towards sustainable production

Author

Saleha Saeed, Sami Ullah, Fazal Amin, Jehad S. Al-Hawadi, Mohammad K. Okla, Ibrahim A. Alaraidh, Hamada AbdElgawad, Ke Liu, Matthew Tom Harrison, Shah Saud, Shah Hassan, Taufiq Nawaz, Mo Zhu, Haitao Liu, Mushtaq Ahmad Khan, and Shah Fahad

Subjects
Salicylic acid, Tocopherol, Physio-biochemical, Deep sowing, Triticum aestivum L, Botany, QK1-989
Abstract

Abstract Background The rate of germination and other physiological characteristics of seeds that are germinating are impacted by deep sowing. Based on the results of earlier studies, conclusions were drawn that deep sowing altered the physio-biochemical and agronomic characteristics of wheat (Triticum aestivum L.). Results In this study, seeds of wheat were sown at 2 (control) and 6 cm depth and the impact of exogenously applied salicylic acid and tocopherol (Vitamin-E) on its physio-biochemical and agronomic features was assessed. As a result, seeds grown at 2 cm depth witnessed an increase in mean germination time, germination percentage, germination rate index, germination energy, and seed vigor index. In contrast, 6 cm deep sowing resulted in negatively affecting all the aforementioned agronomic characteristics. In addition, deep planting led to a rise in MDA, glutathione reductase, and antioxidants enzymes including APX, POD, and SOD concentration. Moreover, the concentration of chlorophyll a, b, carotenoids, proline, protein, sugar, hydrogen peroxide, and agronomic attributes was boosted significantly with exogenously applied salicylic acid and tocopherol under deep sowing stress. Conclusions The results of the study showed that the depth of seed sowing has an impact on agronomic and physio-biochemical characteristics and that the negative effects of deep sowing stress can be reduced by applying salicylic acid and tocopherol to the leaves.

Published
2024
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22. Modulate stress distribution with bio-inspired irregular architected materials towards optimal tissue support

Author

Yingqi Jia, Ke Liu, and Xiaojia Shelly Zhang

Subjects
Science
Abstract

Abstract Natural materials typically exhibit irregular and non-periodic architectures, endowing them with compelling functionalities such as body protection, camouflage, and mechanical stress modulation. Among these functionalities, mechanical stress modulation is crucial for homeostasis regulation and tissue remodeling. Here, we uncover the relationship between stress modulation functionality and the irregularity of bio-inspired architected materials by a generative computational framework. This framework optimizes the spatial distribution of a limited set of basic building blocks and uses these blocks to assemble irregular materials with heterogeneous, disordered microstructures. Despite being irregular and non-periodic, the assembled materials display spatially varying properties that precisely modulate stress distribution towards target values in various control regions and load cases, echoing the robust stress modulation capability of natural materials. The performance of the generated irregular architected materials is experimentally validated with 3D printed physical samples — a good agreement with target stress distribution is observed. Owing to its capability to redirect loads while keeping a proper amount of stress to stimulate bone repair, we demonstrate the potential application of the stress-programmable architected materials as support in orthopedic femur restoration.

Published
2024
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23. Search for ∆S = 2 nonleptonic hyperon decays Ω − → Σ0 π − and Ω − → nK −

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, 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, P. Larin, 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, 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, L. Z. 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, M. M. Ma, Q. M. Ma, R. Q. Ma, T. Ma, X. T. Ma, X. Y. Ma, 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, P. Patteri, 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. 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, 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, 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. C. Xu, Z. P. 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, T. Yang, Y. Yang, Y. F. Yang, Y. X. Yang, Z. W. Yang, Z. P. Yao, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. 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, 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, J. Zhu, K. Zhu, K. J. Zhu, K. S. Zhu, L. Zhu, L. X. Zhu, S. H. Zhu, S. Q. Zhu, T. J. Zhu, W. D. Zhu, Y. C. Zhu, Z. A. Zhu, J. H. Zou, and J. Zu

Subjects
Beyond Standard Model, e +-e − Experiments, Rare Decay, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract Using (27.12 ± 0.14) × 108 ψ(3686) events collected by the BESIII detector at the center-of-mass energy of s $$ \sqrt{s} $$ = 3.686 GeV, we search for the first time for two nonleptonic hyperon decays that change strangeness by two units, Ω − → Σ0 π − and Ω − → nK − . No significant signal is observed. The upper limits on their decay branching fractions are determined to be B $$ \mathcal{B} $$ (Ω − → Σ0 π − ) < 5.4 × 10 −4 and B $$ \mathcal{B} $$ (Ω − → nK − ) < 2.4 × 10 −4 at the 90% confidence level.

Published
2024
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24. Engineering non-conventional yeast Rhodotorula toruloides for ergothioneine production

Author

Ke Liu, Gedan Xiang, Lekai Li, Tao Liu, Jie Ke, Liangbin Xiong, Dongzhi Wei, and Fengqing Wang

Subjects
Ergothioneine, Rhodotorula toruloides, CRISPR-assisted Cre recombination, Metabolic engineering, High-throughput screening, Biotechnology, TP248.13-248.65, Fuel, TP315-360
Abstract

Abstract Background Ergothioneine (EGT) is a distinctive sulfur-containing histidine derivative, which has been recognized as a high-value antioxidant and cytoprotectant, and has a wide range of applications in food, medical, and cosmetic fields. Currently, microbial fermentation is a promising method to produce EGT as its advantages of green environmental protection, mild fermentation condition, and low production cost. However, due to the low-efficiency biosynthetic process in numerous cell factories, it is still a challenge to realize the industrial biopreparation of EGT. The non-conventional yeast Rhodotorula toruloides is considered as a potential candidate for EGT production, thanks to its safety for animals and natural ability to synthesize EGT. Nevertheless, its synthesis efficiency of EGT deserves further improvement. Results In this study, out of five target wild-type R. toruloides strains, R. toruloides 2.1389 (RT1389) was found to accumulate the highest EGT production, which could reach 79.0 mg/L at the shake flask level on the 7th day. To achieve iterative genome editing in strain RT1389, CRISPR-assisted Cre recombination (CACR) method was established. Based on it, an EGT-overproducing strain RT1389-2 was constructed by integrating an additional copy of EGT biosynthetic core genes RtEGT1 and RtEGT2 into the genome, the EGT titer of which was 1.5-fold increase over RT1389. As the supply of S-adenosylmethionine was identified as a key factor determining EGT production in strain RT1389, subsequently, a series of gene modifications including S-adenosylmethionine rebalancing were integrated into the strain RT1389-2, and the resulting mutants were rapidly screened according to their EGT production titers with a high-throughput screening method based on ergothionase. As a result, an engineered strain named as RT1389-3 was selected with a production titer of 267.4 mg/L EGT after 168 h in a 50 mL modified fermentation medium. Conclusions This study characterized the EGT production capacity of these engineered strains, and demonstrated that CACR and high-throughput screening method allowed rapid engineering of R. toruloides mutants with improved EGT production. Furthermore, this study provided an engineered RT1389-3 strain with remarkable EGT production performance, which had potential industrial application prospects.

Published
2024
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25. Measurement of Born cross section of e + e − → Σ + Σ ¯ − $$ {e}^{+}{e}^{-}\to {\Sigma}^{+}{\overline{\Sigma}}^{-} $$ at center-of-mass energies between 3.510 and 4.951 GeV

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, 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, 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, Z. L. 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, 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, 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, P. Larin, 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, Ke 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. Z. Li, Xiaoyu Li, Y. G. Li, Z. J. Li, Z. X. Li, C. Liang, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. 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. 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. 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, 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, M. M. Ma, Q. M. Ma, R. Q. Ma, X. T. Ma, X. Y. Ma, 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, P. Patteri, 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. 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, 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, 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, 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, Meng 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. C. Xu, Z. P. 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, Tao Yang, Y. Yang, Y. F. Yang, Y. X. Yang, Yifan Yang, Z. W. Yang, Z. P. Yao, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, X. D. Yu, Y. C. Yu, C. Z. Yuan, J. Yuan, L. Yuan, S. C. Yuan, Y. Yuan, Y. J. 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, Shuihan Zhang, Shulei Zhang, X. D. Zhang, X. M. Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Y. M. Zhang, Yan Zhang, Yao Zhang, Z. D. Zhang, Z. H. Zhang, Z. L. Zhang, Z. Y. Zhang, Z. Z. Zhang, G. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling 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, J. Zhu, K. Zhu, K. J. Zhu, K. S. Zhu, L. Zhu, L. X. Zhu, S. H. Zhu, S. Q. Zhu, T. J. Zhu, W. D. Zhu, Y. C. Zhu, Z. A. Zhu, J. H. Zou, and J. Zu

Subjects
e +-e − Experiments, QCD, Branching fraction, Electroweak Interaction, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract Using 24.1 fb −1 of e + e − collision data collected with the BESIII detector at the BEPCII collider, the Born cross sections and effective form factors of the e + e − → Σ + Σ ¯ − $$ {e}^{+}{e}^{-}\to {\Sigma}^{+}{\overline{\Sigma}}^{-} $$ reaction are measured. The measurements are performed at center-of-mass energies ranging from 3.510 to 4.951 GeV. No significant evidence for the decay of the charmonium(-like) states, ψ(3770), ψ(4040), ψ(4160), Y(4230), Y(4360), ψ(4415), and Y(4660), into a Σ + Σ ¯ − $$ {\Sigma}^{+}{\overline{\Sigma}}^{-} $$ final state is observed. Consequently, upper limits for the products of the branching fractions and the electronic partial widths at the 90% confidence level are reported for these decays.

Published
2024
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26. An efficient visual servo tracker for herd monitoring by UAV

Author

Wei Luo, Guoqing Zhang, Quanqin Shao, Yongxiang Zhao, Dongliang Wang, Xiongyi Zhang, Ke Liu, Xiaoliang Li, Jiandong Liu, Penggang Wang, Lin Li, Guanwu Wang, Fulong Wang, and Zhongde Yu

Subjects
Medicine, Science
Abstract

Abstract It is a challenging and meaningful task to carry out UAV-based livestock monitoring in high-altitude (more than 4500 m on average) and cold regions (annual average – 4 °C) on the Qinghai Tibet Plateau. The purpose of artificial intelligence (AI) is to execute automated tasks and to solve practical problems in actual applications by combining the software technology with the hardware carrier to create integrated advanced devices. Only in this way, the maximum value of AI could be realized. In this paper, a real-time tracking system with dynamic target tracking ability is proposed. It is developed based on the tracking-by-detection architecture using YOLOv7 and Deep SORT algorithms for target detection and tracking, respectively. In response to the problems encountered in the tracking process of complex and dense scenes, our work (1) Uses optical flow to compensate the Kalman filter, to solve the problem of mismatch between the target bounding box predicted by the Kalman filter (KF) and the input when the target detection in the current frame is complex, thereby improving the prediction accuracy; (2) Using a low confidence trajectory filtering method to reduce false positive trajectories generated by Deep SORT, thereby mitigating the impact of unreliable detection on target tracking. (3) A visual servo controller has been designed for the Unmanned Aerial Vehicle (UAV) to reduce the impact of rapid movement on tracking and ensure that the target is always within the field of view of the UAV camera, thereby achieving automatic tracking tasks. Finally, the system was tested using Tibetan yaks on the Qinghai Tibet Plateau as tracking targets, and the results showed that the system has real-time multi tracking ability and ideal visual servo effect in complex and dense scenes.

Published
2024
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27. Observation of ψ(3686) → Ω − K + Ξ ¯ 0 $$ {\varOmega}^{-}{K}^{+}{\overline{\Xi}}^0 $$ + c.c.

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, 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, X. Chu, 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, Z. L. 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, 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, T. Hu, Y. Hu, G. S. Huang, K. X. Huang, L. Q. Huang, X. T. Huang, Y. P. 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, P. Larin, L. Lavezzi, T. T. Lei, 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, Hui Li, J. R. Li, J. S. Li, Ke 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. Z. Li, Xiaoyu Li, Y. G. Li, Z. J. Li, Z. X. Li, C. Liang, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. 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. 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. 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, 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, M. M. Ma, Q. M. Ma, R. Q. Ma, X. T. Ma, X. Y. Ma, Y. Ma, Y. M. Ma, F. E. Maas, M. Maggiora, S. Malde, 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, 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, P. Patteri, 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, 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, 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. 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, 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, 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, Meng 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. Wei, 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, Q. J. Xu, Q. N. Xu, W. Xu, W. L. Xu, X. P. Xu, Y. C. Xu, Z. P. 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, Tao Yang, Y. Yang, Y. F. Yang, Y. X. Yang, Yifan Yang, Z. W. Yang, Z. P. Yao, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, X. D. Yu, Y. C. Yu, C. Z. Yuan, J. Yuan, L. Yuan, S. C. Yuan, Y. Yuan, Y. J. 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. Y. Zhang, J. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. X. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, L. M. Zhang, Lei Zhang, P. Zhang, R. Y. Zhang, Shuihan Zhang, Shulei Zhang, X. D. Zhang, X. M. Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Y. M. Zhang, Yan Zhang, Yao Zhang, Z. D. Zhang, Z. H. Zhang, Z. L. Zhang, Z. Y. Zhang, Z. Z. Zhang, G. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling 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, 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, J. Zhu, K. Zhu, K. J. Zhu, L. Zhu, L. X. Zhu, S. H. Zhu, S. Q. Zhu, T. J. Zhu, W. D. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, J. H. Zou, and J. Zu

Subjects
Branching fraction, e +-e − Experiments, QCD, Quarkonium, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract Using (27.12 ± 0.14) × 108 ψ(3686) events collected with the BESIII detector at BEPCII, the decay of ψ(3686) → Ω − K + Ξ ¯ 0 $$ {\varOmega}^{-}{K}^{+}{\overline{\Xi}}^0 $$ + c.c. is observed for the first time. The branching fraction of this decay is measured to be B ψ 3686 → Ω − K + Ξ ¯ 0 + c . c . $$ {\mathcal{B}}_{\psi (3686)\to {\varOmega}^{-}{K}^{+}{\overline{\Xi}}^0+\textrm{c}.\textrm{c}.} $$ = (2.78 ± 0.40 ± 0.18) × 10 −6, where the first uncertainty is statistical and the second is systematic. Possible baryon excited states are searched for in this decay, but no evident intermediate state is observed with the current sample size.

Published
2024
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28. Paired electrocatalysis unlocks cross-dehydrogenative coupling of C(sp3)-H bonds using a pentacoordinated cobalt-salen catalyst

Author

Ke Liu, Mengna Lei, Xin Li, Xuemei Zhang, Ying Zhang, Weigang Fan, Man-Bo Li, and Sheng Zhang

Subjects
Science
Abstract

Abstract Cross-dehydrogenative coupling of C(sp3)-H bonds is an ideal approach for C(sp3)-C(sp3) bond construction. However, conventional approaches mainly rely on a single activation mode by either stoichiometric oxidants or electrochemical oxidation, which would lead to inferior selectivity in the reaction between similar C(sp3)-H bonds. Herein we describe our development of a paired electrocatalysis strategy to access an unconventional selectivity in the cross-dehydrogenative coupling of alcoholic α C(sp3)-H with allylic (or benzylic) C-H bonds, which combines hydrogen evolution reaction catalysis with hydride transfer catalysis. To maximize the synergistic effect of the catalyst combinations, a HER catalyst pentacoordinated Co-salen is disclosed. The catalyst displays a large redox-potential gap (1.98 V) and suitable redox potential. With the optimized catalyst combination, an electrochemical cross-dehydrogenative coupling protocol features unconventional chemoselectivity (C-C vs. C-O coupling), excellent functional group tolerance (84 examples), valuable byproduct (hydrogen), and high regio- and site-selectivity. A plausible reaction mechanism is also proposed to rationalize the experimental observations.

Published
2024
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29. TFCP2L1 as a potential diagnostic gene biomarker of Keloid given its association with immune cells-a study based on machine learning and RNA sequence

Author

Jia Huang, Yiyi Gong, Jui-Ming Lin, Haowei Lu, Jun Chen, Ke Liu, Jinran Lin, Wenyu Wu, and Xiaobo Zhou

Subjects
Big data analytics, Machine learning, Diagnostic gene biomarker, Keloid, Engineering (General). Civil engineering (General), TA1-2040
Abstract

Keloids represent a specific type of dermal tumor, where delayed treatment greatly heighten risks of recurrence. This study thus seeks to identify key genes for early keloid diagnosis and compare how immune cell infiltration between keloid lesion skin (KLS) and keloid adjacent non-lesional skin (KNL) differ. Utilizing two GEO datasets, which encompassed KLS (n=8) and KNL (n=6) samples, 564 differentially expressed genes (DEGs) were identified, with a primary emphasis on inflammation- and fibrosis-related pathways. The gene TFCP2L1 was pinpointed from the intersection of LASSO and SVM-RFE algorithms, exhibiting downregulation in KLS when juxtaposed with KNL. To aid prognosis and identification of potential immunotherapy targets, the CIBERSORT algorithm was employed to assess prelative proportions of immune cells. In the KNL samples, there was an observed increase in follicular helper T cells, activated NK cells, and activated dendritic cells. Conversely, M1 macrophages were elevated in KLS samples. TFCP2L1 exhibited a positive correlation with activated NK cells and activated dendritic cells, while it showed a negative correlation with M1macrophages. These findings highlight the intertwined roles of TFCP2L1 and immune cell infiltration, lending to TFCP2L1’s potential as a diagnostic biomarker for keloids and highlights how TFCP2L1 might influence keloid development through immune cell populations.

Published
2024
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30. Data Leakage via Access Patterns of Sparse Features in Deep Learning-based Recommendation Systems

Author

Hashemi, Hanieh, Xiong, Wenjie, Ke, Liu, Maeng, Kiwan, Annavaram, Murali, Suh, G. Edward, and Lee, Hsien-Hsin S.

Subjects
Computer Science - Computational Engineering, Finance, and Science, Computer Science - Cryptography and Security, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Machine Learning
Abstract

Online personalized recommendation services are generally hosted in the cloud where users query the cloud-based model to receive recommended input such as merchandise of interest or news feed. State-of-the-art recommendation models rely on sparse and dense features to represent users' profile information and the items they interact with. Although sparse features account for 99% of the total model size, there was not enough attention paid to the potential information leakage through sparse features. These sparse features are employed to track users' behavior, e.g., their click history, object interactions, etc., potentially carrying each user's private information. Sparse features are represented as learned embedding vectors that are stored in large tables, and personalized recommendation is performed by using a specific user's sparse feature to index through the tables. Even with recently-proposed methods that hides the computation happening in the cloud, an attacker in the cloud may be able to still track the access patterns to the embedding tables. This paper explores the private information that may be learned by tracking a recommendation model's sparse feature access patterns. We first characterize the types of attacks that can be carried out on sparse features in recommendation models in an untrusted cloud, followed by a demonstration of how each of these attacks leads to extracting users' private information or tracking users by their behavior over time.

Published
2022

31. DisaggRec: Architecting Disaggregated Systems for Large-Scale Personalized Recommendation

Author

Ke, Liu, Zhang, Xuan, Lee, Benjamin, Suh, G. Edward, and Lee, Hsien-Hsin S.

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Deep learning-based personalized recommendation systems are widely used for online user-facing services in production datacenters, where a large amount of hardware resources are procured and managed to reliably provide low-latency services without disruption. As the recommendation models continue to evolve and grow in size, our analysis projects that datacenters deployed with monolithic servers will spend up to 12.4x total cost of ownership (TCO) to meet the requirement of model size and complexity over the next three years. Moreover, through in-depth characterization, we reveal that the monolithic server-based cluster suffers resource idleness and wastes up to 30% TCO by provisioning resources in fixed proportions. To address this challenge, we propose DisaggRec, a disaggregated system for large-scale recommendation serving. DisaggRec achieves the independent decoupled scaling-out of the compute and memory resources to match the changing demands from fast-evolving workloads. It also improves system reliability by segregating the failures of compute nodes and memory nodes. These two main benefits from disaggregation collectively reduce the TCO by up to 49.3%. Furthermore, disaggregation enables flexible and agile provisioning of increasing hardware heterogeneity in future datacenters. By deploying new hardware featuring near-memory processing capability, our evaluation shows that the disaggregated cluster achieves 21%-43.6% TCO savings over the monolithic server-based cluster across a three-year span of model evolution.

Published
2022

32. Bidirectional association identified between synovitis and knee and hand osteoarthritis: a general population-based studyResearch in context

Author

Ting Jiang, Qianlin Weng, Ke Liu, Hongyi He, Yuqing Zhang, Weiya Zhang, Michael Doherty, Junqing Xie, Tuo Yang, Jiatian Li, Zidan Yang, Qiu Chen, Huizhong Long, Yilun Wang, Jie Wei, Guanghua Lei, and Chao Zeng

Subjects
Osteoarthritis, Synovitis, Incidence, General population, Public aspects of medicine, RA1-1270
Abstract

Summary: Background: Synovitis has long been considered a common and modifiable inflammatory feature of osteoarthritis (OA), but current disease-modifying anti-inflammatory treatments appear ineffective in OA clinical trials. Elucidating the temporal relationship between synovitis and OA could provide insight into the role of synovitis in OA. Methods: We conducted a prospective cohort study based on the baseline and three-year follow-up data from the Xiangya Osteoarthritis (XO) Study. We assessed bidirectional associations between ultrasound-detected synovitis and radiographic and symptomatic OA at knee and hand sites using generalized estimating equations. Additionally, we performed bidirectional Mendelian randomization (MR) analyses to test these hypotheses utilising whole-genome sequencing data in the XO population. Age, sex, body mass index, smoking, alcohol consumption, educational level, physical activity, and joint injury history were adjusted for these analyses. Findings: A total of 2211, 2420, 2280, and 2600 participants were enrolled for analyses of radiographic knee OA (RKOA), symptomatic knee OA (SKOA), radiographic hand OA (RHOA) and symptomatic hand OA (SHOA), respectively. The baseline synovitis (i.e., with synovitis vs. without synovitis) was associated with the incident RKOA (76/277 vs. 557/3674 knees), SKOA (49/387 vs. 287/4213 knees), RHOA (171/358 vs. 686/3664 hands) and SHOA (35/689 vs. 76/4327 hands), with adjusted odds ratio (aORs) of 2.2 (95% CI 1.7–3.1), 2.0 (1.3–2.9), 3.4 (2.7–4.4), and 2.4 (1.5–3.8), respectively. The baseline RKOA (with OA vs. without OA: 409/1246 vs. 481/3758 knees), SKOA (200/576 vs. 675/4356 knees), RHOA (192/778 vs. 410/3723 hands), and SHOA (41/162 vs. 548/4285 hands) were also associated with the incident synovitis, with aORs of 3.4 (95% CI 2.9–4.1), 2.7 (2.1–3.4), 2.3 (1.8–2.9) and 1.9 (1.2–2.8), respectively. These bidirectional associations were stronger when more active synovitis was compared with the reference group (all P

Published
2024
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33. Probabilistic analysis of drought impact on wheat yield and climate change implications

Author

Bin Wang, Linchao Li, Puyu Feng, Chao Chen, Jing-Jia Luo, Andréa S. Taschetto, Matthew Tom Harrison, Ke Liu, De Li Liu, Qiang Yu, and Xiaowei Guo

Subjects
Wheat yield, SPEI, Drought threshold, Copula functions, Climate change, Meteorology. Climatology, QC851-999
Abstract

Drought is projected to intensify under warming climate and will continuously threaten global food security. Assessing the risk of yield loss due to drought is key to developing effective agronomic options for farmers and policymakers. However, little has been known about determining the likelihood of reduced crop yield under different drought conditions and defining thresholds that trigger yield loss at the regional scale in Australia. Here, we estimated the dependence of yield variation on drought conditions and identified drought thresholds for 12 Australia's key wheat producing regions with historical yield data by developing bivariate models based on copula functions. These identified drought thresholds were used to investigate drought statistics under climate change with an ensemble of 36 climate models from Coupled Model Intercomparison Project Phase 6 (CMIP6). We found that drought-induced yield loss was region-specific. The drought thresholds leading to the same magnitude of wheat yield reduction were smaller in regions of southern Queensland and larger in Western Australia mainly due to different climate and soil conditions. Drought will be more frequent and affect larger areas under future warming climates. Based on our results, we advocate for more effective crop management options, particularly in regions where wheat yield is vulnerable to drought in Australia. This will mitigate potential drought impacts on crop production and safeguard global food security.

Published
2024
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34. Achieving sustainable rice production through nitrogen-potassium harmony for enhanced economic and environmental gains

Author

Jun Deng, Ke Liu, Xin Xiong, Tajamul Hussain, Liying Huang, Peter de Voil, Matthew Tom Harrison, Xiaohai Tian, and Yunbo Zhang

Subjects
Hybrid rice, Nitrogen use efficiency, GHG emissions, Net ecosystem economic benefits, Agriculture (General), S1-972, Agricultural industries, HD9000-9495
Abstract

In the quest for sustainable, high-yield crop production, achieving the optimal balance between nitrogen (N) and potassium (K) stands as a pivotal goal. We carried out a 3-year field experiment to evaluate the impacts of the combined application of three N rates (90, 120,180 kg N ha−1) and three K rates (120, 160, 210 kg K2O ha−1) on rice yield, fertilizer use efficiency, greenhouse gas (GHG) emissions, global warming potential (GWP), GHG intensity (GHGI), and net ecosystem economic benefits (NEEB) in rice paddy. Our results showed that increasing K under the same N treatment proves beneficial for yield gains (average increase of 4.8 %). Such beneficial effect is also reflected in different N treatments, evidenced by the comparable grain yields between N120 × K160 (9.1 t ha−1) and N180×K120 (9.2 t ha−1). Increasing K significantly enhanced N use efficiency (NUE) through the stimulation of NR, GS/GOGAT, and GDH enzyme activities. This enhancement, along with the strengthened radiation use efficiency (4.7 %), contributed to an overall improvement in grain yield. Compared with N180×K120, both rice varieties, under N120×K160 treatment, showed higher NUE with a 47.6 % increase in PFPN, 12.1 % in NHI, 7.6 % in NUEg, and 9.5 % in NUEb, respectively. Higher NUE also reduced GHGI and improved NEEB. Compared with N180 ×K120 treatment, the GWP and GHGI under N120×K160 treatment decreased by 32.7 % and 31.0 %, while the NEEB increased by $31 ha−1. The composite sustainability scores suggested that the N120×K160 treatment was generally more sustainable compared with other treatments. These findings underscore the significance of optimizing N and K application ratios in rice paddy cultivation, not only for maximizing yields and nutrient use efficiency but also for reducing greenhouse gas emissions and enhancing economic sustainability, ultimately promoting a more environmentally and economically responsible approach to rice farming.

Published
2024
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35. Burgeoning food demand outpaces sustainable water supply in China

Author

Shanheng Shi, Shiwei Zhou, Yongdeng Lei, Matthew Tom Harrison, Ke Liu, Fu Chen, and Xiaogang Yin

Subjects
Blue water footprint, Water boundary, Water security, Food security, Agriculture (General), S1-972, Agricultural industries, HD9000-9495
Abstract

China’s agricultural sector has long realized innovation to meet burgeoning food demand, yet often innovation has occurred without concurrent consideration of trade-offs on blue water security. We contend that food security and blue water security should be given equal priority if sustainable production and consumption policies are to be defined. Here, we quantify the interplay between blue water and food security in China from 1990 to 2020 using blue water footprint (BWF) and blue water boundary as lenses. We find that national agri-food BWF has grown over time, being only 4 % below the sustainability boundary in 2020, and with the number of provinces with unsustainable system states increasing from nine in 1990s to 17 in 2010s. While blue water security and minimum food security have been achieved since 2012, the food consumption BWF has surpassed national food production and the BWF boundary by 32 % and 26 % in 2020, respectively. Assuming trends continue ceteris paribus, we project that China’s BWF will transgress the sustainability boundary by 2025. Even so, with appropriate intervention in production, supply chains, and consumption guidelines, the food demand/water supply conundrum could be equitable and sustainable, notwithstanding higher food consumption in 2030. This study clearly addressed the contradictions potential balancing between blue water and food security in China at the national scale, and we articulate a simple, scalable approach for nations facing water scarcity to deconstruct drivers of, and develop alternative futures for, sustainable water and food security.

Published
2024
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36. BFNet: a full-encoder skip connect way for medical image segmentation

Author

Siyu Zhan, Quan Yuan, Xin Lei, Rui Huang, Lu Guo, Ke Liu, and Rong Chen

Subjects
deep learning, U-net, medical image segmentation, pulmonarty embolism, CNN -convolutional neural network, Physiology, QP1-981
Abstract

In recent years, semantic segmentation in deep learning has been widely applied in medical image segmentation, leading to the development of numerous models. Convolutional Neural Network (CNNs) have achieved milestone achievements in medical image analysis. Particularly, deep neural networks based on U-shaped architectures and skip connections have been extensively employed in various medical image tasks. U-Net is characterized by its encoder-decoder architecture and pioneering skip connections, along with multi-scale features, has served as a fundamental network architecture for many modifications. But U-Net cannot fully utilize all the information from the encoder layer in the decoder layer. U-Net++ connects mid parameters of different dimensions through nested and dense skip connections. However, it can only alleviate the disadvantage of not being able to fully utilize the encoder information and will greatly increase the model parameters. In this paper, a novel BFNet is proposed to utilize all feature maps from the encoder at every layer of the decoder and reconnects with the current layer of the encoder. This allows the decoder to better learn the positional information of segmentation targets and improves learning of boundary information and abstract semantics in the current layer of the encoder. Our proposed method has a significant improvement in accuracy with 1.4 percent. Besides enhancing accuracy, our proposed BFNet also reduces network parameters. All the advantages we proposed are demonstrated on our dataset. We also discuss how different loss functions influence this model and some possible improvements.

Published
2024
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37. Accelerated functional fatigue leading to hysteresis widening in Ti44Ni47Nb9 shape memory alloy with multi-scale Nb-rich particles

Author

Ke Liu, Peng Zhang, Yulin Chen, and Jian Zhang

Subjects
Ti-Ni-Nb, Wide hysteresis shape memory alloys, Functional fatigue, Martensitic transformations, Dislocations, Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

Martensitic transformation temperatures are the most important indicators for designing shape memory alloy (SMA) components. Subjected to alternating temperatures in service, they undergo functional fatigue, which affects little the thermal hysteresis. We investigate the thermal cycling induced functional fatigue in Ti44Ni47Nb9 wide hysteresis SMA, decorated with multi-scale Nb-rich particles. We identify an accelerated functional fatigue behavior leading to the hysteresis widening from 58 to 71 K after 20 thermal cycles, in contrast to which hysteresis maintains nearly constant in Ti-Ni binary SMAs. Compared to Ti49Ni51 with similar transformation temperatures and latent heats, the hysteresis widening in Ti44Ni47Nb9 is attributed to accelerated decrease in starting temperature of martensite transformation (Ms).Microscopic characterizations reveal an inhomogeneous microstructure, consisting of (Ti,Nb)Ni B2 matrix and multi-scale Nb-rich particles and (Ti,Nb)2Ni particles. The presence of unique multi-scale Nb-rich particles has been demonstrated at the core of the underlying mechanisms of accelerated functional fatigue. Densely distributed Nb-rich nanoparticles narrow the mean matrix distance of transformation to 156.3 nm, which restricts the size and cross-over of the transformation induced dislocation leaves. Our work provides a new mechanism to widen the thermal hysteresis of SMAs, which is probably applicable to the other SMAs systems with dense nanoparticles.

Published
2024
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38. Research review on land development rights and its implications for China's national territory spatial planning

Author

Peng Cheng, Yongqin Fan, Houtian Tang, Ke Liu, Shiman Wu, Gaoli Zhu, Ping Jiang, and Weili Guo

Subjects
Land development rights, China's national territory spatial planning, Land value-added benefits, Hotspot research, Visual analysis, CiteSpace, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Based on the China National Knowledge Infrastructure (CNKI) and Web of Science (WOS) databases, this article analyzes the deductive context, cooperation network, and research hotspots of land development rights (LDR) research in the Chinese and international literature by using CiteSpace software, and it also explores the implications of this research for the theory and practice of national territory spatial planning (NTSP) in China. The results show that (1) the literature on LDR in Chinese and international journal articles initially appeared in 1995 and 1973, respectively, researches in China experienced three stages: embryonic fluctuating development, rapid growth and stable development, and wave development, while international researches experienced two stages: embryonic fluctuating and a gradually increasing development. (2) Among these scholars and research institutions, there is no obvious difference between Chinese and international scholars, while the Renmin University of China and the State University System of Florida are the research institutions with the largest number of Chinese and international journal articles, respectively. (3) In terms of publishing journals, international journals mainly focus on land policy, cities, and resource fields, while Chinese journals mainly focus on the agricultural economy, civil and commercial law, economic systems, and macroeconomic management fields. (4) The direction and scale of thematic research vary greatly, with Chinese research mainly conducted from the perspectives of rights attribution and benefits distribution, while international research mainly focuses on the operation of the right-to-development system and its impact on the environment. In the future, studies focus on China's need to strengthen the research and institutional practice of LDR at the legal level, value level, and extension level following national conditions, formulate a land value-added benefit distribution system with efficiency and fairness, and strengthen the practice of LDR in China's NTSP based on the differences between urban and rural development.

Published
2024
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39. Green manuring improves soil quality, grain yield, and grain anthocyanin content in colored rice cultivated in tropical regions

Author

Shaokun Song, Qi Yin, Mohammad Nauman Khan, Tingcheng Zhao, Ke Liu, Matthew Tom Harrison, Ye Tao, and Lixiao Nie

Subjects
anthocyanin, colored rice, grain yield, green manure, soil property, Agriculture, Agriculture (General), S1-972
Abstract

Abstract Green manuring is the process by which vegetative crops are incorporated into the soil, and it plays a good substitutable role in reducing chemical fertilizer applications while enhancing soil fertility. Field experiments were conducted at Lingao City of Hainan Province in 2020 and 2021, to evaluate the effects of in situ incorporation of different green manures (fallow (as control), rice, sesbania, and stylosanthes) on soil physical and chemical properties, nitrogen (N) uptake, grain yield, and the grain anthocyanin content in colored rice. Treatments included colored rice cultivated with previous fallow (T0), with previous rice straw manure (T1), with previous sesbania manure (T2), and with previous stylosanthes manure (T3). The seedlings of the colored rice variety Suixiangheinuo were transplanted 23 days after the incorporation of green manure. Our results indicated that both the grain yield and grain anthocyanin content of colored rice were significantly increased when green manure was incorporated into the soil compared to that of the control. Therein, grain yields of T1, T2, and T3 were increased by an average of 12.7%, 29.0%, and 24.5%, respectively, across 2 years in comparison with those of T0. And grain anthocyanin content in colored rice under T1, T2, and T3 was increased by 7.2%–7.5%, 13.9%–24.2%, and 9.8%–20.6%, respectively. In addition, in situ incorporation of leguminous green manure in the soil significantly increased soil fertility and partial factor productivity for N fertilizer. The above results suggested that colored rice crops should be followed in rotation with leguminous green manure, which was beneficial to increasing both grain yield and grain anthocyanin content of colored rice. This research elucidated that the incorporation of leguminous green manure sustained the production of colored rice in tropical regions, which was beneficial to reconcile the relationship between rice production and environmental protection.

Published
2024
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40. Precision prognosis of colorectal cancer: a multi-tiered model integrating microsatellite instability genes and clinical parameters

Author

Yonghong Wang, Ke Liu, Wanbin He, Jie Dan, Mingjie Zhu, Lei Chen, Wenjie Zhou, Ming Li, and Jiangpeng Li

Subjects
enhancing CRC survival prediction colorectal cancer, prognostic model, microsatellite instability, survival, prediction, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

BackgroundPrognostic assessment for colorectal cancer (CRC) displays substantial heterogeneity, as reliance solely on traditional TNM staging falls short of achieving precise individualized predictions. The integration of diverse biological information sources holds the potential to enhance prognostic accuracy.ObjectiveTo establish a comprehensive multi-tiered precision prognostic evaluation system for CRC by amalgamating gene expression profiles, clinical characteristics, and tumor microsatellite instability (MSI) status in CRC patients.MethodsWe integrated genomic data, clinical information, and survival follow-up data from 483 CRC patients obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. MSI-related gene modules were identified using differential expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Three prognostic models were constructed: MSI-Related Gene Prognostic Model (Model I), Clinical Prognostic Model (Model II), and Integrated Multi-Layered Prognostic Model (Model III) by combining clinical features. Model performance was assessed and compared using Receiver Operating Characteristic (ROC) curves, Kaplan-Meier analysis, and other methods.ResultsSix MSI-related genes were selected for constructing Model I (AUC = 0.724); Model II used two clinical features (AUC = 0.684). Compared to individual models, the integrated Model III exhibited superior performance (AUC = 0.825) and demonstrated good stability in an independent dataset (AUC = 0.767).ConclusionThis study successfully developed and validated a comprehensive multi-tiered precision prognostic assessment model for CRC, providing an effective tool for personalized medical management of CRC.

Published
2024
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41. Climate Disaster and Cognitive Ability: Evidence From Wildfire

Author

Ran Du, Ke Liu, Dangru Zhao, and Qiyun Fang

Subjects
human capital, climate disaster, wildfire, cognitive ability, wind direction realization, Public aspects of medicine, RA1-1270
Abstract

ObjectivesWe investigate the impact of wildfire disasters on cognitive health (i.e., thinking and language skills) in individuals aged 10 years and older using 2014 and 2018 wildfire and cognitive ability survey data from China.MethodsWe distinguished wildfires in each county at different wind directions each day by exogenous wind direction changes, and analyzed the effects of wildfires on cognitive abilities through upwind and non-upwind wildfires.ResultsOur analysis shows that for every 10-unit increase in upwind wildfires compared to non-upwind wildfires, respondents’ scores on word and math tests decrease by 0.235 and 0.236 standard deviations, respectively. Furthermore, we find that the impact of wildfire on cognitive ability is more pronounced in younger individuals, and those with lower defensive expenditures experience more severe impacts. Additionally, wildfires negatively affect individuals’ cognitive abilities by generating air pollution.ConclusionWildfires significantly reduce individuals’ cognitive abilities. Two recommendations are as follows: 1) governments should follow the principle of green development, introduce relevant regulations, and increase investment in adaptive technologies. 2) Individuals should raise awareness of climate hazards preparedness and strengthen defensive protection.

Published
2024
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42. Identification and experimental validation of m7G-related molecular subtypes, immune signature, and feature genes in Alzheimer's disease

Author

Piaopiao Lian, Xing Cai, Cailin Wang, Heng Zhai, Ke Liu, Xiaoman Yang, Yi Wu, Zhuoran Ma, Xuebing Cao, and Yan Xu

Subjects
Alzheimer's disease, N7-methylguanosine, Bioinformatic analysis, Characteristic genes, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Background: Studies has shown that N7-methylguanosine (m7G) modification plays a critical role in neurological diseases. However, the exact role and association of m7G with the immune microenvironment in Alzheimer's disease (AD) remain largely unknown and unexplored. Methods: The study datasets comprised 667 AD samples and 503 control samples selected from eight datasets in the Gene Expression Omnibus database; m7G regulator genes were obtained from previous literature. The AD subtypes were identified by consensus clustering analysis according to m7G regulator genes. The clinical characteristics, immune infiltration, and biological functions of the AD subgroups were evaluated. A combination of different types of machine-learning algorithms were used for the identification of AD genes. We also assessed and validated the diagnostic performance of the identified genes via qRT-PCR, immunofluorescence, and immunohistochemical analyses. Results: Two AD distinct subgroups, namely cluster A and cluster B, were identified. Cluster A had poor pathological progression and immune infiltration, representing a high-risk subgroup for AD. The differentially expressed genes of cluster A were enriched in immune and synapse-related pathways, suggesting that these genes probably contribute to AD progression by regulating immune-related pathways. Additionally, five feature genes (AEBP1, CARTPT, AK5, NPTX2, and COPG2IT1) were identified, which were used to construct a nomogram model with good ability to predict AD. The animal experiment analyses further confirmed that these feature genes were associated with AD development. Conclusion: To the best of our knowledge, this is the first study to reveal close correlations among m7G RNA modification, the immune microenvironment, and the pathogenesis of AD. We also identified five feature genes associated with AD, further contributing to our understanding of the underlying mechanisms and potential therapeutic targets for AD.

Published
2024
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43. Gut virome alterations in patients with chronic obstructive pulmonary disease

Author

Yue Liu, Qingsong Huang, Zhenhua Zhuang, Hongjing Yang, Xiaoling Gou, Tong Xu, Ke Liu, Jun Wang, Bo Liu, Peiyang Gao, Feng Cao, Bin Yang, Chuantao Zhang, Mei Chen, and Gang Fan

Subjects
chronic obstructive pulmonary disease, gut virome, metagenomics, gut microbiome, diagnostic performance, Microbiology, QR1-502
Abstract

ABSTRACT Chronic obstructive pulmonary disease (COPD) is one of the primary causes of mortality and morbidity worldwide. The gut microbiome, particularly the bacteriome, has been demonstrated to contribute to the progression of COPD. However, the influence of gut virome on the pathogenesis of COPD is rarely studied. Recent advances in viral metagenomics have enabled the rapid discovery of its remarkable role in COPD. In this study, deep metagenomics sequencing of fecal virus-like particles and bacterial 16S rRNA sequencing was performed on 92 subjects from China to characterize alterations of the gut virome in COPD. Lower richness and diversity of the gut virome were observed in the COPD subjects compared with the healthy individuals. Sixty-four viral species, including Clostridium phage, Myoviridae sp., and Synechococcus phage, showed positive relationships with pulmonary ventilation functions and had markedly declined population in COPD subjects. Multiple viral functions, mainly involved in bacterial susceptibility and the interaction between bacteriophages and bacterial hosts, were significantly declined in COPD. In addition, COPD was characterized by weakened viral-bacterial interactions compared with those in the healthy cohort. The gut virome showed diagnostic performance with an area under the curve (AUC) of 88.7%, which indicates the potential diagnostic value of the gut virome for COPD. These results suggest that gut virome may play an important role in the development of COPD. The information can provide a reference for the future investigation of diagnosis, treatment, and in-depth mechanism research of COPD.IMPORTANCEPrevious studies showed that the bacteriome plays an important role in the progression of chronic obstructive pulmonary disease (COPD). However, little is known about the involvement of the gut virome in COPD. Our study explored the disease-specific virome signatures of patients with COPD. We found the diversity and compositions altered of the gut virome in COPD subjects compared with healthy individuals, especially those viral species positively correlated with pulmonary ventilation functions. Additionally, the declined bacterial susceptibility, the interaction between bacteriophages and bacterial hosts, and the weakened viral-bacterial interactions in COPD were observed. The findings also suggested the potential diagnostic value of the gut virome for COPD. The results highlight the significance of gut virome in COPD. The novel strategies for gut virome rectifications may help to restore the balance of gut microecology and represent promising therapeutics for COPD.

Published
2024
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44. Associations of modifiable factors with risk of irritable bowel syndrome

Author

Ying Chen, Hong Yang, Jie Song, Weiwei Chen, Ke Liu, Bin Liu, Peiyang Luo, Xiaohui Sun, Zhixing He, Yingying Mao, and Ding Ye

Subjects
irritable bowel syndrome, Mendelian randomization, modifiable factors, genetics, single-nucleotide polymorphisms, Nutrition. Foods and food supply, TX341-641
Abstract

BackgroundModifiable factors were found to be associated with the risk of irritable bowel syndrome (IBS) in observational studies, but whether these associations are causal is uncertain. We conducted a Mendelian randomization (MR) study to systematically explore the causal associations of modifiable factors with IBS.MethodsSummary-level statistical data for IBS was obtained from a genome-wide association study (GWAS) meta-analysis of UK Biobank (40,548 cases and 293,220 controls) and the international collaborative Bellygenes initiative (12,852 cases and 139,981 controls). Genetic instruments associated with the exposures at the genome-wide significance (p

Published
2024
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45. The absence of the ribosomal protein Rpl2702 elicits the MAPK-mTOR signaling to modulate mitochondrial morphology and functions

Author

Ling Liu, Yifan Wu, Ke Liu, Mengdan Zhu, Shouhong Guang, Fengsong Wang, Xing Liu, Xuebiao Yao, Jiajia He, and Chuanhai Fu

Subjects
Mitochondria, MAPK, mTOR, Ribosome, Schizosaccharomyces pombe, Medicine (General), R5-920, Biology (General), QH301-705.5
Abstract

Ribosomes mediate protein synthesis, which is one of the most energy-demanding activities within the cell, and mitochondria are one of the main sources generating energy. How mitochondrial morphology and functions are adjusted to cope with ribosomal defects, which can impair protein synthesis and affect cell viability, is poorly understood. Here, we used the fission yeast Schizosaccharomyces Pombe as a model organism to investigate the interplay between ribosome and mitochondria. We found that a ribosomal insult, caused by the absence of Rpl2702, activates a signaling pathway involving Sty1/MAPK and mTOR to modulate mitochondrial morphology and functions. Specifically, we demonstrated that Sty1/MAPK induces mitochondrial fragmentation in a mTOR-independent manner while both Sty1/MAPK and mTOR increases the levels of mitochondrial membrane potential and mitochondrial reactive oxygen species (mROS). Moreover, we demonstrated that Sty1/MAPK acts upstream of Tor1/TORC2 and Tor1/TORC2 and is required to activate Tor2/TORC1. The enhancements of mitochondrial membrane potential and mROS function to promote proliferation of cells bearing ribosomal defects. Hence, our study reveals a previously uncharacterized Sty1/MAPK-mTOR signaling axis that regulates mitochondrial morphology and functions in response to ribosomal insults and provides new insights into the molecular and physiological adaptations of cells to impaired protein synthesis.

Published
2024
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46. Damage assessment of concrete beams repaired with basalt fiber-reinforced polymer sheets through digital image correlation and acoustic emission

Author

Jianmei Chang, Yadong Yao, Ke Liu, Yonghua Wang, Meng Yan, and Yi Bao

Subjects
Acoustic emission (AE), Basalt fiber reinforced polymer (BFRP), Concrete cracks, Damage mechanism, Digital image correlation (DIC), Interface debonding, Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

Basalt fiber-reinforced polymer (BFRP) has high mechanical strengths as a repairing material but exhibits low ductility. This paper investigates the damage process of reinforced concrete beams repaired using BFRP sheets, aimed at understanding the underlying mechanisms of achieving structural ductility when BFRP sheets are used. The damage process was assessed using digital image correlation (DIC) and acoustic emission (AE) techniques applied to monitor surface and internal damages of three full-scale concrete beams subjected to four-point bending. A beam was first loaded to crack, then repaired with BFRP sheets, and finally reloaded to failure. Surface strain fields and cracks were monitored using a DIC method, and cracking events were monitored using AE sensors deployed at different positions of the beams. The AE signals were analyzed to assess the damage process. The test results indicated that (1) tensile cracks predominated throughout the loading process; (2) the BFRP sheets hindered the widening of cracks and promoted the generation of fine cracks; and (3) the development of concrete cracks promoted interfacial debonding at steel-concrete and BFRP-concrete interfaces. A combination of different types of cracks and interfacial debonding helped the repaired beam achieve ductile flexural behaviors.

Published
2024
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