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1. Ninety percent circular polarization detected in a repeating fast radio burst

Author: Jiang, J. C., Xu, J. W., Niu, J. R., Lee, K. J., Zhu, W. W., Zhang, B., Qu, Y., Xu, H., Zhou, D. J., Cao, S. S., Wang, W. Y., Wang, B. J., Cao, S., Zhang, Y. K., Zhang, C. F., Gan, H. Q., Han, J. L., Hao, L. F., Huang, Y. X., Jiang, P., Li, D. Z., Li, H., Li, Y., Li, Z. X., Luo, R., Men, Y. P., Qian, L., Sun, J. H., Wang, L., Xu, Y. H., Xu, R. X., Yang, Y. P., Yao, R., Yue, Y. L., Yu, D. J., Yuan, J. P., and Zhu, Y.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Fast radio bursts (FRBs) are extra-galactic sources with unknown physical mechanisms. They emit millisecond-duration radio pulses with isotropic equivalent energy of $10^{36}\sim10^{41}$ ergs. This corresponds to a brightness temperature of FRB emission typically reaching the level of $10^{36}$ K, but can be as high as above $10^{40}$ K for sub-microsecond timescale structures, suggesting the presence of underlying coherent relativistic radiation mechanisms. polarization carries the key information to understand the physical origin of FRBs, with linear polarization usually tracing the geometric configuration of magnetic fields and circular polarization probing both intrinsic radiation mechanisms and propagation effects. Here we show that the repeating sources FRB 20201124A emits $90.9\pm 1.1\%$ circularly polarized radio pulses. Such a high degree of circular polarization was unexpected in theory and unprecedented in observation in the case of FRBs, since such a high degree of circular polarization was only common among Solar or Jovian radio activities, attributed to the sub-relativistic electrons. We note that there is no obvious correlation between the degree of circular polarization and burst fluence. Besides the high degree of circular polarization, we also detected rapid swing and orthogonal jump in the position angle of linear polarization. The detection of the high degree circular polarization in FRB 20201124A, together with its linear polarization properties that show orthogonal modes, place strong constraints on FRB physical mechanisms, calling for an interplay between magnetospheric radiation and propagation effects in shaping the observed FRB radiation., Comment: 19 pages, 9 figures, 1 table, accepted for publication in National Science Review
Published: 2024

2. Prediction model for the risk of auditory and vestibular disfunction caused by a blast wave

Author: Zhang, J., Chen, K., Li, G., Chen, W., Duan, Z., Kang, J., Liu, X., Zhang, S., Gan, H., Zhou, S., Weng, C., Ma, C., Liu, Y., Zhou, T., and Wang, J.
Published: 2024
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3. Simultaneously improving toughness and strength for biodegradable Poly (lactic acid) modified by rice husk and acetyl tributyl citrate

Author: Wang, Y. B., Ren, L., Gan, H. N., Han, Y. G., Xu, M. F., Wang, Y. H., Liu, Q., and Zhang, M. Y.
Published: 2024
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4. Bioinformatics Identification and Validation of Ferroptosis-Related Key Genes and Therapeutic Compounds in Septic Lung Injury

Author: Li Z, Gan H, Li S, Xue Y, Luo K, Huang K, Zhang Y, Wang Y, Jiang L, and Zhang H
Subjects: sepsis, sli, ferroptosis, bioinformatics, hif-1α，phloretin, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Zhile Li, Han Gan, Siyuan Li, Yuchen Xue, Kai Luo, Kai Huang, Yunqian Zhang, Yan Wang, Lai Jiang, Hui Zhang Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of ChinaCorrespondence: Lai Jiang; Hui Zhang, Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, People’s Republic of China, Email jianglai@xinhuamed.com.cn; zhanghui22002@xinhuamed.com.cnBackground: Septic lung injury (SLI) is a severe condition with high mortality, and ferroptosis, a form of programmed cell death, is implicated in its pathogenesis. However, the explicit mechanisms underlying this condition remain unclear. This study aimed to elucidate and validate key ferroptosis-related genes involved in the pathogenesis of SLI through bioinformatics analysis and experimental validation.Methods: Microarray data related to SLI from the GSE130936 dataset were downloaded from the Gene Expression Omnibus (GEO) database. These data were then intersected with the FerrDb database to obtain ferroptosis-related differentially expressed genes (DEGs). Protein-protein interaction (PPI) networks and functional enrichment analysis were employed to identify key ferroptosis-related DEGs. The Connectivity Map (c-MAP) tool was used to search for potential compounds or drugs that may inhibit ferroptosis-related DEGs. The transcriptional levels of the key genes and potential therapeutic compounds were verified in an LPS-induced mouse model of lung injury. The expression of these key genes was further verified using the GSE60088 and GSE137342 datasets.Results: 38 ferroptosis-related DEGs were identified between the septic and control mice. PPI network analysis revealed four modules, the most significant of which included eight ferroptosis-related DEGs. Functional enrichment analysis showed that these genes were enriched in the HIF-1 signaling pathway, including IL-6 (Interleukin-6), TIMP1 (Tissue Inhibitor of Metalloproteinase 1), HIF-1α (Hypoxia-Inducible Factor-1α), and HMOX1 (Heme Oxygenase-1). Phloretin, a natural compound, was identified as a potential inhibitor of these genes. Treatment with phloretin significantly reduced the expression of these genes (p < 0.05), mitigated lung injury, improved inflammatory profiles by approximately 50%, and ferroptosis profiles by nearly 30% in the SLI models.Conclusion: This study elucidates the significant role of ferroptosis in SLI and identifies phloretin as a potential therapeutic agent. However, further research, particularly involving human clinical trials, is necessary to validate these findings for clinical use.Keywords: sepsis, SLI, ferroptosis, bioinformatics, HIF-1α, phloretin
Published: 2024

5. Assessing the impact of two independent direction-dependent calibration algorithms on the LOFAR 21-cm signal power spectrum

Author: Gan, H., Mertens, F. G., Koopmans, L. V. E., Offringa, A. R., Mevius, M., Pandey, V. N., Brackenhoff, S. A., Ceccotti, E., Ciardi, B., Gehlot, B. K., Ghara, R., Giri, S. K., Iliev, I. T., and Munshi, S.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: Detecting the 21-cm signal from the Epoch of Reionisation (EoR) is challenging due to the strong astrophysical foregrounds, ionospheric effects, radio frequency interference and instrumental effects. Understanding and calibrating these effects are crucial for the detection. In this work, we introduce a newly developed direction-dependent (DD) calibration algorithm DDECAL and compare its performance with an existing algorithm, SAGECAL, in the context of the LOFAR-EoR 21-cm power spectrum experiment. In our data set, the North Celestial Pole (NCP) and its flanking fields were observed simultaneously. We analyse the NCP and one of its flanking fields. The NCP field is calibrated by the standard pipeline, using SAGECAL with an extensive sky model and 122 directions, and the flanking field is calibrated by DDECAL and SAGECAL with a simpler sky model and 22 directions. Additionally, two strategies are used for subtracting Cassiopeia A and Cygnus A. The results show that DDECAL performs better at subtracting sources in the primary beam region due to the application of a beam model, while SAGECAL performs better at subtracting Cassiopeia A and Cygnus A. This indicates that including a beam model during DD calibration significantly improves the performance. The benefit is obvious in the primary beam region. We also compare the 21-cm power spectra on two different fields. The results show that the flanking field produces better upper limits compared to the NCP in this particular observation. Despite the minor differences between DDECAL and SAGECAL due to the beam application, we find that the two algorithms yield comparable 21-cm power spectra on the LOFAR-EoR data after foreground removal. Hence, the current LOFAR-EoR 21-cm power spectrum limits are not likely to depend on the DD calibration method., Comment: 28 pages, 14 figures, accepted for publication in A&A; a few equations in section 3 were corrected in this version
Published: 2022
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6. The Changing and Predicted Trends in Chronic Obstructive Pulmonary Disease Burden in China, the United States, and India from 1990 to 2030

Author: Guo B, Gan H, Xue M, Huang Z, Lin Z, Li S, Zheng P, and Sun B
Subjects: copd, global burden of disease, risk factors, dalys, Diseases of the respiratory system, RC705-779
Abstract: Baojun Guo,1,2 Hui Gan,1 Mingshan Xue,1,3 Zhifeng Huang,1 Zhiwei Lin,1 Shiyun Li,1 Peiyan Zheng,1 Baoqing Sun1 1Department of Clinical Laboratory of the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, 510120, People’s Republic of China; 2School of Medicine, Henan University, Kaifeng, 475004, People’s Republic of China; 3Guangzhou Eighth People’s Hospital, Guangzhou Medical University, Guangzhou, 510060, People’s Republic of ChinaCorrespondence: Baoqing Sun; Peiyan Zheng, Email sunbaoqing@vip.163.com; gdmcslxx@126.comBackground: This study analyzed the burden of chronic obstructive pulmonary disease (COPD) in China, the United States, and India from 1990 to 2019 and projected the trends for the next decade.Methods: This study utilized the GBD 2019 to compare the age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), age-standardized disability-adjusted life years (DALYs) rate, and the proportion attributed to different risk factors in China, the United States, and India. Joinpoint models and autoregressive integrated moving average (ARIMA) models were employed to capture the changing trends in disease burden and forecast outcomes.Results: From 1990 to 2019, China’s age-standardized COPD incidence and mortality rates decreased by 29% and 70%, respectively. In the same period, India’s rates decreased by 8% and 33%, while the United States saw an increase of 9% in COPD incidence and a 22% rise in mortality rates. Smoking and ambient particulate matter pollution are the two most significant risk factors for COPD, while household air pollution from solid fuels and low temperatures are the least impactful factors in the United States and India, respectively. The proportion of risk from household air pollution from solid fuels is higher in India than in China and the United States. Predictions for 2030 suggest that the age-standardized DALY rates, ASIR, and ASMR in the United States and India are expected to remain stable or decrease, while China’s age-standardized incidence rate is projected to rise.Conclusion: Over the past three decades, the incidence of COPD has been decreasing in China and India, while showing a slight increase in the United States. Smoking and ambient particulate matter pollution are the primary risk factors for men and women, respectively. The risk of household air pollution from solid fuels in India needs attention.Keywords: COPD, global burden of disease, risk factors, DALYs
Published: 2024

7. Statistical analysis of the causes of excess variance in the 21 cm signal power spectra obtained with the Low-Frequency Array

Author: Gan, H., Koopmans, L. V. E, Mertens, F. G., Mevius, M., Offringa, A. R., Ciardi, B., Gehlot, B. K., Ghara, R., Ghosh, A., Giri, S. K., Iliev, I. T., Mellema, G., Pandey, V. N., and Zaroubi, S.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The detection of the 21 cm signal of neutral hydrogen from the Epoch of Reionization (EoR) is challenging due to bright foreground sources, radio frequency interference (RFI), the ionosphere, and instrumental effects. Even after correcting for these effects in the calibration step and applying foreground removal techniques, the remaining residuals in the observed 21 cm power spectra are still above the thermal noise, which is referred to as the "excess variance." We study potential causes of this excess variance based on 13 nights of data obtained with the Low-Frequency Array (LOFAR). We focused on the impact of gain errors, the sky model, and ionospheric effects on the excess variance by correlating the relevant parameters such as the gain variance over time or frequency, local sidereal time (LST), diffractive scale, and phase structure-function slope with the level of excess variance. Our analysis shows that excess variance has an LST dependence, which is related to the power from the sky. And the simulated Stokes I power spectra from bright sources and the excess variance show a similar progression over LST with the minimum power appearing at LST bin 6h to 9h. This LST dependence is also present in sky images of the residual Stokes I of the observations. In very-wide sky images, we demonstrate that the extra power comes exactly from the direction of bright and distant sources Cassiopeia A and Cygnus A with the array beam patterns. These results suggest that the level of excess variance in the 21 cm signal power spectra is related to sky effects and, hence, it depends on LST. In particular, very bright and distant sources such as Cassiopeia A and Cygnus A can dominate the effect. This is in line with earlier studies and offers a path forward toward a solution since the correlation between the sky-related effects and the excess variance is non-negligible., Comment: 29 pages, 14 figures, accepted for publication in A&A
Published: 2022
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8. Analysis and Verification of Glycosylation Characteristics of Septic Acute Kidney Injury

Author: Chen S and Gan H
Subjects: acute kidney injury, sepsis, glycosylation, hub genes, bioinformatics, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Si Chen, Hua Gan Department of Nephrology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of ChinaCorrespondence: Hua Gan, Email huagan2022@163.comBackground: Septic acute kidney injury (S-AKI) results from an imbalance in the regulation of systemic inflammatory responses. Glycosylation plays an important role in inflammatory responses. However, the relationship between S-AKI and glycosylation is unclear.Methods: The datasets of the public platform were analyzed using R language to obtain glycosylation-related differentially expressed genes (GRDEGs) in S-AKI. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed for GRDEGs. Hub genes were obtained using three machine learning algorithms and their diagnostic values were evaluated using receiver operating characteristic (ROC) curves. The relationships between the hub genes, immune cells, and signaling pathways were analyzed, and the upstream miRNAs, transcription factors, and compounds of the hub genes were predicted. Mouse models of AKI with sepsis were constructed and the expression of the hub genes was verified.Results: We obtained 45 GRDEGs that were mainly enriched in glycoprotein metabolism and immune inflammatory response, such as “O-glycan biosynthesis”, “phagosome”, “pathogenic Escherichia coli infection”, “glycosyltransferase activity”, etc. Seven hub genes that have potential diagnostic value were identified and were associated with the regulation of immune cells. Through gene set enrichment analysis (GSEA) of hub genes, it was found that these genes may be involved in metabolism, signaling transduction, and inflammation-related signaling pathways, such as “metabolism of amino and derivatives”, “RHO GTPase cycle”, “transport of small molecules”, “neutrophil degranulation”, “immune system”, etc. We then predicted 100 miRNAs, 60 TFs, and 23 compounds of the hub genes using forecasting tools. Finally, animal experiments confirmed the differential expression of ASGR1, UMOD, SPTBN1, and ADAMTS17.Conclusion: This study identified and validated four biomarkers associated with abnormal glycosylation that could be potential targets for AKI in sepsis.Keywords: acute kidney injury, sepsis, glycosylation, hub genes, bioinformatics
Published: 2023

9. Degree-Scale Galactic Radio Emission at 122 MHz around the North Celestial Pole with LOFAR-AARTFAAC

Author: Gehlot, B. K., Koopmans, L. V. E., Offringa, A. R., Gan, H., Ghara, R., Giri, S. K., Kuiack, M., Mertens, F. G., Mevius, M., Mondal, R., Pandey, V. N., Shulevski, A., Wijers, R. A. M. J., and Yatawatta, S.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Aims: Contamination from bright diffuse Galactic thermal and non-thermal radio emission poses crucial challenges in experiments aiming to measure the 21-cm signal of neutral hydrogen from the Cosmic Dawn and Epoch of Reionization. If not included in calibration, this diffuse emission can severely impact the analysis and signal extraction in 21-cm experiments. We examine large-scale diffuse Galactic emission at 122~MHz, around the North Celestial Pole, using the AARTFAAC-HBA system. Methods: In this pilot project, we present the first-ever wide-field image produced with a single sub-band of the data recorded with the AARTFAAC-HBA. We demonstrate two methods: multiscale CLEAN and shapelet decomposition, to model the diffuse emission revealed in the image. We use angular power spectrum metrics to quantify different components of the emission and compare the performance of the two diffuse structure modelling approaches. Results: We observe that the point sources dominate the angular power spectrum ($\ell(\ell+1)C_{\ell}/2\pi\equiv \Delta^2(\ell)$) of the emission in the field on scales $\ell\gtrsim 60$ ($\lesssim 3$~degree). The angular power spectrum after subtraction of compact sources is flat within $20\lesssim \ell \lesssim200$ range, suggesting that the residual power is dominated by the diffuse emission on scales $\ell\lesssim200$. The residual diffuse emission has a brightness temperature variance of $\Delta^2_{\ell=180} = (145.64 \pm 13.61)~{\rm K}^2$ at 122~MHz on angular scales of 1~degree, and is consistent with a power-law following $C_{\ell}\propto \ell^{-2.0}$ in $20\lesssim \ell \lesssim200$ range. We also find that, in the current setup, the multiscale CLEAN is suitable to model the compact and diffuse structures on a wide range of angular scales, whereas the shapelet decomposition method better models the large scales, which are of the order of a few degrees and wider., Comment: 11 pages, 9 figures, accepted (A&A)
Published: 2021
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10. A fast radio burst source at a complex magnetised site in a barred galaxy

Author: Xu, H., Niu, J. R., Chen, P., Lee, K. J., Zhu, W. W., Dong, S., Zhang, B., Jiang, J. C., Wang, B. J., Xu, J. W., Zhang, C. F., Fu, H., Filippenko, A. V., Peng, E. W., Zhou, D. J., Zhang, Y. K., Wang, P., Feng, Y., Li, Y., Brink, T. G., Li, D. Z., Lu, W., Yang, Y. P., Caballero, R. N., Cai, C., Chen, M. Z., Dai, Z. G., Djorgovski, S. G., Esamdin, A., Gan, H. Q., Guhathakurta, P., Han, J. L., Hao, L. F., Huang, Y. X., Jiang, P., Li, C. K., Li, D., Li, H., Li, X. Q., Li, Z. X., Liu, Z. Y., Luo, R., Men, Y. P., Niu, C. H., Peng, W. X., Qian, L., Song, L. M., Stern, D., Stockton, A., Sun, J. H., Wang, F. Y., Wang, M., Wang, N., Wang, W. Y., Wu, X. F., Xiao, S., Xiong, S. L., Xu, Y. H., Xu, R. X., Yang, J., Yang, X., Yao, R., Yi, Q. B., Yue, Y. L., Yu, D. J., Yu, W. F., Yuan, J. P., Zhang, B. B., Zhang, S. B., Zhang, S. N., Zhao, Y., Zheng, W. K., Zhu, Y., and Zou, J. H.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Fast radio bursts (FRBs) are highly dispersed millisecond-duration radio bursts. Recent observations of a Galactic FRB suggest that at least some FRBs originate from magnetars, but the origin of cosmological FRBs is still not settled. Here we report the detection of 1863 bursts in 82 hr over 54 days from the repeating source FRB~20201124A. These observations show irregular short-time variation of the Faraday rotation measure (RM), which probes the density-weighted line-of-sight magnetic field strength, of individual bursts during the first 36 days, followed by a constant RM. We detected circular polarisation in more than half of the burst sample, including one burst reaching a high fractional circular polarisation of 75%. Oscillations in fractional linear and circular polarisations as well as polarisation angle as a function of wavelength were detected. All of these features provide evidence for a complicated, dynamically evolving, magnetised immediate environment within about an astronomical unit (au; Earth-Sun distance) of the source. Our optical observations of its Milky-Way-sized, metal-rich host galaxy reveal a barred spiral, with the FRB source residing in a low stellar density, interarm region at an intermediate galactocentric distance. This environment is inconsistent with a young magnetar engine formed during an extreme explosion of a massive star that resulted in a long gamma-ray burst or superluminous supernova., Comment: 28 pages, 10 figures, updated to match the published version
Published: 2021
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11. A numerical study of 21-cm signal suppression and noise increase in direction-dependent calibration of LOFAR data

Author: Mevius, M., Mertens, F., Koopmans, L. V. E., Offringa, A. R., Yatawatta, S., Brentjens, M. A., Chapman, E., Ciardi, B., Gan, H., Gehlot, B. K., Ghara, R., Ghosh, A., Giri, S. K., Iliev, I. T., Mellema, G., Pandey, V. N., and Zaroubi, S.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: We investigate systematic effects in direction dependent gain calibration in the context of the Low-Frequency Array (LOFAR) 21-cm Epoch of Reionization (EoR) experiment. The LOFAR EoR Key Science Project aims to detect the 21-cm signal of neutral hydrogen on interferometric baselines of $50-250 \lambda$. We show that suppression of faint signals can effectively be avoided by calibrating these short baselines using only the longer baselines. However, this approach causes an excess variance on the short baselines due to small gain errors induced by overfitting during calibration. We apply a regularised expectation-maximisation algorithm with consensus optimisation (sagecal-co) to real data with simulated signals to show that overfitting can be largely mitigated by penalising spectrally non-smooth gain solutions during calibration. This reduces the excess power with about a factor 4 in the simulations. Our results agree with earlier theoretical analysis of this bias-variance trade off and support the gain-calibration approach to the LOFAR 21-cm signal data., Comment: This is a pre-copyedited, author-produced PDF of an article accepted for publication in MNRAS following peer review
Published: 2021
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12. Deciphering the Mechanism of Xijiao Dihuang Decoction in Treating Psoriasis by Network Pharmacology and Experimental Validation

Author: Guo Y, Gan H, Xu S, Zeng G, Xiao L, Ding Z, Zhu J, Xiong X, and Fu Z
Subjects: psoriasis, xijiao dihuang decoction, network pharmacology, molecular docking, angiogenesis, Therapeutics. Pharmacology, RM1-950
Abstract: Yicheng Guo,1 Huiqun Gan,1 Shigui Xu,1 Guosheng Zeng,2 Lili Xiao,2 Zhijun Ding,2 Jie Zhu,3 Xinglong Xiong,3 Zhiyuan Fu1 1Department of Pharmacy, Dermatology Hospital of Jiangxi Province, Nanchang, People’s Republic of China; 2Jiangxi Provincial Clinical Research Center for Skin Diseases, Nanchang, People’s Republic of China; 3Candidate Branch of National Clinical Research Center for Skin Diseases, Nanchang, People’s Republic of ChinaCorrespondence: Zhiyuan Fu, Department of Pharmacy, Dermatology Hospital of Jiangxi Province, 388, Yinbing Road, Nanchang, Jiangxi, People’s Republic of China, Tel +86 13970827820, Email fuzhiyuan0774@yeah.netPurpose: This study aims to confirm the efficacy of Xijiao Dihuang decoction (XJDHT), a classic prescription, in treating psoriasis and to explore the potential therapeutic mechanism.Methods: For pharmacodynamic analysis, a mouse model of imiquimod cream (IMQ)-induced psoriasis was constructed. Active ingredients and genes of XJDHT, as well as psoriasis-related targets, were obtained from public databases. Intersecting genes (IGEs) of XJDHT and psoriasis were collected by Venn Diagram. A protein–protein interaction (PPI) network of IGEs is constructed through the STRING database. The Molecular Complex Detection (MCODE) and Cytohubba plug-ins of Cytoscape software were used to identified hub genes. In addition, we conducted enrichment analysis of IGEs using the R package clusterProfiler. Hub genes were validated via external GEO databases. The influence of XJDHT on Hub gene expression was examined by qPCR and ELISA, and molecular docking was used to evaluate the binding efficacy between active ingredients and hub genes.Results: The results revealed that XJDHT possesses 92 potential genes for psoriasis, and 8 Hub genes were screened. Enrichment analysis suggested that XJDHT ameliorate psoriasis through multiple pathways, including AGE-RAGE, HIF-1, IL-17 and TNF signaling pathway. Validation data confirmed the differential expression of IL6, VEGFA, TNF, MMP9, STAT3, and TLR4. Molecular docking revealed a strong affinity between active ingredients and Hub genes. The efficacy of XJDHT in improving psoriatic lesions in model mice was demonstrated by PASI score and HE staining, potentially attributed to the down-regulation of VEGFA, MMP9, STAT3, TNF, and IL-17A, as evidenced by ELISA and qPCR.Conclusion: This study employed network pharmacology and in vitro experiments to identify the potential mechanisms underlying the therapeutic effects of XJDHT on psoriasis, providing a new theoretical basis for its clinical application in the treatment of psoriasis.Keywords: psoriasis, Xijiao Dihuang decoction, network pharmacology, molecular docking, angiogenesis
Published: 2023

13. Synthesis of 2-(Arylmethyl)benzazoles by the Sulfur-mediated Cyclization of 2-Aminophenol or 2-Aminoaniline with Arylacetylenes

Author: Ma, P. P., Wu, H. L., and Gan, H. F.
Published: 2023
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14. Quantum-enhanced bosonic learning machine

Author: Nguyen, Chi-Huan, Tseng, Ko-Wei, Maslennikov, Gleb, Gan, H. C. J., and Matsukevich, Dzmitry
Subjects: Quantum Physics, Physics - Atomic Physics
Abstract: Quantum processors enable computational speedups for machine learning through parallel manipulation of high-dimensional vectors. Early demonstrations of quantum machine learning have focused on processing information with qubits. In such systems, a larger computational space is provided by the collective space of multiple physical qubits. Alternatively, we can encode and process information in the infinite-dimensional Hilbert space of bosonic systems such as quantum harmonic oscillators. This approach offers a hardware-efficient solution with potential quantum speedups to practical machine learning problems. Here we demonstrate a quantum-enhanced bosonic learning machine operating on quantum data with a system of trapped ions. Core elements of the learning processor are the universal feature-embedding circuit that encodes data into the motional states of ions, and the constant-depth circuit that estimates overlap between two quantum states. We implement the unsupervised K-means algorithm to recognize a pattern in a set of high-dimensional quantum states and use the discovered knowledge to classify unknown quantum states with the supervised k-NN algorithm. These results provide building blocks for exploring machine learning with bosonic processors., Comment: 10 pages, 8 figures
Published: 2021

15. Experimental SWAP test of infinite dimensional quantum states

Author: Nguyen, Chi-Huan, Tseng, Ko-Wei, Maslennikov, Gleb, Gan, H. C. J., and Matsukevich, Dzmitry
Subjects: Quantum Physics, Physics - Atomic Physics
Abstract: Efficient overlap estimation of high-dimensional quantum states is an important task in quantum information and a core element in computational speedups of quantum machine learning. Here we experimentally demonstrate the SWAP test that measures the overlap of two motional states in a system of trapped $^{171}\mathrm{Yb}^+$ ions. To illustrate the versatility of our implementation, we report the overlap measurement of a variety of quantum states: Fock states, coherent states, squeezed vacuum states, and cat states. We highlight applications of the SWAP test by measuring the purity of mixed states. Our results enable quantum information processing with high dimensional quantum states., Comment: 9 pages, 4 figures
Published: 2021

16. Synthesis of 2-Arylbenzoselenazoles by Sulfur-Mediated Cyclization of Bis(2-aminophenyl) Diselenide and Benzyl Chlorides

Author: Guo, X. H., Wu, H. L., and Gan, H. F.
Published: 2023
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17. Prevalence and risk factors of erectile dysfunction in COVID-19 patients: a systematic review and meta-analysis

Author: Zhang, J., Shi, W., Zou, M., Zeng, Q., Feng, Y., Luo, Z., and Gan, H.
Published: 2023
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18. Diverse polarization angle swings from a repeating fast radio burst source

Author: Luo, R., Wang, B. J., Men, Y. P., Zhang, C. F., Jiang, J. C., Xu, H., Wang, W. Y., Lee, K. J., Han, J. L., Zhang, B., Caballero, R. N., Chen, M. Z., Chen, X. L., Gan, H. Q., Guo, Y. J., Hao, L. F., Huang, Y. X., Jiang, P., Li, H., Li, J., Li, Z. X., Luo, J. T., Pan, J., Pei, X., Qian, L., Sun, J. H., Wang, M., Wang, N., Wen, Z. G., Xu, R. X., Xu, Y. H., Yan, J., Yan, W. M., Yu, D. J., Yuan, J. P., Zhang, S. B., and Zhu, Y.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Fast radio bursts (FRBs) are millisecond-duration radio transients of unknown origin. Two possible mechanisms that could generate extremely coherent emission from FRBs invoke neutron star magnetospheres or relativistic shocks far from the central energy source. Detailed polarization observations may help us to understand the emission mechanism. However, the available FRB polarization data have been perplexing, because they show a host of polarimetric properties, including either a constant polarization angle during each burst for some repeaters or variable polarization angles in some other apparently one-off events. Here we report observations of 15 bursts from FRB 180301 and find various polarization angle swings in seven of them. The diversity of the polarization angle features of these bursts is consistent with a magnetospheric origin of the radio emission, and disfavours the radiation models invoking relativistic shocks., Comment: Published online in Nature on 29 Oct, 2020
Published: 2020
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19. Optimization of the JUNO liquid scintillator composition using a Daya Bay antineutrino detector

Author: Bay, Daya, collaborations, JUNO, Abusleme, A., Adam, T., Ahmad, S., Aiello, S., Akram, M., Ali, N., An, F. P., An, G. P., An, Q., Andronico, G., Anfimov, N., Antonelli, V., Antoshkina, T., Asavapibhop, B., de André, J. P. A. M., Babic, A., Balantekin, A. B., Baldini, W., Baldoncini, M., Band, H. R., Barresi, A., Baussan, E., Bellato, M., Bernieri, E., Biare, D., Birkenfeld, T., Bishai, M., Blin, S., Blum, D., Blyth, S., Bordereau, C., Brigatti, A., Brugnera, R., Budano, A., Burgbacher, P., Buscemi, M., Bussino, S., Busto, J., Butorov, I., Cabrera, A., Cai, H., Cai, X., Cai, Y. K., Cai, Z. Y., Cammi, A., Campeny, A., Cao, C. Y., Cao, G. F., Cao, J., Caruso, R., Cerna, C., Chakaberia, I., Chang, J. F., Chang, Y., Chen, H. S., Chen, P. A., Chen, P. P., Chen, S. M., Chen, S. J., Chen, X. R., Chen, Y. W., Chen, Y. X., Chen, Y., Chen, Z., Cheng, J., Cheng, Y. P., Cheng, Z. K., Chepurnov, A., Cherwinka, J. J., Chiarello, F., Chiesa, D., Chimenti, P., Chu, M. C., Chukanov, A., Chuvashova, A., Clementi, ., Clerbaux, B., Di Lorenzo, S. Conforti, Corti, D., Costa, S., Corso, F. D., Cummings, J. P., Dalager, O., De La Taille, C., Deng, F. S., Deng, J. W., Deng, Z., Deng, Z. Y., Depnering, W., Diaz, M., Ding, X. F., Ding, Y. Y., Dirgantara, B., Dmitrievsky, S., Diwan, M. V., Dohnal, T., Donchenko, G., Dong, J. M., Dornic, D., Doroshkevich, E., Dove, J., Dracos, M., Druillole, F., Du, S. X., Dusini, S., Dvorak, M., Dwyer, D. A., Enqvist, T., Enzmann, H., Fabbri, A., Fajt, L., Fan, D. H., Fan, L., Fang, C., Fang, J., Fatkina, A., Fedoseev, D., Fekete, V., Feng, L. C., Feng, Q. C., Fiorentini, G., Ford, R., Formozov, A., Fournier, A., Franke, S., Gallo, J. P., Gan, H. N., Gao, F., Garfagnini, A., Göttel, A., Genster, C., Giammarchi, M., Giaz, A., Giudice, N., Giuliani, F., Gonchar, M., Gong, G. H., Gong, H., Gorchakov, O., Gornushkin, Y., Grassi, M., Grewing, C., Gromov, M., Gromov, V., Gu, M. H., Gu, W. Q., Gu, X. F., Gu, Y., Guan, M. Y., Guardone, N., Gul, M., Guo, C., Guo, J. Y., Guo, L., Guo, W. L., Guo, X. H., Guo, Y. H., Guo, Z., Haacke, M., Hackenburg, R. W., Hackspacher, P., Hagner, C., Han, R., Han, Y., Hans, S., He, M., He, W., Heeger, K. M., Heinz, T., Heng, Y. K., Herrera, R., Higuera, A., Hong, D. J., Hor, Y. K., Hou, S. J., Hsiung, Y. B., Hu, B. Z., Hu, H., Hu, J. R., Hu, J., Hu, S. Y., Hu, T., Hu, Z. J., Huang, C. H., Huang, G. H., Huang, H. X., Huang, Q. H., Huang, W. H., Huang, X. T., Huang, Y. B., Huber, P., Hui, J. Q., Huo, L., Huo, W. J., Huss, C., Hussain, S., Insolia, A., Ioannisian, A., Ioannisyan, D., Isocrate, R., Jaffe, D. E., Jen, K. L., Ji, X. L., Ji, X. P., Ji, X. Z., Jia, H. H., Jia, J. J., Jian, S. Y., Jiang, D., Jiang, X. S., Jin, R. Y., Jing, X. P., Johnson, R. A., Jollet, C., Jones, D., Joutsenvaara, J., Jungthawan, S., Kalousis, L., Kampmann, P., Kang, L., Karagounis, M., Kazarian, N., Kettell, S. H., Khan, A., Khan, W., Khosonthongkee, K., Kinz, P., Kohn, S., Korablev, D., Kouzakov, K., Kramer, M., Krasnoperov, A., Krokhaleva, S., Krumshteyn, Z., Kruth, A., Kutovskiy, N., Kuusiniemi, P., Lachacinski, B., Lachenmaier, T., Langford, T. J., Lee, J., Lee, J. H. C., Lefevre, F., Lei, L., Lei, R., Leitner, R., Leung, J., Li, C., Li, D. M., Li, F., Li, H. T., Li, H. L., Li, J., Li, J. J., Li, J. Q., Li, K. J., Li, M. Z., Li, N., Li, Q. J., Li, R. H., Li, S. C., Li, S. F., Li, S. J., Li, T., Li, W. D., Li, W. G., Li, X. M., Li, X. N., Li, X. L., Li, X. Q., Li, Y., Li, Y. F., Li, Z. B., Li, Z. Y., Liang, H., Liang, J. J., Liebau, D., Limphirat, A., Limpijumnong, S., Lin, C. J., Lin, G. L., Lin, S. X., Lin, T., Lin, Y. H., Ling, J. J., Link, J. M., Lippi, I., Littenberg, L., Littlejohn, B. R., Liu, F., Liu, H., Liu, H. B., Liu, H. D., Liu, H. J., Liu, H. T., Liu, J. C., Liu, J. L., Liu, M., Liu, Q., Liu, R. X., Liu, S. Y., Liu, S. B., Liu, S. L., Liu, X. W., Liu, Y., Lokhov, A., Lombardi, P., Loo, K., Lorenz, S., Lu, C., Lu, H. Q., Lu, J. B., Lu, J. G., Lu, S. X., Lu, X. X., Lubsandorzhiev, B., Lubsandorzhiev, S., Ludhova, L., Luk, K. B., Luo, F. J., Luo, G., Luo, P. W., Luo, S., Luo, W. M., Lyashuk, V., Ma, Q. M., Ma, S., Ma, X. B., Ma, X. Y., Ma, Y. Q., Malyshkin, Y., Mantovani, F., Mao, Y. J., Mari, S. M., Marini, F., Marium, S., Marshall, C., Martellini, C., Martin-Chassard, G., Caicedo, D. A. Martinez, Martini, A., Martino, J., Mayilyan, D., McDonald, K. T., McKeown, R. D., Müller, A., Meng, G., Meng, Y., Meregaglia, A., Meroni, E., Meyhöfer, D., Mezzetto, M., Miller, J., Miramonti, L., Monforte, S., Montini, P., Montuschi, M., Morozov, N., Muralidharan, P., Napolitano, J., Nastasi, M., Naumov, D. V., Naumova, E., Nemchenok, I., Nikolaev, A., Ning, F. P., Ning, Z., Nunokawa, H., Oberauer, L., Ochoa-Ricoux, J. P., Olshevskiy, A., Ortica, F., Pan, H. R., Paoloni, A., Park, J., Parkalian, N., Parmeggiano, S., Patton, S., Payupol, T., Pec, V., Pedretti, D., Pei, Y. T., Pelliccia, N., Peng, A. G., Peng, H. P., Peng, J. C., Perrot, F., Petitjean, P. A., Rico, L. F. Pineres, Popov, A., Poussot, P., Pratumwan, W., Previtali, E., Pun, C. S. J., Qi, F. Z., Qi, M., Qian, S., Qian, X., Qian, X. H., Qiao, H., Qin, Z. H., Qiu, S. K., Rajput, M., Ranucci, G., Raper, N., Re, A., Rebber, H., Rebii, A., Ren, B., Ren, J., Reveco, C. M., Rezinko, T., Ricci, B., Robens, M., Roche, M., Rodphai, N., Rohwer, L., Romani, A., Rosero, R., Roskovec, B., Roth, C., Ruan, X. C., Ruan, X. D., Rujirawat, S., Rybnikov, A., Sadovsky, A., Saggese, P., Salamanna, G., Sangka, A., Sanguansak, N., Sawangwit, U., Sawatzki, J., Sawy, F., Schever, M., Schuler, J., Schwab, C., Schweizer, K., Selivanov, D., Selyunin, A., Serafini, A., Settanta, G., Settimo, M., Shahzad, M., Shi, G., Shi, J. Y., Shi, Y. J., Shutov, V., Sidorenkov, A., Simkovic, F., Sirignano, C., Siripak, J., Sisti, M., Slupecki, M., Smirnov, M., Smirnov, O., Sogo-Bezerra, T., Songwadhana, J., Soonthornthum, B., Sotnikov, A., Sramek, O., Sreethawong, W., Stahl, A., Stanco, L., Stankevich, K., Stefanik, D., Steiger, H., Steiner, H., Steinmann, J., Stender, M., Strati, V., Studenikin, A., Sun, G. X., Sun, L. T., Sun, J. L., Sun, S. F., Sun, X. L., Sun, Y. J., Sun, Y. Z., Suwonjandee, N., Szelezniak, M., Tang, J., Tang, Q., Tang, X., Tietzsch, A., Tkachev, I., Tmej, T., Treskov, K., Troni, G., Trzaska, W., Tse, W. -H., Tull, C. E., Tuve, C., van Waasen, S., Boom, J. Vanden, Vassilopoulos, N., Vedin, V., Verde, G., Vialkov, M., Viaud, B., Viren, B., Volpe, C., Vorobel, V., Votano, L., Walker, P., Wang, C., Wang, C. H., Wang, E., Wang, G. L., Wang, J., Wang, K. Y., Wang, L., Wang, M. F., Wang, M., Wang, N. Y., Wang, R. G., Wang, S. G., Wang, W., Wang, W. S., Wang, X., Wang, X. Y., Wang, Y., Wang, Y. F., Wang, Y. G., Wang, Y. M., Wang, Y. Q., Wang, Z., Wang, Z. M., Wang, Z. Y., Watcharangkool, A., Wei, H. Y., Wei, L. H., Wei, W., Wei, Y. D., Wen, L. J., Whisnant, K., White, C. G., Wiebusch, C., Wong, S. C. F., Wong, H. L. H., Wonsak, B., Worcester, E., Wu, C. H., Wu, D. R., Wu, F. L., Wu, Q., Wu, W. J., Wu, Z., Wurm, M., Wurtz, J., Wysotzki, C., Xi, Y. F., Xia, D. M., Xie, Y. G., Xie, Z. Q., Xing, Z. Z., Xu, D. L., Xu, F. R., Xu, H. K., Xu, J. L., Xu, J., Xu, M. H., Xu, T., Xu, Y., Xue, T., Yan, B. J., Yan, X. B., Yan, Y. P., Yang, A. B., Yang, C. G., Yang, H., Yang, J., Yang, L., Yang, X. Y., Yang, Y. F., Yang, Y. Z., Yao, H. F., Yasin, Z., Ye, J. X., Ye, M., Yegin, U., Yeh, M., Yermia, F., Yi, P. H., You, Z. Y., Young, B. L., Yu, B. X., Yu, C. X., Yu, C. Y., Yu, H. Z., Yu, M., Yu, X. H., Yu, Z. Y., Yuan, C. Z., Yuan, Y., Yuan, Z. X., Yuan, Z. Y., Yue, B. B., Zafar, N., Zambanini, A., Zeng, P., Zeng, S., Zeng, T. X., Zeng, Y. D., Zhan, L., Zhang, C., Zhang, F. Y., Zhang, G. Q., Zhang, H. H., Zhang, H. Q., Zhang, J., Zhang, J. B., Zhang, J. W., Zhang, P., Zhang, Q. M., Zhang, T., Zhang, X. M., Zhang, X. T., Zhang, Y., Zhang, Y. H., Zhang, Y. M., Zhang, Y. P., Zhang, Y. X., Zhang, Y. Y., Zhang, Z. J., Zhang, Z. P., Zhang, Z. Y., Zhao, F. Y., Zhao, J., Zhao, R., Zhao, S. J., Zhao, T. C., Zheng, D. Q., Zheng, H., Zheng, M. S., Zheng, Y. H., Zhong, W. R., Zhou, J., Zhou, L., Zhou, N., Zhou, S., Zhou, X., Zhu, J., Zhu, K. J., Zhuang, H. L., Zong, L., and Zou, J. H.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: To maximize the light yield of the liquid scintillator (LS) for the Jiangmen Underground Neutrino Observatory (JUNO), a 20 t LS sample was produced in a pilot plant at Daya Bay. The optical properties of the new LS in various compositions were studied by replacing the gadolinium-loaded LS in one antineutrino detector. The concentrations of the fluor, PPO, and the wavelength shifter, bis-MSB, were increased in 12 steps from 0.5 g/L and <0.01 mg/L to 4 g/L and 13 mg/L, respectively. The numbers of total detected photoelectrons suggest that, with the optically purified solvent, the bis-MSB concentration does not need to be more than 4 mg/L. To bridge the one order of magnitude in the detector size difference between Daya Bay and JUNO, the Daya Bay data were used to tune the parameters of a newly developed optical model. Then, the model and tuned parameters were used in the JUNO simulation. This enabled to determine the optimal composition for the JUNO LS: purified solvent LAB with 2.5 g/L PPO, and 1 to 4 mg/L bis-MSB., Comment: 13 pages, 8 figures
Published: 2020

20. Improved upper limits on the 21-cm signal power spectrum of neutral hydrogen at $\boldsymbol{z \approx 9.1}$ from LOFAR

Author: Mertens, F. G., Mevius, M., Koopmans, L. V. E, Offringa, A. R., Mellema, G., Zaroubi, S., Brentjens, M. A., Gan, H., Gehlot, B. K., Pandey, V. N., Sardarabadi, A. M., Vedantham, H. K., Yatawatta, S., Asad, K. M. B., Ciardi, B., Chapman, E., Gazagnes, S., Ghara, R., Ghosh, A., Giri, S. K., Iliev, I. T., Jelić, V., Kooistra, R., Mondal, R., Schaye, J., and Silva, M. B.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: A new upper limit on the 21-cm signal power spectrum at a redshift of $z \approx 9.1$ is presented, based on 141 hours of data obtained with the Low-Frequency Array (LOFAR). The analysis includes significant improvements in spectrally-smooth gain-calibration, Gaussian Process Regression (GPR) foreground mitigation and optimally-weighted power spectrum inference. Previously seen `excess power' due to spectral structure in the gain solutions has markedly reduced but some excess power still remains with a spectral correlation distinct from thermal noise. This excess has a spectral coherence scale of $0.25 - 0.45$\,MHz and is partially correlated between nights, especially in the foreground wedge region. The correlation is stronger between nights covering similar local sidereal times. A best 2-$\sigma$ upper limit of $\Delta^2_{21} < (73)^2\,\mathrm{mK^2}$ at $k = 0.075\,\mathrm{h\,cMpc^{-1}}$ is found, an improvement by a factor $\approx 8$ in power compared to the previously reported upper limit. The remaining excess power could be due to residual foreground emission from sources or diffuse emission far away from the phase centre, polarization leakage, chromatic calibration errors, ionosphere, or low-level radio-frequency interference. We discuss future improvements to the signal processing chain that can further reduce or even eliminate these causes of excess power., Comment: 27 pages, 14 figues, accepted in MNRAS (updated with reference to accompanying paper)
Published: 2020
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21. Risk Assessment of Allergic Diseases Among Preschool Children in Guangzhou, China: A Cross-Sectional Study

Author: Huang Z, Gan H, Huang Y, Zhu H, Liu T, Chen T, Lin R, Xie M, and Sun B
Subjects: cross-sectional, heritability, risk factor, questionnaire, allergic rhinitis, Immunologic diseases. Allergy, RC581-607
Abstract: Zhifeng Huang,1,&ast; Hui Gan,1,&ast; Yiyun Huang,2,&ast; Huiqing Zhu,1 Tingting Liu,1 Tong Chen,1 Runpei Lin,1 Manrong Xie,2 Baoqing Sun1 1Department of Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, People’s Republic of China; 2Helong Street Community Health Service Center, Guangzhou, Guangdong, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Baoqing Sun; Manrong Xie, Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510180, People’s Republic of China, Tel +86 18816781502, Email sunbaoqing@vip.163.com; Xmr20041103@163.comPurpose: To investigate the lifestyle and stress of mothers during pregnancy to analyze the risk factors for the disease in early childhood.Patients and Methods: A cross-sectional survey was conducted from January 2022 to June 2022 in a sub-district in Guangzhou, China. A total of 3437 valid questionnaires were eventually collected. The questionnaire consisted of 56 questions in three sections included questions on child’s birth conditions and early life environment, questions on mother’s lifestyle during pregnancy, and questions about father.Results: 49.75% of the children were likely to have allergic diseases (suspected allergy group). There were more boys in the suspected allergy group (58% vs 50%), and the percentage of children born at first birth was also higher in the suspected allergy group (61% vs 51%). 67% to 69% of children had suspicious allergies when one parent claimed an allergy, and 80.1% when both parents reported an allergy. The results of the multifactorial logistic model showed that male had 1.49 (1.28 to 1.73) times the risk of allergic diseases than female, and preterm births increased the risk of allergic diseases by 1.53 (1.13– 2.07) times compared to full-term births. Both unplanned pregnancies and pregnancy complications increased the risk of allergic diseases in children before school age [1.34 (1.15– 1.55) and 1.82 (1.46– 2.26)]. Among pregnant women who reported regular passive smoking, the risk of the disease was increased 2.43 (1.71 to 3.50) times in preschool children. Reported allergies in all family members were significant risk factors for allergic diseases in children, especially mother [2.88 (2.41~3.46)]. In the prenatal period, maternal negative emotions are more common in children with suspected allergies.Conclusion: Nearly half of the children in the region suffer from allergic diseases. Sex, birth order and full-term delivery all contributed to early childhood allergy. Family history of allergy, especially maternal, was the most important risk factor, and the number of family members with allergy was significantly associated with the allergy in children. Maternal effects are also reflected in prenatal conditions such as unplanned pregnancy, smoke exposure, pregnancy complications, and prenatal stress.Keywords: cross-sectional, heritability, risk factor, questionnaire, allergic rhinitis
Published: 2023

22. Monitoring of Atmospheric Corrosion in a Mass Rapid Transit (MRT) Tunnel

Author: Goh, S. M., Tan, L. T., Gan, H. Y., Foo, Y. L., Goh, K. H., and Lee, H. S.
Published: 2022
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23. Hybrid quantum computation gate with trapped ion system

Author: Gan, H. C. J., Maslennikov, Gleb, Tseng, Ko-Wei, Nguyen, Chihuan, and Matsukevich, Dzmitry
Subjects: Quantum Physics, Physics - Atomic Physics
Abstract: The hybrid approach to quantum computation simultaneously utilizes both discrete and continuous variables which offers the advantage of higher density encoding and processing powers for the same physical resources. Trapped ions, with discrete internal states and motional modes which can be described by continuous variables in an infinite dimensional Hilbert space, offer a natural platform for this approach. A nonlinear gate for universal quantum computing can be implemented with the conditional beam splitter Hamiltonian $|e\rangle \langle e| ( a^{\dagger} b + a b^{\dagger})$ that swaps the quantum states of two motional modes, depending on the ion's internal state. We realize such a gate and demonstrate its applications for quantum state overlap measurements, single-shot parity measurement, and generation of NOON states., Comment: 10 pages, 7 figures
Published: 2019
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24. Surface-induced positive planar Hall effect in topological Kondo insulator SmB6 microribbons

Author: Zhou, L., Ye, B. C., Gan, H. B., Tang, J. Y., Chen, P. B., Du, Z. Z., Tian, Y., Deng, S. Z., Guo, G. P., Lu, H. Z., Liu, F., and He, H. T.
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science
Abstract: Whether the surface states in SmB6 are topological is still a critical issue in the field of topological Kondo insulators. In the magneto-transport study of single crystalline SmB6 microribbons, we have revealed a positive planar Hall effect (PHE), the amplitude of which increases dramatically with decreasing temperatures but saturates below 5 K. This positive PHE is ascribed to the surface states of SmB6 and expected to arise from the anisotropy in lifting the topological protection from back-scattering by the in-plane magnetic field, thus suggesting the topological nature of surface states in SmB6. On the contrary, a negative PHE is observed for the bulk states at high temperatures, which is almost three orders of magnitudes weaker than the surface-induced positive PHE.
Published: 2019
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25. Combined Silver Sulfadiazine Nanosuspension with Thermosensitive Hydrogel: An Effective Antibacterial Treatment for Wound Healing in an Animal Model

Author: Liu X, Fan H, Meng Z, Wu Z, Gu R, Zhu X, Gan H, and Dou G
Subjects: antibacterial agent, nanosuspension, thermosensitive hydrogel, silver sulfadiazine, acute toxicity, burn wound model., Medicine (General), R5-920
Abstract: Xiaoya Liu,1,2 Haiyang Fan,3 Zhiyun Meng,2 Zhuona Wu,2 Ruolan Gu,2 Xiaoxia Zhu,2 Hui Gan,2 Guifang Dou2 1Department of Pharmacy, Shenzhen Children’s Hospital, Shenzhen, Guangdong Province, 518026, People’s Republic of China; 2Department of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Academy of Military Medical Sciences, Beijing, 100850, People’s Republic of China; 3Department of Thoracic Surgery, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong Province, 518102, People’s Republic of ChinaCorrespondence: Guifang Dou; Hui Gan, Department of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Academy of Military Medical Sciences, Beijing, 100850, People’s Republic of China, Tel +86 10 66932951, Fax +86 10 66931993, Email dougf@bmi.ac.cn; ganh2003@163.comIntroduction: Silver sulfadiazine (AgSD) is widely used in burn wound treatment due to its broad-spectrum antibacterial activity. However, its application in wound healing is greatly hindered by the low solubility of AgSD particles and their cellular cytotoxicity. Herein, we studied the safety and in vivo efficacy of nano-sized silver sulfadiazine loaded in poloxamer thermosensitive hydrogel (NS/Gel).Methods: In NS/Gel, silver sulfadiazine was prepared into silver sulfadiazine nanosuspension (NS) to improve the solubility and enhance its antibacterial activity, whereas the poloxamer thermosensitive hydrogel was selected as a drug carrier of NS to achieve slow drug release and reduced cytotoxicity. The acute toxicity of silver sulfadiazine nanosuspension was first evaluated in healthy mice, and its median lethal dose (LD50) was calculated by the modified Karber method. Furthermore, in vivo antibacterial effect and wound healing property of NS/Gel were evaluated on the infected deep second-degree burn wound mice model.Results: The mortality ratio of mice was concentration-dependent, and the LD50 for silver sulfadiazine nanosuspension was estimated to be 252.1 mg/kg (230.8 to 275.4 mg/kg, 95% confidence limit). The in vivo dosages used for burn wound treatment (40– 50 mg/kg) were far below LD50 (252.1 mg/kg). NS/Gel significantly accelerated wound healing in the deep second wound infection mice model, achieving > 85% wound contraction on day 14. Staphylococcus aureus in the wound region was eradicated after 7 days in NS/Gel group, while the bacterial colony count was still measurable in the control group. Histological analysis and cytokines measurement confirmed that the mice treated with NS/Gel exhibited well-organized epithelium and multiple keratinized cell layers compared to control groups with the modulated expression of IL-6, VEGF, and TGF-β.Conclusion: The combination of silver sulfadiazine nanosuspension and thermo-responsive hydrogel has great potential in clinical burn wound treatment.Keywords: silver sulfadiazine, antibacterial agent, thermosensitive hydrogel, acute toxicity, burn wound model, median lethal dose
Published: 2023

26. Synthesis of 2-Arylmethylbenzoxazoles by S8-Mediated Cyclization of 2-Aminophenols with Styrenes

Author: Duan, Y. R., Wu, H. L., and Gan, H. F.
Published: 2022
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27. A fast radio burst source at a complex magnetized site in a barred galaxy

Author: Xu, H., Niu, J. R., Chen, P., Lee, K. J., Zhu, W. W., Dong, S., Zhang, B., Jiang, J. C., Wang, B. J., Xu, J. W., Zhang, C. F., Fu, H., Filippenko, A. V., Peng, E. W., Zhou, D. J., Zhang, Y. K., Wang, P., Feng, Y., Li, Y., Brink, T. G., Li, D. Z., Lu, W., Yang, Y. P., Caballero, R. N., Cai, C., Chen, M. Z., Dai, Z. G., Djorgovski, S. G., Esamdin, A., Gan, H. Q., Guhathakurta, P., Han, J. L., Hao, L. F., Huang, Y. X., Jiang, P., Li, C. K., Li, D., Li, H., Li, X. Q., Li, Z. X., Liu, Z. Y., Luo, R., Men, Y. P., Niu, C. H., Peng, W. X., Qian, L., Song, L. M., Stern, D., Stockton, A., Sun, J. H., Wang, F. Y., Wang, M., Wang, N., Wang, W. Y., Wu, X. F., Xiao, S., Xiong, S. L., Xu, Y. H., Xu, R. X., Yang, J., Yang, X., Yao, R., Yi, Q. B., Yue, Y. L., Yu, D. J., Yu, W. F., Yuan, J. P., Zhang, B. B., Zhang, S. B., Zhang, S. N., Zhao, Y., Zheng, W. K., Zhu, Y., and Zou, J. H.
Published: 2022
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28. Sensitization to Furry Animals in Patients with Suspected Allergic Disease in China: A Multicenter Study

Author: Zhu H, Huang Z, Liu T, An N, Gan H, Huang D, Hao C, Luo W, and Sun B
Subjects: animal allergen, specific immunoglobulin e, cross-sectional survey, suspected allergic patient, Immunologic diseases. Allergy, RC581-607
Abstract: Huiqing Zhu,1,&ast; Zhifeng Huang,1,&ast; Tingting Liu,1 Nairui An,1 Hui Gan,1 Dongming Huang,2 Chuangli Hao,3 Wenting Luo,1 Baoqing Sun1 1Department of Allergy and Clinical Immunology, Department of Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, People’s Republic of China; 2Department of Pediatrics, Boai Hospital of Zhongshan City, Zhongshan, 528400, People’s Republic of China; 3Department of Respirology, Children’s Hospital, Soochow University, Suzhou, 215025, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Baoqing Sun; Wenting Luo, Department of Allergy and Clinical Immunology, Department of Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, 151 Yanjiangxi Road, Guangzhou, 510120, Guangdong, People’s Republic of China, Tel +86 20 8306 2865, Fax +86 20 8306 2729, Email sunbaoqing@vip.163.com; 348307379@qq.comPurpose: An objective of this study was to investigate the allergen sensitization characteristics of cat, dog and horse dander in patients with suspected allergic diseases in different geographical regions of Chinese mainland.Patients and Methods: We invited 2377 patients aged 0– 86 years with suspected allergic diseases to participate in a cross-sectional survey in 11 provinces in China. Combined with the questionnaires and animal-specific IgE levels, we analyzed the epidemiological characteristics and risk factors of furry animal sensitization in different regions and populations of Chinese Mainland.Results: Among the 2377 patients with suspected allergic diseases, 14.9% were sensitized to cat dander, 9.3% to dog dander and 5.5% to horse dander. Animal allergens mainly cause low-level sensitization (class 1– 3). There was a significant correlation between cat, dog and horse dander allergen sIgE, with correlation coefficients (rs) all greater than 0.750. The majority (46.5%) of sIgE-positive patients were sensitized to at least two animal allergens simultaneously. The prevalence of these animals all showed a trend of increasing first and then decreasing with age, and all reached the peak in young adolescence. As for the geographical factors, the sensitization rate of cats and dogs in Western was significantly higher than that in Eastern (cat: 18.4% vs 9.2%, dog: 11.6% vs 5.5%, all P < 0.001), however, no significant differences were found in horses. Aged ≤ 6 years, living in Western, and high animal allergen exposure elevated the risk of cat or dog sensitization. Living on a lower floor (aOR: 0.56) was a protective factor for horse sensitization.Conclusion: In this representative sample of Chinese patients with suspected allergic diseases, there was an apparent geographic variation in sensitization to cats and dogs. Age factor and living in Western also had a significant impact on animal allergen sensitization rate.Keywords: animal allergen, specific immunoglobulin E, cross-sectional survey, suspected allergic patient
Published: 2022

29. Oscillating magnetic field effects in high precision metrology

Author: Gan, H. C. J., Maslennikov, G., Tseng, K. W., Tan, T. R., Kaewuam, R., Arnold, K. J., Matsukevich, D., and Barrett, M. D.
Subjects: Physics - Atomic Physics, Physics - Instrumentation and Detectors, Quantum Physics
Abstract: We examine a range of effects arising from ac magnetic fields in high precision metrology. These results are directly relevant to high precision measurements, and accuracy assessments for state-of-the-art optical clocks. Strategies to characterize these effects are discussed and a simple technique to accurately determine trap-induced ac magnetic fields in a linear Paul trap is demonstrated using $^{171}\mathrm{Yb}^+$, Comment: 10 pages, 6 figures
Published: 2018
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30. PSR J1926-0652: A Pulsar with Interesting Emission Properties Discovered at FAST

Author: Zhang, L, Li, D, Hobbs, G, Agar, CH, Manchester, RN, Weltevrede, P, Coles, WA, Wang, P, Zhu, W, Wen, Z, Yuan, J, Cameron, AD, Dai, S, Liu, K, Zhi, Q, Miao, C, Yuan, M, Cao, S, Feng, L, Gan, H, Gao, L, Gu, X, Guo, M, Hao, Q, Huang, L, Jiang, P, Jin, C, Li, H, Li, Q, Liu, H, Pan, G, Pan, Z, Peng, B, Qian, H, Qian, L, Shi, X, Song, J, Song, L, Sun, C, Sun, J, Wang, H, Wang, Q, Wang, Y, Xie, X, Yan, J, Yang, L, Yang, S, Yao, R, Yu, D, Yu, J, Yue, Y, Zhang, C, Zhang, H, Zhang, S, Zheng, X, Zhou, A, Zhu, B, Zhu, L, Zhu, M, and Zhu, Y
Subjects: pulsars: individual, astro-ph.HE, Astronomy & Astrophysics, Astronomical and Space Sciences, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Physical Chemistry (incl. Structural)
Abstract: We describe PSR J1926-0652, a pulsar recently discovered with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Using sensitive single-pulse detections from FAST and long-term timing observations from the Parkes 64 m radio telescope, we probed phenomena on both long and short timescales. The FAST observations covered a wide frequency range from 270 to 800 MHz, enabling individual pulses to be studied in detail. The pulsar exhibits at least four profile components, short-term nulling lasting from 4 to 450 pulses, complex subpulse drifting behaviors and intermittency on scales of tens of minutes. While the average band spacing P 3 is relatively constant across different bursts and components, significant variations in the separation of adjacent bands are seen, especially near the beginning and end of a burst. Band shapes and slopes are quite variable, especially for the trailing components and for the shorter bursts. We show that for each burst the last detectable pulse prior to emission ceasing has different properties compared to other pulses. These complexities pose challenges for the classic carousel-type models.
Published: 2019

31. Simultaneously enhancing strength and toughness for green poly (butylene succinate) composites by regulating the dispersed rice husk with the silane coupling agent

Author: Gan, H. N., Shen, Y. D., Guo, H., Qin, Y. X., Ren, L., Zhang, M. Y., and Zhang, H. X.
Published: 2023
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32. Approximation of the difference of two Poisson-like counts with Skellam

Author: Gan, H. L. and Kolaczyk, Eric D.
Subjects: Mathematics - Probability, 62E17, 60F05, 60J27
Abstract: Poisson-like behavior for event count data is ubiquitous in nature. At the same time, differencing of such counts arises in the course of data processing in a variety of areas of application. As a result, the Skellam distribution -- defined as the distribution of the difference of two independent Poisson random variables -- is a natural candidate for approximating the difference of Poisson-like event counts. However, in many contexts strict independence, whether between counts or among events within counts, is not a tenable assumption. Here we characterize the accuracy in approximating the difference of Poisson-like counts by a Skellam random variable. Our results fully generalize existing, more limited results in this direction and, at the same time, our derivations are significantly more concise and elegant. We illustrate the potential impact of these results in the context of problems from network analysis and image processing, where various forms of weak dependence can be expected., Comment: 17 pages; Minor revisions
Published: 2017

33. Improving approximation error bounds via truncation

Author: Gan, H. L.
Subjects: Mathematics - Probability, 60F05
Abstract: One aspect of Poisson approximation is that the support of the random variable of interest is often finite while the support of the Poisson distribution is not. In this paper we will remedy this by examining truncated negative binomial (of which Poisson is a special limiting case) approximation, so as to match the two supports of both distributions, and show that this will lead to improvements in the error bounds of the approximation., Comment: 6 pages
Published: 2017

34. A Study of Atmospheric Corrosive Environment in the North East Line Tunnel

Author: Tan, L. T., Goh, S. M., Gan, H. Y., Foo, Y. L., Cavas-Martínez, Francisco, Series Editor, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Series Editor, Ivanov, Vitalii, Series Editor, Kwon, Young W., Series Editor, Trojanowska, Justyna, Series Editor, Gelman, Len, editor, Martin, Nadine, editor, Malcolm, Andrew A., editor, and (Edmund) Liew, Chin Kian, editor
Published: 2021
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35. The infiltration of MALT B cells could predict a poor prognosis in clear cell renal carcinoma: Results from single-cell transcriptomics and spatial transcriptome

Author: Zhu, S., primary, Tian, X., additional, Chang, K., additional, Gan, H., additional, Qu, Y., additional, Xu, W., additional, Zhang, H., additional, and Ye, D., additional
Published: 2024
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36. Association of the ENPP1/ENTPD1 Polymorphisms in Hemodialysis Patients

Author: Zhang X, Wan Z, Cheng S, and Gan H
Subjects: chronic kidney disease, ckd, single nucleotide polymorphisms, snps, ectonucleotide pyrophosphatase/phosphodiesterase 1, enpp1, ectonucleoside triphosphate diphosphohydrolase 1, entpd1, rs1044498, rs6584026, Medicine (General), R5-920
Abstract: Xi Zhang,1 Ziming Wan,1 Si Cheng,2 Hua Gan1 1Department of Nephrology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China; 2Department of Orthopaedics, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of ChinaCorrespondence: Hua GanDepartment of Nephrology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of ChinaEmail correspondzx@126.comIntroduction: ENPP1 and ENTPD1 are two main enzymes involved in ATP-AMP-ADP-adenosine axis, which is associated with lipid metabolism, diabetes mellitus (DM) and renal fibrosis. The single nucleotide polymorphisms (SNPs) of ENPP1 and ENTPD1, rs1044498 and rs6584026, are associated with these factors. This retrospective study aimed to address the two SNPs variants in hemodialysis (HD) patients and analyzes their relations with clinical characteristics.Methods: This study included 543 regular HD patients over 3 months at our center. Overnight fasting peripheral blood sample was taken from each subject to extract the DNA. The genotypes of rs1044498 and rs6584026 were detected by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. The basic clinical data were noted such as sex, age, and HD-age, and the main causes of chronic kidney disease (CKD) and the clinical characteristics were collected on average at least three times in half a year. T-test and Chi-test were performed for the statistical analyses. Binary logistic regression was applied for the significant parameters by excluding the confounders, gender, age and HD-age. All statistical tests were considered significant for P< 0.05.Results: The rs1044498 genotypes showed in two types, A/A and A/C without C/C. The rs6584026 genotypes were C/C and C/T without T/T. The genotype frequency of rs1044498 (A/C) was 0.238, and the genotype frequency of rs6584026 (C/T) was 0.328. The age and the level of lipoprotein α showed statistical significance with rs1044498 variant (A/C, P< 0.05). The rs6584026 variant (C/T) was frequently found in patients with nephritis (P< 0.05). The albumin, alkaline phosphatase (ALP), lipoprotein α, cholesterol, apolipoprotein B (Apo B), Apo B/A1 and nephritis were independently associated with rs6584026 variant (C/T, P< 0.05) in binary logistic regression model by controlling the confounders of gender, age and HD-age. High level of triglyceride and low level of urine nitrogen were related to rs6584026 variant (C/T, P< 0.05).Conclusion: The rs1044498 and rs6584026 SNPs were related to several high levels of lipids, and rs6584026 variant was related to nephritis and autoimmune disease. The rs6584026 SNP may contribute to the increased risks of cholesterol and ApoB/A1 in HD patients.Keywords: chronic kidney disease, CKD, single nucleotide polymorphisms, SNPs, ectonucleotide pyrophosphatase/phosphodiesterase 1, ENPP1, ectonucleoside triphosphate diphosphohydrolase 1, ENTPD1, rs1044498, rs6584026
Published: 2021

37. All-optical production and transport of a large $^6$Li quantum gas in a crossed optical dipole trap

Author: Gross, Ch., Gan, H. C. J., and Dieckmann, K.
Subjects: Condensed Matter - Quantum Gases, Physics - Atomic Physics
Abstract: We report on an efficient production scheme for a large quantum degenerate sample of fermionic lithium. The approach is based on our previous work on narrow-line $ 2S_{1/2}\rightarrow 3P_{3/2} $ laser cooling resulting in a high phase-space density of up to $3\times10^{-4}$. This allows utilizing a large volume crossed optical dipole trap with a total power of $45\,\textrm{W}$, leading to high loading efficiency and $8\times10^6$ trapped atoms. The same optical trapping configuration is used for rapid adiabatic transport over a distance of $25\,\textrm{cm}$ in $0.9\,\textrm{s}$, and subsequent evaporative cooling. With optimized evaporation we achieve a degenerate Fermi gas with $1.7\times 10^{6}$ atoms at a temperature of $60 \, \textrm{nK}$, corresponding to $T/T_{\text{F}}=0.16\left(2 \right)$. Furthermore, the performance is demonstrated by evaporation near a broad Feshbach resonance creating a molecular Bose-Einstein condensate of $3\times10^5$ lithium dimers.
Published: 2016
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38. Dirichlet approximation of equilibrium distributions in Cannings models with mutation

Author: Gan, H. L., Röllin, Adrian, and Ross, Nathan
Subjects: Mathematics - Probability
Abstract: Consider a haploid population of fixed finite size with a finite number of allele types and having Cannings exchangeable genealogy with neutral mutation. The stationary distribution of the Markov chain of allele counts in each generation is an important quantity in population genetics but has no tractable description in general. We provide upper bounds on the distributional distance between the Dirichlet distribution and this finite population stationary distribution for the Wright-Fisher genealogy with general mutation structure and the Cannings exchangeable genealogy with parent independent mutation structure. In the first case, the bound is small if the population is large and the mutations do not depend too much on parent type; "too much" is naturally quantified by our bound. In the second case, the bound is small if the population is large and the chance of three-mergers in the Cannings genealogy is small relative to the chance of two-mergers; this is the same condition to ensure convergence of the genealogy to Kingman's coalescent. These results follow from a new development of Stein's method for the Dirichlet distribution based on Barbour's generator approach and a probabilistic description of the semigroup of the Wright-Fisher diffusion due to Griffiths, and Li and Tavar\'e., Comment: Ver3: 30 pages, additions, clarifications, and corrections to proofs; main results slightly strengthened; Ver2: 26 pages, added bounds for convex set indicator metric; Ver1: 22 pages
Published: 2016

39. Utilization of the EpiMed Coronabank Chemical Collection to identify potential SARS-CoV-2 antivirals: in silico studies targeting the nsp14 ExoN domain and PL pro naphthalene binding site

Author: Liang, JJ, Pitsillou, E, Lau, HLY, Mccubbery, CP, Gan, H, Hung, A, Karagiannis, TC, Liang, JJ, Pitsillou, E, Lau, HLY, Mccubbery, CP, Gan, H, Hung, A, and Karagiannis, TC
Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome encodes 29 proteins including four structural, 16 nonstructural (nsps), and nine accessory proteins (https://epimedlab.org/sars-cov-2-proteome/). Many of these proteins contain potential targetable sites for the development of antivirals. Despite the widespread use of vaccinations, the emergence of variants necessitates the investigation of new therapeutics and antivirals. Here, the EpiMed Coronabank Chemical Collection (https://epimedlab.org/crl/) was utilized to investigate potential antivirals against the nsp14 exoribonuclease (ExoN) domain. Molecular docking was performed to evaluate the binding characteristics of our chemical library against the nsp14 ExoN site. Based on the initial screen, trisjuglone, ararobinol, corilagin, and naphthofluorescein were identified as potential lead compounds. Molecular dynamics (MD) simulations were subsequently performed, with the results highlighting the stability of the lead compounds in the nsp14 ExoN site. Protein-RNA docking revealed the potential for the lead compounds to disrupt the interaction with RNA when bound to the ExoN site. Moreover, hypericin, cyanidin-3-O-glucoside, and rutin were previously identified as lead compounds targeting the papain-like protease (PLpro) naphthalene binding site. Through performing MD simulations, the stability and interactions of lead compounds with PLpro were further examined. Overall, given the critical role of the exonuclease activity of nsp14 in ensuring viral fidelity and the multifunctional role of PLpro in viral pathobiology and replication, these nsps represent important targets for antiviral drug development. Our databases can be utilized for in silico studies, such as the ones performed here, and this approach can be applied to other potentially druggable SARS-CoV-2 protein targets.
Published: 2024

40. Real-time monitoring for the next core-collapse supernova in JUNO

Author: Abusleme, A, Adam, T, Ahmad, S, Ahmed, R, Aiello, S, Akram, M, Aleem, A, An, F, An, Q, Andronico, G, Anfimov, N, Antonelli, V, Antoshkina, T, Asavapibhop, B, de André, J, Auguste, D, Bai, W, Balashov, N, Baldini, W, Barresi, A, Basilico, D, Baussan, E, Bellato, M, Beretta, M, Bergnoli, A, Bick, D, Bieger, L, Biktemerova, S, Birkenfeld, T, Morton-Blake, I, Blum, D, Blyth, S, Bolshakova, A, Bongrand, M, Bordereau, C, Breton, D, Brigatti, A, Brugnera, R, Bruno, R, Budano, A, Busto, J, Cabrera, A, Caccianiga, B, Cai, H, Cai, X, Cai, Y, Cai, Z, Callier, S, Cammi, A, Campeny, A, Cao, C, Cao, G, Cao, J, Caruso, R, Cerna, C, Cerrone, V, Chan, C, Chang, J, Chang, Y, Chatrabhuti, A, Chen, C, Chen, G, Chen, P, Chen, S, Chen, Y, Chen, Z, Cheng, J, Cheng, Y, Chepurnov, A, Chetverikov, A, Chiesa, D, Chimenti, P, Chin, Y, Chu, Z, Chukanov, A, Claverie, G, Clementi, C, Clerbaux, B, Molla, M, Lorenzo, S, Coppi, A, Corti, D, Csakli, S, Corso, F, Dalager, O, Datta, J, Taille, C, Deng, Z, Ding, X, Ding, Y, Dirgantara, B, Dittrich, C, Dmitrievsky, S, Dohnal, T, Dolzhikov, D, Donchenko, G, Dong, J, Doroshkevich, E, Dou, W, Dracos, M, Druillole, F, Du, R, Du, S, Dugas, K, Dusini, S, Duyang, H, Eck, J, Enqvist, T, Fabbri, A, Fahrendholz, U, Fan, L, Fang, J, Fang, W, Fargetta, M, Fedoseev, D, Fei, Z, Feng, L, Feng, Q, Ferraro, F, Fournier, A, Gan, H, Gao, F, Garfagnini, A, Gavrikov, A, Giammarchi, M, Giudice, N, Gonchar, M, Gong, G, Gong, H, Gornushkin, Y, Göttel, A, Grassi, M, Gromov, M, Gromov, V, Gu, M, Gu, X, Gu, Y, Guan, M, Guan, Y, Guardone, N, Guo, C, Guo, W, Guo, X, Hagner, C, Han, R, Han, Y, He, M, He, W, Heinz, T, Hellmuth, P, Heng, Y, Herrera, R, Hor, Y, Hou, S, Hsiung, Y, Hu, B, Hu, H, Hu, J, Hu, S, Hu, T, Hu, Y, Hu, Z, Huang, G, Huang, H, Huang, J, Huang, K, Huang, W, Huang, X, Huang, Y, Hui, J, Huo, L, Huo, W, Huss, C, Hussain, S, Imbert, L, Ioannisian, A, Isocrate, R, Jafar, A, Jelmini, B, Jeria, I, Ji, X, Jia, H, Jia, J, Jian, S, Jiang, C, Jiang, D, Jiang, W, Jiang, X, Jing, X, Jollet, C, Kampmann, P, Kang, L, Karaparambil, R, Kazarian, N, Khan, A, Khatun, A, Khosonthongkee, K, Korablev, D, Kouzakov, K, Krasnoperov, A, Kuleshov, S, Kutovskiy, N, Labit, L, Lachenmaier, T, Landini, C, Leblanc, S, Lebrin, V, Lefevre, F, Lei, R, Leitner, R, Leung, J, Li, D, Li, F, Li, G, Li, H, Li, J, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liao, J, Limphirat, A, Lin, G, Lin, S, Lin, T, Ling, J, Ling, X, Lippi, I, Liu, C, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Liu, Z, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, P, Lu, S, Lu, X, Lubsandorzhiev, B, Lubsandorzhiev, S, Ludhova, L, Lukanov, A, Luo, D, Luo, F, Luo, G, Luo, J, Luo, S, Luo, W, Luo, X, Lyashuk, V, Ma, B, Ma, Q, Ma, S, Ma, X, Maalmi, J, Magoni, M, Mai, J, Malyshkin, Y, Mandujano, R, Mantovani, F, Mao, X, Mao, Y, Mari, S, Marini, F, Martini, A, Mayer, M, Mayilyan, D, Mednieks, I, Meng, Y, Meraviglia, A, Meregaglia, A, Meroni, E, Meyhöfer, D, Miramonti, L, Mohan, N, Montuschi, M, Müller, A, Nastasi, M, Naumov, D, Naumova, E, Navas-Nicolas, D, Nemchenok, I, Thi, M, Nikolaev, A, Ning, F, Ning, Z, Nunokawa, H, Oberauer, L, Ochoa-Ricoux, J, Olshevskiy, A, Orestano, D, Ortica, F, Othegraven, R, Paoloni, A, Parmeggiano, S, Pei, Y, Pelicci, L, Peng, A, Peng, H, Peng, Y, Peng, Z, Perrot, F, Petitjean, P, Petrucci, F, Pilarczyk, O, Rico, L, Popov, A, Poussot, P, Previtali, E, Qi, F, Qi, M, Qi, X, Qian, S, Qian, X, Qian, Z, Qiao, H, Qin, Z, Qiu, S, Qu, M, Qu, Z, Ranucci, G, Rasheed, R, Re, A, Rebii, A, Redchuk, M, Ren, B, Ren, J, Ricci, B, Rientong, K, Rifai, M, Roche, M, Rodphai, N, Romani, A, Roskovec, B, Ruan, X, Rybnikov, A, Sadovsky, A, Saggese, P, Sandanayake, D, Sangka, A, Sava, G, Sawangwit, U, Schever, M, Schwab, C, Schweizer, K, Selyunin, A, Serafini, A, Settimo, M, Sharov, V, Shaydurova, A, Shi, J, Shi, Y, Shutov, V, Sidorenkov, A, Šimkovic, F, Singhal, A, Sirignano, C, Siripak, J, Sisti, M, Smirnov, M, Smirnov, O, Sogo-Bezerra, T, Sokolov, S, Songwadhana, J, Soonthornthum, B, Sotnikov, A, Šrámek, O, Sreethawong, W, Stahl, A, Stanco, L, Stankevich, K, Steiger, H, Steinmann, J, Sterr, T, Stock, M, Strati, V, Studenikin, A, Su, A, Su, J, Sun, S, Sun, X, Sun, Y, Sun, Z, Suwonjandee, N, Szelezniak, M, Takenaka, A, Tang, J, Tang, Q, Tang, X, Hariharan, V, Theisen, E, Tietzsch, A, Tkachev, I, Tmej, T, Torri, M, Tortorici, F, Treskov, K, Triossi, A, Triozzi, R, Trzaska, W, Tung, Y, Tuve, C, Ushakov, N, Vedin, V, Venettacci, C, Verde, G, Vialkov, M, Viaud, B, Vollbrecht, C, von Sturm, K, Vorobel, V, Voronin, D, Votano, L, Walker, P, Wang, C, Wang, E, Wang, G, Wang, J, Wang, L, Wang, M, Wang, R, Wang, S, Wang, W, Wang, X, Wang, Y, Wang, Z, Watcharangkool, A, Wei, W, Wei, Y, Wen, K, Wen, L, Weng, J, Wiebusch, C, Wirth, R, Wonsak, B, Wu, D, Wu, Q, Wu, Y, Wu, Z, Wurm, M, Wurtz, J, Wysotzki, C, Xi, Y, Xia, D, Xiao, F, Xiao, X, Xie, X, Xie, Y, Xie, Z, Xin, Z, Xing, Z, Xu, B, Xu, C, Xu, D, Xu, F, Xu, H, Xu, J, Xu, M, Xu, X, Xu, Y, Yan, B, Yan, Q, Yan, T, Yan, X, Yan, Y, Yang, C, Yang, J, Yang, L, Yang, X, Yang, Y, Yao, H, Ye, J, Ye, M, Ye, Z, Yermia, F, You, Z, Yu, B, Yu, C, Yu, G, Yu, H, Yu, M, Yu, X, Yu, Z, Yuan, C, Yuan, Y, Yuan, Z, Yue, B, Zafar, N, Zavadskyi, V, Zeng, F, Zeng, S, Zeng, T, Zeng, Y, Zhan, L, Zhang, A, Zhang, B, Zhang, F, Zhang, H, Zhang, J, Zhang, L, Zhang, M, Zhang, P, Zhang, Q, Zhang, S, Zhang, T, Zhang, X, Zhang, Y, Zhang, Z, Zhao, J, Zhao, R, Zhao, S, Zheng, D, Zheng, H, Zheng, Y, Zhong, W, Zhou, J, Zhou, L, Zhou, N, Zhou, S, Zhou, T, Zhou, X, Zhu, J, Zhu, K, Zhu, Z, Zhuang, B, Zhuang, H, Zong, L, Zou, J, Züfle, J, Null, N, Abusleme, Angel, Adam, Thomas, Ahmad, Shakeel, Ahmed, Rizwan, Aiello, Sebastiano, Akram, Muhammad, Aleem, Abid, An, Fengpeng, An, Qi, Andronico, Giuseppe, Anfimov, Nikolay, Antonelli, Vito, Antoshkina, Tatiana, Asavapibhop, Burin, de André, João Pedro Athayde Marcondes, Auguste, Didier, Bai, Weidong, Balashov, Nikita, Baldini, Wander, Barresi, Andrea, Basilico, Davide, Baussan, Eric, Bellato, Marco, Beretta, Marco, Bergnoli, Antonio, Bick, Daniel, Bieger, Lukas, Biktemerova, Svetlana, Birkenfeld, Thilo, Morton-Blake, Iwan, Blum, David, Blyth, Simon, Bolshakova, Anastasia, Bongrand, Mathieu, Bordereau, Clément, Breton, Dominique, Brigatti, Augusto, Brugnera, Riccardo, Bruno, Riccardo, Budano, Antonio, Busto, Jose, Cabrera, Anatael, Caccianiga, Barbara, Cai, Hao, Cai, Xiao, Cai, Yanke, Cai, Zhiyan, Callier, Stéphane, Cammi, Antonio, Campeny, Agustin, Cao, Chuanya, Cao, Guofu, Cao, Jun, Caruso, Rossella, Cerna, Cédric, Cerrone, Vanessa, Chan, Chi, Chang, Jinfan, Chang, Yun, Chatrabhuti, Auttakit, Chen, Chao, Chen, Guoming, Chen, Pingping, Chen, Shaomin, Chen, Yixue, Chen, Yu, Chen, Zhangming, Chen, Zhiyuan, Chen, Zikang, Cheng, Jie, Cheng, Yaping, Cheng, Yu Chin, Chepurnov, Alexander, Chetverikov, Alexey, Chiesa, Davide, Chimenti, Pietro, Chin, Yen-Ting, Chu, Ziliang, Chukanov, Artem, Claverie, Gérard, Clementi, Catia, Clerbaux, Barbara, Molla, Marta Colomer, Lorenzo, Selma Conforti Di, Coppi, Alberto, Corti, Daniele, Csakli, Simon, Corso, Flavio Dal, Dalager, Olivia, Datta, Jaydeep, Taille, Christophe De La, Deng, Zhi, Deng, Ziyan, Ding, Xiaoyu, Ding, Xuefeng, Ding, Yayun, Dirgantara, Bayu, Dittrich, Carsten, Dmitrievsky, Sergey, Dohnal, Tadeas, Dolzhikov, Dmitry, Donchenko, Georgy, Dong, Jianmeng, Doroshkevich, Evgeny, Dou, Wei, Dracos, Marcos, Druillole, Frédéric, Du, Ran, Du, Shuxian, Dugas, Katherine, Dusini, Stefano, Duyang, Hongyue, Eck, Jessica, Enqvist, Timo, Fabbri, Andrea, Fahrendholz, Ulrike, Fan, Lei, Fang, Jian, Fang, Wenxing, Fargetta, Marco, Fedoseev, Dmitry, Fei, Zhengyong, Feng, Li-Cheng, Feng, Qichun, Ferraro, Federico, Fournier, Amélie, Gan, Haonan, Gao, Feng, Garfagnini, Alberto, Gavrikov, Arsenii, Giammarchi, Marco, Giudice, Nunzio, Gonchar, Maxim, Gong, Guanghua, Gong, Hui, Gornushkin, Yuri, Göttel, Alexandre, Grassi, Marco, Gromov, Maxim, Gromov, Vasily, Gu, Minghao, Gu, Xiaofei, Gu, Yu, Guan, Mengyun, Guan, Yuduo, Guardone, Nunzio, Guo, Cong, Guo, Wanlei, Guo, Xinheng, Hagner, Caren, Han, Ran, Han, Yang, He, Miao, He, Wei, Heinz, Tobias, Hellmuth, Patrick, Heng, Yuekun, Herrera, Rafael, Hor, YuenKeung, Hou, Shaojing, Hsiung, Yee, Hu, Bei-Zhen, Hu, Hang, Hu, Jianrun, Hu, Jun, Hu, Shouyang, Hu, Tao, Hu, Yuxiang, Hu, Zhuojun, Huang, Guihong, Huang, Hanxiong, Huang, Jinhao, Huang, Junting, Huang, Kaixuan, Huang, Wenhao, Huang, Xin, Huang, Xingtao, Huang, Yongbo, Hui, Jiaqi, Huo, Lei, Huo, Wenju, Huss, Cédric, Hussain, Safeer, Imbert, Leonard, Ioannisian, Ara, Isocrate, Roberto, Jafar, Arshak, Jelmini, Beatrice, Jeria, Ignacio, Ji, Xiaolu, Jia, Huihui, Jia, Junji, Jian, Siyu, Jiang, Cailian, Jiang, Di, Jiang, Wei, Jiang, Xiaoshan, Jing, Xiaoping, Jollet, Cécile, Kampmann, Philipp, Kang, Li, Karaparambil, Rebin, Kazarian, Narine, Khan, Ali, Khatun, Amina, Khosonthongkee, Khanchai, Korablev, Denis, Kouzakov, Konstantin, Krasnoperov, Alexey, Kuleshov, Sergey, Kutovskiy, Nikolay, Labit, Loïc, Lachenmaier, Tobias, Landini, Cecilia, Leblanc, Sébastien, Lebrin, Victor, Lefevre, Frederic, Lei, Ruiting, Leitner, Rupert, Leung, Jason, Li, Demin, Li, Fei, Li, Fule, Li, Gaosong, Li, Huiling, Li, Jiajun, Li, Mengzhao, Li, Min, Li, Nan, Li, Qingjiang, Li, Ruhui, Li, Rui, Li, Shanfeng, Li, Tao, Li, Teng, Li, Weidong, Li, Weiguo, Li, Xiaomei, Li, Xiaonan, Li, Xinglong, Li, Yi, Li, Yichen, Li, Yufeng, Li, Zhaohan, Li, Zhibing, Li, Ziyuan, Li, Zonghai, Liang, Hao, Liao, Jiajun, Limphirat, Ayut, Lin, Guey-Lin, Lin, Shengxin, Lin, Tao, Ling, Jiajie, Ling, Xin, Lippi, Ivano, Liu, Caimei, Liu, Fang, Liu, Fengcheng, Liu, Haidong, Liu, Haotian, Liu, Hongbang, Liu, Hongjuan, Liu, Hongtao, Liu, Hui, Liu, Jianglai, Liu, Jiaxi, Liu, Jinchang, Liu, Min, Liu, Qian, Liu, Qin, Liu, Runxuan, Liu, Shenghui, Liu, Shubin, Liu, Shulin, Liu, Xiaowei, Liu, Xiwen, Liu, Xuewei, Liu, Yankai, Liu, Zhen, Lokhov, Alexey, Lombardi, Paolo, Lombardo, Claudio, Loo, Kai, Lu, Chuan, Lu, Haoqi, Lu, Jingbin, Lu, Junguang, Lu, Peizhi, Lu, Shuxiang, Lu, Xianguo, Lubsandorzhiev, Bayarto, Lubsandorzhiev, Sultim, Ludhova, Livia, Lukanov, Arslan, Luo, Daibin, Luo, Fengjiao, Luo, Guang, Luo, Jianyi, Luo, Shu, Luo, Wuming, Luo, Xiaojie, Lyashuk, Vladimir, Ma, Bangzheng, Ma, Bing, Ma, Qiumei, Ma, Si, Ma, Xiaoyan, Ma, Xubo, Maalmi, Jihane, Magoni, Marco, Mai, Jingyu, Malyshkin, Yury, Mandujano, Roberto Carlos, Mantovani, Fabio, Mao, Xin, Mao, Yajun, Mari, Stefano M., Marini, Filippo, Martini, Agnese, Mayer, Matthias, Mayilyan, Davit, Mednieks, Ints, Meng, Yue, Meraviglia, Anita, Meregaglia, Anselmo, Meroni, Emanuela, Meyhöfer, David, Miramonti, Lino, Mohan, Nikhil, Montuschi, Michele, Müller, Axel, Nastasi, Massimiliano, Naumov, Dmitry V., Naumova, Elena, Navas-Nicolas, Diana, Nemchenok, Igor, Thi, Minh Thuan Nguyen, Nikolaev, Alexey, Ning, Feipeng, Ning, Zhe, Nunokawa, Hiroshi, Oberauer, Lothar, Ochoa-Ricoux, Juan Pedro, Olshevskiy, Alexander, Orestano, Domizia, Ortica, Fausto, Othegraven, Rainer, Paoloni, Alessandro, Parmeggiano, Sergio, Pei, Yatian, Pelicci, Luca, Peng, Anguo, Peng, Haiping, Peng, Yu, Peng, Zhaoyuan, Perrot, Frédéric, Petitjean, Pierre-Alexandre, Petrucci, Fabrizio, Pilarczyk, Oliver, Rico, Luis Felipe Piñeres, Popov, Artyom, Poussot, Pascal, Previtali, Ezio, Qi, Fazhi, Qi, Ming, Qi, Xiaohui, Qian, Sen, Qian, Xiaohui, Qian, Zhen, Qiao, Hao, Qin, Zhonghua, Qiu, Shoukang, Qu, Manhao, Qu, Zhenning, Ranucci, Gioacchino, Rasheed, Reem, Re, Alessandra, Rebii, Abdel, Redchuk, Mariia, Ren, Bin, Ren, Jie, Ricci, Barbara, Rientong, Komkrit, Rifai, Mariam, Roche, Mathieu, Rodphai, Narongkiat, Romani, Aldo, Roskovec, Bedřich, Ruan, Xichao, Rybnikov, Arseniy, Sadovsky, Andrey, Saggese, Paolo, Sandanayake, Deshan, Sangka, Anut, Sava, Giuseppe, Sawangwit, Utane, Schever, Michaela, Schwab, Cédric, Schweizer, Konstantin, Selyunin, Alexandr, Serafini, Andrea, Settimo, Mariangela, Sharov, Vladislav, Shaydurova, Arina, Shi, Jingyan, Shi, Yanan, Shutov, Vitaly, Sidorenkov, Andrey, Šimkovic, Fedor, Singhal, Apeksha, Sirignano, Chiara, Siripak, Jaruchit, Sisti, Monica, Smirnov, Mikhail, Smirnov, Oleg, Sogo-Bezerra, Thiago, Sokolov, Sergey, Songwadhana, Julanan, Soonthornthum, Boonrucksar, Sotnikov, Albert, Šrámek, Ondřej, Sreethawong, Warintorn, Stahl, Achim, Stanco, Luca, Stankevich, Konstantin, Steiger, Hans, Steinmann, Jochen, Sterr, Tobias, Stock, Matthias Raphael, Strati, Virginia, Studenikin, Alexander, Su, Aoqi, Su, Jun, Sun, Shifeng, Sun, Xilei, Sun, Yongjie, Sun, Yongzhao, Sun, Zhengyang, Suwonjandee, Narumon, Szelezniak, Michal, Takenaka, Akira, Tang, Jian, Tang, Qiang, Tang, Quan, Tang, Xiao, Hariharan, Vidhya Thara, Theisen, Eric, Tietzsch, Alexander, Tkachev, Igor, Tmej, Tomas, Torri, Marco Danilo Claudio, Tortorici, Francesco, Treskov, Konstantin, Triossi, Andrea, Triozzi, Riccardo, Trzaska, Wladyslaw, Tung, Yu-Chen, Tuve, Cristina, Ushakov, Nikita, Vedin, Vadim, Venettacci, Carlo, Verde, Giuseppe, Vialkov, Maxim, Viaud, Benoit, Vollbrecht, Cornelius Moritz, von Sturm, Katharina, Vorobel, Vit, Voronin, Dmitriy, Votano, Lucia, Walker, Pablo, Wang, Caishen, Wang, Chung-Hsiang, Wang, En, Wang, Guoli, Wang, Jian, Wang, Jun, Wang, Li, Wang, Lu, Wang, Meng, Wang, Ruiguang, Wang, Siguang, Wang, Wei, Wang, Wenshuai, Wang, Xi, Wang, Xiangyue, Wang, Yangfu, Wang, Yaoguang, Wang, Yi, Wang, Yifang, Wang, Yuanqing, Wang, Yuyi, Wang, Zhe, Wang, Zheng, Wang, Zhimin, Watcharangkool, Apimook, Wei, Wei, Wei, Wenlu, Wei, Yadong, Wei, Yuehuan, Wen, Kaile, Wen, Liangjian, Weng, Jun, Wiebusch, Christopher, Wirth, Rosmarie, Wonsak, Bjoern, Wu, Diru, Wu, Qun, Wu, Yiyang, Wu, Zhi, Wurm, Michael, Wurtz, Jacques, Wysotzki, Christian, Xi, Yufei, Xia, Dongmei, Xiao, Fei, Xiao, Xiang, Xie, Xiaochuan, Xie, Yuguang, Xie, Zhangquan, Xin, Zhao, Xing, Zhizhong, Xu, Benda, Xu, Cheng, Xu, Donglian, Xu, Fanrong, Xu, Hangkun, Xu, Jilei, Xu, Jing, Xu, Meihang, Xu, Xunjie, Xu, Yin, Xu, Yu, Yan, Baojun, Yan, Qiyu, Yan, Taylor, Yan, Xiongbo, Yan, Yupeng, Yang, Changgen, Yang, Chengfeng, Yang, Jie, Yang, Lei, Yang, Xiaoyu, Yang, Yifan, Yao, Haifeng, Ye, Jiaxuan, Ye, Mei, Ye, Ziping, Yermia, Frédéric, You, Zhengyun, Yu, Boxiang, Yu, Chiye, Yu, Chunxu, Yu, Guojun, Yu, Hongzhao, Yu, Miao, Yu, Xianghui, Yu, Zeyuan, Yu, Zezhong, Yuan, Cenxi, Yuan, Chengzhuo, Yuan, Ying, Yuan, Zhenxiong, Yue, Baobiao, Zafar, Noman, Zavadskyi, Vitalii, Zeng, Fanrui, Zeng, Shan, Zeng, Tingxuan, Zeng, Yuda, Zhan, Liang, Zhang, Aiqiang, Zhang, Bin, Zhang, Binting, Zhang, Feiyang, Zhang, Haosen, Zhang, Honghao, Zhang, Jialiang, Zhang, Jiawen, Zhang, Jie, Zhang, Jingbo, Zhang, Jinnan, ZHANG, Lei, Zhang, Mohan, Zhang, Peng, Zhang, Ping, Zhang, Qingmin, Zhang, Shiqi, Zhang, Shu, Zhang, Shuihan, Zhang, Siyuan, Zhang, Tao, Zhang, Xiaomei, Zhang, Xin, Zhang, Xuantong, Zhang, Yinhong, Zhang, Yiyu, Zhang, Yongpeng, Zhang, Yu, Zhang, Yuanyuan, Zhang, Yumei, Zhang, Zhenyu, Zhang, Zhijian, Zhao, Jie, Zhao, Rong, Zhao, Runze, Zhao, Shujun, Zheng, Dongqin, Zheng, Hua, Zheng, Yangheng, Zhong, Weirong, Zhou, Jing, Zhou, Li, Zhou, Nan, Zhou, Shun, Zhou, Tong, Zhou, Xiang, Zhu, Jingsen, Zhu, Kangfu, Zhu, Kejun, Zhu, Zhihang, Zhuang, Bo, Zhuang, Honglin, Zong, Liang, Zou, Jiaheng, Züfle, Jan, null, null, Abusleme, A, Adam, T, Ahmad, S, Ahmed, R, Aiello, S, Akram, M, Aleem, A, An, F, An, Q, Andronico, G, Anfimov, N, Antonelli, V, Antoshkina, T, Asavapibhop, B, de André, J, Auguste, D, Bai, W, Balashov, N, Baldini, W, Barresi, A, Basilico, D, Baussan, E, Bellato, M, Beretta, M, Bergnoli, A, Bick, D, Bieger, L, Biktemerova, S, Birkenfeld, T, Morton-Blake, I, Blum, D, Blyth, S, Bolshakova, A, Bongrand, M, Bordereau, C, Breton, D, Brigatti, A, Brugnera, R, Bruno, R, Budano, A, Busto, J, Cabrera, A, Caccianiga, B, Cai, H, Cai, X, Cai, Y, Cai, Z, Callier, S, Cammi, A, Campeny, A, Cao, C, Cao, G, Cao, J, Caruso, R, Cerna, C, Cerrone, V, Chan, C, Chang, J, Chang, Y, Chatrabhuti, A, Chen, C, Chen, G, Chen, P, Chen, S, Chen, Y, Chen, Z, Cheng, J, Cheng, Y, Chepurnov, A, Chetverikov, A, Chiesa, D, Chimenti, P, Chin, Y, Chu, Z, Chukanov, A, Claverie, G, Clementi, C, Clerbaux, B, Molla, M, Lorenzo, S, Coppi, A, Corti, D, Csakli, S, Corso, F, Dalager, O, Datta, J, Taille, C, Deng, Z, Ding, X, Ding, Y, Dirgantara, B, Dittrich, C, Dmitrievsky, S, Dohnal, T, Dolzhikov, D, Donchenko, G, Dong, J, Doroshkevich, E, Dou, W, Dracos, M, Druillole, F, Du, R, Du, S, Dugas, K, Dusini, S, Duyang, H, Eck, J, Enqvist, T, Fabbri, A, Fahrendholz, U, Fan, L, Fang, J, Fang, W, Fargetta, M, Fedoseev, D, Fei, Z, Feng, L, Feng, Q, Ferraro, F, Fournier, A, Gan, H, Gao, F, Garfagnini, A, Gavrikov, A, Giammarchi, M, Giudice, N, Gonchar, M, Gong, G, Gong, H, Gornushkin, Y, Göttel, A, Grassi, M, Gromov, M, Gromov, V, Gu, M, Gu, X, Gu, Y, Guan, M, Guan, Y, Guardone, N, Guo, C, Guo, W, Guo, X, Hagner, C, Han, R, Han, Y, He, M, He, W, Heinz, T, Hellmuth, P, Heng, Y, Herrera, R, Hor, Y, Hou, S, Hsiung, Y, Hu, B, Hu, H, Hu, J, Hu, S, Hu, T, Hu, Y, Hu, Z, Huang, G, Huang, H, Huang, J, Huang, K, Huang, W, Huang, X, Huang, Y, Hui, J, Huo, L, Huo, W, Huss, C, Hussain, S, Imbert, L, Ioannisian, A, Isocrate, R, Jafar, A, Jelmini, B, Jeria, I, Ji, X, Jia, H, Jia, J, Jian, S, Jiang, C, Jiang, D, Jiang, W, Jiang, X, Jing, X, Jollet, C, Kampmann, P, Kang, L, Karaparambil, R, Kazarian, N, Khan, A, Khatun, A, Khosonthongkee, K, Korablev, D, Kouzakov, K, Krasnoperov, A, Kuleshov, S, Kutovskiy, N, Labit, L, Lachenmaier, T, Landini, C, Leblanc, S, Lebrin, V, Lefevre, F, Lei, R, Leitner, R, Leung, J, Li, D, Li, F, Li, G, Li, H, Li, J, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liao, J, Limphirat, A, Lin, G, Lin, S, Lin, T, Ling, J, Ling, X, Lippi, I, Liu, C, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Liu, Z, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, P, Lu, S, Lu, X, Lubsandorzhiev, B, Lubsandorzhiev, S, 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Roskovec, B, Ruan, X, Rybnikov, A, Sadovsky, A, Saggese, P, Sandanayake, D, Sangka, A, Sava, G, Sawangwit, U, Schever, M, Schwab, C, Schweizer, K, Selyunin, A, Serafini, A, Settimo, M, Sharov, V, Shaydurova, A, Shi, J, Shi, Y, Shutov, V, Sidorenkov, A, Šimkovic, F, Singhal, A, Sirignano, C, Siripak, J, Sisti, M, Smirnov, M, Smirnov, O, Sogo-Bezerra, T, Sokolov, S, Songwadhana, J, Soonthornthum, B, Sotnikov, A, Šrámek, O, Sreethawong, W, Stahl, A, Stanco, L, Stankevich, K, Steiger, H, Steinmann, J, Sterr, T, Stock, M, Strati, V, Studenikin, A, Su, A, Su, J, Sun, S, Sun, X, Sun, Y, Sun, Z, Suwonjandee, N, Szelezniak, M, Takenaka, A, Tang, J, Tang, Q, Tang, X, Hariharan, V, Theisen, E, Tietzsch, A, Tkachev, I, Tmej, T, Torri, M, Tortorici, F, Treskov, K, Triossi, A, Triozzi, R, Trzaska, W, Tung, Y, Tuve, C, Ushakov, N, Vedin, V, Venettacci, C, Verde, G, Vialkov, M, Viaud, B, Vollbrecht, C, von Sturm, K, Vorobel, V, Voronin, D, Votano, L, Walker, P, Wang, C, Wang, E, Wang, G, Wang, J, 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Abusleme, Angel, Adam, Thomas, Ahmad, Shakeel, Ahmed, Rizwan, Aiello, Sebastiano, Akram, Muhammad, Aleem, Abid, An, Fengpeng, An, Qi, Andronico, Giuseppe, Anfimov, Nikolay, Antonelli, Vito, Antoshkina, Tatiana, Asavapibhop, Burin, de André, João Pedro Athayde Marcondes, Auguste, Didier, Bai, Weidong, Balashov, Nikita, Baldini, Wander, Barresi, Andrea, Basilico, Davide, Baussan, Eric, Bellato, Marco, Beretta, Marco, Bergnoli, Antonio, Bick, Daniel, Bieger, Lukas, Biktemerova, Svetlana, Birkenfeld, Thilo, Morton-Blake, Iwan, Blum, David, Blyth, Simon, Bolshakova, Anastasia, Bongrand, Mathieu, Bordereau, Clément, Breton, Dominique, Brigatti, Augusto, Brugnera, Riccardo, Bruno, Riccardo, Budano, Antonio, Busto, Jose, Cabrera, Anatael, Caccianiga, Barbara, Cai, Hao, Cai, Xiao, Cai, Yanke, Cai, Zhiyan, Callier, Stéphane, Cammi, Antonio, Campeny, Agustin, Cao, Chuanya, Cao, Guofu, Cao, Jun, Caruso, Rossella, Cerna, Cédric, Cerrone, Vanessa, Chan, Chi, Chang, Jinfan, Chang, Yun, Chatrabhuti, Auttakit, Chen, Chao, Chen, Guoming, Chen, Pingping, Chen, Shaomin, Chen, Yixue, Chen, Yu, Chen, Zhangming, Chen, Zhiyuan, Chen, Zikang, Cheng, Jie, Cheng, Yaping, Cheng, Yu Chin, Chepurnov, Alexander, Chetverikov, Alexey, Chiesa, Davide, Chimenti, Pietro, Chin, Yen-Ting, Chu, Ziliang, Chukanov, Artem, Claverie, Gérard, Clementi, Catia, Clerbaux, Barbara, Molla, Marta Colomer, Lorenzo, Selma Conforti Di, Coppi, Alberto, Corti, Daniele, Csakli, Simon, Corso, Flavio Dal, Dalager, Olivia, Datta, Jaydeep, Taille, Christophe De La, Deng, Zhi, Deng, Ziyan, Ding, Xiaoyu, Ding, Xuefeng, Ding, Yayun, Dirgantara, Bayu, Dittrich, Carsten, Dmitrievsky, Sergey, Dohnal, Tadeas, Dolzhikov, Dmitry, Donchenko, Georgy, Dong, Jianmeng, Doroshkevich, Evgeny, Dou, Wei, Dracos, Marcos, Druillole, Frédéric, Du, Ran, Du, Shuxian, Dugas, Katherine, Dusini, Stefano, Duyang, Hongyue, Eck, Jessica, Enqvist, Timo, Fabbri, Andrea, Fahrendholz, Ulrike, Fan, Lei, Fang, Jian, Fang, Wenxing, Fargetta, Marco, Fedoseev, Dmitry, Fei, Zhengyong, Feng, Li-Cheng, Feng, Qichun, Ferraro, Federico, Fournier, Amélie, Gan, Haonan, Gao, Feng, Garfagnini, Alberto, Gavrikov, Arsenii, Giammarchi, Marco, Giudice, Nunzio, Gonchar, Maxim, Gong, Guanghua, Gong, Hui, Gornushkin, Yuri, Göttel, Alexandre, Grassi, Marco, Gromov, Maxim, Gromov, Vasily, Gu, Minghao, Gu, Xiaofei, Gu, Yu, Guan, Mengyun, Guan, Yuduo, Guardone, Nunzio, Guo, Cong, Guo, Wanlei, Guo, Xinheng, Hagner, Caren, Han, Ran, Han, Yang, He, Miao, He, Wei, Heinz, Tobias, Hellmuth, Patrick, Heng, Yuekun, Herrera, Rafael, Hor, YuenKeung, Hou, Shaojing, Hsiung, Yee, Hu, Bei-Zhen, Hu, Hang, Hu, Jianrun, Hu, Jun, Hu, Shouyang, Hu, Tao, Hu, Yuxiang, Hu, Zhuojun, Huang, Guihong, Huang, Hanxiong, Huang, Jinhao, Huang, Junting, Huang, Kaixuan, Huang, Wenhao, Huang, Xin, Huang, Xingtao, Huang, Yongbo, Hui, Jiaqi, Huo, Lei, Huo, Wenju, Huss, Cédric, Hussain, Safeer, Imbert, Leonard, Ioannisian, Ara, Isocrate, Roberto, Jafar, Arshak, Jelmini, Beatrice, Jeria, Ignacio, Ji, Xiaolu, Jia, Huihui, Jia, Junji, Jian, Siyu, Jiang, Cailian, Jiang, Di, Jiang, Wei, Jiang, Xiaoshan, Jing, Xiaoping, Jollet, Cécile, Kampmann, Philipp, Kang, Li, Karaparambil, Rebin, Kazarian, Narine, Khan, Ali, Khatun, Amina, Khosonthongkee, Khanchai, Korablev, Denis, Kouzakov, Konstantin, Krasnoperov, Alexey, Kuleshov, Sergey, Kutovskiy, Nikolay, Labit, Loïc, Lachenmaier, Tobias, Landini, Cecilia, Leblanc, Sébastien, Lebrin, Victor, Lefevre, Frederic, Lei, Ruiting, Leitner, Rupert, Leung, Jason, Li, Demin, Li, Fei, Li, Fule, Li, Gaosong, Li, Huiling, Li, Jiajun, Li, Mengzhao, Li, Min, Li, Nan, Li, Qingjiang, Li, Ruhui, Li, Rui, Li, Shanfeng, Li, Tao, Li, Teng, Li, Weidong, Li, Weiguo, Li, Xiaomei, Li, Xiaonan, Li, Xinglong, Li, Yi, Li, Yichen, Li, Yufeng, Li, Zhaohan, Li, Zhibing, Li, Ziyuan, Li, Zonghai, Liang, Hao, Liao, Jiajun, Limphirat, Ayut, Lin, Guey-Lin, Lin, Shengxin, Lin, Tao, Ling, Jiajie, Ling, Xin, Lippi, Ivano, Liu, Caimei, Liu, Fang, Liu, Fengcheng, Liu, Haidong, Liu, Haotian, Liu, Hongbang, Liu, Hongjuan, Liu, Hongtao, Liu, Hui, Liu, Jianglai, Liu, Jiaxi, Liu, Jinchang, Liu, Min, Liu, Qian, Liu, Qin, Liu, Runxuan, Liu, Shenghui, Liu, Shubin, Liu, Shulin, Liu, Xiaowei, Liu, Xiwen, Liu, Xuewei, Liu, Yankai, Liu, Zhen, Lokhov, Alexey, Lombardi, Paolo, Lombardo, Claudio, Loo, Kai, Lu, Chuan, Lu, Haoqi, Lu, Jingbin, Lu, Junguang, Lu, Peizhi, Lu, Shuxiang, Lu, Xianguo, Lubsandorzhiev, Bayarto, Lubsandorzhiev, Sultim, Ludhova, Livia, Lukanov, Arslan, Luo, Daibin, Luo, Fengjiao, Luo, Guang, Luo, Jianyi, Luo, Shu, Luo, Wuming, Luo, Xiaojie, Lyashuk, Vladimir, Ma, Bangzheng, Ma, Bing, Ma, Qiumei, Ma, Si, Ma, Xiaoyan, Ma, Xubo, Maalmi, Jihane, Magoni, Marco, Mai, Jingyu, Malyshkin, Yury, Mandujano, Roberto Carlos, Mantovani, Fabio, Mao, Xin, Mao, Yajun, Mari, Stefano M., Marini, Filippo, Martini, Agnese, Mayer, Matthias, Mayilyan, Davit, Mednieks, Ints, Meng, Yue, Meraviglia, Anita, Meregaglia, Anselmo, Meroni, Emanuela, Meyhöfer, David, Miramonti, Lino, Mohan, Nikhil, Montuschi, Michele, Müller, Axel, Nastasi, Massimiliano, Naumov, Dmitry V., Naumova, Elena, Navas-Nicolas, Diana, Nemchenok, Igor, Thi, Minh Thuan Nguyen, Nikolaev, Alexey, Ning, Feipeng, Ning, Zhe, Nunokawa, Hiroshi, Oberauer, Lothar, Ochoa-Ricoux, Juan Pedro, Olshevskiy, Alexander, Orestano, Domizia, Ortica, Fausto, Othegraven, Rainer, Paoloni, Alessandro, Parmeggiano, Sergio, Pei, Yatian, Pelicci, Luca, Peng, Anguo, Peng, Haiping, Peng, Yu, Peng, Zhaoyuan, Perrot, Frédéric, Petitjean, Pierre-Alexandre, Petrucci, Fabrizio, Pilarczyk, Oliver, Rico, Luis Felipe Piñeres, Popov, Artyom, Poussot, Pascal, Previtali, Ezio, Qi, Fazhi, Qi, Ming, Qi, Xiaohui, Qian, Sen, Qian, Xiaohui, Qian, Zhen, Qiao, Hao, Qin, Zhonghua, Qiu, Shoukang, Qu, Manhao, Qu, Zhenning, Ranucci, Gioacchino, Rasheed, Reem, Re, Alessandra, Rebii, Abdel, Redchuk, Mariia, Ren, Bin, Ren, Jie, Ricci, Barbara, Rientong, Komkrit, Rifai, Mariam, Roche, Mathieu, Rodphai, Narongkiat, Romani, Aldo, Roskovec, Bedřich, Ruan, Xichao, Rybnikov, Arseniy, Sadovsky, Andrey, Saggese, Paolo, Sandanayake, Deshan, Sangka, Anut, Sava, Giuseppe, Sawangwit, Utane, Schever, Michaela, Schwab, Cédric, Schweizer, Konstantin, Selyunin, Alexandr, Serafini, Andrea, Settimo, Mariangela, Sharov, Vladislav, Shaydurova, Arina, Shi, Jingyan, Shi, Yanan, Shutov, Vitaly, Sidorenkov, Andrey, Šimkovic, Fedor, Singhal, Apeksha, Sirignano, Chiara, Siripak, Jaruchit, Sisti, Monica, Smirnov, Mikhail, Smirnov, Oleg, Sogo-Bezerra, Thiago, Sokolov, Sergey, Songwadhana, Julanan, Soonthornthum, Boonrucksar, Sotnikov, Albert, Šrámek, Ondřej, Sreethawong, Warintorn, Stahl, Achim, Stanco, Luca, Stankevich, Konstantin, Steiger, Hans, Steinmann, Jochen, Sterr, Tobias, Stock, Matthias Raphael, Strati, Virginia, Studenikin, Alexander, Su, Aoqi, Su, Jun, Sun, Shifeng, Sun, Xilei, Sun, Yongjie, Sun, Yongzhao, Sun, Zhengyang, Suwonjandee, Narumon, Szelezniak, Michal, Takenaka, Akira, Tang, Jian, Tang, Qiang, Tang, Quan, Tang, Xiao, Hariharan, Vidhya Thara, Theisen, Eric, Tietzsch, Alexander, Tkachev, Igor, Tmej, Tomas, Torri, Marco Danilo Claudio, Tortorici, Francesco, Treskov, Konstantin, Triossi, Andrea, Triozzi, Riccardo, Trzaska, Wladyslaw, Tung, Yu-Chen, Tuve, Cristina, Ushakov, Nikita, Vedin, Vadim, Venettacci, Carlo, Verde, Giuseppe, Vialkov, Maxim, Viaud, Benoit, Vollbrecht, Cornelius Moritz, von Sturm, Katharina, Vorobel, Vit, Voronin, Dmitriy, Votano, Lucia, Walker, Pablo, Wang, Caishen, Wang, Chung-Hsiang, Wang, En, Wang, Guoli, Wang, Jian, Wang, Jun, Wang, Li, Wang, Lu, Wang, Meng, Wang, Ruiguang, Wang, Siguang, Wang, Wei, Wang, Wenshuai, Wang, Xi, Wang, Xiangyue, Wang, Yangfu, Wang, Yaoguang, Wang, Yi, Wang, Yifang, Wang, Yuanqing, Wang, Yuyi, Wang, Zhe, Wang, Zheng, Wang, Zhimin, Watcharangkool, Apimook, Wei, Wei, Wei, Wenlu, Wei, Yadong, Wei, Yuehuan, Wen, Kaile, Wen, Liangjian, Weng, Jun, Wiebusch, Christopher, Wirth, Rosmarie, Wonsak, Bjoern, Wu, Diru, Wu, Qun, Wu, Yiyang, Wu, Zhi, Wurm, Michael, Wurtz, Jacques, Wysotzki, Christian, Xi, Yufei, Xia, Dongmei, Xiao, Fei, Xiao, Xiang, Xie, Xiaochuan, Xie, Yuguang, Xie, Zhangquan, Xin, Zhao, Xing, Zhizhong, Xu, Benda, Xu, Cheng, Xu, Donglian, Xu, Fanrong, Xu, Hangkun, Xu, Jilei, Xu, Jing, Xu, Meihang, Xu, Xunjie, Xu, Yin, Xu, Yu, Yan, Baojun, Yan, Qiyu, Yan, Taylor, Yan, Xiongbo, Yan, Yupeng, Yang, Changgen, Yang, Chengfeng, Yang, Jie, Yang, Lei, Yang, Xiaoyu, Yang, Yifan, Yao, Haifeng, Ye, Jiaxuan, Ye, Mei, Ye, Ziping, Yermia, Frédéric, You, Zhengyun, Yu, Boxiang, Yu, Chiye, Yu, Chunxu, Yu, Guojun, Yu, Hongzhao, Yu, Miao, Yu, Xianghui, Yu, Zeyuan, Yu, Zezhong, Yuan, Cenxi, Yuan, Chengzhuo, Yuan, Ying, Yuan, Zhenxiong, Yue, Baobiao, Zafar, Noman, Zavadskyi, Vitalii, Zeng, Fanrui, Zeng, Shan, Zeng, Tingxuan, Zeng, Yuda, Zhan, Liang, Zhang, Aiqiang, Zhang, Bin, Zhang, Binting, Zhang, Feiyang, Zhang, Haosen, Zhang, Honghao, Zhang, Jialiang, Zhang, Jiawen, Zhang, Jie, Zhang, Jingbo, Zhang, Jinnan, ZHANG, Lei, Zhang, Mohan, Zhang, Peng, Zhang, Ping, Zhang, Qingmin, Zhang, Shiqi, Zhang, Shu, Zhang, Shuihan, Zhang, Siyuan, Zhang, Tao, Zhang, Xiaomei, Zhang, Xin, Zhang, Xuantong, Zhang, Yinhong, Zhang, Yiyu, Zhang, Yongpeng, Zhang, Yu, Zhang, Yuanyuan, Zhang, Yumei, Zhang, Zhenyu, Zhang, Zhijian, Zhao, Jie, Zhao, Rong, Zhao, Runze, Zhao, Shujun, Zheng, Dongqin, Zheng, Hua, Zheng, Yangheng, Zhong, Weirong, Zhou, Jing, Zhou, Li, Zhou, Nan, Zhou, Shun, Zhou, Tong, Zhou, Xiang, Zhu, Jingsen, Zhu, Kangfu, Zhu, Kejun, Zhu, Zhihang, Zhuang, Bo, Zhuang, Honglin, Zong, Liang, Zou, Jiaheng, Züfle, Jan, and null, null
Abstract: The core-collapse supernova (CCSN) is considered one of the most energetic astrophysical events in the universe. The early and prompt detection of neutrinos before (pre-SN) and during the supernova (SN) burst presents a unique opportunity for multi-messenger observations of CCSN events. In this study, we describe the monitoring concept and present the sensitivity of the system to pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton liquid scintillator detector currently under construction in South China. The real-time monitoring system is designed to ensure both prompt alert speed and comprehensive coverage of progenitor stars. It incorporates prompt monitors on the electronic board as well as online monitors at the data acquisition stage. Assuming a false alert rate of 1 per year, this monitoring system exhibits sensitivity to pre-SN neutrinos up to a distance of approximately 1.6 (0.9) kiloparsecs and SN neutrinos up to about 370 (360) kiloparsecs for a progenitor mass of 30 solar masses, considering both normal and inverted mass ordering scenarios. The pointing ability of the CCSN is evaluated by analyzing the accumulated event anisotropy of inverse beta decay interactions from pre-SN or SN neutrinos. This, along with the early alert, can play a crucial role in facilitating follow-up multi-messenger observations of the next galactic or nearby extragalactic CCSN.
Published: 2024

41. Conditional Poisson process approximation

Author: Gan, H. L.
Subjects: Mathematics - Probability, 60F05, 60G55, 60E15
Abstract: Point processes are an essential tool when we are interested in where in time or space events occur. The basic starting point for point processes is usually the Poisson process. Over the years, Stein's method has been developed with a great deal of success for Poisson point process approximation. When studying rare events though, typically one only begins modelling after the occurrence of such an event. As a result, a point process that is conditional upon at least one atom, is arguably more appropriate in certain applications. In this paper, we develop Stein's method for conditional Poisson point process approximation, and closely examine what sort of difficulties that this conditioning entails. By utilising a characterising immigration-death process, we calculate bounds for the Stein factors., Comment: 22 pages
Published: 2015

42. JUNO Conceptual Design Report

Author: Adam, T., An, F., An, G., An, Q., Anfimov, N., Antonelli, V., Baccolo, G., Baldoncini, M., Baussan, E., Bellato, M., Bezrukov, L., Bick, D., Blyth, S., Boarin, S., Brigatti, A., Brugière, T., Brugnera, R., Avanzini, M. Buizza, Busto, J., Cabrera, A., Cai, H., Cai, X., Cammi, A., Cao, D., Cao, G., Cao, J., Chang, J., Chang, Y., Chen, M., Chen, P., Chen, Q., Chen, S., Chen, X., Chen, Y., Cheng, Y., Chiesa, D., Chukanov, A., Clemenza, M., Clerbaux, B., D'Angelo, D., de Kerret, H., Deng, Z., Ding, X., Ding, Y., Djurcic, Z., Dmitrievsky, S., Dolgareva, M., Dornic, D., Doroshkevich, E., Dracos, M., Drapier, O., Dusini, S., Díaz, M. A., Enqvist, T., Fan, D., Fang, C., Fang, J., Fang, X., Favart, L., Fedoseev, D., Fiorentini, G., Ford, R., Formozov, A., Gaigher, R., Gan, H., Garfagnini, A., Gaudiot, G., Genster, C., Giammarchi, M., Giuliani, F., Gonchar, M., Gong, G., Gong, H., Gonin, M., Gornushkin, Y., Grassi, M., Grewing, C., Gromov, V., Gu, M., Guan, M., Guarino, V., Guo, W., Guo, X., Guo, Y., Göger-Neff, M., Hackspacher, P., Hagner, C., Han, R., Han, Z., Hao, J., He, M., Hellgartner, D., Heng, Y., Hong, D., Hou, S., Hsiung, Y., Hu, B., Hu, J., Hu, S., Hu, T., Hu, W., Huang, H., Huang, X., Huo, L., Huo, W., Ioannisian, A., Ioannisyan, D., Jeitler, M., Jen, K., Jetter, S., Ji, X., Jian, S., Jiang, D., Jiang, X., Jollet, C., Kaiser, M., Kan, B., Kang, L., Karagounis, M., Kazarian, N., Kettell, S., Korablev, D., Krasnoperov, A., Krokhaleva, S., Krumshteyn, Z., Kruth, A., Kuusiniemi, P., Lachenmaier, T., Lei, L., Lei, R., Lei, X., Leitner, R., Lenz, F., Li, C., Li, F., Li, J., Li, N., Li, S., Li, T., Li, W., Li, X., Li, Y., Li, Z., Liang, H., Liang, J., Licciardi, M., Lin, G., Lin, S., Lin, T., Lin, Y., Lippi, I., Liu, G., Liu, H., Liu, J., Liu, Q., Liu, S., Liu, Y., Lombardi, P., Long, Y., Lorenz, S., Lu, C., Lu, F., Lu, H., Lu, J., Lubsandorzhiev, B., Lubsandorzhiev, S., Ludhova, L., Luo, F., Luo, S., Lv, Z., Lyashuk, V., Ma, Q., Ma, S., Ma, X., Malyshkin, Y., Mantovani, F., Mao, Y., Mari, S., Mayilyan, D., McDonough, W., Meng, G., Meregaglia, A., Meroni, E., Mezzetto, M., Min, J., Miramonti, L., Montuschi, M., Morozov, N., Mueller, T., Muralidharan, P., Nastasi, M., Naumov, D., Naumova, E., Nemchenok, I., Ning, Z., Nunokawa, H., Oberauer, L., Ochoa-Ricoux, J. P., Olshevskiy, A., Ortica, F., Pan, H., Paoloni, A., Parkalian, N., Parmeggiano, S., Pec, V., Pelliccia, N., Peng, H., Poussot, P., Pozzi, S., Previtali, E., Prummer, S., Qi, F., Qi, M., Qian, S., Qian, X., Qiao, H., Qin, Z., Ranucci, G., Re, A., Ren, B., Ren, J., Rezinko, T., Ricci, B., Robens, M., Romani, A., Roskovec, B., Ruan, X., Rybnikov, A., Sadovsky, A., Saggese, P., Salamanna, G., Sawatzki, J., Schuler, J., Selyunin, A., Shi, G., Shi, J., Shi, Y., Sinev, V., Sirignano, C., Sisti, M., Smirnov, O., Soiron, M., Stahl, A., Stanco, L., Steinmann, J., Strati, V., Sun, G., Sun, X., Sun, Y., Taichenachev, D., Tang, J., Tietzsch, A., Tkachev, I., Trzaska, W. H., Tung, Y., van Waasen, S., Volpe, C., Vorobel, V., Votano, L., Wang, C., Wang, G., Wang, H., Wang, M., Wang, R., Wang, S., Wang, W., Wang, Y., Wang, Z., Wei, W., Wei, Y., Weifels, M., Wen, L., Wen, Y., Wiebusch, C., Wipperfurth, S., Wong, S. C., Wonsak, B., Wu, C., Wu, Q., Wu, Z., Wurm, M., Wurtz, J., Xi, Y., Xia, D., Xia, J., Xiao, M., Xie, Y., Xu, J., Xu, L., Xu, Y., Yan, B., Yan, X., Yang, C., Yang, H., Yang, L., Yang, M., Yang, Y., Yanovich, E., Yao, Y., Ye, M., Ye, X., Yegin, U., Yermia, F., You, Z., Yu, B., Yu, C., Yu, G., Yu, Z., Yuan, Y., Yuan, Z., Zanetti, M., Zeng, P., Zeng, S., Zeng, T., Zhan, L., Zhang, C., Zhang, F., Zhang, G., Zhang, H., Zhang, J., Zhang, K., Zhang, P., Zhang, Q., Zhang, T., Zhang, X., Zhang, Y., Zhang, Z., Zhao, J., Zhao, M., Zhao, T., Zhao, Y., Zheng, H., Zheng, M., Zheng, X., Zheng, Y., Zhong, W., Zhou, G., Zhou, J., Zhou, L., Zhou, N., Zhou, R., Zhou, S., Zhou, W., Zhou, X., Zhou, Y., Zhu, H., Zhu, K., Zhuang, H., Zong, L., and Zou, J.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: The Jiangmen Underground Neutrino Observatory (JUNO) is proposed to determine the neutrino mass hierarchy using an underground liquid scintillator detector. It is located 53 km away from both Yangjiang and Taishan Nuclear Power Plants in Guangdong, China. The experimental hall, spanning more than 50 meters, is under a granite mountain of over 700 m overburden. Within six years of running, the detection of reactor antineutrinos can resolve the neutrino mass hierarchy at a confidence level of 3-4$\sigma$, and determine neutrino oscillation parameters $\sin^2\theta_{12}$, $\Delta m^2_{21}$, and $|\Delta m^2_{ee}|$ to an accuracy of better than 1%. The JUNO detector can be also used to study terrestrial and extra-terrestrial neutrinos and new physics beyond the Standard Model. The central detector contains 20,000 tons liquid scintillator with an acrylic sphere of 35 m in diameter. $\sim$17,000 508-mm diameter PMTs with high quantum efficiency provide $\sim$75% optical coverage. The current choice of the liquid scintillator is: linear alkyl benzene (LAB) as the solvent, plus PPO as the scintillation fluor and a wavelength-shifter (Bis-MSB). The number of detected photoelectrons per MeV is larger than 1,100 and the energy resolution is expected to be 3% at 1 MeV. The calibration system is designed to deploy multiple sources to cover the entire energy range of reactor antineutrinos, and to achieve a full-volume position coverage inside the detector. The veto system is used for muon detection, muon induced background study and reduction. It consists of a Water Cherenkov detector and a Top Tracker system. The readout system, the detector control system and the offline system insure efficient and stable data acquisition and processing., Comment: 328 pages, 211 figures
Published: 2015

43. Controllable synthesis of Gd-doped SmB6 nanobelt arrays for modulating their surface transport behaviors

Author: Gan, H., Ye, B., Zhou, L., Zhang, T., Tian, Y., Deng, S., He, H., and Liu, F.
Published: 2020
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44. Prevalence of hypoxia and correlation with glycolytic metabolism and angiogenic biomarkers in metastatic colorectal carcinoma

Author: Lee, ST., Muralidharan, V., Tebbutt, N., Wong, P., Fang, C., Liu, Z., Gan, H., Sachinidis, J., Pathmaraj, K., Christophi, C., and Scott, A. M.
Published: 2021
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45. The Clinical Value of the RA-Adjusted Fracture Risk Assessment Tool in the Fracture Risk Prediction of Patients with Type 2 Diabetes Mellitus in China

Author: Hu L, Li T, Zou Y, Yin XL, and Gan H
Subjects: type 2 diabetes mellitus, frax, fracture risk, bone mineral density, osteoporosis, Medicine (General), R5-920
Abstract: Ling Hu,* Ting Li,* Yi Zou, Xiao-Ling Yin, Hui Gan Department of Endocrinology, The Third Affiliated Hospital of Nanchang University, Nanchang 330000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Ling HuDepartment of Endocrinology, The Third Affiliated Hospital of Nanchang University, No. 128 of Xiangshan North Road, Donghu District, Nanchang 330000, People’s Republic of ChinaTel +86 13970075119Email drhu_hl1172@163.comObjective: This study aimed to explore the clinical value of the fracture risk assessment tool (FRAX) in the fracture risk prediction of Chinese patients after replacing rheumatoid arthritis (RA) with type 2 diabetes mellitus (T2DM) in the FRAX algorithm.Methods: A total of 1,047 patients with T2DM from the Endocrinology Department of the Third Affiliated Hospital of Nanchang University were enrolled in this study. Dual-energy X-ray absorptiometry (DXA) was then used to detect their bone density. RA in the FRAX algorithm was replaced with T2DM, and the new RA-adjusted FRAX was used to assess the fracture risk of the patients.Results: The sensitivity, specificity, and Youden’s index of the RA-adjusted FRAX to the treatment opinions on T2DM-associated hip fractures were 0.4761, 0.9642, and 0.4403, respectively, while the sensitivity, specificity, and Youden’s index of RA-adjusted FRAX to the treatment opinions on T2DM-associated major bone osteoporotic fractures were 0.0080, 1.0000, 0.0080, respectively. The DXA and RA-adjusted FRAX both showed acceptable consistency in the treatment recommendations for hip fractures in patients with T2DM (κ = 0.49) but had poor consistency in treatment recommendations for major bone osteoporotic fractures (κ = 0.010). The body mass index (BMI) scores, femoral neck-bone mineral densities, and number of males in the same treatment opinion group were significantly higher than in the different treatment opinions group (P < 0.001).Conclusion: RA-adjusted FRAX is a useful clinical tool for evaluation of hip fracture risk for Chinese patients with T2DM, and the accuracy of fracture risk prediction for male patients with T2DM and patients with T2DM with high BMI scores or high femoral neck-bone mineral density is higher.Keywords: type 2 diabetes mellitus, FRAX, fracture risk, bone mineral density, osteoporosis
Published: 2021

46. Mg-doping enhanced superconductivity and ferromagnetism in Ti1−xMgxO films

Author: Fan, Y.J., Gan, H., Wang, D., Sun, H.Y., Ma, C., Huang, F.Q., Zhou, J., Yin, Y.W., and Li, X.G.
Published: 2020
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47. Fragility Distributions and their approximations

Author: Gan, H. L. and Xia, A.
Subjects: Mathematics - Probability, 60F05
Abstract: Given a sequence of $n$ identically distributed random variables with common distribution $F$, the \emph{fragility distribution of order $m$}, represented by $\FD$, is the limit conditional distribution of the number of exceedances given there are at least $m$ exceedances, as the threshold tends to the right end point of $F$. In this paper we are concerned with the existence of $\FD$ and its asymptotic behaviour when $n$ becomes large. For a stationary sequence with its exceedance process converging to a compound Poisson process, we derive an explicit formula for calculating $\lim_{n \to \infty} \FD$. We also establish Stein's method for estimating the errors involved in fragility distribution approximations., Comment: 20 Pages
Published: 2014

48. Aroma-matrix interaction in food : an APCI approach

Author: Gan, H. H.
Subjects: 664, TX Home economics
Abstract: An overview is presented of the principle, scope and major applications to date of the use of atmospheric pressure chemical ionisation mass spectrometry (APCI-MS) for monitoring the kinetics of release of flavour volatiles in real time. There are four major areas in this thesis that extend from the measurement of flavour molecular mobility in sugar solutions, to the investigation of APCI-MS as a diagnostic tool for classifying apple cultivars and predicting age of cheese. Headspace techniques are the most extensively employed techniques in food analysis to measure volatile compounds, which play a central role in the perceived quality of food. The use of APCI-MS to measure aroma headspace availability with the addition of solutes was evaluated for two sugars of differing chain lengths (fructose and fructooligosaccharide (FOS)). In vitro aroma release was investigated at equilibrium using APCI-MS. An increase in the concentration of fructose above 25 % (w /w) was shown to significantly (p < 0.05) increase the release of ethyl butyrate, ethyl acetate and benzaldehyde into the gas phase above the aqueous solutions. Proton nuclear magnetic resonance (1 H NMR) was used to investigate the nature of solvent-sugar-aroma interactions with a view to explain the differential availability of aroma volatiles in sweetened and biopolymer rich solutions. The T1 relaxation times, and diffusion coefficients, provided preliminary clues as to the interactions between water, aroma and biopolymer. In the case of in vivo measurement, aroma perception was dependent on two key factors – firstly the equilibrium gas phase concentration of the aroma compounds within the oral/ nasal cavity and secondly the dynamic interaction of the compound with food and saliva (persistence). The overall process was influenced by the properties of the flavour compounds (i.e. its hydrophobicity) and the physiological conditions of the mouth, nose and throat during consumption of the food. A comparison was made between the intensities of anisaldehyde, furaneol and guaiacol in the headspace above simple solutions of water, to demonstrate the impact of matrix on flavour release in a frozen dairy dessert. The oral and nasal persistence of aromas following swallowing samples of a model frozen dairy dessert was investigated by collecting expired air from nose and mouth over 60-seconds. The decay curves (which illustrates persistence) of volatiles in breath showed that furaneol was the most persistent aroma, due to its hydrophilic nature and low volatility, that is expressed by the vapour pressure values of the pure compound. It is presumed to interact with the nasal mucosa, thereby prolonging persistence and potentially offering a significantly different perceptual profile to the less persistent compounds (Hodgson, Parker, Linforth, & Taylor, 2004). Thus, real time APCI-MS headspace data could be used to validate mathematical modelling of flavour release (Harvey & Barra, 2003). The feasibility of APCI-MS volatile compound fingerprinting in conjunction with chemometrics as a new strategy for rapid and non-destructive food classification was demonstrated when 202 clarified monovarietal juices extracted from apples differing in their botanical and geographical origins were characterised. Partial Least Square-Linear Discriminant Analysis (PLS-LDA) gave 100 % correct classification for the categorization by cultivar. Another PLS regression model was built to interpret and predict the age of Cheddar using headspace data from GC-MS and APCI-MS. The RMSEP and R2 values for the prediction model were 3.94 and 0.85 respectively. This further established the applicability of multivariate statistical technique as a tool to monitor the quality of foodstuff. Throughout the thesis, recommendations regarding practical implications for APCI-MS analysis and applications are demonstrated and discussed.
Published: 2015

49. Author Correction: A fast radio burst source at a complex magnetized site in a barred galaxy

Author: Xu, H., Niu, J. R., Chen, P., Lee, K. J., Zhu, W. W., Dong, S., Zhang, B., Jiang, J. C., Wang, B. J., Xu, J. W., Zhang, C. F., Fu, H., Filippenko, A. V., Peng, E. W., Zhou, D. J., Zhang, Y. K., Wang, P., Feng, Y., Li, Y., Brink, T. G., Li, D. Z., Lu, W., Yang, Y. P., Caballero, R. N., Cai, C., Chen, M. Z., Dai, Z. G., Djorgovski, S. G., Esamdin, A., Gan, H. Q., Guhathakurta, P., Han, J. L., Hao, L. F., Huang, Y. X., Jiang, P., Li, C. K., Li, D., Li, H., Li, X. Q., Li, Z. X., Liu, Z. Y., Luo, R., Men, Y. P., Niu, C. H., Peng, W. X., Qian, L., Song, L. M., Stern, D., Stockton, A., Sun, J. H., Wang, F. Y., Wang, M., Wang, N., Wang, W. Y., Wu, X. F., Xiao, S., Xiong, S. L., Xu, Y. H., Xu, R. X., Yang, J., Yang, X., Yao, R., Yi, Q. B., Yue, Y. L., Yu, D. J., Yu, W. F., Yuan, J. P., Zhang, B. B., Zhang, S. B., Zhang, S. N., Zhao, Y., Zheng, W. K., Zhu, Y., and Zou, J. H.
Published: 2022
Full Text: View/download PDF

50. JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo

Author: Abusleme, A, Adam, T, Ahmad, S, Ahmed, R, Aiello, S, Akram, M, Aleem, A, Alexandros, T, An, F, An, Q, Andronico, G, Anfimov, N, Antonelli, V, Antoshkina, T, Asavapibhop, B, de Andre, J, Auguste, D, Bai, W, Balashov, N, Baldini, W, Barresi, A, Basilico, D, Baussan, E, Bellato, M, Bergnoli, A, Birkenfeld, T, Blin, S, Blum, D, Blyth, S, Bolshakova, A, Bongrand, M, Bordereau, C, Breton, D, Brigatti, A, Brugnera, R, Bruno, R, Budano, A, Busto, J, Cabrera, A, Caccianiga, B, Cai, H, Cai, X, Cai, Y, Cai, Z, Callegari, R, Cammi, A, Campeny, A, Cao, C, Cao, G, Cao, J, Caruso, R, Cerna, C, Chan, C, Chang, J, Chang, Y, Chen, G, Chen, P, Chen, S, Chen, X, Chen, Y, Chen, Z, Cheng, J, Cheng, Y, Chetverikov, A, Chiesa, D, Chimenti, P, Chu, Z, Chukanov, A, Claverie, G, Clementi, C, Clerbaux, B, Di Lorenzo, S, Corti, D, Corso, F, Dalager, O, De La Taille, C, Deng, Z, Depnering, W, Diaz, M, Ding, X, Ding, Y, Dirgantara, B, Dmitrievsky, S, Dohnal, T, Dolzhikov, D, Donchenko, G, Dong, J, Doroshkevich, E, Dou, W, Dracos, M, Druillole, F, Du, R, Du, S, Dusini, S, Dvorak, M, Eck, J, Enqvist, T, Fabbri, A, Fahrendholz, U, Fan, D, Fan, L, Fang, J, Fang, W, Fargetta, M, Fedoseev, D, Fei, Z, Feng, L, Feng, Q, Ferraro, F, Ford, R, Fournier, A, Gan, H, Gao, F, Garfagnini, A, Gavrikov, A, Giammarchi, M, Giudice, N, Gonchar, M, Gong, G, Gong, H, Gornushkin, Y, Gottel, A, Grassi, M, Gromov, V, Gu, M, Gu, X, Gu, Y, Guan, M, Guan, Y, Guardone, N, Guo, C, Guo, J, Guo, W, Guo, X, Guo, Y, Hagner, C, Han, R, Han, Y, He, M, He, W, Heinz, T, Hellmuth, P, Heng, Y, Herrera, R, Hor, Y, Hou, S, Hsiung, Y, Hu, B, Hu, H, Hu, J, Hu, S, Hu, T, Hu, Y, Hu, Z, Huang, G, Huang, H, Huang, K, Huang, W, Huang, X, Huang, Y, Hui, J, Huo, L, Huo, W, Huss, C, Hussain, S, Ioannisian, A, Isocrate, R, Jelmini, B, Jeria, I, Ji, X, Jia, H, Jia, J, Jian, S, Jiang, D, Jiang, W, Jiang, X, Jing, X, Jollet, C, Joutsenvaara, J, Kalousis, L, Kampmann, P, Kang, L, Karaparambil, R, Kazarian, N, Khatun, A, Khosonthongkee, K, Korablev, D, Kouzakov, K, Krasnoperov, A, Kutovskiy, N, Kuusiniemi, P, Lachenmaier, T, Landini, C, Leblanc, S, Lebrin, V, Lefevre, F, Lei, R, Leitner, R, Leung, J, Li, D, Li, F, Li, G, Li, H, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liao, J, Limphirat, A, Lin, G, Lin, S, Lin, T, Ling, J, Lippi, I, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, P, Lu, S, Lubsandorzhiev, B, Lubsandorzhiev, S, Ludhova, L, Lukanov, A, Luo, D, Luo, F, Luo, G, Luo, S, Luo, W, Luo, X, Lyashuk, V, Ma, B, Ma, Q, Ma, S, Ma, X, Maalmi, J, Magoni, M, Mai, J, Malyshkin, Y, Mandujano, R, Mantovani, F, Mao, X, Mao, Y, Mari, S, Marini, F, Martellini, C, Martin-Chassard, G, Martini, A, Mayer, M, Mayilyan, D, Mednieks, I, Meinusch, A, Meng, Y, Meregaglia, A, Meroni, E, Meyhofer, D, Mezzetto, M, Miller, J, Miramonti, L, Molla, M, Montini, P, Montuschi, M, Muller, A, Nastasi, M, Naumov, D, Naumova, E, Navas-Nicolas, D, Nemchenok, I, Thi, M, Ning, F, Ning, Z, Nunokawa, H, Oberauer, L, Ochoa-Ricoux, J, Olshevskiy, A, Orestano, D, Ortica, F, Othegraven, R, Paoloni, A, Parmeggiano, S, Pei, Y, Pelicci, L, Pelliccia, N, Peng, A, Peng, H, Peng, Y, Peng, Z, Perrot, F, Petitjean, P, Petrucci, F, Pilarczyk, O, Rico, L, Popov, A, Poussot, P, Previtali, E, Qi, F, Qi, M, Qian, S, Qian, X, Qian, Z, Qiao, H, Qin, Z, Qiu, S, Ranucci, G, Raper, N, Rasheed, R, Re, A, Rebber, H, Rebii, A, Redchuk, M, Ren, B, Ren, J, Ricci, B, Rifai, M, Roche, M, Rodphai, N, Romani, A, Roskovec, B, Ruan, X, Rybnikov, A, Sadovsky, A, Saggese, P, Sanfilippo, S, Sangka, A, Sawangwit, U, Sawatzki, J, Schever, M, Schwab, C, Schweizer, K, Selyunin, A, Serafini, A, Settanta, G, Settimo, M, Shao, Z, Sharov, V, Shaydurova, A, Shi, J, Shi, Y, Shutov, V, Sidorenkov, A, Simkovic, F, Sirignano, C, Siripak, J, Sisti, M, Slupecki, M, Smirnov, M, Smirnov, O, Sogo-Bezerra, T, Sokolov, S, Songwadhana, J, Soonthornthum, B, Sotnikov, A, Sramek, O, Sreethawong, W, Stahl, A, Stanco, L, Stankevich, K, Stefanik, D, Steiger, H, Steinmann, J, Sterr, T, Stock, M, Strati, V, Studenikin, A, Su, J, Sun, S, Sun, X, Sun, Y, Sun, Z, Suwonjandee, N, Szelezniak, M, Tang, J, Tang, Q, Tang, X, Hariharan, V, Theisen, E, Tietzsch, A, Tkachev, I, Tmej, T, Torri, M, Treskov, K, Triossi, A, Troni, G, Trzaska, W, Tuve, C, Ushakov, N, Vedin, V, Verde, G, Vialkov, M, Viaud, B, Vollbrecht, C, Volpe, C, Sturm, K, Vorobel, V, Voronin, D, Votano, L, Walker, P, Wang, C, Wang, E, Wang, G, Wang, J, Wang, L, Wang, M, Wang, R, Wang, S, Wang, W, Wang, X, Wang, Y, Weng, Y, Wang, Z, Watcharangkool, A, Wei, W, Wei, Y, Wen, K, Wen, L, Weng, J, Wiebusch, C, Wong, S, Wonsak, B, Wu, D, Wu, Q, Wu, Z, Wurm, M, Wurtz, J, Wysotzki, C, Xi, Y, Xia, D, Xiao, X, Xie, X, Xie, Y, Xie, Z, Xin, Z, Xing, Z, Xu, B, Xu, C, Xu, D, Xu, F, Xu, H, Xu, J, Xu, M, Xu, Y, Yan, B, Yan, Q, Yan, T, Yan, W, Yan, X, Yan, Y, Yang, C, Yang, H, Yang, J, Yang, L, Yang, X, Yang, Y, Yeng, Y, Yao, H, Ye, J, Ye, M, Ye, Z, Yermia, F, You, Z, Yu, B, Yu, C, Yu, H, Yu, M, Yu, X, Yu, Z, Yuan, C, Yuan, Y, Yuan, Z, Yue, B, Zafar, N, Zavadskyi, V, Zeng, S, Zeng, T, Zeng, Y, Zhan, L, Zhang, A, Zhang, B, Zhang, F, Zhang, G, Zhang, H, Zhang, J, Zhang, M, Zhang, P, Zhang, Q, Zhang, S, Zhang, T, Zhang, X, Zhang, Y, Zhang, Z, Zhao, F, Zhao, J, Zhao, R, Zhao, S, Zheng, D, Zheng, H, Zheng, Y, Zhong, W, Zhou, J, Zhou, L, Zhou, N, Zhou, S, Zhou, T, Zhou, X, Zhu, J, Zhu, K, Zhu, Z, Zhuang, B, Zhuang, H, Zong, L, Zou, J, Zwickel, S, Abusleme A., Adam T., Ahmad S., Ahmed R., Aiello S., Akram M., Aleem A., Alexandros T., An F., An Q., Andronico G., Anfimov N., Antonelli V., Antoshkina T., Asavapibhop B., de Andre J. P. A. M., Auguste D., Bai W., Balashov N., Baldini W., Barresi A., Basilico D., Baussan E., Bellato M., Bergnoli A., Birkenfeld T., Blin S., Blum D., Blyth S., Bolshakova A., Bongrand M., Bordereau C., Breton D., Brigatti A., Brugnera R., Bruno R., Budano A., Busto J., Cabrera A., Caccianiga B., Cai H., Cai X., Cai Y., Cai Z., Callegari R., Cammi A., Campeny A., Cao C., Cao G., Cao J., Caruso R., Cerna C., Chan C., Chang J., Chang Y., Chen G., Chen P., Chen P. -A., Chen S., Chen X., Chen Y., Chen Z., Cheng J., Cheng Y., Cheng Y. C., Chetverikov A., Chiesa D., Chimenti P., Chu Z., Chukanov A., Claverie G., Clementi C., Clerbaux B., Di Lorenzo S. C., Corti D., Corso F. D., Dalager O., De La Taille C., Deng Z., Depnering W., Diaz M., Ding X., Ding Y., Dirgantara B., Dmitrievsky S., Dohnal T., Dolzhikov D., Donchenko G., Dong J., Doroshkevich E., Dou W., Dracos M., Druillole F., Du R., Du S., Dusini S., Dvorak M., Eck J., Enqvist T., Fabbri A., Fahrendholz U., Fan D., Fan L., Fang J., Fang W., Fargetta M., Fedoseev D., Fei Z., Feng L. -C., Feng Q., Ferraro F., Ford R., Fournier A., Gan H., Gao F., Garfagnini A., Gavrikov A., Giammarchi M., Giudice N., Gonchar M., Gong G., Gong H., Gornushkin Y., Gottel A., Grassi M., Gromov V., Gu M., Gu X., Gu Y., Guan M., Guan Y., Guardone N., Guo C., Guo J., Guo W., Guo X., Guo Y., Hagner C., Han R., Han Y., He M., He W., Heinz T., Hellmuth P., Heng Y., Herrera R., Hor Y., Hou S., Hsiung Y., Hu B. -Z., Hu H., Hu J., Hu S., Hu T., Hu Y., Hu Z., Huang G., Huang H., Huang K., Huang W., Huang X., Huang Y., Hui J., Huo L., Huo W., Huss C., Hussain S., Ioannisian A., Isocrate R., Jelmini B., Jeria I., Ji X., Jia H., Jia J., Jian S., Jiang D., Jiang W., Jiang X., Jing X., Jollet C., Joutsenvaara J., Kalousis L., Kampmann P., Kang L., Karaparambil R., Kazarian N., Khatun A., Khosonthongkee K., Korablev D., Kouzakov K., Krasnoperov A., Kutovskiy N., Kuusiniemi P., Lachenmaier T., Landini C., Leblanc S., Lebrin V., Lefevre F., Lei R., Leitner R., Leung J., Li D., Li F., Li G., Li H., Li M., Li N., Li Q., Li R., Li S., Li T., Li W., Li X., Li Y., Li Z., Liang H., Liao J., Limphirat A., Lin G. -L., Lin S., Lin T., Ling J., Lippi I., Liu F., Liu H., Liu J., Liu M., Liu Q., Liu R., Liu S., Liu X., Liu Y., Lokhov A., Lombardi P., Lombardo C., Loo K., Lu C., Lu H., Lu J., Lu P., Lu S., Lubsandorzhiev B., Lubsandorzhiev S., Ludhova L., Lukanov A., Luo D., Luo F., Luo G., Luo S., Luo W., Luo X., Lyashuk V., Ma B., Ma Q., Ma S., Ma X., Maalmi J., Magoni M., Mai J., Malyshkin Y., Mandujano R. C., Mantovani F., Mao X., Mao Y., Mari S. M., Marini F., Martellini C., Martin-Chassard G., Martini A., Mayer M., Mayilyan D., Mednieks I., Meinusch A., Meng Y., Meregaglia A., Meroni E., Meyhofer D., Mezzetto M., Miller J., Miramonti L., Molla M. C., Montini P., Montuschi M., Muller A., Nastasi M., Naumov D. V., Naumova E., Navas-Nicolas D., Nemchenok I., Thi M. T. N., Ning F., Ning Z., Nunokawa H., Oberauer L., Ochoa-Ricoux J. P., Olshevskiy A., Orestano D., Ortica F., Othegraven R., Paoloni A., Parmeggiano S., Pei Y., Pelicci L., Pelliccia N., Peng A., Peng H., Peng Y., Peng Z., Perrot F., Petitjean P. -A., Petrucci F., Pilarczyk O., Rico L. F. P., Popov A., Poussot P., Previtali E., Qi F., Qi M., Qian S., Qian X., Qian Z., Qiao H., Qin Z., Qiu S., Ranucci G., Raper N., Rasheed R., Re A., Rebber H., Rebii A., Redchuk M., Ren B., Ren J., Ricci B., Rifai M., Roche M., Rodphai N., Romani A., Roskovec B., Ruan X., Rybnikov A., Sadovsky A., Saggese P., Sanfilippo S., Sangka A., Sawangwit U., Sawatzki J., Schever M., Schwab C., Schweizer K., Selyunin A., Serafini A., Settanta G., Settimo M., Shao Z., Sharov V., Shaydurova A., Shi J., Shi Y., Shutov V., Sidorenkov A., Simkovic F., Sirignano C., Siripak J., Sisti M., Slupecki M., Smirnov M., Smirnov O., Sogo-Bezerra T., Sokolov S., Songwadhana J., Soonthornthum B., Sotnikov A., Sramek O., Sreethawong W., Stahl A., Stanco L., Stankevich K., Stefanik D., Steiger H., Steinmann J., Sterr T., Stock M. R., Strati V., Studenikin A., Su J., Sun S., Sun X., Sun Y., Sun Z., Suwonjandee N., Szelezniak M., Tang J., Tang Q., Tang X., Hariharan V. T., Theisen E., Tietzsch A., Tkachev I., Tmej T., Torri M. D. C., Treskov K., Triossi A., Troni G., Trzaska W., Tuve C., Ushakov N., Vedin V., Verde G., Vialkov M., Viaud B., Vollbrecht C. M., Volpe C., Sturm K. V., Vorobel V., Voronin D., Votano L., Walker P., Wang C., Wang C. -H., Wang E., Wang G., Wang J., Wang L., Wang M., Wang R., Wang S., Wang W., Wang X., Wang Y., Weng Y., Wang Z., Watcharangkool A., Wei W., Wei Y., Wen K., Wen L., Weng J., Wiebusch C., Wong S. C. -F., Wonsak B., Wu D., Wu Q., Wu Z., Wurm M., Wurtz J., Wysotzki C., Xi Y., Xia D., Xiao X., Xie X., Xie Y., Xie Z., Xin Z., Xing Z., Xu B., Xu C., Xu D., Xu F., Xu H., Xu J., Xu M., Xu Y., Yan B., Yan Q., Yan T., Yan W., Yan X., Yan Y., Yang C., Yang H., Yang J., Yang L., Yang X., Yang Y., Yeng Y., Yao H., Ye J., Ye M., Ye Z., Yermia F., You Z., Yu B., Yu C., Yu H., Yu M., Yu X., Yu Z., Yuan C., Yuan Y., Yuan Z., Yue B., Zafar N., Zavadskyi V., Zeng S., Zeng T., Zeng Y., Zhan L., Zhang A., Zhang B., Zhang F., Zhang G., Zhang H., Zhang J., Zhang M., Zhang P., Zhang Q., Zhang S., Zhang T., Zhang X., Zhang Y., Zhang Z., Zhao F., Zhao J., Zhao R., Zhao S., Zheng D., Zheng H., Zheng Y., Zhong W., Zhou J., Zhou L., Zhou N., Zhou S., Zhou T., Zhou X., Zhu J., Zhu K., Zhu Z., Zhuang B., Zhuang H., Zong L., Zou J., Zwickel S., Abusleme, A, Adam, T, Ahmad, S, Ahmed, R, Aiello, S, Akram, M, Aleem, A, Alexandros, T, An, F, An, Q, Andronico, G, Anfimov, N, Antonelli, V, Antoshkina, T, Asavapibhop, B, de Andre, J, Auguste, D, Bai, W, Balashov, N, Baldini, W, Barresi, A, Basilico, D, Baussan, E, Bellato, M, Bergnoli, A, Birkenfeld, T, Blin, S, Blum, D, Blyth, S, Bolshakova, A, Bongrand, M, Bordereau, C, Breton, D, Brigatti, A, Brugnera, R, Bruno, R, Budano, A, Busto, J, Cabrera, A, Caccianiga, B, Cai, H, Cai, X, Cai, Y, Cai, Z, Callegari, R, Cammi, A, Campeny, A, Cao, C, Cao, G, Cao, J, Caruso, R, Cerna, C, Chan, C, Chang, J, Chang, Y, Chen, G, Chen, P, Chen, S, Chen, X, Chen, Y, Chen, Z, Cheng, J, Cheng, Y, Chetverikov, A, Chiesa, D, Chimenti, P, Chu, Z, Chukanov, A, Claverie, G, Clementi, C, Clerbaux, B, Di Lorenzo, S, Corti, D, Corso, F, Dalager, O, De La Taille, C, Deng, Z, Depnering, W, Diaz, M, Ding, X, Ding, Y, Dirgantara, B, Dmitrievsky, S, Dohnal, T, Dolzhikov, D, Donchenko, G, Dong, J, Doroshkevich, E, Dou, W, Dracos, M, Druillole, F, Du, R, Du, S, Dusini, S, Dvorak, M, Eck, J, Enqvist, T, Fabbri, A, Fahrendholz, U, Fan, D, Fan, L, Fang, J, Fang, W, Fargetta, M, Fedoseev, D, Fei, Z, Feng, L, Feng, Q, Ferraro, F, Ford, R, Fournier, A, Gan, H, Gao, F, Garfagnini, A, Gavrikov, A, Giammarchi, M, Giudice, N, Gonchar, M, Gong, G, Gong, H, Gornushkin, Y, Gottel, A, Grassi, M, Gromov, V, Gu, M, Gu, X, Gu, Y, Guan, M, Guan, Y, Guardone, N, Guo, C, Guo, J, Guo, W, Guo, X, Guo, Y, Hagner, C, Han, R, Han, Y, He, M, He, W, Heinz, T, Hellmuth, P, Heng, Y, Herrera, R, Hor, Y, Hou, S, Hsiung, Y, Hu, B, Hu, H, Hu, J, Hu, S, Hu, T, Hu, Y, Hu, Z, Huang, G, Huang, H, Huang, K, Huang, W, Huang, X, Huang, Y, Hui, J, Huo, L, Huo, W, Huss, C, Hussain, S, Ioannisian, A, Isocrate, R, Jelmini, B, Jeria, I, Ji, X, Jia, H, Jia, J, Jian, S, Jiang, D, Jiang, W, Jiang, X, Jing, X, Jollet, C, Joutsenvaara, J, Kalousis, L, Kampmann, P, Kang, L, Karaparambil, R, Kazarian, N, Khatun, A, Khosonthongkee, K, Korablev, D, Kouzakov, K, Krasnoperov, A, Kutovskiy, N, Kuusiniemi, P, Lachenmaier, T, Landini, C, Leblanc, S, Lebrin, V, Lefevre, F, Lei, R, Leitner, R, Leung, J, Li, D, Li, F, Li, G, Li, H, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liao, J, Limphirat, A, Lin, G, Lin, S, Lin, T, Ling, J, Lippi, I, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, P, Lu, S, Lubsandorzhiev, B, Lubsandorzhiev, S, Ludhova, L, Lukanov, A, Luo, D, Luo, F, Luo, G, Luo, S, Luo, W, Luo, X, Lyashuk, V, Ma, B, Ma, Q, Ma, S, Ma, X, Maalmi, J, Magoni, M, Mai, J, Malyshkin, Y, Mandujano, R, Mantovani, F, Mao, X, Mao, Y, Mari, S, Marini, F, Martellini, C, Martin-Chassard, G, Martini, A, Mayer, M, Mayilyan, D, Mednieks, I, Meinusch, A, Meng, Y, Meregaglia, A, Meroni, E, Meyhofer, D, Mezzetto, M, Miller, J, Miramonti, L, Molla, M, Montini, P, Montuschi, M, Muller, A, Nastasi, M, Naumov, D, Naumova, E, Navas-Nicolas, D, Nemchenok, I, Thi, M, Ning, F, Ning, Z, Nunokawa, H, Oberauer, L, Ochoa-Ricoux, J, Olshevskiy, A, Orestano, D, Ortica, F, Othegraven, 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C. -F., Wonsak B., Wu D., Wu Q., Wu Z., Wurm M., Wurtz J., Wysotzki C., Xi Y., Xia D., Xiao X., Xie X., Xie Y., Xie Z., Xin Z., Xing Z., Xu B., Xu C., Xu D., Xu F., Xu H., Xu J., Xu M., Xu Y., Yan B., Yan Q., Yan T., Yan W., Yan X., Yan Y., Yang C., Yang H., Yang J., Yang L., Yang X., Yang Y., Yeng Y., Yao H., Ye J., Ye M., Ye Z., Yermia F., You Z., Yu B., Yu C., Yu H., Yu M., Yu X., Yu Z., Yuan C., Yuan Y., Yuan Z., Yue B., Zafar N., Zavadskyi V., Zeng S., Zeng T., Zeng Y., Zhan L., Zhang A., Zhang B., Zhang F., Zhang G., Zhang H., Zhang J., Zhang M., Zhang P., Zhang Q., Zhang S., Zhang T., Zhang X., Zhang Y., Zhang Z., Zhao F., Zhao J., Zhao R., Zhao S., Zheng D., Zheng H., Zheng Y., Zhong W., Zhou J., Zhou L., Zhou N., Zhou S., Zhou T., Zhou X., Zhu J., Zhu K., Zhu Z., Zhuang B., Zhuang H., Zong L., Zou J., and Zwickel S.
Abstract: We discuss JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo via detecting inverse beta decay reactions of electron anti-neutrinos resulting from the annihilation. We study possible backgrounds to the signature, including the reactor neutrinos, diffuse supernova neutrino background, charged- and neutral-current interactions of atmospheric neutrinos, backgrounds from muon-induced fast neutrons and cosmogenic isotopes. A fiducial volume cut, as well as the pulse shape discrimination and the muon veto are applied to suppress the above backgrounds. It is shown that JUNO sensitivity to the thermally averaged dark matter annihilation rate in 10 years of exposure would be significantly better than the present-day best limit set by Super-Kamiokande and would be comparable to that expected by Hyper-Kamiokande.
Published: 2023

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