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482 results on '"Huang, J.‐H."'

1. Charged-current non-standard neutrino interactions at Daya Bay

Author

An, F. P., Bai, W. D., Balantekin, A. B., Bishai, M., Blyth, S., Cao, G. F., Cao, J., Chang, J. F., Chang, Y., Chen, H. S., Chen, H. Y., Chen, S. M., Chen, Y., Chen, Y. X., Chen, Z. Y., Cheng, J., Cheng, Y.-C., Cheng, Z. K., Cherwinka, J. J., Chu, M. C., Cummings, J. P., Dalager, O., Deng, F. S., Ding, X. Y., Ding, Y. Y., Diwan, M. V., Dohnal, T., Dolzhikov, D., Dove, J., Dugas, K. V., Duyang, H. Y., Dwyer, D. A., Gallo, J. P., Gonchar, M., Gong, G. H., Gong, H., Gu, W. Q., Guo, J. Y., Guo, L., Guo, X. H., Guo, Y. H., Guo, Z., Hackenburg, R. W., Han, Y., Hans, S., He, M., Heeger, K. M., Heng, Y. K., Hor, Y. K., Hsiung, Y. B., Hu, B. Z., Hu, J. R., Hu, T., Hu, Z. J., Huang, H. X., Huang, J. H., Huang, X. T., Huang, Y. B., Huber, P., Jaffe, D. E., Jen, K. L., Ji, X. L., Ji, X. P., Johnson, R. A., Jones, D., Kang, L., Kettell, S. H., Kohn, S., Kramer, M., Langford, T. J., Lee, J., Lee, J. H. C., Lei, R. T., Leitner, R., Leung, J. K. C., Li, F., Li, H. L., Li, J. J., Li, Q. J., Li, R. H., Li, S., Li, S., Li, S. C., Li, W. D., Li, X. N., Li, X. Q., Li, Y. F., Li, Z. B., Liang, H., Lin, C. J., Lin, G. L., Lin, S., Ling, J. J., Link, J. M., Littenberg, L., Littlejohn, B. R., Liu, J. C., Liu, J. L., Liu, J. X., Lu, C., Lu, H. Q., Luk, K. B., Ma, B. Z., Ma, X. B., Ma, X. Y., Ma, Y. Q., Mandujano, R. C., Marshall, C., McDonald, K. T., McKeown, R. D., Meng, Y., Napolitano, J., Naumov, D., Naumova, E., Nguyen, T. M. T., Ochoa-Ricoux, J. P., Olshevskiy, A., Park, J., Patton, S., Peng, J. C., Pun, C. S. J., Qi, F. Z., Qi, M., Qian, X., Raper, N., Ren, J., Morales Reveco, C., Rosero, R., Roskovec, B., Ruan, X. C., Russell, B., Steiner, H., Sun, J. L., Tmej, T., Tse, W.-H., Tull, C. E., Tung, Y. C., Viren, B., Vorobel, V., Wang, C. H., Wang, J., Wang, M., Wang, N. Y., Wang, R. G., Wang, W., Wang, X., Wang, Y. F., Wang, Z., Wang, Z., Wang, Z. M., Wei, H. Y., Wei, L. H., Wei, W., Wen, L. J., Whisnant, K., White, C. G., Wong, H. L. H., Worcester, E., Wu, D. R., Wu, Q., Wu, W. J., Xia, D. M., Xie, Z. Q., Xing, Z. Z., Xu, H. K., Xu, J. L., Xu, T., Xue, T., Yang, C. G., Yang, L., Yang, Y. Z., Yao, H. F., Ye, M., Yeh, M., Young, B. L., Yu, H. Z., Yu, Z. Y., Yue, B. B., Zavadskyi, V., Zeng, S., Zeng, Y., Zhan, L., Zhang, C., Zhang, F. Y., Zhang, H. H., Zhang, J. L., Zhang, J. W., Zhang, Q. M., Zhang, S. Q., Zhang, X. T., Zhang, Y. M., Zhang, Y. X., Zhang, Y. Y., Zhang, Z. J., Zhang, Z. P., Zhang, Z. Y., Zhao, J., Zhao, R. Z., Zhou, L., Zhuang, H. L., and Zou, J. H.

Published
2024
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7. The value of magnetic resonance diffusion weighted imaging sequence and T2 mapping imaging technology in evaluating knee joint defects.

Author

Huang, C. Z., Lin, C. K., Fu, Q. M., Huang, J. H., Jia, N. L., and Chen, Y.

Subjects
DIFFUSION magnetic resonance imaging, MAGNETIC resonance imaging, KNEE joint, KNEE osteoarthritis
Abstract

Background: Diagnosing knee osteoarthritis (KOA) often relies on limited routine methods. This study investigates the efficacy of T2 mapping and Apparent Diffusion Coefficient (ADC) values in MRI for enhanced assessment of cartilage damage in KOA, focusing on their correlation with pain severity. Materials and Methods: A total of 52 KOA patients (74 knee joints) and 50 healthy individuals (100 knee joints) were assessed from May 2022 to June 2023. Both groups underwent MRI with Diffusion Weighted Imaging (DWI) sequence and T2 mapping to analyze ADC and T2 mapping values across femoral condyle, tibial plateau, and patellar joint surfaces, and their correlation with pain levels. Results: The KOA group showed significantly higher ADC and T2 mapping values in all examined areas compared to the control group (P<0.05). These values were also higher in advanced stages of cartilage degeneration and correlated positively with increased pain scores (P<0.05). Conclusion: MRI utilizing DWI and T2 mapping provides a quantitative reflection of knee joint cartilage degeneration in KOA. These methods show a positive correlation with pain severity, suggesting their potential for more accurate KOA diagnostics and assessment. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Precision Measurement of Reactor Antineutrino Oscillation at Kilometer-Scale Baselines by Daya Bay

Author

Daya Bay Collaboration, An, F. P., Bai, W. D., Balantekin, A. B., Bishai, M., Blyth, S., Cao, G. F., Cao, J., Chang, J. F., Chang, Y., Chen, H. S., Chen, H. Y., Chen, S. M., Chen, Y., Chen, Y. X., Chen, Z. Y., Cheng, J., Cheng, Z. K., Cherwinka, J. J., Chu, M. C., Cummings, J. P., Dalager, O., Deng, F. S., Ding, Y. Y., Ding, X. Y., Diwan, M. V., Dohnal, T., Dolzhikov, D., Dove, J., Duyang, H. Y., Dwyer, D. A., Gallo, J. P., Gonchar, M., Gong, G. H., Gong, H., Gu, W. Q., Guo, J. Y., Guo, L., Guo, X. H., Guo, Y. H., Guo, Z., Hackenburg, R. W., Han, Y., Hans, S., He, M., Heeger, K. M., Heng, Y. K., Hor, Y. K., Hsiung, Y. B., Hu, B. Z., Hu, J. R., Hu, T., Hu, Z. J., Huang, H. X., Huang, J. H., Huang, X. T., Huang, Y. B., Huber, P., Jaffe, D. E., Jen, K. L., Ji, X. L., Ji, X. P., Johnson, R. A., Jones, D., Kang, L., Kettell, S. H., Kohn, S., Kramer, M., Langford, T. J., Lee, J., Lee, J. H. C., Lei, R. T., Leitner, R., Leung, J. K. C., Li, F., Li, H. L., Li, J. J., Li, Q. J., Li, R. H., Li, S., Li, S. C., Li, W. D., Li, X. N., Li, X. Q., Li, Y. F., Li, Z. B., Liang, H., Lin, C. J., Lin, G. L., Lin, S., Ling, J. J., Link, J. M., Littenberg, L., Littlejohn, B. R., Liu, J. C., Liu, J. L., Liu, J. X., Lu, C., Lu, H. Q., Luk, K. B., Ma, B. Z., Ma, X. B., Ma, X. Y., Ma, Y. Q., Mandujano, R. C., Marshall, C., McDonald, K. T., McKeown, R. D., Meng, Y., Napolitano, J., Naumov, D., Naumova, E., Nguyen, T. M. T., Ochoa-Ricoux, J. P., Olshevskiy, A., Pan, H. -R., Park, J., Patton, S., Peng, J. C., Pun, C. S. J., Qi, F. Z., Qi, M., Qian, X., Raper, N., Ren, J., Reveco, C. Morales, Rosero, R., Roskovec, B., Ruan, X. C., Russell, B., Steiner, H., Sun, J. L., Tmej, T., Treskov, K., Tse, W. -H., Tull, C. E., Viren, B., Vorobel, V., Wang, C. H., Wang, J., Wang, M., Wang, N. Y., Wang, R. G., Wang, W., Wang, X., Wang, Y., Wang, Y. F., Wang, Z., Wang, Z. M., Wei, H. Y., Wei, L. H., Wei, W., Wen, L. J., Whisnant, K., White, C. G., Wong, H. L. H., Worcester, E., Wu, D. R., Wu, Q., Wu, W. J., Xia, D. M., Xie, Z. Q., Xing, Z. Z., Xu, H. K., Xu, J. L., Xu, T., Xue, T., Yang, C. G., Yang, L., Yang, Y. Z., Yao, H. F., Ye, M., Yeh, M., Young, B. L., Yu, H. Z., Yu, Z. Y., Yue, B. B., Zavadskyi, V., Zeng, S., Zeng, Y., Zhan, L., Zhang, C., Zhang, F. Y., Zhang, H. H., Zhang, J. L., Zhang, J. W., Zhang, Q. M., Zhang, S. Q., Zhang, X. T., Zhang, Y. M., Zhang, Y. X., Zhang, Y. Y., Zhang, Z. J., Zhang, Z. P., Zhang, Z. Y., Zhao, J., Zhao, R. Z., Zhou, L., Zhuang, H. L., and Zou, J. H.

Subjects
High Energy Physics - Experiment (hep-ex), hep-ex, FOS: Physical sciences, Particle Physics - Experiment, High Energy Physics - Experiment
Abstract

We present a new determination of the smallest neutrino mixing angle ${\theta}_{13}$ and the mass-squared difference ${\Delta}{\rm m}^{2}_{32}$ using a final sample of $5.55 \times 10^{6}$ inverse beta-decay (IBD) candidates with the final-state neutron captured on gadolinium. This sample was selected from the complete data set obtained by the Daya Bay reactor neutrino experiment in 3158 days of operation. Compared to the previous Daya Bay results, selection of IBD candidates has been optimized, energy calibration refined, and treatment of backgrounds further improved. The resulting oscillation parameters are ${\rm sin}^{2}2{\theta}_{13} = 0.0851 \pm 0.0024$, ${\Delta}{\rm m}^{2}_{32} = (2.466 \pm 0.060) \times 10^{-3}{\rm eV}^{2}$ for the normal mass ordering or ${\Delta}{\rm m}^{2}_{32} = -(2.571 \pm 0.060) \times 10^{-3} {\rm eV}^{2}$ for the inverted mass ordering., Comment: 7 pages, 3 figures, 1 table, 10 supplementary files

Published
2022

15. Joint Determination of Reactor Antineutrino Spectra from ²³⁵U and ²³⁹Pu Fission by Daya Bay and PROSPECT

Author

An, F. P., Andriamirado, M., Balantekin, A. B., Band, H. R., Bass, C. D., Bergeron, D. E., Berish, D., Bishai, M., Blyth, S., Bowden, N. S., Bryan, C. D., Cao, G. F., Cao, J., Chang, J. F., Chang, Y., Chen, H. S., Chen, S. M., Chen, Y., Chen, Y. X., Cheng, J., Cheng, Z. K., Cherwinka, J. J., Chu, M. C., Classen, T., Conant, A. J., Cummings, J. P., Dalager, O., Deichert, G., Delgado, A., Deng, F. S., Ding, Y. Y., Diwan, M. V., Dohnal, T., Dolinski, M. J., Dolzhikov, D., Dove, J., Dvořák, M., Dwyer, D. A., Erickson, A., Foust, B. T., Gaison, J. K., Galindo-Uribarri, A., Gallo, J. P., Gilbert, C. E., Gonchar, M., Gong, G. H., Gong, H., Grassi, M., Gu, W. Q., Guo, J. Y., Guo, L., Guo, X. H., Guo, Y. H., Guo, Z., Hackenburg, R. W., Hans, S., Hansell, A. B., He, M., Heeger, K. M., Heffron, B., Heng, Y. K., Hor, Y. K., Hsiung, Y. B., Hu, B. Z., Hu, J. R., Hu, T., Hu, Z. J., Huang, H. X., Huang, J. H., Huang, X. T., Huang, Y. B., Huber, P., Koblanski, J., Jaffe, D. E., Jayakumar, S., Jen, K. L., Ji, X. L., Ji, X. P., Johnson, R. A., Jones, D. C., Kang, L., Kettell, S. H., Kohn, S., Kramer, M., Kyzylova, O., Lane, C. E., Langford, T. J., LaRosa, J., Lee, J., Lee, J. H. C., Lei, R. T., Leitner, R., Leung, J. K. C., Li, F., Li, H. L., Li, J. J., Li, Q. J., Li, R. H., Li, S., Li, S. C., Li, W. D., Li, X. N., Li, X. Q., Li, Y. F., Li, Z. B., Liang, H., Lin, C. J., Lin, G. L., Lin, S., Ling, J. J., Link, J. M., Littenberg, L., Littlejohn, B. R., Liu, J. C., Liu, J. L., Liu, J. X., Lu, C., Lu, H. Q., Lu, X., Luk, K. B., Ma, B. Z., Ma, X. B., Ma, X. Y., Ma, Y. Q., Mandujano, R. C., Maricic, J., Marshall, C., McDonald, K. T., McKeown, R. D., Mendenhall, M. P., Meng, Y., Meyer, A. M., Milincic, R., Mueller, P. E., Mumm, H. P., Napolitano, J., Naumov, D., Naumova, E., Neilson, R., Nguyen, T. M. T., Nikkel, J. A., Nour, S., Ochoa-Ricoux, J. P., Olshevskiy, A., Palomino, J. L., Pan, H.-R., Park, J., Patton, S., Peng, J. C., Pun, C. S. J., Pushin, D. A., Qi, F. Z., Qi, M., Qian, X., Raper, N., Ren, J., Morales Reveco, C., Rosero, R., Roskovec, B., Ruan, X. C., Searles, M., Steiner, H., Sun, J. L., Surukuchi, P. T., Tmej, T., Treskov, K., Tse, W.-H., Tull, C. E., Tyra, M. A., Varner, R. L., Venegas-Vargas, D., Viren, B., Vorobel, V., Wang, C. H., Wang, J., Wang, M., Wang, N. Y., Wang, R. G., Wang, W., Wang, X., Wang, Y., Wang, Y. F., Wang, Z., Wang, Z. M., Weatherly, P. B., Wei, H. Y., Wei, L. H., Wen, L. J., Whisnant, K., White, C., Wilhelmi, J., Wong, H. L. H., Woolverton, A., Worcester, E., Wu, D. R., Wu, F. L., Wu, Q., Wu, W. J., Xia, D. M., Xie, Z. Q., Xing, Z. Z., Xu, H. K., Xu, J. L., Xu, T., Xue, T., Yang, C. G., Yang, L., Yang, Y. Z., Yao, H. F., Ye, M., Yeh, M., Young, B. L., Yu, H. Z., Yu, Z. Y., Yue, B. B., Zavadskyi, V., Zeng, S., Zeng, Y., Zhan, L., Zhang, C., Zhang, F. Y., Zhang, H. H., Zhang, J. W., Zhang, Q. M., Zhang, S. Q., Zhang, X., Zhang, X. T., Zhang, Y. M., Zhang, Y. X., Zhang, Y. Y., Zhang, Z. J., Zhang, Z. P., Zhang, Z. Y., Zhao, J., Zhao, R. Z., Zhou, L., Zhuang, H. L., and Zou, J. H.

Abstract

A joint determination of the reactor antineutrino spectra resulting from the fission of ²³⁵U and ²³⁹Pu has been carried out by the Daya Bay and PROSPECT Collaborations. This Letter reports the level of consistency of ²³⁵U spectrum measurements from the two experiments and presents new results from a joint analysis of both data sets. The measurements are found to be consistent. The combined analysis reduces the degeneracy between the dominant ²³⁵U and ²³⁹Pu isotopes and improves the uncertainty of the ²³⁵U spectral shape to about 3%. The ²³⁵U and ²³⁹Pu antineutrino energy spectra are unfolded from the jointly deconvolved reactor spectra using the Wiener-SVD unfolding method, providing a data-based reference for other reactor antineutrino experiments and other applications. This is the first measurement of the ²³⁵U and ²³⁹Pu spectra based on the combination of experiments at low- and highly enriched uranium reactors.

Published
2022

28. Mobility of trimethyllead and total lead in the forest floor

Author

Huang, J.-H., Kalbitz, K., and Matzner, E.

Subjects
Forest litter -- Research, Forest soils -- Research, Heavy metals -- Research, Soil chemistry -- Research, Earth sciences
Abstract

The forest floor represents an important compartment for the accumulation of heavy metals in forest soils. To study the mobility of Pb species and their linkage to C cycling in the forest floor, we investigated concentrations of trimethyllead ([C.sub.3][H.sub.9][Pb.sup.+]) and total Pb ([Pb.sub.total]) in throughfall and forest floor percolates during 14 snow-free wk. For our study; we used a long-term field experiment with increased input of throughfall and litterfall at a Norway spruce [Picea abies (L.) H. Karst.] site. The concentrations of trimethyllead were highest in throughfall (106 pg Pb [L.sup.-1]) and decreased with depth of the forest floor. Strong correlations between trimethyllead concentrations in throughfall and forest floor percolates suggested that trimethyllead in forest floor percolates originates largely from throughfall. The partition coefficients of trimethyllead and [Pb.sub.total], estimated as ratios of concentrations in percolates to those in forest floors, ranged from 54 to 560 and 870 to 26,400 L [kg.sup.-1], respectively, indicating that the mobility of trimethyllead was greater than [Pb.sub.total]. The [Pb.sub.total] concentrations were low in throughfall and often the highest in Oa horizon percolates (15.2-57.5 [micro]g [L.sup.-1]). They decreased in Oi horizon percolates after increased throughfall addition. Increased litterfall resulted in increased concentrations of [Pb.sub.total] in forest floor percolates. Concurrently, dissolved organic C increased. The tight coupling of [Pb.sub.total] to dissolved organic C was also indicated by correlations (r [greater than or equal to] 0.48) that were stronger than those between [Pb.sub.total] and pH (r [less than or equal to] -0.22). We concluded that the mobilization of [Pb.sub.total] from the large pool in forest floor horizons is strongly linked to the release of dissolved organic matter. Conversely, the mobility of trimethyllead is regulated by throughfall input and not by dissolved organic C.

Published
2008

42. CONGESTION RISK PROPAGATION MODEL BASED ON MULTI-LAYER TIME-VARYING NETWORK.

Author

Huang, J. H., Sun, M. G., and Cheng, Q.

Subjects
*TIME-varying networks, *REINFORCEMENT (Psychology), *TRAFFIC congestion, *MARKOV processes, *MARKET penetration, *INTELLIGENT transportation systems, *4G networks
Abstract

To quantify the responses of drivers to traffic information and the congestion evacuation effect on the basis of traffic guidance information, a multilayer network congestion risk propagation model of urban roads was built to analyse the influence of the advanced traveller information system (ATIS) penetration rate, group behaviours of drivers, and traveller flow distribution features on the traffic congestion risk propagation of urban roads. Meanwhile, the dynamic evolutionary characteristics of group behaviours of drivers in a road network under the guidance of traffic information were analysed with the microscopic Markov chain approach (MMCA). A simulation analysis of the artery network in the fourth ring of Beijing was also carried out. Results demonstrated that the influence of traffic information and drivers' information reinforcement psychology on congestion risk propagation depend on the aggregation effect caused by traffic information. Increasing the ATIS market penetration rate and drivers' acceptance of information is beneficial to relieve traffic congestion as long as the drivers' aggregation effect is within a critical range. [ABSTRACT FROM AUTHOR]

Published
2021
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