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331 results on '"Yang, J.W."'

6. Insight-HXMT insight into switch of the accretion mode: The case of the X-ray pulsar 4U 1901+03

Author

Tuo, Y.L., Ji, L., Tsygankov, S.S., Mihara, T., Song, L.M., Ge, M.Y., Nabizadeh, A., Tao, L., Qu, J.L., Zhang, Y., Zhang, S., Zhang, S.N., Bu, Q.C., Chen, L., Xu, Y.P., Cao, X.L., Chen, Y., Liu, C.Z., Cai, C., Chang, Z., Chen, G., Chen, T.X., Chen, Y.B., Chen, Y.P., Cui, W., Cui, W.W., Deng, J.K., Dong, Y.W., Du, Y.Y., Fu, M.X., Gao, G.H., Gao, H., Gao, M., Gu, Y.D., Guan, J., Guo, C.C., Han, D.W., Huang, Y., Huo, J., Jia, S.M., Jiang, L.H., Jiang, W.C., Jin, J., Jin, Y.J., Kong, L.D., Li, B., Li, C.K., Li, G., Li, M.S., Li, T.P., Li, W., Li, X., Li, X.B., Li, X.F., Li, Y.G., Li, Z.W., Liang, X.H., Liao, J.Y., Liu, B.S., Liu, G.Q., Liu, H.W., Liu, X.J., Liu, Y.N., Lu, B., Lu, F.J., Lu, X.F., Luo, Q., Luo, T., Ma, X., Meng, B., Nang, Y., Nie, J.Y., Ou, G., Sai, N., Shang, R.C., Song, X.Y., Sun, L., Tan, Y., Wang, C., Wang, G.F., Wang, J., Wang, W.S., Wang, Y.S., Wen, X.Y., Wu, B.Y., Wu, B.B., Wu, M., Xiao, G.C., Xiao, S., Xiong, S.L., Yang, J.W., Yang, S., Yang, Y.J., Yi, Q.B., Yin, Q.Q., You, Y., Zhang, A.M., Zhang, C.M., Zhang, F., Zhang, H.M., Zhang, J., Zhang, T., Zhang, W., Zhang, W.C., Zhang, W.Z., Zhang, Y.F., Zhang, Y.J., Zhang, Y.H., Zhang, Z., Zhang, Z.L., Zhao, H.S., Zhao, X.F., Zheng, S.J., Zheng, Y.G., Zhou, D.K., Zhou, J.F., Zhu, Y.X., Zhu, Y., and Zhuang, R.L.

Published
2020
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7. Joint analysis of energy and RMS spectra from MAXI J1535-571 with Insight-HXMT

Author

Kong, L.D., Zhang, S., Chen, Y.P., Ji, L., Zhang, S.N., Yang, Y.R., Tao, L., Ma, X., Qu, J.L., Lu, F.J., Bu, Q.C., Chen, L., Song, L.M., Li, T.P., Xu, Y.P., Cao, X.L., Chen, Y., Liu, C.Z., Cai, C., Chang, Z., Chen, G., Chen, T.X., Chen, Y.B., Cui, W., Cui, W.W., Deng, J.K., Dong, Y.W., Du, Y.Y., Fu, M.X., Gao, G.H., Gao, H., Gao, M., Ge, M.Y., Gu, Y.D., Guan, J., Guo, C.C., Han, D.W., Huang, Y., Huo, J., Jia, S.M., Jiang, L.H., Jiang, W.C., Jin, J., Li, B., Li, C.K., Li, G., Li, M.S., Li, W., Li, X., Li, X.B., Li, X.F., Li, Y.G., Li, Z.W., Liang, X.H., Liao, J.Y., Liu, G.Q., Liu, H.X., Liu, H.W., Liu, S.Z., Liu, X.J., Liu, Y.N., Lu, B., Lu, X.F., Luo, Q., Luo, T., Meng, B., Nang, Y., Nie, J.Y., Ou, G., Ren, X.Q., Sai, N., Song, X.Y., Sun, L., Tan, Y., Tuo, Y.L., Wang, C., Wang, G.F., Wang, J., Wang, P.J., Wang, W.S., Wang, Y.S., Wen, X.Y., Wu, B.Y., Wu, B.B., Wu, M., Xiao, G.C., Xiao, S., Xiong, S.L., Xu, H., Yang, J.W., Yang, S., Yang, Y.J., Yi, Q.B., You, Y., Zhang, A.M., Zhang, C.M., Zhang, F., Zhang, H.M., Zhang, J., Zhang, P., Zhang, T., Zhang, W., Zhang, W.C., Zhang, W.Z., Zhang, Y., Zhang, Y.F., Zhang, Y.J., Zhang, Y.H., Zhang, Z., Zhang, Z.L., Zhao, H.S., Zhao, X.F., Zheng, S.J., Zheng, Y.G., Zhou, D.K., Zhou, J.F., Zhu, Y.X., and Zhu, Y.

Published
2020
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8. Diagnostic of the spectral properties of Aquila X-1 by Insight-HXMT snapshots during the early propeller phase

Author

Güngör, C., Ge, M.Y., Zhang, S., Santangelo, A., Zhang, S.N., Lu, F.J., Zhang, Y., Chen, Y.P., Tao, L., Yang, Y.J., Bu, Q.C., Cai, C., Cao, X.L., Chang, Z., Chen, G., Chen, L., Chen, T.X., Chen, Y., Chen, Y.B., Cui, W., Cui, W.W., Deng, J.K., Dong, Y.W., Du, Y.Y., Fu, M.X., Gao, G.H., Gao, H., Gao, M., Gu, Y.D., Guan, J., Guo, C.C., Han, D.W., Huang, Y., Huo, J., Ji, L., Jia, S.M., Jiang, L.H., Jiang, W.C., Jin, J., Kong, L.D., Li, B., Li, C.K., Li, G., Li, M.S., Li, T.P., Li, W., Li, X., Li, X.B., Li, X.F., Li, Y.G., Li, Z.W., Liang, X.H., Liao, J.Y., Liu, C.Z., Liu, G.Q., Liu, H.W., Liu, X.J., Liu, Y.N., Lu, B., Lu, X.F., Luo, T., Luo, Q., Ma, X., Meng, B., Nang, Y., Nie, J.Y., Ou, G., Sai, N., Song, L.M., Song, X.Y., Sun, L., Tan, Y., Tuo, Y.L., Wang, C., Wang, G.F., Wang, J., Wang, W.S., Wang, Y.S., Wen, X.Y., Wu, B.B., Wu, B.Y., Wu, M., Xiao, G.C., Xiao, S., Xiong, S.L., Xu, Y.P., Yang, J.W., Yang, S., Yi, Q.B., Yin, Q.Q., You, Y., Zhang, A.M., Zhang, C.M., Zhang, F., Zhang, H.M., Zhang, J., Zhang, T., Zhang, W., Zhang, W.C., Zhang, W.Z., Zhang, Y.F., Zhang, Y.J., Zhang, Z., Zhang, Z.L., Zhao, H.S., Zhao, X.F., Zheng, S.J., Zhou, D.K., Zhou, J.F., Zhu, Y., and Zhu, Y.X.

Published
2020
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9. Insight-HXMT study of the timing properties of Sco X-1

Author

Jia, S.M., Bu, Q.C., Qu, J.L., Lu, F.J., Zhang, S.N., Huang, Y., Ma, X., Tao, L., Xiao, G.C., Zhang, W., Chen, L., Song, L.M., Zhang, S., Li, T.P., Xu, Y.P., Cao, X.L., Chen, Y., Liu, C.Z., Cai, C., Chang, Z., Chen, G., Chen, T.X., Chen, Y.B., Chen, Y.P., Cui, W., Cui, W.W., Deng, J.K., Dong, Y.W., Du, Y.Y., Fu, M.X., Gao, G.H., Gao, H., Gao, M., Ge, M.Y., Gu, Y.D., Guan, J., Guo, C.C., Han, D.W., Huo, J., Jiang, L.H., Jiang, W.C., Jin, J., Jin, Y.J., Kong, L.D., Li, B., Li, C.K., Li, G., Li, M.S., Li, W., Li, X., Li, X.B., Li, X.F., Li, Y.G., Li, Z.W., Liang, X.H., Liao, J.Y., Liu, G.Q., Liu, H.W., Liu, X.J., Liu, Y.N., Lu, B., Lu, X.F., Luo, Q., Luo, T., Meng, B., Nang, Y., Nie, J.Y., Ou, G., Sai, N., Shang, R.C., Song, X.Y., Sun, L., Tan, Y., Tuo, Y.L., Wang, C., Wang, G.F., Wang, J., Wang, W.S., Wang, Y.S., Wen, X.Y., Wu, B.Y., Wu, B.B., Wu, M., Xiao, S., Xiong, S.L., Yang, J.W., Yang, S., Yang, Y.J., Yin, Q.Q., Yi, Q.B., You, Y., Zhang, A.M., Zhang, C.M., Zhang, F., Zhang, H.M., Zhang, J., Zhang, T., Zhang, W.C., Zhang, W.Z., Zhang, Y., Zhang, Y.F., Zhang, Y.J., Zhang, Z., Zhang, Z.L., Zhao, H.S., Zhao, X.F., Zheng, S.J., Zhou, D.K., Zhou, J.F., Zhu, Y.X., Zhu, Y., and Zhuang, R.L.

Published
2020
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10. Insight-HXMT observation on 4U 1608–52: Evolving spectral properties of a bright type-I X-ray burst

Author

Chen, Y.P., Zhang, S., Zhang, S.N., Ji, L., Kong, L.D., Santangelo, A., Qu, J.L., Lu, F.J., Li, T.P., Song, L.M., Xu, Y.P., Cao, X.L., Chen, Y., Liu, C.Z., Bu, Q.C., Cai, C., Chang, Z., Chen, G., Chen, L., Chen, T.X., Chen, Y.B., Cui, W., Cui, W.W., Deng, J.K., Dong, Y.W., Du, Y.Y., Fu, M.X., Gao, G.H., Gao, H., Gao, M., Ge, M.Y., Gu, Y.D., Guan, J., Guo, C.C., Han, D.W., Huang, Y., Huo, J., Jia, S.M., Jiang, L.H., Jiang, W.C., Jin, J., Li, B., Li, C.K., Li, G., Li, M.S., Li, W., Li, X., Li, X.B., Li, X.F., Li, Y.G., Li, Z.W., Liang, X.H., Liao, J.Y., Liu, G.Q., Liu, H.W., Liu, X.J., Liu, Y.N., Lu, B., Lu, X.F., Luo, Q., Luo, T., Ma, X., Meng, B., Nang, Y., Nie, J.Y., Ou, G., Ren, X.Q., Sai, N., Sun, L., Tan, Y., Tao, L., Tuo, Y.L., Wang, C., Wang, G.F., Wang, J., Wang, W.S., Wang, Y.S., Wen, X.Y., Wu, B.Y., Wu, B.B., Wu, M., Xiao, G.C., Xiao, S., Xiong, S.L., Yang, J.W., Yang, S., Yang, Y.J., Yi, Q.B., Yin, Q.Q., You, Y., Zhang, A.M., Zhang, C.L., Zhang, C.M., Zhang, F., Zhang, H.M., Zhang, J., Zhang, T., Zhang, W.C., Zhang, W., Zhang, W.Z., Zhang, Yi., Zhang, Y.F., Zhang, Y.J., Zhang, Y., Zhang, Z., Zhang, Z.L., Zhao, H.S., Zhao, X.F., Zheng, S.J., Zhou, D.K., Zhou, J.F., Zhu, Y., and Zhu, Y.X.

Published
2019
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11. Constant cyclotron line energy in Hercules X–1 - Joint Insight-HXMT and NuSTAR observations

Author

Xiao, G.C., Ji, L., Staubert, R., Ge, M.Y., Zhang, S., Zhang, S.N., Santangelo, A., Ducci, L., Liao, J.Y., Guo, C.C., Li, X.B., Zhang, W., Qu, J.L., Lu, F.J., Li, T.P., Song, L.M., Xu, Y.P., Bu, Q.C., Cai, C., Cao, X.L., Chang, Z., Chen, G., Chen, L., Chen, T.X., Chen, Y.B., Chen, Y., Chen, Y.P., Cui, W., Cui, W.W., Deng, J.K., Dong, Y.W., Du, Y.Y., Fu, M.X., Gao, G.H., Gao, H., Gao, M., Gu, Y.D., Guan, J., Gungor, C., Han, D.W., Huang, Y., Huo, J., Jia, S.M., Jiang, L.H., Jiang, W.C., Jin, J., Kong, L.D., Li, B., Li, C.K., Li, G., Li, M.S., Li, W., Li, X., Li, X.F., Li, Y.G., Li, Z.W., Liang, X.H., Liu, C.Z., Liu, G.Q., Liu, H.W., Liu, X.J., Liu, Y.N., Lu, B., Lu, X.F., Luo, Q., Luo, T., Ma, X., Meng, B., Nang, Y., Nie, J.Y., Ou, G., Sai, N., Song, S.X., Sun, L., Tan, Y., Tao, L., Tuo, Y.L., Wang, C., Wang, G.F., Wang, J., Wang, W.S., Wang, Y.S., Wen, X.Y., Wu, B.B., Wu, B.Y., Wu, M., Xiong, S.L., Yang, J.W., Yang, S., Yang, Y.J., Yin, Q.B., Yin, Q.Q., Zhang, A.M., Zhang, C.M., Zhang, F., Zhang, H.M., Zhang, J., Zhang, T., Zhang, W.C., Zhang, W.Z., Zhang, Y., Zhang, Y.F., Zhang, Y.J., Zhang, Z., Zhang, Z.L., Zhao, H.S., Zhao, X.F., Zheng, S.J., Zhou, J.F., Zhu, Y., and Zhu, Y.X.

Published
2019
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20. The Kidney Failure Risk Equation: Evaluation of Novel Input Variables including eGFR Estimated Using the CKD-EPI 2021 Equation in 59 Cohorts

Author

Grams, M.E., Brunskill, N.J., Ballew, Shoshana H., Sang, Y., Coresh, J., Matsushita, K., Surapaneni, A., Bell, S., Carrero, J.J., Chodick, G., Evans, M., Heerspink, H.J., Inker, L.A., Iseki, K., Kalra, P.A., Kirchner, H.L., Lee, B.J., Levin, A., Major, R.W., Medcalf, J., Nadkarni, G.N., Naimark, D.M.J., Ricardo, A.C., Sawhney, S., Sood, M.M., Staplin, N., Stempniewicz, N., Stengel, B., Sumida, K., Traynor, J.P., Brand, J. van den, Wen, C.P., Woodward, M., Yang, J.W., Wang, A.Y., Tangri, N., Grams, M.E., Brunskill, N.J., Ballew, Shoshana H., Sang, Y., Coresh, J., Matsushita, K., Surapaneni, A., Bell, S., Carrero, J.J., Chodick, G., Evans, M., Heerspink, H.J., Inker, L.A., Iseki, K., Kalra, P.A., Kirchner, H.L., Lee, B.J., Levin, A., Major, R.W., Medcalf, J., Nadkarni, G.N., Naimark, D.M.J., Ricardo, A.C., Sawhney, S., Sood, M.M., Staplin, N., Stempniewicz, N., Stengel, B., Sumida, K., Traynor, J.P., Brand, J. van den, Wen, C.P., Woodward, M., Yang, J.W., Wang, A.Y., and Tangri, N.

Abstract

Item does not contain fulltext, SIGNIFICANCE STATEMENT: The kidney failure risk equation (KFRE) uses age, sex, GFR, and urine albumin-to-creatinine ratio (ACR) to predict 2- and 5-year risk of kidney failure in populations with eGFR <60 ml/min per 1.73 m 2 . However, the CKD-EPI 2021 creatinine equation for eGFR is now recommended for use but has not been fully tested in the context of KFRE. In 59 cohorts comprising 312,424 patients with CKD, the authors assessed the predictive performance and calibration associated with the use of the CKD-EPI 2021 equation and whether additional variables and accounting for the competing risk of death improves the KFRE's performance. The KFRE generally performed well using the CKD-EPI 2021 eGFR in populations with eGFR <45 ml/min per 1.73 m 2 and was not improved by adding the 2-year prior eGFR slope and cardiovascular comorbidities. BACKGROUND: The kidney failure risk equation (KFRE) uses age, sex, GFR, and urine albumin-to-creatinine ratio (ACR) to predict kidney failure risk in people with GFR <60 ml/min per 1.73 m 2 . METHODS: Using 59 cohorts with 312,424 patients with CKD, we tested several modifications to the KFRE for their potential to improve the KFRE: using the CKD-EPI 2021 creatinine equation for eGFR, substituting 1-year average ACR for single-measure ACR and 1-year average eGFR in participants with high eGFR variability, and adding 2-year prior eGFR slope and cardiovascular comorbidities. We also assessed calibration of the KFRE in subgroups of eGFR and age before and after accounting for the competing risk of death. RESULTS: The KFRE remained accurate and well calibrated overall using the CKD-EPI 2021 eGFR equation. The other modifications did not improve KFRE performance. In subgroups of eGFR 45-59 ml/min per 1.73 m 2 and in older adults using the 5-year time horizon, the KFRE demonstrated systematic underprediction and overprediction, respectively. We developed and tested a new model with a spline term in eGFR and incorporating the competing risk

Published
2023

21. Estimated Glomerular Filtration Rate, Albuminuria, and Adverse Outcomes: An Individual-Participant Data Meta-Analysis

Author

Grams, M.E., Coresh, J., Matsushita, K., Ballew, S.H., Sang, Y., Surapaneni, A., Pinho, N. Alencar de, Anderson, A., Appel, L.J., Ärnlöv, J., Azizi, F., Bansal, N., Bell, S., Bilo, H.J.G., Brunskill, N.J., Carrero, J.J., Chadban, S., Chalmers, J., Chen, J., Ciemins, E., Cirillo, M., Ebert, N., Evans, M., Ferreiro, Alejandro, Fu, E.L., Fukagawa, M., Green, J.A., Gutierrez, O.M., Herrington, W.G., Hwang, S.J., Inker, L.A., Iseki, K., Jafar, T., Jassal, S.K., Jha, V., Kadota, A., Katz, R., Köttgen, A., Konta, T., Kronenberg, F., Lee, B.J., Lees, J., Levin, A., Looker, H.C., Major, R., Cohen, C. Melzer, Mieno, M., Miyazaki, M., Moranne, O., Muraki, I., Naimark, D., Nitsch, D., Oh, W., Pena, M., Purnell, T.S., Sabanayagam, C., Satoh, M., Sawhney, S., Schaeffner, E., Schöttker, B., Shen, J.I., Shlipak, M.G., Sinha, S., Stengel, B., Sumida, K., Tonelli, M., Valdivielso, J.M., Zuilen, A.D. van, Visseren, F.L.J., Wang, A.Y., Wen, C.P., Wheeler, D.C., Yatsuya, H., Yamagata, K., Yang, J.W., Young, A., Zhang, Haitao, Zhang, L., Wetzels, J.F.M., Levey, A.S., Gansevoort, R.T., Grams, M.E., Coresh, J., Matsushita, K., Ballew, S.H., Sang, Y., Surapaneni, A., Pinho, N. Alencar de, Anderson, A., Appel, L.J., Ärnlöv, J., Azizi, F., Bansal, N., Bell, S., Bilo, H.J.G., Brunskill, N.J., Carrero, J.J., Chadban, S., Chalmers, J., Chen, J., Ciemins, E., Cirillo, M., Ebert, N., Evans, M., Ferreiro, Alejandro, Fu, E.L., Fukagawa, M., Green, J.A., Gutierrez, O.M., Herrington, W.G., Hwang, S.J., Inker, L.A., Iseki, K., Jafar, T., Jassal, S.K., Jha, V., Kadota, A., Katz, R., Köttgen, A., Konta, T., Kronenberg, F., Lee, B.J., Lees, J., Levin, A., Looker, H.C., Major, R., Cohen, C. Melzer, Mieno, M., Miyazaki, M., Moranne, O., Muraki, I., Naimark, D., Nitsch, D., Oh, W., Pena, M., Purnell, T.S., Sabanayagam, C., Satoh, M., Sawhney, S., Schaeffner, E., Schöttker, B., Shen, J.I., Shlipak, M.G., Sinha, S., Stengel, B., Sumida, K., Tonelli, M., Valdivielso, J.M., Zuilen, A.D. van, Visseren, F.L.J., Wang, A.Y., Wen, C.P., Wheeler, D.C., Yatsuya, H., Yamagata, K., Yang, J.W., Young, A., Zhang, Haitao, Zhang, L., Wetzels, J.F.M., Levey, A.S., and Gansevoort, R.T.

Abstract

Item does not contain fulltext, IMPORTANCE: Chronic kidney disease (low estimated glomerular filtration rate [eGFR] or albuminuria) affects approximately 14% of adults in the US. OBJECTIVE: To evaluate associations of lower eGFR based on creatinine alone, lower eGFR based on creatinine combined with cystatin C, and more severe albuminuria with adverse kidney outcomes, cardiovascular outcomes, and other health outcomes. DESIGN, SETTING, AND PARTICIPANTS: Individual-participant data meta-analysis of 27 503 140 individuals from 114 global cohorts (eGFR based on creatinine alone) and 720 736 individuals from 20 cohorts (eGFR based on creatinine and cystatin C) and 9 067 753 individuals from 114 cohorts (albuminuria) from 1980 to 2021. EXPOSURES: The Chronic Kidney Disease Epidemiology Collaboration 2021 equations for eGFR based on creatinine alone and eGFR based on creatinine and cystatin C; and albuminuria estimated as urine albumin to creatinine ratio (UACR). MAIN OUTCOMES AND MEASURES: The risk of kidney failure requiring replacement therapy, all-cause mortality, cardiovascular mortality, acute kidney injury, any hospitalization, coronary heart disease, stroke, heart failure, atrial fibrillation, and peripheral artery disease. The analyses were performed within each cohort and summarized with random-effects meta-analyses. RESULTS: Within the population using eGFR based on creatinine alone (mean age, 54 years [SD, 17 years]; 51% were women; mean follow-up time, 4.8 years [SD, 3.3 years]), the mean eGFR was 90 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 11 mg/g (IQR, 8-16 mg/g). Within the population using eGFR based on creatinine and cystatin C (mean age, 59 years [SD, 12 years]; 53% were women; mean follow-up time, 10.8 years [SD, 4.1 years]), the mean eGFR was 88 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 9 mg/g (IQR, 6-18 mg/g). Lower eGFR (whether based on creatinine alone or based on creatinine and cystatin C) and higher UACR were each significantly associ

Published
2023

32. Identification of a non-thermal X-ray burst with the Galactic magnetar SGR J1935+2154 and a fast radio burst using Insight-HXMT

Author

Li, C.K., primary, Lin, Lin, additional, Xiong, S.L., additional, Ge, Mingyu, additional, Li, X.B., additional, Li, Tipei, additional, Lu, F.J., additional, Zhang, Shuang-Nan, additional, Tuo, Y.L., additional, Nang, Y., additional, Zhang, B., additional, Xiao, S., additional, Chen, Y., additional, Song, L.M., additional, Xu, Y.P., additional, Liu, C.Z., additional, Jia, S.M., additional, Cao, X.L., additional, Qu, J.L., additional, Zhang, Shu, additional, Gu, Y.D., additional, Liao, J.Y., additional, Zhao, X.F., additional, Tan, Y., additional, Nie, J.Y., additional, Zhao, H.S., additional, Zheng, S.J., additional, Zheng, Y.G., additional, Luo, Qi, additional, Cai, C., additional, Li, B., additional, Xue, W.C., additional, Bu, Qingcui, additional, Chang, Zhi, additional, Chen, G., additional, Chen, T.X., additional, Chen, Yu-Peng, additional, Dong, Yong-Wei, additional, Du, Y.Y., additional, Gao, H., additional, Gao, G.H., additional, Gao, M., additional, Huo, J., additional, Han, D.W., additional, Jiang, L.H., additional, Huang, Y., additional, Jiang, Weichun, additional, Jin, J., additional, Kong, L.D., additional, Li, Gang, additional, Guan, J., additional, Li, M.S., additional, Li, W., additional, Li, X., additional, Li, X.F., additional, Li, Y.G., additional, Li, Z.W., additional, Liang, X.H., additional, Liu, B.S., additional, Liu, H.W., additional, Liu, X.J., additional, Lu, B., additional, Lu, X.F., additional, Luo, T., additional, Ma, X., additional, Meng, B., additional, Ou, G., additional, Sai, N., additional, Song, X.Y., additional, Sun, L., additional, Tao, Lian, additional, Wang, J., additional, Wang, G.F., additional, Wang, W.S., additional, Wang, Y.S., additional, Wen, X.Y., additional, Wu, B.B., additional, Wu, B.Y., additional, Wu, M., additional, Xiao, G.C., additional, Xu, H., additional, Yang, J.W., additional, Yang, S., additional, Yang, Yi-Jung, additional, Yang, Y.J., additional, Yi, Q.B., additional, Yin, Q.Q., additional, You, Y., additional, Zhang, C.M., additional, Zhang, A.M., additional, Zhang, F., additional, Zhang, H.M., additional, Zhang, J., additional, Zhang, T., additional, Zhang, Wei, additional, Zhang, W.C., additional, Zhang, Y., additional, Zhang, Yue, additional, Zhang, Y.F., additional, Zhang, Y.J., additional, Zhang, Z.L., additional, Zhou, D.K., additional, Zhu, Y., additional, Zhu, Y.X., additional, Chen, L., additional, Zhang, W.Z., additional, Chen, Y.B., additional, Cui, W., additional, Deng, J.K., additional, Fu, M.X., additional, Jin, Y.J., additional, Liu, G.Q., additional, Liu, Y.N., additional, Shang, R.C., additional, Zhang, Zhao, additional, Zhang, Zhi, additional, Zhou, J.F., additional, Wang, C., additional, Guo, C.C., additional, and Zhuang, R.L., additional

Published
2020
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34. Low-frequency noise in AlGaN/GaN heterojunction field effect transistors on SiC and sapphire substrates

Author

Rumyantsev, S., Levinshtein, M.E., Gaska, R., Shur, M.S., Yang, J.W., and Khan, M.A.

Subjects
Electronic structure -- Research, Gallium -- Research, Semiconductors -- Research, Transistors -- Research, Physics
Abstract

A new study investigates low-frequency noise in gallium nitride/gallium-aluminum nitride field effect transistors grown on silicon carbide and sapphire substrates.

Published
2000

36. Occurrence of Discussion about Lung Cancer Screening Between Patients and Healthcare Providers in the USA, 2017

Author

Silvestri, G.A., Soneji, S., Tanner, N.T., and Yang, J.W.

Abstract

Computed tomography lung cancer screening reduces lung cancer mortality. However, screening is underutilized. This study assesses the extent to which providers discuss lung cancer screening with their patients, as a lack of discussion and counseling may serve as a potential cause of low utilization rates. Data from 1667 adults aged 55–80 years sampled in the 2017 Health Information National Trends Survey was utilized. A weighted multivariable logistic regression model was fit with past-year discussion about lung cancer screening with a provider as the outcome. The adjusted odds of discussion were higher for current cigarette smokers compared to non-cigarette smokers (adjusted odds ratio = 3.91; 95% confidence interval [CI], 1.75 to 8.74). Despite higher odds, the absolute prevalence was low with only 18% (95% CI, 11.8 to 24.2%) of current adult smokers reporting a past-year discussion. Knowledge of screening from trusted sources of medical information, such as doctors, can increase screening rates and may ultimately reduce lung cancer mortality.

Published
2020
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