http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Giles, F J,Abruzzese, E,Rosti, G,Kim, D-W,Bhatia, R,Bosly, A,Goldberg, S,Kam, G L S,Jagasia, M,Mendrek, W,Fischer, T,Facon, T,Dü,nzinger, U,Marin, D,Mueller, M C,Shou, Y,Gallagher, N J,Larson, R A Macmillan Publishers Limited 2010 Leukemia Vol.24 No.7
Nilotinib is a highly selective Bcr–Abl inhibitor approved for imatinib-resistant chronic myeloid leukemia (CML). Nilotinib and dasatinib, a multi-targeted kinase inhibitor also approved for second-line therapy in CML, have different patterns of kinase selectivity, pharmacokinetics, and cell uptake and efflux properties, and thus patients may respond to one following failure of the other. An international phase II study of nilotinib was conducted in CML patients (39 chronic phase (CP), 21 accelerated phase (AP)) after failure of both imatinib and dasatinib. Median times from diagnosis of CP or AP to nilotinib therapy were 89 and 83 months, respectively. Complete hematological response and major cytogenetic response (MCyR) rates in CP were 79% and 43%, respectively. Of 17 evaluable patients with CML-AP, 5 (29%) had a confirmed hematological response and 2 (12%) a MCyR. The median time to progression has not yet been reached in CP patients. At 18 months 59% of patients were progression-free. Median overall survival for both populations has not been reached, and the estimated 18-month survival rate in CML-CP was 86% and that at 12 months for CML-AP was 80%. Nilotinib is an effective therapy in CML-CP and -AP following failure of both imatinib and dasatinib therapy.
Eck, T. F.,Holben, B. N.,Reid, J. S.,Xian, P.,Giles, D. M.,Sinyuk, A.,Smirnov, A.,Schafer, J. S.,Slutsker, I.,Kim, J.,Koo, J.-H.,Choi, M.,Kim, K. C.,Sano, I.,Arola, A.,Sayer, A. M.,Levy, R. C.,Munchak American Geophysical Union 2018 Journal of Geophysical Research: Atmospheres Vol.123 No.10
<P>Analysis of Sun photometer measured and satellite retrieved aerosol optical depth (AOD) data has shown that major aerosol pollution events with very high fine mode AOD (>1.0 in midvisible) in the China/Korea/Japan region are often observed to be associated with significant cloud cover. This makes remote sensing of these events difficult even for high temporal resolution Sun photometer measurements. Possible physical mechanisms for these events that have high AOD include a combination of aerosol humidification, cloud processing, and meteorological covariation with atmospheric stability and convergence. The new development of Aerosol Robotic Network Version 3 Level 2 AOD with improved cloud screening algorithms now allow for unprecedented ability to monitor these extreme fine mode pollution events. Further, the spectral deconvolution algorithm (SDA) applied to Level 1 data (L1; no cloud screening) provides an even more comprehensive assessment of fine mode AOD than L2 in current and previous data versions. Studying the 2012 winter-summer period, comparisons of Aerosol Robotic Network L1 SDA daily average fine mode AOD data showed that Moderate Resolution Imaging Spectroradiometer satellite remote sensing of AOD often did not retrieve and/or identify some of the highest fine mode AOD events in this region. Also, compared to models that include data assimilation of satellite retrieved AOD, the L1 SDA fine mode AOD was significantly higher in magnitude, particularly for the highest AOD events that were often associated with significant cloudiness.</P>
Optimized finite element model updating method for damage detection using limited sensor information
L. Cheng,H. C. Xie,B. F. Spencer, Jr.,R. K. Giles 국제구조공학회 2009 Smart Structures and Systems, An International Jou Vol.5 No.6
Limited, noisy data in vibration testing is a hindrance to the development of structural damage detection. This paper presents a method for optimizing sensor placement and performing damage detection using finite element model updating. Sensitivity analysis of the modal flexibility matrix determines the optimal sensor locations for collecting information on structural damage. The optimal sensor locations require the instrumentation of only a limited number of degrees of freedom. Using noisy modal data from only these limited sensor locations, a method based on model updating and changes in the flexibility matrix successfully determines the location and severity of the imposed damage in numerical simulations. In addition, a steel cantilever beam experiment performed in the laboratory that considered the effects of model error and noise tested the validity of the method. The results show that the proposed approach effectively and robustly detects structural damage using limited, optimal sensor information.
Optimized finite element model updating method for damage detection using limited sensor information
Cheng, L.,Xie, H.C.,Spencer, B.F. Jr.,Giles, R.K. Techno-Press 2009 Smart Structures and Systems, An International Jou Vol.5 No.6
Limited, noisy data in vibration testing is a hindrance to the development of structural damage detection. This paper presents a method for optimizing sensor placement and performing damage detection using finite element model updating. Sensitivity analysis of the modal flexibility matrix determines the optimal sensor locations for collecting information on structural damage. The optimal sensor locations require the instrumentation of only a limited number of degrees of freedom. Using noisy modal data from only these limited sensor locations, a method based on model updating and changes in the flexibility matrix successfully determines the location and severity of the imposed damage in numerical simulations. In addition, a steel cantilever beam experiment performed in the laboratory that considered the effects of model error and noise tested the validity of the method. The results show that the proposed approach effectively and robustly detects structural damage using limited, optimal sensor information.
Tripathi, Om P.,Baldwin, Mark,Charlton‐,Perez, Andrew,Charron, Martin,Eckermann, Stephen D.,Gerber, Edwin,Harrison, R. Giles,Jackson, David R.,Kim, Baek‐,Min,Kuroda, Yuhji,Lang, Andrea,Mah John WileySons, Ltd 2015 Quarterly journal of the Royal Meteorological Soci Vol.141 No.689
<P>Extreme variability of the winter‐ and spring‐time stratospheric polar vortex has been shown to affect extratropical tropospheric weather. Therefore, reducing stratospheric forecast error may be one way to improve the skill of tropospheric weather forecasts. In this review, the basis for this idea is examined. A range of studies of different stratospheric extreme vortex events shows that they can be skilfully forecasted beyond 5 days and into the sub‐seasonal range (0–30 days) in some cases. Separate studies show that typical errors in forecasting a stratospheric extreme vortex event can alter tropospheric forecast skill by 5–7% in the extratropics on sub‐seasonal time‐scales. Thus understanding what limits stratospheric predictability is of significant interest to operational forecasting centres. Both limitations in forecasting tropospheric planetary waves and stratospheric model biases have been shown to be important in this context.</P>
Five polymorphisms and breast cancer risk: results from the Breast Cancer Association Consortium.
Gaudet, Mia M,Milne, Roger L,Cox, Angela,Camp, Nicola J,Goode, Ellen L,Humphreys, Manjeet K,Dunning, Alison M,Morrison, Jonathan,Giles, Graham G,Severi, Gianluca,Baglietto, Laura,English, Dallas R,Cou American Association for Cancer Research 2009 Cancer Epidemiology, Biomarkers & Prevention Vol.18 No.5
<P>Previous studies have suggested that minor alleles for ERCC4 rs744154, TNF rs361525, CASP10 rs13010627, PGR rs1042838, and BID rs8190315 may influence breast cancer risk, but the evidence is inconclusive due to their small sample size. These polymorphisms were genotyped in more than 30,000 breast cancer cases and 30,000 controls, primarily of European descent, from 30 studies in the Breast Cancer Association Consortium. We calculated odds ratios (OR) and 95% confidence intervals (95% CI) as a measure of association. We found that the minor alleles for these polymorphisms were not related to invasive breast cancer risk overall in women of European descent: ECCR4 per-allele OR (95% CI) = 0.99 (0.97-1.02), minor allele frequency = 27.5%; TNF 1.00 (0.95-1.06), 5.0%; CASP10 1.02 (0.98-1.07), 6.5%; PGR 1.02 (0.99-1.06), 15.3%; and BID 0.98 (0.86-1.12), 1.7%. However, we observed significant between-study heterogeneity for associations with risk for single-nucleotide polymorphisms (SNP) in CASP10, PGR, and BID. Estimates were imprecise for women of Asian and African descent due to small numbers and lower minor allele frequencies (with the exception of BID SNP). The ORs for each copy of the minor allele were not significantly different by estrogen or progesterone receptor status, nor were any significant interactions found between the polymorphisms and age or family history of breast cancer. In conclusion, our data provide persuasive evidence against an overall association between invasive breast cancer risk and ERCC4 rs744154, TNF rs361525, CASP10 rs13010627, PGR rs1042838, and BID rs8190315 genotypes among women of European descent.</P>