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Anh Tran
Researcher at University of California, Los Angeles
Publications - 32
Citations - 1406
Anh Tran is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Steam reforming & Model predictive control. The author has an hindex of 15, co-authored 29 publications receiving 1030 citations. Previous affiliations of Anh Tran include University of California & National University of Singapore.
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Journal ArticleDOI
Evidence for sequenced molecular evolution of IDH1 mutant glioblastoma from a distinct cell of origin.
Albert Lai,Samir Kharbanda,Whitney B. Pope,Anh Tran,Orestes E. Solis,Franklin Peale,William F. Forrest,Kanan Pujara,Jose Carrillo,Ajay Pandita,Benjamin M. Ellingson,Chauncey W. Bowers,Robert Soriano,Nils Ole Schmidt,Sankar Mohan,William H. Yong,Somasekar Seshagiri,Zora Modrusan,Zhaoshi Jiang,Kenneth Aldape,Paul S. Mischel,Linda M. Liau,Cameron Escovedo,Weidong Chen,Phioanh L. Nghiemphu,C. David James,Michael D. Prados,Manfred Westphal,Katrin Lamszus,Timothy F. Cloughesy,Heidi S. Phillips,Heidi S. Phillips +31 more
TL;DR: Although histologically similar, GBMs arising with and without IDH1(R132MUT) appear to represent distinct disease entities that arise from separate cell types of origin as the result of largely nonoverlapping sets of molecular events.
Journal ArticleDOI
Apparent Diffusion Coefficient Histogram Analysis Stratifies Progression-Free Survival in Newly Diagnosed Bevacizumab-Treated Glioblastoma
Whitney B. Pope,Albert Lai,Rupal I. Mehta,Hyun J. Kim,Joe X Qiao,Jonathan R. Young,X. Xue,Jonathan G. Goldin,Matthew S. Brown,Phioanh L. Nghiemphu,Anh Tran,Timothy F. Cloughesy +11 more
TL;DR: In this article, an up-front bevacizumab-treated and control patients (n = 59 and 62, respectively) with newly diagnosed GBM were analyzed by using an ADC histogram approach based on enhancing tumor.
Journal ArticleDOI
Machine learning-based predictive control of nonlinear processes. Part I: Theory
TL;DR: Machine learning ensemble regression modeling tools are employed in the formulation of LMPC to improve prediction accuracy of RNN models and overall closed-loop performance while parallel computing is utilized to reduce computation time.
Journal ArticleDOI
CFD modeling and control of a steam methane reforming reactor
TL;DR: In this article, a computational fluid dynamics (CFD) model of an industrial-scale steam methane reforming reactor (reforming tube) used to produce hydrogen was developed and three different feedback control schemes were evaluated to drive the area-weighted average hydrogen mole fraction measured at the reforming tube outlet ( x ¯ H 2 outlet ) to a desired set-point value under the influence of a tube-side feed disturbance.
Journal ArticleDOI
CFD modeling of a industrial-scale steam methane reforming furnace
TL;DR: In this article, a computational fluid dynamics (CFD) model of an industrial-scale steam methane reformer that consists of 336 reforming reactors, 96 burners and 8 flue gas tunnels is presented.