Zobrazeno 1 - 10
of 90
pro vyhledávání: '"Thomas A. Zang"'
Autor:
Soorya Pradeep, Thomas A. Zangle
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-8 (2024)
Abstract The continuous balance of growth and degradation inside cells maintains homeostasis. Disturbance of this balance by internal or external factors cause state of disease, while effective disease treatments seek to restore this balance. Here, w
Externí odkaz:
https://doaj.org/article/0d5fda13aba24cf6a8fc98ca9b2879ff
Autor:
Edward R. Polanco, Tarek E. Moustafa, Andrew Butterfield, Sandra D. Scherer, Emilio Cortes-Sanchez, Tyler Bodily, Benjamin T. Spike, Bryan E. Welm, Philip S. Bernard, Thomas A. Zangle
Publikováno v:
Communications Biology, Vol 5, Iss 1, Pp 1-12 (2022)
The authors developed a real-time and label-free approach based on quantitative phase imaging to determine drug sensitivity with significant advantages over endpoint viability or metabolic assays, and which reveals single cell response heterogeneity.
Externí odkaz:
https://doaj.org/article/bdafcd4216674d5e8612300cafe2762b
Autor:
Tarek E. Moustafa, Edward R. Polanco, Rachel L. Belote, Robert L. Judson-Torres, Thomas A. Zangle
Publikováno v:
HardwareX, Vol 13, Iss , Pp e00399- (2023)
The combination of multiple imaging modalities in a single microscopy system can enable new insights into biological processes. In this work, we describe the construction and rigorous characterization of a custom microscope with multimodal imaging in
Externí odkaz:
https://doaj.org/article/b186bd63057a4636aa94ff3312312e98
Publikováno v:
16th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de0bd92337d0912451b2c7e985e01556
https://doi.org/10.2514/6.2015-3440
https://doi.org/10.2514/6.2015-3440
Publikováno v:
16th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::23ba6646b136b7280eb03fad356dbab0
https://doi.org/10.2514/6.2015-3443
https://doi.org/10.2514/6.2015-3443
Autor:
Soorya Pradeep, Thomas A. Zangle
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-14 (2022)
Abstract Transport of mass within cells helps maintain homeostasis and is disrupted by disease and stress. Here, we develop quantitative phase velocimetry (QPV) as a label-free approach to make the invisible flow of mass within cells visible and quan
Externí odkaz:
https://doaj.org/article/86eec09cea31457fbf7bc1f404ebaff6
Publikováno v:
Numerical Algorithms. 38:209-236
This paper discusses two stochastic approaches to computing the propagation of uncertainty in numerical simulations: polynomial chaos and stochastic collocation. Chebyshev polynomials are used in both cases for the conventional, deterministic portion
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad312f795c5f4773e15b02c5e2461b0f
https://doi.org/10.1007/s11075-004-2866-z
https://doi.org/10.1007/s11075-004-2866-z
Publikováno v:
AIAA Journal. 42:1669-1676
A fully spectral, polynomial chaos method for the propagation of uncertainty in numerical simulations of compressible, turbulent flow is described. The method is applied to the flow in a quasi-one-dimensional nozzle. Results demonstrate the ability o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e9c72fa794602a9165dbfa39f12b262
https://doi.org/10.2514/1.5674
https://doi.org/10.2514/1.5674
Publikováno v:
AIAA Journal. 42:815-822
Many application codes, such as finite-element structural analyses and computational fluid dynamics codes, are capable of producing many sensitivity derivatives at a small fraction of the cost of the underlying analysis. This paper describes a simple
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35fa791b556b79c220bfe98019904bf0
https://doi.org/10.2514/1.2820
https://doi.org/10.2514/1.2820
Publikováno v:
Computational Optimization and Applications. 26:219-230
A general framework is proposed for what we call the sensitivity derivative Monte Carlo (SDMC) solution of optimal control problems with a stochastic parameter. This method employs the residual in the first-order Taylor series expansion of the cost f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c307b09bec0e59cd752f4a623db1390
https://doi.org/10.1023/a:1026079021836
https://doi.org/10.1023/a:1026079021836