Biomedical Engineering Reference
In-Depth Information
models is that they provide insight into the physics of the fundamental processes
and replace the traditional phenomenological models obtained by fitting of parame-
ters through experimental or clinical investigations. Therefore, these models offer a
bridge between the events on the smallest scale and the larger measurable macro-
scale. We mention that, for example, new materials or devices with desired features
rely on certain physics which can be captured by the introduced multiscale computa-
tional models. We anticipate a stronger and seamless multiscale method integration
with imaging for creation of novel and robust computational tools in medicine or
material characterization.
Acknowledgments
This work has been partially supported with the Methodist Research Insti-
tute, by the grants OI 174028 and III 41007 of the Serbian Ministry of Education and Science,
and City of Kragujevac - Serbia. Authors also acknowledge partial supports from the follow-
ing funding sources: the Ernest Cockrell Jr. Distinguished Endowed Chair (M.F.), US Depart-
ment of Defense (W81XWH-09-1-0212) (M.F.), National Institute of Health (U54CA143837,
U54CA151668) (M.F.).
References
1. Adriani G, Tullio MD, Ferrari M, Hussain F, Pascazio G, Liu X, Decuzzi P (2012) The pref-
erential targeting of the diseased microvasculature by disk-like particles. Biomaterials 33:
5504-5513.
2. Alber F, Dokudovskaya S, Veenhoff LM, Zhang W, Kipper J, Devos D, Suprapto A, Karni-
Schmidt O, Williams R, Chait BT (2007) Determining the architectures of macromolecular
assemblies. Nature 450: 683-694.
3. Alber F, Dokudovskaya S, Veenhoff LM, Zhang W, Kipper J, Devos D, Suprapto A, Karni-
Schmidt O, Williams R, Chait BT (2007) Determining the architectures of macromolecular
assemblies. Nature 450 (7170): 683-694.
4. Allen MP, Tildesley DJ (1989). Computer simulation of liquids, Oxford university press.
5. Alpert S, Banks G (1976) The concentration dependence of the hemoglobin mutual diffusion
coefficient. Biophys. Chem. 4(3): 287-296.
6. Bathe KJ (1996). Finite Element Procedures. Englewood Cliffs, N.J., Prentice-Hall, Inc..
7. Boutin C, Geindreau C (2010) Periodic homogenization and consistent estimates of transport
parameters through sphere and polyhedron packings in the whole porosity range Phys. Review
E 82( ): 036311-036318.
8. Boving TB, Grathwohl P (2001) Tracer diffusion coefficients in sedimentary rocks: correlation
to porosity and hydraulic conductivity. J. Contam. Hydrol. 53 (1-2): 85-100.
9. Carlo DD, Irimia D, Tompkins RG, Toner M (2007) Continuous inertial focusing, ordering,
and separation of particles in microchannels. PNAS 104 (48): 18892-18897.
10. Chu-Cruz ER, Aksimentiev A, Schulten K (2006) Water silica force field for simulating nan-
odevices. J. Phys. Chem. B 110(43): 21497-21508.
11. Desai TA, Hansford DJ, Kulinsky L, Nashat AH, Rasi G, Tu J, Wang Y, Zhang M, Ferrari M
(1999) Nanopore technology for biomedical applications. Biomed. Microdev. 2(1): 11-40.
12. English A, Dole M (1950) Diffusion of sucrose in supersaturated solutions. J. Am. Chem. Soc.
72(7): 3261-3267.
13. Fine D, Grattoni A, Hosali S, Ziemys A, Rosa ED, Gill J, Medema R, Hudson L, Kojic M,
Milosevic M, Ferrari M (2010) A robust nanofluidic membrane with tunable zero-order release
for implantable dose specific drug delivery. Lab Chip DOI: 10.1039/c0lc00013b.
14. Forster P, Cheetham A (2003) Hybrid Inorganic-Organic Solids: An Emerging Class of
Nanoporous Catalysts. Top. Catal. 24(1): 79-86.
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