Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.

SCI Publications

2007


 T.J. Lujan, M.S. Dalton, B.M. Thompson, B.J. Ellis, J.A. Weiss. “Effect of ACL Deficiency on MCL Strains and Joint Kinematics,” In Journal of Biomechanical Engineering, Vol. 129, No. 3, pp. 386--392. 2007.


T.J. Lujan, C.J. Underwood, H.B. Henninger, B.M. Thompson, J.A. Weiss. “Effect of Dermatan Sulfate Glycosaminoglycans on the Quasi-Static Material Properties of the Human Medial Collateral Ligament,” In Journal of Orthopaedic Research, Vol. 25, No. 7, pp. 894--903. 2007.


M. Malik, Y. Birnbaum, R.S. MacLeod, V. Shusterman. “Markers of impaired repolarization,” In Journal of Electrocardiology, Vol. 40, No. 1, pp. S54--S57. January, 2007.


N.D. Marsh, I. Preciado, E.G. Eddings, A.F. Sarofim, A.B. Palotas, J.D. Robertson. “Evaluation of Organometallic Fuel Additives for Soot Suppression,” In Combustion Science and Technology, Vol. 179, No. 5, pp. 987--1001. 2007.
DOI: 10.1080/00102200600862497

ABSTRACT

In this work, we investigate the utility of the smoke lamp for evaluating the soot-reducing potential of additives, by comparing it to a more complex liquid-fed laminar diffusion flame. The additives, ferrocene (bis(cyclopentadienyl) iron-Fe(C5H5)2), ruthenocene (bis(cyclopentadienyl)ruthenium-Ru(C5H5)2), iron naphthenate (a 12% iron salt of naphthenic acid, which is a mixture of fatty carboxylic acids, some of which may include a cyclopentane ring), and MMT (Methylcyclopentadienyl manganese tricarbonyl-CH3C5H4Mn(CO)3) are evaluated at various concentrations in the jet fuel JP-8. Although the smoke lamp is a simple, inexpensive, and widely-available test for evaluating the sooting potential of liquid fuels, it does not provide an effective measure of soot suppression by metal-containing additives. The drop-tube reactor more accurately captures the physical conditions and processes—droplet vaporization, ignition, and rich vs. lean operation—typically found in more complex systems. We find in the smoke lamp that ferrocene, and to a lesser degree ruthenocene, are effective soot suppressors when used in JP-8, and that their effectiveness increases with increasing concentration. In the smoke lamp, MMT and iron naphthenate have minimal effect. On the other hand, in the drop-tube reactor, all four additives are quite effective, especially at fuel lean conditions, where soot suppression reaches 90–95%. Under fuel-rich conditions, where in some cases the additives elevate the yield of soot aerosol slightly, we find a significant increase in the production of the soluble organic fraction of the aerosol, i.e., tar. In order to understand why the smoke lamp sometimes fails to indicate a soot suppressing potential (i.e., from MMT and iron naphthenate), soot samples were collected from a wick lamp burning ferrocene and iron naphthenate additives in JP-8. These samples, as well as several from the drop-tube reactor, were analyzed by X-Ray Fluorescence (XRF) in order to determine their metal content, and we find that the soot aerosol produced by the wick lamp using ferrocene-containing fuel had roughly 30 times the iron content of the soot aerosol produced by the wick lamp using iron-naphthenate-containing fuel. This difference in metal content is not found in samples produced in the drop-tube reactor. We conclude that the poor performance of iron naphthenate in the smoke lamp is likely the result poor vaporization of the additive from the wick, a consequence of its high molecular weight (average 465).


 M.D. Meyer, B. Nelson, R.M. Kirby, R.T. Whitaker. “Particle Systems for Efficient and Accurate Finite Element Visualization,” In IEEE Transactions on Visualization and Computer Graphics, Vol. 13, No. 5, pp. 1015--1026. 2007.


M.D. Meyer, R.M. Kirby, R.T. Whitaker. “Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles,” In IEEE Transactions on Visualization and Computer Graphics, Vol. 13, No. 6, IEEE, pp. 1704--1711. Nov, 2007.


D. Nain, M. Styner, M. Niethammer, J.J. Levitt, M.E. Shenton, G. Gerig, A. Bobick, A. Tannenbaum. “Statistical Shape Analysis of Brain Structures Using Spherical Wavelets,” In Proceedings of the 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2007), IEEE Press, pp. 209--212. 2007.


O. Nemitz, T. Tasdizen, M. Rumpf, R.T. Whitaker. “Anisotropic Curvature Motion for Structure Enhancing Smoothing of 3D MR Angiography Data,” In Journal of Mathematical Imaging and Vision, Vol. 7, No. 3, pp. 217--229. 2007.
DOI: 10.1007/s10851-006-0645-2


E.P. Newren, A.L. Fogelson, R.D. Guy, R.M. Kirby. “Unconditionally Stable Discretizations of the Immersed Boundary Equations,” In Journal of Computational Physics, Vol. 222, No. 2, pp. 702--719. 2007.


E.P. Newren, A.L. Fogelson, R.D. Guy, R.M. Kirby. “Unconditionally Stable Discretizations of the Immersed Boundary Equations,” In Journal of Computational Physics, Vol. 222, No. 2, pp. 702--719. March, 2007.


T. Ochotta, C.E. Scheidegger, J. Schreiner, Y. Lima, R.M. Kirby, C.T. Silva. “A Unified Projection Operator for Moving Least Squares Surfaces,” SCI Institute Technical Report, No. UUSCI-2007-006, University of Utah, 2007.


L. Omberg, G.H. Golub, O. Alter. “A Tensor Higher-Order Singular Value Decomposition for Integrative Analysis of DNA Microarray Data From Different Studies,” In Proceedings of the National Academy of Sciences, Vol. 104, No. 47, Proceedings of the National Academy of Sciences, pp. 18371–-18376. November, 2007.
DOI: 10.1073/pnas.0709146104


R. Palmer, G. Gopalakrishnan, R.M. Kirby. “Semantics Driven Dynamic Partial-Order Reduction of MPI-based Parallel Programs,” In Proceedings of Parallel and Distributed Systems: Testing and Debugging (PADTAD), London, UK, Note: Awarded Best Paper, 2007.


S.G. Parker, S. Boulos, J. Bigler, A. Robison. “RTSL: a Ray Tracing Shading Language,” In In 2007 IEEE/Eurographics Symposium on Interactive Ray Tracing, pp. 149--160. 2007.


S.G. Parker, R. Armstrong, D. Bernholdt, T. Dahlgren, T. Epperly, J. Kenny, M. Krishnan, G. Kumfert, J. Larson, L.C. McInnes, J. Nieplocha, J. Ray, S. Shasharina. “Enabling Advanced Scientific Computing Software,” In CTWatch Quarterly, Vol. 3, No. 4, 2007.


V. Pascucci, G. Scorzelli, P.-T. Bremer, A. Mascarenhas. “Robust On-line Computation of Reeb Graphs: Simplicity and Speed,” In ACM Transactions on Graphics: ACM SIGGRAPH 2007 Papers, ACM Press, New York, NY, USA pp. 1057--1066. 2007.


S. Pervez, G. Gopalakrishnan, R.M. Kirby, R. Palmer, R. Thakur, W. Gropp. “Practical Model Checking Method for Verifying Correctness of MPI Programs,” In Recent Advances in Parallel Virtual Machine and Message Passing Interface - Proceedings of EuroPVM-MPI 2007, Paris, France, Vol. 4757/2007, pp. 344--353. 2007.


N.S. Phatak, Q. Sun, S.-E. Kim, D.L. Parker, R.K. Sanders, A.I. Veress, B.J. Ellis, J.A. Weiss. “Noninvasive Determination of Ligament Strain with Deformable Image Registration,” In Annals of Biomedical Engineering, Vol. 35, No. 7, pp. 1175--1187. February, 2007.


A.B. Porter, L. Healy, N.L. Foster, K.A. Josephs. “Compulsive Urination as a Presenting Symptom of Frontotemporal Dementia,” In European Journal of Neurology, Vol. 14, Note: Letter to the Editor, pp. e16--e17. 2007.


G.A. Preston, E.W. Anderson, C.T. Silva. “Effects of 10 Hz rTMS on Alpha Spectral Dynamics and Working Memory Performance,” In Proceedings of Neuroscience 2007 Poster Session, Note: Poster presentation., 2007.