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

2002


 J.M. Kniss, G. Kindlmann, C.D. Hansen. “Multidimensional Transfer Functions for Interactive Volume Rendering,” In IEEE Trans. Vis & Comp. Graph., Vol. 8, No. 3, pp. 270--285. 2002.


J.M. Kniss, C.D. Hansen, M. Grenier, T. Robinson. “Volume Rendering Multivariate Data to Visualize Meteorological Simulations: A Case Study,” In Proceeding of The Joint Eurographics - IEEE TCVG Symposium on Visualization 2002, 2002.


J.M. Kniss, S. Premoze, C.D. Hansen, D. Ebert. “Interactive Translucent Volume Rendering and Procedural Modeling,” In Proceeding of IEEE Visualization 2002, 2002.


I. Lagzi, A.S. Tomlin, T. Turanyi, L. Haszpra, R. Meszaros, M. Berzins. “Modelling Tropospheric Ozone Formation in Hungary Using an Adaptive Gridding Method,” In Proceedings from the EUROTRAC-2 Symposium 2002, Edited by Garmisch-Partenkirchenand P.M. Midgley and M. Reuters, 2002.


I. Lagzi, A.S. Tomlin, T. Turanyi, L. Haszpra, R. Meszaros, M. Berzins. “Modeling Photochemical Air Pollution in Hungary Using an Adaptive Grid Model,” In Air Pollution modeling and Simulation - Proc.2nd International Conference on Air Pollution Modeling and Simulation (APMS'2001), pp. 264--273. april, 2002.
ISBN: 3540425152, 9783540425151


A.E. Lefohn, R.T. Whitaker. “A GPU-Based, Three-Dimensional Level Set Solver with Curvature Flow,” Technical Report, No. UUCS-02-017, University of Utah School of Computing, 2002.


P. Lindstrom, V. Pascucci. “Terrain Simplification Simplified: A General Framework for View-Dependent Out-of-Core Visualization,” In IEEE Transactions on Visualization and Computer Graphics, Vol. 8, No. 3, Note: UCRL-JC-147847, pp. 239--254. July-September, 2002.


L. Linsen, V. Pascucci, M.A. Duchaineau, B. Hamann, K.I. Joy. “Hierarchical Representation of Time-varying Volume Data with 4th-root-of-2 Subdivision and Quadrilinear B-spline Wavelets,” In Proceedings of Tenth Pacific Conference on Computer Graphics and Applications, Beijing, China, Note: UCRL-JC-151063, pp. 346--355. 2002.


Y. Livnat, X. Cavin, C.D. Hansen. “PHASE: Progressive Hardware Assisted IsoSurface Extraction Framework,” SCI Institute Technical Report, No. UUSCI-2002-001, University of Utah, 2002.


G.T. Long, B.A. Brems, C.A. Wight. “Thermal Activation of the High Explosive NTO: Sublimation, Decomposition, and Autocatalysis,” In Journal of Physical Chemistry, B, Vol. 106, No. 15, pp. 4022--4026. March, 2002.
DOI: 10.1021/jp012894v

ABSTRACT

Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) show that the heating of 5-nitro-2,4-dihydro-3H-1,2,4-triazol-3-one (NTO) leads to competitive sublimation and condensed-phase exothermic decomposition. Model-free isoconversional analysis has determined activation energies (Eα) for these processes as a function of the extent of conversion, α. Sublimation occurs most readily in an open pan; although more than simple sublimation was observed, a global activation energy of Eα = 130−140 kJ mol-1 for sublimation was determined. Nonisothermal TGA and DSC traces run on pierced pan samples provide convincing evidence for competitive sublimation and condensed-phase decomposition of NTO. Confining NTO samples in a closed pan results in condensed-phase decomposition that leads to the formation of gaseous reaction products and shows autocatalytic behavior during the latter stages. Isoconversional analysis of DSC traces of closed pan samples yield activation energies for exothermic decomposition that increase from Eα = 273 kJ mol-1 for α = 0.01 to a plateau of 333 kJ mol-1 for 0.17 ≤ α ≤ 0.35 prior to decreasing to 184 kJ mol-1 for α = 0.99. The decrease in Eα with α during the latter stages of decomposition agrees with previous reports of autocatalytic behavior.


 G.T. Long, C.A. Wight. “Thermal Decomposition of a Melt-Castable High Explosive:  Isoconversional Analysis of TNAZ,” In Journal of Physical Chemistry, B, Vol. 106, No. 10, pp. 2791--2795. February, 2002.
DOI: 10.1021/jp012859o

ABSTRACT

The thermal decomposition kinetics of the high explosive 1,3,3-trinitroazetidine (TNAZ) have been measured by nonisothermal differential scanning calorimetry (DSC). Samples of TNAZ in open pans and pierced pans undergo mainly melting (ΔHfus = 27 ± 3 kJ mol-1) and vaporization (ΔHvap = 74 ± 10 kJ mol-1) during heating. However, when confined in sealed high-pressure crucibles, exothermic thermal decomposition is observed. The activation energy for thermal decomposition has been determined as a function of the extent of reaction by isoconversional analysis. The initial value of 184 kJ mol-1 at the start of the reaction decreases to 38 kJ mol-1 near the end of the reaction. The rates clearly exhibit acceleratory behavior that is ascribed to autocatalysis. The measured heat release of thermal decomposition (Q = 640 ± 150 kJ mol-1) is independent of the heating rate and the sample mass. These results are consistent with proposed mechanisms of TNAZ decomposition in which the initial step is preferential loss of the nitramine NO2 group over loss of a gem-dinitroalkyl NO2 group.


 A. Lu, J. Taylor, M. Hartner, D. Ebert, C.D. Hansen. “Hardware-Accelerated Interactive Illustrative Stipple Drawing of Polygonal Objects,” In Proceedings of The 7th International Fall Workshop on Vision, Modeling, and Visualization, Erlangen, Germany, pp. 61--68. November, 2002.


A. Lu, C.J. Morris, D. Ebert, P. Rheingans, C.D. Hansen. “Non-Photorealistic Volume Rendering Using Stippling Techniques,” In Proceeding of IEEE Visualization 2002, Boston, MA, Note: Awarded Best Paper at the conference, pp. 211--218. 2002.


E. Luke, C.D. Hansen. “Semotus Visum: A Flexible Remote Visualization Framework,” In Proceeding of IEEE Visualization 2002, Boston, MA, pp. 61--68. 2002.


R.S. MacLeod, Q. Ni, B. Taccardi. “Modeling Cardiac Bioelectricity in Realistic Volumes: How Real is Real?,” In Einthoven 2002, Leiden, Edited by M.J. Schalij and M.J. Janse and A. van Oosterom and H.J.J. Wellens and E.E. van der Wall, The Einthoven Foundation, pp. 45-56. 2002.


R.S. MacLeod, E.D. DiBella, B.B. Punske, E.K. Jeong. “Multimodal Imaging of Cardiac Activation, Perfusion, and Ischemia,” In 14th Annual Research Symposium of the Medical Imaging Research Laboratory, 2002.


W. Martin, E. Reinhard, P. Shirly, S.G. Parker, W. Thompson. “Temporally Coherent Interactive Ray Tracing,” In Journal of Graphics Tools, Vol. 7, No. 2, pp. 41--48. 2002.


S.S. Nagarajan, O. Portniaguine, K. Sekihara, D. Hwang, C.R. Johnson. “Performance of a Minimum-Support Imaging Method for Biomagnetic Source Localization,” In Proceedings of the IEEE Engineering in Medicine and Biology Society 24th Annual International Conference, Houston, Vol. 3, pp. 2006-2007. October, 2002.


T. Nielsen, R.B. West, S.C. Linn, O. Alter, M.A. Knowling, J. O'Connell, S. Zhu, M. Fero, G. Sherlock, J.R. Pollack, P.O. Brown, D. Botstein, M. van de Rijn. “Molecular Characterisation of Soft Tissue Tumours: a Gene Expression Study,” In Lancet, Vol. 359, No. 9314, pp. 1301–-1307. April, 2002.
DOI: 10.1016/S0140-6736(02)08270-3


S.G. Parker. “Interactive Ray Tracing on a Supercomputer,” In In Practical Parallel Rendering, Edited by A. Chalmers and E. Reinhard, 2002.