A density functional perspective for one-particle systems

Density functional theory is discussed in the context of one-particle systems. We show that the ground state density $\rho_0(x)$ and energy $E_0$ are simply related to a family of external potential energy functions with ground state wave functions $\psi_n(x) \propto \rho_0(x)^n$ and energies $E_n=2nE_0$ for certain integer values of $n$.Comment: 7 pages, ReVTeX4, submitted to Am. J. Phy

Outerbridge grade IV cartilage lesions in the hip identified at arthroscopy

No abstract available

Thermal stability of coupled ferromagnetic and superparamagnetic particles

We consider a single-domain ferromagnetic particle with uniaxial anisotropy coupled to a single-domain soft ferromagnetic particle (superparamagnetic particle). The problem of thermally agitated magnetization reversal in this case can be reduced to the random magnetization dynamics of the first particle with an effectively larger anisotropy field. The magnetic external field is also altered in a manner that depends on the sign of the coupling and can be either enhanced or suppressed.Comment: 3 pages, 2 figures, presented at MMM'0

Using multiple reference ontologies: Managing composite annotations

There are a growing number of reference ontologies available across a variety of biomedical domains and current research focuses on their construction, organization and use. An important use case for these ontologies is annotation—where users create metadata that access concepts and terms in reference ontologies. We draw on our experience in physiological modeling to present a compelling use case that demonstrates the potential complexity of such annotations. In the domain of physiological biosimulation, we argue that most annotations require the use of multiple reference ontologies. We suggest that these “composite” annotations should be retained as a repository of knowledge about post-coordination that promotes sharing and interoperation across biosimulation models

Advances in semantic representation for multiscale biosimulation: a case study in merging models

As a case-study of biosimulation model integration, we describe our experiences applying the SemSim methodology to integrate independently-developed, multiscale models of cardiac circulation. In particular, we have integrated the CircAdapt model (written by T. Arts for MATLAB) of an adapting vascular segment with a cardiovascular system model (written by M. Neal for JSim). We report on three results from the model integration experience. First, models should be explicit about simulations that occur on different time scales. Second, data structures and naming conventions used to represent model variables may not translate across simulation languages. Finally, identifying the dependencies among model variables is a non-trivial task. We claim that these challenges will appear whenever researchers attempt to integrate models from others, especially when those models are written in a procedural style (using MATLAB, Fortran, etc.) rather than a declarative format (as supported by languages like SBML, CellML or JSim’s MML)