The New Biology and International Sharing - Lessons from the Life and Works of George P. Smith, II (Inaugural Lecture: George P. Smith, II, Distinguished Visiting Professorship-Chair of Law)

[The George P. Smith, II, Distinguished Visiting Professorship-Chair of Law and Legal Research endowment was established by George P. Smith to broaden students\u27 exposure to scholars and judges of national and international reputation and to allow distinguished visiting scholars the opportunity to do research at Indiana University and share their ideas with the faculty and students of the Indiana University School of Law and Indiana University. George P. Smith, an Indiana native, received his B.S. degree in business, economics, and public policy in 1961 from Indiana University and his J. D. from the Indiana University School of Law in 1964. He was awarded an LL.M from Columbia University in 1975 and an Honorary Degree from Indiana University in 1998. George P. Smith has been a professor of law at The Catholic University of America, in Washington, D.C., since 1977. To inaugurate this endowment, the Honorable Michael D. Kirby of the High Court of Australia delivered the following lecture on January 26, 2000. Justice Kirby received his B.A., LL.M, and BEc from Sydney University and is internationally recognized for his work in bio-ethics, human rights, and international law. In 1991, Justice Kirby was awarded the Australian Human Rights Medal. He currently serves as the president of the International Commission of Jurists.

Sexuality and Global Forces: Dr. Alfred Kinsey and the Supreme Court of the United States (Branigin Lecture)

Branigin Lecture, presented at Indiana University on October 14,2006

The New Biology and International Sharing - Lessons from the Life and Works of George P. Smith, II (Inaugural Lecture: George P. Smith, II, Distinguished Visiting Professorship-Chair of Law)

[The George P. Smith, II, Distinguished Visiting Professorship-Chair of Law and Legal Research endowment was established by George P. Smith to broaden students\u27 exposure to scholars and judges of national and international reputation and to allow distinguished visiting scholars the opportunity to do research at Indiana University and share their ideas with the faculty and students of the Indiana University School of Law and Indiana University. George P. Smith, an Indiana native, received his B.S. degree in business, economics, and public policy in 1961 from Indiana University and his J. D. from the Indiana University School of Law in 1964. He was awarded an LL.M from Columbia University in 1975 and an Honorary Degree from Indiana University in 1998. George P. Smith has been a professor of law at The Catholic University of America, in Washington, D.C., since 1977. To inaugurate this endowment, the Honorable Michael D. Kirby of the High Court of Australia delivered the following lecture on January 26, 2000. Justice Kirby received his B.A., LL.M, and BEc from Sydney University and is internationally recognized for his work in bio-ethics, human rights, and international law. In 1991, Justice Kirby was awarded the Australian Human Rights Medal. He currently serves as the president of the International Commission of Jurists.

Outcome prediction in mathematical models of immune response to infection

Clinicians need to predict patient outcomes with high accuracy as early as possible after disease inception. In this manuscript, we show that patient-to-patient variability sets a fundamental limit on outcome prediction accuracy for a general class of mathematical models for the immune response to infection. However, accuracy can be increased at the expense of delayed prognosis. We investigate several systems of ordinary differential equations (ODEs) that model the host immune response to a pathogen load. Advantages of systems of ODEs for investigating the immune response to infection include the ability to collect data on large numbers of `virtual patients', each with a given set of model parameters, and obtain many time points during the course of the infection. We implement patient-to-patient variability $v$ in the ODE models by randomly selecting the model parameters from Gaussian distributions with variance $v$ that are centered on physiological values. We use logistic regression with one-versus-all classification to predict the discrete steady-state outcomes of the system. We find that the prediction algorithm achieves near $100\%$ accuracy for $v=0$, and the accuracy decreases with increasing $v$ for all ODE models studied. The fact that multiple steady-state outcomes can be obtained for a given initial condition, i.e. the basins of attraction overlap in the space of initial conditions, limits the prediction accuracy for $v>0$. Increasing the elapsed time of the variables used to train and test the classifier, increases the prediction accuracy, while adding explicit external noise to the ODE models decreases the prediction accuracy. Our results quantify the competition between early prognosis and high prediction accuracy that is frequently encountered by clinicians.Comment: 14 pages, 7 figure

A new family of variational-form-based regularizers for reconstructing epicardial potentials from body-surface mapping

Journal ArticleWe propose a new family of regularizers for the inverse ECG problem, using a variational principle that underlies finite element approximation methods. As an alternative to traditional Tikhonov regularizers, the variational formulation has several advantages: 1)it enables a simple construction of the gradient operator (in a matrix form) over irregular meshes, which is often difficult to derive; 2) it achieves consistent regularization under multi-scale simulations by preserving the norm, which is evaluated by the resolution-independent L2-norm rather than the discrete Euclidean norm; and 3)it allows simultaneous application of multiple constraints efficiently. Our proposed method is validated by simulation on a realistic 3D model with clinical heart data, showing that the variational formulation may improve a broader range of potential-based electrocardiographic problems

On the use of adjoint-based sensitivity estimates to control local mesh refinement

Journal ArticleThe goal of efficient and robust error control, through local mesh adaptation in the computational solution of partial differential equations, is predicated on the ability to identify in an a posteriori way those localized regions whose refinement will lead to the most significant reductions in the error. The development of a posteriori error estimation schemes and of a refinement infrastructure both facilitate this goal, however they are incomplete in the sense that they do not provide an answer as to where the maximal impact of refinement may be gained or what type of refinement - elemental partitioning (h-refinement) or polynomial enrichment (p-refinement) - will best lead to that gain. In essence, one also requires knowledge of the sensitivity of the error to both the location and the type of refinement. In this communication we propose the use of adjoint-based sensitivity analysis to discriminate both where and how to refine. We present both an adjoint-based and an algebraic perspective on defining and using sensitivities, and then demonstrate through several one-dimensional model problem experiments the feasibility and benefits of our approach