Knowledge by Narratives: On the Methodology of Stump’s Defence

Eleonore Stump claims in her book "Wandering in Darkness" that the problem of evil can be solved best by the help of narratives. This - so Stump - is due to the fact that narratives allow one to get a general view about relevant parts of the discussion of suffering. In this context she distinguishes the more detailed view of the discussion from a more general one by two different modes of cognition: the mode of gathering "knowledge that" and that one of gathering "knowledge how". Knowledge by narratives is a subcategory of the last-mentioned one. In the paper I argue for the thesis that this distinction is not really crucial for Stump's argumentation and that in fact only "knowledge that" is relevant for her proposed solution

Phases and phase transitions in a U(1) × U(1) system with θ = 2π/3 mutual statistics

We study a U(1) × U(1) system with short-range interactions and mutual θ = 2π/3 statistics in (2+1) dimensions. We are able to reformulate the model to eliminate the sign problem and perform a Monte Carlo study. We find a phase diagram containing a phase with only small loops and two phases with one species of proliferated loop. We also find a phase where both species of loop condense, but without any gapless modes. Lastly, when the energy cost of loops becomes small, we find a phase that is a condensate of bound states, each made up of three particles of one species and a vortex of the other. We define several exact reformulations of the model that allow us to precisely describe each phase in terms of gapped excitations. We propose field-theoretic descriptions of the phases and phase transitions, which are particularly interesting on the “self-dual” line where both species have identical interactions. We also define irreducible responses useful for describing the phases

Drug Reformulation Regulatory Gaming in Pharmaceuticals: Enforcement & Innovation Implications

This article examines drug reformulation regulatory gaming as a vehicle for analyzing the way in which European courts and the Commission are currently approaching innovation issues in the pharmaceutical sector. First, the economics literature regarding pharmaceutical innovation is briefly summarized. Next, the phenomenon of regulatory gaming is introduced, followed by an analysis of the two primary theories of harm being used to address drug reformulations as a competition concern. In comparing the recent General Court decision in AstraZeneca to earlier U.S. court cases addressing similar conduct, it is asserted that these approaches differ in significant ways with regards to preservation of innovation incentives as well as on the basis of institutional and evidentiary concerns. Finally, this discussion is then placed into the broader context of the ongoing debate regarding pharmaceutical innovation that first surfaced in the Syfait cases—in particular, the desirability of sector-specific competition law analysis of pharmaceutical innovation

Fractal Complex Dimensions, Riemann Hypothesis and Invertibility of the Spectral Operator

A spectral reformulation of the Riemann hypothesis was obtained in [LaMa2] by the second author and H. Maier in terms of an inverse spectral problem for fractal strings. This problem is related to the question "Can one hear the shape of a fractal drum?" and was shown in [LaMa2] to have a positive answer for fractal strings whose dimension is c\in(0,1)-\{1/2} if and only if the Riemann hypothesis is true. Later on, the spectral operator was introduced heuristically by M. L. Lapidus and M. van Frankenhuijsen in their theory of complex fractal dimensions [La-vF2, La-vF3] as a map that sends the geometry of a fractal string onto its spectrum. We focus here on presenting the rigorous results obtained by the authors in [HerLa1] about the invertibility of the spectral operator. We show that given any $c\geq0$, the spectral operator $\mathfrak{a}=\mathfrak{a}_{c}$, now precisely defined as an unbounded normal operator acting in a Hilbert space $\mathbb{H}_{c}$, is `quasi-invertible' (i.e., its truncations are invertible) if and only if the Riemann zeta function $\zeta=\zeta(s)$ does not have any zeroes on the line $Re(s)=c$. It follows that the associated inverse spectral problem has a positive answer for all possible dimensions $c\in (0,1)$, other than the mid-fractal case when $c=1/2$, if and only if the Riemann hypothesis is true.Comment: To appear in: "Fractal Geometry and Dynamical Systems in Pure and Applied Mathematics", Part 1 (D. Carfi, M. L. Lapidus, E. P. J. Pearse and M. van Frankenhuijsen, eds.), Contemporary Mathematics, Amer. Math. Soc., Providence, RI, 2013. arXiv admin note: substantial text overlap with arXiv:1203.482

K-Adaptability in Two-Stage Distributionally Robust Binary Programming

We propose to approximate two-stage distributionally robust programs with binary recourse decisions by their associated K-adaptability problems, which pre-select K candidate secondstage policies here-and-now and implement the best of these policies once the uncertain parameters have been observed. We analyze the approximation quality and the computational complexity of the K-adaptability problem, and we derive explicit mixed-integer linear programming reformulations. We also provide efficient procedures for bounding the probabilities with which each of the K second-stage policies is selected

Time-parallel iterative solvers for parabolic evolution equations

We present original time-parallel algorithms for the solution of the implicit Euler discretization of general linear parabolic evolution equations with time-dependent self-adjoint spatial operators. Motivated by the inf-sup theory of parabolic problems, we show that the standard nonsymmetric time-global system can be equivalently reformulated as an original symmetric saddle-point system that remains inf-sup stable with respect to the same natural parabolic norms. We then propose and analyse an efficient and readily implementable parallel-in-time preconditioner to be used with an inexact Uzawa method. The proposed preconditioner is non-intrusive and easy to implement in practice, and also features the key theoretical advantages of robust spectral bounds, leading to convergence rates that are independent of the number of time-steps, final time, or spatial mesh sizes, and also a theoretical parallel complexity that grows only logarithmically with respect to the number of time-steps. Numerical experiments with large-scale parallel computations show the effectiveness of the method, along with its good weak and strong scaling properties