Single molecule photon counting statistics for quantum mechanical chromophore dynamics

We extend the generating function technique for calculation of single molecule photon emission statistics [Y. Zheng and F. L. H. Brown, Phys. Rev. Lett., 90,238305 (2003)] to systems governed by multi-level quantum dynamics. This opens up the possibility to study phenomena that are outside the realm of purely stochastic and mixed quantum-stochastic models. In particular, the present methodology allows for calculation of photon statistics that are spectrally resolved and subject to quantum coherence. Several model calculations illustrate the generality of the technique and highlight quantitative and qualitative differences between quantum mechanical models and related stochastic approximations. Calculations suggest that studying photon statistics as a function of photon frequency has the potential to reveal more about system dynamics than the usual broadband detection schemes.Comment: Submitted to the Journal of Physical Chemistr

A DISTRIBUTIONAL ANALYSIS OF THE COSTS OF FOODBORNE ILLNESS: WHO ULTIMATELY PAYS?

This paper traces the economic impact of the costs of foodborne illness on the U.S. economy using a Social Accounting Matrix (SAM) framework. Previous estimates of the costs of seven foodborne pathogens are disaggregated by type, and distributed across the population using data from the National Health Interview Survey. Initial income losses resulting from premature death cause a decrease in economic activity. Medical costs, in contrast, result in economic growth, though this growth does not outweigh the total costs of premature death. A SAM accounting of how the costs of illness are diffused through the economy provides useful information for policy makers.Cost of illness, Foodborne illness, Social Accounting Matrix, Food Consumption/Nutrition/Food Safety,

FOOD SAFETY INNOVATION IN THE UNITED STATES: EVIDENCE FROM THE MEAT INDUSTRY

Recent industry innovations improving the safety of the Nation's meat supply range from new pathogen tests, high-tech equipment, and supply chain management systems, to new surveillance networks. Despite these and other improvements, the market incentives that motivate private firms to invest in innovation seem to be fairly weak. Results from an ERS survey of U.S. meat and poultry slaughter and processing plants and two case studies of innovation in the U.S. beef industry reveal that the industry has developed a number of mechanisms to overcome that weakness and to stimulate investment in food safety innovation. Industry experience suggests that government policy can increase food safety innovation by reducing informational asymmetries and strengthening the ability of innovating firms to appropriate the benefits of their investments.Food safety, innovation, meat, asymmetric information, Beef Steam Pasteurization System, Bacterial Pathogen Sampling and Testing Program, Food Consumption/Nutrition/Food Safety, Livestock Production/Industries,

Final State Interactions Effects in Neutrino-Nucleus Interactions

Final State Interactions effects are discussed in the context of Monte Carlo simulations of neutrino-nucleus interactions. A role of Formation Time is explained and several models describing this effect are compared. Various observables which are sensitive to FSI effects are reviewed including pion-nucleus interaction and hadron yields in backward hemisphere. NuWro Monte Carlo neutrino event generator is described and its ability to understand neutral current $\pi^0$ production data in $\sim 1$ GeV neutrino flux experiments is demonstrated.Comment: 13 pages, 16 figure

Fast Primal-Dual Gradient Method for Strongly Convex Minimization Problems with Linear Constraints

In this paper we consider a class of optimization problems with a strongly convex objective function and the feasible set given by an intersection of a simple convex set with a set given by a number of linear equality and inequality constraints. A number of optimization problems in applications can be stated in this form, examples being the entropy-linear programming, the ridge regression, the elastic net, the regularized optimal transport, etc. We extend the Fast Gradient Method applied to the dual problem in order to make it primal-dual so that it allows not only to solve the dual problem, but also to construct nearly optimal and nearly feasible solution of the primal problem. We also prove a theorem about the convergence rate for the proposed algorithm in terms of the objective function and the linear constraints infeasibility.Comment: Submitted for DOOR 201