Lagrangian dynamical geography of the Gulf of Mexico

We construct a Markov-chain representation of the surface-ocean Lagrangian dynamics in a region occupied by the Gulf of Mexico (GoM) and adjacent portions of the Caribbean Sea and North Atlantic using satellite-tracked drifter trajectory data, the largest collection so far considered. From the analysis of the eigenvectors of the transition matrix associated with the chain, we identify almost-invariant attracting sets and their basins of attraction. With this information we decompose the GoM's geography into weakly dynamically interacting provinces, which constrain the connectivity between distant locations within the GoM. Offshore oil exploration, oil spill contingency planning, and fish larval connectivity assessment are among the many activities that can benefit from the dynamical information carried in the geography constructed here.Comment: Submitted to Scientific Report

Monte Carlo Study of the Square-Lattice Annealed Ising Model on Percolating Clusters

Simulations of an Ising q-state Pods model which is equivalent to the Ising model on annealed percolation clusters are used to determine the phase diagram of the model in two dimensions. Three topologically different phase diagrams are obtained: (i) for q=2, there are two critical Ising lines meeting at T=0 at the four-state Potts critical point; (ii) for 24, the Ising:critical line intersects a Line of first-order transitions at a critical end point

Monte Carlo Study of the Square-Lattice Annealed Ising Model on Percolating Clusters

Simulations of an Ising q-state Pods model which is equivalent to the Ising model on annealed percolation clusters are used to determine the phase diagram of the model in two dimensions. Three topologically different phase diagrams are obtained: (i) for q=2, there are two critical Ising lines meeting at T=0 at the four-state Potts critical point; (ii) for 24, the Ising:critical line intersects a Line of first-order transitions at a critical end point

Seasonality, Cost Shocks, and the Production Smoothing Model of Inventories

In recent years there has been a resurgence of interest in the empirical behavior of inventories. A great deal of this research examines some variant of the production smoothing model of finished goods inventories. The overall assessment of this model that exists in the literature is quite negative: there is little evidence that manufacturers hold inventories of finished goods in order to smooth production patterns. This paper examines whether this negative assessment of the model is due to one or both of two features: costs shocks and seasonal fluctuations. The reason for considering costs shocks is that if firms are buffetted more by cost shocks than demand shocks, production should optimally be more variable than sales. The reasons for considering seasonal fluctuations are that seasonal fluctuations account for a major portion of the variance in production and sales, that seasonal fluctuations are precisely the kinds of fluctuations that producers should most easily smooth and that seasonally adjusted data is likely to produce spurious rejections of the production smoothing model even when it is correct.Center for Research on Economic and Social Theory, Department of Economics, University of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/100882/1/ECON334.pd

Production, Sales, and the Change in Inventories: An Identity that Doesn't Add Up

In this paper we examine two different measures of monthly production that have been used by economists. The first measure, which we refer to as IP, is the index of industrial production constructed by the Board of Governors of the Federal Reserve. This measure is used extensively in empirical work on the business cycle, as well as by policymakers and others to assess the current state of the economy. The second measure, which we refer to as Y4, is constructed from the accounting identity that output equals sales plus the change in inventories. Sales and inventory data are reported by the Department of Commerce. This measure of output is frequently used to estimate models of inventory accumulation. theoretically, these two series measuare the same underlying economic variable--the production of goods by firms during the month. We show here that the time series properties of these two series are radically different.Center for Research on Economic and Social Theory, Department of Economics, University of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/100881/1/ECON333.pd

Transition paths of marine debris and the stability of the garbage patches

We used transition path theory (TPT) to infer "reactive" pathways of floating marine debris trajectories. The TPT analysis was applied on a pollution-aware time-homogeneous Markov chain model constructed from trajectories produced by satellite-tracked undrogued buoys from the NOAA Global Drifter Program. The latter involved coping with the openness of the system in physical space, which further required an adaptation of the standard TPT setting. Directly connecting pollution sources along coastlines with garbage patches of varied strengths, the unveiled reactive pollution routes represent alternative targets for ocean cleanup efforts. Among our specific findings we highlight: constraining a highly probable pollution source for the Great Pacific Garbage Patch; characterizing the weakness of the Indian Ocean gyre as a trap for plastic waste; and unveiling a tendency of the subtropical gyres to export garbage toward the coastlines rather than to other gyres in the event of anomalously intense winds.Comment: Submitted to Chao

Markov-chain-inspired search for MH370

Markov-chain models are constructed for the probabilistic description of the drift of marine debris from Malaysian Airlines flight MH370. En route from Kuala Lumpur to Beijing, the MH370 mysteriously disappeared in the southeastern Indian Ocean on 8 March 2014, somewhere along the arc of the 7th ping ring around the Inmarsat-3F1 satellite position when the airplane lost contact. The models are obtained by discretizing the motion of undrogued satellite-tracked surface drifting buoys from the global historical data bank. A spectral analysis, Bayesian estimation, and the computation of most probable paths between the Inmarsat arc and confirmed airplane debris beaching sites are shown to constrain the crash site, near 25$^{\circ}$S on the Inmarsat arc.Comment: Submitted to Chao

Building a Maxey--Riley framework for surface ocean inertial particle dynamics

A framework for the study of surface ocean inertial particle motion is built from the Maxey--Riley set. A new set is obtained by vertically averaging each term of the original set, adapted to account for Earth's rotation effects, across the extent of a sufficiently small spherical particle that floats at an assumed unperturbed air--sea interface with unsteady nonuniform winds and ocean currents above and below, respectively. The inertial particle velocity is shown to exponentially decay in time to a velocity that lies close to an average of seawater and air velocities, weighted by a function of the seawater-to-particle density ratio. Such a weighted average velocity turns out to fortuitously be of the type commonly discussed in the search-and-rescue literature, which alone cannot explain the observed role of anticyclonic mesoscale eddies as traps for marine debris or the formation of great garbage patches in the subtropical gyres, phenomena dominated by finite-size effects. A heuristic extension of the theory is proposed to describe the motion of nonspherical particles by means of a simple shape factor correction, and recommendations are made for incorporating wave-induced Stokes drift, and allowing for inhomogeneities of the carrying fluid density. The new Maxey--Riley set outperforms an ocean adaptation that ignored wind drag effects and the first reported adaption that attempted to incorporate them.Comment: To appear in Phys. Fluid

Chronic oligodendrocyte injury in central nervous system pathologies

Myelin, the membrane surrounding neuronal axons, is critical for central nervous system (CNS) function. Injury to myelin-forming oligodendrocytes (OL) in chronic neurological diseases (e.g. multiple sclerosis) ranges from sublethal to lethal, leading to OL dysfunction and myelin pathology, and consequent deleterious impacts on axonal health that drive clinical impairments. This is regulated by intrinsic factors such as heterogeneity and age, and extrinsic cellular and molecular interactions. Here, we discuss the responses of OLs to injury, and perspectives for therapeutic targeting. We put forward that targeting mature OL health in neurological disease is a promising therapeutic strategy to support CNS function