The Leeway of Shipping Containers at Different Immersion Levels

The leeway of 20-foot containers in typical distress conditions is established through field experiments in a Norwegian fjord and in open-ocean conditions off the coast of France with wind speed ranging from calm to 14 m/s. The experimental setup is described in detail and certain recommendations given for experiments on objects of this size. The results are compared with the leeway of a scaled-down container before the full set of measured leeway characteristics are compared with a semi-analytical model of immersed containers. Our results are broadly consistent with the semi-analytical model, but the model is found to be sensitive to choice of drag coefficient and makes no estimate of the cross-wind leeway of containers. We extend the results from the semi-analytical immersion model by extrapolating the observed leeway divergence and estimates of the experimental uncertainty to various realistic immersion levels. The sensitivity of these leeway estimates at different immersion levels are tested using a stochastic trajectory model. Search areas are found to be sensitive to the exact immersion levels, the choice of drag coefficient and somewhat less sensitive to the inclusion of leeway divergence. We further compare the search areas thus found with a range of trajectories estimated using the semi-analytical model with only perturbations to the immersion level. We find that the search areas calculated without estimates of crosswind leeway and its uncertainty will grossly underestimate the rate of expansion of the search areas. We recommend that stochastic trajectory models of container drift should account for these uncertainties by generating search areas for different immersion levels and with the uncertainties in crosswind and downwind leeway reported from our field experiments.Comment: 25 pages, 11 figures and 5 tables; Ocean Dynamics, Special Issue on Advances in Search and Rescue at Sea (2012

BAKTRAK: Backtracking drifting objects using an iterative algorithm with a forward trajectory model

The task of determining the origin of a drifting object after it has been located is highly complex due to the uncertainties in drift properties and environmental forcing (wind, waves and surface currents). Usually the origin is inferred by running a trajectory model (stochastic or deterministic) in reverse. However, this approach has some severe drawbacks, most notably the fact that many drifting objects go through nonlinear state changes underway (e.g., evaporating oil or a capsizing lifeboat). This makes it difficult to naively construct a reverse-time trajectory model which realistically predicts the earliest possible time the object may have started drifting. We propose instead a different approach where the original (forward) trajectory model is kept unaltered while an iterative seeding and selection process allows us to retain only those particles that end up within a certain time-space radius of the observation. An iterative refinement process named BAKTRAK is employed where those trajectories that do not make it to the goal are rejected and new trajectories are spawned from successful trajectories. This allows the model to be run in the forward direction to determine the point of origin of a drifting object. The method is demonstrated using the Leeway stochastic trajectory model for drifting objects due to its relative simplicity and the practical importance of being able to identify the origin of drifting objects. However, the methodology is general and even more applicable to oil drift trajectories, drifting ships and hazardous material that exhibit non-linear state changes such as evaporation, chemical weathering, capsizing or swamping. The backtracking method is tested against the drift trajectory of a life raft and is shown to predict closely the initial release position of the raft and its subsequent trajectory.Comment: 28 pages, 8 figures, 2 table

An Oligopeptide Transporter of Mycobacterium tuberculosis Regulates Cytokine Release and Apoptosis of Infected Macrophages

Background: The Mycobacterium tuberculosis genome encodes two peptide transporters encoded by Rv3665c-Rv3662c and Rv1280c-Rv1283c. Both belong to the family of ABC transporters containing two nucleotide-binding subunits, two integral membrane proteins and one substrate-binding polypeptide. However, little is known about their functions in M. tuberculosis. Here we report functional characterization of the Rv1280c-Rv1283c-encoded transporter and its substrate-binding polypeptide OppA(MTB). Methodology/Principal Findings: OppA(MTB) was capable of binding the tripeptide glutathione and the nonapeptide bradykinin, indicative of a somewhat broad substrate specificity. Amino acid residues G109, N110, N230, D494 and F496, situated at the interface between domains I and III of OppA, were required for optimal peptide binding. Complementaton of an oppA knockout mutant of M. smegmatis with OppA(MTB) confirmed the role of this transporter in importing glutathione and the importance of the aforesaid amino acid residues in peptide transport. Interestingly, this transporter regulated the ability of M. tuberculosis to lower glutathione levels in infected compared to uninfected macrophages. This ability was partly offset by inactivation of oppD. Concomitantly, inactivation of oppD was associated with lowered levels of methyl glyoxal in infected macrophages and reduced apoptosis-inducing ability of the mutant. The ability to induce the production of the cytokines IL-1 beta, IL-6 and TNF-alpha was also compromised after inactivation of oppD. Conclusions: Taken together, these studies uncover the novel observations that this peptide transporter modulates the innate immune response of macrophages infected with M. tuberculosis

Factors Regulating Early Life History Dispersal of Atlantic Cod (Gadus morhua) from Coastal Newfoundland

To understand coastal dispersal dynamics of Atlantic cod (Gadus morhua), we examined spatiotemporal egg and larval abundance patterns in coastal Newfoundland. In recent decades, Smith Sound, Trinity Bay has supported the largest known overwintering spawning aggregation of Atlantic cod in the region. We estimated spawning and dispersal characteristics for the Smith Sound-Trinity Bay system by fitting ichthyoplankton abundance data to environmentally-driven, simplified box models. Results show protracted spawning, with sharply increased egg production in early July, and limited dispersal from the Sound. The model for the entire spawning season indicates egg export from Smith Sound is 13%•day−1 with a net mortality of 27%•day–1. Eggs and larvae are consistently found in western Trinity Bay with little advection from the system. These patterns mirror particle tracking models that suggest residence times of 10–20 days, and circulation models indicating local gyres in Trinity Bay that act in concert with upwelling dynamics to retain eggs and larvae. Our results are among the first quantitative dispersal estimates from Smith Sound, linking this spawning stock to the adjacent coastal waters. These results illustrate the biophysical interplay regulating dispersal and connectivity originating from inshore spawning of coastal northwest Atlantic