An Observed Entanglement of Lagenorhynchus obliquidens in the High Seas Driftnet Area in the North Pacific

In August, 1991, an entanglement event was observed in the High Seas Driftnet area in the North Pacific. This description of an entanglement of Lagenorhynchus obliquidens is the first such documented report of dolphins entangling while bowriding. One of the entangled dolphins was rescued from the driftnet

Incoherence of Bose-Einstein condensates at supersonic speeds due to quantum noise

We calculate the effect of quantum noise in supersonic transport of Bose-Einstein condensates. When an obstacle obstructs the flow of atoms, quantum fluctuations cause atoms to be scattered incoherently into random directions. This suppresses the propagation of Cherenkov radiation, creating quantum turbulence and a crescent of incoherent atoms around the obstacle. We observe similar dynamics if the BEC is stirred by a laser beam: crescents of incoherent atoms are emitted from the laser's turning-points. Finally, we investigate supersonic flow through a disordered potential, and find that the quantum fluctuations generate an accumulation of incoherent atoms as the condensate enters the disorder.Comment: 6 pages, 5 figure

Morphine activates neuroinflammation in a manner parallel to endotoxin

Opioids create a neuroinflammatory response within the CNS, compromising opioid-induced analgesia and contributing to various unwanted actions. How this occurs is unknown but has been assumed to be via classic opioid receptors. Herein, we provide direct evidence that morphine creates neuroinflammation via the activation of an innate immune receptor and not via classic opioid receptors. We demonstrate that morphine binds to an accessory protein of Toll-like receptor 4 (TLR4), myeloid differentiation protein 2 (MD-2), thereby inducing TLR4 oligomerization and triggering proinflammation. Small-molecule inhibitors, RNA interference, and genetic knockout validate the TLR4/MD-2 complex as a feasible target for beneficially modifying morphine actions. Disrupting TLR4/MD-2 protein–protein association potentiated morphine analgesia in vivo and abolished morphine-induced proinflammation in vitro, the latter demonstrating that morphine-induced proinflammation only depends on TLR4, despite the presence of opioid receptors. These results provide an exciting, nonconventional avenue to improving the clinical efficacy of opioids.Xiaohui Wang, Lisa C. Loram, Khara Ramos, Armando J. de Jesus, Jacob Thomas, Kui Cheng, Anireddy Reddy, Andrew A. Somogyi, Mark R. Hutchinson, Linda R. Watkins and Hang Yi

High-throughput in-situ characterization and modelling of precipitation kinetics in compositionally graded alloys

The development of new engineering alloy chemistries is a time consuming and iterative process. A necessary step is characterization of the nano/microstructure to provide a link between the processing and properties of each alloy chemistry considered. One approach to accelerate the identification of optimal chemistries is to use samples containing a gradient in composition, ie. combinatorial samples, and to investigate many different chemistries at the same time. However, for engineering alloys, the final properties depend not only on chemistry but also on the path of microstructure development which necessitates characterization of microstructure evolution for each chemistry. In this contribution we demonstrate an approach that allows for the in-situ, nanoscale characterization of the precipitate structures in alloys, as a function of aging time, in combinatorial samples containing a composition gradient. The approach uses small angle x-ray scattering (SAXS) at a synchrotron beamline. The Cu-Co system is used for the proof-of-concept and the combinatorial samples prepared contain a gradient in Co from 0% to 2%. These samples are aged at temperatures between 450{\textdegree}C and 550{\textdegree}C and the precipitate structures (precipitate size, volume fraction and number density) all along the composition gradient are simultaneously monitored as a function of time. This large dataset is used to test the applicability and robustness of a conventional class model for precipitation that considers concurrent nucleation, growth and coarsening and the ability of the model to describe such a large dataset.Comment: Published in Acta Materiali

The electric charges and masses of rain drops

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Economic valuation of landscapes: combining landscape ecology and environmental economics methodologies.

Aim of the paper is to outline an integrated methodology for deriving economic values of the different landscape components. Our approach integrates landscape ecology principles and non-market valuation methodologies. Firstly, we identify landscape types and quantify their attributes with ‘metrics’ (i.e., objective components) and use discrete choice experiments to elicit the public’s preferences for these landscapes and their attributes (i.e., subjective components). As a case-study we use the Peninsula of Sorrento in Italy, which is a unique Mediterranean landscape, which is increasingly endangered by urban sprawl and decline of traditional farming. Results show the economic value of different types of landscapes and, importantly, provide convincing support for an interdisciplinary approach for landscape valuation

Task Planner for Simultaneous Fulfillment of Operational, Geometric and Uncertainty-Reduction Goals

Our ultimate goal in robot planning is to develop a planner which can create complete assembly plans given as input a high level description of assembly goals, geometric models of the components of the assembly, and a description of the capabilities of the work cell (including the robot and the sensory system). In this paper, we introduce SPAR, a planning system which reasons about high level operational goals, geometric goals and uncertainty-reduction goals in order to create assembly plans which consist of manipulations as well as sensory operations when appropriate. Operational planning is done using a nonlinear, constraint posting planner. Geometric planning is accomplished by constraining the execution of operations in the plan so that geometric goals are satisfied, or, if the geometric configuration of the world prevents this, by introducing new operations into the plan with the appropriate constraints. When the uncertainty in the world description exceeds that specified by the uncertainty-reduction goals, SPAR introduces either sensing operations or manipulations to reduce that uncertainty to acceptable levels. If SPAR cannot find a way to sufficiently reduce uncertainties, it does not abandon the plan. Instead, it augments the plan with sensing operations to be used to verify the execution of the action, and, when possible, posts possible error recovery plans, although at this point, the verification operations and recovery plans are predefined