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Rainfall and river levels in the Amazon are associated with significant precipitation anomalies of opposite sign in temperate North and South America, which is the dominant mode of precipitation variability in the Americas that often arises during extremes of the El Niño/Southern Oscillation (ENSO). This co-variability of precipitation extremes across the Americas is imprinted on tree growth and is detected when new tree-ring chronologies from the eastern equatorial Amazon are compared with hundreds of moisture-sensitive tree-ring chronologies in mid-latitude North and South America from 1759 to 2016. Pan-American co-variability exists even though the seasonality of precipitation and tree growthmore »only partially overlaps between the Amazon and mid-latitudes because ENSO forcing of climate can persist for multiple seasons and can orchestrate a coherent response, even where the growing seasons are not fully synchronized. The tree-ring data indicate that the El Niño influence on inter-hemispheric precipitation and tree growth extremes has been strong and stable over the past 258-years, but the La Niña influence has been subject to large multi-decadal changes. These changes have implications for the dynamics and forecasting of hydroclimatic variability over the Americas and are supported by analyses of the available instrumental data and selected climate model simulations.

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Rectilinear forms of snake-like robotic locomotion are anticipated to be an advantage in obstacle-strewn scenarios characterizing urban disaster zones, subterranean collapses, and other natural environments. The elongated, laterally narrow footprint associated with these motion strategies is well suited to traversal of confined spaces and narrow pathways. Navigation and path planning in the absence of global sensing, however, remains a pivotal challenge to be addressed prior to practical deployment of these robotic mechanisms. Several challenges related to visual processing and localization need to be resolved to to enable navigation. As a first pass in this direction, we equip a wireless, monocularmore »color camera to the head of a robotic snake. Visiual odometry and mapping from ORB-SLAM permits self-localization in planar, obstacle strewn environments. Ground plane traversability segmentation in conjunction with perception-space collision detection permits path planning for navigation. A previously presented dynamical reduction of rectilinear snake locomotion to a non-holonomic kinematic vehicle informs both SLAM and planning. The simplified motion model is then applied to track planned trajectories through an obstacle configuration. This navigational framework enables a snake-like robotic platform to autonomously navigate and traverse unknown scenarios with only monocular vision.« less

We present an overview of GProM, a generic provenance middleware for relational databases. The sys- tem supports diverse provenance and annotation management tasks through query instrumentation, i.e., compiling a declarative frontend language with provenance-specific features into the query language of a backend database system. In addition to introducing GProM, we also discuss research contributions related to GProM including the first provenance model and capture mechanism for transaction prove- nance, a unified framework for answering why- and why-not provenance questions, and provenance- aware query optimization. Furthermore, by means of the example of post-mortem debugging of transac- tions, we demonstrate how novelmore »applications of provenance are made possible by GProM.« less