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Abstract High-resolution observations have demonstrated the presence of strong time-mean near-surface wind convergence (NSWC) anchored across oceanic frontal zones, such as the western boundary currents. Initial analyses appeared to show a close association between this time-mean NSWC and time-mean properties of the underlying sea surface temperature (SST), such as the gradients and second derivatives (e.g., Laplacian of SST), acting through pressure-adjustment and vertical-mixing mechanisms. However, a series of recent papers have revealed the instantaneous NSWC to be dominated by atmospheric fronts and have suggested the importance of air–sea processes occurring instead on shorter, synoptic time scales. In this paper, using the ERA5 reanalysis dataset in the Gulf Stream region, we aim to reconcile these viewpoints by investigating the spatial and temporal dependence of NSWC and its relationship to SST. It is revealed that while atmospheric frontal processes govern the day-to-day variability of NSWC, the relatively weak but persistent pressure-adjustment and vertical-mixing mechanisms provide lower-frequency modulations in conditions both with and without atmospheric fronts. In addition to their temporal characteristics, each mechanism is shown through spectral analysis to dominate on specific spatial scales. In light of recent work that has tied remote atmospheric responses to NSWC anomalies in western boundary current regions, these results emphasize the importance of oceanic frontal zones for atmospheric variability on all spatiotemporal scales. 

Abstract The High Luminosity upgrade of the Large Hadron Collider (HL-LHC) will produce particle collisions with up to 200 simultaneous proton-proton interactions. These unprecedented conditions will create a combinatorial complexity for charged-particle track reconstruction that demands a computational cost that is expected to surpass the projected computing budget using conventional CPUs. Motivated by this and taking into account the prevalence of heterogeneous computing in cutting-edge High Performance Computing centers, we propose an efficient, fast and highly parallelizable bottom-up approach to track reconstruction for the HL-LHC, along with an associated implementation on GPUs, in the context of the Phase 2 CMS outer tracker. Our algorithm, called Segment Linking (or Line Segment Tracking), takes advantage of localized track stub creation, combining individual stubs to progressively form higher level objects that are subject to kinematical and geometrical requirements compatible with genuine physics tracks. The local nature of the algorithm makes it ideal for parallelization under the Single Instruction, Multiple Data paradigm, as hundreds of objects can be built simultaneously. The computing and physics performance of the algorithm has been tested on an NVIDIA Tesla V100 GPU, already yielding efficiency and timing measurements that are on par with the latest, multi-CPU versions of existing CMS tracking algorithms. 

Mid-infrared (MIR) spectrometers are invaluable tools for molecular fingerprinting and hyper-spectral imaging. Among the available spectroscopic approaches, GHz MIR dual-comb absorption spectrometers have the potential to simultaneously combine the high-speed, high spectral resolution, and broad optical bandwidth needed to accurately study complex, transient events in chemistry, combustion, and microscopy. However, such a spectrometer has not yet been demonstrated due to the lack of GHz MIR frequency combs with broad and full spectral coverage. Here, we introduce the first broadband MIR frequency comb laser platform at 1 GHz repetition rate that achieves spectral coverage from 3 to 13 {\mu}m. This frequency comb is based on a commercially available 1.56 {\mu}m mode-locked laser, robust all-fiber Er amplifiers and intra-pulse difference frequency generation (IP-DFG) of few-cycle pulses in \c{hi}(2) nonlinear crystals. When used in a dual comb spectroscopy (DCS) configuration, this source will simultaneously enable measurements with {\mu}s time resolution, 1 GHz (0.03 cm-1) spectral point spacing and a full bandwidth of >5 THz (>166 cm-1) anywhere within the MIR atmospheric windows. This represents a unique spectroscopic resource for characterizing fast and non-repetitive events that are currently inaccessible with other sources. 

Manipulation of deformable objects is a desired skill in making robots ubiquitous in manufacturing, service, healthcare, and security. Deformable objects are common in our daily lives, e.g., wires, clothes, bed sheets, etc., and are significantly more difficult to model than rigid objects. In this study, we investigate vision-based manipulation of linear flexible objects such as cables. We propose a geometric modeling method that is based on visual feedback to develop a general representation of the linear flexible object that is subject to gravity. The model characterizes the shape of the object by combining the curvatures on two projection planes. In this approach, we achieve tracking of the position and orientation (pose) of a cable-like object, the pose of its tip, and the pose of the selected grasp point on the object, which enables closed-loop manipulation of the object. We demonstrate the feasibility of our approach by completing the Plug Task used in the 2015 DARPA Robotics Challenge Finals, which involves unplugging a power cable from one socket and plugging it into another. Experiments show that we can successfully complete the task autonomously within 30 seconds.