Amazon.com

About: Amazon.com is a company organization based out in Seattle, Washington, United States. It is known for research contribution in the topics: Computer science & Service (business). The organization has 13363 authors who have published 17317 publications receiving 266589 citations.

A crucial role for TNF-α in mediating neutrophil influx induced by endogenously generated or exogenous chemokines, KC/CXCL1 and LIX/CXCL5

Abstract: Background and purpose: Chemokines orchestrate neutrophil recruitment to inflammatory foci. In the present study, we evaluated the participation of three chemokines, KC/CXCL1, MIP-2/CXCL2 and LIX/CXCL5, which are ligands for chemokine receptor 2 (CXCR2), in mediating neutrophil recruitment in immune inflammation induced by antigen in immunized mice. Experimental approach: Neutrophil recruitment was assessed in immunized mice challenged with methylated bovine serum albumin, KC/CXCL1, LIX/CXCL5 or tumour necrosis factor (TNF)-α. Cytokine and chemokine levels were determined in peritoneal exudates and in supernatants of macrophages and mast cells by elisa. CXCR2 and intercellular adhesion molecule 1 (ICAM-1) expression was determined using immunohistochemistry and confocal microscopy. Key results: Antigen challenge induced dose- and time-dependent neutrophil recruitment and production of KC/CXCL1, LIX/CXCL5 and TNF-α, but not MIP-2/CXCL2, in peritoneal exudates. Neutrophil recruitment was inhibited by treatment with reparixin (CXCR1/2 antagonist), anti-KC/CXCL1, anti-LIX/CXCL5 or anti-TNF-α antibodies and in tumour necrosis factor receptor 1-deficient mice. Intraperitoneal injection of KC/CXCL1 and LIX/CXCL5 induced dose- and time-dependent neutrophil recruitment and TNF-α production, which were inhibited by reparixin or anti-TNF-α treatment. Macrophages and mast cells expressed CXCR2 receptors. Increased macrophage numbers enhanced, while cromolyn sodium (mast cell stabilizer) diminished, LIX/CXCL5-induced neutrophil recruitment. Macrophages and mast cells from immunized mice produced TNF-α upon LIX/CXCL5 stimulation. Methylated bovine serum albumin induced expression of ICAM-1 on mesenteric vascular endothelium, which was inhibited by anti-TNF-α or anti-LIX/CXCL5. Conclusion and implications: Following antigen challenge, CXCR2 ligands are produced and act on macrophages and mast cells triggering the production of TNF-α, which synergistically contribute to neutrophil recruitment through induction of the expression of ICAM-1.

Arbitration between voice-enabled devices

Abstract: Architectures and techniques for selecting a voice-enabled device to handle audio input that is detected by multiple voice-enabled devices are described herein. In some instances, multiple voice-enabled devices may detect audio input from a user at substantially the same time, due to the voice-enabled devices being located within proximity to the user. The architectures and techniques may analyze a variety of audio signal metric values for the voice-enabled devices to designate a voice-enabled device to handle the audio input.

Nexus: a GPU cluster engine for accelerating DNN-based video analysis

Abstract: We address the problem of serving Deep Neural Networks (DNNs) efficiently from a cluster of GPUs. In order to realize the promise of very low-cost processing made by accelerators such as GPUs, it is essential to run them at sustained high utilization. Doing so requires cluster-scale resource management that performs detailed scheduling of GPUs, reasoning about groups of DNN invocations that need to be co-scheduled, and moving from the conventional whole-DNN execution model to executing fragments of DNNs. Nexus is a fully implemented system that includes these innovations. In large-scale case studies on 16 GPUs, when required to stay within latency constraints at least 99% of the time, Nexus can process requests at rates 1.8-12.7X higher than state of the art systems can. A long-running multi-application deployment stays within 84% of optimal utilization and, on a 100-GPU cluster, violates latency SLOs on 0.27% of requests.

Providing supplemental content with active media

Abstract: A user viewing a presentation of media content can obtain related supplemental content through the same or a different interface, on the same or a different device. A listener or other such component can attempt to detect information about the media, such as tags present in the media, the occurrence of songs or people in the media, and other such information. The detected information can be analyzed to attempt to identify one or more aspects of the media. The identified aspects can be used to attempt to locate supplemental content that is related to the media content and potentially of interest to the user. The interest of the user can be based upon historical user data, preferences, or other such information. The user can be notified of supplemental content on a primary display, and can access the supplemental content on a secondary display, on the same or a separate device.

Model-Agnostic Counterfactual Explanations for Consequential Decisions

Abstract: Predictive models are being increasingly used to support consequential decision making at the individual level in contexts such as pretrial bail and loan approval As a result, there is increasing social and legal pressure to provide explanations that help the affected individuals not only to understand why a prediction was output, but also how to act to obtain a desired outcome To this end, several works have proposed optimization-based methods to generate nearest counterfactual explanations However, these methods are often restricted to a particular subset of models (eg, decision trees or linear models) and differentiable distance functions In contrast, we build on standard theory and tools from formal verification and propose a novel algorithm that solves a sequence of satisfiability problems, where both the distance function (objective) and predictive model (constraints) are represented as logic formulae As shown by our experiments on real-world data, our algorithm is: i) model-agnostic ({non-}linear, {non-}differentiable, {non-}convex); ii) data-type-agnostic (heterogeneous features); iii) distance-agnostic ($\ell_0, \ell_1, \ell_\infty$, and combinations thereof); iv) able to generate plausible and diverse counterfactuals for any sample (ie, 100% coverage); and v) at provably optimal distances