504 research outputs found

    Content-gnostic Bitrate Ladder Prediction for Adaptive Video Streaming

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    Efficient Bitrate Ladder Construction for Content-Optimized Adaptive Video Streaming

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    One of the challenges faced by many video providers is the heterogeneity of network specifications, user requirements, and content compression performance. The universal solution of a fixed bitrate ladder is inadequate in ensuring a high quality of user experience without re-buffering or introducing annoying compression artifacts. However, a content-tailored solution, based on extensively encoding across all resolutions and over a wide quality range is highly expensive in terms of computational, financial, and energy costs. Inspired by this, we propose an approach that exploits machine learning to predict a content-optimized bitrate ladder. The method extracts spatio-temporal features from the uncompressed content, trains machine-learning models to predict the Pareto front parameters, and, based on that, builds the ladder within a defined bitrate range. The method has the benefit of significantly reducing the number of encodes required per sequence. The presented results, based on 100 HEVC-encoded sequences, demonstrate a reduction in the number of encodes required when compared to an exhaustive search and an interpolation-based method, by 89.06% and 61.46%, respectively, at the cost of an average Bj{\o}ntegaard Delta Rate difference of 1.78% compared to the exhaustive approach. Finally, a hybrid method is introduced that selects either the proposed or the interpolation-based method depending on the sequence features. This results in an overall 83.83% reduction of required encodings at the cost of an average Bj{\o}ntegaard Delta Rate difference of 1.26%

    VMAF-based Bitrate Ladder Estimation for Adaptive Streaming

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    In HTTP Adaptive Streaming, video content is conventionally encoded by adapting its spatial resolution and quantization level to best match the prevailing network state and display characteristics. It is well known that the traditional solution, of using a fixed bitrate ladder, does not result in the highest quality of experience for the user. Hence, in this paper, we consider a content-driven approach for estimating the bitrate ladder, based on spatio-temporal features extracted from the uncompressed content. The method implements a content-driven interpolation. It uses the extracted features to train a machine learning model to infer the curvature points of the Rate-VMAF curves in order to guide a set of initial encodings. We employ the VMAF quality metric as a means of perceptually conditioning the estimation. When compared to exhaustive encoding that produces the reference ladder, the estimated ladder is composed by 74.3% of identical Rate-VMAF points with the reference ladder. The proposed method offers a significant reduction of the number of encodes required, 77.4%, at a small average Bj{\o}ntegaard Delta Rate cost, 1.12%

    Chiral de Rham complex on Riemannian manifolds and special holonomy

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    Interpreting the chiral de Rham complex (CDR) as a formal Hamiltonian quantization of the supersymmetric non-linear sigma model, we suggest a setup for the study of CDR on manifolds with special holonomy. We show how to systematically construct global sections of CDR from differential forms, and investigate the algebra of the sections corresponding to the covariantly constant forms associated with the special holonomy. As a concrete example, we construct two commuting copies of the Odake algebra (an extension of the N=2 superconformal algebra) on the space of global sections of CDR of a Calabi-Yau threefold and conjecture similar results for G_2 manifolds. We also discuss quasi-classical limits of these algebras.Comment: 49 pages, title changed, major rewrite with no changes in the main theorems, published versio

    Amplified melt and flow of the Greenland ice sheet driven by late-summer cyclonic rainfall

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    Intense rainfall events significantly affect Alpine and Alaskan glaciers through enhanced melting, ice-flow acceleration and subglacial sediment erosion, yet their impact on the Greenland ice sheet has not been assessed. Here we present measurements of ice velocity, subglacial water pressure and meteorological variables from the western margin of the Greenland ice sheet during a week of warm, wet cyclonic weather in late August and early September 2011. We find that extreme surface runoff from melt and rainfall led to a widespread acceleration in ice flow that extended 140 km into the ice-sheet interior. We suggest that the late-season timing was critical in promoting rapid runoff across an extensive bare ice surface that overwhelmed a subglacial hydrological system in transition to a less-efficient winter mode. Reanalysis data reveal that similar cyclonic weather conditions prevailed across southern and western Greenland during this time, and we observe a corresponding ice-flow response at all land- and marine-terminating glaciers in these regions for which data are available. Given that the advection of warm, moist air masses and rainfall over Greenland is expected to become more frequent in the coming decades, our findings portend a previously unforeseen vulnerability of the Greenland ice sheet to climate change

    Cabbage and fermented vegetables : From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19

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    Large differences in COVID-19 death rates exist between countries and between regions of the same country. Some very low death rate countries such as Eastern Asia, Central Europe, or the Balkans have a common feature of eating large quantities of fermented foods. Although biases exist when examining ecological studies, fermented vegetables or cabbage have been associated with low death rates in European countries. SARS-CoV-2 binds to its receptor, the angiotensin-converting enzyme 2 (ACE2). As a result of SARS-CoV-2 binding, ACE2 downregulation enhances the angiotensin II receptor type 1 (AT(1)R) axis associated with oxidative stress. This leads to insulin resistance as well as lung and endothelial damage, two severe outcomes of COVID-19. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is the most potent antioxidant in humans and can block in particular the AT(1)R axis. Cabbage contains precursors of sulforaphane, the most active natural activator of Nrf2. Fermented vegetables contain many lactobacilli, which are also potent Nrf2 activators. Three examples are: kimchi in Korea, westernized foods, and the slum paradox. It is proposed that fermented cabbage is a proof-of-concept of dietary manipulations that may enhance Nrf2-associated antioxidant effects, helpful in mitigating COVID-19 severity.Peer reviewe

    Nrf2-interacting nutrients and COVID-19 : time for research to develop adaptation strategies

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    There are large between- and within-country variations in COVID-19 death rates. Some very low death rate settings such as Eastern Asia, Central Europe, the Balkans and Africa have a common feature of eating large quantities of fermented foods whose intake is associated with the activation of the Nrf2 (Nuclear factor (erythroid-derived 2)-like 2) anti-oxidant transcription factor. There are many Nrf2-interacting nutrients (berberine, curcumin, epigallocatechin gallate, genistein, quercetin, resveratrol, sulforaphane) that all act similarly to reduce insulin resistance, endothelial damage, lung injury and cytokine storm. They also act on the same mechanisms (mTOR: Mammalian target of rapamycin, PPAR gamma:Peroxisome proliferator-activated receptor, NF kappa B: Nuclear factor kappa B, ERK: Extracellular signal-regulated kinases and eIF2 alpha:Elongation initiation factor 2 alpha). They may as a result be important in mitigating the severity of COVID-19, acting through the endoplasmic reticulum stress or ACE-Angiotensin-II-AT(1)R axis (AT(1)R) pathway. Many Nrf2-interacting nutrients are also interacting with TRPA1 and/or TRPV1. Interestingly, geographical areas with very low COVID-19 mortality are those with the lowest prevalence of obesity (Sub-Saharan Africa and Asia). It is tempting to propose that Nrf2-interacting foods and nutrients can re-balance insulin resistance and have a significant effect on COVID-19 severity. It is therefore possible that the intake of these foods may restore an optimal natural balance for the Nrf2 pathway and may be of interest in the mitigation of COVID-19 severity
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