117 research outputs found

    WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting

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    Widely adopted motion forecasting datasets substitute the observed sensory inputs with higher-level abstractions such as 3D boxes and polylines. These sparse shapes are inferred through annotating the original scenes with perception systems' predictions. Such intermediate representations tie the quality of the motion forecasting models to the performance of computer vision models. Moreover, the human-designed explicit interfaces between perception and motion forecasting typically pass only a subset of the semantic information present in the original sensory input. To study the effect of these modular approaches, design new paradigms that mitigate these limitations, and accelerate the development of end-to-end motion forecasting models, we augment the Waymo Open Motion Dataset (WOMD) with large-scale, high-quality, diverse LiDAR data for the motion forecasting task. The new augmented dataset WOMD-LiDAR consists of over 100,000 scenes that each spans 20 seconds, consisting of well-synchronized and calibrated high quality LiDAR point clouds captured across a range of urban and suburban geographies (https://waymo.com/open/data/motion/). Compared to Waymo Open Dataset (WOD), WOMD-LiDAR dataset contains 100x more scenes. Furthermore, we integrate the LiDAR data into the motion forecasting model training and provide a strong baseline. Experiments show that the LiDAR data brings improvement in the motion forecasting task. We hope that WOMD-LiDAR will provide new opportunities for boosting end-to-end motion forecasting models.Comment: Dataset website: https://waymo.com/open/data/motion

    Children and older adults exhibit distinct sub-optimal cost-benefit functions when preparing to move their eyes and hands

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    "© 2015 Gonzalez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited"Numerous activities require an individual to respond quickly to the correct stimulus. The provision of advance information allows response priming but heightened responses can cause errors (responding too early or reacting to the wrong stimulus). Thus, a balance is required between the online cognitive mechanisms (inhibitory and anticipatory) used to prepare and execute a motor response at the appropriate time. We investigated the use of advance information in 71 participants across four different age groups: (i) children, (ii) young adults, (iii) middle-aged adults, and (iv) older adults. We implemented 'cued' and 'non-cued' conditions to assess age-related changes in saccadic and touch responses to targets in three movement conditions: (a) Eyes only; (b) Hands only; (c) Eyes and Hand. Children made less saccade errors compared to young adults, but they also exhibited longer response times in cued versus non-cued conditions. In contrast, older adults showed faster responses in cued conditions but exhibited more errors. The results indicate that young adults (18 -25 years) achieve an optimal balance between anticipation and execution. In contrast, children show benefits (few errors) and costs (slow responses) of good inhibition when preparing a motor response based on advance information; whilst older adults show the benefits and costs associated with a prospective response strategy (i.e., good anticipation)

    A high-resolution integrated map of copy number polymorphisms within and between breeds of the modern domesticated dog

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    <p>Abstract</p> <p>Background</p> <p>Structural variation contributes to the rich genetic and phenotypic diversity of the modern domestic dog, <it>Canis lupus familiaris</it>, although compared to other organisms, catalogs of canine copy number variants (CNVs) are poorly defined. To this end, we developed a customized high-density tiling array across the canine genome and used it to discover CNVs in nine genetically diverse dogs and a gray wolf.</p> <p>Results</p> <p>In total, we identified 403 CNVs that overlap 401 genes, which are enriched for defense/immunity, oxidoreductase, protease, receptor, signaling molecule and transporter genes. Furthermore, we performed detailed comparisons between CNVs located within versus outside of segmental duplications (SDs) and find that CNVs in SDs are enriched for gene content and complexity. Finally, we compiled all known dog CNV regions and genotyped them with a custom aCGH chip in 61 dogs from 12 diverse breeds. These data allowed us to perform the first population genetics analysis of canine structural variation and identify CNVs that potentially contribute to breed specific traits.</p> <p>Conclusions</p> <p>Our comprehensive analysis of canine CNVs will be an important resource in genetically dissecting canine phenotypic and behavioral variation.</p

    Lung-selective 25-hydroxycholesterol nanotherapeutics as a suppressor of COVID-19-associated cytokine storm

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    In response to the coronavirus disease-19 (COVID-19) pandemic caused by severe acute respiratory syn-drome coronavirus 2 (SARS-CoV-2), global efforts are focused on the development of new therapeutic in-terventions. For the treatment of COVID-19, selective lung-localizing strategies hold tremendous potential, as SARS-CoV-2 invades the lung via ACE2 receptors and causes severe pneumonia. Similarly, recent reports have shown the association of COVID-19 with decreased 25-hydroxycholesterol (25-HC) and increased cytokine levels. This mechanism, which involves the activation of inflammatory NF-kappa B-and SREBP2-mediated inflammasome signaling pathways, is believed to play a crucial role in COVID-19 pathogenesis, inducing acute respiratory distress syndrome (ARDS) and sepsis. To resolve those clinical conditions ob-served in severe SARS-CoV-2 patients, we report 25-HC and didodecyldimethylammonium bromide (DDAB) nanovesicles (25-HC@DDAB) as a COVID-19 drug candidate for the restoration of intracellular cholesterol level and suppression of cytokine storm. Our data demonstrate that 25-HC@DDAB can selectively accu-mulate the lung tissues and effectively downregulate NF-kappa B and SREBP2 signaling pathways in COVID-19 patient-derived PBMCs, reducing inflammatory cytokine levels. Altogether, our findings suggest that 25-HC@DDAB is a promising candidate for the treatment of symptoms associated with severe COVID-19 pa-tients, such as decreased cholesterol level and cytokine storm. (c) 2021 The Author(s). Published by Elsevier Ltd. CC_BY_NC_ND_4.

    Root-hair endophyte stacking in finger millet creates a physicochemical barrier to trap the fungal pathogen Fusarium graminearum

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    The ancient African crop, finger millet, has broad resistance to pathogens including the toxigenic fungus Fusarium graminearum. Here, we report the discovery of a novel plant defence mechanism resulting from an unusual symbiosis between finger millet and a root-inhabiting bacterial endophyte, M6 (Enterobacter sp.). Seed-coated M6 swarms towards root-invading Fusarium and is associated with the growth of root hairs, which then bend parallel to the root axis, subsequently forming biofilm-mediated microcolonies, resulting in a remarkable, multilayer root-hair endophyte stack (RHESt). The RHESt results in a physical barrier that prevents entry and/or traps F. graminearum, which is then killed. M6 thus creates its own specialized killing microhabitat. Tn5-mutagenesis shows that M6 killing requires c-di-GMP-dependent signalling, diverse fungicides and resistance to a Fusarium-derived antibiotic. Further molecular evidence suggests long-term host-endophyte-pathogen co-evolution. The end result of this remarkable symbiosis is reduced deoxynivalenol mycotoxin, potentially benefiting millions of subsistence farmers and livestock. Further results suggest that the anti-Fusarium activity of M6 may be transferable to maize and wheat. RHESt demonstrates the value of exploring ancient, orphan crop microbiomes

    Metagenome-assembled genomes provide new insight into the microbial diversity of two thermal pools in Kamchatka, Russia.

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    Culture-independent methods have contributed substantially to our understanding of global microbial diversity. Recently developed algorithms to construct whole genomes from environmental samples have further refined, corrected and revolutionized understanding of the tree of life. Here, we assembled draft metagenome-assembled genomes (MAGs) from environmental DNA extracted from two hot springs within an active volcanic ecosystem on the Kamchatka peninsula, Russia. This hydrothermal system has been intensively studied previously with regard to geochemistry, chemoautotrophy, microbial isolation, and microbial diversity. We assembled genomes of bacteria and archaea using DNA that had previously been characterized via 16S rRNA gene clone libraries. We recovered 36 MAGs, 29 of medium to high quality, and inferred their placement in a phylogenetic tree consisting of 3,240 publicly available microbial genomes. We highlight MAGs that were taxonomically assigned to groups previously underrepresented in available genome data. This includes several archaea (Korarchaeota, Bathyarchaeota and Aciduliprofundum) and one potentially new species within the bacterial genus Sulfurihydrogenibium. Putative functions in both pools were compared and are discussed in the context of their diverging geochemistry. This study adds comprehensive information about phylogenetic diversity and functional potential within two hot springs in the caldera of Kamchatka
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