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  • Negotiating risks to natural capital in net-zero transitions

    Negotiating risks to natural capital in net-zero transitions

  • Rogelj, J. et al. Paris Agreement climate proposals need a boost to keep warming well below 2 °C. Nature 534, 631–639 (2016).

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  • Richardson, K. et al. Earth beyond six…

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  • Structural determinants for pH-dependent activation of a plant metacaspase

    Structural determinants for pH-dependent activation of a plant metacaspase

    pH-dependent AtMC9 activation for autolysis and structural changes

    The AtMC9 zymogen is activated by protons, which lead to autolytic self-cleavage after Arg183 in the linker domain that relieves the autoinhibitory function of the linker, similar…

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  • Collaborative energy and land use planning

    Collaborative energy and land use planning

    The author is also affiliated with Oak Ridge National Laboratory, which did not provide specific support for this paper. The views and opinions expressed in this paper are those of the author alone and do not necessarily represent those of the…

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  • A visual–omics foundation model to bridge histopathology with spatial transcriptomics

    A visual–omics foundation model to bridge histopathology with spatial transcriptomics

    Training dataset curation

    We curated a large dataset of histopathology image–transcriptomics pairs using publicly available 10x Visium datasets (Supplementary Table 1). H&E images were cropped to match ST spot sizes, and text sentences were…

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  • How the natural world is inspiring the robot eyes of the future

    How the natural world is inspiring the robot eyes of the future

    The miniature curved compound eye, called CurvACE, was inspired by the eyes of insects.Credit: Alain Herzog, EPFL

    Electrical engineer Young Min Song remembers when his colleague at the Gwangju…

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  • scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links

    scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links

    Method overview

    scMODAL is a deep generative framework that learns integrated cell representations from single-cell multi-omics features. The input to scMODAL comprises cell-by-feature data matrices. For simplicity, we consider the scenario…

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  • ACE2: accurately learning subseasonal to decadal atmospheric variability and forced responses

    ACE2: accurately learning subseasonal to decadal atmospheric variability and forced responses

    Training period evaluation

    We present ACE2 model evaluations initialized in January 1940 and run forward for 81 years through December 2020, spanning nearly the full period of ERA5 and SHiELD data. Although this period overlaps with the training…

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