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  1. Many research and monitoring networks in recent decades have provided publicly available data documenting environmental and ecological change, but little is known about the status of efforts to synthesize this information across networks. We convened a working group to assess ongoing and potential cross‐network synthesis research and outline opportunities and challenges for the future, focusing on the US‐based research network (the US Long‐Term Ecological Research network, LTER) and monitoring network (the National Ecological Observatory Network, NEON). LTER‐NEON cross‐network research synergies arise from the potentials for LTER measurements, experiments, models, and observational studies to provide context and mechanisms for interpreting NEONmore »data, and for NEON measurements to provide standardization and broad scale coverage that complement LTER studies. Initial cross‐network syntheses at co‐located sites in the LTER and NEON networks are addressing six broad topics: how long‐term vegetation change influences C fluxes; how detailed remotely‐sensed data reveal vegetation structure and function; aquatic‐terrestrial connections of nutrient cycling; ecosystem response to soil biogeochemistry and microbial processes; population and species responses to environmental change; and disturbance, stability and resilience. This initial work offers exciting potentials for expanded cross‐network syntheses involving multiple long‐term ecosystem processes at regional or continental scales. These potential syntheses could provide a pathway for the broader scientific community, beyond LTER and NEON, to engage in cross‐network science. These examples also apply to many other research and monitoring networks in the US and globally, and can guide scientists and research administrators in promoting broad‐scale research that supports resource management and environmental policy.« less
  2. Abstract Motivation

    Spectral unmixing methods attempt to determine the concentrations of different fluorophores present at each pixel location in an image by analyzing a set of measured emission spectra. Unmixing algorithms have shown great promise for applications where samples contain many fluorescent labels; however, existing methods perform poorly when confronted with autofluorescence-contaminated images.

    Results

    We propose an unmixing algorithm designed to separate fluorophores with overlapping emission spectra from contamination by autofluorescence and background fluorescence. First, we formally define a generalization of the linear mixing model, called the affine mixture model (AMM), that specifically accounts for background fluorescence. Second, we use the AMMmore »to derive an affine nonnegative matrix factorization method for estimating fluorophore endmember spectra from reference images. Lastly, we propose a semi-blind sparse affine spectral unmixing (SSASU) algorithm that uses knowledge of the estimated endmembers to learn the autofluorescence and background fluorescence spectra on a per-image basis. When unmixing real-world spectral images contaminated by autofluorescence, SSASU greatly improved proportion indeterminacy as compared to existing methods for a given relative reconstruction error.

    Availability and implementation

    The source code used for this paper was written in Julia and is available with the test data at https://github.com/brossetti/ssasu.

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  3. Free, publicly-accessible full text available November 1, 2022
  4. Free, publicly-accessible full text available July 7, 2023
  5. Free, publicly-accessible full text available September 1, 2022
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  7. Free, publicly-accessible full text available June 1, 2023
  8. Abstract The multiplicity dependence of jet production in pp collisions at the centre-of-mass energy of $$\sqrt{s} = 13\ {\mathrm {TeV}}$$ s = 13 TeV is studied for the first time. Jets are reconstructed from charged particles using the anti- $$k_\mathrm {T}$$ k T algorithm with resolution parameters R varying from 0.2 to 0.7. The jets are measured in the pseudorapidity range $$|\eta _{\mathrm{jet}}|< 0.9-R$$ | η jet | < 0.9 - R and in the transverse momentum range $$5more »by the ALICE forward detector V0. The $$p_{\mathrm T}$$ p T differential cross section of charged-particle jets are compared to leading order (LO) and next-to-leading order (NLO) perturbative quantum chromodynamics (pQCD) calculations. It is found that the data are better described by the NLO calculation, although the NLO prediction overestimates the jet cross section below $$20\ {\mathrm {GeV}}/c$$ 20 GeV / c . The cross section ratios for different R are also measured and compared to model calculations. These measurements provide insights into the angular dependence of jet fragmentation. The jet yield increases with increasing self-normalised charged-particle multiplicity. This increase shows only a weak dependence on jet transverse momentum and resolution parameter at the highest multiplicity. While such behaviour is qualitatively described by the present version of PYTHIA, quantitative description may require implementing new mechanisms for multi-particle production in hadronic collisions.« less
    Free, publicly-accessible full text available June 1, 2023