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1. Stage-discharge relationship in tidal channels: Tidal stage-discharge relationship

   https://doi.org/10.1002/lom3.10168  

   Kearney, William S.; Mariotti, Giulio; Deegan, Linda A.; Fagherazzi, Sergio (April 2017, Limnology and Oceanography: Methods)
2. Nitrogen increases early‐stage and slows late‐stage decomposition across diverse grasslands

   https://doi.org/10.1111/1365-2745.13878  

   Gill, Allison L.; Adler, Peter B.; Borer, Elizabeth T.; Buyarski, Christopher R.; Cleland, Elsa E.; D'Antonio, Carla M.; Davies, Kendi F.; Gruner, Daniel S.; Harpole, W. Stanley; Hofmockel, Kirsten S.; et al (June 2022, Journal of Ecology)
3. Growth-stage-related shifts in diatom endometabolome composition set the stage for bacterial heterotrophy

   https://doi.org/10.1038/s43705-022-00116-5  

   Olofsson, Malin; Ferrer-González, Frank X.; Uchimiya, Mario; Schreier, Jeremy E.; Holderman, Nicole R.; Smith, Christa B.; Edison, Arthur S.; Moran, Mary Ann (March 2022, ISME Communications)

   Abstract Phytoplankton-derived metabolites fuel a large fraction of heterotrophic bacterial production in the global ocean, yet methodological challenges have limited our understanding of the organic molecules transferred between these microbial groups. In an experimental bloom study consisting of three heterotrophic marine bacteria growing together with the diatom Thalassiosira pseudonana, we concurrently measured diatom endometabolites (i.e., potential exometabolite supply) by nuclear magnetic resonance (NMR) spectroscopy and bacterial gene expression (i.e., potential exometabolite uptake) by metatranscriptomic sequencing. Twenty-two diatom endometabolites were annotated, with nine increasing in internal concentration in the late stage of the bloom, eight decreasing, and five showing no variation through the bloom progression. Some metabolite changes could be linked to shifts in diatom gene expression, as well as to shifts in bacterial community composition and their expression of substrate uptake and catabolism genes. Yet an overall low match indicated that endometabolome concentration was not a good predictor of exometabolite availability, and that complex physiological and ecological interactions underlie metabolite exchange. Six diatom endometabolites accumulated to higher concentrations in the bacterial co-cultures compared to axenic cultures, suggesting a bacterial influence on rates of synthesis or release of glutamate, arginine, leucine, 2,3-dihydroxypropane-1-sulfonate, glucose, and glycerol-3-phosphate. Better understanding of phytoplankton metabolite production, release, and transfer to assembled bacterial communities is key to untangling this nearly invisible yet pivotal step in ocean carbon cycling. 

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4. Electrolyte Role in SEI Evolution at Si in the Pre-lithiation Stage vs the Post-lithiation Stage

   https://doi.org/10.1149/1945-7111/acb617  

   Cora, Saida; Key, Baris; Vaughey, John; Sa, Niya (February 2023, Journal of The Electrochemical Society)

   The formation and evolution of the dynamic solid electrolyte interphase (SEI) at the Si anode/electrolyte interface are yet to be completely understood to solve irreversible capacity loss and increase battery cycle life. Herein, the evolution of SEI and its dynamic properties at the Si anode/electrolyte interface are investigated in two electrolyte systems, a 1.2 M LiPF 6 in EC: EMC 3:7 (wt%) electrolyte (referred to as Gen2) and a 1.2 M LiTFSI in EC: EMC 3:7 (wt%) electrolyte (referred to as LiTFSI). Two lithiation stages are studied: the pre-lithiation ( pre-Li ) SEI stage and the post-lithiation ( post-Li ) stage. Findings reveal at the pre-Li , SEI formation starts at an early potential and contributes to the greater mass gain in the Si/Gen2, and it is dominated by the formation of a non-uniform F- and P-rich layer in Si/Gen2, in contrast to a homogeneous F- and C-containing layer at the Si/LiTFSI interphase. The initially formed SEI in LiTFSI further benefits the charge transfer kinetics. At the post-Li stage, a more substantial SEI evolution is observed at Si/LiTFSI. This study offers a foundational understanding of the SEI dynamic evolution with electrolyte dependence. Findings from this report offer important insights into solving the complex SEI stability issues on Si. 

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5. Two-stage linear decision rules for multi-stage stochastic programming

   https://doi.org/10.1007/s10107-018-1339-4  

   Bodur, Merve; Luedtke, James R. (October 2018, Mathematical Programming)

   Multi-stage stochastic linear programs (MSLPs) are notoriously hard to solve in general. Linear decision rules (LDRs) yield an approximation of an MSLP by restricting the decisions at each stage to be an affine function of the observed uncertain parameters. Finding an optimal LDR is a static optimization problem that provides an upper bound on the optimal value of the MSLP, and, under certain assumptions, can be formulated as an explicit linear program. Similarly, as proposed by Kuhn et al. (Math Program 130(1):177–209, 2011) a lower bound for an MSLP can be obtained by restricting decisions in the dual of the MSLP to follow an LDR. We propose a new approximation approach for MSLPs, two-stage LDRs. The idea is to require only the state variables in an MSLP to follow an LDR, which is sufficient to obtain an approximation of an MSLP that is a two-stage stochastic linear program (2SLP). We similarly propose to apply LDR only to a subset of the variables in the dual of the MSLP, which yields a 2SLP approximation of the dual that provides a lower bound on the optimal value of the MSLP. Although solving the corresponding 2SLP approximations exactly is intractable in general, we investigate how approximate solution approaches that have been developed for solving 2SLP can be applied to solve these approximation problems, and derive statistical upper and lower bounds on the optimal value of the MSLP. In addition to potentially yielding better policies and bounds, this approach requires many fewer assumptions than are required to obtain an explicit reformulation when using the standard static LDR approach. A computational study on two example problems demonstrates that using a two-stage LDR can yield significantly better primal policies and modestly better dual policies than using policies based on a static LDR. 

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