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This study aims to investigate the design considerations and tensions in developing data visualization activities that integrate multi-disciplinary, critical, and community-centered approaches to data learning. We do so through conjecture mapping and qualitative analysis in the context of a design-based research study of an informal education program focused on data visualization. We found multiple design considerations tied to each approach, with critical approaches often deprioritized and related to tensions with the other approaches. 

Paper presented as part of symposium. 

Voids—the nothingness—broadly exist within nanomaterials and impact properties ranging from catalysis to mechanical response. However, understanding nanovoids is challenging due to lack of imaging methods with the needed penetration depth and spatial resolution. Here, we integrate electron tomography, morphometry, graph theory and coarse-grained molecular dynamics simulation to study the formation of interconnected nanovoids in polymer films and their impacts on permeance and nanomechanical behaviour. Using polyamide membranes for molecular separation as a representative system, three-dimensional electron tomography at nanometre resolution reveals nanovoid formation from coalescence of oligomers, supported by coarse-grained molecular dynamics simulations. Void analysis provides otherwise inaccessible inputs for accurate fittings of methanol permeance for polyamide membranes. Three-dimensional structural graphs accounting for the tortuous nanovoids within, measure higher apparent moduli with polyamide membranes of higher graph rigidity. Our study elucidates the significance of nanovoids beyond the nothingness, impacting the synthesis‒morphology‒function relationships of complex nanomaterials. 

Abstract The molecular gas in galaxies traces both the fuel for star formation and the processes that can enhance or suppress star formation. Observations of the molecular gas state can thus point to when and why galaxies stop forming stars. In this study, we present Atacama Large Millimeter/submillimeter Array observations of the molecular gas in galaxies evolving through the post-starburst phase. These galaxies have low current star formation rates (SFRs), regardless of the SFR tracer used, with recent starbursts ending within the last 600 Myr. We present CO (3–2) observations for three post-starburst galaxies, and dense gas HCN/HCO⁺/HNC (1–0) observations for six (four new) post-starburst galaxies. The post-starbursts have low excitation traced by the CO spectral-line energy distribution up to CO (3–2), more similar to early-type than starburst galaxies. The low excitation indicates that lower density rather than high temperatures may suppress star formation during the post-starburst phase. One galaxy displays a blueshifted outflow traced by CO (3–2). MaNGA observations show that the ionized gas velocity is disturbed relative to the stellar velocity field, with a blueshifted component aligned with the molecular gas outflow, suggestive of a multiphase outflow. Low ratios of HCO⁺/CO, indicating low fractions of dense molecular gas relative to the total molecular gas, are seen throughout post-starburst phase, except for the youngest post-starburst galaxy considered here. These observations indicate that the impact of any feedback or quenching processes may be limited to low excitation and weak outflows in the cold molecular gas during the post-starburst phase. 

Abstract Post-starburst (PSB), or “E + A,” galaxies represent a rapid transitional phase between major, gas-rich mergers and gas-poor, quiescent, early-type galaxies. Surprisingly, many PSBs have been shown to host a significant interstellar medium (ISM), despite theoretical predictions that the majority of the star-forming gas should be expelled in active galactic nuclei– or starburst-driven outflows. To date, the resolved properties of this surviving ISM have remained unknown. We present high-resolution ALMA continuum and CO(2–1) observations in six gas- and dust-rich PSBs, revealing for the first time the spatial and kinematic structure of their ISM on sub-kpc scales. We find extremely compact molecular reservoirs, with dust and gas surface densities rivaling those found in (ultra)luminous infrared galaxies. We observe spatial and kinematic disturbances in all sources, with some also displaying disk-like kinematics. Estimates of the internal turbulent pressure in the gas exceed those of normal star-forming disks by at least 2 orders of magnitude, and rival the turbulent gas found in local interacting galaxies, such as the Antennae. Though the source of this high turbulent pressure remains uncertain, we suggest that the high incidence of tidal disruption events in PSBs could play a role. The star formation in these PSBs’ turbulent central molecular reservoirs is suppressed, forming stars only 10% as efficiently as starburst galaxies with similar gas surface densities. “The fall” of star formation in these galaxies was not precipitated by complete gas expulsion or redistribution. Rather, this high-resolution view of PSBs’ ISM indicates that star formation in their remaining compact gas reservoirs is suppressed by significant turbulent heating. 

Abstract Ligand-induced endocytosis of the immune receptor FLAGELLIN SENSING2 (FLS2) is critical for maintaining its proper abundance in the plasma membrane (PM) to initiate and subsequently down regulate cellular immune responses to bacterial flagellin or flg22-peptide. The molecular components governing PM abundance of FLS2, however, remain mostly unknown. Here, we identified Arabidopsis (Arabidopsis thaliana) DYNAMIN-RELATED PROTEIN1A (DRP1A), a member of a plant-specific family of large dynamin GTPases, as a critical contributor to ligand-induced endocytosis of FLS2 and its physiological roles in flg22-signaling and immunity against Pseudomonas syringae pv. tomato DC3000 bacteria in leaves. Notably, drp1a single mutants displayed similar flg22-defects as those previously reported for mutants in another dynamin-related protein, DRP2B, that was previously shown to colocalize with DRP1A. Our study also uncovered synergistic roles of DRP1A and DRP2B in plant growth and development as drp1a drp2b double mutants exhibited severely stunted roots and cotyledons, as well as defective cell shape, cytokinesis, and seedling lethality. Furthermore, drp1a drp2b double mutants hyperaccumulated FLS2 in the PM prior to flg22-treatment and exhibited a block in ligand-induced endocytosis of FLS2, indicating combinatorial roles for DRP1A and DRP1B in governing PM abundance of FLS2. However, the increased steady-state PM accumulation of FLS2 in drp1a drp2b double mutants did not result in increased flg22 responses. We propose that DRP1A and DRP2B are important for the regulation of PM-associated levels of FLS2 necessary to attain signaling competency to initiate distinct flg22 responses, potentially through modulating the lipid environment in defined PM domains. 

Abstract Near‐term iterative forecasting is a powerful tool for ecological decision support and has the potential to transform our understanding of ecological predictability. However, to this point, there has been no cross‐ecosystem analysis of near‐term ecological forecasts, making it difficult to synthesize diverse research efforts and prioritize future developments for this emerging field. In this study, we analyzed 178 near‐term (≤10‐yr forecast horizon) ecological forecasting papers to understand the development and current state of near‐term ecological forecasting literature and to compare forecast accuracy across scales and variables. Our results indicated that near‐term ecological forecasting is widespread and growing: forecasts have been produced for sites on all seven continents and the rate of forecast publication is increasing over time. As forecast production has accelerated, some best practices have been proposed and application of these best practices is increasing. In particular, data publication, forecast archiving, and workflow automation have all increased significantly over time. However, adoption of proposed best practices remains low overall: for example, despite the fact that uncertainty is often cited as an essential component of an ecological forecast, only 45% of papers included uncertainty in their forecast outputs. As the use of these proposed best practices increases, near‐term ecological forecasting has the potential to make significant contributions to our understanding of forecastability across scales and variables. In this study, we found that forecastability (defined here as realized forecast accuracy) decreased in predictable patterns over 1–7 d forecast horizons. Variables that were closely related (i.e., chlorophyll and phytoplankton) displayed very similar trends in forecastability, while more distantly related variables (i.e., pollen and evapotranspiration) exhibited significantly different patterns. Increasing use of proposed best practices in ecological forecasting will allow us to examine the forecastability of additional variables and timescales in the future, providing a robust analysis of the fundamental predictability of ecological variables.