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  1. Porous polymers have interesting acoustic properties including wave dampening and acoustic impedance matching and may be used in numerous acoustic applications, e.g., waveguiding or acoustic cloaking. These materials can be prepared by the inclusion of gas-filled voids, or pores, within an elastic polymer network; therefore, porous polymers that have controlled porosity values and a wide range of possible mechanical properties are needed, as these are key factors that impact the sound-dampening properties. Here, the synthesis of acoustic materials with varying porosities and mechanical properties that could be controlled independent of the pore morphology using emulsion templated polymerizations is described. Polydimethylsiloxane-based ABA triblock copolymer surfactants were prepared using reversible addition−fragmentation chain transfer polymerizations to control the emulsion template and act as an additional crosslinker in the polymerization. Acoustic materials prepared with reactive surfactants possessed a storage modulus of ∼300 kPa at a total porosity of 71% compared to materials prepared using analogous nonreactive surfactants that possessed storage modulus values of ∼150 kPa at similar porosities. These materials display very low longitudinal sound speeds of ∼35 m/s at ultrasonic frequencies, making them excellent candidates in the preparation of acoustic devices such as metasurfaces or lenses. 
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    Free, publicly-accessible full text available December 20, 2024
  2. Abstract

    Social behaviors are diverse in nature, but it is unclear how conserved genes, brain regions, and cell populations generate this diversity. Here we investigate bower-building, a recently-evolved social behavior in cichlid fishes. We use single nucleus RNA-sequencing in 38 individuals to show signatures of recent behavior in specific neuronal populations, and building-associated rebalancing of neuronal proportions in the putative homolog of the hippocampal formation. Using comparative genomics across 27 species, we trace bower-associated genome evolution to a subpopulation of glia lining the dorsal telencephalon. We show evidence that building-associated neural activity and a departure from quiescence in this glial subpopulation together regulate hippocampal-like neuronal rebalancing. Our work links behavior-associated genomic variation to specific brain cell types and their functions, and suggests a social behavior has evolved through changes in glia.

     
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  3. Polymer-based acoustic metamaterials possess properties including acoustic wave manipulation, cloaking, and sound dampening. Here, PDMS-based elastomers were prepared using thiol–ene “click reactions” with emulsion templating. Acoustic analysis showed these materials achieved sound speed values of ∼ 40 m s −1 , close to the predicted minimum of ∼25 m s −1 attainable. 
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  4. Using a Lewis acid-quenched CF2Ph- reagent, we show C–C bond formation through nucleophilic addition reactions to prepare molecules containing internal –CF2– linkages. We demonstrate C(sp2)–C(sp3) coupling using both SNAr reactions and Pd-catalysis. Finally, C(sp3)–C(sp3) bonds are forged using operationally simple SN2 reactions that tolerate medicinally-relevant motifs. 
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  5. null (Ed.)
    We propose a new family of depth measures called the elastic depths that can be used to greatly improve shape anomaly detection in functional data. Shape anomalies are functions that have considerably different geometric forms or features from the rest of the data. Identifying them is generally more difficult than identifying magnitude anomalies because shape anomalies are often not distinguishable from the bulk of the data with visualization methods. The proposed elastic depths use the recently developed elastic distances to directly measure the centrality of functions in the amplitude and phase spaces. Measuring shape outlyingness in these spaces provides a rigorous quantification of shape, which gives the elastic depths a strong theoretical and practical advantage over other methods in detecting shape anomalies. A simple boxplot and thresholding method is introduced to identify shape anomalies using the elastic depths. We assess the elastic depth’s detection skill on simulated shape outlier scenarios and compare them against popular shape anomaly detectors. Finally, we use hurricane trajectories to demonstrate the elastic depth methodology on manifold valued functional data. 
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  6. Abstract

    We propose the multiple changepoint isolation (MCI) method for detecting multiple changes in the mean and covariance of a functional process. We first introduce a pair of projections to represent the variability “between” and “within” the functional observations. We then present an augmented fused lasso procedure to split the projections into multiple regions robustly. These regions act to isolate each changepoint away from the others so that the powerful univariate CUSUM statistic can be applied region‐wise to identify the changepoints. Simulations show that our method accurately detects the number and locations of changepoints under many different scenarios. These include light and heavy tailed data, data with symmetric and skewed distributions, sparsely and densely sampled changepoints, and mean and covariance changes. We show that our method outperforms a recent multiple functional changepoint detector and several univariate changepoint detectors applied to our proposed projections. We also show that MCI is more robust than existing approaches and scales linearly with sample size. Finally, we demonstrate our method on a large time series of water vapor mixing ratio profiles from atmospheric emitted radiance interferometer measurements.

     
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  7. null (Ed.)