We present possible observing scenarios for the Advanced LIGO, Advanced Virgo and KAGRA gravitational-wave detectors over the next decade, with the intention of providing information to the astronomy community to facilitate planning for multi-messenger astronomy with gravitational waves. We estimate the sensitivity of the network to transient gravitational-wave signals, and study the capability of the network to determine the sky location of the source. We report our findings for gravitational-wave transients, with particular focus on gravitational-wave signals from the inspiral of binary neutron star systems, which are the most promising targets for multi-messenger astronomy. The ability to localize the sources of the detected signals depends on the geographical distribution of the detectors and their relative sensitivity, and credible regions can be as large as thousands of square degrees when only two sensitive detectors are operational. Determining the sky position of a significant fraction of detected signals to areas of 5– requires at least three detectors of sensitivity within a factor of of each other and with a broad frequency bandwidth. When all detectors, including KAGRA and the third LIGO detector in India, reach design sensitivity, a significant fraction of gravitational-wave signals will be localized to a few square degrees by gravitational-wave observations alone.

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A flow-type apparatus and predictive framework were developed for measuring and estimating dipolarity/ polarizability (π*) values of binary mixtures of supercritical carbon dioxide (scCO 2 )−cosolvents. The π* values of scCO 2 with methanol and ethanol cosolvents (up to 10 mol %) are reported at the temperature ranging from 40 to 80 °C and pressure ranging from 10 to 20 MPa and were found to be dependent on fluid density. The predictive framework for scCO 2 −cosolvent mixtures proposed in this work was the modification by the addition of correction functions (g(ρ CO 2 )) of local density enhancement into the previous predictive framework for binary liquid nonpolar−polar mixtures [Ind. Eng. Chem. Res. 2019, 58, 18986−18996]. Four g(ρ CO 2 ) forms with a function of CO 2 density were evaluated by considering literature local density enhancements of pure CO 2 obtained from (i) fluorescence, (ii) Raman, (ii) UV−vis spectroscopic techniques, and (iv) molecular dynamics simulations. The framework was applied to the prediction of π* of four scCO 2 −cosolvent mixtures (methanol, ethanol, 2-propanol, and 1,1,1,2tetrafluoroethane (HFC134a)) and was found to give a reliable value with an overall relative deviation of 0.03 between the experimental and calculated data, where the fluorescence g(ρ CO 2 ) function provided a lower deviation than the other three functions. The application of the framework to separation processes showed that the π* values were found to explain the trends of solubility, extraction yield, and fractionation recovery. The π* values determined from the framework can be used to analyze solvent effect trends in many separation processes that required only cosolvent dipole moment, pure π* component, and CO 2 density (pressure and temperature).

Phospholipid scramblases that catalyze lipid transbilayer movement are associated with intercellular signaling and lipid homeostasis. Although several studies have shown that the hydrophilic residue-rich groove of the proteins mediates lipid scrambling, the interactions between the groove and the lipid bilayers remain poorly understood. Here we have revealed the structural features of model transmembrane peptides that conduct lipid scrambling as well as the interactions between the peptides and the surrounding lipids by means of experimental and simulation techniques. Peptides with two strongly hydrophilic residues located on the same side of the helices and at a deeper position in the membrane exhibited high scramblase activities. All-atom molecular dynamics simulations showed that the interactions between the hydrophilic residues and lipid head groups regulate the membrane thinning and disorder near the peptides in an order that correlates with the scramblase activity of the peptides. These results provide a basis for understanding the lipid scrambling mechanisms by transmembrane regions.

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