No abstract

A method of analyzing small-angle neutron scattering data from polydisperse rodlike micelles is presented and applied to diheptanoylphosphatidylchollne in aqueous solution. This short-chain lecithin forms micelles, which can be modeled by cylinders of minimum size of 27 monomers that grow dramatically in length as the lecithin concentration increases. The thermodynamic theory developed for these particles accounts quantitatively for average micelle size, size distribution, and growth of diheptanoylphosphatidylchollne compared to nongrowing dihexanoylphosphatidylcholine micelles.

Asymmetric unilamellar vesicles are produced when short-chain phospholipids (fatty acyl chain lengths of 6-8 carbons) are mixed with long-chain phospholipids (fatty acyl chain lengths of 14 carbons or longer) in ratios of 1:4 short-chain/long-chain component. Short-chain lecithins are preferentially distributed on the outer monolayer, while a short-chain phosphatidylethanolamine derivative appears to localize on the inner monolayer of these spontaneously forming vesicles. Lanthanide NMR shift experiments clearly show a difference in head-group/ion interactions between the short-chain and long-chain species. Two-dimensional 1H NMR studies reveal efficient spin diffusion networks for the short-chain species embedded in the long-chain bilayer matrix. The short-chain lecithin is considerably more mobile than the long-chain component but has hindered motion compared to short-chain lecithin micelles. This differentiation in physical characteristics of the two phospholipid components is critical to understanding the activity of phospholipases toward these binary systems.

use in three-phase systems and on the development of a comprehensive model to predict mass transfer in vertical bubble flow.

Confirmation bias has been widely studied for its role in failures of reasoning. Individuals exhibiting confirmation bias fail to engage with information that contradicts their current beliefs, and, as a result, can fail to abandon inaccurate beliefs. But although most investigations of confirmation bias focus on individual learning, human knowledge is typically developed within a social structure. How does the presence of confirmation bias influence learning and the development of consensus within a group? In this paper, we use network models to study this question. We find, perhaps surprisingly, that moderate confirmation bias often improves group learning. This is because confirmation bias leads the group to entertain a wider variety of theories for a longer time, and prevents them from prematurely settling on a suboptimal theory. There is a downside, however, which is that a stronger form of confirmation bias can cause persistent polarization, and hurt the knowledge producing capacity of the community. We discuss implications of these results for epistemic communities, including scientific ones.