(C) 2013 Elsevier Ltd. All rights reserved.”
“Three types of water based polyurethane (PU), i.e. one ordinary elastomeric polyurethane (EPU)

and two thermosensitive polyurethane (TSPU), were synthesized and applied in leather finishing. Differential scanning calorimetry, positron annihilation lifetimes (PAL), water swelling, and water vapor permeability (WVP) were measured to evaluate how the structure of the synthesized PU and the temperature influenced the WVP of the PU finished leather. In contrast to EPU, TSPU(b) with a glass transition reversible BEZ235 solubility dmso phase and TSPU(c) with a crystal transition reversible phase showed an obvious phase separation structure and a phase transition in the normal wearing temperature range. PAL study indicated P005091 inhibitor that when the temperature was higher than the designed phase transition temperature, the ortho-positronium lifetime (tau(3))

and the average radius (R) of free volume of TSPU showed dramatic changes, whereas tau(3) and R of EPU remained unchanged. The water swelling and WVP of TSPU finished leather were found to depend on the structure of the polymer and the temperature, and they gave different responses to temperature variation. When the temperature was higher than the designed phase transition temperature, a significant WVP increase from 3800 g/(m(2) 24 h) to 7830 g/(m(2) 24 h) for TSPU(b) finished leather and from 4100 g/(m(2) 24 h) to 9450 g/(m(2) 24 h) for TSPU(c) finished leather were observed. Whereas EPU finished leather showed low WVP, and increased slightly as temperature increased. Phase transition accompanying a significant change in WVP can be used to develop “”smart leather”" with controllable water vapor permeability. (C) 2010 Wiley Periodicals, Inc. J Appl Polym Sci 117: GSK J4 molecular weight 1820-1827, 2010″
“Proteins frequently accomplish their biological function by collective atomic motions. Yet the identification of collective motions related to a specific protein function from, e. g., a molecular dynamics trajectory is often non-trivial. Here, we propose

a novel technique termed “”functional mode analysis”" that aims to detect the collective motion that is directly related to a particular protein function. Based on an ensemble of structures, together with an arbitrary “”functional quantity”" that quantifies the functional state of the protein, the technique detects the collective motion that is maximally correlated to the functional quantity. The functional quantity could, e. g., correspond to a geometric, electrostatic, or chemical observable, or any other variable that is relevant to the function of the protein. In addition, the motion that displays the largest likelihood to induce a substantial change in the functional quantity is estimated from the given protein ensemble.