Slowly relaxing longitudinal density fluctuations in an optically perfect sample of bulk poly(n‐hexyl methacrylate) (PHMA) have been studied by photon correlation spectroscopy in the temperature range 10–36°C. The glass transition temperature for this sample was measured to be Tg = −3°C by differential scanning calorimetry. The optical purity of the sample was verified by Rayleigh‐Brillouin spectroscopy and the Landau‐Placzek ratio was observed to be 2.3 at 25°C. Light‐scattering relaxation functions were obtained over the time range 10−6‐1 s. The shape of the relaxation functions broadened as the temperature was lowered towards the glass transition. Quantitative analysis of the results was carried out using the Kohlrausch‐Williams‐Watts (KWW) function to obtain average relaxation times, 〈τ〉, and width parameters, β. The width parameter decreased from 0.43 to 0.21 over the temperature interval, as suggested by visual inspection. Average relaxation times shifted with temperature in a manner consistent with previous mechanical studies of the primary glass‐rubber relaxation in PHMA. The relaxation functions were also analyzed in terms of a distribution of relaxation rates, G(Γ). The calculated distributions were unimodal at all temperatures. The average relaxation times obtained from G(Γ) were in agreement with the KWW analysis, and the shape of the distribution broadened as the sample was cooled. The rate at which G(Γ) displayed a maximum correlated well with the corresponding frequency of maximum dielectric loss for PHMA. The temperature dependence of these two quantities could be reproduced with an Arrhenius activation energy of 21 Kcal/mol. A consistent picture of the molecular dynamics of PHMA near the glass transition requires a strong secondary relaxation process with a different temperature dependence from the primary glass‐rubber relaxation. The present results suggest that the behavior of PHMA is similar to the other poly(alkyl methacrylates). © 1996 John Wiley & Sons, Inc.

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SummaryReference genomes are refined to reflect error corrections and other improvements. While this process improves novel data generation and analysis, incorporating data analyzed on an older reference genome assembly requires transforming the coordinates and representations of the data to the new assembly. Multiple tools exist to perform this transformation for coordinate-only data types, but none supports accurate transformation of genome-wide short variation. Here we present GenomeWarp, a tool for efficiently transforming variants between genome assemblies. GenomeWarp transforms regions and short variants in a conservative manner to minimize false positive and negative variants in the target genome, and converts over 99% of regions and short variants from a representative human genome.Availability and implementationGenomeWarp is written in Java. All source code and the user manual are freely available at https://github.com/verilylifesciences/genomewarp.Supplementary information Supplementary data are available at Bioinformatics online.

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