Diffraction evidence for the structure of cellulose microfibrils in bamboo, a model for grass and cereal celluloses

Background: Cellulose from grasses and cereals makes up much of the potential raw material for biofuel production. It is not clear if cellulose microfibrils from grasses and cereals differ in structure from those of other plants. The structures of the highly oriented cellulose microfibrils in the cell walls of the internodes of the bamboo Pseudosasa amabilis are reported. Strong orientation facilitated the use of a range of scattering techniques. Results: Small-angle neutron scattering provided evidence of extensive aggregation by hydrogen bonding through the hydrophilic edges of the sheets of chains. The microfibrils had a mean centre-to-centre distance of 3.0 nm in the dry state, expanding on hydration. The expansion on hydration suggests that this distance between centres was through the hydrophilic faces of adjacent microfibrils. However in the other direction, perpendicular to the sheets of chains, the mean, disorder-corrected Scherrer dimension from wide-angle X-ray scattering was 3.8 nm. It is possible that this dimension is increased by twinning (crystallographic coalescence) of thinner microfibrils over part of their length, through the hydrophobic faces. The wide-angle scattering data also showed that the microfibrils had a relatively large intersheet d-spacing and small monoclinic angle, features normally considered characteristic of primary-wall cellulose. Conclusions: Bamboo microfibrils have features found in both primary-wall and secondary-wall cellulose, but are crystallographically coalescent to a greater extent than is common in celluloses from other plants. The extensive aggregation and local coalescence of the microfibrils are likely to have parallels in other grass and cereal species and to influence the accessibility of cellulose to degradative enzymes during conversion to liquid biofuel

Hypotheses for earthquake occurrences

Very little work has been done in generating alternatives to the Poisson process model. The work reported here deals with alternatives to the Poisson process model for the earthquakes and checks them using empirical data and the statistical hypothesis testing apparatus. The strategy used here for generating hypotheses is to compound the Poisson process. The parameter of the Poisson process is replaced by a random variable having prescribed density function. The density functions used are gamma, chi and extended (gamma/chi). The original distribution is then averaged out with respect to these density functions. For the compound Poisson processes the waiting time distributions for the future events are derived. As the parameters for the various statistical models for earthquake occurrences are not known, the problem is basically of composite hypothesis testing. One way of designing a test is to estimate these parameters and use them as true values. Momentmatching is used here to estimate the parameters. The results of hypothesis testing using data from Hindukush and North East India are presented