Abstract: The spiral angle of the elementary cellulose fibril in
the wood cell wall, often called microfibril angle, (MFA). Microfibril
angle in hardwood is one of the key determinants of solid timber
performance due to its strong influence on the stiffness, strength,
shrinkage, swelling, thermal-dynamics mechanical properties and
dimensional stability of wood. Variation of MFA (degree) in the S2
layer of the cell walls among Acacia mangium trees was determined
using small-angle X-ray scattering (SAXS). The length and
orientation of the microfibrils of the cell walls in the irradiated
volume of the thin samples are measured using SAXS and optical
microscope for 3D surface measurement. The undetermined
parameters in the analysis are the MFA, (M) and the standard
deviation (σФ) of the intensity distribution arising from the wandering
of the fibril orientation about the mean value. Nine separate pairs of
values are determined for nine different values of the angle of the
incidence of the X-ray beam relative to the normal to the radial
direction in the sample. The results show good agreement. The
curve distribution of scattered intensity for the real cell wall structure
is compared with that calculated with that assembly of rectangular
cells with the same ratio of transverse to radial cell wall length. It is
demonstrated that for β = 45°, the peaks in the curve intensity
distribution for the real and the rectangular cells coincide. If this
peak position is Ф45, then the MFA can be determined from the
relation M = tan-1 (tan Ф45 / cos 45°), which is precise for rectangular
cells. It was found that 92.93% of the variation of MFA can be
attributed to the distance from pith to bark. Here we shall present our
results of the MFA in the cell wall with respect to its shape, structure
and the distance from pith to park as an important fast check and yet
accurate towards the quality of wood, its uses and application.
Abstract: One of the determinants of a firm-s prosperity is the
customers- perceived service quality and satisfaction. While service
quality is wide in scope, and consists of various dimensions, there
may be differences in the relative importance of these dimensions in
affecting customers- overall satisfaction of service quality.
Identifying the relative rank of different dimensions of service quality
is very important in that it can help managers to find out which
service dimensions have a greater effect on customers- overall
satisfaction. Such an insight will consequently lead to more effective
resource allocation which will finally end in higher levels of
customer satisfaction. This issue –despite its criticality- has not
received enough attention so far. Therefore, using a sample of 240
bank customers in Iran, an artificial neural network is developed to
address this gap in the literature. As customers- evaluation of service
quality is a subjective process, artificial neural networks –as a brain
metaphor- may appear to have a potentiality to model such a
complicated process. Proposing a neural network which is able to
predict the customers- overall satisfaction of service quality with a
promising level of accuracy is the first contribution of this study. In
addition, prioritizing the service quality dimensions in affecting
customers- overall satisfaction –by using sensitivity analysis of
neural network- is the second important finding of this paper.