This study determined the influence of optical properties of constituent layers on the colour of double-layer aesthetic filling materials. Multiple regression equations for the Commission Internationale de I'Eclairage (CIE) L*, a* and b* of layered materials were calculated from the optical values of the covering and underlying layers. Specimens (10 mm diameter, 1 mm thickness) of two light-cured resin composites and one compomer of seven to 11 shades were used. CIE L*, a* and b* values of each specimen were measured with a colour spectrophotometer backed by a standard white background. The scattering coefficient (S), absorption coefficient (K), contrast ratio (C) and translucency parameter (T) were calculated. Double-layered specimens were formed in optical contact by joining two different shades from the same material, or resin composite as covering with a compomer underlying layer. Each of the L*, a* and b* of layered material was used as a dependent variable, and 14 optical values of underlying and covering layers were used as independent variables in forward regression analysis (P = 0.01). CIE L* after layering had a positive correlation with S of covering layer (correlation coefficient; beta = 0.79-0.91, P < 0.01) and a correlation with L* of underlying layer (beta = 0.14-0.16). CIE a* after layering had a correlation with a* of covering layer (beta = 0.83-0.94) and a correlation with a* of underlying layer (beta = 0.30-0.56). CIE b* after layering had a correlation with b* of covering layer (beta = 0.77-0.90) and a correlation with T of covering layer (beta = 0.40-0.59). The layered colour of these materials can be predicted by the derived regression equations within the limitations of this study. CIE L*, a* and b* values of double-layer material are mainly influenced by S, CIE a* and b* of covering layer, respectively.
To determine the effectiveness of rehabilitation on improving ecosystem functions, we examined net photosynthetic rate (P N ), tree species composition, soil enzyme activities, and the microclimate (air and soil temperature, relative humidity) of an area on Mt. Makiling that has been rehabilitated and protected from fire for over 12 years. After it was last burned extensively in 1991, restoration was initiated by planting Acacia mangium and Acacia auriculiformis. We selected three areas to study in 2003. Two areas were rehabilitated with A. mangium and A. auriculiformis, and one was still dominated by Imperata cylindrica and Saccharum spontaneum. P N of A. mangium and A. auriculiformis showed significantly lower values than those of I. cylindrica and S. spontaneum. The Acacia plantations had more naturally regenerated tree species than the grassland. Additionally, more tree species appeared in the A. mangium plantation than in the A. auriculiformis plantation. Ficus spetica was present in all of the study sites. Dehydrogenase and phosphatase activities were significantly higher in soil under the Acacia plantations than under grassland. Grassland showed higher air temperature, relative humidity, and soil temperature as well as a larger variation per hour in these parameters compared to the Acacia plantations. The highest air temperature, relative humidity, and soil temperature were measured in April during the dry season. From the regression analysis, soil temperature was significantly correlated with air temperature. Hence plantations, as a rehabilitation activity for grassland, promote natural regeneration and stabilize the microclimate. This stabilization of the microclimate affects establishment and growth of naturally occurring tree species.
In this paper, local quasi-likelihood regression is considered for stationary random fields of dependent variables. In the case of independent data, local polynomial quasi-likelihood regression is known to have several appealing features such as minimax efficiency, design adaptivity and good boundary behaviour. These properties are shown to carry over to the case of random fields. The asymptotic normality of the regression estimator is established and explicit formulae for its asymptotic bias and variance are derived for strongly mixing stationary random fields. The extension to multi-dimensional covariates is also provided in full generality. Moreover, evaluation of the finite sample performance is made through a simulation study.
ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.