A New Composite Restorative Based on a Hydrophobic Matrix

A hydrophobic restorative composite based on a fluorocarbon analog of an alkyl methacrylate and a bisphenol adduct was formulated into a one-paste system, which polymerized in the presence of blue light. Physical, mechanical, and water-related properties were determined. High contact angles and low water sorption were shown by the experimental composite. Capillary penetration of oral fluids around restorations, therefore, could be prevented in the presence of this highly hydrophobic surface. The physical and mechanical properties of the experimental composite were either comparable to or somewhat less favorable than commercial Bis-GMA composites.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67042/2/10.1177_00220345790580100401.pd

The evolution of hippocampus volume and brain size in relation to food hoarding in birds

Food-hoarding birds frequently use spatial memory to relocate their caches, thus they may evolve a larger hippocampus in their brain than non-hoarder species. However, previous studies testing for such interspecific relationships provided conflicting results. In addition, food hoarding may be a cognitively complex task involving elaboration of a variety of brain regions, even outside of the hippocampus. Hence, specialization to food hoarding may also result in the enlargement of the overall brain. In a phylogenetic analysis of distantly related birds, we studied the interspecific association between food hoarding and the size of different brain regions, each reflecting different resolutions. After adjusting for allometric effects, the relative volume of the hippocampus and the relative size of the entire brain were each positively related to the degree of food-hoarding specialization, even after controlling for migration and brood parasitism. We also found some significant evidence for the relative volume of the telencephalon being associated with food hoarding, but this relationship was dependent on the approach we used. Hence, neural adaptation to food hoarding may favour the evolution of different brain structures

Scaling of Nucleation Rates

The homogeneous nucleation rate, J, for T ≪ Tc can be cast into a corresponding states form by exploiting scaled expressions for the vapor pressure and for the surface tension, σ. In the vapor-to-liquid case with σ = σ0[Tc-T], the classical cluster energy of formation /kT = [16π/3]·Ω3[Tc/T-1]3/(ln S)2 ≡ [x0/x]2, where Ω ≡ σ0[k ñ2/3] and ñ is liquid number density. The Ω ≈ 2 for normal liquids. (A similar approach can be applied to homogeneous liquid to solid nucleation and to heterogeneous nucleation formalisms using appropriate modifications of σ and Ω.) The above [x0/x]2 is sufficiently tenable that in some cases, one can use it to extract approximate critical temperatures from experimental data. In this work, we point out that expansion cloud chamber data (for nonane, toluene, and water) are in excellent agreement with ln J ≈ const. - [x0/x]2 [centimeter-gram-second (cgs) units], and that the constant term is well approximated by ln (Γc), where Γc is the inverse thermal wavelength cubed per second at T = Tc. The ln (Γc) is ≈ 60 in cgs units (74 in SI units) for most materials. A physical basis for the latter form, which includes the behavior at small n, the discrete integer behavior of n, and a configurational entropy term, τ ln (n), is presented

Modelling and monitoring land-cover change processes in tropical regions

Transformations in terrestrial ecosystems are increasingly regarded as an important element of global change. Quantitative data on where, when and why land-cover changes take place globally are still incomplete. This article reviews recent approaches to the monitoring and modelling of deforestation and dryland degradation in tropical regions. The review highlights the requirement to tailor the investigation method to the specific research question of interest. Different techniques to monitor land-cover changes at regional scales are analysed. The following modelling scenarios are discussed and illustrated by specific studies: projection of future land-cover changes with descriptive models, explanation of land-cover changes with empirical models, projection of future spatial patterns of changes with spatial statistical models, test of scenarios on future changes in land-cover with dynamic ecosystem models, and design of policy interventions with economic models. The article stresses the needs for a better integration of social science knowledge in land-cover change models and for a comprehensive theory of land-use changes