Coarse-grid higher order finite-difference time-domain algorithm with low dispersion errors

Higher order (2,4) FDTD schemes used for numerical solutions of Maxwell`s equations are focused on diminishing the truncation errors caused by the Taylor series expansion of the spatial derivatives. These schemes use a larger computational stencil, which generally makes use of the two constant coefficients, C-1 and C-2, for the four-point central-difference operators. In this paper we propose a novel way to diminish these truncation errors, in order to obtain more accurate numerical solutions of Maxwell`s equations. For such purpose, we present a method to individually optimize the pair of coefficients, C-1 and C-2, based on any desired grid size resolution and size of time step. Particularly, we are interested in using coarser grid discretizations to be able to simulate electrically large domains. The results of our optimization algorithm show a significant reduction in dispersion error and numerical anisotropy for all modeled grid size resolutions. Numerical simulations of free-space propagation verifies the very promising theoretical results. The model is also shown to perform well in more complex, realistic scenarios.

How rare is too rare to harvest? Management challenges posed by timber species occurring at low densities in the Brazilian Amazon

Tropical forests are characterized by diverse assemblages of plant and animal species compared to temperate forests. Corollary to this general rule is that most tree species, whether valued for timber or not, occur at low densities (<1 adult tree ha(-1)) or may be locally rare. In the Brazilian Amazon, many of the most highly valued timber species occur at extremely low densities yet are intensively harvested with little regard for impacts on population structures and dynamics. These include big-leaf mahogany (Swietenia macrophylla), ipe (Tabebuia serratifolia and Tabebuia impetiginosa), jatoba (Hymenaea courbaril), and freijo cinza (Cordia goeldiana). Brazilian forest regulations prohibit harvests of species that meet the legal definition of rare - fewer than three trees per 100 ha - but treat all species populations exceeding this density threshold equally. In this paper we simulate logging impacts on a group of timber species occurring at low densities that are widely distributed across eastern and southern Amazonia, based on field data collected at four research sites since 1997, asking: under current Brazilian forest legislation, what are the prospects for second harvests on 30-year cutting cycles given observed population structures, growth, and mortality rates? Ecologically `rare` species constitute majorities in commercial species assemblages in all but one of the seven large-scale inventories we analyzed from sites spanning the Amazon (range 49-100% of total commercial species). Although densities of only six of 37 study species populations met the Brazilian legal definition of a rare species, timber stocks of five of the six timber species declined substantially at all sites between first and second harvests in simulations based on legally allowable harvest intensities. Reducing species-level harvest intensity by increasing minimum felling diameters or increasing seed tree retention levels improved prospects for second harvests of those populations with a relatively high proportion of submerchantable stems, but did not dramatically improve projections for populations with relatively flat diameter distributions. We argue that restrictions on logging very low-density timber tree populations, such as the current Brazilian standard, provide inadequate minimum protection for vulnerable species. Population declines, even if reduced-impact logging (RIL) is eventually adopted uniformly, can be anticipated for a large pool of high-value timber species unless harvest intensities are adapted to timber species population ecology, and silvicultural treatments are adopted to remedy poor natural stocking in logged stands. (C) 2008 Elsevier B.V. All rights reserved.

Strategies for genetic model specification in the screening of genome-wide meta-analysis signals for further replication

Background Meta-analysis is increasingly being employed as a screening procedure in large-scale association studies to select promising variants for follow-up studies. However, standard methods for meta-analysis require the assumption of an underlying genetic model, which is typically unknown a priori. This drawback can introduce model misspecifications, causing power to be suboptimal, or the evaluation of multiple genetic models, which augments the number of false-positive associations, ultimately leading to waste of resources with fruitless replication studies. We used simulated meta-analyses of large genetic association studies to investigate naive strategies of genetic model specification to optimize screenings of genome-wide meta-analysis signals for further replication. Methods Different methods, meta-analytical models and strategies were compared in terms of power and type-I error. Simulations were carried out for a binary trait in a wide range of true genetic models, genome-wide thresholds, minor allele frequencies (MAFs), odds ratios and between-study heterogeneity (tau(2)). Results Among the investigated strategies, a simple Bonferroni-corrected approach that fits both multiplicative and recessive models was found to be optimal in most examined scenarios, reducing the likelihood of false discoveries and enhancing power in scenarios with small MAFs either in the presence or in absence of heterogeneity. Nonetheless, this strategy is sensitive to tau(2) whenever the susceptibility allele is common (MAF epsilon 30%), resulting in an increased number of false-positive associations compared with an analysis that considers only the multiplicative model. Conclusion Invoking a simple Bonferroni adjustment and testing for both multiplicative and recessive models is fast and an optimal strategy in large meta-analysis-based screenings. However, care must be taken when examined variants are common, where specification of a multiplicative model alone may be preferable.

Stability improvement of the fatty acid binding protein Sm14 from S. mansoni by Cys replacement: Structural and functional characterization of a vaccine candidate

The Schistosoma mansoni fatty acid binding protein (FABP), SmA, is a vaccine candidate against, S. mansoni and F hepatica. Previously, we demonstrated the importance of a correct fold to achieve protection in immunized animals after cercariae challenge [[10]. C.R.R. Ramos, R.C.R. Figueredo, T.A. Pertinhez, M.M. Vilar, A.L.T.O. Nascimento, M. Tendler, I. Raw, A. Spisni, P.L. Ho, Gene structure and M20T polymorphism of the Schistosoma mansoni Sm14 fatty acid-binding protein: structural, functional and immunoprotection analysis. J. Biol. Chem. 278 (2003) 12745-12751]. Here we show that the reduction of vaccine efficacy over time is due to protein dimerization and subsequent aggregation. We produced the mutants Sm14-M20(C62S) and Sm14M20(C62V) that, as expected, did not dimerize in SDS-PAGE. Molecular dynamics calculations and unfolding experiments highlighted a higher structural stability of these mutants with respect to the wild-type. In addition, we found that the mutated proteins, after thermal denaturation, refolded to their active native molecular architecture as proved by the recovery of the fatty acid binding ability. Sm14-M20(C62V) turned out to be the more stable form over time, providing the basis to determine the first 3D solution structure of a Sm14 protein in its apo-form. Overall, Sm14-M20(C62V) possesses an improved structural stability over time, an essential feature to preserve its immunization capability and, in experimentally immunized animals, it exhibits a protection effect against S. mansoni cercariae infections comparable to the one obtained with the wild-type protein. These facts indicate this protein as a good lead molecule for large-scale production and for developing an effective Sm14 based anti-helminthes vaccine. (C) 2008 Elsevier B.V. All rights reserved.