University of Georgia

About: University of Georgia is a education organization based out in Athens, Georgia, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 41934 authors who have published 93622 publications receiving 3713212 citations. The organization is also known as: UGA & Franklin College.

Informal and Incidental Learning

Abstract: This chapter provides a theory of informal and incidental learning and updates this theory based on recent research.

Spatial Patterns in the Distribution of Tropical Tree Species

Abstract: Fully mapped tree census plots of large area, 25 to 52 hectares, have now been completed at six different sites in tropical forests, including dry deciduous to wet evergreen forest on two continents. One of the main goals of these plots has been to evaluate spatial patterns in tropical tree populations. Here the degree of aggregation in the distribution of 1768 tree species is examined based on the average density of conspecific trees in circular neighborhoods around each tree. When all individuals larger than 1 centimeter in stem diameter were included, nearly every species was more aggregated than a random distribution. Considering only larger trees (≥ 10 centimeters in diameter), the pattern persisted, with most species being more aggregated than random. Rare species were more aggregated than common species. All six forests were very similar in all the particulars of these results.

Conservation and divergence of methylation patterning in plants and animals

Abstract: Cytosine DNA methylation is a heritable epigenetic mark present in many eukaryotic organisms. Although DNA methylation likely has a conserved role in gene silencing, the levels and patterns of DNA methylation appear to vary drastically among different organisms. Here we used shotgun genomic bisulfite sequencing (BS-Seq) to compare DNA methylation in eight diverse plant and animal genomes. We found that patterns of methylation are very similar in flowering plants with methylated cytosines detected in all sequence contexts, whereas CG methylation predominates in animals. Vertebrates have methylation throughout the genome except for CpG islands. Gene body methylation is conserved with clear preference for exons in most organisms. Furthermore, genes appear to be the major target of methylation in Ciona and honey bee. Among the eight organisms, the green alga Chlamydomonas has the most unusual pattern of methylation, having non-CG methylation enriched in exons of genes rather than in repeats and transposons. In addition, the Dnmt1 cofactor Uhrf1 has a conserved function in maintaining CG methylation in both transposons and gene bodies in the mouse, Arabidopsis, and zebrafish genomes.

Determining the density of states for classical statistical models: a random walk algorithm to produce a flat histogram.

Abstract: We describe an efficient Monte Carlo algorithm using a random walk in energy space to obtain a very accurate estimate of the density of states for classical statistical models. The density of states is modified at each step when the energy level is visited to produce a flat histogram. By carefully controlling the modification factor, we allow the density of states to converge to the true value very quickly, even for large systems. From the density of states at the end of the random walk, we can estimate thermodynamic quantities such as internal energy and specific heat capacity by calculating canonical averages at any temperature. Using this method, we not only can avoid repeating simulations at multiple temperatures, but we can also estimate the free energy and entropy, quantities that are not directly accessible by conventional Monte Carlo simulations. This algorithm is especially useful for complex systems with a rough landscape since all possible energy levels are visited with the same probability. As with the multicanonical Monte Carlo technique, our method overcomes the tunneling barrier between coexisting phases at first-order phase transitions. In this paper, we apply our algorithm to both first- and second-order phase transitions to demonstrate its efficiency and accuracy. We obtained direct simulational estimates for the density of states for two-dimensional ten-state Potts models on lattices up to 200 x 200 and Ising models on lattices up to 256 x 256. Our simulational results are compared to both exact solutions and existing numerical data obtained using other methods. Applying this approach to a three-dimensional +/-J spin-glass model, we estimate the internal energy and entropy at zero temperature; and, using a two-dimensional random walk in energy and order-parameter space, we obtain the (rough) canonical distribution and energy landscape in order-parameter space. Preliminary data suggest that the glass transition temperature is about 1.2 and that better estimates can be obtained with more extensive application of the method. This simulational method is not restricted to energy space and can be used to calculate the density of states for any parameter by a random walk in the corresponding space.

Metabolic, phylogenetic, and ecological diversity of the methanogenic archaea.

Abstract: Although of limited metabolic diversity, methanogenic archaea or methanogens possess great phylogenetic and ecological diversity. Only three types of methanogenic pathways are known: CO(2)-reduction, methyl-group reduction, and the aceticlastic reaction. Cultured methanogens are grouped into five orders based upon their phylogeny and phenotypic properties. In addition, uncultured methanogens that may represent new orders are present in many environments. The ecology of methanogens highlights their complex interactions with other anaerobes and the physical and chemical factors controlling their function.