De sitter relativity: a natural scenario for an evolving Lambda

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Difference variance dispersion graphs for comparing response surface designs with applications in food technology

Variance dispersion graphs have become a popular tool in aiding the choice of a response surface design. Often differences in response from some particular point, such as the expected position of the optimum or standard operating conditions, are more important than the response itself. We describe two examples from food technology. In the first, an experiment was conducted to find the levels of three factors which optimized the yield of valuable products enzymatically synthesized from sugars and to discover how the yield changed as the levels of the factors were changed from the optimum. In the second example, an experiment was conducted on a mixing process for pastry dough to discover how three factors affected a number of properties of the pastry, with a view to using these factors to control the process. We introduce the difference variance dispersion graph (DVDG) to help in the choice of a design in these circumstances. The DVDG for blocked designs is developed and the examples are used to show how the DVDG can be used in practice. In both examples a design was chosen by using the DVDG, as well as other properties, and the experiments were conducted and produced results that were useful to the experimenters. In both cases the conclusions were drawn partly by comparing responses at different points on the response surface.

Spin-orbit coupling for tidally evolving super-Earths

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Tendências econômicas e sociais na América Latina e no Caribe em gráficos = Economic and social trends in Latin America and the Caribbean in graphs = Tendencias económicas y sociales en América Latina y el Caribe en gráficos

Incluye Bibliografía

A Markov random field model for combining optimum-path forest classifiers using decision graphs and game strategy approach

The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.

Portrait of the economist as a young man: Raúl Prebisch's evolving views on the business cycle and money, 1919-1949

Includes bibliography

Unsupervised manifold learning using Reciprocal kNN Graphs in image re-ranking and rank aggregation tasks

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fast-Evolving Mitochondrial DNA in Ceriantharia: A Reflection of Hexacorallia Paraphyly?

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Review of Global Warming in the 21st Century. Volume 1: Our Evolving Climate Crisis; Volume 2: Melting Ice and Warming Seas; Volume 3: Plants and Animals in Peril by Bruce E. Johansen

There is compelling evidence that Planet Earth is on the path to an era of global warming that has serious implications for the well-being of both people and nature. This three-volume synthesis of literature will be a marvelous place for both the public and new scholars interested in global warming to begin their pursuit of the subject. The author captures the best of the scientific literature and press materials appearing in recent years. The utility of these volumes as a resource for gaining a broad background or pursuing a particular aspect of global warming is enhanced by Johansen's talent for explaining with clarity a vast and rapidly growing subject.

NUMERICAL AND ANALYTICAL VERIFICATION OF A MULTISCALE COMPUTATIONAL MODEL FOR IMPACT PROBLEMS IN HETEROGENEOUS VISCOELASTIC MATERIALS WITH EVOLVING DAMAGE

Composites are engineered materials that take advantage of the particular properties of each of its two or more constituents. They are designed to be stronger, lighter and to last longer which can lead to the creation of safer protection gear, more fuel efficient transportation methods and more affordable materials, among other examples. This thesis proposes a numerical and analytical verification of an in-house developed multiscale model for predicting the mechanical behavior of composite materials with various configurations subjected to impact loading. This verification is done by comparing the results obtained with analytical and numerical solutions with the results found when using the model. The model takes into account the heterogeneity of the materials that can only be noticed at smaller length scales, based on the fundamental structural properties of each of the composite’s constituents. This model can potentially reduce or eliminate the need of costly and time consuming experiments that are necessary for material characterization since it relies strictly upon the fundamental structural properties of each of the composite’s constituents. The results from simulations using the multiscale model were compared against results from direct simulations using over-killed meshes, which considered all heterogeneities explicitly in the global scale, indicating that the model is an accurate and fast tool to model composites under impact loads. Advisor: David H. Allen

Evolving Bird Management Research at the USDA Wildlife Service’s National Wildlife Research Center

As the methods-development arm of the U.S. Department of Agriculture’s Wildlife Services program, the National Wildlife Research Center (NWRC) is charged with developing tools and information for protecting agriculture, human health and safety, and property from problems caused by wildlife, including birds. Increasingly the NWRC is being asked to provide basic ecological information on the population status of various bird species, and its role is expanding from a reactive one of providing management options to that of predicting long-term implications of various management actions. This paper describes several areas of research by NWRC scientists to address population-level questions in support of WS mission.

Discriminating Different Classes of Biological Networks by Analyzing the Graphs Spectra Distribution

The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e. g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed.

Properly coloured copies and rainbow copies of large graphs with small maximum degree

Let G be a graph on n vertices with maximum degree ?. We use the Lovasz local lemma to show the following two results about colourings ? of the edges of the complete graph Kn. If for each vertex v of Kn the colouring ? assigns each colour to at most (n - 2)/(22.4?2) edges emanating from v, then there is a copy of G in Kn which is properly edge-coloured by ?. This improves on a result of Alon, Jiang, Miller, and Pritikin [Random Struct. Algorithms 23(4), 409433, 2003]. On the other hand, if ? assigns each colour to at most n/(51?2) edges of Kn, then there is a copy of G in Kn such that each edge of G receives a different colour from ?. This proves a conjecture of Frieze and Krivelevich [Electron. J. Comb. 15(1), R59, 2008]. Our proofs rely on a framework developed by Lu and Szekely [Electron. J. Comb. 14(1), R63, 2007] for applying the local lemma to random injections. In order to improve the constants in our results we use a version of the local lemma due to Bissacot, Fernandez, Procacci, and Scoppola [preprint, arXiv:0910.1824]. (c) 2011 Wiley Periodicals, Inc. Random Struct. Alg., 40, 425436, 2012

Edge Colourings of Graphs Avoiding Monochromatic Matchings of a Given Size

Let k and l be positive integers. With a graph G, we associate the quantity c(k,l)(G), the number of k-colourings of the edge set of G with no monochromatic matching of size l. Consider the function c(k,l) : N --> N given by c(k,l)(n) = max {c(k,l)(G): vertical bar V(G)vertical bar = n}, the maximum of c(k,l)(G) over all graphs G on n vertices. In this paper, we determine c(k,l)(n) and the corresponding extremal graphs for all large n and all fixed values of k and l.

UNIVERSALITY OF RANDOM GRAPHS

We prove that asymptotically (as n -> infinity) almost all graphs with n vertices and C(d)n(2-1/2d) log(1/d) n edges are universal with respect to the family of all graphs with maximum degree bounded by d. Moreover, we provide an efficient deterministic embedding algorithm for finding copies of bounded degree graphs in graphs satisfying certain pseudorandom properties. We also prove a counterpart result for random bipartite graphs, where the threshold number of edges is even smaller but the embedding is randomized.