Muuuitoos estao com expectativas, e outros achando que sera a mesma coisa este ano!A mesma coisa nao sera,Porquee?Porque 2013 nao e 2014 , e eu estou junto com estas pessoas,que estao sendo otimistas em relacao a este ano.2013 foi um ano de vitorias,mas de muitas catastrofes naturais,mortes,guerras civis.E espero que este Ano tudo isto mude.Se houver guerra que possamos entende o proximo,ama-lo.Se a catastrofes que possamos para de poluir o meio ambiente.Se Nos mudarmos coisas simples, gesto de nosso dia-a-dia com certezaa este 2014 sera melhor que 2013.Entao pensa nisso!Vai ver como dara resultado!Beijoos Language is a complex adaptive system: Speakers are agents who interact with each other, and their past and current interactions feed into speakers future behavior in complex ways.The idea that language should be analyzed as a complex adaptive system is gaining currency, particularly among those researchers who are developing models of language behavior (e.g., Smith, Kirby, & Brighton, 2003; Steels, 2000). Research groups that have come together in the Five Graces group share this view (e.g., Baxter, Blythe, Croft, & McKane, 2006; Ellis & Larsen-Freeman, 2006; Ke & Holland, 2006). The Five Graces group defines a complex adaptive system as follows: The system consists of multiple agents interacting with one another. The system is adaptive -- that is, agents behavior is based on their past interactions, and current and past interactions together feed back into future behavior. An agents behavior is the consequence of competing factors from a wide range of environmental affordances and constraints.The premier example of a model of a complex adaptive system is the evolutionary model originally developed and refined in biology by Charles Darwin. (...) we describe the theoretical basis of an application of this model to language behaviorin particular, the language change that naturally emerges from language behavior (Croft, 2000). A language is a complex adaptive system because of the way it is situated in its social context. Hexagon BinningHexagon binning is a bivariate histogram useful for visualizing the structure of data when they depend on two random variables. A simpler model, considering only one variable may have unaddressed, correlated errors, leading them to look simpler than they should. This is problematic because it may suggest spurious regularity. This error is typical in fitting algorithms that assume that $x$ is known perfectly and only $y$ is measured with uncertainty.The concept of hexagon binning is to tessellate the $xy$ plane over a certain range by a regular grid of hexagons. The number of data points falling in each bin is counted. The hexagons are plotted with color or radius varying in proportion to the observed data count in each bin. A hexagon tessellation is preferred over the square counterpart since hexagons have symmetry of nearest neighbors which is lacking in square bins. Moreover, hexagons are the polygon that can create a regular tessellation of the plane that have the largest number of sides. In terms of packing, a hexagon tessellation is 13% more efficient for covering the plane than squares. Hexagons are then less biased for displaying densities than other regular tessellations.The counts observed