Modeling growth of total height using early data from forest inventories in fast growing Eucalyptus spp plantations

This work evaluated the growth trend represented by three biological models used for modeling forest growth and production (Schumacher; Chapman-Richards; Logistic). These curves were chosen because they are widely used by forest science professionals. The functions were adjusted under the hypothesis that there is influence of the initial, 6 and 12 month measurements on the shape of the production curves and, consequently, in the estimate of their parameters. The data that formed the adjustment basis were generated by the continuous monitoring performed at 6, 12, and 24 months and later at each 12 months in order to yield the growth patterns for the evaluated plantations. The results herein presented allow us to conclude that independently of the type of adjustment, the Chapman-Richards function was the one that exhibited the best statistics, with the BIAS values reduced in up to 30% when compared to the others. The Schumacher function presented the worst performance among the proposed criteria in this study. So, given the results obtained, we suggest a broader reflection about the growth and production issue, especially for the use of biometric models applied to forest production forecast, in which stability and adherence of the curves to the data are expected

Radial symmetry molding skull roundness: a human fetal MR study

The aim of this study consists in evaluating the morphological integration and molding shape of the human fetal craniofacial complex development on MR sagittal images. The sella point has been used as a reference point to build eleven dimensional parameters encompassing the craniofacial complex. Data and measurements obtained were statistically analyzed by PCA. The designed rays were significantly correlated, normally distributed and characterized by linearity over the overall fetal development. These findings showed that the craniofacial units are clustering together, whereas craniobasal and craniopharyngeal traits are spread. The data analysis supported the efficacy of specific morphological traits to evaluate differences emerging during the modeling growth processes. Skull modeling seems to be characterized by a rotational symmetry around the sella as inertial point. We firstly present the intriguing hypothesis through which the skull development grows along a dihedral angle symmetry made of a both rotational and reflection vector.

Modeling Growth and Resilience Among Military Personnel

The prospect that people can be resilient to—or even grow from—a stressful experience is an alluring possibility—especially so for soldiers and veterans. Some have proposed that deploying and military experiences provide soldiers with enduring mental resources and toughness that are protective for the rest of their lives. However, definitive evidence for growth and resilience among military personnel has proved elusive. Part of the unknowns about growth and resilience can be attributable to how people think about and model questions related to growth and resilience. In this chapter, the author provides two empirical examples—changes in depressive symptoms among veterans and changes in character strengths among deploying soldiers—to illustrate how different conceptualizations, methods, and analyses can dramatically change the inferences we make about growth and resilience. The demonstrations provide an increased understanding about methodological flexibility in the study of growth and resilience and some expectations about how and why individuals might change in response to adversity.

L-MMH: AN IMPROVED AND NOVEL MODEL FOR GROWTH

Proposing a function for modeling growth is an important development for the curve fitting of data. This study gives a derivation for a new mathematical equation for growth and reports some significant features of this model.

L-MMH: AN IMPROVED AND NOVEL MODEL FOR GROWTH

Proposing a function for modeling growth is an important development for the curve fitting of data. This study gives a derivation for a new mathematical equation for growth and reports some significant features of this model.