Regeneración natural de nueve especies maderables en un bosque intervenido de la Amazonia Boliviana

Un aspecto fundamental del manejo forestal sostenible, es el mantenimiento de la regeneración natural en los bosques aprovechados. A corto y largo plazo, el aprovechamiento forestal tiene varias consecuencias, sobre la regeneración natural de las especies forestales. Esta investigación, compara la abundancia de la regeneración natural y la distribución espacial de plántulas de nueve especies maderables, entre un bosque aprovechado y un testigo. La abundancia y estructura espacial, fue determinada mediante 55 parcelas de muestreo anidadas (20 x 20 m, 10 x 10 m), estas fueron distribuidas en 180 hectáreas en cada condición de bosque evaluado. Dentro de las parcelas de 10 x 10 m, se registraron las categorías: plántula, brinzal y latizal. En las parcelas de 20 x 20, se midieron los árboles semilleros con DAP > 20 cm. En bosque aprovechado C. racemosa, T. altissima y A. lecointei mostraron mayor abundancia total. Según categorías de regeneración, la abundancia de P. corymbosum resultó mayor en bosque aprovechado; pero en las especies C. racemosa, T. altissima, D. odorata y C. micrantha fue mayor en el bosque testigo. La abundancia de A. lecointei, P. heterophylla y Virola sp. no difirió entre sitios. Espacialmente, solo A. lecointei y Virola sp mostraron patrones diferentes entre condiciones de bosque estudiados. Estos resultados, permiten concluir que el aprovechamiento forestal, no modifica significativamente la abundancia y estructura espacial de la regeneración de todas las especies forestales, por lo que, las intensidades de extracción moderada no comprometería el potencial de la regeneración natural en bosques manejados.

Automatic eye blink detection using consumer web cameras

This research aims to advance blinking detection in the context of work activity. Rather than patients having to attend a clinic, blinking videos can be acquired in a work environment, and further automatically analyzed. Therefore, this paper presents a methodology to perform the automatic detection of eye blink using consumer videos acquired with low-cost web cameras. This methodology includes the detection of the face and eyes of the recorded person, and then it analyzes the low-level features of the eye region to create a quantitative vector. Finally, this vector is classified into one of the two categories considered —open and closed eyes— by using machine learning algorithms. The effectiveness of the proposed methodology was demonstrated since it provides unbiased results with classification errors under 5%

Forecasting human entrances at a commercial store using facial recognition data

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Segmentação de imagens fetais com potencial para desenvolvimento de ferramentas de apoio ao diagnóstico

Programa Doutoral em Engenharia Eletrónica e de Computadores

An R package for the integrated analysis of metabolomics and spectral data

Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.

Proceedings of the Academy of Natural Sciences of Philadelphia.

v.45 (1893)

Proceedings of the Academy of Natural Sciences of Philadelphia.

v.5 (1850-1851)

Proceedings of the Academy of Natural Sciences of Philadelphia.

v.34 (1882):[Lacks:pg.76-77]

Proceedings of the Academy of Natural Sciences of Philadelphia.

v.50 (1898)

Proceedings of the Academy of Natural Sciences of Philadelphia.

v.73 (1921)

Proceedings of the Academy of Natural Sciences of Philadelphia.

v.11 (1859)

Proceedings of the Academy of Natural Sciences of Philadelphia.

v.31 (1879)

Proceedings of the Academy of Natural Sciences of Philadelphia.

v.44 (1892)

Proceedings of the Academy of Natural Sciences of Philadelphia.

v.3 (1846-1847)