Caracterização dos dejetos de caprinos: reciclagem energética e de nutrientes

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

Desempenho e características da carcaça e da carne de cordeiros terminados em confinamento com dietas contendo silgens de resíduos de peixes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

In Celebration of the 75th Birthday of Professor CNR Rao

Professor C. N. R. Rao will celebrate his 75th birthday in June 2009. As one of the world's foremost solid-state and materials chemists, he has had an enormous influence on generations of chemists throughout India and the world. Celebrations of Professor Rao's 75th birthday started already last June and will culminate on June 30, 2009. As part of these celebrations and to give tribute to Professor Rao's illustrious career and contributions to the chemistry community, this special issue in honor of this occasion includes 27 invited contributions from top scientists throughout the world, including a special

Cramer-Rao bounds for source localization in shallow ocean with generalized Gaussian noise

Localization of underwater acoustic sources is a problem of great interest in the area of ocean acoustics. There exist several algorithms for source localization based on array signal processing.It is of interest to know the theoretical performance limits of these estimators. In this paper we develop expressions for the Cramer-Rao-Bound (CRB) on the variance of direction-of-arrival(DOA) and range-depth estimators of underwater acoustic sources in a shallow range-independent ocean for the case of generalized Gaussian noise. We then study the performance of some of the popular source localization techniques,through simulations, for DOA/range-depth estimation of underwater acoustic sources in shallow ocean by comparing the variance of the estimators with the corresponding CRBs.

Cramer-Rao-Type Bounds for Sparse Bayesian Learning

In this paper, we derive Hybrid, Bayesian and Marginalized Cramer-Rao lower bounds (HCRB, BCRB and MCRB) for the single and multiple measurement vector Sparse Bayesian Learning (SBL) problem of estimating compressible vectors and their prior distribution parameters. We assume the unknown vector to be drawn from a compressible Student-prior distribution. We derive CRBs that encompass the deterministic or random nature of the unknown parameters of the prior distribution and the regression noise variance. We extend the MCRB to the case where the compressible vector is distributed according to a general compressible prior distribution, of which the generalized Pareto distribution is a special case. We use the derived bounds to uncover the relationship between the compressibility and Mean Square Error (MSE) in the estimates. Further, we illustrate the tightness and utility of the bounds through simulations, by comparing them with the MSE performance of two popular SBL-based estimators. We find that the MCRB is generally the tightest among the bounds derived and that the MSE performance of the Expectation-Maximization (EM) algorithm coincides with the MCRB for the compressible vector. We also illustrate the dependence of the MSE performance of SBL based estimators on the compressibility of the vector for several values of the number of observations and at different signal powers.

C. N. R. Rao and the Growth of Solid State and Materials Chemistry as a Central Domain of Research

In celebrating Professor C. N. R. Rao's 80th birthday, this article recalls his singular contributions to solid state and materials chemistry for about sixty years. In so doing, the article also traces the growth of the field as a central domain of research in chemical sciences from its early origins in Europe. Although Rao's major work lies in solid state and materials chemistry - a field which he started and nurtured in India while its importance was being recognized internationally - his contributions to other areas of chemistry (and physics), viz., molecular spectroscopy, phase transitions, fullerenes, graphene, nanomaterials and multiferroics are equally significant. Illustrative examples of his work devoted to rare earth and transition metal oxides, defects and nonstoichiometry, metal-insulator transitions, investigation of crystal and electronic structures of a variety of solids by means of electron microscopies and photoelectron spectroscopy, superconducting cuprates, magnetoresistive manganites, multiferroic metal oxides of various structures and, last but not the least, development of new strategies for chemical synthesis of a wide variety of solids including nanomaterials and framework solids in different dimensionalities, are highlighted. The article also captures his exemplary role as a science teacher, science educationist and institution builder in post-Independence India.

Residuos de plaguicidas en carne bovina de exportación en el Matadero Industrial Amerrisque

El presente trabajo se realizó en el matadero Amerrisque ubicado a la altura del km 128 carretera el Rama a 130 metros sobre e1 nivel del mar con el objetivo de evaluar los residuos de plaguicidas en carne bovina de exportación. Los datos fueron recopilados de la matanza diaria realizada en dicho matadero a partir del mes de enero de 1987 al mes de diciembre de 1992 a excepción de los meses de marzo, abril, agosto y noviembre del año 1989, de igual forma el año 1990, debido a que los registros ya para este año se encontraron incompletos. Las variables en estudio fueron: Niveles de contaminación aceptable y no aceptable para la exportación, procedencia de dichas carnes, plaguicidas que mayormente se acumulan en 1a carne y las pérdidas económicas. El procedimiento analítico se realizó por medio de una distribución de frecuencias, se hizo uso de medias como estadística descriptiva y también se determinó el rango. Como resultado del presente estudio observamos que la matanza industrial efectuada para los cinco años en estudio fue de 142,919 cabezas, de éstas 18,434 resultaron contaminada con un promedio de contaminación de 0.059 partes por millón, dejándose de percibir USA $ 10,497 dólares.