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Detecting the presence of genetically modified plants (adventitious presence of unwanted transgenic plants, AP) from outcrossing species such as maize requires a method that lowers laboratory costs without losing precision. Group testing is a procedure in which groups that contain several units (plants) are analysed without having to inspect individual plants, with the purpose of estimating the prevalence of AP in a population at a low cost without losing precision. When pool (group) testing is used to estimate the prevalence of AP (p), there are sampling procedures for calculating a confidence interval (CI); however, they usually do not ensure precision in the estimation of p. This research proposes a method to determine the number of pools (g), given a pool size (k), that ensures precision in the estimated proportion of AP (that is, it ensures a narrow CI). In addition, the study computes the maximum likelihood estimator of p under pool testing and its exact CI, considering the detection limit of the laboratory, d, and the concentration of AP per unit (c). The proposed sample procedure involves two steps: (1) obtain a sample size that guarantees that the mean width of the CI (w) is narrower than the desired width (v); and (2) iteratively increase the sample size until w is smaller than the desired width (v) with a specified degree of certainty (g). Simulated data were created and tables are presented showing the different possible scenarios that a researcher may encounter. An R program is given and explained that will reproduce the results and make it easy for the researcher to create other scenarios. [ABSTRACT FROM AUTHOR]

The quarantine is an intervention procedure to control the spread of infectious diseases among farms. However, the dilemma persists of which and how many farms need to be quarantined to achieve effective control, or at least, to make the losses minimum. In the present paper we propose an SEIR modified stochastic model to decide with high objectivity and rapidity the best quarantine strategy. Three quarantine strategies with different percentage of quarantine farms are compared by means of Monte Carlo simulation. We find that the minimum final size of an epidemic is obtained if a small fraction of farms with a high number of edges is quarantined. In addition, the proposed model was applied to a set of real data for avian influenza reported in the northwest of Tehuacán Valley, Puebla, México in 1995. [ABSTRACT FROM AUTHOR]

In the genetic breeding of plants and animals, it is common to make the evaluation of treatments in diverse environmental conditions, emerging the necessity to project researches in a series of similar experiments, such as in the Griffing's designs. In such case, in most of the occasions, the combined analysis of the series of experiments, including the diallel crosses, has been done on the basis of a fixed effects lineal model, in spite of the random nature of the general and specific combining abilities in the diallel crosses experiments. Therefore, in the present work for Griffing's designs one and three, established in complete blocks of randomized designs, the combined empirical best linear unbiased predictors are derived from the general combining ability effects, based on the estimation methodology of random effects in a mixed effects model. Additionally, a computational algorithm is presented, in SAS/IML, for the combined analysis of experiments. [ABSTRACT FROM AUTHOR]

En el mejoramiento genético de plantas y animales es común realizar la evaluación de tratamientos en diversas condiciones ambientales, surgiendo la necesidad de proyectar investigaciones en una serie de experimentos similares, tales como en los diseños de Griffing. En tal caso, en la mayoría de las ocasiones, el análisis combinado de las series de experimentos, incluyendo los de cruzas dialélicas, se han efectuado con un modelo lineal de efectos fijos, a pesar de la naturaleza aleatoria de la aptitud combinatoria general y específica en los experimentos de cruzas dialélicas. Por ello, en el presente trabajo, para los diseños I y III de Griffing establecidos en experimentos de bloques completos al azar, se derivan los mejores predictores lineales e insesgados combinados de los efectos de aptitud combinatoria general, con base en la metodología de estimación de efectos aleatorios en un modelo de efectos mixtos. Adicionalmente, se presenta un algoritmo computacional, en SAS/IML, para el análisis combinado de experimentos. [ABSTRACT FROM AUTHOR]

This article compares the educational level of full-time faculty members at Universidad de Colima with their teaching and academic performance, based on an analysis of variance and canonical discrimination in the 2001-2004 period. During each one of the four years, in terms of teaching performance, no significant difference was found in educational level: professors with doctoral, master's and undergraduate degrees were statistically equal in teaching performance. Educational level was found to have a direct effect, however, on academic performance: the more education the teacher had, the better his academic performance. The predominant factors were teaching duties and research activities, thus minimizing the influence of tutoring and collegiate action. [ABSTRACT FROM AUTHOR]