Instituto Politécnico Nacional

About: Instituto Politécnico Nacional is a education organization based out in Mexico City, Mexico. It is known for research contribution in the topics: Population & Control theory. The organization has 43351 authors who have published 63315 publications receiving 938532 citations. The organization is also known as: Instituto Politécnico Nacional & Instituto Politecnico Nacional.

Recommendations for Medical Management of Adult Lead Exposure

Abstract: Research conducted in recent years has increased public health concern about the toxicity of lead at low dose and has supported a reappraisal of the levels of lead exposure that may be safely tolerated in the workplace. In this article, which appears as part of a mini-monograph on adult lead exposure, we summarize a body of published literature that establishes the potential for hypertension, effects on renal function, cognitive dysfunction, and adverse female reproductive outcome in adults with whole-blood lead concentrations 5 μg/dL. Chelation may have an adjunctive role in the medical management of highly exposed adults with symptomatic lead intoxication but is not recommended for asymptomatic individuals with low blood lead concentrations.

Particle swarm based Data Mining Algorithms for classification tasks

Abstract: Particle Swarm Optimisers are inherently distributed algorithms where the solution for a problem emerges from the interactions between many simple individual agents called particles. This article proposes the use of the Particle Swarm Optimiser as a new tool for Data Mining. In the first phase of our research, three different Particle Swarm Data Mining Algorithms were implemented and tested against a Genetic Algorithm and a Tree Induction Algorithm (J48). From the obtained results, Particle Swarm Optimisers proved to be a suitable candidate for classification tasks. The second phase was dedicated to improving one of the Particle Swarm optimiser variants in terms of attribute type support and temporal complexity. The data sources here used for experimental testing are commonly used and considered as a de facto standard for rule discovery algorithms reliability ranking. The results obtained in these domains seem to indicate that Particle Swarm Data Mining Algorithms are competitive, not only with other evolutionary techniques, but also with industry standard algorithms such as the J48 algorithm, and can be successfully applied to more demanding problem domains.

Numerical experiments on strongly turbulent thermal convection in a slender cylindrical cell

Abstract: Numerical experiments are conducted to study high-Rayleigh-number convective turbulence (Ra ranging from 2 × 10 6 up to 2 × 10 11 ) in a Γ = 1/2 aspect-ratio cylindrical cell heated from below and cooled from above and filled with gaseous helium (Pr = 0.7). The numerical approach allows three-dimensional velocity, vorticity and temperature fields to be analysed. Furthermore, several numerical probes are placed within the fluid volume, permitting point-wise velocity and temperature time series to be extracted. Taking advantage of the data accessibility provided by the direct numerical simulation the flow dynamics has been explored and separated into its mean large-scale and fluctuating components, both in the bulk and in the boundary layer regions