Cardiac output and leg and arm blood flow during incremental exercise to exhaustion on the cycle ergometer

[EN] To determine central and peripheral hemodynamic responses to upright leg cycling exercise, nine physically active men underwent measurements of arterial blood pressure and gases, as well as femoral and subclavian vein blood flows and gases during incremental exercise to exhaustion (Wmax). Cardiac output (CO) and leg blood flow (BF) increased in parallel with exercise intensity. In contrast, arm BF remained at 0.8 l/min during submaximal exercise, increasing to 1.2 +/- 0.2 l/min at maximal exercise (P < 0.05) when arm O(2) extraction reached 73 +/- 3%. The leg received a greater percentage of the CO with exercise intensity, reaching a value close to 70% at 64% of Wmax, which was maintained until exhaustion. The percentage of CO perfusing the trunk decreased with exercise intensity to 21% at Wmax, i.e., to approximately 5.5 l/min. For a given local Vo(2), leg vascular conductance (VC) was five- to sixfold higher than arm VC, despite marked hemoglobin deoxygenation in the subclavian vein. At peak exercise, arm VC was not significantly different than at rest. Leg Vo(2) represented approximately 84% of the whole body Vo(2) at intensities ranging from 38 to 100% of Wmax. Arm Vo(2) contributed between 7 and 10% to the whole body Vo(2). From 20 to 100% of Wmax, the trunk Vo(2) (including the gluteus muscles) represented between 14 and 15% of the whole body Vo(2). In summary, vasoconstrictor signals efficiently oppose the vasodilatory metabolites in the arms, suggesting that during whole body exercise in the upright position blood flow is differentially regulated in the upper and lower extremities.

El método IRDB: aprendizaje incremental para el reconocimiento de caras

[ES]En un problema complejo como es el reconocimiento de caras, donde se utilizan espacios de representación de un número alto de dimensiones, es de gran importancia emplear toda la información disponible. En particular, habrá casos en los que, estando el sistema de reconocimiento en funcionamiento, se acumulará una gran cantidad de información en forma de imágenes faciales con su etiqueta asociada. En este trabajo se propone un algoritmo para utilizar esta información, caso de estar disponible. El algoritmo presenta la principal característica de ser incremental, con lo que la e ciencia del mismo no degenera con el número de imágenes acumuladas...

An incremental learning algorithm for face recognition

[EN]In face recognition, where high-dimensional representation spaces are generally used, it is very important to take advantage of all the available information. In particular, many labelled facial images will be accumulated while the recognition system is functioning, and due to practical reasons some of them are often discarded. In this paper, we propose an algorithm for using this information. The algorithm has the fundamental characteristic of being incremental. On the other hand, the algorithm makes use of a combination of classification results for the images in the input sequence. Experiments with sequences obtained with a real person detection and tracking system allow us to analyze the performance of the algorithm, as well as its potential improvements.