Electrocardiographic manifestation of the middle fibers/septal fascicle block: a consensus report

There are fibers in the left ventricle (LV) (LV middle network) that in around one third of cases may be considered a true septal fascicle that arises from the common left bundle. Its presence and the evidence that there are 3 points of activation onset in the LV favor the quadrifascicular theory of the intravantricular activation of both ventricles. Since the 70s, different authors have suggested that the block of the left middle fibers (MS)/left septal fascicle may explain different electrocardiographic (ECG) patterns. The 2 hypothetically based criteria that are in some sense contradictory include: a) the lack of septal "q" wave due to first left and later posteriorly shifting of the horizontal plane loop and b) the presence of RS in lead V-2 (V-1-V-2) due to some anterior shifting of the horizontal plane vectorcardiogram loop. However, there are many evidence that the lack of septal q waves can be also explained by predivisional first-degree left bundle-branch block and that the RS pattern in the right precordial leads may be also explained by first-degree right bundle-branch block. The transient nature of these patterns favor the concept that some type of intraventricular conduction disturbance exists but a doubt remains about its location. Furthermore, the RS pattern could be explained by many different normal variants. To improve our understanding whether these patterns are due to MF/left septal fascicle block or other ventricular conduction disturbances (or both), it would be advisable: 1) To perform more histologic studies (heart transplant and necropsy) of the ventricular conduction system; 2) To repeat prior experimental studies using new methodology/technology to isolate the MF; and 3) To change the paradigm: do not try to demonstrate if the block of the fibers produces an ECG change but to study with new electroanatomical imaging techniques, if these ECG criteria previously described correlate or not with a delay of activation in the zone of the LV that receives the activation through these fibers or in other zones. (C) 2012 Elsevier Inc. All rights reserved.

A system for classification of time-series data from industrial non-destructive device

This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.