Wavelet entropy as a measure of ventricular beat suppression from the electrocardiogram in atrial fibrillation

A novel method of quantifying the effectiveness of the suppression of ventricular activity from electrocardiograms (ECGs) in atrial fibrillation is proposed. The temporal distribution of the energy of wavelet coefficients is quantified by wavelet entropy at each ventricular beat. More effective ventricular activity suppression yields increased entropies at scales dominated by the ventricular and atrial components of the ECG. Two studies are undertaken to demonstrate the efficacy of the method: first, using synthesised ECGs with controlled levels of residual ventricular activity, and second, using patient recordings with ventricular activity suppressed by an average beat template subtraction algorithm. In both cases wavelet entropy is shown to be a good measure of the effectiveness of ventricular beat suppression

A cognitive architecture for learning in reactive environments

Previous research in machine learning has viewed the process of empirical discovery as search through a space of 'theoretical' terms. In this paper, we propose a problem space for empirical discovery, specifying six complementary operators for defining new terms that ease the statement of empirical laws. The six types of terms include: numeric attributes (such as PV/T); intrinsic properties (such as mass); composite objects (such as pairs of colliding balls); classes of objects (such as acids and alkalis); composite relations (such as chemical reactions); and classes of relations (such as combustion/oxidation). We review existing machine discovery systems in light of this framework, examining which parts of the problem space were, covered by these systems. Finally, we outline an integrated discovery system (IDS) we are constructing that includes all six of the operators and which should be able to discover a broad range of empirical laws

When Men Murder Women: An Analysis of 2004 Homicide Data

The Violence Policy Center (VPC) today released "When Men Murder Women: An Analysis of 2004 Homicide Data". This annual report details national and state-by-state information on female homicides involving one female murder victim and one male offender. The VPC releases the study each year to coincide with Domestic Violence Awareness Month in October. In 2004, according to the most recent data available from the Federal Bureau of Investigation's unpublished Supplementary Homicide Report, firearms were the most common weapon used by males to murder females (811 of 1,663 homicides or 49 percent). Of these, 72 percent (582 of 811) were committed with handguns. In cases where the victims knew their offenders, 62 percent of female homicide victims (966 of 1,563) were wives or intimate acquaintances of their killers. Alaska ranks first in the nation in the rate of women killed by men. Ranked behind Alaska are: New Mexico, Wyoming, Louisiana, Nevada, South Carolina, Georgia, Oklahoma, Kentucky, and Tennessee (see chart below). Nationally, the rate of women killed by men in single victim/single offender instances was 1.29 per 100,000.VPC Legislative Director Kristen Rand states, "These numbers should serve as a wake-up call to the states with the highest rates of female homicide that more needs to be done to protect women.

When Men Murder Women: An Analysis of 2005 Homicide Data

Contains national and state information on homicides involving one female victim and one male offender. Identifies the ten states with the highest rates of female homicide

Colour for behavioural success

Colour information not only helps sustain the survival of animal species by guiding sexual selection and foraging behaviour but also is an important factor in the cultural and technological development of our own species. This is illustrated by examples from the visual arts and from state-of-the-art imaging technology, where the strategic use of colour has become a powerful tool for guiding the planning and execution of interventional procedures. The functional role of colour information in terms of its potential benefits to behavioural success across the species is addressed in the introduction here to clarify why colour perception may have evolved to generate behavioural success. It is argued that evolutionary and environmental pressures influence not only colour trait production in the different species but also their ability to process and exploit colour information for goal-specific purposes. We then leap straight to the human primate with insight from current research on the facilitating role of colour cues on performance training with precision technology for image-guided surgical planning and intervention. It is shown that local colour cues in two-dimensional images generated by a surgical fisheye camera help individuals become more precise rapidly across a limited number of trial sets in simulator training for specific manual gestures with a tool. This facilitating effect of a local colour cue on performance evolution in a video-controlled simulator (pick-and-place) task can be explained in terms of colour-based figure-ground segregation facilitating attention to local image parts when more than two layers of subjective surface depth are present, as in all natural and surgical images

The Apollo 14 docking anomaly

Six docking attempts were required to achieve initial latch engagement during the Apollo 14 translunar docking event. Although subsequent performance of the docking hardware was normal, the docking probe was retained for a thorough postflight investigation. Pertinent design details of the docking system, the mission events related to the anomaly, and a discussion of the postflight investigation of the cause of the anomaly are presented