How strongly do word reading times and lexical decision times correlate? Combining data from eye movement corpora and megastudies

We assess the amount of shared variance between three measures of visual word recognition latencies: eye movement latencies, lexical decision times and naming times. After partialling out the effects of word frequency and word length, two well-documented predictors of word recognition latencies, we see that 7-44% of the variance is uniquely shared between lexical decision times and naming times, depending on the frequency range of the words used. A similar analysis of eye movement latencies shows that the percentage of variance they uniquely share either with lexical decision times or with naming times is much lower. It is 5 – 17% for gaze durations and lexical decision times in studies with target words presented in neutral sentences, but drops to .2% for corpus studies in which eye movements to all words are analysed. Correlations between gaze durations and naming latencies are lower still. These findings suggest that processing times in isolated word processing and continuous text reading are affected by specific task demands and presentation format, and that lexical decision times and naming times are not very informative in predicting eye movement latencies in text reading once the effect of word frequency and word length are taken into account. The difference between controlled experiments and natural reading suggests that reading strategies and stimulus materials may determine the degree to which the immediacy-of-processing assumption and the eye-mind assumption apply. Fixation times are more likely to exclusively reflect the lexical processing of the currently fixated word in controlled studies with unpredictable target words rather than in natural reading of sentences or texts

The spread of epidemic disease on networks

The study of social networks, and in particular the spread of disease on networks, has attracted considerable recent attention in the physics community. In this paper, we show that a large class of standard epidemiological models, the so-called susceptible/infective/removed (SIR) models can be solved exactly on a wide variety of networks. In addition to the standard but unrealistic case of fixed infectiveness time and fixed and uncorrelated probability of transmission between all pairs of individuals, we solve cases in which times and probabilities are non-uniform and correlated. We also consider one simple case of an epidemic in a structured population, that of a sexually transmitted disease in a population divided into men and women. We confirm the correctness of our exact solutions with numerical simulations of SIR epidemics on networks.Comment: 12 pages, 3 figure

A method for robust time-reversal focusing in a fluctuating ocean

In recent years, the authors have demonstrated time-reversal mirrors (TRM) in the ocean. A focus of up to 30 km was achieved with low frequency (445 Hz) transmissions and the focal structure could be maintained over several days at a range of 15 km. However, the stable focus was limited to less than an hour with high frequency (3.5 kHz) transmissions due to the sensitive response of high frequency sound propagation to the medium fluctuations. In this study, an approach for robust time-reversal focusing is investigated based on a method developed for matched-field processing. Instead of using a single probe source pulse, the method makes use of several probe source pulses obtained over a certain period of time where each ping represents a different propagation condition of the medium. The back-propagation from a TRM weighted by a linear combination of the dominant singular vectors obtained from the signal matrix leads to stable focusing for a longer period of time than that with a single probe pulse. The proposed method is useful in non-static propagation conditions and when frequent probe signals are not available