The drinking behaviours of college students have posed significant public health concerns for several generations. However, the dynamics of campus drinking have not been analysed using mathematical models. An epidemiological model capturing the dynamics of campus drinking is used to study how the 'disease' of drinking is spread on campus. The model suggests that the reproductive numbers are not sufficient to predict whether drinking behaviour will persist on campus and that the pattern of recruiting new members plays a significant role in the reduction of campus alcohol problems. In particular, campus alcohol abuse may be reduced by minimizing the ability of problem drinkers to directly recruit non-drinkers.
A modified SIR model is used to explain the transmission of Mycobacterium ulcerans (MU) and its dependence on arsenic (As) environments. Some studies have suggested that As plays a major role in the spread and prevalence of buruli ulcer (BU). In addition, it has been hypothesized that a vector in the form of a water-bug plays a key role in the epidemiology of BU. We develop an epidemiological model based on these assumptions for the dynamics and prevalence of BU and show that As positively induces the growth and spread of MU.
Given a list of real numbers , we determine the conditions under which will form the spectrum of a dense n × n singular symmetric matrix. Based on a solvability lemma, an algorithm to compute the elements of the matrix is derived for a given list and dependency parameters. Explicit computations are performed for 5 n and to illustrate the result.
Wavelet denoising of medical images relies on the technique of thresholding. A disadvantage of this method is that even though it adequately removes noise in an image, it introduces unwanted artifacts into the image near discontinuities due to Gibbs phenomenon. A total variation method for enhancing chest radiographs is implemented. The approach focuses on lung nodules detection using chest radiographs (CRs) and the method achieves high image sensitivity and could reduce the average number of false positives radiologists encounter.
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