Lorenz-like systems and classical dynamical equations with memory forcing: a new point of view for singling out the origin of chaos

A novel view for the emergence of chaos in Lorenz-like systems is presented. For such purpose, the Lorenz problem is reformulated in a classical mechanical form and it turns out to be equivalent to the problem of a damped and forced one dimensional motion of a particle in a two-well potential, with a forcing term depending on the ``memory'' of the particle past motion. The dynamics of the original Lorenz system in the new particle phase space can then be rewritten in terms of an one-dimensional first-exit-time problem. The emergence of chaos turns out to be due to the discontinuous solutions of the transcendental equation ruling the time for the particle to cross the intermediate potential wall. The whole problem is tackled analytically deriving a piecewise linearized Lorenz-like system which preserves all the essential properties of the original model.Comment: 48 pages, 25 figure

Death and Display in the North Atlantic: The Bronze and Iron Age Human Remains from Cnip, Lewis, Outer Hebrides

YesThis paper revisits the series of disarticulated human remains discovered during the 1980s excavations of the Cnip wheelhouse complex in Lewis. Four fragments of human bone, including two worked cranial fragments, were originally dated to the 1st centuries BC/AD based on stratigraphic association. Osteoarchaeological reanalysis and AMS dating now provide a broader cultural context for these remains and indicate that at least one adult cranium was brought to the site more than a thousand years after the death of the individual to whom it had belonged

A Comparative Study Between Weighing and Image Analysis Techniques for Predicting the Amount of Deposited Electrospun Nanofibres

Weighing and direct measurement are currently the two most common techniques used for estimating the amount of deposited nanofibres in electrospinning process. Nevertheless, due to its extremely small fibre size and mass, the task of measuring the weight or thickness of an electrospun nanofibres membrane is difficult and the results are arguable. This study evaluates the effectiveness of using greyscale image analysis for predicting the amount of deposited nanofibres compared to weighing technique. Polyvinyl alcohol electrospun nanofibres were collected at different deposition times on A4 black paper substrates. The substrates were weighed before and after deposition process and then scanned into 8 bit greyscale images. Analyses were carried out using ImageJ software, statistical analysis, high speed camera and scanning electron microscopy. At long deposition times, both techniques showed significant correlations between the measured values and deposition times. However, at short deposition times the weighing technique was found unreliable (p>0.05) compared to image analysis technique due to insignificant fibre masses compared to the weight variation of the substrates. Results suggest that image analysis technique was a better option to be used compared to weighing technique. This technique has the potential to be used as an automated online quality control in electrospun nanofibres manufacture

An investigation of using grey scale image analysis for predicting the amount of deposited electrospun nanofibres

When electrospinning, the amount of electrospun fibres deposited is difficult to determine due to the extremely small size and light weight of the fibres. Several methods have been used to predict the amount of deposited fibres including weighing, imaging and direct measurement. Although these methods work to a certain extent, they all have drawbacks that make them unsuitable for commercial scale process control. The methods are generally time consuming, destructive and only examine a small area of web. In this study, an image analysis method is used to predict the amount of electrospun fibres deposited over a significant area. When images of electrospun fibres are converted into grey scale images, it is suggested that the amount of fibres deposited can be predicted by measuring the grey scale intensity. A conventional weighing method was used to validate the image analysis results. The weighing method was found wanting when the deposition time was short (p>0.05). This was because the measured fibre masses were insignificant compared to the weight variation of the collector substrates. Statistical analyses showed that there were a strong correlation between grey scale intensity and deposition time especially at short deposition times. The results suggest that image analysis method could be used to predict the amount of deposited electrospun nanofibres. Further test on different polymers and different coloured substrates showed that the method was still capable to distinguish the samples. The developed method has the potential to be applied as an in-line non-destructive quality control method for electrospun fibre manufacture