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Significance: The human brain is a highly complex system with nonlinear, dynamic behavior. A majority of brain imaging studies employing functional near-infrared spectroscopy (fNIRS), however, have considered only the spatial domain and have ignored the temporal properties of fNIRS recordings. Methods capable of revealing nonlinearities in fNIRS recordings can provide new insights about how the brain functions. Aim: The temporal characteristics of fNIRS signals are explored by comprehensively investigating their fractal properties. Approach: Fractality of fNIRS signals is analyzed using scaled windowed variance (SWV), as well as using visibility graph (VG), a method which converts a given time series into a graph. Additionally, the fractality of fNIRS signals obtained under resting-state and task-based conditions is compared, and the application of fractality in differentiating brain states is demonstrated for the first time via various classification approaches. Results: Results from SWV analysis show the existence of high fractality in fNIRS recordings. It is shown that differences in the temporal characteristics of fNIRS signals related to task-based and resting-state conditions can be revealed via the VGs constructed for each case. Conclusions: fNIRS recordings, regardless of the experimental conditions, exhibit high fractality. Furthermore, VG-based metrics can be employed to differentiate rest and task-execution brain states.

PubMedID: 26739011 This paper aimed to analyze short-term changes in landscape pattern that primarily results from building development in the east coast of Mersin Province (Turkey). Three sites were selected. Ikonos (2003) and Quickbird (2009) images for these sites were classified, and land cover transformations were quantitatively analyzed using cross-tabulation of classification results. Changes in landscape structure were assessed by comparing the calculated values of area/edge and shape metrics for the earlier and later dates. Area/edge metrics included percentage of land and edge density, while shape metrics included perimeter-area ratio, fractal dimension, and related circumscribing circle (RCC) metrics. Orchards and buildings were dominating land cover classes. Variations in patch edge, size, and shapes were also analyzed and discussed. Degradation of prime agricultural areas due to building development and implications of such development on habitat fragmentation were highlighted. © 2016, Springer International Publishing Switzerland.

We present an analysis of areal mass density correlations in paper. Using {beta} radiography, the local mass density of laboratory paper sheets has been measured. The real space density autocorrelation function calculated from the data reveals a nontrivial power law type of correlations with the decay exponent being roughly independent of the basis weight of the sheets. However, for low densities we find that correlations may extend at least an order of magnitude beyond the fiber length, whereas for heavier paper they quickly die out. {copyright} {ital 1996 The American Physical Society.}