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Direct and indirect networks showed non-trivial differences with respect to connectivity, contact distribution, and super-spreaders identification.
By exploring the geometry of contact distribution at protein-protein interfaces, we provide an improved model of binding energy.
Results from the different comparisons reveal also a major influence of the pad topography and consequently the contact distribution.
The result is based on the comparison of common summary statistics like the pair correlation function and the spherical contact distribution function.
In addition, when the particle particle contact distribution is normalized to the average number of particle contacts, the distribution is statistically invariant with volume fraction.
The first method employs spherical contact distribution functions allowing macrodispersion analysis for micrographs with thick sections or films previously requiring modification for analysis.
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The three-dimensional particle size distribution (PSD) and the particle particle contact distributions were determined.
We identified 7 different contact profiles on the basis of a cluster analysis of different individual contact distributions.
The structural data we used are the cumulative contact distributions based on the Euclidean distances among alpha carbons, the Cutoff Scanning Matrix (CSM).
To further characterize chromosomal contacts around cohesin/CTCF binding sites, we next studied the average contact distributions around these sites using high-resolution quantitative analysis of Hi-C maps.
We investigate the virus dissemination process and compare it with dissemination in networks which have exponential and normal contact distributions, as well as in a social model without time-dependent interactions.
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