The
transport of nanoparticles in semiflexible networks, which
form diverse principal structural components throughout living systems,
is important in biology and biomedical applications. By combining
large-scale molecular simulations as well as theoretical analysis,
we demonstrate here that nanoparticles in polymer networks with semiflexible
strands possess enhanced heterogeneous diffusion characterized by
more evident hopping dynamics. Particularly, the hopping energy barrier
approximates to linear dependence on confinement parameters in the
regime of moderate rigidity, in contrast to the quadratic dependence
of both its soft and hard counterparts. This nonmonotonic feature
can be attributed to the competition between the conformation entropy
and the bending energy regulated by the chain rigidity, captured by
developing an analytical model of a hopping energy barrier. Moreover,
these theoretical results agree reasonably well with previous experiments.
The findings bear significance in unraveling the fundamental physics
of substance transport confined in network-topological environments
and would provide an explanation for the dynamics diversity of nanoparticles
within various networks, biological or synthetic.
The shapes of colloidal particles are crucial to the self-assembled superstructures. Understanding the relationship between the shapes of building blocks and the resulting crystal structures is an important fundamental question....
Abstract:In view of the low accuracy and uncertainty of the traditional rape plant disease recognition relying on a single feature, this paper puts forward a rape plant disease recognition method based on Dempster-Shafer (D-S) evidence theory and multi-feature fusion. Firstly, color matrix and gray-level co-occurrence matrix are extracted as two kinds of features from rape plant images after processing. Then by calculating the Euclidean distance between the test samples and training samples, the basic probability assignment function can be constructed. Finally, the D-S combination rule of evidence is used to achieve fusion, and final recognition results are given by using the variance. This method is used to collect rape plant images for disease recognition, and recognition rate arrives at 97.09%. Compared with other methods, experimental results show that the method is more effective and with lower computational complexity.
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