Link Prediction in Complex Network via Penalizing Noncontribution Relations of Endpoints

Similarity based link prediction algorithms become the focus in complex network research. Although endpoint degree as source of influence diffusion plays an important role in link prediction, some noncontribution links, also called noncontribution relations, involved in the endpoint degree serve nothing to the similarity between the two nonadjacent endpoints. In this paper, we propose a novel link prediction algorithm to penalize those endpoints’ degrees including many null links in influence diffusion, namely, noncontribution relations penalization algorithm, briefly called NRP. Seven mainstream baselines are introduced for comparison on nine benchmark datasets, and numerical analysis shows great improvement of accuracy performance, measured by the Area Under roc Curve (AUC). At last, we simply discuss the complexity of our algorithm

Two Solar Tornadoes Observed with the Interface Region Imaging Spectrograph

The barbs or legs of some prominences show an apparent motion of rotation, which are often termed solar tornadoes. It is under debate whether the apparent motion is a real rotating motion, or caused by oscillations or counter-streaming flows. We present analysis results from spectroscopic observations of two tornadoes by the Interface Region Imaging Spectrograph. Each tornado was observed for more than 2.5 hours. Doppler velocities are derived through a single Gaussian fit to the Mg~{\sc{ii}}~k~2796\AA{}~and Si~{\sc{iv}}~1393\AA{}~line profiles. We find coherent and stable red and blue shifts adjacent to each other across the tornado axes, which appears to favor the interpretation of these tornadoes as rotating cool plasmas with temperatures of $10^4$ K-$10^5$ K. This interpretation is further supported by simultaneous observations of the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory, which reveal periodic motions of dark structures in the tornadoes. Our results demonstrate that spectroscopic observations can provide key information to disentangle different physical processes in solar prominences.Comment: 14 figures, accepted by Ap

Inverse Projection Representation and Category Contribution Rate for Robust Tumor Recognition

Sparse representation based classification (SRC) methods have achieved remarkable results. SRC, however, still suffer from requiring enough training samples, insufficient use of test samples and instability of representation. In this paper, a stable inverse projection representation based classification (IPRC) is presented to tackle these problems by effectively using test samples. An IPR is firstly proposed and its feasibility and stability are analyzed. A classification criterion named category contribution rate is constructed to match the IPR and complete classification. Moreover, a statistical measure is introduced to quantify the stability of representation-based classification methods. Based on the IPRC technique, a robust tumor recognition framework is presented by interpreting microarray gene expression data, where a two-stage hybrid gene selection method is introduced to select informative genes. Finally, the functional analysis of candidate's pathogenicity-related genes is given. Extensive experiments on six public tumor microarray gene expression datasets demonstrate the proposed technique is competitive with state-of-the-art methods.Comment: 14 pages, 19 figures, 10 table

Dynamics of Quincke Particles with Tunable Memory

Memory can remarkably modify the collective behaviors of active particles. In Quincke systems driven by electric fields, the memory of particles, in the form of relaxation of polarization, has been taken to account for the run-and-tumble behaviors under periodical driving. However, we show that the memory of Quincke particles is generally a product of multiple mechanisms including inertia and depolarization. The memory of Quincke particles can be tuned and enhanced by the parameters of electric fields. Moreover, the interplay between inertia and propulsion results in a frequency-dependent mobility such that a balance between activity and attraction can be reached, giving rise to the formation of dense active clusters. The memory in dense clusters becomes even more significant because of the strong electrostatic interactions. Combining the tunable memory and the adjustable mobility, a rich variety of collective motions can be realized. These findings offer new insights into the dynamics of active matter and have broad interests in periodically driven active systems.Comment: 14 pages,6 figures, 3 movie

Diaqua­bis­(4-carb­oxy-2-ethyl-1H-imidazole-5-carboxyl­ato-κ2 N 3,O 4)zinc N,N-dimethyl­formamide disolvate

In the title compound, [Zn(C7H7N2O4)2(H2O)2]·2C3H7NO, the ZnII ion, which lies on a center of inversion, is coordinated by two O atoms and two N atoms from two 4-carboxy-2-ethyl-1H-imid­azole-5-carboxyl­ato anions and two water O atoms in an octa­hedral environment, Each 4-carboxy-2-ethyl-1H-imid­azole-5-carboxyl­ato ligand adopts a bidentate chelating mode to the ZnII ion, forming two five-membered metalla rings. In the crystal, a two-dimensional framework parallel to (010) is formed by N—H⋯O and O—H⋯O hydrogen bonds