Tris(1,10-phenanthroline-κ2 N,N′)nickel(II) bis­(2,4,5-tricarb­oxy­benzo­ate) monohydrate

In the title compound, [Ni(C12H8N2)3](C10H5O8)2·H2O, the NiII cation is coordinated by six N atoms of the three bidentate chelating 1,10-phenanthroline ligands in a slightly distorted octa­hedral coordination geometry. The Ni—N bond lengths range from 2.074 (2) to 2.094 (2) Å. The dihedral angles between the three chelating NCCN groups to each other are 85.71 (3), 73.75 (2) and 85.71 (3)°, respectively. The Ni cation, the phenyl ring of the 1,10-phenanthroline ligand and the lattice water molecule are located on special positions (site symmetry 2). In the crystal, the uncoordinated 2,4,5-tricarb­oxy­benzeno­ate anions join with each other through O—H⋯O hydrogen bonds, forming a two-dimensional hydrogen-bonded layer structure along the bc plane. The layers are further linked via additional O—H⋯O inter­actions between water and carboxyl groups, resulting in a three-dimensional supra­molecular network

Link prediction in evolving networks based on popularity of nodes

Link prediction aims to uncover the underlying relationship behind networks, which could be utilized to predict missing edges or identify the spurious edges. The key issue of link prediction is to estimate the likelihood of potential links in networks. Most classical static-structure based methods ignore the temporal aspects of networks, limited by the time-varying features, such approaches perform poorly in evolving networks. In this paper, we propose a hypothesis that the ability of each node to attract links depends not only on its structural importance, but also on its current popularity (activeness), since active nodes have much more probability to attract future links. Then a novel approach named popularity based structural perturbation method (PBSPM) and its fast algorithm are proposed to characterize the likelihood of an edge from both existing connectivity structure and current popularity of its two endpoints. Experiments on six evolving networks show that the proposed methods outperform state-of-the-art methods in accuracy and robustness. Besides, visual results and statistical analysis reveal that the proposed methods are inclined to predict future edges between active nodes, rather than edges between inactive nodes

Myrica rubra Extracts Protect the Liver from CCl4-Induced Damage

The relationship between the expression of mitochondrial voltage-dependent anion channels (VDACs) and the protective effects of Myrica rubra Sieb. Et Zucc fruit extract (MCE) against carbon tetrachloride (CCl4)-induced liver damage was investigated. Pretreatment with 50 mg kg−1, 150 mg kg−1 or 450 mg kg−1 MCE significantly blocked the CCl4-induced increase in both serum aspartate aminotransferase (sAST) and serum alanine aminotransferase (sALT) levels in mice (P < .05 or .01 versus CCl4 group). Ultrastructural observations of decreased nuclear condensation, ameliorated mitochondrial fragmentation of the cristae and less lipid deposition by an electron microscope confirmed the hepatoprotection. The mitochondrial membrane potential dropped from −191.94 ± 8.84 mV to −132.06 ± 12.26 mV (P < .01) after the mice had been treated with CCl4. MCE attenuated CCl4-induced mitochondrial membrane potential dissipation in a dose-dependent manner. At a dose of 150 or 450 mg kg−1 of MCE, the mitochondrial membrane potentials were restored (P < .05). Pretreatment with MCE also prevented the elevation of intra-mitochondrial free calcium as observed in the liver of the CCl4-insulted mice (P < .01 versus CCl4 group). In addition, MCE treatment (50–450 mg kg−1) significantly increased both transcription and translation of VDAC inhibited by CCl4. The above data suggest that MCE mitigates the damage to liver mitochondria induced by CCl4, possibly through the regulation of mitochondrial VDAC, one of the most important proteins in the mitochondrial outer membrane

Enhancing speed of pinning synchronizability: low-degree nodes with high feedback gains

Controlling complex networks is of paramount importance in science and engineering. Despite recent efforts to improve controllability and synchronous strength, little attention has been paid to the speed of pinning synchronizability (rate of convergence in pinning control) and the corresponding pinning node selection. To address this issue, we propose a hypothesis to restrict the control cost, then build a linear matrix inequality related to the speed of pinning controllability. By solving the inequality, we obtain both the speed of pinning controllability and optimal control strength (feedback gains in pinning control) for all nodes. Interestingly, some low-degree nodes are able to achieve large feedback gains, which suggests that they have high influence on controlling system. In addition, when choosing nodes with high feedback gains as pinning nodes, the controlling speed of real systems is remarkably enhanced compared to that of traditional large-degree and large-betweenness selections. Thus, the proposed approach provides a novel way to investigate the speed of pinning controllability and can evoke other effective heuristic pinning node selections for large-scale systems

Towards a "Swiss Army Knife" for Scalable User-Defined Temporal (k,X)(k,\mathcal{X})-Core Analysis

Querying cohesive subgraphs on temporal graphs (e.g., social network, finance network, etc.) with various conditions has attracted intensive research interests recently. In this paper, we study a novel Temporal $(k,\mathcal{X})$-Core Query (TXCQ) that extends a fundamental Temporal $k$-Core Query (TCQ) proposed in our conference paper by optimizing or constraining an arbitrary metric $\mathcal{X}$ of $k$-core, such as size, engagement, interaction frequency, time span, burstiness, periodicity, etc. Our objective is to address specific TXCQ instances with conditions on different $\mathcal{X}$ in a unified algorithm framework that guarantees scalability. For that, this journal paper proposes a taxonomy of measurement $\mathcal{X}(\cdot)$ and achieve our objective using a two-phase framework while $\mathcal{X}(\cdot)$ is time-insensitive or time-monotonic. Specifically, Phase 1 still leverages the query processing algorithm of TCQ to induce all distinct $k$-cores during a given time range, and meanwhile locates the "time zones" in which the cores emerge. Then, Phase 2 conducts fast local search and $\mathcal{X}$ evaluation in each time zone with respect to the time insensitivity or monotonicity of $\mathcal{X}(\cdot)$. By revealing two insightful concepts named tightest time interval and loosest time interval that bound time zones, the redundant core induction and unnecessary $\mathcal{X}$ evaluation in a zone can be reduced dramatically. Our experimental results demonstrate that TXCQ can be addressed as efficiently as TCQ, which achieves the latest state-of-the-art performance, by using a general algorithm framework that leaves $\mathcal{X}(\cdot)$ as a user-defined function