Cascading failures in coupled networks with both inner-dependency and inter-dependency links

We study the percolation in coupled networks with both inner-dependency and inter-dependency links, where the inner- and inter-dependency links represent the dependencies between nodes in the same or different networks, respectively. We find that when most of dependency links are inner- or inter-ones, the coupled networks system is fragile and makes a discontinuous percolation transition. However, when the numbers of two types of dependency links are close to each other, the system is robust and makes a continuous percolation transition. This indicates that the high density of dependency links could not always lead to a discontinuous percolation transition as the previous studies. More interestingly, although the robustness of the system can be optimized by adjusting the ratio of the two types of dependency links, there exists a critical average degree of the networks for coupled random networks, below which the crossover of the two types of percolation transitions disappears, and the system will always demonstrate a discontinuous percolation transition. We also develop an approach to analyze this model, which is agreement with the simulation results well.Comment: 9 pages, 4 figure

Effects of heritability on evolutionary cooperation in spatial prisoner’s dilemma games

AbstractWe study the effects of heritability on the evolution of the spatial prisoner’s dilemma game. In our model, the fitness of each player is composed of the instantaneous payoff from the interactions and the inherited fitness from the last generation. Based on extensive simulations, we find that the density of cooperators is enhanced by increasing the heritability of players over a wide range of the model parameter. The mean fitness of cooperators and defectors are also studied for understanding our results

Information filtering based on transferring similarity

In this Brief Report, we propose a new index of user similarity, namely the transferring similarity, which involves all high-order similarities between users. Accordingly, we design a modified collaborative filtering algorithm, which provides remarkably higher accurate predictions than the standard collaborative filtering. More interestingly, we find that the algorithmic performance will approach its optimal value when the parameter, contained in the definition of transferring similarity, gets close to its critical value, before which the series expansion of transferring similarity is convergent and after which it is divergent. Our study is complementary to the one reported in [E. A. Leicht, P. Holme, and M. E. J. Newman, Phys. Rev. E {\bf 73} 026120 (2006)], and is relevant to the missing link prediction problem.Comment: 4 pages, 4 figure

Personal Recommendation via Modified Collaborative Filtering

In this paper, we propose a novel method to compute the similarity between congeneric nodes in bipartite networks. Different from the standard Person correlation, we take into account the influence of node's degree. Substituting this new definition of similarity for the standard Person correlation, we propose a modified collaborative filtering (MCF). Based on a benchmark database, we demonstrate the great improvement of algorithmic accuracy for both user-based MCF and object-based MCF.Comment: 7 pages, 8 figures and 1 tabl

Assessment of structural characteristics of regenerated cellulolytic enzyme lignin based on a mild DMSO/[Emim]OAc dissolution system from triploid of Populus tomentosa Carr.

The structural characteristics of native lignin are essential for the further deconstruction of plant cell walls for value-added application of lignocellulosic biomass.</p

Stable Hydrazone-Linked Covalent Organic Frameworks Containing O,N,O'-Chelating Sites for Fe(III) Detection in Water.

Two stable crystalline hydrazone-linked covalent organic frameworks (COFs) (Bth-Dha and Bth-Dma) containing functional O,N,O'-chelating sites have been designed and successfully synthesized by the Schiff-base condensation reactions between benzene-1,3,5-tricarbohydrazide (Bth) and 2,5-dihydroxyterephthalaldehyde (Dha) or 2,5-dimethoxyterephthal-aldehyde (Dma), respectively. Bth-Dma exhibits strong fluorescence in the solid state and in an aqueous dispersion, while no fluorescence can be observed for Bth-Dha. Interestingly, the as-synthesized Bth-Dma can be used as a turn-off fluorescence sensor for the Fe(III) ion in aqueous solution with outstanding selectivity and sensitivity. The recognition process can be attributed to the coordination interaction between Fe(III) ion and the O,N,O'-chelating sites in the pore wall of Bth-Dma COF, as verified by X-ray photoelectron spectroscopy and 1H NMR spectroscopy. To the best of our knowledge, this is the first report on the rational design of luminescent COF with predesigned O,N,O'-chelating sites as a fluorescence sensor for highly selective and sensitive metal ion detection. This work may pave the way for designing luminescent COF sensors with functional binding sites for detecting specific metal ions

KIF5A upregulation in hepatocellular carcinoma: A novel prognostic biomarker associated with unique tumor microenvironment status

Liver hepatocellular carcinoma (LIHC) is one of the most common liver malignancies with high mortality and morbidity. Thus, it is crucial to identify potential biomarker that is capable of accurately predicting the prognosis and therapeutic response of LIHC. Kinesin family member 5A (KIF5A) is a microtubule-based motor protein involved in the transport of macromolecules such as organelle proteins in cells. Recent studies have illustrated that the high expression of KIF5A was related to poor prognosis of solid tumors, including bladder cancer, prostate cancer, and breast cancer. However, little is currently known concerning the clinical significance of KIF5A expression in LIHC. Herein, by adopting multi-omics bioinformatics analysis, we comprehensively uncovered the potential function and the predictive value of KIF5A in stratifying clinical features among patients with LIHC, for which a high KIF5A level predicted an unfavorable clinical outcome. Results from KIF5A-related network and enrichment analyses illustrated that KIF5A might involve in microtubule-based process, antigen processing and presentation of exogenous peptide antigen via MHC class II. Furthermore, immune infiltration and immune function analyses revealed upregulated KIF5A could predict a unique tumor microenvironment with more CD8+T cells and a higher level of anti-tumor immune response. Evidence provided by immunohistochemistry staining (IHC) further validated our findings at the protein level. Taken together, KIF5A might serve as a novel prognostic biomarker for predicting immunotherapy response and could be a potential target for anti-cancer strategies for LIHC