While reversible histone modifications are linked to an ever-expanding range of biological functions1–5, the demethylases for histone H4 lysine 20 and their potential regulatory roles remain unknown. Here, we report that the PHD and Jumonji C (JmjC) domain-containing protein, PHF8, while utilizing multiple substrates, including H3K9me1/2 and H3K27me2, also functions as an H4K20me1 demethylase. PHF8 is recruited to promoters by its PHD domain based on interaction with H3K4me2/3 and controls G1/S transition in conjunction with E2F1, HCF-1 and Set1A, at least in part, by removing the repressive H4K20me1 mark from a subset of E2F1-regulated gene promoters. Phosphorylation-dependent PHF8 dismissal from chromatin in prophase is apparently required for the accumulation of H4K20me1 during early mitosis, which might represent a component of the Condensin II loading process. Accordingly, the HEAT repeat clusters in two non-SMC Condensin II subunits, N-CAPD3 and N-CAPG2, are capable of recognizing H4K20me1, and ChIP-seq. analysis demonstrate a significant overlap of Condensin II and H4K20me1 sites in mitotic HeLa cells. Thus, the identification and characterization of the first H4K20me1 demethylase, PHF8, has revealed an intimate link between this enzyme and two distinct events in cell cycle progression.

We propose a new meta-heuristic algorithm named Levy flights multi-verse optimizer (LFMVO), which incorporates Levy flights into multi-verse optimizer (MVO) algorithm to solve numerical and engineering optimization problems. The Original MVO easily falls into stagnation when wormholes stochastically re-span a number of universes (solutions) around the best universe achieved over the course of iterations. Since Levy flights are superior in exploring unknown, large-scale search space, they are integrated into the previous best universe to force MVO out of stagnation. We test this method on three sets of 23 well-known benchmark test functions and an NP complete problem of test scheduling for Network-on-Chip (NoC). Experimental results prove that the proposed LFMVO is more competitive than its peers in both the quality of the resulting solutions and convergence speed.

Much research has been conducted to improve the defect-detection rate and detection accuracy of the imaging technology used in terahertz nondestructive testing. Due to the power limit of light sources and noise interference in terahertz equipment, images have low resolution and fuzzy defect edges. Hence, improving the resolution is crucial for detecting defects. We designed an edge detection network structure based on a traditional deep neural network. Besides, we devised a node-fusing strategy to train the network. It demonstrates significant improvement of the resolution of the terahertz defect contour. A quartz fiber composites with embedded defects was tested with our network. The results showed that the proposed super-resolution reconstruction algorithm improves resolution, particularly on the edges of defect contours.

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Based on the ant colony algorithm analysis and research, this paper proposed an improved ant colony algorithm. Through updating pheromone and optimal search strategy, then applied to the Traveling Salesman Problem (TSP), effectively improved the searching capability of the algorithm. Finally through the simulation testing and analysis, verified that the improved ant colony algorithm is effective, and has good performance.

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With the wide application of cloud platform, information security based on cloud platform has become a research hot point. In this paper, by analyzing the security features of the cloud platform, researched the intrusion clustering based on Kohonen neural network, and proposed a new framework, and improved the weights of output layer. With the software Matlab simulation, the experimental results were satisfactory, illustrated that invasion clustering of neural network based on cloud platform took good effect.

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