Efficient Subgraph Matching on Billion Node Graphs

The ability to handle large scale graph data is crucial to an increasing number of applications. Much work has been dedicated to supporting basic graph operations such as subgraph matching, reachability, regular expression matching, etc. In many cases, graph indices are employed to speed up query processing. Typically, most indices require either super-linear indexing time or super-linear indexing space. Unfortunately, for very large graphs, super-linear approaches are almost always infeasible. In this paper, we study the problem of subgraph matching on billion-node graphs. We present a novel algorithm that supports efficient subgraph matching for graphs deployed on a distributed memory store. Instead of relying on super-linear indices, we use efficient graph exploration and massive parallel computing for query processing. Our experimental results demonstrate the feasibility of performing subgraph matching on web-scale graph data.Comment: VLDB201

Detoxification of 1,1,2-trichloroethane to ethene by desulfitobacterium and identification of its functional reductase gene

10.1371/journal.pone.0119507PLoS ONE104e011950

Expression of mTOR conduction pathway in human osteosarcoma MG-63 cells and their stem cells, and the inhibitory effect of different doses of rapamycin

Purpose: To investigate the expressions of rapamycin target protein (mTOR) conduction pathway in human osteosarcoma MG-63 cells and their stem cells, and to examine the inhibitory effect of different doses of rapamycin.Methods: mTOR mRNA in osteosarcoma stem-like cells and human osteosarcoma MG-63 cells were determined by quantitative reverse transcription polymerase chain reaction (qRT-PCR). The cells were treated with different doses of rapamycin and divided into low dose group (0.5 mg), medium dose group (1.0 mg), high dose group (2.0 mg) and blank (control) group. Apoptosis and cell cycle of MG-63 cells were determined by flow cytometry, while proliferation of MG-63 cells up was assessed by CCK-8 kit.Results: mTOR in human osteosarcoma MG-63 cells was significantly lower than that in osteosarcoma stem-like cells. Compared with the control group, mRNA expression levels of mTOR in MG-63 cells and osteosarcoma stem-like cells were significantly decreased after treatment with different concentrations of rapamycin (p < 0.05). MG-63 cells treated with various doses of rapamycin exhibited a significant decrease in their proliferation, compared with control group, while only the high rapamycin concentration group exhibited a significant decrease in osteosarcoma stem-like cell proliferation (p < 0.05). Treatment with rapamycin in MG-63 cells and osteosarcoma stem-like cells resulted in a significant increase in apoptosis, prolonged G0/G1 phase and shortened S phase (p < 0.05).Conclusion: Rapamycin inhibits the expression of mTOR mRNA in osteosarcoma stem-like and MG-63 cells. It also inhibits the proliferation and cell cycle formation of osteosarcoma stem-like cells and MG-63 cells via mTOR signal pathway. These findings may provide a new target for the treatment of osteosarcoma

WGCN: Graph Convolutional Networks with Weighted Structural Features

Graph structural information such as topologies or connectivities provides valuable guidance for graph convolutional networks (GCNs) to learn nodes' representations. Existing GCN models that capture nodes' structural information weight in- and out-neighbors equally or differentiate in- and out-neighbors globally without considering nodes' local topologies. We observe that in- and out-neighbors contribute differently for nodes with different local topologies. To explore the directional structural information for different nodes, we propose a GCN model with weighted structural features, named WGCN. WGCN first captures nodes' structural fingerprints via a direction and degree aware Random Walk with Restart algorithm, where the walk is guided by both edge direction and nodes' in- and out-degrees. Then, the interactions between nodes' structural fingerprints are used as the weighted node structural features. To further capture nodes' high-order dependencies and graph geometry, WGCN embeds graphs into a latent space to obtain nodes' latent neighbors and geometrical relationships. Based on nodes' geometrical relationships in the latent space, WGCN differentiates latent, in-, and out-neighbors with an attention-based geometrical aggregation. Experiments on transductive node classification tasks show that WGCN outperforms the baseline models consistently by up to 17.07% in terms of accuracy on five benchmark datasets

A model-based DC fault location scheme for multi-terminal MMC-HVDC systems using a simplified transmission line representation

Accurately determining the location of DC pole-to-pole short-circuit faults in modular multilevel converter (MMC) based multi-terminal HVDC (MTDC) systems is key issue in ensuring fast power recovery. This paper proposes an effective DC fault location scheme for the MMC-MTDC that uses an estimated R-L representation of the transmission lines. By using the measured voltage and current data from both ends of the faulted DC line, the proposed fault location formulas can calculate the location of the fault with high accuracy. The simplified R-L representation greatly reduces the computation burden of the fault detection algorithm. Electromagnetic transient (EMT) simulations of a four-terminal MMC-MTDC system on PSCAD/EMTDC are used to confirm the effectiveness of the proposed approach. The results verify that the proposed scheme is robust and almost not affected by the transmitted power or the fault resistance

Risk factors for the prognosis of pediatric medulloblastoma: a retrospective analysis of 40 cases

OBJECTIVES: In this study, we evaluated the association of molecular subtypes, clinical characteristics and pathological types with the prognosis of patients with medulloblastoma. METHODS: We analyzed forty patients with medulloblastoma who underwent surgical resection at our center between January 2004 and June 2014. Risk factors associated with survival, disease progression and recurrence were analyzed with a univariate Cox regression analysis, and the identified significant risk factors were further analyzed by Kaplan-Meier survival curves. RESULTS: Factors associated with overall survival included M stage (p=0.014), calcification (p=0.012), postoperative treatment, postoperative Karnofsky Performance Scale (KPS) score (p=0.015), and molecular subtype (p=0.005 for WNT and p=0.008 for SHH). Number of symptoms (p=0.029), M stage (p;2 and ≥M1 stage without postoperative radiotherapy. The risk of recurrence increased with advanced M stage. Protective factors for recurrence included M0 stage and a combination of chemotherapy and radiotherapy. CONCLUSION: We identified the risk factors associated with survival, disease progression and recurrence of medulloblastoma patients. This information is helpful for understanding the prognostic factors related to medulloblastoma

DC current flow controller with fault current limiting and interrupting capabilities

Conventionally, the current flow control and DC fault protection issues of HVDC grids are supposed to be solved by the DC current flow controller (CFC) and DC circuit breaker (DCCB) separately, which may result in a high capital cost. This paper proposes a CFC topology with DC fault current limiting and interrupting capabilities. The topology and operating principle of the CFC are presented with theoretical analysis. The control strategies under normal and fault conditions are described. In order to reduce the use of IGBTs, an H-bridge inter-line CFC with fault current limiting capability is further proposed based on the first proposed CFC. The proposed CFCs are tested in PSCAD/EMTDC. Simulation results show that the proposed two CFCs can effectively control the current flow of two lines during normal operation and limit and interrupt DC fault currents