16 research outputs found

    Will More Expressive Graph Neural Networks do Better on Generative Tasks?

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    Graph generation poses a significant challenge as it involves predicting a complete graph with multiple nodes and edges based on simply a given label. This task also carries fundamental importance to numerous real-world applications, including de-novo drug and molecular design. In recent years, several successful methods have emerged in the field of graph generation. However, these approaches suffer from two significant shortcomings: (1) the underlying Graph Neural Network (GNN) architectures used in these methods are often underexplored; and (2) these methods are often evaluated on only a limited number of metrics. To fill this gap, we investigate the expressiveness of GNNs under the context of the molecular graph generation task, by replacing the underlying GNNs of graph generative models with more expressive GNNs. Specifically, we analyse the performance of six GNNs in two different generative frameworks -- autoregressive generation models, such as GCPN and GraphAF, and one-shot generation models, such as GraphEBM -- on six different molecular generative objectives on the ZINC-250k dataset. Through our extensive experiments, we demonstrate that advanced GNNs can indeed improve the performance of GCPN, GraphAF, and GraphEBM on molecular generation tasks, but GNN expressiveness is not a necessary condition for a good GNN-based generative model. Moreover, we show that GCPN and GraphAF with advanced GNNs can achieve state-of-the-art results across 17 other non-GNN-based graph generative approaches, such as variational autoencoders and Bayesian optimisation models, on the proposed molecular generative objectives (DRD2, Median1, Median2), which are important metrics for de-novo molecular design.Comment: 2nd Learning on Graphs Conference (LoG 2023). 26 pages, 5 figures, 11 table

    Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

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    A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

    Measurement of jet fragmentation in Pb+Pb and pppp collisions at sNN=2.76\sqrt{{s_\mathrm{NN}}} = 2.76 TeV with the ATLAS detector at the LHC

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    RNU12 inhibits gastric cancer progression via sponging miR-575 and targeting BLID

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    Abstract Gastric cancer (GC) is one of the major causes of cancer deaths with 5-year survival ratio of 20%. RNU12 is one of long noncoding RNAs (lncRNAs) regulating the tumor progression. However, how RNU12 affecting GC is not clear. qRT-PCR was utilized for determining the RNU12 expression in cell lines, 113 cases of paired gastric cancer (GC) and their adjacent normal gastric tissues. The biofunction alterations of RNU12 were assessed by its overexpression or knockdown in GC cells. MTT and cloning assay were assayed for the cell proliferation, the flow cytometry for the detection of cell cycle and the wound healing assay (WHA) and transwell invasion assay (TIA) for examining the migration and invasion of cells. The expressions of a set of genes related proliferation and migration were investigated with the Western Blotting (WB). RNA immunoprecipitation (RIP), biotinylated RNA pull-down and dual luciferase reporter tests were used to detect the interactions of RNU12 with miR-575/BLID. The in vivo proliferation and migration ability of RNU12 infected cells were determined in zebrafish system. This study revealed that RNU12 inhibited proliferation, invasion and metastasis by sponging of miR-575 and regulating the downstream BLID and modulated EMT of GC cells. The RNU12/miR-575/BLID axis is likely to be the prognosis biomarkers and drug targets of GC

    Search for direct top squark pair production in final states with two leptons in s=13\sqrt{s} = 13 TeV pppp collisions with the ATLAS detector

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    International audienceThe results of a search for direct pair production of top squarks in events with two opposite-charge leptons (electrons or muons) are reported, using 36.1 fb136.1~\hbox {fb}^{-1} of integrated luminosity from proton–proton collisions at s=13\sqrt{s}=13 TeV collected by the ATLAS detector at the Large Hadron Collider. To cover a range of mass differences between the top squark t~\tilde{t} and lighter supersymmetric particles, four possible decay modes of the top squark are targeted with dedicated selections: the decay t~bχ~1±\tilde{t} \rightarrow b \tilde{\chi }_{1}^{\pm } into a b-quark and the lightest chargino with χ~1±Wχ~10\tilde{\chi }_{1}^{\pm } \rightarrow W \tilde{\chi }_{1}^{0} , the decay t~tχ~10\tilde{t} \rightarrow t \tilde{\chi }_{1}^{0} into an on-shell top quark and the lightest neutralino, the three-body decay t~bWχ~10\tilde{t} \rightarrow b W \tilde{\chi }_{1}^{0} and the four-body decay t~bνχ~10\tilde{t} \rightarrow b \ell \nu \tilde{\chi }_{1}^{0} . No significant excess of events is observed above the Standard Model background for any selection, and limits on top squarks are set as a function of the t~\tilde{t} and χ~10\tilde{\chi }_{1}^{0} masses. The results exclude at 95% confidence level t~\tilde{t} masses up to about 720 GeV, extending the exclusion region of supersymmetric parameter space covered by previous searches
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