Learning Rays via Deep Neural Network in a Ray-based IPDG Method for High-Frequency Helmholtz Equations in Inhomogeneous Media

We develop a deep learning approach to extract ray directions at discrete locations by analyzing highly oscillatory wave fields. A deep neural network is trained on a set of local plane-wave fields to predict ray directions at discrete locations. The resulting deep neural network is then applied to a reduced-frequency Helmholtz solution to extract the directions, which are further incorporated into a ray-based interior-penalty discontinuous Galerkin (IPDG) method to solve the Helmholtz equations at higher frequencies. In this way, we observe no apparent pollution effects in the resulting Helmholtz solutions in inhomogeneous media. Our 2D and 3D numerical results show that the proposed scheme is very efficient and yields highly accurate solutions.Comment: 30 page

MALAT1 Activates the P53 Signaling Pathway by Regulating MDM2 to Promote Ischemic Stroke

Background/Aims: This study focused on evaluating the effect of MALAT1 and MDM2 on ischemic stroke through regulation of the p53 signaling pathway. Materials: Bioinformatics analysis was performed to identify abnormally expressed lncRNAs, mRNAs and their associated pathways. Oxygen-glucose deprivation/reoxygenation (OGD/R) in cells and middle cerebral artery occlusion/reperfusion (MCAO/R) in mice were performed to simulate an ischemic stroke environment. Western blot and qRT-PCR were used to examine lncRNA expression and mRNA levels. Fluorescence in situ hybridization (FISH) LncRNA was used to locate mRNA. MTT and flow cytometry were performed to examine cell proliferation and apoptosis. Finally, immunohistochemistry was used to observe the expression of genes in vivo. Results: MALAT1 and MDM2, which exhibit strong expression in stroke tissues, were subjected to bioinformatics analysis, and the p53 pathway was chosen for further study. MALAT1, MDM2 and p53 signaling pathway-related proteins were all up regulated in OGD/R cells. Furthermore, Malat1, Mdm2 and p53 pathway related-proteins were also up regulated in MCAO/R mice. Both MALAT1 and MDM2 were localized in the nuclei. Down regulation of MALAT1 and MDM2 enhanced cell proliferation ability and reduced apoptosis, resulting in decreased infarct size in MCAO/R brains. Conclusion: These results indicate that MALAT1/MDM2/p53 signaling pathway axis may provide more effective clinical therapeutic strategy for patients with ischemic stroke

Pathway to Future Symbiotic Creativity

This report presents a comprehensive view of our vision on the development path of the human-machine symbiotic art creation. We propose a classification of the creative system with a hierarchy of 5 classes, showing the pathway of creativity evolving from a mimic-human artist (Turing Artists) to a Machine artist in its own right. We begin with an overview of the limitations of the Turing Artists then focus on the top two-level systems, Machine Artists, emphasizing machine-human communication in art creation. In art creation, it is necessary for machines to understand humans' mental states, including desires, appreciation, and emotions, humans also need to understand machines' creative capabilities and limitations. The rapid development of immersive environment and further evolution into the new concept of metaverse enable symbiotic art creation through unprecedented flexibility of bi-directional communication between artists and art manifestation environments. By examining the latest sensor and XR technologies, we illustrate the novel way for art data collection to constitute the base of a new form of human-machine bidirectional communication and understanding in art creation. Based on such communication and understanding mechanisms, we propose a novel framework for building future Machine artists, which comes with the philosophy that a human-compatible AI system should be based on the "human-in-the-loop" principle rather than the traditional "end-to-end" dogma. By proposing a new form of inverse reinforcement learning model, we outline the platform design of machine artists, demonstrate its functions and showcase some examples of technologies we have developed. We also provide a systematic exposition of the ecosystem for AI-based symbiotic art form and community with an economic model built on NFT technology. Ethical issues for the development of machine artists are also discussed

Molecular Mechanisms Underlying Inhibitory Binding of Alkylimidazolium Ionic Liquids to Laccase

Water-miscible alkylimidazolium ionic liquids (ILs) are “green” co-solvents for laccase catalysis, but generally inhibit enzyme activity. Here, we present novel insights into inhibition mechanisms by a combination of enzyme kinetics analysis and molecular simulation. Alkylimidazolium cations competitively bound to the TI Cu active pocket in the laccase through hydrophobic interactions. Cations with shorter alkyl chains (C2~C6) entered the channel inside the pocket, exhibiting a high compatibility with laccase (competitive inhibition constant Kic = 3.36~3.83 mM). Under the same conditions, [Omim]Cl (Kic = 2.15 mM) and [Dmim]Cl (Kic = 0.18 mM) with longer alkyl chains bound with Leu296 or Leu297 near the pocket edge and Leu429 around TI Cu, which resulted in stronger inhibition. Complexation with alkylimidazolium cations shifted the pH optima of laccase to the right by 0.5 unit, and might, thereby, lead to invalidation of the Hofmeister series of anions. EtSO4− showed higher biocompatibility than did Ac− or Cl−, probably due to its binding near the TI Cu and its hindering the entry of alkylimidazolium cations. In addition, all tested ILs accelerated the scavenging of 2, 2′-azino-bis-(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) radicals, which, however, did not play a determining role in the inhibition of laccase