Coupling conditions for linear hyperbolic relaxation systems in two-scales problems

This work is concerned with coupling conditions for linear hyperbolic relaxation systems with multiple relaxation times. In the region with small relaxation time, an equilibrium system can be used for computational efficiency. Under the assumption that the relaxation system satisfies the structural stability condition and the interface is non-characteristic, we derive a coupling condition at the interface to couple the two systems in a domain decomposition setting. We prove the validity by the energy estimate and Laplace transform, which shows how the error of the domain decomposition method depends on the smaller relaxation time and the boundary layer effects. In addition, we propose a discontinuous Galerkin (DG) scheme for solving the interface problem with the derived coupling condition and prove the L2 stability. We validate our analysis on the linearized Carleman model and the linearized Grad's moment system and show the effectiveness of the DG scheme.Comment: 30 pages, 2 figure

Low-Loss Polymer-Based Ring Resonator for Resonant Integrated Optical Gyroscopes

Waveguide ring resonator is the sensing element of resonant integrated optical gyroscope (RIOG). This paper reports a polymer-based ring resonator with a low propagation loss of about 0.476 dB/cm for RIOG. The geometrical parameters of the waveguide and the coupler of the resonator were optimally designed. We also discussed the optical properties and gyroscope performance of the polymer resonator which shows a high quality factor of about 105. The polymer-based RIOG exhibits a limited sensitivity of less than 20 deg/h for the low and medium resolution navigation systems

On Efficient Reinforcement Learning for Full-length Game of StarCraft II

StarCraft II (SC2) poses a grand challenge for reinforcement learning (RL), of which the main difficulties include huge state space, varying action space, and a long time horizon. In this work, we investigate a set of RL techniques for the full-length game of StarCraft II. We investigate a hierarchical RL approach involving extracted macro-actions and a hierarchical architecture of neural networks. We investigate a curriculum transfer training procedure and train the agent on a single machine with 4 GPUs and 48 CPU threads. On a 64x64 map and using restrictive units, we achieve a win rate of 99% against the level-1 built-in AI. Through the curriculum transfer learning algorithm and a mixture of combat models, we achieve a 93% win rate against the most difficult non-cheating level built-in AI (level-7). In this extended version of the paper, we improve our architecture to train the agent against the cheating level AIs and achieve the win rate against the level-8, level-9, and level-10 AIs as 96%, 97%, and 94%, respectively. Our codes are at https://github.com/liuruoze/HierNet-SC2. To provide a baseline referring the AlphaStar for our work as well as the research and open-source community, we reproduce a scaled-down version of it, mini-AlphaStar (mAS). The latest version of mAS is 1.07, which can be trained on the raw action space which has 564 actions. It is designed to run training on a single common machine, by making the hyper-parameters adjustable. We then compare our work with mAS using the same resources and show that our method is more effective. The codes of mini-AlphaStar are at https://github.com/liuruoze/mini-AlphaStar. We hope our study could shed some light on the future research of efficient reinforcement learning on SC2 and other large-scale games.Comment: 48 pages,21 figure

Influence of substrate roughness on structure and mechanical property of TiAlN coating fabricated by cathodic arc evaporation

The aim of the present research was to investigate the influence of different substrate roughness on structure and mechanical properties of Titanium Aluminium Nitride (TiAlN) coatings. Tungsten carbide rectangular block was used as substrate. Different surface roughness was achieved by using grinding discs with different grain sizes and diamond polishing powder, and TiAlN coatings were deposited on these substrates under the same preparation technique and parameters. Morphologies of substrates and coatings, crystal structure, thickness and mechanical properties of coatings were investigated using optical microscope, AFM, XRD, CSM scratch tester and tribometer. It was shown that surface morphology of cathodic arc TiAlN coating was mainly affected by the morphology of the substrate surface and the coating growth process. The influence of substrate roughness on crystal structure and thickness of the coatings could be ignored. With the decreasing of the substrate roughness, the adhesion force between coating and substrate increased. Three stresses model was applied to interpret this result. The wear resistance of the coating was also improved with decreasing the substrate roughness. (C) 2011 Published by Elsevier B.V. Selection and/or peer-review under responsibility of Selection and/or peer-review under responsibility of Lanzhou Institute of Physics, China

Chemokine receptor CXCR3 is important for lung tissue damage and airway remodeling induced by short-term exposure to cigarette smoking in mice

Aim: To investigate the role of chemokine receptor CXCR3 in cigarette smoking (CS)-induced pulmonary damage. Methods: CXCR3 knockout (CXCR3-/-) mice were used. Differences in airspace enlargement, mRNA expression of matrix metalloproteinases (MMPs), transforming growth factor (TGF) β1, CXCL10 in lung homogenates, and CXCL10 content in bronchoalveolar lavage (BAL) fluids and homogenates were compared between CXCR3-/- mice and wild-type (WT) mice three days after three-day CS exposures. Results: The linear intercept was significantly less in CXCR3-/- mice than in WT mice (30.1±0.9 μm vs 40.3±2.4 μm, P<0.01). Morphologically, collagen was deposited less around airways and vessels in CXCR3-/- mice. The lung hydroxyproline content was significantly lower in CXCR3-/- mice than in WT mice (6.0±1.0 μg/mL vs 12.0±1.6 μg/mL, P<0.05). Profoundly lower mRNA expression of MMP2, MMP12, TGFβ1, and CXCL10 was seen in lung homogenates from CXCR3-/- mice. CXCL10 concentrations in BAL fluid and lung homogenates were significantly lower in CXCR3-/- mice than in WT mice (BAL fluid: 19.3±1.4 pg/mL vs 24.8±1.6 pg/mL, P<0.05; lung homogenates: 76.6±7.0 pg/mL vs 119.5±15.9 pg/mL, P<0.05). Conclusion: CXCR3 is important in mediating lung tissue damage and airway remodeling following a short-term CS insult, possibly through up-regulation of CXCL10 and inducement of mRNA expression of MMPs. Targeting CXCR3 may be helpful for prevention of CS-induced pulmonary pathology