Metal-organic chemical vapor deposition of 2D van der Waals materials-The challenges and the extensive future opportunities

The last decade has witnessed significant progress in two-dimensional van der Waals (2D vdW) materials research; however, a number of challenges remain for their practical applications. The most significant challenge for 2D vdW materials is the control of the early stages of nucleation and growth of the material on preferred surfaces to eventually create large grains with digital thickness controllability, which will enable their incorporation into high-performance electronic and optoelectronic devices. This Perspective discusses the technical challenges to be overcome in the metal-organic chemical vapor deposition (MOCVD) growth of 2D group 6 transition metal dichalcogenide (TMD) atomic crystals and their heterostructures, as well as future research aspects in vdW epitaxy for 2D TMDs via MOCVD. In addition, we encourage the traditional MOCVD community to apply their expertise in the field of "2D vdW materials," which will continue to grow at an exponential rate

DeepIron: Predicting Unwarped Garment Texture from a Single Image

Realistic reconstruction of 3D clothing from an image has wide applications, such as avatar creation and virtual try-on. This paper presents a novel framework that reconstructs the texture map for 3D garments from a single image with pose. Assuming that 3D garments are modeled by stitching 2D garment sewing patterns, our specific goal is to generate a texture image for the sewing patterns. A key component of our framework, the Texture Unwarper, infers the original texture image from the input clothing image, which exhibits warping and occlusion of texture due to the user's body shape and pose. The Texture Unwarper effectively transforms between the input and output images by mapping the latent spaces of the two images. By inferring the unwarped original texture of the input garment, our method helps reconstruct 3D garment models that can show high-quality texture images realistically deformed for new poses. We validate the effectiveness of our approach through a comparison with other methods and ablation studies

ON POSITIVE QUATERNIONIC KÄHLER MANIFOLDS WITH b_4=1

Let M be a positive quaternionic Kähler manifold of dimension 4m. In earlier papers, Fang and the first author showed that if the symmetry rank is greater than or equal to [m=2]+3, then M is isometric to HP^m or Gr_2(C^). The goal of this paper is to give a more refined classification result for positive quaternionic Kähler manifolds (in particular, of relatively low dimension or with even m) whose fourth Betti number equals one. To be precise, we show in this paper that if the symmetry rank of M with b_4(M)=1is no less than [m/2]+2 for ≥5, then M is isometric to HP^m

Sample Dominance Aware Framework via Non-Parametric Estimation for Spontaneous Brain-Computer Interface

Deep learning has shown promise in decoding brain signals, such as electroencephalogram (EEG), in the field of brain-computer interfaces (BCIs). However, the non-stationary characteristics of EEG signals pose challenges for training neural networks to acquire appropriate knowledge. Inconsistent EEG signals resulting from these non-stationary characteristics can lead to poor performance. Therefore, it is crucial to investigate and address sample inconsistency to ensure robust performance in spontaneous BCIs. In this study, we introduce the concept of sample dominance as a measure of EEG signal inconsistency and propose a method to modulate its effect on network training. We present a two-stage dominance score estimation technique that compensates for performance degradation caused by sample inconsistencies. Our proposed method utilizes non-parametric estimation to infer sample inconsistency and assigns each sample a dominance score. This score is then aggregated with the loss function during training to modulate the impact of sample inconsistency. Furthermore, we design a curriculum learning approach that gradually increases the influence of inconsistent signals during training to improve overall performance. We evaluate our proposed method using public spontaneous BCI dataset. The experimental results confirm that our findings highlight the importance of addressing sample dominance for achieving robust performance in spontaneous BCIs.Comment: 5 pages, 2 figure

Neuroprotective Effects of Astaxanthin in Oxygen-Glucose Deprivation in SH-SY5Y Cells and Global Cerebral Ischemia in Rat

Astaxanthin (ATX), a naturally occurring carotenoid pigment, is a powerful biological antioxidant. In the present study, we investigated whether ATX pharmacologically offers neuroprotection against oxidative stress by cerebral ischemia. We found that the neuroprotective efficacy of ATX at the dose of 30 mg/kg (n = 8) was 59.5% compared with the control group (n = 3). In order to make clear the mechanism of ATX neuroprotection, the up-regulation inducible nitric oxide synthase (iNOS) and heat shock proteins (HSPs) together with the oxygen glucose deprivation (OGD) in SH-SY5Y cells were also investigated. The induction of various factors involved in oxidative stress processes such as iNOS was suppressed by the treatment of ATX at 25 and 50 µM after OGD-induced oxidative stress. In addition, Western blots showed that ATX elevated of heme oxygenase-1 (HO-1; Hsp32) and Hsp70 protein levels in in vitro. These results suggest that the neuroprotective effects of ATX were related to anti-oxidant activities in global ischemia

Two-dimensional heterogeneous photonic bandedge laser

We proposed and realized a two-dimensional (2D) photonic bandedge laser surrounded by the photonic bandgap. The heterogeneous photonic crystal structure consists of two triangular lattices of the same lattice constant with different air hole radii. The photonic crystal laser was realized by room-temperature optical pumping of air-bridge slabs of InGaAsP quantum wells emitting at 1.55 micrometer. The lasing mode was identified from its spectral positions and polarization directions. A low threshold incident pump power of 0.24mW was achieved. The measured characteristics of the photonic crystal lasers closely agree with the results of real space and Fourier space calculations based on the finite-difference time-domain method.Comment: 14 pages, 4 figure

Structural Optimization of a Knuckle with Consideration of Stiffness and Durability Requirements

The automobile’s knuckle is connected to the parts of the steering system and the suspension system and it is used for adjusting the direction of a rotation through its attachment to the wheel. This study changes the existing material made of GCD45 to Al6082M and recommends the lightweight design of the knuckle as the optimal design technique to be installed in small cars. Six shape design variables were selected for the optimization of the knuckle and the criteria relevant to stiffness and durability were considered as the design requirements during the optimization process. The metamodel-based optimization method that uses the kriging interpolation method as the optimization technique was applied. The result shows that all constraints for stiffness and durability are satisfied using A16082M, while reducing the weight of the knuckle by 60% compared to that of the existing GCD450