Majorana corner modes and flat-band Majorana edge modes in superconductor/topological-insulator/superconductor junctions

Recently, superconductors with higher-order topology have stimulated extensive attention and research interest. Higher-order topological superconductors exhibit unconventional bulk-boundary correspondence, thus allow exotic lower-dimensional boundary modes, such as Majorana corner and hinge modes. However, higher-order topological superconductivity has yet to be found in naturally occurring materials. In this work, we investigate higher-order topology in a two-dimensional Josephson junction comprised of two $s$-wave superconductors separated by a topological insulator thin film. We found that zero-energy Majorana corner modes, a boundary fingerprint of higher-order topological superconductivity, can be achieved by applying magnetic field. When an in-plane Zeeman field is applied to the system, two corner states appear in the superconducting junction. Furthermore, we also discover a two dimensional nodal superconducting phase which supports flat-band Majorana edge modes connecting the bulk nodes. Importantly, we demonstrate that zero-energy Majorana corner modes are stable when increasing the thickness of topological insulator thin film.Comment: 9 pages, 4 figure

Full-spectrum noise prediction of the high-speed train head under multi-physics coupling excitations based on statistical energy analysis

The force between wheels and rails of the high-speed train was firstly extracted and applied into the computational model of radiation noises of wheels and rail respectively. As a result, the radiation noise of wheels and rails was obtained. As can be seen from the result, radiation noises of wheels had an obvious directivity on the body surface, while radiation noises of rails had an obvious periodicity on the body surface. With the increase of the analyzed frequency, both directivity and periodicity were shown more obviously. Then the aerodynamic model of the high-speed train was established, and the pressure and velocity distributions on the train surface were computed. The maximum pressure was at the tip of the nose of the high-speed train, the maximum velocity was at the transition of the cabin, and more serious eddy was in the rear of the high speed train. Based on the computed pressure distribution, the aerodynamic noise was distributed evenly on the entire body surface, which was gradually increased with the increasing analyzed frequency. Finally, the wheel radiation noise, rail radiation noise and aerodynamic noise were extracted as excitations and applied into the SEA (Statistical Energy Analysis) model of the high-speed train, in order to compute its full-spectrum noise under multi-physics coupling excitations. The computational result was compared with the experimental result. It was presented that the difference of average sound pressure level (SPL) was 2.8 dB between the experimental and numerical simulations within the entire analytical frequency band. The SEA model with considering the multi-physics coupling was effective

Ameliorative effect of Draba nemorosa extract on chronic heart failure in rats

Purpose: To evaluate the effect of Draba nemorosa extract (DNE) on oxidative stress and hemodynamics in rats with chronic congestive heart failure (CHF).Methods: Adriamycin was used to establish CHF in Sprague Dawley (SD) rat model. Six groups of SD rats were used in this study: control group, CHF group, captopril group (0.1 g/kg), as well as high-, medium- and low-dose DNE groups (5.2, 2.6 and 1.3 g/kg, respectively). Treatment for all groups lasted 4 weeks. Blood pressure and heart index were measured. In addition, serum creatine kinase (CK), superoxide dismutase (SOD), malondialdehyde (MDA), nitric oxide (NO) and nitric oxide synthase (NOS) were determined with enzyme-linked immunosorbent assay (ELISA) kits.Results: In the CHF group, arterial systolic pressure (SBP, 84.22 ± 16.23 mmHg); diastolic pressure (DBP, 77.36 ± 20.29 mmHg); mean arterial pressure (MAP, 78.45 ± 10.56 mmHg); heart rate (HR, 357.18 ± 37.34 beats/min) and left ventricular systolic peak (LVSP, 102.34 ± 16.37 mmHg) were significantly decreased (p < 0.05) when compared with the control group. However, left ventricular end diastolic pressure (LVEDP, 23.38 ± 1.78 mmHg); heart index (2.74 ± 0.16 mg/g); serum CK (0.87 ± 0.15 U/mL); MDA (19.34 ± 2.57 nmol/mL), NO (38.43 ± 3.32 umol/L) and NOS (42.65 ± 3.32 U/mL) were increased. Treatment with high-dose DNE significantly ameliorated hemodynamic function, and reduced MDA (9.13 ± 2.12 nmol/mL) and NO (22.37 ± 3.16 umol/L) levels (p < 0.05). High-dose DNE also led to significant decreases in CK (0.53 ± 0.35 U/mL) and NOS (24.27 ± 3.55U/mL) in the CHF rats (p < 0.05).Conclusion: DNE significantly improves hemodynamic function in CHF rats. Thus, it has a potential for development into a new drug for clinical treatment of CHF.Keywords: Draba nemorosa, Adriamycin, Chronic heart failure, Hemodynamic function, Oxidative stres

THERMAL OSCILLATION ARISING IN A HEAT SHOCK OF A POROUS HIERARCHY AND ITS APPLICATION

A building or a bridge might collapse after a heat shock. This paper shows that a porous hierarchy of a coating can effectively prevent a building or a bridge from such damage. A cocoon’s geometrical structure is studied and its resistance to the heat shock is revealed by a thermal oscillator. The theoretical model reveals an extremely low frequency of the thermal oscillator, which is very important for cocoons’ biomechanism, especially in the heat insulation function. At the same time, it shows that the cocoons have the best thickness to protect the pupa from the environment. In addition, surface temperature measurement of hierarchical mulberry leaves is performed. This work provides new insights into biomimetic design of the protective building and coatings

Enhancing Hydrogen Generation Through Nanoconfinement of Sensitizers and Catalysts in a Homogeneous Supramolecular Organic Framework.

Enrichment of molecular photosensitizers and catalysts in a confined nanospace is conducive for photocatalytic reactions due to improved photoexcited electron transfer from photosensitizers to catalysts. Herein, the self-assembly of a highly stable 3D supramolecular organic framework from a rigid bipyridine-derived tetrahedral monomer and cucurbit[8]uril in water, and its efficient and simultaneous intake of both [Ru(bpy)3 ]2+ -based photosensitizers and various polyoxometalates, that can take place at very low loading, are reported. The enrichment substantially increases the apparent concentration of both photosensitizer and catalyst in the interior of the framework, which leads to a recyclable, homogeneous, visible light-driven photocatalytic system with 110-fold increase of the turnover number for the hydrogen evolution reaction

Various generative adversarial networks model for synthetic prohibitory sign image generation

A synthetic image is a critical issue for computer vision. Traffic sign images synthesized from standard models are commonly used to build computer recognition algorithms for acquiring more knowledge on various and low-cost research issues. Convolutional Neural Network (CNN) achieves excellent detection and recognition of traffic signs with sufficient annotated training data. The consistency of the entire vision system is dependent on neural networks. However, locating traffic sign datasets from most countries in the world is complicated. This work uses various generative adversarial networks (GAN) models to construct intricate images, such as Least Squares Generative Adversarial Networks (LSGAN), Deep Convolutional Generative Adversarial Networks (DCGAN), and Wasserstein Generative Adversarial Networks (WGAN). This paper also discusses, in particular, the quality of the images produced by various GANs with different parameters. For processing, we use a picture with a specific number and scale. The Structural Similarity Index (SSIM) and Mean Squared Error (MSE) will be used to measure image consistency. Between the generated image and the corresponding real image, the SSIM values will be compared. As a result, the images display a strong similarity to the real image when using more training images. LSGAN outperformed other GAN models in the experiment with maximum SSIM values achieved using 200 images as inputs, 2000 epochs, and size 32 × 32

Dense 3D Facial Reconstruction from a Single Depth Image in Unconstrained Environment

With the increasing demands of applications in virtual reality such as 3D films, virtual Human-Machine Interactions and virtual agents, the analysis of 3D human face analysis is considered to be more and more important as a fundamental step for those virtual reality tasks. Due to information provided by an additional dimension, 3D facial reconstruction enables aforementioned tasks to be achieved with higher accuracy than those based on 2D facial analysis. The denser the 3D facial model is, the more information it could provide. However, most existing dense 3D facial reconstruction methods require complicated processing and high system cost. To this end, this paper presents a novel method that simplifies the process of dense 3D facial reconstruction by employing only one frame of depth data obtained with an off-the-shelf RGB-D sensor. The experiments showed competitive results with real world data