Applying Deep Learning for Phase-Array Antenna Design

Master of Engineering (Electrical Engineering), 2021Hybrid beamforming (HBF) can provide rapid data transmission rates while reducing the complexity and cost of massive multiple-input multiple-output (MIMO) systems. However, channel state information (CSI) is imperfect in realistic downlink channels, introducing challenges to hybrid beamforming (HBF) design. For HBF designs, we had a hard time finding the proper labels. If we use the optimized output based on the traditional algorithm as the label, the neural network can only be trained to approximate the traditional algorithm, but not better than the traditional algorithm. This thesis proposes a hybrid beamforming neural network based on unsupervised deep learning (USDNN) to prevent the labeling overhead of supervised learning and improve the achievable sum rate based on imperfect CSI. Compared with the traditional HBF method, the unsupervised learning-based method can avoid the labeling overhead as well as obtain better performance than the traditional algorithm. The network consists of 5 dense layers, 4 batch normalization (BN) layers and 5 activation functions. After training, the optimized beamformer can be obtained, and the optimized beamforming vector can be directly output. The simulation results show that our proposed method is 74% better than manifold optimization (MO) and 120% better than orthogonal match pursuit (OMP) systems. Furthermore, our proposed USDNN can achieve near-optimal performance

Suspension and Measurement of Graphene and Bi2Se3 Atomic Membranes

Coupling high quality, suspended atomic membranes to specialized electrodes enables investigation of many novel phenomena, such as spin or Cooper pair transport in these two dimensional systems. However, many electrode materials are not stable in acids that are used to dissolve underlying substrates. Here we present a versatile and powerful multi-level lithographical technique to suspend atomic membranes, which can be applied to the vast majority of substrate, membrane and electrode materials. Using this technique, we fabricated suspended graphene devices with Al electrodes and mobility of 5500 cm^2/Vs. We also demonstrate, for the first time, fabrication and measurement of a free-standing thin Bi2Se3 membrane, which has low contact resistance to electrodes and a mobility of >~500 cm^2/Vs

Role of CD56-expressing immature biliary epithelial cells in biliary atresia

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Effect of α7 nicotinic acetylcholine receptor activation on cardiac fibroblasts: A mechanism underlying RV fibrosis associated with cigarette smoke exposure

INTRODUCTION: Right ventricular dysfunction is associated with numerous smoking-related illnesses including chronic obstructive pulmonary disease (COPD) where it is present even in absence of pulmonary hypertension. It is unknown if exposure to cigarette smoke has direct effects on RV function and cardiac fibroblast proliferation or collagen synthesis. In this study, we evaluated cardiac function and fibrosis in mice exposed to cigarette smoke (CS) and determined mechanisms of smoke-induced changes in cardiac fibroblast signaling and fibrosis. METHODS: AKR mice were exposed to cigarette smoke for six weeks followed by echocardiography and evaluation of cardiac hypertrophy, collagen content, and pulmonary muscularization. Proliferation and collagen content were evaluated in primary isolated rat cardiac fibroblasts (CF) exposed to cigarette smoke extract (CSE) or nicotine. Markers of cell proliferation, fibrosis, and proliferative signaling were determined by immunoblot or Sircol collagen assay. RESULTS: Mice exposed to CS had significantly decreased RV function as determined by TAPSE. There were no changes in LV parameters. RV collagen content was significantly elevated but there was no change in RV hypertrophy or pulmonary vascular muscularization. CSE directly increased cardiac fibroblast proliferation and collagen content in CF. Nicotine alone reproduced these effects. CSE and nicotine-induced fibroblast proliferation and collagen content were mediated through α7 nicotinic acetylcholine receptors and were dependent on PKC-α, PKC-δ, and reduced p38-MAPK phosphorylation. CONCLUSION: CS and nicotine have direct effects on cardiac fibroblasts to induce proliferation and fibrosis which may negatively affect right heart function

Enhancement of the magnetic anisotropy of nanometer-sized Co clusters: influence of the surface and of the inter-particle interactions

We study the magnetic properties of spherical Co clusters with diameters between 0.8 nm and 5.4 nm (25 to 7500$ atoms) prepared by sequential sputtering of Co and Al2O3. The particle size distribution has been determined from the equilibrium susceptibility and magnetization data and it is compared to previous structural characterizations. The distribution of activation energies was independently obtained from a scaling plot of the ac susceptibility. Combining these two distributions we have accurately determined the effective anisotropy constant Keff. We find that Keff is enhanced with respect to the bulk value and that it is dominated by a strong anisotropy induced at the surface of the clusters. Interactions between the magnetic moments of adjacent layers are shown to increase the effective activation energy barrier for the reversal of the magnetic moments. Finally, this reversal is shown to proceed classically down to the lowest temperature investigated (1.8 K).Comment: 13 figures submitted to Phys. Rev.

Pricing and quality investments in a mixed brown-green product market

Sustainable Supply Chain Management (SSCM) has assumed a position of prominence for academics and industry over the last two decades. The sustainability literature shows that typically manufacturers aim to optimize their pricing and greening level decisions in a mixed (green and brown) consumer market. In this work, we capture a manufacturer’s classic dilemma on the pricing of green and brown products, and greening investments, while subject to budget constraint. We compute and analyze the variations of optimal decisions over time. Our findings underscore the importance of investing in greening technologies and learning for the survival of green products. Furthermore, we show that a manufacturer’s optimal pricing strategy is to enter the market with a lower price for the green product and to increase it over time, eventually, surpassing the price for the brown product. Our analysis reveals that the greening level attraction can nullify the effect of a high price on the green product, resulting in higher green demand than brown. Higher green product demand is a win-win situation for both the manufacturer and the environment

A Condensation-Ordering Mechanism in Nanoparticle-Catalyzed Peptide Aggregation

Nanoparticles introduced in living cells are capable of strongly promoting the aggregation of peptides and proteins. We use here molecular dynamics simulations to characterise in detail the process by which nanoparticle surfaces catalyse the self- assembly of peptides into fibrillar structures. The simulation of a system of hundreds of peptides over the millisecond timescale enables us to show that the mechanism of aggregation involves a first phase in which small structurally disordered oligomers assemble onto the nanoparticle and a second phase in which they evolve into highly ordered beta-sheets as their size increases

Anticancer Gene Transfer for Cancer Gene Therapy

Gene therapy vectors are among the treatments currently used to treat malignant tumors. Gene therapy vectors use a specific therapeutic transgene that causes death in cancer cells. In early attempts at gene therapy, therapeutic transgenes were driven by non-specific vectors which induced toxicity to normal cells in addition to the cancer cells. Recently, novel cancer specific viral vectors have been developed that target cancer cells leaving normal cells unharmed. Here we review such cancer specific gene therapy systems currently used in the treatment of cancer and discuss the major challenges and future directions in this field

Exploring morphological correlations among H2CO, 12CO, MSX and continuum mappings

There are relatively few H2CO mappings of large-area giant molecular cloud (GMCs). H2CO absorption lines are good tracers for low-temperature molecular clouds towards star formation regions. Thus, the aim of the study was to identify H2CO distributions in ambient molecular clouds. We investigated morphologic relations among 6-cm continuum brightness temperature (CBT) data and H2CO (111-110; Nanshan 25-m radio telescope), 12CO (1--0; 1.2-m CfA telescope) and midcourse space experiment (MSX) data, and considered the impact of background components on foreground clouds. We report simultaneous 6-cm H2CO absorption lines and H110\alpha radio recombination line observations and give several large-area mappings at 4.8 GHz toward W49 (50'\times50'), W3 (70'\times90'), DR21/W75 (60'\times90') and NGC2024/NGC2023 (50'\times100') GMCs. By superimposing H2CO and 12CO contours onto the MSX color map, we can compare correlations. The resolution for H2CO, 12CO and MSX data was about 10', 8' and 18.3", respectively. Comparison of H2CO and 12CO contours, 8.28-\mu m MSX colorscale and CBT data revealed great morphological correlation in the large area, although there are some discrepancies between 12CO and H2CO peaks in small areas. The NGC2024/NGC2023 GMC is a large area of HII regions with a high CBT, but a H2CO cloud to the north is possible against the cosmic microwave background. A statistical diagram shows that 85.21% of H2CO absorption lines are distributed in the intensity range from -1.0 to 0 Jy and the \Delta V range from 1.206 to 5 km/s.Comment: 18 pages, 22 figures, 5 tables. Accepted to be published in Astrophysics and Space Scienc