INVESTIGATION OF THE EFFECTS OF SUBGRID-SCALE TURBULENCE ON RESOLVABLE-SCALE STATISTICS

The effects of the subgrid-scale (SGS) turbulence on the resolvable-scale statistics and the effects of SGS models on large-eddy simulation (LES) are studied. It is shown that the SGS turbulence evolves the resolvable-scale joint probability density function (JPDF) through the conditional means of the SGS stress, the SGS scalar flux, and their production rate, which must be reproduced by the SGS model for LES to predict correctly the one-point resolvable-scale statistics, a primary goal of LES. This necessary condition is used as the basis for studying SGS physics and for testing SGS models. Theoretical predictions, measurements data obtained in a turbulent jet and in a convective atmospheric surface layer, and large-eddy simulation data of convective atmospheric boundary layers are combined to investigate the effects of filter size, the dependence of the SGS turbulence on the flow dynamics, and SGS models performance using new statistical a priori and a posteriori tests developed in this research. Analyses of the results show that for the inertial-range filter scales SGS predictions of the mean statistics support the premise of LES at the level of lower-order statistics, but not the higher-order statistics. For the energy-containing filter scales the conditional statistics strongly depend on the resolvable-scale velocity and temperature fluctuations, indicating the strong influence of SGS turbulence on the resolvable-scale statistics. The current SGS models have varying levels of performance in predicting different SGS components. The results suggests that efforts to improve SGS models need to ensure that all the relevant SGS fluxes related to the LES statistics are correct predicted. Given the strong dependence of the conditional statistics on the flow dynamics, it may be necessary to incorporate some aspects of the dynamics to correctly predict these conditional statistics. The statistical a posteriori test results are generally consistent with the a priori test results. Similar model strengths and deficiencies are identified in both types of tests. Therefore, analyses of the conditional statistics can serve as an important guide in studying the SGS physics, identifying model deficiencies, and developing improved SGS models

Algorithm and Architecture for Path Metric Aided Bit-Flipping Decoding of Polar Codes

Polar codes attract more and more attention of researchers in recent years, since its capacity achieving property. However, their error-correction performance under successive cancellation (SC) decoding is inferior to other modern channel codes at short or moderate blocklengths. SC-Flip (SCF) decoding algorithm shows higher performance than SC decoding by identifying possibly erroneous decisions made in initial SC decoding and flipping them in the sequential decoding attempts. However, it performs not well when there are more than one erroneous decisions in a codeword. In this paper, we propose a path metric aided bit-flipping decoding algorithm to identify and correct more errors efficiently. In this algorithm, the bit-flipping list is generated based on both log likelihood ratio (LLR) based path metric and bit-flipping metric. The path metric is used to verify the effectiveness of bit-flipping. In order to reduce the decoding latency and computational complexity, its corresponding pipeline architecture is designed. By applying these decoding algorithms and pipeline architecture, an improvement on error-correction performance can be got up to 0.25dB compared with SCF decoding at the frame error rate of $10^{-4}$, with low average decoding latency.Comment: 6 pages, 6 figures, IEEE Wireless Communications and Networking Conference (2019 WCNC

A large-scale study of fashion influencers on Twitter

The rise of social media has changed the nature of the fashion industry. Influence is no longer concentrated in the hands of an elite few: social networks distribute power across a broad set of tastemakers; trends are driven bottom-up and top-down; and designers, retailers, and consumers are regularly inundated with new styles and looks. This thesis presents a large-scale study of fashion influencers on Twitter and proposes a fashion graph visualization dashboard to explore the social interactions between these Twitter accounts. Leveraging a dataset of 11.5k Twitter fashion accounts, a content-based classifier was trained to predict which accounts are fashion-centric. With the classifier, I identified more than 300k fashion-related accounts through a snowball crawling and then defined a stable group of 1000 influencers as the fashion core. I further human-labeled these influencers’ Twitter accounts and mine their recent tweets. Finally, I built a fashion graph visualization dashboard that allows users to visualize the interactions and relationships between individuals, brands, and media influencers

Neural activity dissociation between thought-based and perception-based response conflict

Based on the idea that intentions have different penetrability to perception and thought (Fodor, 1983), four Stroop-like tasks, AA, AW, WA, and WW are used, where the A represents an arrow and the CPPR (closest processing prior to response) is perception, and the W represents a word and the CPPR is thought. Event-related brain potentials were recorded as participants completed these tasks, and sLORETA (standardized low resolution brain electromagnetic tomography) was used to localize the sources at specific time points. These results showed that there is an interference effect in the AA and WA tasks, but not in the AW or WW tasks. The activated brain areas related to the interference effect in the AA task were the PFC and ACC, and PFC activation took place prior to ACC activation; but only PFC in WA task. Combined with previous results, a new neural mechanism of cognitive control is proposed

Transmission of antibiotic resistance genes in agroecosystems : an overview

The use of antibiotics in human medicine and animal husbandry has resulted in the continuous release of antibiotics into the environment, which imposes high selection pressure on bacteria to develop antibiotic resistance. The spread and aggregation of antibiotic resistance genes (ARGs) in multidrug-resistant pathogens is one of the most intractable clinical challenges. Numerous studies have been conducted to profile the patterns of ARGs in agricultural ecosystems, as this is closely related to human health and wellbeing. This paper provides an overview of the transmission of ARGs in agricultural ecosystems resulting from the application of animal manures and other organic amendments. The future need to control and mitigate the spread of antibiotic resistance in agricultural ecosystems is also discussed, particularly from a holistic perspective, and requires multiple sector efforts to translate fundamental knowledge into effective strategies

Atomic Layer Deposition of High Quality HfO\u3csub\u3e2\u3c/sub\u3e Using In-Situ Formed Hydrophilic Oxide as an Interfacial Layer

High-quality HfO2 cannot be grown directly on Si substrate using atomic layer deposition (ALD), and an interfacial oxide layer is needed. Traditionally, interfacial oxide layer is formed either in SC1 solution (2 NH4OH: 4 H2O2: 200 H2O) or by ozonated water spraying. A highly hydrophilic SiO2 interfacial layer was in-situ formed in the ALD chamber using 1 cycle of ozone and water. The HfO2 deposited on this interfacial layer showed great growth linearity. The gate leakage current is comparable to that formed using chemical oxide as the interfacial layer. The capacitance-voltage (C-V) curves have negligible frequency dispersion and hysteresis, which suggest high quality in both the interface and electrical properties. The in-situ formation of hydrophilic interfacial layer have advantages over the traditional interfacial layer. This might be useful for formation of interfacial layer on sophisticated 3-D MOS structures such as FinFETs and nanowire FETs. In addition, the chemical oxidation step can be eliminated from the integrated circuits manufacturing processes, which is economically beneficial to the industry