Holographic study on the jet quenching parameter in anisotropic systems

We first calculate the jet quenching parameter of an anisotropic plasma with a U(1) chemical potential via the AdS/CFT duality. The effects of charge, anisotropy parameter and quark motion direction on the jet quenching parameter are investigated. We then discuss the situation of anisotropic black brane in the IR region. We study both the jet quenching parameters along the longitudinal direction and transverse plane

Developing a Design Intervention for Academic Procrastination

Abstract This study aims to develop a product or service that can reduce academic procrastination among college students. The current literature suggests that there is a gap in research; existing techniques are debatable and no scientific research appears to be available that tests the success of existing products (such as time management planners). The method of approach for this study is to learn about the experiences of college students and their specific manifestations of procrastination. A convenience sample of college students will be used to conduct product development testing of the design. This thesis work is expected to have important applications to product design, and also disciplines that concern student well-being such as academic counseling and self-regulation. Keywords: academic procrastination, college students, time managemen

A Detailed Loss Analysis Methodology for Centrifugal Compressors

A deep understanding of loss mechanisms inside a turbomachine is crucial for the design and analysis work. By quantifying the various losses generated from different flow mechanisms, a targeted optimization can be carried out on the blading design. In this paper, an evaluation method for computational fluid dynamics (CFD) simulations has been developed to quantify the loss generation based on entropy production in the flow field. A breakdown of losses caused by different mechanisms (such as skin friction, secondary flow, tip clearance vortex, and shock waves) is achieved by separating the flow field into different zones. Each zone is defined by the flow physics rather than by geometrical locations or empirical correlations, which makes the method a more general approach and applicable to different machine types. The method has been applied to both subsonic and transonic centrifugal compressors, where internal flow is complex due to the Coriolis acceleration and the curvature effect. An evaluation of loss decomposition is obtained at various operational conditions. The impact of design modification is also assessed by applying the same analysis to an optimized design

Low-threshold room-temperature AlGaAs/GaAs nanowire/single-quantum-well heterostructure laser

Near-infrared nanowire lasers are promising as ultrasmall, low-consumption light emitters in on-chip optical communications and computing systems. Here, we report on a room-temperature near-infrared nanolaser based on an AlGaAs/GaAs nanowire/single-quantum-well heterostructure grown by Au-catalyzed metal organic chemical vapor deposition. When subjects to pulsed optical excitation, the nanowire exhibits lasing, with a low threshold of 600 W/cm2, a narrow linewidth of 0.39 nm, and a high Q factor of 2000 at low temperature. Lasing is observed up to 300 K, with an ultrasmall temperature dependent wavelength shift of 0.045 nm/K. This work paves the way towards ultrasmall, low-consumption, and high-temperature-stability near-infrared nanolasers

Attributed Multi-order Graph Convolutional Network for Heterogeneous Graphs

Heterogeneous graph neural networks aim to discover discriminative node embeddings and relations from multi-relational networks.One challenge of heterogeneous graph learning is the design of learnable meta-paths, which significantly influences the quality of learned embeddings.Thus, in this paper, we propose an Attributed Multi-Order Graph Convolutional Network (AMOGCN), which automatically studies meta-paths containing multi-hop neighbors from an adaptive aggregation of multi-order adjacency matrices. The proposed model first builds different orders of adjacency matrices from manually designed node connections. After that, an intact multi-order adjacency matrix is attached from the automatic fusion of various orders of adjacency matrices. This process is supervised by the node semantic information, which is extracted from the node homophily evaluated by attributes. Eventually, we utilize a one-layer simplifying graph convolutional network with the learned multi-order adjacency matrix, which is equivalent to the cross-hop node information propagation with multi-layer graph neural networks. Substantial experiments reveal that AMOGCN gains superior semi-supervised classification performance compared with state-of-the-art competitors

A Robust Hybrid Approach Based on Estimation of Distribution Algorithm and Support Vector Machine for Hunting Candidate Disease Genes

Microarray data are high dimension with high noise ratio and relatively small sample size, which makes it a challenge to use microarray data to identify candidate disease genes. Here, we have presented a hybrid method that combines estimation of distribution algorithm with support vector machine for selection of key feature genes. We have benchmarked the method using the microarray data of both diffuse B cell lymphoma and colon cancer to demonstrate its performance for identifying key features from the profile data of high-dimension gene expression. The method was compared with a probabilistic model based on genetic algorithm and another hybrid method based on both genetics algorithm and support vector machine. The results showed that the proposed method provides new computational strategy for hunting candidate disease genes from the profile data of disease gene expression. The selected candidate disease genes may help to improve the diagnosis and treatment for diseases

Quantum Security of TNT

Many classical secure structures are broken by quantum attacks. Evaluating the quantum security of a structure and providing a tight security bound is a challenging research area. As a tweakable block cipher structure based on block ciphers, $\mathsf{TNT}$ was proven to have $O(2^{3n/4})$ CPA and $O(2^{n/2})$ CCA security in the classical setting. We prove that $\mathsf{TNT}$ is a quantum-secure tweakable block cipher with a bound of $O(2^{n/6})$. In addition, we show the tight quantum PRF security bound of $O(2^{n/3})$ when $\mathsf{TNT}$ is based on random functions, which is better than $O(2^{n/4})$ given by Bhaumik et al. and solves their open problem. Our proof uses the recording standard oracle with errors technique of Hosoyamada and Iwata based on Zhandry’s compressed oracle technique

The pattern of late gadolinium enhancement by cardiac MRI in fulminant myocarditis and its prognostic implication: a two-year follow-up study

BackgroundMyocardial fibrosis, as quantified by late gadolinium enhancement (LGE) in cardiac magnetic resonance (CMR), provides valuable prognostic information for patients with myocarditis. However, due to the low incidence rate of fulminant myocarditis (FM) and accordingly small sample size, the knowledge about the role of LGE to patients with FM is limited.Methods and resultsA total of 44 adults with viral-FM receiving the Chinese treating regimen were included in this retrospective study. They were divided into the low LGE group and the high LGE group according to the ratio of LGE to left ventricular mass (LGE mass%). CMR exams and LGE were performed after hemodynamic assistance at discharge in all patients with FM. Routine echocardiography parameters and global longitudinal strain (GLS) at discharge and at 2-year follow-up were obtained and then compared. Both left ventricular ejection fraction (LVEF) and GLS showed no significant difference in both groups at discharge, whereas significant differences were observed at 2-year follow-up between two groups. Moreover, there were significant improvements of LVEF and GLS in the low LGE group, but not in the high LGE group during the 2-year period. Furthermore, LGE mass% was negatively correlated with GLS and LVEF.ConclusionsThere were two distinct forms of LGE presentation in patients with FM. Moreover, the cardiac function of patients with low LGE was significantly better than those with high LGE at 2-year follow-up. LGE mass% at discharge provided significant prognosis information about cardiac function of patients with FM