Crosstalk Impacts on Homogeneous Weakly-Coupled Multicore Fiber Based IM/DD System

We numerically discussed crosstalk impacts on homogeneous weakly-coupled multicore fiber based intensity modulation/direct-detection (IM/DD) systems taking into account mean crosstalk power fluctuation, walk-off between cores, laser frequency offset, and laser linewidth.Comment: 3 pages, 11 figures

Human Vault Nanoparticle Targeted Delivery of Antiretroviral Drugs to Inhibit Human Immunodeficiency Virus Type 1 Infection.

"Vaults" are ubiquitously expressed endogenous ribonucleoprotein nanoparticles with potential utility for targeted drug delivery. Here, we show that recombinant human vault nanoparticles are readily engulfed by certain key human peripheral blood mononuclear cells (PBMC), predominately dendritic cells, monocytes/macrophages, and activated T cells. As these cell types are the primary targets for human immunodeficiency virus type 1 (HIV-1) infection, we examined the utility of recombinant human vaults for targeted delivery of antiretroviral drugs. We chemically modified three different antiretroviral drugs, zidovudine, tenofovir, and elvitegravir, for direct conjugation to vaults. Tested in infection assays, drug-conjugated vaults inhibited HIV-1 infection of PBMC with equivalent activity to free drugs, indicating vault delivery and drug release in the cytoplasm of HIV-1-susceptible cells. The ability to deliver functional drugs via vault nanoparticle conjugates suggests their potential utility for targeted drug delivery against HIV-1

Approximate Dual Averaging Method for Multiagent Saddle-Point Problems with Stochastic Subgradients

This paper considers the problem of solving the saddle-point problem over a network, which consists of multiple interacting agents. The global objective function of the problem is a combination of local convex-concave functions, each of which is only available to one agent. Our main focus is on the case where the projection steps are calculated approximately and the subgradients are corrupted by some stochastic noises. We propose an approximate version of the standard dual averaging method and show that the standard convergence rate is preserved, provided that the projection errors decrease at some appropriate rate and the noises are zero-mean and have bounded variance

Improved Dynamic Regret of Distributed Online Multiple Frank-Wolfe Convex Optimization

In this paper, we consider a distributed online convex optimization problem over a time-varying multi-agent network. The goal of this network is to minimize a global loss function through local computation and communication with neighbors. To effectively handle the optimization problem with a high-dimensional and structural constraint set, we develop a distributed online multiple Frank-Wolfe algorithm to avoid the expensive computational cost of projection operation. The dynamic regret bounds are established as $\mathcal{O}(T^{1-\gamma}+H_T)$ with the linear oracle number $\mathcal{O} (T^{1+\gamma})$, which depends on the horizon (total iteration number) $T$, the function variation $H_T$, and the tuning parameter $0<\gamma<1$. In particular, when the prior knowledge of $H_T$ and $T$ is available, the bound can be enhanced to $\mathcal{O} (1+H_T)$. Moreover, we illustrate the significant advantages of the multiple iteration technique and reveal a trade-off between dynamic regret bound, computational cost, and communication cost. Finally, the performance of our algorithm is verified and compared through the distributed online ridge regression problems with two constraint sets

Improved ASR for Under-Resourced Languages Through Multi-Task Learning with Acoustic Landmarks

Furui first demonstrated that the identity of both consonant and vowel can be perceived from the C-V transition; later, Stevens proposed that acoustic landmarks are the primary cues for speech perception, and that steady-state regions are secondary or supplemental. Acoustic landmarks are perceptually salient, even in a language one doesn't speak, and it has been demonstrated that non-speakers of the language can identify features such as the primary articulator of the landmark. These factors suggest a strategy for developing language-independent automatic speech recognition: landmarks can potentially be learned once from a suitably labeled corpus and rapidly applied to many other languages. This paper proposes enhancing the cross-lingual portability of a neural network by using landmarks as the secondary task in multi-task learning (MTL). The network is trained in a well-resourced source language with both phone and landmark labels (English), then adapted to an under-resourced target language with only word labels (Iban). Landmark-tasked MTL reduces source-language phone error rate by 2.9% relative, and reduces target-language word error rate by 1.9%-5.9% depending on the amount of target-language training data. These results suggest that landmark-tasked MTL causes the DNN to learn hidden-node features that are useful for cross-lingual adaptation.Comment: Submitted in Interspeech201

Identification of rat lung-specific microRNAs by micoRNA microarray: valuable discoveries for the facilitation of lung research

BACKGROUND: An important mechanism for gene regulation utilizes small non-coding RNAs called microRNAs (miRNAs). These small RNAs play important roles in tissue development, cell differentiation and proliferation, lipid and fat metabolism, stem cells, exocytosis, diseases and cancers. To date, relatively little is known about functions of miRNAs in the lung except lung cancer. RESULTS: In this study, we utilized a rat miRNA microarray containing 216 miRNA probes, printed in-house, to detect the expression of miRNAs in the rat lung compared to the rat heart, brain, liver, kidney and spleen. Statistical analysis using Significant Analysis of Microarray (SAM) and Tukey Honestly Significant Difference (HSD) revealed 2 miRNAs (miR-195 and miR-200c) expressed specifically in the lung and 9 miRNAs co-expressed in the lung and another organ. 12 selected miRNAs were verified by Northern blot analysis. CONCLUSION: The identified lung-specific miRNAs from this work will facilitate functional studies of miRNAs during normal physiological and pathophysiological processes of the lung