The essential role of mitochondrial dynamics in antiviral immunity.

Viruses alter cellular physiology and function to establish cellular environment conducive for viral proliferation. Viral immune evasion is an essential aspect of viral persistence and proliferation. The multifaceted mitochondria play a central role in many cellular events such as metabolism, bioenergetics, cell death, and innate immune signaling. Recent findings accentuate that viruses regulate mitochondrial function and dynamics to facilitate viral proliferation. In this review, we will discuss how viruses exploit mitochondrial dynamics to modulate mitochondria-mediated antiviral innate immune response during infection. This review will provide new insight to understanding the virus-mediated alteration of mitochondrial dynamics and functions to perturb host antiviral immune signaling

Nb-doped TiO2 air-electrode for advanced Li-air batteries

As new substrate materials to replace a conventional carbon substrate, TiO2 and Nb-doped TiO2 air-electrodes for Li-air batteries were investigated. Through a simple two-step process, we successfully synthesized anatase Nb-doped TiO2 nanoparticles and demonstrated the potential applicability of TiO2-based materials for use in Li-air battery electrode. An air-electrode with Nb-doped TiO2 nanoparticles could deliver a higher discharge capacity than a bare TiO2 electrode due to the enhanced conductivity, which implies the importance of facile electron transport during the discharge process. © 2014 The Ceramic Society of Japan and the Korean Ceramic Society.

Dynamic All-Red Signal Control Based on Deep Neural Network Considering Red Light Runner Characteristics

Despite recent advances in technologies for intelligent transportation systems, the safety of intersection traffic is still threatened by traffic signal violation, called the Red Light Runner (RLR). The conventional approach to ensure the intersection safety under the threat of an RLR is to extend the length of the all-red signal when an RLR is detected. Therefore, the selection of all-red signal length is an important factor for intersection safety as well as traffic efficiency. In this paper, for better safety and efficiency of intersection traffic, we propose a framework for dynamic all-red signal control that adjusts the length of all-red signal time according to the driving characteristics of the detected RLR. In this work, we define RLRs into four different classes based on the clustering results using the Dynamic Time Wrapping (DTW) and the Hierarchical Clustering Analysis (HCA). The proposed system uses a Multi-Channel Deep Convolutional Neural Network (MC-DCNN) for online detection of RLR and also classification of RLR class. For dynamic all-red signal control, the proposed system uses a multi-level regression model to estimate the necessary all-red signal extension time more accurately and hence improves the overall intersection traffic safety as well as efficiency. © 2020 by the authors.1