Convolutional Neural Network based action recognition methods have achieved significant improvements in recent years. The 3D convolution extends the 2D convolution from operating on one single frame to a video clip, so it is able to extract effective spatial-temporal features for better analysis of human activities in videos. The 3D convolution, however, involves many more parameters than 2D

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This paper investigates a full duplex wirelesspowered two way communication networks, where two hybrid access points (HAP) and a number of amplify and forward (AF) relays both operate in full duplex scenario. We use time switching (TS) and static power splitting (SPS) schemes with two way full duplex wireless-powered networks as a benchmark. Then the new time division duplexing static power splitting (TDD SPS) and full duplex static power splitting (FDSPS) schemes as well as a simple relay selection strategy are proposed to improve the system performance. For TS, SPS and FDSPS, the best relay harvests energy using the received RF signal from HAPs and uses harvested energy to transmit signal to each HAP at the same frequency and time, therefore only partial self-interference (SI) cancellation needs to be considered in the FDSPS case. For the proposed TDD SPS, the best relay harvests the energy from the HAP and its self-interference. Then we derive closed-form expressions for the throughput and outage probability for delay limited transmissions over Rayleigh fading channels. Simulation results are presented to evaluate the effectiveness of the proposed scheme with different system key parameters, such as time allocation, power splitting ratio and residual SI

RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific threedimensional conformations to enable their functions. Experimental determination of high-resolution RNA structures using x-ray crystallography is both laborious and demands expertise, thus, hindering our comprehension of RNA structural biology. The computational modeling of RNA structure was a milestone in the birth of bioinformatics. Although computational modeling has been greatly improved over the last decade showing many successful cases, the accuracy of such computational modeling is not only length-dependent but also varies according to the complexity of the structure. To increase credibility, various experimental data were integrated into computational modeling. In this review, we summarize the experiments that can be integrated into RNA structure modeling as well as the computational methods based on these experimental data. We also demonstrate how computational modeling can help the experimental determination of RNA structure. We highlight the recent advances in computational modeling which can offer reliable structure models using high-throughput experimental data.

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BackgroundThe great advances of nanomaterials have brought out broad important applications, but their possible nanotoxicity and risks have not been fully understood. It is confirmed that exposure of environmental particulate matter (PM), especially ultrafine PM, are responsible for many lung function impairment and exacerbation of pre-existing lung diseases. However, the adverse effect of nanoparticles on allergic asthma is seldom investigated and the mechanism remains undefined. For the first time, this work investigates the relationship between allergic asthma and nanosized silicon dioxide (nano-SiO2).Methodology/Principal FindingsOvalbumin (OVA)-treated and saline-treated control rats were daily intratracheally administered 0.1 ml of 0, 40 and 80 µg/ml nano-SiO2 solutions, respectively for 30 days. Increased nano-SiO2 exposure results in adverse changes on inspiratory and expiratory resistance (Ri and Re), but shows insignificant effect on rat lung dynamic compliance (Cldyn). Lung histological observation reveals obvious airway remodeling in 80 µg/ml nano-SiO2-introduced saline and OVA groups, but the latter is worse. Additionally, increased nano-SiO2 exposure also leads to more severe inflammation. With increasing nano-SiO2 exposure, IL-4 in lung homogenate increases and IFN-γ shows a reverse but insignificant change. Moreover, at a same nano-SiO2 exposure concentration, OVA-treated rats exhibit higher (significant) IL-4 and lower (not significant) IFN-γ compared with the saline-treated rats. The percentages of eosinophil display an unexpected result, in which higher exposure results lower eosinophil percentages.Conclusions/SignificanceThis was a preliminary study which for the first time involved the effect of nano-SiO2 to OVA induced rat asthma model. The results suggested that intratracheal administration of nano-SiO2 could lead to the airway hyperresponsiveness (AHR) and the airway remolding with or without OVA immunization. This occurrence may be due to the Th1/Th2 cytokine imbalance accelerated by the nano-SiO2 through increasing the tissue IL-4 production.

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