SeizureNet: Multi-Spectral Deep Feature Learning for Seizure Type Classification

Automatic classification of epileptic seizure types in electroencephalograms (EEGs) data can enable more precise diagnosis and efficient management of the disease. This task is challenging due to factors such as low signal-to-noise ratios, signal artefacts, high variance in seizure semiology among epileptic patients, and limited availability of clinical data. To overcome these challenges, in this paper, we present SeizureNet, a deep learning framework which learns multi-spectral feature embeddings using an ensemble architecture for cross-patient seizure type classification. We used the recently released TUH EEG Seizure Corpus (V1.4.0 and V1.5.2) to evaluate the performance of SeizureNet. Experiments show that SeizureNet can reach a weighted F1 score of up to 0.94 for seizure-wise cross validation and 0.59 for patient-wise cross validation for scalp EEG based multi-class seizure type classification. We also show that the high-level feature embeddings learnt by SeizureNet considerably improve the accuracy of smaller networks through knowledge distillation for applications with low-memory constraints

Predicting Future Instance Segmentation by Forecasting Convolutional Features

Anticipating future events is an important prerequisite towards intelligent behavior. Video forecasting has been studied as a proxy task towards this goal. Recent work has shown that to predict semantic segmentation of future frames, forecasting at the semantic level is more effective than forecasting RGB frames and then segmenting these. In this paper we consider the more challenging problem of future instance segmentation, which additionally segments out individual objects. To deal with a varying number of output labels per image, we develop a predictive model in the space of fixed-sized convolutional features of the Mask R-CNN instance segmentation model. We apply the "detection head'" of Mask R-CNN on the predicted features to produce the instance segmentation of future frames. Experiments show that this approach significantly improves over strong baselines based on optical flow and repurposed instance segmentation architectures

Integral Human Pose Regression

State-of-the-art human pose estimation methods are based on heat map representation. In spite of the good performance, the representation has a few issues in nature, such as not differentiable and quantization error. This work shows that a simple integral operation relates and unifies the heat map representation and joint regression, thus avoiding the above issues. It is differentiable, efficient, and compatible with any heat map based methods. Its effectiveness is convincingly validated via comprehensive ablation experiments under various settings, specifically on 3D pose estimation, for the first time

Effects of oxidation temperature on Ga 2O3 film thermally grown on GaN

The effects of oxidation temperature on thermally oxidized GaN film were investigated. The GaN wafers were oxidzied at 750 °C, 800 °C and 850 °C respectively. The electrical characteristics and interface quality of MOS capacitors were compared among different oxidation temperatures. The sample oxidized at 800 °C presented best current-voltage, capacitance-voltage characteristics and smoothest surface morphology, while the higher oxidation temperature of 850 °C gave best interface quality. The electrical breakdown field was increased by one order of magnitude when the sample was oxidized at 800 °C as compared with 750 °C and 850 °C. Lastly, after the sample oxidized at 800 °C was annealed at 850 °C for 10 min, the quality of its oxide was significantly degraded. © 2005 IEEE.published_or_final_versio

Packing While Traveling: Mixed Integer Programming for a Class of Nonlinear Knapsack Problems

Packing and vehicle routing problems play an important role in the area of supply chain management. In this paper, we introduce a non-linear knapsack problem that occurs when packing items along a fixed route and taking into account travel time. We investigate constrained and unconstrained versions of the problem and show that both are NP-hard. In order to solve the problems, we provide a pre-processing scheme as well as exact and approximate mixed integer programming (MIP) solutions. Our experimental results show the effectiveness of the MIP solutions and in particular point out that the approximate MIP approach often leads to near optimal results within far less computation time than the exact approach

Manual therapy in addition to physiotherapy does not improve clinical or economic outcomes after ankle fracture

Objective: The primary aim of this study was to determine the effectiveness and cost-effectiveness of adding manual therapy to a physiotherapy programme for ankle fracture. Design: Assessor-blinded randomized controlled trial. Participants: Ninety-four adults were recruited within one week of cast removal for isolated ankle fracture. Inclusion criteria were: they were able to weight-bear as tolerated or partial weight-bear, were referred for physiotherapy, and experienced pain. Ninety-one participants completed the study. Methods: Participants were randomly allocated to receive manual therapy (anterior-posterior joint mobilization over the talus) plus a standard physiotherapy programme (experimental), or the standard physiotherapy programme only (control). They were assessed by a blinded assessor at baseline, and at 4, 12 and 24 weeks. The main outcomes were activity limitation and quality of life. Information on costs and healthcare utilization was collected every 4 weeks up to 24 weeks. Results: There were no clinically worthwhile differences in activity limitation or quality of life between groups at any time-point. There was also no between-group difference in quality-adjusted life-years, but the experimental group incurred higher out-of-pocket costs (mean between-group difference = AU$200, 95% confidence interval 26-432). Conclusion: When provided in addition to a physiotherapy programme, manual therapy did not enhance outcome in adults after ankle fracture. © 2008 Foundation of Rehabilitation Information

Lasing oscillation in a three-dimensional photonic crystal nanocavity with a complete bandgap

We demonstrate lasing oscillation in a three-dimensional photonic crystal nanocavity. The laser is realized by coupling a cavity mode, which is localized in a complete photonic bandgap and exhibits the highest quality factor of ~38,500, with high-quality semiconductor quantum dots. We show a systematic change in the laser characteristics, including the threshold and the spontaneous emission coupling factor by controlling the crystal size, which consequently changes the strength of photon confinement in the third dimension. This opens up many interesting possibilities for realizing future ultimate light sources and three-dimensional integrated photonic circuits and for more fundamental studies of physics in the field of cavity quantum electrodynamics.Comment: 14 pages, 4 figure

Phase separation enhances probability of receptor signalling and drug targeting

The probability of a given receptor tyrosine kinase (RTK) triggering a defined cellular outcome is low because of the promiscuous nature of signalling, the randomness of molecular diffusion through the cell, and the ongoing nonfunctional submembrane signalling activity or noise. Signal transduction is therefore a ‘numbers game’, where enough cell surface receptors and effector proteins must initially be engaged to guarantee formation of a functional signalling complex against a background of redundant events. The presence of intracellular liquid–liquid phase separation (LLPS) at the plasma membrane provides a mechanism through which the probabilistic nature of signalling can be weighted in favour of the required, discrete cellular outcome and mutual exclusivity in signal initiation

Pandemic A/H1N1 2009 Influenza Virus-like Particles Elicited Higher and Broader Immune Responses than the Commercial Panenza Vaccine

Objectives: The aim was to construct 2009 pandemic A/H1N1 influenza VLPs (virus-like particles) and compare the immunogenicity and protection efficacy with the commercial Panenza vaccine in BALB/c mouse model. Methods: VLPs derived from influenza A/Hong Kong/01/2009 (H1N1) virus were constructed by Bac-to-Bac baculovirus expression system. VLPs were purified by sucrose density gradient ultracentrifugation and then characterized by Western blotting analysis and transmission electron microscopy. After single dose vaccination with 3 µg of VLPs and equal amount of Panenza vaccine, the immune responses and efficacy of protection induced by VLPs were compared with those elicited by the Panenza vaccine in 6-8 week female BALB/c mice. Key findings: VLPs could induce higher antibody titer as determined by hemagglutinin inhibition and microneutralization assay. Furthermore, we demonstrated that VLPs induced better antibody response to neuraminidase. In addition, VLP vaccinated mice had stronger cell-mediated immune response. As a result, our VLPs conferred 100% protection while the Panenza vaccine only conferred 67% protection. Conclusion: From the results, we concluded that influenza VLPs are highly immunogenic and they are promising to be developed as an alternative strategy to vaccine production in order to control the spread of influenza viruses.published_or_final_versio