Towards Semantic Fast-Forward and Stabilized Egocentric Videos

The emergence of low-cost personal mobiles devices and wearable cameras and the increasing storage capacity of video-sharing websites have pushed forward a growing interest towards first-person videos. Since most of the recorded videos compose long-running streams with unedited content, they are tedious and unpleasant to watch. The fast-forward state-of-the-art methods are facing challenges of balancing the smoothness of the video and the emphasis in the relevant frames given a speed-up rate. In this work, we present a methodology capable of summarizing and stabilizing egocentric videos by extracting the semantic information from the frames. This paper also describes a dataset collection with several semantically labeled videos and introduces a new smoothness evaluation metric for egocentric videos that is used to test our method.Comment: Accepted for publication and presented in the First International Workshop on Egocentric Perception, Interaction and Computing at European Conference on Computer Vision (EPIC@ECCV) 201

Unsupervised Video Summarization via Attention-Driven Adversarial Learning

This paper presents a new video summarization approach that integrates an attention mechanism to identify the signi cant parts of the video, and is trained unsupervisingly via generative adversarial learning. Starting from the SUM-GAN model, we rst develop an improved version of it (called SUM-GAN-sl) that has a signi cantly reduced number of learned parameters, performs incremental training of the model's components, and applies a stepwise label-based strategy for updating the adversarial part. Subsequently, we introduce an attention mechanism to SUM-GAN-sl in two ways: i) by integrating an attention layer within the variational auto-encoder (VAE) of the architecture (SUM-GAN-VAAE), and ii) by replacing the VAE with a deterministic attention auto-encoder (SUM-GAN-AAE). Experimental evaluation on two datasets (SumMe and TVSum) documents the contribution of the attention auto-encoder to faster and more stable training of the model, resulting in a signi cant performance improvement with respect to the original model and demonstrating the competitiveness of the proposed SUM-GAN-AAE against the state of the art

Summarizing Videos with Attention

In this work we propose a novel method for supervised, keyshots based video summarization by applying a conceptually simple and computationally efficient soft, self-attention mechanism. Current state of the art methods leverage bi-directional recurrent networks such as BiLSTM combined with attention. These networks are complex to implement and computationally demanding compared to fully connected networks. To that end we propose a simple, self-attention based network for video summarization which performs the entire sequence to sequence transformation in a single feed forward pass and single backward pass during training. Our method sets a new state of the art results on two benchmarks TvSum and SumMe, commonly used in this domain.Comment: Presented at ACCV2018 AIU2018 worksho

Local adaptation in populations of Mycobacterium tuberculosis endemic to the Indian Ocean Rim

Background: Lineage 1 (L1) and 3 (L3) are two lineages of the Mycobacterium tuberculosis complex (MTBC) causing tuberculosis (TB) in humans. L1 and L3 are prevalent around the rim of the Indian Ocean, the region that accounts for most of the world's new TB cases. Despite their relevance for this region, L1 and L3 remain understudied. Methods: We analyzed 2,938 L1 and 2,030 L3 whole genome sequences originating from 69 countries. We reconstructed the evolutionary history of these two lineages and identified genes under positive selection. Results: We found a strongly asymmetric pattern of migration from South Asia toward neighboring regions, highlighting the historical role of South Asia in the dispersion of L1 and L3. Moreover, we found that several genes were under positive selection, including genes involved in virulence and resistance to antibiotics . For L1 we identified signatures of local adaptation at the esxH locus, a gene coding for a secreted effector that targets the human endosomal sorting complex, and is included in several vaccine candidates. Conclusions: Our study highlights the importance of genetic diversity in the MTBC, and sheds new light on two of the most important MTBC lineages affecting humans

Multiple introductions of Mycobacterium tuberculosis lineage 2-Beijing into Africa over centuries

The Lineage 2–Beijing (L2–Beijing) sub-lineage of Mycobacterium tuberculosis has received much attention due to its high virulence, fast disease progression, and association with antibiotic resistance. Despite several reports of the recent emergence of L2–Beijing in Africa, no study has investigated the evolutionary history of this sub-lineage on the continent. In this study, we used whole genome sequences of 781 L2 clinical strains from 14 geographical regions globally distributed to investigate the origins and onward spread of this lineage in Africa. Our results reveal multiple introductions of L2–Beijing into Africa linked to independent bacterial populations from East- and Southeast Asia. Bayesian analyses further indicate that these introductions occurred during the past 300 years, with most of these events pre-dating the antibiotic era. Hence, the success of L2–Beijing in Africa is most likely due to its hypervirulence and high transmissibility rather than drug resistance

Progress and Research Needs of Plant Biomass Degradation by Basidiomycete Fungi

Peer reviewe

Toward Reproducible Enzyme Modeling with Isothermal Titration Calorimetry

To apply enzymes in technical processes, a detailed understanding of the molecular mechanisms is required. Kinetic and thermodynamic parameters of enzyme catalysis are crucial to plan, model, and implement biocatalytic processes more efficiently. While the kinetic parameters, Km and kcat, are often accessible by optical methods, the determination of thermodynamic parameters requires more sophisticated methods. Isothermal titration calorimetry (ITC) allows the label-free and highly sensitive analysis of kinetic and thermodynamic parameters of individual steps in the catalytic cycle of an enzyme reaction. However, since ITC is susceptible to interferences due to denaturation or agglomeration of the enzymes, the homogeneity of the enzyme sample must always be considered, and this can be accomplished by means of dynamic light scattering (DLS) analysis. We here report on the use of an ITC-dependent work flow to determine both the kinetic and the thermodynamic data for a cofactor-dependent enzyme. Using a standardized approach with the implementation of sample quality control by DLS, we obtain high-quality data suitable for the advanced modeling of the enzyme reaction mechanism. Specifically, we investigated stereoselective reactions catalyzed by the NADPH-dependent ketoreductase Gre2p under different reaction conditions. The results revealed that this enzyme operates with an ordered sequential mechanism and is affected by substrate or product inhibition depending on the reaction buffer. Data reproducibility is ensured by specifying standard operating procedures, using programmed workflows for data analysis, and storing all data in a F.A.I.R. (findable, accessible, interoperable, and reusable) repository (https://doi.org/10.15490/fairdomhub.1.investigation.464.1). Our work highlights the utility for combined binding and kinetic studies for such complex multisubstrate reactions

Towards Reproducible Enzyme Modeling with Isothermal Titration Calorimetry

An experimental workflow to provide detailed information of the molecular mechanisms of enzymes is described. This workflow will help in the application of enzymes in technical processes by providing crucial parameters needed to plan, model and implement biocatalytic processes more efficiently. These parameters are homogeneity of the enzyme sample (HES), kinetic and thermodynamic parameters of enzyme kinetics and binding of reactants to enzymes. The techniques used to measure these properties are dynamic light scattering (DLS), UV-Vis spectrophotometry and isothermal titration calorimetry (ITC) respectively. The workflow is standardized by the use of SOPs and python-scripted data analysis. We have used the NADPH-dependent alcohol dehydrogenase Gre2p as a challenging enzyme to demonstrate the power of this workflow. Our work highlights the utility for combined binding and kinetic studies for such complex multi-substrate reactions and the importance of sample quality control during experiments. </div