Marginalized average attentional network for weakly-supervised learning

© 7th International Conference on Learning Representations, ICLR 2019. All Rights Reserved. In weakly-supervised temporal action localization, previous works have failed to locate dense and integral regions for each entire action due to the overestimation of the most salient regions. To alleviate this issue, we propose a marginalized average attentional network (MAAN) to suppress the dominant response of the most salient regions in a principled manner. The MAAN employs a novel marginalized average aggregation (MAA) module and learns a set of latent discriminative probabilities in an end-to-end fashion. MAA samples multiple subsets from the video snippet features according to a set of latent discriminative probabilities and takes the expectation over all the averaged subset features. Theoretically, we prove that the MAA module with learned latent discriminative probabilities successfully reduces the difference in responses between the most salient regions and the others. Therefore, MAAN is able to generate better class activation sequences and identify dense and integral action regions in the videos. Moreover, we propose a fast algorithm to reduce the complexity of constructing MAA from O(2T) to O(T2). Extensive experiments on two large-scale video datasets show that our MAAN achieves a superior performance on weakly-supervised temporal action localization

Marginalized average attentional network for weakly-supervised learning

© 7th International Conference on Learning Representations, ICLR 2019. All Rights Reserved. In weakly-supervised temporal action localization, previous works have failed to locate dense and integral regions for each entire action due to the overestimation of the most salient regions. To alleviate this issue, we propose a marginalized average attentional network (MAAN) to suppress the dominant response of the most salient regions in a principled manner. The MAAN employs a novel marginalized average aggregation (MAA) module and learns a set of latent discriminative probabilities in an end-to-end fashion. MAA samples multiple subsets from the video snippet features according to a set of latent discriminative probabilities and takes the expectation over all the averaged subset features. Theoretically, we prove that the MAA module with learned latent discriminative probabilities successfully reduces the difference in responses between the most salient regions and the others. Therefore, MAAN is able to generate better class activation sequences and identify dense and integral action regions in the videos. Moreover, we propose a fast algorithm to reduce the complexity of constructing MAA from O(2T) to O(T2). Extensive experiments on two large-scale video datasets show that our MAAN achieves a superior performance on weakly-supervised temporal action localization

The Effect of Compositional Context on Synthetic Gene Networks

It is well known that synthetic gene expression is highly sensitive to how genetic elements (promoter structure, spacing regions between promoter and coding sequences, ribosome binding sites, etc.) are spatially configured. An important topic that has received far less attention is how the compositional context, or spatial arrangement, of entire genes within a synthetic gene network affects their individual expression levels. In this paper we show, both quantitatively and qualitatively, that compositional context significantly alters transcription levels in synthetic gene networks. We demonstrate that key characteristics of gene induction, such as ultra-sensitivity and dynamic range, strongly depend on compositional context. We postulate that supercoiling can be used to explain this interference and validate this hypothesis through modeling and a series of in vitro supercoiling relaxation experiments. This compositional interference enables a novel form of feedback in synthetic gene networks. We illustrate the use of this feedback by redesigning the toggle switch to incorporate compositional context. We show the context-optimized toggle switch has improved threshold detection and memory properties

Effects of helicobacter pylori treatment on incidence of gastric cancer in older individuals

Background & Aims: Although eradication of Helicobacter pylori infection reduces the risk of gastric cancer, few data are available on its effects in older subjects. We compared the age-specific risk of gastric cancer in a large cohort of subjects who received H pylori eradication therapy vs a matched general population. / Methods: We searched the Hospital Authority database of Hong Kong to identify individuals with H pylori infection who had received a course of clarithromycin-containing eradication therapy from January 2003 through December 2012. We compared the gastric cancer incidence in this cohort with the expected incidence for the local general population by retrieving the gastric cancer incidence of the age- and sex-matched population from 2003 through 2014 (the latest available year) from the Hong Kong Cancer Registry. The primary outcome was the incidence of gastric cancer development in the cohort treated for H pylori infection vs the expected number of gastric cancer cases in the general population. Analyses were conducted by a priori age groups of less than 40 years, 40–59 years, and 60 years or older. / Results: Among 73,237 subjects infected with H pylori who received eradication therapy, 200 (0.27%) developed gastric cancer during a median follow-up time of 7.6 years. Compared with the matched general population, the gastric cancer risk was significantly lower in subjects 60 years or older who had received H pylori treatment (standardized incidence ratio [SIR], 0.82; 95% confidence interval [CI], 0.69–0.97; P = .02) but not in younger groups. When data were stratified based on time from H pylori treatment (less than 5 years, 5–9 years, and 10 or more years), the risk of gastric cancer was significantly lower than the general population 10 or more years after eradication in the group 40–59 years old (SIR 0.32; 95% CI, 0.08–0.88; P = .04) and the group 60 years or older (SIR, 0.42; 95% CI, 0.42–0.84; P = .02) than the other age groups. / Conclusions: In an analysis of data from a public hospital database on Hong Kong, we associated treatment of H pylori infection with a lower risk of gastric cancer, particularly in older subjects, 10 or more years after treatment

Intrusion detection routers: Design, implementation and evaluation using an experimental testbed

In this paper, we present the design, the implementation details, and the evaluation results of an intrusion detection and defense system for distributed denial-of-service (DDoS) attack. The evaluation is conducted using an experimental testbed. The system, known as intrusion detection router (IDR), is deployed on network routers to perform online detection on any DDoS attack event, and then react with defense mechanisms to mitigate the attack. The testbed is built up by a cluster of sufficient number of Linux machines to mimic a portion of the Internet. Using the testbed, we conduct real experiments to evaluate the IDR system and demonstrate that IDR is effective in protecting the network from various DDoS attacks. © 2006 IEEE.published_or_final_versio

Biophysical Constraints Arising from Compositional Context in Synthetic Gene Networks

Synthetic gene expression is highly sensitive to intragenic compositional context (promoter structure, spacing regions between promoter and coding sequences, and ribosome binding sites). However, much less is known about the effects of intergenic compositional context (spatial arrangement and orientation of entire genes on DNA) on expression levels in synthetic gene networks. We compare expression of induced genes arranged in convergent, divergent, or tandem orientations. Induction of convergent genes yielded up to 400% higher expression, greater ultrasensitivity, and dynamic range than divergent- or tandem-oriented genes. Orientation affects gene expression whether one or both genes are induced. We postulate that transcriptional interference in divergent and tandem genes, mediated by supercoiling, can explain differences in expression and validate this hypothesis through modeling and in vitro supercoiling relaxation experiments. Treatment with gyrase abrogated intergenic context effects, bringing expression levels within 30% of each other. We rebuilt the toggle switch with convergent genes, taking advantage of supercoiling effects to improve threshold detection and switch stability

Prenatal Detection of Aneuploidy and Imbalanced Chromosomal Arrangements by Massively Parallel Sequencing

Fetal chromosomal abnormalities are the most common reasons for invasive prenatal testing. Currently, G-band karyotyping and several molecular genetic methods have been established for diagnosis of chromosomal abnormalities. Although these testing methods are highly reliable, the major limitation remains restricted resolutions or can only achieve limited coverage on the human genome at one time. The massively parallel sequencing (MPS) technologies which can reach single base pair resolution allows detection of genome-wide intragenic deletions and duplication challenging karyotyping and microarrays as the tool for prenatal diagnosis. Here we reported a novel and robust MPS-based method to detect aneuploidy and imbalanced chromosomal arrangements in amniotic fluid (AF) samples. We sequenced 62 AF samples on Illumina GAIIx platform and with averagely 0.01× whole genome sequencing data we detected 13 samples with numerical chromosomal abnormalities by z-test. With up to 2× whole genome sequencing data we were able to detect microdeletion/microduplication (ranged from 1.4 Mb to 37.3 Mb of 5 samples from chorionic villus sampling (CVS) using SeqSeq algorithm. Our work demonstrated MPS is a robust and accurate approach to detect aneuploidy and imbalanced chromosomal arrangements in prenatal samples

Evaluating the effective numbers of independent tests and significant p-value thresholds in commercial genotyping arrays and public imputation reference datasets

Current genome-wide association studies (GWAS) use commercial genotyping microarrays that can assay over a million single nucleotide polymorphisms (SNPs). The number of SNPs is further boosted by advanced statistical genotype-imputation algorithms and large SNP databases for reference human populations. The testing of a huge number of SNPs needs to be taken into account in the interpretation of statistical significance in such genome-wide studies, but this is complicated by the non-independence of SNPs because of linkage disequilibrium (LD). Several previous groups have proposed the use of the effective number of independent markers (Me) for the adjustment of multiple testing, but current methods of calculation for Me are limited in accuracy or computational speed. Here, we report a more robust and fast method to calculate Me. Applying this efficient method [implemented in a free software tool named Genetic type 1 error calculator (GEC)], we systematically examined the Me, and the corresponding p-value thresholds required to control the genome-wide type 1 error rate at 0.05, for 13 Illumina or Affymetrix genotyping arrays, as well as for HapMap Project and 1000 Genomes Project datasets which are widely used in genotype imputation as reference panels. Our results suggested the use of a p-value threshold of ~10−7 as the criterion for genome-wide significance for early commercial genotyping arrays, but slightly more stringent p-value thresholds ~5 × 10−8 for current or merged commercial genotyping arrays, ~10−8 for all common SNPs in the 1000 Genomes Project dataset and ~5 × 10−8 for the common SNPs only within genes