Efficient Image Gallery Representations at Scale Through Multi-Task Learning

Image galleries provide a rich source of diverse information about a product which can be leveraged across many recommendation and retrieval applications. We study the problem of building a universal image gallery encoder through multi-task learning (MTL) approach and demonstrate that it is indeed a practical way to achieve generalizability of learned representations to new downstream tasks. Additionally, we analyze the relative predictive performance of MTL-trained solutions against optimal and substantially more expensive solutions, and find signals that MTL can be a useful mechanism to address sparsity in low-resource binary tasks.Comment: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieva

sFlt-1 and NTproBNP independently predict mortality in a cohort of heart failure patients.

Objective: Soluble fms-like tyrosine kinase-1 (sFlt-1) is a circulating receptor for VEGF-A. Recent reports of elevated plasma levels of sFlt-1 in coronary heart disease and heart failure (HF) motivated our study aimed at investigating the utility of sFlt-1 as a prognostic biomarker in heart failure patients. Methods: ELISA assays for sFlt-1 and NTproBNP were performed in n=858 patients from a prospective multicentre, observational study (the PEOPLE study) of outcome among patients after appropriate treatment for an episode of acute decompensated HF in New Zealand. Plasma was sampled at a baseline visit and stored at -80°C. Statistical tests were adjusted for patient age at baseline visit, skewed data were log-adjusted and the endpoint for clinical outcome analysis was all-cause death. Patients were followed for a median of 3.63 (range 0.74-5.50) years. Results: Mean baseline plasma sFlt-1 was 125 +/- 2.01 pg/ml. sFlt-1 was higher in patients with HF with reduced ejection fraction (HFrEF) (130 +/- 2.62 pg/ml, n=553) compared to those with HF with preserved EF (HFpEF) (117 +/-3.59 pg/ml, n=305; p=0.005). sFlt-1 correlated with heart rate (r=0.148, p<0.001), systolic blood pressure (r=-0.139, p<0.001) and LVEF (r=-0.088, p=0.019). A Cox proportional hazards model showed sFlt-1 was a predictor of all-cause death (HR=6.30, p<0.001) in the PEOPLE cohort independent of age, NTproBNP, ischaemic aetiology, and NYHA class (n=842, 274 deaths), established predictors of mortality in the PEOPLE cohort. Conclusion: sFlt-1 levels at baseline should be investigated further as a predictor of death; complementary to established prognostic biomarkers in heart failure

AntiDote: Attention-based Dynamic Optimization for Neural Network Runtime Efficiency

Convolutional Neural Networks (CNNs) achieved great cognitive performance at the expense of considerable computation load. To relieve the computation load, many optimization works are developed to reduce the model redundancy by identifying and removing insignificant model components, such as weight sparsity and filter pruning. However, these works only evaluate model components' static significance with internal parameter information, ignoring their dynamic interaction with external inputs. With per-input feature activation, the model component significance can dynamically change, and thus the static methods can only achieve sub-optimal results. Therefore, we propose a dynamic CNN optimization framework in this work. Based on the neural network attention mechanism, we propose a comprehensive dynamic optimization framework including (1) testing-phase channel and column feature map pruning, as well as (2) training-phase optimization by targeted dropout. Such a dynamic optimization framework has several benefits: (1) First, it can accurately identify and aggressively remove per-input feature redundancy with considering the model-input interaction; (2) Meanwhile, it can maximally remove the feature map redundancy in various dimensions thanks to the multi-dimension flexibility; (3) The training-testing co-optimization favors the dynamic pruning and helps maintain the model accuracy even with very high feature pruning ratio. Extensive experiments show that our method could bring 37.4% to 54.5% FLOPs reduction with negligible accuracy drop on various of test networks.Comment: Accepted in DATE'2020 (Best Paper Nomination

Is high recovery more effective than expected recovery in addressing service failure?: a moral judgment perspective

In the context of two distinctive consumer categories and two different product settings, this research examines the effects of recovery on recovery performance as a function of consumer moral judgment of service failure. The findings of two studies reveal that consumers' response to recovery anchors on the magnitude of recovery but these responses are adjusted according to consumers' moral judgment of service failure. Specifically, consumers react more positively toward expected recovery than high recovery and these effects are pronounced when consumers are low in moral judgment of service failure. In contrast, when consumers are high in moral judgment of service failure, although high recovery (compared with expected recovery) lessens the likelihood of negative word of mouth this effect does not transfer to repurchase tendency. Product involvement does not provide alternative explanations for the findings. The findings of this research have important and meaningful implications for business providers

New insights into the mechanisms of phytochrome-cryptochrome coaction.

Contents Summary 547 I. Introduction 547 II. Phytochromes mediate light-induced transcription of BICs to inactivate cryptochromes 548 III. PPKs phosphorylate light-signaling proteins and histones to affect plant development 548 IV. Prospect 550 Acknowledgements 550 References 550 SUMMARY: Plants perceive and respond to light signals by multiple sensory photoreceptors, including phytochromes and cryptochromes, which absorb different wavelengths of light to regulate genome expression and plant development. Photophysiological analyses have long revealed the coordinated actions of different photoreceptors, a phenomenon referred to as the photoreceptor coaction. The mechanistic explanations of photoreceptor coactions are not fully understood. The function of direct protein-protein interaction of phytochromes and cryptochromes and common signaling molecules of these photoreceptors, such as SPA1/COP1 E3 ubiquitin ligase complex and bHLH transcription factors PIFs, would partially explain phytochrome-cryptochrome coactions. In addition, newly discovered proteins that block cryptochrome photodimerization or catalyze cryptochrome phosphorylation may also participate in the phytochrome and cryptochrome coaction. This Tansley insight, which is not intended to make a comprehensive review of the studies of photoreceptor coactions, attempts to highlight those recent findings and their possible roles in the photoreceptor coaction

Standing genetic variation and compensatory evolution in transgenic organisms: a growth-enhanced salmon simulation

Genetically modified strains usually are generated within defined genetic backgrounds to minimize variation for the engineered characteristic in order to facilitate basic research investigations or for commercial application. However, interactions between transgenes and genetic background have been documented in both model and commercial agricultural species, indicating that allelic variation at transgene-modifying loci are not uncommon in genomes. Engineered organisms that have the potential to allow entry of transgenes into natural populations may cause changes to ecosystems via the interaction of their specific phenotypes with ecosystem components and services. A transgene introgressing through natural populations is likely to encounter a range of natural genetic variation (among individuals or sub-populations) that could result in changes in phenotype, concomitant with effects on fitness and ecosystem consequences that differ from that seen in the progenitor transgenic strain. In the present study, using a growth hormone transgenic salmon example, we have modeled selection of modifier loci (single and multiple) in the presence of a transgene and have found that accounting for genetic background can significantly affect the persistence of transgenes in populations, potentially reducing or reversing a “Trojan gene” effect. Influences from altered life history characteristics (e.g., developmental timing, age of maturation) and compensatory demographic/ecosystem controls (e.g., density dependence) also were found to have a strong influence on transgene effects. Further, with the presence of a transgene in a population, genetic backgrounds were found to shift in non-transgenic individuals as well, an effect expected to direct phenotypes away from naturally selected optima. The present model has revealed the importance of understanding effects of selection for background genetics on the evolution of phenotypes in populations harbouring transgenes

A Multi-wavelength Study of the Sunyaev-Zel'dovich Effect in the Triple-Merger Cluster MACS J0717.5+3745 with MUSTANG and Bolocam

We present 90, 140, and 268GHz sub-arcminute resolution imaging of the Sunyaev-Zel'dovich effect (SZE) in MACSJ0717.5+3745. Our 90GHz SZE data result in a sensitive, 34uJy/bm map at 13" resolution using MUSTANG. Our 140 and 268GHz SZE imaging, with resolutions of 58" and 31" and sensitivities of 1.8 and 3.3mJy/beam respectively, was obtained using Bolocam. We compare these maps to a 2-dimensional pressure map derived from Chandra X-ray observations. Our MUSTANG data confirm previous indications from Chandra of a pressure enhancement due to shock-heated, >20keV gas immediately adjacent to extended radio emission seen in low-frequency radio maps. The MUSTANG data also detect pressure substructure that is not well-constrained by the X-ray data in the remnant core of a merging subcluster. We find that the small-scale pressure enhancements in the MUSTANG data amount to ~2% of the total pressure measured in the 140GHz Bolocam observations. The X-ray template also fails on larger scales to accurately describe the Bolocam data, particularly at the location of a subcluster known to have a high line of sight optical velocity (~3200km/s). Our Bolocam data are adequately described when we add an additional component - not described by a thermal SZE spectrum - coincident with this subcluster. Using flux densities extracted from our model fits, and marginalizing over the temperature constraints for the region, we fit a thermal+kinetic SZE spectrum to our data and find the subcluster has a best-fit line of sight proper velocity of 3600+3440/-2160km/s. This agrees with the optical velocity estimates for the subcluster. The probability of velocity<0 given our measurements is 2.1%. Repeating this analysis using flux densities measured non-parametrically results in a 3.4% probability of a velocity<=0. We note that this tantalizing result for the kinetic SZE is on resolved, subcluster scales.Comment: 10 Figures, 18 pages. this version corrects issues with the previous arXiv versio

Inherent change in MammoSite applicator three-dimensional geometry over time

Accelerated partial breast irradiation is commonly done with the MammoSite applicator, which requires symmetry to treat the patient. This paper describes three cases that were asymmetric when initially placed and became symmetric over time, without manipulation