Neural Attentive Session-based Recommendation

Given e-commerce scenarios that user profiles are invisible, session-based recommendation is proposed to generate recommendation results from short sessions. Previous work only considers the user's sequential behavior in the current session, whereas the user's main purpose in the current session is not emphasized. In this paper, we propose a novel neural networks framework, i.e., Neural Attentive Recommendation Machine (NARM), to tackle this problem. Specifically, we explore a hybrid encoder with an attention mechanism to model the user's sequential behavior and capture the user's main purpose in the current session, which are combined as a unified session representation later. We then compute the recommendation scores for each candidate item with a bi-linear matching scheme based on this unified session representation. We train NARM by jointly learning the item and session representations as well as their matchings. We carried out extensive experiments on two benchmark datasets. Our experimental results show that NARM outperforms state-of-the-art baselines on both datasets. Furthermore, we also find that NARM achieves a significant improvement on long sessions, which demonstrates its advantages in modeling the user's sequential behavior and main purpose simultaneously.Comment: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. arXiv admin note: text overlap with arXiv:1511.06939, arXiv:1606.08117 by other author

Pythia: AI-assisted Code Completion System

In this paper, we propose a novel end-to-end approach for AI-assisted code completion called Pythia. It generates ranked lists of method and API recommendations which can be used by software developers at edit time. The system is currently deployed as part of Intellicode extension in Visual Studio Code IDE. Pythia exploits state-of-the-art large-scale deep learning models trained on code contexts extracted from abstract syntax trees. It is designed to work at a high throughput predicting the best matching code completions on the order of 100 $ms$. We describe the architecture of the system, perform comparisons to frequency-based approach and invocation-based Markov Chain language model, and discuss challenges serving Pythia models on lightweight client devices. The offline evaluation results obtained on 2700 Python open source software GitHub repositories show a top-5 accuracy of 92\%, surpassing the baseline models by 20\% averaged over classes, for both intra and cross-project settings.Comment: Published in Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD '19

Statistical Physics of Fracture Surfaces Morphology

Experiments on fracture surface morphologies offer increasing amounts of data that can be analyzed using methods of statistical physics. One finds scaling exponents associated with correlation and structure functions, indicating a rich phenomenology of anomalous scaling. We argue that traditional models of fracture fail to reproduce this rich phenomenology and new ideas and concepts are called for. We present some recent models that introduce the effects of deviations from homogeneous linear elasticity theory on the morphology of fracture surfaces, succeeding to reproduce the multiscaling phenomenology at least in 1+1 dimensions. For surfaces in 2+1 dimensions we introduce novel methods of analysis based on projecting the data on the irreducible representations of the SO(2) symmetry group. It appears that this approach organizes effectively the rich scaling properties. We end up with the proposition of new experiments in which the rotational symmetry is not broken, such that the scaling properties should be particularly simple.Comment: A review paper submitted to J. Stat. Phy

Optimal treatment allocations in space and time for on-line control of an emerging infectious disease

A key component in controlling the spread of an epidemic is deciding where, whenand to whom to apply an intervention.We develop a framework for using data to informthese decisionsin realtime.We formalize a treatment allocation strategy as a sequence of functions, oneper treatment period, that map up-to-date information on the spread of an infectious diseaseto a subset of locations where treatment should be allocated. An optimal allocation strategyoptimizes some cumulative outcome, e.g. the number of uninfected locations, the geographicfootprint of the disease or the cost of the epidemic. Estimation of an optimal allocation strategyfor an emerging infectious disease is challenging because spatial proximity induces interferencebetween locations, the number of possible allocations is exponential in the number oflocations, and because disease dynamics and intervention effectiveness are unknown at outbreak.We derive a Bayesian on-line estimator of the optimal allocation strategy that combinessimulation–optimization with Thompson sampling.The estimator proposed performs favourablyin simulation experiments. This work is motivated by and illustrated using data on the spread ofwhite nose syndrome, which is a highly fatal infectious disease devastating bat populations inNorth America

Glassy-State Stabilization of a Dominant Negative Inhibitor Anthrax Vaccine Containing Aluminum Hydroxide and Glycopyranoside Lipid A Adjuvants

During transport and storage, vaccines may be exposed to temperatures outside of the range recommended for storage, potentially causing efficacy losses. To better understand and prevent such losses, Dominant Negative Inhibitor (DNI), a recombinant protein antigen for a candidate vaccine against anthrax, was formulated as a liquid and as a glassy lyophilized powder with the adjuvants aluminum hydroxide and glycopyranoside lipid A (GLA). Freeze-thawing of the liquid vaccine caused the adjuvants to aggregate and decreased its immunogenicity in mice. Immunogenicity of liquid vaccines also decreased when stored at 40 °C for 8 weeks, as measured by decreases in neutralizing antibody titers in vaccinated mice. Concomitant with efficacy losses at elevated temperatures, changes in DNI structure were detected by fluorescence spectroscopy and increased deamidation was observed by capillary isoelectric focusing (cIEF) after only 1 week of storage of the liquid formulation at 40 °C. In contrast, upon lyophilization, no additional deamidation after 4 weeks at 40 °C and no detectable changes in DNI structure or reduction in immunogenicity after 16 weeks at 40 °C was observed. Vaccines containing aluminum hydroxide and GLA elicited higher immune responses than vaccines adjuvanted with only aluminum hydroxide, with more mice responding to a single dose

New Modularity of DAP-Kinases: Alternative Splicing of the DRP-1 Gene Produces a ZIPk-Like Isoform

DRP-1 and ZIPk are two members of the Death Associated Protein Ser/Thr Kinase (DAP-kinase) family, which function in different settings of cell death including autophagy. DAP kinases are very similar in their catalytic domains but differ substantially in their extra-catalytic domains. This difference is crucial for the significantly different modes of regulation and function among DAP kinases. Here we report the identification of a novel alternatively spliced kinase isoform of the DRP-1 gene, termed DRP-1β. The alternative splicing event replaces the whole extra catalytic domain of DRP-1 with a single coding exon that is closely related to the sequence of the extra catalytic domain of ZIPk. As a consequence, DRP-1β lacks the calmodulin regulatory domain of DRP-1, and instead contains a leucine zipper-like motif similar to the protein binding region of ZIPk. Several functional assays proved that this new isoform retained the biochemical and cellular properties that are common to DRP-1 and ZIPk, including myosin light chain phosphorylation, and activation of membrane blebbing and autophagy. In addition, DRP-1β also acquired binding to the ATF4 transcription factor, a feature characteristic of ZIPk but not DRP-1. Thus, a splicing event of the DRP-1 produces a ZIPk like isoform. DRP-1β is highly conserved in evolution, present in all known vertebrate DRP-1 loci. We detected the corresponding mRNA and protein in embryonic mouse brains and in human embryonic stem cells thus confirming the in vivo utilization of this isoform. The discovery of module conservation within the DAPk family members illustrates a parsimonious way to increase the functional complexity within protein families. It also provides crucial data for modeling the expansion and evolution of DAP kinase proteins within vertebrates, suggesting that DRP-1 and ZIPk most likely evolved from their ancient ancestor gene DAPk by two gene duplication events that occurred close to the emergence of vertebrates

The shifting terrain of sex and power: From the 'sexualisation of culture' to Me Too

In this short article we will aim to do three things. First, we want to use this opportunity to reflect on some of the changes we have seen in the scholarly field of gender, sexuality, and intimacy over this period, and on new emerging directions. Second, we want to discuss the move away from discussions of ‘sexualization’ to a more critical and political register interested in a variety of ways in which sex and power intersect. Thirdly, we will discuss MeToo as an example of this shifted form of engagement, and raise some questions about its possibilities and limitations

A Moving Magnetic Trap Decelerator: a New Source for Cold Atoms and Molecules

We present an experimental realization of a moving magnetic trap decelerator, where paramagnetic particles entrained in a cold supersonic beam are decelerated in a co-moving magnetic trap. Our method allows for an efficient slowing of both paramagnetic atoms and molecules to near stopping velocities. We show that under realistic conditions we will be able to trap and decelerate a large fraction of the initial supersonic beam. We present our first results on deceleration in a moving magnetic trap by bringing metastable neon atoms to near rest. Our estimated phase space volume occupied by decelerated particles at final velocity of 50 m/s shows an improvement of two orders of magnitude as compared to currently available deceleration techniques

Statefinder diagnostic and stability of modified gravity consistent with holographic and new agegraphic dark energy

Recently one of us derived the action of modified gravity consistent with the holographic and new-agegraphic dark energy. In this paper, we investigate the stability of the Lagrangians of the modified gravity as discussed in [M. R. Setare, Int. J. Mod. Phys. D 17 (2008) 2219; M. R. Setare, Astrophys. Space Sci. 326 (2010) 27]. We also calculate the statefinder parameters which classify our dark energy model.Comment: 12 pages, 2 figures, accepted by Gen. Relativ. Gravi