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

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

Learning is Like a Lava Lamp: The Student Journey to Critical Thinking

This paper explores the ways in which a university Foundation Degree programme supports undergraduate early years students to develop critical thinking, mindfulness and self-actualisation through their lived personal and professional experiences. It considers the impact of this on graduates employed within the Early Years sector. Findings inform future design of a University Foundation Degree programme situated within Early Childhood Education and Care (ECEC). As undergraduates, students engage in higher-level learning aligned to their practice within the workplace. An interpretive Participatory Qualitative Research methodology is used to gather the views of 6 alumni who completed their studies in 2014. They participated in the research freely within ethical parameters approved by a university ethics committee. Findings revealed that the development of critical thinking is empowered by having a personal or professional impetus, which in the case of Early Years is the child as being at the heart of values based practice. This, with the inclusion of mindfulness, drives students to a sustainable deeper layer of thinking to achieve self-actualisation. Through the acquisition of critical thinking students have been subsequently able to take up positions of authority within the early years workforce

The Large Array Survey Telescope -- System Overview and Performances

The Large Array Survey Telescope (LAST) is a wide-field visible-light telescope array designed to explore the variable and transient sky with a high cadence. LAST will be composed of 48, 28-cm f/2.2 telescopes (32 already installed) equipped with full-frame backside-illuminated cooled CMOS detectors. Each telescope provides a field of view (FoV) of 7.4 deg^2 with 1.25 arcsec/pix, while the system FoV is 355 deg^2 in 2.9 Gpix. The total collecting area of LAST, with 48 telescopes, is equivalent to a 1.9-m telescope. The cost-effectiveness of the system (i.e., probed volume of space per unit time per unit cost) is about an order of magnitude higher than most existing and under-construction sky surveys. The telescopes are mounted on 12 separate mounts, each carrying four telescopes. This provides significant flexibility in operating the system. The first LAST system is under construction in the Israeli Negev Desert, with 32 telescopes already deployed. We present the system overview and performances based on the system commissioning data. The Bp 5-sigma limiting magnitude of a single 28-cm telescope is about 19.6 (21.0), in 20 s (20x20 s). Astrometric two-axes precision (rms) at the bright-end is about 60 (30)\,mas in 20\,s (20x20 s), while absolute photometric calibration, relative to GAIA, provides ~10 millimag accuracy. Relative photometric precision, in a single 20 s (320 s) image, at the bright-end measured over a time scale of about 60 min is about 3 (1) millimag. We discuss the system science goals, data pipelines, and the observatory control system in companion publications.Comment: Submitted to PASP, 15p

Does the Reading of Different Orthographies Produce Distinct Brain Activity Patterns? An ERP Study

Orthographies vary in the degree of transparency of spelling-sound correspondence. These range from shallow orthographies with transparent grapheme-phoneme relations, to deep orthographies, in which these relations are opaque. Only a few studies have examined whether orthographic depth is reflected in brain activity. In these studies a between-language design was applied, making it difficult to isolate the aspect of orthographic depth. In the present work this question was examined using a within-subject-and-language investigation. The participants were speakers of Hebrew, as they are skilled in reading two forms of script transcribing the same oral language. One form is the shallow pointed script (with diacritics), and the other is the deep unpointed script (without diacritics). Event-related potentials (ERPs) were recorded while skilled readers carried out a lexical decision task in the two forms of script. A visual non-orthographic task controlled for the visual difference between the scripts (resulting from the addition of diacritics to the pointed script only). At an early visual-perceptual stage of processing (∼165 ms after target onset), the pointed script evoked larger amplitudes with longer latencies than the unpointed script at occipital-temporal sites. However, these effects were not restricted to orthographic processing, and may therefore have reflected, at least in part, the visual load imposed by the diacritics. Nevertheless, the results implied that distinct orthographic processing may have also contributed to these effects. At later stages (∼340 ms after target onset) the unpointed script elicited larger amplitudes than the pointed one with earlier latencies. As this latency has been linked to orthographic-linguistic processing and to the classification of stimuli, it is suggested that these differences are associated with distinct lexical processing of a shallow and a deep orthography

A host signature based on TRAIL, IP-10, and CRP for reducing antibiotic overuse in children by differentiating bacterial from viral infections: a prospective, multicentre cohort study

Objectives: Identifying infection aetiology is essential for appropriate antibiotic use. Previous studies have shown that a host-protein signature consisting of TNF-related apoptosis-induced ligand (TRAIL), interferon-γ-induced protein-10 (IP-10), and C-reactive protein (CRP) can accurately differentiate bacterial from viral infections. Methods: This prospective, multicentre cohort study, entitled AutoPilot-Dx, aimed to validate signature performance and to estimate its potential impact on antibiotic use across a broad paediatric population (>90 days to 18 years) with respiratory tract infections, or fever without source, at emergency departments and wards in Italy and Germany. Infection aetiology was adjudicated by experts based on clinical and laboratory investigations, including multiplex PCR and follow-up data. Results: In total, 1140 patients were recruited (February 2017–December 2018), of which 1008 met the eligibility criteria (mean age 3.5 years, 41.9% female). Viral and bacterial infections were adjudicated for 628 (85.8%) and 104 (14.2%) children, respectively; 276 patients were assigned an indeterminate reference standard outcome. For the 732 children with reference standard aetiology, the signature discriminated bacterial from viral infections with a sensitivity of 93.7% (95%CI 88.7–98.7), a specificity of 94.2% (92.2–96.1), positive predictive value of 73.0% (65.0–81.0), and negative predictive value of 98.9% (98.0–99.8); in 9.8% the test results were equivocal. The signature performed consistently across different patient subgroups and detected bacterial immune responses in viral PCR-positive patients. Conclusions: The findings validate the high diagnostic performance of the TRAIL/IP-10/CRP signature in a broad paediatric cohort, and support its potential to reduce antibiotic overuse in children with viral infections

PKD is a kinase of Vps34 that mediates ROS-induced autophagy downstream of DAPk

Autophagy, a process in which cellular components are engulfed and degraded within double-membrane vesicles termed autophagosomes, has an important role in the response to oxidative damage. Here we identify a novel cascade of phosphorylation events, involving a network of protein and lipid kinases, as crucial components of the signaling pathways that regulate the induction of autophagy under oxidative stress. Our findings show that both the tumor-suppressor death-associated protein kinase (DAPk) and protein kinase D (PKD), which we previously showed to be phosphorylated and consequently activated by DAPk, mediate the induction of autophagy in response to oxidative damage. Furthermore, we map the position of PKD within the autophagic network to Vps34, a lipid kinase whose function is indispensable for autophagy, and demonstrate that PKD is found in the same molecular complex with Vps34. PKD phosphorylates Vps34, leading to activation of Vps34, phosphatydilinositol-3-phosphate (PI(3)P) formation, and autophagosome formation. Consistent with its identification as a novel inducer of the autophagic machinery, we show that PKD is recruited to LC3-positive autophagosomes, where it localizes specifically to the autophagosomal membranes. Taken together, our results describe PKD as a novel Vps34 kinase that functions as an effecter of autophagy under oxidative stress