Generic Intent Representation in Web Search

This paper presents GEneric iNtent Encoder (GEN Encoder) which learns a distributed representation space for user intent in search. Leveraging large scale user clicks from Bing search logs as weak supervision of user intent, GEN Encoder learns to map queries with shared clicks into similar embeddings end-to-end and then finetunes on multiple paraphrase tasks. Experimental results on an intrinsic evaluation task - query intent similarity modeling - demonstrate GEN Encoder's robust and significant advantages over previous representation methods. Ablation studies reveal the crucial role of learning from implicit user feedback in representing user intent and the contributions of multi-task learning in representation generality. We also demonstrate that GEN Encoder alleviates the sparsity of tail search traffic and cuts down half of the unseen queries by using an efficient approximate nearest neighbor search to effectively identify previous queries with the same search intent. Finally, we demonstrate distances between GEN encodings reflect certain information seeking behaviors in search sessions

Microbiological assessment and evaluation of rehydration instructions on powdered infant formulas, follow-up formulas, and infant foods in Malaysia

A total of 90 samples comprised of powdered infant formulas (51), follow-up formulas (21) and infant foods (18) from 15 domestic and imported brands were purchased from various retailers in Klang Valley, Malaysia and evaluated in terms of microbiological quality and the similarity of rehydration instructions on the product label to guidelines set by the World Health Organization. Microbiological analysis included the determination of aerobic plate count (APC) and the presence of Enterobacteriaceae and Cronobacter spp. Isolates of interest were identified using ID 32E (bioMerieux®). In this study 87% of powdered infant formulas, follow-up formulas and infant foods analyzed had aerobic plate counts below the permitted level of 70°C for formula preparation as specified by the 2008 revised World Health Organization guidelines. Six brands instructed the use of water at 40-55°C, a temperature range which would support the survival and even growth of Enterobacteriaceae

Grouped graphical Granger modeling for gene expression regulatory networks discovery

We consider the problem of discovering gene regulatory networks from time-series microarray data. Recently, graphical Granger modeling has gained considerable attention as a promising direction for addressing this problem. These methods apply graphical modeling methods on time-series data and invoke the notion of ‘Granger causality’ to make assertions on causality through inference on time-lagged effects. Existing algorithms, however, have neglected an important aspect of the problem—the group structure among the lagged temporal variables naturally imposed by the time series they belong to. Specifically, existing methods in computational biology share this shortcoming, as well as additional computational limitations, prohibiting their effective applications to the large datasets including a large number of genes and many data points. In the present article, we propose a novel methodology which we term ‘grouped graphical Granger modeling method’, which overcomes the limitations mentioned above by applying a regression method suited for high-dimensional and large data, and by leveraging the group structure among the lagged temporal variables according to the time series they belong to. We demonstrate the effectiveness of the proposed methodology on both simulated and actual gene expression data, specifically the human cancer cell (HeLa S3) cycle data. The simulation results show that the proposed methodology generally exhibits higher accuracy in recovering the underlying causal structure. Those on the gene expression data demonstrate that it leads to improved accuracy with respect to prediction of known links, and also uncovers additional causal relationships uncaptured by earlier works

Computing Volume Bounds of Inclusions by EIT Measurements

The size estimates approach for Electrical Impedance Tomography (EIT) allows for estimating the size (area or volume) of an unknown inclusion in an electrical conductor by means of one pair of boundary measurements of voltage and current. In this paper we show by numerical simulations how to obtain such bounds for practical application of the method. The computations are carried out both in a 2D and a 3D setting.Comment: 20 pages with figure

Measurement of the Crab nebula polarization at 90 GHz as a calibrator for CMB experiments

CMB experiments aiming at a precise measurement of the CMB polarization, such as the Planck satellite, need a strong polarized absolute calibrator on the sky to accurately set the detectors polarization angle and the cross-polarization leakage. As the most intense polarized source in the microwave sky at angular scales of few arcminutes, the Crab nebula will be used for this purpose. Our goal was to measure the Crab nebula polarization characteristics at 90 GHz with unprecedented precision. The observations were carried out with the IRAM 30m telescope employing the correlation polarimeter XPOL and using two orthogonally polarized receivers. We processed the Stokes I, Q, and U maps from our observations in order to compute the polarization angle and linear polarization fraction. The first is almost constant in the region of maximum emission in polarization with a mean value of alpha_Sky=152.1+/-0.3 deg in equatorial coordinates, and the second is found to reach a maximum of Pi=30% for the most polarized pixels. We find that a CMB experiment having a 5 arcmin circular beam will see a mean polarization angle of alpha_Sky=149.9+/-0.2 deg and a mean polarization fraction of Pi=8.8+/-0.2%.Comment: Accepted for publication in A&A, 9 pages, 4 figure

Osteonecrosis of the femoral head safely healed with autologous, expanded, bone marrow-derived mesenchymal stromal cells in a multicentric trial with minimum 5 years follow-up

10.3390/jcm10030508