Compatibility Family Learning for Item Recommendation and Generation

Compatibility between items, such as clothes and shoes, is a major factor among customer's purchasing decisions. However, learning "compatibility" is challenging due to (1) broader notions of compatibility than those of similarity, (2) the asymmetric nature of compatibility, and (3) only a small set of compatible and incompatible items are observed. We propose an end-to-end trainable system to embed each item into a latent vector and project a query item into K compatible prototypes in the same space. These prototypes reflect the broad notions of compatibility. We refer to both the embedding and prototypes as "Compatibility Family". In our learned space, we introduce a novel Projected Compatibility Distance (PCD) function which is differentiable and ensures diversity by aiming for at least one prototype to be close to a compatible item, whereas none of the prototypes are close to an incompatible item. We evaluate our system on a toy dataset, two Amazon product datasets, and Polyvore outfit dataset. Our method consistently achieves state-of-the-art performance. Finally, we show that we can visualize the candidate compatible prototypes using a Metric-regularized Conditional Generative Adversarial Network (MrCGAN), where the input is a projected prototype and the output is a generated image of a compatible item. We ask human evaluators to judge the relative compatibility between our generated images and images generated by CGANs conditioned directly on query items. Our generated images are significantly preferred, with roughly twice the number of votes as others.Comment: 9 pages, accepted to AAAI 201

Fine structure characterization of zero-valent iron nanoparticles for decontamination of nitrites and nitrates in wastewater and groundwater

The main objectives of the present study were to investigate the chemical reduction of nitrate or nitrite species by zero-valent iron nanoparticle (ZVIN) in aqueous solution and related reaction kinetics or mechanisms using fine structure characterization. This work also exemplifies the utilization of field emission-scanning electron microscope (FE-SEM), transmission electron microscopy (TEM), and x-ray diffraction (XRD) to reveal the speciation and possible reaction pathway in a very complex adsorption and redox reaction process. Experimentally, ZVIN of this study was prepared by sodium borohydride reduction method at room temperature and ambient pressure. The morphology of as-synthesized ZVIN shows that the nearly ball and ultrafine particles ranged of 20-50 nm were observed with FE-SEM or TEM analysis. The kinetic model of nitrites or nitrates reductive reaction by ZVIN is proposed as a pseudo first-order kinetic equation. The nitrite and nitrate removal efficiencies using ZVIN were found 65-83% and 51-68%, respectively, based on three different initial concentrations. Based on the XRD pattern analyses, it is found that the quantitative relationship between nitrite and Fe(III) or Fe(II) is similar to the one between nitrate and Fe( III) in the ZVIN study. The possible reason is due to the faster nitrite reduction by ZVIN. In fact, the occurrence of the relative faster nitrite reductive reaction suggested that the passivation of the ZVIN have a significant contribution to iron corrosion. The extended x-ray absorption fine structure (EXAFS) or x-ray absorption near edge structure (XANES) spectra show that the nitrites or nitrates reduce to N-2 or NH3 while oxidizing the ZVIN to Fe2O3 or Fe3O4 electrochemically. It is also very clear that decontamination of nitrate or nitrite species in groundwater via the in-situ remediation with a ZVIN permeable reactive barrier would be environmentally attractive

How do students from different disciplines perceive the concept of “data”?: A visual elicitation method

Transforming the iSquare draw-and-write technique into the dSquare draw-and-tell approach, we conducted synchronous online visual-elicitation inter-views with 37 college students in six different disciplines to examine how they perceived the concept of “data.” The preliminary findings showed that students across disciplines tend to use group diagrams to present ICT and print materials in their dSquares. When explaining their drawings, students typically relate to functional purposes in academic contexts. While students typically use data in coursework or other work-related contexts in a positive way, students in different disciplines consider data in different original forms and use different types of metaphors to express the concept of data. While science students tend to include files or lab tools and describe data processing through the tools, humanities and social science students tend to include texts or secondary sources and describe data processing or application through personal thinking. Future research suggestions are provided based on the findings

MEDock: a web server for efficient prediction of ligand binding sites based on a novel optimization algorithm

The prediction of ligand binding sites is an essential part of the drug discovery process. Knowing the location of binding sites greatly facilitates the search for hits, the lead optimization process, the design of site-directed mutagenesis experiments and the hunt for structural features that influence the selectivity of binding in order to minimize the drug's adverse effects. However, docking is still the rate-limiting step for such predictions; consequently, much more efficient algorithms are required. In this article, the design of the MEDock web server is described. The goal of this sever is to provide an efficient utility for predicting ligand binding sites. The MEDock web server incorporates a global search strategy that exploits the maximum entropy property of the Gaussian probability distribution in the context of information theory. As a result of the global search strategy, the optimization algorithm incorporated in MEDock is significantly superior when dealing with very rugged energy landscapes, which usually have insurmountable barriers. This article describes four different benchmark cases that span a diverse set of different types of ligand binding interactions. These benchmarks were compared with the use of the Lamarckian genetic algorithm (LGA), which is the major workhorse of the well-known AutoDock program. These results demonstrate that MEDock consistently converged to the correct binding modes with significantly smaller numbers of energy evaluations than the LGA required. When judged by a threshold of the number of energy evaluations consumed in the docking simulation, MEDock also greatly elevates the rate of accurate predictions for all benchmark cases. MEDock is available at and

Lasing on nonlinear localized waves in curved geometry

The use of geometrical constraints opens many new perspectives in photonics and in fundamental studies of nonlinear waves. By implementing surface structures in vertical cavity surface emitting lasers as manifolds for curved space, we experimentally study the impacts of geometrical constraints on nonlinear wave localization. We observe localized waves pinned to the maximal curvature in an elliptical-ring, and confirm the reduction in the localization length of waves by measuring near and far field patterns, as well as the corresponding dispersion relation. Theoretically, analyses based on a dissipative model with a parabola curve give good agreement remarkably to experimental measurement on the transition from delocalized to localized waves. The introduction of curved geometry allows to control and design lasing modes in the nonlinear regime.Comment: 6 pages, 6 figure

A Large Panel Two-CCD Camera Coordinate System with an Alternate-Eight-Matrix Look-Up Table Algorithm

AbstractIn this study, a novel positioning model of a double-CCD cameras calibration system, with an Alternate-Eight-Matrix (AEM) Look-Up-Table (LUT), was proposed. Two CCD cameras were fixed on both sides of a large scale screen to redeem Field Of View (FOV) problems. The first to the fourth AEMLUT were used to compute the corresponding positions of intermediate blocks on the screen captured by the right side camera. In these AEMLUT for the right side camera, the coordinate mapping data of the target in a specific space were stored in two matrixes, while the gray level threshold values of different position were stored in the others. Similarly, the fifth to the eighth AEMLUT were used to compute the corresponding positions of intermediate blocks on the screen captured by the left side camera. Experimental results showed that the problems of dead angles and non-uniform light fields were solved. In addition, rapid and precision positioning results can be obtained by the proposed method

A study on the flexibility of enzyme active sites

<p>Abstract</p> <p>Background</p> <p>A common assumption about enzyme active sites is that their structures are highly conserved to specifically distinguish between closely similar compounds. However, with the discovery of distinct enzymes with similar reaction chemistries, more and more studies discussing the structural flexibility of the active site have been conducted.</p> <p>Results</p> <p>Most of the existing works on the flexibility of active sites focuses on a set of pre-selected active sites that were already known to be flexible. This study, on the other hand, proposes an analysis framework composed of a new data collecting strategy, a local structure alignment tool and several physicochemical measures derived from the alignments. The method proposed to identify flexible active sites is highly automated and robust so that more extensive studies will be feasible in the future. The experimental results show the proposed method is (a) consistent with previous works based on manually identified flexible active sites and (b) capable of identifying potentially new flexible active sites.</p> <p>Conclusions</p> <p>This proposed analysis framework and the former analyses on flexibility have their own advantages and disadvantage, depending on the cause of the flexibility. In this regard, this study proposes an alternative that complements previous studies and helps to construct a more comprehensive view of the flexibility of enzyme active sites.</p