Interaction-aware Factorization Machines for Recommender Systems

Factorization Machine (FM) is a widely used supervised learning approach by effectively modeling of feature interactions. Despite the successful application of FM and its many deep learning variants, treating every feature interaction fairly may degrade the performance. For example, the interactions of a useless feature may introduce noises; the importance of a feature may also differ when interacting with different features. In this work, we propose a novel model named \emph{Interaction-aware Factorization Machine} (IFM) by introducing Interaction-Aware Mechanism (IAM), which comprises the \emph{feature aspect} and the \emph{field aspect}, to learn flexible interactions on two levels. The feature aspect learns feature interaction importance via an attention network while the field aspect learns the feature interaction effect as a parametric similarity of the feature interaction vector and the corresponding field interaction prototype. IFM introduces more structured control and learns feature interaction importance in a stratified manner, which allows for more leverage in tweaking the interactions on both feature-wise and field-wise levels. Besides, we give a more generalized architecture and propose Interaction-aware Neural Network (INN) and DeepIFM to capture higher-order interactions. To further improve both the performance and efficiency of IFM, a sampling scheme is developed to select interactions based on the field aspect importance. The experimental results from two well-known datasets show the superiority of the proposed models over the state-of-the-art methods

Multiscale Hierarchical Structure and Laminated Strengthening and Toughening Mechanisms

Metal matrix composites with multiscale hierarchical structure and laminated structure have been developed to provide a novel route to achieve high strength, toughness and ductility. In this chapter, a lot of scientific research has been carried out in the preparation, processing, properties and application of metal matrix composite. Many toughening mechanisms and fracture behavior of composites with multiscale hierarchical structure and laminated structure are overviewed. It is revealed that elastic property and yield strength of laminated composites follow the “rule of average.” However, the estimation of fracture elongation and fracture toughness is complex, which is inconsistent with the “rule of average.” The fracture elongation of laminated composites is related to the layer thickness size, interface, gradient structure, strain hardening exponent, strain rate parameter and tunnel crack, which are accompanied with crack deflection, crack blunting, crack bridging, stress redistribution, local stress deformation, interfacial delamination crack and so on. The concept of laminated composites can be extended by applying different combination of individual layer, and provides theoretical as well as experimental fundamentals on strengthening and toughening of metal matrix composites

PeF: Poisson's Equation Based Large-Scale Fixed-Outline Floorplanning

Floorplanning is the first stage of VLSI physical design. An effective floorplanning engine definitely has positive impact on chip design speed, quality and performance. In this paper, we present a novel mathematical model to characterize non-overlapping of modules, and propose a flat fixed-outline floorplanning algorithm based on the VLSI global placement approach using Poisson's equation. The algorithm consists of global floorplanning and legalization phases. In global floorplanning, we redefine the potential energy of each module based on the novel mathematical model for characterizing non-overlapping of modules and an analytical solution of Poisson's equation. In this scheme, the widths of soft modules appear as variables in the energy function and can be optimized. Moreover, we design a fast approximate computation scheme for partial derivatives of the potential energy. In legalization, based on the defined horizontal and vertical constraint graphs, we eliminate overlaps between modules remained after global floorplanning, by modifying relative positions of modules. Experiments on the MCNC, GSRC, HB+ and ami49\_x benchmarks show that, our algorithm improves the average wirelength by at least 2\% and 5\% on small and large scale benchmarks with certain whitespace, respectively, compared to state-of-the-art floorplanners

ZnO Nanorods Grown Directly on Copper Foil Substrate as a Binder-Free Anode for High Performance Lithium-Ion Batteries

ZnO nanorods directly grown on copper foil substrate were obtained via hydrothermal method without using templates. Structure and morphology of the as-prepared ZnO nanorods were characterized by X-ray diffraction, scanning electron microscopy and high-resolution transmission electron microscopy. The ZnO nanorods on copper foil (ZnO@CF) exhibited remarkably enhanced performance as anode for lithium batteries with the initial discharge capacity of 1236 mAh g-1 and a capacity of 402 mAh g-1 retained over 100 cycles at a current density of 200 mA g-1. The ZnO@CF anode demonstrated an excellent rate capability, delivering a reversible capacity of 390 mAh g-1 at 1500 mA g-1. This superior performance of the ZnO@CF anode is believed to be due to the unique structure of this binder-free anode, favoring mass and charge transfer at its interface with the electrolyte, effectively reducing the Li-ions diffusion paths and providing conditions to accommodate the anode volume variations upon charge-discharge cycling

Modeling Rett Syndrome Using TALEN-Edited MECP2 Mutant Cynomolgus Monkeys

Gene-editing technologies have made it feasible to create nonhuman primate models for human genetic disorders. Here, we report detailed genotypes and phenotypes of TALEN-edited MECP2 mutant cynomolgus monkeys serving as a model for a neurodevelopmental disorder, Rett syndrome (RTT), which is caused by loss-of-function mutations in the human MECP2 gene. Male mutant monkeys were embryonic lethal, reiterating that RTT is a disease of females. Through a battery of behavioral analyses, including primate-unique eye-tracking tests, in combination with brain imaging via MRI, we found a series of physiological, behavioral, and structural abnormalities resembling clinical manifestations of RTT. Moreover, blood transcriptome profiling revealed that mutant monkeys resembled RTT patients in immune gene dysregulation. Taken together, the stark similarity in phenotype and/or endophenotype between monkeys and patients suggested that gene-edited RTT founder monkeys would be of value for disease mechanistic studies as well as development of potential therapeutic interventions for RTT

Visual Search for Wines with a Triangle on the Label in a Virtual Store

Two experiments were conducted in a virtual reality (VR) environment in order to investigate participants’ in-store visual search for bottles of wines displaying a prominent triangular shape on their label. The experimental task involved virtually moving along a wine aisle in a virtual supermarket while searching for the wine bottle on the shelf that had a different triangle on its label from the other bottles. The results of Experiment 1 revealed that the participants identified the bottle with a downward-pointing triangle on its label more rapidly than when looking for an upward-pointing triangle on the label instead. This finding replicates the downward-pointing triangle superiority (DPTS) effect, though the magnitude of this effect was more pronounced in the first as compared to the second half of the experiment, suggesting a modulating role of practice. The results of Experiment 2 revealed that the DPTS effect was also modulated by the location of the target on the shelf. Interestingly, however, the results of a follow-up survey demonstrate that the orientation of the triangle did not influence the participants’ evaluation of the wine bottles. Taken together, these findings reveal how in-store the attention of consumers might be influenced by the design elements in product packaging. These results therefore suggest that shopping in a virtual supermarket might offer a practical means of assessing the shelf standout of product packaging, which has important implications for food marketing

Molecular Mechanisms Underlying Metabolic Resistance to Cyflumetofen and Bifenthrin in Tetranychus urticae Koch on Cowpea

Tetranychus urticae Koch (T. urticae) is one of the most tremendous herbivores due to its polyphagous characteristics, and is resistant to most acaricides. In this study, enzyme-linked immunosorbent assay (ELISA), transcriptome sequencing (RNA-seq) and quantitative real-time PCR (qRT-PCR) were carried out to analyze the mechanisms of T. urticae metabolic resistance to cyflumetofen and bifenthrin on cowpea. The enzyme activity of UDP-glucuronosyltransferases (UGTs) and carboxylesterases (CarEs) in the cyflumetofen-resistant (R_cfm) strain significantly decreased, while that of cytochrome P450 monooxygenases (P450s) significantly increased. Meanwhile, the activities of glutathione-S-transferases (GSTs), CarEs and P450s in the bifenthrin-resistant (R_bft) strain were significantly higher than those in the susceptible strain (Lab_SS). According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses, in the R_cfm mite strain, two carboxyl/cholinesterase (CCE) genes and two P450 genes were upregulated and one gene was downregulated, namely CYP392E7; in the R_bft mite strain, eleven CCE, nine UGT, two P450, four GST and three ABC genes were upregulated, while four CCE and three P450 genes were downregulated. Additionally, 94 differentially expressed genes (DEGs) were common to the two resistant groups. Specifically, TuCCE46 and TuCCE70 were upregulated in both resistant groups. Furthermore, the qRT-PCR validation data were consistent with those from the transcriptome sequencing analysis. Specifically, TuCCE46 (3.37-fold) was significantly upregulated in the R_cfm strain, while in the R_bft strain, TeturUGT22 (5.29-fold), teturUGT58p (1.74-fold), CYP392A11 (2.89-fold) and TuGSTd15 (5.12-fold) were significantly upregulated and TuCCE01 (0.13-fold) and CYP392A2p (0.07-fold) were significantly downregulated. Our study indicates that TuCCE46 might play the most important role in resistance to cyflumetofen, and TuCCE01, teturUGT58p, teturUGT22, CYP392A11, TuGSTd15, TuGSTm09 and TuABCG-13 were prominent in the resistance to bifenthrin. These findings provide further insight into the critical genes involved in the metabolic resistance of T. urticae to cyflumetofen and bifenthrin

Photovoltaic MPPT Algorithm Based on Hybrid Boost Converter and Variable Step Size Incremental Conductance

Aiming at the problem of low voltage gain of traditional boost converter and the incompatibility of tracking speed and tracking accuracy with the traditional incremental conductance algorithm (INC), this paper uses the hybrid boost converter as the DC/DC converter of photovoltaic system, and designs the variable step size INC algorithm control strategy to achieve Maximum power point tracking (MPPT) of photovoltaic. Simulink simulation model verifies the feasibility of the proposed algorithm, which effectively improves the output voltage and power generation efficiency of the photovoltaic system