Discriminative Density-ratio Estimation

The covariate shift is a challenging problem in supervised learning that results from the discrepancy between the training and test distributions. An effective approach which recently drew a considerable attention in the research community is to reweight the training samples to minimize that discrepancy. In specific, many methods are based on developing Density-ratio (DR) estimation techniques that apply to both regression and classification problems. Although these methods work well for regression problems, their performance on classification problems is not satisfactory. This is due to a key observation that these methods focus on matching the sample marginal distributions without paying attention to preserving the separation between classes in the reweighted space. In this paper, we propose a novel method for Discriminative Density-ratio (DDR) estimation that addresses the aforementioned problem and aims at estimating the density-ratio of joint distributions in a class-wise manner. The proposed algorithm is an iterative procedure that alternates between estimating the class information for the test data and estimating new density ratio for each class. To incorporate the estimated class information of the test data, a soft matching technique is proposed. In addition, we employ an effective criterion which adopts mutual information as an indicator to stop the iterative procedure while resulting in a decision boundary that lies in a sparse region. Experiments on synthetic and benchmark datasets demonstrate the superiority of the proposed method in terms of both accuracy and robustness

Sequence effects by non-predictive arrow cues

Previous studies have found that attention orienting is influenced by the orienting processes of previous trials in a spatial cueing paradigm. This study mainly investigated whether this sequence effect could happen for a non-predictive arrow cue and whether it was influenced by the cue-target SOAs in previous and current trials. A significant sequence effect was observed for arrow cues even when voluntary control was not required, and it was significantly influenced by the SOAs of previous trials. The present results support the automatic memory check hypothesis and may reflect some temporal characteristics of the memory mechanism in sequential processes. In addition, contrary to the previous findings, we found an overall response facilitation following a catch trial, suggesting that the influence of preceding catch trials may be sensitive to experimental contexts

Doping induced anisotropic growth in C60

Using density functional theory with generalized gradient approximation for exchange and correlation energy, we show that substitution of a Si atom at one of the C sites in C60 not only allows C59Si to have a hydrophobic head with a hydrophilic tail but also the Si atom acts as a seed for anisotropic growth of the heterofullerene. This is demonstrated by interacting C59Si with N7Sc and B8Si. The resulting complex structures exhibit enhanced electric dipole moments and anisotropy. Thus, doping induced anisotropic growth of nanostructures provides a novel route for the synthesis of bifunctional particles with atomic-level control on selectivity and diversity. These particles may have important applications in biomedical, solar, and display industry

First-principles study of hydrogen adsorption in metal-doped COF-10

Covalent organic frameworks (COFs), due to their low-density, high-porosity, and high-stability, have promising applications in gas storage. In this study we have explored the potential of COFs doped with Li and Ca metal atoms for storing hydrogen under ambient thermodynamic conditions. Using density functional theory we have performed detailed calculations of the sites Li and Ca atoms occupy in COF-10 and their interaction with hydrogen molecules. The binding energy of Li atom on COF-10 substrate is found to be about 1.0 eV and each Li atom can adsorb up to three H2 molecules. However, at high concentration, Li atoms cluster and, consequently, their hydrogen storage capacity is reduced due to steric hindrance between H2 molecules. On the other hand, due to charge transfer from Li to the substrate, O sites provide additional enhancement for hydrogen adsorption. With increasing concentration of dopedmetal atoms, the COF-10 substrate provides an additional platform for storing hydrogen. Similar conclusions are reached for Ca doped COF-10

Spectral tracing of deuterium for imaging glucose metabolism.

Cells and tissues often display pronounced spatial and dynamical metabolic heterogeneity. Common glucose-imaging techniques report glucose uptake or catabolism activity, yet do not trace the functional utilization of glucose-derived anabolic products. Here we report a microscopy technique for the optical imaging, via the spectral tracing of deuterium (STRIDE), of diverse macromolecules derived from glucose. Based on stimulated Raman-scattering imaging, STRIDE visualizes the metabolic dynamics of newly synthesized macromolecules, such as DNA, protein, lipids and glycogen, via the enrichment and distinct spectra of carbon-deuterium bonds transferred from the deuterated glucose precursor. STRIDE can also use spectral differences derived from different glucose isotopologues to visualize temporally separated glucose populations using a pulse-chase protocol. We also show that STRIDE can be used to image glucose metabolism in many mouse tissues, including tumours, brain, intestine and liver, at a detection limit of 10 mM of carbon-deuterium bonds. STRIDE provides a high-resolution and chemically informative assessment of glucose anabolic utilization