Sharif Digital Repository

Recently, distance metric learning has been received an increasing attention and found as a powerful approach for semi-supervised learning tasks. In the last few years, several methods have been proposed for metric learning when must-link and/or cannot-link constraints as supervisory information are available. Although many of these methods learn global Mahalanobis metrics, some recently introduced methods have tried to learn more flexible distance metrics using a kernel-based approach. In this paper, we consider the problem of kernel learning from both pairwise constraints and unlabeled data. We propose a method that adapts a flexible distance metric via learning a nonparametric kernel... 

Monitoring the ratio of 40- and 42-residue amyloid β peptides (i.e., Aβ40 and Aβ42) in human plasma is considered one of the hallmarks of detection of the early stage of Alzheimer's disease (AD). Therefore, development of a specific, yet non-antibody-based method for simultaneous detection of Aβ40 and Aβ42 may have considerable clinical applications. Here, we developed a 'nanoparticle-based colorimetric sensor array' utilizing label-free gold and silver nanoparticles for visual detection of Aβ42 and Aβ40. Different aggregation behaviors of nanoparticles through their conjugation with Aβ42 and Aβ40 followed by the coordination of Aβ42 and Aβ40 with Cu(ii) led to diverse spectral and color...