PURPOSE Peanut agglutinin lectin (PNA) is known for its selective binding to cone cells and to the cone domains of the interphotoreceptor matrix. In the current study, the authors investigated whether there is any difference in PNA binding between color-specific cones of the cone-dominant ground squirrel. METHODS Consecutive serial sections of the retina of Spermophilus tridecemlineatus were ...

electron paramagnetic resonance (epr) spectroscopy, also known as electron spin resonance(esr) especially among physicists, is a strong and versatile spectroscopic method forinvestigation of paramagnetic systems, i.e. systems like free radicals and most transition metalions, which have unpaired electrons. the sensitivity and selectivity of epr are notable andintriguing as compared to other spec...

Multi-label classification problem has become more important in image processing and text analysis where an object often is associated with many labels at the same time. Recently, even in this problem setting dimension reduction aiming at avoiding the curse of dimensionality has gathered an attention, but it is still a challenging problem. Nonnegative Matrix Factorization (NMF) is one of promis...

We present a scalable, generative framework for multi-label learning with missing labels. Our framework consists of a latent factor model for the binary label matrix, which is coupled with an exposure model to account for label missingness (i.e., whether a zero in the label matrix is indeed a zero or denotes a missing observation). The underlying latent factor model also assumes that the low-di...

While multi-label classification can be widely applied for problems where multiple classes can be assigned to an object, its effectiveness may be sacrificed due to curse of dimensionality in the feature space and sparseness of dimensionality in the label space. As a solution, this paper presents two alternative methods, namely Dependent Dual Space Reduction and Independent Dual Space Reduction,...

To tackle a multi-label classification problem with many classes, recently label space dimension reduction (LSDR) is proposed. It encodes the original label space to a low-dimensional latent space and uses a decoding process for recovery. In this paper, we propose a novel method termed FaIE to perform LSDR via Feature-aware Implicit label space Encoding. Unlike most previous work, the proposed ...

labeling theory is one of the most famous theories in criminology domain. the pivots of this theory consist of the role of power owners in definition of crime and determination of offender, effects of labeling and solutions for prevention of entering label. with study the pivots of labeling theory in islamic sources, we observe that however there is no similarity between religious bases and bas...

Multi-label image recognition is a fundamental yet practical task because real-world images inherently possess multiple semantic labels. However, it difficult to collect large-scale multi-label annotations due the complexity of both input and output label spaces. To reduce annotation cost, we propose structured transfer (SST) framework that enables training models with partial labels, i.e., mer...