Searching by parts: Towards fine-grained image retrieval respecting species correlation.

Most of the existing works on fine-grained image categorization and retrieval focus on finding similar images from the same species and often give little importance to inter-species similarities. However, these similarities may carry species correlations such as the same ancestors or similar habits, which are helpful in taxonomy and understanding biological traits. In this paper, we devise a new fine-grained retrieval task that searches for similar instances from different species based on body parts.

Breakthroughs and Applications of Organ-on-a-Chip Technology.

Organ-on-a-chip (OOAC) is an emerging technology based on microfluid platforms and in vitro cell culture that has a promising future in the healthcare industry. The numerous advantages of OOAC over conventional systems make it highly popular. The chip is an innovative combination of novel technologies, including lab-on-a-chip, microfluidics, biomaterials, and tissue engineering.

Epigenetic reactivation of transcriptional programs orchestrating fetal lung development in human pulmonary hypertension.

Phenotypic alterations in resident vascular cells contribute to the vascular remodeling process in diseases such as pulmonary (arterial) hypertension [P(A)H]. How the molecular interplay between transcriptional coactivators, transcription factors (TFs), and chromatin state alterations facilitate the maintenance of persistently activated cellular phenotypes that consequently aggravate vascular remodeling processes in PAH remains poorly explored. RNA sequencing (RNA-seq) in pulmonary artery fibroblasts (FBs) from adult human PAH and control lungs revealed 2460 differentially transcribed genes.

Tensor Representations for Action Recognition.

Human actions in video sequences are characterized by the complex interplay between spatial features and their temporal dynamics. In this paper, we propose novel tensor representations for compactly capturing such higher-order relationships between visual features for the task of action recognition. We propose two tensor-based feature representations, viz.

Targeted mutagenesis in Nicotiana tabacum ADF gene using shockwave-mediated ribonucleoprotein delivery increases osmotic stress tolerance.

DNA-free genome editing involves the direct introduction of ribonucleoprotein (RNP) complexes into cells, but this strategy has rarely been successful in plants. In the present study, we describe a new technique for the introduction of RNPs into plant cells involving the generation of cavitation bubbles using a pulsed laser. The resulting shockwave achieves the efficient transfection of walled cells in tissue explants by creating transient membrane pores.

Generalized One-Class Learning Using Pairs of Complementary Classifiers.

One-class learning is the classic problem of fitting a model to the data for which annotations are available only for a single class. In this paper, we explore novel objectives for one-class learning, which we collectively refer to as Generalized One-class Discriminative Subspaces (GODS). Our key idea is to learn a pair of complementary classifiers to flexibly bound the one-class data distribution, where the data belongs to the positive half-space of one of the classifiers in the complementary pair and to the negative half-space of the other.

Learning Log-Determinant Divergences for Positive Definite Matrices.

Representations in the form of Symmetric Positive Definite (SPD) matrices have been popularized in a variety of visual learning applications due to their demonstrated ability to capture rich second-order statistics of visual data. There exist several similarity measures for comparing SPD matrices with documented benefits. However, selecting an appropriate measure for a given problem remains a challenge and in most cases, is the result of a trial-and-error process.

Image Descriptors for Weakly Annotated Histopathological Breast Cancer Data.

Introduction: Cancerous Tissue Recognition (CTR) methodologies are continuously integrating advancements at the forefront of machine learning and computer vision, providing a variety of inference schemes for histopathological data. Histopathological data, in most cases, come in the form of high-resolution images, and thus methodologies operating at the patch level are more computationally attractive. Such methodologies capitalize on pixel level annotations (tissue delineations) from expert pathologists, which are then used to derive labels at the patch level.

Discriminative Video Representation Learning Using Support Vector Classifiers.

Most popular deep models for action recognition in videos generate independent predictions for short clips, which are then pooled heuristically to assign an action label to the full video segment. As not all frames may characterize the underlying action-indeed, many are common across multiple actions-pooling schemes that impose equal importance on all frames might be unfavorable. In an attempt to tackle this problem, we propose discriminative pooling, based on the notion that among the deep features generated on all short clips, there is at least one that characterizes the action.

Visual Permutation Learning.

We present a principled approach to uncover the structure of visual data by solving a deep learning task coined visual permutation learning. The goal of this task is to find the permutation that recovers the structure of data from shuffled versions of it. In the case of natural images, this task boils down to recovering the original image from patches shuffled by an unknown permutation matrix.

Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices.

Data encoded as symmetric positive definite (SPD) matrices frequently arise in many areas of computer vision and machine learning. While these matrices form an open subset of the Euclidean space of symmetric matrices, viewing them through the lens of non-Euclidean Riemannian (Riem) geometry often turns out to be better suited in capturing several desirable data properties. Inspired by the great success of dictionary learning and sparse coding (DLSC) for vector-valued data, our goal in this paper is to represent data in the form of SPD matrices as sparse conic combinations of SPD atoms from a learned dictionary via a Riem geometric approach.

N-cadherin relocalization during cardiac trabeculation.

During cardiac trabeculation, cardiomyocytes delaminate from the outermost (compact) layer to form complex muscular structures known as trabeculae. As these cardiomyocytes delaminate, the remodeling of adhesion junctions must be tightly coordinated so cells can extrude from the compact layer while remaining in tight contact with their neighbors. In this study, we examined the distribution of N-cadherin (Cdh2) during cardiac trabeculation in zebrafish.

Bayesian Nonparametric Clustering for Positive Definite Matrices.

Symmetric Positive Definite (SPD) matrices emerge as data descriptors in several applications of computer vision such as object tracking, texture recognition, and diffusion tensor imaging. Clustering these data matrices forms an integral part of these applications, for which soft-clustering algorithms (K-Means, expectation maximization, etc.) are generally used.

Erianthus arundinaceus HSP70 (EaHSP70) Acts as a Key Regulator in the Formation of Anisotropic Interdigitation in Sugarcane (Saccharum spp. hybrid) in Response to Drought Stress.

Plant growth during abiotic stress is a long sought-after trait especially in crop plants in the context of global warming and climate change. Previous studies on leaf epidermal cells have revealed that during normal growth and development, adjacent cells interdigitate anisotropically to form cell morphological patterns known as interlocking marginal lobes (IMLs), involving the cell wall-cell membrane-cortical actin continuum. IMLs are growth-associated cell morphological changes in which auxin-binding protein (ABP), Rho GTPases and actin are known to play important roles.

Isotropic actomyosin dynamics promote organization of the apical cell cortex in epithelial cells.

Although cortical actin plays an important role in cellular mechanics and morphogenesis, there is surprisingly little information on cortex organization at the apical surface of cells. In this paper, we characterize organization and dynamics of microvilli (MV) and a previously unappreciated actomyosin network at the apical surface of Madin-Darby canine kidney cells. In contrast to short and static MV in confluent cells, the apical surfaces of nonconfluent epithelial cells (ECs) form highly dynamic protrusions, which are often oriented along the plane of the membrane.

Efficient nearest neighbors via robust sparse hashing.

This paper presents a new nearest neighbor (NN) retrieval framework: robust sparse hashing (RSH). Our approach is inspired by the success of dictionary learning for sparse coding. Our key idea is to sparse code the data using a learned dictionary, and then to generate hash codes out of these sparse codes for accurate and fast NN retrieval.

Jensen-Bregman LogDet divergence with application to efficient similarity search for covariance matrices.

Covariance matrices have found success in several computer vision applications, including activity recognition, visual surveillance, and diffusion tensor imaging. This is because they provide an easy platform for fusing multiple features compactly. An important task in all of these applications is to compare two covariance matrices using a (dis)similarity function, for which the common choice is the Riemannian metric on the manifold inhabited by these matrices.

Pulsed-laser-induced damage in rat corneas: time-resolved imaging of physical effects and acute biological response.

Laser-induced damage is studied in the rat corneal epithelium and stroma using a combination of time-resolved imaging and biological assays. Cavitation bubble interactions with cells are visualized at a higher spatial resolution than previously reported. The shock wave is observed to propagate through the epithelium without cell displacement or deformation.