VideoCapsuleNet: A Simplified Network for Action Detection

The recent advances in Deep Convolutional Neural Networks (DCNNs) have shown extremely good results for video human action classification, however, action detection is still a challenging problem. The current action detection approaches follow a complex pipeline which involves multiple tasks such as tube proposals, optical flow, and tube classification. In this work, we present a more elegant solution for action detection based on the recently developed capsule network. We propose a 3D capsule network for videos, called VideoCapsuleNet: a unified network for action detection which can jointly perform pixel-wise action segmentation along with action classification. The proposed network is a generalization of capsule network from 2D to 3D, which takes a sequence of video frames as input. The 3D generalization drastically increases the number of capsules in the network, making capsule routing computationally expensive. We introduce capsule-pooling in the convolutional capsule layer to address this issue which makes the voting algorithm tractable. The routing-by-agreement in the network inherently models the action representations and various action characteristics are captured by the predicted capsules. This inspired us to utilize the capsules for action localization and the class-specific capsules predicted by the network are used to determine a pixel-wise localization of actions. The localization is further improved by parameterized skip connections with the convolutional capsule layers and the network is trained end-to-end with a classification as well as localization loss. The proposed network achieves sate-of-the-art performance on multiple action detection datasets including UCF-Sports, J-HMDB, and UCF-101 (24 classes) with an impressive ~20% improvement on UCF-101 and ~15% improvement on J-HMDB in terms of v-mAP scores

Emerging targets in human lymphoma: targeting the MYD88 mutation

B cell neoplasms co-opt the molecular machinery of normal B cells for their survival. Technological advances in cancer genomics has significantly contributed to uncovering the root cause of aggressive lymphomas, revealing a previously unknown link between TLR signaling and B cell neoplasm. Recurrent oncogenic mutations in MYD88 have been found in 39% of the activated B cell-like subtype of diffuse large B cell lymphoma (ABC DLBCL). Interestingly, 29% of ABC DLBCL have a single amino acid substitution of proline for the leucine at position 265 (L265P), and the exact same variant has also been identified in a number of lymphoid malignancies. The MYD88 L265P variant was recently identified in 90% of Wadenstrom's macroglobulinemia patients. These recent developments warrant the need for novel diagnostic tools as well as targeted therapeutics. In this review, we discuss the physiological functions of MYD88 and focus on its role in B cell lymphomas, evaluating the potential for targeting oncogenic MYD88 in lymphoma

Exactly solvable PT\mathcal{PT}-symmetric models in two dimensions

Non-hermitian, $\mathcal{PT}$-symmetric Hamiltonians, experimentally realized in optical systems, accurately model the properties of open, bosonic systems with balanced, spatially separated gain and loss. We present a family of exactly solvable, two-dimensional, $\mathcal{PT}$ potentials for a non-relativistic particle confined in a circular geometry. We show that the $\mathcal{PT}$ symmetry threshold can be tuned by introducing a second gain-loss potential or its hermitian counterpart. Our results explicitly demonstrate that $\mathcal{PT}$ breaking in two dimensions has a rich phase diagram, with multiple re-entrant $\mathcal{PT}$ symmetric phases.Comment: 6 pages, 6 figure

Competition between Superconductivity and Charge Density Wave Ordering in the Lu5_5Ir4_4(Si1−x_{1-x}Gex_x)10_{10} Alloy System

We have performed bulk measurements such as dc magnetic susceptibility, electrical resistivity and heat capacity on the pseudo-ternary alloys Lu$_5$Ir$_4$(Si$_{1-x}$Ge$_x$)$_{10}$ to study the interplay and competition between superconductivity and the charge density wave (CDW) ordering transition. We track the evolution of the superconducting transition temperature T$_{SC}$ and the CDW ordering temperature T$_{CDW}$ as a function of x (concentration of Ge) ($0.0 \leq x\leq~1.0$). We find that increasing x (increasing disorder) suppresses the T$_{CDW}$ rapidly with the concomitant increase in T$_{SC}$. We present a temperature-concentration (or volume) phase diagram for this system and compare our results with earlier work on substitution at the Lu or Ir site to show how dilution at the Si site presents a different situation from these other works. The heat capacity data in the vicinity of the CDW transition has been analyzed using a model of critical fluctuations in addition to a mean-field contribution and a smooth lattice background. We find that the critical exponents change appreciably with increasing disorder. This analysis suggests that the strong-coupling and non mean-field like CDW transition in the parent compound Lu$_5$Ir$_4$Si$_{10}$ changes to a mean-field like transition with increasing Ge concentration.Comment: 14 pages and 8 figures. Accepted for publication in Phys. Rev.