Hadronic Molecular States Composed of Spin-323\over 2 Singly Charmed Baryons

We investigate the possible deuteron-like molecules composed of a pair of charmed spin-$\frac{3}{2}$ baryons, or one charmed baryon and one charmed antibaryon within the one-boson-exchange (OBE) model. For the spin singlet and triplet systems, we consider the couple channel effect between systems with different orbital angular momentum. Most of the systems have binding solutions. The couple channel effect plays a significant role in the formation of some loosely bound states. The possible molecular states of $\Omega_c^*\Omega_c^*$ and $\Omega_c^*\bar{\Omega}_c^*$ might be stable once produced.Comment: 18 pages, 7 figure

Photoacoustic tomography with a virtual point detector

We devise and explore a ring-shaped acoustic detector associated with a virtual point detector concept for photoacoustic tomography. The center of the ring transducer scans a circle around the object to be imaged and then is treated as an omni-directional virtual point detector in photoacoustic image reconstruction. The virtual point detector introduces a space-invariant point spread function in photoacoustic image reconstruction and thus improves the tangential resolution, which is due to the finite aperture. Compared with a real point detector, the virtual point detector can provide similar spatial resolution but better SNR. Compared with a real finite-aperture detector, the virtual point detector can provide similar SNR but better spatial resolution. In addition, because of its virtual feature, the virtual point detector can be placed very close to and even inside of a tissue sample to locally scan a region of interest, which yields good SNR and spatial resolution

3D PersonVLAD: Learning Deep Global Representations for Video-based Person Re-identification

In this paper, we introduce a global video representation to video-based person re-identification (re-ID) that aggregates local 3D features across the entire video extent. Most of the existing methods rely on 2D convolutional networks (ConvNets) to extract frame-wise deep features which are pooled temporally to generate the video-level representations. However, 2D ConvNets lose temporal input information immediately after the convolution, and a separate temporal pooling is limited in capturing human motion in shorter sequences. To this end, we present a \textit{global} video representation (3D PersonVLAD), complementary to 3D ConvNets as a novel layer to capture the appearance and motion dynamics in full-length videos. However, encoding each video frame in its entirety and computing an aggregate global representation across all frames is tremendously challenging due to occlusions and misalignments. To resolve this, our proposed network is further augmented with 3D part alignment module to learn local features through soft-attention module. These attended features are statistically aggregated to yield identity-discriminative representations. Our global 3D features are demonstrated to achieve state-of-the-art results on three benchmark datasets: MARS \cite{MARS}, iLIDS-VID \cite{VideoRanking}, and PRID 2011Comment: Accepted to appear at IEEE Transactions on Neural Networks and Learning System

Tetra-μ-acetato-κ8 O:O′-bis[(N 2,N 2-di­methyl­pyrazin-2-amine-κN 4)copper(II)]

The title binuclear complex, [Cu2(C2H3O2)4(C6H9N3)2], lies on an inversion center with four acetate ligands bridging two CuII ions and two monodentate N,N-dimethyl­pyrazine-2-amine ligands coordinating each CuII ion via N atoms, forming slightly distorted square-pyramidal environments