One-Shot Fine-Grained Instance Retrieval

Fine-Grained Visual Categorization (FGVC) has achieved significant progress recently. However, the number of fine-grained species could be huge and dynamically increasing in real scenarios, making it difficult to recognize unseen objects under the current FGVC framework. This raises an open issue to perform large-scale fine-grained identification without a complete training set. Aiming to conquer this issue, we propose a retrieval task named One-Shot Fine-Grained Instance Retrieval (OSFGIR). "One-Shot" denotes the ability of identifying unseen objects through a fine-grained retrieval task assisted with an incomplete auxiliary training set. This paper first presents the detailed description to OSFGIR task and our collected OSFGIR-378K dataset. Next, we propose the Convolutional and Normalization Networks (CN-Nets) learned on the auxiliary dataset to generate a concise and discriminative representation. Finally, we present a coarse-to-fine retrieval framework consisting of three components, i.e., coarse retrieval, fine-grained retrieval, and query expansion, respectively. The framework progressively retrieves images with similar semantics, and performs fine-grained identification. Experiments show our OSFGIR framework achieves significantly better accuracy and efficiency than existing FGVC and image retrieval methods, thus could be a better solution for large-scale fine-grained object identification.Comment: Accepted by MM2017, 9 pages, 7 figure

The gut microbiome in atherosclerotic cardiovascular disease

The gut microbiota may play a role in cardiovascular diseases. Here, the authors perform a metagenome-wide association study on stools from individuals with atherosclerotic cardiovascular disease and healthy controls, identifying microbial strains and functions associated with the disease

A novel compressed sensing-based non-orthogonal multiple access scheme for massive MTC in 5G systems

Abstract The main challenges for massive machine type communication in 5G system are to support random access for massive users and to control signaling overhead and data processing complexity. To address these challenges, we propose a novel compressed sensing (CS)-based non-orthogonal multiple access (NOMA) scheme, called CS-NOMA, which introduces low coherence spreading (LCS) signatures to enable joint activity and data detection without requiring the activity information of users in advance. We present a sufficient condition for the construction of the LCS signatures to ensure that a CS-based multi-user detection (CS-MUD) can be effectively deployed in base station. Furthermore, we study the CS-NOMA scheme with imperfect channel state information (CSI) and present a bound for the performance of the CS-NOMA scheme. Simulation results show that the proposed scheme achieves a relatively high system overload (up to 4) when the active users are relatively sparse with an activity ratio of 1%, which implies that the CS-NOMA scheme can significantly improve the spectral efficiency, avoid the control signaling overhead, and reduce the transmission latency

An Iridoid Glucoside and the Related Aglycones from <i>Cornus florida</i>

A new iridoid glucoside, cornusoside A (<b>1</b>), and four new natural product iridoid aglycones, cornolactones A–D (<b>2</b>–<b>5</b>), together with 10 known compounds were isolated from the leaves of <i>Cornus florida</i>. The structures of compounds <b>1</b>–<b>5</b> were established by interpretation of their spectroscopic data. Cornolactone B (<b>3</b>) is the first natural <i>cis</i>-fused tricyclic dilactone iridoid containing both a five- and a six-membered lactone ring. A biosynthesis pathway is proposed for cornolactones C (<b>4</b>) and D (<b>5</b>), the C-6 epimers of compounds <b>1</b>–<b>3</b>

Ultrasensitive Detection of Testosterone Using Microring Resonator with Molecularly Imprinted Polymers

We report ultrasensitive and highly selective detection of testosterone based on microring resonance sensor using molecularly imprinted polymers (MIP). A silicon-on-insulator (SOI) micoring resonator was modified by MIP films (MIPs) on a surface. The MIPs was synthesized by thermopolymerization using methacrylic acid as functional monomer and ethylene glycol dimethacrylate as crosslinking agent. The concentration of detected testosterone varies from 0.05 ng/mL to 10 ng/mL. The detection limit reaches 48.7 pg/mL. Ultrahigh sensitivity, good specificity and reproducibility have been demonstrated, indicating the great potential of making a cost effective and easy to operate lab-on-Chip and down scaling micro-fluidics devices in biosensing