DarkRank: Accelerating Deep Metric Learning via Cross Sample Similarities Transfer

We have witnessed rapid evolution of deep neural network architecture design in the past years. These latest progresses greatly facilitate the developments in various areas such as computer vision and natural language processing. However, along with the extraordinary performance, these state-of-the-art models also bring in expensive computational cost. Directly deploying these models into applications with real-time requirement is still infeasible. Recently, Hinton etal. have shown that the dark knowledge within a powerful teacher model can significantly help the training of a smaller and faster student network. These knowledge are vastly beneficial to improve the generalization ability of the student model. Inspired by their work, we introduce a new type of knowledge -- cross sample similarities for model compression and acceleration. This knowledge can be naturally derived from deep metric learning model. To transfer them, we bring the "learning to rank" technique into deep metric learning formulation. We test our proposed DarkRank method on various metric learning tasks including pedestrian re-identification, image retrieval and image clustering. The results are quite encouraging. Our method can improve over the baseline method by a large margin. Moreover, it is fully compatible with other existing methods. When combined, the performance can be further boosted

GAS-PHASE ACID-BASE PROPERTIES AND CONFORMATIONS OF OLIGOPEPTIDES THROUGH MASS SPECTROMETRY AND COMPUTATIONAL STUDIES

This dissertation presents a comprehensive study of the peptides of interest to deeper understand the gas-phase acid-base properties in relation to their conformations and chirality. In the first part of the study, two pairs of alanine (A)-based isomeric peptides consisting of a basic probe, lysine (Lys) or 2,3-diaminopropionic acid (Dap), were investigated to understand the nature of the enhanced basicity when the basic probe was moved from the N-terminus to the C-terminus. In the second part of the study, alanine-based peptides containing a cysteine (C) as the acidic probe were investigated to understand the chirality effects on the gas-phase acidity by altering the chiral centers systemically. Previous studies by mass spectrometry showed that the peptides ALys and AADap have had remarkably higher proton affinity (PA) compared to their isomeric counterparts LysA and DapAA. In this work, conformations, energetics, and molecular properties of the peptide systems have been thoroughly characterized through infrared multiple photon dissociation (IRMPD) spectroscopy and quantum chemical computations utilizing a set of molecular modeling tools. The molecular properties include charge distribution, dipole moment, torsional strain, hydrogen bonding, and non-covalent interaction. Computational studies yielded the lowest energy conformations along with their theoretical infrared (IR) spectra for each of the peptide systems. The resulting theoretical proton affinities are in excellent agreement with experiments. The results also suggest that the relative stability of the protonated peptides is the main source of the difference in the gas-phase basicity between the isomeric peptides. Structurally representative conformations for the protonated peptides were identified by matching the theoretical IR spectra to the corresponding IRMPD spectra. The band features of the IRMPD spectra were analyzed in detail by vibrational mode decomposition. The N-probe peptide ions, LysAH+ and DapAAH+, adopt diverse backbone geometries and intramolecular hydrogen bonding networks, and rely heavily on the hydrogen bonds for conformational stabilization. In contrast, the C-probe peptide ions, ALysH+ and AADapH+, adopt helical conformations, and benefit from the interaction between the helix macrodipole and the charged NH3+ group. The low torsional strain on the Lys sidechain contributes significantly to the conformational stability for ALysH+ than for LysAH+. The chirality of each residue in CAAA and Ac-CAAA (Ac represents the acetyl group) alters from the L- to the D-form systematically to generate two series of peptides. Qualitative comparison of the gas-phase acidity was achieved through mass spectrometry measurements using the Cooks’ kinetic method. The following two acidity ladders from the most acidic to the least acidic were obtained: CAAdA \u3e CAdAA ~ CAAA \u3e dCAAA \u3e CdAAA, and Ac-dCAAA \u3e Ac-CAAdA \u3e Ac-CAAA \u3e Ac-CAdAA \u3e Ac-CdAAA, where the superscript-d in front of the amino acid symbol indicates the D-form of that residue. In both non-acetylated and acetylated peptides, the gas-phase acidity increases as the D-alanine moves further away from the N-terminal acidic probe cysteine. Inversion of the cysteine residue from the L- to the D-form reduces the gas-phase acidity of the non-acetylated peptide and enhances the gas-phase acidity of the acetylated one. Overall, the change in the gas-phase acidity is likely due to the conformational reorganization in the deprotonated peptides upon chiral inversion

Protecting Heritage Trees in Weifang City, Shandong Province, Northern China

Heritage trees are long-lived trees or notable trees with great historical significance, scientific value, or commemorative importance. Many heritage trees have been preserved in Weifang City, Shandong Province, Northern China. In this paper, the origin, species diversity, age structure, health, surrounding habitats, distribution, genera floristic composition, and challenges of protecting the heritage trees were investigated using literature analysis, field survey, and interview. There are 864 heritage trees in the city, composed of 49 species, 41 genera, and 25 families. The heritage trees are divided into three original types: religious trees, naturally dispersed and preserved wild trees, and trees with agricultural backgrounds or used as offerings. Particularly, Sophora japonica, Ziziphus jujube, Ginkgo biloba, Sabina chinensis, Platycladus orientalis, and Osmanthus fragrans are the six most common species. There are 208 individuals of 500 years or elder, 293 individuals of 300–499 years old, 359 individuals of 100–299 years old, and 4 individuals of notable trees. Most of them are distributed in low-urbanized areas of the 4 county-level cities and Linqu county, and few are distributed in high-urbanized areas of the 4 districts of Weifang City. There are 14, 12, and 6 genera belonging to the areal-types of Temperate, Cosmopolitan, and Tropic, respectively, similar to that of wild seed plants in Yishan Mountain. There are some challenges in protecting heritage trees, such as urbanization, habitat deterioration, natural disasters, anthropic activities, health decline, and inadequate management. Some protection measures that have been taken previously are summarized, and some measures that should be taken in the future are proposed

CANAMRF: An Attention-Based Model for Multimodal Depression Detection

Multimodal depression detection is an important research topic that aims to predict human mental states using multimodal data. Previous methods treat different modalities equally and fuse each modality by na\"ive mathematical operations without measuring the relative importance between them, which cannot obtain well-performed multimodal representations for downstream depression tasks. In order to tackle the aforementioned concern, we present a Cross-modal Attention Network with Adaptive Multi-modal Recurrent Fusion (CANAMRF) for multimodal depression detection. CANAMRF is constructed by a multimodal feature extractor, an Adaptive Multimodal Recurrent Fusion module, and a Hybrid Attention Module. Through experimentation on two benchmark datasets, CANAMRF demonstrates state-of-the-art performance, underscoring the effectiveness of our proposed approach.Comment: 6 pages, 3 figures. Pacific Rim International Conference on Artificial Intelligence. Singapore: Springer Nature Singapore, 202