Deep Metric Multi-View Hashing for Multimedia Retrieval

Learning the hash representation of multi-view heterogeneous data is an important task in multimedia retrieval. However, existing methods fail to effectively fuse the multi-view features and utilize the metric information provided by the dissimilar samples, leading to limited retrieval precision. Current methods utilize weighted sum or concatenation to fuse the multi-view features. We argue that these fusion methods cannot capture the interaction among different views. Furthermore, these methods ignored the information provided by the dissimilar samples. We propose a novel deep metric multi-view hashing (DMMVH) method to address the mentioned problems. Extensive empirical evidence is presented to show that gate-based fusion is better than typical methods. We introduce deep metric learning to the multi-view hashing problems, which can utilize metric information of dissimilar samples. On the MIR-Flickr25K, MS COCO, and NUS-WIDE, our method outperforms the current state-of-the-art methods by a large margin (up to 15.28 mean Average Precision (mAP) improvement).Comment: Accepted by IEEE ICME 202

Dynamical alterations of brain function and gut microbiome in weight loss

ObjectiveIntermittent energy restriction (IER) is an effective weight loss strategy. However, little is known about the dynamic effects of IER on the brain-gut-microbiome axis.MethodsIn this study, a total of 25 obese individuals successfully lost weight after a 2-month IER intervention. FMRI was used to determine the activity of brain regions. Metagenomic sequencing was performed to identify differentially abundant gut microbes and pathways in from fecal samples.ResultsOur results showed that IER longitudinally reduced the activity of obese-related brain regions at different timepoints, including the inferior frontal orbital gyrus in the cognitive control circuit, the putamen in the emotion and learning circuit, and the anterior cingulate cortex in the sensory circuit. IER longitudinally reduced E. coli abundance across multiple timepoints while elevating the abundance of obesity-related Faecalibacterium prausnitzii, Parabacteroides distasonis, and Bacterokles uniformis. Correlation analysis revealed longitudinally correlations between gut bacteria abundance alterations and brain activity changes.ConclusionsThere was dynamical alteration of BGM axis (the communication of E. coli with specific brain regions) during the weight loss under the IER

Comparative genomics reveals insights into avian genome evolution and adaptation

Birds are the most species-rich class of tetrapod vertebrates and have wide relevance across many research fields. We explored bird macroevolution using full genomes from 48 avian species representing all major extant clades. The avian genome is principally characterized by its constrained size, which predominantly arose because of lineage-specific erosion of repetitive elements, large segmental deletions, and gene loss. Avian genomes furthermore show a remarkably high degree of evolutionary stasis at the levels of nucleotide sequence, gene synteny, and chromosomal structure. Despite this pattern of conservation, we detected many non-neutral evolutionary changes in protein-coding genes and noncoding regions. These analyses reveal that pan-avian genomic diversity covaries with adaptations to different lifestyles and convergent evolution of traits

Metabonomics Study of the Hematopoietic Effect of Medicinal Wine Maoji Jiu on a Blood Deficiency Rat Model by Ultra-High-Performance Liquid Chromatography Coupled to Quadrupole Time-of-Flight Mass Spectrometry and a Pattern Recognition Approach

Maoji Jiu (MJ) is a kind of medicinal wine that has been widely used by Chinese people for many years to nourish and promote blood circulation. The purpose of this study was to investigate the hematopoietic effect of MJ on the metabolism of blood deficient rats and to explore the underlying hematopoietic regulation mechanisms. Blood deficiency model rats were induced by subcutaneous injection of N-acetylphenylhydrazine (APH) and intraperitoneal injection of cyclophosphamide (CTX). The plasma metabolic fingerprints of blood deficiency model rats with and without MJ treatment were obtained by using metabonomics based on ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC–QTOF/MS). Orthogonal partial least squares-discriminant analysis (OPLS–DA) was used to evaluate the hematopoietic effect of MJ and identify potential biomarkers in the plasma of blood deficiency model rats. The levels of white blood cells (WBC), red blood cells (RBC) and hemoglobin (HGB) and the activity of antioxidant capacity showed a recovery trend to the control group after MJ treatment, while the dose of 10 mL/kg showed the best effect. In this study, thirteen potential biomarkers were identified, which were mainly related to seven metabolic pathways, including linoleic acid metabolism, d-glutamine and d-glutamate metabolism, alanine, aspartate and glutamate metabolism, tryptophan metabolism, pyrimidine metabolism, porphyrin and chlorophyll metabolism and arginine biosynthesis. Metabolomics was applied frequently to reflect the physiological and metabolic state of organisms comprehensively, indicating that the rapid plasma metabonomics may be a potentially powerful tool to reveal the efficacy and enriching blood mechanism of MJ

Distributed Model Training based on Data Parallelism in Edge Computing-enabled Elastic Optical Networks

IEEE The emergence of edge computing provides an effective solution to execute distributed model training (DMT). The deployment of training data among edge nodes affects the training efficiency and network resource usage. This letter aims for the efficient provisioning of DMT services by optimizing the partition and distribution of training data in edge computing-enabled optical networks. An integer linear programming (ILP) model and a data parallelism deployment algorithm (DPDA) are proposed to solve this problem. The performance of the proposed approaches is evaluated through simulation. Simulation results show that the proposed algorithm can deploy more DMT services compared with benchmark