MHSA-Net: Multi-Head Self-Attention Network for Occluded Person Re-Identification

This paper presents a novel person re-identification model, named Multi-Head Self-Attention Network (MHSA-Net), to prune unimportant information and capture key local information from person images. MHSA-Net contains two main novel components: Multi-Head Self-Attention Branch (MHSAB) and Attention Competition Mechanism (ACM). The MHSAM adaptively captures key local person information, and then produces effective diversity embeddings of an image for the person matching. The ACM further helps filter out attention noise and non-key information. Through extensive ablation studies, we verified that the Structured Self-Attention Branch and Attention Competition Mechanism both contribute to the performance improvement of the MHSA-Net. Our MHSA-Net achieves state-of-the-art performance especially on images with occlusions. We have released our models (and will release the source codes after the paper is accepted) on https://github.com/hongchenphd/MHSA-Net.Comment: Submitted to IEEE Transactions on Image Processing (TIP

ALR-GAN: Adaptive Layout Refinement for Text-to-Image Synthesis

We propose a novel Text-to-Image Generation Network, Adaptive Layout Refinement Generative Adversarial Network (ALR-GAN), to adaptively refine the layout of synthesized images without any auxiliary information. The ALR-GAN includes an Adaptive Layout Refinement (ALR) module and a Layout Visual Refinement (LVR) loss. The ALR module aligns the layout structure (which refers to locations of objects and background) of a synthesized image with that of its corresponding real image. In ALR module, we proposed an Adaptive Layout Refinement (ALR) loss to balance the matching of hard and easy features, for more efficient layout structure matching. Based on the refined layout structure, the LVR loss further refines the visual representation within the layout area. Experimental results on two widely-used datasets show that ALR-GAN performs competitively at the Text-to-Image generation task.Comment: Accepted by TM

Physicochemical Characteristics and Spoilage Bacteria of Modified Atmosphere Packaged Braised Chicken during Refrigeration

In order to explore dynamic changes in the physicochemical characteristics and microbial diversity of modified atmosphere packaged braised chicken during refrigeration, high-throughput sequencing technology and traditional isolation and identification methods were combined to study the physical and microbial changes of modified atmosphere packaged (25% CO2/75% N2) braised chicken during storage at 4 ℃ for 10 days. The results showed that total volatile basic nitrogen (TVB-N) content and total bacterial count increased significantly during storage (P 0.05). These changes were related to the gas composition in modified atmosphere packaging. The microbial species richness of braised chicken was the highest at the early stage of storage, and then decreased gradually. At the initial stage of storage, the relative abundance of Enterobacteriaceae, Acinetobacter and Aeromonas were high. At the middle and late stages of storage, the relative abundance of Weissella and Enterobacter were high. The relative abundance of Weissella, Enterobacter, Lactococcus and Leuconostoc increased gradually during the whole storage period and their growth was dominant. Six species of spoilage organisms were isolated and identified, namely, Lactobacillus curvatus, Bacillus cereus, Bacillus safensis, Serratia liquefaciens, Hafnia sp. and Enterobacter sp., which could be the major causes of the rot of braised chicken under modified atmosphere packaging conditions

Distractor-aware Event-based Tracking

Event cameras, or dynamic vision sensors, have recently achieved success from fundamental vision tasks to high-level vision researches. Due to its ability to asynchronously capture light intensity changes, event camera has an inherent advantage to capture moving objects in challenging scenarios including objects under low light, high dynamic range, or fast moving objects. Thus event camera are natural for visual object tracking. However, the current event-based trackers derived from RGB trackers simply modify the input images to event frames and still follow conventional tracking pipeline that mainly focus on object texture for target distinction. As a result, the trackers may not be robust dealing with challenging scenarios such as moving cameras and cluttered foreground. In this paper, we propose a distractor-aware event-based tracker that introduces transformer modules into Siamese network architecture (named DANet). Specifically, our model is mainly composed of a motion-aware network and a target-aware network, which simultaneously exploits both motion cues and object contours from event data, so as to discover motion objects and identify the target object by removing dynamic distractors. Our DANet can be trained in an end-to-end manner without any post-processing and can run at over 80 FPS on a single V100. We conduct comprehensive experiments on two large event tracking datasets to validate the proposed model. We demonstrate that our tracker has superior performance against the state-of-the-art trackers in terms of both accuracy and efficiency

Application of radiomics in diagnosis and treatment of lung cancer

Radiomics has become a research field that involves the process of converting standard nursing images into quantitative image data, which can be combined with other data sources and subsequently analyzed using traditional biostatistics or artificial intelligence (Al) methods. Due to the capture of biological and pathophysiological information by radiomics features, these quantitative radiomics features have been proven to provide fast and accurate non-invasive biomarkers for lung cancer risk prediction, diagnosis, prognosis, treatment response monitoring, and tumor biology. In this review, radiomics has been emphasized and discussed in lung cancer research, including advantages, challenges, and drawbacks

Rosmarinic Acid Alleviates the Endothelial Dysfunction Induced by Hydrogen Peroxide in Rat Aortic Rings via Activation of AMPK

Endothelial dysfunction is the key player in the development and progression of vascular events. Oxidative stress is involved in endothelial injury. Rosmarinic acid (RA) is a natural polyphenol with antioxidative, antiapoptotic, and anti-inflammatory properties. The present study investigates the protective effect of RA on endothelial dysfunction induced by hydrogen peroxide (H2O2). Compared with endothelium-denuded aortic rings, the endothelium significantly alleviated the decrease of vasoconstrictive reactivity to PE and KCl induced by H2O2. H2O2 pretreatment significantly injured the vasodilative reactivity to ACh in endothelium-intact aortic rings in a concentration-dependent manner. RA individual pretreatment had no obvious effect on the vasoconstrictive reaction to PE and KCl, while its cotreatment obviously mitigated the endothelium-dependent relaxation impairments and the oxidative stress induced by H2O2. The RA cotreatment reversed the downregulation of AMPK and eNOS phosphorylation induced by H2O2 in HAEC cells. The pretreatment with the inhibitors of AMPK (compound C) and eNOS (L-NAME) wiped off RA’s beneficial effects. All these results demonstrated that RA attenuated the endothelial dysfunction induced by oxidative stress by activating the AMPK/eNOS pathway

Tree species and genetic diversity increase productivity via functional diversity and trophic feedbacks

Addressing global biodiversity loss requires an expanded focus on multiple dimensions of biodiversity. While most studies have focused on the consequences of plant interspecific diversity, our mechanistic understanding of how genetic diversity within plant species affects plant productivity remains limited. Here, we use a tree species × genetic diversity experiment to disentangle the effects of species diversity and genetic diversity on tree productivity, and how they are related to tree functional diversity and trophic feedbacks. We found that tree species diversity increased tree productivity via increased tree functional diversity, reduced soil fungal diversity, and marginally reduced herbivory. The effects of tree genetic diversity on productivity via functional diversity and soil fungal diversity were negative in monocultures but positive in the mixture of the four tree species tested. Given the complexity of interactions between species and genetic diversity, tree functional diversity and trophic feedbacks on productivity, we suggest that both tree species and genetic diversity should be considered in afforestation