Beijing University of Technology

About: Beijing University of Technology is a education organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: Microstructure & Computer science. The organization has 31929 authors who have published 31987 publications receiving 352112 citations. The organization is also known as: Běijīng Gōngyè Dàxué & Beijing Polytechnic University.

MC360IQA: A Multi-channel CNN for Blind 360-Degree Image Quality Assessment

Abstract: 360-degree images/videos have been dramatically increasing in recent years. The characteristic of omnidirectional-view results in high resolution of 360-degree images/videos, which makes them difficult to be transported and stored. To deal with the problem, video coding technologies are used to compress the omnidirectional content but they will introduce the compression distortion. Therefore, it is important to study how popular coding technologies affect the quality of 360-degree images. In this paper, we present a study on both subjective and objective quality assessment of compressed virtual reality (VR) images. We first build a compressed VR image quality (CVIQ) database including 16 reference images and 528 compressed ones with three prevailing coding technologies. Then, we propose a multi-channel convolution neural network (CNN) for blind 360-degree image quality assessment (MC360IQA). To be consistent with the visual content seen in the VR device, we project each 360-degree image into six viewport images, which are adopted as inputs of the proposed model. MC360IQA consists of two parts, a multi-channel CNN and an image quality regressor. The multi-channel CNN includes six parallel hyper-ResNet34 networks, where the hyper structure is used to incorporate the features from intermediate layers. The image quality regressor fuses the features and regresses them to final scores. The experimental results show that our model achieves the best performance among the state-of-art full-reference (FR) and no-reference (NR) image quality assessment (IQA) models on the CVIQ database and other available 360-degree IQA database.

Surface-Functionalized Modified Copper Sulfide Nanoparticles Enhance Checkpoint Blockade Tumor Immunotherapy by Photothermal Therapy and Antigen Capturing

Abstract: Nanomaterial-based tumor photothermal therapy (PTT) has attracted increasing attention and been a promising method for cancer treatment because of its low level of adverse effects and noninvasiveness. However, thermotherapy alone still cannot control tumor metastasis and recurrence. Here, we developed surface-functionalized modified copper sulfide nanoparticles (CuS NPs). CuS NPs can not only be used as photothermal mediators for tumor hyperthermia but can adsorb tumor antigens released during hyperthermia as an antigen-capturing agent to induce antitumor immune response. We selected maleimide polyethylene glycol-modified CuS NPs (CuS NPs-PEG-Mal) with stronger antigen adsorption capacity, in combination with an immune checkpoint blocker (anti-PD-L1) to evaluate the effect of hyperthermia, improving immunotherapy in a 4T1 breast cancer tumor model. The results showed that hyperthermia based on CuS NPs-PEG-Mal distinctly increased the levels of inflammatory cytokines in the serum, leading to a tumor immunogenic microenvironment. In cooperation with anti-PD-L1, PTT mediated by CuS NPs-PEG-Mal enhanced the number of tumor-infiltrating CD8+ T cells and inhibited the growth in primary and distant tumor sites of the 4T1 tumor model. The therapeutic strategies provide a simple and effective treatment option for metastatic and recurrent tumors.