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6. NPR: Nocturnal Place Recognition in Streets

Author

Liu, Bingxi, Fu, Yujie, Lu, Feng, Cui, Jinqiang, Wu, Yihong, and Zhang, Hong

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Visual Place Recognition (VPR) is the task of retrieving database images similar to a query photo by comparing it to a large database of known images. In real-world applications, extreme illumination changes caused by query images taken at night pose a significant obstacle that VPR needs to overcome. However, a training set with day-night correspondence for city-scale, street-level VPR does not exist. To address this challenge, we propose a novel pipeline that divides VPR and conquers Nocturnal Place Recognition (NPR). Specifically, we first established a street-level day-night dataset, NightStreet, and used it to train an unpaired image-to-image translation model. Then we used this model to process existing large-scale VPR datasets to generate the VPR-Night datasets and demonstrated how to combine them with two popular VPR pipelines. Finally, we proposed a divide-and-conquer VPR framework and provided explanations at the theoretical, experimental, and application levels. Under our framework, previous methods can significantly improve performance on two public datasets, including the top-ranked method., Comment: 10 pages, 6 figures

Published
2023

11. Monolithic Fabrication of Metal‐Free On‐Paper Self‐Charging Power Systems

Author

Su, Yingchun, primary, Xue, Han, additional, Fu, Yujie, additional, Chen, Shiqian, additional, Li, Zheng, additional, Li, Lengwan, additional, Knoks, Ainars, additional, Bogdanova, Olga, additional, Lesničenoks, Pēteris, additional, Palmbahs, Roberts, additional, Laurila, Mika‐Matti, additional, Mäntysalo, Matti, additional, Hammar, Mattias, additional, Hallén, Anders, additional, Nordell, Nils, additional, and Li, Jiantong, additional

Published
2024
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17. Targeted Delivery of Active Sites by Oxygen Vacancy-Engineered Bimetal Silicate Nanozymes for Intratumoral Aggregation-Potentiated Catalytic Therapy

Author

Liu, Shuang, primary, Sun, Yu, additional, Ye, Jin, additional, Li, Chunsheng, additional, Wang, Qiang, additional, Liu, Mengting, additional, Cui, Yujie, additional, Wang, Chen, additional, Jin, Guanqiao, additional, Fu, Yujie, additional, Xu, Jiating, additional, and Liang, Xinqiang, additional

Published
2024
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22. Energy-endowed kinetic chromatographic columns for rapid uranium extraction from seawater

Author

FU Yujie, YU Tao, and YE Jianhua

Subjects
energy-endowed, pulsed injection, time-controlled splitting, kinetic chromatography, uranium extraction from seawater, Nuclear engineering. Atomic power, TK9001-9401
Abstract

BackgroundWith the continuous development of society and economy, nuclear energy has emerged as a crucial solution to address global energy shortages. However, uranium reserves on land have diminished after nearly half a century of extraction, resulting in irreversible harm to the natural environment. Consequently, seawater uranium extraction has become a more eco-friendly and abundant source of uranium resources, compared to terrestrial uranium mining. And extracting uranium from seawater emerges as a prudent strategy.PurposeThis study aims to use kinetic chromatography to extract uranium from seawater and investigate the separation mechanism.MethodsLeveraging the concepts of dynamic chromatography, a pulsed-injection energy-endowed kinetic chromatography column was developed. The column utilized spherical SiO2 with a diameter of 0.2 mm and a length of 5 m as the filler. After filling, it encompassed approximately 30 600 chromatographic separation units. A peristaltic pump for pulse injection was applied to the kinetic chromatography system, and a switching pulse injection device was equipped to enable time control splitting. Subsequently, a self-developed on-line spectrophotometric detector was utilized to monitor the concentration of target components in the solution in real-time so as to avoid human control errors during multistage separation experiments. Additionally, the behavior of uranyl ions in kinetic chromatography under varying conditions and determine the best separation conditions was investigated by experiments using different mobile phase carriers, pH values, injection flow rates, energy-endowed modes, and energy-endowed series, and various energy-endowed methods, including water bath heating, ultrasonic, and external magnetic fields, were employed to achieve optimal separation conditions. Finally, the separation factor of uranium and sodium ions in actual seawater uranium extraction was calculated to explore the separation mechanism by separate studies of uranium, europium, and sodium ions, as well as an actual seawater uranium extraction.ResultResults of this series of studies demonstrates that the best separation effect is achieved when using hydrochloric acid as the mobile phase carrier in dynamic chromatography, with a pH of 2, a sample flow rate of 4.109 mL·min-1, water bath heating as the energy-endowed mode, a heating temperature of 50 ℃, and a heating series of 4. Under these optimal conditions, the separation factor between uranium and sodium ions can reach 1.185 4 in the separation studies of uranium, europium and sodium ions. In the real seawater uranium extraction study, the separation factor between uranium and sodium ions can reach 1.575. After simulation and calculation, the theoretical separation of uranium and sodium ions in seawater requires a minimum of 20 levels.ConclusionsThe efficient and rapid extraction and separation of uranium from seawater is facilitated in this study using a pulsed-injection energy-endowed kinetic chromatography column. This separation strategy allows for the efficient separation of light and heavy particles without interaction of the mobile and stationary, resulting in a high sample recovery rate and no need for column regeneration. This technique has potential for the separation of other nuclides, making it a versatile tool for nuclear chemistry research.

Published
2024
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39. Turning Silica into Enzymes by Hydrogenation: Simultaneously Achieving Oxygen Vacancy Engineering and Tumor Adaptive Accumulation for NIR‐II‐Potentiated Therapy

Author

Liu, Mengting, primary, Ye, Jin, additional, Liu, Shuang, additional, Xu, Xiuping, additional, Cui, Yujie, additional, Qu, Jiawei, additional, Zhang, Zhiyong, additional, Zhang, Kefen, additional, Niu, Na, additional, Chen, Ligang, additional, Fu, Yujie, additional, and Xu, Jiating, additional

Published
2023
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42. Research on the High Quality Development of Ice and Snow Sports Tourism Industry under the Integration of Sports and Tourism

Author

Gao Ming, Fu Yujie, Zhu Xiaohui, and Fu Jihong

Subjects
dea model, se-sbm model, malmquist index model, body-travel integration, 97p10, Mathematics, QA1-939
Abstract

With the successful bidding for the 2022 Beijing Winter Olympics, the ice and snow sports tourism industry has received extensive attention from society. In this paper, under the background of the integration of sports and tourism, we construct an efficiency assessment system for the ice and snow sports tourism industry and then use the entropy value method and coefficient of variation method to improve the DEA model and construct a combination-weighted SE-SBM model to explore the operational and developmental efficiency value of the ice and snow sports tourism industry. In addition, considering the changes in regional industrial productivity over time, the Malmquist index model is utilized to respond to the dynamic development efficiency of the ice and snow sports tourism industry. Finally, the development efficiency of the ice and snow sports tourism industry is analyzed based on the panel data of some regions in China from 2014-2023, in which the mean value of the development efficiency of Jilin and Heilongjiang reaches 1.22778. Among the influencing factors, the value of weight gained from expanding consumption is 0.5426, which is greater than that of the other three factors. This study proposes that expanding consumption is the key to promoting the development of the ice and snow sports tourism industry.

Published
2024
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43. Scale-Net: Learning to Reduce Scale Differences for Large-Scale Invariant Image Matching

Author

Fu, Yujie and Wu, Yihong

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Most image matching methods perform poorly when encountering large scale changes in images. To solve this problem, firstly, we propose a scale-difference-aware image matching method (SDAIM) that reduces image scale differences before local feature extraction, via resizing both images of an image pair according to an estimated scale ratio. Secondly, in order to accurately estimate the scale ratio, we propose a covisibility-attention-reinforced matching module (CVARM) and then design a novel neural network, termed as Scale-Net, based on CVARM. The proposed CVARM can lay more stress on covisible areas within the image pair and suppress the distraction from those areas visible in only one image. Quantitative and qualitative experiments confirm that the proposed Scale-Net has higher scale ratio estimation accuracy and much better generalization ability compared with all the existing scale ratio estimation methods. Further experiments on image matching and relative pose estimation tasks demonstrate that our SDAIM and Scale-Net are able to greatly boost the performance of representative local features and state-of-the-art local feature matching methods.

Published
2021

50. Supplementary Table 1 from Endogenous Neoantigen-Specific CD8 T Cells Identified in Two Glioblastoma Models Using a Cancer Immunogenomics Approach

Author

Johanns, Tanner M., primary, Ward, Jeffrey P., primary, Miller, Christopher A., primary, Wilson, Courtney, primary, Kobayashi, Dale K., primary, Bender, Diane, primary, Fu, Yujie, primary, Alexandrov, Anton, primary, Mardis, Elaine R., primary, Artyomov, Maxim N., primary, Schreiber, Robert D., primary, and Dunn, Gavin P., primary

Published
2023
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