A Biocompatible Free Radical Nanogenerator with Real‐Time Monitoring Capability for High Performance Sequential Hypoxic Tumor Therapy

2019 ◽  
Vol 29 (39) ◽  
pp. 1903436 ◽  
Author(s):  
Yingpeng Wan ◽  
Guihong Lu ◽  
Jinfeng Zhang ◽  
Ziying Wang ◽  
Xiaozhen Li ◽  
...  
2020 ◽  
Vol 500 (1) ◽  
pp. 388-396
Author(s):  
Tian Z Hu ◽  
Yong Zhang ◽  
Xiang Q Cui ◽  
Qing Y Zhang ◽  
Ye P Li ◽  
...  

ABSTRACT In astronomy, the demand for high-resolution imaging and high-efficiency observation requires telescopes that are maintained at peak performance. To improve telescope performance, it is useful to conduct real-time monitoring of the telescope status and detailed recordings of the operational data of the telescope. In this paper, we provide a method based on machine learning to monitor the telescope performance in real-time. First, we use picture features and the random forest algorithm to select normal pictures captured by the acquisition camera or science camera. Next, we cut out the source image of the picture and use convolutional neural networks to recognize star shapes. Finally, we monitor the telescope performance based on the relationship between the source image shape and telescope performance. Through this method, we achieve high-performance real-time monitoring with the Large Sky Area Multi-Object Fibre Spectroscopic Telescope, including guiding system performance, focal surface defocus, submirror performance, and active optics system performance. The ultimate performance detection accuracy can reach up to 96.7 per cent.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tadej Bregar ◽  
Donglan An ◽  
Somayeh Gharavian ◽  
Marek Burda ◽  
Isidro Durazo-Cardenas ◽  
...  

An amendment to this paper has been published and can be accessed via a link at the top of the paper.


2021 ◽  
Vol 11 (24) ◽  
pp. 11952
Author(s):  
Xu Zhou ◽  
Tao Wen ◽  
Zhiqiang Long

With the success of the commercial operation of the maglev train, the demand for real-time monitoring and high-performance control of the maglev train suspension system is also increasing. Therefore, a framework for performance monitoring and performance optimization of the maglev train suspension system is proposed in this article. This framework consists of four parts: plant, feedback controller, residual generator, and dynamic compensator. Firstly, after the system model is established, the nominal controller is designed to ensure the stability of the system. Secondly, the observer-based residual generator is identified offline based on the input and output data without knowing the accurate model of the system, which avoids the interference of the unmodeled part. Thirdly, the control performance is monitored and evaluated in real time by analyzing the residual and executing the judgment logic. Fourthly, when the control performance of the system is degraded or not satisfactory, the dynamic compensator based on the residual is updated online iteratively to optimize the control performance. Finally, the proposed framework and theory are verified on the single suspension experimental platform and the results show the effectiveness.


Nanoscale ◽  
2018 ◽  
Vol 10 (39) ◽  
pp. 18812-18820 ◽  
Author(s):  
Donghwa Lee ◽  
Jongyoun Kim ◽  
Honggi Kim ◽  
Hyojung Heo ◽  
Kyutae Park ◽  
...  

High-performance transparent pressure sensors have been successfully fabricated using sea-urchin shaped metal nanoparticles and polyurethane microdome arrays for real-time monitoring.


2020 ◽  
Vol 2 (1) ◽  
pp. 57
Author(s):  
Marco César Prado Soares ◽  
Thiago Destri Cabral ◽  
Beatriz Ferreira Mendes ◽  
Vitor Anastacio da Silva ◽  
Elias Basile Tambourgi ◽  
...  

Bioreactors are employed in several industries, such as pharmaceutics, energy, biomedic and food. To ensure the proper operation of these bioreactors, Enzyme-Linked Immunosorbent Assay (ELISA) and High-Performance Liquid Chromatography (HPLC) systems are commonly used. Although ELISA and HPLC provide very precise results, they are incapable of real-time monitoring and present high operational costs. Given this context, in this work, we discuss the technical and economic viability of implementing fiber optics-based monitoring systems in lieu of traditional ELISA and HPLC systems. We selected fed-batch ethanol fermentative systems for our analysis, as the fed-batch mode is not only prevalent in different fermentative industries, but ethanol production represents a major sector of the Brazilian economy, with annual production in excess of 35 billion liters. Then, a simple fiber sensing system for measuring the refractive index of the fermentation broth, capable of real-time monitoring the fermentation process, is proposed and the advantages of the real-time process control are discussed. Afterward, we present the long-term economic gains of implementing such a system. We estimate that, by using readily commercially available components, the typical Brazilian ethanol plants will see a return for their investment in a time as short as 50 days, with a 5-year Internal Rate of Return (IRR) of 742%/year by setting up a fiber-optic monitoring system over HPLC. With the provided list of components, these numbers can be easily adjusted for industries worldwide, providing incredibly attractive economic prospects.


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