Learned Smartphone ISP on Mobile GPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report

The role of mobile cameras increased dramatically over the past few years, leading to more and more research in automatic image quality enhancement and RAW photo processing. In this Mobile AI challenge, the target was to develop an efficient end-to-end AI-based image signal processing (ISP) pipeline replacing the standard mobile ISPs that can run on modern smartphone GPUs using TensorFlow Lite. The participants were provided with a large-scale Fujifilm UltraISP dataset consisting of thousands of paired photos captured with a normal mobile camera sensor and a professional 102MP medium-format FujiFilm GFX100 camera. The runtime of the resulting models was evaluated on the Snapdragon's 8 Gen 1 GPU that provides excellent acceleration results for the majority of common deep learning ops. The proposed solutions are compatible with all recent mobile GPUs, being able to process Full HD photos in less than 20-50 milliseconds while achieving high fidelity results. A detailed description of all models developed in this challenge is provided in this paper

An Image-Based Double-Smoothing Cohesive Finite Element Framework for Particle-Reinforced Materials

In order to simulate the fracture process of particle-reinforced materials on the micro-scale, an image-based double-smoothing cohesive finite element framework is proposed in the present paper. Two separate smoothing processes are performed to reduce the noise in the digital image and eliminate the jagged elements in the finite element mesh. The main contribution of the present study is the proposed novel image-based cohesive finite element framework, and this method improved the quality of the meshes effectively. Meanwhile, the artificial resistance due to the jagged element is reduced with the double-smoothing cohesive finite element framework during the crack propagation. Therefore, the image-based double-smoothing cohesive finite element framework is significant for the simulation of fracture mechanics

Investigation on Analysis Method of Environmental Fatigue Correction Factor of Primary Coolant Metal Materials in LWR Water Environment

The environmental fatigue correction factor (Fen) is mainly used to analyze the influence of the coolant environment on the fatigue life of primary metal materials. Because the calculation of the transformed strain rate is related to the stress history of the component structure, how to determine the strain rate is the most critical step in calculating the Fen. The approaches of the detailed method were given by the Electric Power Research Institute (EPRI) guidelines and RCC-M-2017 Edition Section VI- RPP No. 3 separately, so a gap analysis was performed between the two methods. Furthermore, another average method was also proposed to determine the average strain rate and strain range. Based on the analysis benchmark provided in the EPRI guideline, a simple case study was performed to account for the effect on the fatigue life in applications with different strain rate approaches and different Fen expressions. Finally, two industry case studies were also completed, including on materials of low alloy steel, austenitic stainless steel, and nickel-base alloy. We suggest adopting a more accurate detailed method, and its methodology is recommended to provide more reasonable solutions

Long Noncoding RNA RGMB-AS1 Indicates a Poor Prognosis and Modulates Cell Proliferation, Migration and Invasion in Lung Adenocarcinoma.

Lung cancer is the most common cause of cancer-related mortality worldwide. It is a complex disease involving multiple genetic and epigenetic alterations. The development of transcriptomics revealed the important role of long non-coding RNAs (lncRNAs) in lung cancer occurrence and development. Here, microarray analysis of lung adenocarcinoma tissues showed the abnormal expression of lncRNA RGMB-AS1. However, the role of lncRNA RGMB-AS1 in lung adenocarcinoma remains largely unknown. We showed that upregulation of lncRNA RGMB-AS1 was significantly correlated with differentiation, TNM stage, and lymph node metastasis. In lung adenocarcinoma cells, downregulation of lncRNA RGMB-AS1 inhibited cell proliferation, migration, invasion, and caused cell cycle arrest at the G1/G0 phase. In vivo experiments showed that lncRNA RGMB-AS1 downregulation significantly suppressed the growth of lung adenocarcinoma. The expression of lncRNA RGMB-AS1 was inversely correlated with that of repulsive guidance molecule b (RGMB) in lung adenocarcinoma tissues, and UCSC analysis and fluorescence detection assay indicated that lncRNA RGMB-AS1 may be involved in the development of human lung adenocarcinoma by regulating RGMB expression though exon2 of RGMB. In summary, our findings indicate that lncRNA RGMB-AS1 may play an important role in lung adenocarcinoma and may serve as a potential therapeutic target

Biological effect of lncRGMB-AS1 downregulation on cell cycle progression in A549 and SPC-A-1 cells.

<p>(A and B) Flow cytometric analysis showed a marked increase in the percentage of cells in the G0/G1 phase and a reduction in the percentage of cells in the S phase in the si-lncRNA group in A549 cells (<i>P</i><0.05), without significant changes in the NC and Blank groups (<i>P</i> > 0.05). (C and D) Flow cytometric analysis of SPC-A-1 cells showed a marked increase in the percentage of G0/G1 phase cells and a decrease the percentage of S phase cells in the si-lncRNA group (<i>P</i><0.05), without significant changes in the NC and Blank groups (<i>P</i> > 0.05). si-lncRNA: cells that were transfected with siRNA of lncRNA RGMB-AS1; NC: cells that were transfected with negative control oligonucleotides, and Blank: cells that were not transfected.</p

Biological effect of lncRGMB-AS1 downregulation on cell proliferation in lung adenocarcinoma in vivo.

<p>(A, C) In mice injected with A549 cells, the luciferase signal was lower in the si-RNA nude mice than in the control groups at 2, 3, and 4 weeks, and the signal intensity became even lower in the si-RNA group with time (<i>P</i> < 0.05). (B, D) In mice injected with SPC-A-1 cells, the luciferase signal was lower in the si-RNA nude mice than in the control groups at 2, 3, and 4 weeks, and the signal intensity also became lower in the si-RNA group with time (<i>P</i> < 0.05). (E, F) Western blot analysis of Ki67 and RGMB expression in xenograft tissues from the three groups of nude mice. Compared with the control groups, Ki67 was downregulated and RGMB was upregulated in the si-RNA group (<i>P</i> < 0.05). si-lncRNA: cells that were transfected with siRNA of lncRNA RGMB-AS1; NC: cells that were transfected with negative control oligonucleotides, and Blank: cells that were not transfected. *Indicated statistical significance (<i>P</i> < 0.05).</p

Potential mechanism of lncRGMB-AS1 in lung adenocarcinoma.

<p>(A) Exon1 and Exon2 of RGMB were amplified from human genomic DNA and inserted into the pEGFP-N3 vector with Hind III and BamHI to construct the recombination plasmids pEGFP-N3-Exon1 and pEGFP-N3-Exon2, respectively. The third exon of lncRNA RGMB-AS1 was also amplified from human genomic DNA and inserted into the pSilencer 3.1 vector with BamHI and Hind III to construct the recombination plasmid pSilencer-RGMB-AS1. (B) The fluorescence intensity of cells co-transfected with pEGFP-N3-Exon1 and pSilencer-RGMB-AS1 did not differ from that of cells transfected with pEGFP-N3-Exon1 only or cells co-transfected with pEGFP-N3-Exon1 and pSilencer 3.1 (<i>P</i> > 0.05). (C) The fluorescence intensity of cells co-transfected with pEGFP-N3-Exon2 and pSilencer-RGMB-AS1 was weaker than that of cells transfected with pEGFP-N3-Exon2 only or cells co-transfected with pEGFP-N3-Exon2 and pSilencer 3.1 (<i>P</i> < 0.05). The fluorescence intensity of the pEGFP-N3-Exon1 group was used as a control. *Indicates statistical significance (<i>P</i> < 0.05).</p