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641 results on '"Fan, Jiahui"'

5. Organizational Structure of Participatory Planning in Urban Regeneration: Cases from Shanghai, China

Author

Liang, Xinmei, Jia, Yuetong, Fan, Jiahui, Luo, Jiemei, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Lu, Xinzheng, Series Editor, Kang, Thomas, editor, and Lee, Youngjin, editor

Published
2024
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11. Neural BRDFs: Representation and Operations

Author

Fan, Jiahui, Wang, Beibei, Hašan, Miloš, Yang, Jian, and Yan, Ling-Qi

Subjects
Computer Science - Graphics, Computer Science - Computer Vision and Pattern Recognition
Abstract

Bidirectional reflectance distribution functions (BRDFs) are pervasively used in computer graphics to produce realistic physically-based appearance. In recent years, several works explored using neural networks to represent BRDFs, taking advantage of neural networks' high compression rate and their ability to fit highly complex functions. However, once represented, the BRDFs will be fixed and therefore lack flexibility to take part in follow-up operations. In this paper, we present a form of "Neural BRDF algebra", and focus on both representation and operations of BRDFs at the same time. We propose a representation neural network to compress BRDFs into latent vectors, which is able to represent BRDFs accurately. We further propose several operations that can be applied solely in the latent space, such as layering and interpolation. Spatial variation is straightforward to achieve by using textures of latent vectors. Furthermore, our representation can be efficiently evaluated and sampled, providing a competitive solution to more expensive Monte Carlo layering approaches.

Published
2021

12. Position-free Multiple-bounce Computations for Smith Microfacet BSDFs

Author

Wang, Beibei, Jin, Wenhua, Fan, Jiahui, Yang, Jian, Holzschuch, Nicolas, and Yan, Ling-Qi

Subjects
Computer Science - Graphics
Abstract

Bidirectional Scattering Distribution Functions (BSDFs) encode how a material reflects or transmits the incoming light. The most commonly used model is the Microfacet BSDF. It computes material response from the micro-geometry of the surface assuming a single bounce on specular microfacets. The original model ignores multiple bounces on the micro-geometry, resulting in energy loss, especially with large roughness. In this paper, we present a position-free formulation of multiple bounces inside the micro-geometry, which eliminates this energy loss. We use an explicit mathematical definition of path space that describes single and multiple bounces in a uniform way. We then study the behavior of light on the different vertices and segments in path space, leading to an accurate and reciprocal multiple-bounce description of BSDFs. We also present practical, unbiased Monte-Carlo estimators to compute multiple scattering. Our method is less noisy than existing algorithms for computing multiple scattering. It is almost noise-free with a very-low sampling rate, from 2 to 4 samples per pixel.

Published
2021

39. Nuclear miR-320 Mediates Diabetes-Induced Cardiac Dysfunction by Activating Transcription of Fatty Acid Metabolic Genes to Cause Lipotoxicity in the Heart

Author

Li, Huaping, Fan, Jiahui, Zhao, Yanru, Zhang, Xiaorong, Dai, Beibei, Zhan, Jiabing, Yin, Zhongwei, Nie, Xiang, Fu, Xiang-Dong, Chen, Chen, and Wang, Dao Wen

Subjects
Biotechnology, Cardiovascular, Genetics, Heart Disease, Diabetes, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Animals, Cell Nucleus, Cells, Cultured, Diabetes Mellitus, Experimental, Diabetic Cardiomyopathies, Fatty Acids, Humans, Male, Mice, MicroRNAs, Myocytes, Cardiac, Rats, Transcriptional Activation, CD36 antigens, cell nucleus, diabetic cardiomyopathies, fatty acids, microRNAs, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Cardiovascular System & Hematology
Abstract

RATIONALE:Diabetes mellitus is often associated with cardiovascular complications, which is the leading cause of morbidity and mortality among patients with diabetes mellitus, but little is known about the mechanism that connects diabetes mellitus to the development of cardiovascular dysfunction. OBJECTIVE:We aim to elucidate the mechanism underlying hyperglycemia-induced cardiac dysfunction on a well-established db/db mouse model for diabetes mellitus and diabetic complications that lead to heart failure. METHODS AND RESULTS:We first profiled the expression of microRNAs (miRNAs) by microarray and quantitative reverse transcription polymerase chain reaction on db/db mice and identified miR-320 as a key miRNA associated with the disease phenotype. We next established the clinical relevance of this finding by showing the upregulation of the same miRNA in the failing heart of patients with diabetes mellitus. We demonstrated the causal role of miR-320 in inducing diabetic cardiomyopathy, showing that miR-320 overexpression exacerbated while its inhibition improved the cardiac phenotype in db/db mice. Unexpectedly, we found that miR-320 acts as a small activating RNA in the nucleus at the level of transcription. By chromatin immunoprecipitation sequencing and chromatin immunoprecipitation quantitive polymerase chain reaction analysis of Ago2 (argonaute RISC catalytic component 2) and RNA polymerase II in response to miR-320 induction, we identified CD36 (fatty acid translocase) as a key target gene for this miRNA and showed that the induced expression of CD36 is responsible for increased fatty acid uptake, thereby causing lipotoxicity in the heart. CONCLUSIONS:These findings uncover a novel mechanism for diabetes mellitus-triggered cardiac dysfunction, provide an endogenous case for small activating RNA that has been demonstrated to date only with synthetic RNAs in transfected cells, and suggest a potential strategy to develop a miRNA-based therapy to treat diabetes mellitus-associated cardiovascular complications.

Published
2019

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