Browsing by Author "Liu, Xin"

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    Associations of CXCL1 gene 5’UTR variations with ovarian cancer
    (2020-04-23) Guo, Man; Xu, Chao; Chen, Yan-Zhe; Sun, Qi-Wen; Zhao, Xin-Ying; Liu, Xin; Yang, Yi; Hu, Yi-Yan; Li, Fei-Feng; Liu, Shu-Lin
    Abstract Background There are about 2.4 hundred thousand new cases and 1.5 hundred thousand deaths of ovarian cancer (OC) annually in the world. Chronic inflammation is a risk factor for OC. C-X-C motif chemokine ligand 1 (CXCL1) defects may facilitate inflammation and transactivate EGFR in ovarian cancer, but the precise haplotypes associated with the potential diseases remained largely unknown. In this work, we characterized CXCL1 gene variations to elucidate their possible associations with OC. Methods We analyzed the CXCL1 gene for 300 OC patients with 400 healthy participants as controls. The statistical analyses and Hardy-Weinberg equilibrium tests of the patients and control populations were conducted using the SPSS software (version 19.0) and Plink (version 1.9). Results The variants rs11547681, rs201090116, rs199791199, rs181868085, rs4074 and rs1814092 within or near the CXCL1 gene were characterized. The genetic heterozygosity of rs11547681 and rs4074 was very high. Statistical analysis showed that the variant rs11547681 in the gene was closely associated with the risk of OC in the Chinese Han population, although this variant was not associated with FIGO stages or pathological grades of the patients. Conclusions Rs11547681 in CXCL1 gene was associated with the risk of OC in the Chinese Han population.
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    Efficient Algorithms for Realistic Lens Effect Simulation
    (2014-01-07) Liu, Xin; Rokne, Jon
    Lens effects play an important role in the realism and aesthetics of graphical rendering. Although a wide range of lens effect simulation algorithms have been proposed in computer graphics, we found that realistic lens effect simulation is still very costly in terms of computing time. In this thesis, we have developed efficient algorithms for rendering images with realistic lens effects. We first strived to improve the efficiency of the physically correct distributed ray tracing algorithm by speeding up the fundamental ray-object intersection operations on a GPU. This work brought forth a new acceleration structure built on the top of a uniform grid, called the micro 64-tree, and a new grid traversal algorithm based on the micro 64-tree. The micro 64-tree speeds up the distributed ray tracing by an order of magnitude compared to algorithms based on the uniform grid. However, it does not improve the computational complexity of the distributed ray tracing algorithm, which is proportional to the number of sampling rays per pixel. A main benefit of distributed ray tracing is that it uses correct visibility and thus can render partial occlusions properly. Observing that the visibility of a lens can be mostly covered by a few representative views, we then proposed a new algorithm that synthesizes lens effects from sparse views. The sparse-view based algorithm can produce high quality lens effects close to the result of distributed ray tracing, but at a much higher speed. Realizing the fact that synthesizing realistic lens effects in 2D space is also computationally expensive, we finally proposed a novel lens effect simulation method based on a physical lens, which “calculates” the complicated optics with the instant physical process of lens imaging. Although the algorithm is still not mature partially because of hardware limitations, it is the first attempt in computer graphics that inserts a physical lens into the graphical rendering pipeline. The physical lens based algorithm can synthesize images incorporating various lens effects with a very low computational complexity.
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