AIM:To explore the association of single nucleotide polymorphisms(SNPs)in the IL33/IL1RL1 gene region with the susceptibility to Behcet’s disease(BD)in a Chinese Han population.METHODS:A total of eight SNPs in the ca...AIM:To explore the association of single nucleotide polymorphisms(SNPs)in the IL33/IL1RL1 gene region with the susceptibility to Behcet’s disease(BD)in a Chinese Han population.METHODS:A total of eight SNPs in the candidate gene region(rs11792633,rs7025417,rs10975519 and rs1048274 in IL33;rs2310220,rs12712142,rs13424006 and rs3821204 in IL1RL1)were genotyped in783 BD patients and 701 healthy controls by the Sequenom Mass Array i PLEX platform.RESULTS:A statistically significant association was observed between IL1RL1 rs12712142 and BD patients.The frequency of IL1RL1 rs12712142 variant allele A was significantly lower in BD patients than that in controls(OR=0.8,95%CI:0.69-0.94,Pc=0.039);the genotype distribution(Pc=0.043)and additive and dominant genetic model analyses(OR=0.8,95%CI:0.69-0.94,Pc=0.040 and OR=0.72,95%CI:0.58-0.88,Pc=0.011)also indicated a strong association between rs12712142 and BD patients.CONCLUSION:This is the first study to reveal the association between IL1RL1 rs12712142 variant allele A and the decreased risk of BD in the Chinese Han population,indicating a protective role of IL1RL1 in the pathogenesis of BD.展开更多
As-built building information model(BIM) is an urgent need of the architecture, engineering, construction and facilities management(AEC/FM) community. However, its creation procedure is still labor-intensive and far f...As-built building information model(BIM) is an urgent need of the architecture, engineering, construction and facilities management(AEC/FM) community. However, its creation procedure is still labor-intensive and far from maturity. Taking advantage of prevalence of digital cameras and the development of advanced computer vision technology, the paper proposes to reconstruct a building facade and recognize its surface materials from images taken from various points of view. These can serve as initial steps towards automatic generation of as-built BIM. Specifically, 3D point clouds are generated from multiple images using structure from motion method and then segmented into planar components, which are further recognized as different structural components through knowledge based reasoning. Windows are detected through a multilayered complementary strategy by combining detection results from every semantic layer. A novel machine learning based 3D material recognition strategy is presented. Binary classifiers are trained through support vector machines. Material type at a given 3D location is predicted by all its corresponding 2D feature points.Experimental results from three existing buildings validate the proposed system.展开更多
基金the National Natural Science Foundation of China (No.81770917)。
文摘AIM:To explore the association of single nucleotide polymorphisms(SNPs)in the IL33/IL1RL1 gene region with the susceptibility to Behcet’s disease(BD)in a Chinese Han population.METHODS:A total of eight SNPs in the candidate gene region(rs11792633,rs7025417,rs10975519 and rs1048274 in IL33;rs2310220,rs12712142,rs13424006 and rs3821204 in IL1RL1)were genotyped in783 BD patients and 701 healthy controls by the Sequenom Mass Array i PLEX platform.RESULTS:A statistically significant association was observed between IL1RL1 rs12712142 and BD patients.The frequency of IL1RL1 rs12712142 variant allele A was significantly lower in BD patients than that in controls(OR=0.8,95%CI:0.69-0.94,Pc=0.039);the genotype distribution(Pc=0.043)and additive and dominant genetic model analyses(OR=0.8,95%CI:0.69-0.94,Pc=0.040 and OR=0.72,95%CI:0.58-0.88,Pc=0.011)also indicated a strong association between rs12712142 and BD patients.CONCLUSION:This is the first study to reveal the association between IL1RL1 rs12712142 variant allele A and the decreased risk of BD in the Chinese Han population,indicating a protective role of IL1RL1 in the pathogenesis of BD.
基金supported by National Natural Science Foundation of China(No.51208425)Research Foundation of Northwestern Polytechnical University(No.JCY20130127)
文摘As-built building information model(BIM) is an urgent need of the architecture, engineering, construction and facilities management(AEC/FM) community. However, its creation procedure is still labor-intensive and far from maturity. Taking advantage of prevalence of digital cameras and the development of advanced computer vision technology, the paper proposes to reconstruct a building facade and recognize its surface materials from images taken from various points of view. These can serve as initial steps towards automatic generation of as-built BIM. Specifically, 3D point clouds are generated from multiple images using structure from motion method and then segmented into planar components, which are further recognized as different structural components through knowledge based reasoning. Windows are detected through a multilayered complementary strategy by combining detection results from every semantic layer. A novel machine learning based 3D material recognition strategy is presented. Binary classifiers are trained through support vector machines. Material type at a given 3D location is predicted by all its corresponding 2D feature points.Experimental results from three existing buildings validate the proposed system.
