Automatic Feature Recognition (AFR) is considered as the key connection technique of the integration of Computer Aided Design (CAD) and Computer Aided Process Planning (CAPP). At present, there is a lack of a systematic method to identify and evaluate the local features of 3D CAD models. The process information such as topological structure, shape and size, tolerance and surface roughness should be considered. Therefore, a novel Model Based Definition (MBD) based on 3D CAD model AFR and similarity evaluation are proposed in this paper. A Multi-Dimensional Attributed Adjacency Matrix (MDAAM) based on MBD is established based on the fully consideration of the topological structure, shape and size, surface roughness, tolerance and other process information of the B-rep model. Based on the MDAAM, a two-stage model local feature similarity evaluation method is proposed, which combines the methods of optimal matching and adjacency judgment. First, the faces of source feature and target model are used as independent sets to construct a bipartite graph. Secondly, supplement the vertices in the independent set of source feature to make the number of vertices in two independent sets equal. Thirdly, based on MDAAM data, the weighted complete bipartite graph is constructed with the face similarity between two independent sets as the weight. Fourthly, Kuhn-Munkres algorithm is used to calculate the optimal matching between the faces of source feature and target model. Fifthly, the adjacency between matching faces in target model is judged. Finally, the similarity between matching faces of the two models is calculated, which is used as the similarity evaluation result. The effectiveness of this method is verified by three applications.

Non-obstructive azoospermia (NOA), a severe form of male infertility, is often suspected to be linked to currently undefined genetic abnormalities. To explore the genetic basis of this condition, we successfully sequenced ~650 infertility-related genes in 757 NOA patients and 709 fertile males. We evaluated the contributions of rare variants to the etiology of NOA by identifying individual genes showing nominal associations and testing the genetic burden of a given biological process as a whole. We found a significant excess of rare, non-silent variants in genes that are key epigenetic regulators of spermatogenesis, such as BRWD1, DNMT1, DNMT3B, RNF17, UBR2, USP1 and USP26, in NOA patients (P = 5.5 × 10(-7)), corresponding to a carrier frequency of 22.5% of patients and 13.7% of controls (P = 1.4 × 10(-5)). An accumulation of low-frequency variants was also identified in additional epigenetic genes (BRDT and MTHFR). Our study suggested the potential associations of genetic defects in genes that are epigenetic regulators with spermatogenic failure in human.

The human genome is diploid, and knowledge of the variants on each chromosome is important for the interpretation of genomic information. Here we report the assembly of a haplotype-resolved diploid genome without using a reference genome. Our pipeline relies on fosmid pooling together with whole-genome shotgun strategies, based solely on next-generation sequencing and hierarchical assembly methods. We applied our sequencing method to the genome of an Asian individual and generated a 5.15-Gb assembled genome with a haplotype N50 of 484 kb. Our analysis identified previously undetected indels and 7.49 Mb of novel coding sequences that could not be aligned to the human reference genome, which include at least six predicted genes. This haplotype-resolved genome represents the most complete de novo human genome assembly to date. Application of our approach to identify individual haplotype differences should aid in translating genotypes to phenotypes for the development of personalized medicine.