An Intelligent Identification Approach of Assembly Interface for CAD Models

Kinematic semantics is often an important content of a CAD model(it refers to a single part/solid model in this work)in many applications,but it is usually not the belonging of the model,especially for the one retrieved from a common database.Especially,the effective and automatic method to reconstruct the above information for a CAD model is still rare.To address this issue,this paper proposes a smart approach to identify each assembly interface on every CAD model since the assembly interface is the fundamental but key element of reconstructing kinematic semantics.First,as the geometry of an assembly interface is formed by one or more adjacent faces on each model,a face-attributed adjacency graph integrated with face structure fingerprint is proposed.This can describe each CAD model as well as its assembly interfaces uniformly.After that,aided by the above descriptor,an improved graph attention network is developed based on a new dual-level anti-interference filtering mechanism,which makes it have the great potential to identify all representative kinds of assembly interface faces with high accuracy that have various geometric shapes but consistent kinematic semantics.Moreover,based on the abovementioned graph and face-adjacent relationships,each assembly interface on a model can be identified.Finally,experiments on representative CAD models are implemented to verify the effectiveness and characteristics of the proposed approach.The results show that the average assembly-interface-face-identification accuracy of the proposed approach can reach 91.75%,which is about 2%–5%higher than those of the recent-representative graph neural networks.Besides,compared with the state-of-the-art methods,our approach is more suitable to identify the assembly interfaces(with various shapes)for each individual CAD model that has typical kinematic pairs.

Multi-channel microfluidic chip-mass spectrometry platform for cell analysis

In this review, we highlight the latest development of multi-channel microfluidic chip-mass spectrometry（chip-MS） in cell analysis and metabolite detection. Following a brief introduction about history and development of multi-channel microchip and MS combination, we will elaborate the key issues of constructing chip-MS platform interface. Then exciting progresses made in this field should be reviewed with well exemplified works, including chip-MS technology for cell introduction, pretreatment of cell secretions and cell metabolite analysis. We will also describe the development of integrated total analysis systems proposed by our group. We hope this brief review will inspire interested readers and provide knowledge about chip-MS platform in the bioanalysis field, particularly in cell analysis and metabolite identifying applications.