Point2Vec for Self-Supervised Representation Learning on Point Clouds

Recently, the self-supervised learning framework data2vec has shown inspiring performance for various modalities using a masked student-teacher approach. However, it remains open whether such a framework generalizes to the unique challenges of 3D point clouds. To answer this question, we extend data2vec to the point cloud domain and report encouraging results on several downstream tasks. In an in-depth analysis, we discover that the leakage of positional information reveals the overall object shape to the student even under heavy masking and thus hampers data2vec to learn strong representations for point clouds. We address this 3D-specific shortcoming by proposing point2vec, which unleashes the full potential of data2vec-like pre-training on point clouds. Our experiments show that point2vec outperforms other self-supervised methods on shape classification and few-shot learning on ModelNet40 and ScanObjectNN, while achieving competitive results on part segmentation on ShapeNetParts. These results suggest that the learned representations are strong and transferable, highlighting point2vec as a promising direction for self-supervised learning of point cloud representations

Purification of an alpha amylase from Aspergillus flavus NSH9 and molecular characterization of its nucleotide gene sequence

In this study, an alpha-amylase enzyme from a locally isolated Aspergillus flavus NSH9 was purified and characterized. The extracellular α-amylase was purified by ammonium sulfate precipitation and anion-exchange chromatography at a final yield of 2.55-fold and recovery of 11.73%. The molecular mass of the purified α-amylase was estimated to be 54 kDa using SDS-PAGE and the enzyme exhibited optimal catalytic activity at pH 5.0 and temperature of 50 °C. The enzyme was also thermally stable at 50 °C, with 87% residual activity after 60 min. As a metalloenzymes containing calcium, the purified α-amylase showed significantly increased enzyme activity in the presence of Ca2+ ions. Further gene isolation and characterization shows that the α-amylase gene of A. flavus NSH9 contained eight introns and an open reading frame that encodes for 499 amino acids with the first 21 amino acids presumed to be a signal peptide. Analysis of the deduced peptide sequence showed the presence of three conserved catalytic residues of α-amylase, two Ca2+-binding sites, seven conserved peptide sequences, and several other properties that indicates the protein belongs to glycosyl hydrolase family 13 capable of acting on α-1,4-bonds only. Based on sequence similarity, the deduced peptide sequence of A. flavus NSH9 α-amylase was also found to carry two potential surface/secondary-binding site (SBS) residues (Trp 237 and Tyr 409) that might be playing crucial roles in both the enzyme activity and also the binding of starch granules. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature