Publications by authors named "Yao Lian"

The purpose of this study was to obtain dental ceramic materials with excellent mechanical properties and high resistance to low temperature degradation (LTD) via stereolithography (SLA) in combination with microwave sintering (MWS). The results have shown that the unaged MWS-1425 °C 3Y-TZP ceramics with uniform microstructure have high density up to 99.04% and excellent mechanical properties (Vickers hardness 14.

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Fractionation is necessary for self-assembly in multicomponent mixtures. Here, reversible fractionation and crystallization are realized and studied in two-dimensional binary colloids which are supersaturated by enhancing the attraction between colloidal particles. As a deep and fast supersaturation results in gels with a uniform distribution of binary particles, a gradual quasistatic supersaturation process leads to a two-step crystallization in which small particles and large particles are fractionated as coexisting crystal and liquid phases respectively.

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Article Synopsis
  • The study aims to link protein amino acid sequences to their ability to produce an antibody response, while also enhancing a computational method for predicting linear B-cell epitopes (LBE).
  • A deep maxout network (DMN) utilizing dropout training was developed for this prediction, with GPU technology speeding up the training process.
  • The DMN-LBE model demonstrated a 68.33% accuracy and a 0.743 AUC score during a rigorous 10-fold cross-validation, outpacing existing prediction methods, and is now available as a free online tool to aid in vaccine research, antibody production, and disease management.
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Background: B-cell epitopes have been studied extensively due to their immunological applications, such as peptide-based vaccine development, antibody production, and disease diagnosis and therapy. Despite several decades of research, the accurate prediction of linear B-cell epitopes has remained a challenging task.

Results: In this work, based on the antigen's primary sequence information, a novel linear B-cell epitope prediction model was developed using the multiple linear regression (MLR).

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