Adaptive shape prior for recognition and variational segmentation of degraded historical characters

We propose a variational method for model based segmentation of gray-scale images of highly degraded historical documents. Given a training set of characters (of a certain letter), we construct a small set of shape models that cover most of the training set's shape variance. For each gray-scale image of a respective degraded character, we construct a custom made shape prior using those fragments of the shape models that best fit the character's boundary. Therefore, we are not limited to any particular shape in the shape model set. In addition, we demonstrate the application of our shape prior to degraded character recognition. Experiments show that our method achieves very accurate results both in segmentation of highly degraded characters and both in recognition. When compared with manual segmentation, the average distance between the boundaries of respective segmented characters was 0.8 pixels (the average size of the characters was 70*70 pixels).     

Development and initial testing of an empirical forcefield for simulation of poly(alkylthiophenes)

Conductive polymers from the polythiophene (PT) family have attracted interest in numerous domains, including potential applications in biosensing. Despite this, atomistic simulations of PTs have tended to use general organic force fields without well-tuned PT parameters, and there exists no optimized and well-validated PT force field that is compatible and consistent with existing biomolecular simulation suites. We present here the development of a new PT forcefield following the AMBER approach, using the program ANTECHAMBER and ab initio calculations at the HF/6-31G* level of theory to assign partial charges and parameterize the critical backbone torsion potential. The optimized geometries and force field potentials match well with both empirical data and previous investigators’ calculations. Initial testing of these parameters through a series of replica exchange simulations of two PT derivatives in aqueous and organic implicit solvents demonstrates that the parameters can match empirical expectations within the limits of an implicit solvent model. This new force field forms a framework for modeling of proposed PT-based devices and sensors, and is expected to accelerate device design and eventual deployment.