Improvement of Heterologous Soluble Expression of L-amino Acid Oxidase Using Logistic Regression.

Successful implementation of enzymes in practical application hinges on the development of efficient mass production techniques. However, in a heterologous expression system, the protein is often unable to fold correctly and, thus, forms inclusion bodies, resulting in the loss of its original activity. In this study, we present a new and more accurate model for predicting amino acids associated with an increased L-amino acid oxidase (LAO) solubility.

Tuning the Trade-Off between Ethane/Ethylene Selectivity and Adsorption Capacity within Isoreticular Microporous Metal-Organic Frameworks by Linker Fine-Fluorination.

The pore dimension and surface property directly dictate the transport of guests, endowing diverse gas selective adsorptions to porous materials. It is highly relevant to construct metal-organic frameworks (MOFs) with designable functional groups that can achieve feasible pore regulation to improve their separation performances. However, the role of functionalization in different positions or degrees within framework on the separation of light hydrocarbon has rarely been emphasized.

Hyperbolic Harmonic Mapping for Surface Registration.

Automatic computation of surface correspondence via harmonic map is an active research field in computer vision, computer graphics and computational geometry. It may help document and understand physical and biological phenomena and also has broad applications in biometrics, medical imaging and motion capture industries. Although numerous studies have been devoted to harmonic map research, limited progress has been made to compute a diffeomorphic harmonic map on general topology surfaces with landmark constraints.

Spherical Parameterization Balancing Angle and Area Distortions.

This work presents a novel framework for spherical mesh parameterization. An efficient angle-preserving spherical parameterization algorithm is introduced, which is based on dynamic Yamabe flow and the conformal welding method with solid theoretic foundation. An area-preserving spherical parameterization is also discussed, which is based on discrete optimal mass transport theory.

Optimal mass transport for shape matching and comparison.

Surface based 3D shape analysis plays a fundamental role in computer vision and medical imaging. This work proposes to use optimal mass transport map for shape matching and comparison, focusing on two important applications including surface registration and shape space. The computation of the optimal mass transport map is based on Monge-Brenier theory, in comparison to the conventional method based on Monge-Kantorovich theory, this method significantly improves the efficiency by reducing computational complexity from O(n(2)) to O(n) .

Shape Classification Using Wasserstein Distance for Brain Morphometry Analysis.

Brain morphometry study plays a fundamental role in medical imaging analysis and diagnosis. This work proposes a novel framework for brain cortical surface classification using Wasserstein distance, based on uniformization theory and Riemannian optimal mass transport theory. By Poincare uniformization theorem, all shapes can be conformally deformed to one of the three canonical spaces: the unit sphere, the Euclidean plane or the hyperbolic plane.

Area-preservation mapping using optimal mass transport.

We present a novel area-preservation mapping/flattening method using the optimal mass transport technique, based on the Monge-Brenier theory. Our optimal transport map approach is rigorous and solid in theory, efficient and parallel in computation, yet general for various applications. By comparison with the conventional Monge-Kantorovich approach, our method reduces the number of variables from O(n2) to O(n), and converts the optimal mass transport problem to a convex optimization problem, which can now be efficiently carried out by Newton's method.

Hyperbolic harmonic brain surface registration with curvature-based landmark matching.

Brain Cortical surface registration is required for inter-subject studies of functional and anatomical data. Harmonic mapping has been applied for brain mapping, due to its existence, uniqueness, regularity and numerical stability. In order to improve the registration accuracy, sculcal landmarks are usually used as constraints for brain registration.

Bis[μ-3-(1H-benzimidazol-2-yl)benzoato]dicopper(I).

The dimeric title complex, [Cu(2)(C(14)H(9)N(2)O(2))(2)], resides on a center of symmetry. In the crystal, the mol-ecules are packed via π-π stacking inter-actions alternating between imidazole and benzene rings [mean inter-planar distances = 3.754 (3) and 3.

1-Methyl-3,5-bis-(3-methyl-phen-yl)benzene.

In the title compound, C(21)H(20), the dihedral angles formed by the central benzene ring with the outer benzene rings are 21.43 (6) and 31.70 (4)°.