Optimized Baxter Model of Protein Solutions: Electrostatics versus Adhesion

A theory is set up of spherical proteins interacting by screened electrostatics and constant adhesion, in which the effective adhesion parameter is optimized by a variational principle for the free energy. An analytical approach to the second virial coefficient is first outlined by balancing the repulsive electrostatics against part of the bare adhesion. A theory similar in spirit is developed at nonzero concentrations by assuming an appropriate Baxter model as the reference state. The first-order term in a functional expansion of the free energy is set equal to zero which determines the effective adhesion as a function of salt and protein concentrations. The resulting theory is shown to have fairly good predictive power for the ionic-strength dependence of both the second virial coefficient and the osmotic pressure or compressibility of lysozyme up to about 0.2 volume fraction.Comment: 40 pages, 9 figure

Collective diffusion coefficient of proteins with hydrodynamic, electrostatic and adhesive interactions

A theory is presented for lambda_C, the coefficient of the first-order correction in the density of the collective diffusion coefficient, for protein spheres interacting by electrostatic and adhesive forces. An extensive numerical analysis of the Stokesian hydrodynamics of two moving spheres is given so as to gauge the precise impact of lubrication forces. An effective stickiness is introduced and a simple formula for lambda_C in terms of this variable is put forward. A precise though more elaborate approximation for lambda_C is also developed. These and numerically exact expressions for lambda_C are compared with experimental data on lysozyme at pH 4.5 and a range of ionic strengths between 0.05 M and 2 M.Comment: 8 pages, 3 figures, 1 tabl

Deep residual learning in CT physics: scatter correction for spectral CT

Recently, spectral CT has been drawing a lot of attention in a variety of clinical applications primarily due to its capability of providing quantitative information about material properties. The quantitative integrity of the reconstructed data depends on the accuracy of the data corrections applied to the measurements. Scatter correction is a particularly sensitive correction in spectral CT as it depends on system effects as well as the object being imaged and any residual scatter is amplified during the non-linear material decomposition. An accurate way of removing scatter is subtracting the scatter estimated by Monte Carlo simulation. However, to get sufficiently good scatter estimates, extremely large numbers of photons is required, which may lead to unexpectedly high computational costs. Other approaches model scatter as a convolution operation using kernels derived using empirical methods. These techniques have been found to be insufficient in spectral CT due to their inability to sufficiently capture object dependence. In this work, we develop a deep residual learning framework to address both issues of computation simplicity and object dependency. A deep convolution neural network is trained to determine the scatter distribution from the projection content in training sets. In test cases of a digital anthropomorphic phantom and real water phantom, we demonstrate that with much lower computing costs, the proposed network provides sufficiently accurate scatter estimation

Application of the Optimized Baxter Model to the hard-core attractive Yukawa system

We perform Monte Carlo simulations on the hard-core attractive Yukawa system to test the Optimized Baxter Model that was introduced in [P.Prinsen and T. Odijk, J. Chem. Phys. 121, p.6525 (2004)] to study a fluid phase of spherical particles interacting through a short-range pair potential. We compare the chemical potentials and pressures from the simulations with analytical predictions from the Optimized Baxter Model. We show that the model is accurate to within 10 percent over a range of volume fractions from 0.1 to 0.4, interaction strengths up to three times the thermal energy and interaction ranges from 6 to 20 % of the particle diameter, and performs even better in most cases. We furthermore establish the consistency of the model by showing that the thermodynamic properties of the Yukawa fluid computed via simulations may be understood on the basis of one similarity variable, the stickiness parameter defined within the Optimized Baxter Model. Finally we show that the Optimized Baxter Model works significantly better than an often used, naive method determining the stickiness parameter by equating the respective second virial coefficients based on the attractive Yukawa and Baxter potentials.Comment: 11 pages, 8 figure

Implications of physical attractiveness on time allocations from salesperson to customer

The purpose of this study was to determine if more attractive females—as compared to less attractive females—received better customer service in terms of time it took the salesperson to interact with the customer. The hypothesis was not supported; in fact, just the opposing outcome occurred. Less attractive females were served more promptly than attractive females. The study was performed in a mid-size city in the Midwest