Monte Carlo Simulations of Observation Time-Dependent Self-Diffusion in Porous Media Models

Observation time-dependent self-diffusion coefficients can be used to obtain microstructural information of porous media. This paper presents two different kinds of Monte Carlo simulations of the self diffusion process of fluids like water in porous systems, a lattice-free method and a lattice-based method. The results for simple porous media model geometries agree well with each other and with published analytical as well as semi-analytical equations. The use of these equations, which are important for the interpretation of Pulsed Field Gradient-Nuclear Magnetic Resonance (PFG-NMR) time-dependent diffusion data with respect to properties of porous media, is discussed.     

RADICAL POLYMERIZATION OF METHYL METHACRYLATE WITH DIPHENYL DISELENIDE UNDER THERMAL OR PHOTOIRRADIATIONAL CONDITIONS

Polymerization of methyl methacrylate (MMA) with diphenyl diselenide (DPDSE) in the presence of AIBN at 60°C was investigated. DPDSE was worked as a chain transfer agent (CTA). The chain transfer constant (C_tr) of DPDSE for MMA was estimated to be 1.43. On the other hand, DPDSE was functioned as a photoiniferter for the photopolymerization of MMA. In a limited range of conversion, both the polymer yield and number average of molecular weight ([Mbar]_n) increased with the reaction time, and the [Mbar]_n linearly increased with the yield. The terminal structure of poly(MMA) was investigated by the ⁷⁷Se NMR spectrum based on Methyl α-phenylseleno isobutylate (MSEPI) as model compound of the ω-chain end of poly(MMA). Further, photopolymerization of poly (MMA) containing phenylseleno group at ω-chain end as a polymeric photoiniferter with MMA effectively afforded a poly (MMA) having higher molecular weight.     

Gas storage of simple molecules in boron oxide nanocapsules

The capability of the B₂₀O₃₀ nanocapsule to store H₂, N₂, CO, CO₂, NH₃, CH₄, and Cl₂ molecules on the outer surface and inside of the cage was investigated using Monte Carlo simulations, long‐range and dispersion corrected density functional theory, and Møller–Plesset second‐order perturbation theory. Also, Monte Carlo simulations were employed to investigate the adsorption behavior of larger number of guest molecules inserted into and onto the larger B₈₀O₁₂₀ and B₂₀O₃₀@B₈₀O₁₂₀ cages. Absolute localized molecular orbitals energy decomposition analysis was used to describe the nature of intermolecular interactions in these endohedral and exohedral complexes. It is found that the hydrogen and ammonia gases are diffused to the inside of spherical B₂₀O₃₀ capsule, while other guest molecules prefer to interact with the outer surface of spherical and pyramidal capsules. For B₈₀O₁₂₀, up to 26 H₂ and 11–14 N₂, CO, CO₂, NH₃, and CH₄ molecules are stored inside the capsule. The residual molecules are adsorbed on the outer surface of nanocapsule. © 2013 Wiley Periodicals, Inc.     

Optimizing Age Penalty in Time-Varying Networks with Markovian and Error-Prone Channel State

In this paper, we consider a scenario where the base station (BS) collects time-sensitive data from multiple sensors through time-varying and error-prone channels. We characterize the data freshness at the terminal end through a class of monotone increasing functions related to Age of information (AoI). Our goal is to design an optimal policy to minimize the average age penalty of all sensors in infinite horizon under bandwidth and power constraint. By formulating the scheduling problem into a constrained Markov decision process (CMDP), we reveal the threshold structure for the optimal policy and approximate the optimal decision by solving a truncated linear programming (LP). Finally, a bandwidth-truncated policy is proposed to satisfy both power and bandwidth constraint. Through theoretical analysis and numerical simulations, we prove the proposed policy is asymptotic optimal in the large sensor regime.     

Ultrasound irradiation alters the spatial structure and improves the antioxidant activity of the yellow tea polysaccharide

In this study, the impact of ultrasound irradiation on the structural characteristics and antioxidant properties of yellow tea polysaccharides with different molecular weights (Mw) were investigated. Native yellow tea polysaccharide containing YTPS-3N, YTPS-5N and YTPS-7N were prepared through precipitation with ethanol at various concentrations of 30%, 50%, and 70%, respectively, and irradiated with high intensity ultrasound (20 kHz) for 55 min to yield yellow tea polysaccharide including YTPS-3U, YTPS-5U and YTPS-7U. The molecular weight (Mw) of YTPS-3N (from 37.7 to 15.1 kDa) and YTPS-5N (from 14.6 to 5.2 kDa) sharply decreased upon ultrasound irradiation, coincidentally particle size (Zavg) was also significantly reduced for YTPS-3N (40%), YTPS-5N (48%) and YTPS-7N (54%). The high-performance liquid chromatography and Fourier transform-infrared spectroscopy analysis revealed a partial degradation of native yellow tea polysaccharide treated with ultrasound, though the monosaccharide composition was not altered. Furthermore, changes in morphology and the breakdown of native yellow tea polysaccharide upon irradiation was confirmed with the circular dichroism spectrum, atomic force and scanning electron microscopy. As a consequence, irradiation of yellow tea polysaccharide increased free radical scavenging activity with YTPS-7U exhibiting the highest levels of 2, 2-diphenyl-1-picrylhydrazyl free radical, superoxide and hydroxyl radicals scavenging activity. These results suggest that the alteration of the spatial structure of yellow tea polysaccharide can enhance its antioxidant activity which is an important property for functional foods or medicines.     

Multiple scattering and modeling of laser in fog

When a laser is transmitted in fog, and the water droplets will scatter and absorb the laser, which affects the intensity of the laser transmission and the accuracy of radar detection. Therefore, it is of great significance to study the laser transmission in the fog. At present, the main method of calculating the scattering and attenuation characteristics of fog is based on the radiation transmission theory, which is realized by a large number of numerical calculations or physical simulation methods, which takes time and cannot meet the requirements for obtaining the fast and accurate results. Therefore, in this paper established are a new laser forward attenuation model and backward attenuation model in low visibility fog. It is found that in low visibility environments, the results calculated by the Monte Carlo method are more accurate than those from most of the existing forward attenuation models. For the cases of 0.86-μm, 1.06-μm, 1.315-μm, 10.6-μm typical lasers incident on different fogs with different visibilities, a backscatter model is established, the error between the fitting result and the calculation result is analyzed, the backward attenuation fitting parameters of the new model are tested, and a more accurate fitting result is obtained.     

Magnetic-resonance image segmentation based on improved variable weight multi-resolution Markov random field in undecimated complex wavelet domain

To solve the problem that the magnetic resonance (MR) image has weak boundaries, large amount of information, and low signal-to-noise ratio, we propose an image segmentation method based on the multi-resolution Markov random field (MRMRF) model. The algorithm uses undecimated dual-tree complex wavelet transformation to transform the image into multiple scales. The transformed low-frequency scale histogram is used to improve the initial clustering center of the K-means algorithm, and then other cluster centers are selected according to the maximum distance rule to obtain the coarse-scale segmentation. The results are then segmented by the improved MRMRF model. In order to solve the problem of fuzzy edge segmentation caused by the gray level inhomogeneity of MR image segmentation under the MRMRF model, it is proposed to introduce variable weight parameters in the segmentation process of each scale. Furthermore, the final segmentation results are optimized. We name this algorithm the variable-weight multi-resolution Markov random field (VWMRMRF). The simulation and clinical MR image segmentation verification show that the VWMRMRF algorithm has high segmentation accuracy and robustness, and can accurately and stably achieve low signal-to-noise ratio, weak boundary MR image segmentation.     

Mixing time of an unaligned Gibbs sampler on the square

The paper concerns a particular example of the Gibbs sampler and its mixing efficiency. Coordinates of a point are rerandomized in the unit square ${[0,1]}^2$ to approach a stationary distribution with density proportional to $exp(?A^2{(u?v)}^2)$ for $(u,v)\in {[0,1]}^2$ with some large parameter $A$.Diaconis conjectured the mixing time of this process to be $O\left(A^2\right)$ which we confirm in this paper. This improves on the currently known $O(exp\left(A^2\right))$ estimate.