Diffusion of helium in non-stoichiometric uranium dioxide

Diffusion coefficients of helium in solid UO_2+x at high temperature and various stoichiometric compositions are evaluated by using molecular dynamics simulations based on a partly-ionic model in conjunction with a polaron ‘Free Hopping Approximation’ proposed earlier. The results are compared with existing experimental and simulation data. A strong dependence of the apparent diffusion activation energy on stoichiometry is found and the mechanisms of He migration in non-stoichiometric solid UO_2+x are discussed.     

Common Molecular Targets of a Quinolone Based Bumped Kinase Inhibitor in Neospora caninum and Danio rerio

Neospora caninum is an apicomplexan parasite closely related to Toxoplasma gondii, and causes abortions, stillbirths and/or fetal malformations in livestock. Target-based drug development has led to the synthesis of calcium-dependent protein kinase 1 inhibitors, collectively named bumped kinase inhibitors (BKIs). Previous studies have shown that several BKIs have excellent efficacy against neosporosis in vitro and in vivo. However, several members of this class of compounds impair fertility in pregnant mouse models and cause embryonic malformation in a zebrafish (Danio rerio) model. Similar to the first-generation antiprotozoal drug quinine, some BKIs have a quinoline core structure. To identify common targets in both organisms, we performed differential affinity chromatography with cell-free extracts from N. caninum tachyzoites and D. rerio embryos using the 5-aminopyrazole-4-carboxamide (AC) compound BKI-1748 and quinine columns coupled to epoxy-activated sepharose followed by mass spectrometry. BKI-binding proteins of interest were identified in eluates from columns coupled to BKI-1748, or in eluates from BKI-1748 as well as quinine columns. In N. caninum, 12 proteins were bound specifically to BKI-1748 alone, and 105 proteins, including NcCDPK1, were bound to both BKI-1748 and quinine. For D. rerio, the corresponding numbers were 13 and 98 binding proteins, respectively. In both organisms, a majority of BKI-1748 binding proteins was involved in RNA binding and modification, in particular, splicing. Moreover, both datasets contained proteins involved in DNA binding or modification and key steps of intermediate metabolism. These results suggest that BKI-1748 interacts with not only specific targets in apicomplexans, such as CDPK1, but also with targets in other eukaryotes, which are involved in common, essential pathways.     

Melting Line Parameters and Thermodynamic Properties of Methane at High Pressures

The location of the melting line in the phase diagram of methane was predicted using two theoretical equations of state: for solid and fluid phases. The equations of state for both phases are constructed in the framework of thermodynamic perturbation theory, considering the octupole–octupole interaction of methane molecules as a perturbation. The results of calculations of the melting line parameters are compared with experimental and computer simulation data.     

Equilibrium, kinetic and sorber design studies on the adsorption of Aniline blue dye by sodium tetraborate-modified Kaolinite clay adsorbent

Raw Kaolinite clay obtained Ubulu-Ukwu, Delta State of Nigeria and its sodium tetraborate (NTB)-modified analogue was used to adsorb Aniline blue dye. Fourier transformed infrared spectra of NTB-modified Kaolinite suggests that modification was effective on the surface of the Kaolinite clay with the strong presence of inner -OH functional group. The modification of Kaolinite clay raised its adsorption capacity from 1666 to 2000 mg/kg. Modeling adsorption data obtained from both unmodified and NTB-modified Kaolinite clay reveals that the adsorption of Aniline blue dye on unmodified Kaolinite clay is on heterogeneous adsorption sites because it followed strongly the Freundlich isotherm equation model while adsorption data from NTB-modified Kaolinite clay followed strongly the Langmuir isotherm equation model which suggest that Aniline blue dye was adsorb homogeneous adsorption sites on the NTB-modified adsorbent surface. There was an observed increase in the amount of Aniline blue adsorbed as initial dye concentration was increased from 10 to 30 mg/L. It was observed that kinetic data obtained generally gave better robust fit to the second-order kinetic model (SOM). The initial sorption rate was found to increased with increasing initial dye concentration (from 10 to 20 mg/L) for data obtained from 909 to 1111 mg kg(-1)min(-1) for unmodified and 3325-5000 mg kg(-1) min(-1) for NTB-modified adsorbents. Thereafter there was a decrease in initial sorption rate with further increase in dye concentration. The linearity of the plots of the pseudo-second-order model with very high-correlation coefficients indicates that chemisorption is involved in the adsorption process. From the design of a single-batch adsorber it is predicted that the NTB-modified Kaolinite clay adsorbent will require 50% less of the adsorbent to treat certain volumes of wastewater containing 30 mg/L of Aniline blue dye when it is compared with the unmodified adsorbent. This will be cost effective in the use of NTB-modified adsorbent for the adsorption of Aniline blue dye from water and wastewater.     

The use of a modified Fedorov exchange algorithm to optimise sampling times for population pharmacokinetic experiments

We propose a new algorithm for optimising sampling times for population pharmacokinetic experiments using D-optimality. The algorithm was used in conjunction with the population Fisher information matrix as implemented in MATLAB (PFIM 1.1 and 1.2) to evaluate population pharmacokinetic designs. The new algorithm based on the classical Fedorov exchange algorithm optimises the determinant of the population Fisher information matrix. The performance of the new algorithm has been compared with other existing algorithms including simplex, simulated annealing and adaptive random search. The new algorithm performed better especially when dealing with complex designs at the expense of longer computing times.     

A Wavelet Neural Network Based Non-linear Model Predictive Controller for a Multi-variable Coupled Tank System

In this paper, a novel real time non-linear model predictive controller(NMPC) for a multi-variable coupled tank system(CTS) is designed. CTSs are highly non-linear and can be found in many industrial process applications. The involvement of multi-input multi-output(MIMO) system makes the design of an effective controller a challenging task. MIMO systems have inherent couplings,interactions in-between the process input-output variables and generally have an complex internal structure. The aim of this paper is to design, simulate, and implement a novel real time constrained NMPC for a multi-variable CTS with the aid of intelligent system techniques. There are two major formidable challenges hindering the success of the implementation of a NMPC strategy in the MIMO case. The first is the difficulty of obtaining a good non-linear model by training a non-convex complex network to avoid being trapped in a local minimum solution. The second is the online real time optimisation(RTO) of the manipulated variable at every sampling time.A novel wavelet neural network(WNN) with high predicting precision and time-frequency localisation characteristic was selected for an MIMO model and a fast stochastic wavelet gradient algorithm was used for initial training of the network. Furthermore, a genetic algorithm was used to obtain the optimised parameters of the WNN as well as the RTO during the NMPC strategy. The proposed strategy performed well in both simulation and real time on an MIMO CTS. The results indicated that WNN provided better trajectory regulation with less mean-squared-error and average control energy compared to an artificial neural network. It is also shown that the WNN is more robust during abnormal operating conditions.     

Synthesis of hierarchical nanoporous HY zeolites from activated kaolin,a central composite design optimization study

In this article, we investigated the optimum formulation towards synthesis of hierarchical nanoporous HY zeolites from acid activate kaolin. A central composite design (CCD) helped to examine the influence of aging (X₁), crystallization (X₂) and NaOH solution to kaolin ratio (X₃) on crystallinity (C%), specific surface area (SSA) and hierarchical factor (HF). From the analysis of variance (ANOVA), we deduced that all the process variables show statistical significance towards obtaining high C% and SSA while only X₃ is statistically significant for optimal HF. The effectiveness of models was further evaluated using margin of error and tolerance interval. The Optimum formulation for this hierarchical nanoporous HY zeolite was 43.60, 64.23 and 6.97 for X₁, X₂, and X₃, respectively. The developed models show that X₃ is the most statistically significant variable because it has the highest coefficient and the lowest p-value in the entire model. These results give instrumental insight into the synthesis of hierarchical nonporous HY zeolite.