Testing predictions of macroscopic binary diffusion coefficients using lattice models with site heterogeneity

Quantitatively predicting mass transport rates for chemical mixtures in porous materials is important in applications of materials such as adsorbents, membranes, and catalysts. Because directly assessing mixture transport experimentally is challenging, theoretical models that can predict mixture diffusion coefficients using Only single-component information would have many uses. One such model was proposed by Skoulidas, Sholl, and Krishna (Langmuir, 2003, 19, 7977), and applications of this model to a variety of chemical mixtures in nanoporous materials have yielded promising results. In this paper, the accuracy of this model for predicting mixture diffusion coefficients in materials that exhibit a heterogeneous distribution of local binding energies is examined. To examine this issue, single-component and binary mixture diffusion coefficients are computed using kinetic Monte Carlo for a two-dimensional lattice model over a wide range of lattice occupancies and compositions. The approach suggested by Skoulidas, Sholl, and Krishna is found to be accurate in situations where the spatial distribution of binding site energies is relatively homogeneous, but is considerably less accurate for strongly heterogeneous energy distributions.

The economics of inclusion body processing

Many recombinant proteins are often over-expressed in host cells, such as Escherichia coli, and are found as insoluble and inactive protein aggregates known as inclusion bodies (IBs). Recently, a novel process for IB extraction and solubilisation, based on chemical extraction, has been reported. While this method has the potential to radically intensify traditional IB processing, the process economics of the new technique have yet to be reported. This study focuses on the evaluation of process economics for several IB processing schemes based on chemical extraction and/or traditional techniques. Simulations and economic analysis were conducted at various processing conditions using granulocyte macrophage-colony stimulating factor, expressed as IBs in E. coli, as a model protein. In most cases, IB processing schemes based on chemical extraction having a shorter downstream cascade demonstrated a competitive economic edge over the conventional route, validating the new process as an economically more viable alternative for IB processing.

The effect of St John's wort extracts on CYP3A: a systematic review of prospective clinical trials

Aim The aim of this systematic review was to assess the quality and outcomes of clinical trials investigating the effect of St John's wort extracts on the metabolism of drugs by CYP3A. Methods Prospective clinical trials assessing the effect of St John's wort (SJW) extracts on metabolism by CYP3A were identified through computer-based searches (from their inception to May 2005) of Medline, Cinahl, PsycINFO, AMED, Current Contents and Embase, hand-searches of bibliographies of relevant papers and consultation with manufacturers and researchers in the field. Two reviewers selected trials for inclusion, independently extracted data and recorded details on study design. Results Thirty-one studies met the eligibility criteria. More than two-thirds of the studies employed a before-and-after design, less than one-third of the studies used a crossover design, and only three studies were double-blind and placebo controlled. In 12 studies the SJW extract had been assayed, and 14 studies stated the specific SJW extract used. Results from 26 studies, including all of the 19 studies that used high-dose hyperforin extracts (> 10 mg day(-1)), had outcomes consistent with CYP3A induction. The three studies using low-dose hyperforin extracts (< 4 mg day(-1)) demonstrated no significant effect on CYP3A. Conclusion There is reasonable evidence to suggest that high-dose hyperforin SJW extracts induce CYP3A. More studies are required to determine whether decreased CYP3A induction occurs after low-dose hyperforin extracts. Future studies should adopt study designs with a control phase or control group, identify the specific SJW extract employed and provide quantitative analyses of key constituents.

The inhibitory effects of free nitrous acid on the energy generation and growth processes of an enriched Nitrobacter culture

The inhibitory effects of nitrite (NO2-)/free nitrous acid (HNO2-FNA) on the metabolism of Nitrobacter were investigated using a method allowing the decoupling of the growth and energy generation processes. A lab-scale sequencing batch reactor was operated for the enrichment of a Nitrobacter culture. Fluorescent in situ hybridization (FISH) analysis showed that 73% of the bacterial population was Nitrobacter. Batch tests were carried out to assess the oxygen and nitrite consumption rates of the enriched culture at low and high nitrite levels, in the presence or absence of inorganic carbon. It was observed that in the absence of CO2, the Nitrobacter culture was able to oxidize nitrite at a rate that is 76% of that in the presence of CO2, with an oxygen consumption rate that is 85% of that measured in the presence of CO2. This enabled the impacts of nitrite/FNA on the catabolic and anabolic processes of Nitrobacter to be assessed separately. FNA rather than nitrite was likely the actual inhibitor to the Nitrobacter metabolism. It was revealed that FNA of up to 0.05 mg HNO2-N center dot L-1 (3.4 mu M), which was the highest FNA concentration used in this study, did not have any inhibitory effect on the catabolic processes of Nitrobacter. However, FNA initiated its inhibition to the anabolic processes of Nitrobacter at approximately 0.011 mg HNO2-N center dot L-1 (0.8 mu M), and completely stopped biomass synthesis at a concentration of approximately 0.023 mg HNO2-N center dot L-1 (1.6 mu M). The inhibitory effect could be described by an empirical inhibitory model proposed in this paper, but the underlying mechanisms remain to be revealed.

Tracking the states of a nonlinear and nonstationary system in the weight-space of artificial neural networks

We propose a novel interpretation and usage of Neural Network (NN) in modeling physiological signals, which are allowed to be nonlinear and/or nonstationary. The method consists of training a NN for the k-step prediction of a physiological signal, and then examining the connection-weight-space (CWS) of the NN to extract information about the signal generator mechanism. We de. ne a novel feature, Normalized Vector Separation (gamma(ij)), to measure the separation of two arbitrary states i and j in the CWS and use it to track the state changes of the generating system. The performance of the method is examined via synthetic signals and clinical EEG. Synthetic data indicates that gamma(ij) can track the system down to a SNR of 3.5 dB. Clinical data obtained from three patients undergoing carotid endarterectomy of the brain showed that EEG could be modeled (within a root-means-squared-error of 0.01) by the proposed method, and the blood perfusion state of the brain could be monitored via gamma(ij), with small NNs having no more than 21 connection weight altogether.

Transient temperature rise in a mouse due to low-frequency regional hyperthermia

A refined nonlinear heat transfer model of a mouse has been developed to simulate the transient temperature rise in a neoplastic tumour and neighbouring tissue during regional hyperthermia using a 150 kHz inductive coil. In this study, we incorporate various bio-energetic enhancements to the heat transfer equation and numerical validations based on experimental findings for the mouse, in terms of nonlinear metabolic heat production, homeothermy, blood perfusion parameters, thermoregulation, psychological and physiological effects. The discretized bio-heat transfer equation has been validated with the commercial software FEMLAB on a canonical multi-sphere object before applying the scheme to the inhomogeneous mouse voxel phantom. The time-dependent numerical results of regional hyperthermia of mouse thigh have been compared with the available experimental temperature results with only a few small disparities. During the first 20 min of local unfocused heating, the temperature in the tumour and the surrounding tissue increased by around 7.5 degrees C. The objective of this preliminary study was to develop a validated electrothermal numerical scheme for inductive hyperthermia of a small mammal with the intention of expanding the model into a complete numerical solution involving ferromagnetic nanoparticles for targeted heating of tumours at low frequencies. In addition, the numerical scheme herein could assist in optimizing and tailoring of focused electromagnetic fields for hyperthermia.

Transport of simple fluids in nanopores: Theory and simulation

A theory is discussed of single-component transport in nanopores, recently developed by Bhatia and coworkers. The theory considers the oscillatory motion of molecules between diffuse wall collisions, arising from the fluid-wall interaction, along with superimposed viscous flow due to fluid-fluid interaction. The theory is tested against molecular dynamics simulations for hydrogen, methane, and carbon tetrafluoride flow in cylindrical nanopores in silica. Although exact at low densities, the theory performs well even at high densities, with the density dependency of the transport coefficient arising from viscous effects. Such viscous effects are reduced at high densities because of the large increase in viscosity, which explains the maximum in the transport coefficient with increase in density. Further, it is seen that in narrow pore sizes of less than two molecular diameters, where a complete monolayer cannot form on the surface, the mutual interference of molecules on opposite sides of the cross section can reduce the transport coefficient, and lead to a maximum in the transport coefficient with increasing density. The theory is also tested for the case of partially diffuse reflection and shows the viscous contribution to be negligible when the reflection is nearly specular. (c) 2005 American Institute of Chemical Engineers AIChE J, 52: 29-38, 2006.

Using machine vision classification to control access of animals to water

Invasive vertebrate pests together with overabundant native species cause significant economic and environmental damage in the Australian rangelands. Access to artificial watering points, created for the pastoral industry, has been a major factor in the spread and survival of these pests. Existing methods of controlling watering points are mechanical and cannot discriminate between target species. This paper describes an intelligent system of controlling watering points based on machine vision technology. Initial test results clearly demonstrate proof of concept for machine vision in this application. These initial experiments were carried out as part of a 3-year project using machine vision software to manage all large vertebrates in the Australian rangelands. Concurrent work is testing the use of automated gates and innovative laneway and enclosure design. The system will have application in any habitat throughout the world where a resource is limited and can be enclosed for the management of livestock or wildlife.

Verifying data refinements using a model checker

In this paper, we consider how refinements between state-based specifications (e.g., written in Z) can be checked by use of a model checker. Specifically, we are interested in the verification of downward and upward simulations which are the standard approach to verifying refinements in state-based notations. We show how downward and upward simulations can be checked using existing temporal logic model checkers. In particular, we show how the branching time temporal logic CTL can be used to encode the standard simulation conditions. We do this for both a blocking, or guarded, interpretation of operations (often used when specifying reactive systems) as well as the more common non-blocking interpretation of operations used in many state-based specification languages (for modelling sequential systems). The approach is general enough to use with any state-based specification language, and we illustrate how refinements between Z specifications can be checked using the SAL CTL model checker using a small example.

Yield criterion of porous materials subjected to complex stress states

Finite-element simulations are used to obtain many thousands of yield points for porous materials with arbitrary void-volume fractions with spherical voids arranged in simple cubic, body-centred cubic and face-centred cubic three-dimensional arrays. Multi-axial stress states are explored. We show that the data may be fitted by a yield function which is similar to the Gurson-Tvergaard-Needleman (GTN) form, but which also depends on the determinant of the stress tensor, and all additional parameters may be expressed in terms of standard GTN-like parameters. The dependence of these parameters on the void-volume fraction is found. (c) 2006 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Yield functions for porous materials with cubic symmetry using different definitions of yield

Plastic yield criteria for porous ductile materials are explored numerically using the finite-element technique. The cases of spherical voids arranged in simple cubic, body-centred cubic and face-centred cubic arrays are investigated with void volume fractions ranging from 2 % through to the percolation limit (over 90 %). Arbitrary triaxial macroscopic stress states and two definitions of yield are explored. The numerical data demonstrates that the yield criteria depend linearly on the determinant of the macroscopic stress tensor for the case of simple-cubic and body-centred cubic arrays - in contrast to the famous Gurson-Tvergaard-Needleman (GTN) formula - while there is no such dependence for face-centred cubic arrays within the accuracy of the finite-element discretisation. The data are well fit by a simple extension of the GTN formula which is valid for all void volume fractions, with yield-function convexity constraining the form of the extension in terms of parameters in the original formula. Simple cubic structures are more resistant to shear, while body-centred and face-centred structures are more resistant to hydrostatic pressure. The two yield surfaces corresponding to the two definitions of yield are not related by a simple scaling.

A flaw in the use of minimal defining sets for secret sharing schemes

It is shown that in some cases it is possible to reconstruct a block design D uniquely from incomplete knowledge of a minimal defining set for D. This surprising result has implications for the use of minimal defining sets in secret sharing schemes.

Effects of graphene layer size on the adsorption of fluids on graphitized thermal carbon black. A computer simulation study

The adsorption of Lennard-Jones fluids (argon and nitrogen) onto a graphitized thermal carbon black surface was studied with a Grand Canonical Monte Carlo Simulation (GCMC). The surface was assumed to be finite in length and composed of three graphene layers. When the GCMC simulation was used to describe adsorption on a graphite surface, an over-prediction of the isotherm was consistently observed in the pressure regions where the first and second layers are formed. To remove this over-prediction, surface mediation was accounted for to reduce the fluid-fluid interaction. Do and co-workers have introduced the so-called surface-mediation damping factor to correct the over-prediction for the case of a graphite surface of infinite extent, and this approach has yielded a good description of the adsorption isotherm. In this paper, the effects of the finite size of the graphene layer on the adsorption isotherm and how these would affect the extent of the surface mediation were studied. It was found that this finite-surface model provides a better description of the experimental data for graphitized thermal carbon black of high surface area (i.e. small crystallite size) while the infinite- surface model describes data for carbon black of very low surface area (i.e. large crystallite size).

Electrostatically mediated specific adsorption of small molecules in metallo-organic frameworks

We investigate the interaction of ethylene and ethane with a Cu-tricarboxylate complex and show that at low loadings the lighter molecule has a higher binding energy as a result of an increased interaction with the framework Cu and stronger hydrogen bonding with the basic framework oxygens. This leads to selective adsorption of ethylene by a factor of about 2 at low pressure, which is overcome by the stronger van der Waals interaction of ethane at high loadings, explaining recent literature data. The results suggest the possibility of separation of light hydrocarbons at low pressures or in trace amounts.