Molecular sieve silica membranes for H2/CO separation

Efficient separation of fuel gas (H2) from other gases in reformed gas mixtures is becoming increasingly important in the development of alternative energy systems. A highly efficient and new technology available for these separations is molecular sieve silica (MSS) membranes derived from tetraethyl-orthosilicate (TEOS). A permeation model is developed from an analogous electronic system and compared to transport theory to determine permeation, selectivity and apparent activation of energy based on experimental values. Experimental results for high quality membranes show single gas permselectivity peaking at 57 for H2/CO at 150°C with a H2 permeation of 5.14 x 10^-8 mol.m^-2.s^-1.Pa^-1. Higher permeance was also achieved, but at the expense of selectivity. This is the case for low quality membranes with peak H2 permeation at 1.78 x 10-7 mol.m-2.s-1.Pa-1 at 22°C and H2/CO permselectivity of 4.5. High quality membranes are characterised with positive apparent activation energy while the low quality membranes have negative values. The model had a good fit of r-squared of 0.99-1.00 using the experimental data.

Superior electric double layer capacitors using ordered mesoporous carbons

This paper reports for the first time superior electric double layer capacitive properties of ordered mesoporous carbon (OMCs) with varying ordered pore symmetries and mesopore structure. Compared to commercially used activated carbon electrode, Maxsorb, these OMC carbons have superior capacitive behavior, power output and high-frequency performance in EDLCs due to the unique structure of their mesopore network, which is more favorable for fast ionic transport than the pore networks in disordered microporous carbons. As evidenced by N-2 sorption, cyclic voltammetry and frequency response measurements, OMC carbons with large mesopores, and especially with 2-D pore symmetry, show superior capacitive behaviors (exhibiting a high capacitance of over 180 F/g even at very high sweep rate of 50 mV/s, as compared to much reduced capacitance of 73 F/g for Maxsorb at the same sweep rate). OMC carbons can provide much higher power density while still maintaining good energy density. OMC carbons demonstrate excellent high-frequency performances due to its higher surface area in pores larger than 3 nm. Such ordered mesoporous carbons (OMCs) offer a great potential in EDLC capacitors, particularly for applications where high power output and good high-frequency capacitive performances are required. (C) 2005 Elsevier Ltd. All rights reserved.

Long-term metabolic and skeletal muscle adaptations to short-sprint training: Implications for sprint training and tapering

The adaptations of muscle to sprint training can be separated into metabolic and morphological changes. Enzyme adaptations represent a major metabolic adaptation to sprint training, with the enzymes of all three energy systems showing signs of adaptation to training and some evidence of a return to baseline levels with detraining. Myokinase and creatine phosphokinase have shown small increases as a result of short-sprint training in some studies and elite sprinters appear better able to rapidly breakdown phosphocreatine (PCr) than the sub-elite. No changes in these enzyme levels have been reported as a result of detraining. Similarly, glycolytic enzyme activity (notably lactate dehydrogenase, phosphofructokinase and glycogen phosphorylase) has been shown to increase after training consisting of either long (> 10-second) or short (< 10-second) sprints. Evidence suggests that these enzymes return to pre-training levels after somewhere between 7 weeks and 6 months of detraining. Mitochondrial enzyme activity also increases after sprint training, particularly when long sprints or short recovery between short sprints are used as the training stimulus. Morphological adaptations to sprint training include changes in muscle fibre type, sarcoplasmic reticulum, and fibre cross-sectional area. An appropriate sprint training programme could be expected to induce a shift toward type Ha muscle, increase muscle cross-sectional area and increase the sarcoplasmic reticulum volume to aid release of Ca2+. Training volume and/or frequency of sprint training in excess of what is optimal for an individual, however, will induce a shift toward slower muscle contractile characteristics. In contrast, detraining appears to shift the contractile characteristics towards type IIb, although muscle atrophy is also likely to occur. Muscle conduction velocity appears to be a potential non-invasive method of monitoring contractile changes in response to sprint training and detraining. In summary, adaptation to sprint training is clearly dependent on the duration of sprinting, recovery between repetitions, total volume and frequency of training bouts. These variables have profound effects on the metabolic, structural and performance adaptations from a sprint-training programme and these changes take a considerable period of time to return to baseline after a period of detraining. However, the complexity of the interaction between the aforementioned variables and training adaptation combined with individual differences is clearly disruptive to the transfer of knowledge and advice from laboratory to coach to athlete.

Advances in application of climate prediction in agriculture

Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. All rights reserved.

How do practitioners use conceptual modeling in practice?

Much research has been devoted over the years to investigating and advancing the techniques and tools used by analysts when they model. As opposed to what academics, software providers and their resellers promote as should be happening, the aim of this research was to determine whether practitioners still embraced conceptual modeling seriously. In addition, what are the most popular techniques and tools used for conceptual modeling? What are the major purposes for which conceptual modeling is used? The study found that the top six most frequently used modeling techniques and methods were ER diagramming, data flow diagramming, systems flowcharting, workflow modeling, UML, and structured charts. Modeling technique use was found to decrease significantly from smaller to medium-sized organizations, but then to increase significantly in larger organizations (proxying for large, complex projects). Technique use was also found to significantly follow an inverted U-shaped curve, contrary to some prior explanations. Additionally, an important contribution of this study was the identification of the factors that uniquely influence the decision of analysts to continue to use modeling, viz., communication (using diagrams) to/from stakeholders, internal knowledge (lack of) of techniques, user expectations management, understanding models' integration into the business, and tool/software deficiencies. The highest ranked purposes for which modeling was undertaken were database design and management, business process documentation, business process improvement, and software development. (c) 2005 Elsevier B.V. All rights reserved.

Hydrogen from coal: Production and utilisation technologies

Error condition detected Although coal may be viewed as a dirty fuel due to its high greenhouse emissions when combusted, a strong case can be made for coal to be a major world source of clean H-2 energy. Apart from the fact that resources of coal will outlast oil and natural gas by centuries, there is a shift towards developing environmentally benign coal technologies, which can lead to high energy conversion efficiencies and low air pollution emissions as compared to conventional coal fired power generation plant. There are currently several world research and industrial development projects in the areas of Integrated Gasification Combined Cycles (IGCC) and Integrated Gasification Fuel Cell (IGFC) systems. In such systems, there is a need to integrate complex unit operations including gasifiers, gas separation and cleaning units, water gas shift reactors, turbines, heat exchangers, steam generators and fuel cells. IGFC systems tested in the USA, Europe and Japan employing gasifiers (Texaco, Lurgi and Eagle) and fuel cells have resulted in energy conversions at efficiency of 47.5% (HHV) which is much higher than the 30-35% efficiency of conventional coal fired power generation. Solid oxide fuel cells (SOFC) and molten carbonate fuel cells (MCFC) are the front runners in energy production from coal gases. These fuel cells can operate at high temperatures and are robust to gas poisoning impurities. IGCC and IGFC technologies are expensive and currently economically uncompetitive as compared to established and mature power generation technology. However, further efficiency and technology improvements coupled with world pressures on limitation of greenhouse gases and other gaseous pollutants could make IGCC/IGFC technically and economically viable for hydrogen production and utilisation in clean and environmentally benign energy systems. (c) 2005 Elsevier B.V. All rights reserved.

Ontological clarity and comprehension in health data models

Conceptual modeling forms an important part of systems analysis. If this is done incorrectly or incompletely, there can be serious implications for the resultant system, specifically in terms of rework and useability. One approach to improving the conceptual modelling process is to evaluate how well the model represents reality. Emergence of the Bunge-Wand-Weber (BWW) ontological model introduced a platform to classify and compare the grammar of conceptual modelling languages. This work applies the BWW theory to a real world example in the health arena. The general practice computing group data model was developed using the Barker Entity Relationship Modelling technique. We describe an experiment, grounded in ontological theory, which evaluates how well the GPCG data model is understood by domain experts. The results show that with the exception of the use of entities to represent events, the raw model is better understood by domain experts

Analysis of steady-state heat transfer through mid-crustal vertical cracks with upward throughflow in hydrothermal systems

We conduct a theoretical analysis of steady-state heat transfer problems through mid-crustal vertical cracks with upward throughflow in hydrothermal systems. In particular, we derive analytical solutions for both the far field and near field of the system. In order to investigate the contribution of the forced advection to the total temperature of the system, two concepts, namely the critical Peclet number and the critical permeability of the system, have been presented and discussed in this paper. The analytical solution for the far field of the system indicates that if the pore-fluid pressure gradient in the crust is lithostatic, the critical permeability of the system can be used to determine whether or not the contribution of the forced advection to the total temperature of the system is negligible. Otherwise, the critical Peclet number should be used. For a crust of moderate thickness, the critical permeability is of the order of magnitude of 10(-20) m(2), under which heat conduction is the overwhelming mechanism to transfer heat energy, even though the pore-fluid pressure gradient in the crust is lithostatic. Furthermore, the lower bound analytical solution for the near field of the system demonstrates that the permeable vertical cracks in the middle crust can efficiently transfer heat energy from the lower crust to the upper crust of the Earth. Copyright (C) 2002 John Wiley Sons, Ltd.

A comparison of low-storage strategies for spectral analysis in dissipative systems: filter diagonalisation in the Lanczos representation and harmonic inversion of the Chebychev-order-domain autocorrelation function

We compare the performance of two different low-storage filter diagonalisation (LSFD) strategies in the calculation of complex resonance energies of the HO2, radical. The first is carried out within a complex-symmetric Lanczos subspace representation [H. Zhang, S.C. Smith, Phys. Chem. Chem. Phys. 3 (2001) 2281]. The second involves harmonic inversion of a real autocorrelation function obtained via a damped Chebychev recursion [V.A. Mandelshtam, H.S. Taylor, J. Chem. Phys. 107 (1997) 6756]. We find that while the Chebychev approach has the advantage of utilizing real algebra in the time-consuming process of generating the vector recursion, the Lanczos, method (using complex vectors) requires fewer iterations, especially for low-energy part of the spectrum. The overall efficiency in calculating resonances for these two methods is comparable for this challenging system. (C) 2001 Elsevier Science B.V. All rights reserved.

Optimisation of poly-b-hydroxyalkanoate analysis using gas chromatography for enhanced biological phosphorus removal systems

Poly-beta-hydroxyalkanoate (PHA) is a polymer commonly used in carbon and energy storage for many different bacterial cells. Polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs), store PHA anaerobically through metabolism of carbon substrates such as acetate and propionate. Although poly-beta-hydroxybutyrate (PHB)and poly-beta-hydroxyvalerate (PHV) are commonly quantified using a previously developed gas chromatography (GC) method, poly-beta-hydroxy-2-methyl valerate (PH2MV) is seldom quantified despite the fact that it has been shown to be a key PHA fraction produced when PAOs or GAOs metabolise propionate. This paper presents two GC-based methods modified for extraction and quantification of PHB, PHV and PH2MV from enhanced biological phosphorus removal (EBPR) systems. For the extraction Of PHB and PHV from acetate fed PAO and GAO cultures, a 3% sulfuric acid concentration and a 2-20 h digestion time is recommended, while a 10% sulfuric acid solution digested for 20 h is recommended for PHV and PH2MV analysis from propionate fed EBPR systems. (c) 2005 Elsevier B.V. All rights reserved.

Analysis of chaotic instabilities in a rotating body with internal energy dissipation

Melnikov's method is used to analytically predict the onset of chaotic instability in a rotating body with internal energy dissipation. The model has been found to exhibit chaotic instability when a harmonic disturbance torque is applied to the system for a range of forcing amplitude and frequency. Such a model may be considered to be representative of the dynamical behavior of a number of physical systems such as a spinning spacecraft. In spacecraft, disturbance torques may arise under malfunction of the control system, from an unbalanced rotor, from vibrations in appendages or from orbital variations. Chaotic instabilities arising from such disturbances could introduce uncertainties and irregularities into the motion of the multibody system and consequently could have disastrous effects on its intended operation. A comprehensive stability analysis is performed and regions of nonlinear behavior are identified. Subsequently, the closed form analytical solution for the unperturbed system is obtained in order to identify homoclinic orbits. Melnikov's method is then applied on the system once transformed into Hamiltonian form. The resulting analytical criterion for the onset of chaotic instability is obtained in terms of critical system parameters. The sufficient criterion is shown to be a useful predictor of the phenomenon via comparisons with numerical results. Finally, for the purposes of providing a complete, self-contained investigation of this fundamental system, the control of chaotic instability is demonstated using Lyapunov's method.

Algebraic Bethe ansatz method for the exact calculation of energy spectra and form factors: applications to models of Bose-Einstein condensates and metallic nanograins

In this review we demonstrate how the algebraic Bethe ansatz is used for the calculation of the-energy spectra and form factors (operator matrix elements in the basis of Hamiltonian eigenstates) in exactly solvable quantum systems. As examples we apply the theory to several models of current interest in the study of Bose-Einstein condensates, which have been successfully created using ultracold dilute atomic gases. The first model we introduce describes Josephson tunnelling between two coupled Bose-Einstein condensates. It can be used not only for the study of tunnelling between condensates of atomic gases, but for solid state Josephson junctions and coupled Cooper pair boxes. The theory is also applicable to models of atomic-molecular Bose-Einstein condensates, with two examples given and analysed. Additionally, these same two models are relevant to studies in quantum optics; Finally, we discuss the model of Bardeen, Cooper and Schrieffer in this framework, which is appropriate for systems of ultracold fermionic atomic gases, as well as being applicable for the description of superconducting correlations in metallic grains with nanoscale dimensions.; In applying all the above models to. physical situations, the need for an exact analysis of small-scale systems is established due to large quantum fluctuations which render mean-field approaches inaccurate.

XSophe-Sophe-XeprView (R). A computer simulation software suite (v. 1.1.3) for the analysis of continuous wave EPR spectra

The XSophe-Sophe-XeprView((R)) computer simulation software suite enables scientists to easily determine spin Hamiltonian parameters from isotropic, randomly oriented and single crystal continuous wave electron paramagnetic resonance (CW EPR) spectra from radicals and isolated paramagnetic metal ion centers or clusters found in metalloproteins, chemical systems and materials science. XSophe provides an X-windows graphical user interface to the Sophe programme and allows: creation of multiple input files, local and remote execution of Sophe, the display of sophelog (output from Sophe) and input parameters/files. Sophe is a sophisticated computer simulation software programme employing a number of innovative technologies including; the Sydney OPera HousE (SOPHE) partition and interpolation schemes, a field segmentation algorithm, the mosaic misorientation linewidth model, parallelization and spectral optimisation. In conjunction with the SOPHE partition scheme and the field segmentation algorithm, the SOPHE interpolation scheme and the mosaic misorientation linewidth model greatly increase the speed of simulations for most spin systems. Employing brute force matrix diagonalization in the simulation of an EPR spectrum from a high spin Cr(III) complex with the spin Hamiltonian parameters g(e) = 2.00, D = 0.10 cm(-1), E/D = 0.25, A(x) = 120.0, A(y) = 120.0, A(z) = 240.0 x 10(-4) cm(-1) requires a SOPHE grid size of N = 400 (to produce a good signal to noise ratio) and takes 229.47 s. In contrast the use of either the SOPHE interpolation scheme or the mosaic misorientation linewidth model requires a SOPHE grid size of only N = 18 and takes 44.08 and 0.79 s, respectively. Results from Sophe are transferred via the Common Object Request Broker Architecture (CORBA) to XSophe and subsequently to XeprView((R)) where the simulated CW EPR spectra (1D and 2D) can be compared to the experimental spectra. Energy level diagrams, transition roadmaps and transition surfaces aid the interpretation of complicated randomly oriented CW EPR spectra and can be viewed with a web browser and an OpenInventor scene graph viewer.

Analysis and application of an equilibrium model for in vitro bioassay systems with three components: Receptor, hormone and hormone-binding-protein

A simple theoretical framework is presented for bioassay studies using three component in vitro systems. An equilibrium model is used to derive equations useful for predicting changes in biological response after addition of hormone-binding-protein or as a consequence of increased hormone affinity. Sets of possible solutions for receptor occupancy and binding protein occupancy are found for typical values of receptor and binding protein affinity constants. Unique equilibrium solutions are dictated by the initial condition of total hormone concentration. According to the occupancy theory of drug action, increasing the affinity of a hormone for its receptor will result in a proportional increase in biological potency. However, the three component model predicts that the magnitude of increase in biological potency will be a small fraction of the proportional increase in affinity. With typical initial conditions a two-fold increase in hormone affinity for its receptor is predicted to result in only a 33% increase in biological response. Under the same conditions an Ii-fold increase in hormone affinity for receptor would be needed to produce a two-fold increase in biological potency. Some currently used bioassay systems may be unrecognized three component systems and gross errors in biopotency estimates will result if the effect of binding protein is not calculated. An algorithm derived from the three component model is used to predict changes in biological response after addition of binding protein to in vitro systems. The algorithm is tested by application to a published data set from an experimental study in an in vitro system (Lim et al., 1990, Endocrinology 127, 1287-1291). Predicted changes show good agreement (within 8%) with experimental observations. (C) 1998 Academic Press Limited.