Chemical and structural disorder in eumelanins: A possible explanation for broadband absorbance

We report the results of an experimental and theoretical study of the electronic and structural properties of a key eumelanin precursor-5,6,-dihydroxyindole-2-carboxylic acid ( DHICA) - and its dimeric forms. We have used optical spectroscopy to follow the oxidative polymerization of DHICA to eumelanin and observe red shifting and broadening of the absorption spectrum as the reaction proceeds. First principles density functional theory calculations indicate that DHICA oligomers ( possible reaction products of oxidative polymerization) have the gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital red-shifted gaps with respect to the monomer. Furthermore, different bonding configurations ( leading to oligomers with different structures) produce a range of gaps. These experimental and theoretical results lend support to the chemical disorder model where the broadband monotonic absorption characteristic of all melanins is a consequence of the superposition of a large number of nonhomogeneously broadened Gaussian transitions associated with each of the components of a melanin ensemble. These results suggest that the traditional model of eumelanin as an amorphous organic semiconductor is not required to explain its optical properties and should be thoroughly reexamined. These results have significant implications for our understanding of the physics, chemistry, and biological function of these important biological macromolecules. Indeed, one may speculate that the robust functionality of melanins in vitro is a direct consequence of its heterogeneity, i.e., chemical disorder is a "low cost" natural resource in these systems

Dynamic rupture in a 3-D particle-based simulation of a rough planar fault

An appreciation of the physical mechanisms which cause observed seismicity complexity is fundamental to the understanding of the temporal behaviour of faults and single slip events. Numerical simulation of fault slip can provide insights into fault processes by allowing exploration of parameter spaces which influence microscopic and macroscopic physics of processes which may lead towards an answer to those questions. Particle-based models such as the Lattice Solid Model have been used previously for the simulation of stick-slip dynamics of faults, although mainly in two dimensions. Recent increases in the power of computers and the ability to use the power of parallel computer systems have made it possible to extend particle-based fault simulations to three dimensions. In this paper a particle-based numerical model of a rough planar fault embedded between two elastic blocks in three dimensions is presented. A very simple friction law without any rate dependency and no spatial heterogeneity in the intrinsic coefficient of friction is used in the model. To simulate earthquake dynamics the model is sheared in a direction parallel to the fault plane with a constant velocity at the driving edges. Spontaneous slip occurs on the fault when the shear stress is large enough to overcome the frictional forces on the fault. Slip events with a wide range of event sizes are observed. Investigation of the temporal evolution and spatial distribution of slip during each event shows a high degree of variability between the events. In some of the larger events highly complex slip patterns are observed.

Iron (Fe) bioavailability and the distribution of anti-Fe nutrition biochemicals in the unpolished, and bran fraction of five rice gei polished grain riotypes

Iron (Fe) bioavailability in unpolished, polished grain and bran fraction of five rice genotypes with a range of Fe contents was measured by in vitro digestion and cultured Caco-2 cells of cooked grain. There was a significant difference in Fe bioavailability among the five rice genotypes tested, in both the unpolished and polished grain. The range of Fe bioavailability variation in polished rice was much wider than that of unpolished, suggesting the importance of using Fe levels and bioavailability in polished rice grain as the basis for selecting high-Fe rice cultivars for both agronomic and breeding purposes. Milling and polishing the grain to produce polished (or white) rice increased Fe bioavailability in all genotypes. Iron bioavailability in polished rice was high in the UBON2 and Nishiki, intermediate in both IR68144 and KDML105, and low in CMU122. All genotypes had low bioavailability of Fe in bran fraction compared to unpolished and polished grain, except in CMU122. CMU122 contained the lowest level of bioavailable Fe in unpolished and polished grain and bran, because of the dark purple pericarp colored grain and associated tannin content. The level of bioavailable Fe was not significantly correlated with grain Fe concentration or grain phytate levels among these five genotypes tested. The negative relationship between Fe bioavailability and the levels of total extractable phenol was only observed in unpolished (r = -0.83**) and bran fraction (r = -0.50*). The present results suggested that total extractable phenol and tannin contents could also contribute to lowering bioavailability of Fe in rice grain, in addition to phytate. (c) 2006 Society of Chemical Industry

Vehicle routing and crew scheduling for metropolitan mail distribution at Australia Post

This paper presents a new multi-depot combined vehicle and crew scheduling algorithm, and uses it, in conjunction with a heuristic vehicle routing algorithm, to solve the intra-city mail distribution problem faced by Australia Post. First we describe the Australia Post mail distribution problem and outline the heuristic vehicle routing algorithm used to find vehicle routes. We present a new multi-depot combined vehicle and crew scheduling algorithm based on set covering with column generation. The paper concludes with a computational investigation examining the affect of different types of vehicle routing solutions on the vehicle and crew scheduling solution, comparing the different levels of integration possible with the new vehicle and crew scheduling algorithm and comparing the results of sequential versus simultaneous vehicle and crew scheduling, using real life data for Australia Post distribution networks.

Motor unit number estimation - A Bayesian approach

All muscle contractions are dependent on the functioning of motor units. In diseases such as amyotrophic lateral sclerosis (ALS), progressive loss of motor units leads to gradual paralysis. A major difficulty in the search for a treatment for these diseases has been the lack of a reliable measure of disease progression. One possible measure would be an estimate of the number of surviving motor units. Despite over 30 years of motor unit number estimation (MUNE), all proposed methods have been met with practical and theoretical objections. Our aim is to develop a method of MUNE that overcomes these objections. We record the compound muscle action potential (CMAP) from a selected muscle in response to a graded electrical stimulation applied to the nerve. As the stimulus increases, the threshold of each motor unit is exceeded, and the size of the CMAP increases until a maximum response is obtained. However, the threshold potential required to excite an axon is not a precise value but fluctuates over a small range leading to probabilistic activation of motor units in response to a given stimulus. When the threshold ranges of motor units overlap, there may be alternation where the number of motor units that fire in response to the stimulus is variable. This means that increments in the value of the CMAP correspond to the firing of different combinations of motor units. At a fixed stimulus, variability in the CMAP, measured as variance, can be used to conduct MUNE using the "statistical" or the "Poisson" method. However, this method relies on the assumptions that the numbers of motor units that are firing probabilistically have the Poisson distribution and that all single motor unit action potentials (MUAP) have a fixed and identical size. These assumptions are not necessarily correct. We propose to develop a Bayesian statistical methodology to analyze electrophysiological data to provide an estimate of motor unit numbers. Our method of MUNE incorporates the variability of the threshold, the variability between and within single MUAPs, and baseline variability. Our model not only gives the most probable number of motor units but also provides information about both the population of units and individual units. We use Markov chain Monte Carlo to obtain information about the characteristics of individual motor units and about the population of motor units and the Bayesian information criterion for MUNE. We test our method of MUNE on three subjects. Our method provides a reproducible estimate for a patient with stable but severe ALS. In a serial study, we demonstrate a decline in the number of motor unit numbers with a patient with rapidly advancing disease. Finally, with our last patient, we show that our method has the capacity to estimate a larger number of motor units.

Analytical electron microscopy of proton exchange membrane fuel cells

Microtome sections of proton exchange membrane cells produce a wide range of information ranging from macroscopic distribution of components through specimens in which the detailed distribution of catalyst particles can be observed. Using modern data management practices it is possible to combine information at different scales and correlate processing and performance data. Analytical electron microscopy reveals the compositional variations across used cells at the electrolyte/electrode interface. In particular analytical techniques indicate that sulphur concentrations are likely to diminish at the interface Nafion/anode interface. © 2006 Elsevier B.V. All rights reserved.

Quantum Information Processing with spin systems: from modeling to possible implementations

The physical implementation of quantum information processing is one of the major challenges of current research. In the last few years, several theoretical proposals and experimental demonstrations on a small number of qubits have been carried out, but a quantum computing architecture that is straightforwardly scalable, universal, and realizable with state-of-the-art technology is still lacking. In particular, a major ultimate objective is the construction of quantum simulators, yielding massively increased computational power in simulating quantum systems. Here we investigate promising routes towards the actual realization of a quantum computer, based on spin systems. The first one employs molecular nanomagnets with a doublet ground state to encode each qubit and exploits the wide chemical tunability of these systems to obtain the proper topology of inter-qubit interactions. Indeed, recent advances in coordination chemistry allow us to arrange these qubits in chains, with tailored interactions mediated by magnetic linkers. These act as switches of the effective qubit-qubit coupling, thus enabling the implementation of one- and two-qubit gates. Molecular qubits can be controlled either by uniform magnetic pulses, either by local electric fields. We introduce here two different schemes for quantum information processing with either global or local control of the inter-qubit interaction and demonstrate the high performance of these platforms by simulating the system time evolution with state-of-the-art parameters. The second architecture we propose is based on a hybrid spin-photon qubit encoding, which exploits the best characteristic of photons, whose mobility is exploited to efficiently establish long-range entanglement, and spin systems, which ensure long coherence times. The setup consists of spin ensembles coherently coupled to single photons within superconducting coplanar waveguide resonators. The tunability of the resonators frequency is exploited as the only manipulation tool to implement a universal set of quantum gates, by bringing the photons into/out of resonance with the spin transition. The time evolution of the system subject to the pulse sequence used to implement complex quantum algorithms has been simulated by numerically integrating the master equation for the system density matrix, thus including the harmful effects of decoherence. Finally a scheme to overcome the leakage of information due to inhomogeneous broadening of the spin ensemble is pointed out. Both the proposed setups are based on state-of-the-art technological achievements. By extensive numerical experiments we show that their performance is remarkably good, even for the implementation of long sequences of gates used to simulate interesting physical models. Therefore, the here examined systems are really promising buildingblocks of future scalable architectures and can be used for proof-of-principle experiments of quantum information processing and quantum simulation.

The impact of supply chain performance measurement systems on dynamic behaviour in supply chains

The amplification of demand variation up a supply chain widely termed ‘the Bullwhip Effect’ is disruptive, costly and something that supply chain management generally seeks to minimise. Originally attributed to poor system design; deficiencies in policies, organisation structure and delays in material and information flow all lead to sub-optimal reorder point calculation. It has since been attributed to exogenous random factors such as: uncertainties in demand, supply and distribution lead time but these causes are not exclusive as academic and operational studies since have shown that orders and/or inventories can exhibit significant variability even if customer demand and lead time are deterministic. This increase in the range of possible causes of dynamic behaviour indicates that our understanding of the phenomenon is far from complete. One possible, yet previously unexplored, factor that may influence dynamic behaviour in supply chains is the application and operation of supply chain performance measures. Organisations monitoring and responding to their adopted key performance metrics will make operational changes and this action may influence the level of dynamics within the supply chain, possibly degrading the performance of the very system they were intended to measure. In order to explore this a plausible abstraction of the operational responses to the Supply Chain Council’s SCOR® (Supply Chain Operations Reference) model was incorporated into a classic Beer Game distribution representation, using the dynamic discrete event simulation software Simul8. During the simulation the five SCOR Supply Chain Performance Attributes: Reliability, Responsiveness, Flexibility, Cost and Utilisation were continuously monitored and compared to established targets. Operational adjustments to the; reorder point, transportation modes and production capacity (where appropriate) for three independent supply chain roles were made and the degree of dynamic behaviour in the Supply Chain measured, using the ratio of the standard deviation of upstream demand relative to the standard deviation of the downstream demand. Factors employed to build the detailed model include: variable retail demand, order transmission, transportation delays, production delays, capacity constraints demand multipliers and demand averaging periods. Five dimensions of supply chain performance were monitored independently in three autonomous supply chain roles and operational settings adjusted accordingly. Uniqueness of this research stems from the application of the five SCOR performance attributes with modelled operational responses in a dynamic discrete event simulation model. This project makes its primary contribution to knowledge by measuring the impact, on supply chain dynamics, of applying a representative performance measurement system.

Conditional distribution modeling for estimating and exploiting uncertainty in control systems

This paper presents a general methodology for estimating and incorporating uncertainty in the controller and forward models for noisy nonlinear control problems. Conditional distribution modeling in a neural network context is used to estimate uncertainty around the prediction of neural network outputs. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localize the possible control solutions to consider. A nonlinear multivariable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non Gaussian distributions of control signal as well as processes with hysteresis.

Size frequency distribution of prion protein (PrP) aggregates in variant Creutzfeldt-Jakob disease (vCJD)

The frequency distribution of aggregate size of the diffuse and florid-type prion protein (PrP) plaques was studied in various brain regions in cases of variant Creutzfeldt-Jakob disease (vCJD). The size distributions were unimodal and positively skewed and resembled those of β-amyloid (Aβ) deposits in Alzheimer's disease (AD) and Down's syndrome (DS). The frequency distributions of the PrP aggregates were log-normal in shape, but there were deviations from the expected number of plaques in specific size classes. More diffuse plaques were observed in the modal size class and fewer in the larger size classes than expected and more florid plaques were present in the larger size classes compared with the log-normal model. It was concluded that the growth of the PrP aggregates in vCJD does not strictly follow a log-normal model, diffuse plaques growing to within a more restricted size range and florid plaques to larger sizes than predicted. © Springer-Verlag 2005.

Variations of local heat transfer coefficient in piped flow of viscous liquids

Measurements were carried out to determine local coefficients of heat transfer in short lengths of horizontal pipe, and in the region of an discontinuity in pipe diameter. Laminar, transitional and turbulent flow regimes were investigated, and mixtures of propylene glycol and water were used in the experiments to give a range of viscous fluids. Theoretical and empirical analyses were implemented to find how the fundamental mechanism of forced convection was modified by the secondary effects of free convection, temperature dependent viscosity, and viscous dissipation. From experiments with the short tube it was possible to determine simple empirical relationships describing the axial distribution of the local 1usselt number and its dependence on the Reynolds and Prandtl numbers. Small corrections were made to account for the secondary effects mentioned above. Two different entrance configurations were investigated to demonstrate how conditions upstream could influence the heat transfer coefficients measured downstream In experiments with a sudden contraction in pipe diameter the distribution of local 1u3se1t number depended on the Prandtl number of the fluid in a complicated way. Graphical data is presented describing this dependence for a range of fluids indicating how the local Nusselt number varied with the diameter-ratio. Ratios up to 3.34:1 were considered. With a sudden divergence in pipe diameter, it was possible to derive the axial distribution of the local Nusse1t number for a range of Reynolds and Prandtl numbers in a similar way to the convergence experiments. Difficulty was encountered in explaining some of the measurements obtained at low Reynolds numbers, and flow visualization techniques wore used to determine the complex flow patterns which could lead to the anomalous results mentioned. Tests were carried out with divergences up to 1:3.34 to find the way in which the local Nusselt number varied with the diameter ratio, and a few experiments were carried out with very large ratios up .to 14.4. A limited amount of theoretical analysis of the 'divergence' system was carried out to substantiate certain explanations of the heat transfer mechanisms postulated.

Solvable model for distribution networks on random graphs

We propose a simple model that captures the salient properties of distribution networks, and study the possible occurrence of blackouts, i.e., sudden failings of large portions of such networks. The model is defined on a random graph of finite connectivity. The nodes of the graph represent hubs of the network, while the edges of the graph represent the links of the distribution network. Both, the nodes and the edges carry dynamical two state variables representing the functioning or dysfunctional state of the node or link in question. We describe a dynamical process in which the breakdown of a link or node is triggered when the level of maintenance it receives falls below a given threshold. This form of dynamics can lead to situations of catastrophic breakdown, if levels of maintenance are themselves dependent on the functioning of the net, once maintenance levels locally fall below a critical threshold due to fluctuations. We formulate conditions under which such systems can be analyzed in terms of thermodynamic equilibrium techniques, and under these conditions derive a phase diagram characterizing the collective behavior of the system, given its model parameters. The phase diagram is confirmed qualitatively and quantitatively by simulations on explicit realizations of the graph, thus confirming the validity of our approach. © 2007 The American Physical Society.

Size frequency distribution of beta-amyloid (Abeta) deposits in dementia with Lewy bodies

In Alzheimer's disease (AD) and Down's syndrome (DS), the size frequency distribution of the beta-amyloid (Abeta) deposits can be described by a log-normal model and may indictae the growth of the deposits. This study determined the size frequency distribution of the Abeta deposits in the temporal lobe in 8 casaes of dementia with Lewy bodies (DLB) with associated AD pathology (DLB/AD. The size distributions of Abeta deposits were unimodal and positively skewed; the mean size of deposi and the degree of skew varying with deposit type and brain region. Size distributions of the primitive deposits had lower means and were less skewed compared with the diffuse and classic deposits. In addition, size distributions in the hippocampus and parahippocampal gyrus (PHG) had larger means and a greater degree of skew compared with other cortical gyri. All size distributions deviated significantly from a log-normal model. There were more Abeta deposits than expected in the smaller size classes and fewer than expected near the mean and in the larger size classes. The data suggest thatthe pattern of growth of the Abeta deposits in DLB/AD depends both on deposit morphology and brain area. In addition, Abeta deposits in DLB appear to grow to within a more restricted size range than predicted and hence, to have less potential for growth compared with cases of 'pure' AD and DS.

Size distribution curves of senile plaques in patients with Alzheimer’s disease: do plaques grow according to the log-normal model?

The size frequency distributions of diffuse, primitive and cored senile plaques (SP) were studied in single sections of the temporal lobe from 10 patients with Alzheimer’s disease (AD). The size distribution curves were unimodal and positively skewed. The size distribution curve of the diffuse plaques was shifted towards larger plaques while those of the neuritic and cored plaques were shifted towards smaller plaques. The neuritic/diffuse plaque ratio was maximal in the 11 – 30 micron size class and the cored/ diffuse plaque ratio in the 21 – 30 micron size class. The size distribution curves of the three types of plaque deviated significantly from a log-normal distribution. Distributions expressed on a logarithmic scale were ‘leptokurtic’, i.e. with excess of observations near the mean. These results suggest that SP in AD grow to within a more restricted size range than predicted from a log-normal model. In addition, there appear to be differences in the patterns of growth of diffuse, primitive and cored plaques. If neuritic and cored plaques develop from earlier diffuse plaques, then smaller diffuse plaques are more likely to be converted to mature plaques.

Plant ecology of lowland Alnus Glutinosa woodlands:The management implications of species composition, requirements and distribution

Wet woodlands have been recognised as a priority habitat and have featured in the UK BAP since 1994. Although this has been acknowledged in a number of UK policies and guidelines, there is little information relating to their detailed ecology and management. This research, focusing on lowland Alnus glutinosa woodlands, aimed to address this data paucity through the analysis of species requirements and to develop a methodology to guide appropriate management for this habitat for the benefit of wildlife. To achieve these aims data were collected from 64 lowland Alnus glutinosa woodlands and a review of the literature was undertaken to identify species associated with the target habitat. The groundflora species found to be associated with lowland Alnus glutinosa woodland were assessed in relation to their optimal environmental conditions (Ellenberg indicator values) and survival strategies (Grime CSR-Strategy) to determine the characteristics (Characters of a Habitat; CoaHs) and range of intra-site conditions (Niches of a Habitat; NoaH). The methodologies, using CSR and Ellenberg indicator values in combination, were developed to determine NoaHs and were tested both quantitatively and qualitatively at different lowland Alnus glutinosa sites. The existence of CoaHs and NoaHs in actual sites was verified by detailed quadrat data gathered at three Alnus glutinosa woodlands at Stonebridge Meadows, Warwickshire, UK and analysed using TWINSPAN and DCA ordination. The CoaHs and NoaHs and their component species were confirmed to have the potential to occur in a particular woodland. Following a literature search relating to the management of small wet woodlands within the UK, in conjunction with the current research, broad principles and strategies were identified for the management of lowland Alnus glutinosa woodland. Using the groundflora composition, an innovative procedure is developed and described for identifying the potential variation within a particular site and determining its appropriate management. Case studies were undertaken on distinct woodlands and the methodology proved effective.