Vibrational dynamics and structure of natural feldspars

The present study gives a contribution to the knowledge on the Na-feldspar and plagioclases, extending the database of the Raman spectra of plagioclases with different chemical compositions and structural orders. This information may be used for the future planetary explorations by “rovers”, for the investigation of ceramics nanocrystal materials and for the mineralogical phase identification in sediments. Na-feldspar and plagioclase solid solution have been investigated by Raman spectroscopy in order to determine the relationships between the vibrational changes and the plagioclase crystal chemistry and structure. We focused on the Raman micro-spectroscopy technique, being a non-destructive method, suited for contactless analysis with high spatial resolution. Chemical and structural analyses have been performed on natural samples to test the usefulness of Raman spectroscopy as a tool in the study of the pressure-induced structural deformations, the disordering processes due to change in the Al-Si distribution in the tetrahedral sites and, finally, in the determination of the anorthitic content (Anx) in plagioclase minerals. All the predicted 39 Ag Raman active modes have been identified and assigned to specific patterns of atomic vibrational motion. A detailed comparison between experimental and computed Raman spectra has been performed and previous assignments have been revised, solving some discrepancies reported in recent literature. The ab initio calculation at the hybrid HF/DFT level with the WC1LYP Hamiltonian has proven to give excellent agreement between calculated and experimentally measured Raman wavenumbers and intensities in triclinic minerals. A short digression on the 36 infrared active modes of Na-feldspar has been done too. The identification of all 39 computed Raman modes in the experimentally measured spectra of the fully ordered Na-feldspar, known as low albite, along with the detailed description of each vibrational mode, has been essential to extend the comparative analysis to the high pressure and high temperature structural forms of albite, which reflect the physical–chemical conditions of the hosting rocks. The understanding of feldspar structure response to pressure and temperature is crucial in order to constrain crustal behaviour. The compressional behaviour of the Na-feldspar has been investigated for the first time by Raman spectroscopy. The absence of phase transitions and the occurrence of two secondary compression mechanisms acting at different pressures have been confirmed. Moreover, Raman data suggest that the internal structural changes are confined to a small pressure interval, localized around 6 GPa, not spread out from 4 to 8 GPa as suggested by previous X-rays studies on elasticity. The dominant compression mechanisms act via tetrahedral tilting, while the T-O bond lengths remain nearly constant at moderate compressional regimes. At the spectroscopic level, this leads to the strong pressure dependencies of T-O-T bending modes, as found for the four modes at 478, 508, 578 and 815 cm-1. The Al-Si distribution in the tetrahedral sites affects also the Raman spectrum of Na-feldspar. In particular, peak broadening is more sensitive than peak position to changes in the degree of order. Raman spectroscopy is found to be a good probe for local ordering, in particular being sensitive to the first annealing steps, when the macroscopic order parameter is still high. Even though Raman data are scattered and there are outliers in the estimated values of the degree of order, the average peak linewidths of the Na-feldspar characteristic doublet band, labelled here as υa and υb, as a function of the order parameter Qod show interesting trends: both peak linewidths linearly increase until saturation. From Qod values lower than 0.6, peak broadening is no more affected by the Al-Si distribution. Moreover, the disordering process is found to be heterogeneous. SC-XRD and Raman data have suggested an inter-crystalline inhomogeneity of the samples, i.e., the presence of regions with different defect density on the micrometric scale. Finally, the influence of Ca-Na substitution in the plagioclase Raman spectra has been investigated. Raman spectra have been collected on a series of well characterized natural, low structural plagioclases. The variations of the Raman modes as a function of the chemical composition and the structural order have been determined. The number of the observed Raman bands at each composition gives information about the unit-cell symmetry: moving away from the C1 structures, the number of the Raman bands enhances, as the number of formula units in the unit cell increases. The modification from an “albite-like” Raman spectrum to a more “anorthite-like” spectrum occurs from sample An78 onwards, which coincides with the appearance of c reflections in the diffraction patterns of the samples. The evolution of the Raman bands υa and υb displays two changes in slope at ~An45 and ~An75: the first one occurs between e2 and e1 plagioclases, the latter separates e1 and I1 plagioclases with only b reflections in their diffraction patterns from I1 and P1 samples having b and c reflections too. The first variation represents exactly the e2→e1 phase transitions, whereas the second one corresponds in good approximation to the C1→I1 transition, which has been determined at ~An70 by previous works. The I1→P1 phase transition in the anorthite-rich side of the solid solution is not highlighted in the collected Raman spectra. Variations in peak broadening provide insights into the behaviour of the order parameter on a local scale, suggesting an increase in the structural disorder within the solid solution, as the structures have to incorporate more Al atoms to balance the change from monovalent to divalent cations. All the information acquired on these natural plagioclases has been used to produce a protocol able to give a preliminary estimation of the chemical composition of an unknown plagioclase from its Raman spectrum. Two calibration curves, one for albite-rich plagioclases and the other one for the anorthite-rich plagioclases, have been proposed by relating the peak linewidth of the most intense Raman band υa and the An content. It has been pointed out that the dependence of the composition from the linewidth can be obtained only for low structural plagioclases with a degree of order not far away from the references. The proposed tool has been tested on three mineralogical samples, two of meteoric origin and one of volcanic origin. Chemical compositions by Raman spectroscopy compare well, within an error of about 10%, with those obtained by elemental techniques. Further analyses on plagioclases with unknown composition will be necessary to validate the suggested method and introduce it as routine tool for the determination of the chemical composition from Raman data in planetary missions.

The dynamics of a genetic algorithm under stabilizing selection

A formalism recently introduced by Prugel-Bennett and Shapiro uses the methods of statistical mechanics to model the dynamics of genetic algorithms. To be of more general interest than the test cases they consider. In this paper, the technique is applied to the subset sum problem, which is a combinatorial optimization problem with a strongly non-linear energy (fitness) function and many local minima under single spin flip dynamics. It is a problem which exhibits an interesting dynamics, reminiscent of stabilizing selection in population biology. The dynamics are solved under certain simplifying assumptions and are reduced to a set of difference equations for a small number of relevant quantities. The quantities used are the population's cumulants, which describe its shape, and the mean correlation within the population, which measures the microscopic similarity of population members. Including the mean correlation allows a better description of the population than the cumulants alone would provide and represents a new and important extension of the technique. The formalism includes finite population effects and describes problems of realistic size. The theory is shown to agree closely to simulations of a real genetic algorithm and the mean best energy is accurately predicted.

Modelling the dynamics of genetic algorithms using statistical mechanics

A formalism for modelling the dynamics of Genetic Algorithms (GAs) using methods from statistical mechanics, originally due to Prugel-Bennett and Shapiro, is reviewed, generalized and improved upon. This formalism can be used to predict the averaged trajectory of macroscopic statistics describing the GA's population. These macroscopics are chosen to average well between runs, so that fluctuations from mean behaviour can often be neglected. Where necessary, non-trivial terms are determined by assuming maximum entropy with constraints on known macroscopics. Problems of realistic size are described in compact form and finite population effects are included, often proving to be of fundamental importance. The macroscopics used here are cumulants of an appropriate quantity within the population and the mean correlation (Hamming distance) within the population. Including the correlation as an explicit macroscopic provides a significant improvement over the original formulation. The formalism is applied to a number of simple optimization problems in order to determine its predictive power and to gain insight into GA dynamics. Problems which are most amenable to analysis come from the class where alleles within the genotype contribute additively to the phenotype. This class can be treated with some generality, including problems with inhomogeneous contributions from each site, non-linear or noisy fitness measures, simple diploid representations and temporally varying fitness. The results can also be applied to a simple learning problem, generalization in a binary perceptron, and a limit is identified for which the optimal training batch size can be determined for this problem. The theory is compared to averaged results from a real GA in each case, showing excellent agreement if the maximum entropy principle holds. Some situations where this approximation brakes down are identified. In order to fully test the formalism, an attempt is made on the strong sc np-hard problem of storing random patterns in a binary perceptron. Here, the relationship between the genotype and phenotype (training error) is strongly non-linear. Mutation is modelled under the assumption that perceptron configurations are typical of perceptrons with a given training error. Unfortunately, this assumption does not provide a good approximation in general. It is conjectured that perceptron configurations would have to be constrained by other statistics in order to accurately model mutation for this problem. Issues arising from this study are discussed in conclusion and some possible areas of further research are outlined.

Flexibility of short-strand RNA in aqueous solution as revealed by molecular dynamics simulation:are A′-RNA and A-RNA distinct conformational structures?

We use molecular dynamics simulations to compare the conformational structure and dynamics of a 21-base pair RNA sequence initially constructed according to the canonical A-RNA and A'-RNA forms in the presence of counterions and explicit water. Our study aims to add a dynamical perspective to the solid-state structural information that has been derived from X-ray data for these two characteristic forms of RNA. Analysis of the three main structural descriptors commonly used to differentiate between the two forms of RNA namely major groove width, inclination and the number of base pairs in a helical twist over a 30 ns simulation period reveals a flexible structure in aqueous solution with fluctuations in the values of these structural parameters encompassing the range between the two crystal forms and more. This provides evidence to suggest that the identification of distinct A-RNA and A'-RNA structures, while relevant in the crystalline form, may not be generally relevant in the context of RNA in the aqueous phase. The apparent structural flexibility observed in our simulations is likely to bear ramifications for the interactions of RNA with biological molecules (e.g. proteins) and non-biological molecules (e.g. non-viral gene delivery vectors). © CSIRO 2009.

Imaging the dynamics of the auditory steady-state evoked response

This study used magnetoencephalography (MEG) to examine the dynamic patterns of neural activity underlying the auditory steady-state response. We examined the continuous time-series of responses to a 32-Hz amplitude modulation. Fluctuations in the amplitude of the evoked response were found to be mediated by non-linear interactions with oscillatory processes both at the same source, in the alpha and beta frequency bands, and in the opposite hemisphere. © 2005 Elsevier Ireland Ltd. All rights reserved.

The effect of pH on PAMAM dendrimer-siRNA complexation:endosomal considerations as determined by molecular dynamics simulation

Intracellular degradation of genes, most notably within the endo-lysosomal compartment is considered a significant barrier to (non-viral) gene delivery in vivo. Previous reports based on in vitro studies claim that carriers possessing a mixture of primary, secondary and tertiary amines are able to buffer the acidic environment within the endosome, allowing for timely release of their contents, leading to higher transfection rates. In this report, we adopt an atomistic molecular dynamics (MD) simulation approach, comparing the complexation of 21-bp siRNA with low-generation polyamidoamine (PAMAM) dendrimers (G0 and G1) at both neutral and acidic pHs, the latter of which mimics the degradative environment within maturing 'late-endosomes'. Our simulations reveal that the time taken for the dendrimer-gene complex (dendriplex) to reach equilibrium is appreciably longer at low pH and this is accompanied by more compact packaging of the dendriplex, as compared to simulations performed at neutral pH. We also note larger absolute values of calculated binding free energies of the dendriplex at low pH, indicating a higher dendrimer-nucleic acid affinity in comparison with neutral pH. These novel simulations provide a more detailed understanding of low molecular-weight polymer-siRNA behavior, mimicking the endosomal environment and provide input of direct relevance to the "proton sponge theory", thereby advancing the rational design of non-viral gene delivery systems.

Molecular phase space transport in water:non-stationary random walk model

Molecular transport in phase space is crucial for chemical reactions because it defines how pre-reactive molecular configurations are found during the time evolution of the system. Using Molecular Dynamics (MD) simulated atomistic trajectories we test the assumption of the normal diffusion in the phase space for bulk water at ambient conditions by checking the equivalence of the transport to the random walk model. Contrary to common expectations we have found that some statistical features of the transport in the phase space differ from those of the normal diffusion models. This implies a non-random character of the path search process by the reacting complexes in water solutions. Our further numerical experiments show that a significant long period of non-stationarity in the transition probabilities of the segments of molecular trajectories can account for the observed non-uniform filling of the phase space. Surprisingly, the characteristic periods in the model non-stationarity constitute hundreds of nanoseconds, that is much longer time scales compared to typical lifetime of known liquid water molecular structures (several picoseconds).

Dynamics and topographic organization of recursive self-organizing maps

Recently there has been an outburst of interest in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. However, there is no general consensus as to how best to process sequences using topographicmaps, and this topic remains an active focus of neurocomputational research. The representational capabilities and internal representations of the models are not well understood. Here, we rigorously analyze a generalization of the self-organizingmap (SOM) for processing sequential data, recursive SOM (RecSOM) (Voegtlin, 2002), as a nonautonomous dynamical system consisting of a set of fixed input maps. We argue that contractive fixed-input maps are likely to produce Markovian organizations of receptive fields on the RecSOM map. We derive bounds on parameter β (weighting the importance of importing past information when processing sequences) under which contractiveness of the fixed-input maps is guaranteed. Some generalizations of SOM contain a dynamic module responsible for processing temporal contexts as an integral part of the model. We show that Markovian topographic maps of sequential data can be produced using a simple fixed (nonadaptable) dynamic module externally feeding a standard topographic model designed to process static vectorial data of fixed dimensionality (e.g., SOM). However, by allowing trainable feedback connections, one can obtain Markovian maps with superior memory depth and topography preservation. We elaborate on the importance of non-Markovian organizations in topographic maps of sequential data. © 2006 Massachusetts Institute of Technology.

Use of computational fluid dynamics in the design of bubble column reactors

Investigations into the modelling techniques that depict the transport of discrete phases (gas bubbles or solid particles) and model biochemical reactions in a bubble column reactor are discussed here. The mixture model was used to calculate gas-liquid, solid-liquid and gasliquid-solid interactions. Multiphase flow is a difficult phenomenon to capture, particularly in bubble columns where the major driving force is caused by the injection of gas bubbles. The gas bubbles cause a large density difference to occur that results in transient multi-dimensional fluid motion. Standard design procedures do not account for the transient motion, due to the simplifying assumptions of steady plug flow. Computational fluid dynamics (CFD) can assist in expanding the understanding of complex flows in bubble columns by characterising the flow phenomena for many geometrical configurations. Therefore, CFD has a role in the education of chemical and biochemical engineers, providing the examples of flow phenomena that many engineers may not experience, even through experimentation. The performance of the mixture model was investigated for three domains (plane, rectangular and cylindrical) and three flow models (laminar, k-e turbulence and the Reynolds stresses). mThis investigation raised many questions about how gas-liquid interactions are captured numerically. To answer some of these questions the analogy between thermal convection in a cavity and gas-liquid flow in bubble columns was invoked. This involved modelling the buoyant motion of air in a narrow cavity for a number of turbulence schemes. The difference in density was caused by a temperature gradient that acted across the width of the cavity. Multiple vortices were obtained when the Reynolds stresses were utilised with the addition of a basic flow profile after each time step. To implement the three-phase models an alternative mixture model was developed and compared against a commercially available mixture model for three turbulence schemes. The scheme where just the Reynolds stresses model was employed, predicted the transient motion of the fluids quite well for both mixture models. Solid-liquid and then alternative formulations of gas-liquid-solid model were compared against one another. The alternative form of the mixture model was found to perform particularly well for both gas and solid phase transport when calculating two and three-phase flow. The improvement in the solutions obtained was a result of the inclusion of the Reynolds stresses model and differences in the mixture models employed. The differences between the alternative mixture models were found in the volume fraction equation (flux and deviatoric stress tensor terms) and the viscosity formulation for the mixture phase.

Investigation of chaotic mixing in laminar fluid systems by the use of computational fluid dynamics

This work presents significant development into chaotic mixing induced through periodic boundaries and twisting flows. Three-dimensional closed and throughput domains are shown to exhibit chaotic motion under both time periodic and time independent boundary motions, A property is developed originating from a signature of chaos, sensitive dependence to initial conditions, which successfully quantifies the degree of disorder withjn the mixing systems presented and enables comparisons of the disorder throughout ranges of operating parameters, This work omits physical experimental results but presents significant computational investigation into chaotic systems using commercial computational fluid dynamics techniques. Physical experiments with chaotic mixing systems are, by their very nature, difficult to extract information beyond the recognition that disorder does, does not of partially occurs. The initial aim of this work is to observe whether it is possible to accurately simulate previously published physical experimental results through using commercial CFD techniques. This is shown to be possible for simple two-dimensional systems with time periodic wall movements. From this, and subsequent macro and microscopic observations of flow regimes, a simple explanation is developed for how boundary operating parameters affect the system disorder. Consider the classic two-dimensional rectangular cavity with time periodic velocity of the upper and lower walls, causing two opposing streamline motions. The degree of disorder within the system is related to the magnitude of displacement of individual particles within these opposing streamlines. The rationale is then employed in this work to develop and investigate more complex three-dimensional mixing systems that exhibit throughputs and time independence and are therefore more realistic and a significant advance towards designing chaotic mixers for process industries. Domains inducing chaotic motion through twisting flows are also briefly considered. This work concludes by offering possible advancements to the property developed to quantify disorder and suggestions of domains and associated boundary conditions that are expected to produce chaotic mixing.

A novel silicon membrane-based biosensing platform using distributive sensing strategy and artificial neural networks for feature analysis

A novel biosensing system based on a micromachined rectangular silicon membrane is proposed and investigated in this paper. A distributive sensing scheme is designed to monitor the dynamics of the sensing structure. An artificial neural network is used to process the measured data and to identify cell presence and density. Without specifying any particular bio-application, the investigation is mainly concentrated on the performance testing of this kind of biosensor as a general biosensing platform. The biosensing experiments on the microfabricated membranes involve seeding different cell densities onto the sensing surface of membrane, and measuring the corresponding dynamics information of each tested silicon membrane in the form of a series of frequency response functions (FRFs). All of those experiments are carried out in cell culture medium to simulate a practical working environment. The EA.hy 926 endothelial cell lines are chosen in this paper for the bio-experiments. The EA.hy 926 endothelial cell lines represent a particular class of biological particles that have irregular shapes, non-uniform density and uncertain growth behaviour, which are difficult to monitor using the traditional biosensors. The final predicted results reveal that the methodology of a neural-network based algorithm to perform the feature identification of cells from distributive sensory measurement has great potential in biosensing applications.

Profit sharing in a manufacturing plant in a developing country : communication and organisational dynamics

The adaptation of profit sharing creates a fundamental change in employee compensation by making a portion of total compensation directly dependent upon the total profits of the firm and the performance of the employee. The major goal of this study is to test for and measure the impact of the independent variable, a profit sharing plan implemented at Shahvand Industrial Company, upon communication behaviour, communication outcomes, and organisational outcomes as dependent variables. A quasi-experimental non-equivalent control group design with pre and posttest was the research design used to test the effects of profit sharing participation on permanent-part-time operative employees implemented by SIC. Several conclusions were reached as a result of the statistical analysis of the data collected in this study. Overall, few of the hypothesised effects of profit sharing participation appeared to have been realised according to the empirical results of this study. The finding that certain communication behaviours were more favourable for profit sharing participants than for non-participants support the general hypothesis of the integrated profit sharing model. The observed changes in communication behaviours indicate that information sharing and idea generation are important components of the profit sharing process. The results of this study did not reveal any changes in either communication or organisational outcomes. A significant finding of this study is that the implementation of profit sharing plans require a relatively long period of time. Patience is required to achieve high levels of success and management must make long-term commitment to profit sharing. Findings of this study should be interpreted with caution, taking into consideration that most of the previo.us researches on profit sharing have been conducted in Western European or American countries, while the current study was based on data collected from an organisation in a developing country. This implies that the findings reported in this thesis may not be comparable in certain respects to results derived from companies in major industrialised economies.

Financial liberalization and dynamics of firm-level financing and investment decisions in the Southeast Asian countries

This thesis examines the dynamics of firm-level financing and investment decisions for six Southeast Asian countries. The study provides empirical evidence on the impacts of changes in the firm-level financing decisions during the period of financial liberalization by considering the debt and equity financing decisions of a set of non-financial firms. The empirical results show that firms in Indonesia, Pakistan, and South Korea have relatively faster speed of adjustment than other Southeast Asian countries to attain optimal debt and equity ratios in response to banking sector and stock market liberalization. In addition, contrary to widely held belief that firms adjust their financial ratios to industry levels, the results indicate that industry factors do not significantly impact on the speed of capital structure adjustments. This study also shows that non-linear estimation methods are more appropriate than linear estimation methods for capturing changes in capital structure. The empirical results also show that international stock market integration of these countries has significantly reduced the equity risk premium as well as the firm-level cost of equity capital. Thus stock market liberalization is associated with a decrease in the cost of equity capital of the firms. Developments in the securities markets infrastructure have also reduced the cost of equity capital. However, with increased integration there is the possibility of capital outflows from the emerging markets, which might reverse the pattern of decrease in cost of capital in these markets.

Applications of Reissner's principle to structural dynamics

The analysis and prediction of the dynamic behaviour of s7ructural components plays an important role in modern engineering design. :n this work, the so-called "mixed" finite element models based on Reissnen's variational principle are applied to the solution of free and forced vibration problems, for beam and :late structures. The mixed beam models are obtained by using elements of various shape functions ranging from simple linear to complex cubic and quadratic functions. The elements were in general capable of predicting the natural frequencies and dynamic responses with good accuracy. An isoparametric quadrilateral element with 8-nodes was developed for application to thin plate problems. The element has 32 degrees of freedom (one deflection, two bending and one twisting moment per node) which is suitable for discretization of plates with arbitrary geometry. A linear isoparametric element and two non-conforming displacement elements (4-node and 8-node quadrilateral) were extended to the solution of dynamic problems. An auto-mesh generation program was used to facilitate the preparation of input data required by the 8-node quadrilateral elements of mixed and displacement type. Numerical examples were solved using both the mixed beam and plate elements for predicting a structure's natural frequencies and dynamic response to a variety of forcing functions. The solutions were compared with the available analytical and displacement model solutions. The mixed elements developed have been found to have significant advantages over the conventional displacement elements in the solution of plate type problems. A dramatic saving in computational time is possible without any loss in solution accuracy. With beam type problems, there appears to be no significant advantages in using mixed models.