Morphological transitions in polymer monolayers under compression

We present a systematic investigation of morphological transitions in poly vinylacetate Langmuir monolayers. On compression, the polymer monolayer is converted to a continuous membrane with a thickness of similar to 2-3 nm. Above a certain surface concentration the monolayer, on water, undergoes a morphological transition-buckling, leading to formation of striped patterns of period of lambda(b)similar to 160 nm, as determined from in situ grazing incidence small angle x-ray scattering measurements. The obtained value is much smaller than what has been typically observed for Langmuir monolayers on water or thin films on soft substrates. Using existing theories for buckling of fluidlike films on fluid substrates, we obtain very low values of bending rigidity and Young's modulus of the polymer monolayer compared to that observed earlier for lipid or polymeric monolayers. Since buckling in these monolayers occurs only above a certain surface concentration, we have looked at the possibility that the buckling in these films occurs due to changes in their mechanical properties under compression. Using the model of Huang and Suo of buckling of solidlike films on viscoelastic substrates, we find values of the mechanical properties, which are much closer to the bulk values but still significantly lower. Although the reduction could be along the lines of what has been observed earlier for ultrathin polymer film or surface layers of polymers, the possibility of micromechanical effects also determining the buckling in such polymer monolayers cannot be ruled out. We have provided possible explanation of the buckling of the poly vinylacetate monolayers in terms of the change in isothermal compression modulus with surface concentration.

Using morphological traits to identify persistent lucernes for dryland agriculture in NSW, Australia

This paper reports on several studies conducted to better understand the variability between lucerne cultivars and lines, and use this to predict persistence in dryland grazing pastures in eastern Australia. Morphological traits of 20 cultivars/lines were measured in irrigated and dryland spaced plant experiments. Studies were also conducted to describe variation among lucernes in their utilisation of starch and responses to water deficit, pests and diseases. Multiple regression analyses were used to develop simple models where the measured traits could be used to predict persistence of lucerne lines in dryland evaluation experiments. Although there was significant variation among cultivars/lines in most measured traits, no single trait reliably predicted persistence of cultivars/lines in dryland evaluation experiments. However, variation in persistence at both sites could be explained by models developed by multiple regression using differences in the mean lengths of the longest stems at 10% flower in summer and winter. Persistent lucernes were those that had relatively long stems in summer and short stems in winter. Water use efficiencies, starch utilisation patterns and resistances to pests and diseases of different lucernes provided some improvement to this simple model, but these improvements were not consistent.

Digital elevation model error in terrain analysis

Digital elevation models (DEMs) have been an important topic in geography and surveying sciences for decades due to their geomorphological importance as the reference surface for gravita-tion-driven material flow, as well as the wide range of uses and applications. When DEM is used in terrain analysis, for example in automatic drainage basin delineation, errors of the model collect in the analysis results. Investigation of this phenomenon is known as error propagation analysis, which has a direct influence on the decision-making process based on interpretations and applications of terrain analysis. Additionally, it may have an indirect influence on data acquisition and the DEM generation. The focus of the thesis was on the fine toposcale DEMs, which are typically represented in a 5-50m grid and used in the application scale 1:10 000-1:50 000. The thesis presents a three-step framework for investigating error propagation in DEM-based terrain analysis. The framework includes methods for visualising the morphological gross errors of DEMs, exploring the statistical and spatial characteristics of the DEM error, making analytical and simulation-based error propagation analysis and interpreting the error propagation analysis results. The DEM error model was built using geostatistical methods. The results show that appropriate and exhaustive reporting of various aspects of fine toposcale DEM error is a complex task. This is due to the high number of outliers in the error distribution and morphological gross errors, which are detectable with presented visualisation methods. In ad-dition, the use of global characterisation of DEM error is a gross generalisation of reality due to the small extent of the areas in which the decision of stationarity is not violated. This was shown using exhaustive high-quality reference DEM based on airborne laser scanning and local semivariogram analysis. The error propagation analysis revealed that, as expected, an increase in the DEM vertical error will increase the error in surface derivatives. However, contrary to expectations, the spatial au-tocorrelation of the model appears to have varying effects on the error propagation analysis depend-ing on the application. The use of a spatially uncorrelated DEM error model has been considered as a 'worst-case scenario', but this opinion is now challenged because none of the DEM derivatives investigated in the study had maximum variation with spatially uncorrelated random error. Sig-nificant performance improvement was achieved in simulation-based error propagation analysis by applying process convolution in generating realisations of the DEM error model. In addition, typology of uncertainty in drainage basin delineations is presented.

Proteomic profiling of forskolin-induced differentiated BeWo cells: an in-vitro model of cytotrophoblast differentiation

Placental trophoblastic differentiation is characterized by the fusion of monolayer cytotrophoblasts into syncytiotrophoblasts. During this process of differentiation, several morphological and biochemical changes are known to occur, and this model has been employed to investigate the changes that occur at the gene and protein level during differentiation. Using the sensitive technique of proteomics [two-dimensional gel electrophoresis (2DGE)], changes in protein profile were evaluated in the control and forskolin-induced differentiated cells of trophoblastic choriocarcinoma BeWo cell line. Several proteins were differentially expressed in control and differentiated cells. Four major proteins were up-regulated as assessed by silver staining, and were further characterized as c-h-ras p 21 (phosphorylated), retinoblastoma susceptibility protein I and integrase interactor protein 1. These proteins are known to play an important role in growth arrest of cells, and thus may play a role in initiating the process of differentiation.

Phase separation in a simple model with dynamical asymmetry

We perform computer simulations of a Cahn-Hilliard model of phase separation that has dynamical asymmetry between the two coexisting phases. The dynamical asymmetry is incorporated by considering a mobility function that is order parameter dependent. Simulations of this model reveal morphological features similar to those observed in viscoelastic phase separation. In the early stages, the minority phase domains form a percolating structure that shrinks with time, eventually leading to the formation of disconnected regions that are characterized by the presence of random interfaces as well as isolated droplets. The domains grow as L(t)similar to t(1/3) in the very late stages. Although dynamical scaling is violated in the area shrinking regime, it is restored at late times. However, the form of the scaling function is found to depend on the extent of dynamical asymmetry. [S1063-651X(99)12101-9].

Active Dendrites Regulate Spectral Selectivity in Location-Dependent Spike Initiation Dynamics of Hippocampal Model Neurons

How does the presence of plastic active dendrites in a pyramidal neuron alter its spike initiation dynamics? To answer this question, we measured the spike-triggered average (STA) from experimentally constrained, conductance-based hippocampal neuronal models of various morphological complexities. We transformed the STA computed from these models to the spectral and the spectrotemporal domains and found that the spike initiation dynamics exhibited temporally localized selectivity to a characteristic frequency. In the presence of the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, the STA characteristic frequency strongly correlated with the subthreshold resonance frequency in the theta frequency range. Increases in HCN channel density or in input variance increased the STA characteristic frequency and its selectivity strength. In the absence of HCN channels, the STA exhibited weak delta frequency selectivity and the characteristic frequency was related to the repolarization dynamics of the action potentials and the recovery kinetics of sodium channels from inactivation. Comparison of STA obtained with inputs at various dendritic locations revealed that nonspiking and spiking dendrites increased and reduced the spectrotemporal integration window of the STA with increasing distance from the soma as direct consequences of passive filtering and dendritic spike initiation, respectively. Finally, the presence of HCN channels set the STA characteristic frequency in the theta range across the somatodendritic arbor and specific STA measurements were strongly related to equivalent transfer-impedance-related measurements. Our results identify explicit roles for plastic active dendrites in neural coding and strongly recommend a dynamically reconfigurable multi-STA model to characterize location-dependent input feature selectivity in pyramidal neurons.

Morphological Effects of G-Quadruplex Stabilization Using a Small Molecule in Zebrafish

Zebrafish (Danio rerio) embryos are transparent and advantageous for studying early developmental changes due to ex utero development, making them an appropriate model for studying gene expression changes as a result of molecular targeting. Zebrafish embryos were injected with a previously reported G-quadruplex selective ligand, and the phenotypic changes were recorded. We report marked discrepancies in the development of intersegmental vessels. In silico analysis determined that the putative G-quadruplex motif occur in the upstream promoter region of the Cdh5 (N-cadherin) gene. A real-time polymerase chain reaction-based investigation indicated that in zebrafish, CDH-2 (ZN-cad) was significantly downregulated in the ligand-treated embryos. Biophysical characterization of the interaction of the ligand with the G-quadruplex motif found in this promoter yielded strong binding and stabilization of the G-quadruplex with this ligand. Hence, we report for the first time the phenotypic impact of G-quadruplex targeting with a ligand in a vertebrate organism. This study has unveiled not only G-quadruplex targeting in non-human animal species but also the potential that G-quadruplexes can provide a ready tool for understanding the phenotypic effects of targeting certain important genes involved in differentiation and developmental processes in a living eukaryotic organism.

Case Study: Influence Of Morphological Changes On Flooding In Jingjiang River

The middle reach of the Yangtze River, customarily called the Jingjiang River, together with its diversion channels and Dongting Lake, form a large complicated drainage system. In the last five decades, significant geomorphological changes have occurred in the drainage system, including the shrinkage of diversion channels, contraction of Dongting Lake, changes in the rating curve at the Luoshan station, and cutoffs of the lower Jingjiang River. These changes are believed to be the cause of the occurrence of abnormal floods in the Jingjiang River. Qualitative analyses suggest that the first three factors aggravate the flood situation in the lower Jingjiang River, while the last factor seems beneficial for flood prevention. To quantitatively evaluate these conclusions, a finite-volume numerical model was constructed. A series of numerical simulations were carried out to test the individual and combined effects of the aforementioned four factors, and these simulations showed that high flood stages in the Jingjiang River clearly are related to the geomorphological changes.

Behavioral, neurochemical and morphological changes induced by the overexpression of munc18-1a in brain of mice: relevance to schizophrenia

Overexpression of the mammalian homolog of the unc-18 gene (munc18-1) has been described in the brain of subjects with schizophrenia. Munc18-1 protein is involved in membrane fusion processes, exocytosis and neurotransmitter release. A transgenic mouse strain that overexpresses the protein isoform munc18-1a in the brain was characterized. This animal displays several schizophrenia-related behaviors, supersensitivity to hallucinogenic drugs and deficits in prepulse inhibition that reverse after antipsychotic treatment. Relevant brain areas (that is, cortex and striatum) exhibit reduced expression of dopamine D-1 receptors and dopamine transporters together with enhanced amphetamine-induced in vivo dopamine release. Magnetic resonance imaging demonstrates decreased gray matter volume in the transgenic animal. In conclusion, the mouse overexpressing brain munc18-1a represents a new valid animal model that resembles functional and structural abnormalities in patients with schizophrenia.

A model for energy and morphology of crystalline grain boundaries with arbitrary geometric character

It has been well-established that interfaces in crystalline materials are key players in the mechanics of a variety of mesoscopic processes such as solidification, recrystallization, grain boundary migration, and severe plastic deformation. In particular, interfaces with complex morphologies have been observed to play a crucial role in many micromechanical phenomena such as grain boundary migration, stability, and twinning. Interfaces are a unique type of material defect in that they demonstrate a breadth of behavior and characteristics eluding simplified descriptions. Indeed, modeling the complex and diverse behavior of interfaces is still an active area of research, and to the author's knowledge there are as yet no predictive models for the energy and morphology of interfaces with arbitrary character. The aim of this thesis is to develop a novel model for interface energy and morphology that i) provides accurate results (especially regarding "energy cusp" locations) for interfaces with arbitrary character, ii) depends on a small set of material parameters, and iii) is fast enough to incorporate into large scale simulations.

In the first half of the work, a model for planar, immiscible grain boundary is formulated. By building on the assumption that anisotropic grain boundary energetics are dominated by geometry and crystallography, a construction on lattice density functions (referred to as "covariance") is introduced that provides a geometric measure of the order of an interface. Covariance forms the basis for a fully general model of the energy of a planar interface, and it is demonstrated by comparison with a wide selection of molecular dynamics energy data for FCC and BCC tilt and twist boundaries that the model accurately reproduces the energy landscape using only three material parameters. It is observed that the planar constraint on the model is, in some cases, over-restrictive; this motivates an extension of the model.

In the second half of the work, the theory of faceting in interfaces is developed and applied to the planar interface model for grain boundaries. Building on previous work in mathematics and materials science, an algorithm is formulated that returns the minimal possible energy attainable by relaxation and the corresponding relaxed morphology for a given planar energy model. It is shown that the relaxation significantly improves the energy results of the planar covariance model for FCC and BCC tilt and twist boundaries. The ability of the model to accurately predict faceting patterns is demonstrated by comparison to molecular dynamics energy data and experimental morphological observation for asymmetric tilt grain boundaries. It is also demonstrated that by varying the temperature in the planar covariance model, it is possible to reproduce a priori the experimentally observed effects of temperature on facet formation.

Finally, the range and scope of the covariance and relaxation models, having been demonstrated by means of extensive MD and experimental comparison, future applications and implementations of the model are explored.

Graphone model interpolation and Arabic pronunciation generation

This paper extends n-gram graphone model pronunciation generation to use a mixture of such models. This technique is useful when pronunciation data is for a specific variant (or set of variants) of a language, such as for a dialect, and only a small amount of pronunciation dictionary training data for that specific variant is available. The performance of the interpolated n-gram graphone model is evaluated on Arabic phonetic pronunciation generation for words that can't be handled by the Buckwalter Morphological Analyser. The pronunciations produced are also used to train an Arabic broadcast audio speech recognition system. In both cases the interpolated graphone model leads to improved performance. Copyright © 2011 ISCA.

How neurons migrate: a dynamic in-silico model of neuronal migration in the developing cortex.

BACKGROUND: Neuronal migration, the process by which neurons migrate from their place of origin to their final position in the brain, is a central process for normal brain development and function. Advances in experimental techniques have revealed much about many of the molecular components involved in this process. Notwithstanding these advances, how the molecular machinery works together to govern the migration process has yet to be fully understood. Here we present a computational model of neuronal migration, in which four key molecular entities, Lis1, DCX, Reelin and GABA, form a molecular program that mediates the migration process. RESULTS: The model simulated the dynamic migration process, consistent with in-vivo observations of morphological, cellular and population-level phenomena. Specifically, the model reproduced migration phases, cellular dynamics and population distributions that concur with experimental observations in normal neuronal development. We tested the model under reduced activity of Lis1 and DCX and found an aberrant development similar to observations in Lis1 and DCX silencing expression experiments. Analysis of the model gave rise to unforeseen insights that could guide future experimental study. Specifically: (1) the model revealed the possibility that under conditions of Lis1 reduced expression, neurons experience an oscillatory neuron-glial association prior to the multipolar stage; and (2) we hypothesized that observed morphology variations in rats and mice may be explained by a single difference in the way that Lis1 and DCX stimulate bipolar motility. From this we make the following predictions: (1) under reduced Lis1 and enhanced DCX expression, we predict a reduced bipolar migration in rats, and (2) under enhanced DCX expression in mice we predict a normal or a higher bipolar migration. CONCLUSIONS: We present here a system-wide computational model of neuronal migration that integrates theory and data within a precise, testable framework. Our model accounts for a range of observable behaviors and affords a computational framework to study aspects of neuronal migration as a complex process that is driven by a relatively simple molecular program. Analysis of the model generated new hypotheses and yet unobserved phenomena that may guide future experimental studies. This paper thus reports a first step toward a comprehensive in-silico model of neuronal migration.

Morphological variability between wild populations and inbred stocks of a Chinese minnow, Gobiocypris rarus

Gobiocypris rarus, a small, native cyprinid fish, is currently widely used in research on fish pathology, genetics, toxicology, embryology, and physiology in China. To develop this species as a model laboratory animal, inbred strains have been successfully created. In this study, to explore a method to discriminate inbred strains and evaluate inbreeding effects, morphological variation among three wild populations and three inbred stocks of G. rarus was investigated by the multivariate analysis of eight meristic and 30 morphometric characters. Tiny intraspecific variations in meristic characters were found, but these were not effective for population distinction. Stepwise discriminant analysis and cluster analysis of conventional measures and truss network data showed considerabe divergence among populations, especially between wild populations and inbred stocks. The average discriminant accuracy for all populations was 82.1% based on conventional measures and 86.4% based on truss data, whereas the discriminant accuracy for inbred strains was much higher. These results suggested that multivariate analyses of morphometric characters are an effective method for discriminating inbred strains of G. rarus. Morphological differences between wild populations and inbred strains appear to result from both genetic differences and environmental factors. Thirteen characters, extracted from stepwise discriminant analysis, played important roles in morphological differentiation. These characters were mainly measures related to body depth and head size.

Morphological computation of multi-gaited robot locomotion based on free vibration.

In recent years, there has been increasing interest in the study of gait patterns in both animals and robots, because it allows us to systematically investigate the underlying mechanisms of energetics, dexterity, and autonomy of adaptive systems. In particular, for morphological computation research, the control of dynamic legged robots and their gait transitions provides additional insights into the guiding principles from a synthetic viewpoint for the emergence of sensible self-organizing behaviors in more-degrees-of-freedom systems. This article presents a novel approach to the study of gait patterns, which makes use of the intrinsic mechanical dynamics of robotic systems. Each of the robots consists of a U-shaped elastic beam and exploits free vibration to generate different locomotion patterns. We developed a simplified physics model of these robots, and through experiments in simulation and real-world robotic platforms, we show three distinctive mechanisms for generating different gait patterns in these robots.

Dynamics of morphological changes for mitochondrial fission and fusion

Mitochondria experience continuous fusion and fission in a living cell, but their dynamics remains poorly quantified. Here a theoretical model was developed, upon a simplified population balance equation (PBE), to predict the morphological changes induced by mitochondrial fission and fusion. Assuming that both fission and fusion events are statistically independent, the survival probability of mitochondria staying in the fission or fusion state was formulated as an exponentially-decayed function with time, which depended on the time-dependent distribution of the mitochondrial volume and the fission and fusion rates. Parametric analysis was done for two typical volume distributions. One was Gamma distribution and the other was Gaussian distribution, derived from the measurements of volume distribution for individual mitochondria in a living cell and purified mitochondria in vitro. The predictions indicated that the survival probability strongly depended on morphological changes of individual mitochondria and was inversely correlated to the fission and fusion rates. This work provided a new insight into quantifying the mitochondrial dynamics via monitoring the evolution of the mitochondrial volume.