Complex temporal patterns in molecular dynamics:a direct measure of the phase-space exploration by the trajectory at macroscopic time scales

Computer simulated trajectories of bulk water molecules form complex spatiotemporal structures at the picosecond time scale. This intrinsic complexity, which underlies the formation of molecular structures at longer time scales, has been quantified using a measure of statistical complexity. The method estimates the information contained in the molecular trajectory by detecting and quantifying temporal patterns present in the simulated data (velocity time series). Two types of temporal patterns are found. The first, defined by the short-time correlations corresponding to the velocity autocorrelation decay times (â‰0.1â€ps), remains asymptotically stable for time intervals longer than several tens of nanoseconds. The second is caused by previously unknown longer-time correlations (found at longer than the nanoseconds time scales) leading to a value of statistical complexity that slowly increases with time. A direct measure based on the notion of statistical complexity that describes how the trajectory explores the phase space and independent from the particular molecular signal used as the observed time series is introduced. © 2008 The American Physical Society.

Can we observe collective neuronal activity from macroscopic aggregate signals?

The fundamental problem faced by noninvasive neuroimaging techniques such as EEG/MEG1 is to elucidate functionally important aspects of the microscopic neuronal network dynamics from macroscopic aggregate measurements. Due to the mixing of the activities of large neuronal populations in the observed macroscopic aggregate, recovering the underlying network that generates the signal in the absence of any additional information represents a considerable challenge. Recent MEG studies have shown that macroscopic measurements contain sufficient information to allow the differentiation between patterns of activity, which are likely to represent different stimulus-specific collective modes in the underlying network (Hadjipapas, A., Adjamian, P., Swettenham, J.B., Holliday, I.E., Barnes, G.R., 2007. Stimuli of varying spatial scale induce gamma activity with distinct temporal characteristics in human visual cortex. NeuroImage 35, 518–530). The next question arising in this context is whether aspects of collective network activity can be recovered from a macroscopic aggregate signal. We propose that this issue is most appropriately addressed if MEG/EEG signals are to be viewed as macroscopic aggregates arising from networks of coupled systems as opposed to aggregates across a mass of largely independent neural systems. We show that collective modes arising in a network of simulated coupled systems can be indeed recovered from the macroscopic aggregate. Moreover, we show that nonlinear state space methods yield a good approximation of the number of effective degrees of freedom in the network. Importantly, information about hidden variables, which do not directly contribute to the aggregate signal, can also be recovered. Finally, this theoretical framework can be applied to experimental MEG/EEG data in the future, enabling the inference of state dependent changes in the degree of local synchrony in the underlying network.

Influence of macroscopic residual stress fields on fatigue crack growth measurement in SiC particulate reinforced 8090 aluminium alloy

The effect of residual stresses, induced by cold water quenching, on the morphology of fatigue crack fronts has been investigated in a powder metallurgy 8090 aluminium alloy, with and without reinforcement in the form of 20 wt-%SiC particles. Residual stress measurements reveal that the surface compressive stresses developed in these materials are significantly greater than in conventional metallurgy ingot 8090, because surface yielding occurs on quenching. The yield stresses of the powder route materials are greater than those of ingot produced 8090 and hence greater surface stresses can be maintained. In fatigue, severe crack front bowing is observed in the powder formed materials as a result of the reduction of the R ratio (minimum load/maximum load) by the compressive residual stresses at the sides of the specimen, causing premature crack closure and hence reducing the local driving force for fatigue crack growth ΔKeff. This distortion of the crack fronts introduces large errors into measurements of crack growth rate and threshold values of ΔK.

Anisotropic surface energetics and wettability of macroscopic form I paracetamol crystals

Advancing (θA) and receding (θR) contact angles were measured with several probe liquids on the external facets (201), (001), (011), and (110) of macroscopic form I paracetamol crystals as well as the cleaved (internal) facet (010). For the external crystal facets, dispersive surface energies γd calculated from the contact angles were found to be similar (34 ± 1 mJ/m2), while the polar components varied significantly. Cleaving the crystals exposed a more apolar (010) surface with very different surface properties, including γd = 45 ± 1 mJ/m2. The relative surface polarity (γp/γ) of the facets in decreasing order was (001) > (011) > (201) > (110) > (010), which agreed with the fraction of exposed polar hydroxyl groups as determined from C and O 1s X-ray photoelectron spectroscopy (XPS) spectra, and could be correlated with the number of non-hydrogen-bonded hydroxyl groups per unit area present for each crystal facet, based on the known crystal structures. In conclusion, all facets of form I paracetamol crystals examined exhibited anisotropic wetting behavior and surface energetics that correlated to the presence of surface hydroxyl groups.  © 2006 American Chemical Society.