Understanding autobiographical memory content using computational text analysis.

Although research on autobiographical memory (AM) continues to grow, there remain few methods to analyze AM content. Past approaches are typically manual, and prohibitively time- and labour-intensive. These methodological limitations are concerning because content may provide insights into the nature and functions of AM. In particular, analyzing content in recurrent involuntary autobiographical memories (IAMs; those that spring to mind unintentionally and repetitively) could resolve controversies about whether these memories typically involve mundane or distressing events. Here, we present computational methods that can analyze content in thousands of participants' AMs, without needing to hand-code each memory. A sample of 6,187 undergraduates completed surveys about recurrent IAMs, resulting in 3,624 text descriptions. Using frequency analyses, we identified common (e.g., "time", "friend") and distinctive words in recurrent IAMs (e.g., "argument" as distinctive to negative recurrent IAMs). Using structural topic modelling, we identified coherent topics (e.g., "Negative past relationships", "Conversations", "Experiences with family members") within recurrent IAMs and found that topic use significantly differed depending on the valence of these memories. Computational methods allowed us to analyze large quantities of AM content with enhanced granularity and reproducibility. We present the means to enable future research on AM content at an unprecedented scope and scale.

Feature identification in time-indexed model output.

We present a method for identifying features (time periods of interest) in data sets consisting of time-indexed model output. The method is used as a diagnostic to quickly focus the attention on a subset of the data before further analysis methods are applied. Mathematically, the infinity norm errors of empirical orthogonal function (EOF) reconstructions are calculated for each time output. The result is an EOF reconstruction error map which clearly identifies features as changes in the error structure over time. The ubiquity of EOF-type methods in a wide range of disciplines reduces barriers to comprehension and implementation of the method. We apply the error map method to three different Computational Fluid Dynamics (CFD) data sets as examples: the development of a spontaneous instability in a large amplitude internal solitary wave, an internal wave interacting with a density profile change, and the collision of two waves of different vertical mode. In all cases the EOF error map method identifies relevant features which are worthy of further study.

Feature identification in time series data sets.

We present a computationally inexpensive, flexible feature identification method which uses a comparison of time series to identify a rank-ordered set of features in geophysically-sourced data sets. Many physical phenomena perturb multiple physical variables nearly simultaneously, and so features are identified as time periods in which there are local maxima of absolute deviation in all time series. Unlike other available methods, this method allows the analyst to tune the method using their knowledge of the physical context. The method is applied to a data set from a moored array of instruments deployed in the coastal environment of Monterey Bay, California, and a data set from sensors placed within the submerged Yax Chen Cave System in Tulum, Quintana Roo, Mexico. These example data sets demonstrate that the method allows for the automated identification of features which are worthy of further study.

Spatial optimization for radiation therapy of brain tumours.

Glioblastomas are the most common primary brain tumours. They are known for their highly aggressive growth and invasion, leading to short survival times. Treatments for glioblastomas commonly involve a combination of surgical intervention, chemotherapy, and external beam radiation therapy (XRT). Previous works have not only successfully modelled the natural growth of glioblastomas in vivo, but also show potential for the prediction of response to radiation prior to treatment. This suggests that the efficacy of XRT can be optimized before treatment in order to yield longer survival times. However, while current efforts focus on optimal scheduling of radiotherapy treatment, they do not include a similarly sophisticated spatial optimization. In an effort to improve XRT, we present a method for the spatial optimization of radiation profiles. We expand upon previous results in the general problem and examine the more physically reasonable cases of 1-step and 2-step radiation profiles during the first and second XRT fractions. The results show that by including spatial optimization in XRT, while retaining a constant prescribed total dose amount, we are able to increase the total cell kill from the clinically-applied uniform case.

Pseudo-interface Rayleigh wave on a permeable porous medium/vacuum interface.

It is well known that the Rayleigh wave propagating along a permeable plane boundary of a poroelastic half-space may have a high-frequency cutoff beyond which the corresponding Rayleigh pole is absent. The present study investigates the specific features of the surface wave propagation during transition through this cut-off frequency. Using a set of experimentally determined mechanical parameter values for water-saturated sintered glass beads in the framework of Biot's theory, this theoretical investigation indicates the following. The Rayleigh wave upper cut-off frequency may occur within a physical frequency range over which the characteristic wavelength far exceeds typical pore size. Beyond the cut-off frequency, the Rayleigh pole migrates onto the non-principal, in other words, unphysical, Riemann sheet. As a consequence, during this transition, the Rayleigh wave transforms into a pseudo-interface wave and radiates part of its energy into the interior of the half-space in the form of P2-wave motion.

Intrinsic breaking of internal solitary waves in a deep lake.

Based on simulations with the Dubreil-Jacotin-Long (DJL) equation, the limiting amplitude and the breaking mechanisms of internal solitary waves of depression (ISWs) are predicted for different background stratifications. These theoretical predictions are compared to the amplitude and the stability of the leading internal solitary waves of more than 200 trains of ISWs observed in the centre of a sub-basin of Lake Constance. The comparison of the model results with the field observations indicates that the simulated limiting amplitude of the ISWs provides an excellent prediction of the critical wave height above which ISWs break in the field. Shear instabilities and convective instabilities are each responsible for about half of the predicted wave breaking events. The data suggest the presence of core-like structures within the convectively unstable waves, but fully developed and stable cores were not observed. The lack of stable trapped cores in the field can be explained by the results from dynamic simulations of ISWs with trapped cores which demonstrate that even slight disturbances of the background stratification cause trapped cores to become unstable.

Energy velocity and quality factor of poroelastic waves in isotropic media.

The energy velocity and Q factor of poroelastic acoustic waves in the context of classical isotropic Biot's theory are revisited. Special attention is paid to the high frequency regime when interphase interaction is viscoelastic. The analogy with viscoelastic behavior is emphasized in derivation of the energy balance equations which relate kinetic energy, potential energy, viscous power dissipation, and elastic energy stored associated with each wave. These lead to exact closed form expressions for the energy velocity and Q factor for both longitudinal and shear waves from energy principles. Most notably, the analysis of the resulting expressions reveals that the energy velocity of both longitudinal and shear waves equals (exceeds) the corresponding phase velocity in the case of the low (full) frequency range theory, and that the exact expression for the Q factor contains an additive correction due to viscoelastic interphase interaction.

Complex group velocity and energy transport in absorbing media.

Complex group velocity is common in absorbing and active media, yet its precise physical meaning is unclear. While in the case of a nondissipative medium the group velocity of propagating waves Cg=dω/dk is exactly equal to the observable energy velocity (defined as the ratio between the energy flux and the total energy density) Cg=F/E , in a dissipative medium Cg=dω/dk is in general a complex quantity which cannot be associated with the velocity of energy transport. Nevertheless, we find that the complex group velocity may contain information about the energy transport as well as the energy dissipated in the medium. The presented analysis is intended to expound the connection between the complex group velocity and energy transport characteristics for a class of hyperbolic dissipative dynamical systems. Dissipation mechanisms considered herein include viscous and viscoelastic types of damping. Both cases of spatial and temporal decay are discussed. The presented approach stems from the Lagrangian formulation and is illustrated with identities that relate the complex group velocity and energy transport characteristics for the damped Klein-Gordon equation; Maxwell's equations, governing electromagnetic waves in partially conducting media; and Biot's theory, governing acoustic wave propagation in porous solids.