A comparison of mathematical models for phase separation in high-rate LiFePO4 cathodes

We construct a two-scale mathematical model for modern, high-rate LiFePO4cathodes. We attempt to validate against experimental data using two forms of the phase-field model developed recently to represent the concentration of Li+ in nano-sized LiFePO4crystals. We also compare this with the shrinking-core based model we developed previously. Validating against high-rate experimental data, in which electronic and electrolytic resistances have been reduced is an excellent test of the validity of the crystal-scale model used to represent the phase-change that may occur in LiFePO4material. We obtain poor fits with the shrinking-core based model, even with fitting based on “effective” parameter values. Surprisingly, using the more sophisticated phase-field models on the crystal-scale results in poorer fits, though a significant parameter regime could not be investigated due to numerical difficulties. Separate to the fits obtained, using phase-field based models embedded in a two-scale cathodic model results in “many-particle” effects consistent with those reported recently.

Happy talk? Toward understanding the significance of dialogue to the practice of public relations

The significance of dialogue to public relations is a persistent and widespread theme in both industry and the academy (International Communication Association, 2013). Dialogue is integral to a number of theoretical perspectives in public relations, from the instrumentalist/functionalist through to the rise of the influence of the two-way symmetric model (Grunig & Hunt, 1984). The emergence of the relational perspective – with its emphasis on dialogue as a means of achieving mutually-beneficial relationships between organisations and stakeholders – brought attention to dialogue as a discrete concept (see, for example, Ledingham, 2003; and 2006). Dialogue continues to be an implicit element in the development of new perspectives on public relations, such as Holtzhausen and Voto’s (2002) postmodern approach...

Semiparametric estimation of count regression models

This paper develops a semiparametric estimation approach for mixed count regression models based on series expansion for the unknown density of the unobserved heterogeneity. We use the generalized Laguerre series expansion around a gamma baseline density to model unobserved heterogeneity in a Poisson mixture model. We establish the consistency of the estimator and present a computational strategy to implement the proposed estimation techniques in the standard count model as well as in truncated, censored, and zero-inflated count regression models. Monte Carlo evidence shows that the finite sample behavior of the estimator is quite good. The paper applies the method to a model of individual shopping behavior. © 1999 Elsevier Science S.A. All rights reserved.

Morphometric stability of the corneal subbasal nerve plexus in healthy individuals a 3-year longitudinal study using corneal confocal microscopy

Purpose We examined the age-dependent alterations and longitudinal course of subbasal nerve plexus (SNP) morphology in healthy individuals. Methods Laser-scanning corneal confocal microscopy, ocular screening, and health and metabolic assessment were performed on 64 healthy participants at baseline and at 12-month intervals for 3 years. At each annual visit, eight central corneal images of the SNP were selected and analyzed using a fully-automated analysis system to quantify corneal nerve fiber length (CNFL). Two linear mixed model approaches were fitted to examine the relationship between age and CNFL, and the longitudinal changes of CNFL over three years. Results At baseline, mean age was 51.9 ± 14.7 years. The cohort was sex balanced (χ2 = 0.56, P = 0.45). Age (t = 1.6, P = 0.12) and CNFL (t = -0.50, P = 0.62) did not differ between sexes. A total of 52 participants completed the 36-month visit and 49 participants completed all visits. Age had a significant effect on CNFL (F1,33 = 5.67, P = 0.02) with a linear decrease of 0.05 mm/mm2 in CNFL per one year increase in age. No significant change in CNFL was observed over the 36-month period (F1,55 = 0.69, P = 0.41). Conclusions The CNFL showed a stable course over a 36-month period in healthy individuals, although there was a slight linear reduction in CNFL with age. The findings of this study have implications for understanding the time-course of the effect of pathology and surgical or therapeutic interventions on the morphology of the SNP, and serves to confirm the suitability of CNFL as a screening/monitoring marker for peripheral neuropathies.

Conformational Spread as a Mechanism for Cooperativity in the Bacterial Flagellar Switch

The bacterial flagellar switch that controls the direction of flagellar rotation during Chemotaxis has a highly cooperative response. This has previously been understood in terms of the classic two-state, concerted model of allosteric regulation. Here, we used high-resolution optical microscopy to observe switching of single motors and uncover the stochastic multistate nature of the switch. Our observations are in detailed quantitative agreement with a recent general model of allosteric cooperativity that exhibits conformational spread-the stochastic growth and shrinkage of domains of adjacent subunits sharing a particular conformational state. We expect that conformational spread will be important in explaining cooperativity in other large signaling complexes.

Multi-action recognition via stochastic modelling of optical flow and gradients

In this paper we propose a novel approach to multi-action recognition that performs joint segmentation and classification. This approach models each action using a Gaussian mixture using robust low-dimensional action features. Segmentation is achieved by performing classification on overlapping temporal windows, which are then merged to produce the final result. This approach is considerably less complicated than previous methods which use dynamic programming or computationally expensive hidden Markov models (HMMs). Initial experiments on a stitched version of the KTH dataset show that the proposed approach achieves an accuracy of 78.3%, outperforming a recent HMM-based approach which obtained 71.2%.

High-performance computing for data analytics

One of the main challenges in data analytics is that discovering structures and patterns in complex datasets is a computer-intensive task. Recent advances in high-performance computing provide part of the solution. Multicore systems are now more affordable and more accessible. In this paper, we investigate how this can be used to develop more advanced methods for data analytics. We focus on two specific areas: model-driven analysis and data mining using optimisation techniques.

Transdimensional sequential Monte Carlo using variational Bayes — SMCVB

A new transdimensional Sequential Monte Carlo (SMC) algorithm called SM- CVB is proposed. In an SMC approach, a weighted sample of particles is generated from a sequence of probability distributions which ‘converge’ to the target distribution of interest, in this case a Bayesian posterior distri- bution. The approach is based on the use of variational Bayes to propose new particles at each iteration of the SMCVB algorithm in order to target the posterior more efficiently. The variational-Bayes-generated proposals are not limited to a fixed dimension. This means that the weighted particle sets that arise can have varying dimensions thereby allowing us the option to also estimate an appropriate dimension for the model. This novel algorithm is outlined within the context of finite mixture model estimation. This pro- vides a less computationally demanding alternative to using reversible jump Markov chain Monte Carlo kernels within an SMC approach. We illustrate these ideas in a simulated data analysis and in applications.

Do pollutions deter foreign direct investment in China?

The scale of environmental problems in China is clearly evident. This paper analyses foreign direct investment (FDI) in China with a finite mixture model, also known as latent class model to understand the relationship between FDI and several pollutions. This is used to regresses FDI as function covariates including pollutants. The results reveal that FDI is affected by pollutants. There are cases reducing pollution deters foreign investment in China.

Non-parametric consistency test for multiple-sensing-modality data fusion

Fusing data from multiple sensing modalities, e.g. laser and radar, is a promising approach to achieve resilient perception in challenging environmental conditions. However, this may lead to \emph{catastrophic fusion} in the presence of inconsistent data, i.e. when the sensors do not detect the same target due to distinct attenuation properties. It is often difficult to discriminate consistent from inconsistent data across sensing modalities using local spatial information alone. In this paper we present a novel consistency test based on the log marginal likelihood of a Gaussian process model that evaluates data from range sensors in a relative manner. A new data point is deemed to be consistent if the model statistically improves as a result of its fusion. This approach avoids the need for absolute spatial distance threshold parameters as required by previous work. We report results from object reconstruction with both synthetic and experimental data that demonstrate an improvement in reconstruction quality, particularly in cases where data points are inconsistent yet spatially proximal.

Robust face clustering for real-world data

This thesis has investigated how to cluster a large number of faces within a multi-media corpus in the presence of large session variation. Quality metrics are used to select the best faces to represent a sequence of faces; and session variation modelling improves clustering performance in the presence of wide variations across videos. Findings from this thesis contribute to improving the performance of both face verification systems and the fully automated clustering of faces from a large video corpus.

Boarding Control System - for Improved Accessibility to Offshore Wind Turbines

This paper considers the dynamic modelling and motion control of a Surface Effect Ship (SES) for safer transfer of personnel and equipment from vessel to-and-from an offshore wind-turbine. Such a vessel is a key enabling factor for operation and maintenance (O&M) of offshore wind-energy infrastructure. The control system designed is referred to as Boarding Control System (BCS). We investigate the performance of this system for a specific wind-farm service vessel–The Wave Craft. A two-modality vessel model is presented to account for the vessel free motion and motion whilst in contact with a wind-turbine. On a SES, the pressurized air cushion carries the majority of the vessel mass. The control problem considered relates to the actuation of the pressure such that wave-induced vessel motions are minimized. This leads to a safer personnel transfer in developed sea-states than what is possible today. Results for the BCS is presented through simulation and model-scale craft testing.

Relative contributions of light interception and radiation use efficiency to the reduction of maize productivity under cold temperatures

Maize (Zea mays L.) is a chill-susceptible crop cultivated in northern latitude environments. The detrimental effects of cold on growth and photosynthetic activity have long been established. However, a general overview of how important these processes are with respect to the reduction of productivity reported in the field is still lacking. In this study, a model-assisted approach was used to dissect variations in productivity under suboptimal temperatures and quantify the relative contributions of light interception (PARc) and radiation use efficiency (RUE) from emergence to flowering. A combination of architectural and light transfer models was used to calculate light interception in three field experiments with two cold-tolerant lines and at two sowing dates. Model assessment confirmed that the approach was suitable to infer light interception. Biomass production was strongly affected by early sowings. RUE was identified as the main cause of biomass reduction during cold events. Furthermore, PARc explained most of the variability observed at flowering, its relative contributions being more or less important according to the climate experienced. Cold temperatures resulted in lower PARc, mainly because final leaf length and width were significantly reduced for all leaves emerging after the first cold occurrence. These results confirm that virtual plants can be useful as fine phenotyping tools. A scheme of action of cold on leaf expansion, light interception and radiation use efficiency is discussed with a view towards helping breeders define relevant selection criteria. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

Hole Pairing In Antiferromagnetically Correlated Layered Oxides

We have considered a two-band Hubbard model having interlaced Cu-3d(x2−y2) and O-2p(x, y) orbitals representing the CuO2 square planes. Simple CuO2 -cluster calculation suggests that the additional holes created by doping stay mainly on oxygen. Motion of an oxygen hole interlacing with the antiferromagnetically correlated background of copper spins, creates a string of high energy spin configuration of finite length giving mass renormalization. Another hole of opposite spin can now anneal this string tension providing a triangular pairing potential for large pair momentum. The latter implies unusual Bose condensation of the wake-bound compact Bose-like pairs on a non-zero momentum shell. Effect of disorder favouring condensation at the mobility edge is pointed out.

Jump Reorientation of Water Molecules Confined in Narrow Carbon Nanotubes

We used molecular dynamics (MD) simulations to study the reorientational dynamics of water molecules confined inside narrow carbon nanotubes immersed in a bath of water. Our simulations show that the confined water molecules exhibit bistability in their reorientational relaxation, which proceeds by angular jumps between the two stable states. The angular jump of a water molecule in the bulk involves the breaking of a hydrogen bond with one of its neighbors and the formation of a hydrogen bond with a different neighbor. In contrast, the angular jump of a confined water molecule corresponds to an interchange of the two hydrogen atoms that can form a hydrogen bond with the same neighbor. The free energy barrier between these two states is a few k(B)T. The analytic solution of a simplified two-state jump model that qualitatively explains the reorientational behavior observed in simulations is also presented.