Identifying constraints on children with movement difficulties : implications for pedagogues and clinicians

A constraints- based framework for understanding processes of movement coordination and control is predicated on a range of theoretical ideas including the work of Bernstein (1967), Gibson (1979), Newell (1986) and Kugler, Kelso & Turvey (1982). Contrary to a normative perspective that focuses on the production of idealized movement patterns to be acquired by children during development and learning (see Alain & Brisson, 1986), this approach formulates the emergence of movement co- ordination as a function of the constraints imposed upon each individual. In this framework, cognitive, perceptual and movement difficulties and disorders are considered to be constraints on the perceptual- motor system, and children’s movements are viewed as emergent functional adaptations to these constraints (Davids et al., 2008; Rosengren, Savelsbergh & van der Kamp, 2003). From this perspective, variability of movement behaviour is not viewed as noise or error to be eradicated during development, but rather, as essentially functional in facilitating the child to satisfy the unique constraints which impinge on his/her developing perceptual- motor and cognitive systems in everyday life (Davids et al., 2008). Recently, it has been reported that functional neurobiological variability is predicated on system degeneracy, an inherent feature of neurobiological systems which facilitates the achievement of task performance goals in a variety of different ways (Glazier & Davids, 2009). Degeneracy refers to the capacity of structurally different components of complex movement systems to achieve different performance outcomes in varying contexts (Tononi et al., 1999; Edelman & Gally, 2001). System degeneracy allows individuals with and without movement disorders to achieve their movement goals by harnessing movement variability during performance. Based on this idea, perceptual- motor disorders can be simply viewed as unique structural and functional system constraints which individuals have to satisfy in interactions with their environments. The aim of this chapter is to elucidate how the interaction of structural and functional organismic, and environmental constraints can be harnessed in a nonlinear pedagogy by individuals with movement disorders.

The 2008 Tibet riots : perspectives, divided group protests and divergent media narratives

Awareness of the power of the mass media to communicate images of protest to global audiences and, in so doing, to capture space in global media discourses is a central feature of the transnational protest movement. A number of protest movements have formed around opposition to concepts and practices that operate beyond national borders, such as neoliberal globalization or threats to the environment. However, transnational protests also involve more geographically discreet issues such as claims to national independence or greater religious or political freedom by groups within specific national contexts. Appealing to the international community for support is a familiar strategy for communities who feel that they are being discriminated against or ignored by a national government.

Facial expression recognition using facial movement features

Facial expression is an important channel for human communication and can be applied in many real applications. One critical step for facial expression recognition (FER) is to accurately extract emotional features. Current approaches on FER in static images have not fully considered and utilized the features of facial element and muscle movements, which represent static and dynamic, as well as geometric and appearance characteristics of facial expressions. This paper proposes an approach to solve this limitation using ‘salient’ distance features, which are obtained by extracting patch-based 3D Gabor features, selecting the ‘salient’ patches, and performing patch matching operations. The experimental results demonstrate high correct recognition rate (CRR), significant performance improvements due to the consideration of facial element and muscle movements, promising results under face registration errors, and fast processing time. The comparison with the state-of-the-art performance confirms that the proposed approach achieves the highest CRR on the JAFFE database and is among the top performers on the Cohn-Kanade (CK) database.

Car following model improvement for traffic safety metrics reproduction

Car Following models have a critical role in all microscopic traffic simulation models. Current microscopic simulation models are unable to mimic the unsafe behaviour of drivers as most are based on presumptions about the safe behaviour of drivers. Gipps model is a widely used car following model embedded in different micro-simulation models. This paper examines the Gipps car following model to investigate ways of improving the model for safety studies application. The paper puts forward some suggestions to modify the Gipps model to improve its capabilities to simulate unsafe vehicle movements (vehicles with safety indicators below critical thresholds). The result of the paper is one step forward to facilitate assessing and predicting safety at motorways using microscopic simulation. NGSIM as a rich source of vehicle trajectory data for a motorway is used to extract its relatively risky events. Short following headways and Time To Collision are used to assess critical safety event within traffic flow. The result shows that the modified proposed car following to a certain extent predicts the unsafe trajectories with smaller error values than the generic Gipps model.

Krylov subspace approximations for the exponential Euler method: Error estimates and the harmonic Ritz approximant

We study Krylov subspace methods for approximating the matrix-function vector product φ(tA)b where φ(z) = [exp(z) - 1]/z. This product arises in the numerical integration of large stiff systems of differential equations by the Exponential Euler Method, where A is the Jacobian matrix of the system. Recently, this method has found application in the simulation of transport phenomena in porous media within mathematical models of wood drying and groundwater flow. We develop an a posteriori upper bound on the Krylov subspace approximation error and provide a new interpretation of a previously published error estimate. This leads to an alternative Krylov approximation to φ(tA)b, the so-called Harmonic Ritz approximant, which we find does not exhibit oscillatory behaviour of the residual error.

Geometry vs appearance for discriminating between posed and spontaneous emotions

Spontaneous facial expressions differ from posed ones in appearance, timing and accompanying head movements. Still images cannot provide timing or head movement information directly. However, indirectly the distances between key points on a face extracted from a still image using active shape models can capture some movement and pose changes. This information is superposed on information about non-rigid facial movement that is also part of the expression. Does geometric information improve the discrimination between spontaneous and posed facial expressions arising from discrete emotions? We investigate the performance of a machine vision system for discrimination between posed and spontaneous versions of six basic emotions that uses SIFT appearance based features and FAP geometric features. Experimental results on the NVIE database demonstrate that fusion of geometric information leads only to marginal improvement over appearance features. Using fusion features, surprise is the easiest emotion (83.4% accuracy) to be distinguished, while disgust is the most difficult (76.1%). Our results find different important facial regions between discriminating posed versus spontaneous version of one emotion and classifying the same emotion versus other emotions. The distribution of the selected SIFT features shows that mouth is more important for sadness, while nose is more important for surprise, however, both the nose and mouth are important for disgust, fear, and happiness. Eyebrows, eyes, nose and mouth are important for anger.

Business cycle dynamics with duration dependence and leading indicators

Durland and McCurdy [Durland, J.M., McCurdy, T.H., 1994. Duration-dependent transitions in a Markov model of US GNP growth. Journal of Business and Economic Statistics 12, 279–288] investigated the issue of duration dependence in US business cycle phases using a Markov regime-switching approach, introduced by Hamilton [Hamilton, J., 1989. A new approach to the analysis of time series and the business cycle. Econometrica 57, 357–384] and extended to the case of variable transition parameters by Filardo [Filardo, A.J., 1994. Business cycle phases and their transitional dynamics. Journal of Business and Economic Statistics 12, 299–308]. In Durland and McCurdy’s model duration alone was used as an explanatory variable of the transition probabilities. They found that recessions were duration dependent whilst expansions were not. In this paper, we explicitly incorporate the widely-accepted US business cycle phase change dates as determined by the NBER, and use a state-dependent multinomial Logit modelling framework. The model incorporates both duration and movements in two leading indexes – one designed to have a short lead (SLI) and the other designed to have a longer lead (LLI) – as potential explanatory variables. We find that doing so suggests that current duration is not only a significant determinant of transition out of recessions, but that there is some evidence that it is also weakly significant in the case of expansions. Furthermore, we find that SLI has more informational content for the termination of recessions whilst LLI does so for expansions.

Can audio-visual speech recognition outperform acoustically enhanced speech recognition in automotive environment?

The use of visual features in the form of lip movements to improve the performance of acoustic speech recognition has been shown to work well, particularly in noisy acoustic conditions. However, whether this technique can outperform speech recognition incorporating well-known acoustic enhancement techniques, such as spectral subtraction, or multi-channel beamforming is not known. This is an important question to be answered especially in an automotive environment, for the design of an efficient human-vehicle computer interface. We perform a variety of speech recognition experiments on a challenging automotive speech dataset and results show that synchronous HMM-based audio-visual fusion can outperform traditional single as well as multi-channel acoustic speech enhancement techniques. We also show that further improvement in recognition performance can be obtained by fusing speech-enhanced audio with the visual modality, demonstrating the complementary nature of the two robust speech recognition approaches.

Computational approaches for modelling intrinsic noise and delays in genetic regulatory networks

This chapter focuses on the interactions and roles between delays and intrinsic noise effects within cellular pathways and regulatory networks. We address these aspects by focusing on genetic regulatory networks that share a common network motif, namely the negative feedback loop, leading to oscillatory gene expression and protein levels. In this context, we discuss computational simulation algorithms for addressing the interplay of delays and noise within the signaling pathways based on biological data. We address implementational issues associated with efficiency and robustness. In a molecular biology setting we present two case studies of temporal models for the Hes1 gene (Monk, 2003; Hirata et al., 2002), known to act as a molecular clock, and the Her1/Her7 regulatory system controlling the periodic somite segmentation in vertebrate embryos (Giudicelli and Lewis, 2004; Horikawa et al., 2006).

Modeling intrinsic noise and delays in chemical kinetics of coupled autoregulated oscillating cells

Delays are an important feature in temporal models of genetic regulation due to slow biochemical processes, such as transcription and translation. In this paper, we show how to model intrinsic noise effects in a delayed setting by either using a delay stochastic simulation algorithm (DSSA) or, for larger and more complex systems, a generalized Binomial τ-leap method (Bτ-DSSA). As a particular application, we apply these ideas to modeling somite segmentation in zebra fish across a number of cells in which two linked oscillatory genes (her1 and her7) are synchronized via Notch signaling between the cells.

DEM test, visagraph eye movement recordings, and reading ability in children

Purpose. To determine how Developmental Eye Movement (DEM) test results relate to reading eye movement patterns recorded with the Visagraph in visually normal children, and whether DEM results and recorded eye movement patterns relate to standardized reading achievement scores. Methods. Fifty-nine school-age children (age = 9.7 ± 0.6 years) completed the DEM test and had eye movements recorded with the Visagraph III test while reading for comprehension. Monocular visual acuity in each eye and random dot stereoacuity were measured and standardized scores on independently administered reading comprehension tests [reading progress test (RPT)] were obtained. Results. Children with slower DEM horizontal and vertical adjusted times tended to have slower reading rates with the Visagraph (r = -0.547 and -0.414 respectively). Although a significant correlation was also found between the DEM ratio and Visagraph reading rate (r = -0.368), the strength of the relationship was less than that between DEM horizontal adjusted time and reading rate. DEM outcome scores were not significantly associated with RPT scores. When the relative contribution of reading ability (RPT) and DEM scores was accounted for in multivariate analysis, DEM outcomes were not significantly associated with Visagraph reading rate. RPT scores were associated with Visagraph outcomes of duration of fixations (r = -0.403) and calculated reading rate (r = 0.366) but not with DEM outcomes. Conclusions.DEM outcomes can identify children whose Visagraph recorded eye movement patterns show slow reading rates. However, when reading ability is accounted for, DEM outcomes are a poor predictor of reading rate. Visagraph outcomes of duration of fixation and reading rate relate to standardized reading achievement scores; however, DEM results do not. Copyright © 2011 American Academy of Optometry.

Evolving genetic regulatory networks performing as stochastic switches

Recent studies have shown that small genetic regulatory networks (GRNs) can be evolved in silico displaying certain dynamics in the underlying mathematical model. It is expected that evolutionary approaches can help to gain a better understanding of biological design principles and assist in the engineering of genetic networks. To take the stochastic nature of GRNs into account, our evolutionary approach models GRNs as biochemical reaction networks based on simple enzyme kinetics and simulates them by using Gillespie’s stochastic simulation algorithm (SSA). We have already demonstrated the relevance of considering intrinsic stochasticity by evolving GRNs that show oscillatory dynamics in the SSA but not in the ODE regime. Here, we present and discuss first results in the evolution of GRNs performing as stochastic switches.