Body mass index has risen more steeply in tall than in short 3-year olds: serial cross-sectional surveys 1988-2003

Objective: To monitor the changing relationship between body mass index ( BMI) and height in young children.Design: Annual cross-sectional surveys using health-visitor-collected routine data 1988 - 2003.Setting: Wirral, England.Participants: Fifty thousand four hundred and fifty-five children ( 49% female) each measured once at the age of 3 years.Main outcome measures: Weight, height and derived BMI ( weight/height(2)) adjusted for age and sex ( British 1990 revised reference) using standard deviation scores.Results: From 1988 to 2003, mean BMI increased by 0.7 kg/m(2), whereas mean height fell by 0.5 cm. Over the same period, the weight - height correlation rose from 0.59 to 0.71 ( P < 0.0001) owing to BMI increasing faster in the taller than the shorter children. Among the shortest 10% of children, mean BMI rose by 0.12 ( 95% confidence interval: - 0.05 - 0.28) kg/m(2) as against 1.38 ( 1.19 - 1.56) kg/m(2) among the tallest 10%, a 12-fold difference. Adjustment for age, sex, seasonality, birth-weight and deprivation did not alter the findings.Conclusions: Among 3-year-old children in Wirral, where BMI has been rising for 16 years, the largest increase in BMI has occurred in the tallest children, whereas in the shortest BMI has hardly changed. Tall stature has, therefore, become important for child obesity. It suggests a drive to increasing adiposity in young children that involves both growth and appetite, with fast growing and hungrier children now more exposed to the 'obesogenic' environment

Occupant–vehicle dynamics and the role of the internal model

With the increasing need to reduce time and cost of vehicle development there is increasing advantage in simulating mathematically the dynamic interaction of a vehicle and its occu- pant. The larger design space arising from the introduction of automated vehicles further increases the potential advantage. The aim of the paper is to outline the role of the internal model hypothesis in understanding and modelling occupant-vehicle dynamics, specifically the dynamics associated with direction and speed control of the vehicle. The internal model is the driver’s or passenger’s understanding of the vehicle dynamics and is thought to be employed in the perception, cognition and action processes of the brain. The internal model aids the estimation of the states of the vehicle from noisy sensory measurements. It can also be used to optimise cognitive control action by predicting the consequence of the action; thus model predictive control theory (MPC) provides a foundation for modelling the cognition process. The stretch reflex of the neuromuscular system also makes use of the prediction of the internal model. Extensions to the MPC approach are described which account for: interaction with an automated vehicle; robust control; intermittent control; and cognitive workload. Further work to extend understanding of occupant-vehicle dynamic interaction is outlined. This paper is based on a keynote presentation given by the author to the 13th International Symposium on Advanced Vehicle Control (AVEC) conference held in Munich, September 2016

Game-theoretic modeling of the steering interaction between a human driver and a vehicle collision avoidance controller

Development of vehicle active steering collision avoidance systems calls for mathematical models capable of predicting a human driver’s response so as to reduce the cost involved in field tests whilst accelerate product development. This article provides a discussion on the paradigms that may be used for modelling a driver’s steering interaction with vehicle collision avoidance control in path-following scenarios. Four paradigms, namely decentralized, noncooperative Nash, noncooperative Stackelberg and cooperative Pareto are established. The decentralized paradigm, developed based on optimal control theory, represents a driver’s interaction with the collision avoidance controllers that disregard driver steering control. The noncooperative Nash and Stackelberg paradigms are used for predicting a driver’s steering behaviour in response to the collision avoidance control that actively compensates for driver steering action. These two are devised based on the principles of equilibria in noncooperative game theory. The cooperative Pareto paradigm is derived from cooperative game theory to model a driver’s interaction with the collision avoidance systems that take into account the driver’s target path. The driver and the collision avoidance controllers’ optimization problems and their resulting steering strategies arise in each paradigm are delineated. Two mathematical approaches applicable to these optimization problems, namely the distributed Model Predictive Control and the Linear Quadratic dynamic optimization approaches are described in some detail. A case study illustrating a conflict in steering control between driver and vehicle collision avoidance system is performed via simulation. It was found that variation of driver path-error cost function weights results in a variety of steering behaviours which are distinct between paradigms.This is the accepted manuscript. The final version is available from IEEE at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6951458&refinements%3D4262294079%26sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A7008592%29

Measurement and mathematical model of a driver's intermittent compensatory steering control

The compensatory (feedback) component of a human driver's steering control is examined. In particular the effect of the cognitive process is studied. Model predictive control theory is used to implement models of intermittency in cognitive processing. Experiments using a fixed-base driving simulator with periodic occlusion of the visual display are used to reveal the nature of the driver's steering behaviour. An intermittent serial-ballistic control strategy is found to match the measured behaviour better than intermittent zero-order hold or continuous control. The findings may enable some insight to driver-vehicle interaction and vehicle handling qualities.This work was supported by the Engineering and Physical Sciences Research Council (EP/P505445/1); the Qualcomm European Research Studentship Fund in Technology; and the Lotus F1 Team (RG61664).This is the final version of the article. It first appeared from Taylor & Francis via http://dx.doi.org/10.1080/00423114.2015.110074

Measurement and Modeling of the Effect of Sensory Conflicts on Driver Steering Control

In previous work, a new model of driver steering control incorporating sensory dynamics was derived and used to explain the performance of drivers in a simulator with full-scale motion feedback. This paper describes further experiments investigating how drivers steer with conflicts between their visual and vestibular measurements, caused by scaling or filtering the physical motion of the simulator relative to the virtual environment. The predictions of several variations of the new driver model are compared with the measurements to understand how drivers perceive sensory conflicts. Drivers are found to adapt well in general, unless the conflict is large, in which case they ignore the physical motion and rely on visual measurements. Drivers make greater use of physical motion which they rate as being more helpful, achieving a better tracking performance. Sensory measurement noise is shown to be signal-dependent, allowing a single set of parameters to be found to fit the results of all the trials. The model fits measured linear steering behavior with an average “variance accounted for (VAF)” of 86%.EPSRC EP/P505445/

Identification and validation of a driver steering control model incorporating human sensory dynamics

Most existing models of driver steering control do not consider the driver's sensory dynamics, despite many aspects of human sensory perception having been researched extensively. The authors recently reported development of a driver model that incorporates sensory transfer functions, noise and delays. The present paper reports the experimental identification and validation of this model. An experiment was carried out with five test subjects in a driving simulator, aiming to replicate a real-world driving scenario with no motion scaling. The results of this experiment are used to identify parameter values for the driver model, and the model is found to describe the results of the experiment well. Predicted steering angles match the linear component of measured results with an average `variance accounted for' of 98% using separate parameter sets for each trial, and 93% with a single fixed parameter set. The identified parameter values are compared with results from the literature and are found to be physically plausible, supporting the hypothesis that driver steering control can be predicted using models of human perception and control mechanisms

Development of a novel model of driver-vehicle steering control incorporating sensory dynamics

This is the author accepted manuscript. The final version is available from CRC Press via http://dx.doi.org/10.1201/b21185-8A novel model of driver steering control is proposed, incorporating models of the driver’s sensory dynamics and limitations. The model is based on the hypothesis that the driver’s steering strategy minimises an internal cost function optimally based on the noisy, delayed information received from the sensory systems. Published results from experiments carried out on pilots were used to identify parameter values for the new model, and to assess the validity of the new modelling approach. The new model was found to fit the results very well, with variance accounted for (VAF) values greater than 90% for all but one trial. The model was found to fit the results almost as well with a single fixed set of parameter values as with separate parameter values for each trial, indicating that a fixed-parameter model is able to predict variations in control behaviour under different conditions.EPSR

Dynamics of Micropollutant Adsorption to Polystyrene Surfaces Probed by Angle-Resolved Second Harmonic Scattering

Angle-resolved second harmonic scattering is used to probe the adsorption dynamics of aqueous cationic and anionic dye molecules onto polystyrene surfaces. The adsorptions of malachite green to negatively charged polystyrene and naphthol yellow S to positively charged polystyrene are both highly favorable, with Î"GAds values of -10.9 ± 0.2 and -10.27 ± 0.09 kcal/mol, respectively. A competitive displacement methodology was employed to obtain values for the adsorption free energies of various smaller neutral organic molecules, including the important micropollutant ascorbic acid, caffeine, and pentoxifylline. For charged adsorbers, electrostatic interactions appear to significantly contribute to adsorption behavior. However, electrostatic repulsion does not necessarily deter the adsorption of molecules with large uncharged moieties (e.g., surfactants). In these cases, the mechanism of adsorption is dominated by van der Waals interactions, with the surface charge playing a relatively minor role

Nonlinear network model analysis of vibrational energy transfer and localisation in the Fenna-Matthews-Olson complex

Collective protein modes are expected to be important for facilitating energy transfer in the Fenna-Matthews-Olson (FMO) complex of photosynthetic green sulphur bacteria, however to date little work has focussed on the microscopic details of these vibrations. The nonlinear network model (NNM) provides a computationally inexpensive approach to studying vibrational modes at the microscopic level in large protein structures, whilst incorporating anharmonicity in the inter-residue interactions which can influence protein dynamics. We apply the NNM to the entire trimeric FMO complex and find evidence for the existence of nonlinear discrete breather modes. These modes tend to transfer energy to the highly connected core pigments, potentially opening up alternative excitation energy transfer routes through their influence on pigment properties. Incorporating localised modes based on these discrete breathers in the optical spectra calculations for FMO using ab initio site energies and excitonic couplings can substantially improve their agreement with experimental results.A.W.C. and S.E.M. acknowledge support from the Winton Programme for the Physics of Sustainability. S.E.M. is also supported by an EPSRC doctoral training award. D.J.C. is supported by a Marie Curie International Outgoing Fellowship within the seventh European Community Framework Programme

A guide to integrating immunohistochemistry and chemical imaging

© 2018 The Royal Society of Chemistry. Chemical imaging provides new insight into the fundamental atomic, molecular, and biochemical composition of tissue and how they are interrelated in normal physiology. Visualising and quantifying products of pathogenic reactions long before structural changes become apparent also adds a new dimension to understanding disease pathogenesis. While chemical imaging in isolation is somewhat limited by the nature of information it can provide (e.g. peptides, metals, lipids, or functional groups), integrating immunohistochemistry allows simultaneous, targeted imaging of biomolecules while also mapping tissue composition. Together, this approach can provide invaluable information on the inner workings of the cell and the molecular basis of diseases