Identifying key belief-based targets for promoting regular physical activity among mothers and fathers with young children

We investigated the key beliefs to target in interventions aimed at increasing physical activity (PA) among mothers and fathers of young children. Parents (288 mothers and 292 fathers) completed a Theory of Planned Behaviour belief-based questionnaire and a 1-week follow-up of PA behaviour. We found that a range of behavioural, normative, and control beliefs were significantly correlated with parents’ PA intentions and behaviour, with only a few differences observed in correlations between PA beliefs and intention and behaviour by gender. A range of key beliefs was identified as making independent contributions to parents’ PA intentions; however, the behavioural beliefs about improving parenting practices (β = 0.13), interfering with other commitments (β = −0.29); normative beliefs about people I exercise with (β = 0.20); and control beliefs about lack of time (β = −0.24), inconvenience (β = −0.14), lack of motivation (β = −0.34), were revealed as significant independent predictors of actual PA behaviour. Furthermore, we found that a limited amount of parents already hold these beliefs, suggesting that these key beliefs warrant changing and, therefore, are appropriate targets for subsequent intervention. The current study fills an empirical gap in the PA literature by investigating an at-risk group and using a well established theoretical framework to identify key beliefs that guide parents’ PA decision-making. Overall, we found support for parents being a unique group who hold distinctive behavioural, normative, and control beliefs toward PA. Attention to these key underlying beliefs will assist intervention work aimed at combating inactivity among this at-risk population.

Nonlinear diffusion and exclusion processes with contact interactions

Exclusion processes on a regular lattice are used to model many biological and physical systems at a discrete level. The average properties of an exclusion process may be described by a continuum model given by a partial differential equation. We combine a general class of contact interactions with an exclusion process. We determine that many different types of contact interactions at the agent-level always give rise to a nonlinear diffusion equation, with a vast variety of diffusion functions D(C). We find that these functions may be dependent on the chosen lattice and the defined neighborhood of the contact interactions. Mild to moderate contact interaction strength generally results in good agreement between discrete and continuum models, while strong interactions often show discrepancies between the two, particularly when D(C) takes on negative values. We present a measure to predict the goodness of fit between the discrete and continuous model, and thus the validity of the continuum description of a motile, contact-interacting population of agents. This work has implications for modeling cell motility and interpreting cell motility assays, giving the ability to incorporate biologically realistic cell-cell interactions and develop global measures of discrete microscopic data.

Migration of breast cancer cells : understanding the roles of volume exclusion and cell-to-cell adhesion

We study MCF-7 breast cancer cell movement in a transwell apparatus. Various experimental conditions lead to a variety of monotone and nonmonotone responses which are difficult to interpret. We anticipate that the experimental results could be caused by cell-to-cell adhesion or volume exclusion. Without any modeling, it is impossible to understand the relative roles played by these two mechanisms. A lattice-based exclusion process random-walk model incorporating agent-to-agent adhesion is applied to the experimental system. Our combined experimental and modeling approach shows that a low value of cell-to-cell adhesion strength provides the best explanation of the experimental data suggesting that volume exclusion plays a more important role than cell-to-cell adhesion. This combined experimental and modeling study gives insight into the cell-level details and design of transwell assays.

Addressing childhood obesity through increased physical activity

Obesity is affecting an increasing proportion of children globally. Despite an appreciation that physical activity is essential for the normal growth and development of children and prevents obesity and obesity-related health problems, too few children are physically active. A concurrent problem is that today’s young people spend more time than previous generations did in sedentary pursuits, including watching television and engaging in screen-based games. Active behavior has been displaced by these inactive recreational choices, which has contributed to reductions in activity-related energy expenditure. Implementation of multifactorial solutions considered to offer the best chance of combating these trends is urgently required to redress the energy imbalance that characterizes obesity. The counterproductive ‘shame and blame’ mentality that apportions responsibility for the childhood obesity problem to sufferers, their parents, teachers or health-care providers needs to be changed. Instead, these groups should offer constant support and encouragement to promote appropriate physical activity in children. Failure to provide activity opportunities will increase the likelihood that the children of today will live less healthy (and possibly shorter)lives than their parents.

Models of collective cell spreading with variable cell aspect ratio : a motivation for degenerate diffusion models

Continuum diffusion models are often used to represent the collective motion of cell populations. Most previous studies have simply used linear diffusion to represent collective cell spreading, while others found that degenerate nonlinear diffusion provides a better match to experimental cell density profiles. In the cell modeling literature there is no guidance available with regard to which approach is more appropriate for representing the spreading of cell populations. Furthermore, there is no knowledge of particular experimental measurements that can be made to distinguish between situations where these two models are appropriate. Here we provide a link between individual-based and continuum models using a multi-scale approach in which we analyze the collective motion of a population of interacting agents in a generalized lattice-based exclusion process. For round agents that occupy a single lattice site, we find that the relevant continuum description of the system is a linear diffusion equation, whereas for elongated rod-shaped agents that occupy L adjacent lattice sites we find that the relevant continuum description is connected to the porous media equation (pme). The exponent in the nonlinear diffusivity function is related to the aspect ratio of the agents. Our work provides a physical connection between modeling collective cell spreading and the use of either the linear diffusion equation or the pme to represent cell density profiles. Results suggest that when using continuum models to represent cell population spreading, we should take care to account for variations in the cell aspect ratio because different aspect ratios lead to different continuum models.

Using biological motion to enhance the conspicuity of roadway workers

This study examined whether the conspicuity of road workers at night can be enhanced by distributing retroreflective strips across the body to present a pattern of biological motion (biomotion). Twenty visually normal drivers (mean age = 40.3 years) participated in an experiment conducted at two open-road work sites (one suburban and one freeway) at night-time. At each site, four road workers walked in place wearing a standard road worker night vest either (a) alone, (b) with additional retroreflective strips on thighs, (c) with additional retroreflective strips on ankles and knees, or (d) with additional retroreflective strips on eight moveable joints (full biomotion). Participants, seated in stationary vehicles at three different distances (80 m, 160 m, 240 m), rated the relative conspicuity of the four road workers. Road worker conspicuity was maximized by the full biomotion configuration at all distances and at both sites. The addition of ankle and knee markings also provided significant benefits relative to the standard vest alone. The effects of clothing configuration were more evident at the freeway site and at shorter distances. Overall, the full biomotion configuration was ranked to be most conspicuous and the vest least conspicuous. These data provide the first evidence that biomotion effectively enhances conspicuity of road workers at open-road work sites.

Are Active Australia physical activity questions valid for older adults?

Objective The Active Australia Survey (AAS) is used for physical activity (PA) surveillance in the general Australian adult population, but its validity in older adults has not been evaluated. Our aim was to examine the convergent validity of the AAS questions in older adults. Design The AAS was validated against pedometer step counts as an objective measure of PA, self-reported physical function, and a step-test to assess cardiorespiratory fitness. Method Participants were community-dwelling adults, aged 65-89 y, with the ability to walk 100 m. They completed a self-administered AAS and the step-test in one interview. One week earlier, they completed the Short Form-36 physical function subscale. Between these two interviews, they each wore a YAMAX Digiwalker SW200 pedometer and recorded daily steps. Using the AAS data, daily walking minutes and total PA minutes (walking, moderate-intensity PA and vigorous-intensity PA) were compared with the validity measures using Spearman rank-order correlations. Fifty-three adults completed the study. Results Median daily walking minutes were 34.2 (interquartile range [IQR] 17.1, 60.0), and median daily total PA minutes were 68.6 (IQR 31.4, 113.6). Walking and total PA minutes were both moderately correlated with pedometer steps (Spearman correlation r=0.42, p=0.003, for each) but not with step-test seconds to completion (r=-0.11, p=0.44; r=-0.25, p=0.08, respectively). Total PA minutes were significantly correlated with physical function scores (r=0.39, p=0.004), but walking minutes were not (r=0.15, p=0.29). Conclusions This initial examination of the psychometric properties of the AAS for older adults suggests that this surveillance tool has acceptable convergent validity for ambulatory, community-dwelling older adults.

Physical function and health-related quality of life of older adults undergoing hospital rehabilitation : how strong is the association?

The purpose of this research is to report preliminary empirical evidence regarding the association between common physical performance measures and health-related quality of life (HRQoL) of hospitalized older adults recovering from illness and injury. Frequently, these patients do not return to premorbid levels of independence and physical ability. Rehabilitation for this population often focuses on improving physical functioning and mobility with the intention of maximizing their HRQoL for discharge and thereafter. For this reason, longitudinal use of physical performance measures as an indicator of improvement in physical functioning (and thus HRQoL) is common. Although this is a logical approach, there have been mixed results from previous investigations into the association between common measures of physical function and HRQoL amongst other adult patient populations.1,2 There has been no previous investigation reporting the association between HRQoL and a variety of common physical performance measures in hospitalized older adults.

Digital processing of diffusion-tensor images of avascular tissues

Diffusion is the process that leads to the mixing of substances as a result of spontaneous and random thermal motion of individual atoms and molecules. It was first detected by the English botanist Robert Brown in 1827, and the phenomenon became known as ‘Brownian motion’. More specifically, the motion observed by Brown was translational diffusion – thermal motion resulting in random variations of the position of a molecule. This type of motion was given a correct theoretical interpretation in 1905 by Albert Einstein, who derived the relationship between temperature, the viscosity of the medium, the size of the diffusing molecule, and its diffusion coefficient. It is translational diffusion that is indirectly observed in MR diffusion-tensor imaging (DTI). The relationship obtained by Einstein provides the physical basis for using translational diffusion to probe the microscopic environment surrounding the molecule.

Persistent ocean monitoring with underwater gliders : towards accurate reconstruction of dynamic ocean processes

Ocean processes are dynamic and complex events that occur on multiple different spatial and temporal scales. To obtain a synoptic view of such events, ocean scientists focus on the collection of long-term time series data sets. Generally, these time series measurements are continually provided in real or near-real time by fixed sensors, e.g., buoys and moorings. In recent years, an increase in the utilization of mobile sensor platforms, e.g., Autonomous Underwater Vehicles, has been seen to enable dynamic acquisition of time series data sets. However, these mobile assets are not utilized to their full capabilities, generally only performing repeated transects or user-defined patrolling loops. Here, we provide an extension to repeated patrolling of a designated area. Our algorithms provide the ability to adapt a standard mission to increase information gain in areas of greater scientific interest. By implementing a velocity control optimization along the predefined path, we are able to increase or decrease spatiotemporal sampling resolution to satisfy the sampling requirements necessary to properly resolve an oceanic phenomenon. We present a path planning algorithm that defines a sampling path, which is optimized for repeatability. This is followed by the derivation of a velocity controller that defines how the vehicle traverses the given path. The application of these tools is motivated by an ongoing research effort to understand the oceanic region off the coast of Los Angeles, California. The computed paths are implemented with the computed velocities onto autonomous vehicles for data collection during sea trials. Results from this data collection are presented and compared for analysis of the proposed technique.

Planning and implementing trajectories for autonomous underwater vehicles to track evolving ocean processes based on predictions from a regional ocean model

Path planning and trajectory design for autonomous underwater vehicles (AUVs) is of great importance to the oceanographic research community because automated data collection is becoming more prevalent. Intelligent planning is required to maneuver a vehicle to high-valued locations to perform data collection. In this paper, we present algorithms that determine paths for AUVs to track evolving features of interest in the ocean by considering the output of predictive ocean models. While traversing the computed path, the vehicle provides near-real-time, in situ measurements back to the model, with the intent to increase the skill of future predictions in the local region. The results presented here extend prelim- inary developments of the path planning portion of an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. This extension is the incorporation of multiple vehicles to track the centroid and the boundary of the extent of a feature of interest. Similar algorithms to those presented here are under development to consider additional locations for multiple types of features. The primary focus here is on algorithm development utilizing model predictions to assist in solving the motion planning problem of steering an AUV to high-valued locations, with respect to the data desired. We discuss the design technique to generate the paths, present simulation results and provide experimental data from field deployments for tracking dynamic features by use of an AUV in the Southern California coastal ocean.

Cooperative multi-AUV tracking of phytoplankton blooms based on ocean model predictions

In recent years, ocean scientists have started to employ many new forms of technology as integral pieces in oceanographic data collection for the study and prediction of complex and dynamic ocean phenomena. One area of technological advancement in ocean sampling if the use of Autonomous Underwater Vehicles (AUVs) as mobile sensor plat- forms. Currently, most AUV deployments execute a lawnmower- type pattern or repeated transects for surveys and sampling missions. An advantage of these missions is that the regularity of the trajectory design generally makes it easier to extract the exact path of the vehicle via post-processing. However, if the deployment region for the pattern is poorly selected, the AUV can entirely miss collecting data during an event of specific interest. Here, we consider an innovative technology toolchain to assist in determining the deployment location and executed paths for AUVs to maximize scientific information gain about dynamically evolving ocean phenomena. In particular, we provide an assessment of computed paths based on ocean model predictions designed to put AUVs in the right place at the right time to gather data related to the understanding of algal and phytoplankton blooms.