Computer models of saliency alone fail to predict subjective visual attention to landmarks during observed navigation

This study aimed to understand whether or not computer models of saliency could explain landmark saliency. An online survey was conducted and participants were asked to watch videos from a spatial navigation video game (Sea Hero Quest). Participants were asked to pay attention to the environments within which the boat was moving and to rate the perceived saliency of each landmark. In addition, state-of-the-art computer saliency models were used to objectively quantify landmark saliency. No significant relationship was found between objective and subjective saliency measures. This indicates that during passive observation of an environment while being navigated, current automated models of saliency fail to predict subjective reports of visual attention to landmarks

Entropy and a Sub-Group of Geometric Measures of Paths Predict the Navigability of an Environment

Despite extensive research on navigation, it remains unclear which features of an environment predict how difficult it will be to navigate. We analysed 478,170 trajectories from 10,626 participants who navigated 45 virtual environments in the research app-based game Sea Hero Quest. Virtual environments were designed to vary in a range of properties such as their layout, number of goals, visibility (varying fog) and map condition. We calculated 58 spatial measures grouped into four families: task-specific metrics, space syntax configurational metrics, space syntax geometric metrics, and general geometric metrics. We used Lasso, a variable selection method, to select the most predictive measures of navigation difficulty. Geometric features such as entropy, area of navigable space, number of rings and closeness centrality of path networks were among the most significant factors determining the navigational difficulty. By contrast a range of other measures did not predict difficulty, including measures of intelligibility. Unsurprisingly, other task-specific features (e.g. number of destinations) and fog also predicted navigation difficulty. These findings have implications for the study of spatial behaviour in ecological settings, as well as predicting human movements in different settings, such as complex buildings and transport networks and may aid the design of more navigable environments

Entropy of city street networks linked to future spatial navigation ability

The cultural and geographical properties of the environment have been shown to deeply influence cognition and mental health1-6. Living near green spaces has been found to be strongly beneficial7-11, and urban residence has been associated with a higher risk of some psychiatric disorders12-14-although some studies suggest that dense socioeconomic networks found in larger cities provide a buffer against depression15. However, how the environment in which one grew up affects later cognitive abilities remains poorly understood. Here we used a cognitive task embedded in a video game16 to measure non-verbal spatial navigation ability in 397,162 people from 38 countries across the world. Overall, we found that people who grew up outside cities were better at navigation. More specifically, people were better at navigating in environments that were topologically similar to where they grew up. Growing up in cities with a low street network entropy (for example, Chicago) led to better results at video game levels with a regular layout, whereas growing up outside cities or in cities with a higher street network entropy (for example, Prague) led to better results at more entropic video game levels. This provides evidence of the effect of the environment on human cognition on a global scale, and highlights the importance of urban design in human cognition and brain function

Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study.

BACKGROUND: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. METHODS: Using cognitive testing data and data on functional limitations from Wave A (2001-2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. RESULTS: Our algorithm had a cross-validated predictive accuracy of 88% (86-90), and an area under the curve of 0.97 (0.97-0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3-4) in individuals 70-79, 11% (9-12) in individuals 80-89 years old, and 28% (22-35) in those 90 and older. CONCLUSIONS: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys

The effects of street network configuration and street-level urban design on route choice behaviour: an analysis of elementary school students walking to/from school in istanbul

This paper explores the association between the built environment, measured through street network configuration and street-level urban design, and route choice of children walking to/from school. The aim is to understand the extent to which student's actual route selections correspond with metric shortest routes and the role of spatial factors in explaining route choice in utilitarian walking. Within this context, randomly selected students (ages 12-14) from five elementary schools in Istanbul, Turkey, were asked to draw their routes walking between home and school. Each student's route choice was modelled within a GIS database and metrically shortest routes between origins and destinations were identified by using the 'network analyst' tool. Street network configuration of the entire system was evaluated by using angular segment integration and choice analyses implemented in Depthmap as well as metric and directional reach implemented in GIS. Street-level urban design characteristics of the streets, including ground floor attractions, prevalence and width of sidewalks, street-level topography, street width (indicating street hierarchy), and existence of signalling/crossings, were evaluated through detailed field surveys and high quality satellite images. The preliminary findings of this study imply that the configuration measures of street network may prove to be important variables for the description and modulation of human spatial behaviour in urban environments. More importantly, directional accessibility appears to play an important role as metric accessibility in route choice behaviour. However; the detailed analysis of selected routes indicates that the amount of ground floor attractions as well as certain streetlevel urban design qualities, such as sidewalk width, seem to be related to the preference of certain streets over and above others. This study contributes to the literature by broadening our understanding of the environmental attributes associated with children's navigation choices in utilitarian walking. Findings augment the knowledgebase that supports urban navigation by emphasizing the contribution of the spatial structure of the street network and the impacts of urban design qualities of the street environment

Using a case-control method to explore the impact of lighting on cycle rates: Investigating the choice of case and control time periods.

Comparing the counts of events occurring at different times of day is one approach to measuring the impact of ambient light level on events such as crime, road traffic collisions and travel flows. We investigated the choice of case and control hours on the outcome of analysis of cyclist flows for two cities, Arlington (VA, USA) and Birmingham (UK). The analyses revealed some differences in the estimated odds ratios. While all combinations tended to show a significant effect, there was some variation in effect size, and that could affect the determination of practical relevance. We suggest that future work presents mean odds ratio from all combinations of case and control hour, weighted by the number of events in the case hour

Darkness is a greater deterrent to cycling in suburban than in city centre locations

Odds ratios for the effect of ambient light level on cyclist numbers tend to reveal a variation between counters at different locations. We investigated reasons for this variation through analysis of cycle count data in two cities, Berlin (Germany) and Birmingham (UK). For Berlin, there was a significant increase in the odds ratio with increasing distance from the city centre, but this was not the case for Birmingham. The influence of location was explored, and this suggested that distance from the city centre may be a relevant factor on subsidiary roads but not on roads of a more major type. It was also found that the odds ratio is associated with the numbers of cyclists, and this tends to decrease with distance from the city centre

Targeting and imaging of cancer cells using nanomaterials

The combination of many nanomaterials and biological components gives the researchers the advantages of both. Recognizing the properties of biocomponents provides selectivity and sensitivity. On the other hand mechanical, catalytical and optical features of nanomaterials make possible the implementation of biomaterials in different fields. Nanomaterials covered with biological materials have great potential in a variety of applications such as bio-detection technologies, targeting and imaging of cancer cells, biofuel cells, food and beverage industry, etc. The use of nanomaterials in medical imaging is increasing rapidly. In this chapter, we provide a brief description of nanomaterials, such as nanoparticles, dendrimers, carbon nanotubes, quantum dots, vesicular systems, and the decoration techniques of nanomaterials with a variety of biological molecules to prepare nanocarrier systems and the use of the obtained nanobiomaterials in targeting and visualization of cancer cells. © 2016 Elsevier Inc. All rights reserved.

Entropy of city street networks linked to future spatial navigation ability.

The cultural and geographical properties of the environment have been shown to deeply influence cognition and mental health1-6. Living near green spaces has been found to be strongly beneficial7-11, and urban residence has been associated with a higher risk of some psychiatric disorders12-14-although some studies suggest that dense socioeconomic networks found in larger cities provide a buffer against depression15. However, how the environment in which one grew up affects later cognitive abilities remains poorly understood. Here we used a cognitive task embedded in a video game16 to measure non-verbal spatial navigation ability in 397,162 people from 38 countries across the world. Overall, we found that people who grew up outside cities were better at navigation. More specifically, people were better at navigating in environments that were topologically similar to where they grew up. Growing up in cities with a low street network entropy (for example, Chicago) led to better results at video game levels with a regular layout, whereas growing up outside cities or in cities with a higher street network entropy (for example, Prague) led to better results at more entropic video game levels. This provides evidence of the effect of the environment on human cognition on a global scale, and highlights the importance of urban design in human cognition and brain function

Entropy and a sub-group of geometric measures of paths predict the navigability of an environment

Despite extensive research on navigation, it remains unclear which features of an environment predict how difficult it will be to navigate. We analysed 478,170 trajectories from 10,626 participants who navigated 45 virtual environments in the research app-based game Sea Hero Quest. Virtual environments were designed to vary in a range of properties such as their layout, number of goals, visibility (varying fog) and map condition. We calculated 58 spatial measures grouped into four families: task-specific metrics, space syntax configurational metrics, space syntax geometric metrics, and general geometric metrics. We used Lasso, a variable selection method, to select the most predictive measures of navigation difficulty. Geometric features such as entropy, area of navigable space, number of rings and closeness centrality of path networks were among the most significant factors determining the navigational difficulty. By contrast a range of other measures did not predict difficulty, including measures of intelligibility. Unsurprisingly, other task-specific features (e.g. number of destinations) and fog also predicted navigation difficulty. These findings have implications for the study of spatial behaviour in ecological settings, as well as predicting human movements in different settings, such as complex buildings and transport networks and may aid the design of more navigable environments