Development and application of a "spray-can" tool for fuzzy geographical analysis

Most information generated by the general public, particularly for the purpose of decision-support, will inherently contain a spatial component. This spatial data can comprise a very valuable resource for researchers, planners and decision makers, and may be collected for analysis using a Public Participation GIS (PPGIS). The imprecise and abstract nature of the thoughts, feelings and opinions of the public do not, however, lend themselves well to the discrete boundaries enforced by ‘traditional’ GIS data constructs (points, lines and polygons), and as such require data structures that allow for the ‘fuzzy’ nature of these data to be incorporated into their capture, storage and analysis. This paper therefore presents a web-based PPGIS platform with a ‘spray-can’ interface for the capture of fuzzy spatial data; and a relational ‘multi-point-and-attribute’ data structure, which reflects the fuzzy nature of the data, whilst supporting flexible spatial and attribute querying. Whilst the idea of the spray-can interface is not itself novel, the platform demonstrated in this paper has the potential to improve the decision-making process in a number of different areas at a variety of different scales. This is achieved by both increasing levels of interaction with the public through the familiar and user-friendly spray-can interface; and increasing the level of understanding of the spatial and aspatial information that participants contribute, by maximising the potential analytical approaches that may be taken

Visualizing patterns in spatially ambiguous point data

As technologies permitting both the creation and retrieval of data containing spatial information continue to develop, so do the number of visualisations using such data. This spatial information will often comprise a place-name that may be ‘geocoded’ into coordinates, and displayed on a map, frequently using a ‘heatmap-style’ visualisation to reveal patterns in the data. Across a dataset, however, there is often ambiguity in the geographic scale to which a place-name refers (country, county, town, street etc.), and attempts to simultaneously map data at a multitude of different scales will result in the formation of ‘false hotspots’ within the map. These form at the centres of administrative areas (countries, counties, towns etc.) and introduce erroneous patterns into the dataset whilst obscuring real ones, resulting in misleading visualisations of the patterns in the dataset. This paper therefore proposes a new algorithm to intelligently redistribute data that would otherwise contribute to these ‘false hotspots’, removing them to locations that likely reflect real-world patterns at a homogenous scale, and so allow more representative visualisations to be created, without the negative effects of ‘false hotspots’ resulting from multi-scale data. This technique demonstrated on a sample dataset taken from Twitter, and validated against the ‘geotagged’ portion of the same dataset

Testing a Dynamic Perspective of Goal Orientation During Complex Skill Acquisition and Adaptation to Unforeseen Change

In the context of learning a dynamic task involving cognitive and perceptual-motor demands, this laboratory study contributed to a multilevel perspective of goal orientation and performance by examining adaptation to a novel and unforeseen change. Repeated measures and discontinuous mixed-effects growth modeling were used to disentangle within- from between-person effects of mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance goal orientation dimensions on performance. At the within-person level, this study failed to replicate previous findings of goal orientation effects corresponding to resource allocation theory. At the between-person level, results were consistent with prior research such that mastery-approach and performance-approach facilitated performance, whereas performance-avoidance hindered it. A positive effect of mastery-avoidance on performance was also found. There were no interactions between goal orientation and adaptation trajectories, suggesting that main effects of goal orientation are stable across changes in task demand. This research contributes toward theories of self-regulation and active learning, and questions the extent to which a dynamic approach for understanding the effects of goal orientation is necessary

Who makes better decisions? The relative importance of numeracy and cognitive abilities for elements of decision making

The rapidly changing nature of work has increased the importance of non-routine thinking skills required to make decisions under risk and uncertainty. Cognitive ability tests are traditionally considered a robust tool for personnel selection and placement, provided how they assess thinking skills that generalize across many jobs. Tests are often designed to measure general cognitive ability, which is conceptualized as the foundation of higher-order thinking skills. However, other studies have suggested that tests of specific abilities are useful as well. There is growing evidence that numeracy, defined as the ability to apply mathematics in practice, is a strong predictor of decision-making skills. However, much remains to be examined in terms of numeracy’s usefulness as a predictor relative to commonly used cognitive ability tests. In this dissertation, I review decision-making competence as a multidimensional performance criterion, in which each of its dimensions have implications for workplace decisions. Using a sample of 355 undergraduate students who completed a battery of assessments, I estimated the relative importance of crystallized ability, fluid ability, and statistical numeracy for predicting overall decision-making competence and the dimensions that comprise it. This study builds on previous incremental validation studies by adopting dominance analysis to partition criterion variance. Numeracy was consistently a superior predictor over fluid ability, whereas the relative importance of numeracy and crystallized ability varied across dimensions. These results contribute to a growing literature on statistical numeracy as an important part of decision-making that is underrepresented in traditional cognitive ability tests. Implications are discussed with respect to the importance of leveraging numeracy in personnel selection and training systems for jobs that require decision-making competence

Mapping traffic pollution exposure:the quantified self

The purpose of this paper is to apply recent developments in the areas of the ‘Quantified Self’ and the ‘Internet of Things’ in order to explore the use of low-cost sensors for the collection of a variety of spatially-referenced biometric and environmental data from participants. This is achieved using a specially designed application on the Android mobile platform, which has been developed for this project in order to log serial sensor data via USB against GPS location and timestamp, allowing the spatio-temporal mapping of a variety of personal data. In this case, traffic pollution data is collected and compared with a measures of nasal airflow, permitting an estimate of exposure to traffic pollution for an individual on a given journey. These data will be fed back to individuals in order to assess the level of correlation with their reported perception of exposure to pollution, as well the extent to which this influences subsequent behaviour; such as whether or not an individual will modify their route for a given journey based upon their new knowledge of pollution levels. In this way, personal pollution exposure can be empirically monitored at the individual level, allowing for a more in-depth understanding of these issues than has so far been possible

Beyond the blandscape:utilizing aesthetics in digital cartography

Despite the rich design history within the field of cartography, the majority of digital maps exhibit a dominant aesthetic that is primarily designed to serve the usability and utility requirements of turn-by-turn urban navigation producing a so-called ‘blandscape’ of map design. In this research we consider not only how to produce more visually appealing digital maps, but also how the cartographic decisions made in the production of maps can influence behavior, particularly with regard to the encouragement of explorative experiences. Novel cartographic and technological solutions are therefore presented, which address exploration using digital maps in the context of location based gaming and tourism. These examples demonstrate the potential of digital cartography to influence behavior and the importance of aesthetics in the cartographic process

Combining physiological, environmental and locational sensors for citizen-oriented health applications

This work investigates the potential of combining the outputs of multiple low-cost sensor technologies for the direct measurement of spatio-temporal variations in phenomena that exist at the interface between our bodies and the environment. The example used herein is the measurement of personal exposure to traffic pollution, which may be considered as a function of the concentration of pollutants in the air and the frequency and volume of that air which enters our lungs. The sensor-based approach described in this paper removes the ‘traditional’ requirements either to model or interpolate pollution levels or to make assumptions about the physiology of an individual. Rather, a wholly empirical analysis into pollution exposure is possible, based upon high-resolution spatio-temporal data drawn from sensors for NO2, nasal airflow and location (GPS). Data are collected via a custom smartphone application and mapped to give an unprecedented insight into exposure to traffic pollution at the individual level. Whilst the quality of data from low-cost miniaturised sensors is not suitable for all applications, there certainly are many applications for which these data would be well suited, particularly those in the field of citizen science. This paper demonstrates both the potential and limitations of sensor-based approaches and discusses the wider relevance of these technologies for the advancement of citizen science

Targeting extracellular lectins of Pseudomonas aeruginosa with glycomimetic liposomes

The antimicrobial resistance crisis requires novel approaches for the therapy of infections especially with Gram-negative pathogens. Pseudomonas aeruginosa is defined as priority 1 pathogen by the WHO and thus of particular interest. Its drug resistance is primarily associated with biofilm formation and essential constituents of its extracellular biofilm matrix are the two lectins, LecA and LecB. Here, we report microbial lectin-specific targeted nanovehicles based on liposomes. LecA- and LecB-targeted phospholipids were synthesized and used for the preparation of liposomes. These liposomes with varying surface ligand density were then analyzed for their competitive and direct lectin binding activity. We have further developed a microfluidic device that allowed the optical detection of the targeting process to the bacterial lectins. Our data showed that the targeted liposomes are specifically binding to their respective lectin and remain firmly attached to surfaces containing these lectins. This synthetic and biophysical study provides the basis for future application in targeted antibiotic delivery to overcome antimicrobial resistance

Targeting extracellular lectins of Pseudomonas aeruginosa with glycomimetic liposomes

The antimicrobial resistance crisis requires novel approaches for the therapy of infections especially with Gram-negative pathogens. Pseudomonas aeruginosa is defined as priority 1 pathogen by the WHO and thus of particular interest. Its drug resistance is primarily associated with biofilm formation and essential constituents of its extracellular biofilm matrix are the two lectins, LecA and LecB. Here, we report microbial lectin-specific targeted nanovehicles based on liposomes. LecA- and LecB-targeted phospholipids were synthesized and used for the preparation of liposomes. These liposomes with varying surface ligand density were then analyzed for their competitive and direct lectin binding activity. We have further developed a microfluidic device that allowed the optical detection of the targeting process to the bacterial lectins. Our data showed that the targeted liposomes are specifically binding to their respective lectin and remain firmly attached to surfaces containing these lectins. This synthetic and biophysical study provides the basis for future application in targeted antibiotic delivery to overcome antimicrobial resistance

Dynamic Transcription of Distinct Classes of Endogenous Retroviral Elements Marks Specific Populations of Early Human Embryonic Cells

SummaryAbout half of the human genome consists of highly repetitive elements, most of which are considered dispensable for human life. Here, we report that repetitive elements originating from endogenous retroviruses (ERVs) are systematically transcribed during human early embryogenesis in a stage-specific manner. Our analysis highlights that the long terminal repeats (LTRs) of ERVs provide the template for stage-specific transcription initiation, thereby generating hundreds of co-expressed, ERV-derived RNAs. Conversion of human embryonic stem cells (hESCs) to an epiblast-like state activates blastocyst-specific ERV elements, indicating that their activity dynamically reacts to changes in regulatory networks. In addition to initiating stage-specific transcription, many ERV families contain preserved splice sites that join the ERV segment with non-ERV exons in their genomic vicinity. In summary, we find that ERV expression is a hallmark of cellular identity and cell potency that characterizes the cell populations in early human embryos