Public disorder and transport networks in the Latin American context

We propose an extension of the Davies et al. model, used to describe the London riots of 2011. This addition allows us to consider long travel distances in a city for potential rioting population. This is achieved by introducing public transport networks, which modifies the perceived travel distance between the population and likely targets. Using this more general formulation, we applied the model to the typical Griffin and Ford pattern for population distribution to describe the general features of most large Latin American cities. The possibility of long-range traveling by part of the general population has, for an immediate consequence, the existence of isolated spots more prone to suffer from rioting activity, as they are easier to reach than the rest of the city. These areas finally made it easier to control the eventual disorder by part of police forces. The reason for this outcome is that transport networks turn riots into highly localized and intense events. They are attracting a large police contingent, which will later extinguish the remaining disorder activity on the rest of the city. Therefore, working transport networks in a city effectively reduces the number of police force contingent required to control public disorder. This result, we must remark, is valid only if the model requisites for order forces are satisfied: extra police contingent can be added swiftly as required, and these forces can move around the city with total freedom

Multiangle observations of Arctic clouds from FIRE ACE: June 3, 1998, case study

In May and June 1998 the Airborne Multiangle Imaging Spectroradiometer (AirMISR) participated in the FIRE Arctic Cloud Experiment (ACE). AirMISR is an airborne instrument for obtaining multiangle imagery similar to that of the satellite-borne MISR instrument. This paper presents a detailed analysis of the data collected on June 3, 1998. In particular, AirMISR radiance measurements are compared with measurements made by two other instruments, the Cloud Absorption Radiometer (CAR) and the MODIS airborne simulator (MAS), as well as to plane-parallel radiative transfer simulations. It is found that the AirMISR radiance measurements and albedo estimates compare favorably both with the other instruments and with the radiative transfer simulations. In addition to radiance and albedo, the multiangle AirMISR data can be used to obtain estimates of cloud top height using stereoimaging techniques. Comparison of AirMISR retrieved cloud top height (using the complete MISR-based stereoimaging approach) shows excellent agreement with the measurements from the airborne Cloud Lidar System (CLS) and ground-based millimeterwave cloud radar

Spatio-temporal modelling for issues in crime and security

The distribution of incidents in time and space is a central issue in the study of crime, for both theoretical and practical reasons. It is also a context in which quantitative analysis and modelling has significant potential value: such research represents a means by which the implications of theory can be examined rigorously, and can also provide tools which support both policing and policy-making. The nature of the field, however, presents a number of challenges, particularly with regard to the incorporation of complex environmental factors and the modelling of individual-level behaviour. In this thesis, the techniques of complexity science are used to overcome these issues, and the approach is demonstrated using a number of examples from a range of crime types. The thesis begins by presenting a network-based framework for the analysis of spatio-temporal clustering. It is demonstrated that signature `motifs' can be identified in patterns of offending for burglary and maritime piracy, and that the technique provides a more nuanced characterisation of clustering than existing approaches. Analysis is then presented of the relationship between street network structure and the distribution of urban crime. It is shown that burglary risk is predicted by the graph-theoretic properties of street segments; in particular, those which correspond to levels of street usage. It is further demonstrated that the `near-repeat' phenomenon in burglary displays a form of directionality, which can be reconciled with a novel street network metric. These results are then used to inform a mathematical model of burglary, which is situated on a network and which may be used for prediction. This model is analysed and its behaviour characterised in terms of urban form. Finally, a model is presented for a contrasting crime problem, the London riots of 2011, and used to examine a number of policy questions

A dynamic spatial model of conflict escalation

In both historical and modern conflicts, space plays a critical role in how interactions occur over time. Despite its importance, the spatial distribution of adversaries has often been neglected in mathematical models of conflict. In this paper, we propose an entropy-maximising spatial interaction method for disaggregating the impact of space, employing a general notion of ‘threat’ between two adversaries. This approach addresses a number of limitations that are associated with partial differential equation approaches to spatial disaggregation. We use this method to spatially disaggregate the Richardson model of conflict escalation, and then explore the resulting model with both analytical and numerical treatments. A bifurcation is identified that dramatically influences the resulting spatial distribution of conflict and is shown to persist under a range of model specifications. Implications of this finding for real-world conflicts are discussed

Modelling patterns of burglary on street networks

A fundamental issue in crime prevention is the efficient deployment of resources and the effective targeting of interventions, both of which require some form of prediction of future crime. One crime for which this is feasible is burglary, the distinctive spatio-temporal signatures of which can be exploited to inform predictions. Mathematical models in particular are capable of both encoding concisely the theoretical foundations of criminal behaviour and allowing the quantitative analysis of specific scenarios, and their capacity to reproduce the general patterns of burglary suggests that the approach has considerable potential. Previous models, however, are situated on simplified representations of space and do not reflect realistically the built environment in which crime takes place; specifically, they do not incorporate urban street networks. Such networks are fundamental to situational theories of crime, in the sense that they determine the configuration of urban space and, therefore, shape those human activity patterns which are thought to give rise to crime. Furthermore, streets are the natural domain for many policing activities, and their structure is determined by planning decisions, so that insight into their relationship with crime is likely to be of immediate practical use. With this in mind, this paper presents a mathematical model of crime which is explicitly situated on a street network. After discussing theoretical considerations and specifying the model itself, examples of typical networks are explored

A spatial model for conflict incorporating within- and between-actor effects

The application of ecological models to human conflict scenarios has given rise to a number of models which describe antagonistic relationships between adversaries. Recent work demonstrates that the spatial disaggregation of such models is not only well-motivated but also gives rise to interesting dynamic behaviour, particularly with respect to the spatial distribution of resources. One feature which is largely absent from previous models, however, is the ability of an adversary to coordinate activity across its various locations. Most immediately, this corresponds to the notion of `support' - the reallocation of resources from one site to another according to need - which plays an important role in real-world conflict. In this paper, we generalise a spatially-disaggregated form of the classic Richardson model of conflict escalation by adding a cross-location interaction term for the within-adversary dynamics at each location. We explore the model analytically, giving conditions for the stability of the balanced equilibrium state. We then also carry out a number of numerical simulations which correspond to stylised real-world conflict scenarios. Potential further applications of the model, and its implications for policy, are then discussed

The effects of cannabidiol on impulsivity and memory during abstinence in cigarette dependent smokers

This is the final version of the article. Available from Springer Nature via the DOI in this record.The dataset generated during the current study are available from the corresponding author on reasonable request.Acute nicotine abstinence in cigarette smokers results in deficits in performance on specific cognitive processes, including working memory and impulsivity which are important in relapse. Cannabidiol (CBD), the non-intoxicating cannabinoid found in cannabis, has shown pro-cognitive effects and preliminary evidence has indicated it can reduce the number of cigarettes smoked in dependent smokers. However, the effects of CBD on cognition have never been tested during acute nicotine withdrawal. The present study therefore aimed to investigate if CBD can improve memory and reduce impulsivity during acute tobacco abstinence. Thirty, non-treatment seeking, dependent, cigarette smokers attended two laboratory-based sessions after overnight abstinence, in which they received either 800 mg oral CBD or placebo (PBO), in a randomised order. Abstinence was biologically verified. Participants were assessed on go/no-go, delay discounting, prose recall and N-back (0-back, 1-back, 2-back) tasks. The effects of CBD on delay discounting, prose recall and the N-back (correct responses, maintenance or manipulation) were null, confirmed by a Bayesian analysis, which found evidence for the null hypothesis. Contrary to our predictions, CBD increased commission errors on the go/no-go task. In conclusion, a single 800 mg dose of CBD does not improve verbal or spatial working memory, or impulsivity during tobacco abstinence.This research was funded by a PhD Studentship from the Medical Research Council (MRC) to the C.H. and an MRC DPFS award (MR/K015524/1) to HVC and CJAM.TPF is funded by a Senior Academic Fellowship from the Society for the Study of Addiction