Impact of average household income and damage exposure on post-earthquake distress and functioning: A community study following the February 2011 Christchurch earthquake.

Post-traumatic stress, depression and anxiety symptoms are common outcomes following earthquakes, and may persist for months and years. This study systematically examined the impact of neighbourhood damage exposure and average household income on psychological distress and functioning in 600 residents of Christchurch, New Zealand, 4–6 months after the fatal February, 2011 earthquake. Participants were from highly affected and relatively unaffected suburbs in low, medium and high average household income areas. The assessment battery included the Acute Stress Disorder Scale, the depression module of the Patient Health Questionnaire (PHQ-9), and the Generalized Anxiety Disorder Scale (GAD-7), along with single item measures of substance use, earthquake damage and impact, and disruptions in daily life and relationship functioning. Controlling for age, gender and social isolation, participants from low income areas were more likely to meet diagnostic cut-offs for depression and anxiety, and have more severe anxiety symptoms. Higher probabilities of acute stress, depression and anxiety diagnoses were evident in affected versus unaffected areas, and those in affected areas had more severe acute stress, depression and anxiety symptoms. An interaction between income and earthquake effect was found for depression, with those from the low and medium income affected suburbs more depressed. Those from low income areas were more likely, post-earthquake, to start psychiatric medication and increase smoking. There was a uniform increase in alcohol use across participants. Those from the low income affected suburb had greater general and relationship disruption post-quake. Average household income and damage exposure made unique contributions to earthquake-related distress and dysfunction.

Experimental Investigation of the Detection of Bridge Dynamic Parameters using a Moving Vehicle

This paper investigates the feasibility of using an instrumented vehicle to detect bridge dynamic parameters, such as natural frequency and structural damping, in a scaled laboratory experiment. In the experiment, a scaled vehicle model crosses a steel girder which has been adopted as the bridge model. The bridge model also includes a scaled road surface profile. The effects of varying vehicle model mass and speed are investigated. The damping of the girder is also varied. The bridge frequency and changes in damping are detected in the vehicle acceleration response in the presence of a rough road surface profile.

Dynamic axle force and road profile identification using a moving vehicle

The axle forces applied by a vehicle through its wheels are a critical part of the interaction between vehicles, pavements and bridges. Therefore, the minimisation of these forces is important in order to promote long pavement life spans and ensure that bridge loads are small. Moreover, as the road surface roughness affects the vehicle dynamic forces, the monitoring of pavements for highways and bridges is an important task. This paper presents a novel algorithm to identify these dynamic interaction forces which involves direct instrumentation of a vehicle with accelerometers. The ability of this approach to predict the pavement roughness is also presented. Moving force identification theory is applied to a vehicle model in theoretical simulations in order to obtain the interaction forces and pavement roughness from the measured accelerations. The method is tested for a range of bridge spans in simulations and the influence of road roughness level on the accuracy of the results is investigated. Finally, the challenge for the real-world problem is addressed in a laboratory experiment.

Moving Out of Conflict: Negotiating Social Identity in Response to Segregation in Northern Ireland

This paper examines the impact of territoriality on young people’s everyday experiences in Northern Ireland’s segregated communities. It shows how urban encounters are reproduced through negotiating differences and the ways in which living in divided communities escalates moods of social inequality and spatial imbalances. The empirical study undertaken in the city of Derry shows how individuals and community groups position and identify themselves under the impact of social segregation. Building on Gordon Allport’s (1954) theories of contact, I explain how people in Derry have established their own sense of belonging, of who they are, based on their group memberships which eventually became an important source of pride and selfesteem. They also presented their own intertextual references as a cause of routine survival and belonging, allowing them to be more constructive about their future. Under deeply rooted segregation in Northern Ireland, the young generations are sought to provide lasting change to foster peace and integration between the two communities.

Generating Realistic Labelled, Weighted Random Graphs

Generative algorithms for random graphs have yielded insights into the structure and evolution of real-world networks. Most networks exhibit a well-known set of properties, such as heavy-tailed degree distributions, clustering and community formation. Usually, random graph models consider only structural information, but many real-world networks also have labelled vertices and weighted edges. In this paper, we present a generative model for random graphs with discrete vertex labels and numeric edge weights. The weights are represented as a set of Beta Mixture Models (BMMs) with an arbitrary number of mixtures, which are learned from real-world networks. We propose a Bayesian Variational Inference (VI) approach, which yields an accurate estimation while keeping computation times tractable. We compare our approach to state-of-the-art random labelled graph generators and an earlier approach based on Gaussian Mixture Models (GMMs). Our results allow us to draw conclusions about the contribution of vertex labels and edge weights to graph structure.

Electron-impact ionization of diatomic molecules using a configuration-average distorted-wave method

Electron-impact ionization cross sections for diatomic molecules are calculated in a configuration-average distorted-wave method. Core bound orbitals for the molecular ion are calculated using a single-configuration self-consistent-field method based on a linear combination of Slater-type orbitals. The core bound orbitals are then transformed onto a two-dimensional (r,θ) numerical lattice from which a Hartree potential with local exchange is constructed. The single-particle Schrödinger equation is then solved for the valence bound orbital and continuum distorted-wave orbitals with S-matrix boundary conditions. Total cross section results for H2 and N2 are compared with those from semiempirical calculations and experimental measurements.

Real-Time Multiple Event Detection and Classification Using Moving Window PCA

This paper proposes a method for the detection and classification of multiple events in an electrical power system in real-time, namely; islanding, high frequency events (loss of load) and low frequency events (loss of generation). This method is based on principal component analysis of frequency measurements and employs a moving window approach to combat the time-varying nature of power systems, thereby increasing overall situational awareness of the power system. Numerical case studies using both real data, collected from the UK power system, and simulated case studies, constructed using DigSilent PowerFactory, for islanding events, as well as both loss of load and generation dip events, are used to demonstrate the reliability of the proposed method.

Navigation in dynamic environments taking advantage of moving agents

Esta tese propõe uma forma diferente de navegação de robôs em ambientes dinâmicos, onde o robô tira partido do movimento de pedestres, com o objetivo de melhorar as suas capacidades de navegação. A ideia principal é que, ao invés de tratar as pessoas como obstáculos dinâmicos que devem ser evitados, elas devem ser tratadas como agentes especiais com conhecimento avançado em navegação em ambientes dinâmicos. Para se beneficiar do movimento de pedestres, este trabalho propõe que um robô os selecione e siga, de modo que possa mover-se por caminhos ótimos, desviar-se de obstáculos não detetados, melhorar a navegação em ambientes densamente populados e aumentar a sua aceitação por outros humanos. Para atingir estes objetivos, novos métodos são desenvolvidos na área da seleção de líderes, onde duas técnicas são exploradas. A primeira usa métodos de previsão de movimento, enquanto a segunda usa técnicas de aprendizagem por máquina, para avaliar a qualidade de candidatos a líder, onde o treino é feito com exemplos reais. Os métodos de seleção de líder são integrados com algoritmos de planeamento de movimento e experiências são realizadas para validar as técnicas propostas.

The Jordan canonical form for a class of weighted directed graphs

Recently, Cardon and Tuckfield (2011) [1] have described the Jordan canonical form for a class of zero-one matrices, in terms of its associated directed graph. In this paper, we generalize this result to describe the Jordan canonical form of a weighted adjacency matrix A in terms of its weighted directed graph.

An evaluation of the accuracy of models for the determination of the weighted mean temperature of the atmosphere

The estimates of the zenith wet delay resulting from the analysis of data from space techniques, such as GPS and VLBI, have a strong potential in climate modeling and weather forecast applications. In order to be useful to meteorology, these estimates have to be converted to precipitable water vapor, a process that requires the knowledge of the weighted mean temperature of the atmosphere, which varies both in space and time. In recent years, several models have been proposed to predict this quantity. Using a database of mean temperature values obtained by ray-tracing radiosonde profiles of more than 100 stations covering the globe, and about 2.5 year’s worth of data, we have analyzed several of these models. Based on data from the European region, we have concluded that the models provide identical levels of precision, but different levels of accuracy. Our results indicate that regionally-optimized models do not provide superior performance compared to the global models.

A vision system for detecting paths and moving obstacles for the blind

In this paper we present a monocular vision system for a navigation aid. The system assists blind persons in following paths and sidewalks, and it alerts the user to moving obstacles which may be on collision course. Path borders and the vanishing point are de-tected by edges and an adapted Hough transform. Opti-cal flow is detected by using a hierarchical, multi-scale tree structure with annotated keypoints. The tree struc-ture also allows to segregate moving objects, indicating where on the path the objects are. Moreover, the centre of the object relative to the vanishing point indicates whether an object is approaching or not.

Average age of pending and disposed cases report for period 7/1/2012 thru 6/30/2013

This gives the average age of pending and disposes criminal cases broken down by county and circuit.