Conflict and Consensus

There are widely differing conceptions as to whether healthy social relations are, in essence, conflictual or consensual; such differences give rise to different approaches to finding peace and managing power. This article outlines the two broad schools of thought from conflict theory (in which society functions through competition) and consensus theory (which sees society developing through cooperation). It outlines the middle ground between them, as found by pluralism and agonism, before considering the ways in which assumptions vis-a-vis conflict and consensus are reflected in different models of democratic system and, in particular, different priorities for post-conflict recovery.

Possible binary progenitors for the Type Ib supernova iPTF13bvn

Cao et al. reported a possible progenitor detection for the Type Ib supernovae iPTF13bvn for the first time. We find that the progenitor is in fact brighter than the magnitudes previously reported by approximately 0.7-0.2 mag with a larger error in the bluer filters. We compare our new magnitudes to our large set of binary evolution models and find that many binary models with initial masses in the range of 10-20M(circle dot) match this new photometry and other constraints suggested from analysing the supernova. In addition, these lower mass stars retain more helium at the end of the model evolution indicating that they are likely to be observed as Type Ib supernovae rather than their more massive, Wolf-Rayet counter parts. We are able to rule out typical Wolf-Rayet models as the progenitor because their ejecta masses are too high and they do not fit the observed SED unless they have a massive companion which is the observed source at the supernova location. Therefore only late-time observations of the location will truly confirm if the progenitor was a helium giant and not a Wolf-Rayet star.

Deep Salience: Visual Salience Modeling via Deep Belief Propagation

Visual salience is an intriguing phenomenon observed in biological neural systems. Numerous attempts have been made to model visual salience mathematically using various feature contrasts, either locally or globally. However, these algorithmic models tend to ignore the problem’s biological solutions, in which visual salience appears to arise during the propagation of visual stimuli along the visual cortex. In this paper, inspired by the conjecture that salience arises from deep propagation along the visual cortex, we present a Deep Salience model where a multi-layer model based on successive Markov random fields (sMRF) is proposed to analyze the input image successively through its deep belief propagation. As a result, the foreground object can be automatically separated from the background in a fully unsupervised way. Experimental evaluation on the benchmark dataset validated that our Deep Salience model can consistently outperform eleven state-of-the-art salience models, yielding the higher rates in the precision-recall tests and attaining the best F-measure and mean-square error in the experiments.

Impact of Free Glasses and a Teacher Incentive on Children's Use of Eyeglasses: A Cluster-Randomized Controlled Trial.

Purpose: To study the effect of free glasses combined with teacher incentives on in-school glasses wear among Chinese urban migrant children. Design: Cluster-randomized controlled trial. Methods: Children with VA <= 6/12 in either eye due to refractive error in 94 randomly-chosen primary schools underwent randomization by school to receive free glasses, education on their use and a teacher incentive (Intervention), or glasses prescriptions only (Control). Intervention group teachers received a tablet computer if >= 80% of children given glasses wore them during un-announced visits 6 weeks and 6 months (main outcome) after intervention. Results: Among 4376 children, 728 (16.7%, mean age 10.9 years, 51.0% boys) met enrollment criteria and were randomly allocated, 358 (49.2%, 47 schools) to Intervention and 370 (50.8%, 47 schools) to Control. Among these, 693 children (95.2%) completed the study and underwent analysis. Spectacle wear was significantly higher at 6 months among Intervention children (Observed [main outcome]: 68.3% versus 23.9%, Adjusted Odds Ratio [OR]=11.5, 95% Confidence Interval [CI] 5.91-22.5, P<0.001; Self-reported: 90.6% versus 32.1%, OR = 43.7, 95% CI = 21.7-88.5, P < 0.001). Other predictors of observed wear at 6 months included baseline spectacle wear (P<0.001), uncorrected VA<6/18 (P=0.01) and parental spectacle wear (P=0.02). The 6-month observed wear rate was only 41% among similar-aged children provided free glasses in our previous trial without teacher incentives. Conclusions: Free spectacles and teacher incentives maintain classroom wear in the large majority of children needing glasses over a school year. Low wear among Control children demonstrates the need for interventions.

Walking the City:No more motorways for Belfast

Streets are key elements of urban space; they are in essence public spaces and connect diverse areas of the city weaving the urban fabric. Once motorways replace existing streets, they tear the fabric and transform the qualities of the urban landscape. As in many cities throughout the world, in Belfast during the 1960s the growth of private car ownership took over the development of the city. The Roads Authority developed plans (1964/1969) to build a ring road surrounding most of the city. This deeply affected the use and shape of the city until today. This plan focused on encouraging the move of population to the outskirts of the city. However, the connections between the city centre and its surrounding neighbourhoods were broken. Only the southern stretch of the motorway was not built. This allowed the connection between South Belfast and the city centre to remain seamless. The current possibility of building the southern stretch of motorway threatens this continuity. This paper will highlight the very high value of streets by analysing their physical qualities.

Predicting impact damage, residual strength and crashworthiness of composite structures

The development of the latest generation of wide-body carbon-fibre composite passenger aircraft has heralded a new era in the utilisation of these materials. The premise of superior specific strength and stiffness, corrosion and fatigue resistance, is tempered by high development costs, slow production rates and lengthy and expensive certification programmes. Substantial effort is currently being directed towards the development of new modelling and simulation tools, at all levels of the development cycle, to mitigate these shortcomings. One of the primary challenges is to reduce the extent of physical testing, in the certification process, by adopting a ‘certification by simulation’ approach. In essence, this aspirational objective requires the ability to reliably predict the evolution and progression of damage in composites. The aerospace industry has been at the forefront of developing advanced composites modelling tools. As the automotive industry transitions towards the increased use of composites in mass-produced vehicles, similar challenges in the modelling of composites will need to be addressed, particularly in the reliable prediction of crashworthiness. While thermoset composites have dominated the aerospace industry, thermoplastics composites are likely to emerge as the preferred solution for meeting the high-volume production demands of passenger road vehicles. This keynote presentation will outline recent progress and current challenges in the development of finite-element-based predictive modelling tools for capturing impact damage, residual strength and energy absorption capacity of thermoset and thermoplastic composites for crashworthiness assessments.

Spiking neural network connectivity and its potential for temporal sensory processing and variable binding

The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well-understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modeling of neural circuits found in the brain.

Spiking Neural Network Connectivity and its Potential for Temporal Sensory Processing and Variable Binding

The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modelling of neural circuits found in the brain. In recent years, much of the focus in neuron modelling has moved to the study of the connectivity of spiking neural networks. Spiking neural networks provide a vehicle to understand from a computational perspective, aspects of the brain’s neural circuitry. This understanding can then be used to tackle some of the historically intractable issues with artificial neurons, such as scalability and lack of variable binding. Current knowledge of feed-forward, lateral, and recurrent connectivity of spiking neurons, and the interplay between excitatory and inhibitory neurons is beginning to shed light on these issues, by improved understanding of the temporal processing capabilities and synchronous behaviour of biological neurons. This research topic aims to amalgamate current research aimed at tackling these phenomena.

Ultralow voltage resonant tunnelling diode electroabsorption modulator

Embedding a double barrier resonant tunnelling diode (RTD) in a unipolar InGaAlAs optical waveguide gives rise to a very low driving voltage electroabsorption modulator (EAM) at optical wavelengths around 1550 nm. The presence of the RTD within the waveguide core introduces high non- linearity and negative di erential resistance in the current±voltage (I±V) characteristic of the waveguide. This makes the electric ®eld distribution across the waveguide core strongly dependent on the bias voltage: when the current decreases from the peak to the valley, there is an increase of the electric ®eld across the depleted core. The electric ®eld enhancement in the core-depleted layer causes the Franz±Keldysh absorption band-edge to red shift, which is responsible for the electroabsorption e ect. High-frequency ac signals as low as 100mV can induce electric ®eld high-speed switching, producing substantial light modulation (up to 15 dB) at photon energies slightly lower than the waveguide core band-gap energy. The key di erence between this device and conventional p-i-n EAMs is that the tunnelling characteristics of the RTD are employed to switch the electric ®eld across the core-depleted region; the RTD- EAM has in essence an integrated electronic ampli®er and, therefore, requires considerably less switching power.

Literacia de escrita em candidatos de RVCC

Trabalho de projecto de mestrado, Ciências da Educação (Formação de Adultos), Universidade de Lisboa, Instituto de Educação, 2011

The transformation of landscape as as aesthetic idear

The present study seeks to thoroughly investigate and delineate the concept alongside the transformation of landscape as an aesthetic idea. On the one side it runs that nature perceived as landscape remains nothing else but granted, evident or 'natural'. On yet another side, and to some fairly significant extend, this thesis identifies landscape as a sheer idea and concept that is shaped and (re-)mediated in an ongoing process. The thesis examines the role of the observer and brings into agreement that every landscape is a produce of creative mental processes. In brief outline, this approach provides a framework for identifying landscape as being inextricably linked with media from the very beginning of their social and cultural inception. As glowing examples for the paradigmatic shift of the classical subjective vision model culminating in the emergence of a new prototype, the camera obscura, together with the panorama, fortify the prevailing argument that the mode of human sense perception is organised and determined by earlier acquainted recognitions. In this matter, as each and every medium strive after accomplishment, then this accomplishment is substantially determined by overwhelming historic, as well as thriving cultural circumstances. In conclusive terms, this study seeks to show how landscape counts as content of a representation, while simultaneously being a very own medium that specifically carries social, geological as well as historic knowledge. In fact, modern vision shall therefore never be bound to any single format or process, rather it will have to always undergo procedures aiming at reshaping the perceivable. Landscape is playing out its major characteristic, specifically that of being, in essence, a purely intellectual, virtual and synthetic product

Nonlinear Phase Filtering Effects on GNSS Receiver Positioning Accuracy

This paper demonstrates nonlinear phase filtering effects on GNSS receiver accuracy. Using a nonlinear phase filter in a GNSS receiver can change the pseudorange estimation up to 250 metres which introduces an error in the overall positioning calculation. Paper shows the study of the nonlinear phase filtering effects on the pseudorange estimation and demonstrates how it can be compensated with minimal hardware usage.

Intersubjectivity and poetic translation

O artigo está disponível em livre acesso no link da versão do editor

Da docência de estagiário em história e geografia ao papel do erro na avaliação e na aprendizagem

Mestrado, Ensino de História e Geografia no 3.º Ciclo do Ensino Básico e no Ensino Secundário, 10 de Março de 2016, Universidade dos Açores (Relatório de Estágio).

Estimação de cobertura rádio em GSM-R através de redes neuronais

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Eletrónica e Telecomunicações