Optical interconnection of core and metro networks

A network concept is introduced that exploits transparent optical grooming of traffic between an access network and a metro core ring network. This network is enabled by an optical router that allows bufferless aggregation of metro network traffic into higher-capacity data streams for core network transmission. A key functionality of the router is WDM to time-division multiplexing (TDM) transmultiplexing.

Forecasting the UK/US exchange rate with divisia monetary models and neural networks

This paper compares the UK/US exchange rate forecasting performance of linear and nonlinear models based on monetary fundamentals, to a random walk (RW) model. Structural breaks are identified and taken into account. The exchange rate forecasting framework is also used for assessing the relative merits of the official Simple Sum and the weighted Divisia measures of money. Overall, there are four main findings. First, the majority of the models with fundamentals are able to beat the RW model in forecasting the UK/US exchange rate. Second, the most accurate forecasts of the UK/US exchange rate are obtained with a nonlinear model. Third, taking into account structural breaks reveals that the Divisia aggregate performs better than its Simple Sum counterpart. Finally, Divisia-based models provide more accurate forecasts than Simple Sum-based models provided they are constructed within a nonlinear framework.

Innovation and policy networks:the social shaping of BSE-related technologies and the inadequate assessmant of related risks

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR CONSULTATION

Combining deformable templates and neural networks for HCR

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Spillovers from FDI and local networks:the importance of transactional linkages and vertical keiretsu in Japan

Purpose – The purpose of this paper is to explore the importance of host country networks and organisation of production in the context of international technology transfer that accompanies foreign direct investment (FDI). Design/methodology/approach – The empirical analysis is based on unbalanced panel data covering Japanese firms active in two-digit manufacturing sectors over a seven-year period. Given the self-selection problem affecting past sectoral-level studies, using firm-level panel data is a prerequisite to provide robust empirical evidence. Findings – While Japan is thought of as being a technologically advanced country, the results show that vertical productivity spillovers from FDI occur in Japan, but they are sensitive to technological differences between domestic firms and the idiosyncratic Japanese institutional network. FDI in vertically organised keiretsu sectors generates inter-industry spillovers through backward and forward linkages, while FDI within sectors linked to vertical keiretsu activities adversely affects domestic productivity. Overall, our results suggest that the role of vertical keiretsu is more prevalent than that of horizontal keiretsu. Originality/value – Japan’s industrial landscape has been dominated by institutional clusters or networks of inter-firm organisations through reciprocated, direct and indirect ties. However, interactions between inward investors and such institutionalised networks in the host economy are seldom explored. The role and characteristics of local business groups, in the form of keiretsu networks, have been investigated to determine the scale and scope of spillovers from inward FDI to Japanese establishments. This conceptualisation depends on the institutional mechanism and the market structure through which host economies absorb and exploit FDI.

Multi-Agent Information Processing and Adaptive Control in Global Telecommunication and Computer Networks

The problems and methods for adaptive control and multi-agent processing of information in global telecommunication and computer networks (TCN) are discussed. Criteria for controllability and communication ability (routing ability) of dataflows are described. Multi-agent model for exchange of divided information resources in global TCN has been suggested. Peculiarities for adaptive and intelligent control of dataflows in uncertain conditions and network collisions are analyzed.

Amyloid β 1-42 induces hypometabolism in human stem cell-derived neuron and astrocyte networks

Alzheimer's disease (AD) is the most common form of dementia, affecting more than 35 million people worldwide. Brain hypometabolism is a major feature of AD, appearing decades before cognitive decline and pathologic lesions. To date, the majority of studies on hypometabolism in AD have used transgenic animal models or imaging studies of the human brain. As it is almost impossible to validate these findings using human tissue, alternative models are required. In this study, we show that human stem cell-derived neuron and astrocyte cultures treated with oligomers of amyloid beta 1-42 (Aβ1-42) also display a clear hypometabolism, particularly with regard to utilization of substrates such as glucose, pyruvate, lactate, and glutamate. In addition, a significant increase in the glycogen content of cells was also observed. These changes were accompanied by changes in NAD+ /NADH, ATP, and glutathione levels, suggesting a disruption in the energy-redox axis within these cultures. The high energy demands associated with neuronal functions such as memory formation and protection from oxidative stress put these cells at particular risk from Aβ-induced hypometabolism. Further research using this model may elucidate the mechanisms associated with Aβ-induced hypometabolism.

Networked gentrification:placemaking strategies and social networks of middle class gentrifiers in Istanbul

This chapter explores how gentrifiers in Istanbul mobilise their social networks and social capital during the gentrification process, and how their networks are constructed through processes of “ place making” and belonging. In addition, this chapter aims to demonstrate how social capital and social networks work in practice during the gentrification process. It also examines place making and claiming strategies of gentrifiers by focusing on the following questions: (a) What are the spatial strategies of the new middle class, and what is the importance of these strategies?; (b) How are class and spatial boundaries designated in gentrified neighbourhoods?; (c) What kinds of networks and relationships play a role in developing certain housing dispositions or belonging patterns

Sustainability and Community Networks

Community networks are IP-based computer networks that are operated by a community as a common good. In Europe, the most well-known community networks are Guifi in Catalonia, Freifunk in Berlin, Ninux in Italy, Funkfeuer in Vienna and the Athens Wireless Metropolitan Network in Greece. This paper deals with community networks as alternative forms of Internet access and alternative infrastructures and asks: What does sustainability and unsustainability mean in the context of community networks? What advantages do such networks have over conventional forms of Internet access and infrastructure provided by large telecommunications corporations? In addition what disadvantages do they face at the same time? This article provides a framework for thinking dialectically about the un/sustainability of community networks. It provides a framework of practical questions that can be asked when assessing power structures in the context of Internet infrastructures and access. It presents an overview of environmental, economic, political and cultural contradictions that community networks may face as well as a typology of questions that can be asked in order to identify such contradictions.

Digitizing dissent: cyborg politics and fluid networks in contemporary Cuban activism

Communication technologies shape how political activist networks are produced and maintain themselves. In Cuba, despite ideologically and physically oppressive practices by the state, a severe lack of Internet access, and extensive government surveillance, a small network of bloggers and cyberactivists has achieved international visibility and recognition for its critiques of the Cuban government. This qualitative study examines the blogger collective known as Voces Cubanas in Havana, Cuba in 2012, advancing a new approach to the study of transnational activism and the role of technology in the construction of political narrative. Voces Cubanas is analyzed as a network of connections between human and non-human actors that produces and sustains powerful political alliances. Voces Cubanas and its allies work collectively to co-produce contentious political discourses, confronting the dominant ideologies and knowledges produced by the Cuban state. Transnational alliances, the act of translation, and a host of unexpected and improvised technologies play central roles in the production of these narratives, indicating new breed of cyborg sociopolitical action reliant upon fluid and flexible networks and the act of writing. 

Undersampled Critical Branching Processes on Small-World and Random Networks Fail to Reproduce the Statistics of Spike Avalanches

The power-law size distributions obtained experimentally for neuronal avalanches are an important evidence of criticality in the brain. This evidence is supported by the fact that a critical branching process exhibits the same exponent t~3=2. Models at criticality have been employed to mimic avalanche propagation and explain the statistics observed experimentally. However, a crucial aspect of neuronal recordings has been almost completely neglected in the models: undersampling. While in a typical multielectrode array hundreds of neurons are recorded, in the same area of neuronal tissue tens of thousands of neurons can be found. Here we investigate the consequences of undersampling in models with three different topologies (two-dimensional, small-world and random network) and three different dynamical regimes (subcritical, critical and supercritical). We found that undersampling modifies avalanche size distributions, extinguishing the power laws observed in critical systems. Distributions from subcritical systems are also modified, but the shape of the undersampled distributions is more similar to that of a fully sampled system. Undersampled supercritical systems can recover the general characteristics of the fully sampled version, provided that enough neurons are measured. Undersampling in two-dimensional and small-world networks leads to similar effects, while the random network is insensitive to sampling density due to the lack of a well-defined neighborhood. We conjecture that neuronal avalanches recorded from local field potentials avoid undersampling effects due to the nature of this signal, but the same does not hold for spike avalanches. We conclude that undersampled branching-process-like models in these topologies fail to reproduce the statistics of spike avalanches.

Exploring social representations of adapting to climate change using topic modeling and Bayesian networks

When something unfamiliar emerges or when something familiar does something unexpected people need to make sense of what is emerging or going on in order to act. Social representations theory suggests how individuals and society make sense of the unfamiliar and hence how the resultant social representations (SRs) cognitively, emotionally, and actively orient people and enable communication. SRs are social constructions that emerge through individual and collective engagement with media and with everyday conversations among people. Recent developments in text analysis techniques, and in particular topic modeling, provide a potentially powerful analytical method to examine the structure and content of SRs using large samples of narrative or text. In this paper I describe the methods and results of applying topic modeling to 660 micronarratives collected from Australian academics / researchers, government employees, and members of the public in 2010-2011. The narrative fragments focused on adaptation to climate change (CC) and hence provide an example of Australian society making sense of an emerging and conflict ridden phenomena. The results of the topic modeling reflect elements of SRs of adaptation to CC that are consistent with findings in the literature as well as being reasonably robust predictors of classes of action in response to CC. Bayesian Network (BN) modeling was used to identify relationships among the topics (SR elements) and in particular to identify relationships among topics, sentiment, and action. Finally the resulting model and topic modeling results are used to highlight differences in the salience of SR elements among social groups. The approach of linking topic modeling and BN modeling offers a new and encouraging approach to analysis for ongoing research on SRs.

I film therefore I am: process and participation, networks and knowledge – examples from Scottish community media projects.

This chapter examines community media projects in Scotland as social processes that nurture knowledge through participation in production. A visual and media anthropology framework (Ginsburg, 2005) with an emphasis on the social context of media production informs the analysis of community media. Drawing on community media projects in the Govan area of Glasgow and the Isle of Bute, the techniques of production foreground “the relational aspects of filmmaking” (Grimshaw and Ravetz, 2005: 7) and act as a catalyst for knowledge and networks of relations embedded in time and place. Community media is defined here as a creative social process, characterised by an approach to production that is multi-authored, collaborative and informed by the lives of participants, and which recognises the relevance of networks of relations to that practice (Caines, 2007: 2). As a networked process, community media production is recognised as existing in collaboration between a director or producer, such as myself, and organisations, institutions and participants, who are connected through a range of identities, practices and place. These relations born of the production process reflect a complex area of practice and participation that brings together “parallel and overlapping public spheres” (Meadows et al., 2002: 3). This relates to broader concerns with networks (Carpentier, Servaes and Lie, 2003; Rodríguez, 2001), both revealed during the process of production and enhanced by it, and how they can be described with reference to the knowledge practice of community media.

Undersampled Critical Branching Processes on Small-World and Random Networks Fail to Reproduce the Statistics of Spike Avalanches

The power-law size distributions obtained experimentally for neuronal avalanches are an important evidence of criticality in the brain. This evidence is supported by the fact that a critical branching process exhibits the same exponent t~3=2. Models at criticality have been employed to mimic avalanche propagation and explain the statistics observed experimentally. However, a crucial aspect of neuronal recordings has been almost completely neglected in the models: undersampling. While in a typical multielectrode array hundreds of neurons are recorded, in the same area of neuronal tissue tens of thousands of neurons can be found. Here we investigate the consequences of undersampling in models with three different topologies (two-dimensional, small-world and random network) and three different dynamical regimes (subcritical, critical and supercritical). We found that undersampling modifies avalanche size distributions, extinguishing the power laws observed in critical systems. Distributions from subcritical systems are also modified, but the shape of the undersampled distributions is more similar to that of a fully sampled system. Undersampled supercritical systems can recover the general characteristics of the fully sampled version, provided that enough neurons are measured. Undersampling in two-dimensional and small-world networks leads to similar effects, while the random network is insensitive to sampling density due to the lack of a well-defined neighborhood. We conjecture that neuronal avalanches recorded from local field potentials avoid undersampling effects due to the nature of this signal, but the same does not hold for spike avalanches. We conclude that undersampled branching-process-like models in these topologies fail to reproduce the statistics of spike avalanches.