468 resultados para Concurrent networks


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Because moving depictions of face emotion have greater ecological validity than their static counterparts, it has been suggested that still photographs may not engage ‘authentic’ mechanisms used to recognize facial expressions in everyday life. To date, however, no neuroimaging studies have adequately addressed the question of whether the processing of static and dynamic expressions rely upon different brain substrates. To address this, we performed an functional magnetic resonance imaging (fMRI) experiment wherein participants made emotional expression discrimination and Sex discrimination judgements to static and moving face images. Compared to Sex discrimination, Emotion discrimination was associated with widespread increased activation in regions of occipito-temporal, parietal and frontal cortex. These regions were activated both by moving and by static emotional stimuli, indicating a general role in the interpretation of emotion. However, portions of the inferior frontal gyri and supplementary/pre-supplementary motor area showed task by motion interaction. These regions were most active during emotion judgements to static faces. Our results demonstrate a common neural substrate for recognizing static and moving facial expressions, but suggest a role for the inferior frontal gyrus in supporting simulation processes that are invoked more strongly to disambiguate static emotional cues.

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Early transcriptional activation events that occur in bladder immediately following bacterial urinary tract infection (UTI) are not well defined. In this study, we describe the whole bladder transcriptome of uropathogenic Escherichia coli (UPEC) cystitis in mice using genome-wide expression profiling to define the transcriptome of innate immune activation stemming from UPEC colonization of the bladder. Bladder RNA from female C57BL/6 mice, analyzed using 1.0 ST-Affymetrix microarrays, revealed extensive activation of diverse sets of innate immune response genes, including those that encode multiple IL-family members, receptors, metabolic regulators, MAPK activators, and lymphocyte signaling molecules. These were among 1564 genes differentially regulated at 2 h postinfection, highlighting a rapid and broad innate immune response to bladder colonization. Integrative systems-level analyses using InnateDB (http://www.innatedb.com) bioinformatics and ingenuity pathway analysis identified multiple distinct biological pathways in the bladder transcriptome with extensive involvement of lymphocyte signaling, cell cycle alterations, cytoskeletal, and metabolic changes. A key regulator of IL activity identified in the transcriptome was IL-10, which was analyzed functionally to reveal marked exacerbation of cystitis in IL-10–deficient mice. Studies of clinical UTI revealed significantly elevated urinary IL-10 in patients with UPEC cystitis, indicating a role for IL-10 in the innate response to human UTI. The whole bladder transcriptome presented in this work provides new insight into the diversity of innate factors that determine UTI on a genome-wide scale and will be valuable for further data mining. Identification of protective roles for other elements in the transcriptome will provide critical new insight into the complex cascade of events that underpin UTI.

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A model of crosslinker unbinding is implemented in a highly coarsegrained granular model of F-actin cytoskeleton. We employ this specific granular model to study the mechanisms of the compressive responses of F-actin networks. It is found that the compressive response of F-actin cytoskeleton has dependency on the strain rate. The evolution of deformation energy in the network indicates that crosslinker unbinding events can induce the remodelling of F-actin cytoskeleton in response to external loadings. The internal stress in F-actin cytoskeleton can efficiently dissipate with the help of crosslinker unbinding, which could lead to the spontaneous relaxation of living cells.

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Organisations employ Enterprise Social Networks (ESNs) (such as Yammer) expecting better intra-organisational communication and collaboration. However, ESNs are struggling to gain momentum and wide adoption among users. Promoting user participation is a challenge, particularly in relation to lurkers – the silent ESN members who do not contribute any content. Building on behaviour change research, we propose a three-route model consisting of the central, peripheral and coercive routes of influence that depict users’ cognitive strategies, and we examine how management interventions (e.g. sending promotional emails) impact users’ beliefs and (consequent) posting and lurking behaviours in ESNs. Furthermore, we identify users’ salient motivations to lurk or post. We employ a multi-method research design to conceptualise, operationalise and validate the research model. This study has implications for academics and practitioners regarding the nature, patterns and outcomes of management interventions in prompting ESN.

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The care of a person living at home near the end of their life is predominantly provided by family carers with the support of health services such as palliative care. In addition, informal caring networks also contribute at times to the support to the dying person and their carer. In this way, these networks can promote social capital in the communities from which they are drawn. This social approach to end of life care enhances community capacity to provide support to those dying at home and their carers. This article examines relevant published literature to explore the conceptual foundations of informal caring networks, examining the place of social capital and community development in the provision of end of life care at home, particularly in the Australian context.

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Integrating Photovoltaic (PV) systems with battery energy storage in the distribution network will be essential to allow for continued uptake of domestic PV system installations. With increasing concerns regarding environmental and climate change issues, incorporating sources of renewable energy into power networks across the world will be key for a sustainable future. Australia is well placed to utilise solar energy as a significant component of its future energy generation and within the last 5 years there has been a rapid growth in the penetration levels seen by the grid. This growth of PV systems is causing a number of issues including intermittency of supply, negative power flow and voltage rises. Using the simulator tool GridLAB-D with a model of a typical South-East Queensland (SEQ) 11 kV distribution feeder, the effect of various configurations of PV systems have been offset with Battery Energy Storage Systems (BESS). From this, combinations of PV and storage that are most effective at mitigating the issues were explored.

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Enterprise social networks provide benefits especially for knowledge-intensive work as they enable communication, collaboration and knowledge exchange. These platforms should therefore lead to increased adoption and use by knowledge-intensive workers such as consultants or indeed researchers. Our interest is in ascertaining whether scientific researchers use enterprise social networks as part of their work practices. This focus is motivated by an apparent schism between a need for researchers to exchange knowledge and profile themselves, and the aversion to sharing breakthrough ideas and joining in an ever-increasing publishing and marketing game. We draw on research on academic work practices and impression management to develop a model of academics’ ESN usage for impression management tactics. We describe important constructs of our model, offer strategies for their operationalization and give an outlook to our ongoing empirical study of the use of an ESN platform by 20 schools across six faculties at an Australian university.

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This study examines the role that the size of a victimised organisation and the size of the victim’s loss have on attitudes regarding the acceptance or unacceptance of 12 questionable consumer actions. A sample of 815 American adults rated each scenario on a scale anchored by very acceptable and very unacceptable. It was shown that the size of the victimised organisation tends to influence consumers’ opinions with more disdain directed towards consumers who take advantage of smaller businesses. Similarly, the respondents tended to be more critical of these actions when the loss incurred by the victimised organisation was large. A 2x2 matrix concurrently delineated the nature of the extent to which opinions regarding the 12 actions differed depending upon the mediating variable under scrutiny.

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This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

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Bayesian networks (BNs) are graphical probabilistic models used for reasoning under uncertainty. These models are becoming increasing popular in a range of fields including ecology, computational biology, medical diagnosis, and forensics. In most of these cases, the BNs are quantified using information from experts, or from user opinions. An interest therefore lies in the way in which multiple opinions can be represented and used in a BN. This paper proposes the use of a measurement error model to combine opinions for use in the quantification of a BN. The multiple opinions are treated as a realisation of measurement error and the model uses the posterior probabilities ascribed to each node in the BN which are computed from the prior information given by each expert. The proposed model addresses the issues associated with current methods of combining opinions such as the absence of a coherent probability model, the lack of the conditional independence structure of the BN being maintained, and the provision of only a point estimate for the consensus. The proposed model is applied an existing Bayesian Network and performed well when compared to existing methods of combining opinions.

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It is well known that, for major infrastructure networks such as electricity, gas, railway, road, and urban water networks, disruptions at one point have a knock on effect throughout the network. There is an impressive amount of individual research projects examining the vulnerability of critical infrastructure network. However, there is little understanding of the totality of the contribution made by these projects and their interrelationships. This makes their review a difficult process for both new and existing researchers in the field. To address this issue, a two-step literature review process is used, to provide an overview of the vulnerability of the transportation network in terms of four main themes - research objective, transportation mode, disruption scenario and vulnerability indicator –involving the analysis of related articles from 2001 to 2013. Two limitations of existing research are identified: (1) the limited amount of studies relating to multi-layer transportation network vulnerability analysis, and (2) the lack of evaluation methods to explore the relationship between structure vulnerability and dynamical functional vulnerability. In addition to indicating that more attention needs to be paid to these two aspects in future, the analysis provides a new avenue for the discovery of knowledge, as well as an improved understanding of transportation network vulnerability.

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This paper reviews the use of multi-agent systems to model the impacts of high levels of photovoltaic (PV) system penetration in distribution networks and presents some preliminary data obtained from the Perth Solar City high penetration PV trial. The Perth Solar City trial consists of a low voltage distribution feeder supplying 75 customers where 29 consumers have roof top photovoltaic systems. Data is collected from smart meters at each consumer premises, from data loggers at the transformer low voltage (LV) side and from a nearby distribution network SCADA measurement point on the high voltage side (HV) side of the transformer. The data will be used to progressively develop MAS models.

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Digital innovation is transforming the media and entertainment industries. The professionalization of YouTube’s platform is paradigmatic of that change. The 100 original channel initiative launched in late 2011 was designed to transform YouTube’s brand through production of a high volume of quality premium video content that would more deeply engage its audience base and in the process attract big advertisers. An unanticipated by-product has been the rapid growth of a wave of aspiring next-generation digital media companies from within the YouTube ecosystem. Fuelled by early venture capital some have ambitious goals to become global media corporations in the online video space. A number of larger MCNs (Multi-Channel Networks) - BigFrame, Machinima, Fullscreen, AwesomenessTV, Maker Studios , Revision3 and DanceOn - have attracted interest from media incumbents like Warner Brothers, DreamWorks, Discovery, Bertlesmann, Comcast and AMC, and two larger MCNs Alloy and Break Media have merged. This indicates that a shakeout is underway in these new online supply chains, after rapid initial growth. The higher profile MCNs seek to rapidly develop scale economies in online distribution and facilitate audience growth for their member channels, helping channels optimize monetization, develop sustainable business models and to facilitate producer-collaboration within a growing online community of like-minded content creators. Some MCNs already attract far larger online audiences than any national TV network. The speed with which these developments have occurred is reminiscent of the 1910s, when Hollywood studios first emerged and within only a few years replaced the incumbent film studios as the dominant force within the film industry.