950 resultados para Virtual networks
Polysynaptic potentials within the lateral amygdala networks as indicators of reverberatory activity
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Synaptic plasticity in the lateral amygdala (LA) may underlie auditory fear conditioning. Hebb postulated that sustained activity in reverberating cellular ensembles can facilitate temporal coincidence detection. Our anatomical data show that LA neurons have extensive local axon collaterals that are topographically organized and that could provide the anatomical basis for reverberatory activity...
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This article presents and evaluates a model to automatically derive word association networks from text corpora. Two aspects were evaluated: To what degree can corpus-based word association networks (CANs) approximate human word association networks with respect to (1) their ability to quantitatively predict word associations and (2) their structural network characteristics. Word association networks are the basis of the human mental lexicon. However, extracting such networks from human subjects is laborious, time consuming and thus necessarily limited in relation to the breadth of human vocabulary. Automatic derivation of word associations from text corpora would address these limitations. In both evaluations corpus-based processing provided vector representations for words. These representations were then employed to derive CANs using two measures: (1) the well known cosine metric, which is a symmetric measure, and (2) a new asymmetric measure computed from orthogonal vector projections. For both evaluations, the full set of 4068 free association networks (FANs) from the University of South Florida word association norms were used as baseline human data. Two corpus based models were benchmarked for comparison: a latent topic model and latent semantic analysis (LSA). We observed that CANs constructed using the asymmetric measure were slightly less effective than the topic model in quantitatively predicting free associates, and slightly better than LSA. The structural networks analysis revealed that CANs do approximate the FANs to an encouraging degree.
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Mismatches between services needing to interoperate have been addressed through the adaptation of structural and behavioural interfaces of services, which in practice incur long lead time through manual, coding effort. We propose a framework, complementary to con- ventional service adaptation, to synthesise service interfaces in the open setting of business networks, allowing consumers to introspect service interfaces and formulate service invocations. The framework also allows evolved service requests, as new features of service capabilities are discov- ered, through interactions with other, similar services. Finally the frame- work fosters reuse of adaptation efforts through normalisation of struc- tural and behavioural interfaces of similar services. This paper provides a first exposition of the service interface synthesis framework, describing patterns containing novel requirements for unilateral service adaptation and detailing the interface synthesis technique. Complex examples of ser- vices drawn from commercial logistic systems are then used to validate the synthesis technique and identify open challenges and future research directions.
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The use of expert knowledge to quantify a Bayesian Network (BN) is necessary when data is not available. This however raises questions regarding how opinions from multiple experts can be used in a BN. Linear pooling is a popular method for combining probability assessments from multiple experts. In particular, Prior Linear Pooling (PrLP), which pools opinions then places them into the BN is a common method. This paper firstly proposes an alternative pooling method, Posterior Linear Pooling (PoLP). This method constructs a BN for each expert, then pools the resulting probabilities at the nodes of interest. Secondly, it investigates the advantages and disadvantages of using these pooling methods to combine the opinions of multiple experts. Finally, the methods are applied to an existing BN, the Wayfinding Bayesian Network Model, to investigate the behaviour of different groups of people and how these different methods may be able to capture such differences. The paper focusses on 6 nodes Human Factors, Environmental Factors, Wayfinding, Communication, Visual Elements of Communication and Navigation Pathway, and three subgroups Gender (female, male),Travel Experience (experienced, inexperienced), and Travel Purpose (business, personal) and finds that different behaviors can indeed be captured by the different methods.
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This project is a step forward in developing effective methods to mitigate voltage unbalance in urban residential networks. The method is proposed to reduce energy losses and improve quality of service in strongly unbalanced low-voltage networks. The method is based on phase swapping as well as optimal placement and sizing of Distribution Static Synchronous Compensator (D-STATCOM) using a Particle Swarm Optimisation method.
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A curvilinear thin film model is used to simulate the motion of droplets on a virtual leaf surface, with a view to better understand the retention of agricultural sprays on plants. The governing model, adapted from Roy et al. (2002 J. Fluid Mech. 454, 235–261) with the addition of a disjoining pressure term, describes the gravity- and curvature driven flow of a small droplet on a complex substrate: a cotton leaf reconstructed from digitized scan data. Coalescence is the key mechanism behind spray coating of foliage, and our simulations demonstrate that various experimentally observed coalescence behaviours can be reproduced qualitatively. By varying the contact angle over the domain, we also demonstrate that the presence of a chemical defect can act as an obstacle to the droplet’s path, causing break-up. In simulations on the virtual leaf, it is found that the movement of a typical spray size droplet is driven almost exclusively by substrate curvature gradients. It is not until droplet mass is sufficiently increased via coalescence that gravity becomes the dominating force.
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Asoftware-based environment was developed to provide practical training in medical radiation principles and safety. The Virtual Radiation Laboratory application allowed students to conduct virtual experiments using simulated diagnostic and radiotherapy X-ray generators. The experiments were designed to teach students about the inverse square law, half value layer and radiation protection measures and utilised genuine clinical and experimental data. Evaluation of the application was conducted in order to ascertain the impact of the software on students’ understanding, satisfaction and collaborative learning skills and also to determine potential further improvements to the software and guidelines for its continued use. Feedback was gathered via an anonymous online survey consisting of a mixture of Likert-style questions and short answer open questions. Student feedback was highly positive with 80 % of students reporting increased understanding of radiation protection principles. Furthermore 72 % enjoyed using the software and 87 %of students felt that the project facilitated collaboration within small groups. The main themes arising in the qualitative feedback comments related to efficiency and effectiveness of teaching, safety of environment, collaboration and realism. Staff and students both report gains in efficiency and effectiveness associated with the virtual experiments. In addition students particularly value the visualisation of ‘‘invisible’’ physical principles and increased opportunity for experimentation and collaborative problembased learning. Similar ventures will benefit from adopting an approach that allows for individual experimentation while visualizing challenging concepts.
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This project constructed virtual plant leaf surfaces from digitised data sets for use in droplet spray models. Digitisation techniques for obtaining data sets for cotton, chenopodium and wheat leaves are discussed and novel algorithms for the reconstruction of the leaves from these three plant species are developed. The reconstructed leaf surfaces are included into agricultural droplet spray models to investigate the effect of the nozzle and spray formulation combination on the proportion of spray retained by the plant. A numerical study of the post-impaction motion of large droplets that have formed on the leaf surface is also considered.
Bayesian networks as a complex system tool in the context of a major industry and university project
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Calleija, a small to medium sized (SME) Australian and internationally recognised fine jeweller has secured a significant strategic global partnership with one of the world’s best-known luxury automobile brands, Aston Martin. Forging this international relationship to produce an elegant fine jewellery collection has given rise to a new network between the Australian jewellery industry and the European automobile industry. Calleija’s exclusive association with Aston Martin consolidates a shared passion for the finest quality and craftsmanship which was inspired by Aston Martin’s Supercar, the One-77. This inspiration lead to John Calleija being chosen by Aston Martin to design this latest high-luxury offering in which each design is limited to only 77 pieces utilising 30 unique designs (Calleija, 2012). The story behind Calleija’s internationalisation to the United Kingdom (UK) and their subsequent business-to-business strategic partnership with Aston Martin is no doubt a good sign for the Australian jewellery industry.
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The major challenge of European Union’s agricultural industry is to ensure sustainable supply of quality food that meets the demands of a rapidly growing population, changing dietary patterns, increased competition for land use, and environmental concerns. Investments in research and innovation, which facilitate integration of external knowledge in food chain operations, are crucial to undertaking such challenges. This paper addresses how SMEs successfully innovate within collaborative networks with the assistance of innovation intermediaries. In particular, we explore the roles of innovation intermediaries in knowledge acquisition, knowledge assimilation, knowledge, transformation, and knowledge exploitation in open innovation initiatives from the wine industry through the theoretical lens of absorptive capacity. Based on two case studies from the wine industry, we identified seven key activities performed by innovation intermediaries that complement SMEs’ ability to successfully leverage external sources of knowledge for innovation purposes. These activities are articulation of knowledge needs and innovation capabilities, facilitation of social interactions, establishment of complementary links, implementation of governance structures, conflict management, enhancement of transparency, and mediation of communication. Our in-depth qualitative study of two innovation intermediaries in the wine industry has several important implications that contribute to research and practice.
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Objetivo Revisar de forma sistemática y realizar una evaluación critica de las diferentes publicaciones existentes sobre el uso de la realidad virtual como elemento rehabilitador en la mano. Estrategias de búsqueda Se ha realizado una búsqueda en la base de datos Medline completada con búsquedas en Google Schoolar. Se ha limitado la búsqueda a 10 años de extensión, idiomas: inglés y español. Selección de estudios: se ha centrado sobre aquellos artículos relacionados con la realidad virtual y la rehabilitación funcional de la mano en el accidente cerebrovascular. Síntesis de resultados Debido a la falta de homogeneidad, no ha sido posible evaluar metodológicamente mediante instrumento Caspe. Se detectaron 200 artículos de los cuales 12 cumplen los criterios de selección de los mismos. Dichos artículos han sido agrupados en relación con diferentes criterios como son: tipo de estudio, sistema de evaluación utilizado, periféricos usados o resultados obtenidos entre otros. Conclusiones No se ha obtenido una homogeneidad conjunta sobre los artículos, por ello se debe continuar realizando avances en este ámbito. A pesar de ello, los entornos de realidad virtual pueden ser un instrumento válido para la recuperación funcional de la mano en los accidentes cerebrovasculares, no siendo aptos como elemento único rehabilitador. Abstract in English Objective To make a systematic review and critical assessment of the different existing publications on the use of virtual reality as an element in rehabilitation of the hand. Search Method A search was made in the Medline database completed with searches in Google Schoolar. The search was limited to a period of ten years, and English and Spanish languages. Study selection The study was focused on those articles related to virtual reality and the functional rehabilitation of the hand in stroke. Synthesis of results It was not possible to perform a methodological evaluation using the Caspe instrument due to lack of homogeneity. Two hundred 200 articles were found. Of these, 12 met the criteria for their selection. These articles were grouped in relation to different criteria such as: type of study, assessment system used, hardware used or outcomes results obtained, among others. Conclusions Joint homogeneity was not obtained for the articles. Therefore, progress must still be made in this area. In spite of this, virtual reality environments can be a valid tool for functional recovery of the hand in strokes but they are not adequate for use as a single rehabilitative treatment element.
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The 'rich club' coefficient describes a phenomenon where a network's hubs (high-degree nodes) are on average more intensely interconnected than lower-degree nodes. Networks with rich clubs often have an efficient, higher-order organization, but we do not yet know how the rich club emerges in the living brain, or how it changes as our brain networks develop. Here we chart the developmental trajectory of the rich club in anatomical brain networks from 438 subjects aged 12-30. Cortical networks were constructed from 68×68 connectivity matrices of fiber density, using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). The adult and younger cohorts had rich clubs that included different nodes; the rich club effect intensified with age. Rich-club organization is a sign of a network's efficiency and robustness. These concepts and findings may be advantageous for studying brain maturation and abnormal brain development.
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Brain connectivity analyses are increasingly popular for investigating organization. Many connectivity measures including path lengths are generally defined as the number of nodes traversed to connect a node in a graph to the others. Despite its name, path length is purely topological, and does not take into account the physical length of the connections. The distance of the trajectory may also be highly relevant, but is typically overlooked in connectivity analyses. Here we combined genotyping, anatomical MRI and HARDI to understand how our genes influence the cortical connections, using whole-brain tractography. We defined a new measure, based on Dijkstra's algorithm, to compute path lengths for tracts connecting pairs of cortical regions. We compiled these measures into matrices where elements represent the physical distance traveled along tracts. We then analyzed a large cohort of healthy twins and show that our path length measure is reliable, heritable, and influenced even in young adults by the Alzheimer's risk gene, CLU.
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Functional connectivity (FC) analyses of resting-state fMRI data allow for the mapping of large-scale functional networks, and provide a novel means of examining the impact of dopaminergic challenge. Here, using a double-blind, placebo-controlled design, we examined the effect of L-dopa, a dopamine precursor, on striatal resting-state FC in 19 healthy young adults.Weexamined the FC of 6 striatal regions of interest (ROIs) previously shown to elicit networks known to be associated with motivational, cognitive and motor subdivisions of the caudate and putamen (Di Martino et al., 2008). In addition to replicating the previously demonstrated patterns of striatal FC, we observed robust effects of L-dopa. Specifically, L-dopa increased FC in motor pathways connecting the putamen ROIs with the cerebellum and brainstem. Although L-dopa also increased FC between the inferior ventral striatum and ventrolateral prefrontal cortex, it disrupted ventral striatal and dorsal caudate FC with the default mode network. These alterations in FC are consistent with studies that have demonstrated dopaminergic modulation of cognitive and motor striatal networks in healthy participants. Recent studies have demonstrated altered resting state FC in several conditions believed to be characterized by abnormal dopaminergic neurotransmission. Our findings suggest that the application of similar experimental pharmacological manipulations in such populations may further our understanding of the role of dopaminergic neurotransmission in those conditions.