204 resultados para Particle-based Model


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We utilise the well-developed quantum decision models known to the QI community to create a higher order social decision making model. A simple Agent Based Model (ABM) of a society of agents with changing attitudes towards a social issue is presented, where the private attitudes of individuals in the system are represented using a geometric structure inspired by quantum theory. We track the changing attitudes of the members of that society, and their resulting propensities to act, or not, in a given social context. A number of new issues surrounding this "scaling up" of quantum decision theories are discussed, as well as new directions and opportunities.

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Over the last twenty years, the use of open content licenses has become increasingly and surprisingly popular. The use of such licences challenges the traditional incentive-based model of exclusive rights under copyright. Instead of providing a means to charge for the use of particular works, what seems important is mitigating against potential personal harm to the author and, in some cases, preventing non-consensual commercial exploitation. It is interesting in this context to observe the primacy of what are essentially moral rights over the exclusionary economic rights. The core elements of common open content licences map somewhat closely to continental conceptions of the moral rights of authorship. Most obviously, almost all free software and free culture licences require attribution of authorship. More interestingly, there is a tension between social norms developed in free software communities and those that have emerged in the creative arts over integrity and commercial exploitation. For programmers interested in free software, licence terms that prohibit commercial use or modification are almost completely inconsistent with the ideological and utilitarian values that underpin the movement. For those in the creative industries, on the other hand, non-commercial terms and, to a lesser extent, terms that prohibit all but verbatim distribution continue to play an extremely important role in the sharing of copyright material. While prohibitions on commercial use often serve an economic imperative, there is also a certain personal interest for many creators in avoiding harmful exploitation of their expression – an interest that has sometimes been recognised as forming a component of the moral right of integrity. One particular continental moral right – the right of withdrawal – is present neither in Australian law or in any of the common open content licences. Despite some marked differences, both free software and free culture participants are using contractual methods to articulate the norms of permissible sharing. Legal enforcement is rare and often prohibitively expensive, and the various communities accordingly rely upon shared understandings of acceptable behaviour. The licences that are commonly used represent a formalised expression of these community norms and provide the theoretically enforceable legal baseline that lends them legitimacy. The core terms of these licences are designed primarily to alleviate risk in sharing and minimise transaction costs in sharing and using copyright expression. Importantly, however, the range of available licences reflect different optional balances in the norms of creating and sharing material. Generally, it is possible to see that, stemming particularly from the US, open content licences are fundamentally important in providing a set of normatively accepted copyright balances that reflect the interests sought to be protected through moral rights regimes. As the cost of creation, distribution, storage, and processing of expression continues to fall towards zero, there are increasing incentives to adopt open content licences to facilitate wide distribution and reuse of creative expression. Thinking of these protocols not only as reducing transaction costs but of setting normative principles of participation assists in conceptualising the role of open content licences and the continuing tensions that permeate modern copyright law.

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The reliability of urban passenger trains is a critical performance measure for passenger satisfaction and ultimately market share. A delay to one train in a peak period can have a severe effect on the schedule adherence of other trains. This paper presents an analytically based model to quantify the expected positive delay for individual passenger trains and track links in an urban rail network. The model specifically addresses direct delay to trains, knock-on delays to other trains, and delays at scheduled connections. A solution to the resultant system of equations is found using an iterative refinement algorithm. Model validation, which is carried out using a real-life suburban train network consisting of 157 trains, shows the model estimates to be on average within 8% of those obtained from a large scale simulation. Also discussed, is the application of the model to assess the consequences of increased scheduled slack time as well as investment strategies designed to reduce delay.

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Virus-like particle-based vaccines for high-risk human papillomaviruses (HPVs) appear to have great promise; however, cell culture-derived vaccines will probably be very expensive. The optimization of expression of different codon-optimized versions of the HPV-16 L1 capsid protein gene in plants has been explored by means of transient expression from a novel suite of Agrobacterium tumefaciens binary expression vectors, which allow targeting of recombinant protein to the cytoplasm, endoplasmic reticulum (ER) or chloroplasts. A gene resynthesized to reflect human codon usage expresses better than the native gene, which expresses better than a plant-optimized gene. Moreover, chloroplast localization allows significantly higher levels of accumulation of L1 protein than does cytoplasmic localization, whilst ER retention was least successful. High levels of L1 (>17% total soluble protein) could be produced via transient expression: the protein assembled into higher-order structures visible by electron microscopy, and a concentrated extract was highly immunogenic in mice after subcutaneous injection and elicited high-titre neutralizing antibodies. Transgenic tobacco plants expressing a human codon-optimized gene linked to a chloroplast-targeting signal expressed L1 at levels up to 11% of the total soluble protein. These are the highest levels of HPV L1 expression reported for plants: these results, and the excellent immunogenicity of the product, significantly improve the prospects of making a conventional HPV vaccine by this means. © 2007 SGM.

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Background: We have previously shown the high prevalence of oral anti-human papillomavirus type 16 (HPV-16) antibodies in women with HPV-associated cervical neoplasia. It was postulated that the HPV antibodies were initiated after HPV antigenic stimulation at the cervix via the common mucosal immune system. The present study aimed to further evaluate the effectiveness of oral fluid testing for detecting the mucosal humoral response to HPV infection and to advance our limited understanding of the immune response to HPV. Methods: The prevalence of oral HPV infection and oral antibodies to HPV types 16, 18 and 11 was determined in a normal, healthy population of children, adolescents and adults, both male and female, attending a dental clinic. HPV types in buccal cells were determined by DNA sequencing. Oral fluid was collected from the gingival crevice of the mouth by the OraSure method. HPV-16, HPV-18 and HPV-11 antibodies in oral fluid were detected by virus-like particle-based enzyme-linked immunosorbent assay. As a reference group 44 women with cervical neoplasia were included in the study. Results: Oral HPV infection was h ighest in children (9/114, 7.9%), followed by adolescents (4/78, 5.1%), and lowest in normal adults (4/116, 3.5%). The predominant HPV type found was HPV-13 (7/22, 31.8%) followed by HPV-32 (5/22, 22.7%). The prevalence of oral antibodies to HPV-16, HPV-18 and HPV-11 was low in children and increased substantially in adolescents and normal adults. Oral HPV-16 IgA was significantly more prevalent in women with cervical neoplasia (30/44, 68.2%) than the women from the dental clinic (18/69, 26.1% P = 0.0001). Significantly more adult men than women displayed oral HPV-16 IgA (30/47 compared with 18/69, OR 5.0, 95% CI 2.09-12.1, P < 0.001) and HPV-18 IgA (17/47 compared with 13/69, OR 2.4, 95% CI 0.97-6.2, P = 0.04). Conclusion: The increased prevalence of oral HPV antibodies in adolescent individuals compared with children was attributed to the onset of sexual activity. The increased prevalence of oral anti-HPV IgA in men compared with women was noteworthy considering reportedly fewer men than women make serum antibodies, and warrants further investigation. © 2006 Marais et al; licensee BioMed Central Ltd.

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A user’s query is considered to be an imprecise description of their information need. Automatic query expansion is the process of reformulating the original query with the goal of improving retrieval effectiveness. Many successful query expansion techniques ignore information about the dependencies that exist between words in natural language. However, more recent approaches have demonstrated that by explicitly modeling associations between terms significant improvements in retrieval effectiveness can be achieved over those that ignore these dependencies. State-of-the-art dependency-based approaches have been shown to primarily model syntagmatic associations. Syntagmatic associations infer a likelihood that two terms co-occur more often than by chance. However, structural linguistics relies on both syntagmatic and paradigmatic associations to deduce the meaning of a word. Given the success of dependency-based approaches and the reliance on word meanings in the query formulation process, we argue that modeling both syntagmatic and paradigmatic information in the query expansion process will improve retrieval effectiveness. This article develops and evaluates a new query expansion technique that is based on a formal, corpus-based model of word meaning that models syntagmatic and paradigmatic associations. We demonstrate that when sufficient statistical information exists, as in the case of longer queries, including paradigmatic information alone provides significant improvements in retrieval effectiveness across a wide variety of data sets. More generally, when our new query expansion approach is applied to large-scale web retrieval it demonstrates significant improvements in retrieval effectiveness over a strong baseline system, based on a commercial search engine.

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Young male drivers are over-represented in road-related fatalities. Speeding represents a pervasive and significant contributor to road trauma. Anti-speeding messages represent a long-standing strategy aimed at discouraging drivers from speeding. These messages, however, have not always achieved their persuasive objectives which may be due, in part, to them not always targeting the most salient beliefs underpinning the speeding behavior of particular driver groups. The current study elicited key beliefs underpinning speeding behavior as well as strategies used to avoid speeding, using a well-validated belief-based model, the Theory of Planned Behavior and in-depth qualitative methods. To obtain the most comprehensive understanding about the salient beliefs and strategies of young male drivers, how such beliefs and strategies compared with those of drivers of varying ages and gender, was also explored. Overall, 75 males and females (aged 17-25 or 30-55 years) participated in group discussions. The findings revealed beliefs that were particularly relevant to young males and that would likely represent key foci for developing message content. For instance, the need to feel in control and the desire to experience positive affect when driving were salient advantages; while infringements were a salient disadvantage and, in particular, the loss of points and the implications associated with potential licence loss as opposed to the monetary (fine) loss (behavioral beliefs). For normative influences, young males appeared to hold notable misperceptions (compared with other drivers, such as young females); for instance, young males believed that females/girlfriends were impressed by their speeding. In the case of control beliefs, the findings revealed low perceptions of control with respect to being able to not speed and a belief that something “extraordinary” would need to happen for a young male driver to lose control of their vehicle while speeding. The practical implications of the findings, in terms of providing suggestions for devising the content of anti-speeding messages, are discussed.

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The traditional hospital-based model of cardiac rehabilitation faces substantial challenges, such as cost and accessibility. These challenges have led to the development of alternative models of cardiac rehabilitation in recent years. The aim of this study was to identify and critique evidence for the effectiveness of these alternative models. A total of 22 databases were searched to identify quantitative studies or systematic reviews of quantitative studies regarding the effectiveness of alternative models of cardiac rehabilitation. Included studies were appraised using a Critical Appraisal Skills Programme tool and the National Health and Medical Research Council's designations for Level of Evidence. The 83 included articles described interventions in the following broad categories of alternative models of care: multifactorial individualized telehealth, internet based, telehealth focused on exercise, telehealth focused on recovery, community- or home-based, and complementary therapies. Multifactorial individualized telehealth and community- or home-based cardiac rehabilitation are effective alternative models of cardiac rehabilitation, as they have produced similar reductions in cardiovascular disease risk factors compared with hospital-based programmes. While further research is required to address the paucity of data available regarding the effectiveness of alternative models of cardiac rehabilitation in rural, remote, and culturally and linguistically diverse populations, our review indicates there is no need to rely on hospital-based strategies alone to deliver effective cardiac rehabilitation. Local healthcare systems should strive to integrate alternative models of cardiac rehabilitation, such as brief telehealth interventions tailored to individual's risk factor profiles as well as community- or home-based programmes, in order to ensure there are choices available for patients that best fit their needs, risk factor profile, and preferences.

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Background: In diabetes care, health care professionals need to provide support for their patients. In order to provide good diabetes self-management support for adults with type 2 diabetes in Vietnam, it is important that health care professionals in Vietnam understand the factors influencing diabetes self-management among these people. However, knowledge about factors influencing diabetes self-management among adults with type 2 diabetes in Vietnam is limited. Objectives: This study aimed to investigate factors influencing diabetes self-management among adults with type 2 diabetes in Vietnam. Methodology: A cross-sectional survey with convenience sampling was conducted on 198 adults with type 2 diabetes in VietnamData collection was administeted via interview. Descriptive statistics, simple correlation statistics and structural equation modelling statistics were used for data analysis. Results: Adults with type 2 diabetes in Vietnam had limited diabetes knowledge (Median = 6.0). The majority of the study participants (72.7%) believed that performing diabetes self-management activities was very important or extremely important for controlling their blood glucose levels and for preventing complications from diabetes; about half usually received support from their family and friends’ (48.5%), and around two thirds rarely received support from their health care providers (68.2%). Many of the participants (41.4%) had limited confidence to perform diabetes management activities. The practices of diabetes self-management were limited among the study population (Mean = 96.7, SD = 19.4). Diabetes knowledge (β = 0.17, p < .001), belief in treatment effectiveness (β = 0.13, p < .01), family and friends’ support (β = 0.13, p < .001), health care providers’ support (β = 0.27, p < .001) and diabetes management self-efficacy (β = 0.43, p < .001) directly influenced their diabetes self-management. Diabetes knowledge, and family and friends’ support also indirectly influenced diabetes self-management among these people through their belief in treatment effectiveness and their diabetes management self-efficacy (p < .05). Conclusion: Findings in this study indicated that health care professionals should provide diabetes self-management support for adults with type 2 diabetes in Vietnam in the future. The adapted theory-based model of factors influencing diabetes self-management among adults with type 2 diabetes in Vietnam found in this study could be a useful framework to develop this supporting program.

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This thesis provides an experimental and computational platform for investigating the performance and behaviour of water filled, plastic portable road safety barriers in an isolated impact scenario. A schedule of experimental impact tests were conducted assessing the impact response of an existing design of road safety barrier utilising a novel horizontal impact testing system. A coupled finite element and smooth particle hydrodynamic model of the barrier system was developed and validated against the results of the experimental tests. The validated model was subsequently used to assess the effect of certain composite materials on the impact performance of the water filled, portable road safety barrier system.

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This paper introduces a parallel implementation of an agent-based model applied to electricity distribution grids. A fine-grained shared memory parallel implementation is presented, detailing the way the agents are grouped and executed on a multi-threaded machine, as well as the way the model is built (in a composable manner) which is an aid to the parallelisation. Current results show a medium level speedup of 2.6, but improvements are expected by incor-porating newer distributed or parallel ABM schedulers into this implementa-tion. While domain-specific, this parallel algorithm can be applied to similarly structured ABMs (directed acyclic graphs).

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Over the last decade, the majority of existing search techniques is either keyword- based or category-based, resulting in unsatisfactory effectiveness. Meanwhile, studies have illustrated that more than 80% of users preferred personalized search results. As a result, many studies paid a great deal of efforts (referred to as col- laborative filtering) investigating on personalized notions for enhancing retrieval performance. One of the fundamental yet most challenging steps is to capture precise user information needs. Most Web users are inexperienced or lack the capability to express their needs properly, whereas the existent retrieval systems are highly sensitive to vocabulary. Researchers have increasingly proposed the utilization of ontology-based tech- niques to improve current mining approaches. The related techniques are not only able to refine search intentions among specific generic domains, but also to access new knowledge by tracking semantic relations. In recent years, some researchers have attempted to build ontological user profiles according to discovered user background knowledge. The knowledge is considered to be both global and lo- cal analyses, which aim to produce tailored ontologies by a group of concepts. However, a key problem here that has not been addressed is: how to accurately match diverse local information to universal global knowledge. This research conducts a theoretical study on the use of personalized ontolo- gies to enhance text mining performance. The objective is to understand user information needs by a \bag-of-concepts" rather than \words". The concepts are gathered from a general world knowledge base named the Library of Congress Subject Headings. To return desirable search results, a novel ontology-based mining approach is introduced to discover accurate search intentions and learn personalized ontologies as user profiles. The approach can not only pinpoint users' individual intentions in a rough hierarchical structure, but can also in- terpret their needs by a set of acknowledged concepts. Along with global and local analyses, another solid concept matching approach is carried out to address about the mismatch between local information and world knowledge. Relevance features produced by the Relevance Feature Discovery model, are determined as representatives of local information. These features have been proven as the best alternative for user queries to avoid ambiguity and consistently outperform the features extracted by other filtering models. The two attempt-to-proposed ap- proaches are both evaluated by a scientific evaluation with the standard Reuters Corpus Volume 1 testing set. A comprehensive comparison is made with a num- ber of the state-of-the art baseline models, including TF-IDF, Rocchio, Okapi BM25, the deploying Pattern Taxonomy Model, and an ontology-based model. The gathered results indicate that the top precision can be improved remarkably with the proposed ontology mining approach, where the matching approach is successful and achieves significant improvements in most information filtering measurements. This research contributes to the fields of ontological filtering, user profiling, and knowledge representation. The related outputs are critical when systems are expected to return proper mining results and provide personalized services. The scientific findings have the potential to facilitate the design of advanced preference mining models, where impact on people's daily lives.

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Many cell types form clumps or aggregates when cultured in vitro through a variety of mechanisms including rapid cell proliferation, chemotaxis, or direct cell-to-cell contact. In this paper we develop an agent-based model to explore the formation of aggregates in cultures where cells are initially distributed uniformly, at random, on a two-dimensional substrate. Our model includes unbiased random cell motion, together with two mechanisms which can produce cell aggregates: (i) rapid cell proliferation, and (ii) a biased cell motility mechanism where cells can sense other cells within a finite range, and will tend to move towards areas with higher numbers of cells. We then introduce a pair-correlation function which allows us to quantify aspects of the spatial patterns produced by our agent-based model. In particular, these pair-correlation functions are able to detect differences between domains populated uniformly at random (i.e. at the exclusion complete spatial randomness (ECSR) state) and those where the proliferation and biased motion rules have been employed - even when such differences are not obvious to the naked eye. The pair-correlation function can also detect the emergence of a characteristic inter-aggregate distance which occurs when the biased motion mechanism is dominant, and is not observed when cell proliferation is the main mechanism of aggregate formation. This suggests that applying the pair-correlation function to experimental images of cell aggregates may provide information about the mechanism associated with observed aggregates. As a proof of concept, we perform such analysis for images of cancer cell aggregates, which are known to be associated with rapid proliferation. The results of our analysis are consistent with the predictions of the proliferation-based simulations, which supports the potential usefulness of pair correlation functions for providing insight into the mechanisms of aggregate formation.

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This thesis explored the potential of a multi-component and multi-disciplinary approach to obesity management using action research methodologies. A preliminary systems-based model for obesity management was developed based around four meta-components (client factors, practitioner factors, process factors and the environment) and two action theories (action research and action science).

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This thesis presents a sequential pattern based model (PMM) to detect news topics from a popular microblogging platform, Twitter. PMM captures key topics and measures their importance using pattern properties and Twitter characteristics. This study shows that PMM outperforms traditional term-based models, and can potentially be implemented as a decision support system. The research contributes to news detection and addresses the challenging issue of extracting information from short and noisy text.