930 resultados para Probabilistic latent semantic analysis (PLSA)


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The present investigation was carried out on a sample of 840 children (5 to 16 years old) from ten small towns of the State of Bahia in northeastern Brazil. The objetive was to study, by using a cross sectional methodology, the evolution of schistosomiasis morbidity (hepatic and splenic enlargement) in children, and the role of the intensity of S. mansoni infection in this process. The children were analised in three age groups (5 to 8, to 12 and 13 to 16 years old) and classified as uninfected, mildly infected, moderately infected and heavily infected according to the number of eggs in the stool. In children aged 5 to 8 years, increasing egg counts were not associated with increasing frequencies of hepatic or splenic enlargement. In the 9 to 12 years old group and association was observed with the prevalence of hepatic enlargement, but not with the prevalence of spleen enlargement. In the oldest group, 13 to 16 years old, an association was observed with the prevalence of enlargement of both organs. It was evident that in this population schistosomiasis morbidity develops in the early period of life as a gradual process starting with liver enlargement and followed by spleen enlargement some years later. It was found that the intensity of infection has a fundamental role in this process, although there is a latent period of some years before clinical splenomegaly appears in moderate-heavily infected children. The Authors suggest that the prevalence of splenomegaly in the 13 to 16 years old group is a good measure of the community level of schistosomiasis morbidity and could be used to measure the impact of control programs.

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Most of distributed generation and smart grid research works are dedicated to network operation parameters studies, reliability, etc. However, many of these works normally uses traditional test systems, for instance, IEEE test systems. This paper proposes voltage magnitude and reliability studies in presence of fault conditions, considering realistic conditions found in countries like Brazil. The methodology considers a hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models and a remedial action algorithm which is based on optimal power flow. To illustrate the application of the proposed method, the paper includes a case study that considers a real 12-bus sub-transmission network.

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In developed countries, civil infrastructures are one of the most significant investments of governments, corporations, and individuals. Among these, transportation infrastructures, including highways, bridges, airports, and ports, are of huge importance, both economical and social. Most developed countries have built a fairly complete network of highways to fit their needs. As a result, the required investment in building new highways has diminished during the last decade, and should be further reduced in the following years. On the other hand, significant structural deteriorations have been detected in transportation networks, and a huge investment is necessary to keep these infrastructures safe and serviceable. Due to the significant importance of bridges in the serviceability of highway networks, maintenance of these structures plays a major role. In this paper, recent progress in probabilistic maintenance and optimization strategies for deteriorating civil infrastructures with emphasis on bridges is summarized. A novel model including interaction between structural safety analysis,through the safety index, and visual inspections and non destructive tests, through the condition index, is presented. Single objective optimization techniques leading to maintenance strategies associated with minimum expected cumulative cost and acceptable levels of condition and safety are presented. Furthermore, multi-objective optimization is used to simultaneously consider several performance indicators such as safety, condition, and cumulative cost. Realistic examples of the application of some of these techniques and strategies are also presented.

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This study describes the change of the ultraviolet spectral bands starting from 0.1 to 5.0 nm slit width in the spectral range of 200–400 nm. The analysis of the spectral bands is carried out by using the multidimensional scaling (MDS) approach to reach the latent spectral background. This approach indicates that 0.1 nm slit width gives higher-order noise together with better spectral details. Thus, 5.0 nm slit width possesses the higher peak amplitude and lower-order noise together with poor spectral details. In the above-mentioned conditions, the main problem is to find the relationship between the spectral band properties and the slit width. For this aim, the MDS tool is to used recognize the hidden information of the ultraviolet spectra of sildenafil citrate by using a Shimadzu UV–VIS 2550, which is in the world the best double monochromator instrument. In this study, the proposed mathematical approach gives the rich findings for the efficient use of the spectrophotometer in the qualitative and quantitative studies.

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Presented at 23rd International Conference on Real-Time Networks and Systems (RTNS 2015). 4 to 6, Nov, 2015, Main Track. Lille, France.

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Assessing the safety of existing timber structures is of paramount importance for taking reliable decisions on repair actions and their extent. The results obtained through semi-probabilistic methods are unrealistic, as the partial safety factors present in codes are calibrated considering the uncertainty present in new structures. In order to overcome these limitations, and also to include the effects of decay in the safety analysis, probabilistic methods, based on Monte-Carlo simulation are applied here to assess the safety of existing timber structures. In particular, the impact of decay on structural safety is analyzed and discussed, using a simple structural model, similar to that used for current semi-probabilistic analysis.

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BACKGROUND: High-grade gliomas are aggressive, incurable tumors characterized by extensive diffuse invasion of the normal brain parenchyma. Novel therapies at best prolong survival; their costs are formidable and benefit is marginal. Economic restrictions thus require knowledge of the cost-effectiveness of treatments. Here, we show the cost-effectiveness of enhanced resections in malignant glioma surgery using a well-characterized tool for intraoperative tumor visualization, 5-aminolevulinic acid (5-ALA). OBJECTIVE: To evaluate the cost-effectiveness of 5-ALA fluorescence-guided neurosurgery compared with white-light surgery in adult patients with newly diagnosed high-grade glioma, adopting the perspective of the Portuguese National Health Service. METHODS: We used a Markov model (cohort simulation). Transition probabilities were estimated with the use of data from 1 randomized clinical trial and 1 noninterventional prospective study. Utility values and resource use were obtained from published literature and expert opinion. Unit costs were taken from official Portuguese reimbursement lists (2012 values). The health outcomes considered were quality-adjusted life-years, lifeyears, and progression-free life-years. Extensive 1-way and probabilistic sensitivity analyses were performed. RESULTS: The incremental cost-effectiveness ratios are below €10 000 in all evaluated outcomes, being around €9100 per quality-adjusted life-year gained, €6700 per life-year gained, and €8800 per progression-free life-year gained. The probability of 5-ALA fluorescence-guided surgery cost-effectiveness at a threshold of €20000 is 96.0% for quality-adjusted life-year, 99.6% for life-year, and 98.8% for progression-free life-year. CONCLUSION: 5-ALA fluorescence-guided surgery appears to be cost-effective in newly diagnosed high-grade gliomas compared with white-light surgery. This example demonstrates cost-effectiveness analyses for malignant glioma surgery to be feasible on the basis of existing data.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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The increasing use of information and communication technologies (ICT) in diverse professional and personal contexts calls for new knowledge, and a set of abilities, competences and attitudes, for an active and participative citizenship. In this context it is acknowledged that universities have an important role innovating in the educational use of digital media to promote an inclusive digital literacy. The educational potential of digital technologies and resources has been recognized by both researchers and practitioners. Multiple pedagogical models and research approaches have already contributed to put in evidence the importance of adapting instructional and learning practices and processes to concrete contexts and educational goals. Still, academic and scientific communities believe further investments in ICT research is needed in higher education. This study focuses on educational models that may contribute to support digital technology uses, where these can have cognitive and educational relevance when compared to analogical technologies. A teaching and learning model, centered in the active role of the students in the exploration, production, presentation and discussion of interactive multimedia materials, was developed and applied using the internet and exploring emergent semantic hypermedia formats. The research approach focused on the definition of design principles for developing class activities that were applied in three different iterations in undergraduate courses from two institutions, namely the University of Texas at Austin, USA and the University of Lisbon, Portugal. The analysis of this study made possible to evaluate the potential and efficacy of the model proposed and the authoring tool chosen in the support of metacognitive skills and attitudes related to information structuring and management, storytelling and communication, using computers and the internet.

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This work studies the combination of safe and probabilistic reasoning through the hybridization of Monte Carlo integration techniques with continuous constraint programming. In continuous constraint programming there are variables ranging over continuous domains (represented as intervals) together with constraints over them (relations between variables) and the goal is to find values for those variables that satisfy all the constraints (consistent scenarios). Constraint programming “branch-and-prune” algorithms produce safe enclosures of all consistent scenarios. Special proposed algorithms for probabilistic constraint reasoning compute the probability of sets of consistent scenarios which imply the calculation of an integral over these sets (quadrature). In this work we propose to extend the “branch-and-prune” algorithms with Monte Carlo integration techniques to compute such probabilities. This approach can be useful in robotics for localization problems. Traditional approaches are based on probabilistic techniques that search the most likely scenario, which may not satisfy the model constraints. We show how to apply our approach in order to cope with this problem and provide functionality in real time.

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INTRODUCTION: Human cytomegalovirus is an opportunistic betaherpesvirus that causes persistent and serious infections in immunodeficient patients. Recurrent infections occur due to the presence of the virus in a latent state in some cell types. It is possible to examine the virus using molecular methods to aid in the immunological diagnosis and to generate a molecular viral profile in immunodeficient patients. The objective of this study was to characterize cytomegalovirus genotypes and to generate the epidemiological and molecular viral profile in immunodeficient patients. METHODS: A total of 105 samples were collected from immunodeficient patients from the City of Belém, including newborns, hemodialysis patients, transplant recipients and HIV+ patients. An IgG and IgM antibody study was completed using ELISA, and enzymatic analysis by restriction fragment length polymorphism (RFLP) was performed to characterize viral genotypes. RESULTS: It was observed that 100% of the patients had IgG antibodies, 87% of which were IgG+/IgM-, consistent with a prior infection profile, 13% were IgG+/IgM+, suggestive of recent infection. The newborn group had the highest frequency (27%) of the IgG+/IgM+ profile. By RFLP analysis, only one genotype was observed, gB2, which corresponded to the standard AD169 strain. CONCLUSIONS: The presence of IgM antibodies in new borns indicates that HCMV continues to be an important cause of congenital infection. The low observed genotypic diversity could be attributed to the small sample size because newborns were excluded from the RFLP analysis. This study will be continued including samples from newborns to extend the knowledge of the general and molecular epidemiology of HCMV in immunodeficient patients.

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According to a recent Eurobarometer survey (2014), 68% of Europeans tend not to trust national governments. As the increasing alienation of citizens from politics endangers democracy and welfare, governments, practitioners and researchers look for innovative means to engage citizens in policy matters. One of the measures intended to overcome the so-called democratic deficit is the promotion of civic participation. Digital media proliferation offers a set of novel characteristics related to interactivity, ubiquitous connectivity, social networking and inclusiveness that enable new forms of societal-wide collaboration with a potential impact on leveraging participative democracy. Following this trend, e-Participation is an emerging research area that consists in the use of Information and Communication Technologies to mediate and transform the relations among citizens and governments towards increasing citizens’ participation in public decision-making. However, despite the widespread efforts to implement e-Participation through research programs, new technologies and projects, exhaustive studies on the achieved outcomes reveal that it has not yet been successfully incorporated in institutional politics. Given the problems underlying e-Participation implementation, the present research suggested that, rather than project-oriented efforts, the cornerstone for successfully implementing e-Participation in public institutions as a sustainable added-value activity is a systematic organisational planning, embodying the principles of open-governance and open-engagement. It further suggested that BPM, as a management discipline, can act as a catalyst to enable the desired transformations towards value creation throughout the policy-making cycle, including political, organisational and, ultimately, citizen value. Following these findings, the primary objective of this research was to provide an instrumental model to foster e-Participation sustainability across Government and Public Administration towards a participatory, inclusive, collaborative and deliberative democracy. The developed artefact, consisting in an e-Participation Organisational Semantic Model (ePOSM) underpinned by a BPM-steered approach, introduces this vision. This approach to e-Participation was modelled through a semi-formal lightweight ontology stack structured in four sub-ontologies, namely e-Participation Strategy, Organisational Units, Functions and Roles. The ePOSM facilitates e-Participation sustainability by: (1) Promoting a common and cross-functional understanding of the concepts underlying e-Participation implementation and of their articulation that bridges the gap between technical and non-technical users; (2) Providing an organisational model which allows a centralised and consistent roll-out of strategy-driven e-Participation initiatives, supported by operational units dedicated to the execution of transformation projects and participatory processes; (3) Providing a standardised organisational structure, goals, functions and roles related to e-Participation processes that enhances process-level interoperability among government agencies; (4) Providing a representation usable in software development for business processes’ automation, which allows advanced querying using a reasoner or inference engine to retrieve concrete and specific information about the e-Participation processes in place. An evaluation of the achieved outcomes, as well a comparative analysis with existent models, suggested that this innovative approach tackling the organisational planning dimension can constitute a stepping stone to harness e-Participation value.

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The assessment of existing timber structures is often limited to information obtained from non or semi destructive testing, as mechanical testing is in many cases not possible due to its destructive nature. Therefore, the available data provides only an indirect measurement of the reference mechanical properties of timber elements, often obtained through empirical based correlations. Moreover, the data must result from the combination of different tests, as to provide a reliable source of information for a structural analysis. Even if general guidelines are available for each typology of testing, there is still a need for a global methodology allowing to combine information from different sources and infer upon that information in a decision process. In this scope, the present work presents the implementation of a probabilistic based framework for safety assessment of existing timber elements. This methodology combines information gathered in different scales and follows a probabilistic framework allowing for the structural assessment of existing timber elements with possibility of inference and updating of its mechanical properties, through Bayesian methods. The probabilistic based framework is based in four main steps: (i) scale of information; (ii) measurement data; (iii) probability assignment; and (iv) structural analysis. In this work, the proposed methodology is implemented in a case study. Data was obtained through a multi-scale experimental campaign made to old chestnut timber beams accounting correlations of non and semi-destructive tests with mechanical properties. Finally, different inference scenarios are discussed aiming at the characterization of the safety level of the elements.

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A novel framework for probabilistic-based structural assessment of existing structures, which combines model identification and reliability assessment procedures, considering in an objective way different sources of uncertainty, is presented in this paper. A short description of structural assessment applications, provided in literature, is initially given. Then, the developed model identification procedure, supported in a robust optimization algorithm, is presented. Special attention is given to both experimental and numerical errors, to be considered in this algorithm convergence criterion. An updated numerical model is obtained from this process. The reliability assessment procedure, which considers a probabilistic model for the structure in analysis, is then introduced, incorporating the results of the model identification procedure. The developed model is then updated, as new data is acquired, through a Bayesian inference algorithm, explicitly addressing statistical uncertainty. Finally, the developed framework is validated with a set of reinforced concrete beams, which were loaded up to failure in laboratory.

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BACKGROUND: Screening and treatment of latent tuberculosis infection (LTBI) in asylum seekers (AS) may prevent future cases of tuberculosis. As the screening with Interferon Gamma Release Assay (IGRA) is costly, the objective of this study was to assess which factors were associated with LTBI and to define a score allowing the selection of AS with the highest risk of LTBI. METHODS: In across-sectional study, AS seekers recently arrived in Vaud County, after screening for tuberculosis at the border were offered screening for LTBI with T-SPOT.TB and questionnaire on potentially risk factors. The factors associated with LTBI were analyzed by univariate and multivariate regression. RESULTS: Among 393 adult AS, 98 (24.93%) had a positive IGRA response, five of them with active tuberculosis previously undetected. Six factors associated with LTBI were identified in multivariate analysis: origin, travel conditions, marital status, cough, age and prior TB exposure. Their combination leads to a robust LTBI predictive score. CONCLUSIONS: The prevalence of LTBI and active tuberculosis in AS is high. A predictive score integrating six factors could identify the asylum seekers with the highest risk for LTBI.