869 resultados para dynamic panel data.


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Objective: The identification of regulatory T cells (Treg cells) as CD4(+)CD25(high) cells may be upset by the increased frequency of activated effector T cells (Teff cells) in inflammatory diseases such as systemic lupus erythematosus (SLE). This study aimed to evaluate the frequency of T-cell subsets according to the expression of CD25 and CD127 in active (A-SLE) and inactive SLE (I-SLE). Methods: Peripheral blood mononuclear cells (PBMCs) from 26 A-SLE patients (SLE Disease Activity Index (SLEDAI) = 10.17 +/- 3.7), 31 I-SLE patients (SLEDAI = 0), and 26 healthy controls (HC) were analysed by multicolour flow. cytometry. Results: CD25(high) cell frequency was increased in A-SLE (5.2 +/- 5.7%) compared to I-SLE (3.4 +/- 3.4%) and HC (1.73 +/- 0.8%) (p < 0.01). However, the percentage of FoxP3(+) cells in the CD25(high) subset was decreased in A-SLE (24.6 +/- 16.4%) compared to I-SLE (33.7 +/- 16) and HC (45 +/- 25.1%) (p < 0.01). This was partly due to the increased frequency of Teff cells (CD25(high)CD127(+)FoxP3(empty set)) in A-SLE (10.7 +/- 7.3%) compared to I-SLE (8.5 +/- 6.5) and HC (6.1 +/- 1.8%) (p = 0.02). Hence the frequency of Treg cells (CD25(+/high)CD127(low/empty set)FoxP3(+)) was equivalent in A-SLE (1.4 +/- 0.8%), I-SLE (1.37 +/- 1.0%), and HC (1.13 +/- 0.59%) (p = 0.42). A-SLE presented an increased frequency of CD25(+)CD127(+)FoxP3(+) and CD25(empty set)FoxP3(+)CD127(low/empty set) T cells, which may represent intermediate phenotypes between Treg and Teff cells. Conclusions: The present study has provided data supporting normal Treg cell frequency in A-SLE and I-SLE as well as increased frequency of Teff cells in A-SLE. This scenario reflects a Treg/Teff ratio imbalance that may favour the inflammatory phenotype of the disease. In addition, the increased frequency of T cells with putative intermediate phenotypes may be compatible with a highly dynamic immune system in SLE.

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Objectives. In this study, we aimed to identify ancestry informative haplotypes and make interethnic admixture estimates using X-chromosome markers. Methods. A significant sample (461 individuals) of European, African, and Native American populations was analyzed, and four linkage groups were identified. The data obtained were used to describe the ancestral contribution of populations from four different geographical regions of Brazil (745 individuals). Results. The global interethnic admixture estimates of the four mixed populations under investigation were calculated applying all the 24 insertion/deletion (INDEL) markers. In the North region, a larger Native Americans ancestry was observed (42%). The Northeast and Southeast regions had smaller Native American contribution (27% in both of them). In the South region, there was a large European contribution (46%). Conclusions. The estimates obtained are compatible with expectations for a colonization model with biased admixture between European men (one X chromosome) and Native American and African women (two X chromosomes), so the 24 X-INDEL panel described here can be a useful to make admixture interethnic estimates in Brazilian populations. Am. J. Hum. Biol. 22:849-852,2010. (C) 2010 Wiley-Liss, Inc.

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Estimating the proportions of different ancestries in admixed populations is very important in population genetics studies, and it is particularly important for detecting population substructure effects in case-control association studies. In this work, a set of 48 ancestry, informative insertion, deletion polymorphisms (INDELs) were selected with the goal of efficiently measuring the proportions of three different ancestries (sub-Saharan African, European, and Native American) in mixed populations. All selected markers can be easily analyzed via multiplex PCR and detected with standard capillary electrophoresis. A total of 593 unrelated individuals representative of European, African, and Native American parental populations were typed, as were 380 individuals from three Brazilian populations with known admixture patterns. As expected, the interethnic admixture estimates show that individuals from southern Brazil present an almost exclusively European ancestry; Afro-descendant communities in the Amazon region, apart from the major African contribution, present some degree of admixture with Europeans and Native Americans; and a sample from Belem, in the northeastern Amazon, shows a significant contribution of the three ethnic groups, although with a greater European proportion. In summary, a panel of ancestry-informative INDELs was optimized and proven to be a variable tool for estimating individual and global ancestry proportions in admixed populations. The ability to accurately infer interethnic admixtures highlights the usefulness of this marker set for assessing population substructure in association studies, particularly those conducted in Brazilian and other Latin American populations sharing trihybrid ancestry patterns. Hum Mutat 31:184-190, 2010. (C) 2009 Wiley-Liss, Inc.

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A dynamic modelling methodology, which combines on-line variable estimation and parameter identification with physical laws to form an adaptive model for rotary sugar drying processes, is developed in this paper. In contrast to the conventional rate-based models using empirical transfer coefficients, the heat and mass transfer rates are estimated by using on-line measurements in the new model. Furthermore, a set of improved sectional solid transport equations with localized parameters is developed in this work to reidentified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.place the global correlation for the computation of solid retention time. Since a number of key model variables and parameters are identified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.

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Questionnaire surveys, while more economical, typically achieve poorer response rates than interview surveys. We used data from a national volunteer cohort of young adult twins, who were scheduled for assessment by questionnaire in 1989 and by interview in 1996-2000, to identify predictors of questionnaire non-response. Out of a total of 8536 twins, 5058 completed the questionnaire survey (59% response rate), and 6255 completed a telephone interview survey conducted a decade later (73% response rate). Multinomial logit models were fitted to the interview data to identify socioeconomic, psychiatric and health behavior correlates of non-response in the earlier questionnaire survey. Male gender, education below University level, and being a dizygotic rather than monozygotic twin, all predicted reduced likelihood of participating in the questionnaire survey. Associations between questionnaire response status and psychiatric history and health behavior variables were modest, with history of alcohol dependence and childhood conduct disorder predicting decreased probability of returning a questionnaire, and history of smoking and heavy drinking more weakly associated with non-response. Body-mass index showed no association with questionnaire non-response. Despite a poor response rate to the self-report questionnaire survey, we found only limited sampling biases for most variables. While not appropriate for studies where socioeconomic variables are critical, it appears that survey by questionnaire, with questionnaire administration by telephone to non-responders, will represent a viable strategy for gene-mapping studies requiring that large numbers of relatives be screened.

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We are witnessing an enormous growth in biological nitrogen removal from wastewater. It presents specific challenges beyond traditional COD (carbon) removal. A possibility for optimised process design is the use of biomass-supporting media. In this paper, attached growth processes (AGP) are evaluated using dynamic simulations. The advantages of these systems that were qualitatively described elsewhere, are validated quantitatively based on a simulation benchmark for activated sludge treatment systems. This simulation benchmark is extended with a biofilm model that allows for fast and accurate simulation of the conversion of different substrates in a biofilm. The economic feasibility of this system is evaluated using the data generated with the benchmark simulations. Capital savings due to volume reduction and reduced sludge production are weighed out against increased aeration costs. In this evaluation, effluent quality is integrated as well.

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This paper presents an artificial neural network applied to the forecasting of electricity market prices, with the special feature of being dynamic. The dynamism is verified at two different levels. The first level is characterized as a re-training of the network in every iteration, so that the artificial neural network can able to consider the most recent data at all times, and constantly adapt itself to the most recent happenings. The second level considers the adaptation of the neural network’s execution time depending on the circumstances of its use. The execution time adaptation is performed through the automatic adjustment of the amount of data considered for training the network. This is an advantageous and indispensable feature for this neural network’s integration in ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to the market negotiating players of MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).

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This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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The tongue is the most important and dynamic articulator for speech formation, because of its anatomic aspects (particularly, the large volume of this muscular organ comparatively to the surrounding organs of the vocal tract) and also due to the wide range of movements and flexibility that are involved. In speech communication research, a variety of techniques have been used for measuring the three-dimensional vocal tract shapes. More recently, magnetic resonance imaging (MRI) becomes common; mainly, because this technique allows the collection of a set of static and dynamic images that can represent the entire vocal tract along any orientation. Over the years, different anatomical organs of the vocal tract have been modelled; namely, 2D and 3D tongue models, using parametric or statistical modelling procedures. Our aims are to present and describe some 3D reconstructed models from MRI data, for one subject uttering sustained articulations of some typical Portuguese sounds. Thus, we present a 3D database of the tongue obtained by stack combinations with the subject articulating Portuguese vowels. This 3D knowledge of the speech organs could be very important; especially, for clinical purposes (for example, for the assessment of articulatory impairments followed by tongue surgery in speech rehabilitation), and also for a better understanding of acoustic theory in speech formation.

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This paper analyses earthquake data in the perspective of dynamical systems and its Pseudo Phase Plane representation. The seismic data is collected from the Bulletin of the International Seismological Centre. The geological events are characterised by their magnitude and geographical location and described by means of time series of sequences of Dirac impulses. Fifty groups of data series are considered, according to the Flinn-Engdahl seismic regions of Earth. For each region, Pearson’s correlation coefficient is used to find the optimal time delay for reconstructing the Pseudo Phase Plane. The Pseudo Phase Plane plots are then analysed and characterised.

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Wireless Sensor Networks (WSNs) are highly distributed systems in which resource allocation (bandwidth, memory) must be performed efficiently to provide a minimum acceptable Quality of Service (QoS) to the regions where critical events occur. In fact, if resources are statically assigned independently from the location and instant of the events, these resources will definitely be misused. In other words, it is more efficient to dynamically grant more resources to sensor nodes affected by critical events, thus providing better network resource management and reducing endto- end delays of event notification and tracking. In this paper, we discuss the use of a WSN management architecture based on the active network management paradigm to provide the real-time tracking and reporting of dynamic events while ensuring efficient resource utilization. The active network management paradigm allows packets to transport not only data, but also program scripts that will be executed in the nodes to dynamically modify the operation of the network. This presumes the use of a runtime execution environment (middleware) in each node to interpret the script. We consider hierarchical (e.g. cluster-tree, two-tiered architecture) WSN topologies since they have been used to improve the timing performance of WSNs as they support deterministic medium access control protocols.

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Data analytic applications are characterized by large data sets that are subject to a series of processing phases. Some of these phases are executed sequentially but others can be executed concurrently or in parallel on clusters, grids or clouds. The MapReduce programming model has been applied to process large data sets in cluster and cloud environments. For developing an application using MapReduce there is a need to install/configure/access specific frameworks such as Apache Hadoop or Elastic MapReduce in Amazon Cloud. It would be desirable to provide more flexibility in adjusting such configurations according to the application characteristics. Furthermore the composition of the multiple phases of a data analytic application requires the specification of all the phases and their orchestration. The original MapReduce model and environment lacks flexible support for such configuration and composition. Recognizing that scientific workflows have been successfully applied to modeling complex applications, this paper describes our experiments on implementing MapReduce as subworkflows in the AWARD framework (Autonomic Workflow Activities Reconfigurable and Dynamic). A text mining data analytic application is modeled as a complex workflow with multiple phases, where individual workflow nodes support MapReduce computations. As in typical MapReduce environments, the end user only needs to define the application algorithms for input data processing and for the map and reduce functions. In the paper we present experimental results when using the AWARD framework to execute MapReduce workflows deployed over multiple Amazon EC2 (Elastic Compute Cloud) instances.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

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This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática