905 resultados para Hierarchical Bayes
Resumo:
The agricultural potential is generally assessed and managed based on a one-dimensional vision of the soil profile, however, the increased appreciation of sustainable production has stimulated studies on faster and more accurate evaluation techniques and methods of the agricultural potential on detailed scales. The objective of this study was to investigate the possibility of using soil magnetic susceptibility for the identification of landscape segments on a detailed scale in the region of Jaboticabal, São Paulo State. The studied area has two slope curvatures: linear and concave, subdivided into three landscape segments: upper slope (US, concave), middle slope (MS, linear) and lower slope (LS, linear). In each of these segments, 20 points were randomly sampled from a database with 207 samples forming a regular grid installed in each landscape segment. The soil physical and chemical properties, CO2 emissions (FCO2) and magnetic susceptibility (MS) of the samples were evaluated represented by: magnetic susceptibility of air-dried fine earth (MS ADFE), magnetic susceptibility of the total sand fraction (MS TS) and magnetic susceptibility of the clay fraction (MS Cl) in the 0.00 - 0.15 m layer. The principal component analysis showed that MS is an important property that can be used to identify landscape segments, because the correlation of this property within the first principal component was high. The hierarchical cluster analysis method identified two groups based on the variables selected by principal component analysis; of the six selected variables, three were related to magnetic susceptibility. The landscape segments were differentiated similarly by the principal component analysis and by the cluster analysis using only the properties with higher discriminatory power. The cluster analysis of MS ADFE, MS TS and MS Cl allowed the formation of three groups that agree with the segment division established in the field. The grouping by cluster analysis indicated MS as a tool that could facilitate the identification of landscape segments and enable the mapping of more homogeneous areas at similar locations.
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We study the relationship between topological scales and dynamic time scales in complex networks. The analysis is based on the full dynamics towards synchronization of a system of coupled oscillators. In the synchronization process, modular structures corresponding to well-defined communities of nodes emerge in different time scales, ordered in a hierarchical way. The analysis also provides a useful connection between synchronization dynamics, complex networks topology, and spectral graph analysis.
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Expression data contribute significantly to the biological value of the sequenced human genome, providing extensive information about gene structure and the pattern of gene expression. ESTs, together with SAGE libraries and microarray experiment information, provide a broad and rich view of the transcriptome. However, it is difficult to perform large-scale expression mining of the data generated by these diverse experimental approaches. Not only is the data stored in disparate locations, but there is frequent ambiguity in the meaning of terms used to describe the source of the material used in the experiment. Untangling semantic differences between the data provided by different resources is therefore largely reliant on the domain knowledge of a human expert. We present here eVOC, a system which associates labelled target cDNAs for microarray experiments, or cDNA libraries and their associated transcripts with controlled terms in a set of hierarchical vocabularies. eVOC consists of four orthogonal controlled vocabularies suitable for describing the domains of human gene expression data including Anatomical System, Cell Type, Pathology and Developmental Stage. We have curated and annotated 7016 cDNA libraries represented in dbEST, as well as 104 SAGE libraries,with expression information,and provide this as an integrated, public resource that allows the linking of transcripts and libraries with expression terms. Both the vocabularies and the vocabulary-annotated libraries can be retrieved from http://www.sanbi.ac.za/evoc/. Several groups are involved in developing this resource with the aim of unifying transcript expression information.
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Peatlands are soil environments that accumulate water and organic carbon and function as records of paleo-environmental changes. The variability in the composition of organic matter is reflected in their morphological, physical, and chemical properties. The aim of this study was to characterize these properties in peatlands from the headwaters of the Rio Araçuaí (Araçuaí River) in different stages of preservation. Two cores from peatlands with different vegetation types (moist grassland and semideciduous seasonal forest) from the Rio Preto [Preto River] headwaters (conservation area) and the Córrego Cachoeira dos Borges [Cachoeira dos Borges stream] (disturbed area) were sampled. Both are tributaries of the Rio Araçuaí. Samples were taken from layers of 15 cm, and morphological, physical, and chemical analyses were performed. The 14C age and δ13C values were determined in three samples from each core and the vertical growth and organic carbon accumulation rates were estimated. Dendrograms were constructed for each peatland by hierarchical clustering of similar layers with data from 34 parameters. The headwater peatlands of the Rio Araçuaí have a predominance of organic material in an advanced stage of decomposition and their soils are classified as Typic Haplosaprists. The organic matter in the Histosols of the peatlands of the headwaters of the Rio Araçuaí shows marked differences with respect to its morphological, physical, and chemical composition, as it is influenced by the type of vegetation that colonizes it. The peat from the headwaters of the Córrego Cachoeira dos Borges is in a more advanced stage of degradation than the peat from the Rio Preto, which highlights the urgent need for protection of these ecosystems/soil environments.
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The observation that real complex networks have internal structure has important implication for dynamic processes occurring on such topologies. Here we investigate the impact of community structure on a model of information transfer able to deal with both search and congestion simultaneously. We show that networks with fuzzy community structure are more efficient in terms of packet delivery than those with pronounced community structure. We also propose an alternative packet routing algorithm which takes advantage of the knowledge of communities to improve information transfer and show that in the context of the model an intermediate level of community structure is optimal. Finally, we show that in a hierarchical network setting, providing knowledge of communities at the level of highest modularity will improve network capacity by the largest amount.
Resumo:
Context: Foreign body aspiration (FbA) is a serious problem in children. Accurate clinical and radiographic diagnosis is important because missed or delayed diagnosis can result in respiratory difficulties ranging from life-treatening airway obstruction to chronic wheezing or recurrent pneumonia. Bronchoscopy also has risks and accurate clinical and radiographc diagnosis can support the decision of bronchoscopy. Objective: To rewiev the diagnostic accuracy of clinical presentation (CP) and pulmonary radiograph (PR) for the diagnosis of FbA. There is no previous rewievMethods: A search of Medline is conducted for articles containing data regarding CP and PR signes of FbA. Calculation of likelihood ratios (LR) and pre and post test probability using Bayes theorem were performed for all signs of CP and PR. Inclusion criteria: Articles containing prospective data regarding CP and PR of FbA. Exclusion criteria: Retrospectives studies. Articles containing incomplete data for calculation of LR. Results: Five prospectives studies are included with a total of 585 patients. Prevalence of FbA is 63% in children suspected of FbA. If CP is normal, probability of FbA is 25% and if PR is normal, probability is 14%. If CP is pathologic, probability of FbA is 69-76% with presence of cough (LR = 1.32) or dyspnea (LR = 1.84) or localized crackles (LR = 1.5). Probability is 81-88% if cyanosis (LR = 4.8) or decreased breaths sounds (LR = 4.3) or asymetric auscultation (LR = 2.9) or localized wheezing (LR = 2.5) are present. When CP is anormal and PR show mediatinal shift (LR = 100), pneumomediatin (LR = 100), radio opaque foreign body (LR = 100), lobar distention (LR = 4), atelectasis (LR = 2.5), inspiratory/expiratory abnormal (LR = 7), the probability of FbA is 96-100%. If CP is normal and PR is abnormal the probability is 40-100%. If CP is abnormal and PR is normal the probability is 55-75%. Conclusions: This rewiev of prospective studies demonstrates the importance of CP and PR and an algorithm can be proposed. When CP is abnormal with or without PR pathologic, the probability of FbA is high and bronchoscopy is indicated. When CP and PR are normal the probability of FbA is low and bronchoscopy is not necessary immediatly, observation should be proposed. This approach should be validated with prospective study.
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Research on achievement goals usually defines mastery goals as the desire to acquire knowledge, and performance goals as the desire to outperform (or not to underperform) others. Educational contexts are most of the time social contexts, involving various persons and groups, of various hierarchical positions, and various cultural and ideological contexts. Surprisingly, most research in the achievement goal field has been conducted at an individual level of analysis. In the present paper, we will review the social consequences and antecedents of goal endorsement. This research indicates that goals strongly affect the way one behaves with co-learners. Moreover, it suggests that more than merely individual dispositions, goals reflect the social relation students have with other persons, institutions, and with the society to which they belong. We conclude this paper by setting an agenda for future achievement goal research.
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We present a heuristic method for learning error correcting output codes matrices based on a hierarchical partition of the class space that maximizes a discriminative criterion. To achieve this goal, the optimal codeword separation is sacrificed in favor of a maximum class discrimination in the partitions. The creation of the hierarchical partition set is performed using a binary tree. As a result, a compact matrix with high discrimination power is obtained. Our method is validated using the UCI database and applied to a real problem, the classification of traffic sign images.
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We conduct a large-scale comparative study on linearly combining superparent-one-dependence estimators (SPODEs), a popular family of seminaive Bayesian classifiers. Altogether, 16 model selection and weighing schemes, 58 benchmark data sets, and various statistical tests are employed. This paper's main contributions are threefold. First, it formally presents each scheme's definition, rationale, and time complexity and hence can serve as a comprehensive reference for researchers interested in ensemble learning. Second, it offers bias-variance analysis for each scheme's classification error performance. Third, it identifies effective schemes that meet various needs in practice. This leads to accurate and fast classification algorithms which have an immediate and significant impact on real-world applications. Another important feature of our study is using a variety of statistical tests to evaluate multiple learning methods across multiple data sets.
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This article employs a unique data set - covering 25 popular votes on foreign, European and immigration/asylum policy held between 1992 and 2006 in Switzerland - in order to examine the conditional impact of context upon utilitarian, cultural, political and cognitive determinants of individual attitudes toward international openness. Our results reveal clear patterns of cross-level interactions between individual determinants and the project-related context of the vote. Thus, although party cues and political competence have a strong impact on individuals' support for international openness, this impact is substantially mediated by the type of coalition that is operating within the party elite. Similarly, subjective utilitarian and cultural considerations influence the voters' decision in interaction with the content of the proposal submitted to the voters as well as with the framing of the voting campaign.
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In developmental research, the family has mainly been studied through dyadic interaction. Three-way interactions have received less attention, partly because of their complexity. This difficulty may be overcome by distinguishing between four hierarchically embedded functions in three-way interactions: (1) participation (inclusion of all participants), (2) organization (partners keeping to their roles), (3) focalization (sharing a common focus) and (4) affective contact (being in tune). We document this hierarchical model on a sample of 80 families observed in the Lausanne Trilogue Play situation across four different sites. Hierarchy between functions was demonstrated by means of Guttman scalability coefficient. Given the importance of the child's development in a threesome, the pertinence of this model for family assessment is discussed.
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In Switzerland there is a strong movement at a national policy level towards strengthening patient rights and patient involvement in health care decisions. Yet, there is no national programme promoting shared decision making. First decision support tools (prenatal diagnosis and screening) for the counselling process have been developed and implemented. Although Swiss doctors acknowledge that shared decision making is important, hierarchical structures and asymmetric physician-patient relationships are still prevailing. The last years have seen some promising activities regarding the training of medical students and the development of patient support programmes. Swiss direct democracy and the habit of consensual decision making and citizen involvement in general may provide a fertile ground for SDM development in the primary care setting.
Resumo:
Functional connectivity affects demography and gene dynamics in fragmented populations. Besides species-specific dispersal ability, the connectivity between local populations is affected by the landscape elements encountered during dispersal. Documenting these effects is thus a central issue for the conservation and management of fragmented populations. In this study, we compare the power and accuracy of three methods (partial correlations, regressions and Approximate Bayesian Computations) that use genetic distances to infer the effect of landscape upon dispersal. We use stochastic individual-based simulations of fragmented populations surrounded by landscape elements that differ in their permeability to dispersal. The power and accuracy of all three methods are good when there is a strong contrast between the permeability of different landscape elements. The power and accuracy can be further improved by restricting analyses to adjacent pairs of populations. Landscape elements that strongly impede dispersal are the easiest to identify. However, power and accuracy decrease drastically when landscape complexity increases and the contrast between the permeability of landscape elements decreases. We provide guidelines for future studies and underline the needs to evaluate or develop approaches that are more powerful.
Resumo:
To study the stress-induced effects caused by wounding under a new perspective, a metabolomic strategy based on HPLC-MS has been devised for the model plant Arabidopsis thaliana. To detect induced metabolites and precisely localise these compounds among the numerous constitutive metabolites, HPLC-MS analyses were performed in a two-step strategy. In a first step, rapid direct TOF-MS measurements of the crude leaf extract were performed with a ballistic gradient on a short LC-column. The HPLC-MS data were investigated by multivariate analysis as total mass spectra (TMS). Principal components analysis (PCA) and hierarchical cluster analysis (HCA) on principal coordinates were combined for data treatment. PCA and HCA demonstrated a clear clustering of plant specimens selecting the highest discriminating ions given by the complete data analysis, leading to the specific detection of discrete-induced ions (m/z values). Furthermore, pool constitution with plants of homogeneous behaviour was achieved for confirmatory analysis. In this second step, long high-resolution LC profilings on an UPLC-TOF-MS system were used on pooled samples. This allowed to precisely localise the putative biological marker induced by wounding and by specific extraction of accurate m/z values detected in the screening procedure with the TMS spectra.