795 resultados para label hierarchical clustering


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Several popular Machine Learning techniques are originally designed for the solution of two-class problems. However, several classification problems have more than two classes. One approach to deal with multiclass problems using binary classifiers is to decompose the multiclass problem into multiple binary sub-problems disposed in a binary tree. This approach requires a binary partition of the classes for each node of the tree, which defines the tree structure. This paper presents two algorithms to determine the tree structure taking into account information collected from the used dataset. This approach allows the tree structure to be determined automatically for any multiclass dataset.

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We study a symplectic chain with a non-local form of coupling by means of a standard map lattice where the interaction strength decreases with the lattice distance as a power-law, in Such a way that one can pass continuously from a local (nearest-neighbor) to a global (mean-field) type of coupling. We investigate the formation of map clusters, or spatially coherent structures generated by the system dynamics. Such clusters are found to be related to stickiness of chaotic phase-space trajectories near periodic island remnants, and also to the behavior of the diffusion coefficient. An approximate two-dimensional map is derived to explain some of the features of this connection. (C) 2008 Elsevier Ltd. All rights reserved.

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Cationic lipids-DNA complexes (lipoplexes) have been used for delivery of nucleic acids into cells in vitro and in vivo. Despite the fact that, over the last decade, significant progress in the understanding of the cellular pathways and mechanisms involved in lipoplexes-mediated gene transfection have been achieved, a convincing relationship between the structure of lipoplexes and their in vivo and in vitro transfection activity is still missing. How does DNA affect the lipid packing and what are the consequences for transfection efficiency is the point we want to address here. We investigated the bilayer organization in cationic liposomes by electron spin resonance (ESR). Phospholipids spin labeled at the 5th and 16th carbon atoms were incorporated into the DNA/diC14-amidine complex. Our data demonstrate that electrostatic interactions involved in the formation of DNA-cationic lipid complex modify the packing of the cationic lipid membrane. DNA rigidifies the amidine fluid bilayer and fluidizes the amidine rigid bilayer just below the gel-fluid transition temperature. These effects were not observed with single nucleotides and are clearly related to the repetitive charged motif present in the DNA chain and not to a charge-charge interaction. These modifications of the initial lipid packing of the cationic lipid may reorient its cellular pathway towards different routes. A better knowledge of the cationic lipid packing before and after interaction with DNA may therefore contribute to the design of lipoplexes capable to reach specific cellular targets. (c) 2009 Elsevier B.V. All rights reserved.

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A continuous version of the hierarchical spherical model at dimension d=4 is investigated. Two limit distributions of the block spin variable X(gamma), normalized with exponents gamma = d + 2 and gamma=d at and above the critical temperature, are established. These results are proven by solving certain evolution equations corresponding to the renormalization group (RG) transformation of the O(N) hierarchical spin model of block size L(d) in the limit L down arrow 1 and N ->infinity. Starting far away from the stationary Gaussian fixed point the trajectories of these dynamical system pass through two different regimes with distinguishable crossover behavior. An interpretation of this trajectories is given by the geometric theory of functions which describe precisely the motion of the Lee-Yang zeroes. The large-N limit of RG transformation with L(d) fixed equal to 2, at the criticality, has recently been investigated in both weak and strong (coupling) regimes by Watanabe (J. Stat. Phys. 115:1669-1713, 2004) . Although our analysis deals only with N = infinity case, it complements various aspects of that work.

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Differently from theoretical scale-free networks, most real networks present multi-scale behavior, with nodes structured in different types of functional groups and communities. While the majority of approaches for classification of nodes in a complex network has relied on local measurements of the topology/connectivity around each node, valuable information about node functionality can be obtained by concentric (or hierarchical) measurements. This paper extends previous methodologies based on concentric measurements, by studying the possibility of using agglomerative clustering methods, in order to obtain a set of functional groups of nodes, considering particular institutional collaboration network nodes, including various known communities (departments of the University of Sao Paulo). Among the interesting obtained findings, we emphasize the scale-free nature of the network obtained, as well as identification of different patterns of authorship emerging from different areas (e.g. human and exact sciences). Another interesting result concerns the relatively uniform distribution of hubs along concentric levels, contrariwise to the non-uniform pattern found in theoretical scale-free networks such as the BA model. (C) 2008 Elsevier B.V. All rights reserved.

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In this work, we propose a hierarchical extension of the polygonality index as the means to characterize geographical planar networks. By considering successive neighborhoods around each node, it is possible to obtain more complete information about the spatial order of the network at progressive spatial scales. The potential of the methodology is illustrated with respect to synthetic and real geographical networks.

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Hierarchical assemblies of CaMoO4 (CM) nano-octahedrons were obtained by microwave-assisted hydrothemial synthesis at 120 degrees C for different times. These structures were structurally, morphologically and optically characterized by X-ray diffraction, micro-Raman spectroscopy, field-emission gun scanning electron microscopy, ultraviolet-visible absorption spectroscopy and photoluminescence measurements. First-principle calculations have been carried out to understand the structural and electronic order-disorder effects as a function of the particle/region size. Supercells of different dimensions were constructed to simulate the geometric distortions along both they and z planes of the scheelite structure. Based on these experimental results and with the help of detailed structural simulations, we were able to model the nature of the order-disorder in this important class of materials and discuss the consequent implications on its physical properties, in particular, the photoluminescence properties of CM nanocrystals.

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The various stages of the interaction between the detergent Triton X-100 (TTX-100) and membranes of whole red blood cells (RBC) were investigated in a broad range of detergent concentrations. The interaction was monitored by RBC hemolysis-assessed by release of intracellular hemoglobin (Hb) and inorganic phosphate- and by analysis of EPR spectra of a fatty acid spin probe intercalated in whole RBC suspensions, as well as pellets and supernatants obtained upon centrifugation of detergent-treated cells. Hemolysis finished at ca. 0.9 mM TTX-100. Spectral analysis and calculation of order parameters (S) indicated that a complex sequence of events takes place, and allowed the characterization of various structures formed in the different stages of detergent-membrane interaction. Upon reaching the end of cell lysis, essentially no pellet was detected, the remaining EPR signal being found almost entirely in the supernatants. Calculated order parameters revealed that whole RBC suspensions, pellets, and supernatants possessed a similar degree of molecular packing, which decreased to a small extent up to 2.5 mM detergent. Between 3.2 and 10 mM TTX-100, a steep decrease in S was observed for both whole RBC suspensions and supernatants. Above 10 mM detergent, S decreased in a less pronounced manner and the EPR spectra approached that of pure TTX-100 micelles. The data were interpreted in terms of the following events: at the lower detergent concentrations, an increase in membrane permeability occurs: the end of hemolysis coincides with the lack of pellet upon centrifugation. Up to 2.5 mM TTX-100 the supernatants consist of a (very likely) heterogeneous population of membrane fragments with molecular packing similar to that of whole cells. As the detergent concentration increases, mixed micelles are formed containing lipid and/or protein, approaching the packing found in pure TTX-100 micelles. This analysis is in agreement with the models proposed by Lasch (Biochim. Biophys Acta 1241 (1995) 269-292) and by Le Maire and coworkers (Biochim. Biophys. Acta 1508 (2000) 86-111). (C) 2010 Elsevier B.V. All rights reserved.

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The necessity to adapt sensors based on electrochemical techniques for high throughput analysis control increases the interest to develop new analytical systems able to perform measurements under buffer now. In this report we explored the possibility of employing a new system to make impedimetric measurements to detect the interaction between proteins and small molecules. The well-known biotin-streptavidin interaction was adopted to evaluate the proposed assembly. This system allows us to perform experiments under flow. Magnetic beads functionalized with streptavidin were used and first characterized using AFM and FTIR. Non-faradic impedance spectroscopy allowed the detection of the biotin-streptavidin interaction. Using our new system and under a flow of PBS buffer, 5 10-5 M of biotin was detected with a stable signal. (c) 2007 Elsevier B.V. All rights reserved.

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Data mining is a relatively new field of research that its objective is to acquire knowledge from large amounts of data. In medical and health care areas, due to regulations and due to the availability of computers, a large amount of data is becoming available [27]. On the one hand, practitioners are expected to use all this data in their work but, at the same time, such a large amount of data cannot be processed by humans in a short time to make diagnosis, prognosis and treatment schedules. A major objective of this thesis is to evaluate data mining tools in medical and health care applications to develop a tool that can help make rather accurate decisions. In this thesis, the goal is finding a pattern among patients who got pneumonia by clustering of lab data values which have been recorded every day. By this pattern we can generalize it to the patients who did not have been diagnosed by this disease whose lab values shows the same trend as pneumonia patients does. There are 10 tables which have been extracted from a big data base of a hospital in Jena for my work .In ICU (intensive care unit), COPRA system which is a patient management system has been used. All the tables and data stored in German Language database.

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Background: Home-management of malaria (HMM) strategy improves early access of anti-malarial medicines to high-risk groups in remote areas of sub-Saharan Africa. However, limited data are available on the effectiveness of using artemisinin-based combination therapy (ACT) within the HMM strategy. The aim of this study was to assess the effectiveness of artemether-lumefantrine (AL), presently the most favoured ACT in Africa, in under-five children with uncomplicated Plasmodium falciparum malaria in Tanzania, when provided by community health workers (CHWs) and administered unsupervised by parents or guardians at home. Methods: An open label, single arm prospective study was conducted in two rural villages with high malaria transmission in Kibaha District, Tanzania. Children presenting to CHWs with uncomplicated fever and a positive rapid malaria diagnostic test (RDT) were provisionally enrolled and provided AL for unsupervised treatment at home. Patients with microscopy confirmed P. falciparum parasitaemia were definitely enrolled and reviewed weekly by the CHWs during 42 days. Primary outcome measure was PCR corrected parasitological cure rate by day 42, as estimated by Kaplan-Meier survival analysis. This trial is registered with ClinicalTrials.gov, number NCT00454961. Results: A total of 244 febrile children were enrolled between March-August 2007. Two patients were lost to follow up on day 14, and one patient withdrew consent on day 21. Some 141/241 (58.5%) patients had recurrent infection during follow-up, of whom 14 had recrudescence. The PCR corrected cure rate by day 42 was 93.0% (95% CI 88.3%-95.9%). The median lumefantrine concentration was statistically significantly lower in patients with recrudescence (97 ng/mL [IQR 0-234]; n = 10) compared with reinfections (205 ng/mL [114-390]; n = 92), or no parasite reappearance (217 [121-374] ng/mL; n = 70; p <= 0.046). Conclusions: Provision of AL by CHWs for unsupervised malaria treatment at home was highly effective, which provides evidence base for scaling-up implementation of HMM with AL in Tanzania.

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Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

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We present the hglm package for fitting hierarchical generalized linear models. It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the model.