967 resultados para fuzzy shape optimization


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Closely related species may be very difficult to distinguish morphologically, yet sometimes morphology is the only reasonable possibility for taxonomic classification. Here we present learning-vector-quantization artificial neural networks as a powerful tool to classify specimens on the basis of geometric morphometric shape measurements. As an example, we trained a neural network to distinguish between field and root voles from Procrustes transformed landmark coordinates on the dorsal side of the skull, which is so similar in these two species that the human eye cannot make this distinction. Properly trained neural networks misclassified only 3% of specimens. Therefore, we conclude that the capacity of learning vector quantization neural networks to analyse spatial coordinates is a powerful tool among the range of pattern recognition procedures that is available to employ the information content of geometric morphometrics.

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Recent evidence indicates that B cells are required for susceptibility to infection with Leishmania major in BALB/c mice. In this study, we analyzed the role of the IL-10 produced by B cells in this process. We showed that B cells purified from the spleen of BALB/c mice produced IL-10 in response to stimulation with L. major in vitro. In vivo, early IL-10 mRNA expression is detected after L. major infection in B cells from draining lymph nodes of susceptible BALB/c, but not of resistant C57BL/6 mice. Although adoptive transfer of naive wild-type B cells prior to infection in B cell-deficient BALB/c mice restored Th2 cell development and susceptibility to infection with L. major of these otherwise resistant mice, adoptive transfer of IL-10(-/-) B cells mice did not. B cells stimulated by L. major, following in vitro or in vivo encounter, express the CD1d and CD5 molecules and the IL-10 produced by these cells downregulate IL-12 production by L. major-stimulated dendritic cells. These observations indicate that IL-10 secreting B cells are phenotypically and functionally regulatory B cells. Altogether these results demonstrate that the IL-10 produced by regulatory CD1d+ CD5+ B cells in response to L. major is critical for Th2 cell development in BALB/c mice.

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Monitoring and management of intracranial pressure (ICP) and cerebral perfusion pressure (CPP) is a standard of care after traumatic brain injury (TBI). However, the pathophysiology of so-called secondary brain injury, i.e., the cascade of potentially deleterious events that occur in the early phase following initial cerebral insult-after TBI, is complex, involving a subtle interplay between cerebral blood flow (CBF), oxygen delivery and utilization, and supply of main cerebral energy substrates (glucose) to the injured brain. Regulation of this interplay depends on the type of injury and may vary individually and over time. In this setting, patient management can be a challenging task, where standard ICP/CPP monitoring may become insufficient to prevent secondary brain injury. Growing clinical evidence demonstrates that so-called multimodal brain monitoring, including brain tissue oxygen (PbtO2), cerebral microdialysis and transcranial Doppler among others, might help to optimize CBF and the delivery of oxygen/energy substrate at the bedside, thereby improving the management of secondary brain injury. Looking beyond ICP and CPP, and applying a multimodal therapeutic approach for the optimization of CBF, oxygen delivery, and brain energy supply may eventually improve overall care of patients with head injury. This review summarizes some of the important pathophysiological determinants of secondary cerebral damage after TBI and discusses novel approaches to optimize CBF and provide adequate oxygen and energy supply to the injured brain using multimodal brain monitoring.

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A biplot, which is the multivariate generalization of the two-variable scatterplot, can be used to visualize the results of many multivariate techniques, especially those that are based on the singular value decomposition. We consider data sets consisting of continuous-scale measurements, their fuzzy coding and the biplots that visualize them, using a fuzzy version of multiple correspondence analysis. Of special interest is the way quality of fit of the biplot is measured, since it is well-known that regular (i.e., crisp) multiple correspondence analysis seriously under-estimates this measure. We show how the results of fuzzy multiple correspondence analysis can be defuzzified to obtain estimated values of the original data, and prove that this implies an orthogonal decomposition of variance. This permits a measure of fit to be calculated in the familiar form of a percentage of explained variance, which is directly comparable to the corresponding fit measure used in principal component analysis of the original data. The approach is motivated initially by its application to a simulated data set, showing how the fuzzy approach can lead to diagnosing nonlinear relationships, and finally it is applied to a real set of meteorological data.

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We address the performance optimization problem in a single-stationmulticlass queueing network with changeover times by means of theachievable region approach. This approach seeks to obtainperformance bounds and scheduling policies from the solution of amathematical program over a relaxation of the system's performanceregion. Relaxed formulations (including linear, convex, nonconvexand positive semidefinite constraints) of this region are developedby formulating equilibrium relations satisfied by the system, withthe help of Palm calculus. Our contributions include: (1) newconstraints formulating equilibrium relations on server dynamics;(2) a flow conservation interpretation of the constraintspreviously derived by the potential function method; (3) newpositive semidefinite constraints; (4) new work decomposition lawsfor single-station multiclass queueing networks, which yield newconvex constraints; (5) a unified buffer occupancy method ofperformance analysis obtained from the constraints; (6) heuristicscheduling policies from the solution of the relaxations.

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To provide a quantitative support to the handwriting evidence evaluation, a new method was developed through the computation of a likelihood ratio based on a Bayesian approach. In the present paper, the methodology is briefly described and applied to data collected within a simulated case of a threatening letter. Fourier descriptors are used to characterise the shape of loops of handwritten characters "a" of the true writer of the threatening letter, and: 1) with reference characters "a" of the true writer of the threatening letter, and then 2) with characters "a" of a writer who did not write the threatening letter. The findings support that the probabilistic methodology correctly supports either the hypothesis of authorship or the alternative hypothesis. Further developments will enable the handwriting examiner to use this methodology as a helpful assistance to assess the strength of evidence in handwriting casework.

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We address the problem of scheduling a multi-station multiclassqueueing network (MQNET) with server changeover times to minimizesteady-state mean job holding costs. We present new lower boundson the best achievable cost that emerge as the values ofmathematical programming problems (linear, semidefinite, andconvex) over relaxed formulations of the system's achievableperformance region. The constraints on achievable performancedefining these formulations are obtained by formulatingsystem's equilibrium relations. Our contributions include: (1) aflow conservation interpretation and closed formulae for theconstraints previously derived by the potential function method;(2) new work decomposition laws for MQNETs; (3) new constraints(linear, convex, and semidefinite) on the performance region offirst and second moments of queue lengths for MQNETs; (4) a fastbound for a MQNET with N customer classes computed in N steps; (5)two heuristic scheduling policies: a priority-index policy, anda policy extracted from the solution of a linear programmingrelaxation.

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Crushed seeds of the Moringa oleifera tree have been used traditionally as natural flocculants to clarify drinking water. We previously showed that one of the seed peptides mediates both the sedimentation of suspended particles such as bacterial cells and a direct bactericidal activity, raising the possibility that the two activities might be related. In this study, the conformational modeling of the peptide was coupled to a functional analysis of synthetic derivatives. This indicated that partly overlapping structural determinants mediate the sedimentation and antibacterial activities. Sedimentation requires a positively charged, glutamine-rich portion of the peptide that aggregates bacterial cells. The bactericidal activity was localized to a sequence prone to form a helix-loop-helix structural motif. Amino acid substitution showed that the bactericidal activity requires hydrophobic proline residues within the protruding loop. Vital dye staining indicated that treatment with peptides containing this motif results in bacterial membrane damage. Assembly of multiple copies of this structural motif into a branched peptide enhanced antibacterial activity, since low concentrations effectively kill bacteria such as Pseudomonas aeruginosa and Streptococcus pyogenes without displaying a toxic effect on human red blood cells. This study thus identifies a synthetic peptide with potent antibacterial activity against specific human pathogens. It also suggests partly distinct molecular mechanisms for each activity. Sedimentation may result from coupled flocculation and coagulation effects, while the bactericidal activity would require bacterial membrane destabilization by a hydrophobic loop.

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Shape-dependent local differentials in cell proliferation are considered to be a major driving mechanism of structuring processes in vivo, such as embryogenesis, wound healing, and angiogenesis. However, the specific biophysical signaling by which changes in cell shape contribute to cell cycle regulation remains poorly understood. Here, we describe our study of the roles of nuclear volume and cytoskeletal mechanics in mediating shape control of proliferation in single endothelial cells. Micropatterned adhesive islands were used to independently control cell spreading and elongation. We show that, irrespective of elongation, nuclear volume and apparent chromatin decondensation of cells in G1 systematically increased with cell spreading and highly correlated with DNA synthesis (percent of cells in the S phase). In contrast, cell elongation dramatically affected the organization of the actin cytoskeleton, markedly reduced both cytoskeletal stiffness (measured dorsally with atomic force microscopy) and contractility (measured ventrally with traction microscopy), and increased mechanical anisotropy, without affecting either DNA synthesis or nuclear volume. Our results reveal that the nuclear volume in G1 is predictive of the proliferative status of single endothelial cells within a population, whereas cell stiffness and contractility are not. These findings show that the effects of cell mechanics in shape control of proliferation are far more complex than a linear or straightforward relationship. Our data are consistent with a mechanism by which spreading of cells in G1 partially enhances proliferation by inducing nuclear swelling and decreasing chromatin condensation, thereby rendering DNA more accessible to the replication machinery.

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Selostus: Ó-lactalbumiinin ja ¿̐ư-lactoglobuliinin sentrifugointierotuksen optimointi