An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

Stereospecificity of the siderophore pyochelin outer membrane transporters in fluorescent pseudomonads.

Pyochelin (Pch) and enantio-pyochelin (EPch) are enantiomer siderophores that are produced by Pseudomonas aeruginosa and Pseudomonas fluorescens, respectively, under iron limitation. Pch promotes growth of P. aeruginosa when iron is scarce, and EPch carries out the same biological function in P. fluorescens. However, the two siderophores are unable to promote growth in the heterologous species, indicating that siderophore-mediated iron uptake is highly stereospecific. In the present work, using binding and iron uptake assays, we found that FptA, the Fe-Pch outer membrane transporter of P. aeruginosa, recognized (K(d) = 2.5 +/- 1.1 nm) and transported Fe-Pch but did not interact with Fe-EPch. Likewise, FetA, the Fe-EPch receptor of P. fluorescens, was specific for Fe-EPch (K(d) = 3.7 +/- 2.1 nm) but did not bind and transport Fe-Pch. Growth promotion experiments performed under iron-limiting conditions confirmed that FptA and FetA are highly specific for Pch and EPch, respectively. When fptA and fetA along with adjacent transport genes involved in siderophore uptake were swapped between the two bacterial species, P. aeruginosa became able to utilize Fe-EPch as an iron source, and P. fluorescens was able to grow with Fe-Pch. Docking experiments using the FptA structure and binding assays showed that the stereospecificity of Pch recognition by FptA was mostly due to the configuration of the siderophore chiral centers C4'' and C2'' and was only weakly dependent on the configuration of the C4' carbon atom. Together, these findings increase our understanding of the stereospecific interaction between Pch and its outer membrane receptor FptA.

Incremental neural networks for function approximation

A new strategy for incremental building of multilayer feedforward neural networks is proposed in the context of approximation of functions from R-p to R-q using noisy data. A stopping criterion based on the properties of the noise is also proposed. Experimental results for both artificial and real data are performed and two alternatives of the proposed construction strategy are compared.

Validation of a clinical algorithm to identify low-risk patients with pulmonary embolism.

Summary Background: We previously derived a clinical prognostic algorithm to identify patients with pulmonary embolism (PE) who are at low-risk of short-term mortality who could be safely discharged early or treated entirely in an outpatient setting. Objectives: To externally validate the clinical prognostic algorithm in an independent patient sample. Methods: We validated the algorithm in 983 consecutive patients prospectively diagnosed with PE at an emergency department of a university hospital. Patients with none of the algorithm's 10 prognostic variables (age >/= 70 years, cancer, heart failure, chronic lung disease, chronic renal disease, cerebrovascular disease, pulse >/= 110/min., systolic blood pressure < 100 mm Hg, oxygen saturation < 90%, and altered mental status) at baseline were defined as low-risk. We compared 30-day overall mortality among low-risk patients based on the algorithm between the validation and the original derivation sample. We also assessed the rate of PE-related and bleeding-related mortality among low-risk patients. Results: Overall, the algorithm classified 16.3% of patients with PE as low-risk. Mortality at 30 days was 1.9% among low-risk patients and did not differ between the validation and the original derivation sample. Among low-risk patients, only 0.6% died from definite or possible PE, and 0% died from bleeding. Conclusions: This study validates an easy-to-use, clinical prognostic algorithm for PE that accurately identifies patients with PE who are at low-risk of short-term mortality. Low-risk patients based on our algorithm are potential candidates for less costly outpatient treatment.

A fully adaptive numerical approximation for a two-dimensional epidemic model with nonlinear cross-diffusion

An epidemic model is formulated by a reactionâeuro"diffusion system where the spatial pattern formation is driven by cross-diffusion. The reaction terms describe the local dynamics of susceptible and infected species, whereas the diffusion terms account for the spatial distribution dynamics. For both self-diffusion and cross-diffusion, nonlinear constitutive assumptions are suggested. To simulate the pattern formation two finite volume formulations are proposed, which employ a conservative and a non-conservative discretization, respectively. An efficient simulation is obtained by a fully adaptive multiresolution strategy. Numerical examples illustrate the impact of the cross-diffusion on the pattern formation.

Ruin Theory with Excess of Loss Reinsurance and Reinstatements

The present paper studies the probability of ruin of an insurer, if excess of loss reinsurance with reinstatements is applied. In the setting of the classical Cramer-Lundberg risk model, piecewise deterministic Markov processes are used to describe the free surplus process in this more general situation. It is shown that the finite-time ruin probability is both the solution of a partial integro-differential equation and the fixed point of a contractive integral operator. We exploit the latter representation to develop and implement a recursive algorithm for numerical approximation of the ruin probability that involves high-dimensional integration. Furthermore we study the behavior of the finite-time ruin probability under various levels of initial surplus and security loadings and compare the efficiency of the numerical algorithm with the computational alternative of stochastic simulation of the risk process. (C) 2011 Elsevier Inc. All rights reserved.

Mutations in the epithelial Na+ channel ENaC outer pore disrupt amiloride block by increasing its dissociation rate.

The epithelial Na+ channel ENaC mediates transepithelial Na+ transport in the distal kidney, the colon, and the lung and is a key element for the maintenance of Na+ balance and the regulation of blood pressure. Mutagenesis studies have identified residues alphaS583 and the homologous betaG525 and gammaG537 in the outer pore entrance that are critical for ENaC block by the K+-sparing diuretic amiloride. The aim of the present study was to determine first, whether these residues are part of the amiloride binding site, and second, whether they are general determinants of ENaC block by amiloride and its derivatives. Kinetic analysis of the association and dissociation rates of amiloride and benzamil to ENaC showed that mutation of residue alphaS583C and the homologous betaG525C increased the dissociation rate of the drugs from the binding site, with little changes in their association rate. Thus, these mutations destabilize the binding interaction between the blockers and the receptor on the channel, favoring the unbinding of the ligand. This strongly suggests that they are part of the binding site. Because mutations of alphaS583, betaG525, and gammaG537 have similar effects on amiloride, benzamil, and triamterene block, we conclude that these three ENaC blockers share a common receptor within the ion channel pore.

Decision-making in pediatrics: a practical algorithm to evaluate complementary and alternative medicine for children.

We herein present a preliminary practical algorithm for evaluating complementary and alternative medicine (CAM) for children which relies on basic bioethical principles and considers the influence of CAM on global child healthcare. CAM is currently involved in almost all sectors of pediatric care and frequently represents a challenge to the pediatrician. The aim of this article is to provide a decision-making tool to assist the physician, especially as it remains difficult to keep up-to-date with the latest developments in the field. The reasonable application of our algorithm together with common sense should enable the pediatrician to decide whether pediatric (P)-CAM represents potential harm to the patient, and allow ethically sound counseling. In conclusion, we propose a pragmatic algorithm designed to evaluate P-CAM, briefly explain the underlying rationale and give a concrete clinical example.