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.

Natural killer cell receptor-repertoire and functions after induction therapy by polyclonal rabbit anti-thymocyte globulin in unsensitized kidney transplant recipients.

Polyclonal rabbit anti-thymocyte globulin (rATG) is widely used in solid organ transplantation (SOT) as induction therapy or to treat corticosteroid-resistant rejection. In vivo, the effect of rATG on natural killer (NK) cells has not been studied. These cells are of particular relevance after SOT because classical immunosuppressive drugs do not inhibit or even can activate NK cells. A cohort of 20 recipients at low immunological risk, that had been receiving rATG as induction therapy, was analyzed for receptor repertoire, cytotoxicity and capacity of NK cells to secrete IFN-γ before kidney transplantation and at different time points thereafter. NK cells expressed fewer killer-cell immunoglobulin-like receptors (KIR), fewer activating receptors NKG2D, but more inhibitory receptor NKG2A compatible with an immature phenotype in the first 6 months post transplantation. Both cytotoxicity of NK cells and the secretion of IFN-γ were preserved over time after transplantation.

Compact matrix expressions for generalized Wald tests of equality of moment vectors

Asymptotic chi-squared test statistics for testing the equality ofmoment vectors are developed. The test statistics proposed aregeneralizedWald test statistics that specialize for different settings by inserting andappropriate asymptotic variance matrix of sample moments. Scaled teststatisticsare also considered for dealing with situations of non-iid sampling. Thespecializationwill be carried out for testing the equality of multinomial populations, andtheequality of variance and correlation matrices for both normal andnon-normaldata. When testing the equality of correlation matrices, a scaled versionofthe normal theory chi-squared statistic is proven to be an asymptoticallyexactchi-squared statistic in the case of elliptical data.

The functions of sleep.

Here we report on The Satellite Symposium on Sleep Function that was held in Lausanne during 6(th) FENS forum and brought together neuroscientists from basic and clinical sleep research. We illustrate the principal questions that arose during this interdisciplinary gathering and introduce the contents of nine review articles on aspects of sleep that are contained in this Special Issue of the European Journal of Neuroscience.

Glut-1 deficiency syndrome masquerading as idiopathic generalized epilepsy.

To report the case of a child with short absences and occasional myoclonias since infancy who was first diagnosed with an idiopathic generalized epilepsy, but was documented at follow-up to have a mild phenotype of glucose transporter type 1 deficiency syndrome. Unlike other reported cases of Glut-1 DS and epilepsy, this child had a normal development as well as a normal head growth and neurological examination. Early onset of seizures and later recognized episodes of mild confusion before meals together with persistent atypical EEG features and unexpected learning difficulties led to the diagnosis. Seizure control and neuropsychological improvements were obtained with a ketogenic diet.

Assigning proctors to exams with scatter search

In this paper we present an algorithm to assign proctors toexams. This NP-hard problem is related to the generalized assignmentproblem with multiple objectives. The problem consists of assigningteaching assistants to proctor final exams at a university. We formulatethis problem as a multiobjective integer program (IP) with a preferencefunction and a workload-fairness function. We then consider also a weightedobjective that combines both functions. We develop a scatter searchprocedure and compare its outcome with solutions found by solving theIP model with CPLEX 6.5. Our test problems are real instances from aUniversity in Spain.

Functions of peroxisome proliferator-activated receptors (PPAR) in skin homeostasis.

The peroxisome proliferator-activated receptors (PPAR) are ligand-activated transcription factors that belong to the nuclear hormone receptor family. Three isotypes (PPAR alpha, PPAR beta or delta, and PPAR gamma) with distinct tissue distributions and cellular functions have been found in vertebrates. All three PPAR isotypes are expressed in rodent and human skin. They were initially investigated for a possible function in the establishment of the permeability barrier in skin because of their known function in lipid metabolism in other cell types. In vitro studies using specific PPAR agonists and in vivo gene disruption approaches in mice indeed suggest an important contribution of PPAR alpha in the formation of the epidermal barrier and in sebocyte differentiation. The PPAR gamma isotype plays a role in stimulating sebocyte development and lipogenesis, but does not appear to contribute to epidermal tissue differentiation. The third isotype, PPAR beta, regulates the late stages of sebaceous cell differentiation, and is the most effective isotype in stimulating lipid production in these cells, both in rodents and in humans. In addition, PPAR beta activation has pro-differentiating effects in keratinocytes under normal and inflammatory conditions. Finally, preliminary studies also point to a potential role of PPAR in hair follicle growth and in melanocyte differentiation. By their diverse biological effects on cell proliferation and differentiation in the skin, PPAR agonists or antagonists may offer interesting opportunities for the treatment of various skin disorders characterized by inflammation, cell hyperproliferation, and aberrant differentiation.

Improving generalized regression analysis for the spatial prediction of forest communities

Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.

Adaptive approach heuristics for the generalized assignment problem

The Generalized Assignment Problem consists in assigning a setof tasks to a set of agents with minimum cost. Each agent hasa limited amount of a single resource and each task must beassigned to one and only one agent, requiring a certain amountof the resource of the agent. We present new metaheuristics forthe generalized assignment problem based on hybrid approaches.One metaheuristic is a MAX-MIN Ant System (MMAS), an improvedversion of the Ant System, which was recently proposed byStutzle and Hoos to combinatorial optimization problems, and itcan be seen has an adaptive sampling algorithm that takes inconsideration the experience gathered in earlier iterations ofthe algorithm. Moreover, the latter heuristic is combined withlocal search and tabu search heuristics to improve the search.A greedy randomized adaptive search heuristic (GRASP) is alsoproposed. Several neighborhoods are studied, including one basedon ejection chains that produces good moves withoutincreasing the computational effort. We present computationalresults of the comparative performance, followed by concludingremarks and ideas on future research in generalized assignmentrelated problems.

Generalized canonical correlation analysis of matrices with different row and column orders

A Method is offered that makes it possible to apply generalized canonicalcorrelations analysis (CANCOR) to two or more matrices of different row and column order. The new method optimizes the generalized canonical correlationanalysis objective by considering only the observed values. This is achieved byemploying selection matrices. We present and discuss fit measures to assessthe quality of the solutions. In a simulation study we assess the performance of our new method and compare it to an existing procedure called GENCOM,proposed by Green and Carroll. We find that our new method outperforms the GENCOM algorithm both with respect to model fit and recovery of the truestructure. Moreover, as our new method does not require any type of iteration itis easier to implement and requires less computation. We illustrate the methodby means of an example concerning the relative positions of the political parties inthe Netherlands based on provincial data.

Riesz-Nágy singular functions revisited

In 1952 F. Riesz and Sz.Nágy published an example of a monotonic continuous function whose derivative is zero almost everywhere, that is to say, a singular function. Besides, the function was strictly increasing. Their example was built as the limit of a sequence of deformations of the identity function. As an easy consequence of the definition, the derivative, when it existed and was finite, was found to be zero. In this paper we revisit the Riesz-N´agy family of functions and we relate it to a system for real numberrepresentation which we call (t, t-1) expansions. With the help of these real number expansions we generalize the family. The singularity of the functions is proved through some metrical properties of the expansions used in their definition which also allows us to give a more precise way of determining when the derivative is 0 or infinity.

Nonlinear models and small sample performance of the generalized method of moments

In this paper I explore the issue of nonlinearity (both in the datageneration process and in the functional form that establishes therelationship between the parameters and the data) regarding the poorperformance of the Generalized Method of Moments (GMM) in small samples.To this purpose I build a sequence of models starting with a simple linearmodel and enlarging it progressively until I approximate a standard (nonlinear)neoclassical growth model. I then use simulation techniques to find the smallsample distribution of the GMM estimators in each of the models.

Unique and conserved functions of B cell-activating factor of the TNF family (BAFF) in the chicken.

The chicken represents the best-characterized animal model for B cell development in the so-called gut-associated lymphoid tissue (GALT) and the molecular processes leading to B cell receptor diversification in this species are well investigated. However, the mechanisms regulating B cell development and homeostasis in GALT species are largely unknown. Here we investigate the role played by the avian homologue of B cell-activating factor of the tumor necrosis factor family (BAFF). Flow cytometric analysis showed that the receptor for chicken B cell-activating factor of the tumor necrosis factor family (chBAFF) is expressed by mature and immature B cells. Unlike murine and human BAFF, chBAFF is primarily produced by B cells both in peripheral lymphoid organs and in the bursa of Fabricius, the chicken's unique primary lymphoid organ. In vitro and in vivo studies revealed that chBAFF is required for mature B cell survival. In addition, in vivo neutralization with a decoy receptor led to a reduction of the size and number of B cell follicles in the bursa, demonstrating that, in contrast to humans and mice, in chickens BAFF is also required for the development of immature B cells. Collectively, we show that chBAFF has phylogenetically conserved functions in mature B cell homeostasis but displays unique and thus far unknown properties in the regulation of B cell development in birds.