Multi-faceted functions of secretory IgA at mucosal surfaces.

Secretory IgA (SIgA) plays an important role in the protection and homeostatic regulation of intestinal, respiratory, and urogenital mucosal epithelia separating the outside environment from the inside of the body. This primary function of SIgA is referred to as immune exclusion, a process that limits the access of numerous microorganisms and mucosal antigens to these thin and vulnerable mucosal barriers. SIgA has been shown to be involved in avoiding opportunistic pathogens to enter and disseminate in the systemic compartment, as well as tightly controlling the necessary symbiotic relationship existing between commensals and the host. Clearance by peristalsis appears thus as one of the numerous mechanisms whereby SIgA fulfills its function at mucosal surfaces. Sampling of antigen-SIgA complexes by microfold (M) cells, intimate contact occurring with Peyer's patch dendritic cells (DC), down-regulation of inflammatory processes, modulation of epithelial, and DC responsiveness are some of the recently identified processes to which the contribution of SIgA has been underscored. This review aims at presenting, with emphasis at the biochemical level, how the molecular complexity of SIgA can serve these multiple and non-redundant modes of action.

Effect of an ectoparasite on lay date, nest-site choice, desertion, and hatching success in the great tit (Parus major)

Ectoparasites are common in most bird species, but experimental evidence of their effects on life-history traits is scarce. We investigated experimentally the effects of the hematophagous hen flea (Ceratophyllus gallinae) on timing of reproduction, nest-site choice, nest desertion, clutch size, and hatching success in the great tit (Parus major). When great tits were offered a choice on their territory between an infested and a parasite-free nest-box, they chose the one without parasites. When there was no choice, the great tits in a territory containing an infested nest-box delayed laying the clutch by 11 days as compared with the birds that were offered a parasite-free nesting opportunity. The finding that there was no difference in phenotypic traits related to dominance between the birds nesting in infested boxes and birds nesting in parasite-free boxes suggests that the delay is not imposed by social dominance. Nest desertion between laying and shortly after hatching was significandy higher in infested nests. There was no difference between infested and parasite-free nests in clutch size, but hatching success and hence brood size at hatching were significantly smaller in infested nests. Nest-box studies of great tits have been seminal in the development of evolutionary, ecological, and behavioral theory, but recently a polemic has arisen in the literature about the validity of the conclusions drawn from nest-box studies where the naturally occurring, detrimental ectoparasites are eliminated by the routine removal of old nests between breeding seasons. Our study suggests that this criticism is valid and that the evaluation of the effects of ectoparasites may improve our understanding of behavioral traits, life-history traits, or population dynamics

L'enseignement du patient diabétique et son évaluation par un questionnaire à choix multiple. [Education of the diabetic patient and its evaluation by a multiple-choice questionnaire].

37 insulin-dependent and non-insulin-dependent diabetics answered a multiple-choice questionnaire during inpatient educational sessions. 12 dietetic and 12 pathophysiologic questions had to be answered. Statistical analysis of factors influencing the number of errors can be summed up as follows: there is a direct correlation between age of the patient and number of errors; the older the patient, the greater the number of errors. However, insulin-dependent diabetics committed fewer errors than non-insulin-dependent subjects of the same age, which suggests greater motivation in the first group due to their treatment. The test likewise affords the patients an opportunity of reviewing unclear topics and enables the educational team to adapt their teaching to the patients.

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.

Portfolio choice and the effects of liquidity

This paper shows how to introduce liquidity into the well known mean-variance framework of portfolio selection. Either by estimating mean-variance liquidity constrained frontiers or directly estimating optimal portfolios for alternative levels of risk aversion and preference for liquidity, we obtain strong effects of liquidity on optimal portfolio selection. In particular, portfolio performance, measured by the Sharpe ratio relative to the tangency portfolio, varies significantly with liquidity. Moreover, although mean-variance performance becomes clearly worse, the levels of liquidity onoptimal portfolios obtained when there is a positive preference for liquidity are much lower than on those optimal portfolios where investors show no sign of preference for liquidity.

Regions of rationality: Maps for bounded agents

An important problem in descriptive and prescriptive research in decision making is to identify regions of rationality, i.e., the areas for which heuristics are and are not effective. To map the contours of such regions, we derive probabilities that heuristics identify the best of m alternatives (m > 2) characterized by k attributes or cues (k > 1). The heuristics include a single variable (lexicographic), variations of elimination-by-aspects, equal weighting, hybrids of the preceding, and models exploiting dominance. We use twenty simulated and four empirical datasets for illustration. We further provide an overview by regressing heuristic performance on factors characterizing environments. Overall, sensible heuristics generally yield similar choices in many environments. However, selection of the appropriate heuristic can be important in some regions (e.g., if there is low inter-correlation among attributes/cues). Since our work assumes a hit or miss decision criterion, we conclude by outlining extensions for exploring the effects of different loss functions.

A randomized concave programming method for choice network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

Welfare of naive and sophisticated players in school choice

Two main school choice mechanisms have attracted the attention in the literature: Boston and deferred acceptance (DA). The question arises on the ex-ante welfareimplications when the game is played by participants that vary in terms of their strategicsophistication. Abdulkadiroglu, Che and Yasuda (2011) have shown that the chances ofnaive participants getting into a good school are higher under the Boston mechanism thanunder DA, and some naive participants are actually better off. In this note we show thatthese results can be extended to show that, under the veil of ignorance, i.e. students not yetknowing their utility values, all naive students may prefer to adopt the Boston mechanism.

The role of awareness, information gathering and processing in school choice

This paper studies the determinants of school choice, focusing on the role of information. Weconsider how parents' search efforts and their capacity to process information (i.e., tocorrectly assess schools) affect the quality of the schools they choose for their children. Usinga novel dataset, we are able to identify parents' awareness of schools in their neighborhoodand measure their capacity to rank the quality of the school with respect to the officialrankings. We find that parents education and wealth are important factors in determiningtheir level of school awareness and information gathering. Moreover, these search effortshave important consequences in terms of the quality of school choice.

Choice by sequential procedures

We propose a rule of decision-making, the sequential procedure guided byroutes, and show that three influential boundedly rational choice models can be equivalentlyunderstood as special cases of this rule. In addition, the sequential procedure guidedby routes is instrumental in showing that the three models are intimately related. We showthat choice with a status-quo bias is a refinement of rationalizability by game trees, which, inturn, is also a refinement of sequential rationalizability. Thus, we provide a sharp taxonomyof these choice models, and show that they all can be understood as choice by sequentialprocedures.

A new compact linear programming formulation for choice network revenue management

The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.

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.

Simple models for multi-attribute choice with many alternatives: When it does and does not pay to face tradeoffs with binary attributes

Working Paper no longer available. Please contact the author.

Choice of partners in multiple two-person prisoner's dilemma games: An experimental study

We examine the effect of unilateral and mutual partner selection in the context of prisoner's dilemmas experimentally. Subjects play simultaneously several finitely repeated two-person prisoner's dilemma games. We find that unilateral choice is the best system. It leads to low defection and fewer singles than with mutual choice. Furthermore, with the unilateral choice setup we are able to show that intendingdefectors are more likely to try to avoid a match than intending cooperators. We compare our results of multiple games with single game PD-experiments and find no difference in aggregate behavior. Hence the multiple game technique is robust and might therefore be an important tool in the future for testing the use of mixed strategies.