Extensió de l'entorn SMARD per permetre la depuració d'aplicacions basades en agents mòbils

Un dels principals obstacles per l’adopció dels agents mòbils, fins i tot per tasques per les quals s’ha demostrat la seva idoneïtat, és la dificultat de desenvolupar-los. Aquest projecte aporta solucions per ajudar en aquest procés. Més concretament, per provar agents i observar-ne el seu comportament en un entorn de simulació, abans d’executar-los en un escenari real. Hem afegit un depurador i un constructor d’agents mòbils a la interfície gràfica de disseny d’itineraris de l’entorn SMARD. Fent servir afegit aquests nous components, el programador pot dissenyar, construir i fer proves d’un agent mòbil des d’aquesta aplicació.

Contribució a la mobilitat inter-plataforma d'agents mòbils: protocol de migració fragmentada

En aquest projecte s’ha dissenyat un protocol de migració d’agents mòbils per a l’arquitectura IPMA basat en l’enviament dels agents fragmentats en diversos missatges FIPA ACL. Aquest s’ha implementat dins el servei de migració JIPMS per a la plataforma JADE. Finalment s’ha dut a terme un conjunt exhaustiu de tests per avaluar-ne el rendiment i comparar-lo amb altres protocols de migració existents.

Desenvolupament d'un component de tolerància a fallades per a un sistema d'agents mòbils sobre plataformes lleugeres

A mesura que la complexitat de les tasques dels agents mòbils va creixent, és més important que aquestes no perdin el treball realitzat. Hem de saber en tot moment que la execució s’està desenvolupant favorablement. Aquest projecte tracta d’explicar el procés d’elaboració d’un component de tolerància a fallades des de la seva idea inicial fins a la seva implementació. Analitzarem la situació i dissenyarem una solució. Procurarem que el nostre component emmascari la fallada d’un agent, detectant-la i posteriorment recuperant l’execució des d’on s’ha interromput. Tot això procurant seguir la metodologia de disseny d’agents mòbils per a plataformes lleugeres.

Multi-agent contracting with countervailing incentives and limited liability

We consider a principal who deals with a privately informed agent protected by limited liability in a correlated information setting. The agent's technology is such that the fixed cost declines with the marginal cost (the type), so that countervailing incentives may arise. We show that, with high liability, the first-best outcome can be effected for any type if (1) the fixed cost is non-concave in type, under the contract that yields the smallest feasible loss to the agent; (2) the fixed cost is not very concave in type, under the contract that yields the maximum sustainable loss to the agent. We further show that, with low liability, the first-best outcome is still implemented for a non-degenerate range of types if the fixed cost is less concave in type than some given threshold, which tightens as the liability reduces. The optimal contract entails pooling otherwise.

Pregnancy Outcome Following Maternal Exposure To Statins: A Multicenter Prospective Study

Introduction: Statin use for the treatment of hypercholesterolemia in women of childbearing age is increasingly common. However, published data on pregnancy outcome after exposure to statins are scarce and conflicting. This contribution addresses the safety of exposure to statins during pregnancy.Method: In a multi-center (n = 11) observational, prospective study we compared the outcomes of 249 women exposed during the 1st trimester of pregnancy to simvastatin (n = 124), atorvastatin (n = 67), pravastatin (n = 32), rosuvastatin (n = 18), fluvastatin (n = 7) or cerivastatin (n = 1) with a control group exposed to agents known to be non-teratogenic (n = 249). The data were collected by members of the European Network of Teratology Information Services (ENTIS) during individual risk counseling between 1990 and 2009. Standardized procedures for data collection were used in each center.Results: The difference in the rate of major birth defects between the statin-exposed group and the control group was not statistically significant (4.0% vs. 2.7% OR 1.5; 95% CI 0.5-4.5, P = 0.44). The crude rate of spontaneous abortions (12.8% vs. 7.1%, OR 1.9, 95% CI 1.0-3.6, P = 0.04) was higher in the exposed group. However, after adjustment to maternal age and gestational age at initial contact, the difference became statistically insignificant. The rate of elective pregnancy-termination (8.8% vs. 4.4%, P = 0.05) was higher and the rate of deliveries resulting in live births was significantly lower in the statin exposed group (77.9% vs. 88.4%, P = 0.002). Prematurity was more frequent in exposed pregnancies (16.1% vs. 8.5%; OR 2.1, 95% CI 1.1-3.8, P = 0.02). Nonetheless, gestational age at birth (median 39 weeks, IQR 37-40 vs. 39 weeks, IQR 38-40, P = 0.27) and birth weight (median 3280 g, IQR 2835-3590 vs. 3250 g, IQR 2880-3600, P = 0.95) did not differ between exposed and non-exposed pregnancies.Conclusion: This study did not detect a clear teratogenic effect of statins. Its statistical power however is not sufficient to reverse the recommendation of treatment discontinuation during pregnancy. At most, the results are reassuring in case of inadvertent exposure.

Reconocimiento de objetos multi-clase basado en descriptores de forma

Este trabajo presenta un sistema para detectar y clasificar objetos binarios según la forma de éstos. En el primer paso del procedimiento, se aplica un filtrado para extraer el contorno del objeto. Con la información de los puntos de forma se obtiene un descriptor BSM con características altamente descriptivas, universales e invariantes. En la segunda fase del sistema se aprende y se clasifica la información del descriptor mediante Adaboost y Códigos Correctores de Errores. Se han usado bases de datos públicas, tanto en escala de grises como en color, para validar la implementación del sistema diseñado. Además, el sistema emplea una interfaz interactiva en la que diferentes métodos de procesamiento de imágenes pueden ser aplicados.

Notes on Agents’ Behavioral Rules Under Adaptive Learning and Studies of Monetary Policy

These notes try to clarify some discussions on the formulation of individual intertemporal behavior under adaptive learning in representative agent models. First, we discuss two suggested approaches and related issues in the context of a simple consumption-saving model. Second, we show that the analysis of learning in the NewKeynesian monetary policy model based on “Euler equations” provides a consistent and valid approach.

Fusion of Multi-Atlas Segmentations with Spatial Distribution Modeling

In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.

Which subgroup of patients with rheumatoid arthritis benefits from switching to rituximab versus alternative anti-tumour necrosis factor (TNF) agents after previous failure of an anti-TNF agent?

BACKGROUND: Patients with rheumatoid arthritis (RA) with an inadequate response to TNF antagonists (aTNFs) may switch to an alternative aTNF or start treatment from a different class of drugs, such as rituximab (RTX). It remains unclear in which clinical settings these therapeutic strategies offer most benefit. OBJECTIVE: To analyse the effectiveness of RTX versus alternative aTNFs on RA disease activity in different subgroups of patients. METHODS: A prospective cohort study of patients with RA who discontinued at least one aTNF and subsequently received either RTX or an alternative aTNF, nested within the Swiss RA registry (SCQM-RA) was carried out. The primary outcome, longitudinal improvement in 28-joint count Disease Activity Score (DAS28), was analysed using multivariate regression models for longitudinal data and adjusted for potential confounders. RESULTS: Of the 318 patients with RA included; 155 received RTX and 163 received an alternative aTNF. The relative benefit of RTX varied with the type of prior aTNF failure: when the motive for switching was ineffectiveness to previous aTNFs, the longitudinal improvement in DAS28 was significantly better with RTX than with an alternative aTNF (p = 0.03; at 6 months, -1.34 (95% CI -1.54 to -1.15) vs -0.93 (95% CI -1.28 to -0.59), respectively). When the motive for switching was other causes, the longitudinal improvement in DAS28 was similar for RTX and alternative aTNFs (p = 0.40). These results were not significantly modified by the number of previous aTNF failures, the type of aTNF switches, or the presence of co-treatment with a disease-modifying antirheumatic drug. CONCLUSION: This observational study suggests that in patients with RA who have stopped a previous aTNF treatment because of ineffectiveness changing to RTX is more effective than switching to an alternative aTNF.

Market Competition and Lower Tier Incentives

The relationship between competition and performance-related pay has been analyzed in single-principal-single-agent models. While this approach yields good predictions for managerial pay schemes, the predictions fail to apply for employees at lower tiers of a firm's hierarchy. In this paper, a principal-multi-agent model of incentive pay is developed which makes it possible to analyze the effect of changes in the competitiveness of markets on lower tier incentive payment schemes. The results explain why the payment schemes of agents located at low and mid tiers are less sensitive to changes in competition when aggregated firm data is used. Journal of Economic Literature classiffication numbers: D82, J21, L13, L22. Keywords: Cournot Competition, Contract Delegation, Moral Hazard, Entry, Market Size, Wage Cost.

Asset Prices, Business Cycles, and Markov-Perfect Fiscal Policy when Agents are Risk-Sensitive

We study a business cycle model in which a benevolent fiscal authority must determine the optimal provision of government services, while lacking credibility, lump-sum taxes, and the ability to bond finance deficits. Households and the fiscal authority have risk sensitive preferences. We find that outcomes are affected importantly by the household's risk sensitivity, but not by the fiscal authority's. Further, while household risk-sensitivity induces a strong precautionary saving motive, which raises capital and lowers the return on assets, its effects on fluctuations and the business cycle are generally small, although more pronounced for negative shocks. Holding the stochastic steady state constant, increases in household risk-sensitivity lower the risk-free rate and raise the return on equity, increasing the equity premium. Finally, although risk-sensitivity has little effect on the provision of government services, it does cause the fiscal authority to lower the income tax rate. An additional contribution of this paper is to present a method for computing Markov-perfect equilibria in models where private agents and the government are risk-sensitive decisionmakers.