Contagion and efficiency in gross and net interbank payment systems

The increased fragility of the banking industry has generatedgrowing concern about the risks associated with the paymentsystems. Although in most industrial countries differentinterbank payment systems coexist, little is really knownabout their propierties in terms of risk and efficiency. Wetackle this question by comparing the two main types ofpayment systems, gross and net, in a framework whereuncertainty arises from several sources: the time ofconsumption, the location of consumption and the return oninvestment. Payments across locations can be made either bydirectly transferrring liquidity or by transferring claimsagainst the bank in the other location. The two mechanism areinterpreted as the gross and net settlement systems ininterbank payments. We characterize the equilibria in the twosystems and identify the trade-off in terms of safety andefficiency.

It's parties that choose electoral systems (or Duverger's Law upside down)

This article presents, discusses and tests the hypothesis that it is the number of parties what can explain the choice of electoral systems, rather than the other way round. Already existing political parties tend to choose electoral systems that, rather than generate new party systems by themselves, will crystallize, consolidate or reinforce previously existing party configurations. A general model develops the argument and presents the concept of 'behavioral-institutional equilibrium' to account for the relation between electoral systems and party systems. The most comprehensive dataset and test of these notions to date, encompassing 219 elections in 87 countries since the 19th century, are presented. The analysis gives strong support to the hypotheses that political party configurations dominated by a few parties tend to establish majority rule electoral systems, while multiparty systems already existed before the introduction of proportional representation. It also offers the new theoretical proposition that strategic party choice of electoral systems leads to a general trend toward proportional representation over time.

On the throughput-WIP trade-off in queueing systems, diminishing returns and the threshold property: A linear programming approach

We present a new unifying framework for investigating throughput-WIP(Work-in-Process) optimal control problems in queueing systems,based on reformulating them as linear programming (LP) problems withspecial structure: We show that if a throughput-WIP performance pairin a stochastic system satisfies the Threshold Property we introducein this paper, then we can reformulate the problem of optimizing alinear objective of throughput-WIP performance as a (semi-infinite)LP problem over a polygon with special structure (a thresholdpolygon). The strong structural properties of such polygones explainthe optimality of threshold policies for optimizing linearperformance objectives: their vertices correspond to the performancepairs of threshold policies. We analyze in this framework theversatile input-output queueing intensity control model introduced byChen and Yao (1990), obtaining a variety of new results, including (a)an exact reformulation of the control problem as an LP problem over athreshold polygon; (b) an analytical characterization of the Min WIPfunction (giving the minimum WIP level required to attain a targetthroughput level); (c) an LP Value Decomposition Theorem that relatesthe objective value under an arbitrary policy with that of a giventhreshold policy (thus revealing the LP interpretation of Chen andYao's optimality conditions); (d) diminishing returns and invarianceproperties of throughput-WIP performance, which underlie thresholdoptimality; (e) a unified treatment of the time-discounted andtime-average cases.

Delayed diagnosis of acute ischemic stroke in children - a registry-based study in Switzerland.

QUESTIONS UNDER STUDY/PRINCIPLES: After arterial ischemic stroke (AIS) an early diagnosis helps preserve treatment options that are no longer available later. Paediatric AIS is difficult to diagnose and often the time to diagnosis exceeds the time window of 6 hours defined for thrombolysis in adults. We investigated the delay from the onset of symptoms to AIS diagnosis in children and potential contributing factors. METHODS: We included children with AIS below 16 years from the population-based Swiss Neuropaediatric Stroke Registry (2000-2006). We evaluated the time between initial medical evaluation for stroke signs/symptoms and diagnosis, risk factors, co-morbidities and imaging findings. RESULTS: A total of 91 children (61 boys), with a median age of 5.3 years (range: 0.2-16.2), were included. The time to diagnosis (by neuro-imaging) was <6 hours in 32 (35%), 6-12 hours in 23 (25%), 12-24 hours in 15 (16%) and >24 hours in 21 (23%) children. Of 74 children not hospitalised when the stroke occurred, 42% had adequate outpatient management. Delays in diagnosis were attributed to: parents/caregivers (n = 20), physicians of first referral (n = 5) and tertiary care hospitals (n = 8). A co-morbidity hindered timely diagnosis in eight children. No other factors were associated with delay to diagnosis. A total of 17 children were inpatients at AIS onset. CONCLUSIONS: One-third of children with AIS were diagnosed within six hours. Diagnostic delay was predominately caused by insufficient recognition of stroke symptoms. Increased public and expert awareness and immediate access to diagnostic imaging are essential. The ability of parents/caregivers and health professionals to recognise stroke symptoms in a child needs to be improved.

Identification of C(4)-dicarboxylate transport systems in Pseudomonas aeruginosa PAO1.

Pseudomonas aeruginosa utilizes preferentially C(4)-dicarboxylates such as malate, fumarate, and succinate as carbon and energy sources. We have identified and characterized two C(4)-dicarboxylate transport (Dct) systems in P. aeruginosa PAO1. Inactivation of the dctA(PA1183) gene caused a growth defect of the strain in minimal media supplemented with succinate, fumarate or malate, indicating that DctA has a major role in Dct. However, residual growth of the dctA mutant in these media suggested the presence of additional C(4)-dicarboxylate transporter(s). Tn5 insertion mutagenesis of the ΔdctA mutant led to the identification of a second Dct system, i.e., the DctPQM transporter belonging to the tripartite ATP-independent periplasmic (TRAP) family of carriers. The ΔdctA ΔdctPQM double mutant showed no growth on malate and fumarate and residual growth on succinate, suggesting that DctA and DctPQM are the only malate and fumarate transporters, whereas additional transporters for succinate are present. Using lacZ reporter fusions, we showed that the expression of the dctA gene and the dctPQM operon was enhanced in early exponential growth phase and induced by C(4)-dicarboxylates. Competition experiments demonstrated that the DctPQM carrier was more efficient than the DctA carrier for the utilization of succinate at micromolar concentrations, whereas DctA was the major transporter at millimolar concentrations. To conclude, this is the first time that the high- and low-affinity uptake systems for succinate DctA and DctPQM have been reported to function coordinately to transport C(4)-dicarboxylates and that the alternative sigma factor RpoN and a DctB/DctD two-component system regulates simultaneously the dctA gene and the dctPQM operon.

Delayed-Choice Experiments and the Metaphysics of Entanglement

Delayed-choice experiments in quantum mechanics are often taken to undermine a realistic interpretation of the quantum state. More specifically, Healey has recently argued that the phenomenon of delayed-choice entanglement swapping is incompatible with the view that entanglement is a physical relation between quantum systems. This paper argues against these claims. It first reviews two paradigmatic delayed-choice experiments and analyzes their metaphysical implications. It then applies the results of this analysis to the case of entanglement swapping, showing that such experiments pose no threat to realism about entanglement.

Hierarchical location-allocation models for congested systems

In this paper we address the issue of locating hierarchical facilities in the presence of congestion. Two hierarchical models are presented, where lower level servers attend requests first, and then, some of the served customers are referred to higher level servers. In the first model, the objective is to find the minimum number of servers and theirlocations that will cover a given region with a distance or time standard. The second model is cast as a Maximal Covering Location formulation. A heuristic procedure is then presented together with computational experience. Finally, some extensions of these models that address other types of spatial configurations are offered.

Male and female reproductive systems of Stolas conspersa (Germar) (Coleoptera, Chrysomelidae, Cassidinae)

Male and female reproductive systems of Stolas conspersa (Germar) (Coleoptera, Chrysomelidae, Cassidinae). The male and female reproductive systems of Stolas conspersa (Germar, 1824) are described and illustrated for the first time. The male reproductive system shows no difference from the subfamily pattern, which is a tubular well-developed median lobe; "Y", "V" or T-shaped tegmen; reduced pygidium; internal sac membranous and tubular; flagellum generally well developed needle-like structured and gastral spiculum absent. However, the female differs from the pattern proposed for Stolas in two aspects: ovary with 28 ovarioles and a reduced ampulla with indistinct velum.

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Evidence of altered antioxidant systems and signs of elevated oxidative stress are reported in peripheral tissue and brain of schizophrenic patients, including low levels of glutathione (GSH), a major thiol antioxidant and redox buffer. Functional and genetic data indicate that an impaired regulation of GSH synthesis is a vulnerability factor for the disease. Impaired GSH synthesis from a genetic origin combined with environmental risk factors generating oxidative stress (e.g., malnutrition, exposure to toxins, maternai infection and diabetes, obstetrical complications, and psychological stress) could lead to redox dysregulation. This could subsequently perturb normal brain development and maturation with delayed functional consequences emerging in early adulthood. Depending on the nature and the time of occurrence of the environmental insults, the structural and functional delayed consequences could vary, giving rise to various endophenotypes. The use of animal models of GSH deficit represents a valuable approach to investigate how interactions between genetic and environmental factors lead to the emergence of pathologies found in the disease. Moreover, these models of GSH can be useful to investigate links between schizophrenia and comorbid somatic disorders, as dysregulation of the GSH system and elevated oxidative stress are also found in cardiovascular diseases and diabetes. This chapter reviews pharmacological and genetic rodent models of GSH synthesis dysregulation used to address some of the aforementioned issues. Up to date, these models revealed that GSH deficits lead to morphological, physiological, and behavioral alterations that are quite analogous to pathologies observed in patients. This includes hypofunction of NMDA receptors, alteration of dopamine neurotransmission, anomalies in parvalbumin-immunoreactive fast-spiking interneurons, and reduced myelination. In addition, a GSH deficit affects the brain in a region-specific manner, the anterior cingulate cortex and the ventral hippocampus being the most vulnerable regions investigated. Interestingly, a GSH deficit during a limited period of postnatal development is sufficient to have long-lasting consequences on the integrity of PV-IR interneurons in the anterior cingulate cortex and impairs cognitive functions in adulthood. Finally, these animal models of GSH deficit display behavioral impairments that could be related to schizophrenia. Altogether, current data strongly support a contributing role of a redox dysregulation on the development of pathologies associated with the illness and demonstrate the usefulness of these models to better understand the biological mechanisms leading to schizophrenia.

Unified formalism for non-autonomous mechanical systems

We present a unified geometric framework for describing both the Lagrangian and Hamiltonian formalisms of regular and non-regular time-dependent mechanical systems, which is based on the approach of Skinner and Rusk (1983). The dynamical equations of motion and their compatibility and consistency are carefully studied, making clear that all the characteristics of the Lagrangian and the Hamiltonian formalisms are recovered in this formulation. As an example, it is studied a semidiscretization of the nonlinear wave equation proving the applicability of the proposed formalism.

Interaction of alpha-melanotropin with central dopamine systems: role of hormonal state and molecular structure

The tubero-infundibular and nigrostriatal DA neurone systems of rats respond to systemic (i.p.) injection of alpha-MSH (2-100 microgram/kg). The response of the tubero-infundibular (arcuate) DA neurones, an increase in cellular fluorescence intensity which can be interpreted as a sign of increased neuronal activity, is essentially the same in males, estrogen-progesterone-pretreated ovariectomized females and hypophysectomized males, whereas the type of response elicited by alpha-MSH in the nigral DA neurones depends upon the hormonal state of the animal. Differences between the two DA neurone groups exist also with regard to the effects of peptide fragments containing the two active sites of the alpha-MSH molecule. Results of lesion experiments in the lower brainstem (area postrema) and of blockade of muscarinic mechanisms by atropine further point to differences in the mechanisms underlying the peptide effects on the two neurone systems. The reaction of the tubero-infundibular DA system (which controls the pars intermedia of the pituitary) can be considered to reflect the activation of a feedback mechanism on MSH secretion, while the functional counterpart of the changes observed in the nigral system remains unknown at the present time.

Efficient T cell activation requires an optimal dwell-time of interaction between the TCR and the pMHC complex.

Cytotoxic T cell (CTL) activation by antigen requires the specific detection of peptide-major histocompatibility class I (pMHC) molecules on the target-cell surface by the T cell receptor (TCR). We examined the effect of mutations in the antigen-binding site of a Kb-restricted TCR on T cell activation, antigen binding and dissociation from antigen.These parameters were also examined for variants derived from a Kd-restricted peptide that was recognized by a CTL clone. Using these two independent systems, we show that T cell activation can be impaired by mutations that either decrease or increase the binding half-life of the TCR-pMHC interaction. Our data indicate that efficient T cell activation occurs within an optimal dwell-time range of TCR-pMHC interaction. This restricted dwell-time range is consistent with the exclusion of either extremely low or high affinity T cells from the expanded population during immune responses.

Maize response to nitrogen fertilization timing in two tillage systems in a soil with high organic matter content

No-tillage systems, associated to black oat as preceding cover crop, have been increasingly adopted. This has motivated anticipated maize nitrogen fertilization, transferring it from the side-dress system at the stage when plants have five to six expanded leaves to when the preceding cover crop is eliminated or to maize sowing. This study was conducted to evaluate the effects of soil tillage system and timing of N fertilization on maize grain yield and agronomic efficiency of N applied to a soil with high organic matter content. A three-year field experiment was conducted in Lages, state of Santa Catarina, from 1999 onwards. Treatments were set up in a split plot arrangement. Two soil tillage systems were tested in the main plots: conventional tillage (CT) and no-tillage (NT). Six N management systems were assessed in the split-plots: S1 - control, without N application; S2 - all N (100 kg ha-1) applied at oat desiccation; S3 - all N applied at maize sowing; S4 - all N side-dressed when maize had five expanded leaves (V5 growth stage); S5 - 1/3 of N rate applied at maize sowing and 2/3 at V5; S6 - 2/3 of nitrogen rate applied at maize sowing and 1/3 at V5. Maize response to the time and form of splitting N was not affected by the soil tillage system. Grain yield ranged from 6.0 to 11.8 t ha-1. The anticipation of N application (S2 and S3) decreased grain yield in two of three years. In the rainiest early spring season (2000/2001) of the experiment, S4 promoted an yield advantage of 2.2 t ha-1 over S2 and S3. Application of total N rate before or at sowing decreased the number of kernels produced per ear in 2000/2001 and 2001/2002 and the number of ears produced per area in 2001/2002, resulting in reduced grain yield. The agronomic efficiency of applied N (kg grain increase/kg of N applied) ranged from 13.9 to 38.8 and was always higher in the S4 than in the S2 and S3 N systems. Short-term N immobilization did not reduce grain yield when no N was applied before or at maize sowing in a soil with high organic matter content, regardless of the soil tillage system.

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.