Method to assess and optimise dependability of complex macro-systems: application to a railway signalling system

Achieving a high degree of dependability in complex macro-systems is challenging. Because of the large number of components and numerous independent teams involved, an overview of the global system performance is usually lacking to support both design and operation adequately. A functional failure mode, effects and criticality analysis (FMECA) approach is proposed to address the dependability optimisation of large and complex systems. The basic inductive model FMECA has been enriched to include considerations such as operational procedures, alarm systems. environmental and human factors, as well as operation in degraded mode. Its implementation on a commercial software tool allows an active linking between the functional layers of the system and facilitates data processing and retrieval, which enables to contribute actively to the system optimisation. The proposed methodology has been applied to optimise dependability in a railway signalling system. Signalling systems are typical example of large complex systems made of multiple hierarchical layers. The proposed approach appears appropriate to assess the global risk- and availability-level of the system as well as to identify its vulnerabilities. This enriched-FMECA approach enables to overcome some of the limitations and pitfalls previously reported with classical FMECA approaches.

Can we disentangle predator-prey interactions from species distributions at a macro-scale? A case study with a raptor species.

There is a debate on whether an influence of biotic interactions on species distributions can be reflected at macro-scale levels. Whereas the influence of biotic interactions on spatial arrangements is beginning to be studied at local scales, similar studies at macro-scale levels are scarce. There is no example disentangling, from other similarities with related species, the influence of predator-prey interactions on species distributions at macro-scale levels. In this study we aimed to disentangle predator-prey interactions from species distribution data following an experimental approach including a factorial design. As a case of study we selected the short-toed eagle because of its known specialization on certain prey reptiles. We used presence-absence data at a 100 Km2 spatial resolution to extract the explanatory capacity of different environmental predictors (five abiotic and two biotic predictors) on the short-toed eagle species distribution in Peninsular Spain. Abiotic predictors were relevant climatic and topographic variables, and relevant biotic predictors were prey richness and forest density. In addition to the short-toed eagle, we also obtained the predictor's explanatory capacities for i) species of the same family Accipitridae (as a reference), ii) for other birds of different families (as controls) and iii) species with randomly selected presences (as null models). We run 650 models to test for similarities of the short-toed eagle, controls and null models with reference species, assessed by regressions of explanatory capacities. We found higher similarities between the short-toed eagle and other species of the family Accipitridae than for the other two groups. Once corrected by the family effect, our analyses revealed a signal of predator-prey interaction embedded in species distribution data. This result was corroborated with additional analyses testing for differences in the concordance between the distributions of different bird categories and the distributions of either prey or non-prey species of the short-toed eagle. Our analyses were useful to disentangle a signal of predator-prey interactions from species distribution data at a macro-scale. This study highlights the importance of disentangling specific features from the variation shared with a given taxonomic level.

Non-functioning pituitary macro-incidentalomas benefit from early surgery before becoming symptomatic.

OBJECTIVE: Pituitary incidentalomas (PIs) constitute an increasingly clinical problem. While the therapeutic management is well defined for symptomatic non-functioning PIs (NFPIs), a controversy still exists for asymptomatic macro-NFPIs between surgery and a "wait and see" approach. The aim of this study is to compare surgical results between symptomatic and asymptomatic macro-NFPIs. METHODS: We conducted a retrospective study on 76 patients with newly diagnosed symptomatic and asymptomatic macro-NFPIs operated on between 2001 and 2010. We compared age, tumor size and surgical results between these two patient groups. RESULTS: After the initial evaluation, 48 patients were found to be symptomatic. Gross total removal (GTR) rate was significantly higher in asymptomatic (82%) than in symptomatic patients (58%; p=0.03). Gross total removal was strongly associated with Knosp's classification (p=0.01). Postoperative endocrinological impairment was significantly associated with the existence of preoperative symptoms (p=0.03). It was 10 times less frequent in the asymptomatic group. In symptomatic patients, postoperative visual and endocrinological impairment were present in 49% and 78% versus 0% and 14% in asymptomatic patients respectively. CONCLUSIONS: The endocrinological and visual outcome was better in those patients who underwent surgery for asymptomatic tumors. The extent of tumor resection was also significantly greater in smaller tumors. It would therefore be appropriate to offer surgery to patients with asymptomatic macro-NFPIs.

Structural macro factors and the affine term structure of interest rates

This work consists of three essays investigating the ability of structural macroeconomic models to price zero coupon U.S. government bonds. 1. A small scale 3 factor DSGE model implying constant term premium is able to provide reasonable a fit for the term structure only at the expense of the persistence parameters of the structural shocks. The test of the structural model against one that has constant but unrestricted prices of risk parameters shows that the exogenous prices of risk-model is only weakly preferred. We provide an MLE based variance-covariance matrix of the Metropolis Proposal Density that improves convergence speeds in MCMC chains. 2. Affine in observable macro-variables, prices of risk specification is excessively flexible and provides term-structure fit without significantly altering the structural parameters. The exogenous component of the SDF is separating the macro part of the model from the term structure and the good term structure fit has as a driving force an extremely volatile SDF and an implied average short rate that is inexplicable. We conclude that the no arbitrage restrictions do not suffice to temper the SDF, thus there is need for more restrictions. We introduce a penalty-function methodology that proves useful in showing that affine prices of risk specifications are able to reconcile stable macro-dynamics with good term structure fit and a plausible SDF. 3. The level factor is reproduced most importantly by the preference shock to which it is strongly and positively related but technology and monetary shocks, with negative loadings, are also contributing to its replication. The slope factor is only related to the monetary policy shocks and it is poorly explained. We find that there are gains in in- and out-of-sample forecast of consumption and inflation if term structure information is used in a time varying hybrid prices of risk setting. In-sample yield forecast are better in models with non-stationary shocks for the period 1982-1988. After this period, time varying market price of risk models provide better in-sample forecasts. For the period 2005-2008, out of sample forecast of consumption and inflation are better if term structure information is incorporated in the DSGE model but yields are better forecasted by a pure macro DSGE model.

A macro-ecological perspective on crassulacean acid metabolism (CAM) photosynthesis evolution in Afro-Madagascan drylands: Eulophiinae orchids as a case study.

Crassulacean acid metabolism (CAM) photosynthesis is an adaptation to water and atmospheric CO2 deficits that has been linked to diversification in dry-adapted plants. We investigated whether CAM evolution can be associated with the availability of new or alternative niches, using Eulophiinae orchids as a case study. Carbon isotope ratios, geographical and climate data, fossil records and DNA sequences were used to: assess the prevalence of CAM in Eulophiinae orchids; characterize the ecological niche of extant taxa; infer divergence times; and estimate whether CAM is associated with niche shifts. CAM evolved in four terrestrial lineages during the late Miocene/Pliocene, which have uneven diversification patterns. These lineages originated in humid habitats and colonized dry/seasonally dry environments in Africa and Madagascar. Additional key features (variegation, heterophylly) evolved in the most species-rich CAM lineages. Dry habitats were also colonized by a lineage that includes putative mycoheterotrophic taxa. These findings indicate that the switch to CAM is associated with environmental change. With its suite of adaptive traits, this group of orchids represents a unique opportunity to study the adaptations to dry environments, especially in the face of projected global aridification.