Methodology for the Calculation of Annualized Incremental Risks in Systems of Dams

In the past few years, the field of dam safety has approached risk informed methodologies throughout the world and several methodologies and programs are appearing to aid in the systematization of the calculations. The most common way of implementing these calculations is through the use of event trees, computing event probabilities, and incremental consequences. This methodology is flexible enough for several situations, but its generalization to the case of systems of several dams is complex and its implementation in a completely general calculation methodology presents some problems. Retaining the event tree framework, a new methodology is proposed to calculate incremental risks. The main advantage of this proposed methodology is the ease with which it can be applied to systems of several dams: with a single risk model that describes the complete system and with a single calculation the incremental risks of the system can be obtained, being able to allocate the risk of each dam and of each failure mode. The article shows how both methodologies are equivalent and also applies them to a case study.     

Quality certification, institutions and innovation in local agro-food systems: Protected designations of origin of olive oil in Spain

This article examines the interrelations between establishment of territorial quality certification systems (Protected Designations of Origin or PDOs), diffusion of innovations through local agro-food chains, and the role of the institutions overseeing geographical designations. Empirical analysis is applied to olive oil PDOs in Spain and entails a detailed case study of the “Sierra Mágina” PDO in Andalusia. Making use of the neoinstitutional concept of ‘organised proximity’—and focussing specifically on the problematic of organizational quality—the article assesses characteristics that support the competitive positions of local certified-product production systems. In particular, the authors find that collective organisation and coordination between PDO agents who are locally responsible for quality assurance and protection can enhance local competitiveness. Three hypotheses are confirmed. First, PDO labels can, through the action of PDO regulators, become quality assurance systems for distributors. Second, PDO Regulatory Boards can enhance and coordinate local inter-professional activities, particularly with respect to the diffusion of quality-enhancing innovations and knowledge. Third, the study indicates that local certified-product systems are starting to incorporate quality attributes linked to the environment and sustainable development, although much remains to be accomplished in this regard.     

Why females live longer than males: control of longevity by sex hormones

Females live longer than males in many species, including humans. We have traced a possible explanation for this phenomenon to the beneficial action of estrogens, which bind to estrogen receptors and increase the expression of longevity-associated genes, including those encoding the antioxidant enzymes superoxide dismutase and glutathione peroxidase. As a result, mitochondria from females produce fewer reactive oxygen species than those from males. Administering estrogens has serious drawbacks, however--they are feminizing (and thus cannot be administered to males) and may increase the incidence of serious diseases such as uterine cancer in postmenopausal women. Phytoestrogens, which are present in soy or wine, may have some of the favorable effects of estrogens without their undesirable effects. Study of gender differences in longevity may help us to understand the basic processes of aging and to devise practical strategies to increase the longevity of both females and males.     

Stochastic Optimization for Natural Disaster Asset Prepositioning

A key strategic issue in pre‐disaster planning for humanitarian logistics is the pre‐establishment of adequate capacity and resources that enable efficient relief operations. This paper develops a two‐stage stochastic optimization model to guide the allocation of budget to acquire and position relief assets, decisions that typically need to be made well in advance before a disaster strikes. The optimization focuses on minimizing the expected number of casualties, so our model includes first‐stage decisions to represent the expansion of resources such as warehouses, medical facilities with personnel, ramp spaces, and shelters. Second‐stage decisions concern the logistics of the problem, where allocated resources and contracted transportation assets are deployed to rescue critical population (in need of emergency evacuation), deliver required commodities to stay‐back population, and transport the transfer population displaced by the disaster. Because of the uncertainty of the event's location and severity, these and other parameters are represented as scenarios. Computational results on notional test cases provide guidance on budget allocation and prove the potential benefit of using stochastic optimization.     

Quadratic perturbation expansions of certain functions of eigenvalues and eigenvectors and their application to sensitivity analysis in multivariate methods

Tanaka (1988) lias derived the influence functions, which are equivalent to the perturbation expansions up to linear terms, of two functions of eigenvalues and eigenvectors of a real symmetric matrix, and applied them to principal component analysis. The present paper deals with the perturbation expansions up to quadratic terms of the same functions and discusses their application to sensitivity analysis in multivariate methods, in particular, principal component analysis and principal factor analysis. Numerical examples are given to show how the approximation improves with the quadratic terms.     

Nonparametric product partition models for multiple change-points analysis

ABSTRACT

We propose an extension of parametric product partition models. We name our proposal nonparametric product partition models because we associate a random measure instead of a parametric kernel to each set within a random partition. Our methodology does not impose any specific form on the marginal distribution of the observations, allowing us to detect shifts of behaviour even when dealing with heavy-tailed or skewed distributions. We propose a suitable loss function and find the partition of the data having minimum expected loss. We then apply our nonparametric procedure to multiple change-point analysis and compare it with PPMs and with other methodologies that have recently appeared in the literature. Also, in the context of missing data, we exploit the product partition structure in order to estimate the distribution function of each missing value, allowing us to detect change points using the loss function mentioned above. Finally, we present applications to financial as well as genetic data.     

Strong consistency of presmoothed Kaplan–Meier integrals when covariables are present

It is known that the Kaplan–Meier estimation may be improved via presmoothing methods. In this article, we introduce an extended presmoothed Kaplan–Meier estimator in the presence of covariates. The main result is the strong consistency of general empirical integrals based on such an estimator. As applications, one can obtain a consis-tent multivariate empirical distribution under censoring, and also can obtain a consistent estimation of regression parameters. We illustrate the new estimation methods through simulations and real data analysis.