Carmen Armero

Bio: Carmen Armero is an academic researcher from University of Valencia. The author has contributed to research in topics: Bayesian probability & Bayesian inference. The author has an hindex of 16, co-authored 63 publications receiving 927 citations.

Bayesian prediction in M/M/1 queues

Abstract: Simple queues with Poisson input and exponential service times are considered to illustrate how well-suited Bayesian methods are used to handle the common inferential aims that appear when dealing with queue problems. The emphasis will mainly be placed on prediction; in particular, we study the predictive distribution of usual measures of effectiveness in anM/M/1 queue system, such as the number of customers in the queue and in the system, the waiting time in the queue and in the system, the length of an idle period and the length of a busy period.

Spatial and temporal variations of water repellency and probability of its occurrence in calcareous Mediterranean rangeland soils affected by fires

Abstract: Water repellency (WR) is a common soil property in many fire-affected ecosystems, but it also occurs in long-unburned terrain. It can vary in space at different scales (between point and pedon or slope and catchment) and time (during the same day, between seasons or years, or with a post-fire recovery period). This paper: i) reports on the occurrence and persistence of WR in fire-affected calcareous forest soils under Mediterranean climatic conditions, examining its spatial variability at macro-, meso- and micro-scales, and monthly changes with soil moisture content; and ii) develops exploratory models to estimate the probability of the natural background (not fire-induced) WR to occur through a Mixed-Effect Logistic Regression Model. Four sites with comparable soil and vegetation types were studied, all of them burned in 1979, the third again 1999, and the fourth in April 2008. All sites were sampled immediately after the fire of 2008, a further 17 times until July 2009, and once more in August 2011. At each site, 5 random plots (10 cm × 10 cm) were selected for each of the vegetation types: Pinus halepensis, Quercus coccifera , Rosmarinus officinalis and bare soil. In each plot we carried out 10 Water Drop Penetration Time measurements at the surface and at 1 cm depth. WR was detected in samples from all sites, although WR was most frequent at the soil surface at the sites last burnt in 1979. The recently burned site had similar WR to the long-unburned ones in surface but greater at 1 cm depth, although for both depths WR was reduced by the following year. WR was still very low in the site burned 10 years before. Variability of WR between different vegetation types was as high as within the same type at the same site, and similarly high at within sites (1 ha) and at 10 cm × 10 cm plot-scales. The lowest variability was found in bare soil plots because they were mostly wettable. An exploratory model to estimate the probability of WR occurrence was derived for each unburned site. The most powerful explanatory variables for the probability of WR to occur (P P. halepensis (associated to vegetation type) for the other. The model input parameters are straightforward to obtain and the model may be a useful tool in estimating occurrence and fluctuation of soil WR.

Understanding disease mechanisms with models of signaling pathway activities.

Abstract: Background: Understanding the aspects of the cell functionality that account for disease or drug action mechanisms is one of the main challenges in the analysis of genomic data and is on the basis of the future implementation of precision medicine. Results: Here we propose a simple probabilistic model in which signaling pathways are separated into elementary sub-pathways or signal transmission circuits (which ultimately trigger cell functions) and then transforms gene expression measurements into probabilities of activation of such signal transmission circuits. Using this model, differential activation of such circuits between biological conditions can be estimated. Thus, circuit activation statuses can be interpreted as biomarkers that discriminate among the compared conditions. This type of mechanism-based biomarkers accounts for cell functional activities and can easily be associated to disease or drug action mechanisms. The accuracy of the proposed model is demonstrated with simulations and real datasets. Conclusions: The proposed model provides detailed information that enables the interpretation disease mechanisms as a consequence of the complex combinations of altered gene expression values. Moreover, it offers a framework for suggesting possible ways of therapeutic intervention in a pathologically perturbed system.

Fundamentals of Queueing Theory

Abstract: Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Interactome networks and human disease

Abstract: Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here, we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease.