Communication in networks with hierarchical branching

We present a simple model of communication in networks with hierarchical branching. We analyze the behavior of the model from the viewpoint of critical systems under different situations. For certain values of the parameters, a continuous phase transition between a sparse and a congested regime is observed and accurately described by an order parameter and the power spectra. At the critical point the behavior of the model is totally independent of the number of hierarchical levels. Also scaling properties are observed when the size of the system varies. The presence of noise in the communication is shown to break the transition. The analytical results are a useful guide to forecasting the main features of real networks.

Modelling the influence of change in fire regime on the local distribution of a Mediterranean pyrophytic plant species (Cistus salviifolius) at its northern range limit

Aims: To assess the potential distribution of an obligate seeder and active pyrophyte, Cistus salviifolius, a vulnerable species in the Swiss Red List; to derive scenarios by changing the fire return interval; and to discuss the results from a conservation perspective. A more general aim is to assess the impact of fire as a natural factor influencing the vegetation of the southern slopes of the Alps. Locations: Alps, southern Switzerland. Methods: Presence-absence data to fit the model were obtained from the most recent field mapping of C. salviifolius. The quantitative environmental predictors used in this study include topographic, climatic and disturbance (fire) predictors. Models were fitted by logistic regression and evaluated by jackknife and bootstrap approaches. Changes in fire regime were simulated by increasing the time-return interval of fire (simulating longer periods without fire). Two scenarios were considered: no fire in the past 15 years; or in the past 35 years. Results: Rock cover, slope, topographic position, potential evapotranspiration and time elapsed since the last fire were selected in the final model. The Nagelkerke R-2 of the model for C. salviifolius was 0.57 and the Jackknife area under the curve evaluation was 0.89. The bootstrap evaluation revealed model robustness. By increasing the return interval of fire by either up to 15 years, or 35 years, the modelled C. salviifolius population declined by 30-40%, respectively. Main conclusions: Although fire plays a significant role, topography and rock cover appear to be the most important predictors, suggesting that the distribution of C. salviifolius in the southern Swiss Alps is closely related to the availability of supposedly competition-free sites, such as emerging bedrock, ridge locations or steep slopes. Fire is more likely to play a secondary role in allowing C. salviifolius to extend its occurrence temporarily, by increasing germination rates and reducing the competition from surrounding vegetation. To maintain a viable dormant seed bank for C. salviifolius, conservation managers should consider carrying out vegetation clearing and managing wild fire propagation to reduce competition and ensure sufficient recruitment for this species.

Hierarchical neural network with high storage capacity

A recent method used to optimize biased neural networks with low levels of activity is applied to a hierarchical model. As a consequence, the performance of the system is strongly enhanced. The steps to achieve optimization are analyzed in detail.

Modelling diffusion of innovations in a social network

A simple model of diffusion of innovations in a social network with upgrading costs is introduced. Agents are characterized by a single real variable, their technological level. According to local information, agents decide whether to upgrade their level or not, balancing their possible benefit with the upgrading cost. A critical point where technological avalanches display a power-law behavior is also found. This critical point is characterized by a macroscopic observable that turns out to optimize technological growth in the stationary state. Analytical results supporting our findings are found for the globally coupled case.

From Empirical Bayes to Full Bayes: Methods for Analysing Traffice Safety Data, October 25, 2004

Traffic safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively appealing, yet relatively easy to implement alternative to purely classical approaches. With the enormous progress in numerical methods made in recent years and with the availability of free, easy to use software that permits implementing a fully Bayesian approach, however, there is now ample justification to progress towards fully Bayesian analyses of crash data. The fully Bayesian approach, in particular as implemented via multi-level hierarchical models, has many advantages over the empirical Bayes approach. In a full Bayesian analysis, prior information and all available data are seamlessly integrated into posterior distributions on which practitioners can base their inferences. All uncertainties are thus accounted for in the analyses and there is no need to pre-process data to obtain Safety Performance Functions and other such prior estimates of the effect of covariates on the outcome of interest. In this slight, fully Bayesian methods may well be less costly to implement and may result in safety estimates with more realistic standard errors. In this manuscript, we present the full Bayesian approach to analyzing traffic safety data and focus on highlighting the differences between the empirical Bayes and the full Bayes approaches. We use an illustrative example to discuss a step-by-step Bayesian analysis of the data and to show some of the types of inferences that are possible within the full Bayesian framework.

From Empirical Bayes to Full Bayes: Methods for Analyzubg Traffic Safey Data, October 25, 2004

Traffic safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively appealing, yet relatively easy to implement alternative to purely classical approaches. With the enormous progress in numerical methods made in recent years and with the availability of free, easy to use software that permits implementing a fully Bayesian approach, however, there is now ample justification to progress towards fully Bayesian analyses of crash data. The fully Bayesian approach, in particular as implemented via multi-level hierarchical models, has many advantages over the empirical Bayes approach. In a full Bayesian analysis, prior information and all available data are seamlessly integrated into posterior distributions on which practitioners can base their inferences. All uncertainties are thus accounted for in the analyses and there is no need to pre-process data to obtain Safety Performance Functions and other such prior estimates of the effect of covariates on the outcome of interest. In this light, fully Bayesian methods may well be less costly to implement and may result in safety estimates with more realistic standard errors. In this manuscript, we present the full Bayesian approach to analyzing traffic safety data and focus on highlighting the differences between the empirical Bayes and the full Bayes approaches. We use an illustrative example to discuss a step-by-step Bayesian analysis of the data and to show some of the types of inferences that are possible within the full Bayesian framework.

Density-based hierarchical clustering of pyro-sequences on a large scale--the case of fungal ITS1.

MOTIVATION: Analysis of millions of pyro-sequences is currently playing a crucial role in the advance of environmental microbiology. Taxonomy-independent, i.e. unsupervised, clustering of these sequences is essential for the definition of Operational Taxonomic Units. For this application, reproducibility and robustness should be the most sought after qualities, but have thus far largely been overlooked. RESULTS: More than 1 million hyper-variable internal transcribed spacer 1 (ITS1) sequences of fungal origin have been analyzed. The ITS1 sequences were first properly extracted from 454 reads using generalized profiles. Then, otupipe, cd-hit-454, ESPRIT-Tree and DBC454, a new algorithm presented here, were used to analyze the sequences. A numerical assay was developed to measure the reproducibility and robustness of these algorithms. DBC454 was the most robust, closely followed by ESPRIT-Tree. DBC454 features density-based hierarchical clustering, which complements the other methods by providing insights into the structure of the data. AVAILABILITY: An executable is freely available for non-commercial users at ftp://ftp.vital-it.ch/tools/dbc454. It is designed to run under MPI on a cluster of 64-bit Linux machines running Red Hat 4.x, or on a multi-core OSX system. CONTACT: dbc454@vital-it.ch or nicolas.guex@isb-sib.ch.

Modelling the evolution and spread of HIV immune escape mutants.

During infection with human immunodeficiency virus (HIV), immune pressure from cytotoxic T-lymphocytes (CTLs) selects for viral mutants that confer escape from CTL recognition. These escape variants can be transmitted between individuals where, depending upon their cost to viral fitness and the CTL responses made by the recipient, they may revert. The rates of within-host evolution and their concordant impact upon the rate of spread of escape mutants at the population level are uncertain. Here we present a mathematical model of within-host evolution of escape mutants, transmission of these variants between hosts and subsequent reversion in new hosts. The model is an extension of the well-known SI model of disease transmission and includes three further parameters that describe host immunogenetic heterogeneity and rates of within host viral evolution. We use the model to explain why some escape mutants appear to have stable prevalence whilst others are spreading through the population. Further, we use it to compare diverse datasets on CTL escape, highlighting where different sources agree or disagree on within-host evolutionary rates. The several dozen CTL epitopes we survey from HIV-1 gag, RT and nef reveal a relatively sedate rate of evolution with average rates of escape measured in years and reversion in decades. For many epitopes in HIV, occasional rapid within-host evolution is not reflected in fast evolution at the population level.

Processus de reconnaissance et d'identification de personnes décédées

Recognition and identification processes for deceased persons. Determining the identity of deceased persons is a routine task performed essentially by police departments and forensic experts. This thesis highlights the processes necessary for the proper and transparent determination of the civil identities of deceased persons. The identity of a person is defined as the establishment of a link between that person ("the source") and information pertaining to the same individual ("identifiers"). Various identity forms could emerge, depending on the nature of the identifiers. There are two distinct types of identity, namely civil identity and biological identity. The paper examines four processes: identification by witnesses (the recognition process) and comparisons of fingerprints, dental data and DNA profiles (the identification processes). During the recognition process, the memory function is examined and helps to clarify circumstances that may give rise to errors. To make the process more rigorous, a body presentation procedure is proposed to investigators. Before examining the other processes, three general concepts specific to forensic science are considered with regard to the identification of a deceased person, namely, matter divisibility (Inman and Rudin), transfer (Locard) and uniqueness (Kirk). These concepts can be applied to the task at hand, although some require a slightly broader scope of application. A cross comparison of common forensic fields and the identification of deceased persons reveals certain differences, including 1 - reverse positioning of the source (i.e. the source is not sought from traces, but rather the identifiers are obtained from the source); 2 - the need for civil identity determination in addition to the individualisation stage; and 3 - a more restricted population (closed set), rather than an open one. For fingerprints, dental and DNA data, intravariability and intervariability are examined, as well as changes in these post mortem (PM) identifiers. Ante-mortem identifiers (AM) are located and AM-PM comparisons made. For DNA, it has been shown that direct identifiers (taken from a person whose civil identity has been alleged) tend to lead to determining civil identity whereas indirect identifiers (obtained from a close relative) direct towards a determination of biological identity. For each process, a Bayesian model is presented which includes sources of uncertainty deemed to be relevant. The results of the different processes combine to structure and summarise an overall outcome and a methodology. The modelling of dental data presents a specific difficulty with respect to intravariability, which in itself is not quantifiable. The concept of "validity" is, therefore, suggested as a possible solution to the problem. Validity uses various parameters that have an acknowledged impact on teeth intravariability. In cases where identifying deceased persons proves to be extremely difficult due to the limited discrimination of certain procedures, the use of a Bayesian approach is of great value in bringing a transparent and synthetic value. RESUME : Titre: Processus de reconnaissance et d'identification de personnes décédées. L'individualisation de personnes décédées est une tâche courante partagée principalement par des services de police, des odontologues et des laboratoires de génétique. L'objectif de cette recherche est de présenter des processus pour déterminer valablement, avec une incertitude maîtrisée, les identités civiles de personnes décédées. La notion d'identité est examinée en premier lieu. L'identité d'une personne est définie comme l'établissement d'un lien entre cette personne et des informations la concernant. Les informations en question sont désignées par le terme d'identifiants. Deux formes distinctes d'identité sont retenues: l'identité civile et l'identité biologique. Quatre processus principaux sont examinés: celui du témoignage et ceux impliquant les comparaisons d'empreintes digitales, de données dentaires et de profils d'ADN. Concernant le processus de reconnaissance, le mode de fonctionnement de la mémoire est examiné, démarche qui permet de désigner les paramètres pouvant conduire à des erreurs. Dans le but d'apporter un cadre rigoureux à ce processus, une procédure de présentation d'un corps est proposée à l'intention des enquêteurs. Avant d'entreprendre l'examen des autres processus, les concepts généraux propres aux domaines forensiques sont examinés sous l'angle particulier de l'identification de personnes décédées: la divisibilité de la matière (Inman et Rudin), le transfert (Locard) et l'unicité (Kirk). Il est constaté que ces concepts peuvent être appliqués, certains nécessitant toutefois un léger élargissement de leurs principes. Une comparaison croisée entre les domaines forensiques habituels et l'identification de personnes décédées montre des différences telles qu'un positionnement inversé de la source (la source n'est plus à rechercher en partant de traces, mais ce sont des identifiants qui sont recherchés en partant de la source), la nécessité de devoir déterminer une identité civile en plus de procéder à une individualisation ou encore une population d'intérêt limitée plutôt qu'ouverte. Pour les empreintes digitales, les dents et l'ADN, l'intra puis l'inter-variabilité sont examinées, de même que leurs modifications post-mortem (PM), la localisation des identifiants ante-mortem (AM) et les comparaisons AM-PM. Pour l'ADN, il est démontré que les identifiants directs (provenant de la personne dont l'identité civile est supposée) tendent à déterminer une identité civile alors que les identifiants indirects (provenant d'un proche parent) tendent à déterminer une identité biologique. Puis une synthèse des résultats provenant des différents processus est réalisée grâce à des modélisations bayesiennes. Pour chaque processus, une modélisation est présentée, modélisation intégrant les paramètres reconnus comme pertinents. À ce stade, une difficulté apparaît: celle de quantifier l'intra-variabilité dentaire pour laquelle il n'existe pas de règle précise. La solution préconisée est celle d'intégrer un concept de validité qui intègre divers paramètres ayant un impact connu sur l'intra-variabilité. La possibilité de formuler une valeur de synthèse par l'approche bayesienne s'avère d'une aide précieuse dans des cas très difficiles pour lesquels chacun des processus est limité en termes de potentiel discriminant.

Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy.

Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.

Building a Social Accounting Matrix within the ESA95 Framework: Obtaining a Dataset for Applied General Equilibrium Modelling

This research provides a description of the process followed in order to assemble a "Social Accounting Matrix" for Spain corresponding to the year 2000 (SAMSP00). As argued in the paper, this process attempts to reconcile ESA95 conventions with requirements of applied general equilibrium modelling. Particularly, problems related to the level of aggregation of net taxation data, and to the valuation system used for expressing the monetary value of input-output transactions have deserved special attention. Since the adoption of ESA95 conventions, input-output transactions have been preferably valued at basic prices, which impose additional difficulties on modellers interested in computing applied general equilibrium models. This paper addresses these difficulties by developing a procedure that allows SAM-builders to change the valuation system of input-output transactions conveniently. In addition, this procedure produces new data related to net taxation information.

Recent misconceptions about the "database search problem": a probabilistic analysis using Bayesian networks

This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern.