Linear random knots and their scaling behavior

We present here a nonbiased probabilistic method that allows us to consistently analyze knottedness of linear random walks with up to several hundred noncorrelated steps. The method consists of analyzing the spectrum of knots formed by multiple closures of the same open walk through random points on a sphere enclosing the walk. Knottedness of individual "frozen" configurations of linear chains is therefore defined by a characteristic spectrum of realizable knots. We show that in the great majority of cases this method clearly defines the dominant knot type of a walk, i.e., the strongest component of the spectrum. In such cases, direct end-to-end closure creates a knot that usually coincides with the knot type that dominates the random closure spectrum. Interestingly, in a very small proportion of linear random walks, the knot type is not clearly defined. Such walks can be considered as residing in a border zone of the configuration space of two or more knot types. We also characterize the scaling behavior of linear random knots.

Optimal dividend strategies for a compound Poisson risk process under transaction costs and power utility

We characterize the value function of maximizing the total discounted utility of dividend payments for a compound Poisson insurance risk model when strictly positive transaction costs are included, leading to an impulse control problem. We illustrate that well known simple strategies can be optimal in the case of exponential claim amounts. Finally we develop a numerical procedure to deal with general claim amount distributions.

Group selection and kin selection: two concepts but one process.

In a recent paper, Traulsen and Nowak use a multilevel selection model to show that cooperation can be favored by group selection in finite populations [Traulsen A, Nowak M (2006) Proc Natl Acad Sci USA 103:10952-10955]. The authors challenge the view that kin selection may be an appropriate interpretation of their results and state that group selection is a distinctive process "that permeates evolutionary processes from the emergence of the first cells to eusociality and the economics of nations." In this paper, we start by addressing Traulsen and Nowak's challenge and demonstrate that all their results can be obtained by an application of kin selection theory. We then extend Traulsen and Nowak's model to life history conditions that have been previously studied. This allows us to highlight the differences and similarities between Traulsen and Nowak's model and typical kin selection models and also to broaden the scope of their results. Our retrospective analyses of Traulsen and Nowak's model illustrate that it is possible to convert group selection models to kin selection models without disturbing the mathematics describing the net effect of selection on cooperation.

Spatial pattern and process at the plant neighbourhood scale: insights from communities dominated by the clonal grass Elymus repens (L.) Gould.

Question: How do clonal traits of a locally dominant grass (Elymus repens (L.) Gould.) respond to soil heterogeneity and shape spatial patterns of its tillers? How do tiller spatial patterns constrain seedling recruitment within the community?Locations: Artificial banks of the River Rhone, France.Material and Methods: We examined 45 vegetation patches dominated by Elymus repens. During a first phase we tested relationships between soil variables and three clonal traits (spacer length, number of clumping tillers and branching rate), and between the same clonal traits and spatial patterns (i.e. density and degree of spatial aggregation) of tillers at a very fine scale. During a second phase, we performed a sowing experiment to investigate effects of density and spatial patterns of E. repens on recruitment of eight species selected from the regional species pool.Results: Clonal traits had clear effects - especially spacer length - on densification and aggregation of E. repens tillers and, at the same time, a clear response of these same clonal traits as soil granulometry changed. The density and degree of aggregation of E. repens tillers was positively correlated to total seedling cover and diversity at the finest spatial scales.Conclusions: Spatial patterning of a dominant perennial grass responds to soil heterogeneity through modifications of its clonal morphology as a trade-off between phalanx and guerrilla forms. In turn, spatial patterns have strong effects on abundance and diversity of seedlings. Spatial patterns of tillers most probably led to formation of endogenous gaps in which the recruitment of new plant individuals was enhanced. Interestingly, we also observed more idiosyncratic effects of tiller spatial patterns on seedling cover and diversity when focusing on different growth forms of the sown species.

Debris flows as a factor of hillslope evolution controlled by a continuous or a pulse process?

Flood effectiveness observations imply that two families of processes describe the formation of debris flow volume. One is related to the rainfall?erosion relationship, and can be seen as a gradual process, and one is related to additional geological/geotechnical events, those named hereafter extraordinary events. In order to discuss the hypothesis of coexistence of two modes of volume formation, some methodologies are applied. Firstly, classical approaches consisting in relating volume to catchments characteristics are considered. These approaches raise questions about the quality of the data rather than providing answers concerning the controlling processes. Secondly, we consider statistical approaches (cumulative number of events distribution and cluster analysis) and these suggest the possibility of having two distinct families of processes. However the quantitative evaluation of the threshold differs from the one that could be obtained from the first approach, but they all agree in the sense of the coexistence of two families of events. Thirdly, a conceptual model is built exploring how and why debris flow volume in alpine catchments changes with time. Depending on the initial condition (sediment production), the model shows that large debris flows (i.e. with important volume) are observed in the beginning period, before a steady-state is reached. During this second period debris flow volume such as is observed in the beginning period is not observed again. Integrating the results of the three approaches, two case studies are presented showing: (1) the possibility to observe in a catchment large volumes that will never happen again due to a drastic decrease in the sediment availability, supporting its difference from gradual erosion processes; (2) that following a rejuvenation of the sediment storage (by a rock avalanche) the magnitude?frequency relationship of a torrent can be differentiated into two phases, the beginning one with large and frequent debris flow and a later one with debris flow less intense and frequent, supporting the results of the conceptual model. Although the results obtained cannot identify a clear threshold between the two families of processes, they show that some debris flows can be seen as pulse of sediment differing from that expected from gradual erosion.

Die Krankheit Depression kann jeden treffen [In Process Citation].

The survey "Datenerhebung zur Depression in der Allgemeinbevölkerung" was conducted from fall 2010 to spring 2011 on several online platforms. The results show that there is a considerable timespan between the appearance of initial symptoms of depression and the first diagnosis of a patient. Intervention at early stages of the disease can reduce a potentially long time of suffering and can lead to the successful treatment of depression. General practitioners play an important role as the link between patient and psychiatrist.

Predictive analysis and mapping of indoor radon concentrations in Switzerland

It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

The co-evolution of culturally inherited altruistic helping and cultural transmission under random group formation.

Limited migration results in kin selective pressure on helping behaviors under a wide range of ecological, demographic and life-history situations. However, such genetically determined altruistic helping can evolve only when migration is not too strong and group size is not too large. Cultural inheritance of helping behaviors may allow altruistic helping to evolve in groups of larger size because cultural transmission has the potential to markedly decrease the variance within groups and augment the variance between groups. Here, we study the co-evolution of culturally inherited altruistic helping behaviors and two alternative cultural transmission rules for such behaviors. We find that conformist transmission, where individuals within groups tend to copy prevalent cultural variants (e.g., beliefs or values), has a strong adverse effect on the evolution of culturally inherited helping traits. This finding is at variance with the commonly held view that conformist transmission is a crucial factor favoring the evolution of altruistic helping in humans. By contrast, we find that under one-to-many transmission, where individuals within groups tend to copy a "leader" (or teacher), altruistic helping can evolve in groups of any size, although the cultural transmission rule itself hitchhikes rather weakly with a selected helping trait. Our results suggest that culturally determined helping behaviors are more likely to be driven by "leaders" than by popularity, but the emergence and stability of the cultural transmission rules themselves should be driven by some extrinsic factors.