Smoothing and high risk areas detection in space-time disease mapping: a comparison of P-splines,autoregressive, and moving average models

Recently, several models have been proposed for smoothing risks in disease mapping. These models consider different ways of introducing both spatial and temporal dependence as well as spatio-temporal interactions. In this work, a comparison among some autoregressive, moving average, and P-spline models is performed. Firstly, brain cancer mortality data are used to analyze the degree of smoothness introduced by these models. Secondly, two separate simulation studies (one model-based and the other model-free) are carried out to evaluate the model performance in terms of bias, variability, sensitivity, and specificity. We conclude that P-spline models seem to be a good alternative to autoregressive and moving average models when analyzing highly sparse disease mapping data.     

Seasonal copula models for the analysis of glacier discharge at King George Island,Antarctica

Modelling glacier discharge is an important issue in hydrology and climate research. Glaciers represent a fundamental water resource when melting of ice and snow contributes to runoff. Glaciers are also studied as natural global warming sensors. GLACKMA association has implemented one of their Pilot Experimental Catchment areas at the King George Island in the Antarctica which records values of the liquid discharge from Collins glacier. In this paper, we propose the use of time-varying copula models for analyzing the relationship between air temperature and glacier discharge, which is clearly non constant and non linear through time. A seasonal copula model is defined where both the marginal and copula parameters vary periodically along time following a seasonal dynamic. Full Bayesian inference is performed such that the marginal and copula parameters are estimated in a one single step, in contrast with the usual two-step approach. Bayesian prediction and model selection is also carried out for the proposed model such that Bayesian credible intervals can be obtained for the conditional glacier discharge given a value of the temperature at any given time point. The proposed methodology is illustrated using the GLACKMA real data where there is, in addition, a hydrological year of missing discharge data which were not possible to measure accurately due to problems in the sounding.     

A stochastic methodology for risk assessment of a large earthquake when a long time has elapsed

We propose a stochastic methodology for risk assessment of a large earthquake when a long time has elapsed from the last large seismic event. We state an approximate probability distribution for the occurrence time of the next large earthquake, by knowing that the last large seismic event occurred a long time ago. We prove that, under reasonable conditions, such a distribution is exponential with a rate depending on the asymptotic slope of the cumulative intensity function corresponding to a nonhomogeneous Poisson process. As it is not possible to obtain an empirical cumulative distribution function of the waiting time for the next large earthquake, an estimator of its cumulative distribution function based on existing data is derived. We conduct a simulation study for detecting scenario in which the proposed methodology would perform well. Finally, a real-world data analysis is carried out to illustrate its potential applications, including a homogeneity test for the times between earthquakes.     

Non-parametric copulas for circular–linear and circular–circular data: an application to wind directions

This paper proposes a nonparametric approach to estimating the dependence relationships between circular variables and other circular or linear variables using copulas. The proposed method is based on the use of Bernstein copulas which are a very flexible class of non-parametric copulas which allows for the approximation of any kind of dependence structure, including non symmetric relationships. In particular, we present a simple procedure to adapt Bernstein copulas to the circular framework and guarantee that the constructed bivariate distributions are strictly continuous. We provide two illustrative case studies, the first on the relation between wind direction and quantity of rainfall in the North of Spain and the second on the dependence between the wind directions in two nearby buoys at the Atlantic ocean.     

Coastal habitat degradation and green sea turtle diets in Southeastern Brazil

To show the influence of coastal habitat degradation on the availability of food for green turtles (Chelonia mydas), we assessed the dietary preferences and macroalgae community at a feeding area in a highly urbanized region. The area showed low species richness and was classified as degraded. We examined stomach contents of 15 dead stranded turtles (CCL = 44.0 cm (SD 6.7 cm)). The diet was composed primarily of green algae Ulva spp. (83.6%). In contrast, the macroalgae community was dominated by the green alga Caulerpa mexicana. We found a selection for red algae, seagrass and Ulva spp., and avoidance for C. mexicana and brown alga Dictyopteris delicatula. The low diversity of available food items, possibly a result of environmental degradation, likely contributed to the low dietary diversity. The nutritional implications of this restricted diet are unclear.     

Experimental testing, numerical modelling and seismic strengthening of traditional stone masonry: comprehensive study of a real Azorian pier

Stone masonry is one of the oldest building techniques used worldwide and it is known to exhibit poor behaviour under seismic excitations. In this context, this work aims at assessing the in-plane behaviour of an existing double-leaf stone masonry pier by experimental testing. Additionally, a detailed 3D finite element numerical analysis based on micro-modelling of the original pier is presented (fully describing the geometry and division of each individual elements, namely infill, blocks and joints) aiming at simulating the experimental test results. This numerical strategy can be seen as an alternative way of analysing this type of constructions, particularly useful for laboratory studies, and suitable for the calibration of simplified numerical models. As part of a wider research activity, this work is further complemented with the presentation of an effective retrofit/strengthening technique (reinforced connected plaster) to achieve a significant improvement of its in-plane cyclic response which is experimentally verified in the results presented herein.     

Evaluation of the presence of major anionic surfactants in marine sediments

The contamination of aquatic environments has become the focus of increasing regulation and public concern due to their potential and unknown negative effects on the ecosystems. The present work develops a monitoring and statistical study, based on the analysis of variance test (ANOVA) and the multivariable analysis, both for insoluble soap and LAS in order to compare the behavior of different anionic surfactants in this environmental compartment. First, a novel and successfully validated methodology to analyze insoluble soap in these samples is developed. The matrix effect and the comparison of different extraction techniques were also performed. The optimized analytical methodologies were applied to 48 representative samples collected from the Almeria Coast (Spain) and then a statistical analysis to correlate anionic surfactant concentration and several variables associated with marine sediment samples was also developed. The results obtained showed relevant conclusions related to the environmental behavior of anionic surfactants in marine sediments.     

Polycyclic aromatic hydrocarbons (PAHs) in a large South American industrial coastal area (Santos Estuary, Southeastern Brazil): sources and depositional history

Located in southeastern Brazil, the Santos Estuary has the most important industrial and urban population area of South America. Since the 1950's, increased urbanization and industrialization near the estuary margins has caused the degradation of mangroves and has increased the discharge of sewage and industrial effluents. The main objectives of this work were to determine the concentrations and sources of polycyclic aromatic hydrocarbons (PAHs) in sediment cores in order to investigate the input of these substances in the last 50 years. The PAHs analyses indicated multiple sources of these compounds (oil and pyrolitic origin), basically anthropogenic contributions from biomass, coal and fossil fuels combustion. The distribution of PAHs in the cores was associated with the formation and development of Cubat?o industrial complex and the Santos harbour, waste disposal, world oil crisis and the pollution control program, which results in the decrease of organic pollutants input in this area.     

Trend analysis of nutrient loadings in a large prairie catchment

Nutrient loadings in many river catchments continue to increase due to rapid expansion of agriculture, urban and industrial development, and population growth. Nutrient enrichment of water bodies has intensified eutrophication which degrades water quality and ecosystem health. In this study, we carried out a trend analysis of total phosphorus and total nitrogen loads in the South Saskatchewan River (SSR) catchment using a novel approach to analyse nutrient time series. Seasonal analysis of trends at each of the water quality stations was performed to determine the relationships between annual flow regimes and nutrient loads in the catchment, in particular, the influence of the high spring runoff on nutrient export. Decadal analysis was also performed to determine the long-term relationships of nutrients with anthropogenic changes in the catchment. Although it was found that seasonal and historical variability of nutrient load trends is mainly determined by streamflow regime changes, there is evidence that increases in nitrogen concentration can also be attributed to anthropogenic changes.