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Toxic cyanobacterial blooms are globally increasing with negative effects on aquatic ecosystems, water use and human health. Blooms' main driving forces are eutrophication, dams construction, urban waste, replacement of natural vegetation with croplands, and climate change and variability. The relative effects of each driver have not still been properly addressed, particularly in large river basins. Here, we performed a historical analysis of cyanobacterial abundance in a large and important ecosystem of South America (Uruguay river, c.a. 1,900 km long, 365,000 km

Pest outbreaks, harmful algal blooms, and population collapses are extreme events with critical consequences for ecosystems, highlighting the importance of deciphering the driving ecological mechanisms underlying extreme events. By combining the generalized extreme value (GEV) theory from statistics and the hypothesis of a resource-limited metabolic restriction to population abundance, we evaluated theoretical predictions on the size-scaling and variance of extreme population abundance. Phytoplankton data from the L4 station in the English Channel showed a negative size scaling of the expected value of maxima, whose confidence interval included the predicted metabolic scaling (a = –1). We showed a humped pattern in variance with maxima at intermediate sizes. These results are consistent with the bounded abundance of small-sized populations that are subjected to strong grazing and with the expected decrease in variance towards large sizes. This approach provides unbiased return times, thereby improving the prediction accuracy of the timing of bloom formation, and describes a coherent framework in which to explore extreme population densities in natural communities.

Purpose This study aims to perform a benefit segmentation and then a classification of visitors that travel to the Rocha Department in Uruguay from the capital city of Montevideo during the summer months. Design/methodology/approach A convenience sample was obtained with an online survey. A total of 290 cases were usable for subsequent data analysis. The following statistical techniques were used: hierarchical cluster analysis, K-means cluster analysis, machine learning, support vector machines, random forest and logistic regression. Findings Visitors that travel to the Rocha Department from Montevideo can be classified into four distinct clusters. Clusters are labelled as “entertainment seekers”, “Rocha followers”, “relax and activities seekers” and “active tourists”. The support vector machine model achieved the best classification results. Research limitations/implications Implications for destination marketers who cater to young visitors are discussed. Destination marketers should determine an optimal level of resource allocation and destination management activities that compare both present costs and discounted potential future income of the different target markets. Surveying non-residents was not possible. Future work should sample tourists from abroad. Originality/value The combination of market segmentation of Rocha Department’s visitors from the city of Montevideo and classification of sampled individuals training various machine learning classifiers would allow Rocha’s destination marketers determine the belonging of an unsampled individual into one of the already obtained four clusters, enhancing marketing promotion for targeted offers.

En este trabajo se construyeron modelos de predicción de coliformes fecales (CF) para su aplicación a la gestión de calidad de agua en playas recreativas. Se análizó la base de datos histórica del monitoreo de CF en playas realizado por el Laboratorio de Calidad Ambiental de la Intendencia de Montevideo (IM), y se generaron modelos basados en inteligencia artificial (IA) para predecir excesos (CF >2.000). Los datos abarcan 10 años de monitoreo en 21 playas de la capital (N=19359, noviembre 2009 a setiembre 2019) y presentan un amplio rango de salinidad y turbidez, con marcadas diferencias entre playas. Los CF presentaron una distribución asimétrica (min=4, mediana=250, media=1.047 y máx=1.280.000) con excesos a la normativa en todas las playas. Las variables registradas in situ, meteorológicas y oceanográficas fueron utilizadas para entrenar modelos de IA. El mejor modelo fue un bosque aleatorio estratificado con un porcentaje de acierto para los excesos de 86%. La predicción de excesos mejoró un 60% respecto al criterio actual de cierre de playas las 24 hs posteriores a precipitaciones. La generación de datos de calidad por parte de la IM junto con estrategias de modelización inteligente resultan en un insumo relevante para la gestión de playas recreativas.

Predicting water contamination by statistical models is a useful tool to manage health risk in recreational beaches. Extreme contamination events, i.e. those exceeding normative are generally rare with respect to bathing conditions and thus the data is said to be imbalanced. Modeling and predicting those rare events present unique challenges. Here we introduce and evaluate several machine learning techniques and metrics to model imbalanced data and evaluate model performance. We do so by using a) simulated data-sets and b) a real data base with records of faecal coliform abundance monitored for 10 years in 21 recreational beaches in Uruguay (N ≈ 19000) using in situ and meteorological variables. We discuss advantages and disadvantages of the methods and provide a simple guide to perform models for a general audience. We also provide R codes to reproduce model fitting and testing. We found that most Machine Learning techniques are sensitive to imbalance and require specific data pre-treatment (e.g. upsampling) to improve performance. Accuracy (i.e. correctly classified cases over total cases) is not adequate to evaluate model performance on imbalanced data set. Instead, true positive rates (TPR) and false positive rates (FPR) are recommended. Among the 52 possible candidate algorithms tested, the stratified Random forest presented the better performance improving TPR in 50% with respect to baseline (0.4) and outperformed baseline in the evaluated metrics. Support vector machines combined with upsampling method or synthetic minority oversampling technique (SMOTE) performed well, similar to Adaboost with SMOTE. These results suggests that combining modeling strategies is necessary to improve our capacity to anticipate water contamination and avoid health risk.

The Río de la Plata estuary (RdlP) and adjacent continental shelf exhibit complex hydrological processes as a result of a highly variable fluvial discharge and associated terrigenous supply, which are primarily controlled by regional climatic forcing in interaction with the oceanographic system. Previous hydrological studies indicate that Little Ice Age and Medieval Climate Anomaly resulted in increased/decreased river runoff due to an enhanced/weakened precipitation regime. This study aims to analyze the cyclicity in the runoff-related continental supply and the associated climatic oscillation behind it over the past 1,000 cal yr BP. To achieve this, we used a 10-m-long sediment core retrieved from the RdlP mud depocenter, which exhibits an extremely high and fairly constant linear sedimentation rate of 1.1 cm yr-1. We performed continuous 1-cm XRF element intensity scans and performed time series analysis on Fe/K, Ti/Al, Fe/Ca, Ti/Ca and Si/Al ratios, considered as regional proxies for inferring fluvial supply. The most significant cyclicities occur at 215, 192, 115, 100, 49, 47, 37, 35, and 2.5-8 yrs recurrence times. The long-term cyclicity is persistent throughout the whole record for all ratios, and it is probably related to solar forcing, i.e., the 200 yr Vries/Suess cycle, which determines the activity of the South American Monsoon System activity. The shorter climate-related cyclicities (˂100 yr) are probably related to the Atlantic Multidecadal Oscillation, the Pacific Decadal Oscillation and the El Niño Southern Oscillation climatic modes, and were registered only for Ti/Al, Fe/K and Si/Al ratios. We further identified an intensification of such shorter climate-related cyclicities over the past 500 yr BP. This study provides new evidence that both tropical Pacific and Atlantic SSTs and solar forcing are the main drivers of changes in rainfall over Southeastern South America on interannual to decadal, multidecadal and centennial scales, and thus modulates the RdlP river discharge. ResumoO estuário do Río de la Plata (RdlP) e a plataforma continental adjacente exibem processos hidrológicos complexos, controlados principalmente pela forçante climática regional em interação com o sistema oceanográfico, o que resulta em grande variabilidade da descarga fluvial e do fornecimento de materiais terrígenos ao sistema oceânico. Estudos hidrológicos anteriores indicam que a Pequena Idade do Gelo e a Anomalia Climática Medieval resultaram no aumento / diminuição do escoamento do rio devido a um regime de precipitação aumentado/ enfraquecido. Este estudo tem como objetivo analisar a ciclicidade no fornecimento continental condicionada por oscilações climáticas nos últimos 1.000 anos e com mudanças no caudal do RdlP. Com este objetivo, foi estudado um testemunho de sedimentos, com 10 m de comprimento, obtido no depósito lodoso do RdlP. O testemunho apresenta uma taxa de acumulação extremamente alta e razoavelmente constante de 1,1 cm ano-1. Foram efetuadas análises elementares de XRF, com resolução de 1 cm, das razões Fe/K, Ti/Al, Fe/Ca, Ti/Ca e Si/Al, consideradas como proxies regionais para inferência de suprimento fluvial. As ciclicidades de recorrência mais significativas ocorreram há 215, 192, 115, 100, 49, 47, 37, 35 e 2,5-8 anos. A ciclicidade mais longas, persentes ao longo de todo o registro, estão provavelmente relacionadas com o forçamento solar, ou seja, com o ciclo de 200 anos de Vries/Suess, que determina a atividade do Sistema de Monção Sul-Americana. As ciclidades mais curtas (˂100 anos) estão provavelmente relacionadas com a Oscilação Multidecadal Atlântica, Oscilação Decadal do Pacífico e fenômeno El Niño-Oscilação Sul, tendo sido registrados por mudanças nos valores das razões Ti/Al, Fe/K e Si/Al. Além disso, identificámos uma intensificação de tais ciclicidades, relacionadas com o clima, nos últimos 500 anos BP. Este estudo fornece novas evidências de que tanto as temperaturas superficiais do oceano Pacífico e Atlântico tropicais, como o forçamento solar, são as causas principais responsáveis pelas mudanças na precipitação no sudeste da América do Sul, á escala interanual a decadal, multidecadal e centenária, e modulam a descarga do Río de la Plata.

The Río de la Plata estuary (RdlP) and adjacent continental shelf exhibit complex hydrological processes as a result of a highly variable fluvial discharge and associated terrigenous supply, which are primarily controlled by regional climatic forcing in interaction with the oceanographic system. Previous hydrological studies indicate that Little Ice Age and Medieval Climate Anomaly resulted in increased/decreased river runoff due to an enhanced/weakened precipitation regime. This study aims to analyze the cyclicity in the runoff-related continental supply and the associated climatic oscillation behind it over the past 1,000 cal yr BP. To achieve this, we used a 10-m-long sediment core retrieved from the RdlP mud depocenter, which exhibits an extremely high and fairly constant linear sedimentation rate of 1.1 cm yr-1. We performed continuous 1-cm XRF element intensity scans and performed time series analysis on Fe/K, Ti/Al, Fe/Ca, Ti/Ca and Si/Al ratios, considered as regional proxies for inferring fluvial supply. The most significant cyclicities occur at 215, 192, 115, 100, 49, 47, 37, 35, and 2.5-8 yrs recurrence times. The long-term cyclicity is persistent throughout the whole record for all ratios, and it is probably related to solar forcing, i.e., the 200 yr Vries/Suess cycle, which determines the activity of the South American Monsoon System activity. The shorter climate-related cyclicities (˂100 yr) are probably related to the Atlantic Multidecadal Oscillation, the Pacific Decadal Oscillation and the El Niño Southern Oscillation climatic modes, and were registered only for Ti/Al, Fe/K and Si/Al ratios. We further identified an intensification of such shorter climate-related cyclicities over the past 500 yr BP. This study provides new evidence that both tropical Pacific and Atlantic SSTs and solar forcing are the main drivers of changes in rainfall over Southeastern South America on interannual to decadal, multidecadal and centennial scales, and thus modulates the RdlP river discharge.

In this work we study virtual social networks known as Facebook. It is used by millions of people worldwide, gathering a combination of virtual elements and real world components. We suggest a probabilistic model to describe the long-term behavior of Facebook. This model includes different friendship connection between profiles, directly or by suggestion. Due to web’s high interactivity level, we simplify the model assuming Markovian dynamic. After the model is established we propose Complete Transversality (CT) communication concept. CT describes people interaction that reflects profile behaviour and leads to estimators that measure this interaction. Then we introduce a weakness version of CT named Segmental Transversality (ST). Within this framework we develop estimators that allow hypothesis testing of CT and ST. And then, in ST context we propose performance measures to address a priori segmentation’s quality.

We study a nonparametric regression model, where the explanatory variable is nonstationary dependent functional data and the response variable is scalar. Assuming that the explanatory variable is a nonstationary mixture of stationary processes and general conditions of dependence of the observations (implied in particular by weak dependence), we obtain the asymptotic normality of the Nadaraya–Watson estimator. Under some additional regularity assumptions on the regression function, we obtain asymptotic confidence intervals for the regression function. We apply this result to estimate the quality of service for an end-to-end connection on a network.

We give a hypothesis testing method to fit the diffusion coefficient σ of a d-dimensional stochastic differential equation on the basis of the observation of certain functionals of regularizations of the solution.

This work addresses the resource sharing problem in broadband communication networks that can guarantee some quality of service (QoS), and develops some results about data source and traffic modelling, especially in aspects of model testing and parameter estimation. The multiplexing of variable bit rate (VBR) sources poses a mathematical and statistical problem: the estimation of the resource requirements of a source or set of sources. The estimation method shall be simple enough to be practically implemented in the connection acceptance control (CAC) function. In this paper, the VBR video sources are taken as a typical case of variable rate, with real-time constraints. This association of requirements makes the case especially interesting. A Markov model is assumed for the VBR sources. The validity of such models is under research, they seem to be appropriate at least in certain time scales. The model is tested against real video traces. In order to estimate the resource allocation or channel occupation of each source, the concept of equivalent bandwidth proposed by Kelly [Notes on effective bandwidth, in: F.P. Kelly, S. Zachary, I.B. Ziedins (Eds.), Stochastic Networks: Theory and Applications, Oxford University Press, Oxford, 1996, pp. 141] is used, it is based on a consistent mathematical theory, and has proven to be robust and useful for technical applications. A calculation of the equivalent bandwidth of a Markov source, given its parameters, can be found in the literature [IEEE ACM Trans. Networking 1 (4) (1993) 424]. But in fact, one can only estimate model and parameters. In this work, an estimation of the equivalent bandwidth is given, which can be obtained from real data. The convergence and the consistency of the estimation are studied, and practical bounds are found. Illustrative calculations are performed from real video traces that were obtained using a software MPEG coder, developed by the authors. The mathematical and statistical results are valid for whatever phenomenon that can be modelled as a Markov process.

At first, we show the convergence to a compound Poisson process of the high-level exceedances point process N n ( B ) = ∑ m n ∈ B 1 { ξ m > u n } 1 A ( m ) , where ξ is a stationary and weakly dependent process, U n grows to infinity with n in a suitable way and A ⊂ N satisfies certain geometrical condition, that includes as particular examples, sets where the size of the border is negligible, periodic sets and level sets (i.e., random sets of the form { m ∈ N : ξ m (ω) ∈ B }, with B a Borel set) of a process ξ that satisfies some ergodic properties. At second, we apply this result to non-stationary processes of the form X m = ϕ(ξ m , Y m ) , where ξ and Y are independent, ξ is stationary and weakly dependent, Y is non-stationary and satisfies certain ergodic conditions, and ϕ is a suitable function: we obtain that the high-level exceedances process of X converges to a compound Poisson process.

Consider a regression model Xn = (ξn, Yn), n ∈ ℤd and assume that Xn is centered, φ is regular, ξ and Y are independent random fields, and that the Central Limit Theorem (CLT) holds for φ(ξ, y), for each y fixed, but that Y satisfies only the Strong Law of Large Numbers applied to (Y, Y−n), for any n ∈ ℤd. Then the CLT holds for X. The basic technique is the application of the CLT over asymptotically measurable sets.

We consider the second order Stochastic Differential Equation dPtβ = Vtβ dt with P0β = p0, dVtβ = βVtβdt − βω2Ptβ + βdWt with V0β = v0, where W stands for a standard Wiener process and where ω is a real constant. It is well-known that Pβ converges, as β goes to infinity, to an Ornstein-Uhlenbeck process P. In this Note, we study the convergence of the crossings of Pβ at level u during the time interval [0, t] · (NtPβ (u)) to the local time of P(LtP (u)).

We study the asymptotic distribution of \(S_N (A,X) = \sqrt {(2N + 1)} ^{ - d} (\sum {_{n \in A_N } } X_n )\) where A is a subset of \(\mathbb{Z}^d \), AN= A∩[−N, N] d , v(A) = lim N card(AN) (2N+1) −d ∈(0, 1) and X is a stationary weakly dependent random field. We show that the geometry of A has a relevant influence on the problem. More specifically, SN(A, X) is asymptotically normal for each X that satisfies certain mixting hypotheses if and only if \(F_N (n;A) = {\text{card\{ }}A_N^c \cap {\text{(}}n + A_N {\text{)\} (}}2N + 1{\text{)}}^{ - d} \) has a limit F(n; A) as N → ∞ for each \(n \in \mathbb{Z}^d \). We also study the class of sets A that satisfy this condition.

A survey of the natural occurrence of deoxynivalenol (DON) in barley harvested in Uruguay from 1996 to 2002 was conducted. A total of 292 samples were analyzed for DON by an immunochemical method using inmunoaffinity columns and fluorimetric detection. Between 26 and 100% of the samples were positive for DON while mean DON contents varied between the quantification limit (500 mug/kg) to 6349 mug/kg. Annual maximum levels in individual samples ranged from 1900 mug/kg to 10,000 mug/kg. The mean DON contents were similar from 1996 to 1999 increasing markedly from 2000 to 2002. The percentage of the samples with DON were highest in 1997, 2000, 2001 and 2002 (67, 90, 100 and 100%) as was the accumulated precipitation during the flowering period. A positive correlation between DON levels and precipitation was seen. These results suggest that monitoring for DON barley crops, particularly in years with heavy rainfall during the flowering period, must be regularly performed.

International audience; We show the convergence to a compound Poisson process of the high-level exceedances point process $N_n(B)= \sum_{j/n\in B} 1_{\{X_j>u_n\}}$, where $X_n=\varphi(\xi_n,Y_n) $, $ \varphi $ is a (regular) regression function, $u_n$ grows to infinity with $n$ in some suitable way, $\xi$ and $Y$ are mutually independent, $\xi$ is stationary and weakly dependent, and $Y$ is non-stationary, satisfying some ergodic conditions. The basic technique is the study of high-level exceedances of stationary processes over suitable collections of random sets.

We show that $$\frac{1}{\sqrt{\varepsilon}}{\int_{-\infty}^{\infty} f(u)k_{\varepsilon}N_{\tau}^{X_{\varepsilon}}(u)du - \int_0^{\tau} f(X_t)a_t dt}$$ converges in law (as a continuous process) to $c_{\psi} \int_0^{\tau}f(X_t)a_t dB_t$ where $X_t = \int_0^t a_s dW_s + \int_0^t b_x ds$, with $W$ a standard Brownian motion, $a$ and $b$ regular and adapted processes, $X_{\varepsilon}(t) = \int_{-\infty}^{\infty}(1/ \varepsilon) \psi ((t - u)/ \varepsilon)X_u du, \psi$ a smooth kernel, $N_t^g (u)$ the number of roots of the equation $g(s) = u, s \epsilon (o, t], k_{\varepsilon} = \sqrt{\pi \varepsilon /2/ \parallel \psi \parallel_2$, $f$ a smooth function, a standard Brownian motion independent of $W$ and $c_{\psi}$ constant depending only on $\psi$. .

We consider a particle of mass 1/β submitted to the action of an harmonic oscillator. If we add a white-noise external force, it is well known that the trajectories of the particle, for β tending to infinity, converge to an Ornstein-Uhlenbeck process. Using the number of crossings of the particle with a fixed level u, we construct a consistent estimator of the Ornstein-Uhlenbeck local time, giving an estimate of the speed of this convergence.