42 resultados para just in time


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Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants

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A compositional time series is obtained when a compositional data vector is observed atdifferent points in time. Inherently, then, a compositional time series is a multivariatetime series with important constraints on the variables observed at any instance in time.Although this type of data frequently occurs in situations of real practical interest, atrawl through the statistical literature reveals that research in the field is very much in itsinfancy and that many theoretical and empirical issues still remain to be addressed. Anyappropriate statistical methodology for the analysis of compositional time series musttake into account the constraints which are not allowed for by the usual statisticaltechniques available for analysing multivariate time series. One general approach toanalyzing compositional time series consists in the application of an initial transform tobreak the positive and unit sum constraints, followed by the analysis of the transformedtime series using multivariate ARIMA models. In this paper we discuss the use of theadditive log-ratio, centred log-ratio and isometric log-ratio transforms. We also presentresults from an empirical study designed to explore how the selection of the initialtransform affects subsequent multivariate ARIMA modelling as well as the quality ofthe forecasts

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Evolution of compositions in time, space, temperature or other covariates is frequentin practice. For instance, the radioactive decomposition of a sample changes its composition with time. Some of the involved isotopes decompose into other isotopes of thesample, thus producing a transfer of mass from some components to other ones, butpreserving the total mass present in the system. This evolution is traditionally modelledas a system of ordinary di erential equations of the mass of each component. However,this kind of evolution can be decomposed into a compositional change, expressed interms of simplicial derivatives, and a mass evolution (constant in this example). A rst result is that the simplicial system of di erential equations is non-linear, despiteof some subcompositions behaving linearly.The goal is to study the characteristics of such simplicial systems of di erential equa-tions such as linearity and stability. This is performed extracting the compositional differential equations from the mass equations. Then, simplicial derivatives are expressedin coordinates of the simplex, thus reducing the problem to the standard theory ofsystems of di erential equations, including stability. The characterisation of stabilityof these non-linear systems relays on the linearisation of the system of di erential equations at the stationary point, if any. The eigenvelues of the linearised matrix and theassociated behaviour of the orbits are the main tools. For a three component system,these orbits can be plotted both in coordinates of the simplex or in a ternary diagram.A characterisation of processes with transfer of mass in closed systems in terms of stability is thus concluded. Two examples are presented for illustration, one of them is aradioactive decay

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During the second half of the nineteenth century a major mineral water bottling industry appeared in Catalonia which vigorously lasted until the first third of the 20th century. The fact that the industry appeared in Catalonia and in other parts of Europe and the United States almost at the same time and had not existed before can be explained by a series of factors which coincided in time. This situation encouraged producers to pack, transport and sell bottled water from their respective sources. Among these factors there is the rise of hygienism, very influential in Catalonia, the declining water quality due to industrialization, the increase in population density, the improvement in transport, the emergence of thermal tourism or the invention of better containers used to store water. This project aims to explain thoroughly all the mentioned factors, and to give some light to why, when and how the Catalan bottled water industry appeared.

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The work presented in this paper belongs to the power quality knowledge area and deals with the voltage sags in power transmission and distribution systems. Propagating throughout the power network, voltage sags can cause plenty of problems for domestic and industrial loads that can financially cost a lot. To impose penalties to responsible party and to improve monitoring and mitigation strategies, sags must be located in the power network. With such a worthwhile objective, this paper comes up with a new method for associating a sag waveform with its origin in transmission and distribution networks. It solves this problem through developing hybrid methods which hire multiway principal component analysis (MPCA) as a dimension reduction tool. MPCA reexpresses sag waveforms in a new subspace just in a few scores. We train some well-known classifiers with these scores and exploit them for classification of future sags. The capabilities of the proposed method for dimension reduction and classification are examined using the real data gathered from three substations in Catalonia, Spain. The obtained classification rates certify the goodness and powerfulness of the developed hybrid methods as brand-new tools for sag classification

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We present the derivation of the continuous-time equations governing the limit dynamics of discrete-time reaction-diffusion processes defined on heterogeneous metapopulations. We show that, when a rigorous time limit is performed, the lack of an epidemic threshold in the spread of infections is not limited to metapopulations with a scale-free architecture, as it has been predicted from dynamical equations in which reaction and diffusion occur sequentially in time

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Alfacs and Fangar Bay in the Ebro Delta, NW Mediterranean are the major sites in Catalonia for shellfish cultivation. These bays are subject to occasional closures in shellfish harvesting due to the presence of phycotoxins. Fish kills have also been associated with harmful algal blooms. The comparison of phytoplankton dynamics in both bays offers the opportunity to reveal differences in bloom patterns of species known to be harmful for the ecosystem and aquaculture activities. Field research is underway under the GEOHAB framework within the Core Research Project on HABs in Fjords and Coastal Embayments. The overall objective of this study is to improve our understanding of HAB biogeographical patterns, and key elements driving bloom dynamics in time and space within these semi-constrained embayments. Via the comparative approach we aim to improve the prediction for monitoring purposes, with a focus on Karlodinium spp. associated with massive kills of aquaculture species. This objective is addressed by incorporating long-term time series of phytoplankton identification and enumeration with the first results of recent field work in both bays. The latter includes the application of optical sensors, to yield a complementary view with enhanced spatial and temporal resolution of bloom phenomena.

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Background: There is evidence that exposure to passive smoking in general, and in babies in particular, is an important cause of morbimortality. Passive smoking is related to an increased risk of pediatric diseases such as sudden death syndrome, acute respiratory diseases, worsening of asthma, acute-chronic middle ear disease and slowing of lung growth.The objective of this article is to describe the BIBE study protocol. The BIBE study aims to determine the effectiveness of a brief intervention within the context of Primary Care, directed to mothers and fathers that smoke, in order to reduce the exposure of babies to passive smoking (ETS).Methods/DesignCluster randomized field trial (control and intervention group), multicentric and open. Subject: Fathers and/or mothers who are smokers and their babies (under 18 months) that attend pediatric services in Primary Care in Catalonia.The measurements will be taken at three points in time, in each of the fathers and/or mothers who respond to a questionnaire regarding their baby's clinical background and characteristics of the baby's exposure, together with variables related to the parents' tobacco consumption. A hair sample of the baby will be taken at the beginning of the study and at six months after the initial visit (biological determination of nicotine). The intervention group will apply a brief intervention in passive smoking after specific training and the control group will apply the habitual care.Discussion: Exposure to ETS is an avoidable factor related to infant morbimortality. Interventions to reduce exposure to ETS in babies are potentially beneficial for their health. The BIBE study evaluates an intervention to reduce exposure to ETS that takes advantage of pediatric visits. Interventions in the form of advice, conducted by pediatric professionals, are an excellent opportunity for prevention and protection of infants against the harmful effects of ETS.

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In this paper, we introduce a pilot-aided multipath channel estimator for Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems. Typical estimation algorithms assume the number of multipath components and delays to be known and constant, while theiramplitudes may vary in time. In this work, we focus on the more realistic assumption that also the number of channel taps is unknown and time-varying. The estimation problem arising from this assumption is solved using Random Set Theory (RST), which is a probability theory of finite sets. Due to the lack of a closed form of the optimal filter, a Rao-Blackwellized Particle Filter (RBPF) implementation of the channel estimator is derived. Simulation results demonstrate the estimator effectiveness.

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The quality of the time dedicated to child care has potential positive effects on children’s life chances. However, the determinants of parental time allocation to child care remain largely unexplored, particularly in context undergoing rapid family change such as Spain. We assess two alternative explanations for differences between parents in the amount of time spent with children. The first, based in the relative resources hypothesis, links variation in time spent with children to the relative attributes (occupation, education or income) of one partner to the other. The second, derived from the social status hypothesis, suggests that variation in time spent with children is attributable to the relative social position of the pair (i.e. higher status couples spend more time with children regardless of within-couple difference).To investigate theses questions, we use a sample of adults (18-50) from the Spanish Time Use Survey (STUS) 2002-2003 (n=7,438). Limiting the analysis to adults who are married or in consensual unions, the STUS allows to assess both the quantity and quality of parental time spent with children. We find little support for the “relative resources hypothesis”. Instead, consistent with the “social status hypothesis”, we find that time spent on child care is attributable to the social position of the couple, regardless of between-parent differences in income of education.

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In much of the western world, and particularly in Europe, there is a widespread perception that multiculturalism has ‘failed’ and that governments who once embraced a multicultural approach to diversity are turning away, adopting a strong emphasis on civic integration. This reaction, we are told, “reflects a seismic shift not just in the Netherlands, but in other European countries as well” (JOPPKE 2007). This paper challenges this view. Drawing on an updated version of the Multiculturalism Policy Index introduced earlier (BANTING and KYMLICKA 2006), the paper presents an index of the strength of multicultural policies for European countries and several traditional countries of immigration at three points in time (1980, 2000 and 2010). The results paint a different picture of contemporary experience in Europe. While a small number of countries, including most notably the Netherlands, have weakened established multicultural policies during the 2000s, such a shift is the exception. Most countries that adopted multicultural approaches in the later part of the twentieth century have maintained their programs in the first decade of the new century; and a significant number of countries have added new ones. In much of Europe, multicultural policies are not in general retreat. As a result, the turn to civic integration is often being layered on top of existing multicultural programs, leading to a blended approach to diversity. The paper reflects on the compatibility of multiculturalism policies and civic integration, arguing that more liberal forms of civic integration can be combined with multiculturalism but that more illiberal or coercive forms are incompatible with a multicultural approach.

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We consider an agent who has to repeatedly make choices in an uncertainand changing environment, who has full information of the past, who discountsfuture payoffs, but who has no prior. We provide a learning algorithm thatperforms almost as well as the best of a given finite number of experts orbenchmark strategies and does so at any point in time, provided the agentis sufficiently patient. The key is to find the appropriate degree of forgettingdistant past. Standard learning algorithms that treat recent and distant pastequally do not have the sequential epsilon optimality property.

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Interdisciplinary frameworks for studying natural hazards and their temporal trends have an important potential in data generation for risk assessment, land use planning, and therefore the sustainable management of resources. This paper focuses on the adjustments required because of the wide variety of scientific fields involved in the reconstruction and characterisation of flood events for the past 1000 years. The aim of this paper is to describe various methodological aspects of the study of flood events in their historical dimension, including the critical evaluation of old documentary and instrumental sources, flood-event classification and hydraulic modelling, and homogeneity and quality control tests. Standardized criteria for flood classification have been defined and applied to the Isère and Drac floods in France, from 1600 to 1950, and to the Ter, the Llobregat and the Segre floods, in Spain, from 1300 to 1980. The analysis on the Drac and Isère data series from 1600 to the present day showed that extraordinary and catastrophic floods were not distributed uniformly in time. However, the largest floods (general catastrophic floods) were homogeneously distributed in time within the period 1600¿1900. No major flood occurred during the 20th century in these rivers. From 1300 to the present day, no homogeneous behaviour was observed for extraordinary floods in the Spanish rivers. The largest floods were uniformly distributed in time within the period 1300-1900, for the Segre and Ter rivers.

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In this paper we consider diffusion of a passive substance C in a temporarily and spatially inhomogeneous two-dimensional medium. As a realization for the latter we choose a phase-separating medium consisting of two substances A and B, whose dynamics is determined by the Cahn-Hilliard equation. Assuming different diffusion coefficients of C in A and B, we find that the variance of the distribution function of the said substance grows less than linearly in time. We derive a simple identity for the variance using a probabilistic ansatz and are then able to identify the interface between A and B as the main cause for this nonlinear dependence. We argue that, finally, for very large times the here temporarily dependent diffusion "constant" goes like t-1/3 to a constant asymptotic value D¿. The latter is calculated approximately by employing the effective-medium approximation and by fitting the simulation data to the said time dependence.

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We introduce a modification to Hele-Shaw flows consisting of a rotating cell. A viscous fluid (oil) is injected at the rotation axis of the cell, which is open to air. The morphological instability of the oil-air interface is thus driven by centrifugal force and is controlled by the density (not viscosity) difference. We derive the linear dispersion relation and verify the maximum growth rate selection of initial patterns within experimental uncertainty. The nonlinear growth regime is studied in the case of vanishing injection rate. Several characteristic lengths are studied to quantify the patterns obtained. Experimental data exhibit good collapse for two characteristic lengths, namely, the radius of gyration and the radial finger length, which in the nonlinear regime appear to grow linearly in time.