Unevenly-sampled signals: a general formalism of the Lomb-Scargle periodogram

The periodogram is a popular tool that tests whether a signal consists only of noise or if it also includes other components. The main issue of this method is to define a critical detection threshold that allows identification of a component other than noise, when a peak in the periodogram exceeds it. In the case of signals sampled on a regular time grid, determination of such a threshold is relatively simple. When the sampling is uneven, however, things are more complicated. The most popular solution in this case is to use the "Lomb-Scargle" periodogram, but this method can be used only when the noise is the realization of a zero-mean, white (i.e. flat-spectrum) random process. In this paper, we present a general formalism based on matrix algebra, which permits analysis of the statistical properties of a periodogram independently of the characteristics of noise (e.g. colored and/or non-stationary), as well as the characteristics of sampling.Comment: 10 pages, 11 figures, Astronomy and Astrophysics, in pres

Indicadores para a avaliação da disponibilidade hídrica para o desenvolvimento sustentável da atividade canavieira irrigada.

Para a racionalização do uso dos recursos hídricos e promoção do desenvolvimento sustentável da atividade canavieira na região Centro-Oeste torna-se importante o desenvolvimento de procedimentos metodológicos que possam fornecer subsídios técnicos para o planejamento e gestão setorial - agricultura e recursos hídricos. O presente trabalho apresenta dois indicadores concebidos para a avaliação do potencial da disponibilidade hídrica para atender a demanda projetada de água para o desenvolvimento da atividade canavieira

Renormalization of the BCS-BEC crossover by order parameter fluctuations

We use the functional renormalization group approach with partial bosonization in the particle-particle channel to study the effect of order parameter fluctuations on the BCS-BEC crossover of superfluid fermions in three dimensions. Our approach is based on a new truncation of the vertex expansion where the renormalization group flow of bosonic two-point functions is closed by means of Dyson-Schwinger equations and the superfluid order parameter is related to the single particle gap via a Ward identity. We explicitly calculate the chemical potential, the single-particle gap, and the superfluid order parameter at the unitary point and compare our results with experiments and previous calculations.Comment: 5 pages, 3 figure

Row spacing for pigeon pea sowing and its influence on the recovery of degraded pasture.

ABSTRACT - The objective of this work was to evaluate the effect of row spacing for sowing of 'BRS Mandarim' pigeon pea (Cajanus cajan) on soil fertility and on the yield and nutritional values of brachiaria (Urochloa decumbens) pasture. Pigeon pea was sown in an area in the initial stage of degradation and cultivated with brachiaria. Four row-spacing treatments were evaluated for pigeon pea sowing, using the following row spacing: single rows spaced at 40, 80, and 120 cm; and a double-row with 40 cm between rows, spaced at 120 cm. In addition, a reference area treatment without pigeon pea was used. The nutritive parameters of the total available forage and of the pigeon pea plants were measured at three following development stages of pigeon pea plants: vegetative stage, at 79 days after sowing (DAS); beginning of the reproductive stage, with green pods, at 157 DAS; and final stage of grain production (dry pods), at 281 DAS. The use of the legume provided an economy of up to R$1,716.30 ha-¹ in the application of nitrogen fertilizers. Pigeon pea used as green manure provides a significant increase of 53.5 to 140$ 1.716,30 ha-¹ na aplicação de fertilizantes nitrogenados. O guandu como adubação verde proporciona um aumento significativo de 53,5 a 140% na produtividade de matéria seca da braquiária.Titulo em português: Espaçamento entre linhas para semeadura de guandu e sua influência na recuperação de pastagens degradadas

Sistema de indicadores para a avaliação da sustentabilidade hídrica da atividade canaviera.

O objetivo deste trabalho é apresentar um estudo de caso realizado na Bacia Hidrográfica do Rio Verde (BHRV) para demonstrar a aplicabilidade do Sistema de Indicadores - SISHidro-Cana - para a avaliação da sustentabilidade hídrica da cultura canavieira, proposta por Ferraz (2012), como uma metodologia para avaliar a disponibilidade de água de bacias hidrográficas para subsidiar a proposição de políticas setoriais, ordenação territorial, planejamento agrícola e gestão dos recursos hídricos

Spatial variability of soil fertility attributes and productivity in a coffee crop farm

ArticleCoffee cultivation is of great importance to Brazilian agribusiness, as coffee occupies extensive production areas and is one of the most exported Brazilian products. To maintain coffee production numbers, productive techniques must be adopted that optimize productive system use. The objective of this work was to apply geostatistical techniques in the evaluation of soil fertility attributes to construct maps of variability in soil fertility parameters and the productivity of a coffee crop in the municipality of Monte Carmelo, Minas Gerais (MG), Brazil. The work was developed with coffee of the cultivar Mundo Novo 379/19, and 19 sample points were georeferenced in Universal Transverse Mercator coordinates. Spatial dependence of the fertility and productivity parameters was analysed via classic semivariogram fitting and interpolation by ordinary kriging using the statistical computer system, R. All parameters evaluated showed high degrees of spatial dependence. The attribute values varied along the sampling points, except for the sodium (Na) contents, which had similar values in all samplings. The studied parameters ranged from 80 to 200 metres. It is conclusion, the use of productivity maps linked to soil chemical attributes can be useful for determining the occurrence of variable productivity rates throughout the area, allowing the adoption of corrective practices for subsequent crops and thus making the maps very useful tools for producers

Convergence of simple adaptive Galerkin schemes based on h − h/2 error estimators

We discuss several adaptive mesh-refinement strategies based on (h − h/2)-error estimation. This class of adaptivemethods is particularly popular in practise since it is problem independent and requires virtually no implementational overhead. We prove that, under the saturation assumption, these adaptive algorithms are convergent. Our framework applies not only to finite element methods, but also yields a first convergence proof for adaptive boundary element schemes. For a finite element model problem, we extend the proposed adaptive scheme and prove convergence even if the saturation assumption fails to hold in general

Seroprevalence of antibodies against SARS-CoV-2 among health care workers in a Portuguese hospital

"Background: Health care workers (HCW) are presumably exposed to a higher risk of infection by SARS-CoV-2 and could possibly represent a source of transmission to susceptible patients. Thus, characterization of SARS-CoV-2 infection among HCW is necessary to better understand the determinants of viral transmission and properly implement strategies to prevent dissemination and protect HCW and vulnerable patients. The aim of this study was to estimate the seroprevalence of antibodies against SARS-CoV-2 in a Portuguese tertiary hospital, in the period of July 2020 to March 2021, before the generalized use of the SARS-CoV-2 vaccine, characterize its evolution over time, and identify risk factors associated with seroconversion. Methods: HCW were approached to collect serum samples for qualitative SARS-CoV-2 antibody testing and completion of an online survey capturing demographics, previous symptoms, and details of health care and community exposure. Odds ratio with bivariable and multivariable logistic regression was used to assess characteristics associated with seroprevalence. Results: One thousand HCW were included for analysis. Two hundred nineteen HCW (22%) were seropositive for immunoglobulin G against SARS-CoV-2, and 166 (17%) were seropositive for immunoglobulin M, most of whom reported a previous diagnosis of SARS-CoV-2 infection. The risk factors associated with seroconversion included a previous COVID-19 diagnosis, contact with patients, occupational contact with colleagues, and outside contact. However, in a multivariate logistic regression analysis, only a previous diagnosis and outside contact were associated with seroconversion. Seropositivity decreased over time, especially 28 weeks after infection. Conclusion: HCWs have a high seroprevalence for SARS-CoV-2 infection, probably due to a combination of health care and community exposure. Seropositivity decreases over time, but further studies are needed to better understand our adaptive immune response.

Dynamics of Enceladus and Dione inside the 2:1 Mean-Motion Resonance under Tidal Dissipation

In a previous work (Callegari and Yokoyama 2007, Celest. Mech. Dyn. Astr. vol. 98), the main features of the motion of the pair Enceladus-Dione were analyzed in the frozen regime, i.e., without considering the tidal evolution. Here, the results of a great deal of numerical simulations of a pair of satellites similar to Enceladus and Dione crossing the 2:1 mean-motion resonance are shown. The resonance crossing is modeled with a linear tidal theory, considering a two-degrees-of-freedom model written in the framework of the general three-body planar problem. The main regimes of motion of the system during the passage through resonance are studied in detail. We discuss our results comparing them with classical scenarios of tidal evolution of the system. We show new scenarios of evolution of the Enceladus-Dione system through resonance not shown in previous approaches of the problem.Comment: 36 pages, 12 figures. Accepted in Celestial Mechanics and Dynamical Astronom

Linking bayesian belief networks and GIS to assess the ecosystem integrity in the brazilian Amazon.

Deforestation and climate change heavily impact the ecosystem of the Amazon rainforest threatening its resilience and the sustainability of many human activities. Land protection may prevent ecosystems and their services to deteriorate from the pressures of agricultural expansion, population growth and wood harvesting. In the Brazilian Amazon land protection occurs in several forms such as environmental conservation, setting biodiversity priority areas and the delineation of indigenous lands. Still, the effects are not clear as understanding of the ecosystems is incomplete and responses to human actions are highly uncertain. Bayesian Belief Networks (BBN) are models that probabilistically represent correlative and causal relationships among variables. BBNs have been successfully applied to natural resource management to address environmental management problems and to assess the impact of alternative management measures. By training the probabilistic relationships using field data, Remote Sensing data and GIS data the BBN can provide information on the ecosystems: the ecosystem integrity and their likely response to climate change or alternative management actions. An increasing number of studies train and apply BBNs with evidence originating from GIS data; a cumbersome and error prone soft-linking method requiring manual conversion of data files between the BBN and GIS software systems. This paper presents the full integration of a BBN software system within an existing GIS based Discussion Support System (DSS) illustrated by the case of the ecosystem integrity of the Brazilian amazon. The full integration speeds up the processing and thereby allows doing multiple runs within a short period of time such as a stakeholder workshop. Each consecutive run is based upon insights from a previous one. Furthermore, the DSS provides the management of different options, visualize spatial summaries and trade-offs between different impact indicators and see regional differences