Calibration of a Species-Specific Spectral Vegetation Index for Leaf Area Index (LAI) Monitoring: Example with MODIS Reflectance Time-Series on Eucalyptus Plantations

The leaf area index (LAI) is a key characteristic of forest ecosystems. Estimations of LAI from satellite images generally rely on spectral vegetation indices (SVIs) or radiative transfer model (RTM) inversions. We have developed a new and precise method suitable for practical application, consisting of building a species-specific SVI that is best-suited to both sensor and vegetation characteristics. Such an SVI requires calibration on a large number of representative vegetation conditions. We developed a two-step approach: (1) estimation of LAI on a subset of satellite data through RTM inversion; and (2) the calibration of a vegetation index on these estimated LAI. We applied this methodology to Eucalyptus plantations which have highly variable LAI in time and space. Previous results showed that an RTM inversion of Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared and red reflectance allowed good retrieval performance (R-2 = 0.80, RMSE = 0.41), but was computationally difficult. Here, the RTM results were used to calibrate a dedicated vegetation index (called "EucVI") which gave similar LAI retrieval results but in a simpler way. The R-2 of the regression between measured and EucVI-simulated LAI values on a validation dataset was 0.68, and the RMSE was 0.49. The additional use of stand age and day of year in the SVI equation slightly increased the performance of the index (R-2 = 0.77 and RMSE = 0.41). This simple index opens the way to an easily applicable retrieval of Eucalyptus LAI from MODIS data, which could be used in an operational way.

Analysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil

Brazil is the largest sugarcane producer in the world and has a privileged position to attend to national and international market places. To maintain the high production of sugarcane, it is fundamental to improve the forecasting models of crop seasons through the use of alternative technologies, such as remote sensing. Thus, the main purpose of this article is to assess the results of two different statistical forecasting methods applied to an agroclimatic index (the water requirement satisfaction index; WRSI) and the sugarcane spectral response (normalized difference vegetation index; NDVI) registered on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite images. We also evaluated the cross-correlation between these two indexes. According to the results obtained, there are meaningful correlations between NDVI and WRSI with time lags. Additionally, the adjusted model for NDVI presented more accurate results than the forecasting models for WRSI. Finally, the analyses indicate that NDVI is more predictable due to its seasonality and the WRSI values are more variable making it difficult to forecast.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Supine sleep and positional sleep apnea after acute ischemic stroke and intracerebral hemorrhage

OBJECTIVE: Obstructive sleep apnea is frequent during the acute phase of stroke, and it is associated with poorer outcomes. A well-established relationship between supine sleep and obstructive sleep apnea severity exists in non-stroke patients. This study investigated the frequency of supine sleep and positional obstructive sleep apnea in patients with ischemic or hemorrhagic stroke. METHODS: Patients who suffered their first acute stroke, either ischemic or hemorrhagic, were subjected to a full polysomnography, including the continuous monitoring of sleep positions, during the first night after symptom onset. Obstructive sleep apnea severity was measured using the apnea-hypopnea index, and the NIHSS measured stroke severity. RESULTS: We prospectively studied 66 stroke patients. The mean age was 57.6+/-11.5 years, and the mean body mass index was 26.5+/-4.9. Obstructive sleep apnea (apnea-hypopnea index >= 5) was present in 78.8% of patients, and the mean apnea-hypopnea index was 29.7+/-26.6. The majority of subjects (66.7%) spent the entire sleep time in a supine position, and positional obstructive sleep apnea was clearly present in the other 23.1% of cases. A positive correlation was observed between the NIHSS and sleep time in the supine position (r(s) = 0.5; p<0.001). CONCLUSIONS: Prolonged supine positioning during sleep was highly frequent after stroke, and it was related to stroke severity. Positional sleep apnea was observed in one quarter of stroke patients, which was likely underestimated during the acute phase of stroke. The adequate positioning of patients during sleep during the acute phase of stroke may decrease obstructive respiratory events, regardless of the stroke subtype.

Solar-Terrestrial Signal Record in Tree Ring Width Time Series from Brazil

This work investigates the behavior of the sunspot number and Southern Oscillation Index (SOI) signal recorded in the tree ring time series for three different locations in Brazil: Humaita in Amaznia State, Porto Ferreira in So Paulo State, and Passo Fundo in Rio Grande do Sul State, using wavelet and cross-wavelet analysis techniques. The wavelet spectra of tree ring time series showed signs of 11 and 22 years, possibly related to the solar activity, and periods of 2-8 years, possibly related to El Nio events. The cross-wavelet spectra for all tree ring time series from Brazil present a significant response to the 11-year solar cycle in the time interval between 1921 to after 1981. These tree ring time series still have a response to the second harmonic of the solar cycle (5.5 years), but in different time intervals. The cross-wavelet maps also showed that the relationship between the SOI x tree ring time series is more intense, for oscillation in the range of 4-8 years.

Obstructive sleep apnea is common among patients referred for coronary artery bypass grafting and can be diagnosed by portable monitoring

Background Obstructive sleep apnea (OSA) is common among patients with coronary artery disease. However, OSA remains largely under recognized. The lack of clinical suspicion and difficulties to access full polysomnography (PSG) are limiting factors. The aim of this study was to evaluate, among patients referred to coronary artery bypass grafting (CABG): (i) the prevalence of OSA, (ii) the association of OSA with clinical symptoms, (iii) the performance of overnight unattended portable monitoring (PM) as an alternative method for the diagnosis of OSA. Methods Consecutive patients referred for CABG were evaluated by standard physical evaluation and validated questionnaires (Berlin questionnaire and Epworth Sleepiness Scale) and underwent full PSG and PM (Stardust II). Results We studied 70 consecutive patients (76% men), age 58 +/- 7 years (mean +/- SD), BMI [median (interquartile range)] 27.6 kg/m(2) (25.8-31.1). The prevalence of OSA (full PSG) using an apnea-hypopnea index of at least 5 events/h was 87%. Commonly used clinical traits for the screening of OSA such as the Epworth Sleepiness Scale and neck circumference had low sensitivities to detect OSA. In contrast, the Berlin questionnaire showed a good sensitivity (72%) to detect OSA. PM showed good sensitivity (92%) and specificity (67%) for the diagnosis of OSA. Conclusion OSA is strikingly common among patients referred for CABG. The Berlin questionnaire, but not symptom of excessive daytime sleepiness is a useful tool to screen OSA. PM is useful for the diagnosis of OSA and therefore is an attractive tool for widespread use among patients with coronary artery disease. Coron Artery Dis 23:31-38 (C) 2011 Wolters Kluwer Health | Lippincott Williams & Wilkins.

Homicide and public security indicator trends in the city of Sao Paulo between 1996 and 2008: a time-series ecological study

The scope of this paper was to analyze the association between homicides and public security indicators in Sao Paulo between 1996 and 2008, after monitoring the unemployment rate and the proportion of youths in the population. A time-series ecological study for 1996 and 2008 was conducted with Sao Paulo as the unit of analysis. Dependent variable: number of deaths by homicide per year. Main independent variables: arrest-incarceration rate, access to firearms, police activity. Data analysis was conducted using Stata. IC 10.0 software. Simple and multivariate negative binomial regression models were created. Deaths by homicide and arrest-incarceration, as well as police activity were significantly associated in simple regression analysis. Access to firearms was not significantly associated to the reduction in the number of deaths by homicide (p>0,05). After adjustment, the associations with both the public security indicators were not significant. In Sao Paulo the role of public security indicators are less important as explanatory factors for a reduction in homicide rates, after adjustment for unemployment rate and a reduction in the proportion of youths. The results reinforce the importance of socioeconomic and demographic factors for a change in the public security scenario in Sao Paulo.

Evaluation of physiologic complexity in time series using generalized sample entropy and surrogate data analysis

Complexity in time series is an intriguing feature of living dynamical systems, with potential use for identification of system state. Although various methods have been proposed for measuring physiologic complexity, uncorrelated time series are often assigned high values of complexity, errouneously classifying them as a complex physiological signals. Here, we propose and discuss a method for complex system analysis based on generalized statistical formalism and surrogate time series. Sample entropy (SampEn) was rewritten inspired in Tsallis generalized entropy, as function of q parameter (qSampEn). qSDiff curves were calculated, which consist of differences between original and surrogate series qSampEn. We evaluated qSDiff for 125 real heart rate variability (HRV) dynamics, divided into groups of 70 healthy, 44 congestive heart failure (CHF), and 11 atrial fibrillation (AF) subjects, and for simulated series of stochastic and chaotic process. The evaluations showed that, for nonperiodic signals, qSDiff curves have a maximum point (qSDiff(max)) for q not equal 1. Values of q where the maximum point occurs and where qSDiff is zero were also evaluated. Only qSDiff(max) values were capable of distinguish HRV groups (p-values 5.10 x 10(-3); 1.11 x 10(-7), and 5.50 x 10(-7) for healthy vs. CHF, healthy vs. AF, and CHF vs. AF, respectively), consistently with the concept of physiologic complexity, and suggests a potential use for chaotic system analysis. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4758815]

Comparing non-stationary and irregularly spaced time series

In this paper, we present approximate distributions for the ratio of the cumulative wavelet periodograms considering stationary and non-stationary time series generated from independent Gaussian processes. We also adapt an existing procedure to use this statistic and its approximate distribution in order to test if two regularly or irregularly spaced time series are realizations of the same generating process. Simulation studies show good size and power properties for the test statistic. An application with financial microdata illustrates the test usefulness. We conclude advocating the use of these approximate distributions instead of the ones obtained through randomizations, mainly in the case of irregular time series. (C) 2012 Elsevier B.V. All rights reserved.

Sleep in patients with large pleural effusion: impact of thoracentesis

This study aimed to evaluate the sleep quality and impact of thoracentesis on sleep in patients with a large pleural effusion. Patients with large unilateral pleural effusion were evaluated by the Pittsburgh Sleep Quality Index (PSQI) questionnaire and dyspnea Borg scale. Full polysomnography (PSG) was performed on the night before and 36 h after thoracentesis. We studied 19 patients, 11 males and 8 females, age 55 +/- 18 years and body mass index of 26 +/- 5 kg/m(2). The baseline sleep quality was poor (PSQI = 9.1 +/- 3.5). Thoracentesis removed 1.624 +/- 796 mL of pleural fluid and resulted in a significant decrease in dyspnea Borg scale (2.3 +/- 2.1 vs. 0.8 +/- 0.9, p < 0.001). The PSG before and after thoracentesis showed no significant change in apnea-hypopnea index and sleep time with oxygen saturation < 90%. There was a significant improvement in sleep efficiency (76% vs. 81%, p = 0.006), decrease percent sleep stage 1 (16% vs. 14%, p = 0.002), and a trend improvement in total sleep time (344 +/- 92 vs. 380 +/- 69 min, p = 0.056) and percentage of rapid eye movement sleep (15% vs. 20%, p = 0.053). No significant changes occurred in six patients that performed two consecutive PSG before thoracentesis. The improvement in sleep quality was not associated with the volume of pleural fluid withdrawn or changes in dyspnea. Patients with large pleural effusion have poor subjective and objective sleep quality that improves after thoracentesis.

Constraint-based analysis of gene interactions using restricted boolean networks and time-series data

Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.

Neural coding tools, based on Information Theory, applied to discrete time series: from electrophysiology to neuroethology

This work is supported by Brazilian agencies Fapesp, CAPES and CNPq

Functional clustering of time series gene expression data by Granger causality

Background: A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results: In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions: This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them.

Comparison between the complete Bayesian method and empirical Bayesian method for ARCH models using Brazilian financial time series

In this work we compared the estimates of the parameters of ARCH models using a complete Bayesian method and an empirical Bayesian method in which we adopted a non-informative prior distribution and informative prior distribution, respectively. We also considered a reparameterization of those models in order to map the space of the parameters into real space. This procedure permits choosing prior normal distributions for the transformed parameters. The posterior summaries were obtained using Monte Carlo Markov chain methods (MCMC). The methodology was evaluated by considering the Telebras series from the Brazilian financial market. The results show that the two methods are able to adjust ARCH models with different numbers of parameters. The empirical Bayesian method provided a more parsimonious model to the data and better adjustment than the complete Bayesian method.

Treatment of snoring and sleep apnea syndrome with a removable mandibular advancement device in patients without TMD

INTRODUCTION: Among the sleep disorders reported by the American Academy of Sleep, the most common is obstructive sleep apnea-hypopnea syndrome (OSAHS), which is caused by difficulties in air passage and complete interruption of air flow in the airway. This syndrome is associated with increased morbidity and mortality in apneic individuals. OBJECTIVE: It was the objective of this paper to evaluate a removable mandibular advancement device as it provides a noninvasive, straightforward treatment readily accepted by patients. METHODS: In this study, 15 patients without temporomandibular disorders (TMD) and with excessive daytime sleepiness or snoring were evaluated. Data were collected by means of: Polysomnography before and after placement of an intraoral appliance, analysis of TMD signs and symptoms using a patient history questionnaire, muscle and TMJ palpation. RESULTS: After treatment, the statistical analysis (t-test, and the "before and after" test) showed a mean reduction of 77.6% (p=0.001) in the apnea-hypopnea index, an increase in lowest oxyhemoglobin saturation (p=0.05), decrease in desaturation (p=0.05), decrease in micro-awakenings or EEG arousals (p=0.05) and highly significant improvement in daytime sleepiness (p=0.005), measured by the Epworth Sleepiness Scale. No TMD appeared during the monitoring period. CONCLUSION: The oral device developed in this study was considered effective for mild to moderate OSAHS.