Error Autocorrelation and Linear Regression for Temperature-Based Evapotranspiration Estimates Improvement

Estimates of evapotranspiration on a local scale is important information for agricultural and hydrological practices. However, equations to estimate potential evapotranspiration based only on temperature data, which are simple to use, are usually less trustworthy than the Food and Agriculture Organization (FAO)Penman-Monteith standard method. The present work describes two correction procedures for potential evapotranspiration estimates by temperature, making the results more reliable. Initially, the standard FAO-Penman-Monteith method was evaluated with a complete climatologic data set for the period between 2002 and 2006. Then temperature-based estimates by Camargo and Jensen-Haise methods have been adjusted by error autocorrelation evaluated in biweekly and monthly periods. In a second adjustment, simple linear regression was applied. The adjusted equations have been validated with climatic data available for the Year 2001. Both proposed methodologies showed good agreement with the standard method indicating that the methodology can be used for local potential evapotranspiration estimates.

Local power properties of some asymptotic tests in symmetric linear regression models

In this paper we obtain asymptotic expansions, up to order n(-1/2) and under a sequence of Pitman alternatives, for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the class of symmetric linear regression models. This is a wide class of models which encompasses the t model and several other symmetric distributions with longer-than normal tails. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, Monte Carlo simulations are presented. An empirical application to a real data set is considered for illustrative purposes. (C) 2011 Elsevier B.V. All rights reserved.

Examination of the performance of different pointwise linear regression progression criteria to detect glaucomatous visual field change

Background: We aimed to investigate the performance of five different trend analysis criteria for the detection of glaucomatous progression and to determine the most frequently and rapidly progressing locations of the visual field. Design: Retrospective cohort. Participants or Samples: Treated glaucoma patients with =8 Swedish Interactive Thresholding Algorithm (SITA)-standard 24-2 visual field tests. Methods: Progression was determined using trend analysis. Five different criteria were used: (A) =1 significantly progressing point; (B) =2 significantly progressing points; (C) =2 progressing points located in the same hemifield; (D) at least two adjacent progressing points located in the same hemifield; (E) =2 progressing points in the same Garway-Heath map sector. Main Outcome Measures: Number of progressing eyes and false-positive results. Results: We included 587 patients. The number of eyes reaching a progression endpoint using each criterion was: A = 300 (51%); B = 212 (36%); C = 194 (33%); D = 170 (29%); and E = 186 (31%) (P = 0.03). The numbers of eyes with positive slopes were: A = 13 (4.3%); B = 3 (1.4%); C = 3 (1.5%); D = 2 (1.1%); and E = 3 (1.6%) (P = 0.06). The global slopes for progressing eyes were more negative in Groups B, C and D than in Group A (P = 0.004). The visual field locations that progressed more often were those in the nasal field adjacent to the horizontal midline. Conclusions: Pointwise linear regression criteria that take into account the retinal nerve fibre layer anatomy enhances the specificity of trend analysis for the detection glaucomatous visual field progression.

AGE INFLUENCE ON THE HEART RATE BEHAVIOR ON THE REST-EXERCICIO TRANSITION: AN ANALYSIS BY DELTAS AND LINEAR REGRESSION

Background: Changes in heart rate during rest-exercise transition can be characterized by the application of mathematical calculations, such as deltas 0-10 and 0-30 seconds to infer on the parasympathetic nervous system and linear regression and delta applied to data range from 60 to 240 seconds to infer on the sympathetic nervous system. The objective of this study was to test the hypothesis that young and middle-aged subjects have different heart rate responses in exercise of moderate and intense intensity, with different mathematical calculations. Methods: Seven middle-aged men and ten young men apparently healthy were subject to constant load tests (intense and moderate) in cycle ergometer. The heart rate data were submitted to analysis of deltas (0-10, 0-30 and 60-240 seconds) and simple linear regression (60-240 seconds). The parameters obtained from simple linear regression analysis were: intercept and slope angle. We used the Shapiro-Wilk test to check the distribution of data and the "t" test for unpaired comparisons between groups. The level of statistical significance was 5%. Results: The value of the intercept and delta 0-10 seconds was lower in middle age in two loads tested and the inclination angle was lower in moderate exercise in middle age. Conclusion: The young subjects present greater magnitude of vagal withdrawal in the initial stage of the HR response during constant load exercise and higher speed of adjustment of sympathetic response in moderate exercise.

A log-linear regression model for the beta-Birnbaum-Saunders distribution with censored data

The beta-Birnbaum-Saunders (Cordeiro and Lemonte, 2011) and Birnbaum-Saunders (Birnbaum and Saunders, 1969a) distributions have been used quite effectively to model failure times for materials subject to fatigue and lifetime data. We define the log-beta-Birnbaum-Saunders distribution by the logarithm of the beta-Birnbaum-Saunders distribution. Explicit expressions for its generating function and moments are derived. We propose a new log-beta-Birnbaum-Saunders regression model that can be applied to censored data and be used more effectively in survival analysis. We obtain the maximum likelihood estimates of the model parameters for censored data and investigate influence diagnostics. The new location-scale regression model is modified for the possibility that long-term survivors may be presented in the data. Its usefulness is illustrated by means of two real data sets. (C) 2011 Elsevier B.V. All rights reserved.

Development and validation of a simple and sensitive high performance liquid chromatographic method for the simultaneous determination of anastrozole, bicalutamide, tamoxifen, and their synthetic impurities

A simple and sensitive analytical method for simultaneous determination of anastrozole, bicalutamide, and tamoxifen as well as their synthetic impurities, anastrozole pentamethyl, bicalutamide 3-fluoro-isomer, and tamoxifen e-isomer, was developed and validated by using high performance liquid chromatography (HPLC). The separation was achieved on a Symmetry (R) C-8 column (100 x 4.6 mm i.d., 3.5 mu m) at room temperature (+/- 24 degrees C), with a mobile phase consisting of acetonitrile/water containing 0.18% N,N dimethyloctylamine and pH adjusted to 3.0 with orthophosphoric acid (46.5/53.5, v/v) at a flow rate of 1.0 mL min(-1) within 20 min. The detection was made at a wavelength of 270 nm by using ultraviolet (UV) detector. No interference peaks from excipients and relative retention time indicated the specificity of the method. The calibration curve showed correlation coefficients (r) > 0.99 calculated by linear regression and analysis of variance (ANOVA). The limit of detection (LOD) and limit of quantitation (LOQ), respectively, were 2.2 and 6.7 mu g mL(-1) for anastrozole, 2.61 and 8.72 mu g mL(-1) for bicalutamide, 2.0 and 6.7 mu g mL(-1) for tamoxifen, 0.06 and 0.22 mu g mL(-1) for anastrozole pentamethyl, 0.02 and 0.07 mu g mL(-1) for bicalutamide 3-fluoro-isomer, and 0.002 and 0.007 mu g mL(-1) for tamoxifen e-isomer. Intraday and interday relative standard deviations (RSDs) were <2.0% (drugs) and <10% (degradation products) as well as the comparison between two different analysts, which were calculated by f test. (C) 2012 Elsevier B.V. All rights reserved.

A NEW METHOD TO QUANTIFY X-RAY SUBSTRUCTURES IN CLUSTERS OF GALAXIES

We present a new method to quantify substructures in clusters of galaxies, based on the analysis of the intensity of structures. This analysis is done in a residual image that is the result of the subtraction of a surface brightness model, obtained by fitting a two-dimensional analytical model (beta-model or Sersic profile) with elliptical symmetry, from the X-ray image. Our method is applied to 34 clusters observed by the Chandra Space Telescope that are in the redshift range z is an element of [0.02, 0.2] and have a signal-to-noise ratio (S/N) greater than 100. We present the calibration of the method and the relations between the substructure level with physical quantities, such as the mass, X-ray luminosity, temperature, and cluster redshift. We use our method to separate the clusters in two sub-samples of high-and low-substructure levels. We conclude, using Monte Carlo simulations, that the method recuperates very well the true amount of substructure for small angular core radii clusters (with respect to the whole image size) and good S/N observations. We find no evidence of correlation between the substructure level and physical properties of the clusters such as gas temperature, X-ray luminosity, and redshift; however, analysis suggest a trend between the substructure level and cluster mass. The scaling relations for the two sub-samples (high-and low-substructure level clusters) are different (they present an offset, i. e., given a fixed mass or temperature, low-substructure clusters tend to be more X-ray luminous), which is an important result for cosmological tests using the mass-luminosity relation to obtain the cluster mass function, since they rely on the assumption that clusters do not present different scaling relations according to their dynamical state.

A New Method to Predict the Epidemiology of Fungal Keratitis by Monitoring the Sales Distribution of Antifungal Eye Drops in Brazil

Purpose: Fungi are a major cause of keratitis, although few medications are licensed for their treatment. The aim of this study is to observe the variation in commercialisation of antifungal eye drops, and to predict the seasonal distribution of fungal keratitis in Brazil. Methods: Data from a retrospective study of antifungal eye drops sales from the only pharmaceutical ophthalmologic laboratory, authorized to dispense them in Brazil (Opthalmos) were gathered. These data were correlated with geographic and seasonal distribution of fungal keratitis in Brazil between July 2002 and June 2008. Results: A total of 26,087 antifungal eye drop units were sold, with a mean of 2.3 per patient. There was significant variation in antifungal sales during the year (p < 0.01). A linear regression model displayed a significant association between reduced relative humidity and antifungal drug sales (R-2 = 0.17, p < 0.01). Conclusions: Antifungal eye drops sales suggest that there is a seasonal distribution of fungal keratitis. A possible interpretation is that the third quarter of the year (a period when the climate is drier), when agricultural activity is more intense in Brazil, suggests a correlation with a higher incidence of fungal keratitis. A similar model could be applied to other diseases, that are managed with unique, or few, and monitorable medications to predict epidemiological aspects.

Maximal exercise test is a useful method for physical capacity and oxygen consumption determination in streptozotocin-diabetic rats

Abstract Background The aim of the present study was to investigate the relationship between speed during maximum exercise test (ET) and oxygen consumption (VO2) in control and STZ-diabetic rats, in order to provide a useful method to determine exercise capacity and prescription in researches involving STZ-diabetic rats. Methods Male Wistar rats were divided into two groups: control (CG, n = 10) and diabetic (DG, n = 8). The animals were submitted to ET on treadmill with simultaneous gas analysis through open respirometry system. ET and VO2 were assessed 60 days after diabetes induction (STZ, 50 mg/Kg). Results VO2 maximum was reduced in STZ-diabetic rats (72.5 ± 1 mL/Kg/min-1) compared to CG rats (81.1 ± 1 mL/Kg/min-1). There were positive correlations between ET speed and VO2 (r = 0.87 for CG and r = 0.8 for DG), as well as between ET speed and VO2 reserve (r = 0.77 for CG and r = 0.7 for DG). Positive correlations were also obtained between measured VO2 and VO2 predicted values (r = 0.81 for CG and r = 0.75 for DG) by linear regression equations to CG (VO2 = 1.54 * ET speed + 52.34) and DG (VO2 = 1.16 * ET speed + 51.99). Moreover, we observed that 60% of ET speed corresponded to 72 and 75% of VO2 reserve for CG and DG, respectively. The maximum ET speed was also correlated with VO2 maximum for both groups (CG: r = 0.7 and DG: r = 0.7). Conclusion These results suggest that: a) VO2 and VO2 reserve can be estimated using linear regression equations obtained from correlations with ET speed for each studied group; b) exercise training can be prescribed based on ET in control and diabetic-STZ rats; c) physical capacity can be determined by ET. Therefore, ET, which involves a relatively simple methodology and low cost, can be used as an indicator of cardio-respiratory capacity in future studies that investigate the physiological effect of acute or chronic exercise in control and STZ-diabetic male rats.

Hollow-fiber liquid-phase microextraction of amphetamine-type stimulants in human hair samples

A fast method was optimized and validated in order to quantify amphetamine-type stimulants (amphetamine, AMP; methamphetamine, MAMP; fenproporex, FPX; 3,4-methylenedioxymethamphetamine, MDMA; and 3,4-methylenedioxyamphetamine, MDA) in human hair samples. The method was based in an initial procedure of decontamination of hair samples (50 mg) with dichloromethane, followed by alkaline hydrolysis and extraction of the amphetamines using hollow-fiber liquid-phase micro extraction (HF-LPME) in the three-phase mode. Gas chromatography-mass spectrometry (GC-MS) was used for identification and quantification of the analytes. The LoQs obtained for all amphetamines (around 0.05 ng/mg) were below the cut-off value (0.2 ng/mg) established by the Society of Hair Testing (SoHT). The method showed to be simple and precise. The intra-day and inter-day precisions were within 10.6% and 11.4%, respectively, with the use of only two deuteratecl internal standards (AMP-d5 and MDMA-d5). By using the weighted least squares linear regression (1/x(2)), the accuracy of the method was satisfied in the lower concentration levels (accuracy values better than 87%). Hair samples collected from six volunteers who reported regular use of amphetamines were submitted to the developed method. Drug detection was observed in all samples of the volunteers. (c) 2012 Elsevier B.V. All rights reserved.

Ambient levels of air pollution induce clinical worsening of blepharitis

Background: Even though air pollutants exposure is associated with changes in the ocular surface and tear film, its relationship to the clinical course of blepharitis, a common eyelid disease, had not yet been investigated. Our objective was to investigate the correlation between air pollution and acute manifestations of blepharitis. Method: We recorded all cases of changes in the eyelids and ocular surface, and rated clinical findings on a scale from zero (normal) to two (severe alterations). Daily values of carbon monoxide, particulate matter smaller than 10 mu m in diameter and nitrogen dioxide concentrations and meteorological variables (temperature and relative humidity) in the vicinity of the medical service were obtained. Specific linear regression models for each outcome were constructed including pollutants as independent variables (single pollutant models). Temperature and humidity were included as confounding variables. Results: increases of 28.8 mu g/m(3) in the concentration of particulate matter and 1.1 ppm in the concentration of CO were associated with increases in cases of blepharitis on the day of exposure (5 cases, 95% CI: 1-10 and 6 cases, 95% CI: 1-12, respectively). Conclusion: Exposure to usual air pollutants concentrations present in large cities affects, in a consistent manner, the eyes of residents contributing to the increasing incidence of diseases of the eyelid margin. (C) 2011 Elsevier Inc. All rights reserved.

Determination of dimethyltryptamine and beta-carbolines (ayahuasca alkaloids) in plasma samples by LC-MS/MS

Background: Ayahuasca is a psychoactive plant beverage originally used by indigenous people throughout the Amazon Basin, long before its modern use by syncretic religious groups established in Brazil, the USA and European countries. The objective of this study was to develop a method for quantification of dimethyltryptamine and beta-carbolines in human plasma samples. Results: The analytes were extracted by means of C18 cartridges and injected into LC-MS/MS, operated in positive ion mode and multiple reaction monitoring. The LOQs obtained for all analytes were below 0.5 ng/ml. By using the weighted least squares linear regression, the accuracy of the analytical method was improved at the lower end of the calibration curve (from 0.5 to 100 ng/ml; r(2)> 0.98). Conclusion: The method proved to be simple, rapid and useful to estimate administered doses for further pharmacological and toxicological investigations of ayahuasca exposure.

Bartlett corrections in Birnbaum-Saunders nonlinear regression models

Lemonte and Cordeiro [Birnbaum-Saunders nonlinear regression models, Comput. Stat. Data Anal. 53 (2009), pp. 4441-4452] introduced a class of Birnbaum-Saunders (BS) nonlinear regression models potentially useful in lifetime data analysis. We give a general matrix Bartlett correction formula to improve the likelihood ratio (LR) tests in these models. The formula is simple enough to be used analytically to obtain several closed-form expressions in special cases. Our results generalize those in Lemonte et al. [Improved likelihood inference in Birnbaum-Saunders regressions, Comput. Stat. DataAnal. 54 (2010), pp. 1307-1316], which hold only for the BS linear regression models. We consider Monte Carlo simulations to show that the corrected tests work better than the usual LR tests.

Depletion study and estimation of the withdrawal period for oxytetracycline in tilapia cultured in Brazil

Defining pharmacokinetic parameters and depletion intervals for antimicrobials used in fish represents important guidelines for future regulation by Brazilian agencies of the use of these substances in fish farming. This article presents a depletion study for oxytetracycline (OTC) in tilapias (Orechromis niloticus) farmed under tropical conditions during the winter season. High performance liquid chromatography, with fluorescence detection for the quantitation of OTC in tilapia fillets and medicated feed, was developed and validated. The depletion study with fish was carried out under monitored environmental conditions. OTC was administered in the feed for five consecutive days at daily dosages of 80 mg/kg body weight. Groups of ten fish were slaughtered at 1, 2, 3, 4, 5, 8, 10, 15, 20, and 25 days after medication. After the 8th day posttreatment, OTC concentrations in the tilapia fillets were below the limit of quantitation (13 ng/g) of the method. Linear regression of the mathematical model of data analysis presented a coefficient of 0.9962. The elimination half- life for OTC in tilapia fillet and the withdrawal period were 1.65 and 6 days, respectively, considering a percentile of 99% with 95% of confidence and a maximum residue limit of 100 ng/g. Even though the study was carried out in the winter under practical conditions where water temperature varied, the results obtained are similar to others from studies conducted under controlled temperature.

THE UBV(RI)(C) COLORS OF THE SUN

Photometric data in the UBV(RI)(C) system have been acquired for 80 solar analog stars for which we have previously derived highly precise atmospheric parameters T-eff, log g, and [Fe/H] using high-resolution, high signal-to-noise ratio spectra. UBV and (RI)(C) data for 46 and 76 of these stars, respectively, are published for the first time. Combining our data with those from the literature, colors in the UBV(RI) C system, with similar or equal to 0.01 mag precision, are now available for 112 solar analogs. Multiple linear regression is used to derive the solar colors from these photometric data and the spectroscopically derived T-eff, log g, and [Fe/H] values. To minimize the impact of systematic errors in the model-dependent atmospheric parameters, we use only the data for the 10 stars that most closely resemble our Sun, i.e., the solar twins, and derive the following solar colors: (B - V)(circle dot) = 0.653 +/- 0.005, (U - B)(circle dot) = 0.166 +/- 0.022, (V - R)(circle dot) = 0.352 +/- 0.007, and (V - I)(circle dot) = 0.702 +/- 0.010. These colors are consistent, within the 1 sigma errors, with those derived using the entire sample of 112 solar analogs. We also derive the solar colors using the relation between spectral-line-depth ratios and observed stellar colors, i.e., with a completely model-independent approach, and without restricting the analysis to solar twins. We find (B - V)(circle dot) = 0.653 +/- 0.003, (U - B)(circle dot) = 0.158 +/- 0.009, (V - R)(circle dot) = 0.356 +/- 0.003, and (V - I)(circle dot) = 0.701 +/- 0.003, in excellent agreement with the model-dependent analysis.