952 resultados para rainfall coefficient


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The purpose of this study was to develop and validate analytical methods for determination of amlodipine besylate in tablets. Simple, accurate and precise liquid chromatographic and spectrophotometric methods are proposed. For the chromatographic method, the conditions were: a LiChrospher (R) 100 RP-18 Merck (R) (125 mm x 4.6 mm, 5 mu m) column; methanol/water containing 1 % of trietylamine adjusted to pH 5.0 with phosphoric acid (35:65) as mobile phase; a flow rate of 1.0 mL/min and UV detector at 238 nm. Linearity was in the range of 50.0 - 350.0 mu g/mL with a correlation coefficient (r) = 0.9999. For the spectrophotometric method, the first dilutions of samples were performed in methanol and the consecutives in ultrapure water. The quantitation was made at 364.4 nm. Linearity was determined within the range of 41.0 - 61.0 mu g/mL with a correlation coefficient (r) = 0.9996. Our results demonstrate that both methods can be used in routine analysis for quality control of tablets containing amlodipine besylate.

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A simple method was optimized and validated for determination of ractopamine hydrochloride (RAC) in raw material and feed additives by HPLC for use in quality control in veterinary industries. The best-optimized conditions were a C8 column (250 x 4.6 mm id, 5.0 mu m particle size) at room temperature with acetonitrile-100 mM sodium acetate buffer (pH 5.0; 75 + 25, v/v) mobile phase at a flow rate of 1.0 mL/min and UV detection at 275 nm. With these conditions, the retention time of RAC was around 5.2 min, and standard curves were linear in the concentration range of 160-240 mu g/mL (correlation coefficient >= 0.999). Validation parameters, such as selectivity, linearity, limit of detection (ranged from 1.60 to 2.05 mu g/mL), limit of quantification (ranged from 4.26 to 6.84 mu g/mL), precision (relative standard deviation <= 1.87%), accuracy (ranged from 96.97 to 100.54%), and robustness, gave results within acceptable ranges. Therefore, the developed method can be successfully applied for the routine quality control analysis of raw material and feed additives.

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Introduction: Whole blood is used for diagnosis of lead exposure. A non-invasive method to obtain samples for the biomonitoring of lead contamination has become a necessity. This study 1) compares the lead content in whole saliva samples (Pb-saliva) of children from a city with no reported lead contamination (Ribeirao Preto, Sao Paulo State, Brazil) and children of a region notoriously contaminated with lead (Bauru, Sao Paulo State, Brazil), and 2) correlates Pb-saliva with the lead content in the enamel microbiopsy samples (Pb-enamel) in the case of these two populations. Methods: From a population of our previous study that had included 247 children (4- to 6-year-old) from Ribeirao Preto, and 26 children from Bauru, Pb-saliva was analyzed in 125 children from Ribeirdo Preto and 19 children from Bauru by inductively coupled plasma mass spectrometry (ICPMS). To correlate Pb-saliva with Pb-enamel, we used Pb-enamel data obtained in our previous study. The Mann-Whitney test was employed to compare the Pb-saliva data of the two cities. Pb-saliva and Pb-enamel values were then Log(10) transformed to normalize data, and Pb-saliva and Pb-enamel were correlated using Pearson`s correlation coefficient. Results: Median Pb-saliva from the Ribeirao Preto population (1.64 mu g/L) and the Bauru population (5.85 mu g/L) were statistically different (p<0.0001). Pearson`s correlation coefficient for Log(10) Pb-saliva versus Log(10) Pb-enamel was 0.15 (p=0.08) for Ribeirao Preto and 0.38 (p=0.11) for Bauru. Conclusions: A clear relationship between Pb-saliva and environmental contamination by lead is shown. Further studies on Pb-saliva should be undertaken to elucidate the usefulness of saliva as a biomarker of lead exposure, particularly in children. (C) 2008 Elsevier B.V. All rights reserved.

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The supervised pattern recognition methods K-Nearest Neighbors (KNN), stepwise discriminant analysis (SDA), and soft independent modelling of class analogy (SIMCA) were employed in this work with the aim to investigate the relationship between the molecular structure of 27 cannabinoid compounds and their analgesic activity. Previous analyses using two unsupervised pattern recognition methods (PCA-principal component analysis and HCA-hierarchical cluster analysis) were performed and five descriptors were selected as the most relevants for the analgesic activity of the compounds studied: R (3) (charge density on substituent at position C(3)), Q (1) (charge on atom C(1)), A (surface area), log P (logarithm of the partition coefficient) and MR (molecular refractivity). The supervised pattern recognition methods (SDA, KNN, and SIMCA) were employed in order to construct a reliable model that can be able to predict the analgesic activity of new cannabinoid compounds and to validate our previous study. The results obtained using the SDA, KNN, and SIMCA methods agree perfectly with our previous model. Comparing the SDA, KNN, and SIMCA results with the PCA and HCA ones we could notice that all multivariate statistical methods classified the cannabinoid compounds studied in three groups exactly in the same way: active, moderately active, and inactive.

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Movements of two female one-humped camels in central Australia were tracked using satellite telemetry between March 1986 and July 1987. During that time both animals travelled a minimum distance of over 1000 km within a radius of 125 km for one animal, and 200 km for the other. However, their movements were uite punctuated and both animals spent periods of up to several months in rleatively small areas before moving over longer distances to new areas. Both camels moved at greater rates overnight. An activity index, probably measuring feeding rate, declined during the study period for both animals. Patchy and sporadic rainfall may explain some of these results.

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The detection of seizure in the newborn is a critical aspect of neurological research. Current automatic detection techniques are difficult to assess due to the problems associated with acquiring and labelling newborn electroencephalogram (EEG) data. A realistic model for newborn EEG would allow confident development, assessment and comparison of these detection techniques. This paper presents a model for newborn EEG that accounts for its self-similar and non-stationary nature. The model consists of background and seizure sub-models. The newborn EEG background model is based on the short-time power spectrum with a time-varying power law. The relationship between the fractal dimension and the power law of a power spectrum is utilized for accurate estimation of the short-time power law exponent. The newborn EEG seizure model is based on a well-known time-frequency signal model. This model addresses all significant time-frequency characteristics of newborn EEG seizure which include; multiple components or harmonics, piecewise linear instantaneous frequency laws and harmonic amplitude modulation. Estimates of the parameters of both models are shown to be random and are modelled using the data from a total of 500 background epochs and 204 seizure epochs. The newborn EEG background and seizure models are validated against real newborn EEG data using the correlation coefficient. The results show that the output of the proposed models has a higher correlation with real newborn EEG than currently accepted models (a 10% and 38% improvement for background and seizure models, respectively).

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There is substantial disagreement among published epidemiological studies regarding environmental risk factors for Parkinson’s disease (PD). Differences in the quality of measurement of environmental exposures may contribute to this variation. The current study examined the test–retest repeatability of self-report data on risk factors for PD obtained from a series of 32 PD cases recruited from neurology clinics and 29 healthy sex-, age-and residential suburb-matched controls. Exposure data were collected in face-to-face interviews using a structured questionnaire derived from previous epidemiological studies. High repeatability was demonstrated for ‘lifestyle’ exposures, such as smoking and coffee/tea consumption (kappas 0.70–1.00). Environmental exposures that involved some action by the person, such as pesticide application and use of solvents and metals, also showed high repeatability (kappas>0.78). Lower repeatability was seen for rural residency and bore water consumption (kappa 0.39–0.74). In general, we found that case and control participants provided similar rates of incongruent and missing responses for categorical and continuous occupational, domestic, lifestyle and medical exposures.

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Mineralogical, hydrochemical and S isotope data were used to constrain hydrogeochemical processes that produce acid mine drainage from sulfidic waste at the historic Mount Morgan Au–Cu mine, and the factors controlling the concentration of SO4 and environmentally hazardous metals in the nearby Dee River in Queensland, Australia. Some highly contaminated acid waters, with metal contents up to hundreds of orders of magnitude greater than the Australia–New Zealand environmental standards, by-pass the water management system at the site and drain into the adjacent Dee River. Mine drainage precipitates at Mt. Morgan were classified into 4 major groups and were identified as hydrous sulfates and hydroxides of Fe and Al with various contents of other metals. These minerals contain adsorbed or mineralogically bound metals that are released into the water system after rainfall events. Sulfate in open pit water and collection sumps generally has a narrow range of S isotope compositions (δ34S = 1.8–3.7‰) that is comparable to the orebody sulfides and makes S isotopes useful for tracing SO4 back to its source. The higher δ34S values for No. 2 Mill Diesel sump may be attributed to a difference in the source. Dissolved SO4 in the river above the mine influence and 20 km downstream show distinctive heavier isotope compositions (δ34S = 5.4–6.8‰). The Dee River downstream of the mine is enriched in 34S (δ34S = 2.8–5.4‰) compared with mine drainage possibly as a result of bacterial SO4 reduction in the weir pools, and in the water bodies within the river channel. The SO4 and metals attenuate downstream by a combination of dilution with the receiving waters, SO4 reduction, and the precipitation of Fe and Al sulfates and hydroxides. It is suggested here that in subtropical Queensland, with distinct wet and dry seasons, temporary reducing environments in the river play an important role in S isotope systematics

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Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

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We investigate the effect of the coefficient of the critical nonlinearity for the Neumann problem on the existence of least energy solutions. As a by-product we establish a Sobolev inequality with interior norm.

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The Direct Simulation Monte Carlo (DSMC) method is used to simulate the flow of rarefied gases. In the Macroscopic Chemistry Method (MCM) for DSMC, chemical reaction rates calculated from local macroscopic flow properties are enforced in each cell. Unlike the standard total collision energy (TCE) chemistry model for DSMC, the new method is not restricted to an Arrhenius form of the reaction rate coefficient, nor is it restricted to a collision cross-section which yields a simple power-law viscosity. For reaction rates of interest in aerospace applications, chemically reacting collisions are generally infrequent events and, as such, local equilibrium conditions are established before a significant number of chemical reactions occur. Hence, the reaction rates which have been used in MCM have been calculated from the reaction rate data which are expected to be correct only for conditions of thermal equilibrium. Here we consider artificially high reaction rates so that the fraction of reacting collisions is not small and propose a simple method of estimating the rates of chemical reactions which can be used in the Macroscopic Chemistry Method in both equilibrium and non-equilibrium conditions. Two tests are presented: (1) The dissociation rates under conditions of thermal non-equilibrium are determined from a zero-dimensional Monte-Carlo sampling procedure which simulates ‘intra-modal’ non-equilibrium; that is, equilibrium distributions in each of the translational, rotational and vibrational modes but with different temperatures for each mode; (2) The 2-D hypersonic flow of molecular oxygen over a vertical plate at Mach 30 is calculated. In both cases the new method produces results in close agreement with those given by the standard TCE model in the same highly nonequilibrium conditions. We conclude that the general method of estimating the non-equilibrium reaction rate is a simple means by which information contained within non-equilibrium distribution functions predicted by the DSMC method can be included in the Macroscopic Chemistry Method.

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The area of private land suitable and available for growing hoop pine (Araucaria cunninghamii) on the Atherton Tablelands in North Queensland was modelled using a geographic information system (GIS). In Atherton, Eacham and Herberton shires, approximately 64,700 ha of privately owned land were identified as having a mean annual rainfall and soil type similar to Forestry Plantations Queensland (FPQ) hoop pine growth plots with an approximate growth rate of 20 m3 per annum. Land with slope of over 25° and land covered with native vegetation were excluded in the estimation. If land which is currently used for high-value agriculture is also excluded, the net area of land potentially suitable and available for expansion of hoop pine plantations is approximately 22,900 ha. Expert silvicultural advice emphasized the role of site preparation and weed control in affecting the long-term growth rate of hoop pine. Hence, sites with less than optimal fertility and rainfall may be considered as being potentially suitable for growing hoop pine at a lower growth rate. The datasets had been prepared at various scales and differing precision for their description of land attributes. Therefore, the results of this investigation have limited applicability for planning at the individual farm level but are useful at the regional level to target areas for plantation expansion.

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The study of the mechanisms of mechanical alloying requires knowledge of the impact characteristics between the ball and vial in the presence of milling powders. In this paper, foe falling experiments have br cn used to investigate the characteristics of impact events involved in mechanical milling. The effects of milling conditions, including impact velocity, ball size and powder thickness. on the coefficient of restitution and impact force are studied. It is found that the powder has a significant influence on the impact process due to its porous structure. This effect can be demonstrated using a modified Kelvin model. This study also confirms that the impact force is a relevant parameter for characterising the impact event due to its sensitivity to the milling conditions. (C) 1998 Elsevier Science S.A.

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The aim of this work is to develop 3-acyl prodrugs of the potent analgesic morphine-6-sulfate (M6S). These are expected to have higher potency and/or exhibit longer duration of analgesic action than the parent compound. M6S and the prodrugs were synthesized, then purified either by recrystallization or by semi-preparative HPLC and the structures confirmed by mass spectrometry, IR spectrophotometry and by detailed 1- and 2-D NMR studies. The lipophilicities of the compounds were assessed by a combination of shake-flask, group contribution and HPLC retention methods. The octanol-buffer partition coefficient could only be obtained directly for 3-heptanoylmorphine-6-sulfate, using the shake-flask method. The partition coefficients (P) for the remaining prodrugs were estimated from known methylene group contributions. A good linear relationship between log P and the HPLC log capacity factors was demonstrated. Hydrolysis of the 3-acetyl prodrug, as a representative of the group, was found to occur relatively slowly in buffers (pH range 6.15-8.01), with a small buffer catalysis contribution. The rates of enzymatic hydrolysis of the 3-acyl group in 10% rat blood and in 10% rat brain homogenate were investigated. The prodrugs followed apparent first order hydrolysis kinetics, with a significantly faster hydrolysis rate found in 10% rat brain homogenate than in 10% rat blood for all compounds. (C) 1998 Elsevier Science B.V. All rights reserved.

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Bulk density of undisturbed soil samples can be measured using computed tomography (CT) techniques with a spatial resolution of about 1 mm. However, this technique may not be readily accessible. On the other hand, x-ray radiographs have only been considered as qualitative images to describe morphological features. A calibration procedure was set up to generate two-dimensional, high-resolution bulk density images from x-ray radiographs made with a conventional x-ray diffraction apparatus. Test bricks were made to assess the accuracy of the method. Slices of impregnated soil samples were made using hardsetting seedbeds that had been gamma scanned at 5-mm depth increments in a previous study. The calibration procedure involved three stages: (i) calibration of the image grey levels in terms of glass thickness using a staircase made from glass cover slips, (ii) measurement of ratio between the soil and resin mass attenuation coefficients and the glass mass attenuation coefficient, using compacted bricks of known thickness and bulk density, and (iii) image correction accounting for the heterogeneity of the irradiation field. The procedure was simple, rapid, and the equipment was easily accessible. The accuracy of the bulk density determination was good (mean relative error 0.015), The bulk density images showed a good spatial resolution, so that many structural details could be observed. The depth functions were consistent with both the global shrinkage and the gamma probe data previously obtained. The suggested method would be easily applied to the new fuzzy set approach of soil structure, which requires generation of bulk density images. Also, it would be an invaluable tool for studies requiring high-resolution bulk density measurement, such as studies on soil surface crusts.