UV determination of epinephrine, uric acid, and acetaminophen in pharmaceutical formulations and some human body fluids using multivariate calibration

In this work, a spectrophotometric methodology was applied in order to determine epinephrine (EP), uric acid (UA), and acetaminophen (AC) in pharmaceutical formulations and spiked human serum, plasma, and urine by using a multivariate approach. Multivariate calibration methods such as partial least squares (PLS) methods and its derivates were used to obtain a model for simultaneous determination of EP, UA and AC with good figures of merit and mixture design was in the range of 1.8 - 35.3, 1.7 - 16.8, and 1.5 - 12.1 µg mL-1. The 2nd derivate PLS showed recoveries of 95.3 - 103.3, 93.3 - 104.0, and 94.0 - 105.5 µg mL-1 for EP, UA, and AC, respectively.

PREDICTING THE BOILING POINT OF PCDD/Fs BY THE QSPR METHOD BASED ON THE MOLECULAR DISTANCE-EDGE VECTOR INDEX

The quantitative structure property relationship (QSPR) for the boiling point (Tb) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) was investigated. The molecular distance-edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR) and artificial neural network (ANN), respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE) of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.

REDUÇÃO DE VARIÁVEIS DE ENTRADA DE REDES NEURAIS ARTIFICIAIS A PARTIR DE DADOS DE ANÁLISE DE COMPONENTES PRINCIPAIS NA MODELAGEM DE OXIGÊNIO DISSOLVIDO

The objective of this work is to demonstrate the efficient utilization of the Principal Components Analysis (PCA) as a method to pre-process the original multivariate data, that is rewrite in a new matrix with principal components sorted by it's accumulated variance. The Artificial Neural Network (ANN) with backpropagation algorithm is trained, using this pre-processed data set derived from the PCA method, representing 90.02% of accumulated variance of the original data, as input. The training goal is modeling Dissolved Oxygen using information of other physical and chemical parameters. The water samples used in the experiments are gathered from the Paraíba do Sul River in São Paulo State, Brazil. The smallest Mean Square Errors (MSE) is used to compare the results of the different architectures and choose the best. The utilization of this method allowed the reduction of more than 20% of the input data, which contributed directly for the shorting time and computational effort in the ANN training.

Description of epidemics of coffee rust with neural networks

The objective of this paper was to evaluate the potential of neural networks (NN) as an alternative method to the basic epidemiological approach to describe epidemics of coffee rust. The NN was developed from the intensities of coffee (Coffea arabica) rust along with the climatic variables collected in Lavras-MG between 13 February 1998 and 20 April 2001. The NN was built with climatic variables that were either selected in a stepwise regression analysis or by the Braincel® system, software for NN building. Fifty-nine networks and 26 regression models were tested. The best models were selected based on small values of the mean square deviation (MSD) and of the mean prediction error (MPE). For the regression models, the highest coefficients of determination (R²) were used. The best model developed with neural networks had an MSD of 4.36 and an MPE of 2.43%. This model used the variables of minimum temperature, production, relative humidity of the air, and irradiance 30 days before the evaluation of disease. The best regression model was developed from 29 selected climatic variables in the network. The summary statistics for this model were: MPE=6.58%, MSE=4.36, and R²=0.80. The elaborated neural networks from a time series also were evaluated to describe the epidemic. The incidence of coffee rust at four previous fortnights resulted in a model with MPE=4.72% and an MSD=3.95.

Uso de análise exploratória de dados e de regressão robusta na avaliação do crescimento de espécies comerciais de terra firme da Amazônia

Esta pesquisa originou-se de uma base de dados de dois inventários a 100%, realizados em 1984 e 2000 sobre uma mesma área de 576 ha de floresta tropical primária, localizada na Floresta Nacional do Tapajós, Belterra, Pará. O objetivo da pesquisa foi utilizar a análise exploratória de dados e a regressão robusta para modelar o crescimento em diâmetro e área basal. Nos dois inventários as circunferências à altura do peito (CAP) foram medidas com fitamétrica, enquanto as alturas comerciais em 1984 foram medidas com o hipsômetro de Weiss e em 2000, estimadas com o uso de varas; o DAP mínimo em 1984 foi de 55 cm para todas as espécies e em 2000 foi adotado o DAP mínimo de 35 cm. As análises estatísticas foram precedidas de análise exploratória de dados (AED), em que foram utilizados o box plot (caixa-de-bigodes) na detecção de outliers (observações discrepantes) e o gráfico stem-and-leaf (tronco-e-folhas) para filtrar as observações extremas. Utilizou-se a regressão robusta para ajustar os modelos na presença de outliers. A pesquisa mostrou que, apesar das variações intra e interespecíficas, as seis espécies, em conjunto, apresentaram taxas de crescimento medianas observadas e esperadas em diâmetro e área basal de 4,56 e 4,28 mm/ano e 13,00 e 13,09 cm²/ha/ano, respectivamente. A pesquisa também mostrou que o uso da análise exploratória de dados e da regressão robusta viabilizou a análise e a determinação dos incrementos periódicos em diâmetro e área basal em bases consistentes. A metodologia empregada no caso específico dos dados disponíveis e tipos de variáveis mostrou ser mais eficiente com o uso de regressão robusta pelo método Least Trimmed Square do que pelo método dos mínimos quadrados ordinários.

Production of baruzeiro seedling in different protected environments and substrates

The high seedlings quality is essential for deployment of homogeneous orchards. This study evaluated the baruzeiro (Dipteryx alata Vog) seedlings formation on different substrates within protected environments. It was used substrates with100% of cattle manure; 100% of cassava stems; 100% of vermiculite; 50% of cattle manure + 50% of cassava stems; 50% of cattle manure + 50% of vermiculite; 50% of cassava stems + 50% of vermiculite; and + ⅓ of cattle manure + ⅓ of cassava stems + ⅓ of vermiculite. These substrates were tested in protected areas: greenhouse; black shade net of 50% shading; and aluminized thermo-reflective screen of 50% shading. A completely randomized experimental design with five replicates of four plants was adopted. Initially, data were submitted to analysis of individual variance of the substrates, in each environment of cultivation, then performing the evaluation of the residual mean square and the analysis of these environments together for comparison. The best substrate for baruzeiro seedlings was pure vermiculite. The substrates with 100% of manure and the substrate with 33.33% of the mixed studied materials can be used for seedlings formation. The environment with screen can be indicated for the production of baruzeiro seedlings, since it gave vigor to the seedlings.

Comparison between hydrographically conditioned digital elevation models in the morphometric charaterization of watersheds

The aim of this study was to compare the hydrographically conditioned digital elevation models (HCDEMs) generated from data of VNIR (Visible Near Infrared) sensor of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), of SRTM (Shuttle Radar Topography Mission) and topographical maps from IBGE in a scale of 1:50,000, processed in the Geographical Information System (GIS), aiming the morphometric characterization of watersheds. It was taken as basis the Sub-basin of São Bartolomeu River, obtaining morphometric characteristics from HCDEMs. Root Mean Square Error (RMSE) and cross validation were the statistics indexes used to evaluate the quality of HCDEMs. The percentage differences in the morphometric parameters obtained from these three different data sets were less than 10%, except for the mean slope (21%). In general, it was observed a good agreement between HCDEMs generated from remote sensing data and IBGE maps. The result of HCDEM ASTER was slightly higher than that from HCDEM SRTM. The HCDEM ASTER was more accurate than the HCDEM SRTM in basins with high altitudes and rugged terrain, by presenting frequency altimetry nearest to HCDEM IBGE, considered standard in this study.

Seedlings of Acrocomia aculeata in diferent substrates and protected environments

The seedling production stage is the key to achieve uniformity in tree breeding stage. This study evaluated "bocaiúva" (Acrocomia aculeata) seedling formation, with pre-germinated seeds in different substrates and protected environments, in the University of Mato Grosso do Sul State, Aquidauana, MS. As substrates, we used 100% cattle manure (M), 100% cassava branches (CB), 100% vermiculite (V), 50% cattle manure + 50% cassava branches, 50 % cattle manure + 50% vermiculite, 50% cassava branches + 50% vermiculite and ⅓ cattle manure + ⅓ cassava branches + ⅓ vermiculite. These substrates were tested in a greenhouse covered with 150 µm low density polyethylene (LDPE) film under thermo-reflective screen with 50% shading under film; black screen with 50% shading on the sides; black monofilament screen with 50% shading set on roof and sides; and aluminized thermo- reflective screen with 50% shading set on roof and sides. The completely randomized experimental design with 5 replications of 5 plants each was adopted. Initially, data were submitted to analysis of substrate individual variance in each growing environment, then performing the waste mean square evaluation and their environment joint analysis for comparison. The best growing environment is the thermo-reflective screen compared to LDPE greenhouse and black screen set. All substrates containing manure are recommended for bocaiúva seedlings formation. The pure cassava branch is not indicated for seedling, even using chemical fertilizer.

Fracture modes and acoustic emission characteristics of hydrogen-assisted cracking in high-strength low-alloy steel weldment

The aim of the present paper is to study the relationship between the fracture modes in hydrogen-assisted cracking (HAC) in microalloied steel and the emission of acoustic signals during the fracturing process. For this reason, a flux-cored arc weld (FCAW) was used in a high-strength low-alloy steel. The consumable used were the commercially available AWS E120T5-K4 and had a diameter of 1.6 mm. Two different shielding gases were used (CO2 and CO2+5% H2) to obtain complete phenomenon characterization. The implant test was applied with three levels of restriction stresses. An acoustic emission measurement system (AEMS) was coupled to the implant test apparatus. The output signal from the acoustic emission sensor was passed through an electronic amplifier and processed by a root mean square (RMS) voltage converter. Fracture surfaces were examined by scanning electron microscopy (SEM) and image analysis. Fracture modes were related with the intensity, the energy and the number of the peaks of the acoustic emission signal. The shielding gas CO2+5% H2 proved to be very useful in the experiments. Basically, three different fracture modes were identified in terms of fracture appearance: microvoid coalescence (MVC), intergranular (IG) and quasi-cleavage (QC). The results show that each mode of fracture presents a characteristic acoustic signal.

Forecasting of wind speeds and directions with artificial neural networks

In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.

Time course of changes in heart rate and blood pressure variability in streptozotocin-induced diabetic rats treated with insulin

Autonomic neuropathy is a frequent complication of diabetes associated with higher morbidity and mortality in symptomatic patients, possibly because it affects autonomic regulation of the sinus node, reducing heart rate (HR) variability which predisposes to fatal arrhythmias. We evaluated the time course of arterial pressure and HR and indirectly of autonomic function (by evaluation of mean arterial pressure (MAP) variability) in rats (164.5 ± 1.7 g) 7, 14, 30 and 120 days after streptozotocin (STZ) injection, treated with insulin, using measurements of arterial pressure, HR and MAP variability. HR variability was evaluated by the standard deviation of RR intervals (SDNN) and root mean square of successive difference of RR intervals (RMSSD). MAP variability was evaluated by the standard deviation of the mean of MAP and by 4 indices (P1, P2, P3 and MN) derived from the three-dimensional return map constructed by plotting MAPn x [(MAPn+1) - (MAPn)] x density. The indices represent the maximum concentration of points (P1), the longitudinal axis (P2), and the transversal axis (P3) and MN represents P1 x P2 x P3 x 10-3. STZ induced increased urinary glucose in diabetic (D) rats compared to controls (C). Seven days after STZ, diabetes reduced resting HR from 380.6 ± 12.9 to 319.2 ± 19.8 bpm, increased HR variability, as demonstrated by increased SDNN, from 11.77 ± 1.67 to 19.87 ± 2.60 ms, did not change MAP, and reduced P1 from 61.0 ± 5.3 to 51.5 ± 1.8 arbitrary units (AU), P2 from 41.3 ± 0.3 to 29.0 ± 1.8 AU, and MN from 171.1 ± 30.2 to 77.2 ± 9.6 AU of MAP. These indices, as well as HR and MAP, were similar for D and C animals 14, 30 and 120 days after STZ. Seven-day rats showed a negative correlation of urinary glucose with resting HR (r = -0.76, P = 0.03) as well as with the MN index (r = -0.83, P = 0.01). We conclude that rats with short-term diabetes mellitus induced by STZ presented modified autonomic control of HR and MAP which was reversible. The metabolic control may influence these results, suggesting that insulin treatment and a better metabolic control in this model may modify arterial pressure, HR and MAP variability

Evaluation of electromyographic activity and heart rate responses to isometric exercise. The role played by muscular mass and type

The purpose of the present study was to examine the relationship between the electromyographic (EMG) activity and heart rate (HR) responses induced by isometric exercise performed by knee extension (KE) and flexion (KF) in men. Fifteen healthy male subjects, 21 ± 1.3 years (mean ± SD), were submitted to KE and KF isometric exercise tests at 100% of maximal voluntary contraction (MVC). The exercises were performed with one leg (right or left) and with two legs simultaneously, for 10 s in the sitting position with the hip and knee flexed at 90o. EMG activity (root mean square values) and HR (beats/min) were recorded simultaneously both at rest and throughout the sustained contraction. The HR responses to isometric exercise in KE and KF were similar when performed with one and two legs. However, the HR increase was always significantly higher in KE than KF (P<0.05), whereas the EMG activity was higher in KE than in KF (P<0.05), regardless of the muscle mass (one or two legs) involved in the effort. The correlation coefficients between HR response and the EMG activity during KE (r = 0.33, P>0.05) and KF (r = 0.15, P>0.05) contractions were not significant. These results suggest that the predominant mechanism responsible for the larger increase in HR response to KE as compared to KF in our study could be dependent on qualitative and quantitative differences in the fiber type composition found in each muscle group. This mechanism seems to demand a higher activation of motor units with a corresponding increase in central command to the cardiovascular centers that modulate HR control.

Relative influence of age, resting heart rate and sedentary life style in short-term analysis of heart rate variability

In order to assess the relative influence of age, resting heart rate (HR) and sedentary life style, heart rate variability (HRV) was studied in two different groups. The young group (YG) consisted of 9 sedentary subjects aged 15 to 20 years (YG-S) and of 9 nonsedentary volunteers (YG-NS) also aged 15 to 20. The elderly sedentary group (ESG) consisted of 16 sedentary subjects aged 39 to 82 years. HRV was assessed using a short-term procedure (5 min). R-R variability was calculated in the time-domain by means of the root mean square successive differences. Frequency-domain HRV was evaluated by power spectrum analysis considering high frequency and low frequency bands. In the YG the effort tolerance was ranked in a bicycle stress test. HR was similar for both groups while ESG showed a reduced HRV compared with YG. Within each group, HRV displayed a negative correlation with HR. Although YG-NS had better effort tolerance than YG-S, their HR and HRV were not significantly different. We conclude that HRV is reduced with increasing HR or age, regardless of life style. The results obtained in our short-term study agree with others of longer duration by showing that age and HR are the main determinants of HRV. Our results do not support the idea that changes in HRV are related to regular physical activity.

Heart rate variability under resting conditions in postmenopausal and young women

The aim of the present study was to compare the modulation of heart rate in a group of postmenopausal women to that of a group of young women under resting conditions on the basis of R-R interval variability. Ten healthy postmenopausal women (mean ± SD, 58.3 ± 6.8 years) and 10 healthy young women (mean ± SD, 21.6 ± 0.82 years) were submitted to a control resting electrocardiogram (ECG) in the supine and sitting positions over a period of 6 min. The ECG was obtained from a one-channel heart monitor at the CM5 lead and processed and stored using an analog to digital converter connected to a microcomputer. R-R intervals were calculated on a beat-to-beat basis from the ECG recording in real time using a signal-processing software. Heart rate variability (HRV) was expressed as standard deviation (RMSM) and mean square root (RMSSD). In the supine position, the postmenopausal group showed significantly lower (P<0.05) median values of RMSM (34.9) and RMSSD (22.32) than the young group (RMSM: 62.11 and RMSSD: 49.1). The same occurred in the sitting position (RMSM: 33.0 and RMSSD: 18.9 compared to RMSM: 57.6 and RMSSD: 42.8 for the young group). These results indicate a decrease in parasympathetic modulation in postmenopausal women compared to young women which was possibly due both to the influence of age and hormonal factors. Thus, time domain HRV proved to be a noninvasive and sensitive method for the identification of changes in autonomic modulation of the sinus node in postmenopausal women.

Effect of the acupoints ST-36 (Zusanli) and SP-6 (Sanyinjiao) on intestinal myoelectric activity of Wistar rats

Despite its ancient use as a therapeutic tool to treat several ailments, acupuncture still faces the challenge of scrutiny by Western science both in terms of its efficacy and in terms of the characterization of its effects and mechanisms of actions underlying these effects. We investigated under well-controlled and carefully characterized conditions the influence of electrical stimulation of acupuncture points ST-36 (Zusanli) and SP-6 (Sanyinjiao) on the myoelectric activity of the small intestine of 38 adult male Wistar rats. Electrical recordings obtained by means of four electrodes chronically implanted in the small intestine were used to assess the effects of acupuncture (electroacupuncture stimulation set at 2 Hz, intermittent stimulation, 1 V, for 30 min). Immobilization of the animals was associated with a consistent decrease (-8 ± 7%) in the myoelectric activity of the small intestine as measured by means of the root mean square. Conversely, acupuncture was able to significantly increase (overshoot) this activity compared to baseline (+44 ± 7%). In contrast, immobilized animals subjected to sham acupuncture had only modest (nonsignificant) increases in myoelectric activity (+9 ± 6%). Using carefully controlled conditions we confirmed previous noncontrolled studies on the ability of acupuncture to alter intestinal motility. The characterization of the topographic and temporal profiles of the effects observed here represents a basis for future dissection of the physiological and pharmacological systems underlying these effects.