953 resultados para Linear multivariate methods


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Conventional reflectance spectroscopy (NIRS) and hyperspectral imaging (HI) in the near-infrared region (1000-2500 nm) are evaluated and compared, using, as the case study, the determination of relevant properties related to the quality of natural rubber. Mooney viscosity (MV) and plasticity indices (PI) (PI0 - original plasticity, PI30 - plasticity after accelerated aging, and PRI - the plasticity retention index after accelerated aging) of rubber were determined using multivariate regression models. Two hundred and eighty six samples of rubber were measured using conventional and hyperspectral near-infrared imaging reflectance instruments in the range of 1000-2500 nm. The sample set was split into regression (n = 191) and external validation (n = 95) sub-sets. Three instruments were employed for data acquisition: a line scanning hyperspectral camera and two conventional FT-NIR spectrometers. Sample heterogeneity was evaluated using hyperspectral images obtained with a resolution of 150 × 150 μm and principal component analysis. The probed sample area (5 cm(2); 24,000 pixels) to achieve representativeness was found to be equivalent to the average of 6 spectra for a 1 cm diameter probing circular window of one FT-NIR instrument. The other spectrophotometer can probe the whole sample in only one measurement. The results show that the rubber properties can be determined with very similar accuracy and precision by Partial Least Square (PLS) regression models regardless of whether HI-NIR or conventional FT-NIR produce the spectral datasets. The best Root Mean Square Errors of Prediction (RMSEPs) of external validation for MV, PI0, PI30, and PRI were 4.3, 1.8, 3.4, and 5.3%, respectively. Though the quantitative results provided by the three instruments can be considered equivalent, the hyperspectral imaging instrument presents a number of advantages, being about 6 times faster than conventional bulk spectrometers, producing robust spectral data by ensuring sample representativeness, and minimizing the effect of the presence of contaminants.

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To subjectively and objectively compare an accessible interactive electronic library using Moodle with lectures for urology teaching of medical students. Forty consecutive fourth-year medical students and one urology teacher were exposed to two teaching methods (4 weeks each) in the form of problem-based learning: - lectures and - student-centered group discussion based on Moodle (modular object-oriented dynamic learning environment) full time online delivered (24/7) with video surgeries, electronic urology cases and additional basic principles of the disease process. All 40 students completed the study. While 30% were moderately dissatisfied with their current knowledge base, online learning course delivery using Moodle was considered superior to the lectures by 86% of the students. The study found the following observations: (1) the increment in learning grades ranged from 7.0 to 9.7 for students in the online Moodle course compared to 4.0-9.6 to didactic lectures; (2) the self-reported student involvement in the online course was characterized as large by over 60%; (3) the teacher-student interaction was described as very frequent (50%) and moderately frequent (50%); and (4) more inquiries and requisitions by students as well as peer assisting were observed from the students using the Moodle platform. The Moodle platform is feasible and effective, enthusing medical students to learn, improving immersion in the urology clinical rotation and encouraging the spontaneous peer assisted learning. Future studies should expand objective evaluations of knowledge acquisition and retention.

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Since the last decade, the combined use of chemometrics and molecular spectroscopic techniques has become a new alternative for direct drug determination, without the need of physical separation. Among the new methodologies developed, the application of PARAFAC in the decomposition of spectrofluorimetric data should be highlighted. The first objective of this article is to describe the theoretical basis of PARAFAC. For this purpose, a discussion about the order of chemometric methods used in multivariate calibration and the development of multi-dimensional methods is presented first. The other objective of this article is to divulge for the Brazilian chemical community the potential of the combination PARAFAC/spectrofluorimetry for the determination of drugs in complex biological matrices. For this purpose, two applications aiming at determining, respectively, doxorrubicine and salicylate in human plasma are presented.

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Chemometric activities in Brazil are described according to three phases: before the existence of microcomputers in the 1970s, through the initial stages of microcomputer use in the 1980s and during the years of extensive microcomputer applications of the ´90s and into this century. Pioneering activities in both the university and industry are emphasized. Active research areas in chemometrics are cited including experimental design, pattern recognition and classification, curve resolution for complex systems and multivariate calibration. New trends in chemometrics, especially higher order methods for treating data, are emphasized.

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In this work, the artificial neural networks (ANN) and partial least squares (PLS) regression were applied to UV spectral data for quantitative determination of thiamin hydrochloride (VB1), riboflavin phosphate (VB2), pyridoxine hydrochloride (VB6) and nicotinamide (VPP) in pharmaceutical samples. For calibration purposes, commercial samples in 0.2 mol L-1 acetate buffer (pH 4.0) were employed as standards. The concentration ranges used in the calibration step were: 0.1 - 7.5 mg L-1 for VB1, 0.1 - 3.0 mg L-1 for VB2, 0.1 - 3.0 mg L-1 for VB6 and 0.4 - 30.0 mg L-1 for VPP. From the results it is possible to verify that both methods can be successfully applied for these determinations. The similar error values were obtained by using neural network or PLS methods. The proposed methodology is simple, rapid and can be easily used in quality control laboratories.

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The validation of an analytical procedure must be certified through the determination of parameters known as figures of merit. For first order data, the acuracy, precision, robustness and bias is similar to the methods of univariate calibration. Linearity, sensitivity, signal to noise ratio, adjustment, selectivity and confidence intervals need different approaches, specific for multivariate data. Selectivity and signal to noise ratio are more critical and they only can be estimated by means of the calculation of the net analyte signal. In second order calibration, some differentes approaches are necessary due to data structure.

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The importance of medicinal plants and their use in industrial applications is increasing worldwide, especially in Brazil. Phyllanthus species, popularly known as quebra-pedras in Brazil, are used in folk medicine for treating urinary infections and renal calculus. This paper reports an authenticity study, based on herbal drugs from Phyllanthus species, involving commercial and authentic samples using spectroscopic techniques: FT-IR, ¹H HR-MAS NMR and ¹H NMR in solution, combined with chemometric analysis. The spectroscopic techniques evaluated, coupled with chemometric methods, have great potential in the investigation of complex matrices. Furthermore, several metabolites were identified by the NMR techniques.

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Remote sensing data are each time more available and can be used to monitor the vegetal development of main agricultural crops, such as the Arabic coffee in Brazil, since that the relationship between spectral and agronomical data be well known. Therefore, this work had the main objective to assess the use of Quickbird satellite images to estimate biophysical parameters of coffee crop. Test area was composed by 25 coffee fields located between the cities of Ribeirão Corrente, Franca and Cristais Paulista (SP), Brazil, and the biophysical parameters used were row and between plants spacing, plant height, LAI, canopy diameter, percentage of vegetation cover, roughness and biomass. Spectral data were the reflectance of four bands of QUICKBIRD and values of four vegetations indexes (NDVI, GVI, SAVI and RVI) based on the same satellite. All these data were analyzed using linear and nonlinear regression methods to generate estimation models of biophysical parameters. The use of regression models based on nonlinear equations was more appropriate to estimate parameters such as the LAI and the percentage of biomass, important to indicate the productivity of coffee crop.

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This study examined the influence of three polymerization cycles (1: heat cure - long cycle; 2: heat cure - short cycle; and 3: microwave activation) on the linear dimensions of three denture base resins, immediately after deflasking, and 30 days after storage in distilled water at 37± 2ºC. The acrylic resins used were: Clássico, Lucitone 550 and Acron MC. The first two resins were submitted to all three polymerization cycles, and the Acron MC resin was cured by microwave activation only. The samples had three marks, and dimensions of 65 mm in length, 10 mm in width and 3 mm in thickness. Twenty-one test specimens were fabricated for each combination of resin and cure cycle, and they were submitted to three linear dimensional evaluations for two positions (A and B). The changes were evaluated using a microscope. The results indicated that all acrylic resins, regardless of the cure cycle, showed increased linear dimension after 30 days of storage in water. The composition of the acrylic resin affected the results more than the cure cycles, and the conventional acrylic resin (Lucitone 550 and Clássico) cured by microwave activation presented similar results when compared with the resin specific for microwave activation.

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The aim of this study was to compare two methods of surface roughness analysis, perfilometry and spectrophotometry, applied to the surface of ionomeric materials (Chelon Fil, Vitremer and Dyract), submitted to different surface finishing treatments. For the perfilometric analysis, sixty specimens of each material were made and randomly separated into three experimental groups. The average surface roughness (Ra, mm) was measured on each specimen by a surface perfilometer (Mitutoyo Surftest 211). The spectrophotometric analysis consisted in quantifying the dye impregnated in the samples. The dyes used were 0.5% fuchsin and 0.5% erythrosin. Data were submitted to variance analysis (ANOVA) and t-Student test at a 0.05 significance level. There was no linear correlation between average roughness and superficial deposition of dye. Perfilometric analysis revealed that 12- and 30-bladed carbide burs caused the roughest surface of Chelon Fil, followed by Sof-Lex discs and mylar band. There were no significant differences between the specimens submitted to finishing and polishing with Sof-Lex discs and the control group (mylar band) for Vitremer, nevertheless, the highest Ra values were obtained when 12- and 30-bladed burs were used. For Dyract, there was no significant difference between the three treatments. The mean values of superficial deposition of dye for Chelon Fil, Vitremer and Dyract were: 1.7261, 1.4759, 1.3318, respectively. There were no significant differences between the restorative materials when different finishing and polishing systems were used.

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OBJECTIVE: To adapted the critical velocity (CV), RAST test and lactate minimum (LM) to evaluation of female basketball players. METHODS: Twelve well-trained female basketball players (19 ± 1yrs) were submitted to four intensities running (10 - 14 km/h) at shuttle exercise until exhaustion, applied on alternate days. The linear model 'velocity vs. 1/tlim' was adopted to determine the aerobic (CV) and anaerobic (CCA) parameters. The lactate minimum test consisted of two phases: 1) hiperlactatemia induction using the RAST test and 2) incremental test composed by five shuttle run (20-m) at 7, 8, 9, 10, and 12 km/h. Blood samples were collected at the end of each stage. RESULTS: The velocity (vLM) and blood lactate concentration at LM were obtained by two polynomial adjustments: lactate vs. intensity (LM1) and lactate vs. time (LM2). ANOVA one-way, Student t-test and Pearson correlation were used for statistical analysis. The CV was obtained at 10.3 ± 0.2 km/h and the CCA estimated at 73.0 ± 3.4 m. The RAST was capable to induce the hiperlactatemia and to determine the Pmax (3.6 ± 0.2 W/kg), Pmed (2.8 ± 0.1 W/kg), Pmin (2.3 ± 0.1 W/kg) and FI (30 ± 3%). The vLM1 and vLM2 were obtained, respectively, at 9.47 ±0.13 km/h and 9.8 ± 0.13 km/h, and CV was higher than vLM1. CONCLUSION: The results suggest that the non-invasive model can be used to determine the aerobic and anaerobic parameters. Furthermore, the LM test adapted to basketball using RAST and progressive phase was effective to evaluate female athletes considering the specificity of modality, with high success rates observed in polynomial adjustment 'lactate vs. time' (LM2).

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OBJECTIVE: The objective of this pilot study was to determine whether glugagon-like peptide 2 (GLP-2) secretion relates to insulin sensitivity (IS) in obese subjects. SUBJECTS AND METHODS: Twenty four obese subjects [body mass index (BMI) 40.0 ± 3.0 kg/m² (mean ± standard deviation)] were included, nine of which were male, age 43 ± 8 years. Twelve subjects had type 2 diabetes, all treated with oral anti-diabetic agents only. The subjects were submitted to standard meal tolerance test (MTT) for dosage of the curves: glucose, insulin, and GLP-2. Insulin sensitivity was measured by HOMA-IR, and OGIS was derived from the MTT. Spearman linear correlations and partial correlations were obtained. RESULTS: There was an inverse relationship between the GLP-2 secretion and IS: HOMA-IR correlated with GLP-2 AUC (R = 0.504; p = 0.012), and OGIS correlated with GLP-2 incremental AUC (R = -0.54; p = 0.054). The correlation persisted after controlling for BMI. CONCLUSION: We found an association of GLP-2 secretion and insulin resistance (IR). The understanding of the underlying mechanisms may provide future directions in the pharmacological manipulation of incretins, and in the treatment of obesity and related metabolic disorders.

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PURPOSE: To evaluate the knowledge glaucoma patients have about their disease and its treatment. METHODS: One hundred and eighty-three patients were interviewed at the Glaucoma Service of Wills Eye Hospital (Philadelphia, USA, Group 1) and 100 at the Glaucoma Service of University of Campinas (Campinas, Brazil, Group 2). An informal, relaxed atmosphere was created by the interviewer before asking a list of 18 open-ended questions. RESULTS: In Group 1, 44% of the 183 patients did not have an acceptable idea about what glaucoma is, 30% did not know the purpose of the medications they were taking, 47% were not aware of what was an average intraocular pressure, and 45% did not understand why visual fields were examined. In Group 2, 54% gave unsatisfactory answers to the question What is glaucoma?, 54% did not know the purpose of the medications they were taking, 80% were not aware of what was an average intraocular pressure, and 94% did not understand why visual fields were examined (p<0.001). Linear regression analysis demonstrated that level of education was positively correlated to knowledge about glaucoma in both groups (r=0.65, p=0.001). CONCLUSION: This study showed that patients' knowledge about glaucoma varies greatly, and that in an urban, American setting, around one third of the patients have minimal understanding, whereas in an urban setting in Brazil around two thirds of patients were lacking basic information about glaucoma. Innovative and effective methods are needed to correct this situation.

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PURPOSE: To determine the mean critical fusion frequency and the short-term fluctuation, to analyze the influence of age, gender, and the learning effect in healthy subjects undergoing flicker perimetry. METHODS: Study 1 - 95 healthy subjects underwent flicker perimetry once in one eye. Mean critical fusion frequency values were compared between genders, and the influence of age was evaluated using linear regression analysis. Study 2 - 20 healthy subjects underwent flicker perimetry 5 times in one eye. The first 3 sessions were separated by an interval of 1 to 30 days, whereas the last 3 sessions were performed within the same day. The first 3 sessions were used to investigate the presence of a learning effect, whereas the last 3 tests were used to calculate short-term fluctuation. RESULTS: Study 1 - Linear regression analysis demonstrated that mean global, foveal, central, and critical fusion frequency per quadrant significantly decreased with age (p<0.05).There were no statistically significant differences in mean critical fusion frequency values between males and females (p>0.05), with the exception of the central area and inferonasal quadrant (p=0.049 and p=0.011, respectively), where the values were lower in females. Study 2 - Mean global (p=0.014), central (p=0.008), and peripheral (p=0.03) critical fusion frequency were significantly lower in the first session compared to the second and third sessions. The mean global short-term fluctuation was 5.06±1.13 Hz, the mean interindividual and intraindividual variabilities were 11.2±2.8% and 6.4±1.5%, respectively. CONCLUSION: This study suggests that, in healthy subjects, critical fusion frequency decreases with age, that flicker perimetry is associated with a learning effect, and that a moderately high short-term fluctuation is expected.

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PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.