Espectroscopia de infravermelho na determinação da textura do solo

A aplicação de técnicas espectroscópicas que utilizam a radiação infravermelha (NIRS-Near Infrared Spectroscopy e DRIFTS-Diffuse Reflectance Fourier Transformed Spectroscopy) na análise inorgânica do solo tem sido proposta desde a década de 1970, mas até os dias atuais são raros os métodos implementados rotineiramente no Brasil. Isso deve-se à dificuldade em construir modelos de calibração, por meio de métodos estatísticos multivariados, utilizando-se amostras reais de solo, de constituição complexa, que varia geograficamente e de acordo com o manejo. Por isso, os objetivos deste trabalho foram construir modelos de calibração em NIRS e DRIFTS para a quantificação das frações de argila e areia, em amostras de solos de classes diferentes - Latossolo Vermelho (predominante), Nitossolo, Argissolo Vermelho e Neossolo Quartzarênico - e avaliar qual dessas duas técnicas é mais adequada para essa finalidade, assim como a interferência do agrupamento de amostras e da seleção de variáveis espectrais na qualidade desses modelos. Para isso, valores de referência obtidos pelo método do densímetro, método largamente utilizado nos laboratórios de análise de solo, foram correlacionados com valores de absorbância em NIRS e DRIFTS pela ferramenta estatística PLS (Partial Least Squares), obtendo-se altos coeficientes de determinação (R²), de 0,95, 0,90 e 0,91 para argila, silte e areia, respectivamente, na validação externa. Isso confirma a aplicabilidade das técnicas espectroscópicas na análise granulométrica do solo para fins agrícolas. O agrupamento das amostras segundo a localização e a seleção de variáveis espectrais pouco influenciou na qualidade dos modelos. A técnica espectroscópica mais indicada para essa finalidade foi a DRIFTS.

Techniques for Estimating Flood-Frequency Discharges for Streams in Iowa, HR-395A, 2001

A statewide study was conducted to develop regression equations for estimating flood-frequency discharges for ungaged stream sites in Iowa. Thirty-eight selected basin characteristics were quantified and flood-frequency analyses were computed for 291 streamflow-gaging stations in Iowa and adjacent States. A generalized-skew-coefficient analysis was conducted to determine whether generalized skew coefficients could be improved for Iowa. Station skew coefficients were computed for 239 gaging stations in Iowa and adjacent States, and an isoline map of generalized-skew-coefficient values was developed for Iowa using variogram modeling and kriging methods. The skew map provided the lowest mean square error for the generalized-skew- coefficient analysis and was used to revise generalized skew coefficients for flood-frequency analyses for gaging stations in Iowa. Regional regression analysis, using generalized least-squares regression and data from 241 gaging stations, was used to develop equations for three hydrologic regions defined for the State. The regression equations can be used to estimate flood discharges that have recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years for ungaged stream sites in Iowa. One-variable equations were developed for each of the three regions and multi-variable equations were developed for two of the regions. Two sets of equations are presented for two of the regions because one-variable equations are considered easy for users to apply and the predictive accuracies of multi-variable equations are greater. Standard error of prediction for the one-variable equations ranges from about 34 to 45 percent and for the multi-variable equations range from about 31 to 42 percent. A region-of-influence regression method was also investigated for estimating flood-frequency discharges for ungaged stream sites in Iowa. A comparison of regional and region-of-influence regression methods, based on ease of application and root mean square errors, determined the regional regression method to be the better estimation method for Iowa. Techniques for estimating flood-frequency discharges for streams in Iowa are presented for determining ( 1) regional regression estimates for ungaged sites on ungaged streams; (2) weighted estimates for gaged sites; and (3) weighted estimates for ungaged sites on gaged streams. The technique for determining regional regression estimates for ungaged sites on ungaged streams requires determining which of four possible examples applies to the location of the stream site and its basin. Illustrations for determining which example applies to an ungaged stream site and for applying both the one-variable and multi-variable regression equations are provided for the estimation techniques.

Polymorphisms in Toll-like receptor 9 influence the clinical course of HIV-1 infection.

BACKGROUND: The clinical course of HIV-1 infection is highly variable among individuals, at least in part as a result of genetic polymorphisms in the host. Toll-like receptors (TLRs) have a key role in innate immunity and mutations in the genes encoding these receptors have been associated with increased or decreased susceptibility to infections. OBJECTIVES: To determine whether single-nucleotide polymorphisms (SNPs) in TLR2-4 and TLR7-9 influenced the natural course of HIV-1 infection. METHODS: Twenty-eight SNPs in TLRs were analysed in HAART-naive HIV-positive patients from the Swiss HIV Cohort Study. The SNPs were detected using Sequenom technology. Haplotypes were inferred using an expectation-maximization algorithm. The CD4 T cell decline was calculated using a least-squares regression. Patients with a rapid CD4 cell decline, less than the 15th percentile, were defined as rapid progressors. The risk of rapid progression associated with SNPs was estimated using a logistic regression model. Other candidate risk factors included age, sex and risk groups (heterosexual, homosexual and intravenous drug use). RESULTS: Two SNPs in TLR9 (1635A/G and +1174G/A) in linkage disequilibrium were associated with the rapid progressor phenotype: for 1635A/G, odds ratio (OR), 3.9 [95% confidence interval (CI),1.7-9.2] for GA versus AA and OR, 4.7 (95% CI,1.9-12.0) for GG versus AA (P = 0.0008). CONCLUSION: Rapid progression of HIV-1 infection was associated with TLR9 polymorphisms. Because of its potential implications for intervention strategies and vaccine developments, additional epidemiological and experimental studies are needed to confirm this association.

Methods for Estimating Annual Exceedance-Probability Discharges for Streams in Iowa, Based on Data through Water Year 2010, TR-519, 2013

A statewide study was performed to develop regional regression equations for estimating selected annual exceedance- probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedanceprobability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized leastsquares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized leastsquares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. These regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.

A Continuous Span Aluminum Girder Concrete Deck Bridge - Part 2 of 2: Fatigue Tests of Aluminum Girders, Final Report, 1997

In 1957, the Iowa State Highway Commission, with financial assistance from the aluminum industry, constructed a 220-ft (67-m) long, four-span continuous, aluminum girder bridge to carry traffic on Clive Road (86th Street) over Interstate 80 near Des Moines, Iowa. The bridge had four, welded I-shape girders that were fabricated in pairs with welded diaphragms between an exterior and an interior girder. The interior diaphragms between the girder pairs were bolted to girder brackets. A composite, reinforced concrete deck served as the roadway surface. The bridge, which had performed successfully for about 35 years of service, was removed in the fall of 1993 to make way for an interchange at the same location. Prior to the bridge demolition, load tests were conducted to monitor girder and diaphragm bending strains and deflections in the northern end span. Fatigue testing of the aluminum girders that were removed from the end spans were conducted by applying constant-amplitude, cyclic loads. These tests established the fatigue strength of an existing, welded, flange-splice detail and added, welded, flange-cover plates and horizontal web plate attachment details. This part, Part 2, of the final report focuses on the fatigue tests of the aluminum girder sections that were removed from the bridge and on the analysis of the experimental data to establish the fatigue strength of full-size specimens. Seventeen fatigue fractures that were classified as Category E weld details developed in the seven girder test specimens. Linear regression analyses of the fatigue test results established both nominal and experimental stress-range versus load cycle relationships (SN curves) for the fatigue strength of fillet-welded connections. The nominal strength SN curve obtained by this research essentially matched the SN curve for Category E aluminum weldments given in the AASHTO LRFD specifications. All of the Category E fatigue fractures that developed in the girder test specimens satisfied the allowable SN relationship specified by the fatigue provisions of the Aluminum Association. The lower-bound strength line that was set at two standard deviations below the least squares regression line through the fatigue fracture data points related well with the Aluminum Association SN curve. The results from the experimental tests of this research have provided additional information regarding behavioral characteristics of full-size, aluminum members and have confirmed that aluminum has the strength properties needed for highway bridge girders.

Alternativas quimiométricas para a resolução de problemas analíticos clássicos: determinação espectrofotométrica de misturas de zircônio e háfnio

The determination of zirconium-hafnium mixtures is one of the most critical problem of the analytical chemistry, on account of the close similarity of their chemical properties. The spectrophotometric determination proposed by Yagodin et al. show not many practical applications due to the significant spectral interference on the 200-220 nm region. In this work we propound the use of a multivariate calibration method called partial least squares ( PLS ) for colorimetric determination of these mixtures. By using PLS and 16 calibration mixtures we obtained a model which permits determination of zirconium and hafnium with accuracy of about 1-2% and 10-20%, respectively. Using conventional univariate calibration the inaccuracy of the determination is about 10-25% for zirconium and above 57% for hafnium.

Estudo QSPR sobre os coeficientes de partição: descritores mecânico-quânticos e análise multivariada

Quantum chemistry and multivariate analysis were used to estimate the partition coefficients between n-octanol and water for a serie of 188 compounds, with the values of the q 2 until 0.86 for crossvalidation test. The quantum-mechanical descriptors are obtained with ab initio calculation, using the solvation effects of the Polarizable Continuum Method. Two different Hartree-Fock bases were used, and two different ways for simulating solvent cavity formation. The results for each of the cases were analised, and each methodology proposed is indicated for particular case.

Modelo de calibração da concentração de metilmetacrilato em solução aquosa utilizando espectroscopia de absorção no ultravioleta

Dilutions of methylmetacrylate ranging between 1 and 50 ppm were obtained from a stock solution of 1 ml of monomer in 100 ml of deionised water, and were analyzed by an absorption spectrophotometer in the UV-visible. Absorbance values were used to develop a calibration model based on the PLS, with the aim to determine new sample concentrations. The number of latent variables used was 6, with the standard errors of calibration and prediction found to be 0,048 ml/100 ml and 0,058 ml/100 ml. The calibration model was successfully used to calculate the concentration of monomer released in water, where complete dentures were kept for one hour after polymerization.

Determinação espectrofotométrica simultânea de paracetamol e ibuprofeno em formulações farmacêuticas usando calibração multivariada

A simple method was proposed for determination of paracetamol and ibuprofen in tablets, based on UV measurements and partial least squares. The procedure was performed at pH 10.5, in the concentration ranges 3.00-15.00 µg ml-1 (paracetamol) and 2.40-12.00 µg ml-1 (ibuprofen). The model was able to predict paracetamol and ibuprofen in synthetic mixtures with root mean squares errors of prediction of 0.12 and 0.17 µg ml-1, respectively. Figures of merit (sensitivity, limit of detection and precision) were also estimated. The results achieved for the determination of these drugs in pharmaceutical formulations were in agreement with label claims and verified by HPLC.

Advanced chemometric methods: Applicability on industrial data

Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

Determinação não destrutiva do nitrogênio total em plantas por espectroscopia de reflectância difusa no infravermelho próximo

Diffuse reflectance near-infrared (DR-NIR) spectroscopy associated with partial least squares (PLS) multivariate calibration is proposed for a direct, non-destructive, determination of total nitrogen in wheat leaves. The procedure was developed for an Analytical Instrumental Analysis course, carried out at the Institute of Chemistry of the State University of Campinas. The DR-NIR results are in good agreement with those obtained by the Kjeldhal standard procedure, with a relative error of less than ± 3% and the method may be used for teaching purposes as well as for routine analysis.

Determinação de sibutramina em formas farmacêuticas através de espectroscopia no infravermelho com refletância difusa e métodos de calibração multivariada

The goal of this work is the development and validation of an analytical method for fast quantification of sibutramine in pharmaceutical formulations, using diffuse reflectance infrared spectroscopy and partial least square regression. The multivariate model was elaborated from 22 mixtures containing sibutramine and excipients (lactose, microcrystalline cellulose, colloidal silicon dioxide and magnesium stearate) and using fragmented (750-1150/ 1350-1500/ 1850-1950/ 2600-2900 cm-1) and smoothing spectral data. Using 10 latent variables, excellent predictive capacity were observed in the calibration (n=20, RMSEC=0.004, R= 0.999) and external validation (n=5, RMSEC= 9.36, R=0.999) phases. In the analysis of synthetic mixtures the precision (SD=3,47%) was compatible with the rules of the Agencia Nacional de Vigilância Sanitária (ANVISA-Brazil). In the analysis of commercial drugs good agreement was observed between spectroscopic and chromatographic methods.

Caracterização espectroscópica multivariada do potencial antioxidante de vinhos

In this work the antioxidant capacity of red wine samples was characterized by conventional spectroscopic and chromatographic methodologies, regarding chemical parameters like color, total polyphenolic and resveratrol content, and antioxidant activity. Additionally, multivariate calibration models were developed to predict the antioxidant activity, using partial least square regression and the spectral data registered between 400 and 800 nm. Even when a close correlation between the evaluated parameters has been expected many inconsistencies were observed, probably on account of the low selectivity of the conventional methodologies. Models developed from mean-centered spectra and using 4 latent variables allowed high prevision capacity of the antioxidant activity, permitting relative errors lower than 3%.

Avaliação da eficiência das técnicas ESI-MS e ATR/FTIR na determinação de adulteração de BX com querosene e óleo residual

Direct infusion electrospray ionization mass spectrometry in the negative ion mode, ESI(-)-MS and Fourier transform infrared spectroscopy (FTIR) were used together with partial least squares (PLS) as a tool to determine B3 adulteration (B3 - mixture of 3% v/v of biodiesel in diesel) with kerosene and residual oil.

Avaliação do perfil de dissolução de medicamentos utilizando-se espectroscopia eletrônica multivariada

In this work the evaluation of the dissolution profile of captopril-hydrochlorothiazide and zidovudine-lamivudine associations were carried out by multivariate spectroscopic method. The models were developed by partial least square regression from 20 synthetic mixtures using mean-centered spectral data. The external validation was accomplished with 5 synthetic mixtures shown mean prevision error of about 1%. Good agreement was observed in the analyses of commercial drugs (content uniformity and dissolution profile), considering the results obtained by the standard chromatographic method, with prevision error lower than 10%.