Determinação de parâmetros (sólidos solúveis, pH e acidez titulável) em ameixas intactas usando espectroscopia no infravermelho próximo e seleção de comprimento de onda

The aim of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) as a rapid and non-destructive method to determine the soluble solid content (SSC), pH and titratable acidity of intact plums. Samples of plum with a total solids content ranging from 5.7 to 15%, pH from 2.72 to 3.84 and titratable acidity from 0.88 a 3.6% were collected from supermarkets in Natal-Brazil, and NIR spectra were acquired in the 714 2500 nm range. A comparison of several multivariate calibration techniques with respect to several pre-processing data and variable selection algorithms, such as interval Partial Least Squares (iPLS), genetic algorithm (GA), successive projections algorithm (SPA) and ordered predictors selection (OPS), was performed. Validation models for SSC, pH and titratable acidity had a coefficient of correlation (R) of 0.95 0.90 and 0.80, as well as a root mean square error of prediction (RMSEP) of 0.45ºBrix, 0.07 and 0.40%, respectively. From these results, it can be concluded that NIR spectroscopy can be used as a non-destructive alternative for measuring the SSC, pH and titratable acidity in plums

Espectroscopia no infravermelho próximo e métodos de calibração multivariada aplicados à determinação simultânea de parâmetros bioquímicos em plasma sanguíneo

In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma

Construção de modelos multivariados para determinação de lipídios totais e unidade em leite em pó comercial utilizando espectroscopia no infravermelho próximo

In this work calibration models were constructed to determine the content of total lipids and moisture in powdered milk samples. For this, used the near-infrared spectroscopy by diffuse reflectance, combined with multivariate calibration. Initially, the spectral data were submitted to correction of multiplicative light scattering (MSC) and Savitzsky-Golay smoothing. Then, the samples were divided into subgroups by application of hierarchical clustering analysis of the classes (HCA) and Ward Linkage criterion. Thus, it became possible to build regression models by partial least squares (PLS) that allowed the calibration and prediction of the content total lipid and moisture, based on the values obtained by the reference methods of Soxhlet and 105 ° C, respectively . Therefore, conclude that the NIR had a good performance for the quantification of samples of powdered milk, mainly by minimizing the analysis time, not destruction of the samples and not waste. Prediction models for determination of total lipids correlated (R) of 0.9955, RMSEP of 0.8952, therefore the average error between the Soxhlet and NIR was ± 0.70%, while the model prediction to content moisture correlated (R) of 0.9184, RMSEP, 0.3778 and error of ± 0.76%

Determinação do teor de diclofenaco sódico em comprimidos por espectroscopia no infravermelho próximo NIR com calibração multivariada PLS

This work is combined with the potential of the technique of near infrared spectroscopy - NIR and chemometrics order to determine the content of diclofenac tablets, without destruction of the sample, to which was used as the reference method, ultraviolet spectroscopy, which is one of the official methods. In the construction of multivariate calibration models has been studied several types of pre-processing of NIR spectral data, such as scatter correction, first derivative. The regression method used in the construction of calibration models is the PLS (partial least squares) using NIR spectroscopic data of a set of 90 tablets were divided into two sets (calibration and prediction). 54 were used in the calibration samples and the prediction was used 36, since the calibration method used was crossvalidation method (full cross-validation) that eliminates the need for a validation set. The evaluation of the models was done by observing the values of correlation coefficient R 2 and RMSEC mean square error (calibration error) and RMSEP (forecast error). As the forecast values estimated for the remaining 36 samples, which the results were consistent with the values obtained by UV spectroscopy

Monitoramento em tempo real de processos fermentativos por espectroscopia no infravermelho próximo (NIRS)

A chemical process optimization and control is strongly correlated with the quantity of information can be obtained from the system. In biotechnological processes, where the transforming agent is a cell, many variables can interfere in the process, leading to changes in the microorganism metabolism and affecting the quantity and quality of final product. Therefore, the continuously monitoring of the variables that interfere in the bioprocess, is crucial to be able to act on certain variables of the system, keeping it under desirable operational conditions and control. In general, during a fermentation process, the analysis of important parameters such as substrate, product and cells concentration, is done off-line, requiring sampling, pretreatment and analytical procedures. Therefore, this steps require a significant run time and the use of high purity chemical reagents to be done. In order to implement a real time monitoring system for a benchtop bioreactor, these study was conducted in two steps: (i) The development of a software that presents a communication interface between bioreactor and computer based on data acquisition and process variables data recording, that are pH, temperature, dissolved oxygen, level, foam level, agitation frequency and the input setpoints of the operational parameters of the bioreactor control unit; (ii) The development of an analytical method using near-infrared spectroscopy (NIRS) in order to enable substrate, products and cells concentration monitoring during a fermentation process for ethanol production using the yeast Saccharomyces cerevisiae. Three fermentation runs were conducted (F1, F2 and F3) that were monitored by NIRS and subsequent sampling for analytical characterization. The data obtained were used for calibration and validation, where pre-treatments combined or not with smoothing filters were applied to spectrum data. The most satisfactory results were obtained when the calibration models were constructed from real samples of culture medium removed from the fermentation assays F1, F2 and F3, showing that the analytical method based on NIRS can be used as a fast and effective method to quantify cells, substrate and products concentration what enables the implementation of insitu real time monitoring of fermentation processes

Predição da maturação puberal de indivíduos do sexo masculino a partir de variáveis antropométricas

The methods of analysis of the selection system sports talent sometimes do not consider the biological age of the athletes, since that the assessment of maturational moment have several limitations The aim of this work is to develop a predictive equation of pubertal assessment in male subjects, based on anthropometric measurements. We evaluated 206 young boys, aged between eight and 18 years, and studing in public and private schools in Natal, Brazil. The sample selection was done randomly, being used the anthropometric measurements and pubertal maturation evaluation according to the Tanner stages. Statistical analysis followed the presentation of central tendency measures and their derivatives. The inferential analysis was performed according to the ANOVA test, multivariate discriminant analysis and weighted Kappa. The advancement of pubertal stages was accompanied by significant changes in anthropometric variables, demonstrating the relationship presented in both. For this purpose, discriminant analysis selected eight variables with the highest prediction of pubertal maturation, and created an equation with a significance level of 75%. and concordance level of 0.840, considered as excellent. This shows that the prediction of pubertal maturation from anthropometric variables presented as a valid method, being used as a practical tool in sports talents selection

Prevalência e fatores associados à alteração vocal em idosos institucionalizados com capacidade cognitiva preservada

Voice disorders (VD) in the elderly can interfere negatively in communication, emotional well-being and quality of life, conditions that correspond to greater exposure to illness and social isolation bringing consequent economic impact for the health system. It is assumed that institutionalized confinement, weakness and morbidity associated to nursing home (NH) contribute to transform VD an especially prevalent condition in institutionalized elderly, including those without cognitive impairment. Thus, the aim of this study was to determine the prevalence and associated factors of VD in NH elderly residents without cognitive impairment. There is no epidemiological diagnostic instruments of VD for elderly populations, so the first step of this study was dedicated to prepare and analyze the psychometric properties of a short, inexpensive and easy to use questionnaire named Screening for Voice Disorders in Older Adults (Rastreamento de Alterações Vocais em Idosos—RAVI). The methodological procedures of this step followed the guidelines of the Standards for Educational and Psychological Testing and contemplated validity evidence based on test content, based on response processes, based on internal structure and based on relations with other variables, as well as reliability analysis and clinical consistency. The result of the validation process showed that the RAVI final score generate valid and reliable interpretations for the epidemiological diagnosis of VD in the elderly, which endorsed the use of the questionnaire in the second stage of the study, performed in ten NH located in the city of Natal, Rio Grande do Norte. At this stage, data from socioeconomic and demographic variables, lifestyle, general health conditions and characterization of the institution were collected. It was performed a bivariate analysis and it was calculated the prevalence ratio as a magnitude association measure, with a confidence interval of 95%. The variables with p-value less than 0.20 were included in the multiple logistic regression model that followed the Forward selection method. The odds ratio found in the multivariate model was converted into prevalence ratio and the level of significance was 5%. The sample consisted of 117 subjects with predominance of females and average of 79.68 (± 7.92) years old. The prevalence of VD was 39.3% (95% CI: 30.4-48.1%). The multivariate model showed statistically significant association between VD and depressive symptoms, smoking for a year or more and selfreported hearing loss. In conclusion, VD is a prevalent health condition in NH elderly residents without cognitive impairment and is associated with factors involving psychosocial, lifestyle and communicative disability that require attention of managers and professionals involved with NH environment. Strategies to encourage communication and social integration, actions to combat smoking and minimizing the effects of hearing loss could stimulate the physical well-being, emotional and mental health of institutionalized elderly population, contributing to the vocal and communicative maintenance, a more effective social inclusion and better overall health condition.

Antecedentes do engajamento em boca a boca eletrônico positivo entre turistas

This study examined the influence of the tourism destination image as well as satisfaction and motivation in the intention of engaging in a positive electronic word of mouth (eWOM) by tourists through Facebook. In addition, it was also specifically expected to assess the sociodemographic profile and frequency of eWOM publications from those who answered the questions; it also assessed the adequacy of the manifested variables for composition of the following dimensions: Quality, Satisfaction, Image, Motivations and Positive Electronic Word of Mouth (eWOM). And finally, it analyzed a relational model where there are relationships between Quality, Satisfaction, Image and Motivations in the explanation of engagement in the Positive Electronic Word of Mouth (eWOM). With this aim it was conducted a study, based on a hypothetical-deductive logic, which was descriptive in relation to its goals. The analytical approach was quantitative (a survey). The sampling procedure was non-probabilistic, by the convenience method of sampling specifically, having the choice of the subject been made through the probabilistic systematic method, and using time as a factor of systematization in an attempt of making randomly the selection of the interviewed people. The study sample consisted of 355 tourists. The used instrument to collect information was the structured questionnaire whose answers were collected in the main points of entry, exit and rides of tourists on the Pipa’s Beach/RN. Data analysis was carried out using descriptive and multivariate statistics, mainly exploratory and confirmatory factor analysis and structural equation modeling. Among the main results, it was possible to confirm that the Motivations, Satisfaction and Image strongly affect the intention of engaging in positive electronic word of mouth (eWOM). Emphasis is given to the motivations, as they demonstrate bigger impact in explaining the dependent variable; they are followed by the satisfaction and the image. The latter, however, is inversely proportional. Among the motivations, the one with the highest percentage of variance were the social benefits sought by tourists; and presenting the same percentage appears the desire to help other tourists and to vent Positive Emotions. The manifested variables demonstrate to be fully acceptable to be taken as reflexes of their respective factors.