942 resultados para Quality analysis
Resumo:
The present paper constitutes a synthesis of the results gotten during the five campaigns of air quality measurement in the years of 2003 and 2004 carried out in the Portuguese city of Viana do Castelo to characterise the reference situation and to accompany the Polis Programme, an urban re-qualification and environmental valorisation plan. The main objective of the monitoring programme consisted of the evaluation of atmospheric pollutants whose levels were susceptible of enhancement in the course of the urbanistic public works. The presented results refer to measurements performed in two distinct places of this city, comprising various consecutive days of acquisition that include, at least, one day of weekend.
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We report the use of an optical fiber sensor to measure the soybean oil concentration in samples obtained from the mixture of pure biodiesel and commercial soybean oil. The operation of the device is based on the long-period grating sensitivity to the surrounding medium refractive index, which leads to measurable modifications in the grating transmission spectrum. The proposed analysis method results in errors in the oil concentration of 0.4% and 2.6% for pure biodiesel and commercial soybean oil, respectively. Techniques of total glycerol, dynamic viscosity, density, and hydrogen nuclear magnetic resonance spectroscopy were also employed to validate the proposed method.
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The analysis of efficiency and productivity in banking has received a great deal of attention for almost three decades now. However, most of the literature to date has not explicitly accounted for risk when measuring efficiency. We propose an analysis of profit efficiency taking into account how the inclusion of a variety of bank risk measures might bias efficiency scores. Our measures of risk are partly inspired by the literature on earnings management and earnings quality, keeping in mind that loan loss provisions, as a generally accepted proxy for risk, can be adjusted to manage earnings and regulatory capital. We also consider some variants of traditional models of profit efficiency where different regimes are stipulated so that financial institutions can be evaluated in different dimensions—i.e., prices, quantities, or prices and quantities simultaneously. We perform this analysis on the Spanish banking industry, whose institutions have been deeply affected by the current international financial crisis, and where re-regulation is taking place. Our results can be explored in multiple dimensions but, in general, they indicate that the impact of earnings management on profit efficiency is of less magnitude than what might a priori be expected, and that on the whole, savings banks have performed less well than commercial banks. However, savings banks are adapting to the new regulatory scenario and rapidly catching up with commercial banks, especially in some dimensions of performance.
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The uncertainty of any analytical determination depends on analysis and sampling. Uncertainty arising from sampling is usually not controlled and methods for its evaluation are still little known. Pierre Gy’s sampling theory is currently the most complete theory about samplingwhich also takes the design of the sampling equipment into account. Guides dealing with the practical issues of sampling also exist, published by international organizations such as EURACHEM, IUPAC (International Union of Pure and Applied Chemistry) and ISO (International Organization for Standardization). In this work Gy’s sampling theory was applied to several cases, including the analysis of chromite concentration estimated on SEM (Scanning Electron Microscope) images and estimation of the total uncertainty of a drug dissolution procedure. The results clearly show that Gy’s sampling theory can be utilized in both of the above-mentioned cases and that the uncertainties achieved are reliable. Variographic experiments introduced in Gy’s sampling theory are beneficially applied in analyzing the uncertainty of auto-correlated data sets such as industrial process data and environmental discharges. The periodic behaviour of these kinds of processes can be observed by variographic analysis as well as with fast Fourier transformation and auto-correlation functions. With variographic analysis, the uncertainties are estimated as a function of the sampling interval. This is advantageous when environmental data or process data are analyzed as it can be easily estimated how the sampling interval is affecting the overall uncertainty. If the sampling frequency is too high, unnecessary resources will be used. On the other hand, if a frequency is too low, the uncertainty of the determination may be unacceptably high. Variographic methods can also be utilized to estimate the uncertainty of spectral data produced by modern instruments. Since spectral data are multivariate, methods such as Principal Component Analysis (PCA) are needed when the data are analyzed. Optimization of a sampling plan increases the reliability of the analytical process which might at the end have beneficial effects on the economics of chemical analysis,
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The ongoing development of the digital media has brought a new set of challenges with it. As images containing more than three wavelength bands, often called spectral images, are becoming a more integral part of everyday life, problems in the quality of the RGB reproduction from the spectral images have turned into an important area of research. The notion of image quality is often thought to comprise two distinctive areas – image quality itself and image fidelity, both dealing with similar questions, image quality being the degree of excellence of the image, and image fidelity the measure of the match of the image under study to the original. In this thesis, both image fidelity and image quality are considered, with an emphasis on the influence of color and spectral image features on both. There are very few works dedicated to the quality and fidelity of spectral images. Several novel image fidelity measures were developed in this study, which include kernel similarity measures and 3D-SSIM (structural similarity index). The kernel measures incorporate the polynomial, Gaussian radial basis function (RBF) and sigmoid kernels. The 3D-SSIM is an extension of a traditional gray-scale SSIM measure developed to incorporate spectral data. The novel image quality model presented in this study is based on the assumption that the statistical parameters of the spectra of an image influence the overall appearance. The spectral image quality model comprises three parameters of quality: colorfulness, vividness and naturalness. The quality prediction is done by modeling the preference function expressed in JNDs (just noticeable difference). Both image fidelity measures and the image quality model have proven to be effective in the respective experiments.
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A research about the quality of life of the older persons of a municipality starting from the analysis of the perceptions, evaluations and expectations related to concrete spheres of their lives (familiar characteristics, housing, health, nearby environment, activities, needs and dependencies and persons helping them to satisfy needs) is presented. Answers to 1988 questionnaires obtained from two representative samples of older per - sons living in private homes in the city have been analysed: persons over 65 years old and a specific one composed by a sub-sample of the general one, with persons over 75 years living alone. Data shaping contextual indicators related to housing have been analysed. The auto - nomy to drive and the evaluation of on’s health seem to be positive indicators to take in account while sutying quality of life at these ages. Sentinel indicators of the physical and relational conditions in the family and indicators of dependency are analysed as well. The evaluations of the older persons about their own life conditions are also analysed through psychosocial indicators connected to housing, nearby environmenent, their activities andincomes. The results obtained are applicable in order to improve the decision making process in social intervention programmes developed in the field of ageing aiming to take into account their perspectives
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A dissolution test for in vitro evaluation of tablet dosage forms containing 10 mg of rupatadine was developed and validated by RP-LC. A discriminatory dissolution method was established using apparatus paddle at a stirring rate of 50 rpm with 900 mL of deaerated 0.01 M hydrochloric acid. The proposed method was validated yielding acceptable results for the parameters evaluated, and was applied for the quality control analysis of rupatadine tablets, and to evaluate the formulation during an accelerated stability study. Moreover, quantitative analyses were also performed, to compare the applicability of the RP-LC and the LC-MS/MS methods.
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Raw measurement data does not always immediately convey useful information, but applying mathematical statistical analysis tools into measurement data can improve the situation. Data analysis can offer benefits like acquiring meaningful insight from the dataset, basing critical decisions on the findings, and ruling out human bias through proper statistical treatment. In this thesis we analyze data from an industrial mineral processing plant with the aim of studying the possibility of forecasting the quality of the final product, given by one variable, with a model based on the other variables. For the study mathematical tools like Qlucore Omics Explorer (QOE) and Sparse Bayesian regression (SB) are used. Later on, linear regression is used to build a model based on a subset of variables that seem to have most significant weights in the SB model. The results obtained from QOE show that the variable representing the desired final product does not correlate with other variables. For SB and linear regression, the results show that both SB and linear regression models built on 1-day averaged data seriously underestimate the variance of true data, whereas the two models built on 1-month averaged data are reliable and able to explain a larger proportion of variability in the available data, making them suitable for prediction purposes. However, it is concluded that no single model can fit well the whole available dataset and therefore, it is proposed for future work to make piecewise non linear regression models if the same available dataset is used, or the plant to provide another dataset that should be collected in a more systematic fashion than the present data for further analysis.
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Two analytical methods were validated for determination of trichlorophenols, tetrachlorophenols and pentachlorophenol in drinking water. Limits of quantification were at least ten times lower than maximum permissible levels set by the Brazilian legislation, which are 200 ng mL-1 for 2,4,6-trichlorophenol and 9 ng mL-1 for pentachlorophenol. Chlorophenol levels were determined in tap water collected in the Municipality of Rio de Janeiro. 2,4,6-Trichlorophenol residues were detected in 36% of the samples, varying from 0.008 to 0.238 ng mL-1. All other analytes were below the limit of quantification. The validated methods showed to be suitable for application in routine quality control.
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Prior to obtain a standardized dried extract from V. ferruginea, lupeol was first time isolated from leaves and used as chemical maker. An analytical method using HPLC-PDA for lupeol determination in V. ferruginea intermediate products was developed using a C8 reverse-phase column, acetonitrile-acetic acid (99.99:0.01, v/v) as mobile phase at 0.8 mL min-1, oven temperature at 23-25 ºC, sample injection volume at 30 µL and detection at 210 nm. The method presented linearity from 10 to 160 µg mL-1, accuracy, precision, robustness and suitable sensitivity proving to be a useful tool to the obtainment process of lupeol standardized dried extracts of V. ferruginea.
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This work shows the application of ¹H NMR spectroscopy and chemometrics for quality control of grape juice. A wide range of quality assurance parameters were assessed by single ¹H NMR experiments acquired directly from juice. The investigation revealed that conditions and time of storage should be revised and indicated on all labels. The sterilization process of homemade grape juices was efficient, making it possible to store them for long periods without additives. Furthermore, chemometric analysis classified the best commercial grape juices to be similar to homemade grape juices, indicating that this approach can be used to determine the authenticity after adulteration.
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In general, laboratory activities are costly in terms of time, space, and money. As such, the ability to provide realistically simulated laboratory data that enables students to practice data analysis techniques as a complementary activity would be expected to reduce these costs while opening up very interesting possibilities. In the present work, a novel methodology is presented for design of analytical chemistry instrumental analysis exercises that can be automatically personalized for each student and the results evaluated immediately. The proposed system provides each student with a different set of experimental data generated randomly while satisfying a set of constraints, rather than using data obtained from actual laboratory work. This allows the instructor to provide students with a set of practical problems to complement their regular laboratory work along with the corresponding feedback provided by the system's automatic evaluation process. To this end, the Goodle Grading Management System (GMS), an innovative web-based educational tool for automating the collection and assessment of practical exercises for engineering and scientific courses, was developed. The proposed methodology takes full advantage of the Goodle GMS fusion code architecture. The design of a particular exercise is provided ad hoc by the instructor and requires basic Matlab knowledge. The system has been employed with satisfactory results in several university courses. To demonstrate the automatic evaluation process, three exercises are presented in detail. The first exercise involves a linear regression analysis of data and the calculation of the quality parameters of an instrumental analysis method. The second and third exercises address two different comparison tests, a comparison test of the mean and a t-paired test.
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The application of automated correlation optimized warping (ACOW) to the correction of retention time shift in the chromatographic fingerprints of Radix Puerariae thomsonii (RPT) was investigated. Twenty-seven samples were extracted from 9 batches of RPT products. The fingerprints of the 27 samples were established by the HPLC method. Because there is a retention time shift in the established fingerprints, the quality of these samples cannot be correctly evaluated by using similarity estimation and principal component analysis (PCA). Thus, the ACOW method was used to align these fingerprints. In the ACOW procedure, the warping parameters, which have a significant influence on the alignment result, were optimized by an automated algorithm. After correcting the retention time shift, the quality of these RPT samples was correctly evaluated by similarity estimation and PCA. It is demonstrated that ACOW is a practical method for aligning the chromatographic fingerprints of RPT. The combination of ACOW, similarity estimation, and PCA is shown to be a promising method for evaluating the quality of Traditional Chinese Medicine.
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This paper reports on the identification of volatile and semi-volatile compounds and a comparison of the chromatographic profiles obtained by Headspace Solid-Phase Microextraction/Gas Chromatography with Mass Spectrometry detection (HS-SPME-GC-MS) of dried leaves of Mikania glomerata Sprengel (Asteraceae), also known as 'guaco.' Three different types of commercial SPME fibers were tested: polydimethylsiloxane (PDMS), polydimethylsiloxane/divinylbenzene (PDMS/DVB) and polyacrylate (PA). Fifty-nine compounds were fully identified by HS-SPME-HRGC-MS, including coumarin, a marker for the quality control of guaco-based phytomedicines; most of the other identified compounds were mono- and sesquiterpenes. PA fibers performed better in the analysis of coumarin, while PDMS-DVB proved to be the best choice for a general and non-selective analysis of volatile and semi-volatile guaco-based compounds. The SPME method is faster and requires a smaller sample than conventional hydrodistillation of essential oils, providing a general overview of the volatile and semi-volatile compounds of M. glomerata.
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Flame atomic absorption spectrometry (FAAS) and inductively coupled plasma optical emission spectrometry (ICP OES) are widely used in academic institutions and laboratories for quality control to analyze inorganic elements in samples. However, these techniques have been observed to underperform in sample nebulization processes. Most of the samples processed through nebulization system are discarded, producing large volumes of waste. This study reports the treatment and reuse of the waste produced from ICP OES technique in a laboratory of analytical research at the Universidade Federal do Ceará, Brazil. The treatment of the waste was performed by the precipitation of elements using (NH4)2CO3. Subsequently, the supernatant solution can be discarded in accordance with CONAMA 430/2011. The precipitate produced from the treatment of residues can be reused as a potential sample in undergraduate qualitative analytical chemistry lab classes, providing students the opportunity to test a real sample.