| 1. |
- Artursson, Tom
(författare)
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Development of Preprocessing Methods for Multivariate Sensor Data
- 2002
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In this work various aspects of data preprocessing are discussed. Preprocessing of data from multivariate sensor data systems is often necessary to extract relevant information or remove disturbances. Depending on the sensor type different preprocessing techniques have to be used. A number of important problems face the user e.g. drifting sensor data which results in very short-lived calibration models, and complex models with a very high number of variables. A systematic approach to handle and analyse data is necessary. In this work different preprocessing techniques are elaborated to reduce these problems.Drift is a gradual change in any quantitative characteristic that is supposed to remain constant. Thus, a drifting chemical sensor does not give exactly the same response even if it is exposed to exactly the same environment for a long time. Drift is a common problem for all chemical sensors, and thus needs to be considered as soon as measurements are made for a long period of time. Drift reduction methods try to compensate for the changes in sensor performance using mathematical models and thus maintaining the identification capability of the chemical sensor. The problem with drifting sensor data and thereby short-lived calibration models is overcome using reference samples and smart algorithms utilizing the relation between the reference measurements and the measurements from the samples. This has been studied in two of the papers in this thesis. Two new approaches have been developed and tested using data from real measurements from the electronic nose and tongue.In industry and science more and more variables are used to describe the process under study which lead to complex models and calculations. In order to increase the interpretability of the measurements, decrease the calculation demand on the computer, and/or to reduce noise an alternative, more compact, representation of the measurement can be made which describes the important features of the measurement well but with a much smaller vector. This data reduction is the topic of three of the papers in this thesis. Two different methods have been used: A double exponential model has been developed to approximate electronic tongue data. The parameters from this model describe the signal and are used as inputs to multivariate models. Secondly, the more general approach wavelet compression with different strategies for selection of wavelet coefficients has also been studied for variable reduction of both electronic tongue data and X-ray powder diffraction data.
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| 2. |
- Artursson, Tom, et al.
(författare)
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Drift correction for gas sensors using multivariate methods
- 2000
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Ingår i: Journal of Chemometrics. - 0886-9383 .- 1099-128X. ; 14:5-6, s. 711-723
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Tidskriftsartikel (refereegranskat)abstract
- Drift is one of the most serious impairments afflicting gas sensors. It can be seen as a gradual change in the sensor response over a long period of time when the external conditions an constant. This paper presents a new simple drift counteraction method based on PCA and PLS. The basic idea is to remove the drift direction component from the measurements. The direction of the drift, p, is calculated from measurements for a reference gas. Projecting the sample gas measurements on this vector gives the score vector t. The drift component tp(T) can then he removed from the sample gas data, which we call component correction (CC). The method is tested on a data set based on a reduced factorial design with four gases and a concentration gradient of hydrogen. It is found that the method works efficiently for both cases. Copyright (C) 2000 John Wiley & Sons, Ltd.
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| 3. |
- Artursson, Tom, et al.
(författare)
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Study of Preprocessing Methods for the Determination of Crystalline Phases in Binary Mixtures of Drug Substances by X-ray Powder Diffraction and Multivariate Calibration
- 2000
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Ingår i: Applied Spectroscopy. - : SAGE Publications. - 0003-7028 .- 1943-3530. ; 54:8, s. 272A-301A
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, various preprocessing methods were tested on data generated by X-ray powder diffraction (XRPD) in order to enhance the partial least-squares (PLS) regression modeling performance. The preprocessing methods examined were 22 different discrete wavelet transforms, Fourier transform, Savitzky-Golay, orthogonal signal correction (OSC), and combinations of wavelet transform and OSC, and Fourier transform and OSC. Root mean square error of prediction (RMSEP) of an independent test set was used to measure the performance of the various preprocessing methods. The best PLS model was obtained with a wavelet transform (Symmlet 8), which at the same time compressed the data set by a factor of 9.5. With the use of wavelet and X-ray powder diffraction, concentrations of less than 10% of one crystal from could be detected in a binary mixture. The linear range was found to be in the range 10-70% of the crystalline form of phenacetin, although semiquantitative work could be carried out down to a level of approximately 2%. Furthermore, the wavelet-pretreated models were able to handle admixtures and deliberately added noise.
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| 4. |
- Artursson, Tom, et al.
(författare)
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Variable reduction on electronic tongue data
- 2002
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Ingår i: Analytica Chimica Acta. - 0003-2670 .- 1873-4324. ; 452:2, s. 255-264
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Tidskriftsartikel (refereegranskat)abstract
- Reduction of the number of variables in data from a so-called electronic tongue contributes to simpler model calculations and less storage requirements. In this study, we have developed a model for this purpose. This model describes the response from the electrodes in the electronic tongue with two exponential functions plus a constant term, i(t) = k + kf e-ta + kc e-tß, where t is the time. From the model, five parameters which describe the signal are extracted. These parameters can be used as inputs instead of the original signal to any multivariate algorithm. The results show that the variables obtained are at least as good as the original data to separate between different classes, even though the number of parameters has been reduced between 80 and 199 times. © 2002 Elsevier Science B.V. All rights reserved.
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| 5. |
- Artursson, Tom, et al.
(författare)
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Wavelet transform of electronic tongue data
- 2002
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Ingår i: Sensors and actuators. B, Chemical. - 0925-4005 .- 1873-3077. ; 87:2, s. 379-391
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Tidskriftsartikel (refereegranskat)abstract
- A measurement in a multi-sensor system is characterized by a large array of numbers (a vector or a matrix), sometimes several thousands. In order to increase the interpretability of the measurements, decrease the calculation demand on the computer, and/or to reduce noise, an alternative, more compact, representation of the measurement can be made which describes the important features of the measurement well but with a much smaller vector. The purpose of this paper is to show that for a particular wet-chemical sensor system (pulsed voltammetry, also called an electronic tongue) the data compression can be made using a wavelet transform together with different wavelet selection algorithms for different purposes. The resulting compressed data can also be used for easy interpretation of the measurements and to give hints for improvements or simplifications of the measurement procedure. Two different criteria for selection of wavelet coefficients have been used, variance and discriminance, in two different cases. The variance criterion was used when variations of any kind in the raw data was studied during monitoring of water in drinking water production plant. In this case, the number of variables was reduced with a factor of 18, without loosing relevant information. In the other case, the focus was to separate different microorganisms, therefore, the discriminance selection criterion was successfully used. The number of variables was reduced by a factor of 144, this smaller data set captured the important information for separating the microorganisms, which led to better classification of the test set. © 2002 Published by Elsevier Science B.V.
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| 6. |
- de Waal, Tom, et al.
(författare)
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Expression of intestinal drug transporter proteins and metabolic enzymes in neonatal and pediatric patients
- 2024
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Ingår i: International Journal of Pharmaceutics. - : Elsevier. - 0378-5173 .- 1873-3476. ; 654
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Tidskriftsartikel (refereegranskat)abstract
- The development of pediatric oral drugs is hampered by a lack of predictive simulation tools. These tools, in turn, require data on the physiological variables that influence oral drug absorption, including the expression of drug transporter proteins (DTPs) and drug-metabolizing enzymes (DMEs) in the intestinal tract. The expression of hepatic DTPs and DMEs shows age-related changes, but there are few data on protein levels in the intestine of children. In this study, tissue was collected from different regions of the small and large intestine from neonates (i.e., surgically removed tissue) and from pediatric patients (i.e., gastroscopic duodenal biopsies). The protein expression of clinically relevant DTPs and DMEs was determined using a targeted mass spectrometry approach. The regional distribution of DTPs and DMEs was similar to adults. Most DTPs, with the exception of MRP3, MCT1, and OCT3, and all DMEs showed the highest protein expression in the proximal small intestine. Several proteins (i.e., P-gp, ASBT, CYP3A4, CYP3A5, CYP2C9, CYP2C19, and UGT1A1) showed an increase with age. Such increase appeared to be even more pronounced for DMEs. This exploratory study highlights the developmental changes in DTPs and DMEs in the intestinal tract of the pediatric population. Additional evaluation of protein function in this population would elucidate the implications of the presented changes in protein expression on absorption of orally administered drugs in neonates and pediatric patients.
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| 7. |
- de Waal, Tom, et al.
(författare)
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The impact of inflammation on the expression of drug transporters and metabolic enzymes in colonic tissue from ulcerative colitis patients
- 2022
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Ingår i: International Journal of Pharmaceutics. - : Elsevier. - 0378-5173 .- 1873-3476. ; 628
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Tidskriftsartikel (refereegranskat)abstract
- The intestinal tract forms an important barrier against xenobiotics while allowing nutrients to pass. In ulcerative colitis (UC), a chronic inflammatory bowel disease, this barrier function is impaired leading to an abnormal immune response and inflammation of the colonic mucosa. Transporter proteins and metabolic enzymes are an integral part of the protective barrier in the gut and play an important role in the disposition of nutrients, toxins and oral drugs. In this study, the protein expression of 13 transporters and 13 enzymes was determined in the sigmoid and rectum of UC patients in endoscopic remission and during active inflammation. In inflamed con-ditions (endoscopic Mayo sub-score 1, 2 or 3), a significant decrease (q < 0.05) was observed in the median expression of the transporters P-gp (0.046 vs 0.529 fmol/mu g protein), MRP4 (0.003 vs 0.023 fmol/mu g protein) and MCT1 (0.287 vs 1.090 fmol/mu g protein), and the enzymes CYP3A5 (0.031 vs 0.046 fmol/mu g protein) and UGT2B7 (0.083 vs 0.176 fmol/mu g protein). Moreover, during severe inflammation, the decrease was even more pro-nounced. Expression levels of other proteins were not altered during inflammation (e.g., OATP2B1, CYP3A4, CYP2B6 and UGT2B15). The results suggest a decreased transport and metabolism of xenobiotics in the colon of UC patients during active inflammation potentially altering local drug concentrations and thus treatment outcome.
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| 8. |
- Unéus, Lars, 1971-, et al.
(författare)
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Evaluation of on-line flue gas measurements by MISiCFET and metal-oxide sensors in boilers
- 2005
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Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 5:1, s. 75-81
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Tidskriftsartikel (refereegranskat)abstract
- Metal insulator silicon carbide field-effect transistor sensors, metal-oxide sensors, and a linear Lambda sensor in an electronic nose was used to measure on-line in hot flue gases from a boiler. Flue gas from a 100-MW pellets-fuelled boiler has been used to feed the experimental setup. Several reference instruments, which measure the flue gases in parallel to the sensor array, are connected to the electronic nose. Data was collected during six weeks and then evaluated. Using principal component analysis as the data evaluation method, different operating modes for the boiler have been identified in the data set. The different modes could be described in terms of high or low O 2 and CO concentration. Furthermore, we have shown that it seems possible to use a sensor array to determine the operating mode of the boiler and, by partial least-squares models, measure the CO concentration when the boiler operates in its optimum mode.
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