Jens Michael Carstensen

Aligning of single and multiple wavelength chromatographic profiles for chemometric data analysis using correlation optimised warping

The use of chemometric data processing is becoming an important part of modern chromatography. Most chemometric analyses are performed on reduced data sets using areas of selected peaks detected in the chromatograms, which means a loss of data and introduces the problem of extracting peak data from the chromatographic profiles. These disadvantages can be overcome by using the entire chromatographic data matrix in chemometric analyses, but it is necessary to align the chromatograms, as small unavoidable differences in experimental conditions causes minor changes and drift. Previous aligning methods either fail to utilise the entire data matrix or rely on peak detection, thus having the same limitations as the commonly used chemometric procedures. The method presented uses the entire chromatographic data matrices and does not require any preprocessing e.g., peak detection. It relies on piecewise linear correlation optimised warping (COW) using two input parameters which can be estimated from the observed peak width. COW is demonstrated on constructed single trace chromatograms and on single and multiple wavelength chromatograms obtained from HPLC diode detection analyses of fungal extracts1.

Robust factorization

Factorization algorithms for recovering structure and motion from an image stream have many advantages, but they usually require a set of well-tracked features. Such a set is in generally not available in practical applications. There is thus a need for making factorization algorithms deal effectively with errors in the tracked features. We propose a new and computationally efficient algorithm for applying an arbitrary error function in the factorization scheme. This algorithm enables the use of robust statistical techniques and arbitrary noise models for the individual features. These techniques and models enable the factorization scheme to deal effectively with mismatched features, missing features, and noise on the individual features. The proposed approach further includes a new method for Euclidean reconstruction that significantly improves convergence of the factorization algorithms. The proposed algorithm has been implemented as a modification of the Christy-Horaud factorization scheme, which yields a perspective reconstruction. Based on this implementation, a considerable increase in error tolerance is demonstrated on real and synthetic data. The proposed scheme can, however, be applied to most other factorization algorithms.

Three‐dimensional surface motion maps estimated from combined interferometric synthetic aperture radar and GPS data

[1] We provide a technique to efficiently produce high-resolution three-dimensional surface motion maps by combining information about the motion of the Earth’s surface from interferometric observations of synthetic aperture radar images and repeated Global Positioning System (GPS) geodetic measurements. Unwrapped interferograms, showing pixel-wise change in range from ground to satellite, and sparse values of threedimensional movements are required as input. The problem of finding the full threedimensional motion field is separated into two two-dimensional problems. Initially, the vertical component of the deformation field and its horizontal component in the look direction of the satellite are found. Later, the look direction component is resolved into north and east components. Initial values for the motion fields are assigned to each pixel of interferograms from interpolation of available GPS observations. These values are then updated and optimized by comparison with the interferograms and the GPS observations. An additional constraint is an assumption of a smoothly varying motion field. Markov random field-based regularization and simulated annealing algorithm are used for the optimization. The technique is applied to create surface motion maps for the Reykjanes Peninsula, SW Iceland. INDEX TERMS: 0933 Exploration Geophysics: Remote sensing; 0910 Exploration Geophysics: Data processing; 1206 Geodesy and Gravity: Crustal movements—interplate (8155); 8150 Tectonophysics: Evolution of the Earth: Plate boundary—general (3040); 8155 Tectonophysics: Evolution of the Earth: Plate motions—general; KEYWORDS: remote sensing, motion maps, deformation, data fusion, interferometry, GPS

Potential of multispectral imaging technology for rapid and non-destructive determination of the microbiological quality of beef filets during aerobic storage

The performance of a multispectral imaging system has been evaluated in monitoring aerobically packaged beef filet spoilage at different storage temperatures (0, 4, 8, 12, and 16°C). Spectral data in the visible and short wave near infrared area (405-970nm) were collected from the surface of meat samples and correlated with microbiological data (log counts), for total viable counts (TVCs), Pseudomonas spp., and Brochothrix thermosphacta. Qualitative analysis (PLS-DA) was employed for the discrimination of meat samples in three microbiological quality classes based on the values of total viable counts, namely Class 1 (TVC<5.5log10CFU/g), Class 2 (5.5log10CFU/g7.0log10CFU/g). Furthermore, PLS regression models were developed to provide quantitative estimations of microbial counts during meat storage. In both cases model validation was implemented with independent experiments at intermediate storage temperatures (2 and 10°C) using different batches of meat. Results demonstrated good performance in classifying meat samples with overall correct classification rate for the three quality classes ranging from 91.8% to 80.0% for model calibration and validation, respectively. For quantitative estimation, the calculated regression coefficients between observed and estimated counts ranged within 0.90-0.93 and 0.78-0.86 for model development and validation, respectively, depending on the microorganism. Moreover, the calculated average deviation between observations and estimations was 11.6%, 13.6%, and 16.7% for Pseudomonas spp., B. thermosphacta, and TVC, respectively. The results indicated that multispectral vision technology has significant potential as a rapid and non-destructive technique in assessing the microbiological quality of beef fillets.

Direct identification of pure penicillium species using image analysis

This paper presents a method for direct identification of fungal species solely by means of digital image analysis of colonies as seen after growth on a standard medium. The method described is completely automated and hence objective once digital images of the reference fungi have been established. Using a digital image it is possible to extract precise information from the surface of the fungal colony. This includes color distribution, colony dimensions and texture measurements. For fungal identification, this is normally done by visual observation that often results in a very subjective data recording. Isolates of nine different species of the genus Penicillium have been selected for the purpose. After incubation for 7 days, the fungal colonies are digitized using a very accurate digital camera. Prior to the image analysis each image is corrected for self-illumination, thereby gaining a set of directly corresponding images with respect to illumination. A Windows application has been developed to locate the position and size of up to three colonies in the digitized image. Using the estimated positions and sizes of the colonies, a number of relevant features can be extracted for further analysis. The method used to determine the position of the colonies will be covered as well as the feature selection. The texture measurements of colonies of the nine species were analyzed and a clustering of the data into the correct species was confirmed. This indicates that it is indeed possible to identify a given colony merely by macromorphological features. A classifier (in the normal distribution) based on measurements of 151 colonies incubated on yeast extract sucrose agar (YES) was used to discriminate between the species. This resulted in a correct classification rate of 100% when used on the training set and 96% using cross-validation. The same methods applied to 194 colonies incubated on Czapek yeast extract agar (CYA) resulted in a correct classification rate of 98% on the training set and 71% using cross-validation.

Estimation of nanoparticle size distributions by image analysis

Knowledge of the nanoparticle size distribution is important for the interpretation of experimental results in many studies of nanoparticle properties. An automated method is needed for accurate and robust estimation of particle size distribution from nanoparticle images with thousands of particles. In this paper, we present an automated image analysis technique based on a deformable ellipse model that can perform this task. Results of using this technique are shown for both nearly spherical particles and more irregularly shaped particles. The technique proves to be a very useful tool for nanoparticle research.

Three-dimensional glacier surface motion maps at the Gjálp eruption site, Iceland, inferred from combining InSAR and other ice-displacement data

Abstract We use topographically corrected interferograms, repeated global positioning system observations of locations of stakes and time series of elevation data to produce time series of high-resolution three-dimensional (3-D) ice surface motion maps for the infilling of the ice depression created by the 1996 subglacial eruption at the Gjálp volcano in Vatnajökull, Iceland. The ice inflow generated uplift in the central parts of the depression. During the first months, the uplift was much reduced by basal melting as the subglacial volcano cooled. For those motions surface-parallel ice flow cannot be assumed. The 3-D motion maps are created by an optimization process that combines the complementary datasets. The optimization is based on a Markov random-field regularization and a simulated annealing algorithm. The 3-D motion maps show the pattern of gradually diminishing ice flow into the depression. They provide a consistent picture of the 3-D motion field, both spatially and with time, which cannot be seen by separate interpretation of the complementary observations. The 3-D motion maps were used to calculate the cooling rate of the subglacial volcano for the first year after the eruption. First an uplift rate resulting solely from the inflow of ice was calculated from inferred horizontal motions. Basal melting was then estimated as the difference between the calculated uplift generated by the inflow of ice, and the observed uplift that was the combined result of ice inflow and basal melting. The basal melting was found to decline from 55 m3 s–1 (due to power of 18 GW) in January 1997 to 5 m3 s–1 (2GW) in October 1997.

Comparison of a multispectral vision system and a colorimeter for the assessment of meat color

The color assessment ability of a multispectral vision system is investigated by a comparison study with color measurements from a traditional colorimeter. The experiment involves fresh and processed meat samples. Meat is a complex material; heterogeneous with varying scattering and reflectance properties, so several factors can influence the instrumental assessment of meat color. In order to assess whether two methods are equivalent, the variation due to these factors must be taken into account. A statistical analysis was conducted and showed that on a calibration sheet the two instruments are equally capable of measuring color. Moreover the vision system provides a more color rich assessment of fresh meat samples with a glossier surface, than the colorimeter. Careful studies of the different sources of variation enable an assessment of the order of magnitude of the variability between methods accounting for other sources of variation leading to the conclusion that color assessment using a multispectral vision system is superior to traditional colorimeter assessments.

Chemical imaging and solid state analysis at compact surfaces using UV imaging.

Fast non-destructive multi-wavelength UV imaging together with multivariate image analysis was utilized to visualize distribution of chemical components and their solid state form at compact surfaces. Amorphous and crystalline solid forms of the antidiabetic compound glibenclamide, and microcrystalline cellulose together with magnesium stearate as excipients were used as model materials in the compacts. The UV imaging based drug and excipient distribution was in good agreement with hyperspectral NIR imaging. The UV wavelength region can be utilized in distinguishing between glibenclamide and excipients in a non-invasive way, as well as mapping the glibenclamide solid state form. An exploratory data analysis supported the critical evaluation of the mapping results and the selection of model parameters for the chemical mapping. The present study demonstrated that the multi-wavelength UV imaging is a fast process analytical technique with the potential for real-time monitoring of critical quality attributes.

Rapid Assessment of Tablet Film Coating Quality by Multispectral UV Imaging

Chemical imaging techniques are beneficial for control of tablet coating layer quality as they provide spectral and spatial information and allow characterization of various types of coating defects. The purpose of this study was to assess the applicability of multispectral UV imaging for assessment of the coating layer quality of tablets. UV images were used to detect, characterize, and localize coating layer defects such as chipped parts, inhomogeneities, and cracks, as well as to evaluate the coating surface texture. Acetylsalicylic acid tablets were prepared on a rotary tablet press and coated with a polyvinyl alcohol-polyethylene glycol graft copolymer using a pan coater. It was demonstrated that the coating intactness can be assessed accurately and fast by UV imaging. The different types of coating defects could be differentiated and localized based on multivariate image analysis and Soft Independent Modeling by Class Analogy applied to the UV images. Tablets with inhomogeneous texture of the coating could be identified and distinguished from those with a homogeneous surface texture. Consequently, UV imaging was shown to be well-suited for monitoring of the tablet coating layer quality. UV imaging is a promising technique for fast quality control of the tablet coating because of the high data acquisition speed and its nondestructive analytical nature.