Probabilistic approach to cloud and snow detection on Advanced Very High Resolution Radiometer (AVHRR) imagery

Derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. Information about a confidence level of provided physical quantities is required to construct an error budget of higher-level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data a common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher-level products and may alter their usability. Within this scope a novel probabilistic cloud mask (PCM) algorithm suited for the 1 km × 1 km Advanced Very High Resolution Radiometer (AVHRR) data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clear-sky/snow conditions. As opposed to the majority of available techniques which are usually based on the decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve probability estimates from the precomputed look-up tables (LUTs). Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of intervals. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the invariant coordinate system (ICS) transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the Polar Platform System (PPS) version 2012 and Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 cloud masks, SYNOP (surface synoptic observations) weather reports, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical feature mask version 3 and to MODIS collection 5 snow mask. The outcomes of conducted analyses proved fine detection skills of the PCM method with results comparable to or better than the reference PPS algorithm.

Detection of degenerative cartilage disease: comparison of high-resolution morphological MR and quantitative T2 mapping at 3.0 Tesla

The aim of the study was to investigate the association of T2 relaxation times of the knee with early degenerative cartilage changes. Furthermore the impact of unloading the knee on T2 values was evaluated.

Inter- and intraobserver reliability of predefined diagnostic levels in high-resolution sonography of the carpal tunnel syndrome - a validation study on healthy volunteers

High-resolution ultrasound is becoming increasingly important in the diagnosis of carpal tunnel syndrome (CTS). Most studies define cut-off values of the cross-sectional area (CSA) of the median nerve in different locations. The individual range of nerve swelling, the size of the nerve, and its CSA are not addressed. The aim of the study is to define the intra- and interobserver reliability of diagnostic ultrasound using two different cross-sectional areas of the median nerve at the carpal tunnel in predefined locations.

Informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry (GCxGC-HRMS)

This paper describes informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution mass spectrometry (HRMS). GCxGC-HRMS analysis produces large data sets that are rich with information, but highly complex. The size of the data and volume of information requires automated processing for comprehensive cross-sample analysis, but the complexity poses a challenge for developing robust methods. The approach developed here analyzes GCxGC-HRMS data from multiple samples to extract a feature template that comprehensively captures the pattern of peaks detected in the retention-times plane. Then, for each sample chromatogram, the template is geometrically transformed to align with the detected peak pattern and generate a set of feature measurements for cross-sample analyses such as sample classification and biomarker discovery. The approach avoids the intractable problem of comprehensive peak matching by using a few reliable peaks for alignment and peak-based retention-plane windows to define comprehensive features that can be reliably matched for cross-sample analysis. The informatics are demonstrated with a set of 18 samples from breast-cancer tumors, each from different individuals, six each for Grades 1-3. The features allow classification that matches grading by a cancer pathologist with 78% success in leave-one-out cross-validation experiments. The HRMS signatures of the features of interest can be examined for determining elemental compositions and identifying compounds.

Investigation of different apple cultivars by high resolution magic angle spinning NMR. A feasibility study

(1)H HR-MAS NMR spectroscopy was applied to apple tissue samples deriving from 3 different cultivars. The NMR data were statistically evaluated by analysis of variance (ANOVA), principal component analysis (PCA), and partial least-squares-discriminant analysis (PLS-DA). The intra-apple variability of the compounds was found to be significantly lower than the inter-apple variability within one cultivar. A clear separation of the three different apple cultivars could be obtained by multivariate analysis. Direct comparison of the NMR spectra obtained from apple tissue (with HR-MAS) and juice (with liquid-state HR NMR) showed distinct differences in some metabolites, which are probably due to changes induced by juice preparation. This preliminary study demonstrates the feasibility of (1)H HR-MAS NMR in combination with multivariate analysis as a tool for future chemometric studies applied to intact fruit tissues, e.g. for investigating compositional changes due to physiological disorders, specific growth or storage conditions.

Structure determination of channel and transport proteins by high-resolution microscopy techniques

High-resolution microscopy techniques provide a plethora of information on biological structures from the cellular level down to the molecular level. In this review, we present the unique capabilities of transmission electron and atomic force microscopy to assess the structure, oligomeric state, function and dynamics of channel and transport proteins in their native environment, the lipid bilayer. Most importantly, membrane proteins can be visualized in the frozen-hydrated state and in buffer solution by cryo-transmission electron and atomic force microscopy, respectively. We also illustrate the potential of the scintillation proximity assay to study substrate binding of detergent-solubilized transporters prior to crystallization and structural characterization.

High-resolution imaging of 2D outer membrane protein F (OmpF) crystals by atomic force microscopy

In this chapter the methodological bases are provided to achieve subnanometer resolution on two-dimensional (2D) membrane protein crystals by atomic force microscopy (AFM). This is outlined in detail with the example of AFM studies of the outer membrane protein F (OmpF) from the bacterium Escherichia coli (E. coli). We describe in detail the high-resolution imaging of 2D OmpF crystals in aqueous solution and under near-physiological conditions. The topographs of OmpF, and stylus effects and artifacts encountered when imaging by AFM are discussed.