In-service monitoring of piping and vessels in nuclear power plants: report on BMU Study SR 2218

The BMU-Study SR 2218 is made with a view to describing and assessing fatigue monitoring as commonly applied today to piping and vessels in nuclear power plants. First, the fundamentals with regard to strain, instrumentation and calculation of fatigue are compiled and the current regulations listed. With reference to the available literature, own experience and a survey conducted among operators and manufacturers of the now common types of installations, the points of measurement, the methods of measuring, the acquisition systems for measured data and the methods of analysis are described, as are the results obtained from the measurements so far. After a careful review of these results, proposals are presented for improving the acquisition of measured data and, most important of all, for analysis and assessment. In the nuclear power plants in Germany those areas which are of relevance to fatigue have been identified by means of temperature measurements taken in the recent past in the various types of installations. Many thorough analyses have been made on the basis of transients measured in order to assess the relevance of the areas in terms of fatigue. The degrees of fatigue established are normally D=0.2–0.3, that is <D=0.5 for loads occurring in service. It can be stated, in summary, that the degrees of fatigue obtained from fatigue monitoring systems are more realistic than those obtained from the approach adopted in the design stage. As the requirements of the nuclear power plants are specific and varied, there can be no universal and flexible system that is adequate for all applications. That is why it will always be necessary to find solutions for each individual case. This paper gives an overview about the content and the results of the study.     

Biologically motivated space-variant filtering for robust optic flow processing

We describe and test a biologically motivated space-variant filtering method for decreasing the noise in optic flow fields. Our filter model adopts certain properties of a particular motion-sensitive area of the brain (area MT), which averages the incoming motion signals over receptive fields, the sizes of which increase with the distance from the center of the projection. We use heading estimation from optic flow as a criterion to evaluate the improvement of the filtered flow field. The tests are conducted on flow fields calculated with a standard flow algorithm from image sequences. We use two different sets of image sequences. The first set is recorded by a camera which is installed in a moving car. The second set is derived from a database containing three dimensional data and reflectance information from natural scenes. The latter set guarantees full control of the camera motion and ground truth about the flow field and the heading. We test the space-variant filtering method by comparing heading estimation results between space-variant filtered flow, flow filtered by averaging over domains of the visual field with constant size (constant filtering) and raw unfiltered flow. Because of noise and the aperture problem the heading estimates obtained from the raw flows are often unreliable. Estimated heading differs widely for different sub-sampled calculations. In contrast, the results obtained from the filtered flows are much less variable and therefore more consistent. Furthermore, we find a significant improvement of the results obtained from the space-variant filtered flow compared to the constant filtered flow. We suggest extensions to the space-variant filtering procedure that take other properties of motion representation in area MT into account.     

Unveiling the molecular basis of intrinsic skin aging(1)

The process of skin aging is a combination of an extrinsic and intrinsic aspect, and knowing the molecular changes underlying both is a prerequisite to being able to effectively counter it. However, despite its importance for a deeper understanding of skin aging as a whole, the process of intrinsic skin aging in particular has barely been investigated. In this study, the molecular changes of intrinsic skin aging were analyzed by applying 'Serial Analysis of Gene Expression' (SAGE(TM)) to skin biopsies of young and aged donors. The analysis resulted in several hundred differentially expressed genes with varying statistical significance. Of these, several genes were identified that either have never been described in skin aging before (e.g. APP) or have no identified function, e.g. EST sequences. This is the first time that intrinsic skin aging has been analyzed in such a comprehensive manner, offering a new and partially unexpected set of target genes that have to be analyzed in more detail in terms of their contribution to the skin aging process.     

Group II and group III metabotropic glutamate receptors in the rat retina: distributions and developmental expression patterns

We have studied the distributions of group II metabotropic glutamate receptors, mGluR2 and mGluR3, and a group III metabotropic glutamate receptor, mGluR4, in the adult rat retina and during postnatal development using receptor specific anti-peptide antisera. Of the three receptors examined, mGluR3 was not expressed in the retina. MGluR2 showed a distinct stratification pattern in the inner plexiform layer (IPL). Double-labelling immunocytochemistry revealed that mGluR2 was localized in the processes of cholinergic amacrine cells. MGluR4 was found throughout the entire IPL. At the subcellular level, both mGluR2 and mGluR4 were found to be localized exclusively in processes postsynaptic to bipolar cell synapses in the IPL. During postnatal development, labelling for mGluR2 was detected at around postnatal day five. MGluR4 was already present at postnatal day one, prior to the establishment of synaptic connections in the IPL. The differential expression patterns of individual metabotropic glutamate receptors in the adult and developing rat retina suggest distinct roles for these receptors in retinal synaptic circuitry.     

Moisture the dominant factor in the stability of doxylamine succinate tablets

During a stability trial at 55°C with doxylamine succinate combined with different excipients at different moisture contents, moisture was found to be the dominant factor affecting the stability of doxylamine succinate. Each excipient however also had a specific affect.     

Fat and hydration monitoring by abdominal bioimpedance analysis: data interpretation by hierarchical electrical modeling

In a previous publication, it was demonstrated that the abdominal subcutaneous fat layer thickness (SFL) is strongly correlated with the abdominal electrical impedance when measured with a transversal tetrapolar electrode arrangement. This article addresses the following questions: 1) To which extent do different abdominal compartments contribute to the impedance? 2) How does the hydration state of tissues affect the data? 3) Can hydration and fat content be assessed independently? For simulating the measured data a hierarchical electrical model was built. The abdomen was subdivided into three compartments (subcutaneous fat, muscle, mesentery). The true anatomical structure of the compartment boundaries was modeled using finite-element modeling (FEM). Each compartment is described by an electrical tissue model parameterized in physiological terms. Assuming the same percent change of the fat fraction in the mesentery and the SFL the model predicts a change of 1,24 omega/mm change of the SFL compared to 1,1 omega/mm measured. 42% of the change stem from the SFL, 56% from the mesentery and 2% from changes of fat within the muscle compartment. A 1% increase of the extracellular water in the muscle is not discernible from a 1% decrease of the SFL. The measured data reflect not only the SFL but also the visceral fat. The tetrapolar electrode arrangement allows the measurement of the abdominal fat content only if the hydration remains constant.     

Temporal sequence learning, prediction, and control: a review of different models and their relation to biological mechanisms

In this review, we compare methods for temporal sequence learning (TSL) across the disciplines machine-control, classical conditioning, neuronal models for TSL as well as spike-timing-dependent plasticity (STDP). This review introduces the most influential models and focuses on two questions: To what degree are reward-based (e.g., TD learning) and correlation-based (Hebbian) learning related? and How do the different models correspond to possibly underlying biological mechanisms of synaptic plasticity? We first compare the different models in an open-loop condition, where behavioral feedback does not alter the learning. Here we observe that reward-based and correlation-based learning are indeed very similar. Machine control is then used to introduce the problem of closed-loop control (e.g., actor-critic architectures). Here the problem of evaluative (rewards) versus nonevaluative (correlations) feedback from the environment will be discussed, showing that both learning approaches are fundamentally different in the closed-loop condition. In trying to answer the second question, we compare neuronal versions of the different learning architectures to the anatomy of the involved brain structures (basal-ganglia, thalamus, and cortex) and the molecular biophysics of glutamatergic and dopaminergic synapses. Finally, we discuss the different algorithms used to model STDP and compare them to reward-based learning rules. Certain similarities are found in spite of the strongly different timescales. Here we focus on the biophysics of the different calcium-release mechanisms known to be involved in STDP.     

Comparison of mass-based and non-mass-based particle measurement systems for ultra-low emissions from automotive sources

Drastic reduction in particle emissions of diesel-powered vehicles and new findings on the health impact of particles raise the question of a more sensitive measurement procedure. In this paper, 16 different particle mass measurement systems are compared on a diesel heavy-duty engine equipped with a particle filter to investigate their feasibility for particle characterization for future ultra-low concentration levels. The group of instruments comprises mass-related methods (filter methods, laser-induced incandescence, photoacoustic detection, photoelectric charging, combined inertial and mobility sizing, opacity) as well as non-mass-related methods (CPC, diffusion battery, diffusion charger, ELPI, light scattering). The instruments are compared on the basis of repeatability, limit of detection, sensitivity, time resolution and correlation with the regulated gravimetric filter method, and elemental carbon fraction (EC). Several time-resolved methods show good performance and give reliable results. Opacimeters and light scattering, however, reveal shortcomings at these low concentrations. For all time-resolved advanced methods, poor correlation with the regulated filter method is observed, but most of them show good correlation with the EC fraction of the particles. This outcome demonstrates the crucial role of the sampling conditions for measurement methods that do not exclude volatile material from detection. A clear improvement in sensitivity is observed when non-mass-based instruments are applied (e.g., number or surface-related methods). The results reveal that reliable measurement methods exist for future measurement procedures. However, a change in the measurement method will lead to a discontinuity in the inventories, making it difficult to compare the particle emissions from future and past vehicle generations.     

Reclustering techniques improve early vision feature maps

We propose a recursive post-processing algorithm to improve feature-maps, like disparity- or motion-maps, computed by early vision modules. The statistical distribution of the features is computed from the original feature-map, and from this the most likely candidate for a correct feature is determined for every pixel. This process is performed automatically by a clustering algorithm which determines the feature candidates as the cluster centres in the distribution. After determining the feature candidates, a cost function is computed for every pixel, and a candidate will only replace the original feature if the cost is reduced. In this way, a new feature-map is generated which, in the next iteration, serves as the basis for the computation of the updated feature distribution. Iterations are stopped if the total cost reduction is less than a pre-defined threshold. In general, our technique is albe to reduce two of the most common problems that affect feature-maps, the sparseness, i.e. the presence of areas where the algorithm is not able to give meaningful measurements, and the blur. To show the efficacy of our approach, we apply the reclustering algorithm to several examples of increasing complexity, showing results for synthetic and natural images.