High Speed - slow motion: Experimente unter der (Zeit-)lupe

Hochgeschwindigkeitsaufnahmen physikalischer Phänomene erforderten früher sehr teures Equipment. Dank digitaler Kameratechnik wird es zunehmend erschwinglich. Im Folgenden wird ein Experiment beispielhaft beschrieben sowie eine Literaturübersicht gegeben

Characterizing small depth and small space classes by operators of higher types

Motivated by the question of how to define an analog of interactive proofs in the setting of logarithmic time- and space-bounded computation, we study complexity classes defined in terms of operators quantifying over oracles. We obtain new characterizations of NC1, L, NL, NP, and NSC (the nondeterministic version of SC). In some cases, we prove that our simulations are optimal (for instance, in bounding the number of queries to the oracle)

Theory of sampling and its application in tissue based diagnosis

<p>Abstract</p> <p>Background</p> <p>A general theory of sampling and its application in tissue based diagnosis is presented. Sampling is defined as extraction of information from certain limited spaces and its transformation into a statement or measure that is valid for the entire (reference) space. The procedure should be reproducible in time and space, i.e. give the same results when applied under similar circumstances. Sampling includes two different aspects, the procedure of sample selection and the efficiency of its performance. The practical performance of sample selection focuses on search for localization of specific compartments within the basic space, and search for presence of specific compartments.</p> <p>Methods</p> <p>When a sampling procedure is applied in diagnostic processes two different procedures can be distinguished: I) the evaluation of a diagnostic significance of a certain object, which is the probability that the object can be grouped into a certain diagnosis, and II) the probability to detect these basic units. Sampling can be performed without or with external knowledge, such as size of searched objects, neighbourhood conditions, spatial distribution of objects, etc. If the sample size is much larger than the object size, the application of a translation invariant transformation results in Kriege's formula, which is widely used in search for ores. Usually, sampling is performed in a series of area (space) selections of identical size. The size can be defined in relation to the reference space or according to interspatial relationship. The first method is called random sampling, the second stratified sampling.</p> <p>Results</p> <p>Random sampling does not require knowledge about the reference space, and is used to estimate the number and size of objects. Estimated features include area (volume) fraction, numerical, boundary and surface densities. Stratified sampling requires the knowledge of objects (and their features) and evaluates spatial features in relation to the detected objects (for example grey value distribution around an object). It serves also for the definition of parameters of the probability function in so – called active segmentation.</p> <p>Conclusion</p> <p>The method is useful in standardization of images derived from immunohistochemically stained slides, and implemented in the EAMUS™ system <url>http://www.diagnomX.de</url>. It can also be applied for the search of "objects possessing an amplification function", i.e. a rare event with "steering function". A formula to calculate the efficiency and potential error rate of the described sampling procedures is given.</p

Image standards in Tissue-Based Diagnosis (Diagnostic Surgical Pathology)

© 2008 Kayser et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

AI (artificial intelligence) in histopathology--from image analysis to automated diagnosis.

The technological progress in digitalization of complete histological glass slides has opened a new door in tissue--based diagnosis. The presentation of microscopic images as a whole in a digital matrix is called virtual slide. A virtual slide allows calculation and related presentation of image information that otherwise can only be seen by individual human performance. The digital world permits attachments of several (if not all) fields of view and the contemporary visualization on a screen. The presentation of all microscopic magnifications is possible if the basic pixel resolution is less than 0.25 microns. To introduce digital tissue--based diagnosis into the daily routine work of a surgical pathologist requires a new setup of workflow arrangement and procedures. The quality of digitized images is sufficient for diagnostic purposes; however, the time needed for viewing virtual slides exceeds that of viewing original glass slides by far. The reason lies in a slower and more difficult sampling procedure, which is the selection of information containing fields of view. By application of artificial intelligence, tissue--based diagnosis in routine work can be managed automatically in steps as follows: 1. The individual image quality has to be measured, and corrected, if necessary. 2. A diagnostic algorithm has to be applied. An algorithm has be developed, that includes both object based (object features, structures) and pixel based (texture) measures. 3. These measures serve for diagnosis classification and feedback to order additional information, for example in virtual immunohistochemical slides. 4. The measures can serve for automated image classification and detection of relevant image information by themselves without any labeling. 5. The pathologists' duty will not be released by such a system; to the contrary, it will manage and supervise the system, i.e., just working at a "higher level". Virtual slides are already in use for teaching and continuous education in anatomy and pathology. First attempts to introduce them into routine work have been reported. Application of AI has been established by automated immunohistochemical measurement systems (EAMUS, www.diagnomX.eu). The performance of automated diagnosis has been reported for a broad variety of organs at sensitivity and specificity levels >85%). The implementation of a complete connected AI supported system is in its childhood. Application of AI in digital tissue--based diagnosis will allow the pathologists to work as supervisors and no longer as primary "water carriers". Its accurate use will give them the time needed to concentrating on difficult cases for the benefit of their patients

Analysis of the Paired TCR α- and β-chains of Single Human T Cells

Analysis of the paired i.e. matching TCR α- and β-chain rearrangements of single human T cells is required for a precise investigation of clonal diversity, tissue distribution and specificity of protective and pathologic T-cell mediated immune responses. Here we describe a multiplex RT-PCR based technology, which for the first time allows for an unbiased analysis of the complete sequences of both α- and β-chains of TCR from single T cells. We validated our technology by the analysis of the pathologic T-cell infiltrates from tissue lesions of two T-cell mediated autoimmune diseases, psoriasis vulgaris (PV) and multiple sclerosis (MS). In both disorders we could detect various T cell clones as defined by multiple T cells with identical α- and β-chain rearrangements distributed across the tissue lesions. In PV, single cell TCR analysis of lesional T cells identified clonal CD8+ T cell expansions that predominated in the epidermis of psoriatic plaques. An MS brain lesion contained two dominant CD8+ T-cell clones that extended over the white and grey matter and meninges. In both diseases several clonally expanded T cells carried dual TCRs composed of one Vβ and two different Vα-chain rearrangements. These results show that our technology is an efficient instrument to analyse αβ-T cell responses with single cell resolution in man. It should facilitate essential new insights into the mechanisms of protective and pathologic immunity in many human T-cell mediated conditions and allow for resurrecting functional TCRs from any αβ-T cell of choice that can be used for investigating their specificity

Flow simulation and shape optimization for aircraft design

AbstractWithin the framework of the German aerospace research program, the CFD project MEGADESIGN was initiated. The main goal of the project is the development of efficient numerical methods for shape design and optimization. In order to meet the requirements of industrial implementations a co-operative effort has been set up which involves the German aircraft industry, the DLR, several universities and some small enterprises specialized in numerical optimization. This paper outlines the planned activities within MEGADESIGN, the status at the beginning of the project and it presents some early results achieved in the project