Verzeichnis der Briefsammlungen Cod. 117-121, 123, 126, 139c, 152o, 153, 154 in der Universitätsbibliothek Gießen

Der Katalog verzeichnet den Inhalt von 12 Sammelhandschriften der Universitätsbibliothek Gießen. Sie umfassen insgesamt exakt 1.000 Briefe des 16. bis 18. Jahrhunderts, im Einzelnen: Hs 117 Briefwechsel zwischen Johann Christian Freiherr von Boyneburg (1622-1673) und Zacharias Prueschenck (1610-1679) (193 Nrn) Hs 118 Briefe von Johann Caselius (1533-1613) (87 Nrn) Hs 119 Briefe von Christoph Forstner (1598-1667) (46 Nrn) Hs 120 größtenteils Briefwechsel zwischen Christoph Forstner (1598-1667) und Johann Albrecht Portner (1628-1687) (110 Nrn) Hs 121 Briefe an Johann Heinrich Boecler (1611-1672) (209 Nrn) Hs 123 Briefe an Johann Walter Slusius (58 Nrn) Hs 126 Briefe von Jacob Sirmond (1559-1651) an Alexander Wiltheim (1604-1684) (15 Nrn) Hs 139 Briefe an Christian Misler (19 Nrn) Hs 139c Briefe an Augustinus Quirinus Rivinus (1652-1723) (6 Nrn) Hs 152o Briefe von Johann Tack (1617-1676) an Johann Eitel Diede zu Fürstenstein (24 Nrn), l Brief von Johann Tack an Johann Daniel Horst (1620-1685) Hs 153 und 154 Briefe von Zacharias Conrad von Uffenbach (1683- 1734) an Johann Heinrich May den Jüngeren (1688-1732) (139 und 94 Nrn

Multiscale Convolutional Neural Networks for Vision–Based Classification of Cells

International audienceWe present a Multiscale Convolutional Neural Network (MCNN) approach for vision-based classification of cells. Based on several deep Convolutional Neural Networks (CNN) acting at different resolutions, the proposed architecture avoid the classical handcrafted features extraction step, by processing features extraction and classification as a whole. The proposed approach gives better classification rates than classical state-of-the-art methods allowing a safer Computer-Aided Diagnosis of pleural cancer

DeadEasy Mito-Glia: Automatic Counting of Mitotic Cells and Glial Cells in Drosophila

Cell number changes during normal development, and in disease (e.g., neurodegeneration, cancer). Many genes affect cell number, thus functional genetic analysis frequently requires analysis of cell number alterations upon loss of function mutations or in gain of function experiments. Drosophila is a most powerful model organism to investigate the function of genes involved in development or disease in vivo. Image processing and pattern recognition techniques can be used to extract information from microscopy images to quantify automatically distinct cellular features, but these methods are still not very extended in this model organism. Thus cellular quantification is often carried out manually, which is laborious, tedious, error prone or humanly unfeasible. Here, we present DeadEasy Mito-Glia, an image processing method to count automatically the number of mitotic cells labelled with anti-phospho-histone H3 and of glial cells labelled with anti-Repo in Drosophila embryos. This programme belongs to the DeadEasy suite of which we have previously developed versions to count apoptotic cells and neuronal nuclei. Having separate programmes is paramount for accuracy. DeadEasy Mito-Glia is very easy to use, fast, objective and very accurate when counting dividing cells and glial cells labelled with a nuclear marker. Although this method has been validated for Drosophila embryos, we provide an interactive window for biologists to easily extend its application to other nuclear markers and other sample types. DeadEasy MitoGlia is freely available as an ImageJ plug-in, it increases the repertoire of tools for in vivo genetic analysis, and it will be of interest to a broad community of developmental, cancer and neuro-biologists

Design for invention: annotation of Functional Geometry Interaction for representing novel working principles

In some mechanical engineering devices the novelty or inventive step of a patented design relies heavily upon how geometric features contribute to device functions. Communicating the functional interactions between geometric features in existing patented designs may increase a designer’s awareness of the prior art and thereby avoid conflict with their emerging design. This paper shows how functional representations of geometry interactions can be developed from patent claims to produce novel semantic graphical and text annotations of patent drawings. The approach provides a quick and accurate means for the designer to understand the patent that is well suited to the designer’s natural way of understanding the device. Through several example application cases we show the application of a detailed representation of Functional Geometry Interactions that captures the working principle of familiar mechanical engineering devices described in patents. A computer tool that is being developed to assist the designer to understand prior art is also described

Data-analysis strategies for image-based cell profiling

Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.Peer reviewe

Real-time automatic evaluation of solid state nuclear track detectors with an on-line TV-device.

An on-line TV-system for real time analysis of two-dimensional images is described which is being used for automatic evaluation of track detectors, histological cell analysis, and a number of other purposes. Results are reported for applications commonly encountered in dielectric track detector evaluation problems; namely determination of the integral track density, of the spatial distribution of tracks, and of statistical distributions of geometrical features of tracks. Special emphasis is given to the region of low track densities