The high rate of unplanned perforation, poor fixation, and nerve injury with freehand pedicle screw insertion has led to the use of image-guided navigation systems. Although these improve accuracy, they have several drawbacks that could be overcome by using image-based drilling guide templates. The accuracy of such templates was tested in a cadaveric study of screw placement in the lumbar, thoracic, and cervical regions of the spine. The dimensional stability with autoclaving of duraform polyamide, to be used for manufacturing the guides, was first determined using test specimens. Computed tomography (CT) images were acquired of 4 cadaveric spines, and placement of 4 cervical, 32 thoracic, and 14 lumbar screws was planned. Eighteen personalized drilling guide templates, in four different designs, were built. Orthopaedic surgeons experienced in the freehand techniques used the templates. CT images were acquired to assess placement position with respect to the pedicle. Duraform polyamide was found to be unaffected by sterilization. Two of the template designs facilitated the placement of 20/20 screws without error. Templates can lead to successful screw placement, even in small pedicles, providing their design is optimized for the application area, e.g. with enhanced rotational stabilization.

This article outlines our practical approach to digitizing historical text sources via Optical Character Recognition (OCR) for subsequent Natural Language Processing (NLP) and corpus analysis. For this purpose we developed two processing pipelines based on pyFlow for parallel computing using Tesseract OCR for OCR and spaCy for NLP. To ensure that the software is developed in terms of reusability and sustainability, the importance of free and open source software and the use of Linux containers via Docker during the development process and within a production environment is also described. Details regarding OCR preprocessing steps, e.g., binarization are also discussed. Besides the software development aspects the article contains some learnings and best practices for end users on how to create high quality input images (avoiding noise, skew, etc.) for the OCR pipeline. By following these steps, OCR results can be significantly improved. For both, our OCR and NLP pipelines, the accuracies and respective error rates are discussed at the ennd of the corresponding chapters.

In Zeiten einer global fortschreitenden Urbanisierung der Lebenswelten gewinnen Imaginationen und Projektionen eines guten Lebens auf dem Land eine neue diskursive Attraktivität. Sie verweisen auf eine lange und ambivalente Geschichte zwischen Anforderungen und Überforderungen gesellschaftlichen Wandels sowie den Ansprüchen auf ein gelingendes Leben. Angesichts umfassender Transformationen, Krisen und Katastrophen bieten die kulturellen Produktionen ländlicher Lebensverhältnisse - und damit verbunden die Vorstellungen von Natur, Idylle und Heimat - sowohl idealisierte Sehnsuchtsorte als auch konkretisierte Orientierungspunkte. Land und Ländlichkeit geraten in ein komplexes Spannungsverhältnis, das auch Auskunft gibt über Wahrnehmung und Selbstverständnis im Leben in und zwischen Stadt und Land.

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