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Background: Following the current gold standard, autologous cancellous bone is used as part of alveolar cleft osteoplasty. To fill the bone defects, autologous bone material is harvested from the iliac crest using manual tools such as shepard chisels or trephine drills. The bone augmentations obtained in this way have a simple geometry, usually cylinders, and must then be manually adapted to the defect to be filled by the surgeon using surgical forceps and scissors. There are no established routines for the manufacturing of patient-specific, cost-effective surgical cutting guides. However, the accuracy of fit of the augmentations plays an important role in the healing process.
Methods: This paper focuses on a concept for the creation of necessary sequenced incision geometries based on 3D X-ray data of alveolar cleft defects.
Results: As a result, a procedure is to be developed for the preoperative design of individualised surgical cutting guides based on image data. We described a workflow to segment the cleft defect using reverse engineering from Cone-beam computed tomography (CBCT) data. The data was further processed and a keyhole contour was created. A stamping guide and a cutting guide were then derived. The stamping guides were scaled 5, 10 and 15% larger than the defect. In addition, two half-shells were produced, which will be used to investigate the clamping forces and the biological consequences in a follow-up study.
Conclusions: This article presents a developed routine for creating patient-specific templates and demonstrates its feasibility.
In this article, I present changes to the content of the Bachelor’s degree programme German Business Communication that I consider necessary in the light of AI-driven developments both in science and economic fields. I focus on developing critical thinking when students use Generative Artificial Intelligence (GenAI) in their scientific work. This fits in well with the programme’s critical and engaged academic approach. The article sets out with an empirical consideration of AI in academic settings and GenAI application within the framework of the degree programme. Based upon this, a teaching/learning unit on GenAI use in a module of the programme is presented, which was designed and implemented in the winter semester 2025/26. The preliminary results reveal that further considerations are required to expand teaching units on AI tools for specific areas of business communication.
Since its inception in early 2022, Artificial Intelligence (AI) has been debated controversially in the media. The emergence of chatbots, Large Language Models (LLMs), generative AI and AI agents has spurred the discussion about AI strengths, weaknesses and the risks of using AI in business, education, and media. There is rising social concern about the effects of man-machine interaction as well as deep fakes. Therefore, AI media coverage spans from broad acceptance to the critical evaluation of ethical risks. This article examines the perception of AI based upon a qualitative corpus analysis of digital newsletters. The study considers German and English newsletter communications on AI and considers the role of this genre in adapting this disruptive new technology by describing macrostructure, visual elements, style and interactivity with the readers.
The genre “presentation” represents a central communicative act in academic settings, particularly in foreign-language and subject-specific language courses accompanying academic studies, where technical content must be appropriately adapted to the target audience in oral format. However, it is precisely in this context that a special focus is needed on the influence and potential of AI in the creation and implementation of presentations. The objective of this article is to discuss how AI-tools — such as those for text generation, visualization, or language analysis — can support the creation, delivery, and reflection of presentations, but also what negative effects they may have on the development of students’ presentation skills in specialized and foreign language university courses. An overview of relevant AI tools that can also be applied in later professional presentation practice and is intended to provide teachers and learners with a practical repertoire of digital aids. The findings provide impetus for the responsible and skill-oriented integration of AI into foreign language teaching.
Was passiert, wenn Künstliche Intelligenz (KI) auf die Herausforderungen der Fachkommunikation trifft? Wie tragfähig sind die aktuellen Modelle und Konzepte für die Arbeit mit KI im fachlichen und fachsprachlichen Kontext? Expertinnen und Experten für Fachkommunikationsforschung aus neun Ländern stellen in diesem Band ihre aktuellen KI-Projekte in Forschung und Lehre vor. Im Mittelpunkt stehen dabei Modellbildung, KI-Kompetenz, Terminologie, Fachübersetzen und Dolmetschen sowie die Vermittlung von Fachsprache im Hochschulkontext. Mit Blick auf die Qualität fachkommunikativer Forschung und Lehre der Zukunft thematisieren sie Potenziale und Risiken der Nutzung von KI.
(Abstract des Verlages.)
Accuracy of the Smart Watch iECG for Documentation of Supraventricular Tachycardias in Children
(2026)
Die vorliegende Arbeit beschäftigt sich mit der Elektromobilitätswende und den daraus resultierenden Herausforderungen für die deutsche Automobilindustrie. Der erstarkende Nachhaltigkeitsgedanke der modernen Gesellschaft verändert das Mobilitäts- und Nachfrageverhalten an weltweiten Märkten. Internationale Automobilhersteller stehen im aktuellen Wandel zwischen politischem Willen und multidimensionalen Grenzen der Umsetzbarkeit. Die wirtschaftlich aufstrebende Volksrepublik China konnte sich dabei in jüngster Vergangenheit als Leitmarkt etablieren. Der chinesische Automobilbau gewinnt dabei ebenso an Bedeutung und neue Marken, wie „BYD“ verstärken den Wettbewerbsdruck auf deutsche Hersteller zunehmend. Die Abhandlung ordnete die Bedeutung der deutschen Automobilindustrie für den Wirtschaftsstandort Deutschland anhand der Analyse quantitativer Indikatoren ein. Zusätzlich wurden traditionelle Stärken, Herausforderungen und Strategien in Bezug auf die Mobilitätswende für die drei erfolgreichsten deutschen Automobilunternehmen „Volkswagen“, „Mercedes Benz“ und „BMW“ untersucht. Die Relevanz Chinas, sowie die Besonderheiten des Marktumfeldes werden daran anknüpfend betrachtet, bevor die etablierten deutschen Hersteller mit dem chinesischen Disruptor „BYD“ gegenübergestellt wurden. Durchgeführt wurde hierzu eine Wettbewerbsanalyse mit Ausrichtung auf Produktdifferenziertheit nach dem „Fünf-Kräfte-Modell“ (Five-Forces) von Michael E. Porter. Die Gesamtstudie wurde abschließend durch eine Kombination von SWOT- und PESTEL-Analyse ausgewertet. Es wurden wesentliche Potentiale und Herausforderungen für deutsche Automobilhersteller abgeleitet. Diese sind nach globalem und chinesischem Kontext aufgeschlüsselt und in politische, ökonomische, soziale und technologische Dimensionen eingeordnet. Die Ergebnisse können als Grundlage für weiterführende Forschung konkreter Aspekte dienen.
Die Integration Künstlicher Intelligenz (KI) in die globale Wirtschaft löst eine tiefgreifende Transformation von Beschäftigungsverhältnissen aus. Die vorliegende explorative Studie untersucht diese Dynamik, ausgehend von einer technologischen Einordnung kognitiver Systeme, und analysiert sektorale Unterschiede in der KI-Adaption – mit Fokus auf das Gesundheitswesen, das Finanzwesen und das verarbeitende Gewerbe. Ein Kernstück der Untersuchung bildet die Bewertung künftiger Kompetenzprofile: Während hochspezialisierte technische Fähigkeiten und ausgeprägte Sozialkompetenzen an Bedeutung gewinnen, unterliegen repetitive Tätigkeiten einem hohen Substitutionsrisiko. Zur Visualisierung dieser disruptiven Kräfte wird das „Hufeisenmodell der KI-bedingten Arbeitsmarktdisruption“ entwickelt. Es zeigt auf, dass insbesondere die breite Mittelschicht der Gefahr einer Verdrängung ausgesetzt ist, während Tätigkeiten im Niedriglohnsektor und im Bereich der Hochspezialisierung bestehen bleiben. Die Arbeit schließt mit einer Debatte über die drohende soziale Einkommenskluft und liefert damit eine fundierte Basis für strategische Entscheidungen und weiterführende Forschungsfragen.
Röpke, Wilhelm
(2025)
Eucken, Walter
(2025)
Ordoliberalism
(2025)
Na sua Grammaire du sens et de l‘expression, Charaudeau (1992: 4) coloca a descrição das intenções do sujeito falante no centro de uma gramática de orientação comunicativa. Contudo, nas gramáticas tradicionais, o princípio de organização não parte das intenções do sujeito falante, mas de categorias formais da língua.
O exemplo da enunciação de objetivos acionais possui um interesse especial para uma aproximação comunicativa à gramática, pois abre a possibilidade de tratar, num mesmo paradigma de gramática comunicativa, as formas verbais gramaticalizadas que na gramática tradicional são categorizadas como tempos e modos verbais e, ao mesmo tempo, verbos gramaticalizados em diferentes graus. Além disso, faz uma junção entre a verbalização de um processo mental específico (a formação de um objetivo acional; cf. Rehbein 1977; Lock 1996: 105) e a ação que tiver como objetivo realizar. Há de considerar também que, por sua vez, cada meio linguístico localiza o objetivo acional, de maneira específica, no processo mental da sua formação (Lobato 1971: 289; Wunderlich 1981; Johnen 2003: 250-256).
O objetivo desta contribuição é em primeiro lugar indagar o lugar da enunciação de objetivos acionais numa gramática comunicativa do português e fazer um levantamento de subcategorias gramaticais relevantes que as gramáticas tradicionais não consideram. Em segundo lugar, apresentar-se-á um esboço para um tratado da enunciação de objetivos acionais numa gramática comunicativa do português.
AI-driven risk estimation: a GPT-based approach to news monitoring for manufacturing resilience
(2026)
In today’s rapidly evolving commercial landscape, manufacturing enterprises face significant challenges in maintaining resilience amid disruptions such as pandemics, natural disasters, and geopolitical conflicts. To address these challenges, we introduce a novel GPT-based early detection tool designed for real-time supply chain risk assessment. This system integrates proprietary company data, including supply chain portfolios, with publicly available information, such as news articles, to estimate risk scores for respective supply chains, thereby enhancing decision-making processes. Leveraging advanced machine learning techniques–Generative Pretrained Transformers (GPT), zero-shot learning, and structured outputs–the tool operates locally to ensure data privacy and minimize information leakage. Utilizing the "news-please" crawler and the "Llama 3.1" GPT model, the system continuously monitors selected media sources, providing timely risk assessments. Our research demonstrates the tool’s potential to enhance proactive risk management in supply chains, validated through testing on both real and augmented datasets. By evaluating four exemplary supply chains, we characterize the tool’s capability to support decision-making in unpredictable global environments. The results indicate that, while the system occasionally exhibits oversensitivity, it consistently aids in identifying critical events that may impact supply chain operations. Future developments will focus on refining the tool’s accuracy and expanding its applications, particularly in monitoring regulatory changes.
Background: The use of generative AI, as represented by ChatGPT, holds promising potential for nursing education. This manifests itself in various areas, including personalized learning, simulation training and teaching process support. However, its integration requires careful consideration of ethical implications, adaptation of curricula and a high level of digital competence on the part of teachers. Only in this way can potential risks, such as the distortion of knowledge, bias and educational inequalities, be avoided.
Methods: Relevant publications were identified between 2019 and 2025 as part of a comprehensive literature search in the specialist databases PubMed, Embase, CINAHL and Scopus. The search was conducted using combined search terms that included the terms “generative AI”, “ChatGPT” and “nursing”. After removing duplicates and screening (PRISMA-guided), 140 full texts were analysed and divided into two publications. This rapid overview focuses on the topic of generative AI in nursing education.
Results: As part of the analysis of the included studies, five thematic areas were identified, which were divided into the categories of nursing education, competence development and nursing skills, implementation possibilities, examination quality and ethical considerations, and evaluated. A key theme is the dual potential of this technology: it can enrich learning through features such as virtual tutors and improved exam preparation, but it also requires critical consideration of ethical issues such as plagiarism, data bias and the need for human oversight.
Outlook: In this context, the conclusion emphasises the urgent need to adapt curricula and provide targeted further training for teachers so that GenAI can be used responsibly and effectively—rather than, as is often the case at present, by banning it altogether.
