Background

Traumatic brain injury (TBI) is one of the most important pediatric conditions worldwide. In Germany, hospitalization rates for mild TBI drastically exceed hospitalization rates from similar healthcare systems.

Methods

The SaVeBRAIN.Kids trial will implement and test a novel care pathway (nCP) for evidence-based standardized risk assessment, structured observation in the emergency department (ED) for several hours, and technology-supported home monitoring with the aim to reduce hospitalizations. This non-inferiority multicenter study will be carried out using a cluster-randomized stepped-wedge design, with all centers starting in the control phase and sequentially transitioning to the intervention. Eligible participants (age ≥ 3 months and < 18 years) must present within 48 h of head injury, have minimal symptoms (Glasgow coma scale ≥ 14), and no risk factors for intracranial complications. The co-primary outcomes are the relative risk of hospitalization and the proportion of unplanned re-visits within 72 h of presentation to the ED for ambulatory cases. Secondary outcomes include clinical safety measures, cost-effectiveness, and process evaluation. Based on power calculations (α = 0.05, power = 0.9), 1390 patients will be recruited over 12 months.

Discussion

 The SaVeBRAIN.Kids trial addresses a relevant healthcare challenge by testing a new approach to pediatric mild TBI management in Germany. It aligns with current evidence while accounting for the country’s specific healthcare context. If successful, the intervention could substantially reduce unnecessary hospitalizations and free inpatient capacities while preserving patient safety.

Trial registration

German Clinical Trials Registry (DRKS00035623). Registered on January 21, 2025.

The ARM TrustZone Trusted Execution Environment (TEE) allows software to run in an isolated environment, separated from the untrusted OS. The isolation is based on the Secure Monitor (SM), software running at the most privileged hardware level, with unrestricted access to all system resources, including those of the TEE. Critically, recent research revealed widespread vulnerabilities in SMs that break the TEE isolation and, thus, undermine the very purpose of the TEE. To this end, we present SH3ARS, a fundamental restructuration of the SM firmware that reduces the privileges of the SM and restores ARM TrustZone isolation. SH3ARS modifies the SM to irrevocably relinquish access to memory outside its own address space through a page table latching mechanism. Furthermore, we introduce guards, carefully crafted, gadget-free code sequences, that supervise the context switch to and from the TEE, preventing code-reuse attacks against the TEE – a technique we refer to as SMC-oriented programming. Relying on software changes, SH3ARS ensures TEE isolation guarantees, even if the SM is compromised. We apply SH3ARS to the reference implementation of the SM on ARMv8.0-A, as deployed on millions of devices. We implement a proof of concept on real hardware, and our evaluation shows that the overhead is lower than 6% for most workloads.

Recently, a call was made for the hypertext community to “return to its roots” by re-exploring our interdisciplinary nature, renewing the areas of common interest with the diverse set of researchers that comprise this community. In this paper, we lay out a set of research questions inspired by several research threads that were active in prior iterations of the hypertext community, but have recently slipped from our focus. The developments of the intervening years have in many cases added nuance and depth to these open questions, potentially making them of renewed interest to the present community. We present these questions through the lens of a maximalist vision that places structure front and center of our model of the world, relegating data to second-class status. We follow the implications of this vision to recover a set of open questions that once occupied, and may once again occupy, a large portion of the interest of the hypertext community.

Capturing human poses with monocular RGB cameras seems like an uncomplicated compared to extensive motion capturing systems or calibrated multi camera setups. In our application scenario we are capturing the biomechanics of surfers on standing waves in rivers with GoPro cameras. Thereby we identified detection quality issues of the joints on the backside of the surfers’ bodies in certain situations.

In this paper we are evaluating different camera positions and angles with regard to the recognition quality of these critical body parts. We are describing the application scenario and the resulting requirements for human pose estimation and hardware setup.

Our evaluation results are identifying patterns of quality issues depending on surfers’ stance, skills and motions on the one hand and camera positions and angles on the other hand. We are concluding our paper with further approaches to improve detection quality.

Kaum eine Begrifflichkeit im Kontext des digitalen Marketings dürfte in jüngerer Zeit so viel Aufmerksamkeit erhalten haben, wie die des „Metaverse“. Das damit beschriebene Zusammenwachsen von virtueller und physischer Welt kann neue Geschäftsmodelle ermöglichen und birgt das Potenzial, die Bedingungen an den digitalen Märkten auf den Kopf zu stellen – auch wenn dafür aktuell noch einige Hürden zu überwinden sind. Dabei scheint es angebracht, sich von allzu einseitigen dogmatischen Zielvorstellungen zu lösen. Denn neben teilweise sehr abstrakten Zukunftsvisionen existieren heute bereits zahlreiche realisierte Anwendungsfälle, die der angestrebten Fusion beider Sphären schon sehr nahekommen.

Nicht zuletzt im Entertainment Segment, auch etwa im Kontext des Gamings, ist dabei die Entwicklung besonders weit fortgeschritten. Auf Gaming-Plattformen wie Fortnite, Minecraft oder Roblox treffen sich - virtuell - Millionen von Menschen, natürlich um zu spielen, aber eben auch zunehmend im Rahmen von Events. Innerhalb von in sich geschlossenen virtuellen Welten wie Sandbox oder Decentraland, werden Festivals und Veranstaltungen entsprechend unserer physischen Realität inszeniert, mit dem Ziel, ein möglichst „immersives“, also den analogen Anmutungen und Gewohnheiten entsprechendes Erlebnis zu gewährleisten.

Auch die Musikindustrie hat diese Spielwiese für sich entdeckt: Bereits 2019 trat der US-amerikanische Produzent und DJ Marshmello live, „digital“ auf der Online-Game-Plattform Fortnite auf und spielte ein Konzert vor 10 Millionen „virtuell“ anwesenden Zuschauern. 2020 konnte Travis Scott diesen Rekord auf 27,7 Millionen User ausbauen. Im gleichen Jahr spielte ein virtualisierter Lil Nas X auf Roblox und generierte dabei 33 Millionen unique Viewers (Regan, 2021).  Inzwischen gibt es neben diesen Spiele-Plattformen eine ganze Reihe von virtuellen Event-Locations vom Spezialanbieter Ceek.io – der Konzerte von Bon Jovi und Lady Gaga im Angebot hat – bis hin zu Meta (Facebook), das 2022 anlässlich des Superbowls die Foo Fighters für ein immersives Konzert auf einer Virtual-Reality-Bühne inszenierte (WuV, 2022).

Wenngleich sich derartige virtuelle Auftritte bisher noch auf den musikalischen Mainstream konzentrieren, bietet das Metaversum jedoch auch für die Spielarten des Metals Chancen, sowohl auf der Veranstalter- als auch auf der Künstlerseite. Konzerte und ganze Festivals könnten ins Metaversum verlegt oder durch parallele virtuelle Veranstaltungen begleitet werden. Merchandise und Musik lassen sich sowohl analog als auch (zusätzlich) digital, etwa als NFT, in der virtuellen Sphäre verkaufen. Und auch Backstage- und VIP-Erlebnisse ließen sich, den analogen Gepflogenheiten entsprechend, virtuell abbilden.

Der vorliegende Beitrag widmet sich - auf Basis einer ethnographisch-technischen Analyse - konzeptionell den Chancen, die sich der Veranstaltungs- und Musikbranche und dabei insbesondere dem Metal-Segment sowie den einschlägigen Festivals im Metaversum eröffnen. Konkret soll untersucht werden, welche Innovationspotenziale virtuelle Welten für die Branche bieten, welche Ansätze bereits erfolgreich sind und welche Erfolgsfaktoren für virtuelle Events, den Handel von korrespondierendem Merchandise und für ein nachhaltiges Branding bestehen. Welche Hindernisse sind dabei für ein erfolgreiches Agieren in virtuellen Sphären zu überwinden? Und wie lassen sich die bestehenden Geschäftsmodelle virtuell anreichern oder übertragen? 

Der Rückgriff auf ChatGPT & Co. vereinfacht vieles im Alltag. Es ist unkompliziert und naheliegend, sich insbesondere Texte durch generative KI schreiben zu lassen oder auch Zusammenfassungen von komplexen und langen Artikeln damit zu erstellen, gerade wenn Zeit und Aufmerksamkeit begrenzt sind. Aber werden wir damit nicht zu bequem? Lassen wir unsere grauen Zellen damit verkümmern? Oder verkennen wir mit solchen Fragen das Potenzial der Technologie? Und welche Kompetenzen brauchen wir dann überhaupt in Zukunft noch?

This paper presents an extension of the Subject-oriented Business Process Management (S-BPM) methodology to integrate organizational structures and agent assignment mechanisms. While S-BPM offers a robust framework for modeling business processes based on the Parallel Activity Specification Schema (PASS), it lacks explicit constructs for associating organizational agents—such as humans, machines, or services—with process subjects. To address this gap, we propose an enhancement of the S-BPM methodology by incorporating an external organizational model and an Organizational Query Language (OQL) interface. This extension enables fine-grained specification of process initiation permissions, dynamic assignment of agents to subjects, and direct derivation of access rights to business objects from process models. Our approach leverages an organization model server to evaluate OQL expressions at runtime, supporting context-sensitive and rule-based agent selection. We demonstrate how these enhancements facilitate advanced organizational scenarios, such as context-dependent approval processes and multi-agent assignments. By embedding access rights directly into process models, our solution eliminates the need for traditional access control lists. This integration significantly improves automation, compliance, and maintainability in enterprise environments.

Künstliche Intelligenz ist derzeit in aller Munde – zwischen Innovationshype und wachsender Skepsis. Auf den bpa Care about Innovation days wird Prof. Dr. Andreas Wagener gleich doppelt vertreten sein: mit einer Keynote zum Spannungsfeld zwischen KI und Nachhaltigkeit – sowie einem praxisorientierten Workshop, der Einsteiger den konkreten Umgang mit generativer KI vermittelt.

Im Interview spricht er über Chancen und Herausforderungen der Technologie – und erklärt, warum gerade die Sozialwirtschaft ein besonderes Potenzial hat, von KI zu profitieren.

This paper systematically analyzes 32 offensive Rowhammer papers, including 48 experiments. However, we avoid finger-pointing but identify 6 threats to the validity and relevance of Rowhammer research results and give multiple examples. The threats include small sample sizes, over-estimated attacker capabilities, unrealistic attack scenarios, non-comparability of the results, age and wear of hardware, and sub-optimal attack performance metrics. Additionally, we provide recommendations with detailed justification to the scientific community to mitigate those threats: (1) pre-experimental testing of DIMM integrity, (2) increasing and broadening the DIMM sample size, (3) expanding reproduction studies of published work, (4) defining attacks in real-world conditions and distinguishing them from theoretical ones, (5) publishing DIMM manufacturing data, (6) documenting DIMM wear and, (7) leveraging multiple metrics for bit flip evaluations.

Virtual reality has proven to be a valuable addition in the tool belt of teachers. Immersive learning environments are applied in various settings, including, but not limited to the medical and nursing domain. In this study we present “We care in VR”, a simulation for practicing nursing tasks for care at home, a part of nursing that is currently underrepresented in available VR applications. We investigate how realistic interactions are perceived by end users compared to consistent usage of buttons on the controllers and how they affect the ease of use of the simulation. We conduct an empirical study with 50 participants from three vocational schools of nursing and a university of applied sciences. Results suggest that our simulation already works quite well and is accepted by the target group, but still needs improvement regarding ease of use, especially for users without any previous experience with VR applications.

In der jüngeren Vergangenheit wurde viel über die Auswirkungen der Digitalisierung auf Politik und Demokratie diskutiert. Gleichzeitig schwächt ein globaler Krisenkreislauf das Vertrauen in die politische Handlungsfähigkeit. Dieser Beitrag untersucht, welche Alternativen die digitale Transformation für die gesellschaftliche Willensbildung bieten könnten. Er identifiziert Handlungsfelder digitalisierter Politik auf regionaler wie globaler Ebene und mögliche Lösungsansätze. Technologien wie KI, Distributed-Ledger-Verfahren und Virtual Reality können die Informationsverarbeitung im Vorfeld politischer Entscheidungen und die Stärkung bürgerlicher Partizipation unterstützen. Ferner bergen sie das Potenzial, tiefgreifende Veränderungen in politischen Systemen zu bewirken, indem menschliche Aufgaben an technische Systeme delegiert werden. Dabei ergibt sich ein schmaler Grat zwischen Utopie und Dystopie, wenn Effizienzerwartungen auf Fragen nach demokratischer Legitimation treffen.

This study examines how Large Language Models (LLMs) can reduce biases in text-to-image generation systems by modifying user prompts. We define bias as a model's unfair deviation from population statistics given neutral prompts. Our experiments with Stable Diffusion XL, 3.5 and Flux demonstrate that LLM-modified prompts significantly increase image diversity and reduce bias without the need to change the image generators themselves. While occasionally producing results that diverge from original user intent for elaborate prompts, this approach generally provides more varied interpretations of underspecified requests rather than superficial variations. The method works particularly well for less advanced image generators, though limitations persist for certain contexts like disability representation. All prompts and generated images are available at https://iisys-hof.github.io/llm-prompt-img-gen/

This paper considers three fundamental approaches to software development, namely manual coding, modeldriven software engineering, and code generation by large language models. All of these approaches have their individual pros and cons, motivating the desire for an integrated approach. We present MoProCo, a technical solution to integrate the three approaches into a single tool chain, allowing the developer to split a software engineering task into modeling, prompting or coding sub-tasks. From a single input file consisting of static model structure, natural language prompts and/or source code fragments, Java source code is generated using a two-stage approach. A case study demonstrates that the MoProCo approach combines the desirable properties of the three development approaches by offering the appropriate level of abstraction, determinism, and dynamism for each specific software engineering sub-task.

Similar to LLMs, the development of vision language models is mainly driven by English datasets and models trained in English and Chinese language, whereas support for other languages, even those considered high-resource languages such as German, remains significantly weaker. In this work we present an analysis of open-weight VLMs on factual knowledge in the German and English language. We disentangle the image-related aspects from the textual ones by analyzing accuracy with jury-as-a-judge in both prompt languages and images from German and international contexts. We found that for celebrities and sights, VLMs struggle because they are lacking visual cognition of German image contents. For animals and plants, the tested models can often correctly identify the image contents according to the scientific name or English common name but fail in German language. Cars and supermarket products were identified equally well in English and German images across both prompt languages.