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Function detection is a well-known problem in binary analysis. While prior work has focused on Linux/ELF, Windows/PE binaries have only partially been considered. This paper introduces FuncPEval, a dataset for Windows x86 and x64 PE files, featuring Chromium and the Conti ransomware, along with ground truth data for 1,092,820 function starts. Utilizing FuncPEval, we evaluate five heuristics-based (Ghidra, IDA, Nucleus, rev.ng, SMDA) and three machine-learning-based (DeepDi, RNN, XDA) function start detection tools. Among these, IDA achieves the highest F1-score (98.44%) for Chromium x64, while DeepDi closely follows (97%) but stands out as the fastest. Towards explainability, we examine the impact of padding between functions on the detection results, finding all tested tools, except rev.ng, are susceptible to randomized padding. The randomized padding significantly diminishes the effectiveness of the RNN, XDA, and Nucleus. Among the learning-based tools, DeepDi exhibits the least sensitivity, while Nucleus is the most adversely affected among the non-learning-based tools.
Virtual Machine Introspection (VMI) is a powerful technology used to detect and analyze malicious software inside Virtual Machines (VMs) from the outside. Asynchronous access to the VM’s memory can be insufficient for efficient monitoring of what is happening inside of a VM. Active VMI introduces breakpoints to intercept VM execution at relevant points. Especially for frequently visited breakpoints, and even more so for production systems, it is crucial to keep performance overhead as low as possible. In this paper, we present an empirical study that compares the performance of four VMI breakpoint-implementation variants—EPT switching (SLAT view switching) with and without fast single-stepping acceleration, instruction repair, and instruction emulation—from two VMI applications (DRAKVUF, SmartVMI) with the XEN hypervisor on 20 Intel Core i processors ranging from the fourth to the thirteenth generation. Instruction emulation was the fastest method across all 20 tested platforms. Modern processors such as the Intel Core i7 12700H and Intel Core i9 13900HX achieved median breakpoint-processing times as low as 15 µs for the emulation mechanism. The slowest method was instruction repair, followed by EPT switching and EPT switching with FSS. The order was the same for all measurements, indicating that this is a strong and generalizable result.
In dieser Arbeit wird der Einsatz von Dark LLMs zur Durchführung von OSINT-Recherchen im Rahmen der polizeilichen Gefahrenabwehr und Strafverfolgung in Nordrhein-Westfalen analysiert. Hierfür wird zunächst eine erste wissenschaftliche Definition des Begriffs Dark LLM erstellt. Anschließend werden relevante Dark LLMs vorgestellt, auf deren Gefahren aufmerksam gemacht und geeignete Gegenmaßnahmen erörtert. Danach erfolgt eine rechtliche Einordnung anhand mehrerer Gesetzestexte. Dann wird eine prototypische Entwicklung eines LLMs durchgeführt, welches für OSINT-Recherchen eingesetzt werden kann. Die rechtliche Analyse und die technische Implementierung ergeben, dass der Einsatz eines Dark LLMs in der polizeilichen Arbeit unzulässig ist. Zudem wird ein polizeiliches LLM nach der KI-Verordnung sowohl als Hochrisiko-KI-System als auch als KI-Modell mit allgemeinem Verwendungszweck eingestuft, wodurch sich etliche Pflichten ergeben, die ein LLM in ihrer Funktion einschränken. Trotz dieser Einschränkungen ist ein Einsatz eines solchen LLMs sinnvoll, denn dieses kann viele OSINT-Informationen sekundenschnell zu einer gebündelten Antwort zusammenfassen, was die polizeiliche Arbeit erheblich erleichtert. Durch allgemeines OSINT-Training und die Anbindung weiterer OSINT-Quellen kann die Qualität der Antwort deutlich verbessert werden.
Thermal 360° micro drone: Operational exercise under a fire roller at the Dortmund fire house
(2024)
The 360° video shows an operational exercise of our new 360° + thermal camera video mini drone (18x18x18 cm) in the fire house in Dortmund. The thermal video is overlaid with the 360° video. The exercise was also accompanied by WDR (https://www.ardmediathek.de/video/wdr-dok/unser-leben-mit-ki-wie-kuenstliche-intelligenz-unsere-arbeit-revolutioniert/wdr/Y3JpZDovL3dkci5kZS9CZWl0cmFnLXNvcGhvcmEtODRjYWI5NjQtYjAxYS00NjdiLThjODgtYzViMGVmNTY3OThj from minute 7:16). The winds occurring during the fire are a particular challenge for the small drone and the pilot.
The 360° video shows an operational exercise under smoke of our new 360° + thermal camera video mini drone (18x18x18 cm) in the fire house in Dortmund. The thermal video is overlaid with the 360° video. The exercise was also accompanied by WDR (https://www.ardmediathek.de/video/wdr-dok/unser-leben-mit-ki-wie-kuenstliche-intelligenz-unsere-arbeit-revolutioniert/wdr/Y3JpZDovL3dkci5kZS9CZWl0cmFnLXNvcGhvcmEtODRjYWI5NjQtYjAxYS00NjdiLThjODgtYzViMGVmNTY3OThj from minute 7:16). The winds occurring during the fire are a particular challenge for the small drone and the pilot.
Theoretical Background
Work-Life Blending refers to the dissolution and permeability of boundaries between work and personal life, leading to an integrated experience across these domains. Despite its growing prevalence, a comprehensive conceptualisation of Work-Life-Blending is lacking. Our study addresses this gap by conducting a systematic review to define and clarify the construct, guided by Clark’s (2000) work/family border theory.
Research Question
Our study aimed to identify key factors and dimensions of Work-Life Blending, leading to a holistic conceptualisation. Specifically, our review seeks to answer: What are the key factors and dimensions of Work-Life-Blending, and how can they be integrated into a unified concept and definition? We aim to review the current state of knowledge, define and clarify the concept, and propose a future research agenda.
Methodology
Following PRISMA guidelines (Liberati et al., 2009; Moher et al., 2009), we analysed 51 relevant articles from an initial pool of 1,400 references. A systematic review approach was used to synthesise existing literature and identify the main factors and dimensions associated with Work-Life Blending.
Findings
Our findings revealed a diverse and multifaceted field, structured using Clark’s (2000) key concepts. This framework provided deeper insights into the complex nature of the topic, highlighting significant diversification in the studies.
Discussion and Implications
The study provides a strong foundation for further research on Work-Life Blending. By establishing a classification of key determinants, we offer a comprehensive framework for future studies, e.g., to explore which lifestyle principles can enhance work-life integration and address the challenges of modern work arrangements.
References
Clark, S. C. (2000). Work/family border theory: A new theory of work/family balance. Human Relations, 53(6), 747-770.
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P. & Moher, D. (2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Journal of clinical epidemiology, 62(10), e1-e34.
Diese systematische Übersichtsarbeit bewertet die Wirksamkeit von Mentalem Imaginationstraining (engl. Mental Imagery Training, MIT) zur Leistungssteigerung und Stressbewältigung für Hochrisikoberufe wie Polizeibeamten und Feuerwehrleuten. MIT, eine kognitive Technik zur mentalen Visualisierung von Aufgaben und Einsatzszenarien, wird auf ihr Potenzial hin untersucht, psychomotorische Fähigkeiten zu verbessern und stressbedingte Gesundheitsprobleme in extrem anspruchsvollen Einsatzfeldern zu reduzieren. Mit dem Job Demands-Resources (JD-R) Modell als theoretischem Rahmen untersucht die Arbeit, wie MIT als Ressource zur Minderung der schädlichen Effekte hoher beruflicher Anforderungen beitragen kann, indem sie berufsbezogene und persönliche Ressourcen stärkt. Eine umfassende Literatursuche gemäß den PRISMA-Richtlinien identifizierte zehn relevante Studien. Diese Studien belegen, dass MIT signifikant zur Stressreduktion, zur Erhöhung der Resilienz und zur Verbesserung der Aufgabenbewältigung in komplexen und fehleranfälligen Einsatzsituationen beitragen kann. Insbesondere zeigt MIT Potenzial für einen prophylaktischen Ansatz zur Prävention stressbedingter Gesundheitsprobleme sowie zur Steigerung der operativen Effizienz. Trotz dieser positiven Befunde sind weitere Forschungen notwendig, um die spezifischen Effekte von MIT im Vergleich zu anderen Stressbewältigungsmaßnahmen zu isolieren und die optimale Umsetzung in Trainingsprogrammen für Hochrisikoberufe zu fördern. Die Ergebnisse deuten auf praktische Anwendungen von MIT in strukturierten Trainingsumgebungen hin, um das Wohlbefinden und die Leistung in stressintensiven Berufen nachhaltig zu verbessern.
Comparative Analysis of Chemical Structure String Representations for Neural Machine Translation
(2025)
In this work, we present a comparative analysis of SMILES, DeepSMILES, and SELFIES string representations for chemical struc-tures in neural machine translation tasks in cheminformatics. Using transformer-based models, we systematically evaluated their effective-ness in translating between these representations and the correspond-ing linguistic IUPAC nomenclature. The experimental results demon-strate comparable performance for all three string representations, with SMILES achieving a marginally higher accuracy (99.30% with stereo-chemical information, 99.21% without) compared to its alternatives. In scaling experiments with 1, 10, and 50 million compounds, the perfor-mance differences remained small, though the performance gap narrowed with larger datasets. These findings suggest that researchers can con-fidently continue using SMILES for neural machine translation tasks with transformers, which benefits from their extensive support in exist-ing chemical libraries, tools, and databases, rather than adopting newer representations. This work has a significant impact on developing more efficient chemical language models in drug discovery, material science, and chemical database curation.
The exponential growth of chemical literature necessitates the development of automated tools for extracting and curating molecular information from unstructured scientific publications into open-access chemical databases. Current optical chemical structure recognition (OCSR) and named entity recognition solutions operate in isolation, which limits their scalability for comprehensive literature curation. Here we present MARCUS (Molecular Annotation and Recognition for Curating Unravelled Structures), a tool to aid curators in performing literature curation in the field of natural products. This integrated web-based platform combines automated text annotation, multi-engine OCSR, and direct submission capabilities to the COCONUT database. MARCUS employs a fine-tuned GPT-4 model to extract chemical entities and utilises an ensemble approach integrating DECIMER, MolNexTR, and MolScribe for structure recognition. The platform aims to streamline the data extraction workflow from PDF upload to database submission, significantly reducing curation time. MARCUS bridges the gap between unstructured chemical literature and machine-actionable databases, enabling FAIR data principles and facilitating AI-driven chemical discovery. Through open-source code, accessible models, and comprehensive documentation, the web application enhances accessibility and promotes community-driven development. This approach facilitates unrestricted use and encourages the collaborative advancement of automated chemical literature curation tools. We dedicate MARCUS to Dr Marcus Ennis, the longest-serving curator of the ChEBI database, on the occasion of his 75th birthday.
Electrodeposited Mo-rich NiMo catalysts offer enhanced catalytic activity for the alkaline hydrogen evolution reaction (HER) and provide an electrically conductive, binder-free substrate connection, making them promising catalysts for green hydrogen production. However, creating Mo-rich deposits is challenging, as the codeposition process typically favors Ni. Optimal deposition conditions for Mo-rich NiMo catalysts remain insufficiently explored. This article investigates Mo-rich NiMo electrodeposition from an ammonia-free citrate bath using NaSO4 as a chlorine-free support electrolyte. The effects of the deposition parameters, 1) sodium molybdate concentration in the electrolyte, 2) deposition current density, and 3) enhanced mass transport via working electrode rotation on the alkaline HER activity, were studied. The electrodeposits, containing 44–66 wt% Mo, exhibited increased surface area due to a rough, cracked morphology and variable oxygen content of the catalyst. The oxygen content was linked to HER activity, revealing an inhibiting effect. The lowest overpotential of 118 mV at −10 mA cm−2 for the alkaline HER was achieved using an electrolyte with 0.02 mol L−1 sodium molybdate, a deposition current density of 600 mA cm−2, without electrode rotation. Respective samples combined a favorable Ni:Mo ratio comprising 56 wt% Mo content with increased surface area and low oxygen content.

