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Foundational Components for B2B Data Sharing Using the Solid Protocol
No full textThis article introduces foundational components for decentralized B2B data sharing based on the Solid Protocol, emphasizing data sovereignty, security, and interoperability.
These components are: (1) Authorization App (AuthApp) -- Facilitating granular control and compliance in access granting and revocation processes; (2) Rights Delegation Proxy (RDP) -- Supporting controlled delegation of rights, enabling natural persons to act on behalf of organizations while ensuring privacy and traceability;
(3) Data Provisioning Proxy (DPP) -- Allowing seamless and secure data provisioning across organizations while masking the identity of upstream data sources to protect business interests.
The components enable the creation of end-to-end, standards-based, flexible data value chains.
We validate their applicability through a real-world financial services use case involving loan processing, which illustrates data sharing and protection challenges in B2B ecosystems
Design, synthesis, antiproliferative assessments, and computational studies of new quinolin-2(1H)-ones as dual EGFR/HER-2 inhibitors (vol 13, 1638489, 2025)
No full textReplication Data for: Activity Boost for Cobalt – Selectivity Shift and Activation during CO2 Methanation by Carbon Nitride modified Al2O3 Support
No full textThe revised German guideline on the monitoring for intakes of radionuclides
No full textIn 2025, the guideline for the realisation of monitoring of occupational intakes of radionuclides (internal monitoring) in Germany was revised. For this purpose, an expert workgroup was mandated to consider the amended German radiation protection legislation, amended international standards and recommendations as well as other recent developments in the subject area. The methodology of the revised guideline for the calculation of the likely committed effective dose based on the handled activity and incorporation factors adapts international recommendations and standards. However, the definitions and values of the subfactors from which the incorporation factors are calculated deviate from international recommendations, for example the physical form safety factor considers the volume or mass of the handled radioactive material. For applications in nuclear medicine, specific incorporation factors based on recent literature are tabulated. Regarding the monitoring of persons of childbearing potential, an assessment of the equivalent dose for the uterus and if required a monthly monitoring are prescribed. Quality assurance of approved monitoring services is based optionally on accreditation or on audits by public authorities. For workplace monitoring, technical requirements, in particular quality-assurance procedures, are also specified. Regarding the dose assessment, a reference method and several individual methods are described, with the investigation threshold for changing to individual methods corresponding to an effective dose of 6 mSv during the calendar year. For the reference method, standard assumptions (inhalation, AMAD 5 μm for workplaces, 1 μm for emergency workers with environmental exposure) are applied
The evolution of cheaper workers facilitated larger societies and accelerated diversification in ants
No full textTrade-offs between quantity and quality are common in the organization and evolution of biological, technological, and economic systems. In social insects, shifts from solitary organisms to complex societies bring this dilemma to the colony scale: producing fewer robust units or many cheaper ones. We investigate how cuticle investment, a major nutritional cost, shaped the evolution of ant societies and diversification. Using a computer vision approach on three-dimensional x-ray microtomography scans of 880 specimens from 507 species, we show that larger colonies were facilitated by reducing exoskeleton investment rather than miniaturizing workers. Reduced cuticle investment was associated with accelerated diversification rates in ants, whereas other candidates—colony size and worker size—did not correlate with diversification. Diet and climate had measurable but secondary effects on cuticle investment. Our results support a hypothesis whereby evolving cheaper but more numerous units through reduced investment in structural tissues was a strategic trend in the evolution and diversification of complex insect societies
Distorting the top resonance with effective interactions
No full textInterference effects in effective field theory (EFT) analyses can significantly distort sensitivity expectations, leaving subtle yet distinct signatures in the reconstruction of final states crucial for limit setting around Standard Model predictions. Using the specific example of four-fermion operators in top-quark pair production at the Large Hadron Collider (LHC), we provide a detailed quantitative assessment of these resonance distortions. We explore how continuum four-fermion interactions affect the resonance shapes, creating potential tensions between the high-statistics resonance regions and rare, high momentum-transfer continuum excesses. Our findings indicate that, although four-fermion interactions do modify the on-shell region comparably to continuum enhancements, current experimental strategies at the high-luminosity LHC are unlikely to capture these subtle interference-induced distortions. Nonetheless, such effects could become critical for precision analyses at future lepton colliders, such as the FCC-ee. Our work underscores the importance of resonance-shape measurements as complementary probes in global EFT approaches, guiding robust and self-consistent experimental strategies in ongoing and future high-energy physics programs
Aerosol effects on convective storms under pseudo-global warming conditions: insights from case studies in Germany
No full textGermany is heading toward a future with warmer temperatures due to climate change, and potentially cleaner air from electrification and stricter emission regulations. But how will these evolving environmental conditions affect severe convective storms? This study addresses this question by simulating three supercell events in high resolution using the ICOsahedral Non-hydrostatic (ICON) model. The events observed during the Swabian MOSES field campaigns in 2021 and 2023 are analysed using the pseudo-global warming approach to assess their evolution in a warmer climate. The effects of aerosols on clouds and precipitation were considered using a two-moment microphysics scheme in four temperature rise scenarios, providing detailed insights into the underlying microphysical mechanisms. The results indicate that higher temperatures generally enhance convection, resulting in more intense convective cells, increased precipitation amounts, and more extreme rainfall and hail events. Additionally, warmer conditions increase the likelihood of supercell formation and more intense mesocyclones. In some cases, precipitation increases exceed 7 % K, indicating super-Clausius–Clapeyron scaling and suggesting that additional dynamical and microphysical processes amplify rainfall beyond thermodynamic expectations. An important finding is that hailstones grow larger under lower cloud condensation nuclei (CCN) concentrations, and the area affected by large hail expands by up to 400 %, indicating growing severity and reach of hail events. In addition, lower CCN concentrations are associated with a reduced cold-to-warm rain formation ratio and decreased precipitation efficiency. These aerosol-related effects appear largely independent of temperature, showing consistent patterns across all simulated warming scenarios. These findings indicate the intensity of severe weather events, such as convective storms and flash floods, may increase in a future climate
Fuzzy-Logic and Deep Learning for Environmental Condition-Aware Road Surface Classification
No full textMonitoring states of road surfaces provides valuable information for the planning and controlling vehicles and active vehicle control systems. Classical road monitoring methods are expensive and unsystematic because they require time for measurements. This article proposes an real time system based on weather conditional data and road surface condition data. For this purpose, we collected data with a mobile phone camera on the roads around the campus of the Karlsruhe Institute of Technology. We tested a large number of different image-based deep learning algorithms for road classification. In addition, we used road acceleration data along with road image data for training by using them as images. We compared the performances of acceleration-based and camera image-based approaches. The performances of the simple Alexnet, LeNet, VGG, and Resnet algorithms were compared as deep learning algorithms. For road condition classification, 5 classes were considered: asphalt, damaged asphalt, gravel road, damaged gravel road, pavement road and over 95% accuracy performance was achieved. It is also proposed to use the acceleration or the camera image to classify the road surface according to the weather and the time of day using fuzzy logic
Efficacy of Spiking Neural Networks for Intrusion Detection Systems
No full textProtection against potential threats is paramount in computer networks and requires robust security measures. However, traditional rule-based Intrusion Detection Systems (IDSs) often fail to adapt to dynamic environments, prompting the exploration of innovative solutions such as Neural Network (NN)-based approaches. Previous advances have primarily focused on conventional NNs. Only more recent studies researched the use of Spiking Neural Networks (SNNs) for IDSs; however, they rely on pre- or post-processing steps in their methods, which interferes with the analysis of the actual applicability of SNNs for IDSs. This study aims to overcome this deficit by analyzing the efficacy of SNNs as the sole data processor for IDSs, i.e., without using any non-essential processing outside of the network (”bare” SNNs). Through extensive experimentation on the NSL-KDD, CIC-IDS-2017, CIC-IOT-2023, and AWID3 datasets, we examined various configurations of bare SNNs, alongside conventional NNs, and Recurrent Neural Networks (RNNs) for comparison. The results demonstrate that SNNs can achieve robust performance for IDSs without the pre- or post-processing steps required by other studies. In detail, the bare SNNs achieved higher or similar accuracy for all datasets compared to the other NN models. Furthermore, a comparative analysis reveals a competitive advantage of SNNs over the other NN models in generating fewer false positives. The results of this study suggest that SNN-based IDSs are a promising direction to strengthen network security. However, further research is essential to ensure broader applicability and scalability
Binary-Level Code Injection for Automated Tool Support on the ESP32 Platform
No full textThe analysis and testing of proprietary ESP32 firmware by independent security experts is often hampered by the lack of specialized tools that provide the necessary capabilities and ease of use to effectively support these tasks.
This paper presents a novel binary rewriting framework that addresses this challenge by allowing additional instructions to be inserted into ESP32 firmware without altering its original functionality. The framework leverages two already existing tools, Esptool and ESP32-Image-Parser, to extract firmware from ESP32 devices and convert it to ELF format, simplifying both the implementation of the framework and the development of subsequent tools.
In addition, an assembler has been developed to encode Xtensa assembly instructions without the need for linking the code afterward, facilitating the development of patch code. The framework includes a new patching methodology adapted from x86 patching tactics to the Xtensa architecture. These tactics have been implemented in a binary rewriting framework capable of inserting code at almost arbitrary locations without affecting the original firmware functionality.
A proof of concept tool that inserts fuzzing instrumentation was implemented to demonstrate the utility of the framework. This tool successfully integrates functional coverage information into ESP32 binaries. This framework represents a significant advancement in the tools available for firmware analysis and security testing of ESP32 devices