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Branching ratios for Higgs-mixed scalars at the GeV scale from hadronisation models with conservation laws
No full textWe investigate the decay modes of a CP-even scalar boson that mixes with the Standard Model Higgs boson, focusing on the mass range between 2 GeV and . Starting from a higher-order perturbative calculation of the inclusive decays and , we employ a hadronisation model to obtain predictions for individual hadronic final states. Our hadronisation model is based on the Herwig cluster model, but incorporates various conservation laws to determine the allowed final states and their respective weights. The model includes two tunable parameters, which we determine using dispersion relation results at GeV, enabling extrapolation to higher masses. Our predictions show that two-particle hadronic final states like and dominate over for near 2 GeV, suggesting promising targets for future experimental searches
Phenomenology of a Kinetic Higgs Portal
No full textWe explore the phenomenological consequences of non-minimal hidden sector interactions on observable correlations in the Higgs sector, mediated through the -symmetric Higgs portal. Particular attention is given to non-standard momentum dependencies of the hidden sector scalar, which arise naturally in an effective field theory (EFT) framework. We demonstrate that perturbatively reliable constraints can be derived from four-top quark production data and precision measurements of Higgs couplings. These constraints are especially relevant in parameter regions where destructive interference suppresses invisible Higgs decays to light exotic scalars, keeping them within experimentally allowed limits. Finally, we discuss the implications of such hidden sector interactions for the thermal history of the universe. We show that non-standard momentum dependencies open up the Higgs portal to account for the observed dark matter relic abundance whilst evading current direct detection constraints. They can also be probed at the (HL-)LHC and, ultimately, at future lepton colliders such as a FCC-ee
A self-sustainable service assembly for decentralized computing environments
No full textThe landscape of modern computing systems is shifting towards architectures built by combining available services under the “everything as a service” paradigm. These architectures are deployed on distributed cloud-edge infrastructures, aiming to provide innovative services to a wide range of users. However, it is crucial for these systems to address environmental sustainability concerns. This poses challenges in operating such systems in open, dynamic, and uncertain environments while minimizing their energy consumption. To tackle these challenges, we propose a decentralized service assembly approach that ensures the assembly is energetically self-sustainable by relying on locally harvested and stored energy. In our contribution, we introduce a general service selection template that enables the derivation of different selection policies. These policies guide the construction and maintenance of the service assembly. To evaluate their effectiveness in meeting the sustainability requirements, we conduct a comprehensive set of simulation experiments, providing valuable insights
Mitigation strategies for confidentiality violations in software architecture using ranked feature importance
No full textA quality attribute like confidentiality is critical to trustworthy software but unfortunately, very challenging to
ensure. This is because modern software systems are complex and interconnected. Architecture-based confiden-
tiality analysis enables the early detection of violations, helping to mitigate risks before deployment. However,
uncertainty in software systems and their environments complicates precise and comprehensive architectural
analysis. Additionally, the complexity of software models and the exponential growth of uncertainty scenarios
pose significant challenges for automated mitigation, often leaving software architects to resolve confidentiality
violations manually, a process that is both time-intensive and error-prone.
In this paper, we extend our machine-learning-based approach to mitigate confidentiality violations. Specif-
ically, we introduce a novel mitigation strategy inspired by TCP Congestion Control, as well as a strategy that
capitalizes on clustering techniques to dynamically adjust batch sizes. Our evaluation on three real-world soft-
ware architectures demonstrates that our extended approach can mitigate confidentiality violations while out-
performing the state-of-the-art. Whereas previously the upper limit was 60 times runtime reduction, now we
achieve 2298 times reduction, with the median being an elevenfold reduction. Our statistical analysis confirms
that the added TCP-inspired strategy is significantly cheaper than the state-of-the-art baseline (Friedman test
= .025 and Nemenyi post hoc test = .039), while also having a strong practical impact (Kendall’s W = 0.721).
This extended work deepens our understanding of the nature of uncertainty and also of the techniques optimally
suited to mitigating the violations caused by uncertainties. It takes us one step closer to designing trustworthier
systems
Transdisziplinäre Nachhaltigkeitsbewertung am Beispiel nachhaltiger Nahrungsmittelversorgungsketten
No full textSpatiotemporal scenarios of socioeconomic futures in Germany
No full textSocioeconomic development influences both the drivers and consequences of climate change, but many scenario applications still rely on highly aggregated indicators such as GDP and population, which mask regional diversity. This study develops spatially explicit socioeconomic scenarios for Germany to support climate action and land-use planning with greater detail and contextual relevance. Using a mixed-methods framework, we integrate historical trend analysis, participatory scenario building, and quantitative projection to generate annual trajectories of key indicators at district level from 2020 to 2100. The indicators cover human, social, financial, and manufactured capital, including demographic dynamics, education, income, employment, inequality, and social cohesion. We analyse the dataset with correlation and clustering methods to explore interdependencies and to identify distinct regional development pathways. Results highlight persistent associations between income, education, and life expectancy, but also scenario-specific changes in the relations between inequality, employment, and urbanisation. Strong east–west disparities and urban–rural contrasts remain across all scenarios, while a sufficiency-oriented pathway demonstrates that wellbeing gains can occur without economic growth. By providing high-resolution, multidimensional socioeconomic scenarios, this study enhances integrated climate–land modelling and informs the design of regionally adaptive and socially equitable climate policies under multiple plausible futures
Highly-cyclable Na-ion battery exploiting a nanostructured tin-carbon anode, layered-oxide P3/P2 cathode and a glyme-based electrolyte
No full textAlternative materials to (purely) carbon-based anodes could enhance the energy density of sodium-ion batteries, and thus favor their complementarity to lithium-ion batteries. This work provides a viable setup of Na-ion cells
combining a P3/P2 sodium-deficient layered cathode and a tin-carbon Na-alloying anode with a glyme-based electrolyte. Galvanostatic cycling in sodium half-cells of the water-processed alloying anode with sodium car-boxymethyl cellulose (CMC) binder shows a maximum capacity of ~260 mAh g, a capacity retention exceeding 70 % after 150 cycles, and an average Coulombic efficiency over 99 %. The multi-metal cathode evidences a great cycling stability over 100 cycles, with average Coulombic efficiency between 99.5 and 99.6 % as favored by the presence of Al ions in its structure. Full Na-ion batteries exploiting ad hoc chemically-sodiated tin-based anode and sodium-deficient layered cathode operate with average working voltage of 3 V, and maximum capacity of 120 mAh g retained for 95 % over 100 cycles in the best experimental setup. The rationally designed full-cell reaches theoretical energy density between 310 and 250 Wh kg as referred to the cathode weight
Process model adaptation for the flexible operation of a power-to-methanol plant
No full textDue to the increasing share of renewable energies, the flexible operation of industrial processes is becoming increasingly important. To ensure efficient operation with methods like optimal production planning, process models are necessary. As most of these processes change their characteristics over time due to aging and wear and tear, these process models must also be adapted over time. There are many possible methods for this, but they are often only suitable for certain processes or process models. This paper investigates the adaptation of characteristic maps for industrial processes using the example of a power-tomethanol process. A novel method is developed, which firstly adapts the initial characteristic maps created from simulation data and continuously adapts the characteristic maps due to drift caused by changes in the characteristics of the process. The aim is to adapt the system as quickly as possible with as little data as possible and, at the same time, ensure transferability to other industrial processes without much effort. The results show a significantly faster adaptation of the maps and a lower error when using the presented algorithm
