Search Results (108)

Machine learning-based systems are increasingly deployed in high-stakes domains, such as healthcare, finance, law, and e-commerce, where their predictions directly influence critical decisions. Although these systems offer powerful data-driven support, they also introduce serious concerns related to fairness, bias, and discrimination. As a result, detecting and addressing unfairness in machine learning software has become a central research challenge. This study presents a systematic mapping of research on software unfairness detection in machine learning systems, with the aim of consolidating existing fairness definitions, identifying major problem types, examining testing approaches, reviewing commonly used datasets, and highlighting open research gaps. A structured search was conducted across five major digital libraries and additional sources, covering publications from 2010 to 2025. From 1805 initially identified records, 67 primary studies met the inclusion and quality assessment criteria. The findings show that research activity has grown significantly since 2019, reaching a peak in 2022. Most studies were published in conference proceedings, accounting for 52% of the primary studies, followed by journals and workshop proceedings, which accounted for 42% and 6% of the primary studies. The literature encompasses multiple research themes, with 36% of the primary studies focusing on the analysis of existing fairness methods, 22% addressing bias mitigation strategies, 30% investigating testing techniques, and 12% proposing or evaluating evaluation frameworks. Fairness testing was conducted across multiple testing levels, including unit, integration, and system testing. Integration-level testing was the most prevalent, accounting for approximately 37.9% of the studies, followed by system-level testing at 27.3% and unit-level testing at 12.1%. Additionally, 22.7% of the studies applied fairness testing across more than one testing level. Frequently used datasets included COMPAS, Adult Census Income, and German Credit. Widely adopted tools, such as IBM AI Fairness 360, Themis, and Aequitas, were also identified. Overall, the systematic mapping study (SMS) highlights the progress made in fairness research while emphasizing the need for stronger integration of fairness into practical machine learning development. Full article

The smart grid concept is based on the full integration of different types of energy sources and intelligent devices. Due to the short- and long-term volatility of these sources, new flexibility measures are necessary to ensure the smart grid operates stably and reliably. One option is to convert renewable energy into hydrogen, especially during periods of generation overcapacity, in order that the hydrogen that is produced can be stored effectively and used “just in time” to stabilize the power system by undergoing a reverse conversion process in gas turbines or fuel cells which then supply power to the network. On the other hand, in order to achieve a sustainable general energy system (GES), it is necessary to replace other forms of fossil energy use, such as that used for heating and other industrial processes. Research indicates that a comprehensive hydrogen supply infrastructure is required. This infrastructure would include electrolyzers, conversion stations, pipelines, storage facilities, and hydrogen gas turbines and/or fuel cell power stations. Some studies in Germany suggest that the existing gas infrastructure could be used for this purpose. Further, nuclear and coal power plants are not considered reserve power plants (as in the German case), and an additional 20–30 GW of generation capacity in H₂-operated gas turbines and strong H₂ transportation infrastructure will be required over the next 10 years. The novelty of the approach presented in this article lies in the development of a unified modeling framework that enables the simultaneous and coherent representation of both economic and technical aspects of hydrogen production systems which will be used for planning and pre-decision making. From the technical perspective, the model, based on the black box approach, captures the key operational characteristics of hydrogen production, including energy consumption, system efficiency, and operational constraints. In parallel, the economic layer incorporates capital expenditures (CAPEX), operational expenditures (OPEX), and cost-related performance indicators, allowing for a direct linkage between technical operation and economic outcomes. This paper describes the systematic transformation from today’s power system to one that includes a hydrogen economy, with a particular focus on practical experiences and developments, especially in the German energy system. It discusses the components of this new system in depth, focusing on current challenges and applications. Some scaled current applications demonstrate the state of the art in this area, including not only technical requirements (reliability, risks) and possibilities, but also economic aspects (cost, business models, impact factors). Full article

Germany’s energy transition to a higher share of renewable energy sources (RESs) is characterized by decentralization, with citizens, cooperatives, SMEs, and municipalities playing a central role. As of early 2025, private individuals own a significant share of renewable energy installations, particularly PV panels, which corresponds to approximately half of the total installed PV power. This trend is driven by physical, technological, and societal factors. Technological advances in battery storage and sector coupling are expected to further decentralize the energy system. Thereby, the electrification of mobility, particularly through electric vehicles (EVs), offers significant storage potential and grid-balancing capabilities via bidirectional charging, although it also introduces challenges, especially for distribution grids during peak loads. Within this work we present a detailed digital twin of the entire distribution grid of the rural German municipality of Wüstenrot. Using grid operator data and transformer measurements, we evaluate strategic expansion scenarios for electromobility, PV and heat pumps based on existing infrastructure and predicted growth in both public and private sectors. A core focus is the intelligent integration of EV charging infrastructure to avoid local overloads and to optimise grid utilisation. Thereby municipally planned and privately driven expansion scenarios are compared, and grid bottlenecks are identified, proposing solutions through charge load management and targeted infrastructure upgrades. This study of Wüstenrot’s low-voltage grid reveals substantial capacity reserves for future integration of heat pumps, electric vehicles (EVs), and photovoltaic systems, supporting the shift to a sustainable energy system. While full-scale expansion would require significant infrastructure investment, mainly due to widespread EV adoption, simple measures like temporary charge load reduction could cut grid stress by up to 51%. Additionally, it is shown that bidirectional charging offers further relief and potential income for EV owners. Full article

This article presents the results of research on the potential development of offshore wind energy in Poland. Wind energy generated in offshore farms is intended to be the second pillar (alongside nuclear power) of Poland’s energy transition, creating the foundation for a zero-emission energy system. The authors constructed a neural network that allowed them to forecast the development of the installed offshore energy capacity for Poland by 2030. For this purpose, the factors that have the greatest impact on the development of wind energy in Poland were identified. This knowledge will facilitate the development of state policy consistent with the Sustainable Development Goals (SDGs) and the European Green Deal. Since Poland currently does not have installed offshore wind energy capacity, Germany was used as a benchmark to train the model. The research results fill the identified gap: to date, forecasts of offshore development in Poland based on a model trained on German data have not been presented in the literature. The research results show that by 2030, Poland can achieve the goals set by the United Nations, the European Union, and the Polish Energy Policy 2040 (PEP2040). The PEP2040 assumes that Poland should have 5.9 GW of energy installed in offshore wind farms in the Baltic Sea by 2030. The forecast indicates that this will be approximately 5.3 GW, with the difference between these values remaining within the model’s margin of error. Full article

Health literacy is crucial for effectively navigating health systems and promoting equitable health outcomes. Multilingual and culturally dual regions present unique challenges for health communication; however, disparities in health literacy within such contexts remain insufficiently explored. This study constitutes the first population-based assessment of health literacy in Alto Adige/South Tyrol, a bilingual province in northern Italy, utilizing the validated HLS-EU-Q16 instrument. A stratified random sample of 2090 residents aged 18 and older was surveyed in 2024. Weighted analyses ensured population representativeness, and scores were analyzed overall, by domain (health care, disease prevention, health promotion), and by language group (German, Italian, multilingual). Regression models incorporating sociodemographic and health-related covariates were employed to identify predictors of health literacy. Half of the population (50.0%) exhibited problematic or inadequate health literacy, with significant differences observed across language groups. Italian speakers demonstrated the highest scores, whereas German speakers scored lowest overall. These differences remained significant after adjustment for age, education, chronic illness, and professional background. Domain-specific analyses revealed distinct patterns: German-speaking respondents scored particularly low in the health promotion domain, while multilingual individuals achieved the highest scores in the prevention and promotion domains. Education level and language background emerged as the strongest predictors of health literacy, while most other covariates exhibited limited explanatory power. The findings underscore the necessity for language-sensitive and domain-specific interventions, highlighting health literacy as both a personal skill and a structural responsibility. Full article

This article examines how gender shapes Holocaust memory through close analyses of two canonical women’s memoirs: Charlotte Delbo’s Auschwitz and After and Ruth Klüger’s Still Alive (2001), a considerably rewritten and culturally reinterpreted version of her earlier German book Weiter leben (1992). Delbo, a French political deportee, and Klüger, an Austrian Jewish survivor, provide testimonies that challenge the male-centered paradigms that have long dominated the Holocaust literature. Although pioneering feminist scholars have shown that women experienced and remembered the Holocaust differently, gender-based analysis remains underused—not only in Holocaust studies but also in broader memory studies, where it is often assumed to be already complete or exhausted. This view of theoretical saturation reflects a Eurocentric bias that equates critical maturity with Western academic prominence, thereby masking the ongoing influence of gender on the production, circulation, and reception of testimony worldwide. Drawing on trauma theory, concepts of multidirectional memory and postmemory, systems theory of media, and ethical approaches to testimony, this article argues that gender is not merely descriptive of Holocaust experience but also constitutive of how trauma is narrated, circulated, and archived. Testimony, as a cultural form, is inherently mediated, and that mediation is fundamentally gendered. This analysis illustrates how Delbo and Klüger create gendered testimonial forms through unique aesthetic strategies. Delbo’s writing focuses on seeing by invoking a feminist aesthetics of voir as imagined and ethical visualization, while Klüger’s narrative emphasizes voice, utilizing rhetorical sharpness and ambivalent narration to challenge postwar silencing. Instead of equating gender with femininity, the article understands gender as a relational and intersectional system—one that includes masculinity, non-binary identities, and structural power differences. It also questions Eurocentric assumptions that feminist critique has been fully explored within memory studies, urging renewed engagement with gender in transnational contexts, such as the often-overlooked testimonies from wartime Shanghai. Ultimately, this article argues that feminist approaches to Holocaust testimony expose the gendered structures of grievability that determine which kinds of suffering are preserved—and which remain unspoken. Full article

The New Space movement led to an exponential increase in the number of the smallest satellites in orbit in the last two decades. The number of required communication channels increased with that as well and revealed the limitations of classical radio frequency channels. Free-space optical communication overcomes these challenges and has been successfully demonstrated, with operational systems in orbit on large and small satellites. The next step is to miniaturize the technology of laser communication to make it usable on CubeSats. Thus, the German Aerospace Center (DLR) developed, together with Tesat-Spacecom GmbH & Co. KG in Backnang, Germany, a highly miniaturized and power-efficient laser terminal, which is based on a potential customer’s use case. OSIRIS4CubeSat uses a new patented design that combines electronics and optomechanics into a single system architecture to achieve a high compactness following the CubeSat standard. Interfaces and software protocols that follow established standards allowed for an easy transition to the industry for a commercial mass market. The successful demonstration of OSIRIS4CubeSat during the PIXL-1 mission proved its capabilities and the advantages of free-space optical communication in the final environment. This paper gives an overview of the system architecture and the development of the single subsystems. The system’s capabilities are verified by the already published in-orbit demonstration results. Full article

This study presents community-specific modeling approaches for simulating power injection from photovoltaic and wind energy systems in a German metropolitan region. Developed within the EMN_SIM project and based on openly accessible datasets, the methods are broadly transferable across Germany. For PV, a cluster-based model groups systems by geographic and technical characteristics, using real weather data to reduce computational effort. Validation against measured specific yields shows strong agreement, confirming energetic accuracy. The wind model operates on a per-turbine basis, integrating technical specifications, land use, and high-resolution wind data. Energetic validation indicates good consistency with Bavarian reference values, while power-based comparisons with selected turbines show reasonable correlation, subject to expected limitations in wind data resolution. The resulting high-resolution generation profiles reveal spatial and temporal patterns valuable for grid planning and targeted policy design. While further validation with additional measurement data could enhance model precision, the current results already offer a robust foundation for urban energy system analyses and future grid integration studies. Full article

Weather-dependent, volatile energy sources, such as wind power and solar photovoltaics (PV), contribute considerably to the German electric energy supply. The current German government aims to substantially increase their market share. Using high-resolution time-series data from energy production and demand measurements, we replicate and analyze scenarios from the “Klimaneutrales Deutschland 2045” (KND2045) study. KND2045 was the basis for the German Government’s 2021 decision to move the abolition of CO₂ emissions from 2050 to 2045. The primary question in KND2045 is whether security of supply can be maintained by relying primarily on an effective duopoly of wind and solar power. We simulate scenarios for 2023, 2030, and 2045 using 15-min time-resolved measurements of wind and solar energy production and demand from 2023 and 2024, incorporating battery and gas storage systems into our model. We assess the overall economic costs for these scenarios. Our calculations demonstrate that the KND2045 scenarios are infeasible, as significant supply gaps persist during dark wind lulls, compromising security of supply. Instead, we propose improvements to these scenarios by incorporating nuclear energy as a backup to address KND2045’s shortcomings. Full article

While digital religion and digital protest can ideally serve the common good, religious nationalist and fundamentalist movements have exploited these tools to disrupt the social fabric and create dangerous political outcomes. This paper examines how religious communicators within Tehreek-e-Labbaik Pakistan (TLP) and Alternative for Germany (AfD) perceive and enact their responsibility within digital spaces, leveraging the power of “networked communities” and the collective identity of the digital “crowd” to advance their agendas of religious fundamentalism and political conservatism. Bypassing traditional media, groups like the AfD and TLP exploit digital religion to build communities, spread propaganda that merges religion with national identity, frame political issues as religious mandates, and mobilize collective action. Campbell’s concept of the “networked community” demonstrates how digital technologies form decentralized, fluid, and global religious communities, distinct from traditional, geographically bound ones. Both the TLP and AfD have tapped into this new digital religious space, shaping and mobilizing political and religious identities across virtual borders. Gerbaudo’s idea of the “digital crowd” complements this by examining how collective action in the digital age reshapes mass mobilization, with social media transforming how political movements operate in the 21st century. Although the AfD’s platform is not overtly religious, the party strategically invokes ethno-Christian identity, framing opposition to Islam and Muslim immigration as a defense of German cultural and Christian values. Similarly, the TLP promotes religious nationalism by advocating for Pakistan’s Islamic identity against secularism and liberalism and calling for strict enforcement of blasphemy laws. Recognizing digital spaces as tools co-opted by religious nationalist movements, this paper explores how communicators in these movements understand their responsibility for the social and long term consequences of their messages. Using Luhmann’s systems theory—where communication is central to social systems—this paper analyzes how the TLP and AfD leverage individuals’ need for purpose and belonging to mobilize them digitally. By crafting emotionally charged experiences, these movements extend their influence beyond virtual spaces and into the broader public sphere. Finally, this paper will reflect on the theological implications of these dynamics both on and offline. How do religious communicators in digital spaces reconcile their theological frameworks with the social impact of their communication? Can digital religious communities be harnessed to foster social cohesion and inclusivity instead of exacerbating social divisions? Through this lens, the paper seeks to deepen our understanding of the intersection between digital religion, political mobilization, and theological responsibility in the digital age. Full article

In the development of more electric aircraft, hydrogen powered fuel cells are one possible solution to progress towards emission reductions in aviation. Currently, there are numerous concepts for integrating fuel cells into future aircraft. The goal of this work was to develop a dynamic fuel cell model for simulations of the powertrain. The Modelica language together with the ThermoFluidStream (TFS) library from the German Aerospace Center (DLR) provided a suitable framework. The fuel cell model takes into account the electrochemical as well as thermodynamic behavior. Hence, the proposed multi-physics model allows simulating the whole fuel cell system, from the hydrogen tank to the electric grid. Under certain simplifications, this enables performing mission simulations of the complete powertrain of future aircraft. As such, polymer electrolyte membrane (PEM) fuel cells and solid oxide fuel cells (SOFC) were considered. The fuel cell models are checked for plausibility in a simple test case against data from the literature. Furthermore, two setups of possible applications are introduced: one for each fuel cell type, which come from two projects. The preliminary control systems of these architectures are presented. Afterwards, the first results of the fuel cell systems are discussed. These results show that the models ran robustly in various environments and operational states. They provided the desired accuracy to predict the behavior of a fuel cell, while maintaining low CPU times and being capable of enabling real-time simulations in the future. Full article

The UK net zero strategy aims to fully decarbonize the power system by 2035, anticipating a 40–60% increase in demand due to the growing electrification of the transport and heating sectors over the next thirteen years. This paper provides a detailed technical and economic analysis of the role of energy storage technologies and transmission lines in balancing the power system amidst large shares of intermittent renewable energy generation. The analysis is conducted using the cost-optimizing energy system modelling framework REMix, developed by the German Aerospace Center (DLR). The obtained results of multiple optimization scenarios indicate that achieving the lowest system cost, with a 73% share of electricity generated by renewable energy sources, is feasible only if planning rules in England and Wales are flexible enough to allow the construction of 53 GW of onshore wind capacity. This flexibility would enable the UK to become a net electricity exporter, assuming an electricity trading market with neighbouring countries. Depending on the scenario, 2.4–11.8 TWh of energy storage supplies an average of 11% of the electricity feed-in, with underground hydrogen storage representing more than 80% of that total capacity. In terms of storage converter capacity, the optimal mix ranges from 32 to 34 GW of lithium-ion batteries, 13 to 22 GW of adiabatic compressed air energy storage, 4 to 24 GW of underground hydrogen storage, and 6 GW of pumped hydro. Decarbonizing the UK power system by 2035 is estimated to cost $37–56 billion USD, with energy storage accounting for 38% of the total system cost. Transmission lines supply 10–17% of the total electricity feed-in, demonstrating that, when coupled with energy storage, it is possible to reduce the installed capacity of conventional power plants by increasing the utilization of remote renewable generation assets and avoiding curtailment during peak generation times. Full article

Given the increasing global emphasis on sustainable energy usage and the rising energy demands of cellular wireless networks, this work seeks an optimal short-term, continuous-time power-procurement schedule to minimize operating expenditure and the carbon footprint of cellular wireless networks equipped with energy-storage capacity, and hybrid energy systems comprising uncertain renewable energy sources. Despite the stochastic nature of wireless fading channels, the network operator must ensure a certain quality-of-service (QoS) constraint with high probability. This probabilistic constraint prevents using the dynamic programming principle to solve the stochastic optimal control problem. This work introduces a novel time-continuous Lagrangian relaxation approach tailored for real-time, near-optimal energy procurement in cellular networks, overcoming tractability problems associated with the probabilistic QoS constraint. The numerical solution procedure includes an efficient upwind finite-difference solver for the Hamilton–Jacobi–Bellman equation corresponding to the relaxed problem, and an effective combination of the limited memory bundle method (LMBM) for handling nonsmooth optimization and the stochastic subgradient method (SSM) to navigate the stochasticity of the dual problem. Numerical results, based on the German power system and daily cellular traffic data, demonstrate the computational efficiency of the proposed numerical approach, providing a near-optimal policy in a practical timeframe. Full article

As wind penetration rates continue to increase, the main challenge faced by operators is how to schedule flexible resources, such as traditional generation and storage, in the future to ensure the safe and stable operation of power grids under multiple uncertainties. In this paper, a security-constrained multi-stage robust dynamic economic dispatch model with storage (SMRDEDS) is proposed to address multiple uncertainties of wind power outputs and N-1 contingencies. Compared to the traditional two-stage robust dynamic economic dispatch model, the proposed multi-stage dispatch model yields sequential operation decisions with uncertainties revealed gradually over time. What is more, a combined two-stage Benders’ decomposition and relaxed approximation–robust dual dynamic programming (RA-RDDP) is proposed to handle the computational issue of multi-stage problems due to large-scale post-contingency constraints and the convergence issue of the stochastic dual dynamic programming (SDDP) algorithm. First, a two-stage Benders’ decomposition algorithm is applied to relax the SMRDEDS model into a master problem and sub-problem. The master problem determines the generator output and storage charge and discharge, and the sub-problem determines the total generation and storage reserve capacity to cover all the generator N-1 contingencies. Second, a relaxed approximation–RDDP algorithm is proposed to solve the multi-stage framework problem. Compared to the traditional SDDP algorithm and RDDP algorithm, the proposed RA-RDDP algorithm uses the inner relaxed approximation and outer approximation methods to approximate the upper and lower bounds of the future cost-to-go function, which overcomes the convergence issue of the traditional SDDP algorithm and solution efficiency of the RDDP algorithm. We tested the proposed algorithm on the IEEE-3 bus, IEEE-118 bus, and the German power system. The simulation results verify the effectiveness of the proposed model and proposed algorithm. Full article

The integration of electromobility with its required charging infrastructures into the existing power grid, which is demanded by politics and society, is an enormous challenge for electrical power grid operators. Especially considering further challenges, such as the electrification of heat supply systems and sector coupling, it is to be expected that the power grid’s capacity will be strongly overstrained. On the other hand, grid expansion is an extremely expensive and time-consuming method of ensuring that the existing grid is not overloaded, and sufficient grid capacity is available. A suitable grid operations management approach can enable comprehensive and grid-serving control of flexibility, especially charging processes. This article presents a cluster-based and incentive-oriented grid operation management concept and describes the integration of the system into the current German regulatory framework. In addition, the structural integration of charging infrastructures for electromobility into a grid-oriented control system is presented. The suitability of grid charges and their dynamization for stimulating grid-oriented behavior is analyzed. Furthermore, the derivation of additional costs arising from the utilization-dependent thermal aging of grid assets and their imputed integration into the incentive system is described. Full article