The 100 most recently published documents
Die BIM-Methode basiert auf dem Austausch von Modellen und Objektdaten. Diese entwickeln sich im Laufe des Bauprojektes weiter und dienen vielen Beteiligten als Grundlage für die eigenen Aufgaben. Daher ist ein eindeutiges und verlässliches Datenmanagement die Basis für eine gelungene Zusammenarbeit. Die dabei erzeugten Daten gehen mittlerweile weit über 3D-Modelle hinaus.
Welche Daten, in welcher Detailtiefe zu welchem Zeitpunkt und in welchem Format vorliegen sollen, ist Gegenstand dieses Buches. Die Modelle und Objektattribute werden vorgestellt und, wo es nötig ist, vertiefend beschrieben. Das dazugehörige Datenmanagement wird anschaulich erklärt. Abgerundet wird das Buch mit Tipps zur richtigen Softwareauswahl und einem Quiz zum Test des eigenen Wissenstand. Die zweite Auflage greift dabei aktuelle Entwicklungen (z. B. IFC4.3 und LOIN) auf und erläutert neue Anforderungen und Inhalte der BIM-Objekte.
Hintergrund
Studierende mit Migrationshintergrund berichten häufiger über ein geringeres Zugehörigkeitsgefühl („sense of belonging“), verbunden mit höherem Stress und erhöhter Abbruchneigung. Trotz dieser Relevanz liegen im deutschsprachigen Raum bislang kaum qualitative Untersuchungen zu diesem Thema vor. Ziel der Studie war es, das subjektive Zugehörigkeitserleben von Studierenden mit Migrationshintergrund zu rekonstruieren und dessen Bedeutung für die mentale Gesundheit zu analysieren.
Methodik
Die Untersuchung folgte einem qualitativ-explorativen, Community-basierten Design. An einer Hochschule für angewandte Wissenschaften im Ruhrgebiet wurden 28 Peer-Interviews mit Studierenden mit Migrationshintergrund geführt. Die Auswertung erfolgte mittels strukturierender qualitativer Inhaltsanalyse nach Kuckartz, theoretisch gerahmt durch die Social-identity-Theorie (Social-cure-Ansatz), den „Social Determinants of Health“-Ansatz und das „Study Demands-Resources“-Modell.
Ergebnisse
Zugehörigkeit erwies sich als zentrale Ressource für psychische Gesundheit. Fehlende Zugehörigkeit war mit emotionaler Erschöpfung, Demotivation und psychosomatischen Symptomen assoziiert, während erlebte Zugehörigkeit als Puffer- und Aktivierungsfaktor wirkte. Hochschulische Kommunikationskultur, soziale Dynamiken unter Studierenden sowie strukturelle Ungleichheiten beeinflussten das Zugehörigkeitserleben maßgeblich.
Schlussfolgerung
Zugehörigkeit stellt eine sozial und institutionell gestaltbare Gesundheitsdeterminante dar. Maßnahmen der Gesundheitsförderung sollten strukturelle, soziale und organisationale Bedingungen in den Blick nehmen, die Zugehörigkeit stärken, etwa durch transparente Regeln, wertschätzende Kommunikation und inklusive Lernumgebungen.
Sensory processing sensitivity (SPS) is characterized by a higher sensitivity to environmental stimuli, both positive and negative. Recent studies have shown two construct facets of SPS, vantage sensitivity (represented by aesthetic sensitivity) and vulnerable sensitivity (which consists of low sensory threshold and ease of excitation) (Pluess & Belsky, 2013), Wyrsch, 2020). Since the seminal publication by Aron and Aron (1997), most empirical studies focused on SPS characteristics in general and especially on the negative consequences of SPS (Greven et al., 2019). However, only a few studies focused on SPS in the organizational context and also targeted the positive effects of SPS. Based on the Job Characteristic model by Hackman and Oldham (1976), we addressed this research gap by investigating the moderating effects of SPS on associations between the job characteristics autonomy and task variety and job satisfaction as an organizational outcome variable. We assumed a positive correlation between job characteristics and job satisfaction and a positive moderating effect of SPS. The survey study results (N = 719) confirm that SPS positively moderates the relationship between autonomy and job satisfaction. However, we also found negative relationships between vulnerable sensitivity and job satisfaction. Regarding task variety, we only found moderating effects for vantage sensitivity. Our findings demonstrate that employees' satisfaction and organizational outcomes could be optimized if modern working environments consider personality traits such as the level of SPS within the workplace.
Human rights violations in global supply chains have been a focus of public discussions for nearly three decades. To address such violations in global supply chains, pressure was put on transnational corporations (TNCs) to use their economic power to prevent such harms from occurring at supplier factories, often located in the Global South. TNCs with well-known brands started to introduce codes of conduct for their suppliers as early as the 1990s. However, this approach was rarely, if ever, addressed or monitored through international or national law. Ensuring socially responsible supply chains was anchored in the voluntary assumption of responsibilities by private corporate actors. The inadequacies of the business-driven soft law approach to improve working conditions at supplier factories and natural resource collection sites drove a shift toward legal regulation. The shift toward national legal regulation consequently established a definitive link between soft and hard international human rights law and national law. The linking of international law to national through human rights due diligence is the focus of this chapter.
This entry discusses the role of sustainability in the law school. It traces the concept of sustainability in law and it argues that, in recent years, ‘Sustainability Law’ has evolved as a new field of law. This view is supported through applying theory on the creation of legal fields. There is an increasing number of regulation (particularly EU Directives) aimed at promoting sustainability and there is a growing number of journal articles as well as law school courses on this issue. There are several longstanding debates in legal modules which already overlap with the three pillars of sustainability (i.e. the economic, environmental and social pillars). Students should be alerted to these links. Finally, the chapter argues that the concept of sustainability should be integrated in modules across the curriculum in law schools as a contribution to UNESCO’s mission to promote Education for Sustainable Development (ESD)
This article discusses the trend towards environmental, social and governance (ESG)-related laws in Germany in the context of Germany’s membership of the European Union (EU). As an EU member state, Germany is subject to a wave of recent directives and regulations that the EU passed as part of its so-called “European Green Deal”. However, Germany also has its own tradition of promoting the goal of sustainability in the law, including company law. The article first distinguishes relevant terminology as some regulations refer to ESG, whereas others to “sustainability”. It then traces the historic development of such laws in German law, including the traditional debate about the interest of the company in German law. This discussion is followed by a case study that critically examines the German Supply Chain Due Diligence Act of 2021 that continues to be subject to heated political discussions. The article demonstrates how ESG has, in recent years, become a compliance issue in Germany that is now a matter of consideration for boards.
Diese Bachelorarbeit erforscht die Einbindung öffentlich zugänglicher künstlicher Intelligenz (KI)-Tools in den Prozess bionischer Innovationen mit dem Ziel, einen sowohl effektiveren als auch einfallsreicheren Ansatz zur Implementierung biologischer Prinzipien in technische Lösungen zu schaffen. Vier Large Language Models – GPT-4.o, Gemini 2.0, Llama 3.3 und Claude 3.5 – werden anhand der Quality, Understandability, Expertise, Safety, and Trust (QUEST)-Methode (basierend auf der Bionikspirale gemäß VDI 6220 Blatt 2) bewertet, wobei Gemini 2.0 die beste Leistung erbringt. In einem prototypischen Versuch wird Gemini 2.0 in Kombination mit NotebookLM und Elicit genutzt, um die Filtrationsmechanismen aquatischer Organismen zu untersuchen. Die Resultate offenbaren, dass KI-Werkzeuge die Effizienz der Literaturrecherche und -analyse steigern und systematisieren. Außerdem werden neuartige Entwürfe für bionische Filtersysteme vorgeschlagen. Die Arbeit hebt die Möglichkeiten von KI-Instrumenten in der Bionik hervor, betont jedoch die zwingende Notwendigkeit menschlichen Fachwissens zur Interpretation, Validierung und Ableitung technischer Konzepte. Grenzen werden durch die eingeschränkte Fähigkeit der KI zur Schaffung biologischer Analogien und das Fehlen standardisierter Schnittstellen bestimmt.
Digitalkompetenz und ein „Growth Mindset“ gelten als begehrte Ressourcen auf der „People Side of Digitization“ – nicht nur im häufig akademisch geprägten Management, sondern auch unter Nachwuchsführungskräften. Wie derartige „Future Skills“ trainiert und vermittelt werden können, wird vor dem Hintergrund des Fachkräftemangels zur Aufgabe von strategischer Bedeutung. Als Hoffnungsträger gelten Weiterbildungsformate. Während Weiterbildung jedoch zur Vervielfältigung von Routinewissen und für Anpassungsqualifizierungen mit dem Ziel der Effizienzsteigerung bewährt ist, sind Möglichkeiten und Grenzen für die Vermittlung von Future Skills weniger erforscht. Vor diesem Hintergrund werden im Rahmen dieses Forschungsberichts Ergebnisse und Erfahrungen aus einer Fallstudie diskutiert. Empirischer Kontext ist die Entwicklung und Evaluation eines Blended-Learning-Weiterbildungsformats „Digitalkompetenz“ für die Zielgruppe Führungskräftenachwuchs. Welche Effekte für Digitalkompetenz sind zu erzielen? Welche Gestaltungsideen kommen in Betracht?
Directed Energy Deposition-Laser (DED-L) enables high-performance coatings through melting and successive powder deposition. Its compositional flexibility suits functionally graded layers that enhance corrosion and wear resistance. This study aimed to improve parameters for producing dense, defect-free, graded Ni- and Fe-based coatings by varying the scanning speed and deposition strategy (monodirectional versus bidirectional, with/without layer rotation), while keeping the power and hatch distance constant. Laser and electron microscopy were used to link parameters to porosity and uniformity. Optimal settings minimized pores, improved interlayer bonding and preserved geometry; inadequate parameters yielded porous, irregular deposits. A bidirectional path with 90° rotation appeared best. Ongoing research activities are needed to assess its properties.
Highlights
What are the main findings?
- Bidirectional samples show fewer pores than samples with monodirectional movement.
- Increasing the scanning speed leads to lower porosity (bidirectional scanning mode with 90°
layer rotation).
- Bidirectional deposition with 90° layer rotation exhibits best quality
What are the implications of the main findings?
- Systematic study of scanning speed and deposition strategy.
- Practical guidance for process improvement of graded metal coatings; properties under evaluation.
- Functionally graded Ni-Fe coatings fabricated by DED-L with tailored microstructures.
The surface of Mercury is highly space weathered, and the products of space weathering are different than on the Moon. Here we simulate the interaction of solar wind ions with the surface of Mercury by implanting low-iron-bearing (∼3 wt% Fe) olivine slices with 4 keV He+ ions both under ambient conditions and at 450 °C during the irradiation. The sample irradiated under ambient conditions shows a ∼140 nm thick partially amorphous layer on top of the grain with high concentrations of bubbles and cavities. However, the sample irradiated at 450 °C has a 110–140 nm thick polycrystalline layer with 1–5 nm sized nanoparticles of metallic iron and no bubbles or cavities. Mg atoms are preferentially sputtered from the ion-damaged layer present on the sample irradiated under ambient conditions, but no difference in composition is seen between the crystalline olivine and the ion-damaged layer in the sample irradiated at 450 °C. In addition, a thin amorphous film deposited on a micro-electromechanical systems–based chip is heated up to 1200 °C in situ inside a transmission electron microscope for a few milliseconds, and it produced nanoparticles of size 5–30 nm. Our results show that solar wind irradiation of low-iron-bearing olivine in the equatorial regions of Mercury will produce nanoparticles of iron whose sizes will be larger than that on the surface of the Moon and that the size will further increase during impacts of dust particles. Solar-wind-implanted He can diffuse out of regolith grains and can be a source of He observed in the exosphere of Mercury.
In supply chain management of port operations querying and visualizing network data often requires complex joins, nested queries and predefined reporting templates, which can hinder exploratory analysis and decision-making. When relational databases become too rigid and cumbersome for transactional processing, we envision an alternative approach using graph data models, provided by transforming entities (e.g. containers, vessels, terminals) into nodes and their relationships (e.g. arrival, loading, handling) into edges. To investigate the potential benefits of transforming relational supply chain data into a graph-based model, we designed and implemented a structured approach that integrated data processing, transformation and performance analysis across both relational and graph databases.
Der Aufsatz untersucht anhand empirischer Daten zu ca. 400 Studierenden wirtschaftsjuristischer Bachelor-Studiengänge an der Westfälischen Hochschule eine Reihe etablierter und neuer Indikatoren für den Studienerfolg. Insbesondere schulnotenbezogene Prädiktoren erweisen sich dabei als nur noch bedingt aussagefähig, andere bekannte (insbes. Motivationslevel) und neue (insbes. Berufsausbildung vor dem Studium) erweisen sich als verlässliche, wenn auch nicht starke Prädiktoren.
We extend the spin-boson model of open quantum systems to the regime of quantum 1/𝑓^𝜂 noise characterized by negative exponents of its spectral distribution. Using the numerically exact time-evolving matrix product operator, we find the dynamic regime diagram, including pseudocoherent dynamics controlled by quantum 1/𝑓^𝜂 noise. We determine the dephasing rate and find for it an empirical formula valid at zero temperature. The bath reorganization energy depends on the infrared bath cutoff frequency, revealing an increased sensitivity of the dephasing on the measurement time of an experiment. Our results apply to a qubit as an elementary building block of a quantum computer and pave the way toward a quantum treatment of low-frequency noise in more complex architectures.
Low pressure capacitively coupled radiofrequency plasmas operated in a mixture of aniline vapor and argon are used for the deposition of thin films on silicon substrates. The influence of the aniline vapor fraction in the gas mixture upon the plasma properties and the characteristics of the deposited thin film is analyzed. Plasmas diagnostics are carried out using mass spectrometry and optical emission spectroscopy and the thin films are characterized by means of Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, and near-edge X-ray absorption fine-structure spectroscopy. Experiments highlight that the use of a low aniline/argon ratio leads to the deposition of an amorphous film whereas high-aniline/argon ratios allow the synthesis of a plasma polymer similar to polyaniline. The properties of such plasmas and the mechanisms involved in the deposition process are discussed in detail.
The design of novel and abundant catalytic materials for electrolysis is crucial for reaching carbon neutrality of the global energy system. A deliberate approach to catalyst design requires both theoretical and experimental knowledge not only of the target reactions but also of the supplementary mechanisms affecting the catalytic activity. In this study, we focus on the interplay of hydrogen mobility and reactivity in the hydrogen evolution reaction catalyst MoS2. We have studied the diffusion of atomic hydrogen and water by means of neutron and X-ray photoelectron spectroscopies combined with classical molecular dynamics simulations. The observed interaction of water with single-crystal MoS2 shows the possibility of intercalation within volume defects, where it can access edge sites of the material. Our surface studies also demonstrate that atomic hydrogen can be inserted into MoS2, where it then occupies various adsorption sites, possibly favoring defect vicinities. The motion of H atoms parallel to the layers of MoS2 is fast with D ≈ 1 × 10−9 m2/s at room temperature and exhibits Brownian diffusion behavior with little dependence on temperature, i.e., with a very low diffusion activation barrier.
In the burgeoning field of quantum computing, the precise design and optimization of quantum pulses are essential for enhancing qubit operation fidelity. This study focuses on refining the pulse engineering techniques for superconducting qubits, employing a detailed analysis of square and Gaussian pulse envelopes under various approximation schemes. We evaluated the effects of coherent errors induced by naive pulse designs. We identified the sources of these errors in the Hamiltonian model’s approximation level. We mitigated these errors through adjustments to the external driving frequency and pulse durations, thus implementing a pulse scheme with stroboscopic error reduction. Our results demonstrate that these refined pulse strategies improve performance and reduce coherent errors. Moreover, the techniques developed herein are applicable across different quantum architectures, such as ion-trap, atomic, and photonic systems.
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 designed for natural product literature curation that integrates COCONUT-aware schema mapping, CIP-based stereochemical validation, and human-in-the-loop structure refinement. 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 a Human-in-the-loop 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.
In this work, a numerical tool is presented to simulate the dynamics of insect wing folding by example of the fan folding of the dermapteran hindwing. The scalability of the system is demonstrated by generalising the mechanical behaviour from the small geometry of the wing to a suitable scale for engineering applications, such as deployable structures for space applications. The tool is written in Python and based on the MuJoCo physics engine. Sections of the anal fan are modelled as a bar-and-hinge model with elastic tendons, allowing a high number of design parameters and fast computation. In light of these advantages, the wing folding and unfolding behaviour is investigated with respect to the tendon’s elastic properties and the actuation of the deformation. Bistability is characterised using a single tendon and the entire fan section. Given the upscaled geometry of the analysed section, the required tendon characteristics to transition between the stable states are identified within a reasonable range for technological transfer towards biomimetic structures modelled after the dermapteran hindwing.
Directed energy deposition–electron beam (DED-EB) additive manufacturing is a highly promising process for the fabrication of titanium components, offering high deposition rates and precise process control under vacuum conditions. However, optimizing the deposition characteristics, such as dimensional accuracy, surface quality, and layer uniformity, remains a key challenge, partly due to the complex dynamics of heat input and melt pool behavior. This study examines the influence of electron beam modulation on these deposition characteristics by systematically varying beam deflection parameters, including frequency and pattern, during the wire-based additive manufacturing of titanium. The effects of beam modulation on wire melting, melt pool stability, layer formation, and overall build geometry were thoroughly evaluated. The results demonstrate that carefully controlled electron beam modulation enables significant improvements in deposition stability, surface finish, and control over geometric features, thereby enhancing process reliability and enabling the production of near-net-shape titanium components. Notably, a parameter set consisting of a circular beam deflection at an oscillation frequency of 500Hz and an overfocus setting of + 40 mA effectively minimized surface ripples and waviness, thereby enhancing process stability and yielding defect-free components. These insights contribute to advancing DED-EB as a viable solution for applications where high geometric accuracy and process efficiency are demanded.
Der Beitrag fokussiert eine strategische Zusammenarbeit von Qualitätsmanagement und Hochschuldidaktik zur Förderung der Lehrqualität beim Einsatz externer Lehrender in der wissenschaftlichen Weiterbildung. Die Hochschuldidaktik unterstützt dabei die Hauptprogrammplanenden und trägt von der Mikro- bis zur Makroebene entscheidend zur Planung und Weiterentwicklung von Lehrkonzepten bei. Externe Lehrende werden hierzu in ein umfassendes Supportsystem eingebunden, das neben einem Grundlagenworkshop und Vernetzungsangeboten auch digitale Tools und KI-gestütztes Lernen umfasst, um ihre Lehre bedarfsorientiert zu optimieren. Dabei agieren sie sowohl als Lehrende als auch als Lernende, was ihre didaktischen Fähigkeiten und das Verständnis der Studierendenperspektive vertieft. Das Angebot zielt dabei gleichermaßen auf eine Steigerung der Motivation sowie der Kompetenz der Lehrenden und ist eingebunden in einen Kreislauf zur iterativen Qualitätsentwicklung.
As the student population becomes increasingly heterogeneous, providing effective feedback is crucial for personalized education. However, human feedback is resource-intensive, while large language models can be unreliable. Our method bridges this gap by offering informative, similarity-based feedback on mathematical inputs. In an experiment with 207 students, we found that this approach encourages engagement, facilitates the completion of harder exercises, and reduces quitting after incorrect inputs. Compared to traditional feedback mechanisms that struggle with unforeseen error patterns, our method increases student perseverance and confidence. By balancing reliability, resources, and robustness, our solution meets the diverse needs of contemporary students. With its potential to enhance self-learning and student outcomes, this research contributes to the growing conversation on personalized education and adaptive learning systems.
The relevance of e-learning for higher education has resulted in a wide variety of online self-learning materials over the last decade like pedagogical agents (PA) or learning games. Regardless of this variety, educators wonder whether they can make use of these tools for their goals and if so, which tool to choose and in which context a specific tool performs best. To do so, the collection and analysis of learning data – referred to as Learning Analytics (LA) – is required. Along with digital learning environments the possibilities of applying LA are growing. Often, LA focuses on data that can easily be quantified: drop-out quota, time or grade performance. To facilitate learning in a more procedural sense, a deeper understanding of learners’ behavior in specific contexts with specific exercise designs is desired. This study therefore focuses on usage patterns. Learners’ movements through three different designs of mathematical exercises – (i) plain exercises, (ii) PA supported and (iii) fantasy game design – are analyzed with Markov chains. The results of an experiment with 503 students inform about which design facilitates what kind of learning. While the PA design lets learners enter more partial solutions, the fantasy game design facilitates exercise repetition.
Leaders’ Psychological Costs and Benefits of Servant Leadership: A Conservation of Resources View
(2025)
Servant leadership is widely recognized for its positive effects on followers, but its impact on leaders' mental health remains understudied. This gap is crucial, as servant leadership might place significant demands on leaders' psychological resources, without sufficient social, psychological, or organizational rewards. Drawing on the Conservation of Resources Theory (COR), we investigate how and when servant leadership affects leaders' mental health, viewing its role not only as resource-depleting but also as resource-generating for leaders, depending on the organizational context. Two cross-sectional studies were conducted using leader self-assessments (N = 101; N = 170). Study 1 focused on the relationship between servant leadership, experienced meaningfulness, emotional exhaustion, and flourishing, emphasizing the resource-generating potential of servant leadership. Study 2, examined the moderating effect of the distributive justice climate (DJC) on the link between servant leadership and emotional exhaustion, exploring the possibility of resource depletion under conditions of low organizational fairness. Results. In Study 1, servant leadership was found to mitigate emotional exhaustion by enhancing experienced meaningfulness at work. Moreover, it fostered leaders' flourishing through the same mechanism, suggesting that servant leadership can be a source of leaders’ well-being. Study 2 demonstrated that DJC moderates the servant leadership–emotional exhaustion relationship. Specifically, when DJC is low, servant leaders are more susceptible to emotional exhaustion, indicating that unfair organizational climates can exacerbate the resource-depleting aspects of servant leadership. Servant leadership has the potential to both reduce and exacerbate emotional exhaustion in leaders. While it generates psychological resources like experienced meaningfulness, which enhances well-being, its effectiveness is influenced by the organizational context. In unjust environments, servant leadership's emotional demands may lead to resource depletion. These findings are in line with COR and highlight the complex impact of servant leadership on the well-being of leaders. Limitations remain to issues of causality.
Purpose – To advance women’s entrepreneurship research,scholarsrequire a clearer understanding of how, and where, researchers have applied the field’s critical theoretical frameworks, as well as how extant studies have shaped the development ofthe frameworks and field of women’s entrepreneurship. This paper addresses this gap by conducting an integrative literature review (ILR) of Brush et al.’s (2009) 5 M framework article and proposes a conceptualization of 5 M framework research alongside future research directions for the field of women’s entrepreneurship.
Design/methodology/approach – Our study utilizes an ILR to analyze how researchers have leveraged the 5 M framework and what this reveals about its development and role in women’s entrepreneurship research. We draw on Scopus and Google Scholar databases to present a comprehensive review of all publications (n 5 944) that cite Brush et al.’s (2009) article (from 2009 to 2023), focusing on those works (n 5 87) which base their methodological or theoretical approach on the 5 M framework.
Findings – Our ILR reveals that research using the 5 M framework can be conceptualized as consisting of four different layers: the specific contributions made by such research to the development of the 5 M framework itself; the key themes and mechanisms within women’s entrepreneurship addressed by this research; the methodological approaches applied; and the empirical contexts in which the framework dimensions have been employed.
Research limitations/implications – Our study identifies pertinent literature gapsin women’s entrepreneurship and provides pathways for diversifying theory-building in the field.
Originality/value – We analyze a prominent theoretical framework in the field of women’s entrepreneurship. Our analysis shows not only pathways for future women’s entrepreneurship research but also the status of the field and how researchers deal with existing frameworks, thus highlighting opportunities to go beyond the status quo.
Sustainability communication as an increasingly circumscribable research field grounds in communication, management and marketing concepts. This chapter focuses on communication of sustainability, sustainable consumption and green claiming and discusses the effects of non-transparent sustainability communication and greenwashing. It specifically presents a study on how the suspicion of greenwashing in green advertising affects attitudes towards the ad and the brand, as well as the purchase intention. The affect transfer hypothesis is used as a model to understand advertising effects in this context. Additionally, this study delves into potential influencing factors on suspicion of greenwashing, such as the type of green advertising and the “lifestyle of health and sustainability” (LOHAS). The research question is addressed through a quantitative experimental online survey. The results demonstrate that the suspicion of greenwashing has a negative effect on attitude towards the ad and on attitude towards the brand, as well as on purchase intention. The chapter therefore offers new insights into one of the critical aspects of strategic sustainable communication and lays the groundwork for future research on “washing” (green, pink, rainbow, etc.) and the need for re-framing sustainability in business-consumer discourses.
Rare vascular diseases such as hereditary haemorrhagic telangiectasia (HHT) represent a big challenge in biomedicine: complex pathomechanisms, limited patient material, and fragmented research communities slow down therapeutic progress. We argue that two elements are pivotal to bypass this problem. First, genuine partnership with patients—ranging from biospecimen donation to agenda setting—can unlock critical resources and align research with real-world needs. Second, molecular intersections between HHT and related pathologies call for coordinated, cross-disease programmes rather than isolated efforts. Recent multi-stakeholder gatherings hosted by patient organisations in Germany and elsewhere, such as the Second Scientific Symposium by the German HHT self-help group (Morbus Osler Selbsthilfe e.V.) in May 2025, have shown that when clinicians, basic scientists from different disciplines, and affected families co-design research questions, novel in vitro models can be generated more accurately, and pragmatic clinical trials emerge. Here, we outline actual opportunities for patient-integrated cellular model systems, shared biobanking, and comparative approaches across vascular malformation syndromes. In our opinion, letting informed and well-organised patient communities assemble such meetings opens unique opportunities twofold: on the one hand, the field can finally break out of its disease-specific silos; on the other hand, the development of novel HHT therapies could be accelerated by learning from progress in related pathologies.
Phishing is an increasing threat to the security of end-users, networks, and organizations. Phishing simulations via email are a widespread tool used to measure user awareness, especially in workplace settings. However, current studies focusing on large-scale analysis of phishing simulations often have issues: The phishing simulations were conducted using a small sample size (mostly one or two organizations), or while many emails are sent, the analysis focuses only on specific companies. This study analyzes phishing simulations conducted over three years at 36 organizations with over 68 000 delivered emails. We compare different dimensions of the organizations where these simulations were conducted, such as the economic sector and departments. Furthermore, we evaluate various dimensions of phishing simulation campaigns, such as detection difficulty and the scenario under which the simulation occurs. Our findings indicate significant disparities in the results, such as the industry sector in which the company operates. Moreover, we find substantial differences between the success rates of varying scenarios used for phishing emails.
Hybrid broadcast broadband television (HbbTV) is an evolving technology that connects linear TV with modern HTML5 applications, delivering extras like games, videos, and online shopping. However, its bidirectional transmission functionality raises privacy concerns, as it introduces new tracking methods for TV channels. While previous studies focused on security issues or user awareness of HbbTV privacy challenges, a detailed examination of the tracking and transparency mechanisms of the HbbTV ecosystem is still missing. This study fills this gap by extensively analyzing these features within the European HbbTV ecosystem, and in particular within German-language TV channels. We monitored more than 350 TV channels for over 400 hours, evaluating 1) prevalent HbbTV tracking methods, 2) consent notice prevalence and user interactions, and 3) privacy policy disclosures. Our findings indicate that the HbbTV tracking system operates independently of the Web, consent notices exploit system constraints to influence users, and privacy policies often do not align with actual data practices.
Steuerschulden als Grund für die Versagung oder Entziehung verwaltungsrechtlicher Erlaubnisse
(2025)
Allgemeines Verwaltungsrecht
(2025)
In vertebrates and plants, dsRNA plays crucial roles as PAMP and as a mediator of RNAi. How higher fungi respond to dsRNA is not known. We demonstrate that Magnaporthe oryzae (Mo), a globally significant crop pathogen, internalizes dsRNA across a broad size range of 21 to about 3000 bp. Incubation of fungal conidia with 10 ng/μL dsRNA, regardless of size or sequence, induced aberrant germ tube elongation, revealing a strong sequence-unspecific effect of dsRNA in this fungus. Accordingly, the synthetic dsRNA analogue poly(I:C) and dsRNA of various sizes and sequences elicited canonical fungal stress pathways, including nuclear accumulation of the stress marker mitogen-activated protein kinase Hog1p and production of ROS. Leaf application of dsRNA to the cereal model species Brachypodium distachyon suppressed the progression of leaf blast disease. Notably, the sequence-unspecific effect of dsRNA depends on higher doses, while pure sequence-specific effects were observed at low concentrations of dsRNA ( < 0.03 ng/μL). The protective effects of dsRNA were further enhanced by maintaining a gap of at least seven days between dsRNA application and inoculation, and by stabilising the dsRNA in alginate-chitosan nanoparticles. Overall, our study opens up additional possibilities for the development and use of dsRNA pesticides in agriculture.
In this study, a novel approach was developed to increase the intracellular trehalose concentration in M. brunneum blastospores by uptake from the medium, improving their desiccation tolerance. Briefly, placing the blastospores in a hypotonic environment induced solute excretion, allowing significantly increased trehalose uptake during subsequent trehalose treatment. Conductivity changes and GC–MS analysis revealed that glycerol and lactate excretion is triggered in a hypotonic NaCl solution. After hypotonic + trehalose treatment, intracellular glycerol, lactate, and glucose levels increased, while other desiccation‑protective solutes remained unaffected. A fluorescence‑based single‑cell analysis of membrane stress and death during osmotic desiccation and rehydration showed that membrane stress and cell death were strongly amplified upon rehydration. Trehalose treatment reduced this amplification, while hypotonic + trehalose treatment minimised cell death and prevented a stress response during rehydration, though it increased membrane stress during desiccation. Newly formed germ tubes were identified as critical points of membrane failure during desiccation. Ultimately, the drying survival of blastospores was significantly improved by the hypotonic + trehalose treatment compared to untreated or trehalose‑only‑treated blastospores. In summary, this technique successfully enhanced blastospore desiccation tolerance and could be adapted to load cells with other solutes.
We developed a formulation of long double-stranded RNA (dsRNA) using interpolyelectrolyte complexes (IPECs) composed of the biopolymers chitosan and alginate, in order to protect the dsRNA from biotic and abiotic factors. Our primary objectives were to enhance stability of dsRNA against environmental nucleases and, secondarily, to mitigate the negative charge of the dsRNA, which may promote foliar uptake. Our approach relies on submicron particles with adjustable surface charge being either positive or negative. Following this approach, we obtained a high encapsulation efficiency of 94 %. Subsequently, we investigated the influence of the charge ratio and total polymer content on the size, size distribution and ζ-potential of the IPECs. We discovered that formulating at low polymer concentrations ≤0.05 g/L with charge ratios of ≤0.9 (+/ ) and ≥ 1.25 (+/ ), respectively, produced <100 nm particles. Furthermore, the IPEC formulation protected dsRNA from enzymatic degradation by RNase III and micrococcal nuclease. In addition, we observed outstanding protection of formulated dsRNA from heat degradation. Experiments on Nicotiana benthamiana plants showed that formulated dsRNA offered protection against tobacco mosaic virus. In essence, this formulation demonstrates versatility for the production of IPECs with customizable size, surface charge, and nucleic acid content.
KI-Lösungen und -Systemen wird im wirtschaftlichen sowie gesellschaftlichen Kontext zunehmend Bedeutung beigemessen. Doch aufgrund damit verbundener Implikationen darf die Diskussion hinsichtlich der Verantwortung beispielsweise mit Blick auf die Haftung für die Verursachung von Schäden nicht ausbleiben. Die Frage ist jedoch: Wer trägt die Verantwortung wofür? Insbesondere unter dem Aspekt, dass sich Verantwortung nicht umfassend reglementieren lässt. Zur Beantwortung und entsprechender Handlungsweise bedarf es hier eines gemeinsamen Spielverständnisses aller Beteiligten – denn nur so lässt sich gewährleisten, dass KI verantwortungsvoll eingesetzt werden kann, auch mit Blick auf die Zukunft. Im Beitrag wird hierfür ein Lösungsansatz vorgestellt.
From 2035 onwards, the European Union will no longer register any new vehicles that are not powered in a climate-neutral way. In alignment with this policy, Germany aims to perceived carbon neutrality by 2045, with the electrification of transport playing a central role. Corporate fleets are particularly well-suited for electrification due to their relatively short ownership cycles and frequent vehicle renewals. However, the pace of adoption in organizations remains slow. The success of such technological transitions depends largely on acceptance at the decision-making level. This study investigates the determinants of organizational decision-makers’ behavioral intention to electrify their corporate fleets prior to implementation. To this end, the newly developed Acceptance Model for Electrification (eAM) integrates the two-stage innovation decision-making process within companies. The model accounts for 60% of the variance in behavioral intention. Drawing on the findings, this paper proposes practical recommendations for policy development.
Shadows and spotlights: A postfeminist analysis of women innovators’ experiences with (in)visibility
(2025)
Contrary to the notion that innovation is a universally accessible and meritocratic endeavor, concerns persist over not only women innovators’ numerical underrepresentation but also their (in)visibility. Studying innovation as a social context structured by power, we focus on 18 women innovators in innovation-driving environments. While these women appear to symbolize gender equality and embody contemporary postfeminist ideals of individualism, choice, and empowerment, many have simultaneously experienced (in)visibility and navigated unequal power structures throughout their careers. We investigate how these (in)visibility experiences are reconciled with the promises of postfeminism, exploring how postfeminist ideals are interpreted and negotiated by them to make sense of their own (in)visibility. While (in)visibility has traditionally been theorized in relation to norms and gendered power structures, our findings reveal how postfeminist discourses reframe visibility as an individualized, moralized imperative rooted in self-responsibility. Through this lens, we identify four postfeminist sense-making approaches: meritocratic visibility (embodying postfeminist ideologies), retraditionalized visibility (conforming to femininity), self-disciplined visibility (adapting to gender inequality), and collective-oriented visibility (challenging the status quo). These sense-making approaches highlight the various ways in which postfeminist sensibilities shape subjective experiences, often masking structural inequalities and allowing these to persist in contexts that claim to promote equal opportunities, such as the innovation environment. We point to the need for collective rather than individualized action for structural transformation.
Shaalke: Development of a MATLAB Software Tool for Advanced Statistical Outdoor Data Evaluation
(2025)
This paper introduces Shaalke, a novel analytical software tool developed for the high-accuracy evaluation of long-term photovoltaic module measurement data. Addressing the critical need for robust parameter extraction from field data, Shaalke integrates advanced filtering, linear regression, and algorithmic processing to overcome limitations of traditional evaluation methods. We demonstrate Shaalke's capability to accurately determine STC parameters and both static and dynamic temperature coefficients, showing excellent agreement with manufacturer specifications and independent laboratory measurements. A key finding is Shaalke's precise mapping of the irradiance dependence of module efficiency, filling a significant gap left by typical datasheet values which often only provide data at 1000 and 200 W/m². Furthermore, the tool enables reliable power degradation analysis, identifying modules that exceed manufacturer-tolerated limits. Shaalke provides a comprehensive, data-driven platform for understanding real-world module performance, offering invaluable insights for system design, operation, and quality assurance, thereby bridging the gap between laboratory specifications and field performance.
Laser cladding is an essential method for strengthening and restoring component surfaces. To increase its efficacy and provide a reliable surface treatment technique, it is necessary to optimize process parameters, enhance material adhesion, and guarantee high-quality, reliable coatings. These measures help to extend the lifespan of components. In this study, the surfaces of AISI 904L stainless steel samples were cladded to prepare various Co-based composite coatings with single and multiple layers reinforced with WC–CoCr–Ni powder. The phases within the newly developed layers were investigated using X-ray Diffraction (XRD), while the microstructure was examined using Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDX). Further tests were performed to assess the hardness, wear resistance and corrosion performance of the deposited coatings. Analyzing and comparing the coatings, it was observed that the coating performance increased with increasing thickness and generally due to a lower amount of Fe present within the microstructure.
Entrepreneurial ecosystem (EE) research has flourished, yet it continues to overlook how power shapes who can mobilize resources, legitimacy, and opportunity within these systems. This paper reframes power as a constitutive, and not incidental, dimension of ecosystem functioning. Integrating insights from Pfeffer's resource-dependence theory with Foucault's and Bourdieu's social perspectives, we develop a Power-Sensitive Entrepreneurial Ecosystem Framework (PSEEF) that conceptualises power across micro (entrepreneurial identity), meso (network structures), and macro (institutional governance) levels. Our key insight is that power dynamics are the hidden mechanisms through which EEs determine who gains visibility and support, and whose ventures remain peripheral. Recognising these mechanisms enables scholars and practitioners to understand ecosystems not merely as collections of resources but as evolving arenas of legitimacy and control. The framework provides actionable tools for ecosystem leaders to diagnose and rebalance inequalities, advancing both the analytical and practical agenda for inclusive and high-performing EEs.
This article explores the importance of belongingness in migrant entrepreneurs' (MEs) engagement within entrepreneurial ecosystems (EEs), focusing on emotional and social dimensions often overlooked in favour of structural factors. Through two case studies in Germany's Ruhr area, the article demonstrates how a strong sense of belonging enhances resilience, trust and social capital, essential for business success. The experiences of two MEs, Ilyas and Elif, illustrate belongingness as a catalyst for connectedness and embeddedness, enabling access to networks and resources while countering discrimination. The study suggests that policy frameworks should acknowledge and support the emotional and relational aspects of MEs' integration in EEs. Emphasising informal support systems, community engagement and tailored interventions could help overcome structural barriers and foster more inclusive ecosystems. Future research should further examine these dynamics across diverse cultural and geographical contexts to offer a more comprehensive understanding of MEs' entrepreneurial trajectories.
Das Nachhaltigkeitsreporting ist und bleibt für viele Unternehmen ein wichtiges, aktuelles und dynamisches Thema - auch politisch gesehen.
Der Studienbericht ist eine Fortführung der im Jahr 2023 durchgeführten empirischen Erhebung zum Stand der digitalen Nachhaltigkeitsberichterstattung in Unternehmen des westlichen Münsterlandes und fand im Rahmen des EFRE-Projekts "DiNaOpt4KMU" statt. Ein Vergleich der Ergebnisse zur ersten Ausgabe zeigt unter anderem, dass ein Großteil der Unternehmen sich im Bereich Nachhaltigkeit positioniert und weiterentwickelt haben. Zudem konnten in der zweiten Auflage Entwicklungen in der Region Westmünsterland aufgezeigt und bewertet werden. Es konnte eine Klassifizierung der teilgenommen Unternehmen in „Neueinsteiger, Einsteigende und Fortgeschrittene“ erfolgen.
Eine weitere Studienauflage ist für das Jahr 2026 in Planung.
Inspection of underground sewerage channel infrastructure by deploying a wireless sensor network
(2024)
Meteorological disasters are soon to be more likely due to climate change. To oppose this expected development regular inspection and maintenance of sewage networks becomes increasingly mandatory. Applying customized swimming sensor nodes also called wireless sensor system could be a possibility to ensure real time information on this matter. Interconnecting sensor nodes resemble a wireless sensor network with mesh topology. Gateways installed in inspection hambers hand data over to a back-end.
Unter dem Titel „WE! Vom Labor in den Mittelstand: Westfälische Erfinderinnen. Analyse der Potenziale und Sichtbarmachung innovativer Frauen in regionalen Innovationsökosystemen“ (kurz WE!) widmete sich ein interdisziplinäres Team aus Forschenden an der Westfälischen Hochschule von 2021-2024 der Erforschung und Sichtbarmachung innovativer Frauen: Forscherinnen, Gründerinnen, Spezialistinnen in der Wirtschaft und Initiatorinnen in sozialen Bereichen aus dem Münsterland und dem Ruhrgebiet. Damit lag dem Projekt WE! ein breiter Innovationsbegriff zugrunde, der Produkt- und Verfahrensinnovationen sowie auch Dienstleistungs- und soziale Innovationen berücksichtigte.
Von der Pflanzenstruktur zur Fahrzeugkühlung. Eine bionische Lösung zur passiven Luftregelung
(2025)
Die Zukunft automobiler Mobilität ist überwiegend elektrisch. Im Vergleich zu bestehenden Systemen ändern sich die Anforderungen an die Teilsysteme. Ein Luftstrom zur Kühlung von Komponenten wird nun vorwiegend benötigt, wenn das Auto steht (d. h. beim Laden) oder bei langsamen Geschwindigkeiten unter Volllast. Bisher werden in solchen Fällen aktiv angetriebene Lüfter verwendet, die Energie verbrauchen und Geräusche emittieren. Wir schlagen zur Komplexitätsreduktion ein passives adaptives System vor, das eine konvektionsgetriebene Kühlung ermöglicht. Das entwickelte System ist ein hoch adaptives Flachventil, das vom Hoftüpfel abgeleitet ist. Es wurde durch einen iterativen Designprozess entwickelt, der sowohl strukturelle als auch thermodynamische Simulationen einschloss. In Harthölzern und Koniferen ermöglichen Hoftüpfel den anspruchsvollen Transport vertikaler Flüssigkeiten, indem sie Schäden lokal begrenzen. Abhängig von der Struktur können sie sich bei plötzlichen Druckänderungen schließen und die Funktion von Ventilen übernehmen. Das Ergebnis des bionischen Entwicklungsprozesses ist ein flaches Ventil, das kostengünstig zu produzieren, langlebig, leicht, wartungsfrei und geräuschlos ist. Es ermöglicht das passive Umschalten der Luftstromerzeugung am Wärmetauscher der Kühlung zwischen natürlicher Konvektion oder einem aktiven Luftstrom, ohne dass komplexe Mess- und Steuersysteme erforderlich sind. Die geometrischen und materiellen Gestaltungsfaktoren ermöglichen eine einfache Anpassung des Ventils an die gewünschten Umschaltbedingungen während des Designprozesses. Hierfür wurden Festigkeitsprüfungen mit unterschiedlichen Materialien und Geometrien durchgeführt. Die auf dessen Basis erstellte Faustformel ist für Entwickelnde ein Hilfestellung, um ohne Finite-Elemente-Analysen die Geometrie und Materialien des Ventils auslegen zu können.
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.
PySSA (Python rich client for visual protein Sequence to Structure Analysis) for Windows is a comfortable open Graphical User Interface (GUI) application combining the protein sequence to structure prediction capabilities of ColabFold with the open-source variant of the molecular structure visualization and analysis system PyMOL to make both available to the scientific end-user. PySSA enables the creation and sharing of workflow projects that comprise defined protein 3D structure predictions from their amino acid sequence, protein 3D structure alignments, as well as their visual analysis with distance diagrams or hotspot inspection. All operations can be conveniently performed by scientists without specialized computer skills or even programming knowledge on their local Windows computers, without the need for powerful GPU hardware. Thus, PySSA can help make protein structure prediction more accessible for end-users in scientific research areas like protein chemistry or molecular biology. In addition, the application is well-suited for educational purposes due to its user-friendliness and low learning curve. PySSA is openly available on GitHub, alongside a convenient installer executable for the Windows operating system: https://urban233.github.io/PySSA/install.html. To demonstrate its capabilities, the usage of PySSA in a protein mutation study on the protein drug Bone Morphogenetic Protein 2 (BMP2) is described: the structure prediction results indicate that the previously reported BMP2-2Hep-7M mutant, which is intended to be less prone to aggregation, does not exhibit significant spatial rearrangements of amino acid residues interacting with the receptor.
Sind Spielhallen und Wettbüros die "schwarzen Schafe" der Stadtkultur? In einem kurzen historischen Abriss wird aufgezeigt, dass die Verheißung eines leistungslos erworbenen Gewinns der "Obrigkeit" immer schon ein Dorn im Auge war.
Aus der Sozialfigur des faulen Müßiggängers wurde im Verlauf der Geschichte dann der stets Suchtgefährdete und potentiell Beschaffungskriminelle.
Das Buch beleuchtet folgende weitere Themen:
- Unterschiede zwischen Spielen/Bedienen und Wetten/Zocken
- volkswirtschaftliche und betriebswirtschaftliche Daten
- Kritik zur Datenlage gefährdeter und pathologischer Spieler
- Sozialstruktur und ein kritischer Blick auf das Verständnis von "Sucht"
- Interviews mit Vertretern von Stadtverwaltungen
- anschauliche Beschreibungen zu Spielhallen und Wettbüros
- Perspektiven für den zukünftigen Umgang mit diesen Einrichtungen
Mixed Reality (MR) is a technology with strong potential for advancing research in Human-Robot Interaction (HRI) for space exploration. Apart from the efficiency and high flexibility MR can offer, we argue that its benefits for HRI research in space contexts lies particularly in its ability to aid human-in-the-loop development, offer realistic hybrid simulations, and foster broader participation in HRI research in the space exploration context. However, we believe that this is only plausible if MR-based simulations can yield comparable results to fully physical approaches in human-centred studies. In this position paper, we highlight several arguments in favour of MR as a tool for space HRI research, while emphasising the importance of the open question regarding its scientific validity. We believe MR could become a central tool for preparing for future human-robotic space exploration missions and significantly diversify research in this domain.
This study examines the effect of elevated printing speeds (100–600 mm/s) on the dimensional accuracy and tensile strength of PLA components fabricated via fused deposition modeling (FDM). To isolate the influence of printing speed, all other parameters were kept constant, and two filament variants—natural (unpigmented) and black PLA—were analyzed. ISO 527-2 type 1A specimens were produced and tested for dimensional deviations and ultimate tensile strength (UTS). The results indicate that printing speed has a marked impact on both geometric precision and mechanical performance. The optimal speed of 300 mm/s provided the best compromise between dimensional accuracy and tensile strength for both filaments. At speeds below 300 mm/s, under-extrusion caused weak layer bonding and air gaps, while speeds above 300 mm/s led to over-extrusion and structural defects due to thermal stress and rapid cooling. Black PLA yielded better dimensional accuracy at higher speeds, with cross-sectional deviations between 2.76% and 5.33%, while natural PLA showed larger deviations of up to 8.63%. However, natural PLA exhibited superior tensile strength, reaching up to 46.59 MPa, with black PLA showing up to 13.16% lower UTS values. The findings emphasize the importance of speed tuning and material selection for achieving high-quality, reliable, and efficient FDM prints.
Die Diskussion um Generationenunterschiede in der Arbeitswelt ist allgegenwärtig – oft geprägt von Klischees und Pauschalisierungen. Dieses Buch liefert eine fundierte, empirisch gestützte Analyse zur Frage, ob sich die Erwartungen an attraktive Arbeitgeber tatsächlich zwischen Generationen unterscheiden. Die Ergebnisse zeigen: Vieles, was als generationsspezifisch gilt, ist eher Ausdruck von gesellschaftlichem Wandel. Auf Basis einer groß angelegten Befragung von Berufstätigen aus vier Generationen werden zentrale Einflussfaktoren identifiziert, die Arbeitgeber unabhängig vom Alter ihrer Mitarbeitenden attraktiv machen. Das Buch bietet praxisnahe Empfehlungen für ein nachhaltiges Personalmanagement – jenseits von Generationsmythen.
Rivers face constant anthropogenic stress, resulting in significant changes in microbial community composition. What remains unclear is whether stream microbiomes exhibit distinct resilience patterns in composition and/or activity upon exposure to different stressors. By subjecting 64 river-connected mesocosms to multiple stressors, we show that sediment microbiomes of small lowland rivers are highly sensitive to low flow velocity. This stress results in altered community compositions incapable of mitigating the applied stressor within a two-week timeframe despite functional stability (inferred via metagenomics). Transcriptomics revealed a systematic heat shock response in the community and a highly active, metabolically versatile, uncharacterized anaerobic keystone species. Increases in temperature (+ 3.5°C) or salinity (+ 0.5 mS/cm) elicited minor responses at community and transcriptomic levels (e.g., upregulation of photosystems). Following a two-week recovery, transcriptomic-inferred stress responses vanished completely, underscoring the river microbiome resilience. Given the complex community responses observed at the activity and compositional levels, we conclude that maintaining natural river flow is vital to preventing energy loss and reduced microbiome activity in river sediments.
The discharge of treated wastewater (TWW) into freshwater ecosystems poses a significant impact on microbial communities, particularly protists, which play a crucial role in nutrient cycling and ecosystem stability. While the ecological effects of TWW on microbial diversity have been studied, understanding the functional responses of protist communities remains limited. This study employs metatranscriptomics to unravel the temporal dynamics of protist community functions in response to TWW exposure. Using mesocosm experiment, water samples were analyzed over a ten-day period to monitor shifts in metabolic pathways and community interactions. Our results indicate that processed metatranscriptomic data, focusing on treatment-significant pathways, is more sensitive than traditional methods, such as meta-barcoding, and non-target screening, in detecting wastewater-induced perturbations. Early exposure to TWW significantly altered expression of pathways associated with signal transduction and environmental interaction, while general metabolic pathways showed resilience. Over time, the protist community showed signs of adaptation with expression levels stabilizing towards the end of the experiment. This study underscores the importance of focussing on functional shifts rather than just taxonomic changes for assessing wastewater impacts on freshwater ecosystems. Our findings advocate for the use of metatranscriptomics as a robust indicator for TWW detection, aiding in development of targeted environmental management strategies.
Significant progress in high-throughput analytical techniques has paved the way for novel approaches to integrating data sets from different compartments. This study leverages nontarget screening (NTS) via liquid chromatography-high-resolution mass spectrometry (LC-HRMS), a crucial technique for analyzing organic micropollutants and their transformation products, in combination with biological indicators. We propose a combined multivariate data processing framework that integrates LC-HRMS-based NTS data with other high-throughput data sets, exemplified here by 18S V9 rRNA and full-length 16S rRNA gene metabarcoding data sets. The power of data fusion is demonstrated by systematically evaluating the impact of treated wastewater (TWW) over time on an aquatic ecosystem through a controlled mesocosm experiment. Highly compressed NTS data were compiled through the implementation of the region of interest-multivariate curve resolution-alternating least-squares (MCR-ALS) method, known as ROIMCR. By integrating ANOVA-simultaneous component analysis with structural learning and integrative decomposition (SLIDE), the innovative SLIDE-ASCA approach enables the decomposition of global and partial common, as well as distinct variation sources arising from experimental factors and their possible interactions. SLIDE-ASCA results indicate that temporal variability explains a much larger portion of the variance (74.6%) than the treatment effect, with both contributing to global shared space variation (41%). Design structure benefits include enhanced interpretability, improved detection of key features, and a more accurate representation of complex interactions between chemical and biological data. This approach offers a greater understanding of the natural and wastewater-influenced temporal patterns for each data source, as well as reveals associations between chemical and biological markers in an exemplified perturbed aquatic ecosystem.
The decomposition of organic matter is essential for sustaining the health of freshwater ecosystems by enabling nutrient recycling, sustaining food webs, and shaping habitat conditions, which collectively enhance ecosystem resilience and productivity. Bacteria and fungi play a crucial role in this process by breaking down coarse particulate organic matter (CPOM), such as leaf litter, into nutrients available for other organisms. However, the specific contribution of bacteria and their functional interactions with fungi in freshwater sediments have yet to be thoroughly explored. In the following study, we enriched organic matter through the addition of alder (Alnus glutinosa) leaves into artificial stream channels (AquaFlow mesocosms). We then investigated enzyme expression, metabolic pathways, and community composition of fungi and bacteria involved in the degradation of CPOM through metatranscriptomics and amplicon sequencing. Enzymes involved in the degradation of lignin, cellulose, and hemicellulose were selectively upregulated with increased organic matter. Analysis of ITS and 16S rRNA gene sequences revealed that during decomposition, fungal communities were predominantly composed of Basidiomycota and Ascomycota, while bacterial communities were largely dominated by Pseudomonadota and Bacteroidota. The similar gene expression patterns of CPOM degradation related enzymes observed between bacteria and fungi indicate potential functional interaction between these microbial groups. This correlation in enzyme expression may indicate that bacteria and fungi are jointly involved in the breakdown of coarse particulate organic matter, potentially through mutualistic interaction. This study uncovers the specific enzymatic activities of bacteria and fungi and the importance of microbial interactions in organic matter decomposition, revealing their central role in facilitating nutrient cycling and maintaining the ecological health and stability of freshwater ecosystems.
Many components in industry are subjected to high loads during operation and therefore often do not reach their intended service life. Conventional steels frequently do not provide sufficient protection against wear and corrosion. One solution is to coat these components using methods like thermal spraying to apply cermet coatings such as Cr3C2-NiCr or WC-Co-Cr. In light of increasingly strict environmental regulations, more eco-friendly alternatives are needed, especially ones that use little or no Cr, Ni, Co, or W. Another alternative is the recycling of powder materials, which is the focus of this research project. This study investigated whether filter dust from an HVOF system could be used to develop a new coating suitable for use in applications requiring resistance to wear and corrosion. This is challenging as the filter dusts have heterogeneous compositions and irregular particle sizes. Nevertheless, this recycled material, referred to as “Green Cermets” (GCs), offers previously untapped potential that may also be of ecological interest. An established WC-Co-Cr coating served as a reference. In addition to friction wear and corrosion resistance, the study also examined particle size distribution, hardness, microstructure, and susceptibility to crack formation at the interface and inside the coating. Even though the results revealed a diminished performance of the GC coatings relative to the conventional WC-CoCr, they may still be applicable in various industrial applications.
High-entropy alloys are known for their promising mechanical properties, wear and corrosion resistance, which are maintained across a wide range of temperatures. In this study, a CoCrFeNiCu-based high-entropy alloy, distinguished from conventional CoCrFeNi systems by the addition of Cu, which is known to enhance toughness and wear resistance, was investigated to better understand the effects of compositional modification on processability and performance. The influence of key process parameters, specifically laser power and scan speed, on the processability of CoCrFeNiCu-based high-entropy alloys produced by laser powder bed fusion additive manufacturing was investigated, with a focus of low laser power, which is critical for minimizing defects and improving the resulting microstructure and mechanical performance. The printed sample density gradually increases with higher volumetric energy density, achieving densities exceeding 99.0%. However, at higher energy densities, the samples exhibit susceptibility to hot cracking, an issue that cannot be mitigated by adjusting the process parameters. Mechanical properties under optimized parameters were further evaluated using Charpy impact and (in situ) tensile tests. These evaluations were supplemented by in situ tensile experiments conducted within a scanning electron microscope to gain insights into the behavior of defects, such as hot cracks, during tensile testing. Despite the sensitivity to hot cracking, the samples exhibited a respectable ultimate tensile strength of 662 MPa, comparable to fine-grained steels like S500MC (070XLK). These findings underscore the potential of CoCrFeNiCu-based high-entropy alloys for advanced applications. However, they also highlight the necessity for developing strategies to ensure stable and reliable processing methods that can mitigate the susceptibility to hot cracking.
Abstract
This study signifies the development and characterization of a composite material with a metallic matrix of aluminum reinforced with a steel mesh, utilizing centrifugal casting technology. An evaluation was conducted to ascertain the influence of the formulation process and the presence of the insert on the mechanical behavior with regard to tensile strength. The aluminum matrix was obtained from commercial and scrap alloys, elaborated by advanced methods of degassing and chemical modification. Meanwhile, the steel mesh reinforcement was cleaned, copper plated, and preheated to optimize wetting and, consequently, adhesion. The structural characterization was performed by scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy analyses (EDX), which highlighted a well-defined interface and uniform copper distribution. The composite was produced by means of horizontal-axis centrifugal casting in a fiberglass mold, followed by cold rolling to obtain flat specimens. A total of eight tensile specimens were examined, with measured ultimate tensile strengths ranging from 78.5 to 119.8 (MPa). A thorough examination of the fractured specimens revealed a brittle fracture mechanism, devoid of substantial plastic deformation. The onset of failures was frequently observed at the interface between the aluminum matrix and the steel mesh. The use of SEM and EDX investigations led to the confirmation of the uniformity of the copper coating and the absence of significant porosity or interfacial defects. A bimodal distribution of tensile strength values was observed, a phenomenon that is likely attributable to variations in mesh positioning and local differences in solidification. A correlation was established between the experimental results and an analytical polynomial model, thereby confirming a reasonable fit. In sum, the present study provides a substantial foundation for the development of metal matrix composites with enhanced performance, specifically designed for challenging structural applications. This method also demonstrates potential for recycling aluminum scrap into high-performance composites with controlled microstructure and mechanical integrity.
Abstract
Integrating bioinspired design and additive manufacturing into engineering education fosters innovation to meet the growing demand for accessible, personalized assistive technologies. This paper presents the outcomes of an international course, “3D Prosthetics and Orthotics”, offered to undergraduate students in the Biomimetic program at Westfälische Hochschule (Germany), in collaboration with the 3D Orthotics and Prosthetics Laboratory at the Federal University of São Paulo—UNIFESP (Brazil). The course combined theoretical and hands-on modules covering digital modeling (CAD), simulation (CAE), and fabrication (CAM), enabling students to develop bioinspired assistive devices through a Project-based learning approach. Working in interdisciplinary teams, students addressed real-world rehabilitation challenges by translating biological mechanisms into engineered solutions using additive manufacturing. Resulting prototypes included a hand prosthesis based on the Fin Ray effect, a modular finger prosthesis inspired by tendon–muscle antagonism, and a cervical orthosis designed based on stingray morphology. Each device was digitally modeled, mechanically analyzed, and physically fabricated using open-source and low-cost methods. This initiative illustrates how biomimetic mechanisms and design can be integrated into education to generate functional outcomes and socially impactful health technologies. Grounded in the Mao3D open-source methodology, this experience demonstrates the value of combining nature-inspired principles, digital fabrication, Design Thinking, and international collaboration to advance inclusive, low-cost innovations in assistive technology.
Abstract
This work presents a vibration-based non-contact monitoring method to classify the physical activity of a mouse inside a home cage. A novel tuned-beam sensing device is developed to measure low-amplitude activity-induced cage vibrations. The sensing device uses a mechanical beam structure to enhance a six-axis IMU that increases the signal-to-noise ratio (SNR) by 20 to 40 times in a relevant environment. A sophisticated classification algorithm is developed to process vibration sequences with a variable time frame that utilizes multi-level discrete wavelet transformation (MLDWT) to extract time–frequency features and optimize signal properties. The extracted features are classified by a convolutional neural network–long short-term memory (CNN-LSTM) machine learning model to determine the activity class. The ground truth is obtained with a camera-based system using EthoVision XT from Noldus and a custom post-processor. The method is developed on a dataset containing 300 h of vibration measurements with camera-based reference and includes two separate home cages and two individual mice. The method classifies the activity types Resting, Stationary Activity, Walking, Activity in Feeder, and Drinking with an accuracy of 86.81% and an average F1 score of 0.798 using a 9 s time frame. In long-term monitoring, the proposed method reproduces behavioral patterns such as sleep and acclimatization as accurately as the reference method, enabling home cage monitoring in the husbandry environment with a low-cost sensor.
Abstract
Animal welfare in barns is strongly influenced by air quality, with gaseous emissions like ammonia posing significant respiratory health risks. However, current state-of-the-art ammonia monitoring systems are labor-intensive and expensive. Metal Oxide Semiconductor (MOS) sensors offer a promising alternative due to their compatibility with sensor networks, enabling high-resolution ammonia monitoring across spatial and temporal scales. While MOS sensors exhibit high sensitivity to various volatile compounds, temperature-cycled operation is commonly employed to enhance selectivity, effectively creating virtual sensor arrays. This study aims to improve ammonia detection by designing a virtual sensor array through a cyclic data-driven approach, integrating machine learning with solid-state sensor modeling. The results of a two-week dataset with measurements of four different pig barns demonstrate ammonia sensing with a sampling rate of about 2/min and a range of 1–30 ppm. The method is robust and exhibits a 10% increase in normalized RMSE when comparing testing results of an unseen sensor module with results of the training dataset. A filter membrane boosts accuracy and prevents data loss due to contamination, such as flyspecks. Overall, the used MOS sensor BME688 is effective and economical for widespread continuous ammonia monitoring and localization of ammonia sources in pig barns.
Die vorliegende Studie untersucht die Auswirkungen dynamischer Stromtarife auf das Stromverbrauchsverhalten und die Gesamtstromkosten in Deutschland im Jahr 2024. Gemäß §41 EnWG sollen dynamische Stromtarife den Stromverbrauch an das wetterabhängige Angebot erneuerbarer Energien (EE) anpassen. Die Studie analysiert 243 Szenarien eines preisgesteuerten Stromverbrauchs, wobei verschiedene Parameter wie das EE-Stromangebot, der minimale Strombörsenpreis und die Verschiebungsperiode des Stromverbrauchs variiert werden. Die Ergebnisse zeigen, dass eine kostenoptimierende Anpassung des Stromverbrauchs nur mit zusätzlichen Kurzzeitspeichern umsetzbar ist, um inakzeptable Verwerfungen im Tagesablauf der Stromverbraucher zu vermeiden. Die Berechnungen verdeutlichen, dass dynamische Stromtarife unter den Bedingungen des Jahres 2024 keine wesentlichen systemischen Vorteile bieten und erhebliche technische und finanzielle Zusatzaufwände erfordern. Die Studie schließt mit der Feststellung, dass die Einführung dynamischer Stromtarife neue Geschäftsmodelle und psychologische Effekte auf die Verbraucher haben könnte, jedoch auch eine neue Form der Stromrationierung darstellt.
Zusammenfassung
Anlass dieser Studie ist die verpflichtende Einführung dynamischer Stromtarife gemäß §41 EnWG. Hierdurch soll ein Paradigmenwechsel im Hinblick auf den Stromverbrauch bewirkt werden: Der Stromverbrauch soll sich künftig bestmöglich an das überwiegend wettergeführte Stromangebot der Erneuerbare-Energien-Quellen anpassen, statt dass sich das Stromangebot wie bisher am Strombedarf orientiert.
Die Studie untersucht, inwieweit dynamische Stromtarife das Stromverbraucher-Verhalten und die Gesamtstromkosten des Jahres 2024 hätten beeinflussen können, wenn diese bereits 2024 deutschlandweit genutzt worden wären.
Die Optimierung mechanischer Bauteile nimmt in der Entwicklung technischer Produkte einen immer größer werdenden Stellenwert ein. Ziel dieses Prozesses ist herauszufinden, welche Form und Topologie eine Struktur besitzen muss, um die an sie gestellte Konstruktionsaufgabe besonders gut zu erfüllen. Damit die optimierten Strukturen auch herstellbar sind, ist das Bestreben aktueller Forschung, Informationen über die Fertigungsprozesse direkt in die entsprechenden Optimierungsverfahren in Form von Fertigungsrestriktionen zu integrieren. In dieser Arbeit wird eine Methodik zur Integration von Fertigungsrestriktionen bei 3D-Fräsverfahren in die Topologieoptimierung mit der Level-Set-Methode entwickelt. Berücksichtigt werden dabei die Gewährleistung der Werkzeugzugänglichkeit aller Bearbeitungspunkte sowie die Einhaltung einer Mindestwandstärke. Die Methodik basiert auf der Induktion eines Strukturwachstums in Bereichen, die entweder unzugänglich oder zu dünn sind. Um diese Bereiche zu identifizieren, wird ein Verfahren entwickelt, bei dem die Level-Set-Funktion entlang der Außenkonturen realistischer Werkzeuggeometrien interpoliert wird. Zur Induktion des Strukturwachstums wird regelmäßig ein Potential definiert. Dieses besitzt innerhalb der Struktur größere Werte als außerhalb und ändert sich normal zum Strukturrand linear. Eine Minimierung des auf dem Strukturrand vorliegenden Potentials wird in ein Strukturwachstum überführt. Dazu werden die Sensitivitäten des Potentials bezüglich Verschiebungen des Strukturrandes ermittelt und mit den Entwicklungsgeschwindigkeiten der Level-Set-Funktion gekoppelt. Dadurch werden beide Fertigungsrestriktionen in eine gemeinsame mathematische Restriktion überführt und schließlich explizit in das Optimierungsproblem integriert.
Grundkurs C++
(2025)
Thoughts about urban development via digital information channels and activators to increase visitor loyalty Online retailers and platforms use digital technologies of all kinds to offer customer-specific 24/7 services and have established new customer-centric, digitalized standards in retail and services. Cities can focus more strongly on the customer-oriented view. In addition to focusing on visitor types and journeys, digitalization can also help to make cities more vibrant.
Abstract
Understanding intricate microbial interactions in the environment is crucial. This is especially true for the relationships between nutrients and bacteria, as phosphorus, nitrogen and organic carbon availability are known to influence bacterial population dynamics. It has been suggested that low nutrient conditions prompt the evolutionary process of genome streamlining. This process helps conserve scarce nutrients and allows for proliferation. Genome streamlining is associated with genomic properties such as %GC content, genes encoding sigma factors, percent coding regions, gene redundancy, and functional shifts in processes like cell motility and ATP binding cassette transporters, among others. The current study aims to unveil the impact of nutrition on the genome size, %GC content, and functional properties of pelagic freshwater bacteria. We do this at finer taxonomic resolutions for many metagenomically characterized communities. Our study confirms the interplay of trophic level and genomic properties. It also highlights that different nutrient types, particularly phosphorus and nitrogen, impact these properties differently. We observed a covariation of functional traits with genome size. Larger genomes exhibit enriched pathways for motility, environmental interaction, and regulatory genes. ABC transporter genes reflect the availability of nutrients in the environment, with small genomes presumably relying more on metabolites from other organisms. We also discuss the distinct strategies different phyla adopt to adapt to oligotrophic environments. The findings contribute to our understanding of genomic adaptations within complex microbial communities.
Assessing the response of an urban stream ecosystem to salinization under different flow regimes
(2024)
Abstract
Urban streams are exposed to a variety of anthropogenic stressors. Freshwater salinization is a key stressor in these ecosystems that is predicted to be further exacerbated by climate change, which causes simultaneous changes in flow parameters, potentially resulting in non-additive effects on aquatic ecosystems. However, the effects of salinization and flow velocity on urban streams are still poorly understood as multiple-stressor experiments are often conducted at pristine rather than urban sites. Therefore, we conducted a mesocosm experiment at the Boye River, a recently restored stream located in a highly urbanized area in Western Germany, and applied recurrent pulses of salinity along a gradient (NaCl, 9 h daily of +0 to +2.5 mS/cm) in combination with normal and reduced current velocities (20 cm/s vs. 10 cm/s). Using a comprehensive assessment across multiple organism groups (macroinvertebrates, eukaryotic algae, fungi, parasites) and ecosystem functions (primary production, organic-matter decomposition), we show that flow velocity reduction has a pervasive impact, causing community shifts for almost all assessed organism groups (except fungi) and inhibiting organic-matter decomposition. Salinization affected only dynamic components of community assembly by enhancing invertebrate emigration via drift and reducing fungal reproduction. We caution that the comparatively small impact of salt in our study can be due to legacy effects from past salt pollution by coal mining activities >30 years ago. Nevertheless, our results suggest that urban stream management should prioritize the continuity of a minimum discharge to maintain ecosystem integrity. Our study exemplifies a holistic approach for the assessment of multiple-stressor impacts on streams, which is needed to inform the establishment of a salinity threshold above which mitigation actions must be taken.
Abstract
Remote participation in school is possible today with the help of telepresence robots. Such technologies can offer great opportunities for children with long-term illnesses to continue attending school. Consequently, telepresence robots are already used in some schools when children are absent for long periods. However, despite their positive impact, such robots also create challenges for the privacy of people involved in such a setting. Therefore, in this paper, we discuss the user needs of such robots in this specific and privacy-sensitive application field. We held three workshops with different user groups with and without experience with the robots. Among them were formerly and currently ill children, parents, teachers, head teachers, media educators, and supporting personnel. We discussed their experiences (if any), ideas, expectations, and concerns with a focus on privacy aspects to find out about the user needs of different user groups. Our results reveal various interrelationships and conflicts between the individual actors. They serve as a basis to discuss the implications for the design of future telepresence robots for schoolchildren.

