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Einleitung und Fragestellung:
Abusive Supervision wird mit willentlicher Leistungszurückhaltung, verringerter Motivation, erhöhtem Stresserleben, psychosomatischen Beschwerden und Burnout bei Mitarbeitenden assoziiert. Angesichts der hohen Prävalenz destruktiver Führung bleibt bislang die Frage offen, welche
protektiven Ressourcen die genannten Zusammenhänge abpuffern.
Theoretischer Hintergrund:
Abusive Supervision bezieht sich auf das Ausmaß der feindseligen verbalen und nonverbalen Verhaltensweisen einer Führungskraft. Basierend auf dem Anforderungs- Ressourcen- Modell gehen wir davon aus, dass sich personale Ressourcen, die Mitarbeitende in der arbeitsfreien Zeit aufbauen, positiv auf den negativen Effekt zwischen destruktiver Führung und Mitarbeitergesundheit auswirken. Wir fokussieren hier die generalisierte Selbstwirksamkeitserwartung, die sich im Sinne der sozialkognitiven Theorie und zahlreichen empirischen Befunden als gesundheitsrelevante Ressource im
Umgang mit domänenübergreifenden Belastungen herausgestellt hat. Diese sollte durch Bewältigungserfahrung in der arbeitsfreien Zeit gefördert werden. Bewältigungserfahrung in der Freizeit bedeutet die Gelegenheit des Erlebens von Kompetenz und Fachwissen.
Methode:
Die Moderatoranalyse wurde im Rahmen einer Querschnittsbefragung einer anfallenden Stichprobe mit N = 305 Personen getestet. Die Variablen wurden mit der Abusive Supervision Scale (Tepper, 2000), dem REQ (Sonnentag & Fritz, 2007), und der Subskala emotionale Erschöpfung des MBI (Büssing & Perrar, 1992) gemessen.
Ergebnisse:
In dieser Studie zeigen „Mastery Experiences“ einen hypothesenkonformen Puffereffekt, nicht jedoch die anderen Erholungsstrategien, die auch mit getestet wurden. Es zeigt sich also die Tendenz, dass sich Mitarbeitende durch das Erlernen neuer Kompetenzen und den Aufbau von Selbstwirksamkeit vor den gesundheitsschädlichen Auswirkungen destruktiver Führung schützen können. Das
Korrelationsmuster deutet aber vrmtl. auch problematische Aspekte dieser Erholungsstrategie an.
Diskussion:
Limitierend muss erwähnt werden, dass wir die vermutete vermittelnde Variable Selbstwirksamkeit nicht explizit gemessen haben, und dass zukünftige Untersuchungen den Effekt in Form einer mediierten Moderation replizieren müssen.
An automated pipeline for comprehensive calculation of intermolecular interaction energies based on molecular force-fields using the Tinker molecular modelling package is presented. Starting with non-optimized chemically intuitive monomer structures, the pipeline allows the approximation of global minimum energy monomers and dimers, configuration sampling for various monomer-monomer distances, estimation of coordination numbers by molecular dynamics simulations, and the evaluation of differential pair interaction energies. The latter are used to derive Flory-Huggins parameters and isotropic particle-particle repulsions for Dissipative Particle Dynamics (DPD). The computational results for force fields MM3, MMFF94, OPLSAA and AMOEBA09 are analyzed with Density Functional Theory (DFT) calculations and DPD simulations for a mixture of the non-ionic polyoxyethylene alkyl ether surfactant C10E4 with water to demonstrate the usefulness of the approach.
Developing and implementing computational algorithms for the extraction of specific substructures from molecular graphs (in silico molecule fragmentation) is an iterative process. It involves repeated sequences of implementing a rule set, applying it to relevant structural data, checking the results, and adjusting the rules. This requires a computational workflow with data import, fragmentation algorithm integration, and result visualisation. The described workflow is normally unavailable for a new algorithm and must be set up individually. This work presents an open Java rich client Graphical User Interface (GUI) application to support the development of new in silico molecule fragmentation algorithms and make them readily available upon release. The MORTAR (MOlecule fRagmenTAtion fRamework) application visualises fragmentation results of a set of molecules in various ways and provides basic analysis features. Fragmentation algorithms can be integrated and developed within MORTAR by using a specific wrapper class. In addition, fragmentation pipelines with any combination of the available fragmentation methods can be executed. Upon release, three fragmentation algorithms are already integrated: ErtlFunctionalGroupsFinder, Sugar Removal Utility, and Scaffold Generator. These algorithms, as well as all cheminformatics functionalities in MORTAR, are implemented based on the Chemistry Development Kit (CDK).
The influence of molecular fragmentation and parameter settings on a mesoscopic dissipative particle dynamics (DPD) simulation of lamellar bilayer formation for a C10E4/water mixture is studied. A “bottom-up” decomposition of C10E4 into the smallest fragment molecules (particles) that satisfy chemical intuition leads to convincing simulation results which agree with experimental findings for bilayer formation and thickness. For integration of the equations of motion Shardlow’s S1 scheme proves to be a favorable choice with best overall performance. Increasing the integration time steps above the common setting of 0.04 DPD units leads to increasingly unphysical temperature drifts, but also to increasingly rapid formation of bilayer superstructures without significantly distorted particle distributions up to an integration time step of 0.12. A scaling of the mutual particle–particle repulsions that guide the dynamics has negligible influence within a considerable range of values but exhibits apparent lower thresholds beyond which a simulation fails. Repulsion parameter scaling and molecular particle decomposition show a mutual dependence. For mapping of concentrations to molecule numbers in the simulation box particle volume scaling should be taken into account. A repulsion parameter morphing investigation suggests to not overstretch repulsion parameter accuracy considerations.
Recent years have seen a sharp increase in the development of deep learning and artificial intelligence-based molecular informatics. There has been a growing interest in applying deep learning to several subfields, including the digital transformation of synthetic chemistry, extraction of chemical information from the scientific literature, and AI in natural product-based drug discovery. The application of AI to molecular informatics is still constrained by the fact that most of the data used for training and testing deep learning models are not available as FAIR and open data. As open science practices continue to grow in popularity, initiatives which support FAIR and open data as well as open-source software have emerged. It is becoming increasingly important for researchers in the field of molecular informatics to embrace open science and to submit data and software in open repositories. With the advent of open-source deep learning frameworks and cloud computing platforms, academic researchers are now able to deploy and test their own deep learning models with ease. With the development of new and faster hardware for deep learning and the increasing number of initiatives towards digital research data management infrastructures, as well as a culture promoting open data, open source, and open science, AI-driven molecular informatics will continue to grow. This review examines the current state of open data and open algorithms in molecular informatics, as well as ways in which they could be improved in future.
The disruptive nature of the changing media landscape and technology-driven advances in communication have led to innovative ways of organizing work in the information and communication industry. This reorganization of work is reflected in the concept of New Work, which rethinks working concepts, styles, and employee behavior. Based on a survey among staff in the information and communication industry (n = 380), this study investigates the status quo of the implementation of New Work measures and their effectiveness in helping companies reach organizational goals. The results show that New Work measures are widely adopted although there is still unused potential. Moreover, the study demonstrates that the implementation of New Work measures supports companies in achieving New Work goals as well as overall organizational goals in the contexts of agile management, change management, internal communication, and evaluation.
The German supply chain law ( Lieferkettensorgfaltspflichtengesetz, abbreviated: LkSG) which enters into force on 1 January 2023 is part of the developing legal framework for human rights in global supply chains. Like the French vigilance law, it represents a new generation of supply chain laws which impose mandatory human rights due diligence obligations. The LkSG requires enterprises to exercise a number of due diligence obligations – from conducting risk analysis to undertaking preventive measures or remedial actions. The law is based on public enforcement via a competent authority, the Federal Office for Economic Affairs and Export Control (BAFA). The BAFA monitors and enforces compliance with the due diligence obligations. Non-compliant enterprises can be fined with up to 800,000 Euros and, in some cases, up to 2% of the annual turnover. Whilst the LkSG is an important step towards achieving greater corporate sustainability, it also has limitations. It was a political compromise and, as such, it does not include a new civil liability for non-compliance. Moreover, by default, it only applies to the enterprise’s own business area and its direct suppliers, whereas indirect suppliers are only included where the enterprise has substantiated knowledge that an obligation has been violated.
This chapter is a commentary on Principle 20 of the United Nations Guiding Principles on Business and Human Rights (UNGPs). The UNGPs, endorsed by the United Nations Human Rights Council in 2011, are the first universally accepted framework for addressing business responsibilities for human rights. They outline State obligations to protect human rights, businesses’ responsibility to respect human rights, and the importance of both States and businesses offering adequate remedies for human rights breaches.
This chapter is a commentary on Principle 21 of the United Nations Guiding Principles on Business and Human Rights (UNGPs). The UNGPs, endorsed by the United Nations Human Rights Council in 2011, are the first universally accepted framework for addressing business responsibilities for human rights. They outline State obligations to protect human rights, businesses’ responsibility to respect human rights, and the importance of both States and businesses offering adequate remedies for human rights breaches.
Dephasing in quantum systems is typically the result of their interaction with environmental degrees of freedom. We investigate within a spin-boson model the influence of a super-Ohmic environment on the dynamics of a quantum two-state system. A super-Ohmic environment thereby models typical bulk phonons which are a common disturbance for solid state quantum systems as, for example, nitrogen-vacancy centers. By applying the numerically exact quasiadiabatic path-integral approach we show that for strong system-bath coupling, pseudocoherent dynamics emerges, i.e., oscillatory dynamics at short times due to slaving of the quantum system to the bath dynamics. We extend the phase diagram known for sub-Ohmic and Ohmic environments into the super-Ohmic regime and observe a pronounced nonmonotonous behavior. Super-Ohmic purely dephasing fluctuations strongly suppress the amplitude of coherent dynamics at very short times with no subsequent further decay at later times. Nevertheless, they render the dynamics overdamped. The corresponding phase separation line shows also a nonmonotonous behavior, very similar to the pseudocoherent dynamics.
We propose a quantum-mechanical model to calculate the current through a single molecular junction immersed in a solvent and surrounded by a thin shell of bound water under an applied ac voltage. The solvent plus hydration shell are captured by a dielectric continuum model for which the resulting spectral density is determined. Here the dielectric properties, e.g., the Debye relaxation time and the dielectric constant, of the bulk solvent and the hydration shell as well as the shell thickness directly enter. We determine the charge current through the molecular junction under an ac voltage in the sequential tunneling regime where we solve a quantum master equation by a real-time diagrammatic technique. Interestingly, the Fourier components of the charge current show an exponential-like decline when the hydration shell thickness increases. Finally, we apply our findings to binary solvent mixtures with varying volume fractions and find that the current is highly sensitive to both the hydration shell thickness as well as the volume fraction of the solvent mixture, giving rise to possible applications as shell and concentration sensors on the molecular scale.
Article 134 TFEU
(2023)
Article 135 TFEU
(2023)
Design and Development of a Bioreactor System for Mechanical Stimulation of Musculoskeletal Tissue
(2023)
We report on the development of a bioreactor system for mechanical stimulation of musculoskeletal tissues. The ultimate object is to improve the quality of medical treatment following injuries of the enthesis tissue. To this end, the tissue formation process through the effect of mechanical stimulation is investigated. A six-well system was designed, 3D printed and tested. An integrated actuator creates strain by applying a force. A contactless position sensor monitors the travels. An electronic circuit controls the bioreactor using a microcontroller. An IoT platform connects the microcontroller to a smartphone, enabling the user to alter variables, trigger actions and monitor the system. The system was stabilised by implementing two PID controllers and safety measures. The results show that the bioreactor design is suited to execute mechanical stimulation and to investigate the tissue formation and regeneration process …
Dem Thema Nachhaltigkeit kommt zunehmend eine größere Bedeutung zu. Dies liegt nicht zuletzt daran, dass die Pflicht, einen Nachhaltigkeitsbericht zu erstellen, mit dem Jahr 2024 auch auf viele kleine und mittlere Unternehmen ausgeweitet wird. Bislang trifft dies überwiegend auf große Unternehmen zu, welche in der Regel strukturell und hinsichtlich Software sehr gut für die Bewältigung dieser Aufgabe aufgestellt sind. Anders verhält es sich jedoch bei KMU, denn in diesen fehlen meist personelle und finanzielle Ressourcen sowie geeignete softwaretechnische Unterstützungswerkzeuge. In diesem Beitrag werden die Ergebnisse einer Studie der Westfälischen Hochschule vorgestellt, die sich auf das Nachhaltigkeitsreporting von KMU fokussiert. Darüber hinaus werden Herausforderungen aus Informationssicht erläutert und mögliche Unterstützungsbedarfe für KMU diskutiert. Ein Überblick über zukünftige Ansatzpunkte und eine abschließende Diskussion runden den Artikel ab.
In this paper, we investigate the influence of different disease groups on the size of different 1 anatomical structures. To this end, we first modify and improve an existing anatomical segmentation 2 model. Then, we use this model to segment 104 anatomical structures from computed tomography 3 (CT) scans and compute their volumes from the segmentation. After correlating the results with each 4 other, we find no new significant correlations. After correlating the volume data with known diseases 5 for each case, we find two weak correlations, one of which has not been described before and for 6 which we present a possible explanation.